Dr. Sullivan is an atmospheric scientist in the Environmental Science Division at Argonne National Laboratory. His research integrates in situ field measurements, remote sensing, numerical modeling, and data analytics (e.g., geospatial statistics/time series analysis/machine learning) to better understand atmospheric processes and their impacts on society. These approaches are being used to study:
-Atmospheric composition and chemistry pertaining to urban air quality and climate forcing via radiation scattering/absorbing and cloud-aerosol interactions
-Land-biosphere-atmosphere coupling via turbulent fluxes and their role in weather and climate extremes

Dr. Sullivan is the Lead Instrument Mentor for the Department of Energy’s Atmospheric Radiation Measurement (ARM) user facility’s Energy Balance Bowen Ratio (EBBR) systems, Eddy Correlation (ECOR) flux measurement systems, and Surface Energy Balance Systems (SEBS), and Associate Instrument Mentor for the Soil Temperature and Moisture Profile (STAMP) systems.

Dr. Sullivan is PI for AmeriFlux sites US-A10: ARM-NSA-Barrow (doi:10.17190/AMF/1498753) and US-A03: ARM-AMF3-Oliktok (doi:10.17190/AMF/1498752)

Education:
2017    Ph.D. Atmospheric Sciences, Cornell University
2016    M.S. Atmospheric Sciences, Cornell University
2014    M.S. Geological Sciences – Atmospheric Science, Indiana University
2012    B.S. Meteorology, Northern Illinois University
2010    A.S. William Rainey Harper College

Publications (full texts available on request):

McNicol, G., Fluet-Chouinard, E., Ouyang, Z., Knox, S. H., Zhang, Z., Aalto, T., Bansal, S., Chang, K.-Y., Chen, M., Delwiche, K., Feron, S., Goeckede, M., Liu, J., Malhotra, A., Melton, J. R., Riley, W., Vargas, R., Yuan, K., Ying, Q., Zhu, Q., Alekseychik, P., Aurela, M., Billesbach, D. P., Campbell, D. I., Chen, J., Chu, H., Desai, A., Euskirchen, E., Goodrich, J., Griffis, T., Helbig, M., Hirano, T., Iwata, H., Jurasinski, G., King, J. S., Koebsch, F., Kolka, R., Krauss, K., Lohila, A., Mammarella, I., Nilson, M., Noormets, A., Oechel, W., Peichl, M., Sachs, T., Sakabe, A., Schulze, C., Sonnentag, O., Sullivan, R. C., Tuittila, E.-S., Ueyama, M., Vesala, T., Ward, E., Wille, C., Wong, G. X., Zona, D., Windham-Myers, L., Poulter, B., and Jackson, R. B. (2023). Upscaling Wetland Methane Emissions From the FLUXNET‐CH4 Eddy Covariance Network (UpCH4 v1. 0): Model Development, Network Assessment, and Budget Comparison. AGU Advances, 4, e2023AV000956. doi: 10.1029/2023AV000956
News coverage 

Feldman, D. R.,  Aiken, A. C., Boos, W. R.,  Carroll, R. W. H, Chandrasekar, V., Collis, S., Creamean, J. M., de Boer, G., Deems, J., DeMott, P. J., Fan, J., Flores, A. N., Gochis, D., Grover, M., Hill, T. C. J., Hodshire, A., Hulm, E., Hume, C. C., Jackson, R., Junyent, F., Kennedy, A., Kumjian, M., Levin, E. J. T., Lundquist, J. D., O’Brien, J., Raleigh, M. S., Reithel, J., Rhoades, A., Rittger, K., Rudisill, W., Sherman, Z., Siirila-Woodburn, E., Skiles, S. M., Smith, J. N., Sullivan, R. C., Theisen, A., Tuftedal, M., Varble, A. C., Wiedlea, A., Wielandt, S., Williams, K., and Xu, Z. (2023). The Surface Atmosphere Integrated Field Laboratory (SAIL) Campaign. Bulletin of the American Meteorological Society. doi:10.1175/BAMS-D-22-0049.1

Muradyan, P., Kotamarthi, R., Coulter. R., PotoSnak, M., Keeler, E., O’Brien, J., Tuftedal, M., Petralaia, K., Sullivan, R., Chang, Y-S., Hamada, Y., and Gartman, D. (2023). Fire Emissions Study at Eglin Air Force Base, Florida: Measurement Collection and Early Insights for Prescribed Burn Emissions Toward Understanding Air Quality Impacts of Prescribed Fires Compared to Wildland Fires. Argonne National Laboratory, prepared for U.S. Air Force Wildland Fire Branch (AFCEC/CZOF). ANL/EVS-23/19.

Oehri, J., Schaepman-Strub, G., Kim, J.-S., Grysko, R., Kropp, H., Grünberg, I., Zemlianskii, V., Sonnentag, O., Euskirchen, E. S., Chacko, M. R., Muscari, G., Blanken, P. D., Dean, J. F., di Sarra, A., Harding, R. J., Sobota, I., Kutzbach, L., Plekhanov, E., Riihelä, A., Boike, J., Miller, N. B., Beringer, J., López-Blanco, E., Stoy, P. C., Sullivan, R. C., Kejna, M., Parmentier, F.-J. W., Gamon, J. A., Mastepanov, M., Wille, C., Jackowicz-Korczynski, M., Karger, D. N., Quinton, W. L., Putkonen, J., van As, D., Christensen, T. R., Hakuba, M .Z., Stone, R. S., Metzger, S., Vandecrux, B., Frost, G. V., Wild, M., Hansen, B., Meloni, D., Domine, F., te Beest, M., Sachs, T., Kalhori, A., Rocha, A. V., Williamson, S. N., Morris, S., Atchley, A. L., Essery, R., Runkle, B. R. K., Holl, D., Riihimaki, L. D., Iwata, H., Schuur, E. A. G., Cox, C., Grachev, A. A., McFadden, J. P., Fausto, R. S., Goeckede, M., Ueyama, M., Pirk, N., de Boer, J., Bret-Harte, M. S., Leppäranta, M., Steffen, K., Friborg, T., Ohmura, A., Edgar, C. W., Olofsson, J., Chambers, S. D. (2022). Vegetation type is an important predictor of the Arctic summer land surface energy budget. Nature Communications, 13, 6379. doi: 10.1038/s41467-022-34049-3
News coverage

Zolkos, S., Tank, S. E., Kokelj, S. V., Striegl, R. G., Shakil, S., Voigt, C., Sonnentag, O., Quinton, W. L., Schuur, E. A. G.,  Zona, D., Lafleur, P. M., Sullivan, R. C., Ueyama, M., Billesbach, D., Cook, D., Humphreys, E. R., Marsh, P. (2022). Permafrost landscape history shapes fluvial chemistry, ecosystem carbon balance, and potential trajectories of future change. Global Biogeochemical Cycles, 36, e2022GB007403. doi: 10.1029/2022GB007403

Sullivan, R. C., Chang, Y.-S., Kotamarthi, R., Muradyan, P., Coulter, R., Hamada, Y., Keeler, E., Potosnak, M., and Gartman, D. M. (2021). Baseline of emission factors used for air quality studies from prescribed burns. Argonne National Laboratory, prepared for U.S. Air Force Wildland Fire Branch (AFCEC/CZOF). ANL/EVS-21/13.

Dorigo, W., Himmelbauer, I., Aberer, D., Schremmer, L., Petrakovic, I., Zappa, L., Preimesberger, W., Xaver, A., Annor, F., Ardö, J., Baldocchi, D., Blöschl, F., Bogena, H., Brocca, L. Calvet, J-C., Camarero, J. J., Capello, G., Choi, M., Cosh, M. C., Demarty, J., van de Giesen, N., Hajdu, I., Jensen, K. H., Kanniah, K. D., de Kat, I., Kirchengast, G., Rai, P. K., Kyrouac, J., Larson, K., Liu, S., Loew, A., Moghaddam, M., Fernández, J. M., Bader, C. M., Morbidelli, R., Musial, J., Osenga, E., Palecki, M. A., Powers, J., Ikonen, J., Robock, A., Rüdiger, C., Rummel, U., Strobel, M., Su, Z., Sullivan, R., Tagesson, T., Walker, J., Wigneron, J-P., Woods, M., Yang, K., Zhang, X., Zreda, M., Dietrich, S., Gruber, A., van Oevelen, P., Wagner, W., Scipal, K., Drusch, M., and Sabia, R. (2021). The International Soil Moisture Network: serving Earth system science for over a decade. Hydrology and Earth System Sciences, 25, 5749–5804. doi: 10.5194/hess-25-5749-2021

Feldman, D., Aiken, A., Boos, W., Carroll, R., Chandrasekar, V., Collins, W., Collis, S., Deems, J., DeMott, P., Fan, J., Flores, A., Gochis, D., Harrington, J., Kumjian, M., Leung, L. R., O’Brien, T., Raleigh, M., Rhoades, A., Skiles, S. M, Smith, J., Sullivan, R., Ullrich, P., Varble, A., and Williams, K. (2021). Surface Atmosphere Integrated Field Laboratory (SAIL) Science Plan. U.S. Department of Energy. DOE/SC-ARM-21-004. doi:10.2172/1781024

Feng, Y., Maulik, R., Wang, J., Balaprakash, P., Huang, W., Rao, V., Xue, P., Pringle, W., Bessac, J., and Sullivan, R. (2021). Characterization of extremes and compound impacts: Applications of machine learning and interpretable neural networks. Artificial Intelligence for Earth System Predictability (AI4ESP). doi:10.2172/1769686

Balaprakash, P., Collis, S., Kim, Y., Beckmann, P., Cadeddu, M., Gonzalez-Meler, M., Sullivan, R., Madireddy, S., and Kotamarthi, R. (2021). AI-enabled MODEX and edge-computing over 5G for improving the predictability of water cycle extremes. Artificial Intelligence for Earth System Predictability (AI4ESP). doi:10.2172/1769672

Irvin, J., Zhou, S., McNicol, G., Lu, F., Liu, V., Fluet-Chouinard, E., Ouyang, Z., Knox, S. H., Lucas-Moffat, A., Trotta, C., Papale, D., Vitale, D., Mammarella, I., Avati, A., Kondrich, A., Ng, A., Rey-Sanchez, A. C., Valach, A. C., Richardson, A. D., Kalhori, A., Lohila, A., Malhotra, A., Noormets, A., Desai, A. R., Mitra, B., Runkle, B. R. K., Helfter, C., Sturtevant, C., Baldocchi, D., Campbell, D. I., Lai, D. Y. F., Zona, D., Euskirchen, E., Ward, E. J., Stuart-Haëntjens, E., Bohrer, G., Jurasinski, G., Vourlitis, G., J., Wong, G. X., Chu, H., Iwata, H., Dalmagro, H. J., Chen, J., Delwiche, K. B., Hemes, K. S., Schäfer, K. V. R., Merbold, L., Aurela, M., Nilsson, M. B., Goeckede, M., Helbig, M., Heimann, M., Peichl, M., Ueyama, M., Sonnentag, O., Alekseychik, P., Vargas, R., Bansal, S., Feron, S., Hirano, T., Jacotot, A., Sakabe, A., Varlagin, A., Wille, C., Szutu, D. J., Billesbach, D. P., Schuur, E. A., Nemitz, E., Tuittila, E-S., Parmentier, F., J., Koebsch, F., Celis, G., Dolman, H., Verfaillie, J. G., Goodrich, J. P., Fuchs, K., Kasak, K., Ono, K., Hörtnagl, L., Alberto, M. C. R., Gondwe, M. J., Gottschalk, P., Oikawa, P. Y., Sullivan, R. C., Maier, R., Shortt, R., Gogo, S., Friborg, T., Morin, T. H., Sachs, T., Oechel, W. C., Windham-Myers, L., Poulter, B., and Jackson R. B. (2021). Gap-filling eddy covariance methane fluxes: Comparison of machine learning model predictions and uncertainties at FLUXNET-CH4 wetlands. Agricultural and Forest Meteorology, 308, 108528. doi:10.1016/j.agrformet.2021.108528

Delwiche, K. B., Knox, S. H., Malhotra, A., Fluet-Chouinard, E., McNicol, G., Feron, S., Ouyang, Z., Papale, D., Trotta, C., Canfora, E., Cheah, Y., Christianson, D., Alberto, M. C. R., Alekseychik, P., Aurela, M., Baldocchi, D., Bansal, S., Billesbach, D. P., Bohrer, G., Bracho, R., Buchmann, N., Campbell, D. I., Celis, G., Chen, J., Chen, W., Chu, H., Dalmagro, H. J., Dengel, S., Desai, A. R., Detto, M., Dolman, H., Eichelmann, E., Euskirchen, E., Famulari, D., Friborg, T., Fuchs, K., Goeckede, M., Gogo, S., Gondwe, M. J., Goodrich, J. P., Gottschalk, P., Graham, S. L., Heimann, M., Helbig, M., Helfter, C., Hemes, K. S., Hirano, T., Hollinger, D., Hörtnagl, L., Iwata, H., Jacotot, A., Jansen, J., Jurasinski, G., Kang, M., Kasak, K., King, J., Klatt, J., Koebsch, F., Krauss, K. W., Lai, D. Y. F., Mammarella, I., Manca, G., Marchesini, L. B., Matthes, J. H., Maximon, T., Merbold, L., Mitra, B., Morin, T. H., Nemitz, E., Nilsson, M. B., Niu, S., Oechel, W. C., Oikawa, P. Y., Ono, K., Peichl, M., Peltola, O., Reba, M. L., Richardson, A. D., Riley, W., Runkle, B. R. K., Ryu, Y., Sachs, T., Sakabe, A., Sanchez, C. R., Schuur, E. A., Schäfer, K. V. R., Sonnentag, O., Sparks, J. P., Stuart-Haëntjens, E., Sturtevant, C., Sullivan, R. C., Szutu, D. J., Thom, J. E., Torn, M. S., Tuittila, E., Turner, J., Ueyama, M., Valach, A. C., Vargas, R., Varlagin, A., Vazquez-Lule, A., Verfaillie, J. G., Vesala, T., Vourlitis, G., L., Ward, E. J., Wille, C., Wohlfahrt, G., Wong, G. X., Zhang, Z., Zona, D., Windham-Myers, L., Poulter, B., and Jackson, R. B. (2021). FLUXNET-CH4: A global, multi-ecosystem database and analysis of methane seasonality from freshwater wetlands. Earth System Science Data, 13, 3607–3689. doi:110.5194/essd-13-3607-2021

Helbig, M., Gerken, T., Beamesderfer, E., Baldocchi, D. D., Banerjee, T., Biraud, S. C., Brown, W. O. J., Brunsell, N. A., Burakowski, W. A., Burns, S. P., Butterworth. B. J., Chan, W. S., Davis, K. J., Desai, A. R., Fuentes, J. D., Hollinger, D. Y., Kljun, N., Mauder, M., Novick, K. A., Perkins, J. M., Rahn, D. A., Rey-Sanchez, C., Santanello, J. A., Scott, R. L., Seyednasrollahm, B., Stoy, P. C., Sullivan, R. C., Vilà-Guerau de Arellano, J., Wharton, S., Yi, C., and Richardson, A. D. (2021). Integrating continuous atmospheric boundary layer and tower-based flux measurements to advance understanding of land-atmosphere interactions. Agricultural and Forest Meteorology, 307, 108509. doi:10.1016/j.agrformet.2021.108509
June 2021 Editors’ Choice - Agricultural and Forest Meteorology

Chu, H., Luo, X., Ouyang, Z., Ouyang, Z., Chan, S., Dengel, S., Biraud, S. C., Torn, M. S., Metzger. S., Kumar, J., Arain, M. A., Arkebauer, T. J., Baldocchi, D., Bernacchi, C., Billesbach, D., Black, T. A., Blanken, P. D., Bohrer, G., Bracho, R., Brown, S., Brunsell, N.A., Chen, J., Chen, X., Clark, K., Desai, A. R., Duman, T., Durden, D., Fares, S., Forbrich, I., Gamon, J., Gough, C. M., Griffis, T., Helbig, M., Hollinger, D., Humphreys, E., Ikawa, H., Iwata, H., Ju, Y., Knowles. J. F., Knox, S., Kobayashi, H., Kolb, T., Law, B., Lee, X., Litvak, M., Liu, H., Munger, J. W., Noormets, A., Novick, K., Oberbauer, S., Oechel, W., Oikawa, P., Papuga, S. A., Pendall, E., Prajapati, P., Prueger, J., Quinton, W. L., Richardson, A. D., Russell, E. S., Scott, R. L., Starr, G., Staebler, R., Stoy, P. C., Stuart-Haëntjens, E., Sonnentag, O., Sullivan, R. C., Suyker, A., Ueyama, M., Vargas, R., Wood, J. D., and Zona, D. (2021). Representativeness of Eddy-Covariance flux footprints for areas surrounding AmeriFlux sites. Agricultural and Forest Meteorology. 301-302, 108350. doi:10.1016/j.agrformet.2021.108350

Bao, T., Xu, X., Jia, G., Billesbach, D. P., and Sullivan, R. C. (2020). Much stronger tundra methane emissions during autumn-freeze than spring-thaw. Global Change Biology. 27, 376– 387. doi:10.1111/gcb.15421
Phys​.org: Arctic tundra emits more methane during autumn freeze than spring thaw

Helbig, M., Gerken, T., Beamesderfer, E., Baldocchi, D. D., Banerjee, T., Biraud, S. C., Brunsell, N. A., Burns, S. P., Chan, W. S., Desai, A. R., Fuentes, J. D., Hollinger, D. Y., Kljun, N., Mauder, M., Rey-Sanchez, C., Seyednasrollahm, B., Stoy, P. C., Sullivan, R. C., Vilà-Guerau de Arellano, J., Wharton, S., Yi, C., and Richardson, A. D. (2020). Understanding biosphere-atmosphere interactions through tower-based flux and continuous atmospheric boundary layer measurements. DOE AmeriFlux.

Beckman, P., Catlett, C., Ahmed, M., Alawad, M., Bai, L., Balaprakash, P., Barker, K., Berry, R., Bhuyan, A., Brebner, G., Burkes, K., Butko, A., Cappello, F., Chard, R., Collis, S., Cree, J., Dasgupta, D., Evdokimov, A., Fields, J., Fuhr, P., Harper, C., Jin, Y., Kettimuthu, R., Kiran, M., Kozma, R., Kumar, P., Kumar, Y., Luo, L., Mashayekhy, L., Monga, I., Nickless, B., Pappas, T., Peterson, E., Pfeffer, T., Rakheja, S., Rodriguez Tribaldos, V., Rooke, S., Roy, S., Saadawi, T., Sandy, A., Sankaran, R., Schwarz, N., Somnath, S., Stan, M., Stuart, C., Sullivan, R., Sumant, A., Tchilinguirian, G., Tran, N., Veeramany, A., Wang, A., Wang, B., Wiedlea, A., Wielandt, S., Windus, T., Wu, Y., Yang, X., Yao, Z., Yu, R., Zeng, Y., and Zhang, Y. (2020). 5G-Enabled energy innovation: Advanced wireless networks for science. doi:10.2172/1606538

Sullivan, R. C., Kotamarthi, V. R., and Feng, Y. (2019). Recovering evapotranspiration trends from biased CMIP5 simulations and sensitivity to changing climate over North America. Journal of Hydrometeorology, 20(8), 1619–1633. doi:10.1175/JHM-D-18-0259.1
ARM Research Highlight

Crippa, P., Sullivan, R. C., Thota, A., and Pryor, S. C. (2019). Sensitivity of simulated aerosol properties over eastern North America to WRF-Chem parameterizations. Journal of Geophysical Research: Atmospheres, 124(6), 3365-3383. doi:10.1029/2018JD029900

Tang, S., Xie, S., Zhang, M., Tang, Q., Zhang, Y., Klein, S. A., Cook, D. R., and Sullivan, R. C. (2019). Differences in eddy-correlation and energy-balance surface turbulent heat flux measurements and their impacts on the large-scale forcing fields at the ARM SGP site. Journal of Geophysical Research: Atmospheres, 124(6), 3301-3318. doi:10.1029/2018JD029689
ARM Research Highlight

Sullivan, R. C., Cook, D. R., Ghate, V. P., Kotamarthi, V. R., and Feng, Y. (2019). Improved spatiotemporal representativeness and bias reduction of satellite-based evapotranspiration retrievals via use of in situ meteorology and constrained canopy surface resistance. Journal of Geophysical Research: Biogeosciences, 124(2), 342-352. doi:10.1029/2018JG004744
ARM Research Highlight

Sullivan, R. C., Crippa, P., Matsui, H., Leung, L. Y. R., Zhao, C., Thota, A., and Pryor, S. C. (2018). New particle formation leads to cloud dimming. Npj Climate and Atmospheric Science, 1(1). doi:10.1038/s41612-018-0019-7

Sullivan, R. C., Levy, R. C., da Silva, A. M., and Pryor, S. C. (2017). Developing and diagnosing climate change indicators of regional aerosol optical properties. Scientific Reports, 7:18093. doi:10.1038/s41598-017-18402-x

Pryor, S. C., Sullivan, R. C., and Schoof J. T. (2017). Modeling the contributions of global air temperature, synoptic-scale phenomena and soil moisture to near-surface static energy variability using artificial neural networks. Atmospheric Chemistry and Physics, 17(23), 14457-14471. doi:10.5194/acp-17-14457-2017

Crippa, P., Sullivan, R. C., Thota, A., and Pryor, S. C. (2017). The impact of resolution on meteorological, chemical and aerosol properties in regional simulations with WRF-Chem. Atmospheric Chemistry and Physics, 17, 1511–1528. doi:10.5194/acp-17-1511-2017

Pryor, S. C., Sullivan, R. C., Bernstein, D. N., Thota, A., and Crippa, P. (2017). Detection and attribution of trends in aerosol populations and extreme aerosol events over North America. In: Report Series in Aerosol Science no. 201: Proceedings of the 3^rd Pan-Eurasian Experiment (PEEX) Conference and the 7^th PEEX Meeting. pp. 403-409. ISSN 0784-3496.

Sullivan, R. C., Crippa, P., Hallar A. G., Clarisse, L., Whitburn, S., Van Damme, M., Leaitch, W. R., Walker, J., Khlystov, A., and Pryor S. C. (2016). Using satellite-based measurements to explore spatiotemporal scales and variability of drivers of new particle formation. Journal of Geophysical Research: Atmospheres, 121, 12217–12235. doi:10.1002/2016JD025568

Pryor, S. C., Joerger, V. M., and Sullivan, R. C. (2016). Empirical estimates of size-resolved precipitation scavenging coefficients for ultrafine particles. Atmospheric Environment, 143, 133-138. doi:10.1016/j.atmosenv.2016.08.036

Sullivan, R. C. and Pryor, S. C. (2016). Dynamic and chemical controls on new particle formation occurrence and characteristics from in situ and satellite-based measurements. Atmospheric Environment, 127, 316-325. doi:10.1016/j.atmosenv.2015.12.050

Pryor, S. C., Sullivan, R. C., and Wright, T. (2016). Quantifying the roles of changing albedo, emissivity, and energy partitioning in the impact of irrigation on atmospheric heat content. Journal of Applied Meteorology and Climatology, 55, 1699–1706. doi:10.1175/JAMC-D-15-0291.1

Crippa, P., Sullivan, R. C., Thota, A., and Pryor, S. C. (2016). Evaluating the skill of high-resolution WRF-Chem simulations in describing drivers of aerosol direct climate forcing at the regional scale. Atmospheric Chemistry and Physics, 16, 397–416. doi:10.5194/acp-16-397-2016

Sullivan, R. C., Levy, R. C., and Pryor, S. C. (2015). Spatiotemporal coherence of mean and extreme aerosol particle events over eastern North America as observed from satellite. Atmospheric Environment, 112, 126-135. doi:10.1016/j.atmosenv.2015.04.026

Pryor S. C., Crippa P., and Sullivan, R. C. (2015). Atmospheric chemistry. In: Elsevier’s Reference Module in Earth Systems and Environmental Sciences (Available at http://​www​.sci​encedi​rect​.com/​s​c​i​e​n​c​e​/​a​r​t​i​c​l​e​/​p​i​i​/​B​9​7​8​0​1​2​4​0​9​5​4​8​9​0​91776). Ed. by J.T. Schoof. doi:10.1016/B978-0-12-409548-9.09177-6.

Sullivan, R. C. and Pryor, S. C. (2014). Quantifying spatiotemporal variability of fine particles in an urban environment using combined fixed and mobile measurements. Atmospheric Environment, 89, 664-671. doi:10.1016/j.atmosenv.2014.03.007