The Ross Sea and Amundsen Sea Ice-Sea Model (RAISE v1.0): a high-resolution ocean-sea ice-ice shelf coupling model for simulating the Dense Shelf Water and Antarctic Bottom Water in the Ross Sea, Antarctica
Zhaoru Zhang, Chuan Xie, Chuning Wang, Yuanjie Chen, Heng Hu, and Xiaoqiao Wang
Geosci. Model Dev. Discuss., https//doi.org/10.5194/gmd-2024-128,2024
Preprint under review for GMD (discussion: open, 0 comments)
A coupled fine-resolution ocean-ice model is developed for the Ross Sea and adjacent regions in Antarctica, a key area for the formation of global ocean bottom water — the Antarctic Bottom Water (AABW) that affects the world ocean circulation. The model has high skills in simulating sea ice production driving the AABW source water formation and water mass properties when assessed against observations. A model experiment shows significant impact of ice shelf melting on the AABW characteristics.
The very-high resolution configuration of the EC-Earth global model for HighResMIP
Eduardo Moreno-Chamarro, Thomas Arsouze, Mario Acosta, Pierre-Antoine Bretonnière, Miguel Castrillo, Eric Ferrer, Amanda Frigola, Daria Kuznetsova, Eneko Martin-Martinez, Pablo Ortega, and Sergi Palomas
Geosci. Model Dev. Discuss., https//doi.org/10.5194/gmd-2024-119,2024
Preprint under review for GMD (discussion: open, 1 comment)
We present the high-resolution model version of the EC-Earth global climate model to contribute to HighResMIP. The combined model resolution is about 10-15 km in both the ocean and atmosphere, which makes it one of the finest ever used to complete historical and scenario simulations. This model is compared with two lower-resolution versions, with a 100-km and a 25-km grid. The three models are compared with observations to study the improvements thanks to the increased in the resolution.
Abstract
In the geocenter motion determination using the Global Navigation Satellite Systems (GNSS), satellite clock offsets are usually estimated as white noise process. The correlation between geocenter coordinates (GCC) and the epoch-wise satellite clocks brings inferior GCC estimates, especially for the Z component. In this contribution, satellite clock offsets are described by the polynomial model, and the deviation of the model from the truth is estimated as a random parameter whose process noise is described by the variogram. Based on 3.7 years of BDS, Galileo and GPS observations from 98 global stations, we investigate the impact of the atomic clock model on GCC estimates. After employing the proposed model, the formal errors of GCC-Z component are reduced by 23–46%, 15–31% and 3–9% for BDS, Galileo and GPS, respectively. When the 7-parameter extended empirical CODE orbit model with the a priori box-wing model (BE7) is used, the atomic clock model reduces the correlation of the B1C parameter and GCC-Z component by 0.28, 0.23 and 0.07 for BDS, Galileo and GPS, respectively. Besides, a mitigation of about 60% is obtained at the 3rd and 5th BDS draconitic harmonics and a mitigation of 55% at the 3rd Galileo draconitic harmonic for the GCC-Z component. The proposed model also contributes to reduce the annual amplitudes of single BDS, Galileo and GPS solutions, improving the agreement with the Satellite Laser Ranging solutions. As an additional verification, the resulting satellite orbits are also improved by satellite clock modeling. When the BE7 model is applied, the day boundary discontinuities of daily orbits are reduced by 3.4–3.6%, and the RMS of orbit differences relative to the ESA precise orbits is reduced by 8.2–8.5% for BDS and Galileo.
SummaryInverse problems occur in many fields of geophysics, wherein surface observations are used to infer the internal structure of the Earth. Given the non-linearity and non-uniqueness inherent in these problems, a standard strategy is to incorporate a priori information regarding the unknown model. Sometimes a solution is obtained by imposing that the inverted model remains close to a reference model and with smooth lateral variations (e.g., a correlation length or a minimal wavelength are imposed). This approach forbids the presence of strong gradients or discontinuities in the recovered model. Admittedly, discontinuities, such as interfaces between layers, or shapes of geological provinces or of geological objects such as slabs can be a priori imposed or even suggested by the data themselves. This is however limited to a small set of possible constraints. For example, it would be very challenging and computationally expensive to perform a tomographic inversion where the subducting slabs would have possible top discontinuities with unknown shapes. The problem seems formidable because one cannot even imagine how to sample the prior space: is each specific slab continuous or broken into different portions having their own interfaces? No continuous set of parameters seems to describe all the possible interfaces that we could consider. To circumvent these questions, we propose to train a Generative Adversarial neural Network (GAN) to generate models from a geologically plausible prior distribution obtained from geodynamical simulations. In a Bayesian framework, a Markov chain Monte Carlo algorithm is used to sample the low-dimensional model space depicting the ensemble of potential geological models. This enables the integration of intricate a priori information, parametrized within a low-dimensional model space conducive to efficient sampling. The application of this approach is demonstrated in the context of a downscaling problem, where the objective is to infer small-scale geological structures from a smooth seismic tomographic image.
SummaryThis study examines error propagation from data space to model space during three-dimensional inversion of controlled-source electromagnetic data using a Gauss-Newton based algorithm. An expression for model parameter correction is obtained using higher-order generalised singular value decomposition for various regularisation strategies. Inverse modelling is performed for different types of noise employing distinct regularisation schemes to investigate the impact of error. Data corrupted with random noise suggests that the random noise mainly propagates when regularisation parameters are small, owing to the high-frequency nature of random noise. Furthermore, the random noise predominantly causes artefacts in the shallower part of the inverted model. However, it has little impact on the estimation of major anomalies because the anomaly primarily depends on the smoothly varying parts of data. These observations are valid for both isotropic and anisotropic inversions. Resistive geological anomalies, like vertical dyke or vertical fractures, may pose a significant challenge for isotropic inversion in terms of convergence and data fit, even if the subsurface is isotropic. On the other hand, anisotropic inversion performs remarkably well in such cases, showing faster convergence and better data fit than isotropic inversion. Anisotropic inversion is indispensable in the case of an anisotropic host medium, as isotropic inversion produces significant artefacts and poorer data fit. Numerical experiments suggest that, in general, anisotropic inversion produces relatively better data fit and faster convergence, even in the case of isotropic subsurface. However, due to the varying degree of sensitivity of CSEM data on thin resistive bodies, caution is required in interpreting an anisotropy obtained using anisotropic inversion. An investigation of field data also supports the observations obtained using synthetic experiments.
Nature Geoscience, Published online: 19 July 2024; doi:10.1038/s41561-024-01483-5
Groundwater supplies about 59% of global river flow, suggesting a larger contribution of groundwater to the global water cycle than currently appreciated, according to an analysis integrating estimates from models and observations.
Nature Geoscience, Published online: 19 July 2024; doi:10.1038/s41561-024-01501-6
The increasing use of manufactured sand in China since 2010 has greatly reduced the proportion of natural sand in the country’s total sand supply, from 80% in 1995 to 21% in 2020, according to a material flow analysis of sand in China.
Abstract
Global Navigation Satellite Systems (GNSS) tropospheric tomography is a commonly used technique for the reconstruction of three-dimensional water vapour field, and a priori vertical constraint models are required for water vapour density (WVD) determination which plays a critical role in the quality of tomographic results. However, generalised exponential models were routinely used for vertical constraints and limited research was carried out in the GNSS tomography by taking epoch-by-epoch variations into consideration. In this study, an adaptive four-dimensional (4-D) WVD model for the vertical constraints in GNSS tropospheric tomography was developed based on both ERA5 and surface meteorological data in Hong Kong for each month during the period of 2015–2019, and the back-propagation neural network technique was used to develop the fitting model. Then, the WVD model was used to obtain the WVD of adjacent voxels in the vertical direction to alleviate the mis-representation of the generalised exponential model. The newly developed WVD model used in GNSS tropospheric tomography was validated using GNSS data from the Hong Kong region in the year 2020 and two tomographic epochs (00:00–00:30 UTC and 12:00–12:30 UTC) were evaluated each day. For each topographic epoch, the WVDs of the tomographic voxels including radiosonde profile are evaluated (10 voxels over 10 height layers) using radiosonde data as the reference and the WVDs of all tomographic voxels are evaluated (300 voxels over 10 height layers) using ERA5 data as the reference. Results showed that when radiosonde/ERA5 data were utilized as the references, corresponding monthly mean values of the root mean square errors (RMSEs) in the entire year reduced from 1.97/1.94 g/m3 of the traditional tomographic method to 1.56/1.36 g/m3 of the new method which showed approximately 21/30% improvements. These results suggest a better performance of the tomographic approach using the new WVD model for the vertical constraints proposed by this study by taking epoch-by-epoch information.
Abstract
Twenty-two years (2002–2023) of infrared radiative cooling rate data derived from the SABER instrument on the NASA TIMED satellite are presented. Global daily and global annual infrared power (Watts, W) emitted by nitric oxide (NO) and carbon dioxide (CO2) illustrate the variability of the geospace environment on timescales from days to decades. The 11-year solar cycle (SC) is evident in the global power data and in vertical profiles of infrared cooling rates (nW/m3). The global annual power radiated by NO and CO2 are larger in 2023 than at any time since 2003 and 2002, respectively. The to-date peak in NO infrared power in SC 25 is larger than in SC 24, is comparable to SC 20, but is less than in SCs 18–19 and 21–23. Two geomagnetic storms in 2023 radiated more than 1 TW and are in the top 10 strongest storms observed by SABER.
The Water Table Model (WTM) v2.0.1: Coupled groundwater and dynamic lake modelling
Kerry L. Callaghan, Andrew D. Wickert, Richard Barnes, and Jacqueline Austermann
Geosci. Model Dev. Discuss., https//doi.org/10.5194/gmd-2024-131,2024
Preprint under review for GMD (discussion: open, 2 comments)
We present the Water Table Model (WTM), which simulates groundwater and lake levels at continental scales over millennia. Our simulations show that North America held more ground- and lake-water at the Last Glacial Maximum than in the present day – enough to lower sea level by 6 cm. We also simulate the changing water table from 21,000 to 16,000 years ago, finding that groundwater storage decreased following reduced precipitation in the model inputs. Open-source WTM code is available on Github.
Dartmouth researchers are using computational mathematics and machine learning to develop models that better predict sea ice thickness in regions of the Arctic.
Abstract
The present paper develops a new framework to predict the mean flow through an array of cylinders in which the flow around the array (array-scale) and the flow around individual cylinders (element-scale) are modeled separately using actuator disc theory and empirical drag models respectively, and then coupled through the net drag force. Applying this framework only requires knowledge of the array geometry and incident flow. The framework is validated using high-fidelity direct numerical simulations for arrays of between 7 and 109 cylinders having different arrangements (staggered, concentric, random) and bounding shapes (circular, square) in both two- and three-dimensional flows. In general, the framework outperforms existing models which require calibration and are only valid for part of the practical parameter space. The demonstrated scale separation suggests different combinations of element-scale and array-scale models/theories may be used for other arrangements of bluff bodies.
Abstract
The Lhasa-Qiangtang collision closed the Meso-Tethys Ocean, but the exact timing of this event remains hotly debated. Here, we present geochronological and paleomagnetic analyses conducted on Cretaceous volcanics from western Qiangtang to constrain the Lhasa-Qiangtang collision in western Tibet. Our investigations yield a paleolatitude of ∼30.5 ± 5.0°N for western Qiangtang during ca. 110–100 Ma. A reanalysis of previously acquired Mesozoic-Cenozoic paleomagnetic data from western Qiangtang suggests a stationary position during ca. 136–34 Ma. Examination of paleomagnetic data from western Lhasa reveals a significant reduction in northward paleolatitudinal motion during the Early Cretaceous, dropping from ∼12.3 cm/yr to nearly zero. Integration of our paleomagnetic findings with available geological records has led to conclude that the Lhasa-Qiangtang collision in western Tibet occurred at ca. 132 Ma. Additionally, we infer that crustal shortening on the order of ∼1,000 km happened between Lhasa and Qiangtang during the Early Cenozoic.
Abstract
Mock-Walker simulations have the potential to play a key role in a tropical model hierarchy, bridging small-scale Radiative-Convective Equilibrium simulations and global models of tropical circulations. We demonstrate that mock-Walker simulations transition from single- to double-celled overturning circulations as mean Sea Surface Temperature (SST) is increased, with the transition occurring near 300 K. The transition is robust to domain geometry and microphysical scheme, and is favored by larger SST gradients. The transition is associated with the development of a mid-tropospheric minimum in the radiative-subsidence velocity over the cold pool of the simulations, and is likely reinforced by zonal moisture and temperature fluxes between the warm and cold pools. Several methods of suppressing the transition are investigated, but all set-ups produce a double-cell at sufficiently warm mean SSTs. The striking dynamical transition of mock-Walker simulations dominates their response to warming, though its relevance for observed tropical climate change is unclear.
A new tool that can be used to predict the emergence of unusually large and unpredictable waves at sea—known as rogue waves—up to five minutes into the future is presented in a study published in Scientific Reports. The authors suggest that the tool could be used to issue advance warnings to ships and offshore platforms to enable those working on them to seek shelter, perform emergency shutdowns, or maneuver to minimize the impacts of approaching rogue waves.
Precipitation extremes in Ukraine from 1979 to 2019: climatology, large-scale flow conditions, and moisture sources
Ellina Agayar, Franziska Aemisegger, Moshe Armon, Alexander Scherrmann, and Heini Wernli
Nat. Hazards Earth Syst. Sci., 24, 2441–2459, https://doi.org/10.5194/nhess-24-2441-2024, 2024
This study presents the results of a climatological investigation of extreme precipitation events (EPEs) in Ukraine for the period 1979–2019. During all seasons EPEs are associated with pronounced upper-level potential vorticity (PV) anomalies. In addition, we find distinct seasonal and regional differences in moisture sources. Several extreme precipitation cases demonstrate the importance of these processes, complemented by a detailed synoptic analysis.
Author(s): W. Fox, G. Fiksel, D. B. Schaeffer, and J. Griff-McMahon
Proton deflectometry is used in magnetized high-energy-density plasmas to observe electromagnetic fields. We describe a reconstruction algorithm to recover the electromagnetic fields from proton fluence data in 1-D. The algorithm is verified against analytic solutions and applied to example data. Ne…
[Phys. Rev. E 110, 015206] Published Thu Jul 18, 2024
Abstract
Snow is the most reflective natural surface on Earth. Since fresh snow on bare sea ice increases the surface albedo, the impact of summer snow accumulation can have a negative radiative forcing effect, which would inhibit sea ice surface melt and potentially slow sea-ice loss. However, it is not well known how often, where, and when summer snowfall events occur on Arctic sea ice. In this study, we used in situ and model snow depth data paired with surface albedo and atmospheric conditions from satellite retrievals to characterize summer snow accumulation on Arctic sea ice from 2003 to 2017. We found that, across the Arctic, ∼2 snow accumulation events occurred on initially snow-free conditions each year. The average snow depth and albedo increases were ∼2 cm and 0.08, respectively. 16.5% of the snow accumulation events were optically thick (>3 cm deep) and lasted 2.9 days longer than the average snow accumulation event (3.4 days). Based on a simple, multiple scattering radiative transfer model, we estimated a −0.086 ± 0.020 W m−2 change in the annual average top-of-the-atmosphere radiative forcing for summer snowfall events in 2003–2017. The following work provides new information on the frequency, distribution, and duration of observed snow accumulation events over Arctic sea ice in summer. Such results may be particularly useful in understanding the impacts of ephemeral summer weather on surface albedo and their propagating effects on the radiative forcing over Arctic sea ice, as well as assessing climate model simulations of summer atmosphere-ice processes.
Northwestern University-led researchers have discovered a new way that nature cycles phosphorus, a finding that uncovers a missing piece of Earth's puzzling phosphorus cycle.
