Global Correlations During Jun-Nov Using 4 Spatial Data Sets
Each Data Set Compared Against 10 Average Dec Values
Within Box Bounded by Lat: -20 to -10 & Lon: 300 to 340
YouTube Video Correlation Interpretation 9:34
  Jun-Nov SLP Jun-Nov Z500 Jun-Nov T2M Jun-Nov RH600 Jun-Nov SST
Compare With
Ave Dec
SLP Within
Bounding Box
Compare With
Ave Dec
Z500 Within
Bounding Box
Compare With
Ave Dec
T2M Within
Bounding Box
Compare With
Ave Dec
RH600 Within
Bounding Box
Compare With
Ave Dec
SST Within
Bounding Box
Compare With
Ave Dec
Global PDO
Index Value
Compare With
Ave Dec
Global NPM
Index Value
Compare With
Ave Dec
Global SOI
Index Value
Compare With
Ave Dec
Sea Ice
Departure From
Trend Line
Sample Interpretation: The user selected the Jun-Nov time period for analysis. This time period is used to generate a forecast for the Dec time period. This page does not show the analog forecasts. Instead it shows spatial correlations. An average variable value is computed for the Lat: -20 to -10 & Lon: 300 to 340 spatial domain during every Dec time period; e.g., an average SLP value. This gives us a list of 68 values for all Dec time periods - one for each year. A total of 10 lists were generated each containg average values for the forecast domain (SLP, Z500 , T2M, RH600 , 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 RH600 ) against the Jun-Nov time period. It may be the case that the initial analogs run used a selection area with a very poor Jun-Nov correlation with Dec conditions. Inspection of these correlations will therefore improve the results on sunsequent iterations.