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Aura Science

Combined use of A-train data for improved cloud study

The A-train detection of distinct multi-layer clouds is important for calculating radiative forcing, evaluating model cloud parameterizations, and obtaining accurate trace gas retrievals

Aura and CloudSat

Aura OMI clouds
Fraction of OMI cloudy pixels containing distinct multi-layer clouds, July 2007

Case study in tropical convection

Aura OMI clouds

CloudSat optical extinction (km-1). Purple : MODIS cloud-top pressure | Pink : OMI optical centroid cloud pressure, (sensitive to bright lower cloud decks)

OMI and MODIS are passive sensors with excellent daily spatial coverage

The CloudSat radar provides excellent vertical information, but with limited spatial coverage; it is used to evaluate OMI/MODIS results

Incoming sunlight (short-wave radiation) can get trapped between two cloud layers, producing enhanced absorption from gases such as water vapor and ozone. Therefore, for the short-wave radiation budget, it is important to know how far into the atmosphere sunlight travels.

The outgoing long-wave radiation is primarily sensitive to the cloud top pressure. That is where most of the outgoing infrared heat is emitted from.

Multi-layer clouds can present difficulties for trace-gas remote sensing when the target absorbing gases are not well mixed (as is the case for NO2, SO2, HCHO, etc. - less of an issue for ozone which is relatively well-mixed in the upper troposphere). We need to be able to detect such problematic cases. We can do this using complementary information from OMI and MODIS (note: this can also be done with MODIS alone using its shortwave H2O channel). This is the first time to our knowledge that such an approach has been validated globally using an active sensor.

Courtesy J. Joiner et al., GSFC, Atmos. Meas. Tech. Disc