Modeling our atmosphere and determining forecasts using numerical methods has been a challenge since the early 20th Century. Most models use a complex dynamical system of equations that prove difficult to solve by hand as they are chaotic by nature. When computer systems became more widely adopted and available, approximating the solution of these equations, numerically, became easier as computational power increased. This advancement in computing has caused numerous weather models to be created and implemented across the world. However a challenge of approximating these solutions accurately still exists as each model have varying set of equations and variables to approximate.
The model under consideration in this paper is the Weather Research and Forecast model (WRF). This model takes input from data files as initial conditions, often from other models, and runs a simulation based on its own set of equations and conditions.
","abstract_html":"<p>Modeling our atmosphere and determining forecasts using numerical methods has been a challenge since the early 20th Century. Most models use a complex dynamical system of equations that prove difficult to solve by hand as they are chaotic by nature. When computer systems became more widely adopted and available, approximating the solution of these equations, numerically, became easier as computational power increased. This advancement in computing has caused numerous weather models to be created and implemented across the world. However a challenge of approximating these solutions accurately still exists as each model have varying set of equations and variables to approximate.</p> <p>The model under consideration in this paper is the Weather Research and Forecast model (WRF). This model takes input from data files as initial conditions, often from other models, and runs a simulation based on its own set of equations and conditions.</p>","abstract_has_math":false,"creators":["Baker, Aaron D"],"institution":null,"degree_name":"Master of Science - Mathematical Sciences","degree_level":"Thesis","degree_discipline":"Mathematics and Statistics","degree_department":null,"school":null,"contributors":["Lynn Greenleaf, Ph.D.","Jeremy Becnel, Ph.D.","Christopher Ivancic, Ph.D."],"advisors":[],"committee_chairs":[],"committee_members":[],"year":2021,"date_issued":"2021-05-01T07:00:00Z","date_published":"2021-05-01T07:00:00Z","updated_at":"2026-07-24T04:30:30Z","subjects":["meteorology","partial differential equations","modeling","statistics","simulations","Atmospheric Sciences","Numerical Analysis and Scientific Computing"],"languages":[],"rights":[],"rights_urls":[],"identifier_entries":[]},"links":{"outbound_url":"https://scholarworks.sfasu.edu/etds/377","outbound_label":"Repository record","outbound_source":"dc:identifier"},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:contributor","label":"Contributor","values":["Lynn Greenleaf, Ph.D.","Jeremy Becnel, Ph.D.","Christopher Ivancic, Ph.D."]},{"key":"dc:creator","label":"Author","values":["Baker, Aaron D"]}]},{"id":"academic_context","label":"Academic Context","entries":[{"key":"dc:date.available","label":"Dc Date Available","values":["2021-04-29T07:00:00Z"]},{"key":"thesis:degree_discipline","label":"Discipline","values":["Mathematics and Statistics"]},{"key":"thesis:degree_level","label":"Degree Level","values":["Thesis"]},{"key":"thesis:degree_name","label":"Degree Name","values":["Master of Science - Mathematical Sciences"]}]},{"id":"subjects_keywords","label":"Subjects and Keywords","entries":[{"key":"dc:subject","label":"Dc Subject","values":["meteorology","partial differential equations","modeling","statistics","simulations","Atmospheric Sciences","Numerical Analysis and Scientific Computing"]}]},{"id":"identifiers","label":"Identifiers","entries":[{"key":"dc:identifier","label":"Identifier","values":["https://scholarworks.sfasu.edu/etds/377"]}]},{"id":"additional","label":"Additional Metadata","entries":[{"key":"dc:description.abstract","label":"Abstract","values":["Modeling our atmosphere and determining forecasts using numerical methods has been a challenge since the early 20th Century. Most models use a complex dynamical system of equations that prove difficult to solve by hand as they are chaotic by nature. When computer systems became more widely adopted and available, approximating the solution of these equations, numerically, became easier as computational power increased. This advancement in computing has caused numerous weather models to be created and implemented across the world. However a challenge of approximating these solutions accurately still exists as each model have varying set of equations and variables to approximate.
The model under consideration in this paper is the Weather Research and Forecast model (WRF). This model takes input from data files as initial conditions, often from other models, and runs a simulation based on its own set of equations and conditions.
"]},{"key":"dc:title","label":"Title","values":["The Effect of Initial Conditions on the Weather Research and Forecasting Model"]}]}],"canonical_facts":{"dc:contributor":["Lynn Greenleaf, Ph.D.","Jeremy Becnel, Ph.D.","Christopher Ivancic, Ph.D."],"dc:creator":["Baker, Aaron D"],"dc:date.available":["2021-04-29T07:00:00Z"],"dc:description.abstract":["Modeling our atmosphere and determining forecasts using numerical methods has been a challenge since the early 20th Century. Most models use a complex dynamical system of equations that prove difficult to solve by hand as they are chaotic by nature. When computer systems became more widely adopted and available, approximating the solution of these equations, numerically, became easier as computational power increased. This advancement in computing has caused numerous weather models to be created and implemented across the world. However a challenge of approximating these solutions accurately still exists as each model have varying set of equations and variables to approximate.
The model under consideration in this paper is the Weather Research and Forecast model (WRF). This model takes input from data files as initial conditions, often from other models, and runs a simulation based on its own set of equations and conditions.
"],"dc:identifier":["https://scholarworks.sfasu.edu/etds/377"],"dc:subject":["meteorology","partial differential equations","modeling","statistics","simulations","Atmospheric Sciences","Numerical Analysis and Scientific Computing"],"dc:title":["The Effect of Initial Conditions on the Weather Research and Forecasting Model"],"thesis:degree_discipline":["Mathematics and Statistics"],"thesis:degree_level":["Thesis"],"thesis:degree_name":["Master of Science - Mathematical Sciences"]},"updated_at":"2026-07-24T04:30:30Z"}