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Search in: Search Results second seconds Settings Shift Back to top Slide Text Space SUBMIT ALL submit all SUBMIT submit Submit Unmute volume principles of doppler meteorological radar super resolution base data generation instructor: andy wood review lesson take your time and review the lesson content provided in this presentation. review lesson technical problems? if you encounter any technical problems with this lesson, please contact the rac team directly by e-mail at: nws.wdtd.rachelp@noaa.gov technical problems? complete the quiz at the end of this lesson, there is an embedded quiz. complete this quiz by selecting the best answer for each question. you need to correctly answer 70% of the quiz questions to receive completion credit in the lms. complete the quiz course completion review lesson review lesson complete the quiz technical problems? technical problems? introduction in order for nws forecasters to receive credit for this course in the nws learning center, you will need to take the following steps roadmap learning objectives identify the operational impacts of the signal processing techniques used to produce super resolution base data why does super-res matter? legacy resolution super resolution (super-res) super resolution signal processing super resolution (super-res): 0.5° azimuth for legacy base data on split cuts how to narrow azimuthal resolution to 0.5°? overlapping radials data windowing “effective” beamwidth = physical beamwidth (single pulse) & antenna movement beamwidth ~1° for a single pulse effective beamwidth effective beamwidth is ~1.4° overlapping radials overlapping radials: change defined center of each radial 1.5° effective beamwidth is still 1.4° choosing new radialcenters not enough data windowing: rectangular data windowing apply weighting function to pulses that comprise base data for a radial rectangular window: all pulses have equal weight data windowing: von hann window with pulses close to center more weight than pulses away (von hann) narrows effectivebeamwidth increases varianceof estimate;data noisier super-res base data quality tradeoffs tradeoff #1 for narrower effective beamwidth: visual detection of smaller features at longer ranges vs. more error in estimate sr base products visually noisier than legacy tradeoff #2: sr base data must be “degraded” for input to algorithms summary wsr-88d specs: single pulse beamwidth: 1° effective beamwidth: 1.4° overlapping radials: change radial center locations insufficient by itself to reduce effective beamwidth windowing techniques: rectangular window (all pulses have same weight) von hann window (pulses near center weighted more) end result: non-rectangular window allows for narrower beamwidth super resolution data 0.5° data noisier because of windowing incorrect you did not select the correct response. continue continue continue continue continue continue correct that's right! you selected the correct response. continue continue continue continue continue continue true true true true true true false false false false false false question #1 of 2 super resolution base data are generated by the signal processor at the radar data acquisition unit (rda). incorrect incorrect: clutter filtering does not narrow the effective beamwidth continue continue continue continue continue continue incorrect incorrect: overlapping radials does not narrow the effective beamwidth continue continue continue continue continue continue incorrect incorrect: velocity dealiasing is applied after the super resolution data are built continue continue continue continue continue continue correct correct. continue continue continue continue continue continue question #2 of 2 _____ is the technique used to narrow the effective beamwidth to a 0.5 degree azimuth for super resolution, resulting in base data that are noisier. windowing windowing windowing windowing windowing windowing velocity dealiasing velocity dealiasing velocity dealiasing velocity dealiasing velocity dealiasing velocity dealiasing overlapping radials overlapping radials overlapping radials overlapping radials overlapping radials overlapping radials clutter filtering clutter filtering clutter filtering clutter filtering clutter filtering clutter filtering roadmap <Document xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xmlns:xsd="http://www.w3.org/2001/XMLSchema"> <Content> <Block> <Style LeadingMargin="0" FirstLineMargin="0" Justification="Left" ListLevel="1" LineSpacingRule="Multiple" LineSpacing="20" SpacingBefore="4.32" SpacingAfter="0"> <ListStyle ListType="None" ListTypeFormat="Plain" Start="0" Color="#000000,00" BulletChar="•" BulletFont="Arial"> <BulletPicture Size="0x0" /> </ListStyle> </Style> <Span Text=" "> <Style FontFamily="+minor" FontSize="11" FontIsBold="False" FontIsItalic="False" FontIsUnderline="False" FontIsStrikeout="False" ForegroundColor="#BABBBA" Elevation="Normal" DisplayCase="AsIs" LinkColor="#BABBBA" /> </Span> <Span Text="Welcome to this lesson on super resolution base data generation."> <Style FontFamily="+minor" FontSize="11" FontIsBold="False" FontIsItalic="False" FontIsUnderline="False" FontIsStrikeout="False" ForegroundColor="#464646" Elevation="Normal" DisplayCase="AsIs" LinkColor="#464646" /> </Span> <Span Text="Let’s get started!"> <Style FontFamily="+minor" FontSize="11" ForegroundColor="#464646" LinkColor="#464646" /> </Span> </Block> </Content> </Document> <Document xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xmlns:xsd="http://www.w3.org/2001/XMLSchema"> <Content> <Block> <Style LeadingMargin="0" FirstLineMargin="0" Justification="Left" ListLevel="1" LineSpacingRule="Multiple" LineSpacing="20" SpacingBefore="4.31999969" SpacingAfter="0"> <ListStyle ListType="None" ListTypeFormat="Plain" Start="0" Color="#000000,00" BulletChar="•" BulletFont="Arial"> <BulletPicture Size="0x0" /> </ListStyle> </Style> <Span Text=" Here is the complete roadmap for the entire “Principles of Doppler Weather Radar” topic of RAC. You are currently in the Base Data Generation section of this topic."> <Style FontFamily="Open Sans" FontSize="11" FontIsBold="False" FontIsItalic="False" FontIsUnderline="False" FontIsStrikeout="False" ForegroundColor="#464646" Elevation="Normal" DisplayCase="AsIs" LinkColor="#464646" /> </Span> </Block> </Content> </Document> <Document xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xmlns:xsd="http://www.w3.org/2001/XMLSchema"> <Content> <Block> <Style /> <Span Text=" This lesson has one learning objective. Please take a moment to read it over and advance to the next slide when you are ready."> <Style FontFamily="+minor" FontSize="11" /> </Span> </Block> </Content> </Document> <Document xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xmlns:xsd="http://www.w3.org/2001/XMLSchema"> <Content> <Block> <Style /> <Span Text=" While this lesson on super resolution base data generation is relatively short, some forecasters may wonder why we discuss this topic in RAC. Knowing how the WSR-88D generates super-res data, the tradeoffs inherent in the process, and other consequences that come along with it can help forecasters better interpret these data in all kinds of meteorological situations. So, lets dive in!"> <Style FontFamily="+minor" FontSize="11" /> </Span> </Block> </Content> </Document> <Document xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xmlns:xsd="http://www.w3.org/2001/XMLSchema"> <Content> <Block> <Style /> <Span Text=" Super resolution data are defined as having a 0.5° azimuth. This resolution is only available for legacy base data on the Split Cut elevations. The upgrade to super resolution was based on signal processing techniques, not on new hardware. There are two signal processing techniques used to narrow the azimuthal resolution from 1.0° degree to 0.5°, overlapping radials and data windowing. 
"> <Style FontFamily="+minor" FontSize="11" /> </Span> </Block> <Block> <Style /> <Span Text=" In order to understand this approach, let’s start with the different types of beamwidth. The physical beamwidth of ~1.0° presented previously is based on the antenna being stationary. Antenna motion produces a smearing of the data which leads to a concept known as the effective beamwidth. "> <Style FontFamily="+minor" FontSize="11" /> </Span> </Block> </Content> </Document> <Document xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xmlns:xsd="http://www.w3.org/2001/XMLSchema"> <Content> <Block> <Style /> <Span Text=" In order for a pulse to be used for the base data estimate for a radial, the beam centerline must be somewhere within that radial. In this example, each dot represents the location of the beam centerline for a single pulse. 11 pulses fall within this simplified 1° radial in this example. As the antenna rotates, the pulse with a centerline that is just on the inside edge of this radial still has a physical beamwidth of 1°. The beam samples a volume that is both inside and outside the radial in these locations. The pulse only samples the radial’s contents when the center of the pulse is the center of the radial. This process of including pulses that capture base data outside the radial increases the physical beamwidth to what we call the effective beamwidth. For the WSR-88D, the effective beamwidth is about 1.4°. "> <Style FontFamily="+minor" FontSize="11" /> </Span> </Block> </Content> </Document> <Document xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xmlns:xsd="http://www.w3.org/2001/XMLSchema"> <Content> <Block> <Style /> <Span Text=" The overlapping radials technique simply changes the definition of the center of each radial. The radial centers for legacy resolution are 0.5°, 1.5°, 2.5°, etc. For super resolution data, the centers change to 0.25°, 0.75°, 1.25°, 1.75°, etc. However, since the number of pulses per radial cannot decrease and the effective beamwidth is still 1.4°, the sampled volume outside of each 0.5° radial continues to be too large. Simply choosing new radial centers is not sufficient. The effective beamwidth must also be narrowed."> <Style FontFamily="+minor" FontSize="11" /> </Span> </Block> </Content> </Document> <Document xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xmlns:xsd="http://www.w3.org/2001/XMLSchema"> <Content> <Block> <Style /> <Span Text=" "> <Style FontSize="11" /> </Span> <Span Text=" The radar can narrow the effective beamwidth using a signal processing technique called data windowing. By applying a weighting function to the pulses included in a particular radial, data windowing can give more value to some pulses than others. If all pulses are given the same weight, that technique would be called a rectangular window. The graphic on the slide demonstrates what a rectangular window looks like. "> <Style FontFamily="+minor" FontSize="11" /> </Span> </Block> </Content> </Document> <Document xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xmlns:xsd="http://www.w3.org/2001/XMLSchema"> <Content> <Block> <Style /> <Span Text=" A rectangular window will not reduce the effective beamwidth. Instead, you need to use a weighting function that gives more emphasis to pulses that collect data towards the center of the radial. This window is called a Von Hann window. So, pulses with centers near the center of the radial get more weight. Pulses collected near the edges get less weight. This technique reduces the effective beamwidth, but also introduces more variance (or error) in the estimate. The error results due to some pulses being overemphasized while others are under emphasized. The end result is super resolution products are noisier than those that have legacy resolution. "> <Style FontFamily="+minor" FontSize="11" /> </Span> </Block> </Content> </Document> <Document xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xmlns:xsd="http://www.w3.org/2001/XMLSchema"> <Content> <Block> <Style /> <Span Text=" There are two primary tradeoffs related to the quality of super resolution base data. The first tradeoff balances the ability to detect smaller features at further ranges with the increased errors that result. Super resolution base data are visually noisier than legacy resolution data. The second tradeoff with super resolution data is that many of the RPG algorithms were not designed to ingest super resolution base data. As a result, super resolution data must be “degraded” back to legacy resolution before they are input into these algorithms."> <Style FontFamily="+minor" FontSize="11" /> </Span> </Block> </Content> </Document> <Document xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xmlns:xsd="http://www.w3.org/2001/XMLSchema"> <Content> <Block> <Style /> <Span Text=" In summary, the WSR-88D has a physical beamwidth of 1 degree. However, antenna rotation makes that an effective beamwidth of 1.4 degrees. To produce super resolution base data, first the overlapping radials technique is used to change the radial center locations. However, this change isn’t sufficient by itself. The radar must also apply a windowing technique that puts more weight on pulses collected near the center of the radial. By combining the overlapping radials and windowing techniques, super resolution data with an azimuth of 0.5 degrees are possible. Super resolution data contain more noise than legacy resolution products and must be processed back to legacy resolution before used as input for many RPG algorithms."> <Style FontFamily="+minor" FontSize="11" /> </Span> </Block> </Content> </Document> <Document xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xmlns:xsd="http://www.w3.org/2001/XMLSchema"> <Content> <Block> <Style LeadingMargin="0" FirstLineMargin="0" Justification="Left" ListLevel="1" LineSpacingRule="Multiple" LineSpacing="20" SpacingBefore="4.31999969" SpacingAfter="0"> <ListStyle ListType="None" ListTypeFormat="Plain" Start="0" Color="#000000,00" BulletChar="•" BulletFont="Arial"> <BulletPicture Size="0x0" /> </ListStyle> </Style> <Span Text=" Here is the complete roadmap for the entire “Principles of Doppler Weather Radar” topic of RAC. You are currently in the Base Data Generation section of this topic."> <Style FontFamily="Open Sans" FontSize="11" FontIsBold="False" FontIsItalic="False" FontIsUnderline="False" FontIsStrikeout="False" ForegroundColor="#464646" Elevation="Normal" DisplayCase="AsIs" LinkColor="#464646" /> </Span> </Block> </Content> </Document>