1. Development of Rapid Prototyping Capability to Evaluate Potential Uses of NASA Research Products and Technologies to Estimate Distribution of Mold Spore Levels over Space and Time RPC Review Meeting July 10 and 11, 2007 Mississippi State University University of Mississippi Medical Center

2. Team Members UMMC  Fazlay S. Faruque, PhD, GIS and Remote Sensing  Gailen Marshall, MD, PhD, Division of Allergy & Clinical  Richard Finley, MD, Division of Emergency Medicine  Bruce Brackin, Agro-medicine  Hui Li, PhD, GIS and Remote Sensing  Worth Williams, GIS and Remote Sensing  Sheila Belk, MD, Division of Allergy & Clinical Immunology GSFC/NASA  Steve Kempler, DAAC, Goddard Earth Sciences (GES), DISC  Gregory Leptoukh, PhD, Goddard Earth Sciences (GES), DISC SSAI  Robert E. Ryan, PhD, SSAI, Stennis Space Center  Kenton W. Ross, PhD, SSAI, Stennis Space Center MSU  Charles O'Hara, PhD, Geo Resources Institute (GRI)

3. Data and Research Products to be Used  NASA Earth-Sun Science Product:  NPP VIIRS (Vegetation Moisture Index)  GPM DPR (Precipitation)  NPP CrIS and ATMS (Humidity)  AMSR-e (Soil moisture)  Non-NASA Products:  Mold spore samples  Temperature  Humidity  Wind

4. 1.Kick off meeting among team members 2.Evaluation/review of RPC system requirements 3.Requisition of ground monitoring equipment and accessories for collecting mold spore and weather data 4.Installation of ground sampling facilities 5.Draft report on capabilities and preliminary design 6.Accessing required NASA data and products 7.Accessing required weather model and data 8.Begin ground data collection and analysis 9.Quarterly meeting First Quarter Milestones

5. Kick off Meeting Date: March 28, 2007 ParticipantsUMMC  Fazlay S. Faruque  Gailen Marshall  Richard Finley  Bruce Brackin  Hui Li  Worth Williams  Sheila Belk SSAIC  Robert E. Ryan  Kenton W. Ross Goddard  Steve Kempler

6. Kick off meeting Tasks for University of Mississippi Medical Center 1.Coordinate team meetings 2.Coordinate meetings with the funding agency 3.Install ground monitoring stations 1.Install volumetric mold spore traps and accessories 2.Install self-powered weather stations with data loggers to record: wind speed, and direction, wind chill, dew point, air temperature, relative humidity, and rainfall 4.Maintain ground monitoring stations 5.Collect ground monitored mold and meteorological data 6.Analyze ground monitored mold spores 7.Evaluate/review RPC system requirements 8.Evaluate NASA data against ground monitored meteorological data 9.Analyze associations between ground monitored meteorological data and ground monitored mold counts 10.Develop mold estimation model using evaluated NASA products and NOAA weather data 11.Evaluate NASA product-derived mold estimation model using independent ground monitored mold counts 12.Make necessary adjustments to the mold estimation model 13.Organize product demonstrations to the public health community 14.Prepare reports 15.Develop manuscripts 16.Conduct presentations

7. Kick off meeting Tasks for GFSC GSFC will provide necessary data, tools and expertise required for this project. Deliverables by GSFC will be as follows: Data a) Dual-frequency Precipitation Radar (DPR) data [Global Precipitation Measurement Mission (GPM)] to estimate precipitation of the study area; b) Cross-track Infrared Sounder (CrIS) data and Advanced Technology Microwave Sounder (ATMS) data [NASA NPOESS Preparatory Project (NPP)] to estimate humidity of the study area; c) Advanced Microwave Scanning Radiometer for EOS (AMSR-E) data to estimate soil moisture of the study area. Data will be provided in best possible spatial resolution so that variation within the study area could be analyzed. The minimum temporal resolution requirement of the data is per day. Data will cover the study area and an additional 30 miles (approximately) around the periphery of the study area. Data will be provided in a format so that it could be readily accessed and analyzed.

8. Kick off Meeting Tasks for GFSC (cont.) Tool GSFC will provide following operational, or near operational tools for data access, dissemination and RPC development: GES-DISC Interactive Online Visualization ANd aNalysis Infrastructure (Giovanni) interactive data exploration tool Parameter and spatial subsetting tools Simple, Scalable, Script-based Science Processor for Measurements (S4PM) and Simple, Scalable, Script-based Science Processor Archives (S4PA) Expertise GSFC will provide expertise to support the collaborators developing an RPC for this project. Provided expertise will include: Earth science data management, visualization, production, archive, distribution, and servicing expertise Earth science data format and organization expertise Earth science data system and tool development GIS expertise to complement those possessed by collaborators, for converting native formatted Earth science data into a GIS format Interpreting Earth science data for science and applications research Steven Kempler and his designee will be the investigators working on this project

9. Kick off Meeting Tasks for SSAI SSAI will provide appropriate data and expertise to successfully develop the RPC of this project. SSAI deliverables will be as follows: Data SSAI will provide simulated and filtered VIIRS (the Visible/Infrared Imager Radiometer Suite) data to estimate the vegetation moisture index of the study area and required time period. A robust uncertainty analysis of the vegetation moisture index data will be conducted as well. To generate useful VIIRS simulated data SSAI will use tools such as ART and TSPT as necessary. Data will be provided in best possible spatial resolution so that variation within the study area could be analyzed. The minimum temporal resolution requirement of the data is per day. Data will cover the study area and an additional 30 miles (approximately) around the periphery of the study area. Data will be provided in a format so that it could be readily accessed and analyzed.

10. Kick off Meeting Tasks for SSAI (cont.) Normalized Difference Moisture Index (NDMI) Using appropriate simulated NASA data, SSAI will provide an NDMI for the study area for the required time period. Expertise To successfully develop an RPC for this project, SSAI will provide expertise in the areas of: remote sensing calibration and validation systems engineering integration of Earth observation inputs into decision support frameworks simulation of future datasets Additionally, SSAI will assist UMMC with spatial statistical expertise to develop mold spore estimation models. Kenton Ross and Robert Ryan are the SSC/ITS investigators working with this project.

11. Kick off Meeting Tasks for MSU Dr. Charles G. O’Hara from Mississippi State University’s GeoResources Institute will serve as a member of the project team and will provide assistance with VIIRS simulations. He will also provide specialized expertise in defining needs for project data, including the range of temporal frequencies for cloud-free composites. Expertise to be provided by Dr. Charles G. O’Hara will be as follows: 1.Provide assistance with VIIRS simulations. 2.Provide specialized expertise in defining needs for project data, including the range of temporal frequencies for cloud-free composites. 3.Work with the other team members to create desired multi-temporal composites needed to evaluate the correlation between plant vigor and other factors that contribute to asthma, allergies, and sinus-related health issues

12. Kick off meeting Other Discussions Ground samples and satellite data will be collected for at least one year to cover all seasonal variations Satellite data will cover study area -and an additional 30 miles (approximately) around the periphery of the study area Process of procuring mold samplers from UK Ground sample collection methods Mold spore collection, reading and storage

13. Evaluation/Review of RPC System Requirements  NASA Products  Weather model data  Ground measurements

14. Predictions and Measurements: Temperature Precipitation Humidity Soil Moisture Wind Solar radiation Amount and type of mold spores (from field samples) Earth System Model: Mold growth conditions Decision Support: Estimation of mold over time and space using NASA data Benefits: Continuous coverage for estimated mold forecasting Potential of global adaptation Potential for forecasting with more precise level and more precise location Potential for reducing health burden due to mold related allergy problems Earth Observations: NPP VIIRS AMSR-E NPP CrIS NPP ATMS GPM DPR Field Data: Mold spore Meteorological From Existing Weather Model: Meteorological Data RPC Experiment using NASA’s NPP VIIRS, NPP CrIS NPP ATMS and GPM DPR data for mold spore level estimation

15. NASA data in association with other meteorological data for estimation of mold spore level distribution.

16. Weather Parameters and Measurements Ground Instruments Primary Environmental Parameters NASA Products WatchDog Weather Station #3340WD2 Precipitation /Rainfall GPM (Proxy) DPR WatchDog – Leaf wetness Sensor #3666 Vegetation Moisture Index NPP (Simulated) VIIRS WatchDog Weather Station #3340WD2 Humidity (Relative) NPP (Proxy) CrIS [AIRS] & ATMS [AMSU] WatchDog –Soil Moisture (Watermark) Sensor #6450WD20 Soil Moisture AQUA AMSR-E

17. Ground Instruments Secondary Environmental Parameters WatchDog – Soil Temperature Sensor #3667-20 (2” and 4” depth) Soil Temperature WatchDog –Silicon Pyranometer Sensor #36701 Solar Luminosity or Radiation Weather Parameters and Measurements

18. Requisition of ground monitoring equipment and accessories for collecting mold spore and meteorological data Meteorological Data Logger  Basic Weather Station (5)  Silicon Pyranometer Sensor for Solar Radiation (1)  Soil moisture sensor (1)  Soil temperature sensor (2)  Leaf wetness sensor (1)

19. Requisition of ground monitoring equipment and accessories for collecting mold spore and weather data  Mold Spore Traps (Burkard Manufacturing Co Ltd., UK)   Six 7 Day Recording Volumetric Spore Trap 12v ( solar charger operated)   Three 7 Day Recording Volumetric Spore Trap 110VAC ( electricity operated) Twenty four 7 day drums Twenty four Drum Carrying cases Two Flow meters

20. Installation of ground sampling facilities  Almost ready to begin

21. Study Area and Sample Locations

30. Accessing required NASA data and products   Agreement issues MSFC SSAI

31. Weather model and data  Weather model Name: North American Mesoscale (NAM)Name: North American Mesoscale (NAM) Spatial resolution: a grid with 12*12 kmSpatial resolution: a grid with 12*12 km Temporal resolution: 4 cycles/day and every three hour prediction in a cycleTemporal resolution: 4 cycles/day and every three hour prediction in a cycle Model output format: GribModel output format: Grib  Weather parameters Relative humidity: 2m above groundRelative humidity: 2m above ground Temperature: 2m above groundTemperature: 2m above ground Wind speed and direction 10m above groundWind speed and direction 10m above ground

32. Weather model and data - Continue  Access NAM model data sets approach Repository web site: NOAA online National Climatic Data Center (NCDC) at http://nomads.ncdc.noaa.govRepository web site: NOAA online National Climatic Data Center (NCDC) at http://nomads.ncdc.noaa.gov http://nomads.ncdc.noaa.gov Access function: ftp4u - allows you to build a collection, select files or parameters from the collection, and ftp selected data to an anonymous ftp serverAccess function: ftp4u - allows you to build a collection, select files or parameters from the collection, and ftp selected data to an anonymous ftp serverftp4u  Data conversion Extract data from Grid file to text formatExtract data from Grid file to text format Tool: wgrid – developed by NCEP/NCAR Reanalysis Project and be downloaded at ftp://ftp.cpc.ncep.noaa.gov/wd51we/wgribTool: wgrid – developed by NCEP/NCAR Reanalysis Project and be downloaded at ftp://ftp.cpc.ncep.noaa.gov/wd51we/wgrib

33. Training on Mold and Pollen ground data collection and analysis  Sheila S. Belk, MD  Date: April 10-11, 2007  Training Institution: US Army Centralized Allergen Extract Laboratory, Washington, DC  Instrument: Burkard Volumetric Spore trap

34. Catch up Schedule for 1 st Quarter  Install instruments – by July  Begin ground monitored data collection – by July  Test ground monitored data – by July  Begin ground monitored data analysis – by August  Complete agreement with GSFC and SSAI - by July  Begin accessing NASA data - by August