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1. Atlantic Multidecadal Variability and Associated Climate Impacts Initiated by Ocean Thermohaline Dynamics

   https://doi.org/10.1175/JCLI-D-19-0530.1  

   Kim, Who M. ; Yeager, Stephen ; Danabasoglu, Gokhan ( January 2020 , Journal of Climate)

   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.
2. Origins of Barents-Kara sea-ice interannual variability modulated by the Atlantic pathway of El Niño–Southern Oscillation

   https://doi.org/10.1038/s41467-023-36136-5  

   Luo, Binhe ; Luo, Dehai ; Ge, Yao ; Dai, Aiguo ; Wang, Lin ; Simmonds, Ian ; Xiao, Cunde ; Wu, Lixin ; Yao, Yao ( December 2023 , Nature Communications)

   Abstract Winter Arctic sea-ice concentration (SIC) decline plays an important role in Arctic amplification which, in turn, influences Arctic ecosystems, midlatitude weather and climate. SIC over the Barents-Kara Seas (BKS) shows large interannual variations, whose origin is still unclear. Here we find that interannual variations in winter BKS SIC have significantly strengthened in recent decades likely due to increased amplitudes of the El Niño-Southern Oscillation (ENSO) in a warming climate. La Niña leads to enhanced Atlantic Hadley cell and a positive phase North Atlantic Oscillation-like anomaly pattern, together with concurring Ural blocking, that transports Atlantic ocean heat and atmospheric moisture toward the BKS and promotes sea-ice melting via intensified surface warming. The reverse is seen during El Niño which leads to weakened Atlantic poleward transport and an increase in the BKS SIC. Thus, interannual variability of the BKS SIC partly originates from ENSO via the Atlantic pathway.
3. RARE: The Regional Arctic Reanalysis

   https://doi.org/10.1175/JCLI-D-22-0340.1  

   Carton, James A. ; Chepurin, Gennady A. ( April 2023 , Journal of Climate)

   This paper describes the new Regional Arctic Ocean/sea ice Reanalysis (RARE) with a domain that spans a subpolar/polar cap poleward of 45°N. Sequential data assimilation constrains temperature and salinity using World Ocean Database profiles as well as in situ and satellite SST, and PIOMAS sea ice thickness estimates. The 41-yr (1980–2020) RARE1.15.2 reanalysis with resolution varying between 2 and 5 km horizontally and 1–10 m vertically in the upper 100 m is examined. To explore the impact of resolution RARE1.15.2 is compared to a coarser-resolution SODA3.15.2, which uses the same modeling and data assimilation system. Improving resolution in the reanalysis system improves agreement with observations. It produces stronger more compact currents, enhances eddy kinetic energy, and strengthens along-isopycnal heat and salt transports, but reduces vertical exchanges and thus strengthens upper ocean haline stratification. RARE1.15.2 and SODA3.15.2 are also compared to the Hadley Center EN4.2.2 statistical objective analysis. In regions of reasonable data coverage such as the Nordic seas the three products produce similar time-mean distributions of temperature and salinity. But in regions of poor coverage and in regions where the coverage changes in time EN4.2.2 suffers more from those inhomogeneities. Finally, the impact on the Arctic of interannual temperaturemore »fluctuations in the subpolar gyres on the Arctic Ocean is compared. The influence of the subpolar North Pacific is limited to a region surrounding Bering Strait. The influence of the subpolar North Atlantic, in contrast, spreads throughout the Nordic seas and Barents Sea in all three products within two years.

   The Arctic Ocean/sea ice system plays crucial roles in climate variability and change by controlling the northern end of the oceanic overturning circulation, the equator to pole air pressure gradient, and Earth’s energy balance. Yet the historical ocean observation set is sparse and inhomogeneous, while ocean dynamics has challengingly fine horizontal and vertical scales. This paper introduces a new Regional Arctic Ocean/sea ice Reanalysis (RARE) whose goal is to use the combined constraints of mesoscale ocean dynamics, historical observations, surface meteorology, and continental runoff in a data assimilation framework to reconstruct historical variability. RARE is used to produce a 41-yr ocean/sea ice reanalysis 1980–2020 whose results are described here.

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4. 100 Years of Progress in Understanding the Dynamics of Coupled Atmosphere–Ocean Variability

   https://doi.org/10.1175/AMSMONOGRAPHS-D-18-0025.1  

   Battisti, David S. ; Vimont, Daniel J. ; Kirtman, Benjamin P. ( October 2019 , Meteorological Monographs)

   In situ observation networks and reanalyses products of the state of the atmosphere and upper ocean show well-defined, large-scale patterns of coupled climate variability on time scales ranging from seasons to several decades. We summarize these phenomena and their physics, which have been revealed by analysis of observations, by experimentation with uncoupled and coupled atmosphere and ocean models with a hierarchy of complexity, and by theoretical developments. We start with a discussion of the seasonal cycle in the equatorial tropical Pacific and Atlantic Oceans, which are clearly affected by coupling between the atmosphere and the ocean. We then discuss the tropical phenomena that only exist because of the coupling between the atmosphere and the ocean: the Pacific and Atlantic meridional modes, the El Niño–Southern Oscillation (ENSO) in the Pacific, and a phenomenon analogous to ENSO in the Atlantic. For ENSO, we further discuss the sources of irregularity and asymmetry between warm and cold phases of ENSO, and the response of ENSO to forcing. Fundamental to variability on all time scales in the midlatitudes of the Northern Hemisphere are preferred patterns of uncoupled atmospheric variability that exist independent of any changes in the state of the ocean, land, or distributionmore »of sea ice. These patterns include the North Atlantic Oscillation (NAO), the North Pacific Oscillation (NPO), and the Pacific–North American (PNA) pattern; they are most active in wintertime, with a temporal spectrum that is nearly white. Stochastic variability in the NPO, PNA, and NAO force the ocean on days to interannual times scales by way of turbulent heat exchange and Ekman transport, and on decadal and longer time scales by way of wind stress forcing. The PNA is partially responsible for the Pacific decadal oscillation; the NAO is responsible for an analogous phenomenon in the North Atlantic subpolar gyre. In models, stochastic forcing by the NAO also gives rise to variability in the strength of the Atlantic meridional overturning circulation (AMOC) that is partially responsible for multidecadal anomalies in the North Atlantic climate known as the Atlantic multidecadal oscillation (AMO); observations do not yet exist to adequately determine the physics of the AMO. We review the progress that has been made in the past 50 years in understanding each of these phenomena and the implications for short-term (seasonal-to-interannual) climate forecasts. We end with a brief discussion of advances of things that are on the horizon, under the rug, and over the rainbow.

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5. Projected Changes in Daily Variability and Seasonal Cycle of Near-Surface Air Temperature over the Globe during the Twenty-First Century

   https://doi.org/10.1175/JCLI-D-19-0438.1  

   Chen, Jiao ; Dai, Aiguo ; Zhang, Yaocun ( November 2019 , Journal of Climate)

   Increases in atmospheric greenhouse gases will not only raise Earth’s temperature but may also change its variability and seasonal cycle. Here CMIP5 model data are analyzed to quantify these changes in surface air temperature (Tas) and investigate the underlying processes. The models capture well the mean Tas seasonal cycle and variability and their changes in reanalysis, which shows decreasing Tas seasonal amplitudes and variability over the Arctic and Southern Ocean from 1979 to 2017. Daily Tas variability and seasonal amplitude are projected to decrease in the twenty-first century at high latitudes (except for boreal summer when Tas variability increases) but increase at low latitudes. The day of the maximum or minimum Tas shows large delays over high-latitude oceans, while it changes little at low latitudes. These Tas changes at high latitudes are linked to the polar amplification of warming and sea ice loss, which cause larger warming in winter than summer due to extra heating from the ocean during the cold season. Reduced sea ice cover also decreases its ability to cause Tas variations, contributing to the decreased Tas variability at high latitudes. Over low–midlatitude oceans, larger increases in surface evaporation in winter than summer (due to strong wintermore »winds, strengthened winter winds in the Southern Hemisphere, and increased winter surface humidity gradients over the Northern Hemisphere low latitudes), coupled with strong ocean mixing in winter, lead to smaller surface warming in winter than summer and thus increased seasonal amplitudes there. These changes result in narrower (wider) Tas distributions over the high (low) latitudes, which may have important implications for other related fields.

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