Tag: 2026

The fourth webinar of the LandAware 2026 webinar series “What Makes Landslide Forecasts Actionable? Lessons from Users of Aotearoa New Zealand’s Trial Products”, by Sara Harrison (Earth Sciences New Zealand) is scheduled for 30 April 2026, 05:00 UTC.

Dr Sara Harrison is a Hazard and Risk Social Scientist at Earth Sciences New Zealand, specialising in the design and use of people‑centred early warning systems for natural hazards.

Her work focuses on how hazard forecasts, warnings, and decision‑support tools are developed, communicated, and used in real‑world risk management, with a strong emphasis on ensuring science is actionable for those who need it most. In her current role, Sara contributes to national and international projects exploring how trial forecasting products—such as landslide, severe weather, and tsunami hazard and impact forecasts—can be made more usable, trusted, and decision‑relevant. Her work bridges social science and operational hazard modelling, helping ensure that forecast products support effective action rather than simply providing more information.

In this webinar, Sara draws on lessons from users of Aotearoa New Zealand’s trial landslide forecasting products to explore what makes forecasts truly actionable—and how understanding user contexts, decision thresholds, and institutional settings is just as critical as improving technical accuracy.

The third webinar of the LandAware 2026 webinar series “Atmospheric River Controls on Extreme Rainfall and Landslide Hazard in Southeast Alaska”, by Deanna Nash (Center for Western Weather and Water Extremes) is scheduled for 26 March 2026, 15:00 UTC.

Abstract:
Landslides triggered by extreme precipitation during atmospheric rivers (ARs) pose significant hazards to rural and Indigenous communities in Southeast Alaska. Recent research has demonstrated a strong relationship between AR strength and extreme precipitation in the region; however, forecasted AR magnitude and duration alone do not fully explain when impacts occur or provide sufficient context for emergency managers and the public. To address this gap, ongoing collaborative work with the National Weather Service (NWS) in Juneau is focused on developing a forecasting tool that leverages the relationship between AR characteristics and extreme precipitation while also incorporating additional key factors such as freezing level, low-level wind speed and direction, AR orientation, and forecasted precipitation.
Using NOAA’s Global Ensemble Forecast System version 12 (GEFSv12) reforecast dataset, we developed a Model Climate (M-Climate) framework for integrated water vapor transport (IVT), freezing level, low-level winds, and quantitative precipitation forecasts (QPF). M-Climate places these forecast variables within the context of historical reforecasts with the same lead time and time of year. For example, a 95th percentile M-Climate IVT indicates that the ensemble-mean IVT is greater than 95% of reforecast values at that location, lead time, and time of year. By comparing forecasts to analogous forecasts rather than to observations, M-Climate preserves the magnitude of ensemble-mean anomalies that might otherwise be dampened when compared to observed climatology.
Using a catalog of impactful landslides compiled by NWS Juneau, we applied the M-Climate framework to develop the Southeast Alaska Atmospheric River Impact Tool, which highlights when forecasted AR conditions are most likely to lead to impacts such as landslides. The tool is now available operationally to support NWS Juneau forecasters by improving situational awareness and enhancing Impact Decision Support Services (IDSS) messaging before and during high-impact weather events. By linking forecasted AR characteristics to potential impacts, the tool also helps forecasters communicate risk more effectively to weather partners, community leaders, and the public.

Bio:
Deanna Nash, Ph.D., is a Precipitation and Geohazards Scientist at the Center for Western Weather and Water Extremes at the Scripps Institution of Oceanography at the University of California San Diego. Her research focuses on improving understanding and forecasting of meteorological conditions during atmospheric rivers that produce extreme precipitation and increase the risk of flooding and landslides, particularly in mountainous regions of the world. In Southeast Alaska, she contributed to an NSF-funded project through the Coastlines and Peoples Initiative called KUTÍ (one of the Tlingit words for weather), which collaborated closely with forecasters at the National Weather Service Weather Forecast Office in Juneau to develop forecasting tools for extreme atmospheric rivers that are now incorporated into their operational workflows.