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Assessment of the GOES-16 Clear Sky Mask Product over the Contiguous USA Using CALIPSO Retrievals

Cloud initialization is a challenge in numerical weather prediction. Probably the most relevant observations for this task come from geostationary satellites. These satellites provide the cloud mask with high spatio-temporal resolution and low latencies. The low latency is an attractive option for n...

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Autor principal: Jiménez, Pedro A.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8243760/
https://www.ncbi.nlm.nih.gov/pubmed/34211763
http://dx.doi.org/10.3390/rs12101630
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author Jiménez, Pedro A.
author_facet Jiménez, Pedro A.
author_sort Jiménez, Pedro A.
collection PubMed
description Cloud initialization is a challenge in numerical weather prediction. Probably the most relevant observations for this task come from geostationary satellites. These satellites provide the cloud mask with high spatio-temporal resolution and low latencies. The low latency is an attractive option for nowcasting systems such as the solar irradiance nowcasting model MAD-WRF. In this study we examine the potential of using the cloud mask from the GOES-16 satellite over the contiguous U.S. for this particular application. With this aim, the GOES-16 cloud mask product is compared against CALIPSO retrievals during a two year period. Both the GOES-16 data and the CALIPSO retrievals are interpolated to a grid that covers the contiguous U.S. at 9 km of horizontal grid spacing that is being used in MAD-WRF nowcasts. Results indicate a probability of detection, or accuracy, of all sky conditions of 86.0%. However, the accuracy is higher for cloud detections, 90.9% than for clear sky detections 74.8%. The lower performance of clear sky retrievals is a result of missdetections during daytime. This is especially clear for summer, and for regions to the north of parallel 36 during winter. However, regions to the south of parallel 36 show acceptable performance during both daytime and nighttime. It is over these regions wherein the cloud mask product should show its largest potential to enhance the cloud initialization in the MAD-WRF model.
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spelling pubmed-82437602021-06-30 Assessment of the GOES-16 Clear Sky Mask Product over the Contiguous USA Using CALIPSO Retrievals Jiménez, Pedro A. Remote Sens (Basel) Article Cloud initialization is a challenge in numerical weather prediction. Probably the most relevant observations for this task come from geostationary satellites. These satellites provide the cloud mask with high spatio-temporal resolution and low latencies. The low latency is an attractive option for nowcasting systems such as the solar irradiance nowcasting model MAD-WRF. In this study we examine the potential of using the cloud mask from the GOES-16 satellite over the contiguous U.S. for this particular application. With this aim, the GOES-16 cloud mask product is compared against CALIPSO retrievals during a two year period. Both the GOES-16 data and the CALIPSO retrievals are interpolated to a grid that covers the contiguous U.S. at 9 km of horizontal grid spacing that is being used in MAD-WRF nowcasts. Results indicate a probability of detection, or accuracy, of all sky conditions of 86.0%. However, the accuracy is higher for cloud detections, 90.9% than for clear sky detections 74.8%. The lower performance of clear sky retrievals is a result of missdetections during daytime. This is especially clear for summer, and for regions to the north of parallel 36 during winter. However, regions to the south of parallel 36 show acceptable performance during both daytime and nighttime. It is over these regions wherein the cloud mask product should show its largest potential to enhance the cloud initialization in the MAD-WRF model. 2020-05-20 2020-05-02 /pmc/articles/PMC8243760/ /pubmed/34211763 http://dx.doi.org/10.3390/rs12101630 Text en https://creativecommons.org/licenses/by/4.0/This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) ).
spellingShingle Article
Jiménez, Pedro A.
Assessment of the GOES-16 Clear Sky Mask Product over the Contiguous USA Using CALIPSO Retrievals
title Assessment of the GOES-16 Clear Sky Mask Product over the Contiguous USA Using CALIPSO Retrievals
title_full Assessment of the GOES-16 Clear Sky Mask Product over the Contiguous USA Using CALIPSO Retrievals
title_fullStr Assessment of the GOES-16 Clear Sky Mask Product over the Contiguous USA Using CALIPSO Retrievals
title_full_unstemmed Assessment of the GOES-16 Clear Sky Mask Product over the Contiguous USA Using CALIPSO Retrievals
title_short Assessment of the GOES-16 Clear Sky Mask Product over the Contiguous USA Using CALIPSO Retrievals
title_sort assessment of the goes-16 clear sky mask product over the contiguous usa using calipso retrievals
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8243760/
https://www.ncbi.nlm.nih.gov/pubmed/34211763
http://dx.doi.org/10.3390/rs12101630
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