Make a table by averaging values nationally and in each NCRA region for each RCM and second by computing the 10, 50, and 90 percentiles from the ensemble of RCM averaged values.
The table would have national and each NCRA region the 10,50 and 90 percentile change in the hazard metric from GWL1.2 for GWL 1.5, 2, 3
rcm1
...
rcm13
ens p10th
ens p50th
ens p90th
NCRA region 0
...
NCRA region 9
AUS
Start with mean change in FFDI from GWL1.2.
Data is at /g/data/ia39/ncra/fire/ffdi for each RCM (20 years of data in each zarr collection).
Compute the average change in FFDI for each RCM and provide that in figures and tables.
See ensemble-table.ipynb for details. This is expensive to run. Request XXL compute size. It is parallelized, so you can request many cores to take advantage of the parallelization.
Make a table by averaging values nationally and in each NCRA region for each RCM and second by computing the 10, 50, and 90 percentiles from the ensemble of RCM averaged values. The table would have national and each NCRA region the 10,50 and 90 percentile change in the hazard metric from GWL1.2 for GWL 1.5, 2, 3
Start with mean change in FFDI from GWL1.2.
Data is at /g/data/ia39/ncra/fire/ffdi for each RCM (20 years of data in each zarr collection).
Compute the average change in FFDI for each RCM and provide that in figures and tables.