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The Kuroshio Extension (KE) has far-reaching influences on climate as well as on local marine ecosystems. Thus, skillful multi-year to decadal prediction of the KE state and understanding sources of skill are valuable. Retrospective forecasts using the high-resolution Community Earth System Model (CESM) show exceptional skill in predicting KE variability up to lead year 4, substantially higher than the skill found in a similarly configured low-resolution CESM. The higher skill is attained because the high-resolution system can more realistically simulate the westward Rossby wave propagation of initialized ocean anomalies in the central North Pacific and their expression within the sharp KE front, and does not suffer from spurious variability near Japan present in the low-resolution CESM that interferes with the incoming wave propagation. These results argue for the use of high-resolution models for future studies that aim to predict changes in western boundary current systems and associated biological fields.

 

We investigate how the ocean responds to 10-yr persistent surface heat flux forcing over the subpolar North Atlantic (SPNA) associated with the observed winter NAO in three CMIP6-class coupled models. The experiments reveal a broadly consistent ocean response to the imposed NAO forcing. Positive NAO forcing produces anomalously dense water masses in the SPNA, increasing the southward lower (denser) limb of the Atlantic meridional overturning circulation (AMOC) in density coordinates. The southward propagation of the anomalous dense water generates a zonal pressure gradient overlying the models’ North Atlantic Current that enhances the upper (lighter) limb of the density-space AMOC, increasing the heat and salt transport into the SPNA. However, the amplitude of the thermohaline process response differs substantially between the models. Intriguingly, the anomalous dense-water formation is not primarily driven directly by the imposed flux anomalies, but rather dominated by changes in isopycnal outcropping area and associated changes in surface water mass transformation (WMT) due to the background surface heat fluxes. The forcing initially alters the outcropping area in dense-water formation regions, but WMT due to the background surface heat fluxes through anomalous outcropping area decisively controls the total dense-water formation response and can explain the intermodel amplitude difference. Our study suggests that coupled models can simulate consistent mechanisms and spatial patterns of decadal SPNA variability when forced with the same anomalous buoyancy fluxes, but the amplitude of the response depends on the background states of the models.

 

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.

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. The potential for multiyear prediction of impactful Earthsystem change remains relatively underexplored compared to shorter(subseasonal to seasonal) and longer (decadal) timescales. In this study, weintroduce a new initialized prediction system using the Community EarthSystem Model version 2 (CESM2) that is specifically designed to probepotential and actual prediction skill at lead times ranging from 1 month outto 2 years. The Seasonal-to-Multiyear Large Ensemble (SMYLE) consists of acollection of 2-year-long hindcast simulations, with four initializations peryear from 1970 to 2019 and an ensemble size of 20. A full suite of output isavailable for exploring near-term predictability of all Earth systemcomponents represented in CESM2. We show that SMYLE skill for ElNiño–Southern Oscillation is competitive with other prominent seasonalprediction systems, with correlations exceeding 0.5 beyond a lead time of 12months. A broad overview of prediction skill reveals varying degrees ofpotential for useful multiyear predictions of seasonal anomalies in theatmosphere, ocean, land, and sea ice. The SMYLE dataset, experimentaldesign, model, initial conditions, and associated analysis tools are allpublicly available, providing a foundation for research on multiyearprediction of environmental change by the wider community. 

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. 

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.

 

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.

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.