Abstract We examine the 1979–2014 Southern Ocean (SO) sea surface temperature (SST) trends simulated in an ensemble of coupled general circulation models and evaluate possible causes of the models' inability to reproduce the observed 1979–2014 SO cooling. For each model we estimate the response of SO SST to step changes in greenhouse gas (GHG) forcing and in the seasonal indices of the Southern Annular Mode (SAM). Using these step‐response functions, we skillfully reconstruct the models' 1979–2014 SO SST trends. Consistent with the seasonal signature of the Antarctic ozone hole and the seasonality of SO stratification, the summer and fall SAM exert a large impact on the simulated SO SST trends. We further identify conditions that favor multidecadal SO cooling: (1) a weak SO warming response to GHG forcing, (2) a strong multidecadal SO cooling response to a positive SAM trend, and (3) a historical SAM trend as strong as in observations.
Abstract Ocean heat transport (OHT) plays a key role in climate and its variability. Here, we identify modes of low-frequency North Atlantic OHT variability by applying a low-frequency component analysis (LFCA) to output from three global climate models. The first low-frequency component (LFC), computed using this method, is an index of OHT variability that maximizes the ratio of low-frequency variance (occurring at decadal and longer timescales) to total variance. Lead-lag regressions of atmospheric and ocean variables onto the LFC timeseries illuminate the dominant mechanisms controlling low-frequency OHT variability. Anomalous northwesterly winds from eastern North America over the North Atlantic act to increase upper ocean density in the Labrador Sea region, enhancing deep convection, which later increases OHT via changes in the strength of the Atlantic Meridional Overturning Circulation (AMOC). The strengthened AMOC carries warm, salty water into the subpolar gyre, reducing deep convection and weakening AMOC and OHT. This mechanism, where changes in AMOC and OHT are driven primarily by changes in Labrador Sea deep convection, holds not only in models where the climatological (i.e., time-mean) deep convection is concentrated in the Labrador Sea, but also in models where the climatological deep convection is concentrated in the Greenland-Iceland-Norwegian (GIN) Seas or the Irminger and Iceland Basins. These results suggest that despite recent observational evidence suggesting that the Labrador Sea plays a minor role in driving the climatological AMOC, the Labrador Sea may still play an important role in driving low-frequency variability in AMOC and OHT.
Arctic surface warming under greenhouse gas forcing peaks in early winter and reaches its minimum during summer in both observations and model projections. Many mechanisms have been proposed to explain this seasonal asymmetry, but disentangling these processes remains a challenge in the interpretation of general circulation model (GCM) experiments. To isolate these mechanisms, we use an idealized single-column sea ice model (SCM) which captures the seasonal pattern of Arctic warming. SCM experiments demonstrate that as sea ice melts and exposes open ocean, the accompanying increase in effective surface heat capacity can alone produce the observed pattern of peak early winter warming by slowing the seasonal heating and cooling rate, thus delaying the phase and reducing the amplitude of the seasonal cycle of surface temperature. To investigate warming seasonality in more complex models, we perform GCM experiments that individually isolate sea-ice albedo and thermodynamic effects under CO2 forcing. These also show a key role for the effective heat capacity of sea ice in promoting seasonal asymmetry through suppressing summer warming, in addition to precluding summer climatological inversions and a positive summer lapse-rate feedback. Peak winter warming in GCM experiments is further supported by a positive winter lapse-rate feedback that persists with only the albedo effects of sea-ice loss prescribed, due to cold initial surface temperatures and strong surface-trapped warming. While many factors support peak early winter warming as Arctic sea ice declines, these results highlight changes in effective surface heat capacity as a central mechanism contributing to this seasonality.
Abstract Eight atmospheric general circulation models (AGCMs) are forced with observed historical (1871–2010) monthly sea surface temperature and sea ice variations using the Atmospheric Model Intercomparison Project II data set. The AGCMs therefore have a similar temperature pattern and trend to that of observed historical climate change. The AGCMs simulate a spread in climate feedback similar to that seen in coupled simulations of the response to CO 2 quadrupling. However, the feedbacks are robustly more stabilizing and the effective climate sensitivity (EffCS) smaller. This is due to a pattern effect , whereby the pattern of observed historical sea surface temperature change gives rise to more negative cloud and longwave clear‐sky feedbacks. Assuming the patterns of long‐term temperature change simulated by models, and the radiative response to them, are credible; this implies that existing constraints on EffCS from historical energy budget variations give values that are too low and overly constrained, particularly at the upper end. For example, the pattern effect increases the long‐term Otto et al. (2013, https://doi.org/10.1038/ngeo1836 ) EffCS median and 5–95% confidence interval from 1.9 K (0.9–5.0 K) to 3.2 K (1.5–8.1 K).
Abstract The observed partitioning of poleward heat transport between atmospheric and oceanic heat transports (AHT and OHT) is compared to that in coupled climate models. Model ensemble mean poleward OHT is biased low in both hemispheres, with the largest biases in the Southern Hemisphere extratropics. Poleward AHT is biased high in the Northern Hemisphere, especially in the vicinity of the peak AHT near 40°N. The significant model biases are persistent across three model generations (CMIP3, CMIP5, CMIP6) and are insensitive to the satellite radiation and atmospheric reanalyzes products used to derive observational estimates of AHT and OHT. Model biases in heat transport partitioning are consistent with biases in the spatial structure of energy input to the ocean and atmosphere. Specifically, larger than observed model evaporation in the tropics adds excess energy to the atmosphere that drives enhanced poleward AHT at the expense of weaker OHT.
Earth and Space Science Open Archive This preprint has been submitted to and is under consideration at Journal of Geophysical Research - Oceans. ESSOAr is a venue for early communication or feedback before peer review. Data may be preliminary.Learn more about preprints preprintOpen AccessYou are viewing the latest version by default [v3]Resolution Dependence of Atmosphere–Ocean Interactions and Water Mass Transformation in the North AtlanticAuthorsDylan Charles ShambanOldenburgiDRobert C. J.WillsiDKyleArmourLuAnneThompsoniDSee all authors Dylan Charles Shamban OldenburgiDCorresponding Author• Submitting AuthorUniversity of WashingtoniDhttps://orcid.org/0000-0002-7891-4721view email addressThe email was not providedcopy email addressRobert C. J. WillsiDUniversity of WashingtoniDhttps://orcid.org/0000-0002-7776-2076view email addressThe email was not providedcopy email addressKyle ArmourUniversity of Washingtonview email addressThe email was not providedcopy email addressLuAnne ThompsoniDUniversity of WashingtoniDhttps://orcid.org/0000-0001-8295-0533view email addressThe email was not providedcopy email address
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