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  1. Modeled water-mass changes in the North Pacific thermocline, both in the subsurface and at the surface, reveal the impact of the competition between anthropogenic aerosols (AAs) and greenhouse gases (GHGs) over the past 6 decades. The AA effect overwhelms the GHG effect during 1950–1985 in driving salinity changes on density surfaces, while after 1985 the GHG effect dominates. These subsurface water-mass changes are traced back to changes at the surface, of which ~70% stems from the migration of density surface outcrops, equatorward due to regional cooling by AAs and subsequent poleward due to warming by GHGs. Ocean subduction connects these surface outcrop changes to the main thermocline. Both observations and models reveal this transition in climate forcing around 1985 and highlight the important role of AA climate forcing on our oceans’ water masses.

     
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    Free, publicly-accessible full text available September 22, 2024
  2. Abstract

    The observed winter Barents-Kara Sea (BKS) sea ice concentration (SIC) has shown a close association with the second empirical orthogonal function (EOF) mode of Eurasian winter surface air temperature (SAT) variability, known as Warm Arctic Cold Eurasia (WACE) pattern. However, the potential role of BKS SIC on this WACE pattern of variability and on its long-term trend remains elusive. Here, we show that from 1979 to 2022, the winter BKS SIC and WACE association is most prominent and statistically significant for the variability at the sub-decadal time scale for 5–6 years. We also show the critical role of the multi-decadal trend in the principal component of the WACE mode of variability for explaining the overall Eurasian winter temperature trend over the same period. Furthermore, a large multi-model ensemble of atmosphere-only experiments from 1979 to 2014, with and without the observed Arctic SIC forcing, suggests that the BKS SIC variations induce this observed sub-decadal variability and the multi-decadal trend in the WACE. Additionally, we analyse the model simulated first or the leading EOF mode of Eurasian winter SAT variability, which in observations, closely relates to the Arctic Oscillation (AO). We find a weaker association of this mode to AO and a statistically significant positive trend in our ensemble simulation, opposite to that found in observation. This contrasting nature reflects excessive hemispheric warming in the models, partly contributed by the modelled Arctic Sea ice loss.

     
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  3. 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.

     
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  4. Abstract

    During recent decades, both greenhouse gases (GHGs) and anthropogenic aerosols (AAs) drove major changes in the Earth's energy imbalance. However, their respective fingerprints in changes to ocean heat content (OHC) have been difficult to isolate and detect when global or hemispheric averages are used. Based on a pattern recognition analysis, we show that AAs drive an interhemispheric asymmetry within the 20°‐35° latitude band in historical OHC change due to the southward shift of the atmospheric and ocean circulation system. This forced pattern is distinct from the GHG‐induced pattern, which dominates the asymmetry in higher latitudes. Moreover, it is found that this significant aerosol‐forced OHC trend pattern can only be captured in analyzed periods of 20 years or longer and including 1975–1990. Using these distinct spatiotemporal characteristics, we show that the fingerprint of aerosol climate forcing in ocean observations can be distinguished from both the stronger GHG‐induced signals and internal variability.

     
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  5. Key Points The external radiative forcing is the primary driver of the 1979–2013 warming for April–September, with varying decadal warming rates The interdecadal Pacific and Atlantic multidecadal variability intensify/dampen the warming when transitioning to positive/negative phase The combined effects of these factors reproduce the observed varied pace of decadal Arctic troposphere warming during 1979–2013 
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  6. Abstract. The main drivers of the continental Northern Hemisphere snow cover are investigated in the 1979–2014 period. Four observational datasets are usedas are two large multi-model ensembles of atmosphere-only simulations with prescribed sea surface temperature (SST) and sea ice concentration (SIC). Afirst ensemble uses observed interannually varying SST and SIC conditions for 1979–2014, while a second ensemble is identical except for SIC witha repeated climatological cycle used. SST and external forcing typically explain 10 % to 25 % of the snow cover variance in modelsimulations, with a dominant forcing from the tropical and North Pacific SST during this period. In terms of the climate influence of the snow coveranomalies, both observations and models show no robust links between the November and April snow cover variability and the atmospheric circulation1 month later. On the other hand, the first mode of Eurasian snow cover variability in January, with more extended snow over western Eurasia, isfound to precede an atmospheric circulation pattern by 1 month, similar to a negative Arctic oscillation (AO). A decomposition of the variabilityin the model simulations shows that this relationship is mainly due to internal climate variability. Detailed outputs from one of the modelsindicate that the western Eurasia snow cover anomalies are preceded by a negative AO phase accompanied by a Ural blocking pattern and astratospheric polar vortex weakening. The link between the AO and the snow cover variability is strongly related to the concomitant role of thestratospheric polar vortex, with the Eurasian snow cover acting as a positive feedback for the AO variability in winter. No robust influence of theSIC variability is found, as the sea ice loss in these simulations only drives an insignificant fraction of the snow cover anomalies, with fewagreements among models. 
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  7. Abstract

    Separating the climate response to external forcing from internal climate variability is a key challenge. While most previous studies have focused on surface responses, here we examine zonal‐mean patterns of North Pacific subsurface temperature responses. In particular, the changes since 1950 driven by anthropogenic aerosol emissions are found by using a pattern recognition method. Based on the single‐forcing large‐ensemble simulations from two models, we show that aerosol forcing caused a nonmonotonic temporal response and a characteristic zonal‐mean pattern within North Pacific, which is distinct from the pattern associated with internal variability. The aerosol‐forced pattern with the nonmonotonic temporal feature shows a substantial temperature change in subpolar regions and a reversed change on the southern flank of the subtropical gyre. A similar characteristic pattern and nonmonotonic time evolution are extracted from the subsurface observations, which likely reflect the subsurface responses to the aerosol forcing, although differences exist with the simulated responses.

     
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  8. Abstract Large ensemble simulations with six atmospheric general circulation models involved are utilized to verify the interdecadal Pacific oscillation (IPO) impacts on the trend of Eurasian winter surface air temperatures (SAT) during 1998–2013, a period characterized by the prominent Eurasia cooling (EC). In our simulations, IPO brings a cooling trend over west-central Eurasia in 1998–2013, about a quarter of the observed EC in that area. The cooling is associated with the phase transition of the IPO to a strong negative. However, the standard deviation of the area-averaged SAT trends in the west EC region among ensembles, driven by internal variability intrinsic due to the atmosphere and land, is more than three times the isolated IPO impacts, which can shadow the modulation of the IPO on the west Eurasia winter climate. 
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