Model2roms is a Python toolbox for creating the necessary climatology, boundary, and initial forcing files required to run the ROMS (Regional Ocean Modeling System) model. The latest version of model2roms can convert several popular model hindcasts and projections including the NORESM (Norways Earth System Model), SODA global re-analysis, HYCOM, World Ocean Atlas (WOA), and GLORYS (Mercator Ocean) to a use as forcing files for a given ROMS grid structure.
- 03.09.2019:Added option to use SODA3 5 day averages as forcing files (SODA3_5DAY). This provides a great opportunity to generate forcing that contains much higher temporal resolution compared to the usual monthly forcing fields. To use this option, define
self.oceanindatatype = 'SODA3_5DAY'self.timefrequencyofinputdata = "5days"(used in method: createlistofdays)
- 30.04.2019:Fixed progressbar options for Python 3.7
- 15.04.2019:Added `LDFLAG` option in `compile.py` for compiling Fortran files using f2py on Python3.7
- 13.03.2019: Model2roms has been refactored and the code is now easier to read. Added support for interpolating and writing BGC (biogeochemistry) data to the BRY, CLIM, and INIT files. The BGC currently only supports NorESM BGC data as input and the output format (variable names, units) is intended to be used as input to the ERSEM model.
- 05.09.2018: Model2roms has been refactored and improved in the following way: we now use an object to store all of the configurations (configM2R.py), the run script has been improved (runM2R.py), supports SODA3 and GLORYS2V4 as forcing inputfiles, and severeal minor bugs has been fixed.
- Support for using Earth System Modeling Framework as the default interpolation method. This allows the input data to be on any kind of grid structure (e.g. irregular) as long as geographical information such as longitude and latitude of grid cells are available. The implementation uses the Python interface to ESMF which can be found here: www.earthsystemcog.org/projects/esmpy/. Using ESMF significantly increases the speed of the interpolation. As an example, interpolating one variable (e.g. temperature distribution) from a global irregular grid to a local non-rectangular grid of size 1250x789, at 70 different depth levels, takes 3 seconds on a Mac Laptop Pro. Additional information as to how to install ESMF and ESMPy from source on Mac OSX is available www.trondkristiansen.com/. For most people, installing using Anaconda would be the best option:
conda create -n model2roms conda config --add channels conda-forge conda activate model2roms conda install esmpy netcdf4 progressbar
- Added support for ICE variables. The latest version writes to file (init, bry, and clim) all necessary ice variables required to run ROMS with ice.
- Added support to generate forcing using global GLORYS2V3 files including sea ice
- Many general improvements to the code such as more generic time and date methods.
For the last few years I have been working on this toolbox model2roms. This toolbox is a collection of Python and Fortran modules that can be used to create climatology (CLIM), initial (INIT), and boundary (BRY) files necessary to run the ROMS model. Currently, the program takes rectangular gridded forcing files at Z-levels as input. These data are first interpolated to the ROMS grid at Z-levels. Next the Z-levels are interpolated vertically to the sigma layers (S-coordinates). For U and V velocities, the interpolation is done at RHO points, and then interpolated to U and V points ((eta_u,xi_u), and (eta_v, xi_v)). All interpolated values are written to netCDF4 files using compression (zlib) to minimize file size. The result of running model2roms is one file for each CLIM, INIT, and BRY files. UBAR and VBAR (barotropic flow) are calculated from U and V velocities. Time is stored as julian day from 01/01/1948 (see model2roms.py). Make sure to edit the main.py file before you run the toolbox using:
python runM2R.py| Without filter | With filter |
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# Set showprogress to "False" if you do not want to see the progress
# indicator for horizontal interpolation.
self.showprogress = False
# Set compileAll to True if you want automatic re-compilation of all the
# fortran files necessary to run model2roms. Options are "gfortran" or "ifort". Edit
# compile.py to add other Fortran compilers.
self.compileall = False
# Extract time-series of data for given longitude/latitude
self.extractstations = False
# Define a set of longitude/latitude positions with names to extract into
# station files (using extractStations)
if self.extractstations:
# stationNames = ['NorthSea', 'Iceland', 'EastandWestGreenland', 'Lofoten', 'Georges Bank']
# lonlist = [2.4301, -22.6001, -47.0801, 13.3801, -67.2001]
# latlist = [54.5601, 63.7010, 60.4201, 67.5001, 41.6423]
self.stationnames = ["Ytre Utsira", "Indre Utsira", "Lista"]
self.latlist = [59.316667, 59.316667, 58.016667]
self.lonlist = [4.800000, 4.983333, 6.533333]
self.numberofpoints = 4 # Number of points around lat/lon to extract and average as output
# Create the bry, init, and clim files for a given grid and input data
self.createoceanforcing = True
# Create atmospheric forcing for the given grid
self.createatmosforcing = False # currently in beta stages and unavailable
# Create a smaller resolution grid based on your original. Decimates every second for
# each time run
self.decimategridfile = False
# Write ice values to file (for Arctic regions)
self.writeice = False
# Write biogeochemistry values to file
self.writebcg = False
# ROMS sometimes requires input of ice and ssh, but if you dont have these write zero files to file
self.set2DvarsToZero=False
# Use ESMF for the interpolation. This requires that you have ESMF and ESMPy installed (import ESMF)
self.useesmf = True
# Apply filter to smooth the 2D fields after interpolation (time consuming but enhances results)
self.usefilter = True
# Format to write the ouput to: 'NETCDF4', 'NETCDF4_CLASSIC', 'NETCDF3_64BIT', or 'NETCDF3_CLASSIC'
# Using NETCDF4 automatically turns on compression of files (ZLIB)
self.myformat = 'NETCDF4'
self.myzlib = True
# Frequency of the input data: usually monthly
self.timefrequencyofinputdata = "month" # , "month", "hour"
# IN GRIDTYPES ------------------------------------------------------------------------------
# Define what grid type you wnat to interpolate from (input MODEL data)
# Options:
# 1. SODA, 2. SODAMONTHLY, 3.WOAMONTHLY, 4. NORESM, 4. GLORYS, 5. SODA3
self.oceanindatatype = 'SODA3'
# Define contact info for final NetCDF files
self.authorname = "Trond Kristiansen"
self.authoremail = "trond.kristiansen (at) niva.no"
# Define what grid type you wnat to interpolate from: Can be Z for SIGMA for ROMS
# vertical coordinate system or ZLEVEL. also define the name of the dimensions in the input files.
# Options:
# 1. SIGMA (not prpoerly implemented yet), 2. ZLEVEL
self.ingridtype = "SIGMA"
# Define the names of the geographical variables in the input files
self.grdtype = 'regular'
self.lonname = "longitude"
self.latname = "latitude"
self.depthname = "depth"
self.timename = "time"
self.realm = "ocean"
self.fillvaluein = -1.e20
# OUT GRIDTYPES ------------------------------------------------------------------------------
# Define what grid type you wnat to interpolate to
# Options: This is just the name of your grid used to identify your selection later
self.outgrid = "ROHO800"
self.outgridtype = "ROMS"
# Subset input data. If you have global data you may want to seubset these to speed up reading. Make
# sure that your input data are cartesian (0-360 or -180:180, -90:90)
self.subsetindata = False
if self.subsetindata:
self.subset = self.definesubsetforindata()
# Define nmber of output depth levels
self.nlevels = 40
# Define the grid stretching properties (leave default if uncertain what to pick)
self.vstretching = 4
self.vtransform = 2
self.theta_s = 7.0
self.theta_b = 0.1
self.tcline = 250.0
self.hc = 250
# PATH TO FORCINGDATA --------------------------------------------------------------------
# Define the path to the input data
self.modelpath = self.defineforcingdatapath()
# PATH TO GRID -----------------------------------------------------------------------------
# Define the path to the grid file
self.romsgridpath = self.defineromsgridpath()
# Climatology is only monthly and model2roms needs to know this
self.isclimatology = True if self.oceanindatatype == 'WOAMONTHLY' else False
# DATE AND TIME DETAILS ---------------------------------------------------------
# Define the period to create forcing for
self.start_year = 1980
self.end_year = 2014
self.start_month = 1
self.end_month = 12
self.start_day = 15
self.end_day = 15
- me @ trondkristiansen.com
- http://github.com/trondkr
- www.trondkristiansen.com
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