1 / 81

Radar Detection of Shallow Weather and Orographic Phenomena

Radar Detection of Shallow Weather and Orographic Phenomena. Paul Joe MSC Basic Radar 2010 20100404. Module Objective. 1. This module briefly explores “radar meteorology” issues of low level weather detection in a generic way. 2. Radar meteorology in complex terrain. Outline.

avon
Download Presentation

Radar Detection of Shallow Weather and Orographic Phenomena

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. Radar Detection of Shallow Weather and Orographic Phenomena Paul Joe MSC Basic Radar 2010 20100404

  2. Module Objective 1. This module briefly explores “radar meteorology” issues of low level weather detection in a generic way. 2. Radar meteorology in complex terrain

  3. Outline • Some “back of envelope calculations” of key elements • Typical reflectivities of rain, drizzle, fog, snow (detection issue) • Beam height (detection issue) • Beam width (quantitative and detection issues) • Sensitivity (detection issue) • Meteorology • Drizzle • Lake Effect Snow • Orographic Precipitation

  4. Low Level Phenomena Detectable by Radar • Meteorological Targets • Precipitation (Rain, Snow, Hail, Drizzle) • Lake Breezes, Convergence Lines, Gust fronts, cold pools • Index of Refraction/Humidity • Turbulence (Bragg scattering) • Ground Clutter (not discussed here) • Building, Mountains, Forests • Hard Targets (not discussed here) • Wind turbines, Cars, ships, airplanes, space debris • Biological Targets (not discussed here) • Insects, birds, bats • Electro-magnetic Targets (not discussed here) • Other radars, RLANs, Sun, second trip echoes • Other • Forest fires • Sea Clutter Romanian Gust Front

  5. General Comments – Low Scanning • Wide variety of phenomena and intensity of targets • Turbulence (too weak) to Mountains (very intense) • From very weak to very strong (-30 dBZ to 95 dBZ) • Different Doppler signatures • Some have 0 velocity • Some have aliased velocity (> Nyquist) • Advanced uses of weather radar • VDRAS – variational doppler radar assimilation system • Refractivity retrieval – use of ground clutter echoes • Quantitative Precipitation Estimation • Need low level scanning • Accurate at ranges < 80-100km • Commonality • Limited range! • Low echo strength (generally), Low height of weather, radar sensitivity is an issue

  6. Drizzle Some Radar Examples

  7. Germany Example 1 Drizzle in surface observations BUT NO/Little RADAR DATA Drizzle reported in surface observations but no radar echoes. Lang, DWD

  8. Germany Example 2 Drizzle (mm/h) and very few echoes Lang, DWD

  9. Drizzle in Finland! • Why was drizzle observed in Finland but not Germany? • Why is the drizzle observed only around the radar? • Why is the reflectivity pattern stronger near the radar and decreases away from the radar? • Why is there a range limit to see drizzle? Saltikoff, FMI

  10. Minimum Detectable Signal Concept

  11. Probability Distribution of Reflectivity with Range (not important for this discussion). Function of Wx. The Radar Equation P = C Z r2 Minimum Detectable Signal (constant power) MDS can expressed as a noise temperature or a power measurement but for meteorologist it more useful to express as reflectivity at a particular range. Typically, -1 dBZ at 50 km. Minimum Detectable SignalThe detection threshold (as a function of range). Reflectivity [dBZ] Range [km]

  12. Reflectivity Factor - Linear Some Radar Considerations P = C Z r2 P = power, C = radar constant, r = range Z = N D6 [Z] = mm6/m-3 dBZ = 10 log Z

  13. Power Range Reflectivy Range Radar Equation and MDSPmin = C Zmin(r) r2 • The Radar measures “P” – power received • The Radar Equation converts P to Z for a given range (r) • Radar Equation accounts for expanding beam with range (1 /r2) • Sensitivity (or MDS) is a certain power level • Just above the noise (hsssssss) level • In terms of P (power), it is a constant • In terms of Z (reflectivity), it is a function of range (1 /r2) • A limitation for long range detection of weak echoes is the radar sensitivity! • If the reflectivity of the target is below MDS then the radar does not detect it! • Beware of artificial MDS!The display of the radar data may be thresholded! Some data may not be displayed!

  14. Homework QuestionEcho Power

  15. A Drizzle Calculation Radius of a drizzle drop ~= 100 microns Rainrate of drizzle ~= 1 mm/h Fall speed ~= 1 cm/s Therefore, Number of drops ~= 28,000 m^-3 Reflectivity ~= -5 dBZ Can your radar see drizzle? How far can you see drizzle from the radar?

  16. -5dBZ So, how far can you see drizzle (-5dBZ)?Or anything else? P = C Z r2 Minimum Detectable Signal (power) ~ 25km

  17. 7dBZ Typical Drizzle reflectivity Data in this shaded area is thresholded (not displayed)! ~ 25km Can you see drizzle – part 2?The Artificial MDS Situation

  18. Typical Radars Reflectivity vs Range for Constant Power (1/r2) Where does your radar fit on this diagram?

  19. Survey Question about your Radars? How well do you know your radars? What is the minimum value that you have seen on your radar and at what range? Put a check in as many boxes as you want! Are you limited by an artificial MDS?

  20. Beam Propagation Re-visited

  21. Beamheight Considerations

  22. Note: the lower the beam the longer the range for detection ability! Beam totally overshoots the weather beyond this range! No detection at all! Non-uniform beamfilling Shallow Weather The weather is detected but the beam is not filled beyond this range, so reflectivities are quantitatively underestimated from this range and beyond OvershootKey Concept! 0.5o

  23. 1 km Drizzle is round! Note: Colour scales are different! Drizzle dBZ dBZ ZDR Drizzle is due to warm rain process. Slow growth which results in small drops (0.1 mm, 1 mm/h) Saltikoff, FMI

  24. Survey: How well do you know your radars?What is the lowest elevation angle of your radars?

  25. Summary: Drizzle in Finland! • Why was drizzle observed in Finland but not Germany? Thresholded! • Why is the drizzle observed only around the radar? Sensitivity • Why is the reflectivity pattern stronger near the radar and decreases away from the radar? Beamfilling • Why is there a range limit to see drizzle? ~80-100km, function of sensitivity, beamfilling, depth of the drizzle! Saltikoff, FMI

  26. Germany Example 3 5-6°C Drizzle ,, Unusual widespread drizzle from cloud echoes aloft. At surface only few echoes above 1dBZ. Note: change in threshold for DWD, see more drizzle! Hamburg Lang, DWD

  27. Major Factors for Detection • Radar Sensitivity • Target Reflectivity/Radar MDS combination • Overshoot • Lowest Angle of Radar/Height of weather / Earth Curvature combination • Beam filling (quantitative) • Weather is too shallow or too low • Beam is very broad • Thresholding • Artificial MDS = Minimum Displayed Signal*

  28. FOG Can the radar see fog?

  29. FogSpecial Cloud/Fog Radar (35 GHz or Ka Band) Non-operational dBZ 10 km Drop Size Distributions Fog has drop sizes from 10 to 30 microns, so very low reflectivities. An operational radar has a sensitivity as -8 dBZ at 50 km. What is the controlling factor of detecting fog for this radar? - Sensitivity? or elevation angle? Or Artificial MDS (color table?)

  30. Snow

  31. Beamheight AgainQuantitative measurements (Advanced Material)

  32. Partial Beam Filling Range bins that are partially beamfilled, decreasing reflectivity with range! 0.5 degree

  33. Non-uniform beamfilling Shallow Weather Question: What do you think the reflectivity will look as a function of range? 0.5o dBZ Range

  34. Vertical Profile of Snow Function of Range 2. The same vertical profile as observed by radar at increasing range due to beam filling, beam broadening (smoothing) and Earth curvature (can’t see lowest levels)! 1. Snow originates aloft but grows as it falls.

  35. Quantitative Impact of Beamfilling Note the fall off of values with range. This is NOT attenuation to which this is commonly attributed. It is a beam filling effect! Michelson, SMHI

  36. Impact of Beamwidth / Beamfilling30 day Accumulation 1.0o (blue) 0.65o (no blue) Example of the impact of beamwidth or beamfilling on quantitative precipitation estimation. One radar is 0.65o and the rest are 1.1o beamwidth radars. Smaller beamwidth means less beamfilling problems with range and farther quantitative reflectivity information. Patrick, EC

  37. Applying the Correctionaka Vertical Profile Correctionaka Range Correction Koistinen, FMI

  38. Orographic

  39. Mountain Top Radars Germann, MCH

  40. Time-Height Temperature Freezing Level from Radiosondes July 2008 Payerne March 2008 Payerne Freezing Level and Mountain Sited Radars Most of the time, the radar sees snow!

  41. Valley Radar Pemberton Winter Olympic Park Blackcomb Whistler Mtn H99 Squamish

  42. Distance Range to Terrain VVO Whistler Squamish Callaghan Callaghan Whistler Squamish Elevation Angle Snow Azimuth North East South West North

  43. Whistler Doppler Weather Radar

  44. Another View Dave Murray Downhill Start VVO

  45. What is this? Would you see it on a mountain top radar?

  46. Blocked flow (downslope winds) means Intense precipitation is on the slope and not on mountain peak Precipitation: the intense precipitation is on the slope. Doppler velocity: Blue means air is moving to the left or downslope

  47. How many low level jets do you see? Do you see convergence?

  48. Remember RABT = Red Away Blue Toward (except in Switzerland)

  49. Why is there a hole in the data? Would you see this on a mountain top radar?

  50. Summary • Shallow Weather • Focus on drizzle as an example to explain detectability and measurability • Observability is a function of the radar too (MDS, beamheight, beamwidth) • A few simple but key calculations to explain (not calibration, not attenuation) • A little insight into “radar meteorology” • A few case examples • Drizzle, snow, lake effect snow, orographic

More Related