EXTREME EVENTS AS REPRESENTED BY HIGH RESOLUTION CMCC CLIMATE MODELS

Antonella Sanna(2), E. Scoccimarro(1), S. Gualdi(1,2), A. Bellucci(2), M. Montesarchio(2), E. Bucchignani(2,3), A. Navarra(1,2)

(1)INGV - Istituto Nazionale di Geofisica e Vulcanologia (National Institute for Geophysics and Volcanology), Bologna, Italy(2)CMCC - Centro Euro-Mediterraneo per i Cambiamenti Climatici (Euro-Mediterranean Centre for Climate Change), Bologna, Italy

(3)CIRA - Centro Italiano Ricerche Aerospaziali

EXTREME EVENTS

AS REPRESENTED BY HIGH RESOLUTION

CMCC CLIMATE MODELS

AT GLOBAL AND REGIONAL (Euro-Mediterranean) SCALE

“International Conference on Fire Behavior and Risk” Alghero, 5 October 2011

STRUCTURE OF PRESENTATIONSTRUCTURE OF PRESENTATION

•Brief models description

•Indexes definition

•Examples of results

•Model verification

2


MODELS DESCRIPTION

3


SST

CLIMATE MODELS AT CMCC: the global modelCLIMATE MODELS AT CMCC: the global model

4

GLOBAL ATMOSPHERE MODEL (historical+sresa1b prescribed gases and

aerosols)

ECHAM5 T159 ~ 80 km and 31 vert. levels

Roeckner et al. (2003)

MEDITERRANEANSEA MODEL

NEMO/MFS 1/16° ~ 7 km71 vert. levels

Oddo et al. (2009)

GLOBAL OCEAN & SEA-ICE MODEL

OPA/ORCA2 2º ~200 km31 vert, levels

Madec et al. (1998)

LOUVAIN-LA-NEUVE SEA- ICE MODEL

Timmermann et al. (2005)

COUPLER

OASIS 3

Valcke (2006)

Heat, Water and Momentum Flux

SST and Sea-ice

Heat, Water and Momentum Flux

T, S,u, v, η

Coupling between atmosphere and oceans every 2 hours

Coupling between global ocean and Mediterranean Sea every 8 hours


5

CLIMATE MODELS AT CMCC: the regional modelCLIMATE MODELS AT CMCC: the regional model

CMCC-CLM Regional Climate Model (RCM) domain. The horizontal resolution is 14 km. The simulation is forced using 6 hourly data from CMCC-MED over 1970-2100 period.


DATA AVAILABILITYDATA AVAILABILITY

1 Global model (T159, 2ox2o, 1/16°)

2 Regional model ~ 14 km

3 Both climate model simulations cover the period 1970-2100

6

INDEXES FOR EXTREME EVENTS

CHARACTERIZATION

7


TEMPERATURE INDEXES:TEMPERATURE INDEXES:

8

5th Percentile of the daily minimum temperature: TN5P




Seasonal average of minimum daily temperature: MEANTN

5th Percentile of the daily maximum temperature: TX5P




Seasonal average of maximum daily temperature: MEANTX

Total number of consecutive days with maximum daily

temperature exceeding the long term (1971-2100)

90th percentile: WSDI90

Total number of consecutive days with minimum daily

temperature is below the long term (1971-2100)

10th percentile: CSDI10


PRECIPITATION INDEXES:PRECIPITATION INDEXES:

9

95th Percentile of the total daily precipitation: PREC95P




Number of days with daily precipitation exceeding

the long term (1971-2100) 90th percentile : R90N

Number of days with daily precipitation exceeding

the long term (1971-2100) 95th percentile : R95N

Number of days with daily precipitation lower than

the long term (1971-2100) 10th percentile : RL10N

Number of days with daily precipitation lower than

the long term (1971-2100) 5th percentile : RL5N

Averaged daily precipitation over wet days

(wet day defined if precipitation is >= 1[mm/day]): SDII

Maximum (not total) number of consecutive dry days

(dry day defined if precipitation is < 1 [mm/day]): CDD


WIND INDEXES:WIND INDEXES:

10

95th Percentile of the 10 meter wind speed: WI95P

90th Percentile of the 10 meter wind speed: WI90P

Number of days with daily wind speed exceeding

the long term (1971-2100) 90th percentile : WI90N

Number of days with daily wind speed exceeding

the long term (1971-2100) 95th percentile : WI95N

95th Percentile of the 10 meter maximum wind speed: WIMAX95P

90th Percentile of the 10 meter maximum wind speed: WIMAX90P

Number of days with maximum wind speed exceeding

the long term (1971-2100) 90th percentile : WIMAX90N

Number of days with maximum wind speed exceeding

the long term (1971-2100) 95th percentile : WIMAX95N


EXAMPLES OF RESULTS

11


Example: CMCC global model TX90P and trendsExample: CMCC global model TX90P and trends

SUMMER SEASON SUMMER SEASON

12


13

Example: CMCC global model PREC10P and trendsExample: CMCC global model PREC10P and trends



14

Example: CMCC global model WI90P and trendsExample: CMCC global model WI90P and trends



15

Example: CMCC global model WI90N and trendsExample: CMCC global model WI90N and trends



MODEL VERIFICATION

16


OBSERVATIONAL DATASET: SPAIN02OBSERVATIONAL DATASET: SPAIN02

Spain02 is a new high-resolution daily precipitation and maximum and minimum temperatures gridded dataset developed for

peninsular Spain and the Balearic islands. A dense network of ~2500 quality-controlled stations (~250 for temperatures) from the

Spanish Meteorological Agency (AEMET) was selected to build the Spain02 grid with a regular 0.2º (aprox. 20 km) horizonal resolution

spanning the period from 1950 to 2008. The gridding methodology used for precipitation is based on a two step kriging approach

(binary for precipitation outcomes, and ordinary for amounts); in the case of temperatures, thin plane splines are fitted to the monthly

data considering the orography (elevation) and an ordinary kriging was later applied to the residuals.

17


PREC90P: DJF 1971-2000PREC90P: DJF 1971-2000

18


PREC90P: JJA 1971-2000PREC90P: JJA 1971-2000

19


PREC10P: DJF 1971-2000PREC10P: DJF 1971-2000

20


PREC10P: JJA 1971-2000PREC10P: JJA 1971-2000

21


TX90P: DJF 1971-2000TX90P: DJF 1971-2000

22


TX90P: JJA 1971-2000TX90P: JJA 1971-2000

23


TN10P: DJF 1971-2000TN10P: DJF 1971-2000

24


TN10P: JJA 1971-2000TN10P: JJA 1971-2000

25


The authors thank AEMET and UC for the data provided for this work (Spain02 dataset)


Documents

EXTREME EVENTS AS REPRESENTED BY HIGH RESOLUTION CMCC CLIMATE MODELS