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CASIX Science Update

July 2006

Measuring atmospheric CO2 from space using Full Spectral Initiation (FSI) WFM-DOAS

Michael Barkley and Paul Monks, EOS Group, University of Leicester

The major focus of the University of Leicester efforts within Project 3 has been the development of the Full Spectral Initiation (FSI) algorithm (described in detail in Barkley et al., 2006) which is designed to retrieve CO2 from space using the SCIAMACHY instrument, on-board ENVSIAT. The FSI algorithm is based on the WFM-DOAS technique (Buchwitz et al., 2000), whereby the total columns of a range of greenhouse gases can be retrieved from spectral measurements in the near-infrared, through the fitting of a model reference spectra plus its derivatives, to the measured sun-normalised radiance. In order to minimize the errors on the retrieved CO2 columns, the FSI algorithm is biased towards the use of a-priori data, generating a model reference spectrum for each individual SCIAMACHY observation using the known, or rather, estimated properties of the atmosphere and the surface at the time of the measurement. This approach is chosen in preference to performing global retrievals using only a finite number of reference spectra (e.g. Buchwitz et al., 2005). To read more click here.

April 2005

From silk to satellite: A half century of ocean color

Dionysios Raitsos and Samantha Lavender, University of Plymouth

Phytoplankton play a major role in the absorption and storage of carbon dioxide in the oceans. Because phytoplankton contain chlorophyll, it is possible to estimate their abundance by measuring the color of ocean waters. Since 1931, researchers on ships have collected plankton on silk and estimated phytoplankton biomass based on the resulting color of the silk. Beginning in 1997, images from NASA's SeaWiFS satellite made it possible to measure the color of large regions of the ocean and estimate phytoplankton abundance. The usefulness of the SeaWiFS dataset is, however, limited by its short time span. Raitsos et al. compared the satellite data and the data collected from ships for a region of the Northeast Atlantic from 1997 to 2002. They found that the two datasets strongly agreed in their estimates of phytoplankton abundance. This allowed them to use the ship-collected data to extrapolate the SeaWiFS dataset back to 1948. They suggest that this extended dataset will improve models of marine ecosystems and our understanding of biogeochemical cycling and climate change.

Title: Extending the SeaWiFS chlorophyll data set back 50 years in the northeast Atlantic

Authors: Dionysios E. Raitsos, Philip C. Reid, Samantha J. Lavender, Martin Edwards, and Anthony J. Richardson, University of Plymouth, Plymouth, United Kingdom.

Source: Geophysical Research Letters (GL) paper 10.1029/2004GL022484, 2005.

From AGU Journal Highlights: http://www.eurekalert.org/pub_releases/2005-04/agu-ajh041405.php

January 2005

Interface Modelling Tool now available to all CASIX members

Helen Kettle and Chris Merchant, University of Edinburgh

A 1-D bio-geochemical ocean turbulence model for air-sea carbon flux is now available to members of CASIX. Using this model you can simulate the ocean carbon cycle and resulting CO2 fluxes at any time and space resolution. The model is ideal for studying short time scale at the air-sea interface. For example, diurnal variations in carbon flux governed by diurnal variation of light and turbulent mixing through the water column. To read more click here.

December 2004

Systematic errors in global air-sea carbon fluxes caused by temporal averaging of sea-level pressure (Project 8)

Helen Kettle and Chris Merchant, University of Edinburgh

Long-term time averaging of meteorological data, such as wind speed and air pressure, can cause large errors in air-sea carbon flux estimates. Other researchers have already shown that time averaging of wind speed data creates large errors in flux due to the non-linear dependence of the gas transfer velocity on wind speed (Bates and Merlivat, 2001). Here we show that long-term time averaging of the partial pressure of CO2 in the atmosphere (pCO2air) also causes significant errors in flux. To read more click here.

November 2004

Quantifying Surface Slicks for CO₂ flux studies (Project 2)

Rob Potter and Gay Mitchelson-Jacob, University of Wales Bangor

Global ocean studies of sea-air CO2 flux based on climatological surface ocean pCO2 and seasonal biological and temperature effects (Takahashi et al 2002) have so far not included the effects of small to mesoscale slicks on CO2 flux (Scott 1999). Our aim is to develop a synergistic use of ENVISAT and ERS data to quantify surface films within oceanic regions that are either a source or sink for air-sea gas flux. Surface films of natural (Espedal 1998) and anthropogenic (Gade and Alpers 1999) origin, are known to dampen the sea surface roughness detected by SAR, that also depends on the polarisation of SAR signal emissions (Gade et al, 1998). The rate of CO2 gas transfer is known to depend on wind velocity and sea surface temperature, with a recent study that highlights the importance of air pressure that dictates the CO2 partial presure at the air-sea boundary (Kettle and Merchant 2005). These factors vary regionally due to complex coupling between the local and remote atmospheric forcing and subsequent oceanic response. Further complications arise, where seasonal phytoplankton blooms occur, that are responsible for biogenic slicks (Frew et al 1990) and CO2 draw down through their photosynthetic reactions (Ditullio et al 2000).

For the selected test sites Envisat ASAR data will be obtained and analysed with the aim to quantify natural and anthropogenic slicks (by size, thickness, type). ESA BEST software will be used to calibrate the ASAR backscatter in dB values (Rosich and Meadows 2004). An analysis of the differences between natural and man made slicks can be determined using fractal analysis – man made slicks tend to have a smooth boundary (Jolly et al, 1999). Considering the variance of slick features both regionally and temporally will lead to an estimate for the upper and lower bounds for the backscatter at selected test locations. CASIX partners at SOC responsible for Project 1, are using dual frequency altimetry to detect surface slicks at scales of the altimeter footprint O(10km). This data will be used to compare with wide swath ASAR data acquired for Project2, to validate the altimeter measurements. A recent development by Horstmann and Koch (2003) explores the potential for retrieving Wind Fields from ASAR. This will allow for the dependency of air-sea gas exchange on the wind velocity to be further investigated. Additionally, Ekman horizontal and vertical velocities could be derived (e.g. sites of upwelling of nutrients) leading to specific studies on the processes that effect air-sea gas transfer.

For regions with known biological blooms the use of MERIS data ought to help us to determine the origin of slicks imaged by ASAR (Da Silva et al 2004). Whilst AATSR SST data should help us to assess the influence of stability of the atmospheric boundary layer that might lead to ambiguity in slick detection imaged by SAR (Wu 1991). The results of this work should therefore lead to a climatology of slicks in a number of test regions and to the development of a robust algorithm to detect slicks. With this developed skill we should then be able to improve the models for calculation of gas transfer in the presence of slicks.

References

Binding,C.E., D.G.Bowers, E.G.Mitchelson-Jacob, An algorithm for the retrieval of suspended sediment concentrations in the Irish Sea from SeaWiFS ocean colour satellite imagery, International Journal of Remote Sensing, 24, Number 19, 10 October 2003.

Da Silva, J.C.B, S.Correla, S.A.Ermakov, I.A.Sergievskaya and I.S.Robinson, Synergy of MERIS/ASAR for observing marine slicks and small scale processes, Proc. MERIS user workshop, Frascati Italy, 10-13

November 2003 (ESA SP-549, May’04).

Ditullio, G.R., J.M.Grebmeier, K.R.Arrigo, M.P.Lizotte, D.H.Robinson, A.Leventer, J.P.Barry, M.L.Vanwoert and R.B.Dunbar, Rapid and early export of Phaeocystis antarctica blooms in the Ross Sea, Antarctica, Nature 404, 595 - 598, 06 April 2000.

Espedal, H.A., et al, COASTWATCH’95: ERS-1/2 SAR detection of natural film on the ocean surface, J.Geophys.Res., 103, no.C11, pp24969-24982, 1998.

Frew, N.M., et al, The impact of phytoplankton generated surfactants on gas exchange at air-sea interface, JGR, 95, pp3337-,1990.

Gade, M. et al, The imaging of biogenic and anthropogenic surface films by the multi-polarisation SIR-C/X-SAR, JGR, 103, pp18866-18866, 1998.
 

Gade, M., and W.Alpers, Using ERS-2 SAR images for routine observations of marine pollution in European coastal waters, Science of the Total Environment, 1999.
 

Heywood,K.J., A.C.Naveira Garabato and D.P.Stevens, High mixing rates in the abyssal Southern Ocean, Nature 415, 1011 - 1014, 28 February 2002.
 

Horstmann, J. and W. Koch, High resolution ocean surface wind fields retrieved from spaceborne SAR operating at C-band, 2003 (http://w3g.gkss.de/G/Mitarbeiter)
 

Jolly, G.W., et al, The Clean Seas Project – A Final Report, November 1999.
 

Kettle, H. and C.J. Merchant, Systematic errors in global air-sea CO2 flux caused by temporal averaging of sea-level pressure, Atmos. Chem. Phys. Discuss., 5, pp325-346, 2005.
 

Kvenvolden, K.A., and C.K. Cooper, Natural seepage of crude oil into the marine environment, Geo.Mar.Lett., 23, 140-146, 2003.
 

Mitchelson-Jacob, E.G., and S.Sundby, Eddies of Vestfjorden, Norway, Continental Shelf Research, 21(16), pp1901-1918, 2001.
 

Romeiser, R, et al, On the remote sensing of oceanic and atmospheric convection in the Greenland Seas by SAR, JGR(oceans), 109, NoC3, 02 March 2004.
 

Rosich, B. and P. Meadows, Absolute calibration of ASAR Level 1 products generated with PF-ASAR, Technical Note, rev. 5, 07 October 2004.
 

Scott, J., Ocean Surface Slicks – Pollution, Productivity, Climate, and Life-Saving, IEEE, IGARSS 1999.
 

Takahashi,T., et al, Global sea-air CO2 flux based on climatological surface ocean pCO2 and seasonal biological and temperature effects, Deep Sea Research, II, 49, pp1601-1622, 2002.
 

Wassmann. P., T.Ratkova, I.Andreassen, M.Vernet, G.Pedersen and F.Rey, Spring Bloom Development in the Marginal Ice Zone and the Central Barents Sea, Marine Ecology, Volume 20, Issue 3-4 P321,December 1999
 

Wu, J., Effects of atmospheric stability on oceanic ripples: A comparison between optical and microwave measurements, J.G.R, 96, pp7265-7269, 1991.