LBA Flux Tower Workshop

Software Intercomparison

Celso von RandowGanabathula Prasad

CPTEC/INPE

December 2001

Quality control – Vickers & Mahrt (1997) Flux sampling problems – Mahrt (1998)

Surface heterogeneity, complex terrains Nonstationarity Random Flux Errors Systematic underestimation of low

frequency fluxes Sensitivity of flux calculations Results of intercomparison among LBA

flux measurements

Software intercomparison

Quality control for Sonic Data Spike Removal Insufficient Amplitude Resolution Drop outs Absolute Limits Skewness and Kurtosis Discontinues- Haar mean, Haar var. Lag Correlation – Not used. Vertical Profile – Not used.

Spike Removal Electronic spikes to have a max. width

of 3 consecutive points in the time series and more than 3.5 standard deviations from the window mean (L=3000 points =5min@10Hz)

The point is replaced using linear interpolation between data points.

The record is flagged when the total number of spikes replaced exceeds 1% of the total number of data points

Insufficient Amplitude Resolution Compute a series of discrete frequency

distributions for half-overlapping windows of length 1,000 data points

The window move one-half the window width at a time through the series

the number of bins is 100 and the interval for the distribution is min(range, 7).

Flagged if number of empty bins in the discrete frequency distribution >70%

Amplitude Resolution

2.2 2.4 2.6 2.8 3 3.2 3.4 3.6 3.8 4

32.2

32.21

32.22

32.23

32.24

32.25

32.26

32.27

32.28

32.29

32.3

time(minutes)

H 2O (m

mol

/m)

Santarem km67 file E1150700

Drop outs Consecutive points that fall into the same

bin are tentatively identified as dropouts Max no of consecutive dropouts as % of

total window points same window and frequency

distributions used for the resolution problem

if bin is within 10% and 90% tentiles of distribution, compare with threshold.

Drop out

5 10 15 20 25 30

298.2

298.3

298.4

298.5

298.6

298.7

298.8

298.9

299

Time(minutes)

T (K

)

Jaru 213, 21:30

Absolute Limits |u|> 30 m/s |v| > 30m/s |w| > 5 m/s T < 275 K (2 C) & T> 323 K (50 C) H2O< 2 & H2O> 40 g/kg

Skewness and Kurtosis

Detrend record Skewness [-2 2] (Empirical value) Kurtosis [1 8] (Empirical value)

Discontinuites Haar transform of window Normalize with the smallest S.D. Discontinuity if Haar mean >3

15 16 17 18 19 20

298.5

298.6

298.7

298.8

298.9

299

299.1

299.2

299.3

time (minutes)

T (K

)

Jaru 216, 20:30 Discontinutite Haar mean=3.2

Flux Sampling Errors

Systematic Error: failure to capture all the largest transporting eddies– underestimation of flux.

Random Error: Inadequate sampling of main transporting eddies, inadequate record size.

Mesoscale variability: inhomogeneity of flow. Dependence of flux on choice of scale.

Systematic Error

Relative Systematic Error:

< w’’>L2 - < w’’>L1 < Th < w’’>L1

Random Error

Partition record into non overlapping subrecords (i=1,2,…)

Average Flux Fi=<Fi> +Ftr + F*i

Ftr = a0 + a1t using a Least Squares fit. RFE = F* |<Fi>| -1 N-0.5

RN = Ftr |<Fi>| -1 N-0.5

Flux Event

Measure of Isolated flux event:

Max(Fi) |<Fi>| -1

Fi is the aver sub-record flux<Fi> is the record mean value of Fi

Preliminary Results on Santarem km67Day 267 No of Records 44 RFE RN EVT RSE FSRWU 5 3 48 1 0WV 45 9 48 34 15WT 6 5 48 3 0WH2O 18 6 48 11 0

Sensitivity of flux calculations

Averaging time scales Rotations Block averaging / Linear detrending /

Recursive digital filter Low frequency corrections Uncertainties

LBA tower sites Rondônia

Rebio Jaru forest – Primary forest Fazenda Nossa Senhora) - Pasture

Manaus Tower K34 – Primary forest Tower C14 – Primary forest

Santarém Tower Km 67 – Primary forest Tower km 83 – Logged forest

(primary) Tower km 77 – Pasture site

LBA tower sites Caxiuanã

Primary forest Brasília

Cerrado Campo Sujo (Biennial fire regime) Campo Sujo (Quadriennial fire

regime) Mato Grosso

Sinop Forest Bragança

Mangrove Venezuela – Savanna site

Venezuela

Softwares used in intercomparison

Rondônia, Manaus – EddyWSC v.2 (Alterra) 3 rotations; Digital recursive filter (800 s time constant); Low frequency corrections

Vickers & Mahrt Software (Oregon St. Univ.) 2 rotations; Block averaging Discard records with high random flux errors and

nonstationarity

+ Softwares used in LBA flux sites

Santarém, km 83 – EddyWSC v.1 (Alterra) 3 rotations; Digital recursive filter (200 s time constant);

Santarém, km 67 – CD-10 Program (Harvard Univ.)

Santarém, Pasture – CD-03 Program (ASRC, Albany)

Caxiuanã – Edisol (Univ. of Edinburgh) Brasília – EddySoft package (MPI)

3 rotations; Linear detrending;

Venezuela – Edisol (Univ. of Edinburgh)

Caxiuanã

y = 0.9953xR2 = 0.9951

-30

-25

-20

-15

-10

-5

0

5

10

15

20

-30 -25 -20 -15 -10 -5 0 5 10 15 20

Fc (EddyWSC) (W/m2)

Fc (E

diso

l) (m

mol

/m2 /s

)Edisol x EddyWSC

Rebio Jaru - Wet Season period

y = 0.9759xR2 = 0.9366

-60

-40

-20

0

20

40

60

-60 -40 -20 0 20 40 60

Fc V & M (mmol/m2/s)

Fc e

ddyW

SC (m

mol

/m2 /s

)EddyWSC x Vickers & Mahrt Software

Rebio Jaru - Wet Season period

y = 0.9937xR2 = 0.974

-100

0

100

200

300

400

500

600

700

-100 0 100 200 300 400 500 600 700

LE V & M (W/m2)

LE e

ddyW

SC (W

/m2 )

Rebio Jaru - Dry Season period

y = 0.9494xR2 = 0.7616

-60

-40

-20

0

20

40

60

80

-40 -30 -20 -10 0 10 20 30 40 50

Fc V & M (mmol/m2/s)

Fc e

ddyW

SC (m

mol

/m2 /s

)

Rebio Jaru - Dry Season period

y = 0.9422xR2 = 0.9488

-100

0

100

200

300

400

500

600

700

-100 0 100 200 300 400 500 600 700

LE V & M (W/m2)

LE e

ddyW

SC (W

/m2)

Manaus km 34 - Wet Season period

y = 1.0361xR2 = 0.9512

-40

-30

-20

-10

0

10

20

30

40

-40 -30 -20 -10 0 10 20 30 40

Fc (V & M)

Fc e

ddyW

SC

Manaus km 34 - Wet Season period

y = 1.0206xR2 = 0.9634

-100

0

100

200

300

400

500

-100 0 100 200 300 400 500

LE (V & M)

LE e

ddyW

SC

Santarem km67 - Wet season period

y = 1.0248xR2 = 0.9766

-0.6

-0.4

-0.2

0

0.2

0.4

0.6

0.8

-0.6 -0.4 -0.2 0 0.2 0.4 0.6 0.8

w-c covariance (Vickers & Mahrt software)

w-c

cov

. (C

D-1

0 pr

ogra

m)

CD-10 x Vickers & Mahrt Software

~ dry season

Santarem km67 - Wet season period

y = 1.0342xR2 = 0.9752

-0.05

0

0.05

0.1

0.15

0.2

0.25

0.3

0.35

-0.05 0 0.05 0.1 0.15 0.2 0.25 0.3

w-q covariance (Vickers & Mahrt software)

w-q

cov

. (C

D-1

0 pr

ogra

m)

~ dry season

Santarem km67 - Wet season period

y = 0.9387xR2 = 0.9615

-0.1

-0.05

0

0.05

0.1

0.15

0.2

-0.05 0 0.05 0.1 0.15 0.2

w-T covariance (Vickers & Mahrt software)

w-T

cov

. (C

D-1

0 pr

ogra

m)

CD-04 x EddyWSC

Santarem km83

y = 0.8965xR2 = 0.9962

-40

-30

-20

-10

0

10

20

30

40

-40 -30 -20 -10 0 10 20 30 40

Fc (EddyWSC v.2) (mmol/m2/s)

Fc (E

ddyW

SC v

.1) (

m mol

/m2 /s

)

200 s x 800 s time constant

Santarem km83

y = 0.8137xR2 = 0.9956

-100

0

100

200

300

400

500

600

700

-100 0 100 200 300 400 500 600 700 800

LE (EddyWSC v.2)

LE (E

ddyW

SC)

Santarem Pasture - Wet season period

y = 0.7667xR2 = 0.7927

-0.6

-0.4

-0.2

0

0.2

0.4

0.6

-0.6 -0.4 -0.2 0 0.2 0.4 0.6

w-c covariance (Vickers & Mahrt software)

w-c

cov

. (C

D-0

3 pr

ogra

m)

CD-03 x Vickers & Mahrt Software

Santarem Pasture - Wet season period

y = 0.8085xR2 = 0.7887

-0.6

-0.4

-0.2

0

0.2

0.4

0.6

0.8

-0.6 -0.4 -0.2 0 0.2 0.4 0.6 0.8

w-c covariance (EddyWSC)

w-c

cov

. (C

D-0

3 pr

ogra

m)

CD-03 x EddyWSC

Brasília - Cerrado - Wet season

y = 0.8982xR2 = 0.9934

-10

-8

-6

-4

-2

0

2

4

6

-10 -8 -6 -4 -2 0 2 4 6

Fc (EddyWSC)

Fc (E

ddyf

lux

pack

age)

Eddysoft package x EddyWSC~ dry season

Brasília - Campo Sujo (biennial) - Dry season

y = 0.8564xR2 = 0.9265

-1

0

1

2

3

4

5

-1 0 1 2 3 4 5

Fc (EddyWSC)

Fc (E

ddyf

lux

pack

age)

Brasília - Campo Sujo (Quadriennial) - Dry season

y = 0.8623xR2 = 0.9705

-5

-4

-3

-2

-1

0

1

2

3

4

5

-5 -4 -3 -2 -1 0 1 2 3 4 5

Fc (EddyWSC)

Fc (E

ddyf

lux

pack

age)

Venezuela

y = 0.6309xR2 = 0.9378

-5

-4

-3

-2

-1

0

1

2

3

4

5

-5 -4 -3 -2 -1 0 1 2 3 4 5

Fc (EddyWSC) (mmol/m2/s)

Fc (E

diso

l) (m

mol

/m2 /s

)Venezuela (Edisol) x EddyWSC

Venezuela

y = 0.5453xR2 = 0.9652

-50

0

50

100

150

200

-50 0 50 100 150 200

LE (EddyWSC) (W/m2)

LE (E

diso

l) (W

/m2 )

In summary... Fluxes calculated by different LBA groups might give

quite different values specially considering different parameters (averaging time scale; corrections; etc)

As fluxes calculations in complex terrains are very sensitive to parameters like rotations and averaging time scales, LBA groups should be VERY CAREFUL when integrating or comparing measurements from different groups.

Softwares used by a few groups (Rondonia/Manaus, Santarém km 67, Caxiuanã/Bragança) agree within + 6 %.

Softwares used by groups CD-03, CD-04, Brasilia and Venezuela calculated substantially lower fluxes than other programs (averaging time scales ? corrections ? )

Acknowledgements

Jair F. MaiaMaria Betânia L. de OliveiraPaulo Kubota

Suggestions for (near) future Continue software intercomparison

Put together a “golden” data set that can be run by each group on their own program;

Integration of measurements on large scale Standardize software parameters ?

How do the differences are reflected in long term budgets ? Are the differences the same in positive

(respiration) and negative (assimilation) fluxes ?

To be continued ...