Dana Parr

486 total citations
9 papers, 399 citations indexed

About

Dana Parr is a scholar working on Global and Planetary Change, Water Science and Technology and Nature and Landscape Conservation. According to data from OpenAlex, Dana Parr has authored 9 papers receiving a total of 399 indexed citations (citations by other indexed papers that have themselves been cited), including 9 papers in Global and Planetary Change, 7 papers in Water Science and Technology and 1 paper in Nature and Landscape Conservation. Recurrent topics in Dana Parr's work include Climate variability and models (8 papers), Hydrology and Watershed Management Studies (7 papers) and Plant Water Relations and Carbon Dynamics (6 papers). Dana Parr is often cited by papers focused on Climate variability and models (8 papers), Hydrology and Watershed Management Studies (7 papers) and Plant Water Relations and Carbon Dynamics (6 papers). Dana Parr collaborates with scholars based in United States, China and Bangladesh. Dana Parr's co-authors include Guiling Wang, Miao Yu, Dagang Wang, Kevin E. Trenberth, Amir Erfanian, Michael G. Bosilovich, K. F. Ahmed, David M. Bjerklie, Weilin Liao and Youlong Xia and has published in prestigious journals such as Nature Climate Change, Climatic Change and Hydrology and earth system sciences.

In The Last Decade

Dana Parr

9 papers receiving 389 citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name	h						Papers	Cites
Dana Parr United States	7	353	201	124	35	34	9	399
Lishu Lian China	8	314 0.9×	199 1.0×	123 1.0×	28 0.8×	60 1.8×	14	386
Wilson Gitau Kenya	8	327 0.9×	166 0.8×	162 1.3×	54 1.5×	46 1.4×	14	414
Dominique Paquin Canada	10	453 1.3×	381 1.9×	88 0.7×	22 0.6×	28 0.8×	24	545
Jinhu Yang China	9	323 0.9×	193 1.0×	103 0.8×	33 0.9×	24 0.7×	28	416
Yanjun Jiao Canada	5	234 0.7×	264 1.3×	112 0.9×	22 0.6×	19 0.6×	6	364
Sumira Nazir Zaz India	6	163 0.5×	179 0.9×	88 0.7×	21 0.6×	49 1.4×	7	317
Heiko Prasse Germany	3	331 0.9×	77 0.4×	153 1.2×	22 0.6×	32 0.9×	5	359
Amir Erfanian United States	8	456 1.3×	251 1.2×	91 0.7×	41 1.2×	33 1.0×	14	521
Julian Mayes United Kingdom	11	239 0.7×	178 0.9×	65 0.5×	26 0.7×	20 0.6×	38	368
Fu Congbin China	11	340 1.0×	261 1.3×	116 0.9×	31 0.9×	56 1.6×	28	436

Countries citing papers authored by Dana Parr

Since Specialization

Citations

This map shows the geographic impact of Dana Parr'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 Dana Parr with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Dana Parr more than expected).

Fields of papers citing papers by Dana Parr

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Dana Parr. 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 Dana Parr. The network helps show where Dana Parr may publish in the future.

Co-authorship network of co-authors of Dana Parr

This figure shows the co-authorship network connecting the top 25 collaborators of Dana Parr. A scholar is included among the top collaborators of Dana Parr based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Dana Parr. Dana Parr is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

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9 of 9 papers shown

Wang, Dagang, Guiling Wang, Dana Parr, et al.. (2017). Incorporating remote sensing ET into Community Land Model version 4.5. 3 indexed citations

Wang, Dagang, et al.. (2017). Incorporating remote sensing-based ET estimates into the Community Land Model version 4.5. Hydrology and earth system sciences. 21(7). 3557–3577. 9 indexed citations

Wang, Guiling, Dagang Wang, Kevin E. Trenberth, et al.. (2017). The peak structure and future changes of the relationships between extreme precipitation and temperature. Nature Climate Change. 7(4). 268–274. 252 indexed citations

Parr, Dana, et al.. (2016). Understanding evapotranspiration trends and their driving mechanisms over the NLDAS domain based on numerical experiments using CLM4.5. Journal of Geophysical Research Atmospheres. 121(13). 7729–7745. 11 indexed citations

Parr, Dana. (2015). Understanding the Hydrological Impacts of Climate Variability and Climate Change based on Numerical Modeling and Observations. OpenCommons - UConn (University of Connecticut). 1 indexed citations

Parr, Dana, Guiling Wang, & David M. Bjerklie. (2015). Integrating Remote Sensing Data on Evapotranspiration and Leaf Area Index with Hydrological Modeling: Impacts on Model Performance and Future Predictions. Journal of Hydrometeorology. 16(5). 2086–2100. 33 indexed citations

Parr, Dana, Guiling Wang, & K. F. Ahmed. (2015). Hydrological changes in the U.S. Northeast using the Connecticut River Basin as a case study: Part 2. Projections of the future. Global and Planetary Change. 133. 167–175. 18 indexed citations

Parr, Dana & Guiling Wang. (2014). Hydrological changes in the U.S. Northeast using the Connecticut River Basin as a case study: Part 1. Modeling and analysis of the past. Global and Planetary Change. 122. 208–222. 21 indexed citations

Yu, Miao, Guiling Wang, Dana Parr, & K. F. Ahmed. (2014). Future changes of the terrestrial ecosystem based on a dynamic vegetation model driven with RCP8.5 climate projections from 19 GCMs. Climatic Change. 127(2). 257–271. 51 indexed citations

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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