Matches in SemOpenAlex for { <https://semopenalex.org/work/W4313574240> ?p ?o ?g. }
Showing items 1 to 69 of
69
with 100 items per page.
- W4313574240 abstract "Regional emulation tools based on statistical relationships, such as pattern scaling, provide a computationally inexpensive way of projecting ocean dynamic sea-level change for a broad range of climate change scenarios. Such approaches usually require a careful selection of one or more predictor variables of climate change so that the statistical model is properly optimized. Even when appropriate predictors have been selected, spatiotemporal oscillations driven by internal climate variability can be a large source of model disagreement. Using pattern recognition techniques that exploit spatial covariance information can effectively reduce internal variability in simulations of ocean dynamic sea level, significantly reducing random errors in regional emulation tools. Here, we test two pattern recognition methods based on Empirical Orthogonal Functions (EOF), namely signal-to-noise maximising EOF pattern filtering and low-frequency component analysis, for their ability to reduce errors in pattern scaling of ocean dynamic sea-level change. These two methods are applied to the initial-condition large ensemble MPI-GE, so that internal variability is optimally characterized while avoiding model biases. We show that pattern filtering provides an efficient way of reducing errors compared to other conventional approaches such as a simple ensemble average. For instance, filtering only two realizations by characterising their common response to external forcing reduces the random error by almost 60 %, a reduction level that is only achieved by averaging at least 12 realizations. We further investigate the applicability of both methods to single realization modelling experiments, including four CMIP5 simulations for comparison with previous regional emulation analyses. Pattern scaling leads to a varying degree of error reduction depending on the model and scenario, ranging from more than 20 % to about 70 % reduction in global-mean root-mean-squared error compared with unfiltered simulations. Our results highlight the relevance of pattern recognition methods as a tool to reduce errors in regional emulation tools of ocean dynamic sea-level change, especially when one or a few realizations are available. Removing internal variability prior to tuning regional emulation tools can optimize the performance of the statistical model and simplify the choice of suitable predictors." @default.
- W4313574240 created "2023-01-06" @default.
- W4313574240 date "2023-01-05" @default.
- W4313574240 modified "2023-10-14" @default.
- W4313574240 title "Comment on egusphere-2022-1293" @default.
- W4313574240 doi "https://doi.org/10.5194/egusphere-2022-1293-rc2" @default.
- W4313574240 hasPublicationYear "2023" @default.
- W4313574240 type Work @default.
- W4313574240 citedByCount "0" @default.
- W4313574240 crossrefType "peer-review" @default.
- W4313574240 hasBestOaLocation W43135742401 @default.
- W4313574240 hasConcept C105795698 @default.
- W4313574240 hasConcept C11413529 @default.
- W4313574240 hasConcept C115961682 @default.
- W4313574240 hasConcept C119857082 @default.
- W4313574240 hasConcept C134306372 @default.
- W4313574240 hasConcept C13724139 @default.
- W4313574240 hasConcept C149810388 @default.
- W4313574240 hasConcept C154945302 @default.
- W4313574240 hasConcept C159985019 @default.
- W4313574240 hasConcept C162324750 @default.
- W4313574240 hasConcept C178650346 @default.
- W4313574240 hasConcept C192562407 @default.
- W4313574240 hasConcept C197115733 @default.
- W4313574240 hasConcept C204323151 @default.
- W4313574240 hasConcept C2524010 @default.
- W4313574240 hasConcept C2781089630 @default.
- W4313574240 hasConcept C33923547 @default.
- W4313574240 hasConcept C41008148 @default.
- W4313574240 hasConcept C50522688 @default.
- W4313574240 hasConcept C99498987 @default.
- W4313574240 hasConcept C99844830 @default.
- W4313574240 hasConceptScore W4313574240C105795698 @default.
- W4313574240 hasConceptScore W4313574240C11413529 @default.
- W4313574240 hasConceptScore W4313574240C115961682 @default.
- W4313574240 hasConceptScore W4313574240C119857082 @default.
- W4313574240 hasConceptScore W4313574240C134306372 @default.
- W4313574240 hasConceptScore W4313574240C13724139 @default.
- W4313574240 hasConceptScore W4313574240C149810388 @default.
- W4313574240 hasConceptScore W4313574240C154945302 @default.
- W4313574240 hasConceptScore W4313574240C159985019 @default.
- W4313574240 hasConceptScore W4313574240C162324750 @default.
- W4313574240 hasConceptScore W4313574240C178650346 @default.
- W4313574240 hasConceptScore W4313574240C192562407 @default.
- W4313574240 hasConceptScore W4313574240C197115733 @default.
- W4313574240 hasConceptScore W4313574240C204323151 @default.
- W4313574240 hasConceptScore W4313574240C2524010 @default.
- W4313574240 hasConceptScore W4313574240C2781089630 @default.
- W4313574240 hasConceptScore W4313574240C33923547 @default.
- W4313574240 hasConceptScore W4313574240C41008148 @default.
- W4313574240 hasConceptScore W4313574240C50522688 @default.
- W4313574240 hasConceptScore W4313574240C99498987 @default.
- W4313574240 hasConceptScore W4313574240C99844830 @default.
- W4313574240 hasLocation W43135742401 @default.
- W4313574240 hasOpenAccess W4313574240 @default.
- W4313574240 hasPrimaryLocation W43135742401 @default.
- W4313574240 hasRelatedWork W2105508921 @default.
- W4313574240 hasRelatedWork W2352047550 @default.
- W4313574240 hasRelatedWork W2364163520 @default.
- W4313574240 hasRelatedWork W2365238420 @default.
- W4313574240 hasRelatedWork W2365695644 @default.
- W4313574240 hasRelatedWork W2370479027 @default.
- W4313574240 hasRelatedWork W2884535015 @default.
- W4313574240 hasRelatedWork W3017054987 @default.
- W4313574240 hasRelatedWork W4231884363 @default.
- W4313574240 hasRelatedWork W641208093 @default.
- W4313574240 isParatext "false" @default.
- W4313574240 isRetracted "false" @default.
- W4313574240 workType "peer-review" @default.