The AMSU-Based Hydrological Bundle Climate Data Record—Description and Comparison with Other Data Sets
Passive microwave measurements have been available on satellites back to the 1970s, first flown on research satellites developed by the National Aeronautics and Space Administration (NASA). Since then, several other sensors have been flown to retrieve hydrological products for both operational weath...
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ftmdpi:oai:mdpi.com:/2072-4292/10/10/1640/ 2023-08-20T04:09:46+02:00 The AMSU-Based Hydrological Bundle Climate Data Record—Description and Comparison with Other Data Sets Ralph R. Ferraro Brian R. Nelson Tom Smith Olivier P. Prat 2018-10-16 application/pdf https://doi.org/10.3390/rs10101640 EN eng Multidisciplinary Digital Publishing Institute https://dx.doi.org/10.3390/rs10101640 https://creativecommons.org/licenses/by/4.0/ Remote Sensing; Volume 10; Issue 10; Pages: 1640 remote sensing climate data record passive microwave hydrology Text 2018 ftmdpi https://doi.org/10.3390/rs10101640 2023-07-31T21:46:56Z Passive microwave measurements have been available on satellites back to the 1970s, first flown on research satellites developed by the National Aeronautics and Space Administration (NASA). Since then, several other sensors have been flown to retrieve hydrological products for both operational weather applications (e.g., the Special Sensor Microwave/Imager—SSM/I; the Advanced Microwave Sounding Unit—AMSU) and climate applications (e.g., the Advanced Microwave Scanning Radiometer—AMSR; the Tropical Rainfall Measurement Mission Microwave Imager—TMI; the Global Precipitation Mission Microwave Imager—GMI). Here, the focus is on measurements from the AMSU-A, AMSU-B, and Microwave Humidity Sounder (MHS). These sensors have been in operation since 1998, with the launch of NOAA-15, and are also on board NOAA-16, -17, -18, -19, and the MetOp-A and -B satellites. A data set called the “Hydrological Bundle” is a climate data record (CDR) that utilizes brightness temperatures from fundamental CDRs (FCDRs) to generate thematic CDRs (TCDRs). The TCDRs include total precipitable water (TPW), cloud liquid water (CLW), sea-ice concentration (SIC), land surface temperature (LST), land surface emissivity (LSE) for 23, 31, 50 GHz, rain rate (RR), snow cover (SC), ice water path (IWP), and snow water equivalent (SWE). The TCDRs are shown to be in general good agreement with similar products from other sources, such as the Global Precipitation Climatology Project (GPCP) and the Modern-Era Retrospective Analysis for Research and Applications (MERRA-2). Due to the careful intercalibration of the FCDRs, little bias is found among the different TCDRs produced from individual NOAA and MetOp satellites, except for normal diurnal cycle differences. Text Sea ice MDPI Open Access Publishing Merra ENVELOPE(12.615,12.615,65.816,65.816) Remote Sensing 10 10 1640 |
institution |
Open Polar |
collection |
MDPI Open Access Publishing |
op_collection_id |
ftmdpi |
language |
English |
topic |
remote sensing climate data record passive microwave hydrology |
spellingShingle |
remote sensing climate data record passive microwave hydrology Ralph R. Ferraro Brian R. Nelson Tom Smith Olivier P. Prat The AMSU-Based Hydrological Bundle Climate Data Record—Description and Comparison with Other Data Sets |
topic_facet |
remote sensing climate data record passive microwave hydrology |
description |
Passive microwave measurements have been available on satellites back to the 1970s, first flown on research satellites developed by the National Aeronautics and Space Administration (NASA). Since then, several other sensors have been flown to retrieve hydrological products for both operational weather applications (e.g., the Special Sensor Microwave/Imager—SSM/I; the Advanced Microwave Sounding Unit—AMSU) and climate applications (e.g., the Advanced Microwave Scanning Radiometer—AMSR; the Tropical Rainfall Measurement Mission Microwave Imager—TMI; the Global Precipitation Mission Microwave Imager—GMI). Here, the focus is on measurements from the AMSU-A, AMSU-B, and Microwave Humidity Sounder (MHS). These sensors have been in operation since 1998, with the launch of NOAA-15, and are also on board NOAA-16, -17, -18, -19, and the MetOp-A and -B satellites. A data set called the “Hydrological Bundle” is a climate data record (CDR) that utilizes brightness temperatures from fundamental CDRs (FCDRs) to generate thematic CDRs (TCDRs). The TCDRs include total precipitable water (TPW), cloud liquid water (CLW), sea-ice concentration (SIC), land surface temperature (LST), land surface emissivity (LSE) for 23, 31, 50 GHz, rain rate (RR), snow cover (SC), ice water path (IWP), and snow water equivalent (SWE). The TCDRs are shown to be in general good agreement with similar products from other sources, such as the Global Precipitation Climatology Project (GPCP) and the Modern-Era Retrospective Analysis for Research and Applications (MERRA-2). Due to the careful intercalibration of the FCDRs, little bias is found among the different TCDRs produced from individual NOAA and MetOp satellites, except for normal diurnal cycle differences. |
format |
Text |
author |
Ralph R. Ferraro Brian R. Nelson Tom Smith Olivier P. Prat |
author_facet |
Ralph R. Ferraro Brian R. Nelson Tom Smith Olivier P. Prat |
author_sort |
Ralph R. Ferraro |
title |
The AMSU-Based Hydrological Bundle Climate Data Record—Description and Comparison with Other Data Sets |
title_short |
The AMSU-Based Hydrological Bundle Climate Data Record—Description and Comparison with Other Data Sets |
title_full |
The AMSU-Based Hydrological Bundle Climate Data Record—Description and Comparison with Other Data Sets |
title_fullStr |
The AMSU-Based Hydrological Bundle Climate Data Record—Description and Comparison with Other Data Sets |
title_full_unstemmed |
The AMSU-Based Hydrological Bundle Climate Data Record—Description and Comparison with Other Data Sets |
title_sort |
amsu-based hydrological bundle climate data record—description and comparison with other data sets |
publisher |
Multidisciplinary Digital Publishing Institute |
publishDate |
2018 |
url |
https://doi.org/10.3390/rs10101640 |
long_lat |
ENVELOPE(12.615,12.615,65.816,65.816) |
geographic |
Merra |
geographic_facet |
Merra |
genre |
Sea ice |
genre_facet |
Sea ice |
op_source |
Remote Sensing; Volume 10; Issue 10; Pages: 1640 |
op_relation |
https://dx.doi.org/10.3390/rs10101640 |
op_rights |
https://creativecommons.org/licenses/by/4.0/ |
op_doi |
https://doi.org/10.3390/rs10101640 |
container_title |
Remote Sensing |
container_volume |
10 |
container_issue |
10 |
container_start_page |
1640 |
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1774723439064514560 |