Difference between revisions of "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. | 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 | + | 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). |
| − | [[File:Rate_dbz_0pt5_annotated.png| | + | [[File:Rate_dbz_0pt5_annotated.png|550px]][[File:beame_0pt5.png|550px]] |
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). | 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). | ||
| − | [[File:Rate_dbz_1pt5_annotated.png| | + | [[File:Rate_dbz_1pt5_annotated.png|550px]][[File:beame_1pt5.png|550px]] |
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 [http://wiki.lrose.net/index.php/RadxQpe#Important_parameters 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. | 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 [http://wiki.lrose.net/index.php/RadxQpe#Important_parameters 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. | ||
| − | [[File:Rate_rhybrid_annotated2.png| | + | [[File:Rate_rhybrid_annotated2.png|550px]][[File:Qpe_rhybrid_annotated2.png|550px]] |
| − | + | === '''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 [http://wiki.lrose.net/index.php/RadxQpe#Additional_parameters_to_edit 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. | 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 [http://wiki.lrose.net/index.php/RadxQpe#Additional_parameters_to_edit 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. | ||
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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). | 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). | ||
| − | [[File:Rate_rhybrid2.png| | + | [[File:Rate_rhybrid2.png|550px]][[File:Qpe_rhybrid2.png|550px]] |
| − | + | === '''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 [http://wiki.lrose.net/index.php/RadxQpe#Additional_parameters_to_edit maximum beam height] above which the precipitation rate will be set to 0. | 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 [http://wiki.lrose.net/index.php/RadxQpe#Additional_parameters_to_edit 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. | 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. | ||
| − | [[File:Rate_rhybrid2.png| | + | [[File:Rate_rhybrid2.png|550px]][[File:Qpe_rhybrid2.png|550px]] |
| − | + | === '''Flowchart''' === | |
A flowchart that describes the order of RadxQpe decisions from [http://wiki.lrose.net/index.php/RadxRate_equations#References Dixon et al. (2015)] is shown below. | A flowchart that describes the order of RadxQpe decisions from [http://wiki.lrose.net/index.php/RadxRate_equations#References Dixon et al. (2015)] is shown below. | ||
[[File:Qpe_flowchart.png|350px]] | [[File:Qpe_flowchart.png|350px]] | ||
| − | + | === '''References''' === | |
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. [https://ams.confex.com/ams/37RADAR/webprogram/Paper275705.html Link] | 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. [https://ams.confex.com/ams/37RADAR/webprogram/Paper275705.html Link] | ||
Latest revision as of 18:34, 9 February 2021
Contents
Overview
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).
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).
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.
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).
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.
Flowchart
A flowchart that describes the order of RadxQpe decisions from Dixon et al. (2015) is shown below.
References
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