Validation of CM SAF CLARA-A2 and SARAH-E Surface Solar Radiation Datasets over China

Wang, Yawen; Trentmann, Jörg; Yuan, Wenping; Wild, Martin

doi:10.3390/rs10121977

Cited by 25 publications

(20 citation statements)

References 56 publications

(114 reference statements)

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“…The overall accuracy of the CLARA-A2 SSR data records for China is documented in Wang et al [39]. We showed that the CLARA-A2 data overestimate the surface irradiance over China on average by 10.0 W m −2 .…”

Section: Resultssupporting

confidence: 62%

“…This is also indicated by the significantly positive correlations between the CLARA-A2 minus CMA SSR biases and the changes of AOD and API shown in Table 1. In addition to this, averaged for Beijing, the AOD climatology used in CLARA-A2 with a mean of 0.19 has largely underestimated the surface-based AERONET AODs with a mean of 0.71 (Figure 8), which could explain the large overestimation of SSR by 19.2 W m −2 [39]. Therefore, aerosols mainly dominate the bias series between surface-and satellite-based SSR, which in turn, could be used to infer aerosol information and quantify aerosol-driven changes in SSR.…”

Section: A Case Study Of Beijingmentioning

confidence: 96%

“…Efforts were made to further homogenize the datasets by picking out long-term records, and applying the physical threshold test [36,37] as well as the standard normal homogeneity test (SNHT, [38]). For details about the homogenization process, please refer to our previous study [39]. In the end, 59 stations across China were selected, as shown in Figure 1.…”

Section: The Cma Ssr Datasetmentioning

confidence: 99%

See 2 more Smart Citations

Improvement of Air Pollution in China Inferred from Changes between Satellite-Based and Measured Surface Solar Radiation

et al. 2019

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The air pollution crisis in China has become a global concern due to its profound effects on the global environment and human health. To significantly improve the air quality, mandatory reductions were imposed on pollution emissions and energy consumption within the framework of the 11th and 12th Five Year Plans of China. This study takes the first step to quantify the implications of recent pollution control efforts for surface solar radiation (SSR), the primary energy source for our planet. The observed bias between satellite-retrieved and surface-observed SSR time series is proposed as a useful indicator for the radiative effects of aerosol changes. This is due to the fact that the effects of temporal variations of aerosols are neglected in satellite retrievals but well captured in surface observations of SSR. The implemented pollution control measures and actions have successfully brought back SSR by an average magnitude of 3.5 W m−2 decade−1 for the whole of China from 2008 onwards. Regionally, effective pollution regulations are indicated in the East Coast regions of South and North China, including the capital Beijing, with the SSR brightening induced by aerosol reduction of 7.5 W m−2 decade−1, 5.2 W m−2 decade−1, and 5.9 W m−2 decade−1, respectively. Seasonally, the SSR recovery in China mainly occurs in the warm seasons of spring and summer, with the magnitudes induced by the aerosol radiative effects of 5.9 W m−2 decade−1 and 4.7 W m−2 decade−1, respectively.

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Section: Resultssupporting

confidence: 62%

Section: A Case Study Of Beijingmentioning

confidence: 96%

Section: The Cma Ssr Datasetmentioning

confidence: 99%

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Improvement of Air Pollution in China Inferred from Changes between Satellite-Based and Measured Surface Solar Radiation

et al. 2019

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“…Specifically, although the ground-based SSI data highlighted significant trends at most stations (slopes between −0.5 and 6.5 Wm −2 decade −1 ), the corresponding SARAH-2 and CLARA-A2 data did not show any significant trend: the slopes of the satellite records turned out to be in the intervals between 0.2 and 2.8 Wm 2 decade −1 and −0.4 and 3.8 Wm 2 decade −1 for SARAH-2 and CLARA-A2, respectively. The relevant role of aerosols in the comparison between satellite and ground-based SSI records has also been highlighted by Wang et al [31] for China. They reported a rather large bias for both SARAH-E (data from Meteosat East satellites) and CLARA-A2 records that largely decreased if the comparison between satellite and ground-based records was performed for rural stations only.…”

Section: Introductionmentioning

confidence: 70%

Comparison of Surface Solar Irradiance from Ground Observations and Satellite Data (1990–2016) over a Complex Orography Region (Piedmont—Northwest Italy)

et al. 2020

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Climate Monitoring Satellite Application Facility (CM SAF) surface solar irradiance (SSI) products were compared with ground-based observations over the Piedmont region (north-western Italy) for the period 1990–2016. These products were SARAH-2.1 (Surface Solar Radiation DataSet—Heliosat version 2.1) and CLARA-A2 (Cloud, Albedo and Surface Radiation dataset version A2). The aim was to contribute to the discussion on the representativeness of satellite SSI data including a focus on high-elevation areas. The comparison between SSI averages shows that for low OCI (orographic complexity index) stations, satellite series have higher values than corresponding ground-based observations, whereas for high OCI stations, SSI values for satellite records are mainly lower than for ground stations. The comparison between SSI anomalies highlights that satellite records have an excellent performance in capturing SSI day-to-day variability of ground-based low OCI stations. In contrast, for high OCI stations, the agreement is much lower, due to the higher uncertainty in both satellite and ground-based records. Finally, if the temporal trends are considered, average low-elevation ground-based SSI observations show a positive trend, whereas satellite records do not highlight significant trends. Focusing on high-elevation stations, the observed trends for ground-based and satellite records are more similar with the only exception of summer. This divergence seems to be due to the relevant role of atmospheric aerosols on SSI trends.

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“…The biases over northeastern China might be related to the fewer sampling and higher retrieval uncertainty of surface albedo induced by longtime coverage of snow in the cold seasons [19]. The reasons for discrepancies over northwestern and southwestern China are likely due to difficulty in evaluating AOD on the variable and high-albedo surface as well as the incapable consideration of elevation impacts on the satellite algorithms and degraded data quality under snow-cover surfaces [58]. For eastern China, the difference may result from an improper representation of AOD induced by rapid economic growth in this region [58,59].…”

Section: Validation Of the Ceres Dataset Using Cma Observationsmentioning

confidence: 99%

Potential Driving Factors on Surface Solar Radiation Trends over China in Recent Years

et al. 2021

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The annual mean surface solar radiation (SSR) trends under all-sky, clear-sky, all-sky-no-aerosol, and clear-sky-no-aerosol conditions as well as their possible causes are analyzed during 2005–2018 across China based on different satellite-retrieved datasets to determine the major drivers of the trends. The results confirm clouds and aerosols as the major contributors to such all-sky SSR trends over China but play differing roles over sub-regions. Aerosol variations during this period result in a widespread brightening, while cloud effects show opposite trends from south to north. Moreover, aerosols contribute more to the increasing all-sky SSR trends over northern China, while clouds dominate the SSR decline over southern China. A radiative transfer model is used to explore the relative contributions of cloud cover from different cloud types to the all-types-of-cloud-cover-induced (ACC-induced) SSR trends during this period in four typical sub-regions over China. The simulations point out that the decreases in low-cloud-cover (LCC) over the North China Plain are the largest positive contributor of all cloud types to the marked annual and seasonal ACC-induced SSR increases, and the positive contributions from both high-cloud-cover (HCC) and LCC declines in summer and winter greatly contribute to the ACC-induced SSR increases over East China. The contributions from medium-low-cloud-cover (mid-LCC) and LCC variations dominate the ACC-caused SSR trends over southwestern and South China all year round, except for the larger HCC contribution in summer.

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Validation of CM SAF CLARA-A2 and SARAH-E Surface Solar Radiation Datasets over China

Cited by 25 publications

References 56 publications

Improvement of Air Pollution in China Inferred from Changes between Satellite-Based and Measured Surface Solar Radiation

Improvement of Air Pollution in China Inferred from Changes between Satellite-Based and Measured Surface Solar Radiation

Comparison of Surface Solar Irradiance from Ground Observations and Satellite Data (1990–2016) over a Complex Orography Region (Piedmont—Northwest Italy)

Potential Driving Factors on Surface Solar Radiation Trends over China in Recent Years

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