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  1. Allen, Michael A., James A. Voogt, and Andreas Christen (2018), Time-Continuous Hemispherical Urban Surface Temperatures, Rem. Sens., 10(1), doi:10.3390/rs10010003.
  2. Arendas, Peter, Tibor Furtenbacher, and Attila G. Csaszar (2021), Selecting lines for spectroscopic (re)measurements to improve the accuracy of absolute energies of rovibronic quantum states, J. Cheminformatics, 13(1), doi:10.1186/s13321-021-00534-y.
  3. Cao, Hongtao, Xingfa Gu, Yuan Sun, Hailiang Gao, Zui Tao, and Shuaiyi Shi (2021), Comparing, validating and improving the performance of reflectance obtention method for UAV-Remote sensing, Int. J. of Applied Earth Observation and Geoinformation, 102, doi:10.1016/j.jag.2021.102391.
  4. Cimini, Domenico, Philip W. Rosenkranz, Mikhail Y. Tretyakov, Maksim A. Koshelev, and Filomena Romano (2018), Uncertainty of atmospheric microwave absorption model: impact on ground-based radiometer simulations and retrievals, Atmos. Chem. Phys., 18(20), 15231–15259, doi:10.5194/acp-18-15231-2018.
  5. Elsey, Jonathan, Marc D. Coleman, Tom D. Gardiner, Kaah P. Menang, and Keith P. Shine (2020), Atmospheric observations of the water vapour continuum in the near-infrared windows between 2500 and 6600 cm(-1), Atmos. Meas. Tech., 13(5), 2335–2361, doi:10.5194/amt-13-2335-2020.
  6. Fahey, Thomas, Maidul Islam, Alessandro Gardi, and Roberto Sabatini (2021), Laser Beam Atmospheric Propagation Modelling for Aerospace LIDAR Applications, Atmos., 12(7), doi:10.3390/atmos12070918.
  7. He, Qiurui, Zhenzhan Wang, and Jiaoyang Li (2022), Fusion Retrieval of Sea Surface Barometric Pressure from the Microwave Humidity and Temperature Sounder and Microwave Temperature Sounder-II Onboard the Fengyun-3 Satellite, Rem. Sens., 14(2), doi:10.3390/rs14020276.
  8. He, Qiu-rui, Rui-ling Zhang, Jiao-yang Li, and Zhen-zhan Wang (2022), Research on the Application of the Radiative Transfer Model Based on Deep Neural Network in One-dimensional Variational Algorithm, J. Trop. Meteorol., 28(3), 326–342, doi:10.46267/j.1006-8775.2022.025.
  9. He, Qiurui, Zhenzhan Wang, Jiaoyang Li, and Wenyu Wang (2022), Sensitivity Testing of Microwave Temperature Sounder-II Onboard the Fengyun-3 Satellite to Sea Surface Barometric Pressure Based on Deep Neural Network, Rem. Sens., 14(12), doi:10.3390/rs14122839.
  10. Iino, Takahiro (2021), Development of Open-Source-Based Software Planetary Atmospheric Spectrum Calculator (PASCAL) Specified for Millimeter/Submillimeter Observation of Titan with ALMA, In: Computational Science and its Applications, ICCSA 2021, PT V, pp. 234–244, Edited by Gervasi, O, B Murgante, S Misra, C Garau, I Blecic, D Taniar, BO Apduhan, AMAC Rocha, E Tarantino, and CM Torre, ISSN: 0302-9743, doi:10.1007/978-3-030-86976-2_16.
  11. Jones, Alexandra L. and Larry Di Girolamo (2018), Design and Verification of a New Monochromatic Thermal Emission Component for the I3RC Community Monte Carlo Model, J. Atmos. Sci., 75(3), 885–906, doi:10.1175/JAS-D-17-0251.1.
  12. Korkin, Sergey, Eun-Su Yang, Robert Spurr, Claudia Emde, Nickolay Krotkov, Alexander Vasilkov, David Haffner, Jungbin Mok, and Alexei Lyapustin (2020), Revised and extended benchmark results for Rayleigh scattering of sunlight in spherical atmospheres, J. Quant. Spectrosc. Radiat. Transfer, 254, doi:10.1016/j.jqsrt.2020.107181.
  13. Korkin, S., A. M. Sayer, A. Ibrahim, and A. Lyapustin (2022), A practical guide to writing a radiative transfer code, Comp. Phys. Comm., 271, doi:10.1016/j.cpc.2021.108198.
  14. Li, Haiying, Zhensen Wu, Zhenwei Zhao, Leke Lin, Changsheng Lu, and Tan Qu (2018), Modified model of equivalent height for predicting atmospheric attenuation at frequencies below 350GHz, IET Microw., Ant. & Propag., 12(8), 1420–1427, doi:10.1049/iet-map.2017.1073.
  15. Li, Mengying, Zhouyi Liao, and Carlos F. M. Coimbra (2018), Spectral model for clear sky atmospheric longwave radiation, J. Quant. Spectrosc. Radiat. Transfer, 209, 196–211, doi:10.1016/j.jqsrt.2018.01.029.
  16. Marsh, Christopher B., Kevin R. Green, B. Wang, and Raymond J. Spiteri (2021), Performance improvements to modern hydrological models via lookup table optimizations, Env. Mod. & Software, 139, doi:10.1016/j.envsoft.2021.105018.
  17. 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.
  18. McCusker, K., C. D. Westbrook, and A. Moiola (2019), Analysis of the internal electric fields of pristine ice crystals and aggregate snowflakes, and their effect on scattering, J. Quant. Spectrosc. Radiat. Transfer, 230, 155–171, doi:10.1016/j.jqsrt.2019.04.019.
  19. Mech, Mario, Maximilian Maahn, Stefan Kneifel, Davide Ori, Emiliano Orlandi, Pavlos Kollias, Vera Schemann, and Susanne Crewell (2020), PAMTRA 1.0: the Passive and Active Microwave radiative TRAnsfer tool for simulating radiometer and radar measurements of the cloudy atmosphere, Geosci. Model Dev., 13(9), 4229–4251, doi:10.5194/gmd-13-4229-2020.
  20. Picard, Ghislain, Melody Sandells, and Henning Loewe (2018), SMRT: an active-passive microwave radiative transfer model for snow with multiple microstructure and scattering formulations (v1.0), Geosci. Model Dev., 11(7), 2763–2788, doi:10.5194/gmd-11-2763-2018.
  21. Ren, T., P. Yang, K. Garrett, Y. Ma, J. Ding, and J. Coy (2023), A Microphysics-Scheme-Consistent Snow Optical Parameterization for the Community Radiative Transfer Model, Mon. Weather Rev., 151(2), 383–402, doi:arts_2018_2023.
  22. Schreier, Franz, Sebastian Gimeno Garcia, Philipp Hochstaffl, and Steffen Staedt (2019), Py4CAtSPYthon for Computational ATmospheric Spectroscopy, Atmos., 10(5), doi:10.3390/atmos10050262.
  23. Stegmann, Patrick G., Guanglin Tang, Ping Yang, and Benjamin T. Johnson (2018), A stochastic model for density-dependent microwave Snow- and Graupel scattering coefficients of the NOAA JCSDA community radiative transfer model, J. Quant. Spectrosc. Radiat. Transfer, 211, 9–24, doi:10.1016/j.jqsrt.2018.02.026.
  24. Tellier, Y., C. Crevoisier, R. Armante, J.-L. Dufresne, and N. Meilhac (2022), Computation of longwave radiative flux and vertical heating rate with 4A-Flux v1.0 as an integral part of the radiative transfer code 4A/OP v1.5, Geosci. Model Dev., 15(13), 5211–5231, doi:10.5194/gmd-15-5211-2022.
  25. Wang, Yingjie and Jean-Philippe Gastellu-Etchegorry (2020), DART: Improvement of thermal infrared radiative transfer modelling for simulating top of atmosphere radiance, Rem. Sen. Env., 251, doi:10.1016/j.rse.2020.112082.
  26. Yang, Jun, Shouguo Ding, Peiming Dong, Lei Bi, and Bingqi Yi (2020), Advanced radiative transfer modeling system developed for satellite data assimilation and remote sensing applications, J. Quant. Spectrosc. Radiat. Transfer, 251, doi:10.1016/j.jqsrt.2020.107043.
  27. Zhang, Yichao, Lakitha O. H. Wijeratne, Shawhin Talebi, and David J. Lary (2021), Machine Learning for Light Sensor Calibration, Sens., 21(18), doi:10.3390/s21186259.