In this study, we investigated whether pictures of natural hazards (i.e., climate change consequences) elicit automatic (negative) affective responses using a picture-word interference task. In picture-word interference tasks, affective pictures and words are paired such that picture valence and word valence match (congruent) or mismatch (incongruent). Participants classify the valence of words (or pictures; targets) via key presses. Corresponding congruency effects in response times or error rates thus indicate that pictures (or words; distractors) interfered with target processing, that is, distractors elicited an automatic affective response. Here, we assessed how 12 natural hazard (negative) and 12 intact landscape (positive) pictures (distractors) interfered with the classification of four affective words (targets) as negative or positive. The obtained congruency effects demonstrate that natural hazard pictures (showing landslides, hail, wildfires, or droughts) elicit automatic affective responses, even though their valence can only be inferred based on scene semantics. Further, this implicit affective response measure did not correlate with self-report valence or arousal ratings for corresponding affective pictures, suggesting differences in the affective processes underlying implicit and explicit affective response measures. We conclude that picture-word interference tasks are a suitable means for determining implicit affective responses to even complex pictures, here negative affective responses to natural hazard scenes. This method thus also lends itself to investigations of affective responses in the context of climate change.