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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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 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 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 m compared to 450 m. Additionally, differences of precipitation between 2830 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 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 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 m compared to
450 m. Additionally, differences of precipitation between 2830 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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