List the properties of the radar or meteorological targets that modify the decorrelation time. Describe how these properties affect the decorrelation time.

1.) Wavelength (λ) : shorter wavelengths means particles can travel less distance to re-shuffle 2.) Breadth of particle size distribution, N(D) -- If all drops same size, all particles fall at same speed or terminal fall speed (V t ) V t = aD b (a, b constant), and sample volume would decorrelate slowly 3.) Turbulence : more turbulence results in more small-scale mixing, re-shuffling of particles 4.) Others such as range averaging and antenna rotation rate

Define the equivalent radar reflectivity factor (z e or Z e ) and explain why one uses this parameter in the radar range equation.

z e /Z e is the reflectivity factor that a radar would measure if all the scatterers in the pulse volume were small, spherical water droplets in the Rayleigh scattering regime. Must assume : 1) Rayleigh conditions (a. sphere, b. D << λ) 2) Liquid water Note : z = z e --> liquid (rain) z ≠ z e --> ice Reasons for use in the radar range equation : 1) The radar can't always determine hydrometeor phase (ice vs. liquid) 2) The dielectric constant |K| 2 varies with phase and type (e.g., graupel vs. hail) 3) Z e assumes liquid water droplets (with a standard |K| 2 ) so that reflectivity values are consistent and comparable across hydrometeor types 4) Mixed-phase or partially melted particles complicate interpretation; Z e simplifies that 5) It's essential for applying standard Z-R relationships used in quantitative precipitation estimation

Define the noise power, signal-to-noise ratio (SNR), dynamic range, saturation power, minimum detectable signal (MDS) power, minimum detectable reflectivity (MDR), and saturation or maximum detectable reflectivity. Noise power

The amount of unwanted signal power present in the received signal, hindering the ability to detect the target

Define the noise power, signal-to-noise ratio (SNR), dynamic range, saturation power, minimum detectable signal (MDS) power, minimum detectable reflectivity (MDR), and saturation or maximum detectable reflectivity. Signal-to-noise ratio (SNR)

The ratio of the power of the desired signal (from a target) to the power of the unwanted noise signal

Define the noise power, signal-to-noise ratio (SNR), dynamic range, saturation power, minimum detectable signal (MDS) power, minimum detectable reflectivity (MDR), and saturation or maximum detectable reflectivity. Dynamic range

Difference between strongest (maximum) and weakest (minimum) signal powers that can be detected by receiver (80-90 dB dynamic range typical)

Define the noise power, signal-to-noise ratio (SNR), dynamic range, saturation power, minimum detectable signal (MDS) power, minimum detectable reflectivity (MDR), and saturation or maximum detectable reflectivity. Saturation power

The maximum received power (typically -30 dBm to -20 dBm)

Define the noise power, signal-to-noise ratio (SNR), dynamic range, saturation power, minimum detectable signal (MDS) power, minimum detectable reflectivity (MDR), and saturation or maximum detectable reflectivity. Minimum Detectable Signal (MDS) power

The weakest signal a radar receiver can reliably process and produce a useful output (MDS of a typical radar receiver is -110 to -120 dBm)

Define the noise power, signal-to-noise ratio (SNR), dynamic range, saturation power, minimum detectable signal (MDS) power, minimum detectable reflectivity (MDR), and saturation or maximum detectable reflectivity. Minimum Detectable Reflectivity (MDR)

The lowest level of radar signal return, or reflectivity, that a radar system can reliably detect and distinguish from background noise

Define the noise power, signal-to-noise ratio (SNR), dynamic range, saturation power, minimum detectable signal (MDS) power, minimum detectable reflectivity (MDR), and saturation or maximum detectable reflectivity. Saturation/Maximum Detectable Reflectivity

The strongest signal received by the radar, indicating the highest concentration of precipitation particles or other targets within the radar's field of view

Describe the physical quantity called “rain rate” (R) in your own words.

Measure of the intensity of rainfall by calculating the amount of rain that would fall over a given interval of time if the rainfall intensity were constant over that time period. Usually expressed in terms of depth (length) per unit time (mm h -1 ) To calculate: # of drops hitting per unit area per unit time) * (drop volume)

In a power law relationship between z and R of the form z=aR b , identify and explain the variability of the parameters “a” and “b” and their dependence on the drop size distribution (DSD).

"a" and "b" vary with: 1) DSD --> If DSD has more large drops , higher reflectivity (z) for (R) ; higher "a" and often lower "b" If DSD has mostly small drops , lower z for the same R ; lower "a", possible higher "b" 2) Rain Type --> Convective rain (more large drops, higher "a", lower "b") Stratiform rain (smaller drops, lower "a", higher "b") 3) Altitude and Melting Layer --> Above the freezing level, rain can turn into snow/graupel ; radar sees different reflectivity without corresponding rainfall ; invalidates Z-R unless corrected

Explain why there are multiple z-R relationships in the literature (e.g., the extreme case of a plot of 69 z-R relationships from Battan.

"a" (especially) and "b" are not constant but vary depending on the rain DSD and other factors. Note most z-R relations empirically derived between radar and rain guage. So, large # relations is reflective of sources of error estimating R from z.

List and describe the potential sources of error in implementing a radar reflectivity based estimation of rain rate (z-R).

1) Variations in DSD geographically, seasonally, by storm type and position within storm (e.g., convective vs. stratiform rain) 2) Power calibration errors (incorrect loss) 3) Attenuation from atmosphere, cloud, precipitation, wetted radome (incorrect loss) 4) Horizontal winds (displace drops as fall from seen by radar to ground) 5) Bright band (reflectivity enhancements in the melting layer) 6) Evaporation (of drops as fall to ground in sub-saturated environment) 7) Beam blockage (partial to complete) (incorrect loss) 8) Ground clutter or anomalous propagation (AP) (artificial enhancement of z) 9) Vertical air motion (changes actual rain water flux and hence rain rate!) ; 1. Downdraft --> z-R underestimates 2. Updraft --> z-R overestimates 10) Incomplete beam filling 11) Rain rate gradients

Describe the radar “bright band.”

Much of the precipitation that falls to the ground as rain starts aloft as precipitation ice (e.g., snow) that grows through cold cloud or ice processes (e.g., deposition, aggregation). Snow melts into rain, which results in an interesting transition seen on radar. Specifically in a relative maximum in the radar observed effective reflectivity factor (z e ) or so-called bright band .

Identify the type of precipitation in which bright bands are most common and explain physically why.

Stratiform precipitation , because: 1) Melting of snow into rain (key physical driver) -- As descending snowflakes melt, they become partially melted, water-coated ice particles that have a very high radar reflectivity due to the strong dielectric constant of liquid water , leading to a spike in radar reflectivity (the bright band 2) Slow, layered descent = Time to form bright band -- Stratiform rain is steady and widespread characterized by gradual vertical motion -- The slow descent gives snowflakes time to grow and melt gradually , enhancing the bright band signature 3) Dominated by aggregates --> strong melting signal -- Snow in stratiform clouds is often made of aggregates (clumps of crystals) --These aggregates melt unevenly , producing partially melted particles with large radar cross-sections -- Radar sees this as a very strong return , more so than fully frozen or fully melted particles

Describe the relationship between VIL and severe convective weather and explain the physical origin(s) of this relationship.

Relationship between VIL and severe convective weather : Higher VIL often indicates stronger updrafts , which are necessary to support large amounts of water and ice aloft Physical origin(s) of this relationship : -- Stronger updrafts in severe storms suspend more hydrometeors (rain, snow, hail) in the vertical column --> results in higher VIL -- Hail growth requires sustained, intense updrafts to hold hailstones aloft while they grow --> high VIL often corresponds with hail-producing storms -- In wet microbursts , large amounts of precipitation (high VIL) can rapidly descend and pull air down with it, causing damaging winds

List and explain the various sources of error for VIL.

Gaps in vertical radar coverage due to inadequate spacing of elevation angle tilts in PPI volume Beam broadening with range Incomplete vertical storm coverage (i.e., not topping storm or cone of silence) Varying particle size distribution and hydrometeor types in the vertical Presence of hail (can be beneficial for hail detection, resulting in larger VIL)

Explain what a WSR-88D Volume Coverage Pattern (VCP) is in general and explain its impact on vertically integrated quantities like VIL.

A WSR-88D Volume Coverage Pattern (VCP) defines how the WSR-88D radar scans the atmosphere: -- Which elevation angles are used -- How often it scans -- How quickly a full volume is completed Impact on vertically integrated quantities like VIL : 1) Vertical sampling resolution -- More elevation angles --> better vertical resolution of reflectivity data 2) Update frequency -- Rapid VCPs (VCP 12) complete a scan every 4-5 minutes -- Slow VCPs (VCP 31) take 10+ minutes 3) Beam geometry and Overshooting -- Higher elevation angles can overshoot shallow storms or low-level hydrometeors (especially far from the radar) -- Some VCPs are designed to focus on lower altitudes , improving VIL in shallow stratiform or winter weather

Explain why VIL might vary geographically and explain the impact on the operational use of VIL to diagnose severe storms.

Varying geographically : 1) Environmental differences -- Temperature and moisture profiles affect storm structure and how much liquid water or ice is suspended -- In humid, warm environments , storms can contain more liquid water --- higher VILs are "normal" and may not signal severe weather -- In cooler or drier environments , storms have less water content, so lower VIL values can still be associated with severe storms 2) Topography and radar beam overshooting -- In mountainous or high-altitude areas, radar beams often overshoot low-level storm features, missing part of the hydrometeor column --> VIL underestimation Impact on Operational Use of VIL : 1) Thresholds must be adjusted regionally -- Operational meteorologists must calibrate VIL expectations based on the region's climatology 2) Must consider environment -- VIL values should always be interpreted in context of temperature, moisture, and storm type -- Example : A high VIL in Florida ≠ same severe risk as the same VIL in Colorado 3) Works best when combined with other data like VILD, reflectivity profiles , and environmental soundings

Describe the key functional difference(s) between the hail kinetic energy flux (used to calculate the severe hail index) and the liquid water content (used to calculate VIL) as a function of Z. (Hint: You do not need to memorize the hail kinetic energy flux equation verbatim to answer. It’s given.)

-- VIL estimates the total mass of liquid (and equivalent melted ice) in the atmospheric column by vertically integrating liquid water content derived from reflectivity Z -- Liquid water content/VIL gives a broader, mass-based view of hydrometeors -- Hail kinetic energy flux estimates the kinetic energy transferred by falling hailstones , which is a function of both mass and velocity -- Hail KE flux is more sensitive to large reflectivity values (e.g., from large hail)

If given the equations for the hail kinetic energy flux and the severe hail index (SHI), describe the form and purpose of the reflectivity, W(Z), and height, W t (h), weighting functions that are used in SHI to estimate the severity of hail. Reflectivity Weighting Function, W(Z)

-- Amplifies the contribution from large reflectivity values , which are strongly associated with large hailstones -- Recognizes that hailstone kinetic energy increases sharply with size --- not just the number of particles

Define the phase angle of a radar wave.

Φ ; Fraction of a full wavelength (angle) a particular point is from nearest reference point , measured in radians or °

Identify the key components of a Doppler radar system (e.g., transmitter, receiver mixer, modulator, computer/signal processor, locking mixer, COHO, STALO, phase detector, IF amplifier), explain how these components function to transmit, receive, and process electromagnetic radiation in order to produce a Doppler frequency shift (and hence a Doppler radial velocity). Transmitter

-- Source of electromagnetic radiation (e.g., power) emitted by a radar -- Range of power: 10 5 W -- 10 6 W -- Three primary types: Magnetron, Klystron, Solid State Function for producing a Doppler frequency : The modulator activates the transmitter to send out a pulse

Explain in your own words the terms “Unambiguous (Doppler) Velocity” and “(Doppler) velocity folding (or aliasing).” Unambiguous (Doppler) Velocity

-- The maximum radial velocity a Doppler radar can measure without making a mistake -- The higher the PRF or the longer the wavelength, the higher the unambiguous velocity

Explain in your own words the terms “Unambiguous (Doppler) Velocity” and “(Doppler) velocity folding (or aliasing).” (Doppler) velocity folding/aliasing

-- When a target's true radial velocity exceeds the unambiguous velocity . The radar then mistakenly "wraps" it back into the allowed range, showing a false velocity -- Leads to folding -- Appears as sudden jumps in velocity (e.g., from strong outbound to strong inbound)

If given the equations for the hail kinetic energy flux and the severe hail index (SHI), describe the form and purpose of the reflectivity, W(Z), and height, W t (h), weighting functions that are used in SHI to estimate the severity of hail. Height Weighting Function , W t (h)

-- Emphasizes hail aloft , especially above the freezing level , where hail can grow -- Reflectivity below the freezing level is less likely to represent large hail, especially if melting is underway

Identify the key components of a Doppler radar system (e.g., transmitter, receiver mixer, modulator, computer/signal processor, locking mixer, COHO, STALO, phase detector, IF amplifier), explain how these components function to transmit, receive, and process electromagnetic radiation in order to produce a Doppler frequency shift (and hence a Doppler radial velocity). Receiver Mixer

Combines the incoming signal with a reference frequency (from STALO) to produce an intermediate frequency (IF) , which is easier to process Function for producing a Doppler frequency shift : The mixer uses the STALO signal to convert the return signal to an intermediate frequency (IF)

Identify the key components of a Doppler radar system (e.g., transmitter, receiver mixer, modulator, computer/signal processor, locking mixer, COHO, STALO, phase detector, IF amplifier), explain how these components function to transmit, receive, and process electromagnetic radiation in order to produce a Doppler frequency shift (and hence a Doppler radial velocity). Modulator

Electronic device that controls transmitter ; Switches the transmitter on and off ; Provides the correct waveform for transmitted pulse Function for producing a Doppler frequency shift : The modulator activates the transmitter to send out a pulse

Identify the key components of a Doppler radar system (e.g., transmitter, receiver mixer, modulator, computer/signal processor, locking mixer, COHO, STALO, phase detector, IF amplifier), explain how these components function to transmit, receive, and process electromagnetic radiation in order to produce a Doppler frequency shift (and hence a Doppler radial velocity). Computer/Signal Processor

-- Control, video processor/display -- Signal processor handles processing of the received signal and computation of radar parameters from that signal -- Controls radar operation via software or digital control Function for producing a Doppler frequency shift : The signal processor computes the Doppler frequency shift , then converts it to radial velocity

Identify the key components of a Doppler radar system (e.g., transmitter, receiver mixer, modulator, computer/signal processor, locking mixer, COHO, STALO, phase detector, IF amplifier), explain how these components function to transmit, receive, and process electromagnetic radiation in order to produce a Doppler frequency shift (and hence a Doppler radial velocity). Locking Mixer

Locks the reference signal to the incoming wave so it can compare frequency/phase changes Function for producing a Doppler frequency shift : The locking mixer and the phase detector compare the return signal with the referencee

Identify the key components of a Doppler radar system (e.g., transmitter, receiver mixer, modulator, computer/signal processor, locking mixer, COHO, STALO, phase detector, IF amplifier), explain how these components function to transmit, receive, and process electromagnetic radiation in order to produce a Doppler frequency shift (and hence a Doppler radial velocity). COHO

-- Coherent Oscillator -- Amplifies and oscillates at an intermediate frequency f c that has same phase relationship as transmitted wave f 0 + f c Function for producing a Doppler frequency shift : The COHO synchronizes with the transmit pulse to provide a phase reference

Radar Exam 2 Study Guide

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Science

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Hard

Josie Nelson

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63 questions

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FLASHCARD QUESTION

Front

Distinguish between a point and distributed target. Determine when to utilize the point or distributed target forms of the radar equation.

Back

Point target:

A radar target that is small compared with the pulse volume, which is the cross-sectional area of the radar beam multiplied by half the length of the radar pulse.

Plane, drone, bird, building, tower

Radar equation:

Target size << resolution cell

Return from a single object

Output desired: Radar cross-section σ of target

Distributed target:

A radar target that is large compared with the pulse volume, which is the cross-sectional area of the radar beam multiplied by one-half the length of the radar pulse

Clouds, precipitation

Radar equation:

Target fills multiple resolution cells

Return from area/volume of scatterers

Output desired: Reflectivity Z

FLASHCARD QUESTION

Front

Describe and derive an approximate form of the radar sample volume (V) for a uniformly illuminated main lobe. Given the range (r), circular parabolic beamwidth (θ₎, pulse width (τ), estimate V.

Back

Contains all objects from which backscattered microwaves return to radar simultaneously

Derivation:

ΔR = cτ/2

A ≈ R^2θΦ

V = A × ΔR

V ≈ R^2θΦcτ/2

FLASHCARD QUESTION

Front

Explain why the range length of a radar sample volume is h/2 where h is the pulse length.

Back

Radar equation requires signals that return to radar at precisely the same time period; For every meter the radar pulse travels forward, the return signal adds 2 meters to the round trip -- 1 m out, 1 m back

FLASHCARD QUESTION

Front

Given typical cloud (or rain) droplet concentrations, estimate the typical number of rain drops in a radar sample volume.

Back

Number of drops = N_R × V

N_R = raindrop concentration (drops per cubic meter)

V = radar sample volume (cubic meters)

FLASHCARD QUESTION

Front

List an expression for the sample volume for a Gaussian shaped beam and explain why it is different than for a uniformly illuminated beam.

Back

Gaussian shaped beam:

V = πr² θΦh / 16 ln(2)

Uniformly illuminated beam:

V = π [(rθ/2) (rΦ/2)] ⋅ h/2

A Gaussian-shaped beam doesn't spread energy uniformly across the beam cross-section. Instead, the intensity is strongest at the center and drops off smoothly toward the edges

FLASHCARD QUESTION

Front

Define in your own words and list a mathematical expression for the total backscattering cross-sectional area (σ_t) for a distributed target.

Back

σ_t represents how much radar energy is scattered back in the direction of the radar by all the individual scatterers (like raindrops or cloud particles) within the radar sample volume

σ_t = V∑_vol σ_i

FLASHCARD QUESTION

Front

Define the “time to independence” or “decorrelation time” and describe its significance for measuring received power (p_r) and hence estimating σ_t (η or z).

Back

Time it takes hydrometeors to rearrange themselves so measurements are independent of one another

If pulse intervals < decorrelation time --> correlated noise --> poor averaging

Pulse intervals >= decorrelation time --> statistically sound averaging --> better power estimate --> more accurate σ_t , η, or z

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