The Evolution of Integrated Assessment · The Evolution of Integrated Assessment: Developing the next generation of use-inspired tools Karen Fisher-Vanden Pennsylvania State University

The Evolution of Integrated Assessment:Developing the next generation of use-inspired tools

Karen Fisher-Vanden

Pennsylvania State University

John Weyant

Stanford University

“…all models are wrong, but some are useful.”

--G.E.P. Box and N.R. Draper (1987)

• “Integrated assessment” in the climate change context began with the pioneering work of William Nordhaus in the early 1990s.

• He was awarded the 2018 Nobel Prize in Economic Science for this work!

• These early IA studies were focused on long-run global mitigation policy analysis, and as a result IAMs were coarse in spatial, sectoral and temporal scale.

Source: IPCC SAR, 1995

The Evolution of Integrated Assessment


Early Integrated Assessment Models“Benefit-Cost” (BC) IAMs:

• include feedbacks between earth system model and socioeconomic model.

• Focused on determining the “optimal” level of emissions reductions

• Also used to generate social cost of carbon estimates

“Detailed Process” (DP) IAMs: have more detailed representations of the underlying socioeconomic processes but ignore climate change induced impacts on the economy

• Used to generate emissions scenarios used as inputs to earth system models.

The Next Generation of IAMs

• With the lack of serious mitigation efforts at the global scale, the modeling focus has moved from mitigation policy assessments to improving our understanding of impacts

• The impacts, adaptation and vulnerability (IAV) community have become interested in the use of IAMs due to their emphasis on interconnected systems.

• Some early IAMs did capture impacts, but at a much coarser resolution and usually did not assign economic value to them

• Past statistical and process model IAV studies focused on a specific sector and/or region but ignored spatial and sectoral interactions.

• Disconnect between detailed empirical impact studies and IAMs


Source: US National Climate Assessment, 2018

The Next Generation of IAMs

• However, the usefulness of these tools for impacts analysis is limited without

improvements to account for finer spatial scale and process detail

• Improvements in data, algorithms, and computational power have led to the emergence of the “multisector dynamics” field (aka IAV IAMs).

• New program in the Office of Science at DOE. Replaces Integrated Assessment program. Emphasis on descriptive rather than prescriptive.

• Emphasis on “use case” framing rather than specific sectors and/or regions.

• Focus has shifted to developing generalizable frameworks for specific types of problem; e.g., rather than studying ag impacts of water scarcity in isolation, study impacts from competing demands for scarce water.

• This new emphasis requires tools that capture detailed sectoral and regional interactions

Integrated Assessment

From the Integrated Assessment Society:

“Integrated assessment (IA) can be defined as the scientific “meta-

discipline” that integrates knowledge about a problem domain and

makes it available for societal learning and decision making

processes. Public policy issues involving long-range and long-term

environmental management are where the roots of integrated

assessment can be found. However, today, IA is used to frame, study

and solve issues at other scales. IA has been developed for acid rain,

climate change, land degradation, water and air quality

management, forest and fisheries management and public health.

The field of Integrated Assessment engages stakeholders and

scientists, often drawing these from many disciplines.”

MultiSector Dynamics

From the Department of Energy, Office of Science:

“MultiSector Dynamics seeks to advance scientific

understanding of the complex interactions, interdependencies,

and co-evolutionary pathways of human and natural systems,

including interdependencies among sectors and

infrastructures. This includes advancing relevant socio-

economic, risk analysis, and complex decision theory methods

to lead insights into earth system science, while emphasizing

the development of interoperable data, modeling, and analysis

tools for integration within flexible modeling frameworks.”

Program on Coupled Human and Earth Systems (PCHES)www.PCHES.psu.edu

A $20 million, five-year Cooperative Research Agreement with the

Department of Energy’s Office of Science (MultiSector Dynamics Program).

Motivation and Purpose:

• Energy, water, and land systems interact in complex and, as yet, poorly-

understood ways

• Enormous implications for international trade, food security, reliability of

electric power supply, demographic patterns, and the resilience of

communities and critical infrastructure to natural hazards

• PCHES seeks to create a new, state-of-the-art, integrated modeling framework to drive advances in the quantitative understanding of these coupled systems

Participants: ~20 investigators, ~8 post-docs, and 10+ grad students from 10 institutions and multiple disciplines (e.g., engineering, hydrology, earth system science, economics, law, statistics, agronomy)

http://www.pches.psu.edu/

Directors

PCHES Teamwww.pches.psu.edu

Karen Fisher-Vanden

Professor, Env and Resource Econ

Penn State University

John Weyant

Professor, Mgmt Science and Eng

Stanford University

Managing Director

Rob Nicholas

Assoc Research Professor, EESI


Senior Personnel

Staff

Katerina Kostadinova


Polly Yan

Stanford University

Lara Fowler

Sr. Lecturer, Penn State Law


Steve Frolking

Research Professor, ISEOS

University of New Hampshire

Murali Haran

Professor, Statistics


Tom Hertel

Professor, Agricultural Economics

Purdue University

Klaus Keller

Professor, Geosciences


Richard Lammers

Research Asst Professor, ISEOS

University of New Hampshire

Erin Mansur

Professor, Tuck School of

Business

Dartmouth College

Doug Wrenn

Asst Professor, Env and Resource Econ


Mort Webster

Professor, Energy Engineering


Ian Sue Wing

Assoc Professor, Dept of Earth and Env

Boston University

Ryan Sriver

Assoc Professor, Atmospheric Science

University of Illinois, Urbana-Champaign

Wolfram Schlenker

Professor, School of Intl and Public Affairs

Columbia University

Sheila Olmstead

Professor, School of Public Affairs

University of Texas, Austin



Research Program Elements:

I. Develop Integrated EWL Modeling Frameworks

I.I. Gridded modeling of integrated energy-water-land systems dynamics

I.2. Capturing governance, institutional, and system constraints in an integrated energy-water-land modeling framework

I.3. Global modeling of integrated energy-water-land systems dynamics

II. Develop Model/Module Integration Methods

III. Frameworks for characterizing uncertainties and developing diagnostics

for multisector dynamics analyses

IV. Multisector dynamics community building activities


Socioeconomic

System

Physical

Systems

Temperature,

Precipitation,

Extreme Events

Prices,

Demand

Crop

productivity

Agricultural System Agriculture / Food

Earth

System

Question: What is the impact of water scarcity on the

interconnected energy-water-land system?

Socioeconomic

System

Physical

Systems

Hydrologic System

Temperature,

Precipitation,

Extreme Events

Prices,

Demand

Crop

productivity

Agricultural System

Water

Demand

Agriculture / Food

Water

Supply

Temperature,

Precipitation,

Extreme Events

Earth

System



Socioeconomic

System

Physical

Systems

Hydrologic System

Temperature,

Precipitation,

Extreme Events

Prices,

Demand

Crop

productivity;

population/

labor

Agricultural System

Water

Demand

Agriculture / Food

Water

Supply

Temperature,

Precipitation,

Extreme Events

Earth

System

Urban systems;

populations



Socioeconomic

System

Physical

Systems

Hydrologic System

Temperature,

Precipitation,

Extreme Events

Prices,

Demand

Crop

productivity;

population/

labor;

electric

power

supply/

productivity

Agricultural System

Water

Demand

Agriculture / Food

Water

Supply

Temperature,

Precipitation,

Extreme Events

Earth

System

Urban systems;

populations

Electric Power System



Socioeconomic

System

Physical

Systems

Hydrologic System

Temperature,

Precipitation,

Extreme Events

Prices,

Demand

Crop

productivity;

population/

labor;

electric

power

supply/

productivity

Agricultural System

Water

Demand

Agriculture / Food

Water

Supply

Temperature,

Precipitation,

Extreme Events

Urban systems;

populations


Water rights systems

Earth

System

Extreme Events;

Disaster declarations



Socioeconomic

System

Physical

Systems

Hydrologic System

Temperature,

Precipitation,

Extreme Events

Prices,

Demand

Crop

productivity;

population/

labor;

electric

power

supply/

productivity

Agricultural System

Water

Demand

Agriculture / Food

Water

Supply

Temperature,

Precipitation,

Extreme Events

Urban systems;

populations


Water rights systems

Earth

System

Extreme Events;

Disaster declarations

Primary energy

Construction

Transportation

Trade

Manufacturing

Electric power

Services; e.g., health,

tourism, insurance

Households




Research Program Elements:

I. Develop Integrated EWL Modeling Frameworks

I.I. Gridded modeling of integrated energy-water-land systems dynamics

I.2. Capturing governance, institutional, and system constraints in an integrated energy-water-land modeling framework

I.3. Global modeling of integrated energy-water-land systems dynamics

II. Develop Model/Module Integration Methods

III. Frameworks for characterizing uncertainties and developing diagnostics

for multisector dynamics analyses

IV. Multisector dynamics community building activities


Socio-Economic Sectors

Physical Models

Energy/Power Systems

Land System

Large-Scale Earth Systems

Ocean

Atmosphere

Cryosphere

Land Surface

Fine-scale Climate Data Translation

Pattern Scaling

Emulation

Empirical-Statistical Downscaling

Uncertainty Quantification

GHG Emissions

Coarse-Scale Climate Fields

Crop prices, water demand

Water System

Project 1.1—Gridded modeling of integrated energy-water-land systems dynamics

Hertel (lead), Grogan, Haqiqi, Lammers, Liu, Schlenker, Sun, Valqui, Webster

Agriculture / Food

Water, energy, land resources

Soft Coupling

Soft Coupling

ESM

Temperature,Precipitation, Extreme Events


Electricity-Land-Water System Dynamics in the

MISO regionWhat if states adopt biomassco-firing of coal units to meet RPS?

Highlights importance of fine‐scale resolution in determining the joint outcome between the spatial distribution of power generation and the spatial distribution of water quality impacts from biomass.

State-level

Model

Physical

Systems

Water Balance Model

Power System model:

hourly; WECC

Population, migration,

demographics model:

yearly; state/region

Primary energyTemperature,

Precipitation,

Extreme Events

Prices,

Wages,

Demand

Population/

labor, crop

productivity,

electric

power

supply/

productivity

Crop Model: yearly;

state/region

Water

Demand

Temperature,

Precipitation,

Extreme Events

Construction

Transportation

Trade

Manufacturing

Agriculture / Food

Electric power

Services; e.g., health,

tourism, insurance

Project 1.2—Capturing governance, institutional, and system constraints in an

integrated energy-water-land modeling framework Fisher-Vanden (lead), Caccese, Fowler,

Frolking, Grogan, Jayasekera, Kumar, Lammers, Nicholas, Peklak, Perla, Webster, Wrenn

Households

Water

Supply

Temperature,

Precipitation,

Extreme Events

Temporal scale: yearly

Spatial scale: CA, rest of

WECC, rest of US

Temporal scale: daily

Spatial scale: grid

Fine-scale

Climate

Drivers

Temporal scale:

daily

Spatial scale: grid

Extreme Events;

Disaster declarations Water rights systems

Soft Coupling

Hard Coupling

Methods: Aggregate to WMA-level representation

Flo

w a

lloca

tio

n%

of

tota

l flo

w a

lloca

tio

nIrrigation

DomesticOther

Environmental

A: Water rights allocation accumulated by priority date

Priority date

B: Each sector’s % of flow allocation

Point of Diversion

Irrigation gets 85% Livestock gets 3%Domestic gets 10%Other gets 2%Environmental gets 0%

1969

1880 2000

B: Distributionof flow allocations

by sector

A: Aggregate WMA flow allocations through time from WBM

Water demand & supply

Modeling scheme:

Simulated by WBM

Water distributionVolume-dependent rules based on water rights data

Water sector distribution is applied across WMA by WBM

Socio-Economic Sectors

Physical Systems Emulators

Population, Migration, Demographics

Energy/Power Systems

Land System

Urban Infrastructure

Industrial Infrastructure

Coastal Infrastructure

Primary energy

Large-scale Earth Systems

Ocean

Atmosphere

Cryosphere

Land Surface

Fine-scale Climate Data Translation

Pattern Scaling

Emulation

Empirical-Statistical Downscaling

Uncertainty Quantification

GHG Emissions

Coarse-Scale Climate Fields

Prices, Wages, Demand

Water System

Demand

Project 1.3--Global modeling of integrated energy-water-land systems dynamics

Sue Wing (lead), Mansur, De Cian, Mansur, Mistry, van Ruijven

Construction

Transportation

Trade

Manufacturing

Agriculture / Food

Electric powerSoft Coupling

Households

Water, energy, land resources, population, productivity, preferences

ESM

Governance,

institutional,

and system

constraints



Services; e.g., health, tourism, insurance

Emulators of Climate Change Impacts

• Objectives

• Simplify the process of incorporating climate change impacts into a diverse range of models

• Represent shifts in key human system endpoints due to future climate change in a computationally

efficient and empirically grounded manner

• Approach

• Estimate empirical models of endpoint responses to meteorology using historical data

• Combine fitted models with outputs of climate models at different spatial/temporal scales

• Incorporate resulting “shocks” into various IAM and IAV models to assess primarily economic effects

Energy

• US counties (Sue Wing, in prep): Shocks to hourly per capita electricity demand under RCP 4.5/8.5 scenarios

simulated by 21 climate models, ca 2050

• Global, gridded (De Cian and Sue Wing, 2019; Van Ruijven, De Cian and Sue Wing, 2019): Shocks to demand for

petroleum, natural gas, electricity in agriculture, residential, commercial, industrial sectors under RCP 4.5/8.5

scenarios simulated by 21 climate models, ca 2050

Agriculture

• US counties (Sue Wing et al, 2015): Maize, wheat, soybean, sorghum, cotton yield changes under 3 warming

scenarios simulated by MIT IGSM, ca 2050, 2090

• Global, countries (Waldhoff et al, in review): Changes in yields of 12 crops under RCP 4.5/8.5 scenarios

simulated by 4 climate models, decadally to 2100

• Global, gridded (Sue Wing, De Cian and Mistry, in review): Maize, wheat, soybean, yield changes under RCP

4.5/8.5 scenarios simulated by 21 climate models, ca 2050, 2090

Building the Next Generation of Integrated Assessment Tools: Challenges

(1) Model Coupling Challenges

• Need new innovative computational methods to connect and translate information across

modeling platforms with very different temporal, sectoral, and spatial resolutions.

(2) Translating Empirical Findings into Integrated Assessment Models (IAMs)

• Persistent problem that excellent econometric work has been done on climate change

impacts that has not found its way into IAMs

• Requires econometricians and IAMers to be working collaboratively to develop empirical

results that can easily translated into IAMs.

(3) Training of the next generation of multidisciplinary scholars

• Graduate students and post-doctoral scholars are the engine of our projects

• No longer possible to toss information “over the fence.” Requires close interactions

between faculty, graduate students and post-docs from different disciplinary backgrounds

and institutions

• Need more students trained in computational economics and willing to learn other

disciplinary tools

• Reward system challenges

Expanding the Definition of IA

Weyant et al, (1996):

Integrated assessment models (IAMs) are computational tools that “link an array of component models based on mathematical representations of information from the various contributing disciplines”

Parson and Fisher-Vanden (1997):

IAMs as tools that “seek to combine knowledge from multiple disciplines in formal integrated representations; inform policy-making, structure knowledge, and prioritize key uncertainties; and advance knowledge of broad system linkages and feedbacks, particularly between socioeconomic and biophysical processes.”

Fisher-Vanden and Weyant (2019):

IAMs are tools that capture the complex interactions and interdependencies across the natural and human systems and across spatial and temporal scales for a wide range of uses including improving the science of fine-scale impact analysis, multi-stakeholder policymaking, and the development of adaptation strategies.

Thank you!!

Documents

The Evolution of Integrated Assessment · The Evolution of Integrated Assessment: Developing the next generation of use-inspired tools Karen Fisher-Vanden Pennsylvania State University