Publication date: December 2020

Abstract

There is a growing demand for data to support climate adaptation efforts, driven by political and practical needs, in the international response to the Paris Agreement. This paper provides an overview of the categories of data required for effective adaptation, the current forms of data provision at different scales, existing gaps, and challenges and opportunities for improving the provision and use of such data.

Adaptation to climate risks involves a continuous and iterative process comprising risk assessment, planning, implementation, and monitoring. These stages necessitate diverse data, including observational, projected, and historical data on both climate and socioeconomic processes. National Meteorological and Hydrological Services (NMHSs) play a central role in providing climate data, while socioeconomic data is sourced from various uncoordinated outlets.

Despite progress, significant gaps persist, especially in regions with heightened risks and insufficient observational systems. Challenges include the lack of downscaled model data at local levels and uncertainties related to climate change drivers and adaptation effectiveness. Data quality assurance faces increasing difficulties due to demands for timely and specific information.

Opportunities for enhancing data provision include leveraging big data through innovative solutions like machine learning, ensuring open access to existing data, and closing remaining gaps through long-term funding for observational systems. Capacity development for data providers and users, especially in vulnerable regions, is crucial. Encouraging data use requires addressing uncertainty through tools such as risk management, participatory approaches, and robust decision-making.