Sensitivity of 24-h Forecast Dryline Position and Structure to Boundary Layer Parameterizations in Convection-Allowing WRF Model Simulations

Abstract

Recent NOAA Hazardous Weather Testbed Spring Forecasting Experiments have emphasized the sensitivity of forecast sensible weather fields to how boundary layer processes are represented in the Weather Research and Forecasting (WRF) Model. Thus, since 2010, the Center for Analysis and Prediction of Storms has configured at least three members of their WRF-based Storm-Scale Ensemble Forecast (SSEF) system specifically for examination of sensitivities to parameterizations of turbulent mixing, including the Mellor-Yamada-Janji c (MYJ); quasi-normal scale elimination (QNSE); Asymmetrical Convective Model, version 2 (ACM2); Yonsei University (YSU); and Mellor-Yamada-Nakanishi-Niino (MYNN) schemes (hereafter PBL members). In postexperiment analyses, significant differences in forecast boundary layer structure and evolution have been observed, and for preconvective environments MYNN was found to have a superior depiction of temperature and moisture profiles. This study evaluates the 24-h forecast dryline positions in the SSEF system PBL members during the period April-June 2010-12 and documents sensitivities of the vertical distribution of thermodynamic and kinematic variables in near-dryline environments. Main results include the following. Despite having superior temperature and moisture profiles, as indicated by a previous study, MYNN was one of the worst-performing PBL members, exhibiting large eastward errors in forecast dryline position. During April-June 2010-11, a dry bias in the North American Mesoscale Forecast System (NAM) initial conditions largely contributed to eastward dryline errors in all PBL members. An upgrade to the NAM and assimilation system in October 2011 apparently fixed the dry bias, reducing eastward errors. Large sensitivities of CAPE and low-level shear to the PBL schemes were found, which were largest between 1.08 and 3.08 to the east of drylines. Finally, modifications to YSU to decrease vertical mixing and mitigate its warm and dry bias greatly reduced eastward dryline errors.

Using Near-Ground Storm Relative Helicity in Supercell Tornado Forecasting

“…The primary advantage of the RUC/RAP data is their superior spatial and temporal availability. However, model representation of forecast parameters can depend significantly on the assimilation technique and the physical parameterization of surface fluxes within the PBL (e.g., Coniglio et al 2013;Clark et al 2015;Cohen et al 2015). Thus, it is important to validate these models given the wide use of objective analysis systems (such as SFCOA) to diagnose the mesoscale environment (Coniglio 2012).…”

Toward reduced transport errors in a high resolution urban CO2 inversion system

“…WRF has been used worldwide for both research and operational applications (Skamarock et al 2008). Its ability to simulate atmospheric processes relevant to atmospheric transport and dispersion has been tested widely (Cintineo et al 2014, Clark et al 2015, Coniglio et al 2013, Hariprasad et al 2014, Rogers et al 2013, Lauvaux et al 2013, Karion et al 2015. In addition to its advanced numerical scheme and continuously upgraded array of model physics parameterizations, WRF has a four dimensional data assimilation (FDDA) capability implemented by Penn State University (Deng et al 2009) that allows meteorological observations to be continuously assimilated, allowing WRF to produce dynamic analyses at user-desired resolution.…”

“…For PBL turbulent processes, the turbulent kinetic energy (TKE)-predicting Mellor-Yamada Nakanishi Niino (MYNN) Level 2.5 turbulent closure scheme (Nakanishi and Niino 2006) is used, along with the MYNN surface layer scheme to preserve consistency. The decision of selecting the MYNN PBL scheme is based on our experiences and previous studies where MYNN appeared to produce the most accurate PBL temperature and moisture profiles (Cintineo et al 2014, Clark et al 2015 as well as the most accurate PBL depth (Coniglio et al 2013, Hariprasad et al 2014 in simulations of the PBL over land, all of which are highly important to simulating transport and dispersion of surface emissions. For land surface processes, the Noah LSM Dudhia 2001, Tewari et al 2004) is used.…”

Influence of a Great Plains Urban Environment on a Simulated Supercell

“…All three domains employ the same parameterization options: Goddard short-and longwave radiation schemes (Chou and Suarez 1999;Chou et al 2001;Matsui et al 2007), a modified version of the Noah land surface model (LSM; Chen and Dudhia 2001;Ek et al 2003;RS17), the Yonsei University (YSU) PBL scheme (Noh et al 2003) and corresponding MM5 Monin-Obukhov surface layer scheme (Monin and Obukhov 1954;Paulson 1970;Dyer and Hicks 1970;Webb 1970), and the double-moment NSSL microphysics scheme (Mansell et al 2010), which uses six hydrometeor classes and predicts graupel density. The YSU scheme is selected, as it yields PBL properties and depths that agree well with observations and because it has been shown to perform well in plains severe weather environments (Coniglio et al 2013;Clark et al 2015). An urban canopy model (UCM) is not used to represent urban areas MAY 2018 because RS17 show that the single-layer UCM (SLUCM; Kusaka et al 2001;Kusaka and Kimura 2004)-the only explicit UCM available in the WRF that is compatible with the YSU PBL scheme-is not appropriate for use in plains cities, particularly because of its poor prediction of urban wind speeds.…”