Transferability of an ensemble downscaling method across ...Transferability of an ensemble downscaling method across time periods and predictor datasets Sabine Radanovics1, Laurie

Transferability of an ensembledownscaling method across timeperiods and predictor datasets

Sabine Radanovics1, Laurie Caillouet1,Jean-Philippe Vidal1, Eric Sauquet1, GuillaumeBontron2, Aurélien Ben Daoud2, and BenjaminGraff2

1Irstea, Hydrology-Hydraulics Research Unit (UR HHLY)2Compagnie Nationale du Rhône (CNR)

17 October 2017 – MISTRALS workshop

1 / 16www.irstea.fr

Outline

1. Research questions

2. SANDHY

3. Design of experiments

4. Results

5. Perspectives & follow-up works

2 / 16

Research questionsTransferability of Statistical Downscaling Methods (SDMs)

For all SDMs

Is a method calibrated in apresent-day period transferableto a future period?

For Perfect Prognosis methods

Is a method calibrated betweenpredictors from a globalreanalysis and local predictandstransferable to predictors fromGCMs?

This work addresses preliminary and necessary questions:

Is a method calibrated in apresent-day period transferableto a another period?

Is a method calibrated betweenpredictors from a globalreanalysis and local predictandstransferable to predictors fromanother reanalysis?

3 / 16

SANDHYEnsemble analogue downscaling approach

4 / 16

SANDHYStepwise ANalogue Downscaling method for HYdrology

Analogy onVertical velocity

5000 analogues

170 analogues

70 analogues

25 analogues

Analogy on temperature

Globalreanalysis

Analogy on geopotential

Analogy onhumidity

Localoptimisation

SANDHY

Specificities

Dedicated to precipitation as predictand

Stepwise refinement of the pool of analogues (Ben Daoud et al.,2011, 2016)

Local optimisation of geopotential spatial domains for individualclimatically homogeneous zones (Radanovics et al., 2013)

5 / 16

SANDHYWhere to look for analogy?

Center of geopotential domains

40

44

48

−5 0 5 10 15

Longitude

Latit

ude

40

44

48

−5 0 5 10 15

Longitude

Latit

ude

ERA40 20CR

500 1000 500 1000

1800

2100

2400

2700

X Lambert (km)

Y L

ambe

rt (

km)

6 / 16

Design of experiments

Fixed features

Optimisation period:1982-2002

Archive period ofanalogue dates:1982-2002

Sensitivity experiments

Reanalysis used for optimisation

ERA40 (Uppala et al., 2005)20CR (Compo et al., 2011)

Reanalysis used for analogue archive

ERA4020CR

Period used for simulation

1982-20021958-1978

Details on experiments

Calibration and daily simulation with SANDHY for each of the 608climatically homogeneous zones covering France in the Safrannear-surface reanalysis (Vidal et al., 2010)

8 experiments × 20 yrs × 608 zones × 25 analogues: ∼110M values

7 / 16


Fixed features

Optimisation period:1982-2002

Archive period ofanalogue dates:1982-2002

Sensitivity experiments

Reanalysis used for optimisation

ERA40 (Uppala et al., 2005)20CR (Compo et al., 2011)

Reanalysis used for analogue archive

ERA4020CR

Period used for simulation

1982-20021958-1978

Details on experiments

Calibration and daily simulation with SANDHY for each of the 608climatically homogeneous zones covering France in the Safrannear-surface reanalysis (Vidal et al., 2010)

8 experiments × 20 yrs × 608 zones × 25 analogues: ∼110M values7 / 16


Reference experiment

ERA40 predictors

ERA40 archive of predictors

1982-2002 simulation

Performance analysis

Performance on precipitation simulation

Ensemble error measure: CRPS (Matheson and Winkler, 1976)

Change in CRPS with respect to the reference experiment

Individual effects in a Analysis of Variance

1. Changing the reanalysis used for optimisation

2. Changing the reanalysis used for analogue archive

3. Changing the period used for simulation

8 / 16

ResultsReference performance

Error

1800

2100

2400

2700

250 500 750 1000 1250

X Lambert (km)

Y L

ambe

rt (

km)

1.0

1.5

2.0

2.5

CRPS (mm)

Skill Score(improvement w/r climatology)

1800

2100

2400

2700

250 500 750 1000 1250

X Lambert (km)

Y L

ambe

rt (

km)

0.0

0.1

0.2

0.3

0.4

0.5CRPSS

9 / 16

ResultsTransferability

Changing the reanalysisused for optimisation

Changing the reanalysisused for analogue archive

Changing the periodused for simulation

0

20

40

Changein CRPS(%)

1. Negligible sensitivity to the definition of predictor domains

2. Performance loss when using analogues from the 20CR archive

3. Reasonably low error in temporal transferability, but highly spatiallyvariable

10 / 16

PerspectivesOn transferability issues

Loss using analogue situations from 20CR

Hypothesis: lower quality of 20CR humidity due to lack ofobservational constraints

Undergoing experiments with hybrid predictors:

Humidity predictors from ERA40All other predictors from 20CR

Temporal transferability

Higher loss in areas with high interannual variability

Hypothesis: too short an archive period of analogues

11 / 16

Follow-up worksOn the downscaling method

From SANDHY to SCOPE (Caillouet et al., 2016, 2017)

Improvement of the local optimization of predictor spatial domains

Further refinement of the pool of analogues: additional predictors(T2m & SST) and correction for dry bias

Reorganisation of analogues across France to add spatial coherence

Reconstruction of historical hydroclimate variability from 20CR

Use of a 50-year archive period

SCOPE Climate: 25-member ensemble reconstruction of daily 8kmprecipitation and temperature fields over France: 1871-2012(Caillouet et al., 2016, 2017) → Poster in the Hall: C2Used as forcings to reconstruct ensemble daily streamflow over morethan 600 near-natural catchments over 1871-2012 (SCOPE Hydro),and to derive a historical catalogue of spatio-temporal extremelow-flow events (Caillouet et al., 2017)

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PerspectivesExamples in the Mediterranean from SCOPE Climate & SCOPE Hydro

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member 21 member 22 member 23 member 24 member 25

member 14 member 15 member 16 member 17 member 18 member 19 member 20

member 7 member 8 member 9 member 10 member 11 member 12 member 13

Obs member 1 member 2 member 3 member 4 member 5 member 6

100

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Precip (mm)

Precipitation in South-East France on the 21 September 1890 that led to a

record flood of the Ardèche river.

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PerspectivesExamples in the Mediterranean from SCOPE Climate & SCOPE Hydro

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Duration − 1878

Duration − 1893

Duration − 1976

Duration − 1990

Return period of duration (years)

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< 2 2−5 5−10

10−20 20−50 > 50

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Severity − 1878

Severity − 1893

Severity − 1976

Severity − 1990

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●1989−06−16

Start date − 1878

Start date − 1893

Start date − 1976

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Number of days

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Duration − 1878

Duration − 1893

Duration − 1976

Duration − 1990

Return period of duration (years)

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Documents

Transferability of an ensemble downscaling method across ...Transferability of an ensemble downscaling method across time periods and predictor datasets Sabine Radanovics1, Laurie