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Yang Liu, Jisk Attema, and Wilco Hazeleger

ocean at interannual to decadal time scales ( Dee et al. 2011 ; Ferry et al. 2012a ; Balmaseda et al. 2013 ; Harada et al. 2016 ; Gelaro et al. 2017 ; Carton et al. 2018 ). But the time series are not long enough to account for the multidecadal variability of energy transports, which are of interest to many studies with numerical models. In this paper, for the first time, Bjerknes compensation is studied using multiple atmospheric and oceanic reanalysis datasets. We quantify and intercompare

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

suggests decadal or lower frequency variability. In Fig. 13 the NAO has large variability and perhaps a slight upward trend, but the MHT at 26°N is distinctly lower, with a small downward trend ( Smeed et al. 2018 ), especially relative to the NAO. Given the obvious NAO interannual effects on MHT, we have performed a regression of MHT on the zero-lag NAO index and removed that component from the anomalies in Fig. 12 (see Fig. 15 ). The main reduction in variance is in midlatitudes. For instance

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Elodie Charles, Benoit Meyssignac, and Aurélien Ribes

extent this detrending is removing all the drift in the PIC simulations. In the future, multi-thousand-year PIC simulations should help in addressing this issue. Note that the partial reduction of the degeneracy has been possible because the GHG and OA forcings have different effects over different regions and periods. The trace of these changes is more easily found in the ocean because the ocean variability is slow and has a long memory of past changes (at least over decades to centuries). Because

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

reflected SW TOA flux and net downward SW surface flux are decomposed in terms ATM and SFC contributions in Figs. 4a and 4b , respectively. Substantial interannual variability is observed with standard deviations of 0.64 W m −2 for reflected SW TOA flux and 0.78 W m −2 for net downward SW surface flux. Anomalies after 2014 significantly exceed the 1 σ values following a shift in the sign of the Pacific decadal oscillation index from negative to positive in spring 2014 and the major 2015/16 El Niño

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Kevin E. Trenberth and Yongxin Zhang

extended. Accordingly, the Tasman Sea heat wave in 2015/16 appears to be a fairly singular event whereby the ocean and atmospheric components to the ocean anomalies were acting in consort, whereas more commonly they are not, and the atmospheric effects and other influences are apt to dominate. Similarly, Behrens et al. (2019) found no relationship between the Tasman Sea heat waves and ENSO or the Pacific decadal oscillation while Sloyan and O’Kane (2015) found pronounced decadal variability in the

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

and spatial variability of α , as well as the difference in the monthly climatology associated with two satellite products and from a parameterization commonly used in oceanographic studies. Then, we quantify the uncertainty in the surface heat budget resulting from these differences. While SW down can be measured from radiometers mounted on towers, ships, and buoys, SW up is quite difficult to measure ( Payne 1972 ). Payne (1972) , Jin et al. (2004) , and others have done so but it is more

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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

1. Introduction Knowledge of the total reflected solar radiation (RSR) by Earth is vital for quantification of the global energy budget, and therefore essential for monitoring, predicting and understanding how climate is evolving ( Stephens et al. 2015 ). As a result, broadband (i.e., spectrally integrated) RSR has been observed from satellites by dedicated energy budget missions for decades ( Vonder Haar and Suomi 1971 ; Barkstrom 1984 ; Kyle et al. 1993 ; Wielicki et al. 1996 ; Harries et

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Christopher M. Thomas, Bo Dong, and Keith Haines

measurements ( Roemmich et al. 2015 ) allow long-term oceanic energy storage to be included in a determination of the global energy cycle. Satellite-based turbulent flux products can be used to determine surface latent and sensible heat exchanges. Precipitation fluxes are available from combinations of satellite observations such as that produced in the GPCP project ( Adler et al. 2003 ; Huffman et al. 2009 ). Finally there are over a decade of surface water storage estimates from the GRACE satellites

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Seiji Kato and Fred G. Rose

the result of global annual mean entropy production followed by spatial distribution of the production. a. Global annual mean entropy production Table 1 summarizes computed global mean shortwave and longwave irradiances averaged from July 2005 through June 2015. Because computed TOA irradiances from SYN1deg-Month are not constrained by observed ocean heating rates averaged over a decade by the method discussed in Loeb et al. (2018a) , the net TOA irradiance is 1.3 W m −2 , which is larger than

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

results is the higher total ocean warming rates in the range of 1.1 to 1.6 W m −2 with regard to to the oceanic area north of 70°N (based on 2001–17 estimates in Table A1 ). The additional warming is mainly located in the North Atlantic (not shown), but this seems to be related to decadal variability related to the North Atlantic Oscillation and meridional overturning circulation ( Robson et al. 2012 ). Another feature of the results in appendix A is the slightly larger discrepancies in inferred

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