Arctic Winds Retrieved from FY-3D Microwave Humidity Sounder-II 183.31 GHz Brightness Temperature Using Atmospheric Motion Vector Method
In this study, we develop an Atmospheric Motion Vector (AMV)-based method for retrieving wind vectors using 183.31 GHz water-vapor absorption channels. The method involves tracking water-vapor features from image triplets and subsequently deriving wind fields from motion vectors. The height of the d...
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2024
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Online Access: | https://doi.org/10.3390/rs16101715 https://doaj.org/article/fc45770a03ed4486bde2c144873e2451 |
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ftdoajarticles:oai:doaj.org/article:fc45770a03ed4486bde2c144873e2451 2024-09-09T19:23:11+00:00 Arctic Winds Retrieved from FY-3D Microwave Humidity Sounder-II 183.31 GHz Brightness Temperature Using Atmospheric Motion Vector Method Bingxu Li Xi Guo Hao Liu Donghao Han Gang Li Ji Wu 2024-05-01T00:00:00Z https://doi.org/10.3390/rs16101715 https://doaj.org/article/fc45770a03ed4486bde2c144873e2451 EN eng MDPI AG https://www.mdpi.com/2072-4292/16/10/1715 https://doaj.org/toc/2072-4292 doi:10.3390/rs16101715 2072-4292 https://doaj.org/article/fc45770a03ed4486bde2c144873e2451 Remote Sensing, Vol 16, Iss 10, p 1715 (2024) Atmospheric Motion Vector (AMV) polar meteorology microwave radiometers water-vapor absorption band Science Q article 2024 ftdoajarticles https://doi.org/10.3390/rs16101715 2024-08-05T17:49:20Z In this study, we develop an Atmospheric Motion Vector (AMV)-based method for retrieving wind vectors using 183.31 GHz water-vapor absorption channels. The method involves tracking water-vapor features from image triplets and subsequently deriving wind fields from motion vectors. The height of the derived wind for each channel is determined by calculating the weighing function peak using monthly averaged ERA5 reanalysis data. By utilizing Microwave Humidity Sounder-II (MWHS-II) brightness temperatures from the five channels centered around 183.31 GHz, wind vectors are retrieved within the Arctic region for the entire year of 2022. The retrieval quality is evaluated through comparative analysis with ERA5 reanalysis data and the Visible Infrared Imaging Radiometer Suite (VIIRS) wind product. The resultant vector root mean square errors (RMSEs) are approximately 4.5 m/s for the three lower-height channels and 5.5 m/s for the two upper-height channels. These findings demonstrate a wind retrieval performance comparable to the existing methods, highlighting its potential for augmenting wind availability at lower height levels. Article in Journal/Newspaper Arctic Directory of Open Access Journals: DOAJ Articles Arctic Triplets ENVELOPE(-59.750,-59.750,-62.383,-62.383) Remote Sensing 16 10 1715 |
institution |
Open Polar |
collection |
Directory of Open Access Journals: DOAJ Articles |
op_collection_id |
ftdoajarticles |
language |
English |
topic |
Atmospheric Motion Vector (AMV) polar meteorology microwave radiometers water-vapor absorption band Science Q |
spellingShingle |
Atmospheric Motion Vector (AMV) polar meteorology microwave radiometers water-vapor absorption band Science Q Bingxu Li Xi Guo Hao Liu Donghao Han Gang Li Ji Wu Arctic Winds Retrieved from FY-3D Microwave Humidity Sounder-II 183.31 GHz Brightness Temperature Using Atmospheric Motion Vector Method |
topic_facet |
Atmospheric Motion Vector (AMV) polar meteorology microwave radiometers water-vapor absorption band Science Q |
description |
In this study, we develop an Atmospheric Motion Vector (AMV)-based method for retrieving wind vectors using 183.31 GHz water-vapor absorption channels. The method involves tracking water-vapor features from image triplets and subsequently deriving wind fields from motion vectors. The height of the derived wind for each channel is determined by calculating the weighing function peak using monthly averaged ERA5 reanalysis data. By utilizing Microwave Humidity Sounder-II (MWHS-II) brightness temperatures from the five channels centered around 183.31 GHz, wind vectors are retrieved within the Arctic region for the entire year of 2022. The retrieval quality is evaluated through comparative analysis with ERA5 reanalysis data and the Visible Infrared Imaging Radiometer Suite (VIIRS) wind product. The resultant vector root mean square errors (RMSEs) are approximately 4.5 m/s for the three lower-height channels and 5.5 m/s for the two upper-height channels. These findings demonstrate a wind retrieval performance comparable to the existing methods, highlighting its potential for augmenting wind availability at lower height levels. |
format |
Article in Journal/Newspaper |
author |
Bingxu Li Xi Guo Hao Liu Donghao Han Gang Li Ji Wu |
author_facet |
Bingxu Li Xi Guo Hao Liu Donghao Han Gang Li Ji Wu |
author_sort |
Bingxu Li |
title |
Arctic Winds Retrieved from FY-3D Microwave Humidity Sounder-II 183.31 GHz Brightness Temperature Using Atmospheric Motion Vector Method |
title_short |
Arctic Winds Retrieved from FY-3D Microwave Humidity Sounder-II 183.31 GHz Brightness Temperature Using Atmospheric Motion Vector Method |
title_full |
Arctic Winds Retrieved from FY-3D Microwave Humidity Sounder-II 183.31 GHz Brightness Temperature Using Atmospheric Motion Vector Method |
title_fullStr |
Arctic Winds Retrieved from FY-3D Microwave Humidity Sounder-II 183.31 GHz Brightness Temperature Using Atmospheric Motion Vector Method |
title_full_unstemmed |
Arctic Winds Retrieved from FY-3D Microwave Humidity Sounder-II 183.31 GHz Brightness Temperature Using Atmospheric Motion Vector Method |
title_sort |
arctic winds retrieved from fy-3d microwave humidity sounder-ii 183.31 ghz brightness temperature using atmospheric motion vector method |
publisher |
MDPI AG |
publishDate |
2024 |
url |
https://doi.org/10.3390/rs16101715 https://doaj.org/article/fc45770a03ed4486bde2c144873e2451 |
long_lat |
ENVELOPE(-59.750,-59.750,-62.383,-62.383) |
geographic |
Arctic Triplets |
geographic_facet |
Arctic Triplets |
genre |
Arctic |
genre_facet |
Arctic |
op_source |
Remote Sensing, Vol 16, Iss 10, p 1715 (2024) |
op_relation |
https://www.mdpi.com/2072-4292/16/10/1715 https://doaj.org/toc/2072-4292 doi:10.3390/rs16101715 2072-4292 https://doaj.org/article/fc45770a03ed4486bde2c144873e2451 |
op_doi |
https://doi.org/10.3390/rs16101715 |
container_title |
Remote Sensing |
container_volume |
16 |
container_issue |
10 |
container_start_page |
1715 |
_version_ |
1809763539624132608 |