Based on temperature data monitored inside the greenhouse and the corresponding surface meteorological observation data, authors established a forecasting model for the highest and lowest temperature in the sunlight greenhouse in autumn, as well as in the sunny and overcast sky separately in winter and spring, by means of stepwise regression method. The models were also tested in the application. The results showed that the absolute error ( ABSE) of the highest and lowest temperatures between the simulated values and the actual values were separately 1. 1 andrn0. 2℃ in autumn,0. 8 and 0.4℃ in the sunny day in winter, 1. 5 and 0. 3℃ in the overcast sky in winter,0. 3 and 0.4℃ in the sunny day in spring,1. 1 and 0. 2℃ in the overcast sky in spring. The root mean square error( RMSE) were separately 1. 3 and 0. 2℃ in autumn, 1. 0 and 0. 5℃ in the sunny day in winter, 1. 7 and 0. 3℃ in the overcast sky in winter,0. 3 and 1. 3℃ in the sunny day in spring,0. 4 and 0. 5℃ in the overcast sky in spring. The ABSE of the highest and lowest temperatures between the simulated values and the actual values in autumn were separately 0. 8 -rn1. 1℃ and 0. 3 -0. 4℃ and the root mean square error were 0. 9 - 1. 2℃ and 0. 3 -0. 5℃ in the examination. This forecast model which can be used to predict the highest and lowest temperatures in future 24 hours inside the sunlight greenhouse, can provide effective decision support for timely ventilation in greenhouse to prevent high temperature as well as for heat insulation measures to prevent cold harm.%利用2010年11月-2011年5月在日光温室内部监测的温度数据和同期地面气象观测资料,采用逐步回归方法,建立秋季日光温室内部最高与最低气温预报模型,冬季和春季晴天与非晴天日光温室内部最高与最低气温预报模型,并进行应用试验.结果表明,各预报模型的模拟值与实测值之间高温和低温的绝对误差(ABSe)分别为秋季为1.1、0.2℃,冬季晴天与非晴天为0.8、0.4和1.5、0.3℃,春季晴天与非晴天为0.3、0.4和1.1、0.2℃；均方根误差(RMSe)分别为秋季为1.3、0.2℃,冬季晴天与非晴天为1.0、0.5和1.7、0.3℃,春季晴天与非晴天为0.3、1.3和0.4、0.5℃.试验预报时段内日光温室内部高温与低温的绝对误差范围分别为0.8～1.1和0.3～0.4℃,均方根误差为0.9 ～1.2和0.3～0.5℃.依据预报模型开展日光温室内部未来24h内的最高与最低气温预报,可为日光温室及时通风换气防止高温危害及采取保温措施防止低温危害提供有效的决策支持.
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