29 October 2024
25 October 2024
About
The Convective Updraft Detection (CUD) Algorithm integrates several proven and validated geostationary satellite products to assess convective cloud types, vertical growth rates (i.e. vigour), updraft locations, storm presence, and storm strength. The CUD Algorithm is innovative in its approach to combining existing geostationary satellite-based algorithms and methods to identify convective updraft regions for both newly forming and mature convective clouds and storms. The primary datasets used include 1- and 5-min resolution GOES-16 and -18 channel data, as well as derived fields. These datasets are utilised to demonstrate potential use cases for the upcoming 2.5-minute resolution Meteosat Third Generation (MTG)-I Flexible Combined Imager (FCI) observations over the European domain in Rapid Scan Service (RSS) mode. In addition to the GOES-16/-18 satellite datasets, theoretical numerical weather prediction model estimates of convective available potential energy are incorporated into the CUD Algorithm to provide insights into updraft magnitude. Additionally, 1 km and 250 m resolution cloud-resolving numerical model simulations using the Weather Research and Forecasting (WRF) model are employed to validate and improve the CUD Algorithm.
Objectives
The CUD Algorithm aims to deliver a convective cloud updraft map enhancing the confidence in detecting convective storm updraft regions while improving the quantification of their strengths. Another objective is to explore new scientific concepts using FCI and Lightning Imager data from the MTG-I satellite for real-time analysis of evolving convective clouds and storms. The CUD product is expected to benefit now-casting of high-impact weather.
Overview
The CUD Algorithm provides updraft estimates that compare within approximately 10-20% of those modelled by cloud-resolving Weather Research and Forecasting (WRF) simulations. Relevant to the FCI on MTG-I, the CUD Algorithm demonstrates how the 2.5-minute resolution RSS datasets can be applied in ways that benefit the severe weather forecasting community (e.g., the European Severe Storms Laboratory), as well as pilots and the aviation sector. A potential next step is to demonstrate the product with actual FCI RSS data and assess the product quality and usefulness together with the European user community.