10 results
Assessment of the relative accuracy of hemispheric-scale snow-cover maps
- Dorothy K. Hall, Richard E. J. Kelly, George A. Riggs, Alfred T. C. Chang, James L. Foster
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- Journal:
- Annals of Glaciology / Volume 34 / 2002
- Published online by Cambridge University Press:
- 14 September 2017, pp. 24-30
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There are several hemispheric-scale satellite-derived snow-cover maps available, but none has been fully validated. For the period 23 October–25 December 2000, we compare snow maps of North America derived from the Moderate Resolution Imaging Spectroradiometer (MODIS) and operational snow maps from the U.S. National Oceanic and Atmospheric Administration (NOAA) National Operational Hydrologic Remote Sensing Center (NOHRSC), both of which rely on satellite data from the visible and near-infrared parts of the spectrum; we also compare MODIS maps with Defense Meteorological Satellite Program (DMSP) Special Sensor Microwave/Imager (SSM/I) passive-microwave snow maps for the same period. The maps derived from visible and near-infrared data are more accurate for mapping snow cover than are the passive-microwave-derived maps, but discrepancies exist as to the location and extent of the snow cover even between operational snow maps. The MODIS snow-cover maps show more snow in each of the 8 day periods than do the NOHRSC maps, in part because MODIS maps the effects of fleeting snowstorms due to its frequent coverage. The large (~30 km) footprint of the SSM/I pixel, and the difficulty in distinguishing wet and shallow snow from wet or snow-free ground, reveal differences up to 5.33 x 106 km2 in the amount of snow mapped using MODIS vs SSM/I data. Algorithms that utilize both visible and passive-microwave data, which would take advantage of the all-weather mapping capability of the passive-microwave data, will be refined following the launch of the Advanced Microwave Scanning Radiometer (AMSR) in the fall of 2001.
Intercomparison of satellite-derived snow-cover maps
- Dorothy K. Hall, Andrew B. Tait, James L. Foster, Alfred T. C. Chang, Milan Allen
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- Journal:
- Annals of Glaciology / Volume 31 / 2000
- Published online by Cambridge University Press:
- 14 September 2017, pp. 369-376
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In anticipation of the launch of the Earth Observing System (EOS) Terra, and the Aqua spacecraft in 1999 and 2000, respectively, efforts are ongoing to determine errors of satellite-derived snow-cover maps. EOS Moderate Resolution Imaging Spectrora-diometer (MODIS) and Advanced Microwave Scanning Radiometer-E (AMSR-E) snow-cover products will be produced. For this study we compare snow maps covering the same study areas in Canada and the United States, acquired from different sensors using different snow-mapping algorithms. Four locations are studied: (1) Saskatchewan, Canada; (2) New England (New Hampshire, Vermont and Massachusetts) and eastern New York; (3) central Idaho and western Montana; and (4) North and South Dakota. Snow maps were produced using a prototype MODIS snow-mapping algorithm from Landsat Thematic Mapper (TM) scenes of each study area at 30 m and when the TM data were degraded to 1 km resolution. U.S. National Operational Hydrologic Remote Sensing Center (NOHRSC) 1km resolution snow maps were also used, as were snow maps derived from 0.5° × 0.5° resolution Special Sensor Microwave Imager (SSM/I) data. A land-cover map derived from the International Geosphere-Biosphere Program land-cover map of North America was also registered to the scenes. The TM, NOHRSC and SSM/ I snow maps, and land-cover maps were compared digitally. In most cases, TM-derived maps show less snow cover than the NOHRSC and SSM/I maps because areas of incomplete snow cover in forests (e.g. tree canopies, branches and trunks) are seen in the TM data but not in the coarser-resolution maps which may map the areas as completely snow-covered. The snow maps generally agree with respect to the spatial variability of the snow cover. The 30 m resolutionTM data provide the most accurate snow maps, and are thus used as the baseline for comparison with the other maps. Results show that the changes in amount of snow cover, as compared to to the 30 m resolution TM maps, are lowest using the TM 1km resolution maps, at 0–40%. The greatest change (>100%) is found in the New England study area, probably due to the presence of patchy snow cover. A scene with patchy snow cover is more difficult to map accurately than is a scene with a well-defined snowline such as is found on the North and South Dakota scene where the changes were 0–40%. There are also some important differences in the amount of snow mapped using the two different SSM/I algorithms because they utilize different channels.
Determination of snow-covered area in different land covers in central Alaska, U.S.A., from aircraft data — April 1995
- Dorothy K. Hall, James L. Foster, Alfred T. C. Chang, Carl S. Benson, Janet Y. L. Chien
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- Journal:
- Annals of Glaciology / Volume 26 / 1998
- Published online by Cambridge University Press:
- 20 January 2017, pp. 149-155
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During April 1995, a field and aircraft experiment was conducted in central Alaska in support of the Moderate Resolution Imaging Spectroradiometer (MODIS) snow-mapping project. The MODIS Airborne Simulator (MAS), a 50 channel spectroradiometer, was flown on board the NASA ER-2 aircraft. An objective of the mission was to determine the accuracy of mapping snow in different surface covers using an algorithm designed to map global snow cover after the launch of MODIS in 1998. The surface cover in this area of central Alaska is typically spruce, birch, aspen, mixed forest and muskeg. Integrated reflectance, Ri was calculated from the visible/near-infrared channels of the MAS sensor. The Ri was used to estimate different vegetation-cover densities because there is an inverse relationship between vegetation-cover density and albedo in snow-covered terrain. A vegetation-cover density map was constructed using MAS data acquired on 13 April 1995 over central Alaska. In the part of the scene that was mapped as having a vegetation-cover density of < 50%, the snow-mapping algorithm mapped 96.41% snow cover. These areas are generally composed of muskeg and mixed forests and include frozen lake. In the part of the scene that was estimated to have a vegetation-cover density of ≥50%, the snow-mapping algorithm mapped 71.23% snow cover. These areas are generally composed of dense coniferous or deciduous forests. Overall, the accuracy of the snow-mapping algorithm is > 87.41% for a 13 April MAS scene with a variety of surface covers (coniferous and deciduous and mixed forests, muskeg, tundra and frozen lake).
Snow depths and grain-size relationships with relevance for passive microwave studies
- Richard L. Armstrong, Alfred Chang, Albert Rango, Edward Josberger
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- Journal:
- Annals of Glaciology / Volume 17 / 1993
- Published online by Cambridge University Press:
- 20 January 2017, pp. 171-176
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The application of passive microwave radiometry to the remote sensing of snow properties is based on the ratio of emitted to scattered portions of the upwelling radiation. Increased scattering is indicative of increased snow amount, i.e. the number of snow grains present. However, scattering is also directly proportional to snow grain-size for a given snow amount. Current snow cover retrieval algorithms produce inaccurate results when snow grain-sizes are unusually large. Therefore, it is necessary to characterize snow grain-size on a regional scale (and perhaps local scale in extreme situations) in order to adjust passive microwave algorithms. Preliminary analysis indicates that: (1) algorithms are not as sensitive to the presence of large grain-sizes as the initial theory had indicated; (2) standard deviation of grain-size diameters throughout the total snow cover may often be less than 0.5 mm, thus average grain-size data may often serve to characterize the detailed stratigraphy of the total snow cover; (3) conditions in subfreezing snow which produce grain-sizes that greatly exceed a mean diameter value of 1–2 mm result from snow cover/climate relationships which can be modelled/monitored on a regional scale. A preliminary method is investigated for selecting snow retrieval algorithms according to prevailing regional-scale grain-size.
Snow conditions and hydrology of the upper Colorado River basin from satellite passive microwave observations
- Edward G. Josberger, William J. Campbell, Per Gloersen, Alfred T.C. Chang, Al Rango
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- Journal:
- Annals of Glaciology / Volume 17 / 1993
- Published online by Cambridge University Press:
- 20 January 2017, pp. 322-326
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Satellite passive microwave observations can provide unique mesoscale (25 km) information on snowpack properties; however, the mountainous terrain of the upper Colorado River basin compounds the difficulty of the problem. Nevertheless, observations of this region from the Scanning Multichannel Microwave Radiometer (SMMR) have provided unique, synoptic, mesoscale snowpack information from 1979 to 1987 on the snowpack extent. For this nine-year period, the SMMR 18 and 37 GHz brightness temperature observations, combined to form a parameter called NGR, show the average maximum snowpack extent covers 70% of the basin and occurs on water year day 130 (mid-February). The minimum snowpack extent took place in 1981 and covered 35% of the basin. The maximum snowpack extent took place in 1979 and covered 99% of the basin. Summation of the NGR values from each SMMR mesoscale pixel within the basin provides an index of the regional snowpack properties on both an intra- and inter-annual basis and exhibits behavior similar to the snowpack extent. When compared to the nine-year average, 1981 is the minimum year and 1979 is the maximum year. Furthermore, the sum over the basin of the annual maximum NGR from each pixel correlates with the annual discharge, r = 0.6. This correlation increases to 0.8 when digital elevation data are used to characterize each SMMR pixel and only the April through July discharge is used in the regression. Hence, this study combines the small scale elevation data with the mesoscale SMMR observations to investigate the basin-wide or regional snowpack characteristics and its hydrology.
Contributors
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- By Mitchell Aboulafia, Frederick Adams, Marilyn McCord Adams, Robert M. Adams, Laird Addis, James W. Allard, David Allison, William P. Alston, Karl Ameriks, C. Anthony Anderson, David Leech Anderson, Lanier Anderson, Roger Ariew, David Armstrong, Denis G. Arnold, E. J. Ashworth, Margaret Atherton, Robin Attfield, Bruce Aune, Edward Wilson Averill, Jody Azzouni, Kent Bach, Andrew Bailey, Lynne Rudder Baker, Thomas R. Baldwin, Jon Barwise, George Bealer, William Bechtel, Lawrence C. Becker, Mark A. Bedau, Ernst Behler, José A. Benardete, Ermanno Bencivenga, Jan Berg, Michael Bergmann, Robert L. Bernasconi, Sven Bernecker, Bernard Berofsky, Rod Bertolet, Charles J. Beyer, Christian Beyer, Joseph Bien, Joseph Bien, Peg Birmingham, Ivan Boh, James Bohman, Daniel Bonevac, Laurence BonJour, William J. Bouwsma, Raymond D. Bradley, Myles Brand, Richard B. Brandt, Michael E. Bratman, Stephen E. Braude, Daniel Breazeale, Angela Breitenbach, Jason Bridges, David O. Brink, Gordon G. Brittan, Justin Broackes, Dan W. Brock, Aaron Bronfman, Jeffrey E. Brower, Bartosz Brozek, Anthony Brueckner, Jeffrey Bub, Lara Buchak, Otavio Bueno, Ann E. Bumpus, Robert W. Burch, John Burgess, Arthur W. Burks, Panayot Butchvarov, Robert E. Butts, Marina Bykova, Patrick Byrne, David Carr, Noël Carroll, Edward S. Casey, Victor Caston, Victor Caston, Albert Casullo, Robert L. Causey, Alan K. L. Chan, Ruth Chang, Deen K. Chatterjee, Andrew Chignell, Roderick M. Chisholm, Kelly J. Clark, E. J. Coffman, Robin Collins, Brian P. Copenhaver, John Corcoran, John Cottingham, Roger Crisp, Frederick J. Crosson, Antonio S. Cua, Phillip D. Cummins, Martin Curd, Adam Cureton, Andrew Cutrofello, Stephen Darwall, Paul Sheldon Davies, Wayne A. Davis, Timothy Joseph Day, Claudio de Almeida, Mario De Caro, Mario De Caro, John Deigh, C. F. Delaney, Daniel C. Dennett, Michael R. DePaul, Michael Detlefsen, Daniel Trent Devereux, Philip E. Devine, John M. Dillon, Martin C. Dillon, Robert DiSalle, Mary Domski, Alan Donagan, Paul Draper, Fred Dretske, Mircea Dumitru, Wilhelm Dupré, Gerald Dworkin, John Earman, Ellery Eells, Catherine Z. Elgin, Berent Enç, Ronald P. Endicott, Edward Erwin, John Etchemendy, C. Stephen Evans, Susan L. Feagin, Solomon Feferman, Richard Feldman, Arthur Fine, Maurice A. Finocchiaro, William FitzPatrick, Richard E. Flathman, Gvozden Flego, Richard Foley, Graeme Forbes, Rainer Forst, Malcolm R. Forster, Daniel Fouke, Patrick Francken, Samuel Freeman, Elizabeth Fricker, Miranda Fricker, Michael Friedman, Michael Fuerstein, Richard A. Fumerton, Alan Gabbey, Pieranna Garavaso, Daniel Garber, Jorge L. A. Garcia, Robert K. Garcia, Don Garrett, Philip Gasper, Gerald Gaus, Berys Gaut, Bernard Gert, Roger F. Gibson, Cody Gilmore, Carl Ginet, Alan H. Goldman, Alvin I. Goldman, Alfonso Gömez-Lobo, Lenn E. Goodman, Robert M. Gordon, Stefan Gosepath, Jorge J. E. Gracia, Daniel W. Graham, George A. Graham, Peter J. Graham, Richard E. Grandy, I. Grattan-Guinness, John Greco, Philip T. Grier, Nicholas Griffin, Nicholas Griffin, David A. Griffiths, Paul J. Griffiths, Stephen R. Grimm, Charles L. Griswold, Charles B. Guignon, Pete A. Y. Gunter, Dimitri Gutas, Gary Gutting, Paul Guyer, Kwame Gyekye, Oscar A. Haac, Raul Hakli, Raul Hakli, Michael Hallett, Edward C. Halper, Jean Hampton, R. James Hankinson, K. R. Hanley, Russell Hardin, Robert M. Harnish, William Harper, David Harrah, Kevin Hart, Ali Hasan, William Hasker, John Haugeland, Roger Hausheer, William Heald, Peter Heath, Richard Heck, John F. Heil, Vincent F. Hendricks, Stephen Hetherington, Francis Heylighen, Kathleen Marie Higgins, Risto Hilpinen, Harold T. Hodes, Joshua Hoffman, Alan Holland, Robert L. Holmes, Richard Holton, Brad W. Hooker, Terence E. Horgan, Tamara Horowitz, Paul Horwich, Vittorio Hösle, Paul Hoβfeld, Daniel Howard-Snyder, Frances Howard-Snyder, Anne Hudson, Deal W. Hudson, Carl A. Huffman, David L. Hull, Patricia Huntington, Thomas Hurka, Paul Hurley, Rosalind Hursthouse, Guillermo Hurtado, Ronald E. Hustwit, Sarah Hutton, Jonathan Jenkins Ichikawa, Harry A. Ide, David Ingram, Philip J. Ivanhoe, Alfred L. Ivry, Frank Jackson, Dale Jacquette, Joseph Jedwab, Richard Jeffrey, David Alan Johnson, Edward Johnson, Mark D. Jordan, Richard Joyce, Hwa Yol Jung, Robert Hillary Kane, Tomis Kapitan, Jacquelyn Ann K. Kegley, James A. Keller, Ralph Kennedy, Sergei Khoruzhii, Jaegwon Kim, Yersu Kim, Nathan L. King, Patricia Kitcher, Peter D. Klein, E. D. Klemke, Virginia Klenk, George L. Kline, Christian Klotz, Simo Knuuttila, Joseph J. Kockelmans, Konstantin Kolenda, Sebastian Tomasz Kołodziejczyk, Isaac Kramnick, Richard Kraut, Fred Kroon, Manfred Kuehn, Steven T. Kuhn, Henry E. Kyburg, John Lachs, Jennifer Lackey, Stephen E. Lahey, Andrea Lavazza, Thomas H. Leahey, Joo Heung Lee, Keith Lehrer, Dorothy Leland, Noah M. Lemos, Ernest LePore, Sarah-Jane Leslie, Isaac Levi, Andrew Levine, Alan E. Lewis, Daniel E. Little, Shu-hsien Liu, Shu-hsien Liu, Alan K. L. Chan, Brian Loar, Lawrence B. Lombard, John Longeway, Dominic McIver Lopes, Michael J. Loux, E. J. Lowe, Steven Luper, Eugene C. Luschei, William G. Lycan, David Lyons, David Macarthur, Danielle Macbeth, Scott MacDonald, Jacob L. Mackey, Louis H. Mackey, Penelope Mackie, Edward H. Madden, Penelope Maddy, G. B. Madison, Bernd Magnus, Pekka Mäkelä, Rudolf A. Makkreel, David Manley, William E. Mann (W.E.M.), Vladimir Marchenkov, Peter Markie, Jean-Pierre Marquis, Ausonio Marras, Mike W. Martin, A. P. Martinich, William L. McBride, David McCabe, Storrs McCall, Hugh J. McCann, Robert N. McCauley, John J. McDermott, Sarah McGrath, Ralph McInerny, Daniel J. McKaughan, Thomas McKay, Michael McKinsey, Brian P. McLaughlin, Ernan McMullin, Anthonie Meijers, Jack W. Meiland, William Jason Melanson, Alfred R. Mele, Joseph R. Mendola, Christopher Menzel, Michael J. Meyer, Christian B. Miller, David W. Miller, Peter Millican, Robert N. Minor, Phillip Mitsis, James A. Montmarquet, Michael S. Moore, Tim Moore, Benjamin Morison, Donald R. Morrison, Stephen J. Morse, Paul K. Moser, Alexander P. D. Mourelatos, Ian Mueller, James Bernard Murphy, Mark C. Murphy, Steven Nadler, Jan Narveson, Alan Nelson, Jerome Neu, Samuel Newlands, Kai Nielsen, Ilkka Niiniluoto, Carlos G. Noreña, Calvin G. Normore, David Fate Norton, Nikolaj Nottelmann, Donald Nute, David S. Oderberg, Steve Odin, Michael O’Rourke, Willard G. Oxtoby, Heinz Paetzold, George S. Pappas, Anthony J. Parel, Lydia Patton, R. P. Peerenboom, Francis Jeffry Pelletier, Adriaan T. Peperzak, Derk Pereboom, Jaroslav Peregrin, Glen Pettigrove, Philip Pettit, Edmund L. Pincoffs, Andrew Pinsent, Robert B. Pippin, Alvin Plantinga, Louis P. Pojman, Richard H. Popkin, John F. Post, Carl J. Posy, William J. Prior, Richard Purtill, Michael Quante, Philip L. Quinn, Philip L. Quinn, Elizabeth S. Radcliffe, Diana Raffman, Gerard Raulet, Stephen L. Read, Andrews Reath, Andrew Reisner, Nicholas Rescher, Henry S. Richardson, Robert C. Richardson, Thomas Ricketts, Wayne D. Riggs, Mark Roberts, Robert C. Roberts, Luke Robinson, Alexander Rosenberg, Gary Rosenkranz, Bernice Glatzer Rosenthal, Adina L. Roskies, William L. Rowe, T. M. Rudavsky, Michael Ruse, Bruce Russell, Lilly-Marlene Russow, Dan Ryder, R. M. Sainsbury, Joseph Salerno, Nathan Salmon, Wesley C. Salmon, Constantine Sandis, David H. Sanford, Marco Santambrogio, David Sapire, Ruth A. Saunders, Geoffrey Sayre-McCord, Charles Sayward, James P. Scanlan, Richard Schacht, Tamar Schapiro, Frederick F. Schmitt, Jerome B. Schneewind, Calvin O. Schrag, Alan D. Schrift, George F. Schumm, Jean-Loup Seban, David N. Sedley, Kenneth Seeskin, Krister Segerberg, Charlene Haddock Seigfried, Dennis M. Senchuk, James F. Sennett, William Lad Sessions, Stewart Shapiro, Tommie Shelby, Donald W. Sherburne, Christopher Shields, Roger A. Shiner, Sydney Shoemaker, Robert K. Shope, Kwong-loi Shun, Wilfried Sieg, A. John Simmons, Robert L. Simon, Marcus G. Singer, Georgette Sinkler, Walter Sinnott-Armstrong, Matti T. Sintonen, Lawrence Sklar, Brian Skyrms, Robert C. Sleigh, Michael Anthony Slote, Hans Sluga, Barry Smith, Michael Smith, Robin Smith, Robert Sokolowski, Robert C. Solomon, Marta Soniewicka, Philip Soper, Ernest Sosa, Nicholas Southwood, Paul Vincent Spade, T. L. S. Sprigge, Eric O. Springsted, George J. Stack, Rebecca Stangl, Jason Stanley, Florian Steinberger, Sören Stenlund, Christopher Stephens, James P. Sterba, Josef Stern, Matthias Steup, M. A. Stewart, Leopold Stubenberg, Edith Dudley Sulla, Frederick Suppe, Jere Paul Surber, David George Sussman, Sigrún Svavarsdóttir, Zeno G. Swijtink, Richard Swinburne, Charles C. Taliaferro, Robert B. Talisse, John Tasioulas, Paul Teller, Larry S. Temkin, Mark Textor, H. S. Thayer, Peter Thielke, Alan Thomas, Amie L. Thomasson, Katherine Thomson-Jones, Joshua C. Thurow, Vzalerie Tiberius, Terrence N. Tice, Paul Tidman, Mark C. Timmons, William Tolhurst, James E. Tomberlin, Rosemarie Tong, Lawrence Torcello, Kelly Trogdon, J. D. Trout, Robert E. Tully, Raimo Tuomela, John Turri, Martin M. Tweedale, Thomas Uebel, Jennifer Uleman, James Van Cleve, Harry van der Linden, Peter van Inwagen, Bryan W. Van Norden, René van Woudenberg, Donald Phillip Verene, Samantha Vice, Thomas Vinci, Donald Wayne Viney, Barbara Von Eckardt, Peter B. M. Vranas, Steven J. Wagner, William J. Wainwright, Paul E. Walker, Robert E. Wall, Craig Walton, Douglas Walton, Eric Watkins, Richard A. Watson, Michael V. Wedin, Rudolph H. Weingartner, Paul Weirich, Paul J. Weithman, Carl Wellman, Howard Wettstein, Samuel C. Wheeler, Stephen A. White, Jennifer Whiting, Edward R. Wierenga, Michael Williams, Fred Wilson, W. Kent Wilson, Kenneth P. Winkler, John F. Wippel, Jan Woleński, Allan B. Wolter, Nicholas P. Wolterstorff, Rega Wood, W. Jay Wood, Paul Woodruff, Alison Wylie, Gideon Yaffe, Takashi Yagisawa, Yutaka Yamamoto, Keith E. Yandell, Xiaomei Yang, Dean Zimmerman, Günter Zoller, Catherine Zuckert, Michael Zuckert, Jack A. Zupko (J.A.Z.)
- Edited by Robert Audi, University of Notre Dame, Indiana
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- The Cambridge Dictionary of Philosophy
- Published online:
- 05 August 2015
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- 27 April 2015, pp ix-xxx
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The Kinematics of Globular Cluster NGC 288
- Chan-Kao Chang, Alfred B. Chen, Wean-Shun Tsay, Wen-Ping Chen, Phillip K. Lu
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- Journal:
- International Astronomical Union Colloquium / Volume 183 / 2001
- Published online by Cambridge University Press:
- 12 April 2016, pp. 333-334
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- 2001
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The mean radial velocity of NGC 288 (accuracy 5.5 km/s) is determined to be −56.3 ± 20.1 km/s which, when combined with the mean proper motion (Guo, 1995), yields a peculiar velocity with respect to the LSR of (u,v,w) = (29.7 ± 18.1, −258.6 ± 18.3,62.3 ± 20.3) km/s. This implies that NGC 288 moves in a retrograde sense with the Galactic rotation. We also derived the effective temperatures for stars in our sample and, as a corroborative effort, compared with those estimated previously from the BATC data (Tsai 1998) by spectral energy distribution fitting. We demonstrate that the BATC/SED fitting is an appropriate and efficient way to estimate the effective temperature of a star.
The NCU Lu-Lin Observatory
- Wean-Shun Tsay, Alfred Bing-Chih Chen, Kuang-Hsiang Chang, Huan-Hsin Li
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- Journal:
- International Astronomical Union Colloquium / Volume 183 / 2001
- Published online by Cambridge University Press:
- 12 April 2016, pp. 299-303
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- 2001
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The NCU (National Central University) Lu-Lin observatory is located at Mt. Front Lu-Lin, 120°52′25”E and 23°28′07” N, a 2862-m peak in the Yu-Shan National Park. The construction of Lu-Lin observatory was finished on January 14, 1999. The initial assessment of Lu-Lin site started in 1989, after which a three-year project was founded by the National Science Council (NSC) to support a modern seeing monitoring program. The average seeing at Lu-Lin is about 1.39 arc-second with an average of 200 clear nights annually. The sky background is 20.72 mag/arcsec2 in V band and 21.22 mag/arcsec2 in B band.
The Lu-Lin observatory is for both research and education. A homemade 76-cm Super Light Telescope (SLT) and four TAOS 50-cm robotic telescopes for a survey on Kuiper Belt Objects will be the two major research facilities. The pilot program for SLT consists of observations of time-varying astrophysical phenomena. The TAOS #1 telescope was installed at Lu-Lin in March 2000. A 90 KW/240 VAC power line and a water pipe system have been pulled to the site in early 2001. A wireless Network system through A-Li Shan has been operating at Lu-Lin observatory while a faster wireless Network system with 11.5 Mbit/sec bandwidth is under consideration and may be available in the near future for remote observing.
6 - Genetically modified tumor cells as tumor vaccines
- Edited by Brian E. Huber, Glaxo Wellcome Research Institute, North Carolina, Ian Magrath, National Cancer Institute, Bethesda, Maryland
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- Gene Therapy in the Treatment of Cancer
- Published online:
- 01 April 2010
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- 24 September 1998, pp 108-136
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Summary
Introduction
Recombinant DNA technology has allowed for the efficient introduction of defined genes into mammalian cells. Utilizing this technology, it has been feasible to express a variety of immunoregulatory proteins in tumor cells in order to modulate the host's immune response to native tumor antigens. The components of the immune response necessary to generate immunity to tumors consist of: (a) emigration of inflammatory cells to the site of tumor growth; (b) processing of tumor antigens by antigen-presenting cells; (c) sensitization of lymphoid cells; and (d) amplification and/or suppression of mature effector cells. Thus, there is a variety of avenues to modulate an immune response by specifically adding defined immune regulatory genes in this process.
Transplantable animal tumors have provided a wealth of information concerning the host antitumor immune response. Depending upon the inherent immunogenicity of the tumor, experimental methods are capable of eliciting systemic immunity to a variety of tumors in naive hosts. Many of the initial studies with genetically modified tumor cells have focused on the ability of the host to reject an inoculum of modified tumor cells, with the induction of systemic immunity to a subsequent challenge of the parental tumor. Hence, the inherent immunogenicity of the tumor being examined is important in interpreting the significance of genetic modification. Tumor immunogenicity has been traditionally defined by transplantation procedures. Table 6.1 presents the framework for discussing immunogenicity that is utilized in this chapter and is based on the ability to immunize animals to resist tumor challenge by various manipulations.
Snow-load excitation of the Earth's annual wobble
- B. Fong Chao, William P. O'Connor, Alfred T. C. Chang
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- Journal:
- Symposium - International Astronomical Union / Volume 128 / 1988
- Published online by Cambridge University Press:
- 03 August 2017, pp. 373-380
- Print publication:
- 1988
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A global, monthly snow depth data set has been generated from weather satellite (Nimbus 7) observations using passive microwave remote-sensing techniques. In this paper we analyzed five years of data, 1980–1984, to compute the snow-load excitation of the annual wobble of the Earth's rotation axis. A uniform sea-level decrease has been assumed in order to conserve water mass. The result shows dominant seasonal cycles. The prograde component of the annual excitation is Ψ+ = (5.0 milliarcsec, −110*) and the retrograde component Ψ− = (5.0 milliarcsec, −31*). These computed values are compared with previous groundwater estimates, as well as the inferred values from ILS and LAGEOS polar motion measurements. The importance of accurate data is stressed and future plans proposed.
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