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The ocean, with its low albedo and vast thermal inertia, plays key roles in the climate system, including absorbing massive amounts of heat as atmospheric greenhouse gas concentrations rise. While the Argo array of profiling floats has vastly improved sampling of ocean temperature in the upper half of the global ocean volume since the mid-2000s, they are not sufficient in number to resolve eddy scales in the oceans. However, satellite sea surface temperature (SST) and sea surface height (SSH) measurements do resolve these scales. Here we use random forest regressions to map ocean heat content anomalies (OHCA) using in situ training data from Argo and other sources on a 7-day × 1/4° × 1/4° grid with latitude, longitude, time, SSH, and SST as predictors. The maps display substantial patterns on eddy scales, resolving variations of ocean currents and fronts. During the well-sampled Argo period, global integrals of these maps reduce noise relative to estimates based on objective mapping of in situ data alone by roughly a factor of 3 when compared to time series of CERES (satellite data) top-of-the-atmosphere energy flux measurements and improve correlations of anomalies with CERES on annual time scales. Prior to and early on in the Argo period, when in situ data were sparser, global integrals of these maps retain low variance, and do not relax back to a climatological mean, avoiding potential deficiencies of various methods for infilling data-sparse regions with objective maps by exploiting temporal and spatial patterns of OHCA and its correlations with SST and SSH. Significance Statement We use a simple machine learning technique to improve maps of subsurface ocean warming by exploiting the relationships between subsurface ocean temperature both sea surface temperature and sea level. Mapping ocean warming is important because it contributes to sea level rise through thermal expansion; impacts marine life through marine heatwaves and changes in mixing, oxygen, and carbon dioxide levels; increases energy available to tropical cyclones; and stores most of the energy building up in Earth’s climate system owing to the accumulation of anthropogenic greenhouse gases in the atmosphere. Our new estimates generally have lower noise energy and higher correlations than other products when compared with global energy fluxes at the top of the atmosphere measured by satellite.

State of the climate in 2019

The ocean takes up about 93% of the global warming heat entering Earth’s climate system. In addition, the associated thermal expansion contributes substantially to sea-level rise. Hence, quantifying the oceanic heat uptake rate and its statistical significance has been a research focus. Here we use gridded ocean heat content maps to examine regional trends in ocean warming for 0–700 m depth from 1993–2019 and 1968–2019, periods based on sampling distributions. The maps are from four research groups, three based on ocean temperature alone and one combining ocean temperature with satellite altimeter sea-level anomalies. We show that use of longer periods results in larger percentages of ocean area with statistically significant warming trends and less ocean area covered by statistically significant cooling trends. We discuss relations of these patterns to climate phenomena, including the Pacific Decadal Oscillation, the Atlantic Meridional Overturning Circulation and global warming. A large proportion of anthropogenic heat energy is being taken up by ocean warming. Analysis of yearly 0–700 m ocean heat content maps from four different estimates shows that the longer the period over which regional trends are estimated, the larger the area of statistically significant warming.

The Earth system is accumulating energy due to human-induced activities. More than 90% of this energy has been stored in the ocean as heat since 1970, with ∼60% of that in the upper 700 m. Differences in upper-ocean heat content anomaly (OHCA) estimates, however, exist. Here, we use a dataset protocol for 1970–2008—with six instrumental bias adjustments applied to expendable bathythermograph (XBT) data, and mapped by six research groups—to evaluate the spatiotemporal spread in upper OHCA estimates arising from two choices: 1) those arising from instrumental bias adjustments and 2) those arising from mathematical (i.e., mapping) techniques to interpolate and extrapolate data in space and time. We also examined the effect of a common ocean mask, which reveals that exclusion of shallow seas can reduce global OHCA estimates up to 13%. Spread due to mapping method is largest in the Indian Ocean and in the eddy-rich and frontal regions of all basins. Spread due to XBT bias adjustment is largest in the Pacific Ocean within 30°N–30°S. In both mapping and XBT cases, spread is higher for 1990–2004. Statistically different trends among mapping methods are found not only in the poorly observed Southern Ocean but also in the well-observed northwest Atlantic. Our results cannot determine the best mapping or bias adjustment schemes, but they identify where important sensitivities exist, and thus where further understanding will help to refine OHCA estimates. These results highlight the need for further coordinated OHCA studies to evaluate the performance of existing mapping methods along with comprehensive assessment of uncertainty estimates.

The reappearance of a northeast Pacific marine heatwave (MHW) sounded alarms in late summer 2019 for a warming event on par with the 2013–2016 MHW known as The Blob. Despite these two events having...

Human-induced atmospheric composition changes cause a radiative imbalance at the top-of-atmosphere which is driving global warming. This Earth Energy Imbalance (EEI) is a fundamental metric of climate change. Understanding the heat gain of the Earth system from this accumulated heat – and particularly how much and where the heat is distributed in the Earth system – is fundamental to understanding how this affects warming oceans, atmosphere and land, rising temperatures and sea level, and loss of grounded and floating ice, which are fundamental concerns for society. This study is a Global Climate Observing System (GCOS) concerted international effort to update the Earth heat inventory, and presents an updated international assessment of ocean warming estimates, and new and updated estimates of heat gain in the atmosphere, cryosphere and land over the period 1960–2018. The study obtains a consistent long-term Earth system heat gain over the past 58 years, with a total heat gain of 393 ± 40 ZJ, which is equivalent to a heating rate of 0.42 ± 0.04 W m−2. The majority of the heat gain (89 %) takes place in the global ocean (0–700 m: 53 %; 700–2000 m: 28 %; > 2000 m: 8 %), while it amounts to 6 % for the land heat gain, to 4 % available for the melting of grounded and floating ice, and to 1 % for atmospheric warming. These new estimates indicate a larger contribution of land and ice heat gain (10 % in total) compared to previous estimates (7 %). There is a regime shift of the Earth heat inventory over the past 2 decades, which appears to be predominantly driven by heat sequestration into the deeper layers of the global ocean, and a doubling of heat gain in the atmosphere. However, a major challenge is to reduce uncertainties in the Earth heat inventory, which can be best achieved through the maintenance of the current global climate observing system, its extension into areas of gaps in the sampling, as well as to establish an international framework for concerted multi-disciplinary research of the Earth heat inventory. Earth heat inventory is published at DKRZ (https://www.dkrz.de/) under the doi: https://doi.org/10.26050/WDCC/GCOS_EHI_EXP (von Schuckmann et al., 2020).

The ocean is the primary heat sink of the global climate system. Since 1971, it has been responsible for storing more than 90% ofthe excess heat added to the Earth system by anthropogenic greenhouse-gas emissions. Adding this heat to the ocean contributes substantially to sea level rise and affects vital marine ecosystems. Considering the global ocean’s large role in ongoing climate variability and change, it is a good place to focus in order to understand what observed changes have occurred to date and, by using models, what future changes might arise under continued anthropogenic forcing of the climate system. While sparse measurement coverage leads to enhanced uncertainties with long-term historical estimates of change, modern measurements are beginning to provide the clearest picture yet of ongoing global ocean change. Observations show that the ocean is warming from the near-surface through to the abyss, a conclusion that is strengthened with each new analysis. In this assessment, we revisit observation- and model-based estimates of ocean warming from the industrial era to the present and show a consistent, full-depth pattern of change over the observed record that is likely to continue at an ever-increasing pace if effective actions to reduce greenhouse-gas emissions are not taken.

The energy radiated by the Earth toward space does not compensate the incoming radiation from the Sun leading to a small positive energy imbalance at the top of the atmosphere (0.4-1 Wm(-2)). This imbalance is coined Earth's Energy Imbalance (EEI). It is mostly caused by anthropogenic greenhouse gas emissions and is driving the current warming of the planet. Precise monitoring of EEI is critical to assess the current status of climate change and the future evolution of climate. But the monitoring of EEI is challenging as EEI is two orders of magnitude smaller than the radiation fluxes in and out of the Earth system. Over 93% of the excess energy that is gained by the Earth in response to the positive EEI accumulates into the ocean in the form of heat. This accumulation of heat can be tracked with the ocean observing system such that today, the monitoring of Ocean Heat Content (OHC) and its long-term change provide the most efficient approach to estimate EEI. In this community paper we review the current four state-of-the-art methods to estimate global OHC changes and evaluate their relevance to derive EEI estimates on different time scales. These four methods make use of: (1) direct observations of in situ temperature; (2) satellite-based measurements of the ocean surface net heat fluxes; (3) satellite-based estimates of the thermal expansion of the ocean and (4) ocean reanalyses that assimilate observations from both satellite and in situ instruments. For each method we review the potential and the uncertainty of the method to estimate global OHC changes. We also analyze gaps in the current capability of each method and identify ways of progress for the future to fulfill the requirements of EEI monitoring. Achieving the observation of EEI with sufficient accuracy will depend on merging the remote sensing techniques with in situ measurements of key variables as an integral part of the Ocean Observing System.

Ocean warming accounts for the majority of the earth’s recent energy imbalance. Historic ocean heat content (OHC) changes are important for understanding changing climate. Calculations of OHC anomalies (OHCA) from in situ measurements provide estimates of these changes. Uncertainties in OHCA estimates arise from calculating global fields from temporally and spatially irregular data (mapping method), instrument bias corrections, and the definitions of a baseline climatology from which anomalies are calculated. To investigate sensitivity of OHCA estimates for the upper 700 m to these different factors, the same quality-controlled dataset is used by seven groups and comparisons are made. Two time periods (1970–2008 and 1993–2008) are examined. Uncertainty due to the mapping method is 16.5 ZJ for 1970–2008 and 17.1 ZJ for 1993–2008 (1 ZJ = 1 × 1021 J). Uncertainty due to instrument bias correction varied from 8.0 to 17.9 ZJ for 1970–2008 and from 10.9 to 22.4 ZJ for 1993–2008, depending on mapping method. Uncertainty due to baseline mean varied from 3.5 to 14.5 ZJ for 1970–2008 and from 2.7 to 9.8 ZJ for 1993–2008, depending on mapping method and offsets. On average mapping method is the largest source of uncertainty. The linear trend varied from 1.3 to 5.0 ZJ yr−1 (0.08–0.31 W m−2) for 1970–2008 and from 1.5 to 9.4 ZJ yr−1 (0.09–0.58 W m−2) for 1993–2008, depending on method, instrument bias correction, and baseline mean. Despite these complications, a statistically robust upper-ocean warming was found in all cases for the full time period.

Data from full-depth closely sampled hydrographic sections and Argo floats are analyzed to inform the design of a future Deep Argo array. Here standard errors of local decadal temperature trends and global decadal trends of ocean heat content and thermosteric sea level anomalies integrated from 2000 to 6000 dbar are estimated for a hypothetical 5° latitude × 5° longitude × 15-day cycle Deep Argo array. These estimates are made using temperature variances from closely spaced full-depth CTD profiles taken during hydrographic sections. The temperature data along each section are high passed laterally at a 500-km scale, and the resulting variances are averaged in 5° × 5° bins to assess temperature noise levels as a function of pressure and geographic location. A mean global decorrelation time scale of 62 days is estimated using temperature time series at 1800 dbar from Argo floats. The hypothetical Deep Argo array would be capable of resolving, at one standard error, local trends from −1 in the quiescent abyssal North Pacific to about 26 m °C decade−1 below 2000 dbar along 50°S in the energetic Southern Ocean. Larger decadal temperature trends have been reported previously in these regions using repeat hydrographic section data, but those very sparse data required substantial spatial averaging to obtain statistically significant results. Furthermore, the array would provide decadal global ocean heat content trend estimates from 2000 to 6000 dbar with a standard error of ±3 TW, compared to a trend standard error of ±17 TW from a previous analysis of repeat hydrographic data.

Characteristics of eddies in the Gulf of Alaska are assessed from January 2003 through April 2012. Ensemble statistics for eddy subsurface water properties on isopycnals are computed using temperature and salinity profiles from Argo profiling floats located within eddies, which are identified in sea-surface height using objective techniques. Ninety cyclonic and 154 anticyclonic eddies are identified during this period. The anticyclonic eddies are strongly nonlinear and exhibit significant warm subsurface temperature anomalies and associated salty anomalies on isopycnals while no clear distinguishing subsurface anomalies on isopycnals are detected in association with the cyclonic eddies. Heat and freshwater fluxes for the eddies are estimated from integrations in depth coordinates. The anticyclonic eddies transport heat both westward off the continental shelf into the Subarctic Gyre and westward within the Alaskan Stream. However, they transport salt into the Subarctic Gyre and freshwater within the Alaskan Stream. In both pathways eddy heat and freshwater transport show possible year-to-year fluctuations, varying from 0 to 50.4 × 1018 J a−1 and −16.8 to +7.4 km3 a−1, respectively. The anticyclonic eddies are capped by relatively fresh water year-round.

In recent decades, over nine-tenths of Earth's top-of-the-atmosphere energy imbalance has been stored in the ocean, which is rising as it warms. Combining satellite sea-level data with ocean mass data or model results allows insights into ocean warming.