Sample JULES4.9 Global Land Surface Processes Simulation
(by Patrick McGuire, Pier Luigi Vidale, Alberto Martinez de la Torre and Grenville Lister)
- Monthly Average Precipitation (1979-1989), used as one of the WFDEI driving factors
- Monthly Average Total Soil Moisture (1979-2012), one of the outputs of the JULES simulation (MP4 version)
- Monthly Average Net Primary Productivity (NPP) (1979-1989), one of the outputs of the JULES simulation
- Anomaly of Monthly Average Total Soil Moisture (1979-2012), computed from the JULES output with CDO (MP4 version)
These animations were produced from the Rose/Cylc suite u-as052 with JULES4.9 (with 0.5 hour time steps) that dumped the data to disk every 6 hours of simulation calendar time (with the 2D variables saved as 1D with an ocean mask) , by using:
i) a CSH script that uses CDO to do the monthly averaging for the 11 year (or 34 year) data set, which creates a new NETCDF file;
ii) a Python script (i.e., for soil moisture or anomaly of soil moisture), that uses the new monthly-averages 1D NETCDF file and saves the PNG animation frames to disk (These Python scripts were adapted from Emma Robinson’s data visualization script); and
iii) this ImageMagick command to merge the PNG frames into an animated GIF:
convert -set delay 0 -colors 256 -dispose 1 -loop 1 precip*.png precip_GL1979-2012.gif
iv) this ffmpeg command to convert the animated gif to an MP4:
~/ffmpeg/bin/ffmpeg -i smc_anom_GL1979-2012_v2.gif -movflags faststart -pix_fmt yuv420p -vf “scale=trunc(iw/2)*2:trunc(ih/2)*2” smc_anom_GL1979-2012_v2.mp4
v) for the animation of the anomaly of soil moisture, this CSH script was used to compute the anomaly with CDO operators.
Compare these global animations to our previous Northern Hemisphere animations. The color bars have been changed since then, and we’re now using Python to make the animation frames instead of Panoply.