Summary of the Final Report of Research Results1) Title of the proposed research
Modeling of the CO2 and CH4 fluxes using advanced mathematical techniques
2) Principal Investigator (PI) and Co-Investigators (Co-Is)
PI:
Prof. Emil Pelikán
Co-I:
Dr. Ing. Marek Brabec
Dr. Mgr. Pavel Jurus
Prof. Milan Palus
Dr. Martin Vejmelka
Dr. Pavel Krc
Dr. Ing. Petr Musilek
3) PI’s affiliation
Institute of Computer Science, Academy of Sciences of the Czech Republic4) Summary of the Final Report of Research Results
The main part of utilizing GOSAT data was aimed towards regional-scale modelling of CO2
concentrations and CO2 fluxes. Most of the activities in the field of anthropogenic emissions
typically addresses reporting and creation of annual inventories. We tried to complement thisapproach by evaluating the role of regional-scale models as the tools that connect in high spatial andtemporal resolution atmospheric concentrations and surface fluxes.
We have set up a testing domain in Northern Alberta, Canada, which has only a few dominantsources of GHG emissions but nevertheless it contains important industrial area of Athabasca oilsands where monitoring, continuous evaluation of GHG inventory, and modelling of the impact ofpotential future changes is advisable. The modelling system consists of the numerical weather model,
chemical transport model (although atmospheric chemistry is not of the real concern in case of CO2,
CTM model is used here mainly for its dispersion part), and model of both biogenic andanthropogenic fluxes.
The results showed fairly good agreement of biogenic surface fluxes and also acceptable agreementof the CO2 concentrations during the daytime. Nighttime peaks in concentrations which are notcorrectly captured by a model can be attributed to incorrectly modelled turbulent mixing and wehave introduced the method of statistical postprocessing of the model to amend this behaviour.

After the verification of the modelling system for CO2 fluxes and concentration on regional scaleversus in-situ flux tower measurements we proceeded with the verification of modelling systemversus GOSAT observations. We have compared the two types of quantities related to CO2concentrations provided by GOSAT project. The first variable is the total column of CO2, a verticalsum of CO2 at the point of measurement. The second is the column-averaged molar fraction of CO2(XCO2), computed as the total column of CO2 divided by the total column of dry air. Dry aircolumns are based on the operational analysis data provided by the Japan Meteorological Agency(JMA).
In order to compare the GOSAT observations with the simulation results, CO2 total columns arecalculated from the model output by summing over all vertical levels. The dry air columns arecomputed in similar fashion. The XCO2 is a simple ratio of those two quantities. The dry aircolumns assumed in GOSAT data are not available directly, but can be derived simply as the ratio of
CO2 column and XCO2, provided by GOSAT.
The comparisons of model versus GOSAT observations shows in general high correlation of themodel and observations. To get unbiased model results for both CO2 and dry air columns we had toadd a compensation for the fact that the model has limited vertical height up to 100 hPa meaning thatabout top 10% of the atmosphere mass is not represented by the model. After this correction, thevalue of mean percentage error changed from -10.4% to -0.482% for the CO2 columns, and from-10.9% to -0.17% for the dry air columns. However, even after the correction, the XCO2 values
show much higher variance for observed values by GOSAT compared to modelled values.
We hypothesize that the difference between model and GOSAT data is caused by the fact that theXCO2 in the model is computed by dividing a modeled CO2 column by a modeled dry air column
which are highly correlated (because CO2 is well mixed in higher layers of the atmosphere), as areerrors in CO2 and dry air quantities. Most of the error in both CO2 and dry air quantities is not due
to the incorrect concentration of CO2, as that is almost constant, especially in higher layers of themodel. Rather, an incorrect distribution of air mass is likely to contribute significantly to the errors.
It affects both the CO2 column and the dry air column proportionally. As a result, division of the twoquantities leads to a reduction in the overall variance. The results obtained by the WRF-VPRM in
this study comply with a study of XCO2 distribution by Olsen and Randerson (2004).
In the case of GOSAT, the CO2 columns are observed, but the dry air columns originate from themeteorological model. Errors in those two quantities can therefore be considered uncorrelated(although some hidden correlation is still possible due to the retrieval algorithms, which often use anumber of model-derived atmospheric variables). The error in the distribution of air mass is thus
amplified: the CO2 column based on a real air mass distribution is divided by a dry air column basedon a modeled air mass distribution. Division in this case causes further nonlinear propagation oferrors and larger overall variance.
Apart from regional-scale CO2 modelling, the GOSAT project data are directly or indirectly used inother activities. One of the uses is for the general spatial and spatio-temporal analysis methods – thetesting and development of the methods as well as for educational purposes – the GOSAT data playpart in promoting science among high-school and university students and in teaching basic
approaches for scientific datasets processing, analysis and visualization. Analysis of GOSAT data
was for example one of the university student projects during international student summer school“Schola ludus”.
Another activity which is partly inspired by GOSAT project is the ongoing investigation andmodelling of atmposphere/ocean CO2 fluxes. Although the GOSAT data have not be utilized yet, we
envision the verification using all available satellite data including the GOSAT in the next stages ofthe research.
5) List of publications relating to the proposed research(In addition, if there are any publication plans, please also describe them as well.)J. Rodway, P. Jurus, P. Musilek, Tracking Greenhouse Gases From Space: Dealing with Missing
Data, 6th Annual University of Alberta Space Symposium, September 25-26, 2009.
P. Jurus, Possibilities for greenhouse gas fluxes modelling, Workshop on modelling of greenhousegas fluxes in ecosystems, Prague, February 24, 2010.
P. Jurus, Relating ground- and satellite-based CO2 observations, Earth Observation Sciences Day,Edmonton, March 4, 2010.
J. Rodway, K. Filimonenkov, Y. Li, P. Jurus, P. Musilek, Source Constitution of Carbon Dioxide inthe Atmosphere: Analysis and Visualization, First Annual Graduate Research Symposium, Edmonton,June 17, 2010
P. Jurus, P. Musilek, Y. Li, J. Rodway, K. Filimonenkov, E. Pelikan, Towards regional-scalemodelling of industrial CO2 emissions, 12th Symposium of the International Commission on
Atmospheric Chemistry and Global Pollution (CACGP), 11th Science Conference of theInternational Global Atmosphere Chemistry (IGAC) Project Halifax, Canada, July 1116, 2010.

P. Jurus, M. Brabec, P. Krc, E. Pelikan, P. Musilek, Utilisation of micrometeorological variables inregional-scale CO2 modelling, Verification and validation in meteorology, climatology and airquality, Annual Workshop of the Czech Meteorological Society, Bozi Dar, September 22-24, 2010.
P. Jurus, P. Musilek, Y. Li, J. Rodway: “Regional-scale modeling of greenhouse gas fluxes,” in„Restoration and Reclamation of Boreal Ecosystems. Attaining Sustainable Development.”
Cambridge University Press, 2012 - (Vitt, D.; Bhatti, J.), p. 23-55 ISBN 978-1-107-01571-5
P. Jurus, J. Resler, K. Eben, E. Pelikan: Towards satellite data assimilation using adjoint in an
Eulerian regional-scale model, 3rd PI meeting of GOSAT Project, Edinburgh, UK, May 19-20, 2011
Vieira, V. M. N. C. S., Sahlée, E., Jurus, P., Clementi, E., Pettersson, H., & Mateus, M. (2015).
Comparing solubility algorithms of greenhouse gases in Earth-System modelling. Biogeosciences
Discussions, 12(18).
Vieira, V. M. N. C. S., Sahlée, E., Jurus, P., Clementi, E., Pettersson, H., & Mateus, M. (2015).
Improving estimations of greenhouse gas transfer velocities by atmosphere–ocean couplers inEarth-System and regional models. Biogeosciences Discussions, 12(18).