Tropical Cyclone Forecasts Impact Assessment from the Assimilation of Hourly Visible, Shortwave, and Clear-Air Water Vapor Atmospheric Motion Vectors in HWRF

Lim, Agnes H. N.; Jung, James A.; Nebuda, Sharon E.; Daniels, Jaime M.; Bresky, Wayne; Tong, Mingjing; Tallapragada, Vijay

doi:10.1175/WAF-D-18-0072.1

i

Tropical Cyclone Forecasts Impact Assessment from the Assimilation of Hourly Visible, Shortwave, and Clear-Air Water Vapor Atmospheric Motion Vectors in HWRF

2019
By Lim, Agnes H. N. ; Jung, James A. ; Nebuda, Sharon E. ; ...

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Journal Title:

Weather and Forecasting
Personal Author:

Lim, Agnes H. N. ; Jung, James A. ; Nebuda, Sharon E. ; Daniels, Jaime M. ; Bresky, Wayne ; Tong, Mingjing ; Tallapragada, Vijay
NOAA Program & Office:

CIMSS (Cooperative Institute for Meteorological Satellite Studies) ; NESDIS (National Environmental Satellite, Data, and Information Service) ; STAR (Center for Satellite Applications and Research) ; NWS (National Weather Service) ; NCEP (National Centers for Environmental Prediction)
Description:

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.
Keywords:

Cyclones Numerical Weather Forecasting Remote Sensing Numerical Weather Forecasting Remote Sensing
Source:

Wea. Forecasting (2019) 34 (1): 177–198
DOI:

https://doi.org/10.1175/WAF-D-18-0072.1
Document Type:

Journal Article
Funding:

Grant no. NA15NES4680010
Rights Information:

Other
Compliance:

Submitted
Main Document Checksum:

urn:sha256:71eb9de50a0d01e5df029ff2028cbc8d126dceb1c00a2c8e2de4f2ef6278a1da
Download URL:

https://repository.library.noaa.gov/view/noaa/27346/noaa_27346_DS1.pdf
File Type:

[PDF - 4.05 MB ]

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