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Spatial dependence of temperature increases and threshold-crossing times. a, Median year of crossing a 2 °C threshold under the IPCC SRES A1B emissions scenario. A large part of the Northern Hemisphere is projected to experience such temperatures during the 2030s or 2040s. b, The expected regional temperatures when global average temperature reaches 2 °C. The spatial patterns are non-uniform.
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Climate change projections are usually presented as 'snapshots' of change at a particular time in the future. Instead, we consider the key question 'when will specific temperature thresholds be exceeded?' Framing the question as 'when might something happen (either permanently or temporarily)?' rather than 'what might happen?' demonstrates that low...
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... Fig. 1 presents a world map of cumulative carbon emissions since 1750 [3], which conveys the overarching contributions from the industrialized economies, namely the United States and Europe. Concomitant to increasing atmospheric CO 2 levels is an increase in the average global temperature, presently approximately 1 C above pre-industrial levels, and without intervention is poised to reach or surpass 2 C above pre-industrial levels in the second half of this century; this threshold must not be surpassed to limit the adverse consequences of climate change [4]. ...
... An increase from 0.48 to 16.55 mm in ensemble SREV is observed from the 95th to 100th percentiles, which is comparably low with other homogeneous regions. Even on a smaller scale, regions with little internal variability may be more predictable than others (Deser et al., 2012;Joshi et al., 2011). The mean values of uncertainties over the six homogeneous regions along with all India mean values are given in Supporting Information (Tables S5 and S6). ...
Global climate model (GCM) projections are subject to significant uncertainties. Quantifying uncertainties in climate change projections improves credibility and makes climate data more reliable. This study aims to quantify the uncertainties in projected extreme precipitation during the 21st century over the homogeneous rainfall regions of India simulated by Coupled Model Intercomparison Project Phase 6 (CMIP6) GCMs. The percentile‐based square root error variance (SREV) method estimates model, scenario and ensemble uncertainties in projections of extreme precipitation. The uncertainty is investigated at four thresholds: 95th, 99th, 99.9th and 100th percentiles. The results show that the wet northeast region has a greater SREV, which is consistent with previous studies. At 99th and 99.9th percentiles, relative model SREV is dominant over the northeast (NE) region. However, at the 95th percentile high relative model SREV is found over the northwest (NW) region during southwest (June, July, August and September) and NE (October, November and December) monsoon seasons. Model uncertainty is the main source of uncertainty, followed by scenario and ensemble uncertainties. The study indicates that the arid NW region in India has a higher level of uncertainty than other regions with homogeneous rainfall. These findings will assist policymakers in planning infrastructure development in arid regions of India.
... Previous studies have shown that the SAT over land has increased by a substantial amount and at an unprecedented pace during the past century, and the spatial and temporal patterns of this warming are non-uniform ) (Ji et al. 2014;Stocker et al. 2014). Some recent studies have reported the spatial distribution of the 2 °C global temperature increase over land (Joshi et al. 2011;Wang and Dillon 2014). However, these studies are limited to local areas, do not employ comprehensive emissions scenarios, and cannot fully display the spatial distribution of the 2 °C global temperature increase over land. ...
The Paris Agreement establishes targets for the increase in global mean temperature of 1.5 °C and 2 °C, relative to pre-industrial levels. Recent studies suggest that the climate change impacts of these two goals are markedly different, and the additional 0.5 °C increase in the global mean surface air temperature (SAT) may lead to drastic, non-linear increases in the extreme and average temperatures of most regions. In this study, we use model results from the Coupled Model Intercomparison Project 5 (CMIP5) to illustrate the asymmetric nature of the warming trends that will result over the global land area under these two climate change targets. The results show that the SAT increase reaches 1.5 °C by 2040 (2040 ± 6), considering RCP2.6 to RCP8.5, whereas the SAT increase reaches 2.0 °C by 2060 (2060 ± 12), considering RCP4.5 to RCP8.5. The SAT increase over land is meridionally and zonally asymmetric, especially in the Northern Hemisphere. What’s global warming and rising concentrations of emissions will exacerbate the asymmetric warming from north to south especially over land. In addition to the longitudinal changes, the magnitude of the SAT increase at higher latitudes is significantly greater than that of comparable areas at middle to low latitudes. Additionally, the time of the SAT increase over the high-latitude land areas occurs much earlier than elsewhere. In addition, the difference in the timing of this onset in the longitudinal direction is substantial, but the difference in the zonal direction is small. Furthermore, the SAT increase over most of the global land area reaches 1.5 °C before the middle of twenty-first century and reaches 2.0 °C before 2070. In addition, over 20% of the global land area, the SAT increase reaches 1.5 °C before 2006, whereas almost none of the land area exhibits a change of 2.0 °C before 2006.
... This paper especially concerns SDG 13, which calls for climate actions by improving energy efficiency, increasing environmental investments, reducing greenhouse gas emissions, especially carbon footprint, and tackling risks caused by climate change. The challenge set by the United Nations Framework Convention on Climate Change is to limit the global temperature increase to below 2°C above pre-industrial levels (Joshi et al., 2011;Gao et al., 2017;;Warren et al., 2018). Therefore, countries worldwide must change the way they operate in agriculture, energy, industry, and transport systems (Sachs, 2006;Sovacool & Brown, 2010;Brown, 2013;Owusu & Asumadu-Sarkodie, 2016;Iglinski et al., 2021). ...
Nowadays, the topic of CO2 emissions has been a subject of intensive debate. There is a significant policy push toward reducing emissions that cause air pollution and other environmental concerns. The aim of this paper is to analyze the CO2 emissions as well as economic growth along with renewable energy use and the level of urbanization in the selected World countries in the period of 1995-2018. In general, almost all of the Northern part of the World was characterized by a high level of CO2 emissions, while the majority of African territory was the least polluted. The empirical result shows that the growth rate of air pollution is much higher in countries that initially had a low level of CO2 emissions, so the convergence process occurred. Conditioning convergence with the renewable energy use and the urbanization level indicates that its speed is higher. Club convergence analysis has proved that well-developed regions in terms of GDP per capita are able to improve the ecological situation despite further economic growth.
... The trend detection studies have been considered a valuable instrument since it offers meaningful insight about the probability of future changes (Lima et al. 2008). However, projecting future climatic variables is more valuable to planners because it helps them comprehend the present and historical climate changes (Joshi et al. 2011). A regional forecasting approach might be used to project future knowledge about climatic factors, in supplementary to the complex climate model that operates on a global scale (Elbeltagi et al. 2022a, b;Lambin et al. 2003). ...
Gujarat contributes to around 16% of industrial and 12% of agricultural production in India (GoI, India: greenhouse gas emissions 2007. Technical report. Ministry of Environment and Forests, Government of India, New Delhi, 2010b). The Government of Gujarat acknowledges that Climate Change is not just a threat to the environment; it has profound implications for economic expansion, social progress, and nearly all other aspects of human wellbeing (Grafton et al., Nat Clim Chang 3:315–321, 2013). A Department of Climate Change has been established by the government of Gujarat to deal with climate change (GoI, Twelfth five year plan (2012–2017). Economic sectors. Government of India, New Delhi, 2013). It includes Missions on Solar Energy, Augmented Power Efficiency, Resilient Ecosystems, Water, Green procurement India, Climate resilient Agriculture, and Collaborative Knowledge for Climate Change (Bring et al., Earth’s Future 3:206–217, 2015). The state of Gujarat has put in place a variety of policies and programs to address some of the issues associated with Climate Change while also assuring the attainment of sustainable development goals (Doll and Bunn, The impact of climate change on freshwater ecosystems due to altered river flow regimes. In: Climate change 2014. Assessment report of the Intergovernmental Panel on Climate Change, pp 143–146, 2014). Efforts are being taken to make farming more environmentally friendly, like setting up agro-meteorological field stations, setting up automatic weather stations, and studying Climate Change in State agriculture universities (Douglas et al., Glob Planet Chang 67:117–128, 2009). According to the Department of Agriculture, Gujarat, about 51% of the state’s land is used for farming. Agriculture makes up about 18.3% of India’s most populous state’s GDP (GoI, Climate change and India: a 44 assessment a sectoral and regional analysis for 2030s. Technical report. Ministry of Environment and Forests, Government of India, New Delhi, 2010a). Despite the Government’s efforts to address climate change, challenges persist. Agriculture in India faces numerous difficulties, one of which includes environmental unpredictability (Gosling et al., Hydrol Earth Syst Sci 7:279–294, 2011). A report from the IPCC says that by 2080–2100, India could lose 10%–40% of its crop production due to climate change. The cumulative result is expected to be a reduction in the viability of terrain for agriculture in arid and semi-arid regions. Salt concentrations’ infiltration is an issue in Gujarat due to its lengthy shoreline (Garduno et al., India groundwater governance case study. Technical report. World Bank, Washington, DC, 2011). An increase in CO2 will increase the output of rice, wheat, legumes, and oilseeds by 10–20%. With each degree Celsius increase in temperature, yields of grains such as wheat, soybeans, mustard, peanuts, and potato are expected to fall by 3%–7%. There is a probability that yields of chickpeas, rabi, maize, millets, and coconuts will increase on the west coast of India (Hsu et al., J Geophys Res Atmos 118:1247–1260, 2013). In particular, to the state of Gujarat, there are not nearly enough data on the impacts of climate change on agriculture. It is anticipated that irrigated rice production in some parts of Gujarat will go down by 2030 (Gordon et al., Natl Acad Sci 102:7612–7617, 2005). According to the most recent available information, climate change will almost certainly result in more people at threat of going hungry. In 2080, the number of people who are not well-fed could rise by 5%–26% because of climate change. Agriculture, according to some assessments, is likely to be impacted in coastal regions since agriculturally productive areas are subject to flooding and soil salinity (Ghose, J Sci Ind Res 60:40–47, 2001). Climate change will have different impacts on food security in different regions of the state of Gujarat. Climate change will make it more difficult for people living in poor socio-economic regions to get their food and make food insecurity even more important (Hoff, Understanding the nexus. Background paper for the Bonn 2011. Stockholm Environment Institute, Stockholm, 2011). The future policy environment will have a significant impact on the long-term effects of climate change (GRDC, Long-term mean monthly discharges and annual characteristics of GRDC stations/online provided by the Global Runoff Data Centre of WMO 3 19. http://www.bafg.de/GRDC/EN/01_GRDC/grdc_node.html, 2020).
... With an existing warming rate of 0.2 °C/decade, global warming could reach 1.5 °C between 2030 and 2052 (IPCC 2018). The Northern Hemisphere is expected to get warmer (Sutton et al. 2007) and is predicted to cross the 2 °C target before global mean annual surface air temperature (Joshi et al. 2011). The present emission scenarios are already either following or very close to the highest emission pathway (RCP 8.5) in future (Sanford et al. 2014). ...
With rising global warming levels (GWL), the severity and frequency of temperature extremes have also increased across the globe. The rural and poor population of developing countries may be more vulnerable due to their limited reliable and relevant adaptation and mitigation capacities. In this context, we investigate the change in temperature extremes and associated area and population exposure over India under 1.5 °C and 2 °C world warmings. We also examined the benefits of 0.5 °C less warming on the area and population exposure over India. Temperature extremes were calculated from the daily maximum and minimum temperature data of 19 CMIP5 models for the RCP 8.5 scenario. We find that almost all of India is warming greater than the global average under both the warming levels. All the temperature extreme indices exhibit a pronounced increase under 2 °C global warming level (GWL) as compared to 1.5 °C GWL. We find a declining severity of extreme cold events and increasing in warm events. We find the largest warming in the western Himalayan region under both GWLs. A 0.5 °C reduction in GWL will not only limit the severity of temperature extremes but also reduce the population exposure by 44% and the area exposure by 50%. The study provides a reliable and inclusive assessment of projected GWL and the benefits of 0.5 °C less warming.
... Over the last several decades, many studies on global and regional climate change have been conducted at different temperature rise targets under future emission scenarios (Aihaiti et al., 2021;Hu et al., 2017;Huang et al., 2017;Joshi et al., 2011;Ullah et al., 2020;Wang et al., 2018;Zhai et al., 2017;Zhang, Zhuang, et al., 2018. The IPCC issued "the special report on global warming at 1.5°C" in 2018, which pointed out that the extreme weather and climate events led by temperature and precipitation changes, such as heat waves, floods and drought, will be more frequent and stronger with the enhancement of global temperature rise targets, causing the climate-related risks to become substantially higher (Intergovernmental Panel on Climate Change (IPCC), 2018). ...
Changes in temperature and precipitation have a profound effect on the ecological environment and socioeconomic systems. In this study, we focus on the major Belt and Road Initiative (BRI) regions and develop a dataset of temperature and precipitation at global temperature rise targets of 1.5°C, 2°C, and 3°C above pre-industrial levels under the Representative Concentration Pathway (RCP) 8.5 emission scenario using 4 downscaled global model datasets data at a fine spatial resolution of 0.0449147848° (~5 km) globally from EnviDat. The temperature variables include the daily maximum (Tmax), minimum (Tmin) and average (Tmp) surface air temperatures, and the diurnal temperature range (DTR). We first evaluate the performance of the downscaled model data using CRU-observed gridded data for the historical period 1986–2005. The results indicate that the downscaled model data can generally reproduce the pattern characteristics of temperature and precipitation variations well over the major BRI regions for 1986–2005. Furthermore, we project temperature and precipitation variations over the major BRI regions at global temperature rise targets of 1.5°C, 2°C, and 3°C under the RCP8.5 emission scenario based on the dataset by adopting the multiple-model ensemble mean. Our dataset contributes to understanding detailed the characteristics of climate change over the major BRI regions, and provides data fundamental for adopting appropriate strategies and options to reduce or avoid disadvantaged consequences associated with climate change over the major BRI regions. The dataset is available at https://doi.org/10.57760/sciencedb.01850.
... Future projections based on observed climate trends indicate that temperatures in SSA are consistently rising at an alarming rate compared to the global average increase during the 21st century [19][20][21][22]. Therefore, it is most likely that SSA might be strongly affected by climate change. ...
Climate change is negatively affecting agricultural production in the Sahel region. Climate-Smart Agricultural Technologies (CSATs) are disseminated to reduce these negative effects, and particularly those on resource-poor farm households. This article investigates the distributional impacts of the adoption of CSAT on-farm households’ welfare using a dataset that covers four regions, 32 communes, 320 villages, and 2240 households in Mali. Using an instrumental variable quantile treatment effects model, the paper addresses the potential endogeneity arising from the selection bias and the heterogeneity of the effect across the quantiles of the outcome variables’ distribution. The results show that the adoption of CSAT is positively associated with improved households’ welfare. The farmers’ decision to adopt any CSAT is influenced by access to credit, contact with extension agents, participation in training, access to information through the television, and being a member of any organization such as a cooperative society. Moreover, the effect of the adoption of CSAT on household welfare varies across the different households. In particular, the results show that the impact of the adoption of CSAT on households’ welfare is generally higher for the poorest (farmers located at the bottom tail of the distribution) end of the welfare distribution. The findings, therefore, highlight the pro-poor impact of the adoption of CSAT in the rural Malian context, as well as the need to tailor the CSAT interventions toward specific socio-economic segments of the rural population in Mali.
... In addition, we collected ancillary ecological and experimental information, including latitude, longitude, elevation, annual mean air temperature (MAT), mean annual precipitation (MAP), ecosystem types (arctic/alpine tundras, boreal forests, [semi]arid grasslands, temperate grasslands, and temperate forests), warming methods (open-top chambers, infrared radiators, and greenhouses), warming season (year-round and seasonal warming), warming magnitude (<2 and ≥2°C; holding global warming at 2°C above pre-industrial temperature was considered as a "safe level" of warming ;Joshi et al., 2011), and experimental duration (≤2, 2-5, and >5 years; ...
Climate warming is changing plant sexual reproduction, having consequences for species distribution and community dynamics. However, the magnitude and direction of plant reproductive efforts (e.g., number of flowers) and success (e.g., number and mass of fruits or seeds) in response to warming have not been well-characterized. Here we generated a global dataset of simulated warming experiments, consisting of 477 pairwise comparisons for 164 terrestrial species. We found evidence that warming overall decreased fruit number and increased seed mass, but little evidence that warming influenced flower number, fruit mass, or seed number. The warming effects on seed mass were regulated by the pollination type, and insect-pollinated plants exhibited a stronger response to warming than wind-pollinated plants. We found strong evidence that warming increased the mass of seeds for the nondominant species but no evidence of this for the dominant species. There was no evidence that phylogenetic relatedness explained the effects of warming on plant reproductive effort and success. In addition, the effects of warming on flowering onset negatively related to the responses in terms of the number of fruits and seeds to warming, revealing a cascading effect of plant reproductive development. These findings provide the first quantification of the response of terrestrial plant sexual reproduction to warming and suggest that plants may increase their fitness by producing heavier seeds under a warming climate.
... The relationship between VPD and soil moisture is debated and at times difficult to disentangle, particularly in moisture-limited conditions 9,22 . [32][33][34]. We project that, when the 2 °C threshold is breached, 7 of 13 Arabica-producing countries assessed have a non-zero probability of surpassing the VPD threshold under baseline (1985-2015) conditions (Fig. 4a). ...
... At 2.69 °C, this increased to a probability of 0.5, and at 2.85 °C to a probability of 0.75. At 3.03 °C, by 2050-2075 under a high-emissions scenario [32][33][34] , when Brazil breaches the threshold, countries currently contributing 75% to global supply are, according to our analysis, certain to exceed the VPD threshold ( The probability of surpassing the VPD threshold increases with global warming temperatures (relative to pre-industrial) for each country (Fig. 5c). El Salvador, Kenya, Tanzania and Mexico, collectively accounting for ~5.5% of global supply, surpass the threshold under baseline conditions (that is, at 0.7 °C above pre-industrial conditions). ...
Our understanding of the impact of climate change on global coffee production is largely based on studies focusing on temperature and precipitation, but other climate indicators could trigger critical threshold changes in productivity. Here, using generalized additive models and threshold regression, we investigate temperature, precipitation, soil moisture and vapour pressure deficit (VPD) effects on global Arabica coffee productivity. We show that VPD during fruit development is a key indicator of global coffee productivity, with yield declining rapidly above 0.82 kPa. The risk of exceeding this threshold rises sharply for most countries we assess, if global warming exceeds 2 °C. At 2.9 °C, countries making up 90% of global supply are more likely than not to exceed the VPD threshold. The inclusion of VPD and the identification of thresholds appear critical for understanding climate change impacts on coffee and for the design of adaptation strategies.
