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Two state-of-the-art models (deterministic: Weather Research and Forecast model with Chemistry (WRF-Chem) and statistic: Artificial Neural Networks: (ANN)) are implemented to predict the ground-level ozone concentration in Sao Paulo (SP), Brazil. Two domains are set up for WRF-Chem simulations: a coarse domain (with 50 km horizontal resolution) including whole South America (D1) and a nested domain (with horizontal resolution of 10 km) including South Eastern Brazil (D2). To evaluate the spatial distribution of the chemical species, model results are compared to the Measurements of Pollution in The Troposphere (MOPITT) data, showing that the model satisfactorily predicts the CO concentrations in both D1 and D2. The model also reproduces the measurements made at three air quality monitoring stations in SP with the correlation coefficients of 0.74, 0.70, and 0.77 for O 3 and 0.51, 0.48, and 0.57 for NO x . The input selection for ANN model is carried out using Forward Selection (FS) method. FS-ANN is then trained and validated using the data from two air quality monitoring stations, showing correlation coefficients of 0.84 and 0.75 for daily mean and 0.64 and 0.67 for daily peak ozone during the test stage. Then, both WRF-Chem and FS-ANN are deployed to forecast the daily mean and peak concentrations of ozone in two stations during 5–20 August 2012. Results show that WRF-Chem preforms better in predicting mean and peak ozone concentrations as well as in conducting mechanistic and sensitivity analysis. FS-ANN is only advantageous in predicting mean daily ozone concentrations considering its significantly lower computational costs and ease of development and implementation, compared to that of WRF-Chem.

Atmospheric CO at Egham in SE England has shown a marked and progressive decline since 1997, following adoption of strict controls on emissions. The Egham site is uniquely positioned to allow both assessment and comparison of ‘clean Atlantic background’ air and CO-enriched air downwind from the London conurbation. The decline is strongest (approximately 50 ppb per year) in the 1997–2003 period but continues post 2003. A ‘local CO increment’ can be identified as the residual after subtraction of contemporary background Atlantic CO mixing ratios from measured values at Egham. This increment, which is primarily from regional sources (during anticyclonic or northerly winds) or from the European continent (with easterly air mass origins), has significant seasonality, but overall has declined steadily since 1997. On many days of the year CO measured at Egham is now not far above Atlantic background levels measured at Mace Head (Ireland). The results are consistent with MOPITT satellite observations and ‘bottom-up’ inventory results. Comparison with urban and regional background CO mixing ratios in Hong Kong demonstrates the importance of regional, as opposed to local reduction of CO emission. The Egham record implies that controls on emissions subsequent to legislation have been extremely successful in the UK.

We present a global chemical data assimilation system using a global atmosphere model, the Community Atmosphere Model (CAM3) with simplified chemistry and the Data Assimilation Research Testbed (DART) assimilation package. DART is a community software facility for assimilation studies using the ensemble Kalman filter approach. Here, we apply the assimilation system to constrain global tropospheric carbon monoxide (CO) by assimilating meteorological observations of temperature and horizontal wind velocity and satellite CO retrievals from the Measurement of Pollution in the Troposphere (MOPITT) satellite instrument. We verify the system performance using independent CO observations taken on board the NSF/NCAR C-130 and NASA DC-8 aircrafts during the April 2006 part of the Intercontinental Chemical Transport Experiment (INTEX-B). Our evaluations show that MOPITT data assimilation provides significant improvements in terms of capturing the observed CO variability relative to no MOPITT assimilation (i.e. the correlation improves from 0.62 to 0.71, significant at 99% confidence). The assimilation provides evidence of median CO loading of about 150 ppbv at 700 hPa over the NE Pacific during April 2006. This is marginally higher than the modeled CO with no MOPITT assimilation (~140 ppbv). Our ensemble-based estimates of model uncertainty also show model overprediction over the source region (i.e. China) and underprediction over the NE Pacific, suggesting model errors that cannot be readily explained by emissions alone. These results have important implications for improving regional chemical forecasts and for inverse modeling of CO sources and further demonstrate the utility of the assimilation system in comparing non-coincident measurements, e.g. comparing satellite retrievals of CO with in-situ aircraft measurements.

A new method is developed to calculate monthly CO emission data using MOZART modeled and MOPITT observed CO data in 2004. New CO emission data were obtained with budget analysis of the processes controlling CO concentration such as surface emission, transport, chemical transform and dry deposition. MOPITT data were used to constrain the model simulation. New CO emission data agree well with Horowitz’s emissions in the spatial distributions. Horowitz’s emissions are found to underestimate CO emissions significantly in the industrial areas of Asia and North America, where high CO emissions are mainly due to the anthropogenic activities. New CO emissions can better reflect the more recent CO actual emissions than Horowitz’s.

Satellite observations have the potential to provide an accurate picture of atmospheric chemistry and air quality on a variety of spatial and temporal scales. A key consideration in the design of new instruments is the spatial resolution required to effectively monitor air quality from space. In this paper, variograms have been used to address this issue by calculating the horizontal length scales of ozone within the boundary layer and free troposphere using both in situ aircraft data from five different NASA aircraft campaigns and simulations with an air-quality model. For both the observations and the model, the smallest scale features were found in the boundary layer, with a characteristic scale of about 50 km which increased to greater than 150 km above the boundary layer. The length scale changes with altitude. It is shown that similar length scales are derived based on a totally independent approach using constituent lifetimes and typical wind speeds. To date, the spaceborne observations of tropospheric constituents have been from several instruments including TOMS, GOME, MOPITT, TES, and OMI which, in general, have different weighting functions that need to be considered, and none really measures at the surface. A further complication is that most satellite measurements (such as those of OMI and GOME) are of the vertically integrated column. In this paper, the length scales in the column measurements were also of the order of 50 km. To adequately resolve the 50-km features, a horizontal resolution of at least 10 km would be desirable

Anthropogenic pollution and wildfires are main producers of carbon monoxide (CO) and black carbon (BC) in the Northern Hemisphere. High concentrations of these compounds are transported into the Arctic troposphere, influencing the ecosystem in high northern latitudes and the global climate. The global chemical transport model MOZART-4 is used to quantify the seasonal evolution of the contribution of CO and BC from different source regions in spring and summer 2008 by tagging their emissions. Aircraft observations from the POLARCAT experiments, in particular NASA ARCTAS, NOAA ARCPAC, POLARCAT-France, DLR GRACE and YAK-AEROSIB, as well as the NSF START08/preHIPPO experiments during Spring-Summer 2008 are combined to quantify the representation of simulated tracer characteristics in anthropogenic and fire plumes. In general, the model reproduces CO and BC well. Based on aircraft measurements and FLEXPART back-trajectories, the altitude contribution of emissions coming from different source regions is well captured in the model. Uncertainties of the MOZART-4 model are identified by comparing the data with model results on the flight tracks and using MOPITT satellite observations. Anthropogenic emissions are underestimated by about 10% in high northern latitudes in spring, and shortcomings exist in simulating fire plumes. The remote impact of East-Siberian fire emissions is underestimated for spring, whereas the impact of Southeast Asian fire emissions to mid-latitude CO values is overestimated by the model. In summer, mid-latitude CO values agree well between model and observations, whereas summer high latitude East-Siberian fire emissions in the model are overestimated by 20% in comparison to observations in the region. On the other hand, CO concentrations are underestimated by about 30% over Alaska and Canada at altitudes above 4 km. BC values are overestimated by the model at altitudes above 4 km in summer. Based on MOZART-4, with tagged CO and BC tracers, anthropogenic emissions of Asia, Europe and the US have the largest contribution to the CO and BC in mid- and high latitudes in spring and summer. Southeast Asian, Chinese and Indian fires have a large impact on CO pollution in spring in low latitudes with a maximum between 20° and 30°, whereas Siberian fires contribute largely to the pollution in high latitudes, up to 10% in spring and up to 30% in summer. The largest contributions to BC values in high latitudes are from anthropogenic emissions (about 70%). CO and BC have larger mass loadings in April than in July, as a result of photochemistry and dynamics.

© 2015. American Geophysical Union. All Rights Reserved. We show the results and evaluation with independent measurements from assimilating both MOPITT (Measurements Of Pollution In The Troposphere) and IASI (Infrared Atmospheric Sounding Interferometer) retrieved profiles into the Community Earth System Model (CESM). We used the Data Assimilation Research Testbed ensemble Kalman filter technique, with the full atmospheric chemistry CESM component Community Atmospheric Model with Chemistry. We first discuss the methodology and evaluation of the current data assimilation system with coupled meteorology and chemistry data assimilation. The different capabilities of MOPITT and IASI retrievals are highlighted, with particular attention to instrument vertical sensitivity and coverage and how these impact the analyses. MOPITT and IASI CO retrievals mostly constrain the CO fields close to the main anthropogenic, biogenic, and biomass burning CO sources. In the case of IASI CO assimilation, we also observe constraints on CO far from the sources. During the simulation time period (June and July 2008), CO assimilation of both instruments strongly improves the atmospheric CO state as compared to independent observations, with the higher spatial coverage of IASI providing better results on the global scale. However, the enhanced sensitivity of multispectral MOPITT observations to near surface CO over the main source regions provides synergistic effects at regional scales.

Carbon monoxide (CO) is a key atmospheric compound that can be remotely sensed by satellite on the global scale. Fifteen years of continuous observations are now available from the MOPITT/Terra mission (2000 to present). Another 15 and more years of observations will be provided by the IASI/MetOp instrument series (2007-2023 >). In order to study long-term variability and trends, a homogeneous record is required, which is not straightforward as the retrieved quantities are instrument and processing dependent. The present study aims at evaluating the consistency between the CO products derived from the MOPITT and IASI missions, both for total columns and vertical profiles, during a 6-year overlap period (2008-2013). The analysis is performed by first comparing the available 2013 versions of the retrieval algorithms (v5T for MOPITT and v20100815 for IASI), and second using a dedicated reprocessing of MOPITT CO profiles and columns using the same a priori information as the IASI product. MOPITT total columns are generally slightly higher over land (bias ranging from 0 to 13 %) than IASI data. When IASI and MOPITT data are retrieved with the same a priori constraints, correlation coefficients are slightly improved. Large discrepancies (total column bias over 15 %) observed in the Northern Hemisphere during the winter months are reduced by a factor of 2 to 2.5. The detailed analysis of retrieved vertical profiles compared with collocated aircraft data from the MOZAIC-IAGOS network, illustrates the advantages and disadvantages of a constant vs. a variable a priori. On one hand, MOPITT agrees better with the aircraft profiles for observations with persisting high levels of CO throughout the year due to pollution or seasonal fire activity (because the climatology-based a priori is supposed to be closer to the real atmospheric state). On the other hand, IASI performs better when unexpected events leading to high levels of CO occur, due to a larger variability associated with the a priori., SCOPUS: ar.j, info:eu-repo/semantics/published

The vertical sensitivity of the new MOPITT version 5 (V5) data is examined in terms of the averaging kernels and the Degree of Freedom of Signals (DFS). The MOPITT's vertical sensitivity is enhanced in V5 NIR/TIR data, noticeably with elevated averaging kernels in the free troposphere, in addition to in the lower troposphere emphasized previously. DFS is most enhanced over land in the Northern Hemispheric middle to high latitudes (up to 1.5). DFS is higher in winter and spring than in summer and autumn, higher over land than over the oceans, higher in the tropics than in the high latitudes. Globally, the mean maximum DFS can reach 2.5, while individual profiles can contain over 2.5 pieces of independent information vertically. Although with limited vertical sensitivity, MOPIIT CO data can generally distinguish CO in the lower, middle, and upper troposphere, thus are useful in addressing scientific questions related to air quality and climate change.

Satellite observations reveal substantial burning during the 2007 and 2010 tropical South America fire season, with both years exhibiting similar total burned area. However, 2010 CO fire emissions, based on satellite CO concentration measurements, were substantially lower (−28%), despite the once‐in‐a‐century drought in 2010. We use Bayesian inference with satellite measurements of CH_4 and CO concentrations and burned area to quantify shifts in combustion characteristics in 2010 relative to 2007. We find an 88% probability in reduced combusted biomass density associated with the 2010 fires and an 82% probability of lower fire carbon losses in 2010 relative to 2007. Higher combustion efficiency was a smaller contributing factor to the reduced 2010 CO emissions. The reduction in combusted biomass density is consistent with a reduction (4–6%) in Global Ozone Monitoring Experiment 2 solar‐induced fluorescence (a proxy for gross primary production) during the preceding months and a potential reduction in biomass (≤8.3%) due to repeat fires.

In this study, we used satellite data (GOME and MOPITT) together with a global chemical-transport-model of atmosphere (MOZART-2) to characterize the chemical/aerosol composition over eastern China. We then estimated the effects of local emissions in China on the chemical budgets in other regions of the world. Likewise, we also investigated the effects of air pollution from other regions on the chemical budget over eastern China. The study shows that the column CO and NO x concentrations are also high in eastern China. The high CO and NO x concentrations produce modest levels of O3 concentrations during summer (about 40 to 50 ppbv) and very low O3 during winter (about 10 to 20 ppbv) in eastern China. The calculated NO2 column is fairly consistent from the GOME measurement. The calculated CO column is underestimated from the MOPITT measurement. One of the reasons of the underestimation of the predicted CO is due to a fact that the CO emissions were taken without considering the rapid increase of emissions from 1990 to 2000. The calculated surface O3 is consistent with the measured values, with strong seasonal variations. However, the measurement is very limited, and more measurements in eastern China will be needed. The column NO2 has a very strong seasonal variation in eastern China, with the highest concentrations during winter and the lowest concentrations during summer. The cause of this seasonal variability is mainly due to the seasonal changes in the chemical loss of NO x , which is very high in summer and very low during winter. The effects of the local emissions in China and long-range transport from other regions on the chemical distributions in eastern China are studied. The results show that NO x concentrations in eastern China are mostly caused by the local emissions in China, especially during the winter. The CO concentration over eastern China is from both the local emissions (30% to 40%) and the transport from other regions. Likewise, the CO emissions in China have an important effect on the other regions of the world, but the effect is limited in the northern hemisphere. The local emissions in China also have an important effect on surface O3 concentrations. During winter, the local emissions reduce the surface O3 concentrations by 30 to 50%. During summer, the local emissions produce about 50 to 70% of the O3 concentration in eastern China.

The development of remote sensing satellite technology potentially will lead to the technical means to monitor air pollution emitted from large cities on a global basis. This paper presents observations by the moderate resolution imaging spectroradiometer (MODIS) and measurements of pollution in the troposphere (MOPITT) experiments of aerosol optical depths and CO mixing ratios, respectively, in the vicinity of Mexico City to illustrate current satellite capabilities. MOPITT CO mixing ratios over Mexico City, averaged between January–March 2002–2005, are 19% above regional values and the CO plume extends over 10° 2 in the free troposphere at 500 hPa. Time series of Red Automatica de Monitoreo Ambiental (RAMA) PM10, and (Aerosol Robotic Network) AERONET and MODIS aerosol optical depths, and RAMA and MOPITT CO time series are inter-compared to illustrate the different perspectives of ground based and satellite instrumentation. Finally, we demonstrate, by examining MODIS and MOPITT data in April 2003, that satellite data can be used to identify episodes in which pollution form fires influences the time series of ground based and satellite observations of urban pollution.

Recent developments in satellite remote sens- ing technologies resulted in the ability to observe major pollution events such as dust and smoke around the world on a daily basis. Satellite imagery can sometimes detect long-range transport episodes. In this paper, a high CO episode at remote GAW station, Mt. Waliguan, detected by MOPITT CO dataset during the end of April 2002, is described. CO concentrations above 600 hPa almost doubled on 27 April and CMDL surface sample mea- surements also observed this significant CO enhance- ment. Using NCEP data, satellite fire products data and backward trajectory model we suggest that this high CO episode of 27 April is not a local pollution event, but that it is due to long-range transport from active biomass burning and biofuel burning areas located in the border areas of PakistanandIndia. Thetrajectory cluster analysis shows that the origins of 5-day backward trajectories, for

The three carbon gases carbon monoxide (CO), carbon dioxide (CO2), and methane (CH4) are important atmospheric constituents affecting air quality and climate. The near-infrared nadir spectra measured by SCIAMACHY on ENVISAT contain information on the vertical columns of these gases which we retrieve using a modified DOAS algorithm (WFM-DOAS or WFMD). Our main data products are CO vertical columns and dry-air column averaged mixing ratios of methane (CH4) and CO2 (denoted XCH4 and XCO2). For CO and CH4 we present new results for the year 2003 obtained with an improved version of WFM-DOAS (WFMDv0.5) retrieved from Level 1 version 4 (Lv1v4) spectra. This data set has recently been compared with a network of ground based FTIR stations. Here we describe the WFMDv0.5 algorithm, present global and regional maps, and comparisons with global reference data. We show that major problems of the previous versions (v0.4 and v0.41) related to the varying ice-layer on the SCIAMACHY channel 8 detector have been solved. Compared to MOPITT the SCIAMACHY CO columns are on average higher by about 10–20%. Regionally, however, especially over central South America, differences can be much larger. For methane we present global and regional maps which are compared to TM5 model simulations performed using standard methane emission inventories. We show that methane source regions can be clearly detected with SCIAMACHY. We also show that the methane data product can be significantly further improved using Lv1v5 spectra with improved calibration. For CO2 we present three years of SCIAMACHY CO2 measurements over Park Falls, Wisconsin, USA, retrieved from Lv1v5. We show that the quality of CO2 retrieved from these spectra is significantly higher compared to WFMDv0.4 XCO2 retrieved from Lv1v4.

The contribution of Korean forests to carbon sequestration for anthropogenic carbon emissions was evaluated. In addition, monitoring of carbon species released from forest fires was conducted. Despite a high carbon uptake by Korean forests, a tremendous increase in fossil fuel burning resulted in a small contribution by forests to carbon removal. The removal efficiency had a 5-31% range with an average of 12% during the period 1973-2002. In 2000, the amount of carbon released from burned trees corresponded to 1.6% of carbon uptake by forests. The distribution of surface CO concentration (ppb) derived from MOPITT (Measurement of Pollution in the Troposphere) showed high CO levels over the East/Japan Sea on April 10, 2000 when the largest forest fires occurred along the east coast of Korea. Trajectory analysis and ground CO measurements also indicated that CO levels over the East/Japan Sea were influenced by forest fires. This study suggests that continuous monitoring of carbon emissions from forest fires is needed for a more reliable estimate of carbon flux in the environment.

To assess the influence of biomass burning and regional pollution on CO levels in Northeast Asia, trajectory analysis and satellite observations from the Measurement of Pollution in the Troposphere (MOPITT) instrument were applied. As a case study, data for April 2000 were used. Ground measurement data at remote sites in Korea showed high CO levels and did not have typical seasonal variations due to regional pollution. Therefore, MOPITT data over the East/Japan Sea was recommended for identification of long-range transport of CO. The locations of biomass burning, distribution of MOPITT CO, and backward trajectories clearly indicated that Siberian fires and industrial activities in East China affected CO levels in Korea and Japan. CO levels over East China for the first two weeks were enhanced more than 35 ppb by biomass burning in Myanmar and Indo-China, and high CO levels over the East/Japan Sea for the last two weeks were affected by both anthropogenic emissions and biomass burning. The average difference in CO concentrations over the East/Japan Sea between fire days (217±18 ppb) and non-fire days (186±15 ppb) was 31 ppb (p

The near-infrared spectra measured with the SCIAMACHY instrument on board the ENVISAT satellite suffer from several instrument calibration problems. The effects of three important instrument calibration issues on the retrieved methane (CH4) and carbon monoxide (CO) total columns have been investigated: the effects of the growing ice layer on the near-infrared detectors, the effects of the orbital variation of the instrument dark signal, and the effects of the dead/bad detector pixels. Corrections for each of these instrument calibration issues have been defined. The retrieved CH4 and CO total columns including these corrections show good agreement with CO measurements from the MOPITT satellite instrument and with CH4 model calculations by the chemistry transport model TM3. Using a systematic approach, it is shown that all three instrument calibration issues have a significant effect on the retrieved CH4 and CO total columns. However, the impact on the CH4 total columns is more pronounced than for CO, because of its smaller variability. Results for three different wavelength ranges are compared and show good agreement. The growing ice layer and the orbital variation of the dark signal show a systematic, but time-dependent effect on the retrieved CH4 and CO total columns, whereas the effect of the dead/bad pixels is rather unpredictable: some dead pixels show a random effect, some more systematic, and others no effect at all. The importance of accurate corrections for each of these instrument calibration issues is illustrated using examples where inaccurate corrections lead to a wrong interpretation of the results.

The amount of solar radiation emerging from the top of the atmosphere is strongly influenced by the reflectance of the underlying surface. For this reason, some information about the magnitude and the spectral variability of the surface reflectance typically has to be included in the retrieval of atmospheric parameters from reflected solar radiation measurements. Sufficient information about the surface reflectance properties is rarely available, and the integration of this effect in the retrieval might turn out to be a challenge, especially for broadband instruments. In this paper the focus is on the Measurements of Pollution in the Troposphere (MOPITT) remote sensing instrument. Theoretical studies are performed to investigate how a spectrally varying surface reflectance might impact the retrieval of the total column amount of methane from MOPITT radiance measurements, and the current findings are compared to observed biases. However, the findings present herein might be valuable and applicable for other remote sensing instruments that are sensitive to the amount of solar radiation reflected from the earth’s surface.

We present a study on MOPITT (Measurements Of Pollution In The Troposphere) detection of CO emission from large forest fires in the year 2000 in the northwest United States. Fire data used are from the space-borne Advanced Very High Resolution Radiometer (AVHRR) at 1-km resolution. The study shows that MOPITT can reliably detect CO plumes from forest fires whenever there are N30 AVHRR hotspots in a 0.258 � 0.258 grid, which is comparable to the pixel area of MOPITT in the region. The spatial CO pattern during the fire events is found to be consistent with the location and density of AVHRR hotspots and wind direction. While the increase of CO abundance inside the study area is closely correlated to the AVHRR-derived hotspot number in general (RN0.75), the non-linearity of fire emission with fuel consumption is also observed. MOPITT can also capture the temporal variation in CO emission from forest fires through 3-day composites so it may offer an opportunity to enhance our knowledge of temporal fire emission over large areas. The CO emission is quantitatively estimated with a one-box model. The result is compared with a bottom-up approach using surface data including burnt area, biomass density, and fire emission factors. If mean emission factors for the region are used, the bottom-up approach results in total emission estimates which are 10%–50% lower than the MOPITT-based estimate. In spite of the limitations and uncertainties addressed in this study, MOPITT data may provide a useful constraint on uncertain ground-based fire emission estimates.

The methane (CH4) and carbon monoxide (CO) total columns retrieved from SCIAMACHY’s near-infrared channel 8 have been compared to satellite measurements by the MOPITT instrument and chemistry transport model calculations (TM3). Results from the SRON retrieval algorithm IMLM (v5.1) are presented here for the month of February 2004. First results show that these monthly averaged data are in good agreement with TM3 model calculations and the measurements by the MOPITT instrument.

The great fires were detected through the Moderate Resolution Imaging Spectroradiometer (MODIS) observations over Northeast Asia. The large amount of smoke produced near Lake Baikal was transported to East Asia using high Aerosol Optical Thickness (AOT) as seen through the satellite images. The smoke pollution from the Russian forest fires would sometimes reach Korea through Mongolia and eastern China. In May 2003, a number of large fires blazed through eastern Russian, producing a thick, widespread pall of smoke over much of East Asia. This study focuses on the identification of the carbon monoxide (CO) for MOPITT released from MOPITT primarily into East Asia during the Russian Fires. In the wake of the fires, the 700hPa MOPITT retrieved CO concentrations which reached up to 250ppbv. Smoke aerosol retrieval using a separation technique was also applied to the MODIS data observed in 14-22 May 2003. Large AOT, 2.0 ~ 5.0, was observed over Korea on 20 May 2003 due to the influence of the long range transport of smoke aerosol plume from the Russian Fires.

This paper reports on Device Single Events (DSEs) occurring in the Measurements Of Pollution In The Troposphere (MOPITT) space instrument piezoelectric accelerometers. It is found that DSEs correlate with the radiation environment, solar activity and high intensity Solar Proton Events.

Ozone enhancement was observed in the lower troposphere over Hong Kong and Kunming on 7 and 8 March 2001 using the electrochemical concentration cell ozonesondes. Based on the data of NCEP, total column ozone, numerical simulation of MM5, AI from TOMS, aerosol optical depths from MODIS, and CO concentration from MOPITT, the influence of biomass burning in Southeast Asia on the ozone distribution in the lower troposphere over Hong Kong and Kunming is analyzed. The transport of the emissions of biomass burning shows that the enhancement of the lower tropospheric ozone over Hong Kong and Kunming is from the region where large-scale fires occurred in Southeast Asia. TOMS AI images and the atmospheric background circulations reveal that the biomass burning plumes in Southeast Asia can be transported to downwind South/Southwest China and lead to enhancement of the ozone concentration in the lower troposphere.

CO vertical profiles have been retrieved from so- lar absorption FTIR spectra recorded at the NDSC station of the Jungfraujoch (46.5 N, 8 E and 3580 m a.s.l.) for the pe- riod from January 1997 to May 2001. The characterisation of these profiles has been established by an information con- tent analysis and an estimation of the error budgets. A partial validation of the profiles has been performed through com- parisons with correlative measurements. The average vol- ume mixing ratios (vmr) in the 3 km layer above the station have been compared with coincident surface measurements. The agreement between monthly means from both measure- ment techniques is very good, with a correlation coefficient of 0.87, and no significant bias observed. The FTIR total columns have also been compared to CO partial columns above 3580 m a.s.l. derived from the MOPITT (Measure- ment Of Pollution In The Troposphere) instrument for the pe- riod March 2000 to May 2001. Relative to the FTIR columns, the MOPITT partial columns exhibit a positive bias of 8±8% for daytime and of 4±7% for nighttime measurements. ments provide accurate measurements of total columns of many atmospheric trace gases. Profile retrieval algorithms improve the quality of the total column measurements while providing information on the vertical distributions. We present a characterisation and a partial validation of the re- trieved ground-based FTIR profiles of CO at the Network for the Detection of Stratospheric Changes (NDSC) Inter- national Scientific Station of the Jungfraujoch (ISSJ) in the Swiss Alps. The characterisation includes an information content analysis and a determination of the error budgets. The validation is performed through comparisons between the FTIR retrieved "surface" (3.58-6.5 km) vmr and correl- ative surface in situ measurements. We also present com- parisons between CO columns and profiles from the FTIR retrievals with MOPITT partial columns.

Daily global analyses and 5-day forecasts are generated in the context of the European Monitoring Atmospheric Composition and Climate (MACC) project using an extended version of the Integrated Forecasting System (IFS) of the European Centre for Medium-Range Weather Forecasts (ECMWF). The IFS now includes modules for chemistry, deposition and emission of reactive gases, aerosols, and greenhouse gases, and the 4-dimensional variational data assimilation scheme makes use of multiple satellite observations of atmospheric composition in addition to meteorological observations. This paper describes the data assimilation setup of the new Composition-IFS (C-IFS) with respect to reactive gases and validates analysis fields of ozone (O3), carbon monoxide (CO), and nitrogen dioxide (NO2) for the year 2008 against independent observations and a control run without data assimilation. The largest improvement in CO by assimilation of Measurements of Pollution in the Troposphere (MOPITT) CO columns is seen in the lower troposphere of the Northern Hemisphere (NH) extratropics during winter, and during the South African biomass-burning season. The assimilation of several O3 total column and stratospheric profile retrievals greatly improves the total column, stratospheric and upper tropospheric O3 analysis fields relative to the control run. The impact on lower tropospheric ozone, which comes from the residual of the total column and stratospheric profile O3 data, is smaller, but nevertheless there is some improvement particularly in the NH during winter and spring. The impact of the assimilation of tropospheric NO2 columns from the Ozone Monitoring Instrument (OMI) is small because of the short lifetime of NO2, suggesting that NO2 observations would be better used to adjust emissions instead of initial conditions. The results further indicate that the quality of the tropospheric analyses and of the stratospheric ozone analysis obtained with the C-IFS system has improved compared to the previous "coupled" model system of MACC.

Negative trends of carbon monoxide (CO) concentrations are observed in the recent decade by both surface measurements and satellite retrievals over many regions, but they are not well explained by current emission inventories. Here, we attribute the observed CO concentration decline with an atmospheric inversion that simultaneously optimizes the two main CO sources (surface emissions and atmospheric hydrocarbon oxidations) and the main CO sink (atmospheric hydroxyl radical OH oxidation) by assimilating observations of CO and other chemically related tracers. Satellite CO column retrievals from Measurements of Pollution in the Troposphere (MOPITT), version 6, and surface in-situ measurements of methane and methyl-chloroform mole fractions are assimilated jointly for the period of 2002–2011. Compared to the prior simulation, the optimized CO concentrations show better agreement with independent surface in-situ measurements in terms of both distributions and trends. At the global scale, the atmospheric inversion primarily interprets the CO concentration decline as a decrease in the CO emissions, and finds noticeable trends neither in the chemical oxidation sources of CO, nor in the OH concentrations that regulate CO sinks. The latitudinal comparison of the model state with independent formaldehyde (CH2O) columns retrieved from the Ozone Measurement Instrument (OMI) confirms the absence of large-scale trends in the atmospheric source of CO. The global CO emission decreased by 17% during the decade, more than twice the negative trend estimated by emission inventories. The spatial distribution of the inferred decrease of CO emissions indicates contributions from both a decrease in fossil- and bio-fuel emissions over Europe, the USA and Asia, and from a decrease in biomass burning emissions in South America, Indonesia, Australia and Boreal regions. An emission decrease of 2% yr−1 is inferred in China, one of the main emitting regions, in contradiction with the bottom-up inventories that report an increase of 2% yr−1 during the study period. A large decrease in CO emission factors due to technology improvements would outweigh the increase of carbon fuel combustions and may explain the observed decrease. In Africa, instead of the negative trend (1% yr−1) reported by CO emission inventories mainly contributed by biomass burning, a positive trend (1.5% yr−1) is found by the atmospheric inversion, suggesting different trends between satellite-detected burned areas and CO emissions.

Optical bandpass filters in the Measurements of Pollution in the Troposphere (MOPITT) satellite remote sensing instrument selectivity limit the throughput radiance to absorptive spectral bands associated with the satellite-observed trace gases CO and CH4. Precise specification of the spectral characteristics of these filters is required to optimize retrieval accuracy. The effects and potential causes of spectral shifts in the optical bandpass filter profiles are described. Specifically, a shift in the assumed bandpass profile produces a relative bias between the calibrated satellite radiances and the corresponding values calculated by an instrument-specific forward radiative transfer model. Conversely, it is shown that the observed bias (as identified and quantified using operational MOPITT satellite radiance data) can be used to determine the relative spectral shift between the nominal (prelaunch) filter profiles and the true operational (in orbit) profiles. Revising both the radiance calibratio...

In the present study, near-surface carbon monoxide (CO) measurements were carried out at a semi-urban site in Agra, India (27°10′N, 78°05′E), during March 2015 to February 2016. The study includes the diurnal, seasonal, and vertical variation of CO and the effect of meteorological parameters on its levels. The diurnal variation of CO was characterized by high levels during morning (9–10 am) and evening (10–11 pm) hours and low levels during the afternoon (3–5 pm). The morning and evening peak levels may be due to high emissions from traffic and low planetary boundary layer (PBL) height which prevents dispersion of pollutants. The low levels during afternoon hours may be due to increasing PBL height and loss through photochemical reactions. CO showed a distinct seasonal variation with highest levels in winter (770 ± 466 ppb) and lowest in monsoon (153 ± 122 ppb). The high levels in the winter season may be attributed to increased emissions from coal and wood burning used for heating in combination with stagnant weather conditions. The study also included latest retrievals of CO using Measurements of Pollution in the Troposphere (MOPITT) to define the vertical and seasonal variation of CO. The pattern of seasonal variation observed by ground level measurements was consistent with MOPITT surface CO levels.

Satellite observations of tropospheric carbon monoxide (CO) are employed in diverse applications including air quality studies, chemical weather forecasting and the characterization of CO emissions through inverse modeling. The TERRA / MOPITT ('Measurements of Pollution in the Troposphere') instrument incorporates a set of gas correlation radiometers to observe CO simultaneously in both a thermal-infrared (TIR) band near 4.7 µm and a near-infrared (NIR) band near 2.3 μm. This multispectral capability is unique to MOPITT. The MOPITT retrieval algorithm for vertical profiles of CO has been refined almost continuously since TERRA was launched at the end of 1999. Retrieval algorithm enhancements are the result of ongoing analyses of instrument performance, improved radiative transfer modeling, and systematic comparisons with correlative data, including in-situ profiles measured from aircraft and products from other satellite instruments. In the following, we describe the methods used to routinely evaluate MOPITT CO profiles. As the satellite instrument with the longest record for CO, methods for assessing the long-term stability are becoming increasingly important.

Terra is the flagship of NASA’s Earth observing systems (EOS), carrying five sensors (ASTER, CERES, MISR, MODIS, and MOPITT), which have been providing high-quality global observations for nearly 15 years. MODIS has 20 reflective solar bands (RSB) and are calibrated using a solar diffuser (SD) with its degradation tracked by a solar diffuser stability monitor (SDSM). Scheduled lunar roll observations and vicarious data from pseudo-invariant sites are used to characterize the scanangle dependence of the MODIS RSB. The Multi-angle Imaging SpectroRadiometer (MISR) makes near simultaneous measurements with MODIS at nine view angles spreading out in the forward and backward directions along the flight path via four spectral bands (blue, green, red and near-infrared). MISR calibration efforts are based on a combination of preflight, onboard, and field vicarious measurements. This study compares coincident MODIS and MISR near-nadir reflectances over their entire mission, and examine the calibration stability and consistency of the two instruments. Reflectances from low to high signal levels are based on measurements obtained from ocean, desert and Antarctic snow surfaces. The absolute calibration differences between MODIS and MISR are examined after correction of their spectral response differences based on the SCIAMACHY measured hyperspectral data for the same sites.

Vertical transport of surface emission to the free troposphere, usually associated with frontal lifting in warm conveyor belts or ascent in deep convection, has significant influence on the vertical structure of atmospheric trace gases. Consequently, it may impact estimates of the surface fluxes of these gases inferred from remote sensing observations that are based on thermal infrared radiances (TIR), since these measurements are sensitive mainly to signals in the free troposphere. In this work, we assessed the sensitivity of regional CO source estimates to the vertical CO distribution, by assimilating multi-spectral MOPITT V5J CO retrievals with the GEOS-Chem model. We compared the source estimates obtained by assimilating the CO profiles and the surface layer retrievals from June 2004 to May 2005. The inversion analyses all produced a reduction in CO emissions in the tropics and subtropics and an increase in the extratropics. The tropical decreases were particularly pronounced for regions where the biogenic source of CO was dominant, suggesting an overestimate of the a priori isoprene source of CO in the model. We found that the differences between the regional source estimates inferred from the profile and surface layer retrievals for 2004–2005 were small, generally less than 5% for the main continental regions, except for estimates for South Asia, North America, and Europe. Because of discrepancies in convective transport in the model, the CO source estimates for India and Southeast Asia inferred from the CO profiles were significantly higher than those estimated from the surface layer retrievals during June–August 2004. On the other hand, the profile inversion underestimated the CO emissions from North America and Europe compared to the assimilation of the surface layer retrievals. We showed that vertical transport of air from the North American and European boundary layer is slower than from other continental regions and thus air in the free troposphere from North America and Europe is more chemically aged, which could explain the discrepancy between the source estimates inferred from the profile and surface layer retrievals. We also examined the impact of the OH distribution on the source estimates using OH fields from versions v5-07-08 and v8-02-01 of GEOS-Chem. The impact of the different OH fields was particularly large for the extratropical source estimates. For example, for North America, using the surface layer retrievals, we estimated a total CO source of 37 and 55 Tg CO with the v5-07-08 and v8-02-01 OH fields, respectively, for June–August 2004. For Europe the source estimates were 57 and 72 Tg CO, respectively. We found that the discrepancies between the source estimates obtained with the two OH fields were larger when using the profile data, which is consistent with greater sensitivity to the more chemically aged air in the free troposphere. Our findings indicate that regional CO source estimates are sensitive to the vertical CO structure. They suggest that assimilating a broader range of composition measurements to provide better constraint on tropospheric OH and the biogenic sources of CO is essential for reliable quantification of the regional CO budget.

Carbon monoxide (CO) emissions in China in 2005–2010 were estimated by inversion, using the Green's function method from vertical CO profiles derived from MOPITT Version 5 satellite data and a tagged CO simulation, and validated with independent in situ observations from the World Data Centre for Greenhouse Gases. Modeling with a posteriori emission successfully reproduced CO outflow from the continent to the East China Sea, Sea of Japan, and Japanese islands during winter and spring, and compensated for underestimates in central and eastern China in summer. A posteriori emissions showed large seasonal variations in which December and March emissions were on average 23% larger than August emissions, consistent with other studies. Estimated Chinese CO emissions were 184.4, 173.1, 184.6, 158.4, 157.4, and 157.3 Tg/year for 2005–2010, respectively. The decrease after 2007 is partly attributed to Chinese socioeconomic conditions and improved combustion efficiency.

A large body of information on emissions from the various types of biomass burning has been accumulated over the past decade, to a large extent as a result of International Geosphere-Biosphere Programme/International Global Atmospheric Chemistry research activities. Yet this information has not been readily accessible to the atmospheric chemistry community because it was scattered over a large number of publications and reported in numerous different units and reference systems. We have critically evaluated the presently available data and integrated these into a consistent format. On the basis of this analysis we present a set of emission factors for a large variety of species emitted from biomass fires. Where data were not available, we have proposed estimates based on appropriate extrapolation techniques. We have derived global estimates of pyrogenic emissions for important species emitted by the various types of biomass burning and compared our estimates with results from inverse modeling studies.

The tropospheric carbon monoxide (CO) column density over the United States Department of Energy (DOE) Atmospheric Radiation Measurement (ARM) Program Southern Great Plains (SGP) Central Facility near Lamont, Oklahoma (latitude 36°37′N, longitude 97°30′W) during the Pre-launch MOPITT Validation Exercise (Pre-MOVE) is retrieved from infrared spectra obtained by the ground-based Atmospheric Emitted Radiance Interferometer (AERI). This paper reports the first tropospheric CO time series retrieved from an AERI. With spectra measured every 8 min, CO retrieved from AERI spectra has a much higher temporal resolution than from any other ground-based instrument measuring atmospheric emission. The retrieved CO column density time series is examined using local meteorological data. Synoptic atmospheric conditions are found to have a controlling effect on tropospheric CO. During 2–4 March, 1998, a southerly to easterly surface wind brought an airmass with higher CO column density over the SGP Central Facility (SGPCF), whereas northerly and/or westerly surface winds tended to reduce the CO column density.

The Measurement of Pollution in the Troposphere (MOPITT) instrument is an eight-channel gas correlation radiometer selected for the Earth Observing System (EOS) Terra spacecraft launched in December 1999. Algorithms for the retrieval of tropospheric carbon monoxide (CO) profiles from MOPITT measurements have been developed. In this paper, validation studies of the MOPITT CO retrieval algorithm using observations by the Interferometric Monitor for greenhouse Gases (IMG) during the Winter Clouds Experiment (WINCE) conducted from 23 January to 13 February 1997 are described. Synthetic radiance spectra calculated by a line-by-line radiative transfer model, FASCOD3, using the retrieved CO profile agrees well with IMG-measured radiance spectra. Observations by the Moderate Resolution Imaging Spectrometer (MODIS) Airborne Simulator (MAS) from the NASA ER-2 platform during WINCE were successfully used to assist in the identification of clear and cloudy IMG observations.

This paper presents a new radiative transfer model based on the correlated-k technique that is particularly suitable for applications associated with broadband infrared satellite remote sounding of the atmosphere. We describe new developments to the approach which improve the accuracy of correlated-k distribution radiative transfer calculations. These include methods to model an instrument response function, spectral line overlap for multiple gases, and the spectral variation of solar and thermal source functions. We also describe an approach to improving vertical spectral correlation along ray paths through a nonhomogeneous atmosphere. For a radiative transfer model to be efficient as the forward model of a retrieval scheme, the calculation of analytical Jacobians is particularly important. This is implemented in the model using a variation on the correlated-k approach. The application of the new model, RADCKD, is demonstrated with example calculations for the EOS Terra satellite Measurements of Pollution in the Troposphere (MOPITT) instrument.

This study explores the evolution and distribution of carbon monoxide (CO) using the National Oceanic and Atmospheric Administration (NOAA) Geophysical Fluid Dynamics Laboratory three-dimensional global chemical transport model (GFDL GCTM). The work aims to gain an improved understanding of the global carbon monoxide budget, specifically focusing on the contribution of each of the four source terms to the seasonal variability of CO. The sum of all CO sources in the model is 2.5 Pg CO/yr (1 Pg = 103 Tg), including fossil fuel use (300 Tg CO/yr), biomass burning (748 Tg CO/yr), oxidation of biogenic hydrocarbons (683 Tg CO/yr), and methane oxidation (760 Tg CO/yr). The main sink for CO is destruction by the hydroxyl radical, and we assume a hydroxyl distribution based on three-dimensional monthly varying fields given by Spivakovsky et al. [1990], but we increase this field by 15% uniformly to agree with a methyl chloroform lifetime of 4.8 years [Prinn et al, 1995]. Our simulation produces a carbon monoxide field that agrees well with available measurements from the NOAA/Climate Monitoring and Diagnostics Laboratory global cooperative flask sampling network and from the Jungfraujoch observing station of the Swiss Federal Laboratories for Materials Testing and Research (EMPA) (93% of seasonal-average data points agree within ±25%) and flight data from measurement campaigns of the NASA Global Tropospheric Experiment (79% of regional-average data points agree within ±25%). For all 34 ground-based measurement sites we have calculated the percentage contribution of each CO source term to the total model-simulated distribution and examined how these contributions vary seasonally due to transport, changes in OH concentration, and seasonality of emission sources. CO from all four sources contributes to the total magnitude of CO in all regions. Seasonality, however, is usually governed by the transport and destruction by OH of CO emitted by fossil fuel and/or biomass burning. The sensitivity to the hydroxyl field varies spatially, with a 30% increase in OH yielding decreases in CO ranging from 4–23%, with lower sensitivities near emission regions where advection acts as a strong local sink. The lifetime of CO varies from 10 days over summer continental regions to well over a year at the winter poles, where we define lifetime as the turnover time in the troposphere due to reaction with OH.

This paper discusses the retrieval scheme associated with the gas correlated radiometer MOPITT which will be on board of EOS-AM1 to measure the global vertical profiles of carbon monoxide. The vertical resolution and retrieval errors caused by errors in the temperature profiles and in the surface temperature have been assessed. The main results are: a. Assuming the noise equivalent radiance (NER) of 1.8 × 105 W m-2 sr-1, the surface temperature can be deduced from the wide band signals with uncertainty less than 1 K, and the atmospheric term of the modulated signal can be deduced with errors almost equal to the NER which does not significantly increase errors in the retrieved CO profiles. b. With typical uncertainty in temperature profiles, errors in the retrieved profiles at latitudes lower than 70‡ are generally less than 20% with the first guess of 100 ppbv. (If a better first guess was used, the errors may decrease). c. By incorporating the total column CO amount derived from the reflected solar radiation in 2.3 Μm spectral region into the retrieval, the accuracy of the retrieved CO profile below 6 km may be greatly improved. d. In the retrieval experiment with 10 CO profiles representing the typical CO profiles, the r.m.s. relative/ absolute errors of the retrieved CO profiles are about 10% / 15-20 ppbv.

This paper describes the radiative transfer modeling effort in support of the EOS Measurements of Pollution in the Troposphere (MOPITT) instrument. MOPITT is due to be launched on the AM-1 Terra platform in the summer of 1999 and is a nadir-viewing gas correlation radiometer designed to measure CO and CH4 in the troposphere using a CO thermal channel at 4.7 μm and reflected solar channels for CO at 2.3 μm and CH4 at 2.2 μm. We describe the spectroscopic considerations and radiative transfer studies that have been performed for this instrument and the implications for operational algorithm design. We outline the construction of MOPITT project forward models, both the research codes and the fast transmittance module that forms part of the operational retrieval algorithm. Several different approaches have been considered for these models: full line-by-line calculations using the general purpose line-by-line transmittance and radiance model GENLN2, absorption coefficient look-up tables, and regression techniques using a recurrence parameterization of transmittance. These models are capable of reproducing MOPITT channel signals and their dependence on temperature, viewing geometry, and the mixing ratios of target and contaminating gases.

Measurement of Pollution in the Troposphere (MOPITT) is an eight-channel gas correlation radiometer selected for the Earth Observing System AM-1 platform to be launched in 1999. Its primary objectives are the measurement of tropospheric carbon monoxide (CO) and methane (CH4). In this paper, the sensitivities of instrument signals and CO retrieval errors to various instrument parameters, especially the gas cell pressure and temperature variations, instrument radiometric noise, and ancillary data errors (such as atmospheric temperature and water vapor profile errors), are presented and discussed. In the MOPITT pressure modulator cell pressure sensitivity study, the instrument calibration process is considered, which leads to the relaxation of previous stringent requirements on the accuracy of in-orbit cell pressure monitoring. The approach of MOPITT CO retrieval error analysis is described, and the error analysis results are compared with retrieval simulation statistics. The error analysis results ...

Global tropospheric carbon monoxide (CO) distributions can be retrieved from observations by spaceborne gas correlation radiometers and high-resolution interferometers. The Measurement of Pollution in the Troposphere (MOPITT) is a gas correlation radiometer designed for tropospheric CO and CH4 remote sensing. It is being developed at the University of Toronto and the National Center for Atmospheric Research for launch on the EOS/AM-1 platform in 1999. Spaceborne high-resolution interferometers with troposphere CO remote sensing capability include the Interferometric Monitor for Greenhouse gases (IMG) instrument and the Troposphere Emission Spectrometer (TES). IMG was developed by the Ministry of International Trade and Industry (MITI) of Japan. It was on the ADEOS-1 spacecraft launched in October 1996. TES is being developed by the Jet Propulsion Laboratory for launch on the EOS/CHEM-1 platform in 2002. For the purpose of testing the MOPITT data processing algorithms before launch, a new digital ...

A retrieval method for deriving the tropospheric carbon monoxide (CO) profile and column amount under clear sky conditions has been developed for the Measurements of Pollution In The Troposphere (MOPITT) instrument, scheduled for launch in 1998 onboard the EOS-AM1 satellite. This paper presents a description of the method along with analyses of retrieval information content. These analyses characterize the forward measurement sensitivity, the contribution of a priori information, and the retrieval vertical resolution. Ensembles of tropospheric CO profiles were compiled both from aircraft in situ measurements and from chemical model results and were used in retrieval experiments to characterize the method and to study the sensitivity to different parameters. Linear error analyses were carried out in parallel with the ensemble experiments. Results of these experiments and analyses indicate that MOPITT CO column measurements will have better than 10% precision, and CO profile measurement will have approximately three pieces of independent information that will resolve 3-5 tropospheric layers to approximately 10% precision. These analyses are important for understanding MOPITT data, both for application of data in tropospheric chemistry studies and for comparison with in situ measurements.

Since 1988, the distribution of carbon monoxide (CO) in the lower troposphere has been determined using a globally distributed air sampling network. Site locations range from 82°N to 90°S, with wide longitudinal coverage, and represent the marine boundary layer, regionally polluted atmospheres, and the free troposphere. These measurements present a unique, intercalibrated, and internally consistent data set that are used to better define the global temporal and spatial distribution of CO. In this paper, times series from 49 sites are discussed. With an average lifetime of ∼2 months, CO showed significant concentration gradients. In the marine boundary layer, mixing ratios were greatest in the northern winter (200-220 ppb) and lowest in the southern summer (35-45 ppb). The interhemispheric gradient showed strong seasonality with a maximum difference between the high latitudes of the northern and southern hemispheres (160-180 ppb) in February and March and a minimum in July and August (10-20 ppb). Higher CO was found in regions near human development relative to those over more remote areas. The distributions provide additional evidence of the widespread pollution of the lower atmosphere. Remote areas in the high northern hemisphere are polluted by anthropogenic activities in the middle latitudes, and those in the southern hemisphere are heavily influenced by the burning of biomass in the tropics. While tropospheric concentrations of CO exhibit periods of increase and decrease, the globally averaged CO mixing ratio over the period from 1990 through 1995 decreased at a rate of approximately 2 ppb yr -1 .

The Measurements of Pollution in the Troposphere (MOPITT) instrument on the NASA Terra platform has now acquired over thirteen years of global tropospheric carbon monoxide (CO) observations, forming the longest satellite record for an important pollutant. [...]

Vegetation fires are an important source of air pollution in several regions of the world including Asia. An important question with respect to satellite retrievals of air pollutants is “how well do they capture temporal and spatial variations and how well do they relate to episodic events such as fires?” We addressed this question using MOPITT surface CO and MODIS fire retrievals. We also evaluated MODIS aerosol optical depth (AOD) as well as small mode aerosol fraction (SMAF) variations in relation to fire seasonality. Results from temporal analysis (2003–2012) of fires in Asia suggested 22 % of all fires occurring in Myanmar, followed by India (20.91 %), Indonesia (18.31 %), Thailand (9.42 %), etc. Fire frequencies were highest in northeast India and Southeast Asia countries. Further, we observed significant spatial variation and seasonality in fires in Southeast Asia. In the northern Southeast Asia, the peak fire season was during January–March whereas in the south, the fires peak is from August through October. AOD followed a similar trend as that of fires, however, small mode aerosol fraction showed some discrepancies. Locally weighted regression yielded good results between vegetation fires and CO emissions. Results showed that areas with high vegetation fires were also areas of high CO emissions, with highest spatial correlation during the month of March. Among the fire counts and FRP, the correlations varied for individual months, however, both showed significant (P < 0.001) positive correlations suggesting that either of them can be used as predictor of CO concentrations. Locally weighted regression maps revealed how the relationship between fire counts versus CO and FRP versus CO change across time and space. The study captures the influence of vegetation fires on CO pollution in Asia using satellite data.

Variations in the mixing ratio of trace gases of tropospheric origin entering the stratosphere in the tropics are of interest for assessing both troposphere to stratosphere transport fluxes in the tropics and the impact of these transport fluxes on the composition of the tropical lower stratosphere. Anomaly patterns of carbon monoxide (CO) and long-lived tracers in the lower tropical stratosphere allow conclusions about the rate and the variability of tropical upwelling to be drawn. Here, we present a simplified chemistry scheme for the Chemical Lagrangian Model of the Stratosphere (CLaMS) for the simulation, at comparatively low numerical cost, of CO, ozone, and long-lived trace substances (CH4, N2O, CCl3F (CFC-11), CCl2F2 (CFC-12), and CO2) in the lower tropical stratosphere. For the long-lived trace substances, the boundary conditions at the surface are prescribed based on ground-based measurements in the lowest model level. The boundary condition for CO in the lower troposphere (below about 4 km) is deduced from MOPITT measurements. Due to the lack of a specific representation of mixing and convective uplift in the troposphere in this model version, enhanced CO values, in particular those resulting from convective outflow are underestimated. However, in the tropical tropopause layer and the lower tropical stratosphere, there is relatively good agreement of simulated CO with in situ measurements (with the exception of the TROCCINOX campaign, where CO in the simulation is biased low &approx;10–15 ppbv). Further, the model results (and therefore also the ERA-Interim winds, on which the transport in the model is based) are of sufficient quality to describe large scale anomaly patterns of CO in the lower stratosphere. In particular, the zonally averaged tropical CO anomaly patterns (the so called "tape recorder" patterns) simulated by this model version of CLaMS are in good agreement with observations, although the simulations show a too rapid upwelling compared to observations as a consequence of the overestimated vertical velocities in the ERA-Interim reanalysis data set. Moreover, the simulated tropical anomaly patterns of N2O are in good agreement with observations. In the simulations, anomaly patterns of CH4 and CFC-11 were found to be very similar to those of N2O; for all long-lived tracers, positive anomalies are simulated because of the enhanced tropical upwelling in the easterly shear phase of the quasi-biennial oscillation.

This paper presents a validation of a method to derive the vertical profile of carbon monoxide (CO) from its total column using data assimilation. We choose version 3 of MOPITT CO total columns to validate the proposed method. MOPITT products have the advantage of providing both the vertical profiles and the total columns of CO. Furthermore, this version has been extensively validated by comparison with many independent data sets, and has been used in many scientific studies. The first step of the paper consists in the specification of the observation errors based on the chi-square (χ2) test. The observations have been binned according to three types: over land during daytime, over land during night-time, and over sea. Their respective errors using the χ2 metric have been found to be 8, 11 and 7%. In the second step, the CO total columns, with their specified errors, are used within the assimilation system to estimate the vertical profiles. These are compared to the retrieved profiles of MOPITT V3 at global and regional scales. Generally, the two data sets show similar patterns and good agreement at both scales. Nevertheless, total column analyses slightly overestimate CO concentrations compared to MOPITT observations. The mean bias between both data sets is +15 and +12% at 700 and 250 hPa, respectively. In the third step, the assimilation of total column has been compared to the assimilation of MOPITT vertical profiles. The differences between both analyses are very small. In terms longitude–latitude maps, the mean bias between the two data sets is +6 and +8% at the pressure levels 700 and 200 hPa, respectively. In terms of zonal means, the CO distribution is similar for both analyses, with a mean bias which does not exceed 12%. Finally, the two analyses have been validated using independent observations from the aircraft-based MOZAIC program in terms of vertical profiles over eight airports. Over most airports, both analyses agree well with aircraft profiles. For more than 50% of recorded measurements, the difference between the analyses and MOZAIC does not exceed 5 ppbv (parts per billion by volume).