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On running a numerical weather prediction model from an ensemble mean initial and boundary condition Steinhart, Rachel
Abstract
The North American Ensemble Forecast System (NAEFS) is used as initial and boundary conditions (IBCs) for the Weather Research and Forecasting Model (WRF) to determine whether ensemble mean initial conditions can be used to successfully initialize a deterministic model, and to analyze how well they perform. Ensemble-average forecasts are usually more accurate than deterministic forecasts, even though the relationship between different forecast fields such as pressure, temperature, and winds can be unphysical. For this reason, it has been often assumed that ensemble average forecasts cannot be used as initial conditions for deterministic models. This research challenges that assumption. Two parallel WRF runs are tested: one with NAEFS ensemble mean IBCs, and the other with traditional deterministic IBCs from the Global Forecast System (GFS) to serve as a benchmark. The NAEFS initialized forecast (NAEFS-WRF) and the GFS initialized forecast (GFS-WRF) were run for a full year, September 2019 through August 2020. The model was set up to cover British Columbia, Canada and Alberta, Canada, with a 36 km horizontal grid scale. Two-meter hourly temperature, two-meter daily maximum and minimum temperatures, daily accumulated precipitation and 90th percentile daily accumulated precipitation events were verified against station observations to determine the accuracy of both NAEFS-WRF and GFS-WRF. The NAEFS-WRF forecast showed increasing skill compared to the GFS-WRF forecast at longer forecast horizons. The mean absolute error (MAE) spread and range was very similar for both forecasts, indicating that they performed similarly, and NAEFS-WRF developed no unreasonable trends in spite of the supposedly “unphysical” NAEFS fields. For rare/extreme (90th percentile) precipitation events, GFS-WRF was slightly more accurate at all forecast horizons. However, NAEFS-WRF was superior in high-precipitation subdomains, such as along the British Columbia coast and in Northern British Columbia at longer forecast horizons. The False Alarm Ratio and Probability of detection results showed that both forecasts could categorically predict whether precipitation would occur almost 90% of the time. This study finds that ensemble mean IBCs can be used to successfully drive a higher-resolution deterministic forecast model to create a reasonable forecast.
Item Metadata
Title |
On running a numerical weather prediction model from an ensemble mean initial and boundary condition
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Creator | |
Supervisor | |
Publisher |
University of British Columbia
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Date Issued |
2022
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Description |
The North American Ensemble Forecast System (NAEFS) is used as initial and boundary conditions (IBCs) for the Weather Research and Forecasting Model (WRF) to determine whether ensemble mean initial conditions can be used to successfully initialize a deterministic model, and to analyze how well they perform. Ensemble-average forecasts are usually more accurate than deterministic forecasts, even though the relationship between different forecast fields such as pressure, temperature, and winds can be unphysical. For this reason, it has been often assumed that ensemble average forecasts cannot be used as initial conditions for deterministic models. This research challenges that assumption.
Two parallel WRF runs are tested: one with NAEFS ensemble mean IBCs, and the other with traditional deterministic IBCs from the Global Forecast System (GFS) to serve as a benchmark. The NAEFS initialized forecast (NAEFS-WRF) and the GFS initialized forecast (GFS-WRF) were run for a full year, September 2019 through August 2020. The model was set up to cover British Columbia, Canada and Alberta, Canada, with a 36 km horizontal grid scale. Two-meter hourly temperature, two-meter daily maximum and minimum temperatures, daily accumulated precipitation and 90th percentile daily accumulated precipitation events were verified against station observations to determine the accuracy of both NAEFS-WRF and GFS-WRF.
The NAEFS-WRF forecast showed increasing skill compared to the GFS-WRF forecast at longer forecast horizons. The mean absolute error (MAE) spread and range was very similar for both forecasts, indicating that they performed similarly, and NAEFS-WRF developed no unreasonable trends in spite of the supposedly “unphysical” NAEFS fields. For rare/extreme (90th percentile) precipitation events, GFS-WRF was slightly more accurate at all forecast horizons. However, NAEFS-WRF was superior in high-precipitation subdomains, such as along the British Columbia coast and in Northern British Columbia at longer forecast horizons. The False Alarm Ratio and Probability of detection results showed that both forecasts could categorically predict whether precipitation would occur almost 90% of the time.
This study finds that ensemble mean IBCs can be used to successfully drive a higher-resolution deterministic forecast model to create a reasonable forecast.
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Genre | |
Type | |
Language |
eng
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Date Available |
2022-04-11
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Provider |
Vancouver : University of British Columbia Library
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Rights |
Attribution-NonCommercial-NoDerivatives 4.0 International
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DOI |
10.14288/1.0412754
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URI | |
Degree | |
Program | |
Affiliation | |
Degree Grantor |
University of British Columbia
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Graduation Date |
2022-05
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Campus | |
Scholarly Level |
Graduate
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Rights URI | |
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DSpace
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Rights
Attribution-NonCommercial-NoDerivatives 4.0 International