A Vertically Nested Regional Numerical Weather Prediction Model with Second-Order Closure Physics

Burk, Stephen D.; Thompson, W. T.

doi:10.1175/1520-0493(1989)117<2305:avnrnw>2.0.co;2

Cited by 119 publications

(63 citation statements)

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“…The first configuration is the Kain-Fritsch (KF) convection scheme (Kain and Fritsch, 1993;Kain, 2004) with the Blackadar boundary layer scheme (Blackadar, 1976(Blackadar, , 1979Zhang and Anthes, 1982;Oncley and Dudhia, 1995). The second configuration is the KF convective scheme coupled with the Burk-Thompson boundary layer scheme (Burk and Thompson, 1989). By doing so, one can compare a scheme that calculates the flux as a function of the exchange coefficients and the adjacent levels (BT is a local scheme) with one that allows mixing between non-neighbouring layers (non-local).…”

Section: Research Model and Selected Parameterizationsmentioning

confidence: 99%

The role of atmospheric boundary layer-surface interactions on the development of coastal fronts

et al. 2007

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Abstract. Frictional convergence and thermal difference between land and sea surface are the two surface conditions that govern the intensity and evolution of a coastal front. By means of the mesoscale model MM5, we investigate the influence of these two processes on wind patterns, temperature and precipitation amounts, associated with a coastal front, observed on the west coast of The Netherlands in the night between 12 and 13 August 2004. The mesoscale model MM5 is further compared with available observations and the results of two operational models (ECMWF and HIRLAM). HIRLAM is not capable to reproduce the coastal front, whereas ECMWF and MM5 both calculate precipitation for the coastal region. The precipitation pattern, calculated by MM5, agrees satisfactorily with the accumulated radar image. The failure of HIRLAM is mainly due to a different stream pattern at the surface and consequently, a different behaviour of the frictional convergence at the coastline.The sensitivity analysis of frictional convergence is carried out with the MM5 model, by varying land surface roughness length (z 0 ). For the sensitivity analysis of thermal difference between sea and land surface, we changed the sea surface temperature (SST). Increasing surface roughness implies stronger convergence near the surface and consequently stronger upward motions and intensification of the development of the coastal front. Setting land surface roughness equal to the sea surface roughness means an elimination of frictional convergence and results in a diminishing coastal front structure of the precipitation pattern. The simulation with a high SST produces much precipitation above the sea, but less precipitation in the coastal area above land. A small increment of the SST results in larger precipitation amounts above the sea; above land increments are calculated for areas near the coast. A decrease of the SST shifts the precipitation maxima inland, although the precipitation amounts diminish.Correspondence to: J. Vilà-Guerau de Arellano (jordi.vila@wur.nl) In the situation under study, frictional convergence is the key process that enhances the coastal front intensity. A thermal difference between land and sea equal to zero still yields the development of the coastal front. A lower SST than land surface temperature generates a reversed coastal front.This study emphasizes the importance of accurate prescription of surface conditions as input of the numerical weather prediction model to improve coastal front predictability.

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Section: Research Model and Selected Parameterizationsmentioning

confidence: 99%

The role of atmospheric boundary layer-surface interactions on the development of coastal fronts

et al. 2007

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“…The five cloud microphysics schemes chosen for evaluation in Set B are the Warm Rain scheme (Kessler 1969), the Simple Ice scheme (Dudhia 1989), the Mixed Phase scheme (Resinser et al 1998), the Goddard Graupel scheme (Tao and Simpson 1993), and the Schultz scheme (Schultz 1995). The five PBL schemes tested in Set C are the Blackadar scheme (Blackadar 1979), the Burk-Thompson scheme (Burk and Thompson 1989), the Eta MellorYamada scheme (Mellor and Yamada 1982), the Medium-Range Forecast model (MRF) PBL scheme (Hong and Pan 1996), and the Pleim-Xiu scheme (Xiu and Pleim 2000). In each set of experiments, all model setting and physics parameters remain the same, except for the testing physical parameterization scheme.…”

Section: Model and Numerical Experimentsmentioning

confidence: 99%

“…Significant differences were found, with minimum central pressures varying by up to 16 hPa and maximum winds by 15 m s 1 − , and simulated horizontal precipitation distribution and TC intensity varied substantially between different PBL schemes. In particular, the Burk and Thompson (1989) and bulk aerodynamic schemes produced the strongest TC, while the Medium-Range Forecast (MRF) model PBL scheme (Hong and Pan 1996) produced the weakest storm.…”

Section: Introductionmentioning

confidence: 99%

A Modeling Study of Typhoon Toraji (2001): Physical Parameterization Sensitivity and Topographic Effect

Yang¹,

Ching²

2005

Terr. Atmos. Ocean. Sci.

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“…This study considers the following parameterizations: Blackadar (BLK), described by Zhang and Anthes (1982), BurkThompson (BT;Burk and Thompson, 1989), ETA (Mellor and Yamada (1974);Janjic (1994) and Hong-Pan (Medium Range Forecast -MRF); Hong and Pan, 1996) PBL schemes available in the MM5 model, in agreement with Table 1. A high-resolution, one-dimensional, moist PBL model is developed following Blackadar (1976) and verified using the 10 April 1979 SESAME data set (Zhang and Anthes, 1982). The model consists of two modules to predict the time-dependent behavior of the PBL under various surface characteristics.…”

Section: Description Of the Modified Mm5 Modelmentioning

confidence: 99%

“…The B-T scheme available in MM5 is based on its initial implementation in NORAPS (Burk and Thompson, 1989). The PBL turbulence parameterization scheme with local second order closure is based on level 3 of Mellor and Yamada (1974).…”

Section: Description Of the Modified Mm5 Modelmentioning

confidence: 99%

The Sensitivity of Wind Forecasts with a Mesoscale Meteorological Model at the Centro de Lançamento de Alcântara

Reuter¹,

Fisch²,

Corrêa

2015

J.Aerosp. Technol. Manag.

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The sensitivity of the planetary boundary layer (PBL) parameterizations is investigated using the hybrid Fifth Generation Penn State University/National Center for Atmospheric Research (NCAR) Mesoscale Model (MM5) and its results were compared with observations from two field campaigns held during the dry and wet seasons at the Centro de Lançamento de Alcântara (CLA). The comparisons were made using the integrated zonal and meridional components of observed and forecasted winds. Initially, three boundary layer parameterizations, in addition to the current parameterization, were selected for evaluation: Blackadar (BLK), Medium Range Forecast (MRF), Janjic (ETA) and Burk-Thompson (BT). The MRF and BLK schemes produced better results than the ETA and BT schemes. Nevertheless, MRF and BLK underestimate the zonal and meridional wind components by around 16% in the rainy season and overestimate them by on average 18% in the dry season.

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A Vertically Nested Regional Numerical Weather Prediction Model with Second-Order Closure Physics

Cited by 119 publications

References 0 publications

The role of atmospheric boundary layer-surface interactions on the development of coastal fronts

The role of atmospheric boundary layer-surface interactions on the development of coastal fronts

A Modeling Study of Typhoon Toraji (2001): Physical Parameterization Sensitivity and Topographic Effect

The Sensitivity of Wind Forecasts with a Mesoscale Meteorological Model at the Centro de Lançamento de Alcântara

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