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GlobColour international context (as seen from IOCCG) Prepared by IOCCG Project Office

GlobColour international context (as seen from IOCCG) Prepared by IOCCG Project Office Presented by Eric Thouvenot (CNES representative to IOCCG). IOCCG’s perpective of International Context of GlobCOLOUR.

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GlobColour international context (as seen from IOCCG) Prepared by IOCCG Project Office

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  1. GlobColour international context (as seen from IOCCG) Prepared by IOCCG Project Office Presented by Eric Thouvenot (CNES representative to IOCCG)

  2. IOCCG’s perpective of International Context of GlobCOLOUR As operational oceanography grows, there is an increased demand for data and information relevant to understanding the marine ecosystem at the global level. Many issues could be addressed using the GlobCOLOUR data set, both global and regional. Example 1: Yoder research - long-term time series are required to examine changes in global chlorophyll levels and to sort out differences between cycles and trends. Example 2: Platt research - long-term ocean colour time series can explain haddock recruitment fluctuations in the Northwest Atlantic. There is great potential that the GlobCOLOUR dataset will provide similar answers elsewhere. The GlobCOLOUR dataset is also relevant to several of the tasks of the intergovernmental Group on Earth Observations (GEO), which is leading a worldwide effort to build a Global Earth Observation System of Systems.

  3. Example 1: Yoder slides

  4. Are Phytoplankton Biomass and Productivity Declining in Large Parts of the Global Ocean Owing to Climate Change Effects on Stratification? Jim Yoder Woods Hole Oceanographic Institution

  5. Questions Are model and SeaWiFS phytoplankton chlorophyll (Chl) trends similar during the SeaWiFS-era (1998-2005) in regions of the open ocean, i.e. does the model agree with the satellite observations? Are model trends unusual during the SeaWiFS-era compared to other 8-year intervals during the model era (1958-2004)?

  6. Motivation and Background Three recent manuscripts indicate that phytoplankton chlorophyll/carbon (Chl) concentrations in large regions of the ocean are decreasing, possibly owing to climate change effects on ocean stratification. Gregg, W. et al. 2005, Geophys. Res. Lett., 32, L03606, doi: 10.1029/2004GL021808. Antoine et al. 2005, J. Geophys. Res., 110, C06009, doi: 10.1029/2004JC002620. Behrenfeld et al. 2006, Nature 444 doe:10.1038/nature0517

  7. Trend in SeaWiFS Mean Chlorophyll (1997-2003) (from Gregg et al. 2005)

  8. Percent differences (“red” is 100%, “blue” is <50%) in SeaWiFS (1998-2002) to CZCS (1979-1983) annual mean chlorophyll (from Antoine et al. 2005)

  9. Trend in SeaWiFS chlorophyll, net primary production (NPP) and stratification anomalies (MEI) for stratified waters of the global ocean (from Behrenfeld et al. 2006) Chl (line) MEI (circles) Chl trend(line)

  10. Impact of 96-97 ENSO on Satellite SST and Chl Anomalies (from Yoder, J.A. and M.A. Kennelly. 2003. Global Biogeochemical Cycles, 17 (4), 1112. ). Note that SST and (inverse) Chl anomalies track ENSO index. low Global anomalies (mean seasonal trend removed from each pixel) summed from 50°S to 50°N. Blue is negative Chl (i.e. 0 - Chl) Black is SST. Red is Nino 3.4 index.

  11. Approach Use the model to see if the trends observed in SeaWiFS imagery are also evident in the longer record (46 years) of the model. Answer the following questions: Are model and SeaWiFS phytoplankton chlorophyll (Chl) trends similar during the SeaWiFS-era (1998-2005) in regions of the open ocean, i.e. does the model agree with the satellite observations? Do model results indicate that the SeaWiFS-era trends are representative of longer period trends showing decreasing Chl concentrations possibly linked to increasing ocean stratification?

  12. Model References • Moore, J.K., S.C. Doney and K. Lindsay, 2004: Upper ocean ecosystem dynamics and iron cycling in a global 3-D model, Global Biogeochem. Cycles, 18, 4, GB4028, 10.1029/2004GB002220. • Doney, S.C., K. Lindsay, I. Fung and J. John, 2006: Natural variability in a stable 1000 year coupled climate-carbon cycle simulation, J. Climate, 19(13), 3033-3054. • Doney, S.C., S. Yeager, G. Danabasoglu, W.G. Large, and J.C. McWilliams, Mechanisms governing interannual variability of upper ocean temperature in a global hindcast simulation, J. Phys. Oceanogr., in press.

  13. Brief Model Description Starts with the 3-D physics of the Parallel Ocean Program (POP) with 3.6° long and 0.9 to 2.0° lat resolution, and we used monthly fields. Forced by NCEP reanalysis fields. Embeds a multi-element, multi-functional group ecosystem model (Moore et al. 2004) and a marine biogeochemistry model (Doney et al. 2006). Primary production is partitioned between pico and nano phytoplankton and includes diatoms and diazotrophs. N-fixation and calcification are calculated. Zooplankton include micro and larger forms. Nutrients include N, P, Si and Fe.

  14. Analysis Sites 11 (green dots) of our 34 stations are within areas identified by Gregg et al as showing significant trends in SeaWiFS Chlorophyll. Used these sites to examine model and SeaWifS Chl trends.

  15. Conclusions Are model and SeaWiFS phytoplankton chlorophyll (Chl) trends similar during the SeaWiFS-era (1998-2005) in selected regions of the open ocean, i.e. does the model agree with the satellite observations? Yes. Do model results indicate that the SeaWiFS-era trends are representative of longer period trends showing decreasing Chl concentrations possibly linked to increasing ocean stratification? No, the model shows that there are 8-year periods of both increasing and decreasing chlorophyll trends throughout the model era (1958-2004).

  16. Speculation Trends observed during SeaWiFS era are related to the very large ENSO which began in 1996 and had global impacts for many years (e.g. seeYoder, J.A. and M.A. Kennelly. 2003. Global Biogeochemical Cycles, 17 (4), 1112. ). Thus, he apparent changes (both increases and declines depending on ocean region may not reflect a long term trend. Yoder and Kennelly 2003 Behrenfeld et al. 2006

  17. Example 2: Platt slides

  18. Example 2: Using ocean-colour remote sensing as a tool for development of ecological indicators in the coastal zone (Platt 2003, plus unpublished data) Ecological indicators are an aid to ecosystem-based management – essential to have long time series. With ocean colour data, construction of time series is possible at any chosen scale of spatial averaging. Time series in NW Atlantic – note differences in the timing of the spring bloom from year to year and region to region. (SeaWiFS data)

  19. Quantifying Seasonality Any or all of these indices may vary between years (at any or all of the pixels in the region of interest) Platt, Sathyendranath & Fuentes-Yaco, 2007

  20. N 44 -10 -8 -6 -4 -2 0 2 4 6 8 10 (Week) Late Earlier 43 W 64 62 60 66 Using time-series data to test Cushing’s Match-Mismatch Hypothesis: Test whether significant proportion of variance in larval abundance (survival) can be accounted for by variations in ecosystem indices (interannual fluctuations in dynamics of spring bloom). Anomalies for Timing of Chlorophyll a Maxima (February - July) 1997 1998 1999 2000 2001 Platt et al. 2003

  21. Using time-series data from CZCS and SeaWiFS, it appears that greatest larval survival coincides with an earlier spring bloom. Haddock survival in the NW Atlantic (after Platt et al. 2003)

  22. Possible mechanism favouring early bloom of phytoplankton • Where number of haddock larvae and biomass of phytoplankton overlap, larvae have food supply adequate for survival • Where this is not so, larvae are vulnerable to death by starvation Early blooms imply a smaller blue area and a smaller proportion of the total larvae produced at risk from inadequate food supply

  23. Conclusion • Remotely-sensed data are useful for construction of time series, but requires care in quality control. • Time series provide cost-effective basis for development of • ecological indicators, averaged at appropriate time and space scales. • Even with only two remotely-sensed variables (chlorophyll and temperature), a rich set of ecological indicators can be derived. • The SeaWiFS 10-year series has yielded interesting results. The GlobCOLOUR data set will likely add more.

  24. Part 3 : GlobColour and GEO

  25. GlobCOLOUR and GEO Other Relevant International Projects: • The GlobCOLOUR dataset may also be relevant to the following GEO tasks: • ChloroGIN Project (Chlorophyll Global Integrated Network). GEO Task EC-06-07. • The SAFARI Project (Societal Applications in Fisheries and Aquaculture using • Remote Sensing Imagery). GEO Task AG-06-02. • Global Ecosystems Classification and Mapping Initiative (GEO Task EC-06-02)

  26. ChloroGIN Project (Task EC-06-07) Chlorophyll Global Integrated Network • Goals: • To develop a global network which will provide information on marine ecosystems for use at national and regional scales, using a combination of Earth observation (EO) data from satellites (Chl and SST) and in situ observations. • To integrate in situ and remote observations into a single network - this will improve understanding of ecosystem processes and dynamics and will help in fisheries management. • To provide a timely delivery of data and information that will benefit society.

  27. ChloroGIN Project contd. • Data delivery may be in near-real time (NRT) or delayed mode time series data (similar to GlobCOLOUR dataset, but not merged data). • Latin American network (ANTARES) already established with the aim of studying long-term changes in coastal ecosystems. In situ and satellite data from around South America shared. • ChloroGIN Africa web portal was recently established along the same lines as ANTARES. • GlobCOLOUR dataset may help fill some of the gaps of ChloroGIN ChloroGIN Africa ANTARES (South America)

  28. SAFARI Project (Task AG-06-02) Societal Applications in Fisheries and Aquaculture using Remotely-sensed Imagery Project initiated: October 2007 Funded by: The Canadian Space Agency Chairman: Dr. Trevor Platt • Project Goals: • To coordinate, at the international scale, various earth-observation initiatives related to fisheries and aquaculture, and add to their value through synergy. • Project Execution: • Host an international coordination workshop • Publish an IOCCG monograph on the state of the art • Highlight excellent demonstration projects of EO in fisheries • Develop an outreach component to increase awareness of the value of EO in the fisheries and aquaculture sector • Convene an international symposium on thistimely topic

  29. SAFARI Demonstration Projects • Examples of some elements that may be included in SAFARI and are relevant to GlobCOLOUR: • An internationally-coordinated programme in the Northwest Atlantic Ocean (SHRIMP) to relate relative abundance and growth of the Northern Shrimp to ecosystem fluctuations, as indexed by remote sensing of ocean colour • A Canadian programme on development and testing of ecological indicators for the pelagic zone, as deduced from EO data, and evaluation of their utility for ecosystem-based management. • The design of an ocean-colour constellation of satellites for long-term, uninterrupted, internally-consistent stream of remotely-sensed data for operational applications (initiative of the IOCCG). • Southern African work on integrated, ecosystem-based and cooperative management of the Benguela ecosystem.

  30. Global Ecosystems Classification and • Mapping Initiative (Task EC-06-02) • Aim: • To establish an ecosystem classification task force, covering freshwater, terrestrial and ocean ecosystems, with a mandate to create a globally agreed, robust and viable classification scheme for ecosystems. • In parallel with the classification effort, develop, review, and initiate a mapping approach to spatially delineate the classified ecosystems.

  31. Global Ecosystems Classification and Mapping • Global ecosystems can be classified at the meso-scale (on the order of 10 to 103 km2) • A biophysical stratification approach can be adopted for terrestrial, freshwater and marine ecosystem delineation. • For the oceans, the approach of Longhurst’s (1998) biogeochemical provinces can adopted. Longhurst Partition Boundaries may move seasonally (Devred 2007)

  32. Summary • We still lack sufficiently long satellite time series to sort out differences between cycles and trends. • We need a sustained international effort to make sure we can link one satellite data set to another to build the long time series that we need. • GlobColour is definitely a significant step in that perspective

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