Kelly Chance

Harvard-Smithsonian Center for Astrophysics, Cambridge, Massachusetts, United States

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Publications (169)215.72 Total impact

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    ABSTRACT: OMI HCHO is validated over the continental US (CONUS), and used to analyze regional sources in Northeast Asia (NA) and Southeast Asia (SA). OMI HCHO Version 2.0 data show unrealistic trends, which prompted the production of a corrected OMI HCHO data set. EOF and SVD are utilized to compare the spatial and temporal variability between OMI HCHO against GOME and SCIAMACHY, and against GEOS-Chem. CONUS HCHO chemistry is well studied; its concentrations are greatest in the southeastern US with annual cycle maximums corresponding to the summer vegetation. The corrected OMI HCHO agrees with this understanding as well as with the other sensors measurements and has no unrealistic trends. In NA the annual cycle is super-posed by extremely large concentrations in polluted mega-cities. The other sensors generally agree with NA's OMI HCHO regional distribution, but megacity signal is not seen in GEOS-Chem. Our study supports the findings proposed by others that the emission inventory used in GEOS-Chem significantly underestimates anthropogenic influence on HCHO emission over megacities. The persistent mega-city signal is also present in SA. In SA the spatial and temporal patterns of OMI HCHO show a maximum in the dry season. The patterns are in remarkably good agreement with fire counts, which illustrates that the variability of HCHO over SA is strongly influenced by biomass burning. The corrected OMI HCHO data has realistic trends, conforms to well-known sources over CONUS, and has shown a stationary large concentration over polluted Asian mega-cities, and a widespread biomass burning in SA.
    Science of The Total Environment 05/2014; 490C:93-105. · 3.26 Impact Factor
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    ABSTRACT: Future geostationary satellite observations of tropospheric ozone aim to improve monitoring of surface ozone air quality. However, ozone retrievals from space have limited sensitivity in the lower troposphere (boundary layer). Data assimilation in a chemical transport model can propagate the information from the satellite observations to provide useful constraints on surface ozone. This may be aided by correlated satellite observations of carbon monoxide (CO), for which boundary layer sensitivity is easier to achieve. We examine the potential of concurrent geostationary observations of ozone and CO to improve constraints on surface ozone air quality through exploitation of ozone–CO model error correlations in a joint data assimilation framework. The hypothesis is that model transport errors diagnosed for CO provide information on corresponding errors in ozone. A paired-model analysis of ozone–CO error correlations in the boundary layer over North America in summer indicates positive error correlations in continental outflow but negative regional-scale error correlations over land, the latter reflecting opposite sensitivities of ozone and CO to boundary layer depth. Aircraft observations from the ICARTT campaign are consistent with this pattern but also indicate strong positive error correlations in fine-scale pollution plumes. We develop a joint ozone–CO data assimilation system and apply it to a regional-scale Observing System Simulation Experiment (OSSE) of the planned NASA GEO-CAPE geostationary mission over North America. We find substantial benefit from joint ozone–CO data assimilation in informing US ozone air quality if the instrument sensitivity for CO in the boundary layer is greater than that for ozone. A high-quality geostationary measurement of CO could potentially relax the requirements for boundary layer sensitivity of the ozone measurement. This is contingent on accurate characterization of ozone–CO error correlations. A finer-resolution data assimilation system resolving the urban scale would need to account for the change in sign of the ozone–CO error correlations between urban pollution plumes and the regional atmosphere.
    Atmospheric Environment. 01/2014; 84:254–261.
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    ABSTRACT: OMI HCHO is validated over the continental US (CONUS), and used to analyze regional sources in Northeast Asia (NA) and Southeast Asia (SA). OMI HCHO Version 2.0 data show unrealistic trends, which prompted the production of a corrected OMI HCHO data set. EOF and SVD are utilized to compare the spatial and temporal variability between OMI HCHO against GOME and SCIAMACHY, and against GEOS-Chem. CONUS HCHO chemistry is well studied; its concentrations are greatest in the southeastern US with annual cycle maximums corresponding to the summer vegetation. The corrected OMI HCHO agrees with this understanding as well as with the other sensors measurements and has no unrealistic trends. In NA the annual cycle is super-posed by extremely large concentrations in polluted mega-cities. The other sensors generally agree with NA’s OMI HCHO regional distribution, but megacity signal is not seen in GEOS-Chem. Our study supports the findings proposed by others that the emission inventory used in GEOS-Chem significantly underestimates anthropogenic influence on HCHO emission over megacities. The persistent mega-city signal is also present in SA. In SA the spatial and temporal patterns of OMI HCHO show a maximum in the dry season. The patterns are in remarkably good agreement with fire counts, which illustrates that the variability of HCHO over SA is strongly influenced by biomass burning. The corrected OMI HCHO data has realistic trends, conforms to well-known sources over CONUS, and has shown a stationary large concentration over polluted Asian mega-cities, and a widespread biomass burning in SA.
    Science of The Total Environment 01/2014; 490:93–105. · 3.26 Impact Factor
  • Cheng Liu, Xiong Liu, Kelly Chance
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    ABSTRACT: We compare three datasets of high-resolution O3 cross sections and evaluate the effects of using these cross sections on O3 profile retrievals from OMI UV (270–330 nm) measurements. These O3 cross sections include Brion–Daumont–Malicet (BDM), Bass–Paur (BP) and a new dataset measured by Serdyuchenko et al. (SGWCB), which is made from measurements at more temperatures and in a wider temperature range than BDM and BP, 193–293 K. Relative to the BDM dataset, the SGWCB data have systematic biases of ‑2 to +4% for 260–340 nm, and the BP data have smaller biases of 1–2% below 315 nm but larger spiky biases of up to ±6% at longer wavelengths. These datasets show distinctly different temperature dependences. Using different cross sections can significantly affect atmospheric retrievals. Using SGWCB data leads to retrieval failure for almost half of the OMI spatial pixels, producing large negative ozone values that cannot be handled by radiative transfer models and using BP data leads to large fitting residuals over 310–330 nm. Relative to the BDM retrievals, total ozone retrieved using original SGWCB data (with linear temperature interpolation/extrapolation) typically shows negative biases of 5–10 DU; retrieved tropospheric ozone column generally shows negative biases of 5–10 DU and 5–20 DU for parameterized and original SGWCB data, respectively. Compared to BDM retrievals, ozone profiles retrieved with BP/SGWCB data on average show large altitude-dependent oscillating differences of up to ±20–40% biases below ~20 km with almost opposite bias patterns. Validation with ozonesonde observations demonstrates that the BDM retrievals agree well with ozonesondes, to typically within 10%, while both BP and SGWCB retrievals consistently show large altitude-dependent biases of up to ±20–70% below 20 km. Therefore, we recommend using the BDM dataset for ozone profile retrievals from UV measurements. Its improved performance is likely due to its better characterization of temperature dependence in the Hartley and Huggins bands.
    Journal of Quantitative Spectroscopy and Radiative Transfer 11/2013; · 2.38 Impact Factor
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    ABSTRACT: TEMPO was selected in 2012 by NASA as the first Earth Venture Instrument, for launch circa 2018. It will measure atmospheric pollution for greater North America from space using ultraviolet and visible spectroscopy. TEMPO measures from Mexico City to the Canadian tar sands, and from the Atlantic to the Pacific, hourly and at high spatial resolution (~2 km N/S×4.5 km E/W at 36.5°N, 100°W). TEMPO provides a tropospheric measurement suite that includes the key elements of tropospheric air pollution chemistry. Measurements are from geostationary (GEO) orbit, to capture the inherent high variability in the diurnal cycle of emissions and chemistry. The small product spatial footprint resolves pollution sources at sub-urban scale. Together, this temporal and spatial resolution improves emission inventories, monitors population exposure, and enables effective emission-control strategies. TEMPO takes advantage of a commercial GEO host spacecraft to provide a modest cost mission that measures the spectra required to retrieve O3, NO2, SO2, H2CO, C2H2O2, H2O, aerosols, cloud parameters, and UVB radiation. TEMPO thus measures the major elements, directly or by proxy, in the tropospheric O3 chemistry cycle. Multi-spectral observations provide sensitivity to O3 in the lowermost troposphere, substantially reducing uncertainty in air quality predictions. TEMPO quantifies and tracks the evolution of aerosol loading. It provides near-real-time air quality products that will be made widely, publicly available. TEMPO will launch at a prime time to be the North American component of the global geostationary constellation of pollution monitoring together with European Sentinel-4 and Korean GEMS.
    Proc SPIE 09/2013;
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    ABSTRACT: We use formaldehyde (HCHO) vertical column measurements from the Scanning Imaging Absorption spectrometer for Atmospheric Chartography (SCIAMACHY) and Ozone Monitoring Instrument (OMI), and a nested-grid version of the GEOS-Chem chemistry transport model, to infer an ensemble of top-down isoprene emission estimates from tropical South America during 2006, using different model configurations and assumptions in the HCHO air-mass factor (AMF) calculation. Scenes affected by biomass burning are removed on a daily basis using fire count observations, and we use the local model sensitivity to identify locations where the impact of spatial smearing is small, though this comprises spatial coverage over the region. We find that the use of the HCHO column data more tightly constrains the ensemble isoprene emission range from 27–61 Tg C to 31–38 Tg C for SCIAMACHY, and 45–104 Tg C to 28–38 Tg C for OMI. Median uncertainties of the top-down emissions are about 60–260% for SCIAMACHY, and 10–90% for OMI. We find that the inferred emissions are most sensitive to uncertainties in cloud fraction and cloud top pressure (differences of ˙10%), the a priori isoprene emissions (˙20%), and the HCHO vertical column retrieval (˙30%). Construction of continuous top-down emission maps generally improves GEOS-Chem’s simulation of HCHO columns over the region, with respect to both the SCIAMACHY and OMI data. However, if local time top-down emissions are scaled to monthly mean values, the annual emission inferred from SCIAMACHY are nearly twice those from OMI. This difference cannot be explained by the different sampling of the sensors or uncertainties in the AMF calculation.
    Journal of Geophysical Research: Atmospheres. 06/2013; 118:n/a-n/a.
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    ABSTRACT: Elevated levels of formaldehyde (HCHO) in Nigeria, as observed using the Ozone Monitoring Instrument, indicate a large source of anthropogenic volatile organic compounds (VOCs). We isolate an anthropogenic signal of HCHO by removing the biomass burning and biogenic signal. We use space-based observations of gas flare hotspots, carbon monoxide, methane, nitrogen dioxide and glyoxal to identify emission source locations - city centers (Lagos, Abuja, Port Harcourt); Niger Delta petroleum and natural gas extraction; and intense biofuel use in populous rural regions. GEOS-Chem underestimates anthropogenic HCHO in Nigeria and we use aircraft observations of VOCs made over Lagos during the AMMA campaign (Jul-Aug 2006) and SCIAMACHY methane observations over the Niger Delta to address this discrepancy. After updating GEOS-Chem VOC emissions in Nigeria we find that local emissions increase surface ozone north of the Nigerian coastline (persistent onshore winds) and ozone and peroxyacetyl nitrate in the free troposphere stretching from the Gulf of Guinea to the east coast of South America (monsoonal convection and advection along a branch of the African Easterly Jet).
    04/2013;
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    ABSTRACT: Lightning is a particularly significant NOx source in the middle and upper troposphere where it affects tropospheric chemistry and ozone. Because the version-4 Community Multiscale Air Quality Modeling System (CMAQ) does not account for NOx emission from lightning, it underpredicts NOx above the mixed layer. In this study, the National Lightning Detection Network™ (NLDN) lightning data are applied to the CMAQ model to simulate the influence of lightning-produced NOx (LNOx) on upper tropospheric NOx and subsequent ozone concentration. Using reasonable values for salient parameters (detection efficiency ∼95%, cloud flash to ground flash ratio ∼3, LNOx production rate ∼500 mol N per flash), the NLDN ground flashes are converted into total lightning NOx amount and then vertically distributed on 39 CMAQ model layers according to a vertical-distribution profile of lightning N mass. This LNOx contributes 27% of the total NOx emission during 15 July ∼7 September 2006. This additional NOx reduces the low-bias of simulated tropospheric O3 columns with respect to OMI tropospheric O3 columns from 10 to 5%. Although the model prediction of ozone in upper troposphere improves by ∼20 ppbv due to lightning-produced NOx above the southeastern and eastern U.S.A., the improved ozone prediction is still ∼20–25 ppbv lower than ozonesonde measurements.
    Atmospheric Environment 03/2013; 67:219–228. · 3.11 Impact Factor
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    ABSTRACT: We use a nested-grid version of the GEOS-Chem chemistry transport model, constrained by isoprene emissions from the Model of Emissions of Gases and Aerosols from Nature (MEGAN), and the Lund-Potsdam-Jena General Ecosystem Simulator (LPJ-GUESS) bottom-up inventories, to evaluate the impact that surface isoprene emissions have on formaldehyde (HCHO) air-mass factors (AMFs) and vertical column densities (VCDs) over tropical South America during 2006, as observed by the Scanning Imaging Absorption Spectrometer for Atmospheric Chartography (SCIAMACHY) and Ozone Monitoring Instrument (OMI). Although the large-scale seasonal variability of monthly mean HCHO VCDs is typically unaffected by the choice of bottom-up inventory, large relative differences of up to �45% in the HCHO VCD can occur for individual regions and months, but typically most VCD differences are of order �20%. These relative changes are comparable to those produced by other sources of uncertainty in the AMF including aerosols and surface albedo, but less than those from clouds. In a sensitivity test, we find that top-down annual isoprene emissions inferred from SCIAMACHY and OMI HCHO vertical columns can vary by as much as �30–50% for each instrument respectively, depending on the region studied and the a priori isoprene emissions used. Our analysis suggests that the influence of the a priori isoprene emissions on HCHO AMFs and VCDs is therefore non-negligible and must be carefully considered when inferring top-down isoprene emissions estimates over this, or potentially any other, region.
    Journal of Geophysical Research 07/2012; 117(D13):D13304. · 3.17 Impact Factor
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    ABSTRACT: We present an assessment study of the Global Ozone Monitoring Experiment 2 (GOME-2) reflectance for the wavelength range 270–350 nm by comparing measurements with simulations calculated using the vector linearized discrete ordinate radiative transfer model (VLIDORT) and Microwave Limb Sounder (MLS) ozone profiles. The results indicate wavelength- and cross-track-position-dependent biases. GOME-2 reflectance is overestimated by 10% near 300 nm and by 15%–20% around 270 nm. Stokes fraction measurements made by onboard polarization measurement devices are also validated directly using the VLIDORT model. GOME-2 measurements agree well with the simulated Stokes fractions, with mean biases ranging from −1.0% to ∼2.9%; the absolute differences are less than 0.05. Cloudiness-dependent biases suggest the existence of uncorrected stray-light errors that vary seasonally and latitudinally. Temporal analysis indicates that reflectance degradation began at the beginning of the mission; the reflectance degrades by 15% around 290 nm and by 2.2% around 325 nm from 2007 through 2009. Degradation shows wavelength- and viewing-angle-dependent features. Preliminary validation of ozone profile retrievals with MLS, Michelson Interferometer for Passive Atmospheric Sounding, and ozonesonde reveals that the application of radiometric recalibration improves the ozone profile retrievals as well as reduces fitting residuals by 30% in band 2b.
    Journal of Geophysical Research 01/2012; 117(D7):D07305. · 3.17 Impact Factor
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    ABSTRACT: The NASA-funded GeoTASO Instrument Incubator project will develop an airborne spectrometer, participate in field campaigns, and test trace gas and aerosol retrieval performance in support of a proposed space-based air quality sensor in orbit.
    Optics for Solar Energy; 11/2011
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    ABSTRACT: We present an evaluation of a nested high-resolution Goddard Earth Observing System (GEOS)-Chem chemistry transport model simulation of tropospheric chemistry over tropical South America. The model has been constrained with two isoprene emission inventories: (1) the canopy-scale Model of Emissions of Gases and Aerosols from Nature (MEGAN) and (2) a leaf-scale algorithm coupled to the Lund-Potsdam-Jena General Ecosystem Simulator (LPJ-GUESS) dynamic vegetation model, and the model has been run using two different chemical mechanisms that contain alternative treatments of isoprene photo-oxidation. Large differences of up to 100 Tg C yr−1 exist between the isoprene emissions predicted by each inventory, with MEGAN emissions generally higher. Based on our simulations we estimate that tropical South America (30–85�W, 14�N–25�S) contributes about 15–35% of total global isoprene emissions. We have quantified the model sensitivity to changes in isoprene emissions, chemistry, boundary layer mixing, and soil NOx emissions using ground-based and airborne observations. We find GEOS-Chem has difficulty reproducing several observed chemical species; typically hydroxyl concentrations are underestimated, whilst mixing ratios of isoprene and its oxidation products are overestimated. The magnitude of model formaldehyde (HCHO) columns are most sensitive to the choice of chemical mechanism and isoprene emission inventory. We find GEOS-Chem exhibits a significant positive bias (10–100%) when compared with HCHO columns from the Scanning Imaging Absorption Spectrometer for Atmospheric Chartography (SCIAMACHY) and Ozone Monitoring Instrument (OMI) for the study year 2006. Simulations that use the more detailed chemical mechanism and/or lowest isoprene emissions provide the best agreement to the satellite data, since they result in lower-HCHO columns.
    Journal of Geophysical Research 08/2011; 116(D16):D16302. · 3.17 Impact Factor
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    ABSTRACT: One of the important science requirements of the Geostationary Coastal and Air Pollution Events (GEO-CAPE) mission is to be able to measure ozone with two degrees of freedom in the troposphere and sensitivity in the lowest 2 km (lowermost troposphere, LMT), in order to characterize air quality and boundary layer transport of pollution. Currently available remote sensing techniques utilize backscattered solar ultraviolet (UV) radiances or thermal infrared (TIR) emissions to perform ozone retrievals. However, in the TIR, measurement sensitivity to the LMT requires high thermal contrast between the Earth’s surface and the near-surface (tens to hundreds of meters above surface) atmosphere, while in the UV, the measurement sensitivity to the LMT is low because of Rayleigh scattering. In this paper, we explore the feasibility of using multi-spectral intensity measurements in the UV, visible (VIS), mid infrared (MIR) and TIR, and polarization measurements in the UV/VIS, to improve tropospheric and lowermost tropospheric ozone retrievals.Simulations for 16 cloud and aerosol free atmospheric profiles spanning a range of ozone mixing ratios indicate that adding VIS measurements to UV measurements significantly enhances the sensitivity to lowermost tropospheric ozone, but only makes a slight improvement to the total degrees of freedom for signal (DFS). On the other hand, the combination of UV and TIR significantly improves the total DFS as well as the lowermost tropospheric DFS.The analysis presented here is a necessary and important first step for defining spectral regions that can meet the GEO-CAPE measurement requirements, and subsequently, the requirements for instrumentation. In this work, the principle of multi-spectral retrievals has been extended from previously published literature and we show that the UV + VIS, UV + TIR and UV + VIS + TIR combinations have the potential to meet the GEO-CAPE measurement requirements for tropospheric ozone. Our analysis includes errors from water and surface properties; further analysis is needed to include temperature, additional gas interferents, clouds, aerosols and more realistic surface properties. These simulations must be run on a much larger dataset, followed by OSSEs (Observing System Simulation Experiments), where simulated retrievals are assimilated into chemical-transport models, to quantitatively assess the impact of the proposed measurements for constraining the spatiotemporal distribution of ozone in the LMT for basic science studies and applications such as air quality forecasts.Highlights► We use multi-spectral retrievals to retrieve lowermost tropospheric ozone. ► Simulations are performed for 16 cloud- and aerosol free atmospheric profiles. ► Combination of visible (VIS) and ultraviolet (UV) measurements has good sensitivity to lowermost tropospheric ozone. ► Combination of UV and thermal infrared (TIR) measurements significantly improves total and lowermost tropospheric degrees of freedom for signal (DFS).
    Atmospheric Environment 01/2011; 45(39):7151-7165. · 3.11 Impact Factor
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    ABSTRACT: Satellite-based atmospheric remote sensing aims at deriving the properties of trace gases, aerosols and clouds, as well as surface parameters from the measured top-of-atmosphere spectral radiance and reflectance. This requires, besides high quality spectra, an accurate modelling of the radiative transfer of solar radiation through the atmosphere to the sensor (forward model) and methods to derive the constituent properties from the measured top-of-atmosphere spectra (inversion methods). Many trace gases have structured absorption spectra in the UV-VIS spectral range serving as the starting point for determining their abundance by applying Differential Optical Absorption Spectroscopy (DOAS) or similar methods. In the UV-VIS-NIR and SWIR spectral regions the solar radiation is strongly scattered by clouds and aerosols. Therefore the presence of clouds and aerosol particles and their properties can also be inferred from the outgoing radiance measured by space-based instruments. Contrary to the forward model, the inversion methods allow to derive characteristics of the atmospheric state based on the measured quantities. A common product of the inversion of satellite measurements in limb, nadir or occultation geometry are total columns or height-resolved profiles of trace gas concentrations and aerosol parameters. Retrieving trace gas amounts in the troposphere constitutes a specific challenge. SCIAMACHY’s unique limb/nadir matching capability provides access to tropospheric columns by combining total columns obtained from nadir geometry with simultaneously measured stratospheric columns obtained from limb geometry.
    01/2011; , ISBN: 978-90-481-9895-5
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    ABSTRACT: We combine aircraft measurements (Second Texas Air Quality Study, Megacity Initiative: Local and Global Research Observations, Intercontinental Chemical Transport Experiment: Phase B) over the United States, Mexico, and the Pacific with a 3-D model (GEOS-Chem) to evaluate formaldehyde column (ΩHCHO) retrievals from the Ozone Monitoring Instrument (OMI) and assess the information they provide on HCHO across local to regional scales and urban to background regimes. OMI ΩHCHO correlates well with columns derived from aircraft measurements and GEOS-Chem (R = 0.80). For the full data ensemble, OMI's mean bias is −3% relative to aircraft-derived ΩHCHO (−17% where ΩHCHO > 5 � 1015 molecules cm−2) and −8% relative to GEOS-Chem, within expected uncertainty for the retrieval. Some negative bias is expected for the satellite and model, given the plume sampling of many flights and averaging over the satellite and model footprints. Major axis regression for OMI versus aircraft and model columns yields slopes (95% confidence intervals) of 0.80 (0.62–1.03) and 0.98 (0.73–1.35), respectively, with no significant intercept. Aircraft measurements indicate that the normalized vertical HCHO distribution, required by the satellite retrieval, is well captured by GEOS-Chem, except near Mexico City. Using measured HCHO profiles in the retrieval algorithm does not improve satellite-aircraft agreement, suggesting that use of a global model to specify shape factors does not substantially degrade retrievals over polluted areas. While the OMI measurements show that biogenic volatile organic compounds dominate intra-annual and regional ΩHCHO variability across the United States, smaller anthropogenic ΩHCHO gradients are detectable at finer spatial scales (∼20–200 km) near many urban areas.
    Journal of Geophysical Research 01/2011; 116(D5):D05303. · 3.17 Impact Factor
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    ABSTRACT: We evaluate the Ozone Monitoring Instrument (OMI) ozone profile retrieval against ozonesonde data and the Environmental Protection Agency (EPA) surface measurements for August 2006. Comparison of individual OMI ozone profile with ozonesonde indicates that OMI ozone profile can explain the general vertical variation of ozone but is limited in observing the boundary layer ozone, due to weak sensitivity to boundary layer ozone and thick lowest layer (∼2.5 km). We made pair-wise comparison between OMI and ozonesondes on 24 OMI vertical layers, as well as the 39 sigma-P vertical layers of the Community Multi-scale Air Quality (CMAQ) modeling system, respectively. OMI shows reasonable agreement with ozonesonde in the lower- to mid-troposphere. In the upper troposphere, while the bias increases, the normalized bias does not show much variation and remains below 10%. Comparison with EPA’s surface-monitoring data indicates that OMI observations at the lowest layer (surface to 2.5 km altitude) represent the mean values. While OMI underestimates elevated ozone concentrations, it explains the larger-scale spatial variation seen in the surface monitors.
    Atmospheric Environment 01/2011; 45(31):5523-5530. · 3.11 Impact Factor
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    ABSTRACT: We conduct an Observing System Simulation Experiment (OSSE) to test the ability of geostationary satellite measurements of ozone in different spectral regions to constrain surface ozone concentrations through data assimilation. Our purpose is to define instrument requirements for the NASA GEO-CAPE geostationary air quality mission over North America. We consider instruments using different spectral combinations of UV (290–340 nm), Vis (560–620 nm), and thermal IR (TIR, 9.6 μm). Hourly ozone data from the MOZART global 3-D chemical transport model (CTM) are taken as the “true” atmosphere to be sampled by the instruments for July 2001. The resulting synthetic data are assimilated in the GEOS-Chem CTM using a Kalman filter. The MOZART and GEOS-Chem CTMs have independent heritages and use different assimilated meteorological data sets for the same period, making for an objective OSSE. We show that hourly observations of ozone from geostationary orbit improve the assimilation considerably relative to daily observation from low earth orbit, and that broad observation over the ocean is unnecessary if the objective is to constrain surface ozone distribution over land. We also show that there is little propagation of ozone information from the free troposphere to the surface, so that instrument sensitivity in the boundary layer is essential. UV + Vis and UV + TIR spectral combinations improve greatly the information on surface ozone relative to UV alone. UV + TIR is preferable under high-sensitivity conditions with strong thermal contrast at the surface, but UV + Vis is preferable under low-sensitivity conditions. Assimilation of data from a UV + Vis + TIR instrument reduces the GEOS-Chem error for surface ozone by a factor of two. Observation in the TIR is critical to obtain ozone information in the upper troposphere relevant to climate forcing.Highlights► We simulate satellite instrument configurations observing ozone air quality. ► Most of ozone pollution is produced within the boundary layer. ► Geostationary observations are much more effective than low earth orbit observations. ► A multispectral instrument is necessary for required vertical sensitivity. ► Thermal infrared channel is critical to quantify climate forcing.
    Atmospheric Environment 01/2011; 45(39):7143-7150. · 3.11 Impact Factor
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    ABSTRACT: Wintertime extreme ozone minima in the total column ozone over the Tibetan Plateau (TP) between 1978 and 2001 are analyzed using observations from the Total Ozone Mapping Spectrometer (TOMS), Global Ozone Monitoring Experiment (GOME), and reanalysis data from both National Centers for Environmental Prediction and European Centre for Medium-Range Weather Forecasts. Results show that total column ozone reduction in nine persistent (lasting for at least 2 days) and four transient events can be substantially attributed to ozone reduction in the upper troposphere and lower stratosphere region (below 25 km). This reduction is generally caused by uplift of the local tropopause and northward transport of tropical ozone-poor air associated with an anomalous anticyclone in the upper troposphere. These anticyclonic anomalies are closely related to anomalous tropical deep convective heating, which is, however, not necessarily phase locked with the tropical Madden-Julian Oscillation as in our earlier case study. Considering stratospheric processes, the selected 13 events can be combined into nine independent events. Moreover, five of the nine independent events, especially the persistent events, are coupled with contributions from stratospheric dynamics between 25 and 40 km, i.e., 15%-40% derived from GOME observations for events in November 1998, February 1999, and December 2001. On the basis of these events, stratospheric column ozone reduction over the TP region can be attributed to the dynamics (development and/or displacement) of the two main stratospheric systems, namely, the polar vortex and the Aleutian High. The effect of a "low-ozone pocket" inside the Aleutian High on the total column ozone in East Asia requires further study.
    Journal of Geophysical Research 09/2010; 115(D18):18311-. · 3.17 Impact Factor
  • Journal of Quantitative Spectroscopy and Radiative Transfer 01/2010; 111(9):1041-1042. · 2.38 Impact Factor
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    ABSTRACT: have revealed the Tibetan Middle Tropospheric Ozone Minimum (TMTOM), a low-ozone layer that occurs in the middle troposphere over the Tibetan Plateau (TP) in June. Ozone profiles were derived from GOME observations and validated by ozonesonde measurements at two stations (Lhasa and Xining) over the TP. The mean bias is 5– 10% within the troposphere. The ozone profiles reveal the TMTOM phenomenon occurs in the middle troposphere (8 – 13 km) over the middle and eastern TP in June. Dynamical field analyses showed that the TMTOM accompanies the onset of the Asian summer monsoon. The low-ozone air from the Bay of Bengal is transported into the middle troposphere over the TP by southwest currents while the lower troposphere over the TP is still occupied by ozone-rich air blocked by the transport barrier of the Himalayas. The TMTOM was most prominent in June 1998 likely linked to the occurrence of the intense El Niño of 1997 – 1998 because the Tibetan anticyclone is of large area and has strong intensity during El Niño years. The occurrence of the TMTOM can serve as an indicator of the phase of evolution of the Asian summer monsoon.
    Geophys. Res. Lett. 01/2009; 36.

Publication Stats

4k Citations
215.72 Total Impact Points

Institutions

  • 1970–2014
    • Harvard-Smithsonian Center for Astrophysics
      • Division of Atomic and Molecular Physics
      Cambridge, Massachusetts, United States
  • 2005
    • University of Washington Seattle
      • Department of Atmospheric Sciences
      Seattle, WA, United States
  • 1997
    • Universität Bremen
      • Institute of Environmental Physics
      Bremen, Bremen, Germany
  • 1991–1993
    • University of Oregon
      • Department of Physics
      Eugene, OR, United States
    • National Institute of Standards and Technology
      Maryland, United States
  • 1415
    • The University of Edinburgh
      • School of GeoSciences
      Edinburgh, SCT, United Kingdom