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71 results for “Chl”
BGC-Argo Satellite matchup to compute variability in the Chl:C ratio of phytoplankton.
<p>This dataset provides matchups between BGC-Argo and MODIS satellites (both atmospheric and ocean color products). This dataset allows users to compare the variability of the Chlorophyll (Chl) to Phytoplankton Carbon ratio from BGC-Argo floats depending on the light in the mixed layer and link to information obtained from satellites about cloud coverage. </p> <p>Quality control previously performed on this dataset and matchup criteria are described in the associated publication.</p> <p>Here are some of the column headers detailed for clarity:</p> <p>Columns 1-25 represent data from the BGC-Argo floats:</p> <ul> <li>ID: Float WMO ID number</li> <li>dt: Datetime in datenum format.</li> <li>biomes: Biomes according to Fay & McKinley, 2014 (with West Mediterranean biome 18 and East Mediterranean biome 19)</li> <li>zenith: Sun zenith angle at time of surfacing.</li> <li>kd_490_Xing: Downwelling diffuse attenuation coefficient at 490nm from Xing et al.,2021 method. </li> <li>kd_PAR_Xing: Downwelling diffuse attenuation coefficient of PAR from Xing et al.,2021 method. </li> <li>chla: Median chlorophyll from fluorescence in the mixed layer (corrected for Non-Photochemical Quenching following Xing et al., 2012)</li> <li>F_indiv: Calibration factor for chla (chlorophyll from fluorescence) according to the method described in Xing et al., 2011. </li> <li>F_median: Median Correction factor (F) for all the floats in a biome</li> <li>F_median_season: Median Correction factor (F) for all the floats in a biome in a given season</li> <li>Chl_cor: Chla from floats corrected using the F_median factor according to Xing et al., 2011. </li> <li>PAR_0_Argo: PAR(0-) right below the surface also from Xing et al., 2021.</li> <li>Z_iso : Depth of the 0.415 mol/quanta/m-2/d-1 isolume. </li> <li>Zeu: Euphotic depth, 1% of surface light.</li> <li>Eg_Argo: Median light level in the mixed layer during a float's profile, bounded by the surface and the MLD (in mol quanta m^-2 h^-1).</li> <li>MLD: Mixed layer depth, determined using the 0.03 density criteria from de Boyer Montégut, et al.,2004.</li> <li>bbp_XXX: Backscattering at a specific wavelength</li> <li>Cphyto: Median Phytoplankton Carbon in the mixed layer computed from Bbp following Graff et al., 2015.</li> <li>Cphyto_B: Median Phytoplankton Carbon in the mixed layer computed from Bbp following Behrenfeld et al., 2005.</li> <li>Cphyto_M: Median Phytoplankton Carbon in the mixed layer computed from Bbp following Martinez-Vincente et al., 2013.</li> <li>ratio_cor: Chl_cor /Cphyto.</li> </ul> <p>Columns 26-45 have products from matchups with ocean-color MODIS files:</p> <ul> <li>sat_dt: Datetime of satellite overpass in datenum format. </li> <li>chlor_a: Satellite chl obtained from NASA's OBPG hybrid algorithm.</li> <li>sat_IPAR: Instantaneous PAR at time of overpass.</li> <li>sat_PAR: MODIS Daily PAR product above the surface.</li> <li>sat_Daily_PARminus: MODIS Daily PAR product propagated right below the surface (0-)</li> <li>sat_Daily_Eg: Daily median light in the mixed layer computed as sat_DailyPAR_minus * exp(-Kd_PAR*MLD/2) ( in mol quanta m^-2 d^-1).</li> </ul> <p>Columns 46-49 have products from matchups with atmospheric MODIS files: </p> <ul> <li>a_lat, a_lon, a_dt: Same as above but for the atmospheric file</li> <li>Confident Cloudy: Number of pixels (Out of 25) with the Confident Cloudy flag. </li> </ul> <p> </p>
Size fractionation for total Chl a within the surface layer and calculated size distribution of total Chl a from discrete bottle samples collected during CCE LTER process cruises in the CCE region, 2006 - 2024 (ongoing).
Water for size fractionation of chlorophyll a is sampled from ~10m depth (surface layer) in the CCE study area. The size distribution of total chlorophyll a is determined by filtering water though filters of differing pore sizes. These are then extracted in acetone and analyzed fluorometrically with Turner Designs 10-AU Fluorometer on CCE Process cruises (since 2006, ongoing). Chlorophyll a and taxon-specific pigments (chlorophylls and carotenoids) are qualitatively and quantitatively characterized in the lab onshore by several size fractions (< 1µm to > 20µm) utilizing High Performance Liquid Chromatography (HPLC) analysis. The samples analyzed within the CCE region are used to develop a metric for phytoplankton community structure that can be used to monitor its state and changes thereof over time.
Station data of passive and active fluorescence measurements of chlorophyll-a (Chl), phycoerythrin (PE), chromophoric dissolved organic matter (CDOM), and variable fluorescence (Fv/Fm) from CCE-CalCOFI Augmented cruises in the California Current System, 2012 - October 2020.
Active and passive fluorescence measurements are made using the ALFA5 system (Chekalyuk and Hafez, 2013) on water from the ship’s underway system (these are not samples from bottles!) during CalCOFI cruises while on station. The instrument uses excitation at 405 and 510 nm to measures passively the fluorescence of chlorophyll-a (Chl), three different phycoerythrins (PE1, PE2 and PE3) and chromophoric dissolved organic matter (CDOM). Variable fluorescence (Fv/Fm) is measured actively using pump-during-probe (PDP) measurements of Chl a fluorescence induction. Fluorescence measurements are normalized to the water’s Raman fluorescence. ALF data are merged with CTD and bottle data that were collected by the CalCOFI group.
Continuous passive and active fluorescence measurements of chlorophyll-a (Chl), phycoerythrin (PE), chromophoric dissolved organic matter (CDOM), and variable fluorescence (Fv/Fm) from CCE-CalCOFI Augmented cruises in the California Current System, 2012 - 2020
Active and passive fluorescence measurements are made using the ALFA5 system (Chekalyuk and Hafez, 2013) on water from the ship’s underway system during CalCOFI cruises. The instrument uses excitation at 405 and 510 nm to measures passively the fluorescence of chlorophyll-a (Chl), three different phycoerythrins (PE1, PE2 and PE3) and chromophoric dissolved organic matter (CDOM). Variable fluorescence (Fv/Fm) is measured actively using pump-during-probe (PDP) measurements of Chl a fluorescence induction. Fluorescence measurements are normalized to the water’s Raman fluorescence.
Continuous passive and active fluorescence measurements of chlorophyll-a (Chl), phycoerythrin (PE), chromophoric dissolved organic matter (CDOM), and variable fluorescence (Fv/Fm) from CCE process cruises in the California Current System, 2012 - 2019 (ongoing).
Active and passive fluorescence measurements are made using the ALFA5 system (Chekalyuk and Hafez, 2013) on water from the ship’s underway system during CCE process cruises. The instrument uses excitation at 405 and 510 nm to measures passively the fluorescence of chlorophyll-a (Chl), three different phycoerythrins (PE1, PE2 and PE3) and chromophoric dissolved organic matter (CDOM). Variable fluorescence (Fv/Fm) is measured actively using pump-during-probe (PDP) measurements of Chl a fluorescence induction. Fluorescence measurements are normalized to the water’s Raman fluorescence.
e-shape P5.6 EO based phytoplankton biomass for WFD reporting - samples of Chl-a and WFD classes maps of lakes Lauwersmeer and Saadjärv
<p>The current data set is a sample of the data generated within the e-shape pilot 5.6 called "EO based phytoplankton biomass for WFD reporting" and consists of maps based on earth observation (EO) data from the Sentinel 2 satellite. There is a set of chlorophyll-a (Chl-a) maps, and a set maps of WFD ecological status of phytoplankton biomass, derived from the Chl-a maps by applying local WFD phytoplankton biomass thresholds. These maps can complement the monitoring for the Water Framework Directive (WFD).<br> The lakes within this sample set are lakes Saadjärv (Estonia) and Lauwersmeer (the Netherlands).</p> <p>For more info please see the readme files which are provided with the data files.</p>
West Antarctic Peninsula (WAP) MITgcm-REcoMv2 outputs for 1991 (T, S, DIC, TA, DIN, Chl, air-sea CO2 flux)
<p>This dataset contains the netCDF files for the year 1991 of dissolved inorganic nitrogen (DIN), dissolved inorganic carbo (DIC), total alkalinity (TA), diatom chlorophyll concentration (DiaPhyto), small phytoplankton chlorophyll (SmPhyto), air-sea CO<sub>2</sub> fluxes (CO2flx), ocean temperature (Temp) and salinity (Salt) for the MITgcm-REcoMv2 ocean circulation and biogeochemistry model implemented for the West Antarctic Peninsula. Latitude and longitude for all variables are contained in the grid.glob.nc file.</p> <p>Files names start with the variable name, followed by the month and year. They are saved either as monthly means, as 10 day means, or 5 day means.</p> <p>The units for each variable are as follows:</p> <p>DIN: mmol/m<sup>3</sup></p> <p>DIC: mmol/m<sup>3</sup></p> <p>TA: mmol/m<sup>3</sup></p> <p>DiaPhyto: mg/m<sup>3</sup></p> <p>SmPhyto: mg/m<sup>3</sup></p> <p>CO2flx: mmol/s</p> <p>Temp: ˚C</p> <p>Results from this simulation are published in:</p> <p><strong><span>SCHULTZ, C., </span></strong><span>DONEY, S.C., ZHANG, W.G., REGAN, H.C., HOLLAND, P., MEREDITH, M., STAMMERJOHN, S.</span><strong><span> </span></strong><span>Modeling of the Influence of Sea Ice Cycle and Langmuir Circulation on the Upper Ocean Mixed Layer Depth and Freshwater distribution at the West Antarctic Peninsula. Journal of Geophysics Research Oceans, 125, 8, 2020. doi:10.1029/2020JC016109</span></p> <p><strong><span>SCHULTZ, C., </span></strong><span>DONEY, S.C., HAUCK, J., KAVANAUGH, M.T., SCHOFIELD, O.</span><strong><span> </span></strong><span>Modeling Phytoplankton Blooms and Inorganic Carbon Responses to Sea-Ice Variability in the West Antarctic Peninsula. Journal of Geophysical Research Biogeosciences, 126, 4, 2021. doi: 10.1029/2020JG006227</span></p> <p> </p>
Spatial and temporal variations in nutrient and Chl a concentration in a Faroese fjord
<p>The datasett is a two-year time series of seawater nitrate, silicate, phosphorous and Chl a content in in a Faroese fjord. Weekly or biweekly sampling from April to September at four depths at two stations.</p>
Ocean Color Data: Modis-aqua_chl-a (JJA, 2002-2018)
<p>Ocean Color Data: Modis-aqua_chl-a (JJA, 2002-2018) downloaded from the ADAM Platform (https://reliance.adamplatform.eu/) used furing the FORCeS eScience course 'Tools in Climate Science: Linking Observations with Modelling'.</p> <p> </p> <p>MODIS Chlorophyll-a Concentration 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 (Rrs) 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 Rrs. 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/m3 to ensure a smooth transition.</p> <p> </p>
observed dataset and FVCOM-ERSEM modeling result of environmental factors and Chl-a concentration in CRE
<p>This data set is mainly used in the article "Formation and Breakdown of an Offshore Summer Cold-Water Zone and Its Ecological Effect on Phytoplankton". "2013-2018 data" was the dataset of obversed data in the Changjiang River Esturary (CRE) during the summer of 2013-2018. And the "cje1v_avg_2015.zip" was the result of three-dimensional physical-biogeochemical coupled model(FVCOM-ERSEM).</p>
Input data files for Dietrich et al. Chl-a and nutrient random forest modeling
<p>Input data for the models originally from:</p> <p>EPA, U. S. <em>WSIO Indicator Data Library</em>, <<a href="https://www.epa.gov/wsio/wsio-indicator-data-library">https://www.epa.gov/wsio/wsio-indicator-data-library</a>> (2023).</p> <p>Platt, L. R., Spaulding, S.A., Covert, A., Murphy, J.C., and Raynor, N. A national harmonized dataset of discrete chlorophyll from lakes and streams (2005-2022). (2023). <a href="https://doi.orghttps">https://doi.org:https://doi.org/10.5066/P9J0ZIOF</a></p> <p>Saad, D. A., Argue, D.M., Schwarz, G.E., Anning, D.W., Ator, S.W., Hoos, A.B., Preston, S.D., Robertson, D.M., and Wise, D.R., 2019. Water-quality and streamflow datasets used for estimating long-term mean daily streamflow and annual loads to be considered for use in regional streamflow, nutrient and sediment SPARROW models, United States, 1999-2014. (2019). <a href="https://doi.orghttps">https://doi.org:https://doi.org/10.5066/F7DN436B</a></p> <p> </p>
Figure An3. Distribution of pCO2 (a), Chl-a (b), and Pheo (c). in Phytoplankton assemblages under hydrochemical conditions of the Volga River Delta
Figure An3. Distribution of pCO2 (a), Chl-a (b), and Pheo (c).
A Study of Nivolumab Plus Brentuximab Vedotin in Patients Between 5 and 30 Years Old, With Hodgkin's Lymphoma (cHL), Relapsed or Refractory From First Line Treatment
ClinicalTrials.gov study NCT02927769. IPD Sharing: Not stated. Countries: 11. Publications: 2.
Brentuximab Vedotin for Newly Diagnosed CHL in Chinese CAYA Based on PET/CT Assessment
ClinicalTrials.gov study NCT06563245. IPD Sharing: YES. Countries: 1. Publications: 10.
To Compare the Efficacy and Safety of Clindamycin Phosphate 1.2% / Benzoyl Peroxide 5% Gel of CHL Versus DUAC® Gel
ClinicalTrials.gov study NCT02005666. IPD Sharing: Not stated. Countries: 2. Publications: 2.
Extr_chl_a_MesoSCOPE_KM1709
<p>Extracted chlorophyll a from in situ samples collected from MesoSCOPE cruise KM1709 in the North Pacific Subtropical Gyre.</p>
Fig. 5. Chl-a in Halocarbon emissions by selected tropical seaweeds exposed to different temperatures
Fig. 5. Chl-a (μg g 1), carotenoid (μg g 1) contents and the Chl-a: carotenoid ratios (average ± standard deviation; n = 12) of the four seaweeds, G. manilaensis (GM), U. reticulata (UR), K. alvarezii (KA) and T. conoides (TC), measured after a 28 h exposure to temperatures of 40, 35, 30, 25 and 20 ◦ C. Data were analysed using a oneway ANOVA. a,b,c, indicate homogeneous groups across temperature based on Tukey's post hoc test (p <0.05).
Family-centered Obesity Prevention: Communities for Healthy Living (CHL)
ClinicalTrials.gov study NCT03334669. IPD Sharing: NO. Countries: 1. Publications: 12.
Ipilimumab With or Without Nivolumab in Relapsed/Refractory cHL
ClinicalTrials.gov study NCT04938232. IPD Sharing: YES. Countries: 1. Publications: 0.
Size fractionation for total Chl a within the surface layer and calculated size distribution of total Chl a from discrete bottle samples from CCE-CalCOFI Augmented Cruises in the California Current System, 2004 - 2017 (ongoing).
Water for size fractionation of chlorophyll a is sampled from ~10m depth (surface layer) on Line 83 and 87, with scattered inshore stations within the CalCOFI and SCCOOS stations located in the CCE study area. The size distribution of total chlorophyll a is determined by filtering water though filters of differing pore sizes. These are then extracted in acetone and analyzed fluorometrically with Turner Designs 10-AU Fluorometer on CalCOFI cruises (since 2006, ongoing). Chlorophyll a and taxon-specific pigments (chlorophylls and carotenoids) are qualitatively and quantitatively characterized in the lab onshore by several size fractions (< 1µm to > 20µm) utilizing High Performance Liquid Chromatography (HPLC) analysis. The samples analyzed within the CCE region are used to develop a metric for phytoplankton community structure that can be used to monitor its state and changes thereof over time.
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