Search Results

You are looking at 11 - 14 of 14 items for :

  • Author or Editor: James B. Elsner x
  • Journal of Climate x
  • Refine by Access: Content accessible to me x
Clear All Modify Search
James B. Elsner
,
Kam-biu Liu
, and
Bethany Kocher

Abstract

The authors provide a statistical and physical basis for understanding regional variations in major hurricane activity along the U.S. coastline on long timescales. Current statistical models of hurricane activity are focused on the frequency of events over the entire North Atlantic basin. The exception is the lead author’s previous work, which models the occurrence of hurricanes over the Caribbean Sea, Gulf of Mexico, and the southeast U.S. coast separately. Here the authors use statistics to analyze data from historical and paleoclimatic records to expand this work. In particular, an inverse correlation in major hurricane activity across latitudes at various timescales is articulated. When activity is above normal at high latitudes it tends to be below normal at low latitudes and vice versa. Past research, paleoclimatic records, and historical data hint at the potential of using the North Atlantic oscillation (NAO) as an indicator of where storms will likely track over long timescales. An excited (relaxed) NAO is associated with higher (lower) latitude recurving (nonrecurving) storms. The Gulf (East) Coast is more susceptible to a major hurricane strike during a relaxed (excited) NAO.

Full access
Se-Hwan Yang
,
Nam-Young Kang
,
James B. Elsner
, and
Youngsin Chun

Abstract

The climate of 2015 was characterized by a strong El Niño, global warmth, and record-setting tropical cyclone (TC) intensity for western North Pacific typhoons. In this study, the highest TC intensity in 32 years (1984–2015) is shown to be a consequence of above normal TC activity—following natural internal variation—and greater efficiency of intensity. The efficiency of intensity (EINT) is termed the “blasting” effect and refers to typhoon intensification at the expense of occurrence. Statistical models show that the EINT is mostly due to the anomalous warmth in the environment indicated by global mean sea surface temperature. In comparison, the EINT due to El Niño is negligible. This implies that the record-setting intensity of 2015 might not have occurred without environmental warming and suggests that a year with even greater TC intensity is possible in the near future when above normal activity coincides with another record EINT due to continued multidecadal warming.

Open access
Sarah Strazzo
,
James B. Elsner
,
Timothy LaRow
,
Daniel J. Halperin
, and
Ming Zhao

Abstract

Of broad scientific and public interest is the reliability of global climate models (GCMs) to simulate future regional and local tropical cyclone (TC) occurrences. Atmospheric GCMs are now able to generate vortices resembling actual TCs, but questions remain about their fidelity to observed TCs. Here the authors demonstrate a spatial lattice approach for comparing actual with simulated TC occurrences regionally using observed TCs from the International Best Track Archive for Climate Stewardship (IBTrACS) dataset and GCM-generated TCs from the Geophysical Fluid Dynamics Laboratory (GFDL) High Resolution Atmospheric Model (HiRAM) and Florida State University (FSU) Center for Ocean–Atmospheric Prediction Studies (COAPS) model over the common period 1982–2008. Results show that the spatial distribution of TCs generated by the GFDL model compares well with observations globally, although there are areas of over- and underprediction, particularly in parts of the Pacific Ocean. Difference maps using the spatial lattice highlight these discrepancies. Additionally, comparisons focusing on the North Atlantic Ocean basin are made. Results confirm a large area of overprediction by the FSU COAPS model in the south-central portion of the basin. Relevant to projections of future U.S. hurricane activity is the fact that both models underpredict TC activity in the Gulf of Mexico.

Full access
James B. Elsner
,
Sarah E. Strazzo
,
Thomas H. Jagger
,
Timothy LaRow
, and
Ming Zhao

Abstract

A statistical model for the intensity of the strongest hurricanes has been developed and a new methodology introduced for estimating the sensitivity of the strongest hurricanes to changes in sea surface temperature. Here, the authors use this methodology on observed hurricanes and hurricanes generated from two global climate models (GCMs). Hurricanes over the North Atlantic Ocean during the period 1981–2010 show a sensitivity of 7.9 ± 1.19 m s−1 K−1 (standard error; SE) when over seas warmer than 25°C. In contrast, hurricanes over the same region and period generated from the GFDL High Resolution Atmospheric Model (HiRAM) show a significantly lower sensitivity with the highest at 1.8 ± 0.42 m s−1 K−1 (SE). Similar weaker sensitivity is found using hurricanes generated from the Florida State University Center for Ocean–Atmospheric Prediction Studies (FSU-COAPS) model with the highest at 2.9 ± 2.64 m s−1 K−1 (SE). A statistical refinement of HiRAM-generated hurricane intensities heightens the sensitivity to a maximum of 6.9 ± 3.33 m s−1 K−1 (SE), but the increase is offset by additional uncertainty associated with the refinement. Results suggest that the caution that should be exercised when interpreting GCM scenarios of future hurricane intensity stems from the low sensitivity of limiting GCM-generated hurricane intensity to ocean temperature.

Full access