20,990 research outputs found
Richard Dorson (interview)
No full textThis interview is included in the American Folklore Society Oral History Project held at the Archive of Folk Culture, American Folklife Center, Library of Congress, Washington, D.C. In this item, Richard M. Dorson is interviewed by Richard Reuss at the American Folklore Society annual meeting in Nashville, Tennessee for the American Folklore Society Oral History Project. Biography/History note: Richard M. Dorson, folklorist, author, and educator, was born in New York City in 1916 and died in 1981. He earned his B.A., M.A. and Ph.D. at Harvard University and taught at Harvard and Michigan State University before becoming professor of history and folklore at Indiana University where he founded its Folklore Institute in 1963 and became the first director and first chair of the Folklore Department at Indiana University in 1978. This collection consists of 1 sound tape reel (40 min.) : analog, 7 1/2 ips, 2 track, mono. ; 7 in. It was originally recorded on November 2, 1973 at the American Folklore Society annual meeting in Nashville, Tennessee by Richard Reuss on a Sony audiocassette. This is a first-generation copy
Folder 9: Schwiderski, Richard Craig v. State of Texas 2, 1979-1984
No full textPhotocopy of a section of an article written by New York author Richard Reeves and titled 'Too Late to Kill the Messenger' and dated 1979, and argues for the role of media during violent situations
Going Beyond Counting First Authors in Author Co-citation Analysis
Get PDFThe 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
Dispelling the Myths Behind First-author Citation Counts
Get PDFWe 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
Evaluation of snow cover and depth simulated by a land-surface model using detailed regional snow observations from Austria
Get PDFAn evaluation is undertaken of the accuracy with which the Joint UK Land Environment Simulator (JULES) can simulate snow cover and depth when driven using data from the Hadley Centre Regional Climate Model. The JULES model provides the facility to diagnose the thermal and hydrological state of the land surface and soil given time-varying inputs of air temperature, wind speed, humidity, shortwave and long-wave radiation, and precipitation. The observed dataset used in this study consists of daily snow depths measurements at 601 climate stations with more than 15 years of observations in the period from January 1976 to December 2000. In this study, the JULES model was driven using two datasets at 25 km horizontal resolution: one produced using the UK Met Office Hadley Centre regional climate model (RCM), HadRM3-P (RCM), the other in which RCM precipitation and air temperature data were replaced with observed values (RCM+PT). The results indicate good agreement between the land-surface model simulations and observations of snow cover at climate stations. The median snow cover accuracy indices for all 601 stations were 89% and 91% for the RCM and the combined RCM+PT driving datasets, respectively, with only a small inter-annual variation. In contrast, the differences between modeled and measured snow depth were much larger. The median values of mean snow depth bias were similar, −0.4 cm for the RCM and −1.2 cm for the RCM+PT, however, the RCM simulation was found to overestimate the observed snow depth at more than 25% of climate stations. The extent to which the results from RCM-driven simulations match observed data is strongly related to the accuracy of the RCM precipitation. The large overestimation has significant impact on the snow mass simulation and the assessment of extreme values in the mountains. We note that even if snow cover can be simulated with a high degree of accuracy, this should not imply a similarly high degree of accuracy in the simulation of snow depth. Model performance was poorest in regions of significant topographic heterogeneity and our findings suggest that the most promising additional model developments should be directed towards computationally-efficient representation of sub-grid topography
GiuliaMazzotti/FSM2: FSM2 for hyper-resolution forest snow modelling applications
No full textThis model release (FSM2.0.3) includes developments specifically targeting hyper-resolution (meter-scale) forest snow modelling applications, as presented in the following publication: Mazzotti, G., Essery, R., Webster, C., Malle, J., and Jonas, T. 2020. Process-Level Evaluation of a Hyper-Resolution Forest Snow Model Using Distributed Multisensor Observations. Water Resources Research, 56(9), e2020WR027572, https://doi.org/10.1029/2020WR02757
Books piece on a reading by Richard Price, author of Samaritan, which will b
No full textBooks piece on a reading by Richard Price, author of Samaritan, which will be presented at Rines Auditorium, Portland Public Library, on March 5
I Remember column in which author Richard Randall writes of his family\u27s disco
No full textI Remember column in which author Richard Randall writes of his family\u27s discovery of abundant wild blueberries growing near Rocky Pond in Osborne Plantation
As I See It piece by Richard Ford, a Pulitzer Prize-winning author turned East
No full textAs I See It piece by Richard Ford, a Pulitzer Prize-winning author turned East Boothbay resident, on how he has learned to fit in in his new home and on the broader implications of being a newcomer
Reanalysis of Scottish mountain snow conditions
Get PDFMountain snowline is important as it is an easily identifiable measure of the phase
state of water in the landscape. However, frequent observation of the snowline in
Scotland is difficult as reduced visibility is common, obscuring ground based and
remotely sensed methods. Changes in seasonal snowline elevation can indicate long-term
climate trends. Snow cover influences local flora and fauna, and knowledge of
snowline can inform management of water and associated risks.
Complete Scottish Snow Survey of Great Britain (SSGB) records were transcribed
and form the primary snow cover dataset used for this work. Voluntary observers
collected the SSGB between 1945 and 2007. Other snow cover data used includes
remotely sensed (Moderate-resolution Imaging Spectroradiometer: MODIS) and Met
Office station observations (as point observations and interpolated to form UK
Climate Projections 2009, UKCP09).
I present a link between the North Atlantic Oscillation (NAO) index and days of
snow cover in Scotland between winters from 1875 to 2013. Broad (5 km resolution)
scale datasets (e.g. UKCP09) are used to extract nationwide patterns, supporting these
findings using SSGB hillslope scale data. The strongest correlations between the NAO
index and snow cover are found in eastern and southern Scotland; these results are
supported by both SSGB and UKCP09 data. Correlations between NAO index and
snow cover are negative with the strongest relationships found for elevations below
750 m.
A degree-day snow model was developed using daily precipitation and
temperature data to derive snow cover and melt. This model was run between 1960
and 2011 using point data from five Met Office stations and data on a 5 km grid
(UKCP09 temperature and CEH GEAR precipitation) across Scotland. Due to CEH
GEAR data underestimating precipitation at higher elevations, absolute values of melt
are uncertain. However, relative correlations are apparent, e.g. the proportion of
precipitation as melt and number of days with snow cover each year are generally
decreasing through time, except around Ben Nevis. Notably, this increase correlates
with positive NAO, and it is thought Ben Nevis remains cold enough to accumulate
lying snow in the face of a warming climate. Snowmelt rates were found to annually
exceed the maximum snowmelt rate used for fluvial impoundment structure design,
but this was only at the highest elevations in areas like the Cairngorms
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