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The IUPAC Critical Evaluation of the Ro-vibrational Spectra of Water Vapor: Results for H 2 18 O, H 2 17 O, and HD 16 O Jonathan Tennyson University College.

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Presentation on theme: "The IUPAC Critical Evaluation of the Ro-vibrational Spectra of Water Vapor: Results for H 2 18 O, H 2 17 O, and HD 16 O Jonathan Tennyson University College."— Presentation transcript:

1 The IUPAC Critical Evaluation of the Ro-vibrational Spectra of Water Vapor: Results for H 2 18 O, H 2 17 O, and HD 16 O Jonathan Tennyson University College London Attila G. Császár, Tibor Furtenbacher Loránd Eötvös University Alexander Z. Fazliev Institute of Atmospheric Optics Laurence S. Rothman, Iouli E. Gordon Harvard-Smithsonian Center for Astrophysics Ohio State University, June 2008

2 Outline ► IUPAC (International Union of Pure and Applied Chemistry) Water Vapor Task Group - Goals ► Results ► Database and Access Issues

3 A Database of Water Transitions from Experiment and Theory Members: Jonathan Tennyson (chair), P.F. Bernath, A. Campargue, M.R. Carleer, A.G. Császár, R.R. Gamache, J. Hodges, A. Jenouvrier, O. Naumenko, O. Polyansky, L.S. Rothman, R.A. Toth, A.C. Vandaele, N. Zobov Objective: Develop a compilation of experimental and theoretical line positions, energy levels, intensities, and line-shape parameters for water vapor and all of its major isotopologues Establish a database structure that retains and enables access to all critically evaluated data

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5 Spectroscopic Networks of Water Water (except for HDO) has two main SNs: (K a + K c + 3 ) is even(K a + K c + 3 ) is odd (para)(ortho)

6 1. Collect, validate, and compile all available measured transitions, including their systematic and unique assignments and uncertainties, into a single database. 2. Based on the given database of assigned transitions, determine those energy levels of the given species which belong to a particular spectroscopic network (SN). 3. Cleansing of the database (misassignments, mislabelings). 4. Within a given SN, set up a vector containing all the experimentally measured transitions selected, another one comprising the requested measured energy levels, and a design matrix which describes the relation between the transitions and the energy levels. 5. Solve the resulting set of linear equations corresponding to the chosen set of vectors and the inversion matrix many times (robust reweighting). During solution of the set of linear equations uncertainties in the measured transitions can be incorporated which result in uncertainties of the energy levels determined. MARVEL Steps

7 1 2 3 MARVELNo. of rotational levels 0000.000000194 0101591.325708(48)153 0203144.980414(31)63 1003653.142263 (21)106 0013748.318070(11)143 030[4657.123]22 1105227.705603 (46)6868 0115320.260507(3)148 040[6121.552]21 1206764.725603(547)63 0216857.272709(32)89 2007193.246623(20)83 1017238.713600(185)102 0027431.076115(1449)28 0501 1303 03110 21034 1118792.544310(925)108 0601 0128982.869215(966)55 04113 22012 12110311.202510(926)75 0221 30065 20110598.475610(926)102 10853.505315(966)53 00346 13111792.827010(6018)31 31028 21112132.992610(926)87 11225 01312541.225510(926)39 1411 0421 3203 22113631.499810(1019)53 40029 07113808.273310(926)2 30113812.158110(926)75 20214 10314296.279510(370)37 34013 2416 H 2 17 O vibrational energy levels

8 IUPAC vs HITRAN Ro-vibrational levels for H 2 17 O

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10 Bending Fundamental: 1250 – 1750 cm -1

11 Observed Transitions of H 2 17 O Interval (cm -1 )References 1.0 - 170 J. Steenbeckeliers, CRAS Paris B273 (1971) 471 2.0 - 170F.C. De Lucia, J. Mol. Spectrosc. 56 (1975) 138 - 145 3.0 - 177 F. Matsushima, H. Nagase, T. Nakauchi, H. Odashima, and K. Takagi, J. Mol. Spectrosc. 193 (1999) 217 – 223 4.177 - 600J. Kauppinen and E. Kyro, J. Mol. Spectrosc. 84 (1980) 405 - 423 5.1315 - 1986G. Guelachvili, J. Opt. Soc. Am. 73 (1983) 137 - 150 6.500 - 7782SISAM database: http://mark4sun.jpl.nasa.gov/http://mark4sun.jpl.nasa.gov/ 7.8564 - 9332 A.-W. Liu, S.-M. Hu, C. Camy-Peyret, J.-Y. Mandin, O. Naumenko, and B. Voronin, J. Mol. Spectrosc. 237 (2006) 53 – 62 8.4206 - 6600 A. Jenouvrier, L. Daumont, L. Regalia-Jarlot, V. G. Tyuterev, M. Carleer, A. C. Vandaele, S. Mikhailenko, and S. Fally, J. Quant. Spectrosc. Rad. Transfer 105 (2007) 326 – 355 9.6170 - 6747 P. Macko, D. Romanini, S. N. Mikhailenko, O. V. Naumenko, S. Kassi, A. Jenouvrier, Vl. G. Tyuterev, and A. Campargue, J. Mol. Spectrosc. 227 (2004) 90 – 108 10.9711 - 10883 C. Camy-Peyret, J.-M. Flaud, J.-Y. Mandin, A. Bykov, O. Naumenko, L. Sinitsa,and B. Voronin, J. Quant. Spectrosc. Rad. Transfer 61 (1999) 795 – 812 1111365 - 14377 M. Tanaka, O. Naumenko, J. W. Brault, and J. Tennyson, J. Mol. Spectrosc. 234 (2005) 1 - 9 12.16570 - 17125 O. Naumenko, M. Sneep, M. Tanaka, S.V. Shirin, W. Ubachs, and J. Tennyson, J. Mol. Spectrosc. 237 (2006) 63-69 Observed Transitions of H 2 17 O

12 Basic requirement ► System has mainly valid data. Data are valid if they are experimentally verified. A user can easily check which data are experimental, which are calculated and which are of indefinite status. Requirements for sorts of data ► System has to have primary (data and knowledge)‏ ► System has to have expert (data and knowledge) based on formal and informal constraints. These constraints have to be explicitly formulated. Requirements for embedded applications ► Applications have to provide collective work with data and knowledge manipulation (upload primary data and download primary and expert data and metadata, check information on formal constrains (selection rules, process types, …), decompose expert data on primary data sources, compare data, construct composite information sources)‏ Technical requirements ► Short time of information actualization ► Access (in any time and from practically any place)‏ ► Additional services for information processing Requirements for Information System on Spectroscopy (W@DIS)‏ Alexander Fazliev

13 primary information source We use term primary information source to define the data and metadata which are the result of solution (measurement) of one of the above mentioned spectroscopy problems, related to one molecule and published as a definite resource (in a journal or via the web). composite information sources The composite information sources (for instance, HITRAN) are the sets of the primary information sources. But it’s rather difficult to check this composition consistence. One of the goals of W@DIS is to make the process of decomposition of the composite information sources on primary information sources automatic. Information Source

14 14 W@DIS Information System State of the Art Done Upload and download of line profile parameters Generation of semantic metadata Data sources search, tabular and graphical data comparison, root mean square deviation Line profilesDatabase Knowledgebase Interfaces Done Upload and download of transitions Generation of semantic metadata Data sources search, tabular and graphical data comparison, root mean square deviation TransitionsDatabase Knowledgebase Interfaces Done Upload and download of energy levels Generation of semantic metadata Data sources search, tabular and graphical data comparison, root mean square deviation Energy levels Database Knowledgebase Interfaces Data manipulation (upload, storage, presentation, download) ‏ Primary data sources References Database Interfaces ProblemsEntitiesPart of IS

15 Line Profile Line Profile Root mean square deviations

16 ► A full set of original experimental and calculation data on water molecules has been gathered in W@DIS. Number of primary data sources ~ 580 ► A knowledgebase of water molecule information sources has been created. One contains more than 40000 facts. ► Informational model of molecular spectroscopy has been developed on the example of C 2v and C s symmetry molecules. In W@DIS one can work with the following molecules: H 2 O, O 3, SO 2, H 2 S ► W@DIS has facilities for pairwise comparison of data sets and calculations of root - mean-square deviations, sets upload and download,… ► IS W@DIS – http://wadis.saga.iao.ru Summary of Database Delivery System


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