Alpine grassland is the main ecosystem of the Tibetan Plateau(TP),thus accurate simulation of water and heat exchange in the grassland will significantly enhance the understanding of the land-atmosphere interaction pr...Alpine grassland is the main ecosystem of the Tibetan Plateau(TP),thus accurate simulation of water and heat exchange in the grassland will significantly enhance the understanding of the land-atmosphere interaction process on the TP.In this study,we assessed and improved the ensemble numerical simulations of the community Noah land surface model with multiparameterization options(Noah-MP)by using observations collected from four alpine grassland observation sites.The four observation sites belong to the upper Heihe River Basin Integrated Observatory Network located in the northeastern part of the TP.First,an ensemble of 1008 numerical simulation experiments,based on multiparameterization options of seven physical processes/variables in the Noah-MP,was carried out for the vegetation growing season.The Taylor skill score was then used to assess the model performance and select the optimal combination of parameterization options for a more exact simulation of the water and heat exchange in alpine grassland.The accuracy of Noah-MP simulation was further improved by introducing new parameterizations of thermal roughness length,soil hydraulic properties,and vertical root distribution.It was found that:(1)Simulation of water and heat exchange over alpine grassland in the growing season was mainly affected by the parameterizations of dynamic vegetation,canopy stomatal resistance,runoff and groundwater dynamics,and surface exchange coefficient for heat transfer.Selection of different parameterization options for these four physical processes/variables led to large differences in the simulation of water and heat fluxes.(2)The optimal combination of parameterization options selected in the current Noah-MP framework suffered from significant overestimation of sensible heat flux(H)and underestimation of soil moisture(θ)at all observation sites.(3)The overestimation of H was significantly improved by introducing a new parameterization of thermal roughness length.Furthermore,the underestimation ofθwas resolved by introducing a new parameterization of soil hydraulic properties that considered the organic matter effect and a new vertical distribution function for the vegetation root system.The results of this study provide an important reference for further improving the simulation of water and heat exchange by using the land surface model in alpine grassland.展开更多
Surface shortwave radiation(SSR)plays an important role in global energy systems.The new generation of geostationary meteorological satellite Himawari-8,with higher spatiotemporal and spectral resolution,offers a new ...Surface shortwave radiation(SSR)plays an important role in global energy systems.The new generation of geostationary meteorological satellite Himawari-8,with higher spatiotemporal and spectral resolution,offers a new opportunity to retrieve SSR with higher accuracy.In this study,an improved algorithm was applied to estimate instantaneous,hourly,and daily mean SSR using cloud products from the Advanced Himawari Imager(AHI)onboard the Himawari-8 satellite.The validation against Baseline Surface Radiation Network(BSRN)stations showed a root mean square error(RMSE)of 95.8 W m^(-2) for instantaneous SSR,82.4 W m^(-2) for hourly SSR,and 22.8 W m^(-2) for daily SSR and mean bias error(MBE)of-15.8 W m^(-2),-14.1 W m^(-2),and-6.6 W m^(-2).The validation against China Meteorological Administration(CMA)stations showed a RMSE of 99.5 W m^(-2) and MBE of-8.2 W m^(-2) for hourly SSR and RMSE of 27.7 W m^(-2) and MBE of-3.9 W m^(-2) for daily SSR,which are generally better than the Himawari-8 SSR product.Overall,the improved algorithm performed well on the new-generation geostationary satellite,with high accuracy and efficiency,and would contribute to surface process research and photovoltaic engineering applications.展开更多
基金supported by the National Natural Science Foundation of China(41988101 and 42171360)the National Key Research and Development Program of China(2017YFA0603604)。
基金supported by the Strategic Priority Research Program of the Chinese Academy of Sciences(Grant Nos.XDA20100101,XDA20100103)。
文摘Alpine grassland is the main ecosystem of the Tibetan Plateau(TP),thus accurate simulation of water and heat exchange in the grassland will significantly enhance the understanding of the land-atmosphere interaction process on the TP.In this study,we assessed and improved the ensemble numerical simulations of the community Noah land surface model with multiparameterization options(Noah-MP)by using observations collected from four alpine grassland observation sites.The four observation sites belong to the upper Heihe River Basin Integrated Observatory Network located in the northeastern part of the TP.First,an ensemble of 1008 numerical simulation experiments,based on multiparameterization options of seven physical processes/variables in the Noah-MP,was carried out for the vegetation growing season.The Taylor skill score was then used to assess the model performance and select the optimal combination of parameterization options for a more exact simulation of the water and heat exchange in alpine grassland.The accuracy of Noah-MP simulation was further improved by introducing new parameterizations of thermal roughness length,soil hydraulic properties,and vertical root distribution.It was found that:(1)Simulation of water and heat exchange over alpine grassland in the growing season was mainly affected by the parameterizations of dynamic vegetation,canopy stomatal resistance,runoff and groundwater dynamics,and surface exchange coefficient for heat transfer.Selection of different parameterization options for these four physical processes/variables led to large differences in the simulation of water and heat fluxes.(2)The optimal combination of parameterization options selected in the current Noah-MP framework suffered from significant overestimation of sensible heat flux(H)and underestimation of soil moisture(θ)at all observation sites.(3)The overestimation of H was significantly improved by introducing a new parameterization of thermal roughness length.Furthermore,the underestimation ofθwas resolved by introducing a new parameterization of soil hydraulic properties that considered the organic matter effect and a new vertical distribution function for the vegetation root system.The results of this study provide an important reference for further improving the simulation of water and heat exchange by using the land surface model in alpine grassland.
基金funded by the National Natural Science Foundation of China(grant number 42171360)the National Key Research and Development Program of China(grant number 2017YFA0603604).
文摘Surface shortwave radiation(SSR)plays an important role in global energy systems.The new generation of geostationary meteorological satellite Himawari-8,with higher spatiotemporal and spectral resolution,offers a new opportunity to retrieve SSR with higher accuracy.In this study,an improved algorithm was applied to estimate instantaneous,hourly,and daily mean SSR using cloud products from the Advanced Himawari Imager(AHI)onboard the Himawari-8 satellite.The validation against Baseline Surface Radiation Network(BSRN)stations showed a root mean square error(RMSE)of 95.8 W m^(-2) for instantaneous SSR,82.4 W m^(-2) for hourly SSR,and 22.8 W m^(-2) for daily SSR and mean bias error(MBE)of-15.8 W m^(-2),-14.1 W m^(-2),and-6.6 W m^(-2).The validation against China Meteorological Administration(CMA)stations showed a RMSE of 99.5 W m^(-2) and MBE of-8.2 W m^(-2) for hourly SSR and RMSE of 27.7 W m^(-2) and MBE of-3.9 W m^(-2) for daily SSR,which are generally better than the Himawari-8 SSR product.Overall,the improved algorithm performed well on the new-generation geostationary satellite,with high accuracy and efficiency,and would contribute to surface process research and photovoltaic engineering applications.
