scholarly journals The potential value of seasonal forecasts in a changing climate in southern Africa

2014 ◽  
Vol 18 (4) ◽  
pp. 1525-1538 ◽  
Author(s):  
H. C. Winsemius ◽  
E. Dutra ◽  
F. A. Engelbrecht ◽  
E. Archer Van Garderen ◽  
F. Wetterhall ◽  
...  
Keyword(s):  
Climate Change ◽  
Heat Stress ◽  
Southern Africa ◽  
Weather Conditions ◽  
Stress Conditions ◽  
Mitigation Measures ◽  
Seasonal Forecasts ◽  
Weather Forecasts ◽  
Dry Spells ◽  
The Future

Abstract. Subsistence farming in southern Africa is vulnerable to extreme weather conditions. The yield of rain-fed agriculture depends largely on rainfall-related factors such as total seasonal rainfall, anomalous onsets and lengths of the rainy season and the frequency of occurrence of dry spells. Livestock, in turn, may be seriously impacted by climatic stress with, for example, exceptionally hot days, affecting condition, reproduction, vulnerability to pests and pathogens and, ultimately, morbidity and mortality. Climate change may affect the frequency and severity of extreme weather conditions, impacting on the success of subsistence farming. A potentially interesting adaptation measure comprises the timely forecasting and warning of such extreme events, combined with mitigation measures that allow farmers to prepare for the event occurring. This paper investigates how the frequency of extreme events may change in the future due to climate change over southern Africa and, in more detail, the Limpopo Basin using a set of climate change projections from several regional climate model downscalings based on an extreme climate scenario. Furthermore, the paper assesses the predictability of these indicators by seasonal meteorological forecasts of the European Centre for Medium-Range Weather Forecasts (ECMWF) seasonal forecasting system. The focus is on the frequency of dry spells as well as the frequency of heat stress conditions expressed in the temperature heat index. In areas where their frequency of occurrence increases in the future and predictability is found, seasonal forecasts will gain importance in the future, as they can more often lead to informed decision-making to implement mitigation measures. The multi-model climate projections suggest that the frequency of dry spells is not likely to increase substantially, whereas there is a clear and coherent signal among the models of an increase in the frequency of heat stress conditions by the end of the century. The skill analysis of the seasonal forecast system demonstrates that there is a potential to adapt to this change by utilizing the weather forecasts, given that both indicators can be skilfully predicted for the December–February season, at least 2 months ahead of the wet season. This is particularly the case for predicting above-normal and below-normal conditions. The frequency of heat stress conditions shows better predictability than the frequency of dry spells. Although results are promising for end users on the ground, forecasts alone are insufficient to ensure appropriate response. Sufficient support for appropriate measures must be in place, and forecasts must be communicated in a context-specific, accessible and understandable format.

scholarly journals The potential value of seasonal forecasts in a changing climate

2013 ◽  
Vol 10 (12) ◽  
pp. 14747-14782 ◽  
Author(s):  
H. C. Winsemius ◽  
E. Dutra ◽  
F. A. Engelbrecht ◽  
E. Archer Van Garderen ◽  
F. Wetterhall ◽  
...  
Keyword(s):  
Climate Change ◽  
Heat Stress ◽  
Weather Conditions ◽  
Stress Conditions ◽  
Mitigation Measures ◽  
Subsistence Farming ◽  
Seasonal Forecasts ◽  
Weather Forecasts ◽  
Dry Spells ◽  
The Future

Abstract. Subsistence farming in Southern Africa is vulnerable to extreme weather conditions. The yield of rain-fed agriculture depends largely on rainfall-related factors such as total seasonal rainfall, anomalous onsets and lengths of the rainy season and the frequency of occurrence of dry spells. Livestock, in turn, may be seriously impacted by climatic stress with, for example, exceptionally hot days, affecting condition, reproduction, vulnerability to pests and pathogens and, ultimately, morbidity and mortality. Climate change may affect the frequency and severity of extreme weather conditions, impacting on the success of subsistence farming. A potentially interesting adaptation measure comprises the timely forecasting and warning of such extreme events, combined with mitigation measures that allow farmers to prepare for the event occurring. This paper investigates how the frequency of extreme events may change in the future due to climate change over southern Africa and, in more detail, the Limpopo basin using a set of climate change projections from several regional climate model downscalings. Furthermore the paper assesses the predictability of these indicators by seasonal meteorological forecasts of the European Centre for Medium-range Weather Forecasts (ECMWF) seasonal forecasting system. The focus is on the frequency of dry spells as well as the frequency of heat stress conditions expressed in the Temperature Heat Index. In areas where their frequency of occurrence increases in the future and predictability is found, seasonal forecasts will gain importance in the future as they can more often lead to informed decision making to implement mitigation measures. The multi-model climate projections suggest that the frequency of dry spells is not likely to increase substantially, whereas there is a clear and coherent signal among the models, of an increase in the frequency of heat stress conditions by the end of the century. The skill analysis of the seasonal forecast system demonstrates that there is a potential to adapt to this change by utilizing the weather forecasts given that both indicators can be skilfully predicted for the December-to-February season, at least two months ahead of the wet season. This is particularly the case for predicting above-normal and below-normal conditions. The frequency of heat stress conditions shows better predictability than the frequency of dry spells. Although results are promising for end users on the ground, forecasts alone are insufficient to ensure appropriate response. Sufficient support for appropriate measures must be in place, and forecasts must be communicated in a context-specific, accessible and understandable format.

scholarly journals Climate Change and Thermal Comfort in Top Tourist Destinations—The Case of Santorini (Greece)

2021 ◽  
Vol 13 (16) ◽  
pp. 9107
Author(s):  
George Katavoutas ◽  
Dimitra Founda ◽  
Gianna Kitsara ◽  
Christos Giannakopoulos
Keyword(s):  
Climate Change ◽  
Heat Stress ◽  
Thermal Environment ◽  
Stress Conditions ◽  
Climate Index ◽  
Mitigation Scenario ◽  
Future Projections ◽  
Tourist Destinations ◽  
The Future ◽  
The Mediterranean

The Mediterranean area is one of the most visited tourist destinations of the world, but it has also been recognized as one of the most vulnerable to climate change areas worldwide with respect to increased thermal risk. The study focuses on a top worldwide tourist destination of the Mediterranean, Santorini Island in Greece, and aims to assess the past, present and future thermal environment in the island based on the advanced Universal Thermal Climate Index (UTCI). The study utilizes historical observations capturing past (late 19th to early 20th century) and more recent (1982–2019) time periods, while future projections are realized based on four regional climate models (RCMs) under the weak mitigation scenario (RCP4.5) and the non-mitigation scenario with high emissions (RCP8.5). The frequency of cold stress conditions at midday decreases during winter and early spring months by up to 19.8% (January) in the recent period compared to the historical one, while heat stress conditions increase in summer by up to 22.4% (August). Future projections suggest progressive shifts of the UTCI towards higher values in the future and an increase in the exposure time under heat stress depending on the RCM and adopted scenario. The increase in moderate and strong heat stress conditions is mainly expected during the summer months (June, July, August); nevertheless, a noticeable increase is also foreseen in September and May. The highest occurrences of favorable (no thermal stress) conditions are also projected to shift by one month, from June to May and from September to October, in the future.

Projecting conflict risk following the Shared Socioeconomic pathways: what role for water stress and climate?

2021 ◽  
Author(s):  
Sophie de Bruin ◽  
Jannis Hoch ◽  
Nina von Uexkull ◽  
Halvard Buhaug ◽  
Nico Wanders
Keyword(s):  
Climate Change ◽  
At Risk ◽  
Machine Learning Techniques ◽  
Mitigation Measures ◽  
Related Factors ◽  
Socioeconomic Impacts ◽  
Learning Techniques ◽  
The Future ◽  
Conflict Risk

<p>The socioeconomic impacts of changes in climate-related and hydrology-related factors are increasingly acknowledged to affect the on-set of violent conflict. Full consensus upon the general mechanisms linking these factors with conflict is, however, still limited. The absence of full understanding of the non-linearities between all components and the lack of sufficient data make it therefore hard to address violent conflict risk on the long-term. </p><p>Although it is neither desirable nor feasible to make exact predictions, projections are a viable means to provide insights into potential future conflict risks and uncertainties thereof. Hence, making different projections is a legitimate way to deal with and understand these uncertainties, since the construction of diverse scenarios delivers insights into possible realizations of the future.  </p><p>Through machine learning techniques, we (re)assess the major drivers of conflict for the current situation in Africa, which are then applied to project the regions-at-risk following different scenarios. The model shows to accurately reproduce observed historic patterns leading to a high ROC score of 0.91. We show that socio-economic factors are most dominant when projecting conflicts over the African continent. The projections show that there is an overall reduction in conflict risk as a result of increased economic welfare that offsets the adverse impacts of climate change and hydrologic variables. It must be noted, however, that these projections are based on current relations. In case the relations of drivers and conflict change in the future, the resulting regions-at-risk may change too.   By identifying the most prominent drivers, conflict risk mitigation measures can be tuned more accurately to reduce the direct and indirect consequences of climate change on the population in Africa. As new and improved data becomes available, the model can be updated for more robust projections of conflict risk in Africa under climate change.</p>

scholarly journals Weather Literacy in Times of Climate Change

2020 ◽  
Vol 12 (3) ◽  
pp. 435-452 ◽  
Author(s):  
Nadine Fleischhut ◽  
Stefan M. Herzog ◽  
Ralph Hertwig
Keyword(s):  
Climate Change ◽  
Weather Conditions ◽  
Extreme Weather ◽  
Extreme Weather Events ◽  
The Public ◽  
Weather Events ◽  
The Future ◽  
Nationally Representative ◽  
And Migration ◽  
Weather Risks

AbstractAs climate change unfolds, extreme weather events are on the rise worldwide. According to experts, extreme weather risks already outrank those of terrorism and migration in likelihood and impact. But how well does the public understand weather risks and forecast uncertainty and thus grasp the amplified weather risks that climate change poses for the future? In a nationally representative survey (N = 1004; Germany), we tested the public’s weather literacy and awareness of climate change using 62 factual questions. Many respondents misjudged important weather risks (e.g., they were unaware that UV radiation can be higher under patchy cloud cover than on a cloudless day) and struggled to connect weather conditions to their impacts (e.g., they overestimated the distance to a thunderstorm). Most misinterpreted a probabilistic forecast deterministically, yet they strongly underestimated the uncertainty of deterministic forecasts. Respondents with higher weather literacy obtained weather information more often and spent more time outside but were not more educated. Those better informed about climate change were only slightly more weather literate. Overall, the public does not seem well equipped to anticipate weather risks in the here and now and may thus also fail to fully grasp what climate change implies for the future. These deficits in weather literacy highlight the need for impact forecasts that translate what the weather may be into what the weather may do and for transparent communication of uncertainty to the public. Boosting weather literacy may help to improve the public’s understanding of weather and climate change risks, thereby fostering informed decisions and mitigation support.

Determination of seasonal forecast skill in identifying extreme events of temperature, wind speed, and SPI

2021 ◽  
Author(s):  
Massimiliano Palma ◽  
Franco Catalano ◽  
Irene Cionni ◽  
Marcello Petitta
Keyword(s):  
Climate Change ◽  
Wind Speed ◽  
Climate Variability ◽  
Extreme Events ◽  
Bias Correction ◽  
Skill Score ◽  
Seasonal Forecast ◽  
Energy Sector ◽  
Seasonal Forecasts ◽  
Weather Forecasts

<p>Renewable energy is the fastest-growing source of electricity globally, but climate variability and impacting events affecting the potential productivity of plants are obstacles to its integration and planning. Knowing a few months in advance the productivity of plants and the impact of extreme events on productivity and infrastructure can help operators and policymakers make the energy sector more resilient to climate variability, promoting the deployment of renewable energy while maintaining energy security.</p><p>The energy sector already uses weather forecasts up to 15 days for plant management; beyond this time horizon, climatologies are routinely used. This approach has inherent weaknesses, including the inability to predict extreme events, the prediction of which is extremely useful to decision-makers. Information on seasonal climate variability obtained through climate forecasts can be of considerable benefit in decision-making processes. The Climate Data Store of the Copernicus Climate Change Service (C3S) provides seasonal forecasts and a common period of retrospective simulations (hindcasts) with equal spatial temporal resolution for simulations from 5 European forecast centres (European Centre for Medium-Range Weather Forecasts (ECMWF), Deutscher Wetterdienst (DWD), Meteo France (MF), UK Met Office (UKMO) and Euro-Mediterranean Centre on Climate Change (CMCC)), one US forecasting centre (NCEP) plus the Japan Meteorological Agency (JMA) model.</p><p>In this work, we analyse the skill and the accuracy of a subset of the operational seasonal forecasts provided by Copernicus C3S, focusing on three relevant essential climate variables for the energy sector: temperature (t2m), wind speed (sfcWind, relevant to the wind energy production), and precipitation. The latter has been analysed by taking the Standard Precipitation Index (SPI) into account.</p><p>First, the methodologies for bias correction have been defined. Subsequently, the reliability of the forecasts has been assessed using appropriate reliability indicators based on comparison with ERA5 reanalysis dataset. The hindcasts cover the period 1993-2017. For each of the variables considered, we evaluated the seasonal averages based on monthly means for two seasons: winter (DJF) and summer (JJA). Data have been bias corrected following two methodologies, one based on the application of a variance inflation technique to ensure the correction of the bias and the correspondence of variance between forecast and observation; the other based on the correction of the bias, the overall forecast variance and the ensemble spread as described in Doblas-Reyes et al. (2005).</p><p>Predictive ability has been assessed by calculating binary (Brier Skill Score, BSS hereafter, and Ranked Probability Skill Score, RPSS hereafter) and continuous (Continuous Ranked Probability Skill Score, CRPSS hereafter) scores. Forecast performance has been assessed using ERA 5 reanalysis as pseudo-observations. </p><p>In this work we discuss the results obtained with different bias correction techniques highlighting the outcomes obtained analyzing the BSS for the first and the last terciles and the first and the last percentiles (10th and 90th). This analysis has the goal to identify the regions in which the seasonal forecast can be used to identify potential extreme events.</p>

Representation of the Angolan low and Southern African Summer Precipitation in the CORDEX and CMIP5 models. 

2021 ◽  
Author(s):  
Sabina Abba-Omar ◽  
Francesca Raffaele ◽  
Erika Coppola ◽  
Daniela Jacob ◽  
Claas Teichmann ◽  
...  
Keyword(s):  
Climate Change ◽  
Regression Analysis ◽  
Southern Africa ◽  
Summer Precipitation ◽  
Precipitation Variability ◽  
Cmip5 Models ◽  
Impact Of Climate Change ◽  
The Future ◽  
Rainfall Patterns ◽  
The Impact

<p>The impact of climate change on precipitation over Southern Africa is of particular interest due to its possible devastating societal impacts. To add to this, simulating precipitation is challenging and models tend to show strong biases over this region, especially during the Austral Summer (DJF) months. One of the reasons for this is the mis-representation of the Angolan Low (AL) and its influence on Southern Africa’s Summer precipitation in the models. Therefore, this study aims to explore and compare different models’ ability to capture the AL and its link to precipitation variability as well as consider the impact climate change may have on this link. We also explore how the interaction between ENSO, another important mode of variability for precipitation, and the Angolan Low, impact precipitation, how the models simulate this and whether this could change in the future under climate change. </p><p>We computed the position and strength of the AL in reanalysis data and compared these results to three different model ensembles with varying resolutions. Namely, the CORDEX-CORE ensemble (CCORE), a new phase of CORDEX simulations with higher resolutions (0.22 degrees), the lower resolution (0.44 degrees) CORDEX-phase 1 ensemble (C44) and the CMIP5 models that drive the two RCM ensembles. We also used Self Organizing Maps to group DJF yearly anomaly patterns and identify which combination of ENSO and AL strength scenarios are responsible for particularly wet or dry conditions. Regression analysis was performed to analyze the relationships between precipitation and the AL and ENSO. This analysis was repeated for near (2041-2060) and far (2080-2099) future climate and compared with the present to understand how the strength of the AL, and its connection to precipitation variability and ENSO, changes in the future. </p><p>We found that, in line with previous studies, models with stronger AL tend to produce more rainfall. CCORE tends to simulate a stronger AL than C44 and therefore, higher precipitation biases. However, the regression analysis shows us that CCORE is able to capture the relationship between precipitation and the AL strength variability as well as ENSO better than the other ensembles. We found that generally dry rainfall patterns over Southern Africa are associated with a weak AL and El Nino event whereas wet rainfall patterns occur during a strong AL and La Nina year. While the models are able to capture this, they also tend to show more neutral ENSO conditions associated with these wet and dry patterns which possibly indicates less of a connection between AL strength and ENSO than seen in the observed results. Analysis of the future results indicates that the AL weakens, this is shown across all the ensembles and could be a contributing factor to some of the drying seen. These results have applications in understanding and improving model representation of precipitation over Southern Africa as well as providing some insight into the impact of climate change on precipitation and some of its associated dynamics over this region.</p>

scholarly journals A Review of Factors to Consider for Permanent Cordon Establishment and Maintenance

Agronomy ◽  
2021 ◽  
Vol 11 (9) ◽  
pp. 1811
Author(s):  
Patrick O’Brien ◽  
Roberta De Bei ◽  
Mark Sosnowski ◽  
Cassandra Collins
Keyword(s):  
Climate Change ◽  
Heat Stress ◽  
Vascular System ◽  
Vascular Diseases ◽  
Stress Conditions ◽  
Normal Flow ◽  
Training Techniques ◽  
Long Term Consequences ◽  
Over Time

Decisions made during the establishment and reworking of permanent cordon arms may have long-term consequences on vineyard health and longevity. This review aims to summarise several of the important considerations that must be taken into account during cordon establishment and maintenance. Commonly practiced cordon training techniques such as wrapping developing arms tightly around the cordon wire may result in a constriction of the vascular system, becoming worse over time and disrupting the normal flow of water and nutrients. Studies have shown that other factors of cordon decline such as the onset of vascular diseases may be influenced by pre-existing stress conditions. Such conditions could be further exacerbated by water and heat stress events, an important consideration as these scenarios become more common under the influence of climate change. Vineyard sustainability may be improved by adopting cordon training techniques which promote long-term vitality and avoid a reduction in vine defence response and the costly, premature reworking of vines.

scholarly journals Heat stress risk in European dairy cattle husbandry under different climate change scenarios – uncertainties and potential impacts

2019 ◽  
Author(s):  
Sabrina Hempel ◽  
Christoph Menz ◽  
Severino Pinto ◽  
Elena Galán ◽  
David Janke ◽  
...  
Keyword(s):  
Climate Change ◽  
Heat Stress ◽  
Dairy Cattle ◽  
Animal Welfare ◽  
Greenhouse Gas ◽  
Milk Yield ◽  
Climate Model ◽  
Stress Conditions ◽  
Gas Concentration ◽  
Cattle Husbandry

Abstract. In the last decades, an exceptional global warming trend was observed. Along with the temperature increase, modifications in the humidity and wind regime amplify the regional and local impacts on livestock husbandry. Direct impacts include the occurrence of climatic stress conditions. In Europe, cows are economically highly relevant and are mainly kept in naturally ventilated buildings that are most susceptible to climate change. The high-yielding cows are particularly vulnerable to heat stress. Modifications in housing management are the main measures taken to improve the ability of livestock to cope with these conditions. Measures are, however, typically taken in direct reaction to uncomfortable conditions instead of in anticipation of a long term risk for climatic stress. Moreover, measures that balance welfare, environmental and economic issues are barely investigated in the context of climate change and are thus almost not available for commercial farms. Quantitative analysis of the climate change impacts on the animal welfare and linked economic and environmental factors are rare. Therefore, we used a numerical modeling approach to estimate the future heat stress risk in such dairy cattle husbandry systems. The indoor climate was monitored inside three reference barns in Central Europe and in the Mediterranean region. An artificial neuronal network (ANN) was trained to relate the outdoor weather conditions provided by official meteorological weather stations to the measured indoor microclimate. Subsequently, this ANN model was driven by an ensemble of regional climate model projections with three different greenhouse gas concentration scenarios. For the evaluation of the heat stress risk, we considered the amount and duration of heat stress events. Based on the changes of the heat stress events various economic and environmental impacts were estimated. We found that the impacts of the projected increase of heat stress risk vary dependent on the region respectively the barn, the climate model and the assumed greenhouse gas concentration. There was an overall increasing trend in number and duration of heat stress events. At the end of the century, the number of annual stress events can be expected to increase by up to 2000 hours while the average duration of the events increases by up to 22 h compared to the end of the last century. This implies strong impacts on economics, environment and animal welfare and an urgent need for mid-term adaptation strategies. We anticipated that up to one tenth of all hours of a year respectively one third of all days will be classified as critical heat stress conditions. Due to heat stress, milk yield may decrease by about 3.5 % relative to the present European milk yield and farmers may expect financial losses in the summer season of about 6.6 % of their monthly income. In addition, an increasing demand for emission reduction measures must be expected, as an emission increase of about 16 Gg ammonia and 0.1 Gg methane per year can be expected under the anticipated heat stress conditions. The cattle respiration rate increases by up to 60 % and the standing time may be prolonged by 1 h. This promotes health issues and increases the probability of medical treatments. The various impacts imply feedback loops in the climate system which are presently underexplored. Hence, future in-depth studies on the different impacts and adaptation options at different stress levels are highly recommended.

Climate Change and Agriculture

2016 ◽  
pp. 393-415 ◽  
Author(s):  
Sunil Lalasaheb Londhe
Keyword(s):  
Climate Change ◽  
Atmospheric Carbon Dioxide ◽  
Crop Production ◽  
Agricultural Sector ◽  
Great Depth ◽  
Mitigation Measures ◽  
Agriculture Sector ◽  
The Future ◽  
Food Security And Nutrition ◽  
Earth’S Climate

Increasing evidence shows that shifts in Earth's climate have already occurred and indicates that changes will continue in the coming years. This chapter is an attempt to distil what is known about the likely effects of climate change on food security and nutrition in coming decades. Apart from few exceptions, the likely impacts of climate change on agricultural sector in the future are not understood in any great depth. There are many uncertainties as to how changes in temperature, rainfall and atmospheric carbon dioxide concentrations will interact in relation to agricultural productivity. The consequences of climate change on various important aspects of agriculture such as crop production, livestock, availability of water, pest and diseases etc. are discussed and summarized. Each of this aspect of agriculture sector will have certain impact which may be positive or negative. The chapter also discusses on the possible mitigation measures and adaptations for agriculture production in the future climate change scenarios.

Increasing adaptation to climate stress by applying conservation agriculture in Southern Africa.

2022 ◽  
pp. 270-283
Author(s):  
Christian Thierfelder ◽  
Peter Steward
Keyword(s):  
Climate Change ◽  
Soil Moisture ◽  
Heat Stress ◽  
Drought Stress ◽  
Southern Africa ◽  
Smallholder Farmers ◽  
Conservation Agriculture ◽  
Crop Productivity ◽  
Soil Disturbance ◽  
On Farm

Abstract Climate change and soil fertility decline are threatening food security in southern Africa and efforts have been made to adapt current cropping systems to the needs of smallholder farmers. Conservation Agriculture (CA) based on minimum soil disturbance, crop residue retention and crop diversification has been proposed as a strategy to address the challenges smallholder farmers face. Here we analyse the potential contributions of CA towards adaptation to the effects of climate change by summarizing data on infiltration, soil moisture dynamics and crop productivity under heat and drought stress. The data were taken in the main from CIMMYT's on-farm and on-station trial network. Data show that CA systems maintain 0.7-7.9 times higher water infiltration than the conventional tilled system depending on soil type, which increases soil moisture during the cropping season by 11%-31% between CA treatments and the conventional control treatment. This leads to greater adaptive capacity of CA systems during in-season dry spells and under heat stress. A supporting regional maize productivity assessment, analysing the results of numerous on-farm and on-station experiments, showed that CA systems will outperform conventional tillage practices (CP), especially on light-textured soils, under heat and drought stress. With higher rainfall and low heat stress, this relation was more positive towards CP and on clay soil there was no benefit of practising CA when rainfall was high. The long dry season and limited biomass production of CA systems in southern Africa require complementary good agricultural practices to increase other soil quality parameters (e.g. increased soil carbon) to maintain higher productivity and sustainability over time. This can be addressed by combinations of improved stress-tolerant seed, targeted fertilization, inclusion of tree-based components or green manure cover crops in the farming system, scale-appropriate mechanization and improved weed control strategies.

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