Support by Inter-RPO WG - NESCAUM
Performed by
CAPITA & Sonoma Technology, Inc
Fast Aerosol Sensing Tools for Natural Event Tracking
FASTNET
Project Synopsis
Haze levels should be reduced to the ‘natural conditions’ by 2064.The space, time, composition features of natural aerosols are not knownThis long-term project goal is to better characterize the natural haze conditionsFocus is on detailed analysis of major natural events, e.g. forest fires and windblown dustFASTNET is primarily a tools development project for data access, archiving and analysis This, first year pilot project focuses on demonstrating the feasibility and utility of approach
Seasonal Average Fine Dust Concentration
Origin of Fine Dust Events over the US
Gobi dust in springSahara in summer
Fine dust events over the US are mainly from intercontinental transport
Daily Average Concentration over the US
Dust is seasonal with noise
Random short spikes added
Sulfate is seasonal with noiseNoise is by synoptic weather
VIEWS Aerosol Chemistry Database
Average Fine Soil, Measured
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Sahara and Local Dust Apportionment: Annual and July
• The maximum annual Sahara dust contribution is about 1 g.m3
• In Florida, the local and Sahara dust contributions are about equal but at Big Bend, the Sahara contribution is < 25%.
The Sahara and Local dust was apportioned based on their respective source profiles.
• In July the Sahara dust contributions are 4-8 g.m3
• Throughout the Southeast, the Sahara dust exceeds the local source contributions by w wide margin (factor of 2-4)
AnnualJuly
Supporting Evidence: Transport Analysis
Satellite data (e.g. SeaWiFS) show Sahara Dust reaching Gulf of Mexico and
entering the continent.
The air masses arrive to Big Bend, TX form the east (July) and from the west
(April)
Seasonal Fine Aerosol Composition, E. USUpper Buffalo Smoky Mtn
Everglades, FLBig Bend, TX
Sahara PM10 Events over Eastern USMuch previous work by Prospero, Cahill, Malm, Scanning the AIRS PM10 and IMPROVE chemical
databases several regional-scale PM10 episodes over the Gulf Coast (> 80 ug/m3) that can be attributed to Sahara.
June 30, 1993
The highest July, Eastern US, 90th percentile PM10 occurs over the Gulf Coast ( > 80 ug/m3)
Sahara dust is the dominant contributor to peak July PM10 levels.
July 5, 1992
June 21 1997
MODIS Rapid Response
FASTNET Event Report: 040219TexMexDust
Texas-Mexico Dust EventFebruary 19, 2004
Contributed by the FASNET Community
Correspondence to R Poirot, R Husar
Satellites detect dust most storms in near real time The MODIS sensor on AQUA and Terra provides 250m resolution images of the dust storm
Visual inspection reveals the dust sources at the beginning of dust streaks.
The NOAA AVHRR sensor highlights the dust by its IR sensors
In the TOMS satellite image, the dust signal is conspicuously absent – too close to the ground
Surface met data from the 1200 station network documents the strong winds that cause the windblown dust and resulting low-visibility regions
High Wind Speed – Dust Spatially Correspond
The spatial/temporal correspondence suggests that most visibility loss is due to locally suspended dust, rather than transported dust
Alternatively, suspended dust and ‘high winds’ travel forward at the same speed
Wind speed animation; Bext animation. (material for model validation?)
PM10 > 10 x PM25During the passage of the dust cloud over El Paso, the PM10 concentration was more
than 10 times higher than the PM2.5
AIRNOW PM10 and Pm25 data
PM10 and PM25, El Paso, Feb. 19 2004 - AIRNOW
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PM10 Avg
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Schematic
Link to dust modelers for faster collective learning?
Monte Carlo simulation of dust transport using surface winds (just a toy, 3D winds are essential!)
See animation Note, how sensitive the transport direction is to the source location (according to this toy)
VIEWS Fine Mass, Sulfate, OC, Dust, 02-07-01
OCOC
Mass SO4
Dust
SeaWiFS AOT – ASOS FBext, 02-07-01
Please Visit http://datafed.net
NCore Integration
NOAA/NASA Satellite: Global/Continental transport
Other Networks: Deposition, Ecosystems
Intensive/diagnostic Field Programs
Longer Term Goal:
Integrated Observation-modeling Complex
Similar to Meteorological Models (FDDA)
Model Adjustments Through Obs.
All in Near Real Time
Full Model Dims (x, y, z, t, chemistry, size)
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