Search Results - "Plant, Robert S."

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  1. 1

    A dynamic extension of the pragmatic blending scheme for scale‐dependent sub‐grid mixing by Efstathiou, Georgios A., Plant, Robert S.

    “…A recent pragmatic blending approach treats sub‐grid turbulent mixing using a weighted average of a 1D mesoscale model and a 3D Smagorinsky formulation. Here…”
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    Turbulence Characteristics Across a Range of Idealized Urban Canopy Geometries by Blunn, Lewis P., Coceal, Omduth, Nazarian, Negin, Barlow, Janet F., Plant, Robert S., Bohnenstengel, Sylvia I., Lean, Humphrey W.

    Published in Boundary-layer meteorology (01-02-2022)
    “…Good representation of turbulence in urban canopy models is necessary for accurate prediction of momentum and scalar distribution in and above urban canopies…”
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  3. 3

    Mixing‐length controls on high‐resolution simulations of convective storms by Hanley, Kirsty E., Plant, Robert S., Stein, Thorwald H. M., Hogan, Robin J., Nicol, John C., Lean, Humphrey W., Halliwell, Carol, Clark, Peter A.

    “…We perform simulations of several convective events over the southern UK with the Met Office Unified Model (UM) at horizontal grid lengths ranging from 1.5 km…”
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  4. 4

    Connections Between Sub‐Cloud Coherent Updrafts and the Life Cycle of Maritime Shallow Cumulus Clouds in Large Eddy Simulation by Gu, Jian‐Feng, Plant, Robert S., Holloway, Christopher E.

    “…We develop a novel approach to detect cloud‐subcloud coupling during the cloud life cycle and analyze a large eddy simulation of marine shallow cumulus based…”
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  5. 5

    The Atmospheric Boundary Layer and the “Gray Zone” of Turbulence: A Critical Review by Honnert, Rachel, Efstathiou, Georgios A., Beare, Robert J., Ito, Junshi, Lock, Adrian, Neggers, Roel, Plant, Robert S., Shin, Hyeyum Hailey, Tomassini, Lorenzo, Zhou, Bowen

    “…Recent increases in computing power mean that atmospheric models for numerical weather prediction are now able to operate at grid spacings of the order of a…”
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  6. 6

    A Machine‐Learning‐Assisted Stochastic Cloud Population Model as a Parameterization of Cumulus Convection by Hagos, Samson, Chen, Jingyi, Barber, Katelyn, Sakaguchi, Koichi, Plant, Robert S., Feng, Zhe, Xiao, Heng

    “…A machine‐learning‐assisted stochastic cloud population model is coupled with the Advanced Research Weather Research and Forecasting (WRF) model to represent…”
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  7. 7

    A Machine Learning Assisted Development of a Model for the Populations of Convective and Stratiform Clouds by Hagos, Samson, Feng, Zhe, Plant, Robert S., Protat, Alain

    “…Traditional parameterizations of the interaction between convection and the environment have relied on an assumption that the slowly varying large‐scale…”
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  8. 8

    THE DYMECS PROJECT: A Statistical Approach for the Evaluation of Convective Storms in High-Resolution NWP Models by Stein, Thorwald H. M., Hogan, Robin J., Clark, Peter A., Halliwell, Carol E., Hanley, Kirsty E., Lean, Humphrey W., Nicol, John C., Plant, Robert S.

    “…A new frontier in weather forecasting is emerging by operational forecast models now being run at convection-permitting resolutions at many national weather…”
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  9. 9

    A Stochastic Framework for Modeling the Population Dynamics of Convective Clouds by Hagos, Samson, Feng, Zhe, Plant, Robert S., Houze, Robert A., Xiao, Heng

    “…A stochastic prognostic framework for modeling the population dynamics of convective clouds and representing them in climate models is proposed. The framework…”
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  10. 10

    Sensitivity of Tropical Cyclone Idai Simulations to Cumulus Parametrization Schemes by Bopape, Mary-Jane M., Cardoso, Hipolito, Plant, Robert S., Phaduli, Elelwani, Chikoore, Hector, Ndarana, Thando, Khalau, Lino, Rakate, Edward

    Published in Atmosphere (01-08-2021)
    “…Weather simulations are sensitive to subgrid processes that are parameterized in numerical weather prediction (NWP) models. In this study, we investigated the…”
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    A simple model of convection with memory by Davies, Laura, Plant, Robert S., Derbyshire, Stephen H.

    “…There are at least three distinct time scales that are relevant for the evolution of atmospheric convection. These are the time scale of the forcing mechanism,…”
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  13. 13

    Grey‐zone simulations of shallow‐to‐deep convection transition using dynamic subgrid‐scale turbulence models by Efstathiou, Georgios A., Plant, Robert S., Chow, Fotini Katopodes

    “…We examine the ability of two dynamic turbulence closure models to simulate the diurnal development of convection and the transition from dry to shallow cumuli…”
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  14. 14

    Evaluating the CoMorph‐A parametrization using idealized simulations of the two‐way coupling between convection and large‐scale dynamics by Daleu, Chimene L., Plant, Robert S., Stirling, Alison J., Whitall, Mike

    “…We present a new methodology to test the interactions of convection schemes with their larger scale environment. A single‐column model (SCM) using the new Met…”
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  15. 15

    Sensible heat fluxes control cloud trail strength by Johnston, Michael C., Holloway, Christopher E., Plant, Robert S.

    “…Convective cloud bands known as “cloud trails” (CTs) are commonly found downwind of small islands (<O$$ \mathcal{O} $$(100) km2) throughout the world. They…”
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    Comparison of stochastic parametrization approaches in a single-column model by Ball, Michael A, Plant, Robert S

    “…We discuss and test the potential usefulness of single-column models (SCMs) for the testing of stochastic physics schemes that have been proposed for use in…”
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  17. 17

    Basic Concepts for Convection Parameterization in Weather Forecast and Climate Models: COST Action ES0905 Final Report by Yano, Jun-Ichi, Geleyn, Jean-Francois, Kohler, Martin, Mironov, Dmitrii, Quaas, Johannes, Soares, Pedro M M, Phillips, Vaughan T J, Plant, Robert S, Deluca, Anna, Marquet, Pascal

    Published in Atmosphere (2015)
    “…The research network "Basic Concepts for Convection Parameterization in Weather Forecast and Climate Models" was organized with European funding (COST Action…”
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  18. 18

    The influence of resolved convective motions on scalar dispersion in hectometric‐scale numerical weather prediction models by Blunn, Lewis P., Plant, Robert S., Coceal, Omduth, Bohnenstengel, Sylvia I., Lean, Humphrey W., Barlow, Janet F.

    “…The UK Met Office has a 300‐m grid length numerical weather prediction (NWP) model running routinely over London and, in research mode, city‐scale hectometric…”
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  19. 19

    The impact of surface heterogeneity on the diurnal cycle of deep convection by Harvey, Natalie J., Daleu, Chimene L., Stratton, Rachel A., Plant, Robert S., Woolnough, Steven J., Stirling, Alison J.

    “…Despite some recent improvements, major deficiencies remain in model simulations using parameterised convection in capturing both the phase and amplitude of…”
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  20. 20

    The use of idealised experiments in testing a new convective parametrization: Performance of CoMorph‐A by Lavender, Sally L., Stirling, Alison J., Whitall, Michael, Stratton, Rachel A., Daleu, Chimene L., Plant, Robert S., Lock, Adrian, Gu, Jian‐Feng

    “…CoMorph is a new mass‐flux convection parametrization under development at the Met Office designed for use within the Unified Model and its successor model,…”
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