Assimilation of METAR cloud and visibility observations in the RUC

ASSIMILATION OF METAR CEILING AND VISIBILITY OBSERVATIONS IN THE RUC

Stan Benjamin, Steve Weygandt, John Brown, Tracy Lorraine Smith, Tanya Smirnova, Bill Moninger, Barry Schwartz, Ed Szoke, and Kevin Brundage

Forecasts of ceiling and visibility for aviation operations remain an area of much needed improvement. Model-based forecasts of these fields are the main source of guidance beyond the first few hours, where persistence or simple extrapolation methods are the primary tool. The Rapid Update Cycle (RUC) cycles full-resolution 5 species of cloud (water and ice) and precipitation (rain, snow, graupel) hydrometeor fields, with the capability for updating these fields from observations. In the operational RUC from NCEP, GOES cloud-top data are used to update these fields to improve RUC cloud initial conditions. However, satellite data define only cloud tops, whereas cloud base is most crucial for aviation (and other transportation) weather users. Therefore, FSL has developed assimilation procedures for METAR-based multilevel cloud, visibility, and current weather observations to improve RUC initial conditions. Our prior research has demonstrated that improved model-based ceiling and visibility 1-12 h forecasts can be achieved by translating the METAR observations of these fields into initial conditions of model parameters that can fairly well define these fields.

An initial technique for assimilating METAR cloud observations has been in testing since fall 2003, with more recent addition of a related technique for assimilating visibility and current weather observations. Initial testing has been evaluating estimates of ceiling and visibility after converting METAR observations into 3D RUC prognostic variables, and then diagnosing ceiling and visibility back using translation algorithms (e.g., variations of the Stoelinga/Warner visibility estimation procedure). This testing has shown that the initial RUC technique is fairly good in capturing ceiling and low cloud data into the RUC analysis, less effective but showing promise for direct assimilation of visibility observations. Some improvement in ceiling forecasts is evident in statistical evaluation, although substantial further improvement is needed and, we think, possible. For example, a change to the model's land-surface scheme to allow deposition of water vapor on the surface as frost when the skin temperature is below 0 deg C should reduce excessive nighttime fog formation in winter.

The techniques for the METAR ceiling and visibility assimilation will be described, with both case studies and examples of its effectiveness, both in improved specification of the initial hydrometeor fields and in forecasts.