Climate extremes are widely projected to become more severe as the global climate continues to warm due to anthropogenic greenhouse gas emissions. These extremes often cause the most severe impacts ...on society. Therefore, the extent to which the extremes might change at regional level as the global climate warms from current levels to proposed policy targets of 1.5 and 2.0 °C above preindustrial levels need to be understood to allow for better preparedness and informed policy formulation. This paper analysed projected changes in temperature and precipitation extremes at 1.0, 1.5 and 2.0 °C warming over Botswana, a country highly vulnerable to the impacts of climate change. Projected changes in temperature extremes are significantly different from each other at the three levels of global warming, across three main climatic zones in the country. Specifically, at 2.0 °C global warming relative to preindustrial, for the ensemble median: (a) country average warm spell duration index increases by 80, 65, 62 days per year across different climatic zones, approximately three (and two) times the change at 1.0 (1.5) °C; (b) cold night (TN10P) and cold day (TX10P) frequencies decrease by 12 and 9 days per year across all regions, respectively, while hot nights (TN90P) and hot days (TX90P) both increase by 8-9 days across all regions. Projected changes in drought-related indices are also distinct at different warming levels. Specifically: (a) projected mean annual precipitation decreases across the country by 5%-12% at 2 °C, 3%-8% at 1.5 °C and 2%-7% at 1.0 °C; (b) dry spell length (ALTCDD) increases by 15-19 days across the three climatic zones at 2.0 °C, about three (and two) times as much as the increase at 1.0 (1.5) °C. Ensemble mean projections indicate increases in heavy rainfall indices, but the inter-model spread is large, with no consistent direction of change, and so changes are not statistically significant. The implications of these changes in extreme temperature and precipitation for key socio-economic sectors are explored, and reveal progressively severe impacts, and consequent adaptation challenges for Botswana as the global climate warms from its present temperature of 1.0 °C above preindustrial levels to 1.5 °C, and then 2.0 °C.
We used the regional climate model RegCM3 to investigate the role of the swamps of southern Sudan in affecting the climate of the surrounding region. Towards this end, we first assessed the ...performance of a high resolution version of the model over northern Africa. RegCM3 shows a good skill in simulating the climatology of rainfall and temperature patterns as well as the related circulation features during the summer season, outperforming previous coarser resolution applications of the model over this region. Sensitivity experiments reveal that, relative to bare soil conditions, the swamps act to locally modify the surface energy budget primarily through an increase of surface latent heat flux. Existence of the swamps leads to lower ground temperature (up to 2 °C), a larger north–south temperature gradient, and increased local rainfall (up to 40 %). Of particular importance is the impact on rainfall in the surrounding regions. The swamps have almost no impact on the rainfall over the source region of the Nile in Ethiopia or in the Sahel region; however, they favor wetter conditions over central Sudan (up to 15 %) in comparison to the bare desert soil conditions.
We analyze the potential effect of global warming levels (GWLs) of 1.5 °C and 2 °C above pre-industrial levels (1861−1890) on mean temperature and precipitation as well as intra-seasonal ...precipitation extremes over the Greater Horn of Africa. We used a large, 25-member regional climate model ensemble from the Coordinated Regional Downscaling Experiment and show that, compared to the control period of 1971−2000, annual mean near-surface temperature is projected to increase by more than 1 °C and 1.5 °C over most parts of the Greater Horn of Africa, under GWLs of 1.5 °C and 2 °C respectively. The highest temperature increases are projected in the northern region, covering most parts of Sudan and northern parts of Ethiopia, and the lowest temperature increases are projected over the coastal belt of Tanzania. However, the projected mean surface temperature difference between 2 °C and 1. 5 °C GWLs is higher than 0.5 °C over nearly all land points, reaching 0.8 °C over Sudan and northern Ethiopia. This implies that the Greater Horn of Africa will warm faster than the global mean. While projected changes in precipitation are mostly uncertain across the Greater Horn of Africa, there is a substantial decrease over the central and northern parts of Ethiopia. Additionally, the length of dry and wet spells is projected to increase and decrease respectively. The combined effect of a reduction in rainfall and the changes in the wet and dry spells will likely impact negatively on the livelihoods of people within the coastal cities, lake regions, highlands as well as arid and semi-arid lands of Kenya, Tanzania, Somalia, Ethiopia and Sudan. The probable impacts of these changes on key sectors such as agriculture, water, energy and health sectors, will likely call for formulation of actionable policies geared towards adaptation and mitigation of the impacts of 1.5 °C and 2 °C warming.
Two hyper-arid regions (Atbara and Kassala stations) in Sudan.
The study aims to evaluate the potential of the D-vine Copula-based quantile regression (DVQR) model for estimating daily ETo during ...2000–2015 based on various input structures. Further, the DVQR model was compared with Multivariate Linear quantile regression (MLQR), Bayesians Model Averaging quantile regression (BMAQR), Empirical Models (EMMs), and Classical Machine Learning (CML). Besides, the CML models including Random Forest (RF), Support Vector Machine (SVM), Extreme Learning Machine (ELM), Extreme Gradient Boosting (XGBoost), and M5 Model Tree (M5Tree) were employed.
The original EMMs showed poor performance, which improved after calibration techniques. The DVQR, MLQR, and BMAQR models showed better performance than the calibrated EMMs. However, the DVQR model exhibited the highest accuracy than the MLQR and BMAQR models over two study sites. The M5Tree, SVM, and XGBoost models perfumed better than ELM and RF models at both study sites. The DVQR and XGBoost models showed equivalent performance (R2, NSE, and WIA > 0.99, MAE, and RMSE < 0.2) to the M5Tree and SVM models, but they had significantly more accuracy than the calibrated EMMs, MLQR, BMAQR, ELM, and RF models in two hyper-arid regions. Overall, the high dimensional DVQR model is recommended as a promising alternative technique for estimating daily ETo in hyper-arid climate conditions around the world.
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•The D-vine copula quantile regression (DVQR) was used for ETo estimation.•The ability of DVQR was compared with empirical and machine learning approaches.•The nonlinear DVQR outperforms the multiple linear QR in daily ETo estimation.•Two hyper-arid regions in Sudan were studied for ETo estimation.
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.
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•We evaluated multiple precipitation and ETa products over the Nile Basin.•CHIRPSv2 was the best-performing precipitation product.•PMLv2 and WaPORv2.1 were the best-performing ETa ...products.•We incorporated GRACE data to evaluate these products at the monthly scale.•Monthly changes in storage were captured better over the White Nile than Blue Nile.
Nile Basin, Africa.
The accurate representation of precipitation (P) and actual evapotranspiration (ETa) patterns is crucial for water resources management, yet there remains a high spatial and temporal variability among gridded products, particularly over data-scarce regions. We evaluated the performance of eleven state-of-the-art P products and seven ETa products over the Nile Basin using a four-step procedure: (i) P products were evaluated at the monthly scale through a point-to-pixel approach; (ii) streamflow was modelled using the Random Forest machine learning technique, and simulated for well-performing catchments for 2009–2018 (to correspond with ETa product availability); (iii) ETa products were evaluated at the multiannual scale using the water balance method; and (iv) the ability of the best-performing P and ETa products to represent monthly variations in terrestrial water storage (ΔTWS) was assessed through a comparison with GRACE Level-3 data.
CHIRPSv2 was the best-performing P product (median monthly KGE’ of 0.80) and PMLv2 and WaPORv2.1 the best-performing ETa products over the majority of the evaluated catchments. The application of the water balance using these best-performing products captures the seasonality of ΔTWS well over the White Nile Basin, but overestimates seasonality over the Blue Nile Basin. Our study demonstrates how gridded P and ETa products can be evaluated over extremely data-scarce conditions using an easily transferable methodology.
West African rainfed agriculture is highly vulnerable to climate variability and change. Global warming is projected to result in higher regional warming and have a strong impact on agriculture. This ...study specifically examines the impact of global warming levels (GWLs) of 1.5°, 2° and 3 °C relative to 1971-2000 on crop suitability over West Africa. We used 10 Coupled Model Intercomparison Project Phase5 Global Climate Models (CMIP5 GCMs) downscaled by Coordinated Regional Downscaling Experiment (CORDEX) Rossby Centre's regional Atmospheric model version 4, RCA4, to drive Ecocrop, a crop suitability model, for pearl millet, cassava, groundnut, cowpea, maize and plantain. The results show Ecocrop simulated crop suitability spatial representation with higher suitability, observed to the south of latitude 14°N and lower suitability to its north for 1971-2000 for all crops except for plantain (12°N). The model also simulates the best three planting months within the growing season from September-August over the past climate. Projected changes in crop suitability under the three GWLs 1.5-3.0 °C suggest a spatial suitability expansion for legume and cereal crops, notably in the central southern Sahel zone; root and tuber and plantain in the central Guinea-Savanna zone. In contrast, projected decreases in the crop suitability index value are predicted to the south of 14°N for cereals, root and tuber crops; nevertheless, the areas remain suitable for the crops. A delay of between 1-3 months is projected over the region during the planting month under the three GWLs for legumes, pearl millet and plantain. A two month delay in planting is projected in the south, notably over the Guinea and central Savanna zone with earlier planting of about three months in the Savanna-Sahel zones. The effect of GWL2.0 and GWL3.0 warming in comparison to GWL1.5 °C are more dramatic on cereals and root and tuber crops, especially cassava. All the projected changes in simulated crop suitability in response to climatic variables are statistically significant at 99% confidence level. There is also an increasing trend in the projected crop suitability change across the three warming except for cowpea. This study has implications for improving the resilience of crop production to climate changes, and more broadly, to food security in West Africa.
Developing countries share many common challenges in addressing current and future climate risks. A key barrier to managing these risks is the limited availability of accessible, reliable and ...relevant weather and climate information. Despite continued investments in Earth System Modelling, and the growing provision of climate services across Africa and India, there often remains a mismatch between available information and what is needed to support on-the-ground decision-making. In this paper, we outline the range of currently available information and present examples from Africa and India to demonstrate the challenges in meeting information needs in different contexts. A review of literature supplemented by interviews with experts suggests that externally provided weather and climate information has an important role in building on local knowledge to shape understanding of climate risks and guide decision-making across scales. Moreover, case studies demonstrate that successful decision-making can be achieved with currently available information. However, these successful examples predominantly use daily, weekly and seasonal climate information for decision-making over short time horizons. Despite an increasing volume of global and regional climate model simulations, there are very few clear examples of long-term climate information being used to inform decisions at sub-national scales. We argue that this is largely because the information produced and disseminated is often ill-suited to inform decision-making at the local scale, particularly for farmers, pastoralists and sub-national governments. Even decision-makers involved in long-term planning, such as national government officials, find it difficult to plan using decadal and multi-decadal climate projections because of issues around uncertainty, risk averseness and constraints in justifying funding allocations on prospective risks. Drawing on lessons learnt from recent successes and failures, a framework is proposed to help increase the utility and uptake of both current and future climate information across Africa and India.
The participating member nations in Paris at the 2015 convention of the United Nations Framework Convention on Climate Change (UNFCCC) resolved to maintain the rise in global average temperature to a ...level much less than 2.0 °C compared to pre-industrial levels. It was also committed that the parties would continue with all-out endeavor to limit warming to 1.5 °C. For a country like India with a primarily agrarian economy this leads to two key questions. Firstly, what does the global rise of mean annual temperature (1.5 °C and 2.0 °C) mean at the regional scale? Secondly, what are the implications of keeping warming at or below 1.5 °C for different sectors and in particular on agriculture and water resources? To address these questions we have examined the annual and seasonal impacts of 1.5 °C and 2 °C global temperature rise (GTR) on temperature and rainfall change over all the states of India under two Representative concentration pathways, RCP 8.5 and RCP 4.5, using all Coupled Model Inter Comparison Project CMIP5 Models. Rainfall is projected to increase over all the states with very low change in the western part of the country and highest change in the North eastern and southern region of the country under RCP 8.5. 35% of the country is projected to witness a temperature change equal to or lesser than global mean temperature of 1.5 °C and 2.0 °C whereas 65% is expected to show a greater rise in temperature. The most severe temperature change is expected to be witnessed by the presently colder Northern most states of India such as Jammu and Kashmir, Himachal Pradesh and Uttaranchal (2.0 °C to 2.2 °C at 1.5 °C and 2.5 °C to 2.8 °C at 2.0 °C) in both RCPs. There are opportunities and threats due to climate change and it is imperative for researchers and policy makers to recognize these in the context of the scenarios of 1.5 °C and 2.0 °C global temperature changes. It is essential for the current national and state action plan on climate change and adaptation to be more sensitive in strategizing an efficient response to the different scenarios at the global level (3 °C, 2 °C and 1.5 °C) in order to take more informed policy decisions at global level in synergy with the regional analysis to be able to develop strategies that benefit the local populace.
EARTH SYSTEM SCIENCE FRONTIERS Rauser, Florian; Alqadi, Mohammad; Arowolo, Steve ...
Bulletin of the American Meteorological Society,
06/2017, Letnik:
98, Številka:
6
Journal Article
Recenzirano
Odprti dostop
The exigencies of the global community toward Earth system science will increase in the future as the human population, economies, and the human footprint on the planet continue to grow. This growth, ...combined with intensifying urbanization, will inevitably exert increasing pressure on all ecosystem services. A unified interdisciplinary approach to Earth system science is required that can address this challenge, integrate technical demands and long-term visions, and reconcile user demands with scientific feasibility. Together with the research arms of the World Meteorological Organization, the Young Earth System Scientists community has gathered early-career scientists from around the world to initiate a discussion about frontiers of Earth system science. To provide optimal information for society, Earth system science has to provide a comprehensive understanding of the physical processes that drive the Earth system and anthropogenic influences. This understanding will be reflected in seamless prediction systems for environmental processes that are robust and instructive to local users on all scales. Such prediction systems require improved physical process understanding, more high-resolution global observations, and advanced modeling capability, as well as high-performance computing on unprecedented scales. At the same time, the robustness and usability of such prediction systems also depend on deepening our understanding of the entire Earth system and improved communication between end users and researchers. Earth system science is the fundamental baseline for understanding the Earth’s capacity to accommodate humanity, and it provides a means to have a rational discussion about the consequences and limits of anthropogenic influence on Earth. Without its progress, truly sustainable development will be impossible.
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