Editing SeaWiFS (section)

==Chlorophyll estimation==
[[Image:AYool SEAWIFS annual.png|thumb|SeaWIFS-derived average sea surface [[chlorophyll]] for the period 1998 to 2006.]]
Chlorophyll concentrations are derived from images of the ocean's color. Generally speaking, the greener the water, the more phytoplankton are present in the water, and the higher the chlorophyll concentrations. {{not a typo|Chlorophyll a}} absorbs more blue and red light than green, with the resulting reflected light changing from blue to green as the amount of chlorophyll in the water increases.  Using this knowledge, scientists were able to use ratios of different reflected colors to estimate chlorophyll concentrations. 
 
[[File:Voyager - Filters - Clear.png|thumbnail|The visible color spectrum with corresponding wavelengths in nanometers]]
Many formulas estimate chlorophyll by comparing the ratio of blue to green light and relating those ratios to known chlorophyll concentrations from the same times and locations as the satellite observations. The [[color]] of light is defined by its wavelength, and visible light has wavelengths from 400 to 700 nanometers, progressing from violet (400&nbsp;nm) to red (700&nbsp;nm). A typical formula used for SeaWiFS data (termed OC4v4) divides the reflectance of the maximum of several wavelengths (443, 490, or 510&nbsp;nm) by the reflectance at 550&nbsp;nm. This roughly equates to a ratio of blue light to green light for two of the numerator wavelengths, and a ratio of two different green wavelengths for the other possible combination.

The reflectance (R) returned by this formula is then plugged into a cubic polynomial that relates the band ratio to chlorophyll.<ref name="O'Reilly">{{cite journal|last=O'Reilly|first=John E.|author2=Maritorena, Stéphane |author3=Mitchell, B. Greg |author4=Siegel, David A. |author5=Carder, Kendall L. |author6=Garver, Sara A. |author7=Kahru, Mati |author8= McClain, Charles |title=Ocean color chlorophyll algorithms for SeaWiFS|journal=Journal of Geophysical Research|date=1 January 1998|volume=103|issue=C11|pages=24937–24953|doi=10.1029/98JC02160|bibcode = 1998JGR...10324937O |url=https://scholarcommons.usf.edu/msc_facpub/6|doi-access=free|url-access=subscription}}</ref>

<math> Chl = antilog(0.366-3.067\mathsf{R}+1.93\mathsf{R}^2 +0.64\mathsf{R}^3 -1.53\mathsf{R}^4)  </math><ref name=BioObook>{{cite book|last=Wheeler|first=Charles B. Miller, Patricia A.|title=Biological oceanography|publisher=[[Wiley-Blackwell]]|location=Chichester|isbn=978-1-4443-3302-2|edition=2nd|author2=Patricia A. Wheeler |date=2012-05-21}}</ref>

This formula, along with others, was derived empirically using observed chlorophyll concentrations. To facilitate these comparisons, NASA maintains a system of oceanographic and atmospheric data called [[SeaBASS (data archive)|SeaBASS]] (SeaWiFS Bio-optical Archive and Storage System). This data archive is used to develop new algorithms and validate satellite data products by matching chlorophyll concentrations measured directly with those estimated remotely from a satellite. These data can also be used to assess atmospheric correction (discussed below) that also can greatly influence chlorophyll concentration calculations.

Numerous chlorophyll algorithms were tested to see which ones best matched chlorophyll globally. Various algorithms perform differently in different environments. Many algorithms estimate chlorophyll concentrations more accurately in deep clear water than in shallow water. In shallow waters reflectance from other pigments, detritus, and the ocean bottom may cause inaccuracies.  The stated goals of the SeaWiFS chlorophyll estimates are "… to produce water leaving radiances with an uncertainty of 5% in clear-water regions and {{not a typo|chlorophyll a}} concentrations within ±35% over the range of 0.05–50 mg m-3.".<ref name=HookerMcClain /> When accuracy is assessed on a global scale, and all observations are grouped together, then this goal is clearly met.<ref name=BailyWerdell>{{cite journal|last=Bailey|first=Sean W.|author2=Werdell, P. Jeremy |title=A multi-sensor approach for the on-orbit validation of ocean color satellite data products|journal=Remote Sensing of Environment|date=1 May 2006|volume=102|issue=1–2|pages=12–23|doi=10.1016/j.rse.2006.01.015|bibcode=2006RSEnv.102...12B}}</ref> Many satellite estimates range from one-third to three times of those directly recorded at sea, though the overall relationship is still quite good.<ref name=BioObook /> Differences arise when examined by region, though overall the values are still very useful. One pixel may not be particularly accurate, though when averages are taken over larger areas, the values average out and provide a useful and accurate view of the larger patterns.  The benefits of chlorophyll data from satellites far outweigh any flaws in their accuracy simply by the spatial and temporal coverage possible. Ship-based measurements of chlorophyll cannot come close to the frequency and spatial coverage provided by satellite data.