Recent advances in seasonal and multi-annual tropical cyclone forecasting

• DOI: 10.1016/j.tcrr.2023.09.003
• Publication Date: 2023-09-17T13:37:17Z
• Authors: Yuhei Takaya; Louis-Philippe Caron; Eric Blake; François Bonnardot; Nicolas Bruneau; Joanne Camp; Johnny Chan; Paul Gregory; Jhordanne J. Jones; Namyoung Kang; Philip J. Klotzbach; Yuriy Kuleshov; Marie-Dominique L...; Julia F. Lockwood; Hiroyuki Murakami; Akio Nishimura; Dushmanta R. Patt...; Tom J. Philp; Yohan Ruprich-Robert; Ralf Toumi; Frédéric Vitart; Seonghee Won; Ruifen Zhan
• Keywords: Predictability; Landfall

Seasonal tropical cyclone (TC) forecasting has evolved substantially since its commencement in the early 1980s. However, present operational seasonal TC services still do not meet requirements of society and stakeholders: current products are mainly basin-scale information, while more detailed sub-basin scale information such as potential risks landfall is anticipated for decision making. To fill this gap make science move forward, paper reviews recent research development forecasting. In particular, features new topics on predictability neutral conditions El Niño–Southern Oscillation (ENSO), emerging techniques activity including Machine Learning/Artificial Intelligence, multi-annual predictions. We also review skill forecast systems at predicting landfalling statistics certain regions North Atlantic, Western Pacific South Indian oceans discuss that remains between user's expectations. New knowledge advanced expected to further enhance capability lead actionable fit-for-purpose products.