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SUMMARY:HPC Training Series - Course 13 "The Weather Research and Forecast
 ing (WRF) Model on HPC"
DTSTART;VALUE=DATE-TIME:20250428T064500Z
DTEND;VALUE=DATE-TIME:20250428T114500Z
DTSTAMP;VALUE=DATE-TIME:20260520T103736Z
UID:indico-event-173@events.grnet.gr
DESCRIPTION:\n\nEuroCC@Greece announced the 13th Course of HPC Training Se
 ries  with the subject "The Weather Research and Forecasting (WRF) Model o
 n HPC"\, that took place online on April 28th\, 2025.  \n\nDate: April 28
 th\, 2025\, at 09:45 EET   \n\nLocation: Online via Zoom \n\nPresentati
 on Languages: Greek\n\nAudience: This course is designed for meteorologist
 s\, climate scientists\, researchers\, and engineers who need to run and o
 ptimize WRF models on High-Performance Computing (HPC) systems. It is also
  suitable for graduate students and professionals in atmospheric sciences\
 , computational physics\, and environmental modeling.\n\nCourse Descriptio
 n: This course provided an overview of the Weather Research and Forecastin
 g (WRF) model\, focusing on its application and optimization on High-Perfo
 rmance Computing (HPC) systems. Participants learned WRF model fundamental
 s\, installation\, configuration\, execution\, and performance tuning tech
 niques specific to HPC environments.\n\nLearning Objectives:\n\nBy the end
  of this course\, participants were able to:\n\n\n	\n	Understand WRF model
  – Explain the fundamentals of Weather Research and Forecasting (WRF) mo
 del and its applications.\n	\n	\n	Set Up and Configure WRF – Install\, c
 onfigure\, and run WRF model on HPC systems.\n	\n	\n	Optimize Performance 
 – Apply parallel computing techniques to enhance WRF model efficiency on
  HPC.\n	\n	\n	Analyze Model Outputs – Interpret WRF simulations and vali
 date results against observational data.\n	\n	\n	Troubleshoot and Debug 
 – Identify and resolve common issues in WRF simulations on HPC platforms
 .\n	\n\n\nPrerequisites:\n\n\n	\n	Basic Meteorology Knowledge – Understa
 nding of atmospheric processes and weather forecasting concepts.\n	\n	\n	L
 inux Proficiency – Familiarity with command-line operations and shell sc
 ripting.\n	\n	\n	Programming Experience – Basic knowledge of Fortran and
 /or C++.\n	\n	\n	Numerical Modeling Basics – Understanding of numerical 
 weather prediction principles.\n	\n	\n	HPC Familiarity – Experience with
  parallel computing\, job scheduling\, and running applications on HPC sys
 tems is beneficial but not required. \n	\n\n\n \n\nNote: Please enter yo
 ur institutional/corporate email when registering.\n\n \n\nhttps://events
 .grnet.gr/event/173/
LOCATION:
URL:https://events.grnet.gr/event/173/
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