| 一种基于空间相关性和B样条曲面拟合的地面气温质量控制算法 |
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| 引用本文： | 叶小岭,杨帅,陈洋,杨星,阚亚进.一种基于空间相关性和B样条曲面拟合的地面气温质量控制算法[J].大气科学学报,2019,42(4):513-520. |
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| 作者姓名： | 叶小岭 杨帅 陈洋 杨星 阚亚进 |
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| 作者单位： | 南京信息工程大学气象灾害预报预警与评估协同创新中心;南京信息工程大学自动化学院 |
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| 基金项目： | 国家自然科学基金资助项目（41675156）；南京信息工程大学人才启动项目（2243141701053） |
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| 摘 要： | 将B样条曲面拟合算法引入到地面气温观测资料的质量控制当中,考虑到区域内各参考站与目标站观测值之间的空间相关性,提出了一种基于空间相关性和B样条曲面拟合的地面气温观测资料质量控制算法(Spatial Correlation and B-spline Surface Fitting,BSF)。选择2012—2014年南平站、南京站、太原站、拉萨站、景洪站和长春站以及周围300 km内参考站的02:00、08:00、14:00、20:00定时气温作为观测资料,结合平均绝对误差(Mean Absolute Error,MAE)、均方根误差(Root Mean Square Error,RMSE)、一致性指标(Index of Agreement,IOA)和纳什系数(Nash-sutcliffe Model Efficiency Coefficient,NSC)这4种评价参数对目标站地面气温资料进行质量控制分析。将BSF算法的质量控制效果分别与传统的反距离加权法(Inverse Distance Weighted,IDW)和空间回归检验法(Spatial Regression Test,SRT)进行对比,试验结果表明:在不同案例下,BSF算法的质量控制效果均优于IDW算法和SRT算法,能更有效地标记出气温观测数据中的可疑值。
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| 关 键 词： | 空间相关性 B样条曲面 拟合 地面气温 质量控制 |
| 收稿时间： | 2018/7/3 0:00:00 |
| 修稿时间： | 2018/9/27 0:00:00 |
A quality control algorithm for surface temperature observations based on spatial correlation and B spline surface fitting |
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| YE Xiaoling,YANG Shuai,CHEN Yang,YANG Xing and KAN Yajin.A quality control algorithm for surface temperature observations based on spatial correlation and B spline surface fitting[J].大气科学学报,2019,42(4):513-520. |
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| Authors: | YE Xiaoling YANG Shuai CHEN Yang YANG Xing and KAN Yajin |
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| Institution: | Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters, Nanjing University of Information Science & Technology, Nanjing 210044, China;School of Automation, Nanjing University of Information Science and Technology, Nanjing 210044, China,School of Automation, Nanjing University of Information Science and Technology, Nanjing 210044, China,School of Automation, Nanjing University of Information Science and Technology, Nanjing 210044, China,School of Automation, Nanjing University of Information Science and Technology, Nanjing 210044, China and School of Automation, Nanjing University of Information Science and Technology, Nanjing 210044, China |
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| Abstract: | Against the background of informatization,numerical weather prediction(NWP) has become an important means of meteorological prediction.The quality control of surface temperature observation data serves as the foundation of data assimilation,which is helpful for improving the accuracy of numerical weather prediction.Based on this,in this paper the B spline surface fitting algorithm is applied to the quality control of surface air temperature observation.Considering the spatial correlation between each reference station and target station with the region,a quality control algorithm for surface temperature observation data based on spatial correlation and B spline surface fitting(BSF) is proposed.Nanping,Nanjing,Taiyuan,Lasa,Jinghong and Changchun Stations are selected as the target stations,and the surrounding stations within 300 km are chosen as the reference stations.The time temperatures at 02:00,08:00,14:00 and 20:00 are selected as the observation data.BSF,SRT and IDW are used to control the quality of the target stations'' surface temperature data.Combined with the mean absolute error(MAE),root mean square error(RMSE),index of agreement(IOA),nash coefficient(NSC) and rate of error detection,the results of the comparison lead to the conclusion that the BSF algorithm is able to effectively identify suspicious values in surface temperature observation data,and that it has a higher error detection rate and stronger adaptability than the traditional method. |
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| Keywords: | spatial correlation B spline surface fitting surface temperature quality control |
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