Ensemble characteristics of an analog ensemble (AE) system for simultaneous prediction of multiple surface meteorological variables at local scale

IF 1.9 4区 地球科学 Q3 METEOROLOGY & ATMOSPHERIC SCIENCES
Navdeep Batolar, Dan Singh, Mukesh Kumar
{"title":"Ensemble characteristics of an analog ensemble (AE) system for simultaneous prediction of multiple surface meteorological variables at local scale","authors":"Navdeep Batolar, Dan Singh, Mukesh Kumar","doi":"10.1007/s00703-024-01029-9","DOIUrl":null,"url":null,"abstract":"<p>Ensemble characteristics of a 10-member analog ensemble (AE) system for simultaneous prediction of six surface meteorological variables are examined at six station locations in the north-west Himalaya (NWH), India for lead times, 0 h (0 h)[d0], 24 h (d1), 48 h (d2) and 72 h (d3). The maximum (MMX), minimum (MNX) and mean (ME) values of each variable in analog days are found to exhibit statistically significant positive correlations with their corresponding observations at each station location for d0 through d3. The MEs of the variables are found to reproduce statistics (temporal mean, temporal standard deviation), empirical distributions of the observations on the variables reasonably well, and the MEs of the variables exhibit reasonable values of the RMSEs for d0 through d3. The observations on each variable and multiple variables simultaneously fall within their ranges (MMXs, MNXs) in ensemble members for maximum number of days for all lead times. The AE system is found to exhibit high spatial and temporal consistency in its predictive characteristics at six station locations in the NWH. Despite our short length data, these results are very interesting and suggest practical utility of the AE system for simultaneous prediction of variables at local scale utilizing local scale surface meteorological observations. Similar studies on various other types of ensemble systems can help to assess their practical utility for various forecasting applications.</p>","PeriodicalId":51132,"journal":{"name":"Meteorology and Atmospheric Physics","volume":null,"pages":null},"PeriodicalIF":1.9000,"publicationDate":"2024-09-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Meteorology and Atmospheric Physics","FirstCategoryId":"89","ListUrlMain":"https://doi.org/10.1007/s00703-024-01029-9","RegionNum":4,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"METEOROLOGY & ATMOSPHERIC SCIENCES","Score":null,"Total":0}
引用次数: 0

Abstract

Ensemble characteristics of a 10-member analog ensemble (AE) system for simultaneous prediction of six surface meteorological variables are examined at six station locations in the north-west Himalaya (NWH), India for lead times, 0 h (0 h)[d0], 24 h (d1), 48 h (d2) and 72 h (d3). The maximum (MMX), minimum (MNX) and mean (ME) values of each variable in analog days are found to exhibit statistically significant positive correlations with their corresponding observations at each station location for d0 through d3. The MEs of the variables are found to reproduce statistics (temporal mean, temporal standard deviation), empirical distributions of the observations on the variables reasonably well, and the MEs of the variables exhibit reasonable values of the RMSEs for d0 through d3. The observations on each variable and multiple variables simultaneously fall within their ranges (MMXs, MNXs) in ensemble members for maximum number of days for all lead times. The AE system is found to exhibit high spatial and temporal consistency in its predictive characteristics at six station locations in the NWH. Despite our short length data, these results are very interesting and suggest practical utility of the AE system for simultaneous prediction of variables at local scale utilizing local scale surface meteorological observations. Similar studies on various other types of ensemble systems can help to assess their practical utility for various forecasting applications.

Abstract Image

模拟集合(AE)系统的集合特征,用于在局部范围内同时预测多个地表气象变量
在印度喜马拉雅山西北部(NWH)的六个台站位置,研究了一个由 10 个成员组成的模拟集合(AE)系统的集合特征,以同时预测六个地表气象变量,前导时间分别为 0 小时(0 h)[d0]、24 小时(d1)、48 小时(d2)和 72 小时(d3)。在模拟日中,每个变量的最大值(MMX)、最小值(MNX)和平均值(ME)在统计上与每个站点在 d0 至 d3 期间的相应观测值呈显著正相关。变量的 ME 值合理地再现了变量观测值的统计量(时间平均值、时间标准偏差)和经验 分布,变量的 ME 值在 d0 至 d3 显示出合理的均方根误差值。在所有提前期的最长天数中,每个变量和多个变量的观测值同时落在集合成员的范围内(MMXs、MNXs)。研究发现,AE 系统在西北高原六个站点的预测特征具有高度的时空一致性。尽管我们的数据长度较短,但这些结果非常有趣,表明 AE 系统在利用当地尺度的地表气象观测数据同时预测当地尺度的变量方面具有实用价值。对其他各种类型的集合系统进行类似研究,有助于评估它们在各种预报应用中的实际效用。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 求助全文
来源期刊
Meteorology and Atmospheric Physics
Meteorology and Atmospheric Physics 地学-气象与大气科学
CiteScore
4.00
自引率
5.00%
发文量
87
审稿时长
6-12 weeks
期刊介绍: Meteorology and Atmospheric Physics accepts original research papers for publication following the recommendations of a review panel. The emphasis lies with the following topic areas: - atmospheric dynamics and general circulation; - synoptic meteorology; - weather systems in specific regions, such as the tropics, the polar caps, the oceans; - atmospheric energetics; - numerical modeling and forecasting; - physical and chemical processes in the atmosphere, including radiation, optical effects, electricity, and atmospheric turbulence and transport processes; - mathematical and statistical techniques applied to meteorological data sets Meteorology and Atmospheric Physics discusses physical and chemical processes - in both clear and cloudy atmospheres - including radiation, optical and electrical effects, precipitation and cloud microphysics.
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信