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Bureau of Meteorology MODIS Activity

Bureau of Meteorology MODIS Activity. Ian Grant Bureau of Meteorology. Outline. Aerosol validation Total water vapour validation Forecast atmospheric fields Bureau near real-time processing trial MODIS DB BRDF: plan & status. Validation of MOD04 aerosol.

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Bureau of Meteorology MODIS Activity

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  1. Bureau of MeteorologyMODIS Activity Ian Grant Bureau of Meteorology

  2. Outline • Aerosol validation • Total water vapour validation • Forecast atmospheric fields • Bureau near real-time processing trial • MODIS DB BRDF: plan & status

  3. Validation of MOD04 aerosol • Database established by MODIS aerosol team (MAPSS) of statistics over sunphotometer sites: • - MOD04 50 km x 50 km • - Sunphotometer 30 minutes • - 470 nm, 660 nm • 4 CSIRO sites (Mitchell) • 15 Bureau sites (Forgan)

  4. Aerosol validation • MAPSS/MODIS comparison: MODIS grossly overestimates AOD • Next: Investigate a case in detail via MOD02, MOD09 data. • Raw Bureau AOD data is available • Need to extract and validate “internal AOD” of MOD09? • Coordinate with CRC-SI aerosol validation and improvement

  5. Validation of Total Water Vapour • Radiosondes (Bureau of Meteorology) • GPS (Geoscience Australia, 16 sites) Radiosondesites

  6. Numerical Weather Model Fields • Model run every 12 hours • Forecast at 3, 6, …, 72 hours • Resolutions 0.75º, 0.375º, 0.125º • Forecasts for input to MOD09: • - Surface Pressure, TWV? • Analysis for validation: TWV

  7. Numerical Weather Model Fields • Surface pressure, Total Water Vapour?, Total ozone? • LAPS forecast of TWV at 3, 6, …, 72 hours. Resolution 0.75º.

  8. Bureau near real-time MODIS processing • Acquaint Bureau users with products: NWP model input, forecasters • Trial with Bureau Linux PC at ES&S antenna in Melbourne • IMAPP: PDS → L1B → L2 • Products: • MOD07 atmospheric temperature and humidity profiles, stability • Truecolour images (CSIRO Marine CAPS software)

  9. Bureau near real-time MOD07 Cloud mask Total Totals Lifted Index

  10. Bureau near real-time images Truecolour images

  11. A Future MODIS ApplicationBushfire CRC - Grassland Curing Project • Develop techniques of satellite based curing assessment that are robust, reliable, validated and applicable across Australia and New Zealand • Approved for July 2004 – June 2010 • Conduct an extensive and systematic field measurement program • Compare MODIS vegetation indices with curing, fuel moisture content A daily AVHRR-based map of Grassland Curing Index for south-eastern Australia has been distributed by the Bureau for four years

  12. MODIS Direct Broadcast BRDF Project • Coordinated by MODIS BRDF Team at Boston University • Participants • US: Boston U, U Maryland, USDA Forest Service • Australia: CSIRO, Bureau of Meteorology, GA, DLI • China: IRSA, BNU • South Africa: CSIR • Daily BRDF • - Detect rapid land change: burns, snow • - Track changing BRDF better: vegetation growth cycle • - Reject cloud contamination • Funded by NASA

  13. MODIS DB BRDF • Boston University group (Alan Strahler, Crystal Schaaf et al.) developed the MODIS BRDF module MOD43. (Crystal is on the NPP team) • NASA funded the BU group to develop a DB version of MOD43 • Groups offered to act as implementation testbeds, in: • Australia (CSIRO, BoM, GA, DLI) • China, South Africa, US • DB code to aggregate MOD09 reflectances “L2Glite” is finished • Initial implementation now happening at BNU, China • Tuning RMSE and WoD thresholds • Australian DB sites are welcome to be next. Crystal here in March. • BRDF inversion and MOD43 products will follow

  14. IWMMM-4 • Fourth International Workshop on • Multiangular Measurements and Models • 20-24 March 2006 UniLodge Hotel, Sydney • www.eoc.csiro.au/iwmmm-4 • An opportunity • - to bring key sensor scientists to Australia • - for Australian and international EO communities to interact • - for Australian users to describe requirements to EO community

  15. Validation of MOD04 aerosol Statistics of error in Aerosol Optical Depth (MOD04 - Sunphotometer)

  16. DB BRDF:Discussion points

  17. Institutional MOD09_L2 to MOD43_L3:Conceptual steps at a grid cell •  For each orbit: • Identify which swath pixels overlap the grid cell • Calculatepointers (Dline, Dsample, fractional overlap, etc.) •  For each UT day: • Group pointers from all orbits • Select swath pixels by geometry (obscov > 24%) • (Only using geometry so far - Now introduce MOD09) • Select swath pixels by MOD09 QA (up to four) • Aggregate swath pixels to one value per orbit • (average, weighted by obscov. This does the regridding) • For each 16 days: • Invert the BRDF model

  18. BRDF - DB Issues (1) • Implement institutional details in DB: selection, aggregation, etc.? • - Bow-tie and IFOV increase give multiple swath pixels at a grid cell • Window length? • Re-use any institutional code? • BRDF as an IMAPP module? (Multipass is new to IMAPP?) • Process in tiles (10º10 º) for efficient memory use? • 250-m resolution? • Feed BRDF upstream, for aerosol and cloud mask?

  19. BRDF - DB Issues (2) • Invert BRDF each day or each orbit? • Terra + Aqua span 5 hours • Sub-day changes: Burns, flood, snow, cloud • Iterate Atmospheric correction and BRDF inversion? • Use yesterday’s BRDF as first guess? • In thick aerosol (smoke)? • Iterative retrieval of aerosol, cloud mask? • In high-value region-season cases (fuel reduction, crop yields)? • Build a flexible framework to accommodate these options? • Recognise the conceptual steps and keep them separate • CSIRO AVHRR BRDF as a testbed?

  20. BRDF window length - VEGETATION approach Duchemin et al., Remote Sens. Env., 81 (2002) 101-113 • BRDF shape from inversion in long window (last 10 looks) • Average normalised clear looks in short window (last 10 days) • Reject inversion outliers (up to three, red band) • In practice, worst cases for inversion • window length are: • >25 days in 11% of cases (Europe) • >50 days in 0.1% of cases (tropics) • Weight more recent looks? • Additive rather than multiplicative normalisation? (needs investigation)

  21. BRDF - DB Issues • Implement institutional details in DB: selection, aggregation, etc.? • Window length? • Re-use any institutional code? • BRDF as an IMAPP module? • Process in tiles for efficient memory use? • 250-m resolution? • Feed BRDF upstream, for aerosol and cloud mask? • Invert BRDF each day or each orbit? • Iterate Atmospheric correction and BRDF inversion? • Build a flexible framework to accommodate processing options?

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