ISCCP-FH Radiative Kernels

The concept of the radiative kernel was introduced as early as 2008 (Soden et al., 2008) for more efficiently calculating climate feedback. With the radiative kernel, the climate feedback or radiative effects/responses due to the perturbation on a climate variable can be separated into two parts, (1) the radiative kernel, which depends only on the radiative algorithm and the base/mean climate (the unperturbed states), and (2) the climate response or change, which is just the change in the mean climatology of the climate variables (due to perturbation) between the two climate states (perturbed and unperturbed). Zelinka et al. (2012) further introduced cloud radiative kernel (CRK) for the top of atmosphere (TOA), and Zhang et al. (2021) calculated CRK for the surface and atmosphere, in addition to the CRK at TOA, based on observations of the ISCCP-H climatology and the radiation code, ISCCP-FH (Zhang and Rossow, 2023).

To create non-cloud radiative kernels, we essentially follow Zhang et al. (2021) using the ISCCP-FH radiation code and the 3-hourly, ISCCP H-series climatology of year 2007 with 110-km, equal-area resolution (Young et al., 2018), but the cloud kernel is for cloud effects while all the other non-cloud kernels are for net flux change for SW, LW or their sum, Net. Their sign is specified as the same as the convention of the ISCCP- FH fluxes such that positive sign means radiative heating in the system (the earth- atmosphere, earth or atmospheric system for TOA, SFC or ATM, respectively). All the 3-hourly kernels are averaged to monthly means and replicated on equal-angle map of 2.5 longitude ×2.0 latitude resolution (consistent with NASA GISS's current ModelE2.1 datasets) as formal products, but since the 110-km resolution kernels have been produced, they may also be available. The six radiative kernels generated so far are listed in Table 1.

Table 1. Radiative kernels generated in this work.
  Climate variable of Kernel Input climatology Radiation code
1 clouds 2007 ISCCP-H ISCCP-FH
2 surface albedo 2007 ISCCP-H with surface albedo replaced by the one of NASA GISS ModelE ISCCP-FH with newly revised sea ice treatment (essentially for sea ice ponds)
3 sea ice fraction
4 surface air temperature
5 column precipitable water
6 atmospheric temperature

Further discussion of how the kernels were generated may be read in extended introduction (PDF).

Questions about using the ISCCP-FH radiative kernels may be directed to Dr. Yuanchong Zhang.

  • To access the FH kernel data, you will be asked for a username and password. Enter "isccpfluxfh" and "clouds", respectively.
  • Kernel Data
  • Documentation

Related Datasets


Soden, B.J., and Held, I.M., 2006: An assessment of climate feedbacks in coupled ocean-atmosphere models. J. Clim., 19, 3354–3360, doi:10.1175/JCLI3799.1.

Sun, M, D.R. Doelling, N.G. Loeb, R.C. Scott, J. Wilkins, L.T. Nguyen, and P. Mlynczak, 2022: Clouds and the Earth’s Radiant Energy System (CERES) FluxByCldTyp Edition 4 data product. J. Atmos. Ocean. Technol., 39, P303-318, doi:10.1175/JTECH-D-21-0029.1.

Wielicki, B.A., B.R. Barkstrom, E.F. Harrison, R.B. Lee, G.L. Smith, and J.E. Cooper, 1996: Clouds and the Earth's Radiant Energy System (CERES): An Earth observing system experiment. Bull. Amer. Meteorol. Soc., 77, 853–868, doi:10.1175/1520-0477(1996)077<0853:catere>;2.

Young, A.H., K.R. Knapp, A. Inamdar, W. Hankins, and W.B. Rossow, 2018: The International Satellite Cloud Climatology Project H-Series climate data record product. Earth Syst. Sci. Data, 10, 583–593, doi:10.5194/essd-10-583-2018.

Zelinka, M.D., S.A. Klein, and D.L. Hartmann, 2012: Computing and partitioning cloud feedbacks using cloud property histograms. Part I: Cloud radiative kernels. J. Clim., 25, 3736–3754, 10.1175/jcli-d-11-00249.1.

Zhang, Y. , and W.B. Rossow, 2023: Global radiative flux profile dataset: Revised and extended. J. Geophys. Res. Atmos., 128, no. 5, e2022JD037340, doi:10.1029/2022JD037340.

Zhang, Y., Z. Jin, and M. Sikand, 2021: The top-of-atmosphere, surface and atmospheric cloud radiative kernels based on ISCCP-H datasets: Method and evaluation. J. Geophys. Res. Atmos., 126, no. 24, e2021JD035053, doi:10.1029/2021JD035053.

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