Sensitivity of Global Upper-Ocean Heat Content Estimates to Mapping Methods, XBT Bias Corrections, and Baseline Climatologies*

Boyer, Tim; Domingues, Catia M.; Good, Simon; Johnson, Gregory C.; Lyman, John M.; Ishii, Masayoshi; Gouretski, Viktor; Willis, Josh; Antonov, John I.; Wijffels, Susan E.; Church, John A.; Cowley, Rebecca; Bindoff, Nathaniel L.

doi:10.1175/jcli-d-15-0801.1

Cited by 100 publications

(157 citation statements)

References 77 publications

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“…These bias corrections were used in addition to the common bias correction (Hanawa et al 1995) which is not time-varying. XBT biases are one of major sources of uncertainty in OHC estimation (Lyman et al 2010;Boyer et al 2016). Three time-varying bias corrections reduced the biases efficiently as reported by the above-listed literature.…”

Section: Uncertainties In Global Mean Temperaturesmentioning

confidence: 72%

“…The current global OHC estimations range widely between various centers and institutes (Smith and Murphy 2007;Palmer et al 2007;Domingues et al 2008;Ishii and Kimoto 2009;Levitus et al 2009). This is intrinsically due to ocean data sparseness, and the estimates are accordingly affected by different methodologies (Boyer et al 2016). An accurate OHC estimation is needed for understanding the global energy balance (Murphy et al 2009), sea level budget (Lombard et al 2005;Cazenave and Llovel 2010), and earth system modeling (Watanabe et al 2010;Yukimoto et al 2012) for future climate predictions.…”

Section: Introductionmentioning

confidence: 99%

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Accuracy of Global Upper Ocean Heat Content Estimation Expected from Present Observational Data Sets

Ishii¹,

Fukuda

Hirahara

et al. 2017

SOLA

Self Cite

144

153

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The simplest global mapping method and dense data coverage for the global oceans by the latest observation network ensure an estimate of global ocean heat content (OHC) within a satisfactory uncertainty for the last 60 years. The observational database conditionally presented a level high enough for practical use for the global OHC estimation when applying bias corrections of expendable bathythermograph, assuming that the other severe observational biases are not included in the database. Uncertainties in annual global mean temperatures averaged vertically from the surface to 1,500 m are within 0.01 K for the period from 1955 onward, when only sampling errors are taken into account. Those in annual mean global OHC of an improved objective analysis for 0−1,500 m depth is 16ZJ on average throughout the period. Compared to previous studies, the new objective analysis provides a higher estimation of the global 0−1,500 m OHC trend for a longer period from 1955 to 2015, which is an increase of 350 ± 57ZJ with a 95% confidence interval.(Citation: Ishii, M., Y. Fukuda, H. Hirahara, S. Yasui, T. Suzuki, and K. Sato, 2017: Accuracy of global upper ocean heat content estimation expected from present observational data sets.

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Section: Uncertainties In Global Mean Temperaturesmentioning

confidence: 72%

Section: Introductionmentioning

confidence: 99%

Accuracy of Global Upper Ocean Heat Content Estimation Expected from Present Observational Data Sets

Ishii¹,

Fukuda

Hirahara

et al. 2017

SOLA

Self Cite

144

153

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“…As a result, estimates of OHC change that extend back to the midtwentieth century tend to be limited to the 0-700 m layer, which represents only the upper 20% of the average open ocean depth. Intercomparisons of upper ocean OHC change time series from both statistical approaches [5,25,[27][28][29] and ocean data assimilation models [30][31][32] have shown large variations among the estimates in terms of both multidecadal trends and interannual variations. As discussed by Palmer et al [29], differences among OHC change estimates essentially arise from three sources: (1) input data and quality control, (2) correction of inter-platform data biases and (3) the mapping method used to infill data.…”

Section: Estimates Of Ocean Heating Ratesmentioning

confidence: 99%

“…As discussed by Palmer et al [29], differences among OHC change estimates essentially arise from three sources: (1) input data and quality control, (2) correction of inter-platform data biases and (3) the mapping method used to infill data. Elements (2) and (3) have emerged as the leading uncertainty terms in estimates of OHC change [27,28] and are the focus of the discussion for the rest of this section. Exploring the impact of (1) on OHC estimates remains an outstanding research challenge, and insights may be offered by the ongoing intercomparison of automated quality control checks under the International Quality Controlled Database initiative (IQuOD; [33]).…”

Section: Estimates Of Ocean Heating Ratesmentioning

confidence: 99%

Reconciling Estimates of Ocean Heating and Earth’s Radiation Budget

Palmer

2017

Curr Clim Change Rep

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Purpose of review The purpose of this review is to summarise the recent literature and scientific challenges on the topic of reconciling estimates of ocean heating rates with satellite-based monitoring of Earth's radiation budget (ERB), including discussion of the satellite record and in situ ocean observing system. Recent findings State-of-the-art climate model simulations suggest that the global ocean becomes the dominant term the planetary heat budget on annual and longer timescales. Therefore, we expect to see a close correspondence between year-to-year variations in ocean heating rates and satellite measurements of ERB. Recent comparisons of satellite ERB time series and ocean heating rates show a marked improvement over earlier studies in terms of consistency and specification of uncertainties. Contemporary research has also emphasised the utility of these independent data sets for cross validation of the climate record and their fundamental importance for monitoring the rate of climate change. Summary Anthropogenic greenhouse gas emissions have brought about an imbalance in Earth's radiation budget that is driving global climate change. Our primary means for monitoring this energy imbalance is via direct satellite measurements of ERB and through estimates of global ocean heat content (OHC) change. CERES satellite measurements of ERB offer high spatiotemporal resolution and uncertainties on annual time series of order 0.1 Wm -2 but cannot provide absolute monitoring of Earth's energy imbalance due to limitations in sensor calibration. The Argo array of autonomous profiling floats has revolutionised the ocean observing system and our ability to estimate absolute ocean heating rates with current uncertainties estimated to be 0.5/0.1 Wm -2 on annual/ decadal timescales. These ocean observations are essential to "anchor" the time series of ERB and can be used to mitigate satellite sensor drifts. Sustaining these highly complementary elements of the climate observing system is essential for improved understanding of climate variability and change. Improvements in satellite sensor calibration, estimates of total solar irradiance and more comprehensive sampling of the global oceans (e.g. Deep Argo) are key aspects to reducing uncertainties in future observations of Earth's energy imbalance.

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“…There is a substantial literature on the accuracy and precision of ocean instrumentation (e.g., Gouretski and Koltermann (2007), 30 Abraham et al (2013), Boyer et al (2016)). Here, our focus is on the role of sampling and mapping methods, and we assume the observations are perfect.…”

Section: Previous Uncertainty Estimatesmentioning

confidence: 99%

An Ensemble Observing System Simulation Experiment of Global Ocean Heat Content Variability

Nelson

Weiss

Fox‐Kemper

et al. 2017

Preprint

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Abstract. We quantify skill and uncertainty in observing the statistics of natural variability using observing system simulation experiments on an ensemble of climate simulations and an observing strategy of in situ measurements and objective mapping. for the fact that the real ocean is more variable than the model, root mean square errors in observing the annual-running mean 10 natural variability of the global ocean heat content are estimated to be 6.2 ZJ for the pre-Argo era (1990)(1991)(1992)(1993)(1994)(1995)(1996)(1997)(1998)(1999)(2000)(2001)(2002)(2003)(2004)(2005) and 2.1 ZJ for the Argo era (2005)(2006)(2007)(2008)(2009)(2010)(2011)(2012)(2013) with relative signal-to-noise ratios of 1.9 and 14.7. Combining the estimated, scaled uncertainties of the observing strategy with its estimated trend, the 1990-2013 trend in global ocean heat content is found to be 5.3 ± 1.0 ZJ/yr.

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Sensitivity of Global Upper-Ocean Heat Content Estimates to Mapping Methods, XBT Bias Corrections, and Baseline Climatologies*

Cited by 100 publications

References 77 publications

Accuracy of Global Upper Ocean Heat Content Estimation Expected from Present Observational Data Sets

Accuracy of Global Upper Ocean Heat Content Estimation Expected from Present Observational Data Sets

Reconciling Estimates of Ocean Heating and Earth’s Radiation Budget

An Ensemble Observing System Simulation Experiment of Global Ocean Heat Content Variability

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