Evaluation of long-term trends in tropical cyclone intensity forecasts |
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| Authors: | M DeMaria J A Knaff C Sampson |
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| Institution: | (1) NOAA/NESDIS, Fort Collins, CO, USA;(2) CIRA/Colorado State University, Fort Collins, CO, USA;(3) Naval Research Laboratory, Monterey, CA, USA |
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| Abstract: | Summary The National Hurricane Center and Joint Typhoon Warning Center operational tropical cyclone intensity forecasts for the three
major northern hemisphere tropical cyclone basins (Atlantic, eastern North Pacific, and western North Pacific) for the past
two decades are examined for long-term trends. Results show that there has been some marginal improvement in the mean absolute
error at 24 and 48 h for the Atlantic and at 72 h for the east and west Pacific. A new metric that measures the percent variance
of the observed intensity changes that is reduced by the forecast (variance reduction, VR) is defined to help account for
inter-annual variability in forecast difficulty. Results show that there have been significant improvements in the VR of the
official forecasts in the Atlantic, and some marginal improvement in the other two basins. The VR of the intensity guidance
models was also examined. The improvement in the VR is due to the implementation of advanced statistical intensity prediction
models and the operational version of the GFDL hurricane model in the mid-1990s. The skill of the operational intensity forecasts
for the 5-year period ending in 2005 was determined by comparing the errors to those from simple statistical models with input
from climatology and persistence. The intensity forecasts had significant skill out to 96 h in the Atlantic and out to 72 h
in the east and west Pacific. The intensity forecasts are also compared to the operational track forecasts. The skill was
comparable at 12 h, but the track forecasts were 2 to 5 times more skillful by 72 h. The track and intensity forecast error
trends for the two-decade period were also compared. Results showed that the percentage track forecast improvement was almost
an order of magnitude larger than that for intensity, indicating that intensity forecasting still has much room for improvement. |
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