基于气象要素的逐日玉米产量气象影响指数

利用1981—2020年5—9月气象数据与玉米产量数据，通过改进逐日降水适宜度并构建逐日气候适宜度模型，建立基于相似年逐日气象要素的作物生育期气候适宜度序列，利用气象产量与气候适宜指数建立模型，设计逐日作物产量气象影响指数以表征气象条件对作物的影响程度，基于该指数构建东北地区玉米逐日产量预报模型并分析其逐日预报准确率，用以表明该指数的准确性。结果表明：利用3个相似年预报结果加权集成综合相似年逐日作物产量气象影响指数可提高逐日预报准确率，黑龙江年尺度逐日预报准确率年际间波动小于东北其他地区。综合相似年月尺度下，随着玉米发育期的推进和实时气象数据的引入，月尺度平均预报准确率逐渐提高。东北地区玉米产量8月31日的日尺度预报准确率普遍高于7月31日；辽宁日尺度预报差异较大，但随着玉米发育期推进逐日预报产量和实际产量接近，准确率也提高。基于气象要素构建的逐日作物产量影响指数和同期气象影响指数可以定量评估不同时段气象条件对作物产量的影响程度，在一定程度上可提高农业气象业务定量化评价水平。

A Daily Meteorological Impact Index of Maize Yield Based on Weather Elements

Ten-day and monthly climate suitability has been widely used in agrometeorological research and operation, but it will underestimate the impact of short-term meteorological disasters on crops. In order to dynamically reflect the effect of meteorological conditions on crop yields, the daily precipitation suitability is optimized by calculating a weighed 10-day mean of daily precipitation including previous 9 days. Daily climate suitability is constructed consideringthe suitability of temperature, sunshine and precipitation. The correlation coefficient and Euclidean distance of daily climate suitability before the forecast period is used to identify three similar years and the comprehensive similar year. The whole growth climate suitability sequence of crop is established based on daily climate suitability before the forecast period and daily climate suitability in the similar years after the forecast period. And the climate suitability index is integrated from daily climate suitability sequence. The yield forecast model is established by using crop meteorological yields and the daily climate suitability. Daily crop meteorological yield impact index is designed to indicate the effect of meteorological conditions on crop yields. A daily yield forecast model is constructed to analyze the accuracy of daily yield forecast in the main maize-producing provinces in Northeast China and to indicate the accuracy of the meteorological impact index on crop yield. The results show that the use of comprehensive similar years can improve the accuracy of forecasts. The interannual fluctuation of daily forecast accuracy in Heilongjiang smaller than that in the other three provinces. The forecast accuracy is the lowest in Liaoning. Under the comprehensive similar years in monthly time scale, the advancement of the maize fertility process and the access of real-time meteorological data will improve the accuracy of monthly average forecasts. The accuracy on 31 August is generally higher that on 31 July. The daily forecast can provide a reference for yield forecast. The daily scale forecast in Liaoning varies greatly.Daily forecast yield and the announced yield are gradually approaching with the advancement of the maize fertility process and the accuracy of daily forecast yield is also improved. The impact index based on daily meteorological data can quantitatively assess the effect of meteorological conditions on crop yields at different time scales. To a certain extent, the daily meteorological impact index on crop yield can improve the quantitative evaluation level of agrometeorology operation.