Future Change of Western North Pacific Typhoons: Projections by a 20-km-Mesh Global Atmospheric Model

Projected future changes in tropical cyclone (TC) activity over the western North Pacific (WNP) under the Special Report on Emissions Scenarios (SRES) A1B emission scenario were investigated using a 20-km-mesh, very-high-resolution Meteorological Research Institute (MRI)-Japan Meteorological Agency (JMA) atmospheric general circulation model. The present-day (1979-2003) simulation yielded reasonably realistic climatology and interannual variability for TC genesis frequency and tracks. The future (2075-99) projection indicates (i) a significant reduction (by about 23%) in both TC genesis number and frequency of occurrence primarily during the late part of the year (September-December). (ii) an eastward shift in the positions of the two prevailing northward-recurving TC tracks during the peak TC season (July-October), and (iii) a significant reduction (by 44%) in TC frequency approaching coastal regions of Southeast Asia. The changes in occurrence frequency are due in part to changes in large-scale steering flows, but they are due mainly to changes in the locations of TC genesis; fewer TCs will form in the western portion of the WNP (west of 145 degrees E), whereas more storms will form in the southeastern quadrant of the WNP (10 degrees-20 degrees N, 145 degrees- 160 degrees E). Analysis of the genesis potential index reveals that the reduced TC genesis in the western WNP is due mainly to in situ weakening of large-scale ascent and decreasing midtropospheric relative humidity, which are associated with the enhanced descent of the tropical overturning circulation. The analysis also indicates that enhanced TC genesis in the southeastern WNP is due to increased low-level cyclonic vorticity and reduced vertical wind shear. These changes appear to be critically dependent on the spatial pattern of future sea surface temperature; therefore, it is necessary to conduct ensemble projections with a range of SST spatial patterns to understand the degree and distribution of uncertainty in future projections.