Global Mean Surface Air Temperature Research Articles

Limited reversal of regional climate signals in overshoot scenarios

Without stringent reductions in emission of greenhouse gases in the coming years, an exceedance of the 1.5 °C temperature limit is increasingly likely. This has given rise to so-called temperature overshoot scenarios, in which the global mean surface air temperature exceeds a certain limit (i.e. 1.5 °C above pre-industrial levels) before bringing temperatures back below that limit. Despite their prominence in the climate mitigation literature, the implications of an overshoot for local climate impacts is still understudied. Here we present a comprehensive analysis of implications of an overshoot for regional temperature and precipitation changes as well as climate extremes indices. Based on a multi-model comparison from the Coupled Model Intercomparison Project we find that temperature changes are largely reversible in many regions, but also report significant land–ocean and latitudinal differences after an overshoot. For precipitation, the emerging picture is less clear. In many regions the drying or wetting trend is continued throughout the overshoot irrespective of a change in the global mean temperature trend with resulting consequences for extreme precipitation. Taken together, our results indicate that even under a reversal of global mean temperature increase, regional climate changes may only be partially reversed in the decades after peak warming. We thus provide further evidence that overshooting of a warming level implies considerable risks on the regional level.

The primary factors influencing the cooling effect of carbon dioxide removal

Carbon dioxide removal (CDR) is a crucial approach in achieving the goals set by the Paris Climate Agreement. However, understanding the cooling effect (CE) of CDR and its primary controlling factors has been challenging due to the limited number of models conducting the CDR simulation. To address this, we employed an energy balance model (EBM), which effectively captures or reproduces the global mean surface air temperature change to CO2 forcing. The outputs of the EBM revealed that even with the same CDR rate, the CE diverse significantly (σ=0.7 K\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$\\sigma =0.7{K}$$\\end{document}). Two main factors significantly affect the CE of CDR. The primary factor is the coefficient of the vertical heat exchange in the ocean [contributes to σCE=0.7 K\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$\\sigma \\left({CE}\\right)=0.7{K}$$\\end{document}], which governs the heat uptake and release of the deep ocean. It directly impacts the heat absorbed by the Earth’s surface and influences the magnitudes of the transient climate responses. The second factor is the estimation of effective radiative forcing (ERF) resulting from changes in CO2 concentration [contributes to σCE=0.6 K\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$\\sigma \\left({CE}\\right)=0.6{K}$$\\end{document}]. This estimation is directly associated with the amplitude of the CO2 radiative forcing and the responses of relevant energy processes, thereby influencing the temperature change. Regarding the timing of the CE emergence, the influences of processes within the EBM are quite small. Therefore, an accurate estimation of the vertical heat exchange in the ocean and ERF may favor designation of a better pathway to achieve the temperature goals outlined in the Paris Climate Agreement.

Selenomethionine alleviates environmental heat stress induced hepatic lipid accumulation and glycogen infiltration of broilers via maintaining mitochondrial and endoplasmic reticulum homeostasis

With the increasing of global mean surface air temperature, heat stress (HS) induced by extreme high temperature has become a key factor restricting the poultry industry. Liver is the main metabolic organ of broilers, HS induces liver damage and metabolic disorders, which impairs the health of broilers and affects food safety. As an essential trace element for animals, selenium (Se) involves in the formation of antioxidant system, and its biological functions are generally mediated by selenoproteins. However, the mechanism of Se against HS induced liver damage and metabolic disorders in broilers is inadequate. Therefore, we developed the chronic heat stress (CHS) broiler model and investigated the potential protection mechanism of organic Se (selenomethionine, SeMet) on CHS induced liver damage and metabolic disorders. In present study, CHS caused liver oxidative damage, and induced hepatic lipid accumulation and glycogen infiltration of broilers, which are accompanied by mitochondrial dysfunction, abnormal mitochondrial tricarboxylic acid (TCA) cycle and endoplasmic reticulum (ER) stress. Dietary SeMet supplementation increased the hepatic Se concentration and exhibited protective effects via promoting the expression of selenotranscriptome and several key selenoproteins (GPX4, TXNRD2, SELENOK, SELENOM, SELENOS, SELENOT, GPX1, DIO1, SELENOH, SELENOU and SELENOW). These key selenoproteins synergistically improved the antioxidant capacity, and mitigated the mitochondrial dysfunction, abnormal mitochondrial TCA cycle and ER stress, thus recovered the hepatic triglyceride and glycogen concentration. What's more, SeMet supplementation suppressed lipid and glycogen biosynthesis and promoted lipid and glycogen breakdown in liver of broilers exposed to CHS though regulating the AMPK signals. Overall, our present study reveals a potential mechanism that Se alleviates environment HS induced liver damage and glycogen and lipid metabolism disorders in broilers, which provides a preventive and/or treatment measure for environment HS-dependent hepatic metabolic disorders in poultry industry.

Effect of climate change on the behaviour of thermo-active diaphragm walls

Energy geo-structures are becoming more common as a renewable energy solution which utilises shallow geothermal energy to provide heating and cooling to buildings and civil infrastructure projects. There has been an upward trend in the use of thermo-active geo-structures in the United Kingdom, from 150 in 2005 to over 5000 in 2012 [2]. Studies so far have shown that diaphragm walls subjected to combined thermo-mechanical loading show overall increases in lateral displacements, bending moments, shear forces, axial forces, and settlements on the retained side with thermal cycles [6, 7, 8].
 This study uses a variation of a validated numerical model [4] to predict the behaviour of thermo-active diaphragm walls in the longer-term including accounting for the influence of climate change. This numerical model also assesses the impact of different modelling assumptions on the model output by comparing a simplified model with a more complex model where atmospheric temperatures affecting ground surface temperatures are included. Research from the IPCC shows increases in ambient temperatures and in maximum extreme temperatures as a result of climate change. Two models are compared in the IPCC report [5], Representative Concentration Pathway (RCP) 2.6 where governments across the world work together to meet the recommendations in the report to reduce overall warming, and RCP8.5 where the current trends of heating continue without any governmental interventions. According to climate model RCP2.6, global mean surface air temperatures will increase by around 1.5°C and extreme daily temperatures (i.e. days where temperatures exceed expected temperatures for the time of year) will increase by around 2°C over the 50-year period chosen for this study, whilst using RCP8.5 global mean surface air temperature increases by approximately 3°C and extreme daily temperatures increase by approximately 5°C.
 This study uses the same model geometry as a model validated through centrifuge testing [4] which is a 5m deep cantilever diaphragm wall, like those that would be used in deep excavations for open-topped tunnels in large civil infrastructure projects. The numerical model was developed using the semi-coupled thermo-hydro-mechanical (THM) thermal module available with PLAXIS 2D and uses the HS-Small soil model [3] to allow for variation in shear modulus at small strains (i.e. those associated with retaining walls) to be captured more accurately. Thermal loads were applied by applying heat flows through a plate element with the same mechanical properties of the model diaphragm wall used in centrifuge testing. This model attempts to capture the influence of atmospheric temperatures by applying thermal boundary conditions to the ground surface as well as to the thermo-active diaphragm wall. Studies have demonstrated that a more complex model capturing atmospheric temperatures increases the impact of thermal loading [4], whilst also capturing a more realistic temperature profile throughout the entire depth of the soil body both adjacent to the wall and in the free field condition. In this study, atmospheric temperatures were captured in RCP2.6 by cycling between 30°C and -5°C over the course of the cycle to represent a typical ‘hottest’ and ‘coldest’ day of the year in cycle 1, increasing to 32°C and -5°C in line with the temperature increases described in the IPCC report [5]. Ambient mean temperatures between heating and cooling cycles increased from 20°C to 21.5°C over the 50-year period. In the same model, the temperature within the diaphragm
 wall cycled between 35°C and 10°C in cycle 1, representing the typical operation of a ground source heat pump (GSHP) in heating and cooling. These temperature inputs increased to 37°C and 10°C over the 50-year period. The RCP8.5 atmospheric temperatures cycled between 30°C and -5°C to represent summer and winter in cycle 1 and increase to 35°C and -5°C over the 50-year period. Thermal flows in the diaphragm wall cycled between 35°C and 10°C in cycle 1 and increased to 40°C and 10°C over the 50-year period. The results from this study show increases in lateral displacement, maximum bending moments, positive and negative shear forces and axial forces (compressive (-) and tensile (+)). These results are shown in Figure 1.
 Significantly, the RCP2.6 model shows that these increases begin to stabilise over the 50-year period, with the increases in the final cycles becoming negligible. With the RCP8.5 model these increases are increasing linearly at the end of the modelling period which can potentially have significant implications not only in terms of serviceability of the structure, but potentially on ultimate limit state as linear increases suggest that design limits will eventually be reached. The findings from this study generally agree with other similar studies, such as a study that analysed the geotechnical performance of energy piles with additional environmental loading as a result of climate change which found that additional compressive and tensile stresses are generated during heating and cooling phases, respectively [1].

Detection and Attribution of Climate Change Using a Neural Network

AbstractA new detection and attribution method is presented and applied to the global mean surface air temperature (GSAT) from 1900 to 2014. The method aims at attributing the climate changes to the variations of greenhouse gases, anthropogenic aerosols, and natural forcings. A convolutional neural network (CNN) is trained using the simulated GSAT from historical and single‐forcing simulations of 12 climate models. Then, we perform a backward optimization with the CNN to estimate the attributable GSAT changes. Such a method does not assume additivity in the effects of the forcings. The uncertainty in the attributable GSAT is estimated by sampling different starting points from single‐forcing simulations and repeating the backward optimization. To evaluate this new method, the attributable GSAT changes are also calculated using the regularized optimal fingerprinting (ROF) method. Using synthetic non‐additive data, we first find that the neural network‐based method estimates attributable changes better than ROF. When using GSAT data from climate model, the attributable anomalies are similar for both methods, which might reflect that the influence of forcing is mainly additive for the GSAT. However, we found that the uncertainties given both methods are different. The new method presented here can be adapted and extended in future work, to investigate the non‐additive changes found at the local scale or on other physical variables.

Anthropogenic fingerprints in daily precipitation revealed by deep learning

According to twenty-first century climate-model projections, greenhouse warming will intensify rainfall variability and extremes across the globe1–4. However, verifying this prediction using observations has remained a substantial challenge owing to large natural rainfall fluctuations at regional scales3,4. Here we show that deep learning successfully detects the emerging climate-change signals in daily precipitation fields during the observed record. We trained a convolutional neural network (CNN)5 with daily precipitation fields and annual global mean surface air temperature data obtained from an ensemble of present-day and future climate-model simulations6. After applying the algorithm to the observational record, we found that the daily precipitation data represented an excellent predictor for the observed planetary warming, as they showed a clear deviation from natural variability since the mid-2010s. Furthermore, we analysed the deep-learning model with an explainable framework and observed that the precipitation variability of the weather timescale (period less than 10 days) over the tropical eastern Pacific and mid-latitude storm-track regions was most sensitive to anthropogenic warming. Our results highlight that, although the long-term shifts in annual mean precipitation remain indiscernible from the natural background variability, the impact of global warming on daily hydrological fluctuations has already emerged.

Tonga volcanic eruption triggered anomalous Arctic warming in early 2022

On 15 January 2022, the submarine volcano on Hunga Tonga-Hunga Ha'apai Island erupted and injected a small amount of SO2 but an unprecedent amount of water vapor into the stratosphere. The impact of Tonga eruption on climate was dynamically simulated using a fully coupled climate prediction system FIO-CPS v2.0 by considering both SO2 and water vapor injections into the stratosphere, which is the first attempt to incorporate the volcanic water vapor injection in a climate prediction system to evaluate its effect on surface climate response. Model results indicated that the surface air temperature (SAT) over the Arctic region was significantly warmer in early 2022 as a response to the co-injection of SO2 and water vapor from Tonga eruption, although its effect on global mean SAT was found to be insignificant. In February 2022, the average warming anomaly in the Arctic area reached up to 1.1 °C, with zonal mean warming of 2.0 °C near the North Pole. The Tonga eruptions induced anomalous heat transport which primarily contributed to the Arctic warming in February. However, it had a cooling effect on the Arctic area in January and March. In addition to heat transport, the eruption also triggered anomalous northward transport of water vapor. This led to an increase in the water vapor content, which further enhanced the downward longwave radiation and cloud-radiative feedback over the Arctic region, ultimately contributing to the Arctic SAT warming in early 2022. In the simulation only SO2 injection was considered without water vapor injection, the pattern of SAT response showed warming over the Eurasian continent and cooling in the north over Arctic Ocean, which is opposite to that in the simulation with co-injection of SO2 and water vapor. This indicated that volcanic water vapor injection of Tonga eruption played a dominant role in the Arctic warming. Consequently, submarine volcano should receive more attention due to its potential climate effects, especially when it involves significant water vapor releases.

Urbanization Heat Flux Modeling Confirms It Is a Likely Cause of Significant Global Warming: Urbanization Mitigation Requirements

Recent ground-based measurements find the magnitude of the urbanization effect on the global average annual mean surface air temperature corresponds to an urbanization contribution of 12.7%. It is important to provide modeling to help understand these results as there are conflicting concerns. This study models the global warming contribution that urbanization heat fluxes (UHF) can make due to anthropogenic heat release (AHR), and solar heating of impermeable surface areas (ISAs), with additional secondary effects. Results help explain and support ground-based observations. Climate models typically omit anthropogenic heat release (AHR) as warming estimates are below 1%. In agreement, the baseline assessment in this paper has similar findings. However, in this study, the methods of climate amplification estimates (MCAE) with data-aided physics-based amplification models are used. When the MCAE are applied at the global and microclimate levels that consider greenhouse gases (GHGs), feedback, and other secondary effects; the results show that AHR fluxes can amplify, increasing to have an estimated global warming (GW) influence of 6.5% from 1950 to 2022 yielding a 0.9% decade−1 increase. This increasing rate due to energy consumption is found as anticipated to be reasonably correlated to the increasing population growth rate over this time. Furthermore, using the MCAEs, this paper studies heat fluxes assessment due to solar heating of unshaded impermeable surfaces including likely secondary amplification effects. Impermeable surface areas (ISAs) such as asphalt roads, roofs, and building sides have been reported with high land surface contact temperatures (LSCTs) relative to non-ISAs and significantly found to contribute to urbanization warming. Results indicate that high-temperature unshaded impermeable surfaces (including building sides) are estimated to average around 10–11 °C above the earth’s ambient temperature of 14.5 °C (showing albedo ISA estimates between 0.133 and 0.115 respectively); the ISA heat fluxes with secondary effects are estimated to have about a GW influence of 6.5%. This is broken down with average contributions of 4.0% from urban ISAs and 2.5% from rural ISA heat fluxes. Asphalt road ISA heat fluxes are estimated to have about a 1.1% global warming influence. Then the total UHF effect from ISAs and AHR with secondary effects is assessed in modeling to yield a combined average GW influence of 13% helping to confirm ground-based measurement results. Several key adjustment values were used for shading, cloud coverage, and rural-to-urban ISA ratios. Microclimate GHGs and related water vapor feedback (WVF) were assessed to increase urban warming by about 50%. As well an assessment of water vapor and radiation increases from UHF is provided. This study also shows the need to incorporate urbanization heat fluxes with secondary effects into climate models and indicates the necessity for Paris Agreement urban heat flux mitigation goals. Results also found that given average climate conditions, it is possible to mitigate much of the UHI effect with an albedo increase of 0.1 that is anticipated to lower the average impermeable surface temperatures by about 9 °C. Studies show this can be accomplished with cost-effective cool roads and roofs. Although roads are only estimated to occupy 14% of ISAs, changing roads from asphalt to concrete-type surfaces would improve reflectivity by about a factor of 5 and is estimated to mitigate about 5.5% of global warming. Unfortunately, the current overuse of black asphalt on pavements and roofs is highly dangerous to our environment causing UHI increases in heatwaves, excessive temperatures, and global warming issues and should be banned. Asphalt usage also reduces opportunities for solar geoengineering of urbanization.

An upper bound for extreme temperatures over midlatitude land

Heatwaves damage societies worldwide and are intensifying with global warming. Several mechanistic drivers of heatwaves, such as atmospheric blocking and soil moisture-atmosphere feedback, are well-known for their ability to raise surface air temperature. However, what limits the maximum surface air temperature in heatwaves remains unclear; this became evident during recent Northern Hemisphere heatwaves which achieved temperatures far beyond the upper tail of the observed statistical distribution. Here, we present evidence for the hypothesis that convective instability limits annual maximum surface air temperatures (TXx) over midlatitude land. We provide a theory for the corresponding upper bound of midlatitude temperatures, which accurately describes the observed relationship between temperatures at the surface and in the midtroposphere. We show that known heatwave drivers shift the position of the atmospheric state in the phase space described by the theory, changing its proximity to the upper bound. This theory suggests that the upper bound for midlatitude TXx should increase 1.9 times as fast as 500-hPa temperatures at the time and location of TXx occurrences. Using empirical 500-hPa warming, we project that the upper bound of TXx over Northern Hemisphere midlatitude land (40°N to 65°N) will increase about twice as fast as global mean surface air temperature, and TXx will increase faster than this bound over regions that dry on the hottest days.

Can global warming bring more dust?

In the late twentieth century, global mean surface air temperature especially on land is continuously warming. Our analyses show that the global mean of dust increased since 1980, using the Modern-Era Retrospective Analysis version 2 for Research and Applications (MERRA-2) reanalysis data. This variation of global dust is mainly contributed by the dust increase outside of dust core areas (i.e. high dust mass concentration region). The causes to result in global dust variations are explored. In dust core areas, surface wind is the primary driving factor for surface dust, both of which show no remarkable trends of increase or decrease since 1980. In areas outside of the core areas, especially in arid and semi-arid areas in North and Middle Asia, surface air temperature warming is the primary impact factor causing the dust increase. An increase in surface air temperature is accompanied by enhancement of atmospheric instability which can trigger more upward motion and bring more dust. All 9 Earth System Models (ESMs) for the Aerosol Chemistry Model Intercomparison Project (AerChemMIP) reproduce the reasonable spatial distribution and seasonal cycle of dust in the present day. But only a few models such as BCC-ESM1 and GFDL-ESM4 simulate the increasing trend of dust similar to MERRA-2. While the primary impact of wind in dust core areas, and surface temperature outside of the core areas, especially in middle to high latitudes in Eurasian continent, are presented in most ESMs.

Assessing Responses and Impacts of Solar climate intervention on the Earth system with stratospheric aerosol injection (ARISE-SAI): protocol and initial results from the first simulations

Abstract. Solar climate intervention using stratospheric aerosol injection is a proposed method of reducing global mean temperatures to reduce the worst consequences of climate change. A detailed assessment of responses and impacts of such an intervention is needed with multiple global models to support societal decisions regarding the use of these approaches to help address climate change. We present a new modeling protocol aimed at simulating a plausible deployment of stratospheric aerosol injection and reproducibility of simulations using other Earth system models: Assessing Responses and Impacts of Solar climate intervention on the Earth system with stratospheric aerosol injection (ARISE-SAI). The protocol and simulations are aimed at enabling community assessment of responses of the Earth system to solar climate intervention. ARISE-SAI simulations are designed to be more policy-relevant than existing large ensembles or multi-model simulation sets. We describe in detail the first set of ARISE-SAI simulations, ARISE-SAI-1.5, which utilize a moderate emissions scenario, introduce stratospheric aerosol injection at ∼21.5 km in the year 2035, and keep global mean surface air temperature near 1.5 ∘C above the pre-industrial value utilizing a feedback or control algorithm. We present the detailed setup, aerosol injection strategy, and preliminary climate analysis from a 10-member ensemble of these simulations carried out with the Community Earth System Model version 2 with the Whole Atmosphere Community Climate Model version 6 as its atmospheric component.

Supraglacial lake expansion, intensified lake drainage frequency, and first observation of coupled lake drainage, during 1985–2020 at Ryder Glacier, Northern Greenland

Along the Greenland Ice Sheet margin, supraglacial lakes store and redistribute ice sheet surface run off, and comprise an important potential hydrological link between the ice surface and the base, with ramifications for subglacial drainage systems and ice flow. As a consequence of increasing global mean surface air temperatures, these lakes have been predicted to expand further inland and to affect larger areas of the ice sheet. However, as contemporary dynamics of such supraglacial lake expansion are not well studied, any assessment of their future implications remains afflicted with uncertainty. Here, recent changes in supraglacial lake distribution and expansion, and in their drainage behavior and frequency, are presented for Ryder Glacier, Northern Greenland, as concluded from a remote sensing based analysis. The 35-year time span covered in the analysis allows for the detection of trends in lake processes and ice velocity, which otherwise were found to exhibit large inter-annual variability. It also reveals the first occurrence of a coupled lake drainage event in 2002. By linking supraglacial lake expansion, drainage modes, and drainage frequency to the efficiency of the subglacial drainage system and ice flow on seasonal and decadal timescales, a contribution is made to better understand the complexity of coupled glacio-hydrological processes, and to help reduce uncertainties in predictions of future mass loss from the Greenland Ice Sheet.

A new global surface temperature reconstruction for the Last Glacial Maximum

Abstract. We present a new reconstruction of surface air temperature and sea surface temperature for the Last Glacial Maximum. The method blends model fields and sparse proxy-based point estimates through a data assimilation approach. Our reconstruction updates that of Annan and Hargreaves (2013), using the full range of general circulation model (GCM) simulations which contributed to three generations of the PMIP database, three major compilations of gridded sea surface temperature (SST) and surface air temperature (SAT) estimates from proxy data, and an improved methodology based on an ensemble Kalman filter. Our reconstruction has a global annual mean surface air temperature anomaly of -4.5±0.9 ∘C relative to the pre-industrial climate. This is slightly colder than the previous estimate of Annan and Hargreaves (2013), with an upwards revision on the uncertainty due to different methodological assumptions. It is, however, substantially less cold than the recent reconstruction of Tierney et al. (2020). We show that the main reason for this discrepancy is in the choice of prior. We recommend the use of the multi-model ensemble of opportunity as potentially offering a credible prior, but it is important that the range of models included in the PMIP ensembles represent the main sources of uncertainty as realistically and comprehensively as practicable if they are to be used in this way.

Future Climate Change Under SSP Emission Scenarios With GISS‐E2.1

AbstractThis paper presents the response to anthropogenic forcing in the GISS‐E2.1 climate models for the 21st century Shared Socioeconomic Pathways emission scenarios within the Coupled Model Intercomparison Project Phase 6 (CMIP6). The experiments were performed using an updated and improved version of the NASA Goddard Institute for Space Studies (GISS) coupled general circulation model that includes two different versions for atmospheric composition: A non‐interactive version (NINT) with prescribed composition and a tuned aerosol indirect effect and the One‐Moment Aerosol model (OMA) version with fully interactive aerosols which includes a parameterized first indirect aerosol effect on clouds. The effective climate sensitivities are 3.0°C and 2.9°C for the NINT and OMA models, respectively. Each atmospheric version is coupled to two different ocean general circulation models: The GISS ocean model (E2.1‐G) and HYCOM (E2.1‐H). We describe the global mean responses for all future scenarios and spatial patterns of change for surface air temperature and precipitation for four of the marker scenarios: SSP1‐2.6, SSP2‐4.5, SSP4‐6.0, and SSP5‐8.5. By 2100, global mean warming ranges from 1.5°C to 5.2°C relative to 1,850–1,880 mean temperature. Two high‐mitigation scenarios SSP1‐1.9 and SSP1‐2.6 limit the surface warming to below 2°C by the end of the 21st century, except for the NINT E2.1‐H model that simulates 2.2°C of surface warming. For the high emission scenario SSP5‐8.5, the range is 4.6–5.2°C at 2100. Due to about 15% larger effective climate sensitivity and stronger transient climate response in both NINT and OMA CMIP6 models compared to CMIP5 versions, there is a stronger warming by 2100 in the SSP emission scenarios than in the comparable Representative Concentration Pathway (RCP) scenarios in CMIP5. Changes in sea ice area are highly correlated to global mean surface air temperature anomalies and show steep declines in both hemispheres, with the largest sea ice area decreases occurring during September in the Northern Hemisphere in both E2.1‐G (−1.21 × 106 km2/°C) and E2.1‐H models (−0.94 × 106 km2/°C). Both coupled models project decreases in the Atlantic overturning stream function by 2100. The largest decrease of 56%–65% in the 21st century overturning stream function is produced in the warmest scenario SSP5‐8.5 in the E2.1‐G model, comparable to the reduction in the corresponding CMIP5 GISS‐E2 RCP8.5 simulation. Both low‐end scenarios SSP1‐1.9 and SSP1‐2.6 also simulate substantial reductions of the overturning (9%–37%) with slow recovery of about 10% by the end of the 21st century (relative to the maximum decrease at the middle of the 21st century).

Transient climate simulations of the Holocene (version 1) – experimental design and boundary conditions

Abstract. The Holocene, which started approximately 11.5 ka, is the latest interglacial period with several rapid climate changes with timescales, from decades to centuries, superimposed on the millennium-scale mean climate trend. Climate models provide useful tools to investigate the underlying dynamic mechanisms for the climate change during this well-studied time period. Thanks to the improvements in the climate model and computational power, transient simulation of the Holocene offers an opportunity to investigate the climate evolution in response to time-varying external forcings and feedbacks. Here, we present the design of a new set of transient experiments for the whole Holocene from 11.5 ka to the preindustrial period (1850; HT-11.5 ka) to investigate both the combined and separated effects of the main external forcing of orbital insolation, atmospheric greenhouse gas (GHG) concentrations, and ice sheets on the climate evolution over the Holocene. The HT-11.5 ka simulations are performed with a relatively high-resolution version of the comprehensive Earth system model CESM1.2.1 without acceleration, both fully and singly forced by time-varying boundary conditions of orbital configurations, atmospheric GHGs, and ice sheets. Preliminary simulation results show a slight decrease in the global annual mean surface air temperature from 11.5 to 7.5 ka due to both changes in orbital insolation and GHG concentrations, with an abrupt cooling at approximately 7.5 ka, which is followed by a continuous warming until the preindustrial period, mainly due to increased GHG concentrations. Both at global and zonal mean scales, the simulated annual and seasonal temperature changes at 6 ka lie within the range of the 14 PMIP4 model results and are overall stronger than their arithmetic mean results for the Middle Holocene simulations. Further analyses on the HT-11.5 ka transient simulation results will be covered by follow-up studies.

Unevenly distributed CO2 and its impacts on surface energy balance

Atmospheric carbon dioxide (CO2) has affected global surface and atmospheric energy balance since the Industrial Revolution. The spatial distribution of CO2 concentrations derived from satellite observation are introduced into the coupled Beijing Normal University Earth System Model (BNU-ESM) to study the responses of temperature and surface energy balance to non-uniform CO2 distribution under the Representative Concentration Pathway 8.5 scenario to 2100. Global annual mean atmospheric CO2 concentrations are set to equal those specified in the standard uniform CO2 simulations with differences in spatial pattern and seasonal cycles amounting to tens of ppm. Relative to the uniform CO2 simulation, global annual mean surface air temperature increases by 0.44 ± 0.03 °C over 2071–2100 when forced with non-uniformly distributed CO2, in the Arctic by 1.63 ± 0.28 °C and by 0.67 ± 0.08 °C in northern midlatitudes. The non-uniform CO2 simulation increases global surface energy by 0.68 ± 0.06 W m−2, principally due to a 0.73 ± 0.08 W m−2 increase in net downward surface longwave flux. Surface energy balance increases by 0.33 ± 0.11 W m−2 (7.4%) averaged over oceans indicting a significant increase in ocean heat uptake. Surface energy budget averaged over the Arctic summer increases by 0.91 ± 0.68 W m−2 in the non-uniform CO2 simulation, which would have impact on sea ice extent and land ice melt rates with associated feedbacks. The increased surface energy fluxes and temperatures imply reduced time and emission space for greenhouse gases before running into scientific and politically flagged temperature limits.

Correlation Between Sea-Level Rise and Aspects of Future Tropical Cyclone Activity in CMIP6 Models.

Future coastal flood hazard at many locations will be impacted by both tropical cyclone (TC) change and relative sea‐level rise (SLR). Despite sea level and TC activity being influenced by common thermodynamic and dynamic climate variables, their future changes are generally considered independently. Here, we investigate correlations between SLR and TC change derived from simulations of 26 Coupled Model Intercomparison Project Phase 6 models. We first explore correlations between SLR and TC activity by inference from two large‐scale factors known to modulate TC activity: potential intensity (PI) and vertical wind shear. Under the high emissions SSP5‐8.5, SLR is strongly correlated with PI change (positively) and vertical wind shear change (negatively) over much of the western North Atlantic and North West Pacific, with global mean surface air temperature (GSAT) modulating the co‐variability. To explore the impact of the joint changes on flood hazard, we conduct climatological–hydrodynamic modeling at five sites along the US East and Gulf Coasts. Positive correlations between SLR and TC change alter flood hazard projections, particularly at Wilmington, Charleston and New Orleans. For example, if positive correlations between SLR and TC changes are ignored in estimating flood hazard at Wilmington, the average projected change to the historical 100 years storm tide event is under‐estimated by 12%. Our results suggest that flood hazard assessments that neglect the joint influence of these factors and that do not reflect the full distribution of GSAT change may not accurately represent future flood hazard.

Sulfur emissions from consumption by developed and developing countries produce comparable climate impacts

Regional consumption activities supported by domestic production and international trade have led to substantial aerosol-related emissions worldwide. Here we quantify sulfur dioxide emissions associated with consumption by developed and developing countries and assess the resulting climate impacts using an Earth system model. We find that although the consumption-associated emissions of developed countries are 40% less than those of developing countries, they lead to similar impacts on global mean surface air temperature and precipitation. This is because the effective radiative forcing induced per emission is greater for developed countries, which we attribute to the emissions being located at higher northern latitudes and being more evenly distributed zonally. Emissions from developing countries have a greater impact on temperature and precipitation over the tropical monsoon regions of China and India. Our results demonstrate the importance of trade and emission region in determining how consumption translates into global climate impact. Sulfur dioxide emissions due to consumption by developed and developing countries differ in magnitude but produce comparable climate impacts due to the regional distribution of emissions, according to simulations using an Earth system model.

Simulation of the mid-Pliocene Warm Period using HadGEM3: experimental design and results from model–model and model–data comparison

Abstract. Here we present the experimental design and results from a new mid-Pliocene simulation using the latest version of the UK's physical climate model, HadGEM3-GC31-LL, conducted under the auspices of CMIP6/PMIP4/PlioMIP2. Although two other palaeoclimate simulations have been recently run using this model, they both focused on more recent periods within the Quaternary, and therefore this is the first time this version of the UK model has been run this far back in time. The mid-Pliocene Warm Period, ∼3 Ma, is of particular interest because it represents a time period when the Earth was in equilibrium with CO2 concentrations roughly equivalent to those of today, providing a possible analogue for current and future climate change. The implementation of the Pliocene boundary conditions is firstly described in detail, based on the PRISM4 dataset, including CO2, ozone, orography, ice mask, lakes, vegetation fractions and vegetation functional types. These were incrementally added into the model, to change from a pre-industrial setup to a Pliocene setup. The results of the simulation are then presented, which are firstly compared with the model's pre-industrial simulation, secondly with previous versions of the same model and with available proxy data, and thirdly with all other models included in PlioMIP2. Firstly, the comparison with the pre-industrial simulation suggests that the Pliocene simulation is consistent with current understanding and existing work, showing warmer and wetter conditions, and with the greatest warming occurring over high-latitude and polar regions. The global mean surface air temperature anomaly at the end of the Pliocene simulation is 5.1 ∘C, which is the second highest of all models included in PlioMIP2 and is consistent with the fact that HadGEM3-GC31-LL has one of the highest Effective Climate Sensitivities of all CMIP6 models. Secondly, the comparison with previous generation models and with proxy data suggests a clear increase in global sea surface temperatures as the model has undergone development. Up to a certain level of warming, this results in a better agreement with available proxy data, and the “sweet spot” appears to be the previous CMIP5 generation of the model, HadGEM2-AO. The most recent simulation presented here, however, appears to show poorer agreement with the proxy data compared with HadGEM2 and may be overly sensitive to the Pliocene boundary conditions, resulting in a climate that is too warm. Thirdly, the comparison with other models from PlioMIP2 further supports this conclusion, with HadGEM3-GC31-LL being one of the warmest and wettest models in all of PlioMIP2, and if all the models are ordered according to agreement with proxy data, HadGEM3-GC31-LL ranks approximately halfway among them. A caveat to these results is the relatively short run length of the simulation, meaning the model is not in full equilibrium. Given the computational cost of the model it was not possible to run it for a longer period; a Gregory plot analysis indicates that had it been allowed to come to full equilibrium, the final global mean surface temperature could have been approximately 1.5 ∘C higher.

Presentation and Evaluation of the IPSL‐CM6A‐LR Ensemble of Extended Historical Simulations

AbstractThe Institut Pierre‐Simon Laplace Climate Modeling Center has produced an ensemble of extended historical simulations using the IPSL‐CM6A‐LR climate model. This ensemble (referred to as IPSL‐EHS) is composed of 32 members over the 1850–2059 period that share the same external forcings but differ in their initial conditions. In this study, we assess the simulated decadal to multidecadal climate variability in the IPSL‐EHS. In particular, we examine the global temperature evolution and recent warming trends, and their consistency with ocean heat content and sea ice cover. The model exhibits a large low‐frequency internal climate variability. In particular, a quasi‐bicentennial mode of internal climate variability is present in the model and is associated with the Atlantic Meridional Overturning Circulation. Such variability modulates the global mean surface air temperature changes over the historical period by about 0.1K. This modulation is found to be linked to the phase present in the initial condition state of each member. This variability appears to decrease during the 1850–2018 period in response to external forcings. The analysis of the ocean heat content reveals furthermore an overestimation of the ocean stratification, which likely leads to an overestimation of the recent warming rate on average.