# Presentation: 663519

##  Constraining the lightning NOx source  estimate over North America  using TES, NLDN data and the GEOS-Chem model 

**L. Jourdain, S. S. Kulawik, H. Worden, K. Pickering,**
**B. Fisher,  D. Rider, A. Thompson** **and the TES team**
**                   **
**                   ****Jet Propulsion Laboratory**

## Motivations

- Cooper et al. (2007)

** ****Tropospheric O****3 ****vmr from ozonesondes (IONS) for August 2006  between 10-11 km.**

- Martin  et al. (2005)

**10e15 molecules/cm2s**

**Strength of the lightning NOx emissions remain largely uncertain.**
-         (Recent overview : 5 TgN/yr +/-3 TgN/yr (or +/- 60%) **Schumann and Huntrieser  [2007]**).**  **
**     **
**Understanding this source is critical to assess **
**                    ****- impact of future NOx changes on ozone in the upper troposphere                 **
**                    ****- feedback  between climate change and lightning. **
**  ****Over the USA, lightning NOx contribute to**
**                                        ****- Summertime upper tropospheric ozone maximum**
**                                        ****- pollution exported from North America**

**Motivations**

**Tropospheric NO2 columns from SCIAMACHYin May-October 2004**

**Notes:**
We have measurements described these 2 2 phenomena that are observed and illustrtated in these 2 pictures

## Methodology

**Compute 5-days forward trajectories from the  1 x 1 gridded and hourly averaged flashes from National Lightning Detection Network for July and August  2006** (National Lightning Detection Network) using HYSPLIT model driven by the GDAS meteorology. Trajectories initialized at 8 km.
**Look for the intersection of trajectories with the TES track **
-       criteria for  coincidences : +/- 1 degree lat/lon, +/- 1 hour
**Run the Global 3D CTM GEOS-Chem (v7-04-09) for Jan-August 2006**,
-      sample model along the TES track, apply the TES operator.
-  **Compare TES and GEOS-Chem prediction**  for the cases where lightning influences were found in the TES data.
**Sensitivity studies  to the lightning source strength** **and distribution** were performed to understand the discrepancy between TES and GEOS-Chem.

**Notes:**
In order to investifate whetre TES ciuld provide some additionnal contratints on the strenght of tid source in particular over the USA. For comparisons with TES, the model profiles are sampled along the Aura orbit track at the observation times, and interpolated onto the TES pressure grid. In order to take into account the vertical sensitivity of each TES retrieval, the model profiles are transformed using the TES observation operator, which is composed of the averaging kernel 
It is impportant to note that we have performed a very large number of SS over the region of interest of this study and USA durinf this summer 2006. Here is the coverage  

## Previous work using the GEOS-Chem model

***Hudman et al. [2007]***

***Martin et al. [2005]***

**Observations and model simulations from ICARTT **
**campaign over eastern N. America in summer 2004**

**Tropospheric NO2 columns from SCIAMACHY and model in May-October 2004**

**GEOS-chem x1**

**GEOS-chem x4**

- These studies had to increase the lightning source by a factor 4 to match NOx
- and ozone measurements
- Possible reason for the discrepancy : distribution of the lightning in the model

**Notes:**
mentionned

## * Baseline Simulation  S1:

**Lightning source scaled to total  6 TgN/yr globally                                            **
**+ lightning regionally scaled to OTD/LIS climatology  **

- Resulting  Source :  0.1 TgN in July 2006 over the USA (  =260 moles NO /Flash in mean consistent with **Schumann and Huntrieser  [2007]****).**

**Flash/km2/yr**

- Regional and
- Global scaling
- to OTD/LIS

- OTD/LIS Climatology

- GEOS-Chem original

- GEOS-Chem  S1

**** Simulation  S0:***
**No lightning source over the USA**

**Notes:**
I had to take care in my different simulations  of that checked 

## * Sensitivity to the distribution of the lightning source 

***= Simulation  S2: ***
**Lightning scaled to NLDN observations over the USA for July 2006 **

**Flash/km2/yr**

- Scaling to
- NLDN data
- over the US

- GEOS-Chem S1

- GEOS-Chem  S2

- Resulting  Source :  0.14 TgN in July 2006  over the USA

**** Sensitivity to the strength of the lightning source***
***    ******= Simulation  S3: ***
**S1 x 2    **520 moles NO/Flash in mean close to **Decaria et al. [2005] **
- Resulting  Source :  0.2 TgN for July 2006  over the USA

**Flash/km2/yr**

**Flash/km2/yr**

- on daily
- basis

**IC/CG is from**
**Boccippio et al. [2001]**

## TES Observes ozone enhanced layers influenced by lightning

**Hysplit Trajectories from NLDN Flashes 07/08/2006 (subset)**

_**TES Run 4497, 07/12/2006**_

**TES Observes ozone enhanced layers influenced by lightning**

**Pressure**

## TES/GEOS-Chem Comparison (07/12/06, Run 4497)

- +AVK

**Difference between  GEOS-Chem**
**baseline (S1) and  without LNOx  (S0)**

**+AVK**

**DOF**

**Lightning Influence inferred from  NLDN and HYSPLIT**

**Enhancement also seen in  **
**GEOS-Chem (LNOx : 0.1 Tg N/month S1)**
**but TES-GEOS-CHEM > 25 ppbv **

- +AVK

- +AVK

**Notes:**
the model profiles are sampled along the Aura orbit track at the observation times, and interpolated onto the TES pressure grid. In order to take into account the vertical sensitivity of each TES retrieval, the model profiles are transformed using the TES observation operator, which is composed of the averaging kernel and the 
We have calculated the degrees of freedom for signal (DOF), as defined in Rodgers [2000], to quantify TES vertical sensitivity to real atmospheric variability.  The DOF for the whole tropospheric profile varies between 1.5 and 1.7 over a latitude range of 30S to 10N as shown in Figure 2.  Between 10N-18S, the middle/upper tropospheric (500 hPa to tropopause) as well as the lower tropospheric (surface to 500hPa) part of the retrievals have a DOF of about 0.7-0.8 each. 

## Sensitivity study to the strength of the lightning source

**(LNOx : 0.2 Tg N/month S3)**

**Sensitivity study to the strength of the lightning source**
**                        **

**. Test  a production of 520 mol NO/Flash more consistent with Decaria et al. [2005]  **

**(LNOx : 0.1 Tg N/month S1)**

**- Better agreement with TES with 0.2 TgN  for the lightning NOx source in July 2006**
** ****over the USA (simulation S3)**

**Notes:**
number

## Comparison between TES and GEOS-Chem for 

**TES locations influenced by lightning **

**S0   : no lightning source**
**S1   : Baseline 0.10 TgN/month **
**S2   : scaling to NLDN **
**          ****0.14 TgN/month**
**S3   : S1x 2  520 mol NO/Flash **
**         ****0.20 TgN/month  **

- - Bias between TES and GEOS-Chem:
- Change  from 260 moles NO/Flash (S1) [**Schumann and Huntrieser, 2007]**
-  to 520 moles NO/Flash (S3) **[ De Caria et al., 2005]  **reduced the bias by  8 ppbv.

**   ****GEOS-Chem – TES (300 hPa)**

**Notes:**
Organized flux.

## Comparison between TES and GEOS-Chem for 

**TES locations influenced by lightning**

-  Correlation between TES and GEOS-Chem at 300 hPa:
-  0.4-0.6 depending the latitude,
- same for all the simulations even when NLDN  lightning distribution is imposed (S2).

**P ( lightning in GEOS-Chem > 0 / when NDLN lightning >0)**

**July2006**
**(Daily mean used and gridded**
**over GEOS-Chem grid )**

- -> convective events that are influencing the air masses sounded by TES over
- the US captured by the model

**%**

**Notes:**
This was done for each grid box and using daily mean value

## Conclusions

** ****We show evidence of ozone enhanced layers influenced by lightning in the TES data over the USA in summer 2006 using National lightning Detection Network and Hysplit.**
** ****The GEOS-Chem model confirms the influence of the NOx lightning emissions to the ozone enhancements seen by TES. The model underestimates the intensity (by  19 ppbv in mean) of these ozone enhancement layers . **
**2 sensitivity studies :**
**	****(1) the distribution of the lightning source set to NLDN : ****does not change **
**	****      ****the comparison between TES and GEOS-Chem.**
**	****(2) increase NO production/Flash from 260 to 520 mol NO/Flash ( Decaria **
**                   ****et al., 2005)** **:   ****improves the comparison between TES and GEOS-**
**                    ****Chem.  The disagreement  is reduced from -19 ppbv to -12 ppbv.**
** ****Possible reasons for the remaining discrepancy between TES and GEOS-Chem include the vertical distribution of lightning NOx emissions, Strat-Trop exchange.**

**Notes:**
Possibly relate this to deficiencies in the lightning Nox param Updated estimate of the NO/flash

## Comparison between TES, GEOS-CHEM and IONS data

- In the upper troposphere :
- Bias between TES- Sondes:  5 to 15 ppbv  Worden et al. [2007]
- Bias between GEOS-CHEM - Sondes:   -10 to -40 ppbv
- -> focus our study at 300 hPa

**Notes:**
We focus 300 hPa because the bias is 6 ppbv there. 

## PDF of ozone differences in GEOS-Chem 

**due to lightning at the TES locations recently influenced by convection  **

- PDF

## Comparison GEOS-Chem/TES for July 2006 

|                  | Correlation  |  Bias (ppbv) | RMS (ppbv) |
| --- | --- | --- | --- |
| GEOS-Chem (S1)  vs TES | 0.68 | -20 | 31 |
| A priori vs TES | 0.32 | 25 | 49 |

**Comparison GEOS-Chem/TES for July 2006 **

- Statistics for the July Step and Stare over the US (78 S&S at 300 hPa)

-  High correlation between TES and GEOS-Chem (significantly larger than
- TES/IG)

**Notes:**
Provide direction to improve this soiurde

## Testing our understanding of the lightning source

**Difference in O3 between the 2 simulations (S1-S0) for a particular day at 300hPa**

**(07/21/2006)**

- Is the bias between TES and GEOS-Chem  the same for these 2 type of locations ?

- Some agreement between our analysis with NLDN and Hysplit and
- the sensitivity study performed with GEOS-Chem.
- But  some inconsistencies are highlighted.
- For our analysis,  we define:
- TES data non influenced by lightning  as :
-                       -TES locations non influenced ( with NLDN and Hysplit)
-                        and S1-S0 < 2ppbv
- TES data strongly  influenced by lightning as :
-                       -TES locations influenced  ( with NLDN and Hysplit)
-                        and  S1-S0 > 10ppbv

- Some agreement between our analysis with NLDN and Hysplit and
- the sensitivity study performed with GEOS-Chem.
- But  some inconsistencies are highlighted.
- For our analysis,  we define:
- TES data non influenced by lightning  as :
-                       -TES locations non influenced ( with NLDN and Hysplit)
-                        and S1-S0 < 2ppbv
- TES data strongly  influenced by lightning as :
-                       -TES locations influenced  ( with NLDN and Hysplit)
-                        and  S1-S0 > 10ppbv

- (ppbv)

- Location strongly influenced by lightning

- Location with limited influence
- by lightning

## Selection of the TES data recently and non recently influenced by lightning 

**PDF of ozone differences in GEOS-Chem due to lightning (S1-S0) at the TES locations  **

**TES locations with no influence from lightning,less than 5 days before,  according to the analysis **
**done with NLDN and  Hysplit**

**PDF**

**Ozone differences in ppbv **

**TES locations with  influence from lightning less than 5 days before  according to the analysis  done with NLDN and  Hysplit**

- Some agreement between our analysis with NLDN and Hysplit and
- the sensitivity study performed with GEOS-Chem.
- But  some inconsistencies are highlighted.
- For our analysis,  we define:
- TES data non influenced by lightning  as :
-                       -TES locations non influenced ( with NLDN and Hysplit)
-                        and S1-S0 < 2ppbv
- TES data strongly  influenced by lightning as :
-                       -TES locations influenced  ( with NLDN and Hysplit)
-                        and  S1-S0 > 10ppbv

- Some agreement between our analysis with NLDN and Hysplit and
- the sensitivity study performed with GEOS-Chem.
- But  some inconsistencies are highlighted.
- For our analysis,  we define:
- TES data non influenced by lightning  as :
-                       -TES locations non influenced ( with NLDN and Hysplit)
-                        and S1-S0 < 2ppbv
- TES data strongly  influenced by lightning as :
-                       -TES locations influenced  ( with NLDN and Hysplit)
-                        and  S1-S0 > 10ppbv

- Some agreement between our analysis with NLDN and Hysplit and
- the sensitivity study performed with GEOS-Chem.
- But  some inconsistencies are highlighted.
- For our analysis,  we define:
- TES data non influenced by lightning  as :
-                       -TES locations non influenced ( with NLDN and Hysplit)
-                        and S1-S0 < 2ppbv
- TES data strongly  influenced by lightning as :
-                       -TES locations influenced  ( with NLDN and Hysplit)
-                        and  S1-S0 > 10ppbv

- Some agreement between our analysis with NLDN and Hysplit and
- the sensitivity study performed with GEOS-Chem.
- But  some inconsistencies are highlighted.
- For our analysis,  we define:
- TES data non influenced by lightning  as :
-                       -TES locations non influenced ( with NLDN and Hysplit)
-                        and S1-S0 < 2ppbv
- TES data strongly  influenced by lightning as :
-                       -TES locations influenced  ( with NLDN and Hysplit)
-                        and  S1-S0 > 10ppbv

- Some agreement between our analysis with NLDN and Hysplit and
- the sensitivity study performed with GEOS-Chem.
- But  some inconsistencies are highlighted.
- For our analysis,  we define:
- TES data non influenced by lightning  as :
-                       -TES locations non influenced ( with NLDN and Hysplit)
-                        and S1-S0 < 2ppbv
- TES data strongly  influenced by lightning as :
-                       -TES locations influenced  ( with NLDN and Hysplit)
-                        and  S1-S0 > 10ppbv

- Some agreement between our analysis with NLDN and Hysplit and
- the sensitivity study performed with GEOS-Chem.
- But  some inconsistencies are highlighted.
- For our analysis,  we define:
- TES data non influenced by lightning  as :
-                       -TES locations non influenced ( with NLDN and Hysplit)
-                        and S1-S0 < 2ppbv
- TES data strongly  influenced by lightning as :
-                       -TES locations influenced  ( with NLDN and Hysplit)
-                        and  S1-S0 > 10ppbv

- TES data non influenced by lightning  :
-                       -TES locations non influenced ( with NLDN and Hysplit)
-                        and S1-S0 < 2ppbv
- TES data strongly  influenced by lightning  :
-                       -TES locations influenced  ( with NLDN and Hysplit)
-                        and  S1-S0 > 10ppbv

- Selection of the TES data recently and non recently influenced by lightning

**Notes:**
Look at PDF lat, lon of black sup 4 ppbv ( inf 4 ppbv  air from thePacific)
Look again at PDF of TES ozone  of black and red

## Bias for  recently influenced or non recently influenced by lightning 

**Bias TES-GEOS-Chem in (ppbv)**

**Bias TES-GEOS-Chem in (ppbv)**

**Bias TES-GEOS-Chem in (ppbv)**

**LNOx in GEOS-Chem in TgN/year**

**LNOx in GEOS-Chem in TgN/year**

**LNOx in GEOS-Chem in TgN/year**

**Latitude band 30-35N**

**Latitude band 35-40 N**

**Latitude band 40-45 N**

**S0**** **

**S1**** **

**S1**** **

**S0**** **

**S1**** **

**S0**** **

- Nb=192
- Nb=492

- Nb=1215
- Nb=632

- Nb=611
- Nb=195

- For cases non influenced by lightning : bias increases with increasing latitude
- For cases strongly influenced by lightning :
- For lat > 35N : biases the same in the non influenced and influenced cases
- For lat < 35 : the bias in the air masses recently influenced by lightning is larger (15ppbv) than in the air masses non  influenced (2ppbv).

- Non influenced cases

- Influenced cases

- Bias for  recently influenced or non recently influenced by lightning
- cases

**Notes:**
The other possible problems contributing to the bias are 

## CH4 lifetime in GEOS-chem

- years

- month

- 7.5 years < 9.6 years (IPCC 2001)
- Overestimation of OH

- H2O NCEP JJA

- H2O  GEOS-CHEM JJA

**NOx lifetime depends on OH **

- Overestimation Of H2o in  GEOS-Chem particularly tropics
- And  DJF

## Distribution  of the lightning activity in GEOS-Chem  for July 2006

***4 simulations :***
*** S1 lightning source scaled to total  6 TgN/yr globally                                                 **
**                           ****+ lightning regionally scaled to OTD/LIS climatology  **
-         Resulting  Source totals :  0.5 TgN/year over the USA (  =260 moles/Flash in mean)
*** S2 lightning scaled to NLDN observations over the USA for July 2006 **
-         Resulting  Source totals :  0.6 gN/year over the USA
- ***S3 = S1 x 2 over the USA ( Testing K. Pickering recent work)**
**        **Resulting  Source totals :  1 TgN/year over the USA (= 520 moles /Flash in mean)
- * **S0 lightning source shut off over the USA** ( initialized the 1st March 2006 with S1)

**Notes:**
Before running the GEOS-Chem model, we had to evaluate the loightning activity in the GEOS-Chem model and compare it to OTD/lis

## Ozone enhanced layers influenced by lightning in the TES data

**Pressure**

- ppbV

_**TES Run 4537, 07/16/2006**_

**Hysplit Trajectories from NDLN Flashes 07/14/2006 (subset)**

**Ozone enhanced layers influenced by lightning in the TES data**

## TES/GEOS-Chem Comparison (07/16/06)

**TES/GEOS-Chem Comparison (07/16/06)**

**( LNOx : 1 Tg N/year S1)**

**( LNOx :  0 Tg N/year S1)**

**( LNOx : 0.25 Tg N/year S1)**

**Lightning**
**influence**
**inferred **
**from NLDN**
**and HYSPLIT**

**+AVK**

**+AVK**

**+AVK**

- +AVK

- +AVK

## Methodology

**Compute 5-days forward trajectories from the  1 x 1 gridded and hourly averaged flashes from NLDN** (National Lightning Detection Network) using HYSPLIT model driven by the GDAS meteorology. Trajectories initialized at 8 km.
**Look for the intersection of trajectories with the TES track **
-       criteria for  coincidences : +/- 1 degree lat/lon, +/- 1 hour
**Run the Global 3D CTM GEOS-Chem  for Jan-August 2006**,
-      sample model along the TES track, apply the TES operator.
-  **Compare TES and GEOS-Chem prediction**  for the cases where lightning influences were found in the TES data.
**Sensitivity studies  to the lightning source strength** were performed to understand the discrepancy between TES and GEOS-Chem.

**Notes:**
For comparisons with TES, the model profiles are sampled along the Aura orbit track at the observation times, and interpolated onto the TES pressure grid. In order to take into account the vertical sensitivity of each TES retrieval, the model profiles are transformed using the TES observation operator, which is composed of the averaging kernel 

## Comparison between TES, GEOS-CHEM and IONS data

- ppbv

- Mean Profiles

- SONDES

- TES

- IG

- Model+AVK

- (GEOS-CHEM-TES)

- (TES-SONDES)

- BIAS +RMS

- (GEOS-CHEM-SONDES)

- In the upper troposphere :
- Bias between TES- Sondes:  5 to 15 ppbv
- Bias between GEOS-CHEM - Sondes:   -10 to -40 ppbv
- -> focus our study at 300 hPa

**Notes:**
We focus 300 hPa because the bias is 6 ppbv there. 

## Distribution  of the lightning activity in different versions of GEOS-Chem

**for July 2006**

- Original version

- Regional and Global
- Scaling (this work)

- Percent of Total Flashes

- Latitude

- Latitude

- Latitudinal variation of Flashes

- F/s/2.5 lat

- %F/2.5 lat

- F/s/2.5 lat

- %F/2.5 lat