A5039306343- Climate variability and models
- Climate change impacts on agriculture
- Atmospheric and Environmental Gas Dynamics
- Meteorological Phenomena and Simulations
- Climate Change Policy and Economics
- Agricultural risk and resilience
- Water resources management and optimization
- demographic modeling and climate adaptation
- Water-Energy-Food Nexus Studies
- Crafts, Textile, and Design
- Geophysics and Gravity Measurements
- Distributed and Parallel Computing Systems
- Environmental Impact and Sustainability
- Agricultural Economics and Policy
- Zebrafish Biomedical Research Applications
- Neural dynamics and brain function
- Geological Modeling and Analysis
- Scientific Research and Discoveries
- Scientific Computing and Data Management
- Physiological and biochemical adaptations
- Greenhouse Technology and Climate Control
- Agriculture Sustainability and Environmental Impact
- Hydrology and Watershed Management Studies
- Crop Yield and Soil Fertility
- Climate Change and Environmental Impact
Joint Global Change Research Institute
2017-2024
Pacific Northwest National Laboratory
2017-2024
John Carroll University
2023
United States Global Change Research Program
2023
University Research Co (United States)
2021-2022
University of Maryland, College Park
2022
Government of the United States of America
2020
Johns Hopkins University
2020
University of Pittsburgh
2010-2017
Abstract. This paper describes GCAM v5.1, an open source model that represents the linkages between energy, water, land, climate, and economic systems. is a market equilibrium model, global in scope, operates from 1990 to 2100 5-year time steps. It can be used examine, for example, how changes population, income, or technology cost might alter crop production, energy demand, water withdrawals, one region's demand affect land other regions. including its assumptions, inputs, outputs. We then...
Abstract Future changes in climate and socioeconomic systems will drive both the availability use of water resources, leading to evolutions scarcity. The contributions can be quantified individually understand impacts around world, but also combined explore how coevolution energy-water-land affects not only driver behind scarcity changes, human interact tandem alter Here we investigate relative on under Shared Socioeconomic Pathways-Representative Concentration Pathways framework. While...
Abstract Climate change mitigation will require substantial investments in renewables. In addition, climate affect future renewable supply and hence, power sector investment requirements. We study the implications of impacts on renewables for under deep decarbonization using a global integrated assessment model. focus Latin American Caribbean, an under-studied region but great interest due to its strong role international vulnerability change. find that accounting results significant...
Abstract The terrestrial carbon cycle is a major source of uncertainty in climate projections. Its dominant fluxes, gross primary productivity (GPP), and respiration (in particular soil respiration, R S ), are typically estimated from independent satellite-driven models upscaled situ measurements, respectively. We combine carbon-cycle flux estimates partitioning coefficients to show that historical global GPP irreconcilable. When we estimate based on measurements some assumptions about :GPP...
Abstract. Climate model output emulation has long been attempted to support impact research, mainly fill in gaps the scenario space. Given computational cost of running coupled earth system models (ESMs), which are usually domain supercomputers and require on order days weeks complete a century-long simulation, only handful different scenarios chosen externally force ESM simulations. An effective emulator, able run standard computers times minutes rather than could therefore be used derive...
Abstract. Previous phases of the Coupled Model Intercomparison Project (CMIP) have primarily focused on simulations driven by atmospheric concentrations greenhouse gases (GHGs), for both idealized model experiments and climate projections different emissions scenarios. We argue that although this approach was practical to allow parallel development Earth system detailed socioeconomic futures, carbon cycle uncertainty as represented diverse, process-resolving models (ESMs) is not manifested...
Integrated assessment models (IAMs) hold great potential to assess how future agricultural systems will be shaped by socioeconomic development, technological innovation, and changing climate conditions. By coupling with crop model emulators, IAMs have the resolve important feedback loops identify unintended consequences of development for systems. Here we propose a framework develop robust representation system responses within IAMs, linking downstream applications coordinated evaluation key...
The spinal locomotor central pattern generator (CPG) generates rhythmic activity with alternating flexion and extension phases. This is likely to result from inhibitory interactions between neural populations representing flexor extensor half-centers. However, it unclear whether the flexor-extensor CPG has a quasi-symmetric organization both half-centers critically involved in rhythm generation, features an asymmetric flexor-driven rhythmogenesis, or comprises pair of intrinsically There are...
Abstract. Earth system models (ESMs) are the gold standard for producing future projections of climate change, but running them is difficult and costly, thus researchers generally limited to a small selection scenarios. This paper presents technique detailed emulation model (ESM) temperature output, based on construction deterministic mean response global temperature. The residuals between ESM output fields used construct variability that added produce final product. method produces...
Abstract. Statistical emulation allows combining advantageous features of statistical and process-based crop models for understanding the effects future climate changes on yields. We describe here development emulators nine five crops using output from Global Gridded Model Intercomparison Project (GGCMI) Phase 2. The GGCMI 2 experiment is designed with explicit goal producing a structured training dataset emulator that samples across four dimensions relevant to yields: atmospheric carbon...
Abstract. Previous phases of the Coupled Model Intercomparison Project (CMIP) have primarily focused on simulations driven by atmospheric concentrations greenhouse gases (GHGs), both for idealized model experiments, and climate projections different emissions scenarios. We argue that although this approach was pragmatic to allow parallel development Earth System detailed socioeconomic futures, carbon cycle uncertainty as represented diverse, process-resolving Models (ESMs) is not manifested...
Abstract Land scarcity is increasing over time, driven by complex multisector dynamics. The impacts of land on the economy and environment are multi‐faceted regional, so any action to convert will contain inherent tradeoffs. These complicated deeply uncertain evolution various sectors influencing scarcity. A need therefore exists provide multi‐metric multi‐sector assessments that robust myriad uncertainties. conservation effectively limits supply productive land, while biofuel consumption...
The increasing data requirements of complex models demand robust, reproducible, and transparent systems to track prepare models' inputs. Here we describe version 1.0 the gcamdata R package that processes raw inputs produce hundreds XML files needed by GCAM integrated human-earth model. It features extensive functional unit testing, tracing visualization, enforces metadata, documentation, flexibility in its component data-processing subunits. Although this is specific GCAM, many structural...
Abstract Simple climate models (SCMs) are computationally efficient and capable of emulating global mean output more complex Earth system (ESMs). In doing so, SCMs can play a critical role in research as stand‐ins for the expensive models, especially studies involving low, spatial, and/or temporal resolution, providing sources data. Here we use Hector v2.5.0 to emulate multiforcing historical RCP scenario 31 concentration seven emission‐driven ESMs. When calibrating Hector, sufficient...
Abstract This study seeks to understand how Argentina's energy, water, and land (EWL) systems will co‐evolve under a representative array of human earth system influences, including socioeconomic change, climate policy. To capture sub‐national EWL dynamics in the context global we couple Global Change Analysis Model with suite consistent, gridded sectoral downscaling models explore multiple stakeholder‐engaged scenarios. Across scenarios, Argentina has economic opportunity use its vast...
Drought research customarily uses statistics collected over a reference period to establish threshold for declaring region be in drought, or estimate baseline return periods. Often these involve quantile values from the tails of distribution observations, such as 10th even 1st percentile values. The length is dictated by available record length; often it no longer than 50–100 years. Depending on purpose which drought study intended, unit time used averaging hydrologic meteorologic variables...
Most studies assessing climate impacts on agriculture have focused average changes in market-mediated responses (e.g. land use, production, and consumption). However, the response of global agricultural markets to interannual variability (IAV) biophysical shocks is poorly understood not well represented economic models. Here we show a strong transmission IAVs climate-induced yield markets, which further magnified by endogenous market fluctuations generated due producers' imperfect...
Abstract. Climate model output emulation has long been attempted to support impact research, mainly fill-in gaps in the scenario space. Given computational cost of running coupled Earth System Models (ESMs) an effective emulator would be used create climatic impact-driver information under scenarios that could not run by ESMs. Lately, necessity accounting for internal variability also made availability initial condition ensembles important, increasing further demand. However, at least so...
Abstract. Earth System Models (ESMs) are heavily used to provide inputs impact and multisectoral dynamic models. Therefore, representing the full range of model uncertainty, scenario interannual variability that ensembles ESMs capture, is critical exploration future co-evolution integrated human-Earth system. The pre-eminent source these has been Coupled Model Intercomparison Project (CMIP). With more modeling centers participating in each new CMIP phase, size ESM archive rapidly increasing,...
The economic welfare effects of climate change on global agriculture will be mediated by several complex biophysical and processes. For a given emissions scenario, these include: (1) the response system to anthropogenic forcing, (2) crop yields carbon dioxide changes, baseline improvements in yields, (3) agricultural markets yield (4) implications such market responses. In this paper, we use information about first two processes from available climate-crop model comparison studies analyze...
Agricultural crop yields are susceptible to changes in future temperature, precipitation, and other Earth system factors. Future these physical attributes their effects on agricultural highly uncertain. United States producers will be affected by such whether they occur domestically or internationally through international commodity markets. Here we present a replication study of previous investigations (with different models) showing that potential direct domestic climate the U.S. have...
Abstract. Hindcasting experiments (conducting a model forecast for time period in which observational data are available) being undertaken increasingly often by the integrated assessment (IAM) community, across many scales of models. When they undertaken, results evaluated using global aggregates or otherwise highly aggregated skill scores that mask deficiencies. We select set deviation-based measures can be applied on different spatial (regional versus global) to make evaluating large...
Earth System Models (ESMs) are excellent tools for quantifying many aspects of future climate dynamics but too computationally expensive to produce large collections scenarios downstream users ESM data. In particular, researchers focused on the impacts change require runs rigorously study both human and natural systems low-frequency high-importance events, such as multi-year droughts. Climate model emulators provide an effective mechanism filling this gap, reproducing ESMs rapidly with lower...
A primary advantage to using reduced complexity climate models (RCMs) has been their ability quickly conduct probabilistic projections, a key component of uncertainty quantification in many impact studies and multisector systems. Providing frameworks for such analyses target several RCMs used the future co-evolution human Earth In this paper, we present Matilda, an open-science R software package that facilitates projection analysis, implemented here Hector simple model seamless easily...
Abstract Deep human‐Earth system uncertainties and strong multi‐sector dynamics make it difficult to anticipate which conditions are most likely lead higher or lower adoption of renewable energy, models project a broad range future solar wind energy shares across scenarios. To elucidate these dynamics, we explore large data set scenarios simulated from the Global Change Analysis Model (GCAM), use scenario discovery identify significant factors affecting by mid‐century. We generated over...