The Advanced Regional Prediction System (ARPS) - A multi-scale nonhydrostatic atmospheric simulation and prediction tool. Part II: Model physics and applications

Xue, Ming; Droegemeier, Kelvin K.; Wong, Vince; Shapiro, Alan; Brewster, Keith; Carr, Frederick H.; Weber, Daniel; Liu, Y.; Wang, D.

doi:10.1007/s007030170027

Cited by 547 publications

(364 citation statements)

References 0 publications

Supporting

Mentioning

358

Contrasting

Unclassified

Order By: Relevance

“…[6] A mesoscale nonhydrostatic model, the Advanced Regional Prediction System (ARPS) [Xue et al, 2000[Xue et al, , 2001 was run for the period 20 to 23 June 2001, covering the Marseille Berre-Pond Region. ARPS employs a finite difference approximation of the fully compressible NavierStokes equations, which are solved on a terrain-following grid.…”

Section: Model Descriptionmentioning

confidence: 99%

Modeling the energy balance in Marseille: Sensitivity to roughness length parameterizations and thermal admittance

Demuzere¹,

Ridder²,

Lipzig³

2008

J. Geophys. Res.

View full text Add to dashboard Cite

[1] During the ESCOMPTE campaign (Experience sur Site pour COntraindre les Modeles de Pollution atmospherique et de Transport d'Emissions), a 4-day intensive observation period was selected to evaluate the Advanced Regional Prediction System (ARPS), a nonhydrostatic meteorological mesoscale model that was optimized with a parameterization for thermal roughness length to better represent urban surfaces. The evaluation shows that the ARPS model is able to correctly reproduce temperature, wind speed, and direction for one urban and two rural measurements stations. Furthermore, simulated heat fluxes show good agreement compared to the observations, although simulated sensible heat fluxes were initially too low for the urban stations. In order to improve the latter, different roughness length parameterization schemes were tested, combined with various thermal admittance values. This sensitivity study showed that the Zilitinkevich scheme combined with and intermediate value of thermal admittance performs best.

show abstract

Section: Model Descriptionmentioning

confidence: 99%

Modeling the energy balance in Marseille: Sensitivity to roughness length parameterizations and thermal admittance

Demuzere¹,

Ridder²,

Lipzig³

2008

J. Geophys. Res.

View full text Add to dashboard Cite

show abstract

“…Details of the model can be found in Xue et al (2000Xue et al ( , 2001. The particular forecast quantity of interest is the surface temperature.…”

Section: Introductionmentioning

confidence: 99%

Neural Networks for Postprocessing Model Output: ARPS

Marzban

2003

Mon. Wea. Rev.

View full text Add to dashboard Cite

“…The numerical simulations used Version 5.0 of the Advanced Regional Prediction system (ARPS, Xue et al, 1995Xue et al, , 2000Xue et al, , 2001Xue et al, , 2003, a general-purpose, compressible, nonhydrostatic numerical weather prediction model. Several simulations were performed using different model start times and model resolutions, the start time of 1200 UTC 3 February was found to produce the best simulation results, which is a time of synoptic observations and is close to the beginning time of snowfall.…”

Section: Mdel Description and Numerical Simulationmentioning

confidence: 99%

“…Meanwhile, the fluxes at the sea surface are calculated using drag and exchange coefficients that are appropriate for water surfaces under moderate-wind conditions, which are set to 2×10 −3 following Chen et al (1983). More details of the physics schemes in the ARPS can be found in Xue et al (2001).…”

Section: Mdel Description and Numerical Simulationmentioning

confidence: 99%

“…Thus, heavy snowfall forecasting in the Yeongdong region is of primary concern during the winter season. Figure 1 shows the topography of the Korean Peninsula and that of the Yeongdong region in a simulation domain of the Advanced Regional Prediction System (ARPS, Xue et al, 2000Xue et al, , 2001Xue et al, , 2003 that is used in this study. The Yeongdong region consists of narrow and steep mountains (called the Taebaek Mountains) with an average height of about 1 km.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

A study on a snowband associated with a coastal front and cold-air damming event of 3–4 February 1998 along the eastern coast of the Korean Peninsula

Lee¹,

Xue

2013

Adv. Atmos. Sci.

View full text Add to dashboard Cite

A 24-h simulation with the Advanced Regional Prediction System (ARPS) nonhydrostatic model is performed for the heavy snowfall event of 3-4 February 1998 along the eastern coast of Korean Peninsula; the results are used to understand the snowfall process, including why the precipitation maxima formed along the Yeongdong coastal region rather than over the mountain slope and ridge top during.The numerical simulation with a 4-km horizontal grid spacing and 43 levels reproduces very well the narrow snowband located off the eastern Korean coast, away from, instead of over, the Yeongdong coastal mountain range. The general evolution of the snowband agrees quite well with radar observations, while the water-equivalent precipitation amount agrees reasonably well with radar precipitation estimate. The simulation results clearly show that the snow band developed due to the lifting by a coastal front that developed because of the damming of cold air against the eastern slope of the coastal mountain range. The damming was enhanced by the advection of cold air by a low-level mountain-parallel jet from the north, formed due to geostrophic adjustment as the on-shore upslope air was decelerated by the mountain blocking. As the onshore flow weakened later due to synoptic-scale flow pattern change, the cold front propagated off shore and the precipitation dissipated.

show abstract

The Advanced Regional Prediction System (ARPS) - A multi-scale nonhydrostatic atmospheric simulation and prediction tool. Part II: Model physics and applications

Cited by 547 publications

References 0 publications

Modeling the energy balance in Marseille: Sensitivity to roughness length parameterizations and thermal admittance

Modeling the energy balance in Marseille: Sensitivity to roughness length parameterizations and thermal admittance

Neural Networks for Postprocessing Model Output: ARPS

A study on a snowband associated with a coastal front and cold-air damming event of 3–4 February 1998 along the eastern coast of the Korean Peninsula

Contact Info

Product

Resources

About