Abstract
In this study we develop methods for dynamically downscaling output from six general circulation models (GCMs) for two emissions scenarios using a variable-resolution atmospheric climate model. The use of multiple GCMs and emissions scenarios gives an estimate of model range in projected changes to the mean climate across the region. By modeling the atmosphere at a very fine scale, the simulations capture processes that are important to regional weather and climate at length scales that are subgrid scale for the host GCM. We find that with a multistaged process of increased resolution and the application of bias adjustment methods, the ability of the simulation to reproduce observed conditions improves, with greater than 95% of the spatial variance explained for temperature and about 90% for rainfall. Furthermore, downscaling leads to a significant improvement for the temporal distribution of variables commonly used in applied analyses, reproducing seasonal variability in line with observations. This seasonal signal is not evident in the GCMs. This multistaged approach allows progressive improvement in the skill of the simulations in order to resolve key processes over the region with quantifiable improvements in the correlations with observations.
| Language | English |
|---|---|
| Pages | 11936-11950 |
| Number of pages | 15 |
| Journal | Journal of Geophysical Research Atmospheres |
| Volume | 118 |
| Issue number | 21 |
| DOIs | |
| Publication status | Published - 16 Nov 2013 |
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Keywords
- conformal cubic atmospheric model
- downscaling
- high resolution climate projections
- regional climate model
- variable-resolution regional climate model
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Performance of downscaled regional climate simulations using a variable-resolution regional climate model : Tasmania as a test case. / Corney, Stuart; Grose, Michael; Bennett, James C.; White, Christopher; Katzfey, Jack; McGregor, John; Holz, Greg; Bindoff, Nathaniel L.
In: Journal of Geophysical Research Atmospheres, Vol. 118, No. 21, 16.11.2013, p. 11936-11950.Research output: Contribution to journal › Article
TY - JOUR
T1 - Performance of downscaled regional climate simulations using a variable-resolution regional climate model
T2 - Journal of Geophysical Research: Atmospheres
AU - Corney, Stuart
AU - Grose, Michael
AU - Bennett, James C.
AU - White, Christopher
AU - Katzfey, Jack
AU - McGregor, John
AU - Holz, Greg
AU - Bindoff, Nathaniel L.
PY - 2013/11/16
Y1 - 2013/11/16
N2 - In this study we develop methods for dynamically downscaling output from six general circulation models (GCMs) for two emissions scenarios using a variable-resolution atmospheric climate model. The use of multiple GCMs and emissions scenarios gives an estimate of model range in projected changes to the mean climate across the region. By modeling the atmosphere at a very fine scale, the simulations capture processes that are important to regional weather and climate at length scales that are subgrid scale for the host GCM. We find that with a multistaged process of increased resolution and the application of bias adjustment methods, the ability of the simulation to reproduce observed conditions improves, with greater than 95% of the spatial variance explained for temperature and about 90% for rainfall. Furthermore, downscaling leads to a significant improvement for the temporal distribution of variables commonly used in applied analyses, reproducing seasonal variability in line with observations. This seasonal signal is not evident in the GCMs. This multistaged approach allows progressive improvement in the skill of the simulations in order to resolve key processes over the region with quantifiable improvements in the correlations with observations.
AB - In this study we develop methods for dynamically downscaling output from six general circulation models (GCMs) for two emissions scenarios using a variable-resolution atmospheric climate model. The use of multiple GCMs and emissions scenarios gives an estimate of model range in projected changes to the mean climate across the region. By modeling the atmosphere at a very fine scale, the simulations capture processes that are important to regional weather and climate at length scales that are subgrid scale for the host GCM. We find that with a multistaged process of increased resolution and the application of bias adjustment methods, the ability of the simulation to reproduce observed conditions improves, with greater than 95% of the spatial variance explained for temperature and about 90% for rainfall. Furthermore, downscaling leads to a significant improvement for the temporal distribution of variables commonly used in applied analyses, reproducing seasonal variability in line with observations. This seasonal signal is not evident in the GCMs. This multistaged approach allows progressive improvement in the skill of the simulations in order to resolve key processes over the region with quantifiable improvements in the correlations with observations.
KW - conformal cubic atmospheric model
KW - downscaling
KW - high resolution climate projections
KW - regional climate model
KW - variable-resolution regional climate model
UR - http://www.scopus.com/inward/record.url?scp=84889820975&partnerID=8YFLogxK
U2 - 10.1002/2013JD020087
DO - 10.1002/2013JD020087
M3 - Article
VL - 118
SP - 11936
EP - 11950
JO - Journal of Geophysical Research: Atmospheres
JF - Journal of Geophysical Research: Atmospheres
SN - 2169-897X
IS - 21
ER -