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© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.

Submitted as: research article 21 Jan 2020

Submitted as: research article | 21 Jan 2020

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This preprint is currently under review for the journal ACP.

Differences in tropical high clouds among reanalyses: origins and radiative impacts

Jonathon S. Wright1, Xiaoyi Sun1, Paul Konopka2, Kirstin Krüger3, Andrea M. Molod4, Susann Tegtmeier5, Guang J. Zhang6, and Xi Zhao7 Jonathon S. Wright et al.
  • 1Ministry of Education Key Laboratory for Earth System Modeling, Department of Earth System Science, Tsinghua University, Beijing, China
  • 2Forschungszentrum Jülich (IEK-7: Stratosphere), Jülich, Germany
  • 3Department of Geosciences, University of Oslo, Oslo, Norway
  • 4Global Modeling and Assimilation Office, NASA Goddard Space Flight Center, Greenbelt, Maryland, USA
  • 5Department of Physics and Engineering Physics, University of Saskatchewan, Saskatoon, Canada
  • 6Scripps Institution of Oceanography, La Jolla, California, USA
  • 7Department of Atmospheric Sciences, Texas A&M University, College Station, Texas, USA

Abstract. We examine differences among reanalysis high cloud products in the tropics, assess the impacts of these differences on radiation budgets at the top of the atmosphere and within the tropical upper troposphere and lower stratosphere (UTLS), and discuss their possible origins in the context of the reanalysis models. We focus on the ERA5, ERA-Interim, JRA-55, MERRA-2, and CFSR/CFSv2 reanalyses, with MERRA included in selected comparisons. As a general rule, JRA-55 produces the smallest tropical high cloud fractions and cloud water contents among the reanalyses, while MERRA-2 produces the largest. Accordingly, cloud radiative effects are relatively weak in JRA-55 and relatively strong in MERRA-2. Only MERRA-2 and ERA5 among the reanalyses produce tropical-mean values of outgoing longwave radiation (OLR) close to observed, but ERA5 tends to underestimate cloud effects while MERRA-2 tends to overestimate variability. ERA5 also produces distributions of longwave, shortwave, and total cloud radiative effects at top-of-atmosphere that are very consistent with observed. The other reanalyses all exhibit substantial biases in at least one of these metrics, although compensation between the longwave and shortwave effects helps to constrain biases in the total cloud effect for most reanalyses. The vertical distribution of cloud water content emerges as a key difference between ERA-Interim and the other reanalyses. Whereas ERA-Interim shows a monotonic decrease of cloud water content with increasing height, the other reanalyses all produce distinct anvil layers. The latter is in better agreement with observations and yields very different profiles of radiative heating in the UTLS. For example, whereas the altitude of the level of zero net radiative heating tends to be lower in convective regions than in the rest of the tropics in ERA-Interim, the opposite is true for the other four reanalyses. Differences in cloud water content also help to explain systematic differences in diabatic ascent in the tropical lower stratosphere among the reanalyses. We discuss several ways in which aspects of the cloud and convection schemes impact the tropical environment. Discrepancies in the vertical profile of moist static energy in convective regions are particularly noteworthy, as this metric is based exclusively on variables that are directly constrained by data assimilation.

Jonathon S. Wright et al.

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Jonathon S. Wright et al.

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Latest update: 25 Feb 2020
Publications Copernicus
Short summary
High clouds are highly influential in tropical climate. Although reanalysis cloud fields are essentially model products, they are indirectly constrained by observations and offer global coverage and easy links to advanced water and energy cycle metrics, giving them many useful applications. We describe how high cloud fields are generated in reanalyses, assess their realism and reliability in the tropics, and evaluate how differences in these fields affect other aspects of the reanalysis state.
High clouds are highly influential in tropical climate. Although reanalysis cloud fields are...