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There are many uncertainties in future climate, including how the Earth may react to different types of radiative forcing, such as CO2, aerosols, and even geoengineered changes in the amount of sunlight absorbed by Earth's surface. Here, we analyze model simulations where the climate system is subjected to an abrupt change of the solar constant by ±4%, and where the atmospheric CO2 concentration is abruptly changed to quadruple and half its preindustrial value. Using these experiments, we examine how clouds respond to changes in solar forcing, compared to CO2, and feedback on global surface temperature. The total cloud response can be decomposed into those responses driven by changes in global surface temperature, called the temperature mediated cloud feedbacks, and responses driven directly by the forcing that are independent of the global surface temperature. In this paper, we study the temperature mediated cloud changes to answer two primary questions: (a) How do temperature mediated cloud feedbacks differ in response to abrupt changes in CO2 and solar forcing? And (b) Are there symmetrical (equal and opposite) temperature mediated cloud feedbacks during global warming and global cooling? We find that temperature mediated cloud feedbacks are similar in response to increasing solar and increasing CO2 forcing, and we provide a short review of recent literature regarding the physical mechanisms responsible for these feedbacks. We also find that cloud responses to warming and cooling are not symmetric, due largely to non‐linearity introduced by phase changes in mid‐to‐high latitude low clouds and sea ice loss/formation. Plain Language Summary: As the global mean temperature changes, there are changes in cloud amount, location, and thickness, which can all impact the radiative balance of the Earth. Cloud changes driven directly by global temperature change are called temperature mediated cloud feedbacks. In this paper, we study the temperature mediated cloud feedbacks that occur in model simulations where the amount of sunlight incident upon the Earth is increased or decreased abruptly, and then held constant for 150 years. We compare the cloud changes in these experiments with experiments where the CO2 concentration is similarly increased or decreased abruptly and held constant for 150 years. In doing so we find that the temperature mediated cloud feedbacks following abrupt changes in solar radiation are characteristically similar to those occurring following CO2 increase. There are however substantial differences in the temperature mediated cloud feedbacks that occur while the climate is warming versus cooling. Key Points: The temperature mediated cloud changes and feedbacks incurred by changes in solar and CO2 forcing are similarOptical depth changes at high latitudes produce substantial differences in cloud feedbacks in cooling and warming experimentsLikewise, tropical circulations respond differently in models to cooling and warming, with a stronger change in the Walker circulation in warming experiments [ABSTRACT FROM AUTHOR]

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The Report: Intergovernmental Panel on Climate Change (IPCC) set a goal global warming of 1.5°C on global temperature change. Extreme climate changes have increased the demand for electricity consumption by people and enterprises. In fact, China's total power generation in 2019 exceeded 25% of the world's amount, and its thermal power generation accounted for more than 70%. Although past research on electricity efficiency seldom discusses the issue of climate change, the topic still remains important. This research thus considers extreme temperature days (climate change variable) as exogenous variable and uses the Two-Stage Meta Under exogenous undesirable EBM model to examine power efficiency in China. The results are as follows. (1) In the west only Qinghai's GDP, CO2, PM2.5, and electricity consumption have technology gap ratio (TGR) efficiency values of 1 in the 5 years. (2) China's electricity consumption has the same trend with the TGR efficiency of CO2 and is higher than PM2.5. (3) The national overall efficiency, meta overall efficiency, and TGR overall efficiency are the worst in China's west region. [ABSTRACT FROM AUTHOR]

The major cause of global warming is greenhouse gases (GHGs). Carbon dioxide (CO2) is the key GHG contributing to environmental pollution and global warming. Overall climatic conditions are changing with global temperatures rising and the level of greenhouse gases increase in the atmosphere. This is of serious concern as this climatic change will have dire consequences for crops, human health, ecological balance and biodiversity. Climatic changes and imbalance in ecology can be ascribed to an increase in carbon-dioxide emissions in the environment. South Africa being a developing economy is at the thirteenth position in carbon-dioxide emissions. It is also one of the developing countries that top in consumption of fossil fuels. It is important to forecast future carbon-dioxide emissions for South Africa so that suitable sustainability policies can be framed and measures can be taken at the right time. Annual time series data of South Africa from the time period 1980 to 2016, has been used in this study to develop autoregressive integrated moving average (ARIMA) model to predict CO2 emissions for the period of 2015–2027. It is forecasted by the use of the ARIMA model that carbon-dioxide emissions will rise at a constant rate in the next ten years in South Africa. This study will add a new dimension to existing literature and will provide a base for framing feasible environmental policies. [ABSTRACT FROM AUTHOR]

Global warming is among the important environmental problems of the earth. The present research aims to study temperature variations around the world. For this purpose, the monthly temperature data of 178 points from the NOAA site were studied from 1950 to 2019. In this study, the temperature changes were investigated in terms of its increase, decrease, and significance level by the Mann–Kendall method. Geographic Information System (GIS) and interpolation methods were used to determine the changes in temperature in global warming maps. According to the obtained results, except for 3.8% of the designated area, other parts of the world show change toward warmer conditions. Overall, the world's land temperature has increased by 1.08℃ during the study period. Also, about 85% of the designated area shows moderate and severe hazardous conditions in terms of global warming. The spatial analysis showed higher change and hazardous conditions for global warming in mid-longitude and high-latitude close to both poles. [ABSTRACT FROM AUTHOR]

There is low confidence in projections of Antarctic sea ice area (SIA), due to deficiencies in climate model sea ice processes. Ensemble regression techniques can help to reduce this uncertainty. We investigate relationships between SIA climatology and 21st century change in the Coupled Model Intercomparison Project, phase 6 (CMIP6) multi‐model ensemble. In summer, under a strong forcing scenario, each model loses the majority of its sea ice. Therefore, models with greater historical SIA exhibit greater reductions, so the observed climatology of SIA strongly constrains projections. Ensemble spread in historical summer SIA is smaller than in CMIP phase 5 (CMIP5), and CMIP6 gives a more robust constraint on future SIA. In winter, by 2100 under a strong forcing scenario, 40% of SIA disappears on average, and ensemble spread in historical mean SIA explains approximately half the spread in projected change. A greater winter ice loss in CMIP6 than CMIP5 is explained by the higher climate sensitivities of some CMIP6 models. Plain Language Summary: Antarctic sea ice area is important for ecosystems, human activity, and for the dynamics of the atmosphere and ocean. However, major climate change assessments such as the Intergovernmental Panel on Climate Change Sixth Assessment Report have placed little confidence in projections of Antarctic sea ice area. This is because climate models struggle to simulate many aspects of sea ice area as observed by satellites. However, not all models should be treated equally. Models with relatively more sea ice area in the recent past project greater losses in the future, especially in summer. This suggests that models with historical sea ice area closest to what we have observed may be more reliable in their future simulations. We use this information in a simple statistical model to show that, firstly, the newest climate models largely show near‐total sea ice loss in summer by the end of the 21st century, which was not universally true for older climate models. Secondly, newer climate models lose more winter sea ice than their predecessors in the same time period, which is related to the known greater global warming response to given greenhouse gas concentrations in the newer models. Key Points: We compare Coupled Model Intercomparison Project (CMIP), phase 5 and the CMIP, phase 6 (CMIP6) projections of Antarctic sea ice loss, assessing drivers of uncertainty and the robustness of projectionsUnder strong forcing, CMIP6 models lose most Antarctic summer sea ice by 2100, so projections are constrained by historical climatologyIncreased winter sea ice loss in CMIP6 is related to increased equilibrium climate sensitivity [ABSTRACT FROM AUTHOR]

There are heated debates on the existence of the global warming slowdown during the early twenty-first century. Although efforts have been made to clarify or reconcile the controversy over this issue, it is not explicitly addressed, restricting the understanding of global temperature change particularly under the background of increasing greenhouse gas concentrations. Here, using extensive temperature datasets, we comprehensively reexamine the existence of the slowdown under all existing definitions during all decadal-scale periods spanning 1990–2017. Results show that the short-term linear trend–dependent definitions of slowdown make its identification severely suffer from the period selection bias, which largely explains the controversy over its existence. Also, the controversy is further aggravated by the significant impacts of the differences between various datasets on the recent temperature trend and the different baselines for measuring slowdown prescribed by various definitions. However, when the focus is shifted from specific periods to the probability of slowdown events, we find the probability is significantly higher in the 2000s than in the 1990s, regardless of which definition and dataset are adopted. This supports a slowdown during the early twenty-first century relative to the warming surge in the late twentieth century, despite higher greenhouse gas concentrations. Furthermore, we demonstrate that this decadal-scale slowdown is not incompatible with the centennial-scale anthropogenic warming trend, which has been accelerating since 1850 and never pauses or slows. This work partly reconciles the controversy over the existence of the warming slowdown and the discrepancy between the slowdown and anthropogenic warming. [ABSTRACT FROM AUTHOR]

A key goal of the 2015 Paris Climate Agreement is to keep global mean temperature change at 2°C and if possible under 1.5°C by the end of the century. To investigate the likelihood of achieving this target, we calculate the year of exceedance of a given global warming threshold (GWT) temperature across 32 CMIP6 models for Shared Socioeconomic Pathway (SSP) and radiative forcing combinations included in the Tier 1 ScenarioMIP simulations. Threshold exceedance year calculations reveal that a majority of CMIP6 models project warming beyond 2°C by the end of the century under every scenario or pathway apart from the lowest emission scenarios considered, SSP1–1.9 and SSP1–2.6, which is largely a function of the ScenarioMIP experiment design. The U.K. Earth System Model (UKESM1) ScenarioMIP projections are analyzed in detail to assess the regional and seasonal variations in climate at different warming levels. The warming signal emerging by midcentury is identified as significant and distinct from internal climate variability in all scenarios considered and includes warming summers in the Mediterranean, drying in the Amazon, and heavier Indian monsoons. Arctic sea ice depletion results in prominent amplification of warming and tropical warming patterns emerge that are distinct from interannual variability. Climate changes projected for a 2°C warmer world are in almost all cases exacerbated with further global warming (e.g., to a 4°C warmer world). Significance Statement: In this study, we look into changes occurring in climate due to global warming by analyzing data from the latest global climate models to see when the Earth will warm by 2° or 4°C, compared to preindustrial temperatures. We then use the UKESM1 climate model to identify regions on Earth where significant climate change is simulated in the future and discuss possible reasons for these changes. Simulations from this model also show that regions such as the Mediterranean, Amazon forests, and tropical countries are likely to see significant changes in climate impacting human lives. Future work to study the regional changes in greater detail will help us improve climate policies to protect society. [ABSTRACT FROM AUTHOR]

When the climate system is forced, for example, by the emission of greenhouse gases, it responds on multiple time scales. As temperatures rise, feedback processes might intensify or weaken. Such state dependencies cannot be fully captured with common linear regression techniques that relate feedback strengths linearly to changes in the global mean temperature. Hence, transient changes are difficult to track and it becomes easy to underestimate future warming this way. Here, we present a multivariate and spatial framework that facilitates the dissection of climate feedbacks over time scales. Using this framework, information on the composition of projected transient future climates and feedback strengths can be obtained. The new framework is illustrated using the Community Earth System Model version 2. Plain Language Summary: When the Earth warms, the internal processes of the climate system change. This can lead to additional warming, forming a feedback loop. For instance, as the ice melts due to increased temperatures, less solar radiation gets reflected back to outer space, causing temperatures to rise even more. To properly understand and assess (future) climatic changes, it is, therefore, necessary to quantify these so‐called climate feedbacks and track how they change over time. However, with current techniques, it is not easy to explicitly track these temporal changes, which hampers the interpretation of long‐term projections of the future climate state and easily leads to systematic underestimation of future (committed) warming. Here, we present a new feedback framework that can capture the temporal evolution of climate feedbacks. Consequently, a better insight into the development of a (projected) future climate is obtained, because not only global mean temperatures can be tracked, but also the temporal change in individual climate feedbacks, including their spatial distribution. Key Points: A multivariate climate feedback framework is introduced that takes into account the transient state dependency of climate feedbacksUsing the new framework, changes in feedback processes can be analyzed per time scale and temporal evolution can be trackedWithin the framework, it is possible to create transient and equilibrium projections of (the spatial patterns of) climate feedbacks [ABSTRACT FROM AUTHOR]