TY - JOUR
T1 - Cloud-Resolving Model Intercomparison of an MC3E Squall Line Case
T2 - Part II. Stratiform Precipitation Properties
AU - Han, Bin
AU - Fan, Jiwen
AU - Varble, Adam
AU - Morrison, Hugh
AU - Williams, Christopher R.
AU - Chen, Baojun
AU - Dong, Xiquan
AU - Giangrande, Scott E.
AU - Khain, Alexander
AU - Mansell, Edward
AU - Milbrandt, Jason A.
AU - Shpund, Jacob
AU - Thompson, Gregory
N1 - Funding Information:
This study was supported by the U.S. Department of Energy (DOE) Atmospheric System Research (ASR) Program and the Climate Model Development and Validation (CMDV) program. The Pacific Northwest National Laboratory (PNNL) is operated for the DOE by Battelle Memorial Institute under contract DE-AC06-76RLO1830. This research used PNNL Institutional Computing resources and also resources at the National Energy Research Scientific Computing Center, which is supported by the Office of Science of the U.S. DOE under contract DE-AC02-05CH1123. Bin Han and Dr. Chen were supported by the National Basic Research Program of China (2013CB430105) and the National Natural Science Foundation of China (41575130 and 41775132). Dr. Varble was supported by U.S. DOE ASR grant DE-SC0008678. Dr. Morrison was supported by U.S. DOE ASR grant DE-SC0008648. Drs. Morrison and Varble were also supported by U.S. DOE ASR grant DE-SC0016476. Dr. Dong was supported by DOE CMDV project at University of Arizona with award number DE-SC0017015. Dr. Giangrande is an employee of Brookhaven Science Associates, LLC, under contract DE-AC02-98CH10886 with the U.S. DOE. Prof. Alexander Khain and Jacob Shpund are supported by grant DE-SC008811 and the Israel Science Foundation grant 2027/17.The National Center for Atmospheric Research is sponsored by the U.S. National Science Foundation. The simulation data are available at http://portal.nersc.gov/project/m2689/evaluation/. We also acknowledge the Atmospheric Radiation Measurement (ARM) Climate Research Facility, a user facility of the U.S. DOE, as well as the MC3E team for the field data. DOE ARM data sets used in this study can be obtained from the ARM Archive at http://www.arm.gov and ARM External Data Center at https://www.arm.gov/xdc/.
Publisher Copyright:
©2019. The Authors.
PY - 2019/1/27
Y1 - 2019/1/27
N2 - In this second part of a cloud microphysics scheme intercomparison study, we focus on biases and variabilities of stratiform precipitation properties for a midlatitude squall line event simulated with a cloud-resolving model implemented with eight cloud microphysics schemes. Most of the microphysics schemes underestimate total stratiform precipitation, mainly due to underestimation of stratiform precipitation area. All schemes underestimate the frequency of moderate stratiform rain rates (2–6 mm/hr), which may result from low-biased ice number and mass concentrations for 0.2–2-mm diameter particles in the stratiform ice region. Most simulations overestimate ice water content (IWC) at altitudes above 7 km for temperatures colder than −20 °C but produce a decrease of IWC approaching the melting level, which is opposite to the trend shown by in situ observations. This leads to general underestimations of stratiform IWC below 5-km altitude and rainwater content above 1-km altitude for a given rain rate. Stratiform precipitation area positively correlates with the convective condensate detrainment flux but is modulated by hydrometeor type, size, and fall speed. Stratiform precipitation area also changes by up to 17%–25% through alterations of the lateral boundary condition forcing frequency. Stratiform precipitation, rain rate, and area across the simulations vary by a factor of 1.5. This large variability is primarily a result of variability in the stratiform downward ice mass flux, which is highly correlated with convective condensate horizontal detrainment strength. The variability of simulated local microphysical processes in the stratiform region plays a secondary role in explaining variability in simulated stratiform rainfall properties.
AB - In this second part of a cloud microphysics scheme intercomparison study, we focus on biases and variabilities of stratiform precipitation properties for a midlatitude squall line event simulated with a cloud-resolving model implemented with eight cloud microphysics schemes. Most of the microphysics schemes underestimate total stratiform precipitation, mainly due to underestimation of stratiform precipitation area. All schemes underestimate the frequency of moderate stratiform rain rates (2–6 mm/hr), which may result from low-biased ice number and mass concentrations for 0.2–2-mm diameter particles in the stratiform ice region. Most simulations overestimate ice water content (IWC) at altitudes above 7 km for temperatures colder than −20 °C but produce a decrease of IWC approaching the melting level, which is opposite to the trend shown by in situ observations. This leads to general underestimations of stratiform IWC below 5-km altitude and rainwater content above 1-km altitude for a given rain rate. Stratiform precipitation area positively correlates with the convective condensate detrainment flux but is modulated by hydrometeor type, size, and fall speed. Stratiform precipitation area also changes by up to 17%–25% through alterations of the lateral boundary condition forcing frequency. Stratiform precipitation, rain rate, and area across the simulations vary by a factor of 1.5. This large variability is primarily a result of variability in the stratiform downward ice mass flux, which is highly correlated with convective condensate horizontal detrainment strength. The variability of simulated local microphysical processes in the stratiform region plays a secondary role in explaining variability in simulated stratiform rainfall properties.
KW - microphysics parameterization
KW - model intercomparison
KW - squall line
KW - stratiform precipitation
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U2 - 10.1029/2018JD029596
DO - 10.1029/2018JD029596
M3 - Article
AN - SCOPUS:85060791960
SN - 2169-897X
VL - 124
SP - 1090
EP - 1117
JO - Journal of Geophysical Research Atmospheres
JF - Journal of Geophysical Research Atmospheres
IS - 2
ER -