In an effort to quantify the potential benefits of the new system for real-time forecasts, a set of full-cycling assimilation experiments, as well as a detailed storm case, were carried out in 2012 by using the close-operational conventional data set. Given the real-time environment, which was not subject to the same perfect assumptions as the OSSE, the assimilation of real observations still produced quantitative improvements that were similar to those seen in the OSSE results.
The initial results suggest that analyses from the new formulation were better than those of traditional ones based on root-mean-square (RMS) errors and bias against radiosonde observations. The improvements in the analysis translated to subsequent gains in forecast skill, especially with respect to bias.
A storm case study was also performed to further investigate the forecast improvement. Although the same temperature and relative humidity data sets were used in the assimilation schemes, more accurate temperature, humidity, and synoptic situation forecasts were obtained from the direct assimilation methodology by the accumulated observation information in the cycling assimilation, which enhanced the accuracy of the precipitation forecast.