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.

Implications of simultaneously mitigating and adapting to climate change: initial experiments using GCAM

Abstract: Most research on future climate change discusses mitigation and impacts/adaptation separately. However, mitigation will have implications for impacts and adaptation. Similarly, impacts and adaptation will affect mitigation. This paper begins to explore these two veins of research simultaneously using an integrated assessment model. We begin by discussing the types of interactions one might expect by impact sector. Then, we develop a numerical experiment in the agriculture sector to illustrate the importance of considering mitigation, impacts, and adaptation at the same time. In our experiment, we find that climate change can reduce crop yields, resulting in an expansion of cropland to feed a growing population and a reduction in bioenergy production. These two effects, in combination, result in an increase in the cost of mitigation.

From Land Use to Land Cover: Restoring the Afforestation Signal in a Coupled Integrated Assessment - Earth System Model and the Implications for CMIP5 RCP Simulations

Abstract: . Climate projections depend on scenarios of fossil fuel emissions and land use change, and the Intergovernmental Panel on Climate Change (IPCC) AR5 parallel process assumes consistent climate scenarios across integrated assessment and earth system models (IAMs and ESMs). The CMIP5 (Coupled Model Intercomparison Project Phase 5) project used a novel "land use harmonization" based on the Global Land use Model (GLM) to provide ESMs with consistent 1500–2100 land use trajectories generated by historical data and four IAMs. A direct coupling of the Global Change Assessment Model (GCAM), GLM, and the Community ESM (CESM) has allowed us to characterize and partially address a major gap in the CMIP5 land coupling design: the lack of a corresponding land cover harmonization. For RCP4.5, CESM global afforestation is only 22% of GCAM's 2005 to 2100 afforestation. Likewise, only 17% of GCAM's 2040 afforestation, and zero pasture loss, were transmitted to CESM within the directly coupled model. This is a problem because GCAM relied on afforestation to achieve RCP4.5 climate stabilization. GLM modifications and sharing forest area between GCAM and GLM within the directly coupled model did not increase CESM afforestation. Modifying the land use translator in addition to GLM, however, enabled CESM to include 66% of GCAM's afforestation in 2040, and 94% of GCAM's pasture loss as grassland and shrubland losses. This additional afforestation increases CESM vegetation carbon gain by 19 PgC and decreases atmospheric CO2 gain by 8 ppmv from 2005 to 2040, which demonstrates that CESM without additional afforestation simulates a different RCP4.5 scenario than prescribed by GCAM. Similar land cover inconsistencies exist in other CMIP5 model results, primarily because land cover information is not shared between models. Further work to harmonize land cover among models will be required to increase fidelity between IAM scenarios and ESM simulations and realize the full potential of scenario-based earth system simulations.

Freeze-Thaw cycle representation alters response of watershed hydrology to future climate change

Abstract: Hydrologic models are widely used for projecting influences of changing climate on water resources. In this study, we compared the original Soil and Water Assessment Tool (SWAT) model and an enhanced version of SWAT model with physically based Freeze-Thaw cycle representation (SWAT-FT) for simulating future annual ET, stream flow, water yield, surface runoff, and subsurface runoff in the Upper Mississippi River Basin (UMRB). SWAT-FT projected fewer frozen days than the original SWAT model due to its better representation of snow cover insulation effects. Both models derived declining trends in annual streamflow and terrestrial water yield in the late 21st century due to increased ET under warmer climate. However, these two models exhibited contrasting mechanisms underlying the streamflow decline. For original SWAT model, the decrease in surface runoff was the major driver, while for SWAT-FT, reduced subsurface runoff was the main cause. In general, the original SWAT model predicted more surface runoff and less subsurface runoff than SWAT-FT. Further geospatial inspection shows large discrepancies between these two models, particularly in the northern colder parts of the UMRB, where the maximum differences in annual surface and subsurface runoff reached 130 mm yr−1 and 140 mm yr−1, respectively. Collectively, the results demonstrate the importance of accounting for Freeze-Thaw cycles for reliable projection of future water resources.