气象要素时空插值方法研究
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摘要
气象要素空间插值技术常用于获取气象站点覆盖的全局范围内各个点位的气象数据。当气象站点稀少且分布不均时,通常需要进行空间插值。然而,利用现有的方法直接进行气象要素空间插值的效果往往不理想。为了获得更高的插值精度,本文在已有空间插值方法的基础上,研究了基于空间聚类的气象要素空间插值方法,并进一步扩展应用于不规则数据集插值和站点缺失数据修补的时空插值情况,发展了气象要素时空插值方法,主要包括以下5个方面的研究工作：
1.详细回顾了国内外关于气象要素空间插值以及时空插值的研究进展,指出了现有的时空插值方法中存在的问题。
2.实现了泰森多边形法、反距离加权法、梯度距离反比法、样条函数法、趋势面法、面积插值法、普通克里金法7种常用的插值算法,并使用7种插值方法对中国的年平均气温和年平均降雨量进行插值。交叉验证结果表明：对于年平均气温,梯度距离反比法明显优于其他6种插值方法；对于年平均降雨量,反距离加权法插值效果最好。
3.提出了基于空间聚类的气象要素空间插值方法。分别采用K均值空间聚类和三步法空间聚类对中国的年平均气温和年平均降雨量进行聚类分析,将聚类后再进行插值的结果与未聚类直接插值的结果进行比较,发现聚类后再进行插值的精度更高。而三步法空间聚类的插值结果优于K均值空间聚类。
4.指出了Li提出的时空插值方法的不足,并对其进行了改进,提出了改进的约减法和时空混合插值方法。将改进的约减法与原方法应用于不规则数据集插值,并对两种方法的插值结果进行了比较。运用时空混合插值方法修补气象站点的缺失数据,结果表明时空混合插值对缺失数据的修补效果优于单独的时间插值或空间插值。
5.基于本文提出的气象要素时空插值方法,开发了济南城市防汛预警系统中等雨量线绘制模块,并在实践中验证所提方法的可行性和正确性。
最后,总结了本文的主要研究内容,并展望了下一步的研究工作。
Spatial interpolation technique for meteorological elements is often used to obtain the meteorological data of every position in the scope which is covered by the meteorological stations. It is need to execute spatial interpolation in the case that the meteorological stations are of scarcity and uneven distribution. However, it is difficult to obtain the satisfying results when the existing spatial interpolation methods are directly utilized to interpolate meteorological elements. For the purpose of obtaining higher interpolation accuracy, this paper firstly reviews the representative spatial interpolation methods, and makes a detailed comparison among them, and secondly, the spatial interpolation method for meteorological elements is presented based on spatial clustering and the spatio-temporal interpolation method for interpolating the irregular data set and repairing the missing data of the meteorological stations is developed. Lastly, a prototype tool for interpolation is designed and implemented to show the rationales and application of the proposed methods in this paper. Main works can be summarized as follows:
1. The background and purpose of this paper are explained, the research progress on spatial interpolation and spatio-temporal interpolation for meteorological elements is reviewed, the problem of the existing spatio-temporal interpolation method is pointed out, and moreover, the research content and structure arrangement are introduced.
2. The interpolation algorithms of Thiessen, Inverse Distance Weighting (IDW), Gradient Plus Inverse Distance Weighting (GIDW), Spline, Trend, Area-based, Ordinary Kriging (OK) are realized and used to interpolate for annual average temperature and precipitation of China. Cross-validation result shows that:for the annual average temperature, GIDW method is better than the other six kinds of interpolation methods, and for the annual average precipitation, IDW method is the most effective.
3. Spatial interpolation method for meteorological elements based on spatial clustering is proposed. K-means spatial clustering and three-step spatial clustering are separately used to cluster for annual average temperature and precipitation of China. The results of interpolating after clustering and directly interpolating are compared. Interpolation after clustering which has better accuracy is found. Moreover, the interpolation result of three-step spatial clustering is better than that of K-Means spatial clustering. Thus, spatial clustering can be used as an effective preprocessing step before spatial interpolation.
4. The shortage of spatio-temporal interpolation proposed by Li is pointed out and has been improved. An improved reduction method and a mixed spatio-temporal interpolation method are proposed. The improved reduction method and the original method are applied to interpolate irregular data set and the interpolation results of two methods are compared. The mixed spatio-temporal interpolation method is used to repair the missing data of the meteorological stations. The result shows that mixed spatio-temporal interpolation is better than a single time interpolation or spatial interpolation for repair the missing data.
5. Based on the spatio-temporal interpolation method for meteorological elements proposed by this paper, the module of drawing rain isoline in the Jinan urban flood warning system is developed. The feasibility and correctness of the spatio-temporal interpolation method are validated by practice.
Finally, after concluding the main achievement in this paper, some issues for further work are presented.
1.详细回顾了国内外关于气象要素空间插值以及时空插值的研究进展,指出了现有的时空插值方法中存在的问题。
2.实现了泰森多边形法、反距离加权法、梯度距离反比法、样条函数法、趋势面法、面积插值法、普通克里金法7种常用的插值算法,并使用7种插值方法对中国的年平均气温和年平均降雨量进行插值。交叉验证结果表明：对于年平均气温,梯度距离反比法明显优于其他6种插值方法；对于年平均降雨量,反距离加权法插值效果最好。
3.提出了基于空间聚类的气象要素空间插值方法。分别采用K均值空间聚类和三步法空间聚类对中国的年平均气温和年平均降雨量进行聚类分析,将聚类后再进行插值的结果与未聚类直接插值的结果进行比较,发现聚类后再进行插值的精度更高。而三步法空间聚类的插值结果优于K均值空间聚类。
4.指出了Li提出的时空插值方法的不足,并对其进行了改进,提出了改进的约减法和时空混合插值方法。将改进的约减法与原方法应用于不规则数据集插值,并对两种方法的插值结果进行了比较。运用时空混合插值方法修补气象站点的缺失数据,结果表明时空混合插值对缺失数据的修补效果优于单独的时间插值或空间插值。
5.基于本文提出的气象要素时空插值方法,开发了济南城市防汛预警系统中等雨量线绘制模块,并在实践中验证所提方法的可行性和正确性。
最后,总结了本文的主要研究内容,并展望了下一步的研究工作。
Spatial interpolation technique for meteorological elements is often used to obtain the meteorological data of every position in the scope which is covered by the meteorological stations. It is need to execute spatial interpolation in the case that the meteorological stations are of scarcity and uneven distribution. However, it is difficult to obtain the satisfying results when the existing spatial interpolation methods are directly utilized to interpolate meteorological elements. For the purpose of obtaining higher interpolation accuracy, this paper firstly reviews the representative spatial interpolation methods, and makes a detailed comparison among them, and secondly, the spatial interpolation method for meteorological elements is presented based on spatial clustering and the spatio-temporal interpolation method for interpolating the irregular data set and repairing the missing data of the meteorological stations is developed. Lastly, a prototype tool for interpolation is designed and implemented to show the rationales and application of the proposed methods in this paper. Main works can be summarized as follows:
1. The background and purpose of this paper are explained, the research progress on spatial interpolation and spatio-temporal interpolation for meteorological elements is reviewed, the problem of the existing spatio-temporal interpolation method is pointed out, and moreover, the research content and structure arrangement are introduced.
2. The interpolation algorithms of Thiessen, Inverse Distance Weighting (IDW), Gradient Plus Inverse Distance Weighting (GIDW), Spline, Trend, Area-based, Ordinary Kriging (OK) are realized and used to interpolate for annual average temperature and precipitation of China. Cross-validation result shows that:for the annual average temperature, GIDW method is better than the other six kinds of interpolation methods, and for the annual average precipitation, IDW method is the most effective.
3. Spatial interpolation method for meteorological elements based on spatial clustering is proposed. K-means spatial clustering and three-step spatial clustering are separately used to cluster for annual average temperature and precipitation of China. The results of interpolating after clustering and directly interpolating are compared. Interpolation after clustering which has better accuracy is found. Moreover, the interpolation result of three-step spatial clustering is better than that of K-Means spatial clustering. Thus, spatial clustering can be used as an effective preprocessing step before spatial interpolation.
4. The shortage of spatio-temporal interpolation proposed by Li is pointed out and has been improved. An improved reduction method and a mixed spatio-temporal interpolation method are proposed. The improved reduction method and the original method are applied to interpolate irregular data set and the interpolation results of two methods are compared. The mixed spatio-temporal interpolation method is used to repair the missing data of the meteorological stations. The result shows that mixed spatio-temporal interpolation is better than a single time interpolation or spatial interpolation for repair the missing data.
5. Based on the spatio-temporal interpolation method for meteorological elements proposed by this paper, the module of drawing rain isoline in the Jinan urban flood warning system is developed. The feasibility and correctness of the spatio-temporal interpolation method are validated by practice.
Finally, after concluding the main achievement in this paper, some issues for further work are presented.
引文
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[17]储少林,周兆叶,袁雷,等.降水空间插值方法应用研究——以甘肃省为例[J].草业科学,2008,25(6)：19-23
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