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The Palaeocene-Eocene Thermal Maximum (PETM) was a significant global warming event in the Earth's history (approx. 55 Ma). The cause for this warming event has been linked to increases in greenhouse gases, specifically carbon dioxide and methane. This rapid warming took place in the presence of the existing Early Eocene warm climate. Given that projected business-as-usual levels of atmospheric carbon dioxide reach concentrations of 800-1100 ppmv by 2100, it is of interest to study past climates where atmospheric carbon dioxide was higher than present. This is especially the case given the difficulty of climate models in simulating past warm climates. This study explores the sensitivity of the simulated pre-PETM and PETM periods to change in cloud condensation nuclei (CCN) and microphysical properties of liquid water clouds. Assuming lower levels of CCN for both of these periods leads to significant warming, especially at high latitudes. The study indicates that past differences in cloud properties may be an important factor in accurately simulating past warm climates. Importantly, additional shortwave warming from such a mechanism would imply lower required atmospheric CO2 concentrations for simulated surface temperatures to be in reasonable agreement with proxy data for the Eocene.

Siberian Traps flood basalt magmatism coincided with the end-Permian mass extinction approximately 252 million years ago. Proposed links between magmatism and ecological catastrophe include global warming, global cooling, ozone depletion and changes in ocean chemistry. However, the critical combinations of environmental changes responsible for global mass extinction are undetermined. In particular, the combined and competing climate effects of sulfur and carbon outgassing remain to be quantified. Here we present results from global climate model simulations of flood basalt outgassing that account for sulfur chemistry and aerosol microphysics with coupled atmosphere and ocean circulation. We consider the effects of sulfur and carbon in isolation and in tandem. We find that coupling with the ocean strongly influences the climate response to prolonged flood basalt-scale outgassing. We suggest that sulfur and carbon emissions from the Siberian Traps combined to generate systemic swings in temperature, ocean circulation and hydrology within a longer-term trend towards a greenhouse world in the early Triassic.

An unforced simulation of the Community Climate System Model, version 4 (CCSM4), is found to have Greenland warming and cooling events that resemble Dansgaard–Oeschger cycles in pattern and magnitude. With the caveat that only three transitions were available to be analyzed, it is found that the transitions are triggered by stochastic atmospheric forcing. The atmospheric anomalies change the strength of the subpolar gyre, leading to a change in Labrador Sea sea ice concentration and meridional heat transport. The changed climate state is maintained over centuries through the feedback between sea ice and sea level pressure in the North Atlantic. Indications that the initial atmospheric pressure anomalies are preceded by precipitation anomalies in the western Pacific warm pool are discussed. The full evolution of the anomalous climate state depends crucially on the climatic background state.

Atmospheric rivers (ARs) are long, narrow synoptic scale weather features important for Earth’s hydrological cycle typically transporting water vapor poleward, delivering precipitation important for local climates. Understanding ARs in a warming climate is problematic because the AR response to climate change is tied to how the feature is defined. The Atmospheric River Tracking Method Intercomparison Project (ARTMIP) provides insights into this problem by comparing 16 atmospheric river detection tools (ARDTs) to a common data set consisting of high resolution climate change simulations from a global atmospheric general circulation model. ARDTs mostly show increases in frequency and intensity, but the scale of the response is largely dependent on algorithmic criteria. Across ARDTs, bulk characteristics suggest intensity and spatial footprint are inversely correlated, and most focus regions experience increases in precipitation volume coming from extreme ARs. The spread of the AR precipitation response under climate change is large and dependent on ARDT selection. Plain Language Summary Atmospheric rivers (ARs) are long and narrow weather features often referred to as “rivers in the sky.” They often transport water from lower latitudes to higher latitudes typically across climate zones and produce precipitation necessary for local climates. Understanding ARs in a warming climate is challenging because of the variety of ways an AR can be defined on gridded data sets. Unlike weather features such as tropical cyclones where identification methodologies are similar, algorithms that determine the characteristics of ARs vary depending on the science question posed. Because there is no real consensus on AR identification methodology, we aim to quantify the algorithmic uncertainty in AR metrics and precipitation. We compare 16 different ways of defining an AR on gridded data sets and present the range of possibilities in which an AR could change under global warming. Generally, ARs are projected to increase but the amount of that increase is a function of the algorithm. Across all algorithms and focus regions, AR precipitation is projected to become more extreme. Key Points High‐resolution historical and future simulations are used to evaluate atmospheric river detection tools (ARDT) uncertainty ARDTs mostly show increases in frequency and intensity of future atmospheric rivers (ARs) but the scale of response is dependent on algorithmic restrictiveness Most regions experience an increase in precipitation volume coming from extreme ARs

Climate models differ in their responses to imposed forcings, such as increased greenhouse gas concentrations, due to different climate feedback strengths. Feedbacks in NCAR’s Community Atmospheric Model (CAM) are separated into two components: the change in climate components in response to an imposed forcing and the “radiative kernel,” the effect that climate changes have on the top-of-the-atmosphere (TOA) radiative budget. This technique’s usefulness depends on the linearity of the feedback processes. For the case of CO₂ doubling, the sum of the effects of water vapor, temperature, and surface albedo changes on the TOA clear-sky flux is similar to the clear-sky flux changes directly calculated by CAM. When monthly averages are used rather than values from every time step, the global-average TOA shortwave change is underestimated by a quarter, partially as a result of intramonth correlations of surface albedo with the radiative kernel. The TOA longwave flux changes do not depend on the averaging period. The longwave zonal averages are within 10% of the model-calculated values, while the global average differs by only 2%. Cloud radiative forcing (ΔCRF) is often used as a diagnostic of cloud feedback strength. The net effect of the water vapor, temperature, and surface albedo changes on ΔCRF is −1.6W m−2, based on the kernel technique, while the total ΔCRF from CAM is −1.3 W m−2, indicating these components contribute significantly to ΔCRF and make it more negative. Assuming linearity of the ΔCRF contributions, these results indicate that the net cloud feedback in CAM is positive.

The extent to which the climate will change due to an external forcing depends largely on radiative feedbacks, which act to amplify or damp the surface temperature response. There are a variety of issues that complicate the analysis of radiative feedbacks in global climate models, resulting in some confusion regarding their strengths and distributions. In this paper, the authors present a method for quantifying climate feedbacks based on “radiative kernels” that describe the differential response of the top-of-atmosphere radiative fluxes to incremental changes in the feedback variables. The use of radiative kernels enables one to decompose the feedback into one factor that depends on the radiative transfer algorithm and the unperturbed climate state and a second factor that arises from the climate response of the feedback variables. Such decomposition facilitates an understanding of the spatial characteristics of the feedbacks and the causes of intermodel differences. This technique provides a simple and accurate way to compare feedbacks across different models using a consistent methodology. Cloud feedbacks cannot be evaluated directly from a cloud radiative kernel because of strong nonlinearities, but they can be estimated from the change in cloud forcing and the difference between the full-sky and clear-sky kernels. The authors construct maps to illustrate the regional structure of the feedbacks and compare results obtained using three different model kernels to demonstrate the robustness of the methodology. The results confirm that models typically generate globally averaged cloud feedbacks that are substantially positive or near neutral, unlike the change in cloud forcing itself, which is as often negative as positive.

Two Earth system models are analyzed to gain insight into the processes that govern projected changes in the South Asian monsoon. Warmer present‐day base state tropical SSTs contribute to coupled processes that produce greater future tropical Pacific warming in CESM2 with less of an increase in season‐mean monsoon precipitation compared to E3SMv2. This is attributed to changes in the large‐scale east‐west atmospheric Walker circulation, with relatively larger increases in precipitation and upper‐level divergence over the tropical Pacific and increases in upper‐level convergence over South Asia in CESM2. The stronger El Niño‐like response in CESM2, which increases Pacific precipitation and upper‐level divergence farther to the east, and larger future ENSO amplitude in E3SMv2, produce a greater relative increase in future monsoon‐ENSO connections in E3SMv2 compared to CESM2. This analysis indicates that the key processes that affect future monsoon‐ENSO connections are ENSO amplitude and size of the future tropical Pacific El Niño‐like response. Plain Language Summary Two different Earth system models are analyzed to investigate processes that contribute to possible future changes of South Asian monsoon precipitation and connections to ENSO. The stronger increase of precipitation in CESM2 over the tropical Pacific, due in part to a larger El Niño‐like response of Pacific SSTs, produces less of an increase in future monsoon precipitation in CESM2 compared to E3SMv2. The eastward shift of precipitation in CESM2, along with the larger increase of ENSO amplitude in E3SMv2, produce a stronger future monsoon‐ENSO connection in E3SMv2 compared to CESM2. Key Points Warmer future tropical Pacific SSTs in CESM2 compared to E3SMv2 produce less of an increase in South Asian monsoon precipitation through the Walker Circulation Future monsoon‐ENSO connections are stronger in E3SMv2 compared to CESM2 due to larger increases in future ENSO amplitude and shifts in the Walker Circulation Key processes that affect future monsoon‐ENSO connections are ENSO amplitude and the size of the future tropical Pacific El Niño‐like response

The effects of differences in climate base state are related to processes associated with the present‐day South Asian monsoon simulations in the Energy Exascale Earth System Model version 2 (E3SMv2) and the Community Earth System Model version 2 (CESM2). Though tropical Pacific and Indian Ocean base state sea surface temperatures (SSTs) are over 1°C cooler in E3SMv2 compared to CESM2, and there is an overall reduction of Indian sector precipitation, the pattern of South Asian monsoon precipitation is similar in the two models. Monsoon‐ENSO teleconnections, dynamically linked by the large‐scale east‐west atmospheric circulation, are reduced in E3SMv2 compared to CESM2. In E3SMv2, this is related to cooler tropical SSTs and ENSO amplitude that is less than half that in CESM2. Comparison to a tropical Pacific pacemaker experiment shows, to a first order, that the base state SSTs and ENSO amplitude contribute roughly equally to lower amplitude monsoon‐ENSO teleconnections in E3SMv2. Plain Language Summary Two different Earth system models are analyzed to investigate how differences in simulated base state tropical sea surface temperatures (SSTs) and El Niño/Southern Oscillation (ENSO) amplitude affect the processes associated with the South Asian monsoon. Though tropical SSTs are over 1°C cooler in the Energy Exascale Earth System Model version 2 (E3SMv2) and there is overall reduced Indian sector precipitation, the regional pattern of South Asian monsoon precipitation is similar in the two models. More significantly, monsoon‐ENSO teleconnections are reduced in E3SMv2 compared to Community Earth System Model version 2 (CESM2) due to cooler mean tropical SSTs combined with ENSO amplitude in E3SMv2 that is less than half that in CESM2. Key Points Base state differences in Energy Exascale Earth System Model version 2 (E3SMv2) compared to Community Earth System Model version 2 (CESM2) include cooler tropical Indian and Pacific sea surface temperatures (SSTs) and reduced ENSO amplitude Base state differences in the two models do not appreciably affect simulations of the regional patterns of South Asian monsoon precipitation Cooler SSTs and lower amplitude ENSO in E3SMv2 combine to contribute about equally to weaker monsoon‐ENSO teleconnections compared to CESM2

The low-resolution version of the Community Climate System Model, version 4 (CCSM4) is a computationally efficient alternative to the intermediate and standard resolution versions of this fully coupled climate system model. It employs an atmospheric horizontal grid of 3.75° × 3.75° and 26 levels in the vertical with a spectral dynamical core (T31) and an oceanic horizontal grid that consists of a nominal 3° resolution with 60 levels in the vertical. This low-resolution version (T31x3) can be used for a variety of applications including long equilibrium simulations, development work, and sensitivity studies. The T31x3 model is validated for modern conditions by comparing to available observations. Significant problems exist for Northern Hemisphere Arctic locales where sea ice extent and thickness are excessive. This is partially due to low heat transport in T31x3, which translates into a globally averaged sea surface temperature (SST) bias of −1.54°C compared to observational estimates from the 1870–99 historical record and a bias of −1.26°C compared to observations from the 1986–2005 historical record. Maximum zonal wind stress magnitude in the Southern Hemisphere matches observational estimates over the ocean, although its placement is incorrectly displaced equatorward. Aspects of climate variability in T31x3 compare to observed variability, especially so for ENSO where the amplitude and period approximate observations. T31x3 surface temperature anomaly trends for the twentieth century also follow observations. An examination of the T31x3 model relative to the intermediate CCSM4 resolution (finite volume dynamical core 1.9° × 2.5°) for preindustrial conditions shows the T31x3 model approximates this solution for climate state and variability metrics examined here.

The low-resolution fully coupled configuration of the Community Climate System Model version 3 (CCSM3) is described and evaluated. In this most economical configuration, an ocean at nominal 3° resolution is coupled to an atmosphere model at T31 resolution. There are climate biases associated with the relatively coarse grids, yet the coupled solution remains comparable to higher-resolution CCSM3 results. There are marked improvements in the new solutioncompared to the low-resolution configuration of CCSM2. In particular, the CCSM3 simulation maintains a robust meridional overturning circulation in the ocean, and it generates more realistic El Niño variability. The improved ocean solution was achieved with no increase in computational cost by redistributing deep ocean and midlatitude resolution into the upper ocean and the key water formation regions of the North Atlantic, respectively. Given its significantly lower resource demands compared to higher resolutions, this configuration shows promise for studies of paleoclimate and other applications requiring long, equilibrated solutions.