NUMERICAL SIMULATION CLOUDS AND PRECIPITATION CAUSED CATASTROPHIC FLOODS ALONG THE ELBE RIVER IN AUGUST 2002 Krakovskaia S.V., Palamarchuk L.V. and Shpyg V.M. Ukrainian Hydrometeorological Research Institute, Atmosphere Physics Department, Kiev, Ukraine

Objective: To carry out numerical experiments to investigate precipitation formation processes in the frontal cloud system caused catastrophic floods along the Elbe river in August To carry out numerical experiments to investigate precipitation formation processes in the frontal cloud system caused catastrophic floods along the Elbe river in August Main tasks:  To fit combined model of cloudy troposphere (CMCT) to study summer clouds by varying intensity of microphysical precipitation formation processes.  To analyze mesostructure of thermodynamical characteristics with aim to find zones of instability and water vapor resource determined intense precipitation formation in mixed clouds.  To verify CMCT outputs by comparing with the precipitation measurements.  To estimate precipitation forecasting ability of CMCT.

COMBINED MODEL OF CLOUDY TROPOSPHERE (CMCT) CMCT is the combination of 3-D time-independent LAM and 1-D CRM with explicit microphysics, when initial thermodynamical characteristics in the vertical column where microphysics is calculated are continuously updated as it moves along horizontal axes over the initial point of 3-D domain at every time step (dt) in 1-D model on: Minus in equations means that the system moves opposite to the air mass displacement. At the same moment the total column movement in relation to initial point on 3-D domain (X 0, Y 0 ) will be: The speed u f,, v f of this movement could be constant and determined by synoptic charts or variable and calculated from the data of 3-D LAM as an average wind speed in layer up to height Z f, that corresponds to level n:

Pressure, mbTemperature, o C

Ice supersaturation, mg/kgUpdrafts, cm/s

Vertical motions, cm/s Ice supersaturation and wet-instability [pink]

U-wind projection, m/sV-wind projection, m/s

Integral thermodynamic condensation rate as precipitation intensity (mm/h) and ice supersaturation (mm) as vapor reservoir 00 UTC UTC

Integral thermodynamic condensation rate as precipitation intensity (mm/h) and ice supersaturation (mm) as vapor reservoir 12 UTC UTC

Treks of 1D on 3D domain started 00 UTC Treks of 1D on 3D domain at 06 UTC

1-D CLOUD RESOLVING MODEL 1. The kinetic equation of cloud droplets (k=1) size distribution function (f 1 ): 2. The kinetic equation of cloud ice crystals (k=2) and raindrops (k=3) size distribution functions (f k ): c 2 = 1, c 3 = 0 3. The equation of heat inflow:4. The equation of moisture inflow: 5. The state equation:

Cloud particles generation on CCN and IN is parameterized as follows: if x > 0, if x 0, if x < 0 The rate of growth of individual particles due to condensation (sublimation) is: and due to gravitational collection by spherical CP of droplets:, k = 2, 3,, k = 2, 3, where r k0 are min radii of CP; Е(r 1,r k ) are coefficients of collection. 1-D CLOUD RESOLVING MODEL

The processes of droplets (I f1 ) and raindrops (I f3 ) freezing and the amount of frozen water CP (I f2 ) is parameterized as follows:, Cloud particles concentrations (N k ), their average sizes (r), ice and water contents (q k ), intensity of precipitation (j): where r kmin and r kmax are minimum and maximum radii of CP. FREEZING PROCESSES IN 1-D CRM INTEGRAL CHARACTERISTICS OF MIXED CLOUD

5-min precipitation totals for Dresden 12 August, 00 UTC, to 13 August, 06 UTC 5-min precipitation totals for Doberlug 12 August, 00 UTC, to 13 August, 06 UTC

5-min precipitation totals for Chemnits 12 August, 00 UTC, to 13 August, 06 UTC 5-min precipitation totals for Cottbus 12 August, 00 UTC, to 13 August, 06 UTC

Weather station Coordinates 1-d precipitation totals, mm Maximum of precipitation rate from 3-D LAM, mm/h geographical Cartesian relative to Praha Measur ed Foreca sted by 1-D CRM , o N, o E X, kmY, km00 h06 h12 h18 h Chemnitz (121.9) 3,00,34,01,0 Cottbus (208.2) 0,59,03,0 Doberlug (56.2) 0,59,03,02,0 Dresden (71.2) 4,09,52,0 Fichtelberg (51.2) 7,00,81,02,0 Grosser Arber (19.2) 0,50,30,12,0 Potsdam (572.6) 3,00,30,80,0 Zinnwald (70.2) 0,03,0 7,0 Meiningen —100.9 (553.9) 0,32,00,72,0 Praha —2636(60.2) 0,51,02,04,0

5-min precipitation totals for Cottbus 12 August, 06 UTC, to 13 August, 06 UTC

CONCLUSIONS CMCT allowed to define zones with potentially intensive precipitation formation processes and to calculate probable precipitation intensity for desired points of 3-D domain. CMCT allowed to define zones with potentially intensive precipitation formation processes and to calculate probable precipitation intensity for desired points of 3-D domain. Certain limitations in running CMCT on the concrete cloud system were defined: intensive updrafts with moisture advection resulted in constantly renewable water vapour resources in clouds which leaded to overestimated precipitation intensities and sums. Certain limitations in running CMCT on the concrete cloud system were defined: intensive updrafts with moisture advection resulted in constantly renewable water vapour resources in clouds which leaded to overestimated precipitation intensities and sums. Varying of probabilities of activation of cloud nuclei by changing their parameters and even excluding of one of precipitation formation processes modified predictable precipitation sum on 10-20%. Varying of probabilities of activation of cloud nuclei by changing their parameters and even excluding of one of precipitation formation processes modified predictable precipitation sum on 10-20%. It is necessary to define parameters of microphysical processes in dependence on thermodynamical conditions of cloud formation for getting meaningful precipitation forecast for concrete point and time. It is necessary to define parameters of microphysical processes in dependence on thermodynamical conditions of cloud formation for getting meaningful precipitation forecast for concrete point and time. Reliability of the model outputs directly depends on quantity and quality of inputs. Upper-air soundings minimum every 6 h are desirable to construct CMCT and to get reliable results. Reliability of the model outputs directly depends on quantity and quality of inputs. Upper-air soundings minimum every 6 h are desirable to construct CMCT and to get reliable results.

3-D LAM results with 1-D CRM trek (digits near trek – t cloud, h) Integral ice supersaturation (mm) Precipitation rate (mm/h)

Initial vertical and time development of: (a) temperature (lines, o C), water (green) and ice supersaturations (shading, mg/kg); (b) vertical motions (cm/s) Vertical and time development of: (a) IC and (b) LWC (mg/kg) In the run with unmodified freezing