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Journal articles on the topic 'Statistical inversions'
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1
Nygård, Tiina, Teresa Valkonen, and Timo Vihma. "Antarctic Low-Tropospheric Humidity Inversions: 10-Yr Climatology." Journal of Climate 26, no. 14 (July 12, 2013): 5205–19. http://dx.doi.org/10.1175/jcli-d-12-00446.1.
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Abstract Humidity inversions are nearly permanently present in the coastal Antarctic atmosphere. This is shown based on an investigation of statistical characteristics of humidity inversions at 11 Antarctic coastal stations using radiosonde data from the Integrated Global Radiosonde Archive (IGRA) from 2000 to 2009. The humidity inversion occurrence was highest in winter and spring, and high atmospheric pressure and cloud-free conditions generally increased the occurrence. A typical humidity inversion was less than 200 m deep and 0.2 g kg−1 strong, and a typical humidity profile contained several separate inversion layers. The inversion base height had notable seasonal variations, but generally the humidity inversions were located at higher altitudes than temperature inversions. Roughly half of the humidity inversions were associated with temperature inversions, especially near the surface, and humidity and temperature inversion strengths as well as depths correlated at several stations. On the other hand, approximately 60% of the humidity inversions were accompanied by horizontal advection of water vapor increasing with height, which is also a probable factor supporting humidity inversions. The spatial variability of humidity inversions was linked to the topography and the water vapor content of the air. Compared to previous results for the Arctic, the most striking differences in humidity inversions in the Antarctic were a much higher frequency of occurrence in summer, at least under clear skies, and a reverse seasonal cycle of the inversion height. The results can be used as a baseline for validation of weather prediction and climate models and for studies addressing changes in atmospheric moisture budget in the Antarctic.
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Cáceres, Mario, Antonio Barbadilla, and Alfredo Ruiz. "Recombination Rate Predicts Inversion Size in Diptera." Genetics 153, no. 1 (September 1, 1999): 251–59. http://dx.doi.org/10.1093/genetics/153.1.251.
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Abstract Most species of the Drosophila genus and other Diptera are polymorphic for paracentric inversions. A common observation is that successful inversions are of intermediate size. We test here the hypothesis that the selected property is the recombination length of inversions, not their physical length. If so, physical length of successful inversions should be negatively correlated with recombination rate across species. This prediction was tested by a comprehensive statistical analysis of inversion size and recombination map length in 12 Diptera species for which appropriate data are available. We found that (1) there is a wide variation in recombination map length among species; (2) physical length of successful inversions varies greatly among species and is inversely correlated with the species recombination map length; and (3) neither the among-species variation in inversion length nor the correlation are observed in unsuccessful inversions. The clear differences between successful and unsuccessful inversions point to natural selection as the most likely explanation for our results. Presumably the selective advantage of an inversion increases with its length, but so does its detrimental effect on fertility due to double crossovers. Our analysis provides the strongest and most extensive evidence in favor of the notion that the adaptive value of inversions stems from their effect on recombination.
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Theune, Ulrich, Ingrid Østgård Jensås, and Jo Eidsvik. "Analysis of prior models for a blocky inversion of seismic AVA data." GEOPHYSICS 75, no. 3 (May 2010): C25—C35. http://dx.doi.org/10.1190/1.3427538.
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Resolving thinner layers and focusing layer boundaries better in inverted seismic sections are important challenges in exploration and production seismology to better identify a potential drilling target. Many seismic inversion methods are based on a least-squares optimization approach that can intrinsically lead to unfocused transitions between adjacent layers. A Bayesian seismic amplitude variation with angle (AVA) inversion algorithm forms sharper boundaries between layers when enforcing sparseness in the vertical gradients of the inversion results. The underlying principle is similar to high-resolution processing algorithms and has been adapted from digital-image-sharpening algorithms. We have investigated the Cauchy and Laplace statistical distributions for their potential to improve contrasts betweenlayers. An inversion algorithm is derived statistically from Bayes’ theorem and results in a nonlinear problem that requires an iterative solution approach. Bayesian inversions require knowledge of certain statistical properties of the model we want to invert for. The blocky inversion method requires an additional parameter besides the usual properties for a multivariate covariance matrix, which we can estimate from borehole data. Tests on synthetic and field data show that the blocky inversion algorithm can detect and enhance layer boundaries in seismic inversions by effectively suppressing side lobes. The analysis of the synthetic data suggests that the Laplace constraint performs more reliably, whereas the Cauchy constraint may not find the optimum solution by converging to a local minimum of the cost function and thereby introducing some numerical artifacts.
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Ruiz, Alfredo, José María Ranz, Mario Cáceres, and Carmen Segarra. "Chromosomal evolution and comparative gene mapping in the Drosophila repleta species group." Brazilian Journal of Genetics 20, no. 4 (December 1997): 553–65. http://dx.doi.org/10.1590/s0100-84551997000400003.
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A review of our recent work on the cromosomal evolution of the Drosophila repleta species group is presented. Most studies have focused on the buzzatii species complex, a monophyletic set of 12 species which inhabit the deserts of South America and the West Indies. A statistical analysis of the length and breakpoint distribution of the 86 paracentric inversions observed in this complex has shown that inversion length is a selected trait. Rare inversions are usually small while evolutionary successful inversions, fixed and polymorphic, are predominantly of medium size. There is also a negative correlation between length and number of inversions per species. Finally, the distribution of inversion breakpoints along chromosome 2 is non-random, with chromosomal regions which accumulate up to 8 breakpoints (putative "hot spots"). Comparative gene mapping has also been used to investigate the molecular organization and evolution of chromosomes. Using in situ hybridization, 26 genes have been precisely located on the salivary gland chromosomes of D. repleta and D. buzzatii; another nine have been tentatively identified. The results are fully consistent with the currently accepted chromosomal homologies between D. repleta and D. melanogaster, and no evidence for reciprocal translocations or pericentric inversions has been found. The comparison of the gene map of D. repleta chromosome 2 with that of the homologous chromosome 3R of D. melanogaster shows an extensive reorganization via paracentric inversions and allows to estimate an evolution rate of ~1 inversion fixed per million years for this chromosome
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Chapman, Ross. "Inference of geoacoustic model parameters from acoustic field data: Perspectives on Geoacoustic Inversion." Journal of the Acoustical Society of America 155, no. 3_Supplement (March 1, 2024): A216. http://dx.doi.org/10.1121/10.0027352.
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Estimation of parameters of geoacoustic models from acoustic field data has been a central research theme in acoustical oceanography and ocean acoustics. During the past several decades, highly efficient numerical inversion techniques have been developed that provide model parameter estimates and their uncertainties based on statistical inference methods. However, the methods are model-based and the inversions are prone to errors related to model mismatch. In any event, the inversions can generate only effective models of the true structure of the ocean bottom, which is generally highly variable over relatively small spatial scales in range and depth. There are also questions about the theory for modelling sound propagation in porous sediment media that raise doubt about the validity of inversion results. In most inversions, a visco-elastic theory is used, but is this the most appropriate propagation model? Another question is about the impact of neglecting shear waves in geoacoustic models. Most inversions assume a fluid model of the ocean bottom. This paper revisits issues that have raised questions about limitations of geoacoustic inversion methods, and discusses the impact of various mitigation measures that have been applied. The paper concludes with musings about new inversion techniques based on machine learning.
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Prado-Alonso, Carlos. "A comprehensive corpus-based analysis of “X Auxiliary Subject” constructions in written and spoken English." Topics in Linguistics 20, no. 2 (December 1, 2019): 17–32. http://dx.doi.org/10.2478/topling-2019-0007.
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Abstract This paper describes a corpus-based analysis of subject-auxiliary inversion in both spoken and written English. The focus of the analysis is Chen’s (2013) X Auxiliary Subject construction (XASC), where X codes the fronting of a constituent which triggers the inversion of the auxiliary and the subject, as in “Never has trade union loyalty faced a more baffling test” or “What did he do?” On the basis of a statistical analysis using corpora of written and spoken English, it is argued that the distribution of XAS inversion, in the interrogative mood, is related to the degree of an addressor’s involvement in a text. It will be shown that, in the interrogative mood, the more involvement in a text, the more XAS inversions are to be expected. It is also argued that XAS inversions in interrogative clauses can be seen to serve as discourse markers through which an addressor’s involvement is coded in written and spoken English discourse. The analysis will also show that XAS inversions in the declarative mood also serve an interpersonal function, this, however, being inherently tied to the clause-linking function performed by the construction. Furthermore, the data will show that the distribution of XAS inversions in declarative clauses is related to the degree of informational content of the texts in which these inversions occur.
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Devasthale, A., J. Sedlar, and M. Tjernström. "Characteristics of water-vapour inversions observed over the Arctic by Atmospheric Infrared Sounder (AIRS) and radiosondes." Atmospheric Chemistry and Physics Discussions 11, no. 5 (May 25, 2011): 15801–29. http://dx.doi.org/10.5194/acpd-11-15801-2011.
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Abstract. An accurate characterization of the vertical structure of the Arctic atmosphere is useful in climate change and attribution studies as well as for the climate modelling community to improve projections of future climate over this highly sensitive region. Here, we investigate one of the dominant features of the vertical structure of the Arctic atmosphere, i.e. water-vapour inversions, using eight years of Atmospheric Infrared Sounder data (2002–2010) and radiosounding profiles released from the two Arctic locations (North Slope of Alaska at Barrow and during SHEBA). We quantify the characteristics of clear-sky water vapour inversions in terms of their frequency of occurrence, strength and height covering the entire Arctic for the first time. We found that the frequency of occurrence of water-vapour inversions is highest during winter and lowest during summer. The inversion strength is, however, higher during summer. The observed peaks in the median inversion-layer heights are higher during the winter half of the year, at around 850 hPa over most of the Arctic Ocean, Siberia and the Canadian Archipelago, while being around 925 hPa during most of the summer half of the year over the Arctic Ocean. The radiosounding profiles agree with the frequency, location and strength of water-vapour inversions in the Pacific sector of the Arctic. In addition, the radiosoundings indicate that multiple inversions are the norm with relatively few cases without inversions. The amount of precipitable water within the water-vapour inversion structures is estimated and we find a distinct, two-mode contribution to the total column precipitable water. These results suggest that water-vapour inversions are a significant source to the column thermodynamics, especially during the colder winter and spring seasons. We argue that these inversions are a robust metric to test the reproducibility of thermodynamics within climate models. An accurate statistical representation of water-vapour inversions in models would mean that the large-scale coupling of moisture transport, precipitation, temperature and water vapour vertical structure and radiation are also essentially captured well in such models.
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Devasthale, A., J. Sedlar, and M. Tjernström. "Characteristics of water-vapour inversions observed over the Arctic by Atmospheric Infrared Sounder (AIRS) and radiosondes." Atmospheric Chemistry and Physics 11, no. 18 (September 22, 2011): 9813–23. http://dx.doi.org/10.5194/acp-11-9813-2011.
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Abstract. An accurate characterization of the vertical structure of the Arctic atmosphere is useful in climate change and attribution studies as well as for the climate modelling community to improve projections of future climate over this highly sensitive region. Here, we investigate one of the dominant features of the vertical structure of the Arctic atmosphere, i.e. water-vapour inversions, using eight years of Atmospheric Infrared Sounder data (2002–2010) and radiosounding profiles released from the two Arctic locations (North Slope of Alaska at Barrow and during SHEBA). We quantify the characteristics of clear-sky water vapour inversions in terms of their frequency of occurrence, strength and height covering the entire Arctic for the first time. We found that the frequency of occurrence of water-vapour inversions is highest during winter and lowest during summer. The inversion strength is, however, higher during summer. The observed peaks in the median inversion-layer heights are higher during the winter half of the year, at around 850 hPa over most of the Arctic Ocean, Siberia and the Canadian Archipelago, while being around 925 hPa during most of the summer half of the year over the Arctic Ocean. The radiosounding profiles agree with the frequency, location and strength of water-vapour inversions in the Pacific sector of the Arctic. In addition, the radiosoundings indicate that multiple inversions are the norm with relatively few cases without inversions. The amount of precipitable water within the water-vapour inversion structures is estimated and we find a distinct, two-mode contribution to the total column precipitable water. These results suggest that water-vapour inversions are a significant source to the column thermodynamics, especially during the colder winter and spring seasons. We argue that these inversions are a robust metric to test the reproducibility of thermodynamics within climate models. An accurate statistical representation of water-vapour inversions in models would mean that the large-scale coupling of moisture transport, precipitation, temperature and water-vapour vertical structure and radiation are essentially captured well in such models.
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Arenas, Conxita, Goran Zivanovic, and Francesc Mestres. "Chromosomal Thermal Index: a comprehensive way to integrate the thermal adaptation of Drosophila subobscura whole karyotype." Genome 61, no. 2 (February 2018): 73–78. http://dx.doi.org/10.1139/gen-2017-0124.
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Drosophila has demonstrated to be an excellent model to study the adaptation of organisms to global warming, with inversion chromosomal polymorphism having a key role in this adaptation. Here, we introduce a new index (Chromosomal Thermal Index or CTI) to quantify the thermal adaptation of a population according to its composition of “warm” and “cold” adapted inversions. This index is intuitive, has good statistical properties, and can be used to hypothesis on the effect of global warming on natural populations. We show the usefulness of CTI using data from European populations of D. subobscura, sampled in different years. Out of 15 comparisons over time, nine showed significant increase of CTI, in accordance with global warming expectations. Although large regions of the genome outside inversions contain thermal adaptation genes, our results show that the total amount of warm or cold inversions in populations seems to be directly involved in thermal adaptation, whereas the interactions between the inversions content of homologous and non-homologous chromosomes are not relevant.
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Mitsuhata, Yuji, Toshihiro Uchida, and Hiroshi Amano. "2.5‐D inversion of frequency‐domain electromagnetic data generated by a grounded‐wire source." GEOPHYSICS 67, no. 6 (November 2002): 1753–68. http://dx.doi.org/10.1190/1.1527076.
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Interpretation of controlled‐source electromagnetic (CSEM) data is usually based on 1‐D inversions, whereas data of direct current (dc) resistivity and magnetotelluric (MT) measurements are commonly interpreted by 2‐D inversions. We have developed an algorithm to invert frequency‐Domain vertical magnetic data generated by a grounded‐wire source for a 2‐D model of the earth—a so‐called 2.5‐D inversion. To stabilize the inversion, we adopt a smoothness constraint for the model parameters and adjust the regularization parameter objectively using a statistical criterion. A test using synthetic data from a realistic model reveals the insufficiency of only one source to recover an acceptable result. In contrast, the joint use of data generated by a left‐side source and a right‐side source dramatically improves the inversion result. We applied our inversion algorithm to a field data set, which was transformed from long‐offset transient electromagnetic (LOTEM) data acquired in a Japanese oil and gas field. As demonstrated by the synthetic data set, the inversion of the joint data set automatically converged and provided a better resultant model than that of the data generated by each source. In addition, our 2.5‐D inversion accounted for the reversals in the LOTEM measurements, which is impossible using 1‐D inversions. The shallow parts (above about 1 km depth) of the final model obtained by our 2.5‐D inversion agree well with those of a 2‐D inversion of MT data.
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Zhuravlev, R. V., E. A. Miller, A. K. Knyazev, N. A. Baranov, E. A. Lezina, and A. V. Troitsky. "Parameterization of a WRF Model Based on Microwave Measurements of Temperature Inversion Characteristics in PBL over Moscow City." Известия Российской академии наук. Физика атмосферы и океана 60, no. 1 (August 6, 2024): 33–51. http://dx.doi.org/10.31857/s0002351524010047.
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In this work the WRF-ARW model was tested with several different combinations of physical parameterizations to assess the quality of temperature inversion parameter predictions over the Moscow city. The dynamic and statistical characteristics of temperature inversions have been calculated and analysed in selecting criteria for comparisons. The calculated of estimating of the dissipation conditions in dependence on the type of temperature inversions are presented. The data source was the results of temperature profiles measurements in a layer up to 1 km, obtained by the MTP-5 passive microwave profiler from 2018 to 2021. One MTP5 on the North of Moscow was used to tune the model parameters and another one on the East of Moscow for validation. The comparison results show that several parameterization options can be chosen to reproduce the main inversion parameters.
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Myers, Timothy A., and Joel R. Norris. "Observational Evidence That Enhanced Subsidence Reduces Subtropical Marine Boundary Layer Cloudiness." Journal of Climate 26, no. 19 (September 24, 2013): 7507–24. http://dx.doi.org/10.1175/jcli-d-12-00736.1.
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Abstract Conventional wisdom suggests that subsidence favors the presence of marine stratus and stratocumulus because regions of enhanced boundary layer cloudiness are observed to climatologically co-occur with regions of enhanced subsidence. Here it is argued that the climatological positive correlation between subsidence and cloudiness is not the result of a direct physical mechanism connecting the two. Instead, it arises because enhanced subsidence is typically associated with stronger temperature inversions capping the marine boundary layer, and stronger temperature inversions favor greater cloudiness. Through statistical analysis of satellite cloud data and meteorological reanalyses for the subsidence regime over tropical (30°S–30°N) oceans, it is shown that enhanced subsidence promotes reduced cloudiness for the same value of inversion strength and that a stronger inversion favors greater cloudiness for the same value of subsidence. Using a simple conceptual model, it is argued that enhanced subsidence leads to reduced cloud thickness, liquid water path, and cloud fraction by pushing down the top of the marine boundary layer. Moreover, a stronger inversion reduces entrainment drying and warming, thus leading to a more humid boundary layer and greater cloud thickness, liquid water path, and cloud fraction. These two mechanisms typically oppose each other for geographical and seasonal cloud variability because enhanced subsidence is usually associated with stronger inversions. If global warming results in stronger inversions but weaker subsidence, the two mechanisms could both favor increased subtropical low-level cloudiness.
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Knibb, WR, and JSF Barker. "Polymorphic Inversion and Esterase Loci Complex on Chromosome 2 of Drosophila buzzatii II. Spatial Variation." Australian Journal of Biological Sciences 41, no. 2 (1988): 239. http://dx.doi.org/10.1071/bi9880239.
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The potential influence of linked inversions on allele frequency variation at the Est-l and Est-210ci among Australian populations of D. buzzatii was determined by statistical analyses of allele and inversion gametic frequencies. Most of the significant spatial and climatic associations found for all Est-l allele frequencies, and for one allele only of Est-2 (Est-2c+), were accounted for by their linkage disequilibria with the inversions, which covaried with environmental variables. Consistent with this result, the spatial and climatic associations for conditional Est-l and Est-2 allele frequencies tended to be different from those for the respective unadjusted allele frequencies. In one important respect, the results for Est-l and Est-2 were not altered by inversions. For both unadjusted and conditional Est-l allele frequencies, few climatic associations remain after correcting for geographic location, whereas for both unadjusted and conditional Est-2 allele frequencies, climatic associations remain after correcting for geographic location. Thus, apparent selection affecting allele frequencies at the Est-2 locus is not accounted for by linked inversions.
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Transtrum, Mark K., Jay C. Spendlove, and Tracianne B. Neilsen. "Parameter reduction for environmental inversions in ocean acoustics." Journal of the Acoustical Society of America 154, no. 4_supplement (October 1, 2023): A41. http://dx.doi.org/10.1121/10.0022734.
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Environmental inversions in ocean acoustics require the simultaneous estimation of many unknown parameters. Unfortunately, many environmental parameters are unidentifiable from available measurements. Recent work in statistical physics has developed tools for analyzing such models using information geometry. The Manifold Boundary Approximation (MBAM) systematically prunes unidentifiable parameters to produce an identifiable model that can be analyzed with traditional statistical methods. In this talk, we report on progress applying MBAM to underwater acoustics models forenvironmental inversion, focusing on transmission loss (TL) in range-independentnormal mode models. The key technical advance is the calculation of geodesics (a generalization of straight lines to curved surfaces) on a geometric representation of the model known as the model manifold. Geodesics inform which environmental parameters are constrained by ocean sounds and guide the removal of unidentifiable parameters. The result is a simplified, identifiable model of comparable accuracy. We summarize physical insights revealed by MBAM applied to ocean inversion. [Work supported by Office of Naval Research.]
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Monteil, Guillaume, and Marko Scholze. "Regional CO<sub>2</sub> inversions with LUMIA, the Lund University Modular Inversion Algorithm, v1.0." Geoscientific Model Development 14, no. 6 (June 7, 2021): 3383–406. http://dx.doi.org/10.5194/gmd-14-3383-2021.
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Abstract. Atmospheric inversions are used to derive constraints on the net sources and sinks of CO2 and other stable atmospheric tracers from their observed concentrations. The resolution and accuracy that the fluxes can be estimated with depends, among other factors, on the quality and density of the observational coverage, on the precision and accuracy of the transport model used by the inversion to relate fluxes to observations, and on the adaptation of the statistical approach to the problem studied. In recent years, there has been an increasing demand from stakeholders for inversions at higher spatial resolution (country scale), in particular in the framework of the Paris agreement. This step up in resolution is in theory enabled by the growing availability of observations from surface in situ networks (such as ICOS in Europe) and from remote sensing products (OCO-2, GOSAT-2). The increase in the resolution of inversions is also a necessary step to provide efficient feedback to the bottom-up modeling community (vegetation models, fossil fuel emission inventories, etc.). However, it calls for new developments in the inverse models: diversification of the inversion approaches, shift from global to regional inversions, and improvement in the computational efficiency. In this context, we developed LUMIA, the Lund University Modular Inversion Algorithm. LUMIA is a Python library for inverse modeling built around the central idea of modularity: it aims to be a platform that enables users to construct and experiment with new inverse modeling setups while remaining easy to use and maintain. It is in particular designed to be transport-model-agnostic, which should facilitate isolating the transport model errors from those introduced by the inversion setup itself. We have constructed a first regional inversion setup using the LUMIA framework to conduct regional CO2 inversions in Europe using in situ data from surface and tall-tower observation sites. The inversions rely on a new offline coupling between the regional high-resolution FLEXPART Lagrangian particle dispersion model and the global coarse-resolution TM5 transport model. This test setup is intended both as a demonstration and as a reference for comparison with future LUMIA developments. The aims of this paper are to present the LUMIA framework (motivations for building it, development principles and future prospects) and to describe and test this first implementation of regional CO2 inversions in LUMIA.
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Taroudakis, Michael I. "Statistical Characterization of Acoustic Signals Using 1D Wavelet Transforms with Applications in Acoustical Oceanography." Journal of Theoretical and Computational Acoustics 26, no. 04 (December 2018): 1850047. http://dx.doi.org/10.1142/s2591728518500470.
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The paper summarizes the research carried out at the University of Crete and the Foundation for Research and Technology-HELLAS aiming at the statistical characterization of underwater acoustic signals and their subsequent use for geoacoustic inversions and applications in ocean acoustic tomography. In these applications, an acoustic signal recorded in the marine environment due to some source is used as the carrier of information on the physical parameters of the environment. Statistical characterization of acoustic signals is a pre-processing technique aiming at the definition of signal observables, to be used as input data of appropriately defined inverse problems aiming at the estimation of critical parameters of the marine environment. The statistical characterization scheme was introduced as a way to define signal observables especially in cases that typical observables such as ray arrivals or modal arrivals cannot be identified in the recorded signals. Moreover, the setting of the associated inverse problem requires just a single recording device, which renders its application practically and relatively cheap in comparison with signal inversion methods requiring reception at an array of hydrophones. The characterization scheme is based on a wavelet transform of the signal at various levels, followed by the statistical description of the wavelet sub-band coefficients. It is shown that A-stable symmetric distributions are capable of defining the statistics of these coefficients, the characteristic parameters of which are the observables of the signal to be exploited for the inversions. As the inverse problems associated with the sought applications are formulated as optimization processes, an objective function to be used as a similarity measure is defined, which in the case of the statistical characterization method is the Kullback–Leibrer Divergence (KLD), capable of comparing probability density functions. The inversion processes are performed by means of neural networks or genetic algorithms, and the performance of the combined signal characterization and inversion method has been tested with simulated and real data. It is shown, that the method works well especially with noise-free or denoised signals.
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Pithan, Felix, and Thorsten Mauritsen. "Comments on “Current GCMs' Unrealistic Negative Feedback in the Arctic”." Journal of Climate 26, no. 19 (September 24, 2013): 7783–88. http://dx.doi.org/10.1175/jcli-d-12-00331.1.
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Abstract In contrast to prior studies showing a positive lapse-rate feedback associated with the Arctic inversion, Boé et al. reported that strong present-day Arctic temperature inversions are associated with stronger negative longwave feedbacks and thus reduced Arctic amplification in the model ensemble from phase 3 of the Coupled Model Intercomparison Project (CMIP3). A permutation test reveals that the relation between longwave feedbacks and inversion strength is an artifact of statistical self-correlation and that shortwave feedbacks have a stronger correlation with intermodel spread. The present comment concludes that the conventional understanding of a positive lapse-rate feedback associated with the Arctic inversion is consistent with the CMIP3 model ensemble.
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Cloyd, C. Bryan, Lillian F. Mills, and Connie D. Weaver. "Firm Valuation Effects of the Expatriation of U.S. Corporations to Tax-Haven Countries." Journal of the American Taxation Association 25, s-1 (January 1, 2003): 87–109. http://dx.doi.org/10.2308/jata.2003.25.s-1.87.
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U.S. corporations that reorganize in tax-haven countries claim to save many millions of dollars in future U.S. corporate income taxes. However, because these “inversion” transactions may involve significant nontax costs, it is not obvious how they affect share value. We use Monte Carlo sampling to analyze the statistical significance of each inverting firm's abnormal returns around the date that it initially announced its intentions and board of director approval of an inversion transaction. We find that five of the 20 single-company expatriations in our analysis have significant negative announcement period returns and only two show significant positive returns. The remaining 13 inversions show no statistically significant market reaction in the announcement period. The average return in the announcement period across all 20 firms is negative, but not significantly different from zero. Overall, we do not detect obvious shareholder benefits from expatriations.
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Geruso, Michael, Dean Spears, and Ishaana Talesara. "Inversions in US Presidential Elections: 1836–2016." American Economic Journal: Applied Economics 14, no. 1 (January 1, 2022): 327–57. http://dx.doi.org/10.1257/app.20200210.
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Inversions—in which the popular vote winner loses the election— have occurred in four US presidential races. We show that rather than being statistical flukes, inversions have been ex ante likely since the early 1800s. In elections yielding a popular vote margin within 1 point (one-eighth of presidential elections), about 40 percent will be inversions in expectation. We show this conditional probability is remarkably stable across historical periods—despite differences in which groups voted, which states existed, and which parties participated. Our findings imply that the United States has experienced so few inversions merely because there have been so few elections (and fewer close elections). (JEL D72, N41, N42)
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Mayfield, John A., and Gilberto J. Fochesatto. "The Layered Structure of the Winter Atmospheric Boundary Layer in the Interior of Alaska." Journal of Applied Meteorology and Climatology 52, no. 4 (April 2013): 953–73. http://dx.doi.org/10.1175/jamc-d-12-01.1.
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AbstractThe high-latitude winter atmospheric boundary layer of interior Alaska continually exhibits a complex layered structure as a result of extreme meteorological conditions. In this paper the occurrence of elevated inversions (EI), surface-based inversions (SBI), and stratified layers in the sub-Arctic from January 2000 to December 2009 is reported. This statistical analysis is based on radiosonde observation data from the Fairbanks National Weather Service station complemented by Winter Boundary Layer Experiment observations in the period 2010–11. This study found that SBIs occurred 64% of the time. An SBI occurred in combination with one, two, three, or four simultaneous EIs 84.86%, 48.49%, 21.23%, and 7.99% of the time, respectively, in 2326 total cases. The calculated mean SBI height was 377 m; EIs occurred at 1231, 2125, 2720, and 3125 m, respectively. This analysis was able to discriminate between locally controlled inversion layers and synoptic-dependent inversions and to identify their formation mechanisms. It was found that, in the presence of an SBI layer, the first EI layer formed 35.8% of the time under anticyclonic conditions at a mean height of 1249 m and 22% of the time in warm-air-advection situations at a mean height of 1049 m. The remaining 23.4% resulted from combined synoptic situations, and 18.8% were unclassified.
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Swenson, Krister M., Yu Lin, Vaibhav Rajan, and Bernard M. E. Moret. "Hurdles and Sorting by Inversions: Combinatorial, Statistical, and Experimental Results." Journal of Computational Biology 16, no. 10 (October 2009): 1339–51. http://dx.doi.org/10.1089/cmb.2009.0156.
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Taroudakis, Michael, and Kostas Smaragdakis. "Statistical signal characterization in ocean acoustic tomography and geoacoustic inversions." Journal of the Acoustical Society of America 125, no. 4 (April 2009): 2730. http://dx.doi.org/10.1121/1.4784505.
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Berchet, A., I. Pison, F. Chevallier, P. Bousquet, S. Conil, M. Geever, T. Laurila, et al. "Towards better error statistics for atmospheric inversions of methane surface fluxes." Atmospheric Chemistry and Physics 13, no. 14 (July 29, 2013): 7115–32. http://dx.doi.org/10.5194/acp-13-7115-2013.
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Abstract. We adapt general statistical methods to estimate the optimal error covariance matrices in a regional inversion system inferring methane surface emissions from atmospheric concentrations. Using a minimal set of physical hypotheses on the patterns of errors, we compute a guess of the error statistics that is optimal in regard to objective statistical criteria for the specific inversion system. With this very general approach applied to a real-data case, we recover sources of errors in the observations and in the prior state of the system that are consistent with expert knowledge while inferred from objective criteria and with affordable computation costs. By not assuming any specific error patterns, our results depict the variability and the inter-dependency of errors induced by complex factors such as the misrepresentation of the observations in the transport model or the inability of the model to reproduce well the situations of steep gradients of concentrations. Situations with probable significant biases (e.g., during the night when vertical mixing is ill-represented by the transport model) can also be diagnosed by our methods in order to point at necessary improvement in a model. By additionally analysing the sensitivity of the inversion to each observation, guidelines to enhance data selection in regional inversions are also proposed. We applied our method to a recent significant accidental methane release from an offshore platform in the North Sea and found methane fluxes of the same magnitude than what was officially declared.
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Fregoso, Emilia, and Luis A. Gallardo. "Cross-gradients joint 3D inversion with applications to gravity and magnetic data." GEOPHYSICS 74, no. 4 (July 2009): L31—L42. http://dx.doi.org/10.1190/1.3119263.
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We extend the cross-gradient methodology for joint inversion to three-dimensional environments and introduce a solution procedure based on a statistical formulation and equality constraints for structural similarity resemblance. We apply the proposed solution to the joint 3D inversion of gravity and magnetic data and gauge the advantages of this new formulation on test and field-data experiments. Combining singular-value decomposition (SVD) and other conventional regularizing constraints, we determine 3D distributions of the density and magnetization with enhanced structural similarity. The algorithm reduces some misleading features of the models, which are introduced commonly by conventional separate inversions of gravity and magnetic data, and facilitates an integrated interpretation of the models.
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Shamsipour, Pejman, Denis Marcotte, Michel Chouteau, Martine Rivest, and Abderrezak Bouchedda. "3D stochastic gravity inversion using nonstationary covariances." GEOPHYSICS 78, no. 2 (March 1, 2013): G15—G24. http://dx.doi.org/10.1190/geo2012-0122.1.
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The flexibility of geostatistical inversions in geophysics is limited by the use of stationary covariances, which, implicitly and mostly for mathematical convenience, assumes statistical homogeneity of the studied field. For fields showing sharp contrasts due, for example, to faults or folds, an approach based on the use of nonstationary covariances for cokriging inversion was developed. The approach was tested on two synthetic cases and one real data set. Inversion results based on the nonstationary covariance were compared to the results from the stationary covariance for two synthetic models. The nonstationary covariance better recovered the known synthetic models. With the real data set, the nonstationary assumption resulted in a better match with the known surface geology.
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Michalak, Anna M., Nina A. Randazzo, and Frédéric Chevallier. "Diagnostic methods for atmospheric inversions of long-lived greenhouse gases." Atmospheric Chemistry and Physics 17, no. 12 (June 20, 2017): 7405–21. http://dx.doi.org/10.5194/acp-17-7405-2017.
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Abstract. The ability to predict the trajectory of climate change requires a clear understanding of the emissions and uptake (i.e., surface fluxes) of long-lived greenhouse gases (GHGs). Furthermore, the development of climate policies is driving a need to constrain the budgets of anthropogenic GHG emissions. Inverse problems that couple atmospheric observations of GHG concentrations with an atmospheric chemistry and transport model have increasingly been used to gain insights into surface fluxes. Given the inherent technical challenges associated with their solution, it is imperative that objective approaches exist for the evaluation of such inverse problems. Because direct observation of fluxes at compatible spatiotemporal scales is rarely possible, diagnostics tools must rely on indirect measures. Here we review diagnostics that have been implemented in recent studies and discuss their use in informing adjustments to model setup. We group the diagnostics along a continuum starting with those that are most closely related to the scientific question being targeted, and ending with those most closely tied to the statistical and computational setup of the inversion. We thus begin with diagnostics based on assessments against independent information (e.g., unused atmospheric observations, large-scale scientific constraints), followed by statistical diagnostics of inversion results, diagnostics based on sensitivity tests, and analyses of robustness (e.g., tests focusing on the chemistry and transport model, the atmospheric observations, or the statistical and computational framework), and close with the use of synthetic data experiments (i.e., observing system simulation experiments, OSSEs). We find that existing diagnostics provide a crucial toolbox for evaluating and improving flux estimates but, not surprisingly, cannot overcome the fundamental challenges associated with limited atmospheric observations or the lack of direct flux measurements at compatible scales. As atmospheric inversions are increasingly expected to contribute to national reporting of GHG emissions, the need for developing and implementing robust and transparent evaluation approaches will only grow.
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Chevallier, F. "On the statistical optimality of CO<sub>2</sub> atmospheric inversions assimilating CO<sub>2</sub> column retrievals." Atmospheric Chemistry and Physics 15, no. 19 (October 7, 2015): 11133–45. http://dx.doi.org/10.5194/acp-15-11133-2015.
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Abstract. The extending archive of the Greenhouse Gases Observing Satellite (GOSAT) measurements (now covering about 6 years) allows increasingly robust statistics to be computed, that document the performance of the corresponding retrievals of the column-average dry air-mole fraction of CO2 (XCO2). Here, we demonstrate that atmospheric inversions cannot be rigorously optimal when assimilating current XCO2 retrievals, even with averaging kernels, in particular because retrievals and inversions use different assumption about prior uncertainty. We look for some practical evidence of this sub-optimality from the view point of atmospheric inversion by comparing a model simulation constrained by surface air-sample measurements with one of the GOSAT retrieval products (NASA's ACOS). The retrieval-minus-model differences result from various error sources, both in the retrievals and in the simulation: we discuss the plausibility of the origin of the major patterns. We find systematic retrieval errors over the dark surfaces of high-latitude lands and over African savannahs. More importantly, we also find a systematic over-fit of the GOSAT radiances by the retrievals over land for the high-gain detector mode, which is the usual observation mode. The over-fit is partially compensated by the retrieval bias-correction. These issues are likely common to other retrieval products and may explain some of the surprising and inconsistent CO2 atmospheric inversion results obtained with the existing GOSAT retrieval products. We suggest that reducing the observation weight in the retrieval schemes (for instance so that retrieval increments to the retrieval prior values are halved for the studied retrieval product) would significantly improve the retrieval quality and reduce the need for (or at least reduce the complexity of) ad-hoc retrieval bias correction.
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Berchet, A., I. Pison, F. Chevallier, P. Bousquet, S. Conil, M. Geever, T. Laurila, et al. "Towards better error statistics for atmospheric inversions of methane surface fluxes." Atmospheric Chemistry and Physics Discussions 13, no. 2 (February 11, 2013): 3735–82. http://dx.doi.org/10.5194/acpd-13-3735-2013.
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Abstract. In this study, we adapt general statistical methods to compute the optimal error covariance matrices in a regional inversion system inferring methane surface emissions from atmospheric concentrations. We optimally estimate the error statistics with a minimal set of physical hypotheses on the patterns of errors. With this very general approach applied within a real-data framework, we recover sources of errors in the observations and in the prior state of the system that are consistent with expert knowledge. By not assuming any specific error patterns, our results show the variability and the inter-dependency of errors induced by complex factors such as the mis-representation of the observations in the transport model or the inability of the model to reproduce well the situations of steep gradients of air mass composition in the atmosphere. By analyzing the sensitivity of the inversion to each observation, ways to improve data selection in regional inversions are also proposed. We applied our method to a recent significant accidental methane release from an offshore platform in the North Sea.
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Liu, Yinghui, Jeffrey R. Key, Axel Schweiger, and Jennifer Francis. "Characteristics of Satellite-Derived Clear-Sky Atmospheric Temperature Inversion Strength in the Arctic, 1980–96." Journal of Climate 19, no. 19 (October 1, 2006): 4902–13. http://dx.doi.org/10.1175/jcli3915.1.
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Abstract The low-level atmospheric temperature inversion is a dominant feature of the Arctic atmosphere throughout most of the year. Meteorological stations that provide radiosonde data are sparsely distributed across the Arctic, and therefore provide little information on the spatial distribution of temperature inversions. Satellite-borne sensors provide an opportunity to fill the observational gap. In this study, a 17-yr time series, 1980–96, of clear-sky temperature inversion strength during the cold season is derived from High Resolution Infrared Radiation Sounder (HIRS) data using a two-channel statistical method. The satellite-derived clear-sky inversion strength monthly mean and trends agree well with radiosonde data. Both increasing and decreasing trends are found in the cold season for different areas. It is shown that there is a strong coupling between changes in surface temperature and changes in inversion strength, but that trends in some areas may be a result of advection aloft rather than warming or cooling at the surface.
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Killingbeck, Siobhan F., Adam D. Booth, Philip W. Livermore, C. Richard Bates, and Landis J. West. "Characterisation of subglacial water using a constrained transdimensional Bayesian transient electromagnetic inversion." Solid Earth 11, no. 1 (January 17, 2020): 75–94. http://dx.doi.org/10.5194/se-11-75-2020.
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Abstract. Subglacial water modulates glacier-bed friction and therefore is of fundamental importance when characterising the dynamics of ice masses. The state of subglacial pore water, whether liquid or frozen, is associated with differences in electrical resistivity that span several orders of magnitude; hence, liquid water can be inferred from electrical resistivity depth profiles. Such profiles can be obtained from inversions of transient (time-domain) electromagnetic (TEM) soundings, but these are often non-unique. Here, we adapt an existing Bayesian transdimensional algorithm (Multimodal Layered Transdimensional Inversion – MuLTI) to the inversion of TEM data using independent depth constraints to provide statistical properties and uncertainty analysis of the resistivity profile with depth. The method was applied to ground-based TEM data acquired on the terminus of the Norwegian glacier, Midtdalsbreen, with depth constraints provided by co-located ground-penetrating radar data. Our inversion shows that the glacier bed is directly underlain by material of resistivity 102 Ωm ± 1000 %, with thickness 5–40 m, in turn underlain by a highly conductive basement (100 Ωm ± 15 %). High-resistivity material, 5×104 Ωm ± 25 %, exists at the front of the glacier. All uncertainties are defined by the interquartile range of the posterior resistivity distribution. Combining these resistivity profiles with those from co-located seismic shear-wave velocity inversions to further reduce ambiguity in the hydrogeological interpretation of the subsurface, we propose a new 3-D interpretation in which the Midtdalsbreen subglacial material is partitioned into partially frozen sediment, frozen sediment/permafrost and weathered/fractured bedrock with saline water.
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Egger, Joseph, and Klaus-Peter Hoinka. "Potential Temperature and Potential Vorticity Inversion: Complementary Approaches." Journal of the Atmospheric Sciences 67, no. 12 (December 1, 2010): 4001–16. http://dx.doi.org/10.1175/2010jas3532.1.
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Abstract Given the distribution of one atmospheric variable, that of nearly all others can be derived in balanced flow. In particular, potential vorticity inversion (PVI) selects potential vorticity (PV) to derive pressure, winds, and potential temperature θ. Potential temperature inversion (PTI) starts from available θ fields to derive pressure, winds, and PV. While PVI has been applied extensively, PTI has hardly been used as a research tool although the related technical steps are well known and simpler than those needed in PVI. Two idealized examples of PTI and PVI are compared. The 40-yr European Centre for Medium-Range Weather Forecasts (ECMWF) Re-Analysis (ERA-40) datasets are used to determine typical anomalies of PV and θ in the North Atlantic storm-track region. Statistical forms of PVI and PTI are applied to these anomalies. The inversions are equivalent but the results of PTI are generally easier to understand than those of PVI. The issues of attribution and piecewise inversion are discussed.
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Geraldo, Issa Cherif. "Exact computation of the asymptotic variance matrix for a tuple of multinomial distributions with dependent parameters." Gulf Journal of Mathematics 15, no. 2 (December 3, 2023): 117–32. http://dx.doi.org/10.56947/gjom.v15i2.1603.
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In this paper, we consider a statistical model consisting of an s-tuple of multinomial distributions whose parameters are dependent. This model is used in road safety to study the effect of a measure implemented on a set of s sites comprising a total of r accident severity levels and is depending on a parameter vector of 1+sr components under s equality constraints. The computation of the so important asymptotic variance matrix W requires some numerical matrix inversions which become very complicated for large values of s and r. To circumvent this difficulty, we use Schur complement for the exact analytic inversion and we propose a strategy for calculating W. We illustrate the effectiveness of our approach using simulated data.
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Escobar-Amado, Christian D., and Mohsen Badiey. "Effect of oceanographic fluctuations on geo-acoustic inversions and source localization using ships of opportunity." Journal of the Acoustical Society of America 155, no. 3_Supplement (March 1, 2024): A89. http://dx.doi.org/10.1121/10.0026913.
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Several merchant ship-radiated noise events were recorded in two separate seabed characterization experiments in the New England Mudpatch region in 2017 (SBCEX17) and 2022 (SBCEX22). These shallow water acoustic experiments were conducted under different oceanographic conditions, resulting in fluctuations in sound propagation. Several statistical inference approaches are used to invert geo-acoustic parameters such as sound speed and density in a mud over sand sediment (See https://doi.org/10.1121/10.0008419). In this work, we explore the effect of sound speed profile fluctuations in the water column on geo-acoustic inversions in the 360–1100 Hz frequency band. Inversions based on measured and simulated data using acoustic models are provided to support our findings. The results demonstrate that sediment parameters become more sensitive to oceanographic variations as the frequency increases and, therefore, sound speed profile fluctuations in the water column need to be taken into close consideration for more accurate geo-acoustic inversions. [Work supported by ONR].
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Song, Yang, Rui Hu, Quan Liu, Huiyang Qiu, Xiaolan Hou, Junjie Qi, and Bernard Konadu-Amoah. "Comparison of Hydraulic Travel Time and Attenuation Inversions, Thermal Tracer Tomography and Geostatistical Inversion for Aquifer Characterization: A Numerical Study." Water 15, no. 13 (June 29, 2023): 2401. http://dx.doi.org/10.3390/w15132401.
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For the characterization of heterogeneous aquifers, transient hydraulic tomography (THT) was proposed as a promising method to obtain the distribution of hydraulic parameters with satisfying spatial resolution using different approaches. These include hydraulic travel time, attenuation inversions, thermal tracer tomography, and geostatistical inversion with successive linear estimator (SLE). For the same hydrogeological test, different inversion methods tend to use different sub-data sets to obtain different hydraulic parameters. Up to now, however, few studies have focused on revealing the respective characteristics of these inversion methods and attempted to improve the accuracy of aquifer characterization by bridging the shortcomings of the inversion methods. The main objective of this study was to evaluate the utility of multiple inversion techniques on aquifer heterogeneity characterization. A series of warm water injection tests were first simulated in a fluvial aquifer analogue outcrop. The calculated head and temperature datasets from these tests were fully utilized to reveal the aquifer heterogeneity by using all of the four above-mentioned inversion methods. The results show that the thermal tracer tomography, hydraulic travel time, and attenuation tomography characterized the high permeability zones more accurately within the well area, whereas the geological statistical method tended to depict the overall distribution of K values for a larger area. By comparison analysis and combinations of the individual inversion results, the scientific and economic complementarity can be studied and some valuable advice for the choice of different inversion methods can be recommended for future practices.
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Sfîcă, Lucian, Iulian Iordache, Pavel Ichim, Alina Leahu, Marius-Mihai Cazacu, Silviu Gurlui, and Cătălin-Răzvan Trif. "The Influence of Weather Conditions and Local Climate on Particulate Matter (PM10) Concentration in Metropolitan Area of Iasi, Romania." Present Environment and Sustainable Development 12, no. 2 (October 1, 2018): 47–69. http://dx.doi.org/10.2478/pesd-2018-0029.
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Abstract The aim of this study is to evaluate the role of the weather conditions and local climate on the temporal and spatial variability of particulate matters (PM 10) in Iași city which is facing major pollution problems in the recent years. Daily data from 4 monitoring stations of Environmental Protection Agency-Iași–for main weather parameters and particulate matters – and the temperature from an inner temperature and relative humidity observation network inside the city were used for a three year study (2013-2015). Linear correlation, composite analysis and multiple regression are the main statistical methods applied in the analysis. In brief, the most important meteorological parameters enhancing air pollution in Iași seem to be represented by thermal inversions developing in the region strongly related to local climate conditions. The Pearson correlation coefficient (stronger than -0.40) between PM10 and thermal gradient, the difference in the PM10 concentration exceeding 20 μg/m3 between strong thermal inversions and unstable conditions and the leading role of thermal gradients in multiple regression are the main indicators of the great role of thermal inversion in generating and sustaining pollution conditions in this area. The maximum concentrations of PM10 occur in May and March, gathering more than 30% of the days for the entire year. Complementary studies were taken into account in order to analyse the aerosol optical properties retrieved from Aerosol Robotic Network (AERONET-NASA).
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Wyatt, Lucy R., and J. J. Green. "Developments in Scope and Availability of HF Radar Wave Measurements and Robust Evaluation of Their Accuracy." Remote Sensing 15, no. 23 (November 28, 2023): 5536. http://dx.doi.org/10.3390/rs15235536.
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HF radar systems form part of many operational coastal monitoring systems providing near-real-time surface currents for many useful applications. Although wave measurements have been possible with these systems for many years, they have not yet been adopted widely for operational monitoring because they have not been thought to be sufficiently accurate or reliable. However, the value of such data is beginning to be appreciated, and this is motivating more work on wave measurement with HF radar systems with many more papers on accuracy assessment and data availability appearing in the literature. In this paper, the wave measurement capability, limitations, and differences between different radar types are reviewed, and methods to assess accuracy are discussed and applied to phased array HF radar data obtained from the University of Plymouth WERA radars using the Seaview Software inversion method during April and November 2012 compared with directional buoy data. Good accuracy over a range of different wave parameters will be demonstrated. Newly available single-radar inversions are shown to be less accurate than dual-radar inversions, although they still provide useful data, and ways to improve performance are discussed. Swell and wind–sea components in the directional spectra are identified, and qualitative agreement with buoy peak parameters is demonstrated. Recommendations are given on statistical methods for the validation of wave parameters.
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Cheltsov, Vladislav. "Cooperative Quantum Phase Mixing Effect or Why the Continuous (He-Ne)-Laser Operates Without Inversion." Modern Physics Letters B 11, no. 28 (December 10, 1997): 1215–29. http://dx.doi.org/10.1142/s0217984997001468.
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Cooperative phase mixing effect (CPME) in the system of N-two-level atoms coupled to one and two resonance modes is described. Caused by irrationality of cooperative energy eigenvalues the CPME leads to quasi-periodic dynamics giving rise to superposition of states with both positive and negative inversions, so that the averaged inversion should be close to zero. To check inversionless operation of the continuous (He-Ne)-laser the nonperturbative theory of beatings in a rotating ring laser (RGL) has been suggested. The derived formula for beating frequency displays two states: with split frequencies of opposite modes and the lock-in regime. Comparison of this formula with the observed lock-in threshold rotation velocity has given the estimation (N_/V)~ (10-5-10-11) cm-3 as dependent on geometry and operation conditions.
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Kaufman, Zachary S., and Nicole Feldl. "Causes of the Arctic’s Lower-Tropospheric Warming Structure." Journal of Climate 35, no. 6 (March 15, 2022): 1983–2002. http://dx.doi.org/10.1175/jcli-d-21-0298.1.
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Abstract Arctic amplification has been attributed predominantly to a positive lapse rate feedback in winter, when boundary layer temperature inversions focus warming near the surface. Predicting high-latitude climate change effectively thus requires identifying the local and remote physical processes that set the Arctic’s vertical warming structure. In this study, we analyze output from the CESM Large Ensemble’s twenty-first-century climate change projection to diagnose the relative influence of two Arctic heating sources, local sea ice loss and remote changes in atmospheric heat transport. Causal effects are quantified with a statistical inference method, allowing us to assess the energetic pathways mediating the Arctic temperature response and the role of internal variability across the ensemble. We find that a step-increase in latent heat flux convergence causes Arctic lower-tropospheric warming in all seasons, while additionally reducing net longwave cooling at the surface. However, these effects only lead to small and short-lived changes in boundary layer inversion strength. By contrast, a step-decrease in sea ice extent in the melt season causes, in fall and winter, surface-amplified warming and weakened boundary layer temperature inversions. Sea ice loss also enhances surface turbulent heat fluxes and cloud-driven condensational heating, which mediate the atmospheric temperature response. While the aggregate effect of many moist transport events and seasons of sea ice loss will be different than the response to hypothetical perturbations, our results nonetheless highlight the mechanisms that alter the Arctic temperature inversion in response to CO2 forcing. As sea ice declines, the atmosphere’s boundary layer temperature structure is weakened, static stability decreases, and a thermodynamic coupling emerges between the Arctic surface and the overlying troposphere.
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Davison, Jennifer L., Robert M. Rauber, Larry Di Girolamo, and Margaret A. LeMone. "A Revised Conceptual Model of the Tropical Marine Boundary Layer. Part I: Statistical Characterization of the Variability Inherent in the Wintertime Trade Wind Regime over the Western Tropical Atlantic." Journal of the Atmospheric Sciences 70, no. 10 (October 1, 2013): 3005–24. http://dx.doi.org/10.1175/jas-d-12-0321.1.
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Abstract This paper investigates wintertime tropical marine boundary layer (TMBL) statistical characteristics over the western North Atlantic using the complete set of island-launched soundings from the Rain in Cumulus over the Ocean (RICO) experiment. The soundings are subdivided into undisturbed and disturbed classifications using two discriminators: 1) dates chosen by Global Energy and Water Cycle Experiment (GEWEX) Cloud System Studies (GCSS) investigators to construct the mean RICO sounding and 2) daily average rain rates. A wide range of relative humidity (RH) values was observed between the surface and 8.0 km. At 2.0 km, half the RH values were within 56%–89%; at 4.0 km, half were within 13%–61%. The rain-rate method of separating disturbed and undisturbed soundings appears more meaningful than the GCSS method. The median RH for disturbed conditions using the rain-rate method showed moister conditions from the surface to 8.0 km, with maximum RH differences of 30%–40%. Moist air generally extended higher on disturbed than undisturbed days. Based on equivalent potential temperature, wind direction, and RH analyses, the most common altitude marking the TMBL top was about 4.0 km. Temperature inversions (over both 50- and 350-m intervals) were observed at every altitude above 1.2 km; there were no dominant inversion heights and most of the inversions were weak. Wind direction analyses indicated that winds within the TMBL originated from more tropical latitudes on disturbed days. The analyses herein suggest that the RICO profile used to initialize many model simulations of this environment represents only a small subset of the broad range of possible conditions characterizing the wintertime trades.
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Li, Liyong, and Hamdi A. Tchelepi. "Conditional Statistical Moment Equations for Dynamic Data Integration in Heterogeneous Reservoirs." SPE Reservoir Evaluation & Engineering 9, no. 03 (June 1, 2006): 280–88. http://dx.doi.org/10.2118/92973-pa.
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Summary An inversion method for the integration of dynamic (pressure) data directly into statistical moment equations (SMEs) is presented. The method is demonstrated for incompressible flow in heterogeneous reservoirs. In addition to information about the mean, variance, and correlation structure of the permeability, few permeability measurements are assumed available. Moreover, few measurements of the dependent variable are available. The first two statistical moments of the dependent variable (pressure) are conditioned on all available information directly. An iterative inversion scheme is used to integrate the pressure data into the conditional statistical moment equations (CSMEs). That is, the available information is used to condition, or improve the estimates of, the first two moments of permeability, pressure, and velocity directly. This is different from Monte Carlo (MC) -based geostatistical inversion techniques, where conditioning on dynamic data is performed for one realization of the permeability field at a time. In the MC approach, estimates of the prediction uncertainty are obtained from statistical post-processing of a large number of inversions, one per realization. Several examples of flow in heterogeneous domains in a quarter-five-spot setting are used to demonstrate the CSME-based method. We found that as the number of pressure measurements increases, the conditional mean pressure becomes more spatially variable, while the conditional pressure variance gets smaller. Iteration of the CSME inversion loop is necessary only when the number of pressure measurements is large. Use of the CSME simulator to assess the value of information in terms of its impact on prediction uncertainty is also presented. Introduction The properties of natural geologic formations (e.g., permeability) rarely display uniformity or smoothness. Instead, they usually show significant variability and complex patterns of correlation. The detailed spatial distributions of reservoir properties, such as permeability, are needed to make performance predictions using numerical reservoir simulation. Unfortunately, only limited data are available for the construction of these detailed reservoir-description models. Consequently, our incomplete knowledge (uncertainty) about the property distributions in these highly complex natural geologic systems means that significant uncertainty accompanies predictions of reservoir flow performance. To deal with the problem of characterizing reservoir properties that exhibit such variability and complexity of spatial correlation patterns when only limited data are available, a probabilistic framework is commonly used. In this framework, the reservoir properties (e.g., permeability) are assumed to be a random space function. As a result, flow-related properties such as pressure, velocity, and saturations are random functions. We assume that the available information about the permeability field includes a few measurements in addition to the spatial correlation structure, which we take here as the two-point covariance. This incomplete knowledge (uncertainty) about the detailed spatial distribution of permeability is the only source of uncertainty in our problem. Uncertainty about the detailed distribution of the permeability field in the reservoir leads to uncertainty in the computed predictions of the flow field (e.g., pressure).
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Sengupta, Madhumita, Houzhu Zhang, Yang Zhao, Mike Jervis, and Dario Grana. "Direct depth-domain Bayesian amplitude-variation-with-offset inversion." GEOPHYSICS 86, no. 5 (August 2, 2021): M167—M176. http://dx.doi.org/10.1190/geo2020-0219.1.
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We have developed a new approach to perform Bayesian linearized amplitude-variation-with-offset (AVO) inversion in the depth domain using nonstationary wavelets. Bayesian linearized AVO inversion, a hybrid approach combining physics-based models with statistical learning, has gained immense popularity because of its superior computational speed and ability to estimate uncertainties in inverted model parameters. Bayesian linearized AVO inversion is performed on time-domain seismic data; therefore, depth-imaged seismic cannot be inverted directly using this method and would require depth-to-time conversion before AVO inversion can be done. Subsequently, time-to-depth conversion of the inverted volumes would be required for reservoir modeling and well placement. Domain conversions introduce additional uncertainty in geophysical workflows. In conventional AVO inversion, the seismic wavelet is assumed to be stationary, and this assumption leads to a restriction in the length of the time window over which the inversion can be performed. Therefore, AVO inversion is usually restricted to a narrow time window around the target of interest, and if multiple targets are present at different depths, multiple inversions must be run on the same volume. Depth-domain amplitude inversion is a recent development and has been previously presented in an iterative formulation. Implementing linearized Bayesian inversion directly in the depth domain using nonstationary wavelets is a convenient new approach that takes advantage of superior computational speed and uncertainty quantification without compromising the accurate spatial location that depth imaging provides. Combining these two ideas creates a novel, unique, and powerful seismic inversion technique that can be useful for quantitative interpretation and reservoir characterization.
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Paasche, Hendrik, Jens Tronicke, Klaus Holliger, Alan G. Green, and Hansruedi Maurer. "Integration of diverse physical-property models: Subsurface zonation and petrophysical parameter estimation based on fuzzy c -means cluster analyses." GEOPHYSICS 71, no. 3 (May 2006): H33—H44. http://dx.doi.org/10.1190/1.2192927.
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Inversions of an individual geophysical data set can be highly nonunique, and it is generally difficult to determine petrophysical parameters from geophysical data. We show that both issues can be addressed by adopting a statistical multiparameter approach that requires the acquisition, processing, and separate inversion of two or more types of geophysical data. To combine information contained in the physical-property models that result from inverting the individual data sets and to estimate the spatial distribution of petrophysical parameters in regions where they are known at only a few locations, we demonstrate the potential of the fuzzy [Formula: see text]-means (FCM) clustering technique. After testing this new approach on synthetic data, we apply it to limited crosshole georadar, crosshole seismic, gamma-log, and slug-test data acquired within a shallow alluvial aquifer. The derived multiparameter model effectively outlines the major sedimentary units observed in numerous boreholes and provides plausible estimates for the spatial distributions of gamma-ray emitters and hydraulic conductivity.
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Luque, Amalia, Alejandro Carrasco, Alejandro Martín, and Juan Ramón Lama. "Exploring Symmetry of Binary Classification Performance Metrics." Symmetry 11, no. 1 (January 3, 2019): 47. http://dx.doi.org/10.3390/sym11010047.
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Selecting the proper performance metric constitutes a key issue for most classification problems in the field of machine learning. Although the specialized literature has addressed several topics regarding these metrics, their symmetries have yet to be systematically studied. This research focuses on ten metrics based on a binary confusion matrix and their symmetric behaviour is formally defined under all types of transformations. Through simulated experiments, which cover the full range of datasets and classification results, the symmetric behaviour of these metrics is explored by exposing them to hundreds of simple or combined symmetric transformations. Cross-symmetries among the metrics and statistical symmetries are also explored. The results obtained show that, in all cases, three and only three types of symmetries arise: labelling inversion (between positive and negative classes); scoring inversion (concerning good and bad classifiers); and the combination of these two inversions. Additionally, certain metrics have been shown to be independent of the imbalance in the dataset and two cross-symmetries have been identified. The results regarding their symmetries reveal a deeper insight into the behaviour of various performance metrics and offer an indicator to properly interpret their values and a guide for their selection for certain specific applications.
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Flecha, I., R. Carbonell, and R. W. Hobbs. "Study on the limitations of traveltime inversion in the presence of extreme velocity anomalies." Solid Earth Discussions 5, no. 1 (March 20, 2013): 189–226. http://dx.doi.org/10.5194/sed-5-189-2013.
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Abstract. The difficulties of seismic imaging beneath high velocity structures are widely recognised. In this setting, theoretical analysis of synthetic wide-angle seismic reflection data indicates that velocity models are not well constrained. A two-dimensional velocity model was built to simulate a simplified structural geometry given by a basaltic wedge placed within a sedimentary sequence. This model reproduces the geological setting in areas of special interest for the oil industry as the Faroe-Shetland Basin. A wide-angle synthetic dataset was calculated on this model using an elastic finite difference scheme. This dataset provided travel times for tomographic inversions. Results show that the original model can not be completely resolved without considering additional information. The resolution of nonlinear inversions lacks a functional mathematical relationship, therefore, statistical approaches are required. Stochastical tests based on Metropolis techniques support the need of additional information to properly resolve subbasalt structures.
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Flecha, I., R. Carbonell, and R. W. Hobbs. "Study on the limitations of travel-time inversion applied to sub-basalt imaging." Solid Earth 4, no. 2 (December 23, 2013): 543–54. http://dx.doi.org/10.5194/se-4-543-2013.
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Abstract. The difficulties of seismic imaging beneath high velocity structures are widely recognised. In this setting, theoretical analysis of synthetic wide-angle seismic reflection data indicates that velocity models are not well constrained. A two-dimensional velocity model was built to simulate a simplified structural geometry given by a basaltic wedge placed within a sedimentary sequence. This model reproduces the geological setting in areas of special interest for the oil industry as the Faroe-Shetland Basin. A wide-angle synthetic dataset was calculated on this model using an elastic finite difference scheme. This dataset provided travel times for tomographic inversions. Results show that the original model can not be completely resolved without considering additional information. The resolution of nonlinear inversions lacks a functional mathematical relationship, therefore, statistical approaches are required. Stochastic tests based on Metropolis techniques support the need of additional information to properly resolve sub-basalt structures.
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Dong, Wenbo, Yonggen Li, Zhixian Gui, and Lei Zhou. "Theory and Application of Geostatistical Inversion: A Facies-Constrained MCMC Algorithm." Processes 11, no. 5 (April 26, 2023): 1335. http://dx.doi.org/10.3390/pr11051335.
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To improve the prediction of thin reservoirs with special geophysical responses, a geostatistical inversion technique is proposed based on an in-depth analysis of the theory of geostatistical inversion. This technique is based on the Markov chain Monte Carlo algorithm, to which we added the contents of facies-constrained. The feasibility of the technique and the reliability of the prediction results are demonstrated by a prediction of the sand bodies in the braided river channel bars in the Xiazijie Oilfield in the Junggar Basin. Based on the MCMC algorithm, the results show that leveraging the lateral changes in the seismic waveforms as geologically relevant information to drive the construction of the variogram and the optimization of the statistical sampling can largely overcome the obstacle that prevents traditional geostatistical inversions from accurately delineating the sedimentary characteristics; thereby, the proposed algorithm truly achieves facies-constrained geostatistical inversion. The case study of the Xiazijie Oilfield showed the feasibility and reliability of this technology. The prediction accuracy of the FCMCMC algorithm-based geostatistical inversion is as high as 6 m for thin interbedded reservoirs, and the coincidence rate between the prediction results and the well log data is more than 85%, which confirms the reliability of the technique. The demonstrated performance of the proposed technique provides a preliminary reference for the prediction of the thin interbedded reservoirs formed in terrestrial sedimentary basins and characterized by small thicknesses and rapid lateral changes with special geophysical responses.
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Sun, Jiajia, and Yaoguo Li. "Joint inversion of multiple geophysical data using guided fuzzy c-means clustering." GEOPHYSICS 81, no. 3 (May 2016): ID37—ID57. http://dx.doi.org/10.1190/geo2015-0457.1.
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Joint inversion of multiple geophysical data has become an active area of research due to its potential to greatly enhance the fidelity of inverted models. Many open questions and challenges still remain. One of them is how to effectively incorporate into joint inversion multimodal petrophysical information that describes the statistical behavior of physical property values in the parameter domain (i.e., in a crossplot). We have regarded the multimodal petrophysical data as different clusters in the parameter domain and developed an approach that handles multimodal petrophysical information through guided fuzzy c-means (FCM) clustering in the parameter domain. We inverted the petrophysical data in the parameter domain in a similar manner to and simultaneously with the geophysical data in the spatial domain through minimizing one common objective function. Numerical examples have determined that the resulting models from this multidomain joint-inversion strategy are able to reproduce both the geophysical and the petrophysical data. In addition to incorporating a priori multimodal petrophysical information into inversion, guided FCM clustering also allows us to integrate geology differentiation and geophysical inversion into one unified framework that makes these two components positively affect each other. Geology differentiation results were obtained as a direct output from joint inversion. We have also developed a strategy for imposing different clustering constraints in different model regions, allowing region-specific a priori petrophysical information to be incorporated into inversion. We have applied our joint-inversion algorithm to the SEG/EAGE salt model in four different scenarios, and we found that the proposed algorithm produced much better geophysical models and geology differentiation results than separate inversions.
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Goñi, B., E. S. de Vaio, M. Beltrami, M. S. Leira, M. Crivel, F. Panzera, P. Castellanos, and A. Basso. "Geographic patterns of chromosomal variation in populations of the grasshopper (Trimerotropis pallidipennis) from southern Argentina." Canadian Journal of Genetics and Cytology 27, no. 3 (June 1, 1985): 259–71. http://dx.doi.org/10.1139/g85-039.
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Geographic variation has been studied on seven south Argentina populations of Trimerotropis pallidipennis polymorphic with respect to centromere position. Univariate and multivariate statistical analysis were used to assess interpopulation relationships by considering the inversion frequency, the chiasma frequency, and the population distance from the Andes, which is considered to be the hypothetical pathway of migration of this typically North American species to southern latitudes. A cluster analysis indicated strong chromosomal differentiation between the almost monomorphic populations in the Andes' "precordillera" and the highly polymorphic populations in more eastern locations. It also showed that chromosomal similarity between populations could be predicted by geographic proximity. No attempt has been made to relate such a pattern of chromosome variation to ecological data. The lack of any clear relationship with phytogeographic regions or climatic characteristics suggests that microenvironmental factors related to aridity may be important in this case. The presence of inversions within a population has a notable effect on chiasma frequency and position. Chiasmata are suppressed within the inverted region of both inversion heterozygotes and homozygotes. The allelic sequences in the inverted region are thus preserved from recombination and exchanges are limited to terminal regions.Key words: geographic variation, chromosome polymorphism, chiasma frequency, B chromosome, pseudomultiple associations.
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Taroudakis, Michael, Costas Smaragdakis, and N. Ross Chapman. "Denoising Underwater Acoustic Signals for Applications in Acoustical Oceanography." Journal of Computational Acoustics 25, no. 02 (January 25, 2017): 1750015. http://dx.doi.org/10.1142/s0218396x17500151.
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A method for denoising underwater acoustic signals used in applications of acoustical oceanography is presented. The method has been introduced for imaging denoising and has been modified to be applied with acoustic signals. The method keeps the energy significant part of the raw signal and reduces the effects of noise by comparing overlapping signal windows and keeping components which resemble true signal energy. It is shown by means of characteristic experiments in connection with a statistical signal characterization scheme based on wavelet transform, that using the statistical features of the wavelet sub-band coefficients of the denoised signal, tomography or geoacoustic inversions lead to a reliable estimation of the parameters of a marine environment.
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Taroudakis, Michael I., and Costas Smaragdakis. "Tomographic and Bottom Geoacoustic Inversions Using Genetic Algorithms and a Statistical Characterization of the Acoustic Signal." Acta Acustica united with Acustica 95, no. 5 (September 1, 2009): 814–22. http://dx.doi.org/10.3813/aaa.918212.
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