188,796 research outputs found
Agreement between MBI and Astudillo Mendinueta criteria (n = 139).
No full textAgreement between MBI and Astudillo Mendinueta criteria (n = 139).</p
Data for Spaulding-Astudillo and Mitchell (2024a), "A simple model for the emergence of relaxation-oscillator convection"
No full text<p>Data for Spaulding-Astudillo and Mitchell (2024a), "A simple model for the emergence of relaxation-oscillator convection"</p>
<p>The main directories have a common nomenclature: e.g., minimal_1p1S_FSC_335K_N7200, where 1p1S indicates a solar constant 1.1 times the present day (1360), FSC indicates that it is a full-sky radiation run, 335 K is the surface temperature (fixed), and N7200 refers to the relaxation timescale of 7200 seconds for CAPE in the quasi-equilibrium closure to the convection scheme. </p>
<p>In every directory, each .nc file contains 5 years of model output. There are 5 types of .nc files, which correspond to different output streams of ECHAM6. The main output stream is ..._echam.nc, which has daily-averaged output.</p>
<p>The tendencies for gross deposition (gdep_ls) and gross condensation (gcnd_ls; both with units of kg/m2/s) from the large-scale scheme are in ..._g1am.nc. This is the mean-value stream, which records daily-averaged values. </p>
<p>The tendencies for gross condensation in convective updrafts are stored in the variable "ddf13" in ..._debugs.nc (units of kg/m2/s). This is another output stream, which records hourly values usually for debugging purposes. The total pressure as a function of height (units of Pa) is stored in the variable "ddf8". Also, the implied surface heat source/sink in the surface energy budget that keeps the surface temperature fixed in time is tracked in the variable "zdf8" (units of W/m2). </p>
<p>The experimental range of surface temperatures is 290-360 K, which remain fixed as a function of time in the simulations through the use of an artificial heat sink. The simulations are from the ECHAM6 climate model, which we ran in single-column mode. </p>
Data and code for Spaulding-Astudillo and Mitchell (2023c), "Clear-sky convergence and the origin of tropical congestus clouds"
No full text<p>Data and code for Spaulding-Astudillo and Mitchell (2023c), "Clear-sky convergence and the origin of tropical congestus clouds".</p><p>The Python code used to create Figures 1, 3-6 and supplementary Figure 1 are included in separate directories. Within each directory, we include experimental data generated by the Reference Forward Model (RFM; Dudhia 2017) that is needed to reproduce the figures. To create the figures, run the provided code in a Jupyter notebook or from the command line. Helper functions for data processing within the figure scripts have the nomenclature ..._data.py. Note that the provided code only allows you to visualize RFM data, not produce it yourself. To do so, you must download and run RFM yourself (https://eodg.atm.ox.ac.uk/RFM/). In addition, Figure 1 requires spatio-temporally averaged data from MERRA-2, ERA5, and CloudSat/CALIPSO (Betrand et al. 2023), which we provide in pickle files. See the main text for data citations, which will allow you to access the original, non-averaged climate data. </p><p>RFM data directories have the nomenclature /ctrl-..... For example, ctrl-RHmid-75-zmid-7-uniform-1 where:<br>RHmid=75% is the relative humidity at a mid-tropospheric height zmid=7.5 km. Uniform=True indicates that the tropospheric relative humidity is constant with height. When uniform=False, the relative humidity follows a C-shaped distribution between the surface and the tropopause. The helper functions in ..._data.py allow you to read the RFM output from .asc files. The nomenclature of the RFM output files is standardized: https://eodg.atm.ox.ac.uk/RFM/. </p><p> </p><p> </p><p> </p><p> </p><p> </p><p> </p><p> </p>
Author-wise bibliometric analysis based on entropy.
No full textAuthor-wise bibliometric analysis based on entropy.</p
Going Beyond Counting First Authors in Author Co-citation Analysis
No full textThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
Supplemental Material, pp-2017-0221-File004 - Why, sometimes, primaries? Intraparty democratization as a default selection mechanism in German and Spanish mainstream parties
No full textSupplemental Material, pp-2017-0221-File004 for Why, sometimes, primaries? Intraparty democratization as a default selection mechanism in German and Spanish mainstream parties by Javier Astudillo, and Klaus Detterbeck in Party Politics</p
Appropriate Similarity Measures for Author Cocitation Analysis
No full textWe provide a number of new insights into the methodological discussion about author cocitation analysis. We first argue that the use of the Pearson correlation for measuring the similarity between authors’ cocitation profiles is not very satisfactory. We then discuss what kind of similarity measures may be used as an alternative to the Pearson correlation. We consider three similarity measures in particular. One is the well-known cosine. The other two similarity measures have not been used before in the bibliometric literature. Finally, we show by means of an example that our findings have a high practical relevance.information science;Pearson correlation;cosine;similarity measure;author cocitation analysis
Dispelling the Myths Behind First-author Citation Counts
No full textWe conducted a full-scale evaluative citation analysis study of scholars in the XML research field to explore just how different from each other author rankings resulting from different citation counting methods actually are, and to demonstrate the capability of emerging data and tools on the Web in supporting more realistic citation counting methods. Our results contest some common arguments for the continued
use of first-author citation counts in the evaluation of scholars, such as high correlations between author rankings by first-author citation counts and other citation
counting methods, and high costs of using more realistic citation counting methods that are not well-supported by the ISI databases. It is argued that increasingly available digital full text research papers make it possible for citation analysis studies to go beyond what the ISI databases have directly supported and to employ more
sophisticated methods
Dr. Edward P. Wimberly, ITC, July 2011
No full textThis video is a conversation with Dr. Edward P. Wimberly. Dr. Wimberly talks about his book, "No Shame in Wesley's Gospel: A Twenty-First Century Pastoral Gospel". Brad Ost, AUC Woodruff Library, is the interviewer
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