Intercomparison of MODIS, MISR, OMI, and CALIPSO aerosol optical depth retrievals for four locations on the Indo-Gangetic plains and validation against AERONET data

Bibi, Humera; Alam, Khan; Chishtie, Farrukh; Bibi, Samina; Shahid, Imran; Blaschke, Thomas

doi:10.1016/j.atmosenv.2015.04.013

Cited by 128 publications

(60 citation statements)

References 85 publications

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“…In general, the best skills of the evaluation of the satellite products against AERONET were found for MODIS, as also indicated in Myhre et al (2005) or Bibi et al (2015). Focusing on the results obtained during the Russian wildfires episode, 20 the best skills were obtained for the DB algorithm of MODIS (correlation values over 0.80 both from the Terra and Aqua platforms).…”

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confidence: 83%

An assessment of aerosol optical properties from remote sensing observations and regional chemistry-climate coupled models over Europe

Palacios-Peña¹,

Baró²,

Baklanov³

et al. 2017

Preprint

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Abstract. Atmospheric aerosols modify the radiative budget of the Earth due to their optical, microphysical and chemical properties, and are considered one of the most uncertain forcing agents. In order to characterise the uncertainties associated with satellite and modelling approaches to represent aerosol optical properties, their representation by different remote sensing sensors and regional online coupled chemistry-climate models over Europe is evaluated. This work also characterises whether the inclusion of aerosol-radiation (ARI) or aerosol-cloud interactions (ACI) helps improve the skills of modelling outputs. Regarding the uncertainty in the satellite representation of AOD, MODIS presented the best agreement with the AERONET observations compared to other satellite AOD observations. The differences found between remote sensing sensors highlighted the uncertainty in the observations, which have to be taken into account when evaluating models. When modelling results were considered, a common trend for underestimating high AOD levels was observed. For the AE, models tended to underestimate its variability, except when considering a sectional approach in the aerosol representation in the models. The modelling results 5showed better skills when ARI+ACI interactions were included; hence this improvement in the representation of AOD (above 30% in the model error) and AE (between 20 and 75%) is important to provide a better description of aerosol-radiation-cloud interactions in regional climate models.

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mentioning

confidence: 83%

An assessment of aerosol optical properties from remote sensing observations and regional chemistry-climate coupled models over Europe

Palacios-Peña¹,

Baró²,

Baklanov³

et al. 2017

Preprint

View full text Add to dashboard Cite

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“…DB performed better than the other dominant aerosol retrieval algorithm, Dark Target (DT), in Indo-Gangetic Plains [24]. The uncertainty of DB retrieval is dependent on geographical location and meteorological season.…”

Section: Datasets Usedmentioning

confidence: 99%

Novel Decomposition Scheme for Characterizing Urban Air Quality with MODIS

2017

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Urban air pollution is one of the most widespread global sustainability problems. Previous research has studied growth or fall of particulate matter (PM) levels using on-ground monitoring stations in urban regions. However, studying this worldwide is difficult because most cities do not have sufficient infrastructure to monitor air quality. Thus, satellite data is increasingly being employed to solve this limitation. In this paper, we use 16 years (2001)(2002)(2003)(2004)(2005)(2006)(2007)(2008)(2009)(2010)(2011)(2012)(2013)(2014)(2015)(2016) of aerosol optical depth (AOD) and Angstrom exponent (α) datasets, retrieved from MODIS (Moderate Resolution Imaging Spectroradiometer) sensors on the National Aeronautics and Space Administration's (NASA) Terra satellite to study air quality over 60 locations globally. We propose a novel technique, called AirRGB decomposition, to characterize urban air quality by decomposing AOD and α retrievals into 'components' of three distinct scenarios. In the AirRGB decomposition method, using AOD and α dataset three scenarios were investigated: 'R'-high α and high AOD, 'G'-high α and low AOD, and 'B'-low α and low AOD values. These scenarios were mapped and quantified over a triangular red, green and blue color scale. This visualization easily segregates regions having a high concentration of industrial aerosol from only natural aerosols. Our analysis indicates that a sharp divide exists between North American and European cities and Asian cities in terms of baseline pollution and slopes of R and G trends. We found that while pollution in cities in China has started to decrease (e.g., since 2011 for Beijing), it continues to increase in South Asia and Southeast Asia. e.g., R offset of Beijing and New Delhi was 54.98 and 50.43 respectively but R slope was −0.04 and 0.08 respectively. High offset (≥45) and slope (≥0.025) of B for New York, Tokyo, Sydney and Sao Paolo shows that they have clean air, which is still getting better.

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“…Kaskaoutis, et al [40] exhibited overall increasing trends in AOD (7.69%) with a high significance based on Aerosol Robotic Network (AERONET) measurements from 2001 to 2010 in northern India, which are consistent with satellite observations (MODIS) of increasing AOD and enhanced anthropogenic emissions over India. Moreover, Bibi, et al [41] also reported a high degree of correlation (above 0.7) between the inter-comparison of MODIS AOD and AERONET data in India. Figure 1b depicts the change in the vertically-averaged aerosol extinction coefficient at 532 nm during the study period.…”

Section: Of 17mentioning

confidence: 99%

Impacts of 3D Aerosol, Cloud, and Water Vapor Variations on the Recent Brightening during the South Asian Monsoon Season

et al. 2018

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South Asia is experiencing a levelling-off trend in solar radiation and even a transition from dimming to brightening. Any change in incident solar radiation, which is the only significant energy source of the global ecosystem, profoundly affects our habitats. Here, we use multiple observations of the A-Train constellation to evaluate the impacts of three-dimensional (3D) aerosol, cloud, and water vapor variations on the changes in surface solar radiation during the monsoon season (June-September) in South Asia from 2006 to 2015. Results show that surface shortwave radiation (SSR) has possibly increased by 16.2 W m −2 during this period. However, an increase in aerosol loading is inconsistent with the SSR variations. Instead, clouds are generally reduced and thinned by approximately 8.8% and 280 m, respectively, with a decrease in both cloud water path (by 34.7 g m −2 ) and particle number concentration under cloudy conditions. Consequently, the shortwave cloud radiative effect decreases by approximately 45.5 W m −2 at the surface. Moreover, precipitable water in clear-sky conditions decreases by 2.8 mm (mainly below 2 km), and related solar brightening increases by 2.5 W m −2 . Overall, the decreases in 3D water vapor and clouds distinctly result in increased absorption of SSR and subsequent surface brightening.

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Intercomparison of MODIS, MISR, OMI, and CALIPSO aerosol optical depth retrievals for four locations on the Indo-Gangetic plains and validation against AERONET data

Cited by 128 publications

References 85 publications

An assessment of aerosol optical properties from remote sensing observations and regional chemistry-climate coupled models over Europe

An assessment of aerosol optical properties from remote sensing observations and regional chemistry-climate coupled models over Europe

Novel Decomposition Scheme for Characterizing Urban Air Quality with MODIS

Impacts of 3D Aerosol, Cloud, and Water Vapor Variations on the Recent Brightening during the South Asian Monsoon Season

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