Numerical investigation of the multi-scale processes inducing convection initiation for the 12 June 2002 IHOP case study Preliminary study: testing the sensitivity of the model to simulate this CI case. Sophie Bastin, Tammy Weckwerth, Fei Chen, Kevin Manning NCAR Acknowledgements: M. Weisman, S. Trier, M. Pagowsky, D. Posselt, D. Birkenheuer, and others (mesouser, …)

Motivations  Better understanding of the influence of the processes at different scales on the location and timing of convection Why did CI occur here?

Numerical simulations  Control simulation MM5 model version domain, 4-km horizontal resolution 44 vertical levels, about 20 half-sigma levels within the boundary layer Initialization at 12Z on June 12 (cold start), from NCEP Eta analyses (40 km resolution) Objective analysis and observations nudging (it’s not a forecast) Eta PBL parameterization, no cumulus scheme, Reisner2 microphysics scheme, Noah LSM  Sensitivity tests: Domain(s) size Initialization: time, 3D fields (NCEP ETA, RUC, LAPS, ECMWF), soil moisture and temperature fields (HRLDAS) Parameterizations: PBL processes, microphysics scheme, cumulus scheme

Control simulation (1) Surface wind at 21 UTC (= initial time + 9h) OK mesonet data simulation

Control simulation (2) Surface temperature at 21 UTC OK mesonet datasimulation

Control simulation (3) Relative humidity at 21 UTC OK mesonet data simulation

CONTROL simulation (4) 19 UTC 20 UTC 21 UTC22 UTC Column-integrated cloud water

Sensitivity study (1) YESNO 3D initial conditionsX (underway) HRLDAS (surface conditions) light DomainsX Initial timeX PBL parameterizationX Microphysics schemeX Convective scheme (with or without) X

Sensitivity study (2) CONTROL2 domainsCold start at 00 UTC dryline Good ~ good Outflow boundary Too weak Good (too strong?) No mesolow Good Too weak Larger scale circulation Surface moisture values GoodGood around the dryline ~ good Surface temperature values Good (except gradient at the outflow boun.) same as CONTROL ~ good CI along the dryline Good but no CI at triple point Too late Too early

Sensitivity to domains Surface mixing ratio and wind at 21 UTC Column-integrated cloud water at 21 UTC Control simulation2 domains

Sensitivity study (2) CONTROL2 domainsCold start at 00 UTC dryline Good ~ good Outflow boundary Too weakGood (too strong?) No mesolow GoodToo weak Larger scale circulation Surface moisture values GoodGood around the dryline ~ good Surface temperature values Good (too hot western of dryline) same as CONTROL ~ good CI along the dryline Good but no CI at triple point Too late Too early

Sensitivity to initial time Control simulationInitialization at 00 UTC Reflectivity, potential temperature and surface wind at 16 UTC

Conclusion and future prospects  Main results: Current parameterizations do not guarantee high degree of accuracy in reproducing an outflow boundary. The number of factors involved in good simulations makes the success of high resolution simulations of thunderstorms a matter of …luck.  Future works Sensitivity to 3D fields initialization Simulation of gravity waves (GV) and horizontal convective rolls (HCR) sensitivity to the horizontal resolution (trying 2km) WRF model Analysis of the pre-storm environment in the different simulations to understand the physical processes affecting convection initiation (absence of GV and HCR = reasons of failure?)

Sensitivity study (2) CONTROL2 domainsInit. at 00ZMRF param. dryline Good ~ goodGood Outflow boundary Too weakGood (too strong?) NoToo weak mesolow GoodToo weakLarger scale circulation Good Surface moisture values GoodGood around the dryline ~ goodToo weak Surface temperature values Good (too hot western of dryline) same as CONTROL ~ goodGood CI along the dryline Good but no CI at triple point Too lateToo earlyGood

Sensitivity to PBL parameterization MRFPBL deeper, surface humidity weaker, moisture gradient at the dryline weaker ETAHumidity more concentrated in the PBL and moisture gradient stronger, propitious to the development of convection CI slightly delayed with the MRF parameterization Control simulation MRF param.