Articles | Volume 7, issue 3
https://doi.org/10.5194/gmd-7-1247-2014
https://doi.org/10.5194/gmd-7-1247-2014
Methods for assessment of models
 | 
30 Jun 2014
Methods for assessment of models |  | 30 Jun 2014

Root mean square error (RMSE) or mean absolute error (MAE)? – Arguments against avoiding RMSE in the literature

T. Chai and R. R. Draxler

Related authors

Foot and Mouth Disease atmospheric dispersion system
Keith Lambkin, James Hamilton, Guy McGrath, Paul Dando, and Roland Draxler
Adv. Sci. Res., 16, 113–117, https://doi.org/10.5194/asr-16-113-2019,https://doi.org/10.5194/asr-16-113-2019, 2019
Short summary
Improving volcanic ash predictions with the HYSPLIT dispersion model by assimilating MODIS satellite retrievals
Tianfeng Chai, Alice Crawford, Barbara Stunder, Michael J. Pavolonis, Roland Draxler, and Ariel Stein
Atmos. Chem. Phys., 17, 2865–2879, https://doi.org/10.5194/acp-17-2865-2017,https://doi.org/10.5194/acp-17-2865-2017, 2017
Short summary

Related subject area

Numerical methods
Modeling large‐scale landform evolution with a stream power law for glacial erosion (OpenLEM v37): benchmarking experiments against a more process-based description of ice flow (iSOSIA v3.4.3)
Moritz Liebl, Jörg Robl, Stefan Hergarten, David Lundbek Egholm, and Kurt Stüwe
Geosci. Model Dev., 16, 1315–1343, https://doi.org/10.5194/gmd-16-1315-2023,https://doi.org/10.5194/gmd-16-1315-2023, 2023
Short summary
A mixed finite-element discretisation of the shallow-water equations
James Kent, Thomas Melvin, and Golo Albert Wimmer
Geosci. Model Dev., 16, 1265–1276, https://doi.org/10.5194/gmd-16-1265-2023,https://doi.org/10.5194/gmd-16-1265-2023, 2023
Short summary
Multifidelity Monte Carlo estimation for efficient uncertainty quantification in climate-related modeling
Anthony Gruber, Max Gunzburger, Lili Ju, Rihui Lan, and Zhu Wang
Geosci. Model Dev., 16, 1213–1229, https://doi.org/10.5194/gmd-16-1213-2023,https://doi.org/10.5194/gmd-16-1213-2023, 2023
Short summary
Massively parallel modeling and inversion of electrical resistivity tomography data using PFLOTRAN
Piyoosh Jaysaval, Glenn E. Hammond, and Timothy C. Johnson
Geosci. Model Dev., 16, 961–976, https://doi.org/10.5194/gmd-16-961-2023,https://doi.org/10.5194/gmd-16-961-2023, 2023
Short summary
Parallelized domain decomposition for multi-dimensional Lagrangian random walk mass-transfer particle tracking schemes
Lucas Schauer, Michael J. Schmidt, Nicholas B. Engdahl, Stephen D. Pankavich, David A. Benson, and Diogo Bolster
Geosci. Model Dev., 16, 833–849, https://doi.org/10.5194/gmd-16-833-2023,https://doi.org/10.5194/gmd-16-833-2023, 2023
Short summary

Cited articles

Chai, T., Carmichael, G. R., Tang, Y., Sandu, A., Heckel, A., Richter, A., and Burrows, J. P.: Regional NOx emission inversion through a four-dimensional variational approach using SCIAMACHY tropospheric NO2 column observations, Atmos. Environ., 43, 5046–5055, 2009.
Chai, T., Kim, H.-C., Lee, P., Tong, D., Pan, L., Tang, Y., Huang, J., McQueen, J., Tsidulko, M., and Stajner, I.: Evaluation of the United States National Air Quality Forecast Capability experimental real-time predictions in 2010 using Air Quality System ozone and NO2 measurements, Geosci. Model Dev., 6, 1831–1850, https://doi.org/10.5194/gmd-6-1831-2013, 2013.
Chatterjee, A., Engelen, R. J., Kawa, S. R., Sweeney, C., and Michalak, A. M.: Background error covariance estimation for atmospheric CO2 data assimilation, J. Geophys. Res., 118, 10140–10154, 2013.
Horn, R. A. and Johnson, C. R.: Matrix Analysis, Cambridge University Press, 1990.
Huber, P. and Ronchetti, E.: Robust statistics, Wiley New York, 2009.