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How do you calculate missing rainfall data?
In this method simultaneous rainfall records of three close-by stations are made use of. The stations should however be evenly spaced around the station with missing records. A simple arithmetic average of the rainfall of the three selected stations gives the estimate of the missing value.
Why do we miss rainfall data?
Missing data is a common problem faced by researchers in environmental studies. Environmental data, particularly, rainfall data are highly vulnerable to be missed, which is due to several reasons, such as malfunction instrument, incorrect measurements, and relocation of stations.
What is rainfall frequency?
Rainfall Frequency means the probability of a rainfall event of defined characteristics occurring in any given year. Information on rainfall frequency is published by the National Weather Service.
How to estimate missing precipitation data from ITH?
1. Simple Arithmetic Mean Method. According to the arithmetic mean method the missing precipitation ‘Px’ is given as: Where ‘n’ is the number of nearby stations, ‘Pi’ is precipitation at ith station and ‘Px’ is missing precipitation. In case of three stations 1, 2 and 3, Px = (P1 + P2 + P3)/3.
Are there any data gaps in rainfall data?
The downloaded daily or hourly meteorological data through National Oceanic and Atmospheric Administration (NOAA), The Consortium of Universities for the Advancement of Hydrologic Science, Inc. (CUAHSI), HDFT web version of Environmental Protection Agency (EPA) contain lots of missing data. The data gaps are unique.
How is precipitation calculated in a rain gauge?
In this method, the precipitation amounts at the index stations are weighted by the ratios of their normal annual precipitation data in a relationship of the form: A double-mass curve is used to check the consistency of a rain gauge record:
How can I fill the missing climatological data?
Depending on how much effort you want to put on this, you may try the followings: 1. Use moving averages of say 3 to 5 steps. 2. Use regression with any neighboring stations for the month of the missing data, if it yields acceptable correlation. Correlation with climate GCM data may also be tested if you are familiar with such data.