Science blog

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From VALORADA to practice: new Jupyter books for climate risk assessments

Two new Jupyter books, developed through the EU-funded VALORADA project, help users combine Copernicus climate data with local information to assess drought and extreme precipitation risks across Europe.
Contour map showing areas of extreme heat intensity across the Northern Hemisphere, with the highest values concentrated over northern Eurasia and parts of Europe, displayed using shades from yellow to dark red.

Forecasting the European heatwaves of May to August 2026

Summer 2026 was the warmest on record for western Europe. How well did we predict the exceptional warmth across the season, as well as the individual heatwaves?
Panoramic landscape with dark storm clouds and heavy rainfall over a valley. Green vegetation fills the foreground, while a bare tree stands on the right, highlighting the contrast between lush forest and approaching severe weather.

Tornadoes in Indonesia: understanding the environments behind Puting Beliung

WMO Fellow Ruth Mahubessy investigates the atmospheric conditions behind Indonesia’s non-supercell tornadoes and what they reveal about tropical tornado environments.
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Making sense of complexity: an AI assistant for the IFS

A new IFS Assistant helps users navigate the Integrated Forecasting System by connecting code, documentation and workflows through natural-language queries.
Urban skyline under extreme heat, with a bright sun and hazy atmosphere illustrating hot, potentially heat-stressful conditions.

What operational use can tell us about forecasting human thermal stress

As heat stress intensifies, what can we learn from real-world experience of thermal stress forecasting around the world?
ERA5 climate stripes

Reanalysis: shedding light on the past, present and future of weather and climate prediction

Reanalysis reconstructs Earth’s past by combining observations and models, underpinning climate science and AI weather forecasting, with ERA5 widely used today and ERA6 set to deliver improved capability and resolution.
Map of world with countries in grey and oceans in red and blue with the El Nino 3.4 region in a box

Measuring the strength of El Niño – introducing Relative Niño indices

ECMWF introduces Relative Niño indices, developed with partners and supported by WMO, to better assess El Niño strength in a warming climate as forecasts suggest an unusually strong El Niño event in 2026.
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Forecasting views of Earth from Artemis II with the IFS

Following NASA’s successful Artemis II mission to the Moon in April, Philippe Lopez explored how well ECMWF’s operational Integrated Forecasting System (IFS) could simulate some of the most iconic views of Earth taken by the crew from the Orion spacecraft.
Map of the tropical Pacific and Americas showing strong warm sea surface temperature anomalies across the eastern and central equatorial Pacific, with broader ocean warming surrounding the region.

How confident should we be in a prediction of El Niño?

Seasonal forecasts are fuelling headlines about El Niño, but uncertainty remains. This blog explains what the signals mean, where confidence is growing, and why caution is still essential.
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Separating the signal from the noise

Separating forecast errors into information and noise reveals true predictive skill, improves how weather models are evaluated, and enables fairer comparisons between traditional numerical and emerging machine learning approaches.
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The AI Weather Quest: spotlighting the best of machine learning sub-seasonal prediction

At the midpoint of its first competitive year, the AI Weather Quest brings together a global community advancing machine learning methods for sub‑seasonal forecasting.
Forest fire

Build your own probability of fire model

The PoF-Toolbox is a lightweight, reproducible framework for building local machine learning probability of fire models using user-defined data, helping translate global fire signals into locally meaningful risk information.
Satellite image of a hurricane

The eye of the storm: how EarthCARE is helping to evaluate hurricane physics in ECMWF forecasts

EarthCARE’s overpass of Hurricane Humberto captured the first space-based view of vertical winds and precipitation inside an eyewall, offering unprecedented insight into storm structure and updrafts that will help ECMWF improve hurricane understanding, intensity prediction and forecasts.
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Simplifying AI for weather forecasting with the European Weather Cloud

Rising demand for AI and ML workloads on the EWC has driven ECMWF to develop ready-made templates that democratise access by simplifying setup and lowering technical barriers. Available through the EWC Community Hub, they help users focus on science over infrastructure.
A green landscape in Indonesia with a dark grey sky above

Forecasting of convective weather in Indonesia

Ruth Mahubessy explores how Indonesia’s complex weather patterns challenge forecasters and how a new ECMWF–WMO Fellowship project aims to improve predictions of extreme rainfall and landspouts in the tropics.
Rain pouring down on a rainforest in Ecuador

Evaluating rainfall forecasts in Ecuador: Observations from AI and physical models

WMO Fellow Angela Iza Wong explores the challenge of forecasting rainfall in Ecuador.
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Getting the most out of ECMWF sub-seasonal forecasts

Tim Hewson introduces a new type of forecast map which enables users to visualise the information content of sub-seasonal forecasts like never before.
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The AI Weather Quest: uniting international expertise to advance sub-seasonal forecasting

As the competition phase of the AI Weather Quest starts, the organisers introduce the competition framework and establish a baseline by assessing the skill of current dynamical sub-seasonal forecast models.
ESA Arctic Weather Satellite

Small-but-mighty Arctic Weather Satellite now assimilated at ECMWF

ECMWF has started operational assimilation of data from a trail-blazing small satellite launched by the European Space Agency (ESA) that provides new microwave sounding measurements from space. The new observations give a robust forecast improvement, complementing similar sensors from larger platforms.