RadxQpe expanded

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The goal of RadxQpe is to provide the best two-dimensional estimate of precipitation rates at ground level. To do so, RadxQpe must account for elevated terrain, areas of weak signal, and the height of the radar beam. This page will walk through how the application handles these factors to produce the end result.

Elevated Terrain

In certain regions, mountain ranges block radar beams at lower elevation angles, as shown in the example of a 0.5º elevation sweep from northern Taiwan below (left image). The white oval highlights weak reflectivity values in the middle of the east-west line of intense reflectivity values. The region of weak reflectivity corresponds to beam blockage by Taiwan's Central Mountain Range (fractional value; right image).

Rate dbz 0pt5 annotated.pngBeame 0pt5.png

However, radars often scan three-dimensional volumes and at a higher elevation angle of 1.5º, the band of intense reflectivity values in the oval is no longer discontinuous (left image) and the beam blockage is far weaker (right image).

Rate dbz 1pt5 annotated.pngBeame 1pt5.png

RadxQpe takes advantage of the three-dimensional radar volume to look at different elevation angles in regions where terrain exists to find to elevation angles closest to but above ground level. This process is done by linking to the output from RadxBeamBlock in the RadxQpe parameter file. The default choice for the maximum fractional beam blockage is 0.25. While the estimated precipitation rate from lowest elevation angle in the RadxRate file (left image) is discontinuous, RadxQpe's estimate of surface precipitation (right image) includes the precipitation rates occurring above the Taiwanese mountain range.

Rate rhybrid annotated2.pngQpe rhybrid annotated2.png

Signal Quality

Factors that impact the signal quality include poor signal to noise ratios and the strength of the rain rate. If the input radar data includes the signal to noise ratio (SNR) as a variable, RadxQpe will use the minimum threshold to determine if the data quality if sufficient or if data from a higher elevation angle is needed. If SNR doesn't exist, RadxQpe will calculate the SNR from the reflectivity field.

RadxQpe also allows the user to set the minimum valid precipitation rate (mm/hr). Any precipitation rates below this threshold will be set to 0.

The two images below show the precipitation rate from RadxRate (left image; 0.5º elevation angle) and RadxQpe (right image). In the RadxRate image, the dark blue color (associated with precipitation rates less than 1 mm/hr) covers a large area, whereas the RadxQpe image shows far less coverage of the lightest precipitation rates (the minimum valid rate was 0.5 mm/hr for this example).

Rate rhybrid2.pngQpe rhybrid2.png

Radar Beam Height

Due to refraction and curvature of the earth, the height of a radar beam increases with increasing range. Thus, at large distances from the radar, the 0.5º sweep is several km above the ground. Since RadxQpe aims to return the estimated surface precipitation, the user can set a maximum beam height above which the precipitation rate will be set to 0.

The two images below show the precipitation rate from RadxRate (left image; 0.5º elevation angle) and RadxQpe (right image). In the example below, the maximum beam height was set to 4 km above mean sea level. All data beyond ~150 km has been removed due to this height requirement.

Rate rhybrid2.pngQpe rhybrid2.png


A flowchart that describes the order of RadxQpe decisions from Dixon et al. (2015) is shown below.

Qpe flowchart.png


Dixon, M. J., J. W. Wilson, T. M. Weckwerth, D. Albo, and E. J. Thompson, 2015: A dual-polarization QPE method based on the NCAR particle ID algorithm: Description and preliminary results. 37th Conf. on Radar Meteorology, Norman, OK, Amer. Meteor. Soc., 9A.1. Link