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NASA NTRS2012

Aerosol and Surface Parameter Retrievals for a Multi-Angle, Multiband Spectrometer

This software retrieves the surface and atmosphere parameters of multi-angle, multiband spectra. The synthetic spectra are generated by applying the modified Rahman-Pinty-Verstraete Bidirectional Reflectance Distribution Function (BRDF) model, and a single-scattering dominated atmosphere model to surface reflectance data from Multiangle Imaging SpectroRadiometer (MISR). The aerosol physical model uses a single scattering approximation using Rayleigh scattering molecules, and Henyey-Greenstein aerosols. The surface and atmosphere parameters of the models are retrieved using the Lavenberg-Marquardt algorithm. The software can retrieve the surface and atmosphere parameters with two different scales. The surface parameters are retrieved pixel-by-pixel while the atmosphere parameters are retrieved for a group of pixels where the same atmosphere model parameters are applied. This two-scale approach allows one to select the natural scale of the atmosphere properties relative to surface properties. The software also takes advantage of an intelligent initial condition given by the solution of the neighbor pixels.

Broderick, Daniel↗

NASA NTRS2012

Intercomparison of MODIS Albedo Retrievals and In Situ Measurements Across the Global FLUXNET Network

Surface albedo is a key parameter in the Earth's energy balance since it affects the amount of solar radiation directly absorbed at the planet surface. Its variability in time and space can be globally retrieved through the use of remote sensing products. To evaluate and improve the quality of satellite retrievals, careful intercomparisons with in situ measurements of surface albedo are crucial. For this purpose we compared MODIS albedo retrievals with surface measurements taken at 53 FLUXNET sites that met strict conditions of land cover homogeneity. A good agreement between mean yearly values of satellite retrievals and in situ measurements was found (R(exp 2)= 0.82). The mismatch is correlated to the spatial heterogeneity of surface albedo, stressing the relevance of land cover homogeneity when comparing point to pixel data. When the seasonal patterns of MODIS albedo is considered for different plant functional types, the match with surface observation is extremely good at all forest sites. On the contrary, in non-forest sites satellite retrievals underestimate in situ measurements across the seasonal cycle. The mismatch observed at grasslands and croplands sites is likely due to the extreme fragmentation of these landscapes, as confirmed by geostatistical attributes derived from high resolution scenes.

Cescatti, Alessandro↗

NASA NTRS2011

Statistically Optimized Inversion Algorithm for Enhanced Retrieval of Aerosol Properties from Spectral Multi-Angle Polarimetric Satellite Observations

The proposed development is an attempt to enhance aerosol retrieval by emphasizing statistical optimization in inversion of advanced satellite observations. This optimization concept improves retrieval accuracy relying on the knowledge of measurement error distribution. Efficient application of such optimization requires pronounced data redundancy (excess of the measurements number over number of unknowns) that is not common in satellite observations. The POLDER imager on board the PARASOL microsatellite registers spectral polarimetric characteristics of the reflected atmospheric radiation at up to 16 viewing directions over each observed pixel. The completeness of such observations is notably higher than for most currently operating passive satellite aerosol sensors. This provides an opportunity for profound utilization of statistical optimization principles in satellite data inversion. The proposed retrieval scheme is designed as statistically optimized multi-variable fitting of all available angular observations obtained by the POLDER sensor in the window spectral channels where absorption by gas is minimal. The total number of such observations by PARASOL always exceeds a hundred over each pixel and the statistical optimization concept promises to be efficient even if the algorithm retrieves several tens of aerosol parameters. Based on this idea, the proposed algorithm uses a large number of unknowns and is aimed at retrieval of extended set of parameters affecting measured radiation.

Dubovik, O↗

NASA NTRS2013

Uncertainty of Passive Imager Cloud Optical Property Retrievals to Instrument Radiometry and Model Assumptions: Examples from MODIS

The optical and microphysical structure of clouds is of fundamental importance for understanding a variety of cloud radiation and precipitation processes. With the advent of MODIS on the NASA EOS Terra and Aqua platforms, simultaneous global-daily 1 km retrievals of cloud optical thickness (COT) and effective particle radius (CER) are provided, as well as the derived water path (WP). The cloud product (MOD06/MYD06 for MODIS Terra and Aqua, respectively) provides separate retrieval datasets for various two-channel retrievals, typically a VISNIR channel paired with a 1.6, 2.1, and 3.7 m spectral channel. The MOD06 forward model is derived from on a homogeneous plane-parallel cloud. In Collection 5 processing (completed in 2007 with a modified Collection 5.1 completed in 2010), pixel-level retrieval uncertainties were calculated for the following non-3-D error sources: radiometry, surface spectral albedo, and atmospheric corrections associated with model analysis uncertainties (water vapor only). The latter error source includes error correlation across the retrieval spectral channels. Estimates of uncertainty in 1 aggregated (Level-3) means were also provided assuming unity correlation between error sources for all pixels in a grid for a single day, and zero correlation of error sources from one day to the next. I n Collection 6 (expected to begin in late summer 2013) we expanded the uncertainty analysis to include: (a) scene-dependent calibration uncertainty that depends on new band and detector-specific Level 1B uncertainties, (b) new model error sources derived from the look-up tables which includes sensitivities associated with wind direction over the ocean and uncertainties in liquid water and ice effective variance, (c) thermal emission uncertainties in the 3.7 m band associated with cloud and surface temperatures that are needed to extract reflected solar radiation from the total radiance signal, (d) uncertainty in the solar spectral irradiance at 3.7 m, and (e) addition of stratospheric ozone uncertainty in visible atmospheric corrections. A summary of the approach and example Collection 6 results will be shown.

Cloud Properties Observations↗

NASA NTRS2013

Surface Reflectance of Mars Observed by CRISM-MRO: 1. Multi-angle Approach for Retrieval of Surface Reflectance from CRISM Observations (mars-reco)

This article addresses the correction for aerosol effects in near-simultaneous multiangle observations acquired by the Compact Reconnaissance Imaging Spectrometer for Mars (CRISM) aboard the Mars Reconnaissance Orbiter. In the targeted mode, CRISM senses the surface of Mars using 11 viewing angles, which allow it to provide unique information on the scattering properties of surface materials. In order to retrieve these data, however, appropriate strategies must be used to compensate the signal sensed by CRISM for aerosol contribution. This correction is particularly challenging as the photometric curve of these suspended particles is often correlated with the also anisotropic photometric curve of materials at the surface. This article puts forward an innovative radiative transfer based method named Multi-angle Approach for Retrieval of Surface Reflectance from CRISM Observations (MARS-ReCO). The proposed method retrieves photometric curves of surface materials in reflectance units after removing aerosol contribution. MARS-ReCO represents a substantial improvement regarding previous techniques as it takes into consideration the anisotropy of the surface, thus providing more realistic surface products. Furthermore, MARS-ReCO is fast and provides error bars on the retrieved surface reflectance. The validity and accuracy of MARS-ReCO is explored in a sensitivity analysis based on realistic synthetic data. According to experiments, MARS-ReCO provides accurate results (up to 10 reflectance error) under favorable acquisition conditions. In the companion article, photometric properties of Martian materials are retrieved using MARS-ReCO and validated using in situ measurements acquired during the Mars Exploration Rovers mission.

CRISM/MRO↗

NASA NTRS2013

Characterizing a New Surface-Based Shortwave Cloud Retrieval Technique, Based on Transmitted Radiance for Soil and Vegetated Surface Types

This paper presents an approach using the GEneralized Nonlinear Retrieval Analysis (GENRA) tool and general inverse theory diagnostics including the maximum likelihood solution and the Shannon information content to investigate the performance of a new spectral technique for the retrieval of cloud optical properties from surface based transmittance measurements. The cumulative retrieval information over broad ranges in cloud optical thickness (tau), droplet effective radius (r(sub e)), and overhead sun angles is quantified under two conditions known to impact transmitted radiation; the variability in land surface albedo and atmospheric water vapor content. Our conclusions are: (1) the retrieved cloud properties are more sensitive to the natural variability in land surface albedo than to water vapor content; (2) the new spectral technique is more accurate (but still imprecise) than a standard approach, in particular for tau between 5 and 60 and r(sub e) less than approximately 20 nm; and (3) the retrieved cloud properties are dependent on sun angle for clouds of tau from 5 to 10 and r(sub e) less than 10 nm, with maximum sensitivity obtained for an overhead sun.

Shannon information content↗

NASA NTRS2014

Development and Testing of the New Surface LER Climatology for OMI UV Aerosol Retrievals

Ozone Monitoring Instrument (OMI) onboard Aura satellite retrieved aerosols properties using UV part of solar spectrum. The OMI near UV aerosol algorithm (OMAERUV) is a global inversion scheme which retrieves aerosol properties both over ocean and land. The current version of the algorithm makes use of TOMS derived Lambertian Equivalent Reflectance (LER) climatology. A new monthly climatology of surface LER at 354 and 388 nm have been developed. This will replace TOMS LER (380 nm and 354nm) climatology in OMI near UV aerosol retrieval algorithm. The main objectives of this study is to produce high resolution (quarter degree) surface LER sets as compared to existing one degree TOMS surface LERs, to product instrument and wavelength consistent surface climatology. Nine years of OMI observations have been used to derive monthly climatology of surface LER. MODIS derived aerosol optical depth (AOD) have been used to make aerosol corrections on OMI wavelengths. MODIS derived BRDF adjusted reflectance product has been also used to capture seasonal changes in the surface characteristics. Finally spatial and temporal averaging techniques have been used to fill the gaps around the globes, especially in the regions with consistent cloud cover such as Amazon. After implementation of new surface data in the research version of algorithm, comparisons of AOD and single scattering albedo (SSA) have been performed over global AERONET sites for year 2007. Preliminary results shows improvements in AOD retrievals globally but more significance improvement were observed over desert and bright locations. We will present methodology of deriving surface data sets and will discuss the observed changes in retrieved aerosol properties with respect to reference AERONET measurements.

Aerosol↗

NASA NTRS2013

Effects of Systematic and Random Errors on the Retrieval of Particle Microphysical Properties from Multiwavelength Lidar Measurements Using Inversion with Regularization

In this work we study the effects of systematic and random errors on the inversion of multiwavelength (MW) lidar data using the well-known regularization technique to obtain vertically resolved aerosol microphysical properties. The software implementation used here was developed at the Physics Instrumentation Center (PIC) in Troitsk (Russia) in conjunction with the NASA/Goddard Space Flight Center. Its applicability to Raman lidar systems based on backscattering measurements at three wavelengths (355, 532 and 1064 nm) and extinction measurements at two wavelengths (355 and 532 nm) has been demonstrated widely. The systematic error sensitivity is quantified by first determining the retrieved parameters for a given set of optical input data consistent with three different sets of aerosol physical parameters. Then each optical input is perturbed by varying amounts and the inversion is repeated. Using bimodal aerosol size distributions, we find a generally linear dependence of the retrieved errors in the microphysical properties on the induced systematic errors in the optical data. For the retrievals of effective radius, number/surface/volume concentrations and fine-mode radius and volume, we find that these results are not significantly affected by the range of the constraints used in inversions. But significant sensitivity was found to the allowed range of the imaginary part of the particle refractive index. Our results also indicate that there exists an additive property for the deviations induced by the biases present in the individual optical data. This property permits the results here to be used to predict deviations in retrieved parameters when multiple input optical data are biased simultaneously as well as to study the influence of random errors on the retrievals. The above results are applied to questions regarding lidar design, in particular for the spaceborne multiwavelength lidar under consideration for the upcoming ACE mission.

vertical profiles↗

NASA NTRS2015

Analyses of Hubble Space Telescope Aluminized-Teflon Multilayer Insulation Blankets Retrieved After 19 Years of Space Exposure

Since its launch in April 1990, the Hubble Space Telescope (HST) has made many important observations from its vantage point in low Earth orbit (LEO). However, as seen during five servicing missions, the outer layer of multilayer insulation (MLI) has become increasingly embrittled and has cracked in many areas. In May 2009, during the 5th servicing mission (called SM4), two MLI blankets were replaced with new insulation and the space-exposed MLI blankets were retrieved for degradation analyses by teams at NASA Glenn Research Center (GRC) and NASA Goddard Space Flight Center (GSFC). The retrieved MLI blankets were from Equipment Bay 8, which received direct sunlight, and Equipment Bay 5, which received grazing sunlight. Each blanket was divided into several regions based on environmental exposure and/or physical appearance. The aluminized-Teflon (DuPont, Wilmington, DE) fluorinated ethylene propylene (Al-FEP) outer layers of the retrieved MLI blankets have been analyzed for changes in optical, physical, and mechanical properties, along with chemical and morphological changes. Pristine and as-retrieved samples (materials) were heat treated to help understand degradation mechanisms. When compared to pristine material, the analyses have shown how the Al-FEP was severely affected by the space environment. Most notably, the Al-FEP was highly embrittled, fracturing like glass at strains of 1 to 8 percent. Across all measured properties, more significant degradation was observed for Bay 8 material as compared to Bay 5 material. This paper reviews the tensile and bend-test properties, density, thickness, solar absorptance, thermal emittance, x-ray photoelectron spectroscopy (XPS) and energy dispersive spectroscopy (EDS) elemental composition measurements, surface and crack morphologies, and atomic oxygen erosion yields of the Al-FEP outer layer of the retrieved HST blankets after 19 years of space exposure.

Radiation↗

NASA NTRS2015

Retrieved Products from Simulated Hyperspectral Observations of a Hurricane

Retrievals were run using the AIRS Science Team Version-6 AIRS Only retrieval algorithm, which generates a Neural-Net first guess (T(sub s))(sup 0), (T(p))(sup 0), and (q(p))(sup 0) as a function of observed AIRS radiances. AIRS Science Team Neural-Net coefficients performed very well beneath 300 mb using the simulated radiances. This means the simulated radiances are very realistic. First guess and retrieved values of T(p) above 300 mb were biased cold, but both represented the model spatial structure very well. QC'd T(p) and q(p) retrievals for all experiments had similar accuracies compared to their own truth fields, and were roughly consistent with results obtained using real data. Spatial coverage of retrievals, as well as the representativeness of the spatial structure of the storm, improved dramatically with decreasing size of the instrument's FOV. We sent QC'd values of T(p) and q(p) to Bob Atlas at AOML for use as input to OSSE Data Assimilation experiments.

CrIS ATMS↗

NASA NTRS2015

Aerosol Retrieval from Multiangle Multispectral Photopolarimetric Measurements: Importance of Spectral Range and Angular Resolution

We investigated the importance of spectral range and angular resolution for aerosol retrieval from multiangle photopolarimetric measurements over land. For this purpose, we use an extensive set of simulated measurements for different spectral ranges and angular resolutions and subsets of real measurements of the airborne Research Scanning Polarimeter (RSP) carried out during the PODEX and SEAC4RS campaigns over the continental USA. Aerosol retrievals performed from RSP measurements show good agreement with ground-based AERONET measurements for aerosol optical depth (AOD), single scattering albedo (SSA) and refractive index. Furthermore, we found that inclusion of shortwave infrared bands (1590 and/or 2250 nm) significantly improves the retrieval of AOD, SSA and coarse mode microphysical properties. However, accuracies of the retrieved aerosol properties do not improve significantly when more than five viewing angles are used in the retrieval.

angular resolution↗

NASA NTRS2016

Phase-Retrieval Uncertainty Estimation and Algorithm Comparison for the JWST-ISIM Test Campaign

Phase retrieval, the process of determining the exitpupil wavefront of an optical instrument from image-plane intensity measurements, is the baseline methodology for characterizing the wavefront for the suite of science instruments (SIs) in the Integrated Science Instrument Module (ISIM) for the James Webb Space Telescope (JWST). JWST is a large, infrared space telescope with a 6.5-meter diameter primary mirror. JWST is currently NASA's flagship mission and will be the premier space observatory of the next decade. ISIM contains four optical benches with nine unique instruments, including redundancies. ISIM was characterized at the Goddard Space Flight Center (GSFC) in Greenbelt, MD in a series of cryogenic vacuum tests using a telescope simulator. During these tests, phase-retrieval algorithms were used to characterize the instruments. The objective of this paper is to describe the Monte-Carlo simulations that were used to establish uncertainties (i.e., error bars) for the wavefronts of the various instruments in ISIM. Multiple retrieval algorithms were used in the analysis of ISIM phase-retrieval focus-sweep data, including an iterativetransform algorithm and a nonlinear optimization algorithm. These algorithms emphasize the recovery of numerous optical parameters, including low-order wavefront composition described by Zernike polynomial terms and high-order wavefront described by a point-by-point map, location of instrument best focus, focal ratio, exit-pupil amplitude, the morphology of any extended object, and optical jitter. The secondary objective of this paper is to report on the relative accuracies of these algorithms for the ISIM instrument tests, and a comparison of their computational complexity and their performance on central and graphical processing unit clusters. From a phase-retrieval perspective, the ISIM test campaign includes a variety of source illumination bandwidths, various image-plane sampling criteria above and below the Nyquist- Shannon critical sampling value, various extended object sizes, and several other impactful effects.

Design Analysis↗

NASA NTRS2015

First SNPP Cal/Val Campaign: Satellite and Aircraft Sounding Retrieval Intercomparison

Satellite ultraspectral infrared sensors provide key data records essential for weather forecasting and climate change science. The Suomi National Polar-orbiting Partnership (SNPP) satellite Environmental Data Record (EDR) is retrieved from calibrated ultraspectral radiance so called Sensor Data Record (SDR). It is critical to understand the accuracy of retrieved EDRs, which mainly depends on SDR accuracy (e.g., instrument random noise and absolute accuracy), an ill-posed retrieval system, and radiative transfer model errors. There are few approaches to validate EDR products, e.g., some common methods are to rely on radiosonde measurements, ground-based measurements, and dedicated aircraft campaign providing in-situ measurements of atmosphere and/or employing similar ultraspectral interferometer sounders. Ultraspectral interferometer sounder aboard aircraft measures SDR to retrieve EDR, which is often used to validate satellite measurements of SDR and EDR. The SNPP Calibration/Validation Campaign was conducted during May 2013. The NASA high-altitude aircraft ER-2 that carried ultraspectral interferometer sounders such as the NASA Atmospheric Sounder Testbed-Interferometer (NAST-I) flew under the SNPP satellite that carries the Cross-track Infrared Sounder (CrIS). Here we inter-compare the EDRs produced with different retrieval algorithms from SDRs measured by the sensors from satellite and aircraft. The available dropsonde and radiosonde measurements together with the European Centre for Medium-Range Weather Forecasts (ECMWF) analysis were also used to draw the conclusion from this experiment.

Zhou, Daniel K.↗

NASA NTRS2016

Retrieval of Macro- and Micro-Physical Properties of Oceanic Hydrosols from Polarimetric Observations

Remote sensing has mainly relied on measurements of scalar radiance and its spectral and angular features to retrieve micro- and macro-physical properties of aerosols/hydrosols. However, it is recognized that measurements that include the polarimetric characteristics of light provide more intrinsic information about particulate scattering. To take advantage of this, we used vector radiative transfer (VRT) simulations and developed an analytical relationship to retrieve the macro and micro-physical properties of the oceanic hydrosols. Specifically, we investigated the relationship between the observed degree of linear polarization (DoLP) and the ratio of attenuation-to- absorption coefficients (c/a) in water, from which the scattering coefficient can be readily computed (b equals c minus a), after retrieving a. This relationship was parameterized for various scattering geometries, including sensor zenith/azimuth angles relative to the Sun's principal plane, and for varying Sun zenith angles. An inversion method was also developed for the retrieval of the microphysical properties of hydrosols, such as the bulk refractive index and the particle size distribution. The DoLP vs c/a relationship was tested and validated against in-situ measurements of underwater light polarization obtained by a custom-built polarimeter and measurements of the coefficients a and c, obtained using an in-water WET (Western Environmental Technologies) Labs ac-s (attenuation coefficients In-Situ Spectrophotometer) instrument package. These measurements confirmed the validity of the approach, with retrievals of attenuation coefficients showing a high coefficient of determination depending on the wavelength. We also performed a sensitivity analysis of the DoLP at the Top of Atmosphere (TOA) over coastal waters showing the possibility of polarimetric remote sensing application for ocean color.

PACE↗

NASA NTRS2016

On the VHF Source Retrieval Errors Associated with Lightning Mapping Arrays (LMAs)

This presentation examines in detail the standard retrieval method: that of retrieving the (x, y, z, t) parameters of a lightning VHF point source from multiple ground-based Lightning Mapping Array (LMA) time-of-arrival (TOA) observations. The solution is found by minimizing a chi-squared function via the Levenberg-Marquardt algorithm. The associated forward problem is examined to illustrate the importance of signal-to-noise ratio (SNR). Monte Carlo simulated retrievals are used to assess the benefits of changing various LMA network properties. A generalized retrieval method is also introduced that, in addition to TOA data, uses LMA electric field amplitude measurements to retrieve a transient VHF dipole moment source.

inversion↗

NASA NTRS2016

New Methods for Retrieval of Chlorophyll Red Fluorescence from Hyperspectral Satellite Instruments: Simulations and Application to GOME-2 and SCIAMACHY

Global satellite measurements of solar-induced fluorescence (SIF) from chlorophyll over land and ocean have proven useful for a number of different applications related to physiology, phenology, and productivity of plants and phytoplankton. Terrestrial chlorophyll fluorescence is emitted throughout the red and far-red spectrum, producing two broad peaks near 683 and 736nm. From ocean surfaces, phytoplankton fluorescence emissions are entirely from the red region (683nm peak). Studies using satellite-derived SIF over land have focused almost exclusively on measurements in the far red (wavelengths greater than 712nm), since those are the most easily obtained with existing instrumentation. Here, we examine new ways to use existing hyperspectral satellite data sets to retrieve red SIF (wavelengths less than 712nm) over both land and ocean. Red SIF is thought to provide complementary information to that from the far red for terrestrial vegetation. The satellite instruments that we use were designed to make atmospheric trace-gas measurements and are therefore not optimal for observing SIF; they have coarse spatial resolution and only moderate spectral resolution (0.5nm). Nevertheless, these instruments, the Global Ozone Monitoring Instrument 2 (GOME-2) and the SCanning Imaging Absorption spectroMeter for Atmospheric CHartographY (SCIAMACHY), offer a unique opportunity to compare red and far-red terrestrial SIF at regional spatial scales. Terrestrial SIF has been estimated with ground-, aircraft-, or satellite-based instruments by measuring the filling-in of atmospheric andor solar absorption spectral features by SIF. Our approach makes use of the oxygen (O2) gamma band that is not affected by SIF. The SIF-free O2 gamma band helps to estimate absorption within the spectrally variable O2 B band, which is filled in by red SIF. SIF also fills in the spectrally stable solar Fraunhofer lines (SFLs) at wavelengths both inside and just outside the O2 B band, which further helps to estimate red SIF emission. Our approach is then an extension of previous approaches applied to satellite data that utilized only the filling-in of SFLs by red SIF. We conducted retrievals of red SIF using an extensive database of simulated radiances covering a wide range of conditions. Our new algorithm produces good agreement between the simulated truth and retrievals and shows the potential of the O2 bands for noise reduction in red SIF retrievals as compared with approaches that rely solely on SFL filling. Biases seen with existing satellite data, most likely due to instrumental artifacts that vary in time, space, and with instrument, must be addressed in order to obtain reasonable results. Our 8-year record of red SIF observations over land with the GOME-2 allows for the first time reliable global mapping of monthly anomalies. These anomalies are shown to have similar spatiotemporal structure as those in the far red, particularly for drought-prone regions. There is a somewhat larger percentage response in the red as compared with the far red for these areas that are drought sensitive. We also demonstrate that good-quality ocean fluorescence line height retrievals can be achieved with GOME-2, SCIAMACHY, and similar instruments by utilizing the full complement of radiance measurements that span the red SIF emission feature.

spatiotemporal structure↗

NASA NTRS2016

Validating MODIS Above-Cloud Aerosol Optical Depth Retrieved from Color Ratio Algorithm Using Direct Measurements Made by NASA's Airborne AATS and 4STAR Sensors

We present the validation analysis of above-cloud aerosol optical depth (ACAOD) retrieved from the color ratio method applied to MODIS cloudy-sky reflectance measurements using the limited direct measurements made by NASAs airborne Ames Airborne Tracking Sunphotometer (AATS) and Spectrometer for Sky-Scanning, Sun-Tracking Atmospheric Research (4STAR) sensors. A thorough search of the airborne database collection revealed a total of five significant events in which an airborne sun photometer, coincident with the MODIS overpass, observed partially absorbing aerosols emitted from agricultural biomass burning, dust, and wildfires over a low-level cloud deck during SAFARI-2000, ACE-ASIA 2001, and SEAC4RS 2013 campaigns, respectively. The co-located satellite-airborne match ups revealed a good agreement (root-mean-square difference less than 0.1), with most match ups falling within the estimated uncertainties associated with the MODIS retrievals (about -10 to +50 ). The co-retrieved cloud optical depth was comparable to that of the MODIS operational cloud product for ACE-ASIA and SEAC4RS, however, higher by 30-50% for the SAFARI-2000 case study. The reason for this discrepancy could be attributed to the distinct aerosol optical properties encountered during respective campaigns. A brief discussion on the sources of uncertainty in the satellite-based ACAOD retrieval and co-location procedure is presented. Field experiments dedicated to making direct measurements of aerosols above cloud are needed for the extensive validation of satellite based retrievals.

airborne sun photometer↗

NASA NTRS2018

A Singular Value Decomposition Framework for Retrievals with Vertical Distribution Information from Greenhouse Gas Column Absorption Spectroscopy Measurements

We describe a variation of the Optimal Estimation (OE) method for greenhouse gas remote sensing retrievals using a singular value decomposition (SVD) and an uninformative prior. The SVD method is capable of discerning vertical information in column integrated absorption measurements. While traditional Bayesian optimal estimation (OE) assumes a prior distribution in order to regularize the inversion problem, the SVD approach identifies principal components that can be retrieved from the measurement without explicitly specifying a prior mean and prior covariance matrix. We discuss the method, illustrate its use on an integrated path differential absorption CO2 lidar measurement model, and compare it to traditional optimal estimation using numerical simulations. In the absence of forward model error, the mathematics behind the SVD method guarantee it to be bias-free, which is confirmed by the numerical simulations. In contrast, traditional OE retrievals exhibit bias when the prior mean used in the retrieval differs from the true mean. While the SVD approach can be used for most trace gas retrievals, it is particularly useful for situations where prior knowledge of the trace gas profile is poor. The SVD analysis is also useful in illustrating how vertical information is treated by the traditional OE approach.

Ramanathan, Anand K.↗