** A NOTE ON SPC SREF PLUMES ** DISCLAIMER: This tool is provided as a proof-of-concept demonstration project and should not be considered operational. Data are updated in a timely manner, but the contents are not deemed operational and processing is not supported 24/7. The statistical methods involved in this project remain under development, both conceptually and statistically, and as such contents on this page are provided as a proof-of-concept experiment for the advancement and utilization of SREF diagnostics, and not as an operational forecast tool. In summary, information is intended for evaluation purposes only. The plume diagnostic tool is probably best suited for point forecasting, but it may prove useful for parameter evaluation on the national scale. All available parameters are first bias corrected and then statistically dressed based on errors over the past 30 days in an attempt to produce calibrated (i.e., reliable) SREF forecasts. Thus, evaluation of these probabilities over a long period of time *should* yield statistically reliable results. At this time, only the calibrated 2m temperature forecasts have been verified over the CONUS yielding very reliable statistical forecasts of temperature. ** WEB INSTRUCTIONS ** The web interface allows you to view the calibrated SREF output in three ways: plume diagrams, probability diagrams (or "prob-o-grams"), and combined prob-o-grams (i.e., "comb-o-grams," which are the product of prob-o-grams. For example, if concerned about red flag conditions one could consider the probability rh <= 20% multiplied by the probability wind >= 20 mph). The comb-o-grams are useful for determining the likelihood multiple ingredients may occur at the same time. Point selection is accomplished through one of two ways. Use the map in the lower left to select any CONUS point via the mouse, or choose a station from the drop down station list. Generally, you want to fill in the information from the top frame down. Start by choosing the SREF run (the latest available is the default), the type of diagram (plume, prob-o-gram, comb-o-gram), the field to graph, and a map background. The map background consists of the default blank map, or the corrected median (50%) forecast of the field you selected. Then, select your options in the middle frame and at some point, choose a location (via the mouse or drop down list) in the lower left frame. The available options depend on the type of plot you selected. Plumes: Calibrated probabilistic forecasts with time. Choose the probability(ies) via the checkbox buttons. You may choose multiple values. A good starting starting methodology is to select the 50% (median, or most likely) value, and the 20% and 80% values. This will plot the corrected median forecast (i.e., 50% chance truth will lie above or below this point, and the 20% and 80% curves which together form the 60% confidence interval, meaning more than likely (60% chance) truth will fall inside the two outer curves). If you add the 10% and 90% thresholds, there's an 80% chance truth will land inside these extreme values, and a 10% chance truth will be higher or lower than these extreme values. Prob-o-grams: Enter the values of interest (up to 3) by entering values inside the text boxes. You can plot one to three curves simultaneously. For example, if you're interested in the probability the temperature will exceed 35, 40, or 45 degrees F, then enter the following: min_1 = 35 and max_1 = 150 (or some very high value) min_2 = 40 and max_2 = 150 min_3 = 45 and max_3 = 150 The three curves that are graphed are the exceedance probabilities for 35F, 40F, and 45F. Likewise, if you're interested in the probability the wind is between 10 and 25 mph, select 10 m wind in the top frame and then enter the following. min_1 = 10 and max_1 = 25 min_2 = and max_2 = (blank out these options) min_3 = and max_3 = (blank out these options) Combo-o-grams: Chose the field and enter the probabilistic range for each variable similar to the above description. Then, the product of the fields is also graphed. For example, if you're interested in the probability of accumulating snow then you might choose the following. Field_1 = 2m Temperature min_1 = -100 and max_1 = 34 Field_2 = Skin Temperature min_1 = -100 and max_1 = 33 Field_3 = Precipitation min_1 = .01 and max_1 = 100 Prob-o-grams for each individual field are graphed, and the product of the three prob-o-grams (i.e., the comb-o-gram) is also be graphed. Thus, from the product one can deduce the relative likelihood that all three of the ingredients will occur simultaneously. The product of the probabilities forms the joint probability if the assumption of independence is made. In other words, the product of the probabilities may not be an actual probability if some degree of dependence exists between the predictors. Nonetheless, experience at the SPC has shown that the combined probabilities are quite useful and can still serve as a tool for assessing forecast confidence (or lack thereof).