基于物理的随机扰动改进对流的高分辨率预测

IF 3 3区 地球科学 Q2 METEOROLOGY & ATMOSPHERIC SCIENCES Quarterly Journal of the Royal Meteorological Society Pub Date : 2023-09-07 DOI:10.1002/qj.4574
Matjaž Puh, Christian Keil, Christoph Gebhardt, C. Marsigli, Mirjam Hirt, Fabian Jakub, George C. Craig
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引用次数: 1

摘要

基于物理的随机扰动方案PSP已在DWD允许对流的ICON‐D2系综预测系统中实现,并于2021年夏天进行了为期三个月的试验。该方案模拟了边界层湍流对最小分辨率尺度的影响,特别是对流降水的影响。一项与天气状况相关的系统评估表明,PSP在弱天气强迫下有效地增加了降水的总体扩散,同时产生了现实的对流结构。在强强迫下,该方案的效果可以忽略不计,正如设计所预期的那样。概率验证表明,其他变量的预测技能也有所提高,尤其是技能扩展比,但确定了该方法进一步改进的起点。这篇文章受版权保护。保留所有权利。
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Physically based stochastic perturbations improve high‐resolution forecast of convection
The physically based stochastic perturbation scheme PSP has been implemented in the convection‐permitting ICON‐D2 ensemble prediction system at DWD and run for a three‐month trial experiment in summer 2021. The scheme mimics the impact of boundary layer turbulence on the smallest resolved scales and impacts in particular convective precipitation. A weather regime‐dependent systematic evaluation shows that PSP efficiently increases ensemble spread of precipitation in weak synoptic forcing, while producing realistic convective structures. During strong forcing, the effect of the scheme is negligible, as expected by design. The probabilistic verification shows improvements in the forecast skill of other variables as well, especially the spread to skill ratio, but identifies starting points for further improvements of the method.This article is protected by copyright. All rights reserved.
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来源期刊
CiteScore
16.80
自引率
4.50%
发文量
163
审稿时长
3-8 weeks
期刊介绍: The Quarterly Journal of the Royal Meteorological Society is a journal published by the Royal Meteorological Society. It aims to communicate and document new research in the atmospheric sciences and related fields. The journal is considered one of the leading publications in meteorology worldwide. It accepts articles, comprehensive review articles, and comments on published papers. It is published eight times a year, with additional special issues. The Quarterly Journal has a wide readership of scientists in the atmospheric and related fields. It is indexed and abstracted in various databases, including Advanced Polymers Abstracts, Agricultural Engineering Abstracts, CAB Abstracts, CABDirect, COMPENDEX, CSA Civil Engineering Abstracts, Earthquake Engineering Abstracts, Engineered Materials Abstracts, Science Citation Index, SCOPUS, Web of Science, and more.
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