Dynamic Parameterization of Priestley-Taylor Coefficient for a More Accurate Potential Evapotranspiration Estimation in Ungauged Regions

Title: "Dynamic Parameterization of Priestley-Taylor Coefficient for a More Accurate Potential Evapotranspiration Estimation in Ungauged Regions"Authors: Pushpendra Raghav, Mukesh KumarAffiliation: Department of Civil, Construction, and Environmental Engineering, University of Alabama, Tuscaloosa, AL, USAContact: ppushpendra@ua.edu The scripts attached are self-explanotory and require input fluxnet data that users can obtain from publicly available sources like AmeriFLux (https://ameriflux.lbl.gov), FluxNet2015 (https://fluxnet.org/data/fluxnet2015-dataset/), ICOS (https://www.icos-cp.eu/data-products/YVR0-4898), etc. LAI data used here was obtained from Moderate Resolution Imaging Spectroradiometer (MODIS) product (MCD15A2H). Below is the description of each file: File "MyFuns_ReadData_FluxNet2015_JapanFlux2024_OzFlux_AMF.py": It read fluxnet data from different sources and performs quality control according to the procedures outlined in the manuscript. File "myPET_funs.py": It contains functions for estimating Potential Evapotranspiration (PET) uisng different methods (e.g., Priestley-Taylor, Penman-Monteith,Penman-Monteith-FAO, etc.). File "meteo_utils.py": It contains utility functions for meteorological data. File "Run_Optimization.py" estimates monthly optimized advection coefficient (alpha) in the Priestley-Taylor equation acorss all flux sites. File "Check_Model_Generability.py" tests the robustness of transferability of dynamic alpha parameterization. File "alpha_sensitivity_EF.csv" contains optimized alpha across all sites.