Profilo Climatico Locale - Kyoto Club · Profilo Climatico Locale ... ARPA E-R Servizio...

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Profilo Climatico Locale Rodica Tomozeiu Lucio Botarelli [email protected] , [email protected] ARPA E-R Servizio IdroMeteoClima www.arpa.emr.it webinar 20 Marzo 2014

Transcript of Profilo Climatico Locale - Kyoto Club · Profilo Climatico Locale ... ARPA E-R Servizio...

Profilo Climatico Locale

Rodica Tomozeiu Lucio Botarelli

[email protected], [email protected]

ARPA E-R

Servizio IdroMeteoClima www.arpa.emr.it

webinar 20 Marzo 2014

Observed global climate changes

Increase of the global temperature is more significant from the 90‘s

Decrease of precipitation in Europe

-1.5

-1

-0.5

0

0.5

1

1.5

2

2.5

3

3.5

19

60

19

65

19

70

19

75

19

80

19

85

19

90

19

95

20

00

20

05

20

10

An

om

alia

Tm

ed

Anomalia di temperatura media annuale

T_globale

T_Italia

T_Bologna

Anomaly of the yearly mean temperature (vs 1961-1990)

Observed climate variability

(http://www.arpa.emr.it/sim/?clima)

Precipitation anomaly 1991-2008 vs 1961-1990

Temperature anomaly 1991-2008 vs 1961-1990 Observed climate variability at regional level

Observed climate variability at regional level

-400

-300

-200

-100

0

100

200

300

400

1962

1964

1966

1968

1970

1972

1974

1976

1978

1980

1982

1984

1986

1988

1990

1992

1994

1996

1998

2000

2002

2004

2006

2008

2010

2012

an

om

ali

a [

mm

]

anni Trend= -16mm/10 years

Yearly precipitation (deviation from the avarage 1961-1990) E-R regional mean

Observed climate variability at regional level

-400,0

-300,0

-200,0

-100,0

0,0

100,0

200,0

300,0

400,0

19

61

19

63

19

65

19

67

19

69

19

71

19

73

19

75

19

77

19

79

19

81

19

83

19

85

19

87

19

89

19

91

19

93

19

95

19

97

19

99

20

01

20

03

20

05

20

07

20

09

20

11

20

13

mm

anni

Andamento BIC medio annuale su Emilia-Romagna Yearly climatic water balance (E-R region)

Observed climate variability at regional level

strongest signal during summer -1,00

-0,50

0,00

0,50

1,00

1,50

2,00

19

61

19

63

19

65

19

67

19

69

19

71

19

73

19

75

19

77

19

79

19

81

19

83

19

85

19

87

19

89

19

91

19

93

19

95

19

97

19

99

20

01

20

03

20

05

20

07

20

09

20

11

20

13

C

°

anni

Scarto medio annuale della Tmed in Emilia-Romagna clima di riferimento 1961-1990

Anomaly of summer Tmax (JJA) E-R regional mean

Increase of 0,5°C/10 years

(from 1986 always over mean climate reference value)

Temperatura massima S. P. Capofiume (pianura BO)

20

22.5

25

27.5

30

32.5

35

37.5

40

01/06/1

2

06/06/1

2

11/06/1

2

16/06/1

2

21/06/1

2

26/06/1

2

01/07/1

2

06/07/1

2

11/07/1

2

16/07/1

2

21/07/1

2

26/07/1

2

31/07/1

2

05/08/1

2

10/08/1

2

15/08/1

2

20/08/1

2

25/08/1

2

30/08/1

2

giorni

°C

Tmax2012

Tmax2003

Tmax clima giugno

Tmax clima luglio

Tmax clima agosto

Heat waves (>35°C) summer 2012 vs summer 2003 (regional central plan)

Observed climate variability

Progressive decrease of the number of rainy days since late 90s‘

2012

Moving avarage on 5 years

frequency of rainy days during spring-summer (regional central plan)

Observed climate variability

Consecutive dry days, summer 2012

Consecutive dry days, summer 2003

Observed climate variability at regional level

Summer climatic water balance 2012 vs 2003

Observed climate variability at regional level

Soil humidity

2003 2007

2012

Observed climate variability at regional level

decrease of air relative humidity

Mann-Kendall test significant

Relative humidity (%, year)

summer trend 1987-2012

Observed climate variability at regional level

NDVI

Observed climate variability at regional level

Extending seasonal (warmer autumns)

Advance in seasonality (early spring)

Longer growing season (limited by water availability)

Warm winters (2006-2007, 2013-2014)

Observed climate variability

Observed climate variability at regional level

severe rains and floods

heat waves and drought

heavy snowfalls

Increase of extreme events

strong anomalies

Observed climate variability at urban scale

• Decrease of frost days during winter

• Increase of heat waves

• Increase of the consecutive dry days

Ondate di calore (HWD) estive e il valore climatico di riferimento(linea tratteggiata) a

Bologna

0

2

4

6

8

10

12

14

1951 1956 1961 1966 1971 1976 1981 1986 1991 1996 2001 2006 2011

anni

gm

ax

.gio

rni c

on

se

cu

tiv

i

HWD clima_HWD

Winter temporal variability of frost days- bologna

0

10

20

30

40

50

60

1950 1955 1960 1965 1970 1975 1980 1985 1990 1995 2000 2005 2010

Years

No

.of

days

Observed climate variability in Bologna

Heat waves

Frost days

0

10

20

30

40

50

60

1951 1956 1961 1966 1971 1976 1981 1986 1991 1996 2001 2006 2011

gio

rni

anni

Andamento temporale del numero massimo di giorni consecutivi senza precipitazione-stagione estiva, Bologna (periodo 1951-2011)

Consecutive dry days

Aim

Climate change scenarios of

seasonal minimum and maximum temperature

periods 2021-2050 and 2070-2099

Emission scenario A1B

future climate projections

Emission scenarios

future climate projections

Tools:

Global Climate Models (GCM);

Regional Climate models(RCM)

Statistical Models (DS)

Statistical Downscaling (SD): based on the statistical relationship between local climate variables and large scale atmospheric variables.

Regional Climate Models (RCM) or Dynamical Downscaling (DD): nested into the global model

AOGCM

RCM

Developed by

ARPA-SIMC

…from CGCMs to RCMs and SDs

Global Continental

Regional

Local

National

Climate projection from global to local

24

CORDEX, Brussels 4-7 November 2013

information at station (or grid point) level; derive variables not always available from

RCMs/GCM (i.e. extremes); SD is simple and computationally

inexpensive.

Strengths

Weakness

need long and homogeneous observational time series for fitting and validating the statistical relationship;

link between predictors and predictands have to be stable in time…

Statistical downscaling

Solution ?

CCAReg applied to the GCMs

Ensemble Mean (EM)

a) GLOBAL EMISSION SCENARIO

b) GENERAL CIRCULATION MODELS

c) STATISTICAL DOWNSCALING MODELS

d) IMPACT MODELS

Uncertainty: how to manage it ?

PDFs of climate change projections of multi-model ensemble mean (EM)

Tmin

Tmax

DJF

DJF

Climate projections: temperature winter (DJF) Tmin and Tmax in Northern Italy

2021-2050

Tmin

Tmax

Note: warming in all seasons with mean values up to 1.8°C (summer) significant shits in the tails of the distributions

…other seasons 2021-2050

Tmin

Tmax

Note: Peak of warming during summer

All the seasons 2070-2099

Seasonal observational data from 75 stations, over Northern Italy (source (http://www.scia.sinanet.apat.it/);

Daily minimum and maximum temperature from 25 observational stations in Emilia-Romagna region

Period: 1960-2002

Data

30

DTmin_DJF (°C) DTmax_JJA(°C)

2021-2050

2070-2099

DTmin_DJF(°C) DTmax_JJA (°C)

Spatial patterns of projected changes in temperature EM 2021-2050 and 2070-2099, A1B

Projected changes of seasonal frost days (EM) and Ice days 2021-2050 and

2070-2099

Projected changes of seasonal number of frost days and ice days, 2021-2050 and

2070-2099

What about “cold extremes” in Emilia-Romagna?

Conclusions

significant increases are projected to occur in minimum and maximum temperature over Northern Italy in all seasons, during the period 2021-2050. The Ensemble Mean computed using all runs (8 runs for each season) projects for each season, a change in the mean of the PDFs of minimum and maximum temperature around 1.5- 2°C over N-Italy;

the magnitude of changes is greater to the end of the century, namely for the period 2070-2099, when the mean of the distributions of EM showed an increase around 3°C (mean over all the stations) during winter, spring and autumn;

the peak of changes is projected to occur during summer season, for both minimum and maximum temperature, with an increase in the mean around 4°C (mean over the stations from N-Italy), with respect to present climate 1961-1990;

the warming is projected to be more intense in the Po Valley, especially to the end of the century;

the lower and upper tail of the PDFs of minimum and maximum temperatures are projected to shift to warmer values, with increases up to 2°C in lower and up to 6°C;

a significant decrease of the seasonal number of frost days and winter ice days is projected to occur over Emilia-Romagna, more intense to the end of the century ( for example during spring could disappear).

Conclusions