forecasting pm 2.5

3-Dimensional Validation of Satellite AOD Products and

the Numerical Aerosol Forecast Models that Use Them

Raymond Hoff, J. Engel-Cox, R. Rogers, N. Jordan, K. McCann, K. Mubenga Physics, MEES and JCET UMBC

S. Palm, J. Spinhirne

GSFC

Forecasting PM2.5

• NOAA-EPA MOU: 2013 PM Forecasts available to the public

• 2006 PM forecasting goes into beta testing mode

• How do you calibrate/validate these forecasts?

Surface Data - Real Time: AIRNoW

Courtesy Jim Szykman, EPA

CAMMSCAMMSTEOMNephelometerBeta Attenuation

Been there, done that…..ozone says this just doesn't work

The problem with 4D-VAR assimilation

• "Everybody says they should do something about getting data for 4D-VAR, but no one wants to do anything about it"

• Two examples follow where it is obvious that 3D and 4D solutions are needed:– Alaskan Fires of 2004– California Fire of 2003

A good IDEA

Courtesy: CIMSS, UW

Linking optical properties and mass concentration

Engel-Cox et al. 2004

Baltimore, MD Summer 2004

MO

DIS

Aer

osol

Opt

ical

Dep

th

PM

2.5

(g/

m3 )

July 9High altitude

smoke

July 21Mixed down

smoke

Courtesy EPA/UWisconsin

Old Town TEOM

MODIS AOD

Smoke mixing in Maryland

20-22 July 2004

Old Town (Baltimore) 19-22 July 2004Mixed down Smoke

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g/m

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Hourly PM2.5Daily Average PM2.5MODIS AODLidar OD Total ColumnLidar OD Below Boundary Layer

U.S. Air Quality (The Smog Blog), http://alg.umbc.edu/usaq

Over 1,000,000 hits over 19 months~ 10,000 visits per month~800 unique visitors per week including

EPA, NASA, NOAA, & States

Daily posts

NASA satellite images, EPA data, etc.

Index & Links

http://alg.umbc.edu/REALM

Data for: September 1, 2004

Click on a REALM Participant for their LIDAR data.

REALM: Wisconsin lidar for July 2004

Eloranta, U. Wisc

July 17 July 18 July 19

MODIS

19 July 2004 21 July 2004

Example 2: GLAS and the California Fires of October 2003

Smoke

13:3502:00Low cloud

Midcloud

MODISAQUA19:43 UTCOctober 30

Smoke

10-5

10-6

5 10-6

October 3112:08

23:01

MODIS 17:05 UTC

This is tough…in 2D or 3D or 4D

• Where was the smoke 6 hours previously?

• We built a tool (CALIPSO-MORPH or C-MORPH)

Backward movie

Forward Movie

The easy validation problems are over

• Now it gets tough….

• Cal/Val has to be 3D+ to be able to integrate multiple profiling sensors

• Cal/Val is going to have to involve a 4D analysis tool

• UMBC/NOAA/NASA/EPA/UW/CDC are collaborating on "3D-AQS", an attempt to integrate multisensor data into the EPA decision support system, AQS

Backup

7/16 7/17 7/18 7/19 7/20 7/22

July 16-22, 2004: Evidence of Effects of Long Range Transport Originating Outside the Modeled Domain Evolution of Model and Observed Aerosol Optical Depth

MODIS

Model

Transport from outside the domain influences observed PM concentrations whichare grossly under-predicted during this period

• Model picks up spatial signatures ahead of the front • Under predictions behind the front (due to LBCs)

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