Bio-optical retrieval of Chl-a from complex waters: the lower Chesapeake Bay case Ilaria Nardello, Xiaoju Pan, David Ruble, Victoria Hill, Richard.C. Zimmerman Old Dominion University “Ocean Earth & Atmospheric Sciences”, 4600 Elkhorn Ave, VA 23539 – USA OBSERVATION PLATFORMS The Chesapeake Light Tower (CLT) -75.713ºE, 36.90 ºN Offshore from the mouth of the Chesapeake Bay, 25 km East of Cape Henry. Mean depth c.a=11m. Daily observations: - Above-water R rs (L t , E d , L sky ) Retrieval of biogeochemical properties from remote sensing of ocean color frequently fails in coastal waters, due to the contributions from riverine run off and sediment re-suspension to seawater absorption and scattering. The mouth of the Chesapeake Bay is an optically complex environment, with discontinuous riverine discharge (peaks: early spring, late summer) counteracted by semi-diurnal tidal mixing, creating a primary frontal zone. The presence of suspended particles and dissolved matter in these mainly case II waters varies, depending upon season (wet vs. dry) and tide cycles. Our research aims at developing in situ, regional, bio-optical relationship to be applied to satellite ocean color observations of the Chesapeake Bay. The R/V Fay Slover (Old Dominion University) The MODIS spectroradiometry on NASA/EOS satellite Aqua Direct Observations: -spectral nL w Derived Observations -Chl-a (O’Reilly et al. 2003) Monthly observations: - Above-water spectral Rrs (L t , L i , E d ) - Underwater IOPs (spectral a, c, b) - Phytoplankton pigments - Total Suspended Matter RESULTS 0 1 2 3 4 5 6 7 Jan-03 Jul-03 Jan-04 Jul-04 Jan-05 Jul-05 Jan-06 time (mmm-yy) Predicted Chl-a (mg/m^3) OC3M OC3-CB CLT 0.000 0.005 0.010 300 400 500 600 700 800 900 ASD wavelenght (nm) Rrs (sr^-1) Apr-05 May-05 Sep-05 COASTAL 0.000 0.005 0.010 300 400 500 600 700 800 900 ASD wavelenght (nm) Rrs (sr^-1) Apr-05 May-05 Sep-05 Evidence of strong variations in water components, according to proximity of the coast & season. CONCLUSIONS • A regional algorithm is necessary for the correct retrieval of Chl-a in the lower Chesapeake Bay • OC3-CB estimates of Chl-a in the lower Chesapeake Bay study area are lower than OC3M, and more accurate. • CLT time series will be a useful tool for the confident use of our algorithm in these highly variable, optically complex waters. Monthly time series of Chl-a (mg/m 3 ), from: - MODIS-A, 9-km resolution, by O C3M (in blue) - CLT data of Rrs, through OC3-CB (orange) REFERENCES - Arnone, R. A., and P. C. Gallacher (1996), Cruise report of the Weatherbird II during the Chesapeake Bay Outfall Plume Experiment (COPE 1, Sept 25-27, 1996), Naval Research Lab, Stennis Space Center, MS. *** Austin, J. (2002), Estimating th e mean ocean-bay exchange rate of the Chesapeake Bay, J. Geophys. Res., 107(C11), 3192, doi: 10.1029/2001JC001246. *** Harding, L. W. (1994), Long-term trends in the distribution of phytoplankton in Chesapeake Bay: roles of light, nutrients and streamflow , Mar. Ecol. Prog. Ser. 104, 267 – 291. *** 4) Mann, K. H., and J. R. N. Lazier (1996), Dynamics of marine ecosystems: biological-physical interactions in the ocean, 2nd ed., 394 pp., Blackwell Science Inc., Malden, Massachusetts *** Harding, L. W., A. Ma gnuson, M. E. Mallonee (2005), SeaWiFS retrievals of chlorophyll in Chesapeake Bay and the mid-Atlantic bight, Estuar. Coast. Shelf Sci. , 62, 75 – 94. *** Bayley S.W. and Werdell J.P., 2006: “A multi-sensor approach for the on-orbit validation of ocean c olor satellite data products”. Remote Sensing of Environment, 102, 1-2, 12-23. *** D'Ortenzio F., Marullo S., Ragni M., Ribera d'Alcala’ M., Santoleri R., 2002. Validation of empirical SeaWiFS algorithms for chlorophyll-a retrieval in the Mediterranean Sea: A case study for oligotrophic seas, Remote Sensing of Environment, 82-1,79-94. *** Hu C., Chen Z., Clayton T.D., Swarzenski P., Brock J.C., Muller–Karger F.E., 2004. Assessment of estuarine water-quality indicators using MODIS medium-resolution ba nds: Initial results from Tampa Bay, FL. Remote Sensing of Environment, 93-3, 423-441.. *** Martin, S., 2004: “An introduction on ocean remote sensing”. Cambridge University Press, Cambridge, United Kingdom, pp. 454. *** Mobley, C., 1994: “Light and Wat er. Radiative Transfer in Natural Waters”. Academic Press, San Diego, CA, USA, 592 pp. *** Mobley, C. D., 1999: “Estimation of the remote-sensing reflectance from above-surface measurements”. Appl. Opt. 36: 7442-7455. *** Morel, A., and L. Prieur, 1977: “Analysis of variations in ocean color”, Limnol. Oceanogr., 22, 709–722. *** Mueller, J. L., G. S. Fargion, and C. R. McClain, 2002: “Data requirements for ocean color algorithms and validation”. In Ocean optics protocols for satellite ocean color sens or validation, Revision 3, Vol. 2, edit by J.L. Mueller and G.S. Fargion, pp. 231-257, NASA Goddard Space Flight Center, Greenbelt, MD. *** O'Reilly, J.E., and 24 Coauthors, 2000: SeaWiFS Postlaunch Calibration and Validation Analyses, Part 3. NASA Tech . Memo. 2000-206892, Vol. 11, S.B. Hooker and E.R. Firestone, Eds., NASA Goddard Space Flight Center, 49 pp. *** Pan, X., 2006: “The observation, modeling and retrieval of bio-optical properties for coastal waters of the southern Chesapeake Bay”. P.h.D AKNOWLEDGEMENTS - This research is supported by the National Aeronautics and Space Administration (NASA), contract NNG04GN77G. OC3-CB corrects Chl-a retrieval in the lower Chesapeake Bay, as well as other coastal areas. The differences in Chl-a retrieval rapidly attenuate eastwards, and become negligible out of the continental shelf area, where the Gulf Stream Current is present. Differences of Chl-a concentration estimated by OC3M (O’Reilly et al., 2000) and OC3-CB. RRs (443>490)/Rrs(555) -0.3 -0.2 -0.1 0.0 0.1 Chl-a (mg/m^3) -0.6 -0.4 -0.2 0.0 0.2 0.4 0.6 0.8 1.0 1.2 OC3M OC3-CB __ __ __ Empirical algorithm OC3-CB Chl-a = 10 (-0.115-3.678*R) where: R = log10(R rs 443>R rs 490/R rs 555) n = 60 r = 0.889 n(95%) = 52 0.01 Chl-a (mg/m3) 7.0 Log10 scale Apr04 Aug04 Dec04 Feb04 0.01 Chl-a (mg/m3) 7.0 Log10 scale 0.01 Chl-a (mg/m3) 7.0 Log10 scale 0.01 Chl-a (mg/m3) 7.0 Log10 scale
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Bio-optical retrieval of Chl-a from complexwaters: the lower Chesapeake Bay case
Ilaria Nardello, Xiaoju Pan, David Ruble, Victoria Hill, Richard.C. ZimmermanOld Dominion University “Ocean Earth & Atmospheric Sciences”, 4600 Elkhorn Ave, VA 23539 – USA
OBSERVATION PLATFORMS The Chesapeake Light Tower
(CLT)
-75.713ºE, 36.90 ºN
Offshore from the mouth of theChesapeake Bay, 25 km East of
Cape Henry.
Mean depth c.a=11m.
Daily observations:- Above-water Rrs (Lt, Ed, Lsky)
Retrieval of biogeochemical properties from remote sensing of ocean color frequently fails in coastal waters, due to thecontributions from riverine run off and sediment re-suspension to seawater absorption and scattering. The mouth of theChesapeake Bay is an optically complex environment, with discontinuous riverine discharge (peaks: early spring, late summer)counteracted by semi-diurnal tidal mixing, creating a primary frontal zone. The presence of suspended particles and dissolvedmatter in these mainly case II waters varies, depending upon season (wet vs. dry) and tide cycles. Our research aims atdeveloping in situ, regional, bio-optical relationship to be applied to satellite ocean color observations of the Chesapeake Bay.
The R/V Fay Slover(Old Dominion University)
The MODIS spectroradiometryon NASA/EOS satellite Aqua
Direct Observations:-spectral nLw
Derived Observations-Chl-a (O’Reilly et al. 2003)
Monthly observations:- Above-water spectral Rrs (Lt, Li, Ed)- Underwater IOPs (spectral a, c, b)- Phytoplankton pigments- Total Suspended Matter
RESULTS
0
1
2
3
4
5
6
7
Jan-03 Jul-03 Jan-04 Jul-04 Jan-05 Jul-05 Jan-06
time (mmm-yy)
Pre
dic
ted
Ch
l-a (
mg
/m^
3)
OC3M
OC3-CB
CLT
0.000
0.005
0.010
300 400 500 600 700 800 900
ASD wavelenght (nm)Rrs
(s
r^-1
) Apr-05May-05
Sep-05
COASTAL
0.000
0.005
0.010
300 400 500 600 700 800 900
ASD wavelenght (nm)
Rrs
(s
r^-1
) Apr-05May-05Sep-05
Evidence of strong variations in watercomponents, according to proximity of thecoast & season.
CONCLUSIONS• A regional algorithm is necessary for thecorrect retrieval of Chl-a in the lowerChesapeake Bay
• OC3-CB estimates of Chl-a in the lowerChesapeake Bay study area are lower thanOC3M, and more accurate.
• CLT time series will be a useful tool for theconfident use of our algorithm in these highlyvariable, optically complex waters.
Monthly time series of Chl-a (mg/m3), from:
- MODIS-A, 9-km resolution, by O C3M (in blue)- CLT data of Rrs, through OC3-CB (orange)
REFERENCES - Arnone, R. A., and P. C. Gallacher (1996), Cruise report of the Weatherbird II during the Chesapeake Bay Outfall Plume Experiment (COPE 1, Sept 25-27, 1996), Naval Research Lab, Stennis Space Center, MS. *** Austin, J. (2002), Estimating the mean ocean-bay exchange rate of the Chesapeake Bay, J. Geophys. Res., 107(C11), 3192, doi: 10.1029/2001JC001246. *** Harding, L. W. (1994), Long-term trends in the distribution of phytoplankton in Chesapeake Bay: roles of light, nutrients and streamflow, Mar. Ecol. Pro g . Ser. 104, 267 – 291. *** 4) Mann, K. H., and J. R. N. Lazier (1996), Dynamics of marine ecosystems: biological-physical interactions in the ocean, 2nd ed., 394 pp., Blackwell Science Inc., Malden, Massachusetts *** Harding, L. W., A. Magnuson, M. E. Mallonee (2005), SeaWiFS retrievals of chlorophyll in Chesapeake Bay and the mid-Atlantic bight, Estuar. Coast. Shelf S c i ., 62, 75 – 94. *** Bayley S.W. and Werdell J.P., 2006: “A multi-sensor approach for the on-orbit validation of ocean color satellite data products”. Remote Sensing of Environment, 102, 1-2, 12-23. *** D'Ortenzio F., Marullo S., Ragni M., Ribera d'Alcala’ M., Santoleri R., 2002. Validation of empirical SeaWiFS algorithms for chlorophyll-a retrieval in the Mediterranean Sea: A case study for oligotrophic seas, Remote Sensing of Environment, 82-1,79-94. *** Hu C., Chen Z., Clayton T.D., Swarzenski P., Brock J.C., Muller–Karger F.E., 2004. Assessment of estuarine water-quality indicators using MODIS medium-resolution bands: Initial results from Tampa Bay, FL. Remote Sensing of Environment, 93-3, 423-441.. *** Martin, S., 2004: “An introduction on ocean remote sensing”. Cambridge University Press, Cambridge, United Kingdom, pp. 454. *** Mobley, C., 1994: “Light and Water. Radiative Transfer in Natural Waters”. Academic Press, San Diego, CA, USA, 592 pp. *** Mobley, C. D., 1999: “Estimation of the remote-sensing reflectance from above-surface measurements”. Appl. Opt. 36: 7442-7455. *** Morel, A., and L. Prieur, 1977: “Analysis of variations in ocean color”, L imno l . Oceanogr., 22, 709–722. *** Mueller, J. L., G. S. Fargion, and C. R. McClain, 2002: “Data requirements for ocean color algorithms and validation”. In Ocean optics protocols for satellite ocean color sensor validation, Revision 3, Vol. 2, edit by J.L. Mueller and G.S. Fargion, pp. 231-257, NASA Goddard Space Flight Center, Greenbelt, MD. *** O'Reilly, J.E., and 24 Coauthors, 2000: SeaWiFS Postlaunch Calibration and Validation Analyses, Part 3. NASA Tech. Memo. 2000-206892, Vol. 11, S.B. Hooker and E.R. Firestone, Eds., NASA Goddard Space Flight Center, 49 pp. *** Pan, X., 2006: “The observation, modeling and retrieval of bio-optical properties for coastal waters of the southern Chesapeake Bay”. P.h.D Dissertation, Old Dominion University, Norfolk, Virginia. *** Robinson, I. S., 2004: “Measuring the oceans from space. The principles and methods of satellite oceanography”. Springer Ed., pp 669. *** Thuillier, G., M. Hersé, P. C. Simon, D. Labs, H.Mandel, D. G i l l o tay , T. Foujols, 2003: "The solar spectral irradiance from 200-2400 nm as measured by the SOLSPEC spectrometer from the ATLAS 1-2-3 and EURECA missions”. Solar Physics, 214(1):1-22
AKNOWLEDGEMENTS - This research is supported bythe National Aeronautics and Space Administration (NASA), contractNNG04GN77G.
OC3-CB corrects Chl-aretrieval in the lowerChesapeake Bay, aswell as other coastalareas. The differences inChl-a retrieval rapidlyattenuate eastwards,and become negligibleout of the continentalshelf area, where theGulf Stream Current ispresent.
Differences of Chl-a concentration estimated by OC3M (O’Reilly et al., 2000) and OC3-CB.
RRs (443>490)/Rrs(555)-0.3 -0.2 -0.1 0.0 0.1
Chl-a (mg/m
^3)
-0.6
-0.4
-0.2
0.0
0.2
0.4
0.6
0.8
1.0
1.2
OC3MOC3-CB
__
____
Empirical algorithmOC3-CB
Chl-a = 10(-0.115-3.678*R)
where:R = log10(Rrs443>Rrs490/Rrs555)n = 60r = 0.889n(95%) = 52
0.01 Chl-a (mg/m3) 7.0
Log10 scale
Apr04 Aug04 Dec04Feb04
0.01 Chl-a (mg/m3) 7.0
Log10 scale
0.01 Chl-a (mg/m3) 7.0
Log10 scale
0.01 Chl-a (mg/m3) 7.0
Log10 scale
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