Articles | Volume 6, issue 1
https://doi.org/10.5194/essd-6-221-2014
© Author(s) 2014. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
https://doi.org/10.5194/essd-6-221-2014
© Author(s) 2014. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
16 Jun 2014
A global climatology of total columnar water vapour from SSM/I and MERIS
R. Lindstrot
Institut für Weltraumwissenschaften, Freie Universität Berlin, Carl-Heinrich-Becker-Weg 6–10, 12165 Berlin, Germany
M. Stengel
Deutscher Wetterdienst, Satellite-Based Climate Monitoring, Dept. Climate and Environment, Strahlenbergerstraße 13, 63067 Offenbach, Germany
M. Schröder
Deutscher Wetterdienst, Satellite-Based Climate Monitoring, Dept. Climate and Environment, Strahlenbergerstraße 13, 63067 Offenbach, Germany
J. Fischer
Institut für Weltraumwissenschaften, Freie Universität Berlin, Carl-Heinrich-Becker-Weg 6–10, 12165 Berlin, Germany
R. Preusker
Institut für Weltraumwissenschaften, Freie Universität Berlin, Carl-Heinrich-Becker-Weg 6–10, 12165 Berlin, Germany
N. Schneider
Deutscher Wetterdienst, Satellite-Based Climate Monitoring, Dept. Climate and Environment, Strahlenbergerstraße 13, 63067 Offenbach, Germany
T. Steenbergen
Deutscher Wetterdienst, Satellite-Based Climate Monitoring, Dept. Climate and Environment, Strahlenbergerstraße 13, 63067 Offenbach, Germany
B. R. Bojkov
ESA/ESRIN, Via Galileo Galilei, Casella Postale 64, 00044 Frascati, Italy
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- Retrieving Precipitable Water Vapor Over Land From Satellite Passive Microwave Radiometer Measurements Using Automated Machine Learning X. Xia et al. https://doi.org/10.1029/2023GL105197
- A method for estimating high spatial resolution total precipitable water in all-weather condition by fusing satellite near-infrared and microwave observations Q. Sun et al. https://doi.org/10.1016/j.rse.2023.113952
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- A Framework for Estimating Clear-Sky Atmospheric Total Precipitable Water (TPW) from VIIRS/S-NPP S. Zhou & J. Cheng https://doi.org/10.3390/rs11080916
- Decadal All-sky Terrestrial Precipitable Water Vapor Dataset from FengYun Microwave Imagers X. Xia et al. https://doi.org/10.1007/s00376-025-5101-6
- Integrating near-infrared, thermal infrared, and microwave satellite observations to retrieve high-resolution precipitable water vapor Z. Du et al. https://doi.org/10.1016/j.rse.2025.114611
- TROPOMI/S5P Total Column Water Vapor validation against AERONET ground-based measurements K. Garane et al. https://doi.org/10.5194/amt-16-57-2023
- Evaluation of tropical water vapour from CMIP6 global climate models using the ESA CCI Water Vapour climate data records J. He et al. https://doi.org/10.5194/acp-22-12591-2022
- Analysis of Short-Term Drought Episodes Using Sentinel-3 SLSTR Data under a Semi-Arid Climate in Lower Eastern Kenya P. Musyimi et al. https://doi.org/10.3390/rs15123041
- Refining MODIS NIR Atmospheric Water Vapor Retrieval Algorithm Using GPS-Derived Water Vapor Data J. He & Z. Liu https://doi.org/10.1109/TGRS.2020.3016655
- The GEWEX Water Vapor Assessment archive of water vapour products from satellite observations and reanalyses M. Schröder et al. https://doi.org/10.5194/essd-10-1093-2018
- A total precipitable water retrieval method over land using the combination of passive microwave and optical remote sensing D. Ji et al. https://doi.org/10.1016/j.rse.2017.01.028
- A Spatial PWV Retrieval Model Over Land for GCOM-W/AMSR2 Using Neural Network Method: A Case in the Western United States Z. Gao et al. https://doi.org/10.1109/JSTARS.2023.3255259
- An Improved Model for the Retrieval of Precipitable Water Vapor in All-Weather Conditions (RCMNT) Based on NIR and TIR Recordings of MODIS Y. Wang et al. https://doi.org/10.1109/TGRS.2024.3381750
- The Advanced Infra-Red WAter Vapour Estimator (AIRWAVE) version 2: algorithm evolution, dataset description and performance improvements E. Castelli et al. https://doi.org/10.5194/amt-12-371-2019
- Retrieval of Daytime Total Column Water Vapour from OLCI Measurements over Land Surfaces R. Preusker et al. https://doi.org/10.3390/rs13050932
- The GEWEX Water Vapor Assessment: Results from Intercomparison, Trend, and Homogeneity Analysis of Total Column Water Vapor M. Schröder et al. https://doi.org/10.1175/JAMC-D-15-0304.1
- Representativeness of total column water vapour retrievals from instruments on polar orbiting satellites H. Diedrich et al. https://doi.org/10.5194/acp-16-8331-2016
- Impact of High Concentrations of Saharan Dust Aerosols on Infrared-Based Land Surface Temperature Products F. Stante et al. https://doi.org/10.1109/JSTARS.2023.3263374
- Precipitable Water Vapor Retrieval Over Land From GCOM-W/AMSR2 Based on a New Integrated Method Z. Gao et al. https://doi.org/10.1109/TGRS.2022.3151384
- Algorithm for Recovery of Integrated Water Vapor Content in the Atmosphere over Land Surfaces Based on Satellite Spectroradiometer Data S. Lisenko https://doi.org/10.1007/s10812-017-0467-6
- Trends and Variability in Precipitable Water Vapor throughout North China from 1979 to 2015 W. Peng et al. https://doi.org/10.1155/2017/7804823
- An Advanced Algorithm to Retrieve Total Atmospheric Water Vapor Content From the Advanced Microwave Scanning Radiometer Data Over Sea Ice and Sea Water Surfaces in the Arctic E. Zabolotskikh et al. https://doi.org/10.1109/TGRS.2019.2948289
- Retrieving snow and ice characteristics by remotely sensed emissivity using the multi-view brightness temperature within 8 μm to 14 μm T. Keck et al. https://doi.org/10.1016/j.rse.2017.09.006
- Accurate and Full-Coverage Retrieval of Total Column Water Vapor From Chinese UV-VIS Satellites Using an Interpretable Machine Learning Approach R. Zhao et al. https://doi.org/10.1109/TGRS.2025.3579262
27 citations as recorded by crossref.
- Retrieval of daytime total columnar water vapour from MODIS measurements over land surfaces H. Diedrich et al. https://doi.org/10.5194/amt-8-823-2015
- Impacts of solar-absorbing aerosol layers on the transition of stratocumulus to trade cumulus clouds X. Zhou et al. https://doi.org/10.5194/acp-17-12725-2017
- Retrieving Precipitable Water Vapor Over Land From Satellite Passive Microwave Radiometer Measurements Using Automated Machine Learning X. Xia et al. https://doi.org/10.1029/2023GL105197
- A method for estimating high spatial resolution total precipitable water in all-weather condition by fusing satellite near-infrared and microwave observations Q. Sun et al. https://doi.org/10.1016/j.rse.2023.113952
- An enhanced integrated water vapour dataset from more than 10 000 global ground-based GPS stations in 2020 P. Yuan et al. https://doi.org/10.5194/essd-15-723-2023
- A Framework for Estimating Clear-Sky Atmospheric Total Precipitable Water (TPW) from VIIRS/S-NPP S. Zhou & J. Cheng https://doi.org/10.3390/rs11080916
- Decadal All-sky Terrestrial Precipitable Water Vapor Dataset from FengYun Microwave Imagers X. Xia et al. https://doi.org/10.1007/s00376-025-5101-6
- Integrating near-infrared, thermal infrared, and microwave satellite observations to retrieve high-resolution precipitable water vapor Z. Du et al. https://doi.org/10.1016/j.rse.2025.114611
- TROPOMI/S5P Total Column Water Vapor validation against AERONET ground-based measurements K. Garane et al. https://doi.org/10.5194/amt-16-57-2023
- Evaluation of tropical water vapour from CMIP6 global climate models using the ESA CCI Water Vapour climate data records J. He et al. https://doi.org/10.5194/acp-22-12591-2022
- Analysis of Short-Term Drought Episodes Using Sentinel-3 SLSTR Data under a Semi-Arid Climate in Lower Eastern Kenya P. Musyimi et al. https://doi.org/10.3390/rs15123041
- Refining MODIS NIR Atmospheric Water Vapor Retrieval Algorithm Using GPS-Derived Water Vapor Data J. He & Z. Liu https://doi.org/10.1109/TGRS.2020.3016655
- The GEWEX Water Vapor Assessment archive of water vapour products from satellite observations and reanalyses M. Schröder et al. https://doi.org/10.5194/essd-10-1093-2018
- A total precipitable water retrieval method over land using the combination of passive microwave and optical remote sensing D. Ji et al. https://doi.org/10.1016/j.rse.2017.01.028
- A Spatial PWV Retrieval Model Over Land for GCOM-W/AMSR2 Using Neural Network Method: A Case in the Western United States Z. Gao et al. https://doi.org/10.1109/JSTARS.2023.3255259
- An Improved Model for the Retrieval of Precipitable Water Vapor in All-Weather Conditions (RCMNT) Based on NIR and TIR Recordings of MODIS Y. Wang et al. https://doi.org/10.1109/TGRS.2024.3381750
- The Advanced Infra-Red WAter Vapour Estimator (AIRWAVE) version 2: algorithm evolution, dataset description and performance improvements E. Castelli et al. https://doi.org/10.5194/amt-12-371-2019
- Retrieval of Daytime Total Column Water Vapour from OLCI Measurements over Land Surfaces R. Preusker et al. https://doi.org/10.3390/rs13050932
- The GEWEX Water Vapor Assessment: Results from Intercomparison, Trend, and Homogeneity Analysis of Total Column Water Vapor M. Schröder et al. https://doi.org/10.1175/JAMC-D-15-0304.1
- Representativeness of total column water vapour retrievals from instruments on polar orbiting satellites H. Diedrich et al. https://doi.org/10.5194/acp-16-8331-2016
- Impact of High Concentrations of Saharan Dust Aerosols on Infrared-Based Land Surface Temperature Products F. Stante et al. https://doi.org/10.1109/JSTARS.2023.3263374
- Precipitable Water Vapor Retrieval Over Land From GCOM-W/AMSR2 Based on a New Integrated Method Z. Gao et al. https://doi.org/10.1109/TGRS.2022.3151384
- Algorithm for Recovery of Integrated Water Vapor Content in the Atmosphere over Land Surfaces Based on Satellite Spectroradiometer Data S. Lisenko https://doi.org/10.1007/s10812-017-0467-6
- Trends and Variability in Precipitable Water Vapor throughout North China from 1979 to 2015 W. Peng et al. https://doi.org/10.1155/2017/7804823
- An Advanced Algorithm to Retrieve Total Atmospheric Water Vapor Content From the Advanced Microwave Scanning Radiometer Data Over Sea Ice and Sea Water Surfaces in the Arctic E. Zabolotskikh et al. https://doi.org/10.1109/TGRS.2019.2948289
- Retrieving snow and ice characteristics by remotely sensed emissivity using the multi-view brightness temperature within 8 μm to 14 μm T. Keck et al. https://doi.org/10.1016/j.rse.2017.09.006
- Accurate and Full-Coverage Retrieval of Total Column Water Vapor From Chinese UV-VIS Satellites Using an Interpretable Machine Learning Approach R. Zhao et al. https://doi.org/10.1109/TGRS.2025.3579262
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