Community Earth System Model Large Ensemble Research Articles

A New Framework for Identifying and Investigating Seasonal Climate Extremes

AbstractPrevious studies have recognized the societal relevance of climatic extremes on the seasonal time scale and examined physical processes leading to individual high-impact extreme seasons (e.g., extremely wet or warm seasons). However, these findings have not yet been generalized beyond case studies since at any specific location only very few seasonal events of such rarity occurred in the observational record. In this concept paper, a pragmatic approach to pool seasonal extremes across space is developed and applied to investigate hot summers and cold winters in ERA-Interim and the Community Earth System Model Large Ensemble (CESM-LENS). We identify spatial extreme season objects as contiguous regions of extreme seasonal mean temperatures based on statistical modeling. Regional pooling of extreme season objects in CESM-LENS then yields considerable samples of analogs to even the most extreme ERA-Interim events. This approach offers numerous opportunities for systematically analyzing large samples of extreme seasons, and several such analyses are illustrated. We reveal a striking co-occurrence of El Niño to La Niña transitions and the largest ERA-Interim midlatitude extreme summer events. Moreover, we perform a climate model evaluation with regard to extreme season size and intensity measures and estimate how often an extreme winter like the cold North American 2013/14 winter is expected anywhere in midlatitude regions. Furthermore, we present a large set of simulated analogs to this event, which makes it possible to study commonalities and differences of their underlying physical processes. Finally, substantial but spatially varying climatological differences in the size of extreme summer and extreme winter objects are identified.

Identifying the evolving human imprint on heat wave trends over the United States and Mexico

Changes in frequency, duration and intensity of three heat wave (HW) types (compound, daytime, and nighttime) over the United States (U.S.) and Mexico during the second half of the 20th-century are investigated using the Community Earth System Model Large Ensemble (CESM-LE). The individual role of anthropogenic aerosols and greenhouse gases (GHGs), as well as the contribution from internal variability (IV), are identified and contrasted by means of the CESM-LE single forcing experiments during two periods: 1950–1975, when North American aerosol emissions peaked, and 1980–2005, when aerosol emissions declined. HW changes are strongly affected by anthropogenic forcing. During 1950–1975, aerosols, via both aerosol-radiation and aerosol-cloud interactions, dominate the decreasing trends in compound HWs over the central U.S., the daytime HWs in large parts of the domain and the nighttime HWs over Mexico. Conversely, all three HW types are considerably more frequent (2 HWs summer−1 decade−1), longer-lasting (with increases of up to 2 days HW−1 decade−1 in some regions) and more intense (e.g., C HW−1 decade−1 in compound HWs) across large regions of the domain during the 1980–2005 period. The results show that the decline in aerosol emissions and the continuous rise in GHGs lead to widespread warming and subsequent circulation adjustments, contributing to the positive HW trends. The contribution of IV is large during 1950–1975 (over 60% in most areas), and considerably reduced later on. This study provides a comprehensive picture of the role of anthropogenic forcing and IV on the marked HW changes in the recent decades and their underpinning physical mechanisms.

Detecting Climate Signals in Southern Ocean Krill Growth Habitat

Climate change is rapidly altering the habitat of Antarctic krill (Euphausia superba), a key species of the Southern Ocean food web. Krill are a critical element of Southern Ocean ecosystems as well as biogeochemical cycles, while also supporting an international commercial fishery. In addition to trends forced by global-scale, human-driven warming, the Southern Ocean is highly dynamic, displaying large fluctuations in surface climate on interannual to decadal timescales. The dual roles of forced climate change and natural variability affecting Antarctic krill habitat, and therefore productivity, complicate interplay of observed trends and contribute to uncertainty in future projections. We use the Community Earth System Model Large Ensemble (CESM-LE) coupled with an empirically derived model of krill growth to detect and attribute trends associated with “forced,” human-driven climate change, distinguishing these from variability arising naturally. The forced trend in krill growth is characterized by a poleward contraction of optimal conditions and an overall reduction in Southern Ocean krill habitat. However, the amplitude of natural climate variability is relatively large, such that the forced trend cannot be formally distinguished from natural variability at local scales over much of the Southern Ocean by 2100. Our results illustrate how natural variability is an important driver of regional krill growth trends and can mask the forced trend until late in the 21st century. Given the ecological and commercial global importance of krill, this research helps inform current and future Southern Ocean krill management in the context of climate variability and change.

The source of uncertainty in projecting the anomalous western North Pacific anticyclone during El Niño–decaying summers

AbstractThe western North Pacific anomalous anticyclone (WNPAC) is a key bridge that links El Niño and East Asian climate variability. Future projections of ENSO-related WNPAC changes under global warming are highly uncertain across climate models. Based on a 40-member ensemble from the Community Earth System Model Large Ensemble (CESM-LE) project, we investigate the effects of internal variability on the El Niño-related WNPAC projection. Here, we first develop a decomposition method to separate the contributions of El Niño amplitude change and non-amplitude change from the leading uncertainty in the El Niño-related WNPAC projection. Based on the decomposition, approximately 23% of the uncertainty in the El Niño-related WNPAC projection is attributed to the El Niño amplitude change, while the remaining 77% is from the non-amplitude change, which is mainly related to the change in the El Niño decaying pace. A larger (smaller) El Niño amplitude can enhance (weaken) the WNPAC through a stronger (weaker) tropical Indian Ocean (TIO) capacitor effect. For non-amplitude change, a faster (slower) El Niño decaying pace can also enhance (weaken) the WNPAC through descending Rossby waves in response to cold sea surface temperature anomalies (SSTA) over the tropical central-eastern Pacific. The decomposition method can be generalized to investigate the sources of uncertainty related to El Niño properties in climate projections and to help improve the understanding of changes in the interannual variability of East Asian-western Pacific climate under global warming.

The Shallowing Surface Temperature Inversions in the Arctic

AbstractTemperature inversions play an important role in various physical processes by affecting the atmospheric stability, regulating the development of clouds and fog, and controlling the transport of heat and moisture fluxes. In the past few decades, previous studies have analyzed the spatiotemporal variability of Arctic inversions, but few studies have investigated changes in temperature inversions. In this study, the changes in the depth of Arctic inversions in the mid-twenty-first century are projected based on a 30-member ensemble from the Community Earth System Model Large Ensemble (CESM-LE) project. The ERA-Interim, JRA-55, and NCEP–NCAR reanalysis were employed to verify the model results. The CESM-LE can adequately reproduce the spatial distribution and trends of present-day inversion depth in the Arctic, and the simulation is better in winter. The mean inversion depth in the CESM-LE is slightly underestimated, and the discrepancy is less than 11 hPa, within a reasonable range. The model results show that during the mid-twenty-first century, the inversion depth will strongly decrease in autumn and slightly decrease in winter. The shallowing of the inversion is most obvious over the Arctic Ocean, and the maximum decrease is over 65 hPa in the Pacific sector in autumn. In contrast, the largest decrease in the inversion depth, which is more than 45 hPa, occurs over the Barents Sea in winter. Moreover, the area where the inversion shallows is consistent with the area where the sea ice is retreating, indicating that the inversion depth over the Arctic Ocean in autumn and winter is likely regulated by the sea ice extent through modulating surface heat fluxes.

A Global Flood Risk Modeling Framework Built With Climate Models and Machine Learning

AbstractLarge scale flood risk analyses are fundamental to many applications requiring national or international overviews of flood risk. While large‐scale climate patterns such as teleconnections and climate change become important at this scale, it remains a challenge to represent the local hydrological cycle over various watersheds in a manner that is physically consistent with climate. As a result, global models tend to suffer from a lack of available scenarios and flexibility that are key for planners, relief organizations, regulators, and the financial services industry to analyze the socioeconomic, demographic, and climatic factors affecting exposure. Here we introduce a data‐driven, global, fast, flexible, and climate‐consistent flood risk modeling framework for applications that do not necessarily require high‐resolution flood mapping. We use statistical and machine learning methods to examine the relationship between historical flood occurrence and impact from the Dartmouth Flood Observatory (1985–2017), and climatic, watershed, and socioeconomic factors for 4,734 HydroSHEDS watersheds globally. Using bias‐corrected output from the NCAR CESM Large Ensemble (1980–2020), and the fitted statistical relationships, we simulate 1 million years of events worldwide along with the population displaced in each event. We discuss potential applications of the model and present global flood hazard and risk maps. The main value of this global flood model lies in its ability to quickly simulate realistic flood events at a resolution that is useful for large‐scale socioeconomic and financial planning, yet we expect it to be useful to climate and natural hazard scientists who are interested in socioeconomic impacts of climate.

Was the 2015 North Atlantic subpolar cold anomaly predictable?

AbstractThe subpolar North Atlantic (SPNA) experienced extreme cold during 2015, an event often called the “cold blob”. The evolution of this event in the Community Earth System Model version 1 Decadal Prediction Large Ensemble (CESM1-DPLE) hindcast initialized in November 2014 is compared to observations. This CESM1-DPLE hindcast failed to predict cold conditions during 2015 despite already cold SPNA initial conditions and despite having high sea surface temperature skill in the SPNA in all other years. The goal of this paper is to understand what led to this prediction failure in order to provide insight for future decadal prediction efforts. Our analysis shows that strongly positive North Atlantic Oscillation (NAO) conditions during winter and spring 2015 likely sustained the cold blob but were not simulated in any CESM1-DPLE members. We examine the rarity of the 2015 event using the CESM1-DPLE’s uninitialized counterpart, the CESM1 Large Ensemble (CESM1-LE). Results from the CESM1-LE indicate that the exceptional state of the observed NAO in the winter of 2015 is at least part of the explanation for why this event was not encompassed in the CESM1-DPLE spread. To test another possibility — that deficiencies in the initial conditions degraded the prediction — we performed additional hindcasts using the CESM1-DPLE protocol but different initial conditions. Altering the initial conditions did not improve the simulation of the 2015 cold blob, and in some cases, degraded it. Given the difficulty of predicting this event, this case could be a useful testbed for future prediction system development.

Decadal phase shift of summertime Arctic dipole pattern and its nonlinear effect on sea ice extent

AbstractThe rapid decline in Arctic sea ice during recent decades has been attributed to the combined influence of global warming and internal climate variability. Herein, we elucidate the process by which the decrease in sea ice is accelerated in association with the decadal phase shift of the Arctic dipole (AD), using observational data and Community Earth System Model (CESM1) simulations. The influence of the AD on Arctic sea ice varied according to its phase; in the negative‐AD decades (1979–1998), atmospheric circulation during summers of positive phase AD acts to reduce the sea ice extent (SIE) in the Pacific sector but increases it in the Atlantic sector. In contrast, in the positive‐AD decades (after 1999), the same atmospheric circulation pattern reduces the SIE in both sectors, resulting in enhanced sea ice melting across the entire Arctic region. A similar nonlinear relationship between the AD phase and SIE change is also observed in CESM1 Pre‐Industrial simulations, which stem from altered background temperature conditions between periods, implying the significant role of internal variability, particularly over the Atlantic sector. However, contrary to the recently observed AD trend, CESM1 Large Ensemble experiments predicted a negative AD trend as global warming proceeded. This suggests that the recent positive AD phase may be naturally driven, but the current state of sea ice decline associated with AD could be altered in the near future because of enhanced global warming.

Impacts of Low-Frequency Internal Climate Variability and Greenhouse Warming on El Niño–Southern Oscillation

AbstractEl Niño–Southern Oscillation (ENSO) is the dominant mode of interannual climate fluctuations with wide-ranging socioeconomic and environmental impacts. Understanding the eastern Pacific (EP) and central Pacific (CP) El Niño response to a warmer climate is paramount, yet the role of internal climate variability in modulating their response is not clear. Using large ensembles, we find that internal variability generates a spread in the standard deviation and skewness of these two El Niño types that is similar to the spread of 17 models from phase 5 of the Coupled Model Intercomparison Project (CMIP5) that realistically simulate ENSO diversity. Based on 40 Community Earth System Model Large Ensemble (CESM-LE) and 99 Max Planck Institute for Meteorology Grand Ensemble (MPI-GE) members, unforced variability can explain more than 90% of the historical EP and CP El Niño standard deviation and all of the ENSO skewness spread in the 17 CMIP5 models. Both CESM-LE and the selected CMIP5 models show increased EP and CP El Niño variability in a warmer climate, driven by a stronger mean vertical temperature gradient in the upper ocean and faster surface warming of the eastern equatorial Pacific. However, MPI-GE shows no agreement in EP or CP standard deviation change. This is due to weaker sensitivity to the warming signal, such that when the eastern equatorial Pacific surface warming is faster, the change in upper ocean vertical temperature gradient tends to be weaker. This highlights that individual models produce a different ENSO response in a warmer climate, and that considerable uncertainty within the CMIP5 ensemble may be caused by internal climate variability.

Assessment of decadal variability in sea ice in the Community Earth System Model against a long-term regional observational record: implications for the predictability of an ice-free Arctic

AbstractUncertainties in the timing of a seasonal ice cover in the Arctic Ocean depend on model physics and parameterizations, natural variability at decadal timescales and uncertainties in climate scenarios and forcings. We use the Gridded Monthly Sea-Ice Extent and Concentration, 1850 Onward product to assess the simulated decadal variability from the Community Earth System Model – Large Ensemble (CESM-LE) in the Pacific, Eurasian and Atlantic sector of the Arctic where a longer observational record exists. Results show that sea-ice decadal (8-16 years) variability in CESM-LE is in agreement with the observational record in the Pacific sector of the Arctic, underestimated in the Eurasian sector of the Arctic, specifically in the East-Siberian Sea, and slightly overestimated in the Atlantic sector of the Arctic, specifically in the Greenland Sea. Results also show an increase in variability at decadal timescales in the Eurasian and Pacific sectors during the transition to a seasonally ice-free Arctic, in agreement with the observational record although this increase is delayed by 10-20 years. If the current sea-ice retreat in the Arctic continues to be Pacific-centric, results from the CESM-LE suggest that uncertainty in the timing of an ice-free Arctic associated with natural variability is realistic, but that a seasonal ice cover may occur earlier than projected.

Poleward shift and intensified variability of Kuroshio-Oyashio extension and North Pacific Transition Zone under climate change

The climate variability of the Kuroshio-Oyashio Extension (KOE) and North Pacific Transition Zone (NPTZ) exerts a strong control on marine populations that are sensitive to the strong productivity gradients between the subtropical and subpolar recirculation gyres. In observations, the relationship between KOE, NPTZ and productivity is evident in the first two dominant covariability modes between sea surface height and Chlorophyll-a anomalies, which are associated with a meridional shift in the location of the KOE (e.g. shift mode 1) and an intensification of the mean circulation of the KOE (e.g. intensification mode 2). To understand the projected impacts of anthropogenic forcing on the NPTZ, we examine these two dominant modes of variability in the Community Earth System Model Large Ensemble (CESM-LE) and an ensemble of climate models from the Coupled Model Intercomparing Project (CMIP5-E) under the Representative Concentration Pathways (RCP8.5). A significant poleward shift has been found in the KOE mean location associated with an equivalent shift of the Aleutian Low atmospheric pressure system. Superimposed to the changes of the mean, we find a significant increase (15–20%) in the variability of the shift mode in both the CESM-LE and CMPI5-E suggesting that variation in the meridional position of the NPTZ are also becoming stronger. These changes in variance of the shift mode are linked to an increase variability of the atmospheric forcing.

On the occurrence of the worst drought in South Asia in the observed and future climate

Droughts in South Asia pose substantial challenges to water resources, agricultural, and socio-economic growth of more than two billion people. However, the most detrimental soil moisture droughts, their impacts, and occurrence in the observed and projected climate in South Asia remain unidentified. We conducted soil moisture simulations using the variable infiltration capacity model and meteorological forcing based on the four global observational products (Climate Research Unit, WATCH-Forcing-Data-ERA-Interim, University of Delaware, and Princeton) to identify the worst soil moisture drought during 1951–2016. The worst soil moisture drought during the observed record occurred in 2002 and affected more than 65% of South Asia and resulted in a decline in rice yield (∼400 kg ha−1). A large uncertainty based on the four observational products was found in the number of drought spells and their characteristics. We estimated the frequency of droughts that exceeded the overall severity score of the worst drought during 1951–2016 under the future climate using 40 simulations from Community Earth System Model-Large Ensemble. The frequency of the worst droughts is projected to increase by about 1.5 times in the future (2035–2100) in comparison to the historic (1951–2016) climate. The worst droughts in the future are likely to be more intense and widespread in South Asia. A considerable influence of industrial aerosols was found on the occurrence of the worst droughts in South Asia. Our findings have implications for food and water security in one of the most densely populated regions in the world.

Emerging Anthropogenic Influences on the Southcentral Alaska Temperature and Precipitation Extremes and Related Fires in 2019

The late-season extreme fire activity in Southcentral Alaska during 2019 was highly unusual and consequential. Firefighting operations had to be extended by a month in 2019 due to the extreme conditions of hot summer temperature and prolonged drought. The ongoing fires created poor air quality in the region containing most of Alaska’s population, leading to substantial impacts to public health. Suppression costs totaled over $70 million for Southcentral Alaska. This study’s main goals are to place the 2019 season into historical context, provide an attribution analysis, and assess future changes in wildfire risk in the region. The primary tools are meteorological observations and climate model simulations from the NCAR CESM Large Ensemble (LENS). The 2019 fire season in Southcentral Alaska included the hottest and driest June–August season over the 1979–2019 period. The LENS simulation analysis suggests that the anthropogenic signal of increased fire risk had not yet emerged in 2019 because of the CESM’s internal variability, but that the anthropogenic signal will emerge by the 2040–2080 period. The effect of warming temperatures dominates the effect of enhanced precipitation in the trend towards increased fire risk.

Scoring Antarctic surface mass balance in climate models to refine future projections

Abstract. An increase in Antarctic Ice Sheet (AIS) surface mass balance (SMB) has the potential to mitigate future sea level rise that is driven by enhanced solid ice discharge from the ice sheet. For climate models, AIS SMB provides a difficult challenge, as it is highly susceptible to spatial, seasonal, and interannual variability. Here we use a reconstructed data set of AIS snow accumulation as “true” observational data, to evaluate the ability of the CMIP5 and CMIP6 suites of models in capturing the mean, trends, temporal variability, and spatial variability in SMB over the historical period (1850–2000). This gives insight into which models are most reliable for predicting SMB into the future. We found that the best scoring models included the National Aeronautics and Space Administration (NASA) GISS model and the Max Planck Institute (MPI) for Meteorology's model for CMIP5, as well as one of the Community Earth System Model v2 (CESM2) models and one MPI model for CMIP6. Using a scoring system based on SMB mean value, trend, and temporal variability across the AIS, as well as spatial SMB variability, we selected a subset of the top 10th percentile of models to refine 21st century (2000–2100) AIS-integrated SMB projections to 2274 ± 282 Gt yr−1, 2358 ± 286 Gt yr−1, and 2495 ± 291 Gt yr−1 for Representative Concentration Pathways (RCPs) 2.6, 4.5, and 8.5, respectively. We also reduced the spread in AIS-integrated mean SMB by 79 %, 79 %, and 74 % in RCPs 2.6, 4.5, and 8.5, respectively. Notably, we find that there is no improvement from CMIP5 to CMIP6 in overall score. In fact, CMIP6 performed slightly worse on average compared to CMIP5 at capturing the aforementioned SMB criteria. Our results also indicate that model performance scoring is affected by internal climate variability (particularly the spatial variability), which is illustrated by the fact that the range in overall score between ensemble members within the CESM1 Large Ensemble is comparable to the range in overall score between CESM1 model simulations within the CMIP5 model suite. We also find that a higher horizontal resolution does not yield to a conclusive improvement in score.

Projected End-of-Century Changes in the South American Monsoon in the CESM Large Ensemble

AbstractProjected changes in the South American monsoon system by the end of the twenty-first century are analyzed using the Community Earth System Model Large Ensemble (CESM-LENS). The wet season is shorter in LENS when compared to observations, with the mean onset occurring 19 days later and the mean retreat date 21 days earlier in the season. Despite a precipitation bias, the seasonality of rainfall over South America is reproduced in LENS, as well as the main circulation features associated with the development of the South American monsoon. Both the onset and retreat of the wet season over South America are delayed in the future compared to current climate by 3 and 7 days, respectively, with a slightly longer wet season. Central and southeastern Brazil are projected to get wetter as a result of moisture convergence from the strengthening of the South Atlantic low-level jet and a weaker South Atlantic subtropical high. The Amazon is projected to get drier by the end of the century, negatively affecting rain forest productivity. During the wet season, an increase in the frequency and intensity of extreme precipitation events is found over most of South America, and especially over northeastern and southern Brazil and La Plata. Meanwhile, during the dry season an increase in the maximum number of consecutive dry days is found over northeastern Brazil and the northern Amazon.

An Internal Atmospheric Process Determining Summertime Arctic Sea Ice Melting in the Next Three Decades: Lessons Learned from Five Large Ensembles and Multiple CMIP5 Climate Simulations

AbstractArctic sea ice melting processes in summer due to internal atmospheric variability have recently received considerable attention. A regional barotropic atmospheric process over Greenland and the Arctic Ocean in summer (June–August), featuring either a year-to-year change or a low-frequency trend toward geopotential height rise, has been identified as an essential contributor to September sea ice loss, in both observations and the CESM1 Large Ensemble (CESM-LE) of simulations. This local melting is further found to be sensitive to remote sea surface temperature (SST) variability in the east-central tropical Pacific Ocean. Here, we utilize five available large “initial condition” Earth system model ensembles and 31 CMIP5 models’ preindustrial control simulations to show that the same atmospheric process, resembling the observed one and the one found in the CESM-LE, also dominates internal sea ice variability in summer on interannual to interdecadal time scales in preindustrial, historical, and future scenarios, regardless of the modeling environment. However, all models exhibit limitations in replicating the magnitude of the observed local atmosphere–sea ice coupling and its sensitivity to remote tropical SST variability in the past four decades. These biases call for caution in the interpretation of existing models’ simulations and fresh thinking about models’ credibility in simulating interactions of sea ice variability with the Arctic and global climate systems. Further efforts toward identifying the causes of these model limitations may provide implications for alleviating the biases and improving interannual- and decadal-time-scale sea ice prediction and future sea ice projection.

Sea Level Rise in the CESM Large Ensemble: The Role of Individual Climate Forcings and Consequences for the Coming Decades

AbstractThe emergence of a spatial pattern in the externally forced response (FR) of dynamic sea level (DSL) during the altimeter era has recently been demonstrated using climate models but our understanding of its initial emergence, drivers, and implications for the future is poor. Here the anthropogenic forcings of the DSL pattern are explored using the Community Earth System Model Large Ensemble (CESM-LE) and Single-Forcing Large Ensemble, a newly available set of simulations where values of individual forcing agents remain fixed at 1920 levels, allowing for an estimation of their effects. Statistically significant contributions to the DSL FR are identified for greenhouse gases (GHGs) and industrial aerosols (AERs), with particularly strong contributions resulting from AERs in the mid-twentieth century and GHGs in the late twentieth and twenty-first century. Secondary, but important, contributions are identified for biomass burning aerosols in the equatorial Atlantic Ocean in the mid-twentieth century, and for stratospheric ozone in the Southern Ocean during the late twentieth century. Key to understanding regional DSL patterns are ocean heat content and salinity anomalies, which are driven by surface heat and freshwater fluxes, ocean dynamics, and the spatial structure of seawater thermal expansivity. Potential implications for the interpretation of DSL during the satellite era and the longer records from tide gauges are suggested as a topic for future research.

An Evaluation of the Large‐Scale Atmospheric Circulation and Its Variability in CESM2 and Other CMIP Models

AbstractThe Community Earth System Model 2 (CESM2) is the latest Earth System Model developed by the National Center for Atmospheric Research in collaboration with the university community and is significantly advanced in most components compared to its predecessor (CESM1). Here, CESM2's representation of the large‐scale atmospheric circulation and its variability is assessed. Further context is providedthrough comparison to the CESM1 large ensemble and other models from the Coupled Model Intercomparison Project (CMIP5 and CMIP6). This includes an assessment of the representation of jet streams and storm tracks, stationary waves, the global divergent circulation, the annular modes, the North Atlantic Oscillation, and blocking. Compared to CESM1, CESM2 is substantially improved in the representation of the storm tracks, Northern Hemisphere (NH) stationary waves, NH winter blocking and the global divergent circulation. It ranks within the top 10% of CMIP class models in many of these features. Some features of the Southern Hemisphere (SH) circulation have degraded, such as the SH jet strength, stationary waves, and blocking, although the SH jet stream is placed at approximately the correct location. This analysis also highlights systematic deficiencies in these features across the new CMIP6 archive, such as the continued tendency for the SH jet stream to be placed too far equatorward, the North Atlantic westerlies to be too strong over Europe, the storm tracks as measured by low‐level meridional wind variance to be too weak and a lack of blocking in the North Atlantic sector.

Mechanisms driving the asymmetric seasonal cycle of Antarctic Sea Ice in the CESM Large Ensemble

AbstractThe yearly paired process of slow growth and rapid melt of some 15 million square kilometers of Antarctic sea ice takes place with a regular asymmetry; the process has been linked to the relationship of the position of the ice edge with the band of low pressure that circles the continent between 60° and 70°S. In autumn, winds to the north of the low-pressure band slow the advancing ice edge. In summer, Ekman divergence created by opposing winds on either side of the low-pressure band opens up warm water regions that rapidly melt sea ice. We use the 40 ensemble members from the CESM-LENS historical run (1920–2005) to examine the relationship between the asymmetry in the annual cycle and the position and intensity of the low-pressure band. CESM-LENS reproduces the magnitude of the annual cycle of Antarctic sea ice extent with a short lag (2 weeks). Melt rate is the characteristic of the annual cycle that varies the most. Our results provide evidence that lower pressure leads to increased melt rates, which supports the importance of the role of divergence in increasing the melt rate of Antarctic sea ice. The role of winds during the growing season remains unquantified.

Internal Variability Dominates Over Externally Forced Ocean Circulation Changes Seen Through CFCs

AbstractObservations of oceanic transient tracers have indicated that the circulation in the Southern Ocean has changed in recent decades, potentially driven by changes in external climate forcing. Here, we use the CESM Large Ensemble to analyze changes in two oceanic tracers that are affected by ocean circulation: the partial pressure of chlorofluorocarbon‐12 (pCFC12) and the idealized model tracer Ideal Age (IAGE) over the 1991 to 2005 period. The small ensemble mean change in IAGE suggests that there has been very little externally forced change in Southern Ocean circulation over this period, in contrast to strong internal variability. Further, our analysis implies that real‐world observations of changes in pCFC12 may not be a robust way to characterize externally driven changes in Southern Ocean circulation because of the large internal variability in pCFC12 changes exhibited by the individual ensemble members.