Climate Science Explainers

Latest Blog Post:

• When the Topic Comes Back to You19/02/2026

  On being invited to write about storylines, extreme rainfall, and why this matters to me.

  A few months ago, I received an email that made me pause for a moment.

  I was invited to write a News & Views in Nature Communications on a paper attributing the 2024 Valencia flash floods — a complex, convective extreme rainfall event analysed using a conditional (storyline-based) approach that I had recently reviewed.

  It felt like a real honour to contribute, and I wrote a piece titled “The essential role of conditional attribution in understanding complex extreme weather“.

  

  Storylines — and more broadly, the question of how we understand climate change in extreme weather events — have been close to my scientific heart for a long time. The debate about statistical versus conditional attribution, about probabilities versus processes, about dynamics versus thermodynamics — these aren’t abstract academic discussions to me. They are questions that shape how we translate climate science into something meaningful for society.

  Flash floods caused by convective storms are among the most difficult events to attribute. They are small-scale, highly dynamic and often chaotic. Exactly the kind of extremes that push our models — and our methods — to their limits.

  The study by Calvo-Sancho and colleagues shows that even in these highly complex systems, a clear climate-change signal can be uncovered when we carefully reconstruct and analyse the physical processes within the storm. It demonstrates that attribution is not just about saying whether an event became “more likely,” but also about understanding how global warming reshapes the physical processes within the extreme event itself.

  For me, writing this piece was not just about explaining a method. It was about reflecting on where attribution science is heading — and on the questions that are currently being discussed within the community.

  How do we best combine statistical and conditional approaches?
  How do we move from understanding probabilities to understanding processes?
  And perhaps most importantly: how do we meaningfully connect attribution results to impact research?

  These are active conversations within the attribution community. My task was to translate that debate in a way that readers outside the field could follow and understand.

  Being invited to contribute to that conversation — even in a small way — was an honour. It reminded me why I care about this topic: because understanding extreme weather is not only about getting the science right, but about making that science useful for all of us.

• Tipping Point of AMOC Expected in 2060: New Study Shows27/08/2025

  A new study led by my colleague René van Westen investigates the future of the Atlantic Meridional Overturning Circulation (AMOC) — the great conveyor belt of ocean currents that moves warm water northward and returns colder, denser water southward at depth. This circulation plays a crucial role in regulating Earth’s climate, including weather patterns in Europe and Africa, the strength of monsoons, and sea level along the Atlantic coasts.

  Why is AMOC important?

  The AMOC transports heat from the tropics towards the north. This means the current redistributes heat, keeping northern Europe relatively mild compared to other regions at the same latitude, such as western Canada.

  We already know from observations that the AMOC has been slowing down. A collapse would cause heat to remain where it is instead of spreading across a larger region. This would lead to: a colder climate in northwestern Europe, stronger storms in some regions, drought in others, and disruptions to ecosystems on land and in the ocean.

  A weakening or collapse of AMOC would not raise sea levels evenly everywhere. Instead, it would cause increased sea level across the northern regions of the Atlantic, especially along the U.S. East Coast and parts of northwestern Europe.

  What does the new study show?

  Using climate model simulations and statistical indicators of stability (early warning signals of approaching tipping points), the researchers estimate when AMOC might cross a critical threshold. Their results suggest that under continued greenhouse gas emissions, the tipping point could be reached as early as 2060.

  In their analysis, the collapse happens after around 2.5 °C of global warming. That means AMOC breaking is not inevitable — if we reduce emissions and limit warming, we can prevent crossing this threshold.

  Crossing the tipping point would mean that the AMOC circulation weakens beyond recovery. In other words:
  ➡️ It cannot be fixed once passed.
  ➡️ Crossing the tipping point is permanent.

  Public attention in the Netherlands

  The research received wide attention here in the Netherlands. My colleague René was interviewed by the national news program Nieuwsuur 📺. The AMOC story runs from 28:45 to 34:42 in the episode of 26 August 2025, which you can watch here (in Dutch):
  👉 Nieuwsuur episode
  

  For those who want to dive into the science itself, the peer-reviewed article is available open access:
  👉 Geophysical Research Letters (2025)

  Why it matters

  This study highlights how tipping points in the Earth system are not distant possibilities, but real risks that may occur within our lifetimes. The precise timing is uncertain — but the message is clear: limiting warming below 2.5 °C keeps the AMOC safe. Acting now gives us the chance to prevent a permanent and dramatic shift in our climate system.

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• 🚨 New paper highlight: Spectrally nudged storylines in extreme event attribution21/08/2025

  A brand new paper by Frauke Feser and Ted Shepherd has just been published:
  “The concepts of spectrally nudged storylines for extreme event attribution” (Nature Communications Earth & Environment, 2025)

  I really enjoyed reading it. The paper is clearly explaining a concept that can often feel quite technical. It covers:

  • What spectrally nudged storylines (SN storylines) actually are
  • Their purpose and scientific foundation
  • The difference between storylines and scenarios
  • How SN storylines relate to other conditional attribution methods
  • The way forward, how SN storylines can be used in the future

  All of this is presented with scientific depth, but in a succinct and accessible way.

  Why it matters

  Extreme event attribution (EEA) is about understanding the role of climate change in today’s extreme weather events. Different methods exist, each with their strengths and limitations. Spectrally nudged storylines are particularly powerful because they allow us to explore how the same event would unfold in different climate states.

  The method works by constraining atmospheric dynamics (using spectral nudging) while letting thermodynamics evolve freely. In practice, this means:

  • You can isolate the thermodynamic effects of climate change (e.g. warming, moisture changes).
  • You can keep the meteorological “story” of the event intact, which makes results easy to interpret and communicate.
  • It is especially suited for studying extremes like heatwaves, droughts, heavy rainfall, and tropical storms.

  The Way Forward

  What excites me most is not just what spectrally nudged storylines can already do, but where the field is heading. The concepts outlined by Feser & Shepherd fit into a much bigger picture of how attribution science is evolving, here a small selection:

  From hazard to impact attribution.
  Until now, most attribution work has focused on the meteorological hazard (e.g. heat, rainfall). The next step is linking directly to impacts — how those hazards translate into damages, health effects, or ecosystem responses. Storyline methods, because of their clarity, are well suited for this bridge.

  Bridging storylines and probabilistic approaches
  The attribution community has sometimes been divided between conditional storylines and unconditioned probabilistic frameworks. In reality, these methods are complementary. By applying statistical analysis on a collection of events in the SN storylines, a bridge between the two methods can be build.

  The role of AI
  New machine learning and AI tools can support attribution by uncovering nonlinear relationships and hidden drivers of extreme weather events. Projects such as CLINT and XAIDA are already exploring how AI can enhance climate storylines, improve uncertainty quantification, and accelerate analysis.

  Spectrally nudged storylines are therefore not just another method in the toolbox — they are a key stepping stone toward a more integrated and collaborative future in attribution science.

  Read the paper here