Conference presentation
Uncertainties in impact studies of future climate change on natural and agricultural ecosystems by using modeled climate data with bias-correction
ESA Annual Convention, 98
2013
Abstract
Bias-correction (BC) of modeled climate data as a post-process is widely used for climate change impacts (CCI) studies at global and regional levels. However, bias-correction could cause uncertainties in estimating changes in hydrological and biogeochemical processes in terrestrial ecosystems over future climate conditions due to the impaired spatial-temporal covariance of climate variations (such as temperature and precipitation) and physical conservation principles from BC process. Here we quantifies the differences of changes in simulated water variables (ET, runoff, snowpack water equivalent (SWE), and water demand for irrigation), crop yield, VOC and NO emissions, and dissolved inorganic nitrogen (DIN) export over the Pacific Northwest and gross primary production (GPP) over a watershed scale (HJ-Andrews). The model climate data were from WRF model runs with ECHAM-5-A1B scenario as boundary condition and a bunch of component models from a regional earth system model (BioEarth) were run as either offline or partially coupled approaches. They include a macro-scale hydrological model (VIC), a coupled agricultural and hydrological model (VIC-CropSyst), an ecohydrological model (RHESSys), a gases and aerosols emission model (MEGAN), and nutrient leaching and export model (NEWS). Series simulation experiments were conducted by using BC climate (on temperature and precipitation), and Non-BC climate.
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Details
- Title
- Uncertainties in impact studies of future climate change on natural and agricultural ecosystems by using modeled climate data with bias-correction
- Creators
- Mingliang LiuJennifer C AdamJennie StephensKirti RajagopalanSerena H ChungXiaoyan JiangTsengel NerguiJohn A HarrisonAlex GuentherChristina L TagueJulian Reyes
- Conference
- ESA Annual Convention, 98
- Academic Unit
- Environment, School of the (CAS)
- Identifiers
- 99900669311901842
- Language
- English
- Resource Type
- Conference presentation