experimental data of the paper

Overview This repository stores all processed derivative datasets, modeling Python scripts, figure support files and analytical outputs generated in this study, based on open-source raw ERA5-Land meteorological reanalysis, MODIS NDVI vegetation index, and SRTM topographic datasets covering the Qinghai–Tibetan Plateau from 2000 to 2020. All original raw datasets are freely accessible via their official public repositories and are not included here to avoid copyright infringement and excessive storage size. Folder Structure Description 1. /dataset This directory contains post-processed monthly ERA5-Land meteorological variables stored as independent NetCDF (.nc) files, separated into subfolders by single climate factor: ERA5_evavt: Total evaporation ERA5_ssr: Net solar radiation at the surface ERA5_swvl1: Volumetric soil water in the topsoil layer (0–7 cm, surface soil moisture) ERA5_swvl2: Volumetric soil water in the second soil layer (7–28 cm, deep soil moisture) ERA5_t2m: 2 m air temperature ERA5_tp: Total precipitation Each subfolder holds spatially clipped, study-area-masked, temporally aggregated monthly NC files tailored for the dual-branch Mamba–SHAP time-lag modeling framework. All time series were standardized into a 24-month sliding lag sequence for vegetation-climate lag response quantification. 2. /python This folder contains complete Python code for the full analytical workflow, including Mamba model training & prediction, SHAP time-lag decomposition, terrain-gradient statistical analysis, seasonal pattern calculation, and all visualization scripts for manuscript figures. 3. /figures This folder includes intermediate data tables, raster extracts, and calculation outputs used to generate all manuscript figures, covering topography grouping statistics (elevation, slope, aspect), SHAP lag contribution results, lag difference comparisons across terrain gradients, and model prediction accuracy metrics. Data Source Statements Raw ERA5-Land meteorological reanalysis data: ECMWF Copernicus Climate Data Store (CDS) MODIS NDVI vegetation dataset: National Tibetan Plateau Data Center SRTM topographic DEM: USGS EarthExplorer Permanent download links for all raw input datasets are listed in the manuscript Data Availability section. Usage Notes All NetCDF files adopt consistent geographic projection, spatial resolution, and monthly time steps matching the NDVI vegetation time series. The provided Python scripts can be run sequentially with the supplied derivative datasets to fully reproduce multi-factor time-lag response modelling, topographic modulation analysis, and all figures presented in the manuscript. This compiled derivative dataset and code are shared under the CC0 1.0 Universal Public Domain Dedication, for non-commercial academic research purposes only. Contact Corresponding author: Xianyu Yu Email: [e-mail]