Responding to Societal Needs
Why WWRP is important for society
The world we are living in is changing. An ever-growing population, in particular in densely populated urban regions give rise to population stresses and land usage change. At the same time, urban environments and the infrastructure they are relying on become more and more complex and interdependent, increasing their sensitivity and vulnerability to weather-related impacts. Strong economic development and associated demand on production and transportation are another factor that is highly sensitive to weather and its impacts. New opportunities also arise from the availability of a wealth of information from various sources. The size and complexity of such ‘big data’ makes data processing with traditional tools and applications nearly impossible. The volume of data will continue to increase in an unprecedented way making the need to capture, store and mine this information increasingly important. At the same time, interconnecting and analysing big data may help reveal undiscovered aspects and new information layers.
To meet these emerging challenges, the weather prediction system of the future must provide accurate, seamless and timely information regarding the location, timing, and structure of weather-related hazards across space and time scales from local to global and minutes to months in advance. Such information will help reduce the impacts of weather-related hazards only if it is translated into products that are useful for end users and communicated in a manner that can be integrated directly into decision-making processes. Regions around the world differ greatly in weather-related challenges, technology for observations and predictions, and socio-economic and cultural factors. These differences must be considered and addressed.
Developing such seamless high-impact weather prediction capabilities requires to understand and quantify weather-related impacts, to estimate and communicate forecast uncertainty, to address diverse stakeholder requirements, to provide actionable information, and to effectively incorporate weather data and information into decision-making processes. This calls for effective collaborations among diverse experts within an interdisciplinary framework that brings together physical and social scientists. Addressing societal impacts will also require working closely with forecast end users to better understand and quantify weather-related impacts, as well as to develop strategies for more effectively communicating information to enable end users to manage specific risks. New technological approaches need to be explored in order to exploit all source of information involving experts from different backgrounds and ways of thinking.
The activities of the WWRP projects, Working Groups and Expert Teams are key contributions to the development of seamless high-impact weather prediction systems. Advances in model development, exploitation and best usage of observations and identification of untapped sources of predictability in the sub-seasonal to seasonal range will help to provide the best seamless forecast information possible. Collaboration and exchange with various stakeholders and users of forecast information will help to assess the impacts of weather events and the information needed for different user groups to mitigate these impacts. Cooperation with social scientists and communication experts will allow improving dissemination of forecast and warning information, in a language and format that meets the recipient’s requirements. Through dedicated workshops and training opportunities, and strong connections with other programmes and partners, the WWRP provides the organizational framework necessary for stimulating international research activities and collaborations across widely varying experts and disciplines.
Responding to Societal Needs for Weather Information
Weather-related disasters pose a major threat to society, the environment and the economy. As the vulnerability to weather related hazards increases due to climate change, growing population, urbanization and other factors it is imperative to coordinate weather research targeted towards improving forecasts and warnings at international level.
The WWRP IP is developed along four major societal and technical challenges that have been identified by WMO research community:
- High-Impact Weather
- Evolving Technologies
For each of these challenges, a set of Action Areas has been defined. Within each of these Action Areas, selected activities by WWRP Working Groups and Core Projects will help to reach the overall WWRP programmatic goals.
High-impact weather events have a growing societal and financial impact in a changing climate, on a growing population and the infrastructure it depends upon. Despite significant progress and advances in scientific understanding, monitoring and prediction achieved in recent years, major loss event statistics constantly remind us of the gaps between scientific knowledge and its beneficial application to both routine and complex weather-related problems faced by society.
Identifying and effectively addressing these gaps requires close interdisciplinary collaboration between the research community, the stakeholders and the users of weather information. Seamless prediction of high-impact weather events at a wide range of scales (from nowcasting to seasonal prediction) must be improved, with a particular focus on local scales. Appropriate and targeted communication of forecasts and warnings, including the information on consequences of high-impact events, together with user-oriented verification is crucial for capitalizing on the achievements made in prediction of high-impact weather events.
Action Areas here are:
• Increase knowledge of the physical and social factors limiting the capability to predict, communicate and mitigate the impacts of high-impact weather events; identify how these limitations can be overcome; demonstrate the resulting improvements for specific high-impact weather events at lead times from minutes to seasons, from global to local, for different users in different parts of the world;
• Identify, characterise and quantify analysis and forecast uncertainty using advanced probabilistic methods, and develop corresponding data channels and communication mechanisms which support decision-making under uncertainty;
• Work with different science communities to develop modelling systems that fully integrate the most relevant components of the Earth system; link to and utilise socio-economic models and data to assess impacts;
• Develop end-to-end approaches from meteorology to impacts, in application areas of public health, commerce, industry, transport, water, energy, defence, agriculture, etc., taking into account the varying user needs in different parts of the world;
• Develop methods to verify forecasts and warnings of high-impact weather and its impacts and demonstrate their benefit, with a focus on probabilistic and impact-based methods, including collecting and processing suitable observations (particularly non-conventional weather observations by non-conventional means); assess the impact of near misses and false alarms; and evaluate the end-to-end forecast chain with emphasis on what is of value to the user;
• Connect knowledge and abilities to simulate high-impact weather events at high spatial and temporal resolution with larger scale climate change expertise to more confidently attribute linkages to longer term climate variability and change.
Humanity depends on the availability of fresh water, not only for supporting life, but also for many human activities such as power generation, agriculture and industry. The water cycle is the crucial link between the various Earth system components that govern weather and climate processes. Reliable guidance on water related aspects, on both the weather and climate time scales, requires information from numerical models of the Earth System. However, the appropriate representation of the water cycle and its various processes still pose a challenge to these models. This results from the complexity of processes as well as from spatial and temporal resolution of the models. Enhancing predictive capabilities thus requires improvements in the representation of all phases of water in numerical models, and an enhanced coupling of atmospheric, oceanographic, hydrological and cryosphere models, alongside with a proper representation of atmospheric chemistry. Collaboration with experts and programmes from these fields, in particular on aspects of hydrology and atmospheric chemistry, is important to reach this goal.
Action Areas here are:
• Improve understanding, observation, assimilation and modelling of the components of the integrated water cycle in its three phases, and its global, regional and local interactions;
• Assess and exploit new in situ and remotely sensed hydro-meteorological observations;
• Improve understanding, observation and modelling of aerosol, cloud and water vapour aspects of precipitation processes, with a view to improved estimation and predictions of precipitation;
• Characterise and communicate how Quantitative Precipitation Estimate (QPE) and Quantitative Precipitation Forecast (QPF) uncertainty translates to hydrological uncertainty (and vice versa).
The population of urban areas will grow significantly in the next few decades, especially in Asia and Africa. Subsequent population stresses and changes in land usage may increase vulnerability even more. Urban environments are particularly sensitive to weather, air quality, climatic conditions and their variability. These aspects impact activities within cities, such as transportation, energy demand, construction, school access, tourism, both directly and indirectly. At the same time, cities are focal points for innovation, driving economic and societal progress locally, regionally and globally. Efforts undertaken in this respect will range from improved modelling, over aspects of communication to the development of best practise guidelines for establishing weather, climate and water related environmental services for cities to support urban planning and safe functioning of cities.
Action Areas here are:
• Improve understanding and knowledge of the relationship between the urban physical and built environment, the social, behavioural and economic needs of its population, and the requirements for integrated weather-related environmental services;
• Improve observations and understanding of the unique urban physical processes, including dynamical, chemical and hydrologic;
• Develop, validate and demonstrate urban prediction capabilities, toward building urban environment integrated information systems to support decision-making for different applications in different parts of the world.
Development of computing technologies promotes the capability to run high-resolution and more complex ensemble based numerical weather prediction systems operationally. The projected exascale computing requires the development of systems capable of harnessing the future computing capacity. Data from non-conventional and probably inhomogeneous observations (e.g. smartphones) might play a more and more important role in developing and providing services. Sophisticated data assimilation techniques have to be developed to account for such novel data and achieve the best possible gain for forecast improvement with increasingly complex models. The increasing amount of data, due to high-resolution satellite data and ensemble forecasts poses a challenge for data archiving as well as for the prediction chain, where it has to be assured that new and improved forecasts are available and accessible to a wide range of users in a timely manner.
Action Areas here are:
• Conduct methodological research (numerical methods, coupling strategies, assimilation methods, observational and model data information exploitation, including post-processing) to ensure that scientific enhancements can be implemented in future forecasting systems, and that systems can provide timely services;
• Enhance access to services (observations, model output, data collection and pre-processing and global models) that require exceptional HPC and data handling, as an enabler for WWRP research;
• Share specialist methods and tools enabling complex modelling systems to be run by a wider community, including beyond WWRP;
• Prepare for exploitation of information from new, advanced observing systems, as well as commodity-technology-based data;
• Inform the design of the future global observing system.