Seasonal tropical cyclone(TC)forecasting has evolved substantially since its commencement in the early 1980s.However,present operational seasonal TC forecasting services still do not meet the requirements of society a...Seasonal tropical cyclone(TC)forecasting has evolved substantially since its commencement in the early 1980s.However,present operational seasonal TC forecasting services still do not meet the requirements of society and stakeholders:current operational products are mainly basin-scale information,while more detailed sub-basin scale information such as potential risks of TC landfall is anticipated for decision making.To fill this gap and make the TC science and services move forward,this paper reviews recent research and development in seasonal tropical cyclone(TC)forecasting.In particular,this paper features new research topics on seasonal TC predictability in neutral conditions of El Ni˜no–Southern Oscillation(ENSO),emerging forecasting techniques of seasonal TC activity including Machine Learning/Artificial Intelligence,and multi-annual TC predictions.We also review the skill of forecast systems at predicting landfalling statistics for certain regions of the North Atlantic,Western North Pacific and South Indian oceans and discuss the gap that remains between current products and potential user's expectations.New knowledge and advanced forecasting techniques are expected to further enhance the capability of seasonal TC forecasting and lead to more actionable and fit-for-purpose products.展开更多
基金support of the MEXT program for the advanced studies of climate change projection(SENTAN),Grant Numbers JPMXD0722680395 and JPMXD0722680734Julia Lockwood would like to acknowledge funding from the C3S_34c contract(number:ECMWF/COPERNICUS/2019/C3S_34c_DWD)of the Copernicus Climate Change Service operated by ECMWF.
文摘Seasonal tropical cyclone(TC)forecasting has evolved substantially since its commencement in the early 1980s.However,present operational seasonal TC forecasting services still do not meet the requirements of society and stakeholders:current operational products are mainly basin-scale information,while more detailed sub-basin scale information such as potential risks of TC landfall is anticipated for decision making.To fill this gap and make the TC science and services move forward,this paper reviews recent research and development in seasonal tropical cyclone(TC)forecasting.In particular,this paper features new research topics on seasonal TC predictability in neutral conditions of El Ni˜no–Southern Oscillation(ENSO),emerging forecasting techniques of seasonal TC activity including Machine Learning/Artificial Intelligence,and multi-annual TC predictions.We also review the skill of forecast systems at predicting landfalling statistics for certain regions of the North Atlantic,Western North Pacific and South Indian oceans and discuss the gap that remains between current products and potential user's expectations.New knowledge and advanced forecasting techniques are expected to further enhance the capability of seasonal TC forecasting and lead to more actionable and fit-for-purpose products.
