FY-3E: The First Operational Meteorological Satellite Mission in an Early Morning Orbit

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.     

Application of Fengyun-4 Satellite to Flood Disaster Monitoring through a Rapid Multi-Temporal Synthesis Approach

Fengyun-4 A(FY-4 A) belongs to the second generation of geostationary meteorological satellite series in China. Its observations with high frequency and resolution provide a better data basis for monitoring of extreme weather such as sudden flood disasters. In this study, the flood disasters occurred in Bangladesh, India, and some other areas of South Asia in August 2018 were investigated by using a rapid multi-temporal synthesis approach for the first time for removal of thick clouds in FY-4 A images. The maximum between-class variance algorithm(OTSU; developed by Otsu in 2007) and linear spectral unmixing methods are used to extract the water area of flood disasters. The accuracy verification shows that the water area of flood disasters extracted from FY-4 A is highly correlated with that from the high-resolution satellite datasets Gaofen-1(GF-1) and Sentinel-1 A, with the square correlation coefficient R2 reaching 0.9966. The average extraction accuracy of FY-4 A is over 90%. With the rapid multi-temporal synthesis approach used in flood disaster monitoring with FY-4 A satellite data, advantages of the wide coverage, fast acquisition,and strong timeliness with geostationary meteorological satellites are effectively combined. Through the synthesis of multi-temporal images of the flood water body, the influence of clouds is effectively eliminated, which is of great significance for the real-time flood monitoring. This also provides an important service guarantee for the disaster prevention and reduction as well as economic and social development in China and the Asia–Pacific region.     

Aerosol Data Assimilation Using Data from Fengyun-3A and MODIS:Application to a Dust Storm over East Asia in 2011

Aerosol optical depth(AOD) is the most basic parameter that describes the optical properties of atmospheric aerosols,and it can be used to indicate aerosol content. In this study, we assimilated AOD data from the Fengyun-3 A(FY-3 A) and MODIS meteorological satellite using the Gridpoint Statistical Interpolation three-dimensional variational data assimilation system. Experiments were conducted for a dust storm over East Asia in April 2011. Each 0600 UTC analysis initialized a24-h Weather Research and Forecasting with Chemistry model forecast. The results generally showed that the assimilation of satellite AOD observational data can significantly improve model aerosol mass prediction skills. The AOD distribution of the analysis field was closer to the observations of the satellite after assimilation of satellite AOD data. In addition, the analysis resulting from the experiment assimilating both FY-3 A/MERSI(Medium-resolution Spectral Imager) AOD data and MODIS AOD data had closer agreement with the ground-based values than the individual assimilation of the two datasets for the dust storm over East Asia. These results suggest that the Chinese FY-3 A satellite aerosol products can be effectively applied to numerical models and dust weather analysis.     

Latest Progress of the Chinese Meteorological Satellite Program and Core Data Processing Technologies

In this paper,the latest progress,major achievements and future plans of Chinese meteorological satellites and the core data processing techniques are discussed.First,the latest three FengYun(FY)meteorological satellites(FY-2H,FY-3D,and FY-4A)and their primary objectives are introduced Second,the core image navigation techniques and accuracies of the FY meteorological satellites are elaborated,including the latest geostationary(FY-2/4)and polar-orbit(FY-3)satellites.Third,the radiometric calibration techniques and accuracies of reflective solar bands,thermal infrared bands,and passive microwave bands for FY meteorological satellites are discussed.It also illustrates the latest progress of real-time calibration with the onboard calibration system and validation with different methods,including the vicarious China radiance calibration site calibration,pseudo invariant calibration site calibration,deep convective clouds calibration,and lunar calibration.Fourth,recent progress of meteorological satellite data assimilation applications and quantitative science produce are summarized at length.The main progress is in meteorological satellite data assimilation by using microwave and hyper-spectral infrared sensors in global and regional numerical weather prediction models.Lastly,the latest progress in radiative transfer,absorption and scattering calculations for satellite remote sensing is summarized,and some important research using a new radiative transfer model are illustrated.     

A Case Study of Impact of FY-2C Satellite Data in Cloud Analysis to Improve Short-Range Precipitation Forecast

Chinese FengYun-2C（FY-2C） satellite data were combined into the Local Analysis and Prediction System（LAPS） model to obtain three-dimensional cloud parameters and rain content. These parameters analyzed by LAPS were used to initialize the Global/Regional Assimilation and Prediction System model（GRAPES） in China to predict precipitation in a rainstorm case in the country. Three prediction experiments were conducted and were used to investigate the impacts of FY-2C satellite data on cloud analysis of LAPS and on short range precipitation forecasts. In the first experiment, the initial cloud fields was zero value. In the second, the initial cloud fields were cloud liquid water, cloud ice, and rain content derived from LAPS without combining the satellite data. In the third experiment, the initial cloud fields were cloud liquid water, cloud ice, and rain content derived from LAPS including satellite data. The results indicated that the FY-2C satellite data combination in LAPS can show more realistic cloud distributions, and the model simulation for precipitation in 1–6 h had certain improvements over that when satellite data and complex cloud analysis were not applied.     

DETECTION OF MULTILAYER CIRRUS CLOUD USING FY-1C DATA

There are ten channels in the FY-1C polar-orbiting meteorological satellite of China.Thesechannels cover visible,near-infrared and infrared spectral bands.Based on simulating analysis ofsingle layer and multilayer clouds that cirrus clouds possibly overlap low water clouds,the casestudy using FY-1C data is performed.Results show that FY-1C data can be used to analyzemultilayer clouds,especially for the ease of low water cloud overlaid by cirrus.     

MODELING AND QUANTITATIVE RETRIEVAL OF FINITE FIELD FOR THE TROPICAL SEA SURFACE WIND SPEED OF THE FY-3B MICROWAVE IMAGER

The purpose of this study is to select a suitable sea wind retrieval method for FY-3B(MWRI). Based on the traditional empirical model of retrieving sea surface wind speed, and in the case of small sample size of FY-3B satellite load regression analysis, this paper analyzes the channel differences between the FY-3B satellite microwave radiation imager(MWRI) and TMI onboard the TRMM. The paper also analyzes the influence of these differences on the channel in terms of receiving temperature, including channel frequency, sensitivity and scaling precision. Then, the limited range of new model coefficient regression analysis is determined(in which the channel range settings include the information and features of channel differences), the regression methods of the finite field are proposed, and the empirical model of wind speed retrieval applicable to MWRI is obtained, which achieves robust results. Compared to the TAO buoy data, the mean deviation of the new model is 0.4 m/s, and the standard deviation is 1.2 m/s. In addition,the schematic diagram of the tropical sea surface wind speed retrieval is provided.     

Thermodynamic phase analysis of cloud particles with FY-1C data

Summary There are ten channels in Chinese FY-1C polar orbiting meteorological satellite. These channels cover visible, near infrared and infrared spectral bands. Based on our simulating analysis of thermodynamic phase of cloud top particles, a case study using FY-1C data is performed. Results show that FY-1C channel 6 (1.58–1.64 μm) can be used to analyze the thermodynamic phase of cloud particles. Received October 10, 2001 Revised December 28, 2001     

PRELIMINARY STUDY ON THE INFLUENCE OF FY-4 LIGHTNING DATA ASSIMILATION ON PRECIPITATION PREDICTIONS

Data from the lightning mapping imager on board the Fengyun-4 meteorological satellite (FY-4) were used to study the assimilation of lightning data and its influence on precipitation predictions. We first conducted a quality control check on the events observed by the first Fengyun-4 satellite (FY-4A) lightning mapping imager, after which the noise points were removed from the lightning distribution. The subsequent distribution was more consistent with the spatial distribution and range of ground-based observations and precipitation. We selected the radar reflectivity, which was closely related to the lightning frequency, as the parameter to assimilate the lightning data and utilized a large sample of lightning frequency and radar reflectivity data from the eastern United States provided by Vaisala. Based on statistical analysis, we found the empirical relationship between the lightning frequency and radar reflectivity and established a look-up table between them. We converted the lightning event data into radar reflectivity data and found that the converted reflectivity and composite reflectivity of ground-based radar observations showed high consistency. We further assimilated the lightning data into the model, adjusted the model cloud analysis process and adjusted the model hydrometeor field by using the lightning data. A rainstorm weather process that occurred on August 8, 2017, in south China was used for the numerical forecast experiment, and three experiments were designed for comparison and analysis: a control experiment, an experiment without the assimilation of FY-4 lightning data (NoLig), and an experiment with the assimilation of FY-4 lightning data (Lig). The results show that after assimilating the FY-4A lightning data, the accuracies of the intensity, central location and range of the precipitation predicted by the Lig experiment were obviously superior to those predicted by the control and NoLig experiments, and the effect was especially obvious in the short-term (1–2 hour) forecast. The studies in this paper highlight the application value and potential of FY-4 lightning data in precipitation predictions.     

Quality Assessment of FY-4A Lightning Data in Inland China

The Lightning Mapping Imager (LMI) equipped on the FY-4A (FengYun-4A) geostationary satellite achieves lightning positioning through optical imaging and has the advantages of high temporal resolution, high stability, and continuous observation. In this study, FY-4A LMI lightning event, group and flash data from April to August 2018 are selected, and their quality are assessed through qualitative and quantitative comparison with the ground-based Advanced Time of Arrival and Direction system (ADTD) lightning observation network data and the American International Space Station (ISS) lightning imaging sensor (LIS) data. The results show that the spatial distributions of FY-4A lightning are consistent with those of the ground-based ADTD and ISS LIS. The temporal variation in FY-4A lightning group frequency is consistent with that of ADTD stroke, which reflects that FY-4A LMI can capture the lightning occurrence in inland China. Quantitative statistics show that the consistency rate of FY-4A LMI and ISS LIS events is relatively high but their consistency rate is lower in terms of lightning group and flash data. Compared with the lightning observations by the ISS LIS and the ground-based ADTD, FY-4A LMI reports fewer lightning events in the Tibetan Plateau. The application of Tibetan Plateau lightning data requires further processing and consideration.     

Evaluation of Cloud Top Height Retrievals from China's Next-Generation Geostationary Meteorological Satellite FY-4A

To evaluate the validity of cloud top height(CTH) retrievals from FY-4A, the first of China's next-generation geostationary meteorological satellite series, the retrievals are compared to those from Himawari-8, CloudSat,Cloud–Aerosol Lidar and Infrared Pathfinder Satellite Observations(CALIPSO), and Moderate Resolution Imaging Spectroradiometer(MODIS) operational products from August to October 2017. Regarding CTHs from CloudSat,CALIPSO, and MODIS as truth, the results show that the performance of FY-4A CTH retrievals is similar to that of Himawari-8. Both FY-4A and Himawari-8 retrieve reasonable CTH values for single-layer clouds, but perform poorly for multi-layer clouds. The mean bias error(MBE) shows that the mean value of FY-4A CTH retrievals is smaller than that of Himawari-8 for single-layer clouds but larger for multi-layer clouds. For ice crystal clouds, both FY-4A and Himawari-8 obtain the underestimated CTHs. However, there is a tendency for FY-4A and Himawari-8 to overestimate the CTH values of CloudSat and CALIPSO mainly for low level liquid water clouds. The temperature inversion near the tops of water clouds may result in an overestimation of CTHs. According to the MBE change with altitude, FY-4A and Himawari-8 overestimate the CTHs mainly for clouds below 3 km, and the overestimation is slightly more apparent in Himawari-8 data than that in FY-4A values. As the cloud optical thickness(COT) increases,the CTH bias of FY-4A CTH retrievals gradually decreases. Two typical cases are analyzed to illustrate the differences between different satellites' CTH retrievals in detail.     

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

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

MONITORING OF 1991 EASTERN CHINA FLOODING WITH POLAR ORBITING METEOROLOGICAL SATELLITES FY-1 AND NOAA

With polar orbiting meteorological satellites FY-1 and NOAA,flooding was monitored in the areas of the HuaiheRiver basin and the Taihu Lake region during June and July 1991.All satellite images from FY-1 and NOAA for concerned areas before and during flooding were examined.Thoseof cloud-free,with small amount of cumulus or thin cirrus were selected to exam the situation.Navigation and projec-tion were carefully performed,to ensure the projected images at different time overlap accurately with each other in 1—2pixels.Channel 1 (CH1) and Channel 2 (CH2) data of FY-1 and NOAA satellites with wavelength of 0.58—0.68μm and0.725—1.1μm were used to monitor the flooding.Albedo of Channel 2 and normalized vegetation index (NDVI) wereadopted as indicators to identify water body from land.With histogram and man-machine interactive methods,analysiswas done.In cloud-free condition,the two indicators identified the same area and scope of the water body.Totally cloud-free image in a large area is quite rare.To understand flood process,it is necessary to use more fre-quent images.It was investigated to distinguish water from land in partly cloudy condition.The result showed that whenthere is small amount of cumulus or thin cirrus,satellite images are still valuable in monitoring water body.In case ofmonitoring area covered with cirrus,vegetation index is useful,and while there is small amount of cumulus on land,albedo of Channel 2 can be used.Ten images from May 16 to August 18 of 1991 were examined.The results show that in the Lixiahe area,JiangsuProvince,the area submerged in total was the largest;along main stream of the Huaihe River,the Chuhe River,andaround the Chaohu Lake,a large percentage of area submerged;while in the Taihu Lake area,less field submerged.Flood monitoring was performed for 87 counties in the region concerned.These counties were put in order accord-ing to the percentage of submerged area in total.This order showed the extent of disaster at one view point.     

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

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 satellites. Fengyun-3E(FY-3E) was launched successfully on 5 July 2021 in China. As 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 system. In th...     

FY-3A SATELLITE MICROWAVE DATA ASSIMILATION EXPERIMENTS IN TROPICAL CYCLONE FORECAST

China’s new generation of polar-orbiting meteorological satellite FY-3A was successfully launched on May 26,2008,carrying microwave sounding devices which had similar performance to ATOVS of NOAA series.In order to study the application of microwave sounding data in numerical prediction of typhoons and to improve typhoon forecasting,we assimilated data directly for numerical forecasting of the track and intensity of the 2009 typhoon Morakot(0908)based on the WRF-3DVar system.Results showed that the initial fields of the numerical model due to direct assimilation of FY-3A microwave sounding data was improved much more than that due to assimilation of conventional observations alone,and the improvement was especially significant over the ocean,which is always without conventional observations.The model initial fields were more reasonable in reflecting the initial situation of typhoon circulation as well as temperature and humidity conditions,and typhoon central position at sea was also adjusted.Through direct 3DVar assimilation of FY-3A microwave data,the regional mesoscale model improves the forecasting of typhoon track.Therefore,the FY-3A microwave data could efficiently improve the numerical prediction of typhoons.     

Vegetation Products Derived from Fengyun-3D Medium Resolution Spectral Imager-Ⅱ

The surface vegetation condition has been operationally monitored from space for many years by the Advanced Very High Resolution Radiometer(AVHRR) and the Moderate Resolution Imaging Spectroradiometer(MODIS) instruments. As these instruments are close to the end of their design life, the surface vegetation products are required by many users from the new satellite missions. The MEdium Resolution Spectral Imager-Ⅱ(MERSI-Ⅱ) onboard the Fengyun(FY) satellite(FY-3 series; FY-3 D) is used to retrieve surface vegetation parameters. First, MERSI-Ⅱ solar channel measurements at the red and near-infrared(NIR) bands at the top of atmosphere(TOA) are corrected to the surface reflectances at the top of canopy(TOC) by removing the contributions of scattering and absorption of molecules and aerosols. The normalized difference vegetation index(NDVI) at both the TOA and TOC is then produced by using the same algorithms as the MODIS and AVHRR. The MERSI-Ⅱ enhanced VI(EVI) at the TOC is also developed. The MODIS technique of compositing the NDVI at various timescales is applied to MERSI-Ⅱ to generate the gridded products at different resolutions. The MERSI-Ⅱ VI products are consistent with the MODIS data without systematic biases. Compared to the current MERSI-Ⅱ EVI generated from the ground operational system, the MERSI-Ⅱ EVI from this study has a much better agreement with MODIS after atmospheric correction.     

Three-dimensional Extension of the Unit-Feature Spatial Classification Method for Cloud Type

We describe how the Unit-Feature Spatial Classification Method(UFSCM) can be used operationally to classify cloud types in satellite imagery efficiently and conveniently.By using a combination of Interactive Data Language(IDL) and Visual C++(VC) code in combination to extend the technique in three dimensions(3-D),this paper provides an efficient method to implement interactive computer visualization of the 3-D discrimination matrix modification,so as to deal with the bi-spectral limitations of traditional two dimensional(2-D) UFSCM.The case study of cloud-type classification based on FY-2C satellite data (0600 UTC 18 and 0000 UTC 10 September 2007) is conducted by comparison with ground station data, and indicates that 3-D UFSCM makes more use of the pattern recognition information in multi-spectral imagery,resulting in more reasonable results and an improvement over the 2-D method.     

On Eastern Asian Dust Storm

In this paper, the characteristics of eastern Asian dust storm are examined with emphasis on the satellite measurements of aerosol optical thickness. The reflectivity of solar radiation from the earth’s atmosphere depends on the optical thickness. The satellite measurement of radiance of sunlight, scattered by the earth and its atmosphere, is used to derive the properties of aerosol on oceanic surfaces. This paper involves the following: (1) investigation of the measurement of dust storm over the oceanic surface by GMS satellite; (2) investigation of the measurement of dust storm over the land surface by ground-based instruments such as actinometer, lidar, etc.; (3) for comparison, de-riving an atmospheric aerosol size distribution over the oceanic surface of calm weather through measurements of NOAA satellite; and (4) the weather process and its mass load of eastern Asian dust storm.     

Comparisons of AGRI/FY-4A Cloud Fraction and Cloud Top Pressure with MODIS/Terra Measurements over East Asia

Fengyun-4 A(FY-4 A), the second generation of China's geostationary meteorological satellite, provides high spatiotemporal resolution cloud products over East Asia. In this study, cloud fraction(CFR) and cloud top pressure(CTP)products in August 2017 derived from the Advanced Geosynchronous Radiation Imager(AGRI) aboard FY-4 A(AGRI/FY-4 A) are retrospectively compared with those from the Moderate Resolution Imaging Spectroradiometer(MODIS) aboard Terra(MODIS/Terra) over East Asia. To avoid possible errors in the comparison caused by the lower temporal coverage of MODIS/Terra products compared to that of AGRI/FY-4 A over the same region and to account for time lags between observations of the two instruments, we construct datasets of AGRI/FY-4 A CFR and CTP to match those of MODIS/Terra in each scan over East Asia in August 2017. Results show that the CFR and CTP datasets of the two instruments generally agree well, with the linear correlation coefficients(R) between CFR(CTP)data of 0.83(0.80) regardless of time lags. Though longer time lags contribute to the worse consistency between CFR(CTP) data derived from observations of the two instruments in most cases, large CFR/CTP discrepancies do not always match with long time lags. Large CFR discrepancies appear in the vicinity of the Tibetan Plateau(TP;28°–45°N, 75°–105°E). These differences in the cloud detection by the two instruments largely occur when MODIS/Terra detects clear-sky while AGRI/FY-4 A detects higher values of CFR, and this accounts for 61% of the CFR discrepancy greater than 50% near the TP. In the case of CTP, the largest discrepancies appear in the eastern Iranian Plateau(IP; 25°–45°N, 60°–80°E), where there are some samples with long time lags(20–35 min) and fewer daily data samples are available for computing monthly means compared to other regions since there are many clearsky data samples there during the study period.     

Application of FY-2C Cloud Drift Winds in a Mesoscale Numerical Model

Statistical tests and error analysis of cloud drift winds(CDWs) from the FY-2C satellite were made by using radiosonde observations.According to the error characteristics of the CDW,a bias correction using the thermal wind theory was applied in the data quality control.The CDW data were then assimilated into the GRAPES-meso model via the GRAPES-3DVar.A torrential rain event that occurred in northwestern China during 1-2 July 2005 was simulated.The results indicate that the CDW data were mainly distribute...