Abstract
The steady-state assumption commonly used in object-based tracking algorithms may be insufficient to determine the right track when a convective storm goes through a complicated evolution. Such an issue is exacerbated by the relatively coarse output frequency of current convection allowing model (CAM) forecasts (e.g., hourly), giving rise to many spatially well resolved but temporally not well resolved storms that steady-state assumption could not account for. To reliably track simulated storms in CAM outputs, this study proposed an object-based method with two new features. First, the method explicitly estimated the probability of each probable track based on either its immediate past and future motion or a reliable “first-guess motion” derived from storm climatology or near-storm environmental variables. Second, object size was incorporated into the method to help identify temporally not well resolved storms and minimize false tracks derived for them. Parameters of the new features were independently derived from a storm evolution analysis using 2-min Multi-Radar Multi-Sensor (MRMS) data and hourly CAM forecasts produced by the University of Oklahoma (OU) Multiscale data Assimilation and Predictability Laboratory (MAP) from May 2019. The performance of the new method was demonstrated with hourly MRMS and CAM forecast examples from May 2018. A systematic evaluation of four severe weather events indicated 99% accuracy achieved for over 600 hourly MRMS tracks derived with the proposed tracking method.
Highlights
Storm tracking techniques were originally designed to track observed storms in radarbased observations [1,2,3]
An object-based method to reliably track convective storms depends on the complexity of storm evolution patterns and the temporal resolution (∆t) of the data relative to the spatial and temporal scales of the storm
To overcome the above limitations and more reliably track simulated convective storms in convection allowing model (CAM) outputs of temporal resolution ∆t, this study proposed an object-based method with two new features
Summary
Storm tracking techniques were originally designed to track observed storms in radarbased observations [1,2,3]. Recent decades have witnessed rapid convection allowing model (CAM) developments [4,5,6,7]. CAM’s ability to realistically simulate convective storms has motivated the adaptation of observation-based storm tracking techniques to track CAMsimulated storms [8]. It provides a framework to systematically evaluate crucial aspects of CAM-simulated storms. Such a framework advances our understanding of the strengths and limitations of CAM forecasts so that they can be more appropriately utilized for severe weather forecasting
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