Victoria Sinclair University of HelsinkI David Schultz University of Helsinki, FMI,

1. Cold Fronts and their relationship to density currents: A case study and idealised modelling experiments Victoria Sinclair University of HelsinkI David Schultz University of Helsinki, FMI, University of Manchester, UK

2. Overview • Previous work and some theory concerning cold fronts and density currents • A Case Study • Observations • AROME simulation • Idealised Modeling Experiments • 2D density current and 3D cold front • Quantify governing dynamics

3. Can cold fronts be considered density currents? • Plenty of papers state that a cold front resembles a density current in appearance • Visual similarity does not equal dynamical similarity Tower observations of a cold front, Colorado Shapiro et al. 1985

4. Density Current theory X • Coriolis force can be neglected • Equations exists which predict the speed of movement as a function of density difference and the depth • Density currents have a low-level feeder flow behind the leading edge: the wind speeds behind the front (u) are greater than the speed that the gravity current moves at (c) X

5. Fronts Theory • Fronts are often assumed to be balanced, at least in the cross front direction • Acceleration term is assumed to be small. X X • No formula to predict the speed that fronts move at • Uncertainty remains as to what factors control the speed that cold fronts move at

6. Questions • What controls the speed that cold fronts move at? • Why do some cold fronts propagate – i.e. move faster than the normal component of the wind? • Why do some cold fronts move slower than the normal wind, and hence share a feature with gravity currents? • When do cold fronts collapse to resemble density currents? • Are collapsed cold fronts dynamically similar to density currents?

7. Motivation • Cold fronts that evolve into gravity current type features can produce hazardous weather • The scale of a collapsed front means that even high resolution NWP models will not capture the structure and evolution well

8. Case Study: synoptic evolution • Developed as a frontal wave on pre-existing front • Mature front and is far from the parent low • Simulated event with AROME 33h1, 2.5km 12 UTC 29 Oct 00 UTC 30 Oct 00 UTC 31 Oct

9. 7 m/s 6 m/s Shallow frontal zone 00:11 UTC • Radial wind speeds from Kumpula Radar • Cold air is confined to a shallow layer • Resembles a density current Image provided by Matti Leskinen

10. Observations AROME Temperature at Kivenlahti black: 5 m red: 26 m blue: 48 m magenta: 93 m grey: 141 m green: 218 m brown: 266 m orange: 296 m black: 2 m blue: 38 m magenta: 112 m green: 200 m orange: 300 m

11. Observations AROME Temperature at Kuopio black: 5 m red: 26 m blue: 48 m magenta: 93 m grey: 141 m green: 218 m brown: 266 m orange: 296 m green: 200 m orange: 300 m black: 2 m blue: 38 m magenta: 112 m

12. Heat Fluxes SMEAR III SMEAR II BLACK: observed. GREY: AROME Data provided by Annika Nordbo and Ivan Mammarella

13. AROME Potential Temperature 900hPa

14. Black: 18:00 UTC Red: 20:00 UTC Green: 22:00 UTC Blue: 00:00 UTC Purple: 02:00 UTC Cyan: 04:00 UTC Location of Cold Front from AROME Averaged speed of front between 22:00 UTC and 02:00 UTC Section B = 5.03 ms-1 Section C = 5.47 ms-1 Section A = 6.92 ms-1 Front is located objectively Hewson (1998) Jenker et al (2010) B B C A

15. 920 hPa 990 hPa u – c > 0 especially in south u – c ≈ 0 Wind Speeds from AROME • Wind speeds decrease behind the front • Unconvincing evidence of a “feeder flow”

16. Ascent, potential temperature Simulated Radar reflectivity 22 UTC, B 00 UTC, B 22 UTC, A 00 UTC, A

17. Case Study Conclusions • Shallow and narrow front • stable mid-troposphere • Stable BL may have prevented frontolysis by turbulent mixing • Dynamics differ to density current dynamics • No clear feeder flow • Prefrontal boundary layer appears to affect structure

18. Idealised Modelling with WRF

19. Idealized Experiment • WRF-ARW • Weather Research and Forecasting – Advance Research WRF. V3.1 • Non-Hydrostatic, range of physics options • Supported by NCAR • First simulated a 2D density current at high resolution (100m grid spacing) • Calculate force balance.

20. Density Current 5 – 10 minutes : 20.5 ms-1 10 – 15 minutes: 15.3 ms-1

21. Force Balancelowest model level (995 hPa) Blue: Potential temperature Red: Pressure Gradient Force Purple: Coriolis Black: Acceleration

22. Simulate a Cold Front • Model a full 3D baroclinic life cycle • Include two nested domains over the cold front • horizontal grid spacing is 100km : 20km : 4km • All nests have 64 levels, model top at 100hPa • Initial experiment has no moisture and no physical parameterizations

23. Potential temperature and surface pressure. Day 4.5. Parent domain

24. Potential Temperature and wind vectors. 20 km domain

25. Potential temperature and vertical motion

26. Force balance LEVEL 1 ~ 975 h Pa LEVEL 7 ~ 805 h Pa Blue: Potential temperature Red: Pressure Gradient Force Purple: Coriolis Black: Acceleration

27. LEVEL 1 ~ 975 h Pa LEVEL 7 ~ 805 h Pa Blue: Potential temperature Red: Pressure Gradient Force Force Balance 5 hrs later Blue: Potential temperature Red: Pressure Gradient Force Purple: Coriolis Black: Acceleration

28. Conclusions • Idealised cold front does not visually resemble a density current, but does have many interesting features • The force balance shows a three way balance near the cold front • HYPOTHESIS • friction and turbulence will change force balance • Trailing part of cold front will be visually more similar to density currents

29. Future work • Higher resolution (1km) simulation of cold front, include boundary layer scheme • Different baroclinic life cycles • Simulate 3D density current at comparable resolution to cold front case

30. Thank you You can look at more animations on my webpages www.atm.helsinki.fi/~vsinclai

31. Force Balance: 5 hrs later

32. Force Balance across cold front