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Evaluation of Daily Precipitation Product in China from the CMA Global Atmospheric Interim Reanalysis

Journal of Meteorological Research 2020年第1期34卷 117-136,1-4页

作者： chunxiang LI Tianbao ZHAO chunxiang shi Zhiquan LIU Key Laboratory of Regional Climate-Environment Research for East Asia Institute of Atmospheric PhysicsChinese Academy of SciencesBeijing 100029 National Meteorological Information Center China Meteorological AdministrationBeijing 100081

The China Meteorological Administration(CMA)recently produced a CMA Global Atmospheric Interim Reanalysis(CRAI)dataset for the years 2007–2016.A comprehensive evaluation of the ability of CRAI to capture the spatiotemporal variability of observed precipitation,in terms of both mean states and extreme indicators over China,is *** are made with other current reanalysis datasets,namely,the ECMWF interim reanalysis(ERAI),Japanese 55-yr reanalysis(JRA55),NCEP Climate Forecast System Reanalysis(CFSR),and NASA Modern-Era Retrospective analysis for Research and Applications version 2(MERRA2),as well as NCEP Climate Prediction Center(CPC)*** results show that,for daily variations of rainfall during warm seasons in eastern China,CRAI and CFSR overestimate the precipitation of the main rain belt,while the overestimation is confined to the area south of 25°N in JRA55 but north of 24°N in MERRA2;whereas ERAI tends to underestimate the precipitation in most regions of eastern *** extreme metrics,the total amount of precipitation on days where daily precipitation exceeds the 95 th percentile(R95 pTOT)and the number of consecutive dry days(CDDs)in one month,are examined to assess the performance of reanalysis *** terms of extreme events,CRAI,ERAI,and JRA55 tend to underestimate the R95 pTOT in most of eastern China,whereas more frequent extreme rainfall can be found in most regions of China in both CFSR and MERRA2;and all of the reanalyses underestimate the *** the reanalysis products,CRAI and JRA55 show better agreement with the observed R95 pTOT than the other datasets,with fewer biases,higher correlation coefficients,and much more similar linear trend patterns,while ERAI stands out in better capturing the amount and temporal variations of the observed CDDs.

关键词： China Meteorological Administration(CMA) the CMA Global Atmospheric Interim Reanalysis(CRAI) precipitation daily

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Fusion of In-Situ Soil Moisture and Land Surface Model Estimates Using Localized Ensemble Optimum Interpolation over China

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Journal of Meteorological Research 2020年第6期34卷 1335-1346页

作者： Lipeng JIANG chunxiang shi Shuai SUN Xiao LIANG School of Geographic Sciences Nanjing University of Information Science&TechnologyNanjing 210044 National Meteorological Information Center China Meteorological AdministrationBeijing 100081

Land data assimilation(DA)is an effective method to provide high-quality spatially and temporally continuous soil moisture datasets that are crucial in weather,climate,hydrological,and agricultural ***,most existing land DA applications have used remote sensing observations,and are based on one-dimensional(1 D)analysis,which cannot be directly employed to reasonably assimilate the recently expanded in-situ soil moisture observations in *** this paper,a two-dimensional(2 D)localized ensemble-based optimum interpolation(En OI)scheme for assimilating in-situ soil moisture observations from over 2200 stations into land surface models(LSMs)is *** scheme uses historical LSM simulations as ensemble samples to provide soil moisture background error covariance,allowing the in-situ observation information to be propagated to surrounding *** is also computationally efficient because no additional ensemble simulations are needed.A set of ensemble sampling and localization length scale sensitivity experiments are *** En OI performs best for in-situ soil moisture fusion over China with an ensemble sampling of hourly soil moisture from the previous 7 days and a localization length scale of 100 *** the evaluation,simulations for in-situ soil moisture fusion are also performed from May 2016 to September *** En OI analysis is notably better than that without in-situ observation fusion,as the wet bias of 0.02 m3 m-3 is removed,the root-mean-square error(RMSE)is reduced by about 37%,and the correlation coefficient is increased by about 25%.Independent evaluation shows that the En OI analysis performs considerably better than that without fusion in terms of bias,and marginally better in terms of RMSE and correlation.

关键词： soil moisture fusion land surface model(LSM) ensemble optimum interpolation localization

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A New Temperature Channel Selection Method Based on Singular Spectrum Analysis for Retrieving Atmospheric Temperature Profiles from FY-4A/GIIRS

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Advances in Atmospheric Sciences 2020年第7期37卷 735-750页

作者： Peipei YU chunxiang shi Ling YANG Shuai SHAN College of Electronic Engineering Chengdu University of Information TechnologyChengdu 610225China CMA Key Laboratory of Atmospheric Sounding Chengdu 610225China National Meteorological Information Center Beijing 100081China College of Geographic Sciences Nanjing University of Information Science and TechnologyNanjing 210044China

Hyperspectral data have important research and application value in the fields of meteorology and remote *** the goal of improving retrievals of atmospheric temperature profiles,this paper outlines a novel temperature channel selection method based on singular spectrum analysis(SSA)for the Geostationary Interferometric Infrared Sounder(GIIRS),which is the first infrared sounder operating in geostationary *** method possesses not only the simplicity and rapidity of the principal component analysis method,but also the interpretability of the conventional channel selection *** novel SSA method is used to decompose the GIIRS observed infrared brightness temperature spectrum(700-1130 cm-1),and the reconstructed grouped components can be obtained to reflect the energy variations in the temperature-sensitive waveband of the respective *** 700-780 cm-1,the channels selected using our method perform better than IASI(Infrared Atmospheric Sounding Interferometer)and Cr IS(Cross-track Infrared Sounder)temperature channels when used as inputs to the neural network retrieval model.

关键词： meteorology Infrared spectrum

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A soil moisture assimilation scheme based on the ensemble Kalman filter using microwave brightness temperature

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Science China Earth Sciences 2009年第11期52卷 1835-1848页

作者： BingHao Jia ZhengHui Xie XiangJun Tian chunxiang shi ICCES/LASG Institute of Atmospheric Physics Chinese Academy of Sciences Beijing 100029 China Graduate University of Chinese Academy of Sciences Beijing 100049 China National Satellite Meteorological Center China Meteorological Administration Beijing 100081 China

This study presents a soil moisture assimilation scheme, which could assimilate microwave brightness temperature directly, based on the ensemble Kalman filter and the shuffled complex evolution method (SCE-UA). It uses the soil water model of the land surface model CLM3.0 as the forecast operator, and a radiative transfer model (RTM) as the observation operator in the assimilation system. The assimilation scheme is implemented in two phases: the parameter calibration phase and the pure soil moisture assimilation phase. The vegetation optical thickness and surface roughness parameters in the RTM are calibrated by SCE-UA method and the optimal parameters are used as the final model parameters of the observation operator in the assimilation phase. The ideal experiments with synthetic data indicate that this scheme could significantly improve the simulation of soil moisture at the surface layer. Further- more, the estimation of soil moisture in the deeper layers could also be improved to a certain extent. The real assimilation experiments with AMSR-E brightness temperature at 10.65 GHz (vertical polariza- tion) show that the root mean square error (RMSE) of soil moisture in the top layer (0―10 cm) by as- similation is 0.03355 m3·m-3, which is reduced by 33.6% compared with that by simulation (0.05052 m3·m-3). The mean RMSE by assimilation for the deeper layers (10―50 cm) is also reduced by 20.9%. All these experiments demonstrate the reasonability of the assimilation scheme developed in this study.

关键词： land data assimilation soil moisture ensemble Kalman filter SCE-UA method radiative transfer model AMSR-E

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Improved Assimilation of Fengyun-3 Satellite-Based Snow Cover Fraction in Northeastern China

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Journal of Meteorological Research 2019年第5期33卷 960-975页

作者： Shuai ZHANG chunxiang shi Runping SHEN Jie WU School of Geographic Sciences Nanjing University of Information Science&TechnologyNanjing 210044 National Meteorological Information Center China Meteorological AdministrationBeijing 100081 Laboratory for Climate Studies National Climate CenterChina Meteorological AdministrationBeijing 100081

Assimilation of snow cover is an important method to improve the accuracy of snow simulation. However, the effects of snow assimilation are poor because satellite observed snow cover data contain erroneous information, such as cloud contamination. In this paper, an improved approach is proposed to reduce the effects of observational errors during assimilation of snow cover fraction acquired by the Fengyun-3(FY-3) satellite in northeastern China. A snow depth constraint was imposed on quality control of a snow depth product from a microwave radiation imager. The assimilation experiments were carried out before and after quality control(denoted as SCFDA and SCFDA_WSD, respectively). The snow cover fraction results were evaluated against the Moderate Resolution Imaging Spectroradiometer(MODIS) snow cover products. When assimilating the snow cover fraction with the snow depth constraint(i.e., SCFDA_WSD), substantially larger improvement was obtained than that without such a constraint/quality control(SCFDA), and the deviation and root mean square error of the snow cover fraction were significantly *** assimilation performance was also evaluated against in-situ snow depth observations. The SCFDA_WSD also showed greater improvements during the snow accumulation and snowmelt periods than the SCFDA. The SCFDA_WSD improvements in woodland and shrubland were the most obvious. At different altitudes, the effects of the SCFDA_WSD were basically equivalent, and the deeper the snow depth was, the better the effect. In addition, the SCFDA_WSD method was found in close agreement with the observations during a sudden snowfall event.

关键词： snow cover assimilation FY-3 satellite-based snow products snow cover fraction

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Ensemble Simulation of Land Evapotranspiration in China Based on a Multi-Forcing and Multi-Model Approach

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Advances in Atmospheric Sciences 2016年第6期33卷 673-684页

作者： Jianguo LIU Binghao JIA Zhenghui XIE chunxiang shi High Performance Computing Center School of Mathematics and Computational ScienceHuaihua University State Key Laboratory of Numerical Modeling for Atmospheric Sciences and Geophysical Fluid Dynamics Institute of Atmospheric PhysicsChinese Academy of Sciences National Meteorological Information Center China Meteorological Administration

In order to reduce the uncertainty of offline land surface model （LSM） simulations of land evapotranspiration （ET）, we used ensemble simulations based on three meteorological forcing datasets [Princeton, ITPCAS （Institute of Tibetan Plateau Research, Chinese Academy of Sciences）, Qian] and four LSMs （BATS, VIC, CLM3.0 and CLM3.5）, to explore the trends and spatiotemporal characteristics of ET, as well as the spatiotemporal pattern of ET in response to climate factors over China's Mainland during 1982-2007. The results showed that various simulations of each member and their arithmetic mean （EnsAVlean） could capture the spatial distribution and seasonal pattern of ET sufficiently well, where they exhibited more significant spatial and seasonal variation in the ET compared with observation-based ET estimates （Obs_MTE）. For the mean annual ET, we found that the BATS forced by Princeton forcing overestimated the annual mean ET compared with Obs_MTE for most of the basins in China, whereas the VIC forced by Princeton forcing showed underestimations. By contrast, the Ens_Mean was closer to Obs_MTE, although the results were underestimated over Southeast China. Furthermore, both the Obs_MTE and Ens_Mean exhibited a significant increasing trend during 1982-98; whereas after 1998, when the last big EI Nifio event occurred, the Ens_Mean tended to decrease significantly between 1999 and 2007, although the change was not significant for Obs_MTE. Changes in air temperature and shortwave radiation played key roles in the long-term variation in ET over the humid area of China, but precipitation mainly controlled the long-term variation in ET in arid and semi-arid areas of China.

关键词： land evapotranspiration ensemble simulations multi-forcing and multi-model approach spatiotemporal varia-tion uncertainty

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China land soil moisture EnKF data assimilation based on satellite remote sensing data

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Science China Earth Sciences 2011年第9期54卷 1430-1440页

作者： shi chunxiang XIE ZhengHui QIAN Hui LIANG MiaoLing YANG XiaoChun National Satellite Meteorological Center China Meteorological Administration Beijing 100081 China Institute of Atmospheric Physics Chinese Academy of Sciences Beijing 100029 China Institute of Geology Chinese Academy of Geological Sciences Key Geodynamics Laboratory the Ministry of Land and Resources Beijing 100037 China National Meteorological Center China Meteorological Administration Beijing 100081 China

Soil moisture plays an important role in land-atmosphere interactions. It is an important geophysical parameter in research on climate, hydrology, agriculture, and forestry. Soil moisture has important climatic effects by influencing ground evapotranspi ration, runoff, surface reflectivity, surface emissivity, surface sensible heat and latent heat flux. At the global scale, the extent of its influence on the atmosphere is second only to that of sea surface temperature. At the terrestrial scale, its influence is even greater than that of sea surface temperatures. This paper presents a China Land Soil Moisture Data Assimilation System (CLSMDAS) based on EnKF and land process models, and results of the application of this system in the China Land Soil Moisture Data Assimilation tests. CLSMDAS is comprised of the following components: 1) A land process mo del—Community Land Model Version 3.0 (CLM3.0)—developed by the US National Center for Atmospheric Research (NCAR); 2) Precipitation of atmospheric forcing data and surface-incident solar radiation data come from hourly outputs of the FY2 geostationary meteorological satellite; 3) EnKF (Ensemble Kalman Filter) land data assimilation method; and 4) Observa tion data including satellite-inverted soil moisture outputs of the AMSR-E satellite and soil moisture observation data. Results of soil moisture assimilation tests from June to September 2006 were analyzed with CLSMDAS. Both simulation and assimila tion results of the land model reflected reasonably the temporal-spatial distribution of soil moisture. The assimilated soil mois ture distribution matches very well with severe summer droughts in Chongqing and Sichuan Province in August 2006, the worst since the foundation of the People’s Republic of China in 1949. It also matches drought regions that occurred in eastern Hubei and southern Guangxi in September.

关键词： EnKF land data assimilation AMSR-E soil moisture FY2C geostationary satellite high-resolution precipitation surface incident solar radiation

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Comparison of the Global Energy Cycle between Chinese Reanalysis Interim and ECMWF Reanalysis

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Journal of Meteorological Research 2019年第3期33卷 563-575页

作者： Bin ZHAO Bo ZHANG chunxiang shi Jingwei LIU Lipeng JIANG National Meteorological Center China Meteorological Administration Beijing 100081 China Meteorological Administration Numerical Weather Prediction Center Beijing 100081 National Meteorological Information Center China Meteorological Administration Beijing 100081

The global energy cycle is a diagnostic metric widely used to gauge the quality of datasets. In this paper, the "Mixed Space-Time Domain" method for diagnosis of energy cycle is evaluated by using newly developed datasets-the Chinese Reanalysis Interim (CRAI) and ECMWF Reanalysis version 5 (ERA5), over a 7-yr period (2010-16) on seasonal and monthly timescales. The results show that the energy components calculated from the two reanalysis datasets are highly consistent;however, some components in the global energy integral from CRAI are slightly larger than those from ERA5. The main discrepancy in the energy components stems from the conversion of baroclinic process, whereas the dominant difference originates from the conversion from stationary eddy available potential energy to stationary eddy kinetic energy (CES), which is caused by systematic differences in the temperature and vertical velocity in low-mid latitudes of the Northern Hemisphere and near the Antarctic, where there exist complex terrains. Furthermore, the monthly analysis reveals that the general discrepancy in the temporal variation between the two datasets also lie mainly in the CES as well as corresponding generation and dissipation rates.

关键词： global energy cycle transient waves conversion terms Chinese Reanalysis Interim (CRAI) ECMWF Reanalysis version 5 (ERA5)

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Evaluation of Surface Relative Humidity in China from the CRA-40 and Current Reanalyses

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Advances in Atmospheric Sciences 2021年第11期38卷 1958-1976页

作者： Jingpeng ZHANG Tianbao ZHAO Zhi LI chunxiang LI Zhen LI Kairan YING chunxiang shi Lipeng JIANG Wenyu ZHANG College of Natural Resources and Environment Northwest A&F UniversityYanglingShaanxi 712100China CAS Key Laboratory of Regional Climate-Environment Research for Temperate East Asia(REC-TEA) Institute of Atmospheric Physics(IAP)Chinese Academy of Sciences(CAS)Beijing 100029China National Meteorological Information Center China Meteorological AdministrationBeijing 100081China School of Geoscience and Technology Zhengzhou UniversityZhengzhouHenan 450001China

Recently,the China Meteorological Administration(CMA)released a new Global Atmospheric Reanalysis(CRA-40)dataset for the period 1979−*** this study,surface relative humidity(RH)from CRA-40 and other current reanalyses(e.g.,CFSR,ERA5,ERA-Interim,JRA-55,and MERRA-2)is comprehensively evaluated against homogenized observations over *** results suggest that most reanalyses overestimate the observations by 15%−30%(absolute difference)over the Tibetan Plateau but underestimate the observations by 5%−10%over most of northern *** CRA-40 performs relatively well in describing the long-term change and variance seen in the observed surface RH over *** of the reanalyses reproduce the observed surface RH climatology and interannual variations well,while few reanalyses can capture the observed long-term RH trends over *** these reanalyses,the CFSR does poorly in describing the interannual changes in the observed RH,especially in Southwest *** empirical orthogonal function(EOF)analysis also suggests that the CRA-40 performs better than other reanalyses to capture the first two leading EOF modes revealed by the *** results of this study are expected to improve understanding of the strengths and weaknesses of the current reanalysis products and thus facilitate their application.

关键词： surface relative humidity CRA-40 reanalysis current reanalysis evaluation

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A 10-Yr Global Land Surface Reanalysis Interim Dataset(CRA-Interim/Land):Implementation and Preliminary Evaluation

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Journal of Meteorological Research 2020年第1期34卷 101-116页

作者： Xiao LIANG Lipeng JIANG Yang PAN chunxiang shi Zhiquan LIU Zijiang ZHOU National Meteorological Information Center China Meteorological AdministrationBeijing 100081China National Center for Atmospheric Research BoulderCO 80301USA

A land surface reanalysis dataset covering the most recent decades is able to provide temporally consistent initial conditions for weather and climate models,and thus is crucial to verifying/improving numerical weather/climate forecasts/*** this paper,we report the development of a 10-yr China Meteorological Administration(CMA)global Land surface ReAnalysis Interim dataset(CRA-Interim/Land;2007–2016,6-h intervals,approximately 34-km horizontal resolution).The dataset was produced and evaluated by using the Global Land Data Assimilation System(GLDAS)and NCEP Climate Forecast System Reanalysis(CFSR)global land surface reanalysis datasets,as well as in situ observations in *** results show that the global spatial patterns and monthly variations of the CRA-Interim/Land,GLDAS,and CFSR climatology are highly consistent,while the soil moisture and temperature values of the CRA-Interim/Land dataset are in between those of the GLDAS and CFSR *** with ground observations in China,CRA-Interim/Land soil moisture is comparable to or better than that of GLDAS and CFSR datasets for the 0–10-cm soil layer and has higher correlations and slightly lower root mean square errors(RMSE)for the 10–40-cm soil ***,CRA-Interim/Land shows negative biases in 10–40-cm soil moisture in Northeast China and north of central *** ground temperature and the soil temperature in different layers,CRA-Interim/Land behaves better than the CFSR,especially in East and central ***-Interim/Land has added value over the land components of CRA-Interim due to the introduction of global precipitation observations and improved soil/vegetation ***,this dataset is potentially a critical supplement to the *** evaluation of the CRA-Interim/Land,assimilation of near-surface atmospheric forcing variables,and extension of the current dataset to 40 yr(1979–2018)are in progress.

关键词： global land surface reanalysis dataset CRA-Interim/Land ground temperature soil temperature soil moisture Global Land Data Assimilation System(GLDAS)

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