Nonlinear Processes in Geophysics最新文献

{"title":"Stability and uncertainty assessment of geoelectrical resistivity model parameters: a new hybrid metaheuristic algorithm and posterior probability density function approach","authors":"Kuldeep Sarkar, Jit V. Tiwari, Upendra K. Singh","doi":"10.5194/npg-31-7-2024","DOIUrl":"https://doi.org/10.5194/npg-31-7-2024","url":null,"abstract":"Abstract. Estimating a reliable subsurface resistivity structure using conventional techniques is challenging due to the nonlinear nature of the inverse problems. The performance of the inversion techniques can be pretty ambiguous based on the optimal error, although traditional methods have proven to be quite effective. In this work, the impacts of the constraints accessible from a borehole are examined for further assessment and to enhance algorithm effectivity. The vPSOGWO strategy is a new approach that is based on a model search space without any prior information, and it describes the hybridization of particle swarm optimization (PSO) with the Grey Wolf Optimizer (GWO). To understand the efficiency and novelty of the algorithm, it has been validated on two different kinds of synthetic resistivity data with various sets of noise and, subsequently, applied to three field datasets of different geological terrains. The analyzed results suggest that the subsurface resistivity model shows considerable uncertainty. Thus, it is superior to examine the histograms and posterior probability density functions (PDFs) of such solutions to exemplify the global solution. A PDF with a 68.27 % confidence interval (CI) selects a region with a higher probability. Therefore, the inverted models are used to estimate the mean global solution and the most negligible uncertainties, where the mean global solution represents the best solution. Our vPSOGWO-inverted outcomes have been proven to be more accurate than classic PSO, GWO, and state-of-the-art variants of classic approaches. As a result, this novel method plays a vital role in vertical electrical sounding (VES) data inversion.","PeriodicalId":54714,"journal":{"name":"Nonlinear Processes in Geophysics","volume":"151 1","pages":""},"PeriodicalIF":2.2,"publicationDate":"2024-01-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139420492","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Brief Communication: A modified Korteweg–de Vries equation for Rossby–Khantadze waves in a sheared zonal flow of the ionospheric E layer","authors":"Laila Zafar Kahlon, Hassan Amir Shah, Tamaz David Kaladze, Qura Tul Ain, Syed Assad Bukhari","doi":"10.5194/npg-31-1-2024","DOIUrl":"https://doi.org/10.5194/npg-31-1-2024","url":null,"abstract":"Abstract not available","PeriodicalId":54714,"journal":{"name":"Nonlinear Processes in Geophysics","volume":"21 1","pages":""},"PeriodicalIF":2.2,"publicationDate":"2024-01-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139414639","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"The dynamic of ion Bernstein-Greene-Kruskal holes in plasmas with regularized κ-distributed electrons","authors":"Qiu Ping Lu, Cai Ping Wu, Hui Chen, Xiao Chang Chen, San Qiu Liu","doi":"10.5194/npg-2023-25","DOIUrl":"https://doi.org/10.5194/npg-2023-25","url":null,"abstract":"<strong>Abstract.</strong> The dynamics of ion holes (IHs) in plasmas where electrons follow the regularized Kappa distribution (RKD) and ions follow the Maxwellian distribution (MD) are investigated based on the Bernstein-Greene-Kruskal (BGK) method. The results show that the depth of the IHs, the allowed combination of width and amplitude to support physically plausible IHs equilibrium depend on the spectral index κ_e and cut-off parameter α of the distribution function. That is, with increasing values of the spectral index κ_e and cut-off parameter α, the IHs formed become deeper and allow a larger permissible region of width and amplitude. In contrast, with decreasing values of the spectral index κ_e and cut-off parameter α, the IHs formed become shallower and have a smaller allowed range of width and amplitude. The present work may contribute to the comprehension of the nonlinear structures in plasmas system where non-thermal particles are found.","PeriodicalId":54714,"journal":{"name":"Nonlinear Processes in Geophysics","volume":"38 1","pages":""},"PeriodicalIF":2.2,"publicationDate":"2024-01-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139396708","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Multi-level data assimilation for simplified ocean models","authors":"Florian Beiser, Håvard Heitlo Holm, Kjetil Olsen Lye, Jo Eidsvik","doi":"10.5194/npg-2023-27","DOIUrl":"https://doi.org/10.5194/npg-2023-27","url":null,"abstract":"<strong>Abstract.</strong> Multi-level Monte Carlo methods have established as a tool in uncertainty quantification for decreasing the computational costs while maintaining the same statistical accuracy as in single-level Monte Carlo. Lately, there have also been theoretical efforts to use similar ideas to facilitate multi-level data assimilation. By applying a multi-level ensemble Kalman filter for assimilating sparse observations of ocean currents into a simplified ocean model based on the shallow-water equations, we study the practical challenges of applying these method to more complex problems. We present numerical results from a realistic test case where small-scale perturbations lead to chaotic behaviour, and in this context we conduct state estimation and drift trajectories forecasting using multi-level ensembles. This represents a new step on the path of making multi-level data assimilation feasible for real-world oceanographic applications.","PeriodicalId":54714,"journal":{"name":"Nonlinear Processes in Geophysics","volume":"208 1","pages":""},"PeriodicalIF":2.2,"publicationDate":"2024-01-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139095111","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Existence and influence of mixed states in a model of vegetation patterns","authors":"Lilian Vanderveken, Marina Martínez Montero, Michel Crucifix","doi":"10.5194/npg-30-585-2023","DOIUrl":"https://doi.org/10.5194/npg-30-585-2023","url":null,"abstract":"Abstract. The Rietkerk vegetation model is a system of partial differential equations, which has been used to understand the formation and dynamics of spatial patterns in vegetation ecosystems, including desertification and biodiversity loss. Here, we provide an in-depth bifurcation analysis of the vegetation patterns produced by Rietkerk's model, based on a linear stability analysis of the homogeneous equilibrium of the system. Specifically, using a continuation method based on the Newton–Raphson algorithm, we obtain all the main heterogeneous equilibria for a given size of the domain. We confirm that inhomogeneous vegetated states can exist and be stable, even for a value of rainfall for which no vegetation exists in the non-spatialized system. In addition, we evidence the existence of a new type of equilibrium, which we call “mixed state”, in which the equilibria are always unstable and take the form of a mix of two equilibria from the main branches. Although these equilibria are unstable, they influence the dynamics of the transitions between distinct stable states by slowing down the evolution of the system when it passes close to it. Our approach proves to be a helpful way to assess the existence of tipping points in spatially extended systems and disentangle the fate of the system in the Busse balloon. Overall, our findings represent a significant step forward in understanding the behaviour of the Rietkerk model and the broader dynamics of vegetation patterns.","PeriodicalId":54714,"journal":{"name":"Nonlinear Processes in Geophysics","volume":"10 1","pages":""},"PeriodicalIF":2.2,"publicationDate":"2023-12-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138579489","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Uncertainties, complexities and possible forecasting of Volcán de Colima energy emissions (Mexico, years 2013–2015) based on a fractal reconstruction theorem","authors":"Marisol Monterrubio-Velasco, Xavier Lana, Raúl Arámbula-Mendoza","doi":"10.5194/npg-30-571-2023","DOIUrl":"https://doi.org/10.5194/npg-30-571-2023","url":null,"abstract":"Abstract. The effusive–explosive energy emission process in a volcano is a dynamic and complex physical phenomenon. The importance of quantifying this complexity in terms of the physical and mathematical mechanisms that govern these emissions should be a requirement for deciding to apply a possible forecasting strategy with a sufficient degree of certainty. The complexity of this process is determined in this research by means of the reconstruction theorem and statistical procedures applied to the effusive–explosive volcanic energy emissions corresponding to the activity in the Volcán de Colima (western segment of the Trans-Mexican Volcanic Belt) along the years 2013–2015. The analysis is focused on measuring the degree of persistence or randomness of the series, the degree of predictability of energy emissions, and the quantification of the degree of complexity and “memory loss” of the physical mechanism throughout an episode of volcanic emissions. The results indicate that the analysed time series depict a high degree of persistence and low memory loss, making the mentioned effusive–explosive volcanic emission structure a candidate for successfully applying a forecasting strategy.","PeriodicalId":54714,"journal":{"name":"Nonlinear Processes in Geophysics","volume":"276 2 1","pages":""},"PeriodicalIF":2.2,"publicationDate":"2023-12-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138553623","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Bridging classical data assimilation and optimal transport","authors":"Marc Bocquet, Pierre J. Vanderbecken, Alban Farchi, Joffrey Dumont Le Brazidec, Yelva Roustan","doi":"10.5194/egusphere-2023-2755","DOIUrl":"https://doi.org/10.5194/egusphere-2023-2755","url":null,"abstract":"<strong>Abstract.</strong> Because optimal transport acts as displacement interpolation in physical space rather than as interpolation in value space, it can potentially avoid double penalty errors. As such it provides a very attractive metric for non-negative physical fields comparison – the Wasserstein distance – which could further be used in data assimilation for the geosciences. The algorithmic and numerical implementations of such distance are however not straightforward. Moreover, its theoretical formulation within typical data assimilation problems face conceptual challenges, resulting in scarce contributions on the topic in the literature. We formulate the problem in a way that offers a unified view on both classical data assimilation and optimal transport. The resulting <em>OTDA</em> framework accounts for both the classical source of prior errors, background and observation, together with a Wasserstein barycentre in between states that stand for these background and observation. We show that the hybrid OTDA analysis can be decomposed as a simpler OTDA problem involving a single Wasserstein distance, followed by a Wasserstein barycentre problem which ignores the prior errors and can be seen as a <em>McCann interpolant</em>. We also propose a less enlightening but straightforward solution to the full OTDA problem, which includes the derivation of its analysis error covariance matrix. Thanks to these theoretical developments, we are able to extend the classical 3D-Var/BLUE paradigm at the core of most classical data assimilation schemes. The resulting formalism is very flexible and can account for sparse, noisy observations and non-Gaussian error statistics. It is illustrated by simple one– and two–dimensional examples that show the richness of the new types of analysis offered by this unification.","PeriodicalId":54714,"journal":{"name":"Nonlinear Processes in Geophysics","volume":"214 1","pages":""},"PeriodicalIF":2.2,"publicationDate":"2023-12-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138531986","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Selecting and weighting dynamical models using data-driven approaches","authors":"Pierre Le Bras, Florian Sévellec, Pierre Tandeo, Juan Ruiz, Pierre Ailliot","doi":"10.5194/egusphere-2023-2649","DOIUrl":"https://doi.org/10.5194/egusphere-2023-2649","url":null,"abstract":"<strong>Abstract.</strong> In geosciences, multi-model ensembles are helpful to explore the robustness of a range of results. To obtain a synthetic and improved representation of the studied dynamic system, the models are usually weighted. The simplest method, namely the model democracy, gives equal weights to all models, while more advanced approaches base weights on agreement with available observations. Here, we focus on determining weights for various versions of an idealized model of Atlantic Meridional Overturning Circulation. This is done by assessing their performance against synthetic observations (generated from one of the model versions) within a data assimilation framework using EnKF. In contrast to traditional data assimilation, we implement data-driven forecasts using the analog method based on catalogs of short-term trajectories. This approach allows us to efficiently emulate the model's dynamics while keeping computational costs low. For each model version, we compute a local performance metric, known as the contextual model evidence, to compare observations and model forecasts. This metric, based on the innovation likelihood, is sensitive to differences in model dynamics and considers forecast and observation uncertainties. Finally, the weights are calculated using both model performance and model codependency, and then evaluated on climatologies of long-term simulations. Results show good performance in identifying numerical simulations that best replicate observed short-term variations. Additionally, it outperforms benchmark approaches such as model democracy or climatologies-based strategies when reconstructing missing distributions. These findings encourage the application of the proposed methodology to more complex datasets in the future, like climate simulations.","PeriodicalId":54714,"journal":{"name":"Nonlinear Processes in Geophysics","volume":"175 1","pages":""},"PeriodicalIF":2.2,"publicationDate":"2023-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138531982","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Downscaling of surface wind forecasts using convolutional neural networks","authors":"Florian Dupuy, Pierre Durand, Thierry Hedde","doi":"10.5194/npg-30-553-2023","DOIUrl":"https://doi.org/10.5194/npg-30-553-2023","url":null,"abstract":"Abstract. Near-surface winds over complex terrain generally feature a large variability at the local scale. Forecasting these winds requires high-resolution numerical weather prediction (NWP) models, which drastically increase the duration of simulations and hinder them in running on a routine basis. Nevertheless, downscaling methods can help in forecasting such wind flows at limited numerical cost. In this study, we present a statistical downscaling of WRF (Weather Research and Forecasting) wind forecasts over southeastern France (including the southwestern part of the Alps) from its original 9 km resolution onto a 1 km resolution grid (1 km NWP model outputs are used to fit our statistical models). Downscaling is performed using convolutional neural networks (CNNs), which are the most powerful machine learning tool for processing images or any kind of gridded data, as demonstrated by recent studies dealing with wind forecast downscaling. The previous studies mostly focused on testing new model architectures. In this study, we aimed to extend these works by exploring different output variables and their associated loss function. We found that there is no one approach that outperforms the others in terms of both the direction and the speed at the same time. Finally, the best overall performance is obtained by combining two CNNs, one dedicated to the direction forecast based on the calculation of the normalized wind components using a customized mean squared error (MSE) loss function and the other dedicated to the speed forecast based on the calculation of the wind components and using another customized MSE loss function. Local-scale, topography-related wind features, which were poorly forecast at 9 km, are now well reproduced, both for speed (e.g., acceleration on the ridge, leeward deceleration, sheltering in valleys) and direction (deflection, valley channeling). There is a general improvement in the forecast, especially during the nighttime stable stratification period, which is the most difficult period to forecast. The result is that, after downscaling, the wind speed bias is reduced from −0.55 to −0.01 m s−1, the wind speed MAE is reduced from 1.02 to 0.69 m s−1 (32 % reduction) and the wind direction MAE is reduced from 25.9 to 15.5∘ (40 % reduction) in comparison with the 9 km resolution forecast.","PeriodicalId":54714,"journal":{"name":"Nonlinear Processes in Geophysics","volume":"214 1","pages":""},"PeriodicalIF":2.2,"publicationDate":"2023-11-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138531955","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Improving Ensemble Data Assimilation through Probit-space Ensemble Size Expansion for Gaussian Copulas (PESE-GC)","authors":"Man-Yau Chan","doi":"10.5194/egusphere-2023-2699","DOIUrl":"https://doi.org/10.5194/egusphere-2023-2699","url":null,"abstract":"<strong>Abstract.</strong> Small forecast ensemble sizes (&lt; 100) are common in the ensemble data assimilation (EnsDA) component of geophysical forecast systems, thus limiting the error-constraining power of EnsDA. This study proposes an efficient and embarrassingly parallel method to generate additional ensemble members: the Probit-space Ensemble Size Expansion for Gaussian Copulas (PESE-GC; \"peace gee see\"). Such members are called \"virtual members\". PESE-GC utilizes the users' knowledge of the marginal distributions of forecast model variables. Virtual members can be generated from any (potentially non-Gaussian) multivariate forecast distribution that has a Gaussian copula. PESE-GC's impact on EnsDA is evaluated using the 40-variable Lorenz 1996 model, several EnsDA algorithms, several observation operators, a range of EnsDA cycling intervals and a range of forecast ensemble sizes. Significant improvements to EnsDA (<em>p</em> &lt; 0.01) are observed when either 1) the forecast ensemble size is small (≤20 members), 2) the user selects marginal distributions that improves the forecast model variable statistics, and/or 3) the rank histogram filter is used with non-parametric priors in high forecast spread situations. These results motivate development and testing of PESE-GC for EnsDA with high-order geophysical models.","PeriodicalId":54714,"journal":{"name":"Nonlinear Processes in Geophysics","volume":"72 1","pages":""},"PeriodicalIF":2.2,"publicationDate":"2023-11-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138531985","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}