The World Weather Research Programme: A 10-year Vision

By Gilbert Brunet¹, Thomas Jung², Neil Gordon³, Frédéric Vitart⁴, Andrew Robertson⁵, Brian Golding⁶, Sarah Jones⁷, Helge Goessling⁸ and WMO Secretariat⁹

Weather prediction has achieved immense progress, driven by research and increasingly sophisticated telecommunication, information technology and observational infrastructure. Predictive skill now extends in some cases beyond 10 days, with an increasing capability to give early warning of severe weather events many days ahead. Ensemble methods now routinely provide essential information on the probability of specific events, a key input in numerous decision-making systems. Partly because of these advances, the needs of the users of weather services have simultaneously diversified to encompass “environmental” prediction products such as air quality and hydrological predictions.

It is the research and technical developments carried out in operational centres and academic institutions, by surface and space-based observational data providers, and in the computing industry, that have made these advancements possible. Over recent decades a number of major international research programmes have been critical in fostering the necessary collaboration. In particular, the WMO World Weather Research Programme (WWRP) and The Observing System Research and Predictability Experiment (THORPEX, which ran from 2005-2014), have been major initiatives to accelerate this progress.

Informed by the realization that there can be predictive power on all space and time-scales arising from what are currently poorly-understood sources of potential predictability, meteorological science is now primed for a step forward.

In this context, the Earth system – and environmental prediction – encompasses the atmosphere and its chemical composition, the oceans, the sea-ice and other cryosphere components and the land-surface, including surface hydrology, wetlands, and lakes. The relevant parts of the system also include the short time-scale phenomena that result from the interaction between one or more components such as severe storms, floods, heat waves, smog episodes, ocean waves and storm surges. On longer – beyond seasonal – time scales, the terrestrial and ocean ecosystems including the carbon and nitrogen cycles and slowly varying cryosphere components, such as the large continental ice sheets and permafrost, are also part of the Earth system; these time scales, however, are the subject of the World Climate Research Programme (WCRP) with which WWRP strongly interacts.

WWRP, working in partnership with others, will ensure the implementation of a research strategy for the seamless prediction of the Earth system from minutes to months. Three THORPEX legacy projects will be the pillars of this strategy in the next 10 years:

• the WWRP Polar Prediction Project, which aims to promote cooperative international research enabling the development of improved weather and environmental prediction services for the polar regions on time scales from hours to seasonal;
• the Subseasonal to Seasonal Prediction Initiative, a joint WWRP/WCRP project, aims to improve forecast skill and enhance knowledge of processes on the subseasonal to seasonal timescale with a focus on the risk of extreme weather, including tropical cyclones, droughts, floods, heat waves and the waxing and waning of monsoon precipitation; and
• the High Impact Weather (HIWeather) project for promoting cooperative international research to achieve a dramatic increase in resilience to high-impact weather worldwide by improving forecasts for timescales of minutes to two weeks and enhancing their communication and utility in social, economic and environmental applications.

The Polar Prediction Project

There has been a growing interest in the polar regions in recent years, fuelled by concerns about the amplification of anthropogenic climate change and the fact that they represent one of the planet’s last major geographic frontiers of natural resource discovery and development. Technological and engineering advances over the past 40 years—especially in the areas of telecommunications, transportation and industrial processes—coupled with escalating global market demands for raw materials like oil, natural gas, and minerals, have drawn considerable investment, research and development, migration (in some areas), and political interest to the polar territories.

Recognising this, the 2011 World Meteorological Congress decided to embark on a decadal endeavour: the development of a Global Integrated Polar Prediction System (GIPPS). Delivering GIPPS will require research to improve understanding of, for example, polar clouds, sea-ice/ocean dynamics, permafrost and ice-sheet dynamics. It will enhance our knowledge of polar-lower latitude linkages, optimize the polar observing system, develop data assimilation systems, enhance modelling systems and advance ensemble prediction components in order to improve predictions across a wide range of time scales.

Two closely related initiatives, the WWRP Polar Prediction Project and the WCRP Polar Climate Predictability Initiative (PCPI), aim to contribute to GIPPS.

In order to meet a rapidly growing demand for skilful and reliable predictions in polar regions and beyond, the following eight key research goals have been identified:

• improve the understanding of the requirements for, and evaluate the benefits of, enhanced prediction information and services in polar regions;
• establish and apply verification methods appropriate for polar regions;
• provide guidance on optimizing polar observing systems and coordinate additional observations to support modelling and verification;
• improve representation of key processes in models of the polar atmosphere, land, ocean and cryosphere;
• develop data assimilation systems that account for the unique characteristics of polar regions;
• develop and exploit ensemble prediction systems with appropriate representation of initial conditions and model uncertainty for polar regions;
• determine predictability and identify key sources of forecast errors in polar regions; and
• improve knowledge of two-way linkages between polar and lower latitudes and their implications for global prediction.

Achieving the above goals will demand enhanced international and interdisciplinary collaboration through the development of strong connections with related initiatives; strengthened linkages between academia, research institutions, and operational forecasting centres; greater interaction and communication between research and stakeholders; and the promotion of education and outreach. But the expected benefits will reach beyond the time scales (hours to seasonal) and regions (Arctic and Antarctic) considered in the Polar Prediction Project:

• improvements anticipated in the representation of key polar processes in (coupled) models, such as stable boundary layers and sea-ice dynamics, are expected to reduce systematic errors in climate model integrations and, hence, help narrow uncertainties of regional and global climate change projections; and
• improved environmental predictions in the polar regions will lead to more precise predictions for non-polar regions due to the existence of global teleconnections.

To exploit the full potential of this truly “seamless” area of research, it is mandatory to develop and maintain close ties with the climate research community and part of the weather prediction community that has traditionally focused on the non-polar regions.

Observations play a cross-cutting role in the context of a coupled polar prediction system. At a fundamental level, it is observations that are used to develop a basic understanding of physical processes that must be modelled within the ocean-atmosphere-land-wave-ice system. Observations are needed for initialization/assimilation and verification of models, and they play a key role in improving parameterizations and forecasts. In situ measurements are required to improve various aspects of satellite retrievals and are the only means of observing the sub-surface ocean. These statements are basic truths whether the forecast system is coupled or un-coupled, polar or global. Therefore, it is important to focus on issues–modelling, data assimilation, and ensemble forecasting–particular to the coupled polar problem.

The Year of Polar Prediction (YOPP), with a core period from mid-2017 to mid-2019, will be the keystone of a focused and intensive international effort to obtain greatly enhanced polar observations and prediction capabilities. This effort is planned to include one or more multi-year sea-ice based observing stations (the planned Multidisciplinary drifting Observatory for the Study of Arctic Climate (MOSAiC) being one of them), enhanced deployment of autonomous samplers, enhanced monitoring from routinely operating polar ships and coordinated intensive field studies from research vessels, aircrafts and surface stations. YOPP will be carried out in close collaboration with PCPI and other related initiatives. It encompasses four major elements: an intensive observing period, a complementary intensive modelling and forecasting period, a period of enhanced monitoring of forecast use in decision-making, including verification, and a special educational effort. (For more information see WMO Bulletin Volume 63 (1) 2014.)

The Subseasonal to Seasonal Prediction project

Forecasting for the sub-seasonal time range has so far received much less attention than medium range and seasonal prediction as it has long been considered a “predictability desert.” Recent research has indicated important potential sources of predictability through better representation of atmospheric phenomena such as the Madden-Julian Oscillation and improved coupling with, and initialization of, the land-ocean-cryosphere and stratosphere.

From the end-user perspective, the sub-seasonal to seasonal time range is a very important one as many management decisions in agriculture and food security, water, disaster risk reduction and health fall into this range. Better understanding of these potential sources of predictability, together with improvements in model development, data assimilation and computing resources, should result in more accurate forecasts.

The sub-seasonal to seasonal prediction initiative will involve the following:

• evaluating the potential predictability of subseasonal events, including identifying windows of opportunity for increased forecast skill with special emphasis on high-impact weather events;
• understanding systematic errors and biases in the sub-seasonal to seasonal forecast range;
• comparing, verifying and testing multi-model combinations from these forecasts and quantifying their uncertainty; and
• focusing on some specific extreme event case studies such as the Russian heat wave of 2010, the floods in Pakistan in 2010 and Australia in 2011 and the European cold spell of 2012. (For more information see WMO Bulletin Volume  61 (2) 2012.)  

The High Impact Weather Project

The potential of advanced weather-related hazard forecasting has been demonstrated – there is clearly a huge opportunity to protect lives and to benefit communities. The HIWeather vision is to “Promote co-operative international research to achieve a dramatic increase in resilience to High Impact Weather worldwide” by improving forecasts for timescales of minutes to two weeks and enhancing their communication and utility in social, economic and environmental applications.

Weather impacts depend both on the severity of the weather-related hazard and on the vulnerability of those exposed to it. In order to increase resilience, research is required to improve the monitoring and prediction of weather and related hazards, but also to better understand the human impacts and effectively communicate information to those most vulnerable. The scope of the project thus integrates work in many physical and social science disciplines.

HIWeather will focus on reducing mortality, morbidity, damage and disruption related to five selected hazards:

• urban floods due to intense rain, out-of-bank river flows, coastal waves and surge overtopping and from consequent urban landslides;
• wildfire and their smoke;
• extreme local wind and wind blown debris due to tropical and extra-tropical cyclones, downslope windstorms and convective storms, including tornadoes;
• extreme winter weather – snow, ice and fog – that impact transport, power and communications infrastructure; and
• heat and air pollution in megacities.

HIWeather will be delivered through five research themes:

• understanding of the processes and predictability of hazard-related weather systems, focusing on how weather forecast errors for extreme events could be reduced, scale interactions, causes of stationarity, the roles of the planetary boundary layer and land-surface and hazard-specific processes;
• multi-scale forecasting of hazards, using coupled numerical weather, ocean, land-surface, ice- and air-quality modelling, nowcasting, data assimilation and post-processing systems, focusing on convective-scale observations, data assimilation, parameterization of cloud and land-surface processes, ensemble prediction and user products for short-range hazard forecasts;
• forecasting the human impacts, exposure, vulnerability and risk of hazards to people, buildings, businesses, infrastructure and environment, focusing on obtaining observations, sharing existing methods, representing vulnerability and increasing expertise in this area of work;
• communicating hazard forecasts and warnings to reach vulnerable communities and achieve responses from risk managers and the public that increase resilience, focusing on sharing and developing good practice, observing and understanding reasons for different responses and growing research capability; and
• evaluating hazardous weather, impact and risk forecasts, alerts and warnings and the resulting responses with user-relevant metrics, focusing on obtaining suitable observations, modelling information loss through the production chain, developing verification methods for hazards, impacts and responses, assessing economic value and growing research capability.

The themes are supported by eight cross-cutting activities: benefits in operational forecasting; design of observing strategies; field campaigns and demonstrations; better understanding of the sources of uncertainty and how uncertainty should be communicated throughout the decision-making chain; knowledge transfer verification; impact forecasting; data management and archiving.

A Steering Group composed of two co-chairs, representing the physical and social sciences, and a lead investigator from each of the research themes will manage the project. A Strategic Advisory Board will provide oversight by the stakeholder communities: national meteorological and hydrological services, disaster reduction, hydrology, health, economic development, forecasting, observations and technology. Outputs will be integrated in forecast demonstration projects that will bring together academics, operational services and end users to evaluate new capabilities in specific hazard warning environments.

A new era

We are entering a new era in technological innovation and in the use and integration of different sources of information for well-being and ability to cope with multi-hazards. In the next 10 years research activities in weather science will deliver new predictive tools that will detail weather conditions to the neighbourhood and street level, provide early warnings a month ahead and forecast rainfall for energy companies. A better understanding of small-scale processes and their inherent predictability should go together with a better comprehension of how weather related information influence decision-making processes and a better communication strategy.

 

¹ Deputy Director, Weather Science, MetOffice, United Kingdom of Great Britain and Northern Ireland (UK)
² Chair, Polar Prediction Project; Expert member, WMO Executive Council Panel of Experts on Polar Observations, Research and Services; and Alfred Wegener Institute, Helmholtz Centre for Polar and Marine Research, Germany
³ Consultant, Polar Prediction Project, New Zealand
⁴ European Center for Medium range Weather Forecasting (ECMWF), Reading, UK
⁵ Head of Climate Group, International Research Institute for Climate and Society (IRI), Earth Institute, Columbia University, United States of America (USA)
⁶ MetOffice, UK
⁷ Head of Research and Development, Deutscher Wetterdienst (DWD), Germany
⁸ Assistant, Polar Prediction Project; Alfred Wegener Institute, Helmholtz Centre for Polar and Marine Research, Germany
⁹ Paolo Ruti, Chief, World Weather Research Division, WMO