1 70 th Symp. Mol. Spectrosc. 2015 MJ14 13 CH 4 in the Octad Measurement and modeling of cold 13 CH 4 spectra from 2.1 to 2.7 µm Linda R. Brown 1, Andrei.

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Presentation transcript:

1 70 th Symp. Mol. Spectrosc MJ14 13 CH 4 in the Octad Measurement and modeling of cold 13 CH 4 spectra from 2.1 to 2.7 µm Linda R. Brown 1, Andrei V. Nikitin 2,3, Keeyoon Sung 1, Michael Rey 4, Sergey A. Tashkun 2,3, Vladimir G. Tyuterev 4, Timothy J. Crawford 1, Mary Ann H. Smith 5, Arlan W. Mantz 6 1 Jet Propulsion Laboratory, California Institute of Technology, Drive, Pasadena, CA 91109, USA 2 Laboratory of Theoretical Spectroscopy, V.E. Zuev Institute of Atmospheric Optics, Tomsk, Russia 3 Tomsk State University, Tomsk, Russian Federation 4 Groupe de Spectrométrie Moléculaire et Atmosphérique, UMR CNRS 7331, Université de Reims, Reims Cedex 2, France 5 Science Directorate, NASA Langley Research Center, Hampton, VA, USA 6 Department of Physics, Astronomy and Geophysics, Connecticut College, New London, CT, USA

2 70 th Symp. Mol. Spectrosc MJ14 Methane Polyads Polyads, P n and name Range (cm -1 ) # vib levels # sub- levels P0P0 GS < P1P1 Dyad 1200 – P2P2 Pentad 2400 – P3P3 Octad 3700 – P4P4 Tetradecad 5000 – P5P5 Icosad 6500 –  Vibrational States  Octad vibrational states for 13 CH 4  Some characteristics Eight different vibrational bands Most have multiple components of vib. sym.species. (i.e., A, E, F) Only F 2 is inherently IR active. All others borrow intensities through interactions. A tends to borrow less while F 1 and E borrows more.

3 70 th Symp. Mol. Spectrosc MJ14 Overview of 13 CH 4 Polyads Pentad cm -1 Octad cm -1 Tetradecad cm -1 Icosad cm -1 H2OH2O L = 10 cm; P = 207 Torr; T = 299 K; resln. = cm -1 H2OH2O

4 70 th Symp. Mol. Spectrosc MJ14 4 Line intensities (log scale) vs cm -1 ~ lines ~ lines CH 4 HITRAN 2012 updates (Brown et al. 2013) Octad Only CH 4 Octad lines were added because many predicted line intensities were wrong!

5 70 th Symp. Mol. Spectrosc MJ14 ConfigurationsKitt Peak McMathJPL Bruker-125HR Light Source Beam Splitter Detector Band pass (cm -1 ) Resolution (cm -1 ) Scanning time (hours) Signal to Noise Quartz-halogen CaF 2 InSb 1850 – :1 Tungsten lamp CaF 2 InSb 3750 – , , ~ :1 ◄ McMath-Pierce FT-IR, Kitt Peak Obs., AZ Bruker 125HR ► JPL, Pasadena Data acquisition with two FT-IR spectrometers ( Kitt-Peak and JPL)

6 70 th Symp. Mol. Spectrosc MJ14 State-of-art cryogenic cells for JPL-FTS Temps = 80 – 296 K ΔT = 0.01 K/day Temp. sensor ZnSe windows Shroud box Cold finger Heaters ◄ m path long Herriott cell; Also designed/ Developed by Arlan Mantz

7 70 th Symp. Mol. Spectrosc MJ14 13 CH 4 : Measurement of line intensities Spectro- meter Temp (K) Pres (Torr) Path (m) Res. (cm -1 ) Calibration factor Kitt Peak McMath FTS JPL Bruker 125HR IFS JPL Kitt Peak JPL  Data acquisition: Experiment conditions  Intensity measurements  Derivation of Empirical lower state energies  Quantum assignments  Analysis and modeling  Line predictions – positions and intensities

8 70 th Symp. Mol. Spectrosc MJ14 Non-linear least squares retrievals Voigt profile assumed (no line mixing used) Nominal sinc function with FOV corrected used Fitting residuals < 1 % Fit spectrum by spectrum Line position, intensity, self- pressure broadening, simultaneously retrieved Separate quality controlled Averaged and compiled  Residuals = Observed - Calculated  Spectrum fitting ~ 15,000 line intensities retrieved ( cm -1 ) 4362 cm

9 70 th Symp. Mol. Spectrosc MJ14 Determination of empirical E″  Population shift with T (from Lyulin et al, 2010)

10 70 th Symp. Mol. Spectrosc MJ14 Nikitin’s graphic tool to assign 13 CH 4 Observed at 80 K Observed at 140 K m: 80 K m: 140 K Predicted 12 CH 4 Assigned

11 70 th Symp. Mol. Spectrosc MJ14 Vibrational sublevels and ranking number Effective band center (cm -1 ) Number of fitted line positions RMS (10 -3 cm -1 ) Number of fitted line intensities RMS (%) 3ν 2 (A 1 ) ν 2 (A 2 ) ν 2 (E) ν 2 +ν 3 (F 2 ) ν 2 +ν 3 (F 1 ) ν 1 +ν 2 (E) ν 2 +ν 4 (F 2 ) ν 2 +ν 4 (F 1 ) ν 2 +ν 4 (F 2 ) ν 3 +ν 4 (A 1 ) ν 3 +ν 4 (F 1 ) ν 3 +ν 4 (E) ν 3 +ν 4 (F 2 ) ν 1 +ν 4 (F 2 ) ν 2 +2ν 4 (A 2 ) ν 2 +2ν 4 (E) ν 2 +2ν 4 (F 2 ) ν 2 +2ν 4 (A 1 ) ν 2 +2ν 4 (F 1 ) ν 2 +2ν 4 (E) ν 4 (F2) ν 4 (F 1 ) ν 4 (A 1 ) ν 4 (F 2 ) All

12 70 th Symp. Mol. Spectrosc MJ14 13 CH 4 Band Intensities Band This work ab initio variational calculation Intensity Ratio TW/calc 3ν e e ν 2 +ν e e ν 1 +ν e e ν 2 +ν e e ν 3 +ν e ν 1 +ν e e ν 2 +2ν e e ν e e All 9.25e e  This work  Two strong bands (ν 3 +ν 4 and ν 1 +ν 4 ) account for 80% of the opacity in this region.  The next four strongest bands (ν 2 +ν 3, 2ν 2 +ν 4, ν 2 +2ν 4 and 3ν 4 ) contribute most of the remaining intensity.  3v 2 borrows very little intensity.  Band intensities (cm -1 /(molecule.cm -2 ))  Further analysis is needed, esp., for ν 2 +ν 3, ν 1 +ν 2, 2ν 2 +ν 4

13 70 th Symp. Mol. Spectrosc MJ database improvement Predicted 13 CH 4 from this work CH 4 intensities fitted in the model HITRAN2012

14 70 th Symp. Mol. Spectrosc MJ14  Summary  13 CH 4 line intensities have been measured in the Octad region.  Empirical lower states energies and assignments have been determined.  The Hamiltonian modeling of the Octad is in progress (Nikitin et al.).  Significance  Supports atmospheric remote sensing of 13 CH 4.  Advances the corresponding analysis of the main isotopologue, 12 CH 4.  Future work is needed; This work - one important step toward the ultimate goal. Acknowledgements This study was supported by The Tomsk State University Academic D.I. Mendeleev Fund Program grant. The support of the Laboratoire International Associé SAMIA between CNRS (France) and RFBR (Russia), from IDRIS / CINES computer centres of France and of the computer centre Reims-Champagne-Ardenne is acknowledged. A.N. thanks computer centres of SKIF Siberia (Tomsk). Part of the research described in this paper was performed at the Jet Propulsion Laboratory, California Institute of Technology, Connecticut College and the NASA Langley Research Center under contracts with the National Aeronautics and Space Administration, including NASA’s Atmospheric Composition Laboratory (ACLAB) program.) database improvement Conclusion and Further work JPL