Distinct global warming rates tied to multiple ocean surface temperature changes

Yao, Shuai‐Lei; Luo, Jing–Jia; Huang, Gang; Wang, Pengfei

doi:10.1038/nclimate3304

Cited by 88 publications

(71 citation statements)

References 34 publications

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“…The hiatus has attracted great attention because it contrasts with the steady increasing trend of greenhouse gas emissions, and various mechanisms have been proposed to explain it. Numerous studies have suggested that the hiatus is a decadal climate fluctuation or variation induced by radiative forcing (Lean and Rind, ), upper or deep ocean heat uptake (Chen and Tung, ; Nieves et al , ), or internal variability modes of the climate system including the El Niño‐Southern Oscillation (ENSO), the North Atlantic Oscillation (NAO), the Pacific Decadal Oscillation (PDO)/Interdecadal Pacific Oscillation (IPO), and the Atlantic Multidecadal Oscillation (AMO) (Kosaka and Xie, , ; England et al , ; Dai et al , ; Steinman et al , ; Zhang, ; Yao et al , ; Zhang et al , ). Mechanistically, a negative phase of PDO/IPO leads to an unprecedented acceleration of the Walker circulation via strengthening of the trade wind in the central‐eastern tropical Pacific, resulting in a La Niña‐like cooling which contributes to the hiatus (Kosaka and Xie, ; McGregor et al , ).…”

Section: Introductionmentioning

confidence: 99%

The global warming hiatus has faded away: An analysis of 2014–2016 global surface air temperatures

Zhang

Luo

et al. 2019

Intl Journal of Climatology

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We present an analysis of the global annual mean surface temperature anomaly in 2014, 2015, and 2016 based on five datasets of historical observational records of surface temperature. These three years are the three warmest on record in all but one of the datasets. The largest warming occurred over land, especially at high latitudes. Since the strong El Niño event that occurred in 2015/2016 was similar to the 1997/1998 El Niño, we compared the 2014–2016 period with 1998, the warmest year in the 20th century. The contribution to the annual mean surface temperature anomaly of climate variations at different time scales was assessed using ensemble empirical mode decomposition. Results based on the HadCRUT4 dataset suggest that the interannual component may have contributed an anomaly of −0.01°C in 2014, 0.12°C in 2015, and 0.06°C in 2016. These values are substantially lower than the contribution in 1998 (0.18°C). In comparison, the combined contribution of the decadal‐to‐multidecadal (DM) component and the long‐term warming trend was 0.64°C in 2014, 0.70°C in 2015, and 0.77°C in 2016, which are substantially greater than that in 1998 (0.41°C). Similar results were obtained using the other four datasets. The larger contribution from the DM component and the long‐term warming trend implies that warmer years like 2014–2016 may occur more frequently in the near future. We conclude that the so‐called warming hiatus has faded away.

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Section: Introductionmentioning

confidence: 99%

The global warming hiatus has faded away: An analysis of 2014–2016 global surface air temperatures

Zhang

Luo

et al. 2019

Intl Journal of Climatology

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“…In addition, the El Nino-Southern Oscillation (ENSO) in the tropical Pacific and the PDO also affect each other to influence global climate (Gershunov and Barnett, 1998;Newman et al, 2003;Wang et al, 2008;Xie et al, 2010;Wang et al, 2012b;Hu et al, 2014;Wang et al, 2014b;Nidheesh et al, 2017). Many studies have suggested that the phase change of the PDO is associated with the decadal transition of the internal variability of the climate system, particularly for the recent transition from the accelerated warming period to the warming hiatus period (Kosaka and Xie, 2013;Trenberth et al, 2014;Watanabe et al, 2014;Guan et al, 2015a;Guan et al, 2015b;Huang et al, 2016;Yao et al, 2016;Molteni et al, 2017;Yao et al, 2017). Therefore, a more accurate simulation of the decadal variations in SSTA (particularly those of the PDO) is important mainly for climate predictions and the related regional economic development (Mantua et al, 1997;Mantua and Hare, 2002;Newman et al, 2012;Kumar et al, 2013).…”

Section: Introductionmentioning

confidence: 99%

Comparison of the Pacific Decadal Oscillation in climate model simulations and observations

Wei

Huang

et al. 2017

Intl Journal of Climatology

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The ability of climate models to simulate the Pacific Decadal Oscillation (PDO) and its global teleconnections is examined using the outputs of 20 Coupled Model Intercomparison Project (CMIP5) models from historical experiments. It is shown that the global warming trend is reproduced by the models, but there is a considerable difference between the models in the PDO region. The standard deviation of detrended sea surface temperature anomalies (SSTAs) in the models is similar to that of the observations, especially in the central and eastern equatorial Pacific and the North Pacific, which are the regions closely associated with the PDO and El Nino‐Southern Oscillation. The globally averaged SSTA during 1900–1940 in the CMIP5 models and observations showed large divergence, which is mainly due to the SSTA in the PDO region. The most significant cycle of the PDO indexes in most of the models had a 60–80 years period, which is different from the observed PDO period (40–60 years). However, the models perform better for the spatial pattern of the PDO, and 90% of the spatial correlations between the models and observations of the spatial pattern of the PDO are above 0.8. In addition, the models can simulate the basic correlation between the PDO and Pacific SSTA variability, but most of them overestimate the relationship in the Indian and Atlantic Oceans. The CMIP5 models are better at simulating the impact of the PDO on winter precipitation in southern North America but are less accurate in simulating summer precipitation in eastern China. This is probably because most of the models are not accurate in simulating the impacts of the PDO on the western Pacific subtropical high and the East Asian summer monsoon.

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“…Trend turning is a commonly observed phenomenon in climate data; it can be found in parameters such as Surface Air Temperature (SAT, Xing et al, 2017; Yao et al, 2017; Yu & Lin, 2018), precipitation (Alexander et al, 2006), tropical cyclone frequency (Cheung et al, 2015), and haze days (Zhao et al, 2016). Some studies in ecoclimate have also reported trend turning (Liang et al, 2015; Peng et al, 2011; Piao et al, 2011).…”

Section: Introductionmentioning

confidence: 99%

Robustness Assessment of the RSDt‐Test for Detecting Trend Turning in a Time Series

Zuo

Hou

Zheng

et al. 2020

Earth and Space Science

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Trend turning (or trend change) is a type of structural change that is common in climate data, and methods for detecting it in time series with multiple turning-points need to be developed. A recently developed method for this, the running slope difference (RSD) t-test, examines trend differences in sub-series of the sample time series to identify the trend turning-points. In this paper, we use Monte Carlo simulation to evaluate this method's detection ability. Evaluation results show the method to be an effective tool for detecting trend turning time series and identify three major advantages of the RSD t-test: ability to detect multiple turning-points, capacity to detect all three types of trend turning, and great performance of reducing false alarm rate. Key Points: • The RSD t-test is a recently developed method for detecting trend turning in climate time series • Monte Carlo simulation is designed to evaluate the detection ability of the RSD t-test comprehensively • The RSD t-test has capacity to detect multiple turning-points of three turning types and great performance of reducing false alarm rate . Robustness assessment of the RSD t-test for detecting trend turning in a time series.

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Distinct global warming rates tied to multiple ocean surface temperature changes

Cited by 88 publications

References 34 publications

The global warming hiatus has faded away: An analysis of 2014–2016 global surface air temperatures

The global warming hiatus has faded away: An analysis of 2014–2016 global surface air temperatures

Comparison of the Pacific Decadal Oscillation in climate model simulations and observations

Robustness Assessment of the RSDt‐Test for Detecting Trend Turning in a Time Series

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