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Page 1: The “Afternoon” constellation of satellites make near simultaneous measurements to better understand important parameters related to climate change
Page 2: The “Afternoon” constellation of satellites make near simultaneous measurements to better understand important parameters related to climate change
Page 3: The “Afternoon” constellation of satellites make near simultaneous measurements to better understand important parameters related to climate change

The “Afternoon” constellation of satellites make near simultaneous measurements to better understand important parameters related to climate change.

The satellites greatly complement each other, making measurements of aerosols, clouds, temperature, relative humidity, and radiative fluxes.

Daily global coverage is achieved in 14.55 orbits per day,@ 24.7 degree separation.Orbits match the World Reference System 2 (WRS-2) reference grid (Developed for LANDSAT).

Page 4: The “Afternoon” constellation of satellites make near simultaneous measurements to better understand important parameters related to climate change

Spacecraft Main Area of Measurement within Earth’s Atmosphere Instruments Carried

Aqua Solid, liquid and gaseous forms of water AIRS/AMSU-A/HSB, AMSR-R, CERES, MODIS

CloudSat Cloud Profiling Radar CPR

CALIPSO LIDAR used to understand aerosols and clouds CALIOP, IIR, WFC

PARASOL Polarimetry to distinguish aerosols. POLDER

Aura Chemistry, pollutants, and greenhouse gases HIRDLS , MLS, OMI, TES

OCO Column integrated concentration of carbon dioxide 3 grating spectrometers

Page 5: The “Afternoon” constellation of satellites make near simultaneous measurements to better understand important parameters related to climate change

• “Ozone Monitoring Instrument” - continues the TOMS record

• Measures total ozone, as well as other ozone-related chemistry.

• Capable of mapping pollution products on urban to super-regional scales.

• Contributed to the EOS Aura mission by the Netherlands's Agency for Aerospace Programs in collaboration with the Finnish Meteorological Institute.

• Uses hyperspectral imaging in a “push-broom” mode to observe solar backscatter radiation in the visible and ultraviolet, using a wide-field telescope feeding two imaging grating spectrometers with CCD.

• Tropospheric NO2 columns are derived from satellite observations based on slant column NO2 retrievals with the DOAS technique, and the KNMI combined modelling/retrieval/assimilation approach.

Page 6: The “Afternoon” constellation of satellites make near simultaneous measurements to better understand important parameters related to climate change

OMI Data: Dutch vs American

DUTCH Algorithm– Array Format -HDF

– Negative Values– Missing Data Points– Data Available From:

May 18, 2006

AMERICAN Algorithm– Matrix Format - HDF-

EOS

– No Negative Values– All Data Points Given– Data Available From:

Sept. 28, 2004

Page 7: The “Afternoon” constellation of satellites make near simultaneous measurements to better understand important parameters related to climate change

AIRPACT Model vs OMI DataSome of the Challenges Involved When Comparing the Different Data Types

AIRPACT Model– 17 Layers Predicted– 9025 Data Points per

Layer over Region– Mixing Ratio Given– Fire Impact Included– Appropriate Layer Must

be Chosen (Max Value)– One Data Set per Hour– Equal Pixel Sizes (12x12

km2)– Full Region Available

OMI Data– One Tropo. Value (VCD)– Approximately 5000 Data

Points over Region– VCD Conversion (mol/cm2)

to PPBV Requires PBL Depth Assumption

– One Data Set per Day (Overhead @ 21:00 UTC)

– Varying Pixel Sizes (12x13 km2 at center of swath)

– Desired Region at Edges?

Page 8: The “Afternoon” constellation of satellites make near simultaneous measurements to better understand important parameters related to climate change

Varying Time Periods Selected and Data Obtained for OMI (American & Dutch) and AIRPACT (Early September Displayed)

OMI Vertical Column Depth Troposphere Values Converted to PPBV Using Assumed PBL Height

Max Concentration Value (1 of 17 Layers) from AIRPACT (closest hour) Used for Comparison

OMI (HDF) and AIRPACT Data Converted to Lat/Long Columnar Format

Data Sets Interpolated onto Standard Coordinate Grid Using IGOR Pro

Bias, Ratio, and Stats Analysis Performed on a Per Point Per Day Basis

Page 9: The “Afternoon” constellation of satellites make near simultaneous measurements to better understand important parameters related to climate change

OMI: American vs

Dutch Results

Page 10: The “Afternoon” constellation of satellites make near simultaneous measurements to better understand important parameters related to climate change

NO2 in Troposphere – Sept. 3, 2006OMI (American) OMI (Dutch)

Am

er. Sub

Dutch

BIAS

Page 11: The “Afternoon” constellation of satellites make near simultaneous measurements to better understand important parameters related to climate change

NO2 in Troposphere – Sept. 4, 2006OMI (American) OMI (Dutch)

Am

er. Sub D

utch

BIAS

Page 12: The “Afternoon” constellation of satellites make near simultaneous measurements to better understand important parameters related to climate change

NO2 in Troposphere – Sept. 5, 2006OMI (American) OMI (Dutch)

Am

er. Sub

Dutch

BIAS

Page 13: The “Afternoon” constellation of satellites make near simultaneous measurements to better understand important parameters related to climate change

NO2 in Troposphere – Sept. 6, 2006OMI (American) OMI (Dutch)

Am

er. Sub

Dutch

BIAS

Page 14: The “Afternoon” constellation of satellites make near simultaneous measurements to better understand important parameters related to climate change

NO2 in Troposphere – Sept. 7, 2006OMI (American) OMI (Dutch)

Am

er. Sub D

utch

BIAS

Page 15: The “Afternoon” constellation of satellites make near simultaneous measurements to better understand important parameters related to climate change

NO2 in Troposphere – Sept. 8, 2006OMI (American) OMI (Dutch)

Am

er. Sub

Dutch

BIAS

Page 16: The “Afternoon” constellation of satellites make near simultaneous measurements to better understand important parameters related to climate change

OMIOMIvs.vs.

AIRPACT AIRPACT ResultsResults

Page 17: The “Afternoon” constellation of satellites make near simultaneous measurements to better understand important parameters related to climate change

NO2 in Troposphere – Sept. 3, 2006OMI (American) AIRPACT

Am

er. Sub A

IRP

AC

T

BIAS

Page 18: The “Afternoon” constellation of satellites make near simultaneous measurements to better understand important parameters related to climate change

NO2 in Troposphere – Sept. 4, 2006OMI (American) AIRPACT

Am

er. Sub A

IRP

AC

T

BIAS

Page 19: The “Afternoon” constellation of satellites make near simultaneous measurements to better understand important parameters related to climate change

NO2 in Troposphere – Sept. 5, 2006OMI (American) AIRPACT

Am

er. Sub A

IRP

AC

T

BIAS

Page 20: The “Afternoon” constellation of satellites make near simultaneous measurements to better understand important parameters related to climate change

NO2 in Troposphere – Sept. 6, 2006OMI (American) AIRPACT

Am

er. Sub A

IRP

AC

T

BIAS

Page 21: The “Afternoon” constellation of satellites make near simultaneous measurements to better understand important parameters related to climate change

NO2 in Troposphere – Sept. 7, 2006OMI (American) AIRPACT

Am

er. Sub A

IRP

AC

T

BIAS

Page 22: The “Afternoon” constellation of satellites make near simultaneous measurements to better understand important parameters related to climate change

NO2 in Troposphere – Sept. 8, 2006OMI (American) AIRPACT

Am

er. Sub

AIR

PA

CT

BIAS

Page 23: The “Afternoon” constellation of satellites make near simultaneous measurements to better understand important parameters related to climate change
Page 24: The “Afternoon” constellation of satellites make near simultaneous measurements to better understand important parameters related to climate change

Seattle/Portland NO2– Sept. 3, 2006Urban Region – (1000 meter Vertical Column Assumed)

OMI (American) OMI (Dutch) AIRPACT Cloud Cover Fraction

Page 25: The “Afternoon” constellation of satellites make near simultaneous measurements to better understand important parameters related to climate change

Seattle/Portland NO2– Sept. 4, 2006Urban Region – (500 meter Vertical Column Assumed)

OMI (American) OMI (Dutch) AIRPACT Cloud Cover Fraction

Page 26: The “Afternoon” constellation of satellites make near simultaneous measurements to better understand important parameters related to climate change

Seattle/Portland NO2– Sept. 5, 2006Urban Region – (500 meter Vertical Column Assumed)

OMI (American) OMI (Dutch) AIRPACT Cloud Cover Fraction

Page 27: The “Afternoon” constellation of satellites make near simultaneous measurements to better understand important parameters related to climate change

Seattle/Portland NO2– Sept. 6, 2006Urban Region – (500 meter Vertical Column Assumed)

OMI (American) OMI (Dutch) AIRPACT Cloud Cover Fraction

Page 28: The “Afternoon” constellation of satellites make near simultaneous measurements to better understand important parameters related to climate change

Seattle/Portland NO2– Sept. 7, 2006Urban Region – (500 meter Vertical Column Assumed)

OMI (American) OMI (Dutch) AIRPACT Cloud Cover Fraction

Page 29: The “Afternoon” constellation of satellites make near simultaneous measurements to better understand important parameters related to climate change

Seattle/Portland NO2– Sept. 8, 2006Urban Region – (500 meter Vertical Column Assumed)

OMI (American) OMI (Dutch) AIRPACT Cloud Cover Fraction

Page 30: The “Afternoon” constellation of satellites make near simultaneous measurements to better understand important parameters related to climate change

Urban vs. Entire AIRPACT Urban vs. Entire AIRPACT Domain Bias ResultsDomain Bias Results

Large Number of Zero Values Agree in Entire Domain. Vertical Height Assumption has Strong Influence

Consistent Bias Between OMI & AIRPACT evident in Urban area but not in entire domain (Fires).

Page 31: The “Afternoon” constellation of satellites make near simultaneous measurements to better understand important parameters related to climate change

Meteorological Meteorological Influence:Influence:

Cloud Cover and Temperature were analyzed to determine if meteorology

directly correlates to differences between AIRPACT and OMI

Cloud cover and temperature not related to differences between OMI and AIRPACT(Sept. 3rd bias vs CFRAC shown. Temperature & CFRAC of other days show similar results)

Am

er. sub A

IRP

AC

T

CFRAC

Page 32: The “Afternoon” constellation of satellites make near simultaneous measurements to better understand important parameters related to climate change

Conclusions:American OMI Data Results:American OMI Data Results:

-Close Agreement to Airpact when Reasonable PBL Height Assumed

-No Negative Values (Some Dutch Contour “lost” to negatives)

-More Troposphere Data Available (No “lost” points; Entire AURA life)

Dutch OMI Data Results: Dutch OMI Data Results:

-Shows higher values in Fire Regions (as predicted)

AIRPACT Results:AIRPACT Results:

-Often Predicts an Order of Magnitude Higher for NO2 from Fires

-Accurately Predicts Urban Concentrations of NO2

-Doesn’t capture rural NO2 reported by OMI algorithms (farms?)

Meteorological Factors:Meteorological Factors:

-Seem to have no direct correlation to the difference in results.

Page 33: The “Afternoon” constellation of satellites make near simultaneous measurements to better understand important parameters related to climate change

Possible Reasons for Major Differences: Possible Reasons for Major Differences:

-Accurate Vertical Height (PBL?) Needed (Majority of NO2 probably resides at the bottom of the troposphere in urban areas)

-AIRPACT may be over-estimating NO2 concentrations in Fire Regions

-OMI may not be detecting fires in small canyon areas

Page 34: The “Afternoon” constellation of satellites make near simultaneous measurements to better understand important parameters related to climate change

Future Endeavors:Future Endeavors:

• Compare other chemical species predicted by AIRPACT to satellite observations (much of the troposphere data has not been released yet)

• Compare results to actual field measurements

• Use Variable PBL Depths as Predicted by AIRPACT per point

• Use a weighted layer average rather than a max layer value for AIRPACT.

Page 35: The “Afternoon” constellation of satellites make near simultaneous measurements to better understand important parameters related to climate change

Thanks to:Thanks to:

• Brian Lamb

• George Mount

• Joseph Vaughan

• Everyone else at LAR – WSU

• NASA & NAAP (Netherlands's Agency for Aerospace Programs)

Page 36: The “Afternoon” constellation of satellites make near simultaneous measurements to better understand important parameters related to climate change

References:References:

http://aura.gsfc.nasa.gov/instruments/http://www.nasa.govhttp://www.temis.nl/airpollution/no2.htmlhttp://www.temis.nl/docs/AD_NO2.pdfhttp://www.temis.nl/products/no2.htmlhttp://www-calipso.larc.nasa.gov/about/atrain.php

Data Access:Data Access:

http://www.temis.nl/airpollution/no2col/omi_data.php?year=2006http://disc.sci.gsfc.nasa.gov/data/datapool/OMI/sftp://zephyr.cmer.wsu.edu