2005
DOI: 10.1175/waf888.1
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The Impact of Different WRF Model Physical Parameterizations and Their Interactions on Warm Season MCS Rainfall

Abstract: In recent years, a mixed-physics ensemble approach has been investigated as a method to better predict mesoscale convective system (MCS) rainfall. For both mixed-physics ensemble design and interpretation, knowledge of the general impact of various physical schemes and their interactions on warm season MCS rainfall forecasts would be useful. Adopting the newly emerging Weather Research and Forecasting (WRF) model for this purpose would further emphasize such benefits. To pursue this goal, a matrix of 18 WRF mo… Show more

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Cited by 235 publications
(199 citation statements)
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“…The Kain-Fritsch (K-F) scheme (Kain 2004) produces the largest deviation (3.8 times larger than the observations), while the ZhangMcFarlane scheme (Zhang and McFarlane 1995) produces the deviation value closest to the observations. Overall, the sensitivity experiments reflect the importance of the cumulus schemes in rainfall simulation over the SE US, which has also been emphasized in previous studies (e.g., Jankov et al 2005;Bukovsky and ) of SE US summer precipitation climatology as calculated from discrete cosine transform (DCT); the color scale has been log-scaled; b power spectrum versus spatial wavelength: the x-axis in the bottom (top) is the number of wave per kilometer (wavelength). The red dashed line denotes wavelength = 60 km, where power spectrum decreases to 1 % of that with the largest wavelength…”
Section: Influence Of Physical Parameterization On Simulation Skillssupporting
confidence: 68%
“…The Kain-Fritsch (K-F) scheme (Kain 2004) produces the largest deviation (3.8 times larger than the observations), while the ZhangMcFarlane scheme (Zhang and McFarlane 1995) produces the deviation value closest to the observations. Overall, the sensitivity experiments reflect the importance of the cumulus schemes in rainfall simulation over the SE US, which has also been emphasized in previous studies (e.g., Jankov et al 2005;Bukovsky and ) of SE US summer precipitation climatology as calculated from discrete cosine transform (DCT); the color scale has been log-scaled; b power spectrum versus spatial wavelength: the x-axis in the bottom (top) is the number of wave per kilometer (wavelength). The red dashed line denotes wavelength = 60 km, where power spectrum decreases to 1 % of that with the largest wavelength…”
Section: Influence Of Physical Parameterization On Simulation Skillssupporting
confidence: 68%
“…In published literature, one can find an extensive list of different parameterization schemes depicting the same physical process, and several studies were conducted aiming to investigate the model performance on the simulation of meteorological variables under different physical parameterization schemes (Awan et al, 2011;Chigullapalli and Mölders, 2008;Gallus and Bresch, 2006;Gilliam and Pleim, 2010;Gilliam et al, 2007;Hutchinson et al, 2005;Jankov et al, 2005Jankov et al, , 2007Krieger et al, 2009). Challa et al (2009) performed a simulation study of mesoscale coastal circulations in Mississippi Gulf coast with the WRF model, concluding that the YSU scheme shows improvement over MYJ scheme in the simulation of internal boundary layer characteristics and the overall performance of predicted mean variables.…”
Section: 42mentioning
confidence: 99%
“…The sensitivity to different parameterization schemes was not specifically investigated in this study, while this is known to be important (Gallus and Bresch, 2006;Jankov et al, 2005;Rajeevan et al, 2010;Ruiz et al, 2010;Zeng et al, 2012;ter Maat et al, 2013). The chosen YSU PBL scheme is a first-order nonlocal scheme that is widely used under convective conditions (Hu et al, 2010).…”
Section: Discussionmentioning
confidence: 99%