Applied Micrometeorology in the Arctic

Summer School in Arctic Atmospheric Science

Nottawasaga Inn

12 July 2011

Ralf Staebler, Environment Canada

Outline

• Significance of surface –

atmosphere interactions

• Crash course in

micrometeorology:

– turbulent transport

– stability / atm. stratification

– flux-gradient relationships

• A flavour of recent Arctic

research projects

Surface-Atmosphere Interactions

in the Arctic

• Weather & climate forecasting: lower boundary condition of input of heat & water vapour into the atmosphere

• The Arctic Ocean as a CO2 sink

• The Arctic Ocean as a source of aerosol particles and/or their precursors (e.g. DMS)

• Deposition of aerosol particles (esp. soot) onto the Arctic snowpack (albedo effects)

• Atmosphere-surface exchange of ozone, mercury vapour and chemical species involved in their destruction / transformation

What is usually available:

• Surface parameters (remote sensing, in situ monitoring)

• Column parameters

(remote sensing, balloon profiles)

• Vertical gradients

What we’re usually really after:

Surface fluxes (emission

&

deposition rates)

Need to develop reliable

flux-gradient relationships

to get from here to there!

Crash Course in Micromet

• Micrometeorology (n.): the study of

meteorology on a spatial scale of < 1km

and time scale of < 1 day

• Focus on boundary layer dynamics,

turbulent transport, local circulations,

microclimates, atmosphere-surface

exchange

From: Oke, Boundary Layer Climates

The Boundary Layer:that part of the troposphere that is directly influenced by the presence

of the earth’s surface and responds to surface forcings with a time

scale of ~ an hour [100’s to low 1000’s of meters]

The Surface Layer:the layer in direct contact with the surface in which turbulent fluxes are

not significantly different from the surface fluxes

(“constant flux layer”)

Often arbitrarily taken as the bottom 10% of the BL.

More Definitions...

From R.B.Stull: An Introduction to Boundary Layer Meteorology

uD

itycosvis

inertiaRe

From: Oke, Boundary Layer Climates

Laminar vs. Turbulent Flow

From: D.A. Haugen (Ed.), Workshop on Micrometeorology

“Big whorls have little whorls,

which feed on their velocity;

and little whorls have lesser whorls,

and so on to viscosity.“L.F. Richardson, 1922

(paraphrasing Jonathan Swift)

Energy source for ALL atmospheric motions:

Horizontal

temperature

gradients

Mechanical turbulence

Wind

Vertical

temperature

gradients

Thermal turbulence

Buoyancy

The SUN

Surface Heating

So you may say: don’t forget about molecular diffusion as

a transport mechanism!

Well…

Molecular diffusivity: ~10-5 m2s-1

Eddy (turbulent) diffusivity at 20 m with moderate

winds: ~ 10 m2s-1 (i.e. a million times higher)

Molecular diffusivity only plays a role really close to the

surface, where eddy diffusivity drops (~ linearly with z),

i.e. for z < 1 mm

The Richardson Number: a measure of stability

2

z

u

z

g

Ri

potential energy

kinetic energy

negative lapse rate Ri < 0 statically unstable

KE > PE Ri < 0.25 dynamically unstable

positive lapse rate &

wind shear not too big: Ri > 0.25 stable

Stull 1988

Profile Statistics, Amundsen 2008Temperature

(Microwave Profiler)

Wind Speed

(Sodar) Richardson Number

Dome C (French/Italian Antarctic Research Station): 3233m ASL

C. GENTHON, D. SIX, V. FAVIER, L. GENONI,

C. POUZENC, A. PELLEGRINI

CNRS / LGGE (France): “Extremely Stable

Boundary Layer on the Antarctic Plateau”. IPY

Science Conference, Oslo, June 2010.

Analogy of turbulent fluxes with diffusion: the eddy diffusivity approach

Classical Diffusion – Fick’s First Law

x

cDJ

Where

J is the diffusion flux [mol m-2 s-1]

D is the diffusion coefficient or diffusivity [m2 s-1]

c is the concentration [mol m-3]

x is the position [m]

z

cKF

So we assume that turbulence transports

quantity c in a similar manner, and say

Where

F is the turbulent flux [mol m-2 s-1]

K is the turbulent transport coefficient

or eddy diffusivity [m2 s-1]

low c

high c

To deal with this, we turn to Monin-Obukhov Similarity Theory:

A bunch of universal empirical relationships to describe

vertical profiles and fluxes in the boundary layer

For example: The wind profile in the surface layer under neutral conditions

(no heat flux) is well described by

kz

u

dz

u *

)''(2

* wuu where u* is the friction velocity and k is the von Karman constant

(0.4). Note that u* is a measure of the momentum flux.

dz

u

u

kzm

*

Let’s define a nondimensional gradient

It stands to reason that the relationship between vertical gradients and

fluxes is a function of stability; i.e.

z

cstabilityKF )(

Similarity Theory continued

There are similar relationships between heat flux and the temperature profile, etc.

[Businger-Dyer relationships]

, z/L > 0 (stable)

, z/L =0 (neutral)

, z/L < 0 (unstable)

L

z7.41

4/1

151

L

z

m = 1

''

3

*

v

v

wkg

uL

Turns out that m under non-neutral conditions can be expressed as a universal

empirical function of the normalized height z/L,

where L, the Obukhov length, is given by

Flux-Gradient Relationships

z

uKF mmm

)(

To get back to the eddy diffusivity concept:

1

*

1)( mmneutralmm kzuKK

It is easy to show that

unstable stable

neutral

and similar for eddy diffusivities for heat and

gases

Low O3

High O3

Updraft:

w’ > 0

O3’ < 0

Downdraft:

w’ < 0

O3’ > 0

Average Wind O3 & w’

Sensors

www '

333 ' OOO

'' 3OwFlux

Still not convinced this is a flux? Check the units: (m/s)(ng/m3) = ng/m2/s

The Eddy Covariance Technique

Example: O3 fluxes

(Ultra)Sonic Anemometers

d / t1 = c - w

d / t2 = c + w

w = d/2(1/t2 – 1/t1)

c = d/2(1/t2 + 1/t1)

Tc

t1t2

Sources

and Sinks (s)

szcw

xcu

zw

xuc

zcw

xcu

tccu

tc

Dt

Dc

'''')()(

dz

z

cwAdvectionVertical :

cdzt

Storage :

The O3

budget: conservation of c (2-D simplification)

'': cwExchangeTurbulent

dzx

cu

AdvectionHorizontal

:

Current Research

• Under what conditions can Arctic surface

fluxes be determined through standard flux

techniques?

• How far can we extend Monin-Obukhov

similarity theory into very stable regimes?

• Can we develop a theory that quantifies

intermittent transport in very stable

regimes?

SHEBA data set

• Micromet tower near the Des

Groseilliers Canadian Coast

Guard Icebreaker, parked in the

Beaufort/Chukchi Seas

• 5 sonics between 2.2 and 18.2m

• 11 months of data

Grachev et al., Boundary-Layer Meteorology (2005) 116:201235

(z1 = 2m)

z

uKFlux neutral

OASIS 2009

Barrow, Alaska

Micromet Tower:

5 sonic anemometers

4-component net radiometer

Temperature & humidity

Surface temperature (IR)

Atmospheric Pressure

nearby (420m south):

SODAR (wind speed & direction up to

800m)

NOAA / ARM (2km east):

ozone sondes

rawinsondes

Microwave profiler

Median sonic SL Profiles, Barrow’09

“There is no critical Richardson number above which the turbulence

vanishes”. Larry Mahrt (2010), “Variability and Maintenance of Turbulence

in the Very Stable Boundary Layer”, BLM 135, 1-18.

Sorbjan & Grachev (2010)

SHEBA Galperin et al. (2007)

Prandtl Number:

Pr = Km/Kh

Summary:

1. It’s not THAT stable in the Barrow

surface layer (in April), i.e. standard

flux methods work well much (85%)

of the time

2. We still don’t know how to deal with

very stable conditions… need multi-

year flux-gradient measurements to

collect enough ultra-stable data

Future Work:

1. Flux-gradient relationships for gas

exchange (Kc(z/L))

2. Flux-gradient “monitoring” at various

locations

3. Theoretical framework to deal with

intermittent mixing in very stable

conditions

Questions?

Collapsible mast:

* Wind-speed/direction

* Global radiation (up/down)

* Sonic anemometer

* Tilt sensor

* Temperature 3 levels

* Relative humidity

* High level gas sampling

Top of instrument box:

* MAXDOAS scanhead with

tilt/compass sensor

* GPS antenna

* WiFi antenna

* webcam

Inside instrument box:

Two shock proof instrument racks :

* 2B ozone monitors (two)

* Gardis GEM monitors (two)

* MAXDOAS spectrometer for BrO

* Licor CO2 monitor

* GPS

* CR3000 data logger

* PC104 computer

* WiFi radio

Other features

* 100% autonomous operation for

duration of battery charge (~2 days)

* Self heating

* 24 VDC power with DC/DC

converters providing stable 12.6 VDC

* Sled on Teflon runners

* Low level gas sampling (10 cm)

* Setup time: 15 min

The famous OOTI sled