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RESEARCH POSTER PRESENTATION DESIGN © 2012 www.PosterPresentations.com Data assimilation is a method of correcting or forcing an iterative model with physical observations to improve the accuracy of the output. We use a Kalman filter to assimilate the satellite data into GEOS-Chem The Kalman Filter Background and Mo6va6on Objec6ve The Asian Monsoon is a phenomena which affects many weather patterns in the northern hemisphere. Most atmospheric models fail to capture the O 3 minimum and CO maximum in the upper troposphere characteristic of the Monsoon Region. (see Figure 1) Figure 1 MLS O 3 /CO Average in Stratospheric Monsoon Region for (Jul-Aug) 2005 [1] This is caused by convective transport from the lower troposphere where CO is abundant. This convective flow is fast enough that there is not significant O 3 production. TES data has been assimilated into the model in an attempt to recreate this ozone minimum. The output of this assimilation still failed to capture the ozone minimum expected (see Figure 2) What is Data Assimila6on? Figure 5 GEOS-Chem O 3 Assimilation at 15.2 km with IASI Data Preliminary Results Conclusions Assimilating IASI data into GEOS-Chem model provides a relatively improved representation of the O 3 minimum This result may not be representative of the physical processes which actually cause this minimum. Further investigation into what aspects of the model are limiting it’s ability to model upper tropospheric O 3 must be conducted. We decided to use the IASI retrieval data set because of it’s superior data density. (see Figure 3) To do this the code used to assimilate TES data was modified to account for IASI retrievals done in altitude while TES was done in pressure levels TES profiles had to be passed through a logarithmic transform IASI’s did not Much larger file sizes in the IASI profiles (optimized input subroutine) After assimilating the model over a five day period with data from August 15 th to the 20 th in 2008 the plot in Figure 5 was generated. Compared to Figure 2 the IASI assimilation was much more successful at raising ozone levels globally with the exception of the Asian Monsoon region. The results are a relatively good representation of the observations in Figure 1. Figure 4 shows the GEOS-Chem simulation on the same time scale as Figure 5 but with no data used for assimilation. Figure 4 GEOS-CHEM O 3 Simulation at 15.2 km with no Data Assimilation It is clear that the assimilation raised O 3 throughout the tropics but this may not have occurred for physically plausible reasons. Preliminary Results Figure 2a GEOS-Chem O 3 Assimilation at 14.2 km with TES Data [1,2] Ryan Ples.d, [2] Dylan Jones, [3] Maya George, [3] Cathy Clerbaux 1‐University of Guelph, Department of Physics 2‐University of Toronto, Department of Physics 3‐UPMC, LATMOS, Paris, France Examining GEOS‐CHEM’s Biases Through Data Assimila6on ˆ x a = x f + K[x obs ! H ( x f ) ] K = P f H T (HP f H T + R) !1 P a = (I - KH)P f Methods Determine if data assimilation can correct GEOS-Chem Ozone simulation in the Asian Monsoon Region Figure 3b IASI Satellite’s Single Day Coverage August 15 th 2008 References [1] Park, M., W. J. Randel, A. GeVelman, S. T. Massie, and J. H. Jiang (2007), Transport above the Asian summer monsoon an.cyclone inferred from Aura Microwave Limb Sounder tracers, J. Geophys. Res., 112, D16309, doi:10.1029/2006JD008294. [2] Randel, W. J., and M. Park (2006), Deep convec.ve influence on the Asian summer monsoon an.cyclone and associated tracer variability observed with Atmospheric Infrared Sounder (AIRS), J. Geophys. Res., 111, D12314, doi:10.1029/2005JD006490. Acknowledgements Ellen Dyer, The CGCS, Gregory Wu, Thomas Walker, Dylan Jones, Daniel Backx, and Kevin Olsen Figure 2b GEOS-Chem O 3 Difference (assimilation minus without assimilation) Tropospheric Emission Spectrometer (TES) assimila6on in GEOS‐Chem Infrared Atmospheric Sounding Interferometer (IASI) Coverage TES Daily Observa6onal Coverage Figure 3a TES Single Day Coverage September 16 th 2006 Figure 3 IASI Satellite’s Single Day Coverage September 16 th 2008 Figure 3 IASI Satellite’s Single Day Coverage September 16 th 2008 GEOS‐Chem O 3 at 15 km at 0 GMT on 24 Aug 2008 GEOS‐Chem O 3 at 15 km at 0 GMT on 24 Aug 2008

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Data assimilation is a method of correcting or forcing an iterative model with physical observations to improve the accuracy of the output.

We use a Kalman filter to assimilate the satellite data into GEOS-Chem The Kalman Filter

Background and Mo6va6on  Objec6ve The Asian Monsoon is a phenomena which affects many weather patterns in the northern hemisphere.

Most atmospheric models fail to capture the O3

minimum and CO maximum in the upper troposphere characteristic of the Monsoon Region. (see Figure 1)

Figure 1 MLS O3/CO Average in Stratospheric Monsoon Region for (Jul-Aug) 2005 [1]

This is caused by convective transport from the lower troposphere where CO is abundant. This convective flow is fast enough that there is not significant O3 production.

TES data has been assimilated into the model in an attempt to recreate this ozone minimum. The output of this assimilation still failed to capture the ozone minimum expected (see Figure 2)

What is Data Assimila6on? 

Figure 5 GEOS-Chem O3 Assimilation at 15.2 km with IASI Data

Preliminary Results  

Conclusions Assimilating IASI data into GEOS-Chem model provides a relatively improved representation of the O3 minimum This result may not be representative of the physical processes which actually cause this minimum. Further investigation into what aspects of the model are limiting it’s ability to model upper tropospheric O3 must be conducted.

We decided to use the IASI retrieval data set because of it’s superior data density. (see Figure 3) To do this the code used to assimilate TES data was modified to account for

•  IASI retrievals done in altitude while TES was done in pressure levels

•  TES profiles had to be passed through a logarithmic transform IASI’s did not

•  Much larger file sizes in the IASI profiles (optimized input subroutine)

After assimilating the model over a five day period with data from August 15th to the 20th in 2008 the plot in Figure 5 was generated. Compared to Figure 2 the IASI assimilation was much more successful at raising ozone levels globally with the exception of the Asian Monsoon region. The results are a relatively good representation of the observations in Figure 1. Figure 4 shows the GEOS-Chem simulation on the same time scale as Figure 5 but with no data used for assimilation.

Figure 4 GEOS-CHEM O3 Simulation at 15.2 km with no Data Assimilation

It is clear that the assimilation raised O3 throughout the tropics but this may not have occurred for physically plausible reasons.

Preliminary Results  

Figure 2a GEOS-Chem O3 Assimilation at 14.2 km with TES Data

[1,2]Ryan Ples.d, [2]Dylan Jones, [3]Maya George, [3]Cathy Clerbaux  

1‐University of Guelph, Department of Physics 2‐University of Toronto, Department of Physics 3‐UPMC, LATMOS, Paris, France 

Examining GEOS‐CHEM’s Biases Through Data Assimila6on  

x̂a = x f +K[xobs ! H (x f )]K = P fHT(HP fHT + R)!1

Pa = (I -KH)P f

Methods 

Determine if data assimilation can correct GEOS-Chem Ozone simulation in the Asian Monsoon Region

Figure 3b IASI Satellite’s Single Day Coverage August 15th 2008

References  [1]  Park, M., W. J. Randel, A. GeVelman, S. T. Massie, and J. H. Jiang (2007), Transport above the Asian summer monsoon an.cyclone inferred from Aura Microwave Limb Sounder tracers, J. Geophys. Res., 112, D16309, doi:10.1029/2006JD008294.  [2] Randel, W. J., and M. Park (2006), Deep convec.ve influence on the Asian summer monsoon an.cyclone and associated tracer variability observed with Atmospheric Infrared Sounder (AIRS), J. Geophys. Res., 111, D12314, doi:10.1029/2005JD006490. 

Acknowledgements Ellen Dyer, The CGCS, Gregory Wu, Thomas Walker, Dylan Jones, Daniel Backx, and  Kevin Olsen 

Figure 2b GEOS-Chem O3 Difference (assimilation minus without assimilation)

Tropospheric Emission Spectrometer (TES) assimila6on in GEOS‐Chem 

Infrared Atmospheric Sounding Interferometer (IASI) Coverage 

TES Daily Observa6onal Coverage 

Figure 3a TES Single Day Coverage September 16th 2006

Figure 3 IASI Satellite’s Single Day Coverage September 16th 2008

Figure 3 IASI Satellite’s Single Day Coverage September 16th 2008

GEOS‐Chem O3 at 15 km at 0 GMT on 24 Aug 2008 

GEOS‐Chem O3 at 15 km at 0 GMT on 24 Aug 2008