Objective Tropical Cyclone Intensity Estimation from Satellite Images ...

of 45˚N. This subset comprised 2016 observations from 165 storms during 1988 – 2006. Several tests
are done to statistically justify the design of the algorithm using n-fold cross-validation. The resulting
averaged mean absolute error is 10.9 kt (50% of points are within 10 kt) or 8.4 mb (50% of points are
within 8 mb); its accuracy is on par with other objective techniques.
3 Conclusion and Future work
Further improvements of FASI are also possible. Given the global coverage of HURSAT, it is possible
that a training set could be constructed for the Western North Pacific during the period of aircraft
reconnaissance (1980-1987). Such an approach would be unique to FASI since other objective
algorithms mentioned here have been developed over the North Atlantic. This approach will also allow a
climatological application: a global estimate of TC activity based on FASI that could be validated in two
separate basins.
Temporal constraints on changes in intensity could also be applied to the algorithm in the future.
The FASI algorithm has no dependency upon time except that which is implied by the use of features
from previous satellite images (6, 12, and 24 hours prior). Other objective algorithms use temporal
constraints on intensity changes (e.g., the ADT and Subjective DT). Including similar constraints in FASI
would likely decrease some of the random error reported herein.
Another application of the FASI technique would be to include it in a satellite consensus
(SatCon) technique, which incorporates strengths and weaknesses of several objective estimates to
compute an intensity estimate that is better than the any of its individual parts [6]. The FASI technique
may well provide independent information for such an approach.
Finally, the FASI technique can be combined with an algorithm to detect the TC center of
circulation for full automation of the technique. But again, this would require some further analysis of the
center location algorithms performance using HURSAT data.
In short, the FASI technique provides a unique approach to estimate the intensity of tropical
cyclones. The error statistics of the technique are on par with other algorithms. This approach has the
potential to provide global TC intensity estimates that could augment intensity estimates made by other
objective techniques.
Acknowledgements This work was supported by the Expeditions in Computing Program of the
National Science Foundation under award CCF-1029731. Special thanks are given to Jim Kossin and
Carl Schreck who provided valuable insight during the development of this work. The opinions
expressed in this paper are those of the authors. They do not necessarily reflect the official views or
policies of NSF, NOAA, Department of Commerce, or the US Government.
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