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Characterizing the radiative effect of rain using a global ensemble of cloud resolving simulations

Hill, P. G. ORCID: https://orcid.org/0000-0002-9745-2120, Chiu, J. C., Allan, R. ORCID: https://orcid.org/0000-0003-0264-9447 and Chern, J.-D. (2018) Characterizing the radiative effect of rain using a global ensemble of cloud resolving simulations. Journal of Advances in Modeling Earth Systems, 10 (10). pp. 2453-2470. ISSN 19422466

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To link to this item DOI: 10.1029/2018MS001415

Abstract/Summary

The effect of rain on radiative fluxes and heating rates is a process that is neglected in most of the large scale atmospheric models used for weather forecasting or climate prediction. Yet, to our knowledge, the magnitude of the resulting radiative bias remains unquantified. This study aims to quantify the rain radiative effect (RRE) at a range of temporal and spatial scales, as a step towards determining whether the radiation schemes in these models should include rain. Using offline radiative transfer calculations with input from an ensemble of cloud resolving model simulations, we find that rain has a negligible effect on global mean radiative fluxes (less than 0.2 W m‐2). Weekly mean RREs at specific locations may be larger (less than 4 W m−2). At the finest temporal and spatial resolutions, the RRE can occasionally be much larger again (greater than 100 W m‐2), but values exceeding 10 W m‐2 occur in less than 0.1% of cases. Using detailed analysis of case studies we demonstrate that the magnitude and direction of the RRE depend on the rain water path, its vertical location with respect to cloud and, for longwave radiation, the temperature at which it occurs. Large RREs generally only occur when the rain water path is large and the cloud water path is small. These cases are infrequent and intermittent. As the RREs are generally small, we conclude that this missing process is unlikely to be important for large scale atmospheric models.

Item Type:Article
Refereed:Yes
Divisions:Science > School of Mathematical, Physical and Computational Sciences > National Centre for Earth Observation (NCEO)
Science > School of Mathematical, Physical and Computational Sciences > Department of Meteorology
ID Code:79686
Publisher:Wiley

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