Abstract
An operational surface analysis system for the continent of Australia is presented. The system is specifically designed to mitigate problems that arise when analyzing surface data with a highly inhomogeneous distribution. Hourly analyses of atmospheric pressure at mean sea level, potential temperature, 2-m dewpoint temperature, and 10-m wind components are generated on a ~4-km grid. The system employs a statistical interpolation technique using observations of pressure, temperature, dewpoint, and wind data. The problem of data gaps in space and time is addressed by introducing pseudo-observations. For stations missing a report at analysis time, estimates are reconstructed by interpolating off-time reports. Underobserved areas in the network are identified from precalculated, gridded observation densities for each analysis time, which also yield weights to combine preliminary analysis and first-guess data into pseudo-observations. A regression-based pressure reduction technique, consistent with local reductions at observing sites and devised specifically for this system, is used for accurate and fast conversion of pressure and, indirectly, temperature variables within the system. Analysis accuracy is verified by withholding observations for specific periods. Analyzed fields are shown to be significantly more accurate than the current operational numerical model fields used as a first guess for the high-resolution surface analysis. The system design and analysis accuracies are also assessed within this context and compared with similar overseas developments.
Mesoscale Surface Analysis System for the Australian Domain: Design Issues, Development Status, and System Validation
