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  • Author or Editor: Lijing Cheng x
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Lijing Cheng
,
Grant Foster
,
Zeke Hausfather
,
Kevin E. Trenberth
, and
John Abraham

Abstract

The increased concentrations of greenhouse gases in the atmosphere create an increase in Earth’s thermal energy, which is mainly stored in the ocean. Quantification of the rate of increase in ocean heat content (OHC) is vital for understanding the current and future climate of Earth. Linear trend lines have been frequently used to quantify long-term rates of change, but are inappropriate because they cannot capture nonlinearity in trends, have large start- and end-point sensitivity, and the assumption of linearity is nonphysical. Here observed and model-based linear regressions with higher-order polynomial (quadratic), piecewise linear, and locally weighted scatterplot smoothing (LOWESS) are compared. Piecewise linear and LOWESS perform best in depicting multidecadal trends. It is shown that linear rates are valid for up to about 15-yr segments (i.e., it is valid to compute linear rates within a 15-yr time window). Using the recommended methods, ocean warming for the upper 2000 m increases from about 0 to 0.06 ± 0.08 W m−2 for 1958–73 to 0.58 ± 0.08 W m−2 for 2003–18, indicating an acceleration of ocean warming that happens in all four ocean basins and from near the sea surface to 2000 m. There is consistency between multimodel-mean historically forced climate models and observations, which implies that the contribution of internal variability is small for global 0–2000 m OHC. Notable increases of OHC in the upper ocean (i.e., 0–300 m) after about 1980 and the deeper ocean (300–2000 m) after the late 1980s are also evident. This study suggests alternative methods to those currently used to estimate ocean warming rates to provide a more accurate quantification of long-term Earth’s energy changes.

Significance Statement

Quantifying long-term rates of change is needed to understand the time evolution of ocean warming and to assess the changing ocean and Earth’s energy budgets. Linear trend lines have been frequently used but cannot capture nonlinearity in trends, and have large start- and end-point sensitivity. Based on an analysis of the statistical features of ocean heat content time series, this study proposes two alternative methods to quantify the rates of change, including piecewise linear fit and LOWESS. Robust increases in warming for the upper 2000 m detected through observational records and climate models from 1958 to 2020, indicate a robust acceleration of ocean warming. Slow penetration of heat from the upper ocean into the deeper ocean is also evident.

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

Abstract

Ocean meridional heat transports (MHTs) are deduced as a residual using energy budgets to produce latitude versus time series for the globe, Indo-Pacific, and Atlantic. The top-of-atmosphere (TOA) radiation is combined with the vertically integrated atmospheric energy divergence from atmospheric reanalyses to produce the net surface energy fluxes everywhere. The latter is then combined with estimates of the vertically integrated ocean heat content (OHC) tendency to produce estimates of the ocean heat divergence. Because seasonal sea ice and land runoff effects are not fully considered, the mean annual cycle is incomplete, but those effects are small for interannual variability. However, there is a mismatch between 12-month inferred surface flux and the corresponding OHC changes globally, requiring adjustments to account for the Earth’s global energy imbalance. Estimates are greatly improved by building in the constraint that MHT must go to zero at the northern and southern extents of the ocean basin at all times, enabling biases between the TOA and OHC data to be reconciled. Zonal mean global, Indo-Pacific, and Atlantic basin ocean MHTs are computed and presented as 12-month running means and for the mean annual cycle for 2000–16. For the Indo-Pacific, the tropical and subtropical MHTs feature a strong relationship with El Niño–Southern Oscillation (ENSO), and in the Atlantic, MHT interannual variability is significantly affected by and likely influences the North Atlantic Oscillation (NAO). However, Atlantic and Pacific changes are linked, suggesting that the northern annular mode (as opposed to NAO) is predominant. There is also evidence of decadal variability or trends.

Open access