Radiative Flux Profiles from the Surface to the Top-of-Atmosphere Derived from ISCCP Cloud and Other Datasets
Department of Applied Physics and Applied Mathematics, Columbia University
William B. Rossow
NASA Goddard Institute for Space Studies
A new 18-year (1983-2000) global radiative flux data product (called ISCCP FD) has been created by employing the NASA GISS climate GCM radiative transfer code and a collection of global datasets describing the properties of the clouds and the surface every 3 hours (ISCCP), daily atmospheric profiles of temperature and humidity (NOAA TOVS), daily ozone abundances (TOMS), a climatology of cloud vertical layer distributions from rawinsonde humidity profiles (Wang et al. 2000), a climatology of cloud particle sizes (Han et al. 1994, 1999), a climatology of stratospheric aerosol and water vapor (SAGE-II), a climatology of the diurnal variations of near-surface air temperature (surface weather observations and NCEP-1 re-analysis), a climatology of tropospheric aerosols (NASA GISS climate model), and the spectral dependence of land surface albedo and emissivity by land-cover type (NASA GISS climate model). The results include the all-sky and clear-sky, upwelling and downwelling, total shortwave (SW = 0.2 - 5 Ám wavelength) and total longwave (LW = 5 - 200 Ám wavelength) radiative fluxes at five levels: surface, 680 mb, 440 mb, 100 mb and top-of-atmosphere. All of these results are reported with a resolution of 3 hours and 280 km (equal-area map equivalent to 2.5 latitude-longitude at the equator) in four data products: (1) Top-of-Atmosphere Radiative Fluxes (TOA RadFlux), (2) Surface Radiative Fluxes (SRF RadFlux), (3) Radiative flux profiles including TOA and SRF fluxes (RadFlux Profiles) and (4) the complete input data collection (RadFlux Inputs). The first three products include a summary of the most relevant input physical parameters, whereas the fourth product contains the exact inputs used to calculate all the fluxes.
The figure illustrates one unique aspect of these results, that they provide physically consistent surface and top-of-atmosphere radiative fluxes, by showing the global monthly mean net SW, net LW, and Total net flux anomalies at the surface, in the atmosphere and at the top-of-atmosphere over the whole time period. Notable features are: (1) a decrease of the net SW at the surface and TOA as well as in the atmosphere produced by the Mt. Pinatubo volcanic aerosols in 1991-2, (2) an overall increase of the net SW at TOA and the surface, but not in the atmosphere, from the 1980's to 1990's associated with a decrease in low-latitude cloud cover, (3) three (possibly four) decreases in net LW at the surface and increases in the atmosphere, but not at TOA, that are not simply associated with El Nino events, and (4) a small decrease of net LW at TOA and in the atmosphere and a larger increase of net LW at the surface occurring in the late 1990's. If correct, these results show a small (~1 Wm-2) increase in radiative heating at the top-of-atmosphere, which is roughly consistent with estimated changes in climate foreign (greehouse gases and aerosols) for this time period, and much larger exchanges between the atmosphere and ocean on time scales of a few years. Another unique feature of the third data product is that it provides, for the first time, a comprehensive determination of the synoptical scale variations of the vertical profiles of radiative diabatic heating, albeit with crude vertical resolution but sufficient to represent radiative heating in the lower, middle or upper troposphere and the stratosphere.
Several papers are being prepared to describe the features of the radiative transfer model and the input datasets and to provide results of comparisons with other more direct determinations of the surface and top-of-atmosphere radiative fluxes (Zhang et al. 2003). More information can be found at
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Zhang, Y-C., W.B. Rossow, A.A. Lacis, V. Oinas and M.I. Mishchenko, 2004: Calculation of radiative flux profiles from the surface to top-of-atmosphere based on ISCCP and other global datasets: Refinements of the radiative transfer model and the input data. J. Geophys. Res., 109, D19105 (Read abstract.)