A lightweight holographic imager for cloud microphysical studies from an untethered balloon
Thomas Edward Chambers, Iain Murray Reid, and Murray Hamilton
Atmos. Meas. Tech., 17, 3237–3253, https://doi.org/10.5194/amt-17-3237-2024, 2024
Clouds have been identified as the largest source of uncertainty in climate modelling. We report an untethered balloon launch of a holographic imager through clouds. This is the first time a holographic imager has been deployed in this way, enabled by the light weight and low cost of the imager. This work creates the potential to significantly increase the availability of cloud microphysical measurements required for the calibration and validation of climate models and remote sensing methods.
An improved and extended parameterization of the CO2 15 µm cooling in the middle and upper atmosphere (CO2_cool_fort-1.0)
Manuel López-Puertas, Federico Fabiano, Victor Fomichev, Bernd Funke, and Daniel R. Marsh
Geosci. Model Dev., 17, 4401–4432, https://doi.org/10.5194/gmd-17-4401-2024, 2024
The radiative infrared cooling of CO2 in the middle atmosphere is crucial for computing its thermal structure. It requires one however to include non-local thermodynamic equilibrium processes which are computationally very expensive, which cannot be afforded by climate models. In this work, we present an updated, efficient, accurate and very fast (~50 µs) parameterization of that cooling able to cope with CO2 abundances from half the pre-industrial values to 10 times the current abundance.
Abstract
State-of-the-art climate models simulate a large spread in the mean-state Atlantic meridional overturning circulation (AMOC), with strengths varying between 12 and 25 Sv. Here, we introduce a framework for understanding this spread by assessing the balance between the thermal-wind expression and surface water mass transformation in the North Atlantic. The intermodel spread in the mean-state AMOC strength is shown to be related to the overturning scale depth: climate models with a larger scale depth tend to have a stronger AMOC. We present a physically motivated scaling relationship that links intermodel variations in the scale depth to surface buoyancy fluxes and stratification in the North Atlantic, and thus connects North Atlantic surface processes to the interior overturning circulation. Climate models with a larger scale depth tend to have stronger surface buoyancy loss and weaker stratification in the North Atlantic. These results offer a framework for reducing mean-state AMOC biases in climate models.
No abstract is available for this article.
Abstract
The southern portion of the eastern North American margin (SENAM) is an archetypical volcanic passive margin formed during Mesozoic rifting. How past magmatic events affect the evolution of the SENAM remains an open question of fundamental importance. To better understand this question, here we construct a high-resolution 3-D crustal velocity model from the oceanic side to the continental interior with a combination of multimodal dispersion inversion and full-waveform ambient noise tomography. Our new model reveals an oceanic-continental transitional crust over a short horizonal distance of 100–150 km across the SENAM, with a local-scale lower-than-surrounding velocity anomaly directly beneath the transitional crust. Furthermore, the new model shows three intra-crustal higher-than-average velocity anomalies beneath the SENAM continent. We suggest that the magmatism assisted the Mesozoic rifting process to form the narrow ocean-continent transitional crust along the coastline. The underplating of magma beneath the transitional crust led to a reduction of seismic velocity of the uppermost mantle. In addition, it is probable that the emplacement of the Central Atlantic Magmatic Province caused widespread magmatic intrusions within the continental crust of the SENAM, which were later solidified into intra-crustal high-velocity plutons. Our findings provide new insights into crustal modification history at the passive margin.
Abstract
De-aliasing products are used in the estimation process of satellite-based gravity field computation to reduce errors from high-frequency mass variations that alias into monthly gravity fields. The latest official product is AOD1B RL07 and describes non-tidal atmosphere and oceanic mass variations at 3-hourly resolution. However, the model-based de-aliasing products are inevitably incomplete and prone to temporally and spatially correlated errors that substantially contribute to errors in the estimated gravity fields. Here, we investigate possible enhancement of current de-aliasing products by nesting a regional high-resolution atmospheric reanalysis over Europe into a global reanalysis. As further novelty we include almost mass consistent terrestrial water storage variability from a regional hydrological model nested into a global model as additional component of the de-aliasing product. While we find in agreement with earlier studies only minor contributions from increasing the temporal resolution beyond 3-hourly data, our investigations suggest that contributions from continental hydrology and from regional non-hydrostatic atmospheric modeling to sub-monthly mass variations could be relevant already for gravity fields estimated from current gravity missions. Moreover, in the context of extreme events, we find regionally contributions from additional moisture fields, such as cloud liquid water, in the order of a few mm over Europe. We suggest this needs to be taken into account when preparing data analysis schemes for future space gravimetric missions.
Abstract
Mass movements and delta collapses are significant sources of tsunamis in lacustrine environments, impacting human societies enormously. Paleotsunamis studies play an essential role in understanding historical events and their consequences, along with their return periods. This study investigates a paleotsunami induced by a subaqueous mass movement during the Younger Dryas to Early Holocene transition, ca. 11,700 years ago in Lake Aiguebelette (NW Alps, France). Utilizing high-resolution seismic and bathymetric surveys associated with sedimentological, geochemical, and magnetic analyses, we uncovered a paleotsunami triggered by a seismically induced mass transport deposit. Numerical simulations of mass movement have been conducted using a visco-plastic Herschel-Bulkley rheological model and corresponding tsunami wave modeled with dispersive and nondispersive models. Our findings reveal for the first time that dispersive effects may be negligible for subaqueous landslides in a relatively small lake. This research reconstructs a previously unreported paleotsunami event and enhances our understanding of tsunami dynamics in lacustrine environments.
Use of an uncrewed aerial system to investigate aerosol direct and indirect radiative forcing effects in the marine atmosphere
Patricia K. Quinn, Timothy S. Bates, Derek J. Coffman, James E. Johnson, and Lucia M. Upchurch
Atmos. Meas. Tech., 17, 3157–3170, https://doi.org/10.5194/amt-17-3157-2024, 2024
An uncrewed aerial observing system has been developed for the measurement of vertical profiles of aerosol and cloud properties that affect Earth's radiation balance. The system was successfully deployed from a ship and from a coastal site and flown autonomously up to 3050 m and for 4.5 h. These results indicate the potential of the observing system to make routine, operational flights from ships and land to characterize aerosol interactions with radiation and clouds.
Observing atmospheric rivers using GNSS radio occultation data
Bahareh Rahimi and Ulrich Foelsche
Atmos. Meas. Tech. Discuss., https://doi.org/10.5194/amt-2024-81,2024
Preprint under review for AMT (discussion: open, 0 comments)
This study explores the use of GNSS-RO data to improve understanding of the vertical structure of humidity in Atmospheric Rivers (ARs). Specific humidity profiles and IWV values from GNSS-RO are evaluated to assess if this method offers additional insights into ARs' vertical characteristics. The results suggest that combining GNSS-RO data, with its high vertical resolution, with SSMI/S data, known for high horizontal resolution, provides a more complete view of the 3D structure of ARs.
Assessment of Operational Non-Time Critical Sentinel-6A Michael Freilich Radio Occultation Data: Insights into Tropospheric GNSS Signal Cutoff Strategies and Processor Improvements
Saverio Paolella, Axel Von Engeln, Sebastiano Padovan, Riccardo Notarpietro, Christian Marquardt, Francisco Sancho, Veronica Rivas Boscan, Nicolas Morew, and Francisco Martin Alemany
Atmos. Meas. Tech. Discuss., https://doi.org/10.5194/amt-2024-82,2024
Preprint under review for AMT (discussion: open, 0 comments)
This study evaluates the ability of the EUMETSAT Sentinel-6A RO-NTC processor to provide high quality bending angle profiles. The analysis spans from the signals SNR and phase noise to the determination of the optimal signals cut-off points in the tropospheric region. Some processor enhancements and the impact on the data quality is also discussed. Data were compared against ECMWF confirming the ability of the EUMETSAT RO processors in maintaining consistent and high-quality data.
A new approach to crystal habit retrieval from far-infrared spectral radiance measurements
Gianluca Di Natale, Marco Ridolfi, and Luca Palchetti
Atmos. Meas. Tech., 17, 3171–3186, https://doi.org/10.5194/amt-17-3171-2024, 2024
This work aims to define a new approach to retrieve the distribution of the main ice crystal shapes occurring inside ice and cirrus clouds from infrared spectral measurements. The capability of retrieving these shapes of the ice crystals from satellites will allow us to extend the currently available climatologies to be used as physical constraints in general circulation models. This could could allow us to improve their accuracy and prediction performance.
Permutation entropy and complexity analysis of large-scale solar wind structures and streams
Emilia K. J. Kilpua, Simon Good, Matti Ala-Lahti, Adnane Osmane, and Venla Koikkalainen
Ann. Geophys., 42, 163–177, https://doi.org/10.5194/angeo-42-163-2024, 2024
The solar wind is organised into slow and fast streams, interaction regions, and transient structures originating from solar eruptions. Their internal characteristics are not well understood. A more comprehensive understanding of such features can give insight itno physical processes governing their formation and evolution. Using tools from information theory, we find that the solar wind shows universal turbulent properties on smaller scales, while on larger scales, clear differences arise.
GEOMAPLEARN 1.0: Detecting geological structures from geological maps with machine learning
David Oakley, Christelle Loiselet, Thierry Coowar, Vincent Labbe, and Jean-Paul Callot
Geosci. Model Dev. Discuss., https//doi.org/10.5194/gmd-2024-35,2024
Preprint under review for GMD (discussion: open, 0 comments)
In this work, we develop two automated workflows for identifying fold structures on geological maps using machine learning. In one method, we identify map patterns suggestive of folding based on pre-defined rules and apply a clustering algorithm to group those from the same fold together. In the other, we train a convolutional neural network to identify folds based on a set of training examples. We apply both methods to a set of synthetic maps and to real-world maps from two locations in France.
Learning from conceptual models – a study of emergence of cooperation towards resource protection in a social-ecological system
Saeed Harati-Asl, Liliana Perez, and Roberto Molowny-Horas
Geosci. Model Dev. Discuss., https//doi.org/10.5194/gmd-2024-57,2024
Preprint under review for GMD (discussion: open, 0 comments)
Social-ecological systems are the subject of many sustainability problems. Because of the complexity of these systems we must be careful when intervening in them, otherwise we may cause irreversible damage. Using computer models, we can gain insight about these complex systems without harming them. In this paper we describe how we connected an ecological model of forest insect infestation with a social model of cooperation, and simulated an intervention measure to save a forest from infestation.
Autoencoder-based feature extraction for the automatic detection of snow avalanches in seismic data
Andri Simeon, Cristina Pérez-Guillén, Michele Volpi, Christine Seupel, and Alec van Herwijnen
Geosci. Model Dev. Discuss., https//doi.org/10.5194/gmd-2024-76,2024
Preprint under review for GMD (discussion: open, 0 comments)
Avalanche seismic detection systems are key for forecasting, but distinguishing avalanches from other seismic sources remains challenging. We propose novel autoencoder models to automatically extract features and compare them with standard seismic attributes. These features are then used to classify avalanches and noise events. The autoencoder feature classifiers have the highest sensitivity to detect avalanches, while the standard seismic classifier performs better overall.
Comparison of the Coastal and Regional Ocean COmmunity model (CROCO) and NCAR-LES in non-hydrostatic simulations
Xiaoyu Fan, Baylor Fox-Kemper, Nobuhiro Suzuki, Qing Li, Patrick Marchesiello, Peter P. Sullivan, and Paul S. Hall
Geosci. Model Dev., 17, 4095–4113, https://doi.org/10.5194/gmd-17-4095-2024, 2024
Simulations of the oceanic turbulent boundary layer using the nonhydrostatic CROCO ROMS and NCAR-LES models are compared. CROCO and the NCAR-LES are accurate in a similar manner, but CROCO’s additional features (e.g., nesting and realism) and its compressible turbulence formulation carry additional costs.
Enhancing mobile aerosol monitoring with CE376 dual-wavelength depolarization lidar
Maria Fernanda Sanchez Barrero, Ioana Elisabeta Popovici, Philippe Goloub, Stephane Victori, Qiaoyun Hu, Benjamin Torres, Thierry Podvin, Luc Blarel, Gaël Dubois, Fabrice Ducos, Eric Bourrianne, Aliaksandr Lapionak, Lelia Proniewski, Brent Holben, David Matthew Giles, and Anthony LaRosa
Atmos. Meas. Tech., 17, 3121–3146, https://doi.org/10.5194/amt-17-3121-2024, 2024
This study showcases the use of a compact elastic lidar to monitor aerosols aboard moving platforms. By coupling dual-wavelength and depolarization measurements with photometer data, we studied aerosols during events of Saharan dust and smoke transport. Our research, conducted in various scenarios, not only validated our methods but also offered insights into the atmospheric dynamics near active fires. This study aids future research to fill observational gaps in aerosol monitoring.
Aerosol trace element solubility determined using ultrapure water batch leaching: an intercomparison study of four different leaching protocols
Rui Li, Prema Piyusha Panda, Yizhu Chen, Zhenming Zhu, Fu Wang, Yujiao Zhu, He Meng, Yan Ren, Ashwini Kumar, and Mingjin Tang
Atmos. Meas. Tech., 17, 3147–3156, https://doi.org/10.5194/amt-17-3147-2024, 2024
We found that for ultrapure water batch leaching, the difference in specific experimental parameters, including agitation methods, filter pore size, and contact time, only led to a small and sometimes insignificant difference in determined aerosol trace element solubility. Furthermore, aerosol trace element solubility determined using four common ultrapure water leaching protocols showed good agreement.
Simulations of Snow Physicochemical Properties in Northern China using WRF-Chem
Xia Wang, Tao Che, Xueyin Ruan, Shanna Yue, Jing Wang, Chun Zhao, and Lei Geng
Geosci. Model Dev. Discuss., https//doi.org/10.5194/gmd-2024-37,2024
Preprint under review for GMD (discussion: open, 0 comments)
We employed the WRF-Chem model to parameterize atmospheric nitrate deposition in snow and evaluated its performance in simulating snow cover, snow depth, and concentrations of black carbon (BC), dust, and nitrate using new observations from Northern China. The results generally exhibit reasonable agreement with field observations in northern China, demonstrating the model's capability to simulate snow properties, including concentrations of reservoir species.
The Multi-Compartment Hg Modeling and Analysis Project (MCHgMAP): Mercury modeling to support international environmental policy
Ashu Dastoor, Hélène Angot, Johannes Bieser, Flora Brocza, Brock Edwards, Aryeh Feinberg, Xinbin Feng, Benjamin Geyman, Charikleia Gournia, Yipeng He, Ian M. Hedgecock, Ilia Ilyin, Terry Keating, Jane Kirk, Che-Jen Lin, Igor Lehnherr, Robert Mason, David McLagan, Marilena Muntean, Peter Rafaj, Eric M. Roy, Andrei Ryjkov, Noelle E. Selin, Francesco De Simone, Anne L. Soerensen, Frits Steenhuisen, Oleg Travnikov, Shuxiao Wang, Xun Wang, Simon Wilson, Rosa Wu, Qingru Wu, Yanxu Zhang, Jun Zhou, Wei Zhu, and Scott Zolkos
Geosci. Model Dev. Discuss., https//doi.org/10.5194/gmd-2024-65,2024
Preprint under review for GMD (discussion: open, 1 comment)
This paper introduces the Multi-Compartment Mercury (Hg) Modeling and Analysis Project (MCHgMAP) aimed to inform the effectiveness evaluations of two multilateral environmental agreements: the Minamata Convention on Mercury and Convention on Long-Range Transboundary Air Pollution. The experimental design exploits a variety of models (atmospheric, land, oceanic and multi-media mass balance models) to assess the short- and long-term influences of anthropogenic Hg releases in the environment.
