R. Bannister
Atmospheric Science · 2008–2017
A researcher in the Science corpus: 2 papers; trusts 75 researchers and is trusted by 27 researchers here, as inferred from the citation graph.
Subfields
- Atmospheric Science — 72 citations into it; #303 of 4,804 by trust here, #2,974 by citations
- Global and Planetary Change — 68 citations into it; #628 of 10,225 by trust here, #6,604 by citations
- Environmental Engineering — 17 citations into it; #2,175 of 5,479 by trust here, #5,257 by citations
- Oceanography — 15 citations into it
Whom R. Bannister trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- L. Berre
- Thomas M. Hamill
- Geir Evensen
- N. Ingleby
- M. Buehner
- Eugenia Kalnay
- Yannick Trémolet
- P. Houtekamer
- Jeffrey L. Anderson
- A. T. Weaver
Who trusts R. Bannister overall
- Peter Weston
- Hongli Wang
- Alberto Carrassi
- A. Barth
- Daryl Timothy Kleist
- William Bell
- Marc Bocquet
- Xiangyu Huang
- Jean-Marie Beckers
- D. Parrish
Papers from R. Bannister's perspective
Ordered by how strongly the researchers R. Bannister trusts endorse each paper. Same corpus, a different order for every researcher.
- Ensemble‐derived stationary and flow‐dependent background‐error covariances: Evaluation in a quasi‐operational NWP setting
- An Ensemble Adjustment Kalman Filter for Data Assimilation
- A Hybrid Ensemble Kalman Filter-3D Variational Analysis Scheme
- The potential of the ensemble Kalman filter for NWP—a comparison with 4D‐Var
- The Ensemble Kalman Filter: theoretical formulation and practical implementation
- Ensemble Data Assimilation without Perturbed Observations
- Distance-dependent filtering of background error covariance estimates in an ensemble Kalman filter
- A Sequential Ensemble Kalman Filter for Atmospheric Data Assimilation
- Ensemble size, balance, and model-error representation in an ensemble Kalman filter
- The Met Office global four‐dimensional variational data assimilation scheme