Verification of the Global Forecast System, North American Mesoscale Forecast System, and High-Resolution Rapid Refresh Model Near-Surface Forecasts by use of the New York State Mesonet
Lauriana C. Gaudet, Kara J. Sulia, R. Torn, Nick P. Bassill
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引用次数: 0
Abstract
Global Forecast System (GFS), North American Mesoscale Forecast System (NAM), and High-Resolution Rapid Refresh (HRRR) 2-m temperature, 10-m wind speed, and precipitation accumulation forecasts initialized at 1200 UTC are verified against New York State Mesonet (NYSM) observations from 1 January 2018 through 31 December 2021. NYSM observations at 126 site locations are used to calculate standard error statistics (e.g., forecast error, root mean square error) for temperature and wind speed and contingency table statistics for precipitation across forecast hours, meteorological seasons, and regions. The majority of the focus is placed on the first 18 forecast hours to allow for comparison among all three models. A daily NYSM station-mean temperature error analysis identified a slight cold bias at temperatures below 25°C in the GFS, a cool-to-warm bias as forecast temperatures warm in the HRRR, and a warm bias at temperatures above 30°C in each model. Differences arise when considering temperature biases with respect to lead times and seasons. Wind speeds are over-forecast at all ranges in each season, and forecast wind speeds ≥ 18 m s−1 are rarely observed. Performance diagrams indicate overall good forecast performance at precipitation thresholds of 0.1–1.5 mm, but with a high frequency bias in the GFS and NAM. This paper provides an overview of deterministic forecast performance across NYS, with the aim of sharing common biases associated with temperature, wind speed, and precipitation with operational forecasters and is the first step in developing a real-time model forecast uncertainty prediction tool.
期刊介绍:
Weather and Forecasting (WAF) (ISSN: 0882-8156; eISSN: 1520-0434) publishes research that is relevant to operational forecasting. This includes papers on significant weather events, forecasting techniques, forecast verification, model parameterizations, data assimilation, model ensembles, statistical postprocessing techniques, the transfer of research results to the forecasting community, and the societal use and value of forecasts. The scope of WAF includes research relevant to forecast lead times ranging from short-term “nowcasts” through seasonal time scales out to approximately two years.