Analysis on the impact of aerosol optical depth on surface solar radiation in the Shanghai megacity, China

Xu, Jianming; Li, C.; Shi, Huli; He, Qianshan; Pan, Liang

doi:10.5194/acp-11-3281-2011

Cited by 28 publications

(9 citation statements)

References 28 publications

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“…The optical depth of the atmosphere, whether due to clouds or aerosols, still presents a challenge to this work. The thickness of clouds and aerosols is a major factor in how much radiation can reach the surface [46][47][48]. The aim of this work was to test if standard machine-learning methods could accurately estimate SSR and PAR without this a priori information, and we have shown that they can within 20% error.…”

Section: Discussionmentioning

confidence: 99%

Intercomparison of Machine-Learning Methods for Estimating Surface Shortwave and Photosynthetically Active Radiation

Brown

Skakun

et al. 2020

Remote Sensing

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Satellite-derived estimates of downward surface shortwave radiation (SSR) and photosynthetically active radiation (PAR) are a part of the surface radiation budget, an essential climate variable (ECV) required by climate and vegetation models. Ground measurements are insufficient for generating long-term, global measurements of surface radiation, primarily due to spatial limitations; however, remotely sensed Earth observations offer freely available, multi-day, global coverage of radiance that can be used to derive SSR and PAR estimates. Satellite-derived SSR and PAR estimates are generated by computing the radiative transfer inversion of top-of-atmosphere (TOA) measurements, and require ancillary data on the atmospheric condition. To reduce computational costs, often the radiative transfer calculations are done offline and large look-up tables (LUTs) are generated to derive estimates more quickly. Recently studies have begun exploring the use of machine-learning techniques, such as neural networks, to try to improve computational efficiency. Here, nine machine-learning methods were tested to model SSR and PAR using minimal input data from the Moderate Resolution Imaging Spectrometer (MODIS) observations at 1 km spatial resolution. The aim was to reduce the input data requirements to create the most robust model possible. The bootstrap aggregated decision tree (Bagged Tree), Gaussian Process Regression, and Neural Network yielded the best results with minimal training data requirements: an R 2 of 0.77, 0.78, and 0.78 respectively, a bias of 0 ± 6, 0 ± 6, and 0 ± 5 W / m 2 , and an RMSE of 140 ± 7, 135 ± 8, and 138 ± 7 W / m 2 , respectively, for all-sky condition total surface shortwave radiation and viewing angles less than 55°. Viewing angles above 55° were excluded because the residual analysis showed exponential error growth above 55°. A simple, robust model for estimating SSR and PAR using machine-learning methods is useful for a variety of climate system studies. Future studies may focus on developing high temporal resolution direct and diffuse estimates of SSR and PAR as most current models estimate only total SSR or PAR.

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Section: Discussionmentioning

confidence: 99%

Intercomparison of Machine-Learning Methods for Estimating Surface Shortwave and Photosynthetically Active Radiation

Brown

Skakun

et al. 2020

Remote Sensing

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“…The impacts of absorption and scattering by aerosols can also be seen in changes of solar radiation at the surface (Li et al, 2011a;Xu et al, 2011). Analysis of data from about 200 meteorological observing stations showed significant decreases in sunshine duration over a large fraction of China [approximately 1% (10 yr) −1 averaged over the whole China] for the period 1954-98 (Kaiser and Qian, 2002).…”

Section: Reductions In Solar Radiation At the Surfacementioning

confidence: 96%

Climatic effects of air pollutants over china: A review

2014

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Tropospheric ozone (O 3 ) and aerosols are major air pollutants in the atmosphere. They have also made significant contributions to radiative forcing of climate since preindustrial times. With its rapid economic development, concentrations of air pollutants are relatively high in China; hence, quantifying the role of air pollutants in China in regional climate change is especially important. This review summarizes existing knowledge with regard to impacts of air pollutants on climate change in China and defines critical gaps needed to reduce the associated uncertainties. Measured monthly, seasonal, and annual mean surface-layer concentrations of O 3 and aerosols over China are compiled in this work, with the aim to show the magnitude of concentrations of O 3 and aerosols over China and to provide datasets for evaluation of model results in future studies. Ground-based and satellite measurements of O 3 column burden and aerosol optical properties, as well as model estimates of radiative forcing by tropospheric O 3 and aerosols are summarized. We also review regional and global modeling studies that have investigated climate change driven by tropospheric O 3 and/or aerosols in China; the predicted sign and magnitude of the responses in temperature and precipitation to O 3 /aerosol forcings are presented. Based on this review, key priorities for future research on the climatic effects of air pollutants in China are highlighted.

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“…The use of this climatology is one of the drawbacks of the HC1 and HC3, and especially HC3, whose high temporal resolution (15 min) is in principle well suited for monitoring and reproducing rapid changes in SSI. Aerosols have different scattering and absorbing properties according to their type and the spatial and temporal heterogeneity of their number, size, chemical composition, and shape (Elias and Roujean, 2008;Xu et al, 2011). These properties as well as total column content in water vapour and ozone may vary rapidly within a day or from day to day, thus influencing the SSI under clear skies.…”

Section: Introductionmentioning

confidence: 99%

Improving HelioClim-3 estimates of surface solar irradiance using the McClear clear-sky model and recent advances in atmosphere composition

Gschwind

Lefèvre

et al. 2014

Atmos. Meas. Tech.

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Abstract. The HelioClim-3 database (HC3v3) provides records of surface solar irradiation every 15 min, estimated by processing images from the geostationary meteorological Meteosat satellites using climatological data sets of the atmospheric Linke turbidity factor. This technical note proposes a method to improve a posteriori HC3v3 by combining it with data records of the irradiation under clear skies from the new McClear clear-sky model, whose inputs are the advanced global aerosol property forecasts and physically consistent total column content in water vapour and ozone produced by the MACC (Monitoring Atmosphere Composition and Climate) projects. The method is validated by comparison with a series of ground measurements for 15 min and 1 h for 6 stations and for daily irradiation for 23 stations. The correlation coefficient is large, greater than respectively 0.92, 0.94, and 0.97, for 15 min, 1 h and daily irradiation. The bias ranges from −4 to 4 % of the mean observed irradiation for most sites. The relative root mean square difference (RMSD) varies between 14 and 38 % for 15 min, 12 and 33 % for 1 h irradiation, and 6 and 20 % for daily irradiation. As a rule of thumb, the farther from the nadir of the Meteosat satellite located at latitude 0 • and longitude 0 • , and the greater the occurrence of fragmented cloud cover, the greater the relative RMSD. The method improves HC3v3 in most cases, and with no degradation in the others. A systematic correction of HC3v3 with McClear is recommended.

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Analysis on the impact of aerosol optical depth on surface solar radiation in the Shanghai megacity, China

Cited by 28 publications

References 28 publications

Intercomparison of Machine-Learning Methods for Estimating Surface Shortwave and Photosynthetically Active Radiation

Intercomparison of Machine-Learning Methods for Estimating Surface Shortwave and Photosynthetically Active Radiation

Climatic effects of air pollutants over china: A review

Improving HelioClim-3 estimates of surface solar irradiance using the McClear clear-sky model and recent advances in atmosphere composition

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