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.

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The Advanced Regional Prediction System (ARPS), storm-scale numerical weather prediction and data assimilation

Meteorology and Atmospheric Physics ◽

10.1007/s00703-001-0595-6 ◽

2003 ◽

Vol 82 (1-4) ◽

pp. 139-170 ◽

Cited By ~ 298

Author(s):

Ming Xue ◽

Donghai Wang ◽

Jidong Gao ◽

Keith Brewster ◽

Kelvin K. Droegemeier

Keyword(s):

Data Assimilation ◽

Numerical Weather Prediction ◽

Weather Prediction ◽

Prediction System ◽

Advanced Regional Prediction System ◽

Numerical Weather ◽

Regional Prediction

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Sensitivity of Tropical Cyclone Idai Simulations to Cumulus Parametrization Schemes

Atmosphere ◽

10.3390/atmos12080932 ◽

2021 ◽

Vol 12 (8) ◽

pp. 932

Author(s):

Mary-Jane M. Bopape ◽

Hipolito Cardoso ◽

Robert S. Plant ◽

Elelwani Phaduli ◽

Hector Chikoore ◽

...

Keyword(s):

Tropical Cyclone ◽

Boundary Conditions ◽

Initial Conditions ◽

Weather Prediction ◽

Cumulus Parameterization ◽

Grey Zone ◽

Lateral Boundary ◽

Convection Scheme ◽

Weather System ◽

Lateral Boundary Conditions

Weather simulations are sensitive to subgrid processes that are parameterized in numerical weather prediction (NWP) models. In this study, we investigated the response of tropical cyclone Idai simulations to different cumulus parameterization schemes using the Weather Research and Forecasting (WRF) model with a 6 km grid length. Seventy-two-hour (00 UTC 13 March to 00 UTC 16 March) simulations were conducted with the New Tiedtke (Tiedtke), New Simplified Arakawa–Schubert (NewSAS), Multi-Scale Kain–Fritsch (MSKF), Grell–Freitas, and the Betts–Miller–Janjic (BMJ) schemes. A simulation for the same event was also conducted with the convection scheme switched off. The twenty-four-hour accumulated rainfall during all three simulated days was generally similar across all six experiments. Larger differences in simulations were found for rainfall events away from the tropical cyclone. When the resolved and convective rainfall are partitioned, it is found that the scale-aware schemes (i.e., Grell–Freitas and MSKF) allow the model to resolve most of the rainfall, while they are less active. Regarding the maximum wind speed, and minimum sea level pressure (MSLP), the scale aware schemes simulate a higher intensity that is similar to the Joint Typhoon Warning Center (JTWC) dataset, however, the timing is more aligned with the Global Forecast System (GFS), which is the model providing initial conditions and time-dependent lateral boundary conditions. Simulations with the convection scheme off were found to be similar to those with the scale-aware schemes. It was found that Tiedtke simulates the location to be farther southwest compared to other schemes, while BMJ simulates the path to be more to the north after landfall. All of the schemes as well as GFS failed to simulate the movement of Idai into Zimbabwe, showing the potential impact of shortcomings on the forcing model. Our study shows that the use of scale aware schemes allows the model to resolve most of the dynamics, resulting in higher weather system intensity in the grey zone. The wrong timing of the peak shows a need to use better performing global models to provide lateral boundary conditions for downscalers.

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Basic Diagnosis and Prediction of Persistent Contrail Occurrence Using High-Resolution Numerical Weather Analyses/Forecasts and Logistic Regression. Part II: Evaluation of Sample Models

Journal of Applied Meteorology and Climatology ◽

10.1175/2009jamc2057.1 ◽

2009 ◽

Vol 48 (9) ◽

pp. 1790-1802 ◽

Cited By ~ 5

Author(s):

David P. Duda ◽

Patrick Minnis

Keyword(s):

Relative Humidity ◽

Wind Direction ◽

Meteorological Data ◽

Logistic Models ◽

Satellite Observations ◽

Lapse Rate ◽

Prediction System ◽

Advanced Regional Prediction System ◽

Regional Prediction ◽

Surface Models

Abstract A probabilistic forecast to accurately predict contrail formation over the conterminous United States (CONUS) is created by using meteorological data based on hourly meteorological analyses from the Advanced Regional Prediction System (ARPS) and the Rapid Update Cycle (RUC) combined with surface and satellite observations of contrails. Two groups of logistic models were created. The first group of models (SURFACE models) is based on surface-based contrail observations supplemented with satellite observations of contrail occurrence. The most common predictors selected for the SURFACE models tend to be related to temperature, relative humidity, and wind direction when the models are generated using RUC or ARPS analyses. The second group of models (OUTBREAK models) is derived from a selected subgroup of satellite-based observations of widespread persistent contrails. The most common predictors for the OUTBREAK models tend to be wind direction, atmospheric lapse rate, temperature, relative humidity, and the product of temperature and humidity.

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The Advanced Regional Prediction System (ARPS) - A multi-scale nonhydrostatic atmospheric simulation and prediction model. Part I: Model dynamics and verification

Meteorology and Atmospheric Physics ◽

10.1007/s007030070003 ◽

2000 ◽

Vol 75 (3-4) ◽

pp. 161-193 ◽

Cited By ~ 589

Author(s):

M. Xue ◽

K. K. Droegemeier ◽

V. Wong

Keyword(s):

Prediction Model ◽

Prediction System ◽

Advanced Regional Prediction System ◽

Multi Scale ◽

Regional Prediction ◽

Model Dynamics

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Well-Posed Lateral Boundary Conditions for Spectral Semi-Implicit Semi-Lagrangian Schemes: Tests in a One-Dimensional Model

Monthly Weather Review ◽

10.1175/2008mwr2539.1 ◽

2009 ◽

Vol 137 (1) ◽

pp. 315-330 ◽

Cited By ~ 9

Author(s):

F. Voitus ◽

P. Termonia ◽

P. Bénard

Keyword(s):

Boundary Conditions ◽

Weather Prediction ◽

Implicit Time ◽

Lateral Boundary ◽

Dimensional Model ◽

One Dimensional ◽

Lateral Boundary Conditions ◽

Boundary Treatment ◽

Truncation Scheme ◽

Well Posed

Abstract The aim of this paper is to investigate the feasibility of well-posed lateral boundary conditions in a Fourier spectral semi-implicit semi-Lagrangian one-dimensional model. Two aspects are analyzed: (i) the complication of designing well-posed boundary conditions for a spectral semi-implicit scheme and (ii) the implications of such a lateral boundary treatment for the semi-Lagrangian trajectory computations at the lateral boundaries. Straightforwardly imposing boundary conditions in the gridpoint-explicit part of the semi-implicit time-marching scheme leads to numerical instabilities for time steps that are relevant in today’s numerical weather prediction applications. It is shown that an iterative scheme is capable of curing these instabilities. This new iterative boundary treatment has been tested in the framework of the one-dimensional shallow-water equations leading to a significant improvement in terms of stability. As far as the semi-Lagrangian part of the time scheme is concerned, the use of a trajectory truncation scheme has been found to be stable in experimental tests, even for large values of the advective Courant number. It is also demonstrated that a well-posed buffer zone can be successfully applied in this spectral context. A promising (but not easily implemented) alternative to these three above-referenced schemes has been tested and is also presented here.

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Nowcasting with the AROME Model: First Results from the High-Resolution AROME Airport

Weather and Forecasting ◽

10.1175/waf-d-13-00083.1 ◽

2014 ◽

Vol 29 (4) ◽

pp. 773-787 ◽

Cited By ~ 9

Author(s):

Susanna Hagelin ◽

Ludovic Auger ◽

Pascal Brovelli ◽

Olivier Dupont

Keyword(s):

High Resolution ◽

Wind Speed ◽

Weather Prediction ◽

Numerical Weather Prediction Model ◽

Lateral Boundary ◽

Charles De Gaulle ◽

Lateral Boundary Conditions ◽

First Results ◽

The Vertical Distribution ◽

De Gaulle

Abstract Applications of Research to Operations at Mesoscale (AROME) Airport is the high-resolution version of the French operational numerical weather prediction model AROME. The purpose of AROME Airport is to provide rapidly updated forecasts with a 500-m resolution for nowcasting over an airport and to help with the prediction of wake vortices in order to increase the efficiency of the airport. Here, the model is evaluated for the area around Paris Charles de Gaulle Airport (CDG), France. AROME Airport and other configurations of the AROME model are compared to observations during two 4-week periods, when additional observations are available for the area around CDG (May–June 2011 and September–October 2012). The root-mean-square error and the bias are calculated for the 2-m temperature, 10-m wind speed, and the vertical distribution of the wind speed using the available measurements. The performance of AROME Airport is compared to the operational configuration of the AROME model both for synoptic hours and in a more realistic setting using the forecasts from AROME Airport starting every hour. It is shown that the forecasts from AROME Airport are an improvement with respect to the operational when comparing runs from all forecast hours, particularly for the wind speed, but when comparing the synoptic hours, the results are less clear. The sensitivity of AROME Airport to its data assimilation and initial and lateral boundary conditions is also discussed.

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