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Evaluating the Diurnal and Semidiurnal Cycle of Precipitation in CMIP6 Models Using Satellite- and Ground-Based Observations

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  • 1 Lawrence Livermore National Laboratory, Livermore, California
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Abstract

The diurnal and semidiurnal cycle of precipitation simulated from CMIP6 models during 1996–2005 are evaluated globally between 60°S and 60°N as well as at 10 selected locations representing three categories of diurnal cycle of precipitation: 1) afternoon precipitation over land, 2) early morning precipitation over ocean, and 3) nocturnal precipitation over land. Three satellite-based and two ground-based rainfall products are used to evaluate the climate models. Globally, the ensemble mean of CMIP6 models shows a diurnal phase of 3 to 4 h earlier over land and 1 to 2 h earlier over ocean when compared with the latest satellite products. These biases are in line with what were found in previous versions of climate models but reduced compared to the CMIP5 ensemble mean. Analysis at the selected locations complemented with in situ measurements further reinforces these results. Several CMIP6 models have shown a significant improvement in the diurnal cycle of precipitation compared to their CMIP5 counterparts, notably in delaying afternoon precipitation over land. This can be attributed to the use of more sophisticated convective parameterizations. Most models are still unable to capture the nocturnal peak associated with elevated convection and propagating mesoscale convective systems, with a few exceptions that allow convection to be initiated above the boundary layer to capture nocturnal elevated convection. We also quantify an encouraging consistency between the satellite- and ground-based precipitation measurements despite differing spatiotemporal resolutions and sampling periods, which provides confidence in using them to evaluate the diurnal and semidiurnal cycle of precipitation in climate models.

Tang’s current affiliation: Pacific Northwest National Laboratory, Richland, Washington.

© 2021 American Meteorological Society. For information regarding reuse of this content and general copyright information, consult the AMS Copyright Policy (www.ametsoc.org/PUBSReuseLicenses).

Corresponding author: Shaocheng Xie, xie2@llnl.gov

Abstract

The diurnal and semidiurnal cycle of precipitation simulated from CMIP6 models during 1996–2005 are evaluated globally between 60°S and 60°N as well as at 10 selected locations representing three categories of diurnal cycle of precipitation: 1) afternoon precipitation over land, 2) early morning precipitation over ocean, and 3) nocturnal precipitation over land. Three satellite-based and two ground-based rainfall products are used to evaluate the climate models. Globally, the ensemble mean of CMIP6 models shows a diurnal phase of 3 to 4 h earlier over land and 1 to 2 h earlier over ocean when compared with the latest satellite products. These biases are in line with what were found in previous versions of climate models but reduced compared to the CMIP5 ensemble mean. Analysis at the selected locations complemented with in situ measurements further reinforces these results. Several CMIP6 models have shown a significant improvement in the diurnal cycle of precipitation compared to their CMIP5 counterparts, notably in delaying afternoon precipitation over land. This can be attributed to the use of more sophisticated convective parameterizations. Most models are still unable to capture the nocturnal peak associated with elevated convection and propagating mesoscale convective systems, with a few exceptions that allow convection to be initiated above the boundary layer to capture nocturnal elevated convection. We also quantify an encouraging consistency between the satellite- and ground-based precipitation measurements despite differing spatiotemporal resolutions and sampling periods, which provides confidence in using them to evaluate the diurnal and semidiurnal cycle of precipitation in climate models.

Tang’s current affiliation: Pacific Northwest National Laboratory, Richland, Washington.

© 2021 American Meteorological Society. For information regarding reuse of this content and general copyright information, consult the AMS Copyright Policy (www.ametsoc.org/PUBSReuseLicenses).

Corresponding author: Shaocheng Xie, xie2@llnl.gov
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