Long-term PM
2.5
exposure has been associated with various adverse health outcomes. However, most ground monitors are located in urban areas, leading to a potentially biased representation of true ...regional PM
2.5
levels. To facilitate epidemiological studies, accurate estimates of the spatiotemporally continuous distribution of PM
2.5
concentrations are important. Satellite-retrieved aerosol optical depth (AOD) has been increasingly used for PM
2.5
concentration estimation due to its comprehensive spatial coverage. Nevertheless, previous studies indicated that an inherent disadvantage of many AOD products is their coarse spatial resolution. For instance, the available spatial resolutions of the Moderate Resolution Imaging Spectroradiometer (MODIS) and the Multiangle Imaging SpectroRadiometer (MISR) AOD products are 10 and 17.6 km, respectively. In this paper, a new AOD product with 1 km spatial resolution retrieved by the multi-angle implementation of atmospheric correction (MAIAC) algorithm based on MODIS measurements was used. A two-stage model was developed to account for both spatial and temporal variability in the PM
2.5
–AOD relationship by incorporating the MAIAC AOD, meteorological fields, and land use variables as predictors. Our study area is in the southeastern US centered at the Atlanta metro area, and data from 2001 to 2010 were collected from various sources. The model was fitted annually, and we obtained model fitting
R
2
ranging from 0.71 to 0.85, mean prediction error (MPE) from 1.73 to 2.50 μg m
−3
, and root mean squared prediction error (RMSPE) from 2.75 to 4.10 μg m
−3
. In addition, we found cross-validation
R
2
ranging from 0.62 to 0.78, MPE from 2.00 to 3.01 μgm
−3
, and RMSPE from 3.12 to 5.00 μgm
−3
, indicating a good agreement between the estimated and observed values. Spatial trends showed that high PM
2.5
levels occurred in urban areas and along major highways, while low concentrations appeared in rural or mountainous areas. Our time-series analysis showed that, for the 10-year study period, the PM
2.5
levels in the southeastern US have decreased by ∼20 %. The annual decrease has been relatively steady from 2001 to 2007 and from 2008 to 2010 while a significant drop occurred between 2007 and 2008. An observed increase in PM
2.5
levels in year 2005 is attributed to elevated sulfate concentrations in the study area in warm months of 2005.
The Collection 6 (C6) MODIS (Moderate Resolution Imaging Spectroradiometer) land and atmosphere data sets are scheduled for release in 2014. C6 contains significant revisions of the calibration ...approach to account for sensor aging. This analysis documents the presence of systematic temporal trends in the visible and near-infrared (500 m) bands of the Collection 5 (C5) MODIS Terra and, to lesser extent, in MODIS Aqua geophysical data sets. Sensor degradation is largest in the blue band (B3) of the MODIS sensor on Terra and decreases with wavelength. Calibration degradation causes negative global trends in multiple MODIS C5 products including the dark target algorithm's aerosol optical depth over land and Ångström exponent over the ocean, global liquid water and ice cloud optical thickness, as well as surface reflectance and vegetation indices, including the normalized difference vegetation index (NDVI) and enhanced vegetation index (EVI). As the C5 production will be maintained for another year in parallel with C6, one objective of this paper is to raise awareness of the calibration-related trends for the broad MODIS user community. The new C6 calibration approach removes major calibrations trends in the Level 1B (L1B) data. This paper also introduces an enhanced C6+ calibration of the MODIS data set which includes an additional polarization correction (PC) to compensate for the increased polarization sensitivity of MODIS Terra since about 2007, as well as detrending and Terra–Aqua cross-calibration over quasi-stable desert calibration sites. The PC algorithm, developed by the MODIS ocean biology processing group (OBPG), removes residual scan angle, mirror side and seasonal biases from aerosol and surface reflectance (SR) records along with spectral distortions of SR. Using the multiangle implementation of atmospheric correction (MAIAC) algorithm over deserts, we have also developed a detrending and cross-calibration method which removes residual decadal trends on the order of several tenths of 1% of the top-of-atmosphere (TOA) reflectance in the visible and near-infrared MODIS bands B1–B4, and provides a good consistency between the two MODIS sensors. MAIAC analysis over the southern USA shows that the C6+ approach removed an additional negative decadal trend of Terra ΔNDVI ~ 0.01 as compared to Aqua data. This change is particularly important for analysis of vegetation dynamics and trends in the tropics, e.g., Amazon rainforest, where the morning orbit of Terra provides considerably more cloud-free observations compared to the afternoon Aqua measurements.
We examine satellite-based measurements of solar-induced chlorophyll fluorescence (SIF) over the region impacted by the Russian drought and heat wave of 2010. Like the popular Normalized Difference ...Vegetation Index (NDVI) that has been used for decades to measure photosynthetic capacity, SIF measurements are sensitive to the fraction of absorbed photosynthetically-active radiation (fPAR). However, in addition, SIF is sensitive to PAR as well as the fluorescence yield that is related to the photosynthetic yield. Both SIF and NDVI from satellite data show drought-related declines early in the growing season in 2010 as compared to other years between 2007 and 2013 for areas dominated by crops and grasslands. This suggests an early manifestation of the dry conditions on fPAR. Using MODIS fPAR retrievals, we computed SIF/APAR which is related to light use efficiencies (LUEs) for fluorescence and photosynthesis. We found drought-related losses in fluorescence efficiency for all areas including those dominated by mixed forests. Unlike croplands and grasslands, areas of mixed forest did not show significant drought-related declines in fPAR. We also simulated SIF and Gross Primary Productivity (GPP) using a global land surface model driven by observation-based meteorological fields. The model provides a reasonable simulation of the drought and heat impacts on SIF in terms of the spatial extents of anomalies, but some differences were found in timing of the peak drought response between modeled and observed SIF. Model data also suggested that drought-related declines in LUE for fluorescence and photosynthesis in areas of mixed forest produce losses in SIF and GPP. SIF and GPP losses due to drought in croplands and grasslands result from both LUE and fPAR reductions. The combination of SIF and NDVI or fPAR data is shown to be an important source of information for evaluating model performance.
•We examined fluorescence (SIF) and NDVI anomalies for the 2010 Russian drought.•Both SIF and NDVI showed drought-related declines early in the 2010 growing season.•SIF and NDVI anomalies for 2010 Russian drought driven primarily by fPAR decline.•Model simulated SIF anomalies are similar to those seen in the satellite SIF data.•SIF has potential to improve the model through assimilation/parameter estimation.
Quality of aerosol retrievals and atmospheric correction over land depends strongly on accuracy of the cloud mask (CM) algorithm. The heritage CM algorithms developed for AVHRR and MODIS use the ...latest sensor measurements of spectral reflectance and brightness temperature and perform processing at the pixel level. The algorithms are threshold‐based and empirically tuned. They do not explicitly address the classical problem of cloud search, wherein the baseline clear‐skies scene is defined for comparison. Here we report on a new land CM algorithm, which explicitly builds and maintains a reference clear‐skies image of the surface (refcm) using a time series of MODIS measurements. The new algorithm, developed as part of the multiangle implementation of atmospheric correction (MAIAC) algorithm for MODIS, relies on the fact that clear‐skies images of the same surface area have a common textural pattern, defined by the surface topography, boundaries of rivers and lakes, distribution of soils and vegetation, etc. This pattern changes slowly given the daily rate of global Earth observations, whereas clouds introduce high‐frequency random disturbances. Under clear skies, consecutive gridded images of the same surface area have a high covariance, whereas in presence of clouds covariance is usually low. This idea is central to initialization of refcm, which is used to derive cloud mask in combination with spectral and brightness temperature tests. The refcm is continuously updated with the latest clear‐skies MODIS measurements, thus adapting to seasonal and rapid surface changes. The algorithm is enhanced by an internal dynamic land–water–snow classification coupled with a surface change mask. An initial comparison shows that the new algorithm offers the potential to perform better than the MODIS MOD35 cloud mask in situations where the land surface is changing rapidly and over Earth regions covered by snow and ice.
Multiangle Implementation of Atmospheric Correction (MAIAC) is a new Moderate Resolution Imaging Spectroradiometer (MODIS) algorithm that combines time series approach and image processing to derive ...surface reflectance and atmosphere products, such as aerosol optical depth (AOD) and columnar water vapor (CWV). The quality assessment of MAIAC AOD at 1 km resolution is still lacking across South America. In the present study, critical assessment of MAIAC AOD(sub 550) was performed using ground-truth data from 19 Aerosol Robotic Network (AERONET) sites over South America. Additionally, we validated the MAIAC CWV retrievals using the same AERONET sites. In general, MAIAC AOD Terra/Aqua retrievals show high agreement with ground-based measurements, with a correlation coefficient (R) close to unity (R(sub Terra):0.956 and R(sub Aqua):0.949). MAIAC accuracy depends on the surface properties and comparisons revealed high confidence retrievals over cropland, forest, savanna, and grassland covers, where more than 2/3 (approximately 66%) of retrievals are within the expected error (EE = +/-(0.05 + 0.05 × AOD)) and R exceeding 0.86. However, AOD retrievals over bright surfaces show lower correlation than those over vegetated areas. Both MAIAC Terra and Aqua retrievals are similarly comparable to AERONET AOD over the MODIS lifetime (small bias offset approximately 0.006). Additionally, MAIAC CWV presents quantitative information with R approximatley 0.97 and more than 70% of retrievals within error (+/-15%). Nonetheless, the time series validation shows an upward bias trend in CWV Terra retrievals and systematic negative bias for CWV Aqua. These results contribute to a comprehensive evaluation of MAIAC AOD retrievals as a new atmospheric product for future aerosol studies over South America.
Using our decades-long experience in radiative transfer (RT) code development for Earth science, we endeavor to reduce the knowledge gap of bringing RT from theory to code quickly. Despite numerous ...classic and recent literature, it is still hard to develop an RT code from scratch within a few weeks. It is equally hard to understand, not to mention modify, an existing “monster” RT code, for which the developer is either located remotely or has retired. Following the format of “Numerical Recipes” by Press et al., we collocate in this paper small pieces of necessary theory with corresponding small pieces of RT code. These are arranged in an order that is natural for code development, which is often opposite of the natural order for laying out the theoretical basis. We focus on the transfer of unpolarized monochromatic solar radiation in a plane-parallel atmosphere over a reflecting surface. Both the surface and the atmosphere are homogeneous (uniform) at all directions. The multiple scattering is numerically solved using the deterministic method of Gauss-Seidel iterations. Except for the presented Python-Numba open-source RT code gsit, the paper does not report any new scientific results, but rather serves as an academic demonstration. If development time is an issue or the reader is familiar with basic concepts of RT theory, we recommend proceeding directly to Sec. 3 “RT code development”.
Program title: gsit (pronounced “jeezit”)
CPC Library link to program files:https://doi.org/10.17632/d3zt5zhx49.1
Developer's repository link:https://github.com/korkins/gsit
Licensing provisions: MIT
Programming language: Python 3
Nature of problem: We present a tutorial code in Python for deterministic (non-stochastic) numerical simulation of multiple scattering of monochromatic solar light in a plane-parallel Earth atmosphere bounded from below by a reflecting surface. The problem is solved in a simplified form (i.e., uniform atmosphere, no polarization, uniform surface reflectance, etc.) to better explain numerical features, rather than physics, of propagation of light in the atmosphere.
Solution method: The method of Gauss-Seidel iterations. It relies on the Fourier decomposition of the Radiative Transfer Equation over azimuth, Gauss quadrature for numerical integration over the zenith and iterative process for integration over height (optical depth) with analytical (hence known) single scattering approximation being the starting point. The method is relatively simple to code and does not require any external libraries.
Biomass burning is a source of fine particulate matter (PM2.5) air pollution, which adversely impacts human health. However, quantifying the health effects from biomass burning PM2.5 is difficult. ...Monitoring networks generally lack the spatial density needed to capture the heterogeneity of biomass burning smoke. Satellite aerosol optical depth (AOD) can be used to fill spatial gaps but does not distinguish surface‐level aerosols. Plume height (PH) observations may provide constraints on the vertical distribution of smoke and its impact on surface concentrations. We assessed PH characteristics from Multi‐Angle Implementation of Atmospheric Correction (MAIAC) and evaluated its correlation with colocated PM2.5 and AOD measurements. PH is generally highest over the western United States. The ratio PM2.5:AOD generally decreases with increasing PH:PBLH (planetary boundary layer height), showing that PH has the potential to refine surface PM2.5 estimates for collections of smoke events.
This article addresses the correction for aerosol effects in near‐simultaneous multi‐angle observations acquired by the Compact Reconnaissance Imaging Spectrometer for Mars (CRISM) aboard the Mars ...Reconnaissance Orbiter. In the targeted mode, CRISM senses the surface of Mars using 11 viewing angles, which allow it to provide unique information on the scattering properties of surface materials. In order to retrieve these data, however, appropriate strategies must be used to compensate the signal sensed by CRISM for aerosol contribution. This correction is particularly challenging as the photometric curve of these suspended particles is often correlated with the also anisotropic photometric curve of materials at the surface. This article puts forward an innovative radiative transfer‐based method named Multi‐angle Approach for Retrieval of Surface Reflectance from CRISM Observations (MARS‐ReCO). The proposed method retrieves photometric curves of surface materials in reflectance units after removing aerosol contribution. MARS‐ReCO represents a substantial improvement regarding previous techniques as it takes into consideration the anisotropy of the surface, thus providing more realistic surface products. Furthermore, MARS‐ReCO is fast and provides error bars on the retrieved surface reflectance. The validity and accuracy of MARS‐ReCO is explored in a sensitivity analysis based on realistic synthetic data. According to experiments, MARS‐ReCO provides accurate results (up to 10% reflectance error) under favorable acquisition conditions. In the companion article, photometric properties of Martian materials are retrieved using MARS‐ReCO and validated using in situ measurements acquired during the Mars Exploration Rovers mission.
Key PointsCorrection method for aerosol effects in CRISM/MRO multi‐angle observationsAccurate reflectance estimates are retrieved as surface anisotropy is consideredSurface reflectance estimates are provided with error bars
•We report numerical results for light reflection from the top of a Rayleigh scattering spherical atmosphere over a dark surface.•We account for polarization of light and height-dependent single ...scattering albedo.•We report single and multiple scattering data separately to support validation and development of RT codes for spherical atmospheres.
We report numerical results for polarized light reflection from the top of a Rayleigh scattering spherical atmosphere with height-dependent single scattering albedo over a dark surface. Michael Mishchenko considered this scenario back in the 1990’s, for a plane-parallel atmosphere of unit optical thickness (OT = 1), for which radiance errors arising from neglecting polarization reaches their highest values. To further extend Mishchenko's results, we consider a value of OT = 0.25, for which the effect of atmospheric curvature is pronounced. New results are generated using three state-of-the art radiative transfer (RT) codes. These are: the MYSTIC and MCSSA models, which simulate light scattering in a true-spherical atmosphere using Monte Carlo methods; and the discrete ordinate code VLIDORT, operating with a new multiple-scatter spherical correction designed to deliver reasonable approximations to spherical-medium scattering. In this work, we report results for both single and multiple scattering; this will help to support the validation of existing and future polarized spherical RT codes, especially those using approximative methods to deal with sphericity.
The Multi-Angle Implementation of Atmospheric Correction (MAIAC) algorithm makes aerosol retrievals from MODIS data at 1 km resolution providing information about the fine scale aerosol variability. ...This information is required in different applications such as urban air quality analysis, aerosol source identification etc. The quality of high resolution aerosol data is directly linked to the quality of cloud mask, in particular detection of small (sub-pixel) and low clouds. This work continues research in this direction, describing a technique to detect small clouds and introducing the "smoke test" to discriminate the biomass burning smoke from the clouds. The smoke test relies on a relative increase of aerosol absorption at MODIS wavelength 0.412 μm as compared to 0.47–0.67 μm due to multiple scattering and enhanced absorption by organic carbon released during combustion. This general principle has been successfully used in the OMI detection of absorbing aerosols based on UV measurements. This paper provides the algorithm detail and illustrates its performance on two examples of wildfires in US Pacific North-West and in Georgia/Florida of 2007.
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