Comparison of Local and Basinwide Methods for Risk Assessment of Tropical Cyclone Landfall

2008 ◽  
Vol 47 (2) ◽  
pp. 361-367 ◽  
Author(s):  
Timothy M. Hall ◽  
Stephen Jewson

Abstract Two statistical methods for predicting the number of tropical cyclones (TCs) making landfall on sections of the North American coastline are compared. The first method—the “local model”—is derived exclusively from historical landfalls on the particular coastline section. The second method—the “track model”—involves statistical modeling of TC tracks from genesis to lysis, and is based on historical observations of such tracks. Identical scoring schemes are used for each model, derived from the out-of-sample likelihood of a Bayesian analysis of the Poisson landfall number distribution. The track model makes better landfall rate predictions on most coastal regions, when coastline sections at a scale of several hundred kilometers or smaller are considered. The reduction in sampling error due to the use of the much larger dataset more than offsets any bias in the track model. When larger coast sections are considered, there are more historical landfalls, and the local model scores better. This is the first clear justification for the use of track models for the assessment of TC landfall risk on regional and smaller scales.

2012 ◽  
Vol 27 (3) ◽  
pp. 757-769 ◽  
Author(s):  
James I. Belanger ◽  
Peter J. Webster ◽  
Judith A. Curry ◽  
Mark T. Jelinek

Abstract This analysis examines the predictability of several key forecasting parameters using the ECMWF Variable Ensemble Prediction System (VarEPS) for tropical cyclones (TCs) in the North Indian Ocean (NIO) including tropical cyclone genesis, pregenesis and postgenesis track and intensity projections, and regional outlooks of tropical cyclone activity for the Arabian Sea and the Bay of Bengal. Based on the evaluation period from 2007 to 2010, the VarEPS TC genesis forecasts demonstrate low false-alarm rates and moderate to high probabilities of detection for lead times of 1–7 days. In addition, VarEPS pregenesis track forecasts on average perform better than VarEPS postgenesis forecasts through 120 h and feature a total track error growth of 41 n mi day−1. VarEPS provides superior postgenesis track forecasts for lead times greater than 12 h compared to other models, including the Met Office global model (UKMET), the Navy Operational Global Atmospheric Prediction System (NOGAPS), and the Global Forecasting System (GFS), and slightly lower track errors than the Joint Typhoon Warning Center. This paper concludes with a discussion of how VarEPS can provide much of this extended predictability within a probabilistic framework for the region.


2018 ◽  
Vol 11 (1) ◽  
pp. 3-15 ◽  
Author(s):  
Matthew J. Widlansky ◽  
H. Annamalai ◽  
Stephen B. Gingerich ◽  
Curt D. Storlazzi ◽  
John J. Marra ◽  
...  

Abstract Potential changing climate threats in the tropical and subtropical North Pacific Ocean were assessed, using coupled ocean–atmosphere and atmosphere-only general circulation models, to explore their response to projected increasing greenhouse gas emissions. Tropical cyclone occurrence, described by frequency and intensity, near islands housing major U.S. defense installations was the primary focus. Four island regions—Guam and Kwajalein Atoll in the tropical northwestern Pacific, Okinawa in the subtropical northwestern Pacific, and Oahu in the tropical north-central Pacific—were considered, as they provide unique climate and geographical characteristics that either enhance or reduce the tropical cyclone risk. Guam experiences the most frequent and severe tropical cyclones, which often originate as weak systems close to the equator near Kwajalein and sometimes track far enough north to affect Okinawa, whereas intense storms are the least frequent around Oahu. From assessments of models that simulate well the tropical Pacific climate, it was determined that, with a projected warming climate, the number of tropical cyclones is likely to decrease for Guam and Kwajalein but remain about the same near Okinawa and Oahu; however, the maximum intensity of the strongest storms may increase in most regions. The likelihood of fewer but stronger storms will necessitate new localized assessments of the risk and vulnerabilities to tropical cyclones in the North Pacific.


2019 ◽  
Vol 34 (5) ◽  
pp. 1239-1255 ◽  
Author(s):  
Dan L. Bergman ◽  
Linus Magnusson ◽  
Johan Nilsson ◽  
Frederic Vitart

Abstract A method has been developed to forecast seasonal landfall risk using ensembles of cyclone tracks generated by ECMWF’s seasonal forecast system 4. The method has been applied to analyze and retrospectively forecast the landfall risk along the North American coast. The main result is that the method can be used to forecast landfall for some parts of the coast, but the skill is lower than for basinwide forecasts of activity. The rank correlations between forecasts issued on 1 May and observations are 0.6 for basinwide tropical cyclone number and 0.5 for landfall anywhere along the coast. When the forecast period is limited to the peak of the hurricane season, the landfall correlation increases to 0.6. Moreover, when the forecast issue date is pushed forward to 1 August, basinwide tropical cyclone and hurricane correlations increase to 0.7 and 0.8, respectively, whereas landfall correlations improve less. The quality of the forecasts is in line with that obtained by others.


2020 ◽  
Vol 117 (20) ◽  
pp. 10706-10714 ◽  
Author(s):  
Hiroyuki Murakami ◽  
Thomas L. Delworth ◽  
William F. Cooke ◽  
Ming Zhao ◽  
Baoqiang Xiang ◽  
...  

Owing to the limited length of observed tropical cyclone data and the effects of multidecadal internal variability, it has been a challenge to detect trends in tropical cyclone activity on a global scale. However, there is a distinct spatial pattern of the trends in tropical cyclone frequency of occurrence on a global scale since 1980, with substantial decreases in the southern Indian Ocean and western North Pacific and increases in the North Atlantic and central Pacific. Here, using a suite of high-resolution dynamical model experiments, we show that the observed spatial pattern of trends is very unlikely to be explained entirely by underlying multidecadal internal variability; rather, external forcing such as greenhouse gases, aerosols, and volcanic eruptions likely played an important role. This study demonstrates that a climatic change in terms of the global spatial distribution of tropical cyclones has already emerged in observations and may in part be attributable to the increase in greenhouse gas emissions.


2014 ◽  
Vol 27 (23) ◽  
pp. 8674-8685 ◽  
Author(s):  
Michael Chenoweth

Abstract A comprehensive new compilation of North Atlantic tropical cyclone activity for the years 1851–98 is presented and compared with the second-generation North Atlantic hurricane database (HURDAT2) for the same years. This new analysis is based on the retrieval of 9072 newspaper marine shipping news reports, 1260 original logbook records, 271 Maury abstract logs, 147 U.S. marine meteorological journals, and 34 Met Office (UKMO) logbooks. Records from throughout North America and the Caribbean region were used along with other primary and secondary references holding unique land and marine data. For the first time, North Atlantic daily weather maps for 1864/65, 1873, and 1881–98 were used in historical tropical cyclone research. Results for the years 1851–98 include the omission of 62 of the 361 HURDAT2 storms, and the further reduction resulting from the merging of storms to a total of 288 unique HURDAT2 tropical cyclones. The new compilation gave a total of 497 tropical cyclones in the 48-yr record, or an average of 10.4 storms per year compared to 6.0 per year in HURDAT2 less the author’s omissions. Of this total, 209 storms are completely new. A total of 90 hurricanes made landfall in the United States during this time. Seven new U.S. landfalling hurricanes are present in the new dataset but not in HURDAT2. Eight U.S. landfalling hurricanes in HURDAT2 are now considered to have only tropical storm impact or were actually extratropical at landfall. Across the North Atlantic, the number of category-4 hurricanes based on the Saffir–Simpson hurricane wind scale, compared with HURDAT2, increased from 11 to 25, 6 of which made U.S. landfall at category-4 level.


2012 ◽  
Vol 140 (3) ◽  
pp. 774-788 ◽  
Author(s):  
Carl J. Schreck ◽  
John Molinari ◽  
Anantha Aiyyer

Abstract This study investigates the number of tropical cyclone formations that can be attributed to the enhanced convection from equatorial waves within each basin. Tropical depression (TD)-type disturbances (i.e., easterly waves) were the primary tropical cyclone precursors over the Northern Hemisphere basins, particularly the eastern North Pacific and the Atlantic. In the Southern Hemisphere, however, the number of storms attributed to TD-type disturbances and equatorial Rossby waves were roughly equivalent. Equatorward of 20°N, tropical cyclones formed without any equatorial wave precursor most often over the eastern North Pacific and least often over the western North Pacific. The Madden–Julian oscillation (MJO) was an important tropical cyclone precursor over the north Indian, south Indian, and western North Pacific basins. The MJO also affected tropical cyclogenesis by modulating the amplitudes of higher-frequency waves. Each wave type reached the attribution threshold 1.5 times more often, and tropical cyclogenesis was 3 times more likely, within positive MJO-filtered rainfall anomalies than within negative anomalies. The greatest MJO modulation was observed for storms attributed to Kelvin waves over the north Indian Ocean. The large rainfall rates associated with tropical cyclones can alter equatorial wave–filtered anomalies. This study quantifies the contamination over each basin. Tropical cyclones contributed more than 20% of the filtered variance for each wave type over large potions of every basin except the South Pacific. The largest contamination, exceeding 60%, occurred for the TD band near the Philippines. To mitigate the contamination, the tropical cyclone–related anomalies were removed before filtering in this study.


2013 ◽  
Vol 26 (11) ◽  
pp. 3631-3643 ◽  
Author(s):  
Gabriele Villarini ◽  
Gabriel A. Vecchi

Abstract By considering the intensity, duration, and frequency of tropical cyclones, the power dissipation index (PDI) and accumulated cyclone energy (ACE) are concise metrics routinely used to assess tropical storm activity. This study focuses on the development of a hybrid statistical–dynamical seasonal forecasting system for the North Atlantic Ocean’s PDI and ACE over the period 1982–2011. The statistical model uses only tropical Atlantic and tropical mean sea surface temperatures (SSTs) to describe the variability exhibited by the observational record, reflecting the role of both local and nonlocal effects on the genesis and development of tropical cyclones in the North Atlantic basin. SSTs are predicted using a 10-member ensemble of the Geophysical Fluid Dynamics Laboratory Climate Model, version 2.1 (GFDL CM2.1), an experimental dynamical seasonal-to-interannual prediction system. To assess prediction skill, a set of retrospective predictions is initialized for each month from November to April, over the years 1981–2011. The skill assessment indicates that it is possible to make skillful predictions of ACE and PDI starting from November of the previous year: skillful predictions of the seasonally integrated North Atlantic tropical cyclone activity for the coming season could be made even while the current one is still under way. Probabilistic predictions for the 2012 North Atlantic tropical cyclone season are presented.


Science ◽  
2021 ◽  
Vol 371 (6528) ◽  
pp. 514-517 ◽  
Author(s):  
Shuai Wang ◽  
Ralf Toumi

Poleward migrations of tropical cyclones have been observed globally, but their impact on coastal areas remains unclear. We investigated the change in global tropical cyclone activity in coastal regions over the period 1982–2018. We found that the distance of tropical cyclone maximum intensity to land has decreased by about 30 kilometers per decade, and that the annual frequency of global tropical cyclones increases with proximity to land by about two additional cyclones per decade. Trend analysis reveals a robust migration of tropical cyclone activity toward coasts, concurrent with poleward migration of cyclone locations as well as a statistically significant westward shift. This zonal shift of tropical cyclone tracks may be mainly driven by global zonal changes in environmental steering flow.


2007 ◽  
Vol 135 (10) ◽  
pp. 3587-3598 ◽  
Author(s):  
William M. Frank ◽  
George S. Young

Abstract This paper examines the interannual variability of tropical cyclones in each of the earth’s cyclone basins using data from 1985 to 2003. The data are first analyzed using a Monte Carlo technique to investigate the long-standing myth that the global number of tropical cyclones is less variable than would be expected from examination of the variability in each basin. This belief is found to be false. Variations in the global number of all tropical cyclones are indistinguishable from those that would be expected if each basin was examined independently of the others. Furthermore, the global number of the most intense storms (Saffir–Simpson categories 4–5) is actually more variable than would be expected because of an observed tendency for storm activity to be correlated between basins, and this raises important questions as to how and why these correlations arise. Interbasin correlations and factor analysis of patterns of tropical cyclone activity reveal that there are several significant modes of variability. The largest three factors together explain about 70% of the variance, and each of these factors shows significant correlation with ENSO, the North Atlantic Oscillation (NAO), or both, with ENSO producing the largest effects. The results suggest that patterns of tropical cyclone variability are strongly affected by large-scale modes of interannual variability. The temporal and spatial variations in storm activity are quite different for weaker tropical cyclones (tropical storm through category 2 strength) than for stronger storms (categories 3–5). The stronger storms tend to show stronger interbasin correlations and stronger relationships to ENSO and the NAO than do the weaker storms. This suggests that the factors that control tropical cyclone formation differ in important ways from those that ultimately determine storm intensity.


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