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Nighttime smoke aerosol optical depth over US rural areas: First retrieval from VIIRS moonlight observations

REMOTE SENSING OF ENVIRONMENT 2021年 267卷 112717-112717页

作者： Zhou, Meng Wang, Jun Chen, Xi Xu, Xiaoguang Colarco, Peter R. Miller, Steven D. Reid, Jeffrey S. Kondragunta, Shobha Giles, David Matthew Holben, Brent Univ Iowa Interdisciplinary Grad Program Informat Iowa City IA 52242 USA Univ Iowa Ctr Global & Reg Environm Res Iowa City IA 52242 USA Univ Iowa Iowa Technol Inst Iowa City IA 52242 USA Univ Iowa Dept Chem & Biochem Engn Iowa City IA 52242 USA Univ Maryland Baltimore Cty Joint Ctr Earth Syst Technol 1000 Hilltop Circle Baltimore MD 21250 USA NASA Goddard Space Flight Ctr Greenbelt MD 20771 USA Colorado State Univ Cooperat Inst Res Atmosphere Ft Collins CO 80523 USA Naval Res Lab Marine Meteorol Div Monterey CA 93943 USA NOAA Ctr Satellite Applicat & Res Natl Environm Satellite Data & Informat Serv College Pk MD 20740 USA

An algorithm for retrieving nighttime aerosol optical depth (AOD) from the Visible Infrared Imaging Radiometer Suite (VIIRS) Day-Night Band (DNB) observations of reflected moonlight is presented for rural areas during the western U.S. fire seasons. The algorithm uses the UNified and Linearized Vector Radiative Transfer Model (UNL-VRTM) with newly developed capabilities for considering lunar illuminations. Cloud and fire pixels are screened out by utilizing the radiance from the VIIRS Moderate-resolution Bands (M-Band) and the DNB. Rural and city pixels are classified based on a pre-calculated city light database. The surface spectral reflectance for DNB ranging from 342 to 1107 nm is estimated by a random forest approach, which is trained using the surface spectral reflectance from the existing spectral libraries. For the fire seasons of 2017 and 2020, the nighttime AOD retrieval is shown to play an indispensable role in describing the nonlinear diurnal movement of smoke transport and discerning the source of smoke plumes heretofore observable only in the daytime. The retrieved AOD values show good agreement with spatiotemporally collocated Aerosol Robotic NETwork (AERONET) and Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) AOD values, with linear correlation coefficient values of -0.96/0.95 and -86%/69% of the AOD pairs falling in an uncertainty envelope of +/-(0.085 + 0.10AOD), which is superior to AOD reanalysis from Modern-Era Retrospective analysis for Research and Applications, version 2 (MERRA-2). These results affirm the significant potential of nighttime AOD to improve the analysis and forecast of regional to global biomass-burning aerosol distributions, filling a critical gap in the diurnal description of a key element of Earth's climate system.

关键词： AOD retrieval retrieval algorithm VIIRS DNB Moonlight observation Smoke Smoke transport Diurnal cycle Rural air quality

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retrieval of Daytime Total Column Water Vapour from OLCI Measurements over Land Surfaces

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REMOTE SENSING 2021年第5期13卷 932-932页

作者： Preusker, Rene Carbajal Henken, Cintia Fischer, Juergen Free Univ Berlin Inst Space Sci Carl Heinrich Becker Weg 6-10 D-12165 Berlin Germany

A new retrieval of total column water vapour (TCWV) from daytime measurements over land of the Ocean and Land Colour Instrument (OLCI) on-board the Copernicus Sentinel-3 missions is presented. The Copernicus Sentinel-3 OLCI Water Vapour product (COWa) retrieval algorithm is based on the differential absorption technique, relating TCWV to the radiance ratio of non-absorbing band and nearby water vapour absorbing band and was previously also successfully applied to other passive imagers Medium Resolution Imaging Spectrometer (MERIS) and Moderate Resolution Imaging Spectroradiometer (MODIS). One of the main advantages of the OLCI instrument regarding improved TCWV retrievals lies in the use of more than one absorbing band. Furthermore, the COWa retrieval algorithm is based on the full Optimal Estimation (OE) method, providing pixel-based uncertainty estimates, and transferable to other Near-Infrared (NIR) based TCWV observations. Three independent global TCWV data sets, i.e., Aerosol Robotic Network (AERONET), Atmospheric Radiation Measurement (ARM) and U.S. SuomiNet, and a German Global Navigation Satellite System (GNSS) TCWV data set, all obtained from ground-based observations, serve as reference data sets for the validation. Comparisons show an overall good agreement, with absolute biases between 0.07 and 1.31 kg/m(2) and root mean square errors (RMSE) between 1.35 and 3.26 kg/m(2). This is a clear improvement in comparison to the operational OLCI TCWV Level 2 product, for which the bias and RMSEs range between 1.10 and 2.55 kg/m(2) and 2.08 and 3.70 kg/m(2), respectively. A first evaluation of pixel-based uncertainties indicates good estimated uncertainties for lower retrieval errors, while the uncertainties seem to be overestimated for higher retrieval errors.

关键词： OLCI Sentinel-3 total column water vapour retrieval algorithm validation AERONET ARM GNSS

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On the Problem of the Sea Ice Detection by Orbital Microwave Doppler Radar at the Nadir Sounding

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REMOTE SENSING 2022年第19期14卷 4937-4937页

作者： Karaev, Vladimir Titchenko, Yury Panfilova, Maria Ponur, Kiril Ryabkova, Maria Meshkov, Eugeny Kovaldov, Dmitry Russian Acad Sci IAP RAS Inst Appl Phys Nizhnii Novgorod 603950 Russia

Orbital radars are used to monitor the state of the sea ice in the Arctic and Antarctic. The backscattering radar cross section (RCS) is used to determine the type of scattering surface. The power of the reflected signal depends on many factors, so the problem of separating sea ice and sea waves is not always unambiguous. Previous research has shown that microwave Doppler radar installed on aircrafts can be used to determine the boundary of sea ice. The width of the Doppler spectrum for wide or knife-like antenna beam depends on the statistical parameters of the reflecting surface, so sea ice and sea waves are easily separated. However, when installing a Doppler radar on a satellite, the spatial resolution becomes extremely low. In this research, we discuss the possibility of improving the spatial resolution by dividing the antenna footprint into elementary scattering cells. To do this, it is proposed to use the original incoherent synthesis procedure, which allows one to determine the dependence of the RCS on the incidence angle for an elementary scattering cell. Numerical modeling was performed and processing of model data confirmed that sea ice and sea waves are separated. The coefficient of kurtosis was used as a criterion in the algorithm. In addition, for sea waves, it is possible to determine the mean square slopes (mss) of large-scale waves, compared to the electromagnetic wavelength of sea waves along the sounding direction.

关键词： Doppler spectrum of the backscattered radar signal sea ice sea waves knife-like antenna beam kurtosis coefficient retrieval algorithm

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Distributed Feedback Interband Cascade Laser Based Laser Heterodyne Radiometer for Column Density of HDO and CH4 Measurements at Dunhuang, Northwest of China

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REMOTE SENSING 2022年第6期14卷 1489页

作者： Lu, Xingji Huang, Yinbo Wu, Pengfei Liu, Dandan Ma, Hongliang Wang, Guishi Cao, Zhensong Chinese Acad Sci Anhui Inst Opt & Fine Mech Key Lab Atmospher Opt Hefei 230031 Peoples R China Adv Laser Technol Lab Anhui Prov Hefei 230037 Peoples R China West Anhui Univ Coll Elect & Optoelect Engn Luan 237012 Peoples R China Anqing Normal Univ Sch Elect Engn & Intelligent Mfg Anqing 246011 Peoples R China

Remote sensing of HDO and CH4 could provide valuable information on environmental and climatological studies. In a recent contribution, we reported a 3.53 mu m distributed feedback (DFB) inter-band cascade laser (ICL)-based heterodyne radiometer. In the present work, we present the details of measurements and inversions of HDO and CH4 at Dunhuang, Northwest of China. The instrument line shape (ILS) of laser heterodyne radiometer (LHR) is discussed firstly, and the spectral resolution is about 0.004 cm(-1) theoretically according to the ILS. Furthermore, the retrieval algorithm, optimal estimation method (OEM), combined with LBLRTM (Line-by-line Radiative Transfer Model) for retrieving the densities of atmospheric HDO and CH4 are investigated. The HDO densities were retrieved to be less than 1.0 ppmv, while the CH4 densities were around 1.79 ppmv from 20 to 24 July 2018. The correlation coefficient of water vapor densities retrieved by LHR and EM27/SUN is around 0.6, the potential reasons for the differences were discussed. Finally, in order to better understand the retrieval procedure, the Jacobian value and the Averaging Kernels are also discussed.

关键词： laser heterodyne radiometer instrument line-shape retrieval algorithm HDO CH4

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Retrieving Soil Moisture in the Permafrost Environment by Sentinel-1/2 Temporal Data on the Qinghai-Tibet Plateau

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REMOTE SENSING 2022年第23期14卷 5966-5966页

作者： Li, Zhibin Zhao, Lin Wang, Lingxiao Zou, Defu Liu, Guangyue Hu, Guojie Du, Erji Xiao, Yao Liu, Shibo Zhou, Huayun Xing, Zanpin Wang, Chong Zhao, Jianting Chen, Yueli Qiao, Yongping Shi, Jianzong Nanjing Univ Informat Sci & Technol Sch Geog Sci Nanjing 210044 Peoples R China Univ Chinese Acad Sci Beijing 100049 Peoples R China Chinese Acad Sci Northwest Inst Ecoenvironm & Resources State Key Lab Cryospher Sci Cryosphere Res Stn Qinghai Tibet Plateau Lanzhou 730000 Peoples R China Ludwig Maximilians Univ Munchen Dept Geog D-80333 Munich Germany

Soil moisture (SM) products presently available in permafrost regions, especially on the Qinghai-Tibet Plateau (QTP), hardly meet the demands of evaluating and modeling climatic, hydrological, and ecological processes, due to their significant bias and low spatial resolution. This study developed an algorithm to generate high-spatial-resolution SM during the thawing season using Sentinel-1 (S1) and Sentinel-2 (S2) temporal data in the permafrost environment. This algorithm utilizes the seasonal backscatter differences to reduce the effect of surface roughness and uses the normalized difference vegetation index (NDVI) and the normalized difference moisture index (NDMI) to characterize vegetation contribution. Then, the SM map with a grid spacing of 50 m x 50 m in the hinterland of the QTP with an area of 505 km x 246 km was generated. The results were independently validated based on in situ data from active layer monitoring sites. It shows that this algorithm can retrieve SM well in the study area. The coefficient of determination (R-2) and root-mean-square error (RMSE) are 0.82 and 0.06 m(3)/m(3), respectively. This study analyzed the SM distribution of different vegetation types: the alpine swamp meadow had the largest SM of 0.26 m(3)/m(3), followed by the alpine meadow (0.23), alpine steppe (0.2), and alpine desert (0.16), taking the Tuotuo River basin as an example. We also found a significantly negative correlation between the coefficient of variation (CV) and SM in the permafrost area, and the variability of SM is higher in drier environments and lower in wetter environments. The comparison with ERA5-Land, GLDAS, and ESA CCI showed that the proposed method can provide more spatial details and achieve better performance in permafrost areas on QTP. The results also indicated that the developed algorithm has the potential to be applied in the entire permafrost regions on the QTP.

关键词： soil moisture SAR retrieval algorithm high spatial resolution permafrost

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THE retrieval OF SURFACE ATMOSPHERIC PRESSURE OVER THE OCEANS USING 50-60 GHZ AND 118.75 GHZ PASSIVE MICROWAVE OBSERVATIONS

THE RETRIEVAL OF SURFACE ATMOSPHERIC PRESSURE OVER THE OCEAN...

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IEEE International Geoscience and Remote Sensing Symposium (IGARSS)

作者： Zhang, Zijin Dong, Xiaolong Chinese Acad Sci Natl Space Sci Ctr CAS Key Lab Microwave Remote Sensing Beijing 100190 Peoples R China Univ Chinese Acad Sci Beijing 100049 Peoples R China

ISBN: (纸本)9781728163741

This paper makes a comparison of the retrieval of sea level pressure using 50-60 GHz and 118.75 GHz passive microwave observations. The 50-60 GHz passive observations of the Microwave Temperature Sounder-II (MWTS-II) and 118.75 GHz observations of the Microwave Humidity and Temperature Sounder (MWHTS) onboard the Chinese Fengyun-3D (FY-3D) meteorological satellite were used to carry out the comparison. Based on neural networkbased retrieval algorithm, sea surface atmospheric pressure retrieval models for MWTS-II and MWHTS were established, respectively. Passive microwave observations from January 2018 to October 2019 and the corresponding Global Data Assimilation System (GDAS) Final (FNL) analysis data were used to develop and test the retrieval models. Results show that the accuracy of sea surface atmospheric pressure from MWTS-II retrieval is similar to that of the MWHTS retrieval for both usual weather conditions and tropical cyclone (TC) conditions. This provides a reference for high spatial resolution surface pressure observations by passive microwave instruments from low orbit satellites and high temporal resolution observations from geostationary orbit in the future.

关键词： sea surface atmospheric pressure Fengyun-3D satellite passive microwave retrieval algorithm tropical cyclone

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A Comprehensive Machine Learning Study to Classify Precipitation Type over Land from Global Precipitation Measurement Microwave Imager (GPM-GMI) Measurements

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REMOTE SENSING 2022年第15期14卷 3631页

作者： Das, Spandan Wang, Yiding Gong, Jie Ding, Leah Munchak, Stephen J. Wang, Chenxi Wu, Dong L. Liao, Liang Olson, William S. Barahona, Donifan O. Carnegie Mellon Univ Dept Comp Sci Pittsburgh PA 15213 USA Amer Univ Dept Comp Sci Washington DC 20016 USA Univ Space Res Assoc Goddard Earth Sci Technol & Res GESTAR Columbia MD 21046 USA NASA Goddard Space Flight Ctr Code 916 Greenbelt MD 20771 USA Univ Maryland Baltimore Cty GESTAR II Baltimore MD 21250 USA Tomorrow Io Boston MA 02210 USA Univ Maryland Baltimore Cty Joint Ctr Earth Syst Technol JCET Baltimore MD 21250 USA Morgan State Univ GESTAR II Baltimore MD 21251 USA

Precipitation type is a key parameter used for better retrieval of precipitation characteristics as well as to understand the cloud-convection-precipitation coupling processes. Ice crystals and water droplets inherently exhibit different characteristics in different precipitation regimes (e.g., convection, stratiform), which reflect on satellite remote sensing measurements that help us distinguish them. The Global Precipitation Measurement (GPM) Core Observatory's microwave imager (GMI) and dual-frequency precipitation radar (DPR) together provide ample information on global precipitation characteristics. As an active sensor, the DPR provides an accurate precipitation type assignment, while passive sensors such as the GMI are traditionally only used for empirical understanding of precipitation regimes. Using collocated precipitation type flags from the DPR as the "truth", this paper employs machine learning (ML) models to train and test the predictability and accuracy of using passive GMI-only observations together with ancillary information from a reanalysis and GMI surface emissivity retrieval products. Out of six ML models, four simple ones (support vector machine, neural network, random forest, and gradient boosting) and the 1-D convolutional neural network (CNN) model are identified to produce 90-94% prediction accuracy globally for five types of precipitation (convective, stratiform, mixture, no precipitation, and other precipitation), which is much more robust than previous similar effort. One novelty of this work is to introduce data augmentation (subsampling and bootstrapping) to handle extremely unbalanced samples in each category. A careful evaluation of the impact matrices demonstrates that the polarization difference (PD), brightness temperature (Tc) and surface emissivity at high-frequency channels dominate the decision process, which is consistent with the physical understanding of polarized microwave radiative transfer over different surface types, a

关键词： machine learning artificial intelligence precipitation type classification passive microwave precipitation radar retrieval algorithm

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Ocean Wave Inversion Based on Airborne IRA Images

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IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING 2022年 60卷

作者： Sun, Daozhong Zhang, Yanmin Wang, Yunhua Chen, Ge Sun, Hanwei Yang, Lei Bai, Yining Yu, Fangjie Zhao, Chaofang Ocean Univ China Coll Informat Sci & Engn Qingdao 266100 Peoples R China Qingdao Natl Lab Marine Sci & Technol Qingdao 266237 Peoples R China Beijing Inst Radio Measurement Beijing 100854 Peoples R China Minist Nat Resources Inst Oceanog 1 Marine Survey Res Ctr Qingdao 266061 Peoples R China

The interferometric radar altimeter (IRA) is one of the main payloads of the ``Guanlan'' ocean science satellite proposed by the National Laboratory for Marine Science and Technology of China. To evaluate the effectiveness and accuracy of the IRA in retrieving the ocean dynamic parameters, such as sea surface height (SSH), ocean wave spectrum, and wind speed, two airborne IRA experiments were carried out at Qingdao Xiaomaidao (XMD) sea area on March 31, 2019, and Rizhao sea area on November 16, 2020. In the present work, wave-induced sea surface elevation (SSE) and its spectrum have been retrieved based on the interferograms acquired by the airborne IRA. To suppress the random phase noise, a mean filtering algorithm has been used in the multilook process of calculating the complex IRA images. The results show that the size of the filter window has a significant effect on the retrieved SSE. If the size of the filter window along THE range direction is too large, the flat earth would cause the spectral density of the retrieved ocean wave to be higher. In addition, the comparisons of the retrieved spectra with the buoy measurements demonstrate that the swell can be well-retrieved by IRA images at low sea-state conditions with significant wave height (SWH) less than 0.7 m. However, for wind wave, because of the effect of the velocity bunching along the azimuth direction, the wind wave spectrum can be extracted only when it propagates approximately along the ground-range direction of the IRA images.

关键词： Ocean waves Sea measurements Satellites Interference Synthetic aperture radar Spaceborne radar Sea surface Interferometric radar altimeter (IRA) ocean wave ocean wave spectrum retrieval algorithm

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Synergy of observations from various satellites for the fast retrieval of atmospheric carbon dioxide amounts 25

Synergy of observations from various satellites for the fast...

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Conference on Remote Sensing of Clouds and the Atmosphere XXV held at SPIE Remote Sensing Conference

作者： Bril, Andrey Maksyutov, Shamil Yoshida, Yukio Chaikovsky, Anatoli Peshcharankou, Vladislau Natl Acad Sci Belarus BI Stepanov Inst Phys Minsk BELARUS Natl Inst Environm Studies Ctr Global Environm Res Tsukuba Ibaraki Japan

ISBN: (纸本)9781510638761;9781510638754

We present an algorithm for the rapid retrieval of the carbon dioxide total column amounts (XCO2) using short wave infrared (SWIR) spectra of the reflected sunlight measured from space. The algorithm takes advantage of the combined processing of observational data from two different satellite missions. For the algorithm implementation we adopted the previously developed EOF (Empirical Orthogonal Functions)-based approach that exploits regression relations of the principal components of the measured spectra with target XCO2 values. In the original algorithm version the regression coefficients were derived by using training sets of collocated satellite and ground-based observations (ground-based observations were treated as "true values"). In this paper we implemented similar approach in which training set for one satellite mission is created using collocated observations of the another "reference" space mission simultaneously onorbit (in this case XCO2 retrievals of the "reference" mission were treated as "true values"). This approach enables rapid data processing of the new satellite missions omitting expensive and time consuming stage of retrieval algorithm development. The feasibility of the approach was tested by joint processing of GOSAT and OCO-2 observation data. For the analysis of the algorithm precision/accuracy characteristics we used the collocated observations from the Total Carbon Column Observing Network (TCCON).

关键词： carbon dioxide retrieval algorithm empirical orthogonal function GOSAT OCO-2

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Monitoring Trace Gases over the Antarctic Using Atmospheric Infrared Ultraspectral Sounder Onboard GaoFen-5: algorithm Description and First retrieval Results of O3, H2O, and HCl

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REMOTE SENSING 2019年第17期11卷 1991-1991页

作者： Li, Xiaoying Xu, Jian Cheng, Tianhai Shi, Hailiang Zhang, Xingying Ge, Shule Wang, Hongmei Zhu, Songyan Miao, Jing Luo, Qi Chinese Acad Sci State Key Lab Remote Sensing Sci Inst Remote Sensing & Digital Earth Beijing 100101 Peoples R China German Aerosp Ctr DLR Remote Sensing Technol Inst D-82234 Oberpfaffenhofen Germany Chinese Acad Sci Anhui Inst Opt & Fine Mech Hefei 230031 Anhui Peoples R China China Meteorol Adm Natl Satellite Meteorol Ctr Beijing 100081 Peoples R China China Ctr Resources Satellite Data & Applicat Beijing 100094 Peoples R China

AIUS (Atmospheric Infrared Ultraspectral Sounder) is an infrared occultation spectrometer onboard the Chinese GaoFen-5 satellite, which covers a spectral range of 2.4-13.3 mu m (750-4100 cm(-1)) with a spectral resolution of about 0.02 cm(-1). AIUS was designed to measure and to study the chemical processes of ozone (O-3) and other trace gases in the upper troposphere and stratosphere over the Antarctic. In this study, the AIUS retrieval methodology is described. A comparison between AIUS measurements and simulated spectra illustrates that AIUS measurements agree well with the simulated spectra. To first evaluate the reliability of the AIUS retrieval algorithm, three retrieval O-3 experiments were performed based on ACE-FTS (Atmospheric Chemistry Experiment-Fourier transform spectrometer) observed spectra. A comparison with the ACE-FTS official products shows that the relative difference of these three retrieval experiments was mostly within 10% between 20 and 70 km. These retrieval experiments demonstrate that the retrieval algorithm described in this study provided reliable results and reliably. Furthermore, O-3, H2O, and HCl profiles were retrieved from 24 orbits of AIUS measurements and compared with the official Aura /MLS (Microwave Limb Sounder) level-2 v4.2 profiles. The relative difference was mostly within 10% (about 0.02-0.4 ppm) between 18 and 58 km for the O-3 retrieval, within 10% (0-0.5 ppm) between 15 and 80 km for the H2O retrieval, and within 10% (about 0.1 ppb) between 30 and 60 km for the HCl retrieval. A good agreement in the retrieved trace gas profiles was reached between AIUS and MLS.

关键词： AIUS occultation retrieval algorithm microwindows ozone

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