Impact of assimilating radar data to the ARPS numerical model in simulating the precipitation due to the synoptic system on the 31st of March 2009 in Tehran province

Remote sensing is a maturing discipline that calls for a wide range of specialties and crosses boundaries between traditional scientific and technological disciplines. Its multidisciplinary nature requires its practitioner to have a good basic knowledge in many areas of science and requires interactions with researchers in a wide range of areas such as electromagnetic theory, spectroscopy, applied physics, geology, atmospheric sciences, agronomy, oceanography, plasma physics, electrical engineering, and optical engineering.
The scattering of electromagnetic waves by precipitation particles and their propagation through precipitation media are of fundamental importance in understanding the signal returns from dual-polarized, Doppler weather radars.
The main advantage of using radars for precipitation estimation is that they can provide measurements over large areas (about 10 000 km²) with fairly high temporal and spatial resolutions. Installing just one guage for each radar spatial sample (150 m resolution in range and one-degree resolution in azimuth) would require more than one-quarter of a million guages over a 150-km radius. These measurements are sent to a central location at the speed of light by “natural” networks. In addition, radars can provide fairly rapid updates of the three-dimensional structure of precipitation.
The use of the radar data to detect atmospheric phenomena with suitable spatial and temporal resolutions has become one of the main methods to improve the performance of numerical weather prediction models. The effects of assimilating radar data to the ARPS numerical model on short time rain forecasts were investigated for a region covering parts of Tehran and Qom Provinces. The investigation was carried out for a synoptic system that affected the central and southern regions of Iran on March 31, 2009. The result of the juxtaposition of a Sudanese low and a strong Siberian high, the synoptic system led to remarkable rainfall in the main parts of the region of interest while leaving the southern flanks of Eastern Alborz with little rain.
The ARPS numerical model was ran in two different ways: first, with the GFS (Global Forecast System) data in 3-hour time intervals; second, using the same GFS data together with the assimilation of the data of Tehran''s meteorological radar. The results of the latter two applications were compared with the actual observed rainfall accumulated over 6-hour and 24-hour intervals on March 31, 2009.
The results demonstrated the usefulness of assimilating radar data to improve the rainfall forecast, both quantitatively and qualitatively. The effects of the radar data are felt more strongly at the final hours of the model run. This is due to the fact that the last part of the radar data was assimilated to the model at 10:30 UTC.  The usefulness of the radar data assimilation is less felt in the high-altitude parts where the rain forecast critically depends on the particular cloud and the scheme used in convection parameterization. For the same reason, the rainfall forecast error is usually larger in the high-altitude parts of the region.