Assessing the Quality and Impact of Surface Observations

John Horel
University of Utah


The heterogeneous nature of surface observing stations tends to lead to subjective decisions to use some observations and avoid others in data assimilation systems. We are attempting to improve the quality control of surface observations as well as determine their impact on high resolution (2.5 km) analyses of temperature, dewpoint, and wind. A combination of quality control procedures are being used including observation departures from the 2.5 km background fields used by the Real-Time Mesoscale Analysis and metrics obtained from the adjoint of a two-dimensional variational surface analysis over the contiguous United States. The relative impact of an observation tends to be controlled by its location through the interplay of the weather conditions observed there, the ability of the background field to diagnose the variability of those conditions, and the proximity of other nearby observations. Of lesser importance are the types of network from which the observations are obtained and the assumptions made regarding their observational errors. Differentiating objectively between high impact observations that result from low observation quality, observation representativeness errors, or accurate observed weather conditions not evident in the background field can be difficult.