Intercomparison of the Land-Surface Schemes within the Weather and Research Forecasting Model

Presenter Information

Jiming Jin

Location

ECC 216

Event Website

https://water.usu.edu/

Start Date

3-31-2008 6:20 PM

End Date

3-31-2008 6:25 PM

Description

The Community Land Model version 3 (CLM3) developed by the National Center for Atmospheric Research (NCAR) was coupled into the Weather Research and Forecasting (WRF) Model version 2.2. The performance of WRF-CLM3 in predicting regional climate was quantitatively compared with that of WRF coupled the soil thermal diffusion (STD), Rapid Update Cycle, and Noah schemes. These three land surface schemes along with CLM3 represent the different sophistication levels of land-surface schemes. CLM3 is the most sophisticated model that includes detailed snow and vegetation processes. The STD scheme is oversimplified, which only calculates soil temperature and neglects vegetation and snow physics. The sophistication level of RUC and NOAH is intermediate among the four schemes, and the major deference between them is that RUC has a multilayer snow scheme, but Noah only has one layer snow that is lumped with the top soil layer. WRF with each of these four land surface schemes was driven by the National Centers for Environmental Prediction Reanalysis data II for one-year simulation over the period of 1 October, 1995 to 30 September, 1996, with a total of four one-year simulations. These simulations have 30km-10km two-way nested domains and focus on the U.S. California region to identify the importance of land surface processes. Our analysis shows that WRF-CLM3 produces the best temperature and snow simulations over the study period that are in better agreement with observations than those generated by the other three schemes with WRF. Without snow and vegetation processes, WRFSTD produces the worst results that show dramatically overestimated surface air temperature. However, no matter what land surface scheme is chosen, WRF can reasonably reproduce the winter precipitation that is the major water resource for California, and the link between land surface processes and precipitation is not explicitly seen. In general, land-surface processes play a significant role in the simulations of regional hydro-climate processes and phenomena, and the coupling of the advanced CLM3 with WRF greatly improves the capability of WRF in predicting them.

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Mar 31st, 6:20 PM Mar 31st, 6:25 PM

Intercomparison of the Land-Surface Schemes within the Weather and Research Forecasting Model

ECC 216

The Community Land Model version 3 (CLM3) developed by the National Center for Atmospheric Research (NCAR) was coupled into the Weather Research and Forecasting (WRF) Model version 2.2. The performance of WRF-CLM3 in predicting regional climate was quantitatively compared with that of WRF coupled the soil thermal diffusion (STD), Rapid Update Cycle, and Noah schemes. These three land surface schemes along with CLM3 represent the different sophistication levels of land-surface schemes. CLM3 is the most sophisticated model that includes detailed snow and vegetation processes. The STD scheme is oversimplified, which only calculates soil temperature and neglects vegetation and snow physics. The sophistication level of RUC and NOAH is intermediate among the four schemes, and the major deference between them is that RUC has a multilayer snow scheme, but Noah only has one layer snow that is lumped with the top soil layer. WRF with each of these four land surface schemes was driven by the National Centers for Environmental Prediction Reanalysis data II for one-year simulation over the period of 1 October, 1995 to 30 September, 1996, with a total of four one-year simulations. These simulations have 30km-10km two-way nested domains and focus on the U.S. California region to identify the importance of land surface processes. Our analysis shows that WRF-CLM3 produces the best temperature and snow simulations over the study period that are in better agreement with observations than those generated by the other three schemes with WRF. Without snow and vegetation processes, WRFSTD produces the worst results that show dramatically overestimated surface air temperature. However, no matter what land surface scheme is chosen, WRF can reasonably reproduce the winter precipitation that is the major water resource for California, and the link between land surface processes and precipitation is not explicitly seen. In general, land-surface processes play a significant role in the simulations of regional hydro-climate processes and phenomena, and the coupling of the advanced CLM3 with WRF greatly improves the capability of WRF in predicting them.

https://digitalcommons.usu.edu/runoff/2008/Posters/13