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1834 items found

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Potential for equation discovery with AI in the climate sciences

AI is impacting science, providing key data insights, but most algorithms are statistical requiring cautious "out-of-sample" extrapolation. Yet climate research concerns predicting future climatic states. We consider a new method of AI-led equation discovery. Equations offer process interpretation and more robust predictions. We recommend this method for climate analysis, suggesting illustrative application to atmospheric convection, land–atmosphere CO₂ flux, and global ocean circulation models.

Composite model-based estimate of the ocean carbon sink from 1959 to 2022

The ocean is a major natural carbon sink. Despite its importance, estimates of the ocean carbon sink remain uncertain. Here, I present a hybrid model estimate of the ocean carbon sink from 1959 to 2022. By combining ocean models in hindcast mode and Earth system models, I keep the strength of each approach and remove the respective weaknesses. This composite model estimate is similar in magnitude to the best estimate of the Global Carbon Budget but 70 % less uncertain.

Modulation of the northern polar vortex by the Hunga Tonga–Hunga Ha'apai eruption and the associated surface response

In January 2022, the Hunga Tonga–Hunga Ha'apai (HTHH) volcano erupted, sending massive amounts of water vapour into the atmosphere. This event had a significant impact on stratospheric and lower-mesospheric chemical composition. Two years later, stratospheric conditions were disturbed during so-called sudden stratospheric warmings. Here we simulate a novel pathway by which this water-rich eruption may have contributed to conditions during these events and consequently impacted the surface climate.

The glaciers of the Dolomites: the last 40 years of melting

We have reconstructed the multi-decadal (1980s–2023) ice mass changes for all the current mountain glaciers in the Dolomites. We used historical aerial photographs, drone surveys, and lidar to fill the glaciological data gap for the region. We observed an alarming decline in both glacier area and volume, with some of the glaciers showing smaller losses due to local topography and debris cover feedback. We strongly recommend more specific monitoring of these glaciers.

Decadal changes in phytoplankton functional composition in the Eastern English Channel: possible upcoming major effects of climate change

This study provides the first assessment of decadal changes in the whole phytoplankton community, addressed by flow cytometry, in the highly productive waters of the Strait of Dover. A significant surface seawater temperature increase of 1°C, associated with an important change in the nutrient concentration and balance, has triggered a change in the phytoplankton communities, characterized by a higher total abundance and an increasing proportion of the smallest cells (picroeukaryotes and picocyanobacteria).

Reconstruction of Holocene and Last Interglacial vegetation dynamics and wildfire activity in southern Siberia

We analyse a southern Siberian stalagmite to reconstruct soil respiration, wildfire, and vegetation trends during the Last Interglacial (LIG) (124.1–118.8 ka) and the Holocene (10–0 ka). Wildfires were more prevalent during the LIG than the Holocene and were supported by fire-prone species, low soil respiration, and a greater difference between summer and winter temperature. We show that vegetation type and summer/winter temperature contrast are strong drivers of Siberian wildfires.

Modelled surface climate response to effusive Icelandic volcanic eruptions: sensitivity to season and size

We use an Earth system model to systematically investigate the climate response to high-latitude effusive volcanic eruptions as a function of eruption season and size, with a focus on the Arctic. We find that different seasons strongly modulate the climate response, with Arctic surface warming observed in winter and cooling in summer. Additionally, as eruptions increase in terms of sulfur dioxide emissions, the climate response becomes increasingly insensitive to variations in emission strength.

Meteorological ingredients of heavy precipitation and subsequent lake-filling episodes in the northwestern Sahara

The Sahara was wetter in the past and may become wetter in the future. Lake remnants are evidence of the desert’s wetter past. If the Sahara gets wetter in the future, these lakes may serve as a water resource. However, it is unclear how these lakes get filled and how moisture is carried into the desert and converted into rain in the first place. Therefore, we examine processes currently leading to the filling of a dry lake in the Sahara, which can help assess future water availability.

Assessing Lagrangian coherence in atmospheric blocking

We identify spatially coherent air streams into atmospheric blockings, which are important weather phenomena. By adapting mathematical methods to the atmosphere, we confirm previous findings. Our work shows that spatially coherent air streams featuring cloud formation correlate with strengthening of the blocking. The developed framework also allows for statements about the spatial behavior of the air parcels as a whole and indicates that blockings reduce the dispersion of the air parcels.

Evaluating F10.7 and F30 radio fluxes as long-term solar proxies of energy deposition in the thermosphere

We study how well the F10.7 and F30 solar radio fluxes have represented solar energy input in the thermosphere in the last 60 years. We found that increased saturation of radio fluxes at recent solar minima leads to an overestimation of solar energy, which changes the relation between thermospheric parameters and F10.7, but this is not an issue for F30 because of a relative increase in F30 with respect to F10.7. This explains why F30 has been found to represent solar energy better than F10.7.

CH-RUN: a deep-learning-based spatially contiguous runoff reconstruction for Switzerland

This study reconstructs daily runoff in Switzerland (1962–2023) using a deep-learning model, providing a spatially contiguous dataset on a medium-sized catchment grid. The model outperforms traditional hydrological methods, revealing shifts in Swiss water resources, including more frequent dry years and declining summer runoff. The reconstruction is publicly available.

RUN: a deep-learning-based spatially contiguous runoff reconstruction for Switzerland">Read more

Sensitivity of tropical orographic precipitation to wind speed with implications for future projections

Rainfall in mountainous regions constitutes an important source of freshwater in the tropics. Yet how it will change with global warming remains an open question. Here, we reveal a strong sensitivity of this rainfall to the speed of prevailing winds. This relationship, validated by theory, simulations, and observational data, suggests that regional wind shifts will significantly influence future rainfall changes in the tropics.

Opinion: Why all emergent constraints are wrong but some are useful – a machine learning perspective

In our article, we review uncertainties in global climate change projections and current methods using Earth observations as constraints, which is crucial for climate risk assessments and for informing society. We then discuss how machine learning can advance the field, discussing recent work that provides potentially stronger and more robust links between observed data and future climate projections. We further discuss the challenges of applying machine learning to climate science.

Brief communication: Sea-level projections, adaptation planning, and actionable science

The Cryosphere
DOI 10.5194/tc-19-793-2025
25 February 2025

As communities try to adapt to climate change, they look for “actionable science” that can inform decision-making. There are risks in relying on novel results that are not yet accepted by the science community. We propose a practical criterion for determining which scientific claims are actionable. We show how premature acceptance of sea-level-rise predictions can lead to confusion and backtracking, and we suggest best practices for communication between scientists and adaptation planners.

Synoptic perspective on the conversion and maintenance of local available potential energy in extratropical cyclones

Although extratropical cyclones in the North Atlantic are among the most impactful midlatitude weather systems, their intensification is not entirely understood. Here, we explore how individual cyclones convert available potential energy (APE) into kinetic energy and relate these conversions to the synoptic development of the cyclones. By combining potential vorticity thinking with a local APE framework, we offer a novel perspective on established concepts in dynamic meteorology.

Toward more robust net primary production projections in the North Atlantic Ocean

Biogeosciences
DOI 10.5194/bg-22-841-2025
20 February 2025

The marine biogeochemistry components of Coupled Model Intercomparison Project phase 6 (CMIP6) models vary widely in their process representations. Using an innovative bioregionalization of the North Atlantic, we reveal that this model diversity largely drives the divergence in net primary production projections under a high-emission scenario. The identification of the most mechanistically realistic models allows for a substantial reduction in projection uncertainty.

Creating a national urban flood dataset for China from news texts (2000–2022) at the county level

We create China’s first open county-level urban flood dataset (2000–2022) using news media data with the help of deep learning. The dataset reflects both natural and societal influences and includes 7595 urban flood events across 2051 counties, covering 46 % of China’s land area. It reveals the predominance of summer floods, an upward trend since 2000, and a decline from southeast to northwest. Notably, some highly developed regions show a decrease, likely due to improved flood management.

What controls planktic foraminiferal calcification?

Biogeosciences
DOI 10.5194/bg-22-791-2025
17 February 2025

Planktic foraminifers are a plankton whose fossilised shell weight is used to reconstruct past environmental conditions such as seawater CO2. However, there is debate about whether other environmental drivers impact shell weight. Here we use a global data compilation and statistics to analyse what controls their weight. We find that the response varies between species and ocean basin, making it important to use regional calibrations and consider which species should be used to reconstruct CO2.

Moving beyond post hoc explainable artificial intelligence: a perspective paper on lessons learned from dynamical climate modeling

We draw from traditional climate modeling practices to make recommendations for machine-learning (ML)-driven climate science. Our intended audience is climate modelers who are relatively new to ML. We show how component-level understanding – obtained when scientists can link model behavior to parts within the overall model – should guide the development and evaluation of ML models. Better understanding yields a stronger basis for trust in the models. We highlight several examples to demonstrate.

Causes of the exceptionally high number of fatalities in the Ahr valley, Germany, during the 2021 flood

Natural Hazards and Earth System Sciences
DOI 10.5194/nhess-25-581-2025
12 February 2025

In July 2021, flooding killed 190 people in Germany, 134 of them in the Ahr valley, making it the deadliest flood in recent German history. The flash flood was extreme in terms of water levels, flow velocities and flood extent, and early warning and evacuation were inadequate. Many died on the ground floor or in the street, with older and impaired individuals especially vulnerable. Clear warnings should urge people to seek safety rather than save belongings, and timely evacuations are essential.