evaluation of satellite-derived high resolution...

EVALUATION OF SATELLITEEVALUATION OF SATELLITE--DERIVED HIGH DERIVED HIGH RESOLUTION RAINFALL ESTIMATES OVER RESOLUTION RAINFALL ESTIMATES OVER

EASTERN SÃO PAULO AND PARANEASTERN SÃO PAULO AND PARANÁÁ, BRAZIL, BRAZIL

Augusto J. Pereira FilhoAugusto J. Pereira Filho11

Phillip Phillip ArkinArkin 22

Joe TurkJoe Turk33

John E. JanowiakJohn E. Janowiak44

Cesar BenetiCesar Beneti55

Leonardo Leonardo CalvettiCalvetti 55

Ricardo HallakRicardo Hallak11

Felipe VemadoFelipe Vemado11

1DAC/IAG, University of São Paulo, Brazil2ESSIC, University of Maryland, College Park, USA

3NRL, Marine Meteorology Division, USA4Climate Prediction Center/NOAA, USA

5SIMEPAR, Paraná, Brazil

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São PauloSão Paulo

ParanParanáá

Background

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HOURLY ACCUMULATION2003 and 2004

(mm)(Pereira Filho et al., 2006)(Pereira Filho et al., 2006)

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TIME OF MAXIMUM RAINFALL

(mm)

(UTC)

2003 and 2004

(Pereira Filho et al., 2006)(Pereira Filho et al., 2006)

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RADAR X SATELLITE

Total Rainfall

1 = Ground Clutter Filtering (2 and 3)4 = Grind Clutter Contamination5 = Range Effect7 = Signal Processing

(Pereira Filho et al., 2002)(Pereira Filho et al., 2002)

Program for the Evaluation of High Resolution Precipitation Products (PEHRPP) coordinated by ESSIC and NRL.

Goal is to compare and to validate these high resolution datasets.

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Estimated Observed

Falsealarms

Hits

MissesObserved

yes no

yes hits false alarms

no misses correct negativesE

stim

ated

Contingency Table

(Elbert, 2003)(Elbert, 2003)

False alarm ratioalarmsfalsehits

alarmsfalseFAR

+

=

Probability of detectionmisseshits

hitsPOD+

=

Critical success indexalarmsfalsemisseshits

hitsCSI ++

=

misseshitsalarmsfalsehitsBIAS

++

= Bias score

Correlation coefficient∑∑

∑−−

−−=

22 )()(

)( )(

OOEE

OOEEρ

Root mean square error 2

1

)(1i

N

ii OE

NRMSE −= ∑

=

SPWR RAINFALL ESTIMATES

X

CMORPH, TRMM, PERSIANN and NRL- BLENDED

(m)

São Paulo, Brazil.

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SPWR DATASETS: 10/2005 TO 03/2006;

SATELLITE PRECIPITATION DATA:

0.25 DEGREE X 3-HOUR;

SYSTEM TYPES:

COLD FRONT, RAIN BANDS, ORDINARY COLD FRONT, RAIN BANDS, ORDINARY CONVECTIONCONVECTION, SQUALL LINES

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EXAMPLES

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COLD FRONTCOLD FRONT

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RAIN BANDSRAIN BANDS

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OR

DIN

AR

Y C

ON

VE

CTIO

NO

RD

INA

RY

CO

NV

EC

TION

0,05

0,1

0,15

0,2

TRMM CMORPH PERSIANN NRL-B

Mea

n C

SI0,1 mm

0,2 mm

1,0 mm

4,0 mm

OVERALL RESULTS

All data sets available 10/05 to 03/06

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DISCUSSION (SP)•• Coordinate discrepancies;Coordinate discrepancies;•• Phase and amplitude errors;Phase and amplitude errors;•• All four methods yielded poor results;All four methods yielded poor results;•• Radar rainfall accumulation higher than satellite ones; Radar rainfall accumulation higher than satellite ones; •• Radar data with range effect and other problems;Radar data with range effect and other problems;•• Best performance for low rainfall accumulation: CMORPH; Best performance for low rainfall accumulation: CMORPH; •• Best performance for higher accumulation: PERSIANN;Best performance for higher accumulation: PERSIANN;•• Fewer data for PERSIANN;Fewer data for PERSIANN;•• All methods are limited;All methods are limited;•• Need for rain gauges and stream gauges verification.Need for rain gauges and stream gauges verification.

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PARANA STATESatellite techniques: CMORPH (Joyce et. al., 2004), PERSIANN (Sorooshian et al., 2000), TRMM (Huffman et. al., 1997), NRLB (Turk et. al., 2003) and CST (Adler e Negri, 1998).

Data

141 weather stations over Parana State

Methodology

1) Observed and estimated rainfall @ 0.25° spatial resolution over 56°W – 46.75°W and 27°S-21.75°S for 1 day to a month accumulation.

2)Period: January 2003 – December 2005

3)Rain/non-rain threshold: 0.3mm/day and 20mm/month;

4)Statistics: average, variance, bias, POD FAR, ETS, MSE, correlation coefficient;

5)Hovmoller diagrams.

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Hovmöller Diagrams

GAUGE CMORPH TRMM

PERSIANN NRLB CSTmm/month mm/month mm/month

mm/month mm/month mm/month

Monthly AccumulationOctober 2005

May 2005

BIAS 0.99 1.00 POD 0.99 1.00FAR 0.00 0.00COR 0.67 0.62RMSE 130.40 79.86GAUGE AVE 245.42 245.42SAT AVE 123.80 182.25 GAUGE VAR 59.71 59.71SAT VAR 54.88 50.48

NRLB CST

GAUGE

GAUGE

NRLB CST

TRMM

mm/month mm/month mm/month

mm/month mm/month

BIAS 0.95 POD 0.95FAR 0.00COR 0.79RMSE 104.02GAUGE AVE 136.22SAT AVE 52.98GAUGE VAR 74.39SAT VAR 23.85

TRMM

CST ra in n o n -ra in

ra in 5 5 2 0n o n -ra in 0 0

NRLB ra in non -ra in

ra in 546 0non -ra in 1 0

TRMM ra in non -ra in

ra in 522 0non -ra in 28 0

Observed

ObservedObserved

Estimated

Estimated Estimated

Monthly Accumulations - Spatial BIAS(Jan/2003 - Dec/2005)

Daily Accumulation

November 17th, 2003

May 12th, 2004

BIAS 1.05 POD 0.99

FAR 0.05 COR 0.64 RMSE 20.40 GAUGE AVE 32.05 SAT AVE 16.43 GAUGE VAR 17.41 SAT VAR 8.59

BIAS 0.99 POD 0.96 FAR 0.03 COR 0.75 RMSE 14.88 GAUGE AVE 25.76 SAT AVE 18.93 GAUGE VAR 19.30 SAT VAR 17.12

CMORPH

TRMM

CMORPH ra in no n -ra in

ra in 5 18 29n on -ra in 3 0

TRMM ra in n on -ra in

ra in 4 24 1 3n on -ra in 1 9 8 4

Observed

Estimated

Observed

Estimated

Discussion (PR)Hovmöller diagrams indicate good agreement between satellite-derived estimates and gauges, though amplitude differences are significant.

Monthly satellite-derived accumulations better for January, May and October. Daily values highly variable.

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Polarimetric Data Sets

Mobile Weather Radar Doppler Dual X-band (MXPOL) Hydrometeorology Lab (LabHidro) – Institute of Astronomy, Geophysics and Atmospheric Sciences (IAG), University of São Paulo .

MXPOL 4,5o PPI at 2119 UTC on 26 April 2007.

Zh Vr W

Kdpρohv

SPWR 3-km CAPPI 1-km x 1-km resolution at 1616 UTC on 22 May 2007. MXPOL at (23o33.4’S; 46o44.1’W).

São Paulo City sounding (83779) at 1200 UTC on 22 May 2007.

MXPOL vertical profiles at 1616 UTC on 22 May 2007. Full clockwise antenna scan (6.0o s-1) @ 90o, pulse width = 0.2 μs, PRF=1000 Hz and 256 samples, Δz=35m.

Vertical profile - Zh

Vertical profile - W

Vertical profile - Vr

MXPOL vertical profiles at 1616 UTC on 22 May 2007. Full clockwise antenna scan (6.0o s-1) @ 90o, pulse width = 0.2 μs, PRF=1000 Hz and 256 samples, Δz=35m.

Vertical profile - Kdp

Vertical profile - Zdr

Vertical profile - ρohv

Vertical profile - φdp

THE END

Work supported by:Work supported by:FAPESP and CNPq (BRAZIL) FAPESP and CNPq (BRAZIL) NCAR and ESSIC (USA)NCAR and ESSIC (USA)WMOWMO

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