Using the CHIRPS Dataset to Investigate Historical Changes in Precipitation Extremes in West Africa

Temporal patterns and influences of monthly, seasonal and annual temperatures on methane emissions in Greece, Armenia and Russia over two decades

This study explores methane emission trends across Greece, Armenia, and Rostov Oblast region of Russia from 2004 to 2023. Our analyses, based on remote sensing and advanced statistical techniques, showed a 1.3-1.8 °C increase in mean annual temperature over this 20-year period in all these three regions, with the highest and the lowest rates of annual warming in Armenia (0.104 °C) and Rostov Oblast of Russia (0.052 °C), respectively. Mean annual methane concentrations increased distinctly in these regions over this period. Greece showed the trend of highest correlations between methane emissions and temperatures, including mean annual and seasonal temperatures, highlighting substantial role of climate change in emission trends. The emission trends with on-ground observations revealed intricate connections between reduced precipitations, farming practices, waste disposal methods, and naturally occurring emissions in Greece. In contrast, Armenia exhibited weak correlations between temperature and methane emissions, with its farming, waste management, energy and manufacturing sectors playing a significant role in determining emission quantities. The Rostov Oblast of Russia demonstrated weaker association between methane emissions and temperatures than Greece and Armenia, with emission trends being primarily shaped by agricultural activities and natural discharges from wetlands. The forecast models predicted further rise in methane emissions over the 7-year period (2024-2030), with the highest elevation rate estimated for Russia. This study emphasizes the need for tailored mitigation strategies to address methane emissions effectively, considering region-specific factors. Advanced monitoring technologies provide crucial insights into the assessment and management of methane emissions in these diverse geomorphological regions.

Learning from history of natural disasters in the Sahel: a comprehensive analysis and lessons for future resilience

One of the first environmental crises to attract interest in development initiatives and aid was the great drought of the 1970s in the Sahel. This study investigates the extent of damage caused by natural disasters from one of the most widely used databases-EM-DAT-with a sample size of 16 Sahelian countries over the period 1960-2020. These countries have been divided into three regions: Western Africa Sahel (WAS), Central Africa Sahel (CAS), and Eastern Africa Sahel (EAS). The analyses encompass four categories of natural hazards, namely, biological, climatological, hydrological, and meteorological. We used descriptive and test statistics to summarize the natural disaster records. Through this approach, we explore tendencies to identify the most frequently reported natural hazards; we examine their spatial distribution and evaluate their impacts in terms of socioeconomic damage and causalities. During the study period, a total of 1000 events were recorded in the database. The Western Africa Sahel (WAS) region had the highest number of disasters, with 476 events, followed by the Eastern Africa Sahel (EAS) region with 369 events. The most common hazards in the Sahel were hydrological (41.8%), mainly floods, and biological (39.5%) hazards. Approximately 300 million people in the Sahel were affected by natural hazards, with 59.17% in EAS, 36.48% in WAS, and 4.35% in CAS. Although droughts occurred less frequently (14%), they had a significant impact on the population, affecting 84% of those affected by natural hazards. In general, EAS experiences a higher impact from natural hazards, potentially influenced by the pastoral lifestyle of its population. However, WAS is also very vulnerable to natural hazards especially epidemics and nowadays floods. The uncontrolled urbanization in the area may contribute to this vulnerability.

Flood Mitigation Measure and Water Storage in East Africa: An Analysis for the Rio Muaguide, Mozambique

In the last century, floods have been more frequently hitting population and human activity, especially in the sub-Saharan context. The aim of this study is to propose suitable flood mitigation measures for the downstream part of the Rio Muaguide, which flows in northern Mozambique. In this terminal part of the river, the bed has been buried by sediment in many reaches; due to the reduction of the section conveyance, wide areas are inundated during the rainy season with negative consequences for several villages relying on subsistence agriculture. The design of any measure requires quantitative determinations but, as many less developed countries, Mozambique is affected by data scarcity. Therefore, in this study global and freely available data have been used to perform hydrologic and two-dimensional hydro-dynamic modelling, finally producing a flood hazard map. Particular care has been put into a critical analysis of several data sources, in terms of their suitability for the purposes of the work. Based on the modelling results and on field evidence, an intervention has been proposed with a double functionality of mitigating the effects of periodic floods and storing water to be used by the agricultural community during drier seasons. The proposed intervention combines restoring a sedimentation-less shape of the river sections and exploiting a natural basin as a storage basin. The methods applied and the intervention proposed for the Rio Muaguide are prototypal for several analogous streams in the coastal portion of Mozambique.

Validation of CHIRPS Precipitation Estimates over Taiwan at Multiple Timescales

The Climate Hazards Group InfraRed Precipitation with Station data (CHIRPS), which incorporates satellite imagery and in situ station information, is a new high-resolution long-term precipitation dataset available since 1981. This study aims to understand the performance of the latest version of CHIRPS in depicting the multiple timescale precipitation variation over Taiwan. The analysis is focused on examining whether CHIRPS is better than another satellite precipitation product—the Integrated Multi-satellitE Retrievals for Global Precipitation Mission (GPM) final run (hereafter IMERG)—which is known to effectively capture the precipitation variation over Taiwan. We carried out the evaluations made for annual cycle, seasonal cycle, interannual variation, and daily variation during 2001–2019. Our results show that IMERG is slightly better than CHIRPS considering most of the features examined; however, CHIRPS performs better than that of IMERG in representing the (1) magnitude of the annual cycle of monthly precipitation climatology, (2) spatial distribution of the seasonal mean precipitation for all four seasons, (3) quantitative precipitation estimation of the interannual variation of area-averaged winter precipitation in Taiwan, and (4) occurrence frequency of the non-rainy grids in winter. Notably, despite the fact that CHIRPS is not better than IMERG for many examined features, CHIRPS can depict the temporal variation in precipitation over Taiwan on annual, seasonal, and interannual timescales with 95% significance. This highlights the potential use of CHIRPS in studying the multiple timescale variation in precipitation over Taiwan during the years 1981–2000, for which there are no data available in the IMERG database.