1. The Western (English) Channel Observatory as a test bed for improving ecosystem forecasts. Icarus Allen, Tim Smyth et al. PML www.westernchannelobservatory.org.uk ‘Growing concern about human influence on marine ecosystems conflicts with our inability to separate man-made from ‘natural’ change. This limitation results from lack of adequate baselines and uncertainty as to whether observed changes are local or on a broad scale. Long-term monitoring programmes should be able to solve both these deficiencies’ (Duarte et al, 1992. Nature)

2. Sustained Observations in the Western English Channel: past, present and future. Plymouth time series since 1900

3. Geographical Region Western English Channel: boundary region between oceanic and neritic waters; straddles biogeographical provinces; both boreal / cold temperate & warm temperate organisms considerable fluctuation of flora and fauna since records began. Southward et al. (2005) Adv. Mar. Biol., 47 Overall aims and purpose Our purpose is to integrate in situ measurements made at stations L4, L5, E1 and adjacent coasts in the western English Channel (see Fig 3) with ecosystem modelling studies and Earth observation; this will be facilitated by web-based GIS technology. which allows the following science questions to be addressed at a range of temporal and spatial scales: What is the current state of the ecosystem? How has the ecosystem changed? Improve short term forecasts of the state of the ecosystem. A national facility for EO algorithm development, calibration and validation.

4. Remote Observatory Virtual Observatory In-situ sampling (L4, E1, L5, buoy, etc.) long-term time-series (linked to non WCO series via MECN) scientific investigation Remote Sensing SST, Ocean Colour Other sensors Modelling ERSEM Met Office (NCOF) Data Database (SQL) Web (Webmap server) each element has strengths and weaknesses – synergy. MECN: Knowledge Transfer / policy advice

5. In-Situ Sampling

6. In situ sampling i) Marine measurements: OPERATIONS: weekly sampling @ L4; fortnightly @ E1 The Observatory consists of the core measurements: Hydrography (CTDf); Nutrients; Optics; Pigments; Zooplankton and phytoplankton ii) Atmospheric measurements: meteorological stations (PML, Rame Head) sun photometric aerosol retrievals (PML)

7. Latest Hydrography The year so far (L4) …

8. 50.67°N latitude: 50.67°N 4.58°W longitude: 4.58°W 1988 start: 1988 weekly sample frequency: weekly 1988- on going abundance: 1988- on going 1993-1998 biomass: 1993-1998 copepods eggs production: 1992-2005 L4 L4 - Zooplankton time-series vertical net hauls: from the sea floor (~55m) to the surface WP2 net: mesh 200µm (UNESCO 1968) samples are stored in 5% formalin taxonomic identification zooplankton database data analysis

9. Composition of the “Top20” dominant species at L4 (Plymouth) 1988- 2006 Sagitta sp. 90%

10. Array of autonomous moorings An observatory needs to directly observe something; Need real-time data (rather than just RS / modelling); Capital bid successful: currently specifications out to tender … Have permissions for moorings at L4 and E1. E1:Moored (profiling?) buoy CTDf, Optics, Nutrients … L4:Moored profiling buoy CTDf, Optics, Nutrients … expandable for visitors? Rame Head:(shore node) Met. Station; Aerosols; PML:(base node) Met. Station; Aerosols;

11. Remote Observatory

12. Remote Sensing SST (1981 - ) and ocean colour (1997 - ) to provide synoptic overview of WCO domain. Delivered via web and Web Map Server technology. Tidal mixing frontal region stratified frontal region case I case II Autumn bloom

13. AVHRR SST 26 Aug - 01 Sep 02-08 Sep 9-15 Sep 16-22 Sep23-29 Sep NRT data provided in partnership with NEODAAS PML.

14. MODIS chlorophyll-a 26 Aug - 01 Sep 02-08 Sep 9-15 Sep 16-22 Sep23-29 Sep NRT data provided in partnership with NEODAAS PML.

15. Virtual Observatory

16. Western English Channel Model 7km Western Channel POLCOMS-ERSEM PML-delayed 7 day Hindcast 2002-pres 2km under-development, 500m regional sub- model in vicinity of L4/E1 proposed

17. Development of Model Metrics Dsicrimination AnalysisTaylor Diagram

18. How well does ERSEM capture the seasonal succession at L4? Multivariate Validation: Comparison of PC1 for modelled and observed phytoplankton Assessing short term forecast skill Like with Like comparison Log Chlorophyll Monthly Mean Chlorophyll

19. Data Delivery

21. Hosting of Ecosystem parameters (NCOF box)

22. Summary

23. If the model predicts a bloom what’s the probability it is correct? Positive Predictive Value A. PPV for threshold > mean chlorophyll, B. PPV for threshold > 1.5 mean chlorophyll for that pixel, Allen et al Harmful Algae (in press)