CAJ | 학술논문

针对我国新一代C波段天气雷达,提出了综合考虑雷达波束阻挡、信号衰减以及雷达波束随距离增加而抬高和展宽等因素影响的定量降水估计算法。该算法基于高分辨率地形高度数据计算极坐标中每个方位-斜距库上不受地形阻挡的最低观测仰角,依此从雷达体扫数据中提取用于降水估计的混合反射率因子;结合雷达和雨量计资料对雷达系统标定偏差进行估计后再对雷达反射率因子作衰减订正;使用雷达和雨量计实时同步结合的方法进行降水估计,在计算Z-R关系中的系数a时,将a看作一个距离指数函数,而非一个与距离无关的常数。使用遵义C波段雷达观测到的5次降水过程的体扫资料和对应1 h地面雨量资料,对本文提出来的定量降水估计算法进行测试和效果评估,并与不考虑衰减订正且将Z-R关系中的系数a看作常数的降水估计方法进行比较,结果表明,使用本文提出的算法估计的1 h降水的相对误差率平均下降7.3%。
침대아국신일대C파단천기뢰체,제출료종합고필뢰체파속조당、신호쇠감이급뢰체파속수거리증가이태고화전관등인소영향적정량강수고계산법。해산법기우고분변솔지형고도수거계산겁좌표중매개방위-사거고상불수지형조당적최저관측앙각,의차종뢰체체소수거중제취용우강수고계적혼합반사솔인자;결합뢰체화우량계자료대뢰체계통표정편차진행고계후재대뢰체반사솔인자작쇠감정정;사용뢰체화우량계실시동보결합적방법진행강수고계,재계산Z-R관계중적계수a시,장a간작일개거리지수함수,이비일개여거리무관적상수。사용준의C파단뢰체관측도적5차강수과정적체소자료화대응1 h지면우량자료,대본문제출래적정량강수고계산법진행측시화효과평고,병여불고필쇠감정정차장Z-R관계중적계수a간작상수적강수고계방법진행비교,결과표명,사용본문제출적산법고계적1 h강수적상대오차솔평균하강7.3%。
To aim at China＇s new generation C-band weather radar,this paper puts forward a new quantitative precipitation estimation algorithm considering some impact factors such as radar beam blocking,signal attenuation,and beam widening and shifting.With the algorithm the lowest elevations for all range bins not be blocked by obstacles is calculated based on high-resolution digital elevation model.According to the lowest elevations,hybrid reflectivity data used for precipitation estimation are obtained from volume scan reflectivity data.After a rain gauge-based radar calibration bias estimation is carried out,the attenuation correction process is performed.Then,the real time synchronously integrated technique for radar and rain gauge based on the concept of quasi-same rain volume sample is used to estimate precipitation,while the coefficient a in Z-R relationship is taken as a distance index function not as a constant.Using volume scan data for five precipitation processes collected by C-band radar located in Zunyi and corresponding 1 h ground rain gauge data,the algorithm is tested and evaluated,and compared with the scheme which does not take into account attenuation correction and regards the coefficient a in Z-R relationship as a constant.The results show that the mean relative error rate of 1 h quantitative precipitation estimation with the new algorithm declined 7.3%.