DOI: 10.7910/dvn/95wf9i
title: Bayesian Markov chain Monte Carlo orographic precipitation output

description: The dataset contains the likelihood and prior for ten Markov chain Monte Carlo chains used for the orographic precipitation analysis in Morales et al. 2020. This data can be used to produce the posterior probability. Output from each CM1 model iteration is provided as well, described in the notes section below. The control CM1 simulation is also included, as well as a text file with other model output.
description: cm1_rain.txt4mcmccontrol --- six column text file, each column represents the six averaging-regions over the mountain (column 1=upwind foothills, column 2=upwind slope, column 3=upwind top, column 4=downwind top, column 5=downwind slope, column 6=downwind foothills), all data is temporally-averaged from hours 6-9 of control simulation, each row represents different output [row1= total precipitation rate (mm hr^-1), row2= liquid precipitation rate (mm hr^-1), row3 = frozen precipitation rate (mm hr^-1), row4 = frozen precipitation fraction, row5=liquid water path (kg m^-2), row6=ice water path (kg m^-2), row7=vertically-integrated condensation rate (mm hr^-1), row8=precipitation efficiency, row9=vertically-integrated autoconversion rate (kg m^-2 hr^-1), row10=vertically-integrated rain accretion rate (kg m^-2 hr^-1), row11=vertically-integrated snow melting rate (kg m^-2 hr^-1), row12=vertically-integrated graupel melting rate (kg m^-2 hr^-1), row13=vertically-integrated rain evaporation rate (kg m^-2 hr^-1), row14=vertically-integrated ice deposition rate (kg m^-2 hr^-1), row15=vertically-integrated snow deposition rate (kg m^-2 hr^-1), row16= vertically-integrated cloud droplet condensation rate (kg m^-2 hr^-1), row17=vertically-integrated cloud droplet evaporation rate (kg m^-2 hr^-1), row18=vertically-integrated graupel deposition rate (kg m^-2 hr^-1)]

control4mcmc.nc --- NetCDF file of the CM1 control simulation 

# -- 1 through 10, for each MCMC chain 
orog_precip_mcmc_p_x#.dat --- total prior probability P(x) summed over all parameters, each row is output from a CM1 iteration produced by the MCMC algorithm, each column represents the six averaging-regions over the mountain (column 1=upwind foothills, column 2=upwind slope, column 3=upwind top, column 4=downwind top, column 5=downwind slope, column 6=downwind foothills)
orog_precip_mcmc_p_yx#.dat --- the total likelihood P(y|x) summed over all observations (mountain subregions), each row is output from a CM1 iteration produced by the MCMC algorithm, each column represents the six averaging-regions over the mountain (column 1=upwind foothills, column 2=upwind slope, column 3=upwind top, column 4=downwind top, column 5=downwind slope, column 6=downwind foothills)
orog_precip_mcmc_p_yx_all#.dat --- the individual likelihood for each individual observation j P(y|x)_j, each row is output from a CM1 iteration produced by the MCMC algorithm, each column represents the six averaging-regions over the mountain (column 1=upwind foothills, column 2=upwind slope, column 3=upwind top, column 4=downwind top, column 5=downwind slope, column 6=downwind foothills)
orog_precip_mcmc_params#.dat --- Each row is output from a CM1 iteration produced by the MCMC algorithm, each column represents the value of the input parameters used to initialize that particular simulation [column 1=ice fallspeed coefficient (m^(1-b) s^-1), column2=snow fallspeed coefficient (m^(1-b) s^-1), column 3=graupel fallspeed coefficient (m^(1-b) s^-1), column4= cloud ice density (kg m^-3), column 5=snow density (kg m^-3), column 6=graupel density (kg m^-3), column7=cloud ice autoconversion threshold (micrometer), column8=nucleated ice crystal radius (micrometer), column9=embryo graupel radius (micrometer), column10=ice-ice collection efficiency, column11=ice-cloud water collection efficiency, column12=radius of splintered ice particle (micrometer), column13=rain accretion multiplicative factor, column14=cloud water autoconversion multiplicative factor, column15=snow deposition multiplicative factor, column16=relative humidity profile additive factor, column17=tropospheric moist Brunt-Vaisala frequency additive factor (s^-2), column18=surface potential temperature (K), column19=horizontal wind speed profile additive factor (m s^-1)]

Each column for the following files represents the six averaging regions over the mountain (one vector per line - matches each line of parameters in the params.dat file)
orog_precip_mcmc_fwd_obs-#.dat --- total precipitation rate (mm hr^-1)
orog_precip_mcmc_fwd_output1-#.dat --- liquid precipitation rate (mm hr^-1)
orog_precip_mcmc_fwd_output2-#.dat --- frozen precipitation rate (mm hr^-1)
orog_precip_mcmc_fwd_output3-#.dat --- frozen precipitation fraction (frozen precip/total precip)
orog_precip_mcmc_fwd_output4-#.dat --- liquid water path (kg m^-2)
orog_precip_mcmc_fwd_output5-#.dat --- ice water path (kg m^-2)
orog_precip_mcmc_fwd_output6-#.dat --- vertically-integrated condensation rate (mm hr^-1)
orog_precip_mcmc_fwd_output7-#.dat --- precipitation efficiency (output1/output6)
orog_precip_mcmc_fwd_output8-#.dat --- vertically-integrated autoconversion rate (kg m^-2 hr^-1)
orog_precip_mcmc_fwd_output9-#.dat --- vertically-integrated rain accretion rate (kg m^-2 hr^-1)
orog_precip_mcmc_fwd_output10-#.dat --- vertically-integrated snow melting rate (kg m^-2 hr^-1)
orog_precip_mcmc_fwd_output11-#.dat --- vertically-integrated graupel melting rate (kg m^-2 hr^-1)
orog_precip_mcmc_fwd_output12-#.dat --- vertically-integrated rain evaporation rate (kg m^-2 hr^-1)
orog_precip_mcmc_fwd_output15-#.dat --- vertically-integrated cloud droplet condensation rate (kg m^-2 hr^-1)
orog_precip_mcmc_fwd_output16-#.dat --- vertically-integrated cloud droplet evaporation rate (kg m^-2 hr^-1)