The first millimeter-wavelength (W-band) radar in space will provide global cloud information that was previously unavailable from other spaceborne instruments. Although the modest sensitivity (~ -28dBZ) and vertical resolution (~500 m with a 240 m sampling) of this radar will hamper retrievals of very thin cirrus and non-drizzling thin stratus clouds, it will effectively fill some gaps in atmospheric hydrometeor property profiling. Vertical information on optically thin clouds was previously available from spaceborne lidars and precipitation retrievals have been available from longer wavelength radars (such as a TRMM radar). Vertically-resolved information about multi-layer clouds and optically thick clouds that are associated with precipitating systems is not readily and unambiguously available from other sensors and such information will be the most unique part of the information available from CloudSat.
This proposal seeks funding to extend CloudSat standard retrieval algorithms and develop and apply new product retrieval techniques for the optically thick clouds that often constitute a part of precipitating systems. The studies will include (i) the development and application of microphysical retrieval techniques that are specifically tailored for thick ice clouds (snow) which are melting and producing precipitation; (ii) the development and application of techniques for estimating cloud extinction profiles and optical thickness for thick ice clouds as an experimental CloudSat product; (iii) the assessment, analysis and correction of biases in the CloudSat standard retrieval products due to sensitivity and resolution limitations of the spaceborne W-band radar; (iv) studies of interactions between the cloud content above the melting level and rain characteristics in precipitating systems.
Although this proposal is mostly focused on the CloudSat data, measurements from other A-train sensors will be used for combined retrievals when appropriate (e.g., single layer clouds that are not opaque) and compared with the CloudSat radar-based retrievals. It will help to better estimate uncertainties of retrievals.
