D-Index & Metrics Best Publications

D-Index & Metrics D-index (Discipline H-index) only includes papers and citation values for an examined discipline in contrast to General H-index which accounts for publications across all disciplines.

Discipline name D-index D-index (Discipline H-index) only includes papers and citation values for an examined discipline in contrast to General H-index which accounts for publications across all disciplines. Citations Publications World Ranking National Ranking
Environmental Sciences D-index 40 Citations 8,514 99 World Ranking 3319 National Ranking 1460

Overview

What is he best known for?

The fields of study he is best known for:

  • Statistics
  • Oceanography
  • Meteorology

Andrew M. Moore focuses on Climatology, Data assimilation, Meteorology, Oceanography and Forcing. His study in Climatology is interdisciplinary in nature, drawing from both Current, Atmosphere and Predictability. His Predictability research incorporates themes from Anomaly and Ocean current.

His Data assimilation research includes elements of Ocean modeling, Constraint and Applied mathematics. His research in Oceanography focuses on subjects like Ecosystem, which are connected to The Blob, Productivity, Glider and Pacific decadal oscillation. His research integrates issues of Stochastic process, Kelvin wave and Heat flux in his study of Forcing.

His most cited work include:

  • Coupled ocean–atmosphere dynamics in the Indian Ocean during 1997–98 (1482 citations)
  • Ocean forecasting in terrain-following coordinates: Formulation and skill assessment of the Regional Ocean Modeling System (812 citations)
  • Stochastic Forcing of ENSO by the Intraseasonal Oscillation (241 citations)

What are the main themes of his work throughout his whole career to date?

Andrew M. Moore mainly focuses on Climatology, Data assimilation, Meteorology, Ocean current and Regional Ocean Modeling System. The various areas that Andrew M. Moore examines in his Climatology study include Oceanography, Upwelling and Predictability. His Data assimilation research focuses on Applied mathematics and how it relates to Mathematical optimization and Covariance.

Andrew M. Moore combines subjects such as Assimilation, Forcing, Argo and Nonlinear system with his study of Meteorology. Andrew M. Moore has included themes like Hydrography and Circulation in his Regional Ocean Modeling System study. His studies examine the connections between Forcing and genetics, as well as such issues in Wind stress, with regards to Heat flux.

He most often published in these fields:

  • Climatology (50.68%)
  • Data assimilation (42.47%)
  • Meteorology (29.45%)

What were the highlights of his more recent work (between 2013-2021)?

  • Data assimilation (42.47%)
  • Climatology (50.68%)
  • Regional Ocean Modeling System (19.86%)

In recent papers he was focusing on the following fields of study:

The scientist’s investigation covers issues in Data assimilation, Climatology, Regional Ocean Modeling System, Oceanography and Meteorology. His Data assimilation study integrates concerns from other disciplines, such as Covariance, Statistics, Ocean observations and Ocean current. His Climatology research is multidisciplinary, incorporating elements of Assimilation and Circulation.

The various areas that Andrew M. Moore examines in his Regional Ocean Modeling System study include Hydrography, Sea surface temperature, Sea-surface height and Geostrophic wind. His work on Upwelling as part of general Oceanography study is frequently linked to Wind circulation, therefore connecting diverse disciplines of science. Andrew M. Moore interconnects Kalman filter and Argo in the investigation of issues within Meteorology.

Between 2013 and 2021, his most popular works were:

  • Impacts of the 2015–2016 El Niño on the California Current System: Early assessment and comparison to past events (165 citations)
  • Regional Ocean Data Assimilation (74 citations)
  • ENSO and the California Current coastal upwelling response (58 citations)

In his most recent research, the most cited papers focused on:

  • Statistics
  • Oceanography
  • Meteorology

His primary areas of investigation include Climatology, Data assimilation, Oceanography, Regional Ocean Modeling System and Sea surface temperature. Forcing and Argo are the core of his Climatology study. His Data assimilation study is focused on Meteorology in general.

Andrew M. Moore focuses mostly in the field of Oceanography, narrowing it down to matters related to Ecosystem and, in some cases, The Blob and Productivity. The concepts of his Regional Ocean Modeling System study are interwoven with issues in Hydrography, Mixed layer, Mathematical model and Deviance. His work carried out in the field of Sea surface temperature brings together such families of science as Bathythermograph, Potential vorticity, Gulf Stream and Temperature salinity diagrams.

This overview was generated by a machine learning system which analysed the scientist’s body of work. If you have any feedback, you can contact us here.

Best Publications

Coupled ocean–atmosphere dynamics in the Indian Ocean during 1997–98

Peter J. Webster;Andrew M. Moore;Johannes P. Loschnigg;Robert R. Leben.
Nature (1999)

2023 Citations

Ocean forecasting in terrain-following coordinates: Formulation and skill assessment of the Regional Ocean Modeling System

D. B. Haidvogel;H. Arango;W. P. Budgell;B. D. Cornuelle.
Journal of Computational Physics (2008)

956 Citations

Stochastic Forcing of ENSO by the Intraseasonal Oscillation

Andrew M. Moore;Richard Kleeman.
Journal of Climate (1999)

337 Citations

Impacts of the 2015–2016 El Niño on the California Current System: Early assessment and comparison to past events

.
Geophysical Research Letters (2016)

302 Citations

The Regional Ocean Modeling System (ROMS) 4-dimensional variational data assimilation systems Part I - System overview and formulation

Andrew M. Moore;Hernan G. Arango;Gregoire Broquet;Brian S. Powell.
Progress in Oceanography (2011)

256 Citations

The dynamics of error growth and predictability in a coupled model of ENSO

Andrew M. Moore;Richard Kleeman.
Quarterly Journal of the Royal Meteorological Society (1996)

234 Citations

A Theory for the Limitation of ENSO Predictability Due to Stochastic Atmospheric Transients

Richard Kleeman;Andrew M. Moore.
Journal of the Atmospheric Sciences (1997)

229 Citations

A comprehensive ocean prediction and analysis system based on the tangent linear and adjoint of a regional ocean model

Andrew M. Moore;Hernan G. Arango;Emanuele Di Lorenzo;Bruce D. Cornuelle.
Ocean Modelling (2004)

211 Citations

Nutrient and salinity decadal variations in the central and eastern North Pacific

E. Di Lorenzo;J. Fiechter;N. Schneider;A. Bracco.
Geophysical Research Letters (2009)

149 Citations

Interdecadal modulation of Australian rainfall

J. M. Arblaster;G. A. Meehl;A. M. Moore.
Climate Dynamics (2002)

144 Citations

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