1. Recent Improvements and Ecological Applications of the UMT AMSR Land Parameter Record Jinyang Du, Lucas A. Jones, and John S. Kimball Numerical Terradynamic Simulation Group and Flathead Lake Biological Station, Division of Biological Sciences, The University of Montana AMSR Science Team Meeting 16-17 September 2015 Huntsville, AL

2. AMSR Science Team Meeting 16-17 September 2015, Huntsville, AL OVERVIEW Continuing efforts to improve retrieval algorithms & continuity of the AMSR- E/2 land parameter record for better detection & understanding of environmental changes & hydro/ecological impacts.  New approach developed for global satellite estimation & monitoring of surface soil moisture from the AMSR sensors using a dynamic albedo method;  New method developed to characterize terrestrial open water inundation dynamics with enhanced (6.25 km) resolution & 10-day fidelity using higher frequency (89 GHz) AMSR-E/2 observations.  Highlights of recent ecological application studies using the UMT AMSR global land parameter record, incl. SMAP Cal/Val support.

3. AMSR Science Team Meeting 16-17 September 2015, Huntsville, AL Soil Moisture Algorithm Refinement Using Variable Scattering Albedo

4. AMSR Science Team Meeting 16-17 September 2015, Huntsville, AL Algorithm Flowchart Temperature Algorithm Tb 6.9 or 10.7 V & H pol.Tb 18.7, 23.8 V & H pol. 60-day running smoother Estimate slope parameter: Estimate emissivity Invert for VOD (assume dry baseline soil conditions) Invert for SM using dynamic albedos

5. AMSR Science Team Meeting 16-17 September 2015, Huntsville, AL Study Sites for Algorithm Development and Validation Spatial distribution of ISMN Sites used for developing the revised algorithm; independent validation site network locations; background images represent the MODIS IGBP global land cover map

6. AMSR Science Team Meeting 16-17 September 2015, Huntsville, AL Effective Scattering Albedo and its relationship with VOD  A general quadratic relationship between VOD and Effective Scattering Albedo was found.  As VOD increases, multiple scattering effects become more significant and counteract increased scattering from vegetation Effective Scattering Albedo is associated with single scattering, but also parameterizes more complex vegetation scattering effects involving multiple scattering mechanisms and interactions between the canopy and ground.

7. AMSR Science Team Meeting 16-17 September 2015, Huntsville, AL Impact of Inaccurate Albedo on Soil moisture estimation  Underestimated albedo results in overestimation of soil moisture and vice versa.  The soil moisture estimation error also increases exponentially at higher VOD levels for a given albedo error level Solution Empirical estimation of albedo values based on VOD Albedo optimization strategy based on uncertainty analysis

8. AMSR Science Team Meeting 16-17 September 2015, Huntsville, AL Optimization of Effective Scattering Albedo Step 1: Initial estimation of Albedo Empirical estimation of albedo at X-band (10.7 GHz) based on the albedo database derived from in-situ measurements for respective moderate and dense vegetation Step 2: Error distributions Analysis Error distributions of estimated V- polarized emissivity values are approximated by a normal distribution. Step 3: Albedo Optimization Optimization process to evaluate the possibility of the potential values so that the optimum one can be obtained for soil moisture retrieval

9. AMSR Science Team Meeting 16-17 September 2015, Huntsville, AL Soil Moisture Inversion Results– Global Pattern Soil moisture from the revised algorithm shows improved spatial distribution and temporal dynamics over the global domain.

10. AMSR Science Team Meeting 16-17 September 2015, Huntsville, AL Soil Moisture Inversion Results – Quantitative Analysis Improved soil moisture inversion performance from the revised algorithm in four global validation regions, with R 2 agreement between retrievals and in- situ measurements increasing by ~16.9% and 41.5%, and bias-corrected RMSEs decreasing by ~25.0% and 38.2% for respective ascending and descending orbits.

11. AMSR Science Team Meeting 16-17 September 2015, Huntsville, AL AMSR 89GHz Fractional Cover of Surface Open water Inundation Retrieval and Analysis

12. AMSR Science Team Meeting 16-17 September 2015, Huntsville, AL Fractional Cover of Surface Open water Inundation – Results A new method to assess land-surface fractional open water (fw) inundation dynamics is being developed using high frequency (89 GHz) Tb from AMSR sensors. The resulting fw estimates provide enhanced (6.25 km) resolution relative to other passive microwave sensor based land observations, with 10-day temporal fidelity.  Important for understanding hydrological and biogeochemical processes in Earth System models.  Required to reduce uncertainty in land surface parameters obtained through microwave remote sensing  The UMT AMSR-E global land parameter record provides consistent global daily time series maps of fw; however, the relatively coarse (25-km) resolution of the fw record limits its capabilities for environmental changes studies. Difference between 89GHz fw summer composite and that of UMT baseline fw product

13. AMSR Science Team Meeting 16-17 September 2015, Huntsville, AL Recent Ecological Application Studies

14. Asynchronous Amazon Forest Canopy Phenology Indicates Adaptation to both Water and Light Availability Matthew O. Jones, John S. Kimball, Ramakrishna R. Nemani, 2014, Environmental Research Letters, 9, 124021 Six synergistic satellite records show distinctive seasonal signals over Amazon forests that follow adaptations to light and water availability. Monthly climatology (2003- 2011) of PAR, TWS, VOD, & LAI for 3 ecoregions; bars are mean dry months per year (TRMM). Major Findings Canopy biomass growth (VOD) and net leaf flush (LAI) become more synchronous as dry season length increases. Seasonal lags between biomass growth, green leaf area, and available resources enable mapping of seasonal canopy adaptations to light and water. Improved understanding of tropical forest seasonality and drought sensitivity. Sponsor: NASA Earth Science program a b c Seasonal canopy adaptation to light or water availability Remote Sensing Data GRACE Terrestrial Water Storage (TWS); AMSR-E Vegetation Optical Depth (VOD); MODIS Leaf Area Index (LAI); CERES Photosynthetically Active Radiation (PAR); TRMM PRCP; MODIS MAIAC EVI Dry months (<100mm) per year (TRMM)

15. SMAP FT validation activities underway using higher frequency (36 GHz) FT records from AMSR-E historical & AMSR2 operational datasets; Potential synergy between higher & lower frequency FT retrievals; Comparisons to refine FT algorithms & retrievals from both SMAP active & passive L- band data SMAP L3_FT (L-band) AMSR-2 (K-band) Landscape Freeze-Thaw (FT) Dynamics from AMSR and SMAP Courtesy: Xiaolan Xu (JPL) and Youngwook Kim (UMT)

16. AMSR Science Team Meeting 16-17 September 2015, Huntsville, AL Summary New developments on UMT Global Land Parameter algorithms were made to the AMSR 1 sensors with improved accuracy in soil moisture retrievals. The study provides insight into general microwave remote sensing challenges common to other microwave Earth observation missions. The new approach and associated 6.25 km fractional water record is complimentary with the 25 km retrievals from the existing UMT AMSR-E land parameter record, by providing enhanced spatial delineation of open water dynamics and approximately 10-day temporal repeat monitoring capabilities. Continuing calibration & extension of UMT record planned in support of several global ecosystem studies as well as on-going L-band SMAP mission. –Tb calibration methodology (Seasonal Sensor Bias). 1 AMSR sensors include AMSR-E V7 reprocessed T b record provided by Remote Sensing Systems; AMSR2 L1R data are from JAXA

17. AMSR Science Team Meeting 16-17 September 2015, Huntsville, AL Recent Publications Journal papers: Du, J., J.S. Kimball, and L.A. Jones, 2015. Passive microwave remote sensing of soil moisture based on dynamic vegetation scattering properties for AMSR-E. TGARS (In-press). Du, J., J.S. Kimball, J.C. Shi, L.A. Jones, S.L. Wu, R.J. Sun, and H. Yang, 2014. Intercalibration of satellite passive microwave land observations from AMSR-E and AMSR2 using overlapping FY3B-MWRI sensor measurements. Remote Sensing 6, 8594-8616. Du, J., J.S. Kimball, and L.A. Jones, 2015. Satellite microwave retrieval of total precipitable water vapor and surface air temperature over land from AMSR2. TGARS 53(5), 2520-2531. Jones, M.O., J.S. Kimball, and R.R. Nemani, 2014. Asynchronous Amazon forest canopy phenology indicates adaptation to both water and light availability. Environmental Research Letters 9, 124021.