OESCHGER CENTRECLIMATE CHANGE RESEARCH

UNIVERSITÄTBERN

Exploring nearly one-in-a-millennium scenariosof extreme rainfall through dynamicallydownscaling palaeoclimatic simulations

Juan José Gómez-Navarro, Christoph Raible,Sandro Blumer and Olivia Martius

September 1, 2015

Outline

OESCHGER CENTRECLIMATE CHANGE RESEARCH

UNIVERSITÄTBERN

1 Motivation and modelling framework

2 Downscaling results and bias correction

3 Caveats and outlook

J.J. Gómez-Navarro 〉 5th European Windstorm Workshop 〉 31 Aug. – 2 Sep. 2015 Bern

Outline

OESCHGER CENTRECLIMATE CHANGE RESEARCH

UNIVERSITÄTBERN

1 Motivation and modelling framework

2 Downscaling results and bias correction

3 Caveats and outlook

J.J. Gómez-Navarro 〉 5th European Windstorm Workshop 〉 31 Aug. – 2 Sep. 2015 Bern

Aim of the project

OESCHGER CENTRECLIMATE CHANGE RESEARCH

UNIVERSITÄTBERN

Studying extremes is important...

• Produce severe damages (relevant to insurancecompanies)

• The fingerprint of Climate Change in extremes isespecially relevant for policy makers

... but challengeling

• Infrequent by definition

• Requires having long series we do not have

• We try to do something in this respect (withmodels!)

J.J. Gómez-Navarro 〉 5th European Windstorm Workshop 〉 31 Aug. – 2 Sep. 2015 Bern

Aim of the project

OESCHGER CENTRECLIMATE CHANGE RESEARCH

UNIVERSITÄTBERN

Studying extremes is important...

• Produce severe damages (relevant to insurancecompanies)

• The fingerprint of Climate Change in extremes isespecially relevant for policy makers

... but challengeling

• Infrequent by definition

• Requires having long series we do not have

• We try to do something in this respect (withmodels!)

J.J. Gómez-Navarro 〉 5th European Windstorm Workshop 〉 31 Aug. – 2 Sep. 2015 Bern

Model chain

OESCHGER CENTRECLIMATE CHANGE RESEARCH

UNIVERSITÄTBERN

GCMCESM

0 15 30 45 60 75 90 105 120 135 150prec

mm

RCMWRF

BIAS CORRECTION

HydrologyPREVAH

1D-HydrailicBASEMENT-

ETH

J.J. Gómez-Navarro 〉 5th European Windstorm Workshop 〉 31 Aug. – 2 Sep. 2015 Bern

Model chain

OESCHGER CENTRECLIMATE CHANGE RESEARCH

UNIVERSITÄTBERN

GCMCESM

RCMWRF

BIAS CORRECTION

HydrologyPREVAH

1D-HydrailicBASEMENT-

ETH

J.J. Gómez-Navarro 〉 5th European Windstorm Workshop 〉 31 Aug. – 2 Sep. 2015 Bern

Model chain

OESCHGER CENTRECLIMATE CHANGE RESEARCH

UNIVERSITÄTBERN

GCMCESM

RCMWRF

BIAS CORRECTION

0

5

10

15

20

25

30

35

40

45

50

0 5 10 15 20 25 30

ER

AIN

CESM

QQ plot JJA 1-day

HydrologyPREVAH

1D-HydrailicBASEMENT-

ETH

J.J. Gómez-Navarro 〉 5th European Windstorm Workshop 〉 31 Aug. – 2 Sep. 2015 Bern

Model chain

OESCHGER CENTRECLIMATE CHANGE RESEARCH

UNIVERSITÄTBERN

GCMCESM

RCMWRF

BIAS CORRECTION

HydrologyPREVAH

1D-HydrailicBASEMENT-

ETH

J.J. Gómez-Navarro 〉 5th European Windstorm Workshop 〉 31 Aug. – 2 Sep. 2015 Bern

Model chain

OESCHGER CENTRECLIMATE CHANGE RESEARCH

UNIVERSITÄTBERN

GCMCESM

RCMWRF

BIAS CORRECTION

HydrologyPREVAH

1D-HydrailicBASEMENT-

ETH

J.J. Gómez-Navarro 〉 5th European Windstorm Workshop 〉 31 Aug. – 2 Sep. 2015 Bern

Details of the climate component

OESCHGER CENTRECLIMATE CHANGE RESEARCH

UNIVERSITÄTBERN

GCM

• CESM run in the University of Bern

• Transient simulation: fully coupled atmosphere &ocean driven by external forcings

• 850–2010 plus control run

RCM

• Weather Research and Forecasting model (WRF)

• Four nested domains down to 2 km

• Convecting-resolving resolution: no convectionparameterization

J.J. Gómez-Navarro 〉 5th European Windstorm Workshop 〉 31 Aug. – 2 Sep. 2015 Bern

Details of the climate component

OESCHGER CENTRECLIMATE CHANGE RESEARCH

UNIVERSITÄTBERN

GCM

• CESM run in the University of Bern

• Transient simulation: fully coupled atmosphere &ocean driven by external forcings

• 850–2010 plus control run

RCM

• Weather Research and Forecasting model (WRF)

• Four nested domains down to 2 km

• Convecting-resolving resolution: no convectionparameterization

J.J. Gómez-Navarro 〉 5th European Windstorm Workshop 〉 31 Aug. – 2 Sep. 2015 Bern

Outline

OESCHGER CENTRECLIMATE CHANGE RESEARCH

UNIVERSITÄTBERN

1 Motivation and modelling framework

2 Downscaling results and bias correction

3 Caveats and outlook

J.J. Gómez-Navarro 〉 5th European Windstorm Workshop 〉 31 Aug. – 2 Sep. 2015 Bern

Picking dates

OESCHGER CENTRECLIMATE CHANGE RESEARCH

UNIVERSITÄTBERN

The problem

• It is NOT possible to run 1000 years of 2km-resolution simulation!• Alternative: select "interesting dates" a priori withinthe GCM... but how?

Solution #0

• A region over Switzerland is selected (12 grid points inthe GCM)

• The precipitation over this region is used to selectevents

• Simple, but ignores the drivers of precipitation

J.J. Gómez-Navarro 〉 5th European Windstorm Workshop 〉 31 Aug. – 2 Sep. 2015 Bern

Picking dates

OESCHGER CENTRECLIMATE CHANGE RESEARCH

UNIVERSITÄTBERN

The problem

• It is NOT possible to run 1000 years of 2km-resolution simulation!• Alternative: select "interesting dates" a priori withinthe GCM... but how?

Solution #0

• A region over Switzerland is selected (12 grid points inthe GCM)

• The precipitation over this region is used to selectevents

• Simple, but ignores the drivers of precipitation

J.J. Gómez-Navarro 〉 5th European Windstorm Workshop 〉 31 Aug. – 2 Sep. 2015 Bern

Criterion in detail

OESCHGER CENTRECLIMATE CHANGE RESEARCH

UNIVERSITÄTBERN

Algorithm

• The 4 most rainy days are selected

• The same is repeated for 2, 3, 5 and 10 windows

• Independently for each season (to minimise systematicerrors arising from GCM biases)

This results in 4× (1+ 2+ 3+ 5+ 10)× 4=336 simulated days,which is feasible

J.J. Gómez-Navarro 〉 5th European Windstorm Workshop 〉 31 Aug. – 2 Sep. 2015 Bern

Criterion in detail

OESCHGER CENTRECLIMATE CHANGE RESEARCH

UNIVERSITÄTBERN

Algorithm

• The 4 most rainy days are selected

• The same is repeated for 2, 3, 5 and 10 windows

• Independently for each season (to minimise systematicerrors arising from GCM biases)

This results in 4× (1+ 2+ 3+ 5+ 10)× 4=336 simulated days,which is feasible

J.J. Gómez-Navarro 〉 5th European Windstorm Workshop 〉 31 Aug. – 2 Sep. 2015 Bern

Criterion in detail

OESCHGER CENTRECLIMATE CHANGE RESEARCH

UNIVERSITÄTBERN

Algorithm

• The 4 most rainy days are selected

• The same is repeated for 2, 3, 5 and 10 windows

• Independently for each season (to minimise systematicerrors arising from GCM biases)

This results in 4× (1+ 2+ 3+ 5+ 10)× 4=336 simulated days,which is feasible

J.J. Gómez-Navarro 〉 5th European Windstorm Workshop 〉 31 Aug. – 2 Sep. 2015 Bern

Criterion in detail

OESCHGER CENTRECLIMATE CHANGE RESEARCH

UNIVERSITÄTBERN

Algorithm

• The 4 most rainy days are selected

• The same is repeated for 2, 3, 5 and 10 windows

• Independently for each season (to minimise systematicerrors arising from GCM biases)

This results in 4× (1+ 2+ 3+ 5+ 10)× 4=336 simulated days,which is feasible

J.J. Gómez-Navarro 〉 5th European Windstorm Workshop 〉 31 Aug. – 2 Sep. 2015 Bern

Downscaling Results

OESCHGER CENTRECLIMATE CHANGE RESEARCH

UNIVERSITÄTBERN

10 W

10 W

0

0

10 E

10 E

20 E

20 E 30 E

35 N 35 N

40 N 40 N

45 N 45 N

50 N 50 N

55 N 55 N

6 E

6 E

8 E

8 E

10 E

10 E

12 E

12 E

14 E

14 E

44 N 44 N

45 N 45 N

46 N 46 N

47 N 47 N

48 N

0

15

30

45

60

75

90

105

120

135

150

prec (mm)

0

0

10 E

10 E

20 E

20 E

40 N 40 N

45 N 45 N

50 N 50 N

3 E

3 E

6 E

6 E

9 E

9 E

12 E

12 E

15 E

15 E

42 N 42 N

45 N 45 N

48 N 48 N

51 N 51 N

10 W

10 W

0

0

10 E

10 E

20 E

20 E 30 E

35 N 35 N

40 N 40 N

45 N 45 N

50 N 50 N

55 N 55 N

GCM

Domain 1 (54 km) Domain 2 (18 km)

Domain 3 (6 km)

Domain 4 (2 km)

J.J. Gómez-Navarro 〉 5th European Windstorm Workshop 〉 31 Aug. – 2 Sep. 2015 Bern

Bias correction: generalities

OESCHGER CENTRECLIMATE CHANGE RESEARCH

UNIVERSITÄTBERN

In some applications, biases are not critical (e.g. delta approach),BUT as part of the model chain, biases are crucial (non linearprocesses)

WRF-ERAinWRF-CESM

J.J. Gómez-Navarro 〉 5th European Windstorm Workshop 〉 31 Aug. – 2 Sep. 2015 Bern

Bias correction: generalities

OESCHGER CENTRECLIMATE CHANGE RESEARCH

UNIVERSITÄTBERN

In some applications, biases are not critical (e.g. delta approach),BUT as part of the model chain, biases are crucial (non linearprocesses)

ClimatesimulationClimate

simulation climateObserved

WRF-ERAinWRF-CESM

J.J. Gómez-Navarro 〉 5th European Windstorm Workshop 〉 31 Aug. – 2 Sep. 2015 Bern

Bias correction: generalities

OESCHGER CENTRECLIMATE CHANGE RESEARCH

UNIVERSITÄTBERN

In some applications, biases are not critical (e.g. delta approach),BUT as part of the model chain, biases are crucial (non linearprocesses)

ClimatesimulationClimate

simulation climateObserved

Transferfunction

WRF-ERAinWRF-CESM

J.J. Gómez-Navarro 〉 5th European Windstorm Workshop 〉 31 Aug. – 2 Sep. 2015 Bern

Bias correction: generalities

OESCHGER CENTRECLIMATE CHANGE RESEARCH

UNIVERSITÄTBERN

In some applications, biases are not critical (e.g. delta approach),BUT as part of the model chain, biases are crucial (non linearprocesses)

ClimatesimulationClimate

simulation climateObserved

Transferfunction

Simulatedextreme

"Actual"extreme

WRF-ERAinWRF-CESM

J.J. Gómez-Navarro 〉 5th European Windstorm Workshop 〉 31 Aug. – 2 Sep. 2015 Bern

Bias correction: generalities

OESCHGER CENTRECLIMATE CHANGE RESEARCH

UNIVERSITÄTBERN

In some applications, biases are not critical (e.g. delta approach),BUT as part of the model chain, biases are crucial (non linearprocesses)

ClimatesimulationClimate

simulation climateObserved

Transferfunction

Simulatedextreme

"Actual"extreme

WRF-ERAinWRF-CESM

J.J. Gómez-Navarro 〉 5th European Windstorm Workshop 〉 31 Aug. – 2 Sep. 2015 Bern

Bias correction: examples

OESCHGER CENTRECLIMATE CHANGE RESEARCH

UNIVERSITÄTBERN

0.00

0.05

0.10

0.15

0.20

0.25

0 5 10 15 20 25 30 35 40 45 50

PD

F

BW

ERACESM

0

10

20

30

40

50

PDF JJA 1-day

prec (mm)

0.00

0.00

0.00

0.01

0.01

0.01

0.01

0.01

0.02

0 20 40 60 80 100 120 140 160

PD

F

BW

0

50

100

150

200

250

ERACESM

PDF DJF 10-day

prec (mm)

J.J. Gómez-Navarro 〉 5th European Windstorm Workshop 〉 31 Aug. – 2 Sep. 2015 Bern

Bias correction: examples

OESCHGER CENTRECLIMATE CHANGE RESEARCH

UNIVERSITÄTBERN

0.00

0.05

0.10

0.15

0.20

0.25

0 5 10 15 20 25 30 35 40 45 50

PD

F

BW

ERACESM

0

10

20

30

40

50

PDF JJA 1-day

prec (mm)

0.00

0.00

0.00

0.01

0.01

0.01

0.01

0.01

0.02

0 20 40 60 80 100 120 140 160

PD

F

BW

0

50

100

150

200

250

ERACESM

PDF DJF 10-day

prec (mm)

J.J. Gómez-Navarro 〉 5th European Windstorm Workshop 〉 31 Aug. – 2 Sep. 2015 Bern

Bias correction: fitting the CDF

OESCHGER CENTRECLIMATE CHANGE RESEARCH

UNIVERSITÄTBERN

0.0001

0.001

0.01

0.1

1

051015202530354045

PD

F

ERACESM

0

10

20

30

40

50

CDF JJA 1-day

PDF = AeB·prec

⇓y︷ ︸︸ ︷

ln(PDF) = lnA+B ·x︷︸︸︷

prec

J.J. Gómez-Navarro 〉 5th European Windstorm Workshop 〉 31 Aug. – 2 Sep. 2015 Bern

Bias correction: fitting the CDF

OESCHGER CENTRECLIMATE CHANGE RESEARCH

UNIVERSITÄTBERN

0.0001

0.001

0.01

0.1

1

051015202530354045

PD

F

ERACESM

0

10

20

30

40

50

CDF JJA 1-day

PDF = AeB·prec

⇓y︷ ︸︸ ︷

ln(PDF) = lnA+B ·x︷︸︸︷

prec

J.J. Gómez-Navarro 〉 5th European Windstorm Workshop 〉 31 Aug. – 2 Sep. 2015 Bern

Bias correction: fitting the CDF

OESCHGER CENTRECLIMATE CHANGE RESEARCH

UNIVERSITÄTBERN

0.0001

0.001

0.01

0.1

1

051015202530354045

PD

F

ERACESM

0

10

20

30

40

50

CDF JJA 1-day

PDF = AeB·prec

⇓y︷ ︸︸ ︷

ln(PDF) = lnA+B ·x︷︸︸︷

prec

J.J. Gómez-Navarro 〉 5th European Windstorm Workshop 〉 31 Aug. – 2 Sep. 2015 Bern

Bias correction: Quantile mapping

OESCHGER CENTRECLIMATE CHANGE RESEARCH

UNIVERSITÄTBERN

0

5

10

15

20

25

30

35

40

45

50

0 5 10 15 20 25 30

ER

AIN

CESM

QQ plot JJA 1-day

J.J. Gómez-Navarro 〉 5th European Windstorm Workshop 〉 31 Aug. – 2 Sep. 2015 Bern

Bias correction: Results

OESCHGER CENTRECLIMATE CHANGE RESEARCH

UNIVERSITÄTBERN

Lin. Fit Raw sim. Q. map

0 15 30 45 60 75 90 105 120 135 150

prec (mm)

DJF 10-dayaggregated

J.J. Gómez-Navarro 〉 5th European Windstorm Workshop 〉 31 Aug. – 2 Sep. 2015 Bern

Outline

OESCHGER CENTRECLIMATE CHANGE RESEARCH

UNIVERSITÄTBERN

1 Motivation and modelling framework

2 Downscaling results and bias correction

3 Caveats and outlook

J.J. Gómez-Navarro 〉 5th European Windstorm Workshop 〉 31 Aug. – 2 Sep. 2015 Bern

Limitations we are aware of

OESCHGER CENTRECLIMATE CHANGE RESEARCH

UNIVERSITÄTBERN

• The dataset used to remove biases is not itself unbiased ⇒use observations instead of model data

• The number of cases is limited ⇒ downscale more cases

• Bias not systematic, but seasonal- and event-dependent ⇒seasonal analysis

• We do not search for the physical mechanisms underlayingevents ⇒ split the analysis for each type of event (e.gVb-events,...)???

J.J. Gómez-Navarro 〉 5th European Windstorm Workshop 〉 31 Aug. – 2 Sep. 2015 Bern

Limitations we are aware of

OESCHGER CENTRECLIMATE CHANGE RESEARCH

UNIVERSITÄTBERN

• The dataset used to remove biases is not itself unbiased ⇒use observations instead of model data

• The number of cases is limited ⇒ downscale more cases

• Bias not systematic, but seasonal- and event-dependent ⇒seasonal analysis

• We do not search for the physical mechanisms underlayingevents ⇒ split the analysis for each type of event (e.gVb-events,...)???

J.J. Gómez-Navarro 〉 5th European Windstorm Workshop 〉 31 Aug. – 2 Sep. 2015 Bern

Limitations we are aware of

OESCHGER CENTRECLIMATE CHANGE RESEARCH

UNIVERSITÄTBERN

• The dataset used to remove biases is not itself unbiased ⇒use observations instead of model data

• The number of cases is limited ⇒ downscale more cases

• Bias not systematic, but seasonal- and event-dependent ⇒seasonal analysis

• We do not search for the physical mechanisms underlayingevents ⇒ split the analysis for each type of event (e.gVb-events,...)???

J.J. Gómez-Navarro 〉 5th European Windstorm Workshop 〉 31 Aug. – 2 Sep. 2015 Bern

Limitations we are aware of

OESCHGER CENTRECLIMATE CHANGE RESEARCH

UNIVERSITÄTBERN

• The dataset used to remove biases is not itself unbiased ⇒use observations instead of model data

• The number of cases is limited ⇒ downscale more cases

• Bias not systematic, but seasonal- and event-dependent ⇒seasonal analysis

• We do not search for the physical mechanisms underlayingevents ⇒ split the analysis for each type of event (e.gVb-events,...)???

J.J. Gómez-Navarro 〉 5th European Windstorm Workshop 〉 31 Aug. – 2 Sep. 2015 Bern

How extreme are the "extremes"we pick?

OESCHGER CENTRECLIMATE CHANGE RESEARCH

UNIVERSITÄTBERN

0.00

0.02

0.04

0.06

0.08

0.10

0.12

0 10 20 30 40 50 60

PD

F

0102030405060

PDF DJF 1-day

prec (mm)

ERACESM

The "extremes" we previously selected within the GCM are notso extreme once downscaled

J.J. Gómez-Navarro 〉 5th European Windstorm Workshop 〉 31 Aug. – 2 Sep. 2015 Bern

How extreme are the "extremes"we pick?

OESCHGER CENTRECLIMATE CHANGE RESEARCH

UNIVERSITÄTBERN

0.00

0.02

0.04

0.06

0.08

0.10

0.12

0 10 20 30 40 50 60

PD

F

0102030405060

PDF DJF 1-day

prec (mm)

ERACESM

Statistical d

ownscaling?

The "extremes" we previously selected within the GCM are notso extreme once downscaled

J.J. Gómez-Navarro 〉 5th European Windstorm Workshop 〉 31 Aug. – 2 Sep. 2015 Bern

Conclusions

OESCHGER CENTRECLIMATE CHANGE RESEARCH

UNIVERSITÄTBERN

• Novel methodology that allows to simulate unprecedented,yet physically based extreme situations

• Although model data, the climate information is bias-free

• Most technical challenges (in the climate models, but andalso in the hydrological models) already addressed

• Further research is required to consistently remove biases ofunprecedented events

• The selection of the dates needs to be considered morecarefully, and more robust methodology should be developed

J.J. Gómez-Navarro 〉 5th European Windstorm Workshop 〉 31 Aug. – 2 Sep. 2015 Bern

Methodological uncertainties toaddress

OESCHGER CENTRECLIMATE CHANGE RESEARCH

UNIVERSITÄTBERN

• The CDFs not always line up

• Quantile mapping is ill-defined for extremely infrequentevents

• Should the transfer function be calibrated for each gridpoint? Separately for each region (regionalisation)?

0.0001

0.001

0.01

0.1

1

020406080100120140

CD

F

050100150200250

CDF DJF 10-day

ERACESM

prec. (mm)

0

10

20

30

40

50

60

70

80

90

100

0 10 20 30 40 50 60 70

QQplot JJA 5-day

?

ER

AIN

CESM

J.J. Gómez-Navarro 〉 5th European Windstorm Workshop 〉 31 Aug. – 2 Sep. 2015 Bern

Methodological uncertainties toaddress

OESCHGER CENTRECLIMATE CHANGE RESEARCH

UNIVERSITÄTBERN

• The CDFs not always line up

• Quantile mapping is ill-defined for extremely infrequentevents

• Should the transfer function be calibrated for each gridpoint? Separately for each region (regionalisation)?

0.0001

0.001

0.01

0.1

1

020406080100120140

CD

F

050100150200250

CDF DJF 10-day

ERACESM

prec. (mm)

0

10

20

30

40

50

60

70

80

90

100

0 10 20 30 40 50 60 70

QQplot JJA 5-day

?

ER

AIN

CESM

J.J. Gómez-Navarro 〉 5th European Windstorm Workshop 〉 31 Aug. – 2 Sep. 2015 Bern

Methodological uncertainties toaddress

OESCHGER CENTRECLIMATE CHANGE RESEARCH

UNIVERSITÄTBERN

• The CDFs not always line up

• Quantile mapping is ill-defined for extremely infrequentevents

• Should the transfer function be calibrated for each gridpoint? Separately for each region (regionalisation)?

0.0001

0.001

0.01

0.1

1

020406080100120140

CD

F

050100150200250

CDF DJF 10-day

ERACESM

prec. (mm)

0

10

20

30

40

50

60

70

80

90

100

0 10 20 30 40 50 60 70

QQplot JJA 5-day

?

ER

AIN

CESM

J.J. Gómez-Navarro 〉 5th European Windstorm Workshop 〉 31 Aug. – 2 Sep. 2015 Bern