David M. Mocko

10.3k total citations · 1 hit paper
81 papers, 3.6k citations indexed

About

David M. Mocko is a scholar working on Global and Planetary Change, Atmospheric Science and Water Science and Technology. According to data from OpenAlex, David M. Mocko has authored 81 papers receiving a total of 3.6k indexed citations (citations by other indexed papers that have themselves been cited), including 51 papers in Global and Planetary Change, 45 papers in Atmospheric Science and 30 papers in Water Science and Technology. Recurrent topics in David M. Mocko's work include Climate variability and models (42 papers), Hydrology and Watershed Management Studies (30 papers) and Meteorological Phenomena and Simulations (27 papers). David M. Mocko is often cited by papers focused on Climate variability and models (42 papers), Hydrology and Watershed Management Studies (30 papers) and Meteorological Phenomena and Simulations (27 papers). David M. Mocko collaborates with scholars based in United States, Australia and United Kingdom. David M. Mocko's co-authors include C. D. Peters‐Lidard, Sujay V. Kumar, Youlong Xia, Michael Ek, Eric F. Wood, Justin Sheffield, Michael G. Bosilovich, Ben Livneh, Kenneth E. Mitchell and Helin Wei and has published in prestigious journals such as SHILAP Revista de lepidopterología, Journal of Geophysical Research Atmospheres and Remote Sensing of Environment.

In The Last Decade

David M. Mocko

78 papers receiving 3.5k citations

Hit Papers

align trajectories

What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

Continental‐scale water and energy flux analysis and validation for the North American Land Data Assimilation System project phase 2 (NLDAS‐2): 1. Intercomparison and application of model products

2011 1.0k citations Kenneth E. Mitchell, Michael Ek et al. profile →

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
David M. Mocko United States	27	2.3k	1.7k	1.3k	1.2k	385	81	3.6k
Sarith Mahanama United States	28	1.9k 0.8×	1.9k 1.1×	958 0.7×	1.4k 1.2×	247 0.6×	54	3.3k
Robin van der Schalie Austria	17	1.9k 0.8×	1.3k 0.7×	941 0.7×	1.2k 1.0×	219 0.6×	38	3.1k
Diego Fernández‐Prieto Italy	19	2.4k 1.0×	1.2k 0.7×	1.3k 1.0×	967 0.8×	296 0.8×	60	3.4k
Mekonnen Gebremichael United States	33	2.4k 1.0×	2.2k 1.2×	1.4k 1.0×	1.1k 0.9×	183 0.5×	98	3.7k
Bertrand Decharme France	42	3.0k 1.3×	2.0k 1.2×	1.5k 1.1×	975 0.8×	912 2.4×	101	4.6k
Helin Wei United States	20	1.7k 0.7×	1.4k 0.8×	951 0.7×	735 0.6×	183 0.5×	27	2.6k
Aaron Boone France	37	3.0k 1.3×	2.8k 1.6×	1.6k 1.2×	951 0.8×	367 1.0×	122	4.7k
Souhail Boussetta United Kingdom	24	2.9k 1.3×	2.4k 1.4×	863 0.6×	1.1k 1.0×	333 0.9×	45	4.5k
Hans Lievens Belgium	23	1.8k 0.8×	2.1k 1.2×	1.2k 0.9×	2.0k 1.6×	237 0.6×	68	4.0k
Michael A. Palecki United States	22	2.4k 1.0×	2.3k 1.3×	479 0.4×	747 0.6×	336 0.9×	45	3.6k

Countries citing papers authored by David M. Mocko

Since Specialization

Citations

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

Fields of papers citing papers by David M. Mocko

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by David M. Mocko. 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 David M. Mocko. The network helps show where David M. Mocko may publish in the future.

Co-authorship network of co-authors of David M. Mocko

This figure shows the co-authorship network connecting the top 25 collaborators of David M. Mocko. A scholar is included among the top collaborators of David M. Mocko 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 David M. Mocko. David M. Mocko is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

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20 of 20 papers shown

Barlow, Mathew, Laurie Agel, Jung‐Hoon Kim, et al.. (2024). Impact of Vegetation Assimilation on Flash Drought Characteristics across the Continental United States. Journal of Hydrometeorology. 25(9). 1263–1281.

He, Cenlin, Fei Chen, Michael Barlage, et al.. (2023). Enhancing the Community Noah-MP Land Model Capabilities for Earth Sciences and Applications. Bulletin of the American Meteorological Society. 104(11). E2023–E2029. 5 indexed citations

Nie, Wanshu, Sujay V. Kumar, Kristi R. Arsenault, et al.. (2022). Towards effective drought monitoring in the Middle East and North Africa (MENA) region: implications from assimilating leaf area index and soil moisture into the Noah-MP land surface model for Morocco. Hydrology and earth system sciences. 26(9). 2365–2386. 24 indexed citations

Nie, Wanshu, Sujay V. Kumar, Kristi R. Arsenault, et al.. (2021). Towards Effective Drought Monitoring in the Middle East and North Africa (MENA) Region: Implications from Assimilating Leaf Area Index and Soil Moisture into the Noah-MP Land Surface Model for Morocco. 3 indexed citations

Maggioni, Viviana, Paul R. Houser, Yuan Xue, et al.. (2020). The influence of assimilating leaf area index in a land surface model on global water fluxes and storages. Hydrology and earth system sciences. 24(7). 3775–3788. 8 indexed citations

Xue, Yuan, Paul R. Houser, Timothy Sauer, et al.. (2020). A synthetic experiment to investigate the potential of assimilating LAI through direct insertion in a land surface model. SHILAP Revista de lepidopterología. 9. 100063–100063. 10 indexed citations

Yoon, Yeosang, Sujay V. Kumar, Barton A. Forman, et al.. (2019). Evaluating the Uncertainty of Terrestrial Water Budget Components Over High Mountain Asia. Frontiers in Earth Science. 7. 51 indexed citations

Mocko, David M.. (2018). Drought Depiction in the Noah-MP (Multiphysics) Land Surface Model in the North American Land Data Assimilation System (NLDAS). 1 indexed citations

Arsenault, Kristi R., Sujay V. Kumar, Shugong Wang, et al.. (2018). The Land surface Data Toolkit (LDT v7.2) – a data fusion environment for land data assimilation systems. Geoscientific model development. 11(9). 3605–3621. 45 indexed citations

10.

Kumar, Sujay V., et al.. (2017). Role of forcing uncertainty and background model error characterization in snow data assimilation. Hydrology and earth system sciences. 21(6). 2637–2647. 18 indexed citations

11.

Rui, Hualan, et al.. (2016). National Climate Assessment - Land Data Assimilation System (NCA-LDAS) Data at NASA GES DISC. 2014 AGU Fall Meeting. 2014. 1 indexed citations

12.

Kumar, Sujay V., et al.. (2016). Role of forcing uncertainty and model error background characterization in snow data assimilation. 4 indexed citations

13.

Ek, M. B., Yu Xia, Wei Han, et al.. (2014). A Successful Example of Transitioning Research to NCEP Operations: The North American Land Data Assimilation System (NLDAS). AGU Fall Meeting Abstracts. 2014. 1 indexed citations

14.

Kala, Jatin, Jason P. Evans, A. J. Pitman, et al.. (2014). Implementation of a soil albedo scheme in the CABLEv1.4b land surface model and evaluation against MODIS estimates over Australia. Geoscientific model development. 7(5). 2121–2140. 16 indexed citations

15.

Vollmer, Bruce, et al.. (2012). Analysis of Water and Energy Budgets and Trends Using the NLDAS Monthly Data Sets. NASA STI Repository (National Aeronautics and Space Administration). 2012.

16.

Mocko, David M., et al.. (2012). Changes to Drought Metrics within the North American Land Data Assimilation System (NLDAS) from the Assimilation of Soil Moisture and Snow. AGUFM. 2012. 1 indexed citations

17.

Peters‐Lidard, C. D., et al.. (2006). Using Remotely-Sensed Estimates of Soil Moisture to Infer Spatially Distributed Soil Hydraulic Properties. AGU Spring Meeting Abstracts. 2007. 2 indexed citations

18.

Mocko, David M., et al.. (2006). The Relative Roles of Soil, Land Cover, and Precipitation Uncertainty for Watershed-scale Soil Moisture Prediction in a Semi-arid Environment. AGU Spring Meeting Abstracts. 2007. 1 indexed citations

19.

Sud, Y. C. & David M. Mocko. (1999). New Snow-Physics to Complement SSiB. Journal of the Meteorological Society of Japan Ser II. 77(1B). 335–348. 25 indexed citations

20.

Mocko, David M., G. K. Walker, & Y. C. Sud. (1999). New Snow-Physics to Complement SSiB. Journal of the Meteorological Society of Japan Ser II. 77(1B). 349–366. 12 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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