气象与环境学报2016，Vol.32Issue(6)：130-136,7.DOI:10.3969/j.issn.1673-503X.2016.06.017
沈阳地区日光温室内最低气温变化特征及其预报模型研究
Variation characteristics and forecasting models of the minimum temperature in solar greenhouse in Shenyang
摘要
Abstract
Based on the meteorological observation data inside and outside solar greenhouse from 2013 to 2014 in Shenyang,variation characteristics and forecasting models of the minimum temperature (Tmin)in greenhouse were studied using methods of a correlation analysis and a stepwise regression analysis.The results show that Tmin inside the greenhouse is significantly correlated with the previous day′s maximum and minimum temperature outside the greenhouse,Tmin outside the greenhouse of the day,and the previous day′s maximum and minimum temperature in-side the greenhouse.Tmin forecasting models for the greenhouse are different depending on different weather types of the four seasons.Forecasting accuracy of the greenhouse Tmin is the highest in winter,followed in spring and au-tumn,and the forecasting accuracy in summer is relatively worse.The differences between observed and simulated greenhouse Tmin less than 3 ℃ in winter,spring,autumn,and summer account for 91%,85%,81% and 79%,re-spectively of the total samples for test.Forecasting accuracy of greenhouse Tmin is the highest in snowy rain days, followed in overcast days and sunny days,and the forecasting accuracy in cloudy days is relatively worse.The model accuracies for the simulated greenhouse Tmin less than 3 ℃ in snowy rain days,overcast days,sunny days, cloudy days are 90%,87%,83% and 77%,respectively.The results suggest the performance of the greenhouse Tmin forecasting model is satisfied and the models have their practical applicability,which provides a reference for the greenhouse Tmin forecast in Shenyang.关键词
日光温室/最低气温/天气类型/相关分析/逐步回归Key words
Solar greenhouse/The minimum temperature/Weather types/Correlation analysis/Stepwise regression analysis分类
天文与地球科学引用本文复制引用
李石,张菁,张淑杰,宋晓巍,慕臣英,徐全辉,郑闯,刘青..沈阳地区日光温室内最低气温变化特征及其预报模型研究[J].气象与环境学报,2016,32(6):130-136,7.基金项目
公益性行业（气象）科研专项“东北设施农业生产专业天气预报关键技术研究”（GYHY20120624）资助。 （）
