This research examined the effects of simultaneous occurrences of different phases of the North Atlantic Oscillation (NAO) and Pacific North American (PNA) teleconnection patterns on daily variations in Northeast climate variables. 30-day normalized Temperature, MSLP, and IPW anomalies gathered from Northeast data locations were compared to daily indices of the NAO and PNA. The computed anomalies from each location were sorted into 25 potential NAO/PNA phase combinations which were based off of the standard deviations of the NAO/PNA daily indices in an 11-year data set from 2004-2014. These anomalies and their relationships to daily NAO/PNA index values were analyzed using regression, correlation, and chi-square analysis. Additionally, each of the 25 combinations and their associated average anomalies were analyzed using composite analysis. This process was done for a full time series and a cool season time series using the months from October-March in the same 11-year data set. Regression analysis revealed that no variation in the analyzed variables can be explained by either the NAO or the PNA daily indices individually or together (using multi-regression). Chi-square analysis revealed that the distribution of the average anomalies associated with the 25 possible combinations was most likely random. Cross correlation tests suggested little to no relationship between daily anomalies in the analyzed variables and the NAO/PNA daily indices. The greatest observed average anomalies in the 25 combinations were consistent at 4/5 data locations and in some cases could be explained by composite analysis. The majority of these significant anomalies occurred when either the NAO or PNA was in an extreme phase (Very Positive/Very Negative). The ability to explain some of these average anomalies with composite analyses of the geopotential height field suggests that NAO/PNA daily indices could prove useful for long term forecasting.