D
David F. Parrish
Researcher at National Oceanic and Atmospheric Administration
Publications - 46
Citations - 9972
David F. Parrish is an academic researcher from National Oceanic and Atmospheric Administration. The author has contributed to research in topics: Data assimilation & Covariance. The author has an hindex of 29, co-authored 46 publications receiving 9173 citations.
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North american regional reanalysis
Fedor Mesinger,Geoff DiMego,Eugenia Kalnay,Kenneth E. Mitchell,Perry Shafran,Wesley Ebisuzaki,Dusan Jovic,John S. Woollen,Eric Rogers,Ernesto Hugo Berbery,Michael Ek,Yun Fan,Robert Grumbine,Wayne Higgins,Hong Li,Ying Lin,Geoff Manikin,David F. Parrish,Wei Shi +18 more
TL;DR: The North American Regional Reanalysis (NARR) project as mentioned in this paper uses the NCEP Eta model and its Data Assimilation System (at 32-km-45-layer resolution with 3-hourly output) to capture regional hydrological cycle, the diurnal cycle and other important features of weather and climate variability.
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The National Meteorological Center's Spectral Statistical-Interpolation Analysis System
David F. Parrish,John Derber +1 more
TL;DR: Results from several months of parallel testing with the NMC spectral model have been very encouraging, and favorable features include smoother analysis increments, greatly reduced changes from initialization, and significant improvement of 1-5-day forecasts.
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Ozone precursor relationships in the ambient atmosphere
William L. Chameides,F. C. Fehsenfeld,Michael O. Rodgers,Carlos A. Cardelino,J. Martinez,David F. Parrish,William A. Lonneman,D. R. Lawson,R. A. Rasmussen,Patrick R. Zimmerman,Jim Greenberg,P. Mlddleton,Tao Wang +12 more
TL;DR: In this article, the concentrations of ozone, nitrogen oxides, and nonmethane hydrocarbons measured near the surface in a variety of urban, suburban, rural, and remote locations are analyzed and compared in order to elucidate the relationships between ozone, its photochemical precursors, and the sources of these precursor.
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Three-Dimensional Variational Analysis with Spatially Inhomogeneous Covariances
TL;DR: In this paper, a global three-dimensional variational analysis system is formulated in model grid space, where the horizontal scales of variables are obtained through the variances of the variables and of their Laplacian.
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Introduction of the GSI into the NCEP Global Data Assimilation System
TL;DR: The Gridpoint Statistical Interpolation (GSI) as mentioned in this paper was developed at the Environmental Modeling Center at NCEP as part of an effort to create a more unified, robust, and efficient analysis scheme.