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内蒙古东部温室大棚温度特征分析及预报模型建立
引用本文:张超,吴瑞芬.内蒙古东部温室大棚温度特征分析及预报模型建立[J].中国农学通报,2014,30(26):213-218.
作者姓名:张超  吴瑞芬
作者单位:1. 内蒙古生态与农业气象中心2.
基金项目:公益性行业(气象)科研专项经费项目“华北日光温室小气候资源高效利用技术研究”(GYHY201306039)
摘    要:为了充分掌握温室大棚内温度变化规律,实现温棚内极端温度的预报、预警,提高农业气象服务保障能力,充分利用2012年全年的内蒙古东部赤峰市温室大棚内、棚外的逐小时气温对比观测资料,分析温棚内气温的月平均日变化、典型日变化和最高气温、最低气温出现的次数和概率;分析温棚内最高气温与最低气温变化规律、温棚内外气温相互关系,利用回归的方法建立晴天温室大棚内温度预报模型。结果表明,不同季节的棚内气温日变化差异明显,棚内最高气温春秋季出现在9:00—10:00时、13:00—14:00时,冬季出现在12:00—15:00时;最低气温春季出现在5:00—7:00时、秋季6:00—7:00时、冬季7:00—8:00时;回归分析方法能较好地模拟棚内温度变化,对最低气温预报上具有更好的效果。

关 键 词:烤烟  烤烟  地膜覆盖  移栽  生长发育  
收稿时间:1/8/2014 12:00:00 AM
修稿时间:2014/2/19 0:00:00

Analyze of Greenhouses Temperature Characteristic and Temperature Prediction Model in Eastern Inner Mongolia
Zhang Chao,Wu Ruifen.Analyze of Greenhouses Temperature Characteristic and Temperature Prediction Model in Eastern Inner Mongolia[J].Chinese Agricultural Science Bulletin,2014,30(26):213-218.
Authors:Zhang Chao  Wu Ruifen
Institution:(Inner Mongolia Ecological and Agricultural Meteorological Center, Hohhot 010051)
Abstract:In order to fully grasp the change rule of temperature in greenhouses, to forecast the extreme temperature within greenhouse and to improve the service support capability of agricultural meteorological, the author used the inside the greenhouse temperature contrast hour observation data in Chifeng of eastern Inner Mongolia in 2012. The author analyzed the diurnal variation of the temperature within greenhouse, typical daily variation, the highest temperature and minimum temperature and the number of occurrences of probability, and analyzed the relationship between the temperature inside and outside the greenhouse, and then used the method of regression analysis, respectively, established the greenhouse temperature prediction model in sunny day. Results showed that: the daily variation of the temperature difference of different season, the highest and lowest temperatures of each season there was not the same time and the temperature of the regression analysis method to build the prediction model had better effect on the lowest temperature forecast.
Keywords:the temperature prediction model
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