From photon paths to pollution plumes: better radiative transfer calculations to monitor NOx emissions with OMI and TROPOMI

Nitrogen oxides (NOx = NO + NO2) play an important role in atmospheric chemistry, therefore affecting air quality and Earth's radiative forcing, which impact public health, ecosystems and climate. Remote sensing from satellites in the ultraviolet and visible (UV-Vis) spectral range results in measurements of tropospheric NO2 column densities with high spatial and temporal resolution that allow, among many applications, to monitor NO2 concentrations and to estimate NOx emissions. NO2 satellite retrievals have improved extensively in the last decade, together with the increased need of having traceable characterization of the uncertainties associated with the NO2 satellite measurements. The spatial resolution of the satellite instruments is improving such that the observed NO2 pollution can now be traced back to emissions from individual cities, power plants, and transportation sectors. However, the uncertainty of satellite NO2 retrievals is still considerable and mainly related to the adequacy of the assumptions made on the state of the atmosphere. In this thesis we have improved the critical assumptions and our understanding in the radiative transfer modelling for NO2 satellite measurements, and we use the new TROPOMI NO2 measurements to quantify daily NOx emissions from a single urban hot spot. The work presented in this thesis contributes to the satellite remote sensing community (1) because of the improvement of the satellite retrieval and the knowledge of its main uncertainty sources (Chapter 2, 3 and 4), and (2) because of the application of TROPOMI NO2 measurements for the first time to infer daily NOx emissions at urban scales (Chapter 5). </p

Remote sensing of surface albedo and cloud properties in the Arctic from AVHRR measurements

Thesis (Ph.D.) University of Alaska Fairbanks, 1996Based on a comprehensive radiative transfer model, algorithms suitable for arctic conditions are developed to retrieve broadband surface albedo and water cloud properties from National Oceanic and Atmospheric Administration (NOAA) Advanced Very High Resolution Radiometer (AVHRR) narrowband measurements. Reflectance anisotropy of snow surfaces is first simulated by an discrete ordinates radiative transfer formulation, and is then included in the comprehensive model for the retrieval. Ground-based irradiance measurements made by NOAA Climate Monitoring and Diagnostics Laboratory (CMDL) in Barrow, Alaska are compared with retrieved albedo and downwelling irradiances computed from retrieved cloud optical depth and effective radius. Good agreement is found between satellite estimates and ground-based measurements, which indicate that the retrieval algorithms proposed in this thesis are suitable for arctic conditions. It is found that the effects of snow bidirectional reflectance on the retrieval of the broadband albedo are significant, and that the Lambertian approximation could lead to a 30% underestimate of the surface albedo. It is also found that cloud effective radius in the Arctic is generally smaller as compared with mid- and low-latitudes

Comprehensive tool for calculation of radiative fluxes: illustration of shortwave aerosol radiative effect sensitivities to the details in aerosol and underlying surface characteristics

The evaluation of aerosol radiative effect on broadband hemispherical solar flux is often performed using simplified spectral and directional scattering characteristics of atmospheric aerosol and underlying surface reflectance. In this study we present a rigorous yet fast computational tool that accurately accounts for detailed variability of both spectral and angular scattering properties of aerosol and surface reflectance in calculation of direct aerosol radiative effect. The tool is developed as part of the GRASP (Generalized Retrieval of Aerosol and Surface Properties) project. We use the tool to evaluate instantaneous and daily average radiative efficiencies (radiative effect per unit aerosol optical thickness) of several key atmospheric aerosol models over different surface types. We then examine the differences due to neglect of surface reflectance anisotropy, nonsphericity of aerosol particle shape and accounting only for aerosol angular scattering asymmetry instead of using full phase function. For example, it is shown that neglecting aerosol particle nonsphericity causes mainly overestimation of the aerosol cooling effect and that magnitude of this overestimate changes significantly as a function of solar zenith angle (SZA) if the asymmetry parameter is used instead of detailed phase function. It was also found that the nonspherical–spherical differences in the calculated aerosol radiative effect are not modified significantly if detailed BRDF (bidirectional reflectance distribution function) is used instead of Lambertian approximation of surface reflectance. Additionally, calculations show that usage of only angular scattering asymmetry, even for the case of spherical aerosols, modifies the dependence of instantaneous aerosol radiative effect on SZA. This effect can be canceled for daily average values, but only if sun reaches the zenith; otherwise a systematic bias remains. Since the daily average radiative effect is obtained by integration over a range of SZAs, the errors vary with latitude and season. In summary, the present analysis showed that use of simplified assumptions causes systematic biases, rather than random uncertainties, in calculation of both instantaneous and daily average aerosol radiative effect. Finally, we illustrate application of the rigorous aerosol radiative effect calculations performed as part of GRASP aerosol retrieval from real POLDER/PARASOL satellite observations

Remote sensing of cloud properties using ground-based measurements of zenith radiance

We have conducted the first extensive field test of two new methods to retrieve optical properties for overhead clouds that range from patchy to overcast. The methods use measurements of zenith radiance at 673 and 870 nm wavelengths and require the presence of green vegetation in the surrounding area. The test was conducted at the Atmospheric Radiation Measurement Program Oklahoma site during September–November 2004. These methods work because at 673 nm (red) and 870 nm (near infrared (NIR)), clouds have nearly identical optical properties, while vegetated surfaces reflect quite differently. The first method, dubbed REDvsNIR, retrieves not only cloud optical depth τ but also radiative cloud fraction. Because of the 1-s time resolution of our radiance measurements, we are able for the first time to capture changes in cloud optical properties at the natural timescale of cloud evolution. We compared values of τ retrieved by REDvsNIR to those retrieved from downward shortwave fluxes and from microwave brightness temperatures. The flux method generally underestimates τ relative to the REDvsNIR method. Even for overcast but inhomogeneous clouds, differences between REDvsNIR and the flux method can be as large as 50%. In addition, REDvsNIR agreed to better than 15% with the microwave method for both overcast and broken clouds. The second method, dubbed COUPLED, retrieves τ by combining zenith radiances with fluxes. While extra information from fluxes was expected to improve retrievals, this is not always the case. In general, however, the COUPLED and REDvsNIR methods retrieve τ to within 15% of each other

Influence of aerosols, clouds, and sunglint on polarization spectra of Earthshine

Ground-based observations of the Earthshine, i.e., the light scattered by Earth to the Moon, and then reflected back to Earth, simulate space observations of our planet and represent a powerful benchmark for the studies of Earth-like planets. Earthshine spectra are strongly linearly polarized, owing to scattering by molecules and small particles in the atmosphere of the Earth and surface reflection, and may allow us to measure global atmospheric and surface properties of planet Earth. Aims. We aim to interpret already published spectropolarimetric observations of the Earthshine by comparing them with new radiative transfer model simulations including a fully realistic three-dimensional (3D) surface-atmosphere model for planet Earth. We used the highly advanced Monte Carlo radiative transfer model MYSTIC to simulate polarized radiative transfer in the atmosphere of the Earth without approximations regarding the geometry, taking into account the polarization from surface reflection and multiple scattering by molecules, aerosol particles, cloud droplets, and ice crystals. We have shown that Earth spectropolarimetry is highly sensitive to all these input parameters, and we have presented simulations of a fully realistic Earth atmosphere-surface model including 3D cloud fields and two-dimensional (2D) surface property maps. Our modeling results show that scattering in high ice water clouds and reflection from the ocean surface are crucial to explain the continuum polarization at longer wavelengths as has been reported in Earthshine observations taken at the Very Large Telescope in 2011 (3.8 % and 6.6 % at 800 nm, depending on which part of Earth was visible from the Moon at the time of the observations). We found that the relatively high degree of polarization of 6.6 % can be attributed to light reflected by the ocean surface in the sunglint region

Retrieval of aerosol optical thickness over snow and ice surfaces in the Arctic using Advanced Along Track Scanning Radiometer

Aerosols in the Arctic cause radiative forcing and a variety of climatic feedbacks, which affect climate of both local and global scales. In order to assess the state of the Arctic climate, information on the aerosol type and amount is needed. Harsh conditions and remoteness of the Arctic region result in very few ground based measurements of aerosol optical thickness. Remote sensing has the potential to provide the necessary temporal and spatial coverage. A non-trivial task of aerosol retrieval over a very bright surface is being solved within the thesis; the developed retrieval consists of cloud screening over snow and two types of aerosol retrieval over snow - in the visible and infrared spectral regions. A number of validation and case studies has been performed to assess the quality of the retrieval. The developed algorithm applies to the data of Advanced Along Track Scanning Radiometer and produces maps of aerosol optical thickness over snow and ice

Remote Sensing of Tropical Ecosystems: Atmospheric Correction and Cloud Masking Matter

Tropical rainforests are significant contributors to the global cycles of energy, water and carbon. As a result, monitoring of the vegetation status over regions such as Amazonia has been a long standing interest of Earth scientists trying to determine the effect of climate change and anthropogenic disturbance on the tropical ecosystems and its feedback on the Earth's climate. Satellite-based remote sensing is the only practical approach for observing the vegetation dynamics of regions like the Amazon over useful spatial and temporal scales, but recent years have seen much controversy over satellite-derived vegetation states in Amaznia, with studies predicting opposite feedbacks depending on data processing technique and interpretation. Recent results suggest that some of this uncertainty could stem from a lack of quality in atmospheric correction and cloud screening. In this paper, we assess these uncertainties by comparing the current standard surface reflectance products (MYD09, MYD09GA) and derived composites (MYD09A1, MCD43A4 and MYD13A2 - Vegetation Index) from the Moderate Resolution Imaging Spectroradiometer (MODIS) onboard the Aqua satellite to results obtained from the Multi-Angle Implementation of Atmospheric Correction (MAIAC) algorithm. MAIAC uses a new cloud screening technique, and novel aerosol retrieval and atmospheric correction procedures which are based on time-series and spatial analyses. Our results show considerable improvements of MAIAC processed surface reflectance compared to MYD09/MYD13 with noise levels reduced by a factor of up to 10. Uncertainties in the current MODIS surface reflectance product were mainly due to residual cloud and aerosol contamination which affected the Normalized Difference Vegetation Index (NDVI): During the wet season, with cloud cover ranging between 90 percent and 99 percent, conventionally processed NDVI was significantly depressed due to undetected clouds. A smaller reduction in NDVI due to increased aerosol levels was observed during the dry season, with an inverse dependence of NDVI on aerosol optical thickness (AOT). NDVI observations processed with MAIAC showed highly reproducible and stable inter-annual patterns with little or no dependence on cloud cover, and no significant dependence on AOT (p less than 0.05). In addition to a better detection of cloudy pixels, MAIAC obtained about 20-80 percent more cloud free pixels, depending on season, a considerable amount for land analysis given the very high cloud cover (75-99 percent) observed at any given time in the area. We conclude that a new generation of atmospheric correction algorithms, such as MAIAC, can help to dramatically improve vegetation estimates over tropical rain forest, ultimately leading to reduced uncertainties in satellite-derived vegetation products globally

Biomass Burning Aerosol Absorption Measurements with MODIS Using the Critical Reflectance Method

This research uses the critical reflectance technique, a space-based remote sensing method, to measure the spatial distribution of aerosol absorption properties over land. Choosing two regions dominated by biomass burning aerosols, a series of sensitivity studies were undertaken to analyze the potential limitations of this method for the type of aerosol to be encountered in the selected study areas, and to show that the retrieved results are relatively insensitive to uncertainties in the assumptions used in the retrieval of smoke aerosol. The critical reflectance technique is then applied to Moderate Resolution Imaging Spectrometer (MODIS) data to retrieve the spectral aerosol single scattering albedo (SSA) in South African and South American 35 biomass burning events. The retrieved results were validated with collocated Aerosol Robotic Network (AERONET) retrievals. One standard deviation of mean MODIS retrievals match AERONET products to within 0.03, the magnitude of the AERONET uncertainty. The overlap of the two retrievals increases to 88%, allowing for measurement variance in the MODIS retrievals as well. The ensemble average of MODIS-derived SSA for the Amazon forest station is 0.92 at 670 nm, and 0.84-0.89 for the southern African savanna stations. The critical reflectance technique allows evaluation of the spatial variability of SSA, and shows that SSA in South America exhibits higher spatial variation than in South Africa. The accuracy of the retrieved aerosol SSA from MODIS data indicates that this product can help to better understand 44 how aerosols affect the regional and global climate