Klaus Keller

• Ph.D. Princeton University
• Hodgson Distinguished Professor at Dartmouth College

Anthropogenic greenhouse gas emissions are changing the Earth’s climate and impose substantial risks for current and future generations. What are scientifically sound, economically viable, and ethically defendable strategies to manage these climate risks? Ratified international agreements call for a reduction of greenhouse gas emissions to avoid da...

Sea-level rise poses considerable risks to coastal communities, ecosystems, and infrastructure. Decision makers are faced with deeply uncertain sea-level projections when designing a strategy for coastal adaptation. The traditional methods have provided tremendous insight into this decision problem, but are often silent on tradeoffs as well as the...

Disentangling the relative importance of climate change abatement policies from the human–Earth system (HES) uncertainties that determine their performance is challenging because the two are inexorably linked, and the nature of this linkage is dynamic, interactive and metric specific ¹ . Here, we demonstrate an approach to quantify the individual a...

Climate change has increased the frequency and intensity of natural disasters. Does this translate into increased economic damages? To date, empirical assessments of damage trends have been inconclusive. Our study demonstrates a temporal increase in extreme damages, after controlling for a number of factors. We analyze event-level data using quanti...

The social cost of methane (SC-CH4) measures the economic loss of welfare caused by emitting one tonne of methane into the atmosphere. This valuation may in turn be used in cost–benefit analyses or to inform climate policies1–3. However, current SC-CH4 estimates have not included key scientific findings and observational constraints. Here we estima...

Riverine flooding poses significant risks. Developing strategies to manage flood risks requires flood projections with decision-relevant scales and well-characterized uncertainties, often at high spatial resolutions. However, calibrating high-resolution flood models can be computationally prohibitive. To address this challenge, we propose a probabi...

Reducing uncertainties in regional carbon balances requires a better understanding of CO2 transport in synoptic weather systems. Here, we apply the Patient Rule Induction Method (PRIM) to airborne observations of of potential temperature, wind speed, water vapor mixing ratio, and CO2 dry mol fraction gathered during the Atmospheric Carbon and Trans...

Harnessing scientific research to address societal challenges requires careful alignment of expertise, resources, and research questions with real‐world needs, timelines, and constraints. In the case of place‐based research, studies can avoid misalignment when grounded in the realities of specific locations and conducted in collaboration with knowl...

Many climate policies adopt improving equity as a key objective. A key challenge is that policies often conceive of equity in terms of individuals but introduce strategies that focus on spatially coarse administrative areas. For example, the Justice40 Initiative in the United States requires 518 diverse federal programs to prioritize funds for “dis...

Plain Language Summary Individuals, organizations, businesses, and governments face difficult choices about how to adapt to the changing climate. Research can help by, for example, providing insights about future climate conditions or showing how potential courses of action may play out under those conditions. But like all decisions, climate adapta...

Many climate policies adopt improving equity as a key objective. Achieving this broad goal is non-trivial. A key challenge is that policies often conceive of equity in terms of individuals but introduce strategies that focus on spatially coarse administrative areas like census tracts. For example, the Justice40 Initiative in the United States requi...

A software package for adding parametric uncertainty to the national structure inventory and estimating flood losses with uncertain depth-damage relationships: https://github.com/abpoll/unsafe.

Decision-makers increasingly invoke equity to motivate, design, implement and evaluate strategies for managing flood risks. Unfortunately, there is little guidance on how analysts can develop measurements that support these tasks. Here we analyse how equity can be defined and measured by surveying 167 peer-reviewed publications that explicitly stat...

Harnessing scientific research to address pressing societal needs requires careful alignment of resources, expertise, and research questions with real-world needs, timelines, and partnerships. Literature on best practices for place-based transdisciplinary research is underdeveloped on the question of choosing locations to help achieve this alignmen...

Atmospheric CO2 flux inversions require as input an estimate of spatial and temporal correlations of errors in their estimate of the prior mean. Some previous studies have used the differences in CO2 daily average flux estimates produced by terrestrial carbon cycle models and eddy covariance measurements to constrain the flux error correlations. Si...

Climate change is predicted to impact corn yields. Previous studies analyzing these impacts differ in data and modeling approaches and, consequently, corn yield projections. We analyze the impacts of climate change on corn yields using two statistical models with different approaches for dealing with county-level effects. The first model, which is...

This poster summarizes the paper, "Transparency on underlying values is needed for useful equity measurements" (https://osf.io/preprints/osf/kvyxr), a review paper on how equity is defined and measured in peer-reviewed flood risk research.

Mission-oriented climate change research is often unverifiable. Therefore, many stakeholders look to peer-reviewed climate change research for trustworthy information about deeply uncertain and impactful phenomena. This is because peer-review signals that research has been vetted for scientific standards like reproducibility and replicability. Here...

Decision-makers increasingly invoke equity to motivate, design, implement, and evaluate strategies for managing flood risks. Unfortunately, there is little guidance on how analysts can develop measurements that support these tasks. Here, we analyze how equity can be defined and measured by surveying 167 peer-reviewed publications that explicitly st...

Government agencies often require cost-benefit tests for environmental risk mitigation measures. These tests implicitly prioritize more valuable assets and may therefore produce inequitable outcomes. Previous studies propose directly prioritizing vulnerable groups or minimizing Gini coefficients, but these violate popular notions of procedural equi...

Climate mitigation can bring air quality and health co-benefits. How these health impacts might be distributed across countries remains unclear. Here we use a coupled climate–energy–health model to assess the country-varying health effects of a global carbon price across nearly 30,000 future states of the world (SOWs). As a carbon price lowers foss...

Green Infrastructure (GI) measures are increasingly used for climate adaptation in urban areas, but it remains a challenge to evaluate their effectiveness and strategically allocate investment. Planning GI is subject to deep uncertainties and requires navigating tradeoffs between multiple objectives. Many-Objective Robust Decision Making (MORDM) ca...

Models with high-dimensional parameter spaces are common in many applications. Global sensitivity analyses can provide insights on how uncertain inputs and interactions influence the outputs. Many sensitivity analysis methods face nontrivial challenges for computationally demanding models. Common approaches to tackle these challenges are to (i) use...

Flooding drives considerable risks. Designing strategies to manage these risks is complicated by the often-large uncertainty surrounding flood risk projections. Uncertainty surrounding riverine flood risks can stem, for example, from choices regarding boundary conditions, model structures, and parameters as well as interactions among hazards, expos...

Flooding drives considerable risks. Designing strategies to manage these risks is complicated by the often large uncertainty surrounding flood risk projections. Uncertainty surrounding riverine flood risks can stem from choices regarding boundary conditions, model structures, and parameters as well as interactions among hazards, exposures, and vuln...

Floods drive dynamic and deeply uncertain risks for people and infrastructures. Uncertainty characterization is a crucial step in improving the predictive understanding of multi-sector dynamics and the design of risk-management strategies. Current approaches to estimate flood hazards often sample only a relatively small subset of the known unknowns...

Plain Language Summary Identifying sound strategies to manage risks driven by climatic changes is a complex task given the large uncertainties surrounding projections of coupled natural‐human systems. These uncertainties often arise from choices experts have to make, for example, about how to formulate scientific models of future water levels. Diff...

The increasingly urgent need to develop knowledge and practices to manage flood risks drives innovative information design. However, experts often disagree about design practices. As a result, flood-risk estimates can diverge, leading to different conclusions for decision-making. Using examples of household-scale fluvial (riverine) flood-risk infor...

Riverine floods pose a considerable risk to many communities. Improving flood hazard projections has the potential to inform the design and implementation of flood risk management strategies. Current flood hazard projections are uncertain, especially due to uncertain model parameters. Calibration methods use observations to quantify model parameter...

Managing climate risks often requires making hard decisions. While decision analysis can help, many analyses narrowly view what matters to people concerning decision outcomes. For instance, government policies may require projects to pass a cost-benefit analysis in which only easily monetized objectives are considered—incorporating a richer view of...

The role of individual and collective human action is increasingly recognized as a prominent and arguably paramount determinant in shaping the behavior, trajectory, and vulnerability of multisector systems. This human influence operates at multiple scales: from short‐term (hourly to daily) to long‐term (annually to centennial) timescales, and from...

We present the comparison of source-partitioned CO2 flux measurements with a high-resolution urban CO2 emissions inventory (Hestia). Tower-based measurements of CO and ¹⁴C are used to partition net CO2 flux measurements into fossil and biogenic components. A flux footprint model is used to quantify spatial variation in flux measurements. We compare...

Urban landscape planners and policymakers aim to find robust/optimal green infrastructure (GI) placement solutions that can perform well over a wide range of plausible futures and meet different objectives. While some studies on the spatial allocation of GI embraced multi-objective optimization to inform multi-functional GI placement decisions, man...

Climate risks are growing. Research is increasingly important to inform the design of strategies to manage these risks. But the relevance of many research studies to real- world decisions can be limited due to misalignment of values. There is no value-neutral strategy assessment, and the values assumed (often implicitly) within research need not al...

The field of MultiSector Dynamics (MSD) explores the dynamics and co‐evolutionary pathways of human and Earth systems with a focus on critical goods, services, and amenities delivered to people through interdependent sectors. This commentary lays out core definitions and concepts, identifies MSD science questions in the context of the current state...

Riverine floods pose a considerable risk to many communities. Improving the projections of flood hazard has the potential to inform the design and implementation of flood risk management strategies. Current flood hazard projections are uncertain. One uncertainty that is often overlooked is uncertainty about model parameters. Calibration methods use...

This free open access online book is meant to provide an open science “living” resource on uncertainty characterization methods for the MultiSector Dynamics (MSD) community and other technical communities confronting sustainability, climate, and energy transition challenges. This guidance text is meant to serve as an evolving resource that helps th...

Probabilistic projections of baseline (with no additional mitigation policies) future carbon emissions are important for sound climate risk assessments. Deep uncertainty surrounds many drivers of projected emissions. Here, we use a simple integrated assessment model, calibrated to century-scale data and expert assessments of baseline emissions, glo...

Convergence research is driven by specific and compelling problems and requires deep integration across disciplines. The potential of convergence research is widely recognized, but questions remain about how to design, facilitate, and assess such research. Here we analyze a seven-year, twelve-million-dollar convergence project on sustainable climat...

This report outlines a vision for MultiSector Dynamics (MSD) as an emerging transdisciplinary field that seeks to advance our understanding of how human-Earth systems interactions shape the resources, goods, and services on which society depends. The core objective of this MSD Vision Report is to clarify core definitions, share research questions,...

Floods drive dynamic and deeply uncertain risks for people and infrastructures. Uncertainty characterization is a crucial step in improving the predictive understanding of multi-sector dynamics and the design of risk-management strategies. Current approaches to estimate flood hazards often sample only a relatively small subset of the known unknowns...

Immersive virtual reality (iVR) can enable users to experience phenomena at real-world scale. This attribute may be useful for communicating the risks of many natural hazards. Storm-surge is a flood hazard whose risk has proven challenging to communicate through traditional means, such as maps. When it comes to storm-surge flooding, iVR experiences...

This white paper provides an overview of priorities related to community resilience to flooding that emerged during a 27 September 2019 meeting with local, regional and state representatives in Selinsgrove, Pennsylvania. The document compiles workshop details, participants and a summary of discussions and outcomes. It does not, however, attempt to...

There is an increasingly urgent need to develop knowledge and practices to manage climate risks. For example, flood-risk information can inform household decisions such as purchasing a home or flood insurance. However, flood-risk estimates are deeply uncertain, meaning that they are subject to sizeable disagreement. Available flood-risk estimates p...

Current approaches to design flood-sensitive infrastructure typically assume a stationary rainfall distribution and neglect many uncertainties. These assumptions are inconsistent with observations that suggest intensifying extreme precipitation events and the uncertainties surrounding projections of the coupled natural-human systems. Here we demons...

Crop yields are sensitive to extreme weather events. Improving the understanding of the mechanisms and the drivers of the projection uncertainties can help to improve decisions. Previous studies have provided important insights, but often sample only a small subset of potentially important uncertainties. Here we expand on a previous statistical mod...

Decisions on how to manage future flood risks are frequently informed by both sophisticated and computationally expensive models. This complexity often limits the representation of uncertainties and the consideration of strategies. Here we use an intermediate complexity model framework that enables us to analyze a richer set of strategies, a wider...

Statistical flood frequency analysis coupled with hydrograph scaling is commonly used to generate design floods to assess dam safety assessment. The safety assessments can be highly sensitive to the choice of the statistical flood frequency model. Standard dam safety assessments are typically based on a single distribution model of flood frequency,...

Efforts to understand and quantify how a changing climate can impact agriculture often rely on bias-corrected and downscaled climate information, making it important to quantify potential biases of this approach. Here, we use a multi-model ensemble of statistically bias-corrected and downscaled climate models, as well as the corresponding parent mo...

Atmospheric CO2 inversion typically relies on the specification of prior flux and atmospheric model transport errors, which have large uncertainties. Here, we used ACT‐America airborne observations to compare CO2 model observation mismatch in the eastern U.S. and during four climatological seasons for the mesoscale WRF(‐Chem) and global scale Carbo...

Flood-related risks to people and property are expected to increase in the future due to environmental and demographic changes. It is important to quantify and effectively communicate flood hazards and exposure to inform the design and implementation of flood risk management strategies. Here we develop an integrated modeling framework to assess pro...

Quantification of regional terrestrial carbon dioxide (CO2) fluxes is critical to our understanding of the carbon cycle. We evaluate inverse estimates of net ecosystem exchange (NEE) of CO2 fluxes in temperate North America, and their sensitivity to the observational data used to drive the inversions. Specifically, we consider the state‐of‐the‐scie...

The United Nations Framework Convention on Climate Change agreed to “strengthen the global response to the threat of climate change, in the context of sustainable development and efforts to eradicate poverty” (UNFCCC 2015). Designing a global mitigation strategy to support this goal poses formidable challenges. For one, there are trade-offs between...

Accelerating global climate change drives new climate risks. People around the world are researching, designing, and implementing strategies to manage these risks. Identifying and implementing sound climate risk management strategies poses nontrivial challenges including ( a) linking the required disciplines, ( b) identifying relevant values and ob...

The long-term temperature response to a given change in CO2 forcing, or Earth-system sensitivity (ESS), is a key parameter quantifying our understanding about the relationship between changes in Earth’s radiative forcing and the resulting long-term Earth-system response. Current ESS estimates are subject to sizable uncertainties. Long-term carbon c...

The Atmospheric Carbon and Transport (ACT) – America NASA Earth Venture Suborbital Mission set out to improve regional atmospheric greenhouse gas (GHG) inversions by exploring the intersection of the strong GHG fluxes and vigorous atmospheric transport that occurs within the midlatitudes. Two research aircraft instrumented with remote and in situ s...

Understanding flood probabilities is essential to making sound decisions about flood-risk management. Many people rely on flood probability maps to inform decisions about purchasing flood insurance, buying or selling real-estate, flood-proofing a house, or managing floodplain development. Current flood probability maps typically use flood zones (fo...

Current approaches to design stormwater infrastructure typically assume a stationary rainfall distribution and neglect many uncertainties. These assumptions are inconsistent with observations that suggest intensifying extreme precipitation events and the uncertainties surrounding projections of the coupled natural-human systems. Here we show that a...

Agent-based models (ABMs) are widely used to analyze coupled natural and human systems. Descriptive models require careful calibration with observed data. However, ABMs are often not calibrated in a formal sense. Here we examine the impact of data record size and aggregation on the calibration of an ABM for housing abandonment in the presence of fl...

Efforts to understand and quantify how a changing climate can impact agriculture often rely on bias-corrected and downscaled climate information, making it important to quantify potential biases of this approach. Previous studies typically focus their uncertainty analyses on climatic variables and are silent on how these uncertainties propagate int...

Understanding flood probabilities is essential to making sound decisions about flood-risk management. Many people rely on flood probability maps to inform decisions about purchasing flood insurance, buying or selling real-estate, flood-proofing a house, or managing floodplain development. Current flood probability maps typically use flood zones (fo...

The decision on how to manage a forest under climate change is subject to deep and dynamic uncertainties. The classic approach to analyze this decision adopts a predefined strategy, tests its robustness to uncertainties, but neglects their dynamic nature (i.e., that decision-makers can learn and adjust the strategy). Accounting for learning through...

Homeowners around the world elevate houses to manage flood risks. Deciding how high to elevate a house poses a nontrivial decision problem. The U.S. Federal Emergency Management Agency (FEMA) recommends elevating existing houses to the Base Flood Elevation (the elevation of the 100-year flood) plus a freeboard. This recommendation neglects many unc...

Decisions on how to manage future flood risks are frequently informed by both sophisticated and computationally expensive models. This complexity often limits the representation of uncertainties and the consideration of strategies. Here, we use an intermediate complexity model framework that enables us to analyze a rich set of strategies, objective...

Flood-related risks to people and property are expected to increase in the future due to environmental and demographic changes. It is important to quantify and effectively communicate flood hazards and exposure to inform the design and implementation of flood risk management strategies. Here we develop an integrated modeling framework to assess pro...

Forests are prone to direct and indirect effects of climate change. Adaptation strategies have been developed to increase the resistance of forests towards climate change and to reduce the associated risks. However, the direction and degree of climate change remain deeply uncertain. This deep uncertainty is often neglected in forest management. Thu...

For computer simulation models to usefully inform climate risk management, uncertainties in model projections must be explored and characterized. Because doing so requires running the model many times over, and because computing resources are finite, uncertainty assessment is more feasible using models that demand less computer processor time. Such...