Statistical analysis of S-Pol polarimetric radar data from NAME 2004

The over-arching goal of the North American Monsoon Experiment (NAME) is to improve prediction of warm-season rainfall over North America, and especially over the southwestern portion of the U.S. where summer rains are forced by the North American Monsoon (NAM). For NAME, a comprehensive network of instrumentation was deployed during summer 2004 in order to document the variability of precipitation across the Sierra Madre Occidental (SMO) and adjacent coastal plain and Gulf of California (GoC), regions central to supplying moisture to the NAM and generating rain over the southwestern U.S. This report focuses on quality control and analysis of the ground-based radar observations collected by the S-Pol radar, an S-Band polarimetric Doppler radar operated by the National Center for Atmospheric Research (NCAR) during the NAME Enhanced Observing Period (EOP), which occurred during July-August 2004. The main dataset for the presented analyses consists of 3-D Cartesian grids, which include all major polarimetric variables (reflectivity, differential reflectivity, specific differential phase, linear depolarization ratio, and correlation coefficient) as well as fuzzy-logic-based hydrometeor identification. This dataset is available at 0.02° horizontal resolution, 1-km vertical resolution, and 15-minute temporal resolution. The grids extend approximately 1.6° in each longitude and latitude direction from S-Pol (~160 km in each direction).

Research on NAME radar datasets is expected to contribute to the existing body of knowledge pertaining to orographic precipitation. The NAME region is an unstable, humid tropical environment with complex topography. This type of region has been rarely studied with polarimetric radar in the past. Similar to several other tropical mountainous environments (e.g., Nepal, Thailand), over the higher terrain in NAME it was observed (with both radars and rain gauges) to rain more frequently but less intensely than over lower elevations (i.e., coastal plain and GoC). We hypothesize that the systematic variation in rainfall is related to changes in the vertical and organizational structure of precipitating systems, and their associated precipitation characteristics, as they develop over the high terrain and move toward the coastal plain. In particular, NAME rain gauge studies have suggested that the relationship between rainfall intensity and elevation is linked to increased access of moisture at low elevations as well as to organizing mesoscale dynamics that are less inhibited by terrain. Distance to the Gulf of California and the configuration of the terrain profile also may have important effects on precipitation in this region. We will test these hypotheses using the NAME S-Pol dataset.

We will statistically analyze the entire S-Pol radar 3-D dataset in order to extract the salient organizational characteristics and microphysical processes from the entire spectrum of precipitating systems (convective and mesoscale) in the NAME region. The dataset will be analyzed to derive statistics for warm rain vs. ice-based precipitation, and properties of the rain drop size distributions (DSDs), evaluated as functions of topography and diurnal cycle. In addition, mean statistics on the vertical reflectivity profile and microphysical structures will be computed and analyzed as functions of topography and diurnal cycle. Other analyses will be presented as well, if they are completed in time for this presentation.