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Detecting surface freeze/thaw states in Northeast China with passive microwave data using an improved standard deviation method

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Advances in Climate Change Research 2023年第2期14卷 190-199页

作者： Hao-Ran MAN Yang XIAO Shu-Ying ZANG Miao LI Xing-Feng DONG Heilongjiang Province Key Laboratory of Geographical Environment Monitoring and Spatial Information Service in Cold Regions Harbin Normal UniversityHarbin 150025China Heilongjiang Province Collaborative Innovation Center of Cold Region Ecological Safety Harbin 150025China

Passive microwave remote sensing datasets are widely used to observe surface freeze/thaw(F/T)states.However,current algorithms are highly affected by snow cover and complex land cover types,compromising their performance.Therefore,this study proposes an improved algorithm for daytime detection of diurnal F/T states by using Advanced microwave Scanning Radiometer 2 data.In the daytime F/T discrimination algorithm,a microwave spectral gradient index is applied to divide the surface into snow-covered and snow-free areas.In the snow-free area,the surface temperature index is optimised to improve the accuracy of the standard deviation method(SDM)in evaluating the accuracy of the F/T state.For the nighttime dataset,the microwave standard deviation index difference values between day and night are used to detect the F/T states based on the daytime results.The accuracy of the improved algorithm reaches 88.6%and 84.5%in the daytime and at nighttime,respectively.Compared with the SDM,the accuracy is improved by 10.2%in the daytime and 5.4%at nighttime.The results demonstrate that the proposed model is able to effectively distinguish the F/T states of snow-covered surfaces.Optimising the surface temperature index can significantly improve the accuracy of the SDM.The results reveal that the proposed surface F/T detection algorithm can be applied to regions with complex land cover types.

关键词： microwave remote sensing Surface F/T algorithm improvement Seasonal snow areas Classification Northeast China

Improved microwave Ocean Emissivity and Reflectivity Models Derived from Two-Scale Roughness Theory

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Advances in Atmospheric Sciences 2023年第10期40卷 1923-1938页

作者： Lingli HE Fuzhong WENG Chinese Academy of Meteorological Sciences Beijing 100081China University of Chinese Academy of Sciences Beijing 100049China CMA Earth System Modeling and Prediction Centre Beijing 100081China

The Geometrical Optics(GO)approach and the FAST Emissivity Model(FASTEM)are widely used to estimate the surface radiative components in atmospheric radiative transfer simulations,but their applications are limited in specific conditions.In this study,a two-scale reflectivity model(TSRM)and a two-scale emissivity model(TSEM)are developed from the two-scale roughness theory.Unlike GO which only computes six non-zero elements in the reflectivity matrix,The TSRM includes 16 elements of Stokes reflectivity matrix which are important for improving radiative transfer simulation accuracy in a scattering atmosphere.It covers the frequency range from L-to W-bands.The dependences of all TSRM elements on zenith angle,wind speed,and frequency are derived and analyzed in details.For a set of downwelling radiances in microwave frequencies,the reflected upwelling brightness temperature(BTs)are calculated from both TSRM and GO and compared for analyzing their discrepancies.The TSRM not only includes the effects of GO but also accounts for the small-scale Bragg scattering effect in an order of several degrees in Kelvins in brightness temperature.Also,the third and fourth components of the Stokes vector can only be produced from the TSRM.For the emitted radiation,BT differences in vertical polarization between a TSEM and FASTEM are generally less than 5 K when the satellite zenith angle is less than 40°,whereas those for the horizontal component can be quite significant,greater than 20 K.

关键词： emissivity microwave remote sensing reflectivity matrix two-scale roughness theory

Validation and accuracy analysis of wind products from scatterometer onboard the HY-2B satellite

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Acta Oceanologica Sinica 2023年第2期42卷 74-82页

作者： Sheng Yang Bo Mu Haoqiang Shi Chaofei Ma Wu Zhou Juhong Zou Mingsen Lin National Satellite Ocean Application Service Ministry of Natural ResourcesBeijing100081China Key Laboratory of Space Ocean remote sensing and Application Ministry of Natural ResourcesBeijing100081China China Academy of Space Technology(Xi’an Branch) Xi’an710100China

The Chinese marine dynamic environment satellite HY-2B was launched in October 2018 and carries a Ku-band scatterometer.This paper focuses on the accuracies of HY-2B scatterometer wind data during the period from November 2018 to May 2021.The HY-2B wind data are validated against global moored buoys operated by the U.S.National Data Buoy Center and Tropical Atmosphere Ocean,numerical model data by the National Centers for Environmental Prediction,and the Advanced Scatterometer data issued by the remote sensing System.The results showed that the wind speeds and directions observed by the HY-2B scatterometer agree well with these buoy wind measurements.The root-mean-squared errors(RMSEs)of the HY-2B wind speed and direction are 0.74 m/s and 11.74°,respectively.For low wind speeds(less than 5 m/s),the standard deviation of the HY-2B-derived wind direction is higher than 20°,which implies that the HY-2B wind direction for low wind speeds is less accurate than that for moderate to high wind speed ranges.The RMSE of the HY-2B wind speed is slightly larger in high latitude oceans(60°–90°S and 60°–90°N)than in low latitude regions.Furthermore,the dependence of the residuals on the cross-track location of wind vector cells and the stability of the HY-2B scatterometer wind products are discussed.The wind stability assessment results indicate that a clear yearly oscillation is observed for the HY-2B wind speed bias which is due to seasonal weather variations.In general,the accuracy of HY-2B winds meets the operational precision requirement and is consistent with other wind data.

关键词： sea surface wind validation microwave remote sensing scatterometer

Exploring the effect of Arctic perennial sea ice on modulation of local air temperature

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Advances in Climate Change Research 2022年第4期13卷 473-488页

作者： Yu-Fang YE Mohammed SHOKR Zhuo-Qi CHEN Xiao CHENG School of Geospatial Engineering and Science Sun Yat-sen Universityand Southern Marine Science and Engineering Guangdong Laboratory(Zhuhai)Zhuhai 519082China Science and Technology Branch Environment and Climate Change CanadaToronto M3H5T4Canada

Sea ice cover plays an important role in modulating local temperature through heat and moisture fuxes.The infuence of thin ice lead and polynya has been wellinvestigated,however,the effect of perennial ice(also called muliyear ice,MYI)has not.This study is motivated by it and investigated a hypothesis that changes in MYI concentration in winter triggers changes in short-term local 2-m air temperature.The hypothesis was tested using time series analysis of the two parameters and correlation between them.Data from the winters of 2004-2009 were used for the examination at three spatial scales.The hypothesis is found to be potentially accepted when MYI exists in a consolidated ice regime with negligible thin ice or open water in the surroundings,and the air temperature is low enough.Conditions for the acceptance of the hypothesis were quantitatively identified.The qualifications entail that the ice cell must experience daily change of MYI concentration meanwhile satisfy the criteria of total ice concentration(TIC),young ice concentration(YIC)and air temperature(Tar)in the surrounding area,which are TIC>88.3%,YIC<9.5%and T_(air)<-19.0℃.Inverse relationships between changes in MYI concentration and the corresponding changes in air temperature were developed retroactively using data that satisfied the acceptance conditions.The relationships varied with years,depending on ice conditions such as ice type distributions and snow cover.This study offers a first attempt to assess the effect of MYI on the same-day local surface air temperature using satelite observations,and provides evidence of this effect under quantitatively quanlifying conditions.

关键词： Arctic sea ice Multiyear ice Arctic response to climate change microwave remote sensing

Correlation and interaction between temperature and freeze-thaw in representative regions of Antarctica

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International Journal of Digital Earth 2022年第1期15卷 2296-2318页

作者： Dong Liang Huadong Guo Qing Cheng Lu Zhang Lingyi Kong Key Laboratory of Digital Earth Science Aerospace Information Research InstituteChinese Academy of SciencesBeijingPeople’s Republic of China University of Chinese Academy of Sciences BeijingPeople’s Republic of China International Research Center of Big Data for Sustainable Development Goals BeijingPeople’s Republic of China School of Computer Science China University of GeoscienceWuhanPeople’s Republic of China

As the most sensitive and direct indicator of global climate change,the freezing and thawing of the Antarctic ice sheet is of great significance for research on surface mass and energy balance.In this study,four representative regions in Antarctica were selected and correlation analysis,Granger causality testing,and cluster analysis were applied to comprehensively analyze the correlation and response of spatiotemporal variation in freeze-thaw and temperature.The conclusions are as follows.(1)In the Antarctic Peninsula,a phenomenon was demonstrated that the summer shifts rearward.Hotter December and colder March temperatures were observed in the Amery Ice Shelf and Queen Maud Land.(2)The Antarctic Peninsula featured the most severe degree of melting among the four regions,with the largest melt area in the past 30 years appearing during the 2015/2016 season.However,the number of melt days in most areas of the Antarctic Peninsula was observed to have decreased.(3)There is a strong correlation between the freeze-thaw state of the Antarctic ice sheet and temperature,as well as spatial differences among regions,but the data were clustered at different time scales.

关键词： Antarctic ice sheet Big Earth Data freeze-thaw microwave remote sensing snowmelt temperature

Preliminary Study on Direct Assimilation of Cloud-affected Satellite microwave Brightness Temperatures

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Advances in Atmospheric Sciences 2017年第2期34卷 199-208页

作者： Sibo ZHANG Li GUAN Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters Key Laboratory for Aerosol-Cloud-Precipitation of China Meteorological AdministrationNanjing University of Information Science and TechnologyNanjing 210044China

Direct assimilation of cloud-affected microwave brightness temperatures from AMSU-A into the GSI three-dimensional variational （3D-Var） assimilation system is preliminarily studied in this paper. A combination of cloud microphysics param- eters retrieved by the 1D-Var algorithm （including vertical profiles of cloud liquid water content, ice water content, and rain water content） and atmospheric state parameters from objective analysis fields of an NWP model are used as background fields. Three cloud microphysics parameters （cloud liquid water content, ice water content, and rain water content） are ap- plied to the control variable. Typhoon Halong （2014） is selected as an example. The results show that direct assimilation of cloud-affected AMSU-A observations can effectively adjust the structure of large-scale temperature, humidity and wind anal- ysis fields due to the assimilation of more AMSU-A observations in typhoon cloudy areas, especially typhoon spiral cloud belts. These adjustments, with temperatures increasing and humidities decreasing in the movement direction of the typhoon, bring the forecasted typhoon moving direction closer to its real path. The assimilation of cloud-affected satellite microwave brightness temperatures can provide better analysis fields that are more similar to the actual situation. Furthermore, typhoon prediction accuracy is improved using these assimilation analysis fields as the initial forecast fields in NWP models.

关键词： atmospheric sounding microwave remote sensing data assimilation cloudy radiances GSI

Improvement of microwave emissivity parameterization of frozen Arctic soils using roughness measurements derived from photogrammetry

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International Journal of Digital Earth 2021年第10期14卷 1380-1396页

作者： J.Meloche A.Royer A.Langlois N.Rutter V.Sasseville Département de Géomatique Appliquée Universitéde SherbrookeSherbrookeCanada Centre d’études nordiques QuébecCanada Department of Geography and Environmental Sciences Northumbria UniversityNewcastle upon TyneUK

Soil emissivity of Arctic regions is a key parameter for assessing surface properties from microwave brightness temperature(Tb)measurements.Particularly in winter,frozen soil permittivity and roughness are two poorly characterized unknowns that must be considered.Here,we show that after removing snow,the 3D soil roughness can be accurately inferred from in-situ photogrammetry using Structure from Motion(SfM).We focus on using SfM techniques to provide accurate roughness measurements and improve emissivity models parametrization of frozen arctic soil for microwave applications.Validation was performed from ground-based radiometric measurements at 19 and 37 GHz using three different soil emission models:the Wegmüller and Mätzler[1999,TGRS]model(Weg99),the Wang and Choudhury[1981,JGR]model(QNH),and a geometrical optics model(Geo Optics).Measured and simulated brightness temperatures over different tundra and rock sites in the Canadian High Arctic show that Weg99,parametrized with SfM-based roughness and optimized permittivity(1),yielded an RMSE of 3.1 K(R2=0.71)for all frequencies and polarizations.Our SfM based approach allowed us to measure roughness with 0.1 mm accuracy at 55 locations of different land cover type using a digital camera and metal plates of know dimensions.

关键词： Surface roughness microwave remote sensing frozen Arctic soil SfM photogrammetry

Bam earthquake: Surface deformation measurement using radar interferometry

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Acta Seismologica Sinica(English Edition) 2005年第4期18卷 451-459,500页

作者：夏耶 GeoForschungsZentrumPotsdam Telegrafenberg A17 D-14473 Potsdam Germany

On the 26th December 2003 an earthquake with MW=6.5 shook a large area of the Kerman Province in Iran. The epicenter of the devastating earthquake was located near the city of Bam. This paper described the application of differential synthetic aperture radar interferometry (D-INSAR) and ENVISAT ASAR data to map the coseismic surface deformation caused by the Bam earthquake including the interferometric data processing and results in detail. Based on the difference in the coherence images before and after the event and edge search of the deforma- tion field, a new fault ruptured on the surface was detected and used as a data source for parameter extraction of a theoretical seismic modeling. The simulated deformation field from the model perfectly coincides with the result derived from the SAR interferometric measurement.

关键词： microwave remote sensing SAR interferometry earthquake deformation measurement

A Multivariable Approach for Estimating Soil Moisture from microwave Radiation Imager(MWRI)

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Journal of Meteorological Research 2020年第4期34卷 732-747页

作者： Sibo ZHANG Fuzhong WENG Wei YAO Qian Xuesen Laboratory of Space Technology China Academy of Space TechnologyBeijing 100094 State Key Laboratory of Severe Weather Chinese Academy of Meteorological SciencesChina Meteorological AdministrationBeijing 100081

Accurate measurements of soil moisture are beneficial to our understanding of hydrological processes in the earth system. A multivariable approach using the random forest(RF) machine learning technique is proposed to estimate the soil moisture from microwave Radiation Imager(MWRI) onboard Fengyun-3 C satellite. In this study, Soil Moisture Operational Products System(SMOPS) products disseminated from NOAA are used as a truth to train the algorithm with the input of MWRI brightness temperatures(TBs) at 10.65, 18.7, 23.8, 36.5, and 89.0 GHz, TB polarization ratios(PRs) at 10.65, 18.7, and 23.8 GHz, height in digital elevation model(DEM), and soil porosity. The retrieved soil moisture is also validated against the independent SMOPS data, and the correlation coefficient is about0.8 and mean bias is 0.002 m^3 m^-3 over the period from 1 August 2017 to 31 May 2019. Our retrieval of soil moisture also has a higher correlation with ECMWF ERA5 soil moisture data than the MWRI operational products. In the western part of China, the spatial distribution of MWRI soil moisture is much improved, compared to the MWRI operational products.

关键词： soil moisture microwave Radiation Imager(MWRI) machine learning microwave remote sensing