Contributions of Internal Variability and External Forcing to the Recent Pacific Decadal Variations

Hua, Wenjian; Dai, Aiguo; Qin, Minhua

doi:10.1029/2018gl079033

Cited by 56 publications

(59 citation statements)

References 51 publications

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“…Note that ̃ decreases upwards on the vertical axis, in order that the effective climate sensitivity increases upwards of climate change to forcing agents (e.g. Jones et al 2013;Hua et al 2018).…”

Section: Time-variation Of Climate Feedback In the Historical Experimentsmentioning

confidence: 99%

How accurately can the climate sensitivity to $$\hbox {CO}_{2}$$ be estimated from historical climate change?

et al. 2019

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The equilibrium climate sensitivity (ECS, in K) to CO 2 doubling is a large source of uncertainty in projections of future anthropogenic climate change. Estimates of ECS made from non-equilibrium states or in response to radiative forcings other than 2 × CO 2 are called "effective climate sensitivity" (EffCS, in K). Taking a "perfect-model" approach, using coupled atmosphere-ocean general circulation model (AOGCM) experiments, we evaluate the accuracy with which CO 2 EffCS can be estimated from climate change in the "historical" period (since about 1860). We find that (1) for statistical reasons, unforced variability makes the estimate of historical EffCS both uncertain and biased; it is overestimated by about 10% if the energy balance is applied to the entire historical period, 20% for 30-year periods, and larger factors for interannual variability, (2) systematic uncertainty in historical radiative forcing translates into an uncertainty of ± 30 to 45% (standard deviation) in historical EffCS, (3) the response to the changing relative importance of the forcing agents, principally CO 2 and volcanic aerosol, causes historical EffCS to vary over multidecadal timescales by a factor of two. In recent decades it reached its maximum in the AOGCM historical experiment (similar to the multimodel-mean CO 2 EffCS of 3.6 K from idealised experiments), but its minimum in the real world (1.6 K for an observational estimate for 1985-2011, similar to the multimodel-mean value for volcanic forcing). The real-world variations mean that historical EffCS underestimates CO 2 EffCS by 30% when considering the entire historical period. The difference for recent decades implies that either unforced variability or the response to volcanic forcing causes a much stronger regional pattern of sea surface temperature change in the real world than in AOGCMs. We speculate that this could be explained by a deficiency in simulated coupled atmosphere-ocean feedbacks which reinforce the pattern (resembling the Interdecadal Pacific Oscillation in some respects) that causes the low EffCS. We conclude that energy-balance estimates of CO 2 EffCS are most accurate from periods unaffected by volcanic forcing. Atmosphere GCMs provided with observed sea surface temperature for the 1920s to the 1950s, which was such a period, give a range of about 2.0-4.5 K, agreeing with idealised CO 2 AOGCM experiments; the consistency is a reason for confidence in this range as an estimate of CO 2 EffCS. Unless another explosive volcanic eruption occurs, the first 30 years of the present century may give a more accurate energy-balance historical estimate of this quantity.

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Section: Time-variation Of Climate Feedback In the Historical Experimentsmentioning

confidence: 99%

How accurately can the climate sensitivity to $$\hbox {CO}_{2}$$ be estimated from historical climate change?

et al. 2019

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“…Previous studies show many different ways to calculate the index representing the PDO/IPO: for example, the EOF method (Mantua and Hare 2002) and the difference of SST anomalies between regions of the Pacific (Henley et al 2015;Salzmann and Cherian 2015), showing an overall similarity in featuring the decadal-tomultidecadal variability of Pacific SST in observations after 1920 (Hua et al 2018). Thus, for easier calculation and for direct comparison between observations and model simulations and comparison between ensemble members, we use the latter method to define the IPO index without applying EOF analysis, similar to Salzmann and Cherian (2015).…”

Section: ) Ipo Definitionmentioning

confidence: 99%

“…Changes in land use and land cover have also been proposed as another contributor: Local evapotranspiration, a source of atmospheric moisture, has decreased as a consequence of deforestation (Paul et al 2016;Chou et al 2018). In addition to the above anthropogenic forcings, a negative-to-positive phase transition from the 1950s to the 1990s of the Pacific decadal oscillation (PDO)/interdecadal Pacific oscillation (IPO), whose recent cycles result mainly from internal variability (Dong et al 2014;Hua et al 2018), also helps to explain the total drying trend over India during this period, as highlighted by Salzmann and Cherian (2015). Using the multimodel ensemble from phase 5 of the Coupled Model Intercomparison Project (CMIP5), the NCI drying trend associated with the PDO/IPO was comparable to that caused by anthropogenic aerosols derived from the single-forcing experiments during the period 1950-99 (Salzmann et al 2014).…”

Section: Introductionmentioning

confidence: 99%

The Recent Decline and Recovery of Indian Summer Monsoon Rainfall: Relative Roles of External Forcing and Internal Variability

et al. 2020

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The Indian summer monsoon (ISM) rainfall affects a large population in South Asia. Observations show a decline in ISM rainfall from 1950 to 1999 and a recovery from 1999 to 2013. While the decline has been attributed to global warming, aerosol effects, deforestation, and a negative-to-positive phase transition of the interdecadal Pacific oscillation (IPO), the cause for the recovery remains largely unclear. Through analyses of a 57-member perturbed-parameter ensemble of model simulations, this study shows that the externally forced rainfall trend is relatively weak and is overwhelmed by large internal variability during both 1950-99 and 1999-2013. The IPO is identified as the internal mode that helps modulate the recent decline and recovery of the ISM rainfall. The IPO induces ISM rainfall changes through moisture convergence anomalies associated with an anomalous Walker circulation and meridional tropospheric temperature gradients and the resultant anomalous convection and zonal moisture advection. The negative-to-positive IPO phase transition from 1950 to 1999 reduces what would have been an externally forced weak upward rainfall trend of 0.01 to 20.15 mm day 21 decade 21 during that period, while the rainfall trend from 1999 to 2013 increases from the forced value of 0.42 to 0.68 mm day 21 decade 21 associated with a positive-to-negative IPO phase transition. Such a significant modulation of the historical ISM rainfall trends by the IPO is confirmed by another 100member ensemble of simulations using perturbed initial conditions. Our findings highlight that the interplay between the effects of external forcing and the IPO needs be considered for climate adaptation and mitigation strategies in South Asia.

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“…The Pacific decadal Oscillation (PDO) (Mantua et al ., ) or the Inter‐decadal Pacific Oscillation (IPO) (Power et al ., ) is the dominant mode of decadal to multi‐decadal sea surface temperature (SST) variability in the Pacific Ocean that broadly resembles the SST anomaly pattern of ENSO but with subtle differences (Zhang et al ., ; Dong et al ., ). Many studies have found that this internal mode could exert large decadal/inter‐decadal modulation effects on regional and global temperature and precipitation (e.g., Zhang et al ., ; Reason and Rouault, ; Krishnan and Sugi, ; Meehl and Hu, ; Dai, ; Dong and Dai, ; Newman et al ., ; Hua et al ., ). Since the IPO/PDO mode provides a major source of decadal predictability, understanding the physical connections between the IPO/PDO and the associated regional climate variations is critically important.…”

Section: Introductionmentioning

confidence: 97%

Understanding the inter‐decadal variability of autumn precipitation over North Central China using model simulations

Qin

Dai

et al. 2019

Intl Journal of Climatology

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A recent study has shown a robust relationship between the Pacific Decadal Oscillation (PDO) and inter‐decadal variations in autumn precipitation over North Central China (NCC). However, the physical processes underlying these inter‐decadal precipitation variations are not fully understood. Here we analyse multi‐member ensembles of atmospheric reanalysis and model simulations to examine the atmospheric and precipitation responses to sea surface temperature (SST) forcing. Despite the large inter‐member spread resulting from atmospheric internal variability, the model simulations forced by the observed SSTs show an important role of mid‐latitude atmospheric circulation in influencing the inter‐decadal precipitation variations over NCC. We also analyse the sensitivity experiments using three atmospheric models forced by the Inter‐decadal Pacific Oscillation (IPO)/PDO‐like SST fields. The results suggest that the SST anomalies associated with a negative IPO phase can induce anomalous positive pressure anomalies over the East Asia‐Japan‐North Pacific region, which weakens the East Asian trough (EAT) and produces southerly advection of warm and moist air into NCC, leading to increased precipitation there. This study provides a depiction of how the IPO/PDO‐associated SSTs induce inter‐decadal oscillations in mid‐latitude atmospheric circulations, which in turn cause inter‐decadal precipitation variations over NCC.

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Contributions of Internal Variability and External Forcing to the Recent Pacific Decadal Variations

Cited by 56 publications

References 51 publications

How accurately can the climate sensitivity to $$\hbox {CO}_{2}$$ be estimated from historical climate change?

How accurately can the climate sensitivity to $$\hbox {CO}_{2}$$ be estimated from historical climate change?

The Recent Decline and Recovery of Indian Summer Monsoon Rainfall: Relative Roles of External Forcing and Internal Variability

Understanding the inter‐decadal variability of autumn precipitation over North Central China using model simulations

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