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Particulate Organic Carbon (POC) measured from satellites Wilford Gardner Mary Jo Richardson Young Baek Son Alexey Mishonov Texas A&M University Fulbright.

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Presentation on theme: "Particulate Organic Carbon (POC) measured from satellites Wilford Gardner Mary Jo Richardson Young Baek Son Alexey Mishonov Texas A&M University Fulbright."— Presentation transcript:

1 Particulate Organic Carbon (POC) measured from satellites Wilford Gardner Mary Jo Richardson Young Baek Son Alexey Mishonov Texas A&M University Fulbright Fellow - Greece

2 OCTET working group report

3 Particle concentration versus depth Biogenic particles dominate

4

5 Chlorophyll content from ocean color Related to phytoplankton biomass Refined over the last 30 years Models to determine primary production Methods to determine phytoplankton types Our goal: Determine Particulate Organic Carbon (POC) from ocean color Why? Bulk Chl ranges from 0.1 to 2% of POC Chl is about 1.5 - 4 % of phyto biomass POC is about 50% of biomass Increase spatial and temporal resolution of carbon dynamics in ocean Monitor past and predict future impacts of climate change on carbon budget

6 Study hydrography of NE Gulf of Mexico 9 cruises over 3 years, 60 POC stations per cruise

7 POC concentration versus beam attenuation POC/PM > or < 25%

8 POC (mg m -3 ) distribution contoured from surface bottle data

9 POC versus Chl POC versus K 490 Previous efforts to estimate POC from satellite data Stramski et al, 1999 POC versus Lwn 555 -not shown

10 Upwelled irradiance versus POC at 6 wavelengths

11 Upwelled irradiance at 6 wavelengths, binned concentrations 20 - >550 mg m -3

12 Garrison Fig. 6.12b Bars show depths at which only 1% of the light energy remains

13 Upwelled irradiance at 6 wavelengths, binned concentrations 20 - >550 mg m -3

14 3rd order polynomial fit of data Normalized Difference Carbon Index

15 Upwelled irradiance at 6 wavelengths, binned concentrations 20 - >550 mg m -3

16 5th order polynomial fit of data Maximum Normalized Difference Carbon Index

17 POC from bottles POC from MNDCI July 2000

18 POC from bottles POC from MNDCI April 2000

19 [Pg C] or Pg C/yr Sabine et al., 2004 SCOPE 62

20 HCMR PM and POC data - testing algorithms

21

22 Conclusions Shipboard sampling is insufficient - obviously Algorithm development of upper ocean parameters is needed Allows global measurements Beyond physical and political reality with ships POC can be well correlated with ocean color Greater spatial & temporal resolution Can guide sampling strategies Test for impacts of climate change - need time series Necessary for ocean modeling - predict future impacts

23 Thanks for sharing your beautiful country with us!

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