Earth’s climate system involves multiple physical processes acting
over a wide range of scales, and much of the physics of processes that
influence climate and climate change occurs on scales smaller than
typical global climate model (GCM) grid sizes. Differences in
representation of the fast physics -- mainly cloud and precipitation
processes -- are largely responsible for the spread in climate
sensitivity and aerosol indirect effects predicted by current climate
models. Improving parameterizations of these fast processes is thus
essential to reducing uncertainty in climate sensitivity and to
increasing confidence in the capability of projecting future climate.
Despite tremendous effort over the past decades progress has been
frustratingly slow. The BNL-led multi-institutional Fast-physics System
Testbed and Research, or FASTER
project, aims to enhance and accelerate evaluation and improvement
of fast physics in GCMs by integrating a spectrum of expertise ranging
from observations to theoretical development to modeling, and by
capitalizing on the high resolution data collected by the DOE ARM
Climate Research Facility. Supported by the DOE
Climate Earth System (ESM) Modeling program, the FASTER project
consists of six objectives.
- Construction of a Fast-Physics Testbed to
rapidly evaluate fast physics in GCMs by comparing model
results against continuous long-term cloud observations
made by the ARM Climate Research Facility.
- Execution of a suite of CRM simulations for
selected periods/cases to augment the Fast-Physics
Testbed. We will run WRFs with different
parameterizations as CRMs, CRMs with bin-microphysics,
and multi-scale modeling framework.
- Continuous evaluation of model performance to
identify and determine model errors by comparing the NWP
and SCM results against continuous ARM observations, and
to each other. The long-time data record at the ARM
sites (e.g., SGP) permits evaluation of various
statistical properties (e.g., PDFs) and recurring cloud
- Examination and improvement of
parameterizations of key cloud
processes/properties (e.g., convection, microphysics and
aerosol-cloud interactions), thus narrowing the range of
treatments of fast processes that exert strong
influences on model sensitivity so as to better
constrain climate sensitivity.
- Assessment and development of metrics of
model performance. Different metrics will be applied and
tested in the evaluation, and new metrics will be
explored. Special care will be taken to address the
issue of scale-mismatch between observations and models.
- Incorporation of newly acquired knowledge
on parameterizations into the full participating GCMs to
evaluate the impact of the refined parameterizations on
GCM and ascertain the improvement in the representation
of fast physics in the GCMs.