The World Meteorological Organization (WMO) World Weather Research Programme (WWRP) High-Impact Weather (HIWeather) research project was designed to increase the effectiveness of forecasts and warnings of high-impact weather. In achieving this, it created a global momentum toward a growing partnership between the social and physical sciences in the weather enterprise, building a community of researchers and practitioners who understand the importance of working across disciplines and are passionate about the value of warnings in reducing the impact of weather-related hazards. Through its promotion of "Warning Chain Thinking" within the Warning Value Cycle, it focused attention on the whole warning system, from monitoring and forecasting through communication and response, emphasizing the role of partnerships among disciplines, organizations, decision-makers, and the public. It brought together a wide body of research from multiple disciplines involved in making warnings more effective, in a series of publications which are increasingly used in education, training, and operations. In doing so, it helped bridge gaps between weather information providers, emergency managers, and humanitarian organizations on a global scale. It has provided a community and a body of evidence as a foundation for the United Nations Early Warnings for All initiative and for the next generation of warnings research. SIGNIFICANCE STATEMENT: The article highlights the importance of considering the high-impact weather forecasting and warning chain as an integrated whole, involving a range of actors from different organizations and disciplines. Three strands of science motivated this work: the need for progress in translating weather hazards into impacts; evidence to underpin the appropriate introduction of impact-based forecasts and warnings; and addressing the gap between the science of community response, espoused by humanitarian organizations, and the science of weather information production, exemplified by national weather services.

Abstract The Paris 2024 Olympics Research Demonstration Project lasted five years and was endorsed by the World Weather Research Programme within WMO to improve urban weather forecasts, using the metropolitan area of Paris as a case study. Meteorological institutes and universities from ten countries participated. The project had three objectives: to increase knowledge on urban summer meteorological hazards; to improve hectometric-scale numerical weather prediction models in cities; and to facilitate the co-production of weather information for large sporting events. Increased convective activity downwind of Paris was highlighted by a new radar- and lightning-based climatology, and numerical experiments identified its potential driving processes. Collaborative analyzes of past heat waves improved air quality models for the Olympics and simulations of thermal comfort variability. Advances in urban-scale modeling enabled real-time intercomparison of seven hectometric or kilometric scale atmospheric models that provided daily forecasts throughout the Olympics and Paralympics. Hectometric models showed similarities in convective precipitation characteristics, tending to have an excessive number of small showers and grid length dependence. Model intercomparisons also showed variability in Urban Heat Island intensity and unexpected differences in urban heat plume extent. A sociological study highlighted the differences in viewpoints between forecasters and sport managers and the importance of transparency in communicating uncertainties. Finally, a decision-making procedure to manage extreme heat contingencies for the “Marathon for All” Olympics public event was developed based on a 100-m grid-length model in collaboration with the weather forecasters’ team. All these insights open new scientific questions in urban climate research and ways forward for future hectometric numerical weather prediction.

Insights from Forecast Demonstration Projects and Research Development Projects, training workshops, and symposia, conducted between 2000 and 2024 are summarized. The projects were organized by the Nowcasting and Mesoscale Research Working Group of the World Weather Research Programme of the World Meteorological Organization. The objective was to advance, promote, and build capacity in nowcasting and very short-range forecasting. The projects were associated with the Olympic Games, emergency management, and aviation services. They brought international experts together to work in a collaborative fashion. Extensive interaction with end users and decision-makers expanded and extended the scope of services from traditional weather hazards (heavy rain, wind, hail, lightning) to include specific user needs (e.g., visibility in complex terrain or airport runways, periods of calm winds or light rain, heat stress). Substantial progress has been made in many areas including advanced radar nowcasting algorithms, stochastic nowcasts, kilometric and hectometric numerical weather prediction models, blending of observations and models, and multimodel systems. Verification was a key and valuable component of the projects quantifying the results. Also, the types of services have expanded to include both summer and winter services, complex terrain and urban environments, air transport, air quality, hydrology, and health. Insights are presented in all aspects of nowcasting and very short-range forecasting from end-user decision-making, critical role of the forecaster, forecast systems (models, heuristics, observations), to science and knowledge gaps.

The World Meteorological Organization (WMO) has called for more meaningful warnings to help reduce the impacts of weather-related events. Impact-based forecasts and warnings (IBFW) are being developed by forecasting agencies globally to meet this call. However, there are many challenges facing those implementing such systems. The WMO World Weather Research Programme High Impact Weather project sought to understand the future direction of research on IBFW systems. This research involved a virtual workshop series in late 2022 with over 350 international registrants to identify and analyse challenges that people are facing in developing IBFW systems, and potential solutions.We found that challenges relate to ten themes, in addition to defining the measures of success of an IBFW system Examples of key research gaps are to develop evaluation methods to explore the value of multi-hazard IBFW, in terms of collating data at appropriate scales, and including avoided losses, behavioural responses, and unconventional observations. We need to explore the value of using quantitative approaches in comparison to more efficient qualitative approaches, as well as of dynamic exposure and vulnerability data sets, and tailored warnings. We must investigate how to effectively communicate uncertainty and explore the governance of underpinning data.Further research on these topics will assist with the successful implementation of more meaningful warnings globally, whilst considering the feasibility and effectiveness of the efforts involved. This is our contribution to reducing the impacts of future hazards, at a time where climate-related events are expected to increase in severity.

The contribution addresses, from a conceptual point of view, the complex issue of evaluating the performance of warning systems that are operating over large areas to cope with the risk posed by extreme weather events. In the protocol, the performance of the systems is evaluated, at each step in the warning production process, considering the “warning value chain” schematization developed in the HIWeather project of the World Meteorological Organization (http://hiweather.net/Lists/130.html). In a perfect warning chain, the warning received by the end user would contain precise and accurate information that perfectly met their need, contributed by each of the many players in the chain; in real warning chains, information, and hence value, are always lost as well as gained at each link in the chain (Golding 2022, https://link.springer.com/book/10.1007/978-3-030-98989-7). The protocol is structured as a three-part evaluation process: 1) description of the system; 2) assessment of criticalities during high impact events; 3) routine assessment of daily operations. For each part, the protocol prescribes a set of must-do. The description of the warning system must be based on the schematic subdivision of the warning value chain, i.e., six main capabilities and outputs and five information exchanges elements. An important focus on the evaluation of an operational warning system must be devoted to high impact events. For such cases, the evaluation must include: essential information on the event; information on how each element of the warning value chain has been working during the event; synthetic assessment on the performance of the warning system. Finally, the routine assessment must include: identification of the system’s operational elements; identification of the areas covered by the system; identification of period for which to conduct the assessment and sources of data to be used; identification of appropriate and computable (considering the available data) performance indicators for the different elements of the warning value chain; analysis of relevant data for the chosen time period in the identified areas; evaluation of the performance of the different elements of the waring value chain; final judgment on the overall performance of the system. This study is being carried out within the Horizon Europe project “The HuT: The Human-Tech Nexus - Building a Safe Haven to cope with Climate Extremes” (https://thehut-nexus.eu/). The protocol has been developed considering two cases studies, and will be further put to test during the remaining part of the project. Through this action, detailed information from many different warning systems will be collected and used for a comparative study between warning systems operating, in different areas of the world, for different weather and climate related risks.

University students can learn about weather warnings and contribute to a database for the World Meteorological Organization (WMO) project on value chain approaches to evaluate the end-to-end warning chain. The project offers students a way to understand how information about high-impact weather is created, shared, and used within a complete warning system for a selected event. Their contributions are intended to inform researchers and practitioners on what has and what has not worked well in the warning process. The students use a structured questionnaire designed to collect information on observations, forecasting, hazards, impacts, warning communications, and responses.

Weather and climate patterns play an intrinsic role in societal health, yet a comprehensive synthesis of specific hazard-mortality causes does not currently exist. Country-level health burdens are thus highly uncertain, but harnessing collective expert knowledge can reduce this uncertainty, and help assess diverse mortality causes beyond what is explicitly quantified. Here, surveying 30 experts, we provide the first structured expert judgement of how weather and climate directly impact mortality, using the UK as an example. Current weather-related mortality is dominated by short-term exposure to hot and cold temperatures leading to cardiovascular and respiratory failure. We find additional underappreciated health outcomes, especially related to long-exposure hazards, including heat-related renal disease, cold-related musculoskeletal health, and infectious diseases from compound hazards. We show potential future worsening of cause-specific mortality, including mental health from flooding or heat, and changes in infectious diseases. Ultimately, this work could serve to develop an expert-based understanding of the climate-related health burden in other countries.

The weather information value chain provides a framework for characterising the production, communication, and use of information by all stakeholders in an end-to-end warning system. It covers weather and hazard monitoring, modelling and forecasting, risk assessment, communication, and preparedness activities. A 4-year international project under the WMO World Weather Research Programme is using value chain approaches to describe and evaluate warning systems for high-impact weather by integrating physical and social science. One of the project’s key outputs is a database questionnaire for high-impact weather event case study collection and analysis. The questionnaire is primarily aimed at scientists and practitioners to review, analyse and learn from previous experience using value chain approaches. Project scientists are using it to analyse high impact weather events that have occurred in recent years. Beyond the professional use for severe event assessment, the questionnaire has proven to be an effective educational tool for university students to learn about high-impact events. Undergraduate students at the University of Miami used the questionnaire to study the warning value chain for Hurricanes Ida (2021) and Ian (2022) as an assignment in an undergraduate tropical meteorology course. Similarly, undergraduate interns at the Bureau of Meteorology completed the questionnaire for the Black Summer Bushfires in south-east Australia (2019/2020) and did a comparative study of the warning value chains for Hurricane Isaias (2020) for the Caribbean and the US. Using available online resources, the students prepared their responses and collaborated in teams to present syntheses of their evaluations. Engaging students in such a cross-disciplinary study enhanced their critical thinking about high-impact weather event forecasting, impacts, warning communication and response. In this presentation we introduce the database questionnaire and how it can be used for educational purposes. The questionnaire and accompanying guide are freely available for anyone to use and can be downloaded at http://hiweather.net/Lists/130.html. We encourage not only the research and operational communities but also academic institutions to participate in this project by contributing case studies of high impact events and collaborating in their analysis. Corresponding/presenting author: David Hoffmann, Bureau of Meteorology, Melbourne, Australia; david.hoffmann@bom.gov.au

"Enhancing the Value of Weather and Climate Services in Society: Identified Gaps and Needs as Outcomes of the First WMO WWRP/SERA Weather and Society Conference" published on 17 Mar 2023 by American Meteorological Society.

Increased rainfall extremes cause severe urban flooding in cities with adverse socio-economic consequences, and Kathmandu city is no exception. Rainfall events are projected to become more intense and frequent in a warm and wet future, and they pose a major challenge to the sustainable development of Kathmandu city. This paper analyses historical extreme rainfall patterns across the city and uses these as the basis for future projections in combination with a range of General Circulation Models. Future projections of extreme rainfall are then fed into the numerical flood model HAIL-CAESAR (Lisflood), using a high-resolution digital elevation model of Kathmandu. We show that rainfall intensity, such as the annual maximum 1-day rainfall (RX1day), is projected to increase by up to 72% in the future, and the historical 100-year return period rainfall will become a 20 or 25-year return period rainfall. The flood modelling results show that the future flood hazard (magnitude and extent) will increase. The historical 100-year return period flood discharge will correspond to a 25-year return period future flood. A 100-year period flood discharge is likely to increase up to 72% (37% median) in the future. Area of land inundated by more than 1 m in a 100-year return period flood event could increase from 11.7 km2 to 23 km2 in the future. Furthermore, the location and timing of rainfall maxima affect the peak, timing, and location of flood hazards. This analysis can serve as a scientific basis to assess future flood-induced risk in Kathmandu in response to climate change.

A priority of weather services is to protect lives and property from hazardous weather. Research on how to achieve that most effectively is the mission of the World Weather Research Programme’s High Impact Weather (HIWeather) project. HIWeather brings together physical and social scientists from a wide variety of disciplines and from across the world to study each step of the process from monitoring the weather to making effective protective responses. HIWeather uses a simple model of the warning production and communication chain that highlights the roles of key actors and organisations involved in forecasting the weather, the resulting hazard and its socio-economic impacts, in formulating the warning and communicating it to the end-user. In this paper I draw on the results of that research which has now been published in our book, “Towards the ‘perfect’ weather warning: bridging disciplinary gaps through partnership and communication” (Golding, 2022). In the context of severe weather associated with monsoons, I shall identify key principles for the design of weather-related warning systems, connecting this work with ideas from the design of community-based warning systems, developments in social media communication, research on impact-based forecasting and with progress in convection-permitting and higher resolution NWP models. A key result is that the communication of knowledge is at least as important as its content and that the creation and nurturing of partnerships between organisations is critical to that.

Intense convective storms cause many deaths around the world each year from flash floods, landslides, lightning, tornadoes and hail. These are also some of the most difficult to forecast weather hazards and are generally not predictable in a deterministic sense by Numerical Weather Prediction models. In the UK the incidence of such storms has increased significantly in recent years, as a result of climate change, and is projected to increase further with increasing summer temperatures and corresponding increases in absolute humidity. The current UK weather warning service is focused on providing early warnings of six or more hours lead time to enable people to plan ahead for safety. However, the small spatial and temporal scales of convective storms mean that only a very general probabilistic indication can be given of timing and location in these warnings. As a result, most recipients do not prepare for the possibility of severe impacts, even when the accompanying message indicates that they are possible. One option being considered for enhancing the current warning service is to developed a complementary very short range warning focused on storms that present a risk to life. This implies a particular set of responses from warning recipients which make specific demands on the information communicated and the means of communication. On the other hand, current forecasting capabilities for these storms are limited and there are known constraints to forecast improvement. This presentation will demonstrate how a value chain approach has helped to identify the critical components of such a warning system, mapping them on to existing and projected capabilities. Results of a preliminary feasibility study will be shown.

The warning value chain is a concept whereby the process of producing a warning is represented by a chain of sources of expertise (components), connected by bridges that convey bidirectional information exchanges. Uncertainties exist at all stages of the warning value chain. For example, uncertainties exist in the current (observational) state of the atmosphere used to initialise the numerical weather prediction models. This in turn contributes towards weather forecast uncertainties (e.g., ensemble-generated forecast probabilities and run-to-run variability). Weather forecast uncertainties then feed into the hazard and impact forecasts where they can be amplified – such as through uncertainties in defining hazard footprints or impact assessments. Often it comes down to operational meteorologists to examine the varying levels of forecast uncertainty across several value chain components and assess the real likelihood of high impact weather and its potential impacts. This presentation will focus on the challenges of forecast uncertainty within the value chain, using the forecasts and warnings associated with Storm Eunice which affected southern parts of the UK in February 2022 as an example. The Met Office Weather Impacts team recently used the warning value chain questionnaire produced by the WMO’s High Impact Weather (HIWeather) Warning Value Chain Flagship Project, to carry out a detailed warning value chain assessment for this event, where evidence was considered from across the value chain. Results showed that all components of the value chain performed well overall, and it was clearly a highly successful set of warnings as shown by the large reach and public/emergency response. However, several recommendations were still made and challenges resulting from forecast uncertainty were evident across many value chain components. A focus of this presentation will be on how operational meteorologists interpreted the changing forecast signal and how this affected warning issuance and communication.

The weather information value chain provides a framework for characterising the production, communication, and use of information by all stakeholders in an end-to-end warning system covering weather and hazard monitoring, modelling and forecasting, risk assessment, communication and preparedness activities. Warning services are typically developed and provided through a multitude of complex and malleable value chains (networks), often established through co-design, co-creation and co-provision. In November 2020, a 4-year international project under the World Meteorological Organization (WMO) World Weather Research Programme was instigated to explore value chain approaches to describe and evaluate warning systems for high impact weather by integrating physical and social science. It aims to create a framework with guidance and tools for using value chain approaches, and to develop a database of high impact weather warning case studies for scientists and practitioners to review, analyse and learn from previous experience using value chain approaches. Here we describe a template for high-impact weather event case study collection that provides a tool for scientists and practitioners involved in researching, designing and evaluating weather-related warning systems to review previous experience of high impact weather events and assess their efficacy.

In 2021, several weather disasters occurred in which conditions surpassed recorded extremes. Analysis of the performance of warning systems in these disasters by the WWRP HIWeather project shows that in most, but not all cases, there was adequate forewarning of the magnitude of the event, but that lack of preparedness and/or communication failures led to loss of life in particularly vulnerable groups. Using information from the HIWeather value chain database, we present an overview of key aspects of each event – the weather and its impact, the forecasts, the warnings, and the responses – followed by some results of a comparative analysis of warning performance and some conclusions about critical components of a successful warning system. In the light of this analysis we conclude with a checklist of key components in the design of an effective warning system for unprecedented weather events.

In an era of climate change, extremes relative to the historical record are expected to occur more frequently. In 2021, several weather disasters occurred in which conditions surpassed recorded extremes. These included floods and associated impacts in the USA, Europe, China and Indonesia, heat waves and wildfires in southern Europe and northwestern North America, and winter weather in Spain and the southern USA. Analysis of the performance of warning systems in these disasters by the WWRP HIWeather project shows that in most, but not all, cases there was adequate forewarning of the nature and magnitude of the event, but that lack of preparedness and/or communication failures led to loss of life in particular vulnerable groups. Using information gathered for the HIWeather value chain database, I will present an overview of key aspects of each event – the weather and its impact, the forecasts, the warnings, and the responses. In the flood cases, a common feature was that limitations in the spatial resolution of the forecasts limited the ability of hydrological prediction systems to translate the rainfall forecast into a realistic flood forecast. In the case of the winter weather and heat waves, a lack of preparedness at both official levels and in the at-risk population led to failures of response. A comparative analysis of warning performance shows that communication failures were often distributed along the warning chain. Drawing on material from our recently published book, Towards the Perfect Weather Warning, I will draw some conclusions about critical components that are necessary for a successful warning system.

AbstractAchieving consistency in the prediction of the atmosphere and related environmental hazards requires careful design of forecasting systems. In this chapter, we identify the benefits of seamless approaches to hazard prediction and the challenges of achieving them in a multi-institution situation. We see that different modelling structures are adopted in different disciplines and that these often relate to the user requirements for those hazards. We then explore the abilities of weather prediction to meet the requirements of these different disciplines. We find that differences in requirement and language can be major challenges to seamless data processing and look at some ways in which these can be resolved. We conclude with examples of partnerships in flood forecasting in the UK and wildfire forecasting in Australia.

AbstractThe bridge from a hazard to its impact is at the heart of current efforts to improve the effectiveness of warnings by incorporating impact information into the warning process. At the same time, it presents some of the most difficult and demanding challenges in contrasting methodology and language. Here we explore the needs of the impact scientist first, remembering that the relevant impacts are those needed to be communicated to the decision maker. We identify the challenge of obtaining historical information on relevant impacts, especially where data are confidential, and then of matching suitable hazard data to them. We then consider the constraints on the hazard forecaster, who may have access to large volumes of model predictions, but cannot easily relate these to the times and locations of those being impacted, and has limited knowledge of model accuracy in hazardous situations. Bridging these two requires an open and pragmatic approach from both sides. Relationships need to be built up over time and through joint working, so that the different ways of thinking can be absorbed. This chapter includes examples of partnership working in the Australian tsunami warning system, on health impact tools for dispersion of toxic materials in the UK and on the health impacts of heatwaves in Australia. We conclude with a summary of the characteristics that contribute to effective impact models as components of warning systems, together with some pitfalls to avoid.

AbstractIn this chapter, we explore the challenges of achieving a level of awareness of disaster risk, by each person or organisation receiving a warning, which allows them to take actions to reduce potential impacts while being consistent with the warning producer’s capabilities and cost-effectiveness considerations. Firstly we show how people respond to warnings and how the nature and delivery of the warning affects their response. We look at the aims of the person providing the warning, the constraints within which they must act and the judgement process behind the issue of a warning. Then we address the delivery of the warning, noting that warning messages need to be tailored to different groups of receivers, and see how a partnership between warner and warned can produce a more effective result. We include illustrative examples of co-design of warning systems in Argentina and Nepal, experience in communicating uncertainty in Germany and the Weather-Ready Nation initiative in the USA. We conclude with a summary of aspects of the warning that need to be considered between warner and decision-maker when designing or upgrading a warning system.

AbstractIn this chapter, we examine the ways that warning providers connect and collaborate with knowledge sources to produce effective warnings. We first look at the range of actors who produce warnings in the public and private sectors, the sources of information they draw on to comprehend the nature of the hazard, its impacts and the implications for those exposed and the process of drawing that information together to produce a warning. We consider the wide range of experts who connect hazard data with impact data to create tools for assessing the impacts of predicted hazards on people, buildings, infrastructure and business. Then we look at the diverse ways in which these tools need to take account of the way their outputs will feed into warnings and of the nature of partnerships that can facilitate this. The chapter includes examples of impact prediction in sport, health impacts of wildfires in Australia, a framework for impact prediction in New Zealand, and communication of impacts through social media in the UK.