Spatial variability in snow precipitation and accumulation in COSMO–WRF simulations and radar estimations over complex terrain

<p>Snow distribution in complex alpine terrain and its evolution in the future climate is important in a variety of applications including hydropower, avalanche forecasting and freshwater resources. However, it is still challenging to quantitatively forecast precipitation, especially over...

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Main Authors: F. Gerber, N. Besic, V. Sharma, R. Mott, M. Daniels, M. Gabella, A. Berne, U. Germann, M. Lehning
Format: Article
Language:English
Published: Copernicus Publications 2018-10-01
Series:The Cryosphere
Online Access:https://www.the-cryosphere.net/12/3137/2018/tc-12-3137-2018.pdf
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spelling doaj-c62693c36f624f6ea243f8c1b1e161ef2020-11-25T01:57:22ZengCopernicus PublicationsThe Cryosphere1994-04161994-04242018-10-01123137316010.5194/tc-12-3137-2018Spatial variability in snow precipitation and accumulation in COSMO–WRF simulations and radar estimations over complex terrainF. Gerber0F. Gerber1N. Besic2N. Besic3V. Sharma4R. Mott5R. Mott6M. Daniels7M. Gabella8A. Berne9U. Germann10M. Lehning11M. Lehning12Laboratory of Cryospheric Sciences, School of Architecture, Civil and Environmental Engineering, École Polytechnique Fédérale de Lausanne, Lausanne, SwitzerlandWSL Institute for Snow and Avalanche Research SLF, Davos, SwitzerlandEnvironmental Remote Sensing Laboratory, School of Architecture, Civil and Environmental Engineering, École Polytechnique Fédérale de Lausanne, Lausanne, SwitzerlandRadar, Satellite, Nowcasting Department, MeteoSwiss, Locarno, SwitzerlandLaboratory of Cryospheric Sciences, School of Architecture, Civil and Environmental Engineering, École Polytechnique Fédérale de Lausanne, Lausanne, SwitzerlandWSL Institute for Snow and Avalanche Research SLF, Davos, SwitzerlandInstitute of Meteorology and Climate Research, Atmospheric Environmental Research (KIT/IMK-IFU), KIT-Campus Alpin, Garmisch-Partenkirchen, Germanyindependent researcher: Sydney, AustraliaRadar, Satellite, Nowcasting Department, MeteoSwiss, Locarno, SwitzerlandEnvironmental Remote Sensing Laboratory, School of Architecture, Civil and Environmental Engineering, École Polytechnique Fédérale de Lausanne, Lausanne, SwitzerlandRadar, Satellite, Nowcasting Department, MeteoSwiss, Locarno, SwitzerlandLaboratory of Cryospheric Sciences, School of Architecture, Civil and Environmental Engineering, École Polytechnique Fédérale de Lausanne, Lausanne, SwitzerlandWSL Institute for Snow and Avalanche Research SLF, Davos, Switzerland<p>Snow distribution in complex alpine terrain and its evolution in the future climate is important in a variety of applications including hydropower, avalanche forecasting and freshwater resources. However, it is still challenging to quantitatively forecast precipitation, especially over complex terrain where the interaction between local wind and precipitation fields strongly affects snow distribution at the mountain ridge scale. Therefore, it is essential to retrieve high-resolution information about precipitation processes over complex terrain. Here, we present very-high-resolution Weather Research and Forecasting model (WRF) simulations (COSMO–WRF), which are initialized by 2.2&thinsp;km resolution Consortium for Small-scale Modeling (COSMO) analysis. To assess the ability of COSMO–WRF to represent spatial snow precipitation patterns, they are validated against operational weather radar measurements. Estimated COSMO–WRF precipitation is generally higher than estimated radar precipitation, most likely due to an overestimation of orographic precipitation enhancement in the model. The high precipitation amounts also lead to a higher spatial variability in the model compared to radar estimates. Overall, an autocorrelation and scale analysis of radar and COSMO–WRF precipitation patterns at a horizontal grid spacing of 450&thinsp;m show that COSMO–WRF captures the spatial variability normalized by the domain-wide variability in precipitation patterns down to the scale of a few kilometers. However, simulated precipitation patterns systematically show a lower variability on the smallest scales of a few hundred meters compared to radar estimates. A comparison of spatial variability for different model resolutions gives evidence for an improved representation of local precipitation processes at a horizontal resolution of 50&thinsp;m compared to 450&thinsp;m. Additionally, differences of precipitation between 2830&thinsp;m above sea level and the ground indicate that near-surface processes are active in the model.</p>https://www.the-cryosphere.net/12/3137/2018/tc-12-3137-2018.pdf
collection DOAJ
language English
format Article
sources DOAJ
author F. Gerber
F. Gerber
N. Besic
N. Besic
V. Sharma
R. Mott
R. Mott
M. Daniels
M. Gabella
A. Berne
U. Germann
M. Lehning
M. Lehning
spellingShingle F. Gerber
F. Gerber
N. Besic
N. Besic
V. Sharma
R. Mott
R. Mott
M. Daniels
M. Gabella
A. Berne
U. Germann
M. Lehning
M. Lehning
Spatial variability in snow precipitation and accumulation in COSMO–WRF simulations and radar estimations over complex terrain
The Cryosphere
author_facet F. Gerber
F. Gerber
N. Besic
N. Besic
V. Sharma
R. Mott
R. Mott
M. Daniels
M. Gabella
A. Berne
U. Germann
M. Lehning
M. Lehning
author_sort F. Gerber
title Spatial variability in snow precipitation and accumulation in COSMO–WRF simulations and radar estimations over complex terrain
title_short Spatial variability in snow precipitation and accumulation in COSMO–WRF simulations and radar estimations over complex terrain
title_full Spatial variability in snow precipitation and accumulation in COSMO–WRF simulations and radar estimations over complex terrain
title_fullStr Spatial variability in snow precipitation and accumulation in COSMO–WRF simulations and radar estimations over complex terrain
title_full_unstemmed Spatial variability in snow precipitation and accumulation in COSMO–WRF simulations and radar estimations over complex terrain
title_sort spatial variability in snow precipitation and accumulation in cosmo–wrf simulations and radar estimations over complex terrain
publisher Copernicus Publications
series The Cryosphere
issn 1994-0416
1994-0424
publishDate 2018-10-01
description <p>Snow distribution in complex alpine terrain and its evolution in the future climate is important in a variety of applications including hydropower, avalanche forecasting and freshwater resources. However, it is still challenging to quantitatively forecast precipitation, especially over complex terrain where the interaction between local wind and precipitation fields strongly affects snow distribution at the mountain ridge scale. Therefore, it is essential to retrieve high-resolution information about precipitation processes over complex terrain. Here, we present very-high-resolution Weather Research and Forecasting model (WRF) simulations (COSMO–WRF), which are initialized by 2.2&thinsp;km resolution Consortium for Small-scale Modeling (COSMO) analysis. To assess the ability of COSMO–WRF to represent spatial snow precipitation patterns, they are validated against operational weather radar measurements. Estimated COSMO–WRF precipitation is generally higher than estimated radar precipitation, most likely due to an overestimation of orographic precipitation enhancement in the model. The high precipitation amounts also lead to a higher spatial variability in the model compared to radar estimates. Overall, an autocorrelation and scale analysis of radar and COSMO–WRF precipitation patterns at a horizontal grid spacing of 450&thinsp;m show that COSMO–WRF captures the spatial variability normalized by the domain-wide variability in precipitation patterns down to the scale of a few kilometers. However, simulated precipitation patterns systematically show a lower variability on the smallest scales of a few hundred meters compared to radar estimates. A comparison of spatial variability for different model resolutions gives evidence for an improved representation of local precipitation processes at a horizontal resolution of 50&thinsp;m compared to 450&thinsp;m. Additionally, differences of precipitation between 2830&thinsp;m above sea level and the ground indicate that near-surface processes are active in the model.</p>
url https://www.the-cryosphere.net/12/3137/2018/tc-12-3137-2018.pdf
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