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Abstract
For a century or so, the Hong Kong Observatory (HKO) has been providing temperature forecast for
the whole of Hong Kong with the HKO Headquarters as the reference location. In recent decades, due to
spreading of population from the main urban center to satellite towns, there is an increasing demand for
regional temperature forecasts. To support such provision, the HKO has developed a regression model to
provide objective guidance to forecasters in formulating forecasts of maximum and minimum temperatures
for the next day at various locations in Hong Kong. In this paper, the regression model is presented, together
with the assessment of its performance. Based on the verification of one year of forecasts, it is found that
the root mean square errors (RMSEs) of maximum (minimum) temperature forecasts are from about 1.3 to
2.1 (1.1 to 1.4) degrees, respectively. The regression model is shown to have generally out-performed the
operational regional spectral model then operated by HKO. Regional temperature forecast methods of other
meteorological or research centers are also surveyed. Equipped with the regression model, the HKO has
launched an online regional temperature forecast service for the next day in Hong Kong since March 2008.
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Citation
LAM Hilda, SHUM Karen Kit-ying, TANG Julian Shu-yan. 2011: Regional Temperature Forecast for the Next Day in Hong Kong. Journal of Meteorological Research, 25(6): 725-733. DOI: 10.1007/s13351-011-0603-9
LAM Hilda, SHUM Karen Kit-ying, TANG Julian Shu-yan. 2011: Regional Temperature Forecast for the Next Day in Hong Kong. Journal of Meteorological Research, 25(6): 725-733. DOI: 10.1007/s13351-011-0603-9
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LAM Hilda, SHUM Karen Kit-ying, TANG Julian Shu-yan. 2011: Regional Temperature Forecast for the Next Day in Hong Kong. Journal of Meteorological Research, 25(6): 725-733. DOI: 10.1007/s13351-011-0603-9
LAM Hilda, SHUM Karen Kit-ying, TANG Julian Shu-yan. 2011: Regional Temperature Forecast for the Next Day in Hong Kong. Journal of Meteorological Research, 25(6): 725-733. DOI: 10.1007/s13351-011-0603-9
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