Closed sdtaylor closed 3 years ago
try splitting out C4/C3 grasses, especially for Deserts( rt: Rachel)
Results for deserts and bleh, maybe try fitting with the observed soil moisture? My major critique is soil moisture is not modeled well. so...
switch to fCover comparison. Thats what the original paper did. probably better to convert observed gcc -> fcover than the other way around.
That'll should drop most of the high values too.
need to extract these from model files...
Note, need to refit everything after addressing some issues: see
https://github.com/sdtaylor/GrasslandModels/issues/39 https://github.com/sdtaylor/GrasslandModels/issues/37
Cut out all the interscale model comparisons, just have:
Model Scale | R2 | rmse | # Timeseries | Site years |
---|---|---|---|---|
All sites | 0.32 | 0.2 | 90 | 235 |
All Grasslands | 0.32 | 0.2 | 90 | 235 |
All Shrubland | 0.32 | 0.2 | 90 | 235 |
All Ag | 0.32 | 0.2 | 90 | 235 |
E. Temperate | ||||
Grasslands | 0.32 | 0.2 | 90 | 235 |
Ag | 0.32 | 0.2 | 90 | 235 |
Gr plains | ||||
Grasslands | 0.32 | 0.2 | 90 | 235 |
Shrub | 0.32 | 0.2 | 90 | 235 |
these things were implemented in the first minor "revision" to BG, b314cb696a00d6ecc1172c6a9371a76a848a0729
Look at site level errors per ecoregion on a MAT/MAP plot to potentially gain some insights.
Maybe look at the seasonality of precip too