Optimizing the Assimilation of the GOES-16/-17 Atmospheric Motion Vectors in the Hurricane Weather Forecasting (HWRF) Model
Hourly and 15 min GOES-16 and -17 atmospheric motion vectors (AMVs) are evaluated using the 2020 version of the operational HWRF to assess their impact on tropical cyclone forecasting. The evaluation includes infrared (IR), visible (VIS), shortwave (SWIR), clear air, and cloud top water vapor (CAWV...
Published in: | Remote Sensing |
---|---|
Main Authors: | , , , , , , , |
Format: | Article in Journal/Newspaper |
Language: | English |
Published: |
MDPI AG
2022
|
Subjects: | |
Online Access: | https://doi.org/10.3390/rs14133068 https://doaj.org/article/4898064c6cdf4fffb6119860860583a3 |
id |
ftdoajarticles:oai:doaj.org/article:4898064c6cdf4fffb6119860860583a3 |
---|---|
record_format |
openpolar |
spelling |
ftdoajarticles:oai:doaj.org/article:4898064c6cdf4fffb6119860860583a3 2023-05-15T17:34:09+02:00 Optimizing the Assimilation of the GOES-16/-17 Atmospheric Motion Vectors in the Hurricane Weather Forecasting (HWRF) Model Agnes H. N. Lim Sharon E. Nebuda James A. Jung Jaime M. Daniels Andrew Bailey Wayne Bresky Li Bi Avichal Mehra 2022-06-01T00:00:00Z https://doi.org/10.3390/rs14133068 https://doaj.org/article/4898064c6cdf4fffb6119860860583a3 EN eng MDPI AG https://www.mdpi.com/2072-4292/14/13/3068 https://doaj.org/toc/2072-4292 doi:10.3390/rs14133068 2072-4292 https://doaj.org/article/4898064c6cdf4fffb6119860860583a3 Remote Sensing, Vol 14, Iss 3068, p 3068 (2022) data assimilation atmospheric motion vectors HWRF GOES-16 and 17 tropical cyclone forecasting Science Q article 2022 ftdoajarticles https://doi.org/10.3390/rs14133068 2022-12-30T23:23:27Z Hourly and 15 min GOES-16 and -17 atmospheric motion vectors (AMVs) are evaluated using the 2020 version of the operational HWRF to assess their impact on tropical cyclone forecasting. The evaluation includes infrared (IR), visible (VIS), shortwave (SWIR), clear air, and cloud top water vapor (CAWV and CTWV) AMVs derived from the ABI imagery. Several changes are made to optimize the assimilation of these winds. The observational error profile is inflated to avoid overweighting of the AMVs. The range of allowable AMV wind speeds entering the assimilation system is increased to include larger wind speeds observed in tropical cyclones. Two data quality checks, commonly used for rejecting AMVs, namely QI and PCT1, have been removed. These changes resulted in a 20–40% increase in the number of AMVs assimilated. One additional change, specific to infrared AMVs, is narrowing the atmospheric layer where IR AMVs are rejected from 400–800 hPa to 400–600 hPa. The AMVs’ impact on forecast skill is assessed using storms from the North Atlantic and the Eastern Pacific, respectively. Overall, GOES-16 and -17 AMVs are beneficial for improving tropical cyclone forecasting. Positive analysis and forecast impact are obtained for track error, intensity error, minimum central pressure error, and storm size. Article in Journal/Newspaper North Atlantic Directory of Open Access Journals: DOAJ Articles Pacific Remote Sensing 14 13 3068 |
institution |
Open Polar |
collection |
Directory of Open Access Journals: DOAJ Articles |
op_collection_id |
ftdoajarticles |
language |
English |
topic |
data assimilation atmospheric motion vectors HWRF GOES-16 and 17 tropical cyclone forecasting Science Q |
spellingShingle |
data assimilation atmospheric motion vectors HWRF GOES-16 and 17 tropical cyclone forecasting Science Q Agnes H. N. Lim Sharon E. Nebuda James A. Jung Jaime M. Daniels Andrew Bailey Wayne Bresky Li Bi Avichal Mehra Optimizing the Assimilation of the GOES-16/-17 Atmospheric Motion Vectors in the Hurricane Weather Forecasting (HWRF) Model |
topic_facet |
data assimilation atmospheric motion vectors HWRF GOES-16 and 17 tropical cyclone forecasting Science Q |
description |
Hourly and 15 min GOES-16 and -17 atmospheric motion vectors (AMVs) are evaluated using the 2020 version of the operational HWRF to assess their impact on tropical cyclone forecasting. The evaluation includes infrared (IR), visible (VIS), shortwave (SWIR), clear air, and cloud top water vapor (CAWV and CTWV) AMVs derived from the ABI imagery. Several changes are made to optimize the assimilation of these winds. The observational error profile is inflated to avoid overweighting of the AMVs. The range of allowable AMV wind speeds entering the assimilation system is increased to include larger wind speeds observed in tropical cyclones. Two data quality checks, commonly used for rejecting AMVs, namely QI and PCT1, have been removed. These changes resulted in a 20–40% increase in the number of AMVs assimilated. One additional change, specific to infrared AMVs, is narrowing the atmospheric layer where IR AMVs are rejected from 400–800 hPa to 400–600 hPa. The AMVs’ impact on forecast skill is assessed using storms from the North Atlantic and the Eastern Pacific, respectively. Overall, GOES-16 and -17 AMVs are beneficial for improving tropical cyclone forecasting. Positive analysis and forecast impact are obtained for track error, intensity error, minimum central pressure error, and storm size. |
format |
Article in Journal/Newspaper |
author |
Agnes H. N. Lim Sharon E. Nebuda James A. Jung Jaime M. Daniels Andrew Bailey Wayne Bresky Li Bi Avichal Mehra |
author_facet |
Agnes H. N. Lim Sharon E. Nebuda James A. Jung Jaime M. Daniels Andrew Bailey Wayne Bresky Li Bi Avichal Mehra |
author_sort |
Agnes H. N. Lim |
title |
Optimizing the Assimilation of the GOES-16/-17 Atmospheric Motion Vectors in the Hurricane Weather Forecasting (HWRF) Model |
title_short |
Optimizing the Assimilation of the GOES-16/-17 Atmospheric Motion Vectors in the Hurricane Weather Forecasting (HWRF) Model |
title_full |
Optimizing the Assimilation of the GOES-16/-17 Atmospheric Motion Vectors in the Hurricane Weather Forecasting (HWRF) Model |
title_fullStr |
Optimizing the Assimilation of the GOES-16/-17 Atmospheric Motion Vectors in the Hurricane Weather Forecasting (HWRF) Model |
title_full_unstemmed |
Optimizing the Assimilation of the GOES-16/-17 Atmospheric Motion Vectors in the Hurricane Weather Forecasting (HWRF) Model |
title_sort |
optimizing the assimilation of the goes-16/-17 atmospheric motion vectors in the hurricane weather forecasting (hwrf) model |
publisher |
MDPI AG |
publishDate |
2022 |
url |
https://doi.org/10.3390/rs14133068 https://doaj.org/article/4898064c6cdf4fffb6119860860583a3 |
geographic |
Pacific |
geographic_facet |
Pacific |
genre |
North Atlantic |
genre_facet |
North Atlantic |
op_source |
Remote Sensing, Vol 14, Iss 3068, p 3068 (2022) |
op_relation |
https://www.mdpi.com/2072-4292/14/13/3068 https://doaj.org/toc/2072-4292 doi:10.3390/rs14133068 2072-4292 https://doaj.org/article/4898064c6cdf4fffb6119860860583a3 |
op_doi |
https://doi.org/10.3390/rs14133068 |
container_title |
Remote Sensing |
container_volume |
14 |
container_issue |
13 |
container_start_page |
3068 |
_version_ |
1766132902442041344 |