Sea Level Forecasts and Early-Warning Application: Expanding Cooperation in the South Pacific

Chowdhury, Md. Rashed; Chu, Pao-Shin

doi:10.1175/bams-d-14-00038.1.2016.1.test

Cited by 4 publications

(4 citation statements)

References 14 publications

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“…pressure fields); and (2) the application of such relationships to the output of global climate model experiments to simulate local climate characteristics in the future. Also note that our experience from other similar regions demonstrated that GCMs/RCMs‐outputs‐based statistical downscaling is an appropriate approach for understanding the climate variability and change for countries like Bangladesh (see Schroeder et al ., ; Chowdhury and Chu, ). Finally, it is also important to improve our understanding of emissions from fires in the region, which would ultimately help improve climate models.…”

Section: Model Limitations and Improvement Optionsmentioning

confidence: 99%

Climate change and variability impacts on the forests of Bangladesh – a diagnostic discussion based on CMIP5 GCMs and ENSO

Chowdhury

Ndiaye

2017

Intl Journal of Climatology

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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.

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Section: Model Limitations and Improvement Optionsmentioning

confidence: 99%

Climate change and variability impacts on the forests of Bangladesh – a diagnostic discussion based on CMIP5 GCMs and ENSO

Chowdhury

Ndiaye

2017

Intl Journal of Climatology

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“…[2011b], modifying their x by using (1) monthly instead of seasonal anomalies, taken from the observational data sets of the 1958-2010 period listed in Table S1 in the supporting information [Kalnay et al, 1996;Rayner et al, 2003;Ishii et al, 2005;Smith et al, 2008;Balmaseda et al, 2013], (2) sea surface height (SSH) instead of thermocline depth anomalies, given the interest in SSH forecasts for their own sake [Chowdhury and Chu, 2015], and (3) 200 and 850 hPa horizontal winds instead of surface zonal wind stresses to represent the atmospheric ENSO component. The anomaly fields were filtered in each field's empirical orthogonal function (EOF) space defined in the global tropical strip 24°S-24°N, retaining the leading 18/6/4 EOFs representing about 85/63/25% of the domain integrated SST/SSH/wind anomaly variances.…”

Section: Linear Inverse Modelmentioning

confidence: 99%

Are we near the predictability limit of tropical Indo‐Pacific sea surface temperatures?

Newman

Sardeshmukh

2017

Geophysical Research Letters

115

100

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The predictability of seasonal anomalies worldwide rests largely on the predictability of tropical sea surface temperature (SST) anomalies. Tropical forecast skill is also a key metric of climate models. We find, however, that despite extensive model development, the tropical SST forecast skill of the operational North American Multi‐Model Ensemble (NMME) of eight coupled atmosphere‐ocean models remains close both regionally and temporally to that of a vastly simpler linear inverse model (LIM) derived from observed covariances of SST, sea surface height, and wind fields. The LIM clearly captures the essence of the predictable SST dynamics. The NMME and LIM skills also closely track and are only slightly lower than the potential skill estimated using the LIM's forecast signal‐to‐noise ratios. This suggests that the scope for further skill improvement is small in most regions, except in the western equatorial Pacific where the NMME skill is currently much lower than the LIM skill.

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“…One of the few examples of El Niño warning at the Pacific regional level is from Chowdhury and Chu (2015) looking at sea level forecasts, mainly for the US-affiliated islands and including but not limited to El Niño years. Forecasts have been given 3-6 months in advance, but they report moves towards 6-12 month forecasts due to demand for them.…”

Section: Preparedness In the Pacific Regionmentioning

confidence: 99%

Pacific island regional preparedness for El Niño

Kelman

2017

Environ Dev Sustain

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The El Niño Southern Oscillation (ENSO) cycle is often blamed for disasters in Pacific island communities. From a disaster risk reduction (DRR) perspective, the challenges with the El Niño part of the ENSO cycle, in particular, are more related to inadequate vulnerability reduction within development than to ENSO-induced hazard influences. This paper analyses this situation, filling in a conceptual and geographic gap in El Niño-related research, by reviewing El Niño-related preparedness (the conceptual gap) for Pacific islands (the geographic gap). Through exploring El Niño impacts on Pacific island communities alongside their vulnerabilities, resiliences, and preparedness with respect to El Niño, El Niño is seen as a constructed discourse rather than as a damaging phenomenon, leading to suggestions for El Niño preparedness as DRR as part of development. Yet the attention which El Niño garners might bring resources to the Pacific region and its development needs, albeit in the short term while El Niño lasts. Conversely, the attention given to El Niño could shift blame from underlying causes of vulnerability to a hazard-centric viewpoint. Instead of focusing on one hazard-influencing phenomenon, opportunities should be created for the Pacific region to tackle wider DRR and development concerns.

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Sea Level Forecasts and Early-Warning Application: Expanding Cooperation in the South Pacific

Cited by 4 publications

References 14 publications

Climate change and variability impacts on the forests of Bangladesh – a diagnostic discussion based on CMIP5 GCMs and ENSO

Climate change and variability impacts on the forests of Bangladesh – a diagnostic discussion based on CMIP5 GCMs and ENSO

Are we near the predictability limit of tropical Indo‐Pacific sea surface temperatures?

Pacific island regional preparedness for El Niño

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