Global Correlations During Mar-Apr Using 4 Spatial Data Sets
Each Data Set Compared Against 10 Average May Values
Within Box Bounded by Lat: 60 to 70 & Lon: 195 to 220
YouTube Video Correlation Interpretation 9:34
  Mar-Apr SLP Mar-Apr Z500 Mar-Apr T2M Mar-Apr T925 Mar-Apr SST
Compare With
Ave May
SLP Within
Bounding Box
Compare With
Ave May
Z500 Within
Bounding Box
Compare With
Ave May
T2M Within
Bounding Box
Compare With
Ave May
T925 Within
Bounding Box
Compare With
Ave May
SST Within
Bounding Box
Compare With
Ave May
Global PDO
Index Value
Compare With
Ave May
Global NPM
Index Value
Compare With
Ave May
Global SOI
Index Value
Compare With
Ave May
Sea Ice
Departure From
Trend Line
Sample Interpretation: The user selected the Mar-Apr time period for analysis. This time period is used to generate a forecast for the May time period. This page does not show the analog forecasts. Instead it shows spatial correlations. An average variable value is computed for the Lat: 60 to 70 & Lon: 195 to 220 spatial domain during every May time period; e.g., an average SLP value. This gives us a list of 68 values for all May time periods - one for each year. A total of 10 lists were generated each containg average values for the forecast domain (SLP, Z500 , T2M, T925 , SST, PDO, NPM, SOI, and sea ice departure from the trend line) during each year. Each of these lists of average values were spatially correlated, grid point by grid point, with the four atmospheric data sets (SLP, Z500 , T2M, and T925 ) against the Mar-Apr time period. It may be the case that the initial analogs run used a selection area with a very poor Mar-Apr correlation with May conditions. Inspection of these correlations will therefore improve the results on sunsequent iterations.