Land Information Systems
LIS can simulate the global land surface at various spatial resolutions, up to 1 kilometer. These visualizations of Leaf Area Index (LAI) show more and more details being revealed as the resolution increases from 1 degree (~100 kilometers) to 1 kilometer.
Land Data Assimilation Systems are a key resource for the global assessment of terrestrial water and energy conditions and fluxes. They are being used extensively by the research community for studies ranging from climate and weather forecast initialization to the improvement of hydrologic decision support systems. Land Data Assimilation Systems ingest satellite- and ground-based observational data products, using advanced land surface modeling and data assimilation techniques, in order to generate optimal fields of land surface states and fluxes. Software for implementing Land Data Assimilation Systems has been streamlined and parallelized in the Land Information System (LIS). LIS drives multiple, offline (not coupled to the atmosphere) land surface models, integrates a huge quantity of observation based data, executes on a global domain at high spatial resolutions (2.5° to 1 km), and is capable of producing results in near-real time. The LIS infrastructure unifies and extends the capabilities of Land Data Assimilation Systems in a common software framework capable of ensemble land surface modeling on points, regions or the globe at spatial resolutions from 2x2.5° down to 1km and finer. The 1km and finer resolution capability of LIS allows it to take advantage of the latest satellite observations, such as MODIS leaf area index and surface temperature, at their full resolution. The hallmark of LIS is its object-oriented software engineering design and integrated high performance computing and communications technologies that enable high-resolution ensemble land surface modeling. LIS has also adopted other Earth system modeling standards and conventions, such as the Earth System Modeling Framework and Assistance for Land Modeling Activities.
Associate professor Paul Houser of the Climate Dynamics Department is studying further advancements and applications of LIS's high-resolution modeling capabilities, in collaboration with partners at NASA and NOAA. Current work focuses on improving ensemble data assimilation methods and enabling operational prediction to address real-world applications in water management, agricultural production, etc.
Contact:
Paul R. Houser
Climate Dynamics
College of Science
George Mason University
4041 Powder Mill Road, Suite 302
Calverton, MD 20705-3106 USA
email: phouser (at gmu.edu)