The use and application of performance metrics with regional climate models

May, Christopher (2016) The use and application of performance metrics with regional climate models. Doctoral thesis, University of East Anglia.

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This thesis aims to assess and develop objective and robust approaches to evaluate
regional climate model (RCM) historical skill using performance metrics and to
provide guidance to relevant groups as to how best utilise these metrics. Performance
metrics are quantitative, scalar measures of the numerical distance, or
’error’, between historical model simulations and observations. Model evaluation
practice tends to involve ad hoc approaches with little consideration to the underlying
sensitivity of the method to small changes in approach. The main questions
that arise are to what degree are the outputs, and subsequent applications, of these
performance metrics robust?
ENSEMBLES and CORDEX RCMs covering Europe are used with E-OBS
observational data to assess historical and future simulation characteristics using a
range of performance metrics. Metric sensitivity is found in some cases to be low,
such as differences between variable types, with extreme indices often producing
redundant information. In other cases sensitivity is large, particularly for temporal
statistics, but not for spatial pattern statistics. Assessments made over a single
decade are found to be robust with respect to the full 40-year time period.
Two applications of metrics are considered: metric combinations and exploration
of the stationarity of historical RCM bias characteristics. The sensitivity of
metric combination procedure is found to be low with respect to the combination
method and potentially high for the type of metric included, but remains uncertain
for the number of metrics included. Stationarity of biases appears to be highly
dependent on the potential for underlying causes of model bias to change substantially
in the future, such as the case of surface albedo in the Alps.
It is concluded that performance metrics and their applications can and should
be considered more systematically using a range of redundancy and stationarity
tests as indicators of historical and future robustness.

Item Type: Thesis (Doctoral)
Faculty \ School: Faculty of Science > School of Environmental Sciences
Depositing User: Users 7376 not found.
Date Deposited: 17 Jun 2016 13:25
Last Modified: 17 Jun 2016 13:25


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