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precipitation

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Python Package for Empirical Statistical Downscaling. pyESD is under active development and all colaborators are welcomed. The purpose of the package is to downscale any climate variables e.g. precipitation and temperature using predictors from reanalysis datasets (eg. ERA5) to point scale. pyESD adopts many ML and AL as the transfer function.

  • Updated Nov 5, 2024
  • Python
intensity_duration_frequency_analysis

heavy rain as a function of the duration and the return period acc. to DWA-A 531 (2012) This program reads the measurement data of the rainfall and calculates the distribution of the rainfall as a function of the return period and the duration for duration steps up to 12 hours (and more) and return period in a range of '0.5a <= T_n <= 100a'

  • Updated Oct 21, 2024
  • Python

A suite of programs aimed at producing temporal series based on the observational dataset. Daily data of precipitation, maximum temperature and minimum temperature are produced. Two different algorithms have been developed: 1) generation of single point weather data series. 2) generation of a spatially coherent two-dimensional data series.

  • Updated Sep 16, 2024
  • C++

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