DEvElOPING HIGH-QUAlItY FIElD PROGRAM SOUNDING DAtASEtS

F or nearly half a century, field experiments have been conducted from the tropics to the polar regions involving intensive observations of atmosphere, ocean, and land processes over selected locations of interest. In a recent article, Johnson et al. (2012) identified more than 50 past field experiments with upper-air sonde datasets (see their Fig. 2, which shows a map depicting the shape, size, and location of many of these sonde networks). Field program sondes are characterized by high temporal (3–6 h) and vertical (5–10 m) resolutions and enhanced accuracy, made possible by the large suite of instruments deployed in the experiment, which allows for cross calibration. In comparison, sondes from operational networks only have data at standard and significant levels with 250–500-m and 12–24-h resolution. Upper-air observations from field experiments have numerous applications: environmental condition descriptions, which provide a context for validating and understanding other observations (radar, aircraft, satellite, etc.); heat and moisture budget analyses from which the properties of convection can be inferred (Yanai et al. 1973); large-scale advective tendency computations that force cloud-resolving and single-column models, which aide in the improvement of model parameterization schemes (Wu et al. 2000); and model initialization for reanalyses and case studies. In addition, these datasets provide the basis for constructing high vertical resolution, model-independent analyses for model validation purposes. Because of their usefulness, accuracy, and resolution, field program sonde datasets are in high demand. Developing a research-quality sonde dataset that is able to meet the scientific objectives of the experiment begins with high-quality observations. This fact was eloquently stated by Ooyama (1987) in his Global Atmospheric Research Program (GARP) DEvElOPING HIGH-QUAlItY FIElD PROGRAM SOUNDING DAtASEtS