4 th internat. symposium on flood defence – toronto/ca sensitivity analysis of lapse rate and...
TRANSCRIPT
4th Internat. Symposium on Flood Defence – Toronto/CA
Sensitivity analysis of lapse rate and corresponding elevation of the snowline
Limited data availability and its impact on snow and glacier melt
Rinderer M., Achleitner S., Asztalos J., Kirnbauer R.
According tomy model
it‘s snowingup there!
Outline
Introduction
Aims and Questions
Method
Analysis and Results
Conclusions
Perspectives
Introduction – Roll of Snow and Glacier Melt Modelling
Fluvial regime of mountainous regions Intermediate-term and long-term retention of precipitation -> influence on
amount of runoff generated during a rainfall event (1) Elevation of the temporary snowline (snow/rain) (2) System conditions: snowfree: immediate runoff/infiltration; snow-
covered: temporary absorption and retention by the snow cover
Water is released in warmer periods Days, weeks, month later
Not only precipitation but also snow and glacier melt influence fluvial regime
Importance for flood forecasting in glaciated areas
Introduction – Flood Forecasting System HOPI
Hybrid-model concept Main river course:
hydraulic model FluxDSS/DESIGNER
Tributary catchments: hydrological model HQsim
Glacier melt: energy-balance model SES
Introduction – Snow and Ice Melt Model SES
photo: USI/Ibk
Physically-based, spatially distributed, energy balance model Based on a snow melt model by Blöschl et al. (1987) and
Blöschl et al. (1991), further developed by Ansztalos (2004) grid based model (1) distributed accumulation of snow (2) snow, firn and ice melt in a glaciated catchment resulting runoff calculated for individual grid elements is
routed to the catchment outlet using a Nash-Cascade approach
Meteologolical input lapse rate air temperature
Introduction – Determination of Snowline
Modelling snowline: Not a straight line but a zone of
transition Simulated using a lower and an
upper temperature-boundary to separate snowfall from rain
In the transition-zone a portion is considered to be snow, the rest rain
Highest weather station measuring air temperature situated at 2850 m a.s.l.
Glaciated area ~ 3000 – 3700 m a.s.l.
-> Temperature extrapolated to glaciated area using linear regression method
photo: USI/Ibk
Questions
1. How well is the temperature in the snow- and ice-region estimated by the simple linear regression method?
2. Which set of stations is most reliable for calculating lapse rate and corresponding elevation of the snowline?
3. How sensitive is the approach to limited data availability?
Method – Study Area Ötztal
45km SW Innsbruck Total area: 895 km² ~ 13% glaciated ~ 700 – 3700m a.s.l. ~ 50 % > 2500m a.s.l. 22 weather stations
Method – Event Selection
Data available 1994 – 2001
-> August 1999
Showing typical warm periods -> runoff induced by melting
Typical cold weather period -> runoff influenced by snowfall
photo: TirolAtlas
Excluding station „Pitztaler Gletscher“ 2850 m a.s.l. -> reference Assort groups of weather stations depending on elevation and number
Estimation of mean lapse rate and corresponding 0°C-temperature line as well as temperature reconstruction at 2850 m a.s.l.
using linear regression method and various sets of data (availability-scenarios)
Method – Mean Lapse Rate and 0°C-Temperature Line
elevation [m a.s.l.] zone number of stations
700 – 1000 submontan 6
1000 – 1800 montan 6
1800 – 2000 subalpin 6
2000 – 2300 alpin 3
2850 alpin 1 (used as reference)
Analysis/Results – Air Temperature at 2850 m a.s.l.
-2
0
2
4
6
8
10
12
14
16ai
r te
mp
erat
ure
at
2850
m a
.s.l.
[°C
]
9.8.99 11.8.99 13.8.99 15.8.99 17.8.99 19.8.99 21.8.99
date
measured at2850 m a.s.l. stations 700 - 2850
stations 1800 - 2300stations 1000 - 2300
stations 700 - 2300stations 700 - 2000
stations 700 - 1800
warm and dry cold and wet moderate to warm and wet
Analysis/Results – Mean Lapse Rate
-1.0
-0.9
-0.8
-0.7
-0.6
-0.5
-0.4
-0.3
-0.2
-0.1
0.0
lap
se
rate
[°C
/100
m]
9.8.99 11.8.99 13.8.99 15.8.99 17.8.99 19.8.99 21.8.99
date
reconstructed
stations 700 - 2850
stations 1800 - 2300stations 1000 - 2300
stations 700 - 2300stations 700 - 2000
stations 700 - 1800
dT
/dz
[°C
/100
m]
warm and dry cold and wet moderate to warm and wet
Analysis/Results – Elevation of 0°C-Temperature Line
2000
2500
3000
3500
4000
4500
5000
5500
6000
6500
7000
elev
atio
n o
f 0°
C-t
emp
erat
ure
lin
e [m
a.s
.l.]
9.8.99 11.8.99 13.8.99 15.8.99 17.8.99 19.8.99 21.8.99
date
reconstructed
stations 700 - 2850
stations 1800 - 2300stations 1000 - 2300
stations 700 - 2300stations 700 - 2000
stations 700 - 1800
warm and dry cold and wet moderate to warm and wet
Conclusions – Temperature Extrapolation
The more measurements of weather stations of different elevation are available the better the extrapolation results
Considering only the (few) stations at high altitude may not directly result in more plausible estimations …
… but causes high variability Mean lapse rate is a major simplification of stratification of the
atmosphere An error in one or two °C/100m considerably influences the
elevation of the snowline … … and therefore may lead to false simulation of snowfall or
rainfall in large parts of the glaciated area -> use of more complex method
1. How sensitive are more complex methods for estimation of lapse rate and corresponding snowline?
2. How sensitive is the simulated runoff to errors in estimation of the snowline in the headwaters? in the lower course?
3. What kind of influence has incorrect snowline modeling to runoff estimation of the total Inn catchment (~7000 km²)
Perspectives
Thanks for your attention
photo: USI/[email protected]