Sakura/Europlanet workshop, Paris, March 2012

1. Winds and sulfur/water photochemistry in the Venus middle atmosphere from ground-based μ-wave Observations of 12CO/13CO, SO2, SO, and HDOB. Sandor and T. Clancy (sandor@spacescience.org) • Ground-based submm (James Clerk Maxwell Telescope – JCMT, Hawaii) and earlier mm (NRAO/U.of AZ 12m Telescope –Arizona, USA) spectroscopic line observations allow retrieval of molecular abundances and altitude distributions based upon depth and shape of absorption lines. Absorption line shape is controlled by pressure broadening, such that vertical distributions are retrieved on a pressure-altitude grid. Altitude sensitivity is within the 70-110 km region, and varies among molecules. • Line-of-sight wind speeds are retrieved from measured doppler shifts of 12CO/13CO line centers at positions distributed across the Venus disk. Spatial resolution at 330-346 GHz corresponds to a 14” diffraction-limited beam placed on a Venus diameter of 10”-60”. Sakura/Europlanet workshop, Paris, March 2012

2. 13CO/12CO Doppler Wind Measurements • Since 2000, we have observed Venus sub-mm 13CO/12CO line frequencies (fig) from the JCMT, obtaining spatial maps at each inferior conjunction. • Each colocated 13CO/12CO pair of optically thin/thick lines is used to retrieve CO and temperature profiles. • Each 13CO, 12CO spectrum is compared respective 13CO, 12CO spectra at other spatial locations to measure winds from relative doppler shift. • Optically thin 13CO characterizes lower altitudes than does optically thick 12CO. • Comparison of spectra across many channels yields wind measurements at higher precision, ±10 m/s, than resolution of the spectrometer.

3. 13CO/12CO Doppler Wind Measurements • Diffraction-limited diameter of the JCMT 330/345 GHz beam is 14”. Large variation of the Venus diameter, 10” (dayside) to 60” (nightside) correspondingly limits the number of spatially independent observations on each date to a value which is phase-dependent. • Best-resolution mapping is possible at at inferior conjunction (night, below left), when ~20 independent positions can be observed on the 60” disk. Doppler winds are measured at each of the indicated 16 measurement positions, by comparison with a reference zero-velocity disk center spectrum (not shown). • At elongation (below center), a cruder 4-position wind map of both day and night sides can be obtained. At superior conjunction (dayside, below right), the disk is not resolved, and no wind measurement is possible.

4. Global Circulation in the Lower Thermosphere • Zonal retrograde flow (below left) dominates winds at the cloud tops. • SubSolar to Antisolar (SSAS) flow characterizes the thermosphere, with upward flow at the subsolar point, axisymmetric horizontal circulation at the subsolar point. Flow is driven by solar heating on the dayside, and strong CO2 IR cooling at night. • Early measurements of lower mesospheric (90-110 km) winds identified patterns [ SSAS (Goldstein et al., 1991); Zonal (Shah et al., 1991) ] that were not consistent. Those determinations were from day- and night-side data respectively, a distinction not realized at the time.

5. Nightside Lower Thermospheric Winds • Submm observations show wind patterns have strong temporal variability, with Zonal (left fig) flow on some dates SSAS (right fig) on others. • We fit observed submm wind fields with a 2-parameter model, in which each observed pattern is presumed to be a linear sum of Zonal and SSAS fields. Derived best-fit values quantify relative strengths of Zonal and SSAS components. Validity of the model is assessed by comparison of best-fit vs observed fields.

6. Nightside Lower Thermospheric Wind Patterns • Model fits to all observation dates (below) show prevailing flow is Zonal, with a smaller SSAS contribution. • Temporal variation is strong, and evident on multiple timescales. Note two changes over 24 hours (2009, red) and one of 4-hours (2006, orange). • Submm results are consistent with 230 GHz (E91, E07) analyses of Lellouch et al. (1994, 2008).

7. Nightside Global Circulation in Lower Thermosphere • Model fits to all observation dates show prevailing flow is Zonal, with a smaller SSAS contribution. • The simple Zonal/SSAS model typically accounts for 50-60% of observed winds, with better fits for predominantly Zonal vs SSAS cases. • Case A: 06 June 2004 (green), Zonal=140±7 m/sec, SSAS=80±8 m/sec • Case B: 28 Mar 2009 (red), Zonal=3±7 m/sec, SSAS=98±5 m/sec B A

8. Case A: Zonally Dominated Flow Doppler winds observed (left, data) on 6June04, exhibited stronger zonal circulation, with model (middle) best fit parameters: Zonal=140±7 m/sec, SSAS=80±8 m/sec. The small residual Doppler winds (generally <10 m/sec; below right) indicate that the Zonal+SSAS model well represents the circulation at this time. Data Model Data − Model

9. Case B: SSAS Dominated Flow • Doppler winds were observed (left, data) on 28Mar09, find the Venus lower thermosphere exhibited stronger SSAS circulation. Model (center) best fit parameters are Zonal=3±7 m/sec, SSAS=98±5 m/sec. The large residual Doppler winds (right panel- generally > 30 m/sec) indicate that the Zonal+SSAS less adequately represents the circulation at this time. • Circulation is in general less organized when the time-variable zonal component is weak. Data Model Data − Model

10. Non-LTE 10 μm CO2 Doppler Winds are Dayside • Venus 110 km doppler wind measurements from 10 μm observations consistently depict SSAS circulation, with negligible Zonal flow (Goldstein et al. 1991; Sornig et al., 2008, 2012). Observations are dayside-only, at very high spatial resolutions (Left figure from presentation by T. Kostiuk + M Sornig- Paris, Jun2010). • At the geometry below, even simultaneous, co-located submm observations are primarily nightside. Comparison for validation purposes should not be made. At this geometry, the submm/10 μm comparison is potentially useful as a constraint on cross-terminator wind gradients.

11. Sulfur/Water (Sulfur/Hydrogen) photochemistry from Ground-based μ-wave observations • SO2 and SO (SOx) react with H2O to form H2SO4 . Sulfur and water chemistries are thus expected to be linked in the Venus mesosphere, though no evidence of this has been found. Destruction of water produces H, OH, and HO2, highly reactive compounds likely to impact all aspects of photochemistry. • We directly measure SO2, SO, and an upper limit for H2SO4 . • Water (H2O) is inferred from measurement of HDO with use of an assumed HDO/H2O ratio (Bjoraker et al., 1992). Our primary result is a finding of temporal variability, which is not dependent on accuracy of the assumed ratio. SOIR observations indicate HDO/H2O is variable (Fedorova et al., 2008). However, observed (SOIR) variation of that ratio is much smaller than observed (submm) variation of HDO, hence of H2O.

12. Mesospheric H2O Abundance shows Strong, Global Time Variation • Mm-wave (225 GHz) observations (upper right and below left) show 20-fold variation of mesospheric water abundance, 1998-2004, which are consistent with earlier observations by T. Encrenaz et al. (1991, 1995). • M. Gurwell et al. (2007) measured similar variation with SWAS (below right), in one case over 2-3 days..and consistently very dry conditions 2004-2007.

13. H2O u-wave Observations • Altitude sensitivity for abundances that vary ~linearly with altitude (below left) is to 70-100 km. Global H2O varies 0.0±0.06 to 3.5±0.3 ppmv), changes 100s of % over ≤ 1-2 months [Sandor + Clancy, 2005], and varies 20x in 2 days [Gurwell et al., 2007]. • Later observations shows drier conditions (H2O < 0.4 ppmv ) for 2005-2007, with large abundances (0.5-1.0 ppmv) seen in 2008-2010.

14. SO, SO2 Altitude and Time Variation • SO2 , SO submm data also show strong time variability (upper right). • Unlike water (below left) observed SOx altitude dependence strongly disagrees with model expectations (below right).

15. SO2 vs z : Data & Model • SO2 measurements are compared with the three Yung+DeMore models (right). • Data and synthetic spectra (left) show the models have too much SO2 in the lower mesosphere. • Note all these SO2 profiles have ~linear altitude dependence.

16. Upper Mesospheric H2SO4 Abundance • Zhang et al. (2010, 2012) proposed novel photochemistry to explain observed large upper mesospheric SO2 abundances. Their model required ~1000 ppb H2SO4 at ≥90 km. This would produce an very strong submm absorption (below left), which is not present. • An H2SO4 upper limit of 3 ppb at 85-100 km is determined from 346 GHz spectra (below left, Sandor et al., 2012), a finding inconsistent with that photochemistry.

17. Submm SO2 is consistent with SOIR data • SOIR SO2 measurements (left fig, Belyaev et al., 2012) show exponential altitude dependence. Submm altitude sensitivity in this case is different from that of linear variation. • SOIR SO2 altitude profiles correspond to synthetic spectra (right below) too broad to distinguish from instrumental baseline artifacts.

18. Submm SO2 is consistent with SOIR data • Over wider bandwidth regions, baseline instability can not be distinguished from very broad absorption signals. • SOIR SO2 altitude profiles correspond to synthetic spectra (right below) too broad to distinguish from instrumental baseline artifacts.

19. Upper Mesospheric SO2 • SPICAV measurements of 85-100 km SO2 and SO (Belyaev et al., 2012) significantly exceed submm values (Sandor et al., 2010). Submm and SPICAV SO2 do not agree in the upper mesosphere. • SPICAV data show negative correlation between SO2 and SO. • Submm data show positive correlation of SO2 vs SO, but only in the dayside data (below left). • SPICAV solar occultation observations are of the twilight atmosphere by definition, neither night nor day. • JCMT observations of the solar transit (below right) will provide submm measurements of the twilight atmosphere, a unique opportunity.