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Localize the Impact of Global Greenhouse Gases Emissions under an Uncertain Future: A Case Study in Western Cape, South Africa

Localize the Impact of Global Greenhouse Gases Emissions under an Uncertain Future: A Case Study... Article Localize the Impact of Global Greenhouse Gases Emissions under an Uncertain Future: A Case Study in Western Cape, South Africa 1 , 2 Bowen He * and Ke J. Ding Department of Civil and Environmental Engineering, Vanderbilt University, Nashville, TN 37235, USA Department of Geological and Atmospherical Sciences, Iowa State University, Ames, IA 50011, USA; keding@iastate.edu * Correspondence: bowen.he@vanderbilt.edu Abstract: The growing impact of CO and other greenhouse-gas (GHG) emissions on the socio- climate system in the Western Cape, South Africa, urgently calls for the need for better climate adaptation and emissions-reduction strategies. While the consensus has been that there is a strong correlation between CO emissions and the global climate system, few studies on climate change in the Western Cape have quantified the impact of climate change on local climate metrics such as precipitation and evaporation under different future climate scenarios. The present study investigates three different CO emissions scenarios: Representative Concentration Pathway (RCP) 2.6, RCP 4.5, and RCP 8.5, from moderate to severe, respectively. Specifically, we used climate metrics including precipitation, daily mean and maximum near-surface air temperature, and evaporation to evaluate the future climate in Western Cape under each different RCP climate scenario. The projected simulation results reveal that temperature-related metrics are more sensitive to CO emissions than water-related metrics. Districts closer to the south coast are more resilient to severer GHG emissions Citation: He, B.; Ding, K.J. Localize scenarios compared to inland areas regarding temperature and rainfall; however, coastal regions the Impact of Global Greenhouse are more likely to suffer from severe droughts such as the “Day-Zero” water crisis. As a result, a Gases Emissions under an Uncertain robust drying signal across the Western Cape region is likely to be seen in the second half of the Future: A Case Study in Western 21st century, especially under the scenario of RCP 8.5 (business as usual) without efficient emissions Cape, South Africa. Earth 2021, 2, reduction policies. 111–123. https://doi.org/10.3390/ earth2010007 Keywords: greenhouse gas (GHG); CO emissions; RCP; precipitation; evaporation; water balance; Academic Editor: Charles Jones South Africa; Western Cape Received: 22 January 2021 Accepted: 23 February 2021 Published: 26 February 2021 1. Introduction The effects of climate change and global warming have exacerbated the need for better Publisher’s Note: MDPI stays neutral water management strategies and emissions reduction policies. The severity of the future with regard to jurisdictional claims in impact of climate change is largely dependent on people’s present understanding and published maps and institutional affil- ability to adapt, with government and policymakers playing a critical leading role [1]. iations. A thorough and integrated understanding of both climate history and future projection, and both the inherent mechanisms and their implications to the society, is important for building a strong resilience to future climate change for a region. Adaptation is particularly critical to secure social-economic well-being [2,3]. For instance, farmers are changing Copyright: © 2021 by the authors. their selection of crops and the timing of their field operations to adapt their farming Licensee MDPI, Basel, Switzerland. strategy to future impacts of climate change to maintain agricultural productivity and rural This article is an open access article livelihoods, although the relationship between farmers’ perception and their adaptation to distributed under the terms and future climate change is far away from being fully understood [4]. conditions of the Creative Commons South Africa has always been one of the most vulnerable regions to climate change Attribution (CC BY) license (https:// on earth, with a mean annual temperature increase by at least 1.5 times the observed creativecommons.org/licenses/by/ global average of 0.65 C during the past five decades [5,6]. In addition to temperature 4.0/). Earth 2021, 2, 111–123. https://doi.org/10.3390/earth2010007 https://www.mdpi.com/journal/earth Earth 2021, 2 112 increase, precipitation is projected to decrease with higher spatial variability, along with drier rainy seasons and higher risks of severe droughts and extreme weather events across the southwestern regions of Africa from now on [7]. For Western Cape Province, the lack of rainfall, decreasing storage levels in major reservoirs, increasing water demand driven by population growth and urban expansion, combined with problematic and ineffective water management practices led to the “Day-Zero” water crisis which caused serious troubles to local citizens, businesses, and agriculture [8–10]. Most research that focused on the meteorological aspects of the drought used only precipitation to approximate drought intensity, overlooking the role of other climate metrics such as near-surface air temperature, evaporation, and their internal relations. For example, Pascale et al. [11] used a higher resolution climate model to further highlight the role of anthropogenic climate change and provided a clear and well-supported mechanism to explain the cause of the increase in drought risk in the South Africa region. They illustrated that a reduction in precipitation during the shoulder seasons is likely to be the cause of drought risk in southwestern Africa in the 21st century. While their study greatly increases the confidence in the projections of a drying South Africa region, they only analyzed the drought risk from a rainfall deficit perspective, ignoring the combined effect of precipitation, temperature, and evaporation. Naik and Abiodun [10] conducted a study to investigate the projected drought characteristics over the Western Cape, South Africa, using CORDEX simulation data, and stressed the importance of the role of potential evapotranspiration (PET) on future drought characteristics. However, they only considered the RCP 8.5 scenario, and more analysis needs to be done under other climate scenarios to better quantify the uncertainties of future climate change. Pendergrass et al. [12] investigated the relationship between extreme precipitation and different emissions scenarios and concluded that the increased rate of global-mean precipitation per degree of global-mean temperature increase differs for greenhouse gas and aerosol forcing scenarios. However, their global-level research provides very limited insights that could be used in local regions. In this context, the overarching goal of the present study is to quantify the effect of climate change on the climate and hydrological system over six main districts in Western Cape Province under 3 climate scenarios: RCP 2.6, RCP 4.5, RCP 8.5. Representative concentration pathway (RCP) 2.6, is a “very stringent” and optimistic pathway that requires that CO emissions start to decline by 2020 and go to zero by 2100. It also requires CH concentration to approximately cut to half of the CH levels in 2020 and 4 4 the SO emissions to decline to about 10% of the 1980–1990 level. This emission scenario is representative of the literature on mitigation scenarios aiming to limit the increase of global mean temperature to not beyond 2 C and is shown to be technically feasible in the IMAGE integrated assessment modeling framework from a medium emission baseline scenario, assuming full participation of all countries [13]. RCP 4.5 is a scenario of long-term, global emissions of greenhouse gases, short-lived species, and land-use-land-cover that stabilizes radiative forcing at 4.5 W/m up to the year 2100 without ever exceeding that value [14]. RCP 4.5 is a stabilization scenario and assumes that climate policies are invoked to achieve the goal of limiting emissions and radiative forcing. The application of RCP 4.5 in climate models provides a platform to explore the long-term climate system response to stabilizing the anthropogenic components of radiative forcing [14]. RCP 8.5 is the highest greenhouse-gas emissions pathway among the three climate scenarios chosen in the study. This scenario does not include any specific climate mitigation strategy, increasing greenhouse-gas emissions as well as concentrations considerably over time, leading to a radiative forcing of 8.5 W/m by the end of this century [15]. Hence, it represents the upper bound of the RCPs’ set system, which can also be called the business- as-usual scenario [15]. By conducting this research, we aim to answer the following research questions: (1) How do different CO emissions scenarios impact the climate and hydrological system in the Western Cape region? (2) How are different districts within Western Cape responding Earth 2021, 2 113 to different CO emissions? The paper is structured as follows: Section 2 describes the data and methods used in the study, Section 3 presents the results and discussion, and Section 4 delivers the conclusions and implications of the study. 2. Methods 2.1. Study Region We chose Western Cape Province in South Africa as our study region, which is located in the southernmost section of Southern Africa (Figure 1). It is surrounded by Northern Cape Province and Eastern Cape Province, as well as the Atlantic Ocean in the west and the Indian Ocean in the south. It ranges from 15.0 E to 25.0 E longitudinally, and 30.0 S to 35.0 S latitudinally. The Western Cape accounts for 12% of South Africa’s total agricultural area, provides 20% of the nation’s total agricultural production outputs, and nurtures a world-famous wine appellation [16,17]. The climate conditions across the region are temperate Mediterranean with warm dry summers and mild moist winters, rendering it favorable for cereal farming such as wheat, oats, and barley, and viticulture [10,18,19]. Average summer temperatures range from 5 C to 27 C, while winter temperatures range from 5 C to 22 C [20]. The Western Cape is one of South Africa’s driest regions with approximately 350 mm annual precipitation, well below the national annual average of Earth 2021, 2, FOR PEER REVIEW 4 500 mm precipitation [21]. Precipitation is also highly heterogeneous and varies greatly, from semi-arid areas to relatively wet areas on the windward slope of mountains [22]. Figure 1. The study domain depicting the six main districts (City of Cape Town, West Coast, Cape Figure 1. The study domain depicting the six main districts (City of Cape Town, West Coast, Cape Winelands, Overberg, Garden Route, Central Karoo) in the Western Cape region (South Africa). Winelands, Overberg, Garden Route, Central Karoo) in the Western Cape region (South Africa). The The black solid line delineates the political boundary of each main district in the Western Cape. black solid line delineates the political boundary of each main district in the Western Cape. 2.2. Data In this study, we obtained the Coordinated Regional Downscaling Experiment Sim- ulations (CORDEX) “Phase 1” simulation data from the Earth System Grid Federation (ESGF). The CORDEX models have been proved to be able to correctly capture the spatial distribution of major climate variables over the Western Cape region and reproduce the essential climatic features in the observed temperature and moisture fields [10]. Thus, they are reliable models to predict the future climatic system over the Western Cape region. “Phase 1” data are made available at the monthly temporal resolution, 0.44-degree spatial resolution, by far the largest GCM-RCK downscaled data available. We downloaded the data under AFR-44, which indicates the Africa continent with 0.44-degree downscaling. We selected several variables including pr (precipitation), tas (average near-surface air temperature), tasmax (daily average maximum near-surface air temperature), and evspsbl (evaporation) as key metrics to describe the regional climate and hydrological system in Western Cape. RCP 2.6, RCP 4.5, and RCP 8.5 were selected as experiment configurations and monthly data were downloaded. We selected MPI-M-MPI-ESM-LR as the driving model for the reason that it is the only driving model available for all 3 RCP scenarios. Moreover, its overall performance is better than its predecessor ECHAM5/MPIOM model based on a modified Reichler–Kim standardized error due to improvements of the extra- tropical circulation [24]. RCA4 was selected as the regional climate model (RCM) because a recent study found that it can adjust the boundary conditions, resulting in a significant reduction of biases in the dynamically downscaled outputs [25]. Furthermore, many pre- vious studies verified the credibility and advantage regarding the MPI-ESM-LR-RCA4 Earth 2021, 2 114 The Western Cape is the fourth largest of the nine provinces with an area of 129,449 square km, and the third most populous province with an estimated 7 million inhabitants in 2020 [23]. 2.2. Data In this study, we obtained the Coordinated Regional Downscaling Experiment Sim- ulations (CORDEX) “Phase 1” simulation data from the Earth System Grid Federation (ESGF). The CORDEX models have been proved to be able to correctly capture the spatial distribution of major climate variables over the Western Cape region and reproduce the essential climatic features in the observed temperature and moisture fields [10]. Thus, they are reliable models to predict the future climatic system over the Western Cape region. “Phase 1” data are made available at the monthly temporal resolution, 0.44-degree spatial resolution, by far the largest GCM-RCK downscaled data available. We downloaded the data under AFR-44, which indicates the Africa continent with 0.44-degree downscaling. We selected several variables including pr (precipitation), tas (average near-surface air temperature), tasmax (daily average maximum near-surface air temperature), and evspsbl (evaporation) as key metrics to describe the regional climate and hydrological system in Western Cape. RCP 2.6, RCP 4.5, and RCP 8.5 were selected as experiment configurations and monthly data were downloaded. We selected MPI-M-MPI-ESM-LR as the driving model for the reason that it is the only driving model available for all 3 RCP scenarios. Moreover, its overall performance is better than its predecessor ECHAM5/MPIOM model based on a modified Reichler–Kim standardized error due to improvements of the extrat- ropical circulation [24]. RCA4 was selected as the regional climate model (RCM) because a recent study found that it can adjust the boundary conditions, resulting in a significant reduction of biases in the dynamically downscaled outputs [25]. Furthermore, many pre- vious studies verified the credibility and advantage regarding the MPI-ESM-LR-RCA4 (GCM-RCM) chain on the projection of climate change signal over different CORDEX regions [26,27]. Full information regarding 3 downscaled GCMs data in this study is summarized in Table 1. Table 1. Summary of the simulation data. Driving Time Downscaling RCM Domain Resolution Ensemble Variable Experiment Model Frequency Resolution Model pr, tas, Rcp26 MPI-M-MPI- Monthly R1i1p1 tasmax, Rcp45 AFR 0.44 V1 RCA 4 ESM-LR evspsbl Rcp85 Monthly spatial climatic data of the Africa continent for 3 RCP scenarios were im- ported and analyzed in the open-source program RStudio [28]. The aim of using RStudio at this step was to quickly retrieve the variable data and generate raster data for further analysis. Specifically, we used the “ncdf4” package in RStudio to retrieve the climate characteristics data such as precipitation, evaporation, and so forth for each RCP scenario for the whole Africa continent. We used the “ncks” command from NetCDF Operators (NCO) to downscale the data from the Africa continent to Western Cape, South Africa, to focus on our study area. The downscaled data were then saved as raster data and im- ported into ArcMap 10.8.1 software to be further analyzed. To reveal the spatial–temporal patterns, we averaged the aforementioned climate metrics over every 20 years for each 0.44 by 0.44-degree grid inside the study area. The averaged data then were mapped for 4 two-decade spans from 2021 to 2100 for each of the 3 climate scenarios. In addition, we also examined how the water availability will change across the Western Cape region under 3 different emission scenarios using a simple water balance approach in Equation (1): P = Q + ET + dS/dt (1) Earth 2021, 2 115 where P is precipitation [mm/month], Q is discharge [mm/month], ET is evapotranspi- ration [mm/month], and dS/dt is storage changes per time step [mm/month] [29]. We used evaporation from the RCM model outputs as a proxy for ET since our purpose was to examine the general trend of water availability. In this case, we used the sum of water discharge and storage changes rate as a critical indicator of a region’s water availability, which can be calculated as the difference between precipitation and evaporation [30–32]. 3. Results and Discussions 3.1. Spatial–Temporal Patterns of Climate Metrics In this section, each climate metric under three different GHG emissions is spatially evaluated using outputs from three downscaled GCMs (Table 1). The results are well aligned with a previous study by Naik and Abiodun (2020) that projected changes in drought characteristics over the Western Cape that show a robust drying signal under the RCP 8.5 emission scenario. In addition, by investigating more emission scenarios such as the RCP 2.6 and the RCP 4.5 scenarios, this study highlights the importance of emission reduction to alleviate the region’s future climate stress. The precipitation ranges from 15 mm/month to 200 mm/month for the whole area, with the junction of City of Cape Town, Cape Winelands, and Overberg receiving the most precipitation and Central Karoo district receiving the least (Figure 2). A clear pattern is seen that coastal regions generally receive more precipitation than inland regions in the same period (Figure 2). There is no significant variability for precipitation distribution under the scenario of the RCP 2.6 and the RCP 4.5 since no noticeable difference was found in the period of 2081–2100 compared to that of 2021–2041. However, the region is dryer Earth 2021, 2, FOR PEER REVIEW 6 under the scenario of the RCP 8.5 with much less precipitation received for the junction of Cape Town, Cape Winelands, and Overberg that is relatively wet under the RCP 2.6 and the RCP 4.5 scenario, and the Central Karoo district will likely face droughts in higher and the RCP 4.5 scenario, and the Central Karoo district will likely face droughts in higher magnitudes and longer duration compared to the beginning of 21st century. magnitudes and longer duration compared to the beginning of 21st century. Figure Figure 2. Spati 2.alSpatial–temporal –temporal patterns of prec patterns ipitation in of Wes precipitation tern Cape, Soutin h Afri Wca estern (for 2021 Cape, –2100) South for 3 emis Africa sion sce(for narios2021–2100) : (a)–(l) exhibit the precipitation projection pattern for the each 20-year span from 2021–2100 under the 3 different GHG for 3 emission scenarios: (a–l) exhibit the precipitation projection pattern for the each 20-year span emission scenarios. from 2021–2100 under the 3 different GHG emission scenarios. The mean near-surface air temperature revealed a more apparent pattern under three different CO2 emissions scenarios (Figure 3). The regional warming signal is not as signif- icant under the RCP 2.6 scenario; however, the signal amplified gradually across the whole region under the RCP 4.5 and RCP 8.5 scenarios and with time. Inland districts such as West Coast and Central Karoo face larger surface air temperature increases than dis- tricts closer to the southern coast such as Overberg and Eden. Earth 2021, 2 116 The mean near-surface air temperature revealed a more apparent pattern under three different CO emissions scenarios (Figure 3). The regional warming signal is not as significant under the RCP 2.6 scenario; however, the signal amplified gradually across the Earth 2021, 2, FOR PEER REVIEW 7 whole region under the RCP 4.5 and RCP 8.5 scenarios and with time. Inland districts such as West Coast and Central Karoo face larger surface air temperature increases than districts closer to the southern coast such as Overberg and Eden. Figure 3. Spatial–temporal patterns of near-surface air temperature in Western Cape, South Africa (2021–2100) for 3 CO Figure 3. Spatial–temporal patterns of near-surface air temperature in Western Cape, South Africa (2021–2100) for 3 CO2 emissions scenarios: (a–l) exhibit the mean near-surface air temperature projection pattern for the each 20-year span from emissions scenarios: (a)–(l) exhibit the mean near-surface air temperature projection pattern for the each 20-year span from 2021-2100 under the 3 different GHG emission scenarios. 2021-2100 under the 3 different GHG emission scenarios. Daily maximum surface air temperature is used typically as a signal for extreme Daily maximum surface air temperature is used typically as a signal for extreme events such as heatwaves for a region. The daily maximum surface air temperature ranges events such as heatwaves for a region. The daily maximum surface air temperature ranges from 20 C to 35 C during the simulation period (Figure 4). West Coast and Central Karoo are more vulnerable to potential heatwave risks, especially under the RCP 8.5 scenario from 20 C to 35 C during the simulation period (Figure 4). West Coast and Central Karoo by the end of the 21st century (Figure 4). A similar trend is found as more variability of are more vulnerable to potential heatwave risks, especially under the RCP 8.5 scenario by maximum temperature occurred with intensifying GHG emissions. Inland districts such the end of the 21st century (Figure 4). A similar trend is found as more variability of max- as the West Coast, Central Karoo, and some areas of Cape Winelands are more likely to imum temperature occurred with intensifying GHG emissions. Inland districts such as the encounter extreme weather under the RCP 8.5 scenario. West Coast, Central Karoo, and some areas of Cape Winelands are more likely to encoun- ter extreme weather under the RCP 8.5 scenario. Earth 2021, 2, FOR PEER REVIEW 8 Earth 2021, 2 117 Figure 4. Spatial–temporal patterns of daily maximum surface air temperature in Western Cape, South Africa (2021–2100) for 3 Figure 4. Spatial–temporal patterns of daily maximum surface air temperature in Western Cape, South Africa (2021–2100) CO emissions scenarios: (a–l) exhibit the daily maximum surface air temperature projection pattern for the each 20-year span from for 3 CO2 emissions scenarios: (a)–(l) exhibit the daily maximum surface air temperature projection pattern for the each 2021–2100 under the 3 different GHG emission scenarios. 20-year span from 2021–2100 under the 3 different GHG emission scenarios. Evaporation is a critical element that affects the region’s water budget. Evaporation Evaporation is a critical element that affects the region’s water budget. Evaporation for the Western Cape area ranges from 10 to 205 mm/month in the future (Figure 5). for thTher e Weste e is no rn significant Cape area variability ranges from for evaporation 10 to 205 mm acr/m ossont difh fer in ent thCO e future emissions (Figuscenarios. re 5). There However, there are decreasing trends in evaporation in inland districts such as the West is no significant variability for evaporation across different CO2 emissions scenarios. How- Coast and Central Karoo compared to coastal regions (Figure 5). Thus, coastal regions are ever, there are decreasing trends in evaporation in inland districts such as the West Coast more resilient to more intense GHG emission scenarios in terms of evaporation since they and Central Karoo compared to coastal regions (Figure 5). Thus, coastal regions are more are easier to adapt to and recover from evaporation-induced extreme climate events caused resilient to more intense GHG emission scenarios in terms of evaporation since they are by GHG emissions increases. easier to adapt to and recover from evaporation-induced extreme climate events caused by GHG emissions increases. Earth 2021, 2, FOR PEER REVIEW 9 Earth 2021, 2 118 Figure 5. Spatial–temporal patterns of spatially distributed evaporation in Western Cape, South Africa (2021–2100) for 3 Figure 5. Spatial–temporal patterns of spatially distributed evaporation in Western Cape, South Africa (2021–2100) for 3 CO emissions scenarios: (a–l) exhibit the evaporation projection pattern for the each 20-year span from 2021–2100 under CO2 emissions scenarios: (a)–(l) exhibit the evaporation projection pattern for the each 20-year span from 2021–2100 under the 3 different GHG emission scenarios. the 3 different GHG emission scenarios. The trend of water availability is going to deeply impact the economic activities, The trend of water availability is going to deeply impact the economic activities, tour- tourism, agricultural practices, and people’s wellbeing in general for a region. Here we ism, consider agricultura the dif l fpracti erenceces of , pr and ecipitation people’ and s we evaporation llbeing in as gene net available ral for a water region. for each Here pixel we con- in the region, and a drought signal over a two-decade period time is identified when the sider the difference of precipitation and evaporation as net available water for each pixel net available water is less than zero. For the RCP 2.6 and 4.5 scenarios, drought signals only in the region, and a drought signal over a two-decade period time is identified when the occur at limited locations such as coastal regions within the Overberg and Eden districts net available water is less than zero. For the RCP 2.6 and 4.5 scenarios, drought signals (Figure 6). There is no significant temporal variability under this scenario. However, for only occur at limited locations such as coastal regions within the Overberg and Eden dis- the RCP 8.5 scenario, a robust drying signal is expected across Western Cape from 2060 tricts (Figure 6). There is no significant temporal variability under this scenario. However, onward, with severe drought expectation near the coastal areas within the City of Cape for the RCP 8.5 scenario, a robust drying signal is expected across Western Cape from 2060 Town, Overberg, and Eden districts (Figure 6). One probable explanation is that although onward, with severe drought expectation near the coastal areas within the City of Cape rainfall is relatively abundant in coastal regions, it is countered by a higher evaporation Town, rateOv that erberg results , and fromEden temperatur districts e incr (Fig ease. ure 6). One probable explanation is that although rainfall is relatively abundant in coastal regions, it is countered by a higher evaporation rate that results from temperature increase. Earth 2021, 2, FOR PEER REVIEW 10 Earth 2021, 2 119 Figure 6. Spatial–temporal patterns of net available water in Western Cape, South Africa (2021–2100) for 3 CO emissions Figure 6. Spatial–temporal patterns of net available water in Western Cape, South Africa (2021–2100) for 3 CO2 emissions scenarios: (a–l) exhibit the net available water projection pattern for the each 20-year span from 2021-2100 under the 3 scenarios: (a)–(l) exhibit the net available water projection pattern for the each 20-year span from 2021-2100 under the 3 different GHG emission scenarios. different GHG emission scenarios. 3.2. Regional Trends of Various Climate Metrics 3.2. Regional Trends of Various Climate Metrics We calculated the regional average for all the climate metrics to assess the overall We calculated the regional average for all the climate metrics to assess the overall impact of various emission scenarios on Western Cape Province. In terms of precipitation impact of various emission scenarios on Western Cape Province. In terms of precipitation (Figure 7a), there is not much fluctuation under both the RCP 4.5 and RCP 8.5 scenarios. (Figure 7a), there is not much fluctuation under both the RCP 4.5 and RCP 8.5 scenarios. However, there is an approximately 3.5% increase of rainfall with greater variability under However, there is an approximately 3.5% increase of rainfall with greater variability un- the scenario of the RCP 2.6 from the year 2020 to the end of the 21st century. For evaporation der the scenario of the RCP 2.6 from the year 2020 to the end of the 21st century. For evap- (Figure 7b), there is no significant increase under both the RCP 2.6 and RCP 4.5 scenarios; oration (Figure 7b), there is no significant increase under both the RCP 2.6 and RCP 4.5 however, there is a steady increasing trend with about a 3.1% increase of evaporation in scenarios; however, there is a steady increasing trend with about a 3.1% increase of evap- 2100 under the RCP 8.5 scenario. In other words, emissions increases will bring more oration in 2100 under the RCP 8.5 scenario. In other words, emissions increases will bring rainfall while causing more evaporation. However, both water-related characteristics did more rainfall while causing more evaporation. However, both water-related characteris- not display a linear trend over time, as opposed to the trends of those temperature metrics. tics did not display a linear trend over time, as opposed to the trends of those temperature Figure 7c,d shows that rates of change of temperature metrics are faster compared to those metrics. Figure 7c,d shows that rates of change of temperature metrics are faster compared of precipitation and evaporation over time, indicating higher sensitivities of temperature metrics to GHG emissions. Figure 8 is a clear indication of how more emissions will Earth 2021, 2, FOR PEER REVIEW 11 Earth 2021, 2 120 Earth 2021, 2, FOR PEER REVIEW 11 to those of precipitation and evaporation over time, indicating higher sensitivities of tem- perature metrics to GHG emissions. Figure 8 is a clear indication of how more emissions will increase the likelihood of water crises in the Western Cape. While the net water avail- increase the likelihood of water crises in the Western Cape. While the net water availability to those of precipitation and evaporation over time, indicating higher sensitivities of tem- ability is negative under all three emissions scenarios, the values under the RCP 2.6 and is negative under all three emissions scenarios, the values under the RCP 2.6 and RCP 8.5 perature metrics to GHG emissions. Figure 8 is a clear indication of how more emissions RCP 8.5 scenarios exhibit the opposite trend: For the RCP 2.6 scenario, water availability scenarios exhibit the opposite trend: For the RCP 2.6 scenario, water availability condition will increase the likelihood of water crises in the Western Cape. While the net water avail- condition in the Western Cape area improves after 2060 while the situation continues to in the Western Cape area improves after 2060 while the situation continues to get worse ability is negative under all three emissions scenarios, the values under the RCP 2.6 and get worse and worse under the RCP 8.5 scenario. and worse under the RCP 8.5 scenario. RCP 8.5 scenarios exhibit the opposite trend: For the RCP 2.6 scenario, water availability condition in the Western Cape area improves after 2060 while the situation continues to (a) Spatial Average Precipitation Spatial Average Evaporation (b) Regional Average Precipitation Regional Average Evaporation get worse and worse under the RCP 8.5 scenario. 101.5 91.5 100.5 (a) Spatial Average Precipitation Spatial Average Evaporation (b) Regional Average Precipitation Regional Average Evaporation 90.5 92 101 10 .5 0 RCP 2.6 RCP 2.6 91.5 89.5 101 99.5 91 RCP 4.5 RCP 4.5 100.5 90.5 88.5 RCP 8.5 RCP 8.5 90 100 98.5 88 RCP 2.6 RCP 2.6 89.5 99.5 87.5 98 RCP 4.5 RCP 4.5 1 2 3 4 5 6 7 8 1 2 3 4 5 6 7 8 88.5 RCP 8.5 20s 30s 40s 50s 60s 70s 80s RC9 P0 8s .5 20s 30s 40s 50s 60s 70s 80s 90s 98.5 88 Time Period Time Period 87.5 98 1 2 3 4 5 6 7 8 1 2 3 4 5 6 7 8 Regional Average Daily Maximum 20s 60s 20s 30s 40s 50s 60s 70s 80s 90s 30s 40s 50s 70s 80s 90s Spatial Average Near Surface Air Temperature (c) Spatial Average Daily Maximum Surface Air Temperature (d) Regional Average Near Surface Air Temperature Time Period Time Period 26 29.5 Near Surface Air Temperature 29 Regional Average Daily Maximum 25.5 Spatial Average Near Surface Air Temperature (c) Spatial Average Daily Maximum Surface Air Temperature (d) Regional Average Near Surface Air Temperature 28.5 26 29.5 Near Surface Air Temperature 24.5 25.5 29 27.5 28.5 24 25 RCP 2.6 RCP 2.6 24.5 23.5 RCP 4.5 RCP 4.5 26.5 27.5 24 RCP 2.6 RCP 2.6 2 27 6 RCP 8.5 RCP 8.5 23.5 RCP 4.5 RCP 4.5 22.5 26.5 25.5 22 RCP 8.5 RCP 8.5 22.5 25.5 1 2 3 4 5 6 7 8 1 2 3 4 6 50s 6 8 70s 9 80s 40s 50s 70s 20s 30s 40s 50s 60s 70s 80s 90s 20s 30s 22 25 Time Period Time Period 1 2 3 4 5 6 7 8 1 2 3 4 5 6 7 8 40s 50s 60s 70s 80s 90s 20s 30s 40s 50s 60s 70s 80s 90s 20s 30s Time Period Time Period Figure 7. Projection of regional averaged climate metrics in Western Cape, South Africa for 3 CO2 emissions scenarios: (a) Figure 7. Projection of regional averaged climate metrics in Western Cape, South Africa for 3 CO emissions scenarios: Figure 7. Projection of regional averaged climate metrics in Western Cape, South Africa for 3 CO2 emissions scenarios: (a) regional average precipitation; (b) regional average evaporation; (c) regional average near-surface air temperature; (d) (a) regional average precipitation; (b) regional average evaporation; (c) regional average near-surface air temperature; (d) regional average precipitation; (b) regional average evaporation; (c) regional average near-surface air temperature; (d) regional average daily maximum surface air temperature. regional average daily maximum surface air temperature. regional average daily maximum surface air temperature. Spatial Average Water Balance Regional Average Net Available Water Spatial Average Water Balance Regional Average Net Available Water -7 -7 1 2 3 4 5 6 80 7s 90 8s 20s 30s 40s 50s 60s 70s 1 2 3 4 5 6 80 7s 90 8s 20s 30s 40s 50s 60s 70s -8 -8 -9 -9 RCP 2.6 RCP 2.6 -10 -10 RCP 4.5 RCP 4.5 RCP 8.5 RCP 8.5 -11 -11 -12 -12 -13 Time Period -13 Time Period Figure 8. Projection of regional average water balance in Western Cape area for 3 CO2 emissions Figure 8. Projection of regional average water balance in Western Cape area for 3 CO emissions scenarios. Figure 8. Projection of regional average water balance in Western Cape area for 3 CO2 emissions scenarios. scenarios. Temperature-related characteristics such as near-surface air temperature and daily Temperature-related characteristics such as near-surface air temperature and daily maximum surface air temperature are more closely connected to GHG emissions compared maximum surface air temperature are more closely connected to GHG emissions com- to water Temperature -related metrics -related such char asac pr teristics ecipitation suc and h as evaporation. near-surface This air is tem because perature increasing and daily pared to water-related metrics such as precipitation and evaporation. This is because in- greenhouse gases will directly affect the temperature, and temperature will further cause maximum surface air temperature are more closely connected to GHG emissions com- rainfall creasing togree decr nho ease use and gases evaporation will direct toly incr affect easeth [33 e tem ]. perature, and temperature will fur- pared to water-related metrics such as precipitation and evaporation. This is because in- ther cause rainfall to decrease and evaporation to increase [33]. creasing greenhouse gases will directly affect the temperature, and temperature will fur- 3.3. Potential Policy Implications ther cause rainfall to decrease and evaporation to increase [33]. 3.3. Potential Policy Implications Based on the results shown above, it is more likely to see severer droughts across the Western Cape region when doing business as usual, as opposed to taking serious actions Based on the results shown above, it is more likely to see severer droughts across the 3.3. Potential Policy Implications and making policies to reduce GHG emissions. In terms of water availability, higher Western Cape region when doing business as usual, as opposed to taking serious actions Based on the results shown above, it is more likely to see severer droughts across the Western Cape region when doing business as usual, as opposed to taking serious actions Temperature (°C) Precipitation (mm/month) Temperature (°C) Precipitation (mm/month) Precipitation - Evaporation (mm/month) Precipitation - Evaporation (mm/month) Evaporation E (v m am po /r m ao tin o tn h )(mm/month) TempeT re at m ur p ee (r°a Ct )ure (°C) Earth 2021, 2 121 evaporation caused by regional warming offsets the relatively abundant rainfall for coastal regions, and those regions may suffer severer water crises than inland districts. Local government and policymakers could make efforts on at least two aspects to increase water availability and avoid the “Day-Zero” water crisis problem: controlling the emissions and at the same time, improving water usage efficiency and diversifying water supply sources. First, in terms of emissions constraining technology, many innovative technologies emerge as solutions to cut emissions. As an example of emission reduction, smart-grid technologies are becoming popular that can use artificial intelligence (AI) to introduce a layer of digital intelligence to the grid to enable the industry to respond to the grid dynamically, restore power interruptions, accommodate alternative energy options, and facilitate demand response strategies [34]. There is significant potential for improving the efficiency of the electrical energy value chain and efficiency by introducing AI-based smart-grid technologies [34]. Carbon-capture technologies may be a more localized ap- proach; however, these require global cooperation and collaboration to reach the level of significance. For improving water-usage efficiency, this requires citizens and government to adopt a water-sensitive approach in city planning and development that could include shifting water-management paradigms, developing new governance mechanisms, and guiding diversification of water supplies to provide resilience to potential future climate shocks [35]. In the meantime, local government should explore interventions that pro- mote and proactively encourage behavioral change and address inequity regarding water rights [35]. Finally, we have to emphasize the importance of governance across all adminis- trative levels [36], because all policies and measures against climate change and improving the livelihoods of the people that could last and be effective rely on proper governance. 4. Conclusions In this study, Co-ordinated Regional Climate Downscaling Experiment (CORDEX) data were used to examine the potential impacts of various greenhouse-gas emissions (RCP 2.6, RCP 4.5 RCP 8.5) on the future climate systems in six districts within the Western Cape, South Africa. The global simulations have been downscaled with RCA 4 for the future 80 years of the 21st century. The precipitation and evaporation data were used to approximately predict future drought in terms of net available water for the region. Both spatial–temporal analysis and regional-average analysis suggest the following: 1. Different climate metrics will respond differently to emissions scenarios. The projected simulation results reveal that temperature-related metrics are more sensitive to GHG emissions than water-related metrics as expected, as lower emissions can considerably alleviate climate vulnerability in Western Cape regions compared to business as usual. 2. Climate change poses a localized effect on different regions in Western Cape. Districts closer to the south coast are more resilient to regional warming compared to inland areas, but less so in terms of water stress. 3. A robust drying signal across the Western Cape region is likely to be seen in the near future if we continue doing business as usual (as seen in RCP 8.5). Efficient water-management practices and greenhouse-gas emissions reduction strategies are urgently needed to avoid more severe droughts such as the “Day-Zero” crisis in 2018, especially for the City of Cape Town and several other coastal regions within the Overberg and Eden district. This study highlights the importance of the impact of climate emissions scenarios (RCP 2.6, RCP 4.5, and RCP 8.5) on the regional climate change signals simulated by the model chain MPI-ESM/RCA4. Since this is the only GCM-RCM model combination available, the results cannot provide a comprehensive evaluation of possible climate change signals in the region. Nonetheless, the results sufficiently demonstrated the great potential of reducing climate risks and vulnerability under lower GHG emission scenarios for Western Cape region. When more downscaled climate data across different RCPs are available for Africa, it will enable uncertainty analyses and quantification of future climate change using a sufficiently large ensemble of simulations. Earth 2021, 2 122 Author Contributions: Conceptualization, B.H. and K.J.D.; methodology, B.H. and K.J.D.; software, B.H.; validation, B.H.; formal analysis, B.H.; investigation, B.H.; resources, B.H.; data curation, B.H.; writing—original draft preparation, B.H.; writing—review and editing, K.J.D.; visualization, B.H.; supervision, K.J.D.; Both authors have read and agreed to the published version of the manuscript. Funding: This research received no external funding. Institutional Review Board Statement: Not applicable. Informed Consent Statement: Not applicable. Data Availability Statement: Not applicable. Conflicts of Interest: Authors declare no competing interests. References 1. Wolf, J.; Moser, S.C. Individual understandings, perceptions, and engagement with climate change: Insights from in-depth studies across the world. Wiley Interdiscip. Rev. Clim. Chang. 2011, 2, 547–569. [CrossRef] 2. Haden, V.R.; Niles, M.T.; Lubell, M.; Perlman, J.; Jackson, L.E. Global and local concerns: What attitudes and beliefs motivate farmers to mitigate and adapt to climate change? PLoS ONE 2012, 7, e52882. [CrossRef] 3. Niang, I.; Ruppel, O.C.; Abdrabo, M.A.; Essel, A.; Lennard, C.; Padgham, J.; Urquhart, P. Climate Change 2014: Impacts, Adaptation, and Vulnerability. Part B: Regional Aspects. 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RStudio; PBC: Boston, MA, USA, 2020; Available online: http://www.rstudio. com/ (accessed on 17 January 2021). 29. Hornberger, G.M.; Wiberg, P.L.; Raffensperger, J.P.; D’Odorico, P. Elements of Physical Hydrology; JHU Press: Baltimore, MD, USA, 30. Arnell, N.W. Climate change and global water resources. Glob. Environ. Chang. 1999, 9, S31–S49. [CrossRef] 31. Milly, P.C.D. Climate, interseasonal storage of soil water, and the annual water balance. Adv. Water Res. 1994, 17, 19–24. [CrossRef] 32. Taylor, R.G.; Scanlon, B.; Döll, P.; Rodell, M.; Van Beek, R.; Wada, Y.; Longuevergne, L.; Leblanc, M.; Famiglietti, J.S.; Edmunds, M.; et al. Ground water and climate change. Nat. Clim. Chang. 2013, 3, 322–329. [CrossRef] 33. Barnett, T.P.; Adam, J.C.; Lettenmaier, D.P. Potential impacts of a warming climate on water availability in snow-dominated regions. Nature 2005, 438, 303–309. [CrossRef] [PubMed] 34. Diab, R. Recommendations for the energy efficiency technology landscape in South Africa. 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Localize the Impact of Global Greenhouse Gases Emissions under an Uncertain Future: A Case Study in Western Cape, South Africa

Earth , Volume 2 (1) – Feb 26, 2021

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Article Localize the Impact of Global Greenhouse Gases Emissions under an Uncertain Future: A Case Study in Western Cape, South Africa 1 , 2 Bowen He * and Ke J. Ding Department of Civil and Environmental Engineering, Vanderbilt University, Nashville, TN 37235, USA Department of Geological and Atmospherical Sciences, Iowa State University, Ames, IA 50011, USA; keding@iastate.edu * Correspondence: bowen.he@vanderbilt.edu Abstract: The growing impact of CO and other greenhouse-gas (GHG) emissions on the socio- climate system in the Western Cape, South Africa, urgently calls for the need for better climate adaptation and emissions-reduction strategies. While the consensus has been that there is a strong correlation between CO emissions and the global climate system, few studies on climate change in the Western Cape have quantified the impact of climate change on local climate metrics such as precipitation and evaporation under different future climate scenarios. The present study investigates three different CO emissions scenarios: Representative Concentration Pathway (RCP) 2.6, RCP 4.5, and RCP 8.5, from moderate to severe, respectively. Specifically, we used climate metrics including precipitation, daily mean and maximum near-surface air temperature, and evaporation to evaluate the future climate in Western Cape under each different RCP climate scenario. The projected simulation results reveal that temperature-related metrics are more sensitive to CO emissions than water-related metrics. Districts closer to the south coast are more resilient to severer GHG emissions Citation: He, B.; Ding, K.J. Localize scenarios compared to inland areas regarding temperature and rainfall; however, coastal regions the Impact of Global Greenhouse are more likely to suffer from severe droughts such as the “Day-Zero” water crisis. As a result, a Gases Emissions under an Uncertain robust drying signal across the Western Cape region is likely to be seen in the second half of the Future: A Case Study in Western 21st century, especially under the scenario of RCP 8.5 (business as usual) without efficient emissions Cape, South Africa. Earth 2021, 2, reduction policies. 111–123. https://doi.org/10.3390/ earth2010007 Keywords: greenhouse gas (GHG); CO emissions; RCP; precipitation; evaporation; water balance; Academic Editor: Charles Jones South Africa; Western Cape Received: 22 January 2021 Accepted: 23 February 2021 Published: 26 February 2021 1. Introduction The effects of climate change and global warming have exacerbated the need for better Publisher’s Note: MDPI stays neutral water management strategies and emissions reduction policies. The severity of the future with regard to jurisdictional claims in impact of climate change is largely dependent on people’s present understanding and published maps and institutional affil- ability to adapt, with government and policymakers playing a critical leading role [1]. iations. A thorough and integrated understanding of both climate history and future projection, and both the inherent mechanisms and their implications to the society, is important for building a strong resilience to future climate change for a region. Adaptation is particularly critical to secure social-economic well-being [2,3]. For instance, farmers are changing Copyright: © 2021 by the authors. their selection of crops and the timing of their field operations to adapt their farming Licensee MDPI, Basel, Switzerland. strategy to future impacts of climate change to maintain agricultural productivity and rural This article is an open access article livelihoods, although the relationship between farmers’ perception and their adaptation to distributed under the terms and future climate change is far away from being fully understood [4]. conditions of the Creative Commons South Africa has always been one of the most vulnerable regions to climate change Attribution (CC BY) license (https:// on earth, with a mean annual temperature increase by at least 1.5 times the observed creativecommons.org/licenses/by/ global average of 0.65 C during the past five decades [5,6]. In addition to temperature 4.0/). Earth 2021, 2, 111–123. https://doi.org/10.3390/earth2010007 https://www.mdpi.com/journal/earth Earth 2021, 2 112 increase, precipitation is projected to decrease with higher spatial variability, along with drier rainy seasons and higher risks of severe droughts and extreme weather events across the southwestern regions of Africa from now on [7]. For Western Cape Province, the lack of rainfall, decreasing storage levels in major reservoirs, increasing water demand driven by population growth and urban expansion, combined with problematic and ineffective water management practices led to the “Day-Zero” water crisis which caused serious troubles to local citizens, businesses, and agriculture [8–10]. Most research that focused on the meteorological aspects of the drought used only precipitation to approximate drought intensity, overlooking the role of other climate metrics such as near-surface air temperature, evaporation, and their internal relations. For example, Pascale et al. [11] used a higher resolution climate model to further highlight the role of anthropogenic climate change and provided a clear and well-supported mechanism to explain the cause of the increase in drought risk in the South Africa region. They illustrated that a reduction in precipitation during the shoulder seasons is likely to be the cause of drought risk in southwestern Africa in the 21st century. While their study greatly increases the confidence in the projections of a drying South Africa region, they only analyzed the drought risk from a rainfall deficit perspective, ignoring the combined effect of precipitation, temperature, and evaporation. Naik and Abiodun [10] conducted a study to investigate the projected drought characteristics over the Western Cape, South Africa, using CORDEX simulation data, and stressed the importance of the role of potential evapotranspiration (PET) on future drought characteristics. However, they only considered the RCP 8.5 scenario, and more analysis needs to be done under other climate scenarios to better quantify the uncertainties of future climate change. Pendergrass et al. [12] investigated the relationship between extreme precipitation and different emissions scenarios and concluded that the increased rate of global-mean precipitation per degree of global-mean temperature increase differs for greenhouse gas and aerosol forcing scenarios. However, their global-level research provides very limited insights that could be used in local regions. In this context, the overarching goal of the present study is to quantify the effect of climate change on the climate and hydrological system over six main districts in Western Cape Province under 3 climate scenarios: RCP 2.6, RCP 4.5, RCP 8.5. Representative concentration pathway (RCP) 2.6, is a “very stringent” and optimistic pathway that requires that CO emissions start to decline by 2020 and go to zero by 2100. It also requires CH concentration to approximately cut to half of the CH levels in 2020 and 4 4 the SO emissions to decline to about 10% of the 1980–1990 level. This emission scenario is representative of the literature on mitigation scenarios aiming to limit the increase of global mean temperature to not beyond 2 C and is shown to be technically feasible in the IMAGE integrated assessment modeling framework from a medium emission baseline scenario, assuming full participation of all countries [13]. RCP 4.5 is a scenario of long-term, global emissions of greenhouse gases, short-lived species, and land-use-land-cover that stabilizes radiative forcing at 4.5 W/m up to the year 2100 without ever exceeding that value [14]. RCP 4.5 is a stabilization scenario and assumes that climate policies are invoked to achieve the goal of limiting emissions and radiative forcing. The application of RCP 4.5 in climate models provides a platform to explore the long-term climate system response to stabilizing the anthropogenic components of radiative forcing [14]. RCP 8.5 is the highest greenhouse-gas emissions pathway among the three climate scenarios chosen in the study. This scenario does not include any specific climate mitigation strategy, increasing greenhouse-gas emissions as well as concentrations considerably over time, leading to a radiative forcing of 8.5 W/m by the end of this century [15]. Hence, it represents the upper bound of the RCPs’ set system, which can also be called the business- as-usual scenario [15]. By conducting this research, we aim to answer the following research questions: (1) How do different CO emissions scenarios impact the climate and hydrological system in the Western Cape region? (2) How are different districts within Western Cape responding Earth 2021, 2 113 to different CO emissions? The paper is structured as follows: Section 2 describes the data and methods used in the study, Section 3 presents the results and discussion, and Section 4 delivers the conclusions and implications of the study. 2. Methods 2.1. Study Region We chose Western Cape Province in South Africa as our study region, which is located in the southernmost section of Southern Africa (Figure 1). It is surrounded by Northern Cape Province and Eastern Cape Province, as well as the Atlantic Ocean in the west and the Indian Ocean in the south. It ranges from 15.0 E to 25.0 E longitudinally, and 30.0 S to 35.0 S latitudinally. The Western Cape accounts for 12% of South Africa’s total agricultural area, provides 20% of the nation’s total agricultural production outputs, and nurtures a world-famous wine appellation [16,17]. The climate conditions across the region are temperate Mediterranean with warm dry summers and mild moist winters, rendering it favorable for cereal farming such as wheat, oats, and barley, and viticulture [10,18,19]. Average summer temperatures range from 5 C to 27 C, while winter temperatures range from 5 C to 22 C [20]. The Western Cape is one of South Africa’s driest regions with approximately 350 mm annual precipitation, well below the national annual average of Earth 2021, 2, FOR PEER REVIEW 4 500 mm precipitation [21]. Precipitation is also highly heterogeneous and varies greatly, from semi-arid areas to relatively wet areas on the windward slope of mountains [22]. Figure 1. The study domain depicting the six main districts (City of Cape Town, West Coast, Cape Figure 1. The study domain depicting the six main districts (City of Cape Town, West Coast, Cape Winelands, Overberg, Garden Route, Central Karoo) in the Western Cape region (South Africa). Winelands, Overberg, Garden Route, Central Karoo) in the Western Cape region (South Africa). The The black solid line delineates the political boundary of each main district in the Western Cape. black solid line delineates the political boundary of each main district in the Western Cape. 2.2. Data In this study, we obtained the Coordinated Regional Downscaling Experiment Sim- ulations (CORDEX) “Phase 1” simulation data from the Earth System Grid Federation (ESGF). The CORDEX models have been proved to be able to correctly capture the spatial distribution of major climate variables over the Western Cape region and reproduce the essential climatic features in the observed temperature and moisture fields [10]. Thus, they are reliable models to predict the future climatic system over the Western Cape region. “Phase 1” data are made available at the monthly temporal resolution, 0.44-degree spatial resolution, by far the largest GCM-RCK downscaled data available. We downloaded the data under AFR-44, which indicates the Africa continent with 0.44-degree downscaling. We selected several variables including pr (precipitation), tas (average near-surface air temperature), tasmax (daily average maximum near-surface air temperature), and evspsbl (evaporation) as key metrics to describe the regional climate and hydrological system in Western Cape. RCP 2.6, RCP 4.5, and RCP 8.5 were selected as experiment configurations and monthly data were downloaded. We selected MPI-M-MPI-ESM-LR as the driving model for the reason that it is the only driving model available for all 3 RCP scenarios. Moreover, its overall performance is better than its predecessor ECHAM5/MPIOM model based on a modified Reichler–Kim standardized error due to improvements of the extra- tropical circulation [24]. RCA4 was selected as the regional climate model (RCM) because a recent study found that it can adjust the boundary conditions, resulting in a significant reduction of biases in the dynamically downscaled outputs [25]. Furthermore, many pre- vious studies verified the credibility and advantage regarding the MPI-ESM-LR-RCA4 Earth 2021, 2 114 The Western Cape is the fourth largest of the nine provinces with an area of 129,449 square km, and the third most populous province with an estimated 7 million inhabitants in 2020 [23]. 2.2. Data In this study, we obtained the Coordinated Regional Downscaling Experiment Sim- ulations (CORDEX) “Phase 1” simulation data from the Earth System Grid Federation (ESGF). The CORDEX models have been proved to be able to correctly capture the spatial distribution of major climate variables over the Western Cape region and reproduce the essential climatic features in the observed temperature and moisture fields [10]. Thus, they are reliable models to predict the future climatic system over the Western Cape region. “Phase 1” data are made available at the monthly temporal resolution, 0.44-degree spatial resolution, by far the largest GCM-RCK downscaled data available. We downloaded the data under AFR-44, which indicates the Africa continent with 0.44-degree downscaling. We selected several variables including pr (precipitation), tas (average near-surface air temperature), tasmax (daily average maximum near-surface air temperature), and evspsbl (evaporation) as key metrics to describe the regional climate and hydrological system in Western Cape. RCP 2.6, RCP 4.5, and RCP 8.5 were selected as experiment configurations and monthly data were downloaded. We selected MPI-M-MPI-ESM-LR as the driving model for the reason that it is the only driving model available for all 3 RCP scenarios. Moreover, its overall performance is better than its predecessor ECHAM5/MPIOM model based on a modified Reichler–Kim standardized error due to improvements of the extrat- ropical circulation [24]. RCA4 was selected as the regional climate model (RCM) because a recent study found that it can adjust the boundary conditions, resulting in a significant reduction of biases in the dynamically downscaled outputs [25]. Furthermore, many pre- vious studies verified the credibility and advantage regarding the MPI-ESM-LR-RCA4 (GCM-RCM) chain on the projection of climate change signal over different CORDEX regions [26,27]. Full information regarding 3 downscaled GCMs data in this study is summarized in Table 1. Table 1. Summary of the simulation data. Driving Time Downscaling RCM Domain Resolution Ensemble Variable Experiment Model Frequency Resolution Model pr, tas, Rcp26 MPI-M-MPI- Monthly R1i1p1 tasmax, Rcp45 AFR 0.44 V1 RCA 4 ESM-LR evspsbl Rcp85 Monthly spatial climatic data of the Africa continent for 3 RCP scenarios were im- ported and analyzed in the open-source program RStudio [28]. The aim of using RStudio at this step was to quickly retrieve the variable data and generate raster data for further analysis. Specifically, we used the “ncdf4” package in RStudio to retrieve the climate characteristics data such as precipitation, evaporation, and so forth for each RCP scenario for the whole Africa continent. We used the “ncks” command from NetCDF Operators (NCO) to downscale the data from the Africa continent to Western Cape, South Africa, to focus on our study area. The downscaled data were then saved as raster data and im- ported into ArcMap 10.8.1 software to be further analyzed. To reveal the spatial–temporal patterns, we averaged the aforementioned climate metrics over every 20 years for each 0.44 by 0.44-degree grid inside the study area. The averaged data then were mapped for 4 two-decade spans from 2021 to 2100 for each of the 3 climate scenarios. In addition, we also examined how the water availability will change across the Western Cape region under 3 different emission scenarios using a simple water balance approach in Equation (1): P = Q + ET + dS/dt (1) Earth 2021, 2 115 where P is precipitation [mm/month], Q is discharge [mm/month], ET is evapotranspi- ration [mm/month], and dS/dt is storage changes per time step [mm/month] [29]. We used evaporation from the RCM model outputs as a proxy for ET since our purpose was to examine the general trend of water availability. In this case, we used the sum of water discharge and storage changes rate as a critical indicator of a region’s water availability, which can be calculated as the difference between precipitation and evaporation [30–32]. 3. Results and Discussions 3.1. Spatial–Temporal Patterns of Climate Metrics In this section, each climate metric under three different GHG emissions is spatially evaluated using outputs from three downscaled GCMs (Table 1). The results are well aligned with a previous study by Naik and Abiodun (2020) that projected changes in drought characteristics over the Western Cape that show a robust drying signal under the RCP 8.5 emission scenario. In addition, by investigating more emission scenarios such as the RCP 2.6 and the RCP 4.5 scenarios, this study highlights the importance of emission reduction to alleviate the region’s future climate stress. The precipitation ranges from 15 mm/month to 200 mm/month for the whole area, with the junction of City of Cape Town, Cape Winelands, and Overberg receiving the most precipitation and Central Karoo district receiving the least (Figure 2). A clear pattern is seen that coastal regions generally receive more precipitation than inland regions in the same period (Figure 2). There is no significant variability for precipitation distribution under the scenario of the RCP 2.6 and the RCP 4.5 since no noticeable difference was found in the period of 2081–2100 compared to that of 2021–2041. However, the region is dryer Earth 2021, 2, FOR PEER REVIEW 6 under the scenario of the RCP 8.5 with much less precipitation received for the junction of Cape Town, Cape Winelands, and Overberg that is relatively wet under the RCP 2.6 and the RCP 4.5 scenario, and the Central Karoo district will likely face droughts in higher and the RCP 4.5 scenario, and the Central Karoo district will likely face droughts in higher magnitudes and longer duration compared to the beginning of 21st century. magnitudes and longer duration compared to the beginning of 21st century. Figure Figure 2. Spati 2.alSpatial–temporal –temporal patterns of prec patterns ipitation in of Wes precipitation tern Cape, Soutin h Afri Wca estern (for 2021 Cape, –2100) South for 3 emis Africa sion sce(for narios2021–2100) : (a)–(l) exhibit the precipitation projection pattern for the each 20-year span from 2021–2100 under the 3 different GHG for 3 emission scenarios: (a–l) exhibit the precipitation projection pattern for the each 20-year span emission scenarios. from 2021–2100 under the 3 different GHG emission scenarios. The mean near-surface air temperature revealed a more apparent pattern under three different CO2 emissions scenarios (Figure 3). The regional warming signal is not as signif- icant under the RCP 2.6 scenario; however, the signal amplified gradually across the whole region under the RCP 4.5 and RCP 8.5 scenarios and with time. Inland districts such as West Coast and Central Karoo face larger surface air temperature increases than dis- tricts closer to the southern coast such as Overberg and Eden. Earth 2021, 2 116 The mean near-surface air temperature revealed a more apparent pattern under three different CO emissions scenarios (Figure 3). The regional warming signal is not as significant under the RCP 2.6 scenario; however, the signal amplified gradually across the Earth 2021, 2, FOR PEER REVIEW 7 whole region under the RCP 4.5 and RCP 8.5 scenarios and with time. Inland districts such as West Coast and Central Karoo face larger surface air temperature increases than districts closer to the southern coast such as Overberg and Eden. Figure 3. Spatial–temporal patterns of near-surface air temperature in Western Cape, South Africa (2021–2100) for 3 CO Figure 3. Spatial–temporal patterns of near-surface air temperature in Western Cape, South Africa (2021–2100) for 3 CO2 emissions scenarios: (a–l) exhibit the mean near-surface air temperature projection pattern for the each 20-year span from emissions scenarios: (a)–(l) exhibit the mean near-surface air temperature projection pattern for the each 20-year span from 2021-2100 under the 3 different GHG emission scenarios. 2021-2100 under the 3 different GHG emission scenarios. Daily maximum surface air temperature is used typically as a signal for extreme Daily maximum surface air temperature is used typically as a signal for extreme events such as heatwaves for a region. The daily maximum surface air temperature ranges events such as heatwaves for a region. The daily maximum surface air temperature ranges from 20 C to 35 C during the simulation period (Figure 4). West Coast and Central Karoo are more vulnerable to potential heatwave risks, especially under the RCP 8.5 scenario from 20 C to 35 C during the simulation period (Figure 4). West Coast and Central Karoo by the end of the 21st century (Figure 4). A similar trend is found as more variability of are more vulnerable to potential heatwave risks, especially under the RCP 8.5 scenario by maximum temperature occurred with intensifying GHG emissions. Inland districts such the end of the 21st century (Figure 4). A similar trend is found as more variability of max- as the West Coast, Central Karoo, and some areas of Cape Winelands are more likely to imum temperature occurred with intensifying GHG emissions. Inland districts such as the encounter extreme weather under the RCP 8.5 scenario. West Coast, Central Karoo, and some areas of Cape Winelands are more likely to encoun- ter extreme weather under the RCP 8.5 scenario. Earth 2021, 2, FOR PEER REVIEW 8 Earth 2021, 2 117 Figure 4. Spatial–temporal patterns of daily maximum surface air temperature in Western Cape, South Africa (2021–2100) for 3 Figure 4. Spatial–temporal patterns of daily maximum surface air temperature in Western Cape, South Africa (2021–2100) CO emissions scenarios: (a–l) exhibit the daily maximum surface air temperature projection pattern for the each 20-year span from for 3 CO2 emissions scenarios: (a)–(l) exhibit the daily maximum surface air temperature projection pattern for the each 2021–2100 under the 3 different GHG emission scenarios. 20-year span from 2021–2100 under the 3 different GHG emission scenarios. Evaporation is a critical element that affects the region’s water budget. Evaporation Evaporation is a critical element that affects the region’s water budget. Evaporation for the Western Cape area ranges from 10 to 205 mm/month in the future (Figure 5). for thTher e Weste e is no rn significant Cape area variability ranges from for evaporation 10 to 205 mm acr/m ossont difh fer in ent thCO e future emissions (Figuscenarios. re 5). There However, there are decreasing trends in evaporation in inland districts such as the West is no significant variability for evaporation across different CO2 emissions scenarios. How- Coast and Central Karoo compared to coastal regions (Figure 5). Thus, coastal regions are ever, there are decreasing trends in evaporation in inland districts such as the West Coast more resilient to more intense GHG emission scenarios in terms of evaporation since they and Central Karoo compared to coastal regions (Figure 5). Thus, coastal regions are more are easier to adapt to and recover from evaporation-induced extreme climate events caused resilient to more intense GHG emission scenarios in terms of evaporation since they are by GHG emissions increases. easier to adapt to and recover from evaporation-induced extreme climate events caused by GHG emissions increases. Earth 2021, 2, FOR PEER REVIEW 9 Earth 2021, 2 118 Figure 5. Spatial–temporal patterns of spatially distributed evaporation in Western Cape, South Africa (2021–2100) for 3 Figure 5. Spatial–temporal patterns of spatially distributed evaporation in Western Cape, South Africa (2021–2100) for 3 CO emissions scenarios: (a–l) exhibit the evaporation projection pattern for the each 20-year span from 2021–2100 under CO2 emissions scenarios: (a)–(l) exhibit the evaporation projection pattern for the each 20-year span from 2021–2100 under the 3 different GHG emission scenarios. the 3 different GHG emission scenarios. The trend of water availability is going to deeply impact the economic activities, The trend of water availability is going to deeply impact the economic activities, tour- tourism, agricultural practices, and people’s wellbeing in general for a region. Here we ism, consider agricultura the dif l fpracti erenceces of , pr and ecipitation people’ and s we evaporation llbeing in as gene net available ral for a water region. for each Here pixel we con- in the region, and a drought signal over a two-decade period time is identified when the sider the difference of precipitation and evaporation as net available water for each pixel net available water is less than zero. For the RCP 2.6 and 4.5 scenarios, drought signals only in the region, and a drought signal over a two-decade period time is identified when the occur at limited locations such as coastal regions within the Overberg and Eden districts net available water is less than zero. For the RCP 2.6 and 4.5 scenarios, drought signals (Figure 6). There is no significant temporal variability under this scenario. However, for only occur at limited locations such as coastal regions within the Overberg and Eden dis- the RCP 8.5 scenario, a robust drying signal is expected across Western Cape from 2060 tricts (Figure 6). There is no significant temporal variability under this scenario. However, onward, with severe drought expectation near the coastal areas within the City of Cape for the RCP 8.5 scenario, a robust drying signal is expected across Western Cape from 2060 Town, Overberg, and Eden districts (Figure 6). One probable explanation is that although onward, with severe drought expectation near the coastal areas within the City of Cape rainfall is relatively abundant in coastal regions, it is countered by a higher evaporation Town, rateOv that erberg results , and fromEden temperatur districts e incr (Fig ease. ure 6). One probable explanation is that although rainfall is relatively abundant in coastal regions, it is countered by a higher evaporation rate that results from temperature increase. Earth 2021, 2, FOR PEER REVIEW 10 Earth 2021, 2 119 Figure 6. Spatial–temporal patterns of net available water in Western Cape, South Africa (2021–2100) for 3 CO emissions Figure 6. Spatial–temporal patterns of net available water in Western Cape, South Africa (2021–2100) for 3 CO2 emissions scenarios: (a–l) exhibit the net available water projection pattern for the each 20-year span from 2021-2100 under the 3 scenarios: (a)–(l) exhibit the net available water projection pattern for the each 20-year span from 2021-2100 under the 3 different GHG emission scenarios. different GHG emission scenarios. 3.2. Regional Trends of Various Climate Metrics 3.2. Regional Trends of Various Climate Metrics We calculated the regional average for all the climate metrics to assess the overall We calculated the regional average for all the climate metrics to assess the overall impact of various emission scenarios on Western Cape Province. In terms of precipitation impact of various emission scenarios on Western Cape Province. In terms of precipitation (Figure 7a), there is not much fluctuation under both the RCP 4.5 and RCP 8.5 scenarios. (Figure 7a), there is not much fluctuation under both the RCP 4.5 and RCP 8.5 scenarios. However, there is an approximately 3.5% increase of rainfall with greater variability under However, there is an approximately 3.5% increase of rainfall with greater variability un- the scenario of the RCP 2.6 from the year 2020 to the end of the 21st century. For evaporation der the scenario of the RCP 2.6 from the year 2020 to the end of the 21st century. For evap- (Figure 7b), there is no significant increase under both the RCP 2.6 and RCP 4.5 scenarios; oration (Figure 7b), there is no significant increase under both the RCP 2.6 and RCP 4.5 however, there is a steady increasing trend with about a 3.1% increase of evaporation in scenarios; however, there is a steady increasing trend with about a 3.1% increase of evap- 2100 under the RCP 8.5 scenario. In other words, emissions increases will bring more oration in 2100 under the RCP 8.5 scenario. In other words, emissions increases will bring rainfall while causing more evaporation. However, both water-related characteristics did more rainfall while causing more evaporation. However, both water-related characteris- not display a linear trend over time, as opposed to the trends of those temperature metrics. tics did not display a linear trend over time, as opposed to the trends of those temperature Figure 7c,d shows that rates of change of temperature metrics are faster compared to those metrics. Figure 7c,d shows that rates of change of temperature metrics are faster compared of precipitation and evaporation over time, indicating higher sensitivities of temperature metrics to GHG emissions. Figure 8 is a clear indication of how more emissions will Earth 2021, 2, FOR PEER REVIEW 11 Earth 2021, 2 120 Earth 2021, 2, FOR PEER REVIEW 11 to those of precipitation and evaporation over time, indicating higher sensitivities of tem- perature metrics to GHG emissions. Figure 8 is a clear indication of how more emissions will increase the likelihood of water crises in the Western Cape. While the net water avail- increase the likelihood of water crises in the Western Cape. While the net water availability to those of precipitation and evaporation over time, indicating higher sensitivities of tem- ability is negative under all three emissions scenarios, the values under the RCP 2.6 and is negative under all three emissions scenarios, the values under the RCP 2.6 and RCP 8.5 perature metrics to GHG emissions. Figure 8 is a clear indication of how more emissions RCP 8.5 scenarios exhibit the opposite trend: For the RCP 2.6 scenario, water availability scenarios exhibit the opposite trend: For the RCP 2.6 scenario, water availability condition will increase the likelihood of water crises in the Western Cape. While the net water avail- condition in the Western Cape area improves after 2060 while the situation continues to in the Western Cape area improves after 2060 while the situation continues to get worse ability is negative under all three emissions scenarios, the values under the RCP 2.6 and get worse and worse under the RCP 8.5 scenario. and worse under the RCP 8.5 scenario. RCP 8.5 scenarios exhibit the opposite trend: For the RCP 2.6 scenario, water availability condition in the Western Cape area improves after 2060 while the situation continues to (a) Spatial Average Precipitation Spatial Average Evaporation (b) Regional Average Precipitation Regional Average Evaporation get worse and worse under the RCP 8.5 scenario. 101.5 91.5 100.5 (a) Spatial Average Precipitation Spatial Average Evaporation (b) Regional Average Precipitation Regional Average Evaporation 90.5 92 101 10 .5 0 RCP 2.6 RCP 2.6 91.5 89.5 101 99.5 91 RCP 4.5 RCP 4.5 100.5 90.5 88.5 RCP 8.5 RCP 8.5 90 100 98.5 88 RCP 2.6 RCP 2.6 89.5 99.5 87.5 98 RCP 4.5 RCP 4.5 1 2 3 4 5 6 7 8 1 2 3 4 5 6 7 8 88.5 RCP 8.5 20s 30s 40s 50s 60s 70s 80s RC9 P0 8s .5 20s 30s 40s 50s 60s 70s 80s 90s 98.5 88 Time Period Time Period 87.5 98 1 2 3 4 5 6 7 8 1 2 3 4 5 6 7 8 Regional Average Daily Maximum 20s 60s 20s 30s 40s 50s 60s 70s 80s 90s 30s 40s 50s 70s 80s 90s Spatial Average Near Surface Air Temperature (c) Spatial Average Daily Maximum Surface Air Temperature (d) Regional Average Near Surface Air Temperature Time Period Time Period 26 29.5 Near Surface Air Temperature 29 Regional Average Daily Maximum 25.5 Spatial Average Near Surface Air Temperature (c) Spatial Average Daily Maximum Surface Air Temperature (d) Regional Average Near Surface Air Temperature 28.5 26 29.5 Near Surface Air Temperature 24.5 25.5 29 27.5 28.5 24 25 RCP 2.6 RCP 2.6 24.5 23.5 RCP 4.5 RCP 4.5 26.5 27.5 24 RCP 2.6 RCP 2.6 2 27 6 RCP 8.5 RCP 8.5 23.5 RCP 4.5 RCP 4.5 22.5 26.5 25.5 22 RCP 8.5 RCP 8.5 22.5 25.5 1 2 3 4 5 6 7 8 1 2 3 4 6 50s 6 8 70s 9 80s 40s 50s 70s 20s 30s 40s 50s 60s 70s 80s 90s 20s 30s 22 25 Time Period Time Period 1 2 3 4 5 6 7 8 1 2 3 4 5 6 7 8 40s 50s 60s 70s 80s 90s 20s 30s 40s 50s 60s 70s 80s 90s 20s 30s Time Period Time Period Figure 7. Projection of regional averaged climate metrics in Western Cape, South Africa for 3 CO2 emissions scenarios: (a) Figure 7. Projection of regional averaged climate metrics in Western Cape, South Africa for 3 CO emissions scenarios: Figure 7. Projection of regional averaged climate metrics in Western Cape, South Africa for 3 CO2 emissions scenarios: (a) regional average precipitation; (b) regional average evaporation; (c) regional average near-surface air temperature; (d) (a) regional average precipitation; (b) regional average evaporation; (c) regional average near-surface air temperature; (d) regional average precipitation; (b) regional average evaporation; (c) regional average near-surface air temperature; (d) regional average daily maximum surface air temperature. regional average daily maximum surface air temperature. regional average daily maximum surface air temperature. Spatial Average Water Balance Regional Average Net Available Water Spatial Average Water Balance Regional Average Net Available Water -7 -7 1 2 3 4 5 6 80 7s 90 8s 20s 30s 40s 50s 60s 70s 1 2 3 4 5 6 80 7s 90 8s 20s 30s 40s 50s 60s 70s -8 -8 -9 -9 RCP 2.6 RCP 2.6 -10 -10 RCP 4.5 RCP 4.5 RCP 8.5 RCP 8.5 -11 -11 -12 -12 -13 Time Period -13 Time Period Figure 8. Projection of regional average water balance in Western Cape area for 3 CO2 emissions Figure 8. Projection of regional average water balance in Western Cape area for 3 CO emissions scenarios. Figure 8. Projection of regional average water balance in Western Cape area for 3 CO2 emissions scenarios. scenarios. Temperature-related characteristics such as near-surface air temperature and daily Temperature-related characteristics such as near-surface air temperature and daily maximum surface air temperature are more closely connected to GHG emissions compared maximum surface air temperature are more closely connected to GHG emissions com- to water Temperature -related metrics -related such char asac pr teristics ecipitation suc and h as evaporation. near-surface This air is tem because perature increasing and daily pared to water-related metrics such as precipitation and evaporation. This is because in- greenhouse gases will directly affect the temperature, and temperature will further cause maximum surface air temperature are more closely connected to GHG emissions com- rainfall creasing togree decr nho ease use and gases evaporation will direct toly incr affect easeth [33 e tem ]. perature, and temperature will fur- pared to water-related metrics such as precipitation and evaporation. This is because in- ther cause rainfall to decrease and evaporation to increase [33]. creasing greenhouse gases will directly affect the temperature, and temperature will fur- 3.3. Potential Policy Implications ther cause rainfall to decrease and evaporation to increase [33]. 3.3. Potential Policy Implications Based on the results shown above, it is more likely to see severer droughts across the Western Cape region when doing business as usual, as opposed to taking serious actions Based on the results shown above, it is more likely to see severer droughts across the 3.3. Potential Policy Implications and making policies to reduce GHG emissions. In terms of water availability, higher Western Cape region when doing business as usual, as opposed to taking serious actions Based on the results shown above, it is more likely to see severer droughts across the Western Cape region when doing business as usual, as opposed to taking serious actions Temperature (°C) Precipitation (mm/month) Temperature (°C) Precipitation (mm/month) Precipitation - Evaporation (mm/month) Precipitation - Evaporation (mm/month) Evaporation E (v m am po /r m ao tin o tn h )(mm/month) TempeT re at m ur p ee (r°a Ct )ure (°C) Earth 2021, 2 121 evaporation caused by regional warming offsets the relatively abundant rainfall for coastal regions, and those regions may suffer severer water crises than inland districts. Local government and policymakers could make efforts on at least two aspects to increase water availability and avoid the “Day-Zero” water crisis problem: controlling the emissions and at the same time, improving water usage efficiency and diversifying water supply sources. First, in terms of emissions constraining technology, many innovative technologies emerge as solutions to cut emissions. As an example of emission reduction, smart-grid technologies are becoming popular that can use artificial intelligence (AI) to introduce a layer of digital intelligence to the grid to enable the industry to respond to the grid dynamically, restore power interruptions, accommodate alternative energy options, and facilitate demand response strategies [34]. There is significant potential for improving the efficiency of the electrical energy value chain and efficiency by introducing AI-based smart-grid technologies [34]. Carbon-capture technologies may be a more localized ap- proach; however, these require global cooperation and collaboration to reach the level of significance. For improving water-usage efficiency, this requires citizens and government to adopt a water-sensitive approach in city planning and development that could include shifting water-management paradigms, developing new governance mechanisms, and guiding diversification of water supplies to provide resilience to potential future climate shocks [35]. In the meantime, local government should explore interventions that pro- mote and proactively encourage behavioral change and address inequity regarding water rights [35]. Finally, we have to emphasize the importance of governance across all adminis- trative levels [36], because all policies and measures against climate change and improving the livelihoods of the people that could last and be effective rely on proper governance. 4. Conclusions In this study, Co-ordinated Regional Climate Downscaling Experiment (CORDEX) data were used to examine the potential impacts of various greenhouse-gas emissions (RCP 2.6, RCP 4.5 RCP 8.5) on the future climate systems in six districts within the Western Cape, South Africa. The global simulations have been downscaled with RCA 4 for the future 80 years of the 21st century. The precipitation and evaporation data were used to approximately predict future drought in terms of net available water for the region. Both spatial–temporal analysis and regional-average analysis suggest the following: 1. Different climate metrics will respond differently to emissions scenarios. The projected simulation results reveal that temperature-related metrics are more sensitive to GHG emissions than water-related metrics as expected, as lower emissions can considerably alleviate climate vulnerability in Western Cape regions compared to business as usual. 2. Climate change poses a localized effect on different regions in Western Cape. Districts closer to the south coast are more resilient to regional warming compared to inland areas, but less so in terms of water stress. 3. A robust drying signal across the Western Cape region is likely to be seen in the near future if we continue doing business as usual (as seen in RCP 8.5). Efficient water-management practices and greenhouse-gas emissions reduction strategies are urgently needed to avoid more severe droughts such as the “Day-Zero” crisis in 2018, especially for the City of Cape Town and several other coastal regions within the Overberg and Eden district. This study highlights the importance of the impact of climate emissions scenarios (RCP 2.6, RCP 4.5, and RCP 8.5) on the regional climate change signals simulated by the model chain MPI-ESM/RCA4. Since this is the only GCM-RCM model combination available, the results cannot provide a comprehensive evaluation of possible climate change signals in the region. Nonetheless, the results sufficiently demonstrated the great potential of reducing climate risks and vulnerability under lower GHG emission scenarios for Western Cape region. When more downscaled climate data across different RCPs are available for Africa, it will enable uncertainty analyses and quantification of future climate change using a sufficiently large ensemble of simulations. Earth 2021, 2 122 Author Contributions: Conceptualization, B.H. and K.J.D.; methodology, B.H. and K.J.D.; software, B.H.; validation, B.H.; formal analysis, B.H.; investigation, B.H.; resources, B.H.; data curation, B.H.; writing—original draft preparation, B.H.; writing—review and editing, K.J.D.; visualization, B.H.; supervision, K.J.D.; Both authors have read and agreed to the published version of the manuscript. 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EarthMultidisciplinary Digital Publishing Institute

Published: Feb 26, 2021

Keywords: greenhouse gas (GHG); CO2 emissions; RCP; precipitation; evaporation; water balance; South Africa; Western Cape

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