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Ka-band Radar for GPM: Issues

Ka-band Radar for GPM: Issues

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Ka-band Radar for GPM: Issues

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  1. Ka-band Radar for GPM:Issues Toshio Iguchi Communications Research Laboratory The Global Precipitation Mission Planning Workshop University of Maryland College Park, Maryland, U.S.A.

  2. Ka-band Antenna Design

  3. Ka-band Planar Array Antenna: Test Model (1) 8-elements are selected (2) 35.5, 35.55, 35.6 GHz

  4. Assume constat Tx peak power & constant antenna gain S/N ∝ sqrt(number of samples)  freq. agility S ∝ Tx pulse width 1/N ∝ 1/(band width) ∝ Tx pulse width Range resolution ∝ Tx pulse width # of samples in Ka = # of samples in Ku for a matched beam Determining Factors of Detectability

  5. Sensitivity (detectability) Horizontal resolutions (Averaging horizontally) Vertical resolution Lowest observable height Matched beams (How many? All or partial?) Swath width (245 km or 100 km or less) Oversamples (125 m?) – data rate Range of observation (0-15 km?) – data rate Requirements and Compromises

  6. Refractive Index of Water and Ice Refractive index: m Permittivity: e

  7. Is Z=270 R^1.27 valid for weak rain? If k=0.23 R^1.05, R=10mm/h, and H=5km, attenuation is about 26 dB.This is the maximum R we can measure near surface. If R=1mm/h, attenuation =2.3dB. No problem to see to the surface. As long as rain is uniform, attenuation is not a limiting factor of detection of weak rasin. Detectability of Rain

  8. Example of Dual-Frequency Radar (X, Ka)

  9. Example of Dual-Frequency Radar (X, Ka) X-band radar reflectivity Ka-band radar reflectivity

  10. Example of Dual-Frequency Radar (X, Ka) X-band radar reflectivity

  11. Example of Dual-Frequency Radar (X, Ka) X-band radar reflectivity X-band radar reflectivity

  12. Example of Dual-Frequency Radar (X, Ka) X-band radar reflectivity

  13. Example of Dual-Frequency Radar (X, Ka) X Ka

  14. Phase Shifter and SSPA

  15. High sensitivity to measure weak rain and snow. High precision Increase of information by the combination of two channels Attenaution and rain rate are nearly proportional at 35GHz. Rain estimation independent of DSD. Separation of snow from rain. Vertical structure  microwave radiometer algorithm To what extent can we realize high sensitivity and high precision? What kind of science can we do with DPR data? What is the Ka-band radar for?

  16. Present Status of Ka-band Radar Design Phased Array System Increase in power consumption and mass Heat release Pulse compression too risky Doppler broadening → range sidelobe Increase in power consumption Matched beam realizable Sensitivity vs. swath width and vertical resolution What are the scientific requirements? Priority? (sensitivity, accuracy, resolution, swath)

  17. Frequency = 35.5GHz Sensitivity 11dBZ (S/N_e = 3 dB) or better Resolutions 4 km (horizontal), 250 m (vertical) Beams matched with Ku-band beams Swath 20 ~ 40 km Weight < 100 kg, Power < 100 W Original Requirements

  18. Attenuation correction essential needs k-Ze relationship utilizes the surface reference technique Conversion from Ze to R Needs Ze-R relationship Both relationships depend on: DSD phase state storm structure (non-uniform beam filling) Validation needed, but very difficult PR Rain Retrieval Algorithm

  19. Phased-Array system Matched beams No need for pulse compression Flexibility in scanning Independent unit Easy in test and inspection Basic Design of Ka-band Radar

  20. Ka-band Radar Development (Designing and testing the key components of the 35GHz radar) Examination of basic performance of hardware Overall configuration Pulse compression (FY2000) Designing of critical components and testing (FY2000) SSPA (2.5 W) Phase shifter (5 bits) Antenna (90 cm) Examination of basic performance of hardware (FY2001) BBM Evaluation of measurement performance (FY2000, 2001) Simulation Experiments Dual-frequency algorithm development CRL’s commitment

  21. Mass & Power Consumption Total Mass: 290 kg Phased-array system is heavy Heat sink Power consumption: 250 W Efficiency of SSPA is limited Dimensions: 1.0 ×1.0 ×0.5 m

  22. DF algorithm is essential for DSD estimation and liquid-ice separation DF algorithm requires a matched beam How well do two beams need matched? Matched beam requirement restricts # of pulses per beam for Ka-band Sensitivity or DF information? Scientific Requirements

  23. Rain Effective Z(Ze) is nearly idential up to 2 mm/h Attenuation (Ka) is about 10 times of attenuation (Ku) Detection of melting height Snow (ice) Ze of snow is different from Ze of rain Ze is nearly identical when particles are small Ze is different when particles are large (hail) Attenuation by absorption are negligible at both Ka, and Ku. At 35.5GHz, 1/22 of rain. At 13.8GHz, 1/48 of rain. Difference in scattering by large ice particles (hail). Difference in attenuation. Difference in Ze. Can we distinguish hail from rain? Interdependence of phase judgement and DSD estimation. Separation of ice from rain(Differences in Ka & Ku echoes)

  24. DPR algorithm uses attenuation difference. Non-uniform rain decreases apparent attenuation. underestimates rain rate. overestimates large drops in DSD. Non-uniformity of rain and beam mismatching may overturn the basic assumptions in dual-frequency algorithms. How well can we match beams? 0.2°(1400m)? Effects of beam mismatch? needs simulations. Non-Uniform Rain and Beam Matching

  25. Engineering Issues in Ka-band Radar Development Sensitivity pulse compression Vertical resolution (Is 500m res. acceptable?) Mass and power consumption (heat release) Data rate Sampling interval 125 m oversample? On-board processing surface detection data compression No. of bits for each echo datum (TRMM uses 8 bits, 0.38 dB res.) Mount: interfarence with TMI’s field of view? Accuracy of beam matching

  26. Present Status of Ka-band Radar Studies for Atmos-A1 Designing with a phased-array system Increasing # of array elements increases total power consumption and mass Mass and power consumption (heat release) are the issues Possibility of 500-m vertical resolution To increase sensitivity by 6 dB Almost no degradation of V resolution except near nadir Power consumption and mass will increase Matched beam requirement Trade-off between sensitivity and swath width Needs scientific compromise Provides multiple observation modes? (Confusing?)

  27. Intrinsic Difficulties in Rain Estimation by TRMM PR Sensitivity (0.5 mm/h) Accuracy Uncertainty in DSD and phase of hydrometeor Attenuation correction & Z-R conversion Low sampling frequency: 1/(3 days) Observation coverage • Addition of 35GHz radar • Dual-freq. algorithm • GPM • Core satellite. • (Atmos-A1) • 35 deg => 70 deg • (>95% of precipitation)

  28. Hardware Specifications Mass Power Consumption Sensitivity Accuracy Science issues Dual-Frequency Algorithm Combining DPR and TMI Information Issues

  29. Issues Sensitivity Pulse compression Vertical resolution (500 m acceptable?) Mass and power consumption (& heat release) Data rate Sampling interval -- 125 m over sample (?) On-board processing Quantization of data Mount -- Interference with TMI field of view

  30. Need for 35GHz Radar Measurable range by 35GHz radar Measurable range by 14GHz radar 35 GHz-band radar is needed to measure weak rain in mid and high latitude regions. Frequency mid and high latitude rain tropical rain } (weak rain) Rain Rate (strong rain) New measurable range by the addition of 35GHz radar

  31. High sensitivity by the use of high frequency (11 dBZ (target) or RR=0.2 mm/h) Discrimination between rain and snow by attenuation difference Accurate estimation of rainfall rate from attenuation difference in common range (2-15 mm/h) Merits of Dual-Frequency RadarMeasurement 14GHz radar beam 35GHz radar beam strong scattering weak scattering small attenuation in snow small attenuation in snow small attenuation in rain large attenuation in rain scattered wave with large attenuation scattered wave with small attenuation

  32. Possible Scan Patterns Ku footprint Ka footprint (Matched with Ka) Ka footprint (Interlaced) Ka-scan (interlaced) Ku-scan Ka-scan (Matched with Ku) 125 km (25 beams) 245 km (49 beams)