The ability to estimate terrestrial water storage(TWS)is essential for monitoring hydrological extremes(e.g.,droughts and floods)and predicting future changes in the hydrological cycle.However,inadequacies in model ph...The ability to estimate terrestrial water storage(TWS)is essential for monitoring hydrological extremes(e.g.,droughts and floods)and predicting future changes in the hydrological cycle.However,inadequacies in model physics and parameters,as well as uncertainties in meteorological forcing data,commonly limit the ability of land surface models(LSMs)to accurately simulate TWS.In this study,the authors show how simulations of TWS anomalies(TWSAs)from multiple meteorological forcings and multiple LSMs can be combined in a Bayesian model averaging(BMA)ensemble approach to improve monitoring and predictions.Simulations using three forcing datasets and two LSMs were conducted over China's Mainland for the period 1979–2008.All the simulations showed good temporal correlations with satellite observations from the Gravity Recovery and Climate Experiment during 2004–08.The correlation coefficient ranged between 0.5 and 0.8 in the humid regions(e.g.,the Yangtze river basin,Huaihe basin,and Zhujiang basin),but was much lower in the arid regions(e.g.,the Heihe basin and Tarim river basin).The BMA ensemble approach performed better than all individual member simulations.It captured the spatial distribution and temporal variations of TWSAs over China's Mainland and the eight major river basins very well;plus,it showed the highest R value(>0.5)over most basins and the lowest root-mean-square error value(<40 mm)in all basins of China.The good performance of the BMA ensemble approach shows that it is a promising way to reproduce long-term,high-resolution spatial and temporal TWSA data.展开更多
Based on satellite data and the estimated inversion strength(EIS) derived by Wood et al.(2006), a feasible and uncomplicated stratocumulus scheme is proposed, referred to as EIS scheme. It improves simulation of cloud...Based on satellite data and the estimated inversion strength(EIS) derived by Wood et al.(2006), a feasible and uncomplicated stratocumulus scheme is proposed, referred to as EIS scheme. It improves simulation of cloud radiative forcing(CRF) in the Grid-point Atmospheric Model of IAP/LASG version 2(GAMIL2.0) model. When compared with the original lower troposphere stability(LTS) scheme, the EIS scheme reproduces more reasonable climatology distributions of clouds and CRF. The parameterization partly corrects CRF underestimation at mid and high latitudes and overestimation in the convective region. Such improvements are achieved by neglecting the effect of free-tropospheric stratification changes that follow a cooler moist adiabat at middle and high latitude, thereby improving simulated cloudiness. The EIS scheme also improves simulation of the CRF interannual variability. The positive net CRF and negative stratiform anomaly in the East Asian and western North Pacific monsoon regions(EAWNPMR) are well simulated. The EIS scheme is more sensitive to sea surface temperature anomalies(SSTA) than the LTS. Therefore, under the effect of a warmer SSTA in the EAWNPMR, the EIS generates a stronger negative stratiform response, which reduces radiative heating in the low and mid troposphere, in turn producing strong subsidence and negative anomalies of both moisture and cloudiness. Consequent decreases in cloud reflection and shading effects ultimately improve simulation of incoming surface shortwave radiative fluxes and CRF. Because of the stronger subsidence, a stronger anomalous anticyclone over the Philippines Sea is simulated by the EIS run, which leads to a better positive precipitation anomaly in eastern China during ENSO winter.展开更多
基金supported by the National Natural Science Foundation of China(Grant Nos.41405083 and 91437220)the Natural Science Foundation of Hunan Province,China(Grant No.2015JJ3098)+1 种基金the Key Research Program of Frontier Sciences,CAS(QYZDY-SSW-DQC012)the Fund Project for The Education Department of Hunan Province(Grant No.16A234)
文摘The ability to estimate terrestrial water storage(TWS)is essential for monitoring hydrological extremes(e.g.,droughts and floods)and predicting future changes in the hydrological cycle.However,inadequacies in model physics and parameters,as well as uncertainties in meteorological forcing data,commonly limit the ability of land surface models(LSMs)to accurately simulate TWS.In this study,the authors show how simulations of TWS anomalies(TWSAs)from multiple meteorological forcings and multiple LSMs can be combined in a Bayesian model averaging(BMA)ensemble approach to improve monitoring and predictions.Simulations using three forcing datasets and two LSMs were conducted over China's Mainland for the period 1979–2008.All the simulations showed good temporal correlations with satellite observations from the Gravity Recovery and Climate Experiment during 2004–08.The correlation coefficient ranged between 0.5 and 0.8 in the humid regions(e.g.,the Yangtze river basin,Huaihe basin,and Zhujiang basin),but was much lower in the arid regions(e.g.,the Heihe basin and Tarim river basin).The BMA ensemble approach performed better than all individual member simulations.It captured the spatial distribution and temporal variations of TWSAs over China's Mainland and the eight major river basins very well;plus,it showed the highest R value(>0.5)over most basins and the lowest root-mean-square error value(<40 mm)in all basins of China.The good performance of the BMA ensemble approach shows that it is a promising way to reproduce long-term,high-resolution spatial and temporal TWSA data.
基金supported by the National Natural Science Foundation of China(Grant No.41125017)the National Basic Research Program of China(Grant No.2010CB951904)
文摘Based on satellite data and the estimated inversion strength(EIS) derived by Wood et al.(2006), a feasible and uncomplicated stratocumulus scheme is proposed, referred to as EIS scheme. It improves simulation of cloud radiative forcing(CRF) in the Grid-point Atmospheric Model of IAP/LASG version 2(GAMIL2.0) model. When compared with the original lower troposphere stability(LTS) scheme, the EIS scheme reproduces more reasonable climatology distributions of clouds and CRF. The parameterization partly corrects CRF underestimation at mid and high latitudes and overestimation in the convective region. Such improvements are achieved by neglecting the effect of free-tropospheric stratification changes that follow a cooler moist adiabat at middle and high latitude, thereby improving simulated cloudiness. The EIS scheme also improves simulation of the CRF interannual variability. The positive net CRF and negative stratiform anomaly in the East Asian and western North Pacific monsoon regions(EAWNPMR) are well simulated. The EIS scheme is more sensitive to sea surface temperature anomalies(SSTA) than the LTS. Therefore, under the effect of a warmer SSTA in the EAWNPMR, the EIS generates a stronger negative stratiform response, which reduces radiative heating in the low and mid troposphere, in turn producing strong subsidence and negative anomalies of both moisture and cloudiness. Consequent decreases in cloud reflection and shading effects ultimately improve simulation of incoming surface shortwave radiative fluxes and CRF. Because of the stronger subsidence, a stronger anomalous anticyclone over the Philippines Sea is simulated by the EIS run, which leads to a better positive precipitation anomaly in eastern China during ENSO winter.
