Subramaniam et al. (2002) represents the most recent attempt at optical characterization of Trichodesmium

Method: Compare nLw() spectra against shape and magnitude criteria determined by empirical modeling results and observations:

1. nLw(490) > 1.3 mW cm-2 m-2 sr-1 & nLw(490) > nLw(412), nLw(443), nLw(555)2. nLw(510) > nLw(443)3. 0.4 < [nLw(490) – nLw(443)]/[nLw(490) – nLw(555)] < 0.6

How often does this dataset meet these criteria?

criteria 1 2 3 1&2 1,2,&3

0% 0% 0% 0% 0%

According to this protocol NONE of these observations should contain Trichodesmium Why doesn’t this method work?

• Levels of Tricho represented in this dataset are too low• Criteria were based upon a single SeaWiFS scene• Variability in Trichodesmium absorbing and scattering

properties not properly accounted for

A new technique for remote sensing of TrichodesmiumA new technique for remote sensing of TrichodesmiumToby Westberry1, Dave Siegel1, Ajit Subramaniam2

1 Institute for Computational Earth System Science, University of California, Santa Barbara, 2 Earth System Science Interdisciplinary Center, University of Maryland

Abstract. Ocean color remote sensing of Trichodesmium spp. provides a method to estimate the importance of N2 fixation in global ocean biogeochemical cycling. This requires a globally applicable bio-optical model that relates Trichodesmium biomass to its water leaving radiance signal. Previous empirical models do not perform well compared with a global dataset containing concurrent measurements of Trichodesmium abundances and available radiometric measurements. Hence, alternative approaches must be developed. Here, we develop and present a new Trichodesmium-specific inverse reflectance model to determine the presence of Trichodesmium blooms. Model coefficients were optimized using the in situ global dataset and >75% of Trichodesmium blooms are correctly identified while the number of false positive retrievals is minimized. An example application of the model to SeaWiFS imagery is shown. Preliminary results show spatial distributions consistent with published syntheses of Trichodesmium bloom occurrences suggesting the validity of this approach. Further work will be focused on understanding the oceanographic and atmospheric conditions which lead to Trichodesmium blooms and an estimate of global N2 fixation due to these blooms.

In situ observations

• coincident radiometric measurements and Trichodesmium abundances

• collected on various cruises from 1994-present (BATS, AMT, others)

• N=130

Acknowledgements and ReferencesCapone, DG, Zehr, JP, Paerl, HW, Bergman, B, Carpenter, EJ. 1997. Trichodesmium, a globally significant marine cyanobacterium, Science, v276, 1221-1229.

Maritorena, S, Siegel, DA, Peterson, AR, in press. Optimization of a semi-analytical ocean color model for global scale applications. Applied Optics, .....................

Subramaniam, A., Brown, CW, Hood, RR, Carpenter, EJ, and Capone, DG, 2002. Detecting Trichodesmium blooms in SeaWiFS imagery. Deep-Sea Research II, v49 (1-3), 107-121.

Many thanks to Ajit Subramaniam, Doug Capone, Stephane Maritorena, Norm Nelson and others for data collection and sharing. Thanks to Stephane Maritorena, Margaret O’Brien and other folks for technical assistance. This work is supported by NASA Earth System Science Fellowship (# NGT5-30406).

• Existing empirical algorithms for quantifying Trichodesmium are inconsistent with field observations

• A refined semi-analytic model for estimating the presence of Trichodesmium blooms was developed and validated, correctly identifying ~75% of blooms in the in situ dataset

• The model has been successfully applied to global SeaWiFS imagery

• Spatial distributions appear roughly consistent with historical areas of recurrent Trichodesmium blooms

• Further observations of Trichodesmium abundance under a wider range of bloom conditions will allow accuracy of model retrievals to be better constrained

• Next steps include:1. Determining environmental conditions under which Trichodesmium blooms are found.2. Estimating N2 fixation rates spatially and temporally using the mapped bloom product

1. INTRODUCTION 2. PREVIOUS WORK

Wavelength [nm]

Rrs

(,0

+)

[s

r-1]

Chl [mg m-3]Tricho [trichomes L-1]

AMTBATS

1. Remote sensing reflectance above the sea surface

2. Surface Trichodesmium abundance 3. Surface chlorophyll concentration

Trichodesmium-specific inverse ocean color model

Development of an inverse ocean color model that retrieves Tricho abundance explicitly given Rrs(,0+):

Details:

- spectral shapes taken from available sources (Subramaniam et al., 1999; Maritorena et al., 2002)

- can be solved by non-linear least squares techniques

- coefficients C1 & C2 are “tuning” parameters and are equal to 0.606 & and 0.146, respectively

*( ) ( )h pp hChl aa

0 0( )( ) exp[ ( )]cdc mdm Saa

red = unknown

blue = measured or modeled

0 = 443 nm

2

1

( ) ( ) ( )( )

( ) ( ) ( ) ( ) ( ) ( ) ( )

i

w p trichoi

i w p tricho w ph cdm tricho

bb bb bbRrs g

bb bb bb a a a a

0.766 550( ) 0.416 0.002 0.02 0.5 0.25logbp Chl Chb l

*2( )( ) trictric hoho trichobbc Cb hlb

*1( )( ) tric trh iotricho chochl a Ca

Rrs()modified

UCSBIOP

chl, aCDM, & chlTricho

Measured Chltricho [mg m-3]

Mod

ele

d C

hl tr

ich

o [

mg

m-3]

3. NEW MODEL DEVELOPMENT AND VALIDATION

How to validate model?

1. Using in situ dataset, look at prediction “success” above and below a threshold value (1.0 mg m-3). ~75% of bloom observations correctly identified while only 14% falsely identified.

2. Using CalCoFI Rrs() dataset we can test for false positive retrievals under the assumption that VERY little Trichodesmium are present. 11% (N=33 of 303) are diagnosed as containing Chltricho > 1.0 mg m-3.

3. Determine whether spatial and temporal patterns of applied model are consistent with historical observations (see next section).

5. RESULTS & CONCLUSIONS4. APPLICATION AND RESULTSAn example of a single SeaWiFS 8-day composite at 0.25 degree resolution. “bloom” = Chltricho > 1.0 mg m-3

Bloom pixels using method described here, method of Subramaniam et al. (2002) and the overlap between the two.

Map adapted from Capone et al. (1997) showing location of process-oriented studies and distribution of Trichodesmium in the subtropical oceans.

Frequency of occurrence of blooms. Shown are the number of 8-day periods (from 09/1997 – 07/2002, N=226 total) which a Tricho bloom was found to occur.