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We study the sensitivity of South Asian Summer Monsoon (SASM) precipitation to Southern Hemisphere (SH) subtropical Absorbed Solar Radiation (ASR) changes using Community Earth System Model 2 simulations. Reducing positive ASR biases over the SH subtropics impacts SASM, and is sensitive to the ocean basin where changes are imposed. Radiation changes over the SH subtropical Indian Ocean (IO) shifts rainfall over the equatorial IO northward causing 1–2 mm/day drying south of equator, changes over the SH subtropical Pacific increases precipitation over northern continental regions by 1–2 mm/day, and changes over the SH subtropical Atlantic have little effect on SASM precipitation. Radiation changes over the subtropical Pacific impacts the SASM through zonal circulation changes, while changes over the IO modify meridional circulation to bring about changes in precipitation over northern IO. Our findings suggest that reducing SH subtropical radiation biases in climate models may also reduce SASM precipitation biases. Precipitation from South Asian Summer Monsoon (SASM) is of high significance to the livelihoods of over a billion people. As the global climate continues to evolve, it is essential to have a clear understanding of the possible future changes to the SASM. However, current state‐of‐the‐art climate models have difficulties in simulating climatological mean SASM precipitations. Here we study sensitivity of SASM precipitation to subtropical southern ocean radiation as one of the possible causes of SASM precipitation bias. Our experiments indicate that SASM precipitation is sensitive to southern hemisphere (SH) subtropical radiation changes particularly to those in subtropical Pacific. These findings imply that improving SH subtropical radiation biases might improve SASM precipitation simulations in climate models. We test if biases in southern hemisphere shortwave radiation contributes to biases in South Asian summer monsoon precipitation in the CESM2Reducing incoming shortwave radiation in the subtropical southern hemisphere reduces dry biases over continental South AsiaThis effect is mostly due to forcing in the South Pacific, with less impact from the Atlantic or Indian Ocean We test if biases in southern hemisphere shortwave radiation contributes to biases in South Asian summer monsoon precipitation in the CESM2 Reducing incoming shortwave radiation in the subtropical southern hemisphere reduces dry biases over continental South Asia This effect is mostly due to forcing in the South Pacific, with less impact from the Atlantic or Indian Ocean

Marine low‐level clouds continue to be poorly simulated in models despite many studies and field experiments devoted to their improvement. Here we focus on the spatial errors in the cloud decks in the Department of Energy Earth system model (the Energy Exascale Earth System Model [E3SM]) relative to the satellite climatology by calculating centroid distances, area ratios, and overlap ratios. Since model dynamics is better simulated than clouds, these errors are attributed primarily to the model physics. To gain additional insight, we performed a sensitivity run in which model winds were nudged to those of reanalysis. This results in a large change (but not necessarily an improvement) in the simulated cloud decks. These differences between simulations are mainly due to the interactions between model dynamics and physics. These results suggest that both model physics (widely recognized) and its interaction with dynamics (less recognized) are important to model improvement in simulating these low‐level clouds. Spatial errors in cloud decks as characterized by centroid distances, area ratios, and overlap ratios from four U.S. models are evaluatedThe reasons for these errors are explored by performing a sensitivity test with model winds nudged to those of reanalysisThe interaction between model dynamics and physics plays an important role in the simulation of these cloud decks

One of the grand challenges of climate science is understanding the changes of the tropical rain belts and monsoon systems owing to CO2‐induced warming. A promising path forward links the fluxes of energy and moisture to tropical circulation features. To this end, we make use of the Energy Exascale Earth System Model version 1, where the divergence of moist static energy and moisture have been calculated online, and employ a normalized gross moist stability (NGMS) diagnostic framework to understand the linkages between changes in the flow of energy and moisture within the monsoons. We focus on the Asian Summer Monsoon system and utilize a series of atmosphere‐land and atmosphere‐land‐ocean simulations to understand the connection between fluxes and monsoons. Uncoupled simulations with prescribed sea surface temperatures indicate that decreases in NGMS over land are important in explaining precipitation increases in response to both sea surface temperature and CO2increases. In fully coupled experiments, NGMS decreases remain an important contributor to the increase in P‐E, but the coupled simulations highlight the importance of consistent ocean and land responses in interpreting the monsoon changes. This study indicates that transient eddy fluxes play an important role in NGMS decreases and that a time‐mean view of the monsoon circulations is insufficient to quantify the link between future changes in the fluxes of energy and moisture. Compensation between dynamic and thermodynamic components of vertical moist static energy advection occurs, with the thermodynamic contribution dominating. The compensation is shown to be sensitive to relative humidity, with higher relative humidity leading to a stronger thermodynamic component. One of the challenges of climate science is understanding how warming will change monsoon rainfall. A promising path forward links the transport of energy to the transport of water vapor. This link, termed the normalized gross moist stability (NGMS), can be used to fingerprint monsoon rainfall changes coming from different energy sources as well as changes to NGMS itself. A fingerprint of the Asian Summer Monsoon rainfall response to warming is made for a general circulation model, which highlights the importance of the NGMS term for understanding the monsoon rainfall response to warming. By examining this NGMS term more carefully, evidence is shown for the importance of the ocean circulation toward explaining the monsoon rainfall response to warming. Further analysis of the NGMS term also suggests that the traditional time‐mean view of the monsoon is insufficient to explain its response to warming. The response of NGMS to warming is shown to be sensitive to the relative humidity of the atmosphere. Normalized gross moist stability framework diagnoses key factors for increase in Asian Summer Monsoon water cycle with warmingPrescribing sea surface temperature increases have an inconsistent circulation response to simulations with an active ocean modelTransient eddies contribute significantly to the changing normalized gross moist stability with warming

Anthropogenic sulfur compounds play an important role in acid deposition, aerosol particle formation, and subsequent radiative forcing and human fine particulate exposure. There are substantial uncertainties in processes influencing sulfate and precursor distributions, however, that have not yet been resolved through comparisons with observations. We find here an underappreciated factor that has a large impact on model results: uncertain emission height. Global aerosol‐climate model simulations indicate that the assumed effective anthropogenic emission height is very important to SO2near‐surface concentrations and vertical profile. The global range of near‐surface SO2concentration over land (ocean) due to uncertainty in industrial (international shipping) emission injection height is 81% (76%), relative to the average concentration. This sensitivity is much larger than the uncertainty of SO2emission rates. Black carbon and primary organic matter concentration and profiles are also sensitive to emission heights (53% over land and 28% over oceans). The impact of emission height uncertainty is larger in winter for land‐based emissions, but larger in summer over the Northern Hemisphere ocean for shipping emissions. The variation in aerosol optical depth related to shipping emission injection heights is 11% over oceans, revealing the potential importance of injection height on aerosol forcing and climatic effects. The large impact on SO2concentrations can confound attempts to use surface, aircraft, and satellite observations to constrain the importance of other processes that govern sulfur compound distributions in the atmosphere. The influence of emission height on vertical SO2column also will impact the accuracy of satellite retrievals. Models are central tools in understanding how air pollutants are transported and transformed within the atmosphere, and it is essential to evaluate modeled air pollutants by comparing to observations. The conversion of sulfur dioxide to sulfate aerosol in the atmosphere is important for both climate forcing and air pollution analysis. We find that modeled near‐surface concentration and vertical distribution of sulfur dioxide gas are very sensitive to the assumed effective emission height, with the influence of injection height differing by season and region. The uncertainty in assumed effective emission height can also affect aerosol radiative forcing and its climatic effects. Given that emission heights are uncertain, the ability to evaluate the sulfur cycle and aerosol forcing in models may be compromised. Uncertainty in assumed effective emission height strongly affects SO2concentration and vertical profileThe impact of emission injection height uncertainty varies by emission speciesAerosols and their climate impacts can be influenced by emission height

The fidelity of a prerelease Energy Exascale Earth System Model (E3SM) in reproducing atmospheric blocking is evaluated with ∼100‐ and ∼25‐km horizontal resolution within ensembles of simulations with Atmospheric Modeling Intercomparison Protocol‐type active atmosphere and land surface configurations. This evaluation is conducted via a hybrid bidimensional blocking index based on geopotential height. The lower‐resolution model correctly reproduces the spatial distribution of blocking frequency maxima over the Northern Hemisphere. However, it overestimates the blocking frequency over western North America, the Pacific Northeast, and Eastern Europe regions and largely underestimates blocking frequency over the North Atlantic. The high‐resolution model significantly reduces the bias over the North Pacific region, particularly over western North America, but the biases over the North Atlantic blocking sector mostly persist. A diagnosis of the mean flow reveals that the subtropical jet is displaced poleward in the high‐resolution model with a jet core speed that is generally more realistic. A time scale analysis of eddies suggests that synoptic eddies associated with the blocking events are increased in the high‐resolution configuration. The discrepancy between the models implies that both synoptic and low‐frequency eddies play significant roles in determining North Pacific blocking, whereas North Atlantic blocking is mainly driven by low‐frequency eddies. The characteristic time scale associated with blocking events is also investigated, and it shows that both model resolutions produce events that are overly persistent. However, the bias in the high‐resolution model is reduced, which reflects more efficient energy dispersion with higher resolution. Understanding atmospheric blocking, or large‐scale persistent flow anomalies, is critical for extreme weather prediction at the Earth's surface. Therefore, we analyze how well the prerelease Energy Exascale Earth System Model (E3SM) reproduces blocking with two configurations: one that resolves the global scale flow and one that is able to capture finer scale features, using grid resolutions of ∼100 and ∼25 km, respectively. Both models generally correctly reproduce the location and distribution of blocks over the Northern Hemisphere; however, the finer‐scale model is more accurate over the North Pacific region. Both models underestimate the number of blocks over the North Atlantic. We analyze the mean flow and find that the jet stream is displaced toward the pole and has a more realistic speed in the fine‐scale model. This improvement appears linked to the ability to capture more finer‐scale eddies, which are associated with blocking. The discrepancy implies that both fine‐scale and low‐frequency eddies are important in determining North Pacific blocking, whereas North Atlantic blocking is mainly driven by low‐frequency eddies, which are not improved with resolution. Both model resolutions produce blocks that last too long; however, the fine‐scale model is closer to observations. The E3SM v0.3 atmosphere model produces improved North Pacific blocking frequency with increased resolutionThe E3SM v0.3 produces a realistic jet maximum latitude over both ocean basin sectorsAtlantic blocks are driven mostly by low‐frequency eddies, so increased horizontal resolution does not lead to improvements

Black carbon (BC) has previously been found to intensify haze in China by stabilizing the planetary boundary layer. With ocean, sea ice, and cloud feedbacks included in a global aerosol‐climate model, we show that BC emitted from the North China Plain can be transported to the oceans, which in turn changes cloud structure and land‐sea thermal contrast. As a result, East Asian winter monsoon wind speeds decrease over the North China Plain. This decrease causes air stagnation that can further intensify haze. Our results suggest that in addition to the local BC‐induced interactions between aerosol and the planetary boundary layer, BC can also amplify haze in the North China Plain by weakening East Asian winter monsoon through ocean, sea ice, and cloud feedbacks. It implies that reducing BC emissions could have significant indirect benefits for air quality in the North China Plain. China has been experiencing severe winter air pollution in recent years. The pollution particles harm human health, affect atmospheric visibility, and cause adverse effects on economic and societal activities. The poor air quality was linked to high emissions from human activities and air stagnation associated with meteorological conditions and climate change. Recent studies reported that black carbon (BC), one of the by‐products when wood or coal is burned, could intensify pollution in China by stabilizing the lower atmosphere (i.e., weakening vertical air mixing and dispersion of pollution plumes). In this study, we show that in addition to the impact on atmospheric mixing, BC can also amplify particle pollution in the North China Plain by weakening the East Asian winter monsoon through ocean, sea ice, and cloud feedbacks. This implies that reducing BC emissions could help mitigate air pollution in the North China Plain. BC weakens East Asian winter monsoon winds by changing cloud structure and land‐sea thermal contrastThe impact on monsoon winds per unit change in Arctic BC is similar to that of local BC emissions but has a larger uncertaintyReducing BC emissions could have significant indirect benefits for air quality control in the North China Plain

As global temperatures increase, sea ice loss will increasingly enable commercial shipping traffic to cross the Arctic Ocean, where the ships' gas and particulate emissions may have strong regional effects. Here we investigate impacts of shipping emissions on Arctic climate using a fully coupled Earth system model (CESM 1.2.2) and a suite of newly developed projections of 21st‐century trans‐Arctic shipping emissions. We find that trans‐Arctic shipping will reduce Arctic warming by nearly 1 °C by 2099, due to sulfate‐driven liquid water cloud formation. Cloud fraction and liquid water path exhibit significant positive trends, cooling the lower atmosphere and surface. Positive feedbacks from sea ice growth‐induced albedo increases and decreased downwelling longwave radiation due to reduced water vapor content amplify the cooling relative to the shipping‐free Arctic. Our findings thus point to the complexity in Arctic climate responses to increased shipping traffic, justifying further study and policy considerations as trade routes open. Global warming is melting Arctic sea ice, thereby enabling greater maritime access to the Arctic Ocean. Emissions such as black carbon and sulfur from ships have the potential to warm the climate further by darkening snow and ice surfaces or cool the climate by promoting cloud formation. This study used a global Earth system model to simulate the climatic effects of emissions from ships crossing the Arctic Ocean from the present to 2099. We find that shipping emissions increase formation of clouds with high liquid water content, and cause the Arctic surface air to cool nearly 1° by 2099 relative to the shipping‐free Arctic. This cooling effect was amplified further by sea ice growth and reduced atmospheric water vapor. Our results illustrate the complexity of climatic responses to increased shipping in the Arctic and the need for greater understanding of the reciprocal nature of climate and human activities. Climatic responses to projected trans‐Arctic shipping emissions are simulated using a fully coupled Earth system model (CESM 1.2.2)Shipping emissions reduce Arctic warming by nearly 1 °C by 2099 due to sulfate‐driven liquid water cloud formationSea ice growth‐induced albedo increases and reduced atmospheric water vapor amplify cooling relative to control runs

We compare various radiative feedbacks over the Arctic (60–90°N) estimated from short‐term climate variations occurring in reanalysis, satellite, and global climate model data sets using the combined Kernel‐Gregory approach. The lapse rate and surface albedo feedbacks are positive, and their magnitudes are comparable. Relative to the tropics (30°S–30°N), the lapse rate feedback is the largest contributor to Arctic amplification among all feedbacks, followed by surface albedo feedback and Planck feedback deviation from its global mean. Both shortwave and longwave water vapor feedbacks are positive, leading to a significant positive net water vapor feedback over the Arctic. The net cloud feedback has large uncertainties including its sign, which strongly depends on the data used for all‐sky and clear‐sky radiative fluxes at the top of the atmosphere, the time periods considered, and the methods used to estimate the cloud feedback. The Arctic has warmed dramatically in recent decades, with temperature increasing at a rate of about twice as fast as the global mean value. This phenomenon, commonly known as Arctic amplification, has been found in the observed and modeled climate changes. Several feedback mechanisms have been shown to contribute to Arctic amplification, but their relative importance is still very uncertain. Here we use a variety of reanalysis and satellite data sets to quantify the Arctic local feedbacks based on short‐term climate variations, evaluate the feedbacks simulated in a global climate model, diagnose the impact of data set choices on the feedback estimates, and identify the sources of main uncertainties. The most disagreement is found in the estimate of cloud feedback. Lapse rate feedback is the largest contributor to Arctic amplification relative to the tropicsLapse rate feedback is consistently comparable to surface albedo feedback over the ArcticEstimated net cloud feedback over the Arctic is largely uncertain including its sign

It has been proposed that increasing greenhouse gas (GHG) driven climate tipping point risks may prompt consideration of solar radiation modification (SRM) climate intervention to reduce those risks. Here, we study marine cloud brightening (MCB) SRM interventions in three subtropical oceanic regions using Community Earth System Model 2 experiments. We assess the MCB impact on tipping element‐related metrics to estimate the extent to which such interventions might reduce tipping element risks. Both the pattern and magnitude of the MCB cooling depend strongly on location of the MCB intervention. We find the MCB cooling effect reduces most tipping element impacts; though differences in MCB versus GHG climate response patterns mean MCB is an imperfect remedy. However, MCB applied in certain regions may exacerbate certain GHG tipping element impacts. Thus, it is crucial to carefully consider the pattern of MCB interventions and their teleconnected responses to avoid unintended climate effects. Marine cloud brightening (MCB) is a proposal to spray sea salt particles into clouds over oceans to increase the reflection of sunlight by the clouds, thus cooling the surface. If greenhouse gas warming continues, technologies like MCB might be considered to avoid climate change impacts such as climate system tipping points. Here, we use state‐of‐the‐art climate model experiments to analyze the MCB impact on elements of the climate system that may have tipping points. In this model, MCB reduces risks for most tipping elements considered here, such as by reducing coral reef heat stress and increasing Atlantic overturning circulation. However, the impact of MCB depends on where it is applied and in some cases adds to GHG impacts, meaning the location of MCB deployments must be carefully considered to avoid unintended regional climate effects. The magnitude and pattern of marine cloud brightening (MCB) climate impacts depend strongly on the location of the interventionWe find MCB impacts that have qualitative similarities to prior work, but there are discrepancies that suggest key inter‐model uncertaintiesMCB simulations generally show reduced tipping element risk overall, but certain MCB patterns may exacerbate some tipping element changes The magnitude and pattern of marine cloud brightening (MCB) climate impacts depend strongly on the location of the intervention We find MCB impacts that have qualitative similarities to prior work, but there are discrepancies that suggest key inter‐model uncertainties MCB simulations generally show reduced tipping element risk overall, but certain MCB patterns may exacerbate some tipping element changes

The relationship between forcing and emission is investigated for black carbon (BC) and primary organic carbon (OC) emitted from North America and Asia. Direct and indirect radiative forcing (DRF and IRF) of BC and OC are simulated with CAM5.1. Two diagnostics are introduced to aid policy‐relevant discussions: linearity and emission‐normalized forcing. DRF is linearly related to emission for both BC and OC from two regions, and the linear relationship is similar, within 15%. IRF is linear in emissions when emissions are lower and regions are far from sources (North American BC and OC). Indirect radiative forcing is sublinear for strong sources and near‐source regions (Asian OC). Emission‐normalized IRF in North America is two to four times higher than that in Asia. The difference among regions and species is primarily caused by particle density as high density of BC results in fewer emitted particles and by the processes for accumulation mode particles to become cloud condensation nuclei and then to activate into cloud droplet. Lower emission‐normalized IRF in more polluted regions means that reductions of OC in these regions would be relatively climate‐neutral rather than causing significant warming via IRF reduction. An optimal aggregation area (30° × 30°) is identified for analysis of the forcing‐to‐emission relationship. For IRF, only 15–40% of the Earth's surface is significantly affected by an emission region, but forcing in these regions comprises most of the global impact. Emission‐normalized forcing can be used to estimate forcing changes due to emission reductions, as long as causes of nonlinearity are identified and considered. Forcing is linear in emission for direct forcing everywhere and indirect forcing far from sources and in regions with low emission fluxIn regions with high emission flux, indirect forcing is less than linear in emission, so emission reductions cause less positive forcingForcing response to emission reductions can be estimated using emission‐normalized forcing, if causes of nonlinearity are considered

Source attribution of Arctic sulfate and its radiative forcing due to aerosol‐radiation interactions (RFari) for 2010–2014 are quantified in this study using the Community Earth System Model equipped with an explicit sulfur source‐tagging technique. The model roughly reproduces the seasonal pattern of sulfate but has biases in simulating the magnitude of near‐surface concentrations and vertical distribution. Regions that have high emissions and/or are near/within the Arctic present relatively large contributions to Arctic sulfate burden, with the largest contribution from sources in East Asia (27%). Seasonal variations of the contribution to Arctic sulfate burden from remote sources are strongly influenced by meteorology. The mean RFari of anthropogenic sulfate offsets one third of the positive top of the atmosphere (TOA) RFari from black carbon. A 20% global reduction in anthropogenic SO2emissions leads to a net Arctic TOA forcing increase of +0.019 W m−2. These results indicate that a joint reduction in BC and SO2emissions could prevent at least some of the Arctic warming from any future SO2emission reductions. Sulfate RFari efficiency calculations suggest that source regions with short transport pathways and meteorology favoring longer lifetimes are more efficient in influencing the Arctic sulfate RFari. Based on Arctic climate sensitivity factors, about −0.19 K of the Arctic surface temperature cooling is attributed to anthropogenic sulfate, with −0.05 K of that from sources in East Asia, relative to preindustrial conditions. Meteorology drives the seasonality of remote contributions to Arctic sulfate burdenSulfate radiative forcing can partly offset Arctic positive forcing from black carbonSources in regions having short transport pathways and long lifetimes are more efficient in influencing Arctic radiation

Anthropogenic emissions and land use changes have modified atmospheric aerosol concentrations and size distributions over time. Understanding preindustrial conditions and changes in organic aerosol due to anthropogenic activities is important because these features (1) influence estimates of aerosol radiative forcing and (2) can confound estimates of the historical response of climate to increases in greenhouse gases. Secondary organic aerosol (SOA), formed in the atmosphere by oxidation of organic gases, represents a major fraction of global submicron‐sized atmospheric organic aerosol. Over the past decade, significant advances in understanding SOA properties and formation mechanisms have occurred through measurements, yet current climate models typically do not comprehensively include all important processes. This review summarizes some of the important developments during the past decade in understanding SOA formation. We highlight the importance of some processes that influence the growth of SOA particles to sizes relevant for clouds and radiative forcing, including formation of extremely low volatility organics in the gas phase, acid‐catalyzed multiphase chemistry of isoprene epoxydiols, particle‐phase oligomerization, and physical properties such as volatility and viscosity. Several SOA processes highlighted in this review are complex and interdependent and have nonlinear effects on the properties, formation, and evolution of SOA. Current global models neglect this complexity and nonlinearity and thus are less likely to accurately predict the climate forcing of SOA and project future climate sensitivity to greenhouse gases. Efforts are also needed to rank the most influential processes and nonlinear process‐related interactions, so that these processes can be accurately represented in atmospheric chemistry‐climate models. Secondary organic aerosol (SOA), formed in the atmosphere by oxidation of organic gases, often represents a major fraction of global submicron‐sized atmospheric organic aerosol. Myriad processes affect SOA formation, several of which relate to interactions between natural biogenic emissions and predominantly anthropogenic species such as SO2, NOx, sulfate, nitrate, and ammonium. Many of these key processes are nonlinear and can be synergistic or act to compensate each other in terms of climate forcing. Current atmospheric chemistry‐climate models mostly do not treat these processes. We highlight a number of process‐level mechanisms related to the interactions between anthropogenic and biogenic SOA precursors, for which the corresponding impacts on the radiative effects of SOA need to be investigated in atmospheric chemistry‐climate models. Ultimately, climate models need to capture enough important features of the chemical and dynamic evolution of SOA, in terms of both aerosol number and aerosol mass, as a function of atmospheric variables and anthropogenic perturbations to reasonably predict the spatial and temporal distributions of SOA. A better understanding of SOA formation mechanisms and physical properties is needed to improve estimates of the extent to which anthropogenic emissions and land use changes have modified global aerosol concentrations and size distributions since preindustrial times. We review some important developments in secondary organic aerosol (SOA) that could impact aerosol radiative forcing and response of climate to greenhouse gasesWe highlight some of the important processes that involve interactions between natural biogenic emissions and anthropogenic emissionsWe discuss fundamental SOA properties volatility and viscosity and their relation to evolution of aerosol mass and number concentrations in the atmosphere

In January 2016, a robust reversal of the Arctic Oscillation took place associated with a rapid tropospheric warming in the Arctic region; this was followed by the occurrence of a classic sudden stratospheric warming in March. The succession of these two distinct Arctic warming events provides a stimulating opportunity to examine their characteristics in terms of similarities and differences. Historical cases of these two types of Arctic warming were identified and validated based upon tropical linkages with the Madden‐Julian Oscillation and El Niño as documented in previous studies. The analysis indicates a recent and seemingly accelerated increase in the tropospheric warming type versus a flat trend in stratospheric warming type. The shorter duration and more rapid transition of tropospheric warming events may connect to the documented increase in midlatitude weather extremes, more so than the route of stratospheric warming type. Forced simulations with an atmospheric general circulation model suggest that the reduced Arctic sea ice contributes to the observed increase in the tropospheric warming events and associated remarkable strengthening of the cold Siberian high manifest in 2016. A distinct type of Arctic warming events is identified, one that is confined in the troposphere without a stratospheric precursorTropospheric warming events occur twice as fast as the stratospheric type, challenging subseasonal predictionTropospheric warming events have increased at an accelerated pace, surpassing stratospheric warming events in the recent decade Rapid Arctic warming events disrupt mid‐latitude weather patterns and oftentimes produce extreme deviations from normal weather conditions. The atmospheric origins of these Arctic warming events have been identified as developing in the troposphere and the stratosphere. Using historical observations, we have found that the frequency of tropospheric warming events has increased through the recent decades, while the stratospheric events have not. We have also found that tropospheric events develop twice as fast as stratospheric events and are therefore less predictable. With observations of historically‐low Arctic sea ice extent occurring alongside the increase of tropospheric warming events, computer simulations provided evidence that the two phenomena are likely linked. Along with observational evidence for enhanced transport of tropical energy helping fuel these Arctic tropospheric warming events, these results suggest that future mid‐latitude weather is likely to undergo an increase to extreme, unseasonal weather patterns that are inherently less predictable.

The magnitude of the aerosol forcing remains among the largest unknowns when assessing climate sensitivity over the historical period. Here, we quantify and explain a crucial but often overlooked source of uncertainty in aerosol forcing: the temporal variability of aerosol emissions. We show that time‐variability in biomass burning (BB) emissions weakens the time‐averaged total aerosol forcing, particularly in the Northern Hemisphere mid‐ to high‐latitudes. BB emissions variability produces weaker (less negative) mean effective radiative forcing (ERF) compared to scenarios with no interannual variability in emissions. Satellite‐estimated BB emissions (and associated variability) result in a June–September absolute ERF (relative to zero BB emissions) of −7.7 W m−2from 50° to 70°N, compared to −10.4 W m−2when no emissions variability is used in the Community Earth System Model version 2 (CESM2). This difference in forcing is attributable to nonlinear aerosol‐cloud interactions. Aerosol forcing will be overestimated (i.e., more negative) if emissions are temporally‐smoothed. Aerosols are small particles in the air that can impact the climate, but we don't know exactly how much. One reason for this uncertainty is that the amount of aerosols can change a lot over time, especially when it comes from burning things like wood or plants (i.e., biomass burning emissions). When the amount of these biomass burning aerosols changes a lot from year‐to‐year, it has less of an impact on the climate. This is because clouds react less strongly when aerosol concentrations are high compared to when they are low. If we smooth out the changes in aerosol amounts over time (as is done with most Earth System Model simulations), we will overestimate their cooling impact on the climate. The radiative forcing due to aerosols is overestimated if emissions are temporally‐smoothedInterannual variability in aerosol emissions leads to a weakened time‐average cloud radiative effectChanges in time‐average cloud radiative effect with differing aerosol variability are due to nonlinear aerosol‐cloud interactions The radiative forcing due to aerosols is overestimated if emissions are temporally‐smoothed Interannual variability in aerosol emissions leads to a weakened time‐average cloud radiative effect Changes in time‐average cloud radiative effect with differing aerosol variability are due to nonlinear aerosol‐cloud interactions

The Community Atmosphere Model Version 5 is run at horizontal grid spacing of 2, 1, 0.5, and 0.25°, with the meteorology nudged toward the Year Of Tropical Convection analysis, and cloud simulators and the collocated A‐Train satellite observations are used to explore the resolution dependence of aerosol‐cloud interactions. The higher‐resolution model produces results that agree better with observations, showing an increase of susceptibility of cloud droplet size, indicating a stronger first aerosol indirect forcing (AIF), and a decrease of susceptibility of precipitation probability, suggesting a weaker second AIF. The resolution sensitivities of AIF are attributed to those of droplet nucleation and precipitation parameterizations. The annual average AIF in the Northern Hemisphere midlatitudes (where most anthropogenic emissions occur) in the 0.25° model is reduced by about 1 W m−2(−30%) compared to the 2° model, leading to a 0.26 W m−2reduction (−15%) in the global annual average AIF. Using simulators and constrained meteorology facilitates fair model evaluationSpopand AIF decrease, but SReincreases with increasing resolutionDroplet nucleation and precipitation processes exhibit resolution sensitivity

The Indian summer monsoon is influenced by numerous factors, including aerosol-induced changes to clouds, surface and atmospheric heating, and atmospheric circulation. Most previous studies assessing the effect of aerosols on monsoon rainfall have focussed on the local impact of aerosols on precipitation on monthly to seasonal timescales. Here, we show that desert dust aerosol levels over the Arabian Sea, West Asia and the Arabian Peninsula are positively correlated with the intensity of the Indian summer monsoon, using satellite data and models; a lead–lag analysis indicates that dust and precipitation vary in concert over timescales of about a week. Our analysis of global climate model simulations indicates that by heating the atmosphere, dust aerosols induce large-scale convergence over North Africa and the Arabian Peninsula, increasing the flow of moisture over India within a week. According to these simulations, dust-induced heating of the atmosphere over North Africa and West Asia rapidly modulates monsoon rainfall over central India.

Historical simulations performed for the Coupled Model Intercomparison Project Phase 6 used biomass burning emissions between 1997 and 2014 containing higher spatial and temporal variability compared to emission inventories specified for earlier years, and compared to emissions used in previous (e.g., CMIP5) simulation intercomparisons. Using the Community Earth System Model version 2 Large Ensemble, we show this increased biomass burning emissions variability leads to amplification of the hydrologic cycle poleward of 40°N. Notably, the high variability of biomass burning emissions leads to increased latent heat fluxes, column‐integrated precipitable water, and precipitation. Greater ocean heat uptake, weaker meridional energy transport from the tropics, greater atmospheric shortwave and longwave absorption, and lower relative humidity act to moderate this hydrologic cycle amplification. Our results suggest it is not only the secular changes (on multidecadal timescales) in biomass burning emissions that impact the hydrologic cycle, but also the shorter timescale variability in emissions. Global climate models use different inputs to simulate the past climate as accurately as possible. One of these inputs is an estimate of emissions from the burning of biomass (e.g., from forests and cropland). In the sixth phase of the Climate Model Intercomparison Project Phase 6, the estimated biomass burning emissions were derived using two very different methods. Prior to 1997, emission estimates relied on a combination of indirect measurements and best‐guess fire modeling resulting in emissions having relatively modest temporal and spatial variability. During later periods (i.e., 1997–2014) satellite based estimates of fire occurrence and intensity were used in combination with biogeochemical models to produce emission estimates containing much larger spatial and temporal variability. This study demonstrates that the differing variability in biomass burning has an impact on the model's water cycle. During years of strong burning episodes, clouds thin and more sunlight reaches the surface, which results in more surface evaporation, and higher atmospheric humidity and precipitation. Additionally, the high variation in emissions increases rainfall, decreases snowfall, and increases the intensity of extreme precipitation events. Our results show that the timing of biomass burning emissions, not just the amount emitted, is an important moderator of the atmospheric water cycle. Increased biomass burning emissions variability in Coupled Model Intercomparison Project Phase 6 amplifies hydrologic cycle in Community Earth System Model version 2Column‐integrated precipitable water, evaporation, and precipitation all increase poleward of 40°NSeveral moderating factors act to mitigate hydrologic cycle amplification Increased biomass burning emissions variability in Coupled Model Intercomparison Project Phase 6 amplifies hydrologic cycle in Community Earth System Model version 2 Column‐integrated precipitable water, evaporation, and precipitation all increase poleward of 40°N Several moderating factors act to mitigate hydrologic cycle amplification

The Southern Ocean has absorbed most of the excess heat associated with anthropogenic greenhouse gas emissions. Since Southern Ocean observations are sparse in certain regions and seasons, much of our knowledge of ocean heat uptake is based on climate model simulations. However, climate models still inadequately represent some properties of Southern Ocean clouds, and they have not identified the mechanisms by which clouds may affect Southern Ocean heat uptake (SOHU). Here, we use the ERA5 and JRA‐55 reanalyses to assess the influence of clouds and other atmospheric processes on SOHU from 1979 to 2020. We find that years with the highest SOHU between 45° and 65°S are dominated by ocean heat uptake anomalies during winter and spring, but not during summer or fall. Winter and spring cloud cover are up to 7% higher when SOHU is up to 5.5 W/m2higher than the climatological seasonal mean, with the largest increases in the South Pacific Ocean. Clouds also contain more liquid water. These changes in cloud properties increase downwelling longwave radiation, amplifying ocean heat uptake. Cloud changes are also concomitant with a more stable lower atmosphere, which suppresses turbulent heat fluxes out of the surface. Overall, we find that SOHU is likely not mediated by enhanced surface shortwave absorption over the observational time period. A better understanding of how atmospheric processes impact ocean heat uptake may help improve our understanding of ocean heat uptake mechanisms in the current generation of climate models. Anomalously strong annual mean Southern Ocean heat uptake is mainly controlled by reduced ocean heat loss during winterChanges in clouds and their associated atmospheric states amplify ocean heat uptake by increasing downward longwave radiation at the surfaceMore clouds are linked to a more stable atmosphere which increases ocean heat uptake by suppressing turbulent heat fluxes out of the surface Anomalously strong annual mean Southern Ocean heat uptake is mainly controlled by reduced ocean heat loss during winter Changes in clouds and their associated atmospheric states amplify ocean heat uptake by increasing downward longwave radiation at the surface More clouds are linked to a more stable atmosphere which increases ocean heat uptake by suppressing turbulent heat fluxes out of the surface

Whether sea‐ice loss or lapse‐rate feedback dominates the Arctic amplification (AA) remains an open question. Analysis of data sets based upon observations reveals a 1.11 K per decade surface warming trend in the Arctic (70°–90°N) during 1979–2020 cold season (October–February) that is five times higher than the corresponding global mean. Based on surface energy budget analysis, we show that the largest contribution (∼82%) to this cold season warming trend is attributed to changes in clear‐sky downward longwave radiation. In contrast to that in Arctic summer and over tropics, a reduction in lower‐tropospheric inversions plays a unique role in explaining the reduction of the downward longwave radiation associated with atmospheric nonuniform temperature and corresponding moisture changes. Our analyses also suggest that Arctic lower‐tropospheric stability should be considered in conjunction with sea‐ice decline during the preceding warm season to explain AA. Observations and climate models have consistently shown a stronger surface warming in the Arctic than the global mean, a.k.a. Arctic amplification (AA), which has a strong asymmetry between the cold season and warm season. Previous studies suggested that key contributors to AA are the positive surface‐albedo feedback and lapse‐rate feedback. However, the lapse‐rate feedback itself depends on temperature profiles and sea‐ice loss. Whether sea‐ice loss or lapse‐rate feedback dominates AA remains an open question. Here, by analyzing the latest generation of observationally‐based reanalysis data (1979–2020), we present a unique role of lower‐tropospheric temperature inversion changes in representing the contribution of vertically inhomogeneous atmospheric temperature and associated moisture changes to clear‐sky downward longwave radiation during the cold season. This unique role is not found either in the tropics or during Arctic summertime. We further link the inversion during the cold season to sea‐ice loss during the preceding warm season. These results reinforce previous findings not only that lapse‐rate feedback and sea‐ice loss play a key role in AA but also that lapse‐rate feedback in the cold season is likely a consequence of sea‐ice albedo feedback during the preceding warm season. An increase in clear‐sky downward longwave radiation (rldsclr) explains 82% of the recent cold season Arctic surface warming trendReduced low inversion largely explains the Arctic rldsclr reduction due to vertical nonuniform temperature and related moisture changesLapse‐rate feedback in the Arctic cold season is likely a consequence of sea‐ice albedo feedback during the preceding warm season An increase in clear‐sky downward longwave radiation (rldsclr) explains 82% of the recent cold season Arctic surface warming trend Reduced low inversion largely explains the Arctic rldsclr reduction due to vertical nonuniform temperature and related moisture changes Lapse‐rate feedback in the Arctic cold season is likely a consequence of sea‐ice albedo feedback during the preceding warm season

1.29 young adult male subjects practiced 15 sec. of maximal isometric contractions of the elbow flexors three times a day, 5 days a week, for 5 weeks. They achieved greater increases in strength than have been claimed for a single two-thirds maximal contraction once a day, although the latter has been said to provide the maximal stimulus for the development of strength. There was a negative correlation between initial strength and strength gains.2.The correlation between the girth of the upper arm and elbow flexor strength, or between changes in upper arm girth and changes in elbow flexor strength, was insignificant. A significant number of subjects developed positive changes in upper arm girth, although the magnitude of such changes was not significant.

1.Training of the elbow flexors by maximal isometric exercise produced a significant increase in the strength of their antagonists.2.There was no difference in the amount of strength increase at any of the three measured points in the arc of movement.

Half of a Physical Training Platoon at Officer Candidate School, Quantico, Virginia, were given protein supplements, while the other half received a placebo. Both groups significantly improved their physical performance scores as a result of the training program, but there was no significant difference between them. It was concluded that ingestion of the protein supplement did not contribute to the improvement of physical performance.

Twenty-six adult male subjects were given a placebo, 20 mg. of amphetamine sulfate, or 800 mg. of meprobamate two hours prior to the administration of tests of reaction time and movement time. No statistically significant differences were found between mean scores or variances for the substances tested. It appears that neither drug in dosages commonly employed in connection with the preparation of athletes for competition has any effect on human simple reaction time or simple movement time in response to a visual stimulus.

The purpose of this study was to investigate the relationship between isometric strength scores, the ability to lift weights before and after a weight training programme, and selected anthropometric measurements in untrained men. The subjects significantly increased the amount of weight they could handle in the training exercises, but there was no accompanying increase in the isometric tension they could exert, and correlations between measurements of arm size and strength were not significant. Weight was the most important determinant of arm size and arm strength, but the correlations involved were too low to justify the usual assumption that the bigger the man the stronger.

The reliability and validity of the Bruce Physical Fitness Index as a means of evaluating the physical fitness of athletes and normal healthy non-athletes are evaluated experimentally. The Index does not correlate well with performance in cross-country running, and is less sensitive to changes in cardio-respiratory fitness than is oxygen consumption alone. Large individual variations are found on test-retest of normal subjects. Participants in different sports show differences which are too great to permit of their being grouped together as ' athletes '. Possible reasons for the failure of the Index to be more discriminatory are discussed

The evolution of tropical anvil clouds from their origin in deep convective cores to their slow decay determines the climatic effects of clouds in tropical convective regions. Despite the relevance of anvil clouds for climate and responses of clouds to global warming, processes dominating their evolution are not well understood. Currently available observational data reveal instantaneous snapshots of anvil cloud properties, but cannot provide a process‐based perspective on anvil evolution. We therefore conduct simulations with the high resolution version of the exascale earth system model in which we track mesoscale convective systems over the tropical Western Pacific and compute trajectories that follow air parcels detrained from peaks of convective activity. With this approach we gain new insight into the anvil cloud evolution both in present day and future climate. Comparison with geostationary satellite data shows that the model is able to simulate maritime mesoscale convective systems reasonably well. Trajectory results indicate that anvil cloud lifetime is about 15 h with no significant change in a warmer climate. The anvil ice mixing ratio is larger in a warmer climate due to a larger source of ice by detrainment and larger depositional growth leading to a more negative net cloud radiative effect along detrained trajectories. However, the increases in sources are counteracted by increases in sinks of ice, particularly snow formation and sedimentation. Furthermore, we find that the mean anvil cloud feedback along trajectories is positive and consistent with results from more traditional cloud feedback calculation methods. Clouds can have both cooling and warming effects on climate. Storm clouds in the tropics preferentially cool the climate as they reflect a large fraction of sunlight back to space. Remains of storm clouds, also known as anvil clouds due to their typical shape, reside at very high altitudes and can persist for many hours after the initial intense rain events and extend over vast regions. They keep part of the terrestrial radiation within the atmosphere and therefore warm the climate, similarly to greenhouse gases. The transition from a very reflective storm cloud to a thin anvil cloud is not yet well understood despite playing an important role for tropical climate. We study such transitions with the help of climate model simulations in which we follow anvil clouds from their origin in storm clouds as they develop into thin anvil clouds and eventually disappear. The climate model allows us to study this process both in present‐day as well as a warmer future climate. We find that in a warmer climate the storm clouds contain more ice and reflect more sunlight, which leads to more cooling, while the thin anvil clouds do not change much with warming. E3SM is able to reproduce many features of the observed albedo‐OLR histogram representing anvil cloud decayThree dimensional air parcel trajectories reveal anvil cloud lifetime of 15 h in both present and future warmer climateThick anvil clouds contain more ice and have a larger optical depth in a warmer climate, while thin anvil clouds do not change substantially E3SM is able to reproduce many features of the observed albedo‐OLR histogram representing anvil cloud decay Three dimensional air parcel trajectories reveal anvil cloud lifetime of 15 h in both present and future warmer climate Thick anvil clouds contain more ice and have a larger optical depth in a warmer climate, while thin anvil clouds do not change substantially

We examine radiative feedbacks based on short‐term climate variability by analyzing atmospheric general circulation model (AGCM) simulations, including Atmospheric Model Intercomparison Project within CMIP phase 6 (AMIP6) with known effective radiative forcing (ERF) for 1980–2014 and one with zero ERF for 1980–2017. We first verify the Kernel‐Gregory feedback calculation by showing that both clear‐sky radiative fluxes and all‐sky radiative feedbacks from the kernel method agree with model simulations. We find that global‐mean net feedback for 1980–2017/2014 is −2 W m−2K−1, about twice the feedback estimated for long‐term warming (4 ×CO2) experiments. This difference is mainly caused by a near‐zero global‐mean net cloud feedback for 1980–2017/2014. We show that the lapse rate feedback for 1980–2017/2014 is the largest contributor to the amplified temperature change over the three poles (Arctic, Antarctic, and Tibetan Plateau), followed by surface albedo feedback and Planck feedback deviation from its global mean. Except for a higher surface albedo feedback in Antarctic, other feedbacks are similar between Arctic and Antarctic. The global annual mean temperature at the Earth's surface has risen rapidly in recent decades. Three regions (Arctic, Antarctic, and Tibetan Plateau) of the Earth, called the “three poles”, have warmed more than the global mean, a phenomenon commonly known as polar amplification. The global warming and polar amplification are a consequence of historical external forcings (due to changes in greenhouse gases, aerosols, ozone, solar radiation, volcanic eruptions, and land use) and feedback processes that influence the planet's response. Because of a short measurement record (since 1980) and natural variability, it is difficult to rigorously quantify how individual feedbacks explain polar amplification. Here, we use simulations without external forcing changes but with observed sea surface temperature (SST) changes for 1980–2017 and newly available simulations from many models with prescribed SSTs to verify a “kernel method” to estimate radiative fluxes and feedbacks. We then investigate the global feedback and local feedback over the three poles. We found that models indicate a stronger negative global‐mean net feedback for 1980–2017 than will occur over longer time periods when warming will be stronger. This is primarily due to a near‐zero global mean net cloud feedback estimated for the recent past. The global net feedback for 1980–2017/2014 is estimated to be negative and stronger than that from long‐term warming (e.g., 4×CO2) experimentsThe stronger negative net feedback is primarily due to a near‐zero global‐mean cloud feedback for 1980–2017/2014Lapse rate feedback is the largest contributor to the amplified temperature response seen over the three poles relative to the tropics for 1980–2017/2014

Thirty male medical college students were placed on a program of progressive resistance exercise. Half of the subjects were given a commercial protein dietary supplement, the other half a placebo. At the end of six weeks of training there were no significant differences between the two groups insofar as changes in body weight, arm volume, upper arm girth or strength were concerned.

Thirty male medical college students were placed on a program of progressive resistance exercise. Half of the subjects were given a commercial protein dietary supplement, the other half a placebo. At the end of six weeks of training there were no significant differences between the two groups insofar as changes in body weight, arm volume, upper arm girth or strength were concerned.

We introduce an explicit emission tagging technique in the Community Atmosphere Model to quantify source‐region‐resolved characteristics of black carbon (BC), focusing on the Arctic. Explicit tagging of BC source regions without perturbing the emissions provides a physically consistent and computationally efficient approach to establish source‐receptor relationships and transport pathways. Our analysis shows that the contributions of major source regions to the global BC burden are not proportional to the respective emissions due to strong region‐dependent removal rates and lifetimes, while the contributions to BC direct radiative forcing show a near‐linear dependence on their respective contributions to the burden. Arctic BC concentrations, deposition, and source contributions all have strong seasonal variations. Eastern Asia contributes the most to the wintertime Arctic BC burden, but has much less impact on lower‐level concentrations and deposition. Northern Europe emissions are more important to both surface concentration and deposition in winter than in summer. The largest contribution to Arctic BC in the summer is from Northern Asia. Although local emissions contribute less than 10% to the annual mean BC burden and deposition within the Arctic, the per‐emission efficiency is much higher than for non‐Arctic sources. The interannual variability (1996–2005) due to meteorology is small in annual mean BC burden and radiative forcing but is significant in yearly seasonal means over the Arctic. When a slow aging treatment of BC is introduced, the increase of BC lifetime and burden is source dependent. Global BC forcing‐per‐burden efficiency also increases primarily due to changes in BC vertical distributions. Arctic BC and source contributions have strong seasonal variationsInterannual variability is significant in seasonal means of Arctic BCArctic BC is extremely sensitive to uncertainties in high‐latitude emissions