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Seiji Kato, Norman G. Loeb, John T. Fasullo, Kevin E. Trenberth, Peter H. Lauritzen, Fred G. Rose, David A. Rutan, and Masaki Satoh

l or ice c i , and T w is the wet-bulb temperature. Because the temperature of a raindrop is close to the wet-bulb temperature near the surface ( Gosnell et al. 1995 ; Fairall et al. 1996 ), we use the sea level (2 m) wet-bulb temperature for T w in this study. While enthalpy is transported to the ocean by precipitation at the rate of c w P ˙ ⁡ ( T w − T ¯ ocn ) , enthalpy is also extracted from the atmosphere at the rate of (41) F fallout , atm ≡ − c w P ˙ ⁡ ( T w − T ¯ atm ) , where T

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Michael Mayer, Steffen Tietsche, Leopold Haimberger, Takamasa Tsubouchi, Johannes Mayer, and Hao Zuo

estimates of the long-term mean and annual cycle of the coupled Arctic energy budget, including atmosphere, ocean, and sea ice. They relied on reanalyses and observations as much as possible, but they used data sources that are now partly outdated, and their budget residual is large (see discussion below). Improved estimates of the Arctic energy budget are essential to understand the pronounced warming trend in recent decades, which at the surface is stronger than the global average warming (Arctic

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Norman G. Loeb, Hailan Wang, Fred G. Rose, Seiji Kato, William L. Smith Jr, and Sunny Sun-Mack

, comparisons between model and observed interannual variability in ERB have provided useful insight ( Wong et al. 2006 ; Allan et al. 2014 ; Trenberth et al. 2014 ; Kolly and Huang 2018 ). In the shortwave (SW) region over dark surfaces (e.g., ocean), these model–observation comparisons test the model representation of cloud variations, particularly when the models are forced with observed sea surface temperature and sea ice boundary conditions [e.g., Atmospheric Model Intercomparison Project (AMIP

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Kevin E. Trenberth, Yongxin Zhang, John T. Fasullo, and Lijing Cheng

into the atmosphere with an El Niño event ( Cheng et al. 2019 ). The energy imbalance clearly varies over time ( Trenberth et al. 2014 , 2016 ). The only way to determine the EEI is to perform a detailed inventory of the changes in energy in various forms in the climate system, the dominant component of which is changes in OHC ( von Schuckmann et al. 2016 ). Because of changes in atmospheric temperatures, sea and land ice, land temperatures, and snow and water on land, there is no requirement for

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Kevin E. Trenberth and Yongxin Zhang

. The melting and thawing of sea ice were approximately accounted for. Not properly dealt with were the changes in runoff from land, although the 12-month running mean removes most of those effects. For the Pacific, we integrated southward from the Bering Strait, where through transports are small enough to be neglected, but could be considered. However, the Indian and Pacific Oceans were combined because of their connection through the Indonesian region, called the Indonesian Throughflow (ITF). In

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Jake J. Gristey, J. Christine Chiu, Robert J. Gurney, Keith P. Shine, Stephan Havemann, Jean-Claude Thelen, and Peter G. Hill

, https://doi.org/10.1029/1998GL900056 . 10.1029/1998GL900056 Harries , J. E. , and Coauthors , 2005 : The Geostationary Earth Radiation Budget Project . Bull. Amer. Meteor. Soc. , 86 , 945 – 960 , https://doi.org/10.1175/BAMS-86-7-945 . 10.1175/BAMS-86-7-945 Hartmann , D. L. , and P. Ceppi , 2014 : Trends in the CERES dataset, 2000–13: The effects of sea ice and jet shifts and comparison to climate models . J. Climate , 27 , 2444 – 2456 , https://doi.org/10.1175/JCLI-D-13

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Yang Liu, Jisk Attema, and Wilco Hazeleger

circulation (AMOC). Moreover, they argued that there is a link between compensation and the variability of the Arctic sea ice. Van der Linden et al. (2016) demonstrated that the link between sea ice cover variations in the Barents Sea and ocean–atmosphere heat exchanges originates from the low-frequency changes in the ocean, which supports the statement from Van der Swaluw et al. (2007) about the link between sea ice and Bjerknes compensation. Jungclaus and Koenigk (2010) investigated Bjerknes

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Christopher M. Thomas, Bo Dong, and Keith Haines

Ocean Reanalysis 4 (UR025.4; Haines et al. 2012 ), and Global Ocean Reanalysis 2 (GLORYS2v4; Ferry et al. 2012 ). Each reanalysis was produced using the ocean model NEMO v3 coupled to the Louvain-la-Neuve sea ice model (LIM) v2 with a model resolution of 0.25°. All products assimilated sea surface temperature (in situ observations, satellite data, or both), sea level from satellite altimetry, subsurface temperature and salinity profiles, and sea ice concentration, together with atmospheric forcing

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Tristan S. L’Ecuyer, Yun Hang, Alexander V. Matus, and Zhien Wang

effects of different cloud types. Here we find that cloud heating reaches a peak of more than 20 W m −2 over the Southern Hemisphere sea ice at 65°S before decreasing substantially over the interior of the Antarctic ice sheet. Conversely, clouds are found to warm the Arctic in winter by a more uniform 15 W m −2 poleward of 60°N. Globally, stratocumulus and multilayered clouds contribute nearly equally to net CRE at the TOA, each imparting a large net cooling to Earth’s energy budget. This can be

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Allison Hogikyan, Meghan F. Cronin, Dongxiao Zhang, and Seiji Kato

.1175/1520-0477(1996)077<0853:CATERE>2.0.CO;2 Wild , M. , D. Folini , C. Schär , N. Loeb , E. Dutton , and G. König-Langlo , 2013 : The global energy balance from a surface perspective . Climate Dyn. , 40 , 3107 – 3134 , https://doi.org/10.1007/s00382-012-1569-8 . 10.1007/s00382-012-1569-8 Yu , L. , and R. A. Weller , 2007 : Objectively analyzed air–sea heat fluxes for the global ice-free oceans (1981–2005) . Bull. Amer. Meteor. Soc. , 88 , 527 – 540 , https://doi.org/10.1175/BAMS-88-4-527 . 10

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