Data and codes underlying the publication: "CLEAR: a new discrete multiplicative random cascade model for disaggregating path-integrated rainfall estimates from commercial microwave links"

Description: This dataset contains all essential data and codes underlying the publication "CLEAR: a new discrete multiplicative random cascade model for disaggregating path-integrated rainfall estimates from commercial microwave links". Please see the README for more in-depth information about the content of each dataset and script.


Datasets:

cml_metadata.csv: contains information about the frequency, polarization, and coordinates of CMLs.

rainfall_field_rain_rates.zip: contains high-resolution simulated rainfall fields (210 events).

rainfall_field_coordinates.csv: contains the coordinates of each grid cell in the simulated rainfall fields.

virtual_rain_rates_along_CMLs.Rdata: contains the distributed and path-averaged rain rates along the CML paths.

clearEnsemble.Rdata: contains 50 realizations of the CLEAR algorithm as well as the GMZ benchmark.

w_table_all_events.Rdata: contains the empirical cascade weights needed to fit the standard deviation model of the cascade generator.


Codes:

fun_CLEAR.R: Functions and helper functions for the CLEAR algorithm.

fun_CML.R: Functions for processing CML data, also available at GitHub (https://github.com/fenclmar/Rcmlrain/tree/master)

01_sample_estimation_empirical_weights.Rmd: R script for calculating empirical cascade weights.

02_sample_estimation_fitting_SDmodel.Rmd: R script for fitting the cascade generator model.

03_extract_virtual_rainfall_from_CMLs.Rmd: R script for extracting distributed and path-averaged rain rates from virtual rainfall fields.

04_CLEAR_disaggregation.Rmd: R script for disaggregating and resampling path-averaged CML rain rates using the CLEAR and GMZ algorithms.