G6904 – Fall 2012 – Assignment #3 – Cluster Analysis
DUE 21 October 2015
Dataset: Global maps of Earth surface temperature (TS) for July 2004 every 3 hrs GMT
(8 files/day x 31 days) = 248 files; Global maps of daily surface air temperature (TA),
precipitable water (WV) and cloud water path (WP) for 2004; Map covers whole globe at
2.5 degree intervals = 72 x 144 array), Values are REAL (xxx.xx) – ASCII
Assignment:
(1) Using the July 2004 TS data, determine for each map cell, the average range of
diurnal temperature variations and make a map of this quantity. Describe how you did
this. Also, make a map of the monthly average temperatures. Define two vectors, the
variation in the maps of the mean temperature and the diurnal range. Perform a K-means
cluster analysis of these two vectors. Make a map where a unique color (classification) is
assigned to each cluster that you found.
(2) Using the 2004 daily average TA and WV datasets for the whole year, determine for
each map cell the average seasonal variations of temperature and humidity and make
maps of these two quantities. Describe how you did this. Define two vectors, the
variation in the maps of the seasonal range of temperature and the seasonal range of
humidity. Perform K-means cluster analysis of these two vectors. Make a map where a
unique color (classification) is assigned to each cluster that you found.
(3) Using the 2004 daily average WV and WP datasets, determine for each map cell the
average seasonal variations of water vapor and cloud water path and make maps of these
two quantities. Define two vectors, the variation in the maps of the seasonal range of
water vapor and the seasonal range of water path. Perform K-means cluster analysis of
these two vectors. Make a map where a unique color (classification) is assigned to each
cluster that you found.
(4) For each exercise above, answer the following questions.
(a) Did you make any modifications to the two datasets before applying the cluster
analysis?
(b) How many clusters did you find?
(c) How did you decide the number of clusters? What evidence can you present that these
clusters are different and that this is the right number?
(d) Can you explain the geographic pattern of the classification results?