Announcing the Stochastic Uncertainty Estimator (SUE)

Looking for a way to start to explore uncertainty in a calculation or a model?  QUEST has launched an on-line tool for uncertainty propagation!  The Stochastic Uncertainty Estimator (SUE) is a program developed by Mark E. Harmon and his colleagues in the early 2000's. With funding from QUEST, Keith Olsen has created a web-based interface for SUE.  The following link allows you to download the software, create and run files for your projects, and download the source code (http://uncertaintyestimator.org/).   

Two QUEST-sponsored uncertainty papers were published on Feb 6 and Feb 7:

Daly, C., M.E. Slater, J.A. Roberti, S.H. Laseter, and L.W. Swift Jr. 2017. High-resolution precipitation mapping in a mountainous watershed: ground truth for evaluating uncertainty in a national precipitation dataset. International Journal of Climatology, DOI: 10.1002/joc.4986

At one time, Coweeta Hydrological Laboratory had over 100 precipitation collectors, which were used to inform interpolation of a reduced monitoring scheme.  These spatially intensive data made it possible to test the predictions of the PRISM national-scale gridded precipitation dataset and quantify sources of uncertainty.

Csavina, J., J.A. Roberti, J.R. Taylor, adn H.W. Loescher. 2017. Traceable measurements and calibration: a primer on uncertainty analysis. Ecosphere, 8(2) e01683, DOI: 10.1002/ecs2.1683

This paper describes the approach used by NEON, the National Ecological Observatory Network, to uncertainty analysis, and includes a glossary of terms.  Bone up on accuracy, precision, and trueness!