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The BMRC Regional Data Assimilation System

G. A. MillsBureau of Meteorology Research Centre, Melbourne, Australia

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R. S. SeamanBureau of Meteorology Research Centre, Melbourne, Australia

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Abstract

A new limited-area data assimilation system has been developed in the BMRC for operational use by the Australian Bureau of Meteorology. The system analyzes deviations from a primitive equations model forecast, using two-dimensional univariate statistical interpolation (SI) to analyze mass, and three-dimensional univariate SI to analyze wind data. Mass and wind increment analyses may mutually influence the other using variational techniques.

Analysis increments are vertically interpolated to prognosis model sigma surfaces, added to the forecast variables, and the model integrated forward to the next analysis time. This ongoing analysis-forecast cycle is now being implemented operationally.

This paper describes in detail the analysis methodology, and presents results from a 17-day trial period. The analyses are compared with operationally prepared analyses for the same period individually, as means, and by data fitting statistics. It is shown that the assimilated analyses have stronger jet streams and greatly improved detail in the moisture analyses. It is also shown that vertical motion patterns in the guess fields are preserved through the analysis initialization phase of the assimilation cycle, and that these vertical motion fields correlate well with the areas of cloud seen in satellite imagery.

Prognoses from this trial period show a much more rapid spinup of forecast rainfall rate than did a series of control forecasts based on operational analyses, and both mean rainfall for the 17-day period and individual cases are presented to demonstrate improved skill of forecasts from the assimilated analyses. Objective verification of mass-field forecasts showed considerable sensitivity of the forecasts to the particular set of bogus mean sea level pressure data used in the analysis; however, preliminary verification statistics from the first 15 days of operational parallel running showed that the assimilation system produced forecasts of similar skill to operational forecasts of MSLP at 24 hours, but greater skill at the upper levels, and had greater skill at all levels for the 36-hour forecast.

Abstract

A new limited-area data assimilation system has been developed in the BMRC for operational use by the Australian Bureau of Meteorology. The system analyzes deviations from a primitive equations model forecast, using two-dimensional univariate statistical interpolation (SI) to analyze mass, and three-dimensional univariate SI to analyze wind data. Mass and wind increment analyses may mutually influence the other using variational techniques.

Analysis increments are vertically interpolated to prognosis model sigma surfaces, added to the forecast variables, and the model integrated forward to the next analysis time. This ongoing analysis-forecast cycle is now being implemented operationally.

This paper describes in detail the analysis methodology, and presents results from a 17-day trial period. The analyses are compared with operationally prepared analyses for the same period individually, as means, and by data fitting statistics. It is shown that the assimilated analyses have stronger jet streams and greatly improved detail in the moisture analyses. It is also shown that vertical motion patterns in the guess fields are preserved through the analysis initialization phase of the assimilation cycle, and that these vertical motion fields correlate well with the areas of cloud seen in satellite imagery.

Prognoses from this trial period show a much more rapid spinup of forecast rainfall rate than did a series of control forecasts based on operational analyses, and both mean rainfall for the 17-day period and individual cases are presented to demonstrate improved skill of forecasts from the assimilated analyses. Objective verification of mass-field forecasts showed considerable sensitivity of the forecasts to the particular set of bogus mean sea level pressure data used in the analysis; however, preliminary verification statistics from the first 15 days of operational parallel running showed that the assimilation system produced forecasts of similar skill to operational forecasts of MSLP at 24 hours, but greater skill at the upper levels, and had greater skill at all levels for the 36-hour forecast.

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