Articles | Volume 11, issue 3
https://doi.org/10.5194/essd-11-1239-2019
https://doi.org/10.5194/essd-11-1239-2019
Data description paper
 | 
21 Aug 2019
Data description paper |  | 21 Aug 2019

A machine-learning-based global sea-surface iodide distribution

Tomás Sherwen, Rosie J. Chance, Liselotte Tinel, Daniel Ellis, Mat J. Evans, and Lucy J. Carpenter

Related authors

Nitrogen oxides in the free troposphere: implications for tropospheric oxidants and the interpretation of satellite NO2 measurements
Viral Shah, Daniel J. Jacob, Ruijun Dang, Lok N. Lamsal, Sarah A. Strode, Stephen D. Steenrod, K. Folkert Boersma, Sebastian D. Eastham, Thibaud M. Fritz, Chelsea Thompson, Jeff Peischl, Ilann Bourgeois, Ilana B. Pollack, Benjamin A. Nault, Ronald C. Cohen, Pedro Campuzano-Jost, Jose L. Jimenez, Simone T. Andersen, Lucy J. Carpenter, Tomás Sherwen, and Mat J. Evans
Atmos. Chem. Phys., 23, 1227–1257, https://doi.org/10.5194/acp-23-1227-2023,https://doi.org/10.5194/acp-23-1227-2023, 2023
Short summary
Fundamental oxidation processes in the remote marine atmosphere investigated using the NO–NO2–O3 photostationary state
Simone T. Andersen, Beth S. Nelson, Katie A. Read, Shalini Punjabi, Luis Neves, Matthew J. Rowlinson, James Hopkins, Tomás Sherwen, Lisa K. Whalley, James D. Lee, and Lucy J. Carpenter
Atmos. Chem. Phys., 22, 15747–15765, https://doi.org/10.5194/acp-22-15747-2022,https://doi.org/10.5194/acp-22-15747-2022, 2022
Short summary
Comparison of model and ground observations finds snowpack and blowing snow aerosols both contribute to Arctic tropospheric reactive bromine
William F. Swanson, Chris D. Holmes, William R. Simpson, Kaitlyn Confer, Louis Marelle, Jennie L. Thomas, Lyatt Jaeglé, Becky Alexander, Shuting Zhai, Qianjie Chen, Xuan Wang, and Tomás Sherwen
Atmos. Chem. Phys., 22, 14467–14488, https://doi.org/10.5194/acp-22-14467-2022,https://doi.org/10.5194/acp-22-14467-2022, 2022
Short summary
Iodine chemistry in the chemistry–climate model SOCOL-AERv2-I
Arseniy Karagodin-Doyennel, Eugene Rozanov, Timofei Sukhodolov, Tatiana Egorova, Alfonso Saiz-Lopez, Carlos A. Cuevas, Rafael P. Fernandez, Tomás Sherwen, Rainer Volkamer, Theodore K. Koenig, Tanguy Giroud, and Thomas Peter
Geosci. Model Dev., 14, 6623–6645, https://doi.org/10.5194/gmd-14-6623-2021,https://doi.org/10.5194/gmd-14-6623-2021, 2021
Short summary
Global tropospheric halogen (Cl, Br, I) chemistry and its impact on oxidants
Xuan Wang, Daniel J. Jacob, William Downs, Shuting Zhai, Lei Zhu, Viral Shah, Christopher D. Holmes, Tomás Sherwen, Becky Alexander, Mathew J. Evans, Sebastian D. Eastham, J. Andrew Neuman, Patrick R. Veres, Theodore K. Koenig, Rainer Volkamer, L. Gregory Huey, Thomas J. Bannan, Carl J. Percival, Ben H. Lee, and Joel A. Thornton
Atmos. Chem. Phys., 21, 13973–13996, https://doi.org/10.5194/acp-21-13973-2021,https://doi.org/10.5194/acp-21-13973-2021, 2021
Short summary

Related subject area

Atmospheric chemistry and physics
Aerosol single-scattering albedo derived by merging OMI/POLDER satellite products and AERONET ground observations
Yueming Dong, Jing Li, Zhenyu Zhang, Chongzhao Zhang, and Qiurui Li
Earth Syst. Sci. Data, 17, 3873–3892, https://doi.org/10.5194/essd-17-3873-2025,https://doi.org/10.5194/essd-17-3873-2025, 2025
Short summary
Remote sensing measurements during PaCE 2022 campaign
Simo Tukiainen, Tuomas Siipola, Niko Leskinen, and Ewan O'Connor
Earth Syst. Sci. Data, 17, 3797–3806, https://doi.org/10.5194/essd-17-3797-2025,https://doi.org/10.5194/essd-17-3797-2025, 2025
Short summary
Biologically effective daily radiant exposure for erythema appearance, previtamin D3 synthesis, and clearing of psoriatic lesions derived from erythemal broadband meters at Belsk, Poland, for the period 1976–2023
Janusz W. Krzyścin, Agnieszka Czerwińska, Bonawentura Rajewska-Więch, Janusz Jarosławski, Piotr S. Sobolewski, and Izabela Pawlak
Earth Syst. Sci. Data, 17, 3757–3775, https://doi.org/10.5194/essd-17-3757-2025,https://doi.org/10.5194/essd-17-3757-2025, 2025
Short summary
Global high-resolution fire-sourced PM2.5 concentrations for 2000–2023
Yonghang Hu, Chenguang Tian, Xu Yue, Yadong Lei, Yang Cao, Rongbin Xu, and Yuming Guo
Earth Syst. Sci. Data, 17, 3741–3756, https://doi.org/10.5194/essd-17-3741-2025,https://doi.org/10.5194/essd-17-3741-2025, 2025
Short summary
A high-resolution divergence and vorticity dataset in Beijing derived from radar wind profiler mesonet measurements
Xiaoran Guo, Jianping Guo, Deli Meng, Yuping Sun, Zhen Zhang, Hui Xu, Liping Zeng, Juan Chen, Ning Li, and Tianmeng Chen
Earth Syst. Sci. Data, 17, 3541–3552, https://doi.org/10.5194/essd-17-3541-2025,https://doi.org/10.5194/essd-17-3541-2025, 2025
Short summary

Cited articles

Becker, J. J., Sandwell, D. T., Smith, W. H. F., Braud, J., Binder, B., Depner, J., Fabre, D., Factor, J., Ingalls, S., Kim, S.-H., Ladner, R., Marks, K., Nelson, S., Pharaoh, A., Trimmer, R., Rosenberg, J. V., Wallace, G., and Weatherall, P.: Global Bathymetry and Elevation Data at 30 Arc Seconds Resolution: SRTM30_PLUS, Mar. Geod., 32, 355–371, https://doi.org/10.1080/01490410903297766, 2009. a
Behrenfeld, M. J. and Falkowski, P. G.: Photosynthetic rates derived from satellite-based chlorophyll concentration, Limnol. Oceanogr., 42, 1–20, https://doi.org/10.4319/lo.1997.42.1.0001, 1997. a
Bey, I., Jacob, D. J., Yantosca, R. M., Logan, J. A., Field, B. D., Fiore, A. M., Li, Q., Liu, H. Y., Mickley, L. J., and Schultz, M. G.: Global modeling of tropospheric chemistry with assimilated meteorology: Model description and evaluation, J. Geophys. Res., 106, 23073–23095, https://doi.org/10.1029/2001JD000807, 2001. a, b
Breiman, L.: Random forests, Mach. Learn., 45, 5–32, 2001. a, b, c, d
Campos, M., Farrenkopf, A., Jickells, T., and Luther, G.: A comparison of dissolved iodine cycling at the Bermuda Atlantic Time-series Station and Hawaii Ocean Time-series Station, Deep Sea Res. Pt. II, 43, 455–466, https://doi.org/10.1016/0967-0645(95)00100-X, 1996. a
Download
Short summary
Iodine plays an important role in the Earth system, as a nutrient to the biosphere and by changing the concentrations of climate and air-quality species. However, there are uncertainties on the magnitude of iodine’s role, and a key uncertainty is our understanding of iodide in the global sea-surface. Here we take a data-driven approach using a machine learning algorithm to convert a sparse set of sea-surface iodide observations into a spatially and temporally resolved dataset for use in models.
Share
Altmetrics
Final-revised paper
Preprint