COST-733 WG4 The EU-WATCH project

and links between WB4 and COST-733

Christel Prudhomme

WATer and global CHange (WATCH)

WATCH

WB7

Assessing the vulnerability of water resources

WB6

Past, present and future population, LUCC and

water demand

WB2

Extremes and scales of

hydrological events

WB4

Feedbacks in the climate hydrological

system

WB5

21st Century Global water cycle

20th Century Global water cycle

WB3

WB1

Management, training anddissemination

WATCH

WB7

Assessing the vulnerability of water resources

WB6

Past, present and future population, LUCC and

water demand

WB2

Extremes and scales of

hydrological events

WB4

Feedbacks in the climate hydrological

system

WB5

21st Century Global water cycle

20th Century Global water cycle

WB3

WB1

Management, training anddissemination

WB7WB7

Assessing the vulnerability of water resources

WB6

Assessing the vulnerability of water resources

WB6

Past, present and future population, LUCC and

water demand

WB2

Past, present and future population, LUCC and

water demand

WB2

Extremes and scales of

hydrological events

WB4

Extremes and scales of

hydrological events

WB4

Feedbacks in the climate hydrological

system

WB5

Feedbacks in the climate hydrological

system

WB5

21st Century Global water cycle

20th Century Global water cycle

WB3

WB1

21st Century Global water cycle21st Century Global water cycle

20th Century Global water cycle20th Century Global water cycle

WB3

WB1

Management, training anddissemination

WATCH Overview

WP4 : extremes scales of hydrological events

• WP4.1 Detection and attribution of extremes in the 20th century – historical droughts and large-scale floods in the 20th century– analysis and characterisation of those extremes

• WP4.2 Indices and tools to detect extremes and to assess uncertainty propagation– development of indices and tools to detect hydrological extremes– assess the uncertainty in the predicted extremes.

• WP4.3 Likely frequency, severity and scale of future hydrological extremes (21st century)– analysis of drought and large-scale floods based on the global and

regional scenarios for the 21st century (WB3)– comparison with the simulations for the 20th century.

WATCH WB4

• Task 4.1.3 ‘ Investigate processes and phenomena of major floods in 20th century’

• Task 4.1.4 ‘Spatial and temporal scales and severity of floods in 20th century

• Task 4.1.6 ‘Large-scale climate drivers and drought and flood patterns

– Flood catalogue– Antecedent conditions: e.g. soil moisture, rainfall; weather

types

– Are GCMs able to reproduce flood-generating rainfall patterns?

– Are large floods in Europe linked to specific weather types– Are flood-generating weather types well reproduced by

GCMs?

WATCH WB4

Understanding large scale antecedent conditions

• Weather Types/ Classifications from COST– A priori, all classifications

• At present only for Europe: D00

• For each large flood events– Frequency of weather type : preceding day(s)– “ : preceding weeks– Frequency anomaly (i.e. is situation exceptional?)– Blocking situation – blocking catalogue?– Systematic occurrence of some WT ?

– Synoptic situation (from ERA-40?)

• Analysis of WT a-priory linked to large floods, but that did not trigger extreme events: How often? Why?

Flood Catalogue (Polish Academy of Science)

Date Duration Spatial extent

River/basin Characteristics Source

1959 December 2

Dam break flood - hours

France (Malpasset dam, Reyran river valley

Intense-and long lasting precipitation led to dam break and flood

Legrand P. , Les grandes catastrophes (4 tomes), Famot / Francois Beauval, Paris, 1977.

1965 June 15

Hungary Danube at Budapest Rainfall flood

Word Catalogue of Maximum Observed Floods. Roche, M and Rodier, J. A IAHS-ASIH Publications 284 in the IAHS Series of Proceedings and Reports: 1984

1987July 15-20

5 days Italy – Central Alps

Adda basin Heavy rain and rapid melting in alpine glaciers

River Flood Disasters ICSU SC/IDNDR Workshop Koblenz, Germany 1996

Reproduction of antecedent conditions by GCMs

• Using Weather Types/ Classifications codes from COST

– In priority for classifications showing good links with large floods

• Generate classifications from GCM runs of 20th century

• Evaluate results against classifications from re-analysis/CRU – Frequency of Weather Type (monthly/seasonal/annual)– In particular, WT linked to large floods– Frequency of Blocking situation

– Feed back systematic errors to WG1 (20th century GCM simulation)

• Area of interest outside Europe

• Application of classifications to future projections from GCM– Changes in frequency of WT– Potential implication for change of frequency in large

floods

After 18th month from now

• Advise on …

• …Best reference set: ERA-40? – but known deficiencies, e.g. rainfall

• …CRU climatology, but not all atmospheric variables?• …What else?

Thank you