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FS 3.216

High-Resolution Modeling of the Atmosphere

Details

Full Title
FS 3.216: High-Resolution Modeling of the Atmosphere
Scheduled
TBA
Location
TBA
Convener
Nikolina Ban
Co-Conveners
Manuela Lehner, Mathias Rotach, Dino Zardi,
Assigned to Synthesis Workshop
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Thematic Focus
Atmosphere, Multi-scale Modeling
Keywords
Climate, Weather, Modeling, High-resolution, Atmospheric processes

Description

Numerical weather prediction (NWP) and climate modeling have gone through significant developments in recent years, with models reaching kilometer-scale horizontal grid spacings and producing high-resolution data. Such a high resolution is a valuable tool in mountain regions, both for process understanding and as input for other environmental models. High horizontal resolution leads to a more realistic representation of topography and an explicit representation of processes like convection. It has been shown that such simulations can, in general, lead to better forecasting and climate simulations, but this does not hold for all cases, especially over complex mountainous terrain. A successful simulation does not only depend on the terrain representation but also on the quality of input data, the land-use representation, the choice of parameterizations, the model setup, and last but not least, on the quality of observational data used for evaluation. The observational data is known to suffer the most over complex mountainous terrain, mostly due to a sparse observational network that is not able to capture complex features of mountain weather and climate. This session invites submissions from a broad range of NWP and climate modeling and applications over mountainous terrain, such as:

Model evaluation;
Process studies;
High-resolution simulations down to the large eddy simulations;
Newest developments and improvements of model set-ups and parameterizations; and
Newest developments of observational datasets.

Submitted Abstracts

ID: 3.5291

Observed and simulated trapped lee waves over Hengduan Mountains

Haile Xue

Abstract/Description

Due to the lack of high temporal and spatial resolution observations, the diurnal variation of the trapped lee wave (TLW) remains unknown. We employed the U-Net deep learning model to identify more than 3.5 thousand images with TLWs from over thirty thousand 500-m resolution Fengyun-4 satellite images with a 15-minute interval during the winter times from 2019 to 2023. Results shows that the wavelength is peaked at the late afternoon with high low-level winds and low atmospheric stability while the amplitude and propagating area are peaked at relative earlier afternoon with a most turbulent boundary in a day. The TLWs were further investigated in realistic and idealized large-eddy simulations by using WRF and ICON models, respectively. It is found that the effects of the stagnant and stable layer near the surface plays a wave-absorbing role in the nonlinear regime as in linear theories or simulations while the wave lengthening is largely related to the wind speed over the mountain.

ID: 3.7455

TIM Severe Storms Field Campaign – Thunderstorm Intensification from Mountains to Plains

Alois Holzer
Fischer, Jannick; Eisenbach, Stefan

Abstract/Description

Meteorology is lacking a deep understanding of the widely observed phenomenon of preferred thunderstorm intensification at the edges of mountain chains. Also high-resolution models struggle with initiation, intensification and quasi-stationarity of thunderstorms, being a frequent topic close to or at mountains. High-resolution data (both in space, time and complementarity) is needed to resolve partially conflicting theories and to provide both reference and experimental input for high-resolution models. This conference contribution provides an overview of the goals, timeline and partners of the TIM Severe Storms Field Campaign and its focus on effects caused by complex topography. All TIM partners are required to follow a responsible conduct strategy for the entire field campaign. This includes minimising the environmental footprint by maximising green mobility and thorough CO2-sensitive planning, and giving preference to local suppliers and small businesses. TIM is aiming not only to collect measurement data but also pre- and post-event data including damage assessment and social studies.

ID: 3.8432

Investigation of aerosol effects on diurnal cycle of precipitation amount, frequency and intensity over Central Africa by a regional clumate model.

Komkoua Mbienda A J

Abstract/Description

Regional climate is affected by a wide variety of aerosols which modify through their radiative effects the precipitation distribution. In this article, the effects of aerosols, mainly dust aerosols on diurnal cycle of precipitation amount, frequency and intensity are investigated over central Africa by using the latest version of the Abdu Salam ICTP regional climate model coupled with the Community Land Model 4.5 as land surface scheme. Two sets of experiments have been conducted (one with aerosols interaction with dynamics and thermodynamics processes and another without this interaction) for a 10-year study period (2002–2011) and the Fourier transformation is used to study the 24-h cycle. In order to clearly understand spatial differences in RegCM experiments over central Africa, three subregions have been considered according to their land cover and climate characteristics. Our results indicate that the pattern of simulated aerosol optical depth (AOD) is well represented particularly northward of the study region compared to AOD from moderate resolution imaging spectroradiometer (MODIS) even if some differences in terms of magnitude are reported. The aerosols’ effects on diurnal cycle are generally not similar to those found in the amplitude and phase. The result pointed out that over the Sahelian region, atmospheric aerosol in general and dust in particular always induced a positive effect on diurnal cycle (increase the magnitude of the cycle) of precipitation intensities and in precipitation amount and precipitation frequency as well. But, the change is opposite in terms of amplitude and peak time over some subregions. It appears that the forcing of aerosols in solar radiation as well as in latent heat flux leads to the changes in the amplitude of the precipitation amount during the DJF and JAS seasons particularly during daytime. The changes in amplitude of the precipitation frequency are not consistent even if the corresponding phase always tends to increase by up to 5 h.

ID: 3.9393

Validation of ICON-LES from HEFEX II field campaign observations

Alexander Georgi
Sauter, Tobias

Abstract/Description

In August 2023, the HEFEX II (HinterEisFerner-EXperiment) campaign was conducted in the Austrian Alps to investigate multi-scale exchanges between the atmosphere and glaciers. The campaign combined data from numerous automatic weather stations (AWS) and Eddy-Covariance (EC) stations operating over four weeks and an intensive three-day observation utilizing unmanned aerial vehicles (UAVs) and LiDAR technology. These measurements provided detailed insights into various atmospheric parameters, including temperature, humidity, wind information, and heat fluxes, across spatial and temporal scales.

The collected data serves as a valuable resource for validating high-resolution ICON-LES (Large Eddy Simulation) models with a horizontal resolution of 51 meters. This validation is performed both qualitatively and quantitatively, focusing on capturing the spatio-temporal variability of the measured atmospheric parameters. Through this process, the campaign aims to refine model parameterization to enhance simulation accuracy, particularly for the complex and dynamic processes governing atmosphere-glacier interactions.

Preliminary results confirm that ICON-LES exhibits strong agreement with observed data. These findings support the potential of ICON-LES as a reliable tool for modeling atmosphere-glacier interactions, paving the way for climate impact studies in alpine regions. This study highlights the synergy between advanced observational techniques and high-resolution simulations, advancing our understanding of atmosphere-glacier dynamics and their broader climatic implications but at the same time also outlines current limitations of numerical modeling.

The HEFEX campaign demonstrated the effective application of UAVs in atmospheric research. These platforms demonstrated their capability to collect high-resolution, flexible, and precise data in challenging high-elevation environments. By integrating UAV observations with traditional measurement methods, the campaign underscores their growing importance in complementing and extending stationary observations.

Overall, the HEFEX campaign contributes to advancing understanding of atmosphere-glacier processes, improving numerical weather prediction models, and showcasing innovative observational techniques in atmospheric science.

ID: 3.9469

Sources of temperature biases in Regional Climate Models over complex orography: a general approach

Francesca Zarabara
Giaiotti, Dario

Abstract/Description

Amid the alarming pace and effects of human-induced climate change, mountainous regions are warming at about twice the global average rate. Modeling climate and climate change scenarios over regions with highly complex topography, such as the Alps, remains a significant challenge for regional climate modeling. Better characterizing the sources of model biases is a major issue, particularly in areas with complex terrain. We analyze the sources of bias affecting near-surface temperature (TAS) in an ensemble of EURO-CORDEX models, focusing on the Friulian Alps. By examining the vertical structure of atmospheric thermal profiles, we identify and quantify four main sources that contribute to surface temperature biases at specific locations or grid points. The first source is related to the ensemble’s ability to reproduce free-atmosphere temperatures, such as those at the 500 hPa level. The second component accounts for the biased representation of the thermal gradient between the free-atmosphere and the boundary layer top. The third component is associated with model errors in the height of the boundary layer top. Under the environmental lapse rate approximation, this component corresponds to the orographic bias at a station or grid point. In the mountainous region we examined, the orographic bias represents a significant source of error. The final contribution to the TAS bias stems from the inadequate representation of processes within the boundary layer, which exhibit temporal and spatial variability depending on the type of mountain boundary layer. We provide seasonal and annual estimates for each TAS bias component and suggest that advanced statistical bias correction techniques, including machine learning approaches, may be particularly effective in addressing the specific challenges posed by the boundary-layer-dependent component of the overall TAS bias.

ID: 3.9792

Exploring the dynamics of Extreme Summer Precipitation events in the Eastern Italian Alps using CORDEX-FPS data

Anna Napoli
Ban, Nikolina; Pasquero, Claudia; Zardi, Dino

Abstract/Description

Extreme precipitation events during summertime pose significant challenges, particularly in regions with complex topography, such as the Eastern Italian Alps, a region characterised by strong convective activity. To analyse the spatial and temporal distribution of these events, with a specific focus on their elevation-dependent patterns and sub-daily dynamics, this study employs results of high-resolution modeling simulations from the Coordinated Regional Climate Downscaling Experiment Flagship Pilot Studies (CORDEX-FPS) on convection phenomena over the Alps and the Mediterranean. By leveraging the advanced modeling capabilities of CORDEX-FPS, in this study, we aim to assess the influence of complex terrain on summer precipitation extremes and explore how these events are modulated at different elevations. The results identify critical hotspots of precipitation intensity and frequency, providing valuable insights for risk management and adaptation strategies in mountainous areas. This case study underscores the importance of using regionally tailored models to better understand the dynamics of extreme summer weather phenomena in complex landscapes. Moreover, improved simulations can be key in supporting more effective adaptation strategies.

ID: 3.10311

Moist convection and tracer transport in the Third Pole region

Bodo Ahrens
Singh, Prashant

Abstract/Description

The Asian Summer Monsoon Anticyclone (ASMA) plays a critical role in trapping, transporting, and redistributing water vapour in the upper troposphere and lower stratosphere, particularly into the extratropical lower stratosphere. Comparison of ERA5 reanalysis data with remote sensing data and simulations with the model ICON-CLM in convection-parameterized (12 km grid spacing) and convection-permitting (3.3 km) set-ups indicate that the transport into the ASMA is overestimated in ERA5 over the Tibetan plateau (Singh & Ahrens 2023). This presentation critically discusses the water vapour transport into the upper-troposphere/lower-stratosphere by deep convective events over the Tibetan plateau and the Himalayas – an area identified as hotspot for troposphere-stratosphere exchange (Škerlak et al. 2014) using convection-parameterized reanalysis data. Our investigations use a decade-long ICON-CLM climate-like simulation (Collier et al. 2024) performed as a contribution to the CORDEX flagship pilot study Convection-Permitting Third Pole (CPTP).

References
Collier, E., N. Ban, N. Richter, B. Ahrens, D. Chen, X. Chen, H-W. Lai, R. Leung, L. Li, T. Ou, P.K. Pothapakula, E. Potter, A. F. Prein, K. Sakaguchi, M. Schroeder, P. Singh, S. Sobolowski, S. Sugimoto, J. Tang, H. Yu, C. Ziska: The First Ensemble of Kilometre-Scale Simulations of a Hydrological Year over the Third Pole. Clim Dyn. 2024
Singh, P., B. Ahrens: Modeling Lightning Activity in the Third Pole Region: Performance of a km-Scale ICON-CLM Simulation. Atmosphere, 14(11), 1655, 2023
Škerlak, B., M. Sprenger, and H. Wernli: A global climatology of stratosphere–troposphere exchange using the ERA-Interim data set from 1979 to 2011. English. Atmospheric Chemistry and Physics 14 (2), 2014

ID: 3.10898

Simulating CH4 concentrations over the Alps with WRF-GHG: Validation Against TROPOMI Observations and Ground-based Measurements

Marco D'emilio
Pasquariello, Pamela; Masiello, Guido; Serio, Carmine; Liuzzi, Giuliano; Carbone, Francesco; Gencarelli, Christian N.; Giosa, Rocco; Cassini, Lorenzo

Abstract/Description

The increasing concentration of methane (CH₄) in the atmosphere represents one of the most pressing challenges for climate change mitigation due to its high global warming potential and significant contribution to the greenhouse effect. The Alpine chain, characterized by its complex orography and significant climatic variability, serves as a key region for the atmospheric transport, accumulation, and redistribution of CH₄ across Europe. To enhance our understanding of the spatial and temporal distribution of CH₄ in this area, we performed numerical simulations using the WRF-Chem model with the WRF-GHG chemical module. The WRF-GHG module is specifically designed for greenhouse gas modeling and treats gases such as CH₄ as passive tracers. This approach assumes that CH₄ does not undergo chemical reactions within the atmosphere, focusing on its transport and dispersion influenced by meteorological conditions, thereby reducing computational complexity while maintaining accuracy in capturing spatial and temporal dynamics. The model combined the Emissions Database for Global Atmospheric Research (EDGAR-2024_GHG) inventory, background data provided by the Whole Atmosphere Community Climate Model (WACCM) database, and biomass burning emissions from the Fire INventory from NCAR (FINN) database. The simulation was conducted for the entire year 2022, with a 7-day spin-up run, to properly initialize the atmospheric conditions. We employed two nested domains: the outer domain with a spatial resolution of 10 km and the inner domain with a resolution of 5 km. This nesting strategy allowed for a detailed representation of atmospheric processes within the Alpine chain while accounting for broader regional influences, with the innermost domain also including part of central Europe. Model outputs were compared with satellite observations from the TROPOspheric Monitoring Instrument (TROPOMI) sensor onboard Sentinel-5P, and ground-based measurements from Integrated Carbon Observation System (ICOS) stations for further validation, assessing the reliability of simulated CH₄ concentrations and their seasonal trends. As part of the PRIN-MVP project, the annual dataset generated through these simulations will serve as a critical input for validating a physics-informed neural network-based retrieval system for CH₄, further advancing the capability to monitor and mitigate greenhouse gas emissions.

ID: 3.11481

Assessing the Added Value of Convection-Permitting Climate Models for Hydrological Extremes in Western Norway

Lu Li
Xie, Kun; Chen, Hua; Xu, Chong-Yu

Abstract/Description

High-resolution convection-permitting regional climate models (CPRCMs) have demonstrated improved representation of extreme precipitation compared to coarser regional climate models (RCMs). However, their added value for simulating hydrological extremes, such as floods, remains uncertain, particularly in complex mountainous terrain. This study assesses the performance of a 3-km convection-permitting model (HCLIM3) against a coarser 12-km model (HCLIM12) from the HARMONIE-Climate (HCLIM) system in reproducing precipitation, temperature, and flood characteristics in two hydrologically contrasting basins in Western Norway: the coastal Røykenes basin, dominated by rainfall-induced floods, and the mountainous Bulken basin, where floods are primarily driven by snowmelt. To evaluate the impact of CPRCMs on hydrological extremes, we employ both a physically-based distributed model (WRF-Hydro) and a conceptual lumped model (HBV) for flood simulations. HCLIM3 better captures the spatial distribution of extreme precipitation, particularly for annual maximum 1-day and 1-hour events, compared to HCLIM12. However, both models exhibit a cold bias, which is more pronounced at lower elevations, especially in HCLIM12. Despite improvements in precipitation representation, HCLIM3-driven flood simulations do not consistently outperform those driven by HCLIM12, except for extreme flood peaks. The choice of hydrological model significantly impacts flood simulations. The HBV model underestimates flood peaks and frequencies, whereas WRF-Hydro provides more accurate simulations in Røykenes but overestimates floods in Bulken, likely due to forcing biases, particularly when driven by HCLIM3. These results suggest that while CPRCMs improve the representation of extreme precipitation and temperature, their direct benefit for flood simulations is less evident without adequate bias correction, especially in snowmelt-driven basins. This study highlights the importance of evaluating high-resolution climate models in an integrated atmosphere-hydrology framework to improve the prediction of hydrological extremes over complex mountainous regions.

ID: 3.11516

Snow Variability Analyses Based on CERRA-Land versus Convection Permitting Climate Simulations in the Upper Euphrates Basin

Mehmet Barış Kelebek
Demirtaş, Esma Nur; Önol, Barış

Abstract/Description

The snow cover in the Upper Euphrates Basin, the headwater of the transboundary Euphrates River located in the mountainous region of Eastern Türkiye, has changed in recent decades due to warming. Particularly, rising temperatures shift the timing of snowmelt and shorten the snow season. Since the snowmelt is crucial for water resources and energy production in the basin, changes in the snow cover pattern increase the basin’s vulnerability to climate change. In this study, we first investigated the changes in snow depth and snow cover during the snow season from November to April in the Upper Euphrates Basin for the 1985–2021 period by using the Copernicus European Regional Reanalysis for Land (CERRA-Land) dataset at 5.5 km horizontal resolution. Following that, we performed convection-permitting climate simulations at a 3 km horizontal resolution for the 2005–2014 reference and 2041–2050, 2061–2070, and 2091-2100 future periods to reveal the changes in temperature extremes and land-atmosphere interactions due to reduced snow cover in detail over the basin. To this end, we downscaled the MPI-ESM1.2-HR simulations under the SSP3-7.0 scenario using the WRF model. The analyses of CERRA-Land indicate that snow cover has diminished significantly in November, with levels remaining below 5% during the 2012–2021 period at grid points between 1.000 and 1.500 meters in altitude. Also, future climate simulations indicate an earlier snowmelt in spring, decreasing the snow cover by about 20%, and the surface albedo by about 10% in the same elevation range due to sudden warming in March across the study area. Moreover, trend analysis of CERRA-Land shows that the maximum snow depth during March and April decreases up to 30 cm/decade. The outcomes of this study emphasize the earlier snowmelt, the retreat of snow cover, and the shortening of the snow season in historical and future periods in the Upper Euphrates Basin.

ID: 3.11701

Convection-permitting simulation of MCSs over the Tibetan Plateau and downstreams: Insights from the first ensemble run of ‘WY2020’ at K-Scale in CORDEX-FPS-CPTP

Puxi Li

Abstract/Description

Mesoscale convective systems (MCSs) are major contributors to extreme precipitation events and have attracted significant attention in the context of global warming. In 2020, large parts of East Asia, downstream of the Tibetan Plateau (TP), experienced an exceptionally wet rainy season and suffered intense MCS precipitation, resulting in severe impacts and losses. Here, based on the first ensemble run of K-scale WRF simulation (~4km) of Water Year 2020 (WY2020) within the CORDEX-FPS-CPTP framework, we investigated the performance of these simulations in simulating MCS precipitation characteristics, using the GPM-IMERG product and the CMA Multi-source merged Precipitation Analysis (CMPA) for comparison. The results indicate that while each member can generally captures the spatial distribution of MCS precipitation, notable differences emerge among the single-physical perturbation runs: Simulations using the Morrison and WSM5 microphysical scheme closely resemble the observations, while simulations using the SBU_Ylin or WDM6 microphysical schemes significantly underestimate MCS precipitation. In terms of boundary layer (PBL) scheme sensitivity, the K-scale simulations using the YSU and ShinHong schemes perform better than those using the MYNN3 scheme. Despites these differences, further analysis reveals an interesting phenomenon: all K-scale simulations collectively underestimate the MCS rainfall area by 30.9% to 43.0%, while overestimating MCS precipitation intensity by 59.4%~64.1%. This indicates that the simulated MCS precipitation tends to be smaller in size but more intense. Expanding the model domain to double its original size (from [15.0N–50.0N; 65.0E–125.0E] to [5.0N–55.0N; 45.0E–160.0E]) for the WY2020 run shows that after the domain expansion, the model not only captures the heavy MCS rainfall center over the Western North Pacific Ocean (south of Japan), but also better reproduces MCS precipitation features than other WRF K-scale WY2020 runs. It even outperforms the GPM product over eastern China, particularly in capturing the local enhancement of heavy MCS precipitation influenced by mountainous terrain. The K-scale WY2020 ensemble run provides a valuable resource for improving our understanding of MCS behavior and the hydrological cycle over the TP and its downstream areas.

ID: 3.12417

High resolution atmospheric modelling of high-altitude precipitation patterns and dynamics in the Third Pole region.

René Wijngaard
Immerzeel, Walter

Abstract/Description

Mountain precipitation is the key driver of the Third Pole water cycle, which provides valuable water resources for millions of people living in the region and its surroundings. However, mountain precipitation can also be a key trigger for natural hazards, such as avalanches, floods, and landslides, leading to a large number of casualties and economic losses. Hence, it is important to understand precipitation patterns, dynamics and corresponding atmospheric processes at different scales (ranging from the valley scale to the synoptic scale), which remains, however, challenging due to the extreme topography and the limited availability of high-altitude precipitation measurements and well-validated high-resolution precipitation datasets.

To address this challenge, we use the numerical atmospheric Weather Research & Forecasting model (WRF) version 4.6.1. We apply WRF with three different nested model domains, with horizontal grid spacings of 9, 3, and 1 km, respectively. The 9 km domain covers an area extending from the Caspian Sea in the west to the western Pacific Ocean in the east, capturing remote atmospheric processes that potentially can influence the Third Pole. The 3 km domain covers the Third Pole region, and the 1 km domains cover transects over two meteorological contrasting regions in the Himalayas (Langtang) and the Pamir (Fedchenko and adjacent valleys). We evaluate the model outcomes by comparisons to gridded outputs derived from existing WRF-based datasets, such as the High Asia Refined analysis version 2 (HAR2), satellite-based datasets (e.g. IMERG-GPM), and high-altitude observational data obtained from automatic weather stations, pluviometers, and tipping buckets. The model outputs aim to contribute to a better understanding of high-altitude precipitation patterns, dynamics, and corresponding atmospheric processes in the Third Pole region.

ID: 3.13130

AlpTherm3d – a convection model on highly resolved orography

Bruno Neininger

Abstract/Description

Originally, ALPTHERM was a tool for assessing convection for air sports. Between 1993 and March 2024, daily results were disseminated by the German, the Austrian, and the Swiss Weather Services as forecasts for soaring conditions. A new version could do more than that, because it allows to simulate mixing processes during convective days, the formation of cold pools, or studies on the influence of surface properties and their interaction with an atmosphere in a changing climate. Operational LAM, still limited by the steepness of the orography, have other priorities, and need big computing power. The Lagrangian architecture and other short-cuts are allowing to make such studies on a PC. AlpTherm3d is not a stand-alone simulation model, but rather a heuristic downscaling algorithm with flexible options for the initial and boundary conditions (e.g. from ICON-D2, or GFS). The horizontal coarse grid is adjusted to ICON-D2 (0.02°; interpolated for other sources), but the formation of katabatic or anabatic flow is running on the much higher resolution of the underlying DTM (e.g. SRTM topography on a horizontal grid spacing of less than 100 m, and 1 m vertical resolution), with several options for the surface properties (e.g. albedo from MODIS). “Lagrangian” means, that pockets of air cooled or heated on the surface pixels are proceeding as katabatic or anabatic flows, or leaving the surface as a thermal plume, after they had the possibility to follow a slope, accumulating and interacting with the wind field. The resulting mass imbalances are then compensated by subsidence, and lifting, before the resulting pressure gradients are relaxed, modifying the larger scale wind field taken from the external model. “Heuristic” means, that the turbulent fluxes are not 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. Results from case studies as well in other regions than the Alps provided good results. The main limitation is the availability of highly resolved, dynamic soil properties.

ID:

Temperatures and Precipitation downscaling in mountainous areas using topography-based information

Quiquet, Aurélien; Roche, Didier ; Paillard, Didier

Abstract/Description

From hydrological impact studies and crop monitoring in agronomy to paleoenvironments reconstructions, many studies from various fields require high spatial resolution climate data (< 5 km to subkilometric scales). Although in situ measurements produce reliable estimations of physical parameters locally, limitations regarding their spatial and temporal coverage often leads to using data derived from models. Among these, Global Climate Models (GCM) provide the most comprehensive representation of the climate system and the interactions between its components. Due to high computational costs, the horizontal resolution of such models yet remains restricted to 50-100 km, when multi-decennal or longer simulations are required. In order to refine GCM outputs, two main downscaling approach have been developed over the years. Firstly, dynamical downscaling techniques explicitly resolves atmospheric physics and dynamics at fine scale but generally involves elevated computational costs, limiting domain extent and their usage over long periods of time. Secondly, statistical downscaling does not physically represent the climate, but attempts instead to identify statistical relationships between coarse resolution and local variables. These cost-effective methods are however dependant on the spatial repartition and quality of observations used for calibration, hampering their use in regions with sparse station coverage. Additionally, statistical downscaling relies on a strong hypothesis of stationarity, supposing that the relationship built on the observation period remains valid through time. Although it cannot be tested explicitly, this assumption may not stay valid under very different climate conditions. Less common, an alternative approach focuses specifically on the interactions between regional atmospheric circulation and high-resolution topography which constitutes a major driver of the local climate, producing strong variability over short distances. Since existing topographic downscaling methods did not meet our requirements, we developed a physically based model, adapted to long-term simulations (multi-millenia) at fine spatial scale and taking into account local terrain characteristics derived from Digital Elevation Models and large scale climate signal. The method allows to downscale temperatures and precipitation in mountainous areas and requires limited inputs as well as low computing resources.

ID: 4.0000

Temperature and Precipitation downscaling in mountainous areas using topography-based information

Brenner Brenner
Quiquet, Aurélien; Roche, Didier; Paillard, Didier

Abstract/Description

From hydrological impact studies and crop monitoring in agronomy to paleoenvironments reconstructions, many studies from various fields require high spatial resolution climate data (< 5 km to subkilometric scales). Although in situ measurements produce reliable estimations of physical parameters locally, limitations regarding their spatial and temporal coverage often leads to using data derived from models. Among these, Global Climate Models (GCM) provide the most comprehensive representation of the climate system and the interactions between its components. Due to high computational costs, the horizontal resolution of such models yet remains restricted to 50-100 km, when multi-decennial or longer simulations are required. In order to refine GCM outputs, two main downscaling approach have been developed over the years. Firstly, dynamical downscaling techniques explicitly resolves atmospheric physics and dynamics at fine scale but generally involves elevated computational costs, limiting domain extent and their usage over long periods of time. Secondly, statistical downscaling does not physically represent the climate, but attempts instead to identify statistical relationships between coarse resolution and local variables. These cost-effective methods are however dependant on the spatial repartition and quality of observations used for calibration, hampering their use in regions with sparse station coverage. Additionally, statistical downscaling relies on a strong hypothesis of stationarity, supposing that the relationship built on the observation period remains valid through time. Although it cannot be tested explicitly, this assumption may not stay valid under very different climate conditions. Less common, an alternative approach focuses specifically on the interactions between regional atmospheric circulation and high-resolution topography which constitutes a major driver of the local climate, producing strong variability over short distances. Since existing topographic downscaling methods did not meet our requirements, we developed a physically based model, adapted to long-term simulations (multi-millennia) at fine spatial scale and taking into account local terrain characteristics derived from Digital Elevation Models and large scale climate signal. The method allows to downscale temperatures and precipitation in mountainous areas and requires limited inputs as well as low computing resources.

FS 3.215: Mountain ecosystems in the 2030 Agenda: sustainable balance between livelihoods and biodiversity conservation as an opportunity for rural development

FS 3.218: Communication in mountains

#IMC: September 14 - 18 2025

FS 3.216

High-Resolution Modeling of the Atmosphere

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