Abstract

Abstract Statistical relationships between topography and the spatial distribution of mean annual precipitation are developed for ten distinct mountainous regions. These relationships are derived through linear bivariate and multivariate analyses, using six topographic variables as predictors of precipitation. These predictors are elevation, slope, orientation, exposure, the product (or interaction) of slope and orientation, and the product of elevation and exposure. The two interactive terms are the best overall bivariate predictors of mean annual precipitation, whereas orientation and exposure are the strongest noninteractive bivariate predictors. The regression equations in many of the climatically similar regions tend to have similar slope coefficients and similar y-intercept values, indicating that local climatic conditions strongly influence the relationship between topography and the spatial distribution of precipitation. In contrast, the regression equations for the tropical and extratropical regi...

Full Text
Paper version not known

Talk to us

Join us for a 30 min session where you can share your feedback and ask us any queries you have

Schedule a call

Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.