1. Towards parametrized GEC current sources for the CESM model FESD project meeting February 2014 Wiebke Deierling, Andreas Baumgaertner, Tina Kalb

2. Background Mach et al. 2011 Investigate parameterizations based on readily available cloud parameters in model such as: -In-Cloud Ice Water Path -Convection Mass Flux -……… Assumption: Cloud characteristics relate to conduction currents of different type Step 1: Investigate spatial and temporal distribution of these cloud parameters. How well do they represent observed cloud parameters? Step 2: Regression between estimated observed currents and cloud parameters to infer currents in model. This can be done on different temporal and spatial scales.

3. Storm counts from TRMM from Liu et al. 2009 Conversion of thunderstorm (TC) / electrified storm (T 30dbZ < -10/-17C) count to current per grid box: x 1.7A #TC over ocean x 1.0A #TC over land x 0.41A #ESC over ocean x 0.13A #ESC over land

4. CESM In-cloud ice water path above 500 hPa CESM Convection updraft mass flux above 800 hPa June Liu et al., 2009 estimated current

5. MERRA Convection updraft mass flux above 800 hPa CESM Convection updraft mass flux above 800 hPa June Liu et al., 2009 estimated current

6. Yearly average CESM Convection updraft mass flux above 800 hPa single-year mean (low resolution) Liu et al., 2009 estimated current

7. June composite day: loop through 0-23 UT CESM updraft mass flux above 800hPa, deviation from mean

8. Carnegie curve: Percent deviation from mean (June) Liu et al. 2009 current CESM % UT

9. Vertical location of charges Altitude above sea level (km) Positive charge at -30C Negative charge at -10C km from CESM temperature distribution

10. Conclusions and future work Convective updraft mass flux from CESM simulations has similar features to derived GEC source current from storm counts → possibly useful for parametrizing source current in the model Future work: o Derive relationships between storm counts and storm-current from ER-2 and radar o Compare results from different reanalysis (NCEP/NCAR, ECMWF) o Improve fitting of model variables to “observed” source current