ELDAS activities at SMHI/Rossby Centre

– 2nd Progress Meeting

L. Phil Graham

Daniel Michelson

Jonas Olsson

Åsa Granström

Swedish Meteorological and Hydrological Institute, Norrköping, Sweden

WP 2100 – precipitation

RR - 3 and 12-hour Gauge-adjusted accumulated precipitationCharacteristics:• 2 x 2 km horizontal resolution

• 3 and 12-hour temporal resolution

• 32-bit depth

• Uses corrected gauge observations

• 3-hour covers BALTRAD area

• 12-hour covers BALTEX Region

• Continuous production

New Doctor!New Doctor!

Quality Control of Weather Radar Data for Quantitative Application

Daniel Michelson

September 2003

Verification of Dynamic Correction Model (DCM) with 1-hr forcing

Jokioinen, Finland

WP 5400 – Baltic demo basins

D33) Baltic Sea

Basin

D34) Swedish Basins

Comparison of Areal Precipitation Estimates by Gauges and Radar: A Case Study for a

Central Swedish Catchment

Jonas Olsson, Barbro Johansson, Daniel Michelson

Swedish Meteorological and Hydrological InstituteSE-601 76 Norrköping, SWEDEN

Torpshammar Basin

Data:• PTHBV: interpolated gauge data• RADAR: gauge-adjusted radar data• Daily accumulations 2000-2002 in a 44 km grid (589 nodes)

Catchment:• Area: 4 300 km²• Mean annual prec.:

700 mm• Mean altitude: 340

m.a.s.l. (range 20-540 m.a.s.l.)

Monthly Precipitation

Differences (RADAR-PTHBV)

-100

-50

0

50

100

150

J F M A M J J A S O N D J F M A M J J A S O N D J F M A M J J A S O N D

(mm

)

Gimån, 2000-2002

0

50

100

150

200

250

300

350

J F M A M J J A S O N D J F M A M J J A S O N D J F M A M J J A S O N D

(mm

)

PTHBV RADAR

Torpshammar Total, 2000-2002

Differences (RADAR-PTHBV)

Daily differences - spatial dependence (2000-2002)

(similar patterns for individual years)

-0,4

-0,2

0

0,2

0,4

0,6

0,8

1

1,2

1,4

1436000 1456000 1476000 1496000 1516000 1536000 1556000

West-East (m)

Dif

fere

nc

e (

mm

)

(RA

DA

R-P

TH

BV

)

0

50

100

150

200

250

300

350

400

450

Altitu

de

(m.a

.s.l.)

Difference Altitude

0

0,2

0,4

0,6

0,8

1

1,2

1,4

1,6

6932000 6944000 6956000 6968000 6980000 6992000 7004000

South-North (m)

Dif

fere

nc

e (

mm

)

(RA

DA

R-P

TH

BV

)

0

50

100

150

200

250

300

350

400

Altitu

de

(m.a

.s.l.)

Difference Altitude

Daily differences - intensity dependence2000

-10

0

10

20

30

0 10 20 30 40 50 60

PTHBV (mm)

Dif

fere

nce

(m

m)

(RA

DA

R-P

TH

BV

)

2001

-30

-20

-10

0

10

20

0 10 20 30 40 50 60 70

PTHBV (mm)

Dif

fere

nce

(m

m)

(RA

DA

R-P

TH

BV

)

2002

-10

-5

0

5

10

0 5 10 15 20 25

PTHBV (mm)

Dif

fere

nce

(m

m)

(RA

DA

R-P

TH

BV

)

Runoff simulation (HBV model)Input: PTHBV

0

200

400

600

00-01-01 00-07-01 01-01-01 01-07-01 02-01-01 02-07-01

Dis

char

ge

(mm

)

HBV OBSERVED

Input: RADAR

0

200

400

600

00-01-01 00-07-01 01-01-01 01-07-01 02-01-01 02-07-01

Dis

char

ge

(mm

)

HBV OBSERVED

• GA radar data reproduce well the gauge-observed mean rainfall for 2002, but less accurately in 2000 and 2001.

• GA radar data contain temporal and spatial inhomogeneities, possibly related to (i) changes in the operation and/or (ii) unstable functionality of the instruments.

• Spatial pattern of differences indicates a consistent overestimation by the GA radar data located north-west of the catchment (Östersund).

• High mean rainfall intensities are often underestimated and low intensities overestimated by the GA radar data.

• Catchment runoff estimated by GA radar data is distinctly overestimated in the first half of the period, but accurate during 2002.

(“GA” = “gauge-adjusted”)

Torpshammar Summary

What’s Next?

• more fair test against forecast conditions

• event-based analysis

• Glafsfjorden basin

• compare to ELDAS precipitation database

• compare soil moisture for different driving P fields and against ELDAS generated fields

• compare runoff

more What’s Next?

• Baltic Basin runoff generation and river discharge (WP 3200)

SN

QRG

SNF

SNM

QDR

wd

dwdz

RAF

ws

RATHR

• European VIC application!

European VIC application

(Variable Infiltration Capacity Model)

cooperation with University of Washington

Why EuroVIC?

• independent source of spatially distributed soil moisture

• sets a climate perspective for SM

• additional verification (e.g. evapotranspiration)

• routed river flow over Europe from ELDAS models??

Details of EuroVIC - 1

• ELDAS grid (0.2° x 0.2°)

• climate based 1980?-2002?

• focus on ELDAS period 1999-2000

• common databases where possible (e.g. ERA-40, ECOCLIMAP)

• higher resolution orography (SRTM?)

Details of EuroVIC - 2

• river routing included

• databases of natural river flow preferred! (who has these?)

old map

European map