Uncertainty quantification based cloud parameterization sensitivity analysis in the NCAR community atmosphere model.

ABSTRACT: Using uncertainty quantification techniques, we carry out a sensitivity analysis of a large number (17) of parameters used in the NCAR CAM5 cloud parameterization schemes. The LLNL PSUADE software is used to identify the most sensitive parameters by performing sensitivity analysis. Using Morris One-At-a-Time (MOAT) method, we find that the simulations of global annual mean total precipitation, convective, large-scale precipitation, cloud fractions (total, low, mid, and high), shortwave cloud forcing, longwave cloud forcing, sensible heat flux, and latent heat flux are very sensitive to the threshold-relative-humidity-for-stratiform-low-clouds ([Formula: see text] and the auto-conversion-size-threshold-for-ice-to-snow [Formula: see text] The seasonal and regime specific dependence of some p

SUBMITTER: Pathak R 

PROVIDER: S-EPMC7567854 | biostudies-literature | 2020 Oct

REPOSITORIES: biostudies-literature