1. EUMETSAT FUTURE PRODUCTS RELEVANTS FOR LAND SAF ACTIVITIES
Yves Govaerts et al.
EUMETSAT
3nd Land SAF workshop
Lisbon, 8-10 February 2006

2. OVERVIEW
ASCAT Soil Moisture (EPS)
Land Daily Aerosol (MSG)
Surface Emissivity (MSG, internal)
Active Fire Detection (MSG)
Fire Radiative Power and Energy (MSG)

3. EUMETSAT ASCAT Level 2 Soil Moisture Product
H. Bonekamp, D. Klaes (EUMETSAT)
With the collaboration of
Institute of Photogrammetry and Remote Sensing, Vienna University of Technology

4. EUMETSAT ASCAT Level 2 Soil Moisture Product
Product processor developed by IPF TU Wien
Generation of a level 2 prototype processor for the intake of ASCAT level 1 data.
Generation of the parameter database as required for the ASCAT processing.
On-site support during the implementation and testing with the EPS ground system at EUMETSAT.
PART A: Processor for ERS-SCAT based Soil Moisture (pilot project completed in December 2005)
PART B: Processor for ASCAT based Soil Moisture ( )

5. EUMETSAT ASCAT Level 2 Soil Moisture Product
Schedule
Q4/2005: WARP_NRT_ km ERS_SCAT processor (first delivery)
Q4/2006: WARP_NRT km ASCAT data
Q1/2007: WARP_NRT_ km ASCAT, uncalibrated processor
Q4/2007: WARP_NRT_ km ASCAT, calibrated processor

6. EUMETSAT ASCAT Level 2 Soil Moisture Product
Output
Level 2 (orbit-based) soil moisture product generated within the EPS ground segment at EUMETSAT
Standard dissemination by end of 2007: GTS, EUMETCast , U-MARF (To be Decided)

7. EUMETSAT ASCAT Level 2 Soil Moisture ProductNb
The parameter database production required for the ASCAT processing shall be based on the implementation plan resulting from the NWP SAF Associated Scientist project.
Soil Moisture Part of ASCAT BUFR template

8. Land Daily Aerosol (LDA)
MSG/SEVIRI Land Daily Aerosol Product
S. Wagner, Y. Govaerts
EUMETSAT

9. Land Daily Aerosol (LDA)
Objective :
Derive a mean daily aerosol optical thickness at 0.55μm for various aerosol types over land surfaces from daily time series of observations in the VIS0.6, VIS0.8 and NIR1.6 bands.
Algorithm :
Based on the inversion (Optimal Estimation) of a forward model against daily time series of observations in the VIS0.6, VIS0.8 and NIR1.6 bands.
Status :
Under development, not available before 2007.

10. Land Daily Aerosol (LDA)
LDA algorithm principle
Model :
Total column ozone
Total column water vapour (ECMWF)
State variables
Tg(O3,H2O)
Measurement vector
VIS0.6
NIR1.6
VIS0.8
Retrieved :
aerosol optical thickness at 0.55μm (1)
surface reflectance (4 × 3 bands) τ
ρ0 (λ),k (λ),θ(λ),h
Absorbing atmosphere
Scattering atmosphere

11. Land Daily Aerosol (LDA)
Fit of the best solution
VIS0.8
NIR1.6
VIS0.6

12. Land Daily Aerosol (LDA)

13. Land Daily Aerosol (LDA)
NIR1.6
VIS0.8
VIS0.6

14. Land Daily Aerosol (LDA)

15. Land Daily Aerosol (LDA)
NIR1.6
VIS0.8
VIS0.6

16. Land Daily Aerosol (LDA)

17. MSG/SEVIRI Optimal Cloud Analysis
Surface Emissivity
MSG/SEVIRI Optimal Cloud Analysis
Ph. Watts
EUMETSAT

18. t, re, pc, f, Ts Surface Emissivity 3.9,
Background : Future cloud micro-physical properties product based on OE method applied on SEVIRI solar and IR observations
t, re, pc, f, Ts
X =
Tbc
Tac
t re pc f Rs
t re pc f Ts
Rbc
Bce
Rdown
Rac
y(x) =
Solar RT model
Thermal RT model
Scattering model
RTMOM - LUTs
Scattering Properties
3.9,
6.2, 7.3, 8.7, 9.7, 10.8, 12., 13.4 ]
y =
[0.6, 0.8, 1.6,
Benefit from accurate lower boundary conditions in case of low optical thickness

19. Surface Emissivity
Surface emissivity could potentially be derived from multiple image cycles:
Estimation of [(e1, e2, e3, .. en, Ts)1, (e1, e2, e3, .. en, Ts)2,…...] from [(BT1, BT2,.. )1 [(BT1, BT2,.. )2 ..]
M.(n+1) unknowns from M.n pieces of information
use ‘fact’ that the e’s changes much more slowly than the Ts

20. Surface Emissivity Simple RT equation
‘Realistic’ but not real channels
Realistic Ts, Es, Tr AR-1 sequences
Estimated error:
Ts : ~0.8 K
Es: ~ %
After 1-2 days continuous data
Parameter estimation stable to unknown statistical parameters
Further investigation with more realistic RT equation and channels still needed.

21. MSG/SEVIRI Active Fire Product
J. Prieto, H.J. Lutz and A. Yildrim
EUMETSAT

22. Based on four quantities:
Active Fire Product
Based on four quantities:
MSG 3.9 µm brightness temperature larger than a threshold (variable with the time of the day)
MSG 10.8 µm standard deviation in 3x3 superpixel (for removing cloud boundaries)
MSG 3.9 µm standard deviation in the superpixel (for detecting small fires)
The BT difference 3.9 – 10.8
Only the clear land pixels are considered in the superpixel
Tests not applied on bare soil and water surfaces

23. Fire detection indicator: 0= No fire detected
Active Fire Product
Final product with cloud mask:
Yellow: potential fire
Red: fire
Fire detection indicator:
0= No fire detected
1= Possible fire detected
2= Probable fire detected
3= Missing
No quality flag included.
Example 21 Aug 2005 at 12:00

24. Active Fire Product : Format and availability
Generated every 15 minutes
Coded as GRIB2 Code table Fire detection indicator
WMO standard for gridded data, with high compression capability
Provisionally located at ftp.eumetsat.int/pub/ops/out/simon/FIRE
After validation, the product will be available at the EUMETSAT web and through EUMETCast (May 2006)

25. Fire Radiative Energy / Power
MSG/SEVIRI Fire Radiative Power / Energy Products
A. Lattanzio, Y. Govaerts (EUMETSAT)
With the collaboration of
Pr. M. Wooster, Environmental Monitoring & Modelling Group
Department of Geography, King's College London

26. Fire Radiative Energy / Power
Increasing Time
Flaming Smouldering
Rate of Biomass = x Fire Radiative
Combustion (kg s-1) Power (MW)
Fire Radiative Power (W)
Rate of Fuel Combustion (kgs-1)
Wooster et al, 2003.
The Fire Radiative Power (FRP) is the amount of radiant energy liberated per unit time during a vegetation fire. It is related to the rate at which the fuel biomass is being consumed (e.g. Wooster et al., 2005).
The Fire Radiative Energy (FRE) is the temporal integration over the lifetime of the fire. It provides a measure of the total energy emitted by fires, which should be proportional to the total fuel mass combusted.
Not available before 2007

27. Fire Radiative Energy / Power
Example of FRP product
in MW, derived from a slot acquired by Met8 on 07/02/2004 at 12:12 UTC.

28. Fire Radiative Energy / Power
Time series of FRP for Angola for 3-8 September 2003, taken from Roberts G. et al 2005.
Estimated FRE is MJ for the period.