Basin-Scale Vegetation Sensitivity to Relative Humidity Variability Across Türkiye Under CMIP6 SSP Pathways

Relative humidity (RH) provides complementary information on atmospheric moisture conditions that is not captured by precipitation alone. This study characterizes basin-scale RH-associated vegetation sensitivity across Türkiye’s 25 hydrographic basins using MODIS MOD13A1 NDVI observations for 2000–2024 and processed CMIP6-derived RH products for SSP1-2.6, SSP2-4.5, SSP3-7.0 and SSP5-8.5 at the 2040, 2060, 2080 and 2100 single-year horizons. MODIS and climate-model products are summarized independently at basin scale, avoiding pixel-level fusion across different native resolutions. The archived 25-by-4 pathway sensitivity matrix is evaluated using cross-pathway dispersion, a robust median-magnitude check, hierarchical clustering with silhouette diagnostics, and explicit percentile-based hotspot criteria. Mean absolute sensitivity is 0.0244, 0.0236, 0.0368, and 0.0386 under SSP1-2.6, SSP2-4.5, SSP3-7.0, and SSP5-8.5, respectively. Antalya, Küçük Menderes, Konya Closed, Ceyhan, and Aras satisfy the magnitude and persistence criteria, and all five also exceed the upper-quartile threshold for median absolute sensitivity. Silhouette diagnostics do not support a unique three-cluster solution, favoring explicit threshold-based response classes. The results are interpreted as comparative basin screening rather than causal attribution or validated vegetation forecasting. Because the retained processed products do not preserve model/member provenance or the horizon-level intermediate values used to generate the pathway index, model-specific and predictive interpretations are deliberately avoided.

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Publication Details

Journal
Climate
Published
2026-09-01
DOI
https://doi.org/10.3390/cli14090179
Primary Topic
Remote Sensing in Agriculture
Type
article
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article

Basin-Scale Vegetation Sensitivity to Relative Humidity Variability Across Türkiye Under CMIP6 SSP Pathways

Yasin Paşa, Mehmet Ali Çelik, İshak Paçal, Adile Bilik
Climate
Remote Sensing in Agriculture
article

Basin-Scale Vegetation Sensitivity to Relative Humidity Variability Across Türkiye Under CMIP6 SSP Pathways

Yasin Paşa, Mehmet Ali Çelik, İshak Paçal, Adile Bilik
article en

Abstract

Relative humidity (RH) provides complementary information on atmospheric moisture conditions that is not captured by precipitation alone. This study characterizes basin-scale RH-associated vegetation sensitivity across Türkiye’s 25 hydrographic basins using MODIS MOD13A1 NDVI observations for 2000–2024 and processed CMIP6-derived RH products for SSP1-2.6, SSP2-4.5, SSP3-7.0 and SSP5-8.5 at the 2040, 2060, 2080 and 2100 single-year horizons. MODIS and climate-model products are summarized independently at basin scale, avoiding pixel-level fusion across different native resolutions. The archived 25-by-4 pathway sensitivity matrix is evaluated using cross-pathway dispersion, a robust median-magnitude check, hierarchical clustering with silhouette diagnostics, and explicit percentile-based hotspot criteria. Mean absolute sensitivity is 0.0244, 0.0236, 0.0368, and 0.0386 under SSP1-2.6, SSP2-4.5, SSP3-7.0, and SSP5-8.5, respectively. Antalya, Küçük Menderes, Konya Closed, Ceyhan, and Aras satisfy the magnitude and persistence criteria, and all five also exceed the upper-quartile threshold for median absolute sensitivity. Silhouette diagnostics do not support a unique three-cluster solution, favoring explicit threshold-based response classes. The results are interpreted as comparative basin screening rather than causal attribution or validated vegetation forecasting. Because the retained processed products do not preserve model/member provenance or the horizon-level intermediate values used to generate the pathway index, model-specific and predictive interpretations are deliberately avoided.

ClimateVol. 14(9)
Fenerbahçe University (TR), Iğdır Üniversitesi (TR), İstanbul Gelişim Üniversitesi (TR), Nakhchivan State University (AZ)
Climate action
Openalex Percentile: Top 10%
Remote Sensing in Agriculture
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