ORIGINAL PAPER Changes in climate extremes over Bangladesh at 1.5 °C, 2 °C, and 4 °C of global warming with high-resolution regional climate modeling Md Jamal Uddin Khan 1 & A. K. M. Saiful Islam 1 & Sujit Kumar Bala 1 & G. M. Tarekul Islam 1 Received: 29 August 2019 /Accepted: 20 February 2020 /Published online: 14 March 2020 # Springer-Verlag GmbH Austria, part of Springer Nature 2020 Abstract Global mean temperature is continuously rising and causing changes in the extreme climatic events. Following these changes, climate extremes—the rare events that reside in the tail of the distribution of essential climate variables—are expected to be further intensified, more frequent, and prolonged. Changes in extremes would vary spatially from region to region and thus need regional assessment for future adaptation planning. This study assesses the climate extremes at 1.5 °C, 2 °C, and 4 °C of global warming over Bangladesh which is one of the most vulnerable countries to climate change. Future changes in climate extremes are assessed using a subset of extreme temperature and precipitation indices devised by Expert Team on Climate Change Detection and Indices (ETCCDI). Projections from high-resolution regional climate model ensembles are used to derive extreme climate indices. Our analysis shows overall upward changes in warm indices and downward changes in cold indices at higher specific warming levels. We found a much higher increase in extreme rainfall compared with the annual total rainfall. Increasing variability of rainfall indices is found at higher specific warming levels. Our analysis also suggests a higher increase of temperature during the winter and post-monsoon seasons, as well as an increase in the 1-day and 5-day maximum rainfall during pre- and post-monsoon seasons. A significant regional difference is found in almost all the rainfall indices. The forecasted increase of extreme rainfall and consecutive dry days (CDD) over the northeast region indicates a possibility of an increase of flash floods in the future. Moreover, the increase in the extreme rainfall over the southeast region will increase the chances of landslides. 1 Introduction The global climate change accompanied by the anthropogenic emissions is changing the pattern of rainfall and temperature in different regions of the world at different scales. The im- pacts of such changes are affecting not only the physical sys- tems but also the social and economic conditions at varying degrees. In recent years, climate change becomes synony- mous with the change in the global mean temperature. The international negotiations have adopted this indicator for glob- al climate governance. For example, at the 21st Conference of the Parties (COP21) of the United Nations Framework Convention on Climate Change (UNFCC), leaders from all the countries reached the first-ever global accord on climate change. Dubbed as Paris Agreement, this accord contains pol- icy obligations for all countries with the goal of “holding the increase in the global average temperature to well below 2 °C above pre-industrial levels and pursuing efforts to limit the temperature increase to 1.5 °C, recognizing that this would significantly reduce the risks and impacts of climate change” (Schleussner et al. 2016). Highlights • Spatiotemporal changes in extreme climate indices over Bangladesh at 1.5, 2, and 4 °C SWLs are studied. • Bias-corrected high-resolution multi-model ensemble projections are considered over this region. • Post-monsoon and winter will likely be warmer in the future than other seasons. • Rainfall variability is likely to be increased in the future at higher SWLs. • The highest increase in extreme rainfall would be in the northeast and southeast regions. * A. K. M. Saiful Islam akmsaifulislam@iwfm.buet.ac.bd; saiful3@gmail.com Md Jamal Uddin Khan jamal919@gmail.com Sujit Kumar Bala bala@iwfm.buet.ac.bd G. M. Tarekul Islam tarek@iwfm.buet.ac.bd 1 Institute of Water and Flood Management, Bangladesh University of Engineering and Technology, Dhaka 1000, Bangladesh Theoretical and Applied Climatology (2020) 140:1451–1466 https://doi.org/10.1007/s00704-020-03164-w