A Linearized Prognostic Cloud Scheme in NASA's Goddard Earth Observing System Data Assimilation Tools.
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| Title: | A Linearized Prognostic Cloud Scheme in NASA's Goddard Earth Observing System Data Assimilation Tools. |
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| Authors: | Holdaway, Daniel, Errico, Ronald, Gelaro, Ronald, Kim, Jong G., Mahajan, Rahul |
| Source: | Monthly Weather Review. Oct2015, Vol. 143 Issue 10, p4198-4219. 22p. 3 Charts, 11 Graphs. |
| Subjects: | United States. National Aeronautics & Space Administration, Earth Observing System (Program), Fluvial geomorphology, Clouds, Meteorology |
| Abstract: | A 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 applications this poor behavior is controlled by replacing this part of the scheme with a perturbation model. For observation impacts, where efficiency is less of a concern, a filtering is developed that examines the Jacobian. The replacement scheme is only invoked if Jacobian elements or eigenvalues violate a series of tuned constants. The linearized prognostic cloud scheme is tested by comparing the linear and nonlinear perturbation trajectories for 6-, 12-, and 24-h forecast times. The tangent linear model performs well and perturbations of clouds are well captured for the lead times of interest. [ABSTRACT FROM AUTHOR] |
| Copyright of Monthly Weather Review is the property of American Meteorological Society and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.) | |
| Database: | Engineering Source |
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| Header | DbId: egs DbLabel: Engineering Source An: 110137272 AccessLevel: 6 PubType: Academic Journal PubTypeId: academicJournal PreciseRelevancyScore: 0 |
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| Items | – Name: Title Label: Title Group: Ti Data: A Linearized Prognostic Cloud Scheme in NASA's Goddard Earth Observing System Data Assimilation Tools. – Name: Author Label: Authors Group: Au Data: <searchLink fieldCode="AR" term="%22Holdaway%2C+Daniel%22">Holdaway, Daniel</searchLink><br /><searchLink fieldCode="AR" term="%22Errico%2C+Ronald%22">Errico, Ronald</searchLink><br /><searchLink fieldCode="AR" term="%22Gelaro%2C+Ronald%22">Gelaro, Ronald</searchLink><br /><searchLink fieldCode="AR" term="%22Kim%2C+Jong+G%2E%22">Kim, Jong G.</searchLink><br /><searchLink fieldCode="AR" term="%22Mahajan%2C+Rahul%22">Mahajan, Rahul</searchLink> – Name: TitleSource Label: Source Group: Src Data: <searchLink fieldCode="JN" term="%22Monthly+Weather+Review%22">Monthly Weather Review</searchLink>. Oct2015, Vol. 143 Issue 10, p4198-4219. 22p. 3 Charts, 11 Graphs. – Name: Subject Label: Subjects Group: Su Data: <searchLink fieldCode="DE" term="%22United+States%2E+National+Aeronautics+%26+Space+Administration%22">United States. National Aeronautics & Space Administration</searchLink><br /><searchLink fieldCode="DE" term="%22Earth+Observing+System+%28Program%29%22">Earth Observing System (Program)</searchLink><br /><searchLink fieldCode="DE" term="%22Fluvial+geomorphology%22">Fluvial geomorphology</searchLink><br /><searchLink fieldCode="DE" term="%22Clouds%22">Clouds</searchLink><br /><searchLink fieldCode="DE" term="%22Meteorology%22">Meteorology</searchLink> – Name: Abstract Label: Abstract Group: Ab Data: A 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 applications this poor behavior is controlled by replacing this part of the scheme with a perturbation model. For observation impacts, where efficiency is less of a concern, a filtering is developed that examines the Jacobian. The replacement scheme is only invoked if Jacobian elements or eigenvalues violate a series of tuned constants. The linearized prognostic cloud scheme is tested by comparing the linear and nonlinear perturbation trajectories for 6-, 12-, and 24-h forecast times. The tangent linear model performs well and perturbations of clouds are well captured for the lead times of interest. [ABSTRACT FROM AUTHOR] – Name: AbstractSuppliedCopyright Label: Group: Ab Data: <i>Copyright of Monthly Weather Review is the property of American Meteorological Society and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.) |
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| RecordInfo | BibRecord: BibEntity: Identifiers: – Type: doi Value: 10.1175/MWR-D-15-0037.1 Languages: – Code: eng Text: English PhysicalDescription: Pagination: PageCount: 22 StartPage: 4198 Subjects: – SubjectFull: United States. National Aeronautics & Space Administration Type: general – SubjectFull: Earth Observing System (Program) Type: general – SubjectFull: Fluvial geomorphology Type: general – SubjectFull: Clouds Type: general – SubjectFull: Meteorology Type: general Titles: – TitleFull: A Linearized Prognostic Cloud Scheme in NASA's Goddard Earth Observing System Data Assimilation Tools. Type: main BibRelationships: HasContributorRelationships: – PersonEntity: Name: NameFull: Holdaway, Daniel – PersonEntity: Name: NameFull: Errico, Ronald – PersonEntity: Name: NameFull: Gelaro, Ronald – PersonEntity: Name: NameFull: Kim, Jong G. – PersonEntity: Name: NameFull: Mahajan, Rahul IsPartOfRelationships: – BibEntity: Dates: – D: 01 M: 10 Text: Oct2015 Type: published Y: 2015 Identifiers: – Type: issn-print Value: 00270644 Numbering: – Type: volume Value: 143 – Type: issue Value: 10 Titles: – TitleFull: Monthly Weather Review Type: main |
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