Pao-Shin Chu - Academia.edu (original) (raw)

Papers by Pao-Shin Chu

Journal of Climate, Jul 1, 2023

Long-term variations in the translation speed of tropical cyclones (TCs) in the South China Sea (... more Long-term variations in the translation speed of tropical cyclones (TCs) in the South China Sea (SCS) are examined based on five TC datasets from different institutions. TC translation speed during the TC peak season in the SCS shows an evident rhythm of interdecadal change throughout 1977-2020. This interdecadal change in TC translation speed in the SCS can be well reproduced by a newly developed trajectory model. The model results indicate that the interdecadal change in TC translation speed is primarily due to an interdecadal change in the steering flow in the SCS. Such an interdecadal change in the steering flow is closely related to an east-west shift of the subtropical high in the western North Pacific (WNP) ocean basin, which may be driven by the zonal sea surface temperature (SST) gradient between the north Indian (NI) and WNP ocean basins. A new index of the zonal SST gradient is proposed, which is shown to be effective for indicating the interdecadal change in east-west shift of subtropical high, and thus, the TC translation speed in the SCS.

Meteorological Applications, 2019

This exploratory research examines the impacts of changing climate on the vulnerable US-Affiliate... more This exploratory research examines the impacts of changing climate on the vulnerable US-Affiliated Pacific Islands (USAPI) from the perspective of the Intergovernmental Panel on Climate Change's (IPCC) Fifth Assessment Report (AR5) coupled with General Circulation Models (GCMs). Island-wide projections of future climate change (e.g. temperature, rainfall, and net water flux) were made using the latest IPCC AR5 GCMs protocol (Coupled Model Intercomparison Project Phase-CMIP5) with 38 GCMs with up to 105 model runs. A review was also made of studies on model-based future projections of the El Niño-Southern Oscillation (ENSO). The CMIP5 model's results clearly illustrate that the past trend in temperature is rising while the rainfall trend remains more or less static. It is also clear from the projections that the long-term trend for temperature rise is fast and significant, while the trend for rainfall and net water flux (P-E) rise appears to be slow and marginal. On the perspective of CMIP5 model's evaluation for the USAPI region, the temperature projections are found to be promising, while the rainfall projection potentials, despite some limitations, are also encouraging. The prime concerns for future disruptions in the USAPI region are the consequences of increasing frequency of the ENSO and related rainfall activities. The long-term warming signal may further complicate the problem. Therefore, the currently water-stressed islands and low-lying atolls in the Federated States of Micronesia (FSM) and Republic of Marshalls Islands (RMI) are particularly vulnerable to El Niño-related heat stress or drought and La Niña-related inundations or flooding. In both cases, the future demand-oriented climate-sensitive water resources sector will be severely affected. A climate-information-based comprehensive water resources management plan (for the 2030s) is therefore essential with more detailed ENSO-related climate information and impacts in terms people can understand and respond to. The general consensus of the scientific community, and an important conclusion of the 2007 report issued by the Intergovernmental Panel on Climate Change (IPCC) (2007), is that global temperatures are increasing. In general, if the higher temperature is coupled with drier conditions, it means that freshwater supplies will decrease on some Pacific Islands. The temperature rise affects agriculture, fisheries, infrastructure, biodiversity, health, human settlement, energy and water resources across the US-Affiliated Pacific Islands (USAPI) region, which is composed of the Territory of Guam (Guam), Commonwealth of the Northern Mariana Islands (CNMI; Saipan), Republic of Palau (Malakal

International Journal of Wildland Fire, 2009

The Hawaiian Islands experience damaging wildfires on a yearly basis. Soil moisture or lack there... more The Hawaiian Islands experience damaging wildfires on a yearly basis. Soil moisture or lack thereof influences the amount and flammability of vegetation. Incorporating daily maximum temperatures and daily rainfall amounts, the Keetch–Byram Drought Index (KBDI) estimates the amount of soil moisture by tracking daily maximum temperatures and rainfall. A previous study found a strong link between the KBDI and total area burned on the four main Hawaiian Islands. The present paper further examines the natural variability of the KBDI. The times of year at which the KBDI is highest, representing the highest fire danger, are found at each of the 27 stations on the island chain. Spectral analysis is applied to investigate the variability of the KBDI on longer time scales. Windward and leeward stations are shown to have different sensitivities to large-scale climatic fluctuations. An El Niño signal displays a strong relationship with leeward stations, when examined with a band-pass filter and...

This article is an open access article distributed under the terms and conditions of the Creative... more This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY

Author response for "An increase in global trends of tropical cyclone translation speed since 1982 and its physical causes

Weather and Forecasting, Feb 1, 2018

A statistical-dynamical model for predicting tropical cyclone (TC) intensity has been developed u... more A statistical-dynamical model for predicting tropical cyclone (TC) intensity has been developed using a track-pattern clustering (TPC) method and ocean-coupled potential predictors. Based on the fuzzy c-means clustering method, TC tracks during 2004-12 in the western North Pacific were categorized into five clusters, and their unique characteristics were investigated. The predictive model uses multiple linear regressions, where the predictand or the dependent variable is the change in maximum wind speed relative to the initial time. To consider TC-ocean coupling effects due to TC-induced vertical mixing and resultant surface cooling, new potential predictors were also developed for maximum potential intensity (MPI) and intensification potential (POT) using depth-averaged temperature (DAT) instead of sea surface temperature (SST). Altogether, 6 static, 11 synoptic, and 3 DAT-based potential predictors were used. Results from a series of experiments for the training period of 2004-12 using TPC and DAT-based predictors showed remarkably improved TC intensity predictions. The model was tested on predictions of TC intensity for 2013 and 2014, which are not used in the training samples. Relative to the nonclustering approach, the TPC and DAT-based predictors reduced prediction errors about 12%-25% between 24-and 96-h lead time. The present model is also compared with four operational dynamical forecast models. At short leads (up to 24 h) the present model has the smallest mean absolute errors. After a 24-h lead time, the present model still shows skill that is comparable with the best operational models.

An increase in global trends of tropical cyclone translation speed since 1982 and its physical causes

Environmental Research Letters, Sep 1, 2020

In this study, the causes of the increase in global mean tropical cyclone translation speed (TCTS... more In this study, the causes of the increase in global mean tropical cyclone translation speed (TCTS) in the post-satellite era were investigated. Analysis reveals that the global-mean TCTS increased by 0.31 km h−1 per decade over the last 36 years, but the steering flow controlling the local TCTS decreased by −0.24 km h−1 per decade in the major tropical cyclone (TC) passage regions. These values correspond to a change of 5.9% and −5.6% during the analysis period for the mean TCTS and steering flow, respectively. The inconsistency between these two related variables (TCTS and steering flows) is caused by relative TC frequency changes according to basin and latitude. The TCTS is closely related to the latitude of the TC position, which shows a significant difference in mean TCTS between basins. That is, the increased global-mean TCTS is mainly attributed to the following: (1) an increase (4.5% per decade) in the relative proportion of the North Atlantic TCs in terms of global TC’s position points (this region has the fastest mean TCTS among all basins); and (2) the poleward shift of TC activities. These two effects account for 76.8% and 25.8% of the observed global-mean TCTS trend, respectively, and thus overwhelm those of the slowing steering flow related to the weakening of large-scale tropical circulation, which leads to a global mean increase in TCTS. Given that TC activity in the North Atlantic is closely related to the Atlantic Multi-decadal Oscillation and a poleward shift of TC exposure is likely induced by global warming, the recent increase in the global-mean TCTS is a joint outcome of both natural variations and anthrophonic effects.

On average, 16 tropical cyclones (TC) form over the eastern North Pacific (ENP) each year. During... more On average, 16 tropical cyclones (TC) form over the eastern North Pacific (ENP) each year. During 1966 to 2003, the annual frequency ranges from 8 to 27, with a standard deviation above 4. The mechanism behind the interannual variability of TC activity is of interest. In this research, both accumulated cyclone energy (ACE) and TC occurrence frequency of each hurricane season (July, August, and September) are employed to represent TC activity. Two extreme events are selected with 1992 being the active and 1977 the inactive, during which large scale environmental parameters are compared. Except sea surface temperatures (SSTs) being consistently warm and favorable, other environmental parameters, which include the vertical wind shear (VWS), low-level relative vorticity, and mid-tropospheric moisture content, experience substantial variation, and display much more favorable patterns for cyclogenesis in 1992 than in 1977. The Atlantic subtropical ridge extends further westward over the G...

Climate Dynamics, 2019

Statistical and dynamical model simulations have been commonly used separately in El Niño-Souther... more Statistical and dynamical model simulations have been commonly used separately in El Niño-Southern Oscillation (ENSO) prediction. Current models are imperfect representations of ENSO and each of them has strength and weakness for capturing different aspects in ENSO prediction. Thus, it is important to utilize the results from a variety of different models. The Bayesian model averaging (BMA) is an effective tool not only in describing uncertainties associated with each model simulation but also providing the forecast performance of different models. The BMA method was developed to combine the NCEP/CPC three statistical and one dynamical model forecasts of seasonal Ocean Niño Index (ONI) from 1982 to 2010. The BMA weights were derived directly from the predictive performance of the combined models. The highly efficient expectation-maximization (EM) algorithm was used to achieve numerical solutions. We show that the BMA method can be used to assess the performance of the individual models and assign greater weights to better performing models. The continuous ranked probability score is applied to evaluate the BMA probability forecasts. As an elaboration of the reliability diagram, the attributes diagram is used that includes the calibration function, refinement distribution, and reference lines. The combination of statistical and dynamical models is found to provide a more skillful prediction of ENSO than only using a suite of statistical models, a single bias-corrected dynamical model, or the equally weighted average forecasts from all four models. Probability forecasts of El Niño events based only on winter ONI values are reliable and exhibit sharpness. In contrast, an under-forecasting bias and less reliable forecasts are noted for La Niña.

International Journal of Climatology, 2018

This study is to investigate changes in maximum 24‐hr precipitation for 20 stations during the ty... more This study is to investigate changes in maximum 24‐hr precipitation for 20 stations during the typhoon season (July–October) and how the El Niño–Southern Oscillation (ENSO) may modulate precipitation extremes in Taiwan. Based on the nonparametric Mann–Kendall method and Sens's test, 15 out of 20 stations (three fourth) exhibited an upward trend from 1958 to 2013. Results of the field significance test suggest that the significant increasing trend is not caused by random variability.The method of the non‐stationary generalized extreme value distribution (NGEV) is then applied to determine temporal changes in return levels. Results show that a large majority of stations are marked by an increasing trend in the three chosen return levels (2, 20, and 100 years) over the last 56 years. Therefore, more intense typhoon producing seasonal maximum 24‐hr precipitation has been observed in Taiwan. The waiting time for an extreme event to occur has shortened considerably in recent years. Fo...

Journal of the Meteorological Society of Japan. Ser. II, 1988

Based on surface winds at 6-h intervals for four Northern Winters and Springs (1970-73), two case... more Based on surface winds at 6-h intervals for four Northern Winters and Springs (1970-73), two cases of strong westerly wind bursts were identified in the core of the equatorial western Pacific (*155*E). One case occurred in early April and another in early May 1972, both prior to the maximum sea surface temperature anomalies along the Peruvian coast during the 1972 ENSO event. During the Northern Spring, as an anomalously strong anticyclone moves rapidly from north-central China to its east coast, the surface wind fields to the southeast of the Philippines respond swiftly, turning from an easterly background to northerly. In the meantime, surface pressure in the far western equatorial Pacific tends to rise. These rapid equatorial resposes are probably due to gravity wave-like motions induced by the pressure-wind imbalance in the midlatitudes. The local pressure increase in the extreme western Pacific enhances the west-to-east pressure gradient in the equatorial trough zone and results in a strong westerly wind acceleration in the core of the equatorial western Pacific. This acceleration is also preceded by a west-to-east displacement of the pressure surge in the equatorial trough zone. The enhanced zonal pressure-gradient force and the associated eastward displacement of the equatorial pressure surge are two critical factors for initiating westerly wind bursts. Westerly wind surges detected primarily from fixed-station data compare favorably with those calculated from ship records of an independent source.

Hawaii rainfall is teleconnected to short-term climate variability in the Pacific Ocean. The summ... more Hawaii rainfall is teleconnected to short-term climate variability in the Pacific Ocean. The summer Southern Oscillation Index (SOI) and summer sea-level pressure (SLP) over the North Pacific are used as predictors, and winter rainfall indices from three islands of Hawaii as predictands. To consolidate the large data array of the SLP field prior to prediction experiments, lagged correlation and empirical orthogonal function analyses are used. Canonical correlation analysis has been used for predicting Hawaii winter rainfall. Among many schemes tested, the one that includes the summer SOI and the first four eigenmodes from summer SLP as predictors yields the best predictions. The cross validation technique has also been used to estimate the overall forecast skill of various schemes and the results are consistent with those from prediction experiments. Winter rainfall in Hawaii can be predicted with a good degree of success two seasons in advance by using the summer SOI and the first ...

Hurricanes and Climate Change, 2010

With an expectation-maximization (EM) algorithm solving model parameters, a clustering method bui... more With an expectation-maximization (EM) algorithm solving model parameters, a clustering method built on a mixture Gaussian model is applied to the Joint Typhoon Warning Center (JTWC) best-track records to objectively classify historical tropical cyclone (TC) tracks (1945-2007) over the western North Pacific into eight types. The first three types are labeled as straight movers (A, B, and C), followed by four recurved types (D, E, F, and G), and one mixed straight-recurved type (H). For each type, a log-linear regression model is then applied to detect abrupt shifts in the time series of TC attributes including frequency, lifespan, intensity, and accumulated cyclone energy (ACE). Results indicate that the major climate shift in 1976/1977 may have affected storm's counts for two track patterns (types F and H). All eight types exhibit at least one abrupt shift in their duration since 1945, with three types (A, C, and H) showing a common shift in 1972. For a majority of the eight types, the storms' mean lifetime became longer after the shift. TC intensity shows a prevalence of abrupt shifts in the 1970s. For type D, its intensity has undergone several changes (1972, 1988, and 1998) with stronger intensity since the last shift. Because of its proximity to the East Asian landmasses and its abundance in numbers, the increasing intensity of type D since 1998 is a concern for Taiwan, the east China coast, the Philippines, Japan, and Korea. For ACE, the signal is mixed. To draw more definitive conclusions, a consistency check with another best-track record is called for.

Theoretical and Applied Climatology, 2006

The El Niñ no-Southern Oscillation (ENSO) climate cycle is the basis for this paper, aimed at pro... more The El Niñ no-Southern Oscillation (ENSO) climate cycle is the basis for this paper, aimed at providing a diagnostic outlook on seasonal sea-level variability (i.e. anomalies with respect to the Climatology) for the U.S.-Affiliated Pacific Islands (USAPI). Results revealed that the sea-level variations in the northwestern tropical Pacific islands (e.g. Guam and Marshall Islands) have been found to be sensitive to ENSO-cycle, with low sea-level during El Niñ no and high sea-level during La Niñ na events. The annual cycle (first harmonic) of sea-level variability in these north Pacific islands has also been found to be very strong. The composites of SST and circulation diagnostic show that strong El Niñ no years feature stronger surface westerly winds in the equatorial western=central Pacific, which causes north Pacific islands to experience lower sea-level from July to December, while the sea-level in south Pacific islands (e.g. American Samoa) remains unchanged. As the season advances, the band of westerly winds propagates towards the south central tropical Pacific and moves eastward, which causes American Samoa to experience a lower sea-level from January to June, but with six months time lag as compared to Guam and the Marshalls. U.S.-Affiliated Pacific Islands are among the most vulnerable communities to climate variability and change. This study has identified the year-to-year ENSO climate cycle to have significant impact on the sea-level variability of these islands. Therefore, regular monitoring of the ENSO climate cycle features that affect seasonal sea-level variability would provide substantial opportunities to develop advance planning and decision options regarding hazard management in these islands.

Tellus A, 2007

The eastern North Pacific experiences large variability in tropical cyclone (tropical storm and h... more The eastern North Pacific experiences large variability in tropical cyclone (tropical storm and hurricane) frequency from year to year. Large-scale environmental conditions during the peak hurricane season (July, August and September) are contrasted for two extreme years; 1992 is the most active year and 1977 the most inactive year. Sea surface temperatures in both 1992 and 1977 are warm and favourable for tropical cyclone (TC) formation, whereas other environmental factors undergo pronounced changes over the major development area (MDA) for the two extreme years. For instance, the 1992 hurricane season features weaker vertical wind shear, larger low-level relative vorticity, stronger mid-tropospheric ascending motion, stronger upper-level divergence, and larger mid-tropospheric moisture content than the 1977 hurricane season. These changes correspond well to the variation of the TC activity during the two extreme years. In addition, a monsoon trough is only present over the MDA in 1992. Convective disturbances within a 4-10-d period propagating consistently from the east bring stronger convection in 1992 than in 1977. In both years, anomalous zonal wind over the MDA oscillates with the intraseasonal timescale. However, TCs do not necessarily form during the westerly phases in either year in the intraseasonal timescale.

Terrestrial, Atmospheric and Oceanic Sciences, 2007

Journal of Geophysical Research: Atmospheres, 2010

Recent observational records show that the dipole oscillation between the Philippine Sea (PS) and... more Recent observational records show that the dipole oscillation between the Philippine Sea (PS) and the northern South China Sea (nSCS) is a leading empirical orthogonal function (EOF) of summertime tropical cyclone (TC) genesis in the western North Pacific (WNP). This PS‐nSCS oscillation is characterized by a distinguished decadal variability in addition to an interannual variability. Meanwhile, the typical El Niño–Southern Oscillation (ENSO)‐related mode is found in the second EOF mode, which is predominantly interannual. With regard to the PS‐nSCS oscillation, its interannual component appears to be linked with the previous wintertime ENSO event, but the linkage is not so robust in the sense that about half of its significant events are classified as the ENSO‐related case, whereas its decadal component is coupled to a sea surface temperature anomaly (SSTA) in the central Pacific with its equatorial core near the Niño‐4 region, which is flanked by an opposite SSTA on both sides alon...

Journal of Coastal Conservation, 2010

The objective of this study is to provide a perspective on the extremes of sea-level variability ... more The objective of this study is to provide a perspective on the extremes of sea-level variability and predictability for the U.S.-Affiliated Pacific Islands (USAPI) on seasonal timescales. Based on the Generalized Extreme Value (GEV) model, the L-moments method has been used to estimate the model parameters. The bootstrap method has been used to define the exceedance probability level of upper and lower bounds of the return periods at the 90% confidence interval. On the basis of these return calculations and expected extremes of high sea level, the seasonal maxima of sea level and the varying likelihood of extreme events have been estimated. For analyzing the predictability of the extremes of sea-level, a canonical correlation analysis (CCA) statistical model has been developed. Findings reveal that there is seasonal climatology of extreme events in the vicinity of USAPI that are variable on temporal and spatial scales. Some of the islands (Yap and Saipan) display considerably higher seasonal extremes than the others for 20 to 100 year return periods because of typhoon-related storm surges. These surges are likely to cause huge tidal large sea-level inundations and increased erosion to low-lying atolls/islands and result in considerable damage to roads, harbors, unstable sandy beaches, and other major infrastructures. Finally, the need for evaluating the extreme events and associated typhoons from a regional perspective has been stressed for coastal hazard management decision analyses in the USAPI.

Journal of Coastal Conservation, 2008

The objective of this study is to provide an improved climatology of sea level extremes on season... more The objective of this study is to provide an improved climatology of sea level extremes on seasonal and long-term time scales for Hawaii and the U.S-Trust islands. Observations revealed that the Hawaiian and U.S.-Trust islands, by and large, display a strong annual cycle. For estimating the statistics of return period, the threeparameter generalized extreme value (GEV) distribution is fitted using the method of L-moments. In the context of extremes (20-to 100-year return periods), the deviations in most of the Hawaiian Islands (except at Nawiliwili and Hilo) displayed a moderate sea-level rise (i.e., close to 200 mm), but the deviations in the U.S.-Trust islands displayed a considerably higher rise (i.e., more than 300 mm) in some seasons due to typhoon-related storm surges. This rise may cause damage to roads, harbors, and unstable sandy beaches. Correlations between the El Niño-Southern Oscillation (ENSO) climate cycle and the variability of seasonal sea level have been investigated. Results show that correlation for the station located west of the International Date Line (DL) is strong, but it is moderate or even weaker for stations east of the DL. The skill of SSTbased Canonical Correlation Analyses (CCA) forecasts was found to be weak to moderate (0.4-0.6 for Honolulu, Kahului, Hilo, and Wake, and 0.3 or below for Kahului, Mokuoloe, and Johnston). Finally, these findings are synthesized for evaluating the potential implications of sea level variability in these islands.

Journal of Climate, 2007

In this study, a Poisson generalized linear regression model cast in the Bayesian framework is ap... more 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 mod...