Neill Bowler

Atmospheric Science · 2006–2009

A researcher in the Science corpus: 3 papers; trusts 8 researchers and is trusted by 2 researchers here, as inferred from the citation graph.

Subfields

Whom Neill Bowler trusts overall

Their strongest outbound trust, strongest first, inferred from their citations.

  1. A. Seed
  2. Urs Germann
  3. Geir Evensen
  4. Xuguang Wang
  5. G. Pegram
  6. H. Mitchell
  7. C. Bishop
  8. Brian R. Hunt
  9. I. Zawadzki
  10. Hans Hersbach

Who trusts Neill Bowler overall

  1. R. Bannister
  2. P. Cheung
  3. Christine Johnson
  4. Sharanya J. Majumdar
  5. Adam Clayton
  6. Peter A. Clark
  7. F. Bouttier
  8. L. Duc
  9. Takemasa Miyoshi
  10. H. Yeung

Papers from Neill Bowler's perspective

Ordered by how strongly the researchers Neill Bowler trusts endorse each paper. Same corpus, a different order for every researcher.

  1. The Ensemble Kalman Filter: theoretical formulation and practical implementation
  2. A Comparison of Breeding and Ensemble Transform Kalman Filter Ensemble Forecast Schemes
  3. A New Vector Partition of the Probability Score
  4. Which Is Better, an Ensemble of Positive–Negative Pairs or a Centered Spherical Simplex Ensemble?
  5. Multiscale Statistical Properties of a High-Resolution Precipitation Forecast
  6. A kinetic energy backscatter algorithm for use in ensemble prediction systems
  7. Decomposition of the Continuous Ranked Probability Score for Ensemble Prediction Systems
  8. VERIFICATION OF FORECASTS EXPRESSED IN TERMS OF PROBABILITY
  9. A Dynamic and Spatial Scaling Approach to Advection Forecasting
  10. Ensemble size, balance, and model-error representation in an ensemble Kalman filter

Their papers