Evaluation and intercomparison of multiple satellite-derived and reanalysis downward shortwave radiation products in China

Downward shortwave radiation(DSR)is a critical variable in energy balance driving Earth’s surface processes.Satellite-derived and reanalysis DSR products have been developed and continuously improved during the last decades.However,as those products have different temporal resolutions,their performances in different time scales have not been well-documented,particularly in China.This study intended to evaluate several DSR products across multiple time scales(i.e.instantaneous,1-hourly,daily,and monthly average)and ecosystems in China.Six DSR products,including GLASS,BESS,CLARA-A2,MCD18A1,ERA5 and MERRA-2,were evaluated against ground measurements at Chinese Ecosystem Research Network(CERN)and integrated land-atmosphere interaction observation(TPDC)sites from 2009 to 2012.The instantaneous DSR of MCD18 showed a root mean square error(RMSE)of 146.02 W/m^(2).The hourly RMSE of ERA5(155.52 W/m^(2))was largely smaller than MERRA-2(188.53 W/m^(2)).On the daily and monthly scale,BESS had the most optimized accuracy among the six products(RMSE of 36.82 W/m^(2)).For the satellite-derived DSR products,the monthly accuracy at CERN can meet the threshold accuracy requirement set by World Meteorological Organization(WMO)for Global Numerical Weather Prediction(20 W/m^(2)).

Influence of mesoscale eddies on primary production in the South China Sea during spring inter-monsoon period

Mesoscale eddies have been suggested to have an impact on biological carbon fixation in the South China Sea （SCS）. However, their overall contribution to primary production during the spring inter-monsoon pe riod is still unknown. Based on large-scale biological and environmental in situ observations and synchro nous remote sensing data, the distribution patterns of phytoplankton biomass and the primary production, and the role of mesoscale eddies in regulating primary production in different eddy-controlled waters were investigated. The results suggested that the surface chlorophyll a concentrations and water column inte grated primary production （IPP） are significantly higher in cyclonic eddies and lower in the anticyclonic eddies as compared to that in non-eddy waters. Although eddies could affect various environmental factors, such as nutrients, temperature and light availability, nutrient supply is suggested to be the most important one through which mesoscale eddies regulated the distribution patterns of phytoplankton biomass and pri mary production. The estimated IPP in cyclonic and anticyclonic eddies are about 29.5% higher and 16.6% lower than the total average in the whole study area, respectively, indicating that the promotion effect of mesoscale cold eddies on the primary production was much stronger than the inhibition effect of the warm eddies per unit area. Overall, mesoscale eddies are crucial physical processes that affect the biological car bon fixation and the distribution pattern of primary production in the SCS open sea, especially during the spring inter-monsoon period.

Application of Spatially Distributed Calibrated Hydrological Model in Evapotranspiration Simulation of Three Gorges Reservoir Area of China:A Case Study in the Madu River Basin

Evapotranspiration(ET)is the key to the water cycle process and an important factor for studying near-surface water and heat balance.Accurately estimating ET is significant for hydrology,meteorology,ecology,agriculture,etc..This paper simulates ET in the Madu River Basin of Three Gorges Reservoir Area of China during 2009-2018 based on the Soil and Water Assessment Tool(SWAT)model,which was calibrated and validated using the MODIS(Moderate-resolution Imaging Spectroradiometer)/Terra Net ET 8-Day L4 Global 500 m SIN Grid(MOD16A2)dataset and measured ET.Two calibration strategies(lumped calibration(LC)and spatially distributed calibration(SDC))were used.The basin was divided into 34 sub-basins,and the coefficient of determination(R^(2))and NashSutcliffe efficiency coefficient(NSE)of each sub-basin were greater than 0.6 in both the calibration and validation periods.The R2 and NSE were higher in the validation period than those in the calibration period.Compared with the measured ET,the accuracy of the model on the daily scale is:R^(2)=0.704 and NSE=0.759(SDC results).The model simulation accuracy of LC and SDC for the sub-basin scale was R^(2)=0.857,R^(2)=0.862(monthly)and R^(2)=0.227,R^(2)=0.404(annually),respectively;for the whole basin scale was R^(2)=0.902,R^(2)=0.900(monthly)and R^(2)=0.507 and R^(2)=0.519(annually),respectively.The model performed acceptably,and SDC performed the best,indicating that remote sensing data can be used for SWAT model calibration.During 2009-2018,ET generally increased in the Madu River Basin(SDC results,7.21 mm/yr),with a multiyear average value of 734.37 mm/yr.The annual ET change rate for the sub-basin was relatively low upstream and downstream.The linear correlation analysis between ET and meteorological factors shows that on the monthly scale,precipitation,solar radiation and daily maximum and minimum temperature were significantly correlated with ET;annually,solar radiation and wind speed had a moderate correlation with ET.The correlation between maximum temperature and ET is best on the monthly scale(Pearson correlation coefficient R=0.945),which may means that the increasing ET originating from increasing temperature(global warming).However,the sub-basins near Shennongjia Nature Reserve that are in upstream have a negative ET change rate,which means that ET decreases in these sub-basins,indicating that the’Evaporation Paradox’exists in these sub-basins.This study explored the potential of remote-sensing-based ET data for hydrological model calibration and provides a decision-making reference for water resource management in the Madu River Basin.

Web service for biodiversity estimation using remote sensing data

This paper presents a technique for the assessment and mapping of land biodiversity by using remote sensing data.The proposed approach uses a fuzzy model that encapsulates different ecological factors influencing biodiversity.We implemented our approach as a web service for the Pre-Black Sea region of the Ukraine.