MISR Aerosol Research Articles

Verification of CALIOP, MODIS, MISR, and OMI aerosol optical depth retrievals against Sun-photometer data over Zanjan

Verification of CALIOP, MODIS, MISR, and OMI aerosol optical depth retrievals against Sun-photometer data over Zanjan

Aerosol characteristics from earth observation systems: A comprehensive investigation over South Asia (2000–2019)

The present study summarizes two decades (2000–2019) of climatology and trends in aerosol loading and optical properties using a high spatial resolution data obtained from NASA's MODIS MAIAC and MISR aerosol products supplemented by moderate resolution aerosol data from OMI sensor over South Asia (SA). MISR AOD showed good agreement against AERONET AOD with 68.68% of the retrievals falling within the expected error and high Pearson's correlation coefficient (R = 0.83). The 20 years geometric mean of MAIAC and MISR AOD revealed higher loading of aerosols over the Indo-Gangetic Plain (IGP) and Eastern coast of India by 30% to 44% compared to the mean AOD over the entire SA. The highest mean AOD under cloud-free conditions was noted during monsoon season, followed by pre-monsoon, post-monsoon, and winter. The high contribution of coarse-mode AOD (cAOD) mainly from natural aerosol emission and small-mode AOD (sAOD) from local anthropogenic emissions are the main driver to high AOD in monsoon and pre-monsoon seasons. Besides, the presence of high humidity during the monsoon season favors the hygroscopic growth of the particles and leads to higher AOD values over SA. The high spatial resolutions of MODIS/MAIAC and MISR aerosol products enabled the identification of previously unobserved aerosol hotspots over Bihar, West Bengal, and the eastern Indian coastal state of Odisha, which is mainly dominated by small aerosol particles. The contributions of smaller aerosol particles to the total aerosol loading were found to be higher during post-monsoon and winter over most states in India, Nepal, and Bangladesh. In contrast, the contribution of coarser particles was higher over Pakistan during pre-monsoon and monsoon seasons. Smaller particles were predominantly retrieved over the Indian states dominated by mining industries, including Jharkhand and Odisha. A typical dominance of absorbing carbonaceous aerosols was also noted over the northwestern region of IGP during post-monsoon, which otherwise was mainly affected by mixed dust aerosols and carbonaceous aerosols in pre-monsoon and monsoon seasons. A statistically significant positive temporal trend in AOD was observed for the whole study period, over most of the SA region, which was influenced by the increase in small particles over India and Bangladesh. Urban/industrial weakly absorbing aerosols were found to be the main contributor to a similarly positive trend over Central India and East coast Indian states. Overall, recent advancements in high spatial resolution satellite-based aerosol optical properties showed good potential to identify the aerosol hotspots and constrain aerosol types across a highly polluted SA region.

CITY-LEVEL ADULT STROKE PREVALENCE IN RELATION TO REMOTE SENSING DERIVED PM2.5 ADJUSTING FOR UNHEALTHY BEHAVIORS AND MEDICAL RISK FACTORS

Abstract. This research explores the use of PM2.5 gird derived from remote sensing for assessing the effect of long-term exposure to PM2.5 (ambient air pollution of particulate matter with an aerodynamic diameter of 2.5 μm or less) on stroke, adjusting for unhealthy behaviors and medical risk factors. Health data was obtained from the newly published CDC “500 Cities Project” which provides city- and census tract-level small area estimates for chronic disease risk factors, and clinical preventive service use for the largest 500 cities in the United States. PM2.5 data was acquired from the “The Global Annual PM2.5 Grids from MODIS, MISR and SeaWiFS Aerosol Optical Depth (AOD), V1 (1998–2012)” datasets. Average PM2.5 were calculated for each city using a GIS zonal statistics function. Map data visualization and pattern comparison, univariate linear regression, and a multivariate linear regression model fitted using a generalized linear model via penalized maximum likelihood found that long-term exposure to ambient PM2.5 may increase the risk of stroke. Increasing physical activity, reducing smoking and body weight, enough sleeping, controlling diseases such as blood pressure, coronary heart disease, diabetes, and cholesterol, may mitigate the effect. PM2.5 grids derived from moderate resolution satellite remote sensing imagery may offer a unique opportunity to fill the data gap due to limited ground monitoring at broader scales. The evidence of raised stroke prevalence risk in high PM2.5 areas would support targeting of policy interventions on such areas to reduce pollution levels and protect human health.

Characterization of Wildfire‐Induced Aerosol Emissions From the Maritime Continent Peatland and Central African Dry Savannah with MISR and CALIPSO Aerosol Products

AbstractAerosol plumes from wildfires affect the Earth's climate system through regulation of the radiative budget and clouds. However, optical properties of aerosols from individual wildfire smoke plumes and their resultant impact on regional climate are highly variable. Therefore, there is a critical need for observations that can constrain the partitioning between different types of aerosols. Here we present the apparent influence of regional ecosystem types on optical properties of wildfire‐induced aerosols based on remote sensing observations from two satellite instruments and three ground stations. The independent observations commonly show that the ratio of the absorbing aerosols is significantly lower in smoke plumes from the Maritime Continent than those from Central Africa, so that their impacts on regional climate are different. The observed light‐absorbing properties of wildfire‐induced aerosols are explained by dominant ecosystem types such as wet peatlands for the Maritime Continent and dry savannah for Central Africa, respectively. These results suggest that the wildfire‐aerosol‐climate feedback processes largely depend on the terrestrial environments from which the fires originate. These feedbacks also interact with climate under greenhouse warming. Our analysis shows that aerosol optical properties retrieved based on satellite observations are critical in assessing wildfire‐induced aerosols forcing in climate models. The optical properties of carbonaceous aerosol mixtures used by state‐of‐the‐art chemistry climate models may overestimate emissions for absorbing aerosols from wildfires over the Maritime Continent.

XBAER-derived aerosol optical thickness from OLCI/Sentinel-3 observation

Abstract. A cloud identification algorithm used for cloud masking, which is based on the spatial variability of reflectances at the top of the atmosphere in visible wavelengths, has been developed for the retrieval of aerosol properties by MODIS. It is shown that the spatial pattern of cloud reflectance, as observed from space, is very different from that of aerosols. Clouds show a high spatial variability in the scale of a hundred metres to a few kilometres, whereas aerosols in general are homogeneous. The concept of spatial variability of reflectances at the top of the atmosphere is mainly applicable over the ocean, where the surface background is sufficiently homogeneous for the separation between aerosols and clouds. Aerosol retrievals require a sufficiently accurate cloud identification to be able to mask these ground scenes. However, a conservative mask will exclude strong aerosol episodes and a less conservative mask could introduce cloud contamination that biases the retrieved aerosol optical properties (e.g. aerosol optical depth and effective radii). A detailed study on the effect of cloud contamination on aerosol retrievals has been performed and parameters are established determining the threshold value for the MODIS aerosol cloud mask (3×3-STD) over the ocean. The 3×3-STD algorithm discussed in this paper is the operational cloud mask used for MODIS aerosol retrievals over the ocean. A prolonged pollution haze event occurred in the northeast part of China during the period 16–21 December 2016. To assess the impact of such events, the amounts and distribution of aerosol particles, formed in such events, need to be quantified. The newly launched Ocean Land Colour Instrument (OLCI) onboard Sentinel-3 is the successor of the MEdium Resolution Imaging Spectrometer (MERIS). It provides measurements of the radiance and reflectance at the top of the atmosphere, which can be used to retrieve the aerosol optical thickness (AOT) from synoptic to global scales. In this study, the recently developed AOT retrieval algorithm eXtensible Bremen AErosol Retrieval (XBAER) has been applied to data from the OLCI instrument for the first time to illustrate the feasibility of applying XBAER to the data from this new instrument. The first global retrieval results show similar patterns of aerosol optical thickness, AOT, to those from MODIS and MISR aerosol products. The AOT retrieved from OLCI is validated by comparison with AERONET observations and a correlation coefficient of 0.819 and bias (root mean square) of 0.115 is obtained. The haze episode is well captured by the OLCI-derived AOT product. XBAER is shown to retrieve AOT well from the observations of MERIS and OLCI.

Bayesian Merging of MISR and MODIS Aerosol Optical Depth Products Using Error Distributions From AERONET

Aerosol Optical depth (AOD) routinely retrieved by spaceborne sensors (e.g., MODIS and MISR) is widely used in studies focused on atmospheric aerosol characterization, their variability/trends, and environmental/climate impacts. Despite significant advancement in the understanding of aerosol loading patterns, there exist global/regional differences among AOD products from various satellite sensors; owing to differences in retrieval algorithms, spatial/temporal resolution and sampling, and cloud-screening schemes. A merged AOD dataset combining multiple satellite retrievals is therefore desirable, which utilizes the strengths of individual products, and at the same time reduces biases relative to ground-based measurements (e.g., from aerosol robotic network (AERONET)). In view of this, a Level-2 ‘‘merged’’ AOD dataset based on MODIS and MISR retrievals is developed in this study using Bayesian principles, which takes into account the error distribution of AOD from AERONET data. The merged AOD dataset is demonstrated over the Indo-Gangetic Plains, in southern Asia, and is intercompared with existing satellite and AERONET data. The RMSE of the merged AOD data (0.08–0.13) is lower than the MISR and MODIS retrievals. Additionally, the merged AOD data have higher correlation with AERONET data ( r within 0.89–0.93), compared to MISR (0.82–0.89) and MODIS (0.76–0.77) data. In terms of the expected error (EE), the accuracy of merged data is found to be higher, with larger percent of merged AOD within the EE envelope (74.7%–88.7%) compared to MISR (62.7%–84.9%) and MODIS (67.9%–69.8%) data. The merging methodology and resulting dataset are especially relevant in the scenario of fusing multisensor retrievals for producing long-term satellite-based climate data records.

Effect of aerosols loading and retention on surface temperature in the DJF months

The effect of aerosols loading most often results in aerosols retention in the atmosphere. Aside the health hazards of aerosol retention, its effect on climate change are visible. In this research, it was proposed that the effect of aerosol retention also affects the fluctuation of the surface temperature. The location of study is Enugu, Nigeria (6.4584° N, 7.5464° E). Twenty-nine years GISS Surface Temperature Analysis (GISTEMP) data set and sixteen years MISR aerosol optical data set were used. The fluctuations in the sixteen years aerosol optical depth (AOD) tallied with the surface temperature. The curve-fitting tool of Matlab was used to generate a polynomial for the surface temperature and used to project a five years prediction of the surface temperature.

Geographical Analysis of Lung Cancer Mortality Rate and PM2.5 Using Global Annual Average PM2.5 Grids from MODIS and MISR Aerosol Optical Depth

Exposure to particulate matter with an aerodynamic diameter of less than 2.5 μm (PM2.5) may increase risk of lung cancer. The repetitive and broad-area coverage of satellites may allow atmospheric remote sensing to offer a unique opportunity to monitor air quality and help fill air pollution data gaps that hinder efforts to study air pollution and protect public health. This geographical study explores if there is an association between PM2.5 and lung cancer mortality rate in the conterminous USA. Lung cancer (ICD-10 codes C34- C34) death count and population at risk by county were extracted for the period from 2001 to 2010 from the U.S. CDC WONDER online database. The 2001-2010 Global Annual Average PM2.5 Grids from MODIS and MISR Aerosol Optical Depth dataset was used to calculate a 10 year average PM2.5 pollution. Exploratory spatial data analyses, spatial regression (a spatial lag and a spatial error model), and spatially extended Bayesian Monte Carlo Markov Chain simulation found that there is a significant positive association between lung cancer mortality rate and PM2.5. The association would justify the need of further toxicological investigation of the biological mechanism of the adverse effect of the PM2.5 pollution on lung cancer. The Global Annual Average PM2.5 Grids from MODIS and MISR Aerosol Optical Depth dataset provides a continuous surface of concentrations of PM2.5 and is a useful data source for environmental health research.

Latest decade’s spatial–temporal properties of aerosols over China based on Multiangle Imaging SpectroRadiometer observations

The analysis of the spatial–temporal variability and trends of aerosols over China based on ∼11 years (February 2000 to December 2010) of Terra-Multiangle Imaging SpectroRadiometer (MISR) Level 3 aerosol products is the focus. The study shows that the MISR aerosol optical depth (AOD) is in good agreement with corresponding AOD from AERONET stations and suggests that MISR aerosol products have higher applicability compared with MODIS AOD products over China. The spatial–temporal distribution and trends for annual and seasonal AOD values over the middle and eastern regions of China are the main focus. The results of our analysis show the significant characteristics and seasonal variation of the aerosol distribution over the study areas. The seasonal distribution in AOD over the study areas is not consistent with the MODIS data. An insignificant trend (5.3%) is observed over the whole study area during the study period. The larger positive tendencies are found in the Yangtze River Delta and the Pearl River Delta (PRD); the values increased by 24.4% and 18% and are considered to be significant with a confidence level of >95% . However, in contrast to the recently reported negligible AOD trends of 0.002 per decade using MODIS data over Sichuan, significant increasing trends of 0.046 per 11 years for MISR over the same areas have been measured. The analysis of seasonal variation revealed the seasonal trend in the AOD and the main types of aerosols. During spring, the largest increasing trend (30.2%) is observed in the PRD with a stable composition of fine and coarse aerosols. A pronounced decreasing trend is found over Shanxi and decreased by −18.7% in spring during the period, which has not been previously reported. MODIS-Terra currently shows artificial negative AOD trends over land. Therefore, trends derived from MODIS-Terra may not reflect the realistic decadal aerosol changes and variability. The study shows that seasonal distribution and trend analyses are inconsistent when using MISR AOD products and MODIS AOD products over study areas, which indicates that the analysis of aerosol variation using MISR sensors is necessary.

Spatial and temporal distribution of MODIS and MISR aerosol optical depth over northern China and comparison with AERONET

Aerosol optical depths (AODs) from MODIS and MISR onboard the Terra satellite are assessed by comparison with measurements from four AERONET sites located in northern China for the period 2006–2009. The results show that MISR performs better than MODIS at the SACOL and Beijing sites. For the Xianghe and Xinglong sites, MODIS AOD retrievals are better than those of MISR. Overall, the relative error of the Angstrom exponent from MISR compared with AERONET is about 14%, but the MODIS error can reach 30%. Thus, it may be better to use the MISR Angstrom exponent to derive wavelength-dependent AOD values when calculating the aerosol radiative forcing in a radiative transfer model. Seasonal analysis of AOD over most of China shows two main areas with high aerosol loading: the Taklimakan Desert region and the southern part of North China and northern part of East China. The locations of these two areas of high aerosol loading do not change with season, but the AOD values have significant seasonal variation. The largest AOD value in the Taklimakan appears in spring when the Angstrom exponents are the lowest, which means the particle radii are relatively large. Over North and East China, the highest aerosol loading appears in summer. The aerosol particles are smallest in summer over both high-AOD areas.

Intra-Seasonal Variability of Aerosols and Their Radiative Impacts on Sahel Climate during the Period 2000-2010 Using AERONET Data

This paper presents a study using in situ measurements (AERONET data) to characterize the intra-seasonal variability of aerosols and their shortwave radiative impacts on Sahel (11N - 18N and 20W - 15E) climate using a long time series (2000 to 2010) from AERONET data. We first used the MISR aerosol optical depth (AOD) averaged between 2000 and 2010 to identify dust maxima regions. They are mainly located over Eastern Mauritania-Northern Mali and Eastern Niger-Western Tchad (near the Bodele depression). Moreover the aerosol loading is stronger during the spring (MAM) and particularly during the summer (JJA). The analysis of AERONET data at 4 Sahelian stations (Dakar, Agoufou, Banizoumbou and Ouagadougou) shows that Sahel is under dust influence all year long. The dust season is mainly located between March and October, with two peaks of AOD recorded in March and June; while the maximum of biomass burning activity is recorded in winter (December to February). The radiative forcing of aerosols on the Sahelian climate results mainly in a cooling as well as at the surface than at the top of the atmosphere (TOA) but the forcing is stronger at the surface and particularly during the summer (JJA) and spring (MAM) periods. Although there is not a sharp difference between DJF and SON periods from a station to another one when considering the aerosol loading (AOD), the radiative forcing is stronger at the surface and weaker at the TOA during DJF for most stations. The analysis of the force effectiveness (ratio between AOD and the radiative forcing) suggests that the BOA radiative forcing is mainly influenced by the nature of aerosols.

The inter-comparison of MODIS, MISR and GOCART aerosol products against AERONET data over China

Aerosols in East Asia have significant direct and indirect effects on the Earth's climate change. Several aerosol products have been generated to provide long-term monitoring of aerosol properties, but the discrepancies among them make the reliability of the products in doubt which leads to the uncertainty in the understanding of the long-time series of aerosols in East Asia, and especially in China. In this study, we investigate the applicability of Aerosol Optical Thickness (AOT) products derived from the measurements or model results of MODIS, MISR and GOCART through a statistical comparison, with Aerosol Robotic Network (AERONET) measurements over four sites located in China during a long-term period (2001–2011). Analysis shows that (1) only 43.06% of MODIS retrieved AOT values fall within ±(0.15τ+0.05) of the paired validation data from the AERONET for most sites, lower than the global averaged level (>66%) announced by Levy and Remer, in addition, MODIS/Terra shows a decreasing trend (−0.009/yr.) while MODIS/Aqua shows an increasing trend (+0.0012/yr.) and provides more stable AOT retrievals than MODIS/Terra during 2001–2011; (2) about 66.82% of MISR retrieved AOTs fall within the error envelop and MISR also shows a high correlation around 0.88 with AERONET data; (3) only 26.82% of GOCART model calculated AOTs fall within ±(0.15τ+0.05) of the paired validation data from the AERONET. GOCART also shows a low correlation (R=0.22–0.60) with AERONET data and thus cannot be well applied to total column AOT. Comparison of MODIS, MISR and GOCART products over the four sites in China and four sites located separately in Europe, North Africa and USA is carried out, which shows lower retrieval accuracy and larger discrepancy of products in China region. This is attributed to the fewer match-ups, larger aerosol load, moderate level of aerosol absorption and the complex nature of the aerosol mixtures. The analysis indicates the need for multiple-viewing-angle measurements of both intensity and polarization to provide the relevant aerosol parameters with sufficient accuracy for climate research.

A critical examination of spatial biases between MODIS and MISR aerosol products – application for potential AERONET deployment

Abstract. AErosol RObotic NETwork (AERONET) data are the primary benchmark for evaluating satellite-retrieved aerosol properties. However, despite its extensive coverage, the representativeness of the AERONET data is rarely discussed. Indeed, many studies have shown that satellite retrieval biases have a significant degree of spatial correlation that may be problematic for higher-level processes or inverse-emissions-modeling studies. To consider these issues and evaluate relative performance in regions of few surface observations, cross-comparisons between the Aerosol Optical Depth (AOD) products of operational MODIS Collection 5.1 Dark Target (DT) and operational MODIS Collection 5.1 Deep Blue (DB) with MISR version 22 were conducted. Through such comparisons, we can observe coherent spatial features of the AOD bias while sidestepping the full analysis required for determining when or where either retrieval is more correct. We identify regions where MODIS to MISR AOD ratios were found to be above 1.4 and below 0.7. Regions where lower boundary condition uncertainty is likely to be a dominant factor include portions of Western North America, the Andes mountains, Saharan Africa, the Arabian Peninsula, and Central Asia. Similarly, microphysical biases may be an issue in South America, and specific parts of Southern Africa, India Asia, East Asia, and Indonesia. These results help identify high-priority locations for possible future deployments of both in situ and ground based remote sensing measurements. The Supplement includes a kml file.

A global dataset of atmospheric aerosol optical depth and surface reflectance from AATSR

We present a new global dataset of aerosol properties and surface reflectance derived from the AATSR instrument for the period 2003–2009. The algorithm retrieves aerosol optical depth (AOD) and aerosol type over a wide variety of surfaces including ocean, vegetated land and desert. The AATSR dual-view allows retrieval without prior information about land surface reflectance. Results show global mean values of AOD at 550nm over land of 0.195, and over ocean of 0.137. The datasets are compared with sun photometer measurements from AERONET and the Maritime Aerosol Network (MAN), and with MODIS and MISR aerosol products. Agreement with AERONET (r=0.80; Δτ=±0.025±0.4τ) and MAN (r=0.97; Δτ=±0.04) was high. Estimates of aerosol coarse/fine mode classification where τ>0.2 show 71% correspondence over land and 81% over ocean. Monthly AOD from MODIS, MISR and AATSR showed close agreement over most regions. However, over deserts AATSR estimates were higher than MODIS or MISR, while over southern oceans both AATSR and MODIS were lower than MISR. Global composites show aerosol sources of desert dust, anthropogenic pollution, biomass burning, and their transport. Aerosol radiative forcing is a major source of uncertainty in climate modelling; this newly derived dataset gives spatially and temporally comprehensive fields of aerosol properties suitable to constrain global models and to analyse regional and global trends.

A decadal regional and global trend analysis of the aerosol optical depth using a data-assimilation grade over-water MODIS and Level 2 MISR aerosol products

Abstract. Using the ten-year (2000–2009) Data-Assimilation (DA) quality Terra MODIS and MISR aerosol products, as well as 7 years of Aqua MODIS, we studied both regional and global aerosol trends over oceans. This included both operational and data assimilation grade versions of the products. After correcting for what appears to be aerosol signal drift from the radiometric calibration of both MODIS instruments, we found MODIS and MISR agreed on a statistically negligible global trend of ±0.003/per decade. Our study also suggests that AODs over the Indian Bay of Bengal, east coast of Asia, and Arabian Sea show increasing trends of 0.07, 0.06, and 0.06 per decade for MODIS, respectively. These regional trends are considered as significant with a confidence level above 95%. Similar increasing trends were found from MISR, but with less relative magnitude. These trends reflect respective increases in the optical intensity of aerosol events in each region: anthropogenic aerosols over the east coast of China and Indian Bay of Bengal; and a stronger influence from dust events over the Arabian Sea. Negative AOD trends, low in confidence levels, are found off Central America, the east coast of North America, and the west coast of Africa, which indicate that longer periods of observation are necessary to be conclusive.

Evaluating aerosol optical properties observed by ground-based and satellite remote sensing over the Mediterranean and the Middle East in 2006

This study evaluates the spatial and temporal variation of the aerosol optical depth (AOD), the particle size characteristics (Ångström coefficients) and single scattering albedos during selected episodes over the Mediterranean area in 2006, based on independent observational datasets. We compare the satellite data of MODIS and MISR with those of the ground-based AERONET and in situ measurements. In general the yearly mean MODIS and MISR AODs as well as their temporal variation are in good agreement with AERONET. The highest AODs are caused by mineral dust outbreaks and the accumulation of anthropogenic aerosols during stagnant meteorological conditions. The comparison of MODIS with MISR aerosol optical properties for June corroborates that the AODs, Ångström coefficients and single scattering albedos agree well, and indicates the presence of high dust loads over the Mediterranean. Later in summer, however, MISR AOD is generally lower than MODIS, which is consistent with previous studies that show that MISR tends to underestimate and MODIS tends to overestimate AOD over land when compared to AERONET observations. Comparing MODIS Aqua Deep Blue with MISR for June over the Saharan desert reveals some differences in the location and the maxima of the AODs. Over the eastern Mediterranean highest dust loads occur during spring and autumn. Biomass burning activities around the Black Sea during July and August cause high AODs (e.g. by agricultural waste burning), and the particulate pollution is transported to the eastern Mediterranean and the Middle East by the prevailing northerly Etesian winds.

Response to “Toward unified satellite climatology of aerosol properties. 3. MODIS versus MISR versus AERONET”

A recent paper by Mishchenko et al. compares near-coincident MISR, MODIS, and AERONET aerosol optical depth (AOD), and gives a much less favorable impression of the utility of the satellite products than that presented by the instrument teams and other groups. We trace the reasons for the differing pictures to whether known and previously documented limitations of the products are taken into account in the assessments. Specifically, the analysis approaches differ primarily in (1) the treatment of outliers, (2) the application of absolute vs. relative criteria for testing agreement, and (3) the ways in which seasonally varying spatial distributions of coincident retrievals are taken into account. Mishchenko et al. also do not distinguish between observational sampling differences and retrieval algorithm error. We assess the implications of the different analysis approaches, and cite examples demonstrating how the MISR and MODIS aerosol products have been applied successfully to a range of scientific investigations.

Toward unified satellite climatology of aerosol properties.

We use the full duration of collocated pixel-level MODIS-Terra and MISR aerosol optical thickness (AOT) retrievals and level 2 cloud-screened quality-assured AERONET measurements to evaluate the likely individual MODIS and MISR retrieval accuracies globally over oceans and land. We show that the use of quality-assured MODIS AOTs as opposed to the use of all MODIS AOTs has little effect on the resulting accuracy. The MODIS and MISR relative standard deviations (RSTDs) with respect to AERONET are remarkably stable over the entire measurement record and reveal nearly identical overall AOT performances of MODIS and MISR over the entire suite of AERONET sites. This result is used to evaluate the likely pixel-level MODIS and MISR performances on the global basis with respect to the (unknown) actual AOTs. For this purpose, we use only fully compatible MISR and MODIS aerosol pixels. We conclude that the likely RSTDs for this subset of MODIS and MISR AOTs are ∼73% over land and ∼30% over oceans. The average RSTDs for the combined [AOT(MODIS)+AOT(MISR)]/2 pixel-level product are close to 66% and 27%, respectively, which allows us to recommend this simple blend as a better alternative to the original MODIS and MISR data. These accuracy estimates still do not represent the totality of MISR and quality-assured MODIS pixel-level AOTs since an unaccounted for and potentially significant source of errors is imperfect cloud screening. Furthermore, many collocated pixels for which one of the datasets reports a retrieval, whereas the other one does not may also be problematic.

Near-surface wind speed retrieval from space-based, multi-angle imaging of ocean sun glint patterns

The relationship between the MISR multi-angle observations of sun glint pattern width over ocean and the near-surface wind speed is explored. With this relationship, we develop an algorithm that can constrain the standard, wind-driven glint/white cap model that defines the ocean–surface boundary condition in MISR aerosol retrievals. The key geometric factor determining wind retrieval quality is the angular distance between the reflection vector and the closest MISR multi-angle observation — the minimum Sun Glint Angle (SGA). MISR-retrieved winds are within 2.4 m/s of buoy-measured values for minimum SGA below about 15° for the 38 cases studied, and usually better than 1.1 m/s, except one for which the wind speed was extremely low. For minimum SGA above about 15°, MISR angular glint pattern reflectance sampling is not adequate to perform wind retrievals. An ambiguity in the retrieval that can occur for minimum SGA greater than 6° or 7° is resolved by the minimum observed absolute reflectance. We also confirm the high accuracy of the Cox–Munk ocean surface reflectance model, used to analyze the glint pattern dependence on wind speed. The wind-retrieval method could be used in an operational multi-angle aerosol retrieval algorithm to dynamically constrain the ocean surface boundary condition when glint pattern angular sampling is adequate.

Application of satellite and ground-based data to investigate the UV radiative effects of Australian aerosols

An understanding of the effect of aerosols on biologically- and photochemically-active UV radiation reaching the Earth's surface is important for many ongoing climate, biophysical, and air pollution studies. In particular, estimates of the UV characteristics of the most common Australian aerosols will be valuable inputs to UV Index forecasts, air quality studies, and assessments of the impact of regional environmental changes. By analyzing climatological distributions of Australian aerosols we have identified sites where co-located ground-based UV-B and ozone measurements were available during episodes of relatively high aerosol activity. Since at least June 2003, surface UV global irradiance spectra (285–450 nm) have been measured routinely at Darwin and Alice Springs in Australia by the Australian Bureau of Meteorology (BoM). Using co-located sunphotometer measurements at Darwin and Alice Springs, we identified several episodes of relatively high aerosol activity. Aerosol air mass types were analyzed from sunphotometer-derived angstrom parameter, MODIS fire maps and MISR aerosol property retrievals. To assess aerosol effects we compared the measured UV irradiances for aerosol-loaded and clear-sky conditions with each other and with irradiances simulated using the libRadtran radiative transfer model for aerosol-free conditions. We found that for otherwise similar atmospheric conditions, smoke aerosols over Darwin reduced the surface UV irradiance by as much as 40–50% at 290–300 nm and 20–25% at 320–400 nm near active fires (aerosol optical depth, AOD, at 500 nm ∼ 0.6). Downwind of fires, the smoke aerosols over Darwin reduced the surface irradiance by 15–25% at 290–300 nm and ∼ 10% at 320–350 nm (AOD at 500 nm ∼ 0.2). The effect of smoke increased with decrease of wavelength and is strongest in the UV-B. The aerosol attenuation factors calculated for the selected cases suggest smoke over Darwin has an effect on surface 340–380 nm irradiances that is comparable to that produced by smoke over Sub-Saharan Africa. Dust activity was very low at Alice Springs during 2004, therefore we were not able to identify strong dust events to fully assess the UV effect of dust. For the cases studied, smoke aerosols seem to produce a stronger reduction in surface UV irradiances than dust aerosols.