The skill and accuracy of atmospheric forecasts from deterministic models have increased so as to improve decisions protecting life and property. And it is now possible to quantify not only the most likely forecast, but also the uncertainty using ensembles of models. This has led to an unprecedented increase in data production and information content from higher resolution, multi-model output and secondary calculations. One difficulty is to obtain the needed subset of data required to estimate the probability of events, and report the information. The calibration required to reliably estimate the probability of events, and honing of threshold adjustments to reduce false alarms for decision makers is also needed. To meet the future needs of the ever-broadening user community and address the strategic climate-water-weather issues on a national and international basis, the weather service implemented the NOAA Operational Model Archive and Distribution System (NOMADS). NOMADS is designed to provide real-time and retrospective format independent access to climate, ocean and weather model data and to deliver high availability content services as part of NOAA's official real time data dissemination at its Web Operations Center (WOC) server. The most important aspect of the servers ability is to aggregate the matrix of model output offering access to probability and calibrating information for real time decision making. The aggregation content server reports over ensemble component and forecast time in addition to the other data dimensions of vertical layer and position for each variable. The unpacking and reading of many binary packed files is accomplished to calculate weather element event probabilities and the thresholds for more accurate decision support. Mobile platforms are emerging as a powerful way to extend information and communication technology opportunities and key services to millions of people. Our goal is to reduce uncertainty for variables of interest, e.g, agricultural importance. The weather service operational Global Forecast System (GFS) model ensemble (GENS) or short range ensemble forecasts (SREF) can make skillful probability forecasts to alert users if and when their selected weather events will occur. A description of how this framework operates and how it can be implemented using existing NOMADS content services and applications is described.