Abstract
An objective analysis scheme for meteorological variables on constant potential temperature surfaces is presented. The analysis uses a form of multivariate statistical interpolation and is designed th retain mesoscale detail in disparate observations including rawinsonde, surface, aircraft, satellite, and wind profiler data while combining them with a forecast background (first guess) field. The wind and mass field analyses are interdependent. The horizontal correlation of forecast error on isentropic surfaces is modeled with an analytical function from statistics collected for this study; the vertical correlation of forecast error is modeled as a function of potential temperature separation. These correlations determine the weights applied to observed-minus-forecast increments in the analysis. The analysis is two-dimensional except with respect to single-level data where it is three-dimensional. Comparisons of isentropic and isobaric analysts are shown, and examples of the effects of single-leve... Abstract An objective analysis scheme for meteorological variables on constant potential temperature surfaces is presented. The analysis uses a form of multivariate statistical interpolation and is designed th retain mesoscale detail in disparate observations including rawinsonde, surface, aircraft, satellite, and wind profiler data while combining them with a forecast background (first guess) field. The wind and mass field analyses are interdependent. The horizontal correlation of forecast error on isentropic surfaces is modeled with an analytical function from statistics collected for this study; the vertical correlation of forecast error is modeled as a function of potential temperature separation. These correlations determine the weights applied to observed-minus-forecast increments in the analysis. The analysis is two-dimensional except with respect to single-level data where it is three-dimensional. Comparisons of isentropic and isobaric analysts are shown, and examples of the effects of single-leve...

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