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

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.

scholarly journals On the Increased Frequency of Mediterranean Drought

2012 ◽  
Vol 25 (6) ◽  
pp. 2146-2161 ◽  
Author(s):  
Martin Hoerling ◽  
Jon Eischeid ◽  
Judith Perlwitz ◽  
Xiaowei Quan ◽  
Tao Zhang ◽  
...  
Keyword(s):  
Radiative Forcing ◽  
Climate Models ◽  
Eastern Mediterranean ◽  
Internal Variability ◽  
Global Ocean ◽  
External Signal ◽  
The North ◽  
Aerosol Forcing ◽  
Tropical Oceans ◽  
The North Atlantic Oscillation

Abstract The land area surrounding the Mediterranean Sea has experienced 10 of the 12 driest winters since 1902 in just the last 20 years. A change in wintertime Mediterranean precipitation toward drier conditions has likely occurred over 1902–2010 whose magnitude cannot be reconciled with internal variability alone. Anthropogenic greenhouse gas and aerosol forcing are key attributable factors for this increased drying, though the external signal explains only half of the drying magnitude. Furthermore, sea surface temperature (SST) forcing during 1902–2010 likely played an important role in the observed Mediterranean drying, and the externally forced drying signal likely also occurs through an SST change signal. The observed wintertime Mediterranean drying over the last century can be understood in a simple framework of the region’s sensitivity to a uniform global ocean warming and to modest changes in the ocean’s zonal and meridional SST gradients. Climate models subjected to a uniform +0.5°C warming of the world oceans induce eastern Mediterranean drying but fail to generate the observed widespread Mediterranean drying pattern. For a +0.5°C SST warming confined to tropical latitudes only, a dry signal spanning the entire Mediterranean region occurs. The simulated Mediterranean drying intensifies further when the Indian Ocean is warmed +0.5°C more than the remaining tropical oceans, an enhanced drying signal attributable to a distinctive atmospheric circulation response resembling the positive phase of the North Atlantic Oscillation. The extent to which these mechanisms and the region’s overall drying since 1902 reflect similar mechanisms operating in association with external radiative forcing are discussed.

scholarly journals 20th century cooling of the deep ocean contributed to delayed acceleration of Earth’s energy imbalance

2021 ◽  
Vol 12 (1) ◽  
Author(s):  
A. Bagnell ◽  
T. DeVries
Keyword(s):  
20Th Century ◽  
Heat Content ◽  
Deep Ocean ◽  
Ocean Warming ◽  
Ocean Heat Content ◽  
Global Ocean ◽  
Energy Imbalance ◽  
Delayed Onset ◽  
The Past ◽  
Historical Reconstructions

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.

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

2014 ◽  
Vol 27 (5) ◽  
pp. 1945-1957 ◽  
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.

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

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

<p>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<sup>-2</sup>, compared to the amount of energy entering and leaving the climate system of ~340 W.m<sup>-2</sup>. Recent studies suggest that the EEI response to anthropogenic GHG and aerosols emissions is 0.5-1 W.m<sup>-2</sup>. It implies that an accuracy of <0.3 W.m<sup>-2</sup> 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<sup>-2</sup> at decadal time scales is desirable if we want to monitor future changes in EEI.</p><p>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  gained by the Earth in response to EEI. The OHC is estimated from space altimetry and gravimetry missions (GRACE). This “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’s entire depth. Consequently, it complements the OHC estimation from the ARGO network. </p><p>The MOHeaCAN product contains monthly time series (between August 2002 and June 2017) of several variables, the main ones being the regional OHC (3°x3° 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. </p><p>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’s Radiant energy System (CERES) measurements at the top of the atmosphere. The mean EEI derived from MOHeaCAN product is 0.84 W.m<sup>-2</sup> over the whole period within an uncertainty of ±0.12 W.m<sup>-2</sup> (68% confidence level - 0.20 W.m<sup>-2</sup> 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.</p><p><strong>The MOHeaCAN product from “altimetry-gravimetry” is now available</strong> and can be downloaded at https://doi.org/10.24400/527896/a01-2020.003. Feedback from interested users on this product are welcome.</p>

scholarly journals Why Hasn’t Earth Warmed as Much as Expected?

2010 ◽  
Vol 23 (10) ◽  
pp. 2453-2464 ◽  
Author(s):  
Stephen E. Schwartz ◽  
Robert J. Charlson ◽  
Ralph A. Kahn ◽  
John A. Ogren ◽  
Henning Rodhe
Keyword(s):  
Climate Sensitivity ◽  
Atmospheric Aerosols ◽  
Climate Models ◽  
Substantial Reduction ◽  
Heat Content ◽  
Historical Record ◽  
Intergovernmental Panel ◽  
Aerosol Forcing ◽  
Best Estimate ◽  
Earth’S Climate

Abstract The observed increase in global mean surface temperature (GMST) over the industrial era is less than 40% of that expected from observed increases in long-lived greenhouse gases together with the best-estimate equilibrium climate sensitivity given by the 2007 Assessment Report of the Intergovernmental Panel on Climate Change (IPCC). Possible reasons for this warming discrepancy are systematically examined here. The warming discrepancy is found to be due mainly to some combination of two factors: the IPCC best estimate of climate sensitivity being too high and/or the greenhouse gas forcing being partially offset by forcing by increased concentrations of atmospheric aerosols; the increase in global heat content due to thermal disequilibrium accounts for less than 25% of the discrepancy, and cooling by natural temperature variation can account for only about 15%. Current uncertainty in climate sensitivity is shown to preclude determining the amount of future fossil fuel CO2 emissions that would be compatible with any chosen maximum allowable increase in GMST; even the sign of such allowable future emissions is unconstrained. Resolving this situation, by empirical determination of the earth’s climate sensitivity from the historical record over the industrial period or through use of climate models whose accuracy is evaluated by their performance over this period, is shown to require substantial reduction in the uncertainty of aerosol forcing over this period.

How Well Do Climate Models Reproduce North Atlantic Subtropical Mode Water?

2013 ◽  
Vol 43 (10) ◽  
pp. 2230-2244 ◽  
Author(s):  
Shenfu Dong ◽  
Kathryn A. Kelly
Keyword(s):  
Heat Flux ◽  
Data Assimilation ◽  
North Atlantic ◽  
Climate Models ◽  
Formation Rate ◽  
Heat Content ◽  
Ocean Heat Content ◽  
Upper Ocean ◽  
Upper Ocean Heat Content ◽  
Mode Water

Abstract Formation and the subsequent evolution of the subtropical mode water (STMW) involve various dynamic and thermodynamic processes. Proper representation of mode water variability and contributions from various processes in climate models is important in order to predict future climate change under changing forcings. The North Atlantic STMW, often referred to as Eighteen Degree Water (EDW), in three coupled models, both with data assimilation [GFDL coupled data assimilation (GFDL CDA)] and without data assimilation [GFDL Climate Model, version 2.1 (GFDL CM2.1), and NCAR Community Climate System Model, version 3 (CCSM3)], is analyzed to evaluate how well EDW processes are simulated in those models and to examine whether data assimilation alters the model response to forcing. In comparison with estimates from observations, the data-assimilating model gives a better representation of the formation rate, the spatial distribution of EDW, and its thickness, with the largest EDW variability along the Gulf Stream (GS) path. The EDW formation rate in GFDL CM2.1 is very weak because of weak heat loss from the ocean in the model. Unlike the observed dominant southward movement of the EDW, the EDW in GFDL CM2.1 and CCSM3 moves eastward after formation in the excessively wide GS in the models. However, the GFDL CDA does not capture the observed thermal response of the overlying atmosphere to the ocean. Observations show a robust anticorrelation between the upper-ocean heat content and air–sea heat flux, with upper-ocean heat content leading air–sea heat flux by a few months. This anticorrelation is well captured by GFDL CM2.1 and CCSM3 but not by GFDL CDA. Only GFDL CM2.1 captures the observed anticorrelation between the upper-ocean heat content and EDW volume. This suggests that, although data assimilation corrects the readily observed variables, it degrades the model thermodynamic response to forcing.

scholarly journals Reply to “Comment on ‘Rethinking the Lower Bound on Aerosol Radiative Forcing’”

2017 ◽  
Vol 30 (16) ◽  
pp. 6585-6589 ◽  
Author(s):  
Bjorn Stevens ◽  
Stephanie Fiedler
Keyword(s):  
Twentieth Century ◽  
Lower Bound ◽  
Radiative Forcing ◽  
Climate Models ◽  
Anthropogenic Aerosols ◽  
Anthropogenic Aerosol ◽  
Aerosol Radiative Forcing ◽  
Clear Sky ◽  
The North ◽  
Aerosol Forcing

Kretzschmar et al., in a comment in 2017, use the spread in the output of aerosol–climate models to argue that the models refute the hypothesis (presented in a paper by Stevens in 2015) that for the mid-twentieth-century warming to be consistent with observations, then the present-day aerosol forcing, [Formula: see text] must be less negative than −1 W m−2. The main point of contention is the nature of the relationship between global SO2 emissions and [Formula: see text] In contrast to the concave (log-linear) relationship used by Stevens and in earlier studies, whereby [Formula: see text] becomes progressively less sensitive to SO2 emissions, some models suggest a convex relationship, which would imply a less negative lower bound. The model that best exemplifies this difference, and that is most clearly in conflict with the hypothesis of Stevens, does so because of an implausible aerosol response to the initial rise in anthropogenic aerosol precursor emissions in East and South Asia—already in 1975 this model’s clear-sky reflectance from anthropogenic aerosol over the North Pacific exceeds present-day estimates of the clear-sky reflectance by the total aerosol. The authors perform experiments using a new (observationally constrained) climatology of anthropogenic aerosols to further show that the effects of changing patterns of aerosol and aerosol precursor emissions during the late twentieth century have, for the same global emissions, relatively little effect on [Formula: see text] These findings suggest that the behavior Kretzschmar et al. identify as being in conflict with the lower bound in Stevens arises from an implausible relationship between SO2 emissions and [Formula: see text] and thus provides little basis for revising this lower bound.

scholarly journals Datasets for the CMIP6 Scenario Model Intercomparison Project (ScenarioMIP) Simulations with the Coupled Model CAS FGOALS-f3-L

2020 ◽  
Author(s):  
Shuwen Zhao ◽  
Yongqiang Yu ◽  
Pengfei Lin ◽  
Hailong Liu ◽  
Bian He ◽  
...  
Keyword(s):  
Radiative Forcing ◽  
Heat Content ◽  
Coupled Model ◽  
Global Ocean ◽  
Model Intercomparison ◽  
Radiative Forcings ◽  
Air Temperatures ◽  
Tier 1 ◽  
Scenario Model ◽  
Intercomparison Project

AbstractThe datasets for the tier-1 Scenario Model Intercomparison Project (ScenarioMIP) experiments from the Chinese Academy of Sciences (CAS) Flexible Global Ocean-Atmosphere-Land System model, finite-volume version 3 (CAS FGOALS-f3-L) are described in this study. ScenarioMIP is one of the core MIP experiments in phase 6 of the Coupled Model Intercomparison Project (CMIP6). Considering future CO2, CH4, N2O and other gases’ concentrations, as well as land use, the design of ScenarioMIP involves eight pathways, including two tiers (tier-1 and tier-2) of priority. Tier-1 includes four combined Shared Socioeconomic Pathways (SSPs) with radiative forcing, i.e., SSP1-2.6, SSP2-4.5, SSP3-7.0 and SSP5-8.5, in which the globally averaged radiative forcing at the top of the atmosphere around the year 2100 is approximately 2.6, 4.5, 7.0 and 8.5 W m−2, respectively. This study provides an introduction to the ScenarioMIP datasets of this model, such as their storage location, sizes, variables, etc. Preliminary analysis indicates that surface air temperatures will increase by about 1.89°C, 3.07°C, 4.06°C and 5.17°C by around 2100 under these four scenarios, respectively. Meanwhile, some other key climate variables, such as sea-ice extension, precipitation, heat content, and sea level rise, also show significant long-term trends associated with the radiative forcing increases. These datasets will help us understand how the climate will change under different anthropogenic and radiative forcings.

scholarly journals Measuring Global Ocean Heat Content to Estimate the Earth Energy Imbalance

2019 ◽  
Vol 6 ◽  
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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