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Kevin W. Manning

Researcher at National Center for Atmospheric Research

Publications -  44
Citations -  7952

Kevin W. Manning is an academic researcher from National Center for Atmospheric Research. The author has contributed to research in topics: Mesoscale meteorology & Weather Research and Forecasting Model. The author has an hindex of 28, co-authored 42 publications receiving 6689 citations.

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The community Noah land surface model with multiparameterization options (Noah-MP): 1. Model description and evaluation with local-scale measurements

TL;DR: In this paper, the authors describe the objectives of community efforts in improving the Noah land surface model (LSM), documents, through mathematical formulations, the augmented conceptual realism in biophysical and hydrological processes, and introduces a framework for multiple options to parameterize selected processes (Noah•MP).
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Explicit Forecasts of Winter Precipitation Using an Improved Bulk Microphysics Scheme. Part I: Description and Sensitivity Analysis

TL;DR: In this paper, the authors evaluated the sensitivity of winter precipitation to various aspects of a bulk, mixed-phase microphysical parameterization found in three widely used mesoscale models [the fifth-generation Pennsylvania State University-National Center for Atmospheric Research Mesoscale Model (MM5), the Rapid Update Cycle (RUC), and the Weather Research and Forecast (WRF) model].
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The COSMIC/FORMOSAT-3 Mission: Early Results

TL;DR: The radio occultation (RO) technique, which makes use of radio signals transmitted by the global positioning system (GPS) satellites, has emerged as a powerful and relatively inexpensive approach for sounding the global atmosphere with high precision, accuracy, and vertical resolution in all weather and over both land and ocean as mentioned in this paper.
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The community Noah land surface model with multiparameterization options (Noah-MP): 2. Evaluation over global river basins

TL;DR: In this paper, the augmented Noah land surface model described in the first part of the two-part series was evaluated over global river basins across various climate zones, across various weather zones, and in addition, global-scale tests can reveal a model's weaknesses and strengths that a local-scale testing cannot.