Schoof, J. T., & Pryor, S. C. (2006). An evaluation of two GCMs: simulation of North American teleconnection indices and synoptic phenomena. Int. J. Climatol. , 26 (2), 267–282.
Arguez, A., O'Brien, J. J., & Smith, S. R. (2009). Air temperature impacts over Eastern North America and Europe associated with low-frequency North Atlantic SST variability. Int. J. Climatol. , 29 (1), 1–10.
Krishnamurthy, V., & Misra, V. (2011). Daily atmospheric variability in the South American monsoon system. Clim Dyn , 37 (3-4), 803–819.
Brolley, J. M. (2007). Effects of ENSO, NAO (PVO), and PDO on Monthly Extreme Temperatures and Precipitation . Ph.D. thesis, Florida State University, Tallahassee, FL.
Abstract: The El Nino-Southern Oscillation (ENSO), the North Atlantic Oscillation (NAO), the Pacific Decadal Oscillation (PDO), and the Polar Vortex Oscillation (PVO) produce conditions favorable for monthly extreme temperatures and precipitation. These climate modes produce upper-level teleconnection patterns that favor regional droughts, floods, heat waves, and cold spells, and these extremes impact agriculture, energy, forestry, and transportation. The above sectors prefer the knowledge of the worst (and sometimes the best) case scenarios. This study examines the extreme scenarios for each phase and the combination of phases that produce the greatest monthly extremes. Data from Canada, Mexico, and the United States are gathered from the Historical Climatology Network (HCN). Monthly data are simulated by the utilization of a Monte Carlo model. This Monte Carlo method simulates monthly data by the stochastic selection of daily data with identical ENSO, PDO, and PVO (NAO) characteristics. In order to test the quality of the Monte Carlo simulation, the simulations are compared with the observations using only PDO and PVO. It has been found that temperatures and precipitation in the simulation are similar to the model. Statistics tests have favored similarities between simulations and observations in most cases. Daily data are selected in blocks of four to eight days in order to conserve temporal correlation. Because the polar vortex occurs only during the cold season, the PVO is used during January, and the NAO is used during other months. The simulated data are arranged, and the tenth and ninetieth percentiles are analyzed. The magnitudes of temperature and precipitation anomalies are the greatest in the western Canada and the southeastern United States during winter, and these anomalies are located near the Pacific North American (PNA) extrema. Western Canada has its coldest (warmest) Januaries when the PDO and PVO are low (high). The southeastern United States has its coldest Januaries with high PDO and low PVO and warmest Januaries with low PDO and high PVO. Although extremes occur during El Nino or La Nina, many stations have the highest or lowest temperatures during neutral ENSO. In California and the Gulf Coast, the driest (wettest) Januaries tend to occur during low (high) PDO, and the reverse occurs in Tennessee, Kentucky, Ohio, and Indiana. Summertime anomalies, on the other hand, are weak because temperature variance is low. Phase combinations that form the wettest (driest) Julies form spatially incoherent patterns. The magnitudes of the temperature and precipitation anomalies and the corresponding phase combinations vary regionally and seasonally. Composite maps of geopotential heights across North America are plot for low, median, and high temperatures at six selected sites and for low, median, and high precipitation at the same sites. The greatest fluctuations occur near the six sites and over some of the loci of the PNA pattern. Geopotential heights tend to decrease (increase) over the target stations during the cold (warm) cases, and the results for precipitation are variable.
Xu, X., & Chassignet, E. P., Wang, F. (2018). On the variability of the Atlantic meridional overturning circulation transports in coupled CMIP5 simulations. Clim Dyn. , 51 (11), 6511–6531.
Abstract: The Atlantic meridional overturning circulation (AMOC) plays a fundamental role in the climate system, and long-term climate simulations are used to understand the AMOC variability and to assess its impact. This study examines the basic characteristics of the AMOC variability in 44 CMIP5 (Phase 5 of the Coupled Model Inter-comparison Project) simulations, using the 18 atmospherically-forced CORE-II (Phase 2 of the Coordinated Ocean-ice Reference Experiment) simulations as a reference. The analysis shows that on interannual and decadal timescales, the AMOC variability in the CMIP5 exhibits a similar magnitude and meridional coherence as in the CORE-II simulations, indicating that the modeled atmospheric variability responsible for AMOC variability in the CMIP5 is in reasonable agreement with the CORE-II forcing. On multidecadal timescales, however, the AMOC variability is weaker by a factor of more than 2 and meridionally less coherent in the CMIP5 than in the CORE-II simulations. The CMIP5 simulations also exhibit a weaker long-term atmospheric variability in the North Atlantic Oscillation (NAO). However, one cannot fully attribute the weaker AMOC variability to the weaker variability in NAO because, unlike the CORE-II simulations, the CMIP5 simulations do not exhibit a robust NAO-AMOC linkage. While the variability of the wintertime heat flux and mixed layer depth in the western subpolar North Atlantic is strongly linked to the AMOC variability, the NAO variability is not.
