Paul W. Stackhouse

7.4k total citations · 3 hit papers
122 papers, 4.8k citations indexed

About

Paul W. Stackhouse is a scholar working on Global and Planetary Change, Atmospheric Science and Artificial Intelligence. According to data from OpenAlex, Paul W. Stackhouse has authored 122 papers receiving a total of 4.8k indexed citations (citations by other indexed papers that have themselves been cited), including 87 papers in Global and Planetary Change, 69 papers in Atmospheric Science and 34 papers in Artificial Intelligence. Recurrent topics in Paul W. Stackhouse's work include Atmospheric aerosols and clouds (52 papers), Atmospheric and Environmental Gas Dynamics (41 papers) and Solar Radiation and Photovoltaics (34 papers). Paul W. Stackhouse is often cited by papers focused on Atmospheric aerosols and clouds (52 papers), Atmospheric and Environmental Gas Dynamics (41 papers) and Solar Radiation and Photovoltaics (34 papers). Paul W. Stackhouse collaborates with scholars based in United States, Greece and Russia. Paul W. Stackhouse's co-authors include Graeme L. Stephens, Si‐Chee Tsay, Piotr J. Flatau, Tristan L’Ecuyer, A. J. Soja, А. И. Сухинин, S. K. Gupta, Seiji Kato, Herman H. Shugart and Martin Wild and has published in prestigious journals such as Nature Communications, SHILAP Revista de lepidopterología and Journal of Geophysical Research Atmospheres.

In The Last Decade

Paul W. Stackhouse

116 papers receiving 4.6k citations

Hit Papers

An update on Earth's energy bala... 1990 2026 2002 2014 2012 2006 1990 200 400 600

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Paul W. Stackhouse United States 29 3.5k 3.0k 520 344 320 122 4.8k
Enrique Sánchez Spain 31 2.9k 0.8× 2.5k 0.8× 104 0.2× 192 0.6× 138 0.4× 119 4.2k
Ronald E. Stewart Canada 37 2.9k 0.8× 3.0k 1.0× 1.5k 2.9× 193 0.6× 1.3k 4.0× 177 6.4k
Fubao Sun China 38 3.5k 1.0× 1.3k 0.4× 139 0.3× 594 1.7× 63 0.2× 127 5.1k
Jan Čermák Germany 30 2.6k 0.7× 2.3k 0.8× 168 0.3× 134 0.4× 52 0.2× 132 3.9k
Bo Jiang China 30 2.2k 0.6× 1.0k 0.3× 285 0.5× 1.0k 3.0× 49 0.2× 123 3.4k
Raúl R. Cordero Chile 25 760 0.2× 887 0.3× 234 0.5× 243 0.7× 190 0.6× 114 2.1k
Babatunde J. Abiodun South Africa 31 2.2k 0.6× 1.2k 0.4× 140 0.3× 166 0.5× 47 0.1× 107 3.0k
Eugene S. Takle United States 40 3.1k 0.9× 2.4k 0.8× 121 0.2× 233 0.7× 30 0.1× 152 5.1k
Hari Prasad Dasari Saudi Arabia 32 1.5k 0.4× 1.5k 0.5× 66 0.1× 261 0.8× 177 0.6× 136 3.2k
M. H. Unsworth United Kingdom 38 2.8k 0.8× 1.8k 0.6× 278 0.5× 620 1.8× 128 0.4× 97 5.0k

Countries citing papers authored by Paul W. Stackhouse

Since Specialization
Citations

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

Fields of papers citing papers by Paul W. Stackhouse

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Paul W. Stackhouse. 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 Paul W. Stackhouse. The network helps show where Paul W. Stackhouse may publish in the future.

Co-authorship network of co-authors of Paul W. Stackhouse

This figure shows the co-authorship network connecting the top 25 collaborators of Paul W. Stackhouse. A scholar is included among the top collaborators of Paul W. Stackhouse 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 Paul W. Stackhouse. Paul W. Stackhouse 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
2.
Burkhardt, Jesse, et al.. (2025). Solar energy resource availability under extreme and historical wildfire smoke conditions. Nature Communications. 16(1). 245–245. 1 indexed citations
4.
Hatzianastassiou, Nikos, Nikos Benas, Jan Fokke Meirink, et al.. (2019). Evaluation of CLARA-A2 and ISCCP-H Cloud Cover Climate Data Records over Europe with ECA&D Ground-Based Measurements. Remote Sensing. 11(2). 212–212. 23 indexed citations
5.
Chen, Xiuhong, Xianglei Huang, Xiquan Dong, et al.. (2018). Using AIRS and ARM SGP Clear‐Sky Observations to Evaluate Meteorological Reanalyses: A Hyperspectral Radiance Closure Approach. Journal of Geophysical Research Atmospheres. 123(20). 3 indexed citations
6.
Stackhouse, Paul W., et al.. (2015). A Beta Version of the GIS-Enabled NASA Surface meteorology and Solar Energy (SSE) Web Site With Expanded Data Accessibility and Analysis Functionality for Renewable Energy and Other Applications. AGU Fall Meeting Abstracts. 2015. 3 indexed citations
7.
Chin, Mian, T. Diehl, Huisheng Bian, et al.. (2014). Multi-decadal trends of solar radiation reaching the surface: What is the role of aerosols?. 2014 AGU Fall Meeting. 2014. 1 indexed citations
8.
Raghavan, Ram K., et al.. (2014). Spatially Heterogeneous Land Cover/Land Use and Climatic Risk Factors of Tick-Borne Feline Cytauxzoonosis. Vector-Borne and Zoonotic Diseases. 14(7). 486–495. 18 indexed citations
9.
Stackhouse, Paul W., et al.. (2010). A GLOBAL ASSESSMENT OF SOLAR ENERGY RESOURCES: NASA's Prediction of Worldwide Energy Resources (POWER) Project. AGU Fall Meeting Abstracts. 2010. 4 indexed citations
10.
Soja, A. J., et al.. (2010). Analysis of the ability of large-scale reanalysis data to define Siberian fire danger in preparation for future fire prediction. EGU General Assembly Conference Abstracts. 14485. 1 indexed citations
11.
Stackhouse, Paul W.. (2010). Assessing uncertainties and variability in global and regional radiative budgets from the NASA/GEWEX Surface Radiation Budget (SRB) Release-3.0 dataset. 3 indexed citations
12.
Stackhouse, Paul W., et al.. (2010). The GEWEX Surface Radiation Budget Project: Results from the 24.5 Year Data Set. EGU General Assembly Conference Abstracts. 10062. 2 indexed citations
13.
Westberg, David, A. J. Soja, & Paul W. Stackhouse. (2009). Linking Satellite-Derived Fire Counts to Satellite-Derived Weather Data in Fire Prediction Models to Forecast Extreme Fires in Siberia. EGU General Assembly Conference Abstracts. 2009. 5597. 1 indexed citations
14.
Hatzianastassiou, N., C. Matsoukas, Emmanuel M. Drakakis, et al.. (2007). The direct effect of aerosols on solar radiation based on satellite observations, reanalysis datasets, and spectral aerosol optical properties from Global Aerosol Data Set (GADS). Atmospheric chemistry and physics. 7(10). 2585–2599. 56 indexed citations
15.
Stackhouse, Paul W.. (2006). Fast Longwave and Shortwave Flux (FLASHFlux) Products from CERES and MODIS Measurements. 3 indexed citations
16.
Gupta, S. K., et al.. (2006). The NASA/GEWEX Surface Radiation Budget Project. AGU Spring Meeting Abstracts. 2007. 6 indexed citations
17.
Cox, Stephen J., et al.. (2005). Interannual Variability on Global and Regional Scales From the GEWEX Surface Radiation Budget Project. AGU Fall Meeting Abstracts. 2005.
18.
Soja, A. J., А. И. Сухинин, Donald R. Cahoon, Herman H. Shugart, & Paul W. Stackhouse. (2004). AVHRR-derived fire frequency, distribution and area burned in Siberia. International Journal of Remote Sensing. 25(10). 1939–1960. 71 indexed citations
19.
Chiacchio, Marc, et al.. (2004). Evaluating Surface Measured vs. Satellite-Retrieved Long-term Surface SW fluxes by Surface Climatological Type.. AGU Spring Meeting Abstracts. 2004. 1 indexed citations
20.
Soja, A. J., et al.. (2002). Fire Frequency, Distribution, and Area Burned in Siberia Described Using AVHRR-Derived Products. AGU Spring Meeting Abstracts. 2002. 1 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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