Value of Assimilating TAMDAR Observations

Sources of observations to improve mesoscale model initial conditions are often limited in battlefield environments. Aircraft are a potential source of additional observations; the Tropospheric Airborne Meteorological Data Reporting (TAMDAR) sensor provides temperature, moisture, and wind from aircraft. An earlier investigation placed a modified TAMDAR sensor on an unmanned aerial system and assimilated the observations into the Advanced Research version of the Weather Research and Forecasting (WRF-ARW) model, but had limited verification data against which to evaluate the results.

We investigate the benefits of assimilating TAMDAR observations from commercial aircraft for five cases in early 2012 over California using observation nudging in WRF-ARW and using nested domains with 9, 3, and 1 km horizontal grid spacing. The forecasts are evaluated against surface, rawinsonde, and aircraft-based observations.