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Auto-analysis of Trough System at 500 hPa Based on Gradient Algorithm
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摘要: 利用位势高度场资料，针对500 hPa高空槽线天气系统，以天气学定义及其图形学特征分析为基础，在保持天气动力学理论约束的同时，提出基于位势高度梯度进行槽线天气系统自动分析的方法。面向各级气象台站的天气预报业务，利用气象信息综合分析系统 (MICAPS) 第4类位势高度格点数据资料，经过梯度计算、垂线确定、方向划分、邻域对比、节点初选、噪声判别、分类滤除、聚类分析、轴向平均等步骤，解决了一系列相关技术问题，完成了西风槽和横槽两类槽线系统自动分析的程序开发。近年宁夏寒潮强降温等过程的分析试验表明，该算法稳定可靠，中高纬度地区槽线分析能力更强，运行效率进一步提高。Abstract: As the forecast products are increasing rapidly and the efficiency of manual process remains pretty low at present, the demand for intelligent assistant computer system of weather forecast is very urgent. It is the fundamental way to improve the automatic level of operational forecast in order to release the working pressure for detail forecast. The study on auto-analysis technology of weather systems is conducted as it is the key to build an intelligent forecast computer software with the thinking way of human kind. Based on synoptic notion and graphic features of trough system, under the guidance of computer graphics theory, trough system at 500 hPa are analyzed.The mathematic relations between gradient of geopotential height, its perpendicular direction and the nodes of trough system are proven by analysis of trough system conception, synoptic and graphics characteristics. The algorithm of trough system auto-analysis is developed under the strict constrain of atmospheric dynamic theory taking gradient of geopotential height as key element, and searching the relative minimal in its perpendicular direction within an optimal neighborhood which is determined by contrastive analysis. A set of software is developed using the geopotential height field of European Centre for Medium-Range Weather Forecasts at 500 hPa in format 4 of MICAPS which is the operational standard of China Meteorological Administration to meet the need of forecast centers at all levels of the country. The technical problems such as gradient calculating, direction zoning, neighborhood designating, primary nodes selecting, noise filtering, cluster analyzing are solved. Some fake troughs and over flow points can be identified with positioning according to the synoptic principals and basic experience, while the indices of density and location of primary nodes are applied to eliminate different noises, which concentrated in some certain areas. The multiple trough lines are merged by clustering and axial direction averaging. The auto-analysis technology and process of both westerly trough and traverse trough lines are developed and products are output in format 14 of MICAPS for forecasters. The algorithm and corresponding software system of auto-analysis of troughs is evaluated with parameters such as offset, length and general inclination angle. Recent experiments on cold wave samples in Ningxia show that the algorithm and the relevant software are stable, the effect in general is satisfying, and the method shows a better performance, especially in areas of middle and high latitudes. Through trail run, the efficiency of trough auto-analysis is improved further, and shortages of contour pursuing method are eliminated.
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Key words:
- gradient vector;
- trough line;
- weather system;
- auto-analysis
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图 1 位势高度场结构
(a) 低涡中西风槽t1与横槽t2，(b) 西风槽线t3
Fig. 1 Structure of geopotential height
(a) troughs from low vortex, (b) westerly trough
图 2 方位与计算 (a) 梯度方位分区，(b) 对应计算区间
Fig. 2 Direction and calculation interval (a) gradient direction, (b) coresponding interval
图 3 计算结果 (a) 位势高度场梯度方向分布，(b) 槽线初选点集
Fig. 3 Result of calculation (a) gradient direction of geopotential height, (b) initial points of troughs
图 4 分析结果 (a) 剔除后的剩余的槽点，(b) 合并后的槽线
Fig. 4 Analysis result (a) selected points after filtering, (b) troughs
图 5 天气系统分析误差三维空间分布及其在二维平面的投影
(透明椭球为误差聚集区)
Fig. 5 Distribution of weather system analysis errors in 3D space and their projections in 2D
(ellipsoid is the aggregation of errors)
图 6 槽线显著误差情况分析 (单位：dagpm)
(a) 14号槽线偏移误差，(b) 36号槽线端点误差，(c) 43号槽线长度误差
Fig. 6 Significant error (unit:dagpm)
(a) offset error of No.14, (b) terminal point error of No.36, (c) length error of No.43
表 1 个例信息
Table 1 Imformation of samples
寒潮强降温过程时段 气温降幅大于10℃常规气象站数 占全区常规站点数比例/% 2012-02-05—07 11 46 2012-11-03—04 15 63 2013-02-28—03-01 20 83 2013-03-09—10 14 58 2014-05-09—10 23 96 2014-10-11—12 18 75 
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