A Typical Weather Radar: A photo of a radar within the Canadian network showing the major physical components of a radar system. The tower is about 30 m high, with a radome fitted with hazard lights and lightning rod. One building houses the transmitter/receiver and computers and the other houses the uninterruptable power supply and diesel generator. Physical Artifacts in Radar Data: The weather radar can detect many things besides weather targets. This schematic illustrates many of these features. The + or - signs indicate whether the radar reflectivity is augmented or diminished by the feature. These artifacts need to be removed for quantitative applications. 0.5 0.3 0.0 -0.3 Earth’s Surface Radar Beam Height in Physical Space: Schematic of beam height for selected elevation angles [-0.4, 0, 0.3 and 0.5] above the Earth's surface (thick black line) for a standard index of refraction profile in the atmosphere plotted in physical space with a Earth curvature equivalent to the Earth radius. Note the downward curvature of the beam paths but still rising relative to the Earth. 25.5 21.8 18.6 15.8 13.4 11.3 9.5 8.0 6.8 5.7 4.8 4.0 3.4 Area not scanned Cone of silence Geometic Progression Factor= 1.19 n tan θ = tan o GP 2.8 2.4 2.0 1.7 1.4 1.2 1.0 0.85 0.7 0.6 0.5 Area not scanned Overshooting θ Geometric Progression of Elevation Angles in Flat Earth Coordinates: The beam height diagram is a useful tool to aid the interpretation of the radar products. The beam height is plotted against a flat Earth which is a more traditional presentation. The elevation angle sequence is one proposed by Marshall and Ballantyne (1978) to produce optimal horizontal products (CAPPI’s, Echo Tops). PRF=1200 PRF = 2400 S Band C Band X Band Doppler Range-Velocity Trade-off with Common Radar Wavelengths: This illustrates the "Doppler Dilemma" for the three common radar bands (X, C, S). The dilemma arises because one parameter, the pulse repetition frequency which is the time between transmitted pulses, controls both the maximum unambiguous velocity and maximum unambiguous range in opposite ways. The markers and red lines indicate commonly used settings. The Doppler Spectrum: This shows the distribution of power within a single radar pulse volume as a function of the Doppler velocity. This is a simulated example showing ground clutter (narrow) and weather (broad), noise and signal fluctuation as well as aliasing of the weather spectrum for a typical C Band radar set up. Doppler Ground Clutter and Data Quality Filtering: Modern Doppler radars can filter bad data or ground clutter in the signal processing phase of the processing chain. The left image shows the raw data and the right image shows the filtering capability of Doppler signal and data processing. Polarization diversity capability for data quality is shown in Fig. 9.29. Radar Radiation Pattern: A generic antenna radiation pattern. Note that the antenna beam width is typically defined at the half-power (50% or -3 dB) points. If the target is highly reflective, there is power emitted and received on the side of the main lobe and the other side lobes. Zero Notch Filtering Artifact: Doppler notch filtering can remove too much echo when the Doppler spectrum of the weather echo is narrow and near the zero Doppler velocity (see arrow). This problem is minor compared to other artifacts illustrated in Fig. 9.2 The Dual-Pulse Repetition Frequency Velocity Extension Technique: This is an example of a C Band radar pulsing at 900 and 1200 s-1 with unambiguous Nyquist velocities of 12 and 16 m/s, respectively (note the labels). The technique relies on the difference between “measured” radial velocities (ordinate on the bottom image) to determine the “fold number” (abscissa on the bottom image) and then use that with the corresponding measured radial velocity to estimate the true radial velocity. Example of Dual-PRF Velocity Extension: This figure illustrates the necessity and ability of a C Band radar to extend the velocity out to at least 48 m/s. This is a case of a hurricane/extra-tropical transition passage and velocities are near 48 m/s. In this situation, the assumptions of the dual-PRF technique (the two measured estimates at different PRF’s are from the same radial velocity) are satisfied and the result has little “noise” (right image, compare with Fig. 9.20). Second Trip Echoes in Doppler Data: An example of second trip echoes in reflectivity (left) and radial velocity (right) for a magnetron radar. Second trip echoes appear as wedge shapes and noisy radial velocities in this magnetron system. a c b d e f g h Example of Random Phase Range Extension: The example on the left (a-d) show a situation where the first trip echo is weak and much of the second trip echo is recoverable. In the example on the right (e-h), there is significant first trip echo which precludes recovering the second trip echo. See text for explanation of the technique. Range-Velocity Extension Using Multiple PRF Scans: Without the advanced phase coded signal processing, multiple PRF techniques are used to recover the second trip. Low PRF scans with long range capability are used to locate the reflectivity echo. High PRF but short range scans are used to measure radial velocity. The radial velocity is assigned to the range bin with the highest power (> 5 dB). Clutter Rejection [dB] 50 40 30 20 10 0 0 1 2 3 4 5 6 Phase Noise [degrees] Doppler Clutter Rejection and Phase Noise: Coherency (phase noise) is a measure of the quality of a Doppler radar and it is directly related to the ability to remove ground clutter and ability to retrieve second trip echoes using phase coding techniques. Radar Failure Modes: Results from the WMO Weather Radar Survey showing the main failure modes of a radar (Sireci et al, 2010); Figure courtesy of Oguzhan Sireci of the Turkish State Meteorological Service. Self-Consistency Calibration Technique of Polarization Diversity Radars: There is a close relationship between reflectivity and specific differential phase (Z and KDP). The left figure shows the relationship from disdrometer measurement. The right figure shows one radial of data with significant differential phase. By adjusting the reflectivity and recomputing the differential phase, the radar can be calibrated in a self-consistent manner (Figures courtesy of Isztar Zawadzki.) Range to Terrain Digital Elevation Model Plot: Global digital elevation model (DEM) data is available and sufficiently accurate that can be used to assess and help determine the siting of a weather radar. Given an azimuth and elevation, the image indicates the distance in which useful data can be collected. 6.4km 0.42 o Radio Local Area Network Interference Examples: Use of the Electromagnetic Spectrum is determined through agreement and managed through the International Telecommunication Union (ITU). In 2003, demand for spectrum by the wireless community at C Band resulted in spectrum sharing with the radar community on a regulated, secondary, non-interfering but non-licensed basis. Image on the left is from a controlled study to demonstrate the type of expected interference from a Radio Local Area Network located at 6.4km away at 0.42o elevation angle. Image on the right is from an operational weather radar, courtesy of Claudia Campetella of Servicio Meteorologico Nacional (Argentina). Dual-Pulse Repetition Frequency Errors: The dual-PRF technique assumes that the measurements are made from a volume with the same radial velocity. The images show the prescribed field, the measured and the corrected data (top to bottom). (Figure adapted from Joe and May, 2003) Vertical Sidelobe Azimuthal Sidelobe Three-Body Scattering Side Lobe and Multiple Scattering Artifacts: Side lobe and multiple scattering effects result in somewhat similar looking artifacts. Side lobe artifacts are at constant range whereas multiple scattering is at constant azimuth. Strong reflecting core (red). Three-body scattering signature appears as an elongated echo due to delay in time. Three body scattering occurs when the radar beam strikes a target (in this case, the core of the thunderstorm); then strikes the wet surface and then reflects back to the core and then back to the radar. Wet Surface provides a good reflection Three-Body Scattering: This schematic describes how three-body scattering occurs. The echo extending to the right (bright yellow) is an artifact due to the three-body scattering. Wind Turbine Artifacts: Wind turbines are proliferating and are difficult to remove using Dopper filters due to the moving turbine blades. Image on the left courtesy of Deustcher Wetterdienst showing blocking (west of radar) and the image on the right shows interference and multiple scattering effects and is courtesy of the National Oceanic and Atmospheric Agency. 1. Large cell with strong elevated reflectivity (MAXR>45 dBZ) 2 2. Tall (high echo top) 3. Weak Echo Region 4. Hook/Kidney beam shape 5. Echo Top over the updraft/low level reflectivity gradient 5 6 1 6. Rotation Mesocyclones 7. Downdrafts 8. Hail 8 3 4 7 Severe Weather Warning Technique and Cell View Product: Use of radar for diagnosing and warning of severe storms was first based on reflectivity only and then subsequently enhanced with Doppler and dual-polarization signatures. The warning technique is listed on the left (Lemon, 1978) and the “cell view” product is an image centered on the automatically detected thunderstorm cell and with relevant products for decision-making (numbers in cell view, match the criteria number). c A B C D Severe Weather Feature – Mesocyclones: Multiple mesocyclones (A-D) are observed along a squall line and are identified as couplets of relative away and toward velocities at constant range. Symmetric velocity signatures are observed in the storm is not evident or removed. Severe Weather Feature – Hook Echo, Mesocyclone and Tornado Vortex Signature: A tornado vortex signature is identified as a away/toward couplet on adjacent range bins (see arrow on right image), embedded within a mesocyclone. High zoom factors are often needed to see this feature. The image on the left shows a classic hook echo. Severe Weather Feature – Downburst: A downburst (micro or macro) is observed as a couplet of away and toward radial velocities aligned along a radial (see arrows on the right image). These are rapidly evolving feature of thunderstorms with a life cycle of 10-20 minutes. They can emanate from very ordinary and small thunderstorms. A B Severe Weather Feature – Derecho/Straight Line Wind: Another signature of strong intense hazardous winds can be observed as a linear or curvilinear feature in the reflectivity (left) or radial velocity data (right). Severe Weather Feature – Hail Signatures: A example of hail detection and hail size estimation. The inset figure is a reflectivity based hail size product and the large image is a polarization diversity product identify precipitation type – including hail. The image on the right provided detailed analysis of this example. The ellipse is the same as on the left. The red and blue markers indicate detections of hail using polarization diversity. The crosses are from a reflectivity only technique (inset figure on the left). Figure is courtesy of Sudesh Boodoo of Environment Canada. + KRA + ADL Nowcasting Application – Echo Tracking and Extrapolation: A example of a cross-correlation nowcast. The weather is moving from the southwest (left image) and the meteogram on the right (most recent time at the top, future time is down the image) shows the most likely and most probable precipitation intensities at different locations (only KRA is shown on the image of the left and is sixth site on the image on the right). B A Nowcasting – Boundary Identification and Convective Initiation: An important use of weather radar is the nowcasting of the initiation of convection. Modern radars are sensitive enough to see lake breeze and thunderstorm outflows (A,B, respectively, left image). The intersection is a location of enhanced lift and therefore a location of potential convective initiation (see storm forming within the dashed white circle). Vertical Profile of Reflectivity and Impact of Beam Smoothing and Propagation with Range: Beam smoothing and beam propagation modifies the appearance of the vertical profile of reflectivity with range. Three situations are depicted with the maximum reflectivity in the column as percentage of the surface precipitation taking into account the bright band. (Adapted after Joss and Waldvogel, 1990). 1o beam 0.65o beam Range Effects on Radar Precipitation Accumulation: This shows an accumulation of radar derived precipitation from over a winter season. The annular pattern is primarily due to lack of “beam filling” at long ranges for shallow winter weather systems. The image of the right shows how this is reflected as a range bias with the radar-gauge comparisons. Figure courtesy of Daniel Michelson of Swedish Meteorological and Hydrologica Institute using data from the Finnish Meteorological Institute. Example of Correcting for Vertical Profile of Reflectivity Effects: Corrections for the vertical profile with range are now routinely made on a radar network basis. A case of an east-west stationary front. Image on left shows the fall off with range (see Fig. 9.33). Image on the right shows the range adjustment made to the data. Figure courtesy of Jarmo Koistinen, Finnish Meteorological Institute. Radar Reflectivity Factor and Rainfall Rate Relationships: A plot of a plethora of Z-R relationships from Battan (1973). The solid red line is that of Marshal-Palmer (1948, Gunn and Marshall, 1952). a b c d Impact of C and S Band Polarization Diversity on Quantitative Precipitation Estimation – Precipitation Maps: Dual-polarization radars can overcome attenuation, partial beam filling and partially block beams. Top figures show attenuation of the C Band (a) radar compared to S Band (b) at one instant. The bottom figures are precipitation accumulation over the period of the event and show remarkable similarities after correction using polarization diversity capability (see text and Fig. 9.37). Figure courtesy of Sudesh Boodoo of Envrionment Canada.) S1: Z‐R (Buffalo S Band) C3: KDP – R (WKR C Band) (solid blue line) S2: Z Dual Pol‐R (Buffalo S Band) (dashed line) Gauge (yellow diamonds) C2: Z – AC R (WKR C Band) C1: Z‐R (King City C Band) Impact of C and S Band Polarization Diversity on Quantitative Precipitation Estimation – Meteogram: A meteogram of accumulated rain from a gauge (yellow line with symbols) and three C Band (C1, C2, C3) and two S Band (S1, S2) estimates of the precipitation accumulation using a variety of polarization diversity techniques for one gauge site (see Fig. 9.36, point is about 7 km to south west of the center, also, see text for more details). Figure courtesy of Sudesh Boodoo of Envrionment Canada.