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Outlines best practices for developing climate data tools to aid decisionmakers in implementing effective policy changes.
The growing demand for climate data tools to support planning, design, and policy decisions has led to a proliferation of platforms, dashboards, and datasets. However, not all tools are equally effective in bridging the gap between climate science and actionable policy. This paper synthesizes insights from eight years of collaboration with decisionmakers across government agencies, water utilities, and other practitioners to develop over 30 climate and environmental data tools. These tools, created as part of the Mid-Atlantic Climate Adaptation Partnership/Regional Integrated Sciences and Assessments Program (MARISA), address diverse challenges such as drought preparedness, air quality management, stormwater infrastructure design, extreme heat management, and environmental modeling. Drawing from user feedback, surveys, and interviews, as well as lessons learned during tool development and maintenance, we outline six best practices for creating user-centered climate data tools. These practices emphasize addressing user-defined data gaps, designing for real-world integration, matching tool complexity to user capacity, prioritizing iterative development, enabling continuous improvement, and supporting users with complementary resources. By distilling key lessons and emerging best practices, this paper aims to guide researchers and developers working at the science–policy interface, supporting a growing community of practice focused on translating climate data into meaningful policy action.
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Miro et al. (2026) studied this question.
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