Glacier atmosphere interactions
and hydrology:
Peyto field experiment discoveries.
D. Scott Munro
University of Toronto
base (2240 m) +
low (2183 m) +
middle (2461 m) +
high (2709 m) +
AWS
Network
• ← Point process
investigation:
glacier atmosphere
interactions and
hydrology
• ← Distribution tools
(DEM, trigonometry,
parameterization)
• ← Distributed
modelling and
prediction
• ← Base AWS/RCM
forcing
Snow
reservoir
Snow accumulation
Ice
reservoir
Ice & Snow melt

K  1  α i/s   L*  Q H  Q E 
Pr/s 
  δM j
 i/s Lf

j
qj
Model – AWS Comparisons
Low AWS - 2003
SR50
DenAdjSR50
Model
2
2
1
1
0
0
-1
-1
h (m)
h (m)
Model
Middle AWS - 2006
-2
-3
-4
-4
-5
-5
Day of Year
DenAdjSR50
-2
-3
30 60 90 120 150 180 210 240 270 300 330 360
SR50
30 60 90 120 150 180 210 240 270 300 330 360
Day of Year
Hydrology
q M  Ar
QM
i  f
K~1.5 h
K~10.5 h
q
S t 1  q M  q (t 1)
K
03-06 Mean
71-74 Mean
Mϋller & Keeler 1969
2.0
q/q24
1.5
1.0
0.5
0.0
170
173
176
179 182
185
188
191 194
197
200
203 206
209
212
215 218
221
224 227
230
233
236 239
241
2.0
2.0
1.5
1.5
1.0
1.0
q/q24
q/q24
June to August Melt Period
0.5
0.5
0.0
0.0
168
169
170
171
172
173
174
175
176
177
232
233
Early Melt Period
235
236
237
238
239
240
241
Late Melt Period
2.0
2.0
R² = 0.73
2008
1.5
2003-06
1971-74
1.5
q/q24
Measured71-74 q/q24
234
1.0
1.0
0.5
0.5
K~11.25 h, ice;
100 h, snow
0.0
0.0
0.0
0.5
1.0
Model03-06 q/q24
1.5
2.0
8
12
16
20
Time ( h )
24
4
Glacier – Atmosphere Interaction
•
Focusing on the sensible heat flux, QH, there are respectively to the right
of the equal sign the gradient, eddy correlation (EC) and bulk transfer
methods of obtaining the flux density:


 Du DT   2
T  TS
2
  c p w' T '  c p k u
Q H  c p k z 

2

D
z
D
z




ln
z
z




o
2
2
•
The key feature of the flow regime is a local wind speed maximum, close
to the surface, through which heat should not flow because Du/Dz = 0, yet
the bulk transfer approach seems to provide reasonable heat flux values,
regardless of the measurement height used.
• Although EC measurements of QH below the local wind speed maximum
seem to agree with bulk transfer estimates, less is known about EC
measurements near to and above the level of maximum wind speed.
• Also to consider is the Oerlemans-Grisogono parameterization (OG)
......which is convenient for modelling, but contrary to classical thinking.....
......about the nature of the glacier atmospheric boundary-layer.
𝑄𝐻 = 𝜌𝑐𝑝
𝐾𝑔𝑒𝑜 + 𝐾𝑘𝑎𝑡
2
𝑇 − 𝑇𝑆
If classical thinking is correct EC measurements of QH → 0 near the
.....local wind speed maximum, but if OG is correct the QH measurements
.....will show a step change across the level of maximum wind speed.
•
Experiment objectives:
Regional Wind ?
A: B-L turbulent flow field, 1-6 m
B to A: B-L acceleration & cooling
6m
6m
B
4m
4m
A
Mobile EC
2m
2m
Fixed EC
1m
1m
~50 m
~ 650 m
Turbulent flow field, 1-6 m
R
e
g
i
o
n
a
l
G
l
a
c
i
e
r
W
i
n
d
W
i
n
d
Acceleration & cooling
6
5
H eig h t (m)
4
3
A: Wind
2
B : Wind
A: T emp.
1
 dDz
B : T emp.
0
0
5
10
15
20
-1
Wind S peed (m s ) T emperature (°C )
Taking mean values, assuming no heat transfer
across 4 m and correcting for adiabatic warming,
expect 1 & 2 m TA< TB by ~2 °C.
Concluding with analogues:
On hydrology:
• An electrical analogue to consider for supraglacial runoff is a
series resistance system that links the runoff potential of the
melting ice surface to supraglacial stream discharge.
• In such a system resistance should increase with weathering
crust development, decrease with decay, so a good test of this
idea is to continuously measure short-term runoff from a
supraglacial basin all summer to see if K depends on the weather.
On glacier-atmosphere interactions:
• An electrical analogue to consider for boundary-layer heat
transfer to the glacier is a parallel resistance system that links the
energy potential of the regional air mass to surface melt.
• One branch of such a system is the geostrophic flow, the other a
katabatic flow that is subject to sporadic breakdown, thus
explaining hot flash behaviour.
• This is supported by the 2008 eddy correlation data that suggest
two turbulent transfer fields adjacent to the glacier surface, one of
which extends above the level of the wind speed maximum.
Acknowledgements
CFCAS → IP3 Network Funding
Environment Canada → CRYSYS Program
NSERC → Discovery Grants
Natural Resources Canada → GSC-CGVMAN
University of Toronto Mississauga