This study examines the effects of 1.5°C and 2°C global warming levels (GWLs) on intra-seasonal rainfall characteristics over the Greater Horn of Africa. The impacts are analysed based on the outputs of a 25-member regional multi-model ensemble from the Coordinated Regional Climate Downscaling Experiment project. The regional climate models were driven by Coupled Model Intercomparison Project Phase 5 Global Climate Models for historical and future (RCP8.5) periods. We analyse the three major seasons over the region, namely March-May, June-September, and October-December. Results indicate widespread robust changes in the mean intra-seasonal rainfall characteristics at 1.5°C and 2°C GWLs especially for the June-September and October-December seasons. The March-May season is projected to shift for both GWL scenarios with the season starting and ending early. During the June-September season, there is a robust indication of delayed onset, reduction in consecutive wet days and shortening of the length of rainy season over parts of the northern sector under 2°C GWL. During the October-December season, the region is projected to have late-onset, delayed cessation, reduced consecutive wet days and a longer season over most of the equatorial region under the 2°C GWL. These results indicate that it is crucial to limit the GWL to below 1.5°C as the differences between the 1.5°C and 2°C GWLs in some cases exacerbates changes in the intra-seasonal rainfall characteristics over the Greater Horn of Africa.
The magnitude and trend of temperature and rainfall extremes as indicators of climate variability and change were investigated in the Arid and Semi-Arid Lands (ASALs) of Kenya using in-situ measurements and gridded climate proxy datasets, and analysed using the Gaussian-Kernel analysis and the Mann-Kendall statistics. The results show that the maximum and minimum temperatures have been increasing, with warmer temperatures being experienced mostly at night time. The average change in the mean maximum and minimum seasonal surface air temperature for the region were 0.74˚C and 0.60˚C, respectively between the 1961-1990 and 1991-2013 periods. Decreasing but statistically insignificant trends in the seasonal rainfall were noted in the area, but with mixed patterns in variability. The March-April-May rainfall season indicated the highest decrease in the seasonal rainfall amounts. The southern parts of the region had a decreasing trend in rainfall that was greater than that of the northern areas. The results of this study are expected to support sustainable pastoralism system prevalent with the local communities in the ASALs.
<div> <p><span>The regions of east Africa are facing unprecedented drought impacts at present and it is expected to intensify with climate change. Impact based forecast can give critical information for disaster preparedness, adaptation, and anticipatory action thereby increasing communities&#8217; resilience. Probabilistic forecasts with uncertainty metrics have in the past provided early warning information for early actions. However, the complexity of drought as a disaster, encompassing and effecting wide range of socio-economic activities with interlinked compounding and cascading effect often makes drought impact forecasting bound to be less effective and robust (Boult et al. 2022). Moreover, drought impacts which are subjected to the influence of other high-impact weather related events, increases the difficulty to ascertain the extent of the impact. Therefore, drought impact forecasting should be viewed as a dynamic process that involves multi-stakeholders to realize its full potential of triggering early action (de Brito 2021). In such a scenario, the availability of an open, and widely accessible information portal can be effective in ensuring early waning information is disseminated widely across all stakeholders to trigger timely action. &#160;</span><span>&#160;</span></p> </div><div> <p><span>This study demonstrates an automatic impact-based drought forecast system to be integrated with existing East Africa Drought Watch (EADW) web portal. For the last two-to-three years, EADW has proven to be single window portal for major hazard related information dissemination for disaster early warning and action. The proposed automatic impact-based drought forecast system is based on TMAST ALERT probabilistic soil moisture and Water Requirement Satisfaction Index (WRSI) forecast using their data Application Programming Interface (API). TAMSAT ALERT is region specific validated, calibrated data source and its effectiveness assessed in impact-based forecast for the region (Boult et al. 2020, Busker et. al 2022). CLIMADA, an open-source software for climate risk assessment was used for integrating the soil moisture hazard data with exposure, and vulnerability to forecast socio-economic impact of drought. The current version of the system, directed for agriculture drought IBF, uses Spatially-Disaggregated Crop Production Statistics Data in Africa and WRSI maize crop unimodal relationship as impact function. The probabilistic forecast of WRSI is used to generate the Impact Based Forecasting (IBF), impact versus probability matrix for region specific map generation. &#160;Finally, implications for early warning and early action on agricultural practices in the Eastern Africa region are discussed. </span><span>&#160;</span></p> </div><div> <p><span>1. Boult, Victoria L., et al. "Towards drought impact-based forecasting in a multi-hazard context." Climate Risk Management 35 (2022): 100402.</span><span>&#160;</span></p> <p><span>2. de Brito, Mariana Madruga. "Compound and cascading drought impacts do not happen by chance: A proposal to quantify their relationships." Science of the Total Environment 778 (2021): 146236.&#8203;&#160;</span></p> </div><div> <p><span>3. </span><span>Boult, Victoria L., et al. "Evaluation and validation of TAMSAT&#8208;ALERT soil moisture and WRSI for use in drought anticipatory action." Meteorological Applications 27.5 (2020): e1959.</span><span>&#160;</span></p> </div><div> <p><span>4. </span><span>Busker, T., de Moel, H., van den Hurk, B., Asfaw, D., Boult, V., and Aerts, J.: Impact-based drought forecasting for agro-pastoralists in the Horn of Africa drylands, IAHS-AISH Scientific Assembly 2022, Montpellier, France, 29 May&#8211;3 Jun 2022, IAHS2022-255, https://doi.org/10.5194/iahs2022-255, 2022.</span><span>&#160;</span></p> </div>
Other experts point to a more conservative estimate with global average losses falling in the range between 15-20 percent. Of course, in localised settings, untreated pest damage could vary widely, reaching as high as 100% in the case of locust swarms, for instance. Of further note, pesticide use might increase losses because it can lead to pest resurgence and resistance. 4 FAO. Climate Related Transboundary Pests and Diseases.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.