Anthropogenic influence on extreme temperature and precipitation in Central Asia

Climate change and urban sprawl: Unveiling the escalating flood risks in river deltas with a deep dive into the GBM river delta

River deltas, such as the Ganges-Brahmaputra-Meghna (GBM) delta, are highly vulnerable to flooding, exacerbated by intense human activities and rapid urban growth. This study explores the evolution of urban flood risks in the GBM delta under the combined impacts of climate change and urban expansion. Unlike traditional assessments that focus on a single flood source, we consider multiple sources-coastal, fluvial, and pluvial. Our findings indicate that future urban expansion will significantly increase flood exposure, with a substantial rise in flood risk from all sources by the end of this century. Climate change is the main driver of increased coastal flood risks, while urban growth primarily amplifies fluvial, and pluvial flood risks. This highlights the urgent need for adaptive urban planning strategies to mitigate future flooding and support sustainable urban development. The extreme high emissions future scenario (SSP5-8.5) shows the largest urban growth and consequent flood risk, emphasizing the necessity for preemptive measures to mitigate future urban flooding. Our study provides crucial insights into flood risk dynamics in delta environments, aiding policymakers and planners in developing resilience strategies against escalating flood threats.

Selecting the optimal gridded climate dataset for Nigeria using advanced time series similarity algorithms

Choosing a suitable gridded climate dataset is a significant challenge in hydro-climatic research, particularly in areas lacking long-term, reliable, and dense records. This study used the most common method (Perkins skill score (PSS)) with two advanced time series similarity algorithms, short time series distance (STS), and cross-correlation distance (CCD), for the first time to evaluate, compare, and rank five gridded climate datasets, namely, Climate Research Unit (CRU), TERRA Climate (TERRA), Climate Prediction Center (CPC), European Reanalysis V.5 (ERA5), and Climatologies at high resolution for Earth's land surface areas (CHELSA), according to their ability to replicate the in situ rainfall and temperature data in Nigeria. The performance of the methods was evaluated by comparing the ranking obtained using compromise programming (CP) based on four statistical criteria in replicating in situ rainfall, maximum temperature, and minimum temperature at 26 locations distributed over Nigeria. Both methods identified CRU as Nigeria's best-gridded climate dataset, followed by CHELSA, TERRA, ERA5, and CPC. The integrated STS values using the group decision-making method for CRU rainfall, maximum and minimum temperatures were 17, 10.1, and 20.8, respectively, while CDD values for those variables were 17.7, 11, and 12.2, respectively. The CP based on conventional statistical metrics supported the results obtained using STS and CCD. CRU's Pbias was between 0.5 and 1; KGE ranged from 0.5 to 0.9; NSE ranged from 0.3 to 0.8; and NRMSE between - 30 and 68.2, which were much better than the other products. The findings establish STS and CCD's ability to evaluate the performance of climate data by avoiding the complex and time-consuming multi-criteria decision algorithms based on multiple statistical metrics.

Projection of climate change impacts on extreme temperature and precipitation in Central Poland

Climate change is exacerbating the risk of the occurrence of extreme weather. This study has projected the change in mean and extreme climate conditions in Central Poland during near-future (2026-2050), mid-term (2051-2075), and far-future (2076-2100) periods under two climate-change scenarios in six General Circulation Models (GCMs) from Coupled Model Intercomparison Project Phase 6 (CMIP6). The results showed that, compared to the historical reference period (1990-2014), Central Poland will experience an increase in temperature and precipitation by the end of the twenty-first century. It is expected that the mean annual temperature and mean annual precipitation totals will increase by 1-4.8 °C and 2-7.5%, respectively. Furthermore, it is projected that the average number of hot, very hot days and extremely hot days (Tmax > 25 °C, > 30 °C, and > 35 °C), tropical nights (Tmin > 20 °C), and extremely high daily precipitation (> 10 mm, > 20 mm and > 30 mm) will also increase, while the average number of slight frost days (Tmin < 0 °C), and frost and severe frost days (Tmax < 0 °C, Tmax <  - 10 °C) will decline on average by the end of the twenty-first century. Therefore, it is essential for policymakers to take some appropriate measurements and strategies in advance to strengthen resilience to extreme climate events.