Climate change
; Information use
; Probability density function
; Rain
; Storms
; Analytical formulation
; Annual precipitation
; Interannual variability
; Missing rainfall data
; Probability density function (pdf)
; Probability modeling
; Rainfall measurements
; Simplifying assumptions
; Precipitation (meteorology)
; algorithm
; annual variation
; numerical method
; numerical model
; precipitation (climatology)
; probability density function
; rainfall
; storm
英文摘要:
Interannual variability of precipitation is traditionally described by fitting a probability model to yearly precipitation totals. There are three potential problems with this approach: a long record (at least 25-30 years) is required in order to fit the model, years with missing rainfall data cannot be used, and the data need to be homogeneous, i.e., one has to assume stationarity. To overcome some of these limitations, we test an alternative methodology proposed by Eagleson (1978), based on the derived distribution (DD) approach. It allows estimation of the probability density function (pdf) of annual rainfall without requiring long records, provided that continuously gauged precipitation data are available to derive external storm properties. The DD approach combines marginal pdfs for storm depths and inter-arrival times to obtain an analytical formulation of the distribution of annual precipitation, under the simplifying assumptions of independence between events and independence between storm depth and time to the next storm. Because it is based on information about storms and not on annual totals, the DD can make use of information from years with incomplete data; more importantly, only a few years of rainfall measurements should suffice to estimate the parameters of the marginal pdfs, at least at locations where it rains with some regularity. � 2016 Author(s).
Department of Civil Engineering, University of Memphis, Memphis, TN, United States; Departamento de Ingenieri� Civil, Universidad de Concepci�n, Concepci�n, Chile; Institute of Environmental Engineering, ETH Z�rich, Zurich, Switzerland
Recommended Citation:
Meier C,I,, Sebasti�n Moraga J,et al. Describing the interannual variability of precipitation with the derived distribution approach: Effects of record length and resolution[J]. Hydrology and Earth System Sciences,2016-01-01,20(10)