Publications
- 136 results
- Tag: Isoprene
- Tag: Model
- Tag: XCO2
- Clear all
2022, Yang, Z., B. Demoz, R. Delgado, A. Tangborn, P. Lee, and J.T. Sullivan, The Dynamical Role of the Chesapeake Bay on the Local Ozone Pollution Using Mesoscale Modeling—A Case Study, Atmosphere, 13(5), 641
Tags: Lidar, Model, Ozone
2022, Summa, D., F. Madonna, N. Franco, B. De Rosa, and P. Di Girolamo , Inter-comparison of atmospheric boundary layer (ABL) height estimates from different profiling sensors and models in the framework of HyMeX-SOP1, Atmospheric Measurement Techniques, 15, 4153–4170, https://doi.org/10.5194/amt-15-4153-2022
Tags: Lidar, Model
2022, Mariaccia, A., Keckhut P., Hauchecorne A., Claud C., Le Pichon A., Meftah M., Khaykin S., Assessment of ERA-5 Temperature Variability in the MiddleAtmosphere Using Rayleigh LiDAR Measurements between 2005 and 2020, Atmosphere, 13 (2), 242, http://doi.org/10.3390/atmos13020242
Tags: Lidar, Model, Temperature
2022, Wells, K.C., Millet, D. B., Payne, V. H., Vigouroux, C., Aquino, C. A. B., De Mazière, M., de Gouw, J. A., Graus, M., Kurosu, T., Warneke, C., and Wisthaler, A., Next-generation Isoprene Measurements from Space: Detecting Daily Variability at High Resolution, Journal of Geophysical Research: Atmospheres, 127, e2021JD036181, https://doi.org/10.1029/2021JD036181
Tags: C5H8, FTIR, Isoprene, Satellite
2021, Marlton, G., et al., Using a network of temperature lidars to identify temperature biases in the upper stratosphere in ECMWF reanalyses, Atmospheric Chemistry and Physics, 21(8), 6079–6092, https://doi.org/10.5194/acp-21-6079-2021
Tags: Lidar, Model, Temperature
2021, Meng, L., J. Liu, D.W. Tarasick and Y. Li , Biases of Global Tropopause Altitude Products in Reanalyses and Implications for Estimates of Tropospheric Column Ozone, Atmosphere, 12, 417, https://doi.org/10.3390/atmos12040417
Tags: Sonde, Ozone, Model
2021, Sun, Y., Yin, H., Liu, C., Zhang, L., Cheng, Y., Palm, M., Notholt, J., Lu, X., Vigouroux, C., Zheng, B., Wang, W., Jones, N., Shan, C., Qin, M., Tian, Y., Hu, Q., Meng, F., and Liu, J., Mapping the drivers of formaldehyde (HCHO) variability from 2015 to 2019 over eastern China: insights from Fourier transform infrared observation and GEOS-Chem model simulation, Atmospheric Chemistry and Physics, 21, 6365–6387, https://doi.org/10.5194/acp-21-6365-2021
Tags: Model, FTIR, HCHO
2021, Schanz, A., Hocke, K.; Kämpfer, N.; Chabrillat, S.; Inness, A.; Palm, M.; Notholt, J.; Boyd, I.; Parrish, A.; Kasai, Y., The Diurnal Variation in Stratospheric Ozone from MACC Reanalysis, ERA-Interim, WACCM, and Earth Observation Data: Characteristics and Intercomparison, Atmosphere, 12, 625, https://doi.org/10.3390/atmos12050625
Tags: Microwave, Diurnal, Ozone, Model
2021, Dogniaux, M., C. Crevoisier, R. Armante, V. Capelle, T. Delahaye, V. Cassé, M. De Mazière, N. M. Deutscher, D.G. Feist, O.E. Garcia, D.W.T. Griffith, F. Hase, L.T. Iraci, R. Kivi, I. Morino, J. Notholt, D.F. Pollard, C.M. Roehl, K. Shiomi, K. Strong, Y. Té, V.A. Velazco, and T. Warneke, The Adaptable 4A Inversion (5AI): description and first XCO2 retrievals from Orbiting Carbon Observatory-2 (OCO-2) observations, Atmospheric Measurement Techniques, 14, 4689–4706, https://doi.org/10.5194/amt-14-4689-2021
Tags: FTIR, Satellite, XCO2
2021, Prignon, M., Chabrillat, S., Friedrich, M., Smale, D., Strahan, S. E., Bernath, P. F., Chipperfield, M. P., Dhomse, S. S., Feng, W., Minganti, D., Servais, C. and Mahieu, E., Stratospheric fluorine as a tracer of circulation changes: comparison between infrared remote‐sensing observations and simulations with five modern reanalyses, Journal of Geophysical Research: Atmospheres, 126(19), https://doi.org/10.1029/2021JD034995
Tags: F, FTIR, Model