H. Dool

Atmospheric Science · 2000–2016

A researcher in the Science corpus: 6 papers; trusts 6 researchers and is trusted by 19 researchers here, as inferred from the citation graph.

Subfields

Whom H. Dool trusts overall

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

  1. Michael K. Tippett
  2. Francisco J. Doblas-Reyes
  3. A. Barnston
  4. R. Hagedorn
  5. Tim N. Palmer

Who trusts H. Dool overall

  1. Abdelwaheb Hannachi
  2. K. Seo
  3. Álvaro González
  4. Q. Ding
  5. Wanqiu Wang
  6. Ian T. Jolliffe
  7. Seth Westra
  8. Mozheng Wei
  9. N. Johnson
  10. D. Wilks

Papers from H. Dool's perspective

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

  1. The rationale behind the success of multi-model ensembles in seasonal forecasting — I. Basic concept
  2. The rationale behind the success of multi-model ensembles in seasonal forecasting-II
  3. Measures of skill and value of ensemble prediction systems, their interrelationship and the effect of ensemble size
  4. A probability and decision‐model analysis of PROVOST seasonal multi‐model ensemble integrations
  5. A New Vector Partition of the Probability Score
  6. Multi-model seasonal hindcasts over the Euro-Atlantic: skill scores and dynamic features
  7. 「Statistical Methods in the Atmospheric Sciences(2nd edition), International Geophysics Series 91」, Daniel S. Wilks著, Academic Press, 2005年11月, 648頁, $94.95, ISBN978-0-12-751966-1(本だな)
  8. The rationale behind the success of multi-model ensembles in seasonal forecasting — II. Calibration and combination
  9. Predictions of Nino3.4 SST in CFSv1 and CFSv2: a diagnostic comparison (Climate Dynamics)
  10. Is unequal weighting significantly better than equal weighting for multi‐model forecasting?

Their papers