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See Platform deployments for cruise specific documentation<\/p><\/div>","@type":"rdf:HTML"}],"http:\/\/ocean-data.org\/schema\/hasBriefDescription":[{"@value":"CTD profile data, including beam attenuation","@language":"en-US"}],"http:\/\/purl.org\/dc\/terms\/description":[{"@value":"
CTD profile data averaged at two decibar intervals, including beam attenuation<\/p><\/div>","@type":"rdf:HTML"}],"http:\/\/www.w3.org\/2000\/01\/rdf-schema#label":[{"@value":"CTD","@type":"xsd:string"}],"http:\/\/ocean-data.org\/schema\/hasProcessingDescription":[{"@value":"
Beam Attenuation Coefficient, Light Scattering, Fluorescence protocols<\/p>\n
\u00a0<\/p>\n
\u00a0<\/p>\n
\nData Reduction Scheme<\/strong>\n\n\tThe primary purpose for measuring the beam attenuation\nin JGOFS programs is to determine the concentration and distribution of\nparticulate matter (PM) or particulate organic carbon (POC) in the\nwater with continuous profiling rather than with limited discrete\nsamples. Towards this end, a 25 cm Sea Tech Transmissometer was\ninterfaced with the University of Washington's SeaBird CTD for all\nArabian Sea cruises. Transmissometer data were analyzed for the five\nprocess cruises (TN043, TN045, TN049, TN050 and TN054) that occupied a\nstandard set of stations. Data from the raw CTD files were binned at 2\ndb intervals through SeaBird's SEASOFT program, which has a spike\nremoval subroutine which we have tested and found to remove\ntransmissometer data spikes properly. The data were corrected for\nfactory and field air calibrations. Beam transmission was converted to\nbeam attenuation coefficients using c=-(1\/r)*ln(%Tr\/100) where c=beam\nattenuation coefficient (m^-1), r=beam path length (m), and Tr=% beam\ntransmission.\n\nThe Arabian Sea data set presented some challenges because 1-4\ndifferent transmissometers were used on any given cruise, complicating\nthe data calibration. It is impractical to do a proper bench or air\ncalibration prior for each CTD cast since the deck of the ship is not\nalways a clean environment and atmospheric conditions can change\nrapidly and affect the air readings. One calibration method is to\ncompare the beam attenuation at depth where the particle concentration\nis relatively invariant. The primary concern is ensuring that the\noptical windows are uniformly clean, which is best determined by\ncomparing adjacent profiles. Unfortunately, many of the CTD casts\nextended only to 150 m or less, which was usually shallower than the\nparticle minimum. Furthermore, the stations covered a wide geographic\narea, so it is more likely that the particle minimum at depth could\nvary. The primary method for comparing the beam attenuation signal to\nparticulate matter (PM) concentration or particulate organic carbon\n(POC) concentration is to filter water samples and determine the dry\nweight using stable filters (0.4 um pore size Poretics filters in this\ncase), or the amount of organic carbon on a glass fiber filter (0.7 um\nnominal pore size). The beam c data for those bottle depths (chosen as\nthe cp value of the 2 db bin within which the sample depth fell) are\nthen regressed against PM or POC using a Model II regression to\ndetermine the intercept where the concentration of particles in the\nwater equals zero. Theoretically this value should be 0.364 since the\ntransmissometers are set at the factory to read 0.364 in particle-free\nwater. PM was filtered on four of the five cruises where beam c was\nanalyzed. POC was measured on the one cruise for which no PM\nmeasurements were made (TN049) as well as most of the other cruises.\n\nIn order to determine the attenuation specific to particulate matter,\nthe attenuation due to water must be subtracted from the beam c values\n( cp = c - cw). Practically, cw is determined as the minimum\nattenuation measured during each cruise. It must be noted that this\nminimum attenuation value is the \"cleanest\" water observed and is not\nparticle free. Thus, the regressions of the cp data versus particle\nconcentrations must be adjusted.\n\n A prediction of the PM concentration can be obtained from the\nresulting equations for each cruise:\n\n TN043 -> PM = 602 * cp (r^2 = 0.86)\n TN045 -> PM = 483 * cp (r^2 = 0.87)\n TN050 -> PM = 687 * cp (r^2 = 0.92)\n TN054 -> PM = 615 * cp (r^2 = 0.86)\n\nPM is in ug\/Kg, and cp is attenuation per meter.\n\nNote that these are Model II regressions so the equations are the same\nif PM is regressed versus cp or vice versa. For comparison,\nthe relationships between particle concentration and attenuation in\nsurface waters of previous JGOFS programs were:\n\n PM = 1022*cp \tNorth Atlantic Bloom Exp.\n PM = 451*cp \tEqPac Spring Time Series\n PM = 647*cp \tEqPac Fall Time Series\n\n\n\nChlorophyll<\/strong>\n\n\tChlorophyll-a fluorescence distribution in the Arabian Sea was\ndetermined, in-situ, with a SeaTech Fluorometer. The fluorometer was\ninterfaced with the Sea-Bird CTD, and the data were acquired in the\nsame format as the transmissometer data. The Fluorometer is a standard\nirradiation\/emission system. When chlorophyll a is excited by blue\nlight (425 nm), it will fluoresce at a peak wavelength of 685 nm (red\nlight). The emission detector is filtered to a peak response in order\nto make the measurement insensitive to the excitation source. The\namount of fluoresced light detected is converted to a voltage range of\n0 to 5 volts. A signal gain of 10x was used, setting sensitivity to\n3mg chl-a m^-3. The fluorometer is set to sample with a three second time\nconstant to smooth the data. A baffle has been placed in front of the\nemission detector in an attempt to make it insensitive to ambient light\n(SeaTech Fluorometer Manual). The SEASOFT software converts the\nmeasured voltage into a relative chlorophyll-a value using the\nequation:\n\n\t\t[volts * signal gain\/5] + offset = mg chl-a m^-3\n\n\tThese relative values were calibrated using discreet\nchlorophyll samples (taken by various JGOFS scientists and analyzed\nonboard the ship using a Turner Fluorometer). There is a good (r^2 =\n0.90) linear correlation between fluorometer-determined chlorophyll-a\nfluorescence, and the chlorophyll-a concentrations determined using a\nTurner fluorometer. Regressions were made for each cruise individually,\nbut the correlations (based on the standard deviation of the slope and\nintercept) were improved when data from cruises TN049, TN050, and TN054\nwere combined. Prior to TN049, chlorophyll samples were taken from the\nTrace-Metal rosette, which contained no CTD or fluorometer for accurate\ndepth or fluorescence measurements. We attempted a comparison between\nstandard CTD\/fluorometer profiles made close in time to the Trace-Metal\ncasts on which chlorophyll measurements were made, but the lack of\naccurate depths or water density for the discreet samples plus the\ntemporal variability between casts introduced too much scatter for a\nuseful correlation. There were too few chlorophyll a measurements made\non the standard CTD casts during TN043 and TN045 to independently\ncalibrate the fluorometer. This added to the appeal of a general\ncalibration for the fluorescence signal for all cruises, though we\nrecognize that data for two cruises were not included. We emphasize\nfor future work that it is necessary to have a fluorometer and CTD on\nthe rosette at the time chlorophyll samples are being taken in order to\naccurately calibrate the fluorescence signal. Furthermore continuous\nprofiles from a fluorometer provide higher resolution than discreet\nsamples alone.\n\n\t Slightly different slopes and intercepts were observed in the\nfluorescence\/chlorophyll correlations for samples above and below the\nchlorophyll maximum. Therefore the depth of the chlorophyll maximum was\ndetermined by visual inspection of each profile (to avoid confusion\nwith individual spikes) and the samples were divided into two\ncategories, separated at a depth 10 m beneath the maximum fluorescence\nvalue. The assumption (substantiated by inspection of the data) is that\nchlorophyll-containing particles within the subsurface chlorophyll\nmaximum are more similar to those above the maximum than below. A model\nII linear regression on each group of data indicated a very slight\ndifference in slopes between the two groups, but a substantial offset\nin the intercepts. This results in a difference in the concentration of\npredicted chlorophyll based on the fluorescence above and below the\nchlorophyll maximum. Similar differences in chlorophyll fluorescence\nabove and below the chlorophyll maximum were noticed by Pak et\nal.(1988). Equations are provided here for both regions in the Arabian Sea.\n\n \tAbove the depth of the chlorophyll maximum:\n\t\tChl a = 0.357*Fl + 0.078 (r^2 = 0.86)\n\n\tBelow the depth of the chlorophyll maximum:\n Chl a = 0.389*Fl - 0.05 (r^2 = 0.93)\n\nLSS - SeaTech Light Scattering Sensor<\/strong>\n\n\tLight scattering due to particles was monitored using a SeaTech\nLight Scattering Sensor (LSS). The LSS projects light from two 880 nm\n(infrared) LEDs into a sampling volume that varies depending upon the\nconcentration of particulate matter, but that is roughly the shape of a\nstretched balloon. Back-scattered light from the particulate matter is\nmeasured by a detector. The range on the LSS was set to 0 - 33 mg\/l.\nThe amount of light detected is scaled to a 0-5 volt output, but in the\nArabian Sea most values were less than 0.5 volts. The LSS output\ndepends upon the nature of the particulate matter and will vary with\nchanges in particle size distribution, shape, index of refraction,\norganic\/inorganic content etc. Therefore the LSS requires site-specific\ncalibration. The LSS was interfaced with the SeaBird CTD and the data\nwere handled in the same format as the transmissometer and fluorometer\ndata.\n<\/pre><\/div>","@type":"rdf:HTML"}],"http:\/\/purl.org\/dc\/terms\/identifier":[{"@value":"2516","@type":"xsd:int"}],"http:\/\/purl.org\/dc\/terms\/title":[{"@value":"CTD"}],"http:\/\/purl.org\/dc\/terms\/date":[{"@value":"2009-10-01T10:17:39-04:00","@type":"xsd:dateTime"}],"http:\/\/purl.org\/dc\/terms\/created":[{"@value":"2009-10-01T10:17:39-04:00","@type":"xsd:dateTime"}],"http:\/\/purl.org\/dc\/terms\/modified":[{"@value":"2020-03-29T20:57:08-04:00","@type":"xsd:dateTime"}],"http:\/\/rdfs.org\/ns\/void#inDataset":[{"@id":"http:\/\/www.bco-dmo.org\/"}],"http:\/\/ocean-data.org\/schema\/namedGraph":[{"@value":"urn:bcodmo:dataset:2516","@type":"xsd:token"}],"http:\/\/ocean-data.org\/schema\/osprey_page":[{"@id":"https:\/\/www.bco-dmo.org\/dataset\/2516"}],"http:\/\/ocean-data.org\/schema\/identifier":[{"@value":"_:Identifier2516"}],"http:\/\/ocean-data.org\/schema\/datasetTitle":[{"@value":"CTD profile data, including beam attenuation from R\/V Thomas G. Thompson TT039, TT043, TT045, TT049, TT050, TT053, TT054 cruises in the Arabian Sea (U.S. JGOFS Arabian Sea project)","@language":"en-US"}],"http:\/\/ocean-data.org\/schema\/abstract":[{"@value":"","@language":"en-US"}],"http:\/\/purl.org\/dc\/terms\/rights":[{"@id":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"http:\/\/ocean-data.org\/schema\/deprecated":[{"@value":"false","@type":"xsd:boolean"}],"http:\/\/purl.org\/dc\/terms\/bibliographicCitation":[{"@value":"Morrison, J. M., Codispoti, L. A. (2002) CTD profile data, including beam attenuation from R\/V Thomas G. Thompson TT039, TT043, TT045, TT049, TT050, TT053, TT054 cruises in the Arabian Sea (U.S. JGOFS Arabian Sea project). Biological and Chemical Oceanography Data Management Office (BCO-DMO). 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