5:15 PM - 6:45 PM
[MIS13-P04] Improvement of the accuracy of rain rate estimation by deriving the sequential Z(Kdp)-R relationship and development of a new type of rain gauge
Keywords:Weather radar, Rain rate estimation
In 2018, a dual-polarization phased-array radar for meteorological applications (MP-PAWR) with high speed and high accuracy was developed to observe severe phenomena that develop in several [min] and hundreds [m], which cause heavy rainfall disasters that have become a social problem in recent years. In general, rainfall intensity estimation by meteorological radar is based on the observation parameters (Zh: radar reflectivity factor, Kdp: specific differencial phase) and the related equations (Zh - R relation, Kdp - R relation).
However, the accuracy of rainfall intensity estimation depends greatly on the coefficients used in the equations, and the coefficients depend on meteorological phenomena, which sometimes causes a large degradation in the accuracy of rainfall intensity estimation. In addition, the spatio-temporal resolution of ground rain gauges is insufficient for severe phenomena. The Japan Meteorological Agency's Advanced Meteorological Data Acquisition System (AMeDAS) has a spacing of about 17[km] and a temporal resolution of 1 or 10 [min], which is insufficient for observing severe phenomena that develop on a scale of several [min] or several hundred [m].
In this study, we propose a new method for estimating rainfall intensity using MP-PAWR and AMeDAS data, which updates the optimal coefficients sequentially, and compare it with the conventional estimation method. We also conducted an initial study on the development of a simple and high-resolution ground rain gauge using an accelerometer and a 3D printer. The results showed that the new rain gauge has the potential to measure rainfall with high accuracy.
However, the accuracy of rainfall intensity estimation depends greatly on the coefficients used in the equations, and the coefficients depend on meteorological phenomena, which sometimes causes a large degradation in the accuracy of rainfall intensity estimation. In addition, the spatio-temporal resolution of ground rain gauges is insufficient for severe phenomena. The Japan Meteorological Agency's Advanced Meteorological Data Acquisition System (AMeDAS) has a spacing of about 17[km] and a temporal resolution of 1 or 10 [min], which is insufficient for observing severe phenomena that develop on a scale of several [min] or several hundred [m].
In this study, we propose a new method for estimating rainfall intensity using MP-PAWR and AMeDAS data, which updates the optimal coefficients sequentially, and compare it with the conventional estimation method. We also conducted an initial study on the development of a simple and high-resolution ground rain gauge using an accelerometer and a 3D printer. The results showed that the new rain gauge has the potential to measure rainfall with high accuracy.