Details:

Journal Title:
Atmosphere
Personal Author:
Torn, Ryan D. ; DeMaria, Mark
Torn, Ryan D. ; DeMaria, Mark Less -
NOAA Program & Office:
NWS (National Weather Service)
Description:
Although there has been substantial improvement to numerical weather prediction models, accurate predictions of tropical cyclone rapid intensification (RI) remain elusive. The processes that govern RI, such as convection, may be inherently less predictable; therefore a probabilistic approach should be adopted. Although there have been numerous studies that have evaluated probabilistic intensity (i.e., maximum wind speed) forecasts from high resolution models, or statistical RI predictions, there has not been a comprehensive analysis of high-resolution ensemble predictions of various intensity change thresholds. Here, ensemble-based probabilities of various intensity changes are computed from experimental Hurricane Weather Research and Forecasting (HWRF) and Hurricanes in a Multi-scale Ocean-coupled Non-hydrostatic (HMON) models that were run for select cases during the 2017–2019 seasons and verified against best track data. Both the HWRF and HMON ensemble systems simulate intensity changes consistent with RI (30 knots 24 h−1; 15.4 m s−1 24 h−1) less frequent than observed, do not provide reliable probabilistic predictions, and are less skillful probabilistic forecasts relative to the Statistical Hurricane Intensity Prediction System Rapid Intensification Index (SHIPS-RII) and Deterministic to Probabilistic Statistical (DTOPS) statistical-dynamical systems. This issue is partly alleviated by applying a quantile-based bias correction scheme that preferentially adjusts the model-based intensity change at the upper-end of intensity changes. While such an approach works well for high-resolution models, this bias correction strategy does not substantially improve ECMWF ensemble-based probabilistic predictions. By contrast, both the HWRF and HMON systems provide generally reliable predictions of intensity changes for cases where RI does not take place. Combining the members from the HWRF and HMON ensemble systems into a large multi-model ensemble does not improve upon HMON probablistic forecasts.
Keywords:
[+]
Atmospheric Science Environmental Science (miscellaneous)
Source:
Atmosphere, 12(3), 373
DOI:
https://doi.org/10.3390/atmos12030373
ISSN:
2073-4433
Format:
PDF
Publisher:
MDPI AG
Document Type:
Journal Article
Funding:
Grant no. NA16NWS4680025 ; Grant no. NA18NWS4680060
Grant no. NA16NWS4680025 ; Grant no. NA18NWS4680060 Less -
License:
https://creativecommons.org/licenses/by/4.0/
Rights Information:
CC BY
Compliance:
Library
Main Document Checksum:
[+]
urn:sha256:0c488e1cf9e0ca06330d3f73ce92e3486c4ca856cbdb6605781a002f51fe4700
Download URL:
https://repository.library.noaa.gov/view/noaa/58755/noaa_58755_DS1.pdf
File Type:

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