Emil M.
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Cloud processes in global climate modelsFunding: Internal LDRD, Argonne National Laboratory. Synopsis: Cloud processes in global climate models (GCMs) are highly parameterized and often tuned to obtain the Earth’s radiative balance and global mean temperature. As a result, clouds constitute the single-largest uncertainty in terms of radiative forcings and climate feedbacks. Improving the cloud processes and especially interactions with aerosols in high-resolution climate models is definitely a priority for the coming decade. NEWS:http://energy.gov/eere/articles/energy-department-announces-25-million-improve-wind-forecasting Online calibration resultsTest 2D-Guassian
Cloud convection ()
MAP output
Median output
Mean output
Configure & build PETSc with debug options (pgi on the Fusion machine):git clone git@bitbucket.org:petsc/petsc.git petsc-dev export
PETSC_DIR=%path to petsc% make PETSC_DIR=$PWD PETSC_ARCH=arch-linux2-c-debug all test <move to netcdf-fortran-xx download it, and read instructions> export FC=$PETSC_DIR/$PETSC_ARCH/bin/mpif90 |
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