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Record 1 of 5399
A Linearized Prognostic Cloud Scheme in NASAs Goddard Earth Observing System Data Assimilation Tools
External Online Source: doi:10.1175/MWR-D-15-0037.1
Author and Affiliation:
Holdaway, Daniel(Universities Space Research Association, Greenbelt, MD, United States)
Errico, Ronald M.(Morgan State Univ., GESTAR, Baltimore, MD, United States)
Gelaro, Ronald(NASA Goddard Space Flight Center, Greenbelt, MD United States)
Kim, Jong G.(Science Systems and Applications, Inc., Lanham, MD, United States)
Mahajan, Rahul(Oak Ridge Associated Universities, Inc., Oak Ridge, TN, United States)
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.
Publication Date: Oct 01, 2015
Document ID:
20150023394
(Acquired Dec 29, 2015)
Subject Category: METEOROLOGY AND CLIMATOLOGY
Report/Patent Number: GSFC-E-DAA-TN28220
Document Type: Journal Article
Publication Information: Monthly Weather Review; p. 4198-4219; Volume 143; No. 10
Publisher Information: American Meteorological Society
Contract/Grant/Task Num: NNG12HP06C; NNG11HP16A
Financial Sponsor: NASA Goddard Space Flight Center; Greenbelt, MD United States
Organization Source: NASA Goddard Space Flight Center; Greenbelt, MD United States
Description: 22p; In English
Distribution Limits: Unclassified; Publicly available; Unlimited
Rights: Copyright
NASA Terms: LINEARIZATION; ADVECTION; CONVECTION; EARTH OBSERVING SYSTEM (EOS); CLOUDS (METEOROLOGY); FORECASTING; EVAPORATION; SUBLIMATION; DIFFUSION; ASSIMILATION; PERTURBATION
Other Descriptors: PRECIPITATION; LINEARIZED ADVECTION; LARGE-SCALE CONDENSATION
Availability Source: Other Sources
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Last Modified: December 29, 2015
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