On the growth of intensity forecast errors in the operational hurricane weather research and forecasting (HWRF) model

Kieu, Chanh; Keshavamurthy, Kushal; Tallapragada, Vijay; Gopalakrishnan, Sundararaman; Trahan, Samuel

doi:10.1002/qj.3344

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On the growth of intensity forecast errors in the operational hurricane weather research and forecasting (HWRF) model

2018
By Kieu, Chanh ; Keshavamurthy, Kushal ; Tallapragada, Vijay ; ...
Source: Quarterly Journal of the Royal Meteorological Society, 144(715)

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This study examines the growth of tropical cyclone (TC) intensity forecast errors and related intensity predictability for the NOAA operational Hurricane Weather Research and Forecasting (HWRF) model. Using operational intensity forecasts during the 2012 to 2016 seasons, two conditions for a limited range of TC intensity predictability are demonstrated, which include (a) the existence of an intensity error saturation limit, and (b) the dependence of the intensity error growth rate on storm intensity during TC development. By stratifying intensity errors based on different initial intensity bins, it is shown that TC intensity error growth rate is relatively small (approximate to 0.3kth(-1)) at the early stage of TC development, but it quickly increases to approximate to 1kth(-1) during TC intensification. Of further importance is that the intensity error saturation varies in the range of 14-18kt in different ocean basins, thus suggesting the potential dependence of the intensity predictability on large-scale environment. Additional idealized experiments with the HWRF model confirm the saturation of intensity errors, even under a perfect model scenario. The existence of the intensity error saturation together with the finding of a faster error growth rate for higher intensity suggests that the TC dynamics possesses an inherent limited predictability, which prevents us from reducing the intensity errors in TC dynamical models below a certain threshold.
Journal Title:

Quarterly Journal of the Royal Meteorological Society
Personal Author:

Kieu, Chanh ; Keshavamurthy, Kushal ; Tallapragada, Vijay ; Gopalakrishnan, Sundararaman ; Trahan, Samuel

Kieu, Chanh ; Keshavamurthy, Kushal ; Tallapragada, Vijay ; Gopalakrishnan, Sundararaman ; Trahan, Samuel Less -
NOAA Program & Office:

NWS (National Weather Service) ; NCEP (National Centers for Environmental Prediction) ; OST (Office of Science and Technology) ; EMC (Environmental Modelling Center) ; OAR (Oceanic and Atmospheric Research) ; ... More +

NWS (National Weather Service) ; NCEP (National Centers for Environmental Prediction) ; OST (Office of Science and Technology) ; EMC (Environmental Modelling Center) ; OAR (Oceanic and Atmospheric Research) ; AOML (Atlantic Oceanographic and Meteorological Laboratory) Less -
Description:

This study examines the growth of tropical cyclone (TC) intensity forecast errors and related intensity predictability for the NOAA operational Hurricane Weather Research and Forecasting (HWRF) model. Using operational intensity forecasts during the 2012 to 2016 seasons, two conditions for a limited range of TC intensity predictability are demonstrated, which include (a) the existence of an intensity error saturation limit, and (b) the dependence of the intensity error growth rate on storm intensity during TC development. By stratifying intensity errors based on different initial intensity bins, it is shown that TC intensity error growth rate is relatively small (approximate to 0.3kth(-1)) at the early stage of TC development, but it quickly increases to approximate to 1kth(-1) during TC intensification. Of further importance is that the intensity error saturation varies in the range of 14-18kt in different ocean basins, thus suggesting the potential dependence of the intensity predictability on large-scale environment. Additional idealized experiments with the HWRF model confirm the saturation of intensity errors, even under a perfect model scenario. The existence of the intensity error saturation together with the finding of a faster error growth rate for higher intensity suggests that the TC dynamics possesses an inherent limited predictability, which prevents us from reducing the intensity errors in TC dynamical models below a certain threshold.
Keywords:

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Hurricane Intensity HWRF Model Intensity Error Growth Intensity Forecasting Practical Predictability Tropical Cyclones
Source:

Quarterly Journal of the Royal Meteorological Society, 144(715)
DOI:

https://doi.org/10.1002/qj.3344
Document Type:

Journal Article
Funding:

Grant no. NA16NWS4680026
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urn:sha256:0c0d349f9cc82fa70df0c4c3c2c444bdd3e67aca2f5d9b27d1a1bdcc9debc20b
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https://repository.library.noaa.gov/view/noaa/30008/noaa_30008_DS1.pdf
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On the growth of intensity forecast errors in the operational hurricane weather research and forecasting (HWRF) model

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