scholarly journals Fifty Year Trends in Global Ocean Heat Content Traced to Surface Heat Fluxes in the Sub‐Polar Ocean

2021 ◽  
Vol 48 (8) ◽  
Author(s):  
Taimoor Sohail ◽  
Damien B. Irving ◽  
Jan D. Zika ◽  
Ryan M. Holmes ◽  
John A. Church
Keyword(s):  
Heat Content ◽  
Surface Heat ◽  
Heat Fluxes ◽  
Ocean Heat Content ◽  
Global Ocean ◽  
Surface Heat Fluxes ◽  
Polar Ocean

Long-term global ocean heat content change driven by sub-polar surface heat fluxes

2020 ◽  
Author(s):  
Taimoor Sohail ◽  
Damien B Irving ◽  
Jan David Zika ◽  
Ryan M Holmes ◽  
John Alexander Church
Keyword(s):  
Heat Content ◽  
Surface Heat ◽  
Heat Fluxes ◽  
Ocean Heat Content ◽  
Global Ocean ◽  
Polar Surface ◽  
Surface Heat Fluxes ◽  
Content Change

On the Hyperbolicity of the Bulk Air–Sea Heat Flux Functions: Insights into the Efficiency of Air–Sea Moisture Disequilibrium for Tropical Cyclone Intensification

2021 ◽  
Vol 149 (5) ◽  
pp. 1517-1534
Author(s):  
Benjamin Jaimes de la Cruz ◽  
Lynn K. Shay ◽  
Joshua B. Wadler ◽  
Johna E. Rudzin
Keyword(s):  
Tropical Cyclone ◽  
Surface Wind ◽  
Heat Content ◽  
Surface Heat ◽  
Heat Fluxes ◽  
Ocean Heat Uptake ◽  
Surface Heat Fluxes ◽  
Heat Uptake ◽  
Moisture Fluxes ◽  
New Perspective

AbstractSea-to-air heat fluxes are the energy source for tropical cyclone (TC) development and maintenance. In the bulk aerodynamic formulas, these fluxes are a function of surface wind speed U10 and air–sea temperature and moisture disequilibrium (ΔT and Δq, respectively). Although many studies have explained TC intensification through the mutual dependence between increasing U10 and increasing sea-to-air heat fluxes, recent studies have found that TC intensification can occur through deep convective vortex structures that obtain their local buoyancy from sea-to-air moisture fluxes, even under conditions of relatively low wind. Herein, a new perspective on the bulk aerodynamic formulas is introduced to evaluate the relative contribution of wind-driven (U10) and thermodynamically driven (ΔT and Δq) ocean heat uptake. Previously unnoticed salient properties of these formulas, reported here, are as follows: 1) these functions are hyperbolic and 2) increasing Δq is an efficient mechanism for enhancing the fluxes. This new perspective was used to investigate surface heat fluxes in six TCs during phases of steady-state intensity (SS), slow intensification (SI), and rapid intensification (RI). A capping of wind-driven heat uptake was found during periods of SS, SI, and RI. Compensation by larger values of Δq > 5 g kg−1 at moderate values of U10 led to intense inner-core moisture fluxes of greater than 600 W m−2 during RI. Peak values in Δq preferentially occurred over oceanic regimes with higher sea surface temperature (SST) and upper-ocean heat content. Thus, increasing SST and Δq is a very effective way to increase surface heat fluxes—this can easily be achieved as a TC moves over deeper warm oceanic regimes.

Seasonal mixed layer heat budget in coastal waters off Angola

2021 ◽  
Author(s):  
Mareike Körner ◽  
Peter Brandt ◽  
Marcus Dengler
Keyword(s):  
Mixed Layer ◽  
Heat Budget ◽  
Heat Content ◽  
Nutrient Supply ◽  
Surface Heat ◽  
Heat Fluxes ◽  
Driving Mechanism ◽  
Near Surface ◽  
Surface Heat Fluxes ◽  
Mixed Layer Heat Budget

<p>The Angolan shelf system represents a highly productive ecosystem that exhibits pronounced seasonal variability. Productivity peaks in austral winter when seasonally prevailing upwelling favorable winds are weakest. Thus, other processes than local wind-driven upwelling contribute to the near-coastal cooling and nutrient supply during this season. Possible processes that lead to changes of the mixed-layer heat content does not only include local mechanism but also the passage of remotely forced coastally trapped waves. Understanding the driving mechanism of changes in the mixed-layer heat content that may be locally or remotely forced are vital for understanding of upward nutrient supply and biological productivity off Angola. Here, we investigate the seasonal mixed layer heat budget by analyzing atmospheric and oceanic causes for heat content variability. We calculate monthly estimates of surface heat fluxes, horizontal advection from near-surface velocities, horizontal eddy advection, and vertical entrainment. Additionally, diapycnal heat fluxes at the mixed-layer base are determined from shipboard and glider microstructure data. The results are discussed in reference to the variability of the eastern boundary circulation, surface heat fluxes and wind forcing.</p>

Interannual Variations in Upper-Ocean Heat Content and Heat Transport Convergence in the Western North Atlantic

2007 ◽  
Vol 37 (11) ◽  
pp. 2682-2697 ◽  
Author(s):  
Shenfu Dong ◽  
Susan L. Hautala ◽  
Kathryn A. Kelly
Keyword(s):  
North Atlantic ◽  
Heat Content ◽  
Heat Fluxes ◽  
Ocean Heat Content ◽  
Upper Ocean ◽  
Interannual Variations ◽  
Upper Ocean Heat Content ◽  
Surface Heat Fluxes ◽  
Storage Rate ◽  
Geostrophic Advection

Abstract Subsurface temperature data in the western North Atlantic Ocean are analyzed to study the variations in the heat content above a fixed isotherm and contributions from surface heat fluxes and oceanic processes. The study region is chosen based on the data density; its northern boundary shifts with the Gulf Stream position and its southern boundary shifts to contain constant volume. The temperature profiles are objectively mapped to a uniform grid (0.5° latitude and longitude, 10 m in depth, and 3 months in time). The interannual variations in upper-ocean heat content show good agreement with the changes in the sea surface height from the Ocean Topography Experiment (TOPEX)/Poseidon altimeter; both indicate positive anomalies in 1994 and 1998–99 and negative anomalies in 1996–97. The interannual variations in surface heat fluxes cannot explain the changes in upper-ocean heat storage rate. On the contrary, a positive anomaly in heat released to the atmosphere corresponds to a positive upper-ocean heat content anomaly. The oceanic heat transport, mainly owing to the geostrophic advection, controls the interannual variations in heat storage rate, which suggests that geostrophic advection plays an important role in the air–sea heat exchange. The 18°C isotherm depth and layer thickness also show good correspondence to the upper-ocean heat content; a deep and thin 18°C layer corresponds to a positive heat content anomaly. The oceanic transport in each isotherm layer shows an annual cycle, converging heat in winter, and diverging in summer in a warm layer; it also shows interannual variations with the largest heat convergence occurring in even warmer layers during the period of large ocean-to-atmosphere flux.

A new project to monitor the Ocean Heat Content and the Earth Energy imbalance from space: MOHeaCAN

2020 ◽  
Author(s):  
Michaël Ablain ◽  
Benoit Meyssignac ◽  
Alejandro Blazquez ◽  
Marti Florence ◽  
Rémi Jugier ◽  
...  
Keyword(s):  
Time Scales ◽  
Radiant Energy ◽  
Heat Content ◽  
Deep Ocean ◽  
Heat Fluxes ◽  
Ocean Heat Content ◽  
Global Ocean ◽  
Energy Imbalance ◽  
The Earth

<p>The Earth Energy Imbalance (EEI) is a key indicator to understand the Earth’s changing. However, measuring this indicator is challenging since it is a globally integrated variable whose variations are small, of the order of several tenth of W.m-2, compared to the amount of energy entering and leaving the climate system of ~340 W.m-2. Recent studies suggest that the EEI response to anthropogenic GHG and aerosols emissions is 0.5-1 W.m-2. It implies that an accuracy of <0.3 W.m-2 at decadal time scales is necessary to evaluate the long term mean EEI associated with anthropogenic forcing. Ideally an accuracy of <0.1 W.m-2 at decadal time scales is desirable if we want to monitor future changes in EEI. The ocean heat content (OHC) is a very good proxy to estimate EEI as ocean concentrates the vast majority of the excess of energy (~93%) associated with EEI. Several methods exist to estimate OHC:</p><ul><li>the direct measurement of in situ temperature based on temperature/Salinity profiles (e.g. ARGO floats),</li> <li>the measurement of the net ocean surface heat fluxes from space (CERES),</li> <li>the estimate from ocean reanalyses that assimilate observations from both satellite and in situ instruments,</li> <li>the measurement of the thermal expansion of the ocean from space based on differences between the total sea-level content derived from altimetry measurements and the mass content derived from GRACE data (noted “Altimetry-GRACE”).</li> </ul><p>To date, the best results are given by the first method based on ARGO network. However ARGO measurements do no sample deep ocean below 2000 m depth and marginal seas as well as the ocean below sea ice. Re-analysis provides a more complete estimation but large biases in the polar oceans and spurious drifts in the deep ocean mask a significant part of the OHC signal related to EEI. The method based on estimation of ocean net heat fluxes (CERES) is not appropriate for OHC calculation due to a too strong uncertainty (±15 W.m-2). </p><p>In the MOHeaCAN project supported by ESA, we are being developed the “Altimetry-GRACE” approach  which is promising since it provides consistent spatial and temporal sampling of the ocean, it samples the entire global ocean, except for polar regions, and it provides estimates of the OHC over the ocean’s entire depth. Consequently, it complements the OHC estimation from ARGO.  However, to date the uncertainty in OHC from this method is close to 0.5 W.m-2, and thus greater than the requirement of 0.3 W.m-2 needed to a good EEI estimation. Therefore the scientific objective of the MOHeaCan project is  to improve these estimates :</p><ol><li>by developing novel algorithms in order to reach the challenging target for the uncertainty quantification of 0.3 W. m−2;</li> <li>by estimating realistic OHC uncertainties thanks to an error budget of measurements applying a rigorous mathematical formalism;</li> <li>by developing a software prototype systems that allow to perform sensitivities studies and OHC product and its uncertainty generation;</li> <li>by assessing our estimation by performing comparison against independent estimates based on ARGO network, and based on the Clouds and the Earth’s Radiant energy System (CERES) measurements at the top of the atmosphere.</li> </ol>

scholarly journals Global representation of tropical cyclone-induced ocean thermal changes using Argo data – Part 2: Estimating air–sea heat fluxes and ocean heat content changes

2014 ◽  
Vol 11 (6) ◽  
pp. 2907-2937
Author(s):  
L. Cheng ◽  
J. Zhu ◽  
R. L. Sriver
Keyword(s):  
Heat Loss ◽  
Heat Budget ◽  
Heat Content ◽  
Global Scale ◽  
Heat Fluxes ◽  
Ocean Heat Content ◽  
Global Ocean ◽  
Storm Events ◽  
Argo Data ◽  
Ocean Heat Uptake

Abstract. We use Argo temperature data to examine changes in ocean heat content (OHC) and air–sea heat fluxes induced by tropical cyclones (TC)s on a global scale. A footprint technique that analyzes the vertical structure of cross-track thermal responses along all storm tracks during the period 2004–2012 is utilized (see part I). We find that TCs are responsible for 1.87 PW (11.05 W m−2 when averaging over the global ocean basin) of heat transfer annually from the global ocean to the atmosphere during storm passage (0–3 days) on a global scale. Of this total, 1.05 ± 0.20 PW (4.80 ± 0.85 W m−2) is caused by Tropical storms/Tropical depressions (TS/TD) and 0.82 ± 0.21 PW (6.25 ± 1.5 W m−2) is caused by hurricanes. Our findings indicate that ocean heat loss by TCs may be a substantial missing piece of the global ocean heat budget. Net changes in OHC after storm passage is estimated by analyzing the temperature anomalies during wake recovery following storm events (4–20 days after storm passage) relative to pre-storm conditions. Results indicate the global ocean experiences a 0.75 ± 0.25 PW (5.98 ± 2.1W m−2) net heat gain annually for hurricanes. In contrast, under TS/TD conditions, ocean experiences 0.41 ± 0.21 PW (1.90 ± 0.96 W m−2) net ocean heat loss, suggesting the overall oceanic thermal response is particularly sensitive to the intensity of the event. The net ocean heat uptake caused by all storms is 0.34 PW.

scholarly journals The interpretation of temperature and salinity variables in numerical ocean model output, and the calculation of heat fluxes and heat content

2021 ◽  
Author(s):  
Trevor J. McDougall ◽  
Paul M. Barker ◽  
Ryan M. Holmes ◽  
Rich Pawlowicz ◽  
Stephen M. Griffies ◽  
...  
Keyword(s):  
Equation Of State ◽  
Potential Temperature ◽  
Heat Content ◽  
Coupled Model ◽  
Heat Fluxes ◽  
Ocean Heat Content ◽  
Global Ocean ◽  
Volume Integral ◽  
Meridional Heat Transport ◽  
Ocean Models

Abstract. The 2010 international thermodynamic equation of seawater, TEOS-10, defined the enthalpy and entropy of seawater, thus enabling the global ocean heat content to be calculated as the volume integral of the product of in situ density, ρ, and potential enthalpy, h0 (with reference sea pressure of 0 dbar). In terms of Conservative Temperature, Θ, ocean heat content is the volume integral of ρcp0Θ, where cp0 is a constant isobaric heat capacity. However, several ocean models in CMIP6 (as well as all of those in previous Coupled Model Intercomparison Project phases, such as CMIP5) have not been converted from EOS-80 (Equation of State - 1980) to TEOS-10, so the question arises of how the salinity and temperature variables in these models should be interpreted. In this article we address how heat content, surface heat fluxes and the meridional heat transport are best calculated in these models, and also how these quantities should be compared with the corresponding quantities calculated from observations. We conclude that even though a model uses the EOS-80 equation of state which expects potential temperature as its input temperature, the most appropriate interpretation of the model's temperature variable is actually Conservative Temperature. This interpretation is needed to ensure that the air-sea heat flux that leaves/arrives-in the atmosphere is the same as that which arrives-in/leaves the ocean. We also show that the salinity variable carried by TEOS-10 based models is Preformed Salinity, while the prognostic salinity of EOS-80 based models is also proportional to Preformed Salinity. These interpretations of the salinity and temperature variables in ocean models are an update on the comprehensive Griffies et al. (2016) paper that discusses the interpretation of many aspects of coupled model runs.

Trends of land surface heat fluxes on the Tibetan Plateau from 2001 to 2012

2017 ◽  
Vol 37 (14) ◽  
pp. 4757-4767 ◽  
Author(s):  
Cunbo Han ◽  
Yaoming Ma ◽  
Xuelong Chen ◽  
Zhongbo Su
Keyword(s):  
Tibetan Plateau ◽  
Land Surface ◽  
Surface Heat ◽  
Heat Fluxes ◽  
The Tibetan Plateau ◽  
Surface Heat Fluxes ◽  
Land Surface Heat Fluxes

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

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

AbstractThe historical evolution of Earth’s energy imbalance can be quantified by changes in the global ocean heat content. However, historical reconstructions of ocean heat content often neglect a large volume of the deep ocean, due to sparse observations of ocean temperatures below 2000 m. Here, we provide a global reconstruction of historical changes in full-depth ocean heat content based on interpolated subsurface temperature data using an autoregressive artificial neural network, providing estimates of total ocean warming for the period 1946-2019. We find that cooling of the deep ocean and a small heat gain in the upper ocean led to no robust trend in global ocean heat content from 1960-1990, implying a roughly balanced Earth energy budget within −0.16 to 0.06 W m−2 over most of the latter half of the 20th century. However, the past three decades have seen a rapid acceleration in ocean warming, with the entire ocean warming from top to bottom at a rate of 0.63 ± 0.13 W m−2. These results suggest a delayed onset of a positive Earth energy imbalance relative to previous estimates, although large uncertainties remain.

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