The extreme El Niño of 2015–2016 and the end of global warming hiatus

Hu, Shineng; Fedorov, Alexey V.

doi:10.1002/2017gl072908

Cited by 149 publications

(100 citation statements)

References 47 publications

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“…These parameter values were obtained by a fit under the constraint that those ones most relevant to this work, namely, τ and b , are close to the values obtained in Hu and Fedorov (). We also give more weight to more recent data points than to older points where measurement accuracy is lower.…”

Section: The Modelsupporting

confidence: 83%

Reproducing Long‐Range Correlations in Global Mean Temperatures in Simple Energy Balance Models

2018

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We study global mean surface temperature records since 1850 and their potential forcings. We find long range correlations by the method of detrended fluctuation analysis in most data sets, in agreement with previous studies. As a predictive model, we employ a zero‐dimensional energy balance model without memory that reproduces temperature data on the timescale of years. Even when driven with white noise, this model generates data that reproduce the observed long‐range correlations. We are able to explain this with theoretical results for the AR(1) process, which demonstrates that even processes with exponentially decaying correlations yield nontrivial detrended fluctuation analysis results if the available data set is too short. This article gives new support to the scepticism about long memory in global mean temperatures and discusses further implications of our findings.

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Section: The Modelsupporting

confidence: 83%

Reproducing Long‐Range Correlations in Global Mean Temperatures in Simple Energy Balance Models

2018

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“…4e Although much needs to be understood about the interrelation between the rapidly changing ENSO and large-scale environment patterns on the WNP TCLs (e.g., Hsu et al 2014;Zhao et al 2014b;Zhao and Wang 2016), we provide further evidence linking ENSO shift and the Pacific climate regime shift to the WNP TCLs, with an emphasis on the roles of the TUTT and MT in autumn. As the interaction between external anthropogenic forcing (i.e., increasing anthropogenic greenhouse gases) and internal natural variability continues to evolve gradually (e.g., Hu and Fedorov 2017), projections of more frequent extreme ENSO (Cai et al 2014(Cai et al , 2015a, ENSO diversity (e.g., Hu et al 2016a, b;Chen et al 2015) and PDO modulation (e.g., Zhao and Wang 2016), as well as their resultant effects on concurrent TCL changes, are inherently uncertain. We expect to see a further TCL change over the WNP, which is closely related to the major population centers across much of eastern China, Korea and Japan, where billions of people can be affected.…”

Section: Resultsmentioning

confidence: 99%

Perspective on the northwestward shift of autumn tropical cyclogenesis locations over the western North Pacific from shifting ENSO

Zhang

Yang

et al. 2017

Clim Dyn

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During the recent decades of satellite era, more tropical cyclogenesis locations (TCLs) were observed over the northwestern part of the western North Pacific (WNP), relative to the southeastern part, during the boreal autumn. This increase in TCLs over the northwestern WNP is largely attributed to the synergy of shifting El Niño-Southern Oscillation (ENSO) and the 1998 Pacific climate regime shift. Both central Pacific (CP) La Niña and CP El Niño have occurred more frequently since 1998, with only one eastern Pacific El Niño observed in autumn 2015. The change in the mean longitude of TCLs is closely linked to the ENSO diversity, whereas the change in the mean latitude is dominated by the warming of the WNP induced by an interdecadal tendency of CP La Niña-like events. The physical mechanisms responsible for this shifting ENSO-TCL linkage can be potentially explained by the tacit-and-mutual configurations between tropical upper-tropospheric trough and monsoon trough, on both interannual and interdecadal timescales, which is mainly due to the ENSO-related large-scale environment changes in ocean and atmosphere that modulate the WNP TCL.

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“…This shows the influence of the extreme El Niño of 2015-2016 [19,74,75]. Although, CO2 release over some area was well been evaluated [22,26], there are some high XCO2 regions that have not been examined in great detail in the literature, such as southern South America and Australia.…”

Section: Spatial Patterns Of Extreme High Co2 Concentrations During Ementioning

confidence: 97%

Detection of Spatiotemporal Extreme Changes in Atmospheric CO2 Concentration Based on Satellite Observations

Lei

Welp

et al. 2018

Remote Sensing

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Atmospheric CO 2 concentrations are sensitive to the effects of climate extremes on carbon sources and sinks of the land biosphere. Therefore, extreme changes of atmospheric CO 2 can be used to identify anomalous sources and sinks of carbon. In this study, we develop a spatiotemporal extreme change detection method for atmospheric CO 2 concentrations using column-averaged CO 2 dry air mole fraction (XCO 2 ) retrieved from the Greenhouse gases Observing SATellite (GOSAT) from 1 June 2009 to 31 May 2016. For extreme events identified, we attributed the main drivers using surface environmental parameters, including surface skin temperature, self-calibrating Palmer drought severity index, burned area, and gross primary production (GPP). We also tested the sensitivity of XCO 2 response to changing surface CO 2 fluxes using model simulations and Goddard Earth Observing System (GEOS)-Chem atmospheric transport. Several extreme high XCO 2 events are detected around mid-2010 over Eurasia and in early 2016 in the tropics. The magnitudes of extreme XCO 2 increases are around 1.5-1.8 ppm in the Northern Hemisphere and 1.2-1.4 ppm in Southern Hemisphere. The spatiotemporal pattern of detected high XCO 2 events are similar to patterns of local surface environmental parameter extremes. The extreme high XCO 2 events often occurred during periods of increased temperature, severe drought, increased wildfire or reduced GPP. Our sensitivity tests show that the magnitude of detectable anomalies varies with location, for example 25% or larger anomalies in local CO 2 emission fluxes are detectable in tropical forest, whereas anomalies must be half again as large in mid-latitudes (~37.5%). In conclusion, we present a method for extreme high XCO 2 detection, and large changes in land CO 2 fluxes. This provides another tool to monitor large-scale changes in the land carbon sink and potential feedbacks on the climate system.

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The extreme El Niño of 2015–2016 and the end of global warming hiatus

Cited by 149 publications

References 47 publications

Reproducing Long‐Range Correlations in Global Mean Temperatures in Simple Energy Balance Models

Reproducing Long‐Range Correlations in Global Mean Temperatures in Simple Energy Balance Models

Perspective on the northwestward shift of autumn tropical cyclogenesis locations over the western North Pacific from shifting ENSO

Detection of Spatiotemporal Extreme Changes in Atmospheric CO2 Concentration Based on Satellite Observations

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