Gridded daily surface weather for North America: development and uncertainty analysis of the Daymet dataset

Peter E. Thornton, Oak Ridge National Laboratory, thorntonpe@ornl.gov (Presenter)
Michele M. Thornton, ORNL DAAC, thorntonmm@ornl.gov
Benjamin W. Mayer, Oak Ridge National Laboratory, mayerbw@ornl.gov
Robert B. Cook, Environmental Sciences Division, ORNL, cookrb@ornl.gov
Ranjeet Devarakonda, Oak Ridge National Laboratory, devarakondar@ornl.gov
Yaxing Wei, ORNL, weiy@ornl.gov
Suresh Kumar Santhana Vannan, ORNL, santhanavans@ornl.gov

Since 1998, a high-resolution dataset (1 km grid spacing) of daily surface weather fields, including temperature, precipitation, radiation, and humidity, has been produced and made available for free public access, with coverage over the conterminous United States, and periodic updates for period of record. As part of a current NASA TE project, several obstacles have been overcome allowing generation of this data product (Daymet) over the entire North American continent. As new algorithmic improvements have been completed, expanded capabilities for data access and distribution have also been deployed, operating through the ORNL DAAC. A unique aspect of the Daymet dataset is its integrated treatment of error statistics, based on cross-validation. Cross validation results have always been available upon request, but we are now preparing to distribute complete evaluation statistics through the ORNL DAAC data interface. Various summaries of the North American dataset and associated error statistics are presented here, with attention to the relationship between density of surface observation stations and cross-validation errors.

Presentation Type:  Poster

Session:  Theme 2: Landscapes to coasts: understanding Earth system connections   (Mon 1:30 PM)

Associated Project(s): 

• Thornton, Peter: Surface Weather Data with Uncertainty Quantification for Terrestrial Ecosystem Process Models ...details

Poster Location ID: 74