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

<strong>Description:</strong> 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.<br><strong>Datasets:</strong><br><strong>cml_metadata.csv:</strong> contains information about the frequency, polarization, and coordinates of CMLs.<br><strong>rainfall_field_rain_rates.zip:</strong> contains high-resolution simulated rainfall fields (210 events).<br><strong>rainfall_field_coordinates.csv: </strong>contains the coordinates of each grid cell in the simulated rainfall fields.<br><strong>virtual_rain_rates_along_CMLs.Rdata:</strong> contains the distributed and path-averaged rain rates along the CML paths.<br><strong>clearEnsemble.Rdata:</strong> contains 50 realizations of the CLEAR algorithm as well as the GMZ benchmark.<br><strong>w_table_all_events.Rdata: </strong>contains the empirical cascade weights needed to fit the standard deviation model of the cascade generator.<br><strong>Codes:</strong><br><strong>fun_CLEAR.R:</strong> Functions and helper functions for the CLEAR algorithm.<br><strong>fun_CML.R: </strong>Functions for processing CML data, also available at GitHub (https://github.com/fenclmar/Rcmlrain/tree/master)<br><strong>01_sample_estimation_empirical_weights.Rmd</strong>: R script for calculating empirical cascade weights.<br><strong>02_sample_estimation_fitting_SDmodel.Rmd</strong>: R script for fitting the cascade generator model.<br><strong>03_extract_virtual_rainfall_from_CMLs.Rmd:</strong> R script for extracting distributed and path-averaged rain rates from virtual rainfall fields.<br><strong>04_CLEAR_disaggregation.Rmd:</strong> R script for disaggregating and resampling path-averaged CML rain rates using the CLEAR and GMZ algorithms.

<strong>数据集说明：</strong> 本数据集包含发表论文《CLEAR：一种用于解译商用微波链路（Commercial Microwave Links, CML）路径积分降雨估算值的新型离散乘法随机级联模型》所依托的全部核心数据与代码。如需了解各数据集及脚本的详细内容，请参阅README文档。<br><strong>数据集列表：</strong><br><strong>cml_metadata.csv：</strong>包含CML的频率、极化方式及坐标信息。<br><strong>rainfall_field_rain_rates.zip：</strong>包含210个事件的高分辨率模拟降雨场数据。<br><strong>rainfall_field_coordinates.csv：</strong>包含模拟降雨场中每个网格单元的坐标信息。<br><strong>virtual_rain_rates_along_CMLs.Rdata：</strong>包含沿CML路径分布的、经路径平均的降雨率数据。<br><strong>clearEnsemble.Rdata：</strong>包含CLEAR算法的50次实现结果以及GMZ基准测试结果。<br><strong>w_table_all_events.Rdata：</strong>包含用于拟合级联生成器标准差模型所需的经验级联权重数据。<br><strong>代码文件：</strong><br><strong>fun_CLEAR.R：</strong>包含CLEAR算法的核心函数及辅助函数。<br><strong>fun_CML.R：</strong>包含用于处理CML数据的函数，该脚本亦可在GitHub（https://github.com/fenclmar/Rcmlrain/tree/master）获取。<br><strong>01_sample_estimation_empirical_weights.Rmd：</strong>用于计算经验级联权重的R脚本。<br><strong>02_sample_estimation_fitting_SDmodel.Rmd：</strong>用于拟合级联生成器模型的R脚本。<br><strong>03_extract_virtual_rainfall_from_CMLs.Rmd：</strong>用于从模拟降雨场中提取分布型及路径平均降雨率的R脚本。<br><strong>04_CLEAR_disaggregation.Rmd：</strong>用于借助CLEAR与GMZ算法对路径平均CML降雨率进行解译与重采样的R脚本。