Lesson - WPS

Defining the model domain and initial conditions using the WRF Preprocessing System (WPS) and associated tools

Overview

This lesson covers creating your case-specific domain and defining static and initial conditions used for the land surface model within WRF-Hydro.

Software and conventions

The lesson uses the wrfhydro/wps:conus-training-v5.1.1 Docker container. There are both standard and training versions of the wrfhydro/wps container. The former run as a service using the directions posted on the wrfhydro/wps DockerHub landing page and the latter include the JupyterLab server allowing users to work with the container interactively and through training notebooks.

The containers include the following:

  • Ubuntu base image
  • WRF and WPS v3.9 built with the GNU Fortran compiler ‘gfortran’
  • Python 3.6 command line utility for creating WRF-Hydro geogrid files using the WPS geogrid.exe program
  • R environment including all libraries for running create_wrfinput and create_soilproperties scripts
  • WRF-WPS geographical input data for the contiguous United States ONLY USGS+DEFAULT DATASETS ARE SUPPORTED, lai_modis_30s, nlcd2011_30m, and topo_30s are subsets for training purposes only

To complete this tutorial you may either execute commands by running each cell of this notebook. Alternatively, you may open a terminal in JupyterLab by selecting File -> New -> Terminal in JupyterLab and input the commands manually if you prefer. You can also use your own terminal by logging into the container with the command docker exec -it wps-training bash

All paths used in this lesson assume that the lesson materials are located under your home directory in a folder named wrf-hydro-training. If your materials are located in another directory, you will not be able to run the commands in this notebook inside Jupyter and will need to type them manually in your terminal session.

Defining the model domain and creating the geogrid file

WRF-Hydro leverages the extensive domain generation and geophysical dataset processing tools available in the WRF Preprocessing System (WPS) to define model domains and generate input files for the land surface model. In particular WRF-Hydro requires the geogrid and wrfinput files derived from these WPS utilities and in the case of wrfinput a utility within WRF as well.

However, this requires that WRF-Hydro users build WRF and WPS on their systems, unpack the large datasets required for these utilties, and obtain meterological data required to run utilities intended to be used for the initialization of atmospheric models. Additionally, much of the functionality of WRF and WPS is not utilized for creating a geogrid file for WRF-Hydro, and many of the options in the namelist.wps are not relevant to this process. Therefore, we have created a Docker container, Python command line utility, and several script packages to abstract much of the WRF/WPS complexity and simplify the process of creating a these files for WRF-Hydro users.

This tutorial walks users through the process of manually creating a geogrid file from an existing WPS installation and creating wrfinput files from provided script packages as well as using the Python utility to generate geogrid and wrfinput files for a more automated approach. For those interested in the details of running the complete WPS system and generating wrfinput files through WRF this is covered in our Docker training on the coupled WRF and WRF-Hydro modeling system.

Data sources

The WPS geographical input data (e.g. land cover, soil texture, and terrain height) are some of the primary datasets used by WRF-Hydro. The entire dataset collection can be obtained from the WPS geographical input data download page. However, these data are rather large (~50GB) and contain a number of datasets that are not used in most implementations of WRF-Hydro.

To facilitate the domain generation process, the WRF-Hydro team has created a subset of the data by removing unnecessary data, removing resolutions of the data not commonly used, and limiting the areal extent of this subset. This is consistent with the availability of other datasets used in this tutorial. Thus, the dataset provided with the wrfhydro/wps Docker container is considerably smaller than the complete WRF-WPS dataset.

geogrid.exe

The WPS program geogrid.exe is used to create the geo_em.d01.nc file, hereafter referred to as the 'geogrid' file. The geogrid.exe program takes a Fortran namelist (namelist.wps) defining the projection, resolution, and extent of the model domain as well as the desired input fields and the WPS geographical input data as inputs and creates the geogrid file.

Defining domain boundaries

The land surface model in WRF-Hydro operates on the domain defined within the geogrid file. The geogrid.exe program generates this file based upon input variables specified in the namelist.wps file. The first step to creating the geogrid file is to define our domain boundaries. The geogrid.exe program takes a centerpoint, x and y grid specifications, and other projection information to define a bounding box for the domain. If you do not already have coordinates, you can obtain them from Google Earth or a standard GIS system. However, for this tutorial we have supplied the coordinates for you and you may use the WRF-Hydro geogrid Python command line utility to visualize the domain location and create the geogrid file given these coordinates.

Exploring the WPS geogrid.exe utility and namelist.wps

The WPS geogrid.exe utility is controlled by options set in the namelist.wps. As previously stated, there are many options in the namelist.wps file that are not relevant to most WRF-Hydro users. For educational purposes, we will take a quick look at a full namelist.wps file and then discuss the relevant options used by the WRF-Hydro geogrid utility in more detail.

Both the full namelist and the shorter annotated version intended for the WRF-Hydro geogrid utility are included within the example case for each WRF-Hydro release so we first need to set up our lesson directory and then download and unpack our the files to view these namelists.

Setting up the lesson directory

Step 1: Setup the directory for this lesson

First, we need to create a directory to hold the inputs and outputs for this lesson.

In [1]:
%%bash
mkdir -p $HOME/wrf-hydro-training/lesson-wps

Step 2: Download the example case.

The example case can be obtained from the WRF-Hydro release page.

In [2]:
%%bash
cd $HOME/wrf-hydro-training

wget https://github.com/NCAR/wrf_hydro_nwm_public/releases/download/v5.1.1-beta/croton_NY_example_testcase.tar.gz &> /dev/null
tar -xf croton_NY_example_testcase.tar.gz
In [3]:
%%bash

cat $HOME/wrf-hydro-training/example_case/supplemental/namelist.wps.FULL_VERSION

&share
 wrf_core = 'ARW',
 max_dom  = 1,
 start_date = '2006-08-16_12:00:00',
 end_date   = '2006-08-16_18:00:00',
 interval_seconds = 21600,
 io_form_geogrid  = 2,
/

&geogrid
 parent_id         =   1,
 parent_grid_ratio =   1,
 i_parent_start    =   1,
 j_parent_start    =   1,
 e_we              =  16,
 e_sn              =  17,
 dx = 1000,
 dy = 1000,
 map_proj  = 'lambert',
 ref_lat   =  41.471,
 ref_lon   = -73.74365,
 truelat1  =  30.0,
 truelat2  =  60.0,
 stand_lon = -97.0,
 geog_data_res  = 'nlcd2011_30m+gtopo_30s+default',
 geog_data_path = '/home/docker/WRF_WPS/utilities/geog_conus',
/

&ungrib
 out_format = 'WPS',
 prefix = 'FILE',
/

&metgrid
 fg_name = 'FILE',
 io_form_metgrid = 2, 
/

A full description of these options can be found in the WPS User Guide.

The options that are of interest to most WRF-Hydro users are the following:

Table 1. WPS namelist options relevent to WRF-Hydro

Option Description
e_we The number of grid edges in the west-east dimension. The number of grid centers will be e_we-1.
e_sn The number of grid edges in the south-north dimension. The number of grid centers will be e_sn-1.
ref_lat A real value specifying the latitude part of a (latitude, longitude) center-point of the domain.
ref_lon A real value specifying the longitude part of a (latitude, longitude) center-point of the domain. West longitudes are negative, and the value of ref_lon should be in the range [-180, 180].
dx A real value specifying the grid distance in the x-direction where the map scale factor is 1. The grid distance is in meters for the 'polar', 'lambert', and 'mercator' projection, and in degrees longitude for the 'lat-lon' projection.
dy A real value specifying the grid distance in the y-direction where the map scale factor is 1. The grid distance is in meters for the 'polar', 'lambert', and 'mercator' projection, and in degrees latitude for the 'lat-lon' projection.
map_proj A character string specifying the projection of the simulation domain. Accepted projections are 'lambert', 'polar', 'mercator', and 'lat-lon'. Default value is 'lambert'.
truelat1 A real value specifying, the first true latitude for the Lambert conformal conic projection, or the only true latitude for the Mercator and polar stereographic projections.
truelat2 A real value specifying, the second true latitude for the Lambert conformal conic projection. For all other projections, truelat2 is ignored. No default value.
stand_lon A real value specifying, the longitude that is parallel with the y-axis in the Lambert conformal and polar stereographic projections. For the regular latitude-longitude projection, this value gives the rotation about the earth's geographic poles. No default value.
geog_data_res A character string specifying a corresponding resolution or list of resolutions separated by + symbols of source data to be used when interpolating static terrestrial data to the grid. This string should contain a resolution matching a string preceding a colon in a rel_path or abs_path specification (see the description of GEOGRID.TBL options) in the GEOGRID.TBL file for each field. If a resolution in the string does not match any such string in a rel_path or abs_path specification for a field in GEOGRID.TBL, a default resolution of data for that field, if one is specified, will be used. If multiple resolutions match, the first resolution to match a string in a rel_path or abs_path specification in the GEOGRID.TBL file will be used. Default value is 'default'.
geog_data_path A character string giving the path, either relative or absolute, to the directory where the geographical data directories may be found. This path is the one to which rel_path specifications in the GEOGRID.TBL file are given in relation to. No default value.

To simplify the process of creating the geogrid file, these options are the only ones needed when using the wrfhydro/wps Docker utility.

Lets take a look at the namelist.wps file used by the wrfhydro/wps docker utility

In [4]:
%%bash

cat $HOME/wrf-hydro-training/example_case/supplemental/namelist.wps.SHORT_ANNOTATED

&share

!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!
! Specify the number of domains
!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!

 max_dom = 1,

/

&geogrid

!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!
! Define the extend in west-east (e_we) and south-north (e_sn) directions
! Note: will create a domain of size (e_we-1) x (e_sn-1)
!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!

 e_we              =  16,
 e_sn              =  17,

!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!
! Define the center point of your domain
!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!

 ref_lat   =   41.47100,
 ref_lon   =  -73.74365,

!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!
! Define the domain grid spacing (in meters)
!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!

 dx = 1000,
 dy = 1000,

!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!
! Define the map projection
!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!

 map_proj  = 'lambert',
 truelat1  =  30.0,
 truelat2  =  60.0,
 stand_lon =  -97.00,

!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!
! Define the data sources and data path
!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!

 geog_data_res  = 'nlcd2011_30m+gtopo_30s+default',
 geog_data_path = '/home/docker/WRF_WPS/utilities/geog_conus',

/

Changing the domain location and boundaries in WPS

In this section we will make a few changes to the example case namelist.wps to demonstrate how to move the domain location and change the extent.

NOTE: Do not edit the ~/wrf-hydro-training/example_case/supplemental/namelist.wps file because we will use this prepared namelist to create the example case geogrid file using WPS in a later section of this lesson

In general, users want to generate the largest, highest-resolution model domain possible. Unfortunately, we are often constrained by available computational power or drive storage. These contraints usually define the acceptable grid sizes for us (e_we, e_sn). Therefore, once we know our domain center, we can play with dx and dy to cover our interested area.

We will edit the dx and dy options in the namelist to grow the size of the domain. We will leave all other options the same, which will simply increase the domain coverage but maintain the domain center and domain dimensions.

Step 1: Visualize the original domain location.

First let's create a basic map of the original example case domain location using the example case namelist.wps file ~/wrf-hydro-training/example_case/supplemental/namelist.wps and the WRF-Hydro geogrid Python utility. You can get help on the arguments to the python utility by accessing its help.

In [5]:
%%bash
python /home/docker/WRF_WPS/utilities/make_geogrid.py --help

usage: make_geogrid.py [-h] [--namelist_path NAMELIST_PATH]
                       [--output_dir OUTPUT_DIR] [--plot_only]
                       [--create_wrf_input]

Step 1: Pull the image docker pull wrfhydro/wps Step 2: Create a directory to
bind-mount to Docker for passing files between your system and docker mkdir
/home/dockerMount Step 3: Create a namelist.wps file for your domain using the
above example as a starting point and save it in your mount directory from
step 1. Step 4: Run Docker invoking the python make_geogrid.py utility with
the required arguments. NOTE THE PATHS LISTED BELOW IN THE ARUGMENT LIST ARE
FOR THE DOCKER FILESYSTEM. ALSO NOTE THAT ALL PATHS MUST BE ABSOLUTEdocker run
-v <path-to-your-local-mount-folder>:/home/docker/mount wrfhydro/wps
--namelist_path /home/docker/mount/namelist.wps --output_dir
/home/docker/mount/ Note: Windows users will need to remove the \ from the end
of each line of the above commands.

optional arguments:
  -h, --help            show this help message and exit
  --namelist_path NAMELIST_PATH
                        Path to namelist file containing the namelist.wps
                        updates
  --output_dir OUTPUT_DIR
                        Path to directory to hold outputs
  --plot_only           Only create a plot of the domain. Geogrid will not be
                        created if plot_only = true, only a plot of the domain
                        will be created.
  --create_wrf_input    create a wrfinput initial condition file for WRF-Hydro

Note that the script takes 4 arguments, the first --namelist_path is the path to your namelist.wps file, the second --output_dir is the path to the directory to hold the output, and the third --plot_only is a boolean True or False indicating whether or not to plot the domain. If plot_only the utility will only plot the domain and not create the geogrid file. This option is useful for making changes to your domain location or extent. The fourth argument --create_wrfinput is a boolean True or False indicating whether or not to create a wrfinput initial conditions.

Now, let's create a plot of the original example case domain location.

In [6]:
%%bash
python /home/docker/WRF_WPS/utilities/make_geogrid.py \
--namelist_path /home/docker/wrf-hydro-training/example_case/supplemental/namelist.wps.SHORT_ANNOTATED \
--output_dir /home/docker/wrf-hydro-training/lesson-wps/ \
--plot_only

Proj4: +proj=lcc +units=meters +a=6370000.0 +b=6370000.0 +lat_1=30.0 +lat_2=60.0 +lat_0=45.0 +lon_0=-97.0 +nadgrids=@null
Grid center x,y: [1849500.1972706 -108771.437837 ]
Grid center lat,lon: [ 58.50955341 -63.99173649]
Domain extent: [1842000.1972705964, 1857000.1972705964, -116771.43783700376, -100771.43783700376]
Process completed after 4.92 seconds.
In [7]:
from IPython.display import Image

Image('/home/docker/wrf-hydro-training/lesson-wps/domain.png')
Out[7]:

Step 2: Make a copy of the original domain namelist.wps

We will copy our original domain namelist.wps that was used to create the example case and edit it. It is located at ~/wrf-hydro-training/example_case/supplemental/namelist.wps.SHORT_ANNOTATED

NOTE: Do not edit the original namelist.wps ~/wrf-hydro-training/example_case/supplemental/namelist.wps.SHORT_ANNOTATED because we will use it later to create our geogrid file.

In [8]:
%%bash
cp ~/wrf-hydro-training/example_case/supplemental/namelist.wps.SHORT_ANNOTATED \
~/wrf-hydro-training/lesson-wps/namelist_edit.wps

Step 3: Edit the ~/wrf-hydro-training/lesson-wps/namelist_edit.wps

Using your editor of choice (can be edited in Jupyter), open the ~/wrf-hydro-training/lesson-wps/namelist_edit.wps file and change the dx and dy values to

dx=2000.0
dy=2000.0
In [9]:
%%bash
python /home/docker/WRF_WPS/utilities/make_geogrid.py \
--namelist_path /home/docker/wrf-hydro-training/lesson-wps/namelist_edit.wps \
--output_dir /home/docker/wrf-hydro-training/lesson-wps/ \
--plot_only

Proj4: +proj=lcc +units=meters +a=6370000.0 +b=6370000.0 +lat_1=30.0 +lat_2=60.0 +lat_0=45.0 +lon_0=-97.0 +nadgrids=@null
Grid center x,y: [1849500.1972706 -108771.437837 ]
Grid center lat,lon: [ 58.50955341 -63.99173649]
Domain extent: [1834500.1972705964, 1864500.1972705964, -124771.43783700376, -92771.43783700376]
Process completed after 4.55 seconds.
In [10]:
from IPython.display import Image

Image('/home/docker/wrf-hydro-training/lesson-wps/domain.png')
Out[10]:

We can see that the domain coverage has expanded but the center and size are the same. You can change any of your domain set-up by editing the variables in namelist.wps.

Making the geogrid file

In this section, we will create the geogrid file using the WRF-Hydro geogrid python utility.

Note: If you would like to use this utilitiy outside of this training, the utility and all required datasets for the Continental United States are available in the wrfhydro/wps Docker container at https://hub.docker.com/r/wrfhydro/wps/.

Step 1: Copy the prepared namelist.wps file for the example case to the lesson-wps output folder

We will copy over the prepared namelist.wps file from the example case to create our geogrid file. We will also rename our edited namelist.wps from the previous domain location exercise, in case you want to retain for reference.

In [11]:
%%bash
cp /home/docker/wrf-hydro-training/example_case/supplemental/namelist.wps.SHORT_ANNOTATED \
~/wrf-hydro-training/lesson-wps/namelist.wps

Step 1: Check the domain boundaries

We will do a quick visual inspection to make sure our supplied domain boundary information is correct.

In [13]:
%%bash
python /home/docker/WRF_WPS/utilities/make_geogrid.py \
--namelist_path /home/docker/wrf-hydro-training/lesson-wps/namelist.wps \
--output_dir /home/docker/wrf-hydro-training/lesson-wps/ \
--plot_only

Proj4: +proj=lcc +units=meters +a=6370000.0 +b=6370000.0 +lat_1=30.0 +lat_2=60.0 +lat_0=45.0 +lon_0=-97.0 +nadgrids=@null
Grid center x,y: [1849500.1972706 -108771.437837 ]
Grid center lat,lon: [ 58.50955341 -63.99173649]
Domain extent: [1842000.1972705964, 1857000.1972705964, -116771.43783700376, -100771.43783700376]
Process completed after 10.15 seconds.
In [14]:
from IPython.display import Image

Image('/home/docker/wrf-hydro-training/lesson-wps/domain.png')
Out[14]:

Step 2: Create the geogrid and wrfinput files.

This time we will run the utility with --plot_only set to False. A plot of the domain will still be produced, but the geogrid.exe utility will also be executed to create the geogrid file.

The wrfinput_d01.nc is a very basic WRF-Hydro initialization file (wrfinput) from a WRF geogrid file and a set of user-specified conditions. The file contains fields of spatially uniform initial model states of soil moisture, soil temperature, soil liquid water content and skin temperature among a few other variables necessary for model cold-start initialization. This file can be used as a 'cold start' for long-term model spin-up or users can overwrite the fields in the file created. Sophisticated and WRF-savvy users can bypass this script and use the WRF utility real.exe to create a wrfinput file from model or reanalysis products.

The R script used to create this file can be downloaded at https://ral.ucar.edu/projects/wrf_hydro/pre-processing-tools.

NOTE: This R script will be replaced in the future with a Python command line utility to eliminate the R dependency.

In [15]:
%%bash
python /home/docker/WRF_WPS/utilities/make_geogrid.py \
--namelist_path /home/docker/wrf-hydro-training/lesson-wps/namelist.wps \
--output_dir /home/docker/wrf-hydro-training/lesson-wps

Parsed 7 entries in GEOGRID.TBL
Processing domain 1 of 1
  Processing XLAT and XLONG
  Processing MAPFAC
  Processing F and E
  Processing ROTANG
  Processing LANDUSEF
  Calculating landmask from LANDUSEF ( WATER =  16 )
  Processing HGT_M
  Processing SOILTEMP
  Processing SOILCTOP
  Processing SCT_DOM
  Processing SOILCBOT
  Processing SCB_DOM
  Processing GREENFRAC
  Processing LAI12M
!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!
!  Successful completion of geogrid.        !
!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!
[1] "ncks -O -4 -v XLAT_M,XLONG_M,HGT_M,SOILTEMP,LU_INDEX,MAPFAC_MX,MAPFAC_MY,GREENFRAC,LAI12M,SOILCTOP /home/docker/WRF_WPS/WPS/geo_em.d01.nc /home/docker/wrfinput_d01.nc"
[1] "ncrename -O -v HGT_M,HGT /home/docker/wrfinput_d01.nc /home/docker/wrfinput_d01.nc"
ncrename: In total renamed 0 attributes, 0 dimensions, 0 groups, and 1 variable
[1] "ncrename -O -v XLAT_M,XLAT /home/docker/wrfinput_d01.nc /home/docker/wrfinput_d01.nc"
ncrename: In total renamed 0 attributes, 0 dimensions, 0 groups, and 1 variable
[1] "ncrename -O -v XLONG_M,XLONG /home/docker/wrfinput_d01.nc /home/docker/wrfinput_d01.nc"
ncrename: In total renamed 0 attributes, 0 dimensions, 0 groups, and 1 variable
[1] "ncrename -O -v LU_INDEX,IVGTYP /home/docker/wrfinput_d01.nc /home/docker/wrfinput_d01.nc"
ncrename: In total renamed 0 attributes, 0 dimensions, 0 groups, and 1 variable
[1] "ncks -O -x -v SOILTEMP,GREENFRAC,LAI12M,SOILCTOP /home/docker/wrfinput_d01.nc /home/docker/wrfinput_d01.nc"
Plotting domain
Proj4: +proj=lcc +units=meters +a=6370000.0 +b=6370000.0 +lat_1=30.0 +lat_2=60.0 +lat_0=45.0 +lon_0=-97.0 +nadgrids=@null
Grid center x,y: [1849500.1972706 -108771.437837 ]
Grid center lat,lon: [ 58.50955341 -63.99173649]
Domain extent: [1842000.1972705964, 1857000.1972705964, -116771.43783700376, -100771.43783700376]
Process completed after 5.55 seconds.
Generating geogrid file
Generating wrfinput file

Inspecting the geogrid file

Now that we have created our geogrid file, we will quickly display the file header using the ncdump command line utility and open the file using the Python library xarray to visualize its contents.

In [16]:
%%bash

ncdump -h ~/wrf-hydro-training/lesson-wps/geo_em.d01.nc

netcdf geo_em.d01 {
dimensions:
	Time = UNLIMITED ; // (1 currently)
	DateStrLen = 19 ;
	west_east = 15 ;
	south_north = 16 ;
	south_north_stag = 17 ;
	west_east_stag = 16 ;
	land_cat = 24 ;
	soil_cat = 16 ;
	month = 12 ;
variables:
	char Times(Time, DateStrLen) ;
	float XLAT_M(Time, south_north, west_east) ;
		XLAT_M:FieldType = 104 ;
		XLAT_M:MemoryOrder = "XY " ;
		XLAT_M:units = "degrees latitude" ;
		XLAT_M:description = "Latitude on mass grid" ;
		XLAT_M:stagger = "M" ;
		XLAT_M:sr_x = 1 ;
		XLAT_M:sr_y = 1 ;
	float XLONG_M(Time, south_north, west_east) ;
		XLONG_M:FieldType = 104 ;
		XLONG_M:MemoryOrder = "XY " ;
		XLONG_M:units = "degrees longitude" ;
		XLONG_M:description = "Longitude on mass grid" ;
		XLONG_M:stagger = "M" ;
		XLONG_M:sr_x = 1 ;
		XLONG_M:sr_y = 1 ;
	float XLAT_V(Time, south_north_stag, west_east) ;
		XLAT_V:FieldType = 104 ;
		XLAT_V:MemoryOrder = "XY " ;
		XLAT_V:units = "degrees latitude" ;
		XLAT_V:description = "Latitude on V grid" ;
		XLAT_V:stagger = "V" ;
		XLAT_V:sr_x = 1 ;
		XLAT_V:sr_y = 1 ;
	float XLONG_V(Time, south_north_stag, west_east) ;
		XLONG_V:FieldType = 104 ;
		XLONG_V:MemoryOrder = "XY " ;
		XLONG_V:units = "degrees longitude" ;
		XLONG_V:description = "Longitude on V grid" ;
		XLONG_V:stagger = "V" ;
		XLONG_V:sr_x = 1 ;
		XLONG_V:sr_y = 1 ;
	float XLAT_U(Time, south_north, west_east_stag) ;
		XLAT_U:FieldType = 104 ;
		XLAT_U:MemoryOrder = "XY " ;
		XLAT_U:units = "degrees latitude" ;
		XLAT_U:description = "Latitude on U grid" ;
		XLAT_U:stagger = "U" ;
		XLAT_U:sr_x = 1 ;
		XLAT_U:sr_y = 1 ;
	float XLONG_U(Time, south_north, west_east_stag) ;
		XLONG_U:FieldType = 104 ;
		XLONG_U:MemoryOrder = "XY " ;
		XLONG_U:units = "degrees longitude" ;
		XLONG_U:description = "Longitude on U grid" ;
		XLONG_U:stagger = "U" ;
		XLONG_U:sr_x = 1 ;
		XLONG_U:sr_y = 1 ;
	float CLAT(Time, south_north, west_east) ;
		CLAT:FieldType = 104 ;
		CLAT:MemoryOrder = "XY " ;
		CLAT:units = "degrees latitude" ;
		CLAT:description = "Computational latitude on mass grid" ;
		CLAT:stagger = "M" ;
		CLAT:sr_x = 1 ;
		CLAT:sr_y = 1 ;
	float CLONG(Time, south_north, west_east) ;
		CLONG:FieldType = 104 ;
		CLONG:MemoryOrder = "XY " ;
		CLONG:units = "degrees longitude" ;
		CLONG:description = "Computational longitude on mass grid" ;
		CLONG:stagger = "M" ;
		CLONG:sr_x = 1 ;
		CLONG:sr_y = 1 ;
	float MAPFAC_M(Time, south_north, west_east) ;
		MAPFAC_M:FieldType = 104 ;
		MAPFAC_M:MemoryOrder = "XY " ;
		MAPFAC_M:units = "none" ;
		MAPFAC_M:description = "Mapfactor on mass grid" ;
		MAPFAC_M:stagger = "M" ;
		MAPFAC_M:sr_x = 1 ;
		MAPFAC_M:sr_y = 1 ;
	float MAPFAC_V(Time, south_north_stag, west_east) ;
		MAPFAC_V:FieldType = 104 ;
		MAPFAC_V:MemoryOrder = "XY " ;
		MAPFAC_V:units = "none" ;
		MAPFAC_V:description = "Mapfactor on V grid" ;
		MAPFAC_V:stagger = "V" ;
		MAPFAC_V:sr_x = 1 ;
		MAPFAC_V:sr_y = 1 ;
	float MAPFAC_U(Time, south_north, west_east_stag) ;
		MAPFAC_U:FieldType = 104 ;
		MAPFAC_U:MemoryOrder = "XY " ;
		MAPFAC_U:units = "none" ;
		MAPFAC_U:description = "Mapfactor on U grid" ;
		MAPFAC_U:stagger = "U" ;
		MAPFAC_U:sr_x = 1 ;
		MAPFAC_U:sr_y = 1 ;
	float MAPFAC_MX(Time, south_north, west_east) ;
		MAPFAC_MX:FieldType = 104 ;
		MAPFAC_MX:MemoryOrder = "XY " ;
		MAPFAC_MX:units = "none" ;
		MAPFAC_MX:description = "Mapfactor (x-dir) on mass grid" ;
		MAPFAC_MX:stagger = "M" ;
		MAPFAC_MX:sr_x = 1 ;
		MAPFAC_MX:sr_y = 1 ;
	float MAPFAC_VX(Time, south_north_stag, west_east) ;
		MAPFAC_VX:FieldType = 104 ;
		MAPFAC_VX:MemoryOrder = "XY " ;
		MAPFAC_VX:units = "none" ;
		MAPFAC_VX:description = "Mapfactor (x-dir) on V grid" ;
		MAPFAC_VX:stagger = "V" ;
		MAPFAC_VX:sr_x = 1 ;
		MAPFAC_VX:sr_y = 1 ;
	float MAPFAC_UX(Time, south_north, west_east_stag) ;
		MAPFAC_UX:FieldType = 104 ;
		MAPFAC_UX:MemoryOrder = "XY " ;
		MAPFAC_UX:units = "none" ;
		MAPFAC_UX:description = "Mapfactor (x-dir) on U grid" ;
		MAPFAC_UX:stagger = "U" ;
		MAPFAC_UX:sr_x = 1 ;
		MAPFAC_UX:sr_y = 1 ;
	float MAPFAC_MY(Time, south_north, west_east) ;
		MAPFAC_MY:FieldType = 104 ;
		MAPFAC_MY:MemoryOrder = "XY " ;
		MAPFAC_MY:units = "none" ;
		MAPFAC_MY:description = "Mapfactor (y-dir) on mass grid" ;
		MAPFAC_MY:stagger = "M" ;
		MAPFAC_MY:sr_x = 1 ;
		MAPFAC_MY:sr_y = 1 ;
	float MAPFAC_VY(Time, south_north_stag, west_east) ;
		MAPFAC_VY:FieldType = 104 ;
		MAPFAC_VY:MemoryOrder = "XY " ;
		MAPFAC_VY:units = "none" ;
		MAPFAC_VY:description = "Mapfactor (y-dir) on V grid" ;
		MAPFAC_VY:stagger = "V" ;
		MAPFAC_VY:sr_x = 1 ;
		MAPFAC_VY:sr_y = 1 ;
	float MAPFAC_UY(Time, south_north, west_east_stag) ;
		MAPFAC_UY:FieldType = 104 ;
		MAPFAC_UY:MemoryOrder = "XY " ;
		MAPFAC_UY:units = "none" ;
		MAPFAC_UY:description = "Mapfactor (y-dir) on U grid" ;
		MAPFAC_UY:stagger = "U" ;
		MAPFAC_UY:sr_x = 1 ;
		MAPFAC_UY:sr_y = 1 ;
	float E(Time, south_north, west_east) ;
		E:FieldType = 104 ;
		E:MemoryOrder = "XY " ;
		E:units = "-" ;
		E:description = "Coriolis E parameter" ;
		E:stagger = "M" ;
		E:sr_x = 1 ;
		E:sr_y = 1 ;
	float F(Time, south_north, west_east) ;
		F:FieldType = 104 ;
		F:MemoryOrder = "XY " ;
		F:units = "-" ;
		F:description = "Coriolis F parameter" ;
		F:stagger = "M" ;
		F:sr_x = 1 ;
		F:sr_y = 1 ;
	float SINALPHA(Time, south_north, west_east) ;
		SINALPHA:FieldType = 104 ;
		SINALPHA:MemoryOrder = "XY " ;
		SINALPHA:units = "none" ;
		SINALPHA:description = "Sine of rotation angle" ;
		SINALPHA:stagger = "M" ;
		SINALPHA:sr_x = 1 ;
		SINALPHA:sr_y = 1 ;
	float COSALPHA(Time, south_north, west_east) ;
		COSALPHA:FieldType = 104 ;
		COSALPHA:MemoryOrder = "XY " ;
		COSALPHA:units = "none" ;
		COSALPHA:description = "Cosine of rotation angle" ;
		COSALPHA:stagger = "M" ;
		COSALPHA:sr_x = 1 ;
		COSALPHA:sr_y = 1 ;
	float LANDMASK(Time, south_north, west_east) ;
		LANDMASK:FieldType = 104 ;
		LANDMASK:MemoryOrder = "XY " ;
		LANDMASK:units = "none" ;
		LANDMASK:description = "Landmask : 1=land, 0=water" ;
		LANDMASK:stagger = "M" ;
		LANDMASK:sr_x = 1 ;
		LANDMASK:sr_y = 1 ;
	float XLAT_C(Time, south_north_stag, west_east_stag) ;
		XLAT_C:FieldType = 104 ;
		XLAT_C:MemoryOrder = "XY " ;
		XLAT_C:units = "degrees latitude" ;
		XLAT_C:description = "Latitude at grid cell corners" ;
		XLAT_C:stagger = "CORNER" ;
		XLAT_C:sr_x = 1 ;
		XLAT_C:sr_y = 1 ;
	float XLONG_C(Time, south_north_stag, west_east_stag) ;
		XLONG_C:FieldType = 104 ;
		XLONG_C:MemoryOrder = "XY " ;
		XLONG_C:units = "degrees longitude" ;
		XLONG_C:description = "Longitude at grid cell corners" ;
		XLONG_C:stagger = "CORNER" ;
		XLONG_C:sr_x = 1 ;
		XLONG_C:sr_y = 1 ;
	float SINALPHA_U(Time, south_north, west_east_stag) ;
		SINALPHA_U:FieldType = 104 ;
		SINALPHA_U:MemoryOrder = "XY " ;
		SINALPHA_U:units = "none" ;
		SINALPHA_U:description = "Sine of rotation angle on U grid" ;
		SINALPHA_U:stagger = "U" ;
		SINALPHA_U:sr_x = 1 ;
		SINALPHA_U:sr_y = 1 ;
	float COSALPHA_U(Time, south_north, west_east_stag) ;
		COSALPHA_U:FieldType = 104 ;
		COSALPHA_U:MemoryOrder = "XY " ;
		COSALPHA_U:units = "none" ;
		COSALPHA_U:description = "Cosine of rotation angle on U grid" ;
		COSALPHA_U:stagger = "U" ;
		COSALPHA_U:sr_x = 1 ;
		COSALPHA_U:sr_y = 1 ;
	float SINALPHA_V(Time, south_north_stag, west_east) ;
		SINALPHA_V:FieldType = 104 ;
		SINALPHA_V:MemoryOrder = "XY " ;
		SINALPHA_V:units = "none" ;
		SINALPHA_V:description = "Sine of rotation angle on V grid" ;
		SINALPHA_V:stagger = "V" ;
		SINALPHA_V:sr_x = 1 ;
		SINALPHA_V:sr_y = 1 ;
	float COSALPHA_V(Time, south_north_stag, west_east) ;
		COSALPHA_V:FieldType = 104 ;
		COSALPHA_V:MemoryOrder = "XY " ;
		COSALPHA_V:units = "none" ;
		COSALPHA_V:description = "Cosine of rotation angle on V grid" ;
		COSALPHA_V:stagger = "V" ;
		COSALPHA_V:sr_x = 1 ;
		COSALPHA_V:sr_y = 1 ;
	float LANDUSEF(Time, land_cat, south_north, west_east) ;
		LANDUSEF:FieldType = 104 ;
		LANDUSEF:MemoryOrder = "XYZ" ;
		LANDUSEF:units = "category" ;
		LANDUSEF:description = "2011 30 meter, USGS reclass" ;
		LANDUSEF:stagger = "M" ;
		LANDUSEF:sr_x = 1 ;
		LANDUSEF:sr_y = 1 ;
	float LU_INDEX(Time, south_north, west_east) ;
		LU_INDEX:FieldType = 104 ;
		LU_INDEX:MemoryOrder = "XY " ;
		LU_INDEX:units = "category" ;
		LU_INDEX:description = "Dominant category" ;
		LU_INDEX:stagger = "M" ;
		LU_INDEX:sr_x = 1 ;
		LU_INDEX:sr_y = 1 ;
	float HGT_M(Time, south_north, west_east) ;
		HGT_M:FieldType = 104 ;
		HGT_M:MemoryOrder = "XY " ;
		HGT_M:units = "meters MSL" ;
		HGT_M:description = "Topography height" ;
		HGT_M:stagger = "M" ;
		HGT_M:sr_x = 1 ;
		HGT_M:sr_y = 1 ;
	float SOILTEMP(Time, south_north, west_east) ;
		SOILTEMP:FieldType = 104 ;
		SOILTEMP:MemoryOrder = "XY " ;
		SOILTEMP:units = "Kelvin" ;
		SOILTEMP:description = "Annual mean deep soil temperature" ;
		SOILTEMP:stagger = "M" ;
		SOILTEMP:sr_x = 1 ;
		SOILTEMP:sr_y = 1 ;
	float SOILCTOP(Time, soil_cat, south_north, west_east) ;
		SOILCTOP:FieldType = 104 ;
		SOILCTOP:MemoryOrder = "XYZ" ;
		SOILCTOP:units = "category" ;
		SOILCTOP:description = "16-category top-layer soil type" ;
		SOILCTOP:stagger = "M" ;
		SOILCTOP:sr_x = 1 ;
		SOILCTOP:sr_y = 1 ;
	float SCT_DOM(Time, south_north, west_east) ;
		SCT_DOM:FieldType = 104 ;
		SCT_DOM:MemoryOrder = "XY " ;
		SCT_DOM:units = "category" ;
		SCT_DOM:description = "Dominant category" ;
		SCT_DOM:stagger = "M" ;
		SCT_DOM:sr_x = 1 ;
		SCT_DOM:sr_y = 1 ;
	float SOILCBOT(Time, soil_cat, south_north, west_east) ;
		SOILCBOT:FieldType = 104 ;
		SOILCBOT:MemoryOrder = "XYZ" ;
		SOILCBOT:units = "category" ;
		SOILCBOT:description = "16-category bottom-layer soil type" ;
		SOILCBOT:stagger = "M" ;
		SOILCBOT:sr_x = 1 ;
		SOILCBOT:sr_y = 1 ;
	float SCB_DOM(Time, south_north, west_east) ;
		SCB_DOM:FieldType = 104 ;
		SCB_DOM:MemoryOrder = "XY " ;
		SCB_DOM:units = "category" ;
		SCB_DOM:description = "Dominant category" ;
		SCB_DOM:stagger = "M" ;
		SCB_DOM:sr_x = 1 ;
		SCB_DOM:sr_y = 1 ;
	float GREENFRAC(Time, month, south_north, west_east) ;
		GREENFRAC:FieldType = 104 ;
		GREENFRAC:MemoryOrder = "XYZ" ;
		GREENFRAC:units = "fraction" ;
		GREENFRAC:description = "MODIS FPAR" ;
		GREENFRAC:stagger = "M" ;
		GREENFRAC:sr_x = 1 ;
		GREENFRAC:sr_y = 1 ;
	float LAI12M(Time, month, south_north, west_east) ;
		LAI12M:FieldType = 104 ;
		LAI12M:MemoryOrder = "XYZ" ;
		LAI12M:units = "m^2/m^2" ;
		LAI12M:description = "MODIS LAI" ;
		LAI12M:stagger = "M" ;
		LAI12M:sr_x = 1 ;
		LAI12M:sr_y = 1 ;

// global attributes:
		:TITLE = "OUTPUT FROM GEOGRID V3.9" ;
		:SIMULATION_START_DATE = "0000-00-00_00:00:00" ;
		:WEST-EAST_GRID_DIMENSION = 16 ;
		:SOUTH-NORTH_GRID_DIMENSION = 17 ;
		:BOTTOM-TOP_GRID_DIMENSION = 0 ;
		:WEST-EAST_PATCH_START_UNSTAG = 1 ;
		:WEST-EAST_PATCH_END_UNSTAG = 15 ;
		:WEST-EAST_PATCH_START_STAG = 1 ;
		:WEST-EAST_PATCH_END_STAG = 16 ;
		:SOUTH-NORTH_PATCH_START_UNSTAG = 1 ;
		:SOUTH-NORTH_PATCH_END_UNSTAG = 16 ;
		:SOUTH-NORTH_PATCH_START_STAG = 1 ;
		:SOUTH-NORTH_PATCH_END_STAG = 17 ;
		:GRIDTYPE = "C" ;
		:DX = 1000.f ;
		:DY = 1000.f ;
		:DYN_OPT = 2 ;
		:CEN_LAT = 41.47101f ;
		:CEN_LON = -73.74365f ;
		:TRUELAT1 = 30.f ;
		:TRUELAT2 = 60.f ;
		:MOAD_CEN_LAT = 41.47101f ;
		:STAND_LON = -97.f ;
		:POLE_LAT = 90.f ;
		:POLE_LON = 0.f ;
		:corner_lats = 41.42282f, 41.55638f, 41.51908f, 41.38562f, 41.42414f, 41.5577f, 41.51775f, 41.38428f, 41.41836f, 41.56083f, 41.52353f, 41.38117f, 41.41969f, 41.56216f, 41.52219f, 41.37983f ;
		:corner_lons = -73.85333f, -73.80026f, -73.63379f, -73.68719f, -73.85928f, -73.80621f, -73.62784f, -73.68127f, -73.8551f, -73.79849f, -73.63202f, -73.689f, -73.86105f, -73.80444f, -73.62607f, -73.68304f ;
		:MAP_PROJ = 1 ;
		:MMINLU = "USGS" ;
		:NUM_LAND_CAT = 24 ;
		:ISWATER = 16 ;
		:ISLAKE = -1 ;
		:ISICE = 24 ;
		:ISURBAN = 1 ;
		:ISOILWATER = 14 ;
		:grid_id = 1 ;
		:parent_id = 1 ;
		:i_parent_start = 1 ;
		:j_parent_start = 1 ;
		:i_parent_end = 16 ;
		:j_parent_end = 17 ;
		:parent_grid_ratio = 1 ;
		:sr_x = 1 ;
		:sr_y = 1 ;
		:FLAG_MF_XY = 1 ;
		:FLAG_LAI12M = 1 ;
}
In [17]:
%matplotlib inline
import xarray as xr

geogrid = xr.open_dataset('~/wrf-hydro-training/lesson-wps/geo_em.d01.nc')
geogrid.HGT_M.plot()
Out[17]:
<matplotlib.collections.QuadMesh at 0x7f6668f4e550>

View the wrfinput_d01.nc file

In [18]:
%%bash
ncdump -h ~/wrf-hydro-training/lesson-wps/wrfinput_d01.nc

netcdf wrfinput_d01 {
dimensions:
	Time = UNLIMITED ; // (1 currently)
	south_north = 16 ;
	west_east = 15 ;
	soil_layers_stag = 4 ;
variables:
	float CANWAT(Time, south_north, west_east) ;
		CANWAT:units = "kg/m^2" ;
		CANWAT:_FillValue = -1.e+36f ;
	float DZS(Time, soil_layers_stag) ;
		DZS:units = "m" ;
		DZS:_FillValue = -1.e+36f ;
	float HGT(Time, south_north, west_east) ;
		HGT:FieldType = 104 ;
		HGT:MemoryOrder = "XY " ;
		HGT:units = "meters MSL" ;
		HGT:description = "Topography height" ;
		HGT:stagger = "M" ;
		HGT:sr_x = 1 ;
		HGT:sr_y = 1 ;
	int ISLTYP(Time, south_north, west_east) ;
		ISLTYP:_FillValue = -9999 ;
	float IVGTYP(Time, south_north, west_east) ;
		IVGTYP:FieldType = 104 ;
		IVGTYP:MemoryOrder = "XY " ;
		IVGTYP:units = "category" ;
		IVGTYP:description = "Dominant category" ;
		IVGTYP:stagger = "M" ;
		IVGTYP:sr_x = 1 ;
		IVGTYP:sr_y = 1 ;
	float LAI(Time, south_north, west_east) ;
		LAI:units = "m^2/m^2" ;
		LAI:_FillValue = -1.e+36f ;
	float MAPFAC_MX(Time, south_north, west_east) ;
		MAPFAC_MX:FieldType = 104 ;
		MAPFAC_MX:MemoryOrder = "XY " ;
		MAPFAC_MX:units = "none" ;
		MAPFAC_MX:description = "Mapfactor (x-dir) on mass grid" ;
		MAPFAC_MX:stagger = "M" ;
		MAPFAC_MX:sr_x = 1 ;
		MAPFAC_MX:sr_y = 1 ;
	float MAPFAC_MY(Time, south_north, west_east) ;
		MAPFAC_MY:FieldType = 104 ;
		MAPFAC_MY:MemoryOrder = "XY " ;
		MAPFAC_MY:units = "none" ;
		MAPFAC_MY:description = "Mapfactor (y-dir) on mass grid" ;
		MAPFAC_MY:stagger = "M" ;
		MAPFAC_MY:sr_x = 1 ;
		MAPFAC_MY:sr_y = 1 ;
	float SEAICE(Time, south_north, west_east) ;
		SEAICE:_FillValue = -1.e+36f ;
	float SHDMAX(Time, south_north, west_east) ;
		SHDMAX:units = "%" ;
		SHDMAX:_FillValue = -1.e+36f ;
	float SHDMIN(Time, south_north, west_east) ;
		SHDMIN:units = "%" ;
		SHDMIN:_FillValue = -1.e+36f ;
	float SMOIS(Time, soil_layers_stag, south_north, west_east) ;
		SMOIS:units = "m^3/m^3" ;
		SMOIS:_FillValue = -1.e+36f ;
	float SNOW(Time, south_north, west_east) ;
		SNOW:units = "kg/m^2" ;
		SNOW:_FillValue = -1.e+36f ;
	float TMN(Time, south_north, west_east) ;
		TMN:units = "K" ;
		TMN:_FillValue = -1.e+36f ;
	float TSK(Time, south_north, west_east) ;
		TSK:units = "K" ;
		TSK:_FillValue = -1.e+36f ;
	float TSLB(Time, soil_layers_stag, south_north, west_east) ;
		TSLB:units = "K" ;
		TSLB:_FillValue = -1.e+36f ;
	int XLAND(Time, south_north, west_east) ;
		XLAND:_FillValue = -9999 ;
	float XLAT(Time, south_north, west_east) ;
		XLAT:FieldType = 104 ;
		XLAT:MemoryOrder = "XY " ;
		XLAT:units = "degrees latitude" ;
		XLAT:description = "Latitude on mass grid" ;
		XLAT:stagger = "M" ;
		XLAT:sr_x = 1 ;
		XLAT:sr_y = 1 ;
	float XLONG(Time, south_north, west_east) ;
		XLONG:FieldType = 104 ;
		XLONG:MemoryOrder = "XY " ;
		XLONG:units = "degrees longitude" ;
		XLONG:description = "Longitude on mass grid" ;
		XLONG:stagger = "M" ;
		XLONG:sr_x = 1 ;
		XLONG:sr_y = 1 ;
	float ZS(Time, soil_layers_stag) ;
		ZS:units = "m" ;
		ZS:_FillValue = -1.e+36f ;

// global attributes:
		:TITLE = "OUTPUT FROM GEOGRID V3.9" ;
		:SIMULATION_START_DATE = "0000-00-00_00:00:00" ;
		:WEST-EAST_GRID_DIMENSION = 16 ;
		:SOUTH-NORTH_GRID_DIMENSION = 17 ;
		:BOTTOM-TOP_GRID_DIMENSION = 0 ;
		:WEST-EAST_PATCH_START_UNSTAG = 1 ;
		:WEST-EAST_PATCH_END_UNSTAG = 15 ;
		:WEST-EAST_PATCH_START_STAG = 1 ;
		:WEST-EAST_PATCH_END_STAG = 16 ;
		:SOUTH-NORTH_PATCH_START_UNSTAG = 1 ;
		:SOUTH-NORTH_PATCH_END_UNSTAG = 16 ;
		:SOUTH-NORTH_PATCH_START_STAG = 1 ;
		:SOUTH-NORTH_PATCH_END_STAG = 17 ;
		:GRIDTYPE = "C" ;
		:DX = 1000.f ;
		:DY = 1000.f ;
		:DYN_OPT = 2 ;
		:CEN_LAT = 41.47101f ;
		:CEN_LON = -73.74365f ;
		:TRUELAT1 = 30.f ;
		:TRUELAT2 = 60.f ;
		:MOAD_CEN_LAT = 41.47101f ;
		:STAND_LON = -97.f ;
		:POLE_LAT = 90.f ;
		:POLE_LON = 0.f ;
		:corner_lats = 41.42282f, 41.55638f, 41.51908f, 41.38562f, 41.42414f, 41.5577f, 41.51775f, 41.38428f, 41.41836f, 41.56083f, 41.52353f, 41.38117f, 41.41969f, 41.56216f, 41.52219f, 41.37983f ;
		:corner_lons = -73.85333f, -73.80026f, -73.63379f, -73.68719f, -73.85928f, -73.80621f, -73.62784f, -73.68127f, -73.8551f, -73.79849f, -73.63202f, -73.689f, -73.86105f, -73.80444f, -73.62607f, -73.68304f ;
		:MAP_PROJ = 1 ;
		:MMINLU = "USGS" ;
		:NUM_LAND_CAT = 24 ;
		:ISWATER = 16 ;
		:ISLAKE = -1 ;
		:ISICE = 24 ;
		:ISURBAN = 1 ;
		:ISOILWATER = 14 ;
		:grid_id = 1 ;
		:parent_id = 1 ;
		:i_parent_start = 1 ;
		:j_parent_start = 1 ;
		:i_parent_end = 16 ;
		:j_parent_end = 17 ;
		:parent_grid_ratio = 1 ;
		:sr_x = 1 ;
		:sr_y = 1 ;
		:FLAG_MF_XY = 1 ;
		:FLAG_LAI12M = 1 ;
		:NCO = "\"4.5.4\"" ;
		:history = "Thu Oct 17 16:01:20 2019: ncks -O -x -v SOILTEMP,GREENFRAC,LAI12M,SOILCTOP /home/docker/wrfinput_d01.nc /home/docker/wrfinput_d01.nc\nThu Oct 17 16:01:19 2019: ncrename -O -v LU_INDEX,IVGTYP /home/docker/wrfinput_d01.nc /home/docker/wrfinput_d01.nc\nThu Oct 17 16:01:19 2019: ncrename -O -v XLONG_M,XLONG /home/docker/wrfinput_d01.nc /home/docker/wrfinput_d01.nc\nThu Oct 17 16:01:19 2019: ncrename -O -v XLAT_M,XLAT /home/docker/wrfinput_d01.nc /home/docker/wrfinput_d01.nc\nThu Oct 17 16:01:19 2019: ncrename -O -v HGT_M,HGT /home/docker/wrfinput_d01.nc /home/docker/wrfinput_d01.nc\nThu Oct 17 16:01:19 2019: ncks -O -4 -v XLAT_M,XLONG_M,HGT_M,SOILTEMP,LU_INDEX,MAPFAC_MX,MAPFAC_MY,GREENFRAC,LAI12M,SOILCTOP /home/docker/WRF_WPS/WPS/geo_em.d01.nc /home/docker/wrfinput_d01.nc" ;
}

Generating wrfinput files for use in WRF-Hydro

As mentioned above, the WRF-Hydro group also provides a script package to generate wrfinput files. This section walks through how to download and run this script package.

In [19]:
%%bash
cd /home/docker/wrf-hydro-training/lesson-wps

wget http://ral.ucar.edu/sites/default/files/public/create_wrfinput.zip &> /dev/null
unzip create_wrfinput.zip

Archive:  create_wrfinput.zip
   creating: create_wrfinput/
  inflating: create_wrfinput/create_wrfinput.R  
  inflating: create_wrfinput/README.txt
In [20]:
%%bash
cat /home/docker/wrf-hydro-training/lesson-wps/create_wrfinput/README.txt

README.txt

Purpose: create_wrfinput.R is an R script developed for the purpose of creating wrfinput files for
         the WRF-Hydro model. The script produces fields of spatially uniform initial model states
         of soil moisture, soil temperature, soil liquid water content and skin temperature among
         a few other variables necessary for model cold-start initialization. This script allows 
         users to avoid running the WRF program real.exe.  

Authors: NCAR WRF-Hydro team

Created: June 2018
Updated: May 2019

Requirements: R, NCO, and the following R packages: ncdf4 and optparse

Input files:
   geo_em.d01.nc - geogrid file defining the model domain of interest generated by the WRF
                   Preprocessing System (WPS)
   
Output files:
   wrfinput_d01.nc (default filename) - wrfinput file to initialize the Noah-MP land surface model in WRF-Hydro

Usage: ./create_wrfinput.R --geogrid='geo_em.d01.nc' --filltyp=3 --laimo=8 

Important notes:
   * Both filltyp and laimo arguments have default values. However, we recommend that users
     specify values more appropriate for their domain / simulation.
   * For more information and descriptions of these and other optional arguments run the script
     with no arguments.
In [21]:
%%bash
cd /home/docker/wrf-hydro-training/lesson-wps/create_wrfinput

Rscript create_wrfinput.R --geogrid='/home/docker/wrf-hydro-training/lesson-wps/geo_em.d01.nc'

[1] "ncks -O -4 -v XLAT_M,XLONG_M,HGT_M,SOILTEMP,LU_INDEX,MAPFAC_MX,MAPFAC_MY,GREENFRAC,LAI12M,SOILCTOP /home/docker/wrf-hydro-training/lesson-wps/geo_em.d01.nc wrfinput_d01.nc"
[1] "ncrename -O -v HGT_M,HGT wrfinput_d01.nc wrfinput_d01.nc"
ncrename: In total renamed 0 attributes, 0 dimensions, 0 groups, and 1 variable
[1] "ncrename -O -v XLAT_M,XLAT wrfinput_d01.nc wrfinput_d01.nc"
ncrename: In total renamed 0 attributes, 0 dimensions, 0 groups, and 1 variable
[1] "ncrename -O -v XLONG_M,XLONG wrfinput_d01.nc wrfinput_d01.nc"
ncrename: In total renamed 0 attributes, 0 dimensions, 0 groups, and 1 variable
[1] "ncrename -O -v LU_INDEX,IVGTYP wrfinput_d01.nc wrfinput_d01.nc"
ncrename: In total renamed 0 attributes, 0 dimensions, 0 groups, and 1 variable
[1] "ncks -O -x -v SOILTEMP,GREENFRAC,LAI12M,SOILCTOP wrfinput_d01.nc wrfinput_d01.nc"

This concludes the lesson on domain definition and initial conditions for WRF-Hydro.

© UCAR 2018