The Experts below are selected from a list of 291 Experts worldwide ranked by ideXlab platform
Daniel Holdaway - One of the best experts on this subject based on the ideXlab platform.
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a linearized prognostic cloud scheme in nasas goddard Earth Observing System data assimilation tools
Monthly Weather Review, 2015Co-Authors: Daniel Holdaway, Ronaldo Gelaro, Ronald M Errico, Jong G Kim, Rahul MahajanAbstract:AbstractA linearized prognostic cloud scheme has been developed to accompany the linearized convection scheme recently implemented in NASA’s Goddard Earth Observing System data assimilation tools. The linearization, developed from the nonlinear cloud scheme, treats cloud variables prognostically so they are subject to linearized advection, diffusion, generation, and evaporation. Four linearized cloud variables are modeled, the ice and water phases of clouds generated by large-scale condensation and, separately, by detraining convection. For each species the scheme models their sources, sublimation, evaporation, and autoconversion. Large-scale, anvil and convective species of precipitation are modeled and evaporated. The cloud scheme exhibits linearity and realistic perturbation growth, except around the generation of clouds through large-scale condensation. Discontinuities and steep gradients are widely used here and severe problems occur in the calculation of cloud fraction. For data assimilation applica...
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Inclusion of Linearized Moist Physics in NASA’s Goddard Earth Observing System Data Assimilation Tools
Monthly Weather Review, 2014Co-Authors: Daniel Holdaway, Ronald M Errico, Ronaldo GelaroAbstract:AbstractInclusion of moist physics in the linearized version of a weather forecast model is beneficial in terms of variational data assimilation. Further, it improves the capability of important tools, such as adjoint-based observation impacts and sensitivity studies. A linearized version of the relaxed Arakawa–Schubert (RAS) convection scheme has been developed and tested in NASA’s Goddard Earth Observing System data assimilation tools. A previous study of the RAS scheme showed it to exhibit reasonable linearity and stability. This motivates the development of a linearization of a near-exact version of the RAS scheme. Linearized large-scale condensation is included through simple conversion of supersaturation into precipitation. The linearization of moist physics is validated against the full nonlinear model for 6- and 24-h intervals, relevant to variational data assimilation and observation impacts, respectively. For a small number of profiles, sudden large growth in the perturbation trajectory is encou...
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inclusion of linearized moist physics in nasa s goddard Earth Observing System data assimilation tools
Monthly Weather Review, 2014Co-Authors: Daniel Holdaway, Ronaldo Gelaro, Ronald M Errico, Jong G KimAbstract:AbstractInclusion of moist physics in the linearized version of a weather forecast model is beneficial in terms of variational data assimilation. Further, it improves the capability of important tools, such as adjoint-based observation impacts and sensitivity studies. A linearized version of the relaxed Arakawa–Schubert (RAS) convection scheme has been developed and tested in NASA’s Goddard Earth Observing System data assimilation tools. A previous study of the RAS scheme showed it to exhibit reasonable linearity and stability. This motivates the development of a linearization of a near-exact version of the RAS scheme. Linearized large-scale condensation is included through simple conversion of supersaturation into precipitation. The linearization of moist physics is validated against the full nonlinear model for 6- and 24-h intervals, relevant to variational data assimilation and observation impacts, respectively. For a small number of profiles, sudden large growth in the perturbation trajectory is encou...
Ronaldo Gelaro - One of the best experts on this subject based on the ideXlab platform.
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a linearized prognostic cloud scheme in nasas goddard Earth Observing System data assimilation tools
Monthly Weather Review, 2015Co-Authors: Daniel Holdaway, Ronaldo Gelaro, Ronald M Errico, Jong G Kim, Rahul MahajanAbstract:AbstractA linearized prognostic cloud scheme has been developed to accompany the linearized convection scheme recently implemented in NASA’s Goddard Earth Observing System data assimilation tools. The linearization, developed from the nonlinear cloud scheme, treats cloud variables prognostically so they are subject to linearized advection, diffusion, generation, and evaporation. Four linearized cloud variables are modeled, the ice and water phases of clouds generated by large-scale condensation and, separately, by detraining convection. For each species the scheme models their sources, sublimation, evaporation, and autoconversion. Large-scale, anvil and convective species of precipitation are modeled and evaporated. The cloud scheme exhibits linearity and realistic perturbation growth, except around the generation of clouds through large-scale condensation. Discontinuities and steep gradients are widely used here and severe problems occur in the calculation of cloud fraction. For data assimilation applica...
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Inclusion of Linearized Moist Physics in NASA’s Goddard Earth Observing System Data Assimilation Tools
Monthly Weather Review, 2014Co-Authors: Daniel Holdaway, Ronald M Errico, Ronaldo GelaroAbstract:AbstractInclusion of moist physics in the linearized version of a weather forecast model is beneficial in terms of variational data assimilation. Further, it improves the capability of important tools, such as adjoint-based observation impacts and sensitivity studies. A linearized version of the relaxed Arakawa–Schubert (RAS) convection scheme has been developed and tested in NASA’s Goddard Earth Observing System data assimilation tools. A previous study of the RAS scheme showed it to exhibit reasonable linearity and stability. This motivates the development of a linearization of a near-exact version of the RAS scheme. Linearized large-scale condensation is included through simple conversion of supersaturation into precipitation. The linearization of moist physics is validated against the full nonlinear model for 6- and 24-h intervals, relevant to variational data assimilation and observation impacts, respectively. For a small number of profiles, sudden large growth in the perturbation trajectory is encou...
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inclusion of linearized moist physics in nasa s goddard Earth Observing System data assimilation tools
Monthly Weather Review, 2014Co-Authors: Daniel Holdaway, Ronaldo Gelaro, Ronald M Errico, Jong G KimAbstract:AbstractInclusion of moist physics in the linearized version of a weather forecast model is beneficial in terms of variational data assimilation. Further, it improves the capability of important tools, such as adjoint-based observation impacts and sensitivity studies. A linearized version of the relaxed Arakawa–Schubert (RAS) convection scheme has been developed and tested in NASA’s Goddard Earth Observing System data assimilation tools. A previous study of the RAS scheme showed it to exhibit reasonable linearity and stability. This motivates the development of a linearization of a near-exact version of the RAS scheme. Linearized large-scale condensation is included through simple conversion of supersaturation into precipitation. The linearization of moist physics is validated against the full nonlinear model for 6- and 24-h intervals, relevant to variational data assimilation and observation impacts, respectively. For a small number of profiles, sudden large growth in the perturbation trajectory is encou...
Jong G Kim - One of the best experts on this subject based on the ideXlab platform.
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a linearized prognostic cloud scheme in nasas goddard Earth Observing System data assimilation tools
Monthly Weather Review, 2015Co-Authors: Daniel Holdaway, Ronaldo Gelaro, Ronald M Errico, Jong G Kim, Rahul MahajanAbstract:AbstractA linearized prognostic cloud scheme has been developed to accompany the linearized convection scheme recently implemented in NASA’s Goddard Earth Observing System data assimilation tools. The linearization, developed from the nonlinear cloud scheme, treats cloud variables prognostically so they are subject to linearized advection, diffusion, generation, and evaporation. Four linearized cloud variables are modeled, the ice and water phases of clouds generated by large-scale condensation and, separately, by detraining convection. For each species the scheme models their sources, sublimation, evaporation, and autoconversion. Large-scale, anvil and convective species of precipitation are modeled and evaporated. The cloud scheme exhibits linearity and realistic perturbation growth, except around the generation of clouds through large-scale condensation. Discontinuities and steep gradients are widely used here and severe problems occur in the calculation of cloud fraction. For data assimilation applica...
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inclusion of linearized moist physics in nasa s goddard Earth Observing System data assimilation tools
Monthly Weather Review, 2014Co-Authors: Daniel Holdaway, Ronaldo Gelaro, Ronald M Errico, Jong G KimAbstract:AbstractInclusion of moist physics in the linearized version of a weather forecast model is beneficial in terms of variational data assimilation. Further, it improves the capability of important tools, such as adjoint-based observation impacts and sensitivity studies. A linearized version of the relaxed Arakawa–Schubert (RAS) convection scheme has been developed and tested in NASA’s Goddard Earth Observing System data assimilation tools. A previous study of the RAS scheme showed it to exhibit reasonable linearity and stability. This motivates the development of a linearization of a near-exact version of the RAS scheme. Linearized large-scale condensation is included through simple conversion of supersaturation into precipitation. The linearization of moist physics is validated against the full nonlinear model for 6- and 24-h intervals, relevant to variational data assimilation and observation impacts, respectively. For a small number of profiles, sudden large growth in the perturbation trajectory is encou...
Ronald M Errico - One of the best experts on this subject based on the ideXlab platform.
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a linearized prognostic cloud scheme in nasas goddard Earth Observing System data assimilation tools
Monthly Weather Review, 2015Co-Authors: Daniel Holdaway, Ronaldo Gelaro, Ronald M Errico, Jong G Kim, Rahul MahajanAbstract:AbstractA linearized prognostic cloud scheme has been developed to accompany the linearized convection scheme recently implemented in NASA’s Goddard Earth Observing System data assimilation tools. The linearization, developed from the nonlinear cloud scheme, treats cloud variables prognostically so they are subject to linearized advection, diffusion, generation, and evaporation. Four linearized cloud variables are modeled, the ice and water phases of clouds generated by large-scale condensation and, separately, by detraining convection. For each species the scheme models their sources, sublimation, evaporation, and autoconversion. Large-scale, anvil and convective species of precipitation are modeled and evaporated. The cloud scheme exhibits linearity and realistic perturbation growth, except around the generation of clouds through large-scale condensation. Discontinuities and steep gradients are widely used here and severe problems occur in the calculation of cloud fraction. For data assimilation applica...
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Inclusion of Linearized Moist Physics in NASA’s Goddard Earth Observing System Data Assimilation Tools
Monthly Weather Review, 2014Co-Authors: Daniel Holdaway, Ronald M Errico, Ronaldo GelaroAbstract:AbstractInclusion of moist physics in the linearized version of a weather forecast model is beneficial in terms of variational data assimilation. Further, it improves the capability of important tools, such as adjoint-based observation impacts and sensitivity studies. A linearized version of the relaxed Arakawa–Schubert (RAS) convection scheme has been developed and tested in NASA’s Goddard Earth Observing System data assimilation tools. A previous study of the RAS scheme showed it to exhibit reasonable linearity and stability. This motivates the development of a linearization of a near-exact version of the RAS scheme. Linearized large-scale condensation is included through simple conversion of supersaturation into precipitation. The linearization of moist physics is validated against the full nonlinear model for 6- and 24-h intervals, relevant to variational data assimilation and observation impacts, respectively. For a small number of profiles, sudden large growth in the perturbation trajectory is encou...
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inclusion of linearized moist physics in nasa s goddard Earth Observing System data assimilation tools
Monthly Weather Review, 2014Co-Authors: Daniel Holdaway, Ronaldo Gelaro, Ronald M Errico, Jong G KimAbstract:AbstractInclusion of moist physics in the linearized version of a weather forecast model is beneficial in terms of variational data assimilation. Further, it improves the capability of important tools, such as adjoint-based observation impacts and sensitivity studies. A linearized version of the relaxed Arakawa–Schubert (RAS) convection scheme has been developed and tested in NASA’s Goddard Earth Observing System data assimilation tools. A previous study of the RAS scheme showed it to exhibit reasonable linearity and stability. This motivates the development of a linearization of a near-exact version of the RAS scheme. Linearized large-scale condensation is included through simple conversion of supersaturation into precipitation. The linearization of moist physics is validated against the full nonlinear model for 6- and 24-h intervals, relevant to variational data assimilation and observation impacts, respectively. For a small number of profiles, sudden large growth in the perturbation trajectory is encou...
Max J Suarez - One of the best experts on this subject based on the ideXlab platform.
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cloud System resolving simulations with the nasa goddard Earth Observing System global atmospheric model geos 5
Geophysical Research Letters, 2011Co-Authors: William M Putman, Max J SuarezAbstract:[1] The NASA Global Modeling and Assimilation Office (GMAO) has developed a global non-hydrostatic cloud-System resolving capability within the NASA Goddard Earth Observing System global atmospheric model version 5 (GEOS-5). Using a non-hydrostatic finite-volume dynamical core coupled with advances in the moist physics and convective parameterization the model has been used to perform cloud-System resolving experiments at resolutions as fine as 3.5- to 14-km globally. An overview of preliminary results highlights the development of mid-latitude cyclones, the overall representation of global tropical convection, intense convective activity within the eye wall and outer rain bands of the 2009 Atlantic hurricane Bill validated by satellite observations, and the seasonal predictability of global tropical cyclone activity with realistic intensities. These preliminary results provide motivation for the use of GEOS-5 to simulate multi-scale convective Systems within a global model at cloud resolving resolutions.
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documentation and validation of the goddard Earth Observing System geos data assimilation System version 4
NASA Tech. Memo, 2005Co-Authors: Max J Suarez, Arlindo Dasilva, S C Bloom, Michael G Bosilovich, Steven Pawson, Siegfried D Schubert, Manli Wu, Meta Sienkiewicz, Ivanka StajnerAbstract:This document describes the structure and validation of a frozen version of the Goddard Earth Observing System Data Assimilation System (GEOS DAS): GEOS-4.0.3. Significant features of GEOS-4 include: version 3 of the Community Climate Model (CCM3) with the addition of a finite volume dynamical core; version two of the Community Land Model (CLM2); the Physical-space Statistical Analysis System (PSAS); and an interactive retrieval System (iRET) for assimilating TOVS radiance data. Upon completion of the GEOS-4 validation in December 2003, GEOS-4 became operational on 15 January 2004. Products from GEOS-4 have been used in supporting field campaigns and for reprocessing several years of data for CERES.
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technical report series on global modeling and data assimilation volume 1 documentation of the goddard Earth Observing System geos general circulation model version 1
trsg, 1994Co-Authors: Max J Suarez, Lawrence L Takacs, Andrea Molod, Tina WangAbstract:This technical report documents Version 1 of the Goddard Earth Observing System (GEOS) General Circulation Model (GCM). The GEOS-1 GCM is being used by NASA's Data Assimilation Office (DAO) to produce multiyear data sets for climate research. This report provides a documentation of the model components used in the GEOS-1 GCM, a complete description of model diagnostics available, and a User's Guide to facilitate GEOS-1 GCM experiments.
