Sea-Level and Ocean Heat-Content Change

Author(s):  
John A. Church ◽  
Neil J. White ◽  
Catia M. Domingues ◽  
Didier P. Monselesan ◽  
Elaine R. Miles
2020 ◽  
Author(s):  
Alexander Todd ◽  
Laure Zanna ◽  
Matthew Couldrey ◽  
Jonathan M. Gregory ◽  
Quran Wu ◽  
...  

2021 ◽  
Author(s):  
William Llovel ◽  
Nicolas Kolodziejczyk ◽  
Thierry Penduff ◽  
Jean-Marc Molines ◽  
Sally Close

<p>Ocean warming accounts for more than 90% of the net Earth energy imbalance. As oceans warm, sea level is rising due to the expansion of seawater. Therefore, estimating ocean heat content (OHC) and thermosteric sea level (TSL) appears of great importance to assess the impact of the on-going global warming.  Different research groups have estimated such climate variables for years now and even routinely (Boyer et al., 2016). These climate variables are derived from in situ temperature measurement at different depths with uneven spatial coverage. Two main sources of uncertainties are attributed to the evolving technology of temperature probes and to the uneven spatio-temporal distribution of in situ measurements (Boyer et al., 2016). A large ensemble of forced eddy-permitting ocean simulations revealed the existence of another uncertainty of regional OHC trend estimates (Sérazin et al 2017): a substantial intrinsic variability emerging from oceanic nonlinearities generates random multi decadal trends, which can mask its atmospherically-forced counterpart. This intrinsic variability can also leave a large imprint on regional sea level trends over the altimetry period (Llovel et al., 2018; Penduff et al., 2019). Less attention has been paid for estimating the imprint of such intrinsic ocean variability in OHC and TSL change associated with the uneven spatial coverage of in situ records. In this study, we investigate the imprint of ocean intrinsic variability and of the uneven distribution of in situ records on OHC and TLS change, by taking advantage of this large ensemble simulation. To do so, we extract synthetic in situ temperature profiles from the simulations in space, time and depth. We then interpolate these synthetic profiles using ISAS (Gaillard et al. 2016) to estimate both the imprint of intrinsic ocean variability and the uneven distribution of in situ data to OHC change and TSL change from 2005 to 2015.</p>


2015 ◽  
Vol 120 (8) ◽  
pp. 5749-5765 ◽  
Author(s):  
Oleg A. Saenko ◽  
Duo Yang ◽  
Jonathan M. Gregory ◽  
Paul Spence ◽  
Paul G. Myers

2020 ◽  
Author(s):  
Taimoor Sohail ◽  
Damien B Irving ◽  
Jan David Zika ◽  
Ryan M Holmes ◽  
John Alexander Church

2021 ◽  
Author(s):  
Florence Marti ◽  
Alejandro Blazquez ◽  
Benoit Meyssignac ◽  
Michaël Ablain ◽  
Anne Barnoud ◽  
...  

Abstract. The Earth energy imbalance (EEI) at the top of the atmosphere is responsible for the accumulation of heat in the climate system. Monitoring the EEI is therefore necessary to better understand the Earth’s warming climate. Measuring the EEI is challenging as it is a globally integrated variable whose variations are small (0.5–1 W m−2) compared to the amount of energy entering and leaving the climate system (~ 340 W m−2). Since the ocean absorbs more than 90 % of the excess energy stored by the Earth system, estimating the ocean heat content (OHC) provides an accurate proxy of the EEI. This study provides a space geodetic estimation of the OHC changes at global and regional scales based on the combination of space altimetry and space gravimetry measurements. From this estimate, the global variations in the EEI are derived with realistic estimates of its uncertainty. The mean EEI value is estimated at +0.74 ± 0.22 W m−2 (90 % confidence level) between August 2002 and August 2016. Comparisons against independent estimates based on Argo data and on CERES measurements show good agreement within the error bars of the global mean and the time variations in EEI. Further improvements are needed to reduce uncertainties and to improve the time series especially at interannual and smaller time scales. The space geodetic OHC-EEI product is freely available at https://doi.org/10.24400/527896/a01-2020.003.


2020 ◽  
Author(s):  
Denis Volkov ◽  
Michael Rudko ◽  
Sang-Ki Lee

<p>The interannual-to-decadal variability of heat content and sea level in the South Indian Ocean (SIO) is strongly influenced by its connection with the Pacific and large-scale climatic forcing in the Indo-Pacific region primarily associated with El Niño-Southern Oscillation (ENSO). Besides the advection by the Indonesian Throughflow, signals generated in the Pacific can enter the SIO as coastally trapped Kelvin waves and propagate along the coast of Western Australia. In the southeast tropical and subtropical Indian Ocean, these signals along the eastern boundary can radiate westward as Rossby waves and eventually impact sea level and heat content in the SIO interior and near the western boundary. Local wind forcing, through Ekman pumping over the open ocean and coastal upwelling, is also able to generate Rossby waves and/or modify those emanated from the eastern boundary.</p><p>As measured by Argo floats and satellite altimetry, a decade-long increase of the upper-ocean heat content and sea level in the SIO in 2004-2013 ended with a remarkable drop returning to the initial values in 2004. This basin-wide heat release was associated with one of the strongest on record El Niño events in 2014-2016. Surprisingly, the basin-averaged heat content and sea level quickly recovered during the weak La Niña event in 2017-2019. Here we present an analysis of the evolution and mechanisms of 2014-2016 cooling and subsequent warming in the SIO subtropical gyre. We show that the 2014-2016 El Niño did contribute to the reduced heat content in the eastern SIO, while the local wind forcing (via increased Ekman upwelling) largely contributed to the heat reduction in the western SIO. We find no evidence to support that the 2017-2018 warming was forced by the weak La Niña, because the upper-ocean heat content in eastern SIO was still below normal during 2016-2018. The recovery largely occurred in the western SIO due to local wind forcing (via increased Ekman downwelling) primarily associated with changes in the strength of the southeasterly trade winds.</p><p>Because sea level is a good proxy for the oceanic heat content in the SIO, we extend our analysis back to 1993 using satellite altimetry records. Using a simple model of wind-forced Rossby waves, we estimate the relative contributions of sea level signals propagating from the eastern boundary, the origin of which is strongly linked to ENSO, and the local wind forcing in the SIO interior to the observed sea level variability. The local wind forcing appears to dominate the sea level (and, hence, the upper-ocean heat content) variability in the western SIO, especially in 2013-2019, while the ENSO-related signals are dominant in the eastern SIO. The local wind forcing over the SIO interior effectively suppressed the cooling associated with the most recent 2014-2016 El Niño event. In contrast, the cooling associated with the strongest on record 1997-1998 El Niño was amplified by the local wind forcing in the basin’s interior.</p>


2018 ◽  
Vol 53 (1-2) ◽  
pp. 287-312 ◽  
Author(s):  
Andrea Storto ◽  
Simona Masina ◽  
Simona Simoncelli ◽  
Doroteaciro Iovino ◽  
Andrea Cipollone ◽  
...  

2019 ◽  
Vol 32 (21) ◽  
pp. 7227-7245 ◽  
Author(s):  
Lei Zhang ◽  
Weiqing Han ◽  
Yuanlong Li ◽  
Nicole S. Lovenduski

Abstract In this study, the Indian Ocean upper-ocean variability associated with the subtropical Indian Ocean dipole (SIOD) is investigated. We find that the SIOD is associated with a prominent southwest–northeast sea level anomaly (SLA) dipole over the western-central south Indian Ocean, with the north pole located in the Seychelles–Chagos thermocline ridge (SCTR) and the south pole at southeast of Madagascar, which is different from the distribution of the sea surface temperature anomaly (SSTA). While the thermocline depth and upper-ocean heat content anomalies mirror SLAs, the air–sea CO2 flux anomalies associated with SIOD are controlled by SSTA. In the SCTR region, the westward propagation of oceanic Rossby waves generated by anomalous winds over the eastern tropical Indian Ocean is the major cause for the SLAs, with cyclonic wind causing negative SLAs during positive SIOD (pSIOD). Local wind forcing is the primary driver for the SLAs southeast of Madagascar, with anticyclonic winds causing positive SLAs. Since the SIOD is correlated with ENSO, the relative roles of the SIOD and ENSO are examined. We find that while ENSO can induce significant SLAs in the SCTR region through an atmospheric bridge, it has negligible impact on the SLA to the southeast of Madagascar. By contrast, the SIOD with ENSO influence removed is associated with an opposite SLA in the SCTR and southeast of Madagascar, corresponding to the SLA dipole identified above. A new subtropical dipole mode index (SDMI) is proposed, which is uncorrelated with ENSO and thus better represents the pure SIOD effect.


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