H-Index & Metrics Best Publications

H-Index & Metrics

Discipline name H-index Citations Publications World Ranking National Ranking
Environmental Sciences D-index 68 Citations 26,418 199 World Ranking 698 National Ranking 346

Overview

What is he best known for?

The fields of study he is best known for:

  • Statistics
  • Meteorology
  • Hydrology

The scientist’s investigation covers issues in Data assimilation, Meteorology, Water content, Climatology and Remote sensing. Rolf H. Reichle interconnects Radiometer, Drainage basin, Scanning multichannel microwave radiometer, Snow and Anomaly in the investigation of issues within Data assimilation. In his articles, Rolf H. Reichle combines various disciplines, including Meteorology and Context.

His work deals with themes such as Errors-in-variables models, Downscaling and Ensemble Kalman filter, which intersect with Water content. In the field of Climatology, his study on Forcing overlaps with subjects such as Retrospective analysis. The various areas that he examines in his Remote sensing study include Mean squared error, Mathematical model, Relation and Standard deviation.

His most cited work include:

  • MERRA: NASA’s Modern-Era Retrospective Analysis for Research and Applications (3577 citations)
  • The Modern-Era Retrospective Analysis for Research and Applications, Version 2 (MERRA-2). (1936 citations)
  • The Soil Moisture Active Passive (SMAP) Mission (1780 citations)

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

His primary scientific interests are in Water content, Data assimilation, Remote sensing, Atmospheric sciences and Meteorology. His Water content study integrates concerns from other disciplines, such as Soil science and Brightness temperature. His Data assimilation study also includes

  • Ensemble Kalman filter which is related to area like Errors-in-variables models,
  • Climatology which connect with Surface runoff.

He has researched Remote sensing in several fields, including Scatterometer and Atmospheric radiative transfer codes. His research in Atmospheric sciences intersects with topics in Soil water, Carbon cycle and Precipitation. Rolf H. Reichle has included themes like Anomaly, Climate model, Data system and Water cycle in his Meteorology study.

He most often published in these fields:

  • Water content (57.89%)
  • Data assimilation (43.77%)
  • Remote sensing (31.02%)

What were the highlights of his more recent work (between 2017-2021)?

  • Water content (57.89%)
  • Atmospheric sciences (26.59%)
  • Data assimilation (43.77%)

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

His primary areas of study are Water content, Atmospheric sciences, Data assimilation, Remote sensing and Hydrology. His Water content research integrates issues from Soil science, Soil water, Streamflow and Brightness temperature. His Atmospheric sciences research is multidisciplinary, incorporating perspectives in Radiometer, Carbon cycle, Precipitation and Evapotranspiration.

His Data assimilation research is multidisciplinary, relying on both Drainage basin, Climatology and Snow. His Snow research incorporates themes from Water cycle and Spatial variability. He usually deals with Remote sensing and limits it to topics linked to Earth observation and Hydrosphere and Anthroposphere.

Between 2017 and 2021, his most popular works were:

  • Satellite and in situ observations for advancing global earth surface modelling: A review (47 citations)
  • Snow depth variability in the Northern Hemisphere mountains observed from space. (39 citations)
  • Assessment of MERRA-2 Land Surface Energy Flux Estimates (35 citations)

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

  • Statistics
  • Meteorology
  • Remote sensing

His primary areas of investigation include Water content, Remote sensing, Atmospheric sciences, Data assimilation and Surface runoff. His Water content study combines topics in areas such as Soil science, Soil water, Surface water, Precipitation and Streamflow. The concepts of his Remote sensing study are interwoven with issues in In situ, Earth observation and Downscaling.

He performs multidisciplinary studies into Data assimilation and Assimilation in his work. His Surface runoff study combines topics from a wide range of disciplines, such as Snow, Eddy covariance and Groundwater. Rolf H. Reichle combines subjects such as Sensible heat and Water cycle with his study of Climatology.

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

MERRA: NASA’s Modern-Era Retrospective Analysis for Research and Applications

Michele M. Rienecker;Max J. Suarez;Ronald Gelaro;Ricardo Todling.
Journal of Climate (2011)

4314 Citations

The Modern-Era Retrospective Analysis for Research and Applications, Version 2 (MERRA-2).

Ronald Gelaro;Will McCarty;Max J. Suárez;Max J. Suárez;Ricardo Todling.
Journal of Climate (2017)

2480 Citations

The Soil Moisture Active Passive (SMAP) Mission

Dara Entekhabi;Eni G Njoku;Peggy E O'Neill;Kent H Kellogg.
Proceedings of the IEEE (2010)

2236 Citations

Hydrologic Data Assimilation with the Ensemble Kalman Filter

Rolf H. Reichle;Dennis B. McLaughlin;Dara Entekhabi.
Monthly Weather Review (2002)

899 Citations

Bias reduction in short records of satellite soil moisture

Rolf H. Reichle;Rolf H. Reichle;Randal D. Koster.
Geophysical Research Letters (2004)

494 Citations

Data assimilation methods in the Earth sciences

Rolf H. Reichle;Rolf H. Reichle.
Advances in Water Resources (2008)

448 Citations

Assessment and Enhancement of MERRA Land Surface Hydrology Estimates

Rolf H. Reichle;Randal D. Koster;Gabriëlle J. M. De Lannoy;Barton A. Forman.
Journal of Climate (2011)

436 Citations

Comparison and assimilation of global soil moisture retrievals from the Advanced Microwave Scanning Radiometer for the Earth Observing System (AMSR‐E) and the Scanning Multichannel Microwave Radiometer (SMMR)

Rolf H. Reichle;Rolf H. Reichle;Randal D. Koster;Ping Liu;Ping Liu;Sarith P. P. Mahanama;Sarith P. P. Mahanama.
Journal of Geophysical Research (2007)

416 Citations

Extended versus Ensemble Kalman Filtering for Land Data Assimilation

Rolf H. Reichle;Jeffrey P. Walker;Randal D. Koster;Paul R. Houser.
Journal of Hydrometeorology (2002)

395 Citations

Assimilation of GRACE Terrestrial Water Storage Data into a Land Surface Model: Results for the Mississippi River Basin

Benjamin F. Zaitchik;Matthew Rodell;Rolf H. Reichle.
Journal of Hydrometeorology (2008)

391 Citations

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