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milennimh edited this page Apr 8, 2024 · 23 revisions

WP 4 task 3 wiki

Task 3 in WP4 is the Extreme event detection module in the On-Demand Extremes Digital Twin (DE_330). Its main objective is to detect different types of weather events, based on precursors on global or large scale grids, that are related to a high potential of becoming extreme events. This entails

  • Developing, testing and documenting methods and algorithms for event detection with a few days lead time. Methods will include both more simplistic threshold-based methods as well as machine learning/deep learning algorithms.
  • Integration of the developed methods in the overall DE_330 engine to provide on-demand information of potential extreme weather events within defined lead times.

Link to the sandbox : https://github.com/DEODE-NWP/WP43-sandbox

Example: Risk assessment for Gävle (Sweden) heavy rainfall event

List of codes with short description:

  • WP43-Surge-ThreshPB : An application is used to estimate the triggers for storm surge events in the Pärnu Bay. This is done by applying thresholds to the field characteristics of air pressure and wind speeds over the Baltic Sea.

  • WP43-ARSO-storm-surge-detection: The repository contains code and instructions for training, testing, and deploying a deep model for storm surge detection for several days in advance. Code for data collection and processing is also included, as well as case analysis for the Adriatic.

  • WP43-OPTI-THRED: OPTImized THReshold-based Event Detection.

  • WP43-Wildfire-CHMI: The repository contains code with algorithm to improve the wildfire risk prediction using a combination of Fire Weather Index, Haines index and current drought intensity using API30.

  • WP43-Frost-CHMI: The repository contains code with algorithm to identify spring frost days with the high potential to damage vegetation.

  • WP43-Drought-CHMI: The repository contains code with algorithm of severe drought evaluation using a combination of current precipitation deficit (API30) and average air temperature in last 7 days.

  • WP43-EFI: The repository contains code with algorithm of using EFI and SOT as Triggers for extreme weather events up to 7 days in advance.

  • WP43-Frost-NIMH: WP43_Frost_NIMH: The repository contains code to identify probability of spring frost with the high potential to damage to orchards using ML technique.

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