Atmospheric boundary layer heights can be estimated from various ground-based profiles such as e.g. temperature, wind or aerosol backscatter and the diversity of atmospheric tracers allows measuring the complete diurnal cycle of ABL sublayers. The various detection methods were compared at stations on the Swiss plateau, where the operational MeteoSwiss NWP Analysis KENDA-1 was found to provide a good estimate of the daily mixing layer height (MLH). The mountainous boundary layer is more difficult to measure and to model due to complex topographic effects. A network of 35 ceilometers installed in Switzerland in 2018, from which 15 are located in alpine valleys, provides data for a 3-year MLH climatology, which can be compared with KENDA-1 results. CABAM is an algorithm that detect up to nine different aerosol backscatter gradients and apply a decision tree mainly based the standard ML diurnal cycle in order to attribute the right gradient to the MLH. The KENDA-1 MLH detection relies on the bulk-Richardson number method using potential temperature and horizontal wind speed profiles. At low altitude stations, a good agreement is found for the maximum MLH between KENDA-1 and CABAM with mean differences smaller than 400 m. The difference between both methods becomes however larger in complex topography, the KENDA-1 MLH being most of the time more than 500 m below the ceilometer MLH for stations higher than 1000 m asl. Another general feature is that the MLH estimated from temperature profiles leads to earlier maxima in clear sky conditions than MLH estimated by aerosol backscattering profiles. The time difference of 1-4 hours depends on the station and the period of the year, but is shorter (1-2 hours) at high altitude stations in complex topography than at stations in the plain (3-4 hours). Adler et al. (BAMS, 2021) explained the maximum of aerosol backscattering during late afternoon in a wide valley by a subsidence of warm and dry air between 1100 and 1500 LT followed by the establishment of the up valley wind around 1400 LT associated with an increase of specific humidity and backscatter. The earlier backscatter maxima at higher altitude stations could then be explained by a more efficient establishment of diurnal slope and valley winds system in complex topography that decreases the period with subsidence of drier warm air masses.

In September 2022 a case study of local winds and thermal stratification in the lowest 120 m above ground level (agl) was observed in a small valley in the Appalachian Mountains in Virginia, USA. The measurements with small off-the-shelf quadcopter drones and an automatic weather station (AWS) were carried out during calm fair-weather conditions. One drone was equipped with a light-weight instrument package for measuring pressure, air temperature and humidity. A second drone was used to derive horizontal winds from drone acceleration data captured by the flight controller. For comparison with ground-based measurements the drones flew hovering maneuvers next to AWS instruments. Vertical drone profiling started at 15:20 LT (UTC-4h) under dry convective conditions with up-valley winds of about 3-4 m/s at 120 m agl. A wind shift to down-valley direction occurred at 17:40 LT, about 45 minutes before the field site became shaded at local sunset. Within the following hour down-valley winds reached maximum speeds of about 3 m/s at a jet-height of about 30 m agl, while the air temperature inversion grew up to about 50 m agl. The case study demonstrates the capabilities of low-cost drone measurements to capture the dynamical and thermal characteristics of small-scale mountain wind systems.

The Pyrenees is a west to east oriented mountain range in southwest Europe along the border between France, Spain and Andorra. In the eastern part there are two relatively high populated valleys oriented ENE to WSW: (i) the Cerdanya basin, a wide valley (35 km long, 9 km wide) with the bottom around 1000 m asl at the centre and (ii) the Andorra Central valley, a more closed close valley (5 km long, 0.5 km wide) with the bottom about 1013 m asl on average. In Cerdanya, northern synoptic flows favour mountain waves formation and associated rotors over the valley, with strong turbulence zones at the upper edge of the mountain wave crest (Udina et al. 2020). For specific precipitation events during the Cerdanya-2017 campaign there was no evidence of modification of precipitation profiles due to mountain-induced circulations (Gonzalez et al. 2019). A decoupling is frequently observed between the stalled air of the valley and the air of the free atmosphere above the mountain crest level, at around 1000-1500 m agl. Circulations in the first hundreds of meters above the surface are dependent on multi-scale interactions and can be described as a function of thermal and dynamical stability. A remarkable feature in the valley is that nocturnal strong temperature inversions with cold-air pools formation occur more than 50% of the nights mainly during winter (Conangla et al. 2018, Miró et al. 2018), which lead to very low minimum temperatures (-22.8 °C, 12th February 2018). In Andorra central valley, terrain-induced circulations dominate the mountain boundary layer structure. Winter temperature inversions and cold pools formation are one of the key factors that determine the thermal stability conditions and limit the pollutant dispersion. Persistent temperature inversions are identified, and selected case studies are explored using pseudo-profiles of observations and mesoscale models. The study and comprehension of the aforementioned phenomena in mountainous terrain are fundamental for improving their representation in models and to assess the model limitations in resolving them. References Gonzalez, S., et al. (2019): Decoupling between precipitation processes and mountain wave induced circulations observed with a vertically pointing K-band Doppler radar. Remote Sens. Miró, J. R., et al. (2018). Key features of cold‐air pool episodes in the northeast of the Iberian Peninsula (Cerdanya, eastern Pyrenees). IJC. Udina, M., et al. (2020): Multi-sensor observations of an elevated rotor during a mountain wave event in the Eastern Pyrenees. Atmos. Res.

Caves are unique atmospheric environments. With their own air dynamics, dependent on cave morphology, near-vertical sag-type caves show a strong seasonal ventilation pattern. During majority of the year they are sealed off from the outside atmosphere by stable stratification, but in the cold part of the year, they are coupled to the outside through episodical intrusions of cold air. Due to their isolated nature, caves are thus natural laboratories to study atmospheric characteristics depending on specific forcings. A year-long measurement campaign took place in the Hundsalm ice cave, Austria, to explore the internal air dynamics of such a sag-type ice cave. In this contribution we explore turbulence characteristics of periods when the cave was decoupled from the outside, and in the coupled period. Periodic intrusions of denser air from outside of the cave in the cold season are shown to increase turbulence kinetic energy, and lead to a rapid change in the thermal and dynamic characteristics of cave atmosphere. Compared to typical outside conditions this buoyancy driven turbulence transports only marginal heat flux and dies down fast as soon as the forcing disappears. In the sealed periods, when stable stratification prevails, the background levels of turbulence are exceptionally low. Still, the turbulence spectrum shows the expected albeit very short inertial subrange, and smallest turbulence eddies are shown to be more similar to the ones found on Mars than on Earth.

Both operational and research mesoscale model simulations, with a horizontal grid spacing ranging from a few hundreds of meters to a few kilometers, are oftentimes evaluated against surface station observations by typically selecting the grid point with the smallest distance from the location of the station (i.e., the nearest grid point). In complex terrain, however, strong land- cover heterogeneity occur together with orographic features at multiple different scales (e.g., large mountain ridges and smaller tributary valleys), which impact atmospheric processes. With the intention of "comparing apples with apples" in mind, we propose in this work that distance should not be the only parameter considered in the grid point selection for model evaluation. The idea is that, by selecting a grid point that is representative of the measurement site, the model evaluation can be used to better disentangle contributions from different processes with the goal of ensuring that the model produces the right results for the right reasons. We will give a brief overview of an experiment made with the Weather Research and Forecasting (WRF) model. First, a new physically consistent grid point selection method is developed taking into account orographic parameters (i.e., the slope angle and aspect), the most relevant land- cover parameters (i.e., albedo and roughness length), and a combination of orographic and land- cover parameters, which usually vary simultaneously in complex terrain. Once the grid point selection is made, elevation-dependent variables are corrected for height differences between the model and the real terrain. Similarly, to allow for a model evaluation with observations at heights other than the typical 2- and 10-m AGL, model variables are extrapolated from the first model level to the respective sensor height using Monin-Obukhov Similarity Theory consistent with the WRF 2-m and 10-m diagnostic output variables. The physically consistent grid point selection is compared with the traditional nearest grid point selection for different horizontal model resolutions by evaluating the model output at the respective grid points against observations from a number of automatic weather stations and from a small network of surface-energy balance stations (i-Box eddy-covariance stations) in the Inn Valley (Austria).

The city of Graz in south-eastern Austria, frequently faces problems with air pollution in the winter half year due to persistent inversions and associated low wind situations, although emission levels are not exceptionally high. Graz is located at the south-eastern edge of the Alps in an oval basin that stretches from north to south. It is bordered on all sides by mountains with a maximum height of 400 to 600 m above city level. The geographical location and the local topography of Graz intensify the strength and persistence of winter inversions. The aim of this work is to assess the ability of the Weather Research and Forecasting (WRF) model to reproduce these weather conditions. The model is run with multiple configurations of parameterizations and spatial resolutions to determine the differences and performances of the different settings. Simulations with the WRF model are run for several fall and winter periods with multi-day inversions over the Basin of Graz. The model is forced with the ECMWF-IFS analysis data with a spatial resolution of 9 km and two one-way nested domains with resolutions of 3 and 1 km are used to investigate which resolution is needed to sufficiently represent the local topography. Several planetary boundary layer, microphysics and shortwave radiation schemes were tested and evaluated with station and radiosonde observations as well as the analysis and nowcasting system INCA.

A new scheme for the parameterization of vertical diffusion applicable under convective conditions is developed using Large eddy simulation (LES) data. Scheme is implemented and tested in Weather Research and Forecasting model with the chemistry (WRF-Chem) model. The novelty mainly relies on non-local contributions to the turbulent transport of heat and momentum as well as the contribution of the entrainment layer to the mixing intensity that are now explicitly included in the model. The proposed scheme includes the implementation of universal empirical coefficients that are independent of stability providing an easy-to-use solution for the parameterization of heat and momentum fluxes. This is an important result pointing to the straightforward applicability of the method in air quality and climate models and the improvement of turbulence parametrizations in the boundary layer. The method is implemented in WRF-Chem model and validated against mast-mounted measurements in a complex terrain as well as against aviation measurements. The results indicated improvement in modeling performance in terms of the near-surface wind speed and generally decreased applied statistical measures: BIAS, root mean square error (RMSE), and normalized mean square error (NMSE) which is an important step in understanding and improving the performance of numerical models.

Considerable variability in cool-season precipitation exists in the Great Basin of the interior western United States where narrow, steeply sloped mountain ranges are separated by broad alluvial basins. In northern Utah, mean wintertime (December to February) liquid precipitation equivalent (LPE) at the Salt Lake City International Airport (1288 m MSL) in the Salt Lake Valley is only 100 mm, compared to 509 mm at Alta (2660 m) in the central Wasatch Range 35 km to the southwest. Mean annual snowfall at Alta exceeds 1250 cm, impacting mountain transportation, water resources, avalanche hazard, and winter tourism. Snowfall at Alta can be especially heavy during northwesterly flow when shallow, post-frontal, orographic or lake-effect convection produces highly localized precipitation. During the 2022–2023 cool season, we are operating a Micro Rain Radar (MRR) and OTT Parsivel disdrometer at Highland High School (1363 m) in the Salt Lake Valley and Alta (2668 m) in the central Wasatch Range. These sites are 23 km apart with Highland High School directly northwest of Alta, enabling comparison of the characteristics of cool-season precipitation events in the Salt Lake Valley and central Wasatch Range, especially during orographic uplift in northwest flow. Fortuitously, the two sites also aligned along the 138˚ azimuth of an operational National Weather Service S-band radar, providing broader context for the interpretation of the MRR and disdrometer data. We will present an initial census and comparison of the radar and hydrometeor characteristics during storms at the two sites, focusing on mechanisms affecting the ratio of upland to lowland precipitation, especially during periods of orographic uplift in northwest flow.

The Yeongdong region (eastern mountainous region of Korea) is frequently vulnerable to heavy snowfall in winter in terms of societal and economical damages. By virtue of a lot of previous efforts, snowfall forecast has been significantly improved, but the performance of light to moderate snowfall forecast is still poor since it is very conducive to synoptic and mesoscale interactions, largely attributable to Taeback mountains and East Sea effects in Korea. A multi-year ongoing intensive observation has been made in cooperation with Gangwon Regional Meteorological Office and National Institute of Meteorological Studies in the winter season since 2019. Two distinctive Cold Air Damming (CAD) events (14 February 2019 and 6 February 2020) were observed for two years when the snowfall forecast was wrong specifically in its location and timing. For two CAD events, lower-level temperature below 2 km ranged to lowest limit in comparisons to those of the previous 6-years (2014 – 2019) rawinsonde soundings for snowfall events, along with the stronger inversion strength (>2.0℃) and thicker inversion depth (>700m) above the snow clouds. Further, the northwesterly was predominant within the CAD layer, whereas the weak easterly wind was exhibited above the CAD layer. For the CAD events, strong cold air accumulation along the east side of Taeback Mountains appeared to prevent snow cloud and convergence zone from penetrating into the Yeongdong region. Meanwhile, an ice pellet (IP) episode (1 March 2021), which is the first measurement in Korea, was analyzed using a MASC (Multi-Angle Snowflake Camera). Abrupt cold air intrusion over the region made very short-time (within an hour) duration of IP possible, which could be identified through temperature profiles with rawinsonde soundings. Still, we need more CAD golden episodes to investigate the various roles of frequent-occurring CAD in solid precipitation in the Yeongdong region using continuous intensive observation and modeling studies altogether.

In this presentation, we will introduce the clouds that form over and leeward Mt. Fuji in Japan and furthermore report the climatological characteristics of the atmosphere at the time of their formation. Mt. Fuji is a typical conical mountain. With a summit elevation of 3376 m, it is the largest mountain in Japan. "Kasa" clouds form over the mountain summit, "Tsurushi" clouds on the leeward side of the mountain, and "Hata" clouds on the leeward slope of the mountain. Kasa clouds mean a cloud that looks like a cap, and this cloud is the same as a cap cloud. Kasa clouds tend to form on cloudy summer mornings when the humidity near the summit (600 hPa level) is high and the wind is strong. The case average of humidity near the summit on the windward side is 71.4%, while the climatological mean at this location is 43.8%. The wind speed at a slightly lower altitude than the summit (700 hPa level) has a case mean value of 16 m/s, while the climatological mean is 11.9 m/s. Tsurushi clouds mean the hung clouds and must be mountain-wave lenticular clouds. This cloud often forms at the same time as the Kasa clouds. Tsurushi clouds may appear at a height similar to that of mountain peaks or at 100 to 300 hPa higher than that. The appearance height strongly depends on the altitude at which the humidity maximum appears. Hata clouds mean Banner or Flag clouds, but they appear to be different from banner clouds in Matterhorn. Hata clouds, unlike Kasa clouds and Tsurushi clouds, tend to form during the daytime on clear winter days. Wind speeds near the summit when Hata clouds appear are considerably higher than those of Kasa and Tsurushi clouds, averaging 31.7 m/s in the case average. On the other hand, the relative humidity is quite low, 31.7% in the case average. The maximum value of relative humidity at the appearance of Hata clouds appears near 850 hPa level, not near the summit.

Mt. Fuji is a typical conical mountain. With a summit elevation of 3776 m, it is the largest mountain in Japan. Cap and Tsurushi clouds often appear over and leeward of this mountain, respectively. Here, Tsurushi clouds mean “the hung clouds” in Japanese and must be mountain-wave lenticular clouds. These clouds are very popular among photographers and weather people. Although the basic mechanism of each cloud’s formation is well known, the factors determining the size of each cloud are not well understood. Here, by combining image data with live cameras and meso-scale objective analysis data, we statistically revealed a connection between cloud size and wind velocity. Furthermore, using a cloud-resolving meteorological model (CM1), we conducted numerical experiments under different weather conditions on five cases of cap clouds that formed over the summit of Mt. Fuji. From these results, the cap clouds grow larger with higher water vapor content and higher wind velocity. Last, we considered that the reasons are the increase in the vertical wavelength of mountain waves and the lifting of moist air masses from lower layers. The same conclusions as the cap clouds’ cases were obtained for the Tsurushi (mountain-wave) clouds’ cases.

During cold-air outbreaks, lake- and sea-effect precipitation systems (hereafter lake effect or LES) can generate heavy snowfall downstream of warm water bodies, potentially gridlocking transportation and presenting hazards to life and property. Broad-coverage LES feature open-cellular convection or multiple, quasi-periodic precipitation bands produced by roll convection that frequently interact with downstream hills, plateaus, and mountains. Using idealized, high-resolution Bryan Cloud Model (CM1) simulations, this presentation examines how the orographic enhancement of broad-coverage LES varies with the strength of the ambient flow. Simulations were run with an idealized open lake, unidirectional wind profiles with varying wind speeds and shear, and downstream orography that included a coastal plain, 250-m plateau, or 1000-m ridge. In weak-flow simulations without orography, precipitation maximized along a land-breeze front near the downstream shoreline and declined with inland extent. Precipitation increased along the land-breeze front with the addition of a plateau or ridge, but still declined with inland extent, even over the windward slopes of both topographic features. In contrast, in intermediate wind speed and shear simulations, the land-breeze front did not form, coastal precipitation was limited, and landfalling precipitation features strengthened and enhanced precipitation over the downstream orography, especially over the 1000-m ridge. In strong wind and wind-shear simulations, banded flow-parallel circulations and precipitation formed, intensified over the downstream orography, and the heaviest precipitation fell at upper elevations due to orographic lift and enhanced hydrometeor growth through the seeder-feeder process. These results further illustrate the transition in storm characteristics affecting the distribution and intensity of snowfall generated by broad-coverage LES and may be relevant for understanding the evolution of convective features during orographic uplift in other mountainous regions.

In the field of geo-hydrological risk, rainfalls represent the most important triggering factor for superficial terrain failures such as shallow landslides, soil slips and debris flows. These phenomena are triggered over mountains regions where the density of the ground-based meteorological network is poor, and the local effects caused by mountains topography can change dramatically the spatial-temporal distribution of rainfalls. Trying to reconstruct a representative rainfall field across mountain areas is a challenge due to the complex interaction between terrain elevation and cloud microphysics. We present here a reanalysis of an ensemble of extreme rainfall events that happened across the central Alps and Pre-Alps, in the northern part of the Lombardy Region, Italy using the Linear Upslope Model Extension (LUME). This model has been designed for describing the mechanism of orographic precipitation considering vertically integrated quantities. The precipitation mechanism is driven by the incoming water vapour flux that hit the mountain upslope region. The model considers also time delays due to microphysical processes such as cloud and rain generation. We aimed to increase the accuracy of LUME including some correlation within the meteorological index retrieved from radiosonde parameters and precipitation efficiency. Moreover, we have extended the LUME model to work automatically with a 2D digital elevation model. Other novelties consider the dynamic simulation where the advection of water vapour flux and the moisture balance have been now taken into account. The hypothesis of a steady-state rainfall event has been discarded using time-dependent quantities to simulate and highlight the most critical phases of the studied events. The results obtained from LUME were validated considering the local rain gauge amounts and the reanalysis database of MERIDA as a reference. They have shown a satisfactory reproduction of the amounts and locations of the rainfall maxima also running in 2D mode, giving a realistic reconstruction of the precipitation that occurred for the critical event studied. LUME 2D is written in Python language and since it considers vertical integrated quantities computations are rather fast. The application of the LUME 2D model could help to better describe past rainfall phenomena and give useful insight into the precipitation processes that occurred in those ungauged areas where geo-hydrological hazards were triggered.

Atmospheric Rivers (ARs) provide necessary, and sometimes extreme, moisture in the hydroclimate of the Andes mountain range, where orographic precipitation is enhanced and snow accumulation increased, particularly for cold season ARs. As the climate warms, South American ARs are expected to increase in frequency and intensity, leading to increased orographic precipitation, but also reduced snowpack in many parts of the world. Improved understanding of the relationship between AR activity and orographic precipitation and snowpack in a warming climate is needed to provide a foundation for understanding future hydroclimate change over the Andes. The goal of this research is to evaluate and understand variations in AR-associated orographic precipitation patterns and their impact on snowpack over the southern Andes (35- 55S) in high-resolution regional climate simulations. Specifically, we use ERA-5-forced Weather Research and Forecasting (WRF) simulations with 4-km grid spacing that were run for 2000-2020 over all South America by the NCAR-led South America Affinity Group (SAAG). The fine grid spacing of these SAAG-WRF simulations relative to most regional climate simulations allows them to better resolve the complex terrain of the Andes. This study uses selected AR detection algorithms from ARTMIP (Atmospheric River Tracking Method Intercomparison Project). AR days are classified depending on the presence/absence of a landfalling AR and on AR characteristics to examine the modulation of orographic precipitation patterns and mountain snowpack by ARs in the SAAG-WRF simulations. Simulated variations in orographic precipitation are evaluated against rain gauge observations from national networks in Argentina and Chile. The model does well overall at capturing the climatological pattern along the domain. Results from subsetting AR days show a general agreement of the model to the various ARTMIP algorithms in terms of precipitation patterns associated with landfalling ARs. Variations in snowpack are evaluated against Andean Snow Reanalysis (ASR) by Cortés and Margulis (2017) and snowpillow data from national networks. The analysis of current and historical AR-associated orographic precipitation and snow cover from a high-resolution climate model is needed to provide more detailed information for future climatic changes in these variables within regions of complex terrain.

It is well known that atmospheric inversions play a crucial role in determining the pattern of atmospheric flow in mountainous regions. In the literature, there has been focus on the impact of inversions on the flow, but less focus on the inversions themselves; when, where and why the occur. In this study, a large set of upper-air data from Iceland is explored to assess the climatology of inversions, and to some extent, the characteristics of the flow associated with statically stable layers in the troposphere. The data reveal high frequency of tropospheric inversions, typically at 800-900 hPa. The maximum frequency is from late winter until late autumn, with a minimum in mid-winter. In the summer, the mean elevation of the inversions is lower than in the late winter and in the autumn. Inversions in southerly flow are typically associated with moderate baroclinicity and advection of relatively warm airmasses above the inversion. Inversions in northerly flow do not show this characteristic. Case studies indicate substantial variability in synoptic-scale flow patterns leading to inversions.

Bora is a well-known downslope windstorm that blows at the NE Adriatic coast from inland towards the sea, mainly from the NE direction. One of the striking bora characteristics are the quasi-periodic gust pulsations. In this work, their characteristics during severe bora in the lee of the Dinaric Alps, near the town of Senj, are explored using rotational spectral analysis and nine months of continuous high-frequency sonic anemometer measurements. Analysis shows that the pulsations' propagation direction does not correspond to the measured near-ground wind direction. Additionally, these two directions seem to be negatively correlated, and their relative angle is larger when bora is forced by an anticyclonic pressure gradient, as opposed to when it is forced by a cyclonic one. Although the pulsations are mostly rectilinear (majority of the energy contained parallel to their propagation direction), positive rotational component is larger than the negative in all but one bora episode, and the motions can become briefly elliptical. Several more notable bora episodes exhibiting most of the aforementioned features are highlighted. Possible reasons for these observations are discussed, such as large directional shear near the top of the lee-side jet (shooting flow) and the presence of the potential vorticity banners. High-resolution simulations are planned to elucidate these observations.

The Jintsu-Oroshi is a representative Japan’s south foehn. This local winds blow in the coastal plain adjacent to the mountains and occur more frequently at night than the daytime. This study revealed the significant factors causing the above unique diurnal variation, using the Weather Research and Forecasting (WRF) model. Simulations and observations showed that in the daytime, the Jintsu-Oroshi did not occur nevertheless the approaching flow conditions were favorable for downslope windstorms. Simulated results suggested that key factors in understanding the reasons are the development of the mixed layer over the mountains and sea breezes in the leeward plain. Indeed, mountain waves did not occur under the near-neutral atmospheric stability condition during the daytime, resulting in no downslope winds. As a result, sea breezes covered the leeward plain. After sunset, the atmospheric stability in the boundary layer over the mountains changed to stable condition, which made the Jintsu-Oroshi blow and descend on the leeward slope of the mountain. After several hours, sea breezes disappeared and the Jintslu-Oroshi reached the leeward plain and caused a temperature increase. We can conclude that the diurnal change of the atmospheric boundary-layer stability and thermally driven local pressure gradient make the Jintsu-Oroshi tends to blow at night.

”Rokko-oroshi” is a relatively strong northerly wind that blows at the southern foot of the Rokko Mountains in Kobe, Japan. Rokko-oroshi is one of the most famous local winds in Japan. However, there have been no studies that defined the properties and clarified the generation mechanism of Rokko-oroshi. Therefore, the purpose of this study is to conduct statistical analysis of Rokko-oroshi to reveal its characteristics and numerical simulation to elucidate the mechanism that causes the strong winds. First, the perceptions of Rokko-oroshi of local residents was investigated. Based on the results and previous studies, “Rokko-oroshi” was quantitatively defined in this study. Based on this definition, 113 cases of Rokko-oroshi were extracted over a 49-year period. Then, statistical analysis was conducted using surface wind observation data provided by the Kobe City Atmospheric Monitoring System. The results showed that Rokko-oroshi blows (1) when a high pressure in the west and low pressure in the east appears in a weather chart, (2) when a south-coast cyclone passes near the Kanto region, (3) when a typhoon moves northeastward off the Kii Peninsula, and (4) when a cold front passes near Kobe City. Because these pressure patterns appear mostly in winter, the frequency of Rokko-oroshi was higher during the cold season. As a daily variation, Rokko-oroshi is most likely to blow during the night and early morning, compared to the daytime. Furthermore, analysis of the upper observation data with radiosonde showed that an inversion layer appears at altitudes between 1500 m and 3000 m about 90 percent of the events. Finally, we analyzed the observed data and conducted a numerical simulation using the Weather Research and Forecasting (WRF) Model for a typical case of Rokko-oroshi. The observed spatial distribution of surface wind indicated that the wind was particularly strong at “Nada” among the leeward of Rokko Mountains. The numerical simulation also showed that the winds from the north to north-northwest weakened rapidly on the windward of Rokko Mountains and became stronger on the leeward. The vertical cross section of the potential temperature showed that a weak wind area was formed around 2000 to 3000 m above the leeward slope of Rokko Mountains, and that strong winds blow near the surface. Furthermore, a slight jump in wind was also simulated on the leeward of the area. From these results, it was concluded that the Rokko-oroshi caused by a winter pressure pattern is a typical downslope wind.

The Obonai-dashi is local winds blowing in the Obonai district of Japan. It is said that it is warm in the Obonai district when the Obonai-dashi blows from the Ou mountains located east of there even when cold and moist winds "Yamase" blows in the east coast of Honshu, Japan. Therefore, the Obonai-dashi is considered to be valuable local winds that bring good harvests. As the temperature rises when the Obonai-dashi blows, it is thought to be one of the foehn winds. However, it cannot be concluded that the Obonai-dashi is foehn because no high-resolution observation and simulation has been conducted around the Obonai district. Moreover, it is questionable whether the Obonai-dashi really blows when the Yamase blows. Thus, we reveal the climatology of the Obonai-dashi by statistical analysis with the observation data, and the three-dimensional wind system when the Obonai-dashi blows by case studies with the observation data and WRF simulation. Statistical analysis showed that it is common that the Obonai-dashi start blowing after a migrative anti-cyclone passes northern Japan and end blowing when a extratropical cyclone approaches there, while the Obonai-dashi doesn't blow much when the Yamase blows. Case study showed that southerly wind at the upper-level bypasses mountains, crosses the Sengan pass located east of the Obonai district, and blows down toward the Obonai district. It also indicated that easterly wind blows only near the surface from the Sengan pass to the Obonai district, while southerly wind parallel to the Ou mountains blows above ridgeline. Therefore, it is considered that the Obonai-dashi is a downslope windstorm blowing from the Sengan pass and its occurrence relates to saddle of the Ou mountains, and a wind with properties of gap winds like a shallow foehn.

The Foehn flow along the Austrian Brenner transect in the Eastern Alps oftentimes sources from elevated upstream levels, which are decoupled from the blocked flow underneath. However, a recent study highlighted striking differences in the origin of Foehn air parcels arriving in western Alpine valleys compared to the ones arriving in eastern Alpine valleys. In fact, the Foehn in the Western Alps is found to partially originate at near-surface levels over the eastern Po Valley. There, air parcels gather within an easterly barrier jet before ascending towards the Alpine crest. The sourcing altitude of air parcels is, in turn, relevant for the for the formation of upstream precipitation and the mechanisms of Foehn air warming. Using a high-resolution COSMO-NWP hindcast, we present evidences that a cold-air pool in the western Po Valley facilitates air parcel lifting towards the Alpine crest within the barrier jet. In the presented South Foehn case, the spatially confined cold-air pool leads to slantwise ascending isentropes in the east-west direction, which then favors an along-isentropic upglide of westward moving air parcels. A Lagrangian methodology is employed to disentangle the adiabatic and diabatic contributions to the lifting of air parcels. The isentropic upglide (i.e., the adiabatic contribution) is found to substantially contribute to the lifting of air parcels from near-surface levels. The processes causing the formation, maintenance and erosion of the cold-air pool are further investigated using an Eulerian heat budget tool. In a second part, the analysis is expanded to a comprehensive five-year dataset of operational COSMO analyses. For the majority of Foehn events, a horizontal gradient in potential temperature is identified in the Po Valley, which however exhibits a distinct case-to-case variability. Events associated with a strong gradient also feature an intense low-level barrier jet. The strength of the horizontal gradient in potential temperature negatively correlates with the sourcing altitude of air parcels, which further corroborates the findings from the case study. Finally, events with a strong gradient are associated with intense orographic precipitation on the Alpine south side and stronger Foehn winds on the Alpine north side, as confirmed by observations in the northern Foehn valleys.

Alpine south foehn has been a favoured subject among Alpine meteorologists for more than a century, with a particular focus on the warming mechanisms and the driving processes leading to the descent of the foehn air parcels into the northern foehn valleys. There has, however, been less focus on the sensitivity of foehn flows into and within the major foehn valleys to the large-scale meteorological situation. For instance, questions such as how different tributary valleys contribute to the foehn flow in a major valley or how foehn air parcels are channeled under different large-scale situations, have rarely been investigated. In this study flow patterns of south foehn in the Rhine Valley in Switzerland are investigated based on semi-idealised large-eddy simulations (LES). The LES are performed with the Finite-Volume Module (FVM) of the Integrated Forecasting System (IFS). They are run at a horizontal resolution of 300m and using realistic topography, while maintaining idealised initial and boundary conditions. The initial conditions are systematically varied in terms of upstream wind speed and wind direction, thus covering a spectrum of potential upstream, large-scale flow conditions during south foehn. The flow patterns emerging in the Rhine valley, at a cross-section to the south of Lake Constance, are systematically analysed based on a Lagrangian methodology. Backward trajectories are calculated from the target cross-section. These are assessed, if and to which degree, a foehn flow is established in the valley. Furthermore, the contributions from several tributary valleys and the free troposphere are determined. The simulations show that foehn flow in the Rhine valley varies substantially if the upstream wind direction changes within a directional window around the typical south-easterly to south-westerly upstream flow conditions. This variability relates both to the degree of foehn intensity in the Rhine valley, as well as to the contributions from the different sources. A strong variability is also discernible with respect to the upstream velocities. In summary, this study is able to shed some new light on the variability of the flow within a major foehn valley by sampling a wide spectrum of upstream flow conditions. The simulations also show the capability of the novel IFS-FVM to study the flow in steep and complex topography.

This work studies nonhydrostatic effects (NHE) on the drag produced by orographic gravity waves (OGWs) forced by relatively narrow isolated three-dimensional mountains, showing that this drag has a key dependence on the Froude number of the incoming flow, Fr, a quantity that is proportional to the incoming wind divided by the product of the Brunt-Väisälä of the incoming flow and the orography width. Based on linear wave theory, an asymptotic expression is derived for the drag produced by OGWs that are vertically propagating, but affected by NHE, i.e., for relatively low Fr. According to this asymptotic solution, which has good accuracy for any value of Fr, NHE can be divided into two parts. The first part only depends on Fr and is related to the high-wavenumber part of the wave spectrum that is often misrepresented as hydrostatic OGWs. The second part arises from the difference between the dispersion relationships of hydrostatic and nonhydrostatic OGWs, having an additional dependency on the horizontal wind direction and orography anisotropy. It can change, not only the drag magnitude, but also its direction. Examination of NHE for OGWs forced by both circular and elliptical orography reveals that the drag is reduced as Fr increases, at a faster rate than for two-dimensional OGWs forced by a ridge. The behaviour of NHE is mainly determined by Fr, while horizontal wind direction and orography anisotropy play a minor role. Implications for the parameterization of nonhydrostatic OGWs in high-resolution and/or variable-resolution models are discussed.

Numerical simulations are carried out using the Weather Research and Forecast (WRF) model to explicitly calculate the ratio of orographic gravity-wave drag (GWD) in the presence of a stable boundary layer (BL) to the inviscid drag in its absence, either obtained from inviscid WRF simulations or estimated using an analytical linear model. This ratio is represented as a function of three scaling variables, defined as ratios of the BL depth to the orography width, height, and stability height scale of the atmosphere. All results suggest that the GWD affected by the stable BL is roughly inversely proportional to the square of the BL depth. The scaling relations are calibrated and tested using a multilinear regression applied to data from the WRF simulations, for idealised orography and inflow atmospheric profiles derived from reanalysis, representative of Antarctica in austral winter, where GWD is expected to be especially strong. These comparisons show that scaling relations in which the drag is normalised by the analytical inviscid estimate work best. This happens because BL friction reduces the amplitude of the waves above the BL, making their dynamics more linear. Knowledge of the BL depth and orography parameters is sufficient to obtain a fairly good correction to the inviscid drag without needing additional information about the wind and stability profiles. Since the drag currently available from numerical weather prediction model parametrizations comes from linear theory uncorrected for BL effects, the results reported here may be straightforwardly applied to improve those parametrizations.

Linear theory remains an important way of thinking about orographic gravity waves and a guide to drag parametrization in models which do not resolve such waves. This poster examines an idealized system with solutions to the Taylor-Goldstein equation with the addition of an artificial damping term: analytical solutions for a theoretical constant damping across the whole model and a computational model for the case of parameters varying with vertical position. The poster additionally compares the propagating and evanescent cases, dependent on the relation between certain physical parameters, which variable is damped, and the magnitude and vertical distribution of damping.

The Adriatic sea area is one of the few areas in mid-latitudes worldwide characterized by hurricane 5 scale wind gusts. In particular, severe bora downslope windstorms are frequent phenomena over the complex terrain of the eastern Adriatic coast. Such events are a major threat to human safety, especially at sea and near the coasts, and may cause large economic damage. Therefore, estimation of extreme winds, in particular for a 50-year return period, serves as a standardized design value for construction of infrastructure. In our work we study wind speed and wind gust extremes along the wider Adriatic area using both observations and high-resolution ALADIN-HR model data. We first analyse long-term records of 60 measurement stations over Croatia and estimate extreme winds using several methods derived from generalized extreme value theory. Then, we utilize ALADIN-HR simulations at 2 km grid spacing to study the spatial properties of maximal simulated wind speed and maximal simulated wind speed gusts in a 10-year period. Moment-based and spectral verification of wind speed, performed on a number of surface stations in different climate regions of Croatia, suggests numerical simulations were successful. We further estimate extreme winds for return periods of 10-100 years and perform a comparison of simulated and observed estimated wind extremes. To study microscale spatial wind variations, we simulate individual extreme wind events using LES model to discuss the representativeness of extreme wind estimations from both measurements and mesoscale numerical models.

Sailing across the Atlantic and the establishment of settlements in N-America that lasted for several hundreds of years and were dependent upon trade with Europe was perhaps the greatest achievement of mankind in the Middle Ages. In this achievement, weather played a key role. Navigation in the Middle Ages was most likely mostly based on persistence of winds, and there are indications that persistence and correlation between elements of the sensible weather, in particular fog and drizzle, helped in navigation in the N-Atlantic during the Viking age. Investigation of the weather in the CARRA dataset, produced by dynamic downscaling reveals that the connection between wind directions and fog is different on the leg between Iceland and Greenland from what it is between Iceland and Norway. Consequently, the same navigational rules could not be applied on both these legs, making navigation from Iceland to Greenland even more difficult than navigation from Norway to Iceland. The CARRA dataset also reveals an extremely high frequency of windstorms during the summer at Cape Farewell, indicating that orographic winds were indeed a much greater hazard to ships on the route between Europe and N-America, than strong winds due to extratropical cyclones.

South foehn has a climatological impact on vegetation in Western Austria due to the drying effect caused by stronger windspeeds and rising temperatures. With an occurrence of 10-20 % on yearly basis in certain regions, it is advisable to analyse possible changes in foehn behaviour in the wake of climate change to better estimate, which trees to cultivate on foehn-affected slopes. Foehn in Switzerland has shown to be predictable with reasonable accuracies by using weather station data and synoptic patterns of reanalysis data over Europe with machine learning approaches like gradient boosted tree models or convolutional neural networks. For applying similar methods on Western Austria, a training data set for daily foehn occurrence has been created out of eleven years of selected semi-automatic weather station data by applying Objective Foehn Forecasting. By counting affected valley-stations, foehn events can be divided into local and widespread events. For the features of the machine learning algorithm, physical meaningful variables like mean sea level pressure, 850 hPa potential temperature gradients and 500 hPa wind speed and wind direction were used. To allow an application on climate change projections, the selection of these variables was limited by the availability in EUROCORDEX models. With this approach, we were able to train two XGBoost models per region with accuracies of over 90 % for classifying between no foehn and foehn and over 80 % for deciding between local and widespread foehn during the training period (2011-2021). These algorithms were then used not only for ERA5 reanalysis data, but also for the OEKS-15 ensemble of EUROCORDEX climate scenarios to be able to analyse possible changes in foehn behaviour until 2100. By comparing the monthly foehn occurrence of the models with reanalysis data in the historic period and its statistical parameters, it is assured that all individual EUROCORDEX models are able to reproduce weather patterns representing foehn. Through applying the algorithms on the suitable models of the ensemble, promising predictions of how foehn frequency and seasonality will change over the course of different representative concentration pathways during the 21st century in Western Austria can be given.

The Yarlung Zsangbo Grand Canyon (YGC) is an important pathway for water vapor transport from south Asia to the Tibetan Plateau (TP). This area exhibits one of the highest frequencies of convective activity in China, and precipitation often brings natural disasters to local communities that can dramatically affect their livelihoods. In addition, the produced precipitation give rise to vast glaciers and large rivers around the YGC. In 2018, the Second Tibetan Plateau Scientific Expedition and Research Programme tasked a research team to conduct an "Investigation of the water vapor channel of the Yarlung Zsangbo Grand Canyon" in the southeastern TP. This team subsequently established a comprehensive observation system of land-air interaction, water vapor, cloud cover, and rainfall activity in the YGC. This paper introduces the developed observation system and summarizes preliminary results obtained during the first two years of the project. Using this observation network, we focus herein on the development of heavy rainfall events in southeast TP that are associated with water vapor changes.

Climate change projections for the 21st century indicate that the intensity of heat waves in France will increase, with the south-east region projected to be the most impacted. Climate change mitigation or adaptation measures will therefore need to be devised to deal with more extreme heat and associated impacts (including on air quality), particularly in urban settings where high temperatures are already a concern during summertime. The present work aims to evaluate such measures for the alpine city of Grenoble (France), which basin is conducive to extreme temperatures. The measures that are being considered in this work are focused on urban planning and include: increased vegetation within the city (e.g., parks and green roofs), increased albedo of buildings (e.g., white roofs), and creation of additional water bodies. Particular attention is paid to the impact of these measures on air quality. The assessment of the urban planning measures is carried out using numerical modelling, with the Weather Research and Forecast (WRF) model to determine atmospheric dynamics. The model was first run for a past heat wave event in Grenoble (that of summer 2018) so as to evaluate its performance against (temperature and wind) observations for various parameterisations of the atmospheric boundary layer and of the urban canopy. Results indicated that the description of the urban canopy effects with the “Building Effect Parametrization + Building Energy Model” (BEP+BEM) coupled with the Bougeault-Lacarrère boundary-layer parameterisation scheme provides a refined distribution of temperature across the city, in accord with observations. This model set-up is being used to consider a future heat wave event (in summer 2052) extracted from climate model projections for a range of mitigation/adaptation scenarios. Results will be discussed in the presentation. This work will be of great interest to local communities and policy makers as they will inform future decisions on urban planning and will contribute to the attractiveness of cities.

In order to understand precipitation characteristics and microphysical processes, measurements obtained from instrumentation in field campaigns can be very useful. Two key instruments that provide detailed information about precipitation processes are: (i) disdrometers (PARSIVEL) that provide detailed ground measurements of precipitating particles and precipitation type, and (ii) vertically pointing Doppler radars -Micro Rain Radar (MRR)-, that provide precipitation profiles (typically 3 km height above ground level, with 100 m vertical resolution), both with a high temporal resolution (1 minute). During 2019-2022, WISE-PreP project -Analysis of Precipitation Processes in the Eastern Ebro Subbasin- was carried out to study precipitation processes aiming to characterize possible differences in precipitation induced by surface characteristics (irrigated vs non-irrigated areas) in NE Spain. Specific deployed instrumentation during the LIAISE-2021 campaign included three sites equipped each with a vertical radar and a laser disdrometer, covering both irrigated and non-irrigated sites. Time series of vertical precipitation profiles and in-situ drop size distributions were recorded to study microphysical processes and related variables including precipitation intensity or convective vs stratiform rainfall regimes. First results show from the disdrometer derived 1-min rainfall rate distributions presented some differences between the irrigated and non-irrigated areas during summer, unlike the other seasons when surface conditions are more similar in both areas. An overview of additional results obtained with numerical simulations using the WRF model is also provided. In 2023-2025 ARTEMIS project -Analysis of orographic impacts on precipitation microphysics and satellite-derived estimates - aims to study the impacts of complex terrain on precipitation characteristics, addressing the variability of surface intensity, phase (i.e. snow, rain), regime (convective vs. stratiform) and also on satellite precipitation estimates. The project will be based on an experimental field campaign: Cerdanya-2024 that will include the deployment of the instrumentation in 4 sites located at different altitudes, from 1100 m (Das Aerodrome) to 2530 m above sea level (Tosa d’Alp peak), on the Lower Cerdanya, NE Spain.

Previous studies have found a pronounced nocturnal low-level jet at the exit of the Inn Valley north of the valley contraction near Schwaigen which reaches into the Alpine foreland for several tenth of kilometers (e.g. Pamperin and Stilke, 1985 as part of the MERKUR experiment or a model study by Zängl, 2004). The exit jet forms under nocturnal stably stratified atmospheric conditions and is interpreted as a transition from subcritical to supercritical hydraulic flow. As part of the pre-experiment of the TEAMx programme in June-August 2022, we have conducted measurements to corroborate the previous findings on the formation and maintenance of the Inn valley exit jet and learn more about its turbulence structure, which has not been studied in previous experiments. For this purpose, a wind lidar was deployed in Brannenburg, north of the valley constriction. Furthermore, during selected days, radiosondes were launched at the site of the wind lidar, accompanied by drone measurements. Additionally, the operational network of the German Meteorological Service (DWD) has been supplemented by ground measurements of wind, temperature and humidity (additionally pressure, radiation and precipitation for selected stations) along the valley between Kufstein and the wind lidar site. This contribution will show the results of the measurement campaign. References: Pamperin, H., and G. Stilke. "Nächtliche Grenzschicht und LLJ im Alpenvorland nahe dem Inntalausgang." Meteorologische Rundschau 38.5 (1985): 145-156 Zängl, G. "A reexamination of the valley wind system in the Alpine Inn Valley with numerical simulations." Meteorology and Atmospheric Physics 87.4 (2004): 241-256.

Mountainous terrain generates regions with turbulent exchange mechanisms which are far more complex than over flat topography. As a result, anisotropic flow interactions occur across a broad continuum of scales. Of particular interest are nighttime, stable conditions, when these flow interactions are usually confined to shallow layers a few tens of meters above the surface. High-resolution, state-of-the-art numerical weather prediction models still struggle adequately representing the impact of such flows and their interactions on the nocturnal mountain boundary layer, given their extremely shallow character. An example of a historically less studied flow interaction is the confluence of nighttime cold air outflows from tributary valleys into a parent valley. TEAMx („Multi-scale transport and exchange processes in the atmosphere over mountains – Programme and experiment“), scheduled to take place in the Alps in summer 2025, offers an ideal opportunity to help improve our knowledge of confluent valley-tributary flow interactions. In preparation and to optimize the intended measurement setup for TEAMx, four Doppler lidars and one cloud radar of the KITcube advanced integrated atmospheric observation system were operated in the Lower Inn Valley in Kolsass, about 20 km east of Innsbruck, Austria, between May 18 and September 19, 2022. This deployment was part of the TEAMx pre-campaign, a collaboration of several European universities, research institutions as well as weather services. This particular region of the Inn Valley was chosen due to the presence of multiple tributary valleys entering into the parent Inn Valley from the south. Two of the deployed Doppler wind lidars were located along the northern Inn Valley sidewall, with the sole purpose of scanning in a purely horizontal plane approximately 65 meters above the Inn Valley floor. By doing so, the derivation of the two-dimensional wind speed and direction using the coplanar retrieval algorithm was made possible, whereas the other instruments delivered continuous wind profiles from the center of the Inn Valley. Up to now, the complexity of tributary valley outflows has never been sampled with such fine and wide spatial detail.

In the lee of the Santa Ynez Mountains north of Santa Barbara, CA, late afternoon-to-early morning episodes of offshore, northerly gusty downslope surface winds are frequently observed. These downslope winds are locally known as Sundowners. Sundowners are spatially non-uniform and can be accompanied by rapid increases in temperature and decreases in relative humidity with significant impact on fire behavior. Our understanding of the spatial and temporal variability of Sundowners and the underlying mesoscale mechanisms is limited. To address this knowledge gap, the NSF-funded Sundowner Wind Experiment (SWEX) was conducted in Spring 2022. In this contribution, we focus on observations made by the surface-based mobile observing platform UWOW (University of Virginia Wind Observatory on Wheels), a trailer-mounted lidar system to measure spatial and temporal variations of lower tropospheric winds. UWOW uses a HALO photonics StreamLine XR Doppler lidar, a GPS, and an inertial navigation system placed in a custom trailer to measure boundary layer winds while traveling on the road. UWOW can measure wind profiles from approximately 100 to 3000 m above ground with 30 m vertical spacing. During SWEX, UWOW travelled about 7000 km on roads around the Santa Ynez Mountains to document the spatial wind and aerosol variability during Sundowner Wind days and during undisturbed days. Data examples and comparisons with 1-km numerical simulations using the Weather Research and Forecasting (WRF) model will be discussed.

The characterization of local wind fields, turbulence and eddies around the High Altitude Research Station Jungfraujoch, located in the Swiss Alps, is of large interest for the atmospheric research performed at the site, because some of the atmospheric in-situ measurements are strongly influenced by these local phenomena. In a pilot project performed in summer and autumn 2022, movies of visualized surface eddies and surface heat transfer around the Jungfraujoch were recorded with help of a high-resolution thermal camera. Time series of thermal images were decomposed by subtracting the average images and the trend deviation of the image average from the total average (Vogt et al., 2008, Hilland et al., 2022). This decomposition delivers temperature fluctuations at the surface, caused by the sensible heat flux in the uppermost layer of the surface. These fluctuations are a function of the thermal admittance and the roughness of the surface, and of the surface wind speed. The time sequence of the decomposed images thus delivers a proxy for the surface wind movements and provide a tool to visualize local turbulence and wind fields at the surface. The first experiments at Jungfraujoch revealed local upwind movement along south-oriented mountain slopes during daytime, as well as night-time valley wind movements along slopes and above glaciers. We aim to put these results in context with other measurements performed at the Jungfraujoch in collaboration with other research groups doing research at the site, and to extend these measurements in upcoming field campaigns related to mountain meteorology.

Within the experimental project of meteorological monitoring in the Regional Forest of Pian Cansiglio (mountain Regions of Veneto and Friuli Venezia Giulia – Italy - https://www.piancansigliometeowebcam.it), three professional sensors with LoRaWAN technology manufactured by Swiss Company Decentlab GmbH have been installed in 2020 and 2021, suitable for the chosen locations and the peculiar climatic conditions (I Bech – 983m a.s.l., Valmenera – 903m a.s.l. and Rif. Carlo e Massimo Semenza – 2.020m a.s.l.). As further level of development in the IoT segment, a self-built electronic board (called "LoRa Weather board") was implemented by Dr. Mauro Girotto, based on LoRaWAN technology, for the acquisition of meteorological/environmental quantities, and equipped with a specific ultrasonic sensor for detecting snow level. The results of such research were presented in Paris at WMO-TEC02022 conference in October 2022.

The Mediterranean alpine zone is a unique environment that offers vital ecosystem services to people and crucial habitat to high elevation biodiversity, in a rapidly changing climate. However, despite their importance, due to their remote location the meteorology of these regions and the hydrology of alpine lakes - a strong climate change indicator for glacierless mountains - remain widely understudied in the Mediterranean basin. Although well developed networks exist for monitoring the climate at lower elevations, measurements of the atmospheric conditions of the alpine zone are scarce and sparsely distributed, and hydrological time-series datasets are nonexistent. Such gaps create critical shortcomings in identifying trajectories of change and the way these affect the ecosystem, thereby constraining the implementation of effective conservation measures. Launched in 2022, the LiMnADs Project - Limnological Monitoring & Alpine Datasets - has developed a holistic environmental monitoring approach to better understand the meteorological, hydrological and ecosystem processes that occur in the alpine zone, as well as the ways these are being affected by human activities and climate change. Using Mount Tymfi, Greece, as a pilot site, the monitoring goals of the project are achieved through measurements from autonomous stations installed on site. Meteorological conditions are monitored through a Davis Vantage Pro 2 weather station measuring atmospheric temperature, wind speed and direction, precipitation, humidity and barometric pressure at an hourly rate. Hydrological conditions are monitored through a self-developed underwater station that records water temperature, pressure, conductivity, pH and dissolved oxygen at a daily rate. In the first few months of field observations, the LiMnADs Project has already provided new insight into the climate of Mount Tymfi’s alpine zone, with some of the highest wind gusts ever recorded in Greece and the first ever time-series dataset of the hydrological conditions of a Greek alpine lake. Both monitoring stations offer low-cost yet robust options, capable of significantly improving our current understanding of climate change trajectories in the Mediterranean alpine zone. Large-scale monitoring of the region will enable the identification of future risks and evidence-based decision making to limit the environmental, economic and societal impacts that these changes might lead to in the future.

Cold air pool formation in topographic depressions have often been studied in an international context for their value in evaluating land surface interactions, surface net radiation, and fluid dynamics. The closed depression that contains Sämtisersee in the Alpstein massif in north-eastern Switzerland is one of the deepest in Switzerland. Three unique factors affect the dynamics of this depression’s cold air pool: i) The depression’s catchment area (13.3 km²) and topographic complexity, ii) the position downstream of the Rhine valley, and iii) the foehn frequency. Combining in-situ measurements, satellite data, as well as high resolution numerical modeling, a multi-faceted approach is taken to understand the cold air pool dynamics at Sämtisersee. Since April 2016, temperature measurements have been taken in this depression. The minimum of -33.4°C measured so far shows the potential for low temperatures. Yet, the measurement period shows frequent and large temperature variations as well as persistent phases with obvious foehn influence. In the winter of 2022/2023, a temporary wind mast with additional sensors was added. A total of 12 additional sensors were installed at different heights along a transect on both sides of the valley, attempting to record seiches of the cold air pool. For several different episodes during the winter season, large eddy simulations at a resolution of down to 4m have been carried out with the PALM model. The COSMO-1E model from MeteoSwiss was used as a dynamic driver. To investigate the cold pool formation and dissolving process, different sensitivity studies were performed, including considerations concerning i) circular versus dynamic boundary conditions, ii) presence of an inversion layer during model initialization and iii) atmospheric stability requirements. Together with the in-situ measurements, visible and infrared satellite data were used to validate the model output of inversion depth and surface temperature variations. This was conducted first with validation and calibration of thermal infrared radiances with surface temperature measurements. In addition, visible data were used to confirm different indicators of inversion levels and surface differential heating. This study gains deeper insight into the formation process of cold pools in complex terrain. We postulate that the refinement of modeling techniques that arise from this work can be applied to short-term weather forecasting in alpine regions where cool pool development is known to produce hazards, such as freezing fog, icy road surfaces, and locally enhanced snowfall or freezing rain.

The Alpine area is one of the most vulnerable and sensitive regions to the continuous warming of climate and it is considered an important hotspot of climate change. In particular, climate change is expected to exert a strong influence on all components of the hydrological cycle, including river regimes, with consequent effects on the services offered by the freshwater ecosystem, as well as on water availability for users, thus affecting several socio-economic sectors. Several observational products of key climate variables are available to the scientific community and have been widely used to evaluate the extent of the ongoing effects of climate change in mountain regions. However, most products suffer from some limitations: for example, some have not been updated to recent decades, or their spatial coverage is quite limited, especially in view of reliably assessing trends at higher elevations. Therefore, more efforts must be dedicated to produce new harmonised and high-resolution products able to permit more robust assessments of climate change in mountain regions. Even though the Alpine region is densely covered with a high number of in-situ weather stations, the collection and management of such data for the whole Alpine area is a challenging task due to strong fragmentation and diversity of data sources. We present here a new observational dataset gathering in-situ daily measurements of meteo-climatic variables provided by a variety of meteorological and hydrological services within the Extended Alpine Area (EAR) for the period ranging from 1991 to 2020. The observational network consists of more than 9000 in-situ weather stations, and its high density allows for an extended and homogeneous coverage both in space and elevation. The data collected, after a preliminary phase of pre-processing, have been subjected to a quality control aimed at checking internal, temporal, and spatial consistency of time series, addressing the problem of outlier removal. In addition, different techniques were exploited to assess data homogeneity. A preliminary climatological analysis in terms of trends and extremes is carried out on homogenised time series, making use of the most common climate indices and statistics. The dataset represents a powerful tool for better understanding Alpine climate changes over the last decades and improving the reliability of future scenarios.

The Berchtesgaden National Park located in the Bavarian Alps in Southeastern Germany is a highly interesting study field due to its extreme topography (~ 600 - 2700 m.a.s.l.) and locally most variable climate conditions. Due to the research objective of the national park and the cooperation with the German Meteorological Service (DWD) we find a dense measurement infrastructure compared to other alpine regions. Ground measurements of temperature, relative humidity, precipitation and wind conducted by both partners go back as long as the 1980s with stations in different altitudes covering the complex terrain. Altogether, data of almost 100 stations is available, albeit with different record lengths (some only have short records of a few years). However, up to now, the datasets of the two institutions have only been used separately and lack a stringent quality control which takes into account the challenges of measurements in complex terrain. New efforts are now underway to create a quality controlled, homogenized dataset for the Berchtesgaden National Park which will be openly available for the research community. Additionally, a gridding of the station data is planned which is of high importance to cover complex high mountain areas as adequately as less complex regions The efforts also include the assessment of uncertainties, both of the measurement devices and of the digitization of thermohygrograph charts, as well as the compilation of metadata. Data from the operational Networks of the German and Austrian Meteorological Services, as well as other available station networks in the region are included in the processing of data. This contribution will introduce this unique dataset which in future can be used as common historical reference e.g. for climate change studies, as boundary conditions for impact models or for the validation of climate models in complex terrain. It will also highlight some of the challenges of measurements in complex terrain and their data processing.

The CLIM-PY project (POCTEFA 2014-2020, Ref. AUEP002-AND / 2015) aimed to develop a cross-border database of temperature, precipitation, and snow depth for the regions of France, Spain, and Andorra. The database incorporated quality control and homogeneity of the instrumental information available from the meteorological services of each country. Specially, the study of snow depth has brought together data from manual and automatic stations, managed by meteorological services and organizations throughout the Pyrenees. The data was collected from stations located between 230m and 2500m altitude and was modelled using the Crocus model to fill gaps and cover the early and late seasons of ski resorts. The data covers a period of 40 years with an average altitude of 1700m, which is where most of the ski resorts in the Pyrenees are concentrated. The primary focus of the study was to characterise the climatic trends of the snow variable. The preliminary results characterised the snow depth from December to April in terms of severity and intensity, specifically by determining the number of days the snow depth was above the P50 and the excess amount. This classification has been completed with an analysis of the evolution over time of the most classic indicators. The objective of this study is to respond to the need for characterizing the evolution of snow cover for the management of snow as a resource in other sectors such as hydrology, energy, and natural hazards. The results of this study have important implications for the sustainable management of snow resources in the Pyrenees region.

This (projected) study explores the changing climate of the Hex River mountains, a prominent range in the south western Cape in South Africa, over the last thirty years (1992-2022). This range is notable for the historical snow cover and related snow sports, plus its steep gradients. The purpose of this study is to garner the observations of a mountain user group in South Africa regarding the impacts of global warming on the range, in particular the high altitude zone between c.1700 and 2249masl, where snow, of varying texture and hardness, occurs during the winter. The literature that has been published on the range’s climate indicates severe storms, and related danger, during the winter months as well as indications that the climate is changing. Accounts of historical storm events will be derived from the journals of the mountain user group. It also appears from previous research that geomorphic processes are increasing due to unexpected summer rainstorms, with debris flow and rockfall resulting. Fire frequency and water shortage appears to be increasing in the summer months. The methodology will comprise a questionnaire which will include a map of the range and information on particular topoclimates of the range to aid in the responses. An appeal will be sent to members of the mountain user group in the Western Cape; respondents will be selected according to their experience of, and frequency of, multi-day traverses of the range. Those respondents with an education in atmosphere science will be emphasized in the text. The expected results will indicate that water supply in summer is becoming more marginal. Other expected answers are that there are differences in climate change between the windward and leeward sides, and south- and north-facing slopes of the range. In addition, climate change appears to be changing altitudinal zones, especially of the temporary cryosphere that exists during the winter months. Possible recommendations include amending routes to avoid eroded sections and possible rockfall for people traversing the range.

The Uttarakhand Himalaya is highly prone to geo-hydrological disasters – flash floods, debris flows, landslides, mass movements, and rock falls. Cloudbursts and glacier bursts generally triggered these disasters, which are very active and frequent in the Uttarakhand Himalaya and occurred mainly during the monsoon season. This study examines the geo-hydrological disasters in the Uttarakhand Himalaya, which occurred from July 1 to September 10, 2022. Further, the study assesses the magnitude of the disaster and maps the disaster hotspot areas. Both qualitative and quantitative approaches were used to conduct this study. Data on geo-hydrological hazards that occurred during the monsoon season were gathered on daily basis from the Times of India, Dehradun edition. Secondly, an empirical study of the Bandal and Song River valleys was conducted. These valleys were severely hit by cloudburst-triggered flash floods and debris flows. Household-level survey of damaged caused by huge flash floods and debris flows in three villages of Bandal valley was carried out. The data were analyzed and mapped and the Uttarakhand Himalaya was divided into disaster hotspot zones. This study recommends that the construction of settlements should be banned in the most disaster-affected areas, along the river valleys, and from fragile slopes. Nature-based eco-disaster risk reduction can reduce the impact of geo-hydrological disasters.

Future changes in river discharge driven by climate change are expected to affect various water-resource sectors. In this study, we investigated the influence of climate change on streamflow in a heavy snowfall area of mountainous central Japan using hydrological model simulations driven by climate projections obtained from the d4PDF database. We projected an increase in snowmelt discharge during winter and a decrease in spring, along with a general decrease in water resources and an increase in the frequency of annual maximum daily discharge during winter because of increasing future snowmelt. Self-organizing maps (SOMs) were then applied using atmospheric data to study the linkage between streamflow and weather regime patterns (WPs) in future and present climate scenarios. The SOM analysis suggested that the impacts of climate change on streamflow varied by WP. The increase in future winter discharge was due to the strengthening of impacts of certain WPs, causing snowmelt. However, the decrease during spring could be due to changes in the predominant discharge-related WPs resulting from a decreasing snowpack. The obtained results can be useful information for considering adaptation strategies for sustainable management of water resources in heavy snowfall areas that must meet both economic and environmental demands.

Rain-on-Snow (ROS) events can cause severe snowmelt hazards such as river flooding, avalanches, and landslides that have significant impacts on various sectors. The influence of climate change on the frequency of ROS events in Japan was investigated using climate projections obtained from the Database for Policy Decision making for Future climate change (d4PDF). The projected future climate in the regional model simulations showed an increase in the ROS events over the mountainous areas in Hokuriku (Sea of Japan side of Central Japan) and Hokkaido (Northern Japan) regions, where a higher amount of snowfall will still occur in the future. Characteristics of ROS events such as rainfall, snowmelt, and related runoff were also enhanced in these regions. Self-organizing maps (SOMs) were applied using the surface atmospheric circulation data to determine the dominant ROS-related weather patterns (WPs) in the present and future climate. The SOMs showed that some WPs had a significant effect on the cause of the ROS events. The differences in the impacts of climate change between the WPs were evaluated to understand the future changes in runoff and snowmelt associated with ROS events. The SOM analysis suggests that the increase in the occurrence of ROS events and the resultant enhancement in their characteristics in the future-climate projection can be attributed to the changes in the dominant ROS-related WPs (from cyclonic to cold-surge type) corresponding to variations in the freezing point line. These findings can inform water hazard and water resource management plans that aim to withstand regional climate change.

The CARRA dataset of high-resolution dynamic downscaling of flow over Iceland reveals all main features of orographic flow. These patterns are explored systematically for different large scale flow conditions. The data reveals a multitude of interesting elements such as variable nature of orographically sheltered regions: some are best sheltered in the summer, while others are best sheltered in the winter. In general, there is extremely high spatial variability, not only in instantanous wind speed, but also in mean winds for pre-defined large scale conditions.

Mountains are playing a major role in shaping the weather and climate of the world. In many cases they are experiencing more rapid changes in temperature than their counterparts at lower elevations. These changes are affecting ecosystems, the water cycle, the mountain cryosphere, and many other dependent systems that are often connected to each other. Such connections occur via a series of process interactions and feedback mechanisms, often involving surface-atmosphere exchange processes. The scientific understanding of mountain climates, their natural fluctuations and their response to global climate change is hence very important. This understanding, however, is still quite limited for a series of reasons including sparse observational networks, the intrinsic complexity of topography-related exchange processes, the coarse resolution of current climate models (not yet able to properly represent the complex mountainous orography) as well as the role of internal variability versus the role of external forcing especially for local scales. To improve on this situation, the TEAMx programme (http://www.teamx-programme.org/) encompasses a working group on Mountain Climate (http://www.teamx-programme.org/workgroups/mountain_climate/). Initially focusing on the European Alps, the primary goal of this group is to improve the scientific understanding of transport and mixing processes by which mountains are shaping regional climates and their spatial and temporal variability. Filling existing research and knowledge gaps will enable more confident projections of future mountain climates and will hence improve mitigation and adaptation strategies for mountain ecosystems and societies. The working group will also ensure an appropriate consideration of climatological aspects in the pan-Alpine TEAMx observational campaign that is planned for 2024/2025 and will seek to transfer insights obtained during the one-year campaign to climatological timescales. The present contribution will provide an overview of the scope and the most recent activities of the working group and its placement in the larger TEAMx framework. The group itself is open for participation from further interested colleagues: the main authors can be contacted any time for this purpose.

The European Alps are more strongly affected by global greenhouse gas emissions than other regions or environments. In this highly sensitive region, the effects of climate change are clearly visible in all seasons. For example, heat is experienced at ever higher altitudes; the rising temperatures also lead to less snowfall and earlier melting of snow cover. As a consequence, glacier volume losses accelerate. These changes do not stop at national borders and affect the entire Alpine region equally. Therefore, information and analyses on the climate in this unique ecosystem are all the more important. In November 2022, the national weather services of Germany, Austria and Switzerland launched a new joint publication series entitled "Alpenklima” in German, respectively “Climat des Alpes” in French and “Clima delle Alpi” in Italian. Alpenklima is produced twice a year for the months of May to October (summer half-year) and for the period November to April (winter half-year). It shows the current state of the climate in the Alpine region of the three countries and puts it into context of the long-term climate development. In addition, selected special climatological events of the half-year are highlighted and presented in more detail. The poster introduces this new report series.

Trace gas simulations and inverse modelling on the regional scale require an accurate representation of atmospheric boundary layer (ABL) processes. Thus, complex terrain, such as the Swiss Midlands, poses challenges like uncertainties in local turbulent transport, advection, and diffusion. Horizontal transport and vertical mixing in the ABL induced by local circulations directly impacts the vertical profiles of trace gases emitted at the surface. A bias in these processes may introduce significant errors in the estimate of trace gas concentrations, especially for the accumulation of greenhouse gases (GHG) during nighttime stable conditions. Therefore, in the present work, high-resolution simulations using Cloud Model 1 (CM1) in Large Eddy Simulation (LES) configuration and with idealized topography, representative of the rolling terrain around the tall tower at Beromünster, are performed. This study contributes to an improved understanding of the relevant storage and transport processes of accumulation of passive tracer in nocturnal cold pools, and their morning depletion, along with sensitivities to initial atmospheric stratifications and upper-level wind. Together with the sensitivity experiments, along-valley averaged, and instantaneous model outputs will be presented.

ALPTHERM as a tool for assessing convection for air sports is old. First ideas about the consequences of the volume effects in Alpine valleys were presented at the ICAM 1982 in Berchtesgaden. Later (1993), a first version of the algorithm was installed at the German, and later at the Swiss and Austrian Weather Services for supporting forecasts for soaring flight. 30 years later, where modified versions under different names such as Toptherm and Regtherm are still in operational service, a completely new version is promising more than just forecasts for air sports. Since it is now fully three-dimensional and is interacting with the wind field, the possible applications have increased. When in 1993, the volume effects of complex terrain with a statistical representation of sunny slopes (applied to a certain catchment) were the important aspect of the basically one-dimensional approach, this is less of importance today, because LAM such as COSMO or ICON are incorporating these processes already. However, operational LAM are still limited by the steepness of the orography, have other priorities, and need big computing power. AlpTherm_3d is still using some of the original concepts, allowing different options for the initial and boundary conditions (soundings, GFS, ICON-D2, and surface stations in any combination). The horizontal grid is adjusted to ICON-D2 (0.02°; interpolated for other sources), but the layers are on constant altitudes. Below these 3-d-cells is the DTM (e.g. SRTM) with a resolution of less than 100 m, with several options for the surface properties (e.g. albedo from MODIS). “Heuristic” means, that the turbulent fluxes cannot be resolved explicitly. However, results from LES, observations and experience are used to parameterise the shortcuts. Despite these shortcuts, the algorithm is conserving mass (including water and optional trace gases) and energy. For the interaction of thermals with the surrounding atmosphere, the exchange of momentum is included. “Lagrangian” means, that pockets of air cooled or heated on the surface pixels are proceeding as a katabatic or anabatic flow or leaving the surface as a thermal plume. The resulting mass imbalances are then compensated by additional horizontal flow, subsidence, and lifting, where the split between the three is a major challenge. AlpTherm_3d can be applied to any region where above-mentioned input data is available. The scalable program, running on a PC, is suitable for the personal use including education and numerical experiments (what, if …), including regional climate studies.

The horizontal grid spacing of numerical weather prediction (NWP) models keeps decreasing towards the hectometric range. However, although topography, land-use, and other static parameters might be better resolved than at the kilometric range, the performance of physical parameterizations also has to be evaluated and assessed. Truly complex, mountainous terrain still poses a challenge for common bounday-layer parameterizations in NWP models due to missing 3D contributions. Furthermore, the turbulence grey zone, where simulated turbulence is both parameterized and resolved, is relevant at sub-kilometric resolutions. A typical phenomenon dominated by boundary-layer processes is the well-researched thermally-induced valley wind system in mountainous terrain. In this study, we perform nested limited-area simulations with the state-of-the-art NWP model ICON (Icosahedral Nonhydrostatic Model) across horizontal grid spacings (1km, 500m, 250m, 125m) in the Inn Valley, Austria for valley wind days. The first simulation set uses the standard 1D turbulence parameterization (Mellor-Yamada-based) in ICON, while the second simulation set is run with a 3D Smagorinsky closure. We evaluate the model with turbulence observations from the CROSSINN campaign providing, among others, measurements from LIDAR systems, radiosondes, and turbulence eddy-covariance towers from August to October 2019. With this data pool, a thorough evaluation of the model for a valley wind case studies across scales is possible. We assess whether increasing the horizontal resolution automatically improves the representation of the thermally-induced circulation, surface exchange, and boundary-layer processes in the valley. Furthermore, we test the model's turbulence schemes across the grey zone towards large-eddy simulations and identify the horizontal resolution at which the 3D turbulence scheme starts to add value over the 1D scheme. This allows us to identify key challenges for turbulence parameterizations at the hectometric range over complex terrain and suggest possible improvements.

In fair weather conditions, thermally driven local winds often dominate the wind climatology in deep Alpine valleys resulting in a unique wind climatology for any given valley. The accurate forecasting of these local wind systems is challenging, as they are the result of complex and multi-scale interactions. Even more so, if the aim is an accurate forecast of the winds from the near-surface to the free atmosphere, which can be considered a prerequisite for the accurate prediction of mountain weather. This study investigates the skill of the ICON model at 1.1 km grid spacing and higher resolution in simulating the thermally driven local winds in the Swiss Alps for a month-long period in September 2016. The study combines the evaluation of the surface winds in several Alpine valleys with a more detailed evaluation of the wind evolution for a particular location in the Swiss Rhone valley, the town of Sion. The former is based on a comparison with observations from the operational measurement network of MeteoSwiss, while the latter uses data from a wind profiler stationed at Sion airport.

The response of the lower atmosphere to resolved versus parametrized orographic drag over moderately complex terrain is investigated. Typically, larger terrain scales may trigger propagating gravity waves and generate flow blocking, while the smaller scales (smaller than 5 km) may modify the turbulent atmospheric boundary layer leading to turbulent orographic form drag (TOFD). We perform high-resolution numerical simulations to evaluate the ability of a TOFD parametrization to reproduce the impact of small-scale orographic features on the flow over moderately complex terrain. The tool selected to perform the simulations is the Icosahedral Nonhydrostatic (ICON) numerical model, a unified modelling system for global numerical weather prediction (NWP) and climate studies. In the present study, the model is used in its limited-area and Large Eddy Simulation modes. In the TOFD parametrization (NWP), the surface stress and the vertical distribution of the resulting momentum flux are formulated in terms of the orography spectrum, meaning that it only depends on the statistical properties of the orography in the box (more specifically, only on the variance of the sub-grid scale orography). First, the simulations using different grid spacings, from the km scale to the 100 m scale, are evaluated with respect to data collected during the intensive observational period (IOP) of the Perdigão field experiment. The km-scale simulations in NWP mode are run continuously for the complete 49-day IOP using ERA5 data for initial and boundary conditions. The large-eddy simulations, at O(100 m) grid spacing, are run for selected periods nested into the NWP runs. The impact of the resolved orography on the wind field is derived by considering the difference between the high-resolution experiments with high (130 m) and the experiment with low (1 km) resolution orography. This is then compared with the impact of parametrized TOFD, deduced from NWP-resolution experiments with and without TOFD parametrization. The experiments focus on a moderately complex terrain to the north of the Perdigão site, the Serra da Estrela mountain range. Preliminary results show an important contribution of the TOFD parametrization (in terms of the accumulate TOFD tendency of wind) when the wind flow is aligned perpendicular to the mountain range, which is frequently observed during the second phase of the IOP characterized by weak synoptic conditions. During such periods, the simulation using the TOFD parametrization tends to be closer to the high resolution simulation, suggesting that the TOFD parametrization has a net positive effect on the simulations.

In the framework of the TEAMx initiative, a multi-model intercomparison study is planned with the goal of quantitatively evaluating the ability of numerical weather prediction models to reproduce the characteristics of the boundary layer over complex terrain. Among other experiments, a model intercomparison study focusing on the cold-air pool (CAP) evolution in the Austrian Inn Valley is designed considering several models including the Icosahedral Nonhydrostatic Model (ICON), Mesoscale Nonhydrostatic Model (Meso-Nh), the Unified Model (UM), and the Weather Research and Forecasting mode (WRF). The case study selected corresponds to a persistent CAP event observed in the Inn valley between 15 and 16 October 2017, which allows to investigate the complete cycle of the CAP from its formation to its breakup. This case relates to an undisturbed period observed during the PIANO (Penetration and Interruption of Alpine Foehn) field campaign. In the framework of such an experiment, we test the performance of our new two-energy turbulence scheme, implemented into the ICON model (ICON-2TE). The scheme parametrizes turbulence and boundary layer clouds in a unified framework enabling it to be more consistent and continuous in time and space than the classical combination of separate turbulence and (shallow) convection schemes. In the past, the two-energy scheme has been tested on several idealized cases (GABLS1, DYCOMS-II, BOMEX and ARM) and a realistic case over flat terrain (FESSTVaL field experiment) showing a good performance. In the present work, taking advance of the TEAMx initiative, we move the setup to very complex terrain in which the effect of the extreme orographic variation is tested in the performance of the new two energy scheme. The simulations have been run in NWP mode at 1 km horizontal grid spacing, with the domain centered around Innsbruck. IFS operational analysis is used for initial conditions and HRES forecast with a temporal resolution of 1 h for the boundary conditions. The simulations last for the whole persistent CAP event. The model is first evaluated using data from the PIANO field experiment, then, in a second phase the performance of ICON-2TE is tested with respect to the standard ICON model with a focus on the model skill to simulate the CAP processes over complex terrain.

The formation of stably stratified nocturnal Cold Air Pools (CAPs) is a frequently observed phenomenon in alpine valleys. Accurate forecasting of these CAPs is important because they may detoriate air quality due to a significant reduction of pollution dispersion, and they may promote high-impact weather such as freezing rain. The CAP episode from October 15-16, 2017, in the Inn Valley (Austria) has been selected for a model intercomparison study in the framework of the TEAMx programme. As this case was part of the Intensive Observational Period 1 during the Penetration and Interuption of Alpine Foehn (PIANO) field campaign, high abundance of observational data allows for a thorough analysis of the horizontal and vertical structure of the CAP. The model intercomparison study comprises simulations at 1km horizontal grid spacing of a variety of models: Icosahedral Nonhydrostatic Model (ICON), Non-hydrostatic Mesoscale Atmospheric Model (Meso-Nh), Unified Model (MetUM), Weather Research and Forecasting Model (WRF). The presented work aims to provide an in-depth analysis of the processes driving the CAP life cycle and focuses on a process-based validation of the simulations performed using ICON. Observational data reveals that the strength of this CAP episode resembles to a near-surface air temperature decrease of approximately 12⁰ C over the course of the night. The spatial expansion of the CAP is limited to the south by advection of warmer air by the nocturnal downvalley flow from the nearby Wipp Valley into the city of Innsbruck. In the vertical direction, the CAP is bounded by a topping inversion at about 1000 m above sea level. First numerical results show that ICON exhibits a significant warm bias in the amplitude of the modeled near-surface temperature. A maximum bias is reached in the morning, shortly before the CAP dissipates. The timing of the break up is well represented by the model. For the vertical structure, the model captures the height of the topping inversion well, while the strength of the inversion is underestimated.

More than 50% of lakes in the world are distributed in mountainous region. The topography around the mountainous lake is complex and diverse, which leads to a unique local circulation. This meteorological phenomenon results from the interaction between lake-land breeze and mountain-valley breeze circulations. Regional energy exchange relies on this mechanism, which is also responsible for material exchange. Based on meteorological and turbulence fluxes data from an eddy covariance observation site at the Erhai Lake in the Dali Basin, southwest China, lake effects on local circulations and their impacts on local energy and carbon dioxide exchange were investigated. The results showed that the lake had great impact on local circulation and atmospheric boundary layer in mountainous area. Due to larger heat capacity and emissivity, smaller surface roughness and albedo, energy exchange between the lake and the atmosphere was different from the surrounding land. The lake enlarged thermal contrast and increased local wind speed in the basin. Cooling effect of the lake was 2~3 ℃ during daytime. Warming effect of the lake was about 2 ℃ in the evening. During daytime, the lake reduced atmospheric boundary layer height and increased specific humidity, whereas at night, it increased atmospheric boundary layer height and decreased specific humidity. The lake in mountainous area promoted latent heat mixing, but suppressed carbon dioxide exchange.

motions from raw time series. Common filter times range from 1 min under stable conditions to 30 min in convective situations. In this presentation, we are going to evaluate the performance of different filter times for stable conditions over strongly complex terrain. Spectral analyses are performed to identify the energy gap, from which a non-constant filter time is derived, which varies with time depending on the mean flow parameters. Eddy-covariance data from five i-Box stations in the Inn Valley, Austria, are analyzed for stable conditions. The i-Box (Innsbruck Box) is a long-term measurement platform, which was designed to study boundary-layer processes over mountainous terrain. The five stations are located within an approximately 6.5-km long section of the valley, which is about 2-3 km wide. One site is located at the almost flat valley floor and two sites each on the north-facing and south-facing sidewall, respectively. (Co)spectra are calculated for different variables using both Fourier analysis and multi-resolution flux decomposition, from which the gap scale is identified. Using the correlation between the identified gap scale and mean flow parameters, a time-varying filter time is defined as a function of the mean wind speed and stability parameter z/L. The performance of the time-varying filter time in separating turbulent and non-turbulent motions is compared to constant filter times ranging from 0.5 to 30 min. Results show that, at the i-Box sites, the time-varying filter time does not outperform a well-chosen constant filter time.

Exchanges of mass and energy between a subalpine coniferous forest and the atmosphere have been continuously monitored since few decades at Renon (Bolzano, Italy) applying the eddy covariance (EC) technique. The station is part of the Integrated Carbon Observation System (ICOS) EU Research Infrastructure. The area surrounding the site is characterized by complex topography, with a mean slope angle of about 11° and a Southward aspect. In this study, we focused on the analysis of turbulent energy fluxes (sensible and latent heat) and the energy budget closure of the forest during a period of about three months (August-October 2021), when a below-canopy EC system was additionally deployed to better understand the dynamics of turbulent exchanges. The energy balance closure was assessed for periods characterized by distinct wind circulation patterns (thermally-driven slope winds vs. synoptic winds) and turbulent energy fluxes were processed applying different coordinate rotation methods (double rotation and planar fit). We found significant differences in the magnitude of sensible and latent heat fluxes computed with double rotation or planar fit. These differences were more marked during periods characterized by slope winds, suggesting a connection with local advection performed by these winds.

Vertical temperature gradients can be empirically determined using a bulk approach which assumes that the temperature difference and gradient between two heights is representative for the layer between the two temperature measurements. Alternatively, different functions can be used to fit point observations. From the first derivative of those functions the vertical temperature gradient can be derived. A new approach is to use distributed temperature sensing (DTS) with a spatial and temporal resolution of 0.25m and 1s. The spatially continuous temperature measurements can be used to either compute discrete gradients between neighboring measurement points or in a similar fashion as the point observation by fitting different functions to the data. We use the valley floor site VF0 of the Innsbruck box (i-Box) near Kolsass, Inn Valley, with four temperature observations up to a height of 17m. In addition a DTS array was deployed on the tower for about four weeks in July 2022 as part of the TEAMx-PC22 campaign. The main goal was to test and compare different empirical representations of the vertical temperature gradient and their impact on similarity relations according to the Monin Obukhov Similarity Theory (MOST). According to MOST the dimensionless gradient of the potential temperature and its relation to stability should be height independent and follow empirically verified universal functions. Since the i-Box site is located in roughly flat terrain within the Alps, we can also test if MOST is applicable over mostly flat terrain surrounded by mountainous terrain.

Slope winds are part of the system of thermally driven circulations typically developing over complex terrain under unperturbed synoptic weather situations. They flow up-slope during daytime and down-slope during nighttime, due to surface heating and cooling, respectively. Our understanding of such circulations still suffers from some gaps, especially concerning the diurnal component, due to the additional complexity determined by convection. In particular, the dispersion and diffusion properties within the boundary layer associated with slope winds are still poorly understood, also due to a lack of experimental evidence. Here we present an analysis of the mixing processes in the surface boundary layer in which down and upslope winds develop using the available datasets from the experimental campaigns of MATERHORN (Fernando et al, 2015), METCRAX (Whiteman et al, 2008) and MAP-RIVIERA (Rotach et al, 2004). Case studies with ideal conditions for the observation of pure thermally driven circulations are selected from each campaign and the slope-normal structures of the heat and momentum fluxes, and turbulent kinetic energy are investigated. The eddy coefficients for heat and momentum diffusivity are found and presented together with their observed vertical structure. Existing formulations for the vertical structure are tested on the basis of their ability to reproduce the observed values and similarity scaling is proposed. References Fernando, H. J. S., et al. "The MATERHORN: Unraveling the intricacies of mountain weather." Bull. of the Amer. Met. Soc. 96.11 (2015): 1945-1967. Whiteman, C. David, et al. "METCRAX 2006: Meteorological experiments in arizona's meteor crater." Bull. of the Amer. Met. Soc. 89.11 (2008): 1665-1680. Rotach, Mathias W., et al. "Turbulence structure and exchange processes in an Alpine Valley: The Riviera project." Bull. of the Amer. Met. Soc. 85.9 (2004): 1367-1386.

Thermally-driven slope winds are daily-periodic mesoscale atmospheric circulations that occur in mountain regions because of the daytime heating and nighttime cooling of valleys and slopes. Known to mostly occur on days with weak synoptic forcing and under clear-sky conditions, the wind blows up valleys and slopes during the daytime, and in the opposite direction during nighttime. A better representation of slope winds can improve our understanding of the soil-atmosphere turbulent exchange processes over complex terrain, as well as the along-slope transport of species (pollens, pollutants, pesticides), as well as water vapor (relevant for the development of convection). A milestone in the study of the equations governing slope winds is the model of Prandtl (1942) for the steady-state case. Then, time-dependent solutions were proposed by Defant (1949) and later corrected by Zardi and Serafin (2015). The latter model provides slope-normal profiles of temperature and along-slope wind velocity as a response to a sinusoidal forcing representing the surface temperature. The profiles exhibit sinusoidal oscillations at every distance from the surface, although with different phase lags under different regimes, determined by different combinations of slope angle and stability of the unperturbed ambient atmosphere. Anyway, being symmetrical, they fail in explaining the differences in timing, magnitude, and height of the observed wind speed peak velocity between daytime and nighttime regimes. In the present work, solutions from Zardi and Serafin (2015) are extended to include a more realistic daily-periodic surface forcing. The daily cycle of surface temperature is derived from the surface energy budget. In particular, the 24-hour periodic radiative input is obtained by means of a Fourier series expansion of incoming solar radiation, accounting for latitude, day of the year, slope angle, exposition, and atmospheric transmittance. The computation of the sensible and ground heat fluxes, and of the longwave radiative balance from the temperature profiles in the atmosphere and in the ground allows the derivation of suitable harmonics describing the daily cycle of surface temperature, forcing the onset and characteristics of slope winds. References: • Prandtl L. 1942. Führer durch die Strömungslehre, Chapter 5. Vieweg und Sohn: Braunschweig, Germany. • Defant F. 1949. Zur Theorie der Hangwinde, nebst Bemerkungen zur Theorie der Berg- und Talwinde. Arch. Meteorol. Geophys. Bioklimatol. A 1: 421–450 • Zardi D., Serafin S. 2015. An analytic solution for time‐periodic thermally driven slope flows. Q. J. R. Meteorol. Soc., 141, 1968–1974

High resolution vertical soundings are performed in Rivolto (UD) in north-eastern Italy at least twice a day (00 and 12 UTC). This study analyzes the average vertical profile of potential temperature and equivalent potential temperature in the PBL, clustering the profiles according to several conditions to investigate the average physical processes developing in those situations. In particular, the average vertical profiles are studied for different hours of the day, seasons and thermodynamical conditions. The focus of the study is on pressure and temperature 6-hour tendencies at the surface (δT0 and δp0). A theoretical model is developed to reproduce the variation in 6 hours of the pressure at the ground considering only the initial profile and some information about the following profile. The model has a good performance and works better if the integration is applied considering only the lowest layers of the PBL, rather than all along the available vertical measurements. Preliminary results show that the average profile with negative product of the tendencies δT0∙δp0 is associated with higher potential temperatures.

A number of national weather services transition from the COSMO model to ICON. While the German weather service, DWD, is already successfully running operational ICON forecasts, the Swiss Federal Office of Meteorology and Climatology, MeteoSwiss, is still in the development process. MeteoSwiss employs a model configuration based on the DWD setup with a couple of adaptations targeting the mostly mountainous terrain in the limited-area model domain. This contribution presents model developments undertaken to improve the forecast skill of ICON at 1km horizontal grid spacing over the Alpine region: Implementation of topographic shading, sensitivity experiments testing various degrees of smoothing of the topography as well as the vertical coordinate surfaces, and increased vertical resolution. Attention is given to both, impact on specific case studies as well as verification scores for longer periods.

The valley wind system belongs to the most characteristic circulations of the atmospheric boundary layer in mountainous terrain. It dominates surface winds at the valley bottom, contributes to the vertical air mass exchange with the free troposphere and the horizontal air mass exchange with neighboring plains and valleys. Accurate prediction of the valley wind system is therefore crucial for forecasting convection and thunderstorms. We assess the ability of the ICON model at varying resolutions (1-10 km grid spacing) to resolve the valley wind system in the Inn Valley, Austria by comparing the model to measurements from the CROSSINN campaign in 2019 for a characteristic valley wind day. The three-dimensional observations allow us to validate valley wind simulations beyond classical statistical validation techniques and to further investigate the underlying processes (process-based evaluation). At 1km horizontal grid spacing, the ICON model can simulate the daytime up-valley flow well, including its strength, timing, and vertical structure (for the Inn Valley with ridge-to-ridge distance of 10 km or 10 dx). However, the ICON model significantly underestimates nighttime down-valley flow.

Meiringen is located in the eastern Bernese Oberland region of the Alps and surrounded by high mountain ridges. The SwissMetNet station (SMN) measuring near ground parameters is situated 4 km east from the measurement site where a microwave radiometer (MWR), a Doppler Wind Lidar (DWL) and a Ceilometer were installed from October 2021 to August 2022. Within this 2 km wide Alpine valley, complex thermal wind systems are common and strong hot and dry Foehn wind may develop. Six months of data (February-August 2022) are used to compare the temperature, wind speed and direction as well as atmospheric boundary layer height of the NWP model (data from operational MeteoSwiss data assimilation system KENDA-1) with SNM and remote sensing measurements under winter and summer conditions. In general, temperature from the lowest level of KENDA and from the SMN station reveals low differences most likely because the SMN data are assimilated by the model. It however presents a clear diurnal cycle with an overestimation during the night and a clear underestimation (1-2 °C) during the day. The night overestimation is maximal in case of fair-weather days with ground-based temperature inversions while in case of Foehn, KENDA always overestimates the ground T. The comparison between MWR and SMN T indicates very low differences without diurnal cycles near ground. In general, the T difference between MWR and KENDA profiles present a small overestimation/underestimation (± 0.5 °C) of the model for low/high altitudes, respectively. In special cases, however, such as good weather days in winter or Foehn events, much larger differences are found. Ground-based inversions are well captured by the MWR but are not caught by KENDA, partly, because the altitude difference between the real and the model topography (130 m) is larger than the inversion height. The diurnal valley winds are measured by the DWL from February to July. Their vertical extension reaches only some hundreds of meter in winter but extends up to the northern ridges (2000 m) in summer. This diurnal valley winds are very well represented in KENDA. The main observed differences with measurements are an earlier setting after sunrise and in general higher up-valley wind speeds. In case of high wind speeds (> 20 m/s), KENDA simulates the main synoptic wind direction deeper into the valley. During Foehn events, the performance of KENDA to estimate the wind speed and direction shows even more variability.

Accurate and precise weather forecasting is essential for a wide range of applications and industries, from agriculture to transportation to renewable energy. However, current weather models often struggle to represent the weather accurately, especially over complex terrain, due to limitations in spatial resolution. To fill this gap, Meteomatics has developed the EURO1k model, the first pan-European weather model with a 1km2 resolution. The EURO1k model consists of approximately 20 million grid points and is run 24 times per day, with a forecast horizon of 24 hours. It is based on the WRF (Weather Research and Forecasting) model and uses global ECMWF-IFS model data for boundary conditions. In addition to standard data sources such as weather stations, radar and satellite data and radiosondes, the EURO1k model also ingests data from a network of Meteodrones - small unmanned aircraft systems (UAS) developed by Meteomatics which collect vertical atmospheric profiles up to 6000m in altitude. In addition, a downscaling technique using topographic maps enables further refinement of the resolution to 90m and vastly improves the precision of the model in mountainous areas. The high resolution of the EURO1k model allows it to accurately represent small-scale weather patterns such as foehn events, which are especially important and difficult to model over complex alpine topography. Statistical analyses of EURO1k model output against observations from 5000 weather stations in Europe demonstrate better accuracy compared to other global and regional models. This has important implications for industry and the public. The EURO1k model can improve the forecasting of extreme weather events, allowing for better preparation and response. It can also enhance the prediction of renewable energy production, which depends on weather conditions. This increases the cost efficiency of renewable energies and helps to reduce CO2 emissions. And, most importantly, it provides a more accurate and reliable weather forecast for communities across Europe. Overall, the EURO1k model represents a major advance in numerical weather prediction, bringing improved understanding and forecasting of the weather to a wide range of users.

The presented ARA system is being developed to create first of its kind high resolution (2.5 km) reanalysis ensemble dataset for Austria. ARA is primarily based on dynamical downscaling of European Centre for Medium-Range Weather Forecasts (ECMWF) ERA5 dataset (with a spatial resolution of 31km) by applying “Application of Research to Operations at Mesoscale” (AROME) non-hydrostatic limited area model to a destination spatial resolution of 2.5km. With the aid of the three-dimensional variational assimilation (3DVAR) system in AROME, observations from multiple sources, such as, satellites, radiosondes, aircraft, wind profiler etc. will be assimilated to construct a ten-member reanalysis ensemble. This re-analysis ensemble will provide spatially, temporally, and physically consistent 3D and 2D essential climate variables for Austria. The presented results are from initial testing phase and are very encouraging. In total five different synoptic situations were chosen for the tests. i.e., an extreme precipitation even, a fog event, a freezing event, a stormy situation, and a snowstorm. The model results are compared with station observations as well with gridded observations. Moreover, the operational models are used as a reference where no observations are available for comparison. Our analysis suggest that the ARA system is performing at par with our operational models. Statistical parameters, such as bias, rmse and spatial correlation along with 2D spatial plots are used to evaluate the model performance on daily and hourly scale.

Global km-scale modelling of the atmosphere is being explored for the future of numerical weather prediction and climate projection. Increasing horizontal resolutions from O(10km) to O(1km) allows models to represent finer details of mountains on the grid-scale. This additional spatial variability has historically led to beneficial impacts on the atmospheric circulation from mountain generated waves, improved surface temperatures and orographically forced convection. However, initial km-scale simulations carried out with the European Centre for Medium-Range Weather Forecasts Integrated Forecasting System (ECMWF IFS) in the framework of the Destination Earth initiative have shown a degradation of certain aspects of the large-scale circulation. This illustrates that further model development is required to fully exploiting the resolution increase. With models being routinely tested and tuned at coarser resolutions, choices made in model configuration and physical processes require revisiting at km-scale. We show that the large-scale circulation around mountainous regions, particularly the Himalayas, is extremely sensitive to: filtering of the model resolved orography; model timestep; parametrized orographic drag; and the hydrostatic approximation made in model dynamics. Lessons learned from these sensitivity experiments will be useful in the development of future global km-scale models.

Snow regimes in high-mountain regions are altering in response to climatic changes. However, the scarcity and limited accuracy of observations of snow and precipitation at high elevation reduce our understanding of cryosphere-climate linkage and the impacts to related components of the Earth System. Novel data from the ICESat-2 (Ice, Cloud, and land Elevation Satellite-2) laser altimeter can potentially provide snow depth observations in worldwide mountain region uncovered by ground observations. However, ICESat-2 observations follow ground tracks and are not repeated on the same ground tracks. Thus, we aim at building an approach for spatio-temporal snow water equivalent (SWE) reconstruction from point observations along ground tracks. Here, we present the developed approach, which combines data assimilation (ensemble Kalman filter (EnKF)) for temporal SWE reconstruction and machine learning (fully connected artificial neural network (FCNN)) for spatial SWE reconstruction. Firstly, the temporal reconstruction is performed along ground tracks with the EnkF, which optimize four parameters of a degree-day model to estimate an ensemble of the daily SWE evolution during the year. The degree-day model requires daily reanalysis precipitation and dowsncaled reanalysis air temperature. MODIS (Moderate-Resolution Imaging Spectroradiometer) snow cover data is used to identify the beginning of the snow accumulation and the end of the snow melt season. Secondly, the daily means and standard deviations of the SWE ensemble members are computed along the ground tracks. The FCNN is responsible for the spatial interpolation of the daily mean and standard deviation of the SWE ensemble members. Thus, the combined approach provides continuous spatio-temporal estimates of the SWE and of its uncertainty. The approach is tested in the alpine Dischma valley (Switzerland), where spatially high-resolution snow depth maps obtained with photogrammetric techniques from airplane (Ultracam Eagle M3) and unmanned aerial system (eBee+ RTK with SenseFly S.O.D.A. camera) observations are available. We converted snow depth into SWE with a parametric model for snow density. We extracted points directly from the high-resolution maps (along hypothetical satellite ground tracks), and we used the SWE observed at the extracted points for the spatio-temporal reconstruction. We study the performance of the combined EnKF-FCNN approach depending on the spatial distance between the hypothetical ground tracks, and depending on the number of observations per year available for the data assimilation step. At first, the implications for an application with real ICESat-2 data are discussed. Finally, the approach is tested with real ICESat-2 data in the Dischma valley.

We have trained a U-Net, a deep learning model, to recognise trapped lee waves from high resolution NWP model output. There is currently no operational way in the UK to recognise regions of waves directly from the NWP model data, short of a forecaster looking at the data themselves. The model was trained on 335 examples of vertical velocities at 700 hPa, along with hand-labelled masks of the wave locations. To expand the size of the small training set, augmentation was used to expose the model to waves in different wavelength and orientation to those in the un-augmented set. The trained model performs at 95% pixel accuracy on unseen test data and produces convincing masks of lee waves over the UK. It has learned to differentiate between other sources of vertical velocity in the data (such as convection) and can recognise wave-like structures within the data. It is hypothesised that during the process of recognising lee waves from the data, the model learned wave characteristics. Transfer learning, where a pre-trained model is fine-tuned to perform a new task (here we predict wave characteristics), was then used to extract those wave characteristics. The weights in the majority of the model were frozen and only the final layer was retrained using synthetic data to extract the desired characteristic. The influence of noise within the synthetic data on the trained characteristic models were explored. The NWP data contains other sources of vertical velocity than just waves, as well as superimposed waves. To try and account for this, characteristic models were also trained using synthetic data with added noise. These produced more realistic wave characteristics and performed well compared with a spectral technique to predict wave characteristics. These trained models have the potential to increase understanding about waves through the development of climatologies, or as a post-processing tool for forecasters. Similar methods could be applied to other classification problems in meteorology.

Analog-based statistical post-processing method (ABM) is proven effective for reducing the overall wind speed NWP error in Croatia, as well as for adequately assessing the forecast uncertainty. After several upgrades were recently made in the operational suite, the optimal NWP configuration to be used as an input to ABM is selected, the set of predictors is weighted and a correction for rare events is applied. These upgraded ABM forecasts are thoroughly evaluated, taking into consideration overall performance and the effect on rare event forecasts, especially in complex terrain prone to high wind speed (e.g., bora wind). Results show that wind direction is the most important predictor, in addition to wind speed. The additional predictor variables, properly weighted, improve results even further, especially in complex terrain. The error in general is larger in complex terrain prone to high-wind speed than in less complex continental areas, and the reduction of error by ABM is thus more pronounced. For the climatologically more common events, the improvement achieved with the ABM over the raw NWP is rather expected. The improvement, however, can also be achieved for rare events in some cases. This is especially the case after applying the statistical correction which enlarges the frequency of such forecasts. Since there are, of course, some limitations of the ABM method that one needs to be careful about, such an example is also shown.

and one of the focus areas of these phenomena is the eastern regions of Italy, because of the Adriatic Sea a Balkan areas is hit by cold intrusion, interacting with the sea and with the Apennine chain, causing severe snowstorm during the winter season and thunderstorm during the summer. An unusual and severe weather events hit Italy on July 9-10, 2019, a trough from Northern Europe affected Italy and the Balkans advecting cold air on the Adriatic Sea, causing heavy damages because of giant hail falling at the ground. The intrusion of relatively cold and dry air on the Adriatic Sea, in a first stage through the "Bora jets" generated by the Dinaric Alps gave rise to a frontal structure on the ground, which rapidly moved from North to South Adriatic. The large thermal gradient (also with the sea surface), the interaction with the complex orography and the coastal zone, generated several storm structures along the eastern Italian coast. During 10 July 2019 between 8UTC and 12UTC a deep convective supercell developed along the coast North of the city of Pescara, producing intense rainfall (accumulated rainfall reaching 130 mm/3h), a large hailstorm with hail grain around 10-14 cm and intense wind gust. The storm quickly moved southward, developing a complex multicellular structure, characterized by a rotating updraft with vertical velocity up to 50 m/s and a deep overshooting-top, clearly shown by the satellite and radar images. In this work the dynamics and thermodynamics for triggering and supporting the storm cell are investigated using the numerical model WRF (Weather Research and Forecasting system). Several numerical experiments are carried out using a 1 km grid on Central Italy, to investigate the impact the anomaly of the SST and the role of orography in the development and location of the convective cell. Results show a supercell characteristic of storm and that both topography and SST fundamental role in formation and developing of supercell: a high-resolution SST and the implementation of SST anomaly during the cold front and Bora Jets movement over the Adriatic Sea allows to correctly reproduce the atmospheric fields; the topography keeps inland the cold and dry air front coming from the Apennines. The interaction and balance between these guarantees the coastal movement of the storm, while the strong vertical shear and thermodynamics drive the intensification.

During the austral summer of 2018, the CACTI and RELAMPAGO joint field campaigns took place over the Argentinian Sierra de Cordoba (SDC) mountains. This north-south oriented ridge is notable for its frequent initiation of thunderstorms that may grow upscale into intense mesoscale convective systems. The SDC also initiates more garden-variety storms with shorter life cycles. Although the latter are less impactful, they may be more difficult to predict in convective-scale NWP models due to their strong sensitivities to uncertain subgrid processes and partially resolved processes in the deep-convection gray zone. To gain insight into the mechanisms and NWP predictability of such storms, this study performs convective-scale ensemble simulations of an isolated, diurnally forced SDC thunderstorm during CACTI/RELAMPAGO with the WRF model. The rich observational data sets allowed for detailed verification of the default ensemble, which used the default WRF geographic data. A major deficiency in soil moisture was identified, which caused the simulated convection to develop too early and reach much shallower depths than that observed. Upon correction of this bias, some ensemble members accurately represented the storm while others failed to generate any deep convection at all. This high degree of ensemble variability is explained by variations in low-level moisture supply and dynamic forcing for ascent over the SDC, with the former being the dominant contributor.

Near-surface winds over complex terrain generally feature 3D structures at the local scale. Forecasting these winds requires high-resolution Numerical Weather Prediction (NWP) models, which drastically increases the duration of simulations and hinders to run them on a routine basis. Nevertheless, downscaling methods can help forecasting such wind flows at limited numerical cost. In this study, we present a statistical downscaling of WRF wind forecasts over south-eastern France (including the south-eastern part of the Alps) from its original 9-km resolution to a 1-km resolution grid. A full year 1-km resolution WRF wind forecast is used to train and validate the statistical model. Downscaling is performed using convolutional neural networks (CNNs), which are the most popular machine learning tool for processing images or any kind of gridded data. In our case, CNNs allow to integrate information from spatial patterns contained in the low-resolution NWP output as well as from high-resolution terrain fields. Climatological features, which were roughly forecast at 9 km, are now well reproduced, both for speeds (ridge acceleration, sheltering in valleys) and directions (valley channeling). There is a general improvement in the forecast, especially during the nighttime, stable stratification period, which is the most difficult to forecast.

The output of Global climate models has a coarse resolution, which is unsuitable for practical applications like agricultural services. Downscaling is the approach used to refine data. There are two main approaches to downscale climate model outputs: Dynamical Downscaling (DD) and Statistical downscaling (SD). In DD, higher resolution climate models called regional climate models (RCM) are used. RCM use lower resolution climate models as boundary conditions and physical principles to reproduce local climate. These RCMs use physical equations and computational calculations to estimate local climate, making them computationally intensive and time-consuming. On the other hand, for SD, a statistical relationship is developed between the historically observed climate data and the climate model output for the same historical period. The relationship is used to develop future climate data. In recent years Machine learning-based statistical downscaling approaches have gained popularity due to their learning abilities from large datasets. We have developed a neural network-based machine learning algorithm to downscale coarser resolution temperature to a finer one over Trentino–South Tyrol (north-eastern Italian Alps). ERA 5 Land-gridded monthly temperature reanalysis data from ECMWF for the period from 1980 to 2018 used as a coarser resolution or predictor data. It is having horizontal resolution of around 0.1° x 0.1° (9 km). Higher resolution gridded data over Trentino and south Tyrol (CRESPI, 2020) having a horizontal resolution of around 1km x 1km is used as a predictand and considered the “ground truth”. In addition to that, considering the high correlation of elevation with temperature, elevation data of high resolution (1km x 1km) from the digital terrain model is used to train the model. We have developed different neural network models with additional complexity in terms number of layers in the model and compared them with a benchmark standard linear model and nonlinear model such as support vector regression for their performance.

Traditional dissemination of weather forecasts to the public often assumes the weather to be the similar in a given geographical region. The definition of such regions may be made by inspection of the correlation of elements of the weather. Using the high-resolution dynamic downscaling spatial correlations of the weather in Iceland is calculated, revealing spatially non-homogenous fields, where correlation between two locations may be more closely related to the aspect of the locations to mountains, than to geographical distance between the locations. This result underlines the importance of fine-scale considerations in mountainous regions, not only for short term, but also for medium and long-term forecasts.