scholarly journals Diagnosing the transition layer at extratropical latitudes using MLS O<sub>3</sub> and MOPITT CO analyses

2013 ◽  
Vol 13 (14) ◽  
pp. 7225-7240 ◽  
Author(s):  
J. Barré ◽  
L. El Amraoui ◽  
P. Ricaud ◽  
W. A. Lahoz ◽  
J.-L. Attié ◽  
...  

Abstract. The behavior of the extratropical transition layer (ExTL) is investigated using a chemistry transport model (CTM) and analyses derived from assimilation of MLS (Microwave Limb Sounder) O3 and MOPITT (Measurements Of Pollution In The Troposphere) CO data. We firstly focus on a stratosphere–troposphere exchange (STE) case study that occurred on 15 August 2007 over the British Isles (50° N, 10° W). We evaluate the effect of data assimilation on the O3–CO correlations. It is shown that data assimilation disrupts the relationship in the transition region. When MLS O3 is assimilated, CO and O3 values are not consistent between each other, leading to unphysical correlations at the STE location. When MLS O3 and MOPITT CO assimilated fields are taken into account in the diagnostics the relationship happens to be more physical. We then use O3–CO correlations to quantify the effect of data assimilation on the height and depth of the ExTL. When the free-model run O3 and CO fields are used in the diagnostics, the ExTL distribution is found 1.1 km above the thermal tropopause and is 2.6 km wide (2σ). MOPITT CO analyses only slightly sharpen (by −0.02 km) and lower (by −0.2 km) the ExTL distribution. MLS O3 analyses provide an expansion (by +0.9 km) of the ExTL distribution, suggesting a more intense O3 mixing. However, the MLS O3 analyses ExTL distribution shows a maximum close to the thermal tropopause and a mean location closer to the thermal tropopause (+0.45 km). When MLS O3 and MOPITT CO analyses are used together, the ExTL shows a mean location that is the closest to the thermal tropopause (+0.16 km). We also extend the study at the global scale on 15 August 2007 and for the month of August 2007. MOPITT CO analyses still show a narrower chemical transition between stratosphere and troposphere than the free-model run. MLS O3 analyses move the ExTL toward the troposphere and broaden it. When MLS O3 analyses and MOPITT CO analyses are used together, the ExTL matches the thermal tropopause poleward of 50°.

2012 ◽  
Vol 12 (8) ◽  
pp. 22023-22057
Author(s):  
J. Barré ◽  
L. El Amraoui ◽  
P. Ricaud ◽  
J.-L. Attié ◽  
W. A. Lahoz ◽  
...  

Abstract. The behavior of the Extra-tropical Transition Layer (ExTL) in the lowermost stratosphere is investigated using a Chemistry Transport Model (CTM) and analyses derived from assimilation of MLS (Microwave Limb Sounder) O3 and MOPITT (Measurements Of Pollution In The Troposphere) CO data. We use O3-CO correlations to quantify the effect of the assimilation on the height and depth of the ExTL. We firstly focus on a Stratosphere-Troposphere Exchange (STE) case study which occurred on 15 August 2007 over the British Isles (50° N, 10° W). We also extend the study at the global scale for the month of August 2007. For the STE case study, MOPITT CO analyses have the capability to sharpen the ExTL distribution whereas MLS O3 analyses provide a tropospheric expansion of the ExTL distribution with its maximum close to the thermal tropopause. When MLS O3 and MOPITT CO analyses are used together, the ExTL shows more realistic results and matches the thermal tropopause. At global scale, MOPITT CO analyses still show a sharper chemical transition between stratosphere and troposphere than the free model run. MLS O3 analyses move the ExTL toward the troposphere and broaden it. When MLS O3 analyses and MOPITT CO analyses are used together the ExTL matches the thermal tropopause poleward of 50°. This study shows that data assimilation can help overcome the shortcomings associated with a relatively coarse model resolution. The ExTL spread is larger in the Northern Hemisphere than the Southern Hemisphere suggesting that mixing processes are more active in the UTLS in the Northern Hemisphere than in the Southern Hemisphere. This work opens perspectives for studying the seasonal variations of the ExTL at extra-tropical latitudes.


2009 ◽  
Vol 9 (2) ◽  
pp. 6691-6737 ◽  
Author(s):  
S. Massart ◽  
C. Clerbaux ◽  
D. Cariolle ◽  
A. Piacentini ◽  
S. Turquety ◽  
...  

Abstract. The Infrared Atmospheric Sounding Interferometer (IASI) is one of the five European new generation instruments carried by the polar-orbiting MetOp-A satellite. Data assimilation is a powerful tool to combine these data with a numerical model. This paper presents the first steps made towards the assimilation of the total ozone columns from the IASI measurements into a chemistry transport model. The IASI ozone data used are provided by an inversion of radiances performed at the LATMOS (Laboratoire Atmosphères, Milieux, Observations Spatiales). As a contribution to the validation of this dataset, the LATMOS-IASI data are compared to a four dimensional ozone field, with low systematic and random errors compared to ozonesondes and OMI-DOAS data. This field results from the combined assimilation of ozone profiles from the MLS instrument and of total ozone columns from the SCIAMACHY instrument. It is found that on average, the LATMOS-IASI data tends to overestimate the total ozone columns by 2% to 8%. The random observation error of the LATMOS-IASI data is estimated to about 6%, except over polar regions and deserts where it is higher. Using this information, the LATMOS-IASI data are then assimilated, combined with the MLS data. This first LATMOS-IASI data assimilation experiment shows that the resulting analysis is quite similar to the one obtained from the combined MLS and SCIAMACHY data assimilation.


2016 ◽  
Author(s):  
Sergey Skachko ◽  
Richard Menard ◽  
Quentin Errera ◽  
Yves Christophe ◽  
Simon Chabrillat

Abstract. We compare two optimized chemical data assimilation systems, one based on the ensemble Kalman filter (EnKF) and the other based on four-dimensional variational (4D-Var), using a comprehensive stratospheric chemistry transport model (CTM). The work is an extension of the Belgian Assimilation System for Chemical ObsErvations (BASCOE), initially designed to work with a 4D-Var data assimilation. A strict comparison of both methods in the case of chemical tracer transport was done in a previous study and indicated that both methods provide essentially similar results. In the present work, we assimilate observations of ozone, HCl, HNO3, H2O and N2O from EOS Aura-MLS data into the BASCOE CTM with a full description of stratospheric chemistry. Two new issues related to the use of full chemistry model with EnKF are taken into account. One issue concerns to a large number of error variance parameters that need to be optimized. We estimate an observation error parameter as function of pressure level for each observed species using the Desroziers' method. For comparison reasons, we apply the same estimate procedure in the 4D-Var data assimilation, where we keep both estimates: the background and observation error variances. However in EnKF, the background error covariance is modelled using the full chemistry model and a model error term. We found that it is adequate to have a single model error based on the chemical tracer formulation that is applied for all species. This is an indication that the main source of model error in chemical transport model is due to the transport. The second issue in EnKF with comprehensive atmospheric chemistry models is the sampling errors between species. When species are weakly chemically related, cross-species sampling noise errors occur at the same location. These errors need to be filtered out, in addition to a localization based on distance. The performance of two data assimilation methods was assessed through an eight-month long assimilation of limb sounding observations from EOS Aura-MLS. The paper discusses the differences in results and their relation to stratospheric chemical processes. Generally speaking, EnKF and 4D-Var provide results of comparable quality but differ substantially in presence of model error or observation biases. If the erroneous chemical modelling is associated with not too small chemical life-times, then EnKF performs better, while 4D-Var develops spurious increments in the chemically related species. If, on the other hand, the observation biases are significant, then 4D-Var is more robust and is able to reject erroneous observations, while EnKF does not.


2020 ◽  
Author(s):  
Christian A. Schmidt ◽  
Peter Huszár ◽  
Monika Mayer ◽  
Johannes Fritzer ◽  
Harald E. Rieder

&lt;p&gt;Despite ambitious efforts to abate surface air pollution, the air quality thresholds for PM10 and PM2.5 are regularly exceeded in the state of Styria. PM target levels are most frequently exceeded in industrial regions and urban cores of the forelands preceeding the alps. Besides local emissions, ambient meteorology and particularly stagnation are of special importance for PM pollution. Here we assess local and regional changes in PM pollution following emission reduction measures, while simultaneously considering effects of meteorological variability. We further supplement our observational study with a set of high-resolution chemistry-transport-model (CTM) simulations to assess future changes in the PM burden in Styria.&lt;/p&gt;


2010 ◽  
Vol 10 (5) ◽  
pp. 2491-2506 ◽  
Author(s):  
A. Voulgarakis ◽  
N. H. Savage ◽  
O. Wild ◽  
P. Braesicke ◽  
P. J. Young ◽  
...  

Abstract. We have run a chemistry transport model (CTM) to systematically examine the drivers of interannual variability of tropospheric composition during 1996–2000. This period was characterised by anomalous meteorological conditions associated with the strong El Niño of 1997–1998 and intense wildfires, which produced a large amount of pollution. On a global scale, changing meteorology (winds, temperatures, humidity and clouds) is found to be the most important factor driving interannual variability of NO2 and ozone on the timescales considered. Changes in stratosphere-troposphere exchange, which are largely driven by meteorological variability, are found to play a particularly important role in driving ozone changes. The strong influence of emissions on NO2 and ozone interannual variability is largely confined to areas where intense biomass burning events occur. For CO, interannual variability is almost solely driven by emission changes, while for OH meteorology dominates, with the radiative influence of clouds being a very strong contributor. Through a simple attribution analysis for 1996–2000 we conclude that changing cloudiness drives 25% of the interannual variability of OH over Europe by affecting shortwave radiation. Over Indonesia this figure is as high as 71%. Changes in cloudiness contribute a small but non-negligible amount (up to 6%) to the interannual variability of ozone over Europe and Indonesia. This suggests that future assessments of trends in tropospheric oxidizing capacity should account for interannual variability in cloudiness, a factor neglected in many previous studies.


2021 ◽  
Vol 3 ◽  
pp. 150-161
Author(s):  
D.V. Borisov ◽  
◽  
I.U. Shalygina ◽  

Refinement of land use data for emission calculations in the CHIMERE chemistry-transport model: A case study for the Nizhny Novgorod region / Borisov D.V., Shalygina I.U. // Hydrometeorological Research and Forecasting, 2021, no. 3 (381), pp. 150-161. The quality of calculating the concentration of pollutants in the chemistry-transport model largely depends on the reliability of used emission data. The possibility of updating the EMEP (European Monitoring and Evaluation Program) emission data using OpenStreetMap geodata for the CHIMERE chemistry-transport model calculations is discussed on the example of the Nizhny Novgorod region. The GlobCover land-use data refinement procedure based on OpenStreetMap information provides a 3.3% increase in the urban area and a more accurate configuration of the emission field as compared to the real distribution of sources of atmospheric emissions. Experimental CHIMERE chemistry-transport model calculations of pollutant concentrations based on the initial and updated emission fields demonstrated the efficiency of the proposed approach. Keywords: emissions, EMEP, land use, OpenStreetMap, CHIMERE chemistry-transport model, air quality


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