A spatial climatology of North Atlantic hurricane intensity change

2013 ◽  
Vol 34 (9) ◽  
pp. 2918-2924 ◽  
Author(s):  
Erik Fraza ◽  
James B. Elsner
Keyword(s):  
North Atlantic ◽  
Intensity Change ◽  
Hurricane Intensity ◽  
Atlantic Hurricane

scholarly journals Natural and Forced North Atlantic Hurricane Potential Intensity Change in CMIP5 Models*

2015 ◽  
Vol 28 (10) ◽  
pp. 3926-3942 ◽  
Author(s):  
Mingfang Ting ◽  
Suzana J. Camargo ◽  
Cuihua Li ◽  
Yochanan Kushnir
Keyword(s):  
North Atlantic ◽  
Large Scale ◽  
First Century ◽  
Intensity Change ◽  
Cmip5 Models ◽  
Historical Period ◽  
Hurricane Intensity ◽  
Multidecadal Variability ◽  
Atlantic Hurricane ◽  
Twenty First Century

Abstract Possible future changes of North Atlantic hurricane intensity and the attribution of past hurricane intensity changes in the historical period are investigated using phase 5 of the Climate Model Intercomparison Project (CMIP5), multimodel, multiensemble simulations. For this purpose, the potential intensity (PI), the theoretical upper limit of the tropical cyclone intensity given the large-scale environment, is used. The CMIP5 models indicate that the PI change as a function of sea surface temperature (SST) variations associated with the Atlantic multidecadal variability (AMV) is more effective than that associated with climate change. Thus, relatively small changes in SST due to natural multidecadal variability can lead to large changes in PI, and the model-simulated multidecadal PI change during the historical period has been largely dominated by AMV. That said, the multimodel mean PI for the Atlantic main development region shows a significant increase toward the end of the twenty-first century under both the RCP4.5 and RCP8.5 emission scenarios. This is because of enhanced surface warming, which would place the North Atlantic PI largely above the historical mean by the mid-twenty-first century, based on CMIP5 model projection. The authors further attribute the historical PI changes to aerosols and greenhouse gas (GHG) forcing using CMIP5 historical single-forcing simulations. The model simulations indicate that aerosol forcing has been more effective in causing PI changes than the corresponding GHG forcing; the decrease in PI due to aerosols and increase due to GHG largely cancel each other. Thus, PI increases in the recent 30 years appears to be dominated by multidecadal natural variability associated with the positive phase of the AMV.

scholarly journals The 2016 North Atlantic hurricane season: A season of extremes

2017 ◽  
Vol 44 (10) ◽  
pp. 5071-5077 ◽  
Author(s):  
Jennifer M. Collins ◽  
David R. Roache
Keyword(s):  
North Atlantic ◽  
Atlantic Hurricane ◽  
Hurricane Season

scholarly journals Climatology and Interannual Variability of North Atlantic Hurricane Tracks

2005 ◽  
Vol 18 (24) ◽  
pp. 5370-5381 ◽  
Author(s):  
Lian Xie ◽  
Tingzhuang Yan ◽  
Leonard J. Pietrafesa ◽  
John M. Morrison ◽  
Thomas Karl
Keyword(s):  
North Atlantic ◽  
The United States ◽  
Track Density ◽  
Spatial And Temporal Variability ◽  
Tropical Atlantic ◽  
Atlantic Hurricane ◽  
The North ◽  
Hurricane Track ◽  
The North Atlantic ◽  
Hurricane Tracks

Abstract The spatial and temporal variability of North Atlantic hurricane tracks and its possible association with the annual hurricane landfall frequency along the U.S. East Coast are studied using principal component analysis (PCA) of hurricane track density function (HTDF). The results show that, in addition to the well-documented effects of the El Niño–Southern Oscillation (ENSO) and vertical wind shear (VWS), North Atlantic HTDF is strongly modulated by the dipole mode (DM) of Atlantic sea surface temperature (SST) as well as the North Atlantic Oscillation (NAO) and Arctic Oscillation (AO). Specifically, it was found that Atlantic SST DM is the only index that is associated with all top three empirical orthogonal function (EOF) modes of the Atlantic HTDF. ENSO and tropical Atlantic VWS are significantly correlated with the first and the third EOF of the HTDF over the North Atlantic Ocean. The second EOF of North Atlantic HTDF, which represents the “zonal gradient” of North Atlantic hurricane track density, showed no significant correlation with ENSO or with tropical Atlantic VWS. Instead, it is associated with the Atlantic SST DM, and extratropical processes including NAO and AO. Since for a given hurricane season, the preferred hurricane track pattern, together with the overall basinwide hurricane activity, collectively determines the hurricane landfall frequency, the results provide a foundation for the construction of a statistical model that projects the annual number of hurricanes striking the eastern seaboard of the United States.

scholarly journals Normalized Convective Characteristics of Tropical Cyclone Rapid Intensification Events in the North Atlantic and Eastern North Pacific

2018 ◽  
Vol 146 (4) ◽  
pp. 1133-1155 ◽  
Author(s):  
Michael S. Fischer ◽  
Brian H. Tang ◽  
Kristen L. Corbosiero ◽  
Christopher M. Rozoff
Keyword(s):  
Tropical Cyclone ◽  
North Atlantic ◽  
North Pacific ◽  
Forecast Skill ◽  
Passive Microwave ◽  
Intensity Change ◽  
Rapid Intensification ◽  
Brightness Temperatures ◽  
The North ◽  
The North Atlantic

The relationship between tropical cyclone (TC) convective characteristics and TC intensity change is explored using infrared and passive microwave satellite imagery of TCs in the North Atlantic and eastern North Pacific basins from 1989 to 2016. TC intensity change episodes were placed into one of four groups: rapid intensification (RI), slow intensification (SI), neutral (N), and weakening (W). To account for differences in the distributions of TC intensity among the intensity change groups, a normalization technique is introduced, which allows for the analysis of anomalous TC convective characteristics and their relationship to TC intensity change. A composite analysis of normalized convective parameters shows anomalously cold infrared and 85-GHz brightness temperatures, as well as anomalously warm 37-GHz brightness temperatures, in the upshear quadrants of the TC are associated with increased rates of TC intensification, including RI. For RI episodes in the North Atlantic basin, an increase in anomalous liquid hydrometeor content precedes anomalous ice hydrometeor content by approximately 12 h, suggesting convection deep enough to produce robust ice scattering is a symptom of, rather than a precursor to, RI. In the eastern North Pacific basin, the amount of anomalous liquid and ice hydrometeors increases in tandem near the onset of RI. Normalized infrared and passive microwave brightness temperatures can be utilized to skillfully predict episodes of RI, as the forecast skill of RI episodes using solely normalized convective parameters is comparable to the forecast skill of RI episodes by current operational statistical models.

Improving Multiseason Forecasts of North Atlantic Hurricane Activity

2008 ◽  
Vol 21 (6) ◽  
pp. 1209-1219 ◽  
Author(s):  
James B. Elsner ◽  
Thomas H. Jagger ◽  
Michael Dickinson ◽  
Dail Rowe
Keyword(s):  
North Atlantic ◽  
Monte Carlo Sampling ◽  
Sea Surface ◽  
Economic Losses ◽  
Atlantic Hurricane ◽  
Time Period ◽  
Hurricane Season ◽  
Hurricane Activity ◽  
Term Management

Abstract Hurricanes cause drastic social problems as well as generate huge economic losses. A reliable forecast of the level of hurricane activity covering the next several seasons has the potential to mitigate against such losses through improvements in preparedness and insurance mechanisms. Here a statistical algorithm is developed to predict North Atlantic hurricane activity out to 5 yr. The algorithm has two components: a time series model to forecast average hurricane-season Atlantic sea surface temperature (SST), and a regression model to forecast the hurricane rate given the predicted SST value. The algorithm uses Monte Carlo sampling to generate distributions for the predicted SST and model coefficients. For a given forecast year, a predicted hurricane count is conditional on a sampled predicted value of Atlantic SST. Thus forecasts are samples of hurricane counts for each future year. Model skill is evaluated over the period 1997–2005 and compared against climatology, persistence, and other multiseasonal forecasts issued during this time period. Results indicate that the algorithm will likely improve on earlier efforts and perhaps carry enough skill to be useful in the long-term management of hurricane risk.

Statistical–Dynamical Predictions of Seasonal North Atlantic Hurricane Activity

2011 ◽  
Vol 139 (4) ◽  
pp. 1070-1082 ◽  
Author(s):  
Gabriel A. Vecchi ◽  
Ming Zhao ◽  
Hui Wang ◽  
Gabriele Villarini ◽  
Anthony Rosati ◽  
...  
Keyword(s):  
High Resolution ◽  
North Atlantic ◽  
Climate Model ◽  
Global Climate ◽  
Global Climate Model ◽  
Atlantic Hurricane ◽  
Uncertainty Estimates ◽  
Hurricane Season ◽  
Hurricane Activity ◽  
Hurricane Forecasting

Abstract Skillfully predicting North Atlantic hurricane activity months in advance is of potential societal significance and a useful test of our understanding of the factors controlling hurricane activity. In this paper, a statistical–dynamical hurricane forecasting system, based on a statistical hurricane model, with explicit uncertainty estimates, and built from a suite of high-resolution global atmospheric dynamical model integrations spanning a broad range of climate states is described. The statistical model uses two climate predictors: the sea surface temperature (SST) in the tropical North Atlantic and SST averaged over the global tropics. The choice of predictors is motivated by physical considerations, as well as the results of high-resolution hurricane modeling and statistical modeling of the observed record. The statistical hurricane model is applied to a suite of initialized dynamical global climate model forecasts of SST to predict North Atlantic hurricane frequency, which peaks during the August–October season, from different starting dates. Retrospective forecasts of the 1982–2009 period indicate that skillful predictions can be made from as early as November of the previous year; that is, skillful forecasts for the coming North Atlantic hurricane season could be made as the current one is closing. Based on forecasts initialized between November 2009 and March 2010, the model system predicts that the upcoming 2010 North Atlantic hurricane season will likely be more active than the 1982–2009 climatology, with the forecasts initialized in March 2010 predicting an expected hurricane count of eight and a 50% probability of counts between six (the 1966–2009 median) and nine.

scholarly journals Reconstructing 7000 years of North Atlantic hurricane variability using deep-sea sediment cores from the western Great Bahama Bank

2013 ◽  
Vol 28 (1) ◽  
pp. 31-41 ◽  
Author(s):  
Michael R. Toomey ◽  
William B. Curry ◽  
Jeffrey P. Donnelly ◽  
Peter J. van Hengstum
Keyword(s):  
North Atlantic ◽  
Deep Sea ◽  
Sediment Cores ◽  
Deep Sea Sediment ◽  
Great Bahama Bank ◽  
Atlantic Hurricane
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