Precipitable water vapor fusion of MODIS and ERA5 based on convolutional neural network

[1]  W. Wang,et al.  A Global Assessment of Precipitable Water Vapor Derived From GNSS Zenith Tropospheric Delays With ERA5, NCEP FNL, and NCEP GFS Products , 2021, Earth and Space Science.

[2]  Yibin Yao,et al.  Precipitable water vapor fusion based on a generalized regression neural network , 2021, Journal of Geodesy.

[3]  Wanqiang Yao,et al.  Hybrid precipitable water vapor fusion model in China , 2020 .

[4]  Guoqing Wang,et al.  A spatiotemporal deep fusion model for merging satellite and gauge precipitation in China , 2020 .

[5]  Zhikui Chen,et al.  A Survey on Deep Learning for Multimodal Data Fusion , 2020, Neural Computation.

[6]  D. Long,et al.  An improvement in accuracy and spatiotemporal continuity of the MODIS precipitable water vapor product based on a data fusion approach , 2020, Remote Sensing of Environment.

[7]  A. Engeln,et al.  Performance of ERA5 data in retrieving Precipitable Water Vapour over East African tropical region , 2020, Advances in Space Research.

[8]  Jia Liu,et al.  Urban big data fusion based on deep learning: An overview , 2020, Inf. Fusion.

[9]  Yibin Yao,et al.  Precipitable water vapor fusion: an approach based on spherical cap harmonic analysis and Helmert variance component estimation , 2019, Journal of Geodesy.

[10]  W. Liu,et al.  On the suitability of ERA5 in hourly GPS precipitable water vapor retrieval over China , 2019, Journal of Geodesy.

[11]  Jia He,et al.  Comparison of Satellite-Derived Precipitable Water Vapor Through Near-Infrared Remote Sensing Channels , 2019, IEEE Transactions on Geoscience and Remote Sensing.

[12]  Wujiao Dai,et al.  Consistency Evaluation of Precipitable Water Vapor Derived From ERA5, ERA‐Interim, GNSS, and Radiosondes Over China , 2019, Radio Science.

[13]  Baocheng Zhang,et al.  A Real-Time Precipitable Water Vapor Monitoring System Using the National GNSS Network of China: Method and Preliminary Results , 2019, IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing.

[14]  Qin Zhang,et al.  Precipitable Water Vapor Retrieval and Analysis by Multiple Data Sources: Ground-Based GNSS, Radio Occultation, Radiosonde, Microwave Satellite, and NWP Reanalysis Data , 2018, J. Sensors.

[15]  Mohammad R. Jahanshahi,et al.  NB-CNN: Deep Learning-Based Crack Detection Using Convolutional Neural Network and Naïve Bayes Data Fusion , 2018, IEEE Transactions on Industrial Electronics.

[16]  Yu Zheng,et al.  Evaluation of radiosonde, MODIS-NIR-Clear, and AERONET precipitable water vapor using IGS ground-based GPS measurements over China , 2017 .

[17]  Robert O. Knuteson,et al.  A global assessment of NASA AIRS v6 and EUMETSAT IASI v6 precipitable water vapor using ground‐based GPS SuomiNet stations , 2016 .

[18]  Peng Jiang,et al.  Retrieving Precipitable Water Vapor Data Using GPS Zenith Delays and Global Reanalysis Data in China , 2016, Remote. Sens..

[19]  Yingyan Cheng,et al.  Water vapor‐weighted mean temperature and its impact on the determination of precipitable water vapor and its linear trend , 2016 .

[20]  F. Meyer,et al.  Water vapor mapping by fusing InSAR and GNSS remote sensing data and atmospheric simulations , 2015 .

[21]  Harald Schuh,et al.  Multi-GNSS Meteorology: Real-Time Retrieving of Atmospheric Water Vapor From BeiDou, Galileo, GLONASS, and GPS Observations , 2015, IEEE Transactions on Geoscience and Remote Sensing.

[22]  Dit-Yan Yeung,et al.  Convolutional LSTM Network: A Machine Learning Approach for Precipitation Nowcasting , 2015, NIPS.

[23]  Xingxing Li,et al.  Real-time retrieval of precipitable water vapor from GPS and BeiDou observations , 2015, Journal of Geodesy.

[24]  K. K. Sahu,et al.  Normalization: A Preprocessing Stage , 2015, ArXiv.

[25]  Heng Hu,et al.  Meteorological applications of precipitable water vapor measurements retrieved by the national GNSS network of China , 2015 .

[26]  Fadwa Alshawaf,et al.  Accurate Estimation of Atmospheric Water Vapor Using GNSS Observations and Surface Meteorological Data , 2015, IEEE Transactions on Geoscience and Remote Sensing.

[27]  Jimmy Ba,et al.  Adam: A Method for Stochastic Optimization , 2014, ICLR.

[28]  Peter Steigenberger,et al.  Troposphere delays from space geodetic techniques, water vapor radiometers, and numerical weather models over a series of continuous VLBI campaigns , 2013, Journal of Geodesy.

[29]  Anup K. Prasad,et al.  Validation of MODIS Terra, AIRS, NCEP/DOE AMIP‐II Reanalysis‐2, and AERONET Sun photometer derived integrated precipitable water vapor using ground‐based GPS receivers over India , 2009 .

[30]  F. Martin Ralph,et al.  Meteorological Characteristics and Overland Precipitation Impacts of Atmospheric Rivers Affecting the West Coast of North America Based on Eight Years of SSM/I Satellite Observations , 2008 .

[31]  E. Rodríguez,et al.  A Global Assessment of the SRTM Performance , 2006 .

[32]  D. Tanré,et al.  SAFARI 2000 MODIS MOD05_L2 Water Vapor Data, Binary Format, for Southern Africa , 2005 .

[33]  Jan-Peter Muller,et al.  Interferometric synthetic aperture radar (InSAR) atmospheric correction: GPS, moderate resolution Imaging spectroradiometer (MODIS), and InSAR integration , 2005 .

[34]  Jan-Peter Muller,et al.  Comparison of precipitable water vapor derived from radiosonde, GPS, and Moderate‐Resolution Imaging Spectroradiometer measurements , 2003 .

[35]  W. Paul Menzel,et al.  Cloud and aerosol properties, precipitable water, and profiles of temperature and water vapor from MODIS , 2003, IEEE Trans. Geosci. Remote. Sens..

[36]  A. Roth,et al.  The shuttle radar topography mission—a new class of digital elevation models acquired by spaceborne radar , 2003 .

[37]  A. Dodson,et al.  GPS estimation of atmospheric water vapour from a moving platform , 2001 .

[38]  Richard B. Langley,et al.  Comparison of Measurements of Atmospheric Wet Delay by Radiosonde, Water Vapor Radiometer, GPS, and VLBI , 2001 .

[39]  Soroosh Sorooshian,et al.  SuomiNet: A Real-Time National GPS Network for Atmospheric Research and Education. , 2000 .

[40]  X. Zou,et al.  Analysis and validation of GPS/MET data in the neutral atmosphere , 1997 .

[41]  Steven Businger,et al.  GPS Meteorology: Direct Estimation of the Absolute Value of Precipitable Water , 1996 .

[42]  John R. Lanzante,et al.  An Assessment of Satellite and Radiosonde Climatologies of Upper-Tropospheric Water Vapor. , 1996 .

[43]  F. Pukelsheim The Three Sigma Rule , 1994 .

[44]  Steven Businger,et al.  GPS Meteorology: Mapping Zenith Wet Delays onto Precipitable Water , 1994 .

[45]  Steven Businger,et al.  Sensing atmospheric water vapor with the global positioning system , 1993 .

[46]  T. Herring,et al.  GPS Meteorology: Remote Sensing of Atmospheric Water Vapor Using the Global Positioning System , 1992 .

[47]  Wanqiang Yao,et al.  Two-Step Precipitable Water Vapor Fusion Method , 2022, IEEE Transactions on Geoscience and Remote Sensing.

[48]  Maorong Ge,et al.  Calibrating the Haiyang-2A Calibration Microwave Radiometer When the 18.7-GHz Band Fails , 2022, IEEE Transactions on Geoscience and Remote Sensing.

[49]  Steven Platnick,et al.  The MODIS Cloud Optical and Microphysical Products: Collection 6 Updates and Examples From Terra and Aqua , 2017, IEEE Transactions on Geoscience and Remote Sensing.

[50]  Liping Di,et al.  The NASA HDF-EOS Web GIS Software Suite , 2006 .

[51]  Yoram J. Kaufman,et al.  The MODIS Near-IR Water Vapor Algorithm , 1998 .

[52]  Bo G Leckner,et al.  The spectral distribution of solar radiation at the earth's surface—elements of a model , 1978 .