Sea level rise and tigers: predicted impacts to Bangladesh’s Sundarbans mangroves

The Sundarbans mangrove ecosystem, shared by India and Bangladesh, is recognized as a global priority for biodiversity conservation. Sea level rise, due to climate change, threatens the long term persistence of the Sundarbans forests and its biodiversity. Among the forests’ biota is the only tiger (Panthera tigris) population in the world adapted for life in mangrove forests. Prior predictions on the impacts of sea level rise on the Sundarbans have been hampered by coarse elevation data in this low-lying region, where every centimeter counts. Using high resolution elevation data, we estimate that with a 28 cm rise above 2000 sea levels, remaining tiger habitat in Bangladesh’s Sundarbans would decline by 96% and the number of breeding individuals would be reduced to less than 20. Assuming current sea level rise predictions and local conditions do not change, a 28 cm sea level rise is likely to occur in the next 50–90 years. If actions to both limit green house gas emissions and increase resilience of the Sundarbans are not initiated soon, the tigers of the Sundarbans may join the Arctic’s polar bears (Ursus maritimus) as early victims of climate change-induced habitat loss.     

Fuzzy logic based melting layer recognition from 3 GHz dual polarization radar: appraisal with NWP model and radio sounding observations

The advent of polarimetry makes it possible to categorize hydrometeor inferences more accurately by providing detailed information of the scattering properties. In light of this, the authors have developed a fuzzy logic based system for the recognition of melting layer in the atmosphere. The fuzzy system is based on characterizing melting layer scatterers from non-melting scatterers using five crisp inputs, namely, horizontal reflectivity (Z _H), differential reflectivity (Z _DR), co-polar correlation coefficient (ρ _HV), linear depolarization ratio (LDR) and height of radar measurements (H). For the implementation of melting layer recognition, the study employs the dual polarized signatures from the 3 GHz Chilbolton Advanced Meteorological Radar (CAMRA). Furthermore, a simple but effective averaging procedure for melting level estimation from a volume RHI scan is proposed. The proposed scheme has been evaluated with Weather Research and Forecasting (WRF) model simulated and radio soundings retrieved melting level height over a total of 84 RHI scan-based bright band cases. The results confirm that the estimated melting level heights from the proposed method are in good agreement with the WRF model and radio sounding observations. The 3 GHz radar melting level height estimates correspond with the R ² and RMSE values of 0.92 and 0.24 km, respectively, when compared to the radio soundings, and 0.93 and 0.21 km, respectively, when compared to the WRF model results. Moreover, the related R ² and RMSE values are reported as 0.93 and 0.22 km respectively between the WRF and radio soundings retrievals. This implies that the downscaled WRF modelled melting level height may also be used for operational or research needs.     

Direct effects and feedback of desert dust on the climate of the Arabian Peninsula during the wet season: a regional climate model study

We investigate the dust radiative forcing and its feedback on the Arabian Peninsula’s wet season climate using the International Centre for Theoretical Physics-Regional Climate Model (ICTP-RegCM4). We have found that the dust plumes exert a negative (positive) radiative forcing at the surface (top of the atmosphere) by reducing incoming solar radiation reaching the ground and locally heating up the atmosphere column. Consequently, the surface air temperature is cooler, hence indicating a decrease in the warm bias and an increase in the temperature gradient. This reduces the geopotential heights and enhances the low-level wind convergence, suggesting stronger upward motion. These changes increase evaporation, the difference between precipitation and evaporation in the atmosphere and rainfall over the Peninsula, indicating an intensification of the hydrologic cycle. The decrease in the precipitation dry bias and the large reduction in the temperature warm bias caused by the impact of dust over the entire Peninsula represent a significant success for the RegCM4 simulation. Therefore, the inclusion of dust in the simulation of the Arabian Peninsula’s climate for the wet season contributes to an improved performance of this regional climate model over the region.     

A long-term trend in precipitation of different spatial regions of Bangladesh and its teleconnections with El Niño/Southern Oscillation and Indian Ocean Dipole

A long-term (1948 to 2012) trend of precipitation (annual, pre-monsoon, monsoon, and post-monsoon seasons) in Bangladesh was analyzed in different regions using both parametric and nonparametric approaches. Moreover, the possible teleconnections of precipitation (annual and monsoon) variability with El Niño/Southern Oscillation (ENSO) episode and Indian Ocean Dipole (IOD) were investigated using both average and individual (both positive and negative) values of ENSO index and IOD. Our findings suggested that for annual precipitation, a significant increasing monotonic trend was found in whole Bangladesh (4.87 mm/year), its western region (5.82 mm/year) including Rangpur (9.41 mm/year) and Khulna (4.95 mm/year), and Sylhet (10.12 mm/year) and Barisal (6.94 mm/year) from eastern region. In pre-monsoon, only Rangpur (2.88 mm/year) showed significant increasing trend, while in monsoon, whole Bangladesh (3.04 mm/year), Sylhet (7.17 mm/year), and Barisal (6.94 mm/year) showed similar trend. In post-monsoon, there was no significant trend. Our results also revealed that the precipitation (annual or monsoon) of whole Bangladesh and almost all of the spatial regions did not show any significant correlation with ENSO events, whereas the average IOD values showed significant correlation only in monsoon precipitation of western region. The individual positive IODs showed significant correlation in whole Bangladesh, western region, and its two divisions (Rajshahi and Khulna). So, in the context of Bangladesh climate, IOD has the more teleconnection to precipitation than that of ENSO. Our findings indicate that the co-occurrence of ENSO and IOD events may suppress their influence on each other.