4800 Oak Grove Drive
M/S 233-300
UCLA / JIFRESSE
Dr. Kubar is an Assistant Research Scientist at JIFRESSE at UCLA, working remotely at Jet Propulsion Laboratory in the Aerosols and Clouds Group. His research interests include satellite remote sensing of clouds, precipitation, and convection using multi-sensor A-Train data, and he has published papers on the vertical structure of tropical clouds, radiative forcing of tropical high clouds, high-topped cloud and rain rate relationships, and controlling factors of deep convective and cirrus clouds. He was the PI of a selected three-year NASA ROSES project in 2014, titled "Radiative and Large-Scale Forcing of Tropical Clouds and Their Controls on High SST Environments Using Multi-Sensor Aqua and ECMWF-Reanalysis Datasets."
Dr. Kubar also analyzes low cloud heights and PBL depths from MODIS and GPS-RO data, using joint distributions of cloud and PBL heights in different low cloud regimes to aid in novel evaluation of three versions of CAM5, including two versions with a new subgrid low cloud parameterization (CAM5-CLUBB). Low cloud parameterization to first order, and increased vertical resolution to second order, provide significant improvement in simulations of cloud height and PBL depth. Current work on this topic includes evaluating how model climate sensitivity may be related to low cloud top biases, the ratio of shallow cumulus to stratocumulus clouds, and PBL decoupling. The importance of properly simulating regional subsidence in low cloud regions also has been shown to coincide with improved joint cloud and PBL height distributions.
Some of Dr. Kubar's latest research interests include characterizing SST and atmosphere interactions over tropical oceans, particularly high SST regions also referred to as SST hot spots, using Lokta-Volterra (LV) equations, which historically have been used to explain ecological predator-prey interactions. In the ocean-atmosphere system, however, the LV equations can describe the intrinsic lag of deep convection to very high SSTs; in this way deep convection, absent other feedbacks, is a stabilizing mechanism on SST hot spots on a variety of spatial and temporal scales, with forecasting skill using the predator-prey system of equations of deep convection ranging from subseasonal to seasonal variability of SST over the Eastern Warm Pool (160°E-180°; 0°-10°S), to synoptic-scale over the Caribbean and Gulf of Mexico. In the latter case study, the evolution of high SST days before the development of Tropical Storm Cindy in June 2017 served as a precursor to enhanced upward heat fluxes and deep convection, and in conjunction with high-resolution remote sensing of the ocean surface, SST through the LV system of equations may be considered more broadly for improvement of tropical cyclone forecasting.
Special Recognition
Dr. Kubar was a group member on the team awarded the Group Achievement NASA Award in September 2017 supporting the student group projects for JPL Center for Climate Sciences Summer School.
Selected Awards