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Sea Surface Temperature and Coral Bleaching Using DevCoCast SST Data

Sea Surface Temperature and Coral Bleaching Using DevCoCast SST Data. Yohana Shaghude ( IMS/UDSM) and Valborg Byfield (NOCS ). Advanced DevCoCast Training Course, ITC, Netherlands 07-18 February 2011. PRESENTATION OF THE MAIN RESULTS. OBJECTIVE.

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Sea Surface Temperature and Coral Bleaching Using DevCoCast SST Data

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  1. Sea Surface Temperature and Coral Bleaching Using DevCoCast SST Data Yohana Shaghude (IMS/UDSM) and Valborg Byfield (NOCS) Advanced DevCoCast Training Course, ITC, Netherlands 07-18 February 2011

  2. PRESENTATION OF THE MAIN RESULTS

  3. OBJECTIVE • The main objective of the proposed application is to investigate the trends in sea surface temperature (SST) from satellite platforms for the purpose of predicting coral bleaching “Hot spots” along the coast of Tanzania. • Specific objectives are: • To investigate the trends in sea surface temperatures along the coast of Tanzania using sea surface temperature (SST) from satellites. • To use the SST satellite data to predict coral bleaching risks along the coast of Tanzania

  4. DATA USED • Local data: • In situ measurements from temperature loggers at Chumbe reefs Zanzibar (1997 – 2010). • Data from GEONETCast: • MODIS SST data from Plymouth Marine Lab (1 km resolution) • Other data: • global SST climatological data from Pathfinder (2 km resolution)

  5. METHODOLOGY & DATA PROCESSING Description of Methodology: • Obtain the DevCocast SST (Jan - March) for 2007 and 2010 from PML • Import of the data (SST night images to ILWIS • Calculation of the weekly Mean of the SST night images. • Set formula to exclude clouds, poor quality pixels, land pixels (define threshold temperature) • Check the validity of the output images by comparison with in situ data

  6. METHODOLOGY & DATA PROCESSING Description of Methodology: • Calculation of monthly mean from the weekly mean SST data • Deterrmine the month with highest SST monthly mean • Extraction of the global Maximum Monthly Mean (MMM) for the area of interest (Tanzania) • Compare the MMM from global climatology with Devcocast data • Calculation of SST anomaly for investigating CRW hotspots

  7. METHODOLOGY & DATA PROCESSING METHODOLOGY & DATA PROCESSING Flow Chart: SST (Raw data) DEVCOCast/PML Import the Devcocast data to Ilwis Calculation of weekly composite Mean Calculation of Maximum Monthly Mean Import and analysis of Global climatology data Calculation of SST anomaly Investigation of CRW Hotspots

  8. RESULTS

  9. RESULTS • The analysed SST data for 2007 and 2010 revealed that highest temperatures along the coast of Tanzania occur towards the end of March (week 12 - 13) with March having the highest maximum mean temperatures.

  10. SSS_WEEK2_MEAN_2007 SSS_WEEK6_MEAN_2007 SSS_WEEK12_MEAN_2007 SSS_WEEK13_MEAN_2007

  11. SSS_WEEK2_MEAN_2010 SSS_WEEK13_MEAN_2010

  12. CRW HOTSPOTS • The SST data analysed indicated that there were no major coral reef threats during the years 2007 and 2010.

  13. CRW_HOTSPOT_FEB_2007

  14. CRW_HOTSPOT_FEB_2010

  15. CRW_HOTSPOT_FEB_2007

  16. CONCLUSIONS • The investigated satellite SST data revealed that there were no significant coral reef threats along the coast of Tanzania during 2007 and 2010. • However there were few coral reef sites where the SST was getting closer to the coral bleaching threshold conditions (especially in 2010). • The developed tool would be important for the future monitoring of coral reefs along the coast of Tanzania. • Ilwis was capable of cleaning off the cloud-contaminated pixels using the formula set for threshold temperature conditions.

  17. ACKNOWLEDGEMETS • ITC staff • Ben • Martin • Laura • Etc. • VITO (Tim) • EAMNet/PML/NOAA • IMS/Southampton NOC • Fellow colleagues and friends

  18. THANK YOU 4 YOUR ATTENTION

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