摘要
利用2006~2010年陕西10地市逐小时的气温和逐日的最高气温、最低气温、平均总云量、降水量资料,通过线性回归方法建立了一种基于日最高气温和最低气温预报以及临近气温实况资料的逐时气温预报模型,并对2011年每天的逐时气温预报进行检验。结果表明:该方法在晴天、多云和阴雨天的预报能力依次减弱,其中晴天和多云天02~18时的预报效果好于19时至次日01时的,而阴雨天01~10时的预报效果好于其它预报时段的;当日最高气温和最低气温预报较为准确时,西安站各预报时刻的准确率均在60%以上,其中14~17时的准确率较高,晴天的达到100%,多云天的在96%~99%之间,阴雨天的准确率偏低一些,特别是11~17时较晴天和多云天偏低了12%~27%;该方法可以将24 h日最高(低)气温预报细化到逐时气温预报,同时考虑了气温日变化的地域差异、季节特征、以及在晴天、多云和阴雨天的不同表现,具有一定的业务应用和推广价值。
Based on the observation data of hourly temperature,daily maximum and minimum temperature,daily mean total cloud cover and rainfall from ten stations in Shaanxi Province from 2006 to 2010,a forecast method of hourly temperature was established by using linear regression method on the basis of forecast values of daily maximum and minimum temperature and observed values of hourly tem-perature,which was tested by comparing forecast values with observed values of hourly temperature at ten stations in Shaanxi Province in 2011. The results show that the forecasting ability of the forecast method of hourly temperature under sunny or lightly cloudy condi-tions was better than that under heavily cloudy or rainy conditions. The forecasting effect of the method was better between 2 o’clock and 18 o’clock than that between 19 o’clock and 1 o’clock of the next day on sunny or lightly cloudy days,and was better between 1 o’clock and 10 o’clock than that at other time on heavily cloudy or rainy days. When the forecasted daily maximum and minimum tem-perature were comparatively accurate,the forecast accuracy of hourly temperature was more than 60% at Xi’an station. The accuracy was 100% on sunny days and from 96% to 99% on lightly cloudy days between 14 o’clock and 17 o’clock. But the accuracy on heav-ily cloudy or rainy days was about 12% ~27% lower than that on sunny or lightly cloudy days between 11 o’clock and 17 o’clock. With the characteristic of diurnal variations of temperature change in different areas,seasons and sky conditions,the method can turn the forecasted daily maximum and minimum temperature into forecast of hourly temperature well. To some extent the forecast method of hourly temperature has application and extension values.
出处
《干旱气象》
2015年第1期89-97,共9页
Journal of Arid Meteorology
基金
干旱气象科学研究基金"西北夏季无降水日数与高温热浪的关系"(IAM201306)资助
关键词
逐时气温预报
线性回归方法
预报准确率
forecast method of hourly temperature
linear regression method
forecast accuracy