Seasonal rainfall is critical to lives and livelihoods within the Horn of Africa drylands (HAD), but it is highly variable in space and time. The main HAD rainfall seasons are typically defined as March–May (MAM) and October–December (OND). However, these 3-month periods are only generalized definitions of seasonality across the HAD, and local experience of rainfall may depart from these substantially. Here, we use daily rain gauge data with a duration of at least 10 years from 69 stations across the drylands of Kenya, Somalia, and Ethiopia to locally delineate key rainfall seasons. By calculating local seasonal rainfall timings, totals, and extremes, we obtain more accurate estimates of the spatial variability in rainfall delivery across the HAD, as well as climatological patterns. Results show high spatial variability in season onset, cessation, and length across the region, indicating that a homogenous classification of rainfall seasons across the HAD (e.g., MAM and OND) is inadequate for representing local rainfall characteristics. Our results show that the “long rains” season is not significantly longer than the “short rains” season over the period of study. This could be related to the previously documented decline of the “long rains” seasonal totals over recent decades. Several rainfall metrics also vary spatially between seasons, and the rainfall on the most extreme days can accumulate to double the local mean seasonal total. The locally defined rainfall seasons better capture the bulk of the rainfall during the season, giving improved characterization of rainfall metrics, consistent with the aim of a better understanding of rainfall impacts on local communities.

Somalia, with almost 2/3 of its land devoted to agriculture and livestock rearing, is facing the negative impacts of uncontrolled deforestation activities. A key driver of such a trend is the extensive and often illicit charcoal production, which leads to forest degradation dynamics and the depletion of the country's woody resources. To monitor and quantify these tendencies, remote sensing offers many advantages in terms of temporal and spatial coverage. Our study aimed to develop a workflow capable of integrating optical (Sentinel-2) and radar (Sentinel-1) imagery to detect charcoal production sites (i.e., kilns) in Somalia. Most of the processing was implemented in Google Earth Engine, enabling it to be fully replicable and easily scalable to other regions. Southern Somalia (Jubbaland State, approx. 110200 km2) was chosen as the test area since charcoal exploitation represents a critical issue in the region. Furthermore, a very detailed dataset, produced by the Food and Agriculture Organization (FAO-SWALIM) through photo-interpretation of kilns’ presence, was available for the area. Our methodology started by producing a single image containing both optical (NDVI) and radar (VV and VH polarizations) information over the first three months of 2016 and 2017. Subsequently, we calculated the difference between the two images and extracted the pixel values in correspondence with the known charcoal sites. Based on the extracted values, different thresholds (e.g., the mean +/- a set number of standard deviations) were tested for classifying the difference image. The results consisted of binary maps at 10 m resolution, showing locations with kilns’ presence or absence. A confusion matrix was used to evaluate the classifications. Overall accuracy reached almost 70% in some cases, while sensitivity and specificity were more variable (0.4 to 0.9), depending on the utilized threshold. Particularly, some of the classifications proved to be very balanced, with values around 0.7 for all three parameters of accuracy, sensitivity, and specificity. Our results demonstrate that a multi-sensor remote sensing approach is a valuable and reliable tool to monitor and quantify forest degradation dynamics, particularly considering the socio-political context of some countries, where in situ data collection is often difficult, when not dangerous.

Hydro-Meteorological Hazards, Risks, and Disasters, 2e, provides an integrated look at the major disasters that have had, and continue to have, major implications for many of the world’s people, such as floods and droughts. This new edition takes a geoscientific approach to the topic, while also covering current thinking about some scientific issues that are socially relevant and can directly affect human lives and assets. This new edition showcases both academic and applied research conducted in developed and developing countries, allowing readers to see the most updated flood and drought modeling research and their applications in the real world, including for humanitarian emergency purposes. Hydro-Meteorological Hazards, Risks, and Disasters, 2e, also contains new insights about how climate change affects hazardous processes. For the first time, information on the many diverse topics relevant to professionals is aggregated into one volume. It is a valuable reference to researchers, graduates, scientists, physical geographers, urban planners, landscape architects, and other people who work on the build environments of the world. Cutting-edge discussion of natural hazard topics that affect the lives and livelihoods of millions of people worldwide Includes numerous full-color tables, GIS maps, diagrams, illustrations, and photographs of hazardous process in action Provides case studies of prominent hydro-meteorological hazards and disasters

Long and temporally consistent rainfall time series are essential in climate analyses and applications. Rainfall data from station observations are inadequate over many parts of the world due to sparse or non‐existent observation networks, or limited reporting of gauge observations. As a result, satellite rainfall estimates have been used as an alternative or as a supplement to station observations. However, many satellite‐based rainfall products with long time series suffer from coarse spatial and temporal resolutions and inhomogeneities caused by variations in satellite inputs. There are some satellite rainfall products with reasonably consistent time series, but they are often limited to specific geographic areas. The Climate Hazards Group Infrared Precipitation (CHIRP) and CHIRP combined with station observations (CHIRPS) are recently produced satellite‐based rainfall products with relatively high spatial and temporal resolutions and quasi‐global coverage. In this study, CHIRP and CHIRPS were evaluated over East Africa at daily, dekadal (10‐day) and monthly time‐scales. The evaluation was done by comparing the satellite products with rain‐gauge data from about 1,200 stations. The CHIRP and CHIRPS products were also compared with two similar operational satellite rainfall products: the African Rainfall Climatology version 2 (ARC2) and the Tropical Applications of Meteorology using Satellite data (TAMSAT). The results show that both CHIRP and CHIRPS products are significantly better than ARC2 with higher skill and low or no bias. These products were also found to be slightly better than the latest version of the TAMSAT product at dekadal and monthly time‐scales, while TAMSAT performed better at the daily time‐scale. The performance of the different satellite products exhibits high spatial variability with weak performances over coastal and mountainous regions.

In Somalia, challenges related to energy access is influenced by both weather and climate extremes and associated conflict. The objective of this article is to gain an improved understanding of these risks and challenges, which are faced by the most vulnerable populations in the country. In particular, cooking energy-related challenges faced by households affected by weather and climate extremes and conflicts include protection risks, malnutrition, health risks, environmental degradation and heightened tension and conflict between social groups. Interventions to address these issues should focus on both fuel supply and fuel demand as well as on improving the livelihoods of affected populations. In the aftermath of an extreme weather event it is recommended that assessments of the energy needs of all affected populations, including both hosts and Internally Displaced People (IDPs), be conducted. Post-disaster support should include the promotion of energy-efficient technologies for cooking as well as alternative sources of fuel where available, including non-wood based renewable energy. The implementation of a field inventory to assess the status of natural resources in areas vulnerable to climate impacts could help to determine woody biomass trends and enable the development of ecosystem restoration plans. These could include provisions for the establishment of woodlots and agro-forestry, thus building resilience to environmental degradation while maintaining woody biomass resources in and around displacement camps. Interventions should also be designed jointly with partners, and activities should be conflict-sensitive to ensure an enhanced state of resiliency and preparedness among vulnerable populations.