CONVECTIVE CLOUD MICROPHYSICS IN A HIGH-RESOLUTION NWP MODEL

Transcription

1 CONVECTIVE CLOUD MICROPHYSICS IN A HIGH-RESOLUTION NWP MODEL J. Trentmann 1, A. Seifert 2, H. Wernli 1 1 Institute for Atmospheric Physics, Johannes Gutenberg University Mainz, Germany 2 German Weather Service, Offenbach, Germany 1. INTRODUCTION Forecasting convective precipitation remains a challenge for numerical weather prediction. In April 2007 a convection-permitting version of the COSMO (Consortium for Small Scale Modeling) model has become operational at the German Weather Service, DWD COSMO-DE. This model operates with a horizontal grid point distance of ( 2.8 km) and resolves the dominant spatial scales involved in deep convection. No parameterization of deep convection is employed. Such a model setup allows to evaluate and to investigate the description of cloud microphysical processes within deep convective clouds under realistic conditions, e.g., without the application of an artificial trigger mechanism for convection. Here, we present model simulations for a case of localized deep convection that occurred on 12 July 2006 in South-West Germany. 2. OBSERVATIONS Summertime precipitation in the lowmountainous region in South-West Germany is dominated by convective precipitation. On 12 July 2006, under weak synoptic-scale forcing, several convective cells formed in the early afternoon in mountainous regions across Europe including the Black Forest in South-West Germany (Fig. 1). While the 1 Corresponding author s address: Jörg Trentmann, Institute for Atmospheric Physics, Johannes Gutenberg University Mainz, Becherweg 21, Mainz, Germany, jtrent@uni-mainz.de Figure 1: Visible image derived from MODIS at 1030 UTC, 12 July 2006, the yellow rectangle marks the convective cell of interest. Rhine-Valley remained free of convective activity, different stages of convective clouds can be identified over the German (Black Forest and Swabian Alb) and the French (Vosgue) low mountain ranges. The convective cell in the Northern Black Forest (marked by the yellow square) is in its active, growing phase. Its top has already reached the level of neutral buoyancy (i.e, the tropopause) and ice has formed in the anvil. In the southern Black Forest, a mature convective cloud is present with a huge ice anvil, while along the Swabian Alb (towards the NE) mainly shallow convection prevails. The mixture of different stages of cloud developments highlights the high spatial and temporal variability of convective clouds under weak synoptic forcing. Here we focus on the convective cell that formed around local noon in the Northern Black Forest. The precipitation field derived from gauge-

2 Figure 2: (a) Gauge-adjusted radar-derived precipitation between 9 and 19 UTC on 12 July 2006 provided by DWD; (b) model simulated precipitation between 9 and 19 UTC, 12 July 2006, thick black contour lines mark the topography, the thin black contour line marks the German-French border. adjusted radar measurements between 09 and 19 UTC shows an area of convective precipitation in the Murg Valley north of Freudenstadt (8.42 E, N) with a maximum precipitation amount of 58 mm within 10 hrs (Figure 2a). Ground-based wind-lidar measurements (not shown) obtained at Hornisgrinde (1177 m asl, the highest peak in the Northern Black Forest) revealed that horizontal wind convergence along the mountain crest, presumably due to thermally-induced mountain wind systems, was responsible for the initiation of these convective cells. Afternoon values of CAPE derived from radiosoundings exceeded 2000 J kg 1. Further information on the experimental results obtained within the PRINCE (Prediction, identification, and tracking of convective cells) field experiment can be found in Groenemeijer et al. (2008). 3. MODEL SIMULATIONS Model simulations were conducted using the COSMO model (Steppeler et al. 2003; Schättler et al. 2005), an atmospheric model used for operational weather forecast and for academic research. For the current investigation, the horizontal resolution was set to 0.025, corresponding to approx. 2.8 km. This spatial resolution allows the explicit description of the processes associated with deep convection and no parameterization of deep convection was employed (Seifert et al. 2008). Initial and boundary conditions for these simulations were provided by hourly COSMO-EU analysis with a spatial resolution of (approx. 7 km). The simulations were started on 12 July 2006 at 07 UTC. In the standard operational COSMO model setup, cloud microphysics is parameterized using a one-moment bulk microphysical scheme. Here, we will present results from simulations that employ a two-moment microphysical scheme that predicts the mass and the number concentrations of six classes of hydrometeors, including hail (Seifert and Beheng 2006; Blahak 2008). Nucleation of cloud droplets is parameterized using the method from Segal and Khain (2006); evaporation of rain drops is considered using the parameterization of Seifert (2008). In the following we present results from model simulations designed to reproduce the situation on 12 July Surface Precipitation Figure 2b shows the simulated precipitation accumulated between 9 and 19 UTC on 12 July 2006 that can be compare to the radar-derived precipitation field presented in Figure 2a. The location and the amount of precipitation is satisfactorily captured by the model simulation. In the model the

3 Figure 3: Visualisation of the model results for 1330 UTC on 12 July (a) The color coding represents the topography. White contour lines correspond to the 30- and 40-dbz isoline of the vertical maximum radar refelctivity derived from the model simulation. Black arrows represent the 10-m wind. The black line indicates the location of the cross section shown in Figure 3b. (b) Mass concentration of hydrometeors along the cross section depicted by the black line in Figure 3a. Blue contour lines represent positive vertical velocity (updraft), red contour lines correspond to negative vertical velocity (downdraft). Black contour lines correspond to the 0- and 40- C isoline. precipitation is also tied to the Murg valley in the Northern Black Forest suggesting that the process leading to the initiation of the convective cell is realistically described in the model simulation. The amount of precipitation is underestimated compared to the radar-derived precipitation (The simulated maximum precipitation is 30 mm.), however, the quantification of surface precipitation from radar observations is also associated with some uncertainty. An analysis of the diurnal precipitation cycle (not shown) reveals that the simulated precipitation is delayed compared to the radar observations by about 2 hrs. Overall, the good comparison between the observed and the simulated accumulated precipitation fields allows an investigation of the microphysical processes that are responsible for the formation of precipitation in the model simulations. 3.2 Cloud Microphysics In the following we will present a more detailed view into the model results from the simulation presented in Section 3.1 focussing on the hydrometeors in the convective cloud. Figure 3a presents the vertical maximum of the simulated radar reflectivity and the 10-wind field at 1330 UTC. The main convective activity is along the mountain crest of the Black Forest. The high spatial resolution allows to explicitly resolve the dynamical processes associated with the convective cell. The impact of the convective scale dynamics, e.g., downdrafts, cold air outflow, on the 10-m wind field is clearly visible. In Figure 3b a vertical cross section through the convective cloud along the black line depicted in Figure 3a is shown. The convection reaches the local tropopause at about 200 hpa. The updraft speed in this convective cell exceeds 9 m s 1, the water/ice mass mixing ratio reaches up to 5.5 g kg 1, and the downdraft exceeds 5 m s 1. The main low level inflow region into this convective cell is slightly further towards the SE and not depicted in this cross section (see Figure 3a). Figure 4 shows the simulated number concentration of hydrometeors by the twomoment scheme along the cross section indicated by the black line in Figure 3a. Also indicated are the regions with mainly liquid, with mainly frozen, and with a mixture of frozen and liquid hydrometeor mass. Significant parts of the cloud, mainly associated

4 Figure 4: Simulated total number concentration of hydrometeors along the cross section depicted by the black line in Figure 3a. Note the huge range of the color colding, from cm 3 (= 1 l 1 ) to 1000 cm 3. The solid black contour shows the 0.2-g kg 1 isoline of liquid hydrometeors, the dotted black contour represents the 0.2-g kg 1 isoline of frozen hydrometeors. Blue contour lines represent positive vertical velocity (updraft), red contour lines correspond to negative vertical velocity (downdraft). Black contour lines correspond to the 0- and 40- C isoline. with the updraft, involve a mixed phase between liquid and frozen hydrometeors. The hydrometeor number concentration in the cloud is extremely variable, ranging from cm 3 to more than 1000 cm 3. The precipitating downdraft region exhibits the lowest number concentration associated with large rain droplets (compare with the mass concentration in Figure 3b). Overall the number and the mass concentration of hydrometeors in the convective cloud are very realistic suggesting that the COSMO model with the two-moment microphysical scheme allows an in-depth investigation of microphysical processes in convective clouds. 4. SUMMARY AND CONCLUSIONS We presented results from a model simulation using the COSMO model with a sophisticated two-moment cloud microphysical scheme. The model is used with a spatial resolution of about 2.8 km without a parameterization of deep convection and is driven by analysis data. No artificial initiation of convection is employed. Model results were presented for the situation on 12 July 2006 when local convection occurred along mountainous regions in Central Europe. Focus was given to the convective cloud that formed in the Northern Black Forest in South-West Germany. The model reproduces the initiation and the lifecylce of the convection, but underestimates the surface precipitation compared to radar data. The dynamical processes (updraft, downdraft, outflow) in the cloud seem to be realistically described by the model. A significant fraction of the convective clouds is composed of a mixture between liquid and frozen hydrometeors with maximum total number concentration exceeding 1000 cm 3. Surface precipitation is composed of large rain droplets with a number concentration in the order of 0.01 cm 3 (corresponding to 10 l 1 ). Overall, the COSMO model with the two-moment cloud microphysics scheme allow detailed investigations of convective clouds and their microphysical processes. 5. ACKNOWLEDGMENTS J.T. thanks the DWD for providing and supporting the use of the COSMO model. References Blahak, U.: 2008, Towards a better representation of high density ice particles in a state-of-the-art two-moment bulk microphysical scheme. Proc. 15th Int. Conf. Clouds and Precip., Cancun, Mexico. Groenemeijer, P., C. Barthlott, A. Behrendt, U. Corsmeier, J. Handwerker,, M. Kohler, C. Kottmeier, H. Mahlke, S. Pal, M. Radlach, J. Trentmann, A. Wieser, and V. Wulfmeyer: 2008, Multisensor measurements of a convective storm cluster over a low mountain range: Adaptive observations during PRINCE, submitted to Mon. Wea. Rev. Schättler, U., G. Doms, and C. Schraff, 2005: A description of the nonhydrostatic regional model LM, Part VII: User s Guide. Technical report, Consortium for Small-Scale Modelling.

5 Segal, Y. and A. Khain, 2006: Dependence of droplet concentration on aerosol conditions in different cloud types: Application to droplet concentration parameterization of aerosol conditions. J. Geophys. Res., 111, doi: /2005jd Seifert, A.: 2008, On the parameterization of evaporation of raindrops below cloud base. Proc. 15th Int. Conf. Clouds and Precip., Cancun, Mexico. Seifert, A., M. Baldauf, K. Stephan, U. Blahak, and K. Beheng: 2008, The challenge of convective-scale quantitative precipitation forecasting. Proc. 15th Int. Conf. Clouds and Precip., Cancun, Mexico. Seifert, A. and K. D. Beheng, 2006: A twomoment cloud microphysics parameterization for mixed-phase clouds. Part 1: Model description. Meteorol. Atmos. Phys., 92, 45 66, doi: /s Steppeler, J., G. Doms, U. Schättler, H. W. Bitzera, A. Gassmann, U. Damrath, and G. Gregoric, 2003: Meso-gamma scale forecasts using the nonhydrostatic model LM. Meteorol. Atmos. Phys., 82,