The AFWA Next Generation Land Data Assimilation System

1. The AFWA Next Generation Land Data Assimilation System BACIMO 2005

2. Program Collaborators • John Eylander, HQ Air Force Weather Agency Meteorological Models Branch • Christa Peters-Lidard, NASA GSFC Hydrological Sciences Branch • Sujay Kumar, Univ. of Maryland at Baltimore County, Goddard Earth Sciences & Technology Center

3. AFWA AGRMET Modelcurrent capabilities • AFWA Agriculture Meteorology model (AGRMET) • Global Land Data Assimilation System (GLDAS) • Generates analyses soil moisture and soil temperature • Global ½ degree resolution • Every 3 hours

4. The AGRMET GLDAS Soil Temperature & Moisture (AGRMET) Analysis  Surface obs, GEOPRECIP, SNODEP, SSM/I merged to derive precip analysis GFS first guess combined with obs of T, u, v, RH to derive shelter analysis  Shelter Analysis  Precipitation Analysis Radiation Analysis CDFS II cloud analysis used to derive surface radiation analysis 

5. AFWA AGRMET Model • Current AGRMET customers include: • USDA Foreign Agriculture Service • AFWA Dust Transport Algorithm • AFWA WRF model • ARL White Sand Missile Range • AFWA CDFSII World Wide Merged Cloud Analysis • Naval Research Lab • AF Technology Application Center • Other modeling centers (NCEP, NWS Offices)

6. Land Information System • Developed at NASA GSFC • Demonstrate use NASA EOS program data (MODIS, TRMM) to analyze surface water states and energy fluxes • Computationally efficient • Parallel computing • Efficient I/O • Highly Configurable (Modular) • High Resolution Capability – resolutions up to 1 km • Multiple Land Surface Models

7. Land Information System AGRMET ½ degree resolution • LIS/AGRMET output comparison for southwest Asia Domain • LIS capable of much higher resolution output Volume Soil Moisture (m3/m3) 0-10cm Soil Depth LIS 15 km resolution LIS 1 km resolution

8. Land Information System Hi-res global background data sources • 1 km terrain elevation • 1 km 24-class USGS vegetation type • 5-minute FAO sand/silt/clay fractional soil type

9. Land Information SystemBackground Datasets Soil Clay Content Soil Sand Content Background soil types have dramatic effect on soil moisture output. 1 km test runs used 5 min UN FAO background soil types Soil type has an effect on the water retention capabilities within the soil Finer clay particles can retain (trap) water longer then larger loose sand particles Volume Soil Moisture Low Clay/High Sand Content affects soil moisture

10. Land Information SystemBackground Datasets • AGRMET soil texture database is coarse resolution • Categorical values refer to soil texture type (i.e sandy loam, or clay loam, or loamy sand) • General soil texture data based upon general soil type makeup

11. Land Information System AGRMET Volume Soil Moisture 1km LIS Volume Soil Moisture • Higher resolution background data + efficient software = higher resolution output • LIS terrain, background soil types, and vegetation datasets have significant impact on the analyzed soil moisture and soil temperature output

12. Land Information System • Initial system will be delivered in Spring 2006 • AGRMET merged precipitation analysis will be included in LIS • Observations, satellite IR and microwave, and climatology • AGRMET radiation scheme is being incorporated into LIS using the WWMCA • Initial Operational Capability date has not been determined

13. This is important Why? Land Information System

14. LIS ApplicabilityInitialize WRF land surface model • AGRMET will be used to initialize the AFWA WRF model • Coarse resolution AGRMET data will need to be interpolated onto higher resolution WRF grid • Interpolation of AGRMET data is a source of model initialization error! • LIS will provide land surface analysis of soil moisture and temperature on each WRF domain at same resolution and projection

15. LIS ApplicabilityTarget Acquisition Weapons Software • TAWS requires background surface data to aid target acquisition determination • TAWS currently uses a global 1o by 1o background surface characteristic look-up table • Pearcy (2005) determined improvement possible by using AGRMET data in place of look-up table • LIS could provide very high resolution background data to aid target acquisition calculations

16. LIS ApplicabilityTarget Acquisition Weapons Software

17. LIS Applicability Target Acquisition Weapons Software

18. LIS Applicability • Other potential applications • AFWA Dust Transport Algorithm • Better identify point sources • Other dispersion models • HPAC • Navy models? • Army Trafficability Tactical Decision Aids

19. Future Development Plan • Begin assimilating satellite observations of surface skin temperature using an Ensemble Kalman Filter • New methods to improve precipitation assimilation • Assimilation of real time remotely sensed vegetation conditions • Vegetation greeness fraction (i.e. NDVI) • Long term goals • Assimilate remotely sensed soil moisture data • Ensemble modeling using multiple land surface models

20. Summary • AFWA working with NASA on an AGRMET/LIS pilot study to benchmark the LIS system on AFWA similar architecture • Tentative LIS delivery to AFWA in April/May 2006 • Future development plan to continue integrating latest assimilation techniques into LIS • LIS provides a common framework between the R&D community and the operational modeling centers to speed the latest research into operations

21. Questions?

22. Backup Slides

23. AFWA AGRMET ModelInput data • Atmospheric temperature, humidity, and wind analyses from the National Centers for Environmental Predication (NCEP) Global Forecast System (GFS) • AGRMET Merged Precipitation Analysis • Surface obs, GEOPRECIP, WWMCA Precip algorithm, SSM/I Rain Rate EDR, climatology • Radiation calculated using the AFWA Cloud Depiction and Forecast System II (CDFSII) World Wide Merged Cloud Analysis (WWMCA) • Noah Community Land Surface Hydrology Module • Partners include NCEP, AFWA, and NCAR