Chlorophyll a (chlor_a)

Table of Contents

  1. Product Summary
  2. Algorithm Description
  3. Implementation
  4. Assessment
  5. References
  6. Data Access

1 - Product Summary

This algorithm returns the near-surface concentration of chlorophyll-a (chlor_a) in mg m-3, calculated using an empirical relationship derived from in situ measurements of chlor_a and remote sensing reflectances ($R_{rs}$) in the blue-to-green region of the visible spectrum. The implementation is contingent on the availability three or more sensor bands spanning the 440 - 670 nm spectral regime. The algorithm is applicable to all current ocean color sensors. The chlor_a product is included as part of the standard Level-2 OC product suite and the Level-3 CHL product suite.

The current implementation for the default chlorophyll algorithm (chlor_a) employs the standard OC3/OC4 (OCx) band ratio algorithm merged with the color index (CI) of Hu et al. (2012). As described in that paper, this refinement is restricted to relatively clear water, and the general impact is to reduce artifacts and biases in clear-water chlorophyll retrievals due to residual glint, stray light, atmospheric correction errors, and white or spectrally-linear bias errors in $R_{rs}$. As implemented, the algorithm diverges slightly from what was published in Hu et al. (2012) in that the transition between CI and OCx now occurs at 0.15 < CI < 0.2 mg/m$^3$ to ensure a smooth transition.

Global chlorophyll map from MODIS Aqua chlorophyll colorbar
MODIS Aqua chlor_a seasonal composite for Spring 2014

Algorithm Point of Contact: P. Jeremy Werdell, NASA Goddard Space Flight Center

2 - Algorithm Description


$R_{rs}$ at 2-4 wavelengths between 440 and 670nm


chlor_a, concentration of chlorophyll a in mg/m-3


The chlor_a product combines two algorithms, the O'Reilly band ratio OCx (e.g. chl_oc4) algorithm and the Hu color index (CI) algorithm (chl_hu).

The CI algorithm is a three-band reflectance difference algorithm employing the difference between $R_{rs}$ in the green band and a reference formed linearly between $R_{rs}$ in the blue and red bands.
$$CI = R_{rs}(\lambda_{green}) - [R_{rs}(\lambda_{blue}) + (\lambda_{green}-\lambda_{blue)}/(\lambda_{red}-\lambda_{blue}) * (R_{rs}(\lambda_{red})-R_{rs}(\lambda_{blue}))]$$
where $\lambda_{blue}$, $\lambda_{green}$ and $\lambda_{red}$ are the instrument-specific wavelengths closest to 443, 555 and 670nm respectively.

The OCx algorithm is a fourth-order polynomial relationship between a ratio of $R_{rs}$ and chlor_a.

$$log_{10}(chlor\_a) = a_0 + \sum\limits_{i=1}^4 a_i \left(log_{10}\left(\frac{R_{rs}(\lambda_{blue})}{R_{rs}(\lambda_{green})}\right)\right)^i$$

where the numerator, $R_{rs}(\lambda_{blue})$, is the greatest of several input $R_{rs}$ values and the coefficients, a0-a4, are sensor-specific:

  sensor default * blue green a0 a1 a2 a3 a4
OC4 SeaWiFS Y 443>490>510 555 0.3272 -2.9940 2.7218 -1.2259 -0.5683
OC4E MERIS Y 443>490>510 560 0.3255 -2.7677 2.4409 -1.1288 -0.4990
OC4O OCTS Y 443>490>516 565 0.3325 -2.8278 3.0939 -2.0917 -0.0257
OC3S SeaWiFS N 443>490 555 0.2515 -2.3798 1.5823 -0.6372 -0.5692
OC3M MODIS Y 443>488 547 0.2424 -2.7423 1.8017 0.0015 -1.2280
OC3V VIIRS Y 443>486 550 0.2228 -2.4683 1.5867 -0.4275 -0.7768
OC3E MERIS N 443>490 560 0.2521 -2.2146 1.5193 -0.7702 -0.4291
OC3O OCTS N 443>490 565 0.2399 -2.0825 1.6126 -1.0848 -0.2083
OC3C CZCS Y 443>520 550 0.3330 -4.3770 7.6267 -7.1457 1.6673
OC2S SeaWiFS N 490 555 0.2511 -2.0853 1.5035 -3.1747 0.3383
OC2E MERIS N 490 560 0.2389 -1.9369 1.7627 -3.0777 -0.1054
OC2O OCTS N 490 565 0.2236 -1.8296 1.9094 -2.9481 -0.1718
OC2M MODIS N 488 547 0.2500 -2.4752 1.4061 -2.8233 0.5405
OC2M-HI MODIS (500-m) Y 469 555 0.1464 -1.7953 0.9718 -0.8319 -0.8073
OC2 OLI/Landsat 8 482 561 0.1977 -1.8117 1.9743 -2.5635 -0.7218
OC3 OLI/Landsat 8 443>482 561 0.2412 -2.0546 1.1776 -0.5538 -0.4570

* Y indicates operational / default algorithm for each sensor within OBPG processing

The coefficients were derived using version 2 of the NASA bio-Optical Marine Algorithm Data set (NOMAD).

For chlorophyll retrievals below 0.15 mg m-3, the CI algorithm is used.
For chlorophyll retrievals above 0.2 mg m-3, the OCx algorithm is used.
In between these values, the CI and OCx algorithm are blended using a weighted approach.

3 - Implementation

Product Short Namechlor_a
Level-2 Product SuiteOC
Level-3 Product SuiteCHL

For further details on the implementation, go to the algorithm source code or the graphical description of the algorithm implementation in the NASA ocean color processing code (l2gen).

Calling in L2GEN
  • l2prod = chlor_a (refers to sensor-specific default CI/OCx blended algorithm)
  • l2prod = chl_oc4, chl_oc3, chl_oc2, chl_hu
  • each satellite will use its sensor-specific coefficients and wavelengths (e.g., SeaWiFS defaults to OC4, OC3S, OC2S)
  • to override the coefficients:
    • chloc4_coef = [a0,a1,a2,a3,a4]
    • chloc3_coef = [a0,a1,a2,a3,a4]
    • chloc2_coef = [a0,a1,a2,a3,a4]
  • to override the wavelengths:
    • chloc4_wave = [array of 4 wavelengths, last will be denominator]
    • chloc3_wave = [array of 3 wavelengths, last will be denominator]
    • chloc2_wave = [numerator wavelength, denominator wavelength]

4 - Assessment

Level-2 satellite-to-in-situ match-up validation results are available for each sensor from the validation tool of the SeaWiFS Bio-Optical Archive and Storage System (SeaBASS). Links to those match-ups are provided below.

Algorithm Development:
Algorithm Verification: internal consistency between operational algorithms
Algorithm Verification: comparison with previous versions

OC4 v4 and v5 correspond with SeaWiFS Reprocessings 3 (2000) and a preliminary NOMAD version, respectively.

Algorithm Verification: comparison with (Morel and Maritorena 2001)

5 - References

Hu, C., Lee, Z., & Franz, B. (2012). Chlorophyll a algorithms for oligotrophic oceans: A novel approach based on three-band reflectance difference . Journal of Geophysical Research, 117(C1). doi: 10.1029/2011jc007395

Morel, A., & Maritorena, S. (2001). Bio-optical properties of oceanic waters: A reappraisal. Journal of Geophysical Research: Oceans, 106(C4), 7163-7180. doi: 10.1029/2000jc000319

O'Reilly, J.E., Maritorena, S.,Mitchell, B. G., Siegel, D. A., Carder, K. L., Garver, S. A., Kahru, M., & McClain, C. R. (1998). Ocean color chlorophyll algorithms for SeaWiFS, Journal of Geophysical Research 103, 24937-24953, doi: 10.1029/98JC02160.

O'Reilly, J.E., & 24 co-authors (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.

Werdell, P. J., & Bailey, S. W. (2005). An improved bio-optical data set for ocean color algorithm development and satellite data product validation. Remote Sensing of Environment 98, 122-140, doi: 10.1016/j.rse.2005.07.001.

6 - Data Access