WE PROPOSE THAT THE DESIGN OF AN IDEAL FIELD CAMPAIGN FOR MEASURING SNOW DENSITY AND SWE IS ONE THAT INTEGRATES REMOTE SENSING MULTIPLE MODELS AND FIELD DATA. AN IDEAL FIELD SAMPLING PROTOCOL SHOULD TARGET SITES SPANNING (1) A RANGE OF UNCERTAINTY IN MODELED DENSITY AND (2) A GRADIENT OF LANDSCAPE SETTINGS LIKE FOREST DENSITY (FIGURE 2). THE FIRST STEP IS TO QUANTIFY UNCERTAINTY IN SNOW MODELS THAT ARISE FROM VARIOUS SOURCES INCLUDING METEOROLOGICAL FORCING [RALEIGH ET AL. 2015 2016] PARAMETERS [REBA ET AL. 2014] AND PROCESS FORMULATIONS [ESSERY ET AL. 2013]. THIS LEADS TO THE GENERATION OF A SINGLE MAP OF DENSITY UNCERTAINTY (FIGURE 2A) THAT CAN GUIDE THE DESIGN OF A MORE TARGETED AND EFFICIENT SAMPLING STRATEGY. WITH THE GOAL OF ADVANCING SNOW MODELS WE WOULD SAMPLE AT LOCATIONS ACROSS THE RANGE OF UNCERTAINTY: FROM NEAR COMPLETE MODEL AGREEMENT (I.E. CV CLOSER TO 0) TO MODERATE AND HIGH UNCERTAINTY ACROSS MODELS. THIS SAMPLING CAN THEN BE STRATIFIED ACROSS A GRADIENT OF LANDSCAPE FEATURES (E.G. FORESTED AREA FIGURE 2C) TO ENHANCE UNDERSTANDING OF PROCESS CONTROLS. THUS A COMBINED CLASSIFICATION ENABLES A SIMULTANEOUS EXAMINATION OF BOTH MODEL UNCERTAINTY AND LANDSCAPE CONTROLS (FIGURE 2B). THIS TYPE OF CLASSIFICATION MAP CAN HELP EVALUATE THE ADEQUACY OF SAMPLING STRATEGIES IN PAST CAMPAIGNS AND CAN INFORM SITE SELECTION FOR FUTURE FIELD CAMPAIGNS (FIGURE 2B INSET). THIS GENERAL APPROACH CAN BE USED IN SNOWEX BOTH WITH AND WITHOUT ASSIMILATION OF REMOTELY SENSED SNOW DEPTH OBSERVATIONS AND OTHER RELEVANT VARIABLES.