Bayesian Integration of multiscale environmental data

Software · Mon Aug 22 00:00:00 EDT 2016

OSTI ID:1314948

CHEN, JINSONG; WAINWRIGHT, HARUKO

The software is designed for efficiently integrating large-size of multi-scale environmental data using the Bayesian framework. Suppose we need to estimate the spatial distribution of variable X with high spatial resolution. The available data include (1) direct measurements Z of the unknowns with high resolution in a subset of the spatial domain (small spatial coverage), (2) measurements C of the unknowns at the median scale, and (3) measurements A of the unknowns at the coarsest scale but with large spatial coverage. The goal is to estimate the unknowns at the fine grids by conditioning to all the available data. We first consider all the unknowns as random variables and estimate conditional probability distribution of those variables by conditioning to the limited high-resolution observations (Z). We then treat the estimated probability distribution as the prior distribution. Within the Bayesian framework, we combine the median and large-scale measurements (C and A) through likelihood functions. Since we assume that all the relevant multivariate distributions are Gaussian, the resulting posterior distribution is a multivariate Gaussian distribution. The developed software provides numerical solutions of the posterior probability distribution. The software can be extended in several different ways to solve more general multi-scale data integration problems.

• Short Name / Acronym: bayesINT; 004901MLTPL00
• Project Type: granted permission to release the source code under a modified BSD license.
• Site Accession Number: 2016-139
• Version: 00
• Programming Language(s): Medium: X; OS: MAC AND WINDOWS
• Research Organization: Lawrence Berkeley National Laboratory (LBNL), Berkeley, CA (United States)
• Sponsoring Organization: USDOE. Japan Atomic Energy Agency, Agreement Number FP00002328
• Contributing Organization: LAWRENCE BERKELEY NATIONAL LABORATORY
• DOE Contract Number: AC02-05CH11231
• OSTI ID: 1314948
• Country of Origin: United States