Convective Meteorology (Mesoscale Dynamics)

Reflectivity Data Assimilation: Techniques, Issues, and Future Possibilities

Jacob Carlin
OU School of Meteorology

24 April 2015, 2:00 PM

National Weather Center, Room 5600
120 David L. Boren Blvd.
University of Oklahoma
Norman, OK

The explicit modeling of convection has become a major area of research over the past twenty years, owing to an increase in computational power and the development of advanced data assimilation techniques. However, conventional observing networks such as radiosondes and METARs do not typically fully resolve convective features. Radar is currently the only source of data with the spatial and temporal resolutions for the task, and the assimilation of radar data into convective-resolving models has therefore received a fair amount of attention in the community. The aim of assimilating radar data is to reduce the storm spin-up time as well as to achieve more accurate representations of forecasted storms. However, unlike many observations at the synoptic scale, the observed variables (Z, Vr) are not the same as those predicted by the model (u, v, w, q, etc.), with retrievals therefore being required. Uncertainty remains on how to best accomplish this, exacerbated by the lack of knowledge of appropriate balance constraints on the convective scale and error covariances of the radar observed variables.

In this talk, a general overview of the techniques used to assimilate reflectivity will be reviewed, including latent heat nudging (LHN), the complex cloud analysis, variational techniques, ensemble Kalman filter techniques, and future hybrid variational-ensemble techniques. Successes and difficulties of each technique will be discussed. In addition, recent research on the potential uses and considerations of dual-polarization data to aid in the modeling of convective storms will be reviewed.

In a preliminary effort to understand the issue at hand, two sensitivity experiments were performed using the Advanced Regional Prediction System (ARPS) cloud analysis for a hailstorm in central Iowa on 12 April 2014. The first experiment assimilated a single radar scan at various start times and found strong forecast sensitivities to the initial strength of the storm. The second experiment modified cloud analysis parameters to test the impact of these changes. It was found that the use of reflectivity was crucial in obtaining realistic storms, and that tuning the latent heating parameter did not have a large impact on the resulting forecast. In addition, ARPS was successful in simulating ZDR columns, and supercell structures including ZDR arcs were able to be simulated when both radial velocity and reflectivity were used. Finally, 2D simulations of a modeled storm using the Hebrew University Cloud Model (HUCM) will be shown, with an emphasis on investigating future uses of radar data in convective modeling.

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Convective Meteorology (Mesoscale Dynamics) Seminar Series website