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Record-Setting Ocean Warmth Continued in 2019

February 2020
Advances in Atmospheric Sciences 37(2):137-142

February 2020
37(2):137-142

DOI:10.1007/s00376-020-9283-7

Authors:

Lijing Cheng

Institute of Atmospheric Physics

John Patrick Abraham

University of St. Thomas

Show all 14 authorsHide

(a) Upper 2000 m OHC from 1955 through 2019. The histogram represents annual anomalies (units: ZJ), wherein positive anomalies relative to a 1981−2010 baseline are shown as red bars and negative anomalies as blue. The two black dashed lines are the linear trends over 1955-86 and 1987−2019, respectively. (b) Ocean heat content anomaly in 2019 relative to 1981−2010 baseline. (c) difference of OHC at upper 2000 m between 2019 and 2018. Units: 10 9 J m −2 . Source: IAP data.

…

(a) Upper 2000 m OHC from 1958 through 2019. The histogram represents annual anomalies (units: ZJ), wherein positive anomalies relative to a 1981−2010 baseline are shown as red bars and negative anomalies as blue. The two black dashed lines are the linear trends over 1955-86 and 1987−2019, respectively. (b) Ocean heat content anomaly in 2019 relative to the 1981−2010 baseline. (c) Difference in the OHC in the upper 2000 m between 2019 and 2018. Units: 10 9 J m −2 . Source: IAP data.

…

Ocean heat budget from 1960 to 2019 based on IAP analysis data from 0 to 2000 m, and from Purkey and Johnson (2010) for deep ocean change below 2000 m (units: ZJ). Figure updated from Cheng et al. (2017). The anomalies are related to 1958−1962 baseline, and the time series are smoothed by LOWESS (locally weighted scatterplot smoothing) with span width of 24 months. The gray dashed lines are the 95% confidence interval of the total ocean heat budget.

…

Vertical section of the ocean temperature trends within 1960 to 2019 from sea surface to 2000 m (60-year Ordinary Least Squares linear trend). Shown are the zonal mean sections in each ocean basin organized around the Southern Ocean (south of 60°S) in the center. Black contours show the associated climatological mean temperature with intervals of 2°C (In the Southern Ocean, 1°C intervals are provided in dashed contours). IAP gridded data are used.

…

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Record-Setting Ocean Warmth Continued in 2019

Lijing CHENG*1,2,11, John ABRAHAM3, Jiang ZHU1,2, Kevin E. TRENBERTH4, John FASULLO4,

Tim BOYER5, Ricardo LOCARNINI5, Bin ZHANG2,6, Fujiang YU7, Liying WAN7,

Xingrong CHEN7, Xiangzhou SONG8, Yulong LIU9, and Michael E. MANN10

1International Center for Climate and Environment Sciences, Institute of Atmospheric Physics,

Chinese Academy of Sciences, Beijing 100029, China

2Center for Ocean Mega-Science, Chinese Academy of Sciences, Qingdao 266071, China

3University of St. Thomas, School of Engineering, Minnesota 55105, USA

4National Center for Atmospheric Research, Boulder, Colorado 80307, USA

5National Oceanic and Atmospheric Administration, National Centers for Environmental Information,

Silver Spring, Maryland 20910, USA

6Institute of Oceanology, Chinese Academy of Sciences, Qingdao 266071, China

7National Marine Environmental Forecasting Center, Ministry of Natural Resources of China, Beijing 100081, China

8College of Oceanography, Hohai University, Nanjing 210098, China

9National Marine Data and Information Service, Tianjin 300171, China

10Department of Meteorology &Atmospheric Science, The Pennsylvania State University,

University Park, Pennsylvania 16802, USA

11State Key Laboratory of Satellite Ocean Environment Dynamics, Second Institute of Oceanography,

Hangzhou 310012, China

(Received 26 December 2019; revised 6 January 2020; accepted 9 January 2020)

Citation: Cheng, L., and Coauthors, 2020: Record-setting ocean warmth continued in 2019. Adv. Atmos. Sci., 37(2),

137−142, https://doi.org/10.1007/s00376-020-9283-7.



Human-emitted greenhouse gases (GHGs) have resulted in a long-term and unequivocal warming of the planet (IPCC,

2019). More than 90% of the excess heat is stored within the world’s oceans, where it accumulates and causes increases in

ocean temperature (Rhein et al., 2013; Abram et al., 2019). Because the oceans are the main repository of the Earth’s

energy imbalance, measuring ocean heat content (OHC) is one of the best ways to quantify the rate of global warming

(Trenberth et al., 2016; Von Schuckmann et al., 2016; Cheng et al., 2018). Following reports released in the previous two

years (Cheng and Zhu, 2018; Cheng et al., 2019c), this article presents new OHC data for the year 2019. These data reveal

that the world’s oceans (especially the upper 2000 m) in 2019 were the warmest in recorded human history. Specifically,

the ocean heat anomaly (0−2000 m) in 2019 was 228 Zetta Joules (ZJ, 1 ZJ=1021 Joules) above the 1981−2010 average and

25 ZJ above 2018 (Table 1).

The OHC values (for the upper 2000 m) were obtained from the Institute of Atmospheric Physics (IAP) ocean analysis

(see “Data and methods” section, below), which uses a relatively new method to treat data sparseness and updates in the in-

struments that have been used to measure ocean temperature (Cheng et al., 2017). The evolution of OHC (Fig. 1)

shows that the upper 2000 m OHC in 2019 was 228 ± 9 ZJ above the 1981–2010 average. The record-setting ocean warmth

is also found in National Oceanic and Atmospheric Administration/National Center for Environmental Information

(NOAA/NCEI) data, showing 217± 4 ZJ in 2019 above the 1981−2010 average (21 ZJ above 2018) (Table 1) (updated

from Levitus et al. 2012). With these newly available IAP data, a ranking of the warmest years since the 1950s is now pos-

sible (Table 1). The past five years are the top five warmest years in the ocean historically with modern instruments, and the

past ten years are also the top ten years on record. The same ranking also applies to NOAA/NCEI data (Table 1).



* Corresponding author: Lijing CHENG

Email: chenglij@mail.iap.ac.cn

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ADVANCES IN ATMOSPHERIC SCIENCES, VOL. 37, FEBRUARY 2020, 137–142

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• News & Views •

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©Institute of Atmospheric Physics/Chinese Academy of Sciences, and Science Press and Springer-Verlag GmbH Germany, part of Springer Nature 2020

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Table 1.  Top five warmest years in the ocean since 1955 for both IAP (updated from Cheng et al., 2017 through 2019)and

NOAA/NCEI data (updated from Levitus et al., 2012 through 2019). The OHC values are the anomalies (units: ZJ) relative to the

1981–2010 average.

Rank Year IAP NOAA/NCEI

1 2019 228 217

2 2018 203 196

3 2017 193 189

4 2015 185 180

5 2016 180 164



Fig. 1. (a) Upper 2000 m OHC from 1958 through 2019. The histogram represents annual

anomalies (units: ZJ), wherein positive anomalies relative to a 1981−2010 baseline are shown

as red bars and negative anomalies as blue. The two black dashed lines are the linear trends

over 1955–86 and 1987−2019, respectively. (b) Ocean heat content anomaly in 2019 relative

to the 1981−2010 baseline. (c) Difference in the OHC in the upper 2000 m between 2019 and

2018. Units: 109 J m−2. Source: IAP data.

138 VOLUME 37

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Since a single annual OHC value can be impacted by internal variabilities (i.e., El Niño–Southern Oscillation, ENSO)

or instrumental errors, long-term trends are much more important than any individual year for showing climate change; and

such trends have been calculated in this work. Simple least-squares trend lines were created for two approximately equal-dura-

tion time periods (period 1 = 1955–86; period 2 = 1987–2019). The warming rates were obtained by the rate of change of

the data in Fig. 1. For the first time period, the warming was relatively constant at ~2.1 ± 0.5 ZJ yr−1. However, the more re-

cent warming was ~450% that of the earlier warming (9.4 ± 0.2 ZJ yr−1, equal to 0.58 W m−2 averaged over the Earth’s sur-

face), reflecting a major increase in the rate of global climate change (Cheng et al., 2019a). Note that the selection of end-

points, the use of smoothing, and other factors may lead to slightly different rates of warming than those reported here, but

in no way change the central findings of this report.

Based on the updated OHC data throughout 2019 from the IAP, a revised ocean energy budget from 0 m to the ocean bot-

tom is provided (Fig. 2), along with the OHC below 2000 m adapted from Purkey and Johnson (2010) (using a linear in-

crease of 1.15 ± 1.0 ZJ yr−1 after 1992). The deep OHC change below 2000 m was extended to 1960 by assuming a zero heat-

ing rate before 1991, consistent with Rhein et al. (2013) and Cheng et al., (2017). The new results indicate a total full-depth

ocean warming of 370 ± 81 ZJ (equal to a net heating of 0.38 ± 0.08 W m−2 over the global surface) from 1960 to 2019,

with contributions of 41.0%, 21.5%, 28.6% and 8.9% from the 0–300-m, 300–700-m, 700–2000-m, and below-2000-m lay-

ers, respectively. The uncertainty in the OHC record has been greatly reduced in recent decades through improvements in

the ocean observation system (Meyssignac et al., 2019), which is represented by error bars in Fig. 1 (the calculation of the un-

certainty range is presented in detail in Cheng et al. (2017). Furthermore, the penetration of heat into the deep oceans is evid-

ent (Figs. 2 and 3), primarily through the Atlantic Ocean and Southern Ocean (Fig. 3).

The heating was distributed throughout the world’s oceans, with the vast majority of regions showing an increase in

thermal energy (Figs. 1b and 3). The Atlantic Ocean and Southern Ocean (especially near the Antarctic Circumpolar Cur-

rent, 40°–60°S) continued to show a larger warming compared to most of the other basins (Cheng et al., 2019c). It is well-es-

tablished that the Southern Ocean has taken up most of the global warming heat since 1970: multiple observations show

that the ocean south of 30°S at 0–2000 m was responsible for 35%–43% of the increase in global OHC within 1970–2017

(Meredith et al., 2019). Also, this is associated with a net northward heat transport by the oceans across the equator

(Trenberth and Zhang, 2019). Such meridional oceanic heat transport has influenced recent marine heatwaves in the Tas-



Fig. 2. Ocean heat budget from 1960 to 2019 based on IAP analysis data from 0 to 2000 m,

and from Purkey and Johnson (2010) for deep ocean change below 2000 m (units: ZJ). Figure

updated from Cheng et al. (2017). The anomalies are related to a 1958−1962 baseline, and

the time series are smoothed by LOWESS (locally weighted scatterplot smoothing) with a

span width of 24 months. The gray dashed lines are the 95% confidence interval of the total

ocean heat budget.

FEBRUARY 2020  139

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man Sea, which imparts a profound influence on marine fisheries and ecosystems (Behrens et al., 2019; Trenberth and

Zhang, 2019). Interestingly, many of the major marine heatwave events in recent years (Collins et al., 2019) have been loc-

ated near the strong ocean heating regions, such as the Mediterranean Sea, North Pacific (nicknamed “The Blob”), equatori-

al central Pacific, Tasman Sea, and North Atlantic (> 40°N) (Fig. 1b, 3). Marine heatwaves and other stresses caused by

ocean environmental changes clearly pose high risks to biodiversity and fisheries, and cause economic losses.

In the tropics, the spatial pattern of OHC anomalies in 2019 relative to 2018 (Fig. 1c) also reveals the impact of ENSO,

which is the dominant mode of the Earth/ocean’s energy variability on interannual scales (Trenberth et al., 2002; Roem-

mich and Gilson, 2011; Cheng et al., 2019b). ENSO is associated with both heat redistributions within the ocean and heat ex-

change between the oceans and atmosphere. From late 2018 to early 2019, El Niño formed, and after the summer of 2019

the El Niño event decayed and a neutral phase persisted throughout the second half of the year. From La Niña (early 2018)

to El Niño (later 2019), heat discharged from the equatorial and South Pacific Ocean (20°S–5°N) into the Northeast Pacific

Ocean (5°–20°N), resulting in a cooling of the Pacific Ocean within 20°S–5°N and a warming of the Pacific/Indian Ocean

within 5°–20°N on the OHC map in Fig. 1c.

The ocean heating is irrefutable, and a key measure of the Earth’s energy imbalance: the excess GHGs in the air trap

more heat inside the climate system and drives global warming. More than 90% of the heat accumulates in the ocean be-

cause of its large heat capacity, and the remaining heating manifests as atmospheric warming, a drying and warming land-

mass, and melting of land and sea ice. There are no reasonable alternatives aside from anthropogenic emissions of heat-trap-

ping gases (IPCC, 2001, 2007, 2013, 2019; USGCRP, 2017). Increased ocean temperatures lead to rising sea levels

(thermal expansion of the ocean and added mass from melting land ice) (Oppenheimer et al., 2019). According to the alti-

metry satellite record, the past 10 years are also the highest in global mean sea level since 1900 (IPCC, 2019).

Increases in ocean temperature reduce dissolved oxygen in the ocean and significantly affect sea life, particularly cor-

als and other temperature- and chemistry-sensitive organisms (Abram et al., 2019; Bindoff et al., 2019). The increasing heat

increases evaporation, and the extra moisture in the warmer atmosphere nourishes heavy rains and promotes flooding

(Trenberth et al., 2003; Held and Soden, 2006; Trenberth, 2011; Collins et al., 2019), leading to a more extreme hydrologic-

al cycle and more extreme weather (in particular hurricanes and typhoons) (Trenberth et al., 2018). It is one of the key reas-



Fig. 3. Vertical section of the ocean temperature trends within 1960 to 2019 from the sea surface to 2000 m (60-year

ordinary least-squares linear trend). Shown are the zonal mean sections in each ocean basin organized around the

Southern Ocean (south of 60°S) in the center. Black contours show the associated climatological mean temperature

with intervals of 2°C (in the Southern Ocean, 1°C intervals are provided in dashed contours). IAP gridded data are

used.

140 VOLUME 37

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ons why the Earth has experienced increasing catastrophic fires in the Amazon, California, and Australia in 2019 (extend-

ing into 2020 for Australia).

It is important to note that ocean warming will continue even if the global mean surface air temperature can be stabil-

ized at or below 2°C (the key policy target of the Paris Agreement) in the 21st century (Cheng et al., 2019a; IPCC, 2019),

due to the long-term commitment of ocean changes driven by GHGs. Here, the term “commitment” means that the ocean

(and some other components in the Earth system, such as the large ice sheets) are slow to respond and equilibrate, and will

continue to change even after radiative forcing stabilizes (Abram et al., 2019). However, the rates and magnitudes of ocean

warming and the associated risks will be smaller with lower GHG emissions (Cheng et al., 2019a; IPCC, 2019). Hence, the

rate of increase can be reduced by appropriate human actions that lead to rapid reductions in GHG emissions (Cheng et al.,

2019a; IPCC, 2019), thereby reducing the risks to humans and other life on Earth.

Data and methods

The method used here, developed at the IAP, involves calculating ocean temperatures down to 2000 m using all avail-

able observations from various measurement devices from the World Ocean Database (WOD) of the National Oceanic and

Atmospheric Administration/National Center for Environmental Information (NOAA/NCEI). The data are available at

http://159.226.119.60/cheng/ and www.mecp.org.cn/. The primary input data are bias-corrected XBT and other available

measurements (i.e. Argo, moorings, gliders, CTD, bottle, MBT etc.) from WOD. Model simulations were used to guide the

gap-filling method from point measurements to the grid, while sampling error was estimated by sub-sampling the Argo data

at the locations of the earlier observations [a full description of the method can be found in Cheng et al. (2017)]. Since approx-

imately 2005, the Argo observing network was instituted, which significantly improved the ocean-measurement capability

(Argo, 2000). The Argo data were collected and made freely available by the International Argo Program and the national

programs that contribute to it (http://www.argo.ucsd.edu; http://argo.jcommops.org). The Argo Program is part of the Global

Ocean Observing System. Altimetry sea level information comes from https://www.aviso.altimetry.fr/en/data/products/ocean-

indicators-products/mean-sea-level.html. ENSO information can be found at https://origin.cpc.ncep.noaa.gov/products/analys-

is_monitoring/ensostuff/ONI_v5.php. NOAA/NCEI ocean heat content data can be found in https://www.nodc.noaa.gov/

OC5/3M_HEAT_CONTENT/.

Acknowledgements.  The IAP analysis is supported by the National Key Research and Development Program of China (Grant Nos.

2016YFC1401806 and 2017YFA0603202). Author contributions: LC and JZ are responsible for the IAP analysis; JA and LC drafted the

initial manuscript. All coauthors provide continual and vital support to the IAP analysis and activities; plus, they contributed to refining

this manuscript. NCAR is sponsored by the US National Science Foundation. TB, RL contribution funded in partnership with the NOAA

OAR Ocean Observing and Monitoring Division. The efforts of Dr. Fasullo in this work were partially supported by the Regional and Glob-

al Model Analysis (RGMA) component of the Earth and Environmental System Modeling Program of the U.S. Department of Energy's Of-

fice of Biological & Environmental Research (BER) via National Science Foundation IA 1844590. The efforts of Dr. Fasullo in this work

were also supported in part by NSF Award #AGS-1419571.

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The marine environment of the Arctic Ocean has changed rapidly in recent decades. We used reanalysis data and observational data to explore the variations in the upper ocean heat content (OHC) of the Canadian Basin (CB) and the variations in the temperature profiles of the Southern Canadian Basin (SCB). Both the reanalysis data and observational data show increasing trends for the OHC of the CB from 1993 to 2023. Compared to the World Ocean Atlas data (WOA 18/23), the reanalysis data (ORAS5 or GLORYS12V1) significantly underestimated the values of the upper OHC of the Canadian Basin. To explain the OHC differences, the Ice-Tethered Profiler (ITP) observational data were used to analyze the variations in the vertical temperature profiles. We found that the reanalysis data remarkably underestimated the maximum temperatures of the subsurface Pacific warm water and its increasing trend. Based on the short-term prediction results from the Bi-LSTM neural network, we forecasted that the upper OHC will continue to increase in the SCB, mainly due to the warming of the intermediate Atlantic warm water. The research results provide a valuable reference for assessing and improving climate-coupled models.

No coral recovery three years after a major bleaching event in reefs in the Southwestern Atlantic refugium

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Apr 2024
MAR BIOL

Mass bleaching events are growing in duration and intensity. Besides causing extensive mortality, the progressively shorter time between events disrupts the ability of reefs to recover. The unique reefs of the Southwestern Atlantic are often considered climate refugia as they have suffered less bleaching-related mortality when compared to Indo–Pacific and Caribbean reefs. However, their recovery capacity still requires investigation. In 2019, an unprecedented heatwave triggered the most severe bleaching episode recorded for Southwestern Atlantic reefs. Therefore, this study aimed to (i) document the bleaching incidence and mortality during the heatwave, and (ii) assess coral recovery over 3 years. We measured bleaching incidence and monitored coral cover through surveys in three Southern Bahia (central Brazilian coast) reefs before, during and after thermal stress. Our findings show that coral assemblages were exposed to a 5-month-long thermal anomaly, experiencing thermal stress peaking at 14.1 ºC-weeks. Roughly 70% of the coral cover was bleached, resulting in a decline of ~ 40%. Millepora alcicornis, Mussismilia braziliensis, and Mussismilia harttii were among species that mortality exceeded 50%. After 3 years, corals showed no increase in cover neither at assemblage nor species levels. This constrained recovery capacity may indicate the breakdown of the refugium, and also trade-off for resistance. Typical features of the region, such as high turbidity and the dominance of massive corals, provide these reefs with bleaching resistance, but likely also limit their recovery. With the anticipated effects of the 2023–24 El Niño–Southern Oscillation in the southern hemisphere, still unrecovered Southwestern Atlantic reefs face a substantial challenge.

Marine fishes experiencing high-velocity range shifts may not be climate change winners

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Mar 2024
Nat. Ecol. Evol.

Climate change is driving the global redistribution of species. A common assumption is that rapid range shifts occur in tandem with overall stable or positive abundance trends throughout the range and thus these species may be considered as climate change ‘winners’. However, although establishing the link between range shift velocities and population trends is crucial for predicting climate change impacts it has not been empirically tested. Using 2,572 estimates of changes in marine fish abundance spread across the world’s oceans, we show that poleward range shifts are not necessarily associated with positive population trends. Species experiencing high-velocity range shifts seem to experience local population declines irrespective of the position throughout the species range. High range shift velocities of 17 km yr⁻¹ are associated with a 50% decrease in population sizes over a period of 10 yr, which is dramatic compared to the overall stable population trends in non-shifting species. This pattern, however, mostly occurs in populations located in the poleward, colder, portion of the species range. The lack of a positive association between poleward range shift velocities and population trends at the coldest portion of the range contrasts with the view that rapid range shifts safeguard against local population declines. Instead, our work suggests that marine fishes experiencing rapid range shifts could be more vulnerable to climatic change and therefore should be carefully assessed for conservation status.

Physics‐Informed Deep Operator Learning Based on Reduced‐Order Modeling for Retrieving the Ocean Interior Density From the Surface

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Feb 2024

Exploring methods to reconstruct the ocean interior from surface data is a crucial focus in the study of ocean processes and phenomena due to the shortage of subsurface and deep‐sea data. Nonetheless, the existing methods predominantly concentrate on either data‐driven or dynamical methodologies, with limited exploration of integrating the strengths of both approaches. To combine the advantages of these two methods for reconstructing the subsurface density field from surface data, a novel dynamics‐constrained deep operator learning network based on reduced‐order model is proposed. Encoding the mean‐squared residuals of the reduced‐order equation along with the mean‐squared error between the network outputs and targets into the loss function effectively merges the dynamical and data constraints during the training process. This integration makes the network outputs and inputs approximately satisfy a specific form of the equation, allowing for interpretability, and once the network is well‐trained, rapid reconstruction evaluation can be performed. The reduced‐order equation is established by the Galerkin projection of quasi‐geostrophic equation onto the low‐dimensional subspace identified via reduced‐basis, which explains the vertical variation of ocean density. The developed model can tackle the challenge of directly measuring subsurface potential vorticity and predicting subsurface density. Evaluation is conducted using simulation data from the Max‐Planck‐Institute ocean model, indicating that it can offer precise estimations, outperforms the purely data‐driven algorithm presented in the paper and the interior plus surface quasi‐geostrophic method, and enables model sharing across different regions.

Biogenic volatile organic compound emissions in response to climate change-induced environmental stresses

Chapter

Jan 2024

Anthropogenic CO2 , air–sea CO2 fluxes, and acidification in the Southern Ocean: results from a time-series analysis at station OISO-KERFIX (51° S–68° E)

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Jun 2024
OCEAN SCI

The temporal variation of the carbonate system, air–sea CO2 fluxes, and pH is analyzed in the southern Indian Ocean, south of the polar front, based on in situ data obtained from 1985 to 2021 at a fixed station (50°40′ S–68°25′ E) and results from a neural network model that reconstructs the fugacity of CO2 (fCO2) and fluxes at monthly scale. Anthropogenic CO2 (Cant) is estimated in the water column and is detected down to the bottom (1600 m) in 1985, resulting in an aragonite saturation horizon at 600 m that migrated up to 400 m in 2021 due to the accumulation of Cant. At the subsurface, the trend of Cant is estimated at +0.53±0.01 µmol kg−1 yr−1 with a detectable increase in the trend in recent years. At the surface during austral winter the oceanic fCO2 increased at a rate close to or slightly lower than in the atmosphere. To the contrary, in summer, we observed contrasting fCO2 and dissolved inorganic carbon (CT) trends depending on the decade and emphasizing the role of biological drivers on air–sea CO2 fluxes and pH inter-annual variability. The regional air–sea CO2 fluxes evolved from an annual source to the atmosphere of 0.8 molC m−2 yr−1 in 1985 to a sink of −0.5 molC m−2 yr−1 in 2020. Over 1985–2020, the annual pH trend in surface waters of -0.0165±0.0040 per decade was mainly controlled by the accumulation of anthropogenic CO2, but the summer pH trends were modulated by natural processes that reduced the acidification rate in the last decade. Using historical data from November 1962, we estimated the long-term trend for fCO2, CT, and pH, confirming that the progressive acidification was driven by the atmospheric CO2 increase. In 59 years this led to a diminution of 11 % for both aragonite and calcite saturation state. As atmospheric CO2 is expected to increase in the future, the pH and carbonate saturation state will decrease at a faster rate than observed in recent years. A projection of future CT concentrations for a high emission scenario (SSP5-8.5) indicates that the surface pH in 2100 would decrease to 7.32 in winter. This is up to −0.86 lower than pre-industrial pH and −0.71 lower than pH observed in 2020. The aragonite undersaturation in surface waters would be reached as soon as 2050 (scenario SSP5-8.5) and 20 years later for a stabilization scenario (SSP2-4.5) with potential impacts on phytoplankton species and higher trophic levels in the rich ecosystems of the Kerguelen Islands area.

Meridional Oceanic Heat Transport Influences Marine Heatwaves in the Tasman Sea on Interannual to Decadal Timescales

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May 2019

Marine heatwaves (MHWs) pose an increasing threat to the ocean’s wellbeing as global warming progresses. Forecasting MHWs is challenging due to the various factors that affect their occurrence, including large variability in the atmospheric state. In this study we demonstrate a causal link between ocean heat content and the area and intensity of MHWs in the Tasman Sea on interannual to decadal time scales. Ocean heat content variations are more persistent than ‘weather-related’ atmospheric drivers (e.g., blocking high pressure systems) for MHWs and thus provide better predictive skill on timescales longer than weeks. Using data from a forced global ocean sea-ice model, we show that ocean heat content fluctuations in the Tasman Sea are predominantly controlled by oceanic meridional heat transport from the subtropics, which in turn is mainly characterized by the interplay of the East Australian Current and the Tasman Front. Variability in these currents is impacted by wind stress curl anomalies north of this region, following Sverdrup’s and Godfrey’s ‘Island Rule’ theories. Data from models and observations show that periods with positive upper (2000 m) ocean heat content anomalies or rapid increases in ocean heat content are characterized by more frequent, larger, longer and more intense MHWs on interannual to decadal timescales. Thus, the oceanic heat content in the Tasman Sea acts as a preconditioner and has a prolonged predictive skill compared to the atmospheric state (e.g., surface heat fluxes), making ocean heat content a useful indicator and measure of the likelihood of MHWs.

Measuring Global Ocean Heat Content to Estimate the Earth Energy Imbalance

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Aug 2019

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.

Evolution of Ocean Heat Content Related to ENSO

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Mar 2019

As the strongest interannual perturbation to the climate system, El Niño–Southern Oscillation (ENSO) dominates the year-to-year variability of the ocean energy budget. Here we combine ocean observations, reanalyses, and surface flux data with Earth system model simulations to obtain estimates of the different terms affecting the redistribution of energy in the Earth system during ENSO events, including exchanges between ocean and atmosphere and among different ocean basins, and lateral and vertical rearrangements. This comprehensive inventory allows better understanding of the regional and global evolution of ocean heat related to ENSO and provides observational metrics to benchmark performance of climate models. Results confirm that there is a strong negative ocean heat content tendency (OHCT) in the tropical Pacific Ocean during El Niño, mainly through enhanced air–sea heat fluxes Q into the atmosphere driven by high sea surface temperatures. In addition to this diabatic component, there is an adiabatic redistribution of heat both laterally and vertically (0–100 and 100–300 m) in the tropical Pacific and Indian oceans that dominates the local OHCT. Heat is also transported and discharged from 20°S–5°N into off-equatorial regions within 5°–20°N during and after El Niño. OHCT and Q changes outside the tropical Pacific Ocean indicate the ENSO-driven atmospheric teleconnections and changes of ocean heat transport (i.e., Indonesian Throughflow). The tropical Atlantic and Indian Oceans warm during El Niño, partly offsetting the tropical Pacific cooling for the tropical oceans as a whole. While there are distinct regional OHCT changes, many compensate each other, resulting in a weak but robust net global ocean cooling during and after El Niño.

2018 Continues Record Global Ocean Warming

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Mar 2019

How fast are the oceans warming?

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Jan 2019

Observational records of ocean heat content show that ocean warming is accelerating

Hurricane Harvey Links to Ocean Heat Content and Climate Change Adaptation

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May 2018

While hurricanes occur naturally, human-caused climate change is supercharging them and exacerbating the risk of major damage. Here using ocean and atmosphere observations, we demonstrate links between increased upper ocean heat content due to global warming with the extreme rainfalls from recent hurricanes. Hurricane Harvey provides an excellent case study as it was isolated in space and time. We show that prior to the beginning of northern summer of 2017, ocean heat content was the highest on record both globally and in the Gulf of Mexico, but the latter sharply decreased with hurricane Harvey via ocean evaporative cooling. The lost ocean heat was realized in the atmosphere as moisture, and then as latent heat in record-breaking heavy rainfalls. Accordingly, record high ocean heat values not only increased the fuel available to sustain and intensify Harvey but also increased its flooding rains on land. Harvey could not have produced so much rain without human-induced climate change. Results have implications for the role of hurricanes in climate. Proactive planning for the consequences of human-caused climate change is not happening in many vulnerable areas, making the disasters much worse.

2017 was the warmest year on record for the global ocean

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Mar 2018

Taking the Pulse of the Planet

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Sep 2017

How fast is Earth warming? Ocean heat content and sea level rise measurements may provide a more reliable answer than atmospheric measurements.

Observed Interhemispheric Meridional Heat Transports and the Role of the Indonesian Throughflow in the Pacific Ocean

Article

Aug 2019

The net surface energy flux is computed as a residual of the energy budget using top-of-atmosphere radiation combined with the divergence of the column-integrated atmospheric energy transports, and then used with the vertically-integrated ocean heat content tendencies to compute the ocean meridional heat transports (MHTs). The mean annual cycles, and 12-month running mean MHTs as a function of latitude are presented for 2000-2016. Effects of the Indonesian Throughflow (ITF), associated with a net volume flow around Australia accompanied by a heat transport are fully included. Because the ITF-related flow necessitates a return current northward in the Tasman Sea that relaxes during El Niño, the reduced ITF during El Niño may contribute to warming in the south Tasman Sea by allowing the East Australian current to push farther south even as it gains volume from the tropical waters not flowing through the ITF. Although evident in 2015-16, when a major marine heat wave occurred, these effects can be overwhelmed by changes in the atmospheric circulation. Large interannual MHT variability in the Pacific is four times that of the Atlantic. Strong relationships reveal influences from the southern subtropics on ENSO for this period. At the equator, northward ocean MHT arises mainly in the Atlantic (0.75 PW), offset by the Pacific (-0.33 PW) and Indian Oceans (-0.20 PW) while the atmosphere transports energy southward (-0.35 PW). The net equatorial MHT southward (-0.18 PW) is enhanced by -0.1 PW that contributes to the greater warming of the southern (vs northern) oceans.

Modeling Global Change Ecology in a High–Carbon Dioxide World

Article