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日光温室小气候要素预报模型研究 被引量:10

Microclimate Forecasting Model in Sunlight Greenhouse
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摘要 了解日光温室小气候要素变化规律,建立小气候要素预报模型,可以对日光温室资源合理开发,为日光温室小气候调控提供依据。应用辽宁省沈阳市东陵区日光温室暖棚内农田小气候观测仪采集的逐小时气温、相对湿度数据,将冬季、春季、秋季和晴天、多云、阴天几种情况进行组合,计算棚内日最高气温、日最低气温、日平均相对湿度,分析其变化规律,并利用自动气象观测站数据,建立基于逐步回归方法的预报模型。分析结果表明,日光温室内日最高气温和日最低气温呈现春季、秋季温度值接近,冬季明显低于春秋两季的特征;而冬季日平均相对湿度高于春秋两季。日最高气温具有显著的从晴天至多云至阴天减少的变化特征,日最低气温特征不如日最高气温明显;日平均相对湿度为从晴天至多云至阴天增加的变化特征。所建立的日光温室小气候要素逐步回归预报模型,均通过了显著性检验,相关系数为0.608~0.933,相对误差范围为0.1%~19.0%,相对误差平均值为2.7%~9.9%。 To study the change regulation of microclimate in sunlight greenhouse and establish the forecasting model of microclimate can provide a basis for rational development of greenhouse resources and microclimatecontrol in sunlight greenhouse. We used hourly temperature and relative humidity to form microclimateobservation instrument in sunlight greenhouse in Dongling of Shenyang, and calculated daily maximumtemperature, daily minimum temperature, daily average relative humidity by the combination of winter, spring,autumn and sunny, cloudy, overcast data, to analyze the microclimate change regulation. And a series offorecasting models based on stepwise regression method were established by using data from automaticmeteorological observation station. The results showed that the daily maximum temperature and daily minimumtemperature in sunlight greenhouse of spring and autumn were close, and that of winter was significantly lowerthan that of spring and autumn, but the daily average relative humidity in winter was higher than that in springand autumn. The daily maximum temperature reduced from sunny to cloudy to overcast days, characteristics ofthe daily maximum temperature were not obvious, but the daily average relative humidity increased from sunnyto cloudy to overcast days. The stepwise regression forecasting models of microclimate in sunlight greenhouseall passed the significance test, the correlation coefficient was from 0.608 to 0.933, the relative error range was from 0.1% to 19.0%, and the average value of relative error was from 2.7% to 9.9%.
作者 张晓月 李荣平 王莹 李琳琳 张琪 黄岩 李雨鸿 Zhang Xiaoyue;Li Rongping;Wang Ying;Li Linlin;Zhang Qi;Huang Yan;Li Yuhong(Institute of Meteorological Science of Liaoning ,Shenyang 110156)
出处 《中国农学通报》 2018年第32期113-118,共6页 Chinese Agricultural Science Bulletin
基金 辽宁省气象局科研类项目"日光温室小气候要素精确预报技术研究"(201706)
关键词 日光温室 气温 相对湿度 变化规律 预报模型 sunlight greenhouse temperature relative humidity change regulation forecasting model
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