A new field verification score based on optical flow technique

摘要

@@ 1. Introduction Nowadays, high resolution num erical models forecast weather with great detail and we might find them useful because observed features are better reproduced. However , the value of these forecasts is diffic ult to prove using traditional grid-point based verification st atistics. The classic al'dou ble penalty problem' illustrates the limitations of the gridpoint based error measures: a forecast of a precipitation feat ure that is correct in terms of intensity, si ze and timing, but incorrect concerning location, results in very poor categorical error scores (many misses and false alarms) and large root mean square errors. To address this problem spatial verification techniques are being developed that do not require the forecasts to exactly match t he observations at fine scales (see e.g. Ahijevych et al. 2009 and Gilleland et al. 2009 and references therein).