Jonathan Hobbs

995 total citations
36 papers, 388 citations indexed

About

Jonathan Hobbs is a scholar working on Global and Planetary Change, Atmospheric Science and Artificial Intelligence. According to data from OpenAlex, Jonathan Hobbs has authored 36 papers receiving a total of 388 indexed citations (citations by other indexed papers that have themselves been cited), including 24 papers in Global and Planetary Change, 15 papers in Atmospheric Science and 8 papers in Artificial Intelligence. Recurrent topics in Jonathan Hobbs's work include Atmospheric and Environmental Gas Dynamics (19 papers), Atmospheric chemistry and aerosols (8 papers) and Atmospheric Ozone and Climate (7 papers). Jonathan Hobbs is often cited by papers focused on Atmospheric and Environmental Gas Dynamics (19 papers), Atmospheric chemistry and aerosols (8 papers) and Atmospheric Ozone and Climate (7 papers). Jonathan Hobbs collaborates with scholars based in United States, United Kingdom and India. Jonathan Hobbs's co-authors include M. R. Gunson, Amy Braverman, Adam Loy, J. Gordon Arbuckle, Lois Wright Morton, M. Turmon, James McDuffie, Vivienne H. Payne, Fabiano Oyafuso and Noel Cressie and has published in prestigious journals such as Nature, Technometrics and Remote Sensing of Environment.

In The Last Decade

Jonathan Hobbs

30 papers receiving 376 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Jonathan Hobbs United States 12 247 164 53 46 43 36 388
Muhammad Shahzaman China 10 390 1.6× 197 1.2× 14 0.3× 66 1.4× 61 1.4× 17 514
Béatrice Morel France 15 339 1.4× 401 2.4× 52 1.0× 6 0.1× 17 0.4× 32 493
A. Savtchenko United States 9 434 1.8× 389 2.4× 34 0.6× 21 0.5× 69 1.6× 32 587
Yang Han China 11 268 1.1× 215 1.3× 83 1.6× 13 0.3× 159 3.7× 33 549
Christina Papagiannopoulou Belgium 6 199 0.8× 82 0.5× 30 0.6× 29 0.6× 89 2.1× 11 314
Bruno Dürr Switzerland 10 480 1.9× 423 2.6× 121 2.3× 20 0.4× 21 0.5× 16 590
Elisabetta Ricciardelli Italy 13 286 1.2× 258 1.6× 119 2.2× 17 0.4× 52 1.2× 33 484
Sandra García-Galiano Spain 11 208 0.8× 59 0.4× 7 0.1× 145 3.2× 33 0.8× 26 361
M. L. Cancillo Spain 14 506 2.0× 488 3.0× 100 1.9× 18 0.4× 18 0.4× 44 678
Nicolas Fournier United Kingdom 15 244 1.0× 359 2.2× 11 0.2× 11 0.2× 34 0.8× 44 650

Countries citing papers authored by Jonathan Hobbs

Since Specialization
Citations

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

Fields of papers citing papers by Jonathan Hobbs

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Jonathan Hobbs

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

All Works

20 of 20 papers shown
1.
Marchetti, Chiara, Jonathan Hobbs, Peter Somkuti, & Joshua L. Laughner. (2025). A Study on Inferring Daytime Variations of XCO2 ${\text{XCO}}_{2}$ From Current and Future Space‐Based Missions. Earth and Space Science. 12(8).
2.
Laughner, Joshua L., C. O’Dell, Steven T. Massie, et al.. (2025). Uncertainty‐Aware Machine Learning Bias Correction and Filtering for OCO‐2: 1. Earth and Space Science. 12(7).
3.
Susiluoto, Jouni, et al.. (2025). Forward model emulator for atmospheric radiative transfer using Gaussian processes and cross validation. Atmospheric measurement techniques. 18(3). 673–694.
4.
Hobbs, Jonathan, Matthias Katzfuß, Nguyen Hai Dang, Vineet Yadav, & Junjie Liu. (2024). Functional analysis of variance (ANOVA) for carbon flux estimates from remote sensing data. Geoscientific model development. 17(3). 1133–1151. 1 indexed citations
5.
Konomi, Bledar A., et al.. (2023). Bayesian Latent Variable Co-kriging Model in Remote Sensing for Quality Flagged Observations. Journal of Agricultural Biological and Environmental Statistics. 28(3). 423–441. 1 indexed citations
6.
Russell, James M. & Jonathan Hobbs. (2023). A year of the Animal Health and Welfare Pathway: focus on sheep. In Practice. 45(10). 619–625. 1 indexed citations
7.
Kuusela, Mikael, et al.. (2022). Objective Frequentist Uncertainty Quantification for Atmospheric \(\mathrm{CO}_2\) Retrievals. SIAM/ASA Journal on Uncertainty Quantification. 10(3). 827–859. 3 indexed citations
8.
9.
Juffe‐Bignoli, Diego, Neil M. Burgess, Jonathan Hobbs, et al.. (2021). Mitigating the Impacts of Development Corridors on Biodiversity: A Global Review. Frontiers in Ecology and Evolution. 9. 13 indexed citations
10.
Massoud, Elias, M. Turmon, J. T. Reager, et al.. (2020). Cascading Dynamics of the Hydrologic Cycle in California Explored through Observations and Model Simulations. Geosciences. 10(2). 71–71. 14 indexed citations
11.
Thompson, David R., Philip G. Brodrick, Niklas Bohn, et al.. (2020). Toward comprehensive uncertainty predictions for remote imaging spectroscopy. 122. 10–10. 1 indexed citations
12.
Hobbs, Jonathan, Jenný Brynjarsdóttir, Marko Laine, et al.. (2019). Accelerated MCMC for Satellite-Based Measurements of Atmospheric CO2. Remote Sensing. 11(17). 2061–2061. 8 indexed citations
13.
David, Cédric H., et al.. (2019). Analytical Propagation of Runoff Uncertainty Into Discharge Uncertainty Through a Large River Network. Geophysical Research Letters. 46(14). 8102–8113. 18 indexed citations
14.
Ramapriyan, H. K., Jonathan Hobbs, Robert R. Downs, et al.. (2019). Understanding the Various Perspectives of Earth Science Observational Data Uncertainty. Figshare. 2 indexed citations
15.
Ramanathan, Anand, Hai Nguyen, Xiaoli Sun, et al.. (2018). A singular value decomposition framework for retrievals with vertical distribution information from greenhouse gas column absorption spectroscopy measurements. Atmospheric measurement techniques. 11(8). 4909–4928. 12 indexed citations
16.
Brynjarsdóttir, Jenný, Jonathan Hobbs, Amy Braverman, & Lukas Mandrake. (2018). Optimal Estimation Versus MCMC for $$\mathrm{{CO}}_{2}$$ CO 2 Retrievals. Journal of Agricultural Biological and Environmental Statistics. 23(2). 297–316. 4 indexed citations
17.
Connor, B. J., Hartmut Bösch, James McDuffie, et al.. (2016). Quantification of uncertainties in OCO-2 measurements of XCO 2 :simulations and linear error analysis. Atmospheric measurement techniques. 9(10). 5227–5238. 88 indexed citations
18.
Cervato, Cinzia, et al.. (2011). Does Students' Source of Knowledge Affect Their Understanding of Volcanic Systems?.. Iowa State University Digital Repository (Iowa State University). 41(1). 14–19. 3 indexed citations
19.
20.
Curtis, Nigel, Jonathan Hobbs, Campbell Thompson, et al.. (1997). High serum D-lactate in patients on continuous ambulatory peritoneal dialysis. Nephrology Dialysis Transplantation. 12(5). 981–983. 11 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.

Explore authors with similar magnitude of impact

Breakdown of academic impact, for papers by Muhammad Shahzaman Breakdown of academic impact, for papers by Béatrice Morel Breakdown of academic impact, for papers by A. Savtchenko Breakdown of academic impact, for papers by Yang Han Breakdown of academic impact, for papers by Christina Papagiannopoulou Breakdown of academic impact, for papers by Bruno Dürr Breakdown of academic impact, for papers by Elisabetta Ricciardelli Breakdown of academic impact, for papers by Sandra García-Galiano Breakdown of academic impact, for papers by M. L. Cancillo Breakdown of academic impact, for papers by Nicolas Fournier
Rankless by CCL
2026