Articles | Volume 10, issue 5
https://doi.org/10.5194/gmd-10-1889-2017
https://doi.org/10.5194/gmd-10-1889-2017
Methods for assessment of models
 | 
12 May 2017
Methods for assessment of models |  | 12 May 2017

Exploring precipitation pattern scaling methodologies and robustness among CMIP5 models

Ben Kravitz, Cary Lynch, Corinne Hartin, and Ben Bond-Lamberty

Related authors

A Climate Intervention Dynamical Emulator (CIDER) for Scenario Space Exploration
Jared Farley, Douglas G. MacMartin, Daniele Visioni, Ben Kravitz, Ewa Bednarz, Alistair Duffey, and Matthew Henry
EGUsphere, https://doi.org/10.5194/egusphere-2025-1830,https://doi.org/10.5194/egusphere-2025-1830, 2025
This preprint is open for discussion and under review for Geoscientific Model Development (GMD).
Short summary
Using Optimization Tools to Explore Stratospheric Aerosol Injection Strategies
Ezra Brody, Yan Zhang, Douglas G. MacMartin, Daniele Visioni, Ben Kravitz, and Ewa M. Bednarz
EGUsphere, https://doi.org/10.5194/egusphere-2024-3974,https://doi.org/10.5194/egusphere-2024-3974, 2025
Short summary
G6-1.5K-SAI: a new Geoengineering Model Intercomparison Project (GeoMIP) experiment integrating recent advances in solar radiation modification studies
Daniele Visioni, Alan Robock, Jim Haywood, Matthew Henry, Simone Tilmes, Douglas G. MacMartin, Ben Kravitz, Sarah J. Doherty, John Moore, Chris Lennard, Shingo Watanabe, Helene Muri, Ulrike Niemeier, Olivier Boucher, Abu Syed, Temitope S. Egbebiyi, Roland Séférian, and Ilaria Quaglia
Geosci. Model Dev., 17, 2583–2596, https://doi.org/10.5194/gmd-17-2583-2024,https://doi.org/10.5194/gmd-17-2583-2024, 2024
Short summary
Hemispherically symmetric strategies for stratospheric aerosol injection
Yan Zhang, Douglas G. MacMartin, Daniele Visioni, Ewa M. Bednarz, and Ben Kravitz
Earth Syst. Dynam., 15, 191–213, https://doi.org/10.5194/esd-15-191-2024,https://doi.org/10.5194/esd-15-191-2024, 2024
Short summary
Injection strategy – a driver of atmospheric circulation and ozone response to stratospheric aerosol geoengineering
Ewa M. Bednarz, Amy H. Butler, Daniele Visioni, Yan Zhang, Ben Kravitz, and Douglas G. MacMartin
Atmos. Chem. Phys., 23, 13665–13684, https://doi.org/10.5194/acp-23-13665-2023,https://doi.org/10.5194/acp-23-13665-2023, 2023
Short summary

Related subject area

Climate and Earth system modeling
SURFER v3.0: a fast model with ice sheet tipping points and carbon cycle feedbacks for short- and long-term climate scenarios
Victor Couplet, Marina Martínez Montero, and Michel Crucifix
Geosci. Model Dev., 18, 3081–3129, https://doi.org/10.5194/gmd-18-3081-2025,https://doi.org/10.5194/gmd-18-3081-2025, 2025
Short summary
NMH-CS 3.0: a C# programming language and Windows-system-based ecohydrological model derived from Noah-MP
Yong-He Liu and Zong-Liang Yang
Geosci. Model Dev., 18, 3157–3174, https://doi.org/10.5194/gmd-18-3157-2025,https://doi.org/10.5194/gmd-18-3157-2025, 2025
Short summary
A method for quantifying uncertainty in spatially interpolated meteorological data with application to daily maximum air temperature
Conor T. Doherty, Weile Wang, Hirofumi Hashimoto, and Ian G. Brosnan
Geosci. Model Dev., 18, 3003–3016, https://doi.org/10.5194/gmd-18-3003-2025,https://doi.org/10.5194/gmd-18-3003-2025, 2025
Short summary
Baseline Climate Variables for Earth System Modelling
Martin Juckes, Karl E. Taylor, Fabrizio Antonio, David Brayshaw, Carlo Buontempo, Jian Cao, Paul J. Durack, Michio Kawamiya, Hyungjun Kim, Tomas Lovato, Chloe Mackallah, Matthew Mizielinski, Alessandra Nuzzo, Martina Stockhause, Daniele Visioni, Jeremy Walton, Briony Turner, Eleanor O'Rourke, and Beth Dingley
Geosci. Model Dev., 18, 2639–2663, https://doi.org/10.5194/gmd-18-2639-2025,https://doi.org/10.5194/gmd-18-2639-2025, 2025
Short summary
PaleoSTeHM v1.0: a modern, scalable spatiotemporal hierarchical modeling framework for paleo-environmental data
Yucheng Lin, Robert E. Kopp, Alexander Reedy, Matteo Turilli, Shantenu Jha, and Erica L. Ashe
Geosci. Model Dev., 18, 2609–2637, https://doi.org/10.5194/gmd-18-2609-2025,https://doi.org/10.5194/gmd-18-2609-2025, 2025
Short summary

Cited articles

Barnes, E. A. and Barnes, R. J.: Estimating linear trends: Simple linear regression versus epoch differences, J. Climate, 28, 9969–9976, https://doi.org/10.1175/JCLI-D-15-0032.1, 2015.
Bentsen, M., Bethke, I., Debernard, J. B., Iversen, T., Kirkevåg, A., Seland, Ø., Drange, H., Roelandt, C., Seierstad, I. A., Hoose, C., and Kristjánsson, J. E.: The Norwegian Earth System Model, NorESM1-M – Part 1: Description and basic evaluation of the physical climate, Geosci. Model Dev., 6, 687–720, https://doi.org/10.5194/gmd-6-687-2013, 2013.
Cagnazzo, C., Manzini, E., Fogli, P. G., Vichi, M., and Davini, P.: Role of stratospheric dynamics in the ozone-carbon connection in the Southern Hemisphere, Clim. Dynam., 41, 3039–3054, https://doi.org/10.1007/s00382-013-1745-5, 2013.
Castruccio, S., McInerney, D. J., Stein, M. L., Crouch, F. L., Jacob, R. L., and Moyer, E. J.: Statistical Emulation of Climate Model Projections Based on Precomputed GCM Runs, J. Climate, 27, 1829–1844, https://doi.org/10.1175/JCLI-D-13-00099.1, 2014.
Davini, P., Cagnazzo, C., Fogi, P. G., Manzini, E., Gualdi, S., and Navarra, A.: European blocking and Atlantic jet stream variability in the NCEP/NCAR reanalysis and the CMCC-CMS climate model, Clim. Dynam., 43, 71–85, https://doi.org/10.1007/s00382-013-1873-y, 2014.
Download
Short summary
Pattern scaling is a way of approximating regional changes without needing to run a full, complex global climate model. We compare two methods of pattern scaling for precipitation and evaluate which methods is better in particular circumstances. We also decompose precipitation into a CO2 portion and a non-CO2 portion. The methodologies discussed in this paper can help provide precipitation fields for other models for a wide variety of scenarios of future climate change.
Share