We present further development of our analysis algorithm for Multi-Filter Rotating Shadowband Radiometer (MFRSR) data. The new additions include techniques allowing us to retrieve spectral aerosol single scattering albedo (SSA) and column amount of precipitable water vapor (PWV). The SSA retrievals employ MFRSR measurements of both direct normal and diffuse horizontal irradiances. We present a sensitivity study indicating dependence of SSA retrievals on optical thickness and other aerosol parameters. Influence on the retrievals of a possible error in separation of the direct and diffuse irradiances by the instrument is discussed. The algorithm has been tested on a long-term dataset from the local MFRSR network at the DOE Atmospheric Radiation Measurement (ARM) Program site in Southern Great Plains (SGP). Our results are compared to AERONET's almucantar retrievals of SSA from CIMEL sun-photometer co-located with the MFRSR at the SGP Central Facility. A constrained variant of the algorithm (assuming zero nitrogen dioxide column values) is used for this comparison and to study the influence of the uncertainty associated with this atmospheric gas on the retrieved aerosol absorption properties. Precipitable water vapor column amounts are determined from the direct normal irradiances in the 940 nm MFRSR spectral channel. HITRAN 2004 spectral database has been used to model the water vapor absorption, while a range of other databases (HITRAN 1996, 2000, ESA) is used in the sensitivity study. The results of the PWV retrievals for SGP's MFRSR network are compared with correlative measurements by Microwave Radiometers (MWR), GPS stations, AERONET, and MODIS satellite product. In the latter case an interpolation technique has been used to determine spatial structure of water vapor field from the network data and to create a 2D dataset comparable with satellite data.
We recently developed a new version of our analysis algorithm for Multi-Filter Rotating Shadowband Radiometer (MFRSR) data that allows us to retrieve fine mode and coarse mode aerosol optical thickness as well as the effective radius of the fine mode. Our retrieval products also include time series of column amounts of ozone and nitrogen dioxide. The algorithm has been tested using a multi-year dataset from the local MFRSR network at the DOE Atmospheric Radiation Measurement (ARM) Program site in Southern Great Plains (SGP). Here we present an overview of the retrieval algorithm and validate its performance through comparison of our MFRSR retrieval products with the corresponding AERONET almucantar retrieval results derived from a CIMEL sunphotometer co-located with the MFRSR at the SGP Central Facility. A constrained variant of the retrieval algorithm (assuming zero nitrogen dioxide column values) is described in detail. We use this variant of the algorithm to derive the range of physically justified values of the fine mode effective radius and for comparison with AERONET particle size retrievals. A multi-instrument, multi-year, MFRSR dataset from the SGP Extended Facilities is used to examine geographical and seasonal variability of aerosol properties. We find a correspondence between the geographical variation in fine mode particle size and aerosol composition (nitrates vs. sulfates) as measured by National Atmospheric Deposition Program. A similar correspondence in terms of temporal variability exists between our retrievals and in-situ measurements of aerosol composition made by NOAA Pacific Marine Environmental Laboratory (PMEL) at SGP Central Facility.
A substantial upgrade of our previously developed MFRSR data analysis algorithm is presented. The new version of the algorithm features an automated cloud screening procedure based on optical thickness variability analysis. This technique is objective, computationally efficient and is able to detect short clear-sky intervals under broken cloud conditions. The performance of the method has been compared with that of AERONET cloud screening algorithm. Another new feature is the adoption of a bimodal gamma distribution as the aerosol particle size model. The size of the fine mode particles and a ratio between optical thicknesses of the two modes are retrievable. The algorithm has been tested on a multi-year dataset from the MFRSR network at the DOE Atmospheric Radiation Measurement (ARM) Program site in Southern Great Plains (SGP). The aerosol optical thicknesses (total, fine, and coarse) obtained from our analysis were successfully compared with the corresponding AERONET almucantar retrievals from a CIMEL sunphotometer colocated with the MFRSR at the SGP Central Facility. Geographical and seasonal variability of aerosol properties has been observed in the multi-instrument dataset from all SGP Extended Facilities for the year 2000. The geographical trends in the fine mode particle size appear to reflect differences in the PM2.5 to PM10 ratios obtained from EPA monitoring data. Long-term temporal variability has been studied on the 1992-1997 dataset from the SGP Central Facility. A significant trend has been detected in coarse mode aerosol optical thickness following the Mt. Pinatubo eruption in 1991, while the fine mode optical thickness exhibits only seasonal variations during that period.
We present the results of a scale analysis of aerosol optical thickness (AOT) variability in time and space. The standard scale analysis methods based on variance spectra, structure functions and singular measures were applied to different datasets to determine AOT scaling properties in the scale range from 0.2 to 1200 km. We used data sets from the local network of Multi-Filter Rotating Shadowband Radiometers (MFRSRs) located at the DOE ARM program's Southern Great Plains (SGP) site. This network consists of 21 instruments arrayed across approximately 55,000 square miles in north-central Oklahoma and south-central Kansas. Our analysis demonstrates that datasets from the SGP network can provide definitive information on both temporal and spatial AOT variability. We compare AOT scale properties derived from MFRSR network data with those derived from MODIS satellite aerosol retrievals over SGP. We also use MODIS retrievals over larger land and ocean areas to study large-scale AOT variability. Our analysis suggests that the variability of AOT splits into three main scale regimes. Three-dimensional turbulent transport dominates small scales (0-30 km), the influence of 2D turbulence at scales larger than 30 km makes AOT more non-stationary, and finally, the influence of the AOT boundedness at scales larger than 100 km presses AOT behavior back towards stationarity. However, the scales used in our analysis were not large enough to observe the boundedness-induced asymptotic regime in AOT variability, where any further scale increase does not change variability properties.
We present results from a preliminary analysis of the multi-instrument MFRSR dataset from ARM CART (SGP) site Extended Facilities (Northern Oklahoma and Southern Kansas). Single-instrument retrievals are performed using our previously reported direct-diffuse algorithm. Retrieval products include daily time series of the aerosol optical depth, column mean aerosol particle size, NO2 and ozone column amounts. The distribution of MFRSR sites at the SGP (central and extended facilities) allows us to combine the retrievals from the individual instruments into series of 2D images. These 2D images facilitate the investigation of spatial and temporal variability of aerosols and trace gases. These images can be also used to evaluate satellite aerosol data products (e.g. MODIS, TOMS, EO-1).
Measurements from ground-based sun photometer networks can be used both to provide a ground-truth validation of satellite aerosol retrieval sand to produce a land-based aerosol climatology which is complementary to satellite retrievals that currently are being performed mostly over ocean. The MFRSR has become a popular network instrument in recent years, several existing networks operate about a hundred instruments providing good geographical coverage of the US. We describe and validate a retrieval algorithm for processing MFRSR data from clear and partially cloudy days. This method uses consistency between direct normal and diffuse horizontal measurements together with a special regression technique for retrieval of daily time series of column mean aerosol particle size, aerosol optical depth, NO2, ozone and water vapor column amounts together with the instrument's calibration constants. This method has bene successfully used to analyze MFRSR measurements from a number of instruments both from large networks and those operated by individual users. The analysis of long-term MFRSR measurements provides a description of seasonal and inter-annual changes in aerosol parameters and in column amounts of ozone, NO2 and water vapor as a function of geographical location. Application of this analysis method to the measurements from growing numbers of MFRSR opens the possibility to build large-scale climatologies basing on MFRSR network data.
The Multi-Filter Rotating Shadow-band Radiometer (MFRSR) makes precise simultaneous measurements of the direct solar beam extinction, and horizontal diffuse flux, at six wavelengths (nominally 415, 500, 615, 670, 870, and 940 nm) at one minute intervals throughout the day. MFRSR data obtained at tens of sites throughout the U.S. has been available for several years. This is a potentially very important but as yet underutilized data set. We describe and validate a retrieval algorithm for processing of MFRSR data from clear and partially cloudy days. This method uses consistency between direct normal and diffuse horizontal measurements together with a special regression technique to retrieve daily time series of column mean aerosol particle size, aerosol optical depth, NO2 and ozone amounts together with the instrument's calibration constants. Our validation studies demonstrate two advantages of our approach compared to the traditional Langley calibration method: less calibration variability and less sensitivity of retrievals to calibration accuracy. This method is currently used for processing data from a growing number of MFRSRs spread throughout the U.S. determining both time and geographic variability of aerosol properties and gaseous column amounts. This method makes the relatively inexpensive and automatic MFRSR an important tool in climatological research.
The depth mode of light propagation in a 2D-medium with strong absorption and sharply- anisotropic scattering is studied analytically outside the framework of the small-angle diffusion approximation. We propose and realize a regular procedure for optimum determination of the parameters of a postulated approximate angular spectrum in the depth mode. The dispersion in the depth mode and the depth damping coefficient are found. Our results are in good agreement with the exact solution to the transport equation written in the quasi-diffusion approximation, that has been obtained recently in the particular case of the Henyey-Greenstein phase function.
A study, performed outside the framework of the Fokker-Planck approximation, is presented of the depth mode of light propagation in turbid media with slowly decreasing scattering phase function X((gamma) ), when the scattering probability decreases more slowly, than (gamma) -4, as the single scattering angle (gamma) is enhanced. Postulating the approximate shape of the angular spectrum in the depth mode, we propose and realize a regular procedure for optimum determination of the parameters of this spectrum. The dispersion in the depth mode and the depth damping coefficient are found analytically. The obtained results are in good agreement with the results of numerical calculations and transform, in the limit, into known results of the diffusion approximation.
A study is presented for the 2-D case of light propagation in a turbid medium involving sharply anisotropic one-center scattering, in accordance with the Heney-Greenstein law, with strong absorption (when the photon absorption length is shorter than the transport length). An exact analytic solution, that takes into account fluctuations of the photon paths, has been obtained, within the framework of the small-angle approximation. Angular spectrum and attenuation coefficient for the deep-propagating mode are analyzed in detail.
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