Does the modern‐era retrospective analysis for research and applications‐2 aerosol reanalysis introduce an improvement in the simulation of surface solar radiation over China?

Intl Journal of Climatology

et al. 2019

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.

Section: Results and Analysismentioning

confidence: 99%

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

Zhou

Lin

Intl Journal of Climatology

et al. 2019

“…Existing studies (Feng & Wang, ; Ma et al, ; Wang et al, ) also show that the CERES EBAF surface product provides reliable estimations of monthly R s . Feng and Wang () find that CERES EBAF has a bias of 7.94 W/m 2 compared with observation and 7.53 W/m 2 compared with SunDu‐derived R s from 2000 to 2014. The comparison results of CERES EBAF, GEWES‐SRB, and ISCCP‐FD‐SRF from Li, Xin, and Peng () show that CERES EBAF have lowest root‐mean‐square error (RMSE, 14.73 W/m 2 ) compare with solar radiation measurements in China.…”

Section: Methodsmentioning

confidence: 99%

“…Moreover, R s measurements are sparsely distributed in China. In spite of uncertainty in short time scales, SunDu‐derived R s data have their advantage in quantifying annual to decadal variability of R s (Feng & Wang, ; Wang, ).…”

Section: Methodsmentioning

confidence: 99%

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

Feng

2019

JGR Atmospheres

Self Cite

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.

“…Merging multisource data can be a practical way to improve Rs data with accurate long-term variations [51][52][53][54][55][56]. The large number of SunDu observations (~2400 stations) with large spatial coverage ( Figure 1 Our previous studies have shown reanalyses have substantial biases due to imperfect parameterization of cloud and aerosols [26,51,58]. Considering the advantages of SunDuderived R s and reliable cloud distribution from satellite retrievals, we recently combined ground-based sunshine duration with satellite cloud and aerosol data to produce high resolution long-term R s [59].…”

Section: Introductionmentioning

confidence: 99%

Merging High-Resolution Satellite Surface Radiation Data with Meteorological Sunshine Duration Observations over China from 1983 to 2017

Feng

2021

Remote Sensing

Self Cite

Surface solar radiation (Rs) is essential to climate studies. Thanks to long-term records from the Advanced Very High-Resolution Radiometers (AVHRR), the recent release of International Satellite Cloud Climatology Project (ISCCP) HXG cloud products provide a promising opportunity for building long-term Rs data with high resolutions (3 h and 10 km). In this study, we compare three satellite Rs products based on AVHRR cloud products over China from 1983 to 2017 with direct observations of Rs and sunshine duration (SunDu)-derived Rs. The results show that SunDu-derived Rs have higher accuracy than the direct observed Rs at time scales of a month or longer by comparing with the satellite Rs products. SunDu-derived Rs is available from the 1960s at more than 2000 stations over China, which provides reliable decadal estimations of Rs. However, the three AVHRR-based satellite Rs products have significant biases in quantifying the trend of Rs from 1983 to 2016 (−4.28 W/m2/decade to 2.56 W/m2/decade) due to inhomogeneity in satellite cloud products and the lack of information on atmospheric aerosol optical depth. To adjust the inhomogeneity of the satellite Rs products, we propose a geographically weighted regression fusion method (HGWR) to merge ISCCP-HXG Rs with SunDu-derived Rs. The merged Rs product over China from 1983 to 2017 with a spatial resolution of 10 km produces nearly the same trend as that of the SunDu-derived Rs. This study makes a first attempt to adjust the inhomogeneity of satellite Rs products and provides the merged high-resolution Rs product from 1983 to 2017 over China, which can be downloaded freely.