Extended Abstract (564K)P1.43
28,000 nmi of microphysical measurements in supercooled clouds
Richard K. Jeck, FAA Technical Center, Atlantic City, NJ
About 28,000 nmi (52,000 km) of select, in-flight measurements of LWC, drop size and concentration, temperature and other variables in supercooled clouds over portions of North America, Europe, and the northern oceans have been collected from dozens of projects by many agencies. Selected, quality-screened data from all these sources have been converted into a common format for ease of use and comparison, and stored in a computerized array of 75 variables.
Several innovations are introduced and recommended for general use by the cloud physics community:
• Uniform cloud intervals (averages over variable distances where the droplet concentration, mass-median diameter (MMD), altitude, etc., stay within defined limits) provide an economical way to organize large numbers of 1-sec samples into a manageable set of averages. These preserve essential features of the cloud without sacrificing horizontal or vertical resolution where it is needed.
• Averaging distance or duration as a variable weighting factor is used for frequency-of-occurrence tabulations so that short and long averages are not counted the same.
• Distance-based graphing solves the dual problem of: 1) comparing values of a given variable (e.g., LWC) averaged over different distances from different sources, and 2) depicting limiting values of LWC and MMD as a function of averaging distance.
• Seasons (cold, mild, and warm) are defined not by the calendar months but by the height of the local freezing level AGL (< 1.5 km, 1.5 to 3 km, or > 3 km, respectively).
Some characteristics revealed by the database, such as the range, frequency and duration of LWC vs. temperature, altitude, season and cloud type will be presented, as well as some new features such as cloud-preferred values of droplet MMD.
Originally compiled for characterizing aircraft icing conditions, this largest-ever combined dataset of cloud microphysical variables should also be useful for cloud modeling and parameterization---either for assigning generic variable values, or for comparing or tuning the models and parameterizations to a variety of specific cloud conditions.
Poster Session 1, Cloud Physics Poster Session I
Monday, 10 July 2006, 5:00 PM-7:00 PM, Grand Terrace
Previous paper Next paper