2004-06-20 Fast Aerosol Sensing Tools for Natural Event Tracking FASTNET

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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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Average Fine Soil, Events

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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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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)