Evaluating Parameterizations in General Circulation Models: Climate Simulation Meets Weather Prediction

By T. Phillips, G. Potter, David L. Williamson, R. Cederwall, J. Boyle, M. Fiorino, J. Hnilo, J. Olson, S. Xie, J. Yio. 2004

232 citations recorded by the source corpus.

Subfields: Atmospheric Science, Global and Planetary Change

View Paper: https://www.semanticscholar.org/paper/42adceea55b39ba41da0d177a0fc34e987188fc0

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Citations in the corpus

Challenges and Prospects for Reducing Coupled Climate Model SST Biases in the Eastern Tropical Atlantic and Pacific Oceans: The U.S. CLIVAR Eastern Tropical Oceans Synthesis Working Group (2016, background): “Systematic biases in model physics can also be uncovered through comparison to observations at high temporal and vertical resolution (Phillips et al. 2004; Webb et al. 2015; Nuijens et al. 2015).”
Improved Diurnal Cycle of Precipitation in E3SM With a Revised Convective Triggering Function (2019, methodology): “An ongoing work that uses the short‐term weather hindcast approach (Ma et al., 2015; Phillips et al., 2004) is being conducted to further understand the behaviors of the revised convective trigger at process level.”
How reliable are climate models? (2007, background): “…59A (2007), 1 sources of information such as the performance of climate models in initial value prediction on daily-to-seasonal time-scales (e.g. Phillips et al., 2004; Graham et al., 2005) and in the simulation of paleoclimates (e.g. Kohfeld and Harrison, 2000) are also available but are…”
The quiet revolution of numerical weather prediction (2015, background): “All rights reserved weather and climate modelling for the next decade 76 and progress in this area will require joint efforts in the weather and climate communities 77,78 .”
An Overview of the Atmospheric Component of the Energy Exascale Earth System Model (2019, methodology): “Associated Parameterizations Testbed (Phillips et al., 2004; Williams et al., 2013) was used to assess candidate physical parameterizations and tune the computationally expensive high‐resolution EAM configurations, following protocols described in previous studies (Boyle & Klein, 2010; Liu et al., 2”
Earth System Modeling 2.0: A Blueprint for Models That Learn From Observations and Targeted High‐Resolution Simulations (2017, methodology): “Fast parameterized processes in climate models often exhibit errors within a few hours or days of integration that are similar to errors in the mean state of the model [Phillips et al., 2004; Rodwell and Palmer, 2007; Xie et al., 2012; Ma et al., 2013; Klocke and Rodwell, 2014].”