Observed Data Verification of the High-Resolution Rapid Refresh Model Using Spectral Analysis

Numerical weather prediction is a vital tool for forecasting complex meteorological phenomena. For forecasted data to be usable, it is important to ensure that the model’s output accurately portrays the environment. Without verification, improvements to the parameters the model uses cannot be efficiently made, and models cannot improve the accuracy of their outputs. One way to verify model derived weather conditions is to compare model outputs to observed data. Spectral analysis can be used to further this comparison, as it allows for the breakdown of complex flows into simpler length scales. These length scales can be easily compared between different data sets to determine how similar the energy distribution may be between them. This methodology can be applied to observed and modeled physical variables, such as wind speeds, temperature and water vapor content.. Observed data from the Collaborative Lower Atmospheric Mobile Profiling System (CLAMPS) during the Verification of the Origins of Rotation in Tornadoes EXperiment-Southeast (VORTEX-SE) and Propagation, Evolution, and Rotation in Linear Storms (PERiLS) campaigns was compared to data returned from the High-Resolution Rapid Refresh version 3 (HRRRv3) numerical model. The differences in temporal and spatial resolution between observed and modeled variables should be reflected in the calculated power spectra. The observations’ resolution allows it to resolve eddies on a finer scale than what is possible with model output. Therefore, to make them comparable to the model output, the observations were averaged to a timescale of one hour. Comparing the returned power spectra, both in the power-frequency space and period-height-power space allows for the comparisons of the length scales of motion represented in each respective data source.