David D. Parrish
Atmospheric Science · 2013
A researcher in the Science corpus: 1 paper; trusts 7 researchers and is trusted by 3 researchers here, as inferred from the citation graph.
Subfields
- Atmospheric Science — 19 citations into it; #2,821 of 4,804 by trust here, #3,967 by citations
- Global and Planetary Change — 18 citations into it; #5,744 of 10,225 by trust here, #8,506 by citations
- Environmental Engineering — 6 citations into it
Whom David D. Parrish trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Xuguang Wang
- M. Buehner
- A. Lorenc
- Thomas M. Hamill
- Milija Zupanski
- G. Shutts
- C. Snyder
- Wan Wu
- C. Bishop
Who trusts David D. Parrish overall
Papers from David D. Parrish's perspective
Ordered by how strongly the researchers David D. Parrish trusts endorse each paper. Same corpus, a different order for every researcher.
- The potential of the ensemble Kalman filter for NWP—a comparison with 4D‐Var
- Ensemble‐derived stationary and flow‐dependent background‐error covariances: Evaluation in a quasi‐operational NWP setting
- A Hybrid Ensemble Kalman Filter-3D Variational Analysis Scheme
- Intercomparison of Variational Data Assimilation and the Ensemble Kalman Filter for Global Deterministic NWP. Part I: Description and Single-Observation Experiments
- A Comparison of Breeding and Ensemble Transform Kalman Filter Ensemble Forecast Schemes
- Three-Dimensional Variational Analysis with Spatially Inhomogeneous Covariances
- Operational implementation of a hybrid ensemble/4D‐Var global data assimilation system at the Met Office
- Maximum Likelihood Ensemble Filter: Theoretical Aspects
- A kinetic energy backscatter algorithm for use in ensemble prediction systems
- Covariance localisation and balance in an Ensemble Kalman Filter