Investigating the utility of weighting schemes on a 51-member short-range ensemble forecast
department or school: Science, Faculty of
department or school: Earth, Ocean and Atmospheric Sciences, Department of
data provider: DSpace
degree campus: UBCV
creator: McKinney, Reagan
issued: 2024-02-26T18:59:03Z
issued: 2024
related degree: Master of Science - MSc
degree grantor: University of British Columbia
description: Accurate weather predictions are crucial to the wellbeing of modern society. The Weather Forecast Research Team (WFRT) runs an ensemble of numerical weather prediction models daily (Short Range Ensemble Forecast; SREF 00Z). The ensemble can be combined into an “average” which is usually the best deterministic forecast. In this study, we experiment with ways of improving its skill for southwestern British Columbia. To do this, four different weighting techniques for ensemble averaging are employed using all 51 members of the SREF. These are constructed using 1 year (October 2021-September 2022) of forecasts and observation data pairs from 90 stations in the region, for temperature, wind speed and precipitation. The weights were then applied to a second year of data (October 2022-September 2023) and compared to the current SREF. To investigate the use of a shorter training set on the weights, as suggested by the literature, a sliding window approach was also used with the weights being calculated with the forecast and observation data pairs for the week and month prior to the forecast of interest. We also experimented with varying the number of ensemble members to explore the sensitivity of the SREF to the number of members. Spatially, there were some special cases where the weighted ensembles performed better or poorer than the current SREF. However, all four weighting schemes did not perform statistically significantly compared to the current equally-weighted SREF (pvalue > 0.05). As for the varying number of ensemble members, it was found that the skill of all of the ensembles varied throughout the year and was never consistently in the small or large range for all tested variables. However, we did note that the skill converged for all members greater than 30. This indicated a lower limit of the necessary ensemble members to match the current SREF skill. Future studies should include more data (i.e. longer datasets; climatology) to get a better picture of the state…
aggregated CHO: https://circle.library.ubc.ca/rest/handle/2429/87478
note: Investigating the utility of weighting schemes on a 51-member short-range ensemble forecast by Reagan McKinney B.A.Sc. Environmental Engineering, University of Waterloo, 2021 A THESIS SUBMITTED IN PARTIAL FULFILLMENT OF THE REQUIREMENTS FOR THE DEGREE OF MASTER OF SCIENCE in THE FACULTY OF GRADUATE AND POSTDOCTORAL STUDIES (Atmospheric Science) The University of British Columbia (Vancouver) February 2024 © Reagan McKinney, 2024 ii The following individuals certify that they have read, and recommend to the Faculty of Graduate and Postdoctoral Studies for acceptance, the thesis entitled: Investigating the utility of weighting schemes on a 51-member short-range ensemble forecast submitted by Reagan McKinney in partial fulfilment of the requirements for the degree of Master of Science in Atmospheric Science Examining Committee: Roland Stull, Professor, Atmospheric Sciences, UBC Supervisor Rachel White, Assistant Professor, Atmospheric Sciences, UBC Supervisory Committee Member Rosie Howard, Research Director, Atmospheric Sciences, UBC Supervisory Committee Member Doug McCollor, Adjunct Professor, Atmospheric Sciences. UBC Additional Examiner iii Abstract Accurate weather predictions are crucial to the wellbeing of modern society. The Weather Forecast Research Team (WFRT) runs an ensemble of numerical weather prediction models daily (Short Range Ensemble Forecast; SREF 00Z). The ensemble can be combined into an “average” which is usually the best deterministic forecast. In this study, we experiment with ways of improving its skill for southwestern British Columbia. To do this, four different weighting techniques for ensemble averaging are employed using all 51 members of the SREF. These are constructed using 1 year (October 2021-September 2022) of forecasts and observation data pairs from 90 stations in the region, for temperature, wind speed and precipitation. The weights were then applied to a second year of data (October 2022-September 2023) and compared to the curren…
has type: Thesis/Dissertation
date issued: 2024-05
is shown at: 10.14288/1.0440411
language: eng
degree discipline: Atmospheric Science
provider: Vancouver : University of British Columbia Library
publisher: University of British Columbia
rights: Attribution-NonCommercial-NoDerivatives 4.0 International
rights URI: http://creativecommons.org/licenses/by-nc-nd/4.0/
scholar level: Graduate
contributor: Stull, Roland B., 1950-
type: Text
identifier URI: http://hdl.handle.net/2429/87478