1 / 14

Initial Implementation of Super-Resolution Data on the NEXRAD Network

Initial Implementation of Super-Resolution Data on the NEXRAD Network. Dr. Sebastian Torres CIMMS/NSSL A presentation to the Data Quality Team June 15, 2007. Legacy Resolution. Super Resolution. Two elements of super-resolution data. What is Super Resolution?.

feng
Download Presentation

Initial Implementation of Super-Resolution Data on the NEXRAD Network

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript

  1. Initial Implementation of Super-Resolution Data on the NEXRAD Network Dr. Sebastian TorresCIMMS/NSSL A presentation to the Data Quality TeamJune 15, 2007

  2. Legacy Resolution Super Resolution Two elements of super-resolution data What is Super Resolution? • Legacy (existing) Resolution spatial sampling • Reflectivity: 1-km by 1-deg grid • Doppler: 250-m by 1-deg grid • Super Resolution spatial sampling • All moments: 250-m by 0.5-deg grid • Finer spatial sampling and smaller resolution volume lead to about 50% improvement in range of detection for mesocyclone and tornado signatures (Brown et al. 2002) Tornado outbreak in Oklahoma City9 May 2003 (Curtis et al. 2003)

  3. Elevation Azimuth Super resolution base data Super Resolution for NEXRAD Signal Proc. Algorithms • Super-resolution data scheduled for operational use on NEXRAD • Short-term goals - Phase I (ORDA Build 10) • Data used for visualization only • Produce legacy- and super-resolution data streams • ORPG algorithms ingest legacy-resolution data • Super-resolution data produced on lower-elevation scans • Higher likelihood of finding tornado signatures • Long-term goals - Phase II (ORDA Build >12?) • Data used by the algorithms • Produce super-resolution data stream only? • Not every algorithm may benefit from super-resolution data Z ORDA ORDA ORPG v Products w

  4. Legacy Resolution Super Resolution 1 deg Characteristics of Super-Resolution Data • Smearing due to antenna rotation is reduced using a data window • Effective beamwidth is 25% narrower than with legacy resolution (Torres and Curtis 2006) • Better spatial resolution due to smaller resolution volume • Reduced data quality due to data windowing • Errors of estimates are ~30% larger and NEXRAD Technical Requirements are not met

  5. Super Resolution Goals and Constraints • Produce stronger signatures of mesocyclones and tornadoes • Assure compatibility with current and future (planned) signal processing techniques • Assure compatibility with current Volume Coverage Patterns (ra, va, update times) • Adhere to CPU load and bandwidth limitations • Meet NEXRAD requirements for errors of estimates • Provide acceptable base data to algorithms

  6. M = 64 1 deg Pulse # 0 deg 0.5 deg 1.0 deg 1.5 deg 2.0 deg GCF Map bypass bypass bypass filter bypass Super Resolution in the ORDA • ORDA must produce base data with finer spatial sampling and resolution • Process overlapping 1-deg radials with data windowing sampled every 0.5 deg and no range averaging • For each range gate, M time-series data samples are weighted • … with von Hann window if clutter filtering is not needed • … with Blackman window if clutter filtering is needed

  7. Super Resolution in the ORDA • ORDA must produce unfolded reflectivity in the Doppler half of split cuts and must include the noise power in the metadata for the ORPG • This additional data are required in the ORPG to produce legacy-like data from super-resolution data • ORDA must double the throughput • Processing pipeline is minimally affected, but there are twice the number of radials in a super-resolution data volume scan • ORDA-ORPG transmission bandwidth must accommodate faster radial rates and additional data

  8. v1 v2 Z11 Z21 Z12 Z22 Z13 Z23 Z14 Z24 Super Resolution in the ORPG • ORPG algorithms expect data with legacy resolution and quality • Super-resolution data does not have the required resolution or quality for the algorithms • Must have both legacy and super-resolution data streams • Two instances of the velocity dealiasing algorithm • Radial recombination • Two super-resolution radials are recombined to form one legacy-resolution radial Zr 1 km vr 250 m 1 deg Super Resolution Legacy Resolution

  9. Doppler velocity v Radial 1PSD Radial 2PSD Acceptabledata quality v1 v2 Super Resolution in the ORPG • The radial recombination algorithm assumes a bimodal Gaussian spectrum model • Recombined data has legacy resolution and acceptable data quality • Recombined super-resolution data will not be exactly the same as the true legacy-resolution data

  10. ZBG ZBG ZBG ZBG ZBG ZBG ZBG Super Resolution in the ORPG • Radial recombination algorithm must deal with missing data and several special boundary conditions • Base data at the ORPG is censored and quantized! • Censoring can occur due to SNR thresholding or overlaid echoes ZBG is derived from a “best-guess” power (PBG) 0 ≤PBG < NSNRth Z11 Z21 ? Zr Z12 Z22 1 km Z13 Z23 Z14 Z24 1 deg

  11. Super-Resolution Reflectivity KCRI March 19, 2006

  12. Recombined Legacy-Resolution Reflectivity KCRI March 19, 2006

  13. True Legacy-Resolution Reflectivity KCRI March 19, 2006

  14. Summary • Super Resolution data produces enhanced mesocyclone and tornado signatures • Potential to detect weaker and/or more distant tornadoes • To meet long-term technical goals, NWS will implement and use Super Resolution with range oversampling techniques • Staged approach • Build 10: • Recommended super resolution with azimuthal radial recombination • Beyond Build 12: • Range oversampling techniques • Algorithms modified to ingest super-resolution data

More Related