How Skillful are the Multiannual Forecasts of Atlantic Hurricane Activity?

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.The first author would like to thank Isadora Jimenez for providing the necessary material for Fig. 2. The first author would like to acknowledge the financial support from the Ministerio de Economía, Industria y Competitividad (MINECO; Project CGL2014- 55764-R), the Risk Prediction Initiative at BIOS (Grant RPI2.0-2013-CARON), and the EU [Seventh Framework Programme (FP7); Grant Agreement GA603521]. We additionally acknowledge the World Climate Research Programme’s Working Group on Coupled Modelling, which is responsible for CMIP, and we thank the climate modeling groups for producing and making available their model output. For CMIP, the U.S. Department of Energy’s Program for Climate Model Diagnosis and Intercomparison provides coordinating support and led development of software infrastructure in partnership with the Global Organization for Earth System Science Portals. LPC's contract is cofinanced by the MINECO under the Juan de la Cierva Incorporacion postdoctoral fellowship number IJCI-2015-23367. Finally, we thank the National Hurricane Center for making the HURDAT2 data available. All climate model data are available at https://esgf-index1.ceda.ac.uk/projects/esgf-ceda/.Peer Reviewe