Evaluation of wet scavenging for the May 29, 2012 DC3 severe storm case Megan Bela (U. Colorado), Mary Barth (NCAR), John Wong, O. Brian Toon (U. Colorado),

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Evaluation of wet scavenging for the May 29, 2012 DC3 severe storm case Megan Bela (U. Colorado), Mary Barth (NCAR), John Wong, O. Brian Toon (U. Colorado), Hugh Morrison, Morris Weisman, Kevin Manning, Glen Romine, Wei Wang (NCAR), Kristin Cummings (U. Maryland), Kenneth Pickering (NASA/GSFC), and the DC3 Science Team

Wet Scavenging and Lightning-NOx in WRF WRF-Chem – Wet scavenging of trace gases based on Neu-Prather parameterization connected to Lin scheme cloud physics (Pfister et al., WRF workshop, 2011) – Now connected to Morrison cloud physics scheme – Lightning-NOx parameterization split into two parts Lightning flashrate predicted in WRF/phys Lightning-NOx production predicted in WRF/chem DC3 Field Campaign – Offers chance to evaluate these parameterizations via case studies

Deep Convective Clouds and Chemistry (DC3) Experiment To characterize thunderstorms and how they process chemical compounds that are ingested into the storm (transport, scavenging, lightning and NOx production, chemistry) To learn how the air that exits the storm in the upper troposphere (UT) changes chemically during the next day (chemical aging) May-June 2012

H 2 O 2 CH 3 OOH CH 3 OH CH 2 O CH 3 COCH 3 RO 2 or HO x NO x O3O3 Strategy for Sampling Near Storms

29 May 2012 Oklahoma Severe Storm photo from Don MacGorman

WRF-Chem Setup ∆x = 3 km ∆x = 15 km May 30, ZWRF Max. 10 cm Radar Reflectivity (dBZ), 15 km CONUS: Grell 3D (G3) convective parameterization 3km: explicit convection MOZART chemistry, GOCART aerosols with radiative feedback

Wet Scavenging Evaluation ∆x = 3 km ∆x = 15 km May 30, ZWRF Max. 10 cm Radar Reflectivity (dBZ), 3km: explicit convection MOZART chemistry, GOCART aerosols with radiative feedback

WRF represents storm location but initiates early and has a larger area of high reflectivity WRF Maximum 10cm reflectivity (dBZ) NEXRAD Composite Reflectivity Z

WRF represents storm location but initiates early and has a larger area of high reflectivity Z WRF Maximum 10cm reflectivity (dBZ) NEXRAD Composite Reflectivity

WRF represents storm location but initiates early and has a larger area of high reflectivity Z WRF Maximum 10cm reflectivity (dBZ) NEXRAD Composite Reflectivity

WRF represents storm location but initiates early and has a larger area of high reflectivity Z WRF Maximum 10cm reflectivity (dBZ) NEXRAD Composite Reflectivity

WRF represents storm location but initiates early and has a larger area of high reflectivity Z WRF Maximum 10cm reflectivity (dBZ) NEXRAD Composite Reflectivity

Neu and Prather (2012) wet scavenging was coupled to MOZART chemistry and Morrison microphysics gas cloud water rainhailsnow Henry’s Law retention factor = 1 evaporation gas Simulations: 1.With the wet scavenging 2.Without the wet scavenging Scavenged: HNO 3, H 2 O 2, HCHO, CH 3 OOH Transport only: CO, O 3, NMHCs

Inflow = DC8 and GV measurements restricted to just before/during storm Outflow = DC8 and GV measurements when sampling anvil outflow, with stratospheric air (O 3 > 100 ppb, CO < 100 ppb) removed Observed (Preliminary) CO WRF-Chem O3 Compare vertical profiles from observations and model output Inflow Ouflow - No Scav. Outflow - Scav. Inflow = Clear sky points just before storm where aircraft flew Outflow = WRF anvil region where CO > 100 ppb at 11 km, and stratospheric air removed

Inflow Outflow Observed (Preliminary) CO WRF-Chem O3 CO and O 3 vertical structure is represented by model and affected little by wet scavenging Inflow Ouflow - No Scav. Outflow - Scav.

Observed (Preliminary) WRF-Chem CH 2 O CH 2 O enhanced in outflow, H 2 O 2 scavenged Inflow Outflow Inflow Ouflow - No Scav. Outflow - Scav. H2O2H2O2

Neu-Prather Wet Scavenging Scheme in the 3 km WRF-Chem simulation Summary Convective transport of non-soluble species is reasonably well represented by the 3 km WRF-Chem simulation Observed mean vertical profiles of some soluble species in outflow are better represented in the model with scavenging, while others are overly scavenged Currently implementing a more detailed scavenging scheme (Barth et al., 2001, 2007)  role of ice (retention during freezing and adsorption of gases) Evaluation of lightning-NOx scheme being done by U. Maryland (Pickering, Allen, Cummings, Li)

Lightning Flash Rate Parameterization Lightning-generated NO (LNOx) is an important emission in the upper troposphere where background NO is low The production of LNOx depends on lightning flash rate, type of lightning, and NO produced WRFV3.5 flash rate parameterization is now in physics directory NO production and emission is in chem directory Able to evaluate lightning flash rate without overhead of running chemistry Parameterizations available for both parameterized convection (Wong et al., 2013, GMD) and resolved convection (Barth et al., 2012, ACP)

Lightning Flash Rate Parameterization in the 15 km WRF-Chem simulation 15 km CONUS: Grell 3D (G3) convective parameterization MOZART chemistry, GOCART aerosols with radiative feedback

Lightning Prediction for Parameterized Convection FR = 3.44x10 -5 z top 4.9 z top = radar cloud top (20 dBZ height; agl) (Williams, 1985) z top = level neutral buoyancy – 2 km (Wong et al., 2013) 500 moles NO/flash placed vertically following Ott et al. (2010) curves From Takahashi and Luo (2012) GRL CloudSat radar reflectivity profile of a tropical deep convective cloud observed on February over Amazon (unit: dBZ). The size of the system is about 140 km and the highest point is about 17 km.

NLDN (obs of CG flashes) WRF (mdl of IC+CG flashes) Flash count for UTC May 29, 2012 DC3 Case Study Evaluation of Lightning Flash Rate Limit flash rate to regions where 1. qtot max > 0.5 g/kg 2. ppt > 5 mm/hr 35-40N, W, UTC WRF NLDN

Qtot > 0.5 g/kg ppt > 5 mm/hr LNB onlyNLDN observations Evaluation of Lightning Flash Rate 2200 UTC 29 May Spatial location and magnitude of flash rate better predicted when flash rate is restricted to regions of resolved cloud or high precipitation rates

Qtot > 0.5 g/kg ppt > 5 mm/hr NLDN observations LNB only Evaluation of Lightning Flash Rate 0000 UTC 30 May Spatial location and magnitude of flash rate better predicted when flash rate is restricted to regions of resolved cloud or high precipitation rates

Qtot > 0.5 g/kg ppt > 5 mm/hr NLDN observations LNB only Evaluation of Lightning Flash Rate 0200 UTC 30 May Spatial location and magnitude of flash rate better predicted when flash rate is restricted to regions of resolved cloud or high precipitation rates

May 29 Case Study Evaluation of NOx in Upper Troposphere Qtot > 0.5 g/kg ppt > 5 mm/hr Bkgd: WRF-Chem model results for NOx at z = 11 km and 00 UTC 30 May. Circles: GV and DC-8 observations of NOx at 10 < z < 12 km and UTC  Location is off somewhat (because of storm location), and magnitude is underpredicted

May 29, 2012 severe storm in northern Oklahoma (photo from Don MacGorman) Summary Restricting flash rate to regions of high precipitation or resolved cloud improves location and magnitude of flash rate Next Steps 1.Finish tweaking flash rate parameterization  Evaluate with lightning mapping array data which gives total flash rate (= IC + CG)  Adjust NO production per flash 2.Use set up for simulating other DC3 cases at Δx = 15 km 3.Recommend refinement to the lightning flash rate parameterization for parameterized convection Thank you! DC3 is sponsored by the National Science Foundation (NSF), NASA, NOAA, and DLR DC3 Preliminary Data Provided by the following Instrument Teams: DC-8 CO: DACOM - G. Diskin, G. Sachse, J. Podolske (NASA/LaRC) DC-8 O3: CSD CL –T. Ryerson, I. Pollack, J. Peischl (NOAA/ESRL/CSD) GV CO, O3: CARI –A. Weinheimer, F. Flocke, T. Campos, D. Knapp, D. Montzka (NCAR)