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/