Estimating Primary Productivity in Central California Using SeaWiFS LT Rachael Spollen OC 3570 Winter 2002

Background and Data Collection Importance of Chlorophyll- a measurements - Carbon Sink Measurements: *Fluorimeter - how it works - inaccuracies *Direct Chlorophyll-a *Primary Productivity - how it’s measured - more accurate representation *SeaWiFS -algorithms remove path radiance -5-10% reflectance from ocean 1. Chlorophyll importance as a Carbon Sink: Terrestrial known to be sink, extent of aquatic plant life as a sink being further studied. Believe phytoplankton to be another major sink. - Contain chlorophyll-a, known to absorb blue and red wavelengths and reflect green. Remote sensing of ocean color believed to be a global method to interpret contribution to carbon uptake. Three techniques were used to estimate chl-a concentrations in-situ: Fluorimeter How it works – emits light at 430nm wavelength, exciting chl-a molecules, which then emit light back to the fluorimeter at 685nm. 2. Should be representative of the amount of phytoplankton in the water column, but not accurate when the phytoplankton is photosynthesizing – will not react to the fluorimeter. Readings taken directly from the raw CTD data. Algorithm applied w/n the SeaBird software has been found to be misleading, therefor raw voltage is used instead. 3. Chlorophyll Measurements Measured directly using the holm- hansen technique. Used as a benchmark for comparison 4. Primary Productivity A measurement of the amount of 14C uptake occurring in the water column – directly representative of the amount of phytoplankton present in the euphotic zone. Euphotic Zone determined using Secchi depth measurements and samples collected at 100,50,30,15,5,1,.1% light penetration Radioactive 14C is used to measure carbon uptake to distinguish between Carbon already present and that which is introduced for measurements. 5. SeaWiFS Can view entire globe w.n a 48-hr period Operates in 6 vis channels and 2 NIR channels derive ocean properties, path radiance must have a small and removeable contribution. 3 sources of radiance are scatter by clouds ( non-removeable, scatter by molecules (Rayleigh scatter), and scatter by aerosols(red and NIR channels). Algorithms applied to path radiance an are extremely important since only 5-10% of the light seen at the satellite is reflected from w.n the ocean.

Frontal Features A strong frontal gradient was present during the cruise as seen in the salinity and fluorimetercontour plots. This frontal feature corresponds to an offshore jet that was present during the cruise. Note the high chl-a concentrations at the edge of the front. Thisis where convergence takes place and the flow of higher chl-a concentrated water meets up w/ the low concentration water, forming a “wall” of sorts. Frontal location was approximately 123.5 deg W.

In Situ Data Fluorimeter Vs. Chlorophyll-a Correlation Coefficient Slope of the Linear Regression APR 2000 .91874 .99032 SEP 2000 .93434 2.64361 JAN 2002 .84927 1.28369 April data represents the spring and summer upwelling seasons, Sep represents the Oceanic season, while the January data represents the Davidson current period. Represents the weaknesses in fluorimeter representation of chl-a concentration. Collectively, chl-a concentrations tend to be on the order of twice the fluorimeter voltage output

In Situ Data A definite correlation is seen for the January data, with two noticeable outlying clusters. Clusters correspond those points I the euphotic zone located prior to the frontal boundary and the cluster below corresponds to those stations located past the frontal boundary Supports the statement made earlier that chl-a molecules engaged inphotosynthesis are less likely to fluoresce in response to the fluorimeter than those not engaged in photosynthesis because the data from below the euphotic zone correlates closely.

In Situ Data Graphical representation of the euphotic zone along Calcofi line 67. Compared to the previous slide the cluster above the regression curve represents the shallower euphotic zone and higher chl-a concentrations while the cluster below represents lower chl-a concentrations in a deeper euphotic zone

In Situ Data Apparent form this chart that there is a higher correlation of direct chlorophyll masurements to primary productivity measurements than to the fluorimeter readings. This is expected since the CHl-a and PP measurements are based on direct readings as opposed to fluorimeter measurements. Fluorimeter measures chl-a through a differents process than that which occurs in photosynthesis.

In Situ Data Primary Productivity Correlation Coefficients: Carbon Uptake vs Chlorophyll-a Carbon Uptake vs. Fluorimeter Output APR 2000 .95961 .64701 SEP 2000 .95192 .93956 JAN 2002 .93632 .12937 A lower correlation is expected since the fluorimeter measures chlorophyll-a through a different process than that which occurs in photosynthesis

SeaWiFS Imagery February 4, 2002 Offshore plume Note offshore plume. A weather system passed through prior to this imagery resulting in the plume being sheared apart

In Situ Data SeaWiFS Correlation Coefficient SeaWiFS vs Chlorophyll-a SeaWiFS vs. Fluorimeter Output SeaWiFS vs. Carbon Uptake APR 2000 .87647 .60769 .95008 SEP 2000 .99511 .94317 .97214 JAN 2002 .63271 .69434 .77903 SeaWiFS correlation coefficients are very poor in comparison to APR and SEP, partly due to the imagery analyzed. Only one days worth of imagery was available where a monthly composite was used previously. Trends of chl-a overestimation are supported I the measurements over the first half of the line, values are slightly underestimated outside 100km. Contrast other paper where oversestimation is most pronounced 100-200km offshore. SeaWiFS coastal measurements are known to be inaccurate in waters off central california du to the factr that processing algorithms are based on calibrations from a marine buoy off Hawaii.

Data Analysis Data supports a correlation btwn remotely sensed chl-a and in-situ chl-a and primary productivity measurements, although not as strong as APR and SEP. Spatial and temporal distributions of chl-a may be identified, but quantitative/exact measurements are not accurate enough to be made on a global scale. Can’t really compare correlations w/ the varying season – need an exhaustive time series plot and complete set of SeaWiFS imagery to make any preliminary determinations. Inherent errors occur as data is taken over a period of days and stations are not sampled concurrently. Could be errors due to diurnal fluctuations that haven’t been considered.

Conclusions Interesting Research Can’t compare relations w/ season conclusively. Inherent errors occur due to data collection methods Diurnal fluctuations not considered Interesting Research UCSB Study on the role of wind on reflected sky radiance *clear-sky/ wind<5m/s, water-leaving radiance undercorrected by nearly 60%