out_usa_shs_rlme_a_shsr_0.2Pot. Temperature [K]SN06.02.2008 00UTC + 06h -92 Eout_usa_shs_rlme_a_shsr_1.0= (dissipation)1/3frontal zoneincreased turbulence activity due to horizontal wind shearMatthias RaschendorferMoscov: 06-10.09.2010COSMO

moderate light SN06.02.2008 00UTC + 06h -77 Emountain ridgeSSO-effect in TKE budgetout_usa_rlme_tkessoout_usa_rlme_ssoout_usa_rlme_tkesso out_usa_rlme_ssoMIN = 0.00104324 MAX = 10.3641 AVE = 0.126079 SIG = 0.604423MIN = 0. 00109619 MAX = 10.3689 AVE = 0.127089 SIG = 0.804444MIN = -0.10315 MAX = 0.391851 AVE = 0.00100152 SIG = 0.00946089= (dissipation)1/3increased turbulence activity due to generation of SSO wakesMatthias RaschendorferMoscov: 06-10.09.2010COSMO

Task 3a: Results (Coupling turbulence and convection)Formal separation of isotropic turbulence from convection within the framework of 2nd order equations is completed [incl. application of double filtering, development of separate equations with scale interaction terms relating turbulence to non-turbulent sub-grid scale structures such as convection]

Proposal towards a reformulated scale interactive convection scheme is developed [incl. budget equations for 3 convective sub-domains in advection form, vertical velocity equation instead of mass flux equation, construction constraints defining the sub-domains instead of parameterization of dynamic de- and entrainment, boundary conditions for convective cells derived from turbulence properties instead of using artificial constraints, initial up- and downdraft at each level without a discrimination between deep and shallow convection, solution for convective volume fractions, intrinsic cut-off against turbulence and grid-scale convection, convective corrections of non linear source terms, overlap of turbulent (Gaussian) probability density for turbulent corrections of non linear source terms, convective source term for TKE (scale interaction term) being the related sink for convective kinetic energy by lateral mixing (de- and entrainment)]

Task 2b: Veniamin Perov and Oleg Evteev Work Content Comprehensive testing against observational and LES data of the new formulation of the non-local turbulence length scale through single-column numerical experiments Testing of the new length-scale formulation within full 3D COSMO model Verification of results in different weather situations

Results An algorithm for computing the non-local turbulence length scale on the basis of parcel displacement method is implemented; the new algorithm is more physically justified than the currently used algorithm based on the Blackadar formula The module TURBDIFF of the COSMO-model code is modified Comparison of model results with the radiosonde and profiler data is performed for the summer season Results show that the model with the new formulation for the turbulence length scale gives the temperature and velocity fields closer to the observational data as compared to the current COSMO-model formulation

Task 2b: Results Vertical profiles of (potential) temperature computed with the current (blue) and new (red left panel, green right panel) formulations for the turbulence length scale. Observational data are shown with the black (left) and red (right) curves.

Task 2b: Results (contd)T2m difference (New L Ref) for Moscow area, 17.07.2009 12UTC

Task 3b: Euripides Avgoustoglou (with Matthias Raschendorfer) Work ContentSystematic evaluation of the performance of the SGS cloud schemes (including water-ice mixed phase implemented by Matthias, see next slide) in terms of cloud cover, T2m, Td2m, and radiation budget at the surface Critical assessment of the suitability of the statistical cloud scheme for use in radiation calculations

Results Various configurations/combinations of the SGS cloud schemes are tested (RH vs. statistical a l Sommeria and Deardorff, different treatment of cloud ice, water-ice mixed phase at sub-grid scales)Results are not conclusive but there are indications in favour of (somewhat) more physically plausible configurations

Matthias RaschendorferDWDCOSMO Cracow 2008turbulent kinetic energy [m^2/s^2] Lon -5 5.5 Lat -5 6.5Effect of SGS release of icing heat

METEOSATRHSGS_defSGS_mixSGS_lowSGS_RH

2 Jan 2005Station #RHSGS_defSGS_E-7SGS_mixSGS_lowSGS_RH

observRHSGS_defSGS_E-7SGS_mixSGS_lowSGS_RH

2

8.410.6310.6310.6310.6310.6310.63

7.610.269.949.949.899.910.08

78.518.058.057.498.018.31

77.876.96.886.376.847.48

67.536.56.465.636.427.16

67.926.556.545.886.57.48

5.67.936.956.956.46.927.52

7.28.947.687.697.117.688.63

02_129.999.248.878.659.39.55

02_158.697.817.847.867.938.23

5.86.696.236.246.256.256.41

5.45.284.834.914.974.915.16

03_005.555.035.044.984.944.97

03_034.774.674.734.754.64.49

03_065.334.814.924.564.854.69

03_097.666.746.75.96.727.02

03_129.218.948.858.318.868.8

observations

grid

subgrid_def

subgrid_E-7

subgrid_R

subgrid_gs

subgrid_2_4

day_time

T_2m (degs C)

Stat # 624 (Chrisoupoli) 01-03 Jan 2005

T_TD_2M

60609.589.589.589.589.589.586.056.056.056.056.056.05

60638.638.48.48.428.48.474.994.794.794.834.794.91

60667.276.586.586.516.556.943.823.213.23.193.183.55

60696.035.095.095.175.045.342.571.491.51.571.481.83

606125.023.863.853.693.784.372.051.071.081.051.011.36

606153.882.452.462.362.442.861.380.250.250.280.190.55

606182.971.721.721.651.71.90.69-0.4-0.4-0.39-0.43-0.23

606215.14.084.083.994.054.351.640.720.720.590.70.98

606248.057.237.227.057.27.433.352.612.62.362.572.81

606276.35.585.585.495.585.872.892.342.352.352.362.66

606304.023.413.423.353.423.70.920.520.520.490.520.67

606332.832.562.572.442.552.54-0.33-0.57-0.59-0.54-0.59-0.44

606362.222.032.032.0622.07-0.98-0.73-0.7-0.65-0.74-0.9

606391.951.891.941.931.91.82-1.21-1.19-1.2-1.16-1.28-1.19

606422.171.951.931.941.921.88-1.97-1.71-1.66-1.49-1.73-1.69

606454.023.463.473.383.363.440.03-0.37-0.34-0.35-0.42-0.34

606487.887.587.596.577.517.4533.013.082.543.022.9

60706.626.626.626.626.626.623.473.473.473.473.473.47

60736.686.746.736.686.736.82.392.892.92.772.892.93

60765.525.035.034.75.015.231.991.691.691.381.681.78

60795.234.354.344.244.314.861.660.830.840.920.821.3

6071254.214.214.064.194.590.6-0.12-0.090.02-0.090.28

607154.773.433.493.513.454.290.15-0.78-0.75-0.89-0.77-0.2

607183.672.312.362.552.362.73-0.92-1.75-1.7-1.85-1.7-1.55

607215.164.34.3144.284.580.75-0.25-0.24-0.62-0.27-0.07

607246.475.625.615.385.595.942.921.971.971.961.942.15

607274.663.843.833.683.834.13.422.432.432.362.392.63

607303.363.033.042.883.053.220.530.640.620.720.60.31

607332.692.282.312.222.292.5-2.13-2.98-3.06-3.16-3.07-2.8

607362.32.062.042.142.012.12-3.21-3.48-3.33-3.46-3.34-3.33

607392.592.142.132.162.152.24-1.86-1.92-1.89-1.99-1.9-1.9

607423.262.562.522.582.522.8-1.28-1.38-1.35-1.55-1.33-1.31

607455.194.143.93.534.084.650.81-0.75-1.08-1.31-0.950.23

607487.026.636.595.436.596.642.542.322.341.172.342.27

61404.64.64.64.64.64.62.182.182.182.182.182.18

61434.534.554.544.344.544.571.911.981.971.841.971.94

61463.733.713.72.963.73.711.571.561.560.971.571.59

61493.53.273.272.713.243.351.261.121.120.561.11.16

614123.383.012.992.12.993.270.990.630.660.010.640.83

614151.851.391.391.021.381.52-0.5-1.06-1.05-1.48-1.06-0.81

614181.10.610.610.410.620.77-1.74-2.29-2.31-2.58-2.33-2.11

614212.31.621.621.341.621.77-1.09-1.49-1.54-1.83-1.54-1.43

614245.915.575.575.315.575.70.590.480.490.490.490.48

614274.494.164.154.054.154.260.890.610.610.570.610.7

614301.711.611.621.621.611.61-0.18-0.34-0.35-0.38-0.34-0.29

614331.471.261.261.451.231.3-1.26-1.55-1.57-1.57-1.59-1.52

614360.830.690.70.810.660.64-2.42-2.48-2.49-2.41-2.53-2.64

614390.510.220.230.410.180.29-2.63-2.73-2.74-2.64-2.78-2.82

614420.250.210.210.260.17-0.25-2.48-2.66-2.67-2.61-2.72-2.84

614451.821.431.431.431.421.47-1.3-1.29-1.28-1.2-1.31-1.37

614484.854.464.463.574.454.560.860.30.31-0.230.270.49

61909.449.449.449.449.449.443.153.153.153.153.153.15

61938.158.028.028.017.988.013.993.983.983.973.963.98

61966.456.16.15.866.066.043.072.972.972.92.952.89

61995.033.733.733.093.74.42.141.331.330.951.311.71

619124.693.333.332.793.2341.60.720.720.390.651.1

619153.89221.671.92.851.180.050.05-0.1-0.040.47

619182.291.291.291.171.271.490.21-0.57-0.57-0.7-0.6-0.39

619215.224.054.053.783.994.481.370.420.420.220.370.81

619248.797.927.927.757.898.232.121.751.751.591.741.91

619277.556.756.756.536.726.992.391.791.781.521.742.01

619304.654.114.123.954.14.371.621.111.120.951.11.29

619333.433.253.243.173.213.10.820.620.650.340.560.49

619362.892.9833.432.842.7-0.3-0.55-0.55-0.17-0.55-0.53

619392.161.9922.081.911.97-0.81-0.86-0.86-0.61-0.92-0.91

619422.091.661.681.771.621.65-0.91-1.11-1.11-0.84-1.17-1.14

619455.113.983.984.223.824.030.51-0.05-0.050.39-0.18-0.04

619488.468.248.227.498.158.042.82.552.572.692.562.55

62209.459.459.459.459.459.454.514.514.514.514.514.51

62238.528.378.378.338.348.353.793.793.793.793.793.81

62266.876.526.536.516.486.633.693.553.553.413.533.65

62295.284.584.584.584.544.621.711.321.321.211.31.38

622125.023.953.943.643.94.71.040.670.670.450.640.84

622154.373.023.022.933.740.620.090.09-0.010.050.32

622183.132.252.252.182.252.520.28-0.41-0.41-0.51-0.43-0.2

622215.424.644.644.524.624.90.1-0.32-0.32-0.5-0.33-0.18

622248.037.327.327.157.37.561.010.480.470.250.450.63

622276.96.216.216.036.196.491.761.441.441.261.441.65

622304.63.963.974.043.954.21.581.151.161.021.161.35

622333.172.822.812.982.782.871.130.920.940.930.920.97

622362.712.892.923.272.692.490.670.780.790.940.640.54

622392.42.332.372.72.32.270.170.220.240.420.170.12

622422.782.572.572.722.522.480.280.110.120.270.080.13

622455.915.35.35.325.255.341.210.90.921.040.870.92

622488.688.48.427.938.358.222.412.32.292.362.242.18

624010.6310.6310.6310.6310.6310.636.26.26.26.26.26.2

624310.269.949.949.899.910.084.724.214.214.174.194.24

62468.518.058.057.498.018.315.014.824.824.54.84.91

62497.876.96.886.376.847.484.263.583.573.093.544.04

624127.536.56.465.636.427.163.562.462.472.242.443.11

624157.926.556.545.886.57.483.542.992.992.642.993.32

624187.936.956.956.46.927.523.653.513.543.273.523.6

624218.947.687.697.117.688.634.23.943.963.713.964.22

624249.999.248.878.659.39.554.554.113.923.914.194.45

624278.697.817.847.867.938.234.764.44.314.224.284.45

624306.696.236.246.256.256.412.632.452.522.772.452.55

624335.284.834.914.974.915.160.710.790.981.20.950.7

624365.555.035.044.984.944.970.130.080.270.130.03-0.29

624394.774.674.734.754.64.49-0.84-0.75-0.64-0.57-0.8-0.95

624425.334.814.924.564.854.69-0.29-0.13-0.030.06-0.18-0.61

624457.666.746.75.96.727.022.021.791.81.741.721.68

624489.218.948.858.318.868.82.962.982.982.832.942.65

62709.759.759.759.759.759.756.726.726.726.726.726.72

62738.327.97.97.897.97.95.935.665.675.685.675.67

62767.596.786.776.716.716.785.094.254.244.224.24.3

62797.647.197.156.827.147.265.475.145.114.925.115.21

627127.466.886.96.016.897.065.264.954.974.454.935.06

627157.056.156.175.156.186.564.64.14.143.584.164.36

627186.455.225.164.645.195.643.933.363.382.953.393.46

627218.247.777.627.257.668.093.673.253.43.433.343.51

627249.849.519.549.29.529.883.192.852.972.582.943.08

627279.28.438.367.638.378.863.313.553.743.453.683.36

627306.525.745.675.055.715.993.83.483.42.323.443.8

627334.534.014.023.814.034.250.40.240.330.370.380.45

627363.733.433.463.723.443.43-0.35-0.58-0.62-0.47-0.66-0.58

627393.453.173.173.493.143.11-0.45-0.91-0.91-0.44-0.95-0.72

627423.373.383.423.643.413.3-0.23-0.62-0.59-0.01-0.63-0.5

627455.975.235.455.35.245.611.460.941.081.730.981.16

627488.478.038.077.347.998.213.83.913.843.343.773.73

62803.53.53.53.53.53.51.541.541.541.541.541.54

62833.123.163.153.13.143.171.341.291.321.331.331.3

62862.542.132.121.982.122.261.361.0111.0811.09

62892.211.941.631.561.5721.921.941.631.561.572

628121.631.371.221.181.191.471.551.291.191.161.171.38

628151.31.241.120.71.11.320.871.080.990.610.971.12

628181.461.131.11.021.081.27-0.52-1-1.05-1.04-1-0.62

628211.721.371.381.281.361.77-2.77-2.87-2.88-2.85-2.8-2.49

628243.743.433.413.33.413.53-0.4-0.51-0.52-0.51-0.5-0.4

628271.791.321.311.151.311.610.530.270.21-0.130.250.25

628301.050.820.790.780.810.9-0.86-1.07-1.13-1.19-1.07-0.93

628330.910.950.981.030.940.88-3.76-3.31-3.34-3.29-3.49-3.76

628361.20.720.70.880.640.54-6.49-5.34-5.4-5.12-5.49-5.58

628390.190.420.410.630.380.35-5.88-5.02-5.08-4.71-5.19-5.29

628420.310.390.40.510.360.33-4.64-4.48-4.48-4.19-4.53-4.54

628451.751.661.661.681.641.67-1.57-1.45-1.5-1.79-1.48-1.36

628484.434.394.374.284.344.420.440.450.470.510.440.54

63204.954.954.954.954.954.951.611.611.611.611.611.61

63234.213.963.963.743.954.041.591.561.561.421.561.62

63262.812.052.041.222.042.571.631.171.160.51.161.49

63291.80.740.730.60.71.110.42-0.28-0.28-0.53-0.310.03

632121.190.590.60.420.580.93-0.5-0.94-0.95-1.08-0.97-0.7

632150.4-0.33-0.33-0.41-0.310.04-1.42-2.03-2.04-2.43-2.12-1.74

63218-0.35-0.91-0.91-1.05-0.89-0.69-1.94-2.6-2.6-3.05-2.67-2.32

632210.880.320.330.20.290.57-1.74-2.04-2.05-2.17-2.08-1.94

632244.073.583.593.53.593.8-1.62-2.17-2.18-2.32-2.19-2.07

632272.331.941.941.861.942.140.06-0.33-0.33-0.48-0.34-0.16

632301.070.750.750.740.750.89-0.94-1.23-1.23-1.34-1.25-1.14

632330.470.10.10.20.090.22-1.47-1.74-1.73-1.83-1.76-1.69

63236-0.03-0.27-0.25-0.12-0.31-0.33-1.74-2.11-2.12-2.17-2.15-2.16

63239-0.41-0.6-0.58-0.42-0.61-0.59-2.44-2.47-2.47-2.37-2.52-2.6

63242-0.59-0.82-0.8-0.71-0.83-0.82-2.73-2.66-2.67-2.56-2.71-2.82

632450.960.630.630.590.60.65-1.08-1.15-1.14-0.91-1.19-1.19

632483.563.073.072.383.063.170.270.120.140.260.10.09

641011.7511.7511.7511.7511.7511.757.687.687.687.687.687.68

641311.1911.1411.131111.1311.127.537.567.567.487.577.55

641610.499.869.869.789.859.997.057.157.167.057.147.08

64199.719.569.559.679.539.247.116.986.957.156.946.69

641129.498.488.418.548.418.297.046.346.256.46.275.98

641158.857.887.847.827.787.786.195.625.565.545.525.58

641188.467.597.577.557.517.485.144.684.64.544.534.48

6412110.249.659.649.599.619.626.556.156.146.116.095.89

6412411.6511.3411.3211.1811.3411.455.475.35.275.255.255.42

641279.519.279.279.29.279.355.495.145.145.15.145.29

641308.338.198.198.138.148.124.674.54.54.424.474.5

641337.697.887.888.187.77.454.594.844.845.14.74.52

641367.257.127.127.377.066.994.424.394.394.634.354.25

641397.096.986.987.096.946.924.54.354.364.424.354.34

641426.796.726.726.836.686.633.142.992.983.062.982.98

641459.028.918.919.048.888.824.324.144.154.344.144.14

6414810.8210.8210.8210.9110.7910.724.584.584.594.994.544.6

64205.895.895.895.895.895.893.893.893.893.893.893.89

64235.685.525.515.255.475.663.052.982.982.792.963.04

64264.744.14.093.994.094.381.941.471.471.221.461.67

64294.613.533.523.63.514.411.630.90.890.860.861.28

642124.223.363.293.233.23.472.081.491.461.51.361.67

642153.742.942.692.842.932.741.760.970.890.960.930.98

642182.992.492.482.192.482.541.080.320.320.230.330.58

642214.572.952.872.732.983.551.830.620.560.470.651.14

642246.916.136.126.026.16.341.941.481.471.461.491.76

642275.214.724.724.654.714.833.32.772.782.782.772.87

642303.152.732.722.642.712.831.41.121.11.031.111.23

642332.122.22.232.32.122.01-0.09-0.11-0.11-0.13-0.15-0.21

642362.52.522.522.752.432.53-2.37-2.1-2.17-1.98-2.28-2.58

642391.631.661.661.821.621.53-3.46-3.47-3.48-3.13-3.57-3.68

642421.361.341.351.621.291.23-3.79-3.72-3.74-3.48-3.8-3.87

642452.872.692.692.722.682.7-2.18-2.26-2.29-2.37-2.31-2.27

642486.796.576.576.636.526.540.870.860.810.690.750.72

643011.7511.7511.7511.7511.7511.755.885.885.885.885.885.88

643311.311.2411.2411.2311.211.176.526.646.646.626.636.63

643610.6910.410.410.2910.3510.3377.077.077.117.077.04

64399.939.239.249.159.229.246.96.776.766.696.746.81

643129.779.349.289.319.189.187.636.466.456.376.426.52

643159.938.898.878.798.818.876.776.166.176.146.126.14

643188.978.078.067.998.058.146.395.695.665.595.635.76

6432110.539.979.979.919.9610.046.295.75.665.595.695.88

6432412.3211.8911.911.8411.911.985.424.954.94.884.915.12

6432711.1710.8510.8410.7510.8510.966.295.875.915.925.915.91

643309.899.629.629.579.619.677.076.846.826.786.826.88

643338.598.628.618.848.498.345.385.195.185.185.165.23

643368.027.987.988.447.837.714444.063.923.87

643397.157.077.097.297.016.954.554.854.925.314.824.62

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Stat # 650 (Limnos) 01- 03 Jan 2005

Task 1: Ekaterina Machulskaya and Dmitrii Mironov Work Content Testing against observational and LES data and consolidation of a second-order closure model of a moist PBL, including transport equations for the TKE and for the scalar variances and a sub-grid scale statistical cloud scheme for non-precipitating clouds Implementation of the best-compromise version of the new closure model (in terms of physical realism and computational stability and efficiency) into the COSMO model, testing within the single-column COSMO framework

Results Single-column tests show that the use of TKE-scalar variance scheme yields some improvements as to fractional cloud cover, second-moment profiles, and evolution of turbulence moments in time; a number of problems remain Modified SGS statistical cloud scheme (effect of shallow cumuli following Bechtold et al. 1995) is tested through parallel experiments; scores are neutral to slightly positive TKE-scalar variance scheme is implemented into three-dimensional COSMO model, parallel experiment is being performed, performance is monitored, results of verification will be reported later

Single-Column Tests: Shallow CumuliFractional cloud cover (upper row) and cloud water content (lower row) in BOMEX.Red TKE scheme, blue TKE-scalar variance scheme. Black solid curves in the middle figures show LES data. GaussianGaussianskewedskewed

Modified SGS Statistical Cloud Scheme Parallel Experiments (COSMO-EU)T2m over COSMO-DE domain in January 2010 (00UTC forecasts).Red Exp7680, blue COSMO-EU. Total cloud cover (left) and low-level cloud cover (right) over COSMO-EU domain in June 2010. Red Exp7692, blue COSMO-EU.

LES and Modelling of SBL over Heterogeneous and Homogeneous Surfaces by D. Mironov, P. Sullivan (NCAR) and E. Machulskaya Blue homogeneous SBL, red heterogeneous SBL.

Tiled TKE-Temperature Variance Closure ModelTransport (prognostic) equations for TKE and for the temperature variances including third-order transport Algebraic (diagnostic) formulations for temperature flux, for the Reynolds-stress components, and for turbulence length scale Tile approach where different tiles have different surface temperature Surface fluxes are computed as weighted means of fluxes over individual tiles is non-zero at the surface in heterogeneous SBL Input parameters of numerical experiments are similar to LES (except for piece-wise vs. sinusoidally varying surface temperature)

Tiled TKE-Temperature Variance Model: Results Blue homogeneous SBL, red heterogeneous SBL.

Plans for the Next COSMO YearTask 1. Ekaterina Machulskaya and Dmitrii Mironov Consolidation of the TKE-scalar variance scheme (based on the results obtained in 2010) Testing of the new scheme through numerical experiments within the framework of the full-fledged three-dimensional COSMO model, further single-column tests as needed Analysis of results from numerical experiments, comparison with observational and numerical data, tuning of the new scheme Preparation of documentation

Plan for the Next COSMO Year (contd)Task 2a. Matthias Raschendorfer Detailed component testing of the COSMO-model turbulence scheme with the COSMO-SC, using measurement data (for forcing and verification), 3D-model results (for 3D corrections), and LES results (for forcing, 3D corrections and verification), with the main aim to fix the scheme weaknesses Further development of turbulence and convection schemes with the emphasis on the interaction of turbulence and convection Task 2b. Veniamin Perov and Oleg Evteev Generalization of non-local formulation of the turbulence length scale to account for moist processes (effect on phase changes on the scale of turbulence) Comprehensive testing of a generalized formulation through single-column and 3D experiments, verification of results Task 3. Euripides Avgoustoglou and Matthias Raschendorfer Systematic evaluation of SGS cloud schemes, including water-ice mixed phase, against satellite data

Task 4: Work did not start Work ContentComparison of the cloud condensate diagnosed by the sub-grid scale cloud schemes (statistical and relative-humidity) and by the grid-scale saturation adjustment procedure (following the prognostics equations for the cloud water and cloud ice) Expected Outcome A prerequisite for improving/tuning the statistical SGS cloud scheme and for eventually improving the treatment of the could water and of the cloud ice with due regard for the sub-grid scale processes

Martin Khler (DWD, FE14) plans to perform this work within the framework of ICON, COSMO will benefit

COSMO General Meeting, Moscow, Russia. 6-10 September 2010.

SummaryThe project results obtained so far look satisfactory, although problems remain (e.g. numerical stability, formulation of turbulence length/time scale, SGS cloud cover)The project is expected (hoped) to proceed according to the plan

COSMO General Meeting, Moscow, Russia. 6-10 September 2010.

Thank you for your kind attention!Acknowledgements: Peter Bechtold, Vittorio Canuto, Sergey Danilov, Evgeni Fedorovich, Jochen Frstner, Jean-Francois Geleyn, Vladimir Gryanik, Thomas Hanisch, Donald Lenschow, Chin-Hoh Moeng, Ned Patton, Pier Siebesma, Peter Sulluvan, Jeffrey Weil, and Jun-Ichi Yano.

Appendix

Performance of the COSMO Model Regarding PBL Clouds by Patrick Volker (DWD-Innovationsprogramm) Short summary of three-year DWD project (end date 1 October 2010)Results from the Analysis The overall COSMO performance (mean over long time and/or large domains) with respect to PBL clouds and T2m is satisfactory, however, there are outliers, i.e. forecasts are occasionally very poor COSMO has trouble maintaining low-level clouds during the forecast, particularly in stably-stratified boundary layer (SBL) The SBL structure is not simulated well (mixing is too strong) COSMO tends to produce 2-delta function cloud-cover distribution (all or nothing) instead of fractional cloudiness Good scores often come at the expense of (large) compensating errors, e.g. area-mean T2m bias In the SBL, T2m is often (far) too high already at the beginning of the forecast

Performance of the COSMO Model Regarding PBL Clouds (contd)6-hour COSMO-DE forecast of low-level cloud cover (target times are 0, 3, 6, 9, 12, 15, 18 and 21 UTC) vs. the model initial state (vv=00). Points are the result of time and area averaging (09.10.2010-13.10.2010; 7.3 to 13.3 E, 48.3 to 50.3 N). An optimal forecast (with given initial state) would have all points lying on the diagonal dashed line. Low-level cloud cover from the 10.12.2008 COSMO-EU analysis. Data are averaged over the COSMO-DE numerical domain.

Performance of the COSMO Model Regarding PBL Clouds (contd)2m temperature from the COSMO-EU analysis on 07.10.2009 (left) and 08.10.2010 (right). !!!

Performance of the COSMO Model Regarding PBL Clouds (contd)Vertical temperature profile in the SBL. Left panel measurements at MOL (Lindenberg), right panel COSMO-EU 00 UTC forecast.

Performance of the COSMO Model Regarding PBL Clouds (contd)(Likely) Cause of Trouble and Proposed Remedial Measures Minimum diffusion coefficient Kmin used within COSMO model are far too large Reducing Kmin improves the stably-stratified PBL structure, including clouds, but produces negative (area-mean) T2m biasSince the COSMO-model soil is too diffusive and too strongly coupled to the surface air layer (as data from MOL clearly show, but this may not be quite true for all points), it seems impossible to improve the SBL structure without changing/tuning the soil model parameters (e.g. heat transfer)Sensitivity experiments with the single-column version of COSMO (e.g. perpetual year runs) suggest that the soil heat transfer is too strong in Lindenberg, but seems to be acceptable in Cabauw Further experiments are necessary to appropriately adjust/tune parameters of the soil model (coupled to the PBL) and to account for the effect of soil moisture on heat conductivity

Performance of the COSMO Model Regarding PBL Clouds (contd)Vertical temperature profile simulated by the single-column version of COSMO with a reduced Kmin (0.01 m2/s). 12-hour COSMO-EU forecast of low-level cloud cover (target times are 0 and 12 UTC). Routine vs. experiment with a reduced Kmin (0.01 m2/s). Points are the result of area averaging over COSMO-DE domain.

Performance of the COSMO Model Regarding PBL Clouds (contd)Measured soil heat flux at 10 cm depth at Cabauw during 1987 (data points are 15 h apart) vs. results from simulation with the single-column version of COSMO forced with measured surface fluxes. Vertical temperature profile near the soil-air interface as suggested by measurements at MOL, solid line, vs. typical temperature profile in COSMO.

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