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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Cited
15 citations as recorded by crossref.
- Retrieval of daytime total columnar water vapour from MODIS measurements over land surfaces H. Diedrich et al. 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. 10.5194/acp-17-12725-2017
- The Advanced Infra-Red WAter Vapour Estimator (AIRWAVE) version 2: algorithm evolution, dataset description and performance improvements E. Castelli et al. 10.5194/amt-12-371-2019
- Retrieval of Daytime Total Column Water Vapour from OLCI Measurements over Land Surfaces R. Preusker et al. 10.3390/rs13050932
- The GEWEX Water Vapor Assessment: Results from Intercomparison, Trend, and Homogeneity Analysis of Total Column Water Vapor M. Schröder et al. 10.1175/JAMC-D-15-0304.1
- A Framework for Estimating Clear-Sky Atmospheric Total Precipitable Water (TPW) from VIIRS/S-NPP . Zhou & . Cheng 10.3390/rs11080916
- Representativeness of total column water vapour retrievals from instruments on polar orbiting satellites H. Diedrich et al. 10.5194/acp-16-8331-2016
- Algorithm for Recovery of Integrated Water Vapor Content in the Atmosphere over Land Surfaces Based on Satellite Spectroradiometer Data S. Lisenko 10.1007/s10812-017-0467-6
- Trends and Variability in Precipitable Water Vapor throughout North China from 1979 to 2015 W. Peng et al. 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. 10.1109/TGRS.2019.2948289
- Refining MODIS NIR Atmospheric Water Vapor Retrieval Algorithm Using GPS-Derived Water Vapor Data J. He & Z. Liu 10.1109/TGRS.2020.3016655
- 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. 10.1016/j.rse.2017.09.006
- The GEWEX Water Vapor Assessment archive of water vapour products from satellite observations and reanalyses M. Schröder et al. 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. 10.1016/j.rse.2017.01.028
- A high-quality, homogenized, global, long-term (1993-2008) DORIS precipitable water data set for climate monitoring and model verification O. Bock et al. 10.1002/2013JD021124
14 citations as recorded by crossref.
- Retrieval of daytime total columnar water vapour from MODIS measurements over land surfaces H. Diedrich et al. 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. 10.5194/acp-17-12725-2017
- The Advanced Infra-Red WAter Vapour Estimator (AIRWAVE) version 2: algorithm evolution, dataset description and performance improvements E. Castelli et al. 10.5194/amt-12-371-2019
- Retrieval of Daytime Total Column Water Vapour from OLCI Measurements over Land Surfaces R. Preusker et al. 10.3390/rs13050932
- The GEWEX Water Vapor Assessment: Results from Intercomparison, Trend, and Homogeneity Analysis of Total Column Water Vapor M. Schröder et al. 10.1175/JAMC-D-15-0304.1
- A Framework for Estimating Clear-Sky Atmospheric Total Precipitable Water (TPW) from VIIRS/S-NPP . Zhou & . Cheng 10.3390/rs11080916
- Representativeness of total column water vapour retrievals from instruments on polar orbiting satellites H. Diedrich et al. 10.5194/acp-16-8331-2016
- Algorithm for Recovery of Integrated Water Vapor Content in the Atmosphere over Land Surfaces Based on Satellite Spectroradiometer Data S. Lisenko 10.1007/s10812-017-0467-6
- Trends and Variability in Precipitable Water Vapor throughout North China from 1979 to 2015 W. Peng et al. 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. 10.1109/TGRS.2019.2948289
- Refining MODIS NIR Atmospheric Water Vapor Retrieval Algorithm Using GPS-Derived Water Vapor Data J. He & Z. Liu 10.1109/TGRS.2020.3016655
- 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. 10.1016/j.rse.2017.09.006
- The GEWEX Water Vapor Assessment archive of water vapour products from satellite observations and reanalyses M. Schröder et al. 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. 10.1016/j.rse.2017.01.028
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