There is observational and modeling evidence that low-frequency variability in the North Atlantic has significant implications for the global climate, particularly for the climate of the Northern ...Hemisphere. This study explores the representation of low-frequency variability in the Atlantic region in historical large ensemble and preindustrial control simulations performed with the Community Earth System Model (CESM). Compared to available observational estimates, it is found that the simulated variability in Atlantic meridional overturning circulation (AMOC), North Atlantic sea surface temperature (NASST), and Sahel rainfall is underestimated on multidecadal time scales but comparable on interannual to decadal time scales. The weak multidecadal North Atlantic variability appears to be closely related to weaker-than-observed multidecadal variations in the simulated North Atlantic Oscillation (NAO), as the AMOC and consequent NASST variability is impacted, to a great degree, by the NAO. Possible reasons for this weak multidecadal NAO variability are explored with reference to solutions from two atmosphere-only simulations with different lower boundary conditions and vertical resolution. Both simulations consistently reveal weaker-than-observed multidecadal NAO variability despite more realistic boundary conditions and better resolved dynamics than coupled simulations. The authors thus conjecture that the weak multidecadal NAO variability in CESM is likely due to deficiencies in air–sea coupling, resulting from shortcomings in the atmospheric model or coupling details.
The sea surface temperature (SST) signature of Atlantic multidecadal variability (AMV) is a key driver of climate variability in surrounding regions. Low-frequency Atlantic meridional overturning ...circulation (AMOC) variability is often invoked as a key driving mechanism of AMV-related SST anomalies. However, the origins of both AMV and multidecadal AMOC variability remain areas of active research and debate. Here, using coupled ensemble experiments designed to isolate the climate response to buoyancy forcing associated with the North Atlantic Oscillation in the Labrador Sea, we show that ocean dynamical changes are the essential drivers of AMV and related climate impacts. Atmospheric teleconnections also play an important role in rendering the full AMV pattern by transmitting the ocean-driven subpolar SST signal into the rest of the basin, including the tropical North Atlantic. As such, the atmosphere response to the tropical AMV in our experiments is limited to a relatively small area in the Atlantic sector in summertime, suggesting that it could be overestimated in widely adopted protocols for AMV pacemaker experiments.
This study presents multiple lines of evidence from observations and model simulations that support a key role for ocean dynamics, rather than external forcings, in Atlantic multidecadal variability ...(AMV) during the last half century. Observed AMV fingerprints considered here include the low‐frequency spatiotemporal evolution of sea surface temperature, surface heat fluxes, and deep ocean hydrography. While largely absent in the forced response of a large ensemble historical simulations (LENSs), these fingerprints are clearly discernible in a long control simulation where the variability is purely internal. Further evidence derives from initialized decadal prediction simulations, which exhibit much higher skill at predicting the observed AMV of the past 50 years than LENS. The high correlation between the observed AMV and the externally forced version derived from LENS, which has been invoked as evidence for externally driven AMV, is shown to be largely an artifact of concurrent warming since the 1990s.
Plain Language Summary
The basin‐wide sea surface temperature variability in the North Atlantic on multidecadal timescales, often called Atlantic multidecadal variability (AMV), has profound impacts on surface climate in the Northern Hemisphere. This work sheds light on the ongoing debate regarding the driving mechanisms of the AMV: whether it is primarily driven by factors associated with natural fluctuations of the coupled ocean‐atmosphere system (such as slow changes in the strength of the ocean circulation) or forced by factors that are external to that system (such as large volcanic eruptions). In this study, we present multiple lines of evidence, from ocean observations as well as climate model simulations, that suggest that AMV is largely attributable to the former and is thus primarily reflecting a natural mode of variability in the climate system.
Key Points
The observed AMV shows distinctive spatiotemporal patterns with concomitant variability in related fields
While absent in the forced signals in historical simulations, this observed evidence is well reproduced in a preindustrial simulation
A high correlation between the observed and externally forced, simulated AMV arises by coincidence from concurrent warming after the 1990s
The Great Salinity Anomaly (GSA) of the 1970s is the most pronounced decadal-scale low-salinity event observed in the subpolar North Atlantic (SPNA). Using various simulations with the Community ...Earth System Model, here we offer an alternative view on some aspects of the GSA. Specifically, we examine the relative roles of reduced surface heat flux associated with the negative phase of the North Atlantic Oscillation (NAO) and extreme Fram Strait sea ice export (FSSIE) in the late 1960s as possible drivers of the shutdown of Labrador Sea (LS) deep convection. Through composite analysis of a long control simulation, the individual oceanic impacts of extreme FSSIE and surface heat flux events in the LS are isolated. A dominant role for the surface heat flux events for the suppression of convection and freshening in the interior LS is found, while the FSSIE events play a surprisingly minor role. The interior freshening results from reduced mixing of fresher upper ocean with saltier deep ocean. In addition, we find that the downstream propagation of the freshwater anomaly across the SPNA is potentially induced by the persistent negative NAO forcing in the 1960s through an adjustment of thermohaline circulation, with the extreme FSSIE-induced low-salinity anomaly mostly remaining in the boundary currents in the western SPNA. Our results suggest a prominent driving role of the NAO-related heat flux forcing for key aspects of the observed GSA, including the shutdown of LS convection and transbasin propagation of low-salinity waters.
Clement et al (Reports, 16 October 2015, p. 320) claim that the Atlantic Multidecadal Oscillation (AMO) is a thermodynamic response of the ocean mixed layer to stochastic atmospheric forcing and that ...ocean circulation changes have no role in causing the AMO. These claims are not justified. We show that ocean dynamics play a central role in the AMO.
Decadal variability in the North Atlantic Ocean impacts regional and global climate, yet changes in internal decadal variability under anthropogenic radiative forcing remain largely unexplored. Here ...we use the Community Earth System Model 2 Large Ensemble under historical and the Shared Socioeconomic Pathway 3-7.0 future radiative forcing scenarios and show that the ensemble spread in northern North Atlantic sea surface temperature (SST) more than doubles during the mid-twenty-first century, highlighting an exceptionally wide range of possible climate states. Furthermore, there are strikingly distinct trajectories in these SSTs, arising from differences in the North Atlantic deep convection among ensemble members starting by 2030. We propose that these are stochastically triggered and subsequently amplified by positive feedbacks involving coupled ocean-atmosphere-sea ice interactions. Freshwater forcing associated with global warming seems necessary for activating these feedbacks, accentuating the impact of external forcing on internal variability. Further investigation on seven additional large ensembles affirms the robustness of our findings. By monitoring these mechanisms in real time and extending dynamical model predictions after positive feedbacks activate, we may achieve skillful long-lead North Atlantic decadal predictions that are effective for multiple decades.
Abstract
Prediction systems to enable Earth system predictability research on the subseasonal time scale have been developed with the Community Earth System Model, version 2 (CESM2) using two ...configurations that differ in their atmospheric components. One system uses the Community Atmosphere Model, version 6 (CAM6) with its top near 40 km, referred to as CESM2(CAM6). The other employs the Whole Atmosphere Community Climate Model, version 6 (WACCM6) whose top extends to ∼140 km, and it includes fully interactive tropospheric and stratospheric chemistry CESM2(WACCM6). Both systems are utilized to carry out subseasonal reforecasts for the 1999–2020 period following the Subseasonal Experiment’s (SubX) protocol. Subseasonal prediction skill from both systems is compared to those of the National Oceanic and Atmospheric Administration CFSv2 and European Centre for Medium-Range Weather Forecasts (ECMWF) operational models. CESM2(CAM6) and CESM2(WACCM6) show very similar subseasonal prediction skill of 2-m temperature, precipitation, the Madden–Julian oscillation, and North Atlantic Oscillation to its previous version and to the NOAA CFSv2 model. Overall, skill of CESM2(CAM6) and CESM2(WACCM6) is a little lower than that of the ECMWF system. In addition to typical output provided by subseasonal prediction systems, CESM2 reforecasts provide comprehensive datasets for predictability research of multiple Earth system components, including three-dimensional output for many variables, and output specific to the mesosphere and lower-thermosphere (MLT) region from CESM2(WACCM6). It is shown that sudden stratosphere warming events, and the associated variability in the MLT, can be predicted ∼10 days in advance. Weekly real-time forecasts and reforecasts with CESM2(CAM6) and CESM2(WACCM6) are freely available.
Significance Statement
We describe here the design and prediction skill of two subseasonal prediction systems based on two configurations of the Community Earth System Model, version 2 (CESM2): CESM2 with the Community Atmosphere Model, version 6 CESM2(CAM6) and CESM 2 with Whole Atmosphere Community Climate Model, version 6 CESM2(WACCM6) as its atmospheric component. These two systems provide a foundation for community-model based subseasonal prediction research. The CESM2(WACCM6) system provides a novel capability to explore the predictability of the stratosphere, mesosphere, and lower thermosphere. Both CESM2(CAM6) and CESM2(WACCM6) demonstrate subseasonal surface prediction skill comparable to that of the NOAA CFSv2 model, and a little lower than that of the ECMWF forecasting system. CESM2 reforecasts provide a comprehensive dataset for predictability research of multiple aspects of the Earth system, including the whole atmosphere up to 140 km, land, and sea ice. Weekly real-time forecasts, reforecasts, and models are publicly available.
Abstract Arctic Ocean warming and sea ice loss are closely linked to increased ocean heat transport (OHT) into the Arctic and changes in surface heat fluxes. To quantitatively assess their respective ...roles, we use the 100-member Community Earth System Model, version 2 (CESM2), Large Ensemble over the 1920–2100 period. We first examine the Arctic Ocean warming in a heat budget framework by calculating the contributions from heat exchanges with atmosphere and sea ice and OHT across the Arctic Ocean gateways. Then we quantify how much anomalous heat from the ocean directly translates to sea ice loss and how much is lost to the atmosphere. We find that Arctic Ocean warming is driven primarily by increased OHT through the Barents Sea Opening, with additional contributions from the Fram Strait and Bering Strait OHTs. These OHT changes are driven mainly by warmer inflowing water rather than changes in volume transports across the gateways. The Arctic Ocean warming driven by OHT is partially damped by increased heat loss through the sea surface. Although absorbed shortwave radiation increases due to reduced surface albedo, this increase is compensated by increasing upwelling longwave radiation and latent heat loss. We also explicitly calculate the contributions of ocean–ice and atmosphere–ice heat fluxes to sea ice heat budget changes. Throughout the entire twentieth century as well as the early twenty-first century, the atmosphere is the main contributor to ice heat gain in summer, though the ocean’s role is not negligible. Over time, the ocean progressively becomes the main heat source for the ice as the ocean warms. Significance Statement Arctic Ocean warming and sea ice loss are closely linked to increased ocean heat transport (OHT) into the Arctic and changes in surface heat fluxes. Here we use 100 simulations from the same climate model to analyze future warming and sea ice loss. We find that Arctic Ocean warming is primarily driven by increased OHT through the Barents Sea Opening, though the Fram and Bering Straits are also important. This increased OHT is primarily due to warmer inflowing water rather than changing ocean currents. This ocean heat gain is partially compensated by heat loss through the sea surface. During the twentieth century and early twenty-first century, sea ice loss is mainly linked to heat transferred from the atmosphere; however, over time, the ocean progressively becomes the most important contributor.
Abstract
There is a growing demand for understanding sources of predictability on subseasonal to seasonal (S2S) time scales. Predictability at subseasonal time scales is believed to come from ...processes varying slower than the atmosphere such as soil moisture, snowpack, sea ice, and ocean heat content. The stratosphere as well as tropospheric modes of variability can also provide predictability at subseasonal time scales. However, the contributions of the above sources to S2S predictability are not well quantified. Here we evaluate the subseasonal prediction skill of the Community Earth System Model, version 1 (CESM1), in the default version of the model as well as a version with the improved representation of stratospheric variability to assess the role of an improved stratosphere on prediction skill. We demonstrate that the subseasonal skill of CESM1 for surface temperature and precipitation is comparable to that of operational models. We find that a better-resolved stratosphere improves stratospheric but not surface prediction skill for weeks 3–4.
This paper presents global comparisons of fundamental global climate variables from a suite of four pairs of matched low- and high-resolution ocean and sea ice simulations that are obtained following ...the OMIP-2 protocol (Griffies et al., 2016) and integrated for one cycle (1958–2018) of the JRA55-do atmospheric state and runoff dataset (Tsujino et al., 2018). Our goal is to assess the robustness of climate-relevant improvements in ocean simulations (mean and variability) associated with moving from coarse (∼ 1∘) to eddy-resolving (∼ 0.1∘) horizontal resolutions. The models are diverse in their numerics and parameterizations, but each low-resolution and high-resolution pair of models is matched so as to isolate, to the extent possible, the effects of horizontal resolution. A variety of observational datasets are used to assess the fidelity of simulated temperature and salinity, sea surface height, kinetic energy, heat and volume transports, and sea ice distribution. This paper provides a crucial benchmark for future studies comparing and improving different schemes in any of the models used in this study or similar ones. The biases in the low-resolution simulations are familiar, and their gross features – position, strength, and variability of western boundary currents, equatorial currents, and the Antarctic Circumpolar Current – are significantly improved in the high-resolution models. However, despite the fact that the high-resolution models “resolve” most of these features, the improvements in temperature and salinity are inconsistent among the different model families, and some regions show increased bias over their low-resolution counterparts. Greatly enhanced horizontal resolution does not deliver unambiguous bias improvement in all regions for all models.
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