The ability of cerebrovasculature to respond to meet tissue demands is vital for normal brain function and health. Cerebrovascular reactivity (CVR), a measure of the responsiveness of cerebrovasculature to vasoactive stimuli, is a valuable tool for evaluating cerebrovascular health. Although CVR is commonly assessed using transcranial Doppler ultrasound (TCD), which measures blood velocity, or magnetic resonance imaging (MRI)-based techniques such as blood-oxygen-level-dependent (BOLD) imaging, which reflect changes in blood oxygenation, direct comparisons between these modalities remain limited, particularly with stimuli that induce a large dynamic range. Because both methods capture hypercapnia-induced vascular changes, we hypothesized that their CVR metrics may be correlated. This study evaluates intermodality correlations of CVR using TCD and BOLD-functional MRI (fMRI) extracted from the middle cerebral artery territory (parietal lobe) during a ramped hypercapnic protocol and different modeling strategies. Linear correlations across broad end-tidal partial pressure of carbon dioxide ([Formula: see text]) ranges validated the utility of linear CVR modeling in capturing repeatable metrics using TCD and MRI. A four-parameter sigmoid model revealed significant intermodality variability in span and bound parameters, improved by fixing these parameters and focusing on slope and inflection point, which enhanced the correlations between modalities. These results support the reliability of linear CVR modeling within narrow vasoactive response ranges in healthy subjects and propose a simplified two-parameter sigmoid model as an effective framework for characterizing nonlinear CVR dynamics. This work adds to the sparse literature on intermodality CVR comparisons and indicates which CVR metrics are comparable between TCD and BOLD-fMRI, emphasizing CVR as a useful tool for assessing cerebrovascular health in research and clinical contexts.NEW & NOTEWORTHY This study compares cerebrovascular reactivity (CVR) between transcranial Doppler ultrasound (TCD) and BOLD-fMRI using a hypercapnia protocol. Linear intermodality correlations across [Formula: see text] ranges validate linear CVR modeling. Significant variability in a four-parameter sigmoid model was mitigated by fixing span and bound parameters, supporting a two-parameter model for improved agreement but reducing sensitivity to diminished reserve. These findings clarify which CVR metrics are consistent between TCD and BOLD-fMRI, advancing multimodal integration for cerebrovascular health assessment.