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W. G. Large and S. G. Yeager

Abstract

Global satellite observations show the sea surface temperature (SST) increasing since the 1970s in all ocean basins, while the net air–sea heat flux Q decreases. Over the period 1984–2006 the global changes are 0.28°C in SST and −9.1 W m−2 in Q, giving an effective air–sea coupling coefficient of −32 W m−2 °C−1. The global response in Q expected from SST alone is determined to be −12.9 W m−2, and the global distribution of the associated coupling coefficient is shown. Typically, about one-half (6.8 W m−2) of this SST effect on heat flux is compensated by changes in the overlying near-surface atmosphere. Slab Ocean Models (SOMs) assume that ocean heating processes do not change from year to year so that a constant annual heat flux would maintain a linear trend in annual SST. However, the necessary 6.1 W m−2 increase is not found in the downwelling longwave and shortwave fluxes, which combined show a −3 W m−2 decrease. The SOM assumptions are revisited to determine the most likely source of the inconsistency with observations of (−12.9 + 6.8 − 3) = −9.1 W m−2. The indirect inference is that diminished ocean cooling due to vertical ocean processes played an important role in sustaining the observed positive trend in global SST from 1984 through 2006, despite the decrease in global surface heat flux. A similar situation is found in the individual basins, though magnitudes differ. A conclusion is that natural variability, rather than long-term climate change, dominates the SST and heat flux changes over this 23-yr period. On shorter time scales the relationship between SST and heat flux exhibits a variety of behaviors.

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Frederic S. Castruccio, Yohan Ruprich-Robert, Stephen G. Yeager, Gokhan Danabasoglu, Rym Msadek, and Thomas L. Delworth

Abstract

Observed September Arctic sea ice has declined sharply over the satellite era. While most climate models forced by observed external forcing simulate a decline, few show trends matching the observations, suggesting either model deficiencies or significant contributions from internal variability. Using a set of perturbed climate model experiments, we provide evidence that atmospheric teleconnections associated with the Atlantic multidecadal variability (AMV) can drive low-frequency Arctic sea ice fluctuations. Even without AMV-related changes in ocean heat transport, AMV-like surface temperature anomalies lead to adjustments in atmospheric circulation patterns that produce similar Arctic sea ice changes in three different climate models. Positive AMV anomalies induce a decrease in the frequency of winter polar anticyclones, which is reflected both in the sea level pressure as a weakening of the Beaufort Sea high and in the surface temperature as warm anomalies in response to increased low-cloud cover. Positive AMV anomalies are also shown to favor an increased prevalence of an Arctic dipole–like sea level pressure pattern in late winter/early spring. The resulting anomalous winds drive anomalous ice motions (dynamic effect). Combined with the reduced winter sea ice formation (thermodynamic effect), the Arctic sea ice becomes thinner, younger, and more prone to melt in summer. Following a phase shift to positive AMV, the resulting atmospheric teleconnections can lead to a decadal ice thinning trend in the Arctic Ocean on the order of 8%–16% of the reconstructed long-term trend, and a decadal trend (decline) in September Arctic sea ice area of up to 21% of the observed long-term trend.

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Gokhan Danabasoglu, Steve G. Yeager, Young-Oh Kwon, Joseph J. Tribbia, Adam S. Phillips, and James W. Hurrell

Abstract

Atlantic meridional overturning circulation (AMOC) variability is documented in the Community Climate System Model, version 4 (CCSM4) preindustrial control simulation that uses nominal 1° horizontal resolution in all its components. AMOC shows a broad spectrum of low-frequency variability covering the 50–200-yr range, contrasting sharply with the multidecadal variability seen in the T85 × 1 resolution CCSM3 present-day control simulation. Furthermore, the amplitude of variability is much reduced in CCSM4 compared to that of CCSM3. Similarities as well as differences in AMOC variability mechanisms between CCSM3 and CCSM4 are discussed. As in CCSM3, the CCSM4 AMOC variability is primarily driven by the positive density anomalies at the Labrador Sea (LS) deep-water formation site, peaking 2 yr prior to an AMOC maximum. All processes, including parameterized mesoscale and submesoscale eddies, play a role in the creation of salinity anomalies that dominate these density anomalies. High Nordic Sea densities do not necessarily lead to increased overflow transports because the overflow physics is governed by source and interior region density differences. Increased overflow transports do not lead to a higher AMOC either but instead appear to be a precursor to lower AMOC transports through enhanced stratification in LS. This has important implications for decadal prediction studies. The North Atlantic Oscillation (NAO) is significantly correlated with the positive boundary layer depth and density anomalies prior to an AMOC maximum. This suggests a role for NAO through setting the surface flux anomalies in LS and affecting the subpolar gyre circulation strength.

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S. G. Yeager, G. Danabasoglu, N. A. Rosenbloom, W. Strand, S. C. Bates, G. A. Meehl, A. R. Karspeck, K. Lindsay, M. C. Long, H. Teng, and N. S. Lovenduski

Abstract

The objective of near-term climate prediction is to improve our fore-knowledge, from years to a decade or more in advance, of impactful climate changes that can in general be attributed to a combination of internal and externally forced variability. Predictions initialized using observations of past climate states are tested by comparing their ability to reproduce past climate evolution with that of uninitialized simulations in which the same radiative forcings are applied. A new set of decadal prediction (DP) simulations has recently been completed using the Community Earth System Model (CESM) and is now available to the community. This new large-ensemble (LE) set (CESM-DPLE) is composed of historical simulations that are integrated forward for 10 years following initialization on 1 November of each year between 1954 and 2015. CESM-DPLE represents the “initialized” counterpart to the widely studied CESM Large Ensemble (CESM-LE); both simulation sets have 40-member ensembles, and they use identical model code and radiative forcings. Comparing CESM-DPLE to CESM-LE highlights the impacts of initialization on prediction skill and indicates that robust assessment and interpretation of DP skill may require much larger ensembles than current protocols recommend. CESM-DPLE exhibits significant and potentially useful prediction skill for a wide range of fields, regions, and time scales, and it shows widespread improvement over simpler benchmark forecasts as well as over a previous initialized system that was submitted to phase 5 of the Coupled Model Intercomparison Project (CMIP5). The new DP system offers new capabilities that will be of interest to a broad community pursuing Earth system prediction research.

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William J. Merryfield, Johanna Baehr, Lauriane Batté, Emily J. Becker, Amy H. Butler, Caio A. S. Coelho, Gokhan Danabasoglu, Paul A. Dirmeyer, Francisco J. Doblas-Reyes, Daniela I. V. Domeisen, Laura Ferranti, Tatiana Ilynia, Arun Kumar, Wolfgang A. Müller, Michel Rixen, Andrew W. Robertson, Doug M. Smith, Yuhei Takaya, Matthias Tuma, Frederic Vitart, Christopher J. White, Mariano S. Alvarez, Constantin Ardilouze, Hannah Attard, Cory Baggett, Magdalena A. Balmaseda, Asmerom F. Beraki, Partha S. Bhattacharjee, Roberto Bilbao, Felipe M. de Andrade, Michael J. DeFlorio, Leandro B. Díaz, Muhammad Azhar Ehsan, Georgios Fragkoulidis, Sam Grainger, Benjamin W. Green, Momme C. Hell, Johnna M. Infanti, Katharina Isensee, Takahito Kataoka, Ben P. Kirtman, Nicholas P. Klingaman, June-Yi Lee, Kirsten Mayer, Roseanna McKay, Jennifer V. Mecking, Douglas E. Miller, Nele Neddermann, Ching Ho Justin Ng, Albert Ossó, Klaus Pankatz, Simon Peatman, Kathy Pegion, Judith Perlwitz, G. Cristina Recalde-Coronel, Annika Reintges, Christoph Renkl, Balakrishnan Solaraju-Murali, Aaron Spring, Cristiana Stan, Y. Qiang Sun, Carly R. Tozer, Nicolas Vigaud, Steven Woolnough, and Stephen Yeager

Abstract

Weather and climate variations on subseasonal to decadal time scales can have enormous social, economic, and environmental impacts, making skillful predictions on these time scales a valuable tool for decision-makers. As such, there is a growing interest in the scientific, operational, and applications communities in developing forecasts to improve our foreknowledge of extreme events. On subseasonal to seasonal (S2S) time scales, these include high-impact meteorological events such as tropical cyclones, extratropical storms, floods, droughts, and heat and cold waves. On seasonal to decadal (S2D) time scales, while the focus broadly remains similar (e.g., on precipitation, surface and upper-ocean temperatures, and their effects on the probabilities of high-impact meteorological events), understanding the roles of internal variability and externally forced variability such as anthropogenic warming in forecasts also becomes important. The S2S and S2D communities share common scientific and technical challenges. These include forecast initialization and ensemble generation; initialization shock and drift; understanding the onset of model systematic errors; bias correction, calibration, and forecast quality assessment; model resolution; atmosphere–ocean coupling; sources and expectations for predictability; and linking research, operational forecasting, and end-user needs. In September 2018 a coordinated pair of international conferences, framed by the above challenges, was organized jointly by the World Climate Research Programme (WCRP) and the World Weather Research Programme (WWRP). These conferences surveyed the state of S2S and S2D prediction, ongoing research, and future needs, providing an ideal basis for synthesizing current and emerging developments in these areas that promise to enhance future operational services. This article provides such a synthesis.

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