scholarly journals STABILITY AND IMPULSE RESPONSE OF EMPIRICAL EIGENFUNCTIONS

1976 ◽  
Vol 1 (15) ◽  
pp. 76 ◽  
Author(s):  
Clinton D. Winant ◽  
David G. Aubrey

The statistical method of empirical eigenfunctions has been applied to four years of beach profile data. The eigenfunctions associated with the three largest eigenvalues are shown to be stable for data sets of one, two, three, and four years length, and they correctly describe beach changes caused by storm activity. The usefulness of the eigenfunction representation is confirmed as a concise means of representing beach profile variability.

2013 ◽  
Vol 6 (3) ◽  
pp. 703-717 ◽  
Author(s):  
C. Córdoba-Jabonero ◽  
J. L. Guerrero-Rascado ◽  
D. Toledo ◽  
M. Parrondo ◽  
M. Yela ◽  
...  

Abstract. Polar stratospheric clouds (PSCs) play an important role in polar ozone depletion, since they are involved in diverse ozone destruction processes (chlorine activation, denitrification). The degree of that ozone reduction is depending on the type of PSCs, and hence on their occurrence. Therefore PSC characterization, mainly focused on PSC-type discrimination, is widely demanded. The backscattering (R) and volume linear depolarization (δV) ratios are the parameters usually used in lidar measurements for PSC detection and identification. In this work, an improved version of the standard NASA/Micro Pulse Lidar (MPL-4), which includes a built-in depolarization detection module, has been used for PSC observations above the coastal Antarctic Belgrano II station (Argentina, 77.9° S 34.6° W, 256 m a.s.l.) since 2009. Examination of the MPL-4 δV feature as a suitable index for PSC-type discrimination is based on the analysis of the two-channel data, i.e., the parallel (p-) and perpendicular (s-) polarized MPL signals. This study focuses on the comparison of coincident δV-profiles as obtained from ground-based MPL-4 measurements during three Antarctic winters with those reported from the space-borne lidar CALIOP (Cloud-Aerosol Lidar with Orthogonal Polarization) aboard the CALIPSO (Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation) satellite in the same period (83 simultaneous cases are analysed for 2009–2011 austral winter times). Three different approaches are considered for the comparison analysis between both lidar profile data sets in order to test the degree of agreement: the correlation coefficient (CC), as a measure of the relationship between both PSC vertical structures; the mean differences together with their root mean square (RMS) values found between data sets; and the percentage differences (BIAS), parameter also used in profiling comparisons between CALIOP and other ground-based lidar systems. All of them are examined as a function of the CALIPSO ground-track distance from the Belgrano II station. Results represent a relatively good agreement between both ground-based MPL-4 and space-borne CALIOP profiles of the volume linear depolarization ratio δV for PSC events, once the MPL-4 depolarization calibration parameters are applied. Discrepancies between CALIOP and MPL-4 profiles in vertical layering structure are enhanced from 20 km up, likely due to a decrease of the signal-to-noise ratio (SNR) for both lidar systems at those altitudes. Regarding the results obtained from the mean and the percentage differences found between MPL-4 and CALIOP δV profiles, a predominance of negative values is also observed, indicating a generalized underestimation of the MPL-4 depolarization as compared to that reported by CALIOP. However, absolute differences between those δV-profile data sets are no higher than a 10 ± 11% in average. Moreover, the degree of agreement between both lidar δV data sets is slightly dependent on the CALIPSO ground-track overpass distance from the Belgrano II station. That is, small discrepancies are found when CALIPSO ground-track distance is as close as far from the ground-based station. These results would indicate that MPL-4 depolarization observations would reflect relatively well the PSC field that CALIOP can detect at relatively large distances from the ground-based station. As a consequence, PSC properties can be statistically similar, on average, over large volumes, and hence the present weak disagreement found between both the lidar δV data sets can be likely dominated by small spatial PSC inhomogeneities along the CALIPSO separation from the station. This statement is based on the fact that Belgrano II is a station located well inside the stable Antarctic polar vortex, allowing determined thermodynamic conditions leading to a very low variability in the PSC field, and in their properties.


2018 ◽  
Author(s):  
Stephanie de Villiers

Abstract. An annual and a seasonal biogeochemical climatology had been constructed for the Southern Benguela Upwelling System, from in situ data collected along a 12 station monitoring line, sampled at monthly intervals from 2001 to 2012. The monitoring line reaches a maximum offshore distance of almost 190 km, with monitoring station depths ranging from 27 to 1465 m. In addition to temperature, salinity and oxygen CTD profile data, archived monitoring data for the macro-nutrients (phosphate, nitrate + nitrite, silicate) and chlorophyll-a was evaluated. The climatologies exhibit clear spatial and seasonal variability patterns for all parameters, that yield important insight into the SBUS upwelling cycle. These data sets comprise valuable additions to our knowledge base, and will aid both future modelling efforts and studies of biogeochemical processes in upwelling systems. Data for the constructed climatologies have been made available via the PANGAEA Data Archiving and Publication database at http://doi.pangaea.de/10.1594/PANGAEA.882218.


2021 ◽  
Vol 13 (12) ◽  
pp. 5711-5729
Author(s):  
Sandip S. Dhomse ◽  
Carlo Arosio ◽  
Wuhu Feng ◽  
Alexei Rozanov ◽  
Mark Weber ◽  
...  

Abstract. High-quality stratospheric ozone profile data sets are a key requirement for accurate quantification and attribution of long-term ozone changes. Satellite instruments provide stratospheric ozone profile measurements over typical mission durations of 5–15 years. Various methodologies have then been applied to merge and homogenise the different satellite data in order to create long-term observation-based ozone profile data sets with minimal data gaps. However, individual satellite instruments use different measurement methods, sampling patterns and retrieval algorithms which complicate the merging of these different data sets. In contrast, atmospheric chemical models can produce chemically consistent long-term ozone simulations based on specified changes in external forcings, but they are subject to the deficiencies associated with incomplete understanding of complex atmospheric processes and uncertain photochemical parameters. Here, we use chemically self-consistent output from the TOMCAT 3-D chemical transport model (CTM) and a random-forest (RF) ensemble learning method to create a merged 42-year (1979–2020) stratospheric ozone profile data set (ML-TOMCAT V1.0). The underlying CTM simulation was forced by meteorological reanalyses, specified trends in long-lived source gases, solar flux and aerosol variations. The RF is trained using the Stratospheric Water and OzOne Satellite Homogenized (SWOOSH) data set over the time periods of the Microwave Limb Sounder (MLS) from the Upper Atmosphere Research Satellite (UARS) (1991–1998) and Aura (2005–2016) missions. We find that ML-TOMCAT shows excellent agreement with available independent satellite-based data sets which use pressure as a vertical coordinate (e.g. GOZCARDS, SWOOSH for non-MLS periods) but weaker agreement with the data sets which are altitude-based (e.g. SAGE-CCI-OMPS, SCIAMACHY-OMPS). We find that at almost all stratospheric levels ML-TOMCAT ozone concentrations are well within uncertainties of the observational data sets. The ML-TOMCAT (V1.0) data set is ideally suited for the evaluation of chemical model ozone profiles from the tropopause to 0.1 hPa and is freely available via https://doi.org/10.5281/zenodo.5651194 (Dhomse et al., 2021).


Geophysics ◽  
1998 ◽  
Vol 63 (1) ◽  
pp. 213-222 ◽  
Author(s):  
L. Neil Frazer ◽  
Xinhua Sun

Inversion is an organized search for parameter values that maximize or minimize an objective function, referred to here as a processor. This note derives three new seismic processors that require neither prior deconvolution nor knowledge of the source‐receiver wavelet. The most powerful of these is the fourwise processor, as it is applicable to data sets from multiple shots and receivers even when each shot has a different unknown signature and each receiver has a different unknown impulse response. Somewhat less powerful than the fourwise processor is the pairwise processor, which is applicable to a data set consisting of two or more traces with the same unknown wavelet but possibly different gains. When only one seismogram exists the partition processor can be used. The partition processor is also applicable when there is only one shot (receiver) and each receiver (shot) has a different signature. In fourwise and pairwise inversions the unknown wavelets may be arbitrarily long in time and need not be minimum phase. In partition inversion the wavelet is assumed to be shorter in time than the data trace itself but is not otherwise restricted. None of the methods requires assumptions about the Green’s function.


Paleobiology ◽  
1978 ◽  
Vol 4 (2) ◽  
pp. 120-134 ◽  
Author(s):  
Fred L. Bookstein ◽  
Philip D. Gingerich ◽  
Arnold G. Kluge

Punctuated equilibrium and phyletic gradualism are alternative hypotheses that purport to explain the tempo and mode of evolution. We evaluate the two hypotheses, as they apply to the fossil record, on both theoretical and empirical grounds. Hidden randomness in data increases as a function of greater aggregation, and the hypothesis of punctuated equilibrium should not be applied to those examples where randomness is likely to occur. False stasis can result from a sustained pattern of emigration and immigration, and geographic variation must be studied in order to posit an unambiguous case of punctuated equilibrium. We describe a statistical method based on the general linear model for testing the relative fit of the alternative hypotheses to any set of temporally ordered metric data. Our method is hierarchical in the sense that subsets of the total explained variance can themselves be explained. The size of the first molar of the primate Pelycodus and of the condylarth Hyopsodus are analyzed. There are 17 tests in the two data sets, and we discover 12 instances of gradualism, four of punctuation and one of equilibrium.


Author(s):  
Colleen Nooney ◽  
Stuart Barber ◽  
Arief Gusnanto ◽  
Walter R. Gilks

AbstractWe introduce a new method to test efficiently for cospeciation in tritrophic systems. Our method utilises an analogy with electrical circuit theory to reduce higher order systems into bitrophic data sets that retain the information of the original system. We use a sophisticated permutation scheme that weights interactions between two trophic layers based on their connection to the third layer in the system. Our method has several advantages compared to the method of Mramba et al. [Mramba, L. K., S. Barber, K. Hommola, L. A. Dyer, J. S. Wilson, M. L. Forister and W. R. Gilks (2013): “Permutation tests for analyzing cospeciation in multiple phylogenies: applications in tri-trophic ecology,” Stat. Appl. Genet. Mol. Biol., 12, 679–701.]. We do not require triangular interactions to connect the three phylogenetic trees and an easily interpreted


2019 ◽  
Vol 9 (16) ◽  
pp. 3396 ◽  
Author(s):  
Jianfeng Wu ◽  
Yongzhu Hua ◽  
Shengying Yang ◽  
Hongshuai Qin ◽  
Huibin Qin

This paper presents a new deep neural network (DNN)-based speech enhancement algorithm by integrating the distilled knowledge from the traditional statistical-based method. Unlike the other DNN-based methods, which usually train many different models on the same data and then average their predictions, or use a large number of noise types to enlarge the simulated noisy speech, the proposed method does not train a whole ensemble of models and does not require a mass of simulated noisy speech. It first trains a discriminator network and a generator network simultaneously using the adversarial learning method. Then, the discriminator network and generator network are re-trained by distilling knowledge from the statistical method, which is inspired by the knowledge distillation in a neural network. Finally, the generator network is fine-tuned using real noisy speech. Experiments on CHiME4 data sets demonstrate that the proposed method achieves a more robust performance than the compared DNN-based method in terms of perceptual speech quality.


1982 ◽  
Vol 1 (18) ◽  
pp. 86 ◽  
Author(s):  
Takaaki Uda ◽  
Hiroshi Hashimoto

In order to analyze beach profile changes due to longshore and onshore-offshore sand transport, here is proposed a new model named the "empirical predictive model of beach profile change", which is an application of the empirical eigenfunction method. The analysis of the profile data obtained at the Misawa fishery port in Ogawarako Coast over five years from 1973 to 1977 indicates that profile changes due to longshore transport and to onshore-offshore transport can be separated. The model is shown to be effective in the analysis of profile changes near coastal structures.


Sign in / Sign up

Export Citation Format

Share Document