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A Daily Meteorological Impact Index of Maize Yield Based on Weather Elements
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摘要: 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。
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关键词:
- 逐日气象要素;
- 相似年;
- 逐日作物产量气象影响指数;
- 东北地区玉米
Abstract: 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. -
图 2 2011—2020年东北地区不同相似年准确率对比
Fig. 2 Comparison on the accuracy of yield in Northeast China from 2011 to 2020
图 4 基于综合相似年的2011—2020年东北地区玉米单产逐月平均预报准确率对比
Fig. 4 Comparison on the accuracy of yield in different month under the comprehensive similar year in Northeast China from 2011 to 2020
图 5 2014年(a)和2018年(b)辽宁逐日预报和实际单产及预报准确率
Fig. 5 Daily forecast yield, announced yield and forecast accuracy of Liaoning in 2014(a) and 2018(b)
图 6 2014年和2018年辽宁逐日作物产量气象影响指数(a)和逐日作物产量同期气象影响指数(b)
Fig. 6 The daily crop meteorological yield impact index(a) and same period index(b)of Liaoning in 2014 and 2018
表 1 2011—2020年东北地区不同年型10年平均准确率(单位：%)
Table 1 Average accuracy of 10 years under the different similar yearsin Northeast China from 2011 to 2020 (unit:%)
年型 辽宁 内蒙古东部 黑龙江 吉林 第1相似年 90.3 93.9 91.8 91.9 第2相似年 90.9 93.7 91.4 91.7 第3相似年 90.3 93.6 92.4 91.8 综合相似年 91.2 94.1 93.4 92.4 
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表 2 2011—2020年东北地区逐月平均预报准确率(单位：%)
Table 2 Monthly average forecast accuracy in Northeast China from 2011 to 2020 (unit:%)
月份 辽宁 内蒙古东部 黑龙江 吉林 5 89.9 94.1 91.6 92.2 6 89.9 94.4 92.5 92.5 7 89.7 94.4 93.5 92.0 8 92.5 94.1 95.1 92.5 9 93.8 93.5 94.4 92.6
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表 3 2011—2020年7月31日和8月31日东北地区预报准确率(单位：%)
Table 3 Forecast accuracy in Northeast China on 31 Jul and 31 Aug from 2011 to 2020 (unit:%)
年份 辽宁 内蒙古东部 黑龙江 吉林 07-31 08-31 07-31 08-31 07-31 08-31 07-31 08-31 2011 94.2 94.5 83.3* 89.3* 95.1 98.4 95.9 95.2 2012 95.9 98.7 91.7 94.2 95.0 98.9 92.0 91.1 2013 87.7* 89.9* 99.1 96.7 94.8 90.3 94.5 93.2 2014 73.8* 83.2* 86.3* 86.3* 91.3 93.3 91.9 98.3 2015 96.2 96.2 93.3 89.8* 89.0* 87.8* 93.6 95.5 2016 91.2 93.9 95.9 96.7 92.8 97.5 93.4 90.9 2017 91.2 92.4 99.6 96.7 92.2 93.7 90.5 96.1 2018 99.5 99.7 99.9 99.2 97.6 98.4 80.7* 85.7* 2019 84.8* 90.6 98.5 95.5 94.1 94.2 92.9 89.8* 2020 93.4 95.0 97.6 95.8 100.0 90.6 93.6 90.0 注：*表示逐日预报准确率低于90%。
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[1] 吴门新, 庄立伟, 侯英雨, 等.中国农业气象业务系统(CAgMSS)设计与实现.应用气象学报, 2019, 30(5):513-527. doi: 10.11898/1001-7313.20190501Wu M X, Zhuang L W, Hou Y Y, et al. The design and implementation of China Agricultural Meteorological Service System(CAgMSS). J Appl Meteor Sci, 2019, 30(5): 513-527. doi: 10.11898/1001-7313.20190501 [2] 侯英雨, 张蕾, 吴门新, 等. 国家级现代农业气象业务技术进展. 应用气象学报, 2018, 29(6): 641-656. doi: 10.11898/1001-7313.20180601Hou Y Y, Zhang L, Wu M X, et al. Advances of modern agrometeorological service and technology in China. J Appl Meteor Sci, 2018, 29(6): 641-656. doi: 10.11898/1001-7313.20180601 [3] 张蕾, 侯英雨, 郑昌玲, 等. 作物长势评估指数的设计与应用. 应用气象学报, 2019, 30(5): 543-554. doi: 10.11898/1001-7313.20190503Zhang L, Hou Y Y, Zheng C L, et al. The construction and application of assessing index to crop growing condition. J Appl Meteor Sci, 2019, 30(5): 543-554. doi: 10.11898/1001-7313.20190503 [4] 郭安红, 李森, 何亮, 等. 近十年国家级农业气象灾害预报评估业务技术进展. 气象, 2021, 47(6): 693-702. https://www.cnki.com.cn/Article/CJFDTOTAL-QXXX202106005.htmGuo A H, Li S, He L, et al. Advance in operational technology of agrometeorological disaster forecasting and assessment in China in recent 10 years. Meteor Mon, 2021, 47(6): 693-702. https://www.cnki.com.cn/Article/CJFDTOTAL-QXXX202106005.htm [5] 马鹏里, 蒲金涌, 赵春雨, 等. 光温因子对大田冬小麦累积生物量的影响. 应用生态学报, 2010, 21(5): 1270-1276. https://www.cnki.com.cn/Article/CJFDTOTAL-YYSB201005029.htmMa P L, Pu J Y, Zhao C Y, et al. Influence of light and temperature factors on biomass accumulation of winter wheat in field. Chinese J Appl Ecology, 2010, 21(5): 1270-1276. https://www.cnki.com.cn/Article/CJFDTOTAL-YYSB201005029.htm [6] 李凯伟, 张继权, 魏思成, 等. 东北春大豆精细化气候区划. 应用气象学报, 2021, 32(4): 408-420. doi: 10.11898/1001-7313.20210403Li K W, Zhang J Q, Wei S C, et al. Refined climatic zoning of spring soybean in Northeast China. J Appl Meteor Sci, 2021, 32(4): 408-420. doi: 10.11898/1001-7313.20210403 [7] 刘聪, 李凯伟, 张继权, 等. 基于气候适宜度的南方柑橘种植精细化气候区划. 应用气象学报, 2021, 32(4): 421-431. doi: 10.11898/1001-7313.20210404Liu C, Li K W, Zhang J Q, et al. Refined climatic zoning for citrus cultivation in southern China based on climate suitability. J Appl Meteor Sci, 2021, 32(4): 421-431. doi: 10.11898/1001-7313.20210404 [8] 邱美娟, 刘布春, 刘园, 等. 中国北方苹果种植需水特征及降水适宜性. 应用气象学报, 2021, 32(2): 175-187. doi: 10.11898/1001-7313.20210204Qiu M J, Liu B C, Liu Y, et al. Water requirement and precipitation suitability of apple planting in northern China. J Appl Meteor Sci, 2021, 32(2): 175-187. doi: 10.11898/1001-7313.20210204 [9] 初征, 郭建平. 未来气候变化对东北玉米品种布局的影响. 应用气象学报, 2018, 29(2): 165-176. doi: 10.11898/1001-7313.20180204Chu Z, Guo J P. Effects of climatic change on maize varieties distribution in the future of Northeast China. J Appl Meteor Sci, 2018, 29(2): 165-176. doi: 10.11898/1001-7313.20180204 [10] 魏瑞江, 宋迎波, 王鑫. 基于气候适宜度的玉米产量动态预报方法. 应用气象学报, 2009, 20(5): 622-627. doi: 10.3969/j.issn.1001-7313.2009.05.014Wei R J, Song Y B, Wang X. Method for dynamic forecast of corn yield based on climatic suitability. J Appl Meteor Sci, 2009, 20(5): 622-627. doi: 10.3969/j.issn.1001-7313.2009.05.014 [11] 邱美娟, 宋迎波, 王建林, 等. 耦合土壤墒情的气候适宜度指数在山东省冬小麦产量动态预报中的应用. 中国农业气象, 2015, 36(2): 187-194. doi: 10.3969/j.issn.1000-6362.2015.02.009Qiu M J, Song Y B, Wang J L, et al. Application of climate suitability index coupling moisture in dynamic yield prediction of winter wheat in Shandong Province. Chinese J Agrometeor, 2015, 36(2): 187-194. doi: 10.3969/j.issn.1000-6362.2015.02.009 [12] 徐敏, 徐经纬, 高萍, 等. 不同统计模型在冬小麦产量预报中的预报能力评估——以江苏麦区为例. 中国生态农业学报, 2020, 28(3): 438-447. https://www.cnki.com.cn/Article/CJFDTOTAL-ZGTN202003014.htmXu M, Xu J W, Gao P, et al. Evaluation of winter wheat yield prediction ability of different statistical models-A case study of Jiangsu wheat-growing region. Chinese J Eco-Agr, 2020, 28(3): 438-447. https://www.cnki.com.cn/Article/CJFDTOTAL-ZGTN202003014.htm [13] 刘维, 宋迎波. 农业气象观测站冬小麦观测产量资料在产量预报业务中的应用研究. 气象, 2021, 47(12): 1546-1554. doi: 10.7519/j.issn.1000-0526.2021.12.010Liu W, Song Y B. Operational application of observed yield of winter wheat from agrometeorological stations in yield prediction. Meteor Mon, 2021, 47(12): 1546-1554. doi: 10.7519/j.issn.1000-0526.2021.12.010 [14] 魏瑞江, 王鑫. 气候适宜度国内外研究进展及展望. 地球科学进展, 2019, 34(6): 584-595. https://www.cnki.com.cn/Article/CJFDTOTAL-DXJZ201906006.htmWei R J, Wang X. Progress and prospects of research on climatic suitability at home and abroad. Adv Earth Sci, 2019, 34(6): 584-595. https://www.cnki.com.cn/Article/CJFDTOTAL-DXJZ201906006.htm [15] 刘维, 李祎君, 吕厚荃. 早稻抽穗开花至成熟期气候适宜度对气候变暖与提前移栽的响应. 中国农业科学, 2018, 51(1): 49-59. https://www.cnki.com.cn/Article/CJFDTOTAL-ZNYK201801005.htmLiu W, Li Y J, Lv H Q. Responses of heading to flowering to maturity of early rice to climate change and different transplant periods. Scientia Agricultura Sinica, 2018, 51(1): 49-59. https://www.cnki.com.cn/Article/CJFDTOTAL-ZNYK201801005.htm [16] 侯英雨, 张艳红, 王良宇, 等. 东北地区春玉米气候适宜度模型. 应用生态学报, 2013, 24(11): 3207-3212. https://www.cnki.com.cn/Article/CJFDTOTAL-YYSB201311026.htmHou Y Y, Zhang Y H, Wang L Y, et al. Climatic suitability model for spring maize in Northeast China. Chinese J Appl Ecology, 2013, 24(11): 3207-3212. https://www.cnki.com.cn/Article/CJFDTOTAL-YYSB201311026.htm [17] 刘兴土. 松嫩平原退化土地整治与农业发展. 北京: 科学出版社, 2001.Liu X T. The Remediation of Degraded Landand Agricultural Development on Songnen Plain in China. Beijing: Science Press, 2001. [18] 马树庆. 吉林农业气候研究. 北京: 气象出版社, 1994.Ma S Q. Agroclimatic Research in Jilin Province. Beijing: China Meteorological Press, 1994. [19] 黄璜. 中国红黄壤地区作物生产的气候生态适应性研究. 自然资源学报, 1996, 11(4): 340-346. doi: 10.3321/j.issn:1000-3037.1996.04.007Huang H. A study on the climatic ecology adaptability of the crop production in the red and yellow soils region of China. J Nat Resources, 1996, 11(4): 340-346. doi: 10.3321/j.issn:1000-3037.1996.04.007 [20] 宋迎波, 郑昌玲, 谭方颖, 等. 粮食增产气象保障技术之作物产量动态预报技术. 北京: 气象出版社, 2020.Song Y B, Zheng C L, Tan F Y, et al. Meteorological Support Technology for Increasing Grain Production: Dynamic Forecasting Technology for Crop Yield. Beijing: China Meteorological Press, 2020. [21] 马树庆. 气候变化对东北区粮食产量的影响及其适应性对策. 气象学报, 1996, 54(4): 484-492. doi: 10.3321/j.issn:0577-6619.1996.04.011Ma S Q. A simulating study on the influences of climate change on grain yield and the countermeasures in the Northeast China. Acta Meteor Sinica, 1996, 54(4): 484-492. doi: 10.3321/j.issn:0577-6619.1996.04.011 [22] 李心怡, 张祎, 赵艳霞, 等. 主要作物产量分离方法比较. 应用气象学报, 2020, 31(1): 78-82. doi: 10.11898/1001-7313.20200107Li X Y, Zhang Y, Zhao Y X, et al. Comparative study on main crop yield separation methods. J Appl Meteor Sci, 2020, 31(1): 78-82. doi: 10.11898/1001-7313.20200107 [23] 金荣花, 代刊, 赵瑞霞, 等. 我国无缝隙精细化网格天气预报技术进展与挑战. 气象, 2019, 45(4): 445-457. https://www.cnki.com.cn/Article/CJFDTOTAL-QXXX201904001.htmJin R H, Dai K, Zhao R X, et al. Progress and challenge of seamless fine gridded weather forecasting technology in China. Meteor Mon, 2019, 45(4): 445-457. https://www.cnki.com.cn/Article/CJFDTOTAL-QXXX201904001.htm [24] 秦鹏程, 刘敏, 万素琴. 不完整气象资料下基于作物模型的产量预报方法. 应用气象学报, 2016, 27(4): 407-416. doi: 10.11898/1001-7313.20160403Qin P C, Lin M, Wan S Q, et al. 2016. Methods for yield forecast based on crop model with incomplete weather observations. J Appl Meteor Sci, 2016, 27(4): 407-416. doi: 10.11898/1001-7313.20160403 [25] 陈上, 窦子荷, 蒋腾聪, 等. 基于聚类法筛选历史相似气象数据的玉米产量DSSAT-CERES-Maize预测. 农业工程学报, 2017, 33(19): 147-155. doi: 10.11975/j.issn.1002-6819.2017.19.019Chen S, Dou Z H, Jiang T C, et al. Maize yield forecast with DSSAT-CERES-Maize model driven by historical meteorological data of analogue years by clustering algorithm. Transactions of the CSAE, 2017, 33(19): 147-155. doi: 10.11975/j.issn.1002-6819.2017.19.019 [26] 刘维, 宋迎波. 基于不同空间尺度的作物产量集成预报——以江苏一季稻为例. 气象科学, 2021, 41(6): 828-834. https://www.cnki.com.cn/Article/CJFDTOTAL-QXKX202106012.htmLiu W, Song Y B. Comparative analysis of different regional scales integration yield prediction-A case study of single rice in Jiangsu. J Meteor Sci, 2021, 41(6): 828-834. https://www.cnki.com.cn/Article/CJFDTOTAL-QXKX202106012.htm [27] 侯英雨, 何亮, 靳宁, 等. 中国作物生长模拟监测系统的构建方法与应用. 农业工程学报, 2018, 34(21): 165-175. doi: 10.11975/j.issn.1002-6819.2018.21.020Hou Y Y, He L, Jin N, et al. Establishment and application of crop growth simulating and monitoring system in China. Transactions of the CSAE, 2018, 34(21): 165-175. doi: 10.11975/j.issn.1002-6819.2018.21.020 -
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