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NASA NTRS2017

TPSAS-NF1676L-28148-DND

Currently, ocean carbon biomass is estimated from ocean color measurements primarily through particulate backscatter coefficients (bbp). Small non-algal particles contribute significantly to bbp due to the fact that small particles scatter more isotropically while bigger particles scatter mostly in the forward direction. CALIPSO’s ocean subsurface cross polarization measurements (Figure 1) are not sensitive to small particles far less than 2 microns in size since these particles rarely cause depolarization. Thus, cross polarization backscatter is contributed mostly by larger, depolarizing phytoplankton particles. This is why CALIPSO’s cross polarization has much larger contrasts comparing with MODIS reflectance (CALIPSO cross polarization is very weak in Gyres and much stronger in high latitudes, See Figure 1). CALIPSO cross-polarization measurements in the Southern Oceans also suggest that water cloud droplet number concentration covaries with phytoplankton carbon biomass (Figure 2), but it has less correlation with particulate organic carbon (POC) (Figure 2) and chlorophyll concentration. The study also agrees with water cloud droplet size retrieved from Parasol’s polarization measurements.

Yongxiang Hu↗

NASA NTRS2017

Water-Leaving Contribution to Polarized Radiation Field Over Ocean

The top-of-atmosphere (TOA) radiation field from a coupled atmosphere-ocean system (CAOS) includes contributions from the atmosphere, surface, and water body. Atmo-spheric correction of ocean color imagery is to retrieve water-leaving radiance from the TOA measurement, from which ocean bio-optical properties can be obtained. Knowledge of the ab-solute and relative magnitudes of water-leaving signal in the TOA radiation field is important for designing new atmospheric correction algorithms and developing retrieval algorithms for new ocean biogeochemical parameters. In this paper we present a systematic sensitivity study of water-leaving contribution to the TOA radiation field, from 340 nm to 865 nm, with polarization included. Ocean water inherent optical properties are derived from bio-optical models for two kinds of waters, one dominated by phytoplankton (PDW) and the other by non-algae particles (NDW). In addition to elastic scattering, Raman scattering and fluorescence from dissolved organic matter in ocean waters are included. Our sensitivity study shows that the polarized reflectance is minimized for both CAOS and ocean signals in the backscattering half plane, which leads to numerical instability when calculating water leaving relative contribution, the ratio between polarized water leaving and CAOS signals. If the backscattering plane is excluded, the water-leaving polarized signal contributes less than 9% to the TOA polarized reflectance for PDW in the whole spectra. For NDW, the polarized water leaving contribution can be as much as 20% in the wavelength range from 470 to 670 nm. For wavelengths shorter than 452 nm or longer than 865 nm, the water leaving contribution to the TOA polarized reflectance is in general smaller than 5% for NDW. For the TOA total reflectance, the water-leaving contribution has maximum values ranging from 7% to 16% at variable wavelengths from 400 nm to 550 nm from PDW. The water leaving contribution to the TOA total reflectance can be as large as 35%for NDW, which is in general peaked at 550 nm. Both the total and polarized reflectances from water-leaving contributions approach zero in the ultraviolet and near infrared bands. These facts can be used as constraints or guidelines when estimating the water leaving contribution to the TOA reflectance for new atmospheric correction algorithms for ocean color imagery.

inelastic scatterin↗

NASA NTRS1999

Global Aerosol Radiative Forcing Derived from Sea WiFS-Inferred Aerosol Optical Properties

Aerosol optical properties inferred from the Sea-viewing Wide Field-of-view Sensor (SeaWiFS) radiance measurements are used to compute the aerosol shortwave radiative forcing using a radiative transfer model. The aerosol optical thickness at the wavelength of 865-nm is taken from the SeaWIFS archive. It is found that the nominal optical thickness over oceans ranges from 0.1 to 0.2. Using a maritime aerosol model and the radiances measured at the various SeaWiFS channels, the Angstrom exponent is determined to be 0.2174, the single-scattering albedo to be 0.995, and the asymmetry factor to be 0.786. The radiative transfer model has eight bands in the visible and ultraviolet spectral regions and three bands in the near infrared. It includes the absorption due to aerosols, water vapor, carbon dioxide, and oxygen, and the scattering due to aerosols and gases (Rayleigh scattering). The radiative forcing is computed over global oceans for four months (January, April, July, and October, 1998) to represent four seasons. It is found that the aerosol radiative forcing is large and changes significantly with seasons near the continents with large-scale forest fires and desert dust. Averaged over oceans and the four months, the aerosol radiative forcing is approximately 7 W/sq m at the top of the atmosphere. This large radiative forcing is expected to have a significant cooling effect on the Earth's climate as implied from simulations of a number of general circulation models.

Chou, Ming-Dah↗

NASA NTRS2020

Dust Aerosol Retrieval Over the Oceans With the MODIS/VIIRS Dark Target Algorithm: 2. Nonspherical Dust Model

The Dark‐target (DT) aerosol algorithm retrieves spectral Aerosol Optical Depth (AOD) and other aerosol properties from Moderate‐resolution Imaging Spectrometer (MODIS) reflectance observations. Over the ocean, the DT algorithm is known to contain scattering‐angle‐dependent biases in its retrievals of AOD, Angstrom Exponent (AE), and Fine Mode Fraction (FMF) for dust aerosols. Following a two‐step strategy to improve the DT retrieval of dust over ocean, for which the first step is to identify dusty pixels (reported in “Part 1”), in this “Part 2,” we report on construction of a new dust model lookup table (LUT) and the strategy for applying it within the existing DT algorithm. In particular, we evaluate different characterizations of dust optical properties from a variety of frameworks and databases, and compare them with the current DT retrieval assumptions. Substituting the standard operational LUT with a spheroid dust model with identified dusty pixels shows significant improvement when compared with collocated AERONET‐identified dusty pixels. Specifically, the application of the new dust model to dusty pixels reduces their AOD bias from 0.06 to 0.02 while improving the fraction of retrievals within expected error from 64% to 82%. At the same time, the overall bias in AE is reduced from 0.13 to 0.06, and the scattering‐angle‐dependent AE bias is largely eliminated. In testing on two full months of data (April and July), the new retrieval will reduce the monthly mean AOD by up to 0.1 and 0.2 in the north Atlantic and Arabian seas, respectively. The average AE and FMF are also reduced in these dust heavy regions

dust aerosol retrieval↗

NASA NTRS2022

Optimal Estimation Framework for Ocean Color Atmospheric Correction and Pixel-level Uncertainty Quantification

Ocean color remote sensing requires compensation for atmospheric scattering and absorption (aerosol, Rayleigh, and trace gases), referred to as atmospheric correction (AC). AC allows inference of parameters such as spectrally resolved remote sensing reflectance ( R rs )(λ) ; sr 1 ) at the ocean surface from the top-of-atmosphere reflectance. Often, the uncertainty of this process is not fully explored. Bayesian inference techniques provide a simultaneous AC and uncertainty assessment via a full posterior distribution of the relevant variables, given the prior distribution of those variables and the radiative transfer (RT) likelihood function. Given uncertainties in the algorithm inputs, the Bayesian framework enables better constraints on the AC process by using the complete spectral information compared to traditional approaches that use only a subset of bands for AC. This paper investigates a Bayesian inference research method (Optimal Estimation, OE) for ocean color AC by simultaneously retrieving atmospheric and ocean properties using all visible and near-infrared spectral bands. The OE algorithm analytically approximates the posterior distribution of parameters based on normality assumptions and provides a potentially viable operational algorithm with a reduced computational expense. We developed a Neural Network (NN) RT forward model look-up-table-based emulator to increase algorithm efficiency further and thus speed up the likelihood computations. We then applied the OE algorithm to synthetic data and observations from the MODerate resolution Imaging Spectroradiometer (MODIS) on NASA’s Aqua spacecraft. We compared the R rs )(λ) retrieval and its uncertainty estimates from the OE method with in-situ validation data from the SeaWiFS Bio-optical Archive and Storage System (SeaBASS) and Aerosol Robotic Network Ocean Color (AERONET-OC) datasets. The OE algorithm improved R rs )(λ) estimates relative to the NASA standard operational algorithm by improving all statistical metrics at 443, 555, and 667 nm. Unphysical negative R rs )(λ) , which often appear in complex water conditions, was reduced by a factor of 3. The OE-derived pixel-level R rs )(λ) uncertainty estimates were also assessed relative to in-situ data and were shown to have skill.

Atmospheric correction↗

NASA NTRS1999

Principles in Remote Sensing of Aerosol from MODIS Over Land and Ocean

The well-calibrated spectral radiances measured by MODIS will be processed to retrieve daily aerosol properties that include optical thickness and mass loading over land and optical thickness, the mean particle size of the dominant mode and the ratio between aerosol modes over ocean. In addition, after launch, aerosol single scattering albedo will be calculated as an experimental product. The retrieval process over land is based on a dark target method that identifies appropriate targets in the mid-IR channels and uses an empirical relationship found between the mid-ER and the visible channels to estimate surface reflectance in the visible from the mid-HZ reflectance measured by satellite. The method employs new aerosol models for industrial, smoke and dust aerosol. The process for retrieving aerosol over the ocean makes use of the wide spectral band from 0.55-2.13 microns and a look-up table constructed from combinations of five accumulation modes and five coarse modes. Both the over land and over ocean algorithms have been validated with satellite and airborne radiance measurements. We estimate that MODIS will be able to measure aerosol optical thickness (t) to within 0.05 +/- 0.2t over land and to within 0.05 +/- 0.05t over ocean. Much of the earth's surface is located far from aerosol sources and experience very low aerosol optical thickness. Will the accuracy expected from MODIS retrievals be sufficient to measure the global aerosol direct and indirect forcing? We are attempting to answer this question using global model results and cloud climatology.

Remer, L. A.↗

NASA NTRS2013

Retrieving Marine Inherent Optical Properties from Satellites Using Temperature and Salinity-dependent Backscattering by Seawater

Time-series of marine inherent optical properties (IOPs) from ocean color satellite instruments provide valuable data records for studying long-term time changes in ocean ecosystems. Semi-analytical algorithms (SAAs) provide a common method for estimating IOPs from radiometric measurements of the marine light field. Most SAAs assign constant spectral values for seawater absorption and backscattering, assume spectral shape functions of the remaining constituent absorption and scattering components (e.g., phytoplankton, non-algal particles, and colored dissolved organic matter), and retrieve the magnitudes of each remaining constituent required to match the spectral distribution of measured radiances. Here, we explore the use of temperature- and salinity-dependent values for seawater backscattering in lieu of the constant spectrum currently employed by most SAAs. Our results suggest that use of temperature- and salinity-dependent seawater spectra elevate the SAA-derived particle backscattering, reduce the non-algal particles plus colored dissolved organic matter absorption, and leave the derived absorption by phytoplankton unchanged.

Passive Remote Sensing↗

NASA NTRS2020

Neural Network Reflectance Prediction Model for Both Open Ocean and Coastal Waters

Remote sensing of global ocean color is a valuable tool for understanding the ecology and biogeochemistry of the worlds oceans, and provides critical input to our knowledge of the global carbon cycle and the impacts of climate change. Ocean polarized reflectance contains information about the constituents of the upper ocean euphotic zone, such as colored dissolved organic matter (CDOM), sediments, phytoplankton, and pollutants. In order to retrieve the information on these constituents, remote sensing algorithms typically rely on radiative transfer models to interpret water color or remote-sensing reflectance; however, this can be resource-prohibitive for operational use due to the extensive CPU time involved in radiative transfer solutions. In this work, we report a fast model based on machine learning techniques, called Neural Network Reflectance Prediction Model (NNRPM), which can be used to predict ocean bidirectional polarized reflectance given inherent optical properties of ocean waters. This supervised model is trained using a large volume of data derived from radiative transfer simulations for coupled atmosphere and ocean systems using the successive order of scattering technique (SOS-CAOS). The performance of the model is validated against another large independent test dataset generated from SOS-CAOS. The model is able to predict both polarized and unpolarized reflectances with an absolute error (AE) less than 0.004 for 99% of test cases. We have also shown that the degree of linear polarization (DoLP) for unpolarized incident light can be predicted with an AE less than 0.002 for 99% of test cases. In general, the simulation time of SOS-CAOS depends on optical depth, and required accuracy. When comparing the average speeds of the NNRPM against the SOS-CAOS model for the same parameters, we see that the NNRPM is able to predict the Ocean BRDF 6000 times faster than SOS-CAOS. Both ultraviolet and visible wavelengths are included in the model to help differentiate between dissolved organic material and chlorophyll in the study of the open ocean and the coastal zone. The incorporation of this model into the retrieval algorithm will make the retrieval process more efficient, and thus applicable for operational use with global satellite observations.

radiative transfer↗

NASA NTRS2019

A Fast Vector Radiative Transfer Model for the Atmosphere-Ocean Coupled System

To infer atmospheric and oceanic constituent properties from polarimetric observations, an efficient and accurate retrieval algorithm is desirable. In-line radiative transfer calculations are indispensable if a large state vector, including both atmospheric profiles and surface properties, is used to improve retrieval accuracy. However, in-line radiative transfer calculations are usually not computationally efficient for remote sensing applications. Therefore, there is a pressing need to develop an accurate and fast vector radiative transfer model (RTM) to fully utilize satellite polarimetric observations. This paper reports on a fast vector RTM, referred to as TAMU-VRTM, in support of polarimetric remote sensing, which is capable of simulating the Stokes vector values observed at the top of the atmosphere and at the surface by fully considering absorption, scattering, and emission in the atmosphere and ocean. Gaseous absorption is parameterized with respect to gas concentration, temperature, and pressure, by using a regression method applicable to an inhomogeneous atmospheric path. An efficient two-component approach combining the small angle approximation and the adding-doubling method is utilized to solve the vector radiative transfer equation (RTE). The thermal emission component of the RTE solution is obtained by an efficient doubling process. The air-sea interface is treated as a wind-ruffled rough surface in the model to mimic a realistic ocean surface. Several oceanic optical property models are introduced to model ocean inherent optical properties. To demonstrate the applicability of the TAMUVRTM, simulations are compared with satellite observations, and results from other vector radiative transfer methods including benchmarks.

radiative transfer in coupled atmosphere-ocean sys↗

NASA NTRS1973

A noncoherent model for microwave emissions and backscattering from the sea surface

The two-scale (small irregularities superimposed upon large undulations) scattering theory proposed by Semyonov was extended and used to compute microwave apparent temperature and the backscattering cross section from ocean surfaces. The effect of the small irregularities upon the scattering characteristics of the large undulations is included by modifying the Fresnel reflection coefficients; whereas the effect of the large undulations upon those of the small irregularities is taken into account by averaging over the surface normals of the large undulations. The same set of surface parameters is employed for a given wind speed to predict both the scattering and the emission characteristics at both polarizations.

Wu, S. T.↗

NASA NTRS2019

Modeling Atmosphere-Ocean Radiative Transfer: A PACE Mission Perspective

The research frontiers of radiative transfer (RT) in coupled atmosphere-ocean systems are explored to enable new science and specifically to support the upcoming Plankton, Aerosol, Cloud ocean Ecosystem (PACE) satellite mission. Given (i) the multitude of atmospheric and oceanic constituents at any given moment that each exhibits a large variety of physical and chemical properties and (ii) the diversity of light-matter interactions (scattering, absorption, and emission), tackling all outstanding RT aspects related to interpreting and/or simulating light reflected by atmosphere-ocean systems becomes impossible. Instead, we focus on both theoretical and experimental studies of RT topics important to the science threshold and goal questions of the PACE mission and the measurement capabilities of its instruments. We differentiate between (a) forward (FWD) RT studies that focus mainly on sensitivity to influencing variables and/or simulating data sets, and (b) inverse (INV) RT studies that also involve the retrieval of atmosphere and ocean parameters. Our topics cover (1) the ocean (i.e., water body): absorption and elastic/inelastic scattering by pure water (FWD RT) and models for scattering and absorption by particulates (FWD RT and INV RT); (2) the air-water interface: variations in ocean surface refractive index (INV RT) and in whitecap reflectance (INV RT); (3) the atmosphere: polarimetric and/or hyperspectral remote sensing of aerosols (INV RT) and of gases (FWD RT); and (4) atmosphere-ocean systems: benchmark comparisons, impact of the Earth's sphericity and adjacency effects on space-borne observations, and scattering in the ultraviolet regime (FWD RT). We provide for each topic a summary of past relevant (heritage) work, followed by a discussion (for unresolved questions) and RT updates.

Chowdhary, Jacek↗

NASA NTRS1988

The 1982-83 ENSO global convective precipitation anomaly derived from Nimbus-7 SMMR 37 GHz scattering measurements

The scattering algorithms of Spencer (1983, 1986) are applied to the December-May period from 1981-1984, to obtain the 1982-1983 December-May convective precipitation anomaly patterns associated with the El Nino/Southern Oscillation. It is shown that semiannual convective precipitation patterns over global land and ocean regions can be mapped using the volume scattering effect of precipitation-size ice on Nimbus-7 SMMR 37 GHz brightness temperature. It is suggested that the Defense Meteorological Satellite Program Special Sensor Microwave/Imager 85 GHz data (in combination with 37 and 19 GHz data) can be valuable in global surveys of precipitation patterns.

Spencer, Roy W.↗

NASA NTRS2002

Using TRMM Data To Understand Interannual Variations In the Tropical Water Balance

A significant element of the science rationale for TRMM centered on assembling rainfall data needed to validate climate models-- climatological estimates of precipitation, its spatial and temporal variability, and vertical modes of latent heat release. Since the launch of TRMM, a great interest in the science community has emerged for quantifying interannual variability (IAV) of precipitation and its relationship to sea-surface temperature (SST) changes. The fact that TRMM has sampled one strong warm/ cold ENSO couplet, together with the prospect for a mission lifetime approaching ten years, has bolstered this interest in these longer time scales. Variability on a regional basis as well as for the tropics as a whole is of concern. Our analysis of TRMM results so far has shown surprising lack of concordance between various algorithms in quantifying IAV of precipitation. The first objective of this talk is to quantify the sensitivity of tropical precipitation to changes in SSTs. We analyze performance of the 3A11, 3A25, and 3B31 algorithms and investigate their relationship to scattering-- based algorithms constructed from SSM/I and TRMM 85 kHz data. The physical basis for the differences (and similarities) in depicting tropical oceanic and land rainfall will be discussed. We argue that scattering-based estimates of variability constitute a useful upper bound for precipitation variations. These results lead to the second question addressed in this talk-- How do TRMM precipitation / SST sensitivities compare to estimates of oceanic evaporation and what are the implications of these uncertainties in determining interannual changes in large-scale moisture transport? We summarize results of an analysis performed using COADS data supplemented by SSM/I estimates of near-surface variables to assess evaporation sensitivity to SST. The response of near 5 W sq m/K is compared to various TRMM precipitation sensitivities. Implied moisture convergence over the tropics and its sensitivity to errors of these algorithms is discussed.

Robertson, Franklin R.↗

NASA NTRS1984

Theory and measure of certain image norms in SAR

The principal properties of synthetic aperture radar SAR imagery of point and distributed objects are summarized. Against this background, the response of a SAR (Synthetic Aperture Radar) to the moving surface of the sea is considered. Certain conclusions are drawn as to the mechanism of interaction between microwaves and the sea surface. Focus and speckle spectral tests may be used on selected SAR imagery for areas of the ocean. The fine structure of the sea imagery is sensitive to processor focus and adjustment. The ocean reflectivity mechanism must include point like scatterers of sufficient radar cross section to dominate the return from certain individual resolution elements. Both specular and diffuse scattering mechanisms are observed together, to varying degree. The effect is sea state dependent. Several experiments are proposed based on imaging theory that could assist in the investigation of reflectivity mechanisms.

Raney, R. K.↗

NASA NTRS1989

V photometry of Titania, Oberon, and Triton

The phase angle and orbital brightness variations of Titania, Oberon, and Triton are presently obtained through analysis of V filter photometry obtained at Mauna Kea in 1982-1983. While Titania and Oberon exhibit magnitude variations with phase angle comparable to those of low-to-moderate albedo asteroids observed within several deg of opposition, Triton's phase variation is distinctly different from these and has a phase coefficient consistent with either a high-albedo regolith or an optically thick nonparticulate scattering layer (perhaps an atmosphere, or an ocean). A low-albedo regolith cannot on the strength of these data be ruled out, however.

Goguen, J. D.↗

NASA NTRS1995

Polarization and wavelength diversities of Gulf Stream fronts imaged by AIRSAR

During the 1990 Gulf Stream Experiment, NASA/JPL AIRSAR imaged the north edge of the Gulf Stream near the coast of Virginia. Simultaneous in-situ measurements of currents, temperatures, salinities, etc. were made for several crossings of the north edge by the R/V Cape Henlopen. Measurements identified two fronts with shearing and converging flows. The polarimetric SAR images from the fronts showed two bright linear features. One of them corresponds to the temperature front, which separated the warm Gulf Stream water to the south from a cool, freshwater filament to the north. The other line, located about 8 km north of the temperature front, is believed to correspond to the velocity front between the filament and the slope water. At these fronts, wave-current interactions produced narrow bands of steep and breaking waves manifesting higher radar returns in polarimetric SAR images. In general, our AIRSAR imagery shows that the signal-to-clutter ratio of radar cross sections for the temperature front is higher than that of the velocity front. In this paper, we study the polarization and wavelength diversities of radar response of these two fronts using the P-, L-, and C-Band Polarimetric SAR data. The north-south flight path of the AIRSAR crossed the temperature front several times and provided valuable data for analysis. Three individual passes are investigated. We found that for the temperature front, the cross-pol (HV) responses are much higher than co-pol responses (VV and HH), and that P-Band HV has the highest signal to clutter ratio. For the velocity front, the ratio is the strongest in P-Band VV, and it is indistinguishable for all polarizations in C-Band. The radar cross sections for all three polarization (HH, HV, and VV) and for all three bands are modelled using an ocean wave model and a composite Bragg scattering model. In our initial investigations, the theoretical model agrees qualitatively with the AIRSAR observations.

Lee, J. S.↗

NASA NTRS2021

Saharan dust effects on North Atlantic sea surface skin Temperatures

Saharan dust outbreaks frequently propagate westward over the Atlantic Ocean; accurate quantification of the dust aerosol scattering and absorption effect on the surface radiative fluxes (SRF) is fundamental to understanding critical climate feedbacks. By exploiting large sets of measurements from many ship campaigns in conjunction with reanalysis products, this study characterizes the sensitivity of the SRF and skin Sea‐Surface Temperature (SSTskin) to the Saharan dust aerosols using models of the atmospheric radiative transfer and thermal skin effect. Saharan dust outbreaks can decrease the surface shortwave radiation up to 190 W/sq.m, and an analysis of the corresponding SST(skin) changes using a thermal skin model suggests dust‐induced cooling effects as large as −0.24 K during daytime and a warming effect of up of 0.06 K during daytime and nighttime respectively. Greater physical insight into the radiative transfer through an aerosol‐burdened atmosphere will substantially improve the predictive capabilities of weather and climate studies on a regional basis.

Saharan Dust↗

NASA NTRS2021

Polarimetric sensitivity of light-absorbing carbonaceous aerosols over ocean: A theoretical assessment

Visible-light-absorbing carbonaceous aerosols within the boundary layer affect the radiance and polarization states of the radiation at the top of the atmosphere. Remote sensing from suborbital and satellite-based platforms utilizes these radiance and polarization signals to retrieve the key properties of these aerosols. Recent retrieval algorithms have shown a progressive trend toward including multi-angular and multi-spectral polarimetric measurements to produce better retrieval accuracy in comparison to those using measurements based on a single viewing angle. Here, we perform a theoretical investigation of the top of atmosphere (TOA) radiance-related reflectance factor (bidirectional reflectance factor (BRF)) and the two types of polarimetry-related factors (polarized bidirectional reflectance factor (pBRF) and the degree of linear polarization (DoLP)) for different types of atmospheric light-absorbing carbonaceous aerosols as a function of particle size distribution. We selected three polarimetric bands corresponding to those utilized by NASA's Airborne Multiangle SpectroPolarimetric Imager (AirMSPI)—near-UV (470 nm), visible (660 nm), and near-infrared (865 nm)—for our simulations which were performed over ocean surface using the successive order of scattering (SOS) algorithm coupled to a Lorenz-Mie aerosol optics model. The analysis of particle phase matrix elements indicates a close relationship between the angular dependencies of DoLP and associated phase matrix components at the shortest polarimetric band (470 nm). Using Jacobian analysis, we find that the radiance- and polarimetry-related reflectance factors of weakly light-absorbing aerosols, such as brown carbon, are more sensitive to changes in particle size and imaginary refractive index in comparison with those of black carbon, which is strongly light-absorbing. Our results suggest that the DoLP data could be used by future retrieval algorithms for reliably estimating microphysical properties of absorbing carbonaceous aerosols with imaginary refractive index less than 0.4.

refractive index↗