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

International conference and young scientists school CITES-2007, Tomsk Lomonosov Moscow State University V. . M M. . Stepanenko Stepanenko, , V D. . N N . . Mikushin Mikushin D Numerical simulation Numerical simulation of dynamics of atmosphere of atmosphere of dynamics and tracer transport and tracer transport above hydrologically heterogeneous land above hydrologically heterogeneous land 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 observations – the numerical simulation is the only tool to study these circulations.

The goal Numerical estimation of breeze circulations and passive tracer transport over hydrologically heterogeneous land The tool Numerical model «atmosphere – land – water reservoir» Tasks • 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.

Numerical model «atmosphere – land – water reservoir» Lake model Atmospheric model Land surface model 3D non-hydrostatic Two-layer 1D model of heat and model in σ - coordinates model of mass transfer Nh3d (Miranda, 1990) heat and moisture (Stepanenko & Lykosov, transfer 2005) in soil and vegetation S U E a ISBA (Meteo-France) E s H,LE (Mahfouf et al., 1995) E tr Snow RAIN SNOW v e g ( E r 1 - p snv ) P r (1-veg)(1-p sng ) P r p sn P r Ice LIQ. WAT. RETAINED ON THE CANOPY (W r ) P S E S p sn R veg (1-p sn ) R veg Water New options: freez s melt s SNOW E g (W S ) 1) Parameterization of LIQ. WAT. IN SNOW (W L ) R surf SOIL LIQUID WATER (w 2 ) R snow shortwave melt g freez g radiation Clirad-SW FROZEN WATER IN SOIL (w F ) Soil (Chou & Suarez, 2002) ; Drain 2) Parameterization of longwave radiation Clirad-LW (Chou & Suarez, 2003)

Modeling of passive tracer transport ∂ ∂ ∂ ∂ ( ) ( ) ( ) ( ) ( ) + + + σ = + & qp uqp vqp qp p D R ∂ ∂ ∂ ∂ σ * * * * * q q t x y = − p p p * surf top - Diffusion term (1 st order turbulence closure), D q R - Rayleigh damping term q ∂ ∂ q q + = C 0 - at lateral boundaries Boundary conditions: ∂ ∂ t n ∂ q = 0 - at the top ∂ σ Numerical scheme: 1) Spatial derivatives – 2 nd order central differences; 2) Time integration – «leap-frog» scheme; 3) Filtration of the numerical mode – Asselin filter; 4) Nonlinear instability suppression – spatial 4 th order filters   Shortcoming of the scheme : + + = n 1 n 1   q max 0, q   non-monotonous, applying the condition

Daytime breeze over single lake: Daytime breeze over single lake: 1. The domain: st day, 15:00 wind field in surface layer at 1 st day, 15:00 360*360 km; wind field in surface layer at 1 2. Grid dimensions: 36*36 points; 350000 3. Horizontal increment: 10 km 300000 4. The number of σ - layers: 21 250000 5. Lake size: Y, km 50*100 км 200000 6. Synoptic speed 0 м / с 150000 The integration started 100000 at 6:00 Vertical size of the breeze cell ~2 km 50000 The distance, that breeze 50000 100000 150000 200000 250000 300000 350000 penetrates into land ~50 km; X, km

Nocturnal breeze over single lake, breeze over single lake, Nocturnal wind field in surface layer at 2 nd day, 4:00 am wind field in surface layer at I. Absorption of the II. Absorption of the longwave radiation longwave radiation in atmosphere in atmosphere r is turned OFF is turned ON U ,m/s 1.3 350000 350000 1.2 1.1 300000 300000 1 0.9 250000 250000 0.8 Y, km Y, km 200000 0.7 200000 0.6 150000 150000 0.5 0.4 100000 100000 0.3 0.2 50000 50000 0.1 50000 100000 150000 200000 250000 300000 350000 50000 100000 150000 200000 250000 300000 350000 X, km X, km

Time evolution of maximal tracer concentration in surface layer in the case of single lake 350000 1 st scenario: II. 2d scenario: 300000 I. large concentration 250000 local emission Y, km in local area at initial time 200000 at a constant rate – – explosion scenario 150000 emission scenario 100000 Emission location 50000 50000 100000 150000 200000 250000 300000 350000 X, km

Adaptation of the model to a territory of interest Surface parameters Initial conditions: to be specified: 1. moisture intercepted by 1. the height above sea level; vegetation at initial time; 2. roughness length; 2. soil moisture at initial time; 3. albedo; 3. soil temperature at initial time; 4. percentage of vegetated area; 4. water temperature at initial time. 5. percentage of water area; 6. water bodies depth; Datasets: 7. the depth of soil; 8. loam fraction in soil; Relief – 9. sand fraction in soil; Digital elevation model (DEM) 10. vegetation type; 11. leaf area index; http://edc.usgs.gov/products/elevation/gtopo30/gt 12. stomatal resistance; opo30.html Two regions in WS are selected: Water bodies – Global land cover (GLC) 2000. 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 http://www-gvm.jrc.it/glc2000/ (includes Surgut & Nizhnevartosk)

Hydrologically heterogeneous territory Hydrologically heterogeneous territory Western Siberia, 54.5 54.5- -58.6 58.6 ° ° N N, 63.1 , 63.1- -66.6 66.6 ° ° E E Western Siberia, H, м 150 1. The domain The domain: : 1. 145 135 355*355 km km; ; 355*355 100 125 115 105 50 2. The grid The grid: : 2. 95 85 96*96 points points; ; 96*96 75 Y, км 0 65 55 3. Horizontal Horizontal 3. 45 35 -50 resolution: : 3.7 3.7 km km resolution 25 15 5 -100 -5 4. Number of Number of 4. σ - σ - levels levels: 21 : 21 -150 -150 -100 -50 0 50 100 150 X, км

st region of in the 1 st Wind in surface layer in the 1 region of Wind in surface layer Western Siberia Western Siberia 150 |U|, м / с 100 2.6 2.4 2.2 50 2 1.8 Y, км 0 1.6 1.4 1.2 -50 1 0.8 0.6 -100 0.4 0.2 -150 -150 -100 -50 0 50 100 150

nd region of Wind in surface layer in 2 nd region of Wind in surface layer in 2 Western Siberia Western Siberia 180000 1. The domain The domain: : 1. |U|, м / с 160000 178* *178 178 km km; ; 178 1.9 1.8 140000 1.7 1.6 2. The grid The grid: : 2. 1.5 120000 1.4 48* *48 48 points points; ; 1.3 48 1.2 1.1 100000 Y, m 1 0.9 3. Horizontal Horizontal 3. 0.8 80000 0.7 resolution: : resolution 0.6 0.5 3.7 km km 3.7 60000 0.4 0.3 0.2 40000 0.1 4. The number The number 4. σ – of σ – levels levels: : of 20000 21 21 20000 40000 60000 80000 100000 120000 140000 160000 180000 X, m

The concentration of passive tracer in the surface layer 180000 180000 «Explosion» 160000 160000 44000 42000 42000 40000 40000 140000 scenario 140000 38000 38000 36000 36000 34000 34000 32000 120000 120000 32000 30000 30000 28000 28000 26000 1 st day, 26000 24000 100000 100000 Y, m Y, m 24000 22000 20000 22000 18000 20000 15:00 80000 16000 18000 80000 14000 16000 12000 14000 10000 12000 60000 8000 60000 10000 = 6000 8000 q 42150 4000 = 6000 2000 4000 q 41050 40000 40000 max 2000 max 20000 20000 20000 40000 60000 80000 100000 120000 140000 160000 180000 20000 40000 60000 80000 100000 120000 140000 160000 180000 X, m X, m 180000 180000 160000 160000 17500 140000 140000 16500 3500 15500 14500 3000 120000 120000 13500 2 nd day, 12500 11500 2500 10500 100000 100000 Y, m Y, m 4:00 9500 2000 8500 7500 80000 80000 6500 1500 5500 4500 60000 60000 1000 = 3500 q 17495 2500 = 1500 40000 500 40000 q 3765 max 500 max 20000 20000 20000 40000 60000 80000 100000 120000 140000 160000 180000 20000 40000 60000 80000 100000 120000 140000 160000 180000 X, m X, m