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Estimating the Influence of Lightning on Estimating the Influence of Lightning on Upper Tropospheric Ozone Using NLDN Upper Tropospheric Ozone Using NLDN Lightning Data Lightning Data Lihua Wang/UAH Lihua Wang/UAH Mike Newchurch/UAH Mike Newchurch/UAH Arastoo Biazar/UAH Arastoo Biazar/UAH William Koshak/NASA William Koshak/NASA 3rd Annual GOES-R GLM Science Meeting, December 1-3, 2010 National Space Science & Technology Center, 320 Sparkman Drive, Huntsville, AL
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Page 1: Estimating the Influence of Lightning on Upper Tropospheric Ozone Using NLDN Lightning Data Lihua Wang/UAH Mike Newchurch/UAH Arastoo Biazar/UAH William.

Estimating the Influence of Lightning on Estimating the Influence of Lightning on Upper Tropospheric Ozone Using NLDN Upper Tropospheric Ozone Using NLDN

Lightning DataLightning Data

Lihua Wang/UAHLihua Wang/UAH

Mike Newchurch/UAHMike Newchurch/UAH

Arastoo Biazar/UAHArastoo Biazar/UAH

William Koshak/NASAWilliam Koshak/NASA

3rd Annual GOES-R GLM Science Meeting, December 1-3, 2010National Space Science & Technology Center, 320 Sparkman Drive, Huntsville, AL

Page 2: Estimating the Influence of Lightning on Upper Tropospheric Ozone Using NLDN Lightning Data Lihua Wang/UAH Mike Newchurch/UAH Arastoo Biazar/UAH William.

CMAQCMAQ 7/15~9/7/20067/15~9/7/2006 U.S. ContinentU.S. Continent

Meteorology: MM5Meteorology: MM5 Emission: SMOKEEmission: SMOKE LNOx: NLDN observationLNOx: NLDN observation Evaluation: IONS06 ozonesonde, OMI Evaluation: IONS06 ozonesonde, OMI

O3/NO2O3/NO2

Page 3: Estimating the Influence of Lightning on Upper Tropospheric Ozone Using NLDN Lightning Data Lihua Wang/UAH Mike Newchurch/UAH Arastoo Biazar/UAH William.

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LNOx ParameterizationLNOx Parameterization

Figure 1 - Total CG flashes (7/15-9/7/2006) observed by NLDN

•Adjust CG flash counts for NLDN detection efficiency of Adjust CG flash counts for NLDN detection efficiency of ~95%~95%•Scale up the CG flash counts to total flashes assuming Scale up the CG flash counts to total flashes assuming IC:CGIC:CG ratio is 3ratio is 3, which is close to the Boccippio et al. (2001) 4-yr mean , which is close to the Boccippio et al. (2001) 4-yr mean IC:CG ratio value (2.94). IC:CG ratio value (2.94). •Estimate the total quantity of lightning-produced N mass Estimate the total quantity of lightning-produced N mass assuming a assuming a 500 moles500 moles (~ 3.011x1026 molecules) N per CG/IC (~ 3.011x1026 molecules) N per CG/IC flash production rate. flash production rate. •Vertically-distribute onto 39 model layers following the Vertically-distribute onto 39 model layers following the mid-mid-latitude continental LNOx distribution profileslatitude continental LNOx distribution profiles Pickering et al. Pickering et al. [1998] developed.[1998] developed.•Add LNOx emission to SMOKE estimated NOx emissions.Add LNOx emission to SMOKE estimated NOx emissions.

LNOx emission accounts for 27% total NOx emission averaged over the entire model domain, and 37.9% (SW), 32.1% (SE), 16.6% (NE), and 15.6% (NW) for the four sub-regions, respectively.

--------•Make a CMAQ run including LNOx (CNTRL_LNOx)Make a CMAQ run including LNOx (CNTRL_LNOx)

Page 4: Estimating the Influence of Lightning on Upper Tropospheric Ozone Using NLDN Lightning Data Lihua Wang/UAH Mike Newchurch/UAH Arastoo Biazar/UAH William.

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Results: Results: Model NOModel NO22 Prediction versus OMI NO Prediction versus OMI NO22 (7/30/2006)(7/30/2006)

OMI trop. NO2

CNTRL trop. NO2

CNTRL trop. NOx

OMI total NO2

CNTRL_LNOx trop. NO2

CNTRL_LNOx trop. NOx

Figure 2 - NO2 column from OMI retrieval and CMAQ model prediction. The CMAQ tropospheric NO2 is calculated based on the tropopause pressure from OMI ozone data.

Page 5: Estimating the Influence of Lightning on Upper Tropospheric Ozone Using NLDN Lightning Data Lihua Wang/UAH Mike Newchurch/UAH Arastoo Biazar/UAH William.

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Results:Results:Model OModel O33 Prediction versus OMI O Prediction versus OMI O33 (trop. (trop. column)column)

7/30/2006

8/10/2006

CNTRL CNTRL_LNOx OMI

Figure 3 – Model-predicted tropospheric ozone column at 19:00 GMT of (upper) July 30, 2006 and (bottom) August 10, 2006, compared with OMI tropospheric ozone retrieval.

Page 6: Estimating the Influence of Lightning on Upper Tropospheric Ozone Using NLDN Lightning Data Lihua Wang/UAH Mike Newchurch/UAH Arastoo Biazar/UAH William.

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Not influenced: Kelowna(26), Bratt’s Lake(28), Trinidad Head(29)

Improved: Table Mountain(25), Holtsville(10), Boulder(27), Egbert(15), Paradox(5), Yarmouth(13), Walsingham(19), Narragansett(27)

Significantly improved: Socorro(25), Houston(16), Ron Brown(23), Huntsville(29), Valparaiso(5), Beltsville(9), Wallops Island(10)

Note: Digits indicate numbers of coincidence pairs between ozonesonde measurements and model prediction.

Kelowna Bratt’s Lake

Trinidad Head

Table MountainHoltville

Socorro

Boulder

Houston

Huntsville

ValparaisoWalsingham

EgbertParadoxYarmouth

NarragansettBeltsvilleWallops Island

Research vessel Ron Brown

Results: Evaluation with ozonesondes Results: Evaluation with ozonesondes (continued)(continued)

Figure 4 - LNOx-influenced ozone at IONS06 stations.

Page 7: Estimating the Influence of Lightning on Upper Tropospheric Ozone Using NLDN Lightning Data Lihua Wang/UAH Mike Newchurch/UAH Arastoo Biazar/UAH William.

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Results: Evaluation with Results: Evaluation with ozonesondes ozonesondes

Kelowna

(not influenced)

Egbert

(slightly improved)

Huntsville

Significantly improved

Overall influence (252 sample pairs)

Figure 5 - Mean normalized bias of model predicted ozone (CNTRL and CNTRL_LNOx runs) and OMI O3, evaluated by ozonesondes at three sites: Kelowna, Egbert and Huntsville, representing three kinds of lightning influence: not influenced, improved and significantly improved, respectively. The last panel gives the overall influence at these 18 sites.

Page 8: Estimating the Influence of Lightning on Upper Tropospheric Ozone Using NLDN Lightning Data Lihua Wang/UAH Mike Newchurch/UAH Arastoo Biazar/UAH William.

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Model versus Sonde

0

2

4

6

8

10

12

14

16

0 50 100 150 200 250

O3 (ppbv)

Alt

itu

de

(km

)

cntrl cntrl_lnox ozonesonde

Figure 7 – Mean of 29 ozonesondes measured between 17:00 ~19:00 GMT during August 2006, as well as mean of model predictions (CNTRL and CNTRL_LNOx) at 19:00 GMT.

Figure 8 – Differences in NO, NO2 and O3 between CNTRL_LNOx and CNTRL for Huntsville, AL during August 2006, due to lightning influence.

O

3

N

O2

N

O

Figure 6 - Model predictions of ozone concentration at Huntsville, AL during August 2006, with 29 ozonesonde profiles (interpolated onto CMAQ vertical resolution) overplotted. Top: CNTRL; Bottom: CNTRL_LNOx

18 ppbv enhancement due to lightning

A case study in Huntsville, AL A case study in Huntsville, AL during August 2006 shows during August 2006 shows increased NOx in upper increased NOx in upper troposphere due to lightning-NOx troposphere due to lightning-NOx injection, and finds corresponding injection, and finds corresponding ozone enhancement around same ozone enhancement around same altitude (~10 km), but still 20 ppbv altitude (~10 km), but still 20 ppbv lower than ozonesonde lower than ozonesonde measurementmeasurement

Page 9: Estimating the Influence of Lightning on Upper Tropospheric Ozone Using NLDN Lightning Data Lihua Wang/UAH Mike Newchurch/UAH Arastoo Biazar/UAH William.

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Consistent with Cooper et al., 2009Consistent with Cooper et al., 2009

Figure 9 - Left: Monthly average location of a 20-day passive LNOx tracer that has been allowed to decay with a 4-day e-folding lifetime, indicating the regions where LNOx would most likely be found, as well as the regions where ozone production would most likely occur, for July through September 2006 [Cooper et al., 2009]. Right: Median filtered tropospheric ozone (FTO3) mixing ratios during August 2006 at all 14 IONS06 measurement sites between 10 and 11 km. FTO3 is the measured ozone within the troposphere with the model calculated stratospheric ozone contribution removed [Cooper et al., 2007].

Page 10: Estimating the Influence of Lightning on Upper Tropospheric Ozone Using NLDN Lightning Data Lihua Wang/UAH Mike Newchurch/UAH Arastoo Biazar/UAH William.

DC3 in 2012DC3 in 2012

May ~ June 2012

NCAR HIAPER aircraft and the NASA DC8 the most extensive set of upper tropospheric

trace gas measurements ever obtained above the south-central United States, with a focus on thunderstorm outflow.

DC3 provides an excellent opportunity to correct the deficiencies in chemical transport models regarding LNOx production, ozone/NOx lifetime and ozone production rates in the upper troposphere.

Page 11: Estimating the Influence of Lightning on Upper Tropospheric Ozone Using NLDN Lightning Data Lihua Wang/UAH Mike Newchurch/UAH Arastoo Biazar/UAH William.

Huntsville, AL in DC3Huntsville, AL in DC3 Huntsville, Alabama is identified as an ideal location to

monitor the build-up and decay of the UTOM due to its location at or near the center of the UTOM [Cooper, et al., 2006; Cooper, et al., 2007; Cooper, et al., 2009].

The ozone lidar will be the primary instrument as it is more cost effective.

Near-daily tropospheric ozone profiles over a 16-week period from June 1 through September 21, 2012

WRF-CHEM chemical transport model at fine resolution (12 km) over the continental United States:

(1) In situ trace gas measurements from the NCAR and NASA aircraft to constrain LNOx production rates and ozone/NOx lifetimes in the upper troposphere.

(2) to quantify the sources of the UTOM during June-September 2012.


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