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DOI | 10.1007/s00382-016-3296-z |
Assessing North American multimodel ensemble (NMME) seasonal forecast skill to assist in the early warning of anomalous hydrometeorological events over East Africa | |
Shukla, Shraddhanand1; Roberts, Jason2; Hoell, Andrew3; Funk, Christopher C.1,4; Robertson, Franklin2; Kirtman, Ben5 | |
2019-12-01 | |
发表期刊 | CLIMATE DYNAMICS |
ISSN | 0930-7575 |
EISSN | 1432-0894 |
出版年 | 2019 |
卷号 | 53期号:12页码:7411-7427 |
文章类型 | Article |
语种 | 英语 |
国家 | USA |
英文摘要 | The skill of North American multimodel ensemble (NMME) seasonal forecasts in East Africa (EA), which encompasses one of the most food and water insecure areas of the world, is evaluated using deterministic, categorical, and probabilistic evaluation methods. The skill is estimated for all three primary growing seasons: March-May (MAM), July-September (JAS), and October-December (OND). It is found that the precipitation forecast skill in this region is generally limited and statistically significant over only a small part of the domain. In the case of MAM (JAS) [OND] season it exceeds the skill of climatological forecasts in parts of equatorial EA (Northern Ethiopia) [equatorial EA] for up to 2 (5) [5] months lead. Temperature forecast skill is generally much higher than precipitation forecast skill (in terms of deterministic and probabilistic skill scores) and statistically significant over a majority of the region. Over the region as a whole, temperature forecasts also exhibit greater reliability than the precipitation forecasts. The NMME ensemble forecasts are found to be more skillful and reliable than the forecast from any individual model. The results also demonstrate that for some seasons (e.g. JAS), the predictability of precipitation signals varies and is higher during certain climate events (e.g. ENSO). Finally, potential room for improvement in forecast skill is identified in some models by comparing homogeneous predictability in individual NMME models with their respective forecast skill. |
领域 | 气候变化 |
收录类别 | SCI-E |
WOS记录号 | WOS:000495247200018 |
WOS关键词 | SPATIAL-ANALYSIS ; RAINFALL ; PREDICTION ; DROUGHT ; TRENDS ; HORN ; PREDICTABILITY ; VARIABILITY ; PACIFIC |
WOS类目 | Meteorology & Atmospheric Sciences |
WOS研究方向 | Meteorology & Atmospheric Sciences |
引用统计 | |
文献类型 | 期刊论文 |
条目标识符 | http://119.78.100.173/C666/handle/2XK7JSWQ/224300 |
专题 | 环境与发展全球科技态势 |
作者单位 | 1.Univ Calif Santa Barbara, Climate Hazards Grp, Dept Geog, Santa Barbara, CA 93106 USA; 2.NASA, Marshall Space Flight Ctr, Huntsville, AL 35812 USA; 3.NOAA, Phys Sci Div, Earth Syst Res Lab, Boulder, CO USA; 4.US Geol Survey, EROS, Garretson, SD USA; 5.Univ Miami, Miami, FL USA |
推荐引用方式 GB/T 7714 | Shukla, Shraddhanand,Roberts, Jason,Hoell, Andrew,et al. Assessing North American multimodel ensemble (NMME) seasonal forecast skill to assist in the early warning of anomalous hydrometeorological events over East Africa[J]. CLIMATE DYNAMICS,2019,53(12):7411-7427. |
APA | Shukla, Shraddhanand,Roberts, Jason,Hoell, Andrew,Funk, Christopher C.,Robertson, Franklin,&Kirtman, Ben.(2019).Assessing North American multimodel ensemble (NMME) seasonal forecast skill to assist in the early warning of anomalous hydrometeorological events over East Africa.CLIMATE DYNAMICS,53(12),7411-7427. |
MLA | Shukla, Shraddhanand,et al."Assessing North American multimodel ensemble (NMME) seasonal forecast skill to assist in the early warning of anomalous hydrometeorological events over East Africa".CLIMATE DYNAMICS 53.12(2019):7411-7427. |
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