机构地区:[1]State Key Laboratory of Severe Weather, Chinese Academy of Meteorological Sciences, Beijing 100081 [2]Hainan Meteorological Service, Haikou 570203
出 处:《Journal of Meteorological Research》2018年第4期636-647,共12页气象学报(英文版)
基 金:Supported by the Project of Basic Scientific Research and Operating Expenses of Chinese Academy of Meteorological Sciences(2016Y009);National Natural Science Foundation of China(31771672)
摘 要:The phenology model is one of the major tools in evaluating the impact of cultivar improvement on crop pheno-logy. Understanding uncertainty in simulating the impact is an important prerequisite for reliably interpreting the ef-fect of cultivar improvement and climate change on phenology. However, uncertainty induced by different temperat-ure response functions and parameterization methods have not been properly addressed. Based on winter wheat phen-ology observations during 1986-2012 in 47 agro-meteorology observation stations in the North China Plain (NCP), the uncertainty of the simulated impacts caused by four widely applied temperature response functions and two para- meterization methods were investigated. The functions were firstly calibrated using observed phenology data during 1986-1988 from each station by means of two parameterization methods, and were then used to quantify the impact of cultivar improvement on wheat phenology during 1986-2012. The results showed that all functions and all para-meterization methods could reach acceptable precision (RMSE 〈 3 days for all functions and parameterization meth-ods), however, substantial differences exist in the simulated impacts between different functions and parameteriza-tion methods. For vegetative growth period, the simulated impact is 0.20 day (10 yr)^-1 [95% confidence interval: -2.81-3.22 day (10 yr)^-1] across the NCP, while for reproductive period, the value is 1.50 day (10 yr)^-1 [-1.03-4.02 day (10 yr)^-1]. Further analysis showed that uncertainty can be induced by both different fimctions and parameteriza-tion methods, while the former has greater influence than the latter. During vegetative period, there is a significant positive linear relationship between ranges of simulated impact and growth period average temperature, while during reproductive period, the relationship is polynomial. This highlights the large inconsistency that exists in most impact quantifying functions and the urgent need to carry out field expeThe phenology model is one of the major tools in evaluating the impact of cultivar improvement on crop pheno-logy. Understanding uncertainty in simulating the impact is an important prerequisite for reliably interpreting the ef-fect of cultivar improvement and climate change on phenology. However, uncertainty induced by different temperat-ure response functions and parameterization methods have not been properly addressed. Based on winter wheat phen-ology observations during 1986-2012 in 47 agro-meteorology observation stations in the North China Plain (NCP), the uncertainty of the simulated impacts caused by four widely applied temperature response functions and two para- meterization methods were investigated. The functions were firstly calibrated using observed phenology data during 1986-1988 from each station by means of two parameterization methods, and were then used to quantify the impact of cultivar improvement on wheat phenology during 1986-2012. The results showed that all functions and all para-meterization methods could reach acceptable precision (RMSE 〈 3 days for all functions and parameterization meth-ods), however, substantial differences exist in the simulated impacts between different functions and parameteriza-tion methods. For vegetative growth period, the simulated impact is 0.20 day (10 yr)^-1 [95% confidence interval: -2.81-3.22 day (10 yr)^-1] across the NCP, while for reproductive period, the value is 1.50 day (10 yr)^-1 [-1.03-4.02 day (10 yr)^-1]. Further analysis showed that uncertainty can be induced by both different fimctions and parameteriza-tion methods, while the former has greater influence than the latter. During vegetative period, there is a significant positive linear relationship between ranges of simulated impact and growth period average temperature, while during reproductive period, the relationship is polynomial. This highlights the large inconsistency that exists in most impact quantifying functions and the urgent need to carry out field expe
关 键 词:observed phenology temperature response function parameterization method renewing cultivar
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