April 29, 2000, Day 120 July 18, 2000, Day 200October 16, 2000, Day 290 Results – Seasonal surface reflectance, Eastern US

SeaWiFS Satellite Platform and Sensors Satellite maps the world daily in 24 polar swaths The 8 sensors are in the transmission windows in the visible & near IR Designed for ocean color but also suitable for land color detection, particularly of vegetation Swath 2300 KM 24/day Polar Orbit: ~ 1000 km, 100 min. Equator Crossing: Local Noon Chlorophyll Absorption Designed for Vegetation Detection

Satellite Aerosol Optical Thickness Climatology SeaWiFS Satellite, Summer Percentile 99 Percentile90 Percentile 60 Percentile

Satellite AOT – Time Fraction (0-100%) SeaWiFS Satellite, Summer Dec, Jan Feb Sep, Oct, NovJun, Jul, Aug Mar, Apr, May

SeaWiFS AOT – Summer 60 Percentile 1 km Resolution

Technical Challenge: Characterization PM characterization requires many different instruments and analysis tools. Each sensor/network covers only a limited fraction of the 8-D PM data space. Most of the 8D PM pattern is extrapolated from sparse measured data. Some devices (e.g. single particle electron microscopy) measure only a small subset of the PM; the challenge is extrapolation to larger space- time domains. Others, like satellites, integrate over height, size, composition, shape, and mixture dimensions; these data need de-convolution of the integral measures.

Summary Satellite data have aided the science of Particulate Matter since the 1970s Satellite data have supported PM air quality management since the 1990s. Past satellite data helped the qualitative description of PM spatial pattern Quantitative satellite data use and fusion with surface data is still in infancy Satellite data applications will require collaboration across disciplines

April 29, 2000, Day 120July 18, 2000, Day 200October 16, 2000, Day 290 Results – Seasonal surface reflectance, Western US

Results – Eight month animation

Apparent Surface Reflectance, R The surface reflectance R 0 is obscured by aerosol scattering and absorption before it reaches the sensor Aerosol acts as a filter of surface reflectance and as a reflector solar radiation Aerosol as Reflector: R a = (e -  – 1) P R = (R 0 + (e -  – 1) P) e -  Aerosol as Filter: T a = e -  Surface reflectance R 0 The apparent reflectance, R, detected by the sensor is: R = (R 0 + R a ) T a Under cloud-free conditions, the sensor receives the reflected radiation from surface and aerosols Both surface and aerosol signal varies independently in time and space Challenge: Separate the total received radiation into surface and aerosol components