bluuebunny/crossref_metadata_2025 huggingface dataset:
Testing ensemble-based estimates of potential observation impact
Authors: Griewank Philipp , Necker Tobias , Weissmann Martin
Published: March 2024

While ensemble methods to estimate the impact of assimilated observations on forecast error have been widely used (known as EFSO), similar methods to estimate the benefit of potential observations not assimilated have received less attention. For this presentation we use a toymodel to illustrate these methods and highlight their strengths and weaknesses. We show that these methods work well over a wide range of lead times and for different types of observations, but only when the localization used in ensemble data assimilation to mitigate sampling errors is accounted for. While previous studies struggled to achieve quantitative results because they treated the localization inconsistently, we found three methods to overcome this limitation. 
Recent developments in the Earth System Model evaluation tool
Authors: Andela Bouwe , Hassler Birgit , Schlund Manuel
Published: March 2024

ESMValTool (Earth System Model eValuation Tool) is open-source, community-developed software for the evaluation of Earth system models, mainly in the context of multi-model analyses, e.g. the Coupled Model Intercomparison Project (CMIP). ESMValTool provides a large number of “recipes” that reproduce published figures, for example, some of the figures found in reports of the Intergovernmental Panel on Climate Change (IPCC). ESMValCore, the framework powering ESMValTool, provides capabilities that make it easy to work with data produced for CMIP as well as related observational and reanalysis data, e.g. discovering, downloading, and preprocessing these data. Here, we present new features that have been added to ESMValCore and ESMValTool in the past year.Improved computational performance: it is now possible to use Dask Distributed to run the tool and almost all preprocessor functions are now using Dask arrays, resulting in lower memory use and faster computations. This enables the analysis of higher-resolution datasets, such as those expected for the next round of CMIP. Further performance improvements are planned this year as part of the ESiWACE3 service project.New recipes and better-looking results: several new analyses have been added, including recipes for reproducing figures from the IPCC’s Fifth and Sixth Assessment Reports and generic recipes for monitoring and evaluating Earth System Model simulations. The webpage displaying the results of a recipe run now looks better and allows for interactive filtering.More datasets: more observational and reanalysis datasets can now be converted to the CMIP data request standard using the tool. Grids used in the Coordinated Regional Climate Downscaling Experiment (CORDEX) are now better supported.Communication: the ESMValTool tutorial at https://tutorial.esmvaltool.org has been updated, more Jupyter notebooks are available to demonstrate the use of ESMValCore, and there is a new, open-source website at https://esmvaltool.org.
Runoff variation and progressive aridity during drought in catchments in southern-central Chile
Authors: Barrientos Guillermo , Rubilar Rafael , Duarte Efrain , Paredes Alberto
Published: March 2024

Persistent drought events frequently intensify the aridity of ecosystems and cause catchments runoff depletion. Here, using large and long-term data sets of meteorological and hydrologic variables (precipitation, runoff, temperature and potential evapotranspiration) investigated the major causes that modulated catchment runoff depletion between years 1980 and 2020 in southern central Chile. We identify the hydrological years where aridity index intensified and analyzed its relationship with annual runoff, and evaluated the effect of annual evaporation index and annual aridity index on water balance of 44 catchments with different precipitation regimes located between 35° and 40°S. Our results showed that observed precipitation and runoff significantly decreased between 1980 and 2020 in 64% of the catchments in the study area. Potential evapotranspiration increased significantly in 39% of the catchments. The runoff value decreased as the aridity index increased from 0.3 to 6.7, and the Budyko curve captured 98.5% of the annual variability of all catchments. Furthermore, for an extreme aridity index (e.g. 6.5), potential evapotranspiration far exceeds mean annual runoff and precipitation. Catchment runoff is modulated by the aridity index, which is a key indicator of insufficient precipitation. As expected, for any type of drought, precipitation and evapotranspiration are key factors modulating catchment runoff response. Hydrological years in which precipitation decreased, showed a decreased runoff trend. This result suggest that meteorological droughts tend to significantly decrease observed runoff. However, our results suggest that runoff in catchments, under consecutive years of water stress, will suffer from an even more severe water deficit in today’s rapidly changing global climate with negative impacts on ecosystem services and human activities.
Exploring physics-informed neural networks for glacier flow.
Authors: K C Mamta , Köstler Harald , Fürst Johannes
Published: March 2024

Deep learning-based surrogate models have emerged as computationally inexpensive tools for simulating glacier dynamic systems defined by complex, nonlinear partial differential equations. Despite the potential, the application of physics-informed neural networks  (PINNS) in glacier modelling is sparse. Thus, this study explores the potential of  NVIDIA Modulus-Sym, a PyTorch-based framework, in simulating glacier velocities. The framework NVIDIA Modulus-Sym provides ground for building, training and fine-tuning physics-based surrogate models targeting computational fluid problems. This study presents the pipeline to generate glacier velocities using the physics-constraint approach that incorporates the physics regularisation term within the loss function to enhance generalisation performance. The study further emphasises the challenges and limitations of tools in glaciological research. Keywords: Deep learning, Surrogate Models, Glacier Dynamics,  Glaciology
Sensitivity of mixed-phase cold-air outbreak clouds to aerosol-cloud interactions and ice production processes depends on environmental conditions: a comparison between spring and autumn CAO case studies over the Labrador Sea
Authors: Huang Xinyi , Field Paul , Murray Benjamin , Grosvenor Daniel , Van Den Heuvel Floortje , Carslaw Kenneth
Published: March 2024

Aerosol-cloud interactions and ice production processes are important uncertainties in models of mixed-phase cold-air outbreak (CAO) clouds, which are vital for the estimation of cloud-phase feedback. Our model simulation results show that the sensitivities of the mixed-phase cloud properties during the two selected CAO cases are different, with Ice Nucleating Particle (INP) concentrations having a strong influence for both case studies, but the cloud droplet number concentration and the HM (Hallett-Mossop) efficiency only affect the warmer case. We also find that the simulations showing the best performance compared to observations are not consistent across multiple satellite-observed cloud properties, which suggests a possible structural deficiency in the model. The two cases are CAO events over the Labrador Sea, 15 March 2022 and 24 October 2022, with the latter one coinciding with the M-Phase aircraft campaign. The regional Met Office Unified Model coupled with a two-moment microphysics scheme was used to quantify the sensitivity of cloud cover, stratocumulus-to-cumulus transition, and cloud radiative properties to cloud droplet number concentration, INP concentration and efficiency of the HM process. Recent studies have aimed to understand how these two aspects influence CAO clouds, but have not compared the sensitivities under different environmental conditions or with a realistic temperature-dependent parameterisation for INPs. This study provides an instructive perspective on how cloud microphysics affects mixed-phase CAO clouds under different environmental conditions, and serves as a good basis for exploring the whole uncertain cloud microphysics parameter space across a range of environmental conditions.
On the contribution of boreal wetlands to the Northern Hemisphere carbonyl sulfide sink
Authors: de Vries Anna , Wohlfahrt Georg , Vesala Timo , Kohonen Kukka-Maaria
Published: March 2024

Previous studies inferred a missing sink of carbonyl sulfide (COS) in high Northern latitudes. Boreal COS budgets, however, typically account solely for the contribution by forests and ignore any uptake that widespread wetland ecosystems may contribute. Here we present the first direct measurements of the ecosystem-atmosphere COS exchange of a boreal wetland and compare this with a needleleaf forest ecosystems. We then use these data to up-scale to the boreal region.We found that the investigated wetland was a stable sink for COS during the vegetation period, taking up on average of 10 pmol m−2s−1COS. While this was just 64% of the forest COS uptake, upscaling to the boreal region using the ORCHIDEE land surface model revealed that the Northern wetland sink, c. 20 GgS/y, was on the same order of magnitude compared to the forest COS sink. Our results thus indicate that northern COS should not neglect contributions by wetland ecosystems.
The Cala Viola-Torre del Porticciolo coastal area: classical geological survey and 3D digital outcrop models (DOMs) analysis to unravel the polyphase tectonics in NW Sardinia (Italy).
Authors: Scarani Rudy , Cipriani Angelo , Menegoni Niccolò , Stori Lorenzo , Citton Paolo , Romano Marco , Nicosia Umberto , Ronchi Ausonio
Published: March 2024

In the Nurra region (NW Sardinia), along the coast that stretches from Cala Viola to Cala del Turco bays, a stratigraphic sequence of continental sediments ranging from the upper Paleozoic to the lower Mesozoic is wonderfully exposed.In the last twenty years this area has been a subject of renewed studies due to its exceptional stratigraphic and sedimentological features and thanks also to an exceptional paleontological record, encompassing trace fossils and body fossils, which provided key chronological data. The most recent investigations have been focused on stratigraphic and structural geology aspects, allowing to reconstruct the tectonic evolutionary history of Sardinia, from the middle Permian up to the Middle Triassic.The redefinition of the stratigraphic and structural framework of the area became possible through integrating traditional geological surveys (mainly, field mapping, facies and structural analyses) with analyses conducted on 3D digital models of outcrops (DOMs) obtained via drone-based aerophotogrammetry. Investigations, both in the field and computer-based, have enabled the identification of the arrangement of cross-cutting relationships among fault systems.Despite the absence of absolute geochronological constraints (e.g., dating of syn-kinematic mineralizations), it has nevertheless been possible to identify at least six to eight deformational events. These analyses have revealed the likely history of deformational processes in this sector of the Island, highlighting the tectonic events that have occurred from the Permian until at least the Pliocene, despite Pleistocene-Holocene tectonics cannot be excluded. The events can be summarized as follows:Event 1: extensional tectonics related to the angular unconformity between Permian and Triassic deposits (age post early middle Permian to Early Triassic)
Event 2: extensional tectonics related to the rifting of the Ligurian-Piedmont Ocean and subsequent carbonates deposition (Middle Jurassic: Bajocian-Bathonian)
Event 3: extensional event related to the early Pyrenaic deformation and represented by an extensive angular unconformity/hiatus in carbonate platform (Early Cretaceous: Aptian-Albian)
Event 4: transpressive and compressive event related to deformative phase called “Laramian” tectonics (Late Cretaceous)
Event 5: compressive and consequent transcurrent tectonics related to the “Pyrenaic phase” (Eocene to Aquitanian age)
Event 6: extensional tectonics related to the opening of the Balearic basin and the rotation of the Sardinia-Corsica block (Burdigalian age)
Event 7: extensional tectonic phases occurred during two different sub-events (Serravalian age and the Pliocene age)
Event 8: extensional event occurred during the Pleistocene-Holocene
Error-aware surrogate modelling with input dimension reduction for groundwater modelling in heterogenous media
Authors: Morales Oreamuno Maria Fernanda , Oladyshkin Sergey , Nowak Wolfgang
Published: March 2024

Machine learning approaches have gained high notoriety to approximate computationally-expensive models in the geosciences. Surrogate models are trained using input-output pairs to emulate the numerics of full complexity models. These fast models then assist in forward and inverse uncertainty quantification for various applied problems. However, large input dimensions, typically found in groundwater modelling for very heterogeneous environments, present a challenge for surrogate models. Input dimension reduction (IDR) methods, such as the Karhunen-Loéve expansion (KLE), are known to reduce the number of input parameters used to train surrogate models, while also generating stochastic realizations of the input random fields for groundwater modelling applications. Traditionally, KLE truncates the input parameters such that 90% of the input variance is considered. However, in some applied cases, this dimension remains too large for reliable surrogate model training. Specifically, using a smaller number of input parameters (considering a smaller percentage of the input variance) may introduce IDR-associated errors in the surrogate output. These errors are often overlooked when assessing uncertainty in surrogate model outputs and could be particularly significant in Bayesian inverse modelling. We are offering a surrogate modelling framework tailored for high-dimensional problems that accounts for IDR-induced errors in the context of Bayesian inverse modelling. Our framework allows for more informed decision-making when using surrogate models as approximators and to widen the scope in which surrogates can be used in heterogeneous media applications. We demonstrate the introduced approach using a groundwater flow and transport model with a heterogeneous hydraulic conductivity field to estimate contaminant concentrations and pressure head values.
Stratospheric chlorine activation after the unprecedented water-rich Hunga Tonga eruption
Authors: Zhang Jun , Wang Peidong , Kinnison Douglas , Solomon Susan , Guan Jian
Published: March 2024

Following the eruption of Hunga Tonga–Hunga Ha’apai (HTHH) in January 2022, a significant reduction in stratospheric hydrochloric acid (HCl) was observed in the Southern Hemisphere mid-latitudes during the austral winter of 2022. This eruption injected sulfur dioxide and unprecedented amounts of water vapor into the stratosphere. The objective of this study is to comprehensively understand the substantial loss of HCl in the aftermath of HTHH. Satellite measurements from the Atmospheric Chemistry Experiment-Fourier Transform Spectrometer (ACE) and Microwave Limb Sounder (MLS), along with data from the global chemistry-climate model Whole Atmosphere Community Climate Model (WACCM), are employed for the analysis. We first compare the modeled 2022 anomalies of HCl and N2O with observations from ACE and MLS, and find noteworthy agreement between the model outputs and the measured data. We then utilize the observed tracer-tracer relations between N2O and HCl to distinguish HCl chemical processing from dynamical transport. The results indicate a significant role of chemical processing in the observed HCl reduction. The chemical changes in HCl derived from ACE and MLS align with the changes calculated from nudged model simulations, where dynamics are fixed to reanalysis. Further delving into the WACCM’s detailed chemistry, we examine individual chlorine gas-phase and heterogeneous reactions. Heterogeneous chemistry emerges as the primary driver for the chemical loss of HCl, with the reaction between HOBr and HCl on sulfate aerosols identified as the dominant loss process.
The role of carbon markets in reducing carbon emissions and strengthening the land sink at scale
Authors: Andela Niels
Published: March 2024

Global CO2 emissions from land use and land cover changes contribute about 10% of anthropogenic carbon emissions annually, while terrestrial ecosystems also remove about 29% of annual emissions through enhanced growth and ecosystem recovery. The conservation and restoration of soils, woody biomass and other carbon pools have therefore emerged as key components of national and corporate net zero strategies. Both compliance and voluntary carbon markets, including bilateral and global carbon trading agreements, have the potential to accelerate emissions reductions and removals at local, national, and global scales. The success of these markets relies on effective policy frameworks, transparency and independent assessments of project integrity. Trust in the voluntary markets was shaken during 2023 following media reports of over crediting, while at COP28 nations failed to agree on standards and frameworks for Article 6 of the Paris agreement (on bilateral and UN-supervised carbon markets).  Carbon ratings agencies provide independent analysis on the effectiveness and claims of carbon projects operating within the voluntary market. These assessments strengthen trust through greater transparency and price discovery, so that funding can be unlocked for the most effective projects. Here we will discuss challenges and opportunities for scaling the carbon markets, based on our assessment of over 130 nature-based carbon projects globally, assessing key risk factors such as project additionality (what would have happened in the absence of carbon finance), carbon accounting, and non-permanence (risk of future reversal). Our methodologies combine novel monitoring tools, including satellite observations and machine learning models, with information about project finances and policy context to assess the efficacy of every credit issued. Lessons learned can help emerging markets scale, and inform future projections and modelling frameworks of terrestrial carbon fluxes.
Autoencoder-based model for improving  reconstruction of heat waves using the analogue method
Authors: Pérez-Aracil Jorge , Marina Cosmin M. , Gutiérrez Pedro , Barriopedro David , García-Herrera Ricardo , Giuliani Matteo , McAdam Ronan , Scoccimarro Enrico , Zorita Eduardo , Castelletti Andrea , Salcedo-Sanz Sancho
Published: March 2024

The Analogue Method (AM) is a classical statistical downscaling technique applied to field reconstruction. It is widely used for prediction and attribution tasks. The method is based on the principle that two similar atmospheric states cause similar local effects. The core of the AM method is a K-nearest neighbor methodology. Thus, two different states have similarities according to the analogy criterion. The method has remained unchanged since its definition, although some attempts have been made to improve its performance. Machine learning (ML) techniques have recently been used to improve AM performance, however, it remains very similar. An ML-based hybrid approach for heatwave (HW) analysis based on the AM is presented here. It is based on a two-step procedure: in the first step, a non-supervised task is developed, where an autoencoder (AE) model is trained to reconstruct the predictor variable, i.e. the pressure field. Second, an HW event is selected, and then the AM method is applied to the latent space of the trained AE. Thus, the analogy between the fields is searched in the encoded data of the input variable, instead of on the original field. Experiments show that the meaningful features extracted by the AE lead to a better reconstruction of the target field when pressure variables are used as input. In addition, the analysis of the latent space allows for interpreting the results, since HW occurrence can be easily distinguished. Further research can be done on including multiple input variables. 
CubeSpark: Space-based 3-D Lightning Mapping using a Constellation of Radio Frequency Sensors
Authors: Behnke Sonja , Katko Kim , Edens Harald , Gatlin Patrick , Lang Timothy , Haynes William , Snow Paul , Rushton Jeremiah , Renck Joellen , Weaver Charley , Bronisz Larry , Pratt Jacob , Dobson Steven , Pailoor Nikhil , Remington Jackson , Stough Sarah
Published: March 2024

CubeSpark is a new concept for a constellation of CubeSats that combines bi-spectral optical lightning imaging with radio frequency (RF) sensing to provide a 3-D lightning detection capability with global coverage from low-Earth Orbit. The development of CubeSpark is a collaboration between Los Alamos National Laboratory and NASA Marshall Space Flight Center. CubeSpark innovates over current ground and space-based global lightning capabilities by determining the altitude of lightning radiation sources, enabling new science in thunderstorm processes and the impact of lightning on climate. The key to determining the altitude of lightning is using a constellation of RF sensors to make coordinated measurements of impulsive RF radiation sources, similar to the approach of a ground-based lightning mapping array. The RF measurements will be enhanced with bi-spectral optical sensors to improve overall lightning detection efficiency and provide additional, complementary information about lightning processes.This presentation introduces the CubeSpark mission concept and science applications with a focus on the RF hardware under development. Two challenges of space-based RF lightning detection are ionospheric effects and RF noise from both the satellite bus and anthropogenic sources from Earth. While the process of removing ionospheric dispersion from broadband waveforms for time-of-arrival (TOA) estimation is well established, CubeSpark further reduces ionospheric impacts on TOA by using a circularly polarized antenna, which suppresses one of the birefringent wave modes. For noise reduction, the CubeSpark receiver leverages programmable high- and low-pass filters to allow for on-orbit modifications of its passband. A benchtop demonstration of the RF hardware has been completed.
Exploring stakeholder priorities regarding decentralized waste-water treatment in the Brantas river basin using Q-methodology
Authors: Ertsen Maurits , Martinez Rodriguez Valeria , De Kreuk Merle , Houser Schuyler , Palmeros Parada Mar
Published: March 2024

Next to the challenges of paramount importance represented by water scarcity, food security, energy transition, and environmental protection issues, the obstacles faced on the matter of water, sanitation, and hygiene (WASH) are immense. WASH interventions are essential to support human health, prosperity, and dignity, as they provide the base for an adequate standard of living. In many low- and middle- income countries, especially in rural and low-income areas, decentralized wastewater treatment systems (DEWATS) can offer a solution to convey, treat, and dispose of or reuse wastewater closer to the source and through smaller conveyance networks. In Indonesia, and as such in the Brantas basin on East Java, focus area of this study, the government has recognized DEWATS as their best available option for improving sanitation in dense low-income urban settings. Although the percentage of households with access to proper sanitation in the province of East Java has been increasing steadily, service coverage and the quality of sanitation systems still need to be increased to reach the desired coverage by 2024. Similar to other fields of application, within WASH and concerning DEWATS, stakeholders engagement, ethics and gender dimension are key topics to develop and strengthen integrated approaches. It is challenging to formulate targeted interventions in the watershed since they depend on the willing support of various stakeholders who may have different priorities (even within their own institutions), having diverse (and sometimes conflicting) viewpoints. This may result in stakeholders strongly contesting the appropriateness of various solutions. An exploration of stakeholder priorities is therefore needed to facilitate the application of wastewater treatment technologies. Due to its participatory approach and the type of interpretation that the method allows, Q-methodology was selected to explore this situation. Q-methodology is a set of techniques which allow for the study of ‘subjectivity’, combining statistics with the depth provided by qualitative data. It is composed of the data collection technique (called Q-sorting) and a data analysis step via correlation and factor analysis. In this contribution, we explore the perspectives and priorities of various stakeholders regarding decentralized wastewater treatment solutions to assess the applicability and acceptability of DEWATS in the Brantas river basin. This allows us to identify context-based criteria and challenges to the implementation of DEWATS in the Brantas watershed. As such, we propose the Q-methodology as a strong methodology to further develop the required transdisciplinary scientific efforts to promote relevant insights and solutions through meaningful, pertinent, and effective stakeholder engagement.
The influence of tides on the AMOC in an eddy-permitting global general circulation model
Authors: Borile Federica , Cessi Paola , Iovino Doroteaciro , Pinardi Nadia
Published: March 2024

The energy budget of the global ocean circulation highlights the importance of winds and tides as primary energy sources. Tidal influence extends throughout the water column, particularly in regions of rough topography where internal waves are generated, leading to the conversion of energy from barotropic to baroclinic high-frequency modes. Our study explores the impact of tidal forcing on the general circulation using different experiments of a mesoscale-permitting global ocean model, with the addition of a topographic wave drag parametrization for unresolved scales. The focus is specifically on the Atlantic meridional overturning circulation (AMOC). Our findings reveal that tides interact with mesoscale structures, either reinforcing or weakening the mean circulation based on the dynamic conditions of the flow. On a basin scale, we find that the meridional circulation is weakened by tides on multidecadal time scales, despite robust interannual variability. We analyze these impacts in the momentum balance, concentrating on the role of tides in altering the AMOC geostrophic balance.
Detailed monitoring and simulation of groundwater salinity in response to extractions in coastal aquifers
Authors: Hendrikx Thijs , Oude Essink Gualbert , Bierkens Marc
Published: March 2024

High-resolution three-dimensional variable-density groundwater flow and coupled salt transport models (3D-VD-FT models) are useful instruments to support coastal groundwater management strategies and to project impacts of climate change. However, the ability of 3D-VD-FT models to provide accurate groundwater salinity predictions depends on computational capabilities, availability of sufficient and adequate high-resolution temporal and spatial data and knowledge of groundwater salinity processes in the subsurface. Current understanding in saltwater intrusion research is mainly based on theoretical, experimental and numerical studies, with intensive monitoring field studies being uncommon. In this paper, we describe a methodology that combines a high-resolution 3D-VD-FT model with an intensively monitored pilot in a coastal area in the Netherlands to improve our understanding of fresh-saline groundwater dynamics in response to multi-level groundwater extractions. We assess the applicability of 3D-VD-FT models to reproduce observed groundwater salinity changes in response to extractions. Moreover, we evaluate multiple extraction regimes of fresh and brackish groundwater. Subsequently, critical pumping rates are determined to secure fresh groundwater supply and the preventive effect of brackish groundwater extractions on saltwater intrusion is evaluated. Preliminary results show improvement of predictions on the scale of individual wells compared to previous studies conducted on similar scales. The 3D-VD-FT model captures the observed salinity trends such as downconing fresh groundwater and upconing saline groundwater, both of which occurred in response to withdrawals. However, the model’s absolute accuracy of downconing and upconing groundwater salinity still requires improvement.
The Inn Valley exit jet: results of the TEAMx pre-campaign
Authors: Sedlmeier Katrin , Kossmann Meinolf , Paunovic Ivan , Eichhorn-Müller Astrid , Nitsche Oliver , Leinweber Ronny , Päschke Eileen , Mühlbacher Gudrun
Published: March 2024

Previous studies have found a pronounced nocturnal low-level jet at the exit of the Inn Valley north of the valley contraction near Schwaigen which reaches into the Alpine foreland (e.g. Pamperin and Stilke, 1985 as part of the MERKUR experiment or a model study by Zängl, 2004). The exit jet forms under nocturnal stably stratified atmospheric conditions and is interpreted as a transition from subcritical to supercritical hydraulic flow.As part of the pre-campaign of the TEAMx programme in June-August 2022, we have conducted measurements to corroborate the previous findings on the formation and maintenance of the Inn valley exit jet and learn more about its turbulence structure, which has not been studied in previous experiments. For this purpose, a wind lidar was deployed in Brannenburg, north of the valley constriction. TKE profiles were derived from the Lidar measurements using the method described in Smalikho and Banakh (2017).  Furthermore, 3-hourly radiosondes were launched at the site of the wind lidar, accompanied by drone measurements during an IOP (18/19 July 2022) in high pressure weather conditions with low cloud cover.  Upper air and surface wind measurements during the IOP captured a well pronounced Inn valley exit jet which is analyzed in detail in this contribution. Additionally, a statistical analysis of the occurrence and characteristics of nocturnal low-level jets within the whole pre-campaign period is presented. References:TEAMx: http://www.teamx-programme.org/Smalikho, I.N., and V.A. Banakh. "Measurements of wind turbulence parameters by a conically scanning coherent Doppler lidar in the atmospheric boundary layer." Atmospheric Measurement Techniques 10.11 (2017): 4191-4208.Pamperin, H., and G. Stilke. "Nächtliche Grenzschicht und LLJ im Alpenvorland nahe dem Inntalausgang." Meteorologische Rundschau 38.5 (1985): 145-156Zängl, G. "A reexamination of the valley wind system in the Alpine Inn Valley with numerical simulations." Meteorology and Atmospheric Physics 87.4 (2004): 241-256.
Detecting Organics with Dust Impact Analyzer Instruments
Authors: Sternovsky Zoltan , Mikula Becca , Armes Steven P. , Ayari Ethan , Bouwman Jordy , Hillier Jon , Horanyi Mihaly , Kempf Sascha , Postberg Frank , Srama Ralf
Published: March 2024

The dust accelerator operated at the University of Colorado is used to study how the organic content of small particulates in space can be detected and identified using dust impact analyzer instruments. The Interstellar Dust Experiment (IDEX) instrument will be launched onboard the Interstellar Mapping and Acceleration Probe (IMAP) mission in 2025 and will detect and analyze the composition of hundreds or thousands of interstellar and interplanetary dust particles from Lagrange point 1. IDEX is an instrument with a large sensitive area and high mass resolution that measures the time-of-flight mass spectra of the ions generated by the hypervelocity impact of dust particles. The laboratory version of IDEX is used to collect calibration data on dust samples of known composition. Such data are required for the interpretation of future IDEX measurements, including identifying their organic content of the detected particles. A comprehensive study was performed recently on the impact ionization properties of anthracene. Measurements were made over a wide (2 - 35 km/s) impact velocity range to investigate the strong variation of the impact spectra with the energy of the impact. Such laboratory studies are also relevant to the Surface Dust Analyzer (SUDA) and DESTINY Dust Analyzer (DDA) instruments on the Europa Clipper and DESTINY+ missions, respectively. In addition, two new laboratory capabilities are in development:  A uniquely capable laboratory setup using Near Infrared (NIR) spectroscopy and Time-of-Flight (TOF) mass spectrometry will allow measuring the physical and chemical alteration of the ice surface and organic compounds due to radiation and micrometeoroid bombardment. A newly developed ice accelerator capability will be used to characterize the impact ionization or organic-bearing compounds embedded in ice particles.
Does Strength Matter? An Exploration into Cyclone Strength and the Impact on Arctic Sea Ice
Authors: Valkonen Elina , Parker Chelsea , Boisvert Linette
Published: March 2024

Arctic cyclones are an integral part of the polar climate system. They import moisture and energy from the midlatitude and impact the underlying surface through dynamic adn thermodynamic interactions. The rapid warming and sea ice decline in the Arctic makes it more important than ever to understand the tightly coupled interactions between the Arctic sea ice and episodic weather events, such as cyclones.In this presentation, we use a Lagrangian ice parcel database to study the impact different strength cyclones have on the Arctic Sea ice. The database includes daily 25km Arctic ice parcel tracks and associated atmospheric and sea ice conditions, including passing cyclone track data from 2002-2021. We divide these cyclone tracks into three distinctive groups based on their central pressure and average wind speed. After this, we split the ice parcel tracks and associated atmospheric data based on these cyclone groups: ice affected by weak cyclones, ice affected by normal cyclones, and ice affected by extreme cyclones.We will then utilize these parcel groups to study the atmospheric conditions (precipitation, temperature, radiative balance) and sea ice changes for three days before, during, and three days after the cyclone passes. We will average the ice parcel and associated atmospheric variable data over the ice parcel life cycle and across the before, during, and after cyclone pass timescales. We will then apply statistical pattern recognition on these averaged sea ice and atmospheric variable fields. This analysis will allow us to better understand the role cyclone strength has in cyclone-sea ice interactions. We will present these results separately for individual seasons, locations, and surrounding SIC.
Brackish water rewetting of a temperate coastal peatland: Effects on biogeochemistry, microorganisms and greenhouse gas emissions
Authors: Gutekunst Cordula , Liebner Susanne , Jenner Anna-Kathrina , Racasa Erwin Don , Knorr Klaus-Holger , Anthony Sara E. , Pönisch Daniel Lars , Böttcher Michael Ernst , Janssen Manon , Kallmeyer Jens , Koebsch Franziska , Rehder Gregor , Jurasinski Gerald
Published: March 2024

Around 4 % of global greenhouse gas (GHG) emissions originate from drained peatlands. Unlike rewetting drained peatlands with freshwater, brackish water rewetting of coastal peatlands might not only reduce CO2 emissions, but also keep methane (CH4) emissions low. The re-establishment of the natural brackish water regime of coastal peatlands with high sulfate levels should favor sulfate reducing bacteria as well as sulfate-driven anaerobic methane oxidizers and therefore limit CH4 production and/or lead to increased CH4 consumption. Here, we compared CO2 and CH4 fluxes, pore water geochemistry, and associated microbial communities of a coastal fen along a moisture gradient before, and a water level gradient after rewetting.Brackish water rewetting increased the abundances of CH4 producing archaea (methanogens) as well as the abundances of sulfate reducing bacteria (SRB) in most of the study site, except at former ditch areas, where methanogenic and SRB abundances had been high before. At the same time, the aerobic methanotroph community was less present, indicating lower aerobic CH4 oxidation potentials after rewetting. Pore water CH4 and CO2 concentrations along with δ13C records suggest that both, methanogenesis and CH4 oxidation, increased after rewetting. Brackish water rewetting raised average CH4 emissions from 2 to 25 mg CH4 m-2 d-1 at locations that were previously drained, which is lower than CH4 emissions reported from most freshwater peatlands. Net CO2 emissions remained high after rewetting with values around 4 g CO2 m-2 d-1. However, since ecosystem respiration strongly decreased from on average 19 to 6 g CO2 m-2 d-1, the remaining net CO2 emissions were mostly associated with low CO2 uptake due to extensive die-back of the vegetation. Hence, brackish water rewetting can keep CH4 emissions relatively low, but, as in freshwater peatlands, hydrological management must allow for the re-establishment of site-specific vegetation to sustain net CO2 uptake.
Increased leaf temperature reduces photosynthetic capacity of top-of-canopy leaves in the wet tropical forest of Costa Rica
Authors: Rodriguez-Caton Milagros , Seibt Ulrike , Stutz Jochen , Parazoo Nicholas , Wong Christopher YS , Dierick Diego , Rao Mukund Palat , Filella Iolanda , Bigwood Julia , Cooperdock Sol , Penuelas Josep , Magney Troy
Published: March 2024

Warming temperatures, high vapor pressure deficit (VPD), and excess light during the middle of the day can reduce CO2 assimilation and cause stomatal closure, a phenomenon known as midday depression of photosynthesis. However, the role of light, temperature and VPD in driving the diurnal cycle of photosynthesis remain poorly studied in tropical biomes. Here we use quantum efficiency of photosystem II in the light (ϕPSII) as indicator of photosynthetic efficiency for top-of-canopy leaves for six tree species with distinct leaf morphology, across eight sampling campaigns over two years. We find midday decreases in ϕPSII when temperature, solar radiation and VPD were higher than normal. Interestingly, the difference between leaf temperature and air temperature is the most important factor driving changes in ϕPSII, while light is less prominent. We also estimated canopy temperature using outgoing longwave irradiance and found that canopy temperature deviates from air temperature at air temperatures of around 27-28 °C, likely indicating a thermal threshold for photochemistry at the canopy level. These measurements can be combined with state-of-the-art satellite remote sensing (e.g. solar-induced chlorophyll fluorescence and land surface temperatures) to better understand temperature thresholds to photosynthesis and transpiration across scales.
Empowering local Climate Change mitigation policies through Eddy Covariance flux measurements
Authors: Galvagno Marta , Filippa Gianluca , Tuzzi Luca , Cremonese Edoardo , Collalti Alessio , Colombo Roberto , Dalmonech Daniela , Grassi Giacomo , Migliavacca Mirco , Tomelleri Enrico , Nelson Jacob
Published: March 2024

According to the IPCC and the Paris Agreement, the imperative to limit global warming to 1.5°C, or well below 2°C, compared to the pre-industrial era, necessitates achieving a balance between anthropogenic emissions by sources and removals by sinks (net-zero anthropogenic CO2 emissions) by the second half of this century. In this context, a prerequisite for credible climate action is an accurate estimation of both these large fluxes. Recent initiatives have focused on improving the quantification of the land sector mitigation potential and reducing the discrepancies between models and observations at a global level. However, the implementation of climate mitigation policies often takes place at the local level, where entities like local authorities (e.g., cities and regions) often wield more impactful roles in the transition to a sustainable economy than higher-level bodies such as Nations. Conversely, the assessment of CO2 removals from forests and other land uses is traditionally lacking at the local compared to the national level. Following a support request from the local administration for the definition of a long-term climate mitigation plan, we tested a data-driven method relying on eddy covariance (EC) data to quantify the carbon sink of the Aosta Valley Region in northwestern Italy for the period 2010-2022. Our model integrates various approaches, incorporating eddy covariance measurements of CO2 fluxes, MODIS NDVI data, daily gridded meteorological variables, and a 250m spatial resolution land cover map to calculate the net carbon uptake of the regional ecosystems. A Random Forest model was used to up-scale the eddy covariance data to the regional level, by testing different sets of drivers (air temperature, VPD, Snow (presence/absence), NDVI, solar radiation,...). Furthermore, global models developed in the framework of the FLUXCOM initiative were fine-tuned with the local predictors and applied at a regional scale. Finally, we compared our findings with independent data derived from the National Greenhouse Gas Inventory.Preliminary results revealed that forests and other ecosystems in the region currently offset on average nearly 70% of anthropogenic emissions in the region, also depending on the interannual variation of air temperature and the occurrence of extreme events. We will delve into the discrepancies among various methods, exploring their respective advantages, limitations, and spatiotemporal variability. This evaluation of the regional carbon budget and associated uncertainties represents an important step toward the benefit of using flux observations for implementing climate-smart land management—a pivotal component in meeting carbon neutrality targets.
Deciphering the origin of sediment waves along the Northwest African margin through multidisciplinary analysis
Authors: Englert Rebecca , Boettner Christoph , Brandt Peter , Cartigny Matthieu , Huang Hao , Krahmann Gerd , Puig Pere , Schoenke Mischa , Stevenson Christopher , Talling Peter , Krastel Sebastian
Published: March 2024

Sediment waves are widely observed on the seafloor in a variety of marine environments (e.g., open slope, submarine channels, levees). They are important for understanding marine hazards because they can influence slope stability and be indicators of currents capable of damaging seafloor infrastructure (e.g., telecommunication cables). However, sediment wave dynamics may vary in different settings and several mechanisms have been invoked to explain their formation including gravity-driven (sediment failure, turbidity currents) and oceanographic (bottom currents, internal tides) processes. In this study, we investigate the generation of large unconfined sediment wave fields along the continental slope of the Northwest African margin using an integrated dataset acquired on the R/V Maria S. Merian cruise MSM113. Data collection included direct monitoring of ocean currents and water column properties over sediment wave fields by CTD casts, acoustic water column profiling, and deployment of short-term moorings equipped with velocity (ADCPs), temperature, salinity, and turbidity sensors. Additional datasets such as shallow and multichannel 2D seismic profiles, multibeam bathymetry, gravity cores, and box cores capture the geomorphic, subsurface, and sedimentary characteristics of the seafloor features. Sediment wave fields occur on the mid-lower slope between 600 – 1900 m water depths and are intersected by straight channels up to 2 km wide and 300 m deep. Individual waves have slope-parallel crests, wavelengths between 400 – 2000 m, and wave heights between 6 – 56 m. In subsurface seismic profiles, sediment waves are composed of upslope-stacking reflectors that indicate preferential deposition on their stoss slopes and upslope crest migration. Sediment cores from sediment waves are predominantly composed of bioturbated gradational sequences of mud, sandy mud, muddy sand, and sand that vary depending on location, suggesting a progressive process of differential sedimentation. Intermittent chaotic muddy deposits and sharp-based sand layers represent occasional punctuated flow events. Time series from moored instruments are dominated by strong semidiurnal tidal fluctuations with current velocities up to 0.3 m/s. Water column measurements and acoustic images reveal a stratified water column with wavy interfaces and small-scale fluctuations caused by the passage of internal waves. Collectively, these findings suggest that downslope gravity flows, along-slope currents, and internal tides contribute to sediment transport along the Northwest African margin; although, tide-topographic interactions are the most likely candidate for maintaining sediment waves. Our integrated analysis provides insight into oceanographic processes, which shape the seafloor and transport sediment along ocean margins.
Role of Artificial Intelligence in Remote Sensing of Cryosphere
Authors: Sood Vishakha , Tiwari Reet Kamal , Singh Sartajvir
Published: March 2024

In remote sensing, Artificial Intelligence (AI) plays a significant role in recognizing earth surface objects and features. With the continuous improvement in the resolution of remote sensing sensors, the applicability of AI is also enhancing with the potential of detailed extraction of Earth surface features. The objective of this article is to explore the potential of AI in remote sensing of the cryosphere, which refers to the portions of the Earth's surface where water is in solid form, including ice sheets, glaciers, snow cover, and permafrost. The incorporation of AI in remote sensing allows the improved monitoring and assessment of the dynamics of the cryosphere. Some of the major milestones of AI in remote sensing of the cryosphere are (a) image classification (e.g., Snow/Ice Detection and Glacier Mapping), (b) Change Detection (e.g., Monitoring Ice Melt and Snow Water Equivalent (SWE) Estimation), (c) Automated Data Processing (e.g., preprocessing, and feature extraction), (d) Climate Modeling and Prediction (e.g., Integration with Climate Models and other relevant datasets), (e) Hazard Assessment (e.g., Glacial Lake Outburst Flood (GLOF) Prediction, snow avalanches, and flash floods), and (f) Data Fusion (e.g., Integration of Multiple Data Sources and Permafrost Thaw Detection). However, these examples are not limited and continuously increasing day by day.