R package for basic GOTM model running. GOTMr holds version 5.3 of the lake branch of the General Ocean Turbulence Model (GOTM) for windows 64bit platforms. This package does not contain the source code for the model, only the executable. Also, use gotm_version() to figure out what version of GOTM you are running. This package was inspired by GOTMr.
You can install GOTMr from Github with:
# install.packages("devtools")
devtools::install_github("aemon-j/GOTMr")
GOTM requires the libgfortran3 and libnetcdff6 libraries so you will need to install this to get GOTM running. You can install this with:
sudo apt-get install libgfortran3
sudo apt-get install libnetcdff6
library(GOTMr)
sim_folder <- system.file('extdata', package = 'GOTMr')
run_gotm(sim_folder)
library(GOTMr)
example("run_gotm")
------------------------------------------------------------------------
GOTM started on 2019/04/06 at 20:42:49
------------------------------------------------------------------------
init_gotm
------------------------------------------------------------------------
reading model setup namelists..
done.
GOTM Simulation
Using 100 layers to resolve a depth of 44.0000000000000
The station Example is situated at (lat,long) 53.0000000000000
-9.00000000000000
Example
initializing modules....
init_input
done
init_time
Time step: 3600.00000000000 seconds
Time format: 2
Start: 2010-01-01 00:00:00
Stop: 2010-12-01 00:00:00
==> 334 day(s) and 0 seconds ==>
8016 micro time steps
init_eqstate
init_meanflow
reading meanflow namelists..
done.
allocation meanflow memory..
done.
init_hypsograph
reading hypsograph from:
hypsograph.dat
# of lines 48 read order 2
adjusting depth from namelist to confirm with hypsograph
depth: 44.0000000000000 ---> 46.8000000000000
init_tridiagonal
sigma coordinates (zooming possible)
init_observations
initial salinity:
none
initial temperature:
Reading temperature profiles from:
init_tprof.dat
external pressure
none
internal pressure
none
extinction method
7
vertical advection
none
elevation
constant
waves
none
velocity profiles
none
dissipations profiles
none
init_streams
.... inflow 1 0.0000000E+00 -1.000000
Only one set of profiles is present in init_tprof.dat.
init_turbulence
reading turbulence namelists..
done.
allocation memory..
allocation memory..
allocation memory..
done.
--------------------------------------------------------
You are using the k-epsilon model
with the following properties:
ce1 = 1.44000000000000
ce2 = 1.92000000000000
ce3minus = -0.744378943205702
ce3plus = 1.00000000000000
sig_k = 1.00000000000000
sig_e = 1.20000006940017
Value of the stability function
in the log-law, cm0 = 0.527046261454271
in shear-free turbulence, cmsf = 0.730911229264925
von Karman constant, kappa = 0.400000000000000
homogeneous decay rate, d = -1.08695652173913
spatial decay rate (no shear), alpha = -7.95123897814375
length-scale slope (no shear), L = 4.595791868626506E-002
steady-state Richardson-number, Ri_st= 0.250000000000000
--------------------------------------------------------
init_air_sea
Reading short wave radiation data from:
swr_input_file.dat
Air-sea exchanges will be calculated
Reading meteo data from:
met_file.dat
heat- and momentum-fluxes:
using Fairall et. all formulation
long-wave back radiation:
using Clark formulation
Reading precipitation data from:
precip_input_file.dat
rain_impact= T
calc_evaporation= T
register_all_variables()
register_coordinate_variables()
register_meanflow_variables()
register_airsea_variables()
register_observation_variables()
register_stream_variables()
register_turbulence_variables()
register_diagnostic_variables()
init_gotm_fabm
init_gotm_fabm_input
done.
------------------------------------------------------------------------
saving initial conditions
Processing output category /state:
- temp
- salt
- u
- uo
- v
- vo
- xP
- h
- ho
- tke
- tkeo
- eps
- num
- nuh
- nus
Processing output category /:
- lon
- lat
- temp
- salt
- rho
- temp_obs
- salt_obs
- u
- v
- xP
- h
- tke
- eps
- num
- nuh
- nus
- u_obs
- v_obs
- fric
- drag
- SS
- P
- uu
- vv
- ww
- NN
- NNT
- NNS
- buoy
- kb
- epsb
- G
- Pb
- avh
- L
- gamu
- gamv
- gamb
- gamh
- gams
- cmue1
- cmue2
- gam
- an
- as
- at
- r
- Rig
- xRf
- taux
- tauy
- u_taus
- u10
- v10
- airt
- airp
- hum
- es
- ea
- qs
- qa
- rhoa
- cloud
- albedo
- precip
- evap
- int_precip
- int_evap
- int_swr
- int_heat
- int_total
- I_0
- qe
- qh
- qb
- heat
- tx
- ty
- sst
- sst_obs
- sss
- zeta
- mld_surf
- rad
- bioshade
- ga
- Af
- z
- zi
- int_water_balance
- Qlayer
- Qs
- Qt
- wq
- FQ
- Qres
- Q_inflow
- T_inflow
- int_inflow
- int_outflow
- mld_bott
- Ekin
- Epot
- Eturb
------------------------------------------------------------------------
time_loop
0 %
10 %
20 %
30 %
40 %
50 %
60 %
70 %
80 %
90 %
100 %
------------------------------------------------------------------------
clean_up
clean_hypsograph
de-allocation hypsograph memory ...
done
clean_meanflow
de-allocation meanflow memory ...
done.
clean_turbulence
de-allocating turbulence memory ...
done.
clean_observations
de-allocate observation memory ...
done.
clean_tridiagonal
------------------------------------------------------------------------
GOTM finished on 2019/04/06 at 20:42:51
------------------------------------------------------------------------
CPU time: 1.638011 seconds
Simulated time/CPU time: 17617469.4650638
------------------------------------------------------------------------
GOTM version: v5.3-400-g90cc2710 (lake branch)
FABM version: v0.95.3-137-gf803260 (master branch)
NetCDF version: 3.6.1-beta1 of Mar 7 2018 17:17:53 $
------------------------------------------------------------------------
Compiler: Intel 19.0.0.20181018
You can download PyNcView for viewing the netCDF output or you can download a set of accompanying tools for working with GOTM data in R gotmtools.
library(gotmtools)
out_file <- file.path(sim_folder, 'output.nc')
plot_wtemp(file = out_file)