#dmdu — Public Fediverse posts

"This paper traces the history of the IPCC’s use of DMDU [decision making under deep uncertainty] and explains the intersection with key IPCC concepts such as risk, scenarios, treatment of uncertainty, storylines and high-impact, low-likelihood outcomes, and both adaptation and climate resilient development pathways. The paper suggests how the IPCC might benefit from enhanced use of DMDU in its current (7th) assessment cycle."

#DMDU
#ScientificUncertainty

https://www.frontiersin.org/articles/10.3389/fclim.2024.1380054/full

"This paper traces the history of the IPCC’s use of DMDU [decision making under deep uncertainty] and explains the intersection with key IPCC concepts such as risk, scenarios, treatment of uncertainty, storylines and high-impact, low-likelihood outcomes, and both adaptation and climate resilient development pathways. The paper suggests how the IPCC might benefit from enhanced use of DMDU in its current (7th) assessment cycle."

#DMDU
#ScientificUncertainty

https://www.frontiersin.org/articles/10.3389/fclim.2024.1380054/full

"This paper traces the history of the IPCC’s use of DMDU [decision making under deep uncertainty] and explains the intersection with key IPCC concepts such as risk, scenarios, treatment of uncertainty, storylines and high-impact, low-likelihood outcomes, and both adaptation and climate resilient development pathways. The paper suggests how the IPCC might benefit from enhanced use of DMDU in its current (7th) assessment cycle."

#DMDU
#ScientificUncertainty

https://www.frontiersin.org/articles/10.3389/fclim.2024.1380054/full

"This paper traces the history of the IPCC’s use of DMDU [decision making under deep uncertainty] and explains the intersection with key IPCC concepts such as risk, scenarios, treatment of uncertainty, storylines and high-impact, low-likelihood outcomes, and both adaptation and climate resilient development pathways. The paper suggests how the IPCC might benefit from enhanced use of DMDU in its current (7th) assessment cycle."

#DMDU
#ScientificUncertainty

https://www.frontiersin.org/articles/10.3389/fclim.2024.1380054/full

"This paper traces the history of the IPCC’s use of DMDU [decision making under deep uncertainty] and explains the intersection with key IPCC concepts such as risk, scenarios, treatment of uncertainty, storylines and high-impact, low-likelihood outcomes, and both adaptation and climate resilient development pathways. The paper suggests how the IPCC might benefit from enhanced use of DMDU in its current (7th) assessment cycle."

#DMDU
#ScientificUncertainty

https://www.frontiersin.org/articles/10.3389/fclim.2024.1380054/full

In a new paper published in Earth’s Future, Klaus Keller (Dartmouth, formerly PSU) and I try to link the exploratory-modeling, robustness-centric #DMDU philosophy back to probabilistic models.

Using formal probability models has many advantages. For example, we can deliberately over-sample low-probability regions of the parameter space without distorting our estimates. We can also use simulation-visualization techniques to explore the implications of our (inevitably flawed) assumptions.

In a new paper published in Earth’s Future, Klaus Keller (Dartmouth, formerly PSU) and I try to link the exploratory-modeling, robustness-centric #DMDU philosophy back to probabilistic models.

Using formal probability models has many advantages. For example, we can deliberately over-sample low-probability regions of the parameter space without distorting our estimates. We can also use simulation-visualization techniques to explore the implications of our (inevitably flawed) assumptions.

In a new paper published in Earth’s Future, Klaus Keller (Dartmouth, formerly PSU) and I try to link the exploratory-modeling, robustness-centric #DMDU philosophy back to probabilistic models.

Using formal probability models has many advantages. For example, we can deliberately over-sample low-probability regions of the parameter space without distorting our estimates. We can also use simulation-visualization techniques to explore the implications of our (inevitably flawed) assumptions.

In a new paper published in Earth’s Future, Klaus Keller (Dartmouth, formerly PSU) and I try to link the exploratory-modeling, robustness-centric #DMDU philosophy back to probabilistic models.

Using formal probability models has many advantages. For example, we can deliberately over-sample low-probability regions of the parameter space without distorting our estimates. We can also use simulation-visualization techniques to explore the implications of our (inevitably flawed) assumptions.

Many classical approaches to climate risk management have used excessively narrow estimates of future risk (sup 👋 bulletin 17C) as a basis for “objective” cost-benefit analyses and the like.

A growing literature on decision making under deep uncertainty (#DMDU) rightly rejects this, instead emphasizing methods that identify plans that perform well over many possible futures.

Many classical approaches to climate risk management have used excessively narrow estimates of future risk (sup 👋 bulletin 17C) as a basis for “objective” cost-benefit analyses and the like.

A growing literature on decision making under deep uncertainty (#DMDU) rightly rejects this, instead emphasizing methods that identify plans that perform well over many possible futures.

Many classical approaches to climate risk management have used excessively narrow estimates of future risk (sup 👋 bulletin 17C) as a basis for “objective” cost-benefit analyses and the like.

A growing literature on decision making under deep uncertainty (#DMDU) rightly rejects this, instead emphasizing methods that identify plans that perform well over many possible futures.

Many classical approaches to climate risk management have used excessively narrow estimates of future risk (sup 👋 bulletin 17C) as a basis for “objective” cost-benefit analyses and the like.

A growing literature on decision making under deep uncertainty (#DMDU) rightly rejects this, instead emphasizing methods that identify plans that perform well over many possible futures.

Going to throw out a few more #hashtags for things that I like to expedite the connection here.
#academia #ExploratoryModeling #ScenarioDiscovery #SensitivityAnalysis #WaterResources #DMDU #Uncertainty #GenerativeArt #DataViz #Cornell #ClimateScience #Fractals #Chaos

Going to throw out a few more #hashtags for things that I like to expedite the connection here.
#academia #ExploratoryModeling #ScenarioDiscovery #SensitivityAnalysis #WaterResources #DMDU #Uncertainty #GenerativeArt #DataViz #Cornell #ClimateScience #Fractals #Chaos

Going to throw out a few more #hashtags for things that I like to expedite the connection here.
#academia #ExploratoryModeling #ScenarioDiscovery #SensitivityAnalysis #WaterResources #DMDU #Uncertainty #GenerativeArt #DataViz #Cornell #ClimateScience #Fractals #Chaos

Going to throw out a few more #hashtags for things that I like to expedite the connection here.
#academia #ExploratoryModeling #ScenarioDiscovery #SensitivityAnalysis #WaterResources #DMDU #Uncertainty #GenerativeArt #DataViz #Cornell #ClimateScience #Fractals #Chaos

Hi! I study water resource systems challenges with focuses on integrated human-natural systems modeling, decision making under #DeepUncertainty, multi-objective optimization.

Lately, I’ve been exploring ML methods for streamflow predictions in ungauged basins.

You can visit my site (which is a bit of a WIP at the moment): https://trevoramestoy.com//

I post frequently on the blog: https://waterprogramming.wordpress.com

Hoping to find some community here!
#introduction #DMDU #hydrology

Hi! I study water resource systems challenges with focuses on integrated human-natural systems modeling, decision making under #DeepUncertainty, multi-objective optimization.

Lately, I’ve been exploring ML methods for streamflow predictions in ungauged basins.

You can visit my site (which is a bit of a WIP at the moment): https://trevoramestoy.com//

I post frequently on the blog: https://waterprogramming.wordpress.com

Hoping to find some community here!
#introduction #DMDU #hydrology

Hi! I study water resource systems challenges with focuses on integrated human-natural systems modeling, decision making under #DeepUncertainty, multi-objective optimization.

Lately, I’ve been exploring ML methods for streamflow predictions in ungauged basins.

You can visit my site (which is a bit of a WIP at the moment): https://trevoramestoy.com//

I post frequently on the blog: https://waterprogramming.wordpress.com

Hoping to find some community here!
#introduction #DMDU #hydrology

Hi! I study water resource systems challenges with focuses on integrated human-natural systems modeling, decision making under #DeepUncertainty, multi-objective optimization.

Lately, I’ve been exploring ML methods for streamflow predictions in ungauged basins.

You can visit my site (which is a bit of a WIP at the moment): https://trevoramestoy.com//

I post frequently on the blog: https://waterprogramming.wordpress.com

Hoping to find some community here!
#introduction #DMDU #hydrology

Hi! I study water resource systems challenges with focuses on integrated human-natural systems modeling, decision making under #DeepUncertainty, multi-objective optimization.

Lately, I’ve been exploring ML methods for streamflow predictions in ungauged basins.

You can visit my site (which is a bit of a WIP at the moment): https://trevoramestoy.com//

I post frequently on the blog: https://waterprogramming.wordpress.com

Hoping to find some community here!
#introduction #DMDU #hydrology