Climate

Global warming poses great challenges for forest managers regarding adaptation strategies and species choices. More frequent drought events and heat spells are expected to reduce growth and increase mortality. Extended growing seasons, warming and elevated CO₂ (eCO₂) can also positively affect forest productivity. We studied the growth, productivity and mortality of beech (Fagus sylvatica L.) and fir (Abies alba Mill.) in the Black Forest (Germany) under three climate change scenarios (representative concentration pathways (RCP): RCP2.6, RCP4.5, RCP8.5) using the detailed biogeochemical forest growth model GOTILWA+. Averaged over the entire simulation period, both species showed productivity losses in RCP2.6 (16–20%) and in RCP4.5 (6%), but productivity gains in RCP8.5 (11–17%). However, all three scenarios had a tipping point (between 2035–2060) when initial gains in net primary productivity (NPP) (6–29%) eventually turned into losses (1–26%). With eCO₂ switched off, the losses in NPP were 26–51% in RCP2.6, 36–45% in RCP4.5 and 33–71% in RCP8.5. Improved water-use efficiency dampened drought effects on NPP between 4 and 5%. Tree mortality increased, but without notably affecting forest productivity. Concluding, cultivation of beech and fir may still be possible in the study region, although severe productivity losses can be expected in the coming decades, which will strongly depend on the dampening CO₂ fertilization effect. Full article

Sri Lanka is experiencing various social and environmental challenges, including drought, storms, floods, and landslides, due to climate change. One of Sri Lanka’s biggest cities, Kurunegala, is a densely populated city that is gradually turning into an economic revitalization area. This fast-growing city needs to establish an integrated urban plan that takes into account the risks of climate change. Thus, a climate change risk assessment was conducted for both the water and heat wave risks via discussions with key stakeholders. The risk assessment was conducted as a survey based on expert assessment of local conditions, with awareness surveys taken by residents, especially women. The assessment determined that the lack of drinking water was the biggest issue, a problem that has become more serious due to recent droughts caused by climate change and insufficient water management. In addition, the outbreak of diseases caused by heat waves was identified as a serious concern. Risk assessment is integral to developing an action plan for minimizing the damage from climate change. It is necessary to support education and awareness in developing countries so that they can perform risk assessment well and develop both problem-solving and policy-making abilities to adapt to a changing climate. Full article

Crop yield depends on multiple factors, including climate conditions, soil characteristics, and available water. The objective of this study was to evaluate the impact of projected temperature and precipitation changes on crop yields in the Monocacy River Watershed in the Mid-Atlantic United States based on climate change scenarios. The Soil and Water Assessment Tool (SWAT) was applied to simulate watershed hydrology and crop yield. To evaluate the effect of future climate projections, four global climate models (GCMs) and three representative concentration pathways (RCP 4.5, 6, and 8.5) were used in the SWAT model. According to all GCMs and RCPs, a warmer climate with a wetter Autumn and Spring and a drier late Summer season is anticipated by mid and late century in this region. To evaluate future management strategies, water budget and crop yields were assessed for two scenarios: current rainfed and adaptive irrigated conditions. Irrigation would improve corn yields during mid-century across all scenarios. However, prolonged irrigation would have a negative impact due to nutrients runoff on both corn and soybean yields compared to rainfed condition. Decision tree analysis indicated that corn and soybean yields are most influenced by soil moisture, temperature, and precipitation as well as the water management practice used (i.e., rainfed or irrigated). The computed values from the SWAT modeling can be used as guidelines for water resource managers in this watershed to plan for projected water shortages and manage crop yields based on projected climate change conditions. Full article

Recently, assessments of global climate model (GCM) ensembles have transitioned from using unweighted means to weighted means designed to account for skill and interdependence among models. Although ensemble-weighting schemes are typically derived using a GCM ensemble, statistically downscaled projections are used in climate change assessments. This study applies four ensemble-weighting schemes for model averaging to precipitation projections in the south-central United States. The weighting schemes are applied to (1) a 26-member GCM ensemble and (2) those 26 members downscaled using Localized Canonical Analogs (LOCA). This study is distinct from prior research because it compares the interactions of ensemble-weighting schemes with GCMs and statistical downscaling to produce summarized climate projection products. The analysis indicates that statistical downscaling improves the ensemble accuracy (LOCA average root mean square error is 100 mm less than the CMIP5 average root mean square error) and reduces the uncertainty of the projected ensemble-mean change. Furthermore, averaging the LOCA ensemble using Bayesian Model Averaging reduces the uncertainty beyond any other combination of weighting schemes and ensemble (standard deviation of the mean projected change in the domain is reduced by 40–50 mm). The results also indicate that it is inappropriate to assume that a weighting scheme derived from a GCM ensemble matches the same weights derived using a downscaled ensemble. Full article

Increasing evidence of changing climate patterns is being observed, and the impact of this change on groundwater has a direct impact on the livelihood and economy of the region. The research focuses on the impacts of global temperature increase and changing precipitation on the groundwater resources of part of the Himalayan river system. The spatial and temporal variations of the hydro-meteorological data of the Kankai River Basin in East Nepal were analyzed using non-parametric Mann–Kendall tests and Sen’s Slope methods, whereas CanESM2 was used to predict the future precipitation scenarios, and an attempt has been made to evaluate the possible impacts on groundwater systems in the region. The temperature shows a significant warming trend (0.14–0.64 °C/decade); however, the precipitation trends suggest remarkable variation mostly at higher elevation. The average annual precipitation suggests a decrease of 1.82 mm/year and a similar decrement has been projected for the future. The groundwater in the region has been influenced by the changing climate and the condition may further be exaggerated by reduced recharge and increased evapotranspiration. This understanding of the impacts and climate scenarios will help the planners with better adaptation strategies, plans, and programs for a better society. Full article

The Chitwan Annapurna Landscape (CHAL) is the central part of the Himalayas and covers all bioclimatic zones with major endemism of flora, unique agro-biodiversity, environmental, cultural and socio-economic importance. Not much is known about temperature and precipitation trends along the different bioclimatic zones nor how changes in these parameters might impact the whole natural process, including biodiversity and ecosystems, in the CHAL. Analysis of daily temperature and precipitation time series data (1970–2019) was carried out in seven bioclimatic zones extending from lowland Terai to the higher Himalayas. The non-parametric Mann-Kendall test was applied to determine the trends, which were quantified by Sen’s slope. Annual and decade interval average temperature, precipitation trends, and lapse rate were analyzed in each bioclimatic zone. In the seven bioclimatic zones, precipitation showed a mixed pattern of decreasing and increasing trends (four bioclimatic zones showed a decreasing and three bioclimatic zones an increasing trend). Precipitation did not show any particular trend at decade intervals but the pattern of rainfall decreases after 2000AD. The average annual temperature at different bioclimatic zones clearly indicates that temperature at higher elevations is increasing significantly more than at lower elevations. In lower tropical bioclimatic zone (LTBZ), upper tropical bioclimatic zone (UTBZ), lower subtropical bioclimatic zone (LSBZ), upper subtropical bioclimatic zone (USBZ), and temperate bioclimatic zone (TBZ), the average temperature increased by 0.022, 0.030, 0.036, 0.042 and 0.051 °C/year, respectively. The decade level temperature scenario revealed that the hottest decade was from 1999–2009 and average decade level increases of temperature at different bioclimatic zones ranges from 0.2 to 0.27 °C /decade. The average temperature and precipitation was found clearly different from one bioclimatic zone to other. This is the first time that bioclimatic zone level precipitation and temperature trends have been analyzed for the CHAL. The rate of additional temperature rise at higher altitudes compared to lower elevations meets the requirements to mitigate climate change in different bioclimatic zones in a different ways. This information would be fundamental to safeguarding vulnerable communities, ecosystem and relevant climate-sensitive sectors from the impact of climate change through formulation of sector-wise climate change adaptation strategies and improving the livelihood of rural communities. Full article

Climate change (CC) represents a global challenge for humanity. It is known that the impacts of anthropogenic actions are an unequivocal contribution to environmental issues aggravation. Human values are recognized as psychological constructs that guide people in their attitudes and actions in different areas of life, and the promotion of pro-environmental behaviors in the context of CC must be considered a priority. The present work aimed to understand the contribution of attitudes towards CC and selected sociodemographic variables to explain Schwartz’s motivational human values. The sample consists of 1270 Portuguese answering the European social survey (ESS) Round 8. Benevolence and self-transcendence are the most prevalent human values among respondents. The majority believe in CC and less than half in its entirely anthropogenic nature. It was found that the concern with CC and education contributes to explain 11.8% of the conservation variance; gender and concern about CC explain 10.1% of the variance of self-transcendence; and age, gender and concern about CC contribute to explain 13% of the variance of openness to change. This study underlines the main human values’ drivers of attitudes towards CC, central components in designing an effective societal response to CC impacts, which must be oriented towards what matters to individuals and communities, at the risk of being ineffective. Full article

Climate Change (CC) and variability are global issues that the world has been facing for a long time. Given the recent catastrophic events, such as flooding, erosion, and drought in Nigeria, many have questioned institutions’ capacity in managing CC impacts in Nigeria. This study explores emerging institutional barriers of adaptation to CC effects on water resources in Nigeria. The study data were obtained from in-depth interviews with institutional heads from water resources management and emergency management and a review of secondary literature from databases such as Google Scholar, Scopus, and Web of Science. The results show that inadequate hydrological data management, low awareness on how to adapt among the public and decision-makers, financial constraints, no political will to pass important bills into law, and inadequate institutional and legal framework are the main institutional barriers of adaptation to climate change in Nigeria. The study concludes that it is essential to strengthen the institutional and legal system, information management mechanism, public awareness, and participatory water resources management. The implications for further research are presented in the study. Full article

On-farm water storage (OFWS) systems are best management practices that consist of a tailwater recovery (TWR) ditch used with a storage pond to provide irrigation water and improve downstream water quality. These systems have been increasingly implemented in the southeastern US, but the individual and cumulative effects of these systems on a watershed scale are unknown. In this study, the runoff, nutrient, and sediment loads entering a TWR ditch in an agricultural catchment were quantified, and contributing sources were identified using the annualized agricultural non-point source (AnnAGNPS) model. Fields with larger areas and soils with a high runoff potential produced more runoff. The volume of runoff exceeded the TWR ditch storage volume approximately 110 times, mostly during the winter and spring seasons. During years when corn and winter wheat were planted, NO₃–N loads increased because these crops need nitrogen fertilization to grow. Planting winter wheat in priority subwatersheds reduced the total phosphorous (TP) and sediment loads by about 19% and 13%, respectively, at the TWR ditch inlet. Planting winter wheat can reduce runoff, TP, and sediment loads but also result in higher NO₃–N loads. AnnAGNPS simulations quantified the benefits of an OFWS system to advance the understanding of their impact on water availability and quality at a watershed scale. Full article

To reach a low-carbon economy in the Netherlands, the level of greenhouse gases (GHG) emissions has to be reduced by 80–95% CO₂ emissions compared to 1990 (223.1 MtCO₂-equivalents). This study aims to address how investment subsidies combined with carbon levies could be deployed to support technological mitigation options to achieve a low-carbon economy in the Netherlands in 2050. A system dynamic model has been built including demographic-economic, energy and environmental sub-systems of the Netherlands. The model has been validated with earlier projections of the EU for the energy and climate policy in 2050. Next to the business-as-usual scenario, there are four policy scenarios simulated from 2010 to 2050. In all policy scenarios a carbon levy was imposed on non-renewable energy to finance subsidies on mitigation options. Results show that imposing subsidies on the mitigation option renewable energy is most effective in combination with the carbon levy. Full article

Variations in urban form lead to the development of distinctive intra-urban surface thermal patterns. Previous assessment of the relation between urban structure and satellite-based Land Surface Temperature (LST) has generally been limited to single-city cases. Here, examining 25 European cities (June–August 2017), we estimated the statistical association between surface parameters—the impervious fraction (λ_imp), the building fraction (λ_b), and the building height (H)—and the neighborhood scale (1000 × 1000 m) LST variations, as captured by the Moderate Resolution Imaging Spectroradiometer (MODIS) sensor. Correlation analysis, multiple linear regression, and spatial regression were used. As expected, λ_imp had a consistent positive influence on LSTs. In contrast, the relation of LST with λ_b and H was generally weaker or negative in the daytime, whereas at night it shifted to a robust positive effect. In particular, daytime LSTs of densely built, high-rise European districts tended to have lower values. This was especially the case for the city of Athens, Greece, where a more focused analysis was conducted, using further surface parameters and the Local Climate Zone (LCZ) scheme. For the urban core of the city, the canyon aspect ratio H/W had a statistically significant (p <0.01) negative relationship with LST by day (Spearman’s rho = −0.68) and positive during nighttime (rho = 0.45). The prevailing intra-urban surface thermal variability in Athens was well reproduced by a 5-day numerical experiment using the meteorological Weather Research and Forecasting Model (WRF) model and a modified urban parameterization scheme. Although the simulation resulted in some systematic errors, the overall accuracy of the model was adequate, regarding the surface temperature (RMSE = 2.4 K) and the near-surface air temperature (RMSE = 1.7 K) estimations. Full article

We report a natural wind cycle, the Antarctic Centennial Wind Oscillation (ACWO), whose properties explain milestones of climate and human civilization, including contemporary global warming. We explored the wind/temperature relationship in Antarctica over the past 226 millennia using dust flux in ice cores from the European Project for Ice Coring in Antarctica (EPICA) Dome C (EDC) drill site as a wind proxy and stable isotopes of hydrogen and oxygen in ice cores from EDC and ten additional Antarctic drill sites as temperature proxies. The ACWO wind cycle is coupled 1:1 with the temperature cycle of the Antarctic Centennial Oscillation (ACO), the paleoclimate precursor of the contemporary Antarctic Oscillation (AAO), at all eleven drill sites over all time periods evaluated. Such tight coupling suggests that ACWO wind cycles force ACO/AAO temperature cycles. The ACWO is modulated in phase with the millennial-scale Antarctic Isotope Maximum (AIM) temperature cycle. Each AIM cycle encompasses several ACWOs that increase in frequency and amplitude to a Wind Terminus, the last and largest ACWO of every AIM cycle. This historic wind pattern, and the heat and gas exchange it forces with the Southern Ocean (SO), explains climate milestones including the Medieval Warm Period and the Little Ice Age. Contemporary global warming is explained by venting of heat and carbon dioxide from the SO forced by the maximal winds of the current positive phase of the ACO/AAO cycle. The largest 20 human civilizations of the past four millennia collapsed during or near the Little Ice Age or its earlier recurrent homologs. The Eddy Cycle of sunspot activity oscillates in phase with the AIM temperature cycle and therefore may force the internal climate cycles documented here. Climate forecasts based on the historic ACWO wind pattern project imminent global cooling and in ~4 centuries a recurrent homolog of the Little Ice Age. Our study provides a theoretically-unified explanation of contemporary global warming and other climate milestones based on natural climate cycles driven by the Sun, confirms a dominant role for climate in shaping human history, invites reconsideration of climate policy, and offers a method to project future climate. Full article

Mid-tropospheric cut-off low (COL) pressure systems are linked to severe weather, heavy rainfall and extreme cold conditions over South Africa. They occur during all the above and often result in floods and snowfalls during the winter months, disrupting economic activities and causing extensive damage to infrastructure. This paper examines the evolution and circulation patterns associated with cases of severe COLs over South Africa. We evaluate the performance of the 4.4 km Unified Model (UM) which is currently used operationally by the South African Weather Service (SAWS) to simulate daily rainfall. Circulation variables and precipitation simulated by the UM were compared against European Centre for Medium-Range Weather Forecast’s (ECMWF’s) ERA Interim re-analyses and GPM precipitation at 24-hour timesteps. We present five recent severe COLs, which occurred between 2016 and 2019, that had high impact and found a higher model skill when simulating heavy precipitation during the initial stages than the dissipating stages of the systems. A key finding was that the UM simulated the precipitation differently during the different stages of development and location of the systems. This is mainly due to inaccurate placing of COL centers. Understanding the performance and limitations of the UM model in simulating COL characteristics can benefit severe weather forecasting and contribute to disaster risk reduction in South Africa. Full article

To examine the evidence of global warming, in recent years, there has been a growing interest in the statistical analysis of time-dependent meteorological data. In this paper, for 116 observational stations in the world, sequential variations of the monthly distributions of meteorological data are analyzed vectorially. For specific monthly data, temperatures and precipitations are chosen, both of which are averaged over three decades. Climate change can be revealed through the intersecting angle between two 33-dimensional vectors being composed with monthly mean values. Subsequently, the angle data for the entire stations are analyzed statistically and compared between the former (1931–1980) and the latter (1951–2010) periods. Irrespective of the period and the hemisphere, the variation of the angles is found to show the exponential growth as a function of their latitudes. Furthermore, consistent with other studies, this trend is shown to become stronger in the latter period, indicating that the so-called snow/ice-albedo feedback occurs. In contrast to the temperatures, for the precipitations, no significant correlation is found between the angle and the latitude. To examine the albedo effect in more detail, a regional analysis for 75 stations in Japan is carried out as well. Numerical results show that the effect is significant even for the relatively narrow latitudinal range (19%) of the hemisphere. Finally, a synchronization of the monthly patterns of temperatures is given between the northern district of Japan and both North America and Eastern Europe. Full article

African countries such as Nigeria are anticipated to be more susceptible to the impacts of climate change due to large dependence on rainfed agriculture and to several uncertainties in the responses of crop production to climate change. The impacts of climate change on crop water requirements (CWR), irrigation water requirements (IWR), yields and crop water productivity (CWP) of rainfed maize in Ogun-Osun River Basin, Nigeria were evaluated for a baseline period (1986–2015) and future projection period (2021–2099) under Representative Concentration Pathway (RCP) 4.5 and RCP 8.5 scenarios. For the baseline period, there is no significant trend within the variables studied. However, IWR is projected to increase significantly by up to 140% in the future period, while yield might likely decline under both scenarios up to −12%. This study shows that in the future periods, supplemental irrigation has little impact in improving yields, but an increase in soil fertility can improve yields and CWP by up to 80% in 2099. This paper offers useful information on suitable adaptation measures which could be implemented by stakeholders and policymakers to counterbalance the effects of climate change on crop production. Full article

Cities in Australia are experiencing unprecedented levels of urban overheating, which has caused a significant impact on the country’s socioeconomic environment. This article provides a comprehensive review on urban overheating, its impact on health, energy, economy, and the heat mitigation potential of a series of strategies in Australia. Existing studies show that the average urban heat island (UHI) intensity ranges from 1.0 °C to 13.0 °C. The magnitude of urban overheating phenomenon in Australia is determined by a combination of UHI effects and dualistic atmospheric circulation systems (cool sea breeze and hot desert winds). The strong relation between multiple characteristics contribute to dramatic fluctuations and high spatiotemporal variabilities in urban overheating. In addition, urban overheating contributes to serious impacts on human health, energy costs, thermal comfort, labour productivity, and social behaviour. Evidence suggest that cool materials, green roofs, vertical gardens, urban greenery, and water-based technologies can significantly alleviate the UHI effect, cool the ambient air, and create thermally balanced cities. Urban greenery, especially trees, has a high potential for mitigation. Trees and hedges can reduce the average maximum UHI by 1.0 °C. The average maximum mitigation performance values of green roofs and green walls are 0.2 °C and 0.1 °C, respectively. Reflective roofs and pavements can reduce the average maximum UHI by 0.3 °C. In dry areas, water has a high cooling potential. The average maximum cooling potential using only one technology is 0.4 °C. When two or more technologies are used at the same time, the average maximum UHI drop is 1.5 °C. The mitigation strategies identified in this article can help the governments and other stakeholders manage urban heating in the natural and built environment, and save health, energy, and economic costs. Full article

Climate change is posing a variety of challenges in the built realm. Among them is the change in future energy consumption and the potential decay of current energy efficient paradigms. Indeed, today’s near-zero Energy buildings (nZEBs) may lose their virtuosity in the near future. The objective of this study is to propose a methodology to evaluate the change in yearly performance between the present situation and future scenarios. Hourly dynamic simulations are performed on a residential nZEB located in Rome, built in compliance with the Italian legislation. We compare the current energy consumption with that expected in 2050, according to the two future projections described in the Fifth Assessment Report (AR5) by the Intergovernmental Panel on Climate Change (IPCC). Implications for thermal comfort are further investigated by assuming no heating and cooling system, and by tracking the free-floating operative temperature. Compared to the current weather conditions, the results reveal an average temperature increase of 3.4 °C and 3.9 °C under RCP4.5 and RCP8.5 scenarios, estimated through ERA-Interim/UrbClim. This comes at the expense of a 47.8% and 50.3% increase in terms of cooling energy needs, and a 129.5% and 185.8% decrease in terms of heating needs. The annual power consumption experiences an 18% increase under both scenarios due to (i) protracted activation of the air conditioning system and (ii) enhanced peak power requirements. A 6.2% and 5.1% decrease in the hours of adaptive comfort is determined under the RCP4.5 and RCP8.5′s 2050 scenarios out of the concerted action of temperature and solar gains. The results for a newly proposed combined index for long-term comfort assessments reveal a milder future penalty, owing to less pronounced excursions and milder daily temperature swings. Full article

Climate-Smart Villages (CSVs) were established by the CGIAR Research Program on Climate Change, Agriculture and Food Security (CCAFS) in the East African countries of Kenya, Tanzania and Uganda to test and promote a portfolio of climate-smart agriculture (CSA) practices that have climate change mitigation potential. This study evaluated the soil carbon sequestration potential of these CSVs compared to the control land use that did not have CSA practices. At the one-meter depth, soil carbon stocks increased by 20–70%, 70–86%, and 51–110% in Kenya, Tanzania and Uganda CSVs, respectively, compared to control. Consequently, CSVs contributed to the reduction of emissions by 87–420 Mg CO₂ eq ha⁻¹. In the topsoil (0–15 cm), CSVs sequestered almost twice more soil carbon than the control and subsequently emissions were reduced by 42–158 Mg CO₂ eq ha⁻¹ under CSVs. The annual increase in carbon sequestration under CSVs ranged between 1.6 and 6.2 Mg C ha⁻¹ yr⁻¹ and substantially varied between the CSA land use types. The forests sequestered the highest soil carbon (5–6 Mg C ha⁻¹ yr⁻¹), followed by grasslands and croplands. The forest topsoil also had lower bulk density compared to the control. The findings suggest that CSA practices implemented through the CSVs approach contribute to climate change mitigation through soil carbon sequestration. Full article

This paper tries to shift the focus of research on the impact of natural disasters on economic growth from global and national levels to sub-national levels. Inadequate sub-national level information is a significant lacuna for planning spatially targeted climate change adaptation investments. A fixed-effect panel regression analyses of 19 states from 2001 to 2015 assess the impacts of exposure to floods and droughts on the growth of gross state domestic product (GSDP) and human development index (HDI) in India. The flood and drought exposure are estimated using satellite data. The 19 states comprise 95% of the population and contribute 93% to the national GDP. The results show that floods indeed expose a large area, but droughts have the most significant impacts at the sub-national level. The most affected GSDPs are in the non-agriculture sectors, positively by the floods and negatively by droughts. No significant influence on human development may be due to substantial investment on mitigation of flood and drought impacts and their influence on better income, health, and education conditions. Because some Indian states still have a large geographical area, profiling disasters impacts at even smaller sub-national units such as districts can lead to effective targeted mitigation and adaptation activities, reduce shocks, and accelerate income growth and human development. Full article