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Title: Parametric Sensitivity Analysis of Precipitation at Global and Local Scales in the Community Atmosphere Model CAM5

We investigate the sensitivity of precipitation characteristics (mean, extreme and diurnal cycle) to a set of uncertain parameters that influence the qualitative and quantitative behavior of the cloud and aerosol processes in the Community Atmosphere Model (CAM5). We adopt both the Latin hypercube and quasi-Monte Carlo sampling approaches to effectively explore the high-dimensional parameter space and then conduct two large sets of simulations. One set consists of 1100 simulations (cloud ensemble) perturbing 22 parameters related to cloud physics and convection, and the other set consists of 256 simulations (aerosol ensemble) focusing on 16 parameters related to aerosols and cloud microphysics. Results show that for the 22 parameters perturbed in the cloud ensemble, the six having the greatest influences on the global mean precipitation are identified, three of which (related to the deep convection scheme) are the primary contributors to the total variance of the phase and amplitude of the precipitation diurnal cycle over land. The extreme precipitation characteristics are sensitive to a fewer number of parameters. The precipitation does not always respond monotonically to parameter change. The influence of individual parameters does not depend on the sampling approaches or concomitant parameters selected. Generally the GLM is able to explain moremore » of the parametric sensitivity of global precipitation than local or regional features. The total explained variance for precipitation is primarily due to contributions from the individual parameters (75-90% in total). The total variance shows a significant seasonal variability in the mid-latitude continental regions, but very small in tropical continental regions.« less
 [1] ;  [2] ;  [1] ;  [3] ;  [3] ;  [3] ;  [4] ;  [1] ;  [5] ;  [3] ;  [1] ;  [6] ;  [1]
  1. Pacific Northwest National Lab. (PNNL), Richland, WA (United States)
  2. Pacific Northwest National Lab. (PNNL), Richland, WA (United States); Lanzhou Univ. (China)
  3. Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States)
  4. National Center for Atmospheric Research, Boulder, CO (United States)
  5. Sandia National Lab. (SNL-NM), Albuquerque, NM (United States)
  6. Nanjing Univ. (China); Collaborative Innovation Center of Climate Change (China)
Publication Date:
Report Number(s):
Journal ID: ISSN 1942-2466; KP1703020
Grant/Contract Number:
AC05-76RL01830; AC04-94AL85000; AC52-07NA27344
Published Article
Journal Name:
Journal of Advances in Modeling Earth Systems
Additional Journal Information:
Journal Volume: 7; Journal Issue: 2; Journal ID: ISSN 1942-2466
American Geophysical Union (AGU)
Research Org:
Pacific Northwest National Lab. (PNNL), Richland, WA (United States); Sandia National Laboratories (SNL), Albuquerque, NM, and Livermore, CA (United States)
Sponsoring Org:
USDOE Office of Science (SC)
Country of Publication:
United States
54 ENVIRONMENTAL SCIENCES; precipitation; CAM5; parameter space; cloud physics
OSTI Identifier:
Alternate Identifier(s):
OSTI ID: 1214066; OSTI ID: 1214703; OSTI ID: 1295965