Improved Algorithm for MODIS Satellite Retrievals of Aerosol Optical Depths Over Western North America

Quantitative evaluation of chemical transport models (CTMs) with aerosol optical depth (AOD) products retrieved from satellite backscattered reflectances can be compromised by inconsistent assumptions of aerosol optical properties and errors in surface reflectance estimates. We present an improved AOD retrieval algorithm for the MODIS satellite instrument using locally derived surface reflectances and CTM aerosol optical properties for the 0.47, 0.65, and 2.13 μm MODIS channels. Assuming negligible atmospheric reflectance at 2.13 μm in cloud-free conditions, we derive 0.65/2.13 surface reflectance ratios at 1° × 1.25° horizontal resolution for the continental United States in summer 2004 from the subset of top-of-atmosphere (TOA) reflectance data with minimal aerosol reflectance. We obtain a mean ratio of 0.57 ± 0.10 for the continental United States, with high values over arid regions and low values over the Midwest prairies. The higher surface reflectance ratios explain the high AOD bias over arid regions found in previous MODIS retrievals. We calculate TOA reflectances for each MODIS scene using local aerosol optical properties from the GEOS-Chem CTM, and fit these reflectances to the observed MODIS TOA reflectances for a best estimate of AODs for that scene. Comparison with coincident ground-based (AERONET) AOD observations at 16 sites in the western and central United States in summer 2004 shows poor correlation in the daily data but the correlation improves as averaging time increases. Averaging over the available coincident observations (n = 11–44 days) results in strong correlations (R0.47μm = 0.90, R0.65μm = 0.67) and a 19% low bias, representing considerable improvement over the operational MODIS AOD products in this region.Earth and Planetary SciencesEngineering and Applied Science

New-generation NASA Aura Ozone Monitoring Instrument (OMI) volcanic SO2 dataset: Algorithm description, initial results, and continuation with the Suomi-NPP Ozone Mapping and Profiler Suite (OMPS)

Since the fall of 2004, the Ozone Monitoring Instrument (OMI) has been providing global monitoring of volcanic SO2 emissions, helping to understand their climate impacts and to mitigate aviation hazards. Here we introduce a new-generation OMI volcanic SO2 dataset based on a principal component analysis (PCA) retrieval technique. To reduce retrieval noise and artifacts as seen in the current operational linear fit (LF) algorithm, the new algorithm, OMSO2VOLCANO, uses characteristic features extracted directly from OMI radiances in the spectral fitting, thereby helping to minimize interferences from various geophysical processes (e.g., O3 absorption) and measurement details (e.g., wavelength shift). To solve the problem of low bias for large SO2 total columns in the LF product, the OMSO2VOLCANO algorithm employs a table lookup approach to estimate SO2 Jacobians (i.e., the instrument sensitivity to a perturbation in the SO2 column amount) and iteratively adjusts the spectral fitting window to exclude shorter wavelengths where the SO2 absorption signals are saturated. To first order, the effects of clouds and aerosols are accounted for using a simple Lambertian equivalent reflectivity approach. As with the LF algorithm, OMSO2VOLCANO provides total column retrievals based on a set of predefined SO2 profiles from the lower troposphere to the lower stratosphere, including a new profile peaked at 13 km for plumes in the upper troposphere. Examples given in this study indicate that the new dataset shows significant improvement over the LF product, with at least 50% reduction in retrieval noise over the remote Pacific. For large eruptions such as Kasatochi in 2008 (∼1700 kt total SO2/ and Sierra Negra in 2005 (\u3e 1100DU maximum SO2/, OMSO2VOLCANO generally agrees well with other algorithms that also utilize the full spectral content of satellite measurements, while the LF algorithm tends to underestimate SO2. We also demonstrate that, despite the coarser spatial and spectral resolution of the Suomi National Polar-orbiting Partnership (Suomi-NPP) Ozone Mapping and Profiler Suite (OMPS) instrument, application of the new PCA algorithm to OMPS data produces highly consistent retrievals between OMI and OMPS. The new PCA algorithm is therefore capable of continuing the volcanic SO2 data record well into the future using current and future hyperspectral UV satellite instruments

Version 2 Ozone Monitoring Instrument SO2 product (OMSO2 V2): New anthropogenic SO2 vertical column density dataset

The Ozone Monitoring Instrument (OMI) has been providing global observations of SO2 pollution since 2004. Here we introduce the new anthropogenic SO2 vertical column density (VCD) dataset in the version 2 OMI SO2 product (OMSO2 V2). As with the previous version (OMSO2 V1.3), the new dataset is generated with an algorithm based on principal component analysis of OMI radiances but features several updates. The most important among those is the use of expanded lookup tables and model a priori profiles to estimate SO2 Jacobians for individual OMI pixels, in order to better characterize pixel-to-pixel variations in SO2 sensitivity including over snow and ice. Additionally, new data screening and spectral fitting schemes have been implemented to improve the quality of the spectral fit. As compared with the planetary boundary layer SO2 dataset in OMSO2 V1.3, the new dataset has substantially better data quality, especially over areas that are relatively clean or affected by the South Atlantic Anomaly. The updated retrievals over snow/ice yield more realistic seasonal changes in SO2 at high latitudes and offer enhanced sensitivity to sources during wintertime. An error analysis has been conducted to assess uncertainties in SO2 VCDs from both the spectral fit and Jacobian calculations. The uncertainties from spectral fitting are reflected in SO2 slant column densities (SCDs) and largely depend on the signal-to-noise ratio of the measured radiances, as implied by the generally smaller SCD uncertainties over clouds or for smaller solar zenith angles. The SCD uncertainties for individual pixels are estimated to be 0.15-0.3DU (Dobson units) between 40 S and 40 N and to be 0.2-0.5DU at higher latitudes. The uncertainties from the Jacobians are approximately 50 %-100% over polluted areas and are primarily attributed to errors in SO2 a priori profiles and cloud pressures, as well as the lack of explicit treatment for aerosols. Finally, the daily mean and median SCDs over the presumably SO2-free equatorial east Pacific have increased by only 0.0035DU and 0.003DU respectively over the entire 15-year OMI record, while the standard deviation of SCDs has grown by only 0.02DU or 10%. Such remarkable long-term stability makes the new dataset particularly suitable for detecting regional changes in SO2 pollution

First Directly Retrieved Global Distribution of Tropospheric Column Ozone from GOME: Comparison with the GEOS-CHEM Model

We present the first directly retrieved global distribution of tropospheric column ozone from Global Ozone Monitoring Experiment (GOME) ultraviolet measurements during December 1996 to November 1997. The retrievals clearly show signals due to convection, biomass burning, stratospheric influence, pollution, and transport. They are capable of capturing the spatiotemporal evolution of tropospheric column ozone in response to regional or short time-scale events such as the 1997–1998 El Niño event and a 10–20 DU change within a few days. The global distribution of tropospheric column ozone displays the well-known wave-1 pattern in the tropics, nearly zonal bands of enhanced tropospheric column ozone of 36–48 DU at 20°S–30°S during the austral spring and at 25°N–45°N during the boreal spring and summer, low tropospheric column ozone of 33 DU at some northern high-latitudes during the spring. Simulation from a chemical transport model corroborates most of the above structures, with small biases of <±5 DU and consistent seasonal cycles in most regions, especially in the southern hemisphere. However, significant positive biases of 5–20 DU occur in some northern tropical and subtropical regions such as the Middle East during summer. Comparison of GOME with monthly-averaged Measurement of Ozone and Water Vapor by Airbus in-service Aircraft (MOZAIC) tropospheric column ozone for these regions usually shows good consistency within 1σ standard deviations and retrieval uncertainties. Some biases can be accounted for by inadequate sensitivity to lower tropospheric ozone, the different spatiotemporal sampling and the spatiotemporal variations in tropospheric column ozone.Earth and Planetary SciencesEngineering and Applied Science