Why Is Improvement of Earth System Models So Elusive? Challenges and Strategies From Dust Aerosol Modeling

Abstract:

Past decades have seen an accelerating increase in computing efficiency,
while climate models are representing a rapidly widening set of
physical processes. Yet simulations of some fundamental aspects of
climate like precipitation or aerosol forcing remain highly uncertain
and resistent to progress. Dust aerosol modeling of soil particles
lofted by wind erosion has seen a similar conflict between increasing
model sophistication and remaining uncertainty. Dust aerosols perturb
the energy and water cycles by scattering radiation and acting as ice
nuclei, while mediating atmospheric chemistry and marine
photosynthesis (and thus the carbon cycle). These effects take place
across scales from the dimensions of an ice crystal to the
planetary-scale circulation that disperses dust far downwind of its
parent soil. Representing this range leads to several modeling
challenges. Should we limit complexity in our model, which consumes
computer resources and inhibits interpretation? How do we decide if a
process involving dust is worthy of inclusion within our model? Can
we identify a minimal representation of a complex process that is
efficient yet retains the physics relevant to climate? Answering
these questions about the appropriate degree of representation is
guided by model evaluation, which presents several more challenges.
How do we proceed if the available observations do not directly
constrain our process of interest? (This could result from competing
processes that influence the observed variable and obscure the
signature of our process of interest.) Examples will be presented
from dust modeling, with lessons that might be more broadly
applicable. The end result will either be clinical depression or the
reassuring promise of continued gainful employment as the community
confronts these challenges.