Diagnosing Secular Variations in Retrospective ENSO Seasonal Forecast Skill Using CMIP5 Model-Analogs

被引：44

作者：

Ding, Hui ^{[1
,2
]}

Newman, Matthew ^{[1
,2
]}

Alexander, Michael A. ^{[2
]}

Wittenberg, Andrew T. ^{[3
]}

机构：

[1] Univ Colorado, CIRES, Boulder, CO 80309 USA

[2] NOAA, Earth Syst Res Lab, Boulder, CO 80305 USA

[3] NOAA, Geophys Fluid Dynam Lab, Princeton, NJ USA

来源：

GEOPHYSICAL RESEARCH LETTERS | 2019年 / 46卷 / 03期

关键词：

EL-NINO; OCEAN; PREDICTABILITY; TEMPERATURE; MODULATION; PREDICTION;

D O I：

10.1029/2018GL080598

中图分类号：

P [天文学、地球科学];

学科分类号：

07 ;

摘要：

Retrospective tropical Indo-Pacific forecasts for 1961-2015 are made using 28 models from the fifth phase of the Coupled Model Intercomparison Project (CMIP5) plus four models from the North American Multi-Model Ensemble (NMME), using a model-analog technique. Forecast ensembles are extracted from preexisting model simulations, by finding those states that initially best match an observed anomaly and tracking their subsequent evolution, requiring no additional model integrations. Model-analog forecasts from the 10 "best" CMIP5 models have skill for sea surface temperature and precipitation comparable to that of both the NMME model-analog forecast ensemble and (since 1982) traditional assimilation-initialized NMME hindcasts. The El Nino-Southern Oscillation (ENSO) forecast skill has no trend over the 55-year period, and its decadal variations appear largely random, although the skill does improve during epochs of increased ENSO activity. Including the CMIP5-projected effects of external radiative forcings improves the tropical sea surface temperature skill of the model-analog forecasts but not within the ENSO region.

引用

页码：1721 / 1730

页数：10

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