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Data from: Limitations of separate cloud and rain categories in parameterizing collision-coalescence for bulk microphysics schemes

Citation

Igel, Adele (2022), Data from: Limitations of separate cloud and rain categories in parameterizing collision-coalescence for bulk microphysics schemes, Dryad, Dataset, https://doi.org/10.25338/B8SK8H

Abstract

Warm rain collision coalescence has been persistently difficult to parameterize in the bulk microphysics schemes used by weather forecast models, climate models, and higher resolution models of the atmosphere. The Arbitrary Moment Predictor (AMP) has been run in a variety of configurations for collision-coalescence to investigate reasons for the difficulty. The simulations suggest that the primary reason traditional bulk schemes struggle with warm rain formation is the use of separate cloud and rain categories. When the drop size distribution is represented a single bimodal distribution rather than two separate unimodal distributions, the simulation of cloud-to-rain conversion is substantially improved. This dataset contains all of the simulation output and scripts required to reproduce the results in the manuscript that support these conclusions.

Methods

This dataset was produced by running AMP. AMP is described in Igel (2019, https://dx.doi.org/10.1029/2019MS001733) and in the current manuscript.

Usage Notes

output_2M_gamma: AMP with separate cloud and rain categories, two moments predicted for each category

output_3M_gamma: AMP with separate cloud and rain categories, three moments predicted for each category

output_4M_gamma: AMP with a single liquid category with an assumed bimodal gamma DSD, four moments predicted for the category

output_4M-v7: AMP with a single liquid category with nonparametric distributions, four moments predicted for the category

output_6M_gamma: AMP with a single liquid category with an assumed bimodal gamma DSD, six moments predicted for the category

..._t12: Same as above except with the threshold bin between cloud and rain set to bin 12 (25 micron radius)

bin_rates_cc2: contains the bin DSD library used to construct AMP-NP look up tables. Also contains the process rates (see below) corresponding to each DSD.

Final Scripts: Contains all Matlab scripts needed to make Figures 1-9 in the manuscript.

Folder names indicate the initial conditions of the unimodal gamma DSD. nu: shape parameter, N: number concentration, M: mass concentration. The number is an index into the array of values used. These arrays are nu: [1, 3, 5, 7, 9, 11, 13, 15]; N: [50, 100, 200, 400, 800, 1600] /cm3. M: [1, 2, 3, 4, 5] g/kg. 

cXXXXtypeX.txt files: Each line is the -3rd - 12th moments of the cloud and rain categories. This is diagnostic and available regardless of the AMP configuration. One line for each second of the simulation.

bin.txt files: Same as above except for the corresponding BIN simulation.

cparamsXXXXtypeX.txt files: Distribution parameters for each second.

cpdfXXXXtypeX.txt files: Explicit DSD at the end of the timestep. Dimensions are d(mass mixing ratio)/d log diameter. Bin width is log(2)/3. Bin radii (cm) and masses (g) are given in masses_radii.mat

binpdf.txt files: Same as above except for the corresponding BIN simulation.

procrates.txt files: moment tendencies for moments -3rd to 9th (columns) for self-collection of cloud, self-collection of rain, autoconversion cloud, autoconversion rain, accretion cloud, accretion rain (rows). Rows repeat for each time step.

Funding