Practically Perfect Paper Code and Data
This page is currently for the use of the anonymous reviewers.
Please download the netCDF files from the url with a prefix of "http://atlas.niu.edu"
Place all 7 files in the "PPer_Climo/data" folder
The code are presented with figures in the "PPer_Climo/pper_notebooks" folder
Requirements:
- xarray
- numpy
- scipy
- matplotlib
- cartopy
Data Description
For a full description of how the raw data are generated, please see the article when/if it is published.
The data provided are generated by thresholding the raw practically perfect data using common SPC product probability thresholds.
Each variable within the netcdf file represents the grids "activated" by each threshold for each daily period.
In other words, these grids would be within that particular contour line. 'pp_qt' is just the combination of all of these, and contains values from 0 (< 2%) to 7 (>= 60 %).
Not all of these data are used in the manuscript.
Dimensions: (time: 14610, x: 185, y: 129)
Coordinates:
* x (x) int64 0 1 2 3 4 5 6 7 8 ... 176 177 178 179 180 181 182 183 184
* y (y) int64 0 1 2 3 4 5 6 7 8 ... 120 121 122 123 124 125 126 127 128
* time (time) datetime64[ns] 1979-01-01 1979-01-02 ... 2018-12-31
Data variables:
pp_02 (time, y, x) uint8 ...
pp_05 (time, y, x) uint8 ...
pp_10 (time, y, x) uint8 ...
pp_15 (time, y, x) uint8 ...
pp_30 (time, y, x) uint8 ...
pp_45 (time, y, x) uint8 ...
pp_60 (time, y, x) uint8 ...
pp_qt (time, y, x) uint8 ...