scholarly journals Zonal-mean data set of global atmospheric reanalyses on pressure levels

2018 ◽  
Vol 10 (4) ◽  
pp. 1925-1941 ◽  
Author(s):  
Patrick Martineau ◽  
Jonathon S. Wright ◽  
Nuanliang Zhu ◽  
Masatomo Fujiwara
Keyword(s):  
Three Dimensional ◽  
Reanalysis Data ◽  
Environmental Data ◽  
Data Sets ◽  
Heating Rates ◽  
Data Set ◽  
Intercomparison Project ◽  
Complete Set ◽  
The Common ◽  
Transformed Eulerian Mean

Abstract. This data set, which is prepared for the Stratosphere–troposphere Processes And their Role in Climate (SPARC) Reanalysis Intercomparison Project (S-RIP), provides several zonal-mean diagnostics computed from reanalysis data on pressure levels. Diagnostics are currently provided for a variety of reanalyses, including ERA-40, ERA-Interim, ERA-20C, NCEP–NCAR, NCEP–DOE, CFSR, 20CR v2 and v2c, JRA-25, JRA-55, JRA-55C, JRA-55AMIP, MERRA, and MERRA-2. The data set will be expanded to include additional reanalyses as they become available. Basic dynamical variables (such as temperature, geopotential height, and three-dimensional winds) are provided in addition to a complete set of terms from the Eulerian-mean and transformed-Eulerian-mean momentum equations. Total diabatic heating and its long-wave and shortwave components are included as availability permits, along with heating rates diagnosed from the basic dynamical variables using the zonal-mean thermodynamic equation. Two versions of the data set are provided, one that uses horizontal and vertical grids provided by the various reanalysis centers and another that uses a common grid (CG) to facilitate comparison among data sets. For the common grid, all diagnostics are interpolated horizontally onto a regular 2.5∘×2.5∘ grid for a subset of pressure levels that are common among all included reanalyses. The dynamical (Martineau, 2017, https://doi.org/10.5285/b241a7f536a244749662360bd7839312) and diabatic (Wright, 2017, https://doi.org/10.5285/70146c789eda4296a3c3ab6706931d56) variables are archived and maintained by the Centre for Environmental Data Analysis (CEDA).

scholarly journals Zonal-mean data set of global atmospheric reanalyses on pressure levels

2018 ◽  
Author(s):  
Patrick Martineau ◽  
Jonathon S. Wright ◽  
Nuanliang Zhu ◽  
Masatomo Fujiwara
Keyword(s):  
Three Dimensional ◽  
Short Wave ◽  
Reanalysis Data ◽  
Environmental Data ◽  
Data Sets ◽  
Heating Rates ◽  
Data Set ◽  
Intercomparison Project ◽  
Complete Set ◽  
Transformed Eulerian Mean

Abstract. This data set, which is prepared for the SPARC-Reanalysis Intercomparison Project (S-RIP), provides several zonal-mean diagnostics computed from reanalysis data on pressure levels. Diagnostics are currently provided for a variety of reanalyses, including ERA-40, ERA-Interim, ERA-20C, NCEP-NCAR, NCEP-DOE, CFSR, 20CR v2 and v2c, JRA-25, JRA-55, JRA-55C, JRA-55AMIP, MERRA, and MERRA-2. The data set will be expanded to include additional reanalyses as they become available. Basic dynamical variables (such as temperature, geopotential height and three-dimensional winds) are provided in addition to a complete set of terms from the Eulerian-mean and transformed Eulerian-mean momentum equations. Total diabatic heating and its long-wave and short-wave components are included as availability permits, along with heating rates diagnosed from the basic dynamical variables using the zonal-mean thermodynamic equation. Two versions of the data set are provided, one that uses horizontal and vertical grids provided by the various reanalysis centers, and another that uses a common grid to facilitate comparison among data sets. For the common grid, all diagnostics are interpolated horizontally onto a regular 2.5° ×2.5° grid for a subset of pressure levels that are common amongst all included reanalyses. The dynamical (Martineau, 2017, http://dx.doi.org/10.5285/b241a7f536a244749662360bd7839312) and diabatic (Wright, 2017, http://dx.doi.org/10.5285/70146c789eda4296a3c3ab6706931d56) variables are archived and maintained by the Centre for Environmental Data Analysis (CEDA).

Three Dimensional Visualization of Complex Environmental Data Sets of Variable Resolution

Leonardo ◽  
2013 ◽  
Vol 46 (3) ◽  
pp. 290-291
Author(s):  
Brian Burnham
Keyword(s):  
New Media ◽  
Social Networking ◽  
Three Dimensional ◽  
Data Retrieval ◽  
Environmental Data ◽  
Data Sets ◽  
Data Set ◽  
Variable Resolution ◽  
The Arts ◽  
Inherent Problem

Three dimensional visualization of complex, variable resolution data sets is an inherent problem with the increase in data retrieval and processing methods. This problem translates across many disciplines in the sciences and engineering, but also in the arts, new media and social networking. In this paper the authors report on a project to integrate terrestrial and aerial based terrain data with variable degrees of resolution. Future implications of big data set visualization and the development of transdisciplinary approaches that can be used in both the sciences and the arts are discussed.

scholarly journals Quantifying uncertainties of climate signals in chemistry climate models related to the 11-year solar cycle – Part 1: Annual mean response in heating rates, temperature, and ozone

2020 ◽  
Vol 20 (11) ◽  
pp. 6991-7019
Author(s):  
Markus Kunze ◽  
Tim Kruschke ◽  
Ulrike Langematz ◽  
Miriam Sinnhuber ◽  
Thomas Reddmann ◽  
...  
Keyword(s):  
Atmospheric Chemistry ◽  
Solar Minimum ◽  
Climate Model ◽  
Solar Maximum ◽  
Sunspot Cycle ◽  
Spectral Irradiance ◽  
Data Sets ◽  
Reference Spectrum ◽  
Heating Rates ◽  
Data Set

Abstract. Variations in the solar spectral irradiance (SSI) with the 11-year sunspot cycle have been shown to have a significant impact on temperatures and the mixing ratios of atmospheric constituents in the stratosphere and mesosphere. Uncertainties in modelling the effects of SSI variations arise from uncertainties in the empirical models reconstructing the prescribed SSI data set as well as from uncertainties in the chemistry–climate model (CCM) formulation. In this study CCM simulations with the ECHAM/MESSy Atmospheric Chemistry (EMAC) model and the Community Earth System Model 1 (CESM1)–Whole Atmosphere Chemistry Climate Model (WACCM) have been performed to quantify the uncertainties of the solar responses in chemistry and dynamics that are due to the usage of five different SSI data sets or the two CCMs. We apply a two-way analysis of variance (ANOVA) to separate the influence of the SSI data sets and the CCMs on the variability of the solar response in shortwave heating rates, temperature, and ozone. The solar response is derived from climatological differences of time slice simulations prescribing SSI for the solar maximum in 1989 and near the solar minimum in 1994. The SSI values for the solar maximum of each SSI data set are created by adding the SSI differences between November 1994 and November 1989 to a common SSI reference spectrum for near-solar-minimum conditions based on ATLAS-3 (Atmospheric Laboratory of Applications and Science-3). The ANOVA identifies the SSI data set with the strongest influence on the variability of the solar response in shortwave heating rates in the upper mesosphere and in the upper stratosphere–lower mesosphere. The strongest influence on the variability of the solar response in ozone and temperature is identified in the upper stratosphere–lower mesosphere. However, in the region of the largest ozone mixing ratio, in the stratosphere from 50 to 10 hPa, the SSI data sets do not contribute much to the variability of the solar response when the Spectral And Total Irradiance REconstructions-T (SATIRE-T) SSI data set is omitted. The largest influence of the CCMs on variability of the solar responses can be identified in the upper mesosphere. The solar response in the lower stratosphere also depends on the CCM used, especially in the tropics and northern hemispheric subtropics and mid-latitudes, where the model dynamics modulate the solar responses. Apart from the upper mesosphere, there are also regions where the largest fraction of the variability of the solar response is explained by randomness, especially for the solar response in temperature.

scholarly journals High resolution atmospheric reconstruction for Europe 1948–2012: coastDat2

2013 ◽  
Vol 6 (2) ◽  
pp. 779-809 ◽  
Author(s):  
B. Geyer
Keyword(s):  
Climate Model ◽  
Numerical Models ◽  
Regional Climate ◽  
Reanalysis Data ◽  
Data Sets ◽  
Data Set ◽  
Horizontal Grid ◽  
Global Reanalysis ◽  
Marine Climate

Abstract. The coastDat data sets were produced to give a consistent and homogeneous database mainly for assessing weather statistics and long-term changes for Europe, especially in data sparse regions. A sequence of numerical models was employed to reconstruct all aspects of marine climate (such as storms, waves, surges etc.) over many decades. Here, we describe the atmospheric part of coastDat2 (Geyer and Rockel, 2013, doi:10.1594/WDCC/coastDat-2_COSMO-CLM). It consists of a regional climate reconstruction for entire Europe, including Baltic and North Sea and parts of the Atlantic. The simulation was done for 1948 to 2012 with a regional climate model and a horizontal grid size of 0.22° in rotated coordinates. Global reanalysis data were used as forcing and spectral nudging was applied. To meet the demands on the coastDat data set about 70 variables are stored hourly.

scholarly journals Plasma convection at high latitudes using the EISCAT VHF and ESR incoherent scatter radars

2000 ◽  
Vol 18 (9) ◽  
pp. 1088-1096 ◽  
Author(s):  
J. M. Holt ◽  
A. P. van Eyken
Keyword(s):  
Three Dimensional ◽  
Data Sets ◽  
Plasma Convection ◽  
Vhf Radar ◽  
Common Assumption ◽  
Incoherent Scatter ◽  
Incoherent Scatter Radars ◽  
The Common ◽  
Convection Patterns

Abstract. The recent availability of substantial data sets taken by the EISCAT Svalbard Radar allows several important tests to be made on the determination of convection patterns from incoherent scatter radar results. During one 30-h period, the Svalbard Radar made 15 min scans combining local field aligned observations with two, low elevation positions selected to intersect the two beams of the Common Programme Four experiment being simultaneously conducted by the EISCAT VHF radar at Tromsø. The common volume results from the two radars are compared. The plasma convection velocities determined independently by the two radars are shown to agree very closely and the combined three-dimensional velocity data used to test the common assumption of negligible field-aligned flow in this regime.Key words: Ionosphere (auroral ionosphere; polar ionosphere) - Magnetospheric physics (plasma convection)

scholarly journals Accuracy of Low-Cost Alternative Facial Scanners: A Prospective Cohort Study.

2021 ◽  
Author(s):  
Alexander K. Bartella ◽  
Josefine Laser ◽  
Mohammad Kamal ◽  
Dirk Halama ◽  
Michael Neuhaus ◽  
...  
Keyword(s):  
Low Cost ◽  
Three Dimensional ◽  
Neck Surgery ◽  
Clinical Analysis ◽  
Smart Device ◽  
Data Sets ◽  
Average Deviation ◽  
Technical Improvement ◽  
Data Set ◽  
Significant Difference

Abstract Introduction: Three-dimensional facial scan images have been showing an increasingly important role in peri-therapeutic management of oral and maxillofacial and head and neck surgery cases. Face scan images can be open using optical facial scanners utilizing line-laser, stereophotography, structured light modality, or from volumetric data obtained from cone beam computed tomography (CBCT). The aim of this study is to evaluate, if two low-cost procedures for creating a three-dimensional face scan images are able to produce a sufficient data set for clinical analysis. Materials and methods: 50 healthy volunteers were included in the study. Two test objects with defined dimensions were attached to the forehead and the left cheek. Anthropometric values were first measured manually, and consecutively, face scans were performed with a smart device and manual photogrammetry and compared to the manually measured data sets.Results: Anthropometric distances on average deviated 2.17 mm from the manual measurement (smart device scanning 3.01 mm vs. photogrammetry 1.34 mm), with 7 out of 8 deviations were statistically significant. Of a total of 32 angles, 19 values showed a significant difference to the original 90° angles. The average deviation was 6.5° (smart device scanning 10.1° vs. photogrammetry 2.8°).Conclusion: Manual photogrammetry with a regular photo-camera shows higher accuracy than scanning with smart device. However, the smart device was more intuitive in handling and further technical improvement of the cameras used should be watched carefully.

scholarly journals Quantifying uncertainties of climate signals related to the 11–year solar cycle. Part I: Annual mean response in heating rates,temperature and ozone

2020 ◽  
Author(s):  
Markus Kunze ◽  
Tim Kruschke ◽  
Ulrike Langematz ◽  
Miriam Sinnhuber ◽  
Thomas Reddmann ◽  
...  
Keyword(s):  
Atmospheric Chemistry ◽  
Climate Model ◽  
Sunspot Cycle ◽  
Spectral Irradiance ◽  
Data Sets ◽  
Heating Rates ◽  
Data Set ◽  
Mixing Ratios ◽  
Solar Signal ◽  
The Tropics

Abstract. Variations of the solar spectral irradiance (SSI) with the 11-year sunspot cycle have been shown to have a significant impact on temperatures and the mixing ratios of atmospheric constituents in the stratosphere and mesosphere. Uncertainties in modelling the effects of SSI variations arise from uncertainties in the empirical models reconstructing the prescribed SSI data set as well as from uncertainties in the chemistry-climate model (CCM) formulation. In this study CCM simulations with the ECHAM MESSy Atmospheric Chemistry (EMAC) model and the Community Earth System Model 1 (CESM1) – Whole Atmosphere Chemistry Climate Model (WACCM) have been performed to quantify the uncertainties of the solar responses in chemistry and dynamics that are due to the usage of five different SSI data sets or the two CCMs. We apply a two-way analysis of variance (ANOVA) to separate the influence of the SSI data sets and the CCMs on the variability of the solar response in shortwave heating rates, temperature and ozone. The ANOVA identifies the SSI data set with the strongest influence on the variability of the solar signal in shortwave heating rates in the upper mesosphere and in the upper stratosphere/lower mesosphere. The strongest influence on the variability of the solar signal in ozone and temperature is identified in the upper stratosphere/lower mesosphere. The largest influence of the CCMs on variability of the solar responses can be identified in the upper mesosphere. The solar response in the lower stratosphere also depends on the CCM used, especially in the tropics and northern hemispheric subtropics and mid latitudes, where the model dynamics modulate the solar responses.

Semi-Automated Roller Parameters Extraction from Terrestrial Lidar

2021 ◽  
Vol 87 (12) ◽  
pp. 879-890
Author(s):  
Sagar S. Deshpande ◽  
Mike Falk ◽  
Nathan Plooster
Keyword(s):  
Rotation Axis ◽  
Moving Average ◽  
Three Dimensional ◽  
Data Sets ◽  
Steel Mill ◽  
Data Set ◽  
Terrestrial Lidar ◽  
Two Dimensional Image ◽  
Average Rotation

Rollers are an integral part of a hot-rolling steel mill. They transport hot metal from one end of the mill to another. The quality of the steel highly depends on the surface quality of the rollers. This paper presents semi-automated methodologies to extract roller parameters from terrestrial lidar points. The procedure was divided into two steps. First, the three-dimensional points were converted to a two-dimensional image to detect the extents of the rollers using fast Fourier transform image matching. Lidar points for every roller were iteratively fitted to a circle. The radius and center of the fitted circle were considered as the average radius and average rotation axis of the roller, respectively. These parameters were also extracted manually and were compared to the measured parameters for accuracy analysis. The proposed methodology was able to extract roller parameters at millimeter level. Erroneously identified rollers were identified by moving average filters. In the second step, roller parameters were determined using the filtered roller points. Two data sets were used to validate the proposed methodologies. In the first data set, 366 out of 372 rollers (97.3%) were identified and modeled. The second, smaller data set consisted of 18 rollers which were identified and modelled accurately.

Geostatistical Joint Interpretation of Gravity and Magnetotelluric Data of the US Cordillera

2021 ◽  
Author(s):  
Mohammad Shehata ◽  
Hideki Mizunaga
Keyword(s):  
Gravity Data ◽  
Three Dimensional ◽  
Data Sets ◽  
Spatial Expansion ◽  
Magnetotelluric Data ◽  
Data Set ◽  
Entire Area ◽  
Mean Values ◽  
Local Means ◽  
The Us

<p>Long-period magnetotelluric and gravity data were acquired to investigate the US cordillera's crustal structure. The magnetotelluric data are being acquired across the continental USA on a quasi-regular grid of ∼70 km spacing as an electromagnetic component of the National Science Foundation EarthScope/USArray Program. International Gravimetreique Bureau compiled gravity Data at high spatial resolution. Due to the difference in data coverage density, the geostatistical joint integration was utilized to map the subsurface structures with adequate resolution. First, a three-dimensional inversion of each data set was applied separately.</p><p>The inversion results of both data sets show a similarity of structure for data structuralizing. The individual result of both data sets is resampled at the same locations using the kriging method by considering each inversion model to estimate the coefficient. Then, the Layer Density Correction (LDC) process's enhanced density distribution was applied to MT data's spatial expansion process. Simple Kriging with varying Local Means (SKLM) was applied to the residual analysis and integration. For this purpose, the varying local means of the resistivity were estimated using the corrected gravity data by the Non-Linear Indicator Transform (NLIT), taking into account the spatial correlation. After that, the spatial expansion analysis of MT data obtained sparsely was attempted using the estimated local mean values and SKLM method at the sections where the MT survey was carried out and for the entire area where density distributions exist. This research presents the integration results and the stand-alone inversion results of three-dimensional gravity and magnetotelluric data.</p>

3-D prestack migration of common‐azimuth data

Geophysics ◽  
1996 ◽  
Vol 61 (6) ◽  
pp. 1822-1832 ◽  
Author(s):  
Biondo Biondi ◽  
Gopal Palacharla
Keyword(s):  
Stationary Phase ◽  
Constant Velocity ◽  
Downward Continuation ◽  
Theoretical Interpretation ◽  
Data Sets ◽  
Phase Approximation ◽  
Data Set ◽  
Prestack Migration ◽  
Surface Location ◽  
The Common

In principle, downward continuation of 3-D prestack data should be carried out in the 5-D space of full 3-D prestack geometry (recording time, source surface location, and receiver surface location), even when the data sets to be migrated have fewer dimensions, as in the case of common‐azimuth data sets that are only four dimensional. This increase in dimensionality of the computational space causes a severe increase in the amount of computations required for migrating the data. Unless this computational efficiency issue is solved, 3-D prestack migration methods based on downward continuation cannot compete with Kirchhoff methods. We address this problem by presenting a method for downward continuing common‐azimuth data in the original 4-D space of the common‐azimuth data geometry. The method is based on a new common‐azimuth downward‐continuation operator derived by a stationary‐phase approximation of the full 3-D prestack downward‐continuation operator expressed in the frequency‐wavenumber domain. Although the new common‐azimuth operator is exact only for constant velocity, a ray‐theoretical interpretation of the stationary‐phase approximation enables us to derive an accurate generalization of the method to media with both vertical and lateral velocity variations. The proposed migration method successfully imaged a synthetic data set that was generated assuming strong lateral and vertical velocity gradients. The common‐azimuth downward‐continuation theory also can be applied to the derivation of a computationally efficient constant‐velocity Stolt migration of common‐azimuth data. The Stolt migration formulation leads to the important theoretical result that constant‐velocity common‐azimuth migration can be split into two exact sequential migration processes: 2-D prestack migration along the inline direction, followed by 2-D zero‐offset migration along the cross‐line direction.

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