Numerical simulation Numerical simulation of dynamics of atmosphere - - PowerPoint PPT Presentation

Numerical simulation Numerical simulation

• f dynamics
• f dynamics of atmosphere
• f atmosphere

and tracer transport and tracer transport above hydrologically heterogeneous land above hydrologically heterogeneous land

International conference and young scientists school CITES-2007, Tomsk

Lomonosov Moscow State University

V V. . M M. . Stepanenko Stepanenko, , D D. . N N . . Mikushin Mikushin

The work is supported by RFBR grant 04-05-64898

The m otivation of study - 1

many regions of the Earth are covered by dense system of small

water reservoirs and rivers (Karalee, Western Siberia, …);

if the water reservoir is sufficiently large (according to empirical evidence and theoretical estimates – if size exceeds 10 km) breezes often develop (Strunin&Hiyama, 2005); it is known, that breezes near the coasts of large lakes and seas significantly affect the tracer transport, that in some cases leads to high concentrations of pollutants (Burman, 1969; Eastman et al., 1995);

The m otivation of study - 2

in Western Siberia there is a widespread oil extracting activity, that is accompanied by emission of pollutants in the atmosphere

• it is important to estimate the

transport of these pollutants by breezes;

the density of hydrological system in Western Siberia does not allow to identify the related breeze circulations by conventional meteorological

• bservations –

the numerical simulation is the

• nly tool to study these

circulations.

The goal Tasks

Numerical estimation of breeze circulations and passive tracer transport

• ver hydrologically heterogeneous land
• verification of the ability of numerical model to realistically simulate

breeze circulations and dependence of breeze intensity on external factors;

• adaptation of the model “atmosphere – land – water reservoir” to

the certain regions in Western Siberia;

• calculation of major characteristics of mesoscale circulations, that

developing over hydrologically heterogeneous regions of Western Siberia;

• estimation of transport of pollutants by breeze circulations.

The tool

Numerical model «atmosphere – land – water reservoir»

Numerical model «atmosphere – land – water reservoir»

Atmospheric model Land surface model Lake model

1D model of heat and mass transfer (Stepanenko & Lykosov, 2005) Snow Ice Water Soil

U H,LE Es Ea S

3D non-hydrostatic model in σ - coordinates

Nh3d (Miranda, 1990)

New options: 1) Parameterization of shortwave radiation Clirad-SW (Chou & Suarez, 2002); 2) Parameterization of longwave radiation Clirad-LW (Chou & Suarez, 2003) Two-layer model of heat and moisture transfer in soil and vegetation ISBA (Meteo-France) (Mahfouf et al., 1995)

RAIN SNOW

• psnv

• LIQ. WAT. IN SNOW (WL)

• LIQ. WAT. RETAINED

Modeling of passive tracer transport

( ) ( ) ( ) ( )

( )

* * * * * q q

qp uqp vqp qp p D R t x y σ σ ∂ ∂ ∂ ∂ + + + = + ∂ ∂ ∂ ∂ &

* surf top

p p p = −

q

D

• Diffusion term (1st order turbulence closure),
• Rayleigh damping term

Numerical scheme:

1) Spatial derivatives – 2nd order central differences; 2) Time integration – «leap-frog» scheme; 3) Filtration of the numerical mode – Asselin filter; 4) Nonlinear instability suppression – spatial 4th order filters

Shortcoming of the scheme: non-monotonous, applying the condition

1 1

max 0,

n n

q q

+ +

  =    

q

R

Boundary conditions:

q q C t n ∂ ∂ + = ∂ ∂

• at lateral boundaries

q σ ∂ = ∂

• at the top

Daytime breeze over single lake: Daytime breeze over single lake: wind field in surface layer at 1 wind field in surface layer at 1st

st day, 15:00

day, 15:00

• 1. The domain:

360*360 km;

• 2. Grid dimensions:

36*36 points;

• 3. Horizontal

increment: 10 km

• 4. The number of

σ - layers: 21

• 5. Lake size:

50*100 км

• 6. Synoptic

speed 0 м/с The integration started at 6:00

Vertical size of the breeze cell ~2 km The distance, that breeze penetrates into land ~50 km;

50000 100000 150000 200000 250000 300000 350000

X, km

50000 100000 150000 200000 250000 300000 350000

Y, km

Nocturnal Nocturnal breeze over single lake, breeze over single lake, wind field in surface layer at wind field in surface layer at 2nd day, 4:00 am

50000 100000 150000 200000 250000 300000 350000

X, km

50000 100000 150000 200000 250000 300000 350000

Y, km

50000 100000 150000 200000 250000 300000 350000

X, km

50000 100000 150000 200000 250000 300000 350000

Y, km

I. Absorption of the longwave radiation in atmosphere is turned OFF II. Absorption of the longwave radiation in atmosphere is turned ON

0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1 1.1 1.2 1.3

,m/s U r

Time evolution of maximal tracer concentration in surface layer in the case of single lake

I. 1st scenario: local emission at a constant rate – emission scenario

• II. 2d scenario:

large concentration in local area at initial time – explosion scenario

Emission location

Adaptation of the model to a territory of interest

Surface parameters to be specified:

1. the height above sea level; 2. roughness length; 3. albedo; 4. percentage of vegetated area; 5. percentage of water area; 6. water bodies depth; 7. the depth of soil; 8. loam fraction in soil; 9. sand fraction in soil;

• 10. vegetation type;
• 11. leaf area index;
• 12. stomatal resistance;

Datasets:

Relief – Digital elevation model (DEM)

http://edc.usgs.gov/products/elevation/gtopo30/gt

• po30.html

Water bodies – Global land cover (GLC) 2000.

http://www-gvm.jrc.it/glc2000/ Initial conditions:

1. moisture intercepted by vegetation at initial time; 2. soil moisture at initial time; 3. soil temperature at initial time; 4. water temperature at initial time. Two regions in WS are selected: 1) 54.5 54.5 – – 58 58.6 .6 ° ° N N, 63.1 , 63.1 – – 66.6 66.6 ° ° E E 2) 60 – 62 º N, 73 – 77 º E (includes Surgut & Nizhnevartosk)

Hydrologically heterogeneous territory Hydrologically heterogeneous territory Western Siberia, Western Siberia, 54.5 54.5-

• 58.6

58.6 ° ° N N, 63.1 , 63.1-

• 66.6

66.6 ° ° E E

1.

• 1. The domain

The domain: : 355*355 355*355 km km; ; 2.

• 2. The grid

The grid: : 96*96 96*96 points points; ; 3.

• 3. Horizontal

Horizontal resolution resolution: : 3.7 3.7 km km 4.

• 4. Number of

Number of σ σ -

• levels

levels: 21 : 21

• 150
• 100
• 50

50 100 150

X, км

• 150
• 100
• 50

50 100 150

Y, км

• 5

5 15 25 35 45 55 65 75 85 95 105 115 125 135 145

H, м

Wind in surface layer Wind in surface layer in the 1 in the 1st

st region of

region of Western Siberia Western Siberia

• 150
• 100
• 50

50 100 150

• 150
• 100
• 50

50 100 150

Y, км 0.2 0.4 0.6 0.8 1 1.2 1.4 1.6 1.8 2 2.2 2.4 2.6 |U|, м/с

Wind in surface layer in 2 Wind in surface layer in 2nd

nd region of

region of Western Siberia Western Siberia

1.

• 1. The domain

The domain: : 178 178* *178 178 km km; ; 2.

• 2. The grid

The grid: : 48 48* *48 48 points points; ; 3.

• 3. Horizontal

Horizontal resolution resolution: : 3.7 3.7 km km 4.

• 4. The number

The number

• f
• f σ

σ – – levels levels: : 21 21

20000 40000 60000 80000 100000 120000 140000 160000 180000

X, m

20000 40000 60000 80000 100000 120000 140000 160000 180000

Y, m

0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1 1.1 1.2 1.3 1.4 1.5 1.6 1.7 1.8 1.9

|U|, м/с

The concentration of passive tracer in the surface layer

X, m

Y, m

X, m

Y, m

X, m

Y, m

X, m

Y, m

1st day, 15:00 2nd day, 4:00

«Explosion» scenario

max

42150 q =

max

17495 q =

max

41050 q =

max

3765 q =

X, km

Y, km

X, km

Y, km

X, km

Y, km

X, km

Y, km

1st day, 15:00 2nd day, 4:00

The concentration of passive tracer in the surface layer «Emission» scenario

5 15 25 35 45 55 65 75 85 95 105 115 125 135 145 155 165

max

29.38 q =

max

160.23 q =

max

23.50 q =

max

85.11 q =

5 10 15 20 25 30

10000 100000

homogeneous land hydrologically heterogeneous land Maximal tracer concentration

Time, hours

Time evolution of maximal concentration

• f a tracer in surface layer

5 10 15 20 25 30 20 40 60 80 100 120 140 160 180

homogeneous land hydrologically heterogeneous land

Maximal tracer concentration Time, hours

“Emission” scenario “Explosion” scenario

Conclusions

• the numerical model “atmosphere – land – water

reservoirs” shows satisfactory skill to simulate daytime breezes in midlatitudes;

• longwave radiation heat exchange is the crucial

mechanism for night breeze development;

• it is shown that breeze circulations over hydrologically

heterogeneous land significantly reduce tracer concentrations (up to several times);

Future work

1) The study of synoptic-scale wind effect on tracer transport; 2) Changing the advection-diffusion numerical scheme: monotonous with higher-order spatial and temporal derivatives (e.g. 3rd order Adams-Bashford scheme); 3) Comparison of the model with measurements!

Thank you for attention!

Future work

1) The study of synoptic-scale wind effect on tracer transport; 2) Inclusion of TKE-equation in turbulence scheme; 3) Changing the advection-diffusion numerical scheme: monotonous with higher-order spatial and temporal derivatives (e.g. 3rd order Adams-Bashford scheme); 4) Comparison of the model with measurements!

20000 40000 60000 80000 100000 120000 140000 160000 180000

X, m

500 1000 1500 2000

Z, m

500 1000 1500 2000 2500 3000 3500 20000 40000 60000 80000 100000 120000 140000 160000 180000

X, m

500 1000 1500 2000

Z, m

500 1000 1500 2000 2500 3000 3500 4000 4500 5000 5500 6000

Tracer concentration in the vertical cross-section of domain Homogeneous land Hydrologically heterogeneous land

2nd day, 4:00 am

• 150
• 100
• 50

50 100 150

X, km

2 4

Z, km

• 2 m/s
• 1.9 m/s
• 1.8 m/s
• 1.7 m/s
• 1.6 m/s
• 1.5 m/s
• 1.4 m/s
• 1.3 m/s
• 1.2 m/s
• 1.1 m/s
• 1 m/s
• 0.9 m/s
• 0.8 m/s
• 0.7 m/s
• 0.6 m/s
• 0.5 m/s
• 0.4 m/s
• 0.3 m/s
• 0.2 m/s
• 0.1 m/s

0 m/s 0.1 m/s 0.2 m/s 0.3 m/s 0.4 m/s 0.5 m/s 0.6 m/s

Zonal speed component Zonal speed component in the y=const plane in the y=const plane

• 150
• 100
• 50

50 100 150

X, km

2 4

Z, km

295 K 296 K 297 K 298 K 299 K 300 K 301 K 302 K 303 K 304 K 305 K 306 K 307 K 308 K 309 K 310 K 311 K 312 K 313 K 314 K 315 K 316 K 317 K 318 K 319 K 320 K 321 K 322 K

Potential temperature Potential temperature in the plane y=const in the plane y=const