 |
| Titel |
Representation of climate extreme indices in the ACCESS1.3b coupled atmosphere–land surface model |
| VerfasserIn |
R. Lorenz, A. J. Pitman, M. G. Donat, A. L. Hirsch, J. Kala, E. A. Kowalczyk, R. M. Law, J. Srbinovsky |
| Medientyp |
Artikel
|
| Sprache |
Englisch
|
| ISSN |
1991-959X
|
| Digitales Dokument |
URL |
| Erschienen |
In: Geoscientific Model Development ; 7, no. 2 ; Nr. 7, no. 2 (2014-04-04), S.545-567 |
| Datensatznummer |
250115581
|
| Publikation (Nr.) |
 copernicus.org/gmd-7-545-2014.pdf |
|
|
|
|
|
| Zusammenfassung |
| Climate extremes, such as heat waves and heavy precipitation events, have
large impacts on ecosystems and societies. Climate models provide useful
tools for studying underlying processes and amplifying effects associated
with extremes. The Australian Community Climate and Earth System Simulator
(ACCESS) has recently been coupled to the Community Atmosphere Biosphere Land
Exchange (CABLE) model. We examine how this model represents climate extremes
derived by the Expert Team on Climate Change Detection and Indices (ETCCDI)
and compare them to observational data sets using the AMIP framework. We find
that the patterns of extreme indices are generally well represented. Indices
based on percentiles are particularly well represented and capture the trends
over the last 60 years shown by the observations remarkably well. The diurnal
temperature range is underestimated, minimum temperatures (TMIN)
during nights are generally too warm and daily maximum temperatures
(TMAX) too low in the model. The number of consecutive wet days is
overestimated, while consecutive dry days are underestimated. The maximum
consecutive 1-day precipitation amount is underestimated on the global scale.
Biases in TMIN correlate well with biases in incoming longwave
radiation, suggesting a relationship with biases in cloud cover. Biases in
TMAX depend on biases in net shortwave radiation as well as
evapotranspiration. The regions and season where the bias in
evapotranspiration plays a role for the TMAX bias correspond to
regions and seasons where soil moisture availability is limited. Our analysis
provides the foundation for future experiments that will examine how
land-surface processes contribute to these systematic biases in the ACCESS
modelling system. |
| |
|
| Teil von |
|
|
|
|
|
|
|
|