DOI: 10.1007/s00382-017-3962-9
Scopus记录号: 2-s2.0-85033463469
论文题名: Different types of drifts in two seasonal forecast systems and their dependence on ENSO
作者: Hermanson L. ; Ren H.-L. ; Vellinga M. ; Dunstone N.D. ; Hyder P. ; Ineson S. ; Scaife A.A. ; Smith D.M. ; Thompson V. ; Tian B. ; Williams K.D.
刊名: Climate Dynamics
ISSN: 9307575
出版年: 2018
卷: 51, 期: 4 起始页码: 1411
结束页码: 1426
语种: 英语
英文关键词: Bias
; Drift
; ENSO
; General circulation model
; Seasonal prediction
Scopus关键词: atmospheric general circulation model
; climate modeling
; climate prediction
; El Nino-Southern Oscillation
; precipitation (climatology)
; sea surface temperature
; seasonal variation
; weather forecasting
英文摘要: Seasonal forecasts using coupled ocean–atmosphere climate models are increasingly employed to provide regional climate predictions. For the quality of forecasts to improve, regional biases in climate models must be diagnosed and reduced. The evolution of biases as initialized forecasts drift away from the observations is poorly understood, making it difficult to diagnose the causes of climate model biases. This study uses two seasonal forecast systems to examine drifts in sea surface temperature (SST) and precipitation, and compares them to the long-term bias in the free-running version of each model. Drifts are considered from daily to multi-annual time scales. We define three types of drift according to their relation with the long-term bias in the free-running model: asymptoting, overshooting and inverse drift. We find that precipitation almost always has an asymptoting drift. SST drifts on the other hand, vary between forecasting systems, where one often overshoots and the other often has an inverse drift. We find that some drifts evolve too slowly to have an impact on seasonal forecasts, even though they are important for climate projections. The bias found over the first few days can be very different from that in the free-running model, so although daily weather predictions can sometimes provide useful information on the causes of climate biases, this is not always the case. We also find that the magnitude of equatorial SST drifts, both in the Pacific and other ocean basins, depends on the El Niño Southern Oscillation (ENSO) phase. Averaging over all hindcast years can therefore hide the details of ENSO state dependent drifts and obscure the underlying physical causes. Our results highlight the need to consider biases across a range of timescales in order to understand their causes and develop improved climate models. © 2017, The Author(s). Citation statistics:
资源类型: 期刊论文
标识符: http://119.78.100.158/handle/2HF3EXSE/109204
Appears in Collections: 影响、适应和脆弱性 气候变化事实与影响
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作者单位: Met Office, Exeter, United Kingdom; China Meteorological Agency, Beijing, China
Recommended Citation:
Hermanson L.,Ren H.-L.,Vellinga M.,et al. Different types of drifts in two seasonal forecast systems and their dependence on ENSO[J]. Climate Dynamics,2018-01-01,51(4)