Polarimetric Meteorological Satellite Data Processing Software Classification Based on Principal Component Analysis and Improved K-Means Algorithm

With the increasing variety of application software of meteorological satellite ground system, how to provide reasonable hardware resources and improve the efficiency of software is paid more and more attention. In this paper, a set of software classification method based on software operating characteristics is proposed. The method uses software run-time resource consumption to describe the software running characteristics. Firstly, principal component analysis (PCA) is used to reduce the dimension of software running feature data and to interpret software characteristic information. Then the modified K-means algorithm was used to classify the meteorological data processing software. Finally, it combined with the results of principal component analysis to explain the significance of various types of integrated software operating characteristics. And it is used as the basis for optimizing the allocation of software hardware resources and improving the efficiency of software operation.

Statistical Downscaling Retrieval of Land Surface Temperature in an Area with Complex Landforms in the Eastern Qinling Mountains of China Based on Sentinel-2/3 Satellite Data

The study of land surface temperature(LST)is of great significance for ecosystem monitoring and ecological environmental protection in the Qinling Mountains of China.In view of the contradicting spatial and temporal resolutions in extracting LST from satellite remote sensing(RS)data,the areas with complex landforms of the Eastern Qinling Mountains were selected as the research targets to establish the correlation between the normalized difference vegetation index(NDVI)and LST.Detailed information on the surface features and temporal changes in the land surface was provided by Sentinel-2 and Sentinel-3,respectively.Based on the statistically downscaling method,the spatial scale could be decreased from 1000 m to 10 m,and LST with a Sentinel-3 temporal resolution and a 10 m spatial resolution could be retrieved.Comparing the 1 km resolution Sentinel-3 LST with the downscaling results,the 10 m LST downscaling data could accurately reflect the spatial distribution of the thermal characteristics of the original LST image.Moreover,the surface temperature data with a 10 m high spatial resolution had clear texture and obvious geomorphic features that could depict the detailed information of the ground features.The results showed that the average error was 5 K on April 16,2019 and 2.6 K on July 15,2019.The smaller error values indicated the higher vegetation coverage of summer downscaling result with the highest level on July 15.

A PRIMARY STUDY OF SUMMER MONSOON INDEX OVER THE SOUTH CHINA SEA AND EAST ASIA BASED ON SATELLITE OBSERVATION

The results by statistical analysis of black body Temperature (TBB) pentad mean from the Japanese GMS in the period of May to August, 1980-2002, show that the summer monsoon index (SMI) is defined to be the pentad mean TBB≤273 K. Its intensity includes three levels: TBB>268 K for weak monsoon, 268 K≥TBB>263 K for normal monsoon and TBB≤263K for strong monsoon over the South China sea and East Asia. In the meantime, a diagnostic method using TBB pentad anomaly is also introduced to help identify monsoon intensity. The SMI is used to run statistical analyses of the initial onset of the monsoon and its pentad variations with the year and month. A fairly close relationship is found between pentad monsoon activity and heavy rainfall periods in the two typical flood years of 1994 and 1998, which resulted from heavy rainfall over the Yangtze River basin and south China.

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

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.

FY-3A/MERSI, ocean color algorithm, products and demonstrative applications

A medium resolution spectral imager （MERSI） on-board the first spacecraft of the second generation of Chinas polar-orbit meteorological satellites FY-3A, is a MODIS-like sensor with 20 bands covering visible to thermal infrared spectral region. FY-3A/MERSI is capable of making continuous global observations, and ocean color application is one of its main targets. The objective is to provide information about the ocean color products of FY-3A/MERSI, including sensor calibration, ocean color algorithms, ocean color prod- ucts validation and applications. Although there is a visible on-board calibration device, it cannot realize the on-board absolute radiometric calibration in the reflective solar bands. A multisite vicarious calibration method is developed, and used for monitoring the in-flight response change and providing post-launch cal- ibration coefficients updating. FY-3A/MERSI ocean color products consist of the water-leaving reflectance retrieved from an atmospheric correction algorithm, a chlorophyll a concentration （CHL1） and a pigment concentration （PIG1） from global empirical models, the chlorophyll a concentration （CHL2）, a total sus- pended mater concentration （TSM） and the absorption coefficient of CDOM and NAP （YS443） from Chi- na＇s regional empirical models. The atmospheric correction algorithm based on lookup tables and ocean color components concentration estimation models are described. By comparison with in situ data, the FY-3A/MERSI ocean color products have been validated and preliminary results are presented. Some suc- cessful ocean color applications such as algae bloom monitoring and coastal suspended sediment variation have demonstrated the usefulness of FY-3A/MERSI ocean color products.

Progress on Observation of Cryospheric Components and Climate-Related Studies in China

Systematic studies on the cryosphere in China started in the late 1950s. Significant achievements have been made by continuous investigation of glacier inventories, frozen ground observations, paleo-climate analyses of ice cores, process studies and the modeling of cryopsheric/atmospheric interactions. The general facts and understanding of these changes include： （1） Solid precipitation, including the number of days with frost and hail storms, shows a decreasing tendency over the past half century. （2） In most areas glaciers are retreating or have completely vanished （〉80%）, some glaciers are still advancing （5%-20% depending upon time period）. The annual glacial melt water has been increasing since the 1980s. This increased supply of melt water to river runoff in Northwest China is about a 10%-13%. （3） The long-term variability of snow cover in western China is characterized by a large inter-annual variation superimposed on a small increasing trend. Snow cover variability in the Qinghai-Xizang Plateau （QXP） is influenced by the Indian monsoon, and conversely impacts monsoon onset and strength and eventually the drought and flood events in middle-low reaches of Yangtze River. （4） Frozen ground, including permafrost, is decaying both in QXP and in Northeast China. The most significant changes occurred in the regions with thickest seasonal frozen ground （SFG）, i.e., inland QXP, then northeastern and northwestern QXP. The cold season air temperature is the main factor controlling SFG change. The increase of ground surface temperatures is more significant than air temperature. （5） The sea ice coverage over the Bohai Sea and Yellow Sea has deceased since the 1980s. （6） River ice duration and ice thickness is also decreasing in northern China. In 2001, the Chinese National Committee of World Climate Research Program/Climate and Cyosphere （WCRP/CliC） （CNC-CliC） was organized to strengthen research on climate and cryosphere in China. Future monitoring of the cryosphere in China will be enhanced both in spatial coverage and through the use of new techniques. Interactions between atmosphere/cryosphere/hydrosphere/land-surface will be assessed to improve our understanding of the mechanisms of cryospheric change.

Growing Operational Use of FY-3 Data in the ECMWF System

This paper reviews the data quality and impact of observations from the FY-3 satellite series used operationally in the ECMWF system. This includes data from the passive microwave radiometers MWHS-1, MWHS-2 and MWRI, as well as observations from the radio occultation receiver GNOS. Evaluations against background equivalents show that the quality of the observations is broadly comparable to that of similar instruments on other polar-orbiting satellites, even though biases for the passive microwave observations can be somewhat larger and more complex for some channels. An observing system experiment shows that the FY-3 instruments jointly contribute significantly to the forecast skill in the ECMWF system. Positive impact of up to 2% is seen for most variables out to the day-2 forecasts over hemispheric scales, with significant benefits for total column water vapor or for temperature and wind in the stratosphere out to day 4.

Scattering and absorption characteristics of non-spherical cirrus cloud ice crystal particles in terahertz frequency band

We used discrete dipole approximation(DDA)to examine the scattering and absorption characteristics of spherical ice crystal particles.On this basis,we studied the scattering characteristics of spherical ice crystal particles at different frequencies and non-spherical ice crystal particles with different shapes,aspect ratios,and spatial orientations.The results indicate that the DDA and Mie methods yield almost the same results for spherical ice crystal particles,illustrating the superior calculation accuracy of the DDA method.Compared with the millimeter wave band,the terahertz band particles have richer scattering characteristics and can detect ice crystal particles more easily.Different frequencies,shapes,aspect ratios,and spatial orientations have specific effects on the scattering and absorption characteristics o f ice crystal particles.The results provide an important theoretical basis for the design of terahertz cloud radars and related cirrus detection methods.

A Thorough Evaluation of the Passive Microwave Radiometer Measurements onboard Three Fengyun-3 Satellites

Microwave Radiometer Imager(MWRI) is a key payload of China’s second generation polar meteorological satellite, i.e., Fengyun-3 series(FY-3). Up to now, 5 satellites including FY-3A(2008), FY-3B(2010), FY-3C(2013), FY-3D(2018), and FY-3E(2021) have been launched successfully to provide multiwavelength, all-weather, and global data for decades. Much progress has been made on the calibration of MWRI and a recalibrated MWRI brightness temperature(BT) product(V2) was recently released. This study thoroughly evaluates the accuracy of this new product from FY-3B, 3C, and 3D by using the simultaneous collocated Global Precipitation Measurement(GPM)Microwave Imager(GMI) measurements as a reference. The results show that the mean biases(MBEs) of the BT between MWRI and GMI are generally less than 0.5 K and the root mean squares(RMSs) between them are less than1.5 K. The previous notable ascending and descending difference of the MWRI has disappeared. This indicates that the new MWRI recalibration procedure is very effective in removing potential errors associated with the emission of the hot-load reflector. Analysis of the dependence of MBE on the latitude and earth scene temperature shows that MBE decreases with decreasing latitude over ocean. Furthermore, MBE over ocean decreases linearly with increasing scene temperature for almost all channels, whereas this does not occur over land. A linear regression fitting is then used to modify MWRI, which can reduce the MBE over ocean to be within 0.2 K. The standard deviation of error of GMI, FY-3B, and FY-3D MWRI BT data derived by using the three-cornered hat method(TCH) shows that GMI has the best overall performance over ocean except at 10.65 GHz where its standard deviation of error is slightly larger than that of FY-3D. Over land, the standard deviation of error of FY-3D is the lowest at almost all channels except at 89V. MWRI onboard FY-3 series satellites would serve as an important passive microwave radiometer member of the constellation to monitor key surface and atmospheric properties.

Tropical Cyclone Monitoring and Analysis Techniques: A Review

Tropical cyclones(TCs),including tropical depressions and different categories of typhoons,hurricanes,and cyclonic storms,mostly originate over the oceans in the absence of direct observations.Thus,detailed monitoring and analysis of TCs has always been an unsolved problem.In the recent 20 years,great changes have taken place in domestic and foreign TC monitoring techniques,imposing a significant impact on TC operations and research.Some new technologies and products gradually emerge to support operations,with improved monitoring accuracy.In this paper,the progress on TC monitoring and analysis via meteorological satellites,radars,and airplanes in China and the world is reviewed,compared,and summarized,with special focuses on multisatellite fusion observations,in situ aircraft measurements,and some unconventional observation equipment such as rockets,saildrones,and underwater gliders.On this basis,the paper points out future directions for improving TC monitoring and analysis in aid of better TC forecast and early warning.

Evaluation of the Madden–Julian Oscillation in Fengyun-3B Polar-Orbiting Satellite Reprocessed OLR Data

The present study compares the spatial and temporal characteristics of the Madden-Julian Oscillation(MJO)in Fengyun-3B(FY-3B)polar-orbiting satellite reprocessed outgoing longwave radiation(OLR)data and NOAA OLR data during 2011-2020.The spatial distributions of climatological mean and intraseasonal standard deviation of FY-3B OLR during boreal winter(November-April)and boreal summer(May-October)are highly consistent with those of NOAA OLR.The FY-3B and NOAA OLRs display highly consistent features in the wavenumber-frequency spectra,the occurrence frequency of MJO active days,the eastward propagation of MJO along the equator,and the interannual variability of MJO according to diagnoses using the all-season multivariate EOF analysis.These results indicate that the FY-3B OLR produced by the polar-orbiting satellites is of high quality and worthy of global application.

First Look of Surface Vegetation from the Advanced Geostationary Radiation Imager(AGRI) onboard Fengyun-4B

For many years, the status of surface vegetation has been monitored by using polar-orbiting satellite imagers such as Moderate Resolution Imaging Spectroradiometer(MODIS). However, limited availability of clear-sky samples makes the derived vegetation index dependent on multiple days of observations. High-frequency observations from the geostationary Fengyun(FY) satellites can significantly reduce the influence of clouds on the synthesis of terrestrial normalized difference vegetation index(NDVI). In this study, we derived the land surface vegetation index based on observational data from the Advanced Geostationary Radiation Imager(AGRI) onboard the FY-4B geostationary satellite. First, the AGRI reflectance of visible band and near-infrared band is corrected to the land surface reflectance by the 6S radiative transfer model. The bidirectional reflectance distribution function(BRDF) model is then used to normalize the AGRI surface reflectance at different observation angles and solar geometries, and an angle-independent reflectance is derived. The AGRI surface reflectance is further corrected to the MODIS levels according to the AGRI spectral response function(SRF). Finally, the daily AGRI data are used to synthesize the surface vegetation index. It is shown that the spatial distribution of NDVI images retrieved by single-day AGRI is consistent with that of 16-day MODIS data. At the same time, the dynamic range of the revised NDVI is closer to that of MODIS.

Random Forest-Based Snow Cover Mapping in China Using Fengyun-3B VIRR Data

Currently,there is variability in the spectral band thresholds for snow cover recognition using remote sensing in different regions and for complex terrains.Using Fengyun-3B Visible and Infra-Red Radiometer(FY-3B VIRR)satellite data,we applied random forest(RF)methodology and selected 13 feature variables to obtain snow cover.A training set was generated,containing approximately 1 million snow and nonsnow samples obtained in China from the snow monitoring reports issued by the National Satellite Meteorological Centre and four snow cover products from the Interactive Multi-sensor Snow and Ice Mapping System(IMS),the FY-3B Multi-Sensor Synergy(MULSS),the Moderate Resolution Imaging Spectroradiometer(MODIS)snow cover product(MYD10A1),and the National Cryosphere Desert Data Center(NCDC).This training set contained many different samples of cloud types and snow under forest cover to help effectively distinguish snow and clouds and improve the recognition rate of snow under forest cover.Then,two RF snow cover recognition models were constructed for the snow and nonsnow seasons and they were used to conduct daily snow cover recognition in China from 2011 to 2020.The results show that the RF models constructed based on FY-3B VIRR data have good recognition performance for shallow snow,understory snow,and snow on the Qinghai–Tibetan Plateau.The recognition accuracy against weather stations and the spatial consistency with the IMS product are better than the MULSS,MYD10A1,and NCDC products.The overall accuracy of the RF product is 90.6%,and the recall rate is 93.8%.The omission and commission errors are 6.2%and11.1%,respectively.Unlike other existing snow cover algorithms,the established RF model skips the complicated atmospheric correction and cloud identification processes and does not involve external auxiliary data;thus,it is more easily popularized and operationally applicable to generating long-time series snow cover products.

Ecological Assessment of Oxygen Balance:A Case Study of China’s Natural Oxygen Bars

Ecological assessment plays a vital role in sustainable development of the environment,and thus exploration of specific and integrated ecological assessment methods has become a critical task.In this study,based on the concept of oxygen balance and by accommodating both natural factors and socioeconomic elements,we establish an oxygen(O_(2))balance index(OBI),i.e.,the ratio of the O_(2)production from the ecosystem to the O_(2)consumption by human behavior,based on the net primary productivity(NPP),fuel consumption,gross domestic production(GDP),population data,and so on.The results show that the spatial distributions of OBI in China are intimately correlated to the regional vegetation and socioeconomic development.The estimated OBI values are then validated by statistical data from 27 counties in China,and it is found that the OBI reflects the ecological environment status well.Moreover,the average OBI values derived from 190 natural oxygen bars in China reveal extreme imbalance between O_(2)production and consumption in highly developed regions,especially in the cities,in contrast to good O_(2)balance in areas with high-quality ecological status and less industrialization.The findings from this study have quantitatively captured the regional ecological quality,providing guidance for sustainable natural and socioeconomic developments in local areas of China.

Impacts of the Urban Spatial Landscape in Beijing on Surface and Canopy Urban Heat Islands

How does the urban spatial landscape(USL)pattern affect the land surface urban heat islands(SUHIs)and canopy urban heat islands(CUHIs)?Based on satellite and meteorological observations,this case study compares the impacts of the USL pattern on SUHI and CUHI in the central urban area(CUA)of Beijing using the satellite land-surface-temperature product and hourly temperature data from automatic meteorological stations from 2009 to 2018.Eleven USL metrics—building height(BH),building density(BD),standard deviation of building height(BSD),floor area ratio(FAR),frontal area index(FAI),roughness length(RL),sky view factor(SVF),urban fractal dimension(FD),vegetation coverage(VC),impervious coverage(IC),and albedo(AB)—with a 500-m spatial resolution in the CUA are extracted for comparative analysis.The results show that SUHI is higher than CUHI at night,and SUHI is only consistent with CUHI at spatial-temporal scales at night,particularly in winter.Spatially,all 11 metrics are strongly correlated with both the SUHI and CUHI at night,with stronger correlation between most metrics and SUHI.VC,AB,and SVF have the greatest impact on both the SUHI and CUHI.High SUHI and CUHI values tend to appear in areas with BD≥0.26,VC≤0.09,AB≤0.09,and SVF≤0.67.In summer,most metrics have a greater impact on the SUHI than CUHI;the opposite is observed in winter.SUHI variation is affected primarily by VC in summer and by VC and AB in winter,which is different for the CUHI variation.The collective contribution of all 11metrics to SUHI spatial variation in summer(61.8%)is higher than that to CUHI;however,the opposite holds in winter and for the entire year,where the cumulative contribution of the factors accounts for 66.6%and 49.6%,respectively,of the SUHI variation.

Performances of six reanalysis profile products in the atmospheric correction of passive microwave data for estimating land surface temperature under cloudy-sky conditions

Passive microwave(PMW)observations from the Advanced Microwave Scanning Radiometer 2 provide a way to obtain cloudy land surface temperatures(LSTs).However,atmospheric corrections must be performed on cloudy LSTs due to the cloud effect at higher frequencies.In this paper,six reanalyzed profiles,including the fifth-generation European Centre for Medium-range Weather Forecasts Reanalysis(ERA5),Interim Reanalysis(ERA-Interim),Japanese 55-year Reanalysis Data(JRA-55),Modern-Era Retrospective analysis for Research and Application V2(MERRA2),National Centers for Environmental Prediction(NCEP)/Final Operational Global Analysis(FNL),and NCEP/Global Forecasting System(GFS),were compared with 2829 radiosonde profiles derived from the University of Wyoming.Then,their performances in correcting the atmospheric effects of LSTs at cloudy skies were investigated.Results showed that the ERA5 had the best accuracy in revealing the actual atmospheric conditions,and the RMSEs of transmittance,downward radiance,and upward radiance were about 0.007,2.01,and 1.89 K,respectively.The RMSEs between the estimated LSTs and referenced LSTs varied from 3.15 K of the ERA5 to 6.12 K of the NCEP/FNL,indicating the ERA5 can be recommended for the atmospheric correction of PMW-based LST retrievals.Additionally,transmittance accuracy plays an essential role in impacting the LST retrievals in any weather.