1. Update status of soil moisture algorithm 2008.7.15 Joint AMSR Science Team Meeting, July 14-16, Telluride, CO H.Fujii (JAXA/EORC) and T.Koike(UT)

2. Defect of Koike's Algorithm "There are significant weaknesses in the JAXA product over vegetated sites" (T.J. Jackson, The GLI / AMSR workshop 2008 in Atami Japan, Jan.23,2008) AMSR-E In-situ (SCAN2027, LR, 5cm depth) 0 60 0 Fig: Scatter plots of AMSR-E Monthly Soil moisture (y-axis) versus in-situ data (x-axis) at the Little River,GA,USA Match-up Data Period January, 2003 -- December 2007 (60 months) In-Situ: -data source: SCAN 2027 Little River, GA, U.S.A -sensor depth ; 5cm -sampling method: observed data which has closest timestamp to AMSR-E observation time within 1 hour AMSR-E: -data source: JAXA product ver.5 Level2 -sampling method: closest FOV to the SCAN point within 5km range. monthly volumetric soil moisture in %

3. Update log of Koike’s algorithm March, 2004 : algorithm ver.3.01 (product ver.2-5) –Radiative transfer model for soil layer –Fractional vegetation cover, f c : T B = (1-f c )T B bare + f c T B vege March, 2008 : algorithm ver.5.11 (product ver.6) –Developing of the global data set of fractional vegetation cover, f c, (3 years average) from Terra/Aqua MODIS(LP DAAC). –Reconfiguration of vegetation parameter set, b and , based on the result of Ground Based Experiment. Jun, 2008 : algorithm ver.5.33 (prototype product) –Expansion of data period of f c global data set ( Jun 2002 - May 2008) –Reconfiguration of roughness parameter set, Q and h

4. Overview of Koike Algorithm Roughness parameter, Q-h AMSR-E / In-situ data CEOP Mongolia Ref. Site Vegetation parameter b-  Ground Based Experiment using the Microwave Radiometer Terra/Aqua MODIS Vegetation Indices (LP DAAC) MOD13A2/MYD13A2 (1km, 16days, v5) NDVI fc=1% fc=100% ・・・ Look-up Table Global Data Set of fractional vegetation cover,f c Period: Jun 2002 – May 2008 Data size: 8 days, 0.05x0.05 grid Resolution: equivalent size to AMSR-E 10GHz FOV fc model: Carlson and replay, 1997 Soil Moisture Algorithm T B bare T B vege bare soilvegetated surface Radiative Transfer Model

5. AMSR-E Global Soil Moisture Map 6-yeas average of July (2002-2007), Descending

6. Comparison of AMSR-E Soil Moisture and Precipitation map AMSR-E Soil Moisture - L2, Descending - Volumetric Soil Moisture [%] Precipitation : - Total amount of precipitation for 48 hours before AMSR-E observation. - Data source: GSMaP MVK hourly (JST-CREST/GSMaP )

7. Validation 1: 0.0 1.0 2003 Jan.Apr.Jul.Oct. EVI 0.2 0.4 0.6 0.8 (a) Gaize (b) B.Bolto(c) Little River (a)Gaize, Tibet, China. (CEOP) location: 32.30N, 84.05E (b)Balranald Bolto, NSW, Australira. (CEOP) location 34.658S, 143.549E (c)Little River, GA, USA. (SCAN, NRCS) location: 31.50N, 82.45W Seasonal Changes of EVI in 2003

8. Validation 1: New product (prototype) 0 30 60 0 30 60 0 30 60 0.0 1.0 2003 Jan.Apr.Jul.Oct. 40 EVI 0.2 0.4 0.6 0.8 20 0 40 20 0 40 Volumetric Soil Moisture [%] Daily Precipitation [ mm/day] Number of Data Des. 214 Asc. 200 Number of Data Des. 217 Asc. 223 Number of Data Des. 200 Asc. 198 (a) Gaize (b) B.Bolto(c) Little River (a) Tibet Gaize sensor depth 3cm (1.5 - 4.5cm) (b) Balranald Bolto sensor depth 0-7cm (c) Little River sensor depth 5cm (3-7cm)

9. Validation 1: JAXA product (ver.5) 0 30 60 0 30 60 0 30 60 0.0 1.0 Apr.Jul.Oct. 40 EVI 0.2 0.4 0.6 0.8 20 0 40 20 0 40 Volumetric Soil Moisture [%] Daily Precipitation [ mm/day] (a) Tibet Gaize sensor depth 3cm (1.5 - 4.5cm) (b) Balranald Bolto sensor depth 0-7cm (c) Little River sensor depth 5cm (3-7cm) 2003 Jan. Number of Data Des. 93 Asc. 167 Number of Data Des. 206 Asc. 220 Number of Data Des. 187 Asc. 184 (a) Gaize (b) B.Bolto(c) Little River

10. Validation 2: Monthly Soil Moisture at LR. AlgorithmOrbitBiasRMSEMAE (a) JAXA ver.5 Des. 11.54.811.5 Asc. 9.04.29.0 (b) new (Prototype) Des. 3.12.53.5 Asc. 2.92.43.5 Scatter plots of AMSR-E monthly averaged soil moisture(y-axis) versus in-situ data at Little River, GA in U.S.A.. The data period is from January 2003 to December 2007 (60 months). unit: volumetric soil moisture in % (b) New Product (prototype) In-situ (SCAN 2027, LR, 5cm) AMSR-E 0 60 0 1020304050 10 20 30 50 40 (a) JAXA product ver.5 In-situ (SCAN 2027, LR, 5cm) AMSR-E 0 60 0 1020304050 10 20 30 50 40

11. Summary The new global data set of fractional vegetation cover, f c, is introduced into the algorithm The roughness parameter calibrated at Mongolia is used in the Ratiative Transfer Model. The algorithm validated at Little River and the result showed that the accuracy was improved by comparing the old algorithms. Near future plan. Masking method for uniformly and dense vegetated area. Behavior of the algorithm in Sahara

14. Impact evaluation of interannual variation of vegetation cover on AMSR-E Soil Moisture retrieval. (a) f c : actual time (b) f c : 6 years average (c) Difference ( b – a ) July, 2003, Descending, Monthly average.

15. Monthly Soil Moisture Map in Africa (July, 2003)