All-hazards resilience · Climate adaptation

Understanding risk.
Building resilience.

Zen Bell

I’m Zen Bell, a disaster resilience and climate adaptation specialist on the Northern Beaches. I share updates, research and practical tools across all hazards, and on how community, education, science and technology build resilience.

All hazards · Disaster resilience · Climate adaptation · Community & education · Science & technology

On my reading list

Latest science.

Explore the digest →

Nature · Aug 2026

WeatherNext Cyclones: AI forecasts of cyclone track, intensity and wind structure

Alet F., Andersson T., Price I. et al. (Google DeepMind, Google Research, US National Hurricane Center, CIRA, UK Met Office)

Google DeepMind’s WeatherNext model reached state-of-the-art accuracy for cyclone track, intensity and wind structure. On 2023–2024 cyclones it gained more than 24 hours of lead time, so its three-day forecasts matched what earlier models gave for two days. A 1,000-member ensemble produces probability maps of tropical-storm to hurricane-force winds up to 15 days ahead. The code and model weights are open source, and live forecasts can be explored in Google’s Weather Lab.

Why it matters

An extra day of warning is time for evacuation, pre-positioning and asset protection. The paper does not report results for the Australian region, so its value for Australian cyclones still needs local evaluation alongside Bureau of Meteorology warnings, which remain the official source.

AICycloneEarly warning
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CSIRO Northern Rivers Resilience Initiative · Jun 2026

Scenario testing and recommendations for future flood mitigation activities in the Richmond River catchment

Vaze J., Mateo C.M., Nguyen C. et al. (CSIRO), for NEMA

The first detailed hydrodynamic model of the whole Richmond River catchment tested community- and council-proposed mitigation bundles against the 2008, 2017 and 2022 floods. For the February 2022 peak at Lismore, one bundle lowered the modelled level by 2.07 m (14.87 m to 12.80 m), though the CBD levee was still overtopped. CSIRO notes a business case, cost-benefit analysis and detailed design are still needed.

Why it matters

A leading Australian example of catchment-scale, co-designed mitigation modelling, and an honest look at what mitigation can and cannot achieve.

FloodNSWMitigation
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Nature Communications · Jun 2026

Deep learning completes US flood hazard maps revealing millions exposed to previously unrecognized risk

Wu A.N., Zhang Y., Stouffs R.

Official US flood maps cover only about a third of river channels. An open-source deep-learning model learned from existing maps to complete a 30 m flood hazard map, finding 11 million more people and 4.1 million more buildings in flood zones than the official baseline, with vulnerable groups over-represented in unmapped areas.

Why it matters

Many councils have patchy or ageing flood studies; AI can help fill gaps for prioritisation, though it does not replace detailed studies.

AIFloodMapping
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The wider picture

Hazard & climate signals.

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A tool for thinking

Which assets need
a closer look?

Climate Risk Prioritiser

Explore exposure, vulnerability and loss of service. Flag compound hazards and consider what should happen next.

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What I focus on

Connecting the pieces.

01

All-hazards risk & resilience

I work across the full hazard picture: flood, storm tide and coastal inundation, cyclone and severe storm, bushfire, heat, drought, earthquake and tsunami, from prevention and preparedness to response and recovery.

02

Compound & cascading hazards

I look at how hazards overlap, sequence and cascade, and why a single-hazard view can miss the risk.

03

Council assets & adaptation pathways

My focus is loss of service: connecting high-risk assets to adaptation pathways with clear triggers for action.

04

Community resilience & education

I make hazard and climate information clear, relevant and usable, so communities, community leaders and decision-makers know what it means for them.

05

Science into practice

I follow new research on hazards, disasters and climate, and translate it into what it means for planning, investment and preparedness in Australia.

06

AI, GIS & decision tools

I’m interested in how AI, GIS and practical decision tools can help people understand hazard and climate risk and explore their options.

About me

Resilience starts
with understanding.

For more than 14 years I’ve worked on disaster risk reduction and climate adaptation across Australia, Japan, Southeast Asia and the Pacific. I believe resilience starts with understanding: risk data only makes a difference when people know what it means for them.

My work spans prevention, preparedness, response and recovery, and the community, education, science and technology that make resilience possible.

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