Download or read book Verification of Aerosol Optical Depth Retrievals from Cloud Shadows Using Satellite Imagery written by and published by . This book was released on 2008 with total page 69 pages. Available in PDF, EPUB and Kindle. Book excerpt: A technique for deriving aerosol optical depths by measuring the radiance inside and outside of shaded regions is expanded to include shadows from clouds. Previous research focused on utilizing QuickBird satellite imagery. The 2.4 meter resolution of QuickBird allowed for sampling to focus on building-generated shadows. Research was done on several different surface types, including dirt, grass, sand, and pavement. The research presented in this thesis focuses on the challenges presented by attempting this technique with three other types of imagery--Moderate Resolution Imaging Spectrometer (MODIS), IKONOS, and Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER). The lower resolution of MODIS and ASTER does not lend itself to focusing on building shadows, but rather cloud shadows. Results from sampling cloud-generated shadows show this method has promise, much like previous studies, and opens up aerosol optical depth determination using this technique to a wide variety of imagery as well as additional sensor platforms.

Download or read book Verification of Aerosol Optical Depth Retrievals Using Cloud Shadows Retrieved from Satellite Imagery written by and published by . This book was released on 2008 with total page 86 pages. Available in PDF, EPUB and Kindle. Book excerpt: A technique for deriving aerosol optical depths by measuring the radiance inside and outside of shaded regions is expanded to include shadows from clouds. Previous research focused on utilizing QuickBird satellite imagery. The 2.4 meter resolution of QuickBird allowed for sampling to focus on building-generated shadows. Research was done on several different surface types, including dirt, grass, sand, and pavement. The research presented in this thesis focuses on the challenges presented by attempting this technique with three other types of imagery Moderate Resolution Imaging Spectrometer (MODIS), IKONOS, and Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER). The lower resolution of MODIS and ASTER does not lend itself to focusing on building shadows, but rather cloud shadows. Results from sampling cloud-generated shadows show this method has promise, much like previous studies and opens up aerosol optical depth determination using this technique to a wide variety of imagery as well as additional sensor platforms.

Download or read book 25 jaar Norbertus written by and published by . This book was released on with total page 18 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Automating the Shadow Method for Aerosol Optical Depth Retrieval written by and published by . This book was released on 2007 with total page 43 pages. Available in PDF, EPUB and Kindle. Book excerpt: A new method for remote sensing retrieval of Aerosol Optical Depth was proposed and investigated by Vincent (2006). This shadow-based method uses the radiance difference between shadow and non-shadow regions in QuickBird high resolution commercial satellite imagery to estimate Aerosol Optical Depth. Though the process is initially time-consuming, requiring a high level of user knowledge to accomplish the procedure, great potential exists for further development into a stand-alone operational method for overland retrievals at any location and time. It is the automation of this process in order to make it more operational in nature that is the purpose of this investigation. Knowledge is gained in the realm of predicting shadow location for future times. Specific process automation is applied through computer programming to decrease the computational complexity of the method. Also the physical variations of shadow regions are investigated in terms of their brightness change across various spatial profiles. This study of shadow region variation is termed shadow morphology and seeks to provide a user with optimum radiance sampling regions within an observed shadow region. Through the integration of these automation techniques, a more unified and operationally focused iteration of the shadow method is derived.

Download or read book A Fully Automated Method of Locating Building Shadows for Aerosol Optical Depth Calculations in High resolution Satellite Imagery written by Brian L. Belson and published by . This book was released on 2010 with total page 119 pages. Available in PDF, EPUB and Kindle. Book excerpt: Vincent (2006) developed a technique for remotely measuring Aerosol Optical Depth (AOD) using commercial high-resolution satellite imagery. This technique measured the radiance difference between a building shadow and an adjacent sunlit region with the same surface reflectance to calculate Total Optical Depth (TOD). AOD is then determined by subtracting Rayleigh scattering from TOD. The procedure for making this calculation was time consuming, particularly locating suitable shadows within the region of interest. This paper outlines a fully automated method of performing the AOD calculation and examining shadow properties. The automated method relies on high-resolution Digital Surface Model (DSM) data collected using a Light Detection and Ranging (LIDAR) sensor coupled with sun and satellite geometry to identify shadow regions. Configuration settings allowed for specific regions in the shadow and sunlit area to be selected before determining their respective radiances. Finally, a technique for aligning the satellite and DSM pixels was developed to correct for small differences between the datasets. Results from the automated method were compared with AERONET data for validation. The automated method using WorldView-1 and QuickBird imagery worked best at Solar Village, Saudi Arabia and an area northeast of Washington, D.C., which included the Goddard Space Flight Center. Testing of IKONOS multispectral imagery suggested the resolution is inadequate in urban settings. Testing in areas that included downtown regions in Houston, TX and Baltimore, MD identified weaknesses in the alignment algorithm.

Download or read book Investigation of Panchromatic Satellite Imagery Sensor Low Bias in Shadow Method Aerosol Optical Depth Retrieval written by Brian J. Rivenbark and published by . This book was released on 2009 with total page 61 pages. Available in PDF, EPUB and Kindle. Book excerpt: A technique known as the Shadow Method was developed for calculating aerosol optical depths by measuring the radiance difference between shaded and unshaded regions in high-resolution satellite imagery by Vincent (2006). Previous research investigated use of the Shadow Method in regions of dust obscuration using buildings and clouds as shadow generation sources and a variety of background surfaces. A recurring low bias was seen when using the Shadow Method with the QuickBird satellite's panchromatic sensor. QuickBird and WorldView1 commercial imagery was examined using the Shadow Method at several sites co-located with AERONET observations sites. The results show that low bias is not attributed to sensor calibration, processing methods of the imagery, or water vapor content. The most likely source of low bias is the region of interest (ROI) selection geometry within the shadow regions.

Download or read book Satellite Aerosol Remote Sensing Over Land written by Alexander A. Kokhanovsky and published by Springer. This book was released on 2009-08-29 with total page 388 pages. Available in PDF, EPUB and Kindle. Book excerpt: Aerosols have a significant influence on the Earth's radiation budget, but there is considerable uncertainty about the magnitude of their effect on the Earth's climate. Currently, satellite remote sensing is being increasingly utilized to improve our understanding of the effect of atmospheric aerosols on the climate system. Satellite Aerosol Remote Sensing Over Land is the only book that brings together in one volume the most up-to-date research and advances in this discipline. As well as describing the current academic theory, the book presents practical applications, utilizing state-of-the-art instrumentation, invaluable to the work of environmental scientists. With contributions by an international group of experts and leaders of correspondent aerosol retrieval groups, the book is an essential tool for all those working in the field of climate change.

Download or read book Real Effect Or Artifact of Cloud Cover on Aerosol Optical Thickness written by and published by . This book was released on 2005 with total page 5 pages. Available in PDF, EPUB and Kindle. Book excerpt: Aerosol measurements over the Southern Great Plains (SGP) Cloud And Radiation Test bed (CART) site under Department of Energy's (DOE) Atmospheric Radiation Measurement (ARM) program characterize the temporal variability, vertical distribution, and optical properties of aerosols in the region. They were made by the Cimel sunphotometer and Multifilter Rotating Shadow-band Radiometer (MFRSR), Raman Lidar, In situ Aerosol Profiling (IAP) flights, and the Aerosol Observing System (AOS). The spatial variability of aerosols relies a network of MFRSR at the Central Facility (CF) and Extended Facilities (EF), together with satellite remote sensing. The current state-of-art satellite-based estimates over land--e.g., MODerate resolution Imaging Scanner (MODIS) aerosol optical thickness--still suffer from large uncertainties. Contamination due to sub-pixel and/or thin cirrus clouds is believed to be one of the major sources of uncertainties. Retrievals near clouds are discouraged to use, which reduces considerably the amount of useful data. In this regard, cloud is considered as an artifact. However, cloud could have a real impact on AOT by changing humidity, which affects aerosol through the aerosol swelling effect. As a preliminary study, we first investigate the effects of cloud cover and humidity on the retrievals of AOT from ground-based Cimel sunphotometer measurements, in order to help us sort out the real influence and artifact. In general, it is very difficult to verify and quantify the effects of cloud on satellite retrieval of aerosol quantities. Speculation and warning of cloud contamination have been made whenever there is a correlation between the retrieved AOT and cloud fraction or their spatial variabilities, while it has also been argued that aerosol humidification effect (AHE) might be at work. The ample measurements available from ARM over the SGP region may allow us to unravel this complex issue. Our ultimate goals are to (1) evaluate various effects on the retrievals of AOT from both satellite and ground sensors; (2) separate artifact from real effect; (3) create ''clean'' aerosol products for studying their direct and indirect effect. Presented are some very preliminary findings.

Download or read book Satellite Aerosol Remote Sensing Over Land written by Alexander A. Kokhanovsky and published by Springer Science & Business Media. This book was released on 2009-08-24 with total page 398 pages. Available in PDF, EPUB and Kindle. Book excerpt: Aerosols have a significant influence on the Earth's radiation budget, but there is considerable uncertainty about the magnitude of their effect on the Earth's climate. Currently, satellite remote sensing is being increasingly utilized to improve our understanding of the effect of atmospheric aerosols on the climate system. Satellite Aerosol Remote Sensing Over Land is the only book that brings together in one volume the most up-to-date research and advances in this discipline. As well as describing the current academic theory, the book presents practical applications, utilizing state-of-the-art instrumentation, invaluable to the work of environmental scientists. With contributions by an international group of experts and leaders of correspondent aerosol retrieval groups, the book is an essential tool for all those working in the field of climate change.

Download or read book Aerosol Surface and Cloud Retrieval Using Passive Remote Sensing Over the Arctic written by Soheila Jafariserajehlou and published by . This book was released on 2021 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: The lack knowledge of aerosol optical properties is one of the sources of uncertainty in assessment and projections of the evolution of climate change and the phenomenon of Arctic Amplification. The spatial and temporal change of microphysical, chemical and optical properties of aerosols in the Arctic and the induced effects through direct and indirect radiative forcing of aerosols remain an open question. The cause of this gap in our understanding and therefore in the global aerosol optical thickness (AOT) maps is associated with the difficulty of retrieving aerosol properties over bright surfaces covered with snow and ice. Decoupling a strong surface signal from that of aerosol in the measured top-of-atmosphere reflectance is challenging and still hampered due to remaining unresolved issues in state-of-the-art algorithms. Despite the promising performance of previously-developed methods and ongoing research, there is no published long-term AOT product over polar regions (over land and ocean) to be used for climate studies. In this work, to extend our knowledge about the open issues and improve the existing algorithms, first we focus on the two major obstacles in the retrieval of AOT over snow/ice surfaces: i) cloud identification, and ii) surface properties; Second, we apply the outcome of studying the two mentioned prerequisites to improve the previously-developed aerosol retrieval algorithm called AEROSNOW and create a long-term data record for aerosol optical thickness over the Arctic circle. In the framework of this work, a new cloud identification algorithm called the AATSR/SLSTR Cloud Identification Algorithm (ASCIA) has been developed to screen cloudy scenes in observations of Advanced Along-Track Scanning Radiometer (AATSR) on-board ENVISAT as well as its successor Sea and Land Surface Temperature Radiometer (SLSTR) on-board Sentinel-3. The cloud detection results are verified by comparing them with available cloud products over the Arctic. Furthermore, the cloud product from ASCIA is validated using the ground-based measurements SYNOP, resulting in a promising agreement. In general, ASCIA shows an improved performance in comparison with other algorithms applied to AATSR measurements over snow/ice. For the study of snow surface properties, the reflectance is simulated in a snow-atmosphere system, using the SCIATRAN radiative transfer model, and the results are compared with those of airborne measurements. A sensitivity study is conducted to highlight the importance of having a priori knowledge about snow morphology (size and shape) and atmospheric parameters to minimise the difference between simulated and real world reflectance. The absolute difference between the modelled results and measurements in off-glint regions is generally small and promising. In the final step, we apply the outcome of previous steps in the AEROSNOW algorithm as far as possible within the scope of this work and retrieve AOT over the Arctic circle for the 2002-2012 period with the spatial resolution of 1 km2. The retrieved AOT is validated using ground-based measurements AErosol RObotic NETwork (AERONET). The results of validation are promising and show the successful performance of the algorithm especially during haze episodes. However, in some cases large differences exist between the retrieved AOT and AERONET measurements for which more statistical and physical analysis are necessary to better understand the cause. Nevertheless, the long-term data record and validation produced hold significant value as are the first attempt to better understand the role of aerosols in the Arctic Amplification over land and ocean on the full Arctic scale.

Download or read book Satellite Cloud Detection With Shortwave Channels Algorithms MISR Applications and Three Dimensional Radiative Effects written by Yuekui Yang and published by . This book was released on 2007 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Aerosol Retrieval Using Remote sensed Observations written by Yueqing Wang and published by . This book was released on 2012 with total page 182 pages. Available in PDF, EPUB and Kindle. Book excerpt: Atmospheric aerosols are solid particles and liquid droplets that are usually smaller than the diameter of a human hair. They can be found drifting in the air in every ecosystem on Earth, leaving significant impacts on human health and our climate. Understanding the spatial and temporal distribution of different atmospheric aerosols, therefore, is an important first step to decode the complex system of aerosols and further, their effects on public health and climate. The development of remote-sensing radiometers provides a powerful tool to monitor the amount of atmospheric aerosols, as well as their compositions. Radiometers aboard satellites measure the amount of electromagnetic solar radiation. The amount of atmospheric aerosols is further quantified by aerosol optical depth (AOD), defined as the amount of solar radiation that aerosols scatter and absorb in the atmosphere and generally prevent from reaching the Earth surface. Despite efforts to improve remote-sensing instruments and a great demand for a detailed profile of aerosol spatial distribution, methods needed to provide AOD estimation at a reasonably fine resolution, are lacking. The quantitative uncertainties in the amount of aerosols, and especially aerosol compositions, limit the utility of traditional methods for aerosol retrieval at a fine resolution. In Chapter 2 and 3 of this thesis, we exploit the use of statistical methods to estimate aerosol optical depth using remote-sensed radiation. A Bayesian hierarchy proves to be useful for modeling the complicated interactions among aerosols of different amount and compositions over a large spatial area. Based on the hierarchical model, Chapter 2 estimates and validates aerosol optical depth using Markov chain Monte Carlo methods, while chapter 3 resorts to an optimization-based approach for faster computation. We extend our study focus from the aerosol amount to the aerosol compositions in Chapter 4. Chapter 1 briefly reviews the characteristics of atmospheric aerosols, including the different types of aerosols and their major impacts on human health. We also introduce a major remote-sensing instrument, NASA's Multi-angle Imaging SpectroRadiometer (MISR), which collects the observations our studies base on. Currently, the MISR operational aerosol retrieval algorithm provides estimates of aerosol optical depth at the spatial resolution of 17.6 km. In Chapter 2, we embed MISR's operational weighted least squares criterion and its forward calculations for aerosol optical depth retrievals in a likelihood framework. We further expand it into a hierarchical Bayesian model to adapt to finer spatial resolution of 4.4 km. To take advantage of the spatial smoothness of aerosol optical depth, our method borrows strength from data at neighboring areas by postulating a Gaussian Markov Random Field prior for aerosol optical depth. Our model considers aerosol optical depth and mixing vectors of different types of aerosols as continuous variables. The inference is then carried out using Metropolis-within-Gibbs sampling methods. Retrieval uncertainties are quantified by posterior variabilities. We also develop a parallel Markov chain Monte Carlo algorithm to improve computational efficiency. We assess our retrieval performance using ground-based measurements from the AErosol RObotic NETwork (AERONET) and satellite images from Google Earth. Based on case studies in the greater Beijing area, China, we show that 4.4 km resolution can improve both the accuracy and coverage of remote-sensed aerosol retrievals, as well as our understanding of the spatial and seasonal behaviors of aerosols. This is particularly important during high-AOD events, which often indicate severe air pollution. Chapter 3 of this thesis continues to improve our statistical aerosol retrievals for better accuracy and more efficient computation by switching to an optimization-based approach. We first establish objective functions for aerosol optical depth and aerosol compositions, based upon MISR operational weighted least squares criterion and its forward calculations. Our method also borrows strength from aerosol spatial smoothness by constructing penalty terms in the objective functions. The penalties correspond to a Gaussian Markov Random Field prior for aerosol optical depth and a Dirichlet prior for aerosol mixing vectors under our hierarchical Bayesian scheme; the optimization-based approach corresponds to Bayesian Maximum a Posteriori (MAP) estimation. Our MAP retrieval algorithm provides computational efficiency almost 60 times that of our Bayesian retrieval algorithm presented in Chapter 2. To represent the increasing heterogeneity of urban aerosol sources, our model continues to expand the pre-fixed aerosol mixtures used in the MISR operational algorithm by considering aerosol mixing vectors as continuous variables. Our retrievals are again validated using ground-based AERONET measurements. Case studies in the greater Beijing and Zhengzhou areas of China reassure that 4.4 km resolution can improve the accuracy and spatial coverage of remotely-sensed retrievals and enhance our understanding of the spatial behaviors of aerosols. When comparing our aerosol retrievals to the extensive ground-based measurements collected in Baltimore, Maryland, we encountered greater uncertainties of aerosol compositions. It is a result from both the complex terrain structures of Baltimore and its various aerosol emission sources. Chapter 4, as result, extends the flexibility of our previous aerosol retrievals by incorporating a complete set of the eight commonly observed types of aerosols. The consequential rise in model complexity is met by a warm-start Markov chain Monte Carlo sampling scheme. We first design two Markov sub-chains, each representing an aerosol mixture containing only four types of the commonly observed aerosols. Combining the samples generated by these two sub-chains, we propose an initialization for the Markov chain that contains all eight types of commonly observed aerosols. Partial information on the interactions of different types of aerosols from the samples generated by the sub-chains proves to be useful in choosing a more efficient initial point for the complete Markov chain. Faster computation is achieved without compromising the retrieval accuracy nor the spatial resolution of the estimated aerosol optical depth. In the end, through case studies of aerosol retrievals for the Baltimore area, we explore the potentials of remote-sensed retrievals in improving our understanding of aerosol compositions.

Download or read book Satellite Sensor Calibration Verification Using the Cloud Shadow Method written by National Aeronautics and Space Administration (NASA) and published by Createspace Independent Publishing Platform. This book was released on 2018-08-20 with total page 34 pages. Available in PDF, EPUB and Kindle. Book excerpt: An atmospheric-correction method which uses cloud-shaded pixels together with pixels in a neighboring region of similar optical properties is described. This cloud-shadow method uses the difference between the total radiance values observed at the sensor for these two regions, thus removing the nearly identical atmospheric radiance contributions to the two signals (e.g. path radiance and Fresnel-reflected skylight). What remains is largely due to solar photons backscattered from beneath the sea to dominate the residual signal. Normalization by the direct solar irradiance reaching the sea surface and correction for some second-order effects provides the remote-sensing reflectance of the ocean at the location of the neighbor region, providing a known 'ground target' spectrum for use in testing the calibration of the sensor. A similar approach may be useful for land targets if horizontal homogeneity of scene reflectance exists about the shadow. Monte Carlo calculations have been used to correct for adjacency effects and to estimate the differences in the skylight reaching the shadowed and neighbor pixels. Reinersman, P. and Carder, K. L. and Chen, F. R. Goddard Space Flight Center NAS5-31716; N00014-89-J-1091...

Download or read book Cloud free Aerosol Optical Depth Determination Over Oceans from Satellite Radiometry written by and published by . This book was released on 1993 with total page 8 pages. Available in PDF, EPUB and Kindle. Book excerpt: Shortwave radiative forcing of climate by anthropogenic sulfate aerosol has been estimated to be of comparable global-average magnitude, but opposite sign, to longwave forcing by greenhouse gases (Charlson et al., 1992). It is therefore important that this forcing be accurately represented in climate models. Sulfate concentrations calculated by a Global Chemistry Model driven by operational meteorological data (GChM; Benkovitz et al., this meeting) exhibit high spatial and temporal variations that closely reproduce observations at continental sites. However, because of the sparsity of sulfate concentration measurements over oceans, aerosol optical depth determinations from satellite data are needed to evaluate the performance of the model over oceans. Previous studies of aerosol optical depths over oceans have employed Advanced Very High Resolution Radiometer Global Area Coverage (AVHRR GAC) data (Rao et al., 1989; Durkee et al., 1991) that should yield the required information, but the emphasis in these studies has been to produce wide spatial coverage by time averaging for periods of a week to a month, thereby masking the high spatial and temporal variability associated with the data and required for model evaluation. The Rao et al. method is employed in the production of the weekly composite aerosol maps by NOAA since June 1987. The authors report results obtained with a modified Durkee algorithm that provides instantaneous optical depths averaged over individual GChM model grid cells (1.125° x 1.125°) for comparison with optical depths predicted by the chemistry model at the same times and places (Berkowitz et al., this meeting). The optical depth retrieval is improved by a more accurate removal of sun-glint contamination, using the formulation of (Cox and Munk, 1956) for sun-glint probability as a function of wind speed, together with the wind speeds available from the operational meteorological data used to drive the chemistry model.

Download or read book Aerosol Remote Sensing written by Jacqueline Lenoble and published by Springer Science & Business Media. This book was released on 2013-02-11 with total page 423 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book gives a much needed explanation of the basic physical principles of radiative transfer and remote sensing, and presents all the instruments and retrieval algorithms in a homogenous manner. The editors provide, for the first time, an easy path from theory to practical algorithms in one easily accessible volume, making the connection between theoretical radiative transfer and individual practical solutions to retrieve aerosol information from remote sensing, and providing the specifics and intercomparison of all current and historical retrieval methods.

Download or read book Aerosol Characterization in the Southeastern U S Using Satellite Data for Applications to Air Quality and Climate written by Erica J. Alston and published by . This book was released on 2012 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: Tropospheric aerosol information from NASA satellites in space has reached the milestone of ten years of continuous measurements. These higher resolution satellite aerosol records allow for a broader regional perspective than can be gained using only sparsely located ground based monitoring sites. Decadal satellite aerosol data have the potential to advance knowledge of the climatic impacts of aerosols through better understanding of solar dimming/brightening and radiative forcings on regional scales, as well as aid in air quality applications. The goal of this thesis is to develop and implement methodologies for using satellite remotely sensed data in conjunction with ground based observations and modeling for characterization of regional aerosol variations with applications to air quality and climate studies in the Southeastern U.S. This region is of special interest because of distinct aerosol types, less warming climate trends compared to the rest of U.S., and growing population. To support this primary goal, a technique is developed that exploits the statistical relationship between PM2.5 (particulate matter that has an aerodynamic radius of 2.5 æm or less) and satellite AOD (Aerosol Optical Depth) from MODIS (Moderate resolution Imaging Spectroradiometer) where a probabilistic approach is used for air quality assessments in the metropolitan Atlanta area. The metropolitan Atlanta area experiences the poorest air quality during the warmer seasons. We found that satellite AODs capture a significant portion of PM2.5 concentration variability during the warmer months of the year with correlation values above 0.5 for a majority of co-located (in time and space) ground based PM2.5 monitors, which is significant at the 95% confidence interval. The developed probabilistic approach uses five years of satellite AOD, PM2.5 and their related AQI (Air Quality Index) to predict future AQI based solely on AOD retrievals through the use of AOD thresholds, e.g., 80% of Code Green AQI days have AOD below 0.3. This approach has broad applicability for concerned stakeholders in that it allows for quick dissemination of pertinent air quality data in near-real time around a satellite overpass. Examination of the use of multiple satellite sensors to aid in investigating the impacts of biomass burning in the region is performed. The utility of data fusion is evaluated in understanding the effects of the large wildfire that burned in May 2007. This wildfire caused PM2.5 in the metropolitan Atlanta area to exceed healthy levels with some measurements surpassing 150 æg/m3 during the month. OMI (Ozone Monitoring Instrument) AI (Aerosol Index), which qualitatively measures absorbing aerosols, have high values of more than 1.5 during May 26 - 31, 2007. CALIPSO (Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations) a space based lidar was used to determine the vertical structure of the atmosphere across the region during the active fire period. CALIPSO was able to identify wildfire aerosols both within the planetary boundary layer (likely affects local air quality) and aloft where aerosol transport occurs. This has important implications for climatic studies specifically aerosol radiative effects. In-depth analysis of the satellite and ground based aerosol data records over the past decade (2000 - 2009) are performed from a climatic perspective. The long temporal scale allowed for better characterization of seasonality, interannual variability, and trends. Spatial analysis of ten years of AOD from both MODIS and MISR (Multi-angle Imaging Spectroradiometer) showed little variability of AOD during the winter with mean AOD below 0.1 for the entire region, while the summer had decidedly more variability with mean AOD around 0.33 for MODIS and 0.3 for MISR. Seasonal analysis of the PM2.5 revealed that summer means are twice as high as winter means for PM2.5. All of the datasets show interannual variability that suggests with time AOD and PM2.5 are decreasing, but seasonal variability obscured the detection of any appreciable trends in AOD; however, once the seasonal influence was removed through the creation of monthly anomalies there were decreasing trends in AOD, but only MODIS had a trend of -0.00434 (per month) that statistically significant at the 95% confidence level. Satellite and ground-based data are used to assess the radiative impacts of aerosols in the region. The regional TOA (Top Of the Atmosphere) direct radiative forcing is estimated by utilizing satellite AOD from MODIS and MISR both on Terra, along with satellite derived cloud fraction, surface albedo (both from MODIS), and single scattering albedo (SSA) from MISR data from 2000 - 2009. Estimated TOA forcing varied from between - 6 to -3 W/m2 during the winter, and during the warmer months there is more variation with [delta]F varying between -28 to -12.6 W/m2 for MODIS and -26 to -11 W/m2 for MISR. The results suggest that when AOD, cloud fraction and surface albedo are all consider they add an additional 6 W/m2 of TOA forcing compared to TOA forcing due to aerosol effects only. Varying SSA can create changes in TOA forcing of about 5 W/m2. With removal of the seasonal variability timeseries anomaly trend analysis revealed that estimated TOA forcing is decreasing (becoming less negative) with MODIS based estimates statistically significant at the 95% confidence level. Optical and radiative 1-D radiative transfer modeling is performed to assess the daily mean TOA forcing and forcing at the surface for representative urban and background aerosol mixtures for summer and winter. During the winter, modeled TOA forcing is -2.8 and -5 W/m2 for the WB and WU cases, and the modeled summer TOA forcings (SB = -13.3 W/m2) also generally agree with earlier estimates. While surface forcings varied from -3 to -210 W/m2. The radiative forcing efficiency at the TOA (amount of forcing per unit of AOD at 550 nm) varied from -9 to - 72 W/m2 [tau]-1, and RFE at the surface varied from -50 to -410 W/m2 [tau]-1. It was found that the forcing efficiency for biomass burning aerosols are similar to the forcing efficiency of background aerosols during the summer that highlights the importance of possible increased biomass burning activity. Ultimately, the methodologies developed in this work can be implemented by the remote sensing community and have direct applicability for society as a whole.

Download or read book Ground Based Aerosol Optical Depth Measurement Using Sunphotometers written by Jedol Dayou and published by Springer. This book was released on 2014-06-03 with total page 67 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book gives a detailed review on ground-based aerosol optical depth measurement with emphasis on the calibration issue. The review is written in chronological sequence to render better comprehension on the evolution of the classical Langley calibration from the past to present. It not only compiles the existing calibration methods but also presents a novel calibration algorithm in Langley sun-photometry over low altitude sites which conventionally is a common practice performed at high observatory stations. The proposed algorithm avoids travelling to high altitudes for frequent calibration that is difficult both in logistics and financial prospects. We addressed the problem by combining clear-sky detection model and statistical filter to strictly imitate the ideal clear-sky condition at high altitude for measurements taken over low altitudes. In this way, the possible temporal atmospheric drifts, abundant aerosol loadings and short time interval cloud transits are properly constrained. We believe that this finding has an integral part of practicality and versatility in ground-based aerosol optical depth measurement, which is nowadays an important climate agent in many atmospheric studies. Finally, the outcome of this book introduces a new calibration technique for the study and measurement of aerosol monitoring with emphasis on aerosol optical depth that we believe could be very beneficial to researchers and scientists in the similar area.