Precipitation Data Analysis


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Precipation Data Analysis
  Precipitation Data Analysis  How to analyze rainfall data? ã In order to avoid erroneous conclusions it is important to give the proper interpretation to rainfall data. ã Checking data homogeneity ã For statistical analysis rainfall data from a single series should ideally possess property of homogeneity -i.e. properties or characteristics of different portion of the data series do not vary significantly. ã Rainfall data for multiple series at neighboring stations should ideally possess spatial homogeneity ã Tests of homogeneity is required for validation purposes and there is a shared need for such tests with other climatic variables  ã Secondary validation of rainfall data ã Spatial homogeneity testing ã Consistency tests using double mass curves ã Correcting and completing rainfall data ã Adjusting rainfall data for long-term systematic shifts  – double mass curves ã Basic statistics are widely required for validation and reporting. The following are commonly used: ã arithmetic meanã median -the median value of a ranked series Xi ã mode -the value of X which occurs with greatest frequency or the middle value of the class with greatest frequency ã standard deviation -the root mean squared deviation Sx: ã skewnessand kurtosis  ã Rain is well described in terms of a depth of rainfall over a certain duration. ã Duration -period of time over which the rain is measured e.g. one year -in the case of annual rainfall; one month (for many climate purposes); or so many days, hours or minutes ã Rainfall rate or intensity rate (in mm per hour is calculated by dividing the depth by the duration and is simply a measure of the 'heaviness' of the rainfall.
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