Search

This paper explores the shaping of Bangladesh's southern coastal region, often framed as the most climate vulnerable place in the world, as a zone of climate crisis. As rising waters threaten communities inhabiting the low‐lying coastal islands scattered across the deltaic plain, many within the government and donor community have identified shrimp aquaculture as a principal adaptation strategy. Shrimp aquaculture is integral to the dynamics of what I call anticipatory ruination, a discursive and material process of social and ecological destruction in anticipation of real or perceived threats. I elaborate anticipatory ruination as a process that both responds to and produces Bangladesh's climate crisis. I use this concept to explore not only the dynamics taking place in Bangladesh's delta region, but also the ways in which climate crisis is constituted more broadly. [ABSTRACT FROM AUTHOR]

This study evaluated the rainfall historical simulations of 15 Global Climate Models (GCMs) of the Coupled Model Intercomparison Project phase 6 (CMIP6) in replicating annual and seasonal rainfall climatology, their temporal variability and trends in Bangladesh for the period 1979–2014, considering ERA5 (ECMWF Reanalysis 5th Generation) reanalysis as the reference dataset. Shannon's Entropy decision‐analysis was employed for GCMs' rating based on eight statistical indicators and a comprehensive rating metric for the final grading of the GCMs. The majority of the CMIP6 GCMs accurately reproduced the spatial feature of ERA5 rainfall. However, the GCMs underestimated annual rainfall by an average of 190.5 mm, with the highest underestimation in monsoon (131.76 mm) and least in winter (3.52 mm) seasons. Most GCMs also underestimated rainfall variability for all seasons except winter. Besides, the GCMs showed an increasing trend in pre‐monsoon and a decreasing trend in post‐monsoon rainfall like ERA5, but an opposite (negative) to ERA5 trend (positive) in monsoon season rainfall. The ensemble mean of the GCMs showed higher skill in reconstructing rainfall climatology, temporal variability and trends than the individual GCMs. The study identified MPI‐ESM1‐2‐LR, MPI‐ESM1‐2‐HR, and GFDL‐ESM4 as the most effective GCMs in reproducing precipitation over Bangladesh. The selected models' simulation can be used for climate change impact assessment in Bangladesh after bias minimization. [ABSTRACT FROM AUTHOR]

Potential increases in the risk of extreme weather events under climate change can have significant socio‐economic impacts at regional levels. These impacts are likely to be particularly high in South Asia where Bangladesh is one of the most vulnerable countries. Regional climate models (RCMs) are valuable tools for studying weather and climate at finer spatial scales than are typically available in global climate models. Quantitative assessment of the likely changes in the risk of extreme events occurring requires very large ensemble simulations due to their rarity. The weather@home setup within the climateprediction.net distributed computing project is capable of providing the necessary very large ensembles at regionally higher resolution, but has only been evaluated over the South Asia region for its representation of seasonal climatological and monthly means. Here, we evaluate how realistically the HadAM3P‐HadRM3P model setup of weather@home can reproduce the observed patterns of temperature and rainfall in Bangladesh with focus on the modelled extreme events. Using very large ensembles of regional simulations, we find that there are substantial spatial and temporal variations in rainfall and temperature biases compared with observations. These are highest in the pre‐monsoon, which are largely caused by timing issues in the model. Modelled mean monsoon and post‐monsoon temperatures are in good agreement with observations, whereas there is a dry bias in the modelled mean monsoon rainfall. The rainfall bias varies both spatially and with the data set used for comparison. Despite of these biases, the model‐simulated temperature and rainfall extremes in summer monsoon over Bangladesh are approximately representative of the observed ones. At the wettest parts of northeast Bangladesh, rainfall extremes are underestimated compared to GPCC and APHRODITE but are within the range of CPC observations. Therefore, the weather@home RCM, HadRM3P may provide a sufficiently reliable tool for studying the extreme weather events in Bangladesh. [ABSTRACT FROM AUTHOR]