Towards constraining climate sensitivity by linear analysis of feedback patterns in thousands of perturbed-physics GCM simulations
A linear analysis is applied to a multi-thousand member "perturbed physics" GCM ensemble to identify the dominant physical processes responsible for variation in climate sensitivity across the ensemble. Model simulations are provided by the distributed computing project, climate prediction...
| Главные авторы: | , , , , |
|---|---|
| Формат: | Journal article |
| Язык: | English |
| Опубликовано: |
Springer
2008
|
| Предметы: |
| _version_ | 1826307361388625920 |
|---|---|
| author | Sanderson, B Piani, C Ingram, W Stone, D Allen, M |
| author_facet | Sanderson, B Piani, C Ingram, W Stone, D Allen, M |
| author_sort | Sanderson, B |
| collection | OXFORD |
| description | A linear analysis is applied to a multi-thousand member "perturbed physics" GCM ensemble to identify the dominant physical processes responsible for variation in climate sensitivity across the ensemble. Model simulations are provided by the distributed computing project, climate prediction.net. A principal component analysis of model radiative response reveals two dominant independent feedback processes, each largely controlled by a single parameter change. The leading EOF was well correlated with the value of the entrainment coefficient - a parameter in the model's atmospheric convection scheme. Reducing this parameter increaes high vertical level moisture causing an enhanced clear sky greenhouse effect both in the control simulation and in the response to greenhouse gas forcing. This effect is compensated by an increase in reflected solar radiation from low level cloud upon warming. A set of 'secondary' cloud formation parameters partly modulate the degree of shortwave compensation from low cloud formation. The second EOF was correlated with the scaling of ice fall speed in clouds which affects the extent of cloud cover in the control simulation. The most prominent feature in the EOF was an increase in longwave cloud forcing. The two leading EOFs account for 70% of the ensemble variance in λ - the global feedback parameter. Linear predictors of feedback strength from model climatology are applied to observational datasets to estimate real world values of the overall climate feedback parameter. The predictors are found using correlations across the ensemble. Differences between predictions are largely due to the differences in observational estimates for top of atmosphere shortwave fluxes. Our validation does not rule out all the strong topical convective feedbacks leading to a large climate sensitivity. |
| first_indexed | 2024-03-07T07:01:57Z |
| format | Journal article |
| id | oxford-uuid:ffca00bd-7617-4cca-9129-8ee21469b1ee |
| institution | University of Oxford |
| language | English |
| last_indexed | 2024-03-07T07:01:57Z |
| publishDate | 2008 |
| publisher | Springer |
| record_format | dspace |
| spelling | oxford-uuid:ffca00bd-7617-4cca-9129-8ee21469b1ee2022-03-27T13:47:43ZTowards constraining climate sensitivity by linear analysis of feedback patterns in thousands of perturbed-physics GCM simulationsJournal articlehttp://purl.org/coar/resource_type/c_dcae04bcuuid:ffca00bd-7617-4cca-9129-8ee21469b1eePhysicsAtmospheric,Oceanic,and Planetary physicsEnvironmentClimate systems and policyEnglishOxford University Research Archive - ValetSpringer2008Sanderson, BPiani, CIngram, WStone, DAllen, MA linear analysis is applied to a multi-thousand member "perturbed physics" GCM ensemble to identify the dominant physical processes responsible for variation in climate sensitivity across the ensemble. Model simulations are provided by the distributed computing project, climate prediction.net. A principal component analysis of model radiative response reveals two dominant independent feedback processes, each largely controlled by a single parameter change. The leading EOF was well correlated with the value of the entrainment coefficient - a parameter in the model's atmospheric convection scheme. Reducing this parameter increaes high vertical level moisture causing an enhanced clear sky greenhouse effect both in the control simulation and in the response to greenhouse gas forcing. This effect is compensated by an increase in reflected solar radiation from low level cloud upon warming. A set of 'secondary' cloud formation parameters partly modulate the degree of shortwave compensation from low cloud formation. The second EOF was correlated with the scaling of ice fall speed in clouds which affects the extent of cloud cover in the control simulation. The most prominent feature in the EOF was an increase in longwave cloud forcing. The two leading EOFs account for 70% of the ensemble variance in λ - the global feedback parameter. Linear predictors of feedback strength from model climatology are applied to observational datasets to estimate real world values of the overall climate feedback parameter. The predictors are found using correlations across the ensemble. Differences between predictions are largely due to the differences in observational estimates for top of atmosphere shortwave fluxes. Our validation does not rule out all the strong topical convective feedbacks leading to a large climate sensitivity. |
| spellingShingle | Physics Atmospheric,Oceanic,and Planetary physics Environment Climate systems and policy Sanderson, B Piani, C Ingram, W Stone, D Allen, M Towards constraining climate sensitivity by linear analysis of feedback patterns in thousands of perturbed-physics GCM simulations |
| title | Towards constraining climate sensitivity by linear analysis of feedback patterns in thousands of perturbed-physics GCM simulations |
| title_full | Towards constraining climate sensitivity by linear analysis of feedback patterns in thousands of perturbed-physics GCM simulations |
| title_fullStr | Towards constraining climate sensitivity by linear analysis of feedback patterns in thousands of perturbed-physics GCM simulations |
| title_full_unstemmed | Towards constraining climate sensitivity by linear analysis of feedback patterns in thousands of perturbed-physics GCM simulations |
| title_short | Towards constraining climate sensitivity by linear analysis of feedback patterns in thousands of perturbed-physics GCM simulations |
| title_sort | towards constraining climate sensitivity by linear analysis of feedback patterns in thousands of perturbed physics gcm simulations |
| topic | Physics Atmospheric,Oceanic,and Planetary physics Environment Climate systems and policy |
| work_keys_str_mv | AT sandersonb towardsconstrainingclimatesensitivitybylinearanalysisoffeedbackpatternsinthousandsofperturbedphysicsgcmsimulations AT pianic towardsconstrainingclimatesensitivitybylinearanalysisoffeedbackpatternsinthousandsofperturbedphysicsgcmsimulations AT ingramw towardsconstrainingclimatesensitivitybylinearanalysisoffeedbackpatternsinthousandsofperturbedphysicsgcmsimulations AT stoned towardsconstrainingclimatesensitivitybylinearanalysisoffeedbackpatternsinthousandsofperturbedphysicsgcmsimulations AT allenm towardsconstrainingclimatesensitivitybylinearanalysisoffeedbackpatternsinthousandsofperturbedphysicsgcmsimulations |