ATTACHMENT B - Radar Performance Targets and Technical Resource Allocations.pdf

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National Aeronautics and Space Administration

Goddard Space Flight Center Greenbelt, Maryland

AOSP-DRADAR-SOW-0005, Revision A Atmosphere Observing System Project, Code 425

Atmosphere Observing System-Polar

Doppler Radar Performance Targets and Technical Resource Allocations

AOS Reviewed – Not Subject to Export Control

GSFC AOS CMO

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Table of Contents

1 INTRODUCTION

1.1 Purpose

1.2 Scope

1.3 Related Documentation

1.3.1 Applicable Documents

1.3.2 Reference Documents

2 CLOUD-CAPABLE RADAR PERFORMANCE

3 DEFINITIONS AND DISCUSSION

4 REFERENCES

Appendix A Abbreviations and Acronyms

List of Tables

Table 1: Target Radar Capabilities for the Polar Orbit Table 2: Minimum Capabilities for the Polar Orbit (changes from target capability are shown in bold font) Table 3: Target Capabilities for a Secondary Radar Channel Table 4: Target Instrument Physical Resource Allocations Table 5: Assumed parameters for radar sensitivity calculations

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1 INTRODUCTION

1.1 Purpose

This document contains the target radar capabilities and technical resource allocations for the purposes of Phase A instrument concept studies. This document should be used in conjunction with the “Atmosphere Observing System-Polar Doppler Radar Instrument Phase A Study Statement of Work (SOW)” provided as Attachment A.

1.2 Scope

This document is relevant to the AOS Phase A Radar Instrument Study.

1.3 Related Documentation

All document citations are assumed to be the latest version unless otherwise noted.

1.3.1 Applicable Documents

Document Number Title Attachment A Atmosphere Observing System-Polar Doppler Radar Instrument

Phase A Study Statement of Work (SOW)

1.3.2 Reference Documents

See Section 4.

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2 CLOUD-CAPABLE RADAR PERFORMANCE

The Polar Orbit radar (the subject of this RFP) should be a highly sensitive instrument that provides equivalent reflectivity factor and Doppler velocity. Table 1 gives a summary of target performance. Minimum capabilities desired for the Polar Radar are shown in Table 2 with changes from the baseline values shown in bold font for clarity. Requirements will not be finalized until the System Requirements Review (SRR) in mid-2024. Brief descriptions and discussions of the fields in Table 1 and Table 2 are provided in the following “DEFINITIONS AND DISCUSSION” section. Responses will be reviewed even if the proposed performance doesn’t fully meet the requirements in Table 2.

Table 1: Target Radar Capabilities for the Polar Orbit

Radar Observable Altitude Sensitivity

Uncertainty

Horizontal Resolution (sampling)

Vertical Resolution Swath

Equivalent Reflectivity Factor (dBZe)

6 to 20 km -24 dBZe

1.5 dB 2 km (1 km)

500 m

Nadir

2.5 to 6 km -20 dBZe 500 m 1 to 2.5 km -15 dBZe 300 m

0.5 to 1 km -5 dBZe 300 m

Doppler Velocity (m/s)

6 to 20 km Reflectivity SNR>0 dB 0.5 m/s 2 km

(1 km)

500 m

Nadir

2.5 to 6 km 500 m 1 to 2.5 km 300 m

0.5 to 1 km 300 m

† Sensitivity targets are defined only for the Nadir beam. Doppler velocity observable uncertainty is defined where the reflectivity signal is significantly above the minimum detectable sensitivity (at approximately 0 dB single-pulse SNR).

§ The uncertainty of the Equivalent Reflectivity Factor is defined at high-SNR. The Doppler Velocity uncertainty includes random noise and non-uniform beam filling. See additional discussion in the DEFINITIONS AND DISCUSSION section.

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Table 2: Minimum Capabilities for the Polar Orbit (changes from target capability are shown in bold font)

Radar Observable Altitude Sensitivity

Uncertainty

Horizontal Resolution (sampling)

Vertical Resolution Swath

Equivalent Reflectivity Factor (dBZe)

6 to 20 km -20 dBZe

1.5 dB 2.5 km (1.25 km)

500 m

Nadir

2.5 to 6 km -13 dBZe 500 m 1 to 2.5 km -8 dBZe 300 m

0.5 to 1 km +2 dBZe 300 m

Doppler Velocity (m/s)

6 to 20 km Reflectivity SNR>0 dB 0.75 m/s 2.5 km

(1.25 km)

500 m

Nadir

2.5 to 6 km 500 m 1 to 2.5 km 300 m

0.5 to 1 km 300 m

† Sensitivity targets are defined only for the Nadir beam. Doppler velocity observable uncertainty is defined where the reflectivity signal is significantly above the minimum detectable sensitivity (at approximately 0 dB single-pulse SNR).

§ The uncertainty of the Equivalent Reflectivity Factor is defined at high-SNR. The Doppler Velocity uncertainty includes random noise and non-uniform beam filling. See additional discussion in the DEFINITIONS AND DISCUSSION section.

Potential approaches for achieving cloud-profiling sensitivity identified by the AOS project team include either W-band or Ka-band instrument architectures, but proposers are encouraged to provide potentially relevant information even if it does not fall within one of these concepts.

There are potential enhancements beyond the performance shown in Table 1 that are being considered by the science team, and will be studied as part of this Phase A study. These enhancements include:

1. Addition of a secondary channel with reduced sensitivity. For example, adding a Ka-band channel to a W-band radar, or an X-, Ku-, or W-band channel to a Ka-band radar. See Table 3 for target performance for this secondary channel.

2. Addition of Linear Depolarization Ratio (LDR) measurement capability.

3. Addition of a small (10 km) swath of radar reflectivity measurements. Sensitivity targets are only for the nadir beam, and reduced sensitivity is acceptable for off-nadir beams.

4. Addition of radiometric brightness temperature measurements co-located with radar reflectivity profiles.

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Table 3: Target Capabilities for a Secondary Radar Channel

Radar Observable Altitude Sensitivity Uncertainty

Horizontal Resolution (sampling)

Vertical Resolution Swath

Equivalent Reflectivity Factor (dBZe)

6 to 20 km +10 dBZe

1.5 dB 2.5 km (1.25 km)

500 m

Nadir

2.5 to 6 km +12 dBZe 500 m 1 to 2.5 km +12 dBZe 300 m

0.5 to 1 km +20 dBZe 300 m

Potential W-band architecture W-band has the advantage of allowing estimation of cloud liquid water over ocean (Lebsock et

al. 2022). One approach to achieving the target performance is a W-band radar with one or more large, fixed antennas. Doppler could be achieved by using a sufficiently large antenna (estimated to be larger than than 3 meters in the along-track direction) and estimating the along-track reflectivity gradient to mitigate non-uniform beam filling (NUBF) effects (Kollias et al. 2014;

McLinden et al. 2021), or by utilizing the displaced phase center (DPCA) approach with two antennas (Durden et al. 2007, Tanelli et al. 2016). Transmitted peak power may need to be on the order of kilowatts for radars utilizing conventional pulsed continuous-wave (CW) waveforms or one hundred watts for radars utilizing pulse compression and/or frequency diversity (McLinden et al. 2013).

Potential Ka-band architecture Ka-band has the advantages of reduced attenuation and improved sensing of precipitation. One approach to achieving the target performance is a Ka-band radar with a single very large deployable antenna. Doppler performance might be achieved by estimating the along-track reflectivity gradient to mitigate NUBF effects (the antenna may need to be 6 meters or larger in the along-track dimension for this technique). Peak transmit power might be hundreds of watts for a radar utilizing pulse compression and/or frequency diversity, or kilowatts for a radar utilizing CW waveforms.

Target Instrument Physical Allocations The radar instrument package will be accommodated on the AOS Polar spacecraft bus along with 4 other instruments. Instrument-provided electronics boxes that do not have to be physically collocated with the instrument should be listed separately and their accommodation will need to be negotiated with the AOS Project. In order to make sure the entire observatory will fit in the launch vehicle fairing the AOS Project is imposing physical allocations on all instruments.

Responses will be reviewed even if the proposed resource usage doesn’t fully meet the allocations in Table 4. The allocations for the radar instrument package are as follows:

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Table 4: Target Instrument Physical Resource Allocations

Area of Interest Constraint Dimensions1 (x, y, z) in S/C frame2 430 cm x 230 cm x 155 cm Allocated Mass 410 kg Allocated Operational Power (Orbit Average)

500 W

Survival Power 200 W Data Rate (including any compression) 3,067 Gb / day (raw science)3 Operational Temp (@S/C I/F) -10C to +40C Survival Temp (@S/C I/F) -30C to +60C Interface Heat Transfer (@S/C I/F) Conductive: < 0.05 W/C (TBR)

Radiative: < 1 W (TBR)

1 If instrument design is deployable, this is the maximum stowed volume 2 +X – velocity direction; +Z – nadir; +Y (completes right-handed coordinate system) 3 Does not include any housekeeping or instrument health and safety data.

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3 DEFINITIONS AND DISCUSSION

References for scholarly citations are found in Section 4.

Altitude is the height above sea level of the observation. The performance targets for sensitivity and vertical resolution vary with altitude at the given levels, but respondents are welcome to provide more detailed or differing information relating instrument performance to the altitude of observations. Improved sensitivity at lower altitudes would provide value if possible without significant cost impact.

Doppler Velocity is defined as the vertical hydrometeor velocity as would be measured by a static nadir-pointing radar. The uncertainty of the Doppler velocity is the combination (as applicable) of spectrum width including that caused by spacecraft motion (Kollias et al. 2014), non-uniform beam filling interactions with spacecraft motion (Tanelli et al. 2002, Schutgens 2008, Kollias et al. 2018, Sy et al. 2013, Sy et al. 2014), system noise, and other potential factors.

As Doppler velocity observations have not been demonstrated in space, respondents are encouraged to discuss the approach to overcoming the challenges associated with this observable, including sufficiently large antenna sizes, along-track reflectivity gradient estimation (Kollias et al. 2014; McLinden et al. 2021), and potentially displaced phase center antenna (DPCA) techniques (Durden et al. 2007; Tanelli et al. 2016).

The project anticipates that the best Doppler performance may be achieved using the DPCA technique to mitigate the effects of spacecraft motion on Doppler measurements. For single-aperture radars, antenna size has a very significant impact on Doppler performance, particularly in the presence of non-uniform beam filling. From McLinden et al. (2021), a single Ka-band antenna may need to be 6 or more meters in the along-track dimension to achieve good Doppler measurements, and a W-band antenna may need to be on the order of 3 meters or more. Non-uniform beam filling effects increase with the square of the antenna beamwidth, so antenna sizes beyond those mentioned here would be expected to continue to provide significant benefit.

Equivalent Reflectivity Factor in units of dBZe is a measure of the volume backscatter from hydrometeors. The equivalent reflectivity factor is defined as in Smith (1984) and Doviak and Zrnic (1993) as dBZe = 10log10 � 𝜂𝜂𝜆𝜆41018 𝜋𝜋5|𝐾𝐾𝑤𝑤|2� , log10 �𝑍𝑍 mm6 m3 � (1) where 𝜂𝜂 is the radar cross section per unit volume and 𝜆𝜆 is the wavelength. The term |𝐾𝐾𝑤𝑤|2 is defined by convention as 0.93 at Ku-band and Ka-band, and as 0.75 at W-band (Stephens et al.

2008).

Horizontal Resolution is defined for the AOS radar as the major axis of the ellipse defined by the -6 dB contour of the horizontal weighting function (two-way antenna pattern) projected on the Earth’s surface after pulse integration. The horizontal resolution as defined here is only required at nadir in the case of a scanning radar. Note that the horizontal resolution (width of the weighting function) is defined separately from the horizontal sampling (radar observable record

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density) and that neighboring samples need not be independent (McLinden et al. 2015).

Horizontal Sampling is defined as the horizontal space between neighboring records of radar observables and is targeted at two samples per horizontal resolution to maintain near-Nyquist sampling of the observable fields. Due to the increased density of this approach compared to contiguous sampling (non-overlapping footprints), neighboring samples need not be independent and running averages of pulses are expected after ground processing.

Sensitivity is defined at the estimated received signal power equal to the standard deviation of the thermal noise after averaging multiple pulses to the target resolution in horizontal distance.

From Doviak and Zrnic (2006) the power received by a radar from clouds or precipitation is expressed as

Pη(r) ≈

𝑃𝑃𝑡𝑡𝑔𝑔𝑠𝑠𝑔𝑔2𝜆𝜆2𝜂𝜂(𝑟𝑟)

(4𝜋𝜋)3𝑟𝑟2𝑙𝑙𝑎𝑎𝑡𝑡𝑎𝑎 𝑐𝑐𝑐𝑐 2𝑙𝑙𝑟𝑟 𝜋𝜋𝜋𝜋𝜋𝜋 8 ln(2)

(2) where 𝑃𝑃𝑡𝑡 is the radiated power (after losses), 𝑟𝑟 is the range, 𝑔𝑔𝑠𝑠 is the receiver gain, 𝑔𝑔 is the antenna gain, 𝜆𝜆 is the wavelength, 𝜂𝜂 is the volume reflectivity, 𝑐𝑐 is the speed of light, 𝑐𝑐 is the pulse width, 𝜋𝜋 and 𝜋𝜋 are the along-and cross-track 3 dB beamwidths of the antenna, 𝑙𝑙𝑎𝑎𝑡𝑡𝑎𝑎 is atmospheric loss, and 𝑙𝑙𝑟𝑟 is the finite bandwidth loss. If available, integrated antenna patterns may be used rather than the Probert-Jones approximation.

The standard deviation of the thermal noise after averaging N pulses is std(Pnoise) = 𝑘𝑘𝑘𝑘𝑘𝑘𝑘𝑘𝑔𝑔𝑠𝑠

√𝑁𝑁

(3) where 𝑘𝑘 is Boltzmann’s Constant, 𝑘𝑘 is the system brightness temperature, 𝑘𝑘 is the receiver matched-filter bandwidth, 𝑘𝑘 is the noise factor, and 𝑁𝑁 is the number of independent samples.

For the purposes of this RFP the sensitivity is defined at the Equivalent Reflectivity Factor (dBZe) such that Pη(r) = std(Pnoise). To compare responses and instrument performance, the AOS project requests respondents provide both the single-pulse noise-equivalent (0 dB SNR) sensitivity and the sensitivity after pulse averaging.

For pulse compression waveforms there is no pulse compression gain in Equations (2) or (3).

Sensitivity improvements associated with pulse compression are captured by the increase of the pulse width 𝑐𝑐 as compared to a conventionally pulsed radar with equal range resolution. Please note that for amplitude-tapered waveforms, 𝑐𝑐 is power-weighted and will be less than the actual waveform length. The finite bandwidth loss 𝑙𝑙𝑟𝑟 may also differ with waveform and matched filter design.

In the case that sensitivity may be limited by pulse compression range sidelobes from surface clutter, please provide the estimated range sidelobe levels and what surface normalized radar cross section (NRCS) would cause the sidelobe level to meet the noise-equivalent thresholding levels. For reference, Battaglia (2017) provides a summary of wind speed and surface NRCS

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over ocean and Tanelli et al. (2008) provides surface NRCS measurements from CloudSat over a variety of surface types. If the radar utilizes pulse compression, respondents are encouraged to provide information on the time-bandwidth product and assumed phase noise.

Table 5: Assumed parameters for radar sensitivity calculations

Parameter Name Variable Assumed Value Range r 450e3 m

Speed of Light c 3e8 m/s Atmospheric Loss 𝑙𝑙𝑎𝑎𝑎𝑎𝑎𝑎 1

Swath is defined as the cross-track distance of the outermost beam centers of a multi-beam radar. A narrow swath at one frequency was identified in the Science and Applications Traceability Matrix (SATM) as a desired enhancement and provides horizontal context (stratiform/convection discrimination) and convective core size estimates. Cross-track sampling of ½ the beam footprint is desired, but contiguous cross-track sampling may be acceptable.

Vertical Resolution is defined as the distance between the -6 dB edges of the range weighting function of the radar pulse after receiver filtering.

Vertical Sampling is defined as the distance between neighboring records of radar observables within a profile and is targeted at two samples per vertical resolution to maintain near-Nyquist sampling of the observable fields.

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4 REFERENCES

Battaglia, Alessandro, et al. "Characterization of surface radar cross sections at W-band at moderate incidence angles." IEEE Transactions on Geoscience and Remote Sensing 55.7 (2017):

3846-3859.

Doviak, Richard J. Doppler radar and weather observations. Dover Publications, 1993.

Durden, Stephen L., P. R. Siqueira, and Simone Tanelli. "On the use of multiantenna radars for spaceborne Doppler precipitation measurements." IEEE Geoscience and Remote Sensing Letters

4.1 (2007): 181-183.

Kollias, Pavlos, et al. "Evaluation of EarthCARE cloud profiling radar Doppler velocity measurements in particle sedimentation regimes." Journal of Atmospheric and Oceanic Technology 31.2 (2014): 366-386.

Kollias, Pavlos, et al. "The EarthCARE cloud profiling radar (CPR) doppler measurements in deep convection: challenges, post-processing, and science applications." Remote sensing of the atmosphere, clouds, and precipitation VII. Vol. 10776. International Society for Optics and Photonics, 2018.

Lebsock, Matthew, et al. "Understanding Errors in Cloud Liquid Water Path Retrievals Derived from CloudSat Path-Integrated Attenuation." Journal of Applied Meteorology and Climatology

61.8 (2022): 955-967.

McLinden, Matthew L., et al. "Utilizing versatile transmission waveforms to mitigate pulse-compression range sidelobes with the HIWRAP radar." IEEE Geoscience and Remote Sensing Letters 10.6 (2013): 1365-1368.

McLinden, Matthew L., et al. "Reduced Image Aliasing with Microwave Radiometers and Weather Radar Through Windowed Spatial Averaging." IEEE Transactions on Geoscience and Remote Sensing 53.12 (2015): 6639-6649.

McLinden, Matthew L. Walker, et al. "Application of Nonuniform Beam Filling (NUBF) Doppler Velocity Error Correction on Airborne Radar Measurements." IEEE Geoscience and Remote Sensing Letters 19 (2021): 1-5.

Schutgens, N. A. J. "Simulated Doppler radar observations of inhomogeneous clouds:

Application to the EarthCARE space mission." Journal of atmospheric and oceanic technology

25.1 (2008): 26-42.

Smith, Paul L. "Equivalent radar reflectivity factors for snow and ice particles." Journal of Climate and Applied Meteorology 23.8 (1984): 1258-1260.

Stephens, Graeme L., et al. "CloudSat mission: Performance and early science after the first year of operation." Journal of Geophysical Research: Atmospheres 113.D8 (2008).

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Sy, Ousmane O., et al. "Simulation of EarthCARE spaceborne Doppler radar products using ground-based and airborne data: Effects of aliasing and nonuniform beam-filling." IEEE transactions on geoscience and remote sensing 52.2 (2013): 1463-1479.

Sy, Ousmane O., et al. "Application of matched statistical filters for EarthCARE cloud Doppler products." IEEE Transactions on Geoscience and Remote Sensing 52.11 (2014): 7297-7316.

Tanelli, Simone, et al. "The effects of nonuniform beam filling on vertical rainfall velocity measurements with a spaceborne Doppler radar." Journal of Atmospheric and Oceanic Technology 19.7 (2002): 1019-1034.

Tanelli, Simone, et al. "CloudSat's cloud profiling radar after two years in orbit: Performance, calibration, and processing." IEEE Transactions on Geoscience and Remote Sensing 46.11 (2008): 3560-3573.

Tanelli, Simone, Stephen L. Durden, and M. P. Johnson. "Airborne demonstration of DPCA for velocity measurements of distributed targets." IEEE Geoscience and Remote Sensing Letters

13.10 (2016): 1415-1419.

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Abbreviations and Acronyms <Populate/alphabetize this table with all abbreviations and acronyms in this document>

Abbreviations/

Acronyms Definition

GSFC Goddard Space Flight Center ITAR International Trade in Arms Regulation SATM Science and Applications Traceability Matrix SBU Sensitive But Unclassified TBD To be determined TBR To be revised TBS To be scheduled