Developing and Exploring Ensemble Forecast Sensitivity to Observations (EFSO) for a Convective-Scale Data Assimilation System over the Dallas-Fort Worth Testbed

Forecast sensitivity to observation (FSO) methods have become increasingly popular
over the past two decades, providing the ability to quantify the impacts of various observing
systems on forecasts without having to conduct costly data denial experiments. While adjoint-
and ensemble-based FSO are employed in many global operational systems, their use for
regional convection-allowing data assimilation (DA) and forecast systems have not been fully
examined. In this study, ensemble FSO (EFSO) is further developed and explored for high-
frequency convective-scale DA for a severe weather case study over the Dallas-Fort
Worth testbed on 3 April 2014. This testbed, originally established by the Collaborative
Adaptive Sensing of the Atmosphere (CASA) project, aims to improve high-resolution DA
systems by assimilating a variety of existing state and regional mesoscale observing systems to
fill gaps of conventional observing networks. This study further develops and utilizes EFSO to
estimate relative impacts of nonconventional surface observations against conventional
observations. Further, it incorporates assimilated radar observations into EFSO estimated impact.
Subjective and objective comparisons are made between the 2D actual error reduction fields and
the summed EFSO estimates from all observations. Results show that, when applying advected
localization and a neighborhood upscale averaging technique, EFSO estimates remain correlated
and skillful with the actual error reduction of all assimilated observations for the duration of 2-h
forecasts. The ability for EFSO to verify against other metrics (surface T, u, v, q) beside energy
norms is also demonstrated, emphasizing that EFSO can be used to evaluate impacts of specific
parts of the forecast system rather than integrated quantities. Partitioned EFSO revealed that
while conventional and radar observations contributed to most of the total energy,
nonconventional observations contributed a significant percentage (up to 25%) of the total
impact to surface thermodynamic fields, which subjectively agrees with results from previous
data denial experiments. This study is an important step towards establishing the feasibility of
EFSO for ensemble convective-scale DA and forecast systems.