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Experiments in soil physics – changes in ”bare soil” parameterization

Institute of Meteorology and Water Management

National Research Institute

Experiments in soil physics – changes in ”bare soil”parameterization



Department of Numerical Weather Forecasts – COSMO

Andrzej Mazur, Grzegorz Duniec




2

Contents

• Introduction.

• Changes in parameterization/theoretical description.

• Numerical experiments.

• Plans for next COSMO year.

• Summary




3

• Two options considered:

kzz

s

s

ssD

B

BB

D

DF

tu

tK

KBB

u

tB

uwm

R

0log41,018,05,5

2

max

max

min 02,15

57,3

15501

kzz

s

s

ssD

B

BB

D

D

T

TF

tu

tK

KBB

u

tB

uw

a

m

R

0log41,018,05,5

2

max

max

min

0

02,15

57,3

15501

• version 1 (with a = -1, ½, 1, 2):

Changes in description of water flux through the soil surface




4

• Option 2:

DFm

a

mT

TDF

0

0T

T

m eDF

Changes in description of water flux through the soil surface

• version 1 (with a = -1, ½, 1, 2):

• version 2:




5

• Correction factor, time-depending:

2

r

2

s

2

r

2

s2

2

r

2

s tt

t8,0t5,1t

tt

7,0t

a

mT

TDtF

0

0

expT

TDtFm

• Fluxes through soil with correction factor (for a= -1, 0, ½, 1, 2 etc.)

Introduction of correction factor for water flux

• In general (remember this until the last slide):

22

222

22

rs

rs

rs tt

ttt

ttt




6

Fields:

• Soil Water Content at 1, 2, 6, 18, 54, 162, 486 and 1458 cm.

• Soil Temperature at 1, 2, 6, 18, 54, 162, 486 and 1458 cm.

• Surface soil temperature.

• Air temperature and dew point temperature 2 m agl.

• Relative Humidity at 2 m agl.

• u- and v-wind component at 10 m a. g. l.

• Total precipitation.

Setup of analysis

Time period: from April, 1st to September, 30th, 2013 (spring and summer)

Comparison:

Results of COSMO Model (reference) with measurements at synops.

Results of COSMO Model (altered parameterization) with measurements at

synops.

Results of different model versions (reference and altered parameterization).




7

wind speed

0

0,5

1

1,5

2

2,5

3

3,5

4

4,5

5

1 3 5 7 9 11 13 15 17 19 21 23 25 27 29 31 33 35 37 39 41 43 45 47 49 51 53 55 57

Serie1

Serie2

Serie3

Serie4

Serie5

Serie6

Serie7

Series 1 – Measurement

Series 2 – Reference

Series 3 – sqrt(T)

Series 4 – f(T)

Series 5 – f(T²)

Series 6 – α(t)exp(T)

Series 7 – exp(T)

difference (wind speed)

-2,5

-2

-1,5

-1

-0,5

0

0,5

1

1,5

2

2,5

1 3 5 7 9 11 13 15 17 19 21 23 25 27 29 31 33 35 37 39 41 43 45 47 49 51 53 55 57

Serie1

Serie2

Serie3

Serie4

Serie5

Serie6

Example – results for 06.04.2013-00 UTC



Series 3 – f(T)

Series 4 – f(T²)


Series 6 – exp(T)




8

air temperature

-11

-10

-9

-8

-7

-6

-5

-4

-3

-2

-1

0

1

2

1 3 5 7 9 11 13 15 17 19 21 23 25 27 29 31 33 35 37 39 41 43 45 47 49 51 53 55 57 Serie1

Serie2

Serie3

Serie4

Serie5

Serie6

Serie7

difference (air temperature)

-6

-4

-2

0

2

4

6

8

1 3 5 7 9 11 13 15 17 19 21 23 25 27 29 31 33 35 37 39 41 43 45 47 49 51 53 55 57

Serie1

Serie2

Serie3

Serie4

Serie5

Serie6




Series 4 – f(T)

Series 5 – f(T²)

Series 6 – α(t)sqrt(T)

Series 7 – exp(T)



Series 3 – f(T)

Series 4 – f(T²)


Series 6 – exp(T)





9

wind speed

0

1

2

3

4

5

6

7

8

9

10

11

1 3 5 7 9 11 13 15 17 19 21 23 25 27 29 31 33 35 37 39 41 43 45 47 49 51 53 55 57 59

Serie1

Serie2

Serie3

Serie4

Serie5

Serie6

Serie7





Series 4 – f(T)

Series 5 – f(T²)


Series 7 – exp(T)



Series 3 – f(T)

Series 4 – f(T²)


Series 6 – exp(T)


-5

-4

-3

-2

-1

0

1

2

3

4

5

1 3 5 7 9 11 13 15 17 19 21 23 25 27 29 31 33 35 37 39 41 43 45 47 49 51 53 55 57 59

Serie1

Serie2

Serie3

Serie4

Serie5

Serie6




10

dew point temperature

-10

-9

-8

-7

-6

-5

-4

-3

-2

-1

0

1

2

1 3 5 7 9 11 13 15 17 19 21 23 25 27 29 31 33 35 37 39 41 43 45 47 49 51 53 55 57 59 Serie1

Serie2

Serie3

Serie4

Serie5

Serie6

Serie7





Series 4 – f(T)

Series 5 – f(T²)


Series 7 – exp(T)



Series 3 – f(T)

Series 4 – f(T²)


Series 6 – exp(T)

difference (dew point temperature)

-9

-8

-7

-6

-5

-4

-3

-2

-1

0

1

2

3

4

5

1 3 5 7 9 11 13 15 17 19 21 23 25 27 29 31 33 35 37 39 41 43 45 47 49 51 53 55 57 59

Serie1

Serie2

Serie3

Serie4

Serie5

Serie6




11

wind speed

00,5

11,5

22,5

33,5

44,5

55,5

66,5

77,5

88,5

1 3 5 7 9 11 13 15 17 19 21 23 25 27 29 31 33 35 37 39 41 43 45 47 49 51 53 55 57

Serie1

Serie2

Serie3

Serie4

Serie5

Serie6

Serie7





Series 4 – f(T)

Series 5 – f(T²)


Series 7 – exp(T)



Series 3 – f(T)

Series 4 – f(T²)


Series 6 – exp(T)


-4,5-4

-3,5-3

-2,5-2

-1,5-1

-0,50

0,51

1,52

2,53

3,54

4,55

1 3 5 7 9 11 13 15 17 19 21 23 25 27 29 31 33 35 37 39 41 43 45 47 49 51 53 55 57

Serie1

Serie2

Serie3

Serie4

Serie5

Serie6




12

wind speed

0

1

2

3

4

5

6

7

8

9

10

1 3 5 7 9 11 13 15 17 19 21 23 25 27 29 31 33 35 37 39 41 43 45 47 49 51 53 55 57 59

Serie1

Serie2

Serie3

Serie4

Serie5

Serie6

Serie7





Series 4 – f(T)

Series 5 – f(T²)


Series 7 – exp(T)



Series 3 – f(T)

Series 4 – f(T²)


Series 6 – exp(T)


-4

-3

-2

-1

0

1

2

3

1 3 5 7 9 11 13 15 17 19 21 23 25 27 29 31 33 35 37 39 41 43 45 47 49 51 53 55 57 59

Serie1

Serie2

Serie3

Serie4

Serie5

Serie6




13

wind speed

0

0,5

1

1,5

2

2,5

3

3,5

4

4,5

5

5,5

6

6,5

1 3 5 7 9 11 13 15 17 19 21 23 25 27 29 31 33 35 37 39 41 43 45 47 49 51 53 55 57 59

Serie1

Serie2

Serie3

Serie4

Serie5

Serie6

Serie7





Series 4 – f(T)

Series 5 – f(T²)


Series 7 – exp(T)



Series 3 – f(T)

Series 4 – f(T²)


Series 6 – exp(T)


-4-3,5

-3-2,5

-2-1,5

-1-0,5

00,5

11,5

22,5

33,5

4

1 3 5 7 9 11 13 15 17 19 21 23 25 27 29 31 33 35 37 39 41 43 45 47 49 51 53 55 57 59

Serie1

Serie2

Serie3

Serie4

Serie5

Serie6




14

For all fields following statistics were produced (data for two seasons):

a) RMSE, R (Pearson) Correlation coefficient

b) Coordinates of ”Mass Center” of field tx of differences

MDV – Maximum Difference of Values

c) NDV – Normalized Difference of Values

Statistical analysis

x

x

r

x

r

xx

dt

rt

r

)j,i(t)j,i(tsign)j,i(t)j,i(tmaxMDV crcr

%100T

TTNDV

r

rc

maxmax

i

1i

j

1j

x

xji

)j,i(t

T

max max

;




15

Instytut Meteorologii i Gospodarki Wodnej – PIB

WSO1 - RMSE

0

0,05

0,1

0,15

0,2

0,25

0,3

0,35

1 22 43 64 85 106 127 148 169 190 211 232 253 274 295 316 337 358

Serie1

Serie2

Serie3

Serie4

Serie5

Series 1- reference – exp(T); Series 2 – reference – sqrt(T); Series 3 – reference – f(1/T);

Series 4 – reference – f(T); Series 5 – reference – f(T²)

Statistical analysis – examples WSO1- CORRELATION COEFFICIENT

0,88

0,9

0,92

0,94

0,96

0,98

1

1,02

1 22 43 64 85 106 127 148 169 190 211 232 253 274 295 316 337 358

Serie1

Serie2

Serie3

Serie4

Serie5

U10-RMSE

0

0,2

0,4

0,6

0,8

1

1,2

1,4

1 22 43 64 85 106 127 148 169 190 211 232 253 274 295 316 337 358

Serie1

Serie2

Serie3

Serie4

Serie5

U10 - CORRELATION COEFFICIENT

0,8

0,85

0,9

0,95

1

1,05

1 22 43 64 85 106 127 148 169 190 211 232 253 274 295 316 337 358

Serie1

Serie2

Serie3

Serie4

Serie5




16


RELHUM-RMSE

0

1

2

3

4

5

6

1 21 41 61 81 101 121 141 161 181 201 221 241 261 281 301 321 341 361

Serie1

Serie2

Serie3

Serie4

Serie5

Statistical analysis – examples AIR TEMPERATURE - RMSE

0

0,2

0,4

0,6

0,8

1

1,2

1 22 43 64 85 106 127 148 169 190 211 232 253 274 295 316 337 358

Serie1

Serie2

Serie3

Serie4

Serie5

DEW POINT TEMPERATURE -RMSE

0

0,1

0,2

0,3

0,4

0,5

0,6

0,7

1 22 43 64 85 106 127 148 169 190 211 232 253 274 295 316 337 358

Serie1

Serie2

Serie3

Serie4

Serie5

Series 1- reference – exp(T); Series 2 – reference – sqrt(T); Series 3 – reference – f(1/T);

Series 4 – reference – f(T); Series 5 – reference – f(T²)

TSO0-RMSE

0

0,5

1

1,5

2

2,5

1 22 43 64 85 106 127 148 169 190 211 232 253 274 295 316 337 358

Serie1

Serie2

Serie3

Serie4

Serie5




17


Results 5 XII 2012

Parameterization sensitive area

– Mass Center of differences

Statistical analysis – examples




18

a) …to continue tests of altered parameterization using ensemble forecast (COTEKINO)

b) … to introduce correction to Richards’ equation via a change in numerical scheme.

c) … to prepare a new parameterization of thermal processes

d) … to combine type of soil (clay, sand, loam…) with different values of exponent ”a”

e) ... to utilize a different values of β, χ and γ

f) … to enter in theoretical work on parameterization of plants physiology and its influence on soil processes in model.

Plans and to-do list

22

222

22

rs

rs

rs tt

ttt

ttt




19

• New parameterization has an impact on Soil Water Content (SWC). This impact declines with depth. It also influences the soil temperature, but mostly in the upper part of soil and only in case if soil is not frozen.

• …it influences on (improves forecasts of) other meteorological fields (windspeed, temperature, dew point, specific water vapor content).

• results are sensitive to parameterization with exponential dependence of temperature together with corrective ratio introduced (best results so far!)

• New parameterization influenced soil fields – magnitude of the influnce quantitatively unknown due to lack of other measurements than soil temperature at four levels.

• Further improvement is expected with changes to Richards’ equation

Summary




Thank you for attention

Grzegorz Duniec, Andrzej Mazur

Instytut Meteorologii i Gospodarki Wodnej

Państwowy Instytut Badawczy



01-673 Warszawa, ul.: Podleśna 61

tel. +48 22 56-94-134

[email protected]

[email protected]

www.imgw.pl

www.pogodynka.pl

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