Proposed Bias Correction Module Workflow

[andersy005]

The Bias correction workflow will follow the following steps adapted from Downscale Paper doc

• Prepare data

  • Gather tavg, tmin, tmax, pr data:

    • Observed historical data at target resolution

    • GCM-simulated historical conditions at MODEL resolution

    • GCM-simulated future climate conditions at MODEL resolution

  • regrid GCM historical and GCM future projections to REGRID resolution
    xmap.XMap(da).remap_to([('lat', 1), ('lon', 1)], how='bilinear')

  • Coarsen historical data to REGRID resolution (same as regrid - remap_like)

• Bias Correct

  • Remove trend from CMIP tasmin/tasmax projections

  • Bias correct each variable, location, and calendar day:

    • Produce paired CDFs/quantile map from GCM → OBS-HIST

    • Replace values in GCM with OBS-HIST for corresponding portion of distribution

  • Reintroduce trend

• Spatially disaggregate

  • Compute spatial climatology for OBS-HIST

  • Compute GCM-ADJ “factor” (for temp, difference) from OBS-HIST

  • Interpolate factors to target resolution using “SYMAP algorithm (Shepard, 1984), which is basically a modified inverse-distance-squared interpolation.”

  • Merge interpolated factors with target-resolution spatial climatology