Examples

Introduction

The model and observation data are located at NERSC, so you can run the examples on Cori.

Make sure you’re using version 2.0.0 or greater of e3sm_diags.

Enter a conda environment that has e3sm_diags installed. Follow either a quickstart guide or the instructions here.

The following tables visualize which comparison each of the following examples demonstrate:

Time Series Comparison Examples
	Model	Observation
Model	Ex.1, Ex.2	Ex.3
Observation

Climatology Comparison Examples
	Model	Observation
Model	Ex.4	Ex.5, Ex.6
Observation		Ex.7

Examples

1. Model Time-series vs Model Time-series: Historical H1 (2011-2013) vs Historical H1 (1850-1852)

This example covers how to compare different time slices between two models. In this case, we’re comparing two different three-year time slices from the same model. The raw model output was run through NCO, which created the time-series files.

2. Model Time-series vs Model Time-series with CMIP data

This example covers how to compare different time slices between two models with CMIP5 conventions. In this case, we’re comparing two different three-year time slices from the same model. The raw model output was run through NCO, which created the time-series files.

3. Model Time-series vs Observation Time-series with CMIP data

This example covers how to compare different time slices between observational data and a model with CMIP5 conventions. In this case, we’re comparing two different three-year time slices. The raw model output was run through NCO, which created the time-series files.

4. Model Climatology vs Model Climatology

This example covers how to compare the climatology between two different model outputs. The raw model output was run through NCO, which computed the climatology. We are comparing two simulations: F1850COSP and FC5COSP.

5. Model Climatology vs Observation Climatology

This example covers how to compare the climatology between model output data and observational data. The raw model output was run through NCO, which computed the climatology. We are comparing model and reanalysis data for surface air temperature for two areas: over land and globally.

6. Model Climatology vs Observation Climatology – Zonal Mean 2D and Lat/Lon

This example covers how to compare the climatology between model output data and observational data on two different sets: zonal_mean_2d an lat_lon.

7. Observation Climatology vs Observation Climatology

This example covers how to compare observational data with itself, so you can compare different version of the data, or the same variable from different datasets. We are comparing CERES EBAF TOA version 2.8 and 4.0.

Running the Examples

Preprocessing the Data (Ex.2,3 only)

There are two things you must do to prepare CMIP data to be used by e3sm_diags.

1. Since CMIP model output files follow specific file naming conventions, they must be renamed to follow the E3SM file naming conventions: <variable>_<start_yr>01_<end_yr>12.nc.

Ex: renaming tas_Amon_CESM1-CAM5_historical_r1i2p1_196001-201112.nc to tas_196001_201112.nc.

All of the variables should be in the same directory.

If you’re running with data not used in this example, you must do the above two steps.

Setting the Parameters

The parameters file contains information related to the location of the data, what years to run the diagnostics on, what plots to create, and more.

The configuration file provides information about the diagnostics you are running. This is used in Ex.4,5,7.

Parameters for each example can be found in this directory.

Running the Diagnostics

Enter the directory containing the example you want to run. Edit the parameter file prefix value so the results will be placed in your web directory. Use the code below to run the diagnostics.

# Allocate a node to run an interactive session on. You can also use a batch job.
salloc --nodes=1 --partition=regular --time=01:00:00 -C haswell
# Enter the E3SM Unified environment. For Cori, the command to do this is:
source /global/common/software/e3sm/anaconda_envs/load_latest_e3sm_unified_cori-haswell.sh
# Running Ex.1. For examples 4,5,7 append ``-d diags.cfg``.
python ex1.py --multiprocessing --num_workers=32
# You may need to change permissions on your web directory to see the example output.
chmod -R 755 <your web directory>

Note: For Ex.7, you shouldn’t run the software with just python ex7.py (i.e., without a .cfg file). The reason is that e3sm_diags doesn’t support the obs vs obs comparison with all of the default variables. For each of the plot sets, the user needs to make a *_obs_vs_obs.cfg file in this directory.

Viewing the Results

Results from running all the examples can be found here. You can navigate to https://portal.nersc.gov/project/e3sm/forsyth/examples/<example directory>/viewer/ to see the viewer for a specific example.