Global Mean Temperature Change Research Articles

Reassessing the Climate Change Narrative

AbstractWe note that the atmosphere has distinct tropical and extratropical regimes. The tropical regime is significantly dependent on the greenhouse effect and is characterized by temperatures that are largely horizontally homogenized. The extratropical regime is dominated by large scale unstable convective eddies that transport heat between the tropics and the poles (leaving the poles warmer than they otherwise would be) and serve to determine the temperature difference between the tropics and the poles. Changes in tropical temperature and in the tropics-to-pole temperature difference both contribute to changes in global mean temperature. It turns out that changes in global mean temperature associated with major climate change (i.e., the last glacial maximum and the warm period of the Eocene about 50 million years ago) were associated primarily with changes in the tropics-to-pole temperature differences. By contrast, changes in global mean temperature over the past 150 years or so are almost entirely associated with changes in tropical temperature. Thus, there is no intrinsic amplification associated with a change in the tropics-to-pole temperature difference. However, model simulations of climate behave differently from both observations and from each other. In particular, they all show more significant contributions for the tropics-to-pole temperature difference – sometimes much more significant. They also show excessive tropical warming.

Atmosphere and ocean energy transport in extreme warming scenarios

Extreme scenarios of global warming out to 2300 from the SSP5-8.5 extension scenario are analyzed in three state-of-the-art climate models, including two models with climate sensitivity greater than 4.5°C. The result is some of the largest warming amounts ever seen in simulations run over the historical record and into the future. The simulations exhibit between 9.3 and 17.5°C global mean temperature change between pre-Industrial and the end of the 23rd century. The extremely large changes in global temperature allow exploration of fundamental questions in climate dynamics, such as the determination of moisture and energy transports, and their relation to global atmosphere-ocean circulation. Three models performed simulations of SSP5-8.5 to 2300: MRI-ESM2-0, IPSL-CM6A-LR, and CanESM5. We analyze these simulations to improve understanding of climate dynamics, rather than as plausible futures. In the model with the most warming, CanESM5, the moisture content of the planet more than doubles, and the hydrologic cycle increases in intensity. In CanESM5 and IPSL-CM6A-LR nearly all sea ice is eliminated in both summer and winter in both hemispheres. In all three models, the Hadley circulation weakens, the tropopause height rises, and storm tracks shift poleward, to varying degrees. We analyze the moist static energy transports in the simulations using a diffusive framework. The dry static energy flux decreases to compensate for the increased moisture transport; however the compensation is imperfect. The total atmospheric transport increases but not as quickly as expected with a constant diffusivity. The decrease in eddy intensity plays an important role in determining the energy transports, as do the pattern of cloud feedbacks and the strength of ocean circulations.

A new conceptual model ofglobaloceanheatuptake.

We formulate a new conceptual model, named "MT2", to describe global ocean heat uptake, as simulated by atmosphere-ocean general circulation models (AOGCMs) forced by increasing atmospheric CO2, as a function of global-mean surface temperature change T and the strength of the Atlantic meridional overturning circulation (AMOC, M). MT2 has two routes whereby heat reaches the deep ocean. On the basis of circumstantial evidence, we hypothetically identify these routes as low- and high-latitude. In low latitudes, which dominate the global-mean energy balance, heat uptake is temperature-driven and described by the two-layer model, with global-mean T as the temperature change of the upper layer. In high latitudes, a proportion p (about 14%) of the forcing is taken up along isopycnals, mostly in the Southern Ocean, nearly like a passive tracer, and unrelated to T. Because the proportion p depends linearly on the AMOC strength in the unperturbed climate, we hypothesise that high-latitude heat uptake and the AMOC are both affected by some characteristic of the unperturbed global ocean state, possibly related to stratification. MT2 can explain several relationships among AOGCM projections, some found in this work, others previously reported: Ocean heat uptake efficiency correlates strongly with the AMOC. Global ocean heat uptake is not correlated with the AMOC. Transient climate response (TCR) is anticorrelated with the AMOC. T projected for the late twenty-first century under high-forcing scenarios correlates more strongly with the effective climate sensitivity than with the TCR.

What Does Global Land Climate Look Like at 2°C Warming?

AbstractConstraining an increase in global mean temperature below 2°C compared to pre‐industrial levels is critical to limiting dangerous and cascading impacts of anthropogenic climate change. Understanding future climatic changes and their spatial heterogeneity at 2°C warming is thus important for policy makers to prepare actionable adaptation and mitigation plans by identifying where and to what extent lives and livelihoods will be impacted. This study uses the recently released NASA Earth eXchange Global Daily Downscaled Projections (NEX‐GDDP) CMIP6 data to provide a broad overview of projected changes in six key climate variables and two climate impact indicators at a time when warming exceeds 2°C. Analysis of global mean temperature changes indicates the 2040s as the decade when most CMIP6 models reach 2°C warming with respect to a pre‐industrial period (1850–1900). During the 2040s, we find that global mean temperature, precipitation, relative humidity, downwelling shortwave and longwave radiation, and wind speed over land under the high emission scenario are projected to change by +2.8°C, +22.4 mm/year, −0.73%, −2.23 , +15.9 W/m2, and −0.04 m/s, respectively. Many of the future changes are expected to exacerbate climate impacts including heat stress and fire danger. Our analysis shows geographic patterns of policy‐relevant climatic changes, as parts of the globe will experience significant climate impacts even if the goal to keep warming below 2°C goal is achieved. Our results highlight the urgent need for further studies focused on identifying key hotspots and advancing region‐specific actionable adaptation and mitigation plans.

When Will the Unprecedented 2022 Summer Heat Waves in Yangtze River Basin Become Normal in a Warming Climate?

AbstractYangtze River basin (YZB) experienced record‐breaking heat in the summer of 2022. Here, we focused on daytime‐nighttime compound heat waves, and used the magnitude index that considers both duration and intensity to investigate the risk of the 2022 extreme heat. The magnitude of heatwaves in 2022 was much larger than the historical average level, which was estimated as a 1‐in‐64‐year event over 1979–2014 climate. Without mitigation efforts (SSP585), the record‐breaking heat would emerge as normal during 2050s, and would affect ∼70% of land and projected population in the basin before global mean temperature change reaches 3°C. Such an emergence could be progressively delayed and impacts could be reduced under lower warming levels. The affected area would be 60% lesser at 2°C warming, and the emergence could be avoided by limiting warming to 1.5°C. Our results call for urgent mitigation efforts for reducing the risk of compound heat extremes.

Converting carbon vulnerable lands to wood plantations for use as building materials: Overall environmental performance and time-dependent assessment of carbon dioxide removals

Bioeconomy addresses the triple balancing challenge posed by the Paris Agreement: inducing additional GHG mitigation alongside biophysical carbon dioxide removals, while keeping fossil carbon in the ground. The use of woody plants as construction materials could simultaneously address this challenge: CO2 is absorbed through photosynthesis, while wood-based products provide mitigation by replacing either petrochemical materials such as plastic boards or energy-intensive materials like bricks. This study combines, at the scale of France, static and dynamic life cycle assessment with soil carbon simulations to investigate the long-term environmental performance of using, as input for the building sector, black locust (Robinia pseudoacacia L.) planted on “carbon vulnerable lands”. These are areas specifically selected for their low soil organic carbon (SOC) levels and low potential to interfere with food security. After the consecutive cultivation of three rotations, black locust was shown to stock an additional 92000 kg ha−1 of carbon in soils as SOC. The mitigation effect from the plastic board replacement is the major contributor to the assessed environmental impacts, including climate change, leading the black locust system to generally perform better than the reference system where the carbon vulnerable areas are left as they are with their initial vegetation. Considering that cultivation starts in 2022, the dynamic evaluation of the global mean temperature change (GMTC) shows that the black locust system results in net negative emissions in the near- and mid-term, but with a GMTC overshot in the second half of the century. Even if a considerable carbon stock is created through time (e.g., 81% and 39% of the carbon captured by photosynthesis, in 2050 and 2100 respectively), the GHG emissions stemming from manufacturing and end-of-life processes were shown to offset the benefit of carbon capture.

Formation of the North Atlantic Warming Hole by reducing anthropogenic sulphate aerosols

The North Atlantic Warming Hole (NAWH) has been observed and predicted due to the increase in carbon dioxide (CO2) concentration. If sulphate aerosols, which have a cooling effect on the atmosphere, are reduced by air pollution control, the NAWH may form as it would if CO2 concentrations increased. In this study, sensitivity experiments using a coupled atmosphere–ocean-aerosol model were conducted by varying the amount of sulphur dioxide (SO2) emissions, a precursor of sulphate which is the primary anthropogenic aerosol in the atmosphere, to analyse the changes in the ocean temperature, salinity, and density. The results showed that although the spatial patterns of the NAWH due to the changes in SO2 emissions was similar to that due to the changes in the CO2 concentrations, the magnitude of the shifts in the ocean parameters due to the changes in SO2 emissions is larger even when changes in global mean temperature are comparable. This can be due to the spatial concentration of sulphate aerosols in the mid-latitudes of the Northern Hemisphere, resulting larger changes in the heat transport from the south on the Gulf Stream and the North Atlantic Current along with changes in freshwater inflow from the Arctic through the Labrador Sea.

Through an Ice Sheet, Darkly

Through an Ice Sheet, Darkly

Spatial patterns of climate change across the Paleocene–Eocene Thermal Maximum

The Paleocene-Eocene Thermal Maximum (PETM; 56 Ma) is one of our best geological analogs for understanding climate dynamics in a "greenhouse" world. However, proxy data representing the event are only available from select marine and terrestrial sedimentary sequences that are unevenly distributed across Earth's surface, limiting our view of the spatial patterns of climate change. Here, we use paleoclimate data assimilation (DA) to combine climate model and proxy information and create a spatially complete reconstruction of the PETM and the climate state that precedes it ("PETM-DA"). Our data-constrained results support strong polar amplification, which in the absence of an extensive cryosphere, is related to temperature feedbacks and loss of seasonal snow on land. The response of the hydrological cycle to PETM warming consists of a narrowing of the Intertropical Convergence Zone, off-equatorial drying, and an intensification of seasonal monsoons and winter storm tracks. Many of these features are also seen in simulations of future climate change under increasing anthropogenic emissions. Since the PETM-DA yields a spatially complete estimate of surface air temperature, it yields a rigorous estimate of global mean temperature change (5.6 ∘C; 5.4 ∘C to 5.9 ∘C, 95% CI) that can be used to calculate equilibrium climate sensitivity (ECS). We find that PETM ECS was 6.5 ∘C (5.7 ∘C to 7.4 ∘C, 95% CI), which is much higher than the present-day range. This supports the view that climate sensitivity increases substantially when greenhouse gas concentrations are high.

Past rapid warmings as a constraint on greenhouse-gas climate feedbacks

There are large uncertainties in the estimation of greenhouse-gas climate feedback. Recent observations do not provide strong constraints because they are short and complicated by human interventions, while model-based estimates differ considerably. Rapid climate changes during the last glacial period (Dansgaard-Oeschger events), observed near-globally, were comparable in both rate and magnitude to current and projected 21st century climate warming and therefore provide a relevant constraint on feedback strength. Here we use these events to quantify the centennial-scale feedback strength of CO2, CH4 and N2O by relating global mean temperature changes, simulated by an appropriately forced low-resolution climate model, to the radiative forcing of these greenhouse gases derived from their concentration changes in ice-core records. We derive feedback estimates (expressed as dimensionless gain) of 0.14 ± 0.04 for CO2, 0.10 ± 0.02 for CH4, and 0.09 ± 0.03 for N2O. This indicates that much lower or higher estimates of gains, particularly some previously published values for CO2, are unrealistic.

Acute climate risks in the financial system: examining the utility of climate model projections

Efforts to assess risks to the financial system associated with climate change are growing. These commonly combine the use of integrated assessment models to obtain possible changes in global mean temperature (GMT) and then use coupled climate models to map those changes onto finer spatial scales to estimate changes in other variables. Other methods use data mined from ‘ensembles of opportunity’ such as the Coupled Model Intercomparison Project (CMIP). Several challenges with current approaches have been identified. Here, we focus on demonstrating the issues inherent in applying global ‘top-down’ climate scenarios to explore financial risks at geographical scales of relevance to financial institutions (e.g. city-scale). We use data mined from the CMIP to determine the degree to which estimates of GMT can be used to estimate changes in the annual extremes of temperature and rainfall, two compound events (heatwaves and drought, and extreme rain and strong winds), and whether the emission scenario provides insights into the change in the 20, 50 and 100 year return values for temperature and rainfall. We show that GMT provides little insight on how acute risks likely material to the financial sector (‘material extremes’) will change at a city-scale. We conclude that ‘top-down’ approaches are likely to be flawed when applied at a granular scale, and that there are risks in employing the approaches used by, for example, the Network of Central Banks and Supervisors for Greening the Financial System. Most fundamental, uncertainty associated with projections of future climate extremes must be propagated through to estimating risk. We strongly encourage a review of existing top-down approaches before they develop into de facto standards and note that existing approaches that use a ‘bottom-up’ strategy (e.g. catastrophe modelling and storylines) are more likely to enable a robust assessment of material risk.

Decarbonizing the Global Economy—Investigating the Role of Carbon Emission Inertia Using the Integrated Assessment Model MIND

In 2015, the 21st Conference of the Parties reaffirmed the target of keeping the global mean temperature rise below 2 °C or 1.5 °C by 2100 while finding no consensus on how to decarbonize the global economy. In this regard, the speed of decarbonization reflects the (in)flexibility of transforming the energy sector due to engineering, political, or societal constraints. Using economy–energy–climate-integrated assessment models (IAMs), the maximum absolute rate of change in carbon emission allowed from each time step to the next, so-called carbon emission inertia (CEI), governs the magnitude of emission change, affecting investment decisions and economic welfare. Employing the model of investment and endogenous technological development (MIND), we conduct a cost-effectiveness analysis and examine anthropogenic global carbon emission scenarios in line with decarbonizing the global economy while measuring the global mean temperature. We examine the role of CEI as a crucial assumption, where the CEI can vary in four scenarios from 3.7% to 12.6% p.a. We provide what-if studies on global carbon emissions, global mean temperature change, and investments in renewable energy production and show that decarbonizing the global economy might still be possible before 2100 only if the CEI is high enough. In addition, we show that climate policy scenarios with early decarbonization and without negative emissions may still comply with the 2 °C target. However, our results indicate that the 1.5 °C target is not likely to be reached without negative emission technologies. Hence, the window of opportunity is beginning to close. This work can also assist to better interpret existing publications on various climate targets when altering CEI could have played a significant role.

Inter-model variability of the CMIP5 future projection of Baiu, Meiyu, and Changma precipitation

Many studies have suggested that mean precipitation associated with the East Asian Summer Monsoon (EASM) will be increased by the ongoing global warming, but its quantitative projection by climate models has large variability, with some models suggesting even decreases. We investigate the inter-model variability of projected centennial changes of the EASM separately for Baiu over Japan, Meiyu over eastern China, and Changma over Korea by using monthly-mean model outputs provided by the Coupled Model Intercomparison Project Phase 5 (CMIP5) project. Results with the Representative Concentration Pathway 4.5 and 8.5 scenarios (RCP4.5 and RCP8.5) are consolidated by normalizing with the global-mean near-surface air temperature changes. For all the three EASM land regions, inter-model differences in the mean precipitation changes are positively correlated with the southerly moisture flux changes to the south of the regions. The correlation is highest in June among the June-to-August months, whose reason may be because precipitation in early summer relies on large-scale southerly moisture transport. These changes are localized and nearly independent among the three regions where Baiu, Meiyu and Changma occur. The low-level southerly change to the south of Japan, which affects the Baiu precipitation change, is positively correlated with upper-tropospheric meridional wind to its north; it further exhibits a stationary Rossby-wave feature associated with the Silk-Road teleconnection. This study suggests that future changes in the EASM mean precipitation depend on circulation changes and more-or-less localized.

Climate Change Prediction Using ARIMA Model

Abstract: It is a challenging task to forecast weather data accurately. The temperature change has important implications for business and economic activity. Effective management of global climate change impacts will depend upon accurate and costeffective forecasts. This paper univariate statistic techniques to model the properties of a world mean temperature dataset to develop a parsimonious forecasting model for managerial decision-making over the short-term horizon and the ARIMAbased prognostication tool has been developed by implementing the ARIMA algorithm in python. Although the model is estimated on global temperature data, the methodology could even be applied to temperature data at more localized levels. The statistical techniques include seasonal and non-seasonal unit root testing with and without structural breaks as well as ARIMA and SARIMA modelling. This paper helps us to predict the air temperature, which is the main problem of global warming. Prediction of the likely impact of climate change on monthly mean maximum and minimum temperature in Tamilnadu. Time-series techniques to develop a parsimonious model of global mean temperature change that can be used to forecast over the short-term horizon (5- 10) years. Keywords: Global warming, Forecasting, temperature

Robust increase in population exposure to heat stress with increasing global warming

Extreme heat, particularly if combined with humidity, poses a severe risk to human health. To estimate future global risk of extreme heat with humidity on health, we calculate indicators of heat stress that have been commonly used: the Heat Index, the Wet-Bulb Globe Temperature and the Wet-Bulb Temperature, from the latest Climate Model Intercomparison Project (CMIP6) projections. We analyse how and where different levels of heat stress hazards will change, from severe to deadly, and how results are sensitive to the choice of the index used. We evaluate this risk at country-level and use population and GDPPPP growth scenario to estimate the vulnerability of each nation. Consistent with previous studies, we find that South and East Asia, and the Middle-East, are highly exposed to heat stress hazards, and that this exposure increases by 20%–60% with global mean temperature change from 1.5 to 3 ∘C. However, we also find substantial increases in heat health risk for some vulnerable countries with less adaptive capacity, such as West Africa, and Central and South America. For these regions, about 20 to more than 50% of the population could be exposed to severe heat stress each year on average, independent of the index used. For global warming of 3∘, European countries and the USA will also be exposed several times per year to conditions with daily mean heat stress level equal to the maximum heat stress of the 2003 heat wave.

Future water levels of the Great Lakes under 1.5 °C to 3 °C warmer climates

With the many different interests that are connected to the water levels of the Laurentian Great Lakes, the future of these water levels are of great concern to many people, businesses, and institutions. Projected future lake levels were calculated using data from the North American component of the Coordinated Regional Downscaling Experiment. The final lake level results are presented in relation to a 1.5 °C, 2.0 °C, 2.5 °C, and 3.0 °C change in global mean temperature. The results show that the range of possible values grows as the climate changes, with more extreme values for the lake levels becoming possible with greater changes in the global mean temperature. This increase in the range on both the high and low end may be a more important consideration than any general increase in the average water level for those living around the lakes Because the most severe impacts on the interests around the lake are usually associated with these extreme high or low levels. A greater understanding that the extremes in water levels observed in the past may be exceeded under a changing climate will help in the planning of future developments and activities within the Great Lakes basin with a forward looking coastal risk assessment and help communites build resilience to future extremes.

Simultaneous carbon storage in arable land and anthropogenic products (CSAAP): Demonstrating an integrated concept towards well below 2°C

Additional carbon dioxide removals from the atmosphere are indispensable for controlling global warming. This study introduces two concepts: (i) ‘biopump’, plants capable of significantly transferring carbon into soils, and (ii) Carbon Storage in Arable land and Anthropogenic Products (CSAAP), the cultivation of biopumps on low-impact target areas and their conversion into long-lived anthropogenic products. It develops and demonstrates a 4-step framework applicable to any region, that allows illustrating the long-term climate effect of CSAAP strategies applied to a selected territory, tracking carbon flows, from biopump cultivation to biomaterials manufacturing and their end-of-life. Based on a list of twenty-seven biopumps uncovered from a literature review, this study first proposes a method for the regional prioritization of biopumps, considering among others their ability to increase soil organic carbon (SOC) and adaptation potential. It then demonstrates how to select target areas on a territory, and shows how to integrate the output of SOC simulations in dynamic carbon balances, that can be translated in terms of effects on global mean temperature change. This is illustrated for products encompassing a variety of lifetimes, for the case of Miscanthus grown on French target areas. A potential ranging from 11,187- 24,007 km2 target areas was identified; translating in additional SOC stocks of 0.23 to 0.49 Mt year−1, which represents 0.19%- 0.41% of the annual French carbon budget, or 13% assuming an indefinite storage in anthropogenic products. We concluded that CSAAP strategies could induce negative emissions by 2100, with efficiency strongly depending upon carbon residence time in the technosphere.

Climate variability and food waste treatment: Analysis for bioenergy sustainability

Although reducing food waste is essential for the necessary reduction in greenhouse gas (GHG) emissions for climate mitigation, not all food waste is avoidable. Currently, food waste is mainly disposed of in landfills in low-income countries, whereas some industrialized countries in Asia recycle a majority of their food waste as animal feed or compost. The present study therefore investigates the large-scale implementation of technological alternatives for the valorization of food waste into biogas and bioethanol. First, a projected scenario of global food waste in 2050 is provided using a data-driven model that takes into account spatial differences in the types of food waste at the country level. This scenario indicates that food-waste-related GHG emissions alone nearly reach the 2 °C target emissions allowance. Next, the food-waste-to-biogas and food-waste-to-bioethanol pathways, including the upgrading of food waste-derived acetic acid to bioethanol, are examined via large-scale modeling and analysis to estimate their potential for bioenergy production and their resulting GHG footprint. Finally, a national-scale optimization of climate mitigation benefits under alternative conversion pathways (bioethanol versus biogas) is performed. This optimal scenario indicates that the production of bioethanol using one half of all the food waste generated by the four largest waste-producing countries (China, USA, India, and Brazil) can generate 31.9–34.0 × 1018 J (or 31.9–34.0 EJ (EJ)) of renewable energy and decrease GHG emissions by 22.8–26.8 Gt CO2 eq. Furthermore, the catalytic conversion of food waste to bioethanol can potentially maximize climate mitigation to 4.0–4.8 trillion USD while preventing a 0.06–0.07 °C increase in global mean temperature change in the cumulative period of 2011–2050.

Emergent constraints on future precipitation changes.

Future projections of global mean precipitation change (ΔP) based on Earth-system models have larger uncertainties than projections of global mean temperature changes (ΔT)1. Although many observational constraints on ΔT have been proposed, constraints on ΔP have not been well studied2-5 and are often complicated by the large influence of aerosols on precipitation4. Here we show that the upper bound (95th percentile) of ΔP (2051-2100 minus 1851-1900, percentage of the 1980-2014 mean) is lowered from 6.2 per cent to 5.2-5.7 per cent (minimum-maximum range of sensitivity analyses) under a medium greenhouse gas concentration scenario. Our results come from the Coupled Model Intercomparison Project phase 5 and phase 6 ensembles6-8, in which ΔP for 2051-2100 is well correlated with the global mean temperature trends during recent decades after 1980 when global anthropogenic aerosol emissions were nearly constant. ΔP is also significantly correlated with the recent past trends in precipitation when we exclude the tropical land areas with few rain-gauge observations. On the basis of these significant correlations and observed trends, the variance of ΔP is reduced by 8-30 per cent. The observationally constrained ranges of ΔP should provide further reliable information for impact assessments.

The Physical Climate at Global Warming Thresholds as Seen in the U.K. Earth System Model

AbstractA 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).