Sensitivity of a Simulated Squall Line During Southern China Monsoon Rainfall Experiment to Parameterization of Microphysics

Abstract

A squall line on 22 May 2014 during the Southern China Monsoon Rainfall Experiment period is simulated with four bulk microphysical parameterizations (BMPs) using the Weather Research and Forecasting (WRF) model. Although most BMPs are able to capture the basic features of the squall line, the movement, morphology, and especially the length of the simulated squall lines differ significantly among BMPs. Morrison scheme tends to simulate a slower moving squall line with a weaker cold pool and better trailing stratiform cloud and precipitation due to the smaller snow fall speed and faster generation of snow particles than other schemes. Assuming hail or graupel in different schemes could result in different melting profiles of rimed‐ice particles, with hail melted substantially below the 0°C isotherm and contributing to the cold pool production significantly in WRF double‐moment six‐class microphysics scheme because of its use of larger fall speed for hail. Although ice‐phase particles simulated differ significantly among BMPs, it is rain evaporation that dominates the cold pool generation and maintenance of the squall line in this case. Stronger rain evaporation generally contributes to stronger cold pools and thus faster movement and longer simulated squall lines. Failure of the Stony Brook University‐YLin scheme in capturing the squall line was identified to be related to the turnoff of rain evaporation once environmental relative humidity is larger than 90%. With modifications of rain evaporation calculation and saturation adjustment method, the scheme is able to simulate this squall line reasonably well.

VDRAS and Polarimetric Radar Investigation of a Bow Echo Formation After a Squall Line Merged With a Preline Convective Cell

“…For instance, the changing microphysical cooling rates resulted in different strengths of cold pools (Adams-Selin et al, 2013), where stronger cold pools generally produced stronger RIJs (Weisman, 1992) as well as stronger mesovortices (Atkins and St. Laurent, 2009a). In addition, various microphysical schemes normally led to different convective organizations under the same dynamic regime in previous simulations (e.g., Lawson & Gallus, 2016;Qian et al, 2018). Finley et al (2001) conducted supercell simulations to find that the intensive precipitation due to convective merger led to a rising pressure behind the gust front, and more evaporative cooling caused a stronger cold pool during the bow echo evolution.…”

“…Moreover, microphysical processes could affect the structural evolution of a bow echo significantly (e.g., Atkins and St. Laurent, 2009a; Adams‐Selin et al, 2013; Lawson & Gallus, 2016; Qian et al, 2018). For instance, the changing microphysical cooling rates resulted in different strengths of cold pools (Adams‐Selin et al, 2013), where stronger cold pools generally produced stronger RIJs (Weisman, 1992) as well as stronger mesovortices (Atkins and St. Laurent, 2009a).…”

Possible roles of fall speed parameters of different graupel densities on microphysics and electrification in an idealized thunderstorm

“…Due to the lack of comprehensive observations and our limited understanding of the microphysical processes of ice‐phase particles, there are many uncertainties not only in the choice of microphysics schemes (Barthlott et al , ; Hazra et al , ) but also in the microphysical parameters used in each scheme (Johnson et al , ; White et al , ). Therefore, parametrizations in microphysical schemes are often tuned so that precipitation intensities and distributions in simulated storms can match observations (Lang et al , ; Qian et al , ).…”

“…Some conflicting results are obtained when using different microphysics schemes. Luo et al (), Bryan and Morrison (), and Qian et al () noted that a simulation with medium‐density graupel would produce unrealistically larger convective regions, while a high‐density simulation showed a much narrower convective line with higher reflectivity and a smaller stratiform region. Morrison and Milbrandt () and Weverberg et al () found that the faster the hail fall speed, the higher the downward precipitation flux, as a result of the higher melting rate.…”

Science and prediction of monsoon heavy rainfall

“…Positive impacts of assimilating the observational data from the wind profiler network, operational weather radar, lightning detector are demonstrated on predicting convection evolution over inland South China and northern South China Sea [8]. Rain evaporation represented by microphysics schemes is critical for simulating the formation, movement, and morphology of a linear-shaped MCS passing over the SCMREX field campaign [9]. An experimental convection-permitting ensemble prediction system based on the Global/Regional Assimilation and Prediction System is developed for quantitative precipitation forecast (QPF) over southern China.…”