Bureau of MeteorologyBureau of MeteorologyMODIS ActivityMODIS Activity

Ian Grant

Bureau of Meteorology

OutlineOutline• Aerosol validation

• Total water vapour validation

• Forecast atmospheric fields

• Bureau near real-time processing trial

• MODIS DB BRDF: plan & status

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)

Aerosol validationAerosol 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

Validation of Total Water VapourValidation of Total Water Vapour

• Radiosondes (Bureau of Meteorology)

• GPS (Geoscience Australia, 16 sites)

Radiosonde sites

Numerical Weather Model FieldsNumerical 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

Numerical Weather Model FieldsNumerical Weather Model Fields

• Surface pressure, Total Water Vapour?, Total ozone?

LAPS forecast of TWV at 3, 6, …, 72 hours. Resolution 0.75º.

Bureau near real-time MODIS processingBureau 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)

Bureau near real-time MOD07Bureau near real-time MOD07

Cloud mask Total Totals Lifted Index

Bureau near real-time imagesBureau near real-time imagesTruecolour images

A Future MODIS ApplicationA Future MODIS ApplicationBushfire CRC - Grassland Curing ProjectBushfire 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

MODIS Direct Broadcast BRDF ProjectMODIS 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

MODIS DB BRDFMODIS 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

IWMMM-4IWMMM-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

Validation of MOD04 aerosol

Statistics of error in Aerosol Optical Depth

(MOD04 - Sunphotometer)

Mean 0.47

StdDev 0.47

Mean 0.66

StdDev 0.66

Number Samples

Canberra -0.02 0.07 0.04 0.08 36

Coleambally 0.06 0.16 0.10 0.16 78

Darwin 0.06 0.09 0.13 0.09 113

Jabiru -0.01 0.09 0.03 0.06 186

Lake Argyle 0.38 0.20 0.31 0.12 151

Rottnest Island 0.12 0.13 0.13 0.12 141

DB BRDF:DB BRDF:Discussion pointsDiscussion points

Institutional MOD09_L2 to MOD43_L3:Institutional MOD09_L2 to MOD43_L3:Conceptual steps at a grid cellConceptual steps at a grid cell

• For each orbit:

- Identify which swath pixels overlap the grid cell

- Calculate pointers (line, sample, 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

BRDF - DB Issues (1)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 (10º10 º) for efficient memory use?

• 250-m resolution?

• Feed BRDF upstream, for aerosol and cloud mask?

BRDF - DB Issues (2)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?

BRDF window length - VEGETATION approachBRDF window length - VEGETATION approach

• 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)

Duchemin et al., Remote Sens. Env., 81 (2002) 101-113

BRDF - DB IssuesBRDF - 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?