Convection Tracking

Motivation and Objectives

One of the fundamental challenges in weather research is understanding why, when, and where storms form, and why only some storms produce extreme weather. Addressing this challenge requires robust algorithms and methodologies to track convective clouds, monitor storm lifecycles, and examine how storms interact with their surrounding environment as they evolve. In this context, the Lagrangian analysis of clouds and other atmospheric phenomena provides a powerful framework for understanding the full lifecycle of convective systems. Improving our understanding of convective lifecycles will support GEWEX’s broader goal of measuring and predicting global and regional energy and water cycles through better integration of observations and models.

Cloud tracking algorithms also play an essential role in linking observations, especially from new satellite missions (e.g., EarthCARE, INCUS, PREFIRE), with the evolution of convective systems. By tracking clouds and storms through time, these methods help characterize convective development, precipitation processes, and the environmental conditions that influence them. Building on recent community activities, the convection tracking effort aims to create a collaborative platform where researchers can share methodologies, datasets, and ideas. The initiative also seeks to identify the geophysical “products” needed to better characterize cloud objects, examine the processes associated with their formation and evolution, and develop toolkits capable of tracking both shallow and deep convection.

To help coordinate these activities, several subgroups are being organized to focus on key topics, and these coordinated efforts will help advance our ability to understand storm evolution and improve our capability to predict extreme weather events.

Subgroups and Key Topics:

• Evaluating different algorithms using the same dataset

• Evaluating different models using the same tracking method

• Assessing model performance across different temporal and spatial scales using the same tracking method

• Evaluating different variables and thresholds for tracking convection
• Assessing the capability of identifying the origin of convection that develops into deep convection

• Identifying key environmental properties that influences deep convection development
• Assessing the capability of reanalysis data for environmental analysis

• Identifying key environmental properties that influences shallow convection development

• Identifying key environmental properties that influence anvil development

For more information, see the Convection Tracking Algorithms and Science Workshop website.