黄淮冬麦区晚霜冻易发时段冠层内最低气温分布及估算

Estimation and Distribution of Minimum Air Temperature within Winter Wheat Canopy in Prone Period of Late Frost

利用2016年和2017年3月中旬-4月下旬两次典型低温过程中,冬小麦田间不同高度逐小时气象观测数据,分析晚霜冻易发时段冬小麦冠层内最低气温出现高度及其变化规律,构建基于150cm高度处气象因子和地表0cm温度的冠层内最低气温估算模型。结果表明:(1)与150cm高度相比,两次典型低温过程中0℃以下气温在冠层高度附近出现时间更早,持续时间更长且温度更低;(2)最低气温总是出现在4/5冠层高度附近,并在2:00-6:00时段,尤以5:00左右发生频率最高;(3)冠层内最低气温与150cm高度处相对湿度、风速的相关性通过了0.01水平的显著性检验,与不同高度气温、不同土壤深度地温的相关性也通过了0.001水平的显著性检验,与地温的相关性随着土壤深度的增加而逐渐降低;(4)冠层内最低气温与150cm高度处气温、风速、相对湿度,以及0cm地温的偏相关系数大小排序表现为,气温>风速>地温>相对湿度;利用以上因子构建基于多元线性回归函数的冠层内最低气温估测模型,其估测值与实测值拟合结果的决定系数达到0.967,均方根误差为0.915。说明基于气象台站常规观测数据构建冠层内最低气温估测模型具备一定可行性,可为冬小麦晚霜冻害的监测预报提供数据支持。

Using the hourly meteorological observation data at different heights within winter wheat canopy in 2016 and 2017,the height and variation of minimum air temperature within winter wheat canopy during the prone period of late frost were analyzed.An estimation model for canopy minimum air temperature was established based on the meteorological factors at the 150cm height and soil temperature at 0cm depth.The results indicated that:(1)the air temperature below 0℃appeared earlier and lasted longer near the canopy.(2)The minimum air temperature appeared mostly at about 4/5 of the highest canopy and between AM 2:00 and AM 6:00,especially at AM 5:00.(3)Correlation of the canopy minimum air temperature with relative humidity and wind speed at 150cm height reaches P<0.01 significant level,and correlation with air temperature at different heights and soil temperature at different depths reaches P<0.001 significance level,and correlation with soil temperature decreases as the soil depth increases.(4)The value of partial correlation coefficient of the canopy minimum air temperature with air temperature,wind speed,relative humidity at 150cm height,and soil temperature at 0cm depth,were listed as temperature>wind speed>soil temperature>relative humidity.An estimation model for canopy minimum air temperature was established by multiple linear regression function.The coefficient of determination(Adj.R2)reached 0.967 and the root mean square error(RMSE)was 0.915.It was feasible to establish the estimation model for canopy minimum air temperature based on the conventional observation data of meteorological stations.The model could provide valuable information on monitoring and predicting for late frost in winter wheat.