May 2017 All future distributions of the StochAtlas will include our publicly available model results in Taylor diagrams whenever a certain threshold of comparisons to observations are reached. We encourage clients to expect no less from any provider of hydroclimatologic forecasting. We welcome competition on a level playing field and encourage all of our competitors, including all VIC and CMIP clients to routinely include the same with forecasts and hindcasts and climate change representations.
Our Stochatlas now features two primary geospatial coverages: the classic treadmarks and the new line of quasi geostrophic global coverages, such as seen here and below. Note that there is no need for an artist to highlight the jet streams. They are illustrated naturally by streamline convergence through this data-centric method.
Our primary focus on a monthly averaged rendition of the time averaged data, along with other perspectives such as our reliance upon a quasi geostrophic three dimensional supporting representation are what make our Stochastic Landscape (SL) features an often vital component of our content.
Here are some unique SL examples (in extreme low resolution) from stochAtlas2016 Q1:
 Koehler, Richard Bruce, 2004, RASTER-BASED ANALYSIS AND VISUALIZATION OF HYDROLOGIC TIME-SERIES, Dissertation. School of Renewable Natural Resources. The University of Arizona
 Michael G. Wallace, 2015, OCEAN OSCILLATION BASED HYDROLOGIC FORECASTING, MW&A Annual HydroClimatology Report for Calendar Year 2014 Michael Wallace and Associates, Albuquerque, NM.