Engineering topics

Pickering, K. E.

Publications and source records attributed to Pickering, K. E..

7 records

NASA NTRS2017

High-Resolution NO2 Observations from the Airborne Compact Atmospheric Mapper: Retrieval and Validation

Nitrogen dioxide (NO2) is a short-lived atmospheric pollutant that serves as an air quality indicator and is itself a health concern. The Airborne Compact Atmospheric Mapper (ACAM) was flown on board the NASA UC-12 aircraft during the Deriving Information on Surface Conditions from Column and Vertically Resolved Observations Relevant to Air Quality Maryland field campaign in July 2011. The instrument collected hyperspectral remote sensing measurements in the 304-910 nm range, allowing daytime observations of several tropospheric pollutants, including nitrogen dioxide (NO2), at an unprecedented spatial resolution of 1.5 × 1.1 sq. km. Retrievals of slant column abundance are based on the differential optical absorption spectroscopy method. For the air mass factor computations needed to convert these retrievals to vertical column abundance, we include high-resolution information for the surface reflectivity by using bidirectional reflectance distribution function data from the Moderate Resolution Imaging Spectroradiometer. We use high-resolution simulated vertical distributions of NO2 from the Community Multiscale Air Quality and Global Modeling Initiative models to account for the temporal variation in atmospheric NO2 to retrieve middle and lower tropospheric NO2 columns (NO2 below the aircraft). We compare NO2 derived from ACAM measurements with in situ observations from NASA's P-3B research aircraft, total column observations from the ground-based Pandora spectrometers, and tropospheric column observations from the space-based Ozone Monitoring Instrument. The high-resolution ACAM measurements not only give new insights into our understanding of atmospheric composition and chemistry through observation of subsampling variability in typical satellite and model resolutions, but they also provide opportunities for testing algorithm improvements for forthcoming geostationary air quality missions.

Lamsal, L. N.↗

NASA NTRS2012

An Overview of the Lightning - Atmospheric Chemistry Aspects of the Deep Convective Clouds and Chemistry (DC3) Experiment

Some of the major goals of the DC3 experiment are to determine the contribution of lightning to NO(x) in the anvils of observed thunderstorms, examine the relationship of lightning NO(x) production to flash rates and to lightning channel lengths, and estimate the relative production per flash for cloud-to-ground flashes and intracloud flashes. In addition, the effects of lightning NO(x) production on photochemistry downwind of thunderstorms is also being examined. The talk will survey the observation types that were conducted during DC3 relevant to these goals and provide an overview of the analysis and modeling techniques which are being used to achieve them. NO(x) was observed on three research aircraft during DC3 (the NCAR G-V, the NASA DC-8, and the DLR Falcon) in flights through storm anvils in three study regions (NE Colorado, Central Oklahoma to West Texas, and northern Alabama) where lightning mapping arrays (LMAs) and radar coverage were available. Initial comparisons of the aircraft NOx observations in storm anvils relative to flash rates have been conducted, which will be followed with calculations of the flux of NO(x) through the anvils, which when combined with observed flash rates can be used to estimate storm-average lightning NOx production per flash. The WRF-Chem model will be run for cloud-resolved simulations of selected observed storms during DC3. Detailed lightning information from the LMAs (flash rates and flash lengths as a function of time and vertical distributions of flash channel segments) will be input to the model along with assumptions concerning NO(x) production per CG flash and per IC flash. These assumptions will be tested through comparisons with the aircraft NOx data from anvil traverses. A specially designed retrieval method for lightning NO2 column amounts from the OMI instrument on NASA fs Aura satellite has been utilized to estimate NO2 over the region affected by selected DC3 storms. Combined with NO(x) to NO2 ratios from the aircraft data and WRF-Chem model and observed flash rates, average NO(x) production per flash can be estimated. Ozone production downwind of observed storms can be estimated from the WRF-Chem simulations and the specific downwind flights.

Pickering, K. E.↗

NASA NTRS2007

Simulations of Tropospheric NO2 by the Global Modeling Initiative (GMI) Model Utilizing Assimilated and Forecast Meteorological Fields: Comparison to Ozone Monitoring Instrument (OMI) Measurements

We present simulations of the tropospheric composition for the years 2004 and 2005, carried out by the GMI Combined Stratosphere-Troposphere (Combo) model, at a resolution of 2degx2.5deg. The model includes a new parameterization of lightning sources of NO(x) which is coupled to the cloud mass fluxes in the adopted meteorological fields. These simulations use two different sets of input meteorological fields: a)late-look assimilated fields from the Global Modeling and Assimilation Office (GMAO), GEOS-4 system and b) 12-hour forecast fields initialized with the assimilated data. Comparison of the forecast to the assimilated fields indicates that the forecast fields exhibit less vigorous convection, and yield tropical precipitation fields in better agreement with observations. Since these simulations include a complete representation of the stratosphere, they provide realistic stratosphere-tropospheric fluxes of O3 and NO(y). Furthermore, the stratospheric contribution to total columns of different troposheric species can be subtracted in a consistent fashion, and the lightning production of NO(y) will depend on the adopted meteorological field. We concentrate here on the simulated tropospheric columns of NO2, and compare them to observations by the OM1 instrument for the years 2004 and 2005. The comparison is used to address these questions: a) is there a significant difference in the agreement/disagreement between simulations for these two different meteorological fields, and if so, what causes these differences?; b) how do the simulations compare to OMI observations, and does this comparison indicate an improvement in simulations with the forecast fields? c) what are the implications of these simulations for our understanding of the NO2 emissions over continental polluted regions?

Rodriquez, J. M.↗

NASA NTRS2006

Exploration of OMI Products for Air Quality Applications Through Comparisons with Models and Observations

The Ozone Monitoring Instrument (OMI) on board NASA s Aura satellite was launched in July 2004, and is now providing daily global observations of total column ozone, NO2, and SO2, as well as aerosol information. Algorithms have also been developed to produce daily tropospheric ozone and NO2 products. The tropospheric ozone product reported here is a tropospheric residual computed through use of Aura Microwave Limb Sounder (MLS) ozone profile data to quantify stratospheric ozone. We are investigating the applicability of OMI products for use in air quality modeling, forecasting, and analysis. These investigations include comparison of the OMI tropospheric O3 and NO2 products with global and regional models and with lower tropospheric aircraft observations. Large-scale transport of pollution seen in the OM1 tropospheric O3 data is compared with output from NASA's Global Modeling Initiative global chemistry and transport model. On the regional scale we compare the OMI tropospheric O3 and NO2 with fields from the National Oceanic and Atmospheric Administration and Environmental Protection Agency (NOAA/EPA) operational Eta/CMAQ air quality forecasting model over the eastern United States. This 12-km horizontal resolution model output is roughly of equivalent resolution to the OMI pixel data. Correlation analysis between lower tropospheric aircraft O3 profile data taken by the University of Maryland over the Mid-Atlantic States and OMI tropospheric column mean volume mixing ratio for O3 will be presented. These aircraft data are representative of the lowest 3 kilometers of the atmosphere, the region in which much of the locally-generated and regionally-transported ozone exists.

Pickering, K. E.↗

NASA NTRS2002

An Intercomparison and Evaluation of Aircraft-Derived and Simulated CO from Seven Chemical Transport Models During the TRACE-P Experiment

Four global scale and three regional scale chemical transport models are intercompared and evaluated during NASA's TRACE-P experiment. Model simulated and measured CO are statistically analyzed along aircraft flight tracks. Results for the combination of eleven flights show an overall negative bias in simulated CO. Biases are most pronounced during large CO events. Statistical agreements vary greatly among the individual flights. Those flights with the greatest range of CO values tend to be the worst simulated. However, for each given flight, the models generally provide similar relative results. The models exhibit difficulties simulating intense CO plumes. CO error is found to be greatest in the lower troposphere. Convective mass flux is shown to be very important, particularly near emissions source regions. Occasionally meteorological lift associated with excessive model-calculated mass fluxes leads to an overestimation of mid- and upper- tropospheric mixing ratios. Planetary Boundary Layer (PBL) depth is found to play an important role in simulating intense CO plumes. PBL depth is shown to cap plumes, confining heavy pollution to the very lowest levels.

Kiley, C. M.↗

NASA NTRS1993

Effect of marine stratocumulus in TOMS ozone

The algorithm used to correct total O3 from the total ozone mapping spectrometer (TOMS) for cloud effects is based on the measured reflectivity, a climatological cloud top height, and an assumed tropospheric O3 column amount below clouds. In regions of persistent subtropical marine stratocumulus it is assumed that this introduces a positive error into total O3 because these clouds are lower than the assumed mean cloud height used in the algorithm. This appears to be confirmed by high correlation between Nimbus 7 TOMS total O3 and reflectivity data for typical regimes of persistent stratus, as identified by the international satellite cloud climatology project (ISCCP) observations. The TOMS total O3 overestimate has been computed using Nimbus 7/solar backscattered ultraviolet total O3 derived using temperature humidity infrared radiometer (THIR) data for years 1979-1984. A functional relationship between the THIR/non-THIR total O3 difference and reflectivity is used with TOMS reflectivity to modify Nimbus 7 TOMS O3 data for selected regions and periods. The correction diminishes or eliminates a number of apparent O3 maxima, with reductions of up to 20 Dobson units (DU) in total O3 on daily maps and approximately 5 DU on monthly mean O3 maps. Significant correlation between corrected TOMS O3 and reflectivity data remains because low-altitude O3 is retrieved more efficiently over a high-albedo surface. It is also possible that dynamical influences leading to stratocumulus formation bring O3-enriched air into the area. These results imply that although good arguments can be made for the use of TOMS total O3 as a proxy for tropospheric O3 in the tropics, caution must be exercised in the use of daily and even monthly O3 maps in the vicinity of clouds. Further research into the TOMS algorithm in cloudy regions is required to derive reliable estimates of tropospheric O3.

Thompson, A. M.↗

NASA NTRS1989

Cumulus cloud model estimates of trace gas transports

Draft structures in convective clouds are examined with reference to the results of the NASA Amazon Boundary Layer Experiments (ABLE IIa and IIb) and calculations based on a multidimensional time dependent dynamic and microphysical numerical cloud model. It is shown that some aspects of the draft structures can be calculated from measurements of the cloud environment. Estimated residence times in the lower regions of the cloud based on surface observations (divergence and vertical velocities) are within the same order of magnitude (about 20 min) as model trajectory estimates.

Garstang, Michael↗