Predicting Martian Dune Characteristics Using Global and Mesoscale MarsWRF Output

1. Predicting Martian Dune Characteristics Using Global and MesoscaleMarsWRFOutput Claire Newman working with Nick Lancaster, Dave Rubin and Mark Richardson Acknowledgements: funding from NASA’s MFR program, and use of NASA’s HEC facility right here at Ames.

2. Overview of talk • Motivation (why dunes?) • Dune features we can compare with • Some dune theory • Modeling approach • Preliminary results: Global • Preliminary results: Gale Crater

3. Motivation: how do dunes provide insight into recent climate change on Mars? • Higher obliquity should produce stronger circulations & surface stresses, hence might expect more saltation and dune formation • Features (i.e., dune orientations, migration directions, etc.) in disagreement with predictions for current wind regime may indicate inactive dunes formed in past orbital epochs Also – • In absence of near-surface meteorological monitoring, predicting characteristics of active dunes can help us confirm that we • have the current wind regime right • understand dune formation processes

4. Dune features we can compare with

5. Dune features we can compare with • Locations Bourke and Goudie, 2009

6. Dune features we can compare with • Locations • Bedform (crest) orientations Images: NASA/JPL/University of Arizona

7. Dune features we can compare with • Locations • Bedform (crest) orientations Images: NASA/JPL/University of Arizona

8. Dune features we can compare with • Locations • Bedform (crest) orientations • Inferred migration directions (crater dunes) Hayward et al., 2009

9. Dune features we can compare with • Locations • Use a numerical model to predict saltation over a Mars year, assuming a range of saltation thresholds • Bedform (crest) orientations • Apply ‘Gross Bedform-Normal Transport’ theory • Inferred migration directions (crater dunes) • Assume correlated with resultant (net) transport direction

10. Some dune theory

11. 2 key issues • Dunes form in the long-term wind field • Dune orientations are not determined by net transport

12. Gross Bedform-Normal Transport A simple example to illustrate a point Dune crest Rubin and Hunter, 1987

13. Gross Bedform-Normal Transport A simple example to illustrate a point First wind direction Dune crest

14. Gross Bedform-Normal Transport A simple example to illustrate a point First wind direction Dune crest Second wind direction

15. Gross Bedform-Normal Transport A simple example to illustrate a point First wind direction Net transport = 0 Dune crest Second wind direction

16. Gross Bedform-Normal Transport A simple example to illustrate a point First wind direction Net transport = 0 But both wind directions shown cause the bedform to build Dune crest Second wind direction

17. Gross Bedform-Normal Transport A simple example to illustrate a point First wind direction Net transport = 0 But both wind directions shown cause the bedform to build => rather than net transport, we are interested in gross transport perpendicular to the bedform, regardless of the ‘sense’ of the wind (i.e., N-S versus S-N) Dune crest Second wind direction

18. Bedform orientation – the theory

19. Bedform orientation – the theory A A = NET TRANSPORT OF SAND

20. Bedform orientation – the theory

21. Bedform orientation – the theory B C B+ C = GROSS BEDFORM-NORMAL SAND TRANSPORT

22. Bedform orientation – the theory • Basic concept: dunes form due to sand transport in both directions across bedform • Bedforms align such that total transport across dune crest is maximum in a given wind field • where total transport = Gross Bedform-Normal Transport [Rubin and Hunter, 1987] B C B+ C = GROSS BEDFORM-NORMAL SAND TRANSPORT

23. Modeling approach (1)

24. Bedform orientation – the approach • Run numerical model to predict near-surface winds at all times for a long time period (at least 1yr) to capture the long-term dune-forming wind field • Choose a saltation threshold and calculate sand fluxes in all directions [0, 1, …359° from N] • Consider all possible bedform orientations [0, 1, …179° from N] • Sum the gross sand flux perpendicular to each orientation over the entire time period • Find the orientation for which the total gross flux is maximum • NB: secondary maxima indicate secondary bedformorientations

25. The numerical model: MarsWRF • Mars version of planetWRF (available at www.planetwrf.com) • Developed from Weather Research and Forecasting [WRF] model widely used for terrestrial meteorology • Multi-scale 3D model capable of: • Large Eddy Simulations • Standalone mesoscale • Global • Global with nesting • Using global and global with nesting for these studies

26. Version of MarsWRF used here includes: • Seasonal and diurnal cycle of solar heating, using correlated-kradiativetransfer scheme (provides good fit to results produced using line-by-line code) • CO2 cycle (condensation and sublimation) • Vertical mixing of heat, dust and momentum according to atmospheric stability • Sub-surface diffusion of heat • Prescribed seasonally-varying atmospheric dust (to mimice.g. a dust storm year or a year with no major storms) or fully interactive dust (with parameterized dust injection) • Ability to place high-resolution nests over regions of interest

27. Results

28. Present day global dune results comparing with Mars Global Digital Dune Database (MGD3, e.g.Hayward et al., 2009):1. Dune centroid azimuth – compare with GCM-predicted resultant transport direction

29. Present day global dune results comparing with Mars Global Digital Dune Database (MGD3, e.g.Hayward et al., 2009):1. Dune centroid azimuth – compare with GCM-predicted resultant transport direction2. Slipface orientation – compare with normal to GCM- predicted bedform orientation

30. Present day global dune results comparing with Mars Global Digital Dune Database (MGD3, e.g.Hayward et al., 2009):1. Dune centroid azimuth – compare with GCM-predicted resultant transport direction –agreement => within 45° of dune centroid azimuth direction2. Slipface orientation – compare with normal to GCM-predicted bedform orientation – agreement => within 45° of normal to slipface

31. Comparison of predicted and inferred migration direction for present day using saltation threshold=0 Green => agreement between predicted and inferred migration direction Blue => no agreement Red => no comparison possible

32. Comparison of predicted and inferred migration direction for present day using saltation threshold=0.007N/m2 Green => agreement between predicted and inferred migration direction Blue => no agreement Red => no comparison possible

33. Comparison of predicted and inferred migration direction for present day using saltation threshold=0.021N/m2 Green => agreement between predicted and inferred migration direction Blue => no agreement Red => no comparison possible

34. Comparison of predicted and measured bedform orientation direction for present day using saltation threshold=0 Green => agreement between predicted and inferredbedform orientation Blue => no agreement Red => no comparison possible

35. Comparison of predicted and measured bedform orientation direction for present day using saltation threshold=0.007N/m2 Green => agreement between predicted and inferredbedform orientation Blue => no agreement Red => no comparison possible

36. Comparison of predicted and measured bedform orientation direction for present day using saltation threshold=0.021N/m2 Green => agreement between predicted and inferredbedform orientation Blue => no agreement Red => no comparison possible

37. Comparison of predicted and inferred migration direction for obliquity 35° using saltation threshold=0.007N/m2 Green => agreement between predicted and inferred migration direction Blue => no agreement Red => no comparison possible

38. Comparison of predicted and inferred migration direction for present day using saltation threshold=0.007N/m2 Green => agreement between predicted and inferred migration direction Blue => no agreement Red => no comparison possible

39. Modeling approach (2)

40. Nesting in MarsWRF One or more high-resolution ‘nests’, placed only over regions in which increased resolution is desired

41. Mother [global] domain (only a portion shown) 5°N Domain 2 (5 x resolution of domain 1) 0° Domain 3 (5 x resolution of domain 2; 25 x resolution of domain 1) 5°S 20°E 15°E 25°E 30°E 35°E

42. Mother [global] domain 2-way nesting => feedbacks between domains 5°N Domain 2 Domain 3 0° 1-way nesting => parent forces child only 5°S 20°E 15°E 25°E 30°E 35°E

43. Sample results for Gale at Ls ~ 0° using mesoscale nesting in global MarsWRF

44. Gale dune studies – early results (~4km resolution) Gale Crater: predicted (a) resultant transport direction [black arrows] (b) dune orientations [white lines] for saltation threshold = 0

45. Gale dune studies – early results (~4km resolution) Gale Crater: predicted (a) resultant transport direction [black arrows] (b) dune orientations [white lines] for saltation threshold = 0.007N/m2

46. Gale dune studies – early results (~4km resolution) Gale Crater: predicted (a) resultant transport direction [black arrows] (b) dune orientations [white lines] for saltation threshold = 0.021N/m2

47. Gale dune studies –present day Mars No saltation threshold Saltation threshold = 0.007N/m2

48. Gale dune studies –present day Mars No saltation threshold Saltation threshold = 0.007N/m2

49. Gale dune studies –present day Mars No saltation threshold Saltation threshold = 0.007N/m2 From Hobbs et al., 2010

50. Gale dune studies –present day Mars • Simply changing the assumed saltation threshold greatly improves the match to observed bedform orientations • Effect of large dust storms not yet examined, but likely will also impact winds hence orientations • Orbital changes and impact on circulation widen parameter space even further!