 |
| | | | | Rainfall Variability | |
| |
|
|
| The global rainfall pattern by classes
|
 |
|
|
|
|
Global rainfall pattern
|
|
|
|
|
|
|
|
|
|
|
|
|
|
Global map
All profiles
The driest
Intermediate classes
The wettest
Coefficient of variation
Classification
Method
To get an overview of global rainfall variability, a pixel-by-pixel classification
has been performed. On that way, areas with similar climatological characteristics
can be identified. The analysis is based on the yearly series of the annual
rainfall images, expressed in mm/month, drawn from the NOAA data base. Using
ADDAPIX software, a spatial and temporal analysis is achieved. After submitting
the yearly series to a principal component analysis a non hierarchical cluster
analysis follows. The principal component analysis allows the reduction of the
data sample with a negligible loss of information. Mostly, a small number of
principle components explain an overwhelming majority of the overall
varialbility of the input data. Subsequently, clustering of the pixels on
the basis of the chosen first principle components is performed in order to
define regions with similar characteristics in rainfall variability between
1961 and 2002. In this analysis we restricted to a number of 12 classes.
The global map
(see menu) shows the spatial distribution of the classes.
Results
As anticipated, the global map with the geographical distribution of the 12
rainfall classes shows the driest classes in the subtropics, the wettest in
the tropical region and intermediate rainfall amounts in
great parts of the midlatitude regions. But superimposed orographic effects
and circulation systems also result in exalted spatial variations of yearly
rainfall amounts (see the rainfall classes of
Burkina Faso,
Cambodia,
Tanzania and
Nepal).
Furthermore, the profiles of the annual rainfall amounts, expressed in
mm/month, are plotted for every rainfall class. In order to compare
the rainfall variability of the rainfall classes, each rainfall amount of
a single year is divided by the average monthly rainfall amount of the
respective class and multiplied with 100. Obviously, the drier the rainfall
class the higher is the interannual variability.
Semi-arid and arid climates show a higher variability than moist climates.
Less variability can be found in countries with high rainfall or in large
countries, which include several agroecological zones.
For a clearer presentation the profiles of
the driest, the
intermediate classes and
the wettest classes
are plotted seperately. Apparently, the presentation of these profiles
also makes the detection of drought-cycles possible. The coefficient
of variation allows a comparison of the variation of populations that
have significantly different mean values. Plotting the coefficient of
variation versus the average monthly rainfall underlines the statements above
(see coefficient of variation).
|
|
|
