Published January 19, 2026 | Version v3
Preprint Restricted

Divergence in global and regional hydroclimatic projections amplified by evapotranspiration state dependence increases maladaptation risk

  • 1. Global Change Research Institute CAS
  • 2. ROR icon Mendel University in Brno
  • 3. EDMO icon Duke University
  • 4. ROR icon Czech University of Life Sciences Prague

Description

Global climate models (GCMs) capture large-scale thermodynamic responses to anthropogenic forcing; however, their coarse spatial resolution limits their utility for impact-relevant hydroclimatic assessment. Regional climate models (RCMs) have been developed to address this limitation through dynamic downscaling, yet their hydroclimatic projections frequently diverge from those of their driving GCMs. Here, contrasting projections for Central Europe under a high-emission scenario are examined: GCMs indicate increasing aridity, whereas RCMs project an intensifying hydrological cycle, with increases in evapotranspiration (ET), precipitation (P), and runoff. An independent Budyko framework linking the aridity index to the evaporative index (EI = ET/P) is used to diagnose these contrasts. Across ensembles, EI remains relatively stable, revealing a robust, state-dependent bimodality in the ET response to vapour pressure deficit (VPD). RCMs occupy the wet branch with increasing ET under rising VPD, whereas GCMs span a broader range of hydroclimatic states, including regimes characterised by declining ET at higher VPD, consistent with an apparent feedforward response whereby enhanced atmospheric demand coincides with stomatal limitation. This bimodality implies that antecedent hydroclimatic model states continue to shape future projections despite standard statistical post-processing, challenging the assumption that higher spatial resolution alone guarantees physically consistent projections for impact and adaptation assessments.

Notes

The manuscript is currently under review at Communications Earth & Environment and is therefore provided in restricted form.

The analysis code and full reproducibility workflow are available at: https://github.com/MilanFischer/GCM-RCM

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Additional details

Funding

Czech Science Foundation
The role of coherent structures in turbulent energy transport and energy balance non-closure 24-12935S
Ministry of Education Youth and Sports
AdAgriF - Advanced methods of greenhouse gases emission reduction and sequestration in agriculture and forest landscape for climate change mitigation CZ.02.01.01/00/22_008/0004635
U.S. National Science Foundation
CAS-MNP--Precursors of Long-Distance Aerial Transport of Fine Particulate Matter and Microorganisms NSF-AGS-2028633
United States Department of Energy
Phloem Catastrophe: Using Bifurcation Analysis to Predict Plant Tipping Points DE-SC0022072
Czech University of Life Sciences Prague
REES - Research Excellence in Environmental Sciences

Software

Repository URL
https://github.com/MilanFischer/GCM-RCM
Programming language
R , Python