Slide 1/32NOAA Soil Moisture/Soil Temperature Workshop, Oak Ridge, TN, 3-5 March, 2009 Value of Ground Network Observations in Development of Satellite Soil Moisture Data Products X. Zhan 1, J. Liu 1, M. Cosh 2, T. Jackson 2, and Y. Yu 1 1 NOAA-NESDIS Center for Satellite Applications and Research, Camp Springs, MD 2 USDA-ARS Hydrology and Remote Sensing Lab, Beltsville, MD

Slide 2/32NOAA Soil Moisture/Soil Temperature Workshop, Oak Ridge, TN, 3-5 March, 2009 OUTLINE  Satellite SM data  Ground SM and ST observations  Results and issues in comparing them  Suggestions for USCRN

Slide 3/32NOAA Soil Moisture/Soil Temperature Workshop, Oak Ridge, TN, 3-5 March, 2009  VUT ESCAT/ASCAT (Wagner et al, 1999)  USDA TMI (Bindlish et al, 2003)  Princeton TMI (Gao et al, 2006)  NASA AMSR-E (Njoku et al, 2003)  USDA AMSR-E (Jackson et al, 2007)  VUA AMSR-E (Owe et al, 2008)  USDA WindSat (Jackson et al, 2008)  NRL WindSat (Li et al, 2008) Satellite Soil Moisture Data Products:

Slide 4/32NOAA Soil Moisture/Soil Temperature Workshop, Oak Ridge, TN, 3-5 March, 2009 USDA TMI (Bindlish et al, 2003): USDA TMI (Bindlish et al, 2003) : Daily estimates, from July 06 to July 21, – 0.52%v/v

Slide 5/32NOAA Soil Moisture/Soil Temperature Workshop, Oak Ridge, TN, 3-5 March, 2009 Princeton University TMI (Gao et al, 2006): Princeton University TMI (Gao et al, 2006) : Jan. 1, 1999 with quality masks applied

Slide 6/32NOAA Soil Moisture/Soil Temperature Workshop, Oak Ridge, TN, 3-5 March, 2009 NASA AMSR-E (Njoku et al, 2003): NASA AMSR-E (Njoku et al, 2003) : Within US: 0.1 – 0.2 v/v

Slide 7/32NOAA Soil Moisture/Soil Temperature Workshop, Oak Ridge, TN, 3-5 March, 2009 VUA-GSFC AMSR-E (Owe et al, 2008): VUA-GSFC AMSR-E (Owe et al, 2008) : Monthly for July 2003: Top: 6.9GHz Bottom: 10.7 GHz

Slide 8/32NOAA Soil Moisture/Soil Temperature Workshop, Oak Ridge, TN, 3-5 March, 2009 USDA WindSat (Jackson et al, 2008): USDA WindSat (Jackson et al, 2008) : WindSat global volumetric soil moisture (%) for July 30, – 0.5 v/v

Slide 9/32NOAA Soil Moisture/Soil Temperature Workshop, Oak Ridge, TN, 3-5 March, 2009 NRL WindSat (Li et al, 2008): NRL WindSat (Li et al, 2008) : WindSat global volumetric soil moisture (%) and vegetation water content (kg/m2) retrievals for 1 – 12 September 2003.

Slide 10/32NOAA Soil Moisture/Soil Temperature Workshop, Oak Ridge, TN, 3-5 March, 2009 MetOp ASCAT (Wagner et al, 1999): MetOp ASCAT (Wagner et al, 1999) : VUT ASCAT soil moisture is actually soil wetness, could be converted to volumetric soil moisture by dividing them with their soil porosity

Slide 11/32NOAA Soil Moisture/Soil Temperature Workshop, Oak Ridge, TN, 3-5 March, 2009  Watershed SM Vitel Network (2001- present)  Soil Climate Analysis Network (1996- present)  Surface Radiation Budget Network (1993- present)  US Climate Reference Network (2002- present) Ground SM & ST Observations:

Slide 12/32NOAA Soil Moisture/Soil Temperature Workshop, Oak Ridge, TN, 3-5 March, 2009 USDA-ARS Watershed SM Vitel Network: LW: Little Washita, OK WG: Walnut Gulch, AZ AMSR-E U.S. Soil Moisture Validation Sites RC: Reynolds Creek, ID LR: Little River, GA

Slide 13/32NOAA Soil Moisture/Soil Temperature Workshop, Oak Ridge, TN, 3-5 March, 2009 USDA-ARS Watershed SM Vitel Network:  Multiple sites within a satellite footprint  Rain gauge overlay SM sites  Multiple layers (5cm, 15cm, 30cm)  Continuous data sampling (30 min.)  Stevens-Vitel Hydra Probes WG LW RC LR

Slide 14/32NOAA Soil Moisture/Soil Temperature Workshop, Oak Ridge, TN, 3-5 March, 2009 USDA-NRCS Soil Climate Analysis Network (SCAN):  Mostly single site in a satellite footprint  Rain gauge at the same site  Multiple layers (2”, 4”, 8”, 20”, 40”)  Hourly data  Hydra Probes

Slide 15/32NOAA Soil Moisture/Soil Temperature Workshop, Oak Ridge, TN, 3-5 March, 2009 NOAA Surface Radiation Budget Network (SurfRad):  6 sites from 1995 and 1 site from 2003  Mainly solar and thermal radiation  LST observational Data  Sample per 1 or 3 minutes  Precision Infrared Radiometer s

Slide 16/32NOAA Soil Moisture/Soil Temperature Workshop, Oak Ridge, TN, 3-5 March, 2009 NOAA Climate Reference Network (USCRN):  >100 stations with a few paired ones  Most climate variables including precipitation  SM/ST planned  SM/ST Sample freq ?  SM/ST sensors ?

Slide 17/32NOAA Soil Moisture/Soil Temperature Workshop, Oak Ridge, TN, 3-5 March, 2009 Validating AMSR-E Soil Moisture Retrievals: with Watershed SM Vitel Network (USDA-ARS)

Slide 18/32NOAA Soil Moisture/Soil Temperature Workshop, Oak Ridge, TN, 3-5 March, 2009 Validating AMSR-E Soil Moisture Retrievals: with SCAN Data (USDA-NRCS)

Slide 19/32NOAA Soil Moisture/Soil Temperature Workshop, Oak Ridge, TN, 3-5 March, 2009 Validating Multiple Soil Moisture Retrievals: with SCAN Data (USDA-NRCS)

Slide 20/32NOAA Soil Moisture/Soil Temperature Workshop, Oak Ridge, TN, 3-5 March, 2009 Evaluating LST Estimates (T skin ) for SM Retrievals: T B,i cmp = T skin {e r,p exp (-  i /cos  ) + (1 –  ) [1 – exp (-  i /cos  )] [1 + R r,i exp (-  i /cos  )]}  i = b *VWC R r,i = R s exp(h cos 2 θ) R s = f(ε) -- Fresnel Equation ε = g(SM) -- Mixing model T B,i obs = T B06h, T B06v, T B10h, T B10v, T B18h, T B18v Multi-channel Inversion (MCI) Algorithm (Njoku & Li, 1999):

Slide 21/32NOAA Soil Moisture/Soil Temperature Workshop, Oak Ridge, TN, 3-5 March, 2009 Evaluating LST Estimates (T skin ) for SM Retrievals: T B10h = T s [1 –R r exp (-2  /cos  )] R r = R s exp(h cos 2 θ) R s = f(ε) -- Fresnel Equation ε = g(SM) -- Mixing model T s = reg 1 (T B37v ) or T s LSM  = b * VWC VWC= reg 2 (NDVI) Single Channel Retrieval (SCR) Algorithm (Jackson, 1993):

Slide 22/32NOAA Soil Moisture/Soil Temperature Workshop, Oak Ridge, TN, 3-5 March, 2009 Evaluating NCEP-GDAS T skin Estimates: withSurfRad(NOAA)

Slide 23/32NOAA Soil Moisture/Soil Temperature Workshop, Oak Ridge, TN, 3-5 March, 2009 Evaluating NCEP-GDAS T skin Estimates: withSurfRad(NOAA)

Slide 24/32NOAA Soil Moisture/Soil Temperature Workshop, Oak Ridge, TN, 3-5 March, 2009 Evaluating NCEP-GDAS T skin Estimates: withSurfRad(NOAA)

Slide 25/32NOAA Soil Moisture/Soil Temperature Workshop, Oak Ridge, TN, 3-5 March, 2009 Evaluating T skin Estimates from AMSR-E TB36v:

Slide 26/32NOAA Soil Moisture/Soil Temperature Workshop, Oak Ridge, TN, 3-5 March, 2009 Evaluating T skin Estimates from AMSR-E TB36v:

Slide 27/32NOAA Soil Moisture/Soil Temperature Workshop, Oak Ridge, TN, 3-5 March, 2009 Evaluating T skin Estimates from AMSR-E TB36v:

Slide 28/32NOAA Soil Moisture/Soil Temperature Workshop, Oak Ridge, TN, 3-5 March, 2009 Issues in Satellite SM Validation with in situ Data: 1.Footprint representation/ heterogeneity issue

Slide 29/32NOAA Soil Moisture/Soil Temperature Workshop, Oak Ridge, TN, 3-5 March, 2009 Issues in Satellite SM Validation with in situ Data: 2.Hydra probe depth vs satellite sensor depth  SCAN probe depth: 2”, 4”, 8”, 20”, 40”  USDA Vitel Network: 5cm, 15cm, 30cm  Noah LSM depth: 10cm, 40cm, 100cm, 200cm  AMSR-E (C-band) sensible depth: < 2cm  SMAP (L-band): < 5cm  USCRN: ?

Slide 30/32NOAA Soil Moisture/Soil Temperature Workshop, Oak Ridge, TN, 3-5 March, 2009 Issues in Satellite SM Validation with in situ Data: 3.Hydra Probe calibration standardization

Slide 31/32NOAA Soil Moisture/Soil Temperature Workshop, Oak Ridge, TN, 3-5 March, 2009  Representation issue: Identify those sites with good area landscape heterogeneity for SM/ST sensor installation if not all sites;  Probe depth issue: Consider future operational or long term C/X-band satellite sensors (MIS, AMSR2, GPM, etc) as well as L-band sensors (SMOS, SMAP);  Data quality issue: Plan frequent sensor calibration based on timely data analysis;  LST (T skin ): LST observations are desirable for both satellite (SM/ST) data products validation and climate monitoring;  Data access: Open, timely, and convenient access to USCRN data benefits all of their potential applications (drought monitoring, satellite data validation, etc) SUGGESTIONS FOR USCRN

Slide 32/32NOAA Soil Moisture/Soil Temperature Workshop, Oak Ridge, TN, 3-5 March, 2009  Currently available satellite SM data products are significantly differing from each other and their qualities need to be improved for operational uses;  SM ground measurements are useful for satellite SM/ST data product validation and verification of land surface model SM/ST data assimilation;  There are spaces for improving the ground SM/ST measurement quality with consideration to satellite footprint representation, sensor depth, calibration standardization and open, timely, convenient data access;  In addition to soil temperature measurements, Land Surface Temperature (T skin ) observations are also desirable for satellite (SM/ST) data product validations; SUMMARY