Joint Global Change Research Institute

About: Joint Global Change Research Institute is a facility organization based out in Riverdale Park, Maryland, United States. It is known for research contribution in the topics: Greenhouse gas & Climate change. The organization has 197 authors who have published 934 publications receiving 62390 citations.

A Global Hydrologic Framework to Accelerate Scientific Discovery

Abstract: With the ability to simulate historical and future global water availability on a monthly time step at a spatial resolution of 0.5 geographic degree, the Python package Xanthos version 1 provided a solid foundation for continuing advancements in global water dynamics science. The goal of Xanthos version 2 was to build upon previous investments by creating a Python framework where core components of the model (potential evapotranspiration (PET), runoff generation, and river routing) could be interchanged or extended without having to start from scratch. Xanthos 2 utilizes a component-style architecture which enables researchers to quickly incorporate and test cutting-edge research in a stable modeling environment prebuilt with diagnostics. Major advancements for Xanthos 2 were also achieved by the creation of a robust default configuration with a calibration module, hydropower modules, and new PET modules, which are now available to the scientific community. Funding statement: This research was supported by the U.S. Department of Energy, Office of Science, as part of research in Multi-Sector Dynamics, Earth and Environmental System Modeling Program. The Pacific Northwest National Laboratory is operated for DOE by Battelle Memorial Institute under contract DE-AC05-76RL01830. The views and opinions expressed in this paper are those of the authors alone.

What are the effects of Agro-Ecological Zones and land use region boundaries on land resource projection using the Global Change Assessment Model?

Abstract: Understanding potential impacts of climate change is complicated by spatially mismatched land representations between gridded datasets and models, and land use models with larger regions defined by geopolitical and/or biophysical criteria. Here we quantify the sensitivity of Global Change Assessment Model (GCAM) outputs to the delineation of Agro-Ecological Zones (AEZs), which are normally based on historical (1961-1990) climate. We reconstruct GCAM's land regions using projected (2071-2100) climate, and find large differences in estimated future land use that correspond with differences in agricultural commodity prices and production volumes. Importantly, historically delineated AEZs experience spatially heterogeneous climate impacts over time, and do not necessarily provide more homogenous initial land productivity than projected AEZs. We conclude that non-climatic criteria for land use region delineation are likely preferable for modeling land use change in the context of climate change, and that uncertainty associated with land delineation needs to be quantified. Land resource inputs and projections are sensitive to land use region boundaries.Developed a system to generate land data for given Agro-Ecological Zones (AEZs).AEZs based on projected climate differ considerably from historical AEZs.Climate within historical AEZs becomes spatially heterogeneous with climate change.Non-climatic land use region boundaries may reduce model error, compared to AEZs.

Incorporating stakeholder decision support needs into an integrated regional Earth system model

Abstract: A new modeling effort exploring the opportunities, constraints, and interactions between mitigation and adaptation at regional scale is utilizing stakeholder engagement in an innovative approach to guide model development and demonstration, including uncertainty characterization, to effectively inform regional decision making. This project, the integrated Regional Earth System Model (iRESM), employs structured stakeholder interactions and literature reviews to identify the most relevant adaptation and mitigation alternatives and decision criteria for each regional application of the framework. The information is used to identify important model capabilities and to provide a focus for numerical experiments. This paper presents the stakeholder research results from the first iRESM pilot region. The pilot region includes the Great Lakes Basin in the Midwest portion of the United States as well as other contiguous states. This geographic area (14 states in total) permits cohesive modeling of hydrologic systems while also providing strong gradients in climate, demography, land cover/land use, and energy supply and demand. The results from the stakeholder research indicate that, for this region, iRESM should prioritize addressing adaptation alternatives in the water resources, urban infrastructure, and agriculture sectors, including water conservation, expanded water quality monitoring, altered reservoir releases, lowered water intakes, urban infrastructure upgrades, increased electric power reserves in urban areas, and land use management/crop selection changes. For mitigation in this region, the stakeholder research implies that iRESM should focus on policies affecting the penetration of renewable energy technologies, and the costs and effectiveness of energy efficiency, bioenergy production, wind energy, and carbon capture and sequestration.

Spatially and Temporally Explicit Life Cycle Environmental Impacts of Soybean Production in the U.S. Midwest

Abstract: Understanding spatially and temporally explicit life cycle environmental impacts is critical for designing sustainable supply chains for biofuel and animal sectors. However, annual life cycle envir...

A hydrological emulator for global applications - HE v1.0.0

Abstract: . While global hydrological models (GHMs) are very useful in exploring water resources and interactions between the Earth and human systems, their use often requires numerous model inputs, complex model calibration, and high computation costs. To overcome these challenges, we construct an efficient open-source and ready-to-use hydrological emulator (HE) that can mimic complex GHMs at a range of spatial scales (e.g., basin, region, globe). More specifically, we construct both a lumped and a distributed scheme of the HE based on the monthly abcd model to explore the tradeoff between computational cost and model fidelity. Model predictability and computational efficiency are evaluated in simulating global runoff from 1971 to 2010 with both the lumped and distributed schemes. The results are compared against the runoff product from the widely used Variable Infiltration Capacity (VIC) model. Our evaluation indicates that the lumped and distributed schemes present comparable results regarding annual total quantity, spatial pattern, and temporal variation of the major water fluxes (e.g., total runoff, evapotranspiration) across the global 235 basins (e.g., correlation coefficient r between the annual total runoff from either of these two schemes and the VIC is > 0.96), except for several cold (e.g., Arctic, interior Tibet), dry (e.g., North Africa) and mountainous (e.g., Argentina) regions. Compared against the monthly total runoff product from the VIC (aggregated from daily runoff), the global mean Kling–Gupta efficiencies are 0.75 and 0.79 for the lumped and distributed schemes, respectively, with the distributed scheme better capturing spatial heterogeneity. Notably, the computation efficiency of the lumped scheme is 2 orders of magnitude higher than the distributed one and 7 orders more efficient than the VIC model. A case study of uncertainty analysis for the world's 16 basins with top annual streamflow is conducted using 100 000 model simulations, and it demonstrates the lumped scheme's extraordinary advantage in computational efficiency. Our results suggest that the revised lumped abcd model can serve as an efficient and reasonable HE for complex GHMs and is suitable for broad practical use, and the distributed scheme is also an efficient alternative if spatial heterogeneity is of more interest.