基于ForcTT模型的开化县油菜花期预报

[目的]为及时向政府和游客提供准确的花期预报,指导乡村旅游活动,[方法]应用2004-2015年油菜生育期观测资料和地面气象观测资料,建立基于ForcTT模型的有效积温法则和逐步回归两种不同的预测模型。[结果]结果表明：基于ForcTT模型的有效积温法则有效避免了有效积温法则中各生育期不确定性的问题。两种预测模型得到的近三年普花期预测值结果相近,与实况值偏差略大,但能准确体现前后年的花期变化。经异地调查发现,积温模型更能体现花期在不同区域的时间差异。[结论]由此,基于ForcTT模型的有效积温法则可作为油菜花期预报的有效手段,为开展更有效的旅游气象服务提供技术支撑。

Prediction of Rape Florescence Based on ForcTT Model in Kaihua

[Objective] This study was completed to provide timely and accurate forecast to the government and tourists, guide rural tourism activities. [Method]Two different prediction models , the effective accumulated temperature rule based on the ForcTT model and the stepwise regression, were established based on the observation data of rape growth period and ground meteorological observation data from 2004 to 2015. [Result] The results showed that: The effective accumulated temperature rule based on the ForcTT model effectively avoided the uncertainty of each growth period in the law of effective accumulated temperature. The results of the two prediction models were approximate to the prediction of florescence for the most recent three years, which were biased from the actual value, but ccould accurately reflect the changes of the florescence of the years before and after. The results showed that the accumulated temperature model could reflect the time difference of flowering period in different regions effectively. [Conclusion]Therefore, the effective accumulated temperature law based on the ForcTT model could serve as an effective means for the prediction of rape flower period and provide technical support for the development of more effective tourism meteorological services.