Radial basis function (RBF) methods are advantageous for a wide-range of applications from analyzing/synthesizing "scattered" data (scalar and vector valued quantities) to numerically solving partial differential equations on geometrically difficult domains. Over the past decade these methods have advanced considerably from being shown to work on small toy problems, to being shown to compete favorably with the best current numerical approaches for some large-scale applications. A central driver behind these advances is the development of ``local’’, highly scalable, RBF techniques, such as RBF generated finite differences, RBF partition-of-unity methods, localized bases, and multilevel methods. This workshop introduces some of these new RBF methodologies and their application/implementation to certain problems arising in the geophysical and biological sciences. A particular focus will be on applications in spherical geometries, including geophysical fluid dynamics, pattern formation, and geometric modeling of biological objects. This will be a hands-on workshop with participants actively learning the theory while working on problems and implementing their own codes.