Journal: Scientific Reports

Article Title: Strengthening North Pacific Influences on United States Temperature Variability

doi: 10.1038/s41598-017-00175-y

Figure Lengend Snippet: EP/NP Time series and EP/NP pattern. ( a ) The EP/NP index from 1950 to 2015 (black curve) together with the 5-year running mean. To reduce edge effects, the running mean was calculated by padding the left edge of the time series with the first value of the time series and padding the right end of the time series with the last value of the time series. Note that the raw and smoothed time series are plotted on different scales. ( b ) Composite of 500-hPa geopotential height anomalies for the positive EP/NP phase. Arrows indicate the wave activity flux ( m 2 s 2 ), which have been scaled relative to maximum wave activity flux vector length of 0.89 m 2 s 2 . The map was generated using MATLAB’s geoshow routine (MATLAB 2015a, http://www.mathworks.com/products/matlab/ ).

Article Snippet: The map was generated using MATLAB’s geoshow routine (MATLAB 2015a, http://www.mathworks.com/products/matlab/ ).

Techniques: Activity Assay, Plasmid Preparation, Generated

Journal: Scientific Reports

Article Title: Strengthening North Pacific Influences on United States Temperature Variability

doi: 10.1038/s41598-017-00175-y

Figure Lengend Snippet: Strength and Trends in EP/NP index-temperature relationships. ( a ) Correlation between EP/NP index and temperature for each climate division from 1950 to 2015. Correlation coefficients statistically significant at the 5% level are indicated by crosses. ( b ) Linear trends per year in explained variance calculated using the sliding correlation analysis. Crosses denote those trends that are statistically significant at the 5% level. ( c ) Same as ( b ) except for the explained variance calculated using the scale-averaged coherence analysis. In this case, explained variance is defined as the scale-averaged coherence multiplied by 100 because coherence by definition is the fraction of variance of one time series explained by another time series. The map was generated using MATLAB’s geoshow routine (MATLAB 2015a, http://www.mathworks.com/products/matlab/ ).

Article Snippet: The map was generated using MATLAB’s geoshow routine (MATLAB 2015a, http://www.mathworks.com/products/matlab/ ).

Techniques: Generated

Journal: Scientific Reports

Article Title: Strengthening North Pacific Influences on United States Temperature Variability

doi: 10.1038/s41598-017-00175-y

Figure Lengend Snippet: Correlation with 300-hPa streamfunction and Convective Precipitation. ( a ) The fraction of statistically significant correlation coefficients calculated between 300-hPa streamfunction and mean monthly temperature anomalies for the 344 US climate divisions. Red contours enclose regions where the mean correlation coefficient exceeds 0.1 and the blue contours enclose regions where the mean correlation coefficient falls below −0.1 Only climate divisions whose temperature time series was negatively correlated with the EP/NP index with at least 5% statistical significance were used in the computation of the means. ( b ) Same as ( a ) but for SST. ( c ) Same as ( a ) but for convective precipitation. The map was generated using MATLAB’s geoshow routine (MATLAB 2015a, http://www.mathworks.com/products/matlab/ ).

Article Snippet: The map was generated using MATLAB’s geoshow routine (MATLAB 2015a, http://www.mathworks.com/products/matlab/ ).

Techniques: Generated

Journal: Scientific Reports

Article Title: Strengthening North Pacific Influences on United States Temperature Variability

doi: 10.1038/s41598-017-00175-y

Figure Lengend Snippet: Correlation between EP/NP index and Atmospheric fields. ( a ) Correlation between EP/NP index and 300-hPa streamfunction. Black contours enclose regions of 5% statistically significance and the magenta contour encloses a region containing correlation coefficients greater than 0.4 used to fill the missing EP/NP index data. ( b ) Same as ( a ) but for SST. ( c ) Same as ( a ) but for convective precipitation. The map was generated using MATLAB’s geoshow routine (MATLAB 2015a, http://www.mathworks.com/products/matlab/ ).

Article Snippet: The map was generated using MATLAB’s geoshow routine (MATLAB 2015a, http://www.mathworks.com/products/matlab/ ).

Techniques: Generated

Journal: Scientific Reports

Article Title: Strengthening North Pacific Influences on United States Temperature Variability

doi: 10.1038/s41598-017-00175-y

Figure Lengend Snippet: Trends in explained variance. ( a ) Average trend in explained variance calculated using scale-averaged coherence between temperature and 300-hPa streamfunction from 1950 to 2015. The average was computed by averaging the scale-averaged coherence trends associated with 17 US climate divisions whose R 2 trends exceeded the 95 th percentile of all trends calculated in the sliding correlation analysis. Black contours enclose regions of statistically significant trends. ( b ) Same as ( a ) but for 300-hPa streamfunction from 1980 to 2015. The map was generated using MATLAB’s geoshow routine (MATLAB 2015a, http://www.mathworks.com/products/matlab/ ).

Article Snippet: The map was generated using MATLAB’s geoshow routine (MATLAB 2015a, http://www.mathworks.com/products/matlab/ ).

Techniques: Generated