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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

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.

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