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Abstract Atmospheric heat transport (AHT) is an important piece of our climate system but has primarily been studied at monthly or longer time scales. We introduce a new method for calculating zonal-mean meridional AHT using instantaneous atmospheric fields. When time averaged, our calculations closely reproduce the climatological AHT used elsewhere in the literature to understand AHT and its trends on long time scales. In the extratropics, AHT convergence and atmospheric heating are strongly temporally correlated suggesting that AHT drives the vast majority of zonal-mean atmospheric temperature variability. Our AHT methodology separates AHT into two components (eddies and the mean meridional circulation) which we find are negatively correlated throughout most of the mid- to high latitudes. This negative correlation reduces the variance in the total AHT compared to eddy AHT. Last, we find that the temporal distribution of the total AHT at any given latitude is approximately symmetric. 

Abstract The observed partitioning of poleward heat transport between atmospheric and oceanic heat transports (AHT and OHT) is compared to that in coupled climate models. Model ensemble mean poleward OHT is biased low in both hemispheres, with the largest biases in the Southern Hemisphere extratropics. Poleward AHT is biased high in the Northern Hemisphere, especially in the vicinity of the peak AHT near 40°N. The significant model biases are persistent across three model generations (CMIP3, CMIP5, CMIP6) and are insensitive to the satellite radiation and atmospheric reanalyzes products used to derive observational estimates of AHT and OHT. Model biases in heat transport partitioning are consistent with biases in the spatial structure of energy input to the ocean and atmosphere. Specifically, larger than observed model evaporation in the tropics adds excess energy to the atmosphere that drives enhanced poleward AHT at the expense of weaker OHT. 

Abstract Given the key role that atmospheric heat transport plays in Earth's climate system, efforts to document its changes over the satellite era are valuable. Clark et al. (2022,https://doi.org/10.1029/2022GL098822) calculated trends in atmospheric heat transport among four reanalysis data sets and found substantial disagreements between data sets. However, after accounting for the lack of mass‐conservation in reanalysis data sets, we find much smaller magnitude trends, with much better agreement among reanalyses. This highlights the importance of mass corrections when calculating atmospheric heat transport. 

Abstract Constraining unforced and forced climate variability impacts interpretations of past climate variations and predictions of future warming. However, comparing general circulation models (GCMs) and last millennium Holocene hydroclimate proxies reveals significant mismatches between simulated and reconstructed low-frequency variability at multidecadal and longer time scales. This mismatch suggests that existing simulations underestimate either external or internal drivers of climate variability. In addition, large differences arise across GCMs in both the magnitude and spatial pattern of low-frequency climate variability. Dynamical understanding of forced and unforced variability is expected to contribute to improved interpretations of paleoclimate variability. To that end, we develop a framework for fingerprinting spatiotemporal patterns of temperature variability in forced and unforced simulations. This framework relies on two frequency-dependent metrics: 1) degrees of freedom (≡N) and 2) spatial coherence. First, we useNand spatial coherence to characterize variability across a suite of both preindustrial control (unforced) and last-millennium (forced) GCM simulations. Overall, we find that, at low frequencies and when forcings are added, regional independence in the climate system decreases, reflected in fewerNand higher coherence between local and global mean surface temperature. We then present a simple three-box moist-static-energy-balance model for temperature variability, which is able to emulate key frequency-dependent behavior in the GCMs. This suggests that temperature variability in the GCM ensemble can be understood through Earth’s energy budget and downgradient energy transport, and allows us to identify sources of polar-amplified variability. Finally, we discuss insights the three-box model can provide into model-to-model GCM differences. Significance StatementForced and unforced temperature variability are poorly constrained and understood, particularly that at time scales longer than a decade. Here, we identify key differences in the time scale–dependent behavior of forced and unforced temperature variability using a combination of numerical climate models and principles of downgradient energy transport. This work, and the spatiotemporal characterizations of forced and unforced temperature variability that we generate, will aid in interpretations of proxy-based paleoclimate reconstructions and improve mechanistic understanding of variability. 

Abstract An unprecedented heatwave impacted East Antarctica in March 2022, peaking at 39°C above climatology, the largest temperature anomaly ever recorded globally. We investigate the causes of the heatwave, the impact of climate change, and a climate model's ability in simulating such an event. The heatwave, which was skillfully forecast, resulted from a highly anomalous large‐scale circulation pattern that advected an Australian airmass to East Antarctica in 4 days and produced record atmospheric heat fluxes. Southern Ocean sea surface temperatures anomalies had a minimal impact on the heatwave's amplitude. Simulations from a climate model fail to simulate such a large temperature anomaly mostly due to biases in its large‐scale circulation variability, showcasing a pathway for future model improvement in simulating extreme heatwaves. The heatwave was made 2°C warmer by climate change, and end of 21st century heatwaves may be an additional 5–6°C warmer, raising the prospect of near‐melting temperatures over the interior of East Antarctica. 

Abstract We investigate the linear trends in meridional atmospheric heat transport (AHT) since 1980 in atmospheric reanalysis datasets, coupled climate models, and atmosphere-only climate models forced with historical sea surface temperatures. Trends in AHT are decomposed into contributions from three components of circulation: (i) transient eddies, (ii) stationary eddies, and (iii) the mean meridional circulation. All reanalyses and models agree on the pattern of AHT trends in the Southern Ocean, providing confidence in the trends in this region. There are robust increases in transient-eddy AHT magnitude in the Southern Ocean in the reanalyses, which are well replicated by the atmosphere-only models, while coupled models show smaller magnitude trends. This suggests that the pattern of sea surface temperature trends contributes to the transient-eddy AHT trends in this region. In the tropics, we find large differences between mean-meridional circulation AHT trends in models and the reanalyses, which we connect to discrepancies in tropical precipitation trends. In the Northern Hemisphere, we find less evidence of large-scale trends and more uncertainty, but note several regions with mismatches between models and the reanalyses that have dynamical explanations. Throughout this work we find strong compensation between the different components of AHT, most notably in the Southern Ocean where transient-eddy AHT trends are well compensated by trends in the mean-meridional circulation AHT, resulting in relatively small total AHT trends. This highlights the importance of considering AHT changes holistically, rather than each AHT component individually. 

Abstract Arctic warming under increased CO₂peaks in winter, but is influenced by summer forcing via seasonal ocean heat storage. Yet changes in atmospheric heat transport into the Arctic have mainly been investigated in the annual mean or winter, with limited focus on other seasons. We investigate the full seasonal cycle of poleward heat transport modeled with increased CO₂or with individually applied Arctic sea‐ice loss and global sea‐surface warming. We find that a winter reduction in dry heat transport is driven by Arctic sea‐ice loss and warming, while a summer increase in moist heat transport is driven by sub‐Arctic warming and moistening. Intermodel spread in Arctic warming controls spread in seasonal poleward heat transport. These seasonal changes and their intermodel spread are well‐captured by down‐gradient diffusive heat transport. While changes in moist and dry heat transport compensate in the annual‐mean, their opposite seasonality may support non‐compensating effects on Arctic warming. 

Abstract The influence of climate feedbacks on regional hydrological changes under warming is poorly understood. Here, a moist energy balance model (MEBM) with a Hadley Cell parameterization is used to isolate the influence of climate feedbacks on changes in zonal‐mean precipitation‐minus‐evaporation (P − E) under greenhouse‐gas forcing. It is shown that cloud feedbacks act to narrow bands of tropicalP − Eand increaseP − Ein the deep tropics. The surface‐albedo feedback shifts the location of maximum tropicalP − Eand increasesP − Ein the polar regions. The intermodel spread in theP − Echanges associated with feedbacks arises mainly from cloud feedbacks, with the lapse‐rate and surface‐albedo feedbacks playing important roles in the polar regions. TheP − Echange associated with cloud feedback locking in the MEBM is similar to that of a climate model with inactive cloud feedbacks. This work highlights the unique role that climate feedbacks play in causing deviations from the “wet‐gets‐wetter, dry‐gets‐drier” paradigm. 

Abstract Global warming is expected to cause significant changes in the pattern of precipitation minus evaporation (P−E), which represents the net flux of water from the atmosphere to the surface or, equivalently, the convergence of moisture transport within the atmosphere. In most global climate model simulations, the pattern ofP−Echange resembles an amplification of the historical pattern—a tendency known as “wet gets wetter, dry gets drier.” However, models also predict significant departures from this approximation that are not well understood. Here, we introduce a new method of decomposing the pattern ofP−Echange into contributions from various dynamic and thermodynamic mechanisms and use it to investigate the response ofP−Eto global warming within the CESM1 Large Ensemble. In contrast to previous decompositions ofP−Echange, ours incorporates changes not only in the monthly means of atmospheric winds and moisture, but also in their temporal variability, allowing us to isolate the hydrologic impacts of changes in the mean circulation, transient eddies, relative humidity, and the spatial and temporal distributions of temperature. In general, we find that changes in the mean circulation primarily control theP−Eresponse in the tropics, while temperature changes dominate at higher latitudes. Although the relative importance of specific mechanisms varies by region, at the global scale departures from the wet-gets-wetter approximation over land are primarily due to changes in the temperature lapse rate, while changes in the mean circulation, relative humidity, and horizontal temperature gradients play a secondary role. 

Abstract Total poleward atmospheric heat transport (AHT) is similar in both magnitude and latitudinal structure between the Northern and Southern Hemispheres. These similarities occur despite more major mountain ranges in the Northern Hemisphere, which help create substantial stationary eddy AHT that is largely absent in the Southern Hemisphere. However, this hemispheric difference in stationary eddy AHT is compensated by hemispheric differences in other dynamic components of AHT so that total AHT is similar between hemispheres. To understand how AHT compensation occurs, we add midlatitude mountain ranges in two different general circulation models that are otherwise configured as aquaplanets. Even when midlatitude mountains are introduced, total AHT is nearly invariant. We explore the near invariance of total AHT in response to orography through dynamic, energetic, and diffusive perspectives. Dynamically, orographically induced changes to stationary eddy AHT are compensated by changes in both transient eddy and mean meridional circulation AHT. This creates an AHT system with three interconnected components that resist large changes to total AHT. Energetically, the total AHT can only change if the top-of-the-atmosphere net radiation changes at the equator-to-pole scale. Midlatitude orography does not create large-enough changes in the equator-to-pole temperature gradient to alter outgoing longwave radiation enough to substantially change total AHT. In the zonal mean, changes to absorbed shortwave radiation also often compensate for changes in outgoing longwave radiation. Diffusively, the atmosphere smooths anomalies in temperature and humidity created by the addition of midlatitude orography, such that total AHT is relatively invariant. Significance StatementThe purpose of this study is to better understand how orography influences heat transport in the atmosphere. Enhancing our understanding of how atmospheric heat transport works is important, as heat transport helps moderate Earth’s surface temperatures and influences precipitation patterns. We find that the total amount of atmospheric heat transport does not change in the presence of mountains in the midlatitudes. Different pieces of the heat transport change, but they change in compensatory ways, such that the total heat transport remains roughly constant.