Based on outgoing longwave radiation (OLR), an index for clustering tropical cyclogenesis (CTC) over the western North Pacific (WNP) was defined. Around 76 % of total CTC events were generated during the active phase of the CTC index, and 38 % of the total active phase was concurrent with CTC events. For its continuous property, the CTC index was used as the representative predictand for extended-range forecasting the temporal distribution of CTC events.
The predictability sources for CTC events were detected via correlation analyses of the previous 35–5-day lead atmospheric fields against the CTC index. The results showed that the geopotential height at different levels and the 200 hPa zonal wind over the global tropics possessed large predictability sources, whereas the predictability sources of other variables, e.g., OLR, zonal wind, and relatively vorticity at 850 hPa and relatively humility at 700 hPa, were mainly confined to the tropical Indian Ocean and western Pacific Ocean.
Several spatial-temporal projection model (STPM) sets were constructed to carry out the extended-range forecast for the CTC index. By combining the output of STPMs separately conducted for the two dominant modes of intraseasonal variability, e.g., the 10–30 and the 30–80 day mode, useful forecast skill could be achieved for a 30-day lead time. The combined output successfully captured both the 10–30 and 30–80 day mode at least 10 days in advance. With a relatively low rate of false alarm, the STPM achieved hits for 80 % (69 %) of 54 CTC events during 2003–2014 at the 10-day (20-day) lead time, suggesting a practical value of the STPM for real-time forecasting WNP CTC events at an extended range.
Lead Time Western North Pacific Outgoing Longwave Radiation Forecast Skill Monsoon Trough
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The authors would like to thank the two anonymous reviewers for their constructive comments. This work was supported by the Natural Science Foundation of Jiangsu Province (BK20140046), the China National 973 project (2015CB453200), the Special Fund for Meteorological Scientific Research of the Public Sector (Grant no. GYHY201306032), the National Natural Science Foundation of China (41575052/41630423), the key project of the Fujian Provincial Department of Science and Technology (2011Y0008), and the PAPD (Priority Academic Program Development) of Jiangsu Higher Education institutions. This paper is SOEST contribution number 9817, IPRC contribution number 1210 and ESMC contribution number 125.
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1.Key Laboratory of Meteorological Disaster, Ministry of Education (KLME)/Joint International Research Laboratory of Climate and Environment Change (ILCEC)/Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters (CIC-FEMD)Nanjing University of Information Science and TechnologyNanjingChina
2.International Pacific Research Center and Department of Atmospheric SciencesUniversity of Hawaii at ManoaHonoluluUSA