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Yan Xue, Mingyue Chen, Arun Kumar, Zeng-Zhen Hu, and Wanqiu Wang

Abstract

The prediction skill and bias of tropical Pacific sea surface temperature (SST) in the retrospective forecasts of the Climate Forecast System, version 2 (CFSv2), of the National Centers for Environmental Prediction were examined. The CFSv2 was initialized from the Climate Forecast System Reanalysis (CFSR) over 1982–2010. There was a systematic cold bias in the central–eastern equatorial Pacific during summer/fall. The cold bias in the Niño-3.4 index was about −2.5°C in summer/fall before 1999 but suddenly changed to −1°C around 1999, related to a sudden shift in the trade winds and equatorial subsurface temperature in the CFSR.

The SST anomaly (SSTA) was computed by removing model climatology for the periods 1982–98 and 1999–2010 separately. The standard deviation (STD) of forecast SSTA agreed well with that of observations in 1982–98, but in 1999–2010 it was about 200% too strong in the eastern Pacific and 50% too weak near the date line during winter/spring. The shift in STD bias was partially related to change of ENSO characteristics: central Pacific (CP) El Niños were more frequent than eastern Pacific (EP) El Niños after 2000. The composites analysis shows that the CFSv2 had a tendency to delay the onset phase of the EP El Niños in the 1980s and 1990s but predicted their decay phases well. In contrast, the CFSv2 predicted the onset phase of the CP El Niños well but prolonged their decay phase. The hit rate for both El Niño and La Niña was lower in the later period than in the early period, and the false alarm for La Niña increased appreciably from the early to the later period.

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Arun Kumar, Hui Wang, Wanqiu Wang, Yan Xue, and Zeng-Zhen Hu

Abstract

Based on analysis of a coupled model simulations with and without variability associated with the El Niño–Southern Oscillation (ENSO), it is demonstrated that knowing the current value of the ocean surface temperature–based index of the Pacific decadal oscillation (the OPDO index), and the corresponding atmospheric teleconnection pattern, does not add a predictive value for atmospheric anomalies in subsequent months. This is because although the OPDO index evolves on a slow time scale, it does not constrain the atmospheric variability in subsequent months, which retains its character of white noise stochastic variability and remains largely unpredictable. Further, the OPDO adds little to the atmospheric predictability originating from the tropical Pacific during ENSO years.

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Jinqin Xu, Yan Zeng, Xinfa Qiu, Yongjian He, Guoping Shi, and Xiaochen Zhu

Abstract

Drylands cover about one-half of the land surface in China and are highly sensitive to climate change. Understanding climate change and its impact drivers on dryland is essential for supporting dryland planning and sustainable development. Using meteorological observations for 1960–2019, the aridity changes in drylands of China were evaluated using aridity index (AI), and the impact of various climatic factors [i.e., precipitation P; sunshine duration (SSD); relative humidity (RH); maximum temperature (Tmax); minimum temperature (Tmin); wind speed (WS)] on the aridity changes was decomposed and quantified. Results of trend analysis based on Sen’s slope estimator and Mann–Kendall test indicated that the aridity trends were very weak when averaged over the whole drylands in China during 1960–2019 but exhibited a significant wetting trend in hyperarid and arid regions of drylands. The AI was most sensitive to changes in water factors (i.e., P and RH), followed by SSD, Tmax, and WS, but the sensitivity of AI to Tmin was very small and negligible. Interestingly, the dominant climatic driver to AI change varied in the four dryland subtypes. The significantly increased P dominated the increase in AI in the hyperarid and arid regions. The significantly reduced WS and the significantly increased Tmax contributed more to AI changes than the P in the semiarid and dry subhumid regions of drylands. Previous studies emphasized the impact of precipitation and temperature on the global or regional dry–wet changes; however, the findings of this study suggest that, beyond precipitation and temperature, the impact of wind speed on aridity changes of drylands in China should be given equal attention.

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Zeng-Zhen Hu, Arun Kumar, Bohua Huang, Yan Xue, Wanqiu Wang, and Bhaskar Jha

Abstract

In this work, the authors analyze the air–sea interaction processes associated with the persistent atmospheric and oceanic anomalies in the North Atlantic Ocean during summer 2009–summer 2010 with a record-breaking positive sea surface temperature anomaly (SSTA) in the hurricane Main Development Region (MDR) in the spring and summer of 2010. Contributions to the anomalies from the El Niño–Southern Oscillation (ENSO), the North Atlantic Oscillation (NAO), and a long-term trend are identified. The warming in the tropical North Atlantic during summer 2009–summer 2010 represented a typical response to ENSO, preconditioned and amplified by the influence of a strong and persistent negative phase of the NAO. The long-term trends enhanced the warming in the high and low latitudes and weakened the cooling in the midlatitudes. The persistent negative phase of the NAO was associated with active thermodynamic air–sea interaction in the North Atlantic basin. Surface wind anomalies associated with the NAO altered the ocean surface heat flux and changed the SSTA, which was likely further enhanced by the positive wind speed–evaporation–SST feedback. The total heat flux was dominated by the latent and sensible heat fluxes, while the shortwave radiation contributed to the tropical SSTA to a lesser degree. Sensitivity experiments with an atmospheric general circulation model forced by observed SST in the Atlantic Ocean alone suggested that the Atlantic SSTA, which was partly forced by the NAO, had some positive contribution to the persistence of the negative phase of the NAO. Therefore, the persistent NAO condition is partly an outcome of the global climate anomalies and the ocean–atmosphere feedback within the Atlantic basin. The combination of the ENSO, NAO, and long-term trend resulted in the record-breaking positive SSTA in the MDR in the boreal spring and summer of 2010. On the basis of the statistical relationship, the SSTA pattern in the North Atlantic was reasonably well predicted by using the preceding ENSO and NAO as predictors.

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Michelle L. L’Heureux, Michael K. Tippett, Ken Takahashi, Anthony G. Barnston, Emily J. Becker, Gerald D. Bell, Tom E. Di Liberto, Jon Gottschalck, Michael S. Halpert, Zeng-Zhen Hu, Nathaniel C. Johnson, Yan Xue, and Wanqiu Wang

Abstract

Three strategies for creating probabilistic forecast outlooks for El Niño–Southern Oscillation (ENSO) are compared. One is subjective and is currently used by the NOAA/Climate Prediction Center (CPC) to produce official ENSO outlooks. A second is purely objective and is based on the North American Multimodel Ensemble (NMME). A new third strategy is proposed in which the forecaster only provides the expected value of the Niño-3.4 index, and then categorical probabilities are objectively determined based on past skill. The new strategy results in more confident probabilities compared to the subjective approach and higher verification scores, while avoiding the significant forecast busts that sometimes afflict the NMME-based objective approach. The higher verification scores of the new strategy appear to result from the added value that forecasters provide in predicting the mean, combined with more reliable representations of uncertainty, which is difficult to represent because forecasters often assume less confidence than is justified. Moreover, the new approach can produce higher-resolution probabilistic forecasts that include ENSO strength information and that are difficult, if not impossible, for forecasters to produce. To illustrate, a nine-category ENSO outlook based on the new strategy is assessed and found to be skillful. The new approach can be applied to other outlooks where users desire higher-resolution probabilistic forecasts, including the extremes.

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