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Population studies show worrisome trends towards earlier breast development, difficulty in breastfeeding, and increasing rates of breast cancer in young women. Multiple epidemiological studies have linked these outcomes with chemical exposures, and experimental studies have shown that many of these chemicals generate similar effects in rodents, often by disrupting hormonal regulation. These endocrine-disrupting chemicals (EDCs) can alter the progression of mammary gland (MG) development, impair the ability to nourish offspring via lactation, increase mammary tissue density, and increase the propensity to develop cancer. However, current toxicological approaches to measuring the effects of chemical exposures on the MG are often inadequate to detect these effects, impairing our ability to identify exposures harmful to the breast and limiting opportunities for prevention. This paper describes key adverse outcomes for the MG, including impaired lactation, altered pubertal development, altered morphology (such as increased mammographic density), and cancer. It also summarizes evidence from humans and rodent models for exposures associated with these effects. We also review current toxicological practices for evaluating MG effects, highlight limitations of current methods, summarize debates related to how effects are interpreted in risk assessment, and make recommendations to strengthen assessment approaches. Increasing the rigor of MG assessment would improve our ability to identify chemicals of concern, regulate those chemicals based on their effects, and prevent exposures and associated adverse health effects.

Do changes in ocean heat transport (OHT) that occur with CO2 forcing, impact climate sensitivity in Earth system models? Changes in OHT with warming are ubiquitous in model experiments: when forced with CO2, such models exhibit declining poleward OHT in both hemispheres at most latitudes, which can persist over multicentennial time scales. To understand how changes in OHT may impact how the climate system responds to CO2 forcing, particularly climate sensitivity, we perform a series of Earth system model experiments in which we systematically perturb OHT (in a slab ocean, relative to its preindustrial control climatology) while simultaneously doubling atmospheric CO2. We find that equilibrium climate sensitivity varies substantially with OHT. Specifically, there is a 0.6 K decrease in global mean surface warming for every 10% decline in poleward OHT. Radiative feedbacks from CO2 doubling, and the warming attributable to each of them, generally become more positive (or less negative) when poleward OHT increases. Water vapor feedback differences account for approximately half the spread in climate sensitivity between experiments, while differences in the lapse rate and surface albedo feedbacks account for the rest. Prescribed changes in OHT instigate opposing changes in atmospheric energy transport and the general circulation, which explain differences in atmospheric water vapor and lapse rate between experiments. Our results show that changes in OHT modify atmospheric radiative feedbacks at all latitudes, thereby driving changes in equilibrium climate sensitivity. More broadly, they demonstrate that radiative feedbacks are not independent of the coupled (atmosphere and ocean) dynamic responses that accompany greenhouse gas forcing.

The processes controlling idealized warming and cooling patterns are examined in 150-yr-long fully coupled Community Earth System Model, version 1 (CESM1), experiments under abrupt CO2 forcing. By simulation end, 2 × CO2 global warming was 20% larger than 0.5 × CO2 global cooling. Not only was the absolute global effective radiative forcing ∼10% larger for 2 × CO2 than for 0.5 × CO2, global feedbacks were also less negative for 2 × CO2 than for 0.5 × CO2. Specifically, more positive shortwave cloud feedbacks led to more 2 × CO2 global warming than 0.5 × CO2 global cooling. Over high-latitude oceans, differences between 2 × CO2 warming and 0.5 × CO2 cooling were amplified by familiar linked positive surface albedo and lapse rate feedbacks associated with sea ice change. At low latitudes, 2 × CO2 warming exceeded 0.5 × CO2 cooling almost everywhere. Tropical Pacific cloud feedbacks amplified the following: 1) more fast warming than fast cooling in the west, and 2) slow pattern differences between 2 × CO2 warming and 0.5 × CO2 cooling in the east. Motivated to quantify cloud influence, a companion suite of experiments was run without cloud radiative feedbacks. Disabling cloud radiative feedbacks reduced the effective radiative forcing and surface temperature responses for both 2 × CO2 and 0.5 × CO2. Notably, 20% more global warming than global cooling occurred regardless of whether cloud feedbacks were enabled or disabled. This surprising consistency resulted from the cloud influence on non-cloud feedbacks and circulation. With the exception of the tropical Pacific, disabling cloud feedbacks did little to change surface temperature response patterns including the large high-latitude responses driven by non-cloud feedbacks. The findings provide new insights into the regional processes controlling the response to greenhouse gas forcing, especially for clouds. Significance Statement We analyze the processing controlling idealized warming and cooling under abrupt CO2 forcing using a modern and highly vetted fully coupled climate model. We were especially interested to compare simulations with and without cloud radiative feedbacks. Notably, 20% more global warming than global cooling occurred regardless of whether cloud feedbacks were enabled or disabled. This surprising consistency resulted from the cloud influence on forcing, non-cloud feedbacks, and circulation. With the exception of the tropical Pacific, disabling cloud feedbacks did little to change surface temperature response patterns including the large high-latitude responses driven by non-cloud feedbacks. The findings provide new insights into the regional processes controlling the response to greenhouse gas forcing, especially for clouds. When combined with estimates of cooling at the Last Glacial Maximum, the findings also help rule out large (4+ K) values of equilibrium climate sensitivity.

During the Arctic night, clouds regulate surface energy budgets through longwave warming alone. During fall, any increase in low-level opaque clouds will increase surface cloud warming and could potentially delay sea ice formation. While more clouds due to fall sea ice loss have been observed, quantifying the surface warming caused by these cloud increases is observationally challenging. Here, we quantify surface cloud warming using spaceborne lidar observations. By instantaneously co-locating surface cloud warming and sea ice observations in regions where sea ice varies, we find October large surface cloud warming values (> 80 W m −2) are much more frequent (~+50%) over open water than over sea ice. Notably, in November large surface cloud warming values (> 80 W m −2) occur more frequently (∼+200%) over open water than over sea ice. These results suggest more surface warming caused by low-level opaque clouds in the future as open water persists later into the fall.

During the Arctic night, clouds regulate surface energy budgets through longwave warming alone. During fall, any increase in low-level opaque clouds will increase surface cloud warming and could potentially delay sea ice formation. While an increase in clouds due to fall sea ice loss has been observed, quantifying the surface warming is observationally challenging. Here, we quantify surface cloud warming using spaceborne lidar observations. By instantaneously co-locating surface cloud warming and sea ice observations in regions where sea ice varies, we find October large surface cloud warming values (> 80 W m-2) are much more frequent (~+50%) over open water than over sea ice. Notably, in November large surface cloud warming values (> 80 W m-2) occur more frequently (~+200%) over open water than over sea ice. These results suggest more surface warming caused by low-level opaque clouds in the future as open water persists later into the fall.

DNA-methylating environmental carcinogens such as N-nitrosodimethylamine (NDMA) and certain alkylators used in chemotherapy form O6-methylguanine (m6G) as a functionally critical intermediate. NDMA is a multi-organ carcinogen found in contaminated water, polluted air, preserved foods, tobacco products, and many pharmaceuticals. Only ten weeks after exposure to NDMA, neonatally-treated mice experienced elevated mutation frequencies in liver, lung and kidney of ∼35-fold, 4-fold and 2-fold, respectively. High-resolution mutational spectra (HRMS) of liver and lung revealed distinctive patterns dominated by GC→AT mutations in 5’-Pu-G-3’ contexts, very similar to human COSMIC mutational signature SBS11. Commonly associated with alkylation damage, SBS11 appears in cancers treated with the DNA alkylator temozolomide (TMZ). When cells derived from the mice were treated with TMZ, N-methyl-N-nitrosourea, and streptozotocin (two other therapeutic methylating agents), all displayed NDMA-like HRMS, indicating mechanistically convergent mutational processes. The role of m6G in shaping the mutational spectrum of NDMA was probed by removing MGMT, the main cellular defense against m6G. MGMT-deficient mice displayed a strikingly enhanced mutant frequency, but identical HRMS, indicating that the mutational properties of these alkylators is likely owed to sequence-specific DNA binding. In sum, the HRMS of m6G-forming agents constitute an early-onset biomarker of exposure to DNA methylating carcinogens and drugs.

The comet assay is a versatile assay for detecting DNA damage in eukaryotic cells. The assay can measure the levels of various types of damage, including DNA strand breaks, abasic sites and alkali-sensitive sites. Furthermore, the assay can also be modified to include purified DNA glycosylases so that alkylated and oxidized bases can be detected. The CometChip is a higher throughput version of the traditional comet assay and has been used to study cultured cells. Here, we have tested its utility for studies of DNA damage present in vivo. We show that the CometChip is effective in detecting DNA damage in multiple tissues of mice exposed to the direct-acting methylating agent methylmethane sulfonate (MMS) and to the metabolically activated methylating agent N-nitrosodimethylamine (NDMA), which has been found to contaminate food, water, and drugs. Specifically, results from MMS-exposed mice demonstrate that DNA damage can be detected in cells from liver, lung, kidney, pancreas, brain and spleen. Results with NDMA show that DNA damage is detectable in metabolically competent tissues (liver, lung, and kidney), and that DNA repair in vivo can be monitored over time. Additionally, it was found that DNA damage persists for many days after exposure. Furthermore, glycosylases were successfully incorporated into the assay to reveal the presence of damaged bases. Overall, this work demonstrates the efficacy of the in vivo CometChip and reveals new insights into the formation and repair of DNA damage caused by MMS and NDMA.

As the atmosphere warms, part of the cloud population shifts from ice and mixed-phase (‘cold’) to liquid (‘warm’) clouds. Because warm clouds are more reflective and longer-lived, this phase change reduces the solar flux absorbed by the Earth and constitutes a negative radiative feedback. This cooling feedback is weaker in the sixth phase of the Coupled Model Intercomparison Project (CMIP6) than in the fifth phase (CMIP5), contributing to greater greenhouse warming. Although this change is often attributed to improvements in the simulated cloud phase, another model bias persists: warm clouds precipitate too readily, potentially leading to underestimated negative lifetime feedbacks. In this study we modified a climate model to better simulate warm-rain probability and found that it exhibits a cloud lifetime feedback nearly three times larger than the default model. This suggests that model errors in cloud-precipitation processes may bias cloud feedbacks by as much as the CMIP5-to-CMIP6 climate sensitivity difference. Reliable climate model projections therefore require improved cloud process realism guided by process-oriented observations and observational constraints. CMIP6 models simulate higher and more accurate cloud liquid water fraction relative to CMIP5, but both ensembles overestimate warm cloud precipitation. Correcting these warm cloud processes in a model exposes compensating biases large enough to offset CMIP5–CMIP6 climate sensitivity differences.

Excessive precipitation over the southeastern tropical Pacific is a major common bias that persists through generations of global climate models. While recent studies suggest an overly warm Southern Ocean as the cause, models disagree on the quantitative importance of this remote mechanism in light of ocean circulation feedback. Here, using a multimodel experiment in which the Southern Ocean is radiatively cooled, we show a teleconnection from the Southern Ocean to the tropical Pacific that is mediated by a shortwave subtropical cloud feedback. Cooling the Southern Ocean preferentially cools the southeastern tropical Pacific, thereby shifting the eastern tropical Pacific rainbelt northward with the reduced precipitation bias. Regional cloud locking experiments confirm that the teleconnection efficiency depends on subtropical stratocumulus cloud feedback. This subtropical cloud feedback is too weak in most climate models, suggesting that teleconnections from the Southern Ocean to the tropical Pacific are stronger than widely thought.

The surface radiative imbalance has large impacts on the long-term trends and year-to-year variability of Arctic sea ice. Clouds are believed to be a key factor in regulating this radiative imbalance, whose underlying processes and mechanisms, however, are not well understood. Compared with observations, the Community Earth System Model version 1 (CESM1) is known to underestimate Arctic cloud liquid water. Here, the following hypothesis is proposed and tested: this underestimation is caused by an overactive Wegener–Bergeron–Findeisen (WBF) process in model as too many supercooled liquid droplets are scavenged by ice crystals via deposition. In this study, the efficiency of the WBF process in CESM1 was reduced to investigate the Arctic climate response, and differentiate the responses induced by atmosphere–ocean–sea ice coupling and global warming. By weakening the WBF process, CESM1 simulated liquid cloud fractions increased, especially in winter and spring. The cloud response resulted in increased downwelling longwave flux and decreased shortwave flux at the surface. Arctic clouds and radiation in simulations with reduced WBF efficiency show a better agreement with satellite retrievals. In addition, both coupling and global warming amplify the cloud response to a less efficient WBF process, due to increased relative humidity and enhanced evaporation, respectively. As a response, the sea ice tends to melt over the North Atlantic Ocean, most likely caused by a positive feedback process between clouds, radiation and sea ice during non-summer months. These results improve our understanding of large-scale effects of the WBF process and the role of cloud liquid water in the Arctic climate system.

Inflammation is a major risk factor for many types of cancer, including colorectal (CRC). There are two fundamentally different mechanisms by which inflammation can contribute to carcinogenesis. First, reactive oxygen and nitrogen species (RONS) can damage DNA to cause mutations that initiate cancer. Second, inflammatory cytokines and chemokines promote proliferation, migration, and invasion. Although it is known that inflammation-associated RONS can be mutagenic, the extent to which they induce mutations in intestinal stem cells (ISCs) has been little explored. Furthermore, it is now widely accepted that cancer is caused by successive rounds of clonal expansion with associated de novo mutations that further promote tumor development. As such, we aimed to understand the extent to which inflammation promotes clonal expansion in normal and tumor tissue. Using an engineered mouse model that is prone to cancer and within which mutant cells fluoresce, here we have explored the impact of inflammation on de novo mutagenesis and clonal expansion in normal and tumor tissue. While inflammation is strongly associated with susceptibility to cancer and a concomitant increase in the overall proportion of mutant cells in the tissue, we did not observe an increase in mutations in normal adjacent tissue. These results are consistent with opportunities for de novo mutations and clonal expansion during tumor growth, and they suggest protective mechanisms that suppress the risk of inflammation-induced accumulation of mutant cells in normal tissue.

Polar bears (Ursus maritimus) require sea ice for capturing seals and are expected to decline range-wide as global warming and sea-ice loss continue1,2. Estimating when different subpopulations will likely begin to decline has not been possible to date because data linking ice availability to demographic performance are unavailable for most subpopulations2 and unobtainable a priori for the projected but yet-to-be-observed low ice extremes3. Here, we establish the likely nature, timing and order of future demographic impacts by estimating the threshold numbers of days that polar bears can fast before cub recruitment and/or adult survival are impacted and decline rapidly. Intersecting these fasting impact thresholds with projected numbers of ice-free days, estimated from a large ensemble of an Earth system model4, reveals when demographic impacts will likely occur in different subpopulations across the Arctic. Our model captures demographic trends observed during 1979–2016, showing that recruitment and survival impact thresholds may already have been exceeded in some subpopulations. It also suggests that, with high greenhouse gas emissions, steeply declining reproduction and survival will jeopardize the persistence of all but a few high-Arctic subpopulations by 2100. Moderate emissions mitigation prolongs persistence but is unlikely to prevent some subpopulation extirpations within this century. Polar bear numbers are expected to decline as the sea ice they rely on to catch their prey declines with global warming. Projections show when fasts caused by declining sea ice are likely to lead to rapid recruitment and survival declines across the polar bear circumpolar range.

Increasing precipitation on the Antarctic Ice Sheet (AIS) in a warming climate has the potential to partially mitigate Antarctica’s contribution to sea level rise. We show that a simple, physically motivated change to the shallow convective cloud phase in the Community Earth System Model (CESM)—improving a long-standing bias in shortwave cloud forcing over the Southern Ocean—leads to an enhanced response of precipitation when the model is forced with realistic stratospheric ozone depletion, with other radiative forcing remaining constant. We analyze two ozone-forced ensemble experiments with the CESM version 1.1: one using the standard version of the model and the other using the cloud-modified version. The standard version exhibits a precipitation increase on the AIS of 34 gigatons year−1; the cloud-modified version shows an increase of 109 Gt year−1. The cloud-modified version shows a more robust, year-round poleward shift in the westerly jet and storm tracks, which brings more precipitation to the AIS, compared to the standard version. Greater surface warming and larger-amplitude stationary waves further increase the Antarctic precipitation response. The enhanced warming in the cloud-modified version is explained by larger positive shortwave cloud feedbacks, while the enhanced poleward jet shift is associated with a stronger meridional temperature gradient in the upper troposphere—lower stratosphere. These results illustrate (1) the sensitivity of forced changes in Antarctic precipitation to the mean state of a climate model and (2) the strong role of atmospheric dynamics in driving that forced precipitation response.

In recent decades, Arctic sea ice has shifted toward a younger, thinner, seasonal ice regime. Studying and understanding this “new” Arctic will be the focus of a year-long ship campaign beginning in autumn 2019. Lagrangian tracking of sea ice floes in the Community Earth System Model Large Ensemble (CESM-LE) during representative “perennial” and “seasonal” time periods allows for understanding of the conditions that a floe could experience throughout the calendar year. These model tracks, put into context a single year of observations, provide guidance on how observations can optimally shape model development, and how climate models could be used in future campaign planning. The modeled floe tracks show a range of possible trajectories, though a Transpolar Drift trajectory is most likely. There is also a small but emerging possibility of high-risk tracks, including possible melt of the floe before the end of a calendar year. We find that a Lagrangian approach is essential in order to correctly compare the seasonal cycle of sea ice conditions between point-based observations and a model. Because of high variability in the melt season sea ice conditions, we recommend in situ sampling over a large range of ice conditions for a more complete understanding of how ice type and surface conditions affect the observed processes. We find that sea ice predictability emerges rapidly during the autumn freeze-up and anticipate that process-based observations during this period may help elucidate the processes leading to this change in predictability.

Work from numerous fields of study suggests that exposures to hormonally active chemicals during sensitive windows of development can alter mammary gland development, function, and disease risk. Stronger links between many environmental pollutants and disruptions to breast health continue to be documented in human populations, and there remain concerns that the methods utilized to identify, characterize, and prioritize these chemicals for risk assessment and risk management purposes are insufficient. There are also concerns that effects on the mammary gland have been largely ignored by regulatory agencies. Here, we provide technical guidance that is intended to enhance collection and evaluation of the mammary gland in mice and rats. We review several features of studies that should be controlled to properly evaluate the mammary gland, and then describe methods to appropriately collect the mammary gland from rodents. Furthermore, we discuss methods for preparing whole mounted mammary glands and numerous approaches that are available for the analysis of these samples. Finally, we conclude with several examples where analysis of the mammary gland revealed effects of environmental toxicants at low doses. Our work argues that the rodent mammary gland should be considered in chemical safety, hazard and risk assessments. It also suggests that improved measures of mammary gland outcomes, such as those we present in this review, should be included in the standardized methods evaluated by regulatory agencies such as the test guidelines used for identifying reproductive and developmental toxicants.

Homology directed repair is a critical process for maintaining the genome of mammalian cells. While considered to be relatively error free, homologous recombination (HR) can lead to insertions, deletions, translocations, and loss of heterozygosity. Furthermore, it is known that conditions that cause HR events are often carcinogenic, and that HR modulates susceptibility to cancer chemotherapeutics, making HR relevant to both cancer etiology and treatment. To learn about HR in vivo, several laboratories have developed mouse models that harbor direct repeat substrates for which HR yields a phenotype that can be visualized by either a change in pigmentation or by expression of a fluorescent protein. An exciting aspect of this work is that it is possible to detect recombinant cells within intact tissues and thus learn about how physiological changes, genes, and exposures modulate HR susceptibility in vivo, as well as which cell types are most susceptible to HR, and the extent to which recombinant cells have undergone clonal expansion. Here, we review progress in studying HR in vivo for four different mouse strains that harbor direct repeat substrates for HR detection, namely the p(un) mice, the fluorescent yellow direct repeat (FYDR) mice, the EGFP-DR mice, and the ROSA26 direct repeat (RaDR) mice. Key advances in our understanding of fundamental processes that modulate HR susceptibility in vivo are the focus of this review.

Teaching climate change is complex because it requires a system-level understanding of many science disciplines and also because students may have preconceptions about climate change. Previous work shows students learn and retain science content better when they are engaged in the learning process. Active learning strategies engage students in learning science, but the engagement impact of active learning has not yet been assessed in a controlled environment using both biometric and self-reporting tools. Here, we analyze 52 university students’ engagement during several common active learning strategies in a controlled research setting. We collected biometric data from all participants with hand sensors that measured changes in skin conductance as a proxy for engagement. Participants self-reported their engagement as a control. The combined biometric and self-reported data show that skin conductance data matched self-reported engagement, confirming that skin conductance is a robust proxy for engagement. Overall, dialog was the most engaging activity, with engagement levels about 165% above baseline. Non-science majors had higher average engagement than science majors (137% vs. 53% above baseline, respectively). Notably, skin conductance data showed no statistically significant differences based on participants’ political or religious affiliations. In summary, our results demonstrate biometric sensors’ potential to measure and monitor engagement in a learning environment. Relevant for climate education, in-class dialog increases student engagement in learning climate science and is especially effective for non-science majors.

In this study, we investigate whether the Pacific decadal oscillation (PDO) can enhance or diminish El Niño Southern Oscillation (ENSO) temperature and precipitation teleconnections over North America using five single model initial-condition large ensembles (SMILEs). The use of SMILEs facilitates a statistically robust comparison of ENSO events that occur during different phases of the PDO. We find that a positive PDO enhances winter and spring El Niño temperature and precipitation teleconnections and diminishes La Niña teleconnections. A negative PDO has the opposite effect. The modulation of ENSO by the PDO is mediated by differences in the location and strength of the Aleutian Low and Pacific Jet during ENSO events under different phases of the PDO. This modulation is a simple combination of the individual effects of the PDO and ENSO over North America. Finally, we show that ENSO and the PDO can be used to evaluate the likelihood of the occurrence of temperature and precipitation anomalies in different regions, but cannot be used as a deterministic predictor of these anomalies due to the large variability between individual events.

The Community Earth System Model version 2 (CESM2) simulates a high equilibrium climate sensitivity (ECS > 5 degC) and a Last Glacial Maximum (LGM) that is substantially colder than proxy temperatu...

This study isolates the influence of sea ice mean state on pre-industrial climate and transient 1850-2100 climate change within a fully coupled global model: The Community Earth System Model versio...

Why would hundreds of scientists from around the world freeze a ship in Arctic sea ice for an entire year, braving subzero temperatures and months of polar darkness? This may sound like a fictional...

DNA damage can be cytotoxic and mutagenic and is directly linked to aging, cancer, and heritable diseases. To counteract the deleterious effects of DNA damage, cells have evolved highly conserved DNA repair pathways. Many commonly used DNA repair assays are relatively low throughput and are limited to analysis of one protein or one pathway. Here, we have explored the capacity of the CometChip platform for parallel analysis of multiple DNA repair activities. Taking advantage of the versatility of the traditional comet assay and leveraging micropatterning techniques, the CometChip platform offers increased throughput and sensitivity compared to the traditional comet assay. By exposing cells to DNA damaging agents that create substrates of Base Excision Repair, Nucleotide Excision Repair, and Non-Homologous End Joining, we show that the CometChip is an effective method for assessing repair deficiencies in all three pathways. With these advanced applications of the CometChip platform, we expand the efficacy of the comet assay for precise, high-throughput, parallel analysis of multiple DNA repair activities.

SummaryN-nitrosodimethylamine (NDMA) is a DNA methylating agent that has been discovered to contaminate water, food and drugs. The alkyladenine glycosylase (AAG) removes methylated bases to initiate the base excision repair (BER) pathway. To understand how gene-environment interactions impact disease susceptibility, we studied Aag−/− and Aag-overexpressing mice that harbor increased levels of either replication-blocking lesions (3-methyladenine, or 3MeA) or strand breaks (BER intermediates), respectively. Remarkably, the disease outcome switched from cancer to lethality simply by changing AAG levels. To understand the underlying basis for this observation, we integrated a suite of molecular, cellular and physiological analyses. We found that unrepaired 3MeA is somewhat toxic but highly mutagenic (promoting cancer), whereas excess strand breaks are poorly mutagenic and highly toxic (suppressing cancer and promoting lethality). We demonstrate that the levels of a single DNA repair protein tips the balance between blocks and breaks, and thus dictates the disease consequences of DNA damage.

Many modeling studies have shown that the Atlantic meridional overturning circulation (AMOC) will weaken under increased greenhouse gas forcing, but the influence of AMOC internal variability on climate change in the context of a large initial condition ensemble has received less attention. Here, the Community Earth System Model Large Ensemble (CESM LE) is used to separate the AMOC-forced response from AMOC internal variability, and then assess their joint influence on surface warming. Similar to other models, the CESM LE projects a weakening AMOC in response to increased greenhouse gas forcing caused by freshening and decreased buoyancy fluxes in the North Atlantic. Yet if this forced response is removed using the ensemble mean, there is a positive relationship between global surface warming and AMOC strength. In other words, when the AMOC strengthens relative to the ensemble mean (i.e., weakens less), global surface warming increases relative to the ensemble mean response. This unforced surface warming occurs in northern Eurasia and in the Nordic and Barents Seas near the sea ice edge. Comparison of CESM simulations with and without a dynamic ocean shows that the unforced surface warming in the Nordic and Barents Seas results from both ocean and atmospheric circulation variability. In contrast, this comparison suggests that AMOC-associated Eurasian warming results from atmospheric circulation variability alone. In sum, the AMOC-forced response and AMOC internal variability have distinct relationships with surface temperature. Forced AMOC weakening decreases with surface warming, while unforced AMOC strengthening leads to surface warming.

Using lidar and radiative flux observations from space and ground, and a lidar simulator, we evaluate clouds simulated by climate models over the Greenland ice sheet, including predicted cloud cover, cloud fraction profile, cloud opacity, and surface cloud radiative effects. The representation of clouds over Greenland is a central concern for the models because clouds impact ice sheet surface melt. We find that over Greenland, most of the models have insufficient cloud cover during summer. In addition, all models create too few nonopaque, liquid-containing clouds optically thin enough to let direct solar radiation reach the surface (−1% to −3.5% at the ground level). Some models create too few opaque clouds. In most climate models, the cloud properties biases identified over all Greenland also apply at Summit, Greenland, proving the value of the ground observatory in model evaluation. At Summit, climate models underestimate cloud radiative effect (CRE) at the surface, especially in summer. The primary driver of the summer CRE biases compared to observations is the underestimation of the cloud cover in summer (−46% to −21%), which leads to an underestimated longwave radiative warming effect (CRELW= −35.7 to −13.6 W m−2compared to the ground observations) and an underestimated shortwave cooling effect (CRESW= +1.5 to +10.5 W m−2compared to the ground observations). Overall, the simulated clouds do not radiatively warm the surface as much as observed.

Climate variability and its response to increasing greenhouse gases are important considerations for impacts and adaptation. Modeling studies commonly assess projected changes in variability in terms of changes in the variance of climate variables. Despite the distant and impactful covariations that climate variables can exhibit, the covariance response has received much less attention. Here, a novel ensemble framework is developed that facilitates a unified assessment of the response of the regional variances and covariances of a climate variable to imposed external forcings and their time of emergence from an unforced climate state. Illustrating the framework, the response of variability and covariability of land and ocean temperatures is assessed in the Community Earth System Model Large Ensemble under historical and RCP8.5 forcing. The results reveal that land temperature variance emerges from its preindustrial state in the 1950s and, by the end of the twenty-first century, grows to 1.5 times its preindustrial level. Demonstrating the importance of covariances for variability projections, the covariance between land and ocean temperature is considerably enhanced by 2100, reaching 1.4 times its preindustrial estimate. The framework is also applied to assess changes in monthly temperature variability associated with the Arctic region and the Northern Hemisphere midlatitudes. Consistent with previous studies and coinciding with sea ice loss, Arctic temperature variance decreases in most months, emerging from its preindustrial state in the late twentieth century. Overall, these results demonstrate the utility of the framework in enabling a comprehensive assessment of variability and its response to external climate forcings.