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During the course of the CCRN project, the CCRN project team downloaded, processed and created several datasets for running MESH. This page documents the locally available datasets and scripts developed to extract the data for a sub-basin, provided it is within the domain of the datasets.This is a top-level document; each dataset is further described in README files and papers in their storage locations mentioned.

  • To run MESH, 7 variables are needed at sub-daily time step (see Meteorological Input).  
  • Any bugs or questions can be directed to Elshamy, Mohamed. 
  • The scripts provided process one variable at a time. 
    • One can easily parallelize by invoking several instances of MATLAB and changing the variable being processed. 
    • Another way would be to build a loop into those scripts to process all variables and use the MATLAB parallel pool. 
  • The scripts print the input and output file names and the time stamps ... please take care that the time progresses in the manner expected, depending on the time step of the dataset (hourly, 3hourly, etc.) and time span.
It is the responsibility of the user to make sure that the data processing is correct and that the scripts work correctly for the basin provided.

This presentation sheds some light on the datasets: Bias Corrected Climate Forcing Datasets for Land Surface Modeling.pdf

The datasets can be accessed by one of the following methods:

  • If you have access to Graham, then you can download the data to use the MATLAB scripts (they were written and tested on Windows machine) or if you have a MATLAB license on Graham, then you can transfer the scripts there and adjust them (normally all what's needed is switch the path slashes from '\' to '/') but it is your responsibility to test them. 
  • If you are at GIWS and have access to GLOBALWATER share on datastore, you can access the files there.
  • If you do not have access to either location, you need to download the data from their original sources if they are published already. Some links are provided below for the publicly-available Federated Research Data Repository (FRDR) and Global Water Futures Cuizinart database. 
  • Otherwise, contact Elshamy, Mohamedor the data custodian to see if you can get access.

Some of forcing datasets, such as CanRCM4-WFDEI-GEM-CaPA, WFDEI-GEM-CaPA, etc. can be acquired directly via Global Water Futures (GWF) data Cuizinart. The Cuizinart is a cloud-based platform that provides an interactive portal for researchers to "slice and dice" large NetCDF datasets across the GWF program and beyond. To access datasets, users should create an account on Cuizinart then obtain a Globus ID and link it with the Cuizinart account. 


Page Contents

Historical Datasets

WFD: Watch Forcing Data

Resolution and Domain: Global surface data; 0.5° spatial resolution

Timestep: 3 or 6 hourly

Period: 1901-2001

Source: ftp://rfdata:forceDATA@ftp.iiasa.ac.at/WATCH_Forcing_Data/ (password: forceDATA)

Paper: journals.ametsoc.org/view/journals/hydr/12/5/2011jhm1369_1.xml

Storage:

Server: \\datastore\GLOBALWATER\giws_research_water_share\JeffersonW\0_Raw_Data\ClimateForcing\ClimateForcing_WATCH

Script: Interpolate_WFD_NC_Seq_SingleVAR.m

Instructions:

  • You need to have the drainage database of the basin or at least the header and RANK field of it. 
  • Please read the comments at the top of the script and within carefully. This script is prepared run from MATLAB on Windows and reads the data from \\datastore\GLOBALWATER which is mapped to drive V:\. It needs to be configured to write data as described in the header comments. It is recommended that data be written to a local HDD for speed. 
  • The script uses bilinear interpolation from a regular (LAT-LON) grid to another regular grid (LAT-LON). 
  • Processed data is saved in SEQ format. 
  • Snowfall and Rainfall are supplied as separate components that need to be summed for use into MESH. 

Script: Interpolate_WFD_Rain_Snow_NC_Seq.m 

Instructions: 

  • Use the above script: to interpolate the rain and snow components then write the sum to a single file for precipitation.

WFDEI: WATCH-Forcing-Data-ERA-Interim

Resolution and Domain: Global surface data, 0.5° spatial resolution

Timestep: 3 hourly

Period: 1979-2018

Source: ftp://rfdata:forceDATA@ftp.iiasa.ac.at/WATCH_Forcing_Data/WFDEI (password: forceDATA) 

Paper: https://agupubs.onlinelibrary.wiley.com/doi/10.1002/2014WR015638

Storage - whole dataset:

Server: \\datastore\GLOBALWATER\giws_research_water_share\JeffersonW\0_Raw_Data\ClimateForcing\ClimateForcing_WFDEI

Storage - pre-processed dataset:

Domain: Various versions of this dataset clipped for the CCRN domain and a bigger North American domain exist on the server but until 2016 only.

Resolution : Interpolated to the 0.125° spatial resolution  

Server: \\datastore\GLOBALWATER\Model_Output\81_WFDEI_1979_2016

Graham: /project/6008034/Model_Output/CCRN/WFDEI_1979_2016

The raw WFDEI raw dataset has a spatial resolution of 0.5°, but the CCRN pre-processed version was interpolated to the 0.125° resolution and Feb 29 on leap years was omitted in preparation for bias correction against GEM-CaPA to produce WGC. The post-processing steps to extract and interpolate the NetCDF forcing for a domain of interest, filling the Feb 29 on leap years, and filling the missing data are provided here.  


Script: Read_WFDEI_SingleVAR.m

The WFDEI forcing data is a land-only dataset, and therefore it contains missing data in sea pixels that should be infilled and processed by the user. The process is described here in case your basin is affected.

Instructions:

  • You need to have the drainage database of the basin or at least the header and RANK field of it 
  • Please read the comments at the top of the script and within carefully. 
  • This script is prepared run from MATLAB on Windows and reads the data from \\datastore\GLOBALWATER which is mapped to drive V:\. It needs to be configured to write data as described in the header comments. It is recommended that data be written to a local HDD for speed. 
  • The script assumes no interpolation is needed, i.e. basin grid has the same resolution as the data and is aligned to that of the data, i.e. it only clips the data for the basin, and formats it using the RANK field to write the space-saving SEQ format. 
  • This script processes only the North American domain version of the data that is already interpolated to 0.125-degree resolution, not the original data.

Princeton Dataset v2

Resolution and Domain: Global surface data, 0.5 deg spatial resolution

Timestep: 3 hourly

Period: 1901-2012

Source: http://hydrology.princeton.edu/data.pgf.php

Storage:

Server: \\datastore\GLOBALWATER\giws_research_water_share\JeffersonW\0_Raw_Data\ClimateForcing\ClimateForcing_Princeton

GEM-CaPA

  • Combines hourly forecasts from the Global Environmental Multiscale (GEM) atmospheric model at 40 m with 6 hourly Canadian Precipitation Analysis (CaPA) but resampled to 1 hourly resolution.

Resolution and Domain: GEM has global coverage but CaPA is restricted to North America. Spatial resolution increased over time from 25 km to 15 km to 10 km.

Timestep: 1 or 3 hourly

Period: 2002 onwards

Source: ECCC

Storage - NetCDF, hourly, Sep 1, 2004 - Aug 31, 2017

Processed by Dan Princz. The dataset is originally 4D (lat, lon, level, time).

Server: \\datastore\GLOBALWATER\Model_Output\101_GEM-CaPA_interpolated_0.125

Graham: /project/6008034/Model_Output/101_GEM-CaPA_interpolated_0.125

The original forcing dataset has four dimensions. The post-processing analysis was applied by Mohamed Elshamy to remove the 'level' dimension (there is one level in the dataset). The post-processed GEM-CaPA forcing has three dimensions, including lat, lon, and time

Graham: /project/6008034/Model_Output/104_GEM-CaPA_interpolated_0.125_3D

Storage - NetCDF, 3 hourly, 2005-2016

Post-processed by Elvis Asong from the above hourly dataset (level is not included as a dimensional variable, Feb 29 on leap years removed)

Server: \\datastore\GLOBALWATER\Model_Output\103_GEM-CaPA-3h

Graham: /project/6008034/Model_Output/CCRN/GEM_CaPA_2005_2016

The 3-hourly version is the one used to produce WFDEI-GEM-CaPA and has been published as part of that - see the section below.

WFDEI-GEM-CaPA

  • This dataset combines the strength of GEM-CaPA (better agreement with observations over Canada) with the length of WFDEI to construct a longer time series that resembles GEM-CaPA to be used for climate analysis and model calibration/validation purposes. 
  • Variables are assumed to be at 40 m because the reference dataset is at 40 m.
  • Combining the two datasets was done by Elvis Asong

The post-proceed version of the dataset has been done by Mohamed and it is available on the Graham based on adding Feb 29 on leap years (using the average of Feb 28th and Mar 1st) for the whole domain. 

The WFDEI forcing data on which WFDEI-GEM-CaPA is built is a land-only dataset and therefore it contains missing values in the sea that should be filled and processed by the user. The process is described here in case your basin is affected.

Resolution and Domain: This dataset is restricted to a large domain covering most of North America (intersection of the WFDEI and GEM-CaPA domains)

Timestep: 3 hourly

Period:  1979-2016

Source: 

Storage:

Server: \\datastore\GLOBALWATER\Model_Output\181_WFDEI-GEM_1979_2016

Graham: /project/6008034/Model_Output/CCRN/WFDEI-GEM_1979_20161 

Graham: /project/6008034/Model_Output/181_WFDEI-GEM-CaPA_1979-20162 

1) Feb 29 on leap years is missing.

2) In the post-processed version, Feb 29 was added in leap years and names of some variables were modified (tas to ta; huss to hus; sfcWind to wind). For the shortwave radiation variable (RSDS) the thresholded one should be used.

FRDR (public): https://www.frdr.ca/repo/handle/doi:10.20383/101.0111

Cuizinart (public): https://tuna.cs.uwaterloo.ca/ (select "wfdei-gem-capa" from drop-down list)

Script: Read_WFDEI_SingleVAR.m

Instructions:

  • This is the same script used to process data for a sub-basin as mentioned above for the NA version of the WFDEI data.

WRF-CTL

Resolution and Domain: 4 km covering the CCRN domain (Western Canada)

Timestep: hourly

Period: Oct 2000 - Sep 2015

Storage:

Server: \\datastore\GLOBALWATER\Model_Output\WRF\WRF4KM_CA\CTRL_Post_Processed

Graham: /project/6008034/Model_Output/WRF/WRF4KM_CA/CTRL_Post_Processed

    • Surface variables important for hydrology are stored at: /project/6008034/Model_Output/WRF/WRF4KM_CA/HYDRO/CTRL

Instructions and Scripts:

To process WRF data for a particular basin, there are a few steps.

  • The process is done partly on Graham using a set of shell and NCL scripts (written by Sopan Kurkute and edited by Zhenhua Li and Mohmed Elshamy) and then completed on Windows using a MATLAB Script. 
  • The scripts use the NCL language to interpolate the WRF data from its rotated-pole coordinate system to a regular LAT-LON grid using "conserve" interpolation which maintains the totals. 
    • This is especially important when interpolating from a fine grid (WRF is 4 km) to a coarser grid (usually 10 km for MESH). 
  • Processing will need to be done on Graham (or other servers that you may move the data to)
    • Note that you will need to create a job script (SLURM) on Graham that calls the shell script and submit the job. 
  • Processing time depends on the size of the basin but is usually several hours. It parallelizes automatically so it would be good to ask for 8 cores - one per variable.

The scripts are included here and steps are as follows:

  1. Configure and run the script convert_to_r2c.wgt.sh which will process a single month to get the weighting matrix for your basin. Configuration means setting some information about the dimensions and location of your basin and the location of input and outputs. Change the output and source (where the scripts reside) folders only. This script will produce a file called "weights_file.nc" in the output and you need to copy/move it to the source folder.
  2. Configure and run the script convert_to_r2c.CTL.sh to your grid specifications. You can also configure which years to process and which months.  The first year goes from month 10 - 12 and has to be processed separately. These scripts produce monthly R2C files. The script uses NCL scripts to process all variables together. Files are arranged per variable in annual folders (each year in a separate folder). If you wish to process some variables, comment blocks of code for unwanted ones.
  3. Collect all files from the annual folders into one folder per variable (keep the variable folder names) and transfer them a windows machine
  4. Run the MATLAB script: multi_r2c_2_seq_SingleVAR.m that will collate all R2C files for a variable into a single SEQ file for that variable. You can parallelize the operation by invoking several instances of MATLAB and processing a variable in each instance. The script is currently configured to process the whole period from Oct 2000 - Sep 2015. There is one unit conversion made within the script for precipitation as it is originally in mm/hr and it is required to be in mm/sec (which is the same as kg/m2/sec given a density of 1000 kg/m3 for water).

WRF-CTL-GEM-CaPA

  • WRF_CTL bias-corrected against GEM-CaPA using the overlap period (Sep 2004 - Sep 2015) using Alex Cannon's Multi-variate bias correction method (MBCn) with 200 iterations.

Resolution and Domain: This dataset covers the CCRN (Western Canada) domain at 0.125deg resolution and reflects variables at 40m height (as the reference dataset) 

Timestep: hourly

Period: Oct 2000 - Sep 2015

Storage:

  • Processed by Zhenhua Li during the summer of 2018

Server: \\datastore\GLOBALWATER\Model_Output\WRF\WRF4KM_CA\124_Corrected_to_GEM-CaPA_monthly_MBCn_it200

Graham: /project/6008034/Model_Output/WRF/WRF4KM_CA/124_WRF-CTL_Corrected_to_GEM-CaPA_monthly_MBCn_it200

Script: Read_WRF_Cor_GEM_CaPA_SingleVAR.m.

Instructions:

  • You need to have the drainage database of the basin or at least the header and RANK field of it
  • Please read the comments at the top of the script and within carefully. 
  • This script is prepared run from MATLAB on Windows and reads the data from \\datastore\GLOBALWATER which is mapped to drive V:\. You need to configure the output data folder and it is recommended that the processed data is written to a local HDD (not a network share) to improve speed and avoid cluttering the GLOBALWATER\Model_Output network share. 
  • The script assumes no interpolation is needed, i.e. basin grid has the same resolution as the data and is aligned to that of the data, i.e. it only clips the data for the basin, and formats it using the RANK field to write the space-saving SEQ format. 

Script: Interpolate_WRF_CTL_Cor_GEM_CaPA_SingleVAR.m

Instructions: 

  • Use this script if you need to interpolate the data (i.e if the grid has a different resolution or is not aligned with the current grid)
  • The script has a very similar structure to the clipping routine and will interpolate the data using bilinear interpolation.

RDRS v2 

Description: Environment and Climate Change Canada (ECCC) has initiated the production of the Regional Deterministic Reforecast System (RDRS), North American precipitation and surface reanalysis data. The outputs from RDRS-10 are available for 2000-2017.

Source: These data are provided by the Canadian Surface Prediction Archive (CaSPAr) (https://caspar-data.ca/)

The procedure for downloading the forcing dataset is explained on the CaSPAr GitHub page. The steps are summarized as the following

  1. Create an account and link it with the Globus ID. If you do not have a Globus ID, you can register.
  2. Identify the product of interest (e.g RDRS_v2) and the time period of interest.
  3. Define the domain of interest whether based on the rectangular/polygon icon or upload it via a shapefile.
  4. Select variables from the variable list indicated in the table below.
  5. Submit the request. 

Spatial resolution: 0.09° (~ 10 km)

Temporal resolution: hourly time series

Variables: 

Name

Description

Comment

RDRS_v2_P_UVC_09944

Windspeed at 40 m vertical level


RDRS_v2_P_WDC_09944

Wind direction at 40 m vertical level

Required for Mountain MESH

RDRS_v2_P_FI_SFC

Downward longwave radiation at the surface


RDRS_v2_P_FB_SFC

Downward shortwave radiation at the surface


RDRS_v2_A_PR0_SFC

Total Precipitation


RDRS_v2_P_TT_09944

Temperature at 40 m vertical level


RDRS_v2_P_HU_09944

specific humidity at 40 m vertical level


RDRS_v2_P_P0_SFC

Surface Pressure



Storage – NetCDF, 1 hourly, 2000-2017: 

The concatenated climate forcing including all eight variables for six Canadian Basins are available on Graham as the following:

Graham: /project/6008034/Model_Output/105_RDRS_v2_10km/01_Mackenzie/MRB_RDRS_v2_2000-2017_MESH

Graham: /project/6008034/Model_Output/105_RDRS_v2_10km/74_Bow_Columbia/Bow_Columbia_RDRS_v2_2000-2017_MESH

Graham: /project/6008034/Model_Output/105_RDRS_v2_10km/91_Fraser/Fraser_RDRS_v2_2000-2017_MESH

Graham: /project/6008034/Model_Output/105_RDRS_v2_10km/92_StJohn/StJohn_RDRS_v2_2000-2017_MESH

Graham: /project/6008034/Model_Output/105_RDRS_v2_10km/93_Great-Lakes/GL_RDRS_v2_2000-2017_MESH

Graham: /project/6008034/Model_Output/105_RDRS_v2_10km/94_Nelson-Churchill/NCRB_RDRS_v2_2000-2017_MESH 


Code: The code script written by Mohamed Elshamy for processing these data is available on the MESH-Model GitHub page. The instruction in the ReadMe file explains the procedure of processing these data. 

Users should supply the variable names in the run_options file. See the variable names on the above table and set the  start_date to < 2000010112> and indicates time_shift based on your domain of interest.


Datasets covering both Historical and Future Periods

CanRCM4

  • These model runs are dynamic downscaling of the CanESM2 earth system model
  • A total of 21 variables were downloaded, including surface and lowest model level (above the surface) variables and water and energy balance components
  • Forced by historical emissions till 2005 and by RCP 8.5 from 2006-2100

The CanRCM4 uses a 365-day calendar originally, so the Feb29 is missing on leap years. The pre-processing procedure to fill the Feb 29 on leap years of the NetCDF data is given here. 


Resolution and Domain: This dataset covers the CORDEX North American Domain, and there is one high-resolution member at 0.22° resolution and 15 members at 0.44° resolution

Timestep: hourly

Period: 1950-2100

Storage:

Server:   

    • \\datastore\GLOBALWATER\Model_Output\110_CanRCM4-44-1h1
    • \\datastore\GLOBALWATER\Model_Output\110_CanRCM4-22-1h2

Graham: 

    • /project/6008034/Model_Output/110_CanRCM4-44-1h1
    • /project/6008034/Model_Output/110_CanRCM4-22-1h2

Script: CanRCM4_NC_44_Seq_fullperiod.m


1) This folder contains CanRCM4 forcing files - fifteen ensemble members arranged by variable. The dataset has a spatial resolution of 0.44°(~50km) at hourly temporal resolution.

2) This folder contains CanRCM4 forcing files - one member arranged by variable. The dataset has a spatial resolution of 0.22° (~ 25km) at hourly temporal resolution.

Instructions:

  • Use this MATLAB script to process the data for a sub-basin 
    • You need to have the drainage database of the basin or at least the header and RANK field of it
  • Please read the comments at the top of the script and within carefully. 
  • This script is prepared run from MATLAB on Windows and reads the data from \\datastore\GLOBALWATER which is mapped to drive V:\. You need to configure the output data folder and it is recommended that the processed data is written to a local HDD (not a network share). It improves speed and avoids cluttering the GLOBALWATER\Model_Output network share. 
  • This script interpolates the data from the CanRCM4 rotated pole grid to a regular LAT-LON grid as defined by the shed file using linear (but sparsely spaced) interpolation. 
  • Processed data is saved in SEQ format.
  • The above script can be used for all variables. 
    • Windspeed at the surface is provided as sfcWind, but the lowest model level, meridional and zonal components need to be combined to get the resultant wind speed.


A processed version of this dataset for MESH users and in preparation for bias correction is available. 

Resolution and Domain: Most of North American, interpolated to 0.125° spatial resolution.

Timestep: 3-hourly

Period: 1951-2100

Storage:

Graham: 

/project/6008034/Model_Output/CCRN/CanRCM4/CanRCM4_Raw

Instructions:

  • use the same script as the CanRCM4-WFDEI-GEM-CaPA dataset - modify for file names

CanRCM4-WFDEI-GEM-CaPA

  • This dataset is the high resolution (0.125°) 15 ensemble members of CanRCM4, bias-corrected against WFDEI-GEM-CaPA
    • Only MESH 7 required variables were bias-corrected for the period 1951-2100
    • Elvis Asong performed the bias correction using Alex Cannon's Multi-variate bias correction method (MBCn)
  • The resulting dataset reflects variables at 40 m height (same as the reference dataset)

The post-proceed version of the dataset has been done by Mohamed and it is available on the Graham based on adding Feb 29 on leap years (using the average of Feb 28th and Mar 1st) for the whole domain. 

Resolution and Domain: Most of North America, 0.125 deg resolution

Timestep: 3 hourly

Period: 1951-2100

Source: https://essd.copernicus.org/articles/12/629/2020/

Storage:

Server: \\datastore\GLOBALWATER\Model_Output\280_CanRCM4_Cor_WFDEI-GEM-CaPA

Graham: /project/6008034/Model_Output/CCRN/CanRCM4/WFDEI-GEM-CaPA1

Graham: /project/6008034/Model_Output/280_CanRCM4_Cor_WFDEI-GEM-CaPA2 

1) Feb 29 on leap years is missing.

2) In the post-process version, Feb 29 was added in leap years and names of some variables were modified (tas to ta; huss to hus; sfcWind to wind).

FRDR (public): https://www.frdr.ca/repo/handle/doi:10.20383/101.0162   (clipped extents to Mackenzie River Basin)

Cuizinart (public): https://tuna.cs.uwaterloo.ca/ (select "canrcm4-wfdei-gem-capa" from drop-down list)

Script: Read_BIAS_Corrected_CanRCM4_WFDEI_GEM_SingleVAR.m

Instructions:

  • You need to have the drainage database of the basin or at least the header and RANK field of it
  • Please read the comments at the top of the script and within carefully. 
  • This script is prepared run from MATLAB on Windows and reads the data from \\datastore\GLOBALWATER which is mapped to drive V:\. It needs to be configured to write data as described in the header comments. It is recommended that data be written to a local HDD for speed. 
  • The script assumes no interpolation is needed, i.e. basin grid has the same resolution as the data and is aligned to that of the data, i.e. it only clips the data for the basin, and formats it using the RANK field to write the space-saving SEQ format. 

Script: Interpolate_BIAS_Corrected_CanRCM4_WFDEI_GEM_SingleVAR.m.

The WFDEI forcing data upon which this dataset is built is a land-only dataset, and therefore it contains missing values in the sea that should be filled and processed by the user. The process is described here in case your basin is affected.

Instructions: 

  • Use this script if you need to interpolate the data (i.e. if the grid has a different resolution or is not aligned to the current grid)  
  • The script uses bilinear interpolation from a regular (LAT-LON) grid to another regular grid (LAT-LON). Processed data is saved in SEQ format.

CanRCM4-WFDEI

  • This dataset is the medium resolution (0.44°), 15 ensemble members of CanRCM4, bias-corrected against WFDEI
    • Only MESH 7 required variables were bias-corrected for the period 1951-2100
    • Elvis Asong performed the bias correction using Alex Cannon's Multi-variate bias correction method (MBCn)
  • The resulting dataset reflects variables at surface height.

Resolution and Domain: Most of North America, 0.5 deg resolution

Timestep: 3 hourly

Period: 1951-2100

Storage:

Server: \\datastore\GLOBALWATER\Model_Output\200_CanRCM4_cor_WFDEI

Graham: /project/6008034/Model_Output/CCRN/CanRCM4_0.5/CanRCM4/CanRCM4_CORR_WFDEI

FRDR (public): https://www.frdr-dfdr.ca/repo/handle/doi:10.20383/101.0230

Script: see scripts for CanRCM4-WFDEI-GEM-CaPA above.

Future (only) Datasets

WRF_PGW

  • This dataset is a dynamical downscaling of ERA-Interim perturbed by 30-yr multi-model mean changes over the period 2070-2100 under RCP 8.5 (pseudo global warming method - PGW). 
  • WRF simulations were performed and post-processed by the Yanping Li group - see https://hess.copernicus.org/articles/23/4635/2019/.

Resolution and Domain: Covers the CCRN domain (Western Canada) at a 4 km resolution

Timestep: 

Period: Oct 2000 - Sep 2015

Storage:

Server: \\datastore\GLOBALWATER\Model_Output\WRF\WRF4KM_CA\PGW_Post_Processed

Graham: /project/6008034/Model_Output/WRF/WRF4KM_CA/PGW_Post_Processed

    • Surface variables important for hydrology are stored at: /project/6008034/Model_Output/WRF/WRF4KM_CA/HYDRO/PGW

Scripts: See "WRF_CTL" above

Instructions:

  • To process WRF data for a particular basin, there are a few steps:
    • The process is done partly on Graham using a set of shell and NCL scripts (written by Sopan Kurkute and edited by Zhenhua Li and Mohmed Elshamy) and then completed on Windows using a MATLAB Script (refer to WRF_CTL, above, for the process). 
    • You do not need to repeat step 1 if you have done the CTL set. 
    • Use convert_to_r2c.PGW.sh in step 2. 
    • Adjust your forcing directory and file names in the MATLAB script in step 3/4.

WRF-PGW-GEM-CaPA

  • WRF_PGW bias-corrected against GEM-CaPA using the overlap period with WRF_CTL (Sep 2004 - Sep 2015) using Alex Cannon's Multi-variate bias correction method (MBCn) with 200 iterations.
  • Bias correction was done by Zhenhua Li during the summer of 2018

Resolution and Domain: This dataset covers the CCRN (Western Canada) domain at 0.125 deg resolution and reflects variables at 40 m height (as the reference dataset)

Timestep:

Period: Oct 2000 - Sep 2015 (corresponding to some 15 year period in 2070-2100)

Storage:

Server: \\datastore\GLOBALWATER\Model_Output\WRF\WRF4KM_CA\134_WRF-PGW_Corrected_to_GEM-CaPA_monthly_MBCn_it200

Graham: /project/6008034/Model_Output/WRF/WRF4KM_CA/134_WRF-PGW_Corrected_to_GEM-CaPA_monthly_MBCn_it200

Instructions:

  • To process the data for a sub-basin, use the same scripts provided above for WRF-CTL-GEM-CaPA. The scripts can be easily set to process PGW instead of CTL data.

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