Evaluation of downward surface solar radiation of three reanalysis products over China from 1979 to 2008

Wu, Xiaocui; Ju, Weimin; Zhou, Yang; Zhou, Bo; Liu, Yibo

doi:10.1201/b18566-144

Cited by 3 publications

(3 citation statements)

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“…Using the best records of historic surface radiation data and trends by Sun duration observed data, this study presents a comprehensive analysis of the performance of five reanalyses commonly used in atmospheric research with regard to geographically distributed surface solar radiation trends over China. Our results show that all five reanalyses are wrong in the same direction with regard to R s , regardless of the different methods and parameterizations used for CF and aerosols, which are consistent with previous findings (Jia et al, ; Wang et al, ; Wu et al, ; Xia et al, ). This is largely because the current climate models have difficulty simulating low‐level clouds, such as stratus clouds in southern China (Yu et al, ; Yu et al, ).…”

Section: Discussionsupporting

confidence: 93%

“…The radiative fluxes from the reanalyses are widely used as forcing data in many climate models (Essou et al, 2017). However, R s reanalyses contain substantial biases (Slater, 2016;Wang et al, 2015;Wu et al, 2015) due to the uncertainties in clouds and aerosols in the reanalyses (Fujiwara et al, 2017). Complete knowledge of the interactions among clouds, aerosols and radiation, and the related parameterizations in the climate models or reanalyses can help to reduce the uncertainty in predicting potential future climate changes, especially at regional scales (Loew et al, 2016;Zadra et al, 2018).…”

Section: Introductionmentioning

confidence: 99%

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Determining Factors of Monthly to Decadal Variability in Surface Solar Radiation in China: Evidences From Current Reanalyses

Feng

Wang

2019

JGR Atmospheres

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Clouds and aerosols play essential roles in regulating surface incident solar radiation (Rs). It has been suggested that the increased aerosol loading over China is a key factor for the decadal variability in Rs and can explain the bias in its trend from reanalyses because the reanalyses do not include the interannual variability of aerosols. In this study, we compare the Rs derived from sunshine duration at 2,400 weather stations in China and that from five reanalyses from 1980 to 2014. The determining factors for the biases in the mean values and trends of Rs from the reanalyses are examined, with the help of Rs and the cloud fraction (CF), from satellite and 2,400 weather stations. Our results show that all reanalyses overestimate the multiyear Rs by 24.10–40.00 W/m2 due to their underestimations of CF, which is more obvious in southern China. The biases in the simulated CF in the reanalyses can explain the biases in Rs by 55–41%, and the bias in clear‐sky surface solar radiation (Rc), which is primarily due to biases in aerosol loading, can explain 32–9% of the bias in Rs. The errors in the trend of the simulated CF can explain the errors in the Rs trends in the reanalyses by 73–12%, and the trend errors in the Rc can explain 43–30% of the trend error in Rs. Our study suggests that more work is needed to improve the simulation of aerosols, clouds, and aerosol‐cloud‐radiation interactions in the reanalyses.

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Section: Discussionsupporting

confidence: 93%

Section: Introductionmentioning

confidence: 99%

Determining Factors of Monthly to Decadal Variability in Surface Solar Radiation in China: Evidences From Current Reanalyses

Feng

Wang

2019

JGR Atmospheres

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“…NCEP‐NCAR product was not as accurate as the other reanalyses, and it showed the R of 0.86, a RMSE of 76.3 W m −2 and a MAE of 68.8 W m −2 . All above results showed that all five products significantly overestimated the monthly SSR over China, especially for three reanalyses, which was in agreement with the previous studies (Slater, ; Wu et al ., , ). The deseasonalized correlation coefficients were usually calculated to reduce the impacts of seasonal cycles, which were a better measurement for the quality of the product.…”

Section: Results and Analysismentioning

confidence: 99%

Trends in downward surface shortwave radiation from multi‐source data over China during 1984–2015

Zhou

Lin

Wang

et al. 2019

Intl Journal of Climatology

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The clear knowledge of decadal variability of surface solar radiation (SSR) is of vitally significant for understanding hydrological and biological processes and climate prediction. However, existing studies have shown observed SSR over China may have large discrepancies and inhomogeneity in decadal variability due to sensitivity drift, inaccurate calibrations and instrument replacement. Therefore, a new procedure of station selection was proposed to eliminate errors and to derive “true” SSR values in this study. Afterward, two satellite retrieves of SSR, including Clouds and the Earth's Radiant Energy System‐energy balanced and filled product (CERES‐EBAF) (edition 4) and Global Energy and Water Cycle Experiment‐Surface Radiation Budget (GEWEX‐SRB) (Version 3.0), and three reanalysis products, including National Centers for Environmental Prediction‐National Center for Atmospheric Research (NCEP‐NCAR), national centers for environmental prediction‐/department of energy (NCEP‐DOE) and Modern‐Era Retrospective analysis for Research and Applications, version 2 (MERRA‐2) were evaluated using “true” SSR values at 39 homogeneous stations from the China Meteorological Administration and it was found that although all five products overestimated SSR, two satellite retrieves showed better accuracy with an overall R of 0.95, an root mean squared error (RMSE) of 20.4 W m−2 and mean absolute bias error (MAE) of 14.9 W m−2 for CERES‐EBAF and an overall R of 0.92, an RMSE of 27.7 W m−2 and MAE of 21.2 W m−2 for GEWEX‐SRB across China. Meanwhile, inter‐comparisons between trends of observations and trends of two satellite retrieves in this study showed that the new trends derived from two satellite retrieves (+0.78 W m−2 decade−1) were good agreement with trends of observation (+0.92 W m−2 decade−1) from 1994 to 2015. However, trends of SSR (+5.8 W m−2 decade−1) in situ measurements were still in disagreement with the trends of SSR (−3.7 W m−2 decade−1) derived from two satellite retrieves from 1984 to 1993 because of the sensitivity drift and instrument replacement in this period. The possible reasons for decadal variability of SSR in China were detected and it was found that variations in aerosol optical depth (AOD) and aerosol‐cloud interaction, rather than cloud, were suggested to be likely the main influencing factor of decadal variability of SSR across China from 1984 to 2015.

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Bias correction and variability attribution analysis of surface solar radiation from MERRA-2 reanalysis

Wang

Zhang

et al. 2023

Clim Dyn

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Evaluation of downward surface solar radiation of three reanalysis products over China from 1979 to 2008

Cited by 3 publications

References 1 publication

Determining Factors of Monthly to Decadal Variability in Surface Solar Radiation in China: Evidences From Current Reanalyses

Determining Factors of Monthly to Decadal Variability in Surface Solar Radiation in China: Evidences From Current Reanalyses

Trends in downward surface shortwave radiation from multi‐source data over China during 1984–2015

Bias correction and variability attribution analysis of surface solar radiation from MERRA-2 reanalysis

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