基于准同雨团样本概念雷达和雨量计的实时同步结合方法

文中提出一种基于准同雨团样本概念雷达与雨量计(R&G)的实时同步结合技术.由于存在探测时空和分辨率的两种差异,雷达与雨量计(R&G)的同样本对应历来被视为一道难题.但观测表明,雨量计与其垂直上空雷达的小时累积量(ZOH,QG)存在符合幂律的相关性.以此为基础,提出旨在基本消除时空差异的准同雨团样本概念和5个R&G直接对应关系,着重研究一种简便实用的"时间积分垂直同步采样"TIVS,以及具有幂律形式的ZOH-QG关系.有意义的是在固定指数条件下系数AB或AM,具有Z-R转换和雨量计调整(订正)同步结合于一式的功能,两种设备在探测分辨率上巨大差异而引起的降水估算误差由此得到明显缓解.这种利用ZOH-QG关系估算地面小时降水累积量的方法称为RASIM.经过两个降水个例的试验初步表明,雷达估算半径为230 km内地面区域小时累积降水量的正确率在90%以上,而全过程以站为计的点评估相对误差率平均为20%左右.本文还对时间积分垂直同步采样在具有风漂移效应各种环境风场中的可利用性作了详细分析,揭示了时间积分垂直同步采样方法的物理本质,明确指出这是一种近似的准同雨团样本采样;同时通过分析R&G数据对的分布规律,研究提出了有效的质量控制方法,明显改善了ZOH-QG关系的稳定性和合理性.

Real time synchronously integrated technique for radar and raingauge based on concept of quasi-same rain volume sample

The real time synchronously integrated technique for radar and raingauge (R&G) based on the concept of quasi-same rain volume sample was presented. Because of the presence of temporal and spatial discrepancies as well as resolution differences, the same sample correspondence of R&G has long been a difficult, lasting problem. However, the observations indicate that there exists the correlation conforming to the power-law between hourly accumulation of raingauge measurement QG and radar detected echo aloft over the rain gauge vertically (ZOH). On the basis of this fact, aiming to eliminate the temporal and spatial discrepancies, the concept of quasi-same rain volume sample and the five direct correspondence relationships of R&G are built up. The quite convenient and practical TIVS, i.e. time integral vertical synchronous sampling, and its ZOH-QG relationship with power law are emphatically studied. What has significance is that under the fixed exponent, the coefficient AB or AM can flexibly vary in accordance with the temporal and spatial variability of the natural precipitation, and has a function to synchronously integrate the Z-R conversion and the gauge adjustment into a single equation, thus the precipitation estimation error caused by detecting resolution differences between radar and gauge can be obviously mitigated. It is apparently different from the traditional methods wherein precipitation is estimated by radar and gauge, respectively. The real time synchronously integrated technique using the ZOH-QG relationship to estimate hourly ground rainfall accumulation, is called radar-gauge synchronously integrated method (RASIM). The experiments of two cases show that the correctness rate for area estimation within 230 km is about 90% and the average relative error rate for point estimation over the whole process is about 20%.Through the analysis of effects for various wind drifts in three kinds of environment fields, the physical substance of TIVS has been revealed, definitely suggesting that it is an approximate quasi-sample rain volume sampling. Fortunately, by full demonstration, the better availability has been explained in most weather conditions and confirmed by experimental tests in the paper. By analyzing the data pairs of R&G, the effective quality control method is established which can greatly improve the stability and the reasonability of ZOH-QG relationship. The forecasting product of hourly accumulated precipitation derived by RASIM method has been put into the operational forecasting and has especially played an important part in the short-term quantitative monitoring and forecasting for torrential rain.RASIM needs to be further studied at many aspects, such as to establish more robust theory concerning with quasi-same sample for R&G, to try searching the methods of accurately temporal and spatial coordinating sampling, to make tests and analysis in field for TIVS in various weather systems and conditions, to explore the data quality control technique influenced by wealth systems and its mechanism of evolution, to study the further application of fixed exponent in calculation of rainfall accumulation, to study multiple ZOH-QG relationships and the characters and application of AB(AM) distribution in space, and so on. All these advances will prospectively help to improve the correctness of radar estimated rainfall accumulation.