Abstract
Cloud radiative kernels (CRK) built with radiative transfer models have been widely used to analyze the cloud radiative effect on top of atmosphere (TOA) fluxes, and it is expected that the CRKs would also be useful in the analyses of surface radiative fluxes, which determines the regional surface temperature change and variability. In this study, CRKs at the surface and TOA were built using the Rapid Radiative Transfer Model (RRTM). Longwave cloud radiative effect (CRE) at the surface is primarily driven by cloud base properties, while TOA CRE is primarily decided by cloud top properties. For this reason, the standard version of surface CRK is a function of latitude, longitude, month, cloud optical thickness (τ) and cloud base pressure (CBP), and the TOA CRK is a function of latitude, longitude, month, τ and cloud top pressure (CTP). Considering that the cloud property histograms provided by climate models are functions of CTP instead of CBP at present, the surface CRKs on CBP-τ histograms were converted to CTP-τ fields using the statistical relationship between CTP, CBP and τ obtained from collocated CloudSat and MODIS observations. For both climate model outputs and satellites observations, the climatology of surface CRE and cloud-induced surface radiative anomalies calculated with the surface CRKs and cloud property histograms are well correlated with those calculated from surface radiative fluxes. The cloud-induced surface radiative anomalies reproduced by surface CRKs and MODIS cloud property histograms are not affected by spurious trends that appear in Clouds and the Earth’s Radiant Energy System (CERES) surface irradiances products.
摘要
云辐射内核已经被广泛应用于分析云属性的变化如何影响大气层顶的辐射通量, 而云辐射效应对地表温度的影响是通过地表辐射通量来直接实现的, 因此本研究使用快速辐射传输模式开发了一套同时适用于大气层顶辐射和地表辐射的云辐射内核. 云顶气压对大气层顶的辐射通量影响显著, 而云底气压对地表云辐射效应有着更重要的影响, 因此标准的大气层顶云辐射内核在各区域和月份中是云顶气压和云光学厚度的函数, 而地表云辐射内核则是云底气压和云光学厚度的函数. 考虑到卫星产品通常提供云顶高度而非云底高度, 本研究使用卫星观测到的云顶高度、 云底高度和光学厚度之间的统计关系将标准的地表云辐射内核转化为云顶气压和云光学厚度的函数. 结合卫星观测或模式输出的云属性产品, 便可以使用云辐射内核估算各区域地表云辐射效应的平均值和距平值, 这些结果和使用传统算法得到的结果有着较好的一致性. 与基于地表辐射通量的传统算法相比, 云辐射内核能够更直观地揭示云属性的变化是如何改变地表辐射平衡的.
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Acknowledgements
We thank Dr. M. ZELINKA for valuable suggestions and thank Dr. Y. ZHANG for useful discussions. This work is supported by the National Natural Science Foundation of China (Grant No. NSFC 41875095 and 42075127). The CRK datasets are available online at Zenodo, doi: https://doi.org/10.5281/zenodo.4732640
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Article Highlights
• Cloud radiative kernels for surface radiative fluxes were built on both CTP-τ and CBP-τ histograms using the Rapid Radiative Transfer Model.
• The kernels could reproduce well the climatology of surface cloud radiative effect for both climate models and satellite observations.
• The cloud-induced anomalies of surface fluxes reproduced by the cloud radiative kernels are well correlated with the actual values.
This paper is a contribution to the special issue on Cloud—Aerosol—Radiation—Precipitation Interaction: Progress and Challenges.
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Zhou, C., Liu, Y. & Wang, Q. Calculating the Climatology and Anomalies of Surface Cloud Radiative Effect Using Cloud Property Histograms and Cloud Radiative Kernels. Adv. Atmos. Sci. 39, 2124–2136 (2022). https://doi.org/10.1007/s00376-021-1166-z
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DOI: https://doi.org/10.1007/s00376-021-1166-z
Key words
- cloud radiative kernel
- surface radiative flux
- cloud feedback
- cloud properties
- cloud top pressure
- cloud base pressure