globalchange  > 影响、适应和脆弱性
项目编号: 1528298
项目名称:
INSPIRE: A CUAHSI-NCAR Collaboration to Improve Hydrologic Process Representation in Weather, Climate and Earth System Models
作者: Ying Fan Reinfelder
承担单位: Rutgers University New Brunswick
批准年: 2014
开始日期: 2015-08-01
结束日期: 2018-07-31
资助金额: USD999775
资助来源: US-NSF
项目类别: Standard Grant
国家: US
语种: 英语
特色学科分类: Geosciences - Earth Sciences
英文关键词: project ; water cycle ; large-scale model ; simulation ; modeler ; large-scale ; model simulation ; future modeling ; climate variability ; model capability ; earth sciences division ; climate scale ; comprehensive model evaluation framework ; earth system model ; model evaluation task ; flux ; new model capability ; land model development ; warming climate ; cross-community collaboration ; predictive model ; ecosystem response ; model test ; earth system context ; document model advance ; large model grid ; community land model ; global-scale model developer ; model deficiency ; new model ; coastal ecosystem dynamics ; model performance
英文摘要: This INSPIRE project is jointly funded by the (a) Office of Integrative Activities, (b) Hydrologic Sciences Program in the Earth Sciences Division and the (c) Physical and Dynamical Meteorology and (d) Climate and Large Scale Dynamics Programs in Atmospheric and Geospace Sciences Division of the Geosciences Directorate. The project will advance our knowledge of the hydrologic cycle (i.e., how water is stored in and moves across the land, in the soils and plants, in rivers, lakes and wetlands, and in underground aquifers) on a continental scale. Although hydrologists have quantified local watersheds for a century, this process data/knowledge has not been fully integrated into continental scale water cycle models and Earth system models. This project will bring together the hydrologists (who quantify hydrologic processes and theories), and modelers (who develop predictive models for large-scale water cycle research), to assess the most critical physics, and how to best describe them mathematically in large-scale models. The improved model capability will allow us to explore questions such as: Will there be an adequate quantity and distribution of freshwater to meet the growing demands of food, energy and water security? How will a changing world (land use change, climate variability, sea-level, population change) affect, and be affected by, the volumes and flows of water between the atmosphere and soils, streams, lakes, wetlands, and aquifers? Knowing how much water is available where and when, and how that will change in the future, constitutes one of society's most basic scientific quests.

This project will (1) create a Hydrology Process Team (HPT) bringing together field hydrologists, theoreticians, process-scale (e.g., hillslope, channel reach) modelers, and global-scale model developers. The team will integrate across communities, disciplines, and scales to advance water cycle science of common interest. The project will convene representatives of the hydrologic and the atmospheric sciences communities to develop state-of-science process syntheses and a framework for scaling from columns to large model grids and meshes, with recommendations for best ways to represent them in large-scale models. (2) These concepts will be implemented into the Community Land Model (CLM) to compare these new CLM water cycle capabilities with observations from the networks of research sites across the country supported by e.g. USDA, USGS, USFS, NOAA, NASA and NSF. The comparisons will especially focus on below-ground water stores and fluxes neglected in earlier model tests. The new process implementation and model evaluation tasks will be guided by the synthesis team of scientists and implemented by a postdoctoral research associate and a software engineer. (3) The project will also conduct a series of model simulations over North America to evaluate new model capabilities derived from this project, to address the water cycle and its controls at various resolutions and to define knowledge gaps for future improvement. Key evaluation criteria will include: how does the new model represent multi-scale stores and fluxes on the continent, and can it better predict droughts and floods at large river basin and national levels? How do the new formulations for water stores and fluxes on land improve the simulation of ecosystem response to environmental stress and the associated carbon fluxes? How do they improve the simulation of latent and sensible heat fluxes and hence advance understanding of land-atmosphere interactions at weather and climate scales? How do they improve the simulations of snowpack and permafrost dynamics and advance our capabilities to predict their responses to a warming climate? How do they improve the simulations of riverine fluxes from the continents to the ocean basins influencing thermohaline circulation and coastal ecosystem dynamics? A comprehensive model evaluation framework will be developed to gage model performance in the Earth System context and document model advances, the latter slated to be included in the release of CLM version 6 for participation of the next IPCC projections. (4) A final synthesis meeting will analyze model deficiencies and causes, and make recommendations for future modeling and observation priorities. A series of synthesis documents will be produced which will serve as historic benchmarks of land model development. This project is expected to achieve significant breakthroughs in large-scale water cycle research and capacity building, and will establish a mechanism for cross-community collaboration to advance our knowledge of the water cycle.
资源类型: 项目
标识符: http://119.78.100.158/handle/2HF3EXSE/93852
Appears in Collections:影响、适应和脆弱性
气候减缓与适应

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Recommended Citation:
Ying Fan Reinfelder. INSPIRE: A CUAHSI-NCAR Collaboration to Improve Hydrologic Process Representation in Weather, Climate and Earth System Models. 2014-01-01.
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