Validation of the Suomi NPP VIIRS Ice Surface Temperature Environmental Data Record
Continuous monitoring of the surface temperature is critical to understanding and forecasting Arctic climate change; as surface temperature integrates changes in the surface energy budget. The sea-ice surface temperature (IST) has been measured with optical and thermal infrared sensors for many year...
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ftmdpi:oai:mdpi.com:/2072-4292/7/12/15880/ 2023-08-20T04:04:06+02:00 Validation of the Suomi NPP VIIRS Ice Surface Temperature Environmental Data Record Yinghui Liu Jeffrey Key Mark Tschudi Richard Dworak Robert Mahoney Daniel Baldwin 2015-12-18 application/pdf https://doi.org/10.3390/rs71215880 EN eng Multidisciplinary Digital Publishing Institute https://dx.doi.org/10.3390/rs71215880 https://creativecommons.org/licenses/by/4.0/ Remote Sensing; Volume 7; Issue 12; Pages: 17258-17271 Suomi NPP ice surface temperature Environmental Data Record calibration and validation Text 2015 ftmdpi https://doi.org/10.3390/rs71215880 2023-07-31T20:48:55Z Continuous monitoring of the surface temperature is critical to understanding and forecasting Arctic climate change; as surface temperature integrates changes in the surface energy budget. The sea-ice surface temperature (IST) has been measured with optical and thermal infrared sensors for many years. With the IST Environmental Data Record (EDR) available from the Visible Infrared Imaging Radiometer Suite (VIIRS) onboard the Suomi National Polar-orbiting Partnership (NPP) and future Joint Polar Satellite System (JPSS) satellites; we can continue to monitor and investigate Arctic climate change. This work examines the quality of the VIIRS IST EDR. Validation is performed through comparisons with multiple datasets; including NASA IceBridge measurements; air temperature from Arctic drifting ice buoys; Moderate Resolution Imaging Spectroradiometer (MODIS) IST; MODIS IST simultaneous nadir overpass (SNO); and surface air temperature from the National Centers for Environmental Prediction/National Center for Atmospheric Research (NCEP/NCAR) reanalysis. Results show biases of −0.34; −0.12; 0.16; −3.20; and −3.41 K compared to an aircraft-mounted downward-looking pyrometer; MODIS; MODIS SNO; drifting buoy; and NCEP/NCAR reanalysis; respectively; root-mean-square errors of 0.98; 1.02; 0.95; 4.89; and 6.94 K; and root-mean-square errors with the bias removed of 0.92; 1.01; 0.94; 3.70; and 6.04 K. Based on the IceBridge and MODIS results; the VIIRS IST uncertainty (RMSE) meets or exceeds the JPSS system requirement of 1.0 K. The product can therefore be considered useful for meteorological and climatological applications. Text Arctic Climate change Sea ice MDPI Open Access Publishing Arctic Remote Sensing 7 12 17258 17271 |
institution |
Open Polar |
collection |
MDPI Open Access Publishing |
op_collection_id |
ftmdpi |
language |
English |
topic |
Suomi NPP ice surface temperature Environmental Data Record calibration and validation |
spellingShingle |
Suomi NPP ice surface temperature Environmental Data Record calibration and validation Yinghui Liu Jeffrey Key Mark Tschudi Richard Dworak Robert Mahoney Daniel Baldwin Validation of the Suomi NPP VIIRS Ice Surface Temperature Environmental Data Record |
topic_facet |
Suomi NPP ice surface temperature Environmental Data Record calibration and validation |
description |
Continuous monitoring of the surface temperature is critical to understanding and forecasting Arctic climate change; as surface temperature integrates changes in the surface energy budget. The sea-ice surface temperature (IST) has been measured with optical and thermal infrared sensors for many years. With the IST Environmental Data Record (EDR) available from the Visible Infrared Imaging Radiometer Suite (VIIRS) onboard the Suomi National Polar-orbiting Partnership (NPP) and future Joint Polar Satellite System (JPSS) satellites; we can continue to monitor and investigate Arctic climate change. This work examines the quality of the VIIRS IST EDR. Validation is performed through comparisons with multiple datasets; including NASA IceBridge measurements; air temperature from Arctic drifting ice buoys; Moderate Resolution Imaging Spectroradiometer (MODIS) IST; MODIS IST simultaneous nadir overpass (SNO); and surface air temperature from the National Centers for Environmental Prediction/National Center for Atmospheric Research (NCEP/NCAR) reanalysis. Results show biases of −0.34; −0.12; 0.16; −3.20; and −3.41 K compared to an aircraft-mounted downward-looking pyrometer; MODIS; MODIS SNO; drifting buoy; and NCEP/NCAR reanalysis; respectively; root-mean-square errors of 0.98; 1.02; 0.95; 4.89; and 6.94 K; and root-mean-square errors with the bias removed of 0.92; 1.01; 0.94; 3.70; and 6.04 K. Based on the IceBridge and MODIS results; the VIIRS IST uncertainty (RMSE) meets or exceeds the JPSS system requirement of 1.0 K. The product can therefore be considered useful for meteorological and climatological applications. |
format |
Text |
author |
Yinghui Liu Jeffrey Key Mark Tschudi Richard Dworak Robert Mahoney Daniel Baldwin |
author_facet |
Yinghui Liu Jeffrey Key Mark Tschudi Richard Dworak Robert Mahoney Daniel Baldwin |
author_sort |
Yinghui Liu |
title |
Validation of the Suomi NPP VIIRS Ice Surface Temperature Environmental Data Record |
title_short |
Validation of the Suomi NPP VIIRS Ice Surface Temperature Environmental Data Record |
title_full |
Validation of the Suomi NPP VIIRS Ice Surface Temperature Environmental Data Record |
title_fullStr |
Validation of the Suomi NPP VIIRS Ice Surface Temperature Environmental Data Record |
title_full_unstemmed |
Validation of the Suomi NPP VIIRS Ice Surface Temperature Environmental Data Record |
title_sort |
validation of the suomi npp viirs ice surface temperature environmental data record |
publisher |
Multidisciplinary Digital Publishing Institute |
publishDate |
2015 |
url |
https://doi.org/10.3390/rs71215880 |
geographic |
Arctic |
geographic_facet |
Arctic |
genre |
Arctic Climate change Sea ice |
genre_facet |
Arctic Climate change Sea ice |
op_source |
Remote Sensing; Volume 7; Issue 12; Pages: 17258-17271 |
op_relation |
https://dx.doi.org/10.3390/rs71215880 |
op_rights |
https://creativecommons.org/licenses/by/4.0/ |
op_doi |
https://doi.org/10.3390/rs71215880 |
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Remote Sensing |
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7 |
container_issue |
12 |
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17271 |
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