globalchange  > 气候变化事实与影响
DOI: 10.1175/JCLI-D-13-00597.1
Scopus记录号: 2-s2.0-84925991639
论文题名:
Predictability and forecast skill in NMME
作者: Becker E.; Van den Dool H.; Zhang Q.
刊名: Journal of Climate
ISSN: 8948755
出版年: 2014
卷: 27, 期:15
起始页码: 5891
结束页码: 5906
语种: 英语
Scopus关键词: Atmospheric temperature ; Mean square error ; Oceanography ; Submarine geophysics ; Surface properties ; Surface waters ; Anomaly correlations ; Individual models ; Interannual variability ; Multi-model ensemble ; Precipitation rates ; Root mean square errors ; Sea surface temperature (SST) ; Seasonal variation ; Forecasting
英文摘要: Forecast skill and potential predictability of 2-m temperature, precipitation rate, and sea surface temperature are assessed using 29 yr of hindcast data from models included in phase 1 of the North American Multimodel Ensemble (NMME) project. Forecast skill is examined using the anomaly correlation (AC); skill of the bias-corrected ensemble means (EMs) of the individual models and of the NMME 7-model EM are verified against the observed value. Forecast skill is also assessed using the root-mean-square error. The models' representation of the size of forecast anomalies is also studied. Predictability was considered from two angles: homogeneous, where one model is verified against a single member from its own ensemble, and heterogeneous, where a model'sEMis compared to a single member from another model. This study provides insight both into the physical predictability of the three fields and into theNMMEand its contributing models. Most of the models in the NMME have fairly realistic spread, as represented by the interannual variability. The NMME 7-model forecast skill, verified against observations, is equal to or higher than the individual models' forecast ACs. Two-meter temperature (T2m) skill matches the highest single-model skill, while precipitation rate and sea surface temperature NMME EM skill is higher than for any single model. Homogeneous predictability is higher than reported skill in all fields, suggesting there may be room for some improvement in model prediction, although there are many regional and seasonal variations. The estimate of potential predictability is not overly sensitive to the choice of model. In general, models with higher homogeneous predictability show higher forecast skill. © 2014 American Meteorological Society.
Citation statistics:
资源类型: 期刊论文
标识符: http://119.78.100.158/handle/2HF3EXSE/51321
Appears in Collections:气候变化事实与影响

Files in This Item:

There are no files associated with this item.


作者单位: NOAA/NWS/NCEP/Climate Prediction Center, College Park, MD, United States

Recommended Citation:
Becker E.,Van den Dool H.,Zhang Q.. Predictability and forecast skill in NMME[J]. Journal of Climate,2014-01-01,27(15)
Service
Recommend this item
Sava as my favorate item
Show this item's statistics
Export Endnote File
Google Scholar
Similar articles in Google Scholar
[Becker E.]'s Articles
[Van den Dool H.]'s Articles
[Zhang Q.]'s Articles
百度学术
Similar articles in Baidu Scholar
[Becker E.]'s Articles
[Van den Dool H.]'s Articles
[Zhang Q.]'s Articles
CSDL cross search
Similar articles in CSDL Cross Search
[Becker E.]‘s Articles
[Van den Dool H.]‘s Articles
[Zhang Q.]‘s Articles
Related Copyright Policies
Null
收藏/分享
所有评论 (0)
暂无评论
 

Items in IR are protected by copyright, with all rights reserved, unless otherwise indicated.