Oceanography and Atmospheric Sciences and Meteorology Commons^™

Ensemble Data Fitting For Bathymetric Models Informed By Nominal Data, Samantha Zambo

Dissertations

Due to the difficulty and expense of collecting bathymetric data, modeling is the primary tool to produce detailed maps of the ocean floor. Current modeling practices typically utilize only one interpolator; the industry standard is splines-in-tension.

In this dissertation we introduce a new nominal-informed ensemble interpolator designed to improve modeling accuracy in regions of sparse data. The method is guided by a priori domain knowledge provided by artificially intelligent classifiers. We recast such geomorphological classifications, such as ‘seamount’ or ‘ridge’, as nominal data which we utilize as foundational shapes in an expanded ordinary least squares regression-based algorithm. To our knowledge …

Analysis Of Uncertainty In Hydrometeorological Ensemble Forecasts, Carolien N. Mossel

Dissertations and Theses

Ensemble hydrometeorological forecasting has great potential for improving flood predictions and use in water management systems, however, the amount of data used and created with an ensemble forecast requires a careful and intentional approach to understand how useful and skillful the forecast is. The NOAA National Water Model (NWM) was run using downscaled NOAA Global Ensemble Forecast System (GEFS) meteorological forcings for the 2016-2017 wet season (October-March) in California to create an 11-member hydrologic forecast ensemble. To evaluate the performance of these ensemble forecasts, we chose to study streamflow sites within Sonoma County, California, a rain-dominated region which includes the …