J. Liebert

945 citations
7 papers · 754 · 1 hit paper · h-index 3

Impact in

Papers in

J. Liebert

7 papers receiving 737 citations

J. Liebert's Hit Papers

HESS Opinions "Should we apply bias correction to global and regional climate model data?" 2012 · 593 citations
5930+4+9Years since publication100200300400500

Peers

J. Liebert
Comparison fields: 5 of 38
  • Global and Planetary Change 650
  • Water Science and Technology 322
  • Atmospheric Science 366
  • Ecology, Evolution, Behavior and Systematics 105
  • Environmental Engineering 46
Replace Chiyu Lin with:
Chiyu Lin United States
Sonja Folwell United Kingdom
Ellen Dyer United Kingdom
Caroline Mourão Brazil
Reepal Shah United States
B. Shifteh Some’e Iran
Alfred de Jager Italy
Irene Kohn Germany
Koji Dairaku Japan
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Citations per field
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Countries citing papers authored by J. Liebert

Since Specialization
Citations

This map shows the geographic impact of J. Liebert's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by J. Liebert with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites J. Liebert more than expected).

Fields of papers citing papers by J. Liebert

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by J. Liebert. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by J. Liebert. The network helps show where J. Liebert may publish in the future.

Co-authors

The 13 scholars most cited alongside J. Liebert, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with J. Liebert Line = papers co-authored together J. Liebert links everyone, so they are left out of the graph.

All Works

7 of 7 papers shown
#Work
1
HESS Opinions "Should we apply bias correction to global and regional climate model data?"
Hit paper breakdown →
2012593
2
Should we apply bias correction to global and regional climate model data
2012121
3 201333
4
Climate change impact on medium and small sized river catchments in Germany: An ensemble assessment
20122
5 20072
6
Flood hazards in a changing climate. Final report
20122
7
Operable Water Quantity Model System to Support Water Quality Management in a River Sub-Basin
20021

About J. Liebert

J. Liebert is a scholar working on Global and Planetary Change, Water Science and Technology, Atmospheric Science, Ecology and Environmental Chemistry, having authored 7 papers that have together received 754 indexed citations. Recurring topics across this work include Hydrology and Watershed Management Studies (3 papers), Climate variability and models (3 papers), Flood Risk Assessment and Management (2 papers), Atmospheric and Environmental Gas Dynamics (2 papers), Hydrological Forecasting Using AI (1 paper), Soil and Water Nutrient Dynamics (1 paper), Cryospheric studies and observations (1 paper) and Hydrology and Drought Analysis (1 paper). The work is most often cited by research in Global and Planetary Change (650 citations), Water Science and Technology (322 citations), Atmospheric Science (366 citations), Ecology, Evolution, Behavior and Systematics (105 citations) and Environmental Engineering (46 citations). J. Liebert has collaborated with scholars based in Germany and Sweden. Frequent co-authors include Uwe Ehret, Volker Wulfmeyer, Erwin Zehe, Kirsten Warrach‐Sagi, Harald Kunstmann, Hendrik Feldmann, Bruno Merz, Sven Wagner, Peter Berg and Doris Duethmann. Their work appears in journals such as Advances in geosciences, Hydrology and earth system sciences, Journal of Hydrometeorology and EGUGA.

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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