Dependencies of Simulated Convective Cell and System Growth Biases on
Atmospheric Instability and Model Resolution
Abstract
This study evaluates convective cell properties and their relationships
with convective and stratiform rainfall within a season-long
convection-permitting simulation over central Argentina using
measurements from the RELAMPAGO-CACTI field campaign. While the
simulation reproduces the total observed rainfall, it underestimates
stratiform rainfall by 46% and overestimates convective rainfall by
43%. As Convective Available Potential Energy (CAPE) increases, the
overestimation of convective rainfall decreases, but the underestimation
of stratiform rainfall increases such that the high bias in the
contribution of convective rainfall to total rainfall remains
approximately constant at 26% across all CAPE conditions. Overestimated
convective rainfall arises from the simulation generating 2.6 times more
convective cells than observed despite similar observed and simulated
cell growth processes, with relatively wide cells contributing most to
excessive convective rainfall. Relatively shallow cells, typically
reaching heights of 4–7 km, contribute most to the cell number bias.
This bias increases as CAPE decreases, potentially because cells and
their updrafts become narrower and more under-resolved as CAPE
decreases. The gross overproduction of shallow cells leads to overly
efficient precipitation and inadequate detrainment of ice aloft, thereby
diminishing the formation of robust stratiform rainfall regions.
Decreasing the model’s horizontal grid spacing from 3 to 1 or 0.333 km
for representative low and high CAPE cases results in minimal change to
the cell number and depth biases, while the stratiform and convective
rainfall biases also fail to improve. This suggests that improving
prediction of deep convective system growth depends on factors beyond
solely increasing model resolution.