Improvements of WRF Simulation Skills of Southeast United States Summer Rainfall: Focus on Physical Parameterization and Horizontal Resolution Laifang.

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Presentation transcript:

Improvements of WRF Simulation Skills of Southeast United States Summer Rainfall: Focus on Physical Parameterization and Horizontal Resolution Laifang Li 1, Wenhong Li 1, and Jiming Jin 2,* 1. Earth and Ocean Science, Nicholas School of the Environment, Duke University, Durham, NC, Department of Watershed Sciences and Department of Plants, Soils and Climate, Utah State University, Logan, UT, 84322

Motivation Accurate regional climate simulation is important for the Southeast US (SE US)  SE US is one of the fastest developing regions in the nation, and the warm season precipitation becomes increasingly important.  Accurate regional climate simulations for the SE US are vital to predicting the seasonal rainfall and creating effective climate policy SE US Drought

Motivation However, simulation skills for SE US summer rainfall are low. Percentage of WRF simulation JJA rainfall bias compared to observation (Mearns et al. 2012, BAMS: ) Q: What hampered WRF simulation skill of SE US summer rainfall? How to make improvement? NARCCAP: North American Regional Climate Change Assessment Program

Objectives Improve WRF skills in simulating SE US summer rainfall Lateral Boundary Condition (LBC) o North Atlantic Subtropical High (NASH) circulation dynamically contributes to the WRF simulation skill in SE US summer precipitation (Poster Presentation P30) Physical Parameterization Schemes o How sensitive is the simulation to physics schemes? o Why some schemes outperform some others? Horizontal Resolutions o Can convection resolving models improve the simulation skills? What are the physical mechanisms?

Influence of Physical Parameterization: Sensitivity Experiment WRF ARW version 3.4 Horizontal Resolution: 15-km LBC : CFSR (6-hr) Land Surface Model: Noah Physics Schemes(Control Exp.): Micro Physics: Thomposon Cumulus: BMJ Shortwave: Dudhia Longwave: RRTM PBL: YSU SST update : True Experiment Case: Aug. 01-Aug.15, 2009 Initialize on Jul.27, 2009; simulations for first 5 days were discarded as spin-up Experiment domain: SE US

Sensitivity to Physical Parameterizations SE US summer precipitation: Insensitive to mp_physics Sensitive to cu_physics Less Sensitive to bl_pbl_physics mp_physics bl_pbl_physics cu_physics

Uncertainty: Caused by cu_physics a) K-F b) Grell c) Grell-3Dd) BMJ e) Zhang-McFarlane Production Run

Influence of Physical Parameterization: 10-yr Production Run Horizontal Resolution: 15-km LBC : CFSR (6-hr) Land Surface Model: Noah Physics Schemes(Control Exp.): MicroPhysics: Lin Cumulus: BMJ/Zhang-McFarlane Shortwave: Dudhia Longwave: RRTM PBL: MYNN3 SST update : True Experiment Period: summer Initialize on May.01; simulations for the first month were discarded as spin-up. Experiment domain: SE US

Pattern Cor.RMSEbias Zhang BMJ WRF 10-yr Production Run ( ) Q: Why Zhang- McFarlane scheme performs better? Observation BMJ Zhang WRF Bias Interannual Variation The Zhang-McFarlane scheme well simulates the observed SE US summer rainfall.

Observation BMJ Zhang-McFarlane Observation BMJ Zhang-McFarlane Importance of Rainfall Triggering Observation BMJ Zhang-McFarlane Entropy CAPE Summer Precipitation Rate Rainy Day Number Storm Intensity

CAPE-Rainfall Relationship in the SE US Over the SE US, CAPE and rainfall has a positive relationship. This positive “CAPE- rainfall” relationship is implicit in Zhang- McFarlane scheme. observation Zhang-McFarlane CAPE: Convective Available Potential Energy

WRF simulation skills of SE US summer rainfall is impacted by physical parameterization schemes: o WRF simulation is insensitive to mp_physics o WRF simulation is very sensitive to cu_physics o WRF simulation is less sensitive to pbl_physics Among the 5 tested cu_physics schemes, Zhang-McFarlane scheme outperforms the other for SE US summer rainfall o Rainfall triggering is more realistic in Zhang-McFarlane scheme o The Zhang-McFarlane scheme captures the positive “CAPE- precipitation” relationship over the SE US, and thus results in higher skills Summary 1: Physical Parameterization

Influence of Horizontal Resolution: 3-km Convection Resolving Simulation Horizontal Resolution: 3-km LBC : CFSR (6-hr) Land Surface Model: Noah Physics Schemes(Control Exp.): MicroPhysics: Lin Cumulus: No Shortwave: Dudhia Longwave: RRTM PBL: MYNN3 SST update : True Experiment Case: Aug. 01-Aug.15, 2009 Initialize on Jul.27, 2009; first 5 days discarded for spin-up Experiment domain: SE US

Pattern Cor.RMSE 3km no cu_physics km Zhang-McFarlane Cloud Resolving Simulation: No Improvement observation 15 km Zhang-McFarlane 3 km no cu_physics  The 3-km simulation does not show improved skills compared with 15-km Zhang-McFarlane simulation.

Conclusions  WRF simulation of SE US summer rainfall is highly sensitive to the choice of cumulus schemes, in which the modeling of rainfall triggering processes is a key.  Due to the implicit positive “CAPE-rainfall” relationship, the Zhang-McFarlane scheme reasonably simulates SE US rainfall triggering processes and results in a higher simulation skill.  Compared with the 15-km Zhang-McFarlane simulation, the 3-km convection resolving simulation does not show obvious advantages. In conclusion, our study suggests that selecting an optimal cumulus scheme is more effective to improve WRF simulation of SE US summer rainfall than merely increasing horizontal resolutions.

Thank You! Q&A