Potential predictability of Northern America surface temperature in AGCMs and CGCMs
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| 008 | 210128e20150701xx s 000 0 eng | ||
| 024 | 7 | 0 | |a 10.1007/s00382-014-2335-x |2 doi |
| 035 | |a (NATIONALLICENCE)springer-10.1007/s00382-014-2335-x | ||
| 245 | 0 | 0 | |a Potential predictability of Northern America surface temperature in AGCMs and CGCMs |h [Elektronische Daten] |c [Youmin Tang, Dake Chen, Xiaoqin Yan] |
| 520 | 3 | |a In this study, the potential predictability of the Northern America (NA) surface air temperature (SAT) was explored using an information-based predictability framework and two multiple model ensemble products: a one-tier prediction by coupled models (T1), and a two-tier prediction by atmospheric models only (T2). Furthermore, the potential predictability was optimally decomposed into different modes for both T1 and T2, by extracting the most predictable structures. Emphasis was placed on the comparison of the predictability between T1 and T2. It was found that the potential predictability of the NA SAT is seasonal and spatially dependent in both T1 and T2. Higher predictability occurs in spring and winter and over the southeastern US and northwestern Canada. There is no significant difference of potential predictability between T1 and T2 for most areas of NA, although T1 has higher potential predictability than T2 in the southeastern US. Both T1 and T2 display similar most predictable components (PrCs) for the NA SAT, characterized by the inter-annual variability mode and the long-term trend mode. The first one is inherent to the tropical Pacific sea surface temperature forcing, such as the El Nino-Southern Oscillation, whereas the second one is closely associated with global warming. In general, the PrC modes can better characterize the predictability in T1 than in T2, in particular for the inter-annual variability mode in the fall. The prediction skill against observations is better measured by the PrC analysis than by principal component analysis for all seasons, indicating the stronger capability of PrCA in extractingprediction targets. | |
| 540 | |a Springer-Verlag Berlin Heidelberg, 2014 | ||
| 690 | 7 | |a Seasonal climate prediction |2 nationallicence | |
| 690 | 7 | |a Potential predictability |2 nationallicence | |
| 690 | 7 | |a Ensemble predictions |2 nationallicence | |
| 700 | 1 | |a Tang |D Youmin |u Environmental Science and Engineering, University of Northern British Columbia, 3333 University Way, V2N 4Z9, Prince George, BC, Canada |4 aut | |
| 700 | 1 | |a Chen |D Dake |u State Key Laboratory of Satellite Ocean Environment Dynamics, Hangzhou, China |4 aut | |
| 700 | 1 | |a Yan |D Xiaoqin |u Environmental Science and Engineering, University of Northern British Columbia, 3333 University Way, V2N 4Z9, Prince George, BC, Canada |4 aut | |
| 773 | 0 | |t Climate Dynamics |d Springer Berlin Heidelberg |g 45/1-2(2015-07-01), 353-374 |x 0930-7575 |q 45:1-2<353 |1 2015 |2 45 |o 382 | |
| 856 | 4 | 0 | |u https://doi.org/10.1007/s00382-014-2335-x |q text/html |z Onlinezugriff via DOI |
| 898 | |a BK010053 |b XK010053 |c XK010000 | ||
| 900 | 7 | |a Metadata rights reserved |b Springer special CC-BY-NC licence |2 nationallicence | |
| 908 | |D 1 |a research-article |2 jats | ||
| 949 | |B NATIONALLICENCE |F NATIONALLICENCE |b NL-springer | ||
| 950 | |B NATIONALLICENCE |P 856 |E 40 |u https://doi.org/10.1007/s00382-014-2335-x |q text/html |z Onlinezugriff via DOI | ||
| 950 | |B NATIONALLICENCE |P 700 |E 1- |a Tang |D Youmin |u Environmental Science and Engineering, University of Northern British Columbia, 3333 University Way, V2N 4Z9, Prince George, BC, Canada |4 aut | ||
| 950 | |B NATIONALLICENCE |P 700 |E 1- |a Chen |D Dake |u State Key Laboratory of Satellite Ocean Environment Dynamics, Hangzhou, China |4 aut | ||
| 950 | |B NATIONALLICENCE |P 700 |E 1- |a Yan |D Xiaoqin |u Environmental Science and Engineering, University of Northern British Columbia, 3333 University Way, V2N 4Z9, Prince George, BC, Canada |4 aut | ||
| 950 | |B NATIONALLICENCE |P 773 |E 0- |t Climate Dynamics |d Springer Berlin Heidelberg |g 45/1-2(2015-07-01), 353-374 |x 0930-7575 |q 45:1-2<353 |1 2015 |2 45 |o 382 | ||