Due to the limited resolution in weather models, the effects associated with turbulence, especially turbulence that does not fully satisfy the assumptions of Kolmogorov theory, are not correctly represented in clouds. In addition, due to the need for more accurate parameterisations, it is useful to divide areas of the atmosphere into those with specific dynamic properties.

As part of this work, analyses of data gathered during EUREC4A campaign near Barbados in 2020 were carried out. Data consisted of three components of wind velocity, temperature and liquid water content. Analyses were carried in the context of turbulent mixing in clouds. First, a number of sections were selected to represent the different physical situations present in the atmosphere.

This was followed by analyses of the turbulence kinetic energy dissipation rate, the integral length scale and the Taylor microscale, as fundamental quantities characterising the turbulent flow. Additional analyses were carried out for the departure of turbulence from isotropy, by means of proportionality coefficient analysis, together with the use of the turbulence triangle method. Morover, analyses of nonequilibrium turbulence were performed, based on recent theoretical studies.

Next, in order to construct conditional statistics, a time-dependent recurrence quantification analysis was performed. One obtains a set of parameters which quantify a segment of a trajectory of an arbitrarily defined vector in the phase space. Here, a time-dependent version of the recurrence quantifiaction analysis was done in order to obtain time series of the parameters.

Finally, based on a selection of a critical value of one of the parameters, a method to distinguish segments was proposed. The division distinguished segments with different dynamical properties, and different properties of turbulence. The portions of the flight representing clouds and their surroundings had similar properties in terms of turbulence, as opposed to other regions.

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