Tropical Cyclone Forecasts Impact Assessment from the Assimilation of Hourly Visible, Shortwave, and Clear-Air Water Vapor Atmospheric Motion Vectors in HWRFSource: Weather and Forecasting:;2019:;volume 034:;issue 001::page 177Author:Lim, Agnes H. N.
,
Jung, James A.
,
Nebuda, Sharon E.
,
Daniels, Jaime M.
,
Bresky, Wayne
,
Tong, Mingjing
,
Tallapragada, Vijay
DOI: 10.1175/WAF-D-18-0072.1Publisher: American Meteorological Society
Abstract: The assimilation of atmospheric motion vectors (AMVs) provides important wind information to conventional data-lacking oceanic regions, where tropical cyclones spend most of their lifetimes. Three new AMV types, shortwave infrared (SWIR), clear-air water vapor (CAWV), and visible (VIS), are produced hourly by NOAA/NESDIS and are assimilated in operational NWP systems. The new AMV data types are added to the hourly infrared (IR) and cloud-top water vapor (CTWV) AMV data in the 2016 operational version of the HWRF Model. In this study, we update existing quality control (QC) procedures and add new procedures specific to tropical cyclone assimilation. We assess the impact of the three new AMV types on tropical cyclone forecasts by conducting assimilation experiments for 25 Atlantic tropical cyclones from the 2015 and 2016 hurricane seasons. Forecasts are analyzed by considering all tropical cyclones as a group and classifying them into strong/weak storm vortices based on their initial model intensity. Metrics such as track error, intensity error, minimum central pressure error, and storm size are used to assess the data impact from the addition of the three new AMV types. Positive impact is obtained for these metrics, indicating that assimilating SWIR-, CAWV-, and VIS-type AMVs are beneficial for tropical cyclone forecasting. Given the results presented here, the new AMV types were accepted into NOAA/NCEP?s operational HWRF for the 2017 hurricane season.
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contributor author | Lim, Agnes H. N. | |
contributor author | Jung, James A. | |
contributor author | Nebuda, Sharon E. | |
contributor author | Daniels, Jaime M. | |
contributor author | Bresky, Wayne | |
contributor author | Tong, Mingjing | |
contributor author | Tallapragada, Vijay | |
date accessioned | 2019-09-22T09:02:49Z | |
date available | 2019-09-22T09:02:49Z | |
date copyright | 1/8/2019 12:00:00 AM | |
date issued | 2019 | |
identifier other | WAF-D-18-0072.1.pdf | |
identifier uri | http://yetl.yabesh.ir/yetl1/handle/yetl/4262474 | |
description abstract | The assimilation of atmospheric motion vectors (AMVs) provides important wind information to conventional data-lacking oceanic regions, where tropical cyclones spend most of their lifetimes. Three new AMV types, shortwave infrared (SWIR), clear-air water vapor (CAWV), and visible (VIS), are produced hourly by NOAA/NESDIS and are assimilated in operational NWP systems. The new AMV data types are added to the hourly infrared (IR) and cloud-top water vapor (CTWV) AMV data in the 2016 operational version of the HWRF Model. In this study, we update existing quality control (QC) procedures and add new procedures specific to tropical cyclone assimilation. We assess the impact of the three new AMV types on tropical cyclone forecasts by conducting assimilation experiments for 25 Atlantic tropical cyclones from the 2015 and 2016 hurricane seasons. Forecasts are analyzed by considering all tropical cyclones as a group and classifying them into strong/weak storm vortices based on their initial model intensity. Metrics such as track error, intensity error, minimum central pressure error, and storm size are used to assess the data impact from the addition of the three new AMV types. Positive impact is obtained for these metrics, indicating that assimilating SWIR-, CAWV-, and VIS-type AMVs are beneficial for tropical cyclone forecasting. Given the results presented here, the new AMV types were accepted into NOAA/NCEP?s operational HWRF for the 2017 hurricane season. | |
publisher | American Meteorological Society | |
title | Tropical Cyclone Forecasts Impact Assessment from the Assimilation of Hourly Visible, Shortwave, and Clear-Air Water Vapor Atmospheric Motion Vectors in HWRF | |
type | Journal Paper | |
journal volume | 34 | |
journal issue | 1 | |
journal title | Weather and Forecasting | |
identifier doi | 10.1175/WAF-D-18-0072.1 | |
journal fristpage | 177 | |
journal lastpage | 198 | |
tree | Weather and Forecasting:;2019:;volume 034:;issue 001 | |
contenttype | Fulltext |