Global Bias-Corrected CORDEX Dataset at Quarter Degree Resolution

High-resolution, bias-corrected climate data from the Coordinated Regional Downscaling Experiment (CORDEX) are essential for regional climate analysis and impact assessments. However, several existing products often rely on inconsistent adjustment methods, heterogeneous observational references, and limited spatial coverage, which hampers comparability across regions. To address this gap, we introduce GloBCORD-QD, a quasi-global dataset at 0.25° (~25 km) resolution covering the historical period (1979-2005) and future projections (2006-2099) under RCP2.6 and RCP8.5 scenarios. The dataset is generated by applying the trend-preserving ISIMIP3BASD quantile mapping approach to dynamically downscaled CORDEX-CORE simulations from four Earth System Models, using CHELSA-W5E5 as a unified observational reference across five key climate variables. Comprehensive validation demonstrates that GloBCORD-QD reduces systematic biases, increases distributional performance (Perkins Skill Score increasing from 0.66 to 0.97), and preserves climate change signals across variables, regions, and scenarios. The dataset integrates multiple CORDEX domains into a consistent quasi-global framework, enabling robust spatial comparisons while maintaining regional detail. By spanning a range of climate sensitivities across multiple models and providing methodologically consistent, high-resolution coverage, GloBCORD-QD can supports robust and comparable climate impact assessments across  various regions and sectors, contributing to improved uncertainty quantification and evidence-based climate adaptation and policy development.