We analyze data of 27 global climate models from the sixth phase of the Coupled Model Intercomparison Project (CMIP6), and examine projected changes in temperature and precipitation over the African continent during the twenty-first century. The temperature and precipitation changes are computed for two future time slices, 2030–2059 (near term) and 2070–2099 (long term), relative to the present climate (1981–2010), for the entire African continent and its eight subregions. The CMIP6 multi-model ensemble projected a continuous and significant increase in the mean annual temperature over all of Africa and its eight subregions during the twenty-first century. The mean annual temperature over Africa for the near (long)-term period is projected to increase by 1.2 °C (1.4 °C), 1.5 °C (2.3 °C), and 1.8 °C (4.4 °C) under the Shared Socioeconomic Pathways (SSPs) for weak, moderate, and strong forcing, referenced as SSP1-2.6, SSP2-4.5, and SSP5-8.5, respectively. The future warming is not uniform over Africa and varies regionally. By the end of the twenty-first century, the largest rise in mean annual temperature (5.6 °C) is projected over the Sahara, while the smallest rise (3.5 °C) is over Central East Africa, under the strong forcing SSP5-8.5 scenario. The projected boreal winter and summer temperature patterns for the twenty-first century show spatial distributions similar to the annual patterns. Uncertainty associated with projected temperature over Africa and its eight subregions increases with time and reaches a maximum by the end of the twenty-first century. On the other hand, the precipitation projections over Africa during the twenty-first century show large spatial variability and seasonal dependency. The northern and southern parts of Africa show a reduction in precipitation, while the central parts of Africa show an increase, in future climates under the three reference scenarios. For the near (long)-term periods, the area-averaged precipitation over Africa is projected to increase by 6.2 (4.8)%, 6.8 (8.5)%, and 9.5 (15.2)% under SSP1-2.6, SSP2-4.5, and SSP5-8.5, respectively. The median warming simulated by the CMIP6 model ensemble remains higher than the CMIP5 ensemble over most of Africa, reaching as high as 2.5 °C over some regions, while precipitation shows a mixed spatial pattern.

This paper describes a convective system, which brought heavy rainfall leading towards a flash flood on November 25, 2009, over Jeddah city and its surrounding regions. Meteosat Second Generation Spinning Enhanced Visible and Infrared Imager (MSG‐SEVIRI) based near‐real‐time MSG‐RGB (red, green, blue) composites and cloud top temperature images are used for the assessment of convection stages during the event. Tropical Rainfall Measuring Mission (TRMM) data is used to quantify the rainfall amount and found reliable as compared with ground observations. Air mass RGB serves as an effective tool for the visual enhancement of cumulonimbus (Cb) clouds as well as differentiating them from other local features. Cloud top temperatures obtained from MSG IR10.8 channel show that the threshold values of cloud top below 220°K can lead to rainfall with the intensity of 10 mm/hr or above over Jeddah region. The results from MSG‐SEVIRI and TRMM satellite data show that satellite data could serve as an effective tool for the near real‐time monitoring of the rainfall event, when analysing convection stages. The study suggests that where ground measurements are minimal, satellite information can be used in as part of a flood warning system to minimise the aftermaths of a flood disaster.

Recently, dust has created many problems, including negative effects on health, and environmental and economic costs, for people who live both near to and far from sources of dust. The aim of this study is to evaluate and quantify the impact of dust sources located inside Saudi Arabia on the physical growth and vegetation status of cities. In order to do so, satellite data sets, simulated surface data, and soil data for Saudi Arabia from 2000 to 2021 were used. In the first step, a dust sources map of the study area was generated using multi-criteria decision analysis. Land surface temperature (LST), vegetation cover, soil moisture, precipitation, air humidity, wind speed, and soil erodibility factors were considered as effective criteria in identifying dust sources. In the second step, built-up land and vegetation status maps of major cities located at different distances from dust sources were generated for different years based on spectral indicators. Then, the spatiaotemporal change of built-up land and vegetation status of the study area and major cities were extracted. Finally, impacts of major dust sources on urban physical growth and vegetation were quantified. The importance degrees of soil erodibility, wind speed, soil moisture, vegetation cover, LST, air humidity, and precipitation to identify dust sources were 0.22, 0.20, 0.16, 0.15, 0.14, 0.07, and 0.05, respectively. Thirteen major dust sources (with at least 8 years of repetition) were identified in the study area based on the overlap of the effective criteria. The identified major dust sources had about 300 days with Aerosol Optical Depth (AOD) values greater than 0.85, which indicates that these dust sources are active. The location of the nine major dust sources identified in this study corresponds to the location of the dust sources identified in previous studies. The physical growth rates of cities located 400 km from a major dust source (DMDS) are 46.2% and 95.4%, respectively. The reduction rates of average annual normalized difference vegetation index (NDVI) in these sub-regions are 0.006 and 0.002, respectively. The reduction rate of the intensity of vegetation cover in the sub-region close to dust sources is three times higher than that of the sub-region farther from dust sources. The coefficients of determination (R²) between the DMDS and urban growth rate and the NDVI change rate are 0.52 and 0.73, respectively, which indicates that dust sources have a significant impact on the physical growth of cities and their vegetation status.