1. Evaluation of the SMAP Combined Radar-Radiometer Soil Moisture Algorithm IGARSS 2011 Paper #3398 N. N. Das1 D. Entekhabi2 S. K. Chan1 R. S. Dunbar1 S. Kim1 E. G. Njoku1 J. C. Shi3 1Jet Propulsion Laboratory, California Institute of Technology, Pasadena, California 91109, USA 2Massachusetts Institute of Technology, Cambridge, MA 02139, USA 3University of California, Santa Barbara, CA 93106, USA

2. Overview of the SMAP Mission SMAP Measurements Approach Radar Frequency: 1.26 GHz Polarizations: VV, HH, HV Resolution: 3 km Relative Accuracy: 1.0 dB (HH ,VV), 1.5 dB (HV) Radiometer Frequency: 1.41 GHz Polarizations: H, V, 3rd & 4th Stokes Resolution: 40 km Relative Accuracy: 1.3 K Shared Antenna Constant Incidence Angle: 40º Wide Swath: 1000 km Orbit Sun-Synchronous, 6 am/pm Orbit, 680 km

4. SMAP Level 1 Science Requirements (1) North of 45°N Latitude (2) % volumetric water content, 1-sigma (3) % classification accuracy (binary: Freeze or Thaw)

5. Definitions and Data Products Flow nc = 1 L1C_TB TB TBdisaggregation (Das et al., Preliminary ATBD) (TGARS, submitted) C nm = 16 L2_SM_AP Merge Algorithms Mnm nf = 144 L1_S0_HiRes σ Fnf C= Coarse (~36 km Radiometer) Mnm= Medium (~9 km Merged Product) Fnf= Fine (~3 km Radar)

6. L2_SM_AP Radar-Radiometer TB Disaggregation Algorithm DOY, 2002 TBh~4 km σvv ~800 m 176 SMEX02 Temporal Changes in TBand σppare Related. Relationship Parameter β is Estimated Statistically at Radiometer C-Scale Using Successive Overpasses: 178 182 183 186 Same evaluated at scale Mj: 187 188 Subtract Two Equations to Write: 189 dB K R2(Low: 0.65, High: 0.93) values between TBhand σvv

7. L2_SM_AP Radar-Radiometer Algorithm Heterogeneity in Vegetation and Roughness Conditions Estimated by Sensitivities Γin Radar HV Cross-Pol: Based on PALS Observations From: SGP99, SMEX02, CLASIC and SMAPVEX08 TB-Disaggregation Algorithm is: TB( Mj) is Used to Retrieve Soil Moisture at 9 km

8. Active-Passive Algorithm Performance Active-Passive Algorithm RMSE: 0.033 [cm3 cm-3] Minimum Performance Algorithm RMSE: 0.055 [cm3 cm-3] Combined Airborne Data From: SGP99, SMEX02, CLASIC and SMAPVEX08

9. The Role of Cross-Pol in Capturing Heterogeneity Minimum Performance Algorithm RMSE: 0.055 [cm3 cm-3] Active-Passive Algorithm Without Cross-Pol RMSE: 0.043[cm3 cm-3] Active-Passive Algorithm RMSE: 0.033 [cm3 cm-3]

10. Assessment of L2_SM_AP Algorithm Using SMAP Algorithm Testbed Study region selected from the CONUS domain.

11. Sample of L3_SM_AP Output from SMAP Algorithm Testbed Global Composite Map of Soil Moisture for April 02 V/V

13. With current baseline approach, the algorithm meets the SMAP Level-1 requirements

14. Algorithm relies on radar co-pols and cross-pols

16. Develop and mature algorithm prior parameters database for Bayesian estimation