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
H2O2 CH3OOH CH3OH CH2O CH3COCH3
RO2 or HOx
NOxO3
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, 2012 00ZWRF Max. 10 cm Radar Reflectivity (dBZ),
15 km CONUS: Grell 3D (G3) convective parameterization3km: explicit convection
MOZART chemistry, GOCART aerosols with radiative feedback
Wet Scavenging Evaluation
∆x = 3 km
∆x = 15 km
May 30, 2012 00ZWRF 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)
NEXRADComposite Reflectivity
2012-05-29 21Z
WRF represents storm location but initiates early and has a larger area of high reflectivity
2012-05-29 22Z WRF Maximum 10cm reflectivity (dBZ)
NEXRADComposite Reflectivity
WRF represents storm location but initiates early and has a larger area of high reflectivity
2012-05-29 23Z WRF Maximum 10cm reflectivity (dBZ)
NEXRADComposite Reflectivity
WRF represents storm location but initiates early and has a larger area of high reflectivity
2012-05-30 00Z WRF Maximum 10cm reflectivity (dBZ)
NEXRADComposite Reflectivity
WRF represents storm location but initiates early and has a larger area of high reflectivity
2012-05-30 01Z WRF Maximum 10cm reflectivity (dBZ)
NEXRADComposite Reflectivity
Neu and Prather (2012) wet scavenging was coupled to MOZART chemistry and Morrison microphysics
gas
cloud water
rain hail snow
Henry’s Law
retention factor = 1
evaporationgas
Simulations:1. With the wet scavenging2. Without the wet scavenging
Scavenged: HNO3, H2O2, HCHO, CH3OOHTransport only: CO, O3, NMHCs
Inflow = DC8 and GV measurements restricted to just before/during stormOutflow = DC8 and GV measurements when sampling anvil outflow, with stratospheric air (O3 > 100 ppb, CO < 100 ppb) removed
Observed (Preliminary)
CO
WRF-Chem
O3
Compare vertical profiles from observations and model output
InflowOuflow - No Scav.
Outflow - Scav.
Inflow = Clear sky points just before storm where aircraft flewOutflow = WRF anvil region where CO > 100 ppb at 11 km, and stratospheric air removed
InflowOutflow
Observed (Preliminary)
CO
WRF-Chem
O3
CO and O3 vertical structure is represented by model and affected little by wet scavenging
InflowOuflow - No Scav.
Outflow - Scav.
Observed (Preliminary)
WRF-Chem
CH2O
CH2O enhanced in outflow, H2O2 scavenged
InflowOutflow
InflowOuflow - No Scav.
Outflow - Scav.
H2O2
Neu-Prather Wet Scavenging Scheme in the 3 km WRF-Chem simulation
SummaryConvective transport of non-soluble species is reasonably well
represented by the 3 km WRF-Chem simulationObserved 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 Parameterizationin the 15 km WRF-Chem simulation
15 km CONUS: Grell 3D (G3) convective parameterizationMOZART chemistry, GOCART aerosols with radiative feedback
Lightning Prediction for Parameterized Convection
FR = 3.44x10-5 ztop4.9
ztop = radar cloud top (20 dBZ height; agl) (Williams, 1985)
ztop = 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 24 2007 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 2100-2200 UTC
May 29, 2012 DC3 Case StudyEvaluation of Lightning Flash Rate
Limit flash rate to regions where1. qtotmax > 0.5 g/kg2. ppt > 5 mm/hr
35-40N, 95-100W, 2200-0100 UTC
WRF
NLDN
Qtot > 0.5 g/kg ppt > 5 mm/hr
LNB onlyNLDN observations
Evaluation of Lightning Flash Rate2200 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 Rate0000 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 Rate0200 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 StudyEvaluation 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 23-01 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)
SummaryRestricting flash rate to regions of high precipitation or resolved cloud improves location and magnitude of flash rate
Next Steps1. Finish tweaking flash rate parameterization
Evaluate with lightning mapping array data which gives total flash rate (= IC + CG)
Adjust NO production per flash2. Use set up for simulating other DC3 cases at Δx = 15 km3. 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)
