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The prime concerns for future disruptions in the El Niño-Southern oscillation (ENSO)-sensitive U.S.-affiliated Pacific islands (USAPIs) are centered on the consequences of increasing frequency of ENSO and related drought and flooding activities. Recent observations also revealed that island-specific rainfall and sea-level patterns appear to be different during the three types of El Niño events (eastern, mixed, and central Pacific). The primary motivation of the study is to identify the impacts of three different types of El Niño on rainfall and sea-level variability in USAPIs. Results reveal that different types of El Niño can lead to different variations in rainfall and sea level in the USAPIs. While the eastern Pacific and mixed El Niño events are associated with lower than normal rainfall in all USAPIs, the central Pacific El Niño events are found to be associated with enhanced rainfall in many USAPIs. Similarly, while all the USAPIs displayed lower than normal sea level during eastern Pacific and mixed El Niño events, some of the USAPIs displayed higher than normal sea level during central Pacific events. Information related to island-specific rainfall and sea-level response to different El Niño events is critical to support the short-to-mid-term planning and management in climate-sensitive sectors in the USAPIs. [ABSTRACT FROM AUTHOR]

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 (1950–2017) 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. [ABSTRACT FROM AUTHOR]

ABSTRACT The aim of this study is to assess the evolution of forests in Bangladesh from the perspective of changing climate, with particular emphasis on the Sundarbans, the world's largest mangrove forest. Projections for temperature and rainfall change have been made using the latest Intergovernmental Panel on Climate Change-Fifth Assessment Report ( IPCC-AR5) general circulation models ( GCMs) protocol (Coupled Model Intercomparison Project Phase 5, CMIP5) with 38 various GCMs and up to 105 model runs. The GCMs findings were verified by the published results of 11 regional climate models ( RCMs) in the Coordinated Regional Climate Downscaling Experiment ( CORDEX)-South Asia models with finer spatial resolution. A CMIP5 model-based synthesis review on the future variability of El Niño-Southern Oscillation ( ENSO) has also been made, as both the seasonal temperature and rainfall variability in Bangladesh are correlated to ENSO. Both global and regional climate change scenarios indicate that temperature would continue to rise and total annual rainfall is likely to increase in the future. However, weak increases in rainfall combined with high increases in temperature would create a high demand and competition for water because of the higher evapotranspiration environment. In addition to changing climate, the interannual variability of ENSO would further aggravate problems because it displays important correlations with the variability of rainfall, temperatures, sea-level, lightning, and forest fires in Bangladesh. This study strongly recommends that future climate change projections should be combined with interannual variability ENSO to improve climate perspectives for stronger forest capacity building efforts in Bangladesh. [ABSTRACT FROM AUTHOR]

Sea level anomaly extremes impact tropical Pacific Ocean islands, often with too little warning to mitigate risks. With El Niño, such as the strong 2015/16 event, comes weaker trade winds and mean sea level drops exceeding 30 cm in the western Pacific that expose shallow-water ecosystems at low tides. Nearly opposite climate conditions accompany La Niña events, which cause sea level high stands (10- 20 cm) and result in more frequent tide- and storm-related inundations that threaten coastlines. In the past, these effects have been exacerbated by decadal sea level variability, as well as continuing global sea level rise. Climate models, which are increasingly better able to simulate past and future evolutions of phenomena responsible for these extremes (i.e., El Niño-Southern Oscillation, Pacific decadal oscillation, and greenhouse warming), are also able to describe, or even directly simulate, associated sea level fluctuations. By compiling monthly sea level anomaly predictions from multiple statistical and dynamical (coupled ocean-atmosphere) models, which are typically skillful out to at least six months in the tropical Pacific, improved future outlooks are achieved. From this multimodel ensemble comes forecasts that are less prone to individual model errors and also uncertainty measurements achieved by comparing retrospective forecasts with the observed sea level. This framework delivers online a new real-time forecasting product of monthly mean sea level anomalies and will provide to the Pacific island community information that can be used to reduce impacts associated with sea level extremes. [ABSTRACT FROM AUTHOR]

ABSTRACT This study describes an improved seasonal sea level forecasting scheme by the Pacific ENSO Applications Climate Center ( PEAC). Since 2005, an operational sea level forecasting scheme (3-5 months in advance) for the US-affiliated Pacific Islands ( USAPI) has been instrumental (). The El Niño-Southern Oscillation ( ENSO) climate cycle and the sea-surface temperatures ( SSTs) in the tropical Pacific Ocean are taken as the primary factors in modulating these forecasts on seasonal time scales. The current SST-based canonical correlations analysis ( CCA) hindcast forecasts have been found to be skillful. However, the skill gradually decreases as the lead-time increases. This has motivated us to revisit the forecasting scheme at PEAC. In contrast to previous endeavours which relied only on SSTs, we now incorporate both trade winds and SSTs for modulating sea level variability on seasonal time scales. The average forecasts for zero to three seasons' lead-times are found to be 0.647, 0.598, and 0.625 for combined SST and the zonal component of the trade wind (U), SST, and wind (U), respectively. It is therefore revealed that the combined SST-wind-based forecasts are more skillful than the SST or wind-based forecasts alone. It is particularly more efficient on longer time scales for most of the stations (e.g. 10-25% improvement on two to three seasons' lead-times). The improvements of these forecasts have enabled the capability of our clients in the USAPI region to develop a more efficient long-term response plan for hazard management. [ABSTRACT FROM AUTHOR]

The Pacific ENSO Applications Center (PEAC) was established in August 1994 as a multi-institutional partnership to conduct research and produce information products on climate variability and impacts related to the El Niño-Southern Oscillation climate cycle for the U.S.-Affiliated Pacific Islands (USAPI). The name of the center was changed to Pacific ENSO Applications Climate (PEAC) Center in 2007. Over the years, the PEAC Center effectively provided advanced warning as part of the hazard management program for the small island countries in the USAPI region. The primary focus of this paper is to synthesize the overall hazard management activities of the PEAC Center by visiting various aspects of the historical and current operational framework, including i) forecasting, ii) interpretation and message formulation, iii) warning preparation and dissemination, iv) responses and feedback, and v) review and analysis. The forecast, warning, and response experience of PEAC can help small island countries in the Pacific develop adaptation strategies for longer time-scale climate variability and change. [ABSTRACT FROM AUTHOR]

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 time-scales. 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. [ABSTRACT FROM AUTHOR]

At present, Bangladesh has a flood forecasting lead time of only 3 days or so. There is demand for a forecasting lead time of a month to a season. The primary objectives of this paper are to study the variability and predictability of seasonal flooding in Bangladesh, as revealed by large-scale predictors of the climate across the watersheds. To explore the source of predictability, accessible Bangladesh hydrological indicators are related to large-scale oceanic variability and to large-scale atmospheric circulation patterns predicted by general circulation models (GCMs). Correlation analyses between the flood-affected area (FAA) for July-September and tropical sea-surface temperature (SST) indicate connections to tropical Pacific and Indian Ocean SSTs, at a short lead time of a month or so. These are related to El Niño southern oscillation (ENSO). Correlations between the SSTs of the preceding October-December and the July-September FAA are weaker but notable. Forecasts of the FAA using the leading principal components (PCs) of SST were made, which provided good skill with a lead time of a month or so. The streamflows and rainfall observed in Bangladesh have been added to these prediction models. Finally, the SST PCs were replaced with PCs of GCM prediction fields (precipitation). The prediction models at short lead time that were constructed for FAA were of generally similar levels of skill to that for SST. This is encouraging, as it suggests that linkages with SST can be successfully recovered in a physical model of the climate system in Bangladesh. This study concludes that seasonal flood prediction in Bangladesh is possible from the unusually warm or cold SST in parts of the tropics. This predictability can be enhanced with the information achievable from monitoring the downstream streamflows (which are generated mainly from upstream rainfall conditions) in advance of the flooding season. Finally, this study recommends formalizing a regional cooperation among the countries in the principal co-basin areas of the Ganges-Brahmaputra-Meghna to achieve this goal. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]