Towards Better Air-Sea Fluxes: Achievements of the ESA OceanFlux

Greenhouse Gases ProjectDavid Woolf (Heriot Watt), Lonneke Goddijn-Murphy,

Jamie Shutler (PML), Peter Land, Phil Nightingale, Ricardo Torres,Margaret Yelland (NOCS), Ben Moat, John Prytherch,

Bertrand Chapron (IFREMER), Jean-Francois Piolle, Fanny Girard-Ardhuin, Jenny Hanafin, Fabrice Ardhuin, Jean Tournadre

OceanFlux GHG was funded by: and affiliated to:

Overview

1. Background to the project

ESA and SOLAS

The role of the oceans in the global carbon cycle

2. Specific objectives

3. Key Achievements

Overview

1. Background to the project

ESA and SOLAS

The role of the oceans in the global carbon cycle

2. Specific objectives

3. Key Achievements

Methodical treatment of uncertainty – gas transfer and fluxes

Transfer velocities from space

Consistent and appropriate treatment of temperatures

Inclusion of secondary processes, e.g. rain

FluxEngine - A flexible architecture for calculations

Flux Uncertainty Estimates

Background: The OceanFlux Initiative

OceanFlux GHG is one of 3 projects arising from collaboration between ESA and International SOLAS under the STSE umbrella. STSE projects are all built upon a few broad principles:

• Reinforce scientific collaboration between ESA and international programmes

• Fostering collaboration between different scientific communities

• Developed in close collaboration with international programmes

Background: The OceanFlux Initiative

OceanFlux GHG is one of 3 projects arising from collaboration between ESA and International SOLAS under the STSE umbrella. STSE projects are all built upon a few broad principles:

• Reinforce scientific collaboration between ESA and international programmes

• Fostering collaboration between different scientific communities

• Developed in close collaboration with international programmes

Initiated by ESA in 2009, a workshop followed in 2010, ESA issued “Invitations to Tender” in 2011.

OceanFlux GHG started November 2011 as a two-year project.

Final meeting was in February 2014.

transfer

Background: The Carbon cycle

Atmosphere

Surface ocean

Deep ocean

F = k (αw pCO2w – αs pCO2a )

F solubility pump F biological pump F mix

pCO2a

pCO2w

Carbon export to the deep ocean

Basic box model

SOLAS

IMBER

OceanFlux GHG

OceanFlux Greenhouse Gases (GHG)

Multi-disciplinary team, expertise in:

• EO scientists and experts (near-infrared, optical, radar, microwave)

• In situ scientists

• Members of the SOLAS community

• Wave modellers

• Hydrodynamic ecosystem modelling

• Expertise in efficient processing of large datasets

OceanFlux Greenhouse Gases (GHG)

Multi-disciplinary team, expertise in:

• EO scientists and experts (near-infrared, optical, radar, microwave)

• In situ scientists

• Members of the SOLAS community

• Wave modellers

• Hydrodynamic ecosystem modelling

• Expertise in efficient processing of large datasets

To meet Specific Objectives:

•…create new products … from … EO data, in situ data and modelling …

•… estimate and reduce uncertainty …

•… transfer velocity calculations using satellite-derived mean square slope …

•… impact of biogenic surface slicks …

•… impact of diurnal variability in SST …

•… exploit modelling frameworks ….

Key Achievements – A methodical and transparent process

In any complex system of knowledge generation it is easy to lose track of underlying assumptions and the origin of commonly-used formulae.

Air-sea GHG fluxes are sufficiently important that a careful and transparent methodology for estimating fluxes with their realistic uncertainties should be required.

OceanFlux GHG “started from basics” and tried to follow dependencies and uncertainty estimates through the sequence of calculations required for air-sea gas flux estimates. Crucial dependencies and uncertainties are identified:

Key Achievements – A methodical and transparent process

In any complex system of knowledge generation it is easy to lose track of underlying assumptions and the origin of commonly-used formulae.

Air-sea GHG fluxes are sufficiently important that a careful and transparent methodology for estimating fluxes with their realistic uncertainties should be required.

OceanFlux GHG “started from basics” and tried to follow dependencies and uncertainty estimates through the sequence of calculations required for air-sea gas flux estimates. Crucial dependencies and uncertainties are identified:

• Uncertainty in transfer velocity

• Sparsity of dissolved gas concentration measurements

• The secular trend in dissolved fugacities and “reference year” calculations

• Treatment of temperature

• Secondary environmental factors (rain, biogenic slicks …)

Key Achievements – A methodical and transparent process

In any complex system of knowledge generation it is easy to lose track of underlying assumptions and the origin of commonly-used formulae.

Air-sea GHG fluxes are sufficiently important that a careful and transparent methodology for estimating fluxes with their realistic uncertainties should be required.

OceanFlux GHG “started from basics” and tried to follow dependencies and uncertainty estimates through the sequence of calculations required for air-sea gas flux estimates. Crucial dependencies and uncertainties are identified:

• Uncertainty in transfer velocity

• Sparsity of dissolved gas concentration measurements

• The secular trend in dissolved fugacities and “reference year” calculations

• Treatment of temperature

• Secondary environmental factors (rain, biogenic slicks …)

Technical - FluxEngine was developed to address

• The dependence of calculations on appropriate and consistent data sets

• The value of ensemble or scenario calculations as an empirical measure of uncertainty

Key Achievements – Ambiguity and Uncertainty in Transfer Velocity

Appropriate choice of gas transfer velocity parameterisations is a matter of expert interpretation

Different data informs different empirical parameterisations (Ambiguity)

The same data can be fitted by different models (Structural Uncertainty)

Any model fit will not precisely determine the coefficients (Parameter Uncertainty)

Structural Ambiguity

Key Achievements – Ambiguity and Uncertainty in Transfer Velocity

Appropriate choice of gas transfer velocity parameterisations is a matter of expert interpretation

Different data informs different empirical parameterisations (Ambiguity)

The same data can be fitted by different models (Structural Uncertainty)

Any model fit will not precisely determine the coefficients (Parameter Uncertainty)

Structural Ambiguity

Results:

• Calibrations of Kw and kw for DMS as a function of σKu and U10

• A scheme to apply our results for DMS to any other gas

Conclusion: σKu from satellite altimeters can be used to assess kw on a global scale

Key Achievements – Transfer Velocities from Space I

Kw calibrations, data binned in 0.01 intervals of 1/σKu and 1 m/s of U10Goddijn-Murphy, L., D. K. Woolf, C. Marandino (2012), “Space-based retrievals of air-sea gas transfer velocities using

altimeters:

Calibration for dimethyl sulfide”, J. Geophys. Res., 117, C08028, doi:10.1029/2011JC007535

Key Achievements – Transfer Velocities from Space II

Methods:• The same DMS gas flux measurements and altimeter database are used (JGR, 2012)

• Values of back scattering coefficients, σKu, and σC of two Ku-band and C-band carrying altimeter satellites

• Comparison of different Kw algorithms using 1/σKu and 1/σC , and also 10m wind speed U10 (in situ and altimeter)

• Test of the statistical robustness of differences in performance using a “bootstrap” method

An improvement by including a second, lower-frequency band in the satellite altimeter algorithms for Kw is demonstrated

Fit results for single band (1-2), dual band (3-4) and wind speed (5) algorithms; the coinciding altimeter data are within 0.5°distance and time dt

Goddijn-Murphy, L., D.K. Woolf , B. Chapron and P. Queffeulou (2013) The enhancement of using dual-frequency, instead of single-frequency, altimeter backscatter for estimating air-sea gas transfer velocity, Remote Sensing of the Environment.

Key Achievements – Treatment of Temperature

Temperature is important implicitly or explicitly at various points in calculations of air-sea gas fluxes

Choice of temperature product depends on understanding vertical profiles of temperature and dissolved gas concentration.

EO-based monthly composite sea surface temperatures provided a reliable and consistent product, but required reprocessing of ship-based measurements of gas concentration (SOCAT)

Key Achievements: Rain impacts on air-sea CO2 flux I

Methods:• Baseline data– default air-sea fluxes calculated using a wind gas transfer (k).• Parameterise wet deposition flux (Fw), rain k (Fk), rain dilution (Fd) and flux (Fk) based on published literature. • Run 20 year time series using OceanFlux-GHG data processing system and Ifremer Cloud (using CCI, GlobWave data etc)• Calculate global and regional Fw, Fk, Fd and compare with the baseline.

Example rainfall dataset (EO + in situ) Average annual rain driven gas transfer

Rain can impact air-sea gas fluxes through a number of mechanisms. Current work to quantify global air-sea gas fluxes ignore rain. Is this a large source of error ?

Key Achievements – Flexible Calculations using FluxEngine

Based on a flexible processing pathway configured by the user

Shutler, J. D., Piolle, J-F., Land, P., Woolf, D. K., Goddijn-Murphy L.,, Paul, F., Girard-Ardhuin, F., Chapron, B., Donlon, C. J., (in-review) Flux Engine: A flexible processing system for calculating air-sea carbon dioxide gas fluxes and climatologies, submitted to Journal of Atmospheric and Oceanic Technology.

Key Achievements – FluxEngine and Data Sets Global regular grid 1o x 1o climatology + processing tools

Uncertainty information

Attribute layers (inc surface biology, diurnal warming etc).

Normalised to 2010

Data at different depths (e.g. interfacial CO2 concentrations, pCO2 at base of micro-layer)

Quantities: SSTskin, SSTfnd, salinity, whitecap coverage, solubility, fugacity, k total, krain +..)

Example outputgenerated on theNephalae cloud.

Key Achievements – Flux Uncertainties

A large number of calculations lead to numerous estimates of the net global air-sea flux of carbon dioxide, each for an assumed “scenario”

Example output: A demonstrated “structural uncertainty” following from different gas transfer model fits to the same Dual Tracer Experiment (DTE) data

Key Achievements – Workshop!

Air-sea gas flux climatology; Progress and Future prospects

24-27 September 2013, IFREMER, Brest, France.

>80 participants, Full report in workshop minutes (D2.18)

OceanFlux GHG – Summary and Reflections

OceanFlux Greenhouse Gases (GHG)

- develop, evaluate, study and reduce uncertainties in EO derived air-sea fluxes

Outputs include:

•Global v0.95 air-sea CO2 flux climatology, FluxEngine

•Series of scientific studies (4 journal papers published, 2 in-review, 5 in draft)

•Community workshop (24-27th Sept 2013, Brest, France)

•www.oceanflux-ghg.org

On reflection:

“Methodical and transparent”; necessary, but easier said than done

Adoption of a “reference year” leads to numerous compromises and ambiguities; calculations for individual months is better where practical

Thank you to the SOCAT community!

Results:• Rain increases the annual global oceanic net sink of CO2 by up to 10 %.

– This can be used as the estimate of rain uncertainty in annual global net fluxes.

• Regional annual variations– Rain can increase the annual Southern ocean net sink by up 13 %

• Regional monthly variations– Pacific and Southern ocean monthly fluxes can be significantly modulated by rain (ie > ± 15%)– Instances of very large modulation (ie > ± 50%)

Conclusion: Rain should be included in any thorough gas flux uncertainty analysis

Shutler, J. D., Land, P. E., Woolf, D. K., Quartly, G., Zappa, C. J., McGillis, W. R. (draft) Characterising the impact of rain on global and regional air-sea fluxes of CO2: a 20 year global sensitivity analysis, to be submitted to JGR Biogeosciences.

Key Achievements: Rain impacts on air-sea CO2 flux II

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Time (10 year results)

Impact of rain on monthly global air-sea CO2 gas fluxes from EO