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.
Development of a multiphase chemical mechanism to improve secondary organic aerosol formation in CAABA/MECCA (version 4.7.0)
Felix Wieser, Rolf Sander, Changmin Cho, Hendrik Fuchs, Thorsten Hohaus, Anna Novelli, Ralf Tillmann, and Domenico Taraborrelli
Geosci. Model Dev., 17, 4311–4330, https://doi.org/10.5194/gmd-17-4311-2024, 2024
The chemistry scheme of the atmospheric box model CAABA/MECCA is expanded to achieve an improved aerosol formation from emitted organic compounds. In addition to newly added reactions, temperature-dependent partitioning of all new species between the gas and aqueous phases is estimated and included in the pre-existing scheme. Sensitivity runs show an overestimation of key compounds from isoprene, which can be explained by a lack of aqueous-phase degradation reactions and box model limitations.
Simple process-led algorithms for simulating habitats (SPLASH v.2.0): robust calculations of water and energy fluxes
David Sandoval, Iain Colin Prentice, and Rodolfo L. B. Nóbrega
Geosci. Model Dev., 17, 4229–4309, https://doi.org/10.5194/gmd-17-4229-2024, 2024
Numerous estimates of water and energy balances depend on empirical equations requiring site-specific calibration, posing risks of "the right answers for the wrong reasons". We introduce novel first-principles formulations to calculate key quantities without requiring local calibration, matching predictions from complex land surface models.
VISIR-2: ship weather routing in Python
Gianandrea Mannarini, Mario Leonardo Salinas, Lorenzo Carelli, Nicola Petacco, and Josip Orović
Geosci. Model Dev., 17, 4355–4382, https://doi.org/10.5194/gmd-17-4355-2024, 2024
Ship weather routing has the potential to reduce CO2 emissions, but it currently lacks open and verifiable research. The Python-refactored VISIR-2 model considers currents, waves, and wind to optimise routes. The model was validated, and its computational performance is quasi-linear. For a ferry sailing in the Mediterranean Sea, VISIR-2 yields the largest percentage emission savings for upwind navigation. Given the vessel performance curve, the model is generalisable across various vessel types.
Investigating ground-level ozone pollution in semi-arid and arid regions of Arizona using WRF-Chem v4.4 modeling
Yafang Guo, Chayan Roychoudhury, Mohammad Amin Mirrezaei, Rajesh Kumar, Armin Sorooshian, and Avelino F. Arellano
Geosci. Model Dev., 17, 4331–4353, https://doi.org/10.5194/gmd-17-4331-2024, 2024
This research focuses on surface ozone (O3) pollution in Arizona, a historically air-quality-challenged arid and semi-arid region in the US. The unique characteristics of this kind of region, e.g., intense heat, minimal moisture, and persistent desert shrubs, play a vital role in comprehending O3 exceedances. Using the WRF-Chem model, we analyzed O3 levels in the pre-monsoon month, revealing the model's skill in capturing diurnal and MDA8 O3 levels.
Application of regional meteorology and air quality models based on the microprocessor without interlocked piped stages (MIPS) and LoongArch CPU platforms
Zehua Bai, Qizhong Wu, Kai Cao, Yiming Sun, and Huaqiong Cheng
Geosci. Model Dev., 17, 4383–4399, https://doi.org/10.5194/gmd-17-4383-2024, 2024
There is relatively limited research on the application of scientific computing on RISC CPU platforms. The MIPS architecture CPUs, a type of RISC CPUs, have distinct advantages in energy efficiency and scalability. The air quality modeling system can run stably on the MIPS and LoongArch platforms, and the experiment results verify the stability of scientific computing on the platforms. The work provides a technical foundation for the scientific application based on MIPS and LoongArch.
Insights into the development of a landslide early warning system prototype in an informal settlement: the case of Bello Oriente in Medellín, Colombia
Christian Werthmann, Marta Sapena, Marlene Kühnl, John Singer, Carolina Garcia, Tamara Breuninger, Moritz Gamperl, Bettina Menschik, Heike Schäfer, Sebastian Schröck, Lisa Seiler, Kurosch Thuro, and Hannes Taubenböck
Nat. Hazards Earth Syst. Sci., 24, 1843–1870, https://doi.org/10.5194/nhess-24-1843-2024, 2024
Early warning systems (EWSs) promise to decrease the vulnerability of self-constructed (informal) settlements. A living lab developed a partially functional prototype of an EWS for landslides in a Medellín neighborhood. The first findings indicate that technical aspects can be manageable, unlike social and political dynamics. A resilient EWS for informal settlements has to achieve sufficient social and technical redundancy to maintain basic functionality in a reduced-support scenario.
