An Experimental 1-km Warn-on-Forecast System for Hazardous Weather Events

Wang, Yaping; Yussouf, Nusrat; Kerr, Christopher A.; Stratman, Derek R.; Matilla, Brian C.

doi:10.1175/MWR-D-22-0094.1

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i

An Experimental 1-km Warn-on-Forecast System for Hazardous Weather Events

2022
By Wang, Yaping ; Yussouf, Nusrat ; Kerr, Christopher A. ; ...

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Journal Title:

Monthly Weather Review
Personal Author:

Wang, Yaping ; Yussouf, Nusrat ; Kerr, Christopher A. ; Stratman, Derek R. ; Matilla, Brian C.

Wang, Yaping ; Yussouf, Nusrat ; Kerr, Christopher A. ; Stratman, Derek R. ; Matilla, Brian C. Less -
NOAA Program & Office:

OAR (Oceanic and Atmospheric Research) ; NSSL (National Severe Storms Laboratory) ; CIWRO (Cooperative Institute for Severe and High-Impact Weather Research and Operations)

OAR (Oceanic and Atmospheric Research) ; NSSL (National Severe Storms Laboratory) ; CIWRO (Cooperative Institute for Severe and High-Impact Weather Research and Operations) Less -
Description:

An experimental Warn-on-Forecast (WoF) ensemble data assimilation (DA) and prediction system at 1-km grid spacing is developed and tested using two landfalling tropical cyclone (TC) events, one springtime severe thunderstorm event, and one summertime flash flood event. To evaluate the impact of DA at 1-km grid spacing, two experiments are conducted. One experiment, namely the WoFS-1km, generates 3-h ensemble forecasts from the 1-km WoFS analyses while another experiment, namely the Downscaled-1km, generates 3-h ensemble forecasts from downscaled 3-km analyses. With 1-km DA, the two landfalling TC events and the summertime event show some improvement in predicting high reflectivity, while the springtime event performs worse. Meanwhile, WoFS-1km is slightly better at predicting heavier precipitation (>20 mm h−1) with lower bias. However, heavy precipitation spatial placement error is only mitigated in one TC event and the summertime event with 1-km DA but is neutral or worse in the other two events. Object-based verification for rotation objects indicates that WoFS-1km performs better in one of the TC events, but worse in the springtime event with lower probability of detection and higher false alarm ratio due to fewer strong rotation objects being generated. The forecast skill of WoFS-1km for the springtime event is degraded mainly because the convective cores do not sufficiently develop as the forecast advances. The conditional benefits from 1-km DA in this study highlights the need for evaluation of a larger sample of convective storm cases and further development of the system.
Keywords:

[+]

Cyclones Floods Thunderstorms Weather Forecasting Data Assimilation (DA) Tropical Cyclone (TC) Warn-on-Forecast (WoF)
DOI:

https://doi.org/10.1175/MWR-D-22-0094.1
Document Type:

Journal Article
Funding:

Grant no. NA11OAR4320072
Rights Information:

Accepted Manuscript
Compliance:

Submitted
Main Document Checksum:

[+]

urn:sha256:e1fe9966bc566b28865cae1c5df8329038f3d80cd290bf65fe1d48926f45dd09
Download URL:

https://repository.library.noaa.gov/view/noaa/46614/noaa_46614_DS1.pdf
File Type:

[PDF-9.20 MB]