CORDEX AFR44 Model Evaluation Data for the Melka-Wakena Watershed, Ethiopia

#OverviewThis dataset supports the study on Africa-CORDEX Regional Climate Models' performance evaluation in simulating air temperature (tasmax and tasmin) and precipitation in the Melka-Wakena watershed, Ethiopia. The evaluation spans from 1991 to 2005 and includes observed daily data and raw CORDEX AFR44 daily data for tasmax, tasmin, and precipitation. The dataset was analyzed using scatter plots, empirical cumulative distribution functions (ECDF), Taylor diagrams, and multi-metric performance evaluations.

#Files and Structure1. Data/>>This directory contains all input and processed datasets used in the study.

#Observed_Data/

>>Observed_Tasmax.csv: Observed daily maximum temperature (tasmax) data.>>Observed_Tasmin.csv: Observed daily minimum temperature (tasmin) data.>>Observed_Precipitation.csv: Observed daily precipitation data.

#CORDEX_Raw_Data/

>>CORDEX_Tasmax_Raw.csv: Daily tasmax data from CORDEX AFR44 models.>>CORDEX_Tasmin_Raw.csv: Daily tasmin data from CORDEX AFR44 models.>>CORDEX_Precipitation_Raw.csv: Daily precipitation data from CORDEX AFR44 models.

#Processed_CORDEX_Data/

>>CORDEX_Tasmax_Processed.csv: Preprocessed daily tasmax data for analysis (e.g., aggregated and formatted).>>CORDEX_Tasmin_Processed.csv: Preprocessed daily tasmin data for analysis.>>CORDEX_Precipitation_Processed.csv: Preprocessed daily precipitation data for analysis.

2. Scripts/This directory contains Python scripts used for preprocessing, evaluation, and visualization of the data.

#Data_Preprocessing_Scripts/

>>Preprocess_Tasmax.py: Script to preprocess daily tasmax data.>>Preprocess_Tasmin.py: Script to preprocess daily tasmin data.>>Preprocess_Precipitation.py: Script to preprocess daily precipitation data.

#Evaluation_Scripts/

>>Scatter_Plot_Script.py: Script for scatter plot visualizations comparing observed and model data.>>ECDF_Script.py: Script for generating empirical cumulative distribution functions (ECDF).>>Taylor_Diagram_Script.py: Script for generating Taylor diagrams to evaluate model performance.>>Performance_Metrics_Script.py: Script to compute evaluation metrics.>>Approach_Comparison_Script.py: Script for comparing different model evaluation approaches using multi-metric weighted ranking.

#Metadata>>Study Area: Melka-Wakena watershed, Ethiopia.>>Time Period: 1991–2005.#Data Source:>>Observed data from local meteorological stations.>>CORDEX AFR44 model data downloaded from the Earth System Grid Federation (ESGF).

#Variables:Tasmax: Daily maximum temperature (°C).Tasmin: Daily minimum temperature (°C).Precipitation: Daily precipitation (mm/day).Evaluation Metrics: RMSE, MAE, R², NSE, Percent Bias (PBIAS) ,and others.

#How to UseDownload the dataset:All required data files are organized in the Data/ folder.

#Run the preprocessing scripts:>>If using new datasets, preprocess the raw data using the scripts in Data_Preprocessing_Scripts/. This step formats the data and ensures compatibility with the evaluation scripts.

#Conduct evaluation:

>>Use the Evaluation_Scripts/ to replicate scatter plots, ECDF, Taylor diagrams, and compute performance metrics.>>Use Approach_Comparison_Script.py for multi-metric weighted ranking comparisons of model performance.

#Citation>>When using this dataset, please cite the following:

#The dataset:"Dataset for CORDEX AFR44 Model Evaluation in the Melka-Wakena Watershed, Ethiopia."DOI: https://doi.org/10.5281/zenodo.14208274

#The source of CORDEX data:>>CORDEX AFR44 data, available from the Earth System Grid Federation (ESGF).

ContactFor questions or additional information, contact:

Tadele: [e-mail].