Carbon Monoxide Retrievals Research Articles

Carbon monoxide over Indian region as observed by MOPITT

A comprehensive study has been carried out on tropospheric carbon monoxide (CO) over the Indian land mass and surrounding oceanic region using the CO retrievals from MOPITT (Measurements of Pollution in the Troposphere) for a period of ∼14 years (2000–2014). The lower-tropospheric CO maximises during winter and shows a broad minimum during summer-monsoon over most of the regions, but with regionally varying seasonal amplitudes. Tropospheric column CO also exhibits a seasonal pattern similar to lower-tropospheric CO. But the upper-tropospheric CO shows an opposite seasonal pattern which peaks during summer monsoon. Columnar CO showed strong positive correlation with fire counts over west, east and north-east India, indicating the dominant role of biomass burning in controlling the seasonal variation of CO. The lower-tropospheric and columnar CO showed decreasing trend of 2.0–3.4 ppb year−1 (1.1–2.0% year−1) and 6.0–13.6 × 1015 molecules cm−2 year−1 (0.3–0.6% year−1) respectively over most of the regions. However, over many land regions trend in columnar CO is not significant. Most strikingly, the upper tropospheric CO showed increasing trend of 1.4–2.4 ppb year−1 (1.8–3.2% year−1). The analysis of biases in the estimated trends due to temporal changes in the MOPITT averaging kernels shows that magnitude of the realistic trend may change depending upon the bias but the sign (positive or negative) of trend remains the same. The decreasing trend in lower tropospheric and columnar CO could be attributed partly to increase in lower tropospheric water vapour and/or tropospheric ozone. The strengthening of convective activity, uplifting the CO to higher altitudes, could be a reason for increasing trend in the upper-tropospheric CO.

An Experiment Using High Spectral Resolution CrIS Measurements for Atmospheric Trace Gases: Carbon Monoxide Retrieval Impact Study

We perform a demonstration experiment using the National Oceanic Atmospheric Administration Unique Cross-track Infrared Sounder (CrIS)/Advanced Technology Microwave Sounder Processing System to assess the improvement on trace gas retrievals upon switching to high spectral resolution CrIS radiance measurements (0.625 cm-1). The focus of this study is carbon monoxide retrievals. The experimental high spectral resolution CO retrievals show a remarkable improvement, of almost up to one order of magnitude in the degree of freedom of the signal, with respect to the low-resolution mode. Furthermore, high-resolution CO retrievals show similar skill with respect to existing CO operational products from the Atmospheric InfraRed Sounder, Atmospheric Sounder Interferometer, and Measurements of Pollution In The Troposphere instruments, both in terms of spatial variability and degrees of freedom. The results of this research provide evidence to support the need for high spectral resolution CrIS measurements. This is a fundamental prerequisite in guaranteeing continuity to the CO afternoon orbit monitoring as part of a multisatellite uniformly integrated long-term data record of atmospheric trace gases.

Global carbon monoxide products from combined AIRS, TES and MLS measurements on A-train satellites

Abstract. This study tests a novel methodology to add value to satellite data sets. This methodology, data fusion, is similar to data assimilation, except that the background model-based field is replaced by a satellite data set, in this case AIRS (Atmospheric Infrared Sounder) carbon monoxide (CO) measurements. The observational information comes from CO measurements with lower spatial coverage than AIRS, namely, from TES (Tropospheric Emission Spectrometer) and MLS (Microwave Limb Sounder). We show that combining these data sets with data fusion uses the higher spectral resolution of TES to extend AIRS CO observational sensitivity to the lower troposphere, a region especially important for air quality studies. We also show that combined CO measurements from AIRS and MLS provide enhanced information in the UTLS (upper troposphere/lower stratosphere) region compared to each product individually. The combined AIRS–TES and AIRS–MLS CO products are validated against DACOM (differential absorption mid-IR diode laser spectrometer) in situ CO measurements from the INTEX-B (Intercontinental Chemical Transport Experiment: MILAGRO and Pacific phases) field campaign and in situ data from HIPPO (HIAPER Pole-to-Pole Observations) flights. The data fusion results show improved sensitivities in the lower and upper troposphere (20–30% and above 20%, respectively) as compared with AIRS-only version 5 CO retrievals, and improved daily coverage compared with TES and MLS CO data.

Tropospheric carbon monoxide variability from AIRS under clear and cloudy conditions

Abstract. We study the carbon monoxide (CO) variability in the last decade measured by NASA's Atmospheric InfraRed Sounder (AIRS) on the Earth Observing System (EOS)/Aqua satellite. The focus of this study is to analyze CO variability and short-term trends separately for background CO and fresh CO emissions based on a new statistical approach. The AIRS Level 2 (L2) retrieval algorithm utilizes cloud clearing to treat cloud contaminations in the signals, and this increases the data coverage significantly to a yield of more than 50% of the total measurements. We first study if the cloud clearing affects CO retrievals and the subsequent trend studies by using the collocated Moderate Resolution Imaging Spectroradiometer (MODIS) cloud mask to identify AIRS clear sky scenes. We then carry out a science analysis using AIRS CO data individually for the clear and cloud-cleared scenes to identify any potential effects due to cloud clearing. We also introduce a new technique to separate background and recently emitted CO observations, which aims to constrain emissions using only satellite CO data. We validate the CO variability of the recent emissions estimated from AIRS against other emission inventory databases (i.e., Global Fire Emissions Database – GFED3 and the MACC/CityZEN UE – MACCity) and calculate that the correlation coefficients between the AIRS CO recently emitted and the emission inventory databases are 0.726 for the Northern Hemisphere (NH) and 0.915 for the Southern Hemisphere (SH). The high degree of agreement between emissions identified using only AIRS CO and independent inventory sources demonstrates the validity of this approach to separate recent emissions from the background CO using one satellite data set.

Averaging kernel prediction from atmospheric and surface state parameters based on multiple regression for nadir-viewing satellite measurements of carbon monoxide and ozone

Abstract. A current obstacle to the observation system simulation experiments (OSSEs) used to quantify the potential performance of future atmospheric composition remote sensing systems is a computationally efficient method to define the scene-dependent vertical sensitivity of measurements as expressed by the retrieval averaging kernels (AKs). We present a method for the efficient prediction of AKs for multispectral retrievals of carbon monoxide (CO) and ozone (O3) based on actual retrievals from MOPITT (Measurements Of Pollution In The Troposphere) on the Earth Observing System (EOS)-Terra satellite and TES (Tropospheric Emission Spectrometer) and OMI (Ozone Monitoring Instrument) on EOS-Aura, respectively. This employs a multiple regression approach for deriving scene-dependent AKs using predictors based on state parameters such as the thermal contrast between the surface and lower atmospheric layers, trace gas volume mixing ratios (VMRs), solar zenith angle, water vapor amount, etc. We first compute the singular value decomposition (SVD) for individual cloud-free AKs and retain the first three ranked singular vectors in order to fit the most significant orthogonal components of the AK in the subsequent multiple regression on a training set of retrieval cases. The resulting fit coefficients are applied to the predictors from a different test set of test retrievals cased to reconstruct predicted AKs, which can then be evaluated against the true retrieval AKs from the test set. By comparing the VMR profile adjustment resulting from the use of the predicted vs. true AKs, we quantify the CO and O3 VMR profile errors associated with the use of the predicted AKs compared to the true AKs that might be obtained from a computationally expensive full retrieval calculation as part of an OSSE. Similarly, we estimate the errors in CO and O3 VMRs from using a single regional average AK to represent all retrievals, which has been a common approximation in chemical OSSEs performed to date. For both CO and O3 in the lower troposphere, we find a significant reduction in error when using the predicted AKs as compared to a single average AK. This study examined data from the continental United States (CONUS) for 2006, but the approach could be applied to other regions and times.

Validation of MOPITT Version 5 thermal‐infrared, near‐infrared, and multispectral carbon monoxide profile retrievals for 2000–2011

AbstractValidation results are reported for the MOPITT (Measurements of Pollution in the Troposphere) “Version 5” (V5) product for tropospheric carbon monoxide (CO) and are compared to results for the “Version 4” product. The V5 retrieval algorithm introduces (1) a method for reducing retrieval bias drift associated with long‐term instrumental degradation, (2) a more exact representation of the effects of random errors in the radiances and, for the first time, (3) the use of MOPITT's near‐infrared (NIR) radiances to complement the thermal‐infrared (TIR) radiances. Exploiting TIR and NIR radiances together facilitates retrievals of CO in the lowermost troposphere. V5 retrieval products based (1) solely on TIR measurements, (2) solely on NIR measurements and (3) on both TIR and NIR measurements are separately validated and analyzed. Actual retrieved CO profiles and total columns are compared with equivalent retrievals based on in situ measurements from (1) routine NOAA aircraft sampling mainly over North America and (2) the “HIAPER Pole to Pole Observations” (HIPPO) field campaign. Particular attention is focused on the long‐term stability and geographical uniformity of the retrieval errors. Results for the retrieved total column clearly indicate reduced temporal bias drift in the V5 products compared to the V4 product, and do not exhibit a positive bias in the Southern Hemisphere, which is evident in the V4 product.

Impact of model errors in convective transport on CO source estimates inferred from MOPITT CO retrievals

Estimates of surface fluxes of carbon monoxide (CO) inferred from remote sensing observations or free tropospheric trace gas measurements using global chemical transport models can have significant uncertainties because of discrepancies in the vertical transport in the models, which make it challenging to unequivocally relate the observations back to the surface fluxes in the models. The new Measurement of Pollution in the Troposphere (MOPITT) version 5 retrievals provide greater sensitivity to lower tropospheric CO over land relative to the previous versions and are, therefore, useful for evaluating vertical transport in models. We have assimilated the new MOPITT CO retrievals, using the Goddard Earth Observing System (GEOS)‐Chem model, to study the influence of vertical transport errors on inferred CO sources. We compared the source estimates obtained by assimilating the CO profiles, the column amounts, and the surface level retrievals for June–August 2006. The three different inversions produced large differences in the source estimates in regions of convection and strong CO emissions. The inversion using the CO profiles suggested an 85% increase in emissions in India/Southeast Asia, which exacerbated the model bias in the lower and middle troposphere, whereas using the surface level retrievals produced a 37% decrease in Indian/Southeast Asian emissions, which exacerbated the underestimate of CO in the upper troposphere. Globally, the inversion with the surface retrievals suggested a 22% reduction in emissions from the a priori estimate of 161 Tg CO/month (from combustion and the oxidation of biogenic volatile organic compounds), averaged in June–August 2006. The analysis results were validated with independent surface CO measurements from NOAA Global Monitoring Division (GMD) network and upper troposphere CO measurements from the Civil Aircraft for the Regular Investigation of the Atmosphere Based on an Instrumented Container (CARIBIC). We found that the inversion with the surface retrievals agreed best with surface CO data but produced the largest discrepancy with the CARIBIC aircraft data in the upper troposphere, suggesting the influence of vertical transport errors in the model. Our results show that the comparison of the a posteriori CO distributions obtained from the inversions using the surface and profile retrievals provides a means of characterizing the potential impact of the vertical transport biases on the source estimates and the CO distribution.

Satellite based analysis of fire–carbon monoxide relationships from forest and agricultural residue burning (2003–2011)

Carbon monoxide (CO) is an important greenhouse gas that is emitted during the incomplete combustion of biomass burning. In this study, we assessed the Measurements Of Pollution In the Troposphere (MOPITT) CO retrievals from two different biomass burning regions, fires in the evergreen forests of Northeast India and agriculture residue fires, Punjab, India. We analyzed long-term trends (2003–2011) in CO retrievals and fire–CO relationships including CO profiles at nine different atmospheric levels. Over a ten year period, the mean monthly CO for Northeast India ranged from 140.86 ppmv (−1σ) to 348.85 ppbv (+1σ) with a mean CO of 244.85 ppbv. We observed a clear increase in CO signal from February to March followed by a decrease in May coinciding with the fire signal. In Punjab, the mean monthly CO ranged from 158.21 ppbv (−1σ) to 286.40 ppbv (+1σ) with a mean CO of 222.30 ppbv. Comparison of mean CO during the peak fire months suggested relatively higher CO (439.06 ppbv) during March (evergreen forest burning) than October (194.83 ppbv) agricultural residue burning. We found MODIS fire radiative power (FRP) as a stronger predictor of surface CO signal than the fire counts in the evergreen forest fires. The segmented regression model fitted using nine years of FRP–CO data was useful in finding the FRP threshold impact on CO concentrations in the evergreen forests. To explain the low correlation between fires and MOPITT CO signal from the agricultural residue fires, we used the CALIPSO data to infer the smoke plume heights. Results suggested an average smoke plume height of 2.2 km during the peak biomass burning month from agricultural fires, compared to 4.61 km from evergreen forest fires. Overall, the MODIS FRP and CALIPSO data were useful in understanding the MOPITT CO sensitivity to fires.

An Improvement of Carbon Monoxide Retrieval from SCIAMACHY by Using a Cloud Correction Scheme

An Improvement of Carbon Monoxide Retrieval from SCIAMACHY by Using a Cloud Correction Scheme

Regional CO pollution over the Indian-subcontinent and various transport pathways as observed by MOPITT

We used day-side Measurement of Pollution in the Troposphere (MOPITT) carbon monoxide (CO) retrievals (2000–2007) to examine the regional CO emission and its transport pathways during the summer/winter monsoon, with a specific focus on the Indian-subcontinent. It is observed that MOPITT CO retrievals at 850 hPa level in general show large scale features of CO emission in India, as reflected in the bottom-up inventory. In particular, high CO mixing ratios over the eastern north-eastern part of India, along the Indo-Gangetic (IG) region, and low CO mixing ratios over central India are generally captured from the MOPITT data. A strong plume with enhanced CO mixing ratios at 350 hPa is observed during the summer monsoon, demonstrating large scale vertical transport of the boundary layer CO from the Indian region into the upper troposphere. During winter outflow CO from the Indian region is found to be transported over the Arabian Sea and Bay of Bengal and reaches up to Saudi Arabia and north-eastern Africa. It is observed that emissions from Southeast Asia and the eastern north-eastern Indian region have the greatest impact over the Bay of Bengal and the eastern Indian Ocean, while emissions from the rest of India dominate over the Arabian Sea and the western Indian Ocean.

Validating the AIRS Version 5 CO Retrieval With DACOM In Situ Measurements During INTEX-A and -B

Herein we provide a description of the atmospheric infrared sounder (AIRS) version 5 (v5) carbon monoxide (CO) retrieval algorithm and its validation with the DACOM in situ measurements during the INTEX-A and -B campaigns. All standard and support products in the AIRS v5 CO retrieval algorithm are documented. Building on prior publications, we describe the convolution of in situ measurements with the AIRS v5 CO averaging kernel and first-guess CO profile as required for proper validation. Validation is accomplished through comparison of AIRS CO retrievals with convolved in situ CO profiles acquired during the NASA Intercontinental Chemical Transport Experiments (INTEX) in 2004 and 2006. From 143 profiles in the northern mid-latitudes during these two experiments, we find AIRS v5 CO retrievals are biased high by 6%-10% between 900 and 300 hPa with a root-mean-square error of 8%-12%. No significant differences were found between validation using spiral profiles coincident with AIRS overpasses and in-transit profiles under the satellite track but up to 13 h off in time. Similarly, no significant differences in validation results were found for ocean versus land, day versus night, or with respect to retrieved cloud top pressure or cloud fraction.

Bayesian statistical modeling of spatially correlated error structure in atmospheric tracer inverse analysis

Abstract. We present and discuss the use of Bayesian modeling and computational methods for atmospheric chemistry inverse analyses that incorporate evaluation of spatial structure in model-data residuals. Motivated by problems of refining bottom-up estimates of source/sink fluxes of trace gas and aerosols based on satellite retrievals of atmospheric chemical concentrations, we address the need for formal modeling of spatial residual error structure in global scale inversion models. We do this using analytically and computationally tractable conditional autoregressive (CAR) spatial models as components of a global inversion framework. We develop Markov chain Monte Carlo methods to explore and fit these spatial structures in an overall statistical framework that simultaneously estimates source fluxes. Additional aspects of the study extend the statistical framework to utilize priors on source fluxes in a physically realistic manner, and to formally address and deal with missing data in satellite retrievals. We demonstrate the analysis in the context of inferring carbon monoxide (CO) sources constrained by satellite retrievals of column CO from the Measurement of Pollution in the Troposphere (MOPITT) instrument on the TERRA satellite, paying special attention to evaluating performance of the inverse approach using various statistical diagnostic metrics. This is developed using synthetic data generated to resemble MOPITT data to define a proof-of-concept and model assessment, and then in analysis of real MOPITT data. These studies demonstrate the ability of these simple spatial models to substantially improve over standard non-spatial models in terms of statistical fit, ability to recover sources in synthetic examples, and predictive match with real data.

A comparison of OEM CO retrievals from the IASI and MOPITT instruments

Abstract. Observations of atmospheric carbon monoxide (CO) can only be made on continental and global scales by remote sensing instruments situated in space. One such instrument is the Infrared Atmospheric Sounding Interferometer (IASI), producing spectrally resolved, top-of-atmosphere radiance measurements from which CO vertical layers and total columns can be retrieved. This paper presents a technique for intercomparisons of satellite data with low vertical resolution. The example in the paper also generates the first intercomparison between an IASI CO data set, in this case that produced by the University of Leicester IASI Retrieval Scheme (ULIRS), and the V3 and V4 operationally retrieved CO products from the Measurements Of Pollution In The Troposphere (MOPITT) instrument. The comparison is performed for a localised region of Africa, primarily for an ocean day-time configuration, in order to develop the technique for instrument intercomparison in a region with well defined a priori. By comparing both the standard data and a special version of MOPITT data retrieved using the ULIRS a priori for CO, it is shown that standard intercomparisons of CO are strongly affected by the differing a priori data of the retrievals, and by the differing sensitivities of the two instruments. In particular, the differing a priori profiles for MOPITT V3 and V4 data result in systematic retrieved profile changes as expected. An application of averaging kernels is used to derive a difference quantity which is much less affected by smoothing error, and hence more sensitive to systematic error. These conclusions are confirmed by simulations with model profiles for the same region. This technique is used to show that for the data that has been processed the systematic bias between MOPITT V4 and ULIRS IASI data, at MOPITT vertical resolution, is less than 7 % for the comparison data set, and on average appears to be less than 4 %. The results of this study indicate that intercomparisons of satellite data sets with low vertical resolution should ideally be performed with: retrievals using a common a priori appropriate to the geographic region studied; the application of averaging kernels to compute difference quantities with reduced a priori influence; and a comparison with simulated differences using model profiles for the target gas in the region.

Episodes of cross-polar transport in the Arctic troposphere during July 2008 as seen from models, satellite, and aircraft observations

Abstract. During the POLARCAT summer campaign in 2008, two episodes (2–5 July and 7–10 July 2008) occurred where low-pressure systems traveled from Siberia across the Arctic Ocean towards the North Pole. The two cyclones had extensive smoke plumes from Siberian forest fires and anthropogenic sources in East Asia embedded in their associated air masses, creating an excellent opportunity to use satellite and aircraft observations to validate the performance of atmospheric transport models in the Arctic, which is a challenging model domain due to numerical and other complications. Here we compare transport simulations of carbon monoxide (CO) from the Lagrangian transport model FLEXPART and the Eulerian chemical transport model TOMCAT with retrievals of total column CO from the IASI passive infrared sensor onboard the MetOp-A satellite. The main aspect of the comparison is how realistic horizontal and vertical structures are represented in the model simulations. Analysis of CALIPSO lidar curtains and in situ aircraft measurements provide further independent reference points to assess how reliable the model simulations are and what the main limitations are. The horizontal structure of mid-latitude pollution plumes agrees well between the IASI total column CO and the model simulations. However, finer-scale structures are too quickly diffused in the Eulerian model. Applying the IASI averaging kernels to the model data is essential for a meaningful comparison. Using aircraft data as a reference suggests that the satellite data are biased high, while TOMCAT is biased low. FLEXPART fits the aircraft data rather well, but due to added background concentrations the simulation is not independent from observations. The multi-data, multi-model approach allows separating the influences of meteorological fields, model realisation, and grid type on the plume structure. In addition to the very good agreement between simulated and observed total column CO fields, the results also highlight the difficulty to identify a data set that most realistically represents the actual pollution state of the Arctic atmosphere.

Characterizing summertime chemical boundary conditions for airmasses entering the US West Coast

Abstract. The objective of this study is to analyze the pollution inflow into California during summertime and how it impacts surface air quality through combined analysis of a suite of observations and global and regional models. The focus is on the transpacific pollution transport investigated by the NASA Arctic Research of the Composition of the Troposphere from Aircraft and Satellites (ARCTAS) mission in June 2008. Additional observations include satellite retrievals of carbon monoxide and ozone by the EOS Aura Tropospheric Emissions Spectrometer (TES), aircraft measurements from the MOZAIC program and ozonesondes. We compare chemical boundary conditions (BC) from the MOZART-4 global model, which are commonly used in regional simulations, with measured concentrations to quantify both the accuracy of the model results and the variability in pollution inflow. Both observations and model reflect a large variability in pollution inflow on temporal and spatial scales, but the global model captures only about half of the observed free tropospheric variability. Model tracer contributions show a large contribution from Asian emissions in the inflow. Recirculation of local US pollution can impact chemical BC, emphasizing the importance of consistency between the global model simulations used for BC and the regional model in terms of emissions, chemistry and transport. Aircraft measurements in the free troposphere over California show similar concentration ranges, variability and source contributions as free tropospheric air masses over ocean, but caution has to be taken that local pollution aloft is not misinterpreted as inflow. A flight route specifically designed to sample boundary conditions during ARCTAS-CARB showed a prevalence of plumes transported from Asia and thus may not be fully representative for average inflow conditions. Sensitivity simulations with a regional model with altered BCs show that the temporal variability in the pollution inflow does impact modeled surface concentrations in California. We suggest that time and space varying chemical boundary conditions from global models provide useful input to regional models, but likely still lead to an underestimate of peak surface concentrations and the variability associated with long-range pollution transport.

Improved agreement of AIRS tropospheric carbon monoxide products with other EOS sensors using optimal estimation retrievals

Abstract. We present in this paper an alternative retrieval algorithm for the Atmospheric Infrared Sounder (AIRS) tropospheric Carbon Monoxide (CO) products using the Optimal Estimation (OE) technique, which is different from the AIRS operational algorithm. The primary objective for this study was to compare AIRS CO, as well as the other retrieval properties such as the Averaging Kernels (AKs), the Degrees of Freedom for Signal (DOFS), and the error covariance matrix, against the Tropospheric Emission Spectrometer (TES) and the Measurement of Pollution in the Troposphere (MOPITT) CO, which were also derived using the OE technique. We also demonstrate that AIRS OE CO results are much more realistic than AIRS V5 operational CO, especially in the lower troposphere and in the Southern Hemisphere (SH). These products are validated with in situ profiles obtained by the Differential Absorption Carbon Monoxide Measurements (DACOM), which took place as part of NASA's Intercontinental Chemical Transport Experiment (INTEX-B) field mission that was conducted over the northern Pacific in Spring 2006. To demonstrate the differences existing in the current operational products we first show a detailed direct comparison between AIRS V5 and TES operational V3 CO for the global datasets from December 2005 to July 2008. We then present global CO comparisons between AIRS OE, TES V3, and MOPITT V4 at selected pressure levels as well as for the total column amounts. We conclude that the tropospheric CO retrievals from AIRS OE and TES V3 agree to within 5–10 ppbv or 5% on average globally and throughout the free troposphere. The agreements in total column CO amounts between AIRS OE and MOPITT V4 have improved significantly compared to AIRS V5 with global relative RMS differences now being 12.7%.

Observations of near‐surface carbon monoxide from space using MOPITT multispectral retrievals

Using both thermal infrared (TIR) and near infrared (NIR) channels of MOPITT (Measurements of Pollution in the Troposphere) on EOS‐Terra, we demonstrate the first coincident multispectral retrievals of carbon monoxide (CO) from space. Exploiting both TIR and NIR channels has been possible due to recent progress in characterizing NIR channel radiance errors. This has allowed us to trade off sensitivity to near surface CO for larger random errors in the combined retrieval. By examining retrieval diagnostics such as DFS (degrees of freedom for signal) and averaging kernels for the multispectral retrieval (TIR + NIR) as compared to the TIR‐only retrieval, we find that adding the NIR channel to the retrieval significantly increases sensitivity to CO, especially near the surface, but with high spatial variability due to surface albedo variations. The cases with the largest increases in DFS are over regions with low thermal contrast between the surface and lower atmosphere. In the tropics (23.4°S–23.4°N), the fraction of daytime land cases with at least 0.4 DFS in the surface layer (surface to 800 hPa) is 20% for TIR‐only retrievals compared to 59% for multispectral retrievals. Vertical resolution for the surface layer is also improved, in some cases from around 6 km for TIR‐only to roughly 1 km for TIR + NIR. Since we apply a single a priori CO profile (unlike MOPITT V4) and error covariance in all the retrievals reported here, these increases are due solely to the addition of the NIR channel. Enhanced sensitivity to near surface CO is especially evident in a case study for central/east Asia where source regions for urban areas with high population density are clearly identifiable. Although these retrievals are still a research product and require further validation and scientific evaluation, they demonstrate the increased sensitivity to CO in the lowermost troposphere that can be obtained from multispectral MOPITT data.

Interpretation of Aura satellite observations of CO and aerosol index related to the December 2006 Australia fires

Enhanced carbon monoxide (CO) in the upper troposphere (UT) is shown by nearly collocated Tropospheric Emission Spectrometer (TES) and Microwave Limb Sounder (MLS) measurements near and down-wind from the known wildfire region of SE Australia from December 12th–19th, 2006. Enhanced ultraviolet (UV) aerosol index (AI) derived from the Ozone Monitoring Instrument (OMI) measurements correlates with these high CO concentrations. The Hybrid Single Particle Langrangian Integrated Trajectory (HYSPLIT) model back trajectories trace selected air parcels, where TES observes enhanced CO in the upper and lower troposphere, to the SE Australia fire region as their initial location. Simultaneously, they show a lack of vertical advection along their tracks. TES retrieved CO vertical profiles in the higher and lower southern latitudes are examined together with the averaging kernels and show that TES CO retrievals are most sensitive at approximately 300–400 hPa. The enhanced CO observed by TES in the upper (215 hPa) and lower (681 hPa) troposphere are, therefore, influenced by mid-tropospheric CO. GEOS-Chem model simulations with an 8-day emission inventory, as the wildfire source over Australia, are sampled to the TES/MLS observation times and locations. These simulations only show CO enhancements in the lower troposphere near and down-wind from the wildfire region of SE Australia with drastic underestimates of UT CO plumes. Although CloudSat along-track ice-water content curtains are examined to see whether possible vertical convection events can explain the high UT CO values, sparse observations of collocated Aura CO and CloudSat along-track ice-water content measurements for the single event precludes any conclusive correlation. Vertical convection that uplifts the fire-induced CO ( i.e., most notably referred to as pyro-cumulonimbus (pyroCb)) may provide an explanation for the incongruence between these simulations and the TES/MLS observations of enhanced CO in the UT.

Constraints on black carbon aerosol distribution from Measurement of Pollution in the Troposphere (MOPITT) CO

We present an approach to constrain simulated atmospheric black carbon (BC) using carbon monoxide (CO) observations. The approach uses: (1) the Community Atmosphere Model with Chemistry to simulate the evolution of BC and CO within an ensemble of model simulations; (2) satellite CO retrievals from the MOPITT/Terra instrument to assimilate observed CO into these simulations; (3) the derived sensitivity of BC to CO within these simulations to correct the simulated BC distributions. We demonstrate the performance of this approach through model experiments with and without the BC corrections during the period coinciding with the Intercontinental Chemical Transport Experiment (INTEX‐B). Our results show significant improvements (∼50%) in median BC profiles using constraints from MOPITT, based on comparisons with INTEX‐B measurements. We find that assimilating MOPITT CO provides considerable impact on simulated BC concentrations, especially over source regions. This approach offers an opportunity to augment our current ability to predict BC distributions.

Review on the applications of Tropospheric Emissions Spectrometer to air-quality research: Perspectives for China

The Tropospheric Emissions Spectrometer (TES) aboard the National Aeronautics and Space Administration’s (NASA’s) Aura satellite launched in July 2004 is the first satellite instrument to provide simultaneous retrievals of ozone (O3) and carbon monoxide (CO) throughout the Earth’s lower atmosphere. This paper briefly reviews the TES instrument, the retrieval of O3 and CO profiles, and the validation of the retrievals. The applications of TES O3 and CO products include mapping the vertical and horizontal distribution of tropospheric O3 and CO and their correlations, examining the regional and continental outflow, and analyzing the variability of the two species associated with certain weather and climatic conditions, such as El Nino and the Asian monsoon. TES retrievals of O3 and CO offer an important new source of satellite data over China with good spatial and temporal coverage that can provide evaluation and constraints on the performance of chemical transport models in simulating the general features of ozone pollution over China. Special observations have been conducted and requests may be submitted to the TES team to make geographically focused observations of O3 and CO over China.