We develop and test an empirical model predicting ground-based observations of ultralow frequency (ULF, 1-20 mHz) wave power across a range of frequencies, latitudes, and MLT sectors. This is parameterized by instantaneous solar wind speed v sw , variance in proton number density var(Np), and interplanetary southward magnetic field B z . A probabilistic model of ULF wave power will allow us to address uncertainty in radial diffusion coefficients and therefore improve diffusion modeling of radial transport in Earth's outer radiation belt. Our model can be used in two ways to reproduce wave power: by sampling from conditional probability distribution functions and by using the mean (expectation) values. We derive a method for testing the quality of the parameterization and test the ability of the model to reproduce ULF wave power time series. Sampling is a better method for reproducing power over an extended time period as it retains the same overall distribution, while mean values are better for predicting the power in a time series. The model predicts each hour in a time series better than the assumption that power persists from the preceding hour. Finally, we review other sources of diffusion coefficient uncertainty. Although this wave model is designed principally for the goal of improved radial diffusion coefficients to include in outer radiation belt diffusion-based modeling, we anticipate that our model can also be used to investigate the occurrence of ULF waves throughout the magnetosphere and hence the physics of ULF wave generation and propagation.
Plain Language SummaryWe construct and test a statistical model for ground-based ultralow frequency wave occurrence, parameterized by solar wind properties. This can be used to find magnetospheric radial diffusion coefficients that determine the transport and energization of electrons in Earth's radiation belts. Our time series prediction outperforms a time series using the assumption that wave power persists from the preceding hour. Using a probabilistic approach reproduces the true distribution of power over extended time periods and is necessary to quantify uncertainty in each step of diffusion modeling.
Key Points:• Determining uncertainty in wave power models is necessary to quantify uncertainty in radial diffusion coefficients for modeling • Our model of ground-based ULF wave power depends on solar wind speed, number density variance, and B z ; this outperforms hourly persistence • Total power over extended events is best modeled probabilistically, while the wave power in a single hour is best modeled deterministically 2019). Capturing uncertainty in magnetospheric ultralow frequency wave models. Space Weather, 17, 599-618. https://