Estimating the Clear-Sky Longwave Downward Radiation in the Arctic from FengYun-3D MERSI-2 Data
Surface longwave downward radiation (LWDR) plays a key role in determining the Arctic surface energy budget, especially in insolation-absent boreal winter. A reliable LWDR product is essential for understanding the intrinsic physical mechanisms of the rapid changes in the Arctic climate. The Medium-...
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ftdoajarticles:oai:doaj.org/article:f7cab5426f9e49d0a826b545687d9333 2023-05-15T14:51:18+02:00 Estimating the Clear-Sky Longwave Downward Radiation in the Arctic from FengYun-3D MERSI-2 Data Yunfeng Cao Manyao Li Yuzhen Zhang 2022-01-01T00:00:00Z https://doi.org/10.3390/rs14030606 https://doaj.org/article/f7cab5426f9e49d0a826b545687d9333 EN eng MDPI AG https://www.mdpi.com/2072-4292/14/3/606 https://doaj.org/toc/2072-4292 doi:10.3390/rs14030606 2072-4292 https://doaj.org/article/f7cab5426f9e49d0a826b545687d9333 Remote Sensing, Vol 14, Iss 606, p 606 (2022) surface downward longwave radiation FengYun-3D MERSI-2 satellite observation machine learning Arctic region Science Q article 2022 ftdoajarticles https://doi.org/10.3390/rs14030606 2022-12-31T14:43:10Z Surface longwave downward radiation (LWDR) plays a key role in determining the Arctic surface energy budget, especially in insolation-absent boreal winter. A reliable LWDR product is essential for understanding the intrinsic physical mechanisms of the rapid changes in the Arctic climate. The Medium-Resolution Spectral Imager (MERSI-2), a major payload of the Chinese second-generation polar-orbiting meteorological satellite, FengYun-3D (FY-3D), was designed similar to the NASA Moderate-Resolution Imaging Spectroradiometer (MODIS) in terms of the spectral bands. Although significant progress has been made in estimating clear-sky LWDR from MODIS observations using a variety of methods, few studies have focused on the retrieval of clear-sky LWDR from FY-3D MERSI-2 observations. In this study, we propose an advanced method to directly estimate the clear-sky LWDR in the Arctic from the FY-3D MERSI-2 thermal infrared (TIR) top-of-atmosphere (TOA) radiances and auxiliary information using the extremely randomized trees (ERT) machine learning algorithm. The retrieval accuracy of RMSE and bias, validated with the Baseline Surface Radiation Network (BSRN) in situ measurements, are 14.14 W/m 2 and 4.36 W/m 2 , respectively, which is comparable and even better than previous studies. The scale effect in retrieval accuracy evaluation was further analyzed and showed that the validating window size could significantly influence the retrieval accuracy of the MERSI-2 clear-sky LWDR dataset. After aggregating to a spatial resolution of 9 km, the RMSE and bias of MERSI-2 retrievals can be reduced to 9.43 W/m 2 and −0.14 W/m 2 , respectively. The retrieval accuracy of MERSI-2 clear-sky LWDR at the CERES SSF FOV spatial scale (approximately 20 km) can be further reduced to 8.64 W/m 2 , which is much higher than the reported accuracy of the CERES SSF products. This study demonstrates the feasibility of producing LWDR datasets from Chinese FY-3D MERSI-2 observations using machine learning methods. Article in Journal/Newspaper Arctic Directory of Open Access Journals: DOAJ Articles Arctic Remote Sensing 14 3 606 |
institution |
Open Polar |
collection |
Directory of Open Access Journals: DOAJ Articles |
op_collection_id |
ftdoajarticles |
language |
English |
topic |
surface downward longwave radiation FengYun-3D MERSI-2 satellite observation machine learning Arctic region Science Q |
spellingShingle |
surface downward longwave radiation FengYun-3D MERSI-2 satellite observation machine learning Arctic region Science Q Yunfeng Cao Manyao Li Yuzhen Zhang Estimating the Clear-Sky Longwave Downward Radiation in the Arctic from FengYun-3D MERSI-2 Data |
topic_facet |
surface downward longwave radiation FengYun-3D MERSI-2 satellite observation machine learning Arctic region Science Q |
description |
Surface longwave downward radiation (LWDR) plays a key role in determining the Arctic surface energy budget, especially in insolation-absent boreal winter. A reliable LWDR product is essential for understanding the intrinsic physical mechanisms of the rapid changes in the Arctic climate. The Medium-Resolution Spectral Imager (MERSI-2), a major payload of the Chinese second-generation polar-orbiting meteorological satellite, FengYun-3D (FY-3D), was designed similar to the NASA Moderate-Resolution Imaging Spectroradiometer (MODIS) in terms of the spectral bands. Although significant progress has been made in estimating clear-sky LWDR from MODIS observations using a variety of methods, few studies have focused on the retrieval of clear-sky LWDR from FY-3D MERSI-2 observations. In this study, we propose an advanced method to directly estimate the clear-sky LWDR in the Arctic from the FY-3D MERSI-2 thermal infrared (TIR) top-of-atmosphere (TOA) radiances and auxiliary information using the extremely randomized trees (ERT) machine learning algorithm. The retrieval accuracy of RMSE and bias, validated with the Baseline Surface Radiation Network (BSRN) in situ measurements, are 14.14 W/m 2 and 4.36 W/m 2 , respectively, which is comparable and even better than previous studies. The scale effect in retrieval accuracy evaluation was further analyzed and showed that the validating window size could significantly influence the retrieval accuracy of the MERSI-2 clear-sky LWDR dataset. After aggregating to a spatial resolution of 9 km, the RMSE and bias of MERSI-2 retrievals can be reduced to 9.43 W/m 2 and −0.14 W/m 2 , respectively. The retrieval accuracy of MERSI-2 clear-sky LWDR at the CERES SSF FOV spatial scale (approximately 20 km) can be further reduced to 8.64 W/m 2 , which is much higher than the reported accuracy of the CERES SSF products. This study demonstrates the feasibility of producing LWDR datasets from Chinese FY-3D MERSI-2 observations using machine learning methods. |
format |
Article in Journal/Newspaper |
author |
Yunfeng Cao Manyao Li Yuzhen Zhang |
author_facet |
Yunfeng Cao Manyao Li Yuzhen Zhang |
author_sort |
Yunfeng Cao |
title |
Estimating the Clear-Sky Longwave Downward Radiation in the Arctic from FengYun-3D MERSI-2 Data |
title_short |
Estimating the Clear-Sky Longwave Downward Radiation in the Arctic from FengYun-3D MERSI-2 Data |
title_full |
Estimating the Clear-Sky Longwave Downward Radiation in the Arctic from FengYun-3D MERSI-2 Data |
title_fullStr |
Estimating the Clear-Sky Longwave Downward Radiation in the Arctic from FengYun-3D MERSI-2 Data |
title_full_unstemmed |
Estimating the Clear-Sky Longwave Downward Radiation in the Arctic from FengYun-3D MERSI-2 Data |
title_sort |
estimating the clear-sky longwave downward radiation in the arctic from fengyun-3d mersi-2 data |
publisher |
MDPI AG |
publishDate |
2022 |
url |
https://doi.org/10.3390/rs14030606 https://doaj.org/article/f7cab5426f9e49d0a826b545687d9333 |
geographic |
Arctic |
geographic_facet |
Arctic |
genre |
Arctic |
genre_facet |
Arctic |
op_source |
Remote Sensing, Vol 14, Iss 606, p 606 (2022) |
op_relation |
https://www.mdpi.com/2072-4292/14/3/606 https://doaj.org/toc/2072-4292 doi:10.3390/rs14030606 2072-4292 https://doaj.org/article/f7cab5426f9e49d0a826b545687d9333 |
op_doi |
https://doi.org/10.3390/rs14030606 |
container_title |
Remote Sensing |
container_volume |
14 |
container_issue |
3 |
container_start_page |
606 |
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1766322354973048832 |