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Application of an Error Statistics Estimation Method to the PSAS Forecast Error Covariance Model

Advances in Atmospheric Sciences 2006年第1期23卷 33-44页

作者： Runhua YANG Jing GUO Lars Peter RIISHФJGAARD Science Systems and Applications Inc. Lanham USA Science Applications International Corporation Beltsville USA Joint Center for Earth Systems Technology/UMBC Baltimore USA global modeling and assimilation office NASA Goddard Space Flight Center Greenbelt USA

In atmospheric data assimilation systems, the forecast error covariance model is an important component. However, the paralneters required by a forecast error covariance model are difficult to obtain due to the absence of the truth. This study applies an error statistics estimation method to the Pfiysical-space Statistical Analysis System （PSAS） height-wind forecast error covariance model. This method consists of two components： the first component computes the error statistics by using the National Meteorological Center （NMC） method, which is a lagged-forecast difference approach, within the framework of the PSAS height-wind forecast error covariance model; the second obtains a calibration formula to rescale the error standard deviations provided by the NMC method. The calibration is against the error statistics estimated by using a maximum-likelihood estimation （MLE） with rawindsonde height observed-minus-forecast residuals. A complete set of formulas for estimating the error statistics and for the calibration is applied to a one-month-long dataset generated by a general circulation model of the global Model and assimilation office （GMAO）, NASA. There is a clear constant relationship between the error statistics estimates of the NMC-method and MLE. The final product provides a full set of 6-hour error statistics required by the PSAS height-wind forecast error covariance model over the globe. The features of these error statistics are examined and discussed.

关键词： forecast error statistics estimation data analysis forecast error covariance model

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Effect of Meteorological Data assimilation on Regional Air Quality Forecasts over the Korean Peninsula

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Journal of Meteorological Research 2024年第2期38卷 262-284页

作者： Yunjae CHO Hyun Mee KIM Eun-Gyeong YANG Yonghee LEE Jae-Bum LEE Soyoung HA Department of Atmospheric Sciences Yonsei UniversitySeoul 03722Republic of Korea Air Quality Forecasting Center National Institute of Environmental ResearchIncheon 22689Republic of Korea National Center for Atmospheric Research BoulderCO 80305USA University of Maryland Baltimore County BaltimoreMD 21250USA global modeling and assimilation office NASA Goddard Space Flight CenterGreenbeltMD 20771USA

The Weather Research and Forecasting model coupled with Chemistry(WRF-Chem),a type of online coupled chemistry-meteorology model(CCMM),considers the interaction between air quality and meteorology to improve air quality *** data assimilation(DA)can be used to reduce uncertainty in meteorological field,which is one factor causing prediction uncertainty in the *** this study,WRF-Chem and three-dimensional variational DA were used to examine the impact of meteorological DA on air quality and meteorological forecasts over the Korean *** nesting model domains were configured over East Asia(outer domain)and the Korean Peninsula(inner domain).Three experiments were conducted by using different DA domains to determine the optimal model domain for the meteorological *** the meteorological DA was performed in the outer domain or both the outer and inner domains,the root-mean-square error(RMSE),bias of the predicted particulate matter(PM)concentrations,and the RMSE of predicted meteorological variables against the observations were smaller than those in the experiment where the meteorological DA was performed only in the inner *** indicates that the improvement of the synoptic meteorological fields by DA in the outer domain enhanced the meteorological initial and boundary conditions for the inner domain,subsequently improving air quality and meteorological *** to the experiment without meteorological DA,the RMSE and bias of the meteorological and PM variables were smaller in the experiments with *** effect of meteorological DA on the improvement of PM predictions lasted for approximately 58-66 h,depending on the ***,the uncertainty reduction in the meteorological initial condition by the meteorological DA contributed to a reduction of the forecast errors of both meteorology and air quality.

关键词： meteorological data assimilation regional air quality forecast particulate matter concentration optimal model domain forecast error WRF-Chem

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Contribution of cloud condensate to surface rainfall process

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Progress in Natural Science:Materials International 2006年第9期16卷 967-973页

作者： ZHOU Yushu , GUI Xiaopeng and LI Xiaofan ( Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing 100029, China Joint Center for Satellite Data assimilation and NOAA/NESDIS/office of Research and Applications Camp Springs, Maryland, USA) Institute of Atmospheric Physics Chinese Academy of Sciences Beijing 100029 China Joint Center for Satellite Data assimilation NOAA NESDIS Office of Research and Applications Camp Springs MD United States

Contribution of cloud condensate to surface rainfall processes is investigated in a life span of tropical convection based on hourly data from a two-dimensional cloud resolving simulation. The model is forced by the large-scale vertical velocity, zonal wind and horizontal advections obtained from tropical ocean global atmosphere coupled ocean-atmosphere response experiment (TOGA COARE). The results show that during the genesis, development, and decay of tropical convection, calculations with water vapor overestimate surface rain rate, and cloud condensate plays an important role in correcting overestimation in surface rain rates. The analysis is carried out in deep convective clouds and anvil clouds during the development of tropical convection. The surface rain rates calculated with water vapor in deep convective clouds and anvil clouds have similar magnitudes, the large surface rain rate appears in deep convective clouds due to the consumption of water hydrometeors whereas the small surface rain rate occurs in anvil clouds because of the gain of ice hydrometeors. Further analysis of the grid data shows that the surface rain rates calculated with water vapor and with cloud condensate are negatively correlated with the correlation coefficient of - 0.85, and the surface rain rate calculated with cloud condensate is mainly contributed to the water hydrometeors in the tropical deep convective regime.

关键词： cloud condensate surface rain rate cloud resolving simulation.

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Scale-dependent Regional Climate Predictability over North America Inferred from CMIP3 and CMIP5 Ensemble Simulations

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Advances in Atmospheric Sciences 2016年第8期33卷 905-918页

作者： Fuqing ZHANG Wei LI Michael E.MANN Department of Meteorology and Center for Advanced Data assimilation and Predictability Techniques The Pennsylvania State UniversityUniversity ParkPA 16802USA IMSG at NOAA NWSNCEPEnvironmental Modeling CenterCollege ParkMD 20740USA

Through the analysis of ensembles of coupled model simulations and projections collected from CMIP3 and CMIP5, we demonstrate that a fundamental spatial scale limit might exist below which useful additional refinement of climate model predictions and projections may not be possible. That limit varies among climate variables and from region to region. We show that the uncertainty（noise） in surface temperature predictions（represented by the spread among an ensemble of global climate model simulations） generally exceeds the ensemble mean（signal） at horizontal scales below 1000 km throughout North America, implying poor predictability at those scales. More limited skill is shown for the predictability of regional precipitation. The ensemble spread in this case tends to exceed or equal the ensemble mean for scales below 2000 km. These findings highlight the challenges in predicting regionally specific future climate anomalies, especially for hydroclimatic impacts such as drought and wetness.

关键词： regional climate predictability CMIP5 ensemble North America climate change

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Correlation Structures between Satellite All-Sky Infrared Brightness Temperatures and the Atmospheric State at Storm Scales

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Advances in Atmospheric Sciences 2022年第5期39卷 714-732页

作者： Yunji ZHANG Eugene E.CLOTHIAUX David J.STENSRUD Center for Advanced Data assimilation and Predictability Techniques and Department of Meteorology and Atmospheric ScienceThe Pennsylvania State UniversityUniversity ParkPennsylvania 16802USA

This study explores the structures of the correlations between infrared(IR)brightness temperatures(BTs)from the three water vapor channels of the Advanced Baseline Imager(ABI)onboard the GOES-16 satellite and the atmospheric ***-based data assimilation techniques such as the ensemble Kalman filter(EnKF)rely on correlations to propagate innovations of BTs to increments of model state *** the three water vapor channels are sensitive to moisture in different layers of the troposphere,the heights of the strongest correlations between these channels and moisture in clear-sky regions are closely related to the peaks of their respective weighting *** cloudy regions,the strongest correlations appear at the cloud tops of deep clouds,and ice hydrometeors generally have stronger correlations with BT than liquid *** magnitudes of the correlations decrease from the peak value in a column with both vertical and horizontal *** how the correlations decrease depend on both the cloud scenes and the cloud structures,as well as the model *** correlations between BTs and moisture,as well as hydrometeors,in fully cloudy regions decrease to almost 0 at about 30 *** horizontal correlations with atmospheric state variables in clear-sky regions are broader,maintaining non-zero values out to~100 *** results in this study provide information on the proper choice of cut-off radii in horizontal and vertical localization schemes for the assimilation of *** also provide insights on the most efficient and effective use of the different water vapor channels.

关键词： severe storm remote sensing data assimilation numerical modeling

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Added Benefit of the Early-Morning-Orbit Satellite Fengyun-3E on the global Microwave Sounding of the Three-Orbit Constellation

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Advances in Atmospheric Sciences 2024年第1期41卷 39-52页

作者： Juan LI Zhengkun QIN Guiqing LIU Jing HUANG CMA Earth System modeling and Prediction Centre Beijing 100081China State Key Laboratory of Severe Weather Chinese Academy of Meteorological SciencesBeijing 100081China Joint Center for Data assimilation Research and Applications School of Atmospheric SciencesNanjing University of Information Science&TechnologyNanjing 210044China

The three-orbit constellation can comprehensively increase the spatial coverage of polar-orbiting satellites,but the polar-orbiting satellites currently in operation are only mid-morning-orbit and afternoon-orbit ***-3E(FY-3E)was launched successfully on 5 July 2021 in *** an early-morning-orbit satellite,FY-3E can help form a complete three-orbit observation system together with the mid-morning and afternoon satellites in the current mainstream operational *** this study,we investigate the added benefit of FY-3E microwave sounding observations to the midmorning-orbit Meteorological Operational satellite-B(Met Op-B)and afternoon-orbit Fengyun-3D(FY-3D)microwave observations in the Chinese Meteorological Administration global forecast system(CMA-GFS).The results show that the additional FY-3E microwave temperature sounder-3(MWTS-3)and microwave humidity sounder-2(MWHS-2)data can increase the global coverage of microwave temperature and humidity sounding data by 14.8% and 10.6%,*** enables the CMA-GFS to achieve nearly 100% global coverage of microwave-sounding observations at each analysis ***,after effective quality control and bias correction,the global biases and standard deviations of the differences between observations and model simulations are also *** on the Advanced Microwave Sounding Unit A and the Microwave Humidity Sounder onboard Met Op-B,and the MWTS-2 and MWHS-2 onboard FY-3D,adding the microwave sounding data of FY-3E can further reduce the errors of analysis results and improve the global prediction skills of CMA-GFS,especially for the southern-hemisphere forecasts within 96 hours,all of which are significant at the 95% confidence level.

关键词： data assimilation microwave temperature sounder MWTS-3

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Cloud microphysical and rainfall responses to zonal perturbations of sea surface temperature:A cloud-resolving modeling study

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Progress in Natural Science:Materials International 2009年第5期19卷 587-594页

作者： Xiaopeng Cuia, Xiaofan Lib, Zhiping Zongc a Laboratory of Cloud-Precipitation Physics and Severe Storms (LACS), Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing 100029, China b Joint Center for Satellite Data assimilation and NOAA/NESDIS/office of Research and Applications, Camp Springs, MD, USA c National Meteorological Center, China Meteorological Administration, Beijing 100081, China Laboratory of Cloud-Precipitation Physics and Severe Storms (LACS) Institute of Atmospheric Physics Chinese Academy of Sciences Beijing 100029 China Joint Center for Satellite Data assimilation and NOAA/NESDIS/office of Research and Applications Camp Springs MD USA National Meteorological Center China Meteorological Administration Beijing 100081 China

The cloud microphysical and rainfall responses to zonal perturbations of sea surface temperature (SST) are investigated by analyzing the equilibrium simulation data (from day 31-40) obtained from a series of two-dimensional cloud-resolving simulations with a zonal model domain of 768 km. Four experiments imposed by zonal SST perturbations of wavenumbers 1 (SST29Z1), 2 (SST29Z2), 4 (SST29Z4), and 8 (SST29Z8) are compared to the control experiment imposed by zonally uniform SST (SST29). The model domain mean SST is 29 °C, and the two-dimensional cloud-resolving model with a cyclic lateral boundary is also imposed by zero vertical velocity and constant zonal wind. The time and model domain mean surface rain rates in SST29Z1, SST29Z2, and SST29Z8 are about 10% larger than those in SST29, whereas the mean surface rain rates in SST29Z4 and SST29 are similar. The analysis of mean surface rainfall budgets shows that local water vapor and hydrometeor changes play important roles in determining the differences and similarities in mean surface rain rate between the perturbation experiments and the control experiment. Both convective and stratiform rain rates are larger in SST29Z1 and SST29Z2 than in SST29 due to the smaller advection of rain from convective regions into raining stratiform regions and the larger vapor condensation rates associated with the larger water vapor convergence over raining stratiform regions in SST29Z1 and SST29Z2. The convective rain rates are larger in SST29Z4 and SST29Z8 than in SST29 because of the larger condensation rates associated with the larger water vapor convergence over convective regions in SST29Z4 and SST29Z8. The stratiform rain rates in SST29Z4 and SST29Z8 are smaller than in SST29 due to the smaller vapor condensation rates and smaller collection rates of cloud water by rain over raining stratiform regions in SST29Z4 and SST29Z8.

关键词： Cloud microphysical and rainfall responses Sea surface temperature Zonal perturbation Cloud-resolving modeling study

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Dynamics of local extreme rainfall of super Typhoon Soudelor (2015) in East China

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Science China Earth Sciences 2018年第5期61卷 572-594页

作者： Jinsong PAN Daigao TENG Fuqing ZHANG Lingli ZHOU Ling LUO Yonghui WENG Yunji ZHANG Zhejiang Meteorological Observatory Hangzhou 310021 China Department of Meteorology and Atmospheric Sciences and Center for Advanced Data Assimilation and Prediction Techniques Pennsylvania State University University Park Pennsylvania 16802 USA

The characteristics and dynamics associated with the distribution, intensity, and triggering factors of local severe precipitation in Zhejiang Province induced by Super Typhoon Soudelor(2015) were investigated using mesoscale surface observations, radar reflectivity, satellite nephograms, and the final(FNL) analyses of the global Forecasting System(GFS) of the National Center for Environmental Prediction(NCEP). The rainfall processes during Soudelor's landfall and translation over East China could be separated into four stages based on rainfall characteristics such as distribution, intensity, and corresponding dynamics. The relatively less precipitation in the first stage resulted from interaction between the easterly wind to the north flank of this tropical cyclone(TC) and the coastal topography along the southeast of Zhejiang Province, China. With landfall of the TC in East China during the second stage, precipitation maxima occurred because of interaction between the TC's principal rainbands and the local topography from northeastern Fujian Province to southwestern Zhejiang Province. The distribution of precipitation presented significant asymmetric features in the third stage with maximal rainfall bands in the northeast quadrant of the TC when Soudelor's track turned from westward to northward as the TC decayed rapidly. Finally, during the northward to northeastward translation of the TC in the fourth stage, the interaction between a mid-latitude weather system and the northern part of the TC resulted in transfer of the maximum rainfall from the north of Zhejiang Province to the north of Jiangsu Province,which represented the end of rainfall in Zhejiang Province. Further quantitative calculations of the rainfall rate induced by the interaction between local topography and TC circulation(defined as "orographic effects") in the context of a one-dimensional simplified model showed that orographic effects were the primary factor determining the intensity of precipit

关键词： TC outer circulation TC principal rainband Orographic effect Expanding of TC's spiral bands

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A New Infrared Atmospheric Sounding Interferometer Channel Selection and Assessment of Its Impact on Met office NWP Forecasts

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Advances in Atmospheric Sciences 2017年第11期34卷 1265-1281页

作者： Young-Chan NOH Byung-Ju SOHN. Yoonjae KIM Sangwon JOO William BELL Roger SAUNDERS School of Earth and Environmental Sciences Seoul National University Seou108826 Korea Numerical modeling Center Korea Meteorological Administration Seou107062 Korea Met office Exeter EXI 3PB United Kingdom

A new set of Infrared Atmospheric Sounding Interferometer （IASI） channels was re-selected from 314 EUMETSAT channels. In selecting channels, we calculated the impact of the individually added channel on the improvement in the analysis outputs from a one-dimensional variational analysis （1D-Var） for the Unified Model （UM） data assimilation system at the Met office, using the channel score index （CSI） as a figure of merit. Then, 200 channels were selected in order by counting each individual channel＇s CSI contribution. Compared with the operationally used 183 channels for the UM at the Met office, the new set shares 149 channels, while the other 51 channels are new. Also examined is the selection from the entropy reduction method with the same 1D-Var approach, Results suggest that channel selection can be made in a more objective fashion using the proposed CSI method. This is because the most important channels can be selected across the whole IASI observation spectrum. In the experimental trial runs using the UM global assimilation system, the new channels had an overall neutral impact in terms of improvement in forecasts, as compared with results from the operational channels. However, upper-tropospheric moist biases shown in the control run with operational channels were significantly reduced in the experimental trial with the newly selected channels. The reduction of moist biases was mainly due to the additional water vapor channels, which are sensitive to the upper-tropospheric water vapor.

关键词： Hyperspectral IR sounding channel selection 1D-Vat data assimilation

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Data Mining for Flooding Episode in the States of Alagoas and Pernambuco—Brazil

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American Journal of Climate Change 2018年第3期7卷 420-430页

作者： Heloisa Musetti Ruivo Haroldo F. de Campos Velho Fernando M. Ramos Saulo R. Freitas Laboratory for Computing and Applied Mathematics National Institute for Space Research S&#227 o José dos Campos Brazil Center for Weather Forecasting and Climate Research National Institute for Space Research S&#227 o José dos Campos Brazil Goddard Earth Sciences Technology and Research Universities Space Research Association Columbia MD USA global modeling and assimilation office NASA Goddard Space Flight Center Greenbelt MD USA

The increasing volume of data in the area of environmental sciences needs analysis and interpretation. Among the challenges generated by this “data deluge”, the development of efficient strategies for the knowledge discovery is an important issue. Here, statistical and tools from computational intelligence are applied to analyze large data sets from meteorology and climate sciences. Our approach allows a geographical mapping of the statistical property to be easily interpreted by meteorologists. Our data analysis comprises two main steps of knowledge extraction, applied successively in order to reduce the complexity from the original data set. The goal is to identify a much smaller subset of climatic variables that might still be able to describe or even predict the probability of occurrence of an extreme event. The first step applies a class comparison technique: p-value estimation. The second step consists of a decision tree (DT) configured from the data available and the p-value analysis. The DT is used as a predictive model, identifying the most statistically significant climate variables of the precipitation intensity. The methodology is employed to the study the climatic causes of an extreme precipitation events occurred in Alagoas and Pernambuco States (Brazil) at June/2010.

关键词： Data Mining Statistical Analysis T-Test p-Value Artificial Intelligence Decision Tree

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