Inter-comparison of OC-CCI chlorophyll-a estimates with precursor data sets. Issue 18 (16th September 2016)
- Record Type:
- Journal Article
- Title:
- Inter-comparison of OC-CCI chlorophyll-a estimates with precursor data sets. Issue 18 (16th September 2016)
- Main Title:
- Inter-comparison of OC-CCI chlorophyll-a estimates with precursor data sets
- Authors:
- Belo Couto, André
Brotas, Vanda
Mélin, Frédéric
Groom, Steve
Sathyendranath, Shubha - Abstract:
- ABSTRACT: Ocean colour is the only essential climate variable that targets a biological variable (chlorophyll- a concentration (chl- a )) and is also amenable to remote sensing at the global scale. However, the finite lifetime of individual ocean-colour sensors, and the differences in their characteristics increase the difficulty of creating a long-term, consistent, ocean-colour time series that meets the requirements of climate studies. The Ocean Colour Climate Change Initiative (OC-CCI), a European Space Agency programme, has recently produced a time series of satellite-based ocean-colour products at the global scale, merging data from three sensors: Sea-viewing Wide Field-of-view Sensor (SeaWiFS), Moderate Resolution Imaging Spectroradiometer on the Aqua Earth Observing System (MODIS-Aqua), and Medium Resolution Imaging Spectrometer (MERIS), while attempting to reduce inter-sensor biases.In this work we present a comparison between the OC-CCI chlorophyll- a product and precursor satellite-derived data sets, from both single missions (SeaWiFS, MODIS-Aqua, and MERIS) and multi-mission products (global ocean colour (GlobColour) and Making Earth Science Data Records for Use in Research Environments (MEaSUREs)). To this end, OC-CCI global monthly composites are compared to the similar products offered by single-mission and multi-mission records. Our results indicate that the OC-CCI product provides a higher number of observations. Comparing the observations that match withABSTRACT: Ocean colour is the only essential climate variable that targets a biological variable (chlorophyll- a concentration (chl- a )) and is also amenable to remote sensing at the global scale. However, the finite lifetime of individual ocean-colour sensors, and the differences in their characteristics increase the difficulty of creating a long-term, consistent, ocean-colour time series that meets the requirements of climate studies. The Ocean Colour Climate Change Initiative (OC-CCI), a European Space Agency programme, has recently produced a time series of satellite-based ocean-colour products at the global scale, merging data from three sensors: Sea-viewing Wide Field-of-view Sensor (SeaWiFS), Moderate Resolution Imaging Spectroradiometer on the Aqua Earth Observing System (MODIS-Aqua), and Medium Resolution Imaging Spectrometer (MERIS), while attempting to reduce inter-sensor biases.In this work we present a comparison between the OC-CCI chlorophyll- a product and precursor satellite-derived data sets, from both single missions (SeaWiFS, MODIS-Aqua, and MERIS) and multi-mission products (global ocean colour (GlobColour) and Making Earth Science Data Records for Use in Research Environments (MEaSUREs)). To this end, OC-CCI global monthly composites are compared to the similar products offered by single-mission and multi-mission records. Our results indicate that the OC-CCI product provides a higher number of observations. Comparing the observations that match with precursors, the OC-CCI product was generally most similar to the single-mission products. Relationships between OC-CCI and other precursors did not change significantly during a common and continuous period, and, on average the root-mean-square differences between log-transformed chlorophyll- a concentration are below or equal to 0.11. Further, when considering variability that could arise when merging data from different sources, it is shown that the OC-CCI product is a longer term constant than those from other multi-mission initiatives studied here. … (more)
- Is Part Of:
- International journal of remote sensing. Volume 37:Issue 18(2016)
- Journal:
- International journal of remote sensing
- Issue:
- Volume 37:Issue 18(2016)
- Issue Display:
- Volume 37, Issue 18 (2016)
- Year:
- 2016
- Volume:
- 37
- Issue:
- 18
- Issue Sort Value:
- 2016-0037-0018-0000
- Page Start:
- 4337
- Page End:
- 4355
- Publication Date:
- 2016-09-16
- Subjects:
- Remote sensing -- Periodicals
Télédétection -- Périodiques
621.3678 - Journal URLs:
- http://www.tandfonline.com/toc/tres20/current ↗
http://www.tandfonline.com/ ↗ - DOI:
- 10.1080/01431161.2016.1209313 ↗
- Languages:
- English
- ISSNs:
- 0143-1161
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library DSC - 4542.528000
British Library DSC - BLDSS-3PM
British Library STI - ELD Digital store - Ingest File:
- 14505.xml