Speaker: Jinming Ge

Affiliation: Lanzhou University

Academic title: Professor

Abstract:

We propose an improved cloud mask method with a new noise reduction scheme, which can reduce the noise distribution to a narrow range, to distinguish hydrometeors from noise and recognize more features with weak signal in Ka band cloud radar observation. This method was successfully applied to the W band cloud radar onboard CloudSat satellite. It was found that our method has significant advantages in reducing the rates of both failed negative and false positive hydrometeor identifications, while retaining a large fraction of the true weak signals that may have been lost in previous algorithms. We also construct a relationship between the radar measured reflectivity, liquid water content (LWC), and intrinsic reflectivity. Based on this intrinsic link, we develop a new self-consistent algorithm to better retrieve cloud LWC and effective radius by constraining radar reflectivity factor and attenuation in the whole liquid cloud layer. 

Biography:

Jinming Ge is from Lanzhou University, current serve as the vice dean of College of Atmospheric Sciences. He earned his Ph.D. in 2010 and visited department of atmosphere in University of Washington twice in 2008 and 2017. His background research is in aerosol and cloud radiative properties retrievals by using ground- and space-based remote sensors. During his career spanning over the recent decades, he has authored 50 influential publications and achieve some academic awards and honors, such as outstanding achievements in higher education of the Ministry of Education.