Total surface shortwave flux distributions 1901-2017 in support of carbon cycle modelling.

This dataset offers 6-hourly distributions of the total downward shortwave flux over the period 1901-2017. Radiative transfer calculations are based on monthly-averaged distributions of tropospheric and stratospheric aerosol optical depth, and 6-hourly distributions of cloud fraction. Methods follow those described in the Methods section of Mercado et al. (doi:10.1038/nature07949, 2009), but with updated input datasets.<br><br>The time series of speciated tropospheric aerosol optical depth is taken from the historical and RCP8.5 simulations by the HadGEM2-ES climate model (Bellouin et al., doi:10.1029/2011JD016074, 2011). To correct for biases in HadGEM2-ES, tropospheric aerosol optical depths are scaled over the whole period to match the global and monthly averages obtained over the period 2003-2017 by the CAMS Reanalysis of atmospheric composition (Inness et al., doi:10.5194/acp-19-3515-2019, 2019), which assimilates satellite retrievals of aerosol optical depth.<br><br>The time series of stratospheric aerosol optical depth is taken from the climatology by Sato et al. (doi:10.1029/93JD02553, 1993), which has been updated to 2012. Years 2013-2017 are assumed to be background years so replicate background year 2010. That assumption is supported by the Global Space-based Stratospheric Aerosol Climatology time series (1979-2016; Thomason et al., doi:10.5194/essd-10-469-2018, 2018).<br><br>The time series of cloud fraction is obtained by scaling the 6-hourly distributions simulated in the Japanese Reanalysis (JRA; Kobayashi et al., doi:10.2151/jmsj.2015-001, 2015) to match the monthly-averaged cloud cover in the CRU TS v4.03 dataset (Harris et al. doi:10.1038/s41597-020-0453-3, 2020).<br><br>Surface radiative fluxes account for aerosol-radiation interactions from both tropospheric and stratospheric aerosols, and for aerosol-cloud interactions from tropospheric aerosols, except mineral dust. Tropospheric aerosols are also assumed to exert interactions with cloud. The radiative effects of those aerosol-cloud interactions are assumed to scale with the radiative effects of aerosol-radiation interactions of tropospheric aerosols, using regional scaling factors derived from HadGEM2-ES.<br><br>Atmospheric constituent other than aerosols and clouds are set to a constant standard mid-latitude summer atmosphere.<br>

本数据集提供1901-2017年间逐6小时的总向下短波通量（total downward shortwave flux）分布。辐射传输计算（radiative transfer calculations）基于对流层（troposphere）与平流层（stratosphere）气溶胶光学厚度（aerosol optical depth）的月平均分布，以及云量（cloud fraction）的逐6小时分布。研究方法参考Mercado等人2009年发表于《自然》（doi:10.1038/nature07949）的方法章节，但使用了更新后的输入数据集。<br><br>分态对流层气溶胶光学厚度（speciated tropospheric aerosol optical depth）的时间序列取自HadGEM2-ES气候模型（Bellouin等人，doi:10.1029/2011JD016074, 2011）的历史与RCP8.5情景模拟结果。为校正HadGEM2-ES的模拟偏差，研究人员对全时段对流层气溶胶光学厚度进行缩放，使其匹配2003-2017年大气成分CAMS再分析（CAMS Reanalysis of atmospheric composition，Inness等人，doi:10.5194/acp-19-3515-2019, 2019）得到的全球逐月平均结果；该再分析数据同化了气溶胶光学厚度的卫星反演产品。<br><br>平流层气溶胶光学厚度的时间序列取自Sato等人1993年的气候学数据集（doi:10.1029/93JD02553, 1993），该数据集已更新至2012年。2013-2017年被设为背景年份，采用2010年的背景值替代。这一假设得到全球天基平流层气溶胶气候学时间序列（1979-2016；Thomason等人，doi:10.5194/essd-10-469-2018, 2018）的支持。<br><br>云量的时间序列通过对日本再分析资料（Japanese Reanalysis, JRA；Kobayashi等人，doi:10.2151/jmsj.2015-001, 2015）模拟得到的逐6小时云量分布进行缩放得到，以匹配CRU TS v4.03数据集（Harris等人，doi:10.1038/s41597-020-0453-3, 2020）中的月平均云量。<br><br>地表辐射通量考虑了对流层与平流层气溶胶的气溶胶-辐射相互作用（aerosol-radiation interactions），以及对流层气溶胶（矿物粉尘除外）的气溶胶-云相互作用（aerosol-cloud interactions）。研究同时假设对流层气溶胶可与云发生相互作用，且此类气溶胶-云相互作用的辐射效应与对流层气溶胶的气溶胶-辐射相互作用的辐射效应成比例，比例系数取自HadGEM2-ES的区域缩放因子。<br><br>除气溶胶与云之外的大气成分，均设置为标准中纬度夏季大气常数。