Delineating the migrating solar and lunar semidiurnal atmospheric tides in general circulation models

Transcription

1 Delineating the migrating solar and lunar semidiurnal atmospheric tides in general circulation models Eryn Cangi, University of Oregon Dr. Astrid Maute, High Altitude Observatory LASP REU 27 July 2016 Image credit: NASA

2 Why this research? Why now? Higher accuracy of tides Better model Better space weather prediction Useful for satellites, the ISS and those of us on the ground too GIF shows content of by James Yoder Existing methods of quantifying lunar tide parameters not well articulated. 2/20 Cangi

3 Some acronyms and definitions... SSW: Sudden Stratospheric Warming SW2: Solar semidiurnal migrating tide Semidiurnal: Two maxima per day (also 2 maxima per longitude) Migrating: Moves west ( W ) at apparent speed of sun M2: Lunar semidiurnal migrating tide This is what we are trying to quantify! Synthetically generated examples. Amplitudes are not necessarily representative of real values. 3/20 Cangi

4 SSW: the basics...planetary wave forcing creates disturbances which couple to the ionosphere...causing plasma density fluctuations of %¹...Fluctuations affect space weather ¹ Goncharenko et al 2010 Image credit: NASA 4/20 Cangi

5 Atmospheric tides: the basics Nonlinear Many variables We focus on: Animation User: Jensob / Wikimedia Commons / CC-BY-SA-3.0 SW2: T = 12h M2: T = h Similar periods make it hard to separate SW2, M2 Quantities: wind speed, temperature, density... Lunar effects are usually much smaller than solar in lower thermosphere, except in periods of SSW. 5/20 Cangi

6 SW2 and M2 overlaid for one lunar cycle Notice two periods of synchronization, ~14.5 days apart (half of the lunar cycle). Similar periods make it hard to separate SW2 and M2! 6/20 Cangi

7 Two more definitions... SLT: Solar Local Time (t) From subsolar point to point P LLT: Lunar Local Time (τ) difference of solar local time (t) and moon phase (ν). Also good to know: Synodic lunar month: time it takes for Moon to orbit Earth relative to line between Earth and Sun days. Figure: Atmospheric Tides, Chapman & Lindzen (1969) 7/20 Cangi

8 Our method for M2 quantification: BSBF Because scientists love a good acronym... Bin-subtract-bin-fit Bin data by solar local time & find averages for each solar local time Subtract averages from total values Bin residuals by lunar local time and take another average Resulting data points: Lunar local time, longitude, tidal value Fit sinusoid to find amplitude and phase 8/20 Cangi

9 The method: surprise, lots and lots of code 9/20 Cangi

10 Testing the method with synthetic data Zero background, constant amplitude (75 m/s) and constant phase (0) Amplitude error: 0.33% Phase: Amplitude error: 1.42% Phase: /20 Cangi

11 Testing the method with synthetic data NON-ZERO background (5 m/s), constant amplitude (75 m/s) and constant phase (0) Amplitude error: 0.33% Phase: Amplitude error: 1.43% Phase: /20 Cangi

12 Testing the method with synthetic data Zero background, constant amplitude (75 m/s), constant phase (0), planetary wave included Amplitude error: 0.33% Phase: Amplitude error: 1.43% Phase: /20 Cangi

13 Results using TIME-GCM* To compare with results of previous methods, we calculated best fit amplitude and phase for each day from mid-december 2012 to end of February (Like in the previous plots, we used a 14.5 day window, half of a lunar cycle, sliding by one day) This was done for each latitude to form a date vs. latitude plot. * thermosphere-ionosphere-mesosphere-electrodynamic general circulation model 13/20 Cangi

14 M2 with BSBF compared to Maute at al (2016) BSBF method Maute et al (2016) ~57 ~80 ~27 ~57 ~47 ~85 ~27 ~50 14/20 Cangi

15 Phase: it s complicated... Shown in lunar local time If shown in solar local time, we see drift: Maute et al (2016) 15/20 Cangi

16 SW2 is a little suspicious Maute et al (2016) BSBF method 16/20 Cangi

17 Final thoughts Good agreement on general feature extraction in M2 Southern Hemisphere differences - why? M2 amplitudes were shown to be slightly larger than previous results (+5 m/s) SW2 amplitudes much lower than previous results in Southern Hemisphere Restriction to southern hemisphere: could be real, but more likely some background fluctuation is not accounted for. We expect to see a peak around the mid latitudes during Southern Hemisphere summer Phase is difficult to convert and difficult to compare Trade-off in accuracy of amplitude, phase fit; watch out for greedy algorithms! BSBF is cleaner than previous methods, produces similar results 17/20 Cangi

18 Future Work Look closely at Southern hemisphere SW2 results: Why is it lower than expected? Check diurnal & solar mean wind for background effects Look at full lunar cycle in addition to half lunar cycle Improve phase recovery and phase comparison plots Examine other data (tides measured in temperature, density) Verify accuracy for situations when tidal amplitudes themselves vary (tide is a product of cosines) Test with more dates, other SSW periods, solar minimum periods 18/20 Cangi

19 References & Acknowledgments Chapman, Sydney, and Richard S. Lindzen. Atmospheric Tides: Thermal and Gravitational. New York: Gordon and Breach, Print. Goncharenko, L. P., A. J. Coster, J. L. Chau, and C. E. Valladares (2010), Impact of sudden stratospheric warmings on equatorial ionization anomaly, J. Geophys. Res., 115, A00G07, doi: /2010ja Forbes, Jeffrey M. et al. "Lunar Semidiurnal Tide In The Thermosphere Under Solar Minimum Conditions". J. Geophys. Res. Space Physics (2013): Web. 26 July Maute, A. et al. "Equatorial Vertical Drift Modulation By The Lunar And Solar Semidiurnal Tides During The 2013 Sudden Stratospheric Warming". J. Geophys. Res. Space Physics (2016): Web. 23 July This work was supported by the NSF REU grant to the University of Colorado. The authors would also like to thank the staff of HAO and LASP for their collaboration in providing an outstanding REU experience.

20 Thank you for your attention! Questions? 19/20 Cangi

21 ~Fin~ 20/20 Cangi

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23 Equation for tide generation (synthetic data) For fitting, use only the L term and add a +C at the end for any possible offset present in real data (e.g., for temperatures).