lateral boundary condition
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2021 ◽  
Vol 25 (1) ◽  
pp. 165-175
Author(s):  
Nurul Amirah Isa ◽  
Siti Aekbal Salleh ◽  
an Mohd Naim Wan Mohd ◽  
Maggie Chel Gee Ooi ◽  
Andy Chan ◽  
...  

2020 ◽  
Vol 59 (5) ◽  
pp. 793-817 ◽  
Author(s):  
Alexander Gavrikov ◽  
Sergey K. Gulev ◽  
Margarita Markina ◽  
Natalia Tilinina ◽  
Polina Verezemskaya ◽  
...  

AbstractWe present in this paper the results of the Russian Academy of Sciences North Atlantic Atmospheric Downscaling (RAS-NAAD) project, which provides a 40-yr 3D hindcast of the North Atlantic (10°–80°N) atmosphere at 14-km spatial resolution with 50 levels in the vertical direction (up to 50 hPa), performed with a regional setting of the WRF-ARW 3.8.1 model for the period 1979–2018 and forced by ERA-Interim as a lateral boundary condition. The dataset provides a variety of surface and free-atmosphere parameters at sigma model levels and meets many demands of meteorologists, climate scientists, and oceanographers working in both research and operational domains. Three-dimensional model output at 3-hourly time resolution is freely available to the users. Our evaluation demonstrates a realistic representation of most characteristics in both datasets and also identifies biases mostly in the ice-covered regions. High-resolution and nonhydrostatic model settings in NAAD resolve mesoscale dynamics first of all in the subpolar latitudes. NAAD also provides a new view of the North Atlantic extratropical cyclone activity with a much larger number of cyclones as compared with most reanalyses. It also effectively captures highly localized mechanisms of atmospheric moisture transports. Applications of NAAD to ocean circulation and wave modeling are demonstrated.


2020 ◽  
Author(s):  
Eren Duzenli ◽  
Heves Pilatin ◽  
Ismail Yucel ◽  
Berina M. Kilicarslan ◽  
M. Tugrul Yilmaz

<p>Global numerical weather prediction models (NWP) such as the European Centre for Medium-Range Weather Forecasts (ECMWF) and Global Forecast System (GFS) generate atmospheric data for the entire world. However, these models provide the data at large spatiotemporal resolutions because of computational limitations. Weather Research and Forecasting (WRF) Model is one of the models, which is capable of dynamically downscaling the NWP models’ output. In this study, all combinations of 4 microphysics and 3 cumulus parametrization schemes, 2 planetary boundary layers (PBL), 2 initial and lateral boundary conditions and 2 horizontal grid spacing (i.e., an ensemble consisting of 96 different scenarios) are simulated to measure the sensitivity of WRF-derived precipitation against different model configurations. The sensitivity analyses are performed for 4 separate events. These events are selected among the extreme precipitation events in the Mediterranean (MED) and eastern Black Sea (EBLS) regions. For each region, a summer and an autumn event are chosen. Here, the fundamental aim is to determine the spatiotemporal differences in WRF input parameters that yield better outcomes. A total of 72 hours simulations are started 24 hours before the event day to avoid spin-up time error. The model is adjusted to produce hourly precipitation outputs. The relative performance of scenarios is measured using Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) method considering 5 categorical validation indices and 4 pairwise statistics calculated between the model estimations and the ground-based precipitation observations. According to the TOPSIS results, microphysics scheme, initial and lateral boundary condition, and horizontal grid spacing are substantially influential on WRF precipitation estimates, while cumulus parameterization has a comparatively low effect. The choice of PBL scheme is essential for the summer events, but the results of the autumn events are independent of PBL selection. WRF products are better for the events of the EBLS basin when ERA5 is used as the initial and lateral boundary condition. On the contrary, GFS is superior in the MED region. In terms of spatial resolution, 9 km horizontal grid spacing is commonly preferable for all the events rather than 3 km. Besides, the model underestimates the area-averaged precipitation amounts except for the MED-autumn incident. Still, the model is successful at catching the peak hours of all events. Moreover, the precipitation detection ability of WRF is better for the autumn months. The probability of detection index is higher than 0.5 at 35% of MED stations and 68% of EBLS stations for the autumn events. The local and convective summer events are investigated considering the event centers. Albeit relatively low relationships are defined for the MED-summer event, a statistically significant correlation is obtained between the central station of the EBLS-summer event and the closest grid for the predictions of 52 scenarios (i.e., 54% of the ensemble).</p>


Atmosphere ◽  
2019 ◽  
Vol 10 (10) ◽  
pp. 570
Author(s):  
Antonio Stanesic ◽  
Kristian Horvath ◽  
Endi Keresturi

The evaluation of several climatological background-error covariance matrix (defined as the B matrix) estimation methods was performed using the ALADIN limited-area modeling data-assimilation system at a 4 km horizontal grid spacing. The B matrices compared were derived using the standard National Meteorological Center (NMC) and ensemble-based estimation methods. To test the influence of lateral boundary condition (LBC) perturbations on the characteristics of ensemble-based B matrix, two ensemble prediction systems were established: one used unperturbed lateral boundary conditions (ENS) and another used perturbed lateral boundary conditions (ENSLBC). The characteristics of the three B matrices were compared through a diagnostic comparison, while the influence of the different B matrices on the analysis and quality of the forecast were evaluated for the ENSLBC and NMC matrices. The results showed that the lateral boundary condition perturbations affected all the control variables, while the smallest influence was found for the specific humidity. The diagnostic comparison showed that the ensemble-based estimation method shifted the correlations toward the smaller spatial scales, while the LBC perturbations gave rise to larger spatial scales. The influence on the analysis showed a smaller spatial correlation for the ensemble B matrix compared to that of the NMC, with the most pronounced differences for the specific humidity. The verification of the forecast showed modest improvement for the experiment with the ensemble B matrix. Among the methods tested, the results suggest that the ensemble-based data-assimilation method is the favorable approach for background-error covariance calculation in high-resolution limited-area data assimilation systems.


2019 ◽  
Vol 7 (6) ◽  
pp. 190 ◽  
Author(s):  
Yan Zhang ◽  
Jianhong Ye ◽  
Kunpeng He ◽  
Songgui Chen

Submarine pipeline is a type of important infrastructure in petroleum industry used for transporting crude oil or natural gas. However, submarine pipelines constructed in high seismic intensity zones are vulnerable of attacks from seismic waves. It is important and meaningful in engineering design to comprehensively understand the seismic wave-induced dynamics characteristics of submarine pipelines. In this study, taking the coupled numerical model FSSI-CAS 2D as the tool, the seismic dynamics of a submarine steel pipeline buried in dense soil is investigated. Computational results indicate that submarine pipeline buried in dense seabed soil strongly responds to seismic wave. The peak acceleration could be double of that of input seismic wave. There is no residual pore pressure in the dense seabed. Significant resonance of the pipeline is observed in horizontal direction. Comparative study shows that the lateral boundary condition which can avoid wave reflection on it, such as laminar boundary and absorbing boundary should be used for seabed foundation domain in computation. Finally, it is proven that the coupled numerical model FSSI-CAS 2D is applicable to evaluate the seismic dynamics of submarine pipeline.


2017 ◽  
Vol 145 (12) ◽  
pp. 5059-5082 ◽  
Author(s):  
Junya Uchida ◽  
Masato Mori ◽  
Masayuki Hara ◽  
Masaki Satoh ◽  
Daisuke Goto ◽  
...  

A nonhydrostatic, regional climate limited-area model (LAM) was used to analyze lateral boundary condition (LBC) errors and their influence on the uncertainties of regional models. Simulations using the fully compressible nonhydrostatic LAM (D-NICAM) were compared against the corresponding global quasi-uniform-grid Nonhydrostatic Icosahedral Atmospheric Model (NICAM) and a stretched-grid counterpart (S-NICAM). By this approach of sharing the same dynamical core and physical schemes, possible causes of model bias and LBC errors are isolated. The simulations were performed for a 395-day period from March 2011 through March 2012 with horizontal grid intervals of 14, 28, and 56 km in the region of interest. The resulting temporal mean statistics of the temperatures at 500 hPa were generally well correlated between the global and regional simulations, indicating that LBC errors had a minor impact on the large-scale flows. However, the time-varying statistics of the surface precipitation showed that the LBC errors lead to the unpredictability of convective precipitation, which affected the mean statistics of the precipitation distributions but induced only minor influences on the large-scale systems. Specifically, extratropical cyclones and orographic precipitation are not severely affected. It was concluded that the errors of the precipitation distribution are not due to the difference of the model configurations but rather to the uncertainty of the system itself. This study suggests that applications of ensemble runs, internal nudging, or simulations with longer time scales are needed to obtain more statistically significant results of the precipitation distribution in regional climate models.


2017 ◽  
Vol 54 (9) ◽  
pp. 1245-1256 ◽  
Author(s):  
Jianfeng Wang ◽  
Su Liu ◽  
Yi Pik Cheng

This paper presents numerical results from a two-dimensional discrete element method (DEM) simulation study on the influence of lateral boundary condition on shaft resistance of a pile driven into a crushable sand. The study was conducted by comparing simulation results from the pile penetration test and the interface shear test employing parallel-bonded agglomerates for modeling of the particle breakage. The interface shear test was performed under three different types of normal boundary conditions; namely, constant normal load (CNL), constant normal stiffness (CNS), and constant volume (CV) boundary conditions. For the pile penetration test, a series of sampling windows were identified on the initial ground configuration to monitor the stress–strain, volume change, and particle breakage behavior of particle groups located within the sampling windows. A detailed investigation was then undertaken by comparing the behavior of particle groups with that from the interface shear test to find out which type of normal boundary condition best describes the lateral boundary condition in the pile penetration test. It has been found that the behavior of a particle group reaches the peak state below the pile tip and the critical state after it reaches the pile shaft. The influence of normal boundary condition on the stress ratio at the critical state is not obvious. The conventional interface shear test (i.e., CNL) can provide valuable information on the determination of skin friction along the pile shaft.


2016 ◽  
Vol 31 (2) ◽  
pp. 515-530 ◽  
Author(s):  
Florian Weidle ◽  
Yong Wang ◽  
Geert Smet

Abstract It is quite common that in a regional ensemble system the large-scale initial condition (IC) perturbations and the lateral boundary condition (LBC) perturbations are taken from a global ensemble prediction system (EPS). The choice of global EPS as a driving model can have a significant impact on the performance of the regional EPS. This study investigates the impact of large-scale IC/LBC perturbations obtained from different global EPSs on the forecast quality of a regional EPS. For this purpose several experiments are conducted where the Aire Limitée Adaption dynamique Développement International–Limited Area Ensemble Forecasting (ALADIN-LAEF) regional ensemble is forced by two of the world’s leading global ensembles, the European Centre for Medium-Range Weather Forecasts’ Ensemble Prediction System (ECMWF-EPS) and the Global Ensemble Forecasting System (GEFS) from the National Centers for Environmental Prediction (NCEP), which provide the IC and LBC perturbations. The investigation is carried out for a 51-day period during summer 2010 over central Europe. The results indicate that forcing of the regional ensemble with GEFS performs better for surface parameters, whereas at upper levels forcing with ECMWF-EPS is superior. Using perturbations from GEFS lead to a considerably higher spread in ALADIN-LAEF, which is beneficial near the surface where regional EPSs are usually underdispersive. At upper levels, forcing with GEFS leads to an overdispersion of ALADIN-LAEF as a result of the large spread of some parameters, where forcing ALADIN-LAEF with ECMWF-EPS provides statistically more reliable forecasts. The results indicate that the best global EPS might not always provide the best ICs and LBCs for a regional ensemble.


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