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possible advantages :

Use of separate prognostic treatment of cloud water and ice in Hirlam (Presentation by Karl-Ivar Ivarsson at the workshop on convection and cloud-microphysic at Tartu university, Estonia januari 24-26 2005 ). Simulate the life cycle of mixed-phase clouds

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possible advantages :

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  1. Use of separateprognostic treatment of cloud water and ice in Hirlam(Presentation by Karl-Ivar Ivarsson at the workshop on convection and cloud-microphysic at Tartu university, Estonia januari 24-26 2005 ) • Simulate the life cycle of mixed-phase clouds • (Initial supercooled water later ice) • Better spatial distribution of the cloud field. • No new clouds before reaching saturation with respect to water • ( down to about -35C) • Spatial distribution of old clouds more related to • saturation with respect to ice. • Better use of detailed micro-physics. possible advantages : • possible disadvantages : • More expensive to run. • Larger output files. • Risk of numerical noise.

  2. Some scientific/modelling questions • What is cloud condensate and what is • precipitation ? • definition ? • precipitation: • - no horizontal advection in large scale models • - falling down within each timestep • - solid precipitation may exist for some time • if T > 0 C • cloud water and cloud ice : • - often advected in models • - no falling speed • - cloud ice melts immediately if T > 0 C. ( ?) • * What is known about the distribution of cloud ice • and cloud water ? • dependency of ... • Temperature ? cloud type ? Part of the cloud ?

  3. Janet Intrieri (2003)This relation between the fraction of cloud-ice and temperatureis rather close to the oneused in the operational Hirlam in Sweden. (red line)

  4. K.N. Bower el al. (1996)For convective clouds, high amounts of cloudwater is found also for low temperatures. Since also larger iceparticles, than typicall for cloud ice are included, the relative amount of cloudwater may be even higher.

  5. K.N. Bower el al. (1996) For nimbostratus, high amounts of cloudice is found also for temperatures near 0 C. Also here, large iceparticles are included and the fraction cloudice content is assumed to be lower than the ice-water-content.

  6. Crystal habitsThe growth of ice crystals is faster near -5C and -15C due to the shape of the ice crystals. Splinters may increse the number of ice crystals near -6C and to some extent also near -15C.

  7. Crystal growthExample of observed and simulated crystal growth. (Miller and Young, 1979)

  8. Ice nucleus concentration (Rotstayn,2000)The one proposed by Meyers (1992) is used in the experiment. Notice the large differences between the proposed concentrations.

  9. The Experiment • Method: • Use extra scalar for cloud ice • Add equation for ice crystal growth • replace temperature-dependent calculations of the fraction of cloud ice with the actual one ( condensation , radiation ) • some adjustments of the condensation-scheme (Rasch-Kristjansen scheme) • Added parameterization: Precipitation release by the Bergeron-Findeisen effect.

  10. 3D experiment 15 days in winter: 14-29/1 1999 • Hirlam 5.1.4 nlat x nlon x nlev = 306 x 306 x 40 • 22km horizontal resolution • Operational reference run: • Kain-Fritch convection, Rasch-Kristjansen large scale • condensation, CBR-scheme, semi-Lagrangian advection 10 min • timestep • Comparison with: • the same as above but also • - separated prognostic equation for cloud water and cloud ice • - cloudice crystal growth as described in Rotstayn (2000) • - spherical crystals - Ice nucleus concentration as • proposed by Meyers el al (1992) • - Precipitation release by the • Bergeron-Findeisen effect • Similar to the parameterization as in Hsie el al (1980), Lin el al (1983)

  11. Verification of surface parameters C22 = reference run i22 = test run

  12. Verification against soundings 48 hour forecasts C22 = reference run i22 = test run

  13. Mean fraction of ice for different temperatures ( C )

  14. Conclusions / Discussion • With current condensation schemes: • Development of weather systems not very different from reference run. • More realistic cloud field in very cold situations, exept some noise in it. • about 20 % longer time to run • For a given temperature, more cloudwater near cloud top than at the bottom in the experimental runs. • The opposite distribution for cloud ice. Somewhat more cloud ice than in the reference run. • Lee- effect in the precipitation field better • Future work ? • More validation of cloud ice /water !!! • Put the code in H6.3.5 • Different crystal habits • Splinters • Advection of precipitation field • Forecasting supercooled rain/drizzle from clouds with supercooled cloudwater.

  15. References • Rotstayn et al (2000): • A Scheme for calculation of the liquid fraction in mixed-phase • stratiform clouds in large scale models. • Monthly weather review, p 1070-1088 • Meyers et al (1992): • New primary ice-nucleation parameterization in an explicit • cloud model. • J. Appl. Meteor. 31 708-721 • Hsie et al (1980): • Numerical simulation of ice-phase convective cloud seeding. • J. Appl. Meteor. 19 1950-1977 • Lin et al (1983): • Bulk parameterization of the snow field in a cloud model. • J. of appl. Meteor. 22 1065-1092 • Miller and Young (1979): • A numerical simulation of ice crystal growth from the vapor phase. • J.A:S. 36 458-469

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