Olson, Joseph B. and John M. Brown, National Oceanic
and Atmospheric Administration/ESRL/GSD/AMB
The
Mellor-Yamada-Nakanishi-Niino (MYNN) planetary boundary layer (PBL) scheme was
introduced into the Advanced Research version of the Weather Research and
Forecasting model (WRF-ARW) a few years ago as an alternative turbulent kinetic
energy (TKE)-based scheme. The unique features of this scheme include closure
constants tuned to match large eddy similations, a more elaborate mixing length
formulation, and an option to run at both closure levels 2.5 and 3.0. The MYNN
surface layer (SFC) scheme originated from an old version of the Yonsei
University (YSU) SFC scheme, with few modifications to customize the
performance with the MYNN PBL scheme. Since implementation, many shortcomings
have been noted, such as a warm-bias over desert/bare soil regions, production
of negative TKE, high 10-m wind speed bias, excessive polar fog in cool season
nocturnal conditions, and excessive low-level clouds over the ocean. This work
presents modifications made to the MYNN PBL and SFC scheme to alleviate these
problems.
Beginning with the
negative TKE problem, the method of Canuto et al. (2008) is implemented, which
results in an elimination of the critical Richardson number, allowing the
mixing of momentum to persist in stable conditions, similar to the QNSE or TEMF
PBL schemes. This modification fixes the negtive TKE problem but results in a
distinct behavioral change that necessitates successive effort to reduce an
over-diffusive nature in stable conditions. Changes to fundamental closure
constants and the mixing lengths return the mixing behavior to near previous
performance, while further effort is made to improve other biases noted above.
Furthermore, modifications to the SFC scheme reduces the high 2-m temperature
bias over the southwest U.S. as well as the high-bias in low-level clouds over
the oceans. With these improvements, the MYNN PBL/SFC schemes become a
realistic candidate for implementation into the Rapid Refresh and
High-Resolution Rapid Refresh forecast systems.