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Impact of lightning-NO on eastern United States photochemistry during the summer of 2006 as determined using the CMAQ model Dale Allen Dept. of Atmos and.

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Presentation on theme: "Impact of lightning-NO on eastern United States photochemistry during the summer of 2006 as determined using the CMAQ model Dale Allen Dept. of Atmos and."— Presentation transcript:

1 Impact of lightning-NO on eastern United States photochemistry during the summer of 2006 as determined using the CMAQ model Dale Allen Dept. of Atmos and Oceanic Sci, UMD-College Park Kenneth Pickering Atmos Chem and Dyn Branch, NASA-GSFC Robert Pinder and Thomas Pierce Atmos Modeling and Analysis Div, U.S. EPA Barron Henderson Dept. of Env Sci and Eng, UNC Chapel Hill William Koshak Earth Science Office, NASA-MSFC 2011 CMAS Meeting 26 October 2011

2 Motivation for Including Lightning NO x in CMAQ In the summer over the US, production of NO by lightning (LNO x ) is responsible for 60-80% of upper tropospheric (UT) NO x and 20-30% of UT ozone (Zhang et al., 2003; Allen et al., 2010). Mid- and upper-tropospheric ozone production rates are highly sensitive to NO x mixing ratios. Inversion-based estimates of NO emissions from CMAQ simulations w/o LNO x have large errors at rural locations (Napelenok et al., 2008). CMAQ-calculated N deposition is much too low without LNO x (e.g., Low-bias in CMAQ nitric acid wet deposition at NADP sites cut in half when LNO x was added). LNO x can add several ppbv to summertime surface O 3 concentrations CMAQ NO 2 amounts are too low (high) at rural (urban) locations (Castellanos et al., 2011; Huijnen et al., 2010) suggesting that the lifetime of NO 2 (Henderson et al., 2011) and/or the transport of NO x (Gilliland et al., 2008) is underestimated by regional models. How will LNO x affect these biases?

3 LNO x Production Lightning-NO production is assumed to be proportional to convective precip rate multiplied by a scaling factor chosen so that monthly avg model flash rates match monthly avg NLDN-based total flash rates. NLDN-based total flash rate is est by multiplying NLDN CG flash rate by Z+1, where Z is the climatological IC/CG ratio (Boccippio et al., 2001) determined by taking the ratio between satellite-retrieved (Optical Transient Detector) total flash rates and NLDN CG flash rates. IC and CG flashes are assumed to produce 500 moles of N per flash, a value that is consistent with cloud resolved modeling of observed convective events [DeCaria et al., 2005; Ott et al., 2009] & with larger- scale modeling of INTEX-A [Hudman et al., 2007; Allen et al., 2010]. Vertical dist of emissions is assumed to be proportional to the pressure convoluted by the segment altitude distribution of flashes in the vicinity of the North Alabama LMA (Koshak et al., 2010)

4 CMAQ simulation of summer 2006 Simulations of 2006 air quality performed at EPA under the management of Wyat Appel and Shawn Roselle as part of the Air Quality Model Evaluation International Initiative (AQMEII) Version of CMAQ used with CB-05 chemical mechanism NEI-based emissions with year specific power plant emissions from CEMS and satellite-derived wildfire emissions Chemical boundary conditions from GEMS (European-led assimilation effort)

5 OMI tropospheric NO 2 products 1.DP-GC product [Lamsal et al., 2010] 2. v2.0 DOMINO product [Boersma et al., 2007; Boersma et al., 2011] DP-GC and DOMINO products begin with same slant column & use same method to remove stratospheric column. Different methods used to convert tropospheric slant cols to overhead cols  Yield different tropospheric vertical column amounts tropopause

6 R=0.79R=0.47



9 Sensitivity of urban/rural ratio to hor/vert smoothing 4. Relative to OMI, CMAQ has high bias at urban sites. Biases at rural sites are relatively small after accounting for LNO x and the smoothing inherent in DOMINO averaging kernels. 1. U/R ratios ↓ when LNOx is added as LNOx is larger part of rural col than urban column 2. U/R ratios ↓ when mapped onto 0.25x0.25 grid because aggregation mixes rural and urban locations 3. U/R ratios ↓ when avgk is applied because U/R ratios are largest near surface where OMI is relatively insensitive


11 How much do uncertainties in CB05 chemistry contribute to CMAQ’s inability to capture the high amounts of UT NO x measured during the INTEX-A period (An upper bound)? CMAQv4.7.1 with CB-05 chemistry and AERO5 aerosols was used to simulate the summer of Three simulations: 1) standard chemistry without lightning-NO, 2) standard chemistry with lightning-NO, and 3) updated chemistry with lightning-NO Updated chemistry: Organic nitrate (ON) yield from the oxidation of paraffins (PAR) was reduced from 15% to 3%. The decrease in ON production reduces NO consumption, increases the NO x lifetime, and is in better agreement with observations (Henderson et al., 2011).

12 Adjusting chemistry increases UT NO x by pptv reducing model biases by 5-16% if data are unbiased and by 10-33% if data are assumed to be 30% too high due to MPN interference (Browne et al., 2011) LNO x increases UT NO x by pptv (X4 increase); however, a pptv low-bias remains. Low-bias is still pptv after accounting for MPN interference

13 Mean summer 2006 enhancement of 8-hr maxO3 in CMAQ due to LNO x O 3 enhancement (ppbv)

14 Adding LNO x eliminates low-bias Adjusting for precip bias leads to better fit Eastern US: Longitudes east of 100W (nitrate)

15 Nitrate Biases NE: +5% SE: +19% West –(5-10)% Ammonium biases NE: +20% SE: +40% West: -(20-25)%

16 Summary For a 500 mole per flash lightning-NO source, mean tropospheric NO 2 columns agree with satellite-retrieved columns to within -5 to +13%. Contribution of LNO x to mean model column is ~25%, ranging from ~10% in the northern states to >45% along the Gulf of Mexico and in the southwestern states. CMAQ columns have a high-bias wrt DOMINO columns over urban areas. Biases at other locations were minor after accounting for the impacts of lightning-NO emissions and the averaging kernel on model columns. Chemistry explains less than 1/3 of upper tropospheric NO 2 underpredictions by CMAQ during the INTEX-A period UT O 3 is biased high wrt eastern U.S. sonde data. While LNO x contributes to bias, most of it is likely due to the specification of BC and noise introduced by vertical velocity calculation within CMAQ. LNO x increases wet dep of nitrate by 43%, total dep of N by 10%, & changes 30% low-bias wrt NADP measurements to 2% high-bias. On poor AQ days (O3>60 ppbv), LNO x contributes >6.5 ppbv to 8hrO 3 at 10% of western sites and 3% of eastern sites

17 Acknowledgements Wyat Appel & Shawn Roselle of EPA: AQMEII simulations Ana Prados of UMBC: Gridding OMI std product Anne Thompson: IONS ozonesonde data, L. Lamsal: DP-GC NO2 data. OTD/LIS data are from NASA/MSFC. NLDN data are collected by Vaisala Inc NASA Applied Science Air Quality Program


19 Adding LNOx eliminates low-bias Adjusting for precip bias lessens scatter but increases bias.

20 Processing of DOMINO & CMAQ fields Gridded DOMINO fields created by mapping version 2.0 level 2 DOMINO fields onto 0.25°x0.25° grid. DOMINO retrievals over snow/ice or with cloud radiance fractions > 50% filtered out (Boersma et al., 2009) Mean value in each grid box obtained using algorithm that gives more weight to near-nadir pixels and to pixels with low geometric cloud fractions (Celarier and Retscher, 2009). CMAQ profiles extracted at location of high-quality DOMINO pixels & weighted in same manner. CMAQ output interpolated onto TM4 vertical grid (TM4 model used to obtain a priori profiles for DOMINO product). When appropriate, averaging kernel is applied to tropospheric model sub- columns before weighting is performed (Allen et al., 2010; Boersma et al., 2009). CMAQ tropospheric NO 2 column determined by summing sub-columns within the troposphere, where the number of tropospheric layers is included in DOMINO data product.

21 CMAQ Lightning-NO Parameterization LNO x = k* PROD*LF, where k: Conversion factor (Molecular weight of N / Avogadros #) PROD: Moles of NO produced per flash LF: Total flash rate (IC + CG), where LF = G * α i,j * (precon i,j – threshold), where Precon:Convective precipitation rate from WRF threshold: Value of precon below which the flash rate is set to zero. G: Scaling factor chosen so that domain-avg WRF flash rate matches domain averaged observed flash rate. α i,j :Local scaling factor chosen so that monthly avg model- calc flash rate for each grid box equals local observed flash rate For these retrospective simulations, the observed flash rate is the NLDN- based total flash rate for June, July, and August Operational forecasts could use satellite-retrieved or NLDN-based climatological flash rates for a season as observations.

22 Vertical distribution of flash channel length in the vicinity of the North Alabama LMA is used along with a direct relationship with pressure to determine the fraction of emissions to put into each layer from the surface to the CMAQ- predicted cloud top Vertical partitioning of lightning-NO emissions Segment altitude distribution for all flashes from Koshak et al. [2010]

23 OMI Level-2 daily ozone profile data courtesy of X. Liu Bias: -1.6 DU Trpps = 150 hPa Comparison of CMAQ & OMI tropospheric column O3


25 Note: Adding LNOx causes Wetdep(OxN) 50%↑ Totdep(OxN) 22%↑ Totdep(N) 11%↑ Adding LNOx NE US: -14%  +11% SE US: -19%  +28% MW/GP US: -32%  +2% RM/W US: -31%  -2% SE bias is reduced to -3% if adjustment is made for a high-bias in SE US CMAQ precip (nitrate)

26 Lightning-NO increases UT ozone by 5-7 ppbv Adjusting chemistry increases UT O3 by ppbv. Changes small in lower troposphere Low-bias is reduced with LNOx However many factors contribute to UT biases in ozone

27 In general, the contribution of LNO x to 8hrO3 decreases on bad AQ days over the eastern U.S.

28 Outline Motivation & Background Describe method used to parameterize lightning-NO within CMAQ Show impact of lightning-NO on tropospheric composition, air quality, and nitrogen deposition over the U.S. during the summer of 2006 Use OMI NO 2 fields to investigate the cause of biases between modeled and “observed” NO 2 mixing ratios at urban and rural locations Investigate the impact of uncertainties in chemistry on upper tropospheric NO x distributions in the context of the INTEX-A mission

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