scholarly journals How well can we derive Global Ocean Indicators from Argo data?

2011 ◽  
Vol 8 (3) ◽  
pp. 999-1024 ◽  
Author(s):  
K. von Schuckmann ◽  
P.-Y. Le Traon
Keyword(s):  
Heat Content ◽  
Global Scale ◽  
Global Ocean ◽  
Argo Data ◽  
Steric Sea Level ◽  
Content Change ◽  
Time Period ◽  
Handling Methods ◽  
Proper Estimation ◽  
Year 2000

Abstract. Argo deployments began in the year 2000 and by November 2007 the array was 100 % complete, covering the global ocean from the surface down to 2000 m depth. In this study, Argo temperature and salinity measurements during the period 2005 to 2010 are used to develop a revised estimation of Global Ocean Indicators (GOIs) such as heat content variability, freshwater content and steric height. These revised indices are based on a simple box averaging scheme using a weighted mean. They include a proper estimation of the errors due to data handling methods and climatology uncertainties. A global ocean heat content change (OHC) trend of 0.55 ± 0.1 W m−2 is estimated over the time period 2005–2010. Similarly, a global steric sea level (GSSL) rise of 0.69 ± 0.14 mm yr−1 is observed. The global ocean freshwater content (OFC) trend is barely significant. Results show that there is significant interannual variability at global scale, especially for global OFC. Annual mean GOIs from the today's Argo samling can be derived with an accuracy of ±0.10 cm for GSSL, ±0.21 × 108 J m−2 for global OHC, and ±700 km3 for global OFC. Long-term trends (15 yr) of GOIs based on the complete Argo sampling (10–1500 m depth) can be performed with an accuracy of about ±0.03 mm yr−1 for steric rise, ±0.02 W m−2 for ocean warming and ±20 km3 yr−1 for global OFC trends – under the assumption that no systematic errors remain in the observing system.

scholarly journals How well can we derive Global Ocean Indicators from Argo data?

Ocean Science ◽  
2011 ◽  
Vol 7 (6) ◽  
pp. 783-791 ◽  
Author(s):  
K. von Schuckmann ◽  
P.-Y. Le Traon
Keyword(s):  
Heat Content ◽  
Global Scale ◽  
Global Ocean ◽  
Argo Data ◽  
Steric Sea Level ◽  
Time Period ◽  
Routine Monitoring ◽  
Long Term Trends ◽  
Set Up ◽  
Year 2000

Abstract. Argo deployments began in the year 2000 and by November 2007, the array reached its initial goal of 3000 floats operating worldwide. In this study, Argo temperature and salinity measurements during the period 2005 to 2010 are used to estimate Global Ocean Indicators (GOIs) such as global ocean heat content (GOHC), global ocean freshwater content (GOFC) and global steric sea level (GSSL). We developed a method based on a simple box averaging scheme using a weighted mean. Uncertainties due to data processing methods and choice of climatology are estimated. This method is easy to implement and run and can be used to set up a routine monitoring of the global ocean. Over the six year time period, trends of GOHC and GSSL are 0.54 ± 0.1 W m−2 and 0.75 ± 0.15 mm yr−1, respectively. The trend of GOFC is barely significant. Results show that there is significant interannual variability at global scale, especially for GOFC. Annual mean GOIs from the today's Argo sampling can be derived with an accuracy of ±0.11 cm for GSSL, ±0.22 × 108 J m−2 for GOHC, and ±700 km3 for GOFC. Long-term trends (15 yr) of GOIs based on the complete Argo sampling for the upper 1500 m depth can be estimated with an accuracy of ±0.04 mm yr−1 for GSSL, ±0.02 W m−2 for GOHC and ±20 km3 yr−1 for GOFC – under the assumption that no systematic errors remain in the observing system.

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 Consistency of the current global ocean observing systems from an Argo perspective

Ocean Science ◽  
2014 ◽  
Vol 10 (3) ◽  
pp. 547-557 ◽  
Author(s):  
K. von Schuckmann ◽  
J.-B. Sallée ◽  
D. Chambers ◽  
P.-Y. Le Traon ◽  
C. Cabanes ◽  
...  
Keyword(s):  
Sea Level ◽  
Heat Content ◽  
Deep Ocean ◽  
Global Ocean ◽  
Regional Variability ◽  
Tropical Ocean ◽  
Steric Sea Level ◽  
Ocean Observing ◽  
Ocean Observing Systems ◽  
Observing Systems

Abstract. Variations in the world's ocean heat storage and its associated volume changes are a key factor to gauge global warming and to assess the earth's energy and sea level budget. Estimating global ocean heat content (GOHC) and global steric sea level (GSSL) with temperature/salinity data from the Argo network reveals a positive change of 0.5 ± 0.1 W m−2 (applied to the surface area of the ocean) and 0.5 ± 0.1 mm year−1 during the years 2005 to 2012, averaged between 60° S and 60° N and the 10–1500 m depth layer. In this study, we present an intercomparison of three global ocean observing systems: the Argo network, satellite gravimetry from GRACE and satellite altimetry. Their consistency is investigated from an Argo perspective at global and regional scales during the period 2005–2010. Although we can close the recent global ocean sea level budget within uncertainties, sampling inconsistencies need to be corrected for an accurate global budget due to systematic biases in GOHC and GSSL in the Tropical Ocean. Our findings show that the area around the Tropical Asian Archipelago (TAA) is important to closing the global sea level budget on interannual to decadal timescales, pointing out that the steric estimate from Argo is biased low, as the current mapping methods are insufficient to recover the steric signal in the TAA region. Both the large regional variability and the uncertainties in the current observing system prevent us from extracting indirect information regarding deep-ocean changes. This emphasizes the importance of continuing sustained effort in measuring the deep ocean from ship platforms and by beginning a much needed automated deep-Argo network.

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

2021 ◽  
Author(s):  
Marti Florence ◽  
Ablain Michaël ◽  
Fraudeau Robin ◽  
Jugier Rémi ◽  
Meyssignac Benoît ◽  
...  
Keyword(s):  
Time Scales ◽  
Radiant Energy ◽  
Heat Content ◽  
Ocean Heat Content ◽  
Global Ocean ◽  
Argo Data ◽  
Data Set ◽  
Energy Imbalance ◽  
Temporal Sampling ◽  
The Earth

<p>The Earth Energy Imbalance (EEI) is a key indicator to understand climate change. However, measuring this indicator is challenging since it is a globally integrated variable whose variations are small, of the order of several tenth of W.m<sup>-2</sup>, compared to the amount of energy entering and leaving the climate system of ~340 W.m<sup>-2</sup>. Recent studies suggest that the EEI response to anthropogenic GHG and aerosols emissions is 0.5-1 W.m<sup>-2</sup>. It implies that an accuracy of <0.3 W.m<sup>-2</sup> at decadal time scales is necessary to evaluate the long term mean EEI associated with anthropogenic forcing. Ideally an accuracy of <0.1 W.m<sup>-2</sup> at decadal time scales is desirable if we want to monitor future changes in EEI.</p><p>In the frame of the MOHeaCAN project supported by ESA, the EEI indicator is deduced from the global change in Ocean Heat Content (OHC) which is a very good proxy of the EEI since the ocean stores 93% of the excess of heat  gained by the Earth in response to EEI. The OHC is estimated from space altimetry and gravimetry missions (GRACE). This “Altimetry-Gravimetry'' approach is promising because it provides consistent spatial and temporal sampling of the ocean, it samples nearly the entire global ocean, except for polar regions, and it provides estimates of the OHC over the ocean’s entire depth. Consequently, it complements the OHC estimation from the ARGO network. </p><p>The MOHeaCAN product contains monthly time series (between August 2002 and June 2017) of several variables, the main ones being the regional OHC (3°x3° spatial resolution grids), the global OHC and the EEI indicator. Uncertainties are provided for variables at global scale, by propagating errors from sea level measurements (altimetry) and ocean mass content (gravimetry). In order to calculate OHC at regional and global scales, a new estimate of the expansion efficiency of heat at global and regional scales have been performed based on the global ARGO network. </p><p>A scientific validation of the MOHeaCAN product has also been carried out performing thorough comparisons against independent estimates based on ARGO data and on the Clouds and the Earth’s Radiant energy System (CERES) measurements at the top of the atmosphere. The mean EEI derived from MOHeaCAN product is 0.84 W.m<sup>-2</sup> over the whole period within an uncertainty of ±0.12 W.m<sup>-2</sup> (68% confidence level - 0.20 W.m<sup>-2</sup> at the 90% CL). This figure is in agreement (within error bars at the 90% CL) with other EEI indicators based on ARGO data (e.g. OHC-OMI from CMEMS) although the best estimate is slightly higher. Differences from annual to inter-annual scales have also been observed with ARGO and CERES data. Investigations have been conducted to improve our understanding of the benefits and limitations of each data set to measure EEI at different time scales.</p><p><strong>The MOHeaCAN product from “altimetry-gravimetry” is now available</strong> and can be downloaded at https://doi.org/10.24400/527896/a01-2020.003. Feedback from interested users on this product are welcome.</p>

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

scholarly journals Monitoring the ocean heat content change and the Earth energy imbalance from space altimetry and space gravimetry

2021 ◽  
Author(s):  
Florence Marti ◽  
Alejandro Blazquez ◽  
Benoit Meyssignac ◽  
Michaël Ablain ◽  
Anne Barnoud ◽  
...  
Keyword(s):  
Heat Content ◽  
Climate System ◽  
Ocean Heat Content ◽  
Argo Data ◽  
Energy Imbalance ◽  
Content Change ◽  
Warming Climate ◽  
The Earth ◽  
Time Variations ◽  
Good Agreement

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.

scholarly journals C-GLORSv5: an improved multi-purpose global ocean eddy-permitting physical reanalysis

2016 ◽  
Author(s):  
Andrea Storto ◽  
Simona Masina
Keyword(s):  
Bias Correction ◽  
General Circulation ◽  
Thermohaline Circulation ◽  
Heat Content ◽  
Global Ocean ◽  
Observation Error ◽  
Background Error ◽  
Steric Sea Level ◽  
Previous Version ◽  
Correction Scheme

Abstract. Global ocean reanalyses combine in-situ and satellite ocean observations with a general circulation ocean model to estimate the time-evolving state of the ocean, and they represent a valuable tool for a variety of applications, ranging from climate monitoring and process studies to downstream applications, initialization of long-range forecasts and regional studies. The purpose of this paper is to document the recent upgrade of C-GLORS (version 5), a state-of-the-art ocean reanalysis produced at the Centro Euro-Mediterraneo per i Cambiamenti Climatici that covers the meteorological satellite era (1980–present) and it is being updated in delayed time mode. The reanalysis is run at eddy-permitting resolution (1/4 degree horizontal resolution and 50 vertical levels) and consists of a three-dimensional variational data assimilation system, a surface nudging and a bias correction scheme. With respect to the previous version (v4), C-GLORSv5 contains a number of improvements. In particular, background- and observation- error covariances have been retuned, allowing a flow-dependent inflation in the globally averaged background-error variance. An additional constraint on the sea-ice thickness was introduced, leading to a realistic ice volume evolution. Finally, the bias correction scheme and the initialization strategy were retuned. Results document that the new reanalysis outperforms the previous version, especially in representing the variability of global heat content and associated steric sea level, the upper ocean temperature and the thermohaline circulation. The dataset is available in NetCDF format at doi:10.1594/PANGAEA.857995.

scholarly journals A Comparison of the Variability and Changes in Global Ocean Heat Content from Multiple Objective Analysis Products During the Argo Period

2021 ◽  
pp. 1-47
Author(s):  
Xinfeng Liang ◽  
Chao Liu ◽  
Rui M. Ponte ◽  
Don P. Chambers
Keyword(s):  
Southern Ocean ◽  
Interannual Variability ◽  
North Atlantic ◽  
Southern Oscillation ◽  
Heat Content ◽  
Global Scale ◽  
Ocean Heat Content ◽  
Objective Analysis ◽  
Global Ocean ◽  
Ocean Measurements

AbstractOcean heat content (OHC) is key to estimating the energy imbalance of the earth system. Over the past two decades, an increasing number of OHC studies were conducted using oceanic objective analysis (OA) products. Here we perform an intercomparison of OHC from eight OA products with a focus on their robust features and significant differences over the Argo period (2005-2019), when the most reliable global scale oceanic measurements are available. For the global ocean, robust warming in the upper 2000 m is confirmed. The 0-300 m layer shows the highest warming rate but is heavily modulated by interannual variability, particularly the El Niño–Southern Oscillation. The 300-700 m and 700-2000 m layers, on the other hand, show unabated warming. Regionally, the Southern Ocean and mid-latitude North Atlantic show a substantial OHC increase, and the subpolar North Atlantic displays an OHC decrease. A few apparent differences in OHC among the examined OA products were identified. In particular, temporal means of a few OA products that incorporated other ocean measurements besides Argo show a global-scale cooling difference, which is likely related to the baseline climatology fields used to generate those products. Large differences also appear in the interannual variability in the Southern Ocean and in the long-term trends in the subpolar North Atlantic. These differences remind us of the possibility of product-dependent conclusions on OHC variations. Caution is therefore warranted when using merely one OA product to conduct OHC studies, particularly in regions and on timescales that display significant differences.

scholarly journals Assimilating synthetic Biogeochemical-Argo and ocean colour observations into a global ocean model to inform observing system design

2021 ◽  
Vol 18 (2) ◽  
pp. 509-534
Author(s):  
David Ford
Keyword(s):  
Global Scale ◽  
Ocean Model ◽  
Point Of View ◽  
Global Ocean ◽  
Ocean Colour ◽  
Ocean Reanalysis ◽  
Argo Data ◽  
Argo Floats ◽  
Improved Model ◽  
The Impact

Abstract. A set of observing system simulation experiments was performed. This assessed the impact on global ocean biogeochemical reanalyses of assimilating chlorophyll from remotely sensed ocean colour and in situ observations of chlorophyll, nitrate, oxygen, and pH from a proposed array of Biogeochemical-Argo (BGC-Argo) floats. Two potential BGC-Argo array distributions were tested: one for which biogeochemical sensors are placed on all current Argo floats and one for which biogeochemical sensors are placed on a quarter of current Argo floats. Assimilating BGC-Argo data greatly improved model results throughout the water column. This included surface partial pressure of carbon dioxide (pCO2), which is an important output of reanalyses. In terms of surface chlorophyll, assimilating ocean colour effectively constrained the model, with BGC-Argo providing no added benefit at the global scale. The vertical distribution of chlorophyll was improved by assimilating BGC-Argo data. Both BGC-Argo array distributions gave benefits, with greater improvements seen with more observations. From the point of view of ocean reanalysis, it is recommended to proceed with development of BGC-Argo as a priority. The proposed array of 1000 floats will lead to clear improvements in reanalyses, with a larger array likely to bring further benefits. The ocean colour satellite observing system should also be maintained, as ocean colour and BGC-Argo will provide complementary benefits.

scholarly journals Sea level budget over 2005–2013: missing contributions and data errors

Ocean Science ◽  
2015 ◽  
Vol 11 (5) ◽  
pp. 789-802 ◽  
Author(s):  
H. B. Dieng ◽  
A. Cazenave ◽  
K. von Schuckmann ◽  
M. Ablain ◽  
B. Meyssignac
Keyword(s):  
Time Series ◽  
Sea Level ◽  
Heat Content ◽  
Deep Ocean ◽  
Time Span ◽  
Ocean Reanalysis ◽  
Argo Data ◽  
Steric Sea Level ◽  
Ocean Mass ◽  
The Impact

Abstract. Based on the sea level budget closure approach, this study investigates the residuals between observed global mean sea level (GMSL) and the sum of components (steric sea level and ocean mass) for the period January 2005 to December 2013. The objective is to identify the impact of errors in one or several components of the sea level budget on the residual time series. This is a key issue if we want to constrain missing contributions such as the contribution to sea level rise from the deep ocean (depths not covered by observations). For that purpose, we use several data sets as processed by different groups: six altimetry products for the GMSL, four Argo products plus the ORAS4 ocean reanalysis for the steric sea level and three GRACE-based ocean mass products. We find that over the study time span, the observed differences in trend of the residuals of the sea level budget equation can be as large as ~ 0.55 mm yr−1 (i.e., ~ 17 % of the observed GMSL rate of rise). These trend differences essentially result from differences in trends of the GMSL time series. Using the ORAS4 reanalysis (providing complete geographical coverage of the steric sea level component), we also show that lack of Argo data in the Indonesian region leads to an overestimate of the absolute value of the residual trend by about 0.25 mm yr−1. Accounting for this regional contribution leads to closure of the sea level budget, at least for some GMSL products. At short timescales (from sub-seasonal to interannual), residual anomalies are significantly correlated with ocean mass and steric sea level anomalies (depending on the time span), suggesting that the residual anomalies are related to errors in both GRACE-based ocean mass and Argo-based steric data. Efforts are needed to reduce these various sources of errors before using the sea level budget approach to estimate missing contributions such as the deep ocean heat content.

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