Global increase of the intensity of tropical cyclones under global warming based on their maximum potential intensity and CMIP6 models

Future changes in the intensity of tropical cyclones (TCs) under global warming are uncertain, although several studies have projected an upward trend in TC intensity. In this study, we examined the changes in the strength of TCs in the twenty-first century based on the Hurricane Maximum Potential Intensity (HuMPI) model forced with the sea surface temperature (SST) from the bias-corrected CMIP6 dataset. We first investigated the relationship between the mean lifetime maximum intensity (LMI) of major hurricanes (MHs) and the maximum potential intensity (MPI) using the SST from the Daily Optimum Interpolation SST database. The LMI of MHs and the MPI in the last two decades was, on average, 2–3% higher than mean values in the sub-period 1982–2000, suggesting a relationship between changes in MPI and LMI. From our findings, the projected changes in TC intensity in the near-future period (2016–2040) will be almost similar for SSP2-4.5 and SSP5-8.5 climate scenarios. However, TCs will be 9.5% and 17% more intense by the end (2071–2100) of the twenty-first century under both climate scenarios, respectively, compared with the mean intensity over the historical period (1985–2014). In addition, the MPI response to a warmed sea surface temperature per degree of warming is a 5–7% increase in maximum potential wind speed. These results should be interpreted as a projection of changes in TC intensity under global warming since the HuMPI formulation does not include environmental factors (i.e., vertical wind shear, mid-level moisture content and environmental stratification) that influence TC long-term intensity variations.Universidade de Vigo/CISU

Cyclone risk assessment of the Cox’s Bazar district and Rohingya refugee camps in southeast Bangladesh

Bangladesh has a long history of devastating tropical cyclones. In view of the effects of the storms on the country, risk assessment is essential for devising the mitigation strategies at various levels. By way of bringing the conceptual structure of general risk model in practice, this work aims to examine the spatial patterns of cyclone risk in the Cox’s Bazar district (I) and Rohingya refugee camps (II) located on the southeastern coast of Bangladesh. We use 14 parameters representing the hazard, exposure, and vulnerability as the components of risk. The selected parameters were analyzed and integrated though the complementary use of Analytic Hierarchy Process (AHP) and Geographic Information System (GIS) for depicting the cyclone risk situation comprehensively at both the spatial scales. The status of the cyclone risk was identified and quantified as very high (6.84%, 3.43%), high (45.78%, 27.82%), moderate (5.97%, 39.42%), low (40.62%, 28.70%), and very low (0.81%, 0.61%) for the spatial scale I and II respectively. In general, northwestern and southern peripheral areas exhibited higher risk than the central and northeastern parts of the Cox’s Bazar district; and in the refugee settlements, camp number 1E, 1W, 7, and 13 revealed relatively higher levels of the risk. The results of the assessment (I) were correlated with experiential damage from the 1991 cyclone; a reasonable consistency was noticed between the simulated scenario and the observed impacts. We assume that the deliverables of this spatial analysis could be useful to stakeholders while formulating the cyclone risk mitigation policies for the region. Furthermore, this work demonstrates that the applied method would deliver reliable results if tested in other coastal environments

Modelling tropical cyclone risks for present and future climate change scenarios using geospatial techniques

© 2017 Informa UK Limited, trading as Taylor & Francis Group. Tropical cyclones and their devastating impacts are of great concern to coastal communities globally. An appropriate approach integrating climate change scenarios at local scales is essential for producing detailed risk models to support cyclone mitigation measures. This study developed a simple cyclone risk-modelling approach under present and future climate change scenarios using geospatial techniques at local scales, and tested using a case study in Sarankhola Upazila from coastal Bangladesh. Linear storm-surge models were developed up to 100-year return periods. A local sea level rise scenario of 0.34 m for the year 2050 was integrated with surge models to assess the climate change impact. The resultant storm-surge models were used in the risk-modelling procedures. The developed risk models successfully identified the spatial extent and levels of risk that match with actual extent and levels within an acceptable limit of deviation. The result showed that cyclone risk areas increased with the increase of return period. The study also revealed that climate change scenario intensified the cyclone risk area by 5–10% in every return period. The findings indicate this approach has the potential to model cyclone risk in other similar coastal environments for developing mitigation plans and strategies