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Ambient ion chemical composition measurements provide insight into trace gases that are precursors for the formation and growth of new aerosol particles. We use a new data analysis approach to increase the chemical information from these measurements. We analyze results from an agricultural region – an understudied land use type that is ~41 % of global land use – and find that the composition of gases important for aerosol formation and growth differ significantly from those in other ecosystems.

We collated the Open Tension-disk Infiltrometer Meta-database (OTIM). We analyzed topsoil hydraulic conductivities at supply tensions between 0 to 100 mm of 466 data entries. We found indications of different flow mechanisms at saturation than at tensions > 20 mm. Climate factors were better correlated to near-saturated hydraulic conductivities than soil properties. Land use, tillage system, soil compaction and experimenter bias significantly influenced K to a similar degree as soil properties.

A framework was developed to automatically detect plumes and compute estimate emissions from cross-sectional flux method (CFM) for biomass burning events in TROPOMI CO datasets using VIIRS Active fire data. The emissions were more reliable when changing plume height in downwind direction was used compared to constant injection height. The CFM was found to have large uncertainty even when the meteorological conditions were accurate. Thus highlighting a need for better inversion models for fires.

Accurate fog forecast is difficult in a complex environment. Spatial variations in soil moisture could have impact on fog. Here we carried out fog simulations with spatially different soil moisture in complex topography. The soil moisture was calculated using satellite observations. The results show that the spatial variations in soil moisture do not have significant impact on where fog occurred, but do impact how long fog lasted. This finding could improve fog forecast in the future.

Antarctic sea ice thickness is an important quantity in the earth system. Due to the thick and complex snow cover on Antarctic sea ice, estimating the thickness of the ice pack is difficult using traditional methods in radar altimetry. In this work, we use a waveform model to estimate the freeboard and snow depth of Antarctic sea ice from CryoSat-2, and use these values to calculate sea ice thickness and volume between 2010 and 2021 and showcase how the sea ice pack has changed over this time.

A geostationary satellite can now provide hourly NO₂ columns and obtaining the NO₂ columns from space relies on NO₂ vertical distribution from the chemical transport model (CTM). In this work, we update the CTM to better represent the chemistry environment so that the CTM can accurately provide NO₂ vertical distribution. Then we find that the changes in NO₂ vertical distribution and the length of the light path over the course of the day play important roles in the NO₂ column’s hourly variation.

The Hunga Tonga-Hunga Ha‘apai volcanic eruption was one of the most vigorous volcanic explosions in the last centuries. The eruption launched many atmospheric waves traveling around the Earth. In this study, we identify these volcanic waves at the edge of space in the mesosphere/lower thermosphere leveraging wind observations conducted with multi-static meteor radars in Northern Europe and with the Chilean Observation Network De Meteor Radars (CONDOR).

Snow-layer segmentation and classification is an essential diagnostic task for cryospheric applications. A SnowMicroPen (SMP) can be used to that end, however, the manual classification of its profiles becomes infeasible for large datasets. Here, we evaluate how well machine learning models can automate this task. Of the 14 different models trained on the MOSAiC SMP dataset, the long short-term memory performed the best. The findings presented here facilitate and accelerate SMP data analysis.

We introduce a framework for regional scale evaluation of simulated precipitation distributions with 62 climate reference regions and 10 metrics, and we apply it to evaluate CMIP5 and CMIP6 models against multiple satellite-based precipitation products. The common model biases identified in this study are mainly associated with the overestimated light precipitation and underestimated heavy precipitation. These biases persist from earlier generation models and have been little improved in CMIP6.

Basic understandings of ozone processes, especially transport and chemistry, are essential to reduce ozone pollution, but studies often have different views on their relative importance. To explore the causes, we developed a tool based on the WRF-CMAQ modelling results to quantify their contributions in the ozone mass and concentration budgets, and found that the difference between two budgets well explains these distinct views. Future studies should be careful with budget-type selections.

In this study, we analyse and compare the results of four different approaches in modelling bora-driven dense water dynamics in the Adriatic Sea. The study investigated the requirements for appropriate modelling of the ocean circulation in the Adriatic and found that the evaluation run of the Adriatic climate model is able to outperform most aspects of the reanalysis product, the short-term hindcast and the data assimilated simulation, in reproducing the dense water dynamics in the Adriatic Sea.

For the rainfall-runoff simulation from a certain area hydrological models are used, which require precipitation and temperature data as input. Since these are often not available as observations, we tested simulation results from atmospheric models. Two products were tested (ERA5-Land & COSMO-REA6) for Slovenian catchments, both lead to good simulations results. Their usage enables the of rainfall-runoff simulation in unobserved catchments as a requisite for e.g. flood protection measures.

This paper describes and evaluates a new modelling methodology to quantify the impacts of climate change on water, biomes and the carbon cycle. We have created a new configuration and setup for the JULES-ES land surface model, driven by bias-corrected historical and future climate model output provided by the Inter-Sectoral Impacts Model Inter-comparison Project (ISIMIP). This allows us to compare projections of the impacts of climate change across multiple impacts models and multiple sectors.

El Niño Southern Oscillation (ENSO) is a climatic phenomenon that causes abnormal climatic conditions in Chile. We investigated how ENSO affects catchment hydrology and found strong seasonal and spatial differences in the hydrological response to ENSO which was caused by different hydrological processes in catchments that are dominated by snowmelt-generated runoff or rainfall-generated runoff. These results are relevant for water resources management and ENSO mitigation in Chile.

Eighty Ma old fossil leaf assemblages suggest a widespread distribution of tropical rainforest in north-eastern Africa.

We measured rock strength and amount of fracturing in the two different rock types, sandstones and carbonates, in Last Chance Canyon, New Mexico, USA. Where there is more carbonate bedrock, hills and channels steepen in Last Chance Canyon. This is because the carbonate type bedrock tends to be more thickly bedded, is less fractured, and is stronger. The carbonate bedrock produces larger boulders than the sandstone bedrock which can protect the more fractured sandstone bedrock from erosion.

Carbonyl Sulfide (COS) is a useful constraint on photosynthesis. To simulate COS leaf flux better in the SiB4 model, we propose a new temperature function for the enzyme carbonic anhydrase (CA) and optimize conductances using observations. CA has an optimum temperature below 40 °C, which can be influenced critically by air temperature changes. It brings tropics a smaller and higher latitudes a larger uptake. This update helps resolve gaps in the COS budget identified in earlier studies.

We use apatite (U-Th-Sm)/He thermochronologic on detrital grains sampled from a well to unravel the exhumation history of the northern Swiss Molasse Basin and reconcile seemingly contradicting previous studies. With single grain ages and provenance ages, we achieve to narrowly constrain exhumation magnitude and timing and embed previous results into a single consistent thermal history. This includes proof for hydrothermal activity and a contribution to the discussion on exhumation drivers.

This study uses the trajectories of water parcels traced within an ocean model simulation to identify the pathways responsible for the seasonal cycle of dense water formation (overturning) in the eastern subpolar North Atlantic. We show that overturning seasonality is due to the fastest water parcels circulating within the eastern basins in less than 8.5 months. Slower pathways set the average strength of overturning in this region since water parcels cannot escape intense wintertime cooling.

Tropical upwelling systems are among the most productive ecosystems globally. The tropical Atlantic upwelling undergoes a strong seasonal cycle that is forced by the seasonal cycle of the zonal wind along the equator and the near-coastal wind field off Africa. Besides the wind forcing that lead to an up- and downward movement of the nitracline, turbulent diffusion results in upward mixing of nutrients. Here, we review the different physical processes responsible for upward nutrient supply.

The TCCON is a network of ground based remote sensing instruments that measure greenhouses in the atmosphere. The consistency between the TCCON measurements is crucial to accurately infer changes in atmospheric composition. In this work, we use portable remote sensing instruments (EM27/SUNs) as traveling standards to evaluate biases between TCCON stations in North America. We also improve the retrievals of EM27/SUNs and evaluate the previous (GGG2014) and newest (GGG2020) retrieval algorithms.

Several studies have noted that ozone in the lower part of the stratosphere ozone has not increased and perhaps even continued to decline in recent decades. This study demonstrates that the amount of ozone in this region is highly sensitive to the amount of air upwelling into the stratosphere in the tropics, and that some climate models fail to accurately capture the variations in upwelling that control these short term trends in ozone.

Understanding whether variations in ocean heat content are driven by air-sea heat fluxes or by ocean dynamics is of crucial importance to enhance climate projections. We use a relatively novel causal method to quantify interactions between ocean heat budget terms based on climate models. We find that low-resolution models overestimate the influence of ocean dynamics in the upper ocean, and that changes in ocean heat content are dominated by air-sea fluxes at high resolution.

In this study, the atmospheric ozone evolution simulated with SOCOLv4 for the period 2015–2099 under SSP2-4.5 and SSP5-8.5 scenarios has been assessed using the DLM approach. The SOCOLv4 projects a decline in tropospheric ozone, but in the 2030s in SSP2-4.5 and in the 2060s in SSP5-8.5. The stratospheric ozone increase is ~3 times higher in SSP5-8.5, confirming the important role of GHGs in ozone evolution. We also showed that tropospheric ozone impacts strongly the total column in the tropics.

Climate change will alter heat and freshwater fluxes and ocean circulation, driving local changes in sea level. This sea-level change component is known as ocean dynamic sea level (DSL), and it is usually projected using computationally expensive General Circulation Models. Statistical models are a cheaper alternative for projecting DSL, but may contain significant errors. Here, we partly remove those errors (driven by natural variability) by using pattern recognition techniques.

The standard linear fluid theory of Farley-Buneman predicts that kinetic physics is required to avoid the artificial growth of smaller structures. We decided to explore the possibility of simulating Farley-Buneman using, for the first time, a fully fluid five-moment model. This is the first time a fully fluid model has been used to simulate the Farley-Buneman instability. The results obtained with both models are qualitatively consistent with the ones from kinetic simulations.

Data assimilation techniques are a promising approach to improve snowpack simulations in remote areas that are difficult to monitor. This paper studies the ability of satellite-observed land surface temperature to improve snowpack simulations through data assimilation. We show that it is possible to improve snowpack simulations, but the temporal resolution of the observations and the algorithm used are critical to obtain satisfactory results.

Extensive virga research is uncommon, even though it is a common phenomenon. A systematic method was developed to characterize the virga using available datasets. 50 virga events were observed, which appeared only during a specific time of the year, revealing a seasonal occurrence pattern. These virga events were identified and classified, and their impact on surface measurements was investigated. A more detailed examination of selected events reveals that virga impacts regional air quality.

Long-term inorganic P fertilization increased total P, available P, and inorganic P, but manure fertilization accelerated the accumulation of organic P. Long-term mineral fertilization had a negative impact on bacterial communities, whereas manure fertilization and rhizosphere provided more nutrient that improved the separation of bacterial communities. Correspondingly, P indicators such as inorganic P and total P were related to the variation of phosphorus solubilizing bacterial community.

Magnetic-fabric analysis provides information about the reorientation of magnetic grains and is applied to three sandbox models that simulate different stages of basin inversion. The analysed magnetic fabrics reflect the different developed structures and provides insights in the different deformed stages of basin inversion. It is a first attempt of applying magnetic-fabric analyses to basin inversion sandbox models, but shows the possibility of applying it to such models.

Gelatinous zooplankton play a key role in the ocean carbon cycle. In particular, pelagic tunicates, which feed on a wide size range of preys, produce rapidly sinking detritus. Thus, they efficiently transfer carbon from the surface to the depth. Consequently, we added these organisms to a marine biogeochemical model (PISCES-v2) and evaluated their impact on the global carbon cycle. We found that they contribute significantly to carbon export, and that this contribution increases with depth.

The Earth Clouds, Aerosols and Radiation (EarthCARE) satellite mission developed by European Space Agency (ESA) and the Japan Aerospace Exploration Agency (JAXA) features the first spaceborne 94-GHz Doppler Cloud Profiling Radar (CPR) with Doppler capability. Here, we describe the post-processing algorithms that apply quality control and corrections to CPR measurements, and derive key geophysical variables such as hydrometeor locations and best estimates of particle sedimentation fall velocities.

Water in natural environments consists of many ions. Ions are electrically charged and exert electric forces on each other. We discuss whether the electric forces are relevant in describing mixing and reaction processes in natural environments. By comparing our computer simulations to lab experiments in literature, we show that the electric interactions between ions can play an essential role in mixing and reaction processes, in which case they should not be neglected in numerical modeling.

An model was developed with the possibility to utilize satellite-derived daily surface albedo driven by high-resolution climate data estimate the surface energy balance (SEB) for all Icelandic glaciers for the period 2000–2021.

Ski resorts are a key socio-economic asset of several mountain areass. Grooming and snowmaking are routinely used to manage the snow cover on ski pistes, but despite vivid debate, little is known about their impact on water resources downstreams. This study quantifies, for the pilot ski resort La Plagne in the French Alps, the impact of grooming and snowmaking on downstream river flow. Hydrological impacts are mostly apparent at the seasonal scale but rather neutral on the annual scale.

The goal of this paper is to obtain probabilistic predictions of a partially observed dynamical system, without knowing the model equations. It is illustrated using the 3-dimensional Lorenz system where only two components are observed. In the era of deep learning and large datasets, the proposed data-driven procedure is low-cost, easy to implement, using linear and Gaussian assumptions, and requires only a small amount of data.

Root-zone soil moisture, important for ecosystems and agriculture, is now substantially modified by human activities and global warming. We studied how it changes in possible future climates (2021–2100). Based on the output of climate models, we can say that the Mediterranean, South Africa, parts of North and South America will become permanently drier, while Northern Africa and Southern Asia become wetter. This occurs even under mitigation scenarios, making climate adaptation imperative.

Large numbers of marine organisms such as zooplankton and fish perform daily vertical migration between the surface (during nighttime) and the depths (during daytime). This fascinating migration is important for the carbon cycle, as these organisms actively bring carbon to depths, where it is stored away from the atmosphere for a long time. Here, we quantify the contributions of different animals to this carbon draw-down and storage, and show that fish are important to the biological carbon pump

The waxing and waning of the Antarctic ice sheet caused the Earth’s surface to deform, which is stabilizing the ice sheet and mainly determined by the spatially variable viscosity of the mantle. Including this feedback in model simulations leads to significant differences in ice sheet extend and ice thickness at present day. The results underline and quantify the importance of including this local feedback effect in ice-sheet models when simulating the Antarctic Ice Sheet evolution.

Reservoirs and wetlands are important regulators of watershed hydrology, which should be considered when projecting floods and droughts. We developed a semi-spatially integration modeling framework that coupling wetland modules and reservoir operation into basin hydrological simulation. We applied the framework in a large river basin and found that the risk of future floods and droughts will overall increase further even under the combined influence of reservoirs and wetlands.

The Araripe Basin in NE Brazil was originally formed during Cretaceous times, as South America and Africa broke up. The basin is an important analogue to offshore South Atlantic break-up basins; its sediments were uplifted and are now found at a 1000 m height, allowing for study, but the cause of the uplift remains debated. Here we ran a series of tectonic laboratory experiments that show how a specific plate tectonic configuration can explain the evolution of the Araripe Basin.

Extension leading to the formation of ocean-continental transition can be highly oblique to the main direction of crustal thinning. Here we explore the case of a continental margin exposed in the Betics, north of the Alboran margin, that developed in back-arc setting perpendicular to the direction of retreating Gibraltar subduction. We show that transtension is the main mode of crustal deformation that best explains the formation of metamorphic domes, extensional basins and brittle faults.

The CH2O-CHOO TRAIN model can simulate how climate and the long-term carbon cycle interact across millions of years on a standard PC. While efficient, the model accounts for many factors including the location of land masses, the spatial pattern of the water cycle, and fundamental climate feedbacks. The model is a powerful tool for investigating how short-term climate processes can affect long-term changes in the Earth System.

We need to understand where faults are to (1) assess their seismic hazard, (2) to explore for natural resources and (3) to store CO2 safely in the subsurface. Currently we still map faults manually using seismic data i.e. acoustic images of the subsurface. Mapping these images is however difficult and time-consuming. Here we show how to use deep learning and network analysis to accelerate and simplify fault mapping.

Topographic highs (“bumps”) across glaciated landscapes have the potential to affect glacial ice. Topographic bumps in the deglaciated Puget Lowland are assessed for streamlined glacial features to provide insight on ice-bed interactions. We identify a threshold in which bumps will consistently and significantly disrupt and sedimentary processes in this location. However, not all bumps have the same degree of impact. The system assessed here has relevance to parts of the Greenland Ice Sheet.

We introduce an aerosol classification model that has been developed for the Earth Clouds, Aerosols and Radiation Explorer (EarthCARE). The model provides a consistent description of microphysical, optical, and radiative properties of common aerosol types such as dust, sea salt, pollution, and smoke. It is used for aerosol classification and assessment of radiation effects based on the synergy of active and passive observations with lidar, imager, and radiometer of the multi-instrument platform.

Ice formation is a key atmospheric process facilitated by a wide range of aerosols. We present a method to model and interpret of ice nucleation experiments and extract the distribution of potency of nucleation sites. We use the method to optimize conditions of laboratory sampling and extract distribution of ice nucleation temperatures from bacteria, fungi and pollen. These reveal unforeseen subpopulations of nuclei in these systems and how they respond to changes in their environment.

Based on the combined measurements of gas- and particle-phase highly oxygenated organic molecules (HOM) from α-pinene ozonolysis, enhancement of C₁₆-C₁₉ HOM dimers in particles was observed. Especially, C₁₇H₂₆O_z, which has often been reported by offline measurements, dominates the particle-phase HOM. Our results indicate that these C₁₇ compounds might be closely related to particle-phase HOM formation. These results are important for a better understanding of SOA formation in the atmosphere.

This study tests the new water condensation particle counter (MAGIC 210-LP) for the deployment on passenger aircraft coordinated by the European research infrastructure IAGOS . We conducted a series of laboratory experiments for flight altitude conditions. We demonstrate that this model water condensation particle counter shows excellent agreement with a butanol-based instrument used in parallel, and a Faraday cup electrometer as reference instrument at all tested pressure conditions.

Models are essential to diagnose the significant effects of nitrogen oxides (NO_x) on air pollution. We use an air quality model to illustrate 1) the variability of NO_x resolution-dependent simulation biases; 2) how these biases depend on specific chemical environments, driving mechanisms, and vertical variabilities; and 3) how these biases affect the interpretation of satellite observations. High resolution simulation is thus critical to accurately interpret NO_x and its relevance to air quality.