fr1.l10.1: overview of smos retrievals over land
TRANSCRIPT
OVERVIEW OF SMOS
RETRIEVALS OVER LAND
Y.H. Kerr, F Cabot, P. Richaume, A. AlBitar, E. Jacquette, A. Mialon, C. Gruhier, S. Juglea, P.
Ferrazzoli, A. Mahmoodi, S. Delwart, J.P. Wigneron
Layout
• Introduction• Summary of Commissioning phase• Most Significant improvements• Cal Val activities• Examples of results• Conclusions and next steps
YHK July 2010
Commissioning phase
• First SM retrieval almost on the first day• Discovery of RFI importance!• Intensive work on RFI
– Europe Asia out!– Winter focus on simple cases!
• Australian campaign• Search for Argentinian sites• Calibration and image reconstruction
improvements• Geolocation, calibration strategy• Mode selection
YHK July 2010
% Rejected TB
Nb of Retrievals
norm % sucess
LO freq
Proc version
L1C errors
Pol mode
improvement
More rejected TBs in FULL mod
Effect of Polarization mode is clear
1- Global Analysis – Results for All nodes
A;Al Bitar
% Rejected TB
Nb of Retrievals
norm % sucess
LO freq
Proc version
L1C errors
Pol mode
3% decrease in FULL
In average 60% of the nodes ara retieved
1- Global Analysis – Results for Soil Cover
% Rejected TB
Nb of Retrievals
norm % sucess
LO freq
Proc version
L1C errors
Pol mode
2% increase in FULL mode
1- Global Analysis – Results for Forest Cover
L2SM functional
• Allows to compare L1C TB with model outputs
After fiddling a little
YHK July 2010Ph Waldteufel LTT
L2SM functional
• SML2PP prototype operating OK
• Tested with operational and prototype L1C products
Example
AMSR
SMOS
ECMWF
First data analysis• Range Ok for typical scenes
– low values when dry– Maximum around 40 to 60%– But
• Negative values• Not as many retrievals as expected!
• Improved with – Calibration and geolocation!– Bug corrections!!
• Other issues identified
YHK July 2010
Algorithms
• Improvements– Dielectric constant (Mironov)– ECMWF Soil moisture too high– Roughness adjustments– Forest parameterisation
YHK July 2010
PORTOS-1993: a re-analysis based on a 4 -parameter (Qr, Hr, Nrv, Nrh) approach
[Wigneron et al., 2010]
→ confirming Qr ~ = 0
→ calibrating Hr = f(STD) or =f(slope)
→ calibrating ∆= (Nrh – Nrv) = f(STD):
- ∆ ~ 2 over smooth soils- ∆ ~ 0 over rough soils
→ Choudhury approach over-estimates Hr for STD > 15mm (Cf figure)
Γsoil-p = (Qr.Γ∗soil-p + (1-Qr). Γ∗
soil-q) e-Hr cosNrp(θ)
7 fields, STD varies from 5 to 60 mm
HR = (a.STD /(c.STD+d))b
Nrh-Nrv = a. STD +b
ATBD values (Ferrazzoli Rahmoune)
From present ATBD (broadleaf forests ):τ = 0.295 (LAIFmax+ LAIVmax) (0.93 for Chaco)
(leads to overestimation)ω = 0.095
Under reprocessing:τ = 0.29 LAIFmax+ 0.06 LAIVmax (0.52 for Chaco)
ω = 0.08
Note: τ includes litter effects, new Hr
Cal/Val activities• Need to start from level 1
– First analysis of TB values•Ocean, Antarctica, Land
– Correct order of magnitude but some biases to be corrected– Salinity very good indicator due to high sensitivity
• Campaigns– Australia No RFI, Cal activities …data? J. Walker
– Valencia Sever problem many RFI just solved E. Baeza
– Danube potential RFI problem see UM presentation
– Mali see Gruhier’s presentation
– Denmark Okay ?
– Sites in the US and in Argentina
YHK July 2010
Australia Sites (Met Stations)C.Mialon,D.C. Rûdiger
Some Results
• Temporal evolution• Sensor intercomparison• Area RFI affected• Sites in France• Global fields
YHK May 2010IOCP-KP3 Avila
Cumulated precipitations between May 1 and May 3, 2010. Ffrom the TRMM Science Data and Information System, http://earthobservatory.nasa.gov/IOTD/view.php?id=43873&src=eoa-iotd),
source : http://earthobservatory.nasa.gov/IOTD/view.php?id=43873&src=eoa-iotd
2010/04/28 2010/04/28 2010/04/29
2010/05/01 2010/05/01 2010/05/02
2010/05/04
SMOS L2 Soil Moisture (A. Mialon)
Soil moisture map Onset of the rainy season
Soil Moisture m3/m3
Convective rainsRFI
Dense forest
C. Gruhier
YHK July 2010
Site Description
Semi-aridZone :< 900 mm/yr20km 20km 00 20km 20km 00
Semi-humid zone
1500mm
/yr
900mm
/yr
750mm
/yr
1200mm
/yr
2000mm
/yr
5000mm/yr
Kabiniwatershed
Maddur
Gundlupet
Humid zone : >1500 mm/yr
Ambalavayal
South india Kabini river bassin from west to east gradient
Climate Humid Semi-aridVegetation Forest AgricultureTopography Mountains plains
A. Al Bitar Sat Kumar
SMOS Grids Points over site
GPID: 3160499LAT : 11.89
LON : 76.633
MOFN0: 0.80MOFF0: 0.19
GPID: 3160498LAT:11.753LON:76.638
MOFN0:0.5742M0FF0: 0.423
SMOS data – (1) Soil Moisture Ascending orbits
If more than 50% of samples have been removed due to RFI the SMOS data is excludedi.e. (NRFIx + NRFI y -Nwild)/ M_AVA0 < 0,5
GPID 3160499
GPID 3160498
YHK July 2010N Novello
Thank You!
Soil moisture retrievals June 20 -23 2010 P. Richaume
YHK July 2010 P. Richaume
Thank You!
http:/ /www.cesbio.ups-t lse.fr/SMOS_blog/
Soil moisture retrievals January - July 2010
Next Steps!• Keep on Cal Val Activities
– merge with other missions sites– Nominal surfaces, Forests– More complex scenes– Quantitative assessments and limits
• Improve algorithms piece wise• Keep foot work on RFI reductions• Get feed back from others• Synergisms with other sensors• Level 3 and 4
YHK July 2010
YHK July 2010
Summary• SMOS delivers first global maps of soil
moisture and vegegation opacity • Still some issues but to be sorted out (CalVal
activities) but already very encouraging• Some improvements (Forested areas, roughness,
Dielectric constant modelling) already initiated• Need to Reprocess all data with up to date
algorithm from beginning (Australian campaign)• Need to have many groups addressing Cal Val• See also all presentation and posters today and ...
Yesterday!
• Visit our Blog http://www.cesbio.ups-tlse.fr/SMOS_blog/