AOS SW Spectrometer Target Parameter List.pdf

SHORTWAVE SPECTROMETER

Introduction

The AOS hyperspectral shortwave (SW) spectrometer (SWSpec), targeting the near UV, visible (VIS), near infrared (NIR) and shortwave infrared (SWIR) spectral regions, will enable new capabilities, in particular pixel-level SW radiative flux closure studies to better understand radiative processes and cloud radiative effects [Stephens et al., 2021]. The spectrometer will also allow for enhanced scene identification (e.g., aerosol dust discrimination [Green et al., 2020], cloud detection and phase [Thompson et al., 2016; Coddington et al., 2017]) as well as improved retrievals of aerosol (Hou et al, 2017) and cloud Geophysical Variables (GVs) [Coddington et al., 2012]. In addition to stand-alone uses, SWSpec parameters provide unique information content that is expected to bring strong mission synergy with other expected AOS polar orbiter imaging assets, e.g., a multispectral/multi-angle polarimeter (subject of a separate RFI), an anticipated contributed longwave spectrometer [Libois and Blanchet, 2017], and an imaging microwave radiometer (subject of a separate RFI), as well as AOS active sensors. A summary of the information available from hyperspectral shortwave observations and the contribution to AOS science objectives is presented in Stephens et al. [2021].

The legacy for hyperspectral atmospheric multispectral GV retrievals includes multispectral satellite imagers that have a long history of providing observations applicable to a wide variety of Earth science studies. MODIS, the NASA Earth Observing System (EOS) imager, has provided about two decades of data records from two platforms. More relevant to AOS, the MODIS and follow-on operational VIIRS imagers have provided global aerosol and cloud products that have found wide use in the radiation and atmospheric communities [e.g., Hsu et al., 2019; Sawyer et al, 2020; Platnick et al., 2021].

Measurement Parameters and Performance Targets

Table 1 provides a notional range of targeted SW spectrometer performance values that will address shortwave flux and GVs to be retrieved with sufficient accuracy to meet the capabilities provided in the Science and Applications Traceability Matrix (SATM) from the ACCP study. The Expected target performance describes capabilities that are intended to enable core mission science objectives; the Desired target performance describes capabilities that are intended to enhance mission science objectives. Table 1 is intended to solicit responses that address SATM objectives without prescribing design solutions. An orbit altitude of 450 km is assumed.

Table 1. Measurement parameters and target performance values, separated into four separate parameter categories: spectral, optical, radiometric, and signal/noise/dynamic range. The rationale for some parameter targets can be found in the previous RFI (https://sam.gov/opp/61587d141bbe40969e6250da4c657d3b/view). An orbit altitude of 450 km is assumed. Definitions of Expected and Desired performance targets are given in the text.

Spectrometer Parameter SWSpec Target - Expected SWSpec Target – Desired (if different than Expected)

Spectral Spectral coverage (µm) 350–1700 nm 305–2400 nm Number of channels No requirement. Determined by spectral coverage and detector pixel bandwidth/binning.

Channel bandwidth with binning for radiometry

10 nm 5 nm

Spectral sampling Oversampling (i.e., sampling in nm < channel bandpass) anticipated

Tunable spectral capability No requirement. Potential flexibility with oversampling; desirable to align a channel to O2 A-band.

https://gcc02.safelinks.protection.outlook.com/?url=https%3A%2F%2Fsam.gov%2Fopp%2F61587d141bbe40969e6250da4c657d3b%2Fview&data=04%7C01%7Ckerry.meyer%40nasa.gov%7C019a4e58817e41184a4308d93a7f46b1%7C7005d45845be48ae8140d43da96dd17b%7C0%7C0%7C637605140576684374%7CUnknown%7CTWFpbGZsb3d8eyJWIjoiMC4wLjAwMDAiLCJQIjoiV2luMzIiLCJBTiI6Ik1haWwiLCJXVCI6Mn0%3D%7C1000&sdata=Hc6dj1K60XcnnXOTwXhvQEgr10PvdBBMCYb%2Ft5k%2BUKQ%3D&reserved=0

Spectrometer Parameter SWSpec Target - Expected SWSpec Target – Desired (if different than Expected)

Optical IFOV, FOR, etc.

Across-track swath width (km) 100 km ≥ 300 km Instantaneous across-track field of view (deg)

Determined by across-track swath and operating altitude

Accessible across-track field of regard

Same as across-track swath width ---a Ground footprint per pixel at nadir

500 m ≤ 300 m a Ground footprint per pixel at most oblique view angle/edge of FOV (i.e., worst case)

No added requirement. Specify if known.

Along-track spatial coverage Continuous --- Pixel co-registration across the spectrum

≤ 100 m (0.2 of ground IFOV) ≤ 60 m (0.2 of ground IFOV) a Respondent can define the spatial resolution metric as considered appropriate, e.g., encircled energy, PSF, MTF.

Radiometric Radiometric calibration technique(s), e.g., on-board systems, vicarious

Methodology not a requirement driver but description of calibration strategy, mission support (e.g., maneuvers) and expected performance should be provided.

Absolute spectral radiometric uncertainty (%)

5% ≤ 3%

Channel-to-channel spectral radiometric uncertainty (%)

3% 1%

Radiometric stability (%) < absolute spectral uncertainty requirement

< 1% over mission lifetime, based on GV experience with MODIS/VIIRS. Depending on radiometric accuracy methodology, acceptable to be corrected or improved in re-processing.

Polarization spectral sensitivity, knowledge

No target specified at this time. Describe likely sensitivity and knowledge.

Signal, noise, dynamic range, etc.

S/N, NEdL, NEdR, dynamic range, saturation

See Table 2. Derived from heritage MODIS/VIIRS requirements.

See Table 2. Derived from heritage MODIS/VIIRS requirements.

Precision Quantization ≥ 12 bits. To exceed NEdR and dynamic range (see Table 3) with 1- 2 bits of margin. Consistent with SW flux precision of <0.1%.

Table 2 gives dynamic range and noise performance targets for various spectrometer spectral regions. The noise equivalent delta reflectance (NEdR) is used as the primary driver for defining noise performance and is given as 0.001 and 0.0005 for the expected and desired targets, respectively. Because of the wide dynamic range needed to accommodate aerosol and cloud scenes, the traditional specification of the typical radiance (Ltyp) or reflectance (Rtyp) values are of limited practical use. However, for example purposes, the typical values were chosen to roughly correspond to the reflectance from an optically thin cirrus cloud over a dark ocean surface (Rtyp=0.04 for all spectral channels for simplicity). With noise and typical values tied to reflectance units, SNR at Ltyp is 40 and is roughly 1000 for Rmax. See the table notes for more details.

Table 2. Spectral dynamic range and noise performance targets.

CW (nm)

Solar Spectral

Irradiance* (W/m2/µm)

Rmaxa (µ0=1)

Lmaxa (W/m2/sr/µm)

Ltypb (W/m2/sr/µm)

NEdLc Expected

NEdLc Desired

412 1624 1.10 569 20.7 0.517 0.258

490 1948 1.10 682 24.8 0.620 0.310

550 1868 1.10 654 23.8 0.595 0.297

650 1583 1.10 554 20.1 0.504 0.252

750 1266 1.10 443 16.1 0.403 0.201

860 977 1.10 342 12.4 0.311 0.156

940 866 0.88 243 11.0 0.276 0.138 1250 460 1.00 146 5.9 0.146 0.073 1380 354 0.88 99 4.5 0.113 0.056 1640 227 0.88 64 2.9 0.072 0.036 1880 132 0.88 37 1.7 0.042 0.021 2135 86 0.83 23 1.1 0.027 0.014 2250 74 0.83 19 0.9 0.023 0.012

Footnotes for Table 2:

a Max values chosen for consistency with MODIS 1 km native resolution channels. Values also generally consistent with corresponding VIIRS M-bands and PACE OCI (courtesy G. Meister, GSFC). For MODIS, Rsat margin was generally 1.15Rmax in these channels.

b Provided as an example only, Ltyp in the table is for Rtyp = 0.04 (roughly corresponding to a thin cirrus cloud with an optical thickness of 0.2–0.3 over a dark ocean surface).

c Corresponding to expected NEdR = 0.001; desired NEdR = 0.0005 or better, generally consistent with corresponding MODIS 1 km native resolution channels. Since Ltyp and NEdL values are tagged to fixed reflectances, SNR = 40 at Ltyp and 830-1111 at Lmax. Expected and desired bandpasses are 10 nm and 5 nm, respectively. To the extent that Lmin is defined as the radiance corresponding to SNR=1, Lmin=NEdL.

* VIS/NIR: Neckel and Lab (1984); SWIR: Thekekara (1974).

SHORTWAVE SPECTROMETER RESOURCE ALLOCATION TARGETS

The AtmOS team has developed target spacecraft resource allocations for the SW Spectrometer based on information gathered during the ACCP Architecture Study Phase, including information gathered from an instrumentation Request for Information submitted during that period. From this information the mission systems team developed spacecraft concepts commensurate with allocations as found in Table . The respondent should provide both their Current Best Estimate and Maximum Expected Value resource needs in the attached spreadsheet under the tab labeled ‘Spacecraft Accommodation.’ Note: The values in the table below are not requirements but rather for informational purposes to provide the respondent with the notional resource needs currently envisioned by the AtmOS team. Exceedance of these values are acceptable and expected, especially in the event of enhanced performance capability.

Table 4. SW Spectrometer Target Resource Allocations

Resource Units Target Allocation (Current Best Estimate)** Mass kg 27 Operational Power (Orbit Average)

W 70

Envelope Dimensions in Operational Configuration (L x W x H) cm 45 x 20 x 35

Data Rate (Peak*) bits/second 74x106

*Peak data rate is the nominal rate while the instrument is in its acquisition mode.

**Please provide both the Current Best Estimate (CBE) and the Maximum Expected Value (MEV) for these resources. MEV = [(100 + XX)/100] CBE where XX is contingency in percent.

Figure 2. Instrument reference coordinate system.

REFERENCES

Coddington, O., P. Pilewskie, and T. Vukicevic (2012), The Shannon information content of hyperspectral shortwave cloud albedo measurements: Quantification and practical applications, J. Geophys. Res., 117, D04205, doi:10.1029/2011JD016771.

Coddington, O. M., T. Vukicevic, K. S. Schmidt, and S. Platnick (2017), Characterizing the information content of cloud thermodynamic phase retrievals from the notional PACE OCI shortwave reflectance measurements, J. Geophys.

Res., 122(15), 8079–8100, doi:10.1002/2017JD026493.

Green, R. O., et al., The Earth Surface Mineral Dust Source Investigation: An Earth Science Imaging Spectroscopy Mission, IEEE Xplore conference proceeding, 2020, ieeexplore.ieee.org/document/9172731.

Hou, W., J. Wang, et al., An algorithm for hyperspectral remote sensing of aerosols: 2. Information content analysis for aerosol parameters and principal components of surface spectra, J. Quant. Spectroscopy Rad. Transfer, 192, 14-29, 2017.

Hsu, N. C., J. Lee, A. M. Sayer, W. Kim, C. Bettenhausen, and S.-C. Tsay (2019), VIIRS Deep Blue aerosol products over land: extending EOS long-term aerosol data records, J. Geophys. Res., 124, doi.org/10.1029/2018JD029688.

Libois, Q., and J.-P. Blanchet, 2017: Added value of far-infrared radiometry for remote sensing of ice clouds, J. Geophys.

Res.,122, 6541–6564, doi:10.1002/2016JD026423.

Platnick, S.; Meyer, K.; Wind, G.; Holz, R.E.; Amarasinghe, N.; Hubanks, P.A.; Marchant, B.; Dutcher, S.; Veglio, P. The NASA MODIS-VIIRS Continuity Cloud Optical Properties Products. Remote Sens. 2021, 13, 2.

https://www.mdpi.com/2072-4292/13/1/2.

Sawyer, V., R. Levy, et al., Continuing the MODIS Dark Target Aerosol Time Series with VIIRS." Remote Sens., 2020, 12 (2): 308 [10.3390/rs12020308]

Stephens, G., et al., The spectral nature of Earth’s reflected radiation: measurement and science applications, Frontiers, 2021, https://www.frontiersin.org/article/10.3389/frsen.2021.664291.

Thompson, D. R., et al. (2016), Measuring cloud thermodynamic phase with shortwave infrared imaging spectroscopy, J. Geophys. Res. Atmos., 121, doi:10.1002/2016JD024999.

https://ieeexplore.ieee.org/document/9172731 https://www.mdpi.com/2072-4292/13/1/2 http://dx.doi.org/10.3390/rs12020308 https://www.frontiersin.org/article/10.3389/frsen.2021.664291