Abstract: Lévy noise versus Gaussian-noise-induced transitions in the Ghil–Sellers energy balance model Valerio Lucarini, Larissa Serdukova, and Georgios Margazoglou Nonlin. Processes Geophys., 29, 183–205, https://doi.org/10.5194/npg-29-183-2022, 2022 In most of the investigations on metastable systems, the stochastic forcing is modulated by Gaussian noise. Lévy noise laws, which describe jump processes, have recently received a lot of attention, but much less is known. We study stochastic versions of the Ghil–Sellers energy balance model, and we highlight the fundamental difference between how transitions are performed between the competing warm and snowball states, depending on whether Gaussian or Lévy noise acts as forcing. PubDate: Wed, 11 May 2022 10:18:50 +020 DOI: 10.5194/npg-29-183-2022 2022
Abstract: Using neural networks to improve simulations in the gray zone Raphael Kriegmair, Yvonne Ruckstuhl, Stephan Rasp, and George Craig Nonlin. Processes Geophys., 29, 171–181, https://doi.org/10.5194/npg-29-171-2022, 2022 Our regional numerical weather prediction models run at kilometer-scale resolutions. Processes that occur at smaller scales not yet resolved contribute significantly to the atmospheric flow. We use a neural network (NN) to represent the unresolved part of physical process such as cumulus clouds. We test this approach on a simplified, yet representative, 1D model and find that the NN corrections vastly improve the model forecast up to a couple of days. PubDate: Mon, 02 May 2022 14:28:25 +020 DOI: 10.5194/npg-29-171-2022 2022
Abstract: Estimate of energy loss from internal solitary waves breaking on slopes Kateryna Terletska and Vladimir Maderich Nonlin. Processes Geophys., 29, 161–170, https://doi.org/10.5194/npg-29-161-2022, 2022 Internal solitary waves (ISWs) emerge in the ocean and seas in various forms and break on the shelf zones in a variety of ways. This results in intensive mixing that affects processes such as biological productivity and sediment transport. Mechanisms of wave interaction with slopes are related to breaking and changing polarity. Our study focuses on wave transformation over idealized shelf-slope topography using a two-layer stratification. Four types of ISW transformation over slopes are shown. PubDate: Thu, 07 Apr 2022 17:38:59 +020 DOI: 10.5194/npg-29-161-2022 2022
Abstract: Regional study of mode-2 internal solitary waves at the Pacific coast of Central America using marine seismic survey data Wenhao Fan, Haibin Song, Yi Gong, Shun Yang, and Kun Zhang Nonlin. Processes Geophys., 29, 141–160, https://doi.org/10.5194/npg-29-141-2022, 2022 Compared with mode-1 internal solitary waves (ISWs), mode-2 ISWs in the ocean require further study. A mass of mode-2 ISWs developing at the Pacific coast of Central America have been imaged using seismic reflection data. We find that the relationship between the mode-2 ISW propagation speed and amplitude is diverse. It is affected by seawater depth, pycnocline depth, and pycnocline thickness. The ISW vertical amplitude structure is affected by the ISW nonlinearity and the pycnocline deviation. PubDate: Mon, 04 Apr 2022 17:38:59 +020 DOI: 10.5194/npg-29-141-2022 2022
Abstract: Using a Hybrid Optimal Interpolation-Ensemble Kalman Filter for the Canadian Precipitation Analysis Dikraa Khedhaouiria, Stéphane Bélair, Vincent Fortin, Guy Roy, and Franck Lespinas Nonlin. Processes Geophys. Discuss., https//doi.org/10.5194/npg-2022-10,2022 Preprint under review for NPG (discussion: open, 0 comments) This study introduces a well-known use of hybrid methods in data assimilation (DA) algorithms yet not explored for precipitation analyses. Our approach combined an ensemble-based DA approach with an existing deterministically based DA. Both DA scheme families have desirable aspects that can be leveraged if combined. The DA hybrid method showed better precipitation analyses in regions with a low rate of assimilated surface observations, which is typically the case in winter. PubDate: Mon, 04 Apr 2022 17:38:59 +020 DOI: 10.5194/npg-2022-102022
Abstract: Control simulation experiment with Lorenz's butterfly attractor Takemasa Miyoshi and Qiwen Sun Nonlin. Processes Geophys., 29, 133–139, https://doi.org/10.5194/npg-29-133-2022, 2022 The weather is chaotic and hard to predict, but the chaos implies an effective control where a small control signal grows rapidly to make a big difference. This study proposes a control simulation experiment where we apply a small signal to control nature in a computational simulation. Idealized experiments with a low-order chaotic system show successful results by small control signals of only 3 % of the observation error. This is the first step toward realistic weather simulations. PubDate: Mon, 28 Mar 2022 14:35:48 +020 DOI: 10.5194/npg-29-133-2022 2022
Abstract: Characteristics of intrinsic non-stationarity and its effect on eddy-covariance measurements of CO2 fluxes Lei Liu, Yu Shi, and Fei Hu Nonlin. Processes Geophys., 29, 123–131, https://doi.org/10.5194/npg-29-123-2022, 2022 We find a new kind of non-stationarity. This new kind of non-stationarity is caused by the intrinsic randomness. Results show that the new kind of non-stationarity is widespread in small-scale variations of CO2 turbulent fluxes. This finding reminds us that we need to handle the short-term averaged turbulent fluxes carefully, and we also need to re-screen the existing non-stationarity diagnosis methods because they could make a wrong diagnosis due to this new kind of non-stationarity. PubDate: Thu, 24 Mar 2022 07:28:47 +010 DOI: 10.5194/npg-29-123-2022 2022
Abstract: Fortnight conditioning of historical data to improve short-term precipitation predictions Yoshito Hirata and Yoshinori Yamada Nonlin. Processes Geophys. Discuss., https//doi.org/10.5194/npg-2022-9,2022 Preprint under review for NPG (discussion: open, 0 comments) We show that there exists some complicated days-of-week effects in precipitation at Tokyo. By using the effects, we could improve short-term precipitation forecasts up to 2 hours ahead. PubDate: Tue, 08 Mar 2022 14:49:34 +010 DOI: 10.5194/npg-2022-92022
Abstract: Applying prior correlations for ensemble-based spatial localization Chu-Chun Chang and Eugenia Kalnay Nonlin. Processes Geophys. Discuss., https//doi.org/10.5194/npg-2022-5,2022 Preprint under review for NPG (discussion: open, 0 comments) This study introduces a new approach for optimizing the model initialization process, effectively reducing unrealistic error estimations and improving weather prediction. Our method uses the prescribed error correlations to limit the observation usage during the model initialization. The experiment results on the simplified atmosphere model show that our method has a similar performance as the traditional method, while it is better in the early stage and is more computationally efficient. PubDate: Tue, 01 Mar 2022 04:25:33 +010 DOI: 10.5194/npg-2022-52022
Abstract: Fractional relaxation noises, motions and the fractional energy balance equation Shaun Lovejoy Nonlin. Processes Geophys., 29, 93–121, https://doi.org/10.5194/npg-29-93-2022, 2022 The difference between the energy that the Earth receives from the Sun and the energy it emits as black-body radiation is stored in a scaling hierarchy of structures in the ocean, soil and hydrosphere. The simplest scaling storage model leads to the fractional energy balance equation (FEBE). We examine the statistical properties of FEBE when it is driven by random fluctuations. In this paper, we explore the statistical properties of this mathematically simple yet neglected equation. PubDate: Fri, 25 Feb 2022 14:02:52 +010 DOI: 10.5194/npg-29-93-2022 2022
Abstract: Adaptive Smoothing of the Ensemble Mean of Climate Model Output for Improved Projections of Future Rainfall Stephen Jewson, Giuliana Barbato, Paola Mercogliano, and Maximiliano Sassi Nonlin. Processes Geophys. Discuss., https//doi.org/10.5194/npg-2022-7,2022 Preprint under review for NPG (discussion: open, 0 comments) It may be possible to make climate model projections more precise using spatial smoothing. We introduce a new spatial smoothing method that differs from previously used methods in that it varies the amount of smoothing by location. For the European rainfall projections we apply the method to, we show that the new method is three times more effective than standard smoothing methods. This improved precision may benefit applications of climate model projections. PubDate: Tue, 22 Feb 2022 14:02:52 +010 DOI: 10.5194/npg-2022-72022
Abstract: Ensemble Riemannian data assimilation: towards large-scale dynamical systems Sagar K. Tamang, Ardeshir Ebtehaj, Peter Jan van Leeuwen, Gilad Lerman, and Efi Foufoula-Georgiou Nonlin. Processes Geophys., 29, 77–92, https://doi.org/10.5194/npg-29-77-2022, 2022 The outputs from Earth system models are optimally combined with satellite observations to produce accurate forecasts through a process called data assimilation. Many existing data assimilation methodologies have some assumptions regarding the shape of the probability distributions of model output and observations, which results in forecast inaccuracies. In this paper, we test the effectiveness of a newly proposed methodology that relaxes such assumptions about high-dimensional models. PubDate: Fri, 18 Feb 2022 14:14:14 +010 DOI: 10.5194/npg-29-77-2022 2022
Abstract: An approach for constraining mantle viscosities through assimilation of palaeo sea level data into a glacial isostatic adjustment model Reyko Schachtschneider, Jan Saynisch-Wagner, Volker Klemann, Meike Bagge, and Maik Thomas Nonlin. Processes Geophys., 29, 53–75, https://doi.org/10.5194/npg-29-53-2022, 2022 Glacial isostatic adjustment is the delayed reaction of the Earth's lithosphere and mantle to changing mass loads of ice sheets or water. The deformation behaviour of the Earth's surface depends on the ability of the Earth's mantle to flow, i.e. its viscosity. It can be estimated from sea level observations, and in our study, we estimate mantle viscosity using sea level observations from the past. This knowledge is essential for understanding current sea level changes due to melting ice. PubDate: Thu, 17 Feb 2022 14:14:14 +010 DOI: 10.5194/npg-29-53-2022 2022
Abstract: Direct Bayesian model reduction of smaller scale convective activity conditioned on large-scale dynamics Robert Polzin, Annette Müller, Henning Rust, Peter Névir, and Péter Koltai Nonlin. Processes Geophys., 29, 37–52, https://doi.org/10.5194/npg-29-37-2022, 2022 In this study, a recent algorithmic framework called Direct Bayesian Model Reduction (DBMR) is applied which provides a scalable probability-preserving identification of reduced models directly from data. The stochastic method is tested in a meteorological application towards a model reduction to latent states of smaller scale convective activity conditioned on large-scale atmospheric flow. PubDate: Wed, 16 Feb 2022 14:14:14 +010 DOI: 10.5194/npg-29-37-2022 2022
Abstract: How many modes are needed to predict climate bifurcations' Lessons from an experiment Bérengère Dubrulle, François Daviaud, Davide Faranda, Louis Marié, and Brice Saint-Michel Nonlin. Processes Geophys., 29, 17–35, https://doi.org/10.5194/npg-29-17-2022, 2022 Present climate models discuss climate change but show no sign of bifurcation in the future. Is this because there is none or because they are in essence too simplified to be able to capture them' To get elements of an answer, we ran a laboratory experiment and discovered that the answer is not so simple. PubDate: Mon, 07 Feb 2022 14:14:14 +010 DOI: 10.5194/npg-29-17-2022 2022
Abstract: Predicting Sea Surface Temperatures with Coupled Reservoir Computers Benjamin Walleshauser and Erik Bollt Nonlin. Processes Geophys. Discuss., https//doi.org/10.5194/npg-2022-4,2022 Preprint under review for NPG (discussion: open, 0 comments) As sea surface temperature is vital towards understanding the greater climate of the Earth and an important variable in weather prediction, we propose a model that effectively capitalizes on the reduced complexity of machine learning models while still being able to efficiently predict over a large spatial domain. We find that it is proficient at predicting the sea surface temperature at specific locations, as well as over the greater domain of the Earth’s oceans. PubDate: Wed, 02 Feb 2022 14:14:14 +010 DOI: 10.5194/npg-2022-42022
Abstract: Effects of Rotation and Topography on Internal Solitary Waves Governed by the Rotating-Gardner Equation Karl Helfrich and Lev Ostrovsky Nonlin. Processes Geophys. Discuss., https//doi.org/10.5194/npg-2022-3,2022 Preprint under review for NPG (discussion: open, 0 comments) This paper studies internal solitary waves (ISWs) in the ocean under simultaneous action of the main defining factors: nonlinearity (quadratic and cubic), earth rotation, and depth variation. Both analytical (adiabatic) theory and numerical simulation are used in the study. The results show a complex interplay of the factors mentioned above that can result in amplification of the ISW or, on the contrary, its destruction. The calculations are made for realistic oceanic parameters. PubDate: Fri, 21 Jan 2022 14:14:14 +010 DOI: 10.5194/npg-2022-32022
Abstract: Climate Bifurcations in a Schwarzschild Equation Model of the Arctic Atmosphere Kolja L. Kypke, William F. Langford, Gregory M. Lewis, and Allan R. Willms Nonlin. Processes Geophys. Discuss., https//doi.org/10.5194/npg-2022-2,2022 Preprint under review for NPG (discussion: open, 0 comments) Climate change is causing rapid temperature increases in the polar regions. A fundamental question is whether these temperature increases are reversible. If we control carbon dioxide emissions will the temperatures revert, or will we have passed a tipping point beyond which return to the present state is impossible' Our mathematical model of the Arctic climate indicates that under present emissions the Arctic climate will change irreversibly to a warm climate before the end of the century. PubDate: Wed, 19 Jan 2022 04:57:59 +010 DOI: 10.5194/npg-2022-22022
Abstract: Rigid Sets and Coherent Sets in Realistic Ocean Flows Florian Feppon and Pierre Lermusiaux Nonlin. Processes Geophys. Discuss., https//doi.org/10.5194/npg-2022-1,2022 Preprint under review for NPG (discussion: open, 0 comments) We develop and showcase new methods to extract Lagrangian Coherent Sets from ocean flow data and simulations. The first method extracts “rigid sets” defined as ocean regions that evolve almost as a rigid object. The second method is a matrix-free methodology that provides a simple and efficient framework to compute “coherent sets” with operator methods. We showcase results using three numerically simulated flow examples, including complex ocean current fields in the Palau Island region. PubDate: Wed, 12 Jan 2022 15:01:54 +010 DOI: 10.5194/npg-2022-12022
Abstract: A waveform skewness index for measuring time series nonlinearity and its applications to the ENSO–Indian monsoon relationship Justin Schulte, Frederick Policelli, and Benjamin Zaitchik Nonlin. Processes Geophys., 29, 1–15, https://doi.org/10.5194/npg-29-1-2022, 2022 The skewness of a time series is commonly used to quantify the extent to which positive (negative) deviations from the mean are larger than negative (positive) ones. However, in some cases, traditional skewness may not provide reliable information about time series skewness, motivating the development of a waveform skewness index in this paper. The waveform skewness index is used to show that changes in the relationship strength between climate time series could arise from changes in skewness. PubDate: Mon, 10 Jan 2022 15:01:54 +010 DOI: 10.5194/npg-29-1-2022 2022
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