ALBERT

Description: In this paper, the task of parsing and matching inconsistent, poorly formed text data through the use of parser combinators and fuzzy matching is discussed. An object-oriented implementation of the parser combinator technique is used to allow for a relatively simple interface for adapting base parsers. For matching tasks, a fuzzy matching algorithm with Levenshtein distance calculations is implemented to match string pair, which are otherwise difficult to match due to the aforementioned irregularities and errors in one or both pair members. Used in concert, the two techniques allow parsing and matching operations to be performed which had previously only been done manually.

Description: LASE (Lidar Atmospheric Sensing Experiment) on-board the NASA DC-8 measured high resolution profiles of water vapor and aerosols, and cloud distributions in 14 flights over the eastern North Atlantic during the NAMMA (NASA African Monsoon Multidisciplinary Analyses) field experiment. These measurements were used to study African easterly waves (AEWs), tropical cyclones (TCs), and the Saharan Air Layer(s) (SAL). Interactions between the SAL and tropical air were observed during the early stages of the TC development. These LASE measurements represent the first simultaneous water vapor and aerosol lidar measurements to study the SAL and its impact on AEWs and TCs. Examples of profile measurements of aerosol scattering ratios, aerosol extinction coefficients, aerosol optical thickness, water vapor mixing ratios, RH, and temperature are presented to illustrate their characteristics in SAL, convection, and clear air regions. LASE data suggest that the SAL suppresses low-altitude convection at the convection-SAL interface region. Mid-level convection associated with the AEW and transport are likely responsible for high water vapor content observed in the southern regions of the SAL on August 20, 2008. This interaction is responsible for the transfer of about 7 x 10(exp 15) J latent heat energy within a day to the SAL. Measurements of lidar extinction-to-backscatter ratios in the range 36+/-5 to 45+/-5 are within the range of measurements from other lidar measurements of dust. LASE aerosol extinction and water vapor profiles are validated by comparison with onboard in situ aerosol measurements and GPS dropsonde water vapor soundings, respectively.

Description: We determine the extinction-to-backscatter (Sa) ratios of dust using (1) airborne in-situ measurements of microphysical properties, (2) modeling studies, and (3) the Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) observations recorded during the NASA African Monsoon Multidisciplinary Analyses (NAMMA) field experiment conducted from Sal, Cape Verde during Aug-Sept 2006. Using CALIPSO measurements of the attenuated backscatter of lofted Saharan dust layers, we apply the transmittance technique to estimate dust Sa ratios at 532 nm and a 2-color method to determine the corresponding 1064 nm Sa. This method yielded dust Sa ratios of 39.8 plus or minus 1.4 sr and 51.8 plus or minus 3.6 sr at 532 nm and 1064 nm, respectively. Secondly, Sa at both wavelengths is independently calculated using size distributions measured aboard the NASA DC-8 and estimates of Saharan dust complex refractive indices applied in a T-Matrix scheme. We found Sa ratios of 39.1 plus or minus 3.5 sr and 50.0 plus or minus 4 sr at 532 nm and 1064 nm, respectively, using the T-Matrix calculations applied to measured size spectra. Finally, in situ measurements of the total scattering (550 nm) and absorption coefficients (532 nm) are used to generate an extinction profile that is used to constrain the CALIPSO 532 nm extinction profile and thus generate a stratified 532 nm Sa. This method yielded an Sa ratio at 532 nm of 35.7 sr in the dust layer and 25 sr in the marine boundary layer consistent with a predominantly seasalt aerosol near the ocean surface. Combinatorial simulations using noisy size spectra and refractive indices were used to estimate the mean and uncertainty (one standard deviation) of these Sa ratios. These simulations produced a mean (plus or minus uncertainty) of 39.4 (plus or minus 5.9) sr and 56.5 (plus or minus 16.5) sr at 532 nm and 1064 nm, respectively, corresponding to percent uncertainties of 15% and 29%. These results will provide a measurements-based estimate of the dust Sa for use in backscatter lidar inversion algorithms such as CALIOP.

Description: As part of the NASA's INTEX-B mission, the NASA DC-8 and NSF C-130 conducted three wing-tip to wing-tip comparison flights. The intercomparison flights sampled a variety of atmospheric conditions (polluted urban, non-polluted, marine boundary layer, clean and polluted free troposphere). These comparisons form a basis to establish data consistency, but also should also be viewed as a continuation of efforts aiming to better understand and reduce measurement differences as identified in earlier field intercomparison exercises. This paper provides a comprehensive overview of 140 intercomparisons of data collected as well as a record of the measurement consistency demonstrated during INTEX-B. It is the primary goal to provide necessary information for the future research to determine if the observations from different INTEX-B platforms/instrument are consistent within the PI reported uncertainties and used in integrated analysis. This paper may also contribute to the formulation strategy for future instrument developments. For interpretation and most effective use of these results, the reader is strongly urged to consult with the instrument principle investigator.

Description: To investigate the ability of column (or partial column) information to represent surface air quality, results of linear regression analyses between surface mixing ratio data and column abundances for O3 and NO2 are presented for the July 2011 Maryland deployment of the DISCOVER-AQ mission. Data collected by the P-3B aircraft, ground-based Pandora spectrometers, Aura/OMI satellite instrument, and simulations for July 2011 from the CMAQ air quality model during this deployment provide a large and varied data set, allowing this problem to be approached from multiple perspectives. O3 columns typically exhibited a statistically significant and high degree of correlation with surface data (R(sup 2) 〉 0.64) in the P- 3B data set, a moderate degree of correlation (0.16 〈 R(sup 2) 〈 0.64) in the CMAQ data set, and a low degree of correlation (R(sup 2) 〈 0.16) in the Pandora and OMI data sets. NO2 columns typically exhibited a low to moderate degree of correlation with surface data in each data set. The results of linear regression analyses for O3 exhibited smaller errors relative to the observations than NO2 regressions. These results suggest that O3 partial column observations from future satellite instruments with sufficient sensitivity to the lower troposphere can be meaningful for surface air quality analysis.

Description: The first field campaign of DISCOVER-AQ (Deriving Information on Surface conditions from COlumn and VERtically resolved observations relevant to Air Quality) took place in July 2011 over Baltimore-Washington Corridor (BWC). A suite of airborne remote sensing and in-situ sensors was deployed along with ground networks for mapping vertical and horizontal distribution of aerosols. Previous researches were based on a single lidar station because of the lack of regional coverage. This study uses the unique airborne HSRL (High Spectral Resolution Lidar) data to baseline PM2.5 (particulate matter of aerodynamic diameter less than 2.5 m) estimates and applies to regional air quality with satellite AOD (Aerosol Optical Depth) retrievals over BWC (6500 sq. km). The linear approximation takes into account aerosols aloft above AML (Aerosol Mixing Layer) by normalizing AOD with haze layer height (i.e., AOD/HLH). The estimated PM2.5 mass concentrations by HSRL AOD/HLH are shown within 2 RMSE (Root Mean Square Error 9.6 g/cu. m) with correlation 0.88 with the observed over BWC. Similar statistics are shown when applying HLH data from a single location over the distance of 100 km. In other words, a single lidar is feasible to cover the range of 100 km with expected uncertainties. The employment of MPLNET-AERONET (MicroPulse Lidar NETwork - AErosol RObotic NETwork) measurements at NASA GSFC produces similar statistics of PM2.5 estimates as those derived by HSRL. The synergy of active and passive remote sensing aerosol measurements provides the foundation for satellite application of air quality on a daily basis. For the optimal range of 10 km, the MODIS-estimated PM2.5 values are found satisfactory at 27 (out of 36) sunphotometer locations with mean RMSE of 1.6-3.3 g/cu. m relative to PM2.5 estimated by sunphotometers. The remaining 6 of 8 marginal sites are found in the coastal zone, for which associated large RMSE values 4.5-7.8 g/cu. m are most likely due to overestimated AOD because of water-contaminated pixels.