波兰选定的短期和长期数值天气预报模式的气温预报精度

Pub Date : 2018-01-01 DOI:10.15233/GFZ.2018.35.5
Sebastian Kendzierski, B. Czernecki, Leszek Kolendowicz, A. Jaczewski
{"title":"波兰选定的短期和长期数值天气预报模式的气温预报精度","authors":"Sebastian Kendzierski, B. Czernecki, Leszek Kolendowicz, A. Jaczewski","doi":"10.15233/GFZ.2018.35.5","DOIUrl":null,"url":null,"abstract":"The article discusses the results of air temperature forecasts from four short-term and two long-term forecasts of numerical weather prediction models. The analysis covered the results of model simulations from January 2015 to January 2016 and compared them at 14 meteorological stations in Poland. The comparison was made based on the most commonly used measures for continuous parameters i.e., ME (mean error), MAE (mean absolute error), RMSE (root mean square error), MSE (mean square error), BIAS and Pearson correlation. In the short time horizon, the best results in the context of the MAE, RMSE, MSE and correlation values were obtained by the Unified Model, although the diagnosed differences between the models are small. All models in the 0–72 h projection horizon reached a correlation of 0.95–0.97 and an MAE in the range of 1.5 °C to 2.1 °C. In the case of long-term forecasts, the HIRLAM model was slightly better than the GFS model. Clearly, in both cases, there is a marked decrease in quality after the fourth and in the following forecast lead days.","PeriodicalId":0,"journal":{"name":"","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2018-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"11","resultStr":"{\"title\":\"Air temperature forecasts' accuracy of selected short-term and long-term numerical weather prediction models over Poland\",\"authors\":\"Sebastian Kendzierski, B. Czernecki, Leszek Kolendowicz, A. Jaczewski\",\"doi\":\"10.15233/GFZ.2018.35.5\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The article discusses the results of air temperature forecasts from four short-term and two long-term forecasts of numerical weather prediction models. The analysis covered the results of model simulations from January 2015 to January 2016 and compared them at 14 meteorological stations in Poland. The comparison was made based on the most commonly used measures for continuous parameters i.e., ME (mean error), MAE (mean absolute error), RMSE (root mean square error), MSE (mean square error), BIAS and Pearson correlation. In the short time horizon, the best results in the context of the MAE, RMSE, MSE and correlation values were obtained by the Unified Model, although the diagnosed differences between the models are small. All models in the 0–72 h projection horizon reached a correlation of 0.95–0.97 and an MAE in the range of 1.5 °C to 2.1 °C. In the case of long-term forecasts, the HIRLAM model was slightly better than the GFS model. Clearly, in both cases, there is a marked decrease in quality after the fourth and in the following forecast lead days.\",\"PeriodicalId\":0,\"journal\":{\"name\":\"\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":0.0,\"publicationDate\":\"2018-01-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"11\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"\",\"FirstCategoryId\":\"89\",\"ListUrlMain\":\"https://doi.org/10.15233/GFZ.2018.35.5\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"","FirstCategoryId":"89","ListUrlMain":"https://doi.org/10.15233/GFZ.2018.35.5","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 11

摘要

本文讨论了数值天气预报模式的4种短期预报和2种长期预报的气温预报结果。该分析涵盖了2015年1月至2016年1月的模式模拟结果,并对波兰14个气象站的模拟结果进行了比较。比较基于连续参数最常用的测量方法,即ME(平均误差)、MAE(平均绝对误差)、RMSE(均方根误差)、MSE(均方误差)、BIAS和Pearson相关。在短时间范围内,统一模型在MAE、RMSE、MSE和相关值的背景下获得了最好的结果,尽管模型之间的诊断差异很小。所有模式在0 ~ 72 h投影水平的相关系数为0.95 ~ 0.97,MAE在1.5 ~ 2.1℃范围内。在长期预报方面,HIRLAM模式略优于GFS模式。很明显,在这两种情况下,在第四天和接下来的预测提前日之后,质量都明显下降。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
Air temperature forecasts' accuracy of selected short-term and long-term numerical weather prediction models over Poland
The article discusses the results of air temperature forecasts from four short-term and two long-term forecasts of numerical weather prediction models. The analysis covered the results of model simulations from January 2015 to January 2016 and compared them at 14 meteorological stations in Poland. The comparison was made based on the most commonly used measures for continuous parameters i.e., ME (mean error), MAE (mean absolute error), RMSE (root mean square error), MSE (mean square error), BIAS and Pearson correlation. In the short time horizon, the best results in the context of the MAE, RMSE, MSE and correlation values were obtained by the Unified Model, although the diagnosed differences between the models are small. All models in the 0–72 h projection horizon reached a correlation of 0.95–0.97 and an MAE in the range of 1.5 °C to 2.1 °C. In the case of long-term forecasts, the HIRLAM model was slightly better than the GFS model. Clearly, in both cases, there is a marked decrease in quality after the fourth and in the following forecast lead days.
求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
×
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
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 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 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1