Tracking Clouds: Comparing Geostationary Satellite Observations and Model Data

Tracking clouds has multiple applications. It is used for short-term weather forecasting as well as long-term weather and climate analyses. Our long-term goal is to investigate cloud life cycles under different conditions, such as marine or continental areas, over deserts, or in areas with increased anthropogenic aerosols. This is a key element in understanding cloud radiation effects and the human influence on the cloud life cycle.

To identify clouds and their trajectories, we are using Particle Image Velocimetry [1] which is well-known for measuring velocities in fluid dynamics. These velocity fields are used to predict the positions of clouds in the next timestep. The predicted positions are then compared to the observed positions to match clouds across timesteps. The algorithm can work on any geostationary satellite data set or equivalent model data [2].

Currently we are comparing satellite data from the EUREC⁴A campaign [3] (observed by the Advanced Baseline Image onboard the GOES-16 satellite) and model output from ICON-LEM [4]. Both datasets are located east of Barbados in the Caribbean Sea. This is done to benchmark the model settings and to identify which of the three model resolution best captures the satellite data. The cloud tracking allows us to look at the lifetimes of the clouds and the development of cloud physical properties over the lifetime of a cloud. This leads to a more refined investigation into the cloud behavior.

The presented results are twofold. Firstly, we will show a direct comparison of individual cloud trajectories between observed and model data to establish a deeper understanding of the methodology and datasets. Secondly, we will look at the distributions of clouds sizes and lifetimes to compare different resolutions of model data to the observed satellite data.

 

References:

[1] Raffel et al. (2007) "Particle Image Velocimetry - A Practical Guide", Springer Verlag, doi: 10.1007/978-3-540-72308-0

[2] Seelig et al. (2021) "Life cycle of shallow marine cumulus clouds from geostationary satellite observations", in JGR: Atmospheres, doi: 10.1029/2021JD035577

[3] EUREC4A campaign: www.eurec4a.eu

[4] Dipankar et al. (2015) “Large eddy simulation using the general circulation model ICON”, in Journal of Advances in Modeling Earth Systems 7(3): 963-986, doi: 10.1002/2015MS000431