# E3SM Diagnostics Package v2¶

- E3SM Diagnostics Package v2
- Input Data Requirement
- Quick Guides
- Examples
- Running examples v2
- Model Time-series vs Model Time-series: Historical H1 (2011-2013) vs Historical H1 (1850-1852)
- Model Time-series vs Model Time-series with CMIP data
- Model Time-series vs Observation Time-series with CMIP data
- Model Climatology vs Model Climatology
- Model Climatology vs Observation Climatology
- Observation Climatology vs Observation Climatology

- Installation
- Configuration and Running
- Defining Parameters
- Available Parameters
- Colormaps
- How to Add New Diagnostics Runs
- Developer Guide
- Contributing to E3SM Diags

## Overview¶

This diagnostics package is constructed to support the diagnostics needs of DOE’s Energy Exascale Earth System Model (E3SM) project, formerly known as Accelerated Climate Modeling for Energy (ACME). The ultimate goal of this work is to develop a comprehensive diagnostics package that:

integrates the basic functionality of NCAR’s AMWG diagnostics package;

utilizes most updated observational datasets, including remote sensing, reanalysis and in-situ datasets;

interfaces with diagnostics developed from different E3SM focus groups: atmosphere group, coupled simulation group, land group;

interacts effectively with the PCMDI’s metrics package and the ARM diagnostics package through a unifying framework: Community Diagnostics Package (CDP).

is flexible for user-specified diagnostics and configuration for use by other climate models.

## Current State (v2 release)¶

Algorithm and visualization codes for **latitude-longitude contour maps**,
**polar contour maps**, the accompanying **summarizing table** and **Taylor diagram plots**, **pressure-latitude zonal mean contour plots**,
**zonal mean line plots**, **pressure-longitude meridional mean contour plots**, **area mean time series plots**, and **Cloud Top Height-Tau** joint histograms
from COSP cloud simulator output. Plots can be created for annual
and seasonal climatologies, and monthly mean time series.

The package also supports custom user diagnostics, by specifying plot type, desired region (global, ocean, land, etc.), pressure levels for variables with the vertical dimension.

For flexibility, the code structure cleanly separates data manipulation (reading input files, processing data, etc) from plotting functions. To satisfy specific user tastes, two graphical back-ends are available:

matplotlib/ cartopy (

**mpl**)CDAT VCS (

**vcs**)

Additional back-ends could be implemented if the need arose.

### Feature availability for each backend¶

Not all plot sets and feature are currently supported for every backend. The table below summarizes current status.

Plot set or Feature |
mpl |
vcs |
---|---|---|

Latitude-longitude contour maps |
✔ |
✔ |

Polar contour maps |
✔ |
✔ |

Pressure-latitude zonal mean contour plots |
✔ |
✔ |

Pressure-longitude meridional mean contour |
✔ |
✘ |

Zonal mean line plots |
✔ |
✔ |

Cloud Top Height-Tau joint histograms |
✔ |
✘ |

Area Mean time series plots |
✔ |
✘ |

Multi-processing |
✔ |
✔ |

^{[1]}Defaults to matplotlib instead.