scholarly journals Eastern North American climate in phase with fall insolation throughout the last three glacial-interglacial cycles

2019 ◽  
Vol 522 ◽  
pp. 125-134 ◽  
Author(s):  
Hai Cheng ◽  
Gregory S. Springer ◽  
Ashish Sinha ◽  
Benjamin F. Hardt ◽  
Liang Yi ◽  
...  
2004 ◽  
Vol 23 (2) ◽  
pp. 117-132 ◽  
Author(s):  
K. W. Oleson ◽  
G. B. Bonan ◽  
S. Levis ◽  
M. Vertenstein

Science ◽  
1999 ◽  
Vol 283 (5405) ◽  
pp. 1109-1109
Author(s):  
R. A. Kerr

Science ◽  
2003 ◽  
Vol 302 (5648) ◽  
pp. 1200-1203 ◽  
Author(s):  
D. J. Karoly

2013 ◽  
Vol 26 (23) ◽  
pp. 9209-9245 ◽  
Author(s):  
Justin Sheffield ◽  
Andrew P. Barrett ◽  
Brian Colle ◽  
D. Nelun Fernando ◽  
Rong Fu ◽  
...  

This is the first part of a three-part paper on North American climate in phase 5 of the Coupled Model Intercomparison Project (CMIP5) that evaluates the historical simulations of continental and regional climatology with a focus on a core set of 17 models. The authors evaluate the models for a set of basic surface climate and hydrological variables and their extremes for the continent. This is supplemented by evaluations for selected regional climate processes relevant to North American climate, including cool season western Atlantic cyclones, the North American monsoon, the U.S. Great Plains low-level jet, and Arctic sea ice. In general, the multimodel ensemble mean represents the observed spatial patterns of basic climate and hydrological variables but with large variability across models and regions in the magnitude and sign of errors. No single model stands out as being particularly better or worse across all analyses, although some models consistently outperform the others for certain variables across most regions and seasons and higher-resolution models tend to perform better for regional processes. The CMIP5 multimodel ensemble shows a slight improvement relative to CMIP3 models in representing basic climate variables, in terms of the mean and spread, although performance has decreased for some models. Improvements in CMIP5 model performance are noticeable for some regional climate processes analyzed, such as the timing of the North American monsoon. The results of this paper have implications for the robustness of future projections of climate and its associated impacts, which are examined in the third part of the paper.


2013 ◽  
Vol 26 (23) ◽  
pp. 9247-9290 ◽  
Author(s):  
Justin Sheffield ◽  
Suzana J. Camargo ◽  
Rong Fu ◽  
Qi Hu ◽  
Xianan Jiang ◽  
...  

This is the second part of a three-part paper on North American climate in phase 5 of the Coupled Model Intercomparison Project (CMIP5) that evaluates the twentieth-century simulations of intraseasonal to multidecadal variability and teleconnections with North American climate. Overall, the multimodel ensemble does reasonably well at reproducing observed variability in several aspects, but it does less well at capturing observed teleconnections, with implications for future projections examined in part three of this paper. In terms of intraseasonal variability, almost half of the models examined can reproduce observed variability in the eastern Pacific and most models capture the midsummer drought over Central America. The multimodel mean replicates the density of traveling tropical synoptic-scale disturbances but with large spread among the models. On the other hand, the coarse resolution of the models means that tropical cyclone frequencies are underpredicted in the Atlantic and eastern North Pacific. The frequency and mean amplitude of ENSO are generally well reproduced, although teleconnections with North American climate are widely varying among models and only a few models can reproduce the east and central Pacific types of ENSO and connections with U.S. winter temperatures. The models capture the spatial pattern of Pacific decadal oscillation (PDO) variability and its influence on continental temperature and West Coast precipitation but less well for the wintertime precipitation. The spatial representation of the Atlantic multidecadal oscillation (AMO) is reasonable, but the magnitude of SST anomalies and teleconnections are poorly reproduced. Multidecadal trends such as the warming hole over the central–southeastern United States and precipitation increases are not replicated by the models, suggesting that observed changes are linked to natural variability.


2011 ◽  
Vol 24 (16) ◽  
pp. 4519-4528 ◽  
Author(s):  
Martin Hoerling ◽  
James Hurrell ◽  
Arun Kumar ◽  
Laurent Terray ◽  
Jon Eischeid ◽  
...  

Abstract The predictability of North American climate is diagnosed by taking into account both forced climate change and natural decadal-scale climate variability over the next decade. In particular, the “signal” in North American surface air temperature and precipitation over 2011–20 associated with the expected change in boundary conditions related to future anthropogenic greenhouse gas (GHG) forcing, as well as the “noise” around that signal due to internally generated ocean–atmosphere variability, is estimated. The structural uncertainty in the estimate of decadal predictability is diagnosed by examining the sensitivity to plausible scenarios for the GHG-induced change in boundary forcing, the model dependency of the forced signals, and the dependency on methods for estimating internal decadal noise. The signal-to-noise analysis by the authors is thus different from other published decadal prediction studies, in that this study does not follow a trajectory from a particular initial state but rather considers the statistics of internal variability in comparison with the GHG signal. The 2011–20 decadal signal is characterized by surface warming over the entire North American continent, precipitation decreases over the contiguous United States, and precipitation increases over Canada relative to 1971–2000 climatological conditions. The signs of these forced responses are robust across different sea surface temperature (SST) scenarios and the different models employed, though the amplitude of the response differs. The North American decadal noise is considerably smaller than the signal associated with boundary forcing, implying a potential for high forecast skill for 2011–20 North American climate even for prediction methods that do not attempt to initialize climate models. However, the results do suggest that initialized decadal predictions, which seek to forecast externally forced signals and also constrain the internal variability, could potentially improve upon uninitialized methods in regions where the external signal is small relative to internal variability.


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