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Desert dust forms nitrate coatings as it travels through the atmosphere. However, current models that predict this process vary greatly due to different methods and inaccuracies. We examined how nitrate forms in a global model, focusing on how gases condense on dust, the lifespan of different particles, and the impact of alkalinity. Our findings show that models work best when they consider reversible gas condensation with alkalinity. This should lead to better estimates of climate impacts.

Through simultaneous measurements of aerosol particles and fog droplets, the evolution of droplets size distribution during the eight observed fog events was investigated. The results showed that the concentration and size distribution of pre-fog aerosol had significant impacts on fog microphysical characteristics. The extinction of fog interstitial particles played an important role in visibility degradation for light fogs, especially in polluted regions.

Our study examines how temperature and humidity representations influence contrail (-cirrus) formation criteria. Using various model setups, we identified biases that lead to overestimation of contrail formation areas. By comparing simulations with in-flight and satellite observations, we confirmed that humidity threshold choices greatly affect contrail predictions. These findings can help develop strategies for climate-optimized flight routes, potentially reducing aviation's climate effect.

We analysed debris flows in Sichuan, China, using satellite data and simulations to assess check dam efficacy. Our study found whilst check dams can mitigate smaller flows, they may increase exposure to extreme events, with up to 40 % of structures in some areas affected. Urban development and reliance on check dams can create a false sense of security, raising exposure during large debris flows and highlights the need for risk management and infrastructure planning in hazard-prone areas.

Sulfuric acid forms particles in the atmosphere, but the airborne sampling faces challenges due to vapor losses in inlet lines. An innovative aircraft sampling system to sample sulfuric acid from the sea surface into the lower stratosphere (0–15 km) is described and characterized. Our results challenge the widely held view that laminar core sampling is the best strategy to sample condensable vapors, and identify better strategies to sample condensable vapors.

In this study, we found that the accumulation of nutrients (e.g., carbon, nitrogen, phosphorus, calcium) in leaves is an important factor in explaining tree growth in forest ecosystems. This result provides evidence for forest growth studies aimed at forest conservation and restoration to better direct their resources to data collection and measurement. Collecting data on nutrient stocks in tree leaves can also provide valuable information to broaden our understanding of forest functioning.

Our study examines glacier movement in the tropical Andes from 2013 to 2022 using satellite data. Despite challenges like small glacier size and frequent cloud cover, we tracked annual speeds and seasonal changes. We found stable annual speeds but significant shifts between wet and dry seasons, likely due to changes in meltwater production and glacier-bedrock conditions. This research enhances understanding of how tropical glaciers react to climate change.

Anthropogenic greenhouse gas emissions significantly impact ocean ecosystems through climate change and acidification, leading to either progressive or abrupt changes. This study maps the crossing of physical and ecological limits for various ocean impact metrics under three emission scenarios. Using Earth system models, we identify when these limits are exceeded, highlighting the urgent need for ambitious climate action to safeguard the world's oceans and ecosystems.

Clouds lie at the heart of uncertainty in both climate sensitivity and radiative forcing, making it imperative to properly diagnose their radiative effects. Here we provide a recommended methodology and code base for the community to use in performing such diagnoses using cloud radiative kernels. We show that properly accounting for changes in obscuration of lower-level clouds by upper-level is important for accurate diagnosis and attribution of cloud feedbacks and adjustments.

As a World Heritage site, the deterioration and scientific conservation of the Temple of Heaven Park in Beijing, China, is a topic of widespread concern. This paper presents the first detailed study of biological weathering of marble relics in the Temple of Heaven Park, using a novel statistical method to quantitatively analyze the biological communities. This research will provide important scientific basis and effective measures for the protection of marble relics.

CLIMCAPS extends the Aqua AIRS+AMSU record with retrievals from CrIS+ATMS on Suomi National Polar-orbiting Partnership (SNPP) and Joint Polar Satellite System series (JPSS-1 to JPSS-4). With “continuous” we mean a data record that is consistent in its characterization of natural variation despite changes in source instrumentation. Here we investigate how sounding continuity can improved across the full CLIMCAPS record (2002 to present day) spanning multiple instruments and satellites.

This study develops a new method to improve the calibration and evaluation of models that predict soil erosion by water. By using advanced imaging techniques, we can capture detailed changes of the soil surface over time. This helps improve models that forecast erosion, especially as climate change creates new and unpredictable conditions. Our findings highlight the need for more precise tools to better model erosion of our land and environment in the future.

Laser desorption of individual particles prior to ionization is the key to reveal their organic composition. The CO₂ lasers required are bulky and maintenance-intensive, limiting their use in the field. We have developed a compact solid-state IR laser that is easily aligned with the particle beam. Mass spectra and hit rates are similar to those of the CO₂ laser. For combined characterization of organic and inorganic particle compositions both lasers are superior to conventional single UV pulses.

We contribute to the knowledge about the differences in lightning flashes of opposite polarity. We found and explained a distinct behaviour of in-cloud processes happening immediately after return strokes of cloud-to-ground lightning flashes, considering a recharging of in-cloud part of bidirectional leader.

Sediment transport in rivers and under glaciers depends on water velocity and channel width. In rivers, water discharge changes affect flow depth, width, and velocity. Under glaciers, pressurized water changes velocity more than shape. Due to these differences, this study shows that sediment transport under glaciers varies widely and peaks before water flow does, creating a complex relationship. Understanding these dynamics helps interpret sediment discharge from glaciers in different climates.

We present SURFER v3.0, a simple climate model designed to estimate the impact of CO₂ and CH₄ emissions on global temperatures, sea levels, and ocean pH. We added new carbon cycle processes and calibrated the model to observations and results from more complex models, enabling use over time scales ranging from decades to millions of years. SURFER v3.0 is fast, transparent, and easy to use, making it an ideal tool for policy assessments and suitable for educational purposes.

To measure Arctic ice thickness, we often check how much ice sticks out of the water. This method depends on knowing the ice's density, which drops significantly in summer. Our study, validated with sonar and laser data, shows that these seasonal changes in density can complicate melt measurements. We stress the importance of considering these density changes for more accurate ice thickness readings.

The accuracy of the chemical transport model, a key focus of our research, is strongly dependent on the dry deposition parameterization. Our finding shows that the refined CMAQ dust model correlated well with the ground and high altitude in-situ measurements by implementing the suggested dry deposition schemes. Furthermore, we reveal the mixing state of two types of aerosols at the upper level, a finding supported by both the optimized model and measurement.

Mid-latitude wind in upper stratosphere is indispensable in establishing quasi-biennial oscillation (QBO)-vortex coupling in Southern hemisphere. During the Westerly QBO, positive zonal wind anomalies at 20° S−40° S in upper stratosphere in July, named as positive extratropical mode, lead to a stronger polar vortex in November, with a correlation reaching 0.75. This suggests that Antarctic stratospheric polar vortex and ozone concentration in spring can be predicted up to five months in advance.

At treeline, plant species change abruptly from low stature plants in tundra to trees in forests. Our study documents that from tundra towards forest, the litter layer gets strongly enriched in nutrients. We show that these litter quality changes alter nutrient processing by soil microbes and increase the nutrient release during decomposition in forest than in tundra. The associated improvement of nutrient availability in the forest potentially stimulates tree growth and treeline shifts.

The Earth’s magnetic field is not closed at high latitudes. Electrically charged particles can penetrate the Earth’s atmosphere, deposit their energy, and heat the local atmosphere-ionosphere. This presumably causes an upwelling of the neutral atmosphere which affects the atmosphere-ionosphere coupling. We apply a new analysis technique to infer the atmospheric density from incoherent scatter radar measurements. We show qualitatively how particle precipitation affects the neutral atmosphere.

Ocean alkalinity enhancement (OAE) is a promising strategy for ocean-based carbon dioxide removal, as it attempts to accelerate a natural process operating on Earth and may have climatically significant scalability. However, our best strategy for assessing OAE effects involves running computationally expensive climate models. We develop a powerful statistical technique that is able to encapsulate the climatic response to OAE interventions, thus simplifying the OAE carbon accounting problem.

The current research and application of the Copula function is mainly limited to two-dimensional; with the advancement of computer technology and the complexity of the research problems, the application of three-dimensional and above Copula function and the accompanying problems of parameter estimation and the choice of the function type need to be further researched. Therefore, the Copula function has great potential in the risk assessment of natural disasters caused by multiple factors.

Snowfall measurements at high latitudes are crucial for estimating ice sheet mass balance. Spaceborne radar and radiometer missions help estimate snowfall but face uncertainties. This work evaluates uncertainties in snowfall estimates from a fixed near-nadir radar (CloudSat-like) and a conically scanning radar (WIVERN-like), determining that WIVERN will provide much better estimates than CloudSat, and at much smaller spatial and temporal scales.

In water-scarce regions, precipitation is a highly variable and essential resource for crop production. Developing countries like India have an uneven distribution of rain gauges, so reliance on satellite and reanalysis-based precipitation products is critical for their prudent management. Hence, the study statistically evaluated different precipitation products against the station data for water-scarce regions in Tamil Nadu and found that ERA5-Land performed the best, followed by MSWEP.

Machine learning has the potential to aid the identification organic molecules involved in aerosol formation. Yet, progress is stalled by a lack of curated atmospheric molecular datasets. Here, we compared atmospheric compounds with large molecular datasets used in machine learning and found minimal overlap with similarity algorithms. Our result underlines the need for collaborative efforts to curate atmospheric molecular data to facilitate machine learning model in atmospheric sciences.

In recent years, the western Baltic Sea has experienced severe storm surges. By analysing the individual contributions and the total water level, these events can be put into a climate perspective. It was found that individual contributions were not exceptional in all events and no clear trend can be identified, often the combination of the individual contributions leads to the extreme events of recent years. This points to the importance of analysing composite events.

Key controlling factors of cirrus clouds were individually quantified using machine learning models, based on global-scale in-situ observations compiled from 12 flight campaigns at 67° S – 87° N. Relative humidity shows much larger effects on cirrus occurrences than vertical velocity. Aerosol indirect effects are seen from both large and small aerosols, which affect predictions of cirrus occurrences. Large aerosols significantly improve predictions of ice water content but not small aerosols.

This study presents a comprehensive analysis of radiative properties and effects of cirrus clouds based on 4 years of continuous ground-based lidar measurements with the Barcelona (Spain) Micro Pulse Lidar. A novel approach of a self-consistent scattering model for cirrus clouds is presented to determine their radiative properties at different wavelengths and the radiative effects of the cirrus clouds are calculated with the Discrete Ordinates Method (DISORT) embedded in the ARTDECO package.

Box modeling with the master chemical mechanism (MCM) was used to address the puzzle of summertime PAN formation and its association with aerosol pollution under high ozone conditions. The MCM model proves to be an ideal tool for investigating PAN photochemical formation (IOA=0.75). The model performed better during the clean period than during the haze period. Through the machine learning method of XGBoost, we found that the top three factors leading to simulation bias were NH₃, NO₃, and PM_2.5.

We studied the transport and chemical decomposition of volcanic SO₂, focusing on the 2019 Raikoke event. By comparing two different chemistry modeling schemes, we found that including complex chemical reactions leads to a more accurate prediction of how long SO₂ stays in the atmosphere. This research helps improve our understanding of volcanic pollution and its impact on air quality and climate, providing better tools for scientists to track and predict the movement of these pollutants.

This study explores the formation of NH₄NO₃, a key component of atmospheric aerosols, by simulating photochemical reactions in a controlled chamber. Laser absorption spectroscopy explores how UV-C light intensity, O₃ concentration, and humidity affect the conversion of NO and NH₃ into aerosols. The findings show that increased UV-C intensity, O₃, and humidity significantly enhance aerosol formation, offering insights into air pollution control and atmospheric chemistry.

Methane (CH₄) is a potent greenhouse gas. Northern China contributes a large proportion of CH₄ emissions yet large observation gaps are existed. Here we compiled a comprehensive dataset which is publicly available including ground-based, satellite-based, inventory and modeling results, to show the CH₄ concentrations, enhancements and spatial-temporal variations. The data can benefit the research community, and policy makers for future observations, atmospheric inversions and policy-making.

Ice crystal orientation influence how glacier ice deforms. Radar polarimetry is commonly used to study the bulk ice crystal orientation, but the often used coherence method only provides information of the shallow ice in fast-flowing areas. This study shows that reducing the bandwidth of high-bandwidth radar data significantly enhances the depth limit of the coherence method. This improvement helps us to better understand ice dynamics in fast-flowing ice streams.

The speed at which Antarctic ice flows is dependent on its viscosity and the sliperiness of the ice/bedrock interface. Often, these unknown variables are inferred from observations of ice speed. This article presents an attempt to make this difficult procedure easier by making use of additional information in the form of observations of crevasses, which make ice appear less viscous to numerical models. We find in some circumstances that this leads to more appealing solutions to this problem.

Glacier retreat poses big challenges, making understanding how climate affects glaciers vital. But glacier measurements worldwide are limited. We created a simple machine-learning model called miniML-MB, which estimates annual changes in glacier mass in the Swiss Alps. As input, miniML-MB uses two climate variables: average temperature (May–Aug.) and total precipitation (Oct.–Febr.). Our model can accurately predict glacier mass from 1961–2021 but struggles for extreme years (2022 and 2023).

This study use the WRF-Chem model to assess how meteorological conditions and unexpected emission reductions affected PM_2.5 in the North China Plain (NCP). It highlights regional disparities: in the Northern NCP, adverse weather negated emission reduction effects. In contrast, the Southern NCP with PM_2.5 decrease due to favorable weather and emission reductions. The research highlighted the interaction between emissions, meteorology and air quality.

This study introduces a new method to reduce uncertainty in climate model projections of future precipitation patterns over land. By using advanced causal discovery techniques, our approach improves the reliability of precipitation projections under different global warming scenarios, supporting the development of more effective strategies to address the impacts of climate change.

This study explores how anisotropic scattering and birefringence affect radar signals in ice sheets. Analyzing data from Northeast Greenland, we found anisotropic scattering, caused by small changes in ice crystals, dominates the azimuthal power response. We observe a strong link between scattering strength, orientation, and ice-sheet stratigraphy. Anisotropic scattering can thus be used to determine ice crystal orientation and distinguish ice units from different climatic periods.

High ozone (O₃) formed by reactions of nitrogen oxides (NO_x) and volatile organic compounds (VOCs) can harm human health and welfare. High O₃ is usually associated with hot summer days, but under certain conditions, high O₃ can also form under winter conditions. In this study, we describe a high O₃ event that occurred in Colorado during the COVID-19 quarantine that was caused in part by the decrease in traffic, and in part by a shallow inversion created by descent of stratospheric air.

A channel may be aggraded by overloaded sediment. In this study we realize an aggradation experiment and determine the celerity at which an aggradation wave, due to sediment overloading, migrates. We also investigate the celerity of small perturbations, as quantified based on mathematical formulations. The celerities of the two kinds are correlated with each other. However, the celerity of small perturbations is larger than the other one, that is less than a few percent of the water velocity.

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 special focus on the Arctic. We find that different seasons strongly modulate the climate response with Arctic surface warming in winter and cooling in summer. Also, as eruptions become larger in terms of sulfur dioxide emissions, the climate response becomes increasingly insensitive to variations in the emission strength.

Plants affect the Amazon's water cycle through processes such as transpiration and evaporation. Characteristics related to leaf size and biomass have the most significant impact on atmospheric water content and land surface temperature, but they affect soil moisture content only minimally. These relationships also vary at extreme water cycle values and across Amazon subbasins. The study underscores the critical role of plants in maintaining the resilience of the Amazon’s hydrological processes.

Nitrogen dioxide is an air pollutant largely controlled by human activity that affects ozone, methane and aerosols. Satellite instruments can quantify column NO₂, and by carefully matching the time and location of measurements, enable evaluation of model simulations. NO₂ over SE Asia is assessed, showing that the model captures many features of the measurements, but also important differences that suggest model deficiencies in representing several aspects of the atmospheric chemistry of NO₂.

Turbidity is a key factor for water quality monitoring. We tested an image-based procedure in a full-scale river monitoring experiment using digital cameras. This procedure can increase our knowledge of the real status of water bodies, solving the spatial and temporal data resolution problems of the existing techniques, promoting also the development of early warning networks, moving water research forward thanks to a large increase of information and the reduction of operating expenses.

Our study maps global nitrogen (N) and phosphorus (P) availability and how they’ve changed from 1901 to 2018. We found that tropical regions are mostly P-limited, while temperate and boreal areas face N limitations. Over time, P limitation has increased, especially in the tropics, while N limitation has decreased. These shifts are key to understanding global plant growth and carbon storage, highlighting the importance of including P dynamics in ecosystem models.

This study applied the CoupModel to simulate carbon dynamics and ecohydrology for a restored peatland and evaluated the responses of the simulated carbon fluxes to varying acrotelm thickness and climate. The results show that CoupModel can simulate the coupled carbon and ecohydrology dynamics for the restored peatland system, and the restored peatland has less resilience in its C uptake functions than pristine peatlands under a changing climate.