Community Climate System Model Version Research Articles

Fast parameter estimation of generalized extreme value distribution using neural networks

AbstractThe heavy‐tailed behavior of the generalized extreme‐value distribution makes it a popular choice for modeling extreme events such as floods, droughts, heatwaves, wildfires and so forth. However, estimating the distribution's parameters using conventional maximum likelihood methods can be computationally intensive, even for moderate‐sized datasets. To overcome this limitation, we propose a computationally efficient, likelihood‐free estimation method utilizing a neural network. Through an extensive simulation study, we demonstrate that the proposed neural network‐based method provides generalized extreme value distribution parameter estimates with comparable accuracy to the conventional maximum likelihood method but with a significant computational speedup. To account for estimation uncertainty, we utilize parametric bootstrapping, which is inherent in the trained network. Finally, we apply this method to 1000‐year annual maximum temperature data from the Community Climate System Model version 3 across North America for three atmospheric concentrations: 289 ppm (pre‐industrial), 700 ppm (future conditions), and 1400 ppm , and compare the results with those obtained using the maximum likelihood approach.

The Weakened Atlantic Meridional Overturning Circulation Diminishes Recent Arctic Sea Ice Loss

AbstractThe Arctic sea ice has been rapidly dwindling over the past four decades, significantly impacting the Arctic region and beyond. During the same period, the Atlantic meridional overturning circulation (AMOC) was also found in a declining trend. Here we investigate the role of the AMOC in the recent Arctic sea ice changes by comparing simulations from the Community Climate System Model version 4 with decelerated and stationary AMOCs under anthropogenic climate change. We find that the weakened AMOC can slow down the decline rates of Arctic sea ice area and volume by 36% and 22% between 1980 and 2020, respectively. The decelerated ocean circulation causes a reduction of northward Atlantic heat transport and hence a general interior ocean cooling in the Arctic Mediterranean, which helps alleviate the Arctic sea ice loss primarily through thermodynamic processes occurring at the base of the sea ice.

The Impact of Model Resolution on the Southern Hemisphere in Community Climate System Model Version 4 Idealized Climate Simulations

Model resolution plays a large role in accurately simulating the Southern Hemisphere circulation in both the ocean and atmosphere. Resolving the mesoscale field is important as it has been shown to have a significant impact on the large-scale climate in eddy-rich regions, which are regions of large CO2 absorption. The presence of ocean and atmospheric mesoscale features can affect sea surface temperatures, the strength and location of storm tracks, and many other air-sea processes. Additionally, with an improvement in resolution, the eddy kinetic energy in the ocean can be expected to change considerably. The significance model resolution has on the Southern Hemisphere is examined using the Community Climate System Model, Version 4, eddy-parameterizing and eddy-resolving simulations. The CO2 concentrations and ozone levels are specified independently to better understand how the mesoscale field responds to extreme changes in external forcing and the resulting climate impacts. Overall, in the eddy-parameterizing simulations, the ozone forcing is found to be more important than the changes in CO2 concentrations. However, in the case of the eddy-resolving simulations, the CO2 concentrations are found to be more dominant, especially in eddy-rich regions. These results demonstrate the need for an increase in model resolution for climate prediction.

Enhanced multi-year predictability after El Niño and La Niña events

Several aspects of regional climate including near-surface temperature and precipitation are predictable on interannual to decadal time scales. Despite indications that some climate states may provide higher predictability than others, previous studies analysing decadal predictions typically sample a variety of initial conditions. Here we assess multi-year predictability conditional on the phase of the El Niño–Southern Oscillation (ENSO) at the time of prediction initialisation. We find that predictions starting with El Niño or La Niña conditions exhibit higher skill in predicting near-surface air temperature and precipitation multiple years in advance, compared to predictions initialised from neutral ENSO conditions. This holds true in idealised prediction experiments with the Community Climate System Model Version 4 and to a lesser extent also real-world predictions using the Community Earth System Model and a multi-model ensemble of hindcasts contributed to the Coupled Model Intercomparison Project Phase 6 Decadal Climate Prediction Project. This enhanced predictability following ENSO events is related to phase transitions as part of the ENSO cycle, and related global teleconnections. Our results indicate that certain initial states provide increased predictability, revealing windows of opportunity for more skillful multi-year predictions.

Future climate change in the Agulhas system and its associated impact on South African rainfall

South African climate variability has been linked to changes in both the Agulhas system and external forcing (i.e. CO2 and ozone). We analysed future climate change in the Agulhas system volume transport and its associated impacts on South Africa’s precipitation using the Community Climate System Model version 4 as part of the Coupled Model Intercomparison Project, phase 5. Output from one historical and three future greenhouse gas emission scenarios were examined to project various climate storylines. We found that the Agulhas Current volume transport decreases across all three scenarios and that the current displays a strong baroclinic component with an increase in transport at the surface and decrease at intermediate depths. Agulhas leakage was found to increase with historical emissions. Additionally, an east-west dipole pattern for convective precipitation was found over South Africa, with an increase over the eastern region related to an increase in greenhouse gas emissions and a decrease in the western region linked to the location of Hadley cell edge latitude. Moving into the 21st century, future predictions in regional climate variability are shown to be dependent on the intensity of greenhouse gas emissions and are extremely important for South Africa, a region prone to drought and flooding and home to a large population dependent on rain-fed agriculture. Significance: Future climate variability in the Agulhas system and South African region is heavily dependent on changes in external forcing. The Agulhas Current volume transport decreases as the greenhouse gas emissions continue to increase and a strong baroclinic component is found with an increase in transport at the surface and a decrease at the intermediate depths. A strong east-west dipole precipitation pattern is found over South Africa with the increase in the eastern region related to the increase in greenhouse gas emissions and the decrease in the western region related to the location of the Hadley cell edge latitude.

A Comparative Study Between Regional Atmospheric Model Simulations Coupled and Uncoupled to a Regional Ocean Model of the Indian Summer Monsoon

AbstractWe evaluate the impact of air‐sea coupling in simulating the characteristics of the Indian summer monsoon (ISM) and its intraseasonal oscillations (ISOs) by using a coupled ocean‐atmosphere regional climate model (CRSM) and an atmosphere‐only regional climate model (URSM). These 20‐km resolution regional climate models (RCMs) were driven by the boundary conditions from Community Climate System Model version 4 (CCSM4) global model. The mean ISM rainfall simulated by URSM and CRSM is comparable with observations and shows an improvement over the CCSM4. The systematic error in the spatial distribution of the mean June–September low‐level and upper‐level winds, sea surface temperature, and latent heat flux shows that CRSM performs better than URSM, suggesting the benefits of air‐sea coupling in the RCM simulations of the mean ISM. Both the CRSM and the URSM perform reasonably and comparably in capturing the spatiotemporal evolution of 10–20‐day high‐frequency and 20–70‐day low‐frequency ISOs of the ISM rainfall. These RCMs simulated the observed features of the ISO‐filtered rainfall anomalies that propagate at a faster rate across the Arabian Sea compared to that over the Bay of Bengal. Furthermore, the difference in the track density of the monsoon low‐pressure systems between the wet and the dry phases of ISOs shows insignificant differences between CRSM and URSM but is found to be superior to the CCSM4 simulation. This study suggests a relative insensitivity of air‐sea coupling in the RCM for simulating ISO and LPS features of ISM, which is likely abetted by the realistic ISO signals in the parent CCSM4.

CHELSA-TraCE21k – high-resolution (1 km) downscaled transient temperature and precipitation data since the Last Glacial Maximum

Abstract. High-resolution, downscaled climate model data are used in a wide variety of applications across environmental sciences. Here we introduce a new, high-resolution dataset, CHELSA-TraCE21k. It is obtained by downscaling TraCE-21k data, using the “Climatologies at high resolution for the earth's land surface areas” (CHELSA) V1.2 algorithm with the objective to create global monthly climatologies for temperature and precipitation at 30 arcsec spatial resolution in 100-year time steps for the last 21 000 years. Paleo-orography at high spatial resolution and for each time step is created by combining high-resolution information on glacial cover from current and Last Glacial Maximum (LGM) glacier databases and interpolations using data from a global model of glacial isostasy (ICE-6G_C) and a coupling to mean annual temperatures from TraCE21k (Transient Climate Evolution of the last 21 000 years) based on the Community Climate System Model version 3 (CCSM3). Based on the reconstructed paleo-orography, mean annual temperature and precipitation were downscaled using the CHELSA V1.2 algorithm. The data were validated by comparisons with the glacial extent of the Laurentide ice sheet based on expert delineations, proxy data from Greenland ice cores, historical climate data from meteorological stations, and a dynamic simulation of species distributions throughout the Holocene. Validations show that the CHELSA-TraCE21k V1.0 dataset reasonably represents the distribution of temperature and precipitation through time at an unprecedented 1 km spatial resolution, and simulations based on the data are capable of detecting known LGM refugia of species.

Decoupling of species and plant communities of the U.S. Southwest: A CCSM4 climate scenario example

AbstractClimate change is predicted to alter the current climate suitability under which plant species and communities occur. Predictions of change have focused on individual species or entire communities, but theory indicates plants will not respond uniformly to climate change within or between communities. We developed models of the current climate suitability (the baseline) of 66 plant species characteristic of 29 plant communities of the arid Southwest, made predictions of climate suitability for the species under two climate change scenarios for the years 2041–2060 (Community Climate System Model version 1.4 [CCSM4] global climate model [GCM], Representative Concentration Pathway [RCP] 4.5 and 8.5 scenarios), and calculated changes in suitability between the future scenarios and baseline for each species. Climate change exposure for the entire community was then evaluated as the composite change of the predicted future climate suitability of the communities' characteristic species. Loss of 25% or more of favorable climate suitability was predicted for 39 (RCP4.5) and 51 (RCP8.5) species within their communities. The proportion of the study area with all species in a community having unfavorable suitability was 17.9% (RCP4.5) and 21.3% (RCP8.5) compared to 6.2% for baseline. We show that suitable climates for species within a plant community are not expected to be a single community‐wide trajectory, but rather changes in climate suitability will be unique to the species and not experienced uniformly across the extant communities. This decoupling of plant species within their traditional plant communities may lead to a cascade of unanticipated ecological responses and unprecedented challenges to resource management. Our study results can inform hypotheses of the future successional track of plant communities, characteristic species, and the decisions resource managers must make for management.

Decadal variability of the interannual climate predictability associated with the Indo-Pacific oceanic channel dynamics in CCSM4

The lag correlations between the observed sea surface temperature anomalies (SSTA) in the southeastern tropical Indian Ocean in fall and those in the Pacific cold tongue at the one-year time lag are calculated in running windows of 7–11 years and are shown to have decadal variability. Similar decadal variability has also been identified in the historical simulations of the Community Climate System Model version 4 (CCSM4) that participates in the Coupled Model Intercomparison Project phase-5 (CMIP5). During the positive phases of the decadal variability, the significant lag correlations are diagnosed to be dominated by the oceanic channel dynamics, i.e., upwelling Kelvin waves associated with the Indian Ocean Dipole (IOD) force enhanced Indonesian Throughflow transport anomalies and western Pacific thermocline anomalies to propagate eastward, resulting in SSTA in the central-eastern equatorial Pacific Ocean. During the negative phases of the decadal variability, the subsurface lag correlations suggest that the western Pacific Ocean are still dominated by the oceanic channel dynamics, but do not correlate well with the SSTA in the cold tongue due to a deeper thermocline in the eastern equatorial Pacific. The IOD-ENSO teleconnection is not affected significantly by the anthropogenic forcing during either the positive or the negative decadal phases. The CCSM4 model is found to underestimate Indonesian Throughflow transport variability but overestimate the westerly wind anomalies in the western-central equatorial Pacific, which forces unrealistic anomalies in the equatorial Pacific Ocean associated with the IOD.

Mapping the changing distribution of two important pollinating giant honeybees across 21000 years

Pollinators play an important role in ecosystems, but global climate change threatens the diversity and geographical distribution of pollinators. Bees are some of the most important pollinators and are particularly sensitive to climate change and environmental change. Apis laboriosa and Apis dorsata are two species of giant honeybees distributed in Asia, and play important roles in their ecosystems. In this study, we analyzed the key factors affecting the distribution of two species, as well as their potential suitable areas and possible co-existence regional changes under the global climate change. We collected and filtered global distribution data of A. laboriosa and A. dorsata, then used eight climatic variables and Community Climate System Model version 4 (CCSM4) to simulate their potential suitable areas for the past, present and future (using two different climate scenarios) using MaxEnt. Finally, we used ArcGIS 10.2 and ENMTools to calculate range overlap and niche overlap of the two species in order to infer areas of co-existence. Temperature-related variables had the largest contribution to the model simulation. Among these variables, temperature seasonality (Bio 4) and mean temperature of coldest quarter (Bio 11) showed the strongest influence on the distributions of two giant honeybees. Under the current climate scenario, the species overlap in Nepal and Yunnan of China, with low niche overlap index. Between the last-glacial maximum to the present both honeybees moved northwest to their present range. A. laboriosa is projected to move to the northeast and A. dorsata may move southeast. Only 6.6% of overlapping distribution is currently protected, and further work is needed to protect these key areas.

Elevation dependence of projected hydro-climatic change in eastern Siberia

Over the last several decades, eastern Siberia has experienced some of the largest temperature increases worldwide. We use the RCP8.5 simulation of the Community Climate System Model version 4 to examine how projected monthly changes in temperature and hydro-climatic variables in eastern Siberia depend on latitude and elevation. Temperature increases are largest at the highest latitudes in winter and late fall and are smaller at higher elevations. For precipitation and snowfall, there is a latitudinal dependence in autumn and spring, with precipitation, snowfall, and snow depth mostly increasing between 60 and 70° N. Although snow cover extent (SCE) decreases almost everywhere, the largest changes occur during the transition seasons which we define as spring and autumn, and the timing of the changes depends on latitude, elevation, and the specific month within seasons. The decreases in SCE are larger at lower latitudes and lower elevations in April and November and larger at higher elevations and higher latitudes in June and September. For the highest latitudes, snow depth actually increases, and increases more at higher elevations. These projections are generally consistent with those of four other climate models. For precipitation, all models project increases in non-summer seasons, but they are not consistent with respect to the direction of the elevation dependence of precipitation. We discuss the complex interactions among the projected changes in all the variables.

A Hybrid Dynamical Approach for Seasonal Prediction of Sea‐Level Anomalies: A Pilot Study for Charleston, South Carolina

AbstractUsing Earth system models for seasonal sea‐level prediction remains challenging due to model biases and initialization shocks. Here we present a hybrid dynamical approach for seasonal sea‐level prediction to alleviate some of these issues. The approach is based on convolving atmospheric forcings with sea‐level sensitivities to these forcings. The sensitivities are pre‐computed by the adjoint model of the Estimating Circulation and Climate of the Ocean (ECCO) system. The forcings are a concatenation of ECCO forcings before prediction initialization and a 10‐member predicted atmospheric forcing ensemble from the Community Climate System Model version 4 (CCSM4) after initialization, with offline forcing bias corrections applied using the observationally‐constrained ECCO seasonal forcing climatology. As a pilot study, we conducted 12‐month hindcasts from 1995 to 2016 in Charleston (United States East Coast). Our approach avoids drifts in CCSM4 sea‐level predictions and beats seasonal climatology and damped persistence as predictors up to a 6‐month lead time. The prediction skill comes from two factors: (a) ECCO forcings prior to prediction initialization influence sea level after initialization through delayed oceanic adjustments (e.g., coastally‐trapped waves, open‐ocean Rossby waves, and advection of steric anomalies) leading to skillful predictions beyond 2 months after initialization, and (b) the 10‐member CCSM4 ensemble forcing predictions have relatively good skill at 1–2 months lead times. Our method is computationally efficient for operational sea‐level prediction at specific locations and can attribute sea‐level prediction skill and uncertainty to specific forcings or forcing from particular regions, thereby providing useful information to seasonal prediction centers for improving their prediction systems.

Contrary Responses of the Gulf Stream and the Kuroshio to Arctic Sea Ice Loss

The impact on the Gulf Stream and Kuroshio from Arctic sea ice loss is investigated using the Community Climate System Model version 4 (CCSM4) model for their important roles during climate change. Results show that the Gulf Stream (Kuroshio) weakens (strengthens) in response to Arctic sea ice loss via ocean (atmosphere) adjustments. More precisely, the Kuroshio acceleration is mainly due to the anomalous wind stress over the North Pacific, while the ocean gyre adjustments in the Atlantic are responsible for the weakened Gulf Stream. As positive buoyancy fluxes induced by Arctic sea ice loss trigger a slowdown of the Atlantic Meridional Overturning Circulation (AMOC), the Gulf Stream decelerates evidently and the current speed decreases by about 5–8 cm/s in the upper ocean. Resulting from less advection and horizontal diffusion in the temperature budget, less poleward warm water leads to narrow sea surface cooling sandwiched between strong warming in the subpolar and subtropical Atlantic. Furthermore, colder surface decreases the upward heat flux (mainly latent heat flux) along the Gulf Stream Extension (GE) path, which leads to a warming hole in the atmosphere.

Atmospheric blockings in Coupled Model Intercomparison Project Phase 5 models with different representations of Antarctic sea ice extent

This study investigated whether there are differences in the frequency and position of Southern Hemisphere atmospheric blockings between Coupled Model Intercomparison Project Phase 5 models with different representations of Antarctic sea ice extent in historical experiments. In the model with the greatest sea ice underestimation (Model for Interdisciplinary Research on Climate version 5) there is a weakening of the polar jet and an increase in 500-hPa height. These atmospheric conditions favor the predomination of simulated blocking frequency overestimations (autumn-winter), in relation to the observed (ERA-Interim). On the other hand, in the models with the greatest sea ice overestimations (Community Climate System Model version 4) and the better sea ice representation (Norwegian Earth System Model version 1) there is a strengthening of the polar jet and weaker positive differences in 500-hPa height in the Antarctic region. These atmospheric conditions favor a predominance of simulated blocking frequency underestimations (all seasons). All models present a good representation of the preferred blocking regions (South Pacific), although they do not represent the longitudinal location of the maximum frequency. In years of sea ice retraction (expansion), there is a predominance of a higher (lower) blocking frequency in the 60°S for all models and observed data.

The seasonal predictability of the wet season over Peninsular Florida

AbstractIn this study, we examine the seasonal predictability of Peninsular Florida (PF)'s boreal summer season, which is also known as the PF wet season (PFWS) due to the coinciding peak of the robust seasonal cycle of rainfall. The seasonal predictability is examined in the Community Climate System Model, version 4 (CCSM4), which is one of the models of the North American Multi‐Model Ensemble used for routine, operational seasonal forecasts by the National Oceanic and Atmospheric Administration (NOAA) Climate Prediction Center (CPC). An objective definition of the onset and the demise of the PFWS are then implemented, and the predictability of the onset, the demise and the seasonal rainfall anomaly is assessed from the CCSM4 seasonal hindcasts. Our study shows that the 33 years (1983–2015) of the CCSM4 seasonal hindcasts display very poor deterministic and probabilistic skill in predicting the onset and the demise of the PFWS and its seasonal rainfall anomalies for all lead times. It is shown that the seasonal hindcasts display poor skill for both the fixed calendar month and varying seasonal length of the PFWS. In many of these instances, the skills deteriorate with the lead time of the CCSM4 hindcasts, although, in some cases, they bear no relation (e.g., demise date of the PFWS). Our analysis reveals that the interannual variability of the location of the western ridge of the North Atlantic subtropical high is poorly rendered in the seasonal hindcast of CCSM4 with respect to reanalysis. This could explain the origins of some of the potential issues of the CCSM4 seasonal hindcasts with the variability of the PFWS.

Thermal Niche for Seed Germination and Species Distribution Modelling of Swietenia macrophylla King (Mahogany) under Climate Change Scenarios.

Swietenia macrophylla is an economically important tree species propagated by seeds that lose their viability in a short time, making seed germination a key stage for the species recruitment. The objective of this study was to determine the cardinal temperatures and thermal time for seed germination of S. macrophylla; and its potential distribution under different climate change scenarios. Seeds were placed in germination chambers at constant temperatures from 5 to 45 °C and their thermal responses modelled using a thermal time approach. In addition, the potential biogeographic distribution was projected according to the Community Climate System Model version 4 (CCSM4). Germination rate reached its maximum at 37.3 ± 1.3 °C (To); seed germination decreased to near zero at 52.7 ± 2.2 °C (ceiling temperature, Tc) and at 12.8 ± 2.4 °C (base temperature, Tb). The suboptimal thermal time needed for 50% germination was ca. 190 °Cd, which in the current scenario is accumulated in 20 days. The CCSM4 model estimates an increase of the potential distribution of the species of 12.3 to 18.3% compared to the current scenario. The temperature had an important effect on the physiological processes of the seeds. With the increase in temperature, the thermal needs for germination are completed in less time, so the species will not be affected in its distribution. Although the distribution of the species may not be affected, it is crucial to generate sustainable management strategies to ensure its long-term conservation.

Sea surface temperatures in the South China Sea as a natural thermostat to the rainfall over Borneo: preliminary results

Community Climate System Model version 4 (CCSM4) simulated warmer sea surface temperatures (SSTs) in the South China Sea (SCS) for the mid-Holocene scenario compared to the pre-Industrial. Previous sensitivity experiments using the atmospheric component of the CCSM4, the Community Atmospheric Model version 4 (CAM4), showed that warmer SSTs in the SCS suppresses rainfall over Borneo, which is in-contrary to the effect of the stronger insolation over the island. In this study, we show that warmer SSTs in the SCS, as simulated in the CCSM4, is responding to a weaker low-level wind impacted by the stronger convectional rainfall over Borneo due to stronger insolation. These results suggest that warmer SSTs in the SCS might act as a negative feedback which damps the effect of the stronger insolation on rainfall changes over Borneo.

Current and future predicting habitat suitability map of Cunninghamia konishii Hayata using MaxEnt model under climate change in Northern Vietnam

Cunninghamia konishii Hayata is a rare and endangered plant species that plays a relevant role in ecological andcommercial systems of natural forests in Vietnam. In this research, we evaluated the potential geographic distribution ofC. konishii under current and future climatic conditions in Northern Vietnam using the ecological niche modelling approachbased on the largest available database of occurrence records for this species. C. konishii is mainly distributed inthe northern part of Vietnam at altitudes above 1000 m where the slopes range between 12 and 25 degrees, particularlyin special-use and protected forest. The optimal distribution area of C. konishii requires specific climatic conditions: anannual precipitation around 1200 mm, precipitation of the warmest quarter ranging from 600 to 800 mm, a precipitationseasonality of 90 to100 mm, an annual mean temperature ranging from 12°C to 19°C, and a temperature seasonalityranging from 300 to 350. Additionally, the species requires specific soil groups: humic acrisols, ferralic acrisols, andyellow-red humic soils. Considering these requirements, the results of our research show that the suitable regions for thegrowth of C. konishii are found in the provinces of Ha Giang, Son La, Thanh Hoa and Nghe An, covering a total area of1509.56 km2. However, analyzing the results under the Community Climate System Model version 4 (CCSM4) model, itis possible to observe that the area will decline to 504.39 km2 by 2090 according to RCP 2.6 scenario, to 406.25 km2 inthe RCP 4.5 scenario, and to 47.62 km2 in the RCP 8.5 scenario. The findings of this present research may be applied toseveral additional studies such as identifying current and future locations to establish conservation areas for C. konishii.

Simulation and estimation of future precipitation changes in arid regions: a case study of Xinjiang, Northwest China

Precipitation is critical for maintaining the stability of an ecosystem, especially in arid regions. This study primarily focuses on climatic changes during present (from 1985 to 2005) and future (from 2040 to 2059) periods in Xinjiang, Northwest China. In this study, the Weather Research and Forecasting model is implemented in Xinjiang to efficiently predict the future climate. Moreover, the National Climate Research Center Community Climate System Model version 4 is employed for the mid-21st century under representative concentration pathways 4.5 and 8.5 (RCP4.5 and RCP8.5, respectively). Our results indicate that the amount of annual precipitation will increase in the future under RCP4.5 and RCP8.5 in Xinjiang, especially in mountainous areas. The increase in precipitation is predicted to be much smaller under RCP8.5 than under RCP4.5, except in Southern Xinjiang. Moreover, the increasing precipitation predicted in Xinjiang implies that the current humid and warm conditions will persist, thereby further indicating that Xinjiang is still currently suffering from a dry climate. The largest increase in seasonal precipitation is predicted to occur in spring and summer in Tianshan and Northern Xinjiang, whereas this phenomenon is predicted to occur in spring and winter in Southern Xinjiang. In addition, it is predicted that daily heavy precipitation events will occur more frequently in various subregions of Xinjiang, although light rain events will remain dominant. Finally, the relative humidity is closely related to the changes in annual and seasonal precipitation.

A dynamic ocean driven by changes in CO2 and Antarctic ice-sheet in the middle Miocene

The middle Miocene climate transition (MMCT), likely triggered by a decrease in atmospheric CO2 concentration and changes in the Earth's orbital configuration, entailed major expansion of the Antarctic ice-sheet and cooling of the global ocean at ~15–13 Ma. By comparing simulations that use boundary conditions representative of 15 and 13 Ma, we assess the response of ocean temperatures and deep ocean circulation to atmospheric CO2 drawdown (from 400 to 200 ppmv) and Antarctic ice-sheet expansion (43 m of sea-level equivalent) during the MMCT by means of the Community Climate System Model version 3. The model simulates a decrease in mean global sea-surface temperature by 1.6 °C across the transition. Individual forcing experiments reveal that surface cooling is fully attributable to the CO2 drop, whereas expansion of the Antarctic ice-sheet tends to cause a slight global warming of the upper ocean. At depth, modelled ocean temperatures decrease by 1.5–2 °C across the MMCT in most regions. While the CO2 effect dominates deep-ocean cooling, about 25–30% is attributable to the expansion of the Antarctic ice-sheet.In the convection regions of the Southern Ocean, the CO2 drawdown causes an increase in salinity through sea ice formation and changes in the precipitation-evaporation balance. This increase in salinity, together with a decrease in surface temperatures, translates into an intensification in Antarctic Bottom Water formation that cools the deep ocean. The contribution of the Antarctic ice-sheet expansion to bottom and deep water cooling occurs through an increase in the surface heat flux from the ocean to the atmosphere, which is linked to intensified cold surface winds blowing off the Antarctic continent.This study suggests that the magnitude of cooling of deep waters across the MMCT inferred from proxy records can be explained by the combined effects of the CO2 decrease and Antarctic ice-sheet expansion. Our surface cooling estimates are generally lower than those indicated by proxies.