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Performance of Hourly Operational Consensus Forecasts (OCFs) in the Australian Region
Author(s) -
Chermelle Engel,
Elizabeth E. Ebert
Publication year - 2007
Publication title -
weather and forecasting
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.393
H-Index - 106
eISSN - 1520-0434
pISSN - 0882-8156
DOI - 10.1175/2007waf2006104.1
Subject(s) - downscaling , environmental science , meteorology , wind speed , wind direction , numerical weather prediction , climatology , precipitation , geography , geology
This paper presents an extension of the operational consensus forecast (OCF) method, which performs a statistical correction of model output at sites followed by weighted average consensus on a daily basis. Numerical weather prediction (NWP) model forecasts are received from international centers at various temporal resolutions. As such, in order to extend the OCF methodology to hourly temporal resolution, a method is described that blends multiple models regardless of their temporal resolution. The hourly OCF approach is used to generate forecasts of 2-m air temperature, dewpoint temperature, RH, mean sea level pressure derived from the barometric pressure at the station location (QNH), along with 10-m wind speed and direction for 283 Australian sites. In comparison to a finescale hourly regional model, the hourly OCF process results in reductions in average mean square error of 47% (air temperature), 40% (dewpoint temperature), 43% (RH), 29% (QNH), 42% (wind speed), and 11% (wind direction) during February–March with slightly higher reductions in May. As part of the development of the approach, the systematic and random natures of hourly NWP forecast errors are evaluated and found to vary with forecast hour, with a diurnal modulation overlaying the normal error growth with time. The site-based statistical correction of the model forecasts is found to include simple statistical downscaling. As such, the method is found to be most appropriate for meteorological variables that vary systematically with spatial resolution.

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