ca.netcdf.wrapper: High-level NetCDF I/O wrapper for the Constructed Analogues (CA) pipeline
Description
CA starts by spatially aggregating high-resolution
gridded observations up to the scale of a GCM. Then it proceeds to
bias correcting the GCM based on those observations. Finally, it
conducts the search for temporal analogues (which is the most
expensive part of the operation). This involves taking each
timestep in the GCM and searching for the top 30 closest timesteps
(for some function of "close") in the gridded observations. For
each of the 30 closest "analogue" timesteps, CA records the
integer number of the timestep and a weight for each of the
analogues. These are all saved in output.file.
Filename of high-res gridded historical observations
varname
Name of the NetCDF variable to downscale (e.g. 'tasmax')
Value
A list object with two values: 'indices' and 'weights', each of which is a vector with 30 items
References
Maurer, E. P., Hidalgo, H. G., Das, T., Dettinger, M. D., & Cayan, D. R. (2010). The utility of daily large-scale climate data in the assessment of climate change impacts on daily streamflow in California. Hydrology and Earth System Sciences, 14(6), 1125-1138.
# NOT RUN {options(
calibration.end=as.POSIXct('1972-12-31', tz='GMT')
)
analogues <- ClimDown::ca.netcdf.wrapper('./tiny_gcm.nc', './tiny_obs.nc')
# }# NOT RUN {# }