2007
DOI: 10.1175/bams-88-3-375
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Transferability Intercomparison: An Opportunity for New Insight on the Global Water Cycle and Energy Budget

Abstract: Transferability intercomparisons provide a new approach for advancing the science of modeling the water cycle and energy budget on regional to global scales by using multiple limited-area models applied to multiple domains. The water and associated energy cycles introduce exponential, episodic, and other nonlinear processes that create difficulties for observing, simulating, and predicting climate variations. The water cycle both creates and responds to spatial heterogeneities that feed back strongly on the en… Show more

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Cited by 57 publications
(51 citation statements)
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“…In the context of hydrological modelling, avoiding the one-case-study application should become the rule rather than the exception, as also argued by Andréassian et al (2006). This is one convincing way to make our results more generalisable and our models more reliable (Takle et al, 2007).…”
Section: Repeating Experimentssupporting
confidence: 54%
“…In the context of hydrological modelling, avoiding the one-case-study application should become the rule rather than the exception, as also argued by Andréassian et al (2006). This is one convincing way to make our results more generalisable and our models more reliable (Takle et al, 2007).…”
Section: Repeating Experimentssupporting
confidence: 54%
“…A model is considered transferable if it is able to produce realistic results outside of the domain for which it was developed and tested (Takle et al, 2007). Model transferability is closely related to the concept of model sensitivity, which is a measure of how variation in model output can be attributed to variation in model input (Saltelli et al, 2004).…”
mentioning
confidence: 99%
“…A climate change assessment for international market systems also allows for what Takle et al (2007) refer to as "transferability intercomparisons." Models developed for one region may not be transferable to another region, as the parameters of the functions and models may have been specifically "tuned" to phenomena unique to a region.…”
Section: Uncertainty Analysis and Transferability Intercomparisonsmentioning
confidence: 99%
“…While poor performance when models are applied out-of-sample is a challenge, an industry-wide assessment provides an opportunity for comparing multiple models in multiple regions, which, in contrast to typical model intercomparisons that are limited to either applying multiple models to a single region or a single model to multiple regions, is more likely to expose the limits of current models and model parameterizations and contribute to global model improvement (Takle et al 2007). Furthermore, more confidence can be placed in the transferability of models to future time slices if, based on comparisons for current and historical periods, the models perform well in multiple spatial domains that experience a wide range of conditions, some of which might be reflective of the future expectations for a specific region.…”
Section: Uncertainty Analysis and Transferability Intercomparisonsmentioning
confidence: 99%