Determination of 3-D Cloud Ice Water Contents by Combining Multiple Data Sources from Satellite, Ground Radar, and a Numerical Model
| Liu, Guosheng | Florida State University |
| Seo, Eun-Kyoung | Florida State University |
Category: Cloud Properties
This study aims at determining the 3-dimensional distribution of ice water content over a broad area near the Atmospheric Radiation Measurement Southern Great Plain site, where cloud radar and meteorological observations have been routinely conducted. Together with wind fields from other measurements, the ice water content retrievals can be used to derive cloud ice water advective tendency terms needed for single-column model simulations. In this study, a Bayesian retrieval algorithm has been developed, which combines multiple data sources from satellite high-frequency microwave radiometry and ground cloud radar observations, and mesoscale numerical model analysis. The cloud radar observations allow us to infer the characteristics of vertical ice water content structures. The numerical model data are used to locate the cloud height. The satellite data provide information on the integrated ice water path, its horizontal distribution over a broad area, and, to a lesser extent, the vertical structure of ice water content. Our approach is to retrieve the 3-dimensional cloud ice water content in a 10° by 10° area surrounding the cloud radar site by combining all the information contained in the above datasets through a Bayesian framework. Validation of the algorithm has been done by comparing the retrievals with measurements from two ground radars. The comparison shows that the mean ice water content profiles and the 2-dimensional (height-ice water content) probability density functions retrieved for 19 coincident cases agree fairly well with the validation data. Overall, the vertical structures retrieved by our algorithm capture the main characteristics retrieved by the surface cloud radar. On the other hand, this study strongly suggests that using measured cloud top height (or temperature) as a constraint could improve the algorithm’s performance in the retrieval of vertical structure of ice water content.
This poster will be displayed at the ARM Science Team Meeting.
