IPILPS Workshop ANSTO 18-22 April 2005 IPILPS Forcing & REMOiso Performance by Dr Matt Fischer and Kristof Sturm.

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Presentation transcript:

IPILPS Workshop ANSTO April 2005 IPILPS Forcing & REMOiso Performance by Dr Matt Fischer and Kristof Sturm

Topics History ECHAM Forcing Variables Performance - Europe - South America - Australia FAR interpolation

History PILPS, 8 forcing variables: 2 radiation, pressure, 2 wind, temp., r’fall, humidity IPILPS, where to get isotope var’s from? Observations?: high resolution data rare, & no information on spatial variance Models? - MUGCM - GISS - ECHAM - REMOiso Resolution ? Climate ? Isotopes ? Locations ?

ECHAM ECMWF model, aimed at climate simulations ECHAMiso: Spectral resolution : T30, i.e. 3.75º (~ 450 km) Vertical resolution: 19 levels REMOiso - RCM nested in ECHAMiso, run in Europe & South America

List

Forcing VariablesForcing Variables

Tumbarumba EQY1: Radiation List

Tumbarumba EQY1: Rainfall

Tumbarumba BC24: variance

REMOiso was run for 4 years (except Manaus), at =< 5 minute resolution EQY1 Equilibrium experiment BC24 experiment FAR interpolation (for Manaus) REMOiso

Topics History ECHAM Forcing Variables Performance - Europe - South America - Australia FAR interpolation

Locations Mid-latitude deciduous forest eg. Munich 48°N 16°E Tropical rainforest eg. Manaus 3°S 60°W Mid-latitude eucalypt forest eg.Tumbarumba 35°S 148°E

Nordeney  18 O from April 97 to Feb 99  18 O  18 O as good, or bad, as precipitation amounts (Sturm et al., 2004)  18 O Obs REMO Europe

Europe

South America 5 minute simulations, written for 25 cells: Manaus x9 Zongo x9 Rocafuerte x9 Belem x1 Izobamba x1

 18 O in precipitation

Manaus

Australia First experiment for this domain GNIP Stations: Perth, Darwin, Alice Springs, Brisbane, Adelaide, Cape Grim, Melbourne Tumbarumba x9 Padthaway x9

 18 O Australia January

July  18 O Australia

Temperature

Rainfall

Rainfall

 18 O

D-excess

Summary so far... REMOiso simulations of Europe and South America compare with data from GNIP stations and general climatology REMOiso simulations of Australia are too wet or dry for some sites, but generally compare with GNIP data, excpet perhaps for D-excess

Topics History ECHAM Forcing Variables Performance - Europe - South America - Australia FAR interpolation

Functional autoregression (FAR) y t =  y t-1 +  x t +  t but, we can replace x & y by orthonormal vector subsets. y is 5 minute data, x is 6 hour data Estimation: of the parameters , ,  ( ,  ) using method of Damon & Guillas 2001 Interpolation: Eigenvectors of x & y are ‘stretched & pulled’ over a new set of 6 hour data to form a new set of 5 min data. Applications: NCEP

Temperature & Wind FAR 5 min. Linear 5 m. Original 5 m.

Temperature & Wind

FAR 5 min. Linear 5 m. Original 5 m.

Rainfall FAR 5 min. Linear 5 m. Original 5 m.

Rainfall

Rainfall FAR 5 min. Linear 5 m. Original 5 m.

Future : more comparisons! REMOiso comparison of: the stochastic properties of storms (duration, intensity, rainout) with Australian BOM data (40 yrs of 6 minute rainfall data, Capital cities only) Isotopic rainout of individual storms, for BOM data this is an inverse problem using storm data + monthly GNIP data

Conclusions REMOiso, a regional climate model, produces monthly isotope values in 3 domains which compare with GNIP data, except, perhaps for D-excess FAR can be used to downscale observational data; and is based on functional relationships between different timescales, calibrated with an isotope model.

model

FAR FAR 5 min. Linear 5 m. Original 5 m.

FAR FAR 5 min. Linear 5 m. Original 5 m.

‘ List