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Dataset

 
Quantifying and Understanding the Earth System (QUEST) Logo

MarQUEST: Phytoplankton Size Class (Micro, Nano, Pico) for 1998-2007 estimated from SeaWiFS/SeaStar Level 3 products

Update Frequency: Not Planned
Status: Completed
Online Status: ONLINE
Publication State: Published
Publication Date: 2014-09-21
Download Stats: last 12 months

Abstract

MarQUEST was led by Prof Andrew Watson (UEA), with 15 co-investigators at UEA/BAS, the Universities of Southampton, Essex, and Reading, and from the Plymouth Marine Laboratory and Proudman Oceanographic Laboratory.

This dataset contains climatology and monthly measurements of phytoplankton Size Class from the SeaWiFS/SeaStar products.

QUEST scientists cooperated in comparing various models, and examining more fundamental (physiological) approaches to understanding the planktonic ecoystem. MarQUEST also developed a module to simulate coastal ecosystems, usable in global ocean biogeochemical simulations. Finally, the project team generated an accurate physical simulation of the North Atlantic guided by data assimilation, into which ecosystem simulations can be embedded. This allows the variation in air-sea fluxes of gases (CO2, oxygen and dimethyl sulphide) from ocean to atmosphere to be quantified for the contemporary period.

This data was produced by Takafumi Hirata, Plymouth Marine Laboratory, Plymouth, UK as part of NERC Programmes: Centre for the observation of Air-Sea Interaction and fluXes (CASIX), National Centre for Earth Observation (NCEO) and Quantifying and Understanding the Earth System (QUEST).

Citable as:  Hirata, T.; Smyth, T. (2014): MarQUEST: Phytoplankton Size Class (Micro, Nano, Pico) for 1998-2007 estimated from SeaWiFS/SeaStar Level 3 products. NCAS British Atmospheric Data Centre, date of citation. https://catalogue.ceda.ac.uk/uuid/02f6ef21247f465fe14b5cb5246c255c
Abbreviation: Not defined
Keywords: QUEST, MarQUEST, CASIX, Marine, ocean, biogeochemistry, model

Details

Previous Info:
No news update for this record
Previously used record identifiers:
http://badc.nerc.ac.uk/view/badc.nerc.ac.uk__ATOM__ACTIVITY_53cd857e-41d1-11e4-9517-00163e251233
Access rules:
Access to these data is available to any registered CEDA user. Please Login or Register for an account to gain access.
Use of these data is covered by the following licence: http://licences.ceda.ac.uk/image/data_access_condition/quest.pdf. When using these data you must cite them correctly using the citation given on the CEDA Data Catalogue record.
Data lineage:

OCCAM model data provided by Bablu Sinha at NOC. Plankton data from PML.

Data Quality:
Not known.
File Format:
Data are netCDF formatted

Process overview

This dataset was generated by the computation detailed below.
Title Global Phytoplankton Size Class (PSC) Monthly (Composites) Climatology from Plymouth Marine Laboratory using SeaWiFS satellite
Abstract A three-component model was developed which calculates the fractional contributions of three phytoplankton size classes (micro-, nano- and picoplankton) to the overall chlorophyll-a concentration in the Atlantic Ocean. The model is an extension of the Sathyendranath et al. (2001) approach, based on the assumption that small cells dominate at low chlorophyll-a concentrations and large cells at high chlorophyll-a concentrations. Diagnostic pigments were used to infer cell size using an established technique adapted to account for small picoeukaroytes in ultra-oligotrophic environments. Atlantic Meridional Transect (AMT) pigment data taken between 1997 and 2004 were split into two datasets; 1935 measurements were used to parameterise the model, and a further 241 surface measurements, spatially and temporally matched to chlorophyll-a derived from SeaWiFS satellite data, were set aside to validate the model. Comparison with an independent global pigment dataset (256 measurements) also supports the broader-scale application of the model. The effect of optical depth on the model parameters was also investigated and explicitly incorporated into the model. It is envisaged that future applications would include validating multi-plankton biogeochemical models and improving primary-production estimates by accounting for community composition.
Input Description None
Output Description None
Software Reference None
  • var_id: phytoplankton_size_class
  • units: 1
  • long_name: Monthly Phytoplankton Size Class (Micro, Nano, Pico) for 1998-2007 estimated from SeaWiFS/SeaStar Level 3
  • names: Monthly Phytoplankton Size Class (Micro, Nano, Pico) for 1998-2007 estimated from SeaWiFS/SeaStar Level 3, phytoplankton_size_class
  • var_id: bounds
  • names: climatological_bounds

Co-ordinate Variables

  • standard_name: latitude
  • var_id: latitude
  • long_name: latitude
  • units: degrees_north
  • names: latitude
  • units: degrees_east
  • standard_name: longitude
  • long_name: longitude
  • var_id: longitude
  • names: longitude
  • long_name: time: days since start of 1998 [0 = January 1st]
  • standard_name: time
  • var_id: time
  • names: time, time: days since start of 1998 [0 = January 1st]
  • long_name: time: days since start of 1999 [0 = January 1st]
  • standard_name: time
  • var_id: time
  • names: time, time: days since start of 1999 [0 = January 1st]
  • long_name: time: days since start of 2000 [0 = January 1st]
  • standard_name: time
  • var_id: time
  • names: time, time: days since start of 2000 [0 = January 1st]
  • long_name: time: days since start of 2001 [0 = January 1st]
  • var_id: time
  • standard_name: time
  • names: time, time: days since start of 2001 [0 = January 1st]
  • standard_name: time
  • var_id: time
  • long_name: time: days since start of 2002 [0 = January 1st]
  • names: time, time: days since start of 2002 [0 = January 1st]
  • standard_name: time
  • var_id: time
  • long_name: time: days since start of 2003 [0 = January 1st]
  • names: time, time: days since start of 2003 [0 = January 1st]
  • long_name: time: days since start of 2004 [0 = January 1st]
  • standard_name: time
  • var_id: time
  • names: time, time: days since start of 2004 [0 = January 1st]
  • long_name: time: days since start of 2005 [0 = January 1st]
  • standard_name: time
  • var_id: time
  • names: time, time: days since start of 2005 [0 = January 1st]
  • long_name: time: days since start of 2006 [0 = January 1st]
  • standard_name: time
  • var_id: time
  • names: time, time: days since start of 2006 [0 = January 1st]
  • long_name: time: days since start of 2007 [0 = January 1st]
  • standard_name: time
  • var_id: time
  • names: time, time: days since start of 2007 [0 = January 1st]
Coverage
Temporal Range
Start time:
1998-01-01T00:00:00
End time:
2007-12-31T23:59:59
Geographic Extent

 
90.0000°
 
-180.0000°
 
180.0000°
 
-90.0000°