  # WEEK 4: TURBULENCE Homework assignment robwood/teaching/431/... WEEK 4: TURBULENCE Homework assignment

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• WEEK 4: TURBULENCE

Homework assignment

Read Chapters 8 and 9 of Introduction to Micrometeorology, by Arya Problems: 1. Describe the mechanisms by which turbulence can form in the boundary layer. Include in the description the two basic types of instability. Under which conditions do you expect each of these types of instability to be most important? 2. Given the data in Figures 1 and 2 below estimate the static stability and the wind shear as a function of height. Calculate the Richardson number and attempt to determine which levels, if any, might be unstable. If so, what type of instability you think would dominate? Given what you know about the nature of sea-breezes, do you think that the use of potential temperature rather than virtual potential temperature would be important?

Figure 1: Cross-section of wind vectors and potential temperature associated with a sea-breeze front propagating from right to left. The surface front is at x’=0. The vertical coordinate is height above the (flat) surface. The measurements were made using a series of flight legs with an instrumented aircraft.

Figure 2: Vertical profiles of potential temperature and front-normal wind speed as a function of height averaged horizontally over the region 0

• Assuming that any instability would likely lead to turbulence and mixing, what consequences might such mixing have for the sea-breeze front? Consider what mixing does to the buoyancy and to the momentum. 3. Describe how eddy viscosity can be used in place of molecular (kinematic/dynamic) viscosity in the equations of motion. Given that eddy viscosities for even weakly turbulent flows are much greater than the kinematic viscosity for air, what consequences does this have for the depth of the Ekman layers that form in the atmosphere and ocean? 4. A turbulent time series (e.g. Fig. 8.1 in Arya) can be considered as consisting of the sum of many signals of different frequencies. A power spectrum of a time series gives the amount of variance in a signal broken down by the temporal scale of the signal. Below is a time series of the near-surface horizontal wind speed taken over land. The x-axis shows the frequency in cycles per hour (or, in reverse, the number of hours per cycle), from motions on scales of a few seconds to several hundred hours. What does a peak in this spectrum imply about the structure of the flow? Determine the timescales (hours per cycle) for the three peaks shown. Given a mean horizontal wind of 5 m s-1, what does this imply for the spatial scales of the motions. Is it possible to attach physical significance to the three peaks?

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