When Tracking Disasters Went Dark—and the Rescuers of a Vital Climate Database

Why restoring transparency in disaster data is crucial for our Climate and Ecological resilience

I, Mr. Alvarez, urge you to download (free) and listen to this week’s episode of BradBlog — it’s a must-listen for anyone serious about Adaptive Resiliency, the Climate Emergency, and the Ecological (Green) Emergency we face. Support BradBlog, subscribe, and engage deeply. The conversation with climate scientist Tom Di Liberto (formerly of NOAA, now at Climate Central) is both alarming and empowering.

Introduction & Context

We are in the midst of a Climate Emergency and an Ecological (Green) Emergency. What does that mean? It means the planet’s systems are under stress—oceans warming, storms growing in power, wildfires raging, communities being disrupted. In response, building Adaptive Resiliency—the capacity of individuals, communities, systems to adapt, bounce back, and transform—is not optional: it is essential.

So it matters deeply that we track what’s happening—and yet, as this podcast reveals, a crucial dataset was shut down, only to be resurrected thanks to dedicated scientists. That in itself is a story about resilience, accountability, and the power of transparent data in the service of survival.

Let me walk you through the key insights from the show, extend them with additional research, point out blind spots, and suggest how we—through the Climate Tribe and our organization (Climate Change Community LLC) —can act on it.

The Podcast in a Nutshell

In the BradBlog episode (10/23/2025) host Brad Friedman speaks with Tom Di Liberto about the fate of the Billion-Dollar Weather and Climate Disasters database—originally managed by NOAA—and how it was effectively shut down under the Trump administration, only to be revived by Climate Central with the participation of the very scientists who were exiled. The database had long tracked U.S. weather events causing at least one billion dollars in damage each. According to the podcast:

The first half of 2025 saw 14 events exceeding $1 B each — totaling over $100 B in losses in the U.S., with the Los Angeles wildfires alone topping ~$60 B.
Historically (1980–2024), the average number of those disasters was ~9 per year. Now the recent average is ~24/year and climbing.
The Trump administration closed the update of the database this year. The scientists who built it were laid off or forced out.
Climate Central picked up the baton: the dataset is now “a jewel” of national and global importance.
The danger: without this data, we are operating in the dark, even as disasters accelerate.

Quote (from Di Liberto):

“If you can’t see it, you can’t deal with it.”
“The amount of information that goes into creating this billion-dollar disaster analysis is a lot… it was much too difficult for an individual company to be able to do this.”

Why This Matters for Adaptive Resiliency

Data is not just a bureaucratic detail. When we talk about Adaptive Resiliency, we are talking about the capacity of systems (governments, communities, insurers, infrastructure) to anticipate, absorb, recover from, and adapt to adverse events. That cannot happen without rigorous data.

Planning and preparedness: Knowing how often, how costly, how intense disasters have become helps communities allocate resources, update infrastructure and educate the public.
Insurance and finance: Insurers price risk based on data. When the data disappears or becomes proprietary, risk becomes opaque, premiums may hide the true exposure, and individuals/communities may be blindsided.
Policy and accountability: Transparent disaster records hold leadership to account; shielding or eliminating them weakens democratic oversight.
Public awareness: When the human and economic toll of the Climate Emergency is visible, the motivation for transformation is stronger.

In short: tracking disasters is essential to adaptive resiliency, because you cannot adapt to what you do not know.

What the Research Says: Trends, Gaps & Implications

Trends

According to Climate Central, from 1980–2024 the U.S. experienced 403 billion-dollar disasters, nearly 17,000 deaths, and ~$2.9 trillion in direct damages. Climate Central+2HSToday+2
The average number of these events per year has surged: from about 3 events annually in the 1980s to ~19 per year in the last decade. Climate Central+1
The time between such events shrank from 82 days in the 1980s to 19 days recently. Climate Central
The most costly disaster types: tropical cyclones (hurricanes) account for ~53% of total costs; severe storms (hail, tornadoes, damaging winds) are the most frequent. Climate Central

Gaps & Critical Risks

The original NOAA dataset ceased updates beyond 2024, meaning we risk losing visibility of ongoing trends. PBS+1
The privatization or closure of public data sets raises issues of access, transparency, and equity: proprietary data may not be freely available to all communities. Insurance Journal
Many disasters under the $1 B threshold fall out of this tracking—even though cumulative damage from “smaller” events can be astronomical, especially in vulnerable communities. Climate Central
Climate models show that the Ecological (Green) Emergency—loss of biodiversity, ecosystem collapse—interacts with disaster risk in ways not always captured by purely cost‐based metrics.
The influence of Urbanization, Infrastructure Fragility, and Social Inequality means that disaster cost metrics understate human suffering and unpriced losses (mental health, social displacement, ecosystem services).

The Strategic Narrative: From Silence to Data Resurrection

There is a narrative arc here that matters for our community and our mission of Adaptive Resiliency:

Silence: When tracking stopped, the message to the public and to officials was: “We don’t need to know, or we won’t know.” That undermines preparedness.
Resurrection: A nonprofit and ex‐government scientists stepped in. They refused to let the database die. That is a powerful example of proactive resilience.
Resistance and Renewal: This story shows how institutional resilience (bringing the data threatened with extinction back) is part of the broader resilience we must build for people and ecosystems.
Call to Action: We must not wait for perfect institutions. We must support transparency, hold systems accountable, and build redundant capacities.

How You (and the Climate Tribe) Can Respond

Since our work at Climate Change Community LLC and our Climate Tribe is focused on Adaptive Resiliency, we can draw actionable steps from this story:

Promote Transparency: Advocate for open data systems in your local region or network. Use the now‐revived database from Climate Central as a model.
Use the Data: Integrate the dataset’s insights into our learning modules: show how disaster frequency and cost are rising, use the visuals from Climate Central.
Educate Others: Use the podcast episode as a resource in workshops, newsletters, or webinars—make it required listening for community members.
Expand the Metrics: Recognize that cost‐based disaster metrics are important—but also push for ecological health metrics, social vulnerability metrics, and long-term recovery metrics.
Build Redundancy: Just as a dataset was rescued, we should build backup learning, backup community networks, and community‐led data gathering in case institutional supports falter.
Support AI & Monitoring: Since part of our vision is using AI for Adaptive Resiliency, use this as a case study for how AI‐assisted monitoring and early-warning systems (powered by renewables) can plug data gaps and empower communities.

Risks and Blind Spots (Constructive Pushback)

Celebrating the resurrection is valid—but we must be cautious: Non‐governmental data initiatives often rely on voluntary funding, which may make them vulnerable to budget cuts or donor shifting. Sustainability of the dataset is not guaranteed.
The $1 B threshold is arbitrary—many disasters less costly still devastate marginalized communities. The focus on big numbers may obscure structural inequities.
The data focuses on direct economic cost—but ignores ecosystem services loss, cultural heritage damage, mental health toll, and indirect economic effects (supply chains, food security) which are central to Ecological (Green) Emergency thinking.
Institutional memory matters: When the agency that held the data is undermined (as NOAA was, per story), rebuilding trust takes time. Our work must include strengthening community trust and local systems.
The narrative of “rescue” may obscure the deeper issue: the systemic weakening of climate science capacity at national level. Our goal must include strengthening institutions broadly—not just patching one broken link.

Real-World Example: Wildfire Costs in California

The podcast mentions the Los Angeles wildfires as causing more than $60 billion in damage—making them among the costliest ever. This illustrates the convergence of several factors:

A warming climate that primes landscapes for fire.
Wildland-urban interface development increasing exposure.
Infrastructure (power lines, gas lines, homes) that are vulnerable.
Insurance markets strained and premiums soaring.
The human toll—not just dollars—of families displaced, smoke inhalation, ecosystem damage.

When we build Adaptive Resiliency, we must address all of those dimensions: ecological health (forest regeneration), community planning (zoning), infrastructure (hardened grid), and insurance/finance adaptation (community risk pools).

A Vision for the Future: Integrating Data, AI, and Adaptive Resiliency

Imagine a public-facing AI assistant (running on renewable energy), built by the Climate Tribe, that can:

Pull in the revived billion-dollar disaster dataset (and subsequent updates).
Map local risk exposures (wildfire, flood, heat, storms) for any neighbourhood.
Provide community planners, citizens, insurers with real-time dashboards on disaster trends + projections.
Integrate ecological indicators (biodiversity loss, wetland degradation) alongside economic cost metrics.
Offer scenario modelling: “If the interval between billion-dollar disasters shrinks from 19 days to 15 days by 2030, here’s what your region looks like.”
Surfacing not just vulnerabilities but also resilience levers: e.g., community microgrids, nature-based infrastructure, community education.

In other words: data + AI + community action = meaningful Adaptive Resiliency.

Call to Action

If you haven’t yet, please download and listen to the BradBlog episode with Tom Di Liberto. Share it within your networks. Treat it as required listening.
Consider writing a blog post, organizing a listening party with the Climate Tribe, or incorporating the data insights into your next learning session with Eva Garcia.
Support BradBlog and Climate Central. Why? Because the public good—transparent climate data—is under constant pressure. If we don’t support it, we risk enabling silence.

Conclusion

The story of the billion-dollar disaster database is not just a data story. It is a story about truth, resilience, vigilance, and community. When the dataset was threatened, the scientists acted. When the system faltered, the mission persisted. That is exactly the ethos of Adaptive Resiliency—not waiting for perfect systems, but acting decisively, collaboratively, and ethically in the face of crisis.

We stand at a confluence of the Climate Emergency, the Ecological (Green) Emergency, and the imperative of Adaptive Resiliency. To navigate that confluence, we need reliable data, engaged communities, intelligent tools, and unflinching realism. The podcast offers one piece of that roadmap.

Let’s take it seriously. Let’s do the hard work. Let’s build the resilient, equitable future our planet demands.

Mr. Alvarez + Eva Garcia
Level 3 Strategic Addendum & Level 4 Blueprint coming in next post.

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