云量的时间精细化预报研究-以榆中为例

利用2001年7月至2011年7月甘肃省榆中县地面测站的每日8次云量资料和同期NCEP每日4次等压面资料，由NCEP资料构造预报因子，以总云量和低云量为预报对象，分析预报因子和预报对象的相关性，采用逐步回归方法建立榆中县逐月8个时次的云量预报方程并进行回代；并利用2012年的资料检验预报方程的预报效果。结果表明：云量主要受整层湿度、垂直运动、不稳定能量、槽强度指数和700 hPa水汽通量散度影响，其中湿度状况和垂直运动是重要因素。建立的预报方程对总云量的预报效果比低云量好；总云量平均预报误差在2成左右，低云量平均预报误差在3成左右；预报值变化趋势可以部分地反映实际云量的变化趋势。

Refined forecast of cloud cover based on a case study in Yuzhong

Based on daily cloud cover data with 3 hours interval and corresponding NCEP data with 6 hours interval from July of 2001 to July of 2011 in Yuzhong of Gansu province, relationships between forecast factors built by the NCEP data and forecast object such as the total cloud cover and low cloud cover were analyzed. A series of monthly forecast equations of cloud cover with daily 8 times was established by a stepwise regression analysis method and were tested by back substitution, and then prediction effect was checked using data of 2012. The results show that cloud cover is mainly affected by the whole layer humidity, vertical velocity, instability energy, trough intensity index and divergence of moisture flux in 700 hPa, especially the first two elements. Forecast effect of total cloud cover is better than that of low cloud cover; average errors of total cloud cover and low cloud cover are about 20% and about 30%, respectively. Tendency of predicted values can partly reflect that of observed values.