Sylwester Arabas

Effective radius and droplet spectral width from in‐situ aircraft observations in trade‐wind cumuli during RICO

Received 19 March 2009; accepted 28 April 2009; published 3 June 2009. [1] This paper presents statistics of cloud microphysical properties of shallow tropical cumuli observed by a research aircraft during RICO field campaign. Cloud properties are derived from 10 Hz (about 10 m spatial distance) Fast-FSSP data in four different flights. The motivation comes from similar analyses of either aircraft data from stratocumulus clouds or remote-sensing data of tropical cumuli. In the lowest few hundred meters, the standard deviation of the droplet size distribution sr and the relative dispersion, the ratio of sr and the mean radius, are similar to stratocumulus clouds, but they are significantly larger in the upper half of the cloud field depth. The frequency distribution of the effective radius is significantly narrower than in the remote-sensing observations in the middle and upper third of the cloud field. These results can be used in parameterizations and validations of cloud microphysics in numerical models of various complexity. Citation: Arabas, S., H. Pawlowska, and W. W. Grabowski (2009), Effective radius and droplet spectral width from insitu aircraft observations in trade-wind cumuli during RICO, Geophys. Res. Lett., 36, L11803, doi:10.1029/2009GL038257.

Large-Eddy Simulations of Trade Wind Cumuli Using Particle-Based Microphysics with Monte Carlo Coalescence

AbstractA series of simulations employing the superdroplet method (SDM) for representing aerosol, cloud, and rain microphysics in large-eddy simulations (LES) is discussed. The particle-based formulation treats all particles in the same way, subjecting them to condensational growth and evaporation, transport of the particles by the flow, gravitational settling, and collisional growth. SDM features a Monte Carlo–type numerical scheme for representing the collision and coalescence process. All processes combined cover representation of cloud condensation nuclei (CCN) activation, drizzle formation by autoconversion, accretion of cloud droplets, self-collection of raindrops, and precipitation, including aerosol wet deposition. The model setup used in the study is based on observations from the Rain in Cumulus over the Ocean (RICO) field project. Cloud and rain droplet size spectra obtained in the simulations are discussed in context of previously published analyses of aircraft observations carried out during ...In this study we present a series of LES simulations employing the Super-Droplet Method (SDM) for representing aerosol, cloud and rain microphysics. SDM is a particle-based and probabilistic approach in which a Monte-Carlo type algorithm is used for solving the particle collisions and coalescence process. The model does not differentiate between aerosol particles, cloud droplets, drizzle or rain drops. Consequently, it covers representation of such cloud-microphysical processes as: CCN activation, drizzle formation by autoconversion, accretion of cloud droplets, self-collection of raindrops and precipitation including aerosol wet deposition. Among the salient features of the SDM, there are: (i) the robustness of the model formulation (i.e. employment of basic principles rather than parametrisations) and (ii) the ease of comparison of the model results with experimental data obtained with particle-counting instruments. The model set-up used in the study is based on observations from the Rain In Cumulus over Ocean (RICO) field project (the GEWEX Cloud System Study Boundary Layer Cloud Working Group RICO case). Cloud and rain droplet size spectrum features obtained in the simulations are compared with previously published aircraft observations carried out during the RICO field project. The analysis covers height-resolved statistics of simulated cloud microphysical parameters such as droplet number concentration, effective radius, and the width of the cloud droplet size spectrum. The sensitivity of the results to the grid resolution of the LES, as well as to the sampling density of the probabilistic (Monte-Carlo type) model is discussed.

libcloudph++ 1.0: a single-moment bulk, double-moment bulk, and particle-based warm-rain microphysics library in C++

Abstract. This paper introduces a library of algorithms for representing cloud microphysics in numerical models. The library is written in C++, hence the name libcloudph++. In the current release, the library covers three warm-rain schemes: the single- and double-moment bulk schemes, and the particle-based scheme with Monte Carlo coalescence. The three schemes are intended for modelling frameworks of different dimensionalities and complexities ranging from parcel models to multi-dimensional cloud-resolving (e.g. large-eddy) simulations. A two-dimensional (2-D) prescribed-flow framework is used in the paper to illustrate the library features. The libcloudph++ and all its mandatory dependencies are free and open-source software. The Boost.units library is used for zero-overhead dimensional analysis of the code at compile time. The particle-based scheme is implemented using the Thrust library that allows one to leverage the power of graphics processing units (GPU), retaining the possibility of compiling the unchanged code for execution on single or multiple standard processors (CPUs). The paper includes a complete description of the programming interface (API) of the library and a performance analysis including comparison of GPU and CPU set-ups.

Formula Translation in Blitz++, NumPy and Modern Fortran: A Case Study of the Language Choice Tradeoffs

Three object-oriented implementations of a prototype solver of the advection equation are introduced. The presented programs are based on BlitzThree object-oriented implementations of a prototype solver of the advection equation are introduced. The presented programs are based on Blitz++ (C++), NumPy (Python), and Fortran’s built-in array containers .T he solvers include an implementation of the Multidimensional Positive-Definite Advective Transport Algorithm (MPDATA). The introduced codes exemplify ho wt he application of object-oriented programming (OOP) techniques allows to reproduce the mathematical notation used in th el iterature within the program code. A discussion on the tradeo! so f the programming language choice is presented. The main a ngles of comparison are code brevity and syntax clarity (and hence maintainability and auditability) as well as performance. In the case of Python, a significant performance gain is observed when switching from the standard interpreter (CPython) to the PyPy implementation of Python. Entire source code of all three implementations is embedded in the text and is licensed under the terms of the GNU GPL license.

On the CCN (de)activation nonlinearities

We take into consideration the evolution of particle size in a monodisperse aerosol population during activation and deactivation of cloud condensation nuclei (CCN). The phase portrait of the system derived through a weakly-nonlinear analysis reveals a saddle-node bifurcation and a cusp catastrophe. An analytical estimate of the activation timescale is derived through estimation of the time spent in the saddle-node bifurcation bottleneck. Numerical integration of the system portrays two types of activation/deactivation hystereses: one associated with the kinetic limitations on droplet growth when the system is far from equilibrium, and one occurring close to equilibrium and associated with the cusp catastrophe. The hysteretic behaviour close to equilibrium imposes stringent time-resolution constraints on numerical integration, particularly during deactivation.

Object-oriented implementations of the MPDATA advection equation solver in C++, Python and Fortran

Three object-oriented implementations of a prototype solver of the advection equation are introduced. The presented programs are based on BlitzThree object-oriented implementations of a prototype solver of the advection equation are introduced. The presented programs are based on Blitz++ (C++), NumPy (Python), and Fortran’s built-in array containers .T he solvers include an implementation of the Multidimensional Positive-Definite Advective Transport Algorithm (MPDATA). The introduced codes exemplify ho wt he application of object-oriented programming (OOP) techniques allows to reproduce the mathematical notation used in th el iterature within the program code. A discussion on the tradeo! so f the programming language choice is presented. The main a ngles of comparison are code brevity and syntax clarity (and hence maintainability and auditability) as well as performance. In the case of Python, a significant performance gain is observed when switching from the standard interpreter (CPython) to the PyPy implementation of Python. Entire source code of all three implementations is embedded in the text and is licensed under the terms of the GNU GPL license.