Advanced Regional Prediction System Model Research Articles

Assessment of the Integrated ARPS–CMAQ Modeling System through Simulating PM10 Concentration in Beijing, China

In this study, the Advanced Regional Prediction System (ARPS) model was introduced to replace the default weather module in Models-3 Community Multiscale Air Quality (CMAQ) modeling system, to provide a complete meteorological dataset required for urban air quality simulations. The ARPS model was chosen because of its nonhydrostatic dynamics, the generalized terrain-following height vertical coordinate, and the Arakawa-C horizontal grids, which are identical to the ones used in CMAQ, as well as its capabilities of simulating assorted-scale meteorological circulations within a large spectrum (especially at small scales). To assess its performance, the integrated ARPS–CMAQ modeling system was applied to Beijing, China, for simulating its PM10 concentration. The study region was delineated into a two-level nested-grid domain with spatial resolutions of 12 and 4 km, respectively. Three monitoring stations within the urban area of Beijing representing different categories of city function zones were selected t...

Simulation of mesoscale structure of thunderstorm using ARPS Model

In this paper mesoscale structures of two thunderstorm events over Delhi have been simulated using ARPS (Advanced Regional Prediction System) model. Numerical experiments were carried out using radiosonde data of Delhi and applying a potential temperature perturbation for triggering convective activity. The simulation exercise demonstrates strong updrafts and downdrafts associated with the thunderstorm cells, indicating the presence of very strong localized convection. The development and evolution of thunderstorm and propagation of associated precipitation zone are clearly brought out in this simulation study.

Precipitation simulation of synoptic scale systems over western Himalayan region using Advanced Regional Prediction System (ARPS) model

Operational weather prediction over western Himalayan region is a challenging job due to scarcity of data and complex topography that interacts with approaching weather system. Accurate prediction of complex weather phenomena requires dense data network which is difficult to establish in mountain due to complex terrain and hostile weather conditions over Himalaya. The alternate method to overcome this problem is by ingesting three-dimensional meteorological variables from global model’s analysis and forecast values as initial and lateral boundary conditions in meso-scale numerical models. Simultaneously, data assimilation is a potential tool in which non-conventional [satellite, radar and Automatic Weather Station (AWS)] and conventional (surface and upper air observations) data are ingested in the numerical models to generate high resolution and accurate initial fields for the initialization of the mesoscale model. In the present study, Advanced Regional Prediction System (ARPS) model has been used for the prediction of synoptic weather system known as Western Disturbance (WD) that affects the weather of western and central Himalaya during winter period (November – April).The ARPS model has been selected for this study because the model has its own objective analysis and quality control system. It has the capacity to ingest the satellite, Doppler weather radar data and other types of observations. Its assimilation system can also be used to overcome the problem of data scarcity in Himalayan region. In this study, initial and lateral boundary fields are taken from the T-80 spectral global model operationally used at National Centre for Medium Range Prediction (NCMRWF), Noida (UP), India. The global model’s analysis was taken as the initial condition and 24 hour’s interval forecasts as lateral boundary conditions. The model has been used for the simulation of few WDs for 96 hours (Four days). The comparison of ARPS simulation with T-80 forecast shows that the ARPS model could produce better results in respect of the circulation of WDs and hence it can be utilized for the operational weather prediction over the Indian region.

A Simple Simulation of Parabola-Shaped Clouds in the Lee of a Low Bell-Shaped Mountain Using the ARPS

A three-dimensional linear model and the Advanced Regional Prediction System (ARPS) were used to simulate parabola-shaped disturbances and clouds in the lee of a bell-shaped mountain. The ARPS model was compared in the x-y plane against the linear model's analytic solution. Under similar conditions with the linear theory, the ARPS produced well-developed parabola-shaped mountain disturbances and confirmed the features are accounted for in the linear regime. A parabola-shaped cloud in the lee of an isolated bell-shaped mountain was successfully simulated in the ARPS after 6 hours of integration time with the prescribed initial and boundary conditions, as well as a microphysical scheme.

Numerical Simulations of the Effects of Coastlines on the Evolution of Strong, Long-Lived Squall Lines

Abstract This study develops conceptual models of how a land–water interface affects the strength and structure of squall lines. Two-dimensional numerical simulations using the Advanced Regional Prediction System model are employed. Five sets of simulations are performed, each testing eight wind shear profiles of varying strength and depth. The first set of simulations contains a squall line but no surface or radiation physics. The second and third sets do not contain a squall line but include surface and radiation physics with a land surface on the right and a water surface on the left of the domain. The land is either warmer or cooler than the sea surface. These three simulations provide a control for later simulations. Finally, the remaining two simulation sets examine squall-line interaction with a relatively cool or warm land surface. The simulations document the thermodynamic and shear characteristics of squall lines interacting with the coastline. Results show that the inclusion of a land surface did not sufficiently affect the thermodynamic properties ahead of the squall line to change its overall structure. Investigation of ambient shear ahead of the squall line revealed that the addition of either warm or cool land reduced the strength of the net circulation in the inflow layer as measured by ambient shear. The amount of reduction in shear was found to be directly proportional to the depth and strength of the original shear layer. For stronger and deeper shears, the reduction in shear is sufficiently great that the buoyancy gradient circulation at the leading edge of the cold pool is no longer in balance with the shear circulation leading to changes in squall-line updraft structure. The authors hypothesize two ways by which a squall line might respond to passing from water to land. The weaker and more shallow the ambient shear, the greater likelihood that the squall-line structure remains unaffected by this transition. Conversely, the stronger and deeper the shear, the greater likelihood that the squall line changes updraft structure from upright/downshear to upshear tilted.

Influence of the scorer parameter profile on the wavelength of trapped lee waves

A three-layer theoretical model was established, in which the atmosphere is divided into three layers based on the Scorer parameter l 2, which is large in the middle layer and small in the other two layers. The wave number formula of lee waves was deduced with this theoretical model, and a typical example for the lee wave was calculated. Thus, the influence of changes in the thickness of every layer and values of the Scorer parameter in every layer was examined. The results show that the wavelength decreases with an increase in the thickness of the lower and the middle layers and is more sensitive to the changes in the middle layer. Therefore, if the changes in these two layers are different, the changes in the middle layer will dominate the changes in the wavelength. The results also show that the wavelength decreases with the increase in the value of l2 in every layer, among which the sensitivity to the l2 in the upper layer is the most striking. The calculation results reasonably can explain the influence of diurnal changes on the wavelength. The example was simulated using Advanced Regional Prediction System model, and the sensitivity experiments were performed to confirm the effects of the Scorer parameter profiles on the wavelengths. The simulated results are consistent with the calculated results.

Simulation of heavy precipitation over Santacruz, Mumbai on 26 July 2005, using Mesoscale model

An attempt has been made to simulate the unprecedented heavy precipitation of 94.4 cm in a day over Santacruz, Mumbai during 0300 UTC 26 July to 0300 UTC 27 July 2005. Three experiments have been conducted using Advanced Regional Prediction System model developed by Center for Analysis and Prediction of Storms of Oklahoma University, USA. In first experiment the model input at large domain size has been obtained using NCEP/NCAR reanalysis data at 2.5° × 2.5° lat.–lon. resolution. In other two experiments model input at large as well as at small domain sizes, have been obtained from NCEP/NCAR FNL data of 1° × 1° lat.–lon. resolution. In all three experiments model’s horizontal resolution is 40 km and integration period is 30 hours from 0000 UTC 26 July 2005. Based on the temporal distribution of observed rainfall rates it is considered that the rainfall of 38.1 cm during 0900–1200 UTC on 26 July could be due to cloud burst phenomenon and 56.3 cm from 1200 UTC of 26 July to 0300 UTC of 27 July has been due to continuous regeneration of thunderstorm activity under influence of mesoscale cloud complex. It is found that model forecast of rainfall in first experiment was qualitatively as well as quantitatively very poor. Among other two, experiment with large domain size has predicted better rainfall values and location compared to the experiment with small domain size. The larger domain has produced rainfall of 41 cm as against observed rain rate of 56.3 cm. during 1200 UTC of 26 July to 0300 UTC of 27 July. Divergence, vorticity, vertical velocity and moisture parameters are examined in relation with the various stages of the event. The maximum values of convergence, vorticity and moisture fluxes precede the initial phase of mature stage, however vertical velocity follows the later phase of mature stage. Vorticity budget over the location of maximum rainfall, revealed the significant role of tilting term in maintenance and dissipation of the cloud complex responsible for the event. The model has simulated mixing ratios of ice, snow and hail up to height of 15 km which matches with the observations that clouds reaching up to 15 km were present at the time of event of heavy precipitation.

Simulation of weather systems over Indian region using mesoscale models

Simulation studies have been carried out for two weather systems namely; a pre-monsoon thunderstorm over east coast of India and a weak cyclonic circulation associated with feeble low pressure area over south peninsular India. Two sets of forecast results are obtained: one using Advanced Regional Prediction System Model and other using Weather Research and Forecasting Model. The model performances are compared by examining the predicted parameters like mean sea level pressure, wind, moisture fields and rainfall. The rainfall prediction is assessed qualitatively by comparing the spatial distribution with satellite cloud images and quantitatively by comparing rainfall rates with Tropical Rainfall Measuring Mission products and/or the observed station values reported in Indian Daily Weather Reports. It is found that in case of idealized simulation of thunderstorm, Advanced Regional Prediction System Model has well predicted the spatial distribution of rainfall which is consistent with the clouding in satellite cloud images. It also has simulated the diverging winds at lower levels associated with downdraft during mature/dissipation stage of thunderstorm. Weather Research and Forecasting Model failed to predict these features. In case of a weak cyclonic circulation simulation experiment, Advanced Regional Prediction System model is able to simulate the rainy area better compared to those produced by Weather Research and Forecasting Model. Both models failed to produce observed heavy precipitation rates.

Generating artificial vertical soundings over complex terrain from the aLMo model output to drive a high resolution snow-drift model

To obtain a high-resolution wind field and to model snow drift over complex topography, the Swiss Federal Institute for Snow and Avalanche Research (SLF) uses the atmospheric model ARPS (Advanced Regional Prediction System, University of Oklahoma). ARPS accesses horizontally homogeneous initial fields. Until recently, this model was driven by atmospheric soundings recorded at sites far away from the actual model domain. In order to optimise the initial conditions of ARPS and to provide the option of producing real forecasts, a new downscaling method has been developed, which can also be applied to other uses. Based on the vertical structure of the atmosphere produced by the operational mesoscale forecast model aLMo (Alpine Model, MeteoSwiss), an artificial sounding is created for a specified location within the ARPS grid. Some of the techniques applied include model bias adjustment (based on aLMo verification studies), the introduction of horizontal filters, the assimilation of surface observation data and the vertical displacement of the boundary layer, motivated by the distinct topographies of the ARPS and the aLMo model. The combination of the methods differs from parameter to parameter. This paper describes details of the downscaling technique and gives an example of the application of the method. Copyright © 2004 Royal Meteorological Society.

A parameterization of wave stress in the planetary boundary layer for use in mesoscale models

Abstract A parameterization of gravity wave stress generated by subgrid-scale topography is described and tested in a one-dimensional version of the Advanced Regional Prediction System (ARPS) model. It is argued that in the planetary boundary layer (PBL) where wave reflections occur, the so-called WKB method for evaluating wave stress may not be applicable. Gravity waves launched by a subgrid-scale Gaussian ridge are calculated on line using a linear wave model. The total flow is constrained to be convectively stable by using a terrain-height adjustment to decrease wave amplitudes and thereby prevent wave overturning. In this method when the waves grow large enough to overturn, the wave amplitudes are decreased by decreasing the maximum height of the terrain obstacle, H. At each time step, the ARPS model flow is modified by the divergence of the wave stress. The effects of wave-stress divergence on turbulence parameterization is examined using three turbulence closure schemes, K-theory with constant eddy diffusivity, the Smagorinsky closure, and the turbulence-kinetic energy closure. Also, the effects of vertical grid spacing are tested using spacings of 10, 20, 50 and 100 m . The model is initialized with a hyperbolic-tangent wind profile and constant Brunt–Vaisala frequency. It is shown that wave-stress divergence can lead to elevated layers of turbulence and diffusion where they would not occur in the absence of the wave-stress parameterization. It is also shown that if the vertical grid spacing is too great, then the effects of wave breaking are not fully realized.

Impact of Cloud Analysis on Numerical Weather Prediction in the Galician Region of Spain

The Advanced Regional Prediction System (ARPS) is applied to operational numerical weather prediction in Galicia, northwest Spain. The model is run daily for 72-h forecasts at a 10-km horizontal spacing. Located on the northwest coast of Spain and influenced by the Atlantic weather systems, Galicia has a high percentage (nearly 50%) of rainy days per year. For these reasons, the precipitation processes and the initialization of moisture and cloud fields are very important. Even though the ARPS model has a sophisticated data analysis system (‘‘ADAS’’) that includes a 3D cloud analysis package, because of operational constraints, the current forecast starts from the 12-h forecast of the National Centers for Environmental Prediction Aviation Model (AVN). Still, procedures from the ADAS cloud analysis are being used to construct the cloud fields based on AVN data and then are applied to initialize the microphysical variables in ARPS. Comparisons of the ARPS predictions with local observations show that ARPS can predict very well both the daily total precipitation and its spatial distribution. ARPS also shows skill in predicting heavy rains and high winds, as observed during November 2000, and especially in the prediction of the 5 November 2000 storm that caused widespread wind and rain damage in Galicia. It is demonstrated that the cloud analysis contributes to the success of the precipitation forecasts.

Cluster Analysis of Multimodel Ensemble Data from SAMEX

Short-range ensemble forecasts from the Storm and Mesoscale Ensemble Experiment (SAMEX) are examined to explore the importance of model diversity in short-range ensemble forecasting systems. Two basic techniques from multivariate data analysis are used: cluster analysis and principal component analysis. This 25-member ensemble is constructed of 36-h forecasts from four different numerical weather prediction models, including the Eta Model, the Regional Spectral Model (RSM), the Advanced Regional Prediction System (ARPS), and the Pennsylvania State University‐National Center for Atmospheric Research fifth-generation Mesoscale Model (MM5). The Eta Model and RSM forecasts are initialized using the breeding of growing modes approach, the ARPS model forecasts are initialized using a scaled lagged average forecasting approach, and the MM5 forecasts are initialized using a random coherent structures approach. The MM5 forecasts also include different model physical parameterization schemes, allowing us to examine the role of intramodel physics differences in the ensemble forecasting process. Cluster analyses of the 3-h accumulated precipitation, mean sea level pressure, convective available potential energy, 500-hPa geopotential height, and 250-hPa wind speed forecasts started at 0000 UTC 29 May 1998 indicate that the forecasts cluster largely by model, with few intermodel clusters found. This clustering occurs within the first few hours of the forecast and persists throughout the entire forecast period, even though the perturbed initial conditions from some of the models are very similar. This result further highlights the important role played by model physics in determining the resulting forecasts and the need for model diversity in shortrange ensemble forecasting systems.

Numerical Simulation of Transitions in Boundary Layer Convective Structures in a Lake-Effect Snow Event

Abstract Numerical simulations are used to study transitions between boundary layer rolls and more cellular convective structures observed during a lake-effect snow event over Lake Michigan on 17 December 1983. Weak lake-effect nonroll convection was observed near the eastern (downwind) shore preceding passage of a secondary cold front. After frontal passage horizontal wind speeds in the convective boundary layer increased, with subsequent development of linear convective patterns. Thereafter the convective pattern became more three-dimensional as low-level wind speeds decreased. Little directional shear was observed in any of the wind profiles. Numerical simulations with the Advanced Regional Prediction System model were initialized with an upwind sounding and radar-derived wind profiles corresponding to each of the three convective structure regimes. Model-derived reflectivity fields were in good agreement with the observed regimes. These simulations differed primarily in the initial wind speed profiles...