Cloud Base Height Estimation from ISCCP Cloud-Type Classification Applied to A-Train Data

[摘要] Cloud base height (CBH) is an important cloud macro parameter that plays a key role in global radiation balance and aviation flight. Building on a previous algorithm, CBH is estimated by combining measurements from CloudSat/CALIPSO and MODIS based on the International Satellite Cloud Climatology Project (ISCCP) cloud-type classification and a weighted distance algorithm. Additional constraints on cloud water path (CWP) and cloud top height (CTH) are introduced. The combined algorithm takes advantage of active and passive remote sensing to effectively estimate CBH in a wide-swath imagery where the cloud vertical structure details are known only along the curtain slice of the nonscanning active sensors. Comparisons between the estimated and observed CBHs show high correlation. The coefficient of association (R2) is 0.8602 with separation distance between donor and recipient points in the range of 0 to 100?km and falls off to 0.5856 when the separation distance increases to the range of 401 to 600?km. Also, differences are mainly within 1?km when separation distance ranges from 0?km to 600?km. The CBH estimation method was applied to the 3D cloud structure of Tropical Cyclone Bill, and the method is further assessed by comparing CTH estimated by the algorithm with the MODIS CTH product.

[学科分类] 大气科学