The study, published in Communications Earth & Environment, examined how extensive offshore wind development could influence the atmosphere over the Northwest European shelf. The researchers used COSMO-CLM, a high-resolution regional climate model designed to simulate atmospheric processes at a scale suitable for investigating regional weather and climate effects. Rather than focusing on individual storms or isolated weather events, the team analyzed simulations covering the decade from 2008 to 2017. This long period allowed them to calculate average atmospheric behavior across many different weather conditions and reduce the influence of unusual individual years.

The model experiments included existing offshore wind farms as well as areas identified for possible future development in the North Sea and Baltic Sea. The researchers selected a deliberately extreme scenario in which every designated development area was assumed to be used at maximum technical capacity. The resulting installed capacity would substantially exceed the European Union’s currently discussed target of 300 gigawatts of offshore wind power by 2050. Such a build-out is not presented as a precise forecast of Europe’s energy system. Instead, it functions as a stress test, designed to reveal the largest potential atmospheric effects and show how those effects might change as wind farms become larger, denser, and more spatially connected.

Wind turbines affect the atmosphere because they remove some of the kinetic energy contained in moving air. As air passes through a turbine array, wind speeds are reduced and turbulence increases. The rotating blades and the physical structure of the turbines disturb the lower atmosphere, enhancing vertical mixing between air layers that would otherwise remain more separated. This interaction can influence the transfer of momentum, heat, and moisture across the atmospheric boundary layer—the lowest part of the atmosphere, which is directly affected by the Earth’s surface and plays a central role in the formation of clouds and near-surface weather.

According to the simulations, the enhanced turbulence behind large offshore wind farms can promote upward transport of moist air. As that air rises, it expands and cools. Cooler air can hold less water vapor, so some of the moisture condenses into tiny droplets or ice particles, supporting cloud formation and, under suitable conditions, precipitation. The model therefore showed a tendency toward increased rainfall over or near the offshore wind-farm areas. The effect is not caused by turbines creating new moisture; rather, the installations alter how existing moisture is transported and where it is released from the atmosphere.

The atmospheric changes become particularly important as air masses move toward the European coastline. Under the extreme expansion scenario, a larger share of the available moisture could fall as rain over the sea before the air reaches land. By the time these air masses arrive at coastal regions, they may contain less water vapor capable of producing precipitation. The simulated result was a reduction in rainfall along sections of the coasts of Denmark, Germany, the Netherlands, and the United Kingdom, with local decreases reaching approximately 15 percent. The size of the effect varies across the region because it depends on prevailing wind direction, atmospheric stability, moisture availability, turbine density, and the arrangement of individual wind farms.

The researchers emphasize that the findings describe changes in long-term weather statistics rather than a simple rule that every wind farm will cause a fixed decline in rainfall onshore. Atmospheric circulation over the North Sea and Baltic Sea is highly variable, and the influence of turbines can change with the season and with the structure of incoming weather systems. The study’s modeled values also represent an intentionally oversized technical scenario, not the expected impact of current projects alone. Actual effects would depend on which sites are developed, how many turbines are installed, their individual dimensions, the spacing between them, and the combined layout of multiple wind-farm clusters.

That distinction is important as European nations expand offshore renewable energy while attempting to balance climate goals with environmental protection, maritime transport, fisheries, coastal planning, and water management. Even modest changes in average precipitation could become relevant in areas already facing competing demands for freshwater or experiencing shifting rainfall patterns because of climate change. At the same time, the study does not suggest that offshore wind power should be abandoned. Instead, it highlights the need to consider atmospheric interactions alongside electricity generation, marine habitats, seabird movements, shipping routes, and the wider consequences of large-scale infrastructure.

Previous work by Hereon researchers has indicated that the dimensions and design of wind farms can strongly influence their atmospheric footprint. Turbine height, rotor size, spacing, density, and the overall geographic arrangement of installations can determine how efficiently momentum and moisture are mixed through the lower atmosphere. A group of small, widely separated wind farms may produce a different regional response from a nearly continuous corridor of dense turbine arrays. Understanding these differences could allow future planners to reduce undesirable effects while preserving the climate benefits of replacing fossil-fuel power generation with renewable electricity.

The researchers now plan to investigate a broader range of development pathways rather than relying on a single extreme case. Future simulations will examine how precipitation responds to different turbine densities, wind-farm sizes, and spatial distributions, as well as how offshore installations affect the ocean and marine ecosystems. Such work could help governments coordinate development across national borders, since atmospheric effects do not stop at maritime boundaries. The study’s central message is that the climate consequences of renewable infrastructure are not limited to carbon emissions: when energy systems become large enough, they can also interact with the physical processes that govern clouds, rainfall, and regional weather.

Subject of Research: Computational simulation/modeling

Article Title: Projected impacts of future offshore wind farms on coastal precipitation over the Northwest European shelf

News Publication Date: 12-Aug-2026

Web References: https://doi.org/10.1038/s43247-026-03852-x

References: Communications Earth & Environment, DOI: 10.1038/s43247-026-03852-x

Image Credits: Hereon/Sabine Billerbeck

Keywords: Offshore wind farms, atmospheric science, precipitation, regional climate modeling, North Sea, Baltic Sea, coastal climate, atmospheric turbulence, renewable energy, climate impacts

Mega-cities, defined by their population size exceeding ten million inhabitants, represent some of the most complex and rapidly evolving urban areas on the planet. Their sheer scale alone gives rise to unique climate phenomena, chief among them the urban heat island (UHI) effect—a localized warming that occurs due to the replacement of natural land surfaces with heat-retaining materials like concrete and asphalt. This study’s central ambition was to intricately map how the UHI effect manifests in such mega-cities on a global scale, leveraging the advanced modeling techniques of CORDEX-CORE.

Regional climate models hold significant promise in simulating environmental responses at scales finer than global models typically achieve. CORDEX-CORE, as a coordinated regional climate downscaling experiment, offers high-resolution climate scenarios that can resolve urban-scale phenomena better than many predecessors. The team applied these sophisticated tools to simulate temperature differentials between urban cores and their surrounding rural landscapes, thereby quantifying the intensity and spatial spread of UHIs across a diverse array of world cities.

One of the most striking findings from the simulations is that urban heat islands are becoming not only more pronounced but also more heterogeneous across global mega-cities. Various factors such as urban geometry, local meteorological conditions, land use patterns, and anthropogenic heat emissions interact in complex ways, resulting in spatial gradients of heat accumulation. For instance, towering skyscrapers can trap heat in dense canyons, while green spaces interrupt this pattern, creating cooler microclimates within the urban fabric.

The study meticulously characterized these dynamics by validating model outputs against observed data from weather stations, satellite remote sensing, and in situ measurements specifically within key metropolitan centers. This rigorous approach provides robust confidence in the model’s capacity to faithfully represent UHI phenomena and offers a critical tool for policymakers aiming to mitigate urban warming through targeted interventions such as urban greening, reflective building materials, and optimized city planning.

Beyond quantifying present-day heat island patterns, the study projects how ongoing urban expansion combined with climate change will likely exacerbate temperature extremes in mega-cities by mid-century. Projections indicate that without intervention, some urban areas might experience heat differentials up to 5°C higher than their rural surroundings during peak summer months. These escalating temperatures pose alarming risks to public health, energy consumption, and overall urban livability, particularly for vulnerable populations.

The multi-disciplinary team also explored how regional atmospheric circulation patterns modulate UHI intensity. For example, coastal mega-cities may benefit from maritime breezes that reduce heat buildup, while inland urban areas often suffer from stagnant airflow conditions amplifying thermal stress. Such nuanced insights are essential for tailoring climate adaptation strategies to local context, anchoring them in both scientific evidence and socio-environmental realities.

In synthesizing these findings, the research underscores the critical role of integrating high-resolution urban climate modeling into broader climate adaptation and mitigation frameworks. Mega-cities, which currently house over half the world’s population, are both hotspots of vulnerability and innovation. Understanding and anticipating their climatic shifts through models like CORDEX-CORE paves the way for smarter urban designs that balance development with environmental stewardship.

The study also propels future research directions, emphasizing the urgent need to refine regional models to capture transient phenomena such as heat waves and nocturnal cooling patterns with greater precision. Coupling climate simulations with human behavior and infrastructure resilience models could further enhance preparedness strategies, potentially saving lives as urban heat risks intensify globally.

Several limitations inherent in the current CORDEX-CORE model configurations were acknowledged, particularly relating to the representation of complex urban microphysics and socioeconomic variables influencing heat production. Moving forward, incorporating finer-scale data and deploying emerging technologies like machine learning for parameter optimization may unlock unprecedented modeling fidelity.

Importantly, the research calls attention to the equity challenges embedded in urban heat dynamics. Lower-income neighborhoods often bear the brunt of intensified UHIs due to fewer green spaces and higher building density, exacerbating social inequalities under climate stress. Climate justice emerges as a critical lens through which urban heat mitigation plans must be developed, ensuring inclusive resilience pathways.

The interdisciplinary collaboration behind this research – blending climatology, urban planning, atmospheric science, and social analysis – highlights a robust model for addressing one of the 21st century’s most pressing environmental challenges. It reinforces the axiom that comprehending and tackling climate risks demands holistic, multi-scalar perspectives that bridge science and policy seamlessly.

In conclusion, this pioneering study published in npj Urban Sustainability significantly advances our understanding of urban heat islands on a global scale, elucidating their underlying drivers and future trajectories amidst accelerating urbanization and climate variability. Its rich technical insights offer a beacon for urban planners, climate scientists, and policymakers striving to create cooler, healthier cities in an era of intense environmental change.

The authors’ deployment of CORDEX-CORE regional climate simulations signifies an important leap toward operationalizing climate model outputs for urban sustainability applications, demonstrating that precision modeling at local scales is within reach. This capability is pivotal for embedding climate risk assessments into the urban developmental agenda, guiding transformative actions with data-driven clarity.

As global mega-cities continue to expand and the climate crisis intensifies, studies like this one provide not only urgent warning signals but also the vital knowledge base to navigate the path forward. The intersection of advanced climate science and urban resilience planning is poised to define the sustainability narratives of our time—and this research decisively contributes to that endeavor.

Subject of Research: Representation of global mega-cities and their urban heat island effect in regional climate model simulations.

Article Title: Representation of global mega-cities and their urban heat island in CORDEX-CORE regional climate model simulations.

Article References:
Langendijk, G.S., Fernandez, J., Demuzere, M. et al. Representation of global mega-cities and their urban heat island in CORDEX-CORE regional climate model simulations. npj Urban Sustain (2025). https://doi.org/10.1038/s42949-025-00325-6

Image Credits: AI Generated

Traditional climate models, typically operating at spatial resolutions around 100 kilometers, have confronted inherent limitations in accurately representing the complex mesoscale processes that drive extreme rainfall. These coarse models tend to oversimplify or entirely miss key convective systems that organize precipitation at scales of tens of kilometers, leading to underestimated intensity and frequency in their simulations. The new study addresses this fundamental gap by employing an ensemble of simulations with markedly refined grid resolutions—in the range of 10 to 25 kilometers—integrating sophisticated schemes that better replicate the behavior of mesoscale convective systems (MCS). This approach bridges the divide between global atmospheric circulation and localized convective dynamics, thereby capturing the detailed spatial and temporal characteristics of extreme precipitation.

One of the salient outcomes of the high-resolution modeling is its ability to more faithfully replicate the observed patterns and intensities of daily extreme precipitation events over land during the historical period. When benchmarked against observational data, the improved simulations reveal a substantially enhanced representation of precipitation hotspots and regional variability, aspects traditionally obscured in lower-resolution counterparts. This fidelity is crucial not only for understanding current climate behaviors but also for predicting how extremes might shift under various greenhouse gas concentration trajectories.

Under a high emissions scenario simulating continued rise in atmospheric carbon dioxide, the analyses project a sobering increase of approximately 41% in the magnitude of daily extreme precipitation over land by the year 2100. This amplification is largely attributed to intensified mesoscale moisture convergence. Moisture convergence, the atmospheric process whereby moist air masses are drawn together and forced upward, is fundamental to convective precipitation formation. As warming progresses, the atmosphere’s capacity to hold water vapor increases in accordance with the Clausius-Clapeyron relationship, yet the dynamical aspects—namely the convergence and uplift of this moisture—have often been underrepresented in earlier modelling studies.

Importantly, the study quantifies how the contribution of these dynamical processes to extreme precipitation is underestimated by about a factor of three in conventional low-resolution models. This underrepresentation reveals a critical blind spot in many climate impact assessments to date, suggesting that previous predictions may have substantially downplayed the risks posed by supercharged precipitation extremes in a warming world. The enhanced resolution allows for capturing interaction scales that blend large-scale climatic influences with local convective phenomena, an essential step for producing actionable forecasts.

Moreover, these findings illuminate a complex interplay between thermodynamic and dynamic factors driving precipitation extremes. While thermodynamics dictate the sheer availability of moisture in the atmosphere, it is the dynamic mechanisms like mesoscale convergence that organize and amplify precipitation events, effectively modulating their intensity and spatial extent. The improved climate models demonstrate that future extreme rainfall intensification will not merely be a passive consequence of a moister atmosphere but also a dynamically active process reshaping precipitation patterns.

This research carries profound implications for climate risk management and adaptation strategies worldwide. Infrastructure, urban planning, flood defenses, and agricultural systems have all historically relied upon historical rainfall statistics and model projections that may now appear overly optimistic or incomplete. Recognizing the heightened risks associated with extreme precipitation events driven by dynamic moisture convergence compels a reevaluation of design standards and disaster preparedness policies, particularly in vulnerable regions prone to flash flooding and landslides.

Furthermore, the enhanced modelling capability sets a new benchmark for climate science, highlighting the importance of spatial resolution in simulating the atmospheric processes underpinning extreme weather. It challenges the research community to reexamine other climate phenomena that may be similarly sensitive to mesoscale dynamics and calls for increased computational investment to scale such high-fidelity simulations globally. The ensemble-based approach also underscores the importance of probabilistic assessments, offering more robust estimations that capture uncertainty and variability inherent in climate projections.

Additionally, the study provides a valuable template for integrating observational data with modeling efforts to refine parameterizations and reduce bias. This iterative process between empirical observations and simulation advances ensures that climate projections become progressively more trustworthy, bolstering their utility for policymakers, emergency responders, and communities at large.

Crucially, the authors advocate that their results should serve as a clarion call to the climate modeling community and stakeholders alike: without embracing higher-resolution simulations that explicitly resolve mesoscale convective processes and moisture dynamics, projections of future precipitation extremes will remain fundamentally constrained. The upcoming decades, marked by increasing greenhouse gas emissions in many regions, will thus witness weather extremes that exceed many current expectations if planning and mitigation measures do not evolve accordingly.

In summary, the study by Chang, Fu, Liu, and colleagues represents a significant leap forward in understanding and forecasting future precipitation extremes in a warming climate. By illuminating the underestimated role of intensified mesoscale moisture convergence and harnessing high-resolution climate modeling, the research ushers in a new era of climate projections that are more nuanced, accurate, and actionable. As extreme precipitation events become more frequent and intense, harnessing such advanced modeling tools is indispensable for equipping societies to anticipate and adapt to the mounting challenges climate change imposes on water resources, ecosystems, and human safety.

Subject of Research: Future projections of extreme precipitation events driven by mesoscale atmospheric dynamics and moisture convergence under climate change scenarios.

Article Title: Future extreme precipitation amplified by intensified mesoscale moisture convergence.

Article References:
Chang, P., Fu, D., Liu, X. et al. Future extreme precipitation amplified by intensified mesoscale moisture convergence. Nat. Geosci. (2025). https://doi.org/10.1038/s41561-025-01859-1

Image Credits: AI Generated

DOI: https://doi.org/10.1038/s41561-025-01859-1

Recent advances in high-resolution climate modeling have begun to peel back the layers of this complex ocean-atmosphere interplay. Yet, until now, the precise reason that finer model resolutions improve AMO simulations remained elusive. An international team of researchers, spearheaded by Xiaojie Hao of the Alfred Wegener Institute Helmholtz Center for Polar and Marine Research, has published groundbreaking findings revealing the key role of oceanic and atmospheric resolution in replicating the AMO’s true character.

This landmark study, published in Ocean-Land-Atmosphere Research on March 21, 2025, leverages the sophisticated Alfred Wegener Institute Climate Model (AWI-CM) to conduct a series of meticulously designed numerical experiments. By varying the spatial resolution of the ocean and atmosphere in four different configurations—low-resolution atmosphere with low-resolution ocean, high-resolution atmosphere with low-resolution ocean, low-resolution atmosphere with high-resolution ocean, and high-resolution atmosphere with high-resolution ocean—the team dissected how resolution influences the fidelity of simulated AMO cycles.

Intriguingly, their results demonstrate that increasing the resolution of ocean models is paramount to capturing the true temporal scale of AMO variability. Models utilizing low-resolution ocean grids produced spurious oscillations with repeat times of merely 10 to 20 years, inconsistent with observations. Contrastingly, high-resolution ocean simulations faithfully generated the classical 40 to 80-year periodicity intrinsic to the AMO, underscoring the ocean’s dynamical processes that only emerge when fine-scale currents and eddies are adequately resolved.

Beyond ocean resolution, enhancing atmospheric resolution contributed notably by refining the amplitude of the AMO in the simulations, aligning modeled temperature swings more closely with real-world measurements. This atmospheric detail improves the representation of transient weather phenomena that modulate oceanic conditions, such as blocking high-pressure systems and regional wind patterns, which in turn influence sea surface temperatures and ocean circulation.

The study’s true conceptual breakthrough lies in elucidating the feedback mechanisms linking the AMO to Fram Strait sea ice export (FSSIE) and atmospheric blocking over Greenland. Fram Strait is the gateway through which Arctic sea ice is transported from the polar region into the North Atlantic, impacting salinity gradients and ocean circulation—a critical driver of the Atlantic Meridional Overturning Circulation (AMOC). This circulation substantially modulates heat transport in the Atlantic, thereby influencing the AMO’s development and persistence.

By deploying the high-resolution ocean model, the researchers uncovered a positive feedback loop whereby the AMO phase regulates atmospheric blocking events over Greenland. During the warm AMO+ phase, reduced meridional temperature gradients encourage persistent atmospheric blocking, manifesting as high-pressure systems that suppress south-to-north winds. This inhibits Fram Strait sea ice export, maintaining high salinity in the Labrador Sea which supports a robust AMOC and prolongs the warm AMO phase. Conversely, in the cool AMO– phase, diminished blocking allows stronger winds to enhance sea ice export, lowering Labrador Sea salinity and weakening the AMOC, thus extending the cool phase.

This intricate dance between oceanic salinity, sea ice dynamics, and atmospheric circulation emerges as a pivotal mechanism through which the AMO sustains its multidecadal rhythm. Crucially, only models with sufficiently fine oceanic and atmospheric grids can replicate these interdependent phenomena, highlighting the indispensable role of multi-scale resolution in climate modeling.

Moreover, the enhanced atmospheric resolution accentuates processes such as transient weather events and detailed sea ice-atmosphere interactions. These refinements enable a more realistic simulation of how short-term atmospheric dynamics feed back into long-term ocean variability—bridging a gap between weather and climate scales that has historically challenged modelers.

The implications of these findings are profound for the future of climate prediction and risk assessment. Understanding and accurately simulating the AMO’s phases improves projections of extreme weather events, regional climate anomalies, and marine ecosystem shifts. It equips society with better-informed tools to anticipate and adapt to climate variability and change, particularly in vulnerable coastal communities and fisheries.

Looking ahead, Xiaojie Hao stresses the need for further investigations utilizing ultra-high-resolution models to unravel the full spectrum of physical mechanisms underlying low-frequency climate oscillations like the AMO. Such endeavors will refine our grasp of ocean-atmosphere interactions and the feedback loops shaping Earth’s climate system over decades and centuries.

Contributing to this study were distinguished collaborators including Dimitry V. Sein, Tobias Spiegl, Lu Niu, and Gerrit Lohmann from the Alfred Wegener Institute, alongside Xianyao Chen of the Ocean University of China and affiliated institutions in Russia and Germany. Their multidisciplinary expertise spanning physical oceanography, atmospheric sciences, and computational climate modeling underscores the collaborative nature required for breakthroughs in Earth system science.

This research was supported by several key funding bodies, including the Natural Science Foundation of China, the Germany-Sino Joint Project, the Fundamental Research Funds for the Central Universities, the MHESRF Scientific Task, and the Moscow Institute of Physics and Technology Development Program, reflecting the international commitment to resolving climate complexities.

Ultimately, this work marks a significant step forward in climate science by explicitly demonstrating that the resolution of oceanic and atmospheric components in numerical models is not merely a technical choice but a fundamental prerequisite for capturing the CANONICAL behavior of the Atlantic Multidecadal Oscillation. It opens a promising pathway toward more reliable climate forecasts and enhanced resilience to the profound environmental changes reshaping our planet.

Subject of Research: Not applicable

Article Title: Modeling the Atlantic Multidecadal Oscillation: The High-Resolution Ocean Brings the Timescale; the Atmosphere, the Amplitude

News Publication Date: 21-Mar-2025

Web References:

• Ocean-Land-Atmosphere Research article
• Alfred Wegener Institute Climate Model

Image Credits: Figure from Modeling the Atlantic Multidecadal Oscillation: The High-Resolution Ocean Brings the Timescale; the Atmosphere, the Amplitude, created by Xiaojie Hao.

Keywords: Weather simulations, Climate modeling, Basic research, Discovery research, Earth systems science