Air-sea CO 2 flux climatology for the Baltic Sea

Transcription

1 ESA SOLAS EGU meeting 28 th- 31 st October 2014 Air-sea CO 2 flux climatology for the Baltic Sea Gaëlle Parard 1, A.A.Charantonis 2 S. Raj Parampil 1 and A. Rutgerson 1 1 Department of Earth Sciences, Uppsala University, Sweden 2 LOCEAN, IPSL/UPMC,/CNRS, Paris, France 1

2 Context Exchange of CO 2 between coastal environments and atmosphere 16 % of the open ocean sink but continental shelf < 7 % of the oceanic surface Problem for the quantification the oceanic sink and large uncertainty related to sparse of in-situ data coverage in time and space Baltic Sea is comparably well monitoring (program for several decades) Nevertheless air-sea CO 2 flux estimation in Baltic Sea remains particularly challenging Neural network have the potential to generate additional information Estimate pco 2 variability in the global Baltic Sea with satellite data Estimate the CO 2 flux in Baltic Sea 2

3 In situ Data: monthly average 1445 measurement between at monthly scale : - Measurement of pco 2 (SAMI sensor) at Östergarnsholm station since June SMHI mooring in Baltic Sea ( ) (pco 2 compute with carbonate relation (TA and ph ) ) - Ship measurements VOS ( )(Schneider et al., 2006) GB Problem : concentrate in the middle of the Baltic Sea Combined methods : Self Organizing Map and Multiple Linear regression (SOMLO from Sasse et al., 2013) 3

4 SST: Satellite DATA - Federal Maritime and Hydrographic Agency (BSH) processing the data from AVHRR-NOAA( ) - GRHSST (Group for High Resolution Sea Surface Temperature) product for Baltic Sea ( ). - NOAA/NASA Advanced Very High Resolution Radiometer (AVHRR) data stream conducted by the University of Miami s Rosenstiel School of Marine and Atmospheric Science (RSMAS) ( ) Chlorophyll : - SeaWiFS (Sept Dec. 2002) 4 km monthly - MODIS-Aqua (Jul Jun. 2011) 4 km monthly CDOM : - MODIS data 4km monthly average. Primary Production: MLD WIND - EMIS: depth-integrated model (Lee et al., 2005). The primary production calculation is based on Platt and Sathyendranath (1993). monthly average (Oct to Sept. 2008). - Vertically Generalized Production Model ( VGPM) ( ). The VGPM is a "chlorophyll-based" model that estimate net primary production from chlorophyll using a temperature-dependent description of chlorophyll-specific photosynthetic efficiency. - One3D hydrodynamic model currently used at the JRC/IES is the public domain GETM model (General Estuarine Transport Model monthly averages ( ), - Carbon-based production model at monthly scale (Behrenfeld et al. 2005) (2008 and 2011) to July 1999, July 1999 to December 1999: QuikSCAT 2000 to 2009: Flux-merged 4

5 Distribution of each parameters Strongly dependant of SST and chlorophyll. MLD : Higher value during winter 5

6 Validation of the method Monthly data : 10 % of the data set RMS = 36.7 μatm 45 % > 20 μatm Good correlation R=0.93 Close from some other studies with more vectors ( ) 6

7 pco 2 Map MARCH 2010 JULY 2010 SEPTEMBER 2010 Reconstruction from 1998 to 2011 : Seasonal cycle well reproduce (winter : 437 μatm and summer :274 μatm similar to Wesslander, 2011) 7

8 A simple flag MARCH 2010 JULY 2010 SEPTEMBER 2010 Simple Flag : Value neuron Value estimated 1. <20 μatm μatm <x< 30 μatm 3. > 30 μatm 8

9 Comparison with model BS GF GB CP Model output : 13 basins in Baltic Sea ( Horizontal average, vertical resolution) Higher correlation for BS & CB : 0.7 Higher variation : GF Lower variation : BB 9

10 Climatology of pco 2 10

11 FCO 2 =k(u)*δpco 2 pco 2atm =x trend +x anthropogeni + x tnatural (Norman et al., 2013) U : Satellite product : (R= 0.8 & RMSD = 1.3) Baltic Sea : source or sink : several studies from model not agree : -3.6<F<2.9 mol CO 2 m -2 y -1 Low sink : but without data in January and December molco 2 m -2 y -1 Wind product and pco 2atm increased the errors Need Validation Air-sea CO 2 Fluxes : Interannual variability 11

12 Summary Promising results : Study based on 1445 vectors : R=0.93 and RMS=36 μatm Other study with lower and close result but more vectors (e.g.:friedrich and Oschlies 2009, Hales et al.,2012) Central basin well reproduce compare to Gulf of Bothnia : due to the lake of data Climatology of pco 2 computed from in-situ data Air-sea CO 2 flux: order of magnitude seems in agreement with other studies Wind product lower resolution difficult to compute 12

13 Perspectives Improvement of the results due to acquisition of new data Sami sensor, SMHI, VOS transect New acquisition : Data from ferry boat from Gothenburg Utö Atmospheric and Marine research station Improve the estimation of pco 2 in Gulf of Bothnia Succeeds to have data in January and December 13

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15 Method : Self Organising Maps 15

16 Air-Sea flux of CO 2 FCO 2 =k(u)*(pco 2water -pco 2atm ) pco 2atm =x trend +x anthropogeni +x tnatural (Norman et al., 2013) U : Wind (Satellite product) : Comparison in-situ data & satellite product : R= 0.8 RMSD = 1.3 Lower resolution than pco 2 Problem with 1998 and 1999 : Lower resolution and low correlation : Flux really high not realistic 16

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