Teaching
Courses That I Commonly Teach
ASP731 Data Analysis Methods for Atmospheric and Oceanic Sciences
Credits: 3.00 (1 0 2)
Description: Introduction to MATLAB, using Mathworks resources; MATLAB I/O with NetCDF, HDF and GRIB2; plotting 1, 2 and 3 dimensional weather/climate data and animations with MATLAB; Univariate & bivariate statistics, mean/median/mode, variance/standard deviation, correlation, errors, regression; probability and distributions, how to frame and test a hypothesis, principles of statistical significance, using MATLAB functions to test hypotheses and estimate statistical significance; working with spatial weather/climate data, regridding meteorological station data, interpolation, map overlays; working with time series, interpolation, estimating trend in weather/climate variables.
ASL760 Renewable Energy Meteorology
Credits: 3.00 (3 0 0)
Description: Introduction to the atmosphere: weather and climate processes; Solar radiation and surface energy balance; Meteorological considerations for solar power: solar resource assessment, solar forecasting for different timescales, uncertainty estimation, types of solar systems; Wind in the atmospheric boundary layer: boundary layer structure and evolution, surface layer, stability, log and power laws, flow over complex terrain, low-level jets, offshore winds; Meteorological considerations for wind power: wind resource assessment, wind forecasting for different timescales using statistical and numerical methods, uncertainty estimation, types of turbines, turbine wakes, wake interactions in wind farms, turbine and wake models, LES and mesoscale models of wind farms; Solar-wind coupling: resource variability, power demand, optimization.
ASL738 Numerical Modeling of the Atmosphere and Ocean
Credits: 3.00 (2 0 2)
Description: Introduction to weather and climate models, Numerical Modeling Vs. Other Modeling Approaches, Examples of atmospheric and oceanic simulations, Governing equations in Cartesian, Isobaric and sigma coordinate systems; Numerical discretization and integration, model components, dynamical core, physical parameterization, hands-on exercises with the WRF model, conducting simple simulations, understanding and manipulating model code for selected parameterization schemes.