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Pao-Shin Chu and James D. Clark

Tropical cyclone activity (tropical depressions, tropical storms, and hurricanes combined) in the central North Pacific has been found to be on the rise and this increase amounts to about 3.2 cyclones over the last 32 years (1966–97). An examination of time series of tropical storms and hurricanes and hurricane records alone also reveals an increasing trend in both series since 1966.

The upward trend is characterized by decadal-scale variability as manifested by fewer cyclones during the first half of the record (1966–81) and more during the second half of the record (1982–97). The maximum hurricane intensity has also increased in the central North Pacific, as well as the number of intense hurricanes from the first to the second half of the record. Relative to 1966–81, sea surface temperatures in the tropical Pacific and relative vorticity near the surface to the south of Hawaii have increased dramatically during 1982–97. The changes in the frequency and intensity of tropical cyclones in the central North Pacific appear to be modulated by decadal-scale variability of the basic state of SST, which transitioned from a cold to a warm phase in the late 1970s; this warm phase may have resulted in stronger and more frequent El Niño events as seen during the second half of the record, leading to more cyclones in the central North Pacific.

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Md. Rashed Chowdhury and Pao-Shin Chu


Because of the need for information related to the variability and predictability of sea level on season-to-longer time scales, the Pacific ENSO Applications Climate (PEAC) Center runs the El Niño-Southern Oscillation (ENSO)-based canonical correlation analysis (CCA) statistical model to generate sea level forecasts for the U.S.-affiliated Pacific Islands (USAPI) region with lead times of 3–6 months in advance. However, in order to meet the increasing demand for longer lead-time (e.g., 6–12 months) forecasts, the PEAC Center, as part of the advances in operational sea level forecasts, recently incorporated both SST and zonal wind components of trade winds (U) for modulating sea level variability on longer time scales. The combined SST and U-based forecasts are found to be more skillful on longer time scales. This improvement has enabled the capability of our clients in the USAPI region to develop a more efficient long-term response plan for hazard management.

In a recent “Regional Integrated Water Level Service” meeting, it was revealed that the development and distribution of “seasonal water level outlooks” in the Pacific basin region is an area of mutual interest. We therefore synthesize the current operational forecasting, warning, and response activities of the PEAC Center and discuss the manner in which our experience in the USAPI region can contribute to the development of adaptation strategies for longer time-scale climate variability and change for the non-USAPI region in the south Pacific.

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Pao-Shin Chu, Zhi-Ping Yu, and Stefan Hastenrath

To detect climate change in the Amazon Basin, as possibly induced by deforestation, time series of monthly mean outgoing longwave radiation (OLR), an index of tropical convection, and monthly rainfall totals at Belem and Manaus for the past 15 years are analyzed. A systematic bias in the original OLR series was removed prior to the analysis. Linear regression analysis and nonlinear Mann-Kendall rank statistic are employed to detect trends. Over almost all of the basin, the OLR trend values are negative, indicating an increase of convection with time. The largest negative and statistically significant values are found in the western equatorial portion of Amazonia, where rainfall is most abundant. Consistent with this, the rainfall series at Belém and Manaus also feature upward trends. Small positive and statistically insignificant, OLR trend values are confined to the southern fringe of the basin, where deforestation has been most drastic. Thus, there is little indication for a rainfall increase associated with deforestation, but rather a strong signal of enhanced convection in the portion of Amazonia contributing most strongly to the total precipitation over the basin.

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Yi-Leng Chen, Pay-Liam Lin, Feng Hsiao, Pao-Shin Chu, and Mei-Huei Su
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Thomas W. Giambelluca, Qi Chen, Abby G. Frazier, Jonathan P. Price, Yi-Leng Chen, Pao-Shin Chu, Jon K. Eischeid, and Donna M. Delparte
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