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Improvement of Numerical Weather Prediction for Complex Terrain

Improvement of Numerical Weather Prediction for Complex Terrain
复杂地形数值天气预报的改进
批准号:
184017-2012
负责人:
Stull, Roland
金额:
$2.77万
依托单位国家:
加拿大
项目类别:
Discovery Grants Program - Individual
财政年份:
2015
资助国家:
加拿大
项目状态:
已结题
起止时间:
2015-01-01 至 2016-12-31

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中文摘要
翻译
。我们的动机是更好地预测与天气有关的灾害,并帮助提高与天气有关的清洁能源(风能和水力发电)的效率和安全性。为了实现这一目标,我们的研究目标是提高复杂山区和沿海地形(如加拿大西部)的数值天气预报技能。
英文摘要
. Our motivation is to better predict weather-related disasters, and to help enhance the efficiency and safety of weather-related clean energy (wind and hydro). To achieve this, our research goal is to improve the skill of numerical weather prediction for complex mountainous and coastal terrains such as in Western Canada. Numerical weather prediction (NWP) is a computational tool that uses high-performance computers to numerically integrate the atmospheric fluid-dynamics equations. The large, publically available NWP computer codes that solve these equations are called "models". No model is perfect, so we post-process the computer output to correct any systematic errors. We also utilize an "ensemble" of NWP forecasts from many models to account for the chaotic nature of the atmosphere. The spread of the ensemble forecasts can be calibrated to estimate the probability of different forecast outcomes -- important information for the optimum management of energy resources. Our following activities will help achieve our goals. Hazardous weather events are often relatively rare and hard to forecast, so we will improve ways to utilize "analog weather ensembles" from past rare events that were similar. Hydro reservoirs and river flood forecasts rely on imperfect hydrologic models, so we will drive an ensemble of hydrologic models with output from an ensemble of NWP models to improve skill. High-resolution weather forecasts will be applied to, and will be improved by, data from smart electric meters being deployed in W. Canada. We will test whether a new type of genetic programming can help predict sharp changes in wind speed that modulate wind-power production. We will enhance an NWP model to enable finer-resolution forecasts in mountainous terrain for better prediction of rainfall-triggered landslides, debris flows, rail washouts, local flooding, and snow avalanches along transportation corridors in steep narrow mountain valleys. This work will help save lives, reduce energy costs, make transportation more reliable, and help Canadian industries to thrive.
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Numerical Weather Prediction Advances for a Growing Canadian Economy
  • 批准号:
    RGPIN-2017-03849
  • 项目类别:
    Discovery Grants Program - Individual
  • 资助金额:
    $4.66万
  • 财政年份:
    2021
  • 负责人:
    Stull, Roland
  • 依托单位:
Numerical Weather Prediction Advances for a Growing Canadian Economy
  • 批准号:
    RGPIN-2017-03849
  • 项目类别:
    Discovery Grants Program - Individual
  • 资助金额:
    $2.33万
  • 财政年份:
    2020
  • 负责人:
    Stull, Roland
  • 依托单位:
Numerical Weather Prediction Advances for a Growing Canadian Economy
  • 批准号:
    RGPIN-2017-03849
  • 项目类别:
    Discovery Grants Program - Individual
  • 资助金额:
    $2.33万
  • 财政年份:
    2019
  • 负责人:
    Stull, Roland
  • 依托单位:
Numerical Weather Prediction Advances for a Growing Canadian Economy
  • 批准号:
    RGPIN-2017-03849
  • 项目类别:
    Discovery Grants Program - Individual
  • 资助金额:
    $2.33万
  • 财政年份:
    2018
  • 负责人:
    Stull, Roland
  • 依托单位:
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