Publication Date

2025

Document Type

Dissertation/Thesis

First Advisor

Michaelis, Allison C.

Degree Name

M.S. (Master of Science)

Legacy Department

Department of Geographic and Atmospheric Sciences

Abstract

The research a long-term, high-resolution (15-km) global simulation using the Model for Prediction Across Scales – Atmosphere (MPAS-A) version 7.0, a community atmospheric modeling platform with unique capabilities for weather and climate research. This simulation spans 30 continuous years, covering water years 1990 through 2019 (i.e., 1 October 1989–30 September 2019) and is initialized with the European Centre for Medium-Range Weather Forecasts Reanalysis v5 (ERA5). Sea surface temperatures and sea ice are prescribed and updated daily using the fine-scale (0.05°) Operational Sea Surface Temperature and Ice Analysis (OSTIA). To date, this is one of the few high-resolution MPAS-A simulations at the climate scale to date.

This study analyzes how MPAS-A represents atmospheric variables such as 2-meter temperature (T2M), mean sea-level pressure (MSLP), 500-hPa geopotential height (Z500), and 250-hPa zonal wind (U250) compares to ERA5. We find that MPAS-A reasonably captures large-scale atmospheric features and their variability in the Northern Hemisphere, including maritime sea-level pressure systems, upper-tropospheric flow regimes, and mid-tropospheric height patterns. To further evaluate the ability of MPAS-A to replicate high-impact weather, this study examines the representation of the Northern Hemispheric tropical cyclone (TC) climatology by tracking simulated TCs using the objective TempestExtremes tracking algorithm and compare results to the International Best Track Archive for Climate Stewardship (IBTrACS) across major Northern Hemisphere ocean basins. These results indicate that MPAS-A effectively captures key TC characteristics, including intensity, location, and seasonality in both hemispheres. However, MPAS-A struggles to generate TCs in the main development region (MDR) of the North Atlantic (NATL), likely due to positive vertical wind shear and negative specific humidity biases.

These findings highlight the capability of MPAS-A to reproduce large-scale climate patterns and extreme weather events at spatial resolutions generally unachievable by general circulation models. These results demonstrate the utility of MPAS-A for studying climate-scale phenomena and suggest its applicability for future research on high-impact weather systems, including TCs, within a model-relative framework.

Extent

102 pages

Language

en

Publisher

Northern Illinois University

Rights Statement

In Copyright

Rights Statement 2

NIU theses are protected by copyright. They may be viewed from Huskie Commons for any purpose, but reproduction or distribution in any format is prohibited without the written permission of the authors.

Media Type

Text

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