Norman T. O'Neill

Spectral discrimination of coarse and fine mode optical depth

[1] The recognition that the aerosol particle size distribution (PSD) is effectively bimodal permits the extraction of the fine and coarse mode optical depths (tf and tc) from the spectral shape of the total aerosol optical depth (ta = tf + tc). This purely optical technique avoids intermediate computations of the PSD and yields a direct optical output that is commensurate in complexity with the spectral information content of ta. The separation into tf and tc is a robust process and yields aerosol optical statistics, which are more intrinsic than those, obtained from a generic analysis of ta. Partial (optical) validation is provided by (1) demonstrating the physical coherence of the simple model employed, (2) demonstrating that tc variation is coherent with photographic evidence of thin cloud events and that tf variation is coherent with photographic evidence of clear sky and haze events, and (3) showing that the retrieved values of tf and tc are wellcorrelated, if weakly biased, relative to formal inversions of combined solar extinction and sky radiance data. The spectral inversion technique permitted a closer scrutiny of a standard (temporally based) cloud-screening algorithm. Perturbations of monthly or longer-term statistics associated with passive or active shortcomings of operational cloud screening were inferred to be small to occasionally moderate over a sampling of cases. Diurnal illustrations were given where it was clear that such shortcomings can have a significant impact on the interpretation of specific events; (1) commission errors in tf due to the exclusion of excessively high-frequency fine mode events and (2) omission errors in tc due to the inclusion of insufficiently high-frequency thin homogeneous cloud events. INDEX TERMS: 0305 Atmospheric Composition and Structure: Aerosols and particles (0345, 4801); 0360 Atmospheric Composition and Structure: Transmission and scattering of radiation; 3360 Meteorology and Atmospheric Dynamics: Remote sensing; 4801 Oceanography: Biological and Chemical: Aerosols (0305); KEYWORDS: Sun photometry, aerosol, optical depth, fine mode, coarse mode, cloud screening

Climatological aspects of the optical properties of fine/coarse mode aerosol mixtures

[1] Aerosol mixtures composed of coarse mode desert dust combined with fine mode combustion generated aerosols (from fossil fuel and biomass burning sources) were investigated at three locations that are in and/or downwind of major global aerosol emission source regions. Multiyear monitoring data at Aerosol Robotic Network sites in Beijing (central eastern China), Kanpur (Indo-Gangetic Plain, northern India), and Ilorin (Nigeria, Sudanian zone of West Africa) were utilized to study the climatological characteristics of aerosol optical properties. Multiyear climatological averages of spectral single scattering albedo (SSA) versus fine mode fraction (FMF) of aerosol optical depth at 675 nm at all three sites exhibited relatively linear trends up to ~50% FMF. This suggests the possibility that external linear mixing of both fine and coarse mode components (weighted by FMF) dominates the SSA variation, where the SSA of each component remains relatively constant for this range of FMF only. However, it is likely that a combination of other factors is also involved in determining the dynamics of SSA as a function of FMF, such as fine mode particles adhering to coarse mode dust. The spectral variation of the climatological averaged aerosol absorption optical depth (AAOD) was nearly linear in logarithmic coordinates over the wavelength range of 440-870 nm for both the Kanpur and Ilorin sites. However, at two sites in China (Beijing and Xianghe), a distinct nonlinearity in spectral AAOD in logarithmic space was observed, suggesting the possibility of anomalously strong absorption in coarse mode aerosols increasing the 870 nm AAOD.

A generalized approach to the vicarious calibration of multiple Earth observation sensors using hyperspectral data

Abstract The paper describes a new methodology that uses spatially extensive hyperspectral imagery as reference data to carry out vicarious radiometric calibrations for multiple satellite sensors. The methodology has been validated using data from a campaign at the Railroad Valley playa test site in Nevada in June 1998. The proof of concept has been further tested based on data acquisition campaigns at the Newell County rangeland test site in Alberta in August and October 1998. The rangeland test site in the Newell County region of Alberta is tested for its suitability as a calibration test site for satellite sensor systems. All three campaigns included ground-based measurements, satellite imagery, and airborne hyperspectral data. The airborne hyperspectral sensor data were acquired using the Airborne Visible and Infrared Imaging Spectrometer (AVIRIS) at Railroad Valley and the Compact Airborne Spectrographic Imager (casi) in all three campaigns. This paper describes the formulation and implementation of the new methodology, and radiometric calibration monitoring results obtained for five different sensors: NOAA-14 AVHRR, OrbView-2 SeaWiFS, SPOT-4 VGT, SPOT-1/2 HRV, and Landsat-5 TM. The results indicate that the nominal on-orbit radiometric calibrations of all the satellite sensors fit within their predicted uncertainties. The combination of both lower-reflectance and higher-reflectance test sites is shown to improve the quality of the calibration monitoring results. In particular, the combined QUASAR monitoring results obtained from the three airborne data acquisition days at the two test sites, encompassing five satellite sensors and a total of 40 spectral band cases, yield a correlation between QUASAR-based and nominal TOA radiances characterized by y=1.026x−1.26, and r2=0.990. Temporal extensions of QUASAR data sets to calibrate satellite sensors imaging the test site one or more days away from the airborne data acquisition day yield mixed results.

Optical properties of boreal forest fire smoke derived from Sun photometry

[1] Aerosol optical properties derived from Sun photometry were investigated in terms of climatological trends at two Sun photometer sites significantly affected by western Canadian boreal forest fire smoke and in terms of a 2-week series of smoke events observed at stations near and distant from boreal forest fires. Aerosol optical depth (ta) statistics for Waskesiu, Saskatchewan, and Thompson, Manitoba, were analyzed for summer data acquired between 1994 and 1999. A significant correlation between the geometric mean and the forest fire frequency indices (hot spots) was found; on the average, 80% of summertime optical depth variation in western Canada can be linked to forest fire sources. The average geometric mean and geometric standard deviation at 500 nm was observed to be 0.074 and 1.7 for the clearest, relatively smoke-free summer and 0.23 and 3.0 for the summer most influenced by smoke. A systematic decrease of fine mode Angstrom exponent (af) was noted (daf /d log ta �� 0.6). This decrease roughly corresponds to an increase in the fine mode effective radius (reff) from 0.09 to 0.15 mm and an abundance (A) to size rate increase near 2.0 (d log A / d log reff). A 1998 series of forest fire events was tracked using TOMS, AVHRR, and GOES imagery, back trajectories, and data from six Sun photometer sites in Canada and eastern United States. The results showed rates of decrease of af with increasing ta which were similar to the climatological data. An analysis in terms of source to station distance showed a decrease in af and an increase in reff with increasing distance. This observation was coherent with previous observations on the particle growth effects of aging. INDEX TERMS: 0360 Atmospheric Composition and Structure: Transmission and scattering of radiation; 0305 Atmospheric Composition and Structure: Aerosols and particles (0345, 4801); 3360 Meteorology and Atmospheric Dynamics: Remote sensing; 4801 Oceanography: Biological and Chemical: Aerosols (0305); KEYWORDS: aerosols, forest fire smoke, Sun photometry, optics

Optical properties of aerosol mixtures derived from sun-sky radiometry during SAMUM-2

The SAMUM-2 experiment took place in the Cape Verde is lands in January–February 2008. The colocated ground-based and airborne instruments allow the study of desert dust optical and microphysical properties in a closure experiment. The Meteorological Institute of the University of Munich deployed one sun-sky photometer and two tropospheric lidar systems. A travelling AERONET-Cimel sun-sky radiometer was also deployed. During the measurement period the aerosol scenario over Cape Verde mostly consisted of a dust layer below 2 km and a smoke-dust layer above 2–4 km a.s.l. The Saharan dust arrived at the site from the NE, whereas the smoke originated in the African equatorial region. This paper describes the main results of the Sun photometer observations, supported by lidar information. An analysis of the variations in the aerosol optical depth (AOD) in the range 340–1550 nm, the Ångström exponent, volume size distributions and single scattering albedo is presented. The aerosol mixtures are analysed by means of the fine mode fraction of the AOD provided by the sun-sky inversion data and the Spectral Deconvolution Algorithm. The mean AOD (500 nm) was 0.31, with associated low ångström exponent of 0.46. Several types of events were detected within the data set, with prevalence of dust or mixtures as characterized by the Ångstr¨om exponents of extinction and absorption and the fine mode fraction. Aerosol properties derived from sunphotometry were compared to in situ measurements of size distribution, effective radius and single scattering albedo.

Comparison Of Radiative Transfer Models Used To Determine Atmospheric Optical Parameters From Space

An array of models and techniques exist for the calculation of the atmospheric backscattered radiance and ground reflected radiance received at satellite altitudes. In remote sensing applications, where one deals in mega-byte units of data, it is essential that these models be computationally fast while retaining a reasonable degree of accuracy. We have evaluated a number of such models (Lowtran 6, Turner, Discrete ordinates method, 5S) relative to an accurate multiple scattering, multi-layer (Dave) model in order to assess the performance of these models in an inversion scheme for aerosol optical depth. The Turner and single scatter Lowtran 6 models generally produced large errors in apparent reflectance. Overall, the Turner model was not significantly better than the Lowtran 6 model except at near nadir geometries and non zero albedos. The 5S model which is orders of magnitude more rapid than the DOM model was significantly more accurate than the L6 and Turner models. The accuracy of the inversion procedures for the extraction of aerosol optical depth from satellite apparent reflectance was then analyzed for the two most precise models (DOM and 5S). For typical measurement conditions, the 5S inversion errors were found to be of the order of .1 in a turbid atmosphere case (aerosol optical depth approximately .5). The DOM produced the most impressive results in terms of comparisons with the Dave computations. Its time of execution, however, is a serious constraint with respect to satellite remote sensing applications.

Multialtitude airborne observations of insolation effects of forest fire smoke aerosols at BOREAS: Estimates of aerosol optical parameters

Forest fire disturbance, as part of the natural cycle of the boreal ecosystem renewal, proved a significant factor in the acquisition scheduling of optical remote imagery at the northern study site of the Boreal Ecosystem-Atmosphere Study (BOREAS), conducted in northern/central Canada during the July/August months of 1994. One such episode, between July 28 and 31, was due entirely to smoke transported over the study site from nearby and distant downwind fires. Noon insolation was reduced from 800 W/m2 on July 28 to 680 W/m2 on July 31 and incident PAR radiation from 320 to 250 W/m2. During the July 31 smoke episode the compact airborne spectrographic imager (CASI) was flown at 150, 300, 900, 1500, and 3200 m agl over a forested site, while measuring the scene-reflected radiance as well as upwelling and downwelling irradiances in the spectral range 403 and 916 nm (2.5 nm resolution). These multialtitude observations of upwelling and downwelling irradiance and the hemispherical reflectance are used to estimate at two wavelengths, 550 and 672 nm, the vertical profiles of aerosol optical depth, attenuation coefficient, and single-scattering albedo representative of the smoke aerosols encountered at BOREAS. For smoke aerosols from distant fires (high altitude) the single-scattering albedo was 0.9 and the attenuation coefficient was 0.32 km−1 at 672 nm, whereas for smoke aerosols from nearby fires, values of 0.6 and 0.60 km−1 were found. This is qualitatively consistent with differences expected for distant primarily sulfate aerosols and higher soot aerosols for nearby flaming fires.

Validation of a DDV‐based aerosol optical depth retrieval algorithm using multialtitude spectral imagery

One of the classical weaknesses of remote sensing algorithms is their statistically limited validation data sets. Validation procedures are generally carried out over sparse ground-based data sets which are orders of magnitude smaller in number than the image products they are meant to validate and often of a physical scale that is inconsistent with the footprint scale of a single pixel. The multialtitude regression methodology seeks to address this problem by exploiting the flexibility and programmability of an airborne sensor whose potential for acquiring algorithm test data is much more commensurate with the validation needs of high altitude or satellite sensors. The multialtitude regression procedure was employed to validate a single-altitude aerosol optical depth (AOD) inversion algorithm which uses an atmospherically resistant vegetation index criterion to select dense dark vegetation (DDV) pixels in a boreal forest image acquired by the CASI (Compact Airborne Spectrographic Imager) imaging spectrometer. The multialtitude regression procedure permits the extraction of AOD images that are reasonably independent of the surface bidirectional reflectance factor (BRF) required as input to the DDV-based AOD inversion algorithm. This independence of surface BRF is a fundamental requirement for the validation of DDV-based algorithm since the basic weakness of this algorithm is its sensitivity to surface BRF variations. The results indicate that the multialtitude regression procedure is an effective tool for validating DDV inversion algorithms.

Measurements of CO, HCN, and C2H6 Total Columns in Smoke Plumes Transported from the 2010 Russian Boreal Forest Fires to the Canadian High Arctic

In August 2010, simultaneous enhancements of aerosol optical depth and total columns of carbon monoxide (CO), hydrogen cyanide (HCN), and ethane (C2H6) were observed at the Polar Environment Atmospheric Research Laboratory (PEARL, 80.05°N, −86.42°W, 0.61 km above sea level, Eureka, Nunavut, Canada). Moderate Resolution Imaging Spectroradiometer (MODIS) hot spots, Ozone Monitoring Instrument (OMI) aerosol index maps, and Hybrid Single Particle Lagrangian Integrated Trajectory (HYSPLIT) back-trajectories were used to attribute these enhancements to an intense boreal fire event occurring in Russia. A ground-based Fourier Transform InfraRed (FTIR) spectrometer at PEARL provided vertically integrated measurements of trace gases transported in smoke plumes. We derived HCN and C2H6 equivalent emission ratios with respect to CO of 0.0054 ± 0.0022 and 0.0108 ± 0.0036, respectively, and converted them into equivalent emission factors of 0.66 ± 0.27 g kg−1 and 1.47 ± 0.50 g kg−1 (in grams of gas per kilogram of dry biomass burnt, with one-sigma uncertainties). These emission factors add new observations to the relatively sparse datasets available and can be used to improve the simulation of biomass burning fire emissions in chemical transport models. These emission factors for the boreal forest are in agreement with the mean values recently reported in a compilation study.

Thermal infrared remote sensing of soils: Evolution, trends and perspectives

Abstract This overview of thermal infrared remote sensing applied to soils presents the soil thermal behavior and parameters such as thermal inertia and their relation to soil moisture. It addresses the effect of emissivities and atmosphere on soil surface temperature evaluation and examines the potential of combining thermal data with information from other spectral ranges such as visible and microwave data.