Location: Location not imported yet.Title: CLIGEN: Addressing deficiencies in the generator and its databases) Author
Submitted to: Meeting Proceedings
Publication Type: Proceedings
Publication Acceptance Date: 7/15/2011
Publication Date: 9/18/2011
Citation: Rust, W.J., Fox, F.A., Wagner, L.E. 2011. CLIGEN: Addressing deficiencies in the generator and its databases. In: Proceedings International Symposium on Erosion and Landscape Evolution (ISELE), 18-21 September 2011, Anchorage, Alaska. ISELE Paper No. 11083. D.C. Flanagan, J.C. Ascough II, and J.L. Nieber (eds.). St. Joseph, MI ASABE. Interpretive Summary:
Technical Abstract: CLIGEN is a stochastic generator that estimates daily temperatures, precipitation and other weather related phenomena. It is an intermediate model used by the Water Erosion Prediction Program (WEPP), the Wind Erosion Prediction System (WEPS), and other models that require daily weather observations. Sub-models of these programs use CLIGEN’s output to calculate plant growth and decomposition, soil surface changes and movement of water through soil layers. Over the years, changes to CLIGEN have been made without being adequately documented. This paper documents those changes and discusses needed changes to CLIGEN. Issues in the existing program include improving the quality of the input meteorological datasets and documenting their source, improving the correlation, both cross and serial, between generated observations, making the observations more accurately reflect seasonal variations, making the generated distributions correspond better to the observed distributions, changing how the random number variate sets are created and tested, moving to a histogram based precipitation model, changing how interpolations are performed to better reflect seasonality and converting from FORTRAN to Java to improve code readability and maintainability. In addition, new features are added to produce break-point precipitation for downstream models in addition to the current intensity, duration and time to peak observations and to parametrically change inputs to facilitate climate change studies. These issues are discussed and the solutions being implemented are described.