Weather and data visualization for non-technical stakeholders
We translate complex weather and climate data into clear information for decisions. We currently offer pro bono support to organizations, public bodies, and community groups that need clarity on weather and climate risks.
Liminal Weather is a small consultancy focused on making weather and climate information understandable and useful. We turn model output, observations, and technical reports into concise explanations and visuals for people who do not work with meteorology every day.
As part of our commitment to open and shared knowledge, we are currently offering our services pro bono to non-profits, public institutions, and community groups.
We work with open source software and open data, and document our methods so results can be understood, reproduced, and reused.
Liminal Weather is led by an atmospheric and data scientist with over 25 years of experience in numerical weather prediction, ensemble and probabilistic forecasting, climate and reanalysis projects, and data visualization.
Experience spans national weather services, research institutes, and industry, including work on wind energy, computational fluid dynamics, and road weather applications.
We help organizations understand how weather and climate affect operations, planning, and risk, by turning technical data into clear, actionable material for decision-makers.
Analysis of forecasts, reanalyses, and observations tailored to your locations, assets, or projects. We provide simple statistics, uncertainty estimates, and concise summaries focused on the questions you need to answer.
Design of clear plots, maps, and dashboards that show what matters at a glance. We create visuals that can be reused in internal reports, presentations, and public communication.
Plain-language explanations of technical documents, model output, and scientific reports. We prepare written summaries and briefings for boards, management, and other non-technical stakeholders.
Analysis workflows built with open source tools (e.g. Python, R, and common geospatial libraries). Methods and scripts are documented so your team can rerun, adapt, and extend the work as needed.
Methods, assumptions, and limitations are documented. Where possible, underlying code and data processing steps are shared.
We use open source software and data whenever we can, avoiding vendor lock-in and making it easier to reuse and adapt our work.
We focus on what is relevant for your decisions, remove unnecessary complexity, and explain uncertainty in straightforward terms.
Realistic statements about what forecasts and climate data can and cannot provide, and practical recommendations grounded in the available evidence.
If you have a project or dataset where weather or climate play a role, briefly describe your organization, the decisions you need to support, and any timing constraints. You will receive a response about whether Liminal Weather can help and what a collaboration could look like.