Austin Harris
NWP Assignment #2
December 10th 2015
Evaluating the Performance of Planetary Boundary Layer and Cloud
Microphysical Parameterization Schemes in Convection-Permitting
Ensemble Forecasts Using Synthetic GOES-13 Satellite Observations
Cintineo et al. in Monthly Weather Review
Background
Cloud microphysics and planetary boundary layer (PBL) parameterization
schemes have been shown to strongly affect the structure of simulated clouds, which
ultimately influences the ability of NWP models to handle the solar radiation budget and
atmospheric stability, and consequentially, the prediction of hazardous atmospheric
phenomenon like extra-tropical cyclones and thunderstorms. In particular, microphysics
schemes influence cloud structure by simulating a variety of hydrometeor species
involved in the complicated cloud dynamics and subsequent precipitation. Doublemoment microphysics schemes, which predict both the mass mixing ratio and total
number concentration for all species, have improved our ability to predict the cloud
structure and evolution, although there is considerable room for improvement. PBL
schemes, on the other hand, influence the prediction of clouds by parameterizing the
small-scale turbulence arising from the transfer of moisture, heat, and momentum
between the surface and the atmosphere.
Previous evaluations assessing the utility of such schemes have been achieved
through the comparisons of NWP model output to both real and model-derived satellite
operations. Although these studies have shown that PBL and microphysics schemes
substantially influence the cloud properties of maritime extra-tropical cyclones and
atmospheric rivers, the utility of such parameterizations has only been evaluated for a
small number of events. Moreover, the “best” schemes have yet to be identified. With
that being said, this study expands our assessment of both microphysics and PBL
schemes by comparing various parameterizations within the convection-permitting WRF
ensemble to synthetic infrared brightness temperature observations from satellites. This
paper is different from previous studies in that only double-moment schemes will be
used, several events are investigated during the 4-week spring experiment in 2012, and
the domain covers the entire continental United States as opposed to a smaller, regional
domain.
Methods
To investigate the impact of the microphysics schemes on the cloud simulations,
four microphysics parameterizations were employed while all other model components
and parameterizations were held the same. All schemes tested were double moment in
some fashion, however, the schemes differ in which particular species are double-
moment and how they treat various cloud processes. For example, the WRF doublemoment 6-class (WDM6) scheme is double moment for the warm rain processes only,
while the cloud condensation nuclei and the cloud and rainwater number concentrations
are predicted. Only the cloud ice and rainwater species are double moment in the
Thompson scheme (THOM), which also utilizes prognostic equations for cloud water,
cloud ice, snow, rain, and graupel mass mixing ratios. The Morrison scheme (MORR)
also predicts these same mass mixing ratios, but with number concentrations predicted
for all species excluding cloud water. Lastly, the Milbrandt-Yau scheme (M-Y) is double
moment for all types, and even separates graupel and hail.
Five ensemble members were used for the PBL comparisons, while all other
model components were held constant to isolate the influence of the PBL schemes. These
parameterizations can be categorized into local and non-local schemes, in which the
former calculates turbulent fluxes for each grid point in the vertical column using data
from adjacent levels, while the latter calculates fluxes based on variables throughout the
depth of the model. The local schemes used in this study are: 1) the MYJ scheme, which
includes prognostic equations for turbulent kinetic energy (TKE), 2) the quasi-normal
scale elimination (QNSE) scheme, which is similar, except that it determines the mixing
length differently for a stable PBL, 3) the Mellor-Yamada-Nakanishi-Niino scheme
(MYNN), which is also similar, except that this includes improvements to the closure
constants and mixing length scale. Meanwhile, the non-local schemes used in this study
include: 1) the YSU scheme, which permits nonlocal mixing with explicit entrainment
processes, 2) the asymmetric convective model version2 (ACM2), which includes a local
mixing component rather than a nonlocal transport in stable and neutral conditions in
order to balance computational expense against accurately capturing sub and super-scale
fluxes.
Each ensemble member was evaluated through the comparisons of real and
synthetic GOES-13 IR brightness temperatures, which have been previously shown to be
accurate within 1K. More specifically, the synthetic brightness temperatures were
computed on the WRF grid for two IR-bands, and were then remapped to the GOES-13
projections to directly compare the real and synthetic data. Point-to-point verification
metrics like the bias, root-mean-square error (RMSE), and mean absolute error (MAE)
we computed for the 6.7 and 10.7-µm bands, while the neighborhood-based verification
metric, fraction skill score (FSS), was used too.
Key Findings
The M-Y and MORR microphysics parameterization schemes were the most
accurate at forecasting the low-level clouds despite grossly underestimating the spatial
extent of these clouds. However, these schemes resulted in an over-forecast of upperlevel cloud extent and were the least skillful in terms of RMSE and MAE there, and it
was suggested that this could be the result of an over-production of ice. The simple
WDM6 scheme under-forecast cloud extent at all vertical levels, and although this led to
a worse FSS than the others, the RMSE and MAE were slightly better for the WDM6
than the M-Y and MORR schemes, which was also likely due to how the models handled
ice. With that being said, it was argued that the improved WDM6 scores relative to the
M-Y and MORR schemes point out the flaws in using one verification statistic only.
Overall, it was determined that the moderately complex THOM scheme was the most
accurate for the spring experiment.
There was a lack of low-level clouds for the PBL schemes, although the ACM2
performed the best. In particular, this scheme certainly performed the best during preconvective hours, and it had the highest FSS for the upper-level clouds. However, the
local mixing schemes, QNSE and MYJ, performed best during the convective hours,
despite over-forecasting cloud extent. The MYNN had the worst FSS with an underforecast of clouds everywhere except at the tropopause (where it performed best), while
the MYJ and QNSE contained too many overshooting tops, thus implying an overforecast of updraft strength. Overall though, the differences in the PBL schemes were not
as stark as with the microphysics schemes, and so it is not entirely clear which PBL
scheme is superior, although the ACM2, YSU, and MYNN seemed to perform better than
the MYJ and QNSE schemes.
Potential Refinement and/or Extensions
 An obvious extension to the work while maintaining the current experimental
design would be to replicate the study for a variety of synoptic setups, including
particularly impactful situations like a nor-easter or an MCS. Such a study should
further elucidate the most accurate PBL and microphysics schemes, as well as the
types of errors associated with them.
 While maintaining the same general experimental design, another extension of
this study would be to utilize rain gauge data and/or radar estimated precipitation
to compare against forecast precipitation amounts generated with each of the PBL
and microphysics schemes.
 Another easy extension of the study would to also evaluate the performances of
all combinations of the 9 parameterization schemes.