Supplemental Regional Haze-Related Data

1. Supplemental Regional Haze-Related Data Rich Poirot, VT DEC Dallas RPO Mtg, December 2002

2. Collected, Distributed & Archived with Other Objectives • Large Domain Spatial Coverage (National - Global) • High Spatial and/or Temporal Resolution • Info on Aerosols: Space, Time, Size & Optical Properties

3. Regional Haze is a Complex 8-Dimensional Problem • Aerosol Concentrations x Compositions x Size Distributions x Optical Properties x Latitude x Longitude x Altitude x Time, • IMPROVE Data provide Site-Specific Information on Concentrations & Compositions at the Surface, • Information on Particle Size, Optical Properties, (3D) Spatial & Temporal Patterns is limited. • Sources of Supplemental Regional Haze-Related Data • Collected, Archived & Distributed (with Other Objectives) • Large Spatial Coverage (National - Global) • High Spatial and/or Temporal Resolution • “Extractable Information Content”: Space, Time, Size, Optics, etc.

4. ASOS Data Availability Beginning 2004 • Around 1995 the human observed visibility was replaced by the automatic forward light scattering detectors, reporting every minute (ASOS)    • Early evaluation by Richards et al in 1996/97 showed that the ASOS signal compared favorably with continuous PM2.5 measurements, however, data truncation was a major problem • CAPITA analyzed 230 station - 5 month - 1 minute data and found the network to be of high potential  value; however, many sensors appeared to have poor absolute calibration • A comparison with 26 hourly PM2.5 monitors over the country, was also favorable • As of 2003, NCDC provides (for a charge) real-time data access to 230 existing ASOS sites • Beginning Sept 2003, NOAA/NWS is upgrading 880 ASOS stations and will expose the real-time data through an FTP site, as well as through NCDC

5. The ASOS Visibility Sensor • The ASOS visibility sensor is a forward scattering instrument • Replaced Hourly Human Observers in about 1995-96 • “Better Quality” Extinction Data, But Need QA and Archived Data are Averaged, Binned, Truncated (Need Direct Access & Routine Processing)

6. ASOS Stations from FAA, NWS and Archived at NCDC For this analysis (Husar, 2002) data for 220 stations were available from NCDC These ASOS sites are mostly NWS sites, uniformly distributed over the country (Imagine if we could get the entire set, including the DOD sites, not listed).

7. Comparison of Sites with Duplicate ASOS Sensors • Co-located ASOS sensors are installed at different runways of the same airport. • Dual ASOS sensors (55) are distributed uniformly over the 800+ station network • Triple sensors are particularly useful for sensor calibration and consistency checking

8. Duplicate Sensors: Good Sites Dallas-FW, TX Erie, PA San Diego, CA Houston, TX • At several duplicate sites the 2-sensor correlation is excellent and the absolute values also match. • This indicates that the scattering sensor per se has high precision and temporal stability.

9. Albuquerque, NM Duluth, MN Albuquerque, NM Duplicate Sensors:Poor Sites • Duplicate sensors at some sites show significant deviation in scale and offset. • The nature of these deviations indicate poor instrument calibration maintenance for the ASOS visibility sensors.

10. ASOS Bext Threshold: 0.05 km(-1) Reported by NWS • The Bext values below 0.05 km-1 are reported as 0.05. • For Koschmieder coeff K=3.9, this threshold VR=78km(~ 50 mile); for K=2 VR=40km(~25mi) • In the pristine SW US, the ASOS threshold distorts the “cleaner day” data • Over the East and West, the (raw data) ASOS signal is well over the threshold most of the time (although Archived data are Truncated at 10 mi.)

11. Typical Diurnal Pattern of Bext, Temperature & Dewpoint • Typically, Bext shows a strong nighttime peak due to high relative humidity. • Most of the increase is due to water absorption by hygroscopic aerosols. At RH >90% , the aerosol is mostly water • At RH < 90%, the Bext is mostly influenced by the dry aerosol content; the RH effect can be corrected. Macon, GA, Jul 24, 2000

12. Adopted RH Correction Curve(To be validated for different locations/seasons) RH is calculated from T – Temperature, deg C and D – Dewpoint, deg C RH = 100*((112-(0.1*T)+D)/(112+(0.9*T)))8 • The ASOS Bext value are filtered & adjusted for high humidity • Values at RH >= 90% are not used • The Bext is also corrected for RH: RHCorrBext = Bext/RHFactor

13. Seasonal Average Diurnal Bext Pattern • For each minute of the day, the data were averaged over June, July and August, 2000 • Average Bext was calculated for • Raw, as reported • For data with RH < 90% • RH < 90% and RH Corrected • Based on the three values, the role of water can be estimated for each location

14. Location of ASOS and Nearby Hourly PM2.5 Sites • There are no co-located ASOS and PM2.5 sites • The stations are not co-located but in the same city • Hourly PM2.5 data are compared to the filtered and RH-corrected one minute Bext

15. ASOS-Hourly PM2.5 Allentown, PA • RH-Adjusted Bext is a good surrogate for PM-2.5, and • RH-Screened Bext is good surrogate for PM-2.5 + H2O

16. Islip, Long Island, NY San Diego, CA

17. Are There Areas of Common Interest between ASOS Data Providers & RPOs? • ASOS Sites are Spatially Dense (1000 sites), Evenly Distributed (airports everywhere “just out of town”, and Have High Temporal Resolution • Currently Archived Data are Averaged (1-hour), Truncated (at >= 10 miles) and Binned (into VR categories < 10 mi.) but, • Are Useful for evaluating Episodes, even in their current form, but • Require “Expert Processing” to extract “aerosol & haze-relevant Info, and • Could be extraordinarily Useful if: • We could access them in near-real time (& historical), • In their raw, uncensored form (1-minute uncensored Bext + RH), • From any & all sites, and Processed for Haze-Relevant Info, and • Merge them with other Haze-Related data…