Engineering topics
Publications and source records attributed to Ma, Po-Lun.
Aerosol process analysis in model-native Spectral Element (SE) grid. Aerosol Diagnostics on Model Native Grid is a Python-based tool designed for diagnosing aerosol processes in E3SM. It is particularly designed to analyze simulation data on the model-native spectral element (SE) grid, soit is also known as Aerosol SE Diagnostics or “asediag”
NeuralMie was developed to improve the representation of aerosol optical properties in E3SM, the DOE's Earth system model. NeuralMie is able to closely emulate numerical solutions to the problem at a fraction of the computational cost. TAMie was written to generate training data for NeuralMie.
Aerosol-cloud interactions remain a major uncertainty in climate research. Studies have indicated that model estimates of cloud susceptibility to aerosols frequently exceed satellite estimates, motivating model reformulations to increase agreement. Here we show that conventional ways of using satellite information to estimate susceptibility can serve as only a weak constraint on models because the estimation is sensitive to errors in the retrieval procedures. Using instrument simulators to investigate differences between model and satellite estimates of susceptibilities, we find that low aerosol loading conditions are not well characterized by satellites, but model clouds are sensitive to aerosol perturbations in these conditions. We quantify the observational requirements needed to constrain models, and find that the nighttime lidar measurements of aerosols provide a better characterization of ten- uous aerosols. We conclude that observational uncertainties and limitations need to be accounted for when assessing the role of aerosols in the climate system.
Episodic events of both Saharan dust outbreaks and African Easterly Waves (AEWs) are observed to move westward over the eastern tropical Atlantic Ocean. The relationship between the warm, dry, and dusty Saharan Air Layer (SAL) on the nearby storms has been the subject of considerable debate. In this study, the Weather Research and Forecasting (WRF) model is used to investigate the radiative effect of dust on the development of AEWs during August and September, the months of maximum tropical cyclone activity, in years 2003-2007. The simulations show that dust radiative forcing enhances the convective instability of the environment. As a result, most AEWs intensify in the presence of a dust layer. The Lorenz energy cycle analysis reveals that the dust radiative forcing enhances the condensational heating, which elevates the zonal and eddy available potential energy. In turn, available potential energy is effectively converted to eddy kinetic energy, in which local convective overturning plays the primary role. The magnitude of the intensification effect depends on the initial environmental conditions, including moisture, baroclinity, and the depth of the boundary layer. We conclude that dust radiative forcing, albeit small, serves as a catalyst to promote local convection that facilitates AEW development.