# Presentation: 259915

## Aerosol / Cloud / SO2 Session Summary

**AURA Validation Meeting**
**September 11-15, 2006**
**Boulder, CO**

## Slide 2

## Validation Comparisons

## Comparison of AOD spectra from AATS & OMI 10 Mar 2006

**Comparison of AOD spectra from AATS & OMI 10 Mar 2006**

**Livingston et al**

**Mexico**

## MLS and AIRS Comparison of Seasonal Cloudiness

- The MLS IWC (mg/m3) and AIRS CFR (%) are two different quantities and thus they can not compare directly. But time series show they have the same seasonal variation, which they should.
- The MLS cloud occurrence frequency (%) is computed as total number of cloud detected divided by total number of samples. They show good agreement with AIRS CFR.

**MLS and AIRS Comparison of Seasonal Cloudiness**

**Jiang et al**

**IWC**

**Red – AIRS**
**Blue - MLS**

## Boersma 

**Boersma **

## Improvements in data products

## Improvement of TES v002

- No longer have tail of -200 mb differences

- v001

- v002

**Eldering et al**

**Cloud Top pressure differences (TES-MODIS)**

**Cloud Top pressure differences (TES-MODIS****)**

## V1.5

- V2.1

-  lacks of IWC > 50 mg/m3
-  some large negative outliers
-  latitude-dependent biases
-  false alarms at high latitudes

-  more IWC > 50 mg/m3
-  no large negative outliers
-  little latitude-dependent biases
-  reduced false alarms at high latitudes

**V2.1 *****vs.***** V1.5 IWC statistics: **** Probability Density Function (PDF)**

**316 hPa**

**261 hPa**

**177 hPa**

**215 hPa**

**121 hPa**

**147 hPa**

**100 hPa**

**83 hPa**

**316 hPa**

**261 hPa**

**177 hPa**

**215 hPa**

**121 hPa**

**147 hPa**

**100 hPa**

**83 hPa**

**Wu and Jiang**

## Validation Challenges

## 1 km

**1 km**

**Massie et al**

**Very large Vertical Gradients in Extinction**

## Results of Comparison

- Ocean only*r* = 0.862,  = 0.650,  = 0.032, *N* ~ 350,000

**Results of Comparison**
*r*  = 0.833,  = 0.477,  = 0.053, *N* ~ 620,000
*r correlation, **** slope, **** intercept, N # obs *

**Braak et al**

**slope**

**Notes:**
Here, the same data as in the previous slide are represented in the form of a scatter plot (on the left), showing a clear correlation between OMI and MODIS AOT. However, the scatter cloud deviates considerably from the 1-1 line, hinting at an overestimation by OMI at large AOT, and an underestimation at lower AOTs.

The plots on the right are similar, but for land and ocean pixels separately. This indicates that retrievals over ocean are better than retrievals over land, which is understandable because the surface albedo of the ocean is much better defined than that for land.

The values of N don’t add up because there are also combined land-and-ocean pixels.

## Credits: CALIPSO Science Team

**OMI and CALIPSO Observations on July 5 and 7**

- 5

- 7

- Aerosols between 7 and 10 km

**Torres et al**

## New Algorithms / Directions

## Hsu et al

**Hsu et al**

## Richland NATIVE AOT

**Taubman et al**

**Mobile Trailer with Instrument Suite**

## Multi-Wavelength Approach (20 ’s)

- Wavelength (nm)

**Multi-Wavelength Approach (20 ********’s)**

- Reflectance

- ● Best fitting aerosol model
- ● Information on Type, AOD, SSA, Size, Height?
- ● Surface reflectivity? Clouds?

**Veilehmann et al**