Overview Climate change poses an increasing threat to people and their livelihoods. Record heat waves, catastrophic floods, prolonged droughts, and other extreme weather events in Asia and the Pacific are becoming more frequent. However, critical data gaps hinder the understanding of climate impacts, particularly on vulnerable populations in developing Asia and the Pacific. National statistical systems, which include national statistics offices and other government agencies responsible for compiling official statistics, play a crucial role in gathering and analyzing climate change data. They provide insights into how economies are performing in terms of climate-related targets, forming the foundation for informed policy decisions and the development of effective strategies for mitigating and adapting to climate change impacts. A survey conducted by Asian Development Bank (ADB) statisticians presents evidence of statistical gaps in climate change data systems. The findings highlight how to better understand the implications of these gaps for vulnerable populations in developing Asia. The results also underscore the importance of strengthening the capacity of national statistical systems to address these challenges. This article presents key takeaways from the survey included in the 55th edition of Key Indicators for Asia and the Pacific: Data for Climate Action. Statistical Gaps in Key Areas Accurate, timely, and comprehensive climate data is essential for making informed decisions, guiding policy development, and creating effective interventions to address the impact of climate change in the region. Without meaningful climate data, policymakers struggle to develop and implement strategies to tackle the complex challenges of climate change, potentially putting the Asia and the Pacific’s pursuit for sustainable development at risk. Over time, the quality of data for select climate change indicators has improved and continues to do so. For example, data on historic weather patterns and future climate projections now cover longer periods and offer enhanced spatial and temporal resolution, thanks to advances in climatological science, although uncertainties remain. However, significant statistical gaps persist in several key areas. Climate risk and climate vulnerability data indices are still relatively underdeveloped in major international databases. A major shortcoming is the lack of granular data connecting climate change and social development. Specifically, there is no national database available to identify risks due to climate change and the benefits of transitioning to low-carbon economies when conducting poverty, gender, and social analyses. This limitation restricts researchers and policymakers from linking and monitoring climate-induced poverty, thereby hindering efforts to target aid for vulnerable populations. Unavailability of Relevant Data When asked to identify pressing issues on climate change statistical requirements, national statistics offices that participated in ADB’s survey cited the unavailability of relevant data as one of the most prominent concerns. Unavailability of data may stem from the fact that a number of crucial indicators of climate change do not have agreed definitions and/or compilation methodologies. In some instances, the issue on lack of data may be due to limited understanding on how to integrate climate data that exist with the conventional macroeconomic data that national statistics offices usually compile. Figure 1. Critical Issues for Climate Change Data in Asia and the Pacific NSO = national statistics office, SIDS = small island developing states.Notes: The figures at the base of each bar refer to the number of respondents who provided a specific response while the figures in parentheses represent the total number of respondents falling under a specific type of economy.Source: Asian Development Bank analysis using data from the bank’s 2024 Climate Change Data Granularity and Statistical Capacity Building Survey. Additionally, the survey showed that policymakers in several economies in Asia and the Pacific are confronted with infrastructure limitations and financial constraints. If these issues are not resolved, they can lead to far-reaching implications, such as ineffective responses, inefficient resource allocation, and increased vulnerability. Conversely, addressing the key challenges in the statistical capacity of national statistics offices could enhance data accuracy and reliability, improve policy formulation and implementation, enable timely climate action, and facilitate better monitoring and evaluation—optimizing resource allocation. Lack of National Statistics Plan on Climate Change A national statistics plan serves as the centerpiece for guiding the collection, analysis, and dissemination of information for development purposes. A climate change statistics development strategy can help national statistics offices and other agencies to use resources more efficiently by prioritizing climate data based on actual demand. It also identifies existing data collected by other organizations, facilitating data-sharing and reducing duplication. The plan can also offer recommendations to improve coordination among stakeholders, leading to better use of resources and expertise. However, the ADB survey showed that only 20 of 29 respondents had a national statistics plan and only 13 had a climate change component integrated into their national statistics plan. Nearly half of the economies at medium to high levels of risk from climate change and natural hazards did not have climate change components in their national statistics plans. Figure 2. Existence of National Statistics Plan and Climate Change Statistics Program SIDS = small island developing state.Sources: Asian Development Bank analysis using data from the bank’s 2024 Climate Change Data Granularity and Statistical Capacity Building Survey; and World Bank. Statistical Performance Indicators (accessed 11 June 2024). Disparities in Climate Statistics Staffing Investment in human resources is crucial to developing effective climate statistics programs. Highly skilled statisticians, data analysts, people who are well-trained in geospatial data, and climate scientists are needed to collect, analyze, and interpret complex climate data. Effective management of climate change statistics also requires continuous training to enhance the staff’s capacity and foster a culture of learning and adaptation. A well-equipped human resource pool can drive the creation of robust, reliable, and relevant climate statistics, informing policy decisions and contributing to sustainable development. While room for further improvement remains, the survey on the compilation of climate change statistics in Asia and the Pacific noted some progress in human resource allocation. Of the 29 national statistics offices that responded to the survey, 22 reported having a dedicated unit or team of technical staff that handles climate change or environmental statistics and data. However, it is important to note that 19 of the 22 were either lower or upper middle-income or high-income economies (non-small island developing states), and only three were small island developing states. More concerningly, only three of the 29 participating economies reported having sufficient staff working on climate change statistics, with no small island developing states having sufficient staff in this area. These results underscore the need to address disparities and drive further progress in critical staffing areas, especially for ADB’s most vulnerable members. Figure 3. Availability of Dedicated Unit and/or Sufficient Staff for Climate Change Data NSO = national statistics office, SIDS = Small island developing states.Notes: The figures at the base of each bar refer to the number of respondents who provided a specific response while the figures in parentheses represent the total number of respondents falling under a specific type of economy.Source: Asian Development Bank analysis using data from the bank’s 2024 Climate Change Data Granularity and Statistical Capacity Building Survey. Enhancement of Analytical Capabilities Several emerging trends and innovations in data collection, analysis, and dissemination are bolstering the understanding of climate change impacts. Technologies such as remote sensing, artificial intelligence, and big data analytics are providing more precise and timely data. To harness these advancements and create more appropriate climate action into the future, it is crucial to integrate cutting-edge data tools into broader development planning. For example, employing AI-driven predictive models can help forecast climate impacts and inform proactive measures. Additionally, utilizing big data analytics can uncover patterns and trends that were previously undetectable, providing deeper insights into climate dynamics. Big data analytics in climate change requires strong capacity-building among national statistical systems. Initiatives should focus on providing national statistical systems with advanced technology and analytical expertise needed to effectively utilize big data. Investing in education, training, and the development of new methodologies will be essential for enhancing the national statistical systems’ analytical capabilities, ensuring they are ready to address the complexities of climate data. Development of Best Practices Improving statistical capacity in various areas of climate change relies on collaboration among governments, international development and research organizations, academia, and the private sector to foster innovation and the exchange of knowledge. By pooling resources and expertise, new capacity building initiatives can drive the development of best practices in the compilation of climate change data and statistics, ensuring national statistics offices have the latest and most powerful statistical tools and methodologies at their disposal. Through these collaborative efforts, national statistics offices will be better positioned to contribute effectively to global climate action, bolstering efforts to mitigate and adapt to the impacts of a changing climate. ADB’s survey on the compilation of climate change statistics in Asia and the Pacific suggests that such collaboration is already underway among national statistics offices in member economies. Eighteen national statistics offices reported collaborating with other government agencies, sectors, or international organizations to address data gaps in statistics related to climate change. Other actions commonly taken by national statistics offices included use of administrative and big data and improvements to data infrastructure. Figure 4. Measures Taken by National Statistics Offices to Address Data Gaps on Climate Change NSO = national statistics office.Source: Asian Development Bank analysis using data from the bank’s 2024 Climate Change Data Granularity and Statistical Capacity Building Survey. Support provided by more advanced national statistics offices to their peers with fewer resources can also help build capacity and promote the exchange of best practices, ultimately contributing to the development of robust climate change statistics programs across Asia and the Pacific. The survey showed that six of the 29 national statistics offices respondents in Asia and the Pacific indicated that they had provided support related to climate change statistics to other economies, either directly (three of six) or through associated organizations (four of six). Feedback from the six economies that provided support states that the most common types of assistance were for capacity building and project proposals. Other types of support included short-term assistance, provision of experts, and support on acquisition of technological and/or digital infrastructure and equipment. Commitment to Climate Data Building resilient national statistical systems is not just an administrative necessity—it’s the bedrock of effective climate action in Asia and the Pacific. By addressing data gaps, investing in human resources, and leveraging emerging technologies, policymakers can be empowered with the insights they need to make informed decisions. As climate challenges intensify, so too must the commitment to improving the quality and availability of climate data. Through collaboration, innovation, and sustained investment, no country or community will be left behind in the pursuit of sustainable, data-driven solutions to climate change. Resources Asian Development Bank. 2024. Key Indicators for Asia and the Pacific 2024: Data for Climate Action. Manila. Ask the Experts Nalwino Billones Consultant, Asian Development Bank Nal Billones is an economics and statistics specialist at the Asian Development Bank. He is part of the team compiling various indicators for the ADB Key Indicators for the Asia and the Pacific report. Before ADB, he worked as a statistician and an information technology officer with the Philippine statistics office. Karen Firshan Consultant, Asian Development Bank Karen Firshan works on compilation of indicators for ADB’s publications Key Indicators for Asia and the Pacific and Basic Statistics. She holds a degree in Statistics from Visayas State University and a master’s degree in Economics from Tokyo International University. Prior to joining ADB, she worked in the production of official statistics at the Philippine Statistics Authority. Arturo Martinez, Jr. Senior Statistician, Economic Research and Development Impact Department, Asian Development Bank Art Martinez works on Sustainable Development Goals indicator compilation, particularly poverty statistics and big data analytics. Prior to joining ADB, he was a research fellow at the University of Queensland where he also got his doctorate in Social Statistics. Yating Ru Economist, Economic Research and Development Impact Department, Asian Development Bank Yating Ru works on interdisciplinary approaches that harness geospatial big data, data science tools, and economic methods to tackle development challenges related to poverty, food insecurity, and climate change. She earned her master’s degree in Regional Planning and PhD in Regional Science from Cornell University. Prior to joining ADB, she worked at the International Food Policy Research Institute in Washington, DC. Follow Yating Ru on Raymond Adofina Consultant, Asian Development Bank Raymond Adofina is an economics and statistics specialist, working on compiling and analyzing data for the Key Indicators for Asia and the Pacific. His experience includes managing and visualizing economic and statistical data, and he has contributed to similar efforts at UNICEF Philippines. He holds a bachelor’s degree in Business Economics from the University of Santo Tomas. Asian Development Bank (ADB) The Asian Development Bank is committed to achieving a prosperous, inclusive, resilient, and sustainable Asia and the Pacific, while sustaining its efforts to eradicate extreme poverty. Established in 1966, it is owned by 69 members—49 from the region. Its main instruments for helping its developing member countries are policy dialogue, loans, equity investments, guarantees, grants, and technical assistance. Follow Asian Development Bank (ADB) on Leave your question or comment in the section below: View the discussion thread.