Journal of Climate · 2010 · 37 citations · 15 references
EngineeringWeather ForecastingClimate ModelingEarth ScienceData AssimilationNumerical Weather PredictionRobustness ”Uncertainty QuantificationClimate ProjectionStatisticsClimate ChangeMeteorologyGeographyTruncation ParameterForecastingHybrid MethodClimatologyClimate Reconstruction MethodsSurrogate EnsemblesClimate Modelling
Abstract In a recent paper, Christiansen et al. compared climate reconstruction methods using surrogate ensembles from a coupled general circulation model and pseudoproxies. Their results using the regularized expectation maximization method with truncated total least squares (RegEM-TTLS) appear inconsistent with previous studies. Results presented here show that the poor performance of RegEM-TTLS in Christiansen et al. is due to 1) their use of the nonhybrid method compared to the hybrid method; 2) a stagnation tolerance that is too large and does not permit the solution to stabilize, which is compounded in another paper by Christiansen et al. by the introduction of an inappropriate measure of stagnation; and 3) their use of a truncation parameter that is too large. Thus, the poor performance of RegEM-TTLS in both Christiansen et al. papers is due to poor implementation of the method rather than to shortcomings inherent to the method.
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Statistical Methods in the Atmospheric Sciences
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Michael Mann, Zhihua Zhang, Malcolm K. Hughes et al. · Proceedings of the National Academy of Sciences · 2008 · 1.3K citations · Full text
Future Climatic Change, Engineering, Surface Temperature Reconstructions +17