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

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

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

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

关键词： data assimilation microwave temperature sounder MWTS-3

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Identifying Supercooled Liquid Water in Cloud Based on Airborne Observations: Correlation of Cloud Particle Number Concentration with Icing Probability and Proportion of Spherical Particles

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Journal of Meteorological Research 2022年第4期36卷 574-585页

作者： Yuquan ZHOU Can SONG Miao CAI Siyao LIU Yang GAO Rong ZHANG CMA Cloud–Precipitation Physics and Weather Modification Key Laboratory(CPML) Beijing 100081 Weather Modification Center of Henan Province Zhengzhou 450000 College of Global Change and Earth System Science Beijing Normal UniversityBeijing 100875

Identifying supercooled liquid water(SLW)in clouds is critical for weather modification,aviation safety,and atmospheric radiation ***,aircraft identification in the SLW area mostly depends on emprical estimation of cloud particle number concentration(N_(c))in China,and scientific verification and quantitative identification criteria are urgently *** this study,the observations are from the Fast Cloud Droplets Probe,Rosemount ice detector(RICE),and Cloud Particle Imager(CP_(i))onboard a King Air aircraft during seven flights in 2018 and 2019 over central and eastern *** on this,the correlation among N_(c),the proportion of spherical particles(P_(s)),and the probability of icing(P_(i))in supercooled stratiform and cumulus-stratus clouds is statistically ***,this study proposes a method to identify SLW areas using N_(c) in combination with ambient *** reliability of this method is evaluated through the true skill statistics(TSS)and threat score(TS)*** airborne observations during the seven flights reveal a strong correlation among Nc,P_(s),and P_(i)at the temperature from 0 to−18°*** Nc is greater than a certain threshold of 5 cm^(−3),there is always the SLW,i.e.,P_(i)and P_(s)are *** results demonstrate that the TSS and TS values for Nc=5 cm^(−3)are higher than those for Nc5 cm^(−3))corresponds to a higher SLW identification hit rate and a higher SLW ***,Nc=5 cm^(−3)can be used as the minimum criterion for identifying the SLW in clouds at temperature lower than 0°*** SLW identification method proposed in this study is especially helpful in common situations where aircraft are equipped with only Nc probes and without the CP_(i)and RICE.

关键词： supercooled liquid water(SLW) icing probability cloud particle shape cloud particle number concentration

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Predicting community traits along an alpine grassland transect using field imaging spectroscopy

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Journal of Integrative Plant Biology 2023年第12期65卷 2604-2618页

作者： Feng Zhang Wenjuan Wu Lang Li Xiaodi Liu Guangsheng Zhou Zhenzhu Xu State Key Laboratory of Vegetation and Environmental Change Institute of Botanythe Chinese Academy of SciencesBeijing100093 China China National Botanical Garden Beijing100093 China University of Chinese Academy of Sciences Beijing100049 China Chinese Academy of Meteorological Sciences Beijing100081 China

Assessing plant community traits is important for understanding how terrestrial ecosystems respond and adapt to global climate *** hyperspectral remote sensing is effective for quantitatively estimating vegetation properties in most terrestrial ecosystems,although it remains to be tested in areas with dwarf and sparse vegetation,such as the Tibetan *** measured canopy reflectance in the Tibetan Plateau using a handheld imaging spectrometer and conducted plant community investigations along an alpine grassland *** estimated community structural and functional traits,as well as community function based on a field survey and laboratory analysis using 14 spectral vegetation indices(VIs)derived from hyperspectral *** quantified the contributions of environmental drivers,VIs,and community traits to community function by structural equation modelling(SEM).Univariate linear regression analysis showed that plant community traits are best predicted by the normalized difference vegetation index,enhanced vegetation index,and simple *** equation modelling showed that VIs and community traits positively affected community function,whereas environmental drivers and specific leaf area had the opposite ***,VIs integrated with environmental drivers were indirectly linked to community function by characterizing the variations in community structural and functional *** study demonstrates that community-level spectral reflectance will help scale plant trait information measured at the leaf level to larger-scale ecological *** imaging spectroscopy represents a promising tool to predict the responses of alpine grassland communities to climate change.

关键词： aboveground net primary productivity canopy chlorophyll content canopy leaf nitrogen concentration fractional vegetation cover hyperspectral remote sensing Tibetan Plateau

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Assessing CMIP6 simulations of Arctic sea ice drift:Role of near-surface wind and surface ocean current in model performance

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Advances in Climate Change Research 2023年第5期14卷 691-706页

作者： Xue WANG Ran LU Shao-Yin WANG Run-Tong CHEN Zhuo-Qi CHEN Feng-Ming HUI Hua-Bing HUANG Xiao CHENG School of Geospatial Engineering and Science Sun Yat-sen Universityand Southern Marine Science and Engineering Guangdong Laboratory(Zhuhai)Zhuhai 519082China Key Laboratory of Comprehensive Observation of Polar Environment(Sun Yat-sen University) Ministry of EducationZhuhai 519082China

Sea ice drift is a critical parameter for understanding the rapid changes in Arctic sea *** the release of the Coupled Model Intercomparison project Phase 6(CMIP6),there has been a lack of quantitative analysis regarding CMIP6's simulation of Arctic sea ice *** study aims to assess the simulated Arctic sea ice drift from 1979 to 2014 by fifteen CMIP6 models against recent satellite retrievals,utilizing various quantitative ***,the influence of near-surface wind and surface ocean current on model performance is further *** CMIP6 models capture several aspects of the observed Arctic sea ice drift climatology and *** seasonal patterns of sea ice drift speed in all models exhibit similarities with the observed data,and the models agree with the evaluation datasets,indicating that the seasonal evolution of sea ice drift corresponds to near-surface wind ***,notable discrepancies are *** models overestimate sea ice drift speed,exceeding the observational data by 36%e97%.Fourteen out of fifteen models display larger seasonal variability(ranging from 0.74 to 1.28 km d^(-1))compared to the observed data(0.54 km d^(-1)).Seven out of fifteen models exhibit a significant increasing trend in annual sea ice drift speed,similar to the observed trend of 0.58 km d^(-1) per decade,but with weaker trends(ranging from 0.11 to 0.33 km d^(-1) per decade).The remaining eight models reveal no statistically significant *** potential causes of such biases were further explored in this *** suggests that the overestimation of sea ice drift speed in the models might be primarily attributed to the overestimation of near-surface wind speeds and their influence on sea ice drift *** models'overestimation of seasonal variability in near-surface wind speeds may account for the overestimation of seasonal variability in sea ice *** models'inability to represent the trend in sea ice drift speed may result fr

关键词： Arctic sea ice drift CMIP6 Model evaluation Near-surface wind Surface ocean current

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Variability of Sea Ice from 2008 to 2019 in the Bohai and Northern Huanghai Sea, China and the Relationship with Climatic Factors

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Journal of Ocean University of China 2022年第5期21卷 1189-1197页

作者： GONG Shaoqi CHEN Wenqian ZHANG Cunjie YAN Qingyun YANG Hong School of Remote Sensing and Geomatics Engineering Nanjing University of Information Science and TechnologyNanjing 210044China National Climate Center China Meteorological AdministrationBeijing 100081China Department of Geography and Environment Science University of ReadingReading RG66ABUK

Sea ice has important effect on the marine ecosystem and people living in the surrounding regions in ***,the understanding on changes of sea ice in the Bohai and northern Huanghai Sea(BNHS),China is still *** on the images from Visible and InfraRed Radiometer(VIRR)onboard Chinese second generation polar-orbit meteorological series satellites FY-3A/B/C,the sea ice areas in the BNHS were extracted from December 2008 to March 2019,the spatio-temporal distribution charac-teristics of sea ice and the relationship between sea ice area and climatic factors were analyzed,then a preliminary sea ice forecast model based on the climatic factors was *** results showed that sea ice area in the BNHS in each December was relatively small and rather high sea ice occurrence probability appeared in the offshore areas in Liaodong Bay and northern Huanghai *** sea ice area in January or February each year was the largest,and sea ice occurred in most of areas in Liaodong Bay and northern Huanghai Sea with rather high probability and in some areas in Bohai Bay and Laizhou Bay with relatively high ***-ever,the sea ice area in each March was the smallest,and sea ice was even melted completely occasionally,hence with relatively low occurrence probability in Liaodong *** for the inter-annual variability of sea ice in the BNHS during the research period,the sea ice area was largest in winter 2010/11 and smallest in winter 2014/15,and annual sea ice area presented a decreasing *** at-mospheric temperature,western Pacific subtropical high(WPSH),Asia polar vortex(APV),Asian monsoon circulation(AMC)and Eurasian monsoon circulation(EMC)were very important climatic factors for sea ice formation and they had significant correlations with sea ice ***,a preliminary sea ice forecast model was constructed by using eight climatic factors including western Pacific subtropical high area index(WPSHAI),western Pacific subtropical high intensi

关键词： sea ice polar-orbit meteorological series satellites FY-3/VIRR Bohai Sea climatic factors

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Granulation-based LSTM-RF combination model for hourly seasurface temperature prediction

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International Journal of Digital Earth 2023年第1期16卷 3838-3859页

作者： Mengmeng Cao Kebiao Mao Sayed M.Bateni Changhyun Jun Jiancheng Shi Yongming Du Guoming Du Hulunbeir Grassland Ecosystem Research Station Institute of Agricultural Resources and Regional PlanningChinese Academy of Agricultural SciencesBeijingPeople’s Republic of China State Key Laboratory of Remote Sensing Science Aerospace Information Research InstituteChinese Academy of SciencesBeijingPeople’s Republic of China School of Physics and Electronic-Engineering Ningxia UniversityNingxia University750021China Department of Civil and Environmental Engineering and Water Resources Research Center University of Hawaii at Mano1HonoluluHIUSA Department of Civil and Environmental Engineering College of EngineeringChung-Ang UniversitySeoulSouth Korea National Space Science Center Chinese Academy of SciencesBeijingPeople’s Republic of China School of Public Administration and Law Northeast Agricultural UniversityHarbinPeople’s Republic of China

Accurate predictions of sea surface temperature(SST)are crucial due to the significant impact of SST on the global ocean-atmospheric system and its potential to trigger extreme weather *** existing machine-learning-based ssT predictions adapt the traditional iterative point-wise prediction mechanism,whose predicting horizons and accuracy are limited owing to the high sensitivity to cumulative errors during iterative ***,this paper proposes a novel granulation-based long short-term memory(LsTM)-random forest(RF)combination model that can fully capture the feature dependencies involved in the fluctuation of SsT sequences,reduce the cumulative error in the iteration process,and extend the prediction horizons,which includes two sub-models(adaptive granulation model and hybrid prediction model).They can restack the one-dimensional ssT time-series into multidimensional feature variables,and achieve a strong forecasting *** analysis shows that the proposed model can achieve more accurate prediction-hours in nearly all prediction ranges from 1 to 125 *** average prediction error of the proposed model in 25-125 h is 0.07 K,similar to that(0.067 K)in the first 24 h,which exhibits a high generalization performance and robustness and isthus a promising platform for the medium-and long-term forecasting of hourly SSTs.

关键词： SST prediction adaptive granulation method LSTM RF error reciprocal method

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Verification of tropical cyclones(TC)wind structure forecasts from global NWP models and ensemble prediction systems(EPSs)

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Tropical Cyclone Research and Review 2022年第2期11卷 88-102页

作者： Xiaoqin Lu Wai Kin Wong Kin Chung Au-Yeung Chun Wing Choy Hui Yu Shanghai Typhoon Institute and Laboratory of Typhoon Forecast Technique China Meteorological AdministrationShanghaiChina Hong Kong Observatory Hong KongChina

Forecasting wind structure of tropical cyclone(TC)is vital in assessment of impact due to high winds using Numerical Weather Prediction(NWP)*** usual verification technique on TC wind structure forecasts are based on grid-to-grid comparisons between forecast field and the actual ***,precision of traditional verification measures is easily affected by small scale errors and thus cannot well discriminate the accuracy or effectiveness of NWP model *** this study,the Method for Object-Based Diagnostic Evaluation(MODE),which has been widely adopted in verifying precipitation fields,is utilized in TC’s wind field verification for the first *** TC wind field forecast of deterministic NWP model and Ensemble Prediction System(EPS)of the European Centre for Medium-Range Weather Forecasts(ECMWF)over the western North Pacific and the South China Sea in 2020 were evaluated.A MODE score of 0.5 is used as a threshold value to represent a skillful(or good)*** is found that the R34(radius of 34 knots)wind field structure forecasts within 72 h are good regardless of DET or *** performance of R50 and R64 is slightly worse but the R50 forecasts within 48 h remain good,with MODE exceeded *** R64forecast within 48 h are worth for reference as well with MODE of around *** study states that the TC wind field structure forecast by ECMWF is skillful for TCs over the western North Pacific and the South China Sea.

关键词： Verification Tropical cyclones wind structure forecasts Numerical weather prediction models Ensemble prediction system

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High-resolution sea surface wind speeds of Super Typhoon Lekima (2019) retrieved by Gaofen-3 SAR

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Frontiers of Earth Science 2022年第1期16卷 90-98页

作者： He FANG William PERRIE Gaofeng FAN Zhengquan LI Juzhen CAI Yue HE Jingsong YANG Tao XIE Xuesong ZHU Zhejiang Climate Centre Hangzhou 310017China State Key Laboratory of Satellite Ocean Environment Dynamics Second Institute of OceanographyMinistry of Natural ResourcesHangzhou 310012China Shanghai Typhoon Institute and Key Laboratory of Numerical Modeling for Tropical Cyclone of China Meteorological AdministrationShanghai 200030China Fisheries&Oceans Canada Bedford Institute of OceanographyDartmouth B2Y4A2Canada School of Remote Sensing and Geomatics Engineering Nanjing University of Information Science and TechnologyNanjing 210044China

Gaofen-3(GF-3)is the first Chinese spaceborne multi-polarization synthetic aperture radar(SAR)instrument at C-band(5.43 GHz).In this paper,we use data collected from GF-3 to observe Super Typhoon Lekima(2019)in the East China *** a VH-polarized wide ScanSAR(WSC)image,ocean surface wind speeds at 100m horizontal resolution are obtained at 21:56:59 UTC on 8 August 2019,with the maximum wind speed,38.9 m·s^(-1).Validating the SAR-retrieved winds with buoymeasured wind speeds,we find that the root mean square error(RMSE)is 1.86 m·s^(-1),and correlation coefficient,*** suggests that wind speeds retrieved from GF-3 SAR are *** the European Centre for MediumRange Weather Forecasts(ECMWF)fine grid operational forecast products with spatial resolution,and China Global/Regional Assimilation and Prediction Enhance System(GRAPES)have good performances on surface wind prediction under weak wind speed condition(24m·s^(-1)).With respect to SAR-retrieved wind speeds,the RMSEs are 5.24 m·s^(–1) for ECMWF and 5.17 m·s^(–1) for GRAPES,with biases of 4.16 m·s^(–1) for ECMWF and 3.84 m·s^(-1)for GRAPES during Super Typhoon Lekima(2019).

关键词： synthetic aperture radar wind speed numerical weather predication(NWP) typhoon

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