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Plants influence extreme heat events by regulating land-atmosphere water and energy exchanges. The contribution of plants to changes in future heat extremes will depend on the responses of vegetation growth and physiology to the direct and indirect effects of elevated CO2. Here we use a suite of earth system models to disentangle the radiative versus vegetation effects of elevated CO2 on heat wave characteristics. Vegetation responses to a quadrupling of CO2 increase summer heat wave occurrence by 20 days or more-30-50% of the radiative response alone-across tropical and mid-to-high latitude forests. These increases are caused by CO2 physiological forcing, which diminishes transpiration and its associated cooling effect, and reduces clouds and precipitation. In contrast to recent suggestions, our results indicate CO2-driven vegetation changes enhance future heat wave frequency and intensity in most vegetated regions despite transpiration-driven soil moisture savings and increases in aboveground biomass from CO2 fertilization.

Atmospheric rivers (ARs) are an important driver of surface mass balance over today's Greenland and Antarctic ice sheets. Using paleoclimate simulations with the Community Earth System Model, we find ARs also had a key influence on the extensive ice sheets of the Last Glacial Maximum (LGM). ARs provide up to 53% of total precipitation along the margins of the eastern Laurentide ice sheet and up to 22%–27% of precipitation along the margins of the Patagonian, western Cordilleran, and western Fennoscandian ice sheets. Despite overall cold conditions at the LGM, surface temperatures during AR events are often above freezing, resulting in more rain than snow along ice sheet margins and conditions that promote surface melt. The results suggest ARs may have had an important role in ice sheet growth and melt during previous glacial periods and may have accelerated ice sheet retreat following the LGM. Plain Language Summary During the Last Glacial Maximum (∼21,000 years ago), ice sheets covered much of northern North America, Fennoscandia, and the Patagonian Andes. Using climate model simulations, we find that much of the precipitation that fell on the margins of these ice sheets came from transient, narrow corridors of atmospheric moisture known as atmospheric rivers. The atmospheric rivers were important in driving ice sheet accumulation during cold seasons, and ice sheet melt during warm seasons. The results suggest that atmospheric rivers may have had a role in driving the movement of ice sheets during Earth's past. Key Points Atmospheric rivers were less frequent and supplied less precipitation globally during the Last Glacial Maximum (LGM) Over land, atmospheric river precipitation peaked along the margins of the extratropical ice sheets Atmospheric rivers were important contributors to the surface mass balance of LGM ice sheets

Atmospheric stagnation can have serious health implications due to increased pollution exposure. This study investigates how global warming will alter atmospheric circulation and the resulting changes in the frequency and persistence of stagnation events. The authors find an overall increase in the size of the population exposed to these events and highlight the need to evaluate air pollution management. Poor air quality causes an estimated 2.6–4.4 million premature deaths per year 1 , 2 , 3 . Hazardous conditions form when meteorological components allow the accumulation of pollutants in the near-surface atmosphere 4 , 5 , 6 , 7 , 8 . Global-warming-driven changes to atmospheric circulation and the hydrological cycle 9 , 10 , 11 , 12 , 13 are expected to alter the meteorological components that control pollutant build-up and dispersal 5 , 6 , 7 , 8 , 14 , but the magnitude, direction, geographic footprint and public health impact of this alteration remain unclear 7 , 8 . We used an air stagnation index and an ensemble of bias-corrected climate model simulations to quantify the response of stagnation occurrence and persistence to global warming. Our analysis projects increases in stagnation occurrence that cover 55% of the current global population, with areas of increase affecting ten times more people than areas of decrease. By the late twenty-first century, robust increases of up to 40 days per year are projected throughout the majority of the tropics and subtropics, as well as within isolated mid-latitude regions. Potential impacts over India, Mexico and the western US are particularly acute owing to the intersection of large populations and increases in the persistence of stagnation events, including those of extreme duration. These results indicate that anthropogenic climate change is likely to alter the level of pollutant management required to meet future air quality targets.

A set of atmosphere-only timeslice experiments are described, designed to examine the processes that cause regional climate change and inter-model uncertainty in coupled climate model responses to C O 2 forcing. The timeslice experiments are able to reproduce the pattern of regional climate change in the coupled models, and are applied here to two cases where inter-model uncertainty in future projections is large: the tropical hydrological cycle, and European winter circulation. In tropical forest regions, the plant physiological effect is the largest cause of hydrological cycle change in the two models that represent this process. This suggests that the CMIP5 ensemble mean may be underestimating the magnitude of water cycle change in these regions, due to the inclusion of models without the plant effect. SST pattern change is the dominant cause of precipitation and circulation change over the tropical oceans, and also appears to contribute to inter-model uncertainty in precipitation change over tropical land regions. Over Europe and the North Atlantic, uniform SST increases drive a poleward shift of the storm-track. However this does not consistently translate into an overall polewards storm-track shift, due to large circulation responses to SST pattern change, which varies across the models. Coupled model SST biases influence regional rainfall projections in regions such as the Maritime Continent, and so projections in these regions should be treated with caution.

The primary objective of CFMIP is to inform future assessments of cloud feedbacks through improved understanding of cloud–climate feedback mechanisms and better evaluation of cloud processes and cloud feedbacks in climate models. However, the CFMIP approach is also increasingly being used to understand other aspects of climate change, and so a second objective has now been introduced, to improve understanding of circulation, regional-scale precipitation, and non-linear changes. CFMIP is supporting ongoing model inter-comparison activities by coordinating a hierarchy of targeted experiments for CMIP6, along with a set of cloud-related output diagnostics. CFMIP contributes primarily to addressing the CMIP6 questions “How does the Earth system respond to forcing?” and “What are the origins and consequences of systematic model biases?” and supports the activities of the WCRP Grand Challenge on Clouds, Circulation and Climate Sensitivity.A compact set of Tier 1 experiments is proposed for CMIP6 to address this question: (1) what are the physical mechanisms underlying the range of cloud feedbacks and cloud adjustments predicted by climate models, and which models have the most credible cloud feedbacks? Additional Tier 2 experiments are proposed to address the following questions. (2) Are cloud feedbacks consistent for climate cooling and warming, and if not, why? (3) How do cloud-radiative effects impact the structure, the strength and the variability of the general atmospheric circulation in present and future climates? (4) How do responses in the climate system due to changes in solar forcing differ from changes due to CO2, and is the response sensitive to the sign of the forcing? (5) To what extent is regional climate change per CO2 doubling state-dependent (non-linear), and why? (6) Are climate feedbacks during the 20th century different to those acting on long-term climate change and climate sensitivity? (7) How do regional climate responses (e.g. in precipitation) and their uncertainties in coupled models arise from the combination of different aspects of CO2 forcing and sea surface warming?CFMIP also proposes a number of additional model outputs in the CMIP DECK, CMIP6 Historical and CMIP6 CFMIP experiments, including COSP simulator outputs and process diagnostics to address the following questions.How well do clouds and other relevant variables simulated by models agree with observations?What physical processes and mechanisms are important for a credible simulation of clouds, cloud feedbacks and cloud adjustments in climate models?Which models have the most credible representations of processes relevant to the simulation of clouds?How do clouds and their changes interact with other elements of the climate system?

Spatially compounding droughts over multiple regions pose amplifying pressures on the global food system, the reinsurance industry, and the global economy. Using observations and climate model simulations, we analyze the influence of various natural Ocean variability modes on the likelihood, extent, and severity of compound droughts across ten regions that have similar precipitation seasonality and cover important breadbaskets and vulnerable populations. Although a majority of compound droughts are associated with El Niños, a positive Indian Ocean Dipole, and cold phases of the Atlantic Niño and Tropical North Atlantic (TNA) can substantially modulate their characteristics. Cold TNA conditions have the largest amplifying effect on El Niño-related compound droughts. While the probability of compound droughts is ~3 times higher during El Niño conditions relative to neutral conditions, it is ~7 times higher when cold TNA and El Niño conditions co-occur. The probability of widespread and severe compound droughts is also amplified by a factor of ~3 and ~2.5 during these co-occurring modes relative to El Niño conditions alone. Our analysis demonstrates that co-occurrences of these modes result in widespread precipitation deficits across the tropics by inducing anomalous subsidence, and reducing lower-level moisture convergence over the study regions. Our results emphasize the need for considering interactions within the larger climate system in characterizing compound drought risks rather than focusing on teleconnections from individual modes. Understanding the physical drivers and characteristics of compound droughts has important implications for predicting their occurrence and characterizing their impacts on interconnected societal systems.

The spatial extent of an extreme heat event influences the total exposure of people and natural systems to heat-related stresses, straining water, energy, and emergency management resources. Here, we quantify how the contiguous area of individual heat wave events varies across heat wave types, time of year, and in response to observed climate change within the Berkeley Earth Surface Temperature Dataset. Across the mid-high latitudes, cold season heat waves cover areas that are 1.25 to 3 times larger than warm season events, and daytime heat waves impact 1.25 to 2 times the area of nighttime heat waves. The reverse relationship is found throughout tropical regions. Average heat wave size, regardless of type or season, has increased across most land in recent years, often by 1.5 to 2 times in the mid-latitudes. The contiguous spatial extent of dry soil anomalies and lower tropospheric subsidence events have also increased in some locations, potentially contributing to the increases in heat wave size. Heat wave size has increased by a factor of 1.5 to 2 times across much of the mid- and high-latitudes according to a surface temperature analysis from 1980-2019.

Spatially compounding extremes pose substantial threats to globally interconnected socio-economic systems. Here we use multiple large ensemble simulations of the high-emissions scenario to show increased risk of compound droughts during the boreal summer over ten global regions. Relative to the late twentieth century, the probability of compound droughts increases by ~40% and ~60% by the middle and late twenty-first century, respectively, with a disproportionate increase in risk across North America and the Amazon. These changes contribute to an approximately ninefold increase in agricultural area and population exposure to severe compound droughts with continued fossil-fuel dependence. ENSO is the predominant large-scale driver of compound droughts with 68% of historical events occurring during El Niño or La Niña conditions. With ENSO teleconnections remaining largely stationary in the future, a ~22% increase in frequency of ENSO events combined with projected warming drives the elevated risk of compound droughts.The co-occurrence of drought across different regions will have far-reaching effects on global agriculture and food supply. Model projections show an increased likelihood of these compound droughts under a high-emissions scenario, with a ninefold increase of farm land and population exposure.

We use a quantile-based bias correction technique and a multi-member ensemble of the atmospheric component of NCAR CCSM3 (CAM3) simulations to investigate the influence of sea surface temperature (SST) biases on future climate change projections. The simulations, which cover 1977-1999 in the historical period and 2077-2099 in the future (A1B) period, use the CCSM3-generated SSTs as prescribed boundary conditions. Bias correction is applied to the monthly time-series of SSTs so that the simulated changes in SST mean and variability are preserved. Our comparison of CAM3 simulations with and without SST correction shows that the SST biases affect the precipitation distribution in CAM3 over many regions by introducing errors in atmospheric moisture content and upper-level (lower-level) divergence (convergence). Also, bias correction leads to significantly different precipitation and surface temperature changes over many oceanic and terrestrial regions (predominantly in the tropics) in response to the future anthropogenic increases in greenhouse forcing. The differences in the precipitation response from SST bias correction occur both in the mean and the percent change, and are independent of the ocean-atmosphere coupling. Many of these differences are comparable to or larger than the spread of future precipitation changes across the CMIP3 ensemble. Such biases can affect the simulated terrestrial feedbacks and thermohaline circulations in coupled climate model integrations through changes in the hydrological cycle and ocean salinity. Moreover, biases in CCSM3-generated SSTs are generally similar to the biases in CMIP3 ensemble mean SSTs, suggesting that other GCMs may display a similar sensitivity of projected climate change to SST errors. These results help to quantify the influence of climate model biases on the simulated climate change, and therefore should inform the effort to further develop approaches for reliable climate change projection.

Over the course of a season, a location’s precipitation is comprised of moisture sourced from a diverse set of geographic regions. Seasonal extremes in precipitation may arise from changes in the contribution of one or several of these sources. Here, we use the Community Earth System Model with numerical water tracers to quantify the contribution of locally sourced, known as precipitation recycling, versus remotely sourced precipitation to seasonal wet and dry extremes across North America. The greatest impact of recycling on both wet and dry extremes is found in the Interior West of the United States where changes to recycling contribute as much as 25%–30% of drought deficit and pluvial surplus. Recycling contributions are smaller across the eastern U.S., generally less than 8%, highlighting the greater role of imported moisture for explaining hydroclimate extremes in these regions. Robust contributions of precipitation recycling to drought and pluvials across the Interior West are driven by consistent changes to local evaporation and the conversion of local evaporation to local precipitation during extreme hydroclimate conditions. The results are consistent with an energy-limited and water-limited evaporation framework and provide a new estimate of the role of local processes in shaping hydroclimate extremes.