• No results found

Snow Monitoring and Glaciers Mass Balance from SPOT/VEGETATION

N/A
N/A
Protected

Academic year: 2021

Share "Snow Monitoring and Glaciers Mass Balance from SPOT/VEGETATION"

Copied!
24
0
0

Loading.... (view fulltext now)

Full text

(1)

Snow Monitoring and Glaciers Mass Balance from SPOT/VEGETATION

Vanessa Drolon Else Swinnen Etienne Berthier Philippe Maisongrande

Copyrights E. Berthier

(2)

Probing VEGETATION Conference – Antwerpen 4-5 July 2013

15 years of monitoring

devoted to various thematic Issues

• NDVI as a proxy of LAI, productivity

• Evapotranspiration and water budget

• SWVI as a proxy of Water stress

• Land use land cover

• Water bodies, Snow and Glaciers

(3)

NDVI = ρ

pir

rouge

Ρ

pir

rouge

NDSI = ρ

mir

vis

Ρ

mir

vis

Normalized Difference

Vegetation Index

Normalized Difference Snow Index

Vegetation and Snow index

(4)

Probing VEGETATION Conference – Antwerpen 4-5 July 2013

LANDSAT vs VEGETATION Snow Cover

High-Atlas mountains

(Morocco)

(5)

NDSI

sn ow c ov er r at io Snow Monitoring

Altitude 2600-4200m

0 200 400

Snow surface (km²)

North South

Optimal snow indices NDSI

Space time dynamics of snow cover sensitivity to elevation & exposure

0 0,5 1

Snow cover proportion

1000-1400m 1400-1800m 1800-2200m 2200-2600m 2600-3000m 3000-3400m 3400-3800m 3800-4200m

Boudhar et al. Sècheresse 2007. Chaponnière et al. International Journal of Remote Sensing. 2005

(6)

Probing VEGETATION Conference – Antwerpen 4-5 July 2013

50 100 150 200 250 300 350 400 450 500 20

40

60

80

100

120

140

NDSI applications

50 100 150 200 250 300 350 400 450 500

20 40 60 80 100 120

140 -0.6

-0.4 -0.2 0 0.2 0.4 0.6

Pas de neige σ(NAO de août à octobre) = 1,35

σ(NAO de août à octobre) = 0,7 σ(NAO de août à octobre) = 0,1

Snow coverage climatology

Internannual variability, trends in extent & duration, etc…

Sensitivity to meteo. e.g.NAO…

Hydrology & Glaciers Mass Balance

(7)

The Sea Level Rise and its causes

1993 2010 Global Sea Level Rise

Cazenave & Llovel; Church et al. 2011

Observed SLR +3.2 mm/a Thermosteric

Dilatation

+1.0 mm/a Polaires ice caps +0.6 mm/a

Glaciers +0.9 mm/a

Sea Level Rise (Kemp et al. 2011) For 2000 years = 0.5 mm/year, 100 ans = 1.7 mm/year

0.24 ± 0.15 mm/y due to Antarctic

0.2 mm/y due to Himalaya (s.l.)

(8)

Probing VEGETATION Conference – Antwerpen 4-5 July 2013

Melting of Alpin glaciers from 1979 to 2003

E. Berthier (LEGOS)

The Mont Blanc glacier

by SPOT 5

(9)

Glaciers Mass Balance Monitoring

•e.g. :Himalayan glaciers ~ 0,2mm/y (20% cont.melting)

•SPOT/HRS, Accurate but sparse

Available SPOT/HRS data

•SPOT/HRS (120km *600)

•Sparse Coverage

•Weak revisiting period

•Not free of charge…

T 0 + 90 s

T 0

(10)

Probing VEGETATION Conference – Antwerpen 4-5 July 2013

•Glaciers Annual Mass Balance = f(snonw_cov. (time, altitude)) (Snow line altitude: Kulkarni et al. 2004, Rabatel et al. 2005)

SRTM NDSI map

A need for an alternative methodology

NDSI Reliable

interanuality

(11)

SPOT/VEGETATION (1998 -> 2010)

NDSI altitudinal distribution

(12)

Probing VEGETATION Conference – Antwerpen 4-5 July 2013

BMG Chhota Shigri

SPOT/VEGETATION (1998 -> 2010)

NDSI altitudinal distribution

(13)

Probing VEGETATION Conference – Antwerpen 4-5 July 2013

Glaciers Mass Balance Vs Snowline Altitude

Equation de la droite de régression y = -0,0036x + 14,16 Coefficient de corrélation R2 = 0,9346

-2,00 -1,50 -1,00 -0,50 0,00 0,50

3700 3800 3900 4000 4100 4200 4300 4400

Altitude (en mètre)

Bilan de masse annuel (en mètre d'eau)

BMG = -0,0036*altitude+14,16 R²=0,93

Goal: validate and apply on a larger scale

(14)

Probing VEGETATION Conference – Antwerpen 4-5 July 2013

Ph.D Thesis of Vanessa Drolon Since Janvier 2013

(thanks to CLS/VITO)

•Improve & validate in the alpine massif

∆ Glaciers Mass=f (snow coverage altitude)

•Move this relationship towards other

regions (Andin, Rockies, high latitudes…)

(15)

In situ measurements of Glacier Mass Balance available in the Alps

15

50 glaciers from 1996 to 2008 (Huss et al 2010)

46 glaciers from 1949 to 2010 (World Glaciers Monitoring Service)

(16)

Probing VEGETATION Conference – Antwerpen 4-5 July 2013

Validation in the alpes

16

Average NDSI (1998-2012) S10 NDSI (1998->2012)

(17)

Clouds filtering

(VITO+ CESBIO)

08/07/2013 17

(18)

Probing VEGETATION Conference – Antwerpen 4-5 July 2013

Available in situ measurements of Alpine Glaciers Mass Balance

50 glaciers from 1996 to 2008 (Huss et al 2010)

46 glaciers de 1949 to 2010 (World Glaciers Monitoring Service)

18

(19)

The Albigna glacier 2160-3340 m

(46.3 N, 9.6 E) 5.93 km²

19

-5000 -4000 -3000 -2000 -1000 0 1000 2000 3000 4000

GMB in mm water equivalent

Albigna's winter, summer and annual Mass Balance evolution

Winter Summer Annual

NDSI Time series (9x9 pixels)

(20)

Probing VEGETATION Conference – Antwerpen 4-5 July 2013

Relationship

Mass balance=F(Altitude) ROI size 15kmx15km

(NDSI * )=0.15

20

y = -0,0040626x + 7,1749 R² = 0,8345

-2500 -2000 -1500 -1000 -500 0 500 1000 1500

0 500 1000 1500 2000 2500

Snow Line Altitude (m)

GMB ( mm water equivalent)

(21)

Probing VEGETATION Conference – Antwerpen 4-5 July 2013

Seuil R² Equation NDSI

0 0.545499 9.912727 - 0.003083* alt 0,05 0.735725 18.047213 - 0.005291* alt 0,1 0.649704 11.896153 - 0.003414* alt 0,15 0.801422 27.767681 - 0.007504* alt 0,2 0.794974 13.644640 - 0.003631* alt 0,25 0.934395 14.236548 - 0.003662* alt 0,3 0.925652 12.406763 - 0.003131* alt

Seuil R² Equation NDSI

0 0.436324 2.480335 - 0.002171* alt 0,05 0.670659 7.035954 - 0.004299* alt 0,1 0.725319 6.885831 - 0.004043* alt 0,15 0.83446 7.174913 - 0.004063* alt 0,2 0.45393 9.45282 - 0.004892* alt 0,25 0.626545 13.32955 - 0.006368* alt 0,3 0.558737 11.55336 - 0.005379* alt

Equation de la droite de régression y = -0,0036x + 14,16 Coefficient de corrélation R2 = 0,9346

-2,00 -1,50 -1,00 -0,50 0,00 0,50

3700 3800 3900 4000 4100 4200 4300 4400

Altitude (en mètre)

Bilan de masse annuel (en mètre d'eau)

BMG = -0,0041*alti + 7,175 R² = 0,83

-2500 -2000 -1500 -1000 -500 0 500 1000 1500

0 500 1000 1500 2000 2500

Snow Line Altitude (m)

GM B ( mm w at er e qu .)

BMG = -0,0036*alti+14,16 R2=0.93

Chhota Shigri

alt max: 6263m; taille: 16,3 km²;

orientation: Nord

Albigna

alt:2160-3340 m, taille: 4,69,

orientation: Nord

(22)

Probing VEGETATION Conference – Antwerpen 4-5 July 2013

Short term work ahead (2013)

•Making use of our alpine in situ GMB data base:

- Altitude, size, orientation - Season

- NDSI threshold criteria - Other ?

•Change the S10 compositing criteria for snow (MVC not optimized for snow) … clouds filtering

Probing VEGETATION Conference – Antwerpen 3-4July 2013

(23)

1. Apply the validated relationship to other Glaciers in the world (Himalaya, Andes, Rockies, Greenland)

2. Study the VGT/PROBAV overlap until S3 and/or Probav2

NDSI climato

Probing VEGETATION Conference – Antwerpen 3-4July 2013

Work ahead 2014

(24)

Probing VEGETATION Conference – Antwerpen 4-5 July 2013

Copyrights E. Berthier

Thank you

References

Related documents

MindWorks | Team 5 : Ann Ferracane, Sachin Jain, Richard Joltes, Kit Miller, Samir Sanghavi ISMT E-200 | Capstone Seminar in Enterprise Systems.. Harvard University

This study looks at the effect of the introduction of price competition into the Dutch hospital market and examines whether its impact on the quality of hip replacements

Impacts of landuse/landcover changes coupled with climate variability are well felt in areas of pristine environments like the dominantly high rainforest covered

These sections borrow from Berbel, Garrido and Calatrava (2007), but have been summarised and.. Resource costs are the most difficult to quantify. Usual notions of resource

 Social Studies 10-1, 20-1 and 30-1 are designed for those students who are seeking a high school diploma and who will pursue post-secondary studies at the college

The objective of Perception Task 1 was to understand if the respondent could identify lexical stress in the speech of Malaysian speakers. The objective of Perception Task 2 was

• Staffing of elementary schools and high school of ZEP according to the special needs of schools (increase of Assistant Headmasters number, placement of experienced personnel).

The students joining the modules in HPC are expected to use prior knowledge acquired during their undergraduate studies in technologies that include computer system architecture,