Abstract
Regional distributions of the mean annual temperature in the 2000s are computed with and without the effect of anthropogenic influences on the climate in several sub-continental regions. Simulated global patterns of the temperature response to external forcings are regressed against observations using optimal fingerprinting. The global analysis provides constraints which are then used to construct the regional temperature distributions. A similar approach was also employed in previous work, but here the methodology is extended to examine changes in any region, including areas with a poor observational coverage that were omitted in the earlier study. Two different General Circulation Models (GCMs) are used in the analysis. Anthropogenic forcings are found to have at least quadrupled the likelihood of occurrence of a year warmer than the warmest year since 1900 in 23 out of the 24 regions. The temperature distributions computed with the two models are very similar. While a more detailed assessment of model dependencies remains to be made once additional suitable GCM simulations become available, the present study introduces the statistical methodology and demonstrates its first application. The derived information concerning the effect of human influences on the regional climate is useful for adaptation planning. Moreover, by pre-computing the change in the likelihood of exceeding a temperature threshold over a range of thresholds, this kind of analysis enables a near real-time assessment of the anthropogenic impact on the observed regional temperatures.
| Original language | English |
|---|---|
| Pages (from-to) | 1259-1274 |
| Number of pages | 16 |
| Journal | Climate Dynamics |
| Volume | 39 |
| Issue number | 6 |
| DOIs | |
| Publication status | Published - Sep 2012 |
| Externally published | Yes |
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Keywords
- Anthropogenic forcings
- Detection and attribution
- Regional temperature
ASJC Scopus subject areas
- Atmospheric Science
Cite this
The contribution of anthropogenic forcings to regional changes in temperature during the last decade. / Christidis, Nikolaos; Stott, Peter A.; Zwiers, Francis W.; Shiogama, Hideo; Nozawa, Toru.
In: Climate Dynamics, Vol. 39, No. 6, 09.2012, p. 1259-1274.Research output: Contribution to journal › Article
}
TY - JOUR
T1 - The contribution of anthropogenic forcings to regional changes in temperature during the last decade
AU - Christidis, Nikolaos
AU - Stott, Peter A.
AU - Zwiers, Francis W.
AU - Shiogama, Hideo
AU - Nozawa, Toru
PY - 2012/9
Y1 - 2012/9
N2 - Regional distributions of the mean annual temperature in the 2000s are computed with and without the effect of anthropogenic influences on the climate in several sub-continental regions. Simulated global patterns of the temperature response to external forcings are regressed against observations using optimal fingerprinting. The global analysis provides constraints which are then used to construct the regional temperature distributions. A similar approach was also employed in previous work, but here the methodology is extended to examine changes in any region, including areas with a poor observational coverage that were omitted in the earlier study. Two different General Circulation Models (GCMs) are used in the analysis. Anthropogenic forcings are found to have at least quadrupled the likelihood of occurrence of a year warmer than the warmest year since 1900 in 23 out of the 24 regions. The temperature distributions computed with the two models are very similar. While a more detailed assessment of model dependencies remains to be made once additional suitable GCM simulations become available, the present study introduces the statistical methodology and demonstrates its first application. The derived information concerning the effect of human influences on the regional climate is useful for adaptation planning. Moreover, by pre-computing the change in the likelihood of exceeding a temperature threshold over a range of thresholds, this kind of analysis enables a near real-time assessment of the anthropogenic impact on the observed regional temperatures.
AB - Regional distributions of the mean annual temperature in the 2000s are computed with and without the effect of anthropogenic influences on the climate in several sub-continental regions. Simulated global patterns of the temperature response to external forcings are regressed against observations using optimal fingerprinting. The global analysis provides constraints which are then used to construct the regional temperature distributions. A similar approach was also employed in previous work, but here the methodology is extended to examine changes in any region, including areas with a poor observational coverage that were omitted in the earlier study. Two different General Circulation Models (GCMs) are used in the analysis. Anthropogenic forcings are found to have at least quadrupled the likelihood of occurrence of a year warmer than the warmest year since 1900 in 23 out of the 24 regions. The temperature distributions computed with the two models are very similar. While a more detailed assessment of model dependencies remains to be made once additional suitable GCM simulations become available, the present study introduces the statistical methodology and demonstrates its first application. The derived information concerning the effect of human influences on the regional climate is useful for adaptation planning. Moreover, by pre-computing the change in the likelihood of exceeding a temperature threshold over a range of thresholds, this kind of analysis enables a near real-time assessment of the anthropogenic impact on the observed regional temperatures.
KW - Anthropogenic forcings
KW - Detection and attribution
KW - Regional temperature
UR - http://www.scopus.com/inward/record.url?scp=84866411817&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84866411817&partnerID=8YFLogxK
U2 - 10.1007/s00382-011-1184-0
DO - 10.1007/s00382-011-1184-0
M3 - Article
AN - SCOPUS:84866411817
VL - 39
SP - 1259
EP - 1274
JO - Climate Dynamics
JF - Climate Dynamics
SN - 0930-7575
IS - 6
ER -