Work Description

Title: Results from Morales et al. 2018 (JAS) - Orographic precipitation sensitivity analysis Open Access Deposited

h
Attribute Value
Methodology
  • The data is produced from Cloud Model 1 simulations of idealized orographic precipitation. The detailed methods used are found in Morales et al. 2018, Journal of Atmospheric Science. The model output is initially in a .dat format, which is then convert to netCDF using the cdo -f nc import_binary command in a Linux terminal. The analysis is performed using the NCAR Command Language (NCL), and the results and description of analysis methods and model configurations are found in Morales et al. 2018 (JAS). The data can be accessed using any programming language that reads in netCDF or binary files. We used NCL and GrADS.
Description
  • The research that produced this data involves exploring the sensitivity of orographic precipitation to changes in microphysical parameters found in the Morrison microphysics scheme within CM1 model. These microphysical sensitivities are also tested within different environments. The tests can be described as "one-at-a-time" experiments, i.e., an individual parameter is perturbed while keeping the rest constant. Annareli Morales conducted this research for her PhD research while working at the Mesoscale and Microscale Meteorology lab at NCAR in Boulder, CO.
Creator
Depositor
  • annareli@umich.edu
Contact information
Discipline
Funding agency
  • National Aeronautics and Space Administration (NASA)
ORSP grant number
  • NNX14AG68G
Keyword
Citations to related material
  • Morales, A., H. Morrison, and D. Posselt, 2018: Orographic precipitation response to microphysical parameter perturbations for idealized moist nearly neutral flow. Journal of Atmospheric Science, 75, 1933-1953, https://doi.org/10.1175/JAS-D-17-0389.1
Resource type
Last modified
  • 11/14/2019
Published
  • 03/06/2019
DOI
  • https://doi.org/10.7302/0zt4-2e62
License
To Cite this Work:
Morales, A. (2019). Results from Morales et al. 2018 (JAS) - Orographic precipitation sensitivity analysis [Data set], University of Michigan - Deep Blue Data. https://doi.org/10.7302/0zt4-2e62

Relationships

This work is not a member of any user collections.

Files (Count: 10; Size: 272 GB)

#!/bin/bash
# this script makes directories for all the one-parameter runs and
# soft links the source code and executable and copies over
# the namelist.input for CM1

cd /raid00/annareli/cm1_output/OLYMPEX_20151113_ideal/mp_param_runs/one-time/runs/one-param_morePRs

# Create each directory first
var1=1
while [ $var1 -le 60 ]
do

cd /raid00/annareli/cm1_output/OLYMPEX_20151113_ideal/mp_param_runs/one-time/runs/one-param_morePRs

mkdir 1p-run_PRs_$var1
cd 1p-run_PRs_$var1
ln -sf /home/annareli/MODEL/cm1r17_2Xdom_shift_hh1km_WR+SDEP+morePRs/include ./include
ln -sf /home/annareli/MODEL/cm1r17_2Xdom_shift_hh1km_WR+SDEP+morePRs/src ./src

mkdir run
cd run
ln -sf /home/annareli/MODEL/cm1r17_2Xdom_shift_hh1km_WR+SDEP+morePRs/run/LANDUSE.TBL ./LANDUSE.TBL
ln -sf /home/annareli/MODEL/cm1r17_2Xdom_shift_hh1km_WR+SDEP+morePRs/run/cm1.exe ./cm1.exe
cp /raid00/annareli/cm1_output/OLYMPEX_20151113_ideal/mp_param_runs/one-time/paramlist/one-param_withPRs/namelist.input .
cp /raid00/annareli/cm1_output/OLYMPEX_20151113_ideal/mp_param_runs/one-time/paramlist/one-param_withPRs/paramlist.input_$var1 .
mv paramlist.input_$var1 paramlist.input

/usr/local/openmpi/bin/mpirun -np 14 ./cm1.exe >& cm1.print.out

echo $var1

let var1=$var1+1
done

Download All Files (To download individual files, select them in the “Files” panel above)

Total work file size of 272 GB is too large to download directly. Consider using Globus (see below).



Best for data sets > 3 GB. Globus is the platform Deep Blue Data uses to make large data sets available.   More about Globus

Remediation of Harmful Language

The University of Michigan Library aims to describe library materials in a way that respects the people and communities who create, use, and are represented in our collections. Report harmful or offensive language in catalog records, finding aids, or elsewhere in our collections anonymously through our metadata feedback form. More information at Remediation of Harmful Language.