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Fusion SST from Infrared and Microwave Measurement of FY-3D meteorological satellite

Journal of Tropical Meteorology 2024年第1期30卷 89-96页

作者：张淼徐娜陈林 National satellite meteorological center/National center for Space Weather Beijing 100081 China innovation center for fengyun meteorological satellite(FYSIC) Beijing 100081 China Key Laboratory of Radiometric Calibration and Validation for Environmental satellites China Meteorological AdministrationBeijing 100081 China

Sea surface temperature(SST)is one of the important parameters of global ocean and climate research,which can be retrieved by satellite infrared and passive microwave remote sensing instruments.While satellite infrared SST offers high spatial resolution,it is limited by cloud cover.On the other hand,passive microwave SST provides all-weather observation but suffers from poor spatial resolution and susceptibility to environmental factors such as rainfall,coastal effects,and high wind speeds.To achieve high-precision,comprehensive,and high-resolution SST data,it is essential to fuse infrared and microwave SST measurements.In this study,data from the fengyun-3D(FY-3D)medium resolution spectral imager II(MERSI-II)SST and microwave imager(MWRI)SST were fused.Firstly,the accuracy of both MERSIII SST and MWRI SST was verified,and the latter was bilinearly interpolated to match the 5km resolution grid of MERSI SST.After pretreatment and quality control of MERSI SST and MWRI SST,a Piece-Wise Regression method was employed to correct biases in MWRI SST.Subsequently,SST data were selected based on spatial resolution and accuracy within a 3-day window of the analysis date.Finally,an optimal interpolation method was applied to fuse the FY-3D MERSI-II SST and MWRI SST.The results demonstrated a significant improvement in spatial coverage compared to MERSI-II SST and MWRI SST.Furthermore,the fusion SST retained true spatial distribution details and exhibited an accuracy of–0.12±0.74℃compared to OSTIA SST.This study has improved the accuracy of FY satellite fusion SST products in China.

关键词： SST data fusion FY3 infrared microwave

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Characteristics of Lightning Activity in Southeast China and its Relation to the Atmospheric Background

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Journal of Tropical Meteorology 2024年第1期30卷 76-88页

作者：支树林朱杰刘岩毛梦妮 Jiangxi meteorological Observatory Nanchang 330096 China Key Laboratory of Radiometric Calibration and Validation for Environmental satellites National Satellite Meteorological Center(National Center for Space Weather)China Meteorological AdministrationBeijing 100081 China Shanghai Typhoon Institute China Meteorological AdministrationShanghai 200030 China innovation center for fengyun meteorological satellite(FYSIC) Beijing 100081 China Key Laboratory of Transportation Meteorology of China meteorological Administration Nanjing Joint Institute for Atmospheric SciencesNanjing 210041 China Key Laboratory of meteorological Disaster(KLME) Ministry of Education&Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters(CICFEMD)Nanjing University of Information Science&TechnologyNanjing 210041 China Jiujiang Observatory JiujiangJiangxi 332000 China

Based on the lightning observation data from the fengyun-4A(FY-4A)Lightning Mapping Imager(FY-4A/LMI)and the Lightning Imaging Sensor(LIS)on the International Space Station(ISS),we extract the“event”type data as the lightning detection results.These observations are then compared with the cloud-to-ground(CG)lightning observation data from the China meteorological Administration.This study focuses on the characteristics of lightning activity in Southeast China,primarily in Jiangxi Province and its adjacent areas,from April to September,2017–2022.In addition,with the fifth-generation European Centre for Medium-Range Weather Forecasts reanalysis data,we further delved into the potential factors influencing the distribution and variations in lightning activity and their primary related factors.Our findings indicate that the lightning frequency and density of the FY-4A/LMI,ISS-LIS and CG data are higher in southern and central Jiangxi,central Fujian Province,and western and central Guangdong Province,while they tend to be lower in eastern Hunan Province.In general,the high-value areas of lightning density for the FY-4A/LMI are located in inland mountainous areas.The lower the latitude is,the higher the CG lightning density is.High-value areas of the CG lightning density are more likely to be located in eastern Fujian and southeastern Zhejiang Province.However,the high-value areas of lightning density for the ISS-LIS are more dispersed,with a scattered distribution in inland mountainous areas and along the coast of eastern Fujian.Thus,the mountainous terrain is closely related to the high-value areas of the lightning density.The locations of the high-value areas of the lightning density for the FY-4A/LMI correspond well with those for the CG observations,and the seasonal variations are also consistent.In contrast,the distribution of the high-value areas of the lightning density for the ISS-LIS is more dispersed.The positions of the peak frequency of the FY-4A/LMI lightning and CG lightning contrast with local altitudes

关键词： lightning satellite and ground detections atmospheric background Southeast China

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Quantitative Applications of Weather satellite Data for Nowcasting: Progress and Challenges

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Journal of meteorological Research 2024年第3期38卷 399-413页

作者： Jun LI Jing ZHENG Bo LI Min MIN Yanan LIU Chian-Yi LIU Zhenglong LI W.Paul MENZEL Timothy J.SCHMIT John L.CINTINEO Scott LINDSTROM Scott BACHMEIER Yunheng XUE Yayu MA Di DI Han LIN Key Laboratory of Spatial Data Mining and Information Sharing of Ministry of Education National and Local Joint Engineering Research Center of Satellite Geospatial Information Technology Fuzhou University innovation Centre for fengyun meteorological satellite (FYSIC) National Satellite Meteorological Centre China Meteorological Administration School of Atmospheric Sciences and Guangdong Province Key Laboratory for Climate Change and Natural Disaster Studies Sun Yat-sen University and Southern Laboratory of Ocean Science and Engineering Key Laboratory of Geographic Information Science (Ministry of Education) East China Normal University Research center for Environmental Changes Academia Sinica Cooperative Institute for meteorological satellite Studies University of Wisconsin-Madison Sensors and Calibration Branch STAR/NESDIS Wuxi University School of Computer Science Chengdu University of Information Technology Collaborative innovation center on Forecast and Evaluation of meteorological Disasters Nanjing University of Information Science & Technology

Monitoring and predicting highly localized weather events over a very short-term period, typically ranging from minutes to a few hours, are very important for decision makers and public action. Nowcasting these events usually relies on radar observations through monitoring and extrapolation. With advanced high-resolution imaging and sounding observations from weather satellites, nowcasting can be enhanced by combining radar, satellite, and other data,while quantitative applications of those data for nowcasting are advanced through using machine learning techniques.Those applications include monitoring the location, impact area, intensity, water vapor, atmospheric instability, precipitation, physical properties, and optical properties of the severe storm at different stages(pre-convection, initiation,development, and decaying), identification of storm types(wind, snow, hail, etc.), and predicting the occurrence and evolution of the storm. satellite observations can provide information on the environmental characteristics in the preconvection stage and are very useful for situational awareness and storm warning. This paper provides an overview of recent progress on quantitative applications of satellite data in nowcasting and its challenges, and future perspectives are also addressed and discussed.

关键词： weather satellite quantitative applications nowcasting pre-convection

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Consistency of Tropospheric Water Vapor between Reanalyses and Himawari-8/AHI Measurements over East Asia

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Advances in Atmospheric Sciences 2024年第1期41卷 19-38页

作者： Di DI Jun LI Yunheng XUE Min MIN Bo LI Zhenglong LI Collaborative innovation center on Forecast and Evaluation of meteorological Disasters Nanjing University of Information Science and TechnologyNanjing 210044China Key Laboratory for Aerosol-Cloud-Precipitation China Meteorological AdministrationSchool of Atmospheric PhysicsNanjing University of Information Science and TechnologyNanjing 210044China FYSIC National Satellite Meteorological CenterChina Meteorological AdministrationBeijing 100081China Chengdu University of Information Science and Technology Chengdu 610225China School of Atmospheric Sciences and Guangdong Province Key laboratory for Climate Change and Natural Disaster Studies Sun Yat-sen University and Southern Laboratory of Ocean Science and EngineeringZhuhai 519082China Cooperative Institute for meteorological satellite Studies University of Wisconsin–MadisonMadison WI 53706WisconsinUSA Wuxi University Wuxi 214105China

High spatiotemporal resolution radiances from the advanced imagers onboard the new generation of geostationary weather satellites provide a unique opportunity to evaluate the abilities of various reanalysis datasets to depict multilayer tropospheric water vapor(WV),thereby enhancing our understanding of the deficiencies of WV in reanalysis datasets.Based on daily measurements from the Advanced Himawari Imager(AHI)onboard the Himawari-8 satellite in 2016,the bias features of multilayer WV from six reanalysis datasets over East Asia are thoroughly evaluated.The assessments show that wet biases exist in the upper troposphere in all six reanalysis datasets;in particular,these biases are much larger in summer.Overall,we find better depictions of WV in the middle troposphere than in the upper troposphere.The accuracy of WV in the ERA5 dataset is the highest,in terms of the bias magnitude,dispersion,and pattern similarity.The characteristics of the WV bias over the Tibetan Plateau are significantly different from those over other parts of East Asia.In addition,the reanalysis datasets all capture the shift of the subtropical high very well,with ERA5 performing better overall.

关键词： AHI reanalysis dataset multilayer water vapor assessment radiative transfer model

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Impact of Atmospheric Transmittance and NLTE Correction on Simulation of High Spectral Infrared Atmospheric Sounder onboard FY-3E

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Journal of meteorological Research 2024年第2期38卷 225-234页

作者： Chenggege FANG Peiming DONG Yang HAN Wanlin KAN Collaborative innovation center on Forecast and Evaluation of meteorological Disasters Key Laboratory for Aerosol-Cloud-Precipitation of China Meteorological AdministrationNanjing University of Information Science&TechnologyNanjing 210044 Donghai Laboratory Zhoushan 316021 State Key Laboratory of Severe Weather Chinese Academy of Meteorological SciencesChina Meteorological AdministrationBeijing 100081 CMA Earth System Modeling and Prediction Centre China Meteorological Administration(CMA)Beijing 100081 Key Laboratory of Transportation Meteorology of China meteorological Administration Nanjing Joint Institute for Atmospheric SciencesNanjing 210041

With the launch of the first civilian early-morning orbit satellite fengyun-3E(FY-3E),higher demands are placed on the accuracy of radiative transfer simulations for hyperspectral infrared data.Therefore,several key issues are investigated in the paper.First,the accuracy of the fast atmospheric transmittance model implemented in the Advanced Research and Modeling System(ARMS)has been evaluated with both the line-by-line radiative transfer model(LBLRTM)and the actual satellite observations.The results indicate that the biases are generally less than 0.25 K when compared to the LBLRTM,while below 1.0 K for the majority of the channels when compared to the observations.However,during both comparisons,significant biases are observed in certain channels.The accuracy of Hyperspectral Infrared Atmospheric Sounder-II(HIRAS-II)onboard FY-3E is comparable to,and even superior to that of the Cross-track Infrared Sounder(CrIS)onboard NOAA-20.Furthermore,apodization is a crucial step in the processing of hyperspectral data in that the apodization function is utilized as the instrument channel spectral response function to produce the satellite channel-averaged transmittance.To further explore the difference between the apodized and unapodized simulations,Sinc function is adopted in the fast transmittance model.It is found that the use of Sinc function can make the simulations fit the original satellite observations better.When simulating with apodized observations,the use of Sinc function exhibits larger deviations compared to the Hamming function.Moreover,a correction module is applied to minimize the impact of Non-Local Thermodynamic Equilibrium(NLTE)in the shortwave infrared band.It is verified that the implementation of the NLTE correction model leads to a significant reduction in the bias between the simulation and observation for this band.

关键词： high spectral infrared sounding atmospheric transmittance apodization Non-Local Thermodynamic Equilibrium fengyun-3E(FY-3E)

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Improvement of cloud microphysical parameterization and its advantages in simulating precipitation along the Sichuan-Xizang Railway

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Science China Earth Sciences 2024年第3期67卷 856-873页

作者： Xiaoqi XU Zhiwei HENG Yueqing LI Shunjiu WANG Jian LI Yuan WANG Jinghua CHEN Peiwen ZHANG Chunsong LU China meteorological Administration Transportation Meteorology Key Laboratory Nanjing Joint Institute for Atmospheric SciencesNanjing 210041China Heavy Rain and Drought-Flood Disasters in Plateau and Basin Key Laboratory of Sichuan Province Institute of Plateau MeteorologyCMAChengdu 610072China State Key Laboratory of Disaster Weather Chinese Academy of Meteorological SciencesBeijing 100081China Collaborative innovation center for Western Ecological Safety Lanzhou UniversityLanzhou 730000China China meteorological Administration Aerosol-Cloud and Precipitation Key Laboratory and Collaborative innovation center on Forecast and Evaluation of meteorological Disasters(CIC-FEMD) Nanjing University of Information Science and TechnologyNanjing 210044China

The Sichuan-Xizang Railway is an important part of the railway network in China, and geological disasters, such as mountain floods and landslides, frequently occur in this region. Precipitation is an important cause of these disasters;therefore,accurate simulation of the precipitation in this region is highly important. In this study, the descriptions for uncertain processes in the cloud microphysics scheme are improved;these processes include cloud droplet activation, cloud-rain autoconversion, rain accretion by cloud droplets, and the entrainment-mixing process. In the default scheme, the cloud water content of different sizes corresponds to the same cloud droplet concentration, which is inconsistent with the actual content;this results in excessive cloud droplet size, unreasonable related conversion rates of microphysical process(such as cloud-rain autoconversion), and an overestimation of precipitation. Our new scheme overcomes the problem of excessive cloud droplet size. The processes of cloudrain autoconversion and rain accretion by cloud droplets are similar to the stochastic collection equation, and the mixing mechanism of cloud droplets is more consistent with that occurred during the actual physical process in the cloud. Based on the new and old schemes, multiple precipitation processes in the flood season of 2021 along the Sichuan-Xizang Railway are simulated, and the results are evaluated using ground observations and satellite data. Compared to the default scheme, the new scheme is more suitable for the simulation of cloud physics, reducing the simulation deviation of the liquid water path and droplet radius from 2 times to less than 1 time and significantly alleviating the overestimation of precipitation intensity and range of precipitation center. The average root-mean-square error is reduced by 22%. Our results can provide a scientific reference for improving precipitation forecasting and disaster prevention in this region.

关键词： The Sichuan-Xizang Railway Cloud microphysics Precipitation Model improvement

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Quantification of Central and Eastern China's atmospheric CH_(4) enhancement changes and its contributions based on machine learning approach

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Journal of Environmental Sciences 2024年第4期138卷 236-248页

作者： Xinyue Ai Cheng Hu Yanrong Yang Leying Zhang Huili Liu Junqing Zhang Xin Chen Guoqiang Bai Wei Xiao College of Biology and the Environment Joint Center for sustainable Forestry in Southern ChinaNanjing Forestry UniversityNanjing 210037China Collaborative innovation center on Forecast and Evaluation of meteorological Disasters(CIC-FEMD) Nanjing University of Information Science&TechnologyNanjing 210044China Guang’an Vocational&Technical College Guangan 638550China HuaNan meteorological Administration Huanan 154400China

Methane is the second largest anthropogenic greenhouse gas,and changes in atmospheric methane concentrations can reflect the dynamic balance between its emissions and sinks.Therefore,the monitoring of CH_(4) concentration changes and the assessment of underlying driving factors can provide scientific basis for the government’s policy making and evaluation.China is the world’s largest emitter of anthropogenic methane.However,due to the lack of ground-based observation sites,little work has been done on the spatial-temporal variations for the past decades and influencing factors in China,especially for areas with high anthropogenic emissions as Central and Eastern China.Here to quantify atmospheric CH_(4) enhancements trends and its driving factors in Central and Eastern China,we combined the most up-to-date TROPOMI satellite-based column CH_(4)(xCH_(4))concentration from 2018 to 2022,anthropogenic and natural emissions,and a random forest-based machine learning approach,to simulate atmospheric xCH_(4) enhancements from 2001 to 2018.The results showed that(1)the random forest model was able to accurately establish the relationship between emission sources and xCH_(4) enhancement with a correlation coefficient(R^(2))of 0.89 and a root mean-square error(RMSE)of 11.98 ppb;(2)The xCH_(4) enhancement only increased from 48.21±2.02 ppb to 49.79±1.87 ppb from the year of 2001 to 2018,with a relative change of 3.27%±0.13%;(3)The simulation results showed that the energy activities and waste treatment were the main contributors to the increase in xCH_(4) enhancement,contributing 68.00% and 31.21%,respectively,and the decrease of animal ruminants contributed-6.70% of its enhancement trend.

关键词： TROPOMI Methane column concentrations Anthropogenic sources Random Forest model

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Fusion of Ground-Based and Spaceborne Radar Precipitation Based on Spatial Domain Regularization

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Journal of meteorological Research 2024年第2期38卷 285-302页

作者： Anfan HUANG Leilei KOU Yanzhi LIANG Ying MAO Haiyang GAO Zhigang CHU School of Atmospheric Physics Nanjing University of Information Science&TechnologyNanjing 210044 Collaborative innovation center on Forecast and Evaluation of meteorological Disasters Nanjing University of Information Science&TechnologyNanjing 210044

High-quality and accurate precipitation estimations can be obtained by integrating precipitation information measures using ground-based and spaceborne radars in the same target area.Estimating the true precipitation state is a typical inverse problem for a given set of noisy radar precipitation observations.The regularization method can appropriately constrain the inverse problem to obtain a unique and stable solution.For different types of precipitation with different prior distributions,the L_(1) and L_(2) norms were more effective in constraining stratiform and convective precipitation,respectively.As a combination of L_(1) and L_(2) norms,the Huber norm is more suitable for mixed precipitation types.This study uses different regularization norms to combine precipitation data from the C-band dual-polarization ground radar(CDP)and dual-frequency precipitation radar(DPR)on the Global Precipitation Measurement(GPM)mission core satellite.Compared to single-source radar data,the fused figures contain more information and present a comprehensive precipitation structure encompassing the reflectivity and precipitation fields.In 27 precipitation cases,the fusion results utilizing the Huber norm achieved a structural similarity index measure(SSIM)and a peak signal-to-noise ratio(PSNR)of 0.8378 and 30.9322,respectively,compared with the CDP data.The fusion results showed that the Huber norm effectively amalgamate the features of convective and stratiform precipitation,with a reduction in the mean absolute error(MAE;16.1%and 22.6%,respectively)and root-mean-square error(RMSE;11.7%and 13.6%,respectively)compared to the 1-norm and 2-norm.Moreover,in contrast to the fusion results of scale recursive estimation(SRE),the Huber norm exhibits superior capability in capturing the localized precipitation intensity and reconstructing the detailed features of precipitation.

关键词： dual-frequency precipitation radar(DPR) dual-polarization radar data fusion regularization Huber norm

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Impacts of Roof/Ground Mitigation Strategies on Improving the Urban Thermal Environment and Human Comfort over the Yangtze River Delta, China

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Journal of meteorological Research 2024年第1期38卷 108-125页

作者： Hongyun MA Mi ZHANG Haishan CHEN Yan WANG Collaborative innovation center on Forecast and Evaluation of meteorological Disasters(CIC-FEMD)/Key Laboratory of meteorological Disaster Ministry of Education(KLME)/Joint International Research Laboratory of Climate and Environmental Change(ILCEC)Nanjing University of Information Science&TechnologyNanjing 210044 School of Atmospheric Sciences Nanjing UniversityNanjing 210023 Experimental Teaching center for Meteorology and Environment Nanjing University of Information Science&TechnologyNanjing 210044

The combined effects of global warming and the urban heat islands exacerbate the risk of urban heat stress. It is crucial to implement effective cooling measures in urban areas to improve the comfort of the thermal environment. In this study, the Weather Research and Forecasting Model(WRF), coupled with a single-layer Urban Canopy Model(UCM), was used to study the impact of heat mitigation strategies. In addition, a 5-km resolution land-cover dataset for China(ChinaLC), which is based on satellite remote sensing data, was adjusted and used, and 18 groups of numerical experiments were designed, to increase the albedo and vegetation fraction of roof/ground parameters. The experiments were conducted for four heatwave events that occurred in the summer of 2013 in the Yangtze River Delta urban agglomeration of China. The simulated results demonstrated that, for the single roof/ground schemes, the mitigation effects were directly proportional to the albedo and greening. Among all the experimental schemes, the superposed schemes presented better cooling effects. For the ground greening scheme, with similar net radiation flux and latent heat flux, its storage heat was lower than that of the roof greening scheme, resulting in more energy flux into the atmosphere, and its daytime cooling effect was not as good as that of the roof greening scheme. In terms of human thermal comfort(HTC), the improvement achieved by the ground greening scheme was better than any other single roof/ground schemes, because the increase in the relative humidity was small. The comprehensive evaluation of the mitigation effects of different schemes on the thermal environment presented in this paper provides a theoretical basis for improving the urban environment through rational urban planning and construction.

关键词： urban heat island human thermal comfort urban canopy mitigation strategies Yangtze River Delta Weather Research and Forecasting Model(WRF) Urban Canopy Model(UCM)

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FY-3E:The First Operational meteorological satellite Mission in an Early Morning Orbit

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Advances in Atmospheric Sciences 2022年第1期39卷 1-8页

作者： Peng ZHANG Xiuqing HU Qifeng LU Aijun ZHU Manyun LIN Ling SUN Lin CHEN Na XU innovation center for fengyun meteorological satellite National Satellite Meteorological CenterChina Meteorological AdministrationBeijing 100081China

fengyun-3 E(FY-3E),the world’s first early-morning-orbit meteorological satellite for civil use,was launched successfully at the Jiuquan satellite Launch center on 5 July 2021.The FY-3E satellite will fill the vacancy of the global early-morning-orbit satellite observation,working together with the FY-3C and FY-3D satellites to achieve the data coverage of early morning,morning,and afternoon orbits.The combination of these three satellites will provide global data coverage for numerical weather prediction(NWP)at 6-hour intervals,effectively improving the accuracy and time efficiency of global NWP,which is of great significance to perfect the global earth observing system.In this article,the background and meteorological requirements for the early-morning-orbit satellite are reviewed,and the specifications of the FY-3E satellite,as well as the characteristics of the onboard instrumentation for earth observations,are also introduced.In addition,the ground segment and the retrieved geophysical products are also presented.It is believed that the NWP communities will significantly benefit from an optimal temporal distribution of observations provided by the early morning,mid-morning,and afternoon satellite missions.Further benefits are expected in numerous applications such as the monitoring of severe weather/climate events,the development of improved sampling designs of the diurnal cycle for accurate climate data records,more efficient monitoring of air quality by thermal infrared remote sensing,and the quasicontinuous monitoring of the sun for space weather and climate.

关键词： FY-3E operational meteorological satellite early morning orbit

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