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Optical and Mechanical Designs of the Multi-band SWIR Receiver for the Lunar Flashlight CubeSat Mission
Mapping and quantifying lunar water ice addresses one of NASA’s Strategic Knowledge Gaps to understand the lunar resource potential for future human exploration of the Moon. Lunar Flashlight is an innovative NASA CubeSat mission dedicated to mapping water ice in the permanently-shadowed and occasionally-sunlit regions in the vicinity of the lunar South Pole. Lunar Flashlight will acquire these measurements from lunar orbit using a multi-band laser reflectometer composed of an optical receiver aligned with four lasers emitting different wavelengths in the shortwave infrared spectral region between 1 µm and 2 µm. The receiver measures the laser radiance reflected from the lunar surface in each spectral band and continuum/absorption reflectance band ratios are then analyzed to quantify water ice concentration in the illuminated spot. The receiver utilizes a 70×70-mm, aluminum, off-axis paraboloidal mirror with a focal length of 70 mm, which collects the incoming light onto a single, 2 mm diameter InGaAs detector with a cutoff wavelength of 2.4 µm. We present the optical and mechanical designs of the receiver, including its optimization for rejection of solar stray-light from outside its intended field of view. This highly mass- and volume-constrained instrument payload will demonstrate several firsts, including being one of the first instruments onboard a CubeSat performing science measurements beyond low Earth orbit and the first planetary mission to use multi-band active reflectometry from orbit.
The Lunar Flashlight CubeSat Instrument: A Compact SWIR Laser Reflectometer to Quantify and Map Water Ice on the Surface of the Moon
The Lunar Flashlight (LF) mission will send a CubeSat to lunar orbit via NASA’s Space Launch System (SLS) test flight. The LF spacecraft will carry a novel instrument to quantify and map water ice harbored in the permanently shadowed craters of the lunar South Pole. The LF instrument, an active multi-band reflectometer which employs four high power diode lasers in the 1-2 μm infrared band, will measure the reflectance of the lunar surface near water ice absorption peaks. We present the detailed instrument design and system engineering required to deploy this instrument within very demanding CubeSat resource allocations.
Drone-Acquired Short-Wave Infrared (SWIR) Imagery in Landscape Archaeology: An Experimental Approach
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Enabling the Assimilation of CrIS Shortwave Infrared Observations in Global NWP at NOAA. Part II: OSEs and Results
The assimilation of data from hyperspectral infrared sounders in global data assimilation systems has historically been focused on observations in the longwave infrared (LWIR) region of the spectrum (650-1100 cm−1), despite the often concurrent availability of measurements from the shortwave infrared (SWIR) region of the spectrum (2150-2550 cm−1), because issues (like solar effects) have generally prevented the assimilation of SWIR observations. Recent advances in radiative transfer models have worked to address some of the previous challenges in simulating SWIR observations, and the assimilation of SWIR data (e.g. from potential future small-satellites) is now a feasible prospect. Still, a better understanding of how these observations perform in a data assimilation system and impact resulting analyses and NWP forecasts is necessary. In this study, the value of SWIR observations in global NWP is assessed by assimilating SWIR observations from the Cross-track Infrared Sounder (CrIS) in NOAA’s Global Data Assimilation System (GDAS). The methodologies used to enable the assimilation of these observations, including the implementation of a scene-dependent observation error and the enhancement of quality control procedures, are discussed, as are the results of Observing System Experiments (OSEs) conducted to evaluate the impact of assimilating SWIR observations on forecast skill. The overall results show that SWIR assimilation produces similar forecast impacts to LWIR assimilation. The ability to demonstrate that the assimilation or SWIR observations in NWP is a realistic prospect may help to shape future constellations of small-satellites to serve as a beneficial complement to the current constellation if hyperspectral IR sounders.
Improvements of On-orbit Characterization of Terra MODIS Short-wave Infrared Spectral Bands Out-of-Band Responses
The short-wave infrared (SWIR) bands (5-7, 26) of Terra MODIS, which are co-located with the mid-wav e infrared (MWIR) bands (20-25) on the short and mid-wave infrared (SMIR) Focal Plane Assembly (FPA),have a known issue related to 5.3 μm out-of-band (OOB) thermal leak and electronic crosstalk that was identified prelaunch. As a result, a crosstalk correction algorithm was designed and implemented in the MODIS Level 1B (L1B) calibration. Shortly after the Terra launch, extensive efforts were under taken to help characterize and mitigate the impact due to the OOB response and crosstalk on the SWIR on-orbit calibration and, consequently, the associated L1Bdata products. In addition, special night time day mode (NTDM) operations have been regularly scheduled to derive the crosstalk correction coefficients. Since MODIS does not have a spectral band centered at 5.3 μm, its band 28 (7.325 μm) was chosen as the surrogate sending band to simulate the OOB radiances at 5.3 μm. This was largely based on the measurements from the MODIS Airborne Simulator (MAS) spectrometer field campaigns in the early months after the Terra launch. In the case of Aqua MODIS, the magnitude of the SWIR crosstalk was much smaller and band 25 (4.52 μm) was found to be more effective as the sending band for the crosstalk correction. In recent years, the Terra MODIS photovoltaic (PV) long-wave infrared (LWIR) bands (27-30)electronic crosstalk has increased considerably, especially after the spacecraft safe-mode event occurred in February2016. This accentuated degradation in the PV LWIR performance has also impacted the performance of the SWIR crosstalk correction and thus its calibration and data quality. In this paper, we examine the use of band 25 as the sending band for the Terra MODIS SWIR crosstalk correction and compare its performance with that based on band 28 as the sending band. Results indicate an improvement of on-orbit gain stability for the SWIR calibration and reduced detector to detector and sub-frame to sub-frame striping in the calibrated L1B imagery, especially during the period when the PV LWIR electronic crosstalk has become more severe. This approach has been implemented in the forward production of Terra MODIS Collection 6 and Collection 6.1,starting from July 2019, and is planned to be used for the future reprocessing of MODIS L1B and to help improve the mission-long reflectance calibration and trending stability of the SWIR bands.
Evaluation of Shortwave Infrared Atmospheric Correction for Ocean Color Remote Sensing of Chesapeake Bay
The NASA Moderate Resolution Imaging Spectroradiometer onboard the Aqua platform (MODIS-Aqua) provides a viable data stream for operational water quality monitoring of Chesapeake Bay. Marine geophysical products from MODIS-Aqua depend on the efficacy of the atmospheric correction process, which can be problematic in coastal environments. The operational atmospheric correction algorithm for MODIS-Aqua requires an assumption of negligible near-infrared water-leaving radiance, nL(sub w)(NIR). This assumption progressively degrades with increasing turbidity and, as such, methods exist to account for non-negligible nL(sub w)(NIR) within the atmospheric correction process or to use alternate radiometric bands where the assumption is satisfied, such as those positioned within shortwave infrared (SWIR) region of the spectrum. We evaluated a decade-long time-series of nL(sub w)(lambda) from MODIS-Aqua in Chesapeake Bay derived using NIR and SWIR bands for atmospheric correction. Low signal-to-noise ratios (SNR) for the SWIR bands of MODIS-Aqua added noise errors to the derived radiances, which produced broad, flat frequency distributions of nL(sub w)(lambda) relative to those produced using the NIR bands. The SWIR approach produced an increased number of negative nL(sub w)(lambda) and decreased sample size relative to the NIR approach. Revised vicarious calibration and regional tuning of the scheme to switch between the NIR and SWIR approaches may improve retrievals in Chesapeake Bay, however, poor SNR values for the MODIS-Aqua SWIR bands remain the primary deficiency of the SWIR-based atmospheric correction approach.
Leveraging hyperspectral phenotyping for accurate, non-destructive prediction of metabolite profiles in poplar under drought stress
Accurately predicting drought tolerance in woody perennial bioenergy crops is critical for sustainable biomass production under fluctuating precipitation. Hyperspectral imaging (HSI) in the visible-near-infrared (VNIR) and shortwave-infrared (SWIR) ranges offers a promising approach for predicting plant biochemical traits, yet its application in metabolite profiling remains underexplored. We integrated VNIR+SWIR HSI with untargeted metabolomics to investigate drought-induced metabolic shifts in Populus leaves from eight Populus genotypes. Metabolite profiling identified 127 compounds, with 73 showing significant drought responses spanning amino acids (AA), carbohydrates (CHO), phenolic glycosides (PG), organic acids (OA), fatty acids and alcohols (FA), terpenes (T), phenolic metabolites (P), and unclassified metabolites. Spectral analysis revealed consistently higher reflectance across VNIR and SWIR wavelengths in drought-stressed plants, corresponding with increased accumulation of AA and reduced CHO and PG levels. Least absolute shrinkage and selection operator (LASSO) regression modeling identified robust spectral predictors of metabolite concentrations, associating VNIR wavelengths (500–700 nm) predominantly with AA and P, whereas SWIR wavelengths (1680–1700 nm) reliably predicted CHO, OA, and T. Several stable spectral-metabolite associations persisted across the two watering regimes (drought vs. well-watered), highlighting their potential as spectral biomarkers for non-destructive stress monitoring. Minimal genotype-specific variation suggests that observed spectral and metabolic responses were driven primarily by environmental factors, likely reflecting limited genetic diversity among the commercial Populus genotypes examined. This work establishes VNIR+SWIR hyperspectral imaging as a powerful, non-destructive phenotyping tool for precision monitoring and targeted improvement of drought resilience in bioenergy crops.
Short-Wave Infrared Upconverting Nanoparticles
Optical technologies enable real-time, noninvasive analysis of complex systems but are limited to discrete regions of the optical spectrum. While wavelengths in the short-wave infrared (SWIR) window (typically, 1700-3000 nm) should enable deep subsurface penetration and reduced photodamage, there are few luminescent probes that can be excited in this region. Here, we report the discovery of lanthanide-based upconverting nanoparticles (UCNPs) that efficiently convert 1740 or 1950 nm excitation to wavelengths compatible with conventional silicon detectors. Screening of Ln3+ ion combinations by differential rate equation modeling identifies Ho3+/Tm3+ or Tm3+ dopants with strong visible or NIR-I emission following SWIR excitation. Experimental upconverted photoluminescence excitation (U-PLE) spectra find that 10% Tm3+-doped NaYF4 core/shell UCNPs have the strongest 800 nm emission from SWIR wavelengths, while UCNPs with an added 2% or 10% Ho3+ show the strongest red emission when excited at 1740 or 1950 nm. Mechanistic modeling shows that addition of a low percentage of Ho3+ to Tm3+-doped UCNPs shifts their emission from 800 to 652 nm by acting as a hub of efficient SWIR energy acceptance and redistribution up to visible emission manifolds. Parallel experimental and computational analysis shows rate equation models are able to predict compositions for specific wavelengths of both excitation and emission. These SWIR-responsive probes open a new IR bioimaging window, and are responsive at wavelengths important for vision technologies.
A Framework Based on 2-D Taylor Expansion for Quantifying the Impacts of Subpixel Reflectance Variance and Covariance on Cloud Optical Thickness and Effective Radius Retrievals Based on the Bispectral Method
The bispectral method retrieves cloud optical thickness (τ) and cloud droplet effective radius (re) simultaneously from a pair of cloud reflectance observations, one in a visible or near-infrared (VIS/NIR) band and the other in a shortwave infrared (SWIR) band. A cloudy pixel is usually assumed to be horizontally homogeneous in the retrieval. Ignoring subpixel variations of cloud reflectances can lead to a significant bias in the retrieved τ and re. In the literature, the retrievals of τ and re are often assumed to be independent and considered separately when investigating the impact of subpixel cloud reflectance variations on the bispectral method. As a result, the impact on τ is contributed only by the subpixel variation of VIS/NIR band reflectance and the impact on re only by the subpixel variation of SWIR band reflectance. In our new framework, we use the Taylor expansion of a two-variable function to understand and quantify the impacts of subpixel variances of VIS/NIR and SWIR cloud reflectances and their covariance on the τ and re retrievals. This framework takes into account the fact that the retrievals are determined by both VIS/NIR and SWIR band observations in a mutually dependent way. In comparison with previous studies, it provides a more comprehensive understanding of how subpixel cloud reflectance variations impact the τ and re retrievals based on the bispectral method. In particular, our framework provides a mathematical explanation of how the subpixel variation in VIS/NIR band influences the re retrieval and why it can sometimes outweigh the influence of variations in the SWIR band and dominate the error in re retrievals, leading to a potential contribution of positive bias to the re retrieval. We test our framework using synthetic cloud fields from a large-eddy simulation and real observations from Moderate Resolution Imaging Spectroradiometer. The predicted results based on our framework agree very well with the numerical simulations. Our framework can be used to estimate the retrieval uncertainty from subpixel reflectance variations in operational satellite cloud products and to help understand the differences in τ and re retrievals between two instruments.
Enabling the Assimilation of CrIS Shortwave Infrared Observations in Global NWP at NOAA. Part I: Background and Methods
Radiance observations from Earth-observing satellites have a significant positive impact on numerical weather prediction (NWP) forecasts, but some spectral regions are not fully exploited. Observations from hyperspectral infrared (IR) sounders in the longwave region (650-1100 cm -1 ), for instance, are routinely assimilated in many NWP models, but observations in the shortwave region (2155-2550 cm -1 ) are not. Each of these regions provides information on the temperature structure of the atmosphere, but the shortwave IR (SWIR) region is considered challenging to assimilate due to noise equivalent delta temperature (NEDT) that is highly variable depending on scene brightness temperature and to phenomena that are difficult to model, like non-Local Thermodynamic Equilibrium (NLTE) and solar reflectance. With recent advances in small-satellite technology, SWIR temperature sounders may provide an agile and cost-effective complement to the current constellation of IR sounders. Therefore, a better understanding of the use and impact of SWIR observations in data assimilation for NWP is warranted. In part one of this study, as presented here, the amount of unique information (as determined by Empirical Orthogonal Decomposition (EOD)) made available to a data assimilation system by Cross-track Infrared Sounder (CrIS) SWIR observations is reviewed, recent advancements to the Community Radiative Transfer Model (CRTM) for the simulation of CrIS shortwave radiances are tested, and enhancements to NOAA’s Global Data Assimilation System (GDAS) for the assimilation of CrIS SWIR observations are implemented and evaluated. Part two of this study, which seeks to assess the value of assimilating shortwave IR observations in global NWP, is also introduced.
NGC 4314. I - Visible and short-wavelength infrared surface photometry of the nucleus and bar
BVI (TI CCD) and JHK (University of Texas IR Camera) surface photometry of NGC 4314, an SB (rs)ap anemic spiral with a nuclear ring containing recent star formation, is presented. The shortwave IR (SWIR) frames reveal a nuclear bar of length 2 arcsec at PA of 0 deg. The nuclear ring and associated dust were detected in all SWIR color indices. A nuclear spiral was detected in the visible and SWIR just exterior to the ring. Extremely low-amplitude spiral-shaped deficits were found in the stellar distribution in the SWIR in this same region. These are attributed to dust, since CO is detectable at or near these locations. Average minor-axis profiles show this galaxy to have a nuclear bulge obeying the de Vaucouleurs r exp 1/4 law for values in the range 2-7 arcsec. The extinction and scattering characteristics of dust near the sites of recent star formation in the nuclear ring are discussed.
Development and Application of Non-Linear Image Enhancement and Multi-Sensor Fusion Techniques for Hazy and Dark Imaging
The purpose of this research was to develop enhancement and multi-sensor fusion algorithms and techniques to make it safer for the pilot to fly in what would normally be considered Instrument Flight Rules (IFR) conditions, where pilot visibility is severely restricted due to fog, haze or other weather phenomenon. We proposed to use the non-linear Multiscale Retinex (MSR) as the basic driver for developing an integrated enhancement and fusion engine. When we started this research, the MSR was being applied primarily to grayscale imagery such as medical images, or to three-band color imagery, such as that produced in consumer photography: it was not, however, being applied to other imagery such as that produced by infrared image sources. However, we felt that it was possible by using the MSR algorithm in conjunction with multiple imaging modalities such as long-wave infrared (LWIR), short-wave infrared (SWIR), and visible spectrum (VIS), we could substantially improve over the then state-of-the-art enhancement algorithms, especially in poor visibility conditions. We proposed the following tasks: 1) Investigate the effects of applying the MSR to LWIR and SWIR images. This consisted of optimizing the algorithm in terms of surround scales, and weights for these spectral bands; 2) Fusing the LWIR and SWIR images with the VIS images using the MSR framework to determine the best possible representation of the desired features; 3) Evaluating different mixes of LWIR, SWIR and VIS bands for maximum fog and haze reduction, and low light level compensation; 4) Modifying the existing algorithms to work with video sequences. Over the course of the 3 year research period, we were able to accomplish these tasks and report on them at various internal presentations at NASA Langley Research Center, and in presentations and publications elsewhere. A description of the work performed under the tasks is provided in Section 2. The complete list of relevant publications during the research periods is provided in Section 5. This research also resulted in the generation of intellectual property.
Detectors and Focal Plane Modules for Weather Satellites
Weather satellite instruments require detectors with a variety of wavelengths ranging from the visible to VLWIR. One of the remote sensing applications is the geostationary GOES-ABI imager covering wavelengths from the 450 to 490 nm band through the 13.0 to 13.6 micron band. There are a total of 16 spectral bands covered. The Cross-track infrared Sounder (CrIS) is a Polar Orbiting interferometric sensor that measures earth radiances at high spectral resolution, using the data to provide pressure, temperature and moisture profiles of the atmosphere. The pressure, temperature and moisture sounding data are used in weather prediction models that track storms, predict levels of precipitation etc. The CrIS instrument contains SWIR (lamba(sub c) approximately 5 micron at 98K), MWIR (lambda(sub c) approximately 9 micron at 98K) and LWIRs (lamba(sub c) approximately 15.5 micron at 81K) bands in three Focal Plane Array Assemblies (FPAAs). GOES-ABI contains three focal plane modules (FPMs), (i) a visible-near infrared module consisting of three visible and three near infrared channels, (ii) a MWIR module comprised of five channels from 3.9 micron to 8.6 micron and (iii) a 9.6 micron to 13.3 micron, five-channel LWIR module. The VNIR FPM operates at 205 K, and the MWIR and LWIR FPMs operate at 60 K. Each spectral channel has a redundant array built into a single detector chip. Switching is thus permitted from the primary selected array in each channel to the redundant array, given any degradation in performance of the primary array during the course of the mission. Silicon p-i-n detectors are used for the 0.47 micron to 0.86 micron channels. The thirteen channels above 1 micron are fabricated in various compositions of Hg1-xCdxTe, and in this particular case using two different detector architectures. The 1.38 micron to 9.61 micron channels are all fabricated in Hg1-xCdxTe grown by Liquid Phase Epitaxy (LPE) using the HDVIP detector architecture. Molecular beam epitaxy (MBE)-grown Hg1-xCdxTe material are used for the LWIR 10.35 micron to 13.3 micron channels fabricated in Double layer planar heterostructure (DLPH) detectors. This is the same architecture used for the CrIS detectors CrIS detectors are 850 micron diameter detectors with each FPAA consisting of nine photovoltaic detectors arranged in a 3 x 3 pattern. Each detector has an accompanying cold preamplifier. SWIR and MWIR FPAAs operate at 98 K and the LWIR FPAA at 81 K, permitting the use of passive radiators to cool the detectors. D* requirements at peak wavelength are ≥ 5.0E+10 Jones for LWIR, ≥ 9.3E+10 Jones for MWIR and ≥ 3.0E+11 Jones for SWIR. All FPAAs exceeded the D* requirements. Measured mean values for the nine photodiodes in each of the LWIR, MWIR and SWIR FPAAs are D* = 5.3 x 10(exp 10) cm-Hz(exp 1/2)/W at 14.0 micron, 1.0 x 10(exp 11) cm-Hz(exp 1/2)/W at 8.0 micron and 3.1 x 10(exp 11) cm-Hz(exp 1/2)/W at 4.64 micron.
Detectors and Focal Plane Modules for Weather Instruments
Weather satellite instruments require detectors with a variety of wavelengths ranging from the visible to VLWIR. The Cross-track infrared Sounder (CrIS) is a Polar Orbiting interferometric sensor that measures earth radiances at high spectral resolution, using the data to provide pressure, temperature and moisture profiles of the atmosphere. The pressure, temperature and moisture sounding data are used in weather prediction models that track storms, predict levels of precipitation etc. The CrIS instrument contains SWIR (lambda(sub c) (is) approximately 5 micrometers at 98 K), MWIR (lambda(sub c) (is) approximately 9 micrometers at 98 K) and LWIRs (lambda(sub c) (is) approximately 15.4 m at 81 K) bands in three Focal Plane Array Assemblies (FPAAs). CrIS detectors are 850 micrometers diameter detectors with each FPAA consisting of nine photovoltaic detectors arranged in a 3 x 3 pattern. Molecular beam epitaxy (MBE)-grown Hg1-xCdxTe material are used for the detectors fabricated in a modified Double Layer Planar Heterostructure (DLPH) architecture. Each detector has an accompanying cold preamplifier. SWIR and MWIR FPAAs operate at 98 K and the LWIR FPAA at 81 K, permitting the use of passive radiators to cool the detectors. D* requirements at peak 14.01 micrometers wavelength are greater than 5.0E+10 Jones for LWIR, greater than 7.5E+10 Jones at 8.26 micrometers for MWIR and greater than 3.0E+11 Jones at peak 4.64 micrometers wavelength for SWIR. All FPAAs exceeded the D* requirements. Measured mean values for the nine photodiodes in each of the LWIR, MWIR and SWIR FPAAs are D* = 5.3 x 10(exp 10) cm-Hz1/2/W at 14.0 micrometers, 9.6 x 10(exp 10) cm-Hz1/2/W at 8.0 micrometers and 3.4 x 10(exp 11) cm-Hz1/2/W at 4.64 micrometers.
A Framework for Quantifying the Impacts of Sub-Pixel Reflectance Variance and Covariance on Cloud Optical Thickness and Effective Radius Retrievals Based on the Bi-Spectral Method.
The so-called bi-spectral method retrieves cloud optical thickness (τ) and cloud droplet effective radius (re) simultaneously from a pair of cloud reflectance observations, one in a visible or near infrared (VIS/NIR) band and the other in a shortwave-infrared (SWIR) band. A cloudy pixel is usually assumed to be horizontally homogeneous in the retrieval. Ignoring sub-pixel variations of cloud reflectances can lead to a significant bias in the retrieved τ and re. In this study, we use the Taylor expansion of a two-variable function to understand and quantify the impacts of sub-pixel variances of VIS/NIR and SWIR cloud reflectances and their covariance on the τ and re retrievals. This framework takes into account the fact that the retrievals are determined by both VIS/NIR and SWIR band observations in a mutually dependent way. In comparison with previous studies, it provides a more comprehensive understanding of how sub-pixel cloud reflectance variations impact the τ and re retrievals based on the bi-spectral method. In particular, our framework provides a mathematical explanation of how the sub-pixel variation in VIS/NIR band influences the re retrieval and why it can sometimes outweigh the influence of variations in the SWIR band and dominate the error in re retrievals, leading to a potential contribution of positive bias to the re retrieval.
Is There an Optimal CO2 Partial Column for Flux Inversions?
The fidelity of flux estimates from an atmospheric inversion depends on the ability of atmospheric transport models to simulate the measured quantity. For species such as CO2, with surface fluxes and a large network of surface measurements, this means correctly simulating the dynamics of the planetary boundary layer (PBL), which is one of the most uncertain aspects of atmospheric transport modeling. In contrast, the simulated total column average mole fraction of CO2 (XCO2) is largely insensitive to simulated PBL dynamics. Therefore, measurements of XCO2 provided by current and future short wave infrared (SWIR) greenhouse gas (GHG) satellites such as GOSAT and the OCO family would seem to be more appropriate to flux inversions, as far as minimizing transport model errors (the "noise") is concerned. Unfortunately, the flux-induced variation of CO2 (the "signal") is the largest within the PBL and smallest in XCO2. Therefore, assimilating XCO2 as opposed to PBL CO2 need not give us the strongest "signal to noise" in flux inversions. Recent work on GOSAT and OCO2 retrievals suggest that SWIR satellite spectra may be used to estimate a lower partial column CO2, which could be assimilated in a flux inversion, instead of XCO2.Here we report on a study to assess whether there is an optimal partial column average CO2, intermediate between PBL CO2 and XCO2, whose assimilation might yield the best signal to noise in flux inversions, where (as before) "signal" is the flux-induced variation and "noise" is the error in transport modeling. We simulate atmospheric CO2 with five different global transport models and a common surface CO2 flux over ten years. We consider the spread across the five models to be a proxy for transport model error (the "noise"), and the common variation of CO2 in all five models to be a proxy for the "signal". We compare these signals and noises at different spatiotemporal scales for different partial column specifications to investigate whether there exists an optimal partial column that has large surface flux-driven variations and yet is relatively insensitive to errors in transport models. Finally, we comment on the feasibility of estimating such a partial column from current and future SWIR GHG satellites in the light of recent work on vertically resolved CO2 from current SWIR GHG satellites.
Sensitivity of Multispectral Imager Liquid Water Cloud Microphysical Retrievals to the Index of Refraction
A cloud property retrieved from multispectral imagers having spectral channels in the shortwave infrared (SWIR) and/or midwave infrared (MWIR) is the effective particle radius (CER), a radiatively relevant weighting of the cloud particle size distribution. The physical basis of the CER retrieval is the dependence of SWIR/MWIR cloud reflectance on the cloud particle single scattering absorption, which in turn depends on the complex index of refraction of bulk liquid water (or ice) in addition to the cloud particle size. There is a general consistency in the choice of the liquid water index of refraction by the cloud remote sensing community, largely due to the few available independent datasets and compilations. Here we examine the sensitivity of CER retrievals to the available laboratory index of refraction datasets in the SWIR and MWIR using the retrieval software package that produces NASA’s standard MODIS/VIIRS continuity cloud products. The sensitivity study incorporates two laboratory index of refraction datasets that include measurements at supercooled water temperatures, one in the SWIR [Kou et al., 1993] and one in the MWIR [Wagner et al., 2005]. Neither has been broadly utilized in the cloud remote sensing community. It is shown that these two new datasets can significantly change CER retrievals (e.g., 1-2 μm) relative to common datasets used by the community. Further, index of refraction data for a 265 K water temperature results in more consistent retrievals between the two spectrally distinct 2.2 μm atmospheric window channels on MODIS and VIIRS. As a result, the 265 K values from the SWIR and MWIR index of refraction datasets were adopted for use in the production version of the continuity cloud product. The results indicate the need to better understand temperature-dependent bulk water absorption and uncertainties in these spectral regions.