Validation of CMIP5 multimodel ensembles through the smoothness of
                        climate variables

Lee, Myoungji; Jun, Mikyoung; Genton, Marc G.

doi:10.3402/tellusa.v67.23880

Cited by 5 publications

(5 citation statements)

References 26 publications

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“…Lower resolution indicative results are provided in a global analysis, useful for a high-level identification of regions with a high potential for thermal mass passive cooling, to guide the focus of subsequent regional studies. (Lee et al 2015). The same method as outlined above for the regional analysis is used for the lower resolution global analysis: adaptive comfort thresholds are computed by extracting the average daily mean and maximum 2 m air temperature of the yearly rolling 30 hottest days in every GCM grid cell.…”

Section: • Ineffectivementioning

confidence: 99%

Internal thermal mass for passive cooling and ventilation: adaptive comfort limits, ideal quantities, embodied carbon

Toldi

Craig

Sushama

2022

Buildings and Cities

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How effective is naturally ventilated internal thermal mass for obviating air-conditioning, mitigating heatwaves and storing carbon in buildings? This study combines detailed climate model outputs with scaling rules for optimizing internal thermal mass coupled with buoyancy ventilation. It identifies regions where this passive design strategy is most effective during future heatwaves and determines how much internal thermal mass each person needs to stay comfortable in these regions, with a special focus on Canada. Results suggest that naturally ventilated internal thermal mass is likely to become less effective due to future global heating. Regions where internal thermal mass will no longer be sufficient to obviate air-conditioning and where it can still play a significant role in hybrid cooling are identified. By comparing the ideal per capita thermal mass quantities in different regions, it is found that biomass-based materials require approximately 3.5 times the volume of cementitious materials to perform equivalently, if thermal proportions for surface area and thickness are respected. Finally, an analysis of the per capita embodied carbon of these ideal internal thermal mass quantities is undertaken, suggesting a fair functional unit to compare thermal mass materials.

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Section: • Ineffectivementioning

confidence: 99%

Internal thermal mass for passive cooling and ventilation: adaptive comfort limits, ideal quantities, embodied carbon

Toldi

Craig

Sushama

2022

Buildings and Cities

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“…temperature, chemical species concentrations and jet position) or be a more derived quantity which gets closer to evaluating the model against the process it is trying to simulate (e.g. ozone trends versus temperature trends, chemical species correlations, and relationships of chemistrymeteorology and transport ) (Eyring et al, 2006;Waugh and Eyring, 2008;Christensen et al, 2010;Lee et al, 2015). Performance metrics are chosen based upon expert knowledge of the modelled system to ensure that metrics are highly related to the physical or chemical processes that the models are being evaluated on.…”

Section: Introductionmentioning

confidence: 99%

Projecting ozone hole recovery using an ensemble of chemistry–climate models weighted by model performance and independence

et al. 2020

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Abstract. Calculating a multi-model mean, a commonly used method for ensemble averaging, assumes model independence and equal model skill. Sharing of model components amongst families of models and research centres, conflated by growing ensemble size, means model independence cannot be assumed and is hard to quantify. We present a methodology to produce a weighted-model ensemble projection, accounting for model performance and model independence. Model weights are calculated by comparing model hindcasts to a selection of metrics chosen for their physical relevance to the process or phenomena of interest. This weighting methodology is applied to the Chemistry–Climate Model Initiative (CCMI) ensemble to investigate Antarctic ozone depletion and subsequent recovery. The weighted mean projects an ozone recovery to 1980 levels, by 2056 with a 95 % confidence interval (2052–2060), 4 years earlier than the most recent study. Perfect-model testing and out-of-sample testing validate the results and show a greater projective skill than a standard multi-model mean. Interestingly, the construction of a weighted mean also provides insight into model performance and dependence between the models. This weighting methodology is robust to both model and metric choices and therefore has potential applications throughout the climate and chemistry–climate modelling communities.

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“…The analysis of spatial and temporal correlation of the climate output has been discussed in previous works (Koichi et al, 2012;Jun et al, 2008b,a;Lee et al, 2015), but always in terms of trend, although the necessity of pursuing an investigation on the variability about the mean climate was mentioned (but not implemented) in Jun et al (2008a). This work is the first that addresses this issue by defining a space-time statistical model and comparing the estimated statistical parameters among climate models and reanalyses.…”

Section: Introductionmentioning

confidence: 99%

Assessing the spatio-temporal structure of annual and seasonal surface temperature for CMIP5 and reanalysis

Castruccio

2016

Spatial Statistics

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Comparison of climate models in an ensemble with reanalysis data is crucial for the climate model user community, as detection of discrepancies can convey information to improve models. Current comparison methodologies focus on statistical space-time properties of the climatological mean, and allow for a sensible model comparison only if the forcing scenario is identical or very similar. We analyse the annual and seasonal surface temperature of the CMIP5 ensemble and three reanalysis data products, and propose a scenario-independent, statistical-based classification relying on the space-time structure of the variability around the climatological mean. This approach exploits the gridded geometry of the atmospheric component of a global climate model, complements traditional criteria based on characteristics of the climatological trend and allows for a novel measure of similarity. For models with a similar physical scheme, we found a high degree of similarity for the same grid resolution, and a moderate similarity if the resolution is different. Further, we found that a considerable difference among reanalysis data products, thus indicating that different assimilation algorithms can significantly impact the space-time structure of the variability around the mean climate.

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Validation of CMIP5 multimodel ensembles through the smoothness of climate variables

Cited by 5 publications

References 26 publications

Internal thermal mass for passive cooling and ventilation: adaptive comfort limits, ideal quantities, embodied carbon

Internal thermal mass for passive cooling and ventilation: adaptive comfort limits, ideal quantities, embodied carbon

Projecting ozone hole recovery using an ensemble of chemistry–climate models weighted by model performance and independence

Assessing the spatio-temporal structure of annual and seasonal surface temperature for CMIP5 and reanalysis

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