在Liu and Kalnay（2008）的研究基础上,将基于集合的观测资料影响性评价方法（简称LK08法）运用到一个简单的大气环流模式中,对模拟探空资料的预报影响性进行了综合评价,考察了LK08法在真实大气环流模式上的适用性。研究结果表明,应用...在Liu and Kalnay（2008）的研究基础上,将基于集合的观测资料影响性评价方法（简称LK08法）运用到一个简单的大气环流模式中,对模拟探空资料的预报影响性进行了综合评价,考察了LK08法在真实大气环流模式上的适用性。研究结果表明,应用基于集合的评价方法可以一次性计算出同化系统中每个观测的影响性,然后按观测手段、观测区域等进行影响性数值的简单累加,以此可以比较不同类型观测的相对影响性。比较结果显示,不同半球的模拟探空观测对预报的总影响性相差不大,但由于南半球资料个数要远远少于北半球,因此,南半球单个观测的影响性要大于北半球的单个观测。不同观测类型对预报的总影响性也不相同。有效性验证分析表明,按LK08法计算得到的总体观测影响性能解释实际影响性的70%~80%,且很好地抓住了其变化和走势。展开更多
In this paper we investigate the impact of the Atmospheric Infra-Red Sounder (AIRS) temperature retrievals on data assimilation and the resulting forecasts using the four-dimensional Local Ensemble Transform Kalman Fi...In this paper we investigate the impact of the Atmospheric Infra-Red Sounder (AIRS) temperature retrievals on data assimilation and the resulting forecasts using the four-dimensional Local Ensemble Transform Kalman Filter (LETKF) data assimilation scheme and a reduced resolution version of the NCEP Global Forecast System (GFS).Our results indicate that the AIRS temperature retrievals have a significant and consistent positive impact in the Southern Hemispheric extratropics on both analyses and forecasts,which is found not only in the temperature field but also in other variables.In tropics and the Northern Hemispheric extratropics these impacts are smaller,but are still generally positive or neutral.展开更多
The ensemble based forecast sensitivity to observation method by Liu and Kalnay is applied to the SPEEDY-LETKF system to estimate the observation impact of three types of simulated observations.The estimation results ...The ensemble based forecast sensitivity to observation method by Liu and Kalnay is applied to the SPEEDY-LETKF system to estimate the observation impact of three types of simulated observations.The estimation results show that all types of observations have positive impact on short-range forecast.The largest impact in Northern Hemisphere is produced by rawinsondes,followed by satellite retrieved profiles and cloud drift wind data,which in Southern Hemisphere is produced by satellite retrieved profiles,rawinsondes and cloud drift wind data.Satellite retrieved profiles influence more on the Southern Hemisphere than on the Northern Hemisphere due to few observations from rawinsondes in the Southern Hemisphere.At the level of 200 to 300 h Pa,the largest impact is attributed to wind observations from rawinsondes and cloud drift wind.展开更多
Information on the spatial and temporal patterns of surface carbon flux is crucial to understanding of source/sink mechanisms and projection of future atmospheric CO2 concentrations and climate. This study presents th...Information on the spatial and temporal patterns of surface carbon flux is crucial to understanding of source/sink mechanisms and projection of future atmospheric CO2 concentrations and climate. This study presents the construction and implementation of a terrestrial carbon cycle data assimilation system based on a dynamic vegetation and terrestrial carbon model Vegetation-Global-Atmosphere-Soil(VEGAS) with an advanced assimilation algorithm, the local ensemble transform Kalman filter(LETKF, hereafter LETKF-VEGAS). An observing system simulation experiment(OSSE) framework was designed to evaluate the reliability of this system, and numerical experiments conducted by the OSSE using leaf area index(LAI) observations suggest that the LETKF-VEGAS can improve the estimations of leaf carbon pool and LAI significantly, with reduced root mean square errors and increased correlation coefficients with true values, as compared to a control run without assimilation. Furthermore, the LETKF-VEGAS has the potential to provide more accurate estimations of the net primary productivity(NPP) and carbon flux to atmosphere(CFta).展开更多
文摘在Liu and Kalnay（2008）的研究基础上,将基于集合的观测资料影响性评价方法（简称LK08法）运用到一个简单的大气环流模式中,对模拟探空资料的预报影响性进行了综合评价,考察了LK08法在真实大气环流模式上的适用性。研究结果表明,应用基于集合的评价方法可以一次性计算出同化系统中每个观测的影响性,然后按观测手段、观测区域等进行影响性数值的简单累加,以此可以比较不同类型观测的相对影响性。比较结果显示,不同半球的模拟探空观测对预报的总影响性相差不大,但由于南半球资料个数要远远少于北半球,因此,南半球单个观测的影响性要大于北半球的单个观测。不同观测类型对预报的总影响性也不相同。有效性验证分析表明,按LK08法计算得到的总体观测影响性能解释实际影响性的70%~80%,且很好地抓住了其变化和走势。
基金National Natural Science Foundation of China (40975067)973 Program (2009CB421500)+1 种基金CMA Grant GYHY200806029NASA grant NNX07AM97G in U.S.A
文摘In this paper we investigate the impact of the Atmospheric Infra-Red Sounder (AIRS) temperature retrievals on data assimilation and the resulting forecasts using the four-dimensional Local Ensemble Transform Kalman Filter (LETKF) data assimilation scheme and a reduced resolution version of the NCEP Global Forecast System (GFS).Our results indicate that the AIRS temperature retrievals have a significant and consistent positive impact in the Southern Hemispheric extratropics on both analyses and forecasts,which is found not only in the temperature field but also in other variables.In tropics and the Northern Hemispheric extratropics these impacts are smaller,but are still generally positive or neutral.
基金National Natural Science Foundation of China(41575107,40975067)973 Program(2013CB430305)+1 种基金Project of Shanghai Meteorological Bureau(YJ201401)National Programme on Global Change and Air-Sea Interaction(GASI-IPOVAI-04)
文摘The ensemble based forecast sensitivity to observation method by Liu and Kalnay is applied to the SPEEDY-LETKF system to estimate the observation impact of three types of simulated observations.The estimation results show that all types of observations have positive impact on short-range forecast.The largest impact in Northern Hemisphere is produced by rawinsondes,followed by satellite retrieved profiles and cloud drift wind data,which in Southern Hemisphere is produced by satellite retrieved profiles,rawinsondes and cloud drift wind data.Satellite retrieved profiles influence more on the Southern Hemisphere than on the Northern Hemisphere due to few observations from rawinsondes in the Southern Hemisphere.At the level of 200 to 300 h Pa,the largest impact is attributed to wind observations from rawinsondes and cloud drift wind.
基金supported by the National Natural Science Foundation of China (Grant No. 41305066)the Special Funds for Public Welfare of China (Grant No. GYHY201306045)the National Basic Research Program of China (Grant Nos. 2010CB951101 and 2010CB428403)
文摘Information on the spatial and temporal patterns of surface carbon flux is crucial to understanding of source/sink mechanisms and projection of future atmospheric CO2 concentrations and climate. This study presents the construction and implementation of a terrestrial carbon cycle data assimilation system based on a dynamic vegetation and terrestrial carbon model Vegetation-Global-Atmosphere-Soil(VEGAS) with an advanced assimilation algorithm, the local ensemble transform Kalman filter(LETKF, hereafter LETKF-VEGAS). An observing system simulation experiment(OSSE) framework was designed to evaluate the reliability of this system, and numerical experiments conducted by the OSSE using leaf area index(LAI) observations suggest that the LETKF-VEGAS can improve the estimations of leaf carbon pool and LAI significantly, with reduced root mean square errors and increased correlation coefficients with true values, as compared to a control run without assimilation. Furthermore, the LETKF-VEGAS has the potential to provide more accurate estimations of the net primary productivity(NPP) and carbon flux to atmosphere(CFta).
