Application of Contiguous Rain Area (CRA) Methods to Tropical Cyclone Rainfall Forecast Verification. Issue 11 (12th November 2018)

• Record Type: Journal Article
• Authors: Chen, Yingjun; Ebert, Elizabeth E.; Davidson, Noel E.; Walsh, Kevin J. E.
• Is Part Of: Earth and space science. Volume 5:Issue 11(2018)
• Page Start: 736
• Page End: 752
• Publication Date: 2018-11-12
• Subjects: typhoon -- hurricane -- precipitation -- spatial verification -- evaluation -- model forecast; Space sciences -- Periodicals; Geophysics -- Periodicals; 500.5
• DOI: 10.1029/2018EA000412
• Languages: English
• ISSNs: 2333-5084

Abstract

Abstract : This study demonstrates the useful information that can be derived from contiguous rain area (CRA) evaluation, such as systematic errors in tropical cyclone (TC) rainfall location and components of rainfall error due to incorrect predictions of location, rain volume, and rain pattern. CRA verification uses pattern matching techniques to determine the location error, as well as errors in area, mean and maximum intensity, and spatial pattern. In this study, CRA verification was applied to evaluate Australian Community Climate and Earth System Simulator (ACCESS)‐TC, the TC version of ACCESS, daily rainfall forecasts over 15 TCs in the north west Pacific ocean during 2012–2013, by comparing with Tropical Rainfall Measuring Mission (TRMM) 3B42 satellite estimates. The results showed that pattern error was the major contributor to the total TC rainfall forecast error, followed by volume and displacement. ACCESS‐TC forecasts tended to predict more rainfall closer to the TC center compared to Tropical Rainfall Measuring Mission (TRMM) 3B42 estimates. This bias occurred for different CRA rainfall thresholds, verification grid resolutions and forecast lead times. Furthermore, rain event verification showed that for short lead time (24 hr) forecasts, overestimation of rain volume was a major problem for ACCESS‐TC forecasts, while displacement error was more significant in longer lead time (72 hr) forecasts. Finally, we compared empirical probability distribution functions and radial probability distributions of rainfall in the forecasts and observations to further characterise the rain volume error. This confirmed that ACCESS‐TC tended to produce more extreme rain in the locations closer to the TC center (eyewall). Key Points: The object‐based CRA method is useful for TC rainfall verification Systematic errors in location and intensity of TC rainfall forecasts can be identified by CRA The ACCESS‐TC numerical weather prediction model tends to produce more extreme rain in the locations closer to the TC center