Abstract
This study describes a recently developed object-oriented method suitable for Taiwan for the purpose to verify quantitative precipitation forecasts (QPFs) produced by mesoscale models as a complement to the traditional approaches in existence. Using blended data from the rain-gauge network in Taiwan and the Tropical Rainfall Measuring Mission (TRMM) as the observation, the method developed herein is applied to twice-daily 0–48 h QPFs produced by the Cloud-Resolving Storm Simulator (CReSS) during the South-West Monsoon Experiment (SoWMEX) in May–June 2008. In this method, rainfall objects are identified through a procedure that includes smoothing and thresholding. Various attribute parameters and the characteristics of observed and forecast rain-area objects are then compared and discussed. Both the observed and the QPF frequency distributions of rain-area objects with respect to total water production, object size, and rainfall are similar to chi-distribution, with highest frequency at smaller values and decreased frequencies toward greater values. The model tends to produce heavier rainfall than observation, while the latter exhibits a higher percentage of larger objects with weaker rainfall intensity. The distributions of shape-related attributes are similar between QPF and observed rainfall objects, with more northeast–southwest oriented and fewer northwest–southeast oriented objects. Both observed and modeled object centroid locations have relative maxima over the terrain of Taiwan, indicating reasonable response to the topography. The above results are consistent with previous studies.
Highlights
Quantitative precipitation forecast (QPF) verification is a critical component in the development and use of forecasting systems [1,2]
The model objects produced by 1200-UTC runs (1613 of them) are matched with the observed ones (1141) for the time period shifted by 12 h (i.e., 00:00 UTC 16 May to 00:00 UTC 1 July)
An object-oriented verification method is developed for Taiwan, as a complement to existing conventional methods
Summary
Quantitative precipitation forecast (QPF) verification is a critical component in the development and use of forecasting systems [1,2] It plays a crucial role in monitoring the quality of forecasts and to identify differences among forecasts made by different models or forecasters. [4,5,6,7,8], are categorical statistics of the “measure-oriented” approach. Such measures have the advantages of reducing the vast amount of information from a set of forecasts and observations into a few single values and are easy to apply [9]. Today, forecasting approaches have become more complex due to the increase in the requirement of applicability at the finer scale
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