Improvements in the land surface configuration to better simulate seasonal snow cover in the European Alps with the CNRM-AROME (cycle 46) convection-permitting regional climate model

被引:0
作者
Monteiro, Diego [1 ]
Caillaud, Cecile [2 ]
Lafaysse, Matthieu [1 ]
Napoly, Adrien [2 ]
Fructus, Mathieu [1 ]
Alias, Antoinette [2 ]
Morin, Samuel [2 ]
机构
[1] Univ Grenoble Alpes, Univ Toulouse, Ctr Etud Neige, CNRS,CNRM,Meteo France, F-38000 Grenoble, France
[2] Univ Toulouse, CNRM, Meteo France, CNRS, Toulouse, France
关键词
ENERGY BUDGET; PARAMETERIZATION; SCALE; TEMPERATURE; IMPACT; SCHEME; INFORMATION; RESOLUTION; VARIABLES; INCLUSION;
D O I
10.5194/gmd-17-7645-2024
中图分类号
P [天文学、地球科学];
学科分类号
07 ;
摘要
Snow cover modeling remains a major challenge in climate and numerical weather prediction (NWP) models even in recent versions of high-resolution coupled surface-atmosphere (i.e., at kilometer scale) regional models. Evaluation of recent climate simulations, carried out as part of the WCRP-CORDEX Flagship Pilot Study on Convection (FPSCONV) with the CNRM-AROME convection-permitting regional climate model at 2.5 km horizontal resolution, has highlighted significant snow cover biases, severely limiting its potential in mountain regions. These biases, which are also found in AROME numerical weather prediction (NWP) model results, have multiple causes, involving atmospheric processes and their influence on input data to the land surface models in addition to deficiencies of the land surface model itself. Here we present improved configurations of the SURFEX-ISBA land surface model used in CNRM-AROME. We thoroughly evaluated these configurations on their ability to represent seasonal snow cover across the European Alps. Our evaluation was based on coupled simulations spanning the winters of 2018-2019 and 2019-2020, which were compared against remote sensing data and in situ observations. More specifically, the study tests the influence of various changes in the land surface configuration, such as the use of multi-layer soil and snow schemes, the division of the energy balance calculation by surface type within a grid cell (multiple patches), and new physiographic databases and parameter adjustments. Our findings indicate that using only more detailed individual components in the surface model did not improve the representation of snow cover due to limitations in the approach used to account for partial snow cover within a grid cell. These limitations are addressed in further configurations that highlight the importance, even at kilometer resolution, of taking into account the main subgrid surface heterogeneities and improving representations of interactions between fractional snow cover and vegetation. Ultimately, we introduce a land surface configuration, which substantially improves the representation of seasonal snow cover in the European Alps in coupled CNRM-AROME simulations. This holds promising potential for the use of such model configurations in climate simulations and numerical weather prediction both for AROME and other high-resolution climate models.
引用
收藏
页码:7645 / 7677
页数:33
相关论文
共 90 条
[81]   The AROME-France Convective-Scale Operational Model [J].
Seity, Y. ;
Brousseau, P. ;
Malardel, S. ;
Hello, G. ;
Benard, P. ;
Bouttier, F. ;
Lac, C. ;
Masson, V. .
MONTHLY WEATHER REVIEW, 2011, 139 (03) :976-991
[82]   EURO-CORDEX regional climate model analysis for the Greater Alpine Region: Performance and expected future change [J].
Smiatek, Gerhard ;
Kunstmann, Harald ;
Senatore, Alfonso .
JOURNAL OF GEOPHYSICAL RESEARCH-ATMOSPHERES, 2016, 121 (13) :7710-7728
[83]   The ALADIN System and its canonical model configurations AROME CY41T1 and ALARO CY40T1 [J].
Termonia, Piet ;
Fischer, Claude ;
Bazile, Eric ;
Bouyssel, Francois ;
Brozkova, Radmila ;
Benard, Pierre ;
Bochenek, Bogdan ;
Degrauwe, Daan ;
Derkova, Maria ;
El Khatib, Ryad ;
Hamdi, Rafiq ;
Masek, Jan ;
Pottier, Patricia ;
Pristov, Neva ;
Seity, Yann ;
Smolikova, Petra ;
Spaniel, Oldrich ;
Tudor, Martina ;
Wang, Yong ;
Wittmann, Christoph ;
Joly, Alain .
GEOSCIENTIFIC MODEL DEVELOPMENT, 2018, 11 (01) :257-281
[84]   Snow water equivalent in the Alps as seen by gridded data sets, CMIP5 and CORDEX climate models [J].
Terzago, Silvia ;
von Hardenberg, Jost ;
Palazzi, Elisa ;
Provenzale, Antonello .
CRYOSPHERE, 2017, 11 (04) :1625-1645
[85]   Large Differences in Global and Regional Total Soil Carbon Stock Estimates Based on SoilGrids, HWSD, and NCSCD: Intercomparison and Evaluation Based on Field Data From USA, England, Wales, and France [J].
Tifafi, Marwa ;
Guenet, Bertrand ;
Hatte, Christine .
GLOBAL BIOGEOCHEMICAL CYCLES, 2018, 32 (01) :42-56
[86]   The S2M meteorological and snow cover reanalysis over the French mountainous areas: description and evaluation (1958-2021) [J].
Vernay, Matthieu ;
Lafaysse, Matthieu ;
Monteiro, Diego ;
Hagenmuller, Pascal ;
Nheili, Rafife ;
Samacoits, Raphaelle ;
Verfaillie, Deborah ;
Morin, Samuel .
EARTH SYSTEM SCIENCE DATA, 2022, 14 (04) :1707-1733
[87]  
VERSEGHY DL, 1991, INT J CLIMATOL, V11, P111
[88]   Numerical Weather Forecasts at Kilometer Scale in the French Alps: Evaluation and Application for Snowpack Modeling [J].
Vionnet, Vincent ;
Dombrowski-Etchevers, Ingrid ;
Lafaysse, Matthieu ;
Queno, Louis ;
Seity, Yann ;
Bazile, Eric .
JOURNAL OF HYDROMETEOROLOGY, 2016, 17 (10) :2591-2614
[89]   Evaluation of CMIP6 DECK Experiments With CNRM-CM6-1 [J].
Voldoire, A. ;
Saint-Martin, D. ;
Senesi, S. ;
Decharme, B. ;
Alias, A. ;
Chevallier, M. ;
Colin, J. ;
Gueremy, J-F ;
Michou, M. ;
Moine, M-P ;
Nabat, P. ;
Roehrig, R. ;
Salas y Melia, D. ;
Seferian, R. ;
Valcke, S. ;
Beau, I ;
Belamari, S. ;
Berthet, S. ;
Cassou, C. ;
Cattiaux, J. ;
Deshayes, J. ;
Douville, H. ;
Ethe, C. ;
Franchisteguy, L. ;
Geoffroy, O. ;
Levy, C. ;
Madec, G. ;
Meurdesoif, Y. ;
Msadek, R. ;
Ribes, A. ;
Sanchez-Gomez, E. ;
Terray, L. ;
Waldman, R. .
JOURNAL OF ADVANCES IN MODELING EARTH SYSTEMS, 2019, 11 (07) :2177-2213
[90]   Past and future snowmelt trends in the Swiss Alps: the role of temperature and snowpack [J].
Vorkauf, Maria ;
Marty, Christoph ;
Kahmen, Ansgar ;
Hiltbrunner, Erika .
CLIMATIC CHANGE, 2021, 165 (3-4)