Average Forecast Errors Using MM5 and WRF Over Complex Terrain: Utah, July/August 2003 and January/February 2004

Sauter, Barbara; Henmi, Teizi

doi:10.21236/ada428275

Cited by 2 publications

(2 citation statements)

References 2 publications

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“…Wind-direction RMSE values of 591 and 661 were found for numerical forecasts made for Sydney 2000 Olympic Games (Spark and Connor, 2004). Comparisons of WRF and MM5 models run over complex terrain in Utah found typical winddirection errors of 501-601 (Sauter and Henmi, 2004). Wind-speed RMSEs are much more commonly reported and vary widely from 2.5 m s À 1 (Spark and Connor, 2004) to $ 6 m s À 1 (e.g., Nutter and Manobianco, 1999;Bauman, 2010).…”

Section: Verification Metricsmentioning

confidence: 99%

Forecasting near-surface weather conditions and precipitation in Alaska's Prince William Sound with the PWS-WRF modeling system

Olsson

Volz

Liu

2013

Continental Shelf Research

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In the summer of 2009, several scientific teams engaged in a field program in Prince William Sound (PWS), Alaska to test an end-to-end atmosphere/ocean prediction system specially designed for this region. The ''Sound Predictions Field Experiment'' (FE) was a test of the PWS-Observing System (PWS-OS) and the culmination of a five-year program to develop an observational and prediction system for the Sound. This manuscript reports on results of an 18-day high-resolution atmospheric forecasting field project using the Weather Research and Forecasting (WRF) model. Special attention was paid to surface meteorological properties and precipitation. Upon reviewing the results of the real-time forecasts, modifications were incorporated in the PWS-WRF modeling system in an effort to improve objective forecast skill. Changes were both geometric (model grid structure) and physical (different physics parameterizations). The weather during the summertime FE was typical of the PWS in that it was characterized by a number of minor disturbances rotating around an anchored low, but with no major storms in the Gulf of Alaska. The basic PWS-WRF modeling system as implemented operationally for the FE performed well, especially considering the extremely complex terrain comprising the greater PWS region. Modifications to the initial PWS-WRF modeling system showed improvement in predicting surface variables, especially where the ambient flow interacted strongly with the terrain. Prediction of precipitation on an accumulated basis was more accurate than prediction on a day-today basis. The 18-day period was too short to provide reliable assessment and intercomparison of the quantitative precipitation forecasting (QPF) skill of the PWS-WRF model variants.

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Section: Verification Metricsmentioning

confidence: 99%

Forecasting near-surface weather conditions and precipitation in Alaska's Prince William Sound with the PWS-WRF modeling system

Olsson

Volz

Liu

2013

Continental Shelf Research

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“…In a previous study, two mesoscale forecast models were run over northern Utah (1). These models were the Pennsylvania State University/National Center for Atmospheric Research (NCAR) Mesoscale Model Version 5 (MM5) and the first version of the Weather Research and Forecasting (WRF) model, under development by NCAR, the National Oceanic and Atmospheric Administration, and several universities (2,3).…”

Section: Introductionmentioning

confidence: 99%

A Case Study of the Persistence of Weather Forecast Model Errors

Sauter¹

2005

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Average Forecast Errors Using MM5 and WRF Over Complex Terrain: Utah, July/August 2003 and January/February 2004

Cited by 2 publications

References 2 publications

Forecasting near-surface weather conditions and precipitation in Alaska's Prince William Sound with the PWS-WRF modeling system

Forecasting near-surface weather conditions and precipitation in Alaska's Prince William Sound with the PWS-WRF modeling system

A Case Study of the Persistence of Weather Forecast Model Errors

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