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Overview and New Opportunities for Multi-Source data assimilation

Journal of Meteorological research 2025年第1期39卷 1-25页

作者： Xiaolei ZOU Joint Center of Data Assimilation for Research and Application Nanjing University of Information Science&TechnologyNanjing210044China

The world witnessed an accelerated development of various types of meteorological observing technology,an evolution of numerical weather prediction(NWP)models from single atmospheric component to coupled multi-components of the earth system,as well as the multi graphics processing unit technology in computer sciences,a new era for rapidly advancing data assimilation science and technology development has *** multi-source data assimilation is important not only for NWP but also for further understanding of global and regional weather *** article firstly selectively reviews past methods of multi-source data *** opportunities are then discussed for future development of data assimilation system framework,for innovative uses of high-resolution observations,and for applications of artificial intelligence machine learning in meteorological data assimilation.

关键词： multi-source observations data assimilation innovative use of high-resolution observations

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GOES-16 ABI Brightness Temperature Observations Capturing Vortex Rossby Wave Signals during Rapid Intensification of Hurricane Irma(2017)

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Journal of Meteorological research 2024年第4期38卷 768-783页

作者： Yanyang HU Xiaolei ZOU Joint Center of Data Assimilation for Research and Application Nanjing University of Information Science&TechnologyNanjing 210044

Geostationary Operational Environmental Satellite-16(GOES-16) Advanced Baseline Imager(ABI) observations of brightness temperature(TB) are used to examine the temporal evolutions of convection-affected structures of Hurricane Irma(2017) during its rapid intensification(RI) period from 0600 to 1800 UTC 4 September *** ABI observations reveal that both an elliptical eye and a spiral rainband that originated from Irma's eyewall obviously exhibit wavenumber-2 TB *** elliptical eye underwent a counterclockwise rotation at a mean speed of a wavenumber-2 vortex Rossby edge wave from 0815 to 1005 UTC 4 *** the following about 2 hours(1025–1255 UTC 4 September),an inner spiral rainband originated from the eyewall and propagated at a phase speed that approximates the vortex Rossby wave(VRW) phase speed calculated from the aircraft reconnaissance *** the RI period of Irma,ABI TB observations show an on–off occurrence of low TB intrusions into the eye,accompanying a phase lock of eyewall TB asymmetries of wavenumbers 1 and 2 and an outward propagation of VRW-like inner spiral rainbands from the *** phase lock leads to an energy growth of Irma's eyewall *** the eye remained clear from 1415 to 1725 UTC 4 September,an inner spiral rainband that originated from a large convective area also had a VRW-like outward propagation,which is probably due to a vertical tilt of *** study suggests a potential link between convection sensitive GOES imager observations and hurricane dynamics.

关键词： Geostationary Operational Environmental Satellite(GOES)imager brightness temperature(TB) hurricane vortex Rossby wave(VRW)

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Relationships of along-the-track local variations of GPS RO impact parameter to strong local vertical gradient of wet refractivity in the tropics

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Science China Earth Sciences 2021年第11期64卷 2015-2026页

作者： Shengpeng YANG Xiaolei ZOU Joint Center of Data Assimilation for Research and Application Nanjing University of Information Science&TechnologyNanjing 210044China

Atmospheric refractivity fields are more strongly affected by more water vapor in the tropical lower troposphere than *** this study,based on model simulations,we first collocated the radio occultation(RO)data in 2009 from the Constellation Observing System for Meteorology,Ionosphere,and Climate(COSMIC)with CloudSat cloud profiling radar *** then investigate where and why a RO ray path intersects with other simulated rays of impact heights above and/or below the impact height of the *** the European Centre for Medium-Range Weather Forecasts ERA5 reanalysis as input to a raytracing observation operator,we show that the simulated impact parameters could vary along the ray in the tropical lower *** brevity,an intersection of a GPS RO ray path with rays above it or below it or both will be called an impact *** overlapping simulated ray trajectories over the vertical and horizontal gradients of refractivity in 2D occultation planes,impact multipath occurrences are vividly *** results show that the impact multipath is caused mostly by strong local vertical gradients of atmospheric wet refractivity mostly within 300 km horizontal distances from their perigee *** impact multipath occurs more frequently below 5-km impact height,with a maximum occurrence around the 3.4 km impact height(about 1.8 km geometric height).It is shown that both the simulated impact multipath phenomena and locally strong vertical gradients of wet refractivity are found in both cloudy and clear-sky conditions,and most frequently in presences of stratocumulus clouds.

关键词： GPS RO Multipath Troposphere

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applications of the Three-cornered Hat Method to the Error Variance Estimations of FY-4A Atmospheric Temperature Profiles

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Atmosphere 2023年第1期61卷 12-24页

作者： Yue Zhang Yudong Gao Xu Xu Fang Zhao 1 Chongqing Institute of Meteorological Sciences Chongqing 401147 People’s Republic of China2 Chongqing Engineering Research Center of Agrometeorology and Satellite Remote Sensing Chongqing 401147 People’s Republic of China 3 Joint Center of Data Assimilation for Research and Application Nanjing University of Information Science & Technology Nanjing 210044 People’s Republic of China 4 Chongqing Meteorological Information and Technology Support center Chongqing 401147 People’s Republic of China

ABSTRACTABSTRACTThis study applied the three-cornered hat method to the error variance estimations of temperature profiles retrieved from the Geosynchronous Interferometric Infrared Sounder (GIIRS), the first hyperspectral infrared sounder onboard Fengyun-4A (FY-4A) geostationary satellite. An accurate observational error is a crucial input parameter for FY-4A temperature profile assimilation. Using multiple data sets from 2020, this study examined the error variances of FY-4A temperature profiles in clear-sky and cloudy-sky respectively. Because of the effects of clouds on GIIRS, the error variances in cloudy-sky are much larger than in clear-sky. Provided that error variances less than 4K2are significant for data assimilation, the FY-4A temperature profiles in clear-sky from 900 to 150 hPa are meaningful to be assimilated. Results reveal that the latitudinal dependency of error variances is strong at 100 hPa. Encouraged by the vertical distributions of the temperature profile differences between FY-4A and other data sets, the error variance of total potential energy is also examined in this study. Although the detailed structures of temperature profiles are removed, the vertical integration obtains a more minor percentage error. Further studies on data assimilation are worth discussing if total potential energy is more meaningful than the FY-4A temperature profiles.RÉSUMÉLa présente étude a appliqué la méthode du chapeau à trois angles aux estimations de la variance d’erreur des profils de température récupérés par le sondeur infrarouge interférométrique géosynchrone (GIIRS), le premier sondeur infrarouge hyperspectral à bord du satellite géostationnaire Fengyun-4A (FY-4A). Une erreur d’observation précise est un paramètre d’entrée crucial pour l’assimilation du profil de température de FY-4A. En utilisant plusieurs ensembles de données de 2020, cette étude a examiné les variances d’erreur des profils de température de FY-4A par ciel clair et par ciel nuageux resp

关键词： error variance estimation FY-4A GIIRS temperature profiles total potential energy

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Surface Temperature assimilation Improving Geostationary Meteorological Satellite Surface-Sensitive Brightness Temperature Simulations Over Land

SSRN

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SSRN 2023年

作者： Li, Xin Zou, Xiaolei Zeng, Mingjian Zhuge, Xiaoyong Wu, Yang Wang, Ning Key Laboratory of Transportation Meteorology of China Meteorological Administration Nanjing Joint Institute for Atmospheric Sciences Chinese Academy of Meteorological Sciences Jiangsu Meteorological Service Nanjing210041 China Center of Data Assimilation for Research and Application Nanjing University of Information Science & Technology Nanjing210044 China Jiangsu Climate Center Nanjing210041 China

This study explores a possibility of improving Advanced Himawari Imager (AHI) surface-sensitive brightness temperature (TB) simulations over land by assimilating land surface temperature (LST) observations from the National Basic Meteorological Observing Stations of China. The Gridpoint Statistical Interpolation 3D-Var regional data assimilation (DA) system is modified to add LST as a new control variable and its background error variances, horizontal correlations and cross-correlations. The background covariances of LST with other control variables are calculated separately for daytime and nighttime samples in summer and winter seasons. A control experiment (ExpCTL) and three LST DA experiments with (ExpLST) and without (ExpLST_NBC) bias correction or with an average of LST within 2°Í2° grid boxes (ExpLST_SO) are conducted. Considering the fact that surface station observations are point measurements while the satellite TBs measure the total radiation effect of earth's surface within fields-of-view, a bias correction is found necessary for LST DA during daytimes (ExpLST). The biases are quantified by the differences from the Moderate-resolution Imaging Spectroradiometer LST retrievals to compensate for the representative differences. The analyzed fields are then used as input to the Community Radiative Transfer Model to simulate TBs of AHI surface-sensitive channels over land. A long-period statistics shows that ExpLST significantly reduces the observations minus simulations (O-B) biases and standard deviations of surface-sensitive TBs in terms of reducing the diurnal variations and season dependences of TB biases over different surface types, which also outperforms ExpLST_NBC and ExpLST_SO at daytime. This study suggests a potential benefit of combining the use of LST observations for assimilating surface-sensitive infrared TBs. © 2023, The Authors. All rights reserved.

关键词： Geostationary satellites

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Bias characterization of ATMS low-level channels under clearsky and cloudy conditions

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Frontiers of Earth Science 2019年第2期13卷 277-289页

作者： Qi LI Xiaolei ZOU Joint Center of Data Assimilation for Research and Application College of Atmospheric ScienceNanjing University of Information Science and Technology (NUIST)Nanjing 210044China Earth System Science Interdisciplinary Center (ESSIC) University of MarylandCollege ParkMD 20740-3823USA

The Advanced Technology Microwave Soun? der (ATMS) onboard the Suomi National Polar-Orbiting Partnership satellite is a cross-track scanning instrument containing 22 sounding channels in *** this study,the bias characteristics of channels 1-6,which could have significant cloud contamination in heavy precipitation,are first analyzed based on the differences between ATMS observations (O) and model simulations (B) under clearsky conditions over *** dependencies of the biases of window channels 1-3 are greater than those of channels *** of all nadir-only observations examined in different latitudinal bands[μ1(φ)]are positive and no more than 7.0 *** at higher latitudes are *** 1-5 have a generally symmetric scan bias pattern [μ2(α)].The global distributions of brightness temperature differences after subtracting the biases,i.e.,O-B-μ1(φ)-μ2(α),for channels 3-6 spatially match the liquid water path *** ice-affected observations,channel 3-6 O-B differences systematically increase as the liquid water path increases under cloudy *** investigation is needed to apply these findings for ATMS data assimilation under both clear-sky and cloudy conditions.

关键词： ATMS O-B clear-sky bias characteristics impact of clouds on biases

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A Machine Learning Approach for Deriving Atmospheric Temperatures and Typhoon Warm Cores From FY-3E MWTS-3 Observations

Journal of Geophysical Research: Machine Learning and Comput...

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Journal of Geophysical research: Machine Learning and Computation 2024年第3期1卷

作者： Zeyi Niu Xiaolei Zou Shanghai Typhoon Institute and Key Laboratory of Numerical Modeling for Tropical Cyclone of the China Meteorological Administration Shanghai China Department of Atmospheric and Oceanic Sciences and Institute of Atmospheric Sciences Fudan University Shanghai China Joint Center of Data Assimilation for Research and Application Nanjing University of Information and Science & Technology Nanjing China

Machine learning has gained an increasing popularity in the fields of satellite retrieval and numerical weather modeling. In this study, machine-learning (ML) neural-network (NN) models are utilized to retrieve atmospheric temperatures from observations of brightness temperature from the Microwave Temperature Sounder-3 (MWTS-3) onboard the China's first dawn-dusk polar-orbiting satellite Fengyun (FY)-3E, with the ERA5 reanalysis serving as training data sets. The root mean square errors of the ML-retrieved temperatures at all pressure levels are smaller than those obtained by a previously used traditional linear regression method compared to the ERA5 reanalysis over global oceans as well as radiosonde observations over land. Less than a 1-week period of training data is usually sufficient for an ML NN model to converge in less than 50–100 iterations. The shortest time period of training data is 3-days right before the testing data period. While the horizontal patterns and temporal evolutions of the ML-retrieved warm cores of Typhoon Malakas (2022) and Typhoon Haikui (2023) in the upper troposphere compared favorably with those obtained by traditional regression methods as well as the ERA5 reanalysis in the testing periods. The vertical structures of ML-retrieved warm cores extend further down to the middle and lower troposphere while those from the traditional regression method are confined in the upper troposphere. A comparison among ML results with additional training data sets across different seasons confirms the above conclusion. Neural networks retrieve atmospheric temperatures from FY-3E's MWTS-3, outperforming traditional methods For Typhoon Malakas, machine learning reveals detailed warm core structures, especially in middle- and lower-levels troposphere This study indicates that the outputs of NN models combine the characteristics of input MWTS-3 observations and the ERA5 reanalysis This study applies a machine learning neural network method to retrieve at

关键词： FY-3E MWTS-3 typhoon warm core machine learning

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INTRODUCTION

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Bulletin of the American Meteorological Society 2024年第8期105卷 S1-S11页

作者： Boyer, T. Blunden, J. Dunn, R.J.H. NOAA/NESDIS National Centers for Environmental Information Silver Spring Maryland NOAA/NESDIS National Centers for Environmental Information Asheville North Carolina Met Office Hadley Centre Exeter United Kingdom European Centre for Medium-Range Weather Forecasts Reading United Kingdom University of Maryland College Park Maryland Scripps Institution of Oceanography University of California San Diego La Jolla California NOAA/NWS National Centers for Environmental Prediction Climate Prediction Center College Park Maryland Brandenburg University of Technology (BTU) Cottbus-Senftenberg Germany Servicio Meteorológico Nacional Buenos Aires Argentina NOAA/OAR Physical Sciences Laboratory Boulder Colorado European Centre for Medium-Range Weather Forecasts Bonn Germany Center for Geophysical Research and School of Physics University of Costa Rica San José Costa Rica Department of Meteorology and National Centre for Earth Observation University of Reading Reading United Kingdom Centro Nacional de Monitoramento e Alertas de Desastres Naturais CEMADEN São Paulo Brazil Université Grenoble Alpes Institut des Géosciences de l’Environnement IRD CNRS Grenoble INP Grenoble France Hampton University Hampton Virginia Seychelles Meteorological Authority Mahe Seychelles Section for Glaciers Ice and Snow Norwegian Water Resources and Energy Directorate Oslo Norway National Research Institute for Agriculture Food and Environment (INRAE) CARRTEL Université Savoie Mont Blanc Thonon les Bains France Graduate School of Agriculture Osaka Metropolitan University Sakai Japan Science Faculty Universidad Nacional de Colombia Bogotá Colombia University of Bremen Bremen Germany NOAA Global Monitoring Laboratory Boulder Colorado Servicio Nacional de Meteorología e Hidrología del Perú Lima Perú Centro de Investigaciones sobre Desertificación – Spanish National Research Council (CSIC-UV-GVA) Valencia Spain Hydro-Climate Extremes Lab (H-CEL) Ghent University Ghent Belgium Department o

In 2023, La Niña conditions that generally prevailed in the eastern Pacific Ocean from mid-2020 into early 2023 gave way to a strong El Niño by October. Atmospheric concentrations of Earth’s major greenhouse gases—carbon dioxide, methane, and nitrous oxide—all increased to record-high levels. The annual global average carbon dioxide concentration in the atmosphere rose to 419.3±0.1 ppm, which is 50% greater than the pre-industrial level. The growth from 2022 to 2023 was 2.8 ppm, the fourth highest in the record since the 1960s. The combined short-term effects of El Niño and the long-term effects of increasing levels of heat-trapping gases in the atmosphere contributed to new records for many essential climate variables reported here. The annual global temperature across land and oceans was the highest in records dating as far back as 1850, with the last seven months (June–December) having each been record warm. Over land, the globally averaged temperature was also record high. Dozens of countries reported record or near-record warmth for the year, including China and continental Europe as a whole (warmest on record), India and Russia (second warmest), and Canada (third warmest). Intense and widespread heatwaves were reported around the world. In Vietnam, an all-time national maximum temperature record of 44.2°C was observed at Tuong Duong on 7 May, surpassing the previous record of 43.4°C at Huong Khe on 20 April 2019. In Brazil, the air temperature reached 44.8°C in Araçuaí in Minas Gerais on 20 November, potentially a new national record and 12.8°C above normal. The effect of rising temperatures was apparent in the cryosphere, where snow cover extent by June 2023 was the smallest in the 56-year record for North America and seventh smallest for the Northern Hemisphere overall. Heatwaves contributed to the greatest average mass balance loss for Alpine glaciers around the world since the start of the record in 1970. Due to rapid volume loss beginning in 2021, St. A

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Liquid Water Path Retrieval Using the Lowest Frequency Channels of Fengyun-3C Microwave Radiation Imager(MWRI)

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Journal of Meteorological research 2017年第6期31卷 1109-1122页

作者： Fei TANG Xiaolei ZOU Joint Center of Data Assimilation for Research and Application College of Atmospheric ScienceNanjing University of Information Science &Technology State Key Laboratory of Severe Weather Chinese Academy of Meteorological SciencesChina Meteorological Administration Earth System Science Interdisciplinary Center University of Maryland College Park

The Microwave Radiation Imager （MWRI） on board Chinese Fengyun-3 （FY-3） satellites provides measurements at 10.65, 18.7, 23.8, 36.5, and 89.0 GHz with both horizontal and vertical polarization channels. Brightness temperature measurements of those channels with their central frequencies higher than 19 GHz from satellite-based microwave imager radiometers had traditionally been used to retrieve cloud liquid water path （LWP） over ocean. The results show that the lowest frequency channels are the most appropriate for retrieving LWP when its values are large. Therefore, a modified LWP retrieval algorithm is developed for retrieving LWP of different magnitudes involving not only the high frequency channels but also the lowest frequency channels of FY-3 MWRI. The theoretical estimates of the LWP retrieval errors are between 0.11 and 0.06 mm for 10.65- and 18.7-GHz channels and between 0.02 and 0.04 mm for 36.5- and 89.0-GHz channels. It is also shown that the brightness temperature observations at 10.65 GHz can be utilized to better retrieve the LWP greater than 3 mm in the eyewall region of Super Typhoon Neoguri （2014）. The spiral structure of clouds within and around Typhoon Neoguri can be well captured by combining the LWP retrievals from different frequency channels.

关键词： microwave remote sensing Fengyun-3C Microwave Radiation Imager （MWRI） liquid water path （LWP） retrieval

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Development and Initial Assessment of a New Land Index for Microwave Humidity Sounder Cloud Detection

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Journal of Meteorological research 2016年第1期30卷 12-37页

作者：秦正坤邹晓蕾 Center of Data Assimilation for Research and Application Nanjing University of Information Science & Technology Earth System Science Interdisciplinary Center University of Maryland

This paper describes a new quality control （QC） scheme for microwave humidity sounder （MHS） data assimilation. It consists of a cloud detection step and an O-B （i.e., differences of brightness temperatures between observations and model simulations） check. Over ocean, cloud detection can be carried out based on two MHS window channels and two Advanced Microwave Sounding Unit-A （AMSU-A） window channels, which can be used for obtaining cloud ice water path （IWP） and liquid water path （LWP）, respectively. Over land, cloud detection of microwave data becomes much more challenging due to a much larger emission contribution from land surface than that from cloud. The current MHS cloud detection over land employs an 0-]3 based method, which could fail to identify cloudy radiances when there is mismatch between actual clouds and model clouds. In this study, a new MHS observation based index is developed for identifying MHS cloudy radiances over land. The new land index for cloud detection exploits the large variability of brightness temperature observations among MHS channels over different clouds, It is shown that those MHS cloudy radiances that were otherwise missed by the current O-B based QC method can be successfully identified by the new land index. An O-B check can then be employed to the remaining data after cloud detection to remove additional outliers with model simulations deviated greatly from observations. It is shown that MHS channel correlations are significantly reduced by the newly proposed QC scheme.

关键词： microwave humidity sounder cloud detection data assimilation

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