Stationarity of the tropical pacific teleconnection to North America in CMIP5/PMIP3 model simulations

Coats, Sloan; Smerdon, Jason E.; Cook, Benjamin I.; Seager, Richard

doi:10.1002/grl.50938

Cited by 78 publications

(88 citation statements)

References 39 publications

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“…This result suggests that the observed sea surface temperature is important for the correct simulation of precipitation at different regions. Nevertheless, some of the differences between the observed and modeled precipitation patterns in the middle and high latitudes may be due to different internal variabilities that are present in the observations and in the AMIP runs (Coats et al 2013).…”

Section: Conclusion and Discussionmentioning

confidence: 99%

Temporal and Spatial Variability of Precipitation from Observations and Models*

Trammell

Jiang

et al. 2016

Journal of Climate

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Principal component analysis (PCA) is utilized to explore the temporal and spatial variability of precipitation from GPCP and a CAM5 simulation from 1979 to 2010. In the tropical region, the interannual variability of tropical precipitation is characterized by two dominant modes (El Niño and El Niño Modoki). The first and second modes of tropical GPCP precipitation capture 31.9% and 15.6% of the total variance, respectively. The first mode has positive precipitation anomalies over the western Pacific and negative precipitation anomalies over the central and eastern Pacific. The second mode has positive precipitation anomalies over the central Pacific and negative precipitation anomalies over the western and eastern Pacific. Similar variations are seen in the first two modes of tropical precipitation from a CAM5 simulation, although the magnitudes are slightly weaker than in the observations. Over the Northern Hemisphere (NH) high latitudes, the first mode, capturing 8.3% of the total variance of NH GPCP precipitation, is related to the northern annular mode (NAM). During the positive phase of NAM, there are negative precipitation anomalies over the Arctic and positive precipitation anomalies over the midlatitudes. Over the Southern Hemisphere (SH) high latitudes, the first mode, capturing 13.2% of the total variance of SH GPCP precipitation, is related to the southern annular mode (SAM). During the positive phase of the SAM, there are negative precipitation anomalies over the Antarctic and positive precipitation anomalies over the midlatitudes. The CAM5 precipitation simulation demonstrates similar results to those of the observations. However, they do not capture both the high precipitation anomalies over the northern Pacific Ocean or the position of the positive precipitation anomalies in the SH.

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Section: Conclusion and Discussionmentioning

confidence: 99%

Temporal and Spatial Variability of Precipitation from Observations and Models*

Trammell

Jiang

et al. 2016

Journal of Climate

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“…The possible impacts of model biases in last-millennium simulations have been explicitly discussed for only a few specific regional aspects of climate dynamics and variability (e.g., Coats et al, 2013aCoats et al, , 2016aZanchet-tin et al, 2015;Stevenson et al, 2016). A broader assessment of model biases in simulated patterns, variability, and teleconnections would therefore increase our confidence in both climate dynamics and the variability inferred from climate simulations of the last millennium.…”

Section: Opportunities For Modeling Progressmentioning

confidence: 99%

“…Conversion of the proxy into a climatic variable can be achieved through regression or traditional inverse methods as is done with the widely used regional drought atlases (Cook et al, , 2010aPalmer et al, 2015). Nevertheless, in many cases the multivariate nature of proxy data, the presence of large uncertainties and limited spatiotemporal coverage in a calibration proxy network or nonstationary behavior between the proxy predictor and the climate predictand render regression and inversion challenging (e.g., Wilson et al, 2010;Lehner et al, 2012;Smerdon, 2012;Tingley et al, 2012;Coats et al, 2013a;Gallant et al, 2013;Evans et al, 2014;Konecky et al, 2014;Raible et al, 2014;Wang et al, 2014bWang et al, , 2015Konecky et al, 2016).…”

Section: Expectations Of Temporal or Spatial Consistency Betweenmentioning

confidence: 99%

Comparing proxy and model estimates of hydroclimate variability and change over the Common Era

Smerdon¹,

Luterbacher²,

Phipps³

et al. 2017

Clim. Past

101

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Abstract. Water availability is fundamental to societies and ecosystems, but our understanding of variations in hydroclimate (including extreme events, flooding, and decadal periods of drought) is limited because of a paucity of modern instrumental observations that are distributed unevenly across the globe and only span parts of the 20th and 21st centuries. Such data coverage is insufficient for characterizing hydroclimate and its associated dynamics because of its multidecadal to centennial variability and highly regionalized spatial signature. High-resolution (seasonal to decadal) hydroclimatic proxies that span all or parts of the Common Era (CE) and paleoclimate simulations from climate models are therefore important tools for augmenting our understanding of hydroclimate variability. In particular, the comparison of the two sources of information is critical for addressing the uncertainties and limitations of both while enriching each of their interpretations. We review the principal proxy data available for hydroclimatic reconstructions over the CE and highlight the contemporary understanding of how these proxies are interpreted as hydroclimate indicators. We also review the available last-millennium simulations from fully coupled climate models and discuss several outstanding challenges associated with simulating hydroclimate variability and change over the CE. A specific review of simulated hydroclimatic changes forced by volcanic events is provided, as is a discussion of expected improvements in estimated radiative forcings, models, and their implementation in the future. Our review of hydroclimatic proxies and last-millennium model simulations is used as the basis for articulating a variety of considerations and best practices for how to perform proxy-model comparisons of CE hydroclimate. This discussion provides a framework for how best to evaluate hydroclimate variability and its associated dynamics using these comparisons and how they can better inform interpretations of both proxy data and model simulations. We subsequently explore means of using proxy-model comparisons to better constrain and characterize future hydroclimate risks. This is explored specifically in the context of several examples that demonstrate how proxy-model comparisons can be used to quantitatively constrain future hydroclimatic risks as estimated from climate model projections.

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“…Moreover, exploiting teleconnected locations implicitly assumes that the teleconnected relationship does not significantly depend on the external forcing (Batehup et al 2015). Coats et al 2013 found that atmospheric forcing cannot account for the non-stationary teleconnection between tropical Pacific SSTs and 200 mb geopotential height. Gallant et al 2013 found significant variations through time in teleconnections on near-centennial timescales in model simulations forced by internal dynamics alone, but Batehup et al 2015 found that using multiple teleconnected regions minimizes any effects of non-stationarities.…”

Section: Introductionmentioning

confidence: 99%

Evaluation of CMIP5 models over the northern North Atlantic in the context of forthcoming paleoclimatic reconstructions

2017

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We evaluated 11 coupled climate model simulations regarding the spatial structures of sea-surface temperature (SST) variability in the North Atlantic, during the second half of the twentieth century. The subset of models includes CCSM4, CSIRO, CanESM and MPI-ESM, participating in the fifth phase of the Climate Model Intercomparison Project. The evaluation was performed to determine the potential of these models to be used at a later stage as test beds for the evaluation of climate field reconstruction methods that will use the extremely long-lived bivalve mollusk Arctica islandica, an outstanding paleoclimate archive for the boreal and temperate North Atlantic (Schöne, Glob Planet Change 111:199–225, 2013). Several validation metrics such as the mean bias, variance, spatial and temporal co-variability and trends of the North Atlantic summer SSTs showed that some of the models can be used to test paleoclimatic reconstructions. However, most models showed shortcomings in simulating the Atlantic Multidecadal Oscillation. Concerning the co-variability of summer SSTs between proxy sites and the whole North Atlantic SST field, we found that these proxy locations contain a SST signal that might represent a (basin-wide) signal for the north-eastern North Atlantic basin

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Stationarity of the tropical pacific teleconnection to North America in CMIP5/PMIP3 model simulations

Cited by 78 publications

References 39 publications

Temporal and Spatial Variability of Precipitation from Observations and Models*

Temporal and Spatial Variability of Precipitation from Observations and Models*

Comparing proxy and model estimates of hydroclimate variability and change over the Common Era

Evaluation of CMIP5 models over the northern North Atlantic in the context of forthcoming paleoclimatic reconstructions

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