Cell tracking of convective rainfall: sensitivity of climate-change signal to tracking algorithm and cell definition (Cell-TAO v1.0)

Abstract

Abstract. Lagrangian analysis of convective precipitation involves identifying convective cells (“objects”) and tracking them through space and time. The Lagrangian approach helps to gain insight into the physical properties and impacts of convective cells and, in particular, how these may respond to climate change. Lagrangian analysis requires both a fixed definition of what constitutes a convective object and a reliable tracking algorithm. Whether the climate-change signals of various object properties are sensitive to the choice of tracking algorithm or to how a convective object is defined has received little attention. Here we perform ensemble pseudo global warming experiments at convection-permitting resolution to test this question. Using two conceptually different tracking algorithms, Lagrangian analysis is systematically repeated with different thresholds for defining a convective object, namely minimum values for object area, intensity and lifetime. We find that the tracking method has no impact on the detected climate-change signal. The criteria for identifying a convective object, however, can have a strong and statistically significant impact on the magnitude of the climate-change signal, for all analysed object properties. For the case considered in our study, this insight reveals that projected changes in the characteristics of convective rainfall vary considerably between cells of differing intensity, area and lifetime; for example, an increase in the area of moderate-intensity cells alongside a decrease for the most intense cells. Our results suggest that for Lagrangian analysis of precipitation in climate models, sensitivity analysis of the climate-change signal in relation to how an object is defined is a useful enhancement.