Articles | Volume 10, issue 1
https://doi.org/10.5194/gmd-10-57-2017
https://doi.org/10.5194/gmd-10-57-2017
Methods for assessment of models
 | 
05 Jan 2017
Methods for assessment of models |  | 05 Jan 2017

ASoP (v1.0): a set of methods for analyzing scales of precipitation in general circulation models

Nicholas P. Klingaman, Gill M. Martin, and Aurel Moise

Related authors

Atmospheric convergence zones stemming from large-scale mixing
Gabriel M. P. Perez, Pier Luigi Vidale, Nicholas P. Klingaman, and Thomas C. M. Martin
Weather Clim. Dynam., 2, 475–488, https://doi.org/10.5194/wcd-2-475-2021,https://doi.org/10.5194/wcd-2-475-2021, 2021
Short summary
Effects of horizontal resolution and air–sea coupling on simulated moisture source for East Asian precipitation in MetUM GA6/GC2
Liang Guo, Ruud J. van der Ent, Nicholas P. Klingaman, Marie-Estelle Demory, Pier Luigi Vidale, Andrew G. Turner, Claudia C. Stephan, and Amulya Chevuturi
Geosci. Model Dev., 13, 6011–6028, https://doi.org/10.5194/gmd-13-6011-2020,https://doi.org/10.5194/gmd-13-6011-2020, 2020
Short summary
Boreal summer intraseasonal oscillation in a superparameterized general circulation model: effects of air–sea coupling and ocean mean state
Yingxia Gao, Nicholas P. Klingaman, Charlotte A. DeMott, and Pang-Chi Hsu
Geosci. Model Dev., 13, 5191–5209, https://doi.org/10.5194/gmd-13-5191-2020,https://doi.org/10.5194/gmd-13-5191-2020, 2020
Short summary
The effect of seasonally and spatially varying chlorophyll on Bay of Bengal surface ocean properties and the South Asian monsoon
Jack Giddings, Adrian J. Matthews, Nicholas P. Klingaman, Karen J. Heywood, Manoj Joshi, and Benjamin G. M. Webber
Weather Clim. Dynam., 1, 635–655, https://doi.org/10.5194/wcd-1-635-2020,https://doi.org/10.5194/wcd-1-635-2020, 2020
Short summary
The Indian summer monsoon in MetUM-GOML2.0: effects of air–sea coupling and resolution
Simon C. Peatman and Nicholas P. Klingaman
Geosci. Model Dev., 11, 4693–4709, https://doi.org/10.5194/gmd-11-4693-2018,https://doi.org/10.5194/gmd-11-4693-2018, 2018
Short summary

Related subject area

Climate and Earth system modeling
An overview of cloud–radiation denial experiments for the Energy Exascale Earth System Model version 1
Bryce E. Harrop, Jian Lu, L. Ruby Leung, William K. M. Lau, Kyu-Myong Kim, Brian Medeiros, Brian J. Soden, Gabriel A. Vecchi, Bosong Zhang, and Balwinder Singh
Geosci. Model Dev., 17, 3111–3135, https://doi.org/10.5194/gmd-17-3111-2024,https://doi.org/10.5194/gmd-17-3111-2024, 2024
Short summary
The computational and energy cost of simulation and storage for climate science: lessons from CMIP6
Mario C. Acosta, Sergi Palomas, Stella V. Paronuzzi Ticco, Gladys Utrera, Joachim Biercamp, Pierre-Antoine Bretonniere, Reinhard Budich, Miguel Castrillo, Arnaud Caubel, Francisco Doblas-Reyes, Italo Epicoco, Uwe Fladrich, Sylvie Joussaume, Alok Kumar Gupta, Bryan Lawrence, Philippe Le Sager, Grenville Lister, Marie-Pierre Moine, Jean-Christophe Rioual, Sophie Valcke, Niki Zadeh, and Venkatramani Balaji
Geosci. Model Dev., 17, 3081–3098, https://doi.org/10.5194/gmd-17-3081-2024,https://doi.org/10.5194/gmd-17-3081-2024, 2024
Short summary
Subgrid-scale variability of cloud ice in the ICON-AES 1.3.00
Sabine Doktorowski, Jan Kretzschmar, Johannes Quaas, Marc Salzmann, and Odran Sourdeval
Geosci. Model Dev., 17, 3099–3110, https://doi.org/10.5194/gmd-17-3099-2024,https://doi.org/10.5194/gmd-17-3099-2024, 2024
Short summary
INFERNO-peat v1.0.0: a representation of northern high-latitude peat fires in the JULES-INFERNO global fire model
Katie R. Blackford, Matthew Kasoar, Chantelle Burton, Eleanor Burke, Iain Colin Prentice, and Apostolos Voulgarakis
Geosci. Model Dev., 17, 3063–3079, https://doi.org/10.5194/gmd-17-3063-2024,https://doi.org/10.5194/gmd-17-3063-2024, 2024
Short summary
The 4DEnVar-based weakly coupled land data assimilation system for E3SM version 2
Pengfei Shi, L. Ruby Leung, Bin Wang, Kai Zhang, Samson M. Hagos, and Shixuan Zhang
Geosci. Model Dev., 17, 3025–3040, https://doi.org/10.5194/gmd-17-3025-2024,https://doi.org/10.5194/gmd-17-3025-2024, 2024
Short summary

Cited articles

Bollasina, M. A. and Ming, Y.: The general circulation model precipitation bias over the southwestern equatorial Indian Ocean and its implications for simulating the South Asian monsoon, Clim. Dynam., 40, 823–838, 2013.
Brown, J. R., Jakob, C., and Haynes, J. M.: An evaluation of rainfall frequency and intensity over the Australian region in a global climate model, J. Climate, 23, 6504–6525, 2010.
Catto, J. L., Jakob, C., and Nicholls, N.: A global evaluation of fronts and precipitation in the ACCESS model, Aust. Meteorol. Oceanogr. Soc. J., 63, 191–203, 2013.
Dai, A.: Precipitation characteristics in eighteen coupled climate models, J. Climate, 19, 4606–4630, 2006.
Demory, M.-E., Vidale, P. L., Roberts, M. J., Berrisford, P., Strachan, J., Schiemann, R., and Mizielinski, M. S.: The role of horizontal resolution in simulating drivers of the global hydrological cycle, Clim. Dynam., 42, 2201–2225, 2014.
Download
Short summary
Weather and climate models show large errors in the frequency, intensity and persistence of daily rainfall, particularly in the tropics. We introduce a set of diagnostics to reveal the spatial and temporal scales of precipitation in models and compare them to satellite observations to inform development efforts. Although models show similar errors in 3 h precipitation, at the time step and gridpoint level some produce coherent precipitation and others exhibit worrying quasi-random behavior.