Snow studies in Spain
Juan Ignacio López Moreno
Pyrenean Institute of Ecology, CSIC
nlopez@ipe.csic.es
Snow studies in IPE-CSIC:
- Spatial and temporal variability: interactions with topography and vegetation
- Snow hydrology and water management.
- Sensitivity of snowpack to climate and trends
- Snow and climate change.
>100km
˜km
˜hm‐m
˜m‐dm
Spatial variability
Predictors from DEMs
Statistical models
Snow maps
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Snow depth (cm)
0
10 - 50
50 - 100
100 - 150
150 - 200
200 - 250
250 - 300
300 - 350
350 - 400
400 - 450
450 - 500
>500
Long-term average snow depth in the Spanish Pyrennes at early April
Spatial variability
Spatial variability
Importance of local snow variability for snow sampling
0.25
Coefficient of variation
0.20
0.15
Error (%)
2
4
6
8
10
12
14
16
0.10
0.05
April
2
4
6
8
10
12
14
16
18
20
Replications
López Moreno, J.I., Fassnacht, S.R., Beguería, S.; Latron, J. (2011). Variability of snow depth at the plot scale: implications for
mean depth estimation and sampling strategies. The Cryosphere 5: 617-629.
Izas catchment (2056 m a.s.l.)
Functioning since 1996
‐Temperature
‐Relative humidity
‐ Atmospheric pressure
‐In and out solar radiation
‐Wind speed and direction
‐Precipitation (Geonor)
‐Runoff (33ha)
* Snow pillow
*Surface snow temperature
• Soil temperature (4 levels)
Telenivometer
Spice site
Authomatic Weather stations
Snow dynamics in the Izas Catchment
Snow products from time‐lapse photos
Terrestrial laser scanner technology (TLS)
Riegl LPM-321
Range: up to 6000 m
Coefficient of variation: persistence between different dates
February, 22nd
April, 17th
May, 14th
Coefficient of variation:
persistence amongst different
spatial scales
February, 22nd
5x5m
25x25m
49x49m
99x99m
Intra-seasonal and intra-annual
persitence of snow models
USE of TLS for correcting snow models
Distributed simulation of Crocus
USE of TLS for correcting snow models
Spatial variability: forests
Spatial variability: forests
2001
Spatial variability: forests
2009
Spatial variability: forests
Spatial variability: forests
Canopy density from (GLA v2.0)
Spatial variability: forests
Relation between snowpack and canopy density
Gap fraction (Zenit angle=55º)
January
February
March
April
May
70
60
SWE (mm)
0
100
200
300
400
500
600
50
40
30
1
9
16 22
29
37
51
59
70
79
87 92
Day of measurement
99 104 110 117 125130134 141
Spatial variability: forests
Ene
Feb
Marzo
Abril
Mayo
2.0
1.5
Densidad forestal elevada
Factorial scores (-)
1.0
0.5
0.0
-0.5
-1.0
Baja densidad de bosque
-1.5
-2.0
1
9
16
22
29
37
51
59
70
79
87 92
99 104 110
117
125 130134
141
Spatial variability: forests
Spatial variability: forests
Spatial variability: forests
Target
Target
Spatial variability: forests
Spatial variability: forests
Deep
snowpack
PCA component
C1
Shallow
snowpack
C2
Late Wind
season
C3
C4
Survey date
Open AvgSD [m]
Canopy AvgSD [m]
Diff.Open‐Cnpy [%]
27/02/2013
1.53
1.11
28
04/03/2013
1.45
1.04
28
08/03/2013
1.29
0.90
30
15/03/2013
1.53
1.04
32
21/03/2013
1.45
0.98
33
09/04/2013
1.14
0.67
41
14/04/2013
0.96
0.51
46
18/03/2013
0.73
0.29
60
20/12/2011
0.16
0.08
52
02/02/2012
0.15
0.05
69
06/12/2012
0.49
0.32
36
11/12/2012
0.30
0.19
37
20/12/2012
0.30
0.15
51
27/12/2012
0.22
0.07
70
09/02/2012
0.26
0.13
50
28/02/2012
0.14
0.03
81
13/03/2012
0.03
0.01
68
16/04/2012
0.02
0.01
14
26/04/2013
0.41
0.10
76
02/05/2013
0.30
0.06
80
Avg Dif.%
37
52
53
78