1. Python GUI of Earth Observations and Model Evaluation Toolkit (PyGEOMET)
Andrew White, Brian Freitag, Udaysankar Nair, and Arastoo Pour Biazar
The University of Alabama in Huntsville

2. Motivation
Process studies for earth science research often require analysis of multiple datasets, including numerical model outputs, in situ observations, satellite and ground based remote sensing datasets.
Model evaluation can be very time consuming and tedious.
Graphical User Interfaces (GUIs) allow users to quickly and easily view data.
For computationally expensive analysis, direct access to objects is desirable.
PyGEOMET is an effort that was started as a class project, to not only build a GUI for easy viewing of data, but also to build a library that can be used to read and manipulate datasets.

3. Background
PyGEOMET uses the PyQt5 python bindings for Qt cross-platform framework.
Compatible with Python 2.7 and 3.5
Runs on Windows, Linux and Mac.
Additional dependencies include: numpy, matplotlib, mpl_toolkits, netCDF4, PyART, datetime, scipy, csv, boto, ftplib, requests, os, sys, glob, time, warnings
Makes use of OPeNDAP, when possible, to access data remotely.
MERRA
NCEP/NCAR Reanalysis 2
NEXRAD
Local datasets include:
Weather Research and Forecasting (WRF) model
Community Multi-scale Air Quality (CMAQ) model
Geostationary Operational Environmental Satellite (GOES)

4. PyGEOMET Layout PyGEOMET Datasets Main GUI WRFDataset CMAQDataset
GOESClassDataset
GOESDataset
NCARDataset
MERRADataset
RadarDataset
Utilities
Layout Format
Icons
Wrf functions
Derived Variables
NEXRAD sites
Radar sites (csv)

5. Design
The main GUI sets up the user interface and contains all of the plotting code.
Easily add new datasets without having to worry about plotting routines.
New plot types only have to be added to the main GUI for them to be available to all datasets.
The dataset objects, which are used for importing and accessing each dataset, were created so that they could be used independently.
Provides a way to easily read in a particular dataset and have access to all of the files in a specified directory.
Reduces the repetitiveness of having to write code to read in the same dataset in different scripts/programs.

6. Functionality Main GUI Datasets Current plot types: Plot options:
Horizontal cross-sections
Vertical cross-sections
Skew-T
Vertical profiles
Time series
Difference
Plot options:
Filled contour or pcolormesh
Map resolution control
Map background control
Colorbar control – range and colormap
Second control overlays
Wind barbs or vectors
Plot Interaction
Displays plot values and grid location information
Ability to draw and outline features in the plot window.
Reads in all of the data contained in a user specified location.
Sets up grid and projection information.
Single line function calls to interact with the data.
Extract a variable
Change the time, grid, and level
Built-in connection to the main GUI
Basemap object
Projection type
Center latitude and longitude
Grid dimensions
Datetime object
Function to setup the dataset control bar in the GUI
Consistent function names throughout

7. MERRA
Data is accessed through OPeNDAP.

8. NCEP/NCAR Reanalysis II
The GUI allows for the projection to be changed in global datasets.

9. GOES
GOES from NOAA CLASS in netCDF format can be visualized within the GUI.
The Matplotlib library provides zooming and saving features.

10. NEXRAD Data is accessed through Amazon Web Services.
Provides real-time and historical NEXRAD (Level 2) data.

11. CMAQ
The GUI provides the ability to load in the multiple different CMAQ output files and switch between them.

12. WRF
A list of derived variables based on the input WRF variable list is created dynamically.

13. Difference Plots
From two sets of data on the same grid, the instantaneous difference can be displayed.

14. Skew-T
Parcel path can be changed between Surface Base, Mixed Layer and Most Unstable.

15. Vertical Profile
The horizontal variable and vertical profile variable can be controlled independently.

16. Vertical Cross-Section
Ability to change the orientation, location and max pressure level.
Ability to add a second control.

17. Time Series
Can plot any variable at a given point as a function of time.

18. Future Development Currently planned dataset additions:
OLAM
RAMS
TRMM
GPM
CloudSat
Calipso
MODIS
OSTIA
Surface observation data
Currently planned GUI functionality:
Hovmöller diagrams
Allow users to mark a polygon region on the plot and compute statistics for the sampled region.
Allow the comparison between observations and model output.

19. Summary
PyGEOMET was designed to not only to aid in research by quickly creating visualizations, but also to provide a library for reading and manipulating different datasets.
The package has already been released internally and has aided the completion of graduate thesis work.
Provides a quick way to analyze data in a way that can also be beneficial to teaching topics such as atmospheric dynamics.
The ultimate goal for the package is to become a community project.

20. Thank you. https://github
Thank you!