Articles | Volume 11, issue 8
https://doi.org/10.5194/gmd-11-3089-2018
https://doi.org/10.5194/gmd-11-3089-2018
Development and technical paper
 | 
01 Aug 2018
Development and technical paper |  | 01 Aug 2018

Quasi-Newton methods for atmospheric chemistry simulations: implementation in UKCA UM vn10.8

Emre Esentürk, Nathan Luke Abraham, Scott Archer-Nicholls, Christina Mitsakou, Paul Griffiths, Alex Archibald, and John Pyle

Related authors

Last-millennium volcanic forcing and climate response using SO2 emissions
Lauren R. Marshall, Anja Schmidt, Andrew P. Schurer, Nathan Luke Abraham, Lucie J. Lücke, Rob Wilson, Kevin J. Anchukaitis, Gabriele C. Hegerl, Ben Johnson, Bette L. Otto-Bliesner, Esther C. Brady, Myriam Khodri, and Kohei Yoshida
Clim. Past, 21, 161–184, https://doi.org/10.5194/cp-21-161-2025,https://doi.org/10.5194/cp-21-161-2025, 2025
Short summary
Data supporting the North Atlantic Climate System Integrated Study (ACSIS) programme, including atmospheric composition; oceanographic and sea-ice observations (2016–2022); and output from ocean, atmosphere, land, and sea-ice models (1950–2050)
Alex T. Archibald, Bablu Sinha, Maria R. Russo, Emily Matthews, Freya A. Squires, N. Luke Abraham, Stephane J.-B. Bauguitte, Thomas J. Bannan, Thomas G. Bell, David Berry, Lucy J. Carpenter, Hugh Coe, Andrew Coward, Peter Edwards, Daniel Feltham, Dwayne Heard, Jim Hopkins, James Keeble, Elizabeth C. Kent, Brian A. King, Isobel R. Lawrence, James Lee, Claire R. Macintosh, Alex Megann, Bengamin I. Moat, Katie Read, Chris Reed, Malcolm J. Roberts, Reinhard Schiemann, David Schroeder, Timothy J. Smyth, Loren Temple, Navaneeth Thamban, Lisa Whalley, Simon Williams, Huihui Wu, and Mingxi Yang
Earth Syst. Sci. Data, 17, 135–164, https://doi.org/10.5194/essd-17-135-2025,https://doi.org/10.5194/essd-17-135-2025, 2025
Short summary
Virtual Integration of Satellite and In-situ Observation Networks (VISION) v1.0: In-Situ Observations Simulator (ISO_simulator)
Maria R. Russo, Sadie L. Bartholomew, David Hassell, Alex M. Mason, Erica Neininger, A. James Perman, David A. J. Sproson, Duncan Watson-Parris, and Nathan Luke Abraham
Geosci. Model Dev., 18, 181–191, https://doi.org/10.5194/gmd-18-181-2025,https://doi.org/10.5194/gmd-18-181-2025, 2025
Short summary
Applications of Machine Learning and Artificial Intelligence in Tropospheric Ozone Research
Sebastian H. M. Hickman, Makoto Kelp, Paul T. Griffiths, Kelsey Doerksen, Kazuyuki Miyazaki, Elyse A. Pennington, Gerbrand Koren, Fernando Iglesias-Suarez, Martin G. Schultz, Kai-Lan Chang, Owen R. Cooper, Alexander T. Archibald, Roberto Sommariva, David Carlson, Hantao Wang, J. Jason West, and Zhenze Liu
EGUsphere, https://doi.org/10.5194/egusphere-2024-3739,https://doi.org/10.5194/egusphere-2024-3739, 2025
This preprint is open for discussion and under review for Geoscientific Model Development (GMD).
Short summary
Climate Forcing due to Future Ozone Changes: An intercomparison of metrics and methods
William J. Collins, Fiona M. O'Connor, Connor R. Barker, Rachael E. Byrom, Sebastian D. Eastham, Øivind Hodnebrog, Patrick Jöckel, Eloise A. Marais, Mariano Mertens, Gunnar Myhre, Matthias Nützel, Dirk Olivié, Ragnhild Bieltvedt Skeie, Laura Stecher, Larry W. Horowitz, Vaishali Naik, Gregory Faluvegi, Ulas Im, Lee T. Murray, Drew Shindell, Kostas Tsigaridis, Nathan Luke Abraham, and James Keeble
EGUsphere, https://doi.org/10.5194/egusphere-2024-3698,https://doi.org/10.5194/egusphere-2024-3698, 2024
Short summary

Related subject area

Atmospheric sciences
Coupling the urban canopy model TEB (SURFEXv9.0) with the radiation model SPARTACUS-Urbanv0.6.1 for more realistic urban radiative exchange calculation
Robert Schoetter, Robin James Hogan, Cyril Caliot, and Valéry Masson
Geosci. Model Dev., 18, 405–431, https://doi.org/10.5194/gmd-18-405-2025,https://doi.org/10.5194/gmd-18-405-2025, 2025
Short summary
Forecasting contrail climate forcing for flight planning and air traffic management applications: the CocipGrid model in pycontrails 0.51.0
Zebediah Engberg, Roger Teoh, Tristan Abbott, Thomas Dean, Marc E. J. Stettler, and Marc L. Shapiro
Geosci. Model Dev., 18, 253–286, https://doi.org/10.5194/gmd-18-253-2025,https://doi.org/10.5194/gmd-18-253-2025, 2025
Short summary
Simulation of the heat mitigation potential of unsealing measures in cities by parameterizing grass grid pavers for urban microclimate modelling with ENVI-met (V5)
Nils Eingrüber, Alina Domm, Wolfgang Korres, and Karl Schneider
Geosci. Model Dev., 18, 141–160, https://doi.org/10.5194/gmd-18-141-2025,https://doi.org/10.5194/gmd-18-141-2025, 2025
Short summary
AI-NAOS: an AI-based nonspherical aerosol optical scheme for the chemical weather model GRAPES_Meso5.1/CUACE
Xuan Wang, Lei Bi, Hong Wang, Yaqiang Wang, Wei Han, Xueshun Shen, and Xiaoye Zhang
Geosci. Model Dev., 18, 117–139, https://doi.org/10.5194/gmd-18-117-2025,https://doi.org/10.5194/gmd-18-117-2025, 2025
Short summary
Orbital-Radar v1.0.0: a tool to transform suborbital radar observations to synthetic EarthCARE cloud radar data
Lukas Pfitzenmaier, Pavlos Kollias, Nils Risse, Imke Schirmacher, Bernat Puigdomenech Treserras, and Katia Lamer
Geosci. Model Dev., 18, 101–115, https://doi.org/10.5194/gmd-18-101-2025,https://doi.org/10.5194/gmd-18-101-2025, 2025
Short summary

Cited articles

Banzon, V., Reynolds, R., and National Center for Atmospheric Research Staff (Eds.): The Climate Data Guide: SST data: NOAA High-resolution (0.25×0.25) Blended Analysis of Daily SST and Ice, OISSTv2, available at: https://climatedataguide.ucar.edu/climate-data/sst-data-noaa-high-resolution-025x025-blended-analysis-daily -sst-and-ice-oisstv2, last access: 23 June 2018.
Atkinson, K.: Introduction to Numerical Analysis, John Wiley & Sons Inc., 1989.
Banerjee, A., Maycock, A. C., Archibald, A. T., Abraham, N. L., Telford, P., Braesicke, P., and Pyle, J. A.: Drivers of changes in stratospheric and tropospheric ozone between year 2000 and 2100, Atmos. Chem. Phys., 16, 2727–2746, https://doi.org/10.5194/acp-16-2727-2016, 2016.
Brandt, A.: Multilevel adaptive solutions to boundary value problems, Math. Comp., 31, 333–390, 1977.
Download
Short summary
An integral and expensive part of coupled climate model simulations is the gas-phase chemistry which gives rise to hundreds of coupled differential equations. We propose a method which improves the convergence and robustness properties of commonly used Newton–Raphson solvers. The method is flexible and can be appended to most algorithms. The approach can be useful for a broader community of computational scientists whose interests lie in solving systems with intensive interactive chemistry.