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The Impact of Ice Phase Cloud Parameterizations on Tropical Cyclone Prediction

Yi Jin Naval Research Laboratory, Monterey, California

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Shouping Wang Naval Research Laboratory, Monterey, California

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Jason Nachamkin Naval Research Laboratory, Monterey, California

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James D. Doyle Naval Research Laboratory, Monterey, California

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Gregory Thompson NCAR, Boulder, Colorado

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Lewis Grasso CIRA, Fort Collins, Colorado

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Teddy Holt Naval Research Laboratory, Monterey, California

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Jon Moskaitis Naval Research Laboratory, Monterey, California

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Hao Jin Naval Research Laboratory, Monterey, California

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Richard M. Hodur Naval Research Laboratory, Monterey, California

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Qingyun Zhao Naval Research Laboratory, Monterey, California

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Ming Liu Naval Research Laboratory, Monterey, California

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Mark DeMaria NOAA/NESDIS, Fort Collins, Colorado

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Print Publication:
01 Feb 2014
DOI:
https://doi.org/10.1175/MWR-D-13-00058.1
Page(s):
606–625
Restricted access

Abstract

The impact of ice phase cloud microphysical processes on prediction of tropical cyclone environment is examined for two microphysical parameterizations using the Coupled Ocean–Atmosphere Mesoscale Prediction System–Tropical Cyclone (COAMPS-TC) model. An older version of microphysical parameterization is a relatively typical single-moment scheme with five hydrometeor species: cloud water and ice, rain, snow, and graupel. An alternative newer method uses a hybrid approach of double moment in cloud ice and rain and single moment in the other three species. Basin-scale synoptic flow simulations point to important differences between these two schemes. The upper-level cloud ice concentrations produced by the older scheme are up to two orders of magnitude greater than the newer scheme, primarily due to differing assumptions concerning the ice nucleation parameterization. Significant (1°–2°C) warm biases near the 300-hPa level in the control experiments are not present using the newer scheme. The warm bias in the control simulations is associated with the longwave radiative heating near the base of the cloud ice layer. The two schemes produced different track and intensity forecasts for 15 Atlantic storms. Rightward cross-track bias and positive intensity bias in the control forecasts are significantly reduced using the newer scheme. Synthetic satellite imagery of Hurricane Igor (2010) shows more realistic brightness temperatures from the simulations using the newer scheme, in which the inner core structure is clearly discernible. Applying the synthetic satellite imagery in both quantitative and qualitative analyses helped to pinpoint the issue of excessive upper-level cloud ice in the older scheme.

Corresponding author address: Yi Jin, Naval Research Laboratory, 7 Grace Hopper Avenue, Monterey, CA 93943-5502. E-mail: yi.jin@nrlmry.navy.mil

Abstract

The impact of ice phase cloud microphysical processes on prediction of tropical cyclone environment is examined for two microphysical parameterizations using the Coupled Ocean–Atmosphere Mesoscale Prediction System–Tropical Cyclone (COAMPS-TC) model. An older version of microphysical parameterization is a relatively typical single-moment scheme with five hydrometeor species: cloud water and ice, rain, snow, and graupel. An alternative newer method uses a hybrid approach of double moment in cloud ice and rain and single moment in the other three species. Basin-scale synoptic flow simulations point to important differences between these two schemes. The upper-level cloud ice concentrations produced by the older scheme are up to two orders of magnitude greater than the newer scheme, primarily due to differing assumptions concerning the ice nucleation parameterization. Significant (1°–2°C) warm biases near the 300-hPa level in the control experiments are not present using the newer scheme. The warm bias in the control simulations is associated with the longwave radiative heating near the base of the cloud ice layer. The two schemes produced different track and intensity forecasts for 15 Atlantic storms. Rightward cross-track bias and positive intensity bias in the control forecasts are significantly reduced using the newer scheme. Synthetic satellite imagery of Hurricane Igor (2010) shows more realistic brightness temperatures from the simulations using the newer scheme, in which the inner core structure is clearly discernible. Applying the synthetic satellite imagery in both quantitative and qualitative analyses helped to pinpoint the issue of excessive upper-level cloud ice in the older scheme.

Corresponding author address: Yi Jin, Naval Research Laboratory, 7 Grace Hopper Avenue, Monterey, CA 93943-5502. E-mail: yi.jin@nrlmry.navy.mil
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