Based on the hourly observational data during 2007-2016 from surface meteorological stations in China,this paper compares the influence of 3-hourly precipitation data,mainly from the Chinese Reanalysis-Interim(CRA-Int...Based on the hourly observational data during 2007-2016 from surface meteorological stations in China,this paper compares the influence of 3-hourly precipitation data,mainly from the Chinese Reanalysis-Interim(CRA-Interim),ECMWF Reanalysis 5(ERA5)and Japanese Reanalysis-55(JRA-55),on the simulation of the spatial and temporal distribution of regional precipitation in China and the bias distribution of the simulation.The results show that:(1)The three sets of reanalysis datasets can all reflect the basic spatial distribution characteristics of annual average precipitation in China.The simulation of topographic forced precipitation in complex terrain by using CRA-interim is more detailed,while CRA-interim has larger negative bias in central and East China,and larger positive bias in southwest China.(2)In terms of seasonal precipitation,the three sets of reanalysis datasets overestimate the precipitation in the heavy rainfall zone in spring and summer,especially in southwest China.According to CRA-interim,location of the rain belt in the First Rainy Season in South China is west by south,and the summer precipitation has positive bias in southwest and South China.(3)All of the reanalysis datasets can basically reflect the distribution difference of inter-annual variation of drought and flood,but overall the CRA-Interim generally shows negative bias,while the ERA5 and JRA-55 exhibit positive bias.(4)For the diurnal variation of precipitation in summer,all the reanalysis datasets perform better in simulating the daytime precipitation than in the night,and the bias of CRA-interim is less in the Southeast and Northeast than elsewhere.(5)The ERA5 generally performs the best on the evaluation of quantitative precipitation forecast,the JRA-55 is the next,followed by the CRA-Interim.The CRA-Interim has higher missing rate and lower threat score for heavy rains;however,at the level of downpour,the CRA-Interim performs slightly better.展开更多
The spatial and temporal distributions of the stable isotopes such as HD16O (or 1H2H16O, or HDO) and H2 18O in atmospheric water vapor are related to evaporation in source places, vapor condensation during transport...The spatial and temporal distributions of the stable isotopes such as HD16O (or 1H2H16O, or HDO) and H2 18O in atmospheric water vapor are related to evaporation in source places, vapor condensation during transport, and vapor convergence and divergence, and thus provide useful information for investigation and understanding of the global water cycle. This paper analyzes spatiotemporal variations of the content of iso- tope HDO (i.e., 5D), in atmospheric water vapor, namely, δDv, and the relationship of δDv with atmospheric humidity and temperature at different levels in the troposphere, using the HDO and H2O data retrieved from the Tropospheric Emission Spectrometer (TES) at seven pressure levels from 825 to 100 hPa. The results indicate that δDv has a clear zonal distribution in the troposphere and a good correspondence with atmospheric precipitable water. The results also show that δDv decreases logarithmically with atmospheric pressure and presents a decreasing trend from the equator to high latitudes and from lands to oceans. Sea- sonal changes of δDv exhibit regional differences. The spatial distribution and seasonal variation of δDv in the low troposphere are consistent with those in the middle troposphere, but opposite situations occur from the upper troposphere to the lower stratosphere. The correlation between δDv and temperature has a similar distribution pattern to the correlation between δDv and precipitable water in the troposphere. The stable isotope HDO in water vapor (δDv), compared with that in precipitation (δDp), is of some differences in spatial distribution and seasonal variation, and in its relationship with temperature and humidity, in- dicating that the impacts of stable isotopic fractionation and atmospheric circulation on the two types of stable isotopes are different.展开更多
基金National Natural Science Foundation of China(42030611,91937301)Second Tibetan Plateau Scientific Expedition and Research(STEP)Program(2019QZKK0105)。
文摘Based on the hourly observational data during 2007-2016 from surface meteorological stations in China,this paper compares the influence of 3-hourly precipitation data,mainly from the Chinese Reanalysis-Interim(CRA-Interim),ECMWF Reanalysis 5(ERA5)and Japanese Reanalysis-55(JRA-55),on the simulation of the spatial and temporal distribution of regional precipitation in China and the bias distribution of the simulation.The results show that:(1)The three sets of reanalysis datasets can all reflect the basic spatial distribution characteristics of annual average precipitation in China.The simulation of topographic forced precipitation in complex terrain by using CRA-interim is more detailed,while CRA-interim has larger negative bias in central and East China,and larger positive bias in southwest China.(2)In terms of seasonal precipitation,the three sets of reanalysis datasets overestimate the precipitation in the heavy rainfall zone in spring and summer,especially in southwest China.According to CRA-interim,location of the rain belt in the First Rainy Season in South China is west by south,and the summer precipitation has positive bias in southwest and South China.(3)All of the reanalysis datasets can basically reflect the distribution difference of inter-annual variation of drought and flood,but overall the CRA-Interim generally shows negative bias,while the ERA5 and JRA-55 exhibit positive bias.(4)For the diurnal variation of precipitation in summer,all the reanalysis datasets perform better in simulating the daytime precipitation than in the night,and the bias of CRA-interim is less in the Southeast and Northeast than elsewhere.(5)The ERA5 generally performs the best on the evaluation of quantitative precipitation forecast,the JRA-55 is the next,followed by the CRA-Interim.The CRA-Interim has higher missing rate and lower threat score for heavy rains;however,at the level of downpour,the CRA-Interim performs slightly better.
基金Supported by the National Natural Science Foundation of China (40871094 and 41171035)Construction Program of the Key Discipline in Hunan Province (2012001)+1 种基金Open Fund of Key Laboratory of Tibetan Environment Changes and Land Surface Processes of the Chinese Academy of Sciences (2011004)Scientific Research Fund of Hunan Provincial Education Department (09A056)
文摘The spatial and temporal distributions of the stable isotopes such as HD16O (or 1H2H16O, or HDO) and H2 18O in atmospheric water vapor are related to evaporation in source places, vapor condensation during transport, and vapor convergence and divergence, and thus provide useful information for investigation and understanding of the global water cycle. This paper analyzes spatiotemporal variations of the content of iso- tope HDO (i.e., 5D), in atmospheric water vapor, namely, δDv, and the relationship of δDv with atmospheric humidity and temperature at different levels in the troposphere, using the HDO and H2O data retrieved from the Tropospheric Emission Spectrometer (TES) at seven pressure levels from 825 to 100 hPa. The results indicate that δDv has a clear zonal distribution in the troposphere and a good correspondence with atmospheric precipitable water. The results also show that δDv decreases logarithmically with atmospheric pressure and presents a decreasing trend from the equator to high latitudes and from lands to oceans. Sea- sonal changes of δDv exhibit regional differences. The spatial distribution and seasonal variation of δDv in the low troposphere are consistent with those in the middle troposphere, but opposite situations occur from the upper troposphere to the lower stratosphere. The correlation between δDv and temperature has a similar distribution pattern to the correlation between δDv and precipitable water in the troposphere. The stable isotope HDO in water vapor (δDv), compared with that in precipitation (δDp), is of some differences in spatial distribution and seasonal variation, and in its relationship with temperature and humidity, in- dicating that the impacts of stable isotopic fractionation and atmospheric circulation on the two types of stable isotopes are different.