Another Record: Ocean Warming Continues through 2021 despite La Niña Conditions

Abstract

The increased concentration of greenhouse gases in the atmosphere from human activities traps heat within the climate system and increases ocean heat content (OHC). Here, we provide the first analysis of recent OHC changes through 2021 from two international groups. The world ocean, in 2021, was the hottest ever recorded by humans, and the 2021 annual OHC value is even higher than last year’s record value by 14 ± 11 ZJ (1 zetta J = 1021 J) using the IAP/CAS dataset and by 16 ± 10 ZJ using NCEI/NOAA dataset. The long-term ocean warming is larger in the Atlantic and Southern Oceans than in other regions and is mainly attributed, via climate model simulations, to an increase in anthropogenic greenhouse gas concentrations. The year-to-year variation of OHC is primarily tied to the El Niño-Southern Oscillation (ENSO). In the seven maritime domains of the Indian, Tropical Atlantic, North Atlantic, Northwest Pacific, North Pacific, Southern oceans, and the Mediterranean Sea, robust warming is observed but with distinct inter-annual to decadal variability. Four out of seven domains showed record-high heat content in 2021. The anomalous global and regional ocean warming established in this study should be incorporated into climate risk assessments, adaptation, and mitigation.

Full text

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Another Record: Ocean Warming Continues through 2021
despite La Niña Conditions
Lijing CHENG*1,2, John ABRAHAM3, Kevin E. TRENBERTH4, John FASULLO4, Tim BOYER5,
Michael E. MANN6, Jiang ZHU1,2, Fan WANG2,7, Ricardo LOCARNINI5, Yuanlong LI2,7, Bin ZHANG2,7,
Zhetao TAN1,2, Fujiang YU8, Liying WAN8, Xingrong CHEN8, Xiangzhou SONG9, Yulong LIU10,
Franco RESEGHETTI11, Simona SIMONCELLI12, Viktor GOURETSKI1, Gengxin CHEN13,
Alexey MISHONOV5,14, and Jim REAGAN5
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
6Department of Meteorology &Atmospheric Science, The Pennsylvania
State University, University Park, Pennsylvania 16802, USA
7Institute of Oceanology, Chinese Academy of Sciences, Qingdao 266071, China
8National Marine Environmental Forecasting Center, Ministry of
Natural Resources of China, Beijing 100081, China
9College of Oceanography, Hohai University, Nanjing 210098, China
10National Marine Data and Information Service, Tianjin 300171, China
11Italian National Agency for New Technologies, Energy and Sustainable Economic
Development, S. Teresa Research Center, Lerici 19032, Italy
12Istituto Nazionale di Geofisica e Vulcanologia, Sede di Bologna, Bologna 40128, Italy
13South China Sea Institute of Oceanology, Chinese Academy of Sciences, Guangzhou 510301, China
14ESSIC/CISESS-MD, University of Maryland, College Park, MD 20742, USA
(Received 19 December 2021; revised 8 January 2022; accepted 10 January 2022)
ABSTRACT
The increased concentration of greenhouse gases in the atmosphere from human activities traps heat within the climate
system and increases ocean heat content (OHC). Here, we provide the first analysis of recent OHC changes through 2021
from two international groups. The world ocean, in 2021, was the hottest ever recorded by humans, and the 2021 annual
OHC value is even higher than last year’s record value by 14 ± 11 ZJ (1 zetta J = 1021 J) using the IAP/CAS dataset and by
16 ± 10 ZJ using NCEI/NOAA dataset. The long-term ocean warming is larger in the Atlantic and Southern Oceans than in
other regions and is mainly attributed, via climate model simulations, to an increase in anthropogenic greenhouse gas
concentrations. The year-to-year variation of OHC is primarily tied to the El Niño-Southern Oscillation (ENSO). In the
seven maritime domains of the Indian, Tropical Atlantic, North Atlantic, Northwest Pacific, North Pacific, Southern oceans,
and the Mediterranean Sea, robust warming is observed but with distinct inter-annual to decadal variability. Four out of
seven domains showed record-high heat content in 2021. The anomalous global and regional ocean warming established in
this study should be incorporated into climate risk assessments, adaptation, and mitigation.
Key words:La Niña,ocean heat,ocean warming,attribution,observation
Citation: Cheng, L. J, and Coauthors, 2022: Another record: Ocean warming continues through 2021 despite La Niña
conditions. Adv. Atmos. Sci., https://doi.org/10.1007/s00376-022-1461-3.
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* Corresponding author: Lijing CHENG
Email: chenglij@mail.iap.ac.cn
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ADVANCES IN ATMOSPHERIC SCIENCES, 2022
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• Original Paper •
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©The Author(s) 2022. This article is published with open access at link.springer.com
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Article Highlights:
• The world ocean, in 2021, was the hottest ever recorded by humans.
• The warming pattern is mainly attributed to increased anthropogenic greenhouse gas concentrations, offset by the impact
of aerosols.
• Ocean warming has far-reaching consequences and should be incorporated into climate risk assessments, adaptation, and
mitigation.
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1.Introduction
The increased concentrations of greenhouse gases in
the atmosphere from human activities trap heat within the cli-
mate system and result in massive changes in the climate sys-
tem. As a result, outgoing energy from the Earth system is
not balancing the incoming solar radiation, thus creating
Earth’s Energy Imbalance (EEI) in the climate system
(Trenberth et al., 2014; von Schuckmann et al., 2016a,
2020a; Wijffels et al., 2016; Johnson et al., 2018; Cheng et
al., 2019a). The oceans store over 90% of EEI, leading to an
increase of ocean heat content (OHC), which currently
provides the best estimate for EEI (Hansen et al., 2011;
IPCC, 2013; Rhein et al., 2013; Trenberth et al., 2016;
Abram et al., 2019). Ocean warming leads to increased
ocean vertical stratification, thermal expansion, and sea-
level rise. These processes provide a compelling means to
quantify climate change (Cheng et al., 2018).
This study provides the first analysis of recent OHC
changes through 2021. Two international data products
include those from the Institute of Atmospheric Physics
(IAP) at the Chinese Academy of Sciences (CAS) (Cheng et
al., 2017) and the National Centers for Environmental Inform-
ation (NCEI) of the National Oceanic and Atmospheric
Administration (NOAA) (Levitus et al., 2012). Both data-
sets corrected systematic errors and then used thorough map-
ping methods to convert discrete ocean measurements into a
comprehensive picture of the ocean. Both global and
regional analyses of OHC changes are provided in this
study.
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2.Data and Methods
The IAP/CAS and NCEI/NOAA analyses are based on
available in situ observations from various measurement
devices held in the World Ocean Database (WOD) of the
NCEI/NOAA. Data from all instruments are used, includ-
ing eXpendable BathyThermographs (XBTs), profiling
floats from Argo, moorings, gliders, Conductivity/Temperat-
ure/Depth devices (CTDs), bottles, and instruments on mar-
ine mammals (Boyer et al., 2018). The XBT biases are correc-
ted according to Cheng et al. (2014) for IAP/CAS and Levi-
tus et al. (2009) for NCEI/NOAA. Model simulations guide
the mapping method from point measurements to the compre-
hensive grid in the IAP/CAS product. At the same time,
sampling errors are estimated by sub-sampling the Argo
data at the locations of the earlier observations (a full descrip-
tion of the method is in Cheng et al., 2017).
The Argo Program is part of the Global Ocean
Observing System. The Argo observing network achieved a
near-global upper-2000 m coverage since about 2005
(Argo, 2020). Argo data are made freely available by the
International Argo Program and the contributing national pro-
grams (http://www.argo.ucsd.edu; http://argo.jcommops.
org).
In addition to these observations, the Community Earth
System Model Version 1 (CESM1) Large Ensemble
(LENS; Kay et al., 2015) data are used to explore the influ-
ence of different forcings (aerosols, greenhouse gasses, indus-
trial aerosols, biomass aerosols, land use, and land cover)
on the formation of OHC patterns in a large ensemble simula-
tion of climate. Previous assessments indicate that CESM is
one of the most skilled models representing the global
energy budget, water cycles, and associated dynamics
(Fasullo, 2020).
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3.Global ocean changes
The up-to-date data indicate that the OHC in the upper
2000 m layer of the world’s oceans has increased with a
mean rate of 5.7 ± 1.0 ZJ yr–1 for the 1958–2021 period
(IAP/CAS) and 4.7 ± 1.0 ZJ yr–1 for the 1958–2021 period
(NCEI/NOAA) (Fig. 1a). Both datasets show an unambigu-
ous increase in ocean warming since the late 1980s (Fig. 1a).
From 1986–2021, the average annual increase is 9.1 ± 0.3
ZJ yr–1 for IAP and 8.3 ± 0.7 ZJ yr–1 for NCEI/NOAA.
These warming rates represent a maximum of 8-fold
increase compared to 1958–85 (1.2 ± 0.6 ZJ yr–1 IAP/CAS,
1.5 ± 1.0 ZJ yr–1 for NCEI/NOAA). Moreover, each decade
since 1958 has been warmer than the preceding decades.
The 2021 annual OHC value is higher than the last
year’s value, by 14 ± 11 ZJ using the IAP/CAS data and by
16 ± 10 ZJ using NCEI/NOAA (95% confidence interval).
Both projections are the highest on record (Table 1). Differ-
ences between the OHC analyses reflect the uncertainties in
the calculation due to data quality, mapping differences, and
data coverage. Nevertheless, it is evident that according to
both IAP/CAS and NCEI/NOAA, the 2021 oceans were the
hottest ever recorded by humans.
There are notable inter-annual fluctuations in the OHC
record (Fig. 1b); Cheng et al. (2018) indicated that it
requires ~four years for the long-term trend signal to signific-
antly exceed the inter-annual variability at the 95% confid-
ence interval, noting that ENSO is the dominant driver of
year-to-year variations in OHC (i.e., Cheng et al., 2019b).
2RECORD OCEAN WARMING IN 2021
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The Indo-Pacific basin transitioned from a weak El Niño
state in the first six months of 2020 toward a La Niña state
during the last half of 2020, and a La Niña state has since con-
tinued in 2021. There is a decreasing tendency in OHC dur-
ing the transition from El Niño to La Niña because of ocean
heat release associated with anomalous warming of sea sur-
face conditions in the tropical Pacific Ocean (Cheng et al.,
2019b) (Fig. 1b). During La Niña, the ocean absorbs heat,
which caused an increase in OHC from late-2020 to early
2021 (Fig. 1b). Similar OHC changes also have occurred dur-
ing the 2009, 2015, and 2017 El Niño events. The El Niño-
driven heat buildup and higher sea levels are most typical of
the tropical western Pacific region (see Fig. 2).
In addition to providing an update on the 2021 OHC,
we present an improved calculation for previous years. Both
IAP/CAS and NCEI/NOAA have re-calculated the 2020
OHC values using the most up-to-date observations. A not-
able revision of 0–2000 m OHC anomaly from 234 ZJ to
221 ZJ is found for IAP/CAS data. With this correction, the
IAP/CAS and NCEI/NOAA OHC time series become consist-
ent in 2020 and 2021 (Fig. 1b), increasing confidence in the
near real-time OHC calculation. By comparing the two ver-
sions of WOD in situ observational data, it was found that
data Quality-Control (QC) flags had not been assigned in
the previous dataset (i.e., there is no QC applied to the
Table 1.  Ranked order of the hottest five years of the global
ocean, since 1955. The OHC values are anomalies for the upper
2000 m in units of ZJ relative to the 1981–2010 average.
Rank Year IAP/CAS NCEI/NOAA
1 2021 235 227
2 2020 221 211
3 2019 214 210
4 2017 202 189
5 2018 195 196
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Fig. 1. (upper) The global upper 2000 m OHC from 1958 through 2021. The histogram presents annual anomalies
relative to a 1981–2010 baseline, with positive anomalies shown as red bars and negative anomalies as blue. Units:
ZJ. (bottom) Detrended OHC time series from 2005 to 2021 compared with ONI index.
CHENG ET AL. 3
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data), highlighting the importance of QC in OHC calcula-
tions. Considering the non-negligible impact of QC on the
OHC estimate, comprehensive quantification of QC uncer-
tainty continues to be a priority.
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4.Regional patterns of ocean warming
The spatial pattern of upper OHC anomaly (0–2000 m)
(Fig. 2a) illustrates several key features, including an anom-
aly maxima near 40° in both hemispheres and broad anomal-
ous warming in the Atlantic Ocean relative to other ocean
basins, but a pronounced minimum in the northern North
Atlantic Ocean. The drivers of these features can be
explored by using so-called single-forcing large ensembles,
within which only a single external climate forcing agent is
held fixed over time in a multi-member ensemble experi-
ment (Deser et al., 2020). By averaging across ensemble mem-
bers and differencing with the fully-forced ensemble, the con-
tributions of internal variability are reduced to allow direct
estimation of the response to forcing. Important uncertain-
ties exist in inferring natural changes from such ensembles,
including uncertainties related to model structure and
imposed external forcing agents. Strategies for addressing
these uncertainties are addressed below.
Here, we use the Community Earth System Version 1
(CESM1) Large Ensemble (CESM1-LE; Kay et al., 2015)
and Single-Forcing Large Ensemble (CESM1-SF; Deser et
al., 2020) to attribute the drivers of observed OHC trend pat-
terns from 1979 to 2020 (Fig. 3). A strong correlation pat-
tern exists between the fully-forced ensemble mean and
observed changes (Fig. 3a vs. Fig. 2a), thus providing eviden-
tiary support for both the fidelity of the CESM1-LE and the
emergence of forced changes in the presence of internal vari-
ability (i.e., Cheng et al., 2018; Fasullo and Nerem, 2018).
Many of the salient features apparent in observations are
also evident in the ensemble mean, suggesting a role for for-
cing in their development. Examples include the relative max-
ima near 40° in each hemisphere, the region of strong cool-
ing in the northern Atlantic southeast of Greenland, the
subtle changes in the Pacific Ocean equatorward of 30°, and
the relative warming of the Atlantic Ocean as compared to
other ocean basins (Fig. 3a). Variability in trends across
ensemble members is largest in the oceans north of 30°N
(Fig. 3b).
The influence of industrial aerosols (AER, Fig. 3c) is
strong and pervasive across much of the global ocean, exert-
ing a strong cooling influence between 30°N and 60°S and
significantly contributing to the regional cooling southeast
of Greenland. The influence of biomass aerosols (BMB,
Fig. 3d) is more regional yet important, with strong cooling
signals evident in all basins and a warming contribution to
the North Atlantic. The contribution of greenhouse gases
(GHG, Fig. 3e) is notable in nearly all regions, with substan-
tial warming, especially near 40°S and across the Atlantic
Ocean. A strong contribution to cooling southeast of Green-
land is also evident. Lastly, land use and land cover (LULC)
contributions are small, with significant areas spanning less
than 5% of the global ocean.
Together these results promote an understanding of the
observed pattern of ocean warming since 1980. Forcing
from greenhouse gases dominates many of the observed fea-
tures but contributions from AER and BMB are also import-
ant. Pervasive warming of the global ocean is driven by
GHG and offset somewhat by both AER and BMB (Fig. 3c,
d). The elevated warming of the Atlantic Ocean relative to
other basins results from both the elevated warming effects
of GHG and the reduced cooling effects of AER in the
Atlantic. Together these effects are offset somewhat by a
strong regional cooling driven by BMB. The region of
strong cooling southeast of Greenland is driven by both
GHG and AER influences (associated with AMOC
changes). It stands out as one of the few regions where
GHG and AER effects mutually reinforce each other.
Lastly, the relative minimum in the tropical Pacific Ocean
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Fig. 2. (a) The ocean heat content anomaly in 2021 relative to
1981–2010 baseline. (b) The difference of OHC for upper
2000 m between 2021 and 2020. (c) As in (b) but for
NCEI/NOAA data. Units: 109 J m–2. [Data updated from
Cheng et al. (2017) in (a) and (b), from Levitus et al. (2012) in
(c)].
4RECORD OCEAN WARMING IN 2021
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equatorward of 30° results from the combined influences of
relatively weak GHG-driven warming and the offsetting
effects of both AER and BMB.
This diagnosis of the drivers of OHC trend patterns
relies on the fidelity of the CESM1 and the estimates of
external forcing agents used in the CESM1-LE. Further
exploration with alternative models and forcings will play
an important role in establishing confidence in the interpreta-
tions based on the experiments used here. Because of space
limitations here, accounting for the uncertainties in forcings
(Fasullo et al., 2021; Fyfe et al., 2021; Smith and Foster,
2021) remains a topic for future work. Formal detection and
attribution analysis plus single forcing experiments with
more climate models are also being conducted.
Comparing the spatial OHC anomalies in 2021 versus
2020 shows an imprint of La Niña (Figs. 2b, c, Cheng et al.,
2019b). The NCEI/NOAA data (Fig. 2c) shows a consistent
spatial pattern compared with IAP/CAS (Fig. 2b), but the
anomalies are spottier and tied to the spatial covariance in
mapping strategy. The IAP/CAS product is smoother than
NCEI/NOAA because of the stronger effect of smoothing
(Cheng et al., 2017). There is a strong increase of OHC in
the western Pacific that extends into the South and North
Pacific regions to 20°S and 20°N, and a broad decrease of
OHC in the eastern Pacific, including coastal Peru and the
California oceans (Figs. 2b, c). A reverse zonal gradient
(warm in the east and cold in the west) is evident in the
Indian Ocean. This pattern in the Indo-Pacific Ocean mainly
reflects the thermocline changes during ENSO: the thermo-
cline is steeper during La Niña, with a deeper thermocline
in the western Pacific-Indonesian warm pool. Meanwhile,
the thermocline uplifts in the tropical eastern Pacific and west-
ern Indian oceans, leading to cooling anomalies. The trop-
ical Atlantic Ocean shows a small decrease of OHC
(20°S−20°N), likely due to two separate but reinforcing
factors: (1) the shift of the Walker circulation during La
Niña events increases evaporation in the tropical Atlantic
(Wang, 2019) and (2) those same La Niña conditions contrib-
uted to an especially active and energetic Atlantic hurricane
season as tropical storm-related mixing leads to substantial
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Fig. 3. Ensemble mean trends in 0–2000 m OHC in (a) the CESM1-LE and CESM1-SF estimated contributions from (c)
industrial and (d) biomass aerosols, (e) greenhouse gasses, and (f) change in land use and land cover. Units: 109 J m–2.
Stippled and hatched regions correspond to areas where positive and negative trends exceed twice the standard ensemble
error, respectively. (b) The standard deviation of CESM1-LE members in 0–2000 m OHC trend.
CHENG ET AL. 5
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poleward ocean heat export from the tropics (Sriver and
Huber, 2007).
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5.Basin-wide changes and regional hot spots
A regional assessment of ocean warming is relevant to
community risk assessment and societal adaptation, even
more so than global metrics. Here, we briefly assess basin
OHC changes, including several regional hot spots.
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5.1.The northwest Pacific Ocean
The Northwest Pacific Ocean is the most active basin
for tropical storms on the planet, accounting for one-third of
all tropical cyclones. Changes in its nature are directly relev-
ant to weather conditions and societies in East Asia. The
OHC shows strong inter-annual and decadal fluctuations in
this area (Fig. 4a), which are predominantly associated with
internal climate variabilities such as ENSO and Pacific
Decadal Variability (PDV) (Cheng et al., 2019b; Xiao et al.,
2020). The typhoon activities in the Northwest Pacific show
correlations with PDV and further reveal the remote
impacts of the tropical Indian Ocean and Western Pacific
(Yang et al., 2018). Nevertheless, the mean OHC over the
recent decade (2012–21) is higher than the 1981–2010 aver-
age, which could, in turn, impact the regional OHC (Wang
et al., 2014).
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5.2.The Indian Ocean
There was no significant trend in the Indian OHC dur-
ing the late 20th century (Fig. 4b), owing to interdecadal
changes of the Indo-Pacific Walker circulation that drove an
upper-layer cooling of the tropical Indian Ocean and greatly
moderated the greenhouse-gas forced warming (Ummen-
hofer et al., 2021). Unprecedented rapid warming during the
2000s was mainly associated with an increased Indonesian
throughflow heat transport under a negative Interdecadal
Pacific Oscillation (IPO) condition (La Niña-like) of the trop-
ical Pacific (Lee et al., 2015; Li et al., 2018). The warming
trend has been delayed since ~2013, as the IPO shifted back
to its positive phase. Hence, the pronounced interannual fluc-
tuations in the past decade were primarily dictated by
ENSO. The thermocline of the southern tropical Indian
Ocean is particularly sensitive to teleconnection imprints of
ENSO (Xie et al., 2002), as evidenced by the thermocline
depression and OHC increase during the 2015−16 super El
Niño and subsequent thermocline shoaling and OHC
decrease during the 2017−18 La Niña (Li et al., 2020b;
Volkov et al., 2020) (Fig. 4b). The climate of the Southern
Ocean also modulates the subtropical sector of the southern
Indian Ocean. During past decades, the poleward migration
of westerly winds has led to a southward shift of the subtrop-
ical circulation gyre and thereby caused a multi-decadal
increasing trend in the OHC of the subtropical southern
Indian Ocean (Yang et al., 2020; Duan et al., 2021).
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5.3.The tropical Atlantic Ocean
The tropical western North Atlantic Ocean 10°−30°N,
where hurricanes initiate and develop, has shown a continu-
ous increase of OHC since 1958 (Fig. 4c; Trenberth et al.,
2018). La Niña conditions typically are associated with
reduced tropical storm activity in the eastern tropical Pacific
and a greater risk of enhanced activity in the tropical North
Atlantic. In addition to the global warming signature from
continuous unabated warming since 1958 (Fig. 4c), this is
associated with high levels of Atlantic tropical storm activ-
ity during the past two northern summers (Emanuel, 2021a,
b). During 2021 there were 21 named storms, ~30% fewer
than the record 30 named storms of 2020. When atmo-
spheric conditions are favorable, the increased thermal
energy provided by high OHC fuels increased tropical
storm activity (in terms of both frequency, intensity, size
and/or lifetime) and also increases rainfall (Trenberth et al.,
2018).
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5.4.The Mediterranean Sea
In 2021, the OHC in the Mediterranean Sea was the
highest on record since reliable records exist (Fig. 4d). A
marked temperature increase appeared in the last few dec-
ades, starting from the Eastern Basin where warmer Intermedi-
ate Waters (IW) formed and spread towards the Western
Basin on their way back to the North Atlantic (Pinardi et al.,
2015; Section 3.1 in von Schuckmann et al., 2016b; Simon-
celli et al., 2018, 2019; Storto et al., 2019). The Sicily Chan-
nel represents the chokepoint between the Eastern and West-
ern Mediterranean basins where a two-layer system brings
Atlantic Waters (0–150 m) eastwards and IW (150–450 m)
westwards (Schroeder et al., 2017). A temperature and salin-
ity time series collected since 1993 at 400 m depth at the
Sicily Channel show increasing trends for both parameters,
stronger than those observed at intermediate depths in differ-
ent regions of the global ocean (Ben Ismail et al., 2021).
The reported IW rate of temperature increase averages
0.026°C yr–1 with a maximum value of 0.034°C yr–1 after
2011. The IW enters the Tyrrhenian Sea after crossing the
Sicily Channel, where the temperature has been monitored
with XBT probes since 1999 along the MX04 Genova-
Palermo transect (Fig. 5d) as part of the Ship of Opportun-
ity program of GOOS. Figure 5 presents two Hovmöller
plots of mean temperature anomalies in the layer 0–800 m
layer computed along the transect considering different
baselines: one subtracting the monthly average computed
from the MX04 survey (Fig. 5a); the other subtracting the
IAP/CAS baseline 1981–2010 (Fig. 5b). Consistent and con-
tinuous warming of the IW appears from spring 2013 in the
150–450 m layer and propagates progressively deeper. The
mean temperature evolution in the 150–450 m layer (Fig. 5c)
indicates a steep increase between 2014 and 2017 and a lin-
ear trend over the time period 1999–2021 equal to 0.028°C
yr–1, consistent with the one observed in the Sicily Channel.
The overall mean temperature variation is approximately
0.6°C, with temperatures ranging from 13.8°C to 14.4°C.
The warm IW propagated northwards mainly from 38° to
42°N and, as in the Sicily Channel, the IW exhibited a slight
decrease in 2018-2019. The data gathered in September and
6RECORD OCEAN WARMING IN 2021
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Fig. 4. Regional observed upper 2000 m OHC change from 1955 through 2021 relative to 1981–2010 baseline. The time series (black) are smoothed by LOWESS (locally weighted
scatterplot smoothing) with a span width of 24 months. The gray shadings are the 95% confidence interval. [Data updated from Cheng et al. (2017)].
CHENG ET AL. 7
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December 2021 report mean values greater than or equal to
14.4°C, as in 2017, but the heat penetrates progressively
deeper and occupies a larger area.
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5.5.The North Atlantic Ocean
The North Atlantic Ocean shows a warming trend for
the entire instrumental record, with an increasing trend com-
mencing around 2000 (Fig. 4e). The most dramatic warm-
ing occurs in the Gulf Stream region (Figs. 2, 3). Despite
the broad-scale warming, a key feature of the North Atlantic
Ocean is a cooling region south of Greenland (the so-called
“warming hole”) (Seidov et al., 2017). In single forcing exper-
iments, it is demonstrated that both GHG and AER forcings
can produce such a cooling signature (Fig. 3). Previous stud-
ies have indicated that this cooling trend reveals a slow-
down of the Atlantic meridional overturning circulation,
which leads to reduced oceanic heat transport into the warm-
ing hole region (Rahmstorf et al., 2015; Keil et al., 2020).
Other potential culprits include the changes to the Gulf
Stream extension region (Seidov et al., 2019; Piecuch,
2020; Boers, 2021), local atmospheric forcing (Li et al.,
2021), and Indian Ocean warming (Hu and Fedorov, 2020).
In 2021, the North Atlantic OHC was the highest on record
since 1958 (Fig. 4e).
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5.6.The North Pacific Ocean
The North Pacific (30°−62°N) showed a dramatic
increase in OHC after 1990 and reached a record high level
in 2021 (Fig. 4f). The North Pacific Ocean warming is
broad and deep-reaching. Warming anomalies in 2021 (relat-
ive to the 1981–2010 baseline) are ~2°C near the surface
and 1oC at ~300 m in the middle North Pacific (Fig. 6). The
relentless increases in OHC have direct implications for the
frequency, intensity, and extent of marine heat waves
(MHWs) and other “hot spots ” within the ocean (Holbrook
et al., 2019). A series of MHWs have developed here within
the past decade. These are typically triggered by benign atmo-
spheric conditions with anticyclonic circulation, decreased
evaporative cooling, and lighter winds that lead to less
ocean mixing (Holbrook et al., 2019). In the North Pacific
winter, such conditions are favored by La Niña through an
atmospheric bridge (Trenberth et al., 1998), and this helped
set up the North Pacific MHW in 2013-14. Such events
impact marine life and propagate through the food web to lar-
ger marine creatures. “The Blob” was one such strong event
from 2014–16 and demonstrated that the entire ocean food
web can be severely impacted due to these extremes (Corn-
wall, 2019). The 2021 North Pacific warm “blob” was a con-
tinuation of the 2020 anomaly. Scannell et al. (2020) indic-
ate that the oceanic conditions (OHC, salinity, and stratifica-
tion) support the development of marine heat waves in the
North Pacific Ocean. The marine heat wave is also associ-
ated with an atmospheric circulation pattern. A “high-pres-
sure heat dome” developed in late June over the Pacific North-
west and southwest Canada, along with temperatures that
exceeded 40°C (a record-breaking major heatwave), which
resulted in widespread wildfires and associated destruction.
In September and October 2021, the MHW continued and
was strongest in the central North Pacific, consistent with
La Niña influences through the atmospheric bridge from the


Fig. 5. The temperature along the MX04 Genova-Palermo transect in the 1999–2021 time period recorded by XBT probes from
ships of opportunity: (a) Hovmöller plot of mean temperature anomalies computed subtracting the overall average 1999–2021
from each monitoring survey; (b) Hovmöller plot of mean temperature anomalies computed subtracting the IAP/CAS 1981–2010
baseline from each monitoring survey; (c) mean temperature values and relative linear trend in the layer 150–450 m; (d) data
distribution map in the Tyrrhenian and Ligurian Seas (Western Mediterranean).
8RECORD OCEAN WARMING IN 2021




tropics.

5.7.The Southern Ocean
According to model simulations, the Southern Ocean
(SO) served as a major anthropogenic heat sink in the past
century (Frölicher et al., 2015); observation-based estim-
ates suggest that the SO accounted for 30%–60% of the
global OHC increase since ~1970 (IPCC, 2019), contempo-
raneous with significant ocean warming (Fig. 4g; Gille,
2002). Mass subduction of water from the SO mixed layer
serves as a rapid pathway for anthropogenic warming signa-
tures to be communicated to the deep ocean (Marshall and
Speer, 2012). Based on CMIP5 model simulations, Silvy et
al. (2020) showed that the anthropogenic signal ‘emerges’
from the noise and overwhelms the natural variability much
more quickly in the well-ventilated SO water masses than in
Northern Hemisphere waters. The SO shows a clear warm-
ing peak on the northern flank of the Antarctic Circumpolar
Current (ACC) (Figs. 2 and 6) (Böning et al., 2008; Gouret-
ski et al., 2013; Roemmich et al., 2015), corresponding to
the rapid warming of the Subantarctic Mode Water
(SAMW) (Gao et al., 2018) and Antarctic Intermediate
Water (Schmidtko and Johnson, 2012) with widespread
impacts across the entire Southern Hemisphere. By 2021,


Fig. 6. 3-D fields of oceanic temperature changes at 2021 (January to September) relative to 1981–2010 baseline in the
North Pacific Ocean (30°−62°N) (upper), and in the Southern oceans (78°−30°S) (bottom). The IAP/CAS data are used, and
the illustration is modified from Seidov et al. (2021).
CHENG ET AL. 9




the warming exceeded 0.6°C in the major formation regions
of the SAMW, compared to the 1981–2010 baseline (Fig.
6b). The Antarctic continental shelf and adjacent seas also
show significant warming trends (Schmidtko et al., 2014)
linked to the detected warming of abyssal and bottom
waters over the globe (Purkey and Johnson, 2010, 2013).
The surface layer of the subpolar regions shows little warm-
ing and has slightly cooled over the past decades, owing to
wind-driven upwelling, increased northward heat export to
the northern flank of the ACC, and sea ice changes (Armour
et al., 2016). Purich et al. (2018) added that the freshening
of the SO — linked to the amplification of the global hydrolo-
gical cycle — may also favor subpolar surface cooling by
reducing the entrainment of subsurface warm water. These
complex heat uptake and storage patterns are primarily attrib-
utable to greenhouse-gas forcing, with stratospheric ozone
depletion playing a secondary role (Swart et al., 2018).

6.Summary and implications for climate
actions
This study provides up-to-date estimates of OHC
through 2021 based on two international datasets. Single for-
cing simulations are used to analyze the contribution of differ-
ent forcings on the regional OHC pattern. The regional and
global changes both reveal a robust and significant ocean
warming since the late-1950s — the entirety of the reliable
instrumental record. Natural variability and change in ocean
circulation play important roles locally, but the predomin-
ant changes result from human-related changes in atmo-
spheric composition. As oceans warm, the water expands,
and sea level rises. Preparing for sea level rise and its implica-
tions for coastal communities are particularly important.
Changes to engineering design, building codes, and modi-
fications to coastal development plans are recommended in
anticipation of increased sea levels and increases in extreme
precipitation events, which are already being observed (Abra-
ham et al., 2015, 2017; Scambos and Abraham, 2015). In addi-
tion, warmer oceans supercharge the weather systems, creat-
ing more powerful storms and hurricanes, and increased pre-
cipitation. Warmer oceans lead to a warmer and moister atmo-
sphere that promotes more intense rainfall in all storms, espe-
cially hurricanes, thereby increasing the risk of flooding
(Trenberth et al. 2003; IPCC, 2021). Warming ocean waters
threaten marine ecosystems and human livelihoods, for
example, coral reefs and fisheries (IPCC, 2019).
The United Nations has proposed 17 inter-linked goals
and 169 targets focused on maintaining the health and vital-
ity of human societies and natural ecosystems worldwide
(UN, 2021). The Sustainable Development Goals (SDGs)
were set up in 2015 by the United Nations General
Assembly and are intended to be achieved by 2030. Many
goals are closely related to the health of the world’s oceans,
and the ocean’s health is vital to the SDGs. For example,
the SDG13-Climate Actions; SDG14-Life Below Water;
SDG6-Clean Water and Sanitation; SDG2-Zero Hunger;
SDG3-Good Health and Well-Being (Abram et al., 2019;
von Schuckmann et al., 2020) are all either directly or indir-
ectly related to oceans. In 2021, the United Nations initi-
ated the Decade of Ocean Science for SDGs to increase the
awareness of many problems the ocean faces and to build
up capability for ocean monitoring and scientific research.
This study indicates that there are still uncertainties and know-
ledge gaps in monitoring ocean warming; for example, the
quantification of uncertainty from inter-annual to multi-
decadal scales and the impact of data QC and regional differ-
ences of OHCs revealed by different datasets. Thus, better
awareness and understanding of ocean dynamics are funda-
mental in combating climate change.
Acknowledgements.  The IAP/CAS analysis is supported by
the National Natural Science Foundation of China (Grant No.
42122046, 42076202), Strategic Priority Research Program of the
Chinese Academy of Sciences (Grant No. XDB42040402),
National Natural Science Foundation of China (Grant No.
42076202), National Key R&D Program of China (Grant No.
2017YFA0603202), and Key Deployment Project of Centre for
Ocean Mega-Research of Science, CAS (Grant Nos.
COMS2019Q01 and COMS2019Q07). NCAR is sponsored by the
US National Science Foundation. The efforts of Dr. Fasullo in this
work were supported by NASA Award 80NSSC17K0565, and by
the Regional and Global Model Analysis (RGMA) component of
the Earth and Environmental System Modeling Program of the
U.S. Department of Energy’s Office of Biological & Environ-
mental Research (BER) via National Science Foundation IA
1844590. The efforts of Dr. Mishonov and Mr. Reagan were par-
tially supported by NOAA (Grant NA14NES4320003 to CISESS-
MD at the University of Maryland). The IAP/CAS data are avail-
able at http://www.ocean.iap.ac.cn/ and https://msdc.qdio.ac.cn/.
The NCEI/NOAA data are available at https://www.ncei.noaa.
gov/products/climate-data-records/global-ocean-heat-content. The
historical XBT data along the MX04 line (Genova-Palermo) are
available through SeaDataNet - Pan-European infrastructure
(http://www.seadatanet.org) for ocean and marine data manage-
ment. Since 2021, XBT data have been collected in the frame-
work of the MACMAP project funded by the Istituto Nazionale di
Geofisica e Vulcanologia in agreement between INGV, ENEA,
and GNV SpA shipping company that provides hospitality on their
commercial vessels.
Open Access This article is licensed under a Creative Com-
mons Attribution 4.0 International License, which permits use, shar-
ing, adaptation, distribution and reproduction in any medium or
format, as long as you give appropriate credit to the original author (s)
and the source, provide a link to the Creative Commons licence,
and indicate if changes were made. The images or other third party
material in this article are included in the article’s Creative Com-
mons licence, unless indicated otherwise in a credit line to the mater-
ial. If material is not included in the article’s Creative Commons
licence and your intended use is not permitted by statutory regula-
tion or exceeds the permitted use, you will need to obtain permis-
sion directly from the copyright holder. To view a copy of this
licence, visit http://creativecommons.org/licenses/by/4.0/.
10 RECORD OCEAN WARMING IN 2021
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REFERENCES

Abraham, J., J. R. Stark, and W. J. Minkowycz, 2015: Briefing:
Extreme weather: Observed Precipitation Changes in the
USA. Proceedings of the Institution of Civil Engineers-
Forensic Engineering, 168, 68−70, https://doi.org/10.1680/
feng.14.00015.
Abraham, J., L. J. Cheng, and M. E. Mann, 2017: Briefing:
Future climate projections allow engineering planning.
Forensic Engineering, Proceedings of the Institution of Civil
Engineers, 170, 54−57. https://doi.org/10.1680/jfoen.17.
00002.
Abram, N., and Coauthors, 2019: Framing and context of the
report. IPCC Special Report on the Ocean and Cryosphere
in a Changing Climate, H.-O. Pörtner et al., Eds., Intergovern-
mental Panel on Climate Chang, in press.
Argo, 2020: Argo Float Data and Metadata from Global Data
Assembly Centre (Argo GDAC). SEANOE. Available from
https://doi.org/10.17882/42182.
Armour, K. C., J. Marshall, J. R. Scott, A. Donohoe, and E. R.
Newsom, 2016: Southern Ocean warming delayed by circum-
polar upwelling and equatorward transport. Nature
Geoscience, 9(7), 549−554, https://doi.org/10.1038/Ngeo
2731.
Ben Ismail S., K. Schroeder, J. Chiggiato, S. Sparnocchia, and M.
Borghini, 2021: Long term changes monitored in two Mediter-
ranean Channels. Copernicus Marine Service Ocean State
Report, Issue 5, K. von Schuckmann et al., Eds., 48−52,
https://doi.org/10.1080/1755876X.2021.1946240.

Boers, N., 2021: Observation-based early-warning signals for a col-
lapse of the Atlantic Meridional Overturning Circulation.
Nature Climate Change, 11, 680−688, https://doi.org/10.
1038/s41558-021-01097-4.
Böning, C. W., A. Dispert, M. Visbeck, S. R. Rintoul, and F. U.
Schwarzkopf, 2008: The response of the Antarctic Circum-
polar Current to recent climate change. Nature Geoscience,
1(12), 864−869, https://doi.org/10.1038/ngeo362.

Boyer, T. P., and Coauthors, 2018: World Ocean Database 2018.
A. V. Mishonov, Technical Editor, NOAA Atlas NESDIS
87.
Cheng, L., Zhu, J., Cowley, R., Boyer, T., & Wijffels, S., 2014:
Time, Probe Type, and Temperature Variable Bias Correc-
tions to Historical Expendable Bathythermograph Observa-
tions. Journal of Atmospheric and Oceanic Technology,
31(8), 1793−1825, https://doi.org/10.1175/JTECH-D-13-
00197.1.

Cheng, L. J., J. Abraham, Z. Hausfather, and K. E. Trenberth,
2019a: How fast are the oceans warming. . Science, 363,
128−129, https://doi.org/10.1126/science.aav7619.

Cheng, L. J., K. E. Trenberth, J. Fasullo, T. Boyer, J. Abraham,
and J. Zhu, 2017: Improved estimates of ocean heat content
from 1960 to 2015. Science Advances, 3, e1601545, https://
doi.org/10.1126/sciadv.1601545.

Cheng, L. J., K. E. Trenberth, J. T. Fasullo, M. Mayer, M. Bal-
maseda, and J. Zhu, 2019b: Evolution of ocean heat content
related to ENSO. J. Climate, 32(12), 3529−3556, https://doi.
org/10.1175/JCLI-D-18-0607.1.
Cheng, L. J., K. Trenberth, J. Fasullo, J. Abraham, T. Boyer, K.
von Schuckmann, and J. Zhu, 2018: Taking the pulse of the
planet. Eos, 99, 14−16, https://doi.org/10.1029/2017EO08
1839.
Cornwall, W., 2019: A new ‘Blob’ menaces Pacific ecosystems.
Science, 365, 1233, https://doi.org/10.1126/science.365.
6459.1233.
Deser, C., and Coauthors, 2020: Isolating the evolving contribu-
tions of anthropogenic aerosols and greenhouse gases: A
new CESM1 large ensemble community resource. J. Cli-
mate, 33(18), 7835−7858, https://doi.org/10.1175/JCLI-D-
20-0123.1.

Duan, J., and Coauthors, 2021: Rapid sea level rise in the South-
ern Hemisphere subtropical oceans. J. Climate, 34(23),
9401−9423, https://doi.org/10.1175/JCLI-D-21-0248.1.

Emanuel, K., 2021a: Response of global tropical cyclone activity
to increasing CO2: Results from downscaling CMIP6 mod-
els. J. Climate, 34(1), 57−70, https://doi.org/10.1175/JCLI-
D-20-0367.1.

Emanuel, K., 2021b: Atlantic tropical cyclones downscaled from
climate reanalyses show increasing activity over past 150
years.. Nat Commun., 12, 7027, https://doi.org/10.1038/
s41467-021-27364-8.

Fasullo, J. T., 2020: Evaluating simulated climate patterns from
the CMIP archives using satellite and reanalysis datasets
using the Climate Model Assessment Tool (CMATv1).
Geoscientific Model Development, 13, 3627−3642, https://
doi.org/10.5194/gmd-13-3627-2020.

Fasullo, J. T., and R. S. Nerem, 2018: Altimeter-era emergence
of the patterns of forced sea-level rise in climate models and
implications for the future. Proceedings of the National
Academy of Sciences of the United States of America, 115,
12 944−12 949, https://doi.org/10.1073/pnas.1813233115.

Fasullo, J. T., N. Rosenbloom, R. R. Buchholz, G. Danabasoglu,
D. M. Lawrence, and J.-F. Lamarque, 2021: Coupled cli-
mate responses to recent Australian wildfire and COVID-19
emissions anomalies estimated in CESM2. Geophys Res.
Lett., 48, e2021GL093841, https://doi.org/10.1029/
2021GL093841.

Frölicher, T. L., J. L. Sarmiento, D. J. Paynter, J. P. Dunne, J. P.
Krasting, and M. Winton, 2015: Dominance of the Southern
Ocean in anthropogenic carbon and heat uptake in CMIP5
models. J. Climate, 28(2), 862−886, https://doi.org/10.1175/
JCLI-D-14-00117.1.

Fyfe, J. C., V. V. Kharin, N. Swart, G. M. Flato, M. Sigmond,
and N. P. Gillett, 2021: Quantifying the influence of short-
term emission reductions on climate. Science Advances,
7(10), eabf7133, https://doi.org/10.1126/sciadv.abf7133.

Gao, L. B., S. R. Rintoul, and W. D. Yu, 2018: Recent wind-
driven change in Subantarctic Mode Water and its impact on
ocean heat storage. Nature Climate Change, 8(1), 58−63,
https://doi.org/10.1038/s41558-017-0022-8.

Gille, S. T., 2002: Warming of the Southern Ocean since the
1950s. Science, 295(5558), 1275−1277, https://doi.org/10.
1126/science.1065863.

Gouretski, V., J. H. Jungclaus, and H. Haak, 2013: Revisiting the
Meteor 1925-1927 hydrographic dataset reveals centennial
full-depth changes in the Atlantic Ocean. Geophys. Res.
Lett., 40, 2236−2241, https://doi.org/10.1002/grl.50503.

Johnson, G., and Coauthors, 2018: Ocean heat content [in State
of the Climate in 2017]. Bull. Amer. Meteor. Soc., 99,
S72−S77.

Hansen, J., M. Sato, P. Kharecha, and K. Von Schuckmann,
2011: Earth’s energy imbalance and implications. Atmo-
spheric Chemistry and Physics, 11, 13 421−13 449, https://
doi.org/10.5194/acp-11-13421-2011.

Holbrook, N. J., and Coauthors, 2019: A global assessment of mar-
ine heatwaves and their drivers. Nature Communications,
10, 2624, https://doi.org/10.1038/s41467-019-10206-z.

Hu, S. N., and A. V. Fedorov, 2020: Indian Ocean warming as a
CHENG ET AL. 11




driver of the North Atlantic warming hole. Nature Communic-
ations, 11, 4785, https://doi.org/10.1038/s41467-020-18522-
5.

IPCC, 2013: Climate Change 2013: The physical Science Basis.
Contribution of Working Group I to the Fifth Assessment
Report of the Intergovernmental Panel on Climate Change.
Cambridge University Press, 1535 pp.

IPCC, 2019: Summary for policymakers. IPCC Special Report on
the Ocean and Cryosphere in a Changing Climate, H.-O.
Pörtner et al., Eds. In press

IPCC, 2021: Summary for policymakers. Climate Change 2021:
The Physical Science Basis. Contribution of Working Group
I to the Sixth Assessment Report of the Intergovernmental
Panel on Climate Change, V. Masson-Delmotte et al., Eds.,
IPCC.

Kay, J. E., and Coauthors, 2015: The Community Earth System
Model (CESM) large ensemble project: A community
resource for studying climate change in the presence of
internal climate variability. Bull. Amer. Meteor. Soc., 96(8),
1333−1349, https://doi.org/10.1175/BAMS-D-13-00255.1.

Keil, P., T. Mauritsen, J. Jungclaus, C. Hedemann, D. Olon-
scheck, and R. Ghosh, 2020: Multiple drivers of the North
Atlantic warming hole. Nature Climate Change, 10,
667−671, https://doi.org/10.1038/s41558-020-0819-8.

Lee, S.-K., W. Park, M. O. Baringer, A. L. Gordon, B. Huber,
and Y. Y. Liu, 2015: Pacific origin of the abrupt increase in
Indian Ocean heat content during the warming hiatus.
Nature Geoscience, 8(6), 445−449, https://doi.org/10.1038/
ngeo2438.

Levitus, S., J. I. Antonov, T. P. Boyer, and C. Stephens, 2000:
Warming of the world ocean. Science, 287(5461),
2225−2229, https://doi.org/10.1126/science.287.5461.2225.

Levitus, S., J. I. Antonov, T. P. Boyer, R. A. Locarnini, H. E. Gar-
cia, and A. V. Mishonov, 2009: Global ocean heat content
1955–2008 in light of recently revealed instrumentation prob-
lems. Geophys. Res. Lett., 36, L07608, https://doi.org/10.
1029/2008GL037155.

Levitus, S., and Coauthors, 2012: World ocean heat content and
thermosteric sea level change (0−2000 m), 1955−2010. Geo-
phys Res. Lett., 39, L10603, https://doi.org/10.1029/
2012GL051106.

Li, G. C., L. J. Cheng, J. Zhu, K. E. Trenberth, M. E. Mann, and
J. P. Abraham, 2020a: Increasing ocean stratification over
the past half-century. Nature Climate Change, 10,
1116−1123, https://doi.org/10.1038/s41558-020-00918-2.

Li, L. F., M. S. Lozier, and F. L. Li, 2021: Century-long cooling
trend in subpolar North Atlantic forced by atmosphere: An
alternative explanation. Climate Dyn., in press, https://doi.
org/10.1007/s00382-021-06003-4.

Li, Y. L., W. Q. Han, A. X. Hu, G. A. Meehl, and F. Wang, 2018:
Multi-decadal changes of the Upper Indian Ocean heat con-
tent during 1965–2016.. J Climate, 31(19), 7863−7884,
https://doi.org/10.1175/JCLI-D-18-0116.1.

Li, Y. L., W. Q. Han, F. Wang, L. Zhang, and J. Duan, 2020b: Ver-
tical structure of the Upper-Indian Ocean thermal variability.
J. Climate, 33(17), 7233−7253, https://doi.org/10.1175/
JCLI-D-19-0851.1.

Marshall, J., and K. Speer, 2012: Closure of the meridional over-
turning circulation through Southern Ocean upwelling.
Nature Geoscience, 5(3), 171−180, https://doi.org/10.1038/
Ngeo1391.

Piecuch, C. G., 2020: Likely weakening of the Florida Current dur-
ing the past century revealed by sea-level observations.
Nature Communications, 11, 3973, https://doi.org/10.1038/
s41467-020-17761-w.

Pinardi, N., and Coauthors, 2015: Mediterranean Sea large-scale
low-frequency ocean variability and water mass formation
rates from 1987 to 2007: A retrospective analysis. Progress
in Oceanography, 132, 318−332, https://doi.org/10.1016/j.
pocean.2013.11.003.

Purich, A., M. H. England, W. J. Cai, A. Sullivan, and P. J. Dur-
ack, 2018: Impacts of broad-scale surface freshening of the
Southern Ocean in a coupled climate model. J. Climate,
31(7), 2613−2632, https://doi.org/10.1175/JCLI-D-17-0092.
1.

Purkey, S. G., and G. C. Johnson, 2010: Warming of global
abyssal and deep southern ocean waters between the 1990s
and 2000s: Contributions to global heat and sea level rise
budgets. J. Climate, 23, 6336−6351, https://doi.org/10.1175/
2010JCLI3682.1.

Purkey, S. G., and G. C. Johnson, 2013: Antarctic Bottom Water
warming and freshening: Contributions to sea level rise,
ocean freshwater budgets, and global heat gain. J. Climate,
26(16), 6105−6122, https://doi.org/10.1175/JCLI-D-12-
00834.1.

Rahmstorf, S., J. E, Box, G. Feulner, M. E. Mann, A. Robinson,
S. Rutherford, and E. Schaffernicht, 2015: Exceptional twenti-
eth-century slowdown in Atlantic Ocean overturning circula-
tion. Nature Climate Change, 5, 475−480, https://doi.org/10.
1038/nclimate2554.

Rhein, M., and Coauthors, 2013: Observations: Ocean. Climate
Change 2013: The Physical Science Basis. Contribution of
Working Group I to the Fifth Assessment Report of the Inter-
governmental Panel on Climate Change, T. F. Stocker et al.,
Eds., Cambridge University Press.

Roemmich, D., J. Church, J. Gilson, D. Monselesan, P. Sutton,
and S. Wijffels, 2015: Unabated planetary warming and its
ocean structure since 2006. Nature Climate Change, 5(3),
240−245. https://doi.org/10.1038/nclimate2513.

Scambos T , J. Abraham, 2015: Briefing: Antarctic ice sheet
mass loss and future sea-level rise. Proceedings of the Institu-
tion of Civil Engineers – Forensic Engineering, 168, 81−84,
https://doi.org/10.1680/feng.14.00014.

Scannell, H. A., G. C. Johnson, L. Thompson, J. M. Lyman, and
S. C. Riser, 2020: Subsurface evolution and persistence of
marine heatwaves in the Northeast Pacific. Geophys. Res.
Lett., 47, e2020GL090548, https://doi.org/10.1029/2020GL
090548.

Schmidtko, S., and G. C. Johnson, 2012: Multi-decadal warming
and shoaling of Antarctic intermediate water. J. Climate,
25(1), 207−221, https://doi.org/10.1175/Jcli-D-11-00021.1.

Schmidtko, S., K. J. Heywood, A. F. Thompson, and S. Aoki,
2014: Multi-decadal warming of Antarctic waters. Science,
346(6214), 1227−1231, https://doi.org/10.1126/science.
1256117.

Schroeder, K., J. Chiggiato, S. A. Josey, M. Borghini, S. Aracri,
and S. Sparnocchia, 2017: Rapid response to climate change
in a marginal sea. Scientific Reports, 7, 4065, https://doi.org/
10.1038/s41598-017-04455-5.

Seidov, D., A. Mishonov, and R. Parsons, 2021: Recent warming
and decadal variability of Gulf of Maine and Slope Water.
Limnology and Oceanography, 66, 3472−3488, https://doi.
org/10.1002/lno.11892.

Seidov, D., A. Mishonov, J. Reagan, and R. Parsons, 2017:
12 RECORD OCEAN WARMING IN 2021




Multi-decadal variability and climate shift in the North
Atlantic Ocean. Geophys. Res. Lett., 44, 4985−4993, https://
doi.org/10.1002/2017GL073644.

Seidov, D., A. Mishonov, J. Reagan, and R. Parsons, 2019: Resili-
ence of the Gulf Stream path on decadal and longer times-
cales. Scientific Reports, 9, 11549, https://doi.org/10.1038/
s41598-019-48011-9.

Silvy, Y., E. Guilyardi, J. B. Sallée, and P. J. Durack, 2020:
Human-induced changes to the global ocean water masses
and their time of emergence. Nature Climate Change,
10(11), 1030−1036, https://doi.org/10.1038/s41558-020-
0878-x.

Simoncelli, S., C. Fratianni, and G. Mattia, 2019: Monitoring and
long-term assessment of the Mediterranean Sea physical
state through ocean reanalyses. INGV Workshop on Marine
Environment, L. Sagnotti et al., Eds., Rome, IVGV, 62−64,
https://doi.org/10.13127/misc/51.

Simoncelli, S., N. Pinardi, C. Fratianni, C. Dubois, and G. Not-
arstefano, 2018: Water mass formation processes in the Medi-
terranean Sea over the past 30 years. Copernicus Marine Ser-
vice Ocean State Report, Issue 2. K. von Schuckmann et al.,
Eds., s96−s100, https://doi.org/10.1080/1755876X.2018.
1489208.

Smith, C. J., and P. M. Forster, 2021: Suppressed late-20th Cen-
tury warming in CMIP6 models explained by forcing and feed-
backs. Geophys. Res. Lett., 48, e2021GL094948, https://doi.
org/10.1029/2021GL094948.

Sriver, R. L., and M. Huber, 2007: Observational evidence for an
ocean heat pump induced by tropical cyclones. Nature, 447,
577−580, https://doi.org/10.1038/nature05785.

Storto, A., and Coauthors, 2019: The added value of the multi-sys-
tem spread information for ocean heat content and steric sea
level investigations in the CMEMS GREP ensemble reana-
lysis product. Climate Dyn., 53, 287−312, https://doi.org/10.
1007/s00382-018-4585-5.

Swart, N. C., S. T. Gille, J. C. Fyfe, and N. P. Gillett, 2018:
Recent Southern Ocean warming and freshening driven by
greenhouse gas emissions and ozone depletion. Nature
Geoscience, 11(11), 836−841, https://doi.org/10.1038/
s41561-018-0226-1.

Trenberth, K. E., J. T. Fasullo, and M. A. Balmaseda, 2014:
Earth’s energy imbalance. J. Climate, 27, 3129−3144, https:/
/doi.org/10.1175/JCLI-D-13-00294.1.

Trenberth, K. E., A. G. Dai, R. M. Rasmussen, and D. B. Par-
sons, 2003: The changing character of precipitation. Bull.
Amer. Meteor. Soc., 84(9), 1205−1218, https://doi.org/10.
1175/BAMS-84-9-1205.

Trenberth, K. E., J. T. Fasullo, K. von Schuckmann, and L. J.
Cheng, 2016: Insights into Earth’s energy imbalance from
multiple sources. J. Climate, 29, 7495−7505, https://doi.org/
10.1175/JCLI-D-16-0339.1.

Trenberth, K. E., L. J. Cheng, P. Jacobs, Y. X. Zhang, and J.
Fasullo, 2018: Hurricane Harvey links to ocean heat content
and climate change adaptation. Earth’s Future, 6, 730−744,
https://doi.org/10.1029/2018EF000825.

Trenberth, K. E., G. W. Branstator, D. Karoly, A. Kumar, N.-C.
Lau, and C. Ropelewski, 1998: Progress during TOGA in
understanding and modeling global teleconnections associ-
ated with tropical sea surface temperatures. J. Geophys.
Res.: Oceans, 103, 14 291−14 324, https://doi.org/10.1029/
97JC01444.

Ummenhofer, C. C., S. Ryan, M. H. England, M. Scheinert, P.
Wagner, A. Biastoch, and C. W. Böning, 2020: Late 20th cen-
tury Indian Ocean heat content gain masked by wind for-
cing. Geophys. Res. Lett., 47(22), e2020GL088692, https://
doi.org/10.1029/2020GL088692.

Ummenhofer, C. C., S. A. Murty, J. Sprintall, T. Lee, and N. J.
Abram, 2021: Heat and freshwater changes in the Indian
Ocean region. Nature Reviews Earth & Environment, 2(8),
525−541, https://doi.org/10.1038/s43017-021-00192-6.

United Nations, 2021: Sustainable Development Goals. Avail-
able from https://sdgs.un.org/goals.

Volkov, D. L., S.-K. Lee, A. L. Gordon, and M. Rudko, 2020:
Unprecedented reduction and quick recovery of the South
Indian Ocean heat content and sea level in 2014–2018. Sci-
ence Advances, 6(36), eabc1151, https://doi.org/10.1126/
sciadv.abc1151.

von Schuckmann, K., E. Holland, P. Haugan, and P. Thomson,
2020a: Ocean science, data, and services for the UN 2030 Sus-
tainable Development Goals. Marine Policy, 121, 104154,
https://doi.org/10.1016/j.marpol.2020.104154.

von Schuckmann, K., and Coauthors, 2016a: An imperative to mon-
itor Earth’s energy imbalance. Nature Climate Change, 6,
138−144, https://doi.org/10.1038/nclimate2876.

von Schuckmann, K., and Coauthors, 2016b: The Copernicus mar-
ine environment monitoring service ocean state report.
Journal of Operational Oceanography, 9, s235−s320, https:/
/doi.org/10.1080/1755876X.2016.1273446.

von Schuckmann, K., and Coauthors, 2020b: Heat stored in the
Earth system: Where does the energy go. . Earth System Sci-
ence Data, 12, 2013−2041, https://doi.org/10.5194/essd-12-
2013-2020.

Wang, C. Z., 2019: Three-ocean interactions and climate variabil-
ity: A review and perspective. Climate Dyn., 53,
5119−5136, https://doi.org/10.1007/s00382-019-04930-x.

Wang, X. D., C. Z. Wang, G. J. Han, W. Li, and X. R. Wu, 2014:
Effects of tropical cyclones on large-scale circulation and
ocean heat transport in the South China Sea. Climate Dyn.,
43, 3351−3366, https://doi.org/10.1007/s00382-014-2109-5.

Wijffels, S., D. Roemmich, D. Monselesan, J. Church, and J.
Gilson, 2016: Ocean temperatures chronicle the ongoing
warming of Earth. Nature Climate Change, 6, 116−118,
https://doi.org/10.1038/nclimate2924.

Xiao, F. A., D. X. Wang, and L. Yang, 2020: Can tropical Pacific
winds enhance the footprint of the Interdecadal Pacific Oscilla-
tion on the upper-ocean heat content in the South China Sea.
J. Climate, 33(10), 4419−4437, https://doi.org/10.1175/
JCLI-D-19-0679.1.

Xie, S.-P., H. Annamalai, F. A. Schott, and J. P. McCreary Jr.,
2002: Structure and mechanisms of south Indian Ocean cli-
mate variability. J. Climate, 15(8), 864−878, https://doi.org/
10.1175/1520-0442(2002)015<0864:SAMOSI>2.0.CO;2.

Yang, L., S. Chen, C. Z. Wang, D. X. Wang, and X. Wang, 2018:
Potential impact of the Pacific Decadal Oscillation and sea sur-
face temperature in the tropical Indian Ocean–Western
Pacific on the variability of typhoon landfall on the China
coast. Climate Dyn., 51, 2695−2705, https://doi.org/10.
1007/s00382-017-4037-7.

Yang, L. N., R. Murtugudde, L. Zhou, and P. Liang, 2020: A poten-
tial link between the Southern Ocean warming and the South
Indian Ocean heat balance. J. Geophys. Res.: Oceans,
125(12), e2020JC016132, https://doi.org/10.1029/2020JC01
6132.
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