You may have many questions about tropical precipitation features,
such as
- what is the mean climatology
- where are the maximum and minimum
precipitation regions
- how much does precipitation vary from the mean
climatology on seasonal, annual and interannual time scales
- what is the
diurnal variation,
- what other meteorological variables vary together with
precipitation
- what are the relationship among them
Some of these questions may already have answers, but some are still under
investigation.
Data analysis methods provide you the means to look insightfully at the
information in the data and help you answer these questions regarding tropical
precipitation features. Precipitation data or other meteorological data have
up to four dimensions. These are surface dimensions of width and length, the
dimension of vertical space extending from the earth to the upper levels of the
atmosphere and the time dimension. So, spatial and temporal variability of a
meteorological field is one of the basic features we have to analyze.
Moreover, there is more than one variable in a weather system, therefore the
study of mutual correlations among these meteorological variables is as
important as the feature itself. There are a variety of analysis methods that
are able to depict spatial and temporal characteristics of meteorological data,
and to extract the correlated variation signature from a pair of data
fields.
If you are new to the analysis methods in meteorology, you may
like to
learn them, and then apply these methods to tropical precipitation
data. Here we provide you
this opportunity. We describe some popular analysis
methods for meteorological data. If a method is suitable to
TRMM precipitation data, we will apply it to sample TRMM data,
and discuss the results.
All these TRMM data are
accessible via TRMM DATA SEARCH
AND ORDER SYSTEM at the GES DISC.
Contents
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Atmos Composition
