scholarly journals The impact of a thermodynamic sea-ice module in the COSMO numerical weather prediction model on simulations for the Laptev Sea, Siberian Arctic

2011 ◽  
Vol 30 (1) ◽  
pp. 6334 ◽  
Author(s):  
David Schröder ◽  
Günther Heinemann ◽  
Sascha Willmes
Keyword(s):  
Sea Ice ◽  
Prediction Model ◽  
Numerical Weather Prediction ◽  
Weather Prediction ◽  
Numerical Weather Prediction Model ◽  
Laptev Sea ◽  
Numerical Weather ◽  
Siberian Arctic ◽  
The Impact ◽  
The Laptev Sea

scholarly journals On the Effect of Model Parameters on Forecast Objects

2017 ◽  
Author(s):  
Caren Marzban ◽  
Corinne Jones ◽  
Ning Li ◽  
Scott Sandgathe
Keyword(s):  
Prediction Model ◽  
Numerical Weather Prediction ◽  
Numerical Models ◽  
Weather Prediction ◽  
Clustering Algorithms ◽  
Numerical Weather Prediction Model ◽  
Model Parameters ◽  
Numerical Weather ◽  
The Impact ◽  
Mesoscale Numerical Weather Prediction

Abstract. Many physics-based numerical models produce a gridded, spatial field of forecasts, e.g., a temperature "map". However, the field for some quantities such as precipitation generally consists of spatially coherent and disconnected "objects". Certain features of these objects (e.g., number, size, and intensity) are generally of interest. Here, a methodology is developed for assessing the impact of model parameters on features of forecast objects. Although, in principle, the objects can be defined by any means, here they are identified via clustering algorithms. The methodology is demonstrated on precipitation forecasts from a mesoscale numerical weather prediction model.

scholarly journals Estimation of GNSS tropospheric products and their meteorological exploitation in Slovakia

2020 ◽  
Vol 50 (1) ◽  
pp. 83-111
Author(s):  
Martin Imrišek ◽  
Mária Derková ◽  
Juraj Janák
Keyword(s):  
Prediction Model ◽  
Numerical Weather Prediction ◽  
Initial Conditions ◽  
Weather Prediction ◽  
Numerical Weather Prediction Model ◽  
Precipitation Forecast ◽  
Total Delay ◽  
Numerical Weather ◽  
Zenith Total Delay ◽  
The Impact

This paper discusses the in near–real time processing of Global Navigation Satellite System observations at the Department of Theoretical Geodesy at the Slovak University of Technology in Bratislava. Hourly observations from Central Europe are processed with 30 minutes delay to provide tropospheric products. The time series and maps of tropospheric products over Slovakia are published online. Zenith total delay is the most important tropospheric parameter. Its comparison with zenith total delays from IGS and E–GVAP solutions and the validation of estimated zenith total delay error over year 2018 have been made. Zenith total delays are used to improve initial conditions of numerical weather prediction model by the means of the three–dimensional variational analysis at Slovak Hydrometeorological Institute. The impact of assimilation of different observation types into numerical weather prediction model is discussed. The case study was performed to illustrate the impact of zenith total delay assimilation on the precipitation forecast.

scholarly journals Computational Efficiency Examination of a Regional Numerical Weather Prediction Model using KISTI Supercomputer NURION

2021 ◽  
Vol 12 (6) ◽  
pp. 743-749
Author(s):  
Ji-Sun Kang Et.al
Keyword(s):  
Prediction Model ◽  
Numerical Weather Prediction ◽  
Computational Efficiency ◽  
Prediction Models ◽  
Weather Prediction ◽  
Numerical Weather Prediction Model ◽  
Extreme Weather Events ◽  
Numerical Weather ◽  
Computational Performance ◽  
The Impact

For well-resolving extreme weather events, running numerical weather prediction model with high resolution in time and space is essential. We explore how efficiently such modeling could be, using NURION. We have examined one of community numerical weather prediction models, WRF, and KISTI’s 5th supercomputer NURION of national HPC. Scalability of the model has been tested at first, and we have compared the computational efficiency of hybrid openMP + MPI runs with pure MPI runs. In addition to those parallel computing experiments, we have tested a new storage layer called burst buffer to see whether it can accelerate frequent I/O. We found that there are significant differences between the computational environments for running WRF model. First of all, we have tested a sensitivity of computational efficiency to the number of cores per node. The sensitivity experiments certainly tell us that using all cores per node does not guarantee the best results, rather leaving several cores per node could give more stable and efficient computation. For the current experimental configuration of WRF, moreover, pure MPI runs gives much better computational performance than any hybrid openMP + MPI runs. Lastly, we have tested burst buffer storage layer that is expected to accelerate frequent I/O. However, our experiments show that its impact is not consistently positive. We clearly confirm the positive impact with relatively smaller problem size experiments while the impact was not seen with bigger problem experiments. Significant sensitivity to the different computational configurations shown this paper strongly suggests that HPC users should find out the best computing environment before massive use of their applications

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