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Description of NAAPS AOD / TOMS AI Composite Plots

NAAPS Optical Depth/TOMS AI
Today's image       Loop of last 5 days images


Plots of combined NAAPS results and TOMS aerosol residuals are presented in a 2-panel format as individual images for a day, or as 8-day loops containing 9 images (1-daily plots).

GM-Centered : These images have 180W on the left, and 180E on the right with GM in the center.

Dateline-Centered : These images have GM on the left and right with the dateline in the center.

Left: GSFC/TOMS aerosol residual for the world. Data are valid for the time of the overpass, or roughly noon LOCAL TIME, so it is not valid for any one particular time, eg 1200Z. For GM-Centered images, the data are the same as the original image distributed by GSFC. The Dateline-Centered images use the current day's data from 0-160E and the previous day's data for 160E-0W.

Right: NAAPS optical depths for sulfate, dust, and smoke. To simulate the age of the TOMS data, the GM-Centered images use the 00Z NAAPS simulation for 90-180E, the 06Z simulation for 00-90E, the 12Z simulation for 90-00W, and the 18Z simulation for 180-80W. The Dateline-Centered images use use the 00Z NAAPS simulation for 90-180E, the 06Z simulation for 00-90E, the 12Z simulation from the previous day for 90-00W, and the 18Z simulation from the previous day for 180-80W. This chunking of the data significantly improves the comparison and someday will be done even more accurately by using finer temporal resolution data from NAAPS.

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Description of Comparison of NAAPS Dust and Smoke AOD and NASA/GSFC TOMS AI

NAAPS Optical Depth
Today's image       Loop of last 5 days images
 

NAAPS simulations of atmospheric aerosols are validated by comparing the NAAPS simulated dust and smoke aerosol optical depth ( AOD; upper-left image) with the TOMS aerosol index (AI) retrieved daily by NASA/GSFCS from TOMS data (TOMS Home Page; top row, middle and right images).

The comparison is made on a pixel-by-pixel basis with the pixels being 1 degree square for both NAAPS and the TOMS AI. The TOMS AI is available over most of the globe near local noon on a daily basis (upper-right panel) but there are areas where the AI is contaminated by cloud and sunglint. Cloud contamination is defined by reflectivity greater than 15 percent. Sunglint contamination is defined by psi-angle less than 30 degrees over water points. The cloud and sunglint-screened data are shown in the top-middle panel. The TOMS AI has a strong dependence on aerosol altitude, with higher values when the aerosol is at higher altitude. The AI does not detect aerosols in the lowest part (about 1 km) of the atmosphere. The positive AI values reflect the presence of absorbing aerosols; the presence of non-absorbing aerosols will suppress the AI value. The AI is also amplified by underlying bright surfaces (desert, clouds). For these reasons, we would not expect a perfect correlation between NAAPS and AI, even if NAAPS were perfect. However, we feel the comparison can still reveal biases and deficiencies in the model. The comparison is made as scatter plots with TOMS AI on the abscissa and NAAPS dust and smoke AOD on the ordinate. When either the NAAPS or TOMS AI values exceed the limits of axes, both are scaled by 0.25 and then the point is plotted as a larger red asterisk.

To identify regional biases, the comparison is made on a number of subdomains, denoted by the red boxes in the upper row of panels. These are chosen to enclose aerosol types:

REGION Abbreviation Predominant Aerosol Type
Northwest Pacific nwpac Dust, anthropogenic
West Tropical Atlantic. wtatl Dust
Sahara sahara Dust, smoke
Central Asia casia Dust, anthropogenic
Northeast Pacific nepac Anthropogenic, dust
South America, SW Tropical Atlantic soamer Smoke, dust
Africa africa Dust, Smoke
Indian Ocean, India, Australia, Indonesia indaus Anthropogenic, Dust, Smoke
Other. other All types
Globe globe All types


Those valid points not included in one of the subdomains are then plotted as `other' so that unidentified or unexpected patterns and biases do not go unnoticed. All valid points are plotted in the `globe' plot (lower-right). The linear coefficient of correlation is calculated and displayed in each scatter plot following the subdomain name and the number of valid pixels.

Some preliminary findings are:

NAAPS shows skill in regions dominated by dust, such as the Sahara and parts of the Central Asia domains.

It also shows skill in late 1999 at and downwind of the smoke producing areas of South America and Africa. (From August-October 1999, NAAPS is simulating smoke in South America using the ABBA fire detection data. As of September 1999, NAAPS is simulating smoke in Africa using the 1993 ESA IONIA ATSR fire detection data. As of January 2000, NAAPS is simulating smoke in Africa, South America, Australia and Indonesia using the 1993 ESA IONIA ATSR fire detection data.)

Our first efforts should be to eliminate those cases (pixels) where TOMS AI consistently shows aerosol while NAAPS does not, and vice versa.

Subsequent efforts would be to achieve a better correlation between NAAPS AOD and TOMS AI by improving the source, transformation, and sinks in the model, though a perfect correlation is impossible due to the characteristics of the AI retrieval mentioned above.

Acknowlegements 


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