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Data from: Assessing uncertainties and approximations in solar heating of the climate system

Cite this dataset

Hsu, Juno; Prather, Michael (2020). Data from: Assessing uncertainties and approximations in solar heating of the climate system [Dataset]. Dryad.


Plain language summary of the manuscript "Assessing Uncertainties and Approximations in Solar Heating of the Climate System" to be published in Journal of Advances in Modeling Earth Systems:

"Solar heating of the climate system-- the atmosphere, land surface, and ocean--drives the climate.
Accurate numerical calculation of solar heating is a core component of the models we use to
project and prepare for climate change. The community has identified many potential sources of
error and published studies showing how to improve the solar heating codes used in climate
models. Here we assemble a wide range of these errors, either numerical approximations or
uncertainties in defining atmospheric conditions, and put them through the same test: calculating
the atmospheric and surface heating over a month of simulated climate conditions. Combining
the new calculations here with previous work, we discuss more than a dozen specific areas where
improvements could be made and identify high-priority actions."


Solar-J code is developed at UC Irvine, an 8-stream radiative transfer module to be implemented in climate models such as E3SM supported by the Department of Energy. In developing Solar-J, we conducted a suite of numerical experiments addressing about a dozen common errors due to approximations or simplifications in radiative transfer process. We either built these approximations as alternatives into Solar-J code or compared them directly to the current 2-stream radiative transfer code (RRTMG-SW), a widely used package in  the current climate simulation models. We have analyzed 22 paired numerical experiments. The Fotran source code of the Solar-J, the numerical output and the scripts in producing the figures and tables in the manuscript are archived here.    


United States Department of Energy, Award: Office of Science, Biological and Environmental Research Program, DE-SC0012536

Lawrence Livermore National Laboratory, Award: subcontract B628407

National Aeronautics and Space Administration, Award: Modeling, Analysis and Prediction program, NNX13AL12G