A Physically Based Algorithm for Non-Blackbody Correction of Cloud-Top...

Wang, C., Z. J. Luo, X. Chen, X. Zeng, W. Tao, and X. Huang (2014), A Physically Based Algorithm for Non-Blackbody Correction of Cloud-Top Temperature and Application to Convection Study, J. Appl. Meteor. Climat., 53, 1844-1857, doi:10.1175/JAMC-D-13-0331.1.

Cloud-top temperature (CTT) is an important parameter for convective clouds and is usually different from the 11-mm brightness temperature due to non-blackbody effects. This paper presents an algorithm for estimating convective CTT by using simultaneous passive [Moderate Resolution Imaging Spectroradiometer (MODIS)] and active [CloudSat 1 Cloud–Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO)] measurements of clouds to correct for the non-blackbody effect. To do this, a weighting function of the MODIS 11-mm band is explicitly calculated by feeding cloud hydrometer profiles from CloudSat and CALIPSO retrievals and temperature and humidity profiles based on ECMWF analyses into a radiation transfer model. Among 16 837 tropical deep convective clouds observed by CloudSat in 2008, the averaged effective emission level (EEL) of the 11-mm channel is located at optical depth ;0.72, with a standard deviation of 0.3. The distance between the EEL and cloud-top height determined by CloudSat is shown to be related to a parameter called cloud-top fuzziness (CTF), defined as the vertical separation between 230 and 10 dBZ of CloudSat radar reflectivity. On the basis of these findings a relationship is then developed between the CTF and the difference between MODIS 11-mm brightness temperature and physical CTT, the latter being the non-blackbody correction of CTT. Correction of the non-blackbody effect of CTT is applied to analyze convective cloud-top buoyancy. With this correction, about 70% of the convective cores observed by CloudSat in the height range of 6–10 km have positive buoyancy near cloud top, meaning clouds are still growing vertically, although their final fate cannot be determined by snapshot observations.

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Research Program: 
Modeling Analysis and Prediction Program (MAP)
Radiation Science Program (RSP)