12th Conference on IOAS-AOLS


Assimilation of radar reflectivity data using a diabatic digital filter within the Rapid Update Cycle

Stephen S. Weygandt, NOAA/ESRL/GSD, Boulder, CO; and S. G. Benjamin, T. G. Smirnova, and J. M. Brown

A new procedure for assimilating radar reflectivity data within the hourly updated Rapid Update Cycle (RUC) system has been developed and tested and is producing significant improvements for short-range forecasts of precipitation systems. The new procedure ingests the National Severe Storms Laboratory (NSSL) national radar reflectivity mosaic data and uses elements of the RUC cloud analysis and diabatic digital filter initialization (DFI) to force latent heating consistent with the hydrometeor fields derived from the radar data. Within the cloud analysis, the radar reflectivity data are used to compute a latent heat based temperature tendency. This tendency is then applied during the forward-model integration portion of the diabatic DFI. This is accomplished by replacing the temperature tendency from both the parameterized convection and explicit microphysics with that derived from the radar data. Application of this latent heat derived temperature tendency induces an associated vertical circulation, with low-level convergence and upper-level divergence. In addition to this latent heat nudging during the diabatic DFI, the relative humidity is increased in the radar reflectivity echo regions.

The algorithm to force precipitation in radar-echo regions is complemented by a convective suppression procedure in echo free regions. In this procedure, a convective suppression mask is created that includes all area that have a 300 mb deep layer that is at least 100 km in the horizontal from any radar echoes. Areas for convective suppression areas are distinguished from areas where convection is allowed and areas where radar data coverage is insufficient to make a determination. Within the convective suppression area, the cumulus parameterization scheme is inhibited during the forward model portion of the DFI and the first 30 min. of the model integration.

Real-time testing within a parallel cycle at ESRL/GSD (ongoing since February 2007) indicates that the new assimilation procedure yields significant improvement in short-range forecasts of precipitation systems, as revealed by qualitative examination of model simulated reflectivity and precipitation plots and quantitative precipitation verification. Improvements are especially pronounced for warm season convective systems that are frequently poorly analyzed using conventional observations. Analysis of specific case studies indicates that the assimilation procedure projects onto both the grid-scale and parameterized model precipitation processes. Improvements are most dramatic during the first few hours of the model forecast and then gradually diminish with time. We are currently examining the sensitivity of the radar assimilation procedure to a variety of factors and evaluating possible modification to the cumulus parameterization to improve the longevity of the positive forecast impact.

Based on the very encouraging results, this radar reflectivity assimilation algorithm will be included as a part of the RUC operational upgrade package scheduled for NCEP implementation in early 2008. Toward that goal, work is progressing to make the radar reflectivity mosaic data available in real-time at NCEP and RUC code has been transferred to NCEP for real-time trials of the parallel RUC system. At the conference, we will present updated quantitative and case study results from the real-time cycle tests, as well as more detailed analysis of selected off-line test cases.

extended abstract  Extended Abstract (2.1M)

wrf recording  Recorded presentation

Session 8, Mesoscale Data Assimilation
Tuesday, 22 January 2008, 3:30 PM-5:30 PM, 204

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