scholarly journals Evaluating the Performance of Planetary Boundary Layer and Cloud Microphysical Parameterization Schemes in Convection-Permitting Ensemble Forecasts Using Synthetic GOES-13 Satellite Observations

2014 ◽  
Vol 142 (1) ◽  
pp. 163-182 ◽  
Author(s):  
Rebecca Cintineo ◽  
Jason A. Otkin ◽  
Ming Xue ◽  
Fanyou Kong
Keyword(s):  
Boundary Layer ◽  
Planetary Boundary Layer ◽  
Cloud Cover ◽  
Model Performance ◽  
Ensemble Forecasts ◽  
Verification Method ◽  
Parameterization Schemes ◽  
Brightness Temperatures ◽  
Double Moment ◽  
Planetary Boundary Layer Parameterization

Abstract In this study, the ability of several cloud microphysical and planetary boundary layer parameterization schemes to accurately simulate cloud characteristics within 4-km grid-spacing ensemble forecasts over the contiguous United States was evaluated through comparison of synthetic Geostationary Operational Environmental Satellite (GOES) infrared brightness temperatures with observations. Four double-moment microphysics schemes and five planetary boundary layer (PBL) schemes were evaluated. Large differences were found in the simulated cloud cover, especially in the upper troposphere, when using different microphysics schemes. Overall, the results revealed that the Milbrandt–Yau and Morrison microphysics schemes tended to produce too much upper-level cloud cover, whereas the Thompson and the Weather Research and Forecasting Model (WRF) double-moment 6-class (WDM6) microphysics schemes did not contain enough high clouds. Smaller differences occurred in the cloud fields when using different PBL schemes, with the greatest spread in the ensemble statistics occurring during and after daily peak heating hours. Results varied somewhat depending upon the verification method employed, which indicates the importance of using a suite of verification tools when evaluating high-resolution model performance. Finally, large differences between the various microphysics and PBL schemes indicate that large uncertainties remain in how these schemes represent subgrid-scale processes.

Optimizing cloud cover prediction by the Ensemble for Stochastic Integration of Atmospheric Simulations (ESIAS)

2021 ◽  
Author(s):  
Yen-Sen Lu ◽  
Philipp Franke ◽  
Dorit Jerger
Keyword(s):  
Boundary Layer ◽  
Solar Radiation ◽  
Planetary Boundary Layer ◽  
Cloud Cover ◽  
Weather Forecasting ◽  
Extreme Weather ◽  
Atmospheric Modeling ◽  
The Other ◽  
Extreme Weather Events ◽  
Weather Events

<p>ESIAS is an atmospheric modeling system including the ensemble version of the Weather Forecasting and Research Model (WRF V3.7.1) and the ensemble version of the EURopean Air pollution Dispersion-Inverse Model (EURAD-IM), the latter uses the output of the WRF model to calculate, amongst others, the transportation of aerosols. <!-- Maybe you can make more clear that only the wrf ensemble is used in this presentation. -->To capture extreme weather events causing the uncertainty in the solar radiation and wind speed for the renewable energy industry, we employ ESIAS by using stochastic schemes, such as Stochastically Perturbed Parameterization Tendency (SPPT) and Stochastic Kinetic Energy Backscatter (SKEBS) schemes, to generate the random fields for ensembles of up to 4096 members.</p><p>     Our first goal is to produce 48 hourly weather predictions for the European domain with a 20 KM horizontal resolution to capture extreme weather events affecting wind, solar radiation, and cloud cover forecasts. We use the ensemble capability of ESIAS to optimize the physics configuration of WRF to have a more precise weather prediction. A total of 672 ensemble members are generated to study the effect of different microphysical schemes, cumulus schemes, and planetary boundary layer parameterization schemes. We examine our simulation outputs with 288 simulation hours in 2015 using model input from the Global Ensemble Forecast System (GEFS). Our results are validated by the cloud cover data from EUMETSAT CMSAF. Besides the precision of weather forecasting, we also determine the greatest spread by generating total 768 ensemble members: 16 stochastic members for each different configurations of physical parameterizations (48 combinations). The optimization of WRF will help for improving the air quality prediction<!-- 16 member out of 48 configurations? Is this a mistake? Otherwise maybe you can be a bit more precise --><!-- I agree with Philipp, this is most unclear. --><!-- Reply to Jerger, Dorit (01/07/2021, 17:15): "..." Well I tried my best for it. The “blue” and the “cross-out red” ones are the two versions, hopefully the “blue” one is better than the “cross-out red” one. --> by EURAD-IM, which will be demonstrated on a test case basis.</p><p>     Our results show that for the performed analysis the Community Atmosphere Model (CAM) 5.1, WRF Single-Moment 6-class scheme (WSM6), and the Goddard microphysics outstand the other 11 microphysics parameterizations, where the highest daily average matching rate is 64.2%. The Mellor–Yamada Nakanishi Niino (MYNN) 2 and MYNN3 schemes give better results compared to the other 8 planetary boundary layer schemes, and Grell 3D (Grell-3) works generally well with the above mentioned physical schemes. Overall, the combination of Goddard and MYNN3 produces the greatest spread comparing to the lowest spread (Morrison 2-moment & GFS) by 40%.</p>

Derivation of Turbulent Kinetic Energy from a First-Order Nonlocal Planetary Boundary Layer Parameterization

2013 ◽  
Vol 70 (6) ◽  
pp. 1795-1805 ◽  
Author(s):  
Hyeyum Hailey Shin ◽  
Song-You Hong ◽  
Yign Noh ◽  
Jimy Dudhia
Keyword(s):  
Boundary Layer ◽  
Kinetic Energy ◽  
Turbulent Kinetic Energy ◽  
Planetary Boundary Layer ◽  
Water Cycle ◽  
Convective Boundary ◽  
First Order ◽  
Eddy Simulation ◽  
Pbl Parameterization ◽  
Planetary Boundary Layer Parameterization

Abstract Turbulent kinetic energy (TKE) is derived from a first-order planetary boundary layer (PBL) parameterization for convective boundary layers: the nonlocal K-profile Yonsei University (YSU) PBL. A parameterization for the TKE equation is developed to calculate TKE based on meteorological profiles given by the YSU PBL model. For this purpose buoyancy- and shear-generation terms are formulated consistently with the YSU scheme—that is, the combination of local, nonlocal, and explicit entrainment fluxes. The vertical transport term is also formulated in a similar fashion. A length scale consistent with the K profile is suggested for parameterization of dissipation. Single-column model (SCM) simulations are conducted for a period in the second Global Energy and Water Cycle Experiment (GEWEX) Atmospheric Boundary Layer Study (GABLS2) intercomparison case. Results from the SCM simulations are compared with large-eddy simulation (LES) results. The daytime evolution of the vertical structure of TKE matches well with mixed-layer development. The TKE profile is shaped like a typical vertical velocity (w) variance, and its maximum is comparable to that from the LES. By varying the dissipation length from −23% to +13% the TKE maximum is changed from about −15% to +7%. After normalization, the change does not exceed the variability among previous studies. The location of TKE maximum is too low without the effects of the nonlocal TKE transport.

A Review of Planetary Boundary Layer Parameterization Schemes and Their Sensitivity in Simulating Southeastern U.S. Cold Season Severe Weather Environments

2015 ◽  
Vol 30 (3) ◽  
pp. 591-612 ◽  
Author(s):  
Ariel E. Cohen ◽  
Steven M. Cavallo ◽  
Michael C. Coniglio ◽  
Harold E. Brooks
Keyword(s):  
Boundary Layer ◽  
Planetary Boundary Layer ◽  
Turbulent Mixing ◽  
Convective Available Potential Energy ◽  
Lower Troposphere ◽  
Cold Season ◽  
Severe Weather ◽  
Parameterization Schemes ◽  
Lapse Rates ◽  
Local Schemes

Abstract The representation of turbulent mixing within the lower troposphere is needed to accurately portray the vertical thermodynamic and kinematic profiles of the atmosphere in mesoscale model forecasts. For mesoscale models, turbulence is mostly a subgrid-scale process, but its presence in the planetary boundary layer (PBL) can directly modulate a simulation’s depiction of mass fields relevant for forecast problems. The primary goal of this work is to review the various parameterization schemes that the Weather Research and Forecasting Model employs in its depiction of turbulent mixing (PBL schemes) in general, and is followed by an application to a severe weather environment. Each scheme represents mixing on a local and/or nonlocal basis. Local schemes only consider immediately adjacent vertical levels in the model, whereas nonlocal schemes can consider a deeper layer covering multiple levels in representing the effects of vertical mixing through the PBL. As an application, a pair of cold season severe weather events that occurred in the southeastern United States are examined. Such cases highlight the ambiguities of classically defined PBL schemes in a cold season severe weather environment, though characteristics of the PBL schemes are apparent in this case. Low-level lapse rates and storm-relative helicity are typically steeper and slightly smaller for nonlocal than local schemes, respectively. Nonlocal mixing is necessary to more accurately forecast the lower-tropospheric lapse rates within the warm sector of these events. While all schemes yield overestimations of mixed-layer convective available potential energy (MLCAPE), nonlocal schemes more strongly overestimate MLCAPE than do local schemes.

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