Bias correction for gridded GCM’s precipitation data
Bias correction is the process of adjusting projected raw GCM’s simulated data with respect to the reference period observed datasets. Linear Scaling and Quantile Mapping (empirical, theoretical, parametric, regression quantile-quantile, smoothing spline quantile mapping) bias correction methods for correcting gridded raw GCM’s data have been implemented in R scripts (See the GitHub repository). The input to the script is gridded raw GCM datasets. Output from the script is bias corrected gridded GCM’s variables. This R script can be executed with any ordinary computers. Please follow the read me file for detailed execution of the script.
Reference paper to cite:
Shanmugam, M., Lim, S., Hosan, M.L., Shrestha, S., Babel, M.S., Virdis, S.G.P., 2024. Lapse rate-adjusted bias correction for CMIP6 GCM precipitation data: An application to the Monsoon Asia Region. Environ Monit Assess 196, 49. https://doi.org/10.1007/s10661-023-12187-5