Diffuse fraction distributions 1901-2017 in support of carbon cycle modelling: Constant aerosols.

This diffuse fraction dataset offers 6-hourly distributions of the diffuse fraction of surface shortwave fluxes over the period 1901-2017. This is a companion dataset of doi:10.6084/m9.figshare.14423690, where time variations in tropospheric aerosols are ignored, and stratospheric aerosols are not accounted for. Radiative transfer calculations are based on monthly-averaged distributions of tropospheric 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. Monthly distributions of sulfate and carbonaceous optical depth are then averaged over the 1901-1920 period, and those multi-annual monthly averages are used for the whole 1901-2017 period. The only interannual changes in tropospheric aerosols therefore come from mineral dust and seasalt.<br><br>Stratospheric aerosol optical depth is not accounted for in the radiative transfer calculations.<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 and aerosol-cloud interactions by tropospheric aerosols, except mineral dust which only exerts aerosol-radiation interactions. The radiative effects of 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>Diffuse fraction is assumed to be 1 in cloudy sky. Atmospheric constituents other than aerosols and clouds are set to a constant standard mid-latitude summer atmosphere, but their variations do not affect the diffuse fraction of surface shortwave fluxes.本弥散分数（diffuse fraction）数据集提供了1901年至2017年间地表短波通量（surface shortwave fluxes）弥散分数的逐6小时分布。本数据集为DOI:10.6084/m9.figshare.14423690的配套数据集，该数据集未考虑对流层气溶胶（tropospheric aerosols）的时间变化，且未纳入平流层气溶胶（stratospheric aerosols）的影响。辐射传输计算（radiative transfer calculations）基于对流层气溶胶光学厚度（aerosol optical depth）的月均分布，以及云量（cloud fraction）的逐6小时分布。本研究采用的方法参考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。 分类型对流层气溶胶光学厚度（speciated tropospheric aerosol optical depth）的时间序列取自HadGEM2-ES气候模式的历史情景与RCP8.5情景模拟结果（Bellouin等人，2011年，DOI:10.1029/2011JD016074）。为校正HadGEM2-ES的模拟偏差，本研究对整个研究时段的对流层气溶胶光学厚度进行比例缩放，使其与2003-2017年间由大气成分CAMS再分析数据集（Inness等人，2019年，DOI:10.5194/acp-19-3515-2019）得到的全球月均气溶胶光学厚度相匹配；该再分析数据集同化了卫星反演的气溶胶光学厚度数据。随后，对1901-1920年时段的硫酸盐与碳质气溶胶光学厚度的月分布进行多年逐月平均，将得到的逐月多年平均值用于整个1901-2017研究时段。因此，对流层气溶胶仅有的年际变化来自矿物沙尘与海盐气溶胶。 辐射传输计算未纳入平流层气溶胶光学厚度的影响。 云量的时间序列通过对日本再分析数据集（Japanese Reanalysis, JRA；Kobayashi等人，2015年，DOI:10.2151/jmsj.2015-001）模拟的逐6小时云量分布进行比例缩放得到，使其与CRU TS v4.03数据集（Harris等人，2020年，DOI:10.1038/s41597-020-0453-3）的月均云量相匹配。 地表辐射通量考虑了对流层气溶胶的气溶胶-辐射相互作用（aerosol-radiation interactions）与气溶胶-云相互作用（aerosol-cloud interactions），但矿物沙尘气溶胶仅考虑其气溶胶-辐射相互作用。气溶胶-云相互作用的辐射效应被假定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模式得到的区域尺度因子。 多云天空下的弥散分数被假定为1。除气溶胶与云之外的大气成分被设置为恒定的标准中纬度夏季大气，但其变化不会影响地表短波通量的弥散分数。