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  1. Adams, Ian Stuart and Justin Bobak (2018), The Feasibility of Detecting Supercooled Liquid With a Forward-Looking Radiometer, IEEE J. Sel. Top. Appl. Rem. Sens., 11(6, SI), 1932–1938, Publisher: Institute of Elect & Electron Engineers Geoscience & Remote Sensing Soc; IEEE; IEEE GRSS, doi:10.1109/JSTARS.2018.2844684.
  2. Adams, Ian S., S. Joseph Munchak, Kwo-Sen Kuo, Craig Pelissier, Thomas Clune, Rachael Kroodsma, Adrian Loftus, and Xioawen Li (2019), Active and passive radiative transfer simulations for GMP-related field campaigns, In: 2019 IEEE International Geoscience and Remote Sensing Symposium (IGARSS 2019), pp. 4553–4556, Inst Elect & Elect Engineers; Inst Elect & Elect Engineers, Geoscience & Remote Sensing Soc, ISSN: 2153-6996.
  3. Barlakas, Vasileios and Patrick Eriksson (2020), Three Dimensional Radiative Effects in Passive Millimeter/Sub-Millimeter All-sky Observations, Rem. Sens., 12(3), doi:10.3390/rs12030531.
  4. Duncan, David Ian, Patrick Eriksson, and Simon Pfreundschuh (2019), An experimental 2D-Var retrieval using AMSR2, Atmos. Meas. Tech., 12(12), 6341–6359, doi:10.5194/amt-12-6341-2019.
  5. Ekelund, Robin, Patrick Eriksson, and Michael Kahnert (2020), Microwave single-scattering properties of non-spheroidal raindrops, Atmos. Meas. Tech., 13(12), 6933–6944, doi:10.5194/amt-13-6933-2020.
  6. Ekelund, Robin, Patrick Eriksson, and Simon Pfreundschuh (2020), Using passive and active observations at microwave and sub-millimetre wavelengths to constrain ice particle models, Atmos. Meas. Tech., 13(2), 501–520, doi:10.5194/amt-13-501-2020.
  7. Fox, S. (2020), An Evaluation of Radiative Transfer Simulations of Cloudy Scenes from a Numerical Weather Prediction Model at Sub-Millimetre Frequencies Using Airborne Observations, Rem. Sens., 12(17), doi:10.3390/rs12172758.
  8. Geer, Alan J., Peter Bauer, Katrin Lonitz, Vasileios Barlakas, Patrick Eriksson, Jana Mendrok, Amy Doherty, James Hocking, and Philippe Chambon (2021), Bulk hydrometeor optical properties for microwave and sub-millimetre radiative transfer in RTTOV-SCATT v13.0, Geosci. Model Dev., 14(12), 7497–7526, doi:10.5194/gmd-14-7497-2021.
  9. Grieco, Francesco, Kristell Perot, Donal Murtagh, Patrick Eriksson, Peter Forkman, Bengt Rydberg, Bernd Funke, Kaley A. Walker, and Hugh C. Pumphrey (2020), Recovery and validation of Odin/SMR long-term measurements of mesospheric carbon monoxide, Atmos. Meas. Tech., 13(9), 5013–5031, doi:10.5194/amt-13-5013-2020.
  10. Grieco, Francesco, Kristell Perot, Donal Murtagh, Patrick Eriksson, Bengt Rydberg, Michael Kiefer, Maya Garcia-Comas, Alyn Lambert, and Kaley A. Walker (2021), Improvement of Odin/SMR water vapour and temperature measurements and validation of the obtained data sets, Atmos. Meas. Tech., 14(8), 5823–5857, doi:10.5194/amt-14-5823-2021.
  11. Kaur, Inderpreet, Patrick Eriksson, Simon Pfreundschuh, and David Ian Duncan (2021), Can machine learning correct microwave humidity radiances for the influence of clouds?, Atmos. Meas. Tech., 14(4), 2957–2979, doi:10.5194/amt-14-2957-2021.
  12. Kaur, Inderpreet, Patrick Eriksson, Vasileios Barlakas, Simon Pfreundschuh, and Stuart Fox (2022), Fast Radiative Transfer Approximating Ice Hydrometeor Orientation and Its Implication on IWP Retrievals, Rem. Sens., 14(7), doi:10.3390/rs14071594.
  13. Larsson, R., Y. Kasai, T. Kuroda, S. Sato, T. Yamada, H. Maezawa, Y. Hasegawa, T. Nishibori, S. Nakasuka, and P. Hartogh (2018), Mars submillimeter sensor on microsatellite: sensor feasibility study, Geosci. Instr., Methods and Data Syst., 7(4), 331–341, doi:10.5194/gi-7-331-2018.
  14. Mattioli, Vinia, Christophe Accadia, Catherine Prigent, Susanne Crewell, Alan Geer, Patrick Eriksson, Stuart Fox, Juan R. Pardo, Eli J. Mlawer, Maria Cadeddu, Michael Bremer, Carlos De Breuck, Alain Smette, Domenico Cimini, Emma Turner, Mario Mech, Frank S. Marzano, Pascal Brunel, Jerome Vidot, Ralf Bennartz, Tobias Wehr, Sabatino Di Michele, and Viju O. John (2019), Atmospheric Gas Absorption Knowledge in the Submillimeter: Modeling, Field Measurements, and Uncertainty Quantification, Bull. Amer. Met. Soc., 100(12), ES291–ES295, doi:10.1175/BAMS-D-19-0074.1.
  15. Pfreundschuh, S., P. Eriksson, D. Duncan, B. Rydberg, N. Hakansson, and A. Thoss (2018), A neural network approach to estimating a posteriori distributions of Bayesian retrieval problems, Atmos. Meas. Tech., 11(8), 4627–4643, doi:10.5194/amt-11-4627-2018.
  16. Yang, Hu and Martin Burgdorf (2020), A Study of Lunar Microwave Radiation Based on Satellite Observations, Rem. Sens., 12(7), doi:10.3390/rs12071129.