Estimating global ocean heat content from tidal magnetic satellite observations

AbstractThe historical evolution of Earth’s energy imbalance can be quantified by changes in the global ocean heat content. However, historical reconstructions of ocean heat content often neglect a large volume of the deep ocean, due to sparse observations of ocean temperatures below 2000 m. Here, we provide a global reconstruction of historical changes in full-depth ocean heat content based on interpolated subsurface temperature data using an autoregressive artificial neural network, providing estimates of total ocean warming for the period 1946-2019. We find that cooling of the deep ocean and a small heat gain in the upper ocean led to no robust trend in global ocean heat content from 1960-1990, implying a roughly balanced Earth energy budget within −0.16 to 0.06 W m−2 over most of the latter half of the 20th century. However, the past three decades have seen a rapid acceleration in ocean warming, with the entire ocean warming from top to bottom at a rate of 0.63 ± 0.13 W m−2. These results suggest a delayed onset of a positive Earth energy imbalance relative to previous estimates, although large uncertainties remain.

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Estimating Global Ocean Heat Content Changes in the Upper 1800 m since 1950 and the Influence of Climatology Choice*

Journal of Climate ◽

10.1175/jcli-d-12-00752.1 ◽

2014 ◽

Vol 27 (5) ◽

pp. 1945-1957 ◽

Cited By ~ 55

Author(s):

John M. Lyman ◽

Gregory C. Johnson

Keyword(s):

Heat Content ◽

Ocean Heat Content ◽

Global Ocean ◽

Ocean Temperature ◽

Vertical Separation ◽

Ocean Heat Uptake ◽

Expendable Bathythermograph ◽

Heat Uptake ◽

The Mean

Abstract Ocean heat content anomalies are analyzed from 1950 to 2011 in five distinct depth layers (0–100, 100–300, 300–700, 700–900, and 900–1800 m). These layers correspond to historic increases in common maximum sampling depths of ocean temperature measurements with time, as different instruments—mechanical bathythermograph (MBT), shallow expendable bathythermograph (XBT), deep XBT, early sometimes shallower Argo profiling floats, and recent Argo floats capable of worldwide sampling to 2000 m—have come into widespread use. This vertical separation of maps allows computation of annual ocean heat content anomalies and their sampling uncertainties back to 1950 while taking account of in situ sampling advances and changing sampling patterns. The 0–100-m layer is measured over 50% of the globe annually starting in 1956, the 100–300-m layer starting in 1967, the 300–700-m layer starting in 1983, and the deepest two layers considered here starting in 2003 and 2004, during the implementation of Argo. Furthermore, global ocean heat uptake estimates since 1950 depend strongly on assumptions made concerning changes in undersampled or unsampled ocean regions. If unsampled areas are assumed to have zero anomalies and are included in the global integrals, the choice of climatological reference from which anomalies are estimated can strongly influence the global integral values and their trend: the sparser the sampling and the bigger the mean difference between climatological and actual values, the larger the influence.

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Monitoring the Ocean Heat Content and the Earth Energy imbalance from space altimetry and space gravimetry: the MOHeaCAN product

10.5194/egusphere-egu21-1225 ◽

2021 ◽

Author(s):

Marti Florence ◽

Ablain Michaël ◽

Fraudeau Robin ◽

Jugier Rémi ◽

Meyssignac Benoît ◽

...

Keyword(s):

Time Scales ◽

Radiant Energy ◽

Heat Content ◽

Ocean Heat Content ◽

Global Ocean ◽

Argo Data ◽

Data Set ◽

Energy Imbalance ◽

Temporal Sampling ◽

The Earth

The Earth Energy Imbalance (EEI) is a key indicator to understand climate change. However, measuring this indicator is challenging since it is a globally integrated variable whose variations are small, of the order of several tenth of W.m-2, compared to the amount of energy entering and leaving the climate system of ~340 W.m-2. Recent studies suggest that the EEI response to anthropogenic GHG and aerosols emissions is 0.5-1 W.m-2. It implies that an accuracy of <0.3 W.m-2 at decadal time scales is necessary to evaluate the long term mean EEI associated with anthropogenic forcing. Ideally an accuracy of <0.1 W.m-2 at decadal time scales is desirable if we want to monitor future changes in EEI.In the frame of the MOHeaCAN project supported by ESA, the EEI indicator is deduced from the global change in Ocean Heat Content (OHC) which is a very good proxy of the EEI since the ocean stores 93% of the excess of heat&#160; gained by the Earth in response to EEI. The OHC is estimated from space altimetry and gravimetry missions (GRACE). This &#8220;Altimetry-Gravimetry'' approach is promising because it provides consistent spatial and temporal sampling of the ocean, it samples nearly the entire global ocean, except for polar regions, and it provides estimates of the OHC over the ocean&#8217;s entire depth. Consequently, it complements the OHC estimation from the ARGO network.&#160;The MOHeaCAN product contains monthly time series (between August 2002 and June 2017) of several variables, the main ones being the regional OHC (3&#176;x3&#176; spatial resolution grids), the global OHC and the EEI indicator. Uncertainties are provided for variables at global scale, by propagating errors from sea level measurements (altimetry) and ocean mass content (gravimetry). In order to calculate OHC at regional and global scales, a new estimate of the expansion efficiency of heat at global and regional scales have been performed based on the global ARGO network.&#160;A scientific validation of the MOHeaCAN product has also been carried out performing thorough comparisons against independent estimates based on ARGO data and on the Clouds and the Earth&#8217;s Radiant energy System (CERES) measurements at the top of the atmosphere. The mean EEI derived from MOHeaCAN product is 0.84 W.m-2 over the whole period within an uncertainty of &#177;0.12 W.m-2 (68% confidence level - 0.20 W.m-2 at the 90% CL). This figure is in agreement (within error bars at the 90% CL) with other EEI indicators based on ARGO data (e.g. OHC-OMI from CMEMS) although the best estimate is slightly higher. Differences from annual to inter-annual scales have also been observed with ARGO and CERES data. Investigations have been conducted to improve our understanding of the benefits and limitations of each data set to measure EEI at different time scales.The MOHeaCAN product from &#8220;altimetry-gravimetry&#8221; is now available and can be downloaded at https://doi.org/10.24400/527896/a01-2020.003. Feedback from interested users on this product are welcome.

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Observational Constraint on Greenhouse Gas and Aerosol Contributions to Global Ocean Heat Content Changes

Journal of Climate ◽

10.1175/jcli-d-19-0091.1 ◽

2020 ◽

Vol 33 (24) ◽

pp. 10579-10591

Author(s):

Elodie Charles ◽

Benoit Meyssignac ◽

Aurélien Ribes

Keyword(s):

Greenhouse Gas ◽

Radiative Forcing ◽

Climate Models ◽

Ghg Emissions ◽

Heat Content ◽

Ocean Heat Content ◽

Global Ocean ◽

Detection And Attribution ◽

Aerosol Forcing ◽

Bivariate Method

AbstractObservations and climate models are combined to identify an anthropogenic warming signature in the upper ocean heat content (OHC) changes since 1971. We apply a new detection and attribution analysis developed by Ribes et al. that uses a symmetric treatment of the magnitude and the pattern of the climate response to each radiative forcing. A first estimate of the OHC response to natural, anthropogenic, greenhouse gas, and other forcings is derived from a large ensemble of CMIP5 simulations. Observational datasets from historical reconstructions are then used to constrain this estimate. A spatiotemporal observational mask is applied to compare simulations with actual observations and to overcome reconstruction biases. Results on the 0–700-m layer from 1971 to 2005 show that the global OHC would have increased since 1971 by 2.12 ± 0.21 × 107 J m−2 yr−1 in response to GHG emissions alone. But this has been compensated for by other anthropogenic influences (mainly aerosol), which induced an OHC decrease of 0.84 ± 0.18 × 107 J m−2 yr−1. The natural forcing has induced a slight global OHC decrease since 1971 of 0.13 ± 0.09 × 107 J m−2 yr−1. Compared to previous studies we have separated the effect of the GHG forcing from the effect of the other anthropogenic forcing on OHC changes. This has been possible by using a new detection and attribution (D&A) method and by analyzing simultaneously the global OHC trends over 1957–80 and over 1971–2005. This bivariate method takes advantage of the different time variation of the GHG forcing and the aerosol forcing since 1957 to separate both effects and reduce the uncertainty in their estimates.

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Measuring Global Ocean Heat Content to Estimate the Earth Energy Imbalance

Frontiers in Marine Science ◽

10.3389/fmars.2019.00432 ◽

2019 ◽

Vol 6 ◽

Cited By ~ 26

Author(s):

Benoit Meyssignac ◽

Tim Boyer ◽

Zhongxiang Zhao ◽

Maria Z. Hakuba ◽

Felix W. Landerer ◽

...

Keyword(s):

Heat Content ◽

Ocean Heat Content ◽

Global Ocean ◽

Energy Imbalance ◽

The Earth

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OPEN: A New Estimation of Global Ocean Heat Content for Upper 2000 Meters from Remote Sensing Data

Remote Sensing ◽

10.3390/rs12142294 ◽

2020 ◽

Vol 12 (14) ◽

pp. 2294

Author(s):

Hua Su ◽

Haojie Zhang ◽

Xupu Geng ◽

Tian Qin ◽

Wenfang Lu ◽

...

Keyword(s):

Neural Network ◽

Remote Sensing ◽

Network Architecture ◽

Climate Changes ◽

Heat Content ◽

Remote Sensing Data ◽

Ocean Heat Content ◽

Global Ocean ◽

Coefficient Of Determination ◽

Sensing Data

Retrieving information concerning the interior of the ocean using satellite remote sensing data has a major impact on studies of ocean dynamic and climate changes; however, the lack of information within the ocean limits such studies about the global ocean. In this paper, an artificial neural network, combined with satellite data and gridded Argo product, is used to estimate the ocean heat content (OHC) anomalies over four different depths down to 2000 m covering the near-global ocean, excluding the polar regions. Our method allows for the temporal hindcast of the OHC to other periods beyond the 2005–2018 training period. By applying an ensemble technique, the hindcasting uncertainty could also be estimated by using different 9-year periods for training and then calculating the standard deviation across six ensemble members. This new OHC product is called the Ocean Projection and Extension neural Network (OPEN) product. The accuracy of the product is accessed using the coefficient of determination (R2) and the relative root-mean-square error (RRMSE). The feature combinations and network architecture are optimized via a series of experiments. Overall, intercomparison with several routinely analyzed OHC products shows that the OPEN OHC has an R2 larger than 0.95 and an RRMSE of <0.20 and presents notably accurate trends and variabilities. The OPEN product can therefore provide a valuable complement for studies of global climate changes.

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The Annual Cycle of the Energy Budget. Part I: Global Mean and Land–Ocean Exchanges

Journal of Climate ◽

10.1175/2007jcli1935.1 ◽

2008 ◽

Vol 21 (10) ◽

pp. 2297-2312 ◽

Cited By ~ 90

Author(s):

John T. Fasullo ◽

Kevin E. Trenberth

Keyword(s):

Energy Budget ◽

Annual Cycle ◽

Radiant Energy ◽

Heat Content ◽

Ocean Heat Content ◽

Radiation Budget ◽

Global Ocean ◽

Net Radiation ◽

Community Land Model ◽

The Mean

Abstract The mean and annual cycle of energy flowing into the climate system and its storage, release, and transport in the atmosphere, ocean, and land surface are estimated with recent observations. An emphasis is placed on establishing internally consistent quantitative estimates with discussion and assessment of uncertainty. At the top of the atmosphere (TOA), adjusted radiances from the Earth Radiation Budget Experiment (ERBE) and Clouds and the Earth’s Radiant Energy System (CERES) are used, while in the atmosphere the National Centers for Environmental Prediction–National Center for Atmospheric Research (NCEP–NCAR) reanalysis and 40-yr European Centre for Medium-Range Weather Forecasts (ECMWF) Re-Analysis (ERA-40) estimates are used. The net upward surface flux (FS) over ocean is derived as the residual of the TOA and atmospheric energy budgets, and is compared with direct calculations of ocean heat content (OE) and its tendency (δOE/δt) from several ocean temperature datasets. Over land, FS from a stand-alone simulation of the Community Land Model forced by observed fields is used. A depiction of the full energy budget based on ERBE fluxes from 1985 to 1989 and CERES fluxes from 2000 to 2004 is constructed that matches estimates of the global, global ocean, and global land imbalances. In addition, the annual cycle of the energy budget during both periods is examined and compared with ocean heat content changes. The near balance between the net TOA radiation (RT) and FS over ocean and thus with OE, and between RT and atmospheric total energy divergence over land, are documented both in the mean and for the annual cycle. However, there is an annual mean transport of energy by the atmosphere from ocean to land regions of 2.2 ± 0.1 PW (1 PW = 1015 W) primarily in the northern winter when the transport exceeds 5 PW. The global albedo is dominated by a semiannual cycle over the oceans, but combines with the large annual cycle in solar insolation to produce a peak in absorbed solar and net radiation in February, somewhat after the perihelion, and with the net radiation 4.3 PW higher than the annual mean, as it is enhanced by the annual cycle of outgoing longwave radiation that is dominated by land regions. In situ estimates of the annual variation of OE are found to be unrealistically large. Challenges in diagnosing the interannual variability in the energy budget and its relationship to climate change are identified in the context of the episodic and inconsistent nature of the observations.

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Comparison of retrospective analyses of the global ocean heat content

Dynamics of Atmospheres and Oceans ◽

10.1016/s0377-0265(99)00004-4 ◽

1999 ◽

Vol 29 (2-4) ◽

pp. 119-145 ◽

Cited By ~ 7

Author(s):

Gennady A Chepurin ◽

James A Carton

Keyword(s):

Heat Content ◽

Ocean Heat Content ◽

Global Ocean

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Long-term global ocean heat content change driven by sub-polar surface heat fluxes

10.1002/essoar.10504695.1 ◽

2020 ◽

Author(s):

Taimoor Sohail ◽

Damien B Irving ◽

Jan David Zika ◽

Ryan M Holmes ◽

John Alexander Church

Keyword(s):

Heat Content ◽

Surface Heat ◽

Heat Fluxes ◽

Ocean Heat Content ◽

Global Ocean ◽

Polar Surface ◽

Surface Heat Fluxes ◽

Content Change

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Contributions of Interdecadal Pacific Oscillation and Atlantic Multidecadal Oscillation to Global Ocean Heat Content Distribution

Journal of Climate ◽

10.1175/jcli-d-17-0204.1 ◽

2018 ◽

Vol 31 (3) ◽

pp. 1227-1244 ◽

Cited By ~ 9

Author(s):

Zeyuan Hu ◽

Aixue Hu ◽

Yongyun Hu

Keyword(s):

Pacific Ocean ◽

Surface Temperature ◽

Heat Content ◽

Atlantic Multidecadal Oscillation ◽

Meridional Overturning Circulation ◽

Ocean Heat Content ◽

Global Ocean ◽

Negative Phase ◽

Heat Distribution ◽

Interdecadal Pacific Oscillation

Abstract Regional sea surface temperature (SST) mode variabilities, especially the La Niña–like Pacific Ocean temperature pattern known as the negative phase of the interdecadal Pacific oscillation (IPO) and the associated heat redistribution within the ocean, are the leading mechanisms explaining the recent global warming hiatus. Here version 1 of the Community Earth System Model (CESM) is used to examine how different phases of two leading decadal time scale SST modes, namely the IPO and the Atlantic multidecadal oscillation (AMO), contribute to heat redistribution in the global ocean in the absence of time-evolving external forcings. The results show that both the IPO and AMO contribute a similar magnitude to global mean surface temperature and ocean heat redistribution. Both modes contribute warmer surface temperature and higher upper ocean heat content in their positive phase, and the reverse in their negative phase. Regionally, patterns of ocean heat distribution in the upper few hundred meters of the tropical and subtropical Pacific Ocean depend highly on the IPO phase via the IPO-associated changes in the subtropical cell. In the Atlantic, ocean heat content is primarily associated with the state of the AMO. The interconnections between the IPO, AMO, and global ocean heat distribution are established through the atmospheric bridge and the Atlantic meridional overturning circulation. An in-phase variant of the IPO and AMO can lead to much higher surface temperatures and heat content changes than an out-of-phase variation. This result suggests that changes in the IPO and AMO are potentially capable of modulating externally forced SST and heat content trends.

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