Stochastic Weather and Climate Models
0
Citation
50
Reference
10
Related Paper
Keywords:
Forcing (mathematics)
Component (thermodynamics)
Climate system
Abstract. Disentangling the effects of internal variability and anthropogenic forcing on regional climate trends remains a key challenge with far-reaching implications. Due to its largely unpredictable nature on timescales longer than a decade, internal climate variability limits the accuracy of climate model projections, introduces challenges in attributing past climate changes, and complicates climate model evaluation. Here, we highlight recent advances in climate modeling and physical understanding that have led to novel insights about these key issues. In particular, we synthesize new findings from large-ensemble simulations with Earth system models, observational large ensembles, and dynamical adjustment methodologies, with a focus on European climate.
Forcing (mathematics)
Climate system
Earth system science
Cite
Citations (0)
Abstract. Disentangling the effects of internal variability and anthropogenic forcing on regional climate trends remains a key challenge with far-reaching implications. Due to its largely unpredictable nature on timescales longer than a decade, internal climate variability limits the accuracy of climate model projections, introduces challenges in attributing past climate changes, and complicates climate model evaluation. Here, we highlight recent advances in climate modeling and physical understanding that have led to novel insights about these key issues. In particular, we synthesize new findings from large-ensemble simulations with Earth system models, observational large ensembles, and dynamical adjustment methodologies, with a focus on European climate.
Climate system
Forcing (mathematics)
Earth system science
Cite
Citations (0)
Abstract. Disentangling the effects of internal variability and anthropogenic forcing on regional climate trends remains a key challenge with far-reaching implications. Due to its largely unpredictable nature on timescales longer than a decade, internal climate variability limits the accuracy of climate model projections, introduces challenges in attributing past climate changes, and complicates climate model evaluation. Here, we highlight recent advances in climate modeling and physical understanding that have led to novel insights about these key issues. In particular, we synthesize new findings from large-ensemble simulations with Earth system models, observational large ensembles, and dynamical adjustment methodologies, with a focus on European climate.
Forcing (mathematics)
Climate system
Earth system science
Cite
Citations (0)
Abstract. Disentangling the effects of internal variability and anthropogenic forcing on regional climate trends remains a key challenge with far-reaching implications. Due to its largely unpredictable nature on timescales longer than a decade, internal climate variability limits the accuracy of climate model projections, introduces challenges in attributing past climate changes, and complicates climate model evaluation. Here, we highlight recent advances in climate modeling and physical understanding that have led to novel insights about these key issues. In particular, we synthesize new findings from large-ensemble simulations with Earth system models, observational large ensembles, and dynamical adjustment methodologies, with a focus on European climate.
Climate system
Forcing (mathematics)
Earth system science
Cite
Citations (0)
The NCAR Community Climate System Model and Parallel Climate Model have produced one the largest data sets for the Intergovernmental Panel on Climate Change (IPCC) and its fourth Assessment. There will be some discussion of what is in state-of-art climate models. As a result of this and other climate assessments, most of the climate research science community now believes that mankind is changing the earth's system and that global warming is taking place. The changes are not only reflected in terms of means but also extremes. The new IPCC research findings will be presented along with future computational challenges. It is expected that in the future there will be a need for both terascale and petascale computing, which will allow for higher resolution climate models that have embedded hurricanes and smaller scale weather features as well as viable biogeochemical cycles. Because of concerns of burning fossil fuels there will be special emphasis on better estimates of the Earth's carbon cycle, which is a special concern for the DOE. In order to perform future climate change simulations, the computational methods will necessarily undergo a reexamination. Finally, at the end of talk there will be a discussion of how climate model studiesmore » can aid in future policy options, some of which will address 'geoengineering' the climate system.« less
Earth system science
Climate system
Climate state
Petascale computing
Climate commitment
Transient climate simulation
Cite
Citations (0)
Abstract. Disentangling the effects of internal variability and anthropogenic forcing on regional climate trends remains a key challenge with far-reaching implications. Due to its largely unpredictable nature on timescales longer than a decade, internal climate variability limits the accuracy of climate model projections, introduces challenges in attributing past climate changes, and complicates climate model evaluation. Here, we highlight recent advances in climate modeling and physical understanding that have led to novel insights about these key issues. In particular, we synthesize new findings from large-ensemble simulations with Earth system models, observational large ensembles, and dynamical adjustment methodologies, with a focus on European climate.
Climate system
Forcing (mathematics)
Earth system science
Climate science
Cite
Citations (0)
In this paper we study stochastic currents of Brownian motion $\xi(x)$, $x\in\mathbb{R}^{d}$, by using white noise analysis. For $x\in\mathbb{R}^{d}\backslash\{0\}$ and for $x=0\in\mathbb{R}$ we prove that the stochastic current $\xi(x)$ is a Hida distribution. Moreover for $x=0\in\mathbb{R}^{d}$ with $d>1$ we show that the stochastic current is not a Hida distribution.
Brownian noise
Backslash
Cite
Citations (0)
Disentangling the effects of internal variability and anthropogenic forcing on regional climate change remains a key challenge with far-reaching implications. Due to its largely unpredictable nature on timescales longer than a decade, internal climate variability limits the accuracy of climate model projections, introduces challenges in attributing past climate changes, and complicates climate model evaluation. Here, we highlight recent advances in climate modeling and physical understanding that have led to novel insights on these key issues. In particular, we synthesize new findings from Large Ensemble simulations with Earth System Models, Observational Large Ensembles, and “dynamical adjustment” methodologies, with a focus on European climate.
Forcing (mathematics)
Climate system
Earth system science
Cite
Citations (0)
Abstract. Disentangling the effects of internal variability and anthropogenic forcing on regional climate trends remains a key challenge with far-reaching implications. Due to its largely unpredictable nature on timescales longer than a decade, internal climate variability limits the accuracy of climate model projections, introduces challenges in attributing past climate changes, and complicates climate model evaluation. Here, we highlight recent advances in climate modeling and physical understanding that have led to novel insights about these key issues. In particular, we synthesize new findings from large-ensemble simulations with Earth system models, observational large ensembles, and dynamical adjustment methodologies, with a focus on European climate.
Forcing (mathematics)
Climate system
Earth system science
Cite
Citations (0)
Abstract. Disentangling the effects of internal variability and anthropogenic forcing on regional climate trends remains a key challenge with far-reaching implications. Due to its largely unpredictable nature on timescales longer than a decade, internal climate variability limits the accuracy of climate model projections, introduces challenges in attributing past climate changes, and complicates climate model evaluation. Here, we highlight recent advances in climate modeling and physical understanding that have led to novel insights about these key issues. In particular, we synthesize new findings from large-ensemble simulations with Earth system models, observational large ensembles, and dynamical adjustment methodologies, with a focus on European climate.
Forcing (mathematics)
Climate system
Climate science
Cite
Citations (0)