4-9 September 2022, Bonn, Germany
EMS Annual Meeting Abstracts
Vol. 19, EMS2022-116, 2022, updated on 28 Jun 2022
EMS Annual Meeting 2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.

Recurrence quantification analysis of high-resolution cloud temperature data from EUREC4A

Stanislaw Krol and Szymon Malinowski
Stanislaw Krol and Szymon Malinowski
  • Uniwersytet Warszawski, Warszawa, Poland (skrol@fuw.edu.pl)

Clouds are the source of the biggest uncertainty in weather and climate models. One cannot fully understand clouds without understanding turbulence and microphysical processes in clouds. EUREC4A [1] experiment conducted during January and February focused on studying stratocumulus clouds (the most common marine clouds on earth) in atmoshperic boundary layer near Barbados. One of many measurements conducted during the campaign, was one using Twin-Otter aircraft, on which an Ultra Fast Thermometer 2b [2] was mounted. This thermometer, developed at Institute of Geophysics at the University of Warsaw is able to measure temperature at a 20 kHz frequency. After averaging to a frequency of 2 kHz, and assuming that the plane is moving at an average speed of 60 m/s, the spatial resolution of the thermometer is of the order of centimeters. The aircraft performed cloud penetrations together with measurements of temperature and other parameters such as the three components of wind velocity, pressure and humidity. The proposed method to study temperature time series is the time-dependent Recurrence Quantification Analysis (RQA) [3].

Recurrence Plots (RPs) are a visualization of a square matrix, which elements correspond to the moments when the system recurs, or when phase space trajectory of a system visits the same area in the phase space. RQA is a technique of data analysis based on the analysis of structures present in RPs. This method is used to study non-linear behaviors in the system, and to study determinism and chaos of the system, and transitions between them. In this study, portions of temperature records corresponding to cloud penetration were analyzed.

The analyzed clouds were divided into groups based on the angle of the penetration (windward, leeward, or from the side), as well as the variability of the wind during the penetration. Preliminary results suggest that the sharp edges of either the windward side of a dissipative cloud or both sides of a developing cloud are the places where the behavior of temperature is the most stochastic. Some clouds exhibited a behavior where the temperature behavior shifted from more stochastic near the windward side to more deterministic near the leeward side of the cloud. There are also side penetrations that, based on the RQA, contain information about the structure of the cloud and its dynamical properties.

We acknowledge funding by Poland’s National Science Centre grant no. UMO-2018/30/M/ST10/00674.

[1] Stevens B. et. al. 2021: EUREC4A, Earth System Science Data, vol. 13(8), pp. 4067-4119, 10.5194/essd-13-4067-2021
[2] Kumala, W. et. al. 2013: Modified ultrafast thermometer UFT-M and temperature measurements during Physics of Stratocumulus Top (POST), Atmos. Meas. Tech., vol. 6, pp. 2043–2054, 10.5194/amt-6-2043-2013
[3] N. Marwan, et. al. 2007: Recurrence Plots for the Analysis of Complex Systems, Physics Reports, vol. 438(5–6), pp. 237–329, 10.1016/j.physrep.2006.11.001

How to cite: Krol, S. and Malinowski, S.: Recurrence quantification analysis of high-resolution cloud temperature data from EUREC4A, EMS Annual Meeting 2022, Bonn, Germany, 5–9 Sep 2022, EMS2022-116, https://doi.org/10.5194/ems2022-116, 2022.


Display file

Supporters & sponsors