Models’ increasing capabilities to capture environmental phenomena at higher and more joined-up resolutions is blurring formerly distinct boundaries between weather, climate and air quality services. It is well established that the scale of the issue being modelled – e.g., an expected climate change impact – and the scale at which it is governed must be aligned to effectively create change. Yet only recently have real-world issues started to be treated as multi-scalar, requiring a degree of continuity between one type of scale framing and another.
A lack of awareness that scale framing varies across scientific disciplines, is dynamic, and is a socially and politically constructed process risks delaying the effective deployment of weather, climate and air quality services. For example, the physical sciences often equate spatial and temporal scale with a model resolution, while in the social sciences or ecology scale refers to the conceptual hierarchy of spaces and their interplay to reflect levels of organisation in the real world. Even within the physical sciences, research communities providing air quality and weather forecasts and those providing climate predictions and projections have traditionally worked in silos, using different methods, models, language and, of course, scales. These academic divides make no sense to most practitioners, where planning and decision making often simultaneously considers different time horizons, spatial resolutions, and types of environmental stressor.
What’s more, new types of modelling (e.g. seamless and km-scale climate models) are attracting new types of decision makers to these services. While co-production efforts have worked hard to show that one size of service doesn't fit all users, effort is now needed to show that that one scale doesn't fit all either.
We thus envisage a transdisciplinary session, welcoming submissions from practitioners and researchers to kick-start a collaborative, scale-related, community of practice. As long as each presentation foregrounds the issue of scale, we are open to the background setting it draws on (it may be a model, a co-production experience, a societal need etc.). We aim to actively facilitate the debate around three staging points:
1) Setting scales: Why scale is important to a particular phenomenon/use case, e.g. to:
a) resolve specific environmental phenomena, like urban canyon effects, or
b) align with decision making contexts, like at a municipal or basin level.
2) Crossing scales: How similar information can be provided across different framings of the same dimension, e.g.,
a) seamless climate services providing comparable information across prediction/projection timescales.
3) Transforming scales: Where reframing the scale of an issue can answer different questions or achieve different outcomes, e.g.,
a) zooming in, like overlaying climate predictions with air quality forecasts to map heat–health vulnerabilities, or
b) zooming out, like extrapolating lessons learned during local co-production efforts to designing regional-level services.
A lack of awareness that scale framing varies across scientific disciplines, is dynamic, and is a socially and politically constructed process risks delaying the effective deployment of weather, climate and air quality services. For example, the physical sciences often equate spatial and temporal scale with a model resolution, while in the social sciences or ecology scale refers to the conceptual hierarchy of spaces and their interplay to reflect levels of organisation in the real world. Even within the physical sciences, research communities providing air quality and weather forecasts and those providing climate predictions and projections have traditionally worked in silos, using different methods, models, language and, of course, scales. These academic divides make no sense to most practitioners, where planning and decision making often simultaneously considers different time horizons, spatial resolutions, and types of environmental stressor.
What’s more, new types of modelling (e.g. seamless and km-scale climate models) are attracting new types of decision makers to these services. While co-production efforts have worked hard to show that one size of service doesn't fit all users, effort is now needed to show that that one scale doesn't fit all either.
We thus envisage a transdisciplinary session, welcoming submissions from practitioners and researchers to kick-start a collaborative, scale-related, community of practice. As long as each presentation foregrounds the issue of scale, we are open to the background setting it draws on (it may be a model, a co-production experience, a societal need etc.). We aim to actively facilitate the debate around three staging points:
1) Setting scales: Why scale is important to a particular phenomenon/use case, e.g. to:
a) resolve specific environmental phenomena, like urban canyon effects, or
b) align with decision making contexts, like at a municipal or basin level.
2) Crossing scales: How similar information can be provided across different framings of the same dimension, e.g.,
a) seamless climate services providing comparable information across prediction/projection timescales.
3) Transforming scales: Where reframing the scale of an issue can answer different questions or achieve different outcomes, e.g.,
a) zooming in, like overlaying climate predictions with air quality forecasts to map heat–health vulnerabilities, or
b) zooming out, like extrapolating lessons learned during local co-production efforts to designing regional-level services.