1. NASA Drought Project Meeting
October 2009
National Drought Monitoring System for Drought Early Warning Using Hydrologic and Ecologic Observations from NASA Satellite Data
S. V. Nghiem and G. Neumann
Jet Propulsion Laboratory
California Institute of Technology
Pasadena, California 91109

2. Investigator Team • Brakenridge, G.R.: Dartmouth College
• Dole, R.: NOAA Physical Science Division
• Le Comte, D.: NOAA Climate Prediction Center
• Nghiem, S.V.: Jet Propulsion Laboratory
• Njoku, E.G.: Jet Propulsion Laboratory
• Verdin, J.: U.S. Geological Survey
• Wilhite, D.: National Drought Mitigation
Center
Advisory Board: D. Entekhabi (MIT), D. Hall (NASA GSFC), P. Houser (George Mason U.), A. Huete (U. Arizona), G. Leshkevich (NOAA GLERL), K. Steffen (U. Colorado/CIRES), and P. Whung (USDA).

3. Overall Objectives National Drought Monitoring System (NDMS)
Enhancing U.S. Drought Monitor (USDM)
Potential NASA data use for drought forecast
Utilizing NASA satellite data/results: AMSR-E microwave radiometer, QuikSCAT microwave scatterometer, MODIS spectro-radiometer, and ASTER radiometer
Integrating with diverse indicators to monitor major components of hydrologic and ecologic system
Prototype demonstration and validation
Near-term goal: Applications to NIDIS.
Long-term goal: Expandable to GEOSS.

4. Soil Moisture Change Algorithm Soil Moisture Algorithm
National Drought Monitoring System Using NASA Data/Results – Wiring Diagram
QuikSCAT
AMSR-E
ASTER
Terra & Aqua
MODIS
Receiving Stations
Receiving Stations
Receiving Stations
Soil Moisture Change Algorithm
NDVI Algorithm
Soil Moisture Algorithm
NDVI Algorithm
Reservoir Algorithm
JPL Data System
USGS Data System
DFO Data System
Surface Obs
Networks
Climatic
Data
US DROUGHT MONITOR
NDMC, NOAA, USGS, …
V&V

5. Integrated System Solution: National Drought Information System
NASA Water Management Project: National Drought Monitoring System
Earth System
Satellite Algorithms
AMSR-E algorithms (JPL)
Soil moisture
Vegetation water content
QuikSCAT algorithms (JPL)
Precipitation water change on
land surface
Precipitation frequency
Experimental NDVI
MODIS/ASTER algorithms
Vegetation indices (USGS)
Lake/reservoir area (DFO)
Predictions/Forecasts
Decision Support Systems, Assessments, Management Actions
National Integrated Drought Information System
US Drought Monitor
Weekly map and web portal
Analyses and Forecast
Early Drought Detection
Drought Spatial Extent
Drought State/Drought Severity
Drought duration
Decisions / Actions
Drought Plans Activated
Urban Water Restrictions
Drought Assistance Programs
Agricultural Choices for Water Conservation
Information products
Water Monitoring
Soil moisture change
Precipitation frequency
Lake/reservoir change
Vegetation Monitoring
Vegetation Indices
Season start
Season length
Drought Indices
Palmer Drought index
Standardized
Precipitation Index
Stream flow percentile
Soil moisture percentile
Drought indicator blend
Value & Benefits
to Society
Quantitative and qualitative benefits from improved decisions
Wider dissemination of
drought information
Improved understanding of
drought effects at sub-
county scale
Quicker response for State
Drought Task Forces and
State Governors
Increased spatial precision
in drought emergency
designations
Better informed state and
local decision making
leading to more effective
use of available water and
drought relief program
resources
Earth Observations
NASA Satellite Data:
- AMSR-E Radiometer
- QuikSCATScatterometer
MODIS Spectroradiometer
ASTER Radiometer
Surface Data:
- Weather station networks
Soil moisture : SCAN
Network, SNOTEL Network
- Long-term stations
- Surface radars
Observations, Parameters & Products

6. JPL Status and Progress
Three-year project: Year-1 completed; Year-2 completed; Year-3 started (funds on open account Sep. 2009).
JPL Year 2:
Providing QuikSCAT soil moisture change (SMC) data for drought applications: data for entire CONUS, daily data production, nearly daily of CONUS, and automated routine upload processor is ready. (AMSR-E soil moisture data available from NSIDC).
Resolution benchmarking: SMC data gridded at ¼ degree in latitude and longitude, resolving county scale per Nyquist scale requirement estimated at 27 km.
Demonstration of improvement (all) – JPL automated SMC data upload to NOAA Physical Science Division.
Publications: Drought related meeting abstracts, paper manuscript on going.
Programmatic: Subcontracts to all, Year-2 extension to all; Meetings with NASA and NASA reports.

7. JPL Year 3 Work Plan
Three-year project: Year-1 completed; Year-2 completed; Year-3 started (funds on open account Sep. 2009).
JPL Year 3 Plan:
Incorporating latest satellite algorithm improvements and advanced NASA products/results for drought monitoring: Improving SMC algorithms and products, initiating and testing new QS products for drought monitoring/forecast.
Participation in refinements of prototype products, ingestion of NASA results in into the USDM operational environment for decision support, improvement of drought forecast, and system performance evaluation and verification.
Participation in demonstration of improvements for drought monitoring and forecast.
Publications: Drought related meeting abstracts, journal paper and/or book chapter.
Programmatic: Meetings with NASA and NASA reports.

8. Infrastructure for Soil Moisture Change
Automated Processing and Production
L1B
QuikSCAT Scatteromter Data Bank
JPL SMC Processor
SMC Data Archive
SMC Map Archive
NOAA PSD Processor
NDMC Vectors
Ancillary Overlay
3 Color Protocols
Png, Pdf, Kmz
9 SMC Products
DrtVector +Options
Posting
Automatic JPL-NOAA PSD Upload
Prototypes

9. Texas SMC in Sep-Oct 2009
9/06
9/10
9/11
9/13
9/14
9/15
9/22
10/4

10. Wet Precipitation Frequency (WPF)
Experimental WPF Product in development

11. Wet Precipitation Frequency (WPF)
Experimental WPF Product in development
OND
T3/31/Va
Red 15
Green 10

12. Summary Automated processing of SMC (1-2 day delay)
Automated uploading of SMC to NOAA PDS
Identifying potential improvements: Multiple passes, azimuth specular return, averaging duration to account for severe rain events
Experimental products for wet precipitation frequency: monthly, seasonally, annually – forward and backward in time
Potential new products: number of days since last wet precipitation event