Optimal Climate Normals for North Atlantic Hurricane Activity

2021 ◽  
Author(s):  
Carl J. Schreck ◽  
Philip J. Klotzbach ◽  
Michael M. Bell
Keyword(s):  
North Atlantic ◽  
Atlantic Hurricane ◽  
Hurricane Activity

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 Remote subsurface ocean temperature as a predictor of Atlantic hurricane activity

2018 ◽  
Vol 115 (45) ◽  
pp. 11460-11464 ◽  
Author(s):  
Enrico Scoccimarro ◽  
Alessio Bellucci ◽  
Andrea Storto ◽  
Silvio Gualdi ◽  
Simona Masina ◽  
...  
Keyword(s):  
Atlantic Ocean ◽  
North Atlantic ◽  
Wind Shear ◽  
Heat Content ◽  
Global Ocean ◽  
Trade Wind ◽  
Upper Ocean ◽  
Ocean Temperature ◽  
Atlantic Hurricane ◽  
Hurricane Activity

Predicting North Atlantic hurricane activity months in advance is of great potential societal significance. The ocean temperature, both in terms of North Atlantic/tropical averages and upper ocean heat content, is demonstrated to be a significant predictor. To investigate the relationship between the thermal state of the Atlantic Ocean and the tropical cyclone (TC) activity in terms of accumulated cyclone energy (ACE), we use observed 1980–2015 TC records and a 1/4° resolution global ocean reanalysis. This paper highlights the nonlocal effect associated with eastern Atlantic Ocean temperature, via a reduction of wind shear, and provides additional predictive skill of TC activity, when considering subsurface temperature instead of sea surface temperature (SST) only. The most active TC seasons occur for lower than normal wind shear conditions over the main development region, which is also driven by reduced trade wind strength. A significant step toward operationally reliable TC activity predictions is gained after including upper ocean mean temperatures over the eastern Atlantic domain. Remote effects are found to provide potential skill of ACE up to 3 months in advance. These results indicate that consideration of the upper 40-m ocean average temperature improves upon a prediction of September Atlantic hurricane activity using only SST.

scholarly journals How Skillful are the Multiannual Forecasts of Atlantic Hurricane Activity?

2018 ◽  
Vol 99 (2) ◽  
pp. 403-413 ◽  
Author(s):  
Louis-Philippe Caron ◽  
Leon Hermanson ◽  
Alison Dobbin ◽  
Jara Imbers ◽  
Llorenç Lledó ◽  
...  
Keyword(s):  
North Atlantic ◽  
Climate Models ◽  
Atlantic Hurricane ◽  
Current State ◽  
Recent Emergence ◽  
Hurricane Activity ◽  
Near Term ◽  
Art Research ◽  
Deterministic And Probabilistic Approaches ◽  
Forecasting Techniques

Abstract The recent emergence of near-term climate prediction, wherein climate models are initialized with the contemporaneous state of the Earth system and integrated up to 10 years into the future, has prompted the development of three different multiannual forecasting techniques of North Atlantic hurricane frequency. Descriptions of these three different approaches, as well as their respective skill, are available in the peer-reviewed literature, but because these various studies are sufficiently different in their details (e.g., period covered, metric used to compute the skill, measure of hurricane activity), it is nearly impossible to compare them. Using the latest decadal reforecasts currently available, we present a direct comparison of these three multiannual forecasting techniques with a combination of simple statistical models, with the hope of offering a perspective on the current state-of-the-art research in this field and the skill level currently reached by these forecasts. Using both deterministic and probabilistic approaches, we show that these forecast systems have a significant level of skill and can improve on simple alternatives, such as climatological and persistence forecasts.

Multi-year prediction model of North Atlantic hurricane activity

1998 ◽  
Vol 68 (1-2) ◽  
pp. 43-51 ◽  
Author(s):  
J. B. Elsner ◽  
X. Niu ◽  
A. A. Tsonis
Keyword(s):  
Prediction Model ◽  
North Atlantic ◽  
Atlantic Hurricane ◽  
Hurricane Activity
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