ALBERT

Description: Hawaii rainfall has exhibited both interannual and interdecadal variations. On the interannual time scale, Hawaii tends to be dry during most El Niño events, but low rainfall also occurred in the absence of El Niño. On the interdecadal time scale, Hawaii rainfall is negatively and significantly correlated with the Pacific decadal oscillation (PDO) signal; an epoch of low rainfall persists from the mid-1970s to 2001, which is preceded by an epoch of high rainfall lasting for nearly 28 yr. Difference patterns in winter [November–December–January–February–March (NDJFM)] rainfall are investigated for composites of extremely dry and wet winters during the dry and wet epochs, respectively. These patterns (i.e., DRY minus WET) are then compared to the difference in constructive match conditions of El Niño and PDO (i.e., El Niño/+PDO minus La Niña/−PDO). Relative to the El Niño/PDO stage, the magnitude of dryness during the rainfall-based stage is enhanced. The corresponding large-scale atmospheric circulation composites are studied. Similar patterns are revealed between these two stages. However, anomalously stronger and deeper sinking motions over Hawaii are revealed in the height–latitude section of the rainfall-based analysis compared to the El Niño/PDO stage. Moreover, an anomalous zonal circulation cell is well established over the subtropical North Pacific with a pronounced descending branch over Hawaii in the rainfall-based stage. The band of anomalous surface westerlies to the north of Hawaii, and the deep sinking motion as well as the anomalously vertically integrated moisture flux divergence over Hawaii are all unfavorable for rainfall in Hawaii.

Description: In this study, a Poisson generalized linear regression model cast in the Bayesian framework is applied to forecast the tropical cyclone (TC) activity in the central North Pacific (CNP) in the peak hurricane season (July–September) using large-scale environmental variables available up to the antecedent May and June. Specifically, five predictor variables are considered: sea surface temperatures, sea level pressures, vertical wind shear, relative vorticity, and precipitable water. The Pearson correlation between the seasonal TC frequency and each of the five potential predictors over the eastern and central North Pacific is computed. The critical region for which the local correlation is statistically significant at the 99% confidence level is determined. To keep the predictor selection process robust, a simple average of the predictor variable over the critical region is then computed. With a noninformative prior assumption for the model parameters, a Bayesian inference for this model is derived in detail. A Gibbs sampler based on the Markov chain Monte Carlo (MCMC) method is designed to integrate the desired posterior predictive distribution. The proposed hierarchical model is physically based and yields a probabilistic prediction for seasonal TC frequency, which would better facilitate decision making. A cross-validation procedure was applied to predict the seasonal TC counts within the period of 1966–2003 and satisfactory results were obtained.

Description: Bayesian analysis is applied to detect changepoints in the time series of seasonal typhoon counts in the vicinity of Taiwan. An abrupt shift in the typhoon count series occurs in 2000. On average, 3.3 typhoons per year have been noted before 2000 (1970–99), with the rate increasing to 5.7 typhoons per year since 2000 (2000–06). This abrupt change is consistent with a northward shift of the typhoon track over the western North Pacific–East Asian region and an increase of typhoon frequency over the Taiwan–East China Sea region. The northward shift of the typhoon track tends to be associated with typhoon-enhancing environmental conditions over the western North Pacific, namely, the weakening of the western North Pacific subtropical high, the strengthening of the Asian summer monsoon trough, and the enhanced positive vorticity anomalies in the lower troposphere. Based on observational analysis and model simulations, warm sea surface temperature anomalies over the equatorial western and central Pacific appear to be a major factor contributing to a northward-shifted typhoon track.

Description: For the first time, trends of five climate change indices related to extreme precipitation events in the Hawaiian Islands are investigated using daily observational records from the 1950s to 2007. Four indices [simple daily intensity index (SDII), total number of day with precipitation ≥25.4 mm (R25), annual maximum consecutive 5-day precipitation amount (R5d), and the fraction of annual total precipitation from events exceeding the 1961–90 95th percentile (R95p)] describe the intensity (SDII), frequency (R25), and magnitude (R5d and R95p) of precipitation extremes, and the fifth index [consecutive dry days (CDD)] describes drought conditions. The annual probability density functions (PDFs) of precipitation indices for two epochs (i.e., 1950–79 and 1980–2007) are analyzed. Since the 1980s, there has been a change in the types of precipitation intensity, resulting in more frequent light precipitation and less frequent moderate and heavy precipitation intensity. The other three precipitation-related indices (R25, R5d, and R95p) demonstrate a shift toward the left of the distribution over time, suggesting shorter annual number of days with intense precipitation and smaller consecutive 5-day precipitation amounts and smaller fraction of annual precipitation due to events exceeding the 1961–90 95th percentile in the recent epoch relative to the first epoch. The changes of PDF distribution for SDII, R25, R5d, and CDD are significant at the 5% level according to a two-sample Kolmogorov–Smirnov test. A nonparametric trend analysis is then performed for four periods, with different starting years (e.g., the 1950s, the 1960s) but the same ending year (2007). Long-term downward trends are evident for four precipitation-related indices, and long-term upward trends are observed for CDD. Geographically, Kauai and Oahu are dominated by long-term decreasing trends for four precipitation-related indices, while increasing trends play the major role over the island of Hawaii. The upward trends of drought conditions in the long run are predominant on all the major Hawaiian Islands. To investigate whether the trends are stable throughout the time, the derivatives of trends for each of the 30-yr running series are calculated (e.g., 1950–79, 1951–80, … , 1978–2007) for four precipitation-related indices at each station. For Kauai and Oahu, positive derivatives prevail for all indices in the presence of long-term negative trends, suggestive of a phase change in precipitation extremes and such extremes showing an upswing recently. For the island of Hawaii, there is also an indication of phase reversal over the last 60 yr, with negative derivatives occurring in the presence of the background positive trends. A positive relationship is found between the precipitation indices and the Southern Oscillation index (SOI), implying more precipitation extremes during La Niña years and vice versa for El Niño years. Spatial patterns of standardized anomalies of indices are presented for the La Niña/−PDO minus El Niño/+PDO composites.

Description: A fuzzy c-means clustering method (FCM) is applied to cluster tropical cyclone (TC) tracks. FCM is suitable for the data where cluster boundaries are ambiguous, such as a group of TC tracks. This study introduces the feasibility of a straightforward metric to incorporate the entire shapes of all tracks into the FCM, that is, the interpolation of all tracks into equal number of segments. Four validity measures (e.g., partition coefficient, partition index, separation index, and Dunn index) are used objectively to determine the optimum number of clusters. This results in seven clusters from 855 TCs over the western North Pacific (WNP) from June through October during 1965–2006. The seven clusters are characterized by 1) TCs striking the Korean Peninsula and Japan with north-oriented tracks, 2) TCs affecting Japan with long trajectories, 3) TCs hitting Taiwan and eastern China with west-oriented tracks, 4) TCs passing the east of Japan with early recurving tracks, 5) TCs traveling the easternmost region over the WNP, 6) TCs over the South China Sea, and 7) TCs moving straight across the Philippines. Each cluster shows distinctive characteristics in its lifetime, traveling distance, intensity, seasonal variation, landfall region, and distribution of TC-induced rainfall. The roles of large-scale environments (e.g., sea surface temperatures, low-level relative vorticity, and steering flows) on cluster-dependent genesis locations and tracks are also discussed.

Description: Rainfall in Hawaii during La Niña years has undergone abnormal variability since the early 1980s. Traditionally, Hawaii receives greater-than-normal precipitation during the La Niña wet seasons. Recently, La Niña years have experienced less-than-normal rainfall. A drying trend in Hawaiian precipitation during La Niña years is evident. A changepoint analysis determined that the shift in precipitation occurred in 1983, forming the two epochs used for comparison in this study. The first epoch (E1) runs from 1956 to 1982 and the second epoch (E2) from 1983 to 2010. Location-specific changes in rainfall anomalies from E1 to E2 throughout the Hawaiian Islands are examined, illustrating that the greatest difference in rainfall between epochs is found on the climatologically drier sides (i.e., south and west) of the islands. Variations in tropical sea surface temperatures and circulation features in the northern Pacific Ocean have changed during La Niña wet seasons, thus changing La Niña–year rainfall. The strengthening, broadening, and westward shifting of the eastern North Pacific subtropical high, coupled with an eastward elongation and intensification of the subtropical jet stream, are two main influences when considering the lack of precipitation during the recent La Niña wet seasons. Moisture transport analysis shows that variations in circulation structures play a dominant role in the reduction of moisture flux convergence in the Hawaiian region during the second epoch. Additionally, a storm-track analysis reveals that the changes found in the aforementioned circulation features are creating a less favorable environment for the development of Kona lows and midlatitude fronts in the vicinity of Hawaii.

Description: Bayesian analysis is applied to detect change points in the time series of annual tropical cyclone counts over the central North Pacific. Specifically, a hierarchical Bayesian approach involving three layers—data, parameter, and hypothesis—is formulated to demonstrate the posterior probability of the shifts throughout the time from 1966 to 2002. For the data layer, a Poisson process with gamma distributed intensity is presumed. For the hypothesis layer, a “no change in the intensity” hypothesis and a “single change in the intensity” hypothesis are considered. Results indicate that there is a great likelihood of a change point on tropical cyclone rates around 1982, which is consistent with earlier work based on a simple log-linear regression model. A Bayesian approach also provides a means for predicting decadal tropical cyclone variations. A higher number of tropical cyclones is predicted in the next decade when the possibility of the change point in the early 1980s is taken into account.

Description: A Bayesian framework is developed to detect multiple abrupt shifts in a time series of the annual major hurricanes counts. The hurricane counts are modeled by a Poisson process where the Poisson intensity (i.e., hurricane rate) is codified by a gamma distribution. Here, a triple hypothesis space concerning the annual hurricane rate is considered: “a no change in the rate,” “a single change in the rate,” and “a double change in the rate.” A hierarchical Bayesian approach involving three layers—data, parameter, and hypothesis—is formulated to demonstrate the posterior probability of each possible hypothesis and its relevant model parameters through a Markov chain Monte Carlo (MCMC) method. Based on sampling from an estimated informative prior for the Poisson rate parameters and the posterior distribution of hypotheses, two simulated examples are illustrated to show the effectiveness of the proposed method. Subsequently, the methodology is applied to the time series of major hurricane counts over the eastern North Pacific (ENP). Results indicate that the hurricane activity over ENP has very likely undergone a decadal variation with two changepoints occurring around 1982 and 1999 with three epochs characterized by the inactive 1972–81 epoch, the active 1982–98 epoch, and the inactive 1999–2003 epoch. The Bayesian method also provides a means for predicting decadal major hurricane variations. A lower number of major hurricanes are predicted for the next decade given the recent inactive period of hurricane activity.