Cloud parameter retrievals from Meteosat and their effects on the shortwave radiation at the surface

A method based on Spinning Enhanced Visible and Infrared Imager (SEVIRI) measured reflectance at 0.6 and 3.9 µm is used to retrieve the cloud optical thickness (COT) and cloud effective radius (r_e) over the Iberian Peninsula. A sensitivity analysis of simulated retrievals to the input parameters demonstrates that the cloud top height is an important factor in satellite retrievals of COT and r_e with uncertainties around 10% for small values of COT and r_e; for water clouds these uncertainties can be greater than 10% for small values of r_e. The uncertainties found related with geometries are around 3%. The COT and r_e are assessed using well-known satellite cloud products, showing that the method used characterize the cloud field with more than 80% (82%) of the absolute differences between COT (r_e) mean values of all clouds (water plus ice clouds) centred in the range from ±10 (±10 µm), with absolute bias lower than 2 (2 μm) for COT (r_e) and root mean square error values lower than 10 (8 μm) for COT (r_e). The cloud water path (CWP), derived from satellite retrievals, and the shortwave cloud radiative effect at the surface (CRE_SW) are related for high fractional sky covers (F_sc >0.8), showing that water clouds produce more negative CRE_SW than ice clouds. The COT retrieved was also related to the cloud modification factor, which exhibits reductions and enhancements of the surface SW radiation of the order of 80% and 30%, respectively, for COT values lower than 10. A selected case study shows, using a ground-based sky camera that some situations classified by the satellite with high F_sc values correspond to situations of broken clouds where the enhancements actually occur. For this case study, a closure between the liquid water path (LWP) obtained from the satellite retrievals and the same cloud quantity obtained from ground-based microwave measurements was performed showing a good agreement between both LWP data set values.     

Validation of Ozone Monitoring Instrument NO2 measurements using ground based NO2 measurements at Zvenigorod,Russia

We present the results of comparison between Ozone Monitoring Instrument (OMI) data of NO₂ measurements (Collection 3) onboard the NASA EOS-Aura satellite and correlative ground-based twilight measurements at Zvenigorod station in Russia in 2004–2008. Compared quantities are unpolluted column and tropospheric column amounts of NO₂ which are standard products of OMI measurements. The NO₂ columns observed by our ground-based instrument have been interpolated to the time of OMI measurements using a one-dimensional photochemical model. According to our comparison, the OMI unpolluted NO₂ columns underestimate ground-based measurements by (0.084 ± 0.025)?×?10¹⁵ molecules/cm², or (3.2 ± 0.9)%. The correlation coefficient between the OMI and ground-based unpolluted NO₂ columns is 0.92. The tropospheric NO₂ columns derived from OMI measurements are on average by (1.8 ± 0.5)?×?10¹⁵ cm^?2, or approximately 40%, less than those derived from ground-based measurements. The correlation coefficient between these data is about 0.3. Reasons for this discrepancy are discussed.     

Intercomparisons of cloud-top and cloud-base heights from ground-based Lidar,CloudSat and CALIPSO measurements

This study presents results of the intercomparison of cloud-top height (CTH) and cloud-bottom height (CBH) obtained from a space-borne active sensor Cloud Profiling Radar (CPR), the Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP), the space-borne passive sensor Moderate Resolution Imaging Spectroradiometer (MODIS) and ground-based Lidar measurements. Three selected cases (one daytime and two night-time cases) involving various cloud conditions such as semi-transparent thin cirrus, opaque thick tropospheric clouds and multi-layered clouds are studied, with special attention to CBH. The space-based CALIOP provides reliable heights of thin high-altitude cirrus clouds containing small ice particles, but the 94 GHz CPR has low sensitivity to these clouds. The CTHs retrieved from the CPR and CALIOP for thick tropospheric clouds are in good agreement with each other. Discrepancies between the CPR and the CALIOP values of the CBH for thick opaque clouds arise from strong Lidar signal attenuations. In cloud-overlap conditions (i.e. multi-layered clouds are present), the CALIOP has difficulties in determining the cloud vertical structure (CVS) for thick clouds underlying thin cirrus clouds due to signal attenuations, whereas the CPR detects the CTH and CBH of both the cloud layers. This fact is also confirmed by the comparison of seasonal variations of occurrences of CBH and CTH retrieved from 1 year measurements. The CBHs derived from the CPR and ground-based Lidar are generally in good agreement with each other. Especially, comparison of CBH between the ground-based Lidar and CPR retrieved from June 2006 to October 2008 shows an excellent linear relationship (coefficient of determination, R ² ～ 0.996).     

Impact of MODIS-derived cloud cover on aerosol optical depth measured with a sun photometer: a case study from Nanjing,China

Sun photometers have been used increasingly to monitor the atmospheric environment by measuring indicators such as aerosol optical depth (AOD). However, ground-measured AOD results are subject to the presence of clouds in the air. When cloud cover is not extensive, it is still possible to use sun photometry to determine AOD, even though accuracy is reduced by cloud contamination. This research aims to detect cloud cover from Moderate Resolution Imaging Spectroradiometer (MODIS) data and then assess its impact on in situ-measured AOD. Normalized difference cloud index (NDCI) and linear spectral unmixing (LSU) were used to detect cloud cover from MODIS data. AOD at the time of acquisition of MODIS data was measured on the ground by sun photometry within 20 min of satellite overpasses (10 min before and 10 min after). Correlation analysis of NDCI- and LSU-derived cloud cover with in situ-measured AOD data demonstrates that LSU has a higher correlation coefficient with AOD than with NDCI. At 550 nm, a unit of cloud cover (e.g. 1%) raises ground-observed AOD by 0.0157. The findings of this study can be used to modify ground-derived AOD results to improve their reliability.     

Evaluation of optical satellite remote sensing for rice paddy phenology in monsoon Asia using a continuous in situ dataset

In monsoon Asia, optical satellite remote sensing for rice paddy phenology suffers from atmospheric contaminations mainly due to frequent cloud cover. We evaluated the quality of satellite remote sensing of paddy phenology: (1) through continuous in situ observations of a paddy field in Japan for 1.5 years, we investigated phenological signals in the reflectance spectrum of the paddy field; (2) we tested daily satellite data taken by Terra/Aqua MODIS (MOD09 and L1B products) with regard to the agreement with the in situ data and the influence of cloud contamination. As a result, the in situ spectral characteristics evidently indicated some phenological changes in the rice paddy field, such as irrigation start, padding, heading, harvest and ploughing. The Enhanced Vegetation Index (EVI) was the best vegetation index in terms of agreement with the in situ data. More than 65% of MODIS observations were contaminated with clouds in this region. However, the combined use of Terra and Aqua decreased the rate of cloud contamination of the daily data to 43%. In conclusion, the most robust dataset for monitoring rice paddy phenology in monsoon Asia would be daily EVI derived from a combination of Terra/MODIS and Aqua/MODIS.     

Wind and cloud cover effects on spectral measurements of flooded rice crops in red and near-infrared SPOT-HRV bands

Wind and cloud cover effects on variabilities of radiance, irradiance and reflectance were analysed using ground-based measurements acquired over flooded rice crops in the red and near-infrared SPOT-HRV bands under variable wind and cloud cover conditions. Overall, spectral measurements were more variable in the near-infrared than in the red band. Wind speed was positively correlated to variability of radiances (r=0.186 (p>0.001)) and reflectances (r= 0.245 (p>0.001)) in near-infrared, but not in red wavelengths. The proportion of diffuse radiation in the total incident solar radiation was positively correlated to the radiance variability in red (r=0.086 (p>0.001)) and near-infrared (r=0.123 (p>0.001)) as well as to the irradiance variability in red (r=0.248 (p>0.001)) and near-infrared (r=0.243 (p>0.001)), but not to the reflectance variability. Such an analysis should be done every time ground spectral measurements are performed under variable weather conditions.     

First results of ground-based Fourier Transform Infrared measurements of the H2O total column in the atmosphere over West Siberia

The first results of the water vapour total column (WVTC) Fourier Transform Infrared (FTIR) measurements carried out over West Siberia (near Tomsk) in the framework of the combined experiment (22 May 2012) are presented. Direct solar radiation spectra with high spectral resolution were recorded by ground-based FTIR spectrometer Bruker IFS-125M. New spectral intervals (the advantage of this spectral band is that observations could be performed without cooling the interferometer’s detector) were tested and then used to retrieve the H₂O total columns in the atmosphere by SFIT2 v3.92. Ground-based measurements of the WVTC and aerosol optical thickness in the atmosphere were carried out by means of the automated sun photometers (SP series). Sun photometer and FTIR observations were performed under clear-sky conditions. During this study, we compared data obtained from ground-based remote sensing systems to the results of infrared atmospheric sounding interferometer (IASI) MetOP-A satellite measurements and airborne measurements with the use of the Tu-134 aircraft laboratory. Comparison shows that FTIR observations could give reasonable agreements with sun photometer data within 1%. This value is less than the combined error (1.2%) of both techniques. The average values of total H₂O obtained for three measurement systems were as follows: 1.50 and 1.49 g cm^–2 for the Fourier spectrometer and sun photometer, respectively, and 1.84 g cm^–2 for IASI.     

Satellite-derived UV irradiance for a region with complex morphology and meteorology: comparison against ground measurements in Santiago de Chile

Ground-based measurements of ultraviolet (UV) irradiance, carried out by a four-channel UV radiometer in Santiago de Chile from October 2004 to December 2011, have been used to estimate daily values of the UV index (UVI). These ground-based data have been compared with UVI estimates retrieved from the Ozone Measurement Instrument (OMI) on board the Aura spacecraft. Since the widely used OMI-gridded UVI data may not be suitable for the complex local morphology and meteorology, a careful screening of overpass OMI data was applied.

Nevertheless, we found that OMI-derived UVI data overestimate ground-based values; depending on cloud-cover conditions, the mean bias (MB) and the root mean square error (RMSE) range from 34.53% to 30.29% and from 35.22% to 43.50%, respectively, with the lowest MB (and the highest RMSE) values occurring under overcast conditions. Moreover, the difference between satellite-derived and ground-based UVI data exhibits a limited seasonality with somewhat larger differences in the fall season. The detected overestimation seems to be linked with the boundary layer aerosol absorption that is not accounted for by the OMI algorithm. Indeed, we found that the difference in UVI increases with the aerosol concentration (which in Santiago shows seasonal variations). Ceilometer profiles of backscatter intensities, directly related to aerosol concentrations, and PM10 concentrations correlate with UVI differences (correlation coefficient r of approximately 0.6 and 0.4, respectively) under cloud-free conditions for time scales ranging from months to years.

Additional comparisons were performed between UVI estimates retrieved from our ground-based measurements in Santiago and from the Tropospheric Emission Monitoring Internet Service (TEMIS) Scanning Imaging Absorption Spectrometer for Atmospheric Cartography (SCIAMACHY). Under cloudless conditions, also TEMIS-derived data overestimate ground-based UVI estimations (by about 31%) and exhibit a small seasonality.     

Inter-comparison of INSAT-3D atmospheric motion vectors height with cloud-base height from a Ceilometer

ABSTRACT

The atmospheric motion vectors (AMV) are derived by tracking cloud and moisture features in the subsequent images of geostationary as well as polar satellites. The heights of the AMVs are nothing but the height of cloud tracers used during the retrieval process for tracking. This height is derived using different complex techniques. In this study, a detailed comparison has been performed with the use of ground-based cloud-base height (CBH) measurements from ceilometer CL31, installed at Ahmedabad (23.03°N, 72.54°E), India and height assigned to AMVs which are retrieved from INSAT-3D satellite images. Six months CBH measurement over Ahmedabad from ceilometer CL31 has been used to inter-compare the co-located AMV heights. Although both ground-based and satellite-based techniques have their own limitations, however, it is found from this study that the ceilometer is an excellent instrument to precisely detect low- and mid-level clouds and height-assignments technique of AMVs retrieved from INSAT-3D satellite provides all high-, mid- and low-levels cloud information over this region. As an example, it is found that AMVs height of INSAT-3D is about 867.92, 750.00 and 465.09 hPa on 26 May 2014, 7 July 2014 and 29 October 2014, respectively, which matches very closely with ceilometer-measured CBH of about 873.15, 769.16 and 507.44 hPa, respectively. However, in case multi-level clouds present on rainy days, CBH measurements from ceilometer are differing from INSAT-3D AMV cloud tracer heights.     

Temporal and spatial variability of total ozone column using TOMS satellite observations and comparison with measurements from the Dobson network

This article presents a detailed analysis of seasonal and interannual variability of total ozone content (TOC) at 16 different stations in Africa using Nimbus-7 Total Ozone Mapping Spectrometer (TOMS) data for a period of 14 years (January 1979–December 1992). The analysis provides not only an estimate of the long-term annual and seasonal trends but also statistics of means and variability of ozone on temporal and spatial scales. For example, high negative deviations were observed for stations in Northern Africa in spring (March–May), with as much as –20 DU in Alexandria. A comparison of total ozone column data retrieved from the TOMS satellite with measurements obtained from the Dobson ground-based network is further presented for Cairo, Irene, Nairobi and Springbok. Estimates of the percentage seasonal difference between TOMS satellite and Dobson ground-based measurements reveal that the ground measurements were higher in magnitude at all stations with the exception of Nairobi. To verify the level of correlation between the ground-based and satellite observations, rank correlation coefficients were determined for all stations using daily and monthly observations. The results show that there is good correlation between the compared data sets, with daily coefficient of determination (r ²) values of 0.87, 0.76, 0.58 and 0.87 for Cairo, Irene, Nairobi and Springbok, respectively.     

Estimating surface solar irradiance from METEOSAT SEVIRI-derived cloud properties

A satellite retrieval of surface solar irradiance based on METEOSAT SEVIRI-derived cloud properties is presented and validated for the Netherlands with one year of pyranometer measurements from 35 stations. The approach requires two independent steps: 1. Cloud properties are determined from narrow-band satellite radiances. 2. These cloud properties are used together with data on water vapor column and surface albedo to calculate the atmospheric flux transmittance. The retrieved irradiance is biased low by about 3-4 W/m² throughout the year, corresponding to an underestimate in atmospheric flux transmittance of about 0.015 in summer and 0.04 in winter. From a least-squares linear regression, residual standard deviations of 56 W/m² (0.072, 17.0%), 11 W/m² (0.052, 10.8%), and 4 W/m² (0.021, 4.2%) are found for hourly, daily and monthly mean irradiance (transmittance, relative error), respectively. These findings indicate that the accuracy of the retrieval is comparable to first-class pyranometers in the summer half year (5% of daily-mean values), but significantly lower in winter. Two aspects requiring further investigation have been identified: 1. For thin clouds, the atmospheric flux transmittance is strongly underestimated. 2. The retrieval accuracy is reduced for snow-covered surfaces.     

SCIAMACHY/Envisat,OMI/Aura,and ground-based total ozone measurements over Kyiv-Goloseyev station

Validation of satellite ozone measurements is important for data improvement due to instrumental long-term drifts and retrieval algorithm limitations. For satellite data quality estimation, we compare the total ozone content (TOC) derived from the satellite Scanning Imaging Absorption Spectrometer for Atmospheric Chartography (SCIAMACHY)/Envisat and Ozone Monitoring Instrument (OMI)/Aura spectrometer overpass data and the ground-based measurements made with the Dobson spectrophotometer 040 at the GAW station No. 498 Kyiv-Goloseyev. The station was opened for Dobson ozone measurements in 2010. The results for Direct Sun, Zenith Blue, and Zenith Cloud observations are presented separately, in order to assess the influence of weather conditions (clear or cloudy sky) on the difference between satellite and ground-based measurements. Results from the SCIAMACHY–Dobson and OMI–Dobson difference analyses show small relative overestimation of TOC for satellite data. The ground-based Dobson 040 data are of high quality for Direct Sun and Zenith Blue from AD ((305.5 and 325.0 nm) and (317.5 and 339.9 nm)) pair measurements. Seasonal variations of the difference are seen with maximal satellite–Dobson data discrepancy near the winter solstice. Satellite TOC values are systematically higher than Dobson ones at solar zenith angles larger than 70°. This difference could be explained by seasonal non-uniformity in the satellite data.     

Comparison of total ozone column observations from space-borne Ozone Monitoring Instrument with ground-based Dobson Ozone Spectrophotometer measurements at an urban location in Indo-Gangetic Basin

This article presents a comparison analysis of OMIT (Ozone Monitoring Instrument retrieved overpass total ozone column (TOC)), and DOST (Dobson Ozone Spectrophotometer observed TOC) over Delhi during a period from October 2004 to June 2011. Megacity Delhi, located in Indo-Gangetic Basin, is an important site for comparison of ground-based and satellite retrieved TOCs due to significant anthropogenic emissions of ozone precursors, large shift in seasons, and large-scale crop residue burning in the region. DOST and OMIT data show an overall bias of 3.07% and significant correlation with coefficient of determination R² = 0.73. Large seasonal fluctuations in the biases and correlations have been observed ranging from 2.46% (winter) to 3.82% (spring), and R² = 0.84 (winter) to R² = 0.09 (summer), respectively. The large biases are attributed to changes in temperature, cloud cover, pollutants emissions from urban area, and crop-residue burning events. We also find notable variations in correlations between the datasets due to the varying burden of absorbing aerosols from open field crop-residue burning. The R² has changed from 0.67 (for aerosol optical depth, AOD 1.5–3.5) to 0.77 (for AOD 0–0.99). The dependence of the bias on solar zenith angle, cloud fraction, and satellite distance is also discussed. A simple linear regression analysis is applied to check the linkage between DOST and OMIT. The influence of atmospheric air temperature and relative humidity on OMIT at different pressure levels between 1000 and 20 hPa has been discussed.     

Improving estimates of fractional vegetation cover based on UAV in alpine grassland on the Qinghai–Tibetan Plateau

Fractional vegetation cover (FVC) is an important parameter in studies of ecosystem balance, soil erosion, and climate change. Remote-sensing inversion is a common approach to estimating FVC. However, there is an important gap between ground-based surveys (quadrat level) and remote-sensing imagery (satellite image pixel scale) from satellites. In this study we evaluated that gap with unmanned aerial vehicle (UAV) aerial images of alpine grassland on the Qinghai–Tibetan Plateau (QTP). The results showed that: (1) the most accurate estimations of FVC came from UAV (FVC_UAV) at the satellite image pixel scale, and when FVC was estimated using ground-based surveys (FVC_ground), the accuracy increased as the number of quadrats used increased and was inversely proportional to the heterogeneity of the underlying surface condition; (2) the UAV method was more efficient than conventional ground-based survey methods at the satellite image pixel scale; and (3) the coefficient of determination (R²) between FVC_UAV and vegetation indices (VIs) was significantly greater than that between FVC_ground and VIs (p < 0.05, n = 5). Our results suggest that the use of UAV to estimate FVC at the satellite image pixel scale provides more accurate results and is more efficient than conventional ground-based survey methods.     

On the applicability of the Heliosat-2 method to assess surface solar irradiance in the Intertropical Convergence Zone,French Guiana

Measurements of daily means of surface solar irradiance made at four ground stations in French Guiana are compared to estimates from the HelioClim-3 database produced by the Heliosat-2 method applied to Meteosat satellite images. The bias ranges from 12 W m^?2 (6% of the mean of measurements) to 23 W m^?2 (12%), depending on the stations. The root mean square difference ranges between 23 W m^?2 (11%) and 35 W m^?2 (18%). The correlation coefficient (r) is close to 0.9. Better results are observed during the rainy season than during the dry season. Uncertainties are mainly due to the presence of clouds, large viewing angles of the Meteosat satellite, and limitations of the atmospheric transmittance model under the tropical atmospheric conditions. It is concluded that the Heliosat-2 method provides new knowledge about solar radiation in French Guiana.     

Satellite and surface-based remote sensing of Saharan dust aerosols

The spatial and temporal characteristics of dust aerosols and their properties are assessed from satellite and ground-based sensors. The spatial distribution of total column aerosol optical depth at 550 nm (AOD) from the Moderate Resolution Imaging SpectroRadiometer (MODIS) coupled with top of atmosphere Clouds and the Earth's Radiant Energy System (CERES) shortwave fluxes are examined from the Terra satellite over the Atlantic Ocean. These data are then compared with AOD from two Aerosol Robotic Network (AERONET) ground-based sun photometer measurement sites for nearly six years (2000-2005). These two sites include Capo Verde (CV) (16°N, 24°W) near the Saharan dust source region and La Paguera (LP) (18°N, 67°W) that is downwind of the dust source regions. The AOD is two to three times higher during spring and summer months over CV when compared to LP and the surrounding regions. For a unit AOD value, the instantaneous TOA shortwave direct radiative effect (DRE) defined as the change in shortwave flux between clear and aerosol skies for CV and LP are − 53 and − 68 Wm^− 2 respectively. DRE for LP is likely more negative due to fall out of larger particles during transport from CV to LP. However, separating the CERES-derived DRE by MODIS aerosol effective radii was difficult. Satellite and ground-based dust aerosol data sets continue to be useful to understand dust processes related to the surface and the atmosphere.     

Mesoscale cloud pattern classification over ocean with a neural network using a new index of cloud variability

The purpose of this study is to determine the feasibility of a mesoscale (<300 km) cloud classification using infrared radiance data of satellite‐borne instruments. A new method is presented involving an index called the diversity index (DI), derived from a parameter commonly used to describe ecosystem variability. In this respect, we consider several classes of value ranges of standard deviation of the brightness temperature at 11 µm (σ_BT). In order to calculate DI for 128×128 km² grids, subframes of 8 km×8 km are superimposed to the satellite image, and then σ_BT is calculated for all 256 subframes and assigned to one of the classes. Each observed cloud pattern is associated with an index characterized by the frequency of σ_BT classes within the scene, representative of a cloud type. Classification of different clouds is obtained from Advanced Very High Resolution Radiometer (AVHRR)‐NOAA 16 data at 1 km resolution. Stratus, stratocumulus and cumulus are specifically recognized by this window analysis using a DI threshold. Then, a six‐class scheme is presented, with the standard deviation of the infrared brightness temperature of the entire cloud scene (σ_c) and DI as inputs of a neural network algorithm. This neural network classifier achieves an overall accuracy of 77.5% for a six‐class scheme, and 79.4% for a three‐class scheme, as verified against the analyses of nephanalists as verified against a cloud classification from Météo France. As an application of the proposed methodology, regional cloud variability over Pacific is examined using cloud patterns derived from the Moderate Resolution Imaging Spectroradiometer (MODIS) carried aboard Earth Observing System (EOS) Terra polar orbiter platform, for February 2003 and 2004. The comparison shows regional change in monthly mean cloud types, associated with 2003 El Niño and 2004 neutral events. A significant increase in the occurrence of convective clouds (+15%) and a decrease in stratiform clouds (?10%) are observed between the two months.     

A dispersed approach to a central problem

Clouds are important modulators of UV radiation, but quantification of their effects has been limited. This preliminary study assesses satellite-derived fractional cloud cover as an estimator of cloud effects on UV radiation measured at Lauder, New Zealand. Although there is a good correlation between measures of cloud cover from satellite and from the ground, their correlation with surface irradiance in either the visible or UV parts of the spectrum is found to be weaker. Measurement of fractional cloud cover alone is inadequate to parameterize cloud effects on incoming radiation. In particular, knowledge of whether or not the Sun is obscured is required, while estimates of cloud optical depth also appear to be important. The strong correlation between UV and visible radiation suggests that the use of ground-based pyranometer data to infer cloud effects on UV radiation is more accurate than the use of presently available satellite data for process studies of the relationship between cloud cover and instantaneous UV measurements at a particular location.     

Trends of night-time hourly cloud-cover values over Manila Observatory: ground-based remote-sensing observations using a digital camera for 13 months

ABSTRACT

Night-time cloud detection provides data sets of cloud-cover percentage. Although night-time cloud-cover data sets from satellite-based instruments are common, these data sets do not have relatively high temporal resolution. To quantify local temporal cloud-cover variability and to attain long-term cloud-cover measurements, ground-based instruments would be the appropriate apparatus. In this study, a digital camera is used to continuously gather images of the night sky at 5-min intervals over Manila Observatory (14.64° N, 121.07° E). For the first time in Manila, ground-based remote-sensing data gathered from October 2015 to October 2016 are analysed for hourly cloud cover. The results indicate that wet season has relatively higher cloud-cover values (median >40%) as compared to the dry season (median <40%). Moreover, cloud-cover values are observed to decrease during the night. For the wet season, August having the highest cloud-cover values has the highest value of change of hourly cloud-cover percentage (?0.82% h^?1). For the dry season, February having the lowest cloud-cover values has the highest value of change of hourly cloud-cover percentage (?1.04% h^?1).     

Ozone Monitoring Instrument aerosol products: a comparison study with ground-based airborne sun photometer measurements over Europe

Airborne sun photometer measurements are used to evaluate retrievals of extinction aerosol optical depth (AOD). These data are extracted from spatially coincident and temporally near-coincident measurements by the Ozone Monitoring Instrument (OMI) aboard the Aura satellite taken during 2005. OMI-measured top of atmosphere (TOA) reflectances are routinely inverted to yield aerosol products such as AOD using two different retrieval techniques: the Aura OMI Near-Ultraviolet Aerosol Data Product, OMAERUV, and the multi-wavelength Aura OMI Aerosol Data Product, OMAERO. In this work, we propose a study that specifically compares the instantaneous aerosol optical thicknesses retrieved from OMI at several locations containing sites and those of the Aerosol Robotic Network (AERONET). The result of the comparison shows that, just over Europe, OMI aerosol optical thicknesses are better retrieved in the multi-wavelength retrieval than in the near-ultraviolet. Correlations have been improved by applying a simple criterion to avoid scenes probably contaminated by thin clouds, and surface scattering. The ultraviolet irradiance positive bias in the OMI data is corrected using a procedure based on global climatological fields of aerosol absorption optical depth. The results generally show a bias significantly reduced by 5–20%, a lower variability and an unchanged, high correlation coefficient.