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This study presents an analysis of daily temperature and precipitation extremes with return periods ranging from 2 to 50 years in phase 6 of the Coupled Model Intercomparison Project (CMIP6) multimodel ensemble of simulations. Judged by similarity with reanalyses, the new-generation models simulate the present-day temperature and precipitation extremes reasonably well. In line with previous CMIP simulations, the new simulations continue to project a large-scale picture of more frequent and more intense hot temperature extremes and precipitation extremes and vanishing cold extremes under continued global warming. Changes in temperature extremes outpace changes in global annual mean surface air temperature (GSAT) over most landmasses, while changes in precipitation extremes follow changes in GSAT globally at roughly the Clausius–Clapeyron rate of ∼7% °C−1. Changes in temperature and precipitation extremes normalized with respect to GSAT do not depend strongly on the choice of forcing scenario or model climate sensitivity, and do not vary strongly over time, but with notable regional variations. Over the majority of land regions, the projected intensity increases and relative frequency increases tend to be larger for more extreme hot temperature and precipitation events than for weaker events. To obtain robust estimates of these changes at local scales, large initial-condition ensemble simulations are needed. Appropriate spatial pooling of data from neighboring grid cells within individual simulations can, to some extent, reduce the needed ensemble size.

Anthropogenic increases in atmospheric greenhouse gas concentrations are the main driver of current and future climate change. The integrated assessment community has quantified anthropogenic emissions for the shared socio-economic pathway (SSP) scenarios, each of which represents a different future socio-economic projection and political environment. Here, we provide the greenhouse gas concentrations for these SSP scenarios – using the reduced-complexity climate–carbon-cycle model MAGICC7.0. We extend historical, observationally based concentration data with SSP concentration projections from 2015 to 2500 for 43 greenhouse gases with monthly and latitudinal resolution. CO2 concentrations by 2100 range from 393 to 1135 ppm for the lowest (SSP1-1.9) and highest (SSP5-8.5) emission scenarios, respectively. We also provide the concentration extensions beyond 2100 based on assumptions regarding the trajectories of fossil fuels and land use change emissions, net negative emissions, and the fraction of non-CO2 emissions. By 2150, CO2 concentrations in the lowest emission scenario are approximately 350 ppm and approximately plateau at that level until 2500, whereas the highest fossil-fuel-driven scenario projects CO2 concentrations of 1737 ppm and reaches concentrations beyond 2000 ppm by 2250. We estimate that the share of CO2 in the total radiative forcing contribution of all considered 43 long-lived greenhouse gases increases from 66 % for the present day to roughly 68 % to 85 % by the time of maximum forcing in the 21st century. For this estimation, we updated simple radiative forcing parameterizations that reflect the Oslo Line-By-Line model results. In comparison to the representative concentration pathways (RCPs), the five main SSPs (SSP1-1.9, SSP1-2.6, SSP2-4.5, SSP3-7.0, and SSP5-8.5) are more evenly spaced and extend to lower 2100 radiative forcing and temperatures. Performing two pairs of six-member historical ensembles with CESM1.2.2, we estimate the effect on surface air temperatures of applying latitudinally and seasonally resolved GHG concentrations. We find that the ensemble differences in the March–April–May (MAM) season provide a regional warming in higher northern latitudes of up to 0.4 K over the historical period, latitudinally averaged of about 0.1 K, which we estimate to be comparable to the upper bound (∼5 % level) of natural variability. In comparison to the comparatively straight line of the last 2000 years, the greenhouse gas concentrations since the onset of the industrial period and this studies' projections over the next 100 to 500 years unequivocally depict a “hockey-stick” upwards shape. The SSP concentration time series derived in this study provide a harmonized set of input assumptions for long-term climate science analysis; they also provide an indication of the wide set of futures that societal developments and policy implementations can lead to – ranging from multiple degrees of future warming on the one side to approximately 1.5 ∘C warming on the other.

Global radiative feedbacks have been found to vary in global climate model (GCM) simulations. Atmospheric GCMs (AGCMs) driven with historical patterns of sea surface temperatures (SSTs) and sea ice concentrations produce radiative feedbacks that trend toward more negative values, implying low climate sensitivity, over recent decades. Freely evolving coupled GCMs driven by increasing CO₂ produce radiative feedbacks that trend toward more positive values, implying increasing climate sensitivity, in the future. While this time variation in feedbacks has been linked to evolving SST patterns, the role of particular regions has not been quantified. Here, a Green’s function is derived from a suite of simulations within an AGCM (NCAR’s CAM4), allowing an attribution of global feedback changes to surface warming in each region. The results highlight the radiative response to surface warming in ascent regions of the western tropical Pacific as the dominant control on global radiative feedback changes. Historical warming from the 1950s to 2000s preferentially occurred in the western Pacific, yielding a strong global outgoing radiative response at the top of the atmosphere (TOA) and thus a strongly negative global feedback. Long-term warming in coupled GCMs occurs preferentially in tropical descent regions and in high latitudes, where surface warming yields small global TOA radiation change but large global surface air temperature change, and thus a less-negative global feedback. These results illuminate the importance of determining mechanisms of warm pool warming for understanding how feedbacks have varied historically and will evolve in the future.

The Scenario Model Intercomparison Project (ScenarioMIP) defines and coordinates the main set of future climate projections, based on concentration-driven simulations, within the Coupled Model Intercomparison Project phase 6 (CMIP6). This paper presents a range of its outcomes by synthesizing results from the participating global coupled Earth system models. We limit our scope to the analysis of strictly geophysical outcomes: mainly global averages and spatial patterns of change for surface air temperature and precipitation. We also compare CMIP6 projections to CMIP5 results, especially for those scenarios that were designed to provide continuity across the CMIP phases, at the same time highlighting important differences in forcing composition, as well as in results. The range of future temperature and precipitation changes by the end of the century (2081–2100) encompassing the Tier 1 experiments based on the Shared Socioeconomic Pathway (SSP) scenarios (SSP1-2.6, SSP2-4.5, SSP3-7.0 and SSP5-8.5) and SSP1-1.9 spans a larger range of outcomes compared to CMIP5, due to higher warming (by close to 1.5 °C) reached at the upper end of the 5 %–95 % envelope of the highest scenario (SSP5-8.5). This is due to both the wider range of radiative forcing that the new scenarios cover and the higher climate sensitivities in some of the new models compared to their CMIP5 predecessors. Spatial patterns of change for temperature and precipitation averaged over models and scenarios have familiar features, and an analysis of their variations confirms model structural differences to be the dominant source of uncertainty. Models also differ with respect to the size and evolution of internal variability as measured by individual models' initial condition ensemble spreads, according to a set of initial condition ensemble simulations available under SSP3-7.0. These experiments suggest a tendency for internal variability to decrease along the course of the century in this scenario, a result that will benefit from further analysis over a larger set of models. Benefits of mitigation, all else being equal in terms of societal drivers, appear clearly when comparing scenarios developed under the same SSP but to which different degrees of mitigation have been applied. It is also found that a mild overshoot in temperature of a few decades around mid-century, as represented in SSP5-3.4OS, does not affect the end outcome of temperature and precipitation changes by 2100, which return to the same levels as those reached by the gradually increasing SSP4-3.4 (not erasing the possibility, however, that other aspects of the system may not be as easily reversible). Central estimates of the time at which the ensemble means of the different scenarios reach a given warming level might be biased by the inclusion of models that have shown faster warming in the historical period than the observed. Those estimates show all scenarios reaching 1.5 °C of warming compared to the 1850–1900 baseline in the second half of the current decade, with the time span between slow and fast warming covering between 20 and 27 years from present. The warming level of 2 °C of warming is reached as early as 2039 by the ensemble mean under SSP5-8.5 but as late as the mid-2060s under SSP1-2.6. The highest warming level considered (5 °C) is reached by the ensemble mean only under SSP5-8.5 and not until the mid-2090s.d-2090s.

Including an exceptionally warm Northern Hemisphere summer 1 , 2 , 2023 has been reported as the hottest year on record 3 , 4 – 5 . However, contextualizing recent anthropogenic warming against past natural variability is challenging because the sparse meteorological records from the nineteenth century tend to overestimate temperatures 6 . Here we combine observed and reconstructed June–August surface air temperatures to show that 2023 was the warmest Northern Hemisphere extra-tropical summer over the past 2,000 years exceeding the 95% confidence range of natural climate variability by more than ca. 0.4 °C. Comparison of the 2023 June–August warming against the coldest reconstructed summer in ce 536 shows a maximum range of pre-Anthropocene-to-2023 temperatures of 3.93 °C. Although 2023 is consistent with a greenhouse-gases-induced warming trend 7 that is amplified by an unfolding El Niño event 8 , this extreme emphasizes the urgency to implement international agreements for carbon emission reduction. Observations and a reconstruction of the June–August surface air temperatures show that 2023 was the warmest summer over the past 2,000 years exceeding the 95% confidence range of natural climate variability by more than 0.5 °Cs.

Here we evaluate the sea ice, surface air temperature, and sea level pressure from 34 of the models used in phase 6 of the Coupled Model Intercomparison Project (CMIP6) for their biases, trends, and variability, and compare them to the CMIP5 ensemble and ERA5 for the period 1979 to 2004. The principal purpose of this assessment is to provide an overview of the ability of the CMIP6 ensemble to represent the Arctic climate, and to see how this has changed since the last phase of CMIP. Overall, we find a distinct improvement in the representation of the sea ice volume and extent, the latter mostly linked to improvements in the seasonal cycle in the Barents Sea. However, numerous model biases have persisted into CMIP6 including too-cold conditions in the winter (4-K cold bias) and a negative trend in the day-to-day variability over ice in winter. We find that under the low-emission scenario, SSP126, the Arctic climate is projected to stabilize by 2060 with an annual mean sea ice extent of around 2.5 million km² and an annual mean temperature 4.7 K warmer than the early-twentieth-century average, compared to 1.7 K of warming globally.

The Modern-Era Retrospective Analysis for Research and Applications, version 2 (MERRA-2), features several major advances from the original MERRA reanalysis, including the use, outside of high latitudes, of observations-based precipitation data products to correct the precipitation falling on the land surface in the MERRA-2 system. The method for merging the observed precipitation into MERRA-2 has been refined from that of the (land-only) MERRA-Land reanalysis. This paper describes the method and evaluates the MERRA-2 land surface precipitation. Compared to monthly GPCPv2.2 observations, the corrected MERRA-2 precipitation (M2CORR) is better than the precipitation generated by the atmospheric models within the cycling MERRA-2 and MERRA systems. M2CORR is also better than MERRA-Land precipitation over Africa because in MERRA-2 a merged satellite–gauge precipitation product is used instead of the gauge-only data used for MERRA-Land. Compared to 3-hourly TRMM observations, the M2CORR diurnal cycle has better amplitude but less realistic phasing than MERRA-2 model-generated precipitation. Because correcting the precipitation within the coupled atmosphere–land modeling system allows the MERRA-2 near-surface air temperature and humidity to respond to the improved precipitation forcing, MERRA-2 provides more self-consistent surface meteorological data than were available from MERRA-Land, which is important for applications such as land-only modeling studies. Where precipitation observations of sufficient quality are available for use in the reanalysis, the corrections facilitate the seamless spinup of the land surface initial conditions across the MERRA-2 production streams. At high latitudes, however, the lack of reliable precipitation observations results in undesirable land spinup effects that impact mostly the first published year of each MERRA-2 stream (1980, 1992, 2001, and 2011).

The main advancements of the Beijing Climate Center (BCC) climate system model from phase 5 of the Coupled Model Intercomparison Project (CMIP5) to phase 6 (CMIP6) are presented, in terms of physical parameterizations and model performance. BCC-CSM1.1 and BCC-CSM1.1m are the two models involved in CMIP5, whereas BCC-CSM2-MR, BCC-CSM2-HR, and BCC-ESM1.0 are the three models configured for CMIP6. Historical simulations from 1851 to 2014 from BCC-CSM2-MR (CMIP6) and from 1851 to 2005 from BCC-CSM1.1m (CMIP5) are used for models assessment. The evaluation matrices include the following: (a) the energy budget at top-of-atmosphere; (b) surface air temperature, precipitation, and atmospheric circulation for the global and East Asia regions; (c) the sea surface temperature (SST) in the tropical Pacific; (d) sea-ice extent and thickness and Atlantic Meridional Overturning Circulation (AMOC); and (e) climate variations at different timescales, such as the global warming trend in the 20th century, the stratospheric quasi-biennial oscillation (QBO), the Madden–Julian Oscillation (MJO), and the diurnal cycle of precipitation. Compared with BCC-CSM1.1m, BCC-CSM2-MR shows significant improvements in many aspects including the tropospheric air temperature and circulation at global and regional scales in East Asia and climate variability at different timescales, such as the QBO, the MJO, the diurnal cycle of precipitation, interannual variations of SST in the equatorial Pacific, and the long-term trend of surface air temperature.

Parties to the Paris Agreement agreed to holding global average temperature increases “well below 2 °C above pre-industrial levels and pursuing efforts to limit the temperature increase to 1.5 °C above pre-industrial levels”. Monitoring the contributions of human-induced climate forcings to warming so far is key to understanding progress towards these goals. Here we use climate model simulations from the Detection and Attribution Model Intercomparison Project, as well as regularized optimal fingerprinting, to show that anthropogenic forcings caused 0.9 to 1.3 °C of warming in global mean near-surface air temperature in 2010–2019 relative to 1850–1900, compared with an observed warming of 1.1 °C. Greenhouse gases and aerosols contributed changes of 1.2 to 1.9 °C and −0.7 to −0.1 °C, respectively, and natural forcings contributed negligibly. These results demonstrate the substantial human influence on climate so far and the urgency of action needed to meet the Paris Agreement goals.Quantifying the temperature impacts of anthropogenic emissions helps monitor proximity to the Paris Agreement goals. Human activities warmed global mean temperature during the past decade by 0.9 to 1.3 °C above 1850–1900 values, with 1.2 to 1.9 °C from greenhouse gases and −0.7 to −0.1 °C from aerosols.

We present the first Antarctic-wide analysis of extreme near-surface air temperatures based on data collected up to the end of 2019 as part of the synoptic meteorological observing programs. We consider temperatures at 17 stations on the Antarctic continent and nearby sub-Antarctic islands. We examine the frequency distributions of temperatures and the highest and lowest individual temperatures observed. The variability and trends in the number of extreme temperatures were examined via the mean daily temperatures computed from the 0000, 0600, 1200, and 1800 UTC observations, with the thresholds for extreme warm and cold days taken as the 5th and 95th percentiles. The five stations examined from the Antarctic Peninsula region all experienced a statistically significant increase (p < 0.01) in the number of extreme high temperatures in the late-twentieth-century part of their records, although the number of extremes decreased in subsequent years. For the period after 1979 we investigate the synoptic background to the extreme events using ECMWF interim reanalysis (ERA-Interim) fields. The majority of record high temperatures were recorded after the passage of air masses over high orography, with the air being warmed by the foehn effect. At some stations in coastal East Antarctica the highest temperatures were recorded after air with a high potential temperature descended from the Antarctic plateau, resulting in an air mass 5°–7°C warmer than the maritime air. Record low temperatures at the Antarctic Peninsula stations were observed during winters with positive sea ice anomalies over the Bellingshausen and Weddell Seas.