Data: Driving Science. Informing Decisions. Enriching Humanity.

We observe, create, measure, simulate, collect, and process data at a prodigious rate, propelled by modern digital technology, and use it to create new knowledge and insights; inform and validate models and hypotheses; guide policies and decisions; and advance the scientific, environmental, and societal dimensions of the weather, water, and climate enterprise (WWC). 

This theme uses data as the locus for interlinking heterogeneous disciplines across the WWC enterprise along braids of commonality to propel new science, expand and empower the stakeholder ecosystem across all sectors, and ameliorate bias and socioeconomic inequity, through the suffusion of both theory and data centric approaches.

1. Data driving scientific inquiry: For centuries, data, mostly in the form of observations, have been used to test theories and validate hypotheses. Now, with modern digital sensors, Internet of Things (IoT) sensors, active and passive in situ and remote sensing technologies, and with the explosion of computing technologies there is an emergence of new insights inviting further inquiry and spawning innovation and discovery. The spectrum of data is diverse and includes the full suite of observations, environmental predictions generated by numerical models, data products derived from integration and assimilation of observational and model-generated sources, empirical products based on algorithms, and AI and machine learning innovations that promise to revolutionize inquiry and discovery in the atmospheric and related sciences. Full, open, and timely access to data is critical to the advancement of atmospheric and related sciences, the provision of products and services for the benefit of society, and the promotion of commerce and private-sector activities. Adopting policies for free and open access to data could accelerate scientific discoveries, broaden, and enhance participation in scientific enterprise, promote entrepreneurship, and benefit society. 

2. Data transforming education and training, and bridging disciplines: Technology, computation, and/or big data can be leveraged to develop, implement, and analyze educational interventions designed to prepare a diverse and equitable workforce, including exploring how students learn to integrate knowledge and engage in transdisciplinary research to solve complex problems.  Computing, sensing (e.g., active/passive remote, IoT, digital sensors, AI/ML), data storage, data access, communication, and hardware technologies continue to change our lives and work environments. These new technologies are changing the way we learn and do science, math, and engineering, and it is paramount that we not only know how to navigate these changes, but that we can ensure equitable access, engagement, and   participation of all groups in the STEM workforce. To prepare scientists (environmental, data, social), technologists, and practitioners, innovative educational paradigms must be able to harness the technologies that produce unprecedented volumes of data and vast interconnectivity capabilities, such as data provided by ubiquitous sensing and the IoT. Environmental data in their myriad of formats (numerical, imagery, audio, visualizations, and others) are available at ever greater speeds, propelling innovations such as artificial intelligence and machine learning and demanding that the growing influence of data-driven science be explicitly subsumed into the new curriculum and reflected in AMS guidelines and government service requirements.  

3. Data advancing racial and socioeconomic justice, equity, and visibility: Data are the foundation of evidence-based solutions needed to thwart the pernicious effects of systemic barriers to justice and equity across the racial and socioeconomic landscape. There is already a data-based awareness (e.g., AIP Statistical Research Center) that the geosciences community suffers from the lack of racial and ethnic diversity at all levels of higher education and in the workforce.  The AMS is committed to, and benefits from, the full and equitable participation of a diverse and inclusive community in its membership, in its activities, and in the audiences that it serves. The advancement of the AMS mission is dependent on its ability to have a professional membership that is fully representative of societal demographics. Data are at the core of the intervention that can make this happen. Data can be used to identify unconscious and explicit biases, which can taint policies, programs, practices, perspectives, as well as the increasing number of autonomous options that play into informing decisions. Passive commitment is not enough! The Covid-19 pandemic has exposed the disproportionate impact on marginalized and minoritized communities, which its presents our community and beyond the opportunity for transformative change. Data/information can be used more effectively to deliver a fundamental shift in the way we work internally within our community and how we use environmental data to build a more just, equitable, inclusive, and accessible framework for outreach to the global community – WWC has a global reach! Open access to science must be equitable if we are to improve how we are empowering treating the marginalized communities. We must use data to be vigilant of biases, exclusion, reinforcing dominance, and further entrenching existing inequalities.    

4. Data shaping environmental attitude and behavior: We can use the deluge of Earth observations, contextual information provided by social media, unprecedented dissemination mechanisms, and high-performance computing platforms to change the way people and businesses view WWC data and experience the force-multiplying effects it has on improving life and weather sensitive decision making (Conference summary statement.pdf (wmo.int)). Using data to develop an impact-oriented strategy by identifying the human activities with the strongest environmental impact, where knowledge from the natural and social sciences is integrated, more adequately reflecting the nature of most environmental problems, and enabling evidence-based intervention towards solutions. However, developing new evidence-based tools, methods, or insights does not mean they will be deployed with the intended impact. As being powerfully illustrated right now with the Delta variant of COVID-19, data are needed to understand how to effectively motivate vaccinations and appropriate behavior. Issuing hurricane/tornado/heatwave warnings does not mean people follow them as intended. Data are needed on how to improve uptake. Shaping new environmental attitude and behavior requires expertise from across our community and beyond, providing rich opportunities for cross-disciplinary collaboration in research, education, policy, and practice from physical and data sciences to the social and health sciences, technology, and engineering.     

5. Data integrating public-private-academic partnerships: Partnerships can often accomplish what single entities cannot do alone. Actionable weather, water, and climate information are key to developing successful strategies to address the challenges facing society today; to develop and deliver them cost-effectively requires creative partnerships that draw on the strengths of both the public and private sectors. Public-private alliances involving the free and unrestricted exchange of data are paramount to filling gaps in the global-data coverage and delivering critical services. Environmental data can be the link for an integrated value chain connecting public and private partners while spawning the creation of proprietary products and services for economic sustainability (https://meetings.wmo.int/WMO-Data-Conference/SitePages/Outcome%20Material.aspx). 

6. Data powering economic growth: Data fuel innovation and bring value and competitive advantage. The organization of meteorology increasingly reflects a political—economic approach that treats science as an economic entity in which market-based criteria can be used to allocate scientific resources. The emergence of weather derivatives markets — financial products that enable trading on weather indices — have reshaped how some businesses are interacting with meteorologists; forecasting and weather modeling is being adopted within the private sector to enable product development and commercialization strategies. Space weather commerce is growing at a rapid rate and the benefits span nearly every sector from geo-location users to power grid systems and the national commercial airline fleet. There is a premise in business that "people don’t simply buy products or services, they ‘hire’ them to make progress in specific circumstances.” When data is the business, the most common circumstance people are hiring for is to inform decisions. More sophisticated users also use it to inform uncertainty and manage WWC-related risk.  But data does not just fuel innovation, its often the backbone of many products and services that drive economic growth.  Data fuels products, informs decisions, including uncertainty and risk, and when combined with application knowledge, can be the foundational product for the existence of an entire organization. Entire careers and organizations exist for this purpose.  Ethical dissemination of data requires an understanding of its limitations, representativeness, access, biases, and equity.

Motivation for the theme on Data

Environmental Earth and space system data has one of the largest digital footprints and is a central component of scientific inquiry, but we have not yet collectively solved the problem of data access, discovery, and service. This theme will be the catalyst for a year-long inclusive and collaborative discourse on the challenges posed by the data deluge with a focus on how to stage environmental data to make it efficiently useful and accessible for the plethora of applications important to driving science, informing decisions, and enriching humanity within our community and beyond.

Data is the engine of hypothesis-driven science and the fuel for inductive, empirical investigation. In recent years, atmospheric, oceanic, climate, and hydrological data have come to be as much of an asset as any natural resource. Databases and their derivatives have become increasingly valuable commodities. On the other hand, the paucity of data in regions (e.g., parts of the ocean, polar regions, and some rural areas) impairs decision-making and could affect prediction scenarios for climate change and other global environmental changes. As the value proposition of data has grown, nations of the world are revisiting arrangements to share data, improve data collection, drive research and innovation, stimulate two-way transfer of research [R] and operations [O] (R2O2R), support education and training, and economic growth. Big Data is revolutionizing knowledge production by enabling novel, highly efficient ways to conduct research. The field of data science is creating new techniques for extrapolating knowledge and emergent discovery from data. The Open Data movement, emerging from policy trends such as “Open Government and Open Science,” encourages sharing data via digital infrastructures, which, in turn can serve as scaffolding for the development of artificial intelligence (AI) and machine learning (ML), and an incentive for more efficient processing, reuse, and knowledge creation. 

The WWC research enterprise along with private and government sectors will lead the way in finding the acumen, resources, and technological prowess to effectively harness the data revolution to advance their imperatives, exploit emergent technologies, and pursue frontiers. 

Still, as a community we have the shared obligation to ensure that the next generation workforce is prepared for a world where data profoundly influences every facet of the enterprise. Academic curricula must evolve to accommodate a new balance between foundational underpinnings in science and mathematics, the breadth of technical skills, cross-disciplinarity and cross-cultural competencies, and the wherewithal to use data responsibly for the common good. Our imperative must be to ensure that data in all its forms, and the actions taken based on this data, are free of biases and fully accessible.