Data and code for "Managing spatial data-transfer uncertainty in climate-driven ecological modelling: an integrated trace–attribute–localise–diagnose framework"
Year: 2026
Type: dataset
Abstract: This repository provides the data, code, metadata, and reproducibility materials supporting the study “Managing spatial data-transfer uncertainty in climate-driven ecological modelling: an integrated trace–attribute–localise–diagnose framework”. The study benchmarks how alternative spatial climate-data transfer operators propagate uncertainty into downstream ecological-model outputs. The factorial design comprises five CMIP6 global climate models, three Shared Socioeconomic Pathways, and three spatial transfer operators: nearest neighbour (NN), inverse-distance weighting using four neighbours (IDW4), and bilinear interpolation, yielding 45 complete CLIMEX endpoints over 92,163 CM10 Locations. Version 1.1.0 extends the original repository by adding the complete pointwise historical dataset and all 15 canonical NN future endpoints, enabling reconstruction of the full 45-endpoint pointwise benchmark. The archive includes the complete master table, exact factorial attribution, Location-level localisation of operator disagreement, EI-threshold sensitivity analysis from T=0 to T=20, spatial block-bootstrap diagnostics, spatial cross-validation materials, audit tables, reproduction scripts, documentation, and SHA-256 integrity manifests. Proprietary CLIMEX software and licensed CLIMEX/MetManager files are not redistributed. Original NASA NEX-GDDP-CMIP6 NetCDF source files are also excluded and remain available from their original provider. The repository instead supplies derived outputs, exact parameter metadata, source-data citations, file fingerprints, and reproducibility documentation sufficient to audit and reproduce the analytical workflow subject to access to the required third-party software and source climate data. DOI for this version: 10.5281/zenodo.22167906
Author: Ortiz-Jiménez, Mario Alberto
Language: English
Subfield: Ecological Modeling
Field: Environmental Science
Domain: Physical Sciences
SDG: Climate action
Open Access status: green
OpenAlex ID: W7204187880