globalchange  > 气候变化事实与影响
DOI: doi:10.1038/nclimate2492
论文题名:
Increased frequency of extreme La Niña events under greenhouse warming
作者: Wenju Cai
刊名: Nature Climate Change
ISSN: 1758-1053X
EISSN: 1758-7173
出版年: 2015-01-26
卷: Volume:5, 页码:Pages:132;137 (2015)
语种: 英语
英文关键词: Atmospheric dynamics ; Physical oceanography ; Projection and prediction ; Environmental health
英文摘要:

The El Niño/Southern Oscillation is Earths most prominent source of interannual climate variability, alternating irregularly between El Niño and La Niña, and resulting in global disruption of weather patterns, ecosystems, fisheries and agriculture1, 2, 3, 4, 5. The 1998–1999 extreme La Niña event that followed the 1997–1998 extreme El Niño event6 switched extreme El Niño-induced severe droughts to devastating floods in western Pacific countries, and vice versa in the southwestern United States4, 7. During extreme La Niña events, cold sea surface conditions develop in the central Pacific8, 9, creating an enhanced temperature gradient from the Maritime continent to the central Pacific. Recent studies have revealed robust changes in El Niño characteristics in response to simulated future greenhouse warming10, 11, 12, but how La Niña will change remains unclear. Here we present climate modelling evidence, from simulations conducted for the Coupled Model Intercomparison Project phase 5 (ref. 13), for a near doubling in the frequency of future extreme La Niña events, from one in every 23 years to one in every 13 years. This occurs because projected faster mean warming of the Maritime continent than the central Pacific, enhanced upper ocean vertical temperature gradients, and increased frequency of extreme El Niño events are conducive to development of the extreme La Niña events. Approximately 75% of the increase occurs in years following extreme El Niño events, thus projecting more frequent swings between opposite extremes from one year to the next.

During typical La Niña events, the central-to-eastern equatorial Pacific is colder than normal, inhibiting formation of rain-producing clouds there, but enhancing atmospheric convection and rainfall in the western equatorial Pacific. The associated atmospheric circulation generates extreme weather events in many parts of the world, including droughts in the southwestern United States1, 14 and eastern equatorial Pacific regions, floods in the western Pacific and central American countries1, 15, and increased land-falling west Pacific cyclones and Atlantic hurricanes2, 16, 17.

La Niña-related sea surface temperate (SST) anomaly patterns, however, differ from event to event (Fig. 1a, b). Compared with the weak event of 1995, cold anomalies of the 1998 extreme event peaked notably farther west, and exerted much greater impacts. During 1998, extreme events occurred, in part linked to the developing 1998–1999 La Niña event. The southwestern United States experienced one of the most severe droughts in history4, 7, 18. Venezuela endured flash flooding and landslides that killed 25,000 to 50,000 people19. In China, river floods and storms led to the death of thousands, and displaced over 200 million people20. Bangladesh experienced one of the most destructive flooding events in modern history, with over 50% of the countrys land area flooded, leading to severe food shortages and the spread of waterborne epidemic diseases, killing several thousand people and affecting over 30 million more21, 22, 23. The 1998 North Atlantic hurricane season saw one of the deadliest and strongest hurricanes (Mitch) in the historical record4, claiming more than 11,000 lives in Honduras and Nicaragua24.

Figure 1: Identification of observed extreme La Niña events.
Identification of observed extreme La Nina events.

a,b, December–February average SST anomalies (shading, −0.75 °C contour highlighted by a black curve) and surface wind stress anomalies (vectors, scale shown in the top right corner of each panel) associated with a weak (a) and extreme (b) La Niña. c,d, Principal variability patterns of SST obtained by applying EOF analysis to satellite-era SST anomalies (see Methods), in the equatorial region (15° S–15° N, 140° E–280° E). The SST anomalies and wind stress vectors are presented as linear regression onto the EOF time series. e, Relationship between the two principal component time series. An extreme La Niña event (blue dots, big blue 1998) can be defined as when the first and second principal component are both greater than 1.0 standard deviation (s.d.). Extreme El Niño events are indicated by red dots. Green dots indicate moderate La Niña, and purple dots weak La Niña (big purple 1995), defined as when quadratically detrended Niño4 is greater than 0.5 s.d. but less than 1.0 s.d. in amplitude. Black dots indicate all other years. f, Relationship between Niño4 and a time series of the Maritime continent region (5° S–5° N, 100° E–125° E)–central Pacific (Niño4, 5° S–5° N, 160° E–150° W) surface temperature gradient, with a correlation coefficient of r = −0.93. Colours are the same as in e.

EOF analysis and characterization of extreme La Niña events.

EOF analysis was applied to observed SST anomalies, referenced to the long-term mean since 1979, in an equatorial domain (15° S–15° N, 140° E–80° W). The extreme La Niña events were diagnosed using a suite of distinct process-based indicators associated with the two EOFs, such as low temperature, low rainfall and wind anomalies. In particular, the SST anomalies are centred at the central Pacific during extreme La Niña, as opposed to the eastern equatorial Pacific during extreme El Niño. The difference in spatial patterns is captured by a different combination of two principal variability patterns. EOF1 reflects a canonical La Niña pattern embedded in the commonly used Niño3 index, featuring cool and dry anomalies extending from the eastern equatorial Pacific to the central Pacific. EOF2 resembles the La Niña Modoki pattern26, featuring cool and dry anomalies in the central Pacific, but warm and wet anomalies in the far western equatorial Pacific. Thus, an extreme La Niña is an appropriately weighted superposition of the two patterns, giving rise to an anomaly centred in the central Pacific. As such, a depiction of extreme La Niña must use a different index from that for extreme El Niño, and we show that an average of SST anomalies over the Niño4 region is an appropriate index.

Model selection and analysis.

We used 21 CMIP5 coupled global climate models (CGCMs; Supplementary Table 1) forced with historical anthropogenic and natural forcings, and future greenhouse gases under the Representative Concentration Pathway 8.5 (ref. 13) emission scenario, covering a 200-year period. These were chosen from a total of 32 models, on the basis of their ability to simulate extreme La Niña events (Supplementary Table 1). As extreme La Niña tends to occur after extreme El Niño, we select models that are also able to simulate extreme El Niño. These were selected in terms of two features10: the positive skewness of rainfall anomalies, and the ability to generate rainfall greater than 5 mm d−1 over the eastern equatorial Pacific. Only a subgroup of CGCMs simulate the observed nonlinear ocean–atmosphere coupling that characterizes extreme El Niño, as depicted by the positive skewness of rainfall anomalies over the eastern equatorial Pacific during austral summer (December–February), which is 2.7 in observations since 1979. The level of nonlinearity varies vastly among CGCMs, and we considered positive skewness of 1 as our threshold. Out of the 32 CGCMs, 21 models satisfy the rainfall skewness criterion. The selected CGCMs yield a mean skewness of 2.6, close to the observed value of 2.7 (Supplementary Table 1).

All 21 selected CGCMs reproduce the observed extreme La Niña pattern. Before the analysis, data were interpolated onto a common grid of 1.5° latitude by 1.5° longitude. As for the observations, EOF analysis was carried out for each individual model using SST anomalies referenced to the mean over the Control period. All 21 models produce the nonlinear relationship between the two leading EOFs, indicating their ability to generate the nonlinear equatorial positive feedback associated with extreme La Niña events. On the basis of analysis of observed SSTs, we used a quadratically detrended Niño4 index over the full 200-year period to describe La Niña events. Applying quadratical detrending over each of the periods separately yields almost identical results.

We tested the sensitivity of our results to varying threshold values for Niño4 (Supplementary Table 1). We also tested our results using a negative Niño4 SST skewness (Supplementary Text and Table 2), as observations show a negative skewness of −0.44 (using data since 1979). In all cases, including using all available models (Supplementary Text), there is an increase in the occurrences of extreme La Niña events from the Control to the Climate Change period, with a strong inter-model consensus.

Statistical significance test.

We used a bootstrap method to examine whether the increased frequency is statistically significant. The 2,100 samples from the 21 models in the Control period were re-sampled randomly to construct 10,000 realizations of 2,100-year records. In the random re-sampling process, any extreme La Niña event is allowed to be selected again. The standard deviation of the extreme La Niña frequency using a threshold value of Niño4 amplitude greater than 1.75 s.d. in the inter-realization is 9.4 events per 2,100 years, far smaller than the difference of 67 events per 2,100 years between the Climate Change and the Control periods. Using a threshold value of Niño4 amplitude greater than 1.5 s.d. in the inter-realization yields 12 events per 2,100 years, also far smaller than the difference of 65 events per 2,100 years between the Climate Change and the Control periods (Fig. 3a, b), indicating strong statistical significance. Using a threshold value of Niño4 amplitude greater than 2.0 s.d. again shows a strong significance. Increasing the realizations to 20,000 or 30,000 in the bootstrapping methodology yields essentially identical results.

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  3. Changnon, S. A. Impacts of 1997–98 El Niño generated weather in the United States. Bull. Am. Meteorol. Soc. 80, 18191827 (1999).
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  5. McPhaden, M. J., Zebiak, S. E. & Glantz, M. H. ENSO as an integrating concept in Earth science. Science 314, 17401745 (2006).
  6. McPhaden, M. J. El Niño: The child prodigy of 1997–98. Nature 398, 559562 (1999).
  7. Hoerling, M. & Kumar, A. The perfect ocean for drought. Science 299, 691694 (2003). URL:
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资源类型: 期刊论文
标识符: http://119.78.100.158/handle/2HF3EXSE/4881
Appears in Collections:气候变化事实与影响
科学计划与规划
气候变化与战略

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Wenju Cai. Increased frequency of extreme La Niña events under greenhouse warming[J]. Nature Climate Change,2015-01-26,Volume:5:Pages:132;137 (2015).
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