A5070403772- Climate Change Policy and Economics
- Distributed and Parallel Computing Systems
- Energy, Environment, and Transportation Policies
- Atmospheric and Environmental Gas Dynamics
- Climate variability and models
- Soil and Water Nutrient Dynamics
- Tropical and Extratropical Cyclones Research
- Regional Development and Policy
- Model-Driven Software Engineering Techniques
- Climate change and permafrost
- Atmospheric Ozone and Climate
- Geophysics and Gravity Measurements
- Arctic and Russian Policy Studies
- Advanced Software Engineering Methodologies
- Software Engineering Techniques and Practices
- Ocean Acidification Effects and Responses
- Fire effects on ecosystems
- Water Quality and Pollution Assessment
- Oceanographic and Atmospheric Processes
- Hydrology and Watershed Management Studies
- Underground infrastructure and sustainability
- Scientific Computing and Data Management
- Cryospheric studies and observations
- Infrastructure Resilience and Vulnerability Analysis
- Marine and coastal ecosystems
University of California, Berkeley
2021-2024
University of Washington
2022
Princeton University
2022
Abstract The social cost of carbon dioxide (SC-CO 2 ) measures the monetized value damages to society caused by an incremental metric tonne CO emissions and is a key informing climate policy. Used governments other decision-makers in benefit–cost analysis for over decade, SC-CO estimates draw on science, economics, demography disciplines. However, 2017 report US National Academies Sciences, Engineering, Medicine 1 (NASEM) highlighted that current no longer reflect latest research. provided...
Cyanobacterial harmful algal blooms (CyanoHABs) have serious adverse effects on human and environmental health. Herein, we developed a modeling framework that predicts the effect of climate change cyanobacteria concentrations in large reservoirs contiguous U.S. The framework, which uses projections from five global circulation models, two greenhouse gas emission scenarios, cyanobacterial growth is unique coupling with hydrologic/water quality network model United States. Thus, it generates...
Significance Climate change in Alaska is causing widespread environmental that damaging critical infrastructure. As climate continues, infrastructure may become more vulnerable to damage, increasing risks residents and resulting large economic impacts. We quantified the potential damages public from climate-driven changes flooding, precipitation, near-surface permafrost thaw, freeze–thaw cycles using high low future scenarios. Additionally, we estimated coastal erosion losses for villages...
The social cost of carbon (SCC) is a crucial metric for informing climate policy, most notably guiding regulations issued by the US government. Characterization uncertainty and transparency assumptions are critical supporting such an influential metric. Challenges inherent to SCC estimation push boundaries typical analytical techniques require augmented approaches assess uncertainty, raising important considerations discounting. This paper addresses challenges projecting very long-term...
Climate change and freshwater quality are well-linked. Changes in climate result changes streamflow rising water temperatures, which impact biochemical reaction rates increase stratification lakes reservoirs. Using two modeling systems (the Hydrologic Water Quality System; HAWQS US Basins), five models, greenhouse gas (GHG) mitigation policies, we assess future the continental U.S. to 2100 considering four parameters: temperature, dissolved oxygen, total nitrogen, phosphorus. Once these...
Climate change is altering wildfire activity across Alaska, with increased area burned projected for the future. Changes in are expected to affect need management and suppression resources; however, potential economic implications of these needs have not been evaluated. We associated response costs 2100 under relatively high low climate forcing scenarios (representative concentration pathways (RCP) 8.5 4.5) using Alaskan Frame-based Ecosystem Code (ALFRESCO) model. calculated unique each...
New government guidelines could transform benefit-cost analysis of US climate policy
Sea-level rise and associated flood hazards pose severe risks to the millions of people globally living in coastal zones. Models representing adaptation impacts are important tools inform design strategies manage these risks. Representing often deep uncertainties influencing poses nontrivial challenges. A common uncertainty characterization approach is use a few benchmark cases represent range relative probabilities set possible outcomes. This has been done studies, for example, by using...
Uncertainty in future carbon dioxide (CO2) emissions, and the geophysical response to drives variability sea-level rise (SLR). However, relative contribution of emissions dynamics (e.g. Antarctic Ice Sheet (AIS) tipping points) projections is poorly understood. Here, we disentangle their importance by propagating several ensembles CO2 trajectories, representing relevant deep uncertainties, through a calibrated cycle-climate-sea-level model chain. The trajectory, particularly timing when are...
Wong et al., (2022). MimiBRICK.jl: A Julia package for the BRICK model sea-level change in Mimi integrated modeling framework. Journal of Open Source Software, 7(76), 4556, https://doi.org/10.21105/joss.04556
Programming tools are increasingly integral to research and analysis in myriad domains, including specialized areas with no formal relation computer science. Embedded domain-specific languages (eDSLs) have the potential serve these programmers while placing relatively light implementation burdens on language designers. However, barriers eDSL use reduce their practical value adoption. In this paper, we aim deepen our understanding of how eDSLs identify user needs inform future designs. We...
Sea-level rise and associated flood hazards pose severe risks to the millions of people globally living in coastal zones. Models representing adaptation impacts are important tools inform design strategies manage these risks. Representing often deep uncertainties influencing poses nontrivial challenges. A common uncertainty characterization approach is use a few benchmark cases represent range relative probabilities set possible outcomes. This has been done studies, for example, by using...