AN IMPORTANT NOTE TO IIDA AND IIFA USERS ---------------------------------------- IIDA and IIFA users should be aware that icing conditions sometimes change rapidly in time and space. IIDA and IIFA flight level and cross-section plots may not be able to capture rapid changes and/or small-scale differences in icing. They also will not capture all occurrences of icing. Users are advised to look at several of the icing plots to assess the icing situation along their route. Flight route cross-sections show icing within ~60km of a straight line route, and icing conditions may be significantly different just beyond this +/-60km window. Flight level plots show the icing that is expected at that altitude, and icing conditions may be significantly different at altitudes just above and below these heights. The concept behind the Integrated Icing Forecast Algorithm (IIFA) ------------------------------------------------------------------ ***IIFA is an experimental product and undergoing changes and tests on a regular basis. Please consult standard information for making icing related flight decisions.*** IIFA updates essentially every three hours, depending upon data availability from the National Weather Service forecasting computers. Sometimes data will be a little slow in coming, so the 3-hour forecast fields may be valid for now, or even an hour ago. If this is the case, look to the 6, 9, and 12 hour forecasts, which can be found on the big yellow bar at the bottom right hand side of the web page interface (says "IIDA", "3-HR", "6-HR", "9-HR" and "12-HR" in the bar). Click on "6-HR" to go to the page that accesses 6-hour forecast plots... 9-HR for 9-hour forecasts, etc. If you have questions, problems, etc., please email Ben Bernstein (bernstei@rap.ucar.edu) or Frank McDonough (mcdono@rap.ucar.edu), or call us (Ben: 303-497-8424, Frank: 303-497-8414). We'll be glad to help explain things, or figure out what's up if something goes wrong. What is IIFA? ------------- IIFA is a forecast version of IIDA (http:/www.rap.ucar.edu/iida), and is meant to mimic to IIDA technique of combining information from satellite, surface observations and radar. Since these observations are not available for 3-12 hours in the future, IIFA creates surrogates for each input data field, based upon output from the RUC (Rapid Update Cycle) model. Cloud top temperature is estimated by finding the coldest temperature at which relative humidity is 70% or higher for each grid point. While this is a fairly crude approximation at cloud top temperature, this estimate still provides a conservative, reasonable guess at the height of the highest cloud top, as well some clue as to the phase expected within the highest cloud deck. Multiple cloud decks are still treated seperately, as in IIDA (McDonough and Bernstein, 1999). Surface precipitation occurrence is simply extracted from the RUC model's predicted precipitation field. Precipitation type is determined via examination of the thermodynamic profile within each column, using a precipitatioin type scheme adapted from that used in the Eta model (Baldwin et al 1994). Freezing drizzle (FZDZ) and drizzle (DZ) categories have been added to the Baldwin/Coturno scheme for situations with warm cloud tops and simultaneous precipitation predicted at the surface. The surface precipitation field from RUC also replaces the radar data ingested into IIDA. One key addition for IIFA is the use of SLW from the RUC microphysics package (Reisner et al 1998). Past verification has shown that icing is very likely in locations where the SLW is explicitly predicted by the microphysics package, but that the current operational version only captures roughly one-third of all icing PIREPs. Thus, it cannot stand alone as an icing forecast, but our confidence that icing conditions exist is boosted when SLW is explicitly predicted. IIFA calculates an initial icing potential using the surrogate information described above, then uses the SLW field as a "boosting factor" to the initial icing potential. Real-time runs of IIFA have taken place off-line for more than a year. Examination of output has shown that it is very similar to IIDA, as one would expect. Extensive verification has shown that IIFA is not quite as good as IIDA, as one would expect, considering the loss of such valuable observations from satellite, etc. Still, IIFA has verified quite well, and is still an improvement over past icing algorithms, as well as a 3-hour persistence forecast from IIDA (e.g. using the 15Z IIDA output and verifying it using 18Z PIREPs). REFERENCES ---------- Baldwin, M., R. Treadon and S. Coturno, 1994: Precipitation type prediction using a decision tree approach with NMC's mesoscale eta model. Preprints, 10th Conf. on Numerical Weather Prediction, Portland OR, Amer. Meteor. Soc., Boston, pp. 30-31. McDonough, F. and B.C. Bernstein, 1999: Combining satellite, radar, and surface observations with model data to create a better aircraft icing diagnosis. Preprints, 8th Conf. on Aviation, Range and Aerospace Meteorology, Dallas TX, Amer. Meteor. Soc., Boston, pp. 467-471. Reisner, J., R.M. Rasmussen and R.T. Bruintjes, 1998: Explicit forecasting of supercooled liquid water in winter storms using the MM5 mesoscale model. QJRMS, 124, 1071-1107.