Current Operational Algorithm Research Articles

Consistency of the Single Calculus Chain Optical Products with Archived Measurements from an EARLINET Lidar Station

A long-term analysis and climatology of aerosol backscatter and extinction coefficients profiles using a five-year study period lidar dataset derived from a multiwavelenth Raman lidar at Thessaloniki station is presented. All measurements have been processed with the latest version of the Single Calculus Chain (SCCv5.1.6) fully automated algorithm, which has been developed to provide a common lidar processing tool, within EARLINET (European Aerosol Research Lidar NETwork) stations. The optical products delivered by the SCC tool have already been compared with the optical products derived from the operational algorithm of Thessaloniki (THessaloniki Aerosol LIdar Algorithm-THALIA) and discussed in terms of inhomogeneities. In this contribution, we analyze these products for climatological purposes, in order to investigate the aerosol columnar properties over Thessaloniki lidar station, drawing conclusions about the issues to be considered when switching from the current operational algorithm to the SCCv5. The SCCv5 algorithm is evaluated for the AOD both for 355 and 532 nm. The agreement with THALIA algorithm seems promising with correlations of 0.89 and 0.84, respectively, and absolute deviations within the range of the EARLINET quality requirements. Time series of the AOD at 355 nm denote a decrease of 0.017 per year in the free troposphere, a trend that is also shown in the AOD values derived from the operational algorithm (0.014). A decrease of 0.01 per year in the lower troposphere is also noted from the SCC, whereas the corresponding AOD values derived from the operational algorithm denote a decrease of 0.017.

Scale dependence of cirrus heterogeneity effects. Part II: MODIS NIR and SWIR channels

Abstract. In a context of global climate change, the understanding of the radiative role of clouds is crucial. On average, ice clouds such as cirrus have a significant positive radiative effect, but under some conditions the effect may be negative. However, many uncertainties remain regarding the role of ice clouds on Earth's radiative budget and in a changing climate. Global satellite observations are particularly well suited to monitoring clouds, retrieving their characteristics and inferring their radiative impact. To retrieve ice cloud properties (optical thickness and ice crystal effective size), current operational algorithms assume that each pixel of the observed scene is plane-parallel and homogeneous, and that there is no radiative connection between neighboring pixels. Yet these retrieval assumptions are far from accurate, as real radiative transfer is 3-D. This leads to the plane-parallel and homogeneous bias (PPHB) plus the independent pixel approximation bias (IPAB), which impacts both the estimation of top-of-the-atmosphere (TOA) radiation and the retrievals. An important factor that determines the impact of these assumptions is the sensor spatial resolution. High-spatial-resolution pixels can better represent cloud variability (low PPHB), but the radiative path through the cloud can involve many pixels (high IPAB). In contrast, low-spatial-resolution pixels poorly represent the cloud variability (high PPHB), but the radiation is better contained within the pixel field of view (low IPAB). In addition, the solar and viewing geometry (as well as cloud optical properties) can modulate the magnitude of the PPHB and IPAB. In this, Part II of our study, we simulate TOA 0.86 and 2.13 µm solar reflectances over a cirrus uncinus scene produced by the 3DCLOUD model. Then, 3-D radiative transfer simulations are performed with the 3DMCPOL code at spatial resolutions ranging from 50 m to 10 km, for 12 viewing geometries and nine solar geometries. It is found that, for simulated nadir observations taken at resolution higher than 2.5 km, horizontal radiation transport (HRT) dominates biases between 3-D and 1-D reflectance calculations, but these biases are mitigated by the side illumination and shadowing effects for off-zenith solar geometries. At resolutions coarser than 2.5 km, PPHB dominates. For off-nadir observations at resolutions higher than 2.5 km, the effect that we call THEAB (tilted and homogeneous extinction approximation bias) due to the oblique line of sight passing through many cloud columns contributes to a large increase of the reflectances, but 3-D radiative effects such as shadowing and side illumination for oblique Sun are also important. At resolutions coarser than 2.5 km, the PPHB is again the dominant effect. The magnitude and resolution dependence of PPHB and IPAB is very different for visible, near-infrared and shortwave infrared channels compared with the thermal infrared channels discussed in Part I of this study. The contrast of 3-D radiative effects between solar and thermal infrared channels may be a significant issue for retrieval techniques that simultaneously use radiative measurements across a wide range of solar reflectance and infrared wavelengths.

Exploiting the synergy between SMAP and SMOS to improve brightness temperature simulations and soil moisture retrievals in arid regions

The objective of this study was to exploit the synergy between SMOS and SMAP based on vegetation optical depth (VOD) to improve brightness temperature (TB) simulations and land surface soil moisture (SM) retrievals in arid regions of the world. In the current operational algorithm of SMAP (level 2), vegetation water content (VWC) is considered as a proxy to compute VOD which is calculated by an empirical conversion function of NDVI. Avoiding the empirical estimation of VOD, the SMOS algorithm is used to retrieve simultaneously SM and VOD from TB observations. The present study attempted to improve SMAP TB simulations and SM retrievals by benefiting from the advantages of the SMOS (L-MEB) algorithm. This was achieved by using a synergy method based on replacing the default value of SMAP VOD with the retrieved value of VOD from the SMOS multi angular and bi-polarization observations of TB. The insitu SM measurements, used as reference SM in this study, were obtained from the International Soil Moisture Network (ISMN) over 180 stations located in arid regions of the world. Furthermore, four stations were randomly selected to analyze the temporal variations in VOD and SM. Results of the synergy method showed that the accuracy of the TB simulations and SM retrievals was respectively improved at 144 and 124 stations (out of a total of 180 stations) in terms of coefficient of determination (R2) and unbiased root mean squared error (UbRMSE). Analyzing the temporal variations in VOD showed that the SMOS VOD, conversely to the SMAP VOD, can better illustrate the presence of herbaceous plants and may be a better indicator of the seasonal changes in the vegetation density and biomass over the year.

Retrieval of Sea Surface Temperature from MODIS Data in Coastal Waters

Accurate measurements of sea surface temperature retrieved from remote images is a fundamental need for monitoring ocean and coastal waters. This study proposes a method for retrieving accurate measurements of SST in coastal waters. The method involves the estimation of effect of total suspended particulate matter (SPM) concentration on the value of sea surface emissivity (SSE) and the inclusion of this effect in SSE value that is put into SST calculation. Data collected in three Italian coastal waters were exploited to obtain SSTskin and SSE values and to analyze SPM effects on SSE value. The method was tested on MODIS images. Satellite measurements of SST obtained with current operational algorithm, which does not require SSE value as explicit input, were compared with in situ values of SSTskin and RMSD is equal to 1.13 K. Moreover, SST data were retrieved with an algorithm for retrieving SST measurements from MODIS data, which allows the inclusion of SSE value with SPM effect. These data were compared with in situ values of SSTskin, and RMSD is equal to 0.68 K.

Improved near-infrared ocean reflectance correction algorithm for satellite ocean color data processing.

A new approach for the near-infrared (NIR) ocean reflectance correction in atmospheric correction for satellite ocean color data processing in coastal and inland waters is proposed, which combines the advantages of the three existing NIR ocean reflectance correction algorithms, i.e., Bailey et al. (2010) [Opt. Express18, 7521 (2010)Appl. Opt.39, 897 (2000)Opt. Express20, 741 (2012)], and is named BMW. The normalized water-leaving radiance spectra nLw(λ) obtained from this new NIR-based atmospheric correction approach are evaluated against those obtained from the shortwave infrared (SWIR)-based atmospheric correction algorithm, as well as those from some existing NIR atmospheric correction algorithms based on several case studies. The scenes selected for case studies are obtained from two different satellite ocean color sensors, i.e., the Moderate Resolution Imaging Spectroradiometer (MODIS) on the satellite Aqua and the Visible Infrared Imaging Radiometer Suite (VIIRS) on the Suomi National Polar-orbiting Partnership (SNPP), with an emphasis on several turbid water regions in the world. The new approach has shown to produce nLw(λ) spectra most consistent with the SWIR results among all NIR algorithms. Furthermore, validations against the in situ measurements also show that in less turbid water regions the new approach produces reasonable and similar results comparable to the current operational algorithm. In addition, by combining the new NIR atmospheric correction with the SWIR-based approach, the new NIR-SWIR atmospheric correction can produce further improved ocean color products. The new NIR atmospheric correction can be implemented in a global operational satellite ocean color data processing system.

Spectral calibration and validation of the Cross‐track Infrared Sounder on the Suomi NPP satellite

The Cross‐track Infrared Sounder (CrIS) radiometric accuracy depends upon accurate frequency calibration. Here we present both the prelaunch calibration of the sensor and the minor modifications needed to this calibration post launch. Particular emphasis is given to ensuring that all nine detectors on each of the three CrIS focal planes are on a common frequency scale with accurate off‐axis apodization corrections. Radiances from the current operational algorithm have a frequency calibration that is stable to 2 ppm, although this work suggests that the CrIS instrument is capable of a frequency calibration stability of better than 1 ppm.

Improvement of aerosol optical depth retrieval from MODIS spectral reflectance over the global ocean using new aerosol models archived from AERONET inversion data and tri-axial ellipsoidal dust database

Abstract. New over-ocean aerosol models are developed by integrating the inversion data from the Aerosol Robotic Network (AERONET) sun/sky radiometers with a database for the optical properties of tri-axial ellipsoid particles. The new aerosol models allow more accurate retrieval of aerosol optical depth (AOD) from the Moderate Resolution Imaging Spectroradiometer (MODIS) in the case of high AOD (AOD > 0.3). The aerosol models are categorized by using the fine-mode fraction (FMF) at 550 nm and the single-scattering albedo (SSA) at 440 nm from the AERONET inversion data to include a variety of aerosol types found around the globe. For each aerosol model, the changes in the aerosol optical properties (AOPs) as functions of AOD are considered to better represent aerosol characteristics. Comparisons of AODs between AERONET and MODIS for the period from 2003 to 2010 show that the use of the new aerosol models enhances the AOD accuracy with a Pearson coefficient of 0.93 and a regression slope of 0.99 compared to 0.92 and 0.85 calculated using the MODIS Collection 5 data. Moreover, the percentage of data within an expected error of ± (0.03 + 0.05 × AOD) is increased from 62% to 64% for overall data and from 39% to 5% for AOD > 0.3. Errors in the retrieved AOD are further characterized with respect to the Ångström exponent (AE), scattering angle (Θ), SSA, and air mass factor (AMF). Due to more realistic AOPs assumptions, the new algorithm generally reduces systematic errors in the retrieved AODs compared with the current operational algorithm. In particular, the underestimation of fine-dominated AOD and the scattering angle dependence of dust-dominated AOD are significantly mitigated as results of the new algorithm's improved treatment of aerosol size distribution and dust particle nonsphericity.

Iterative atmospheric correction scheme and the polarization color of alpine snow

Characterization of the Earth's surface is crucial to remote sensing, both to map geomorphological features and because subtracting this signal is essential during retrievals of the atmospheric constituents located between the surface and the sensor. Current operational algorithms model the surface total reflectance through a weighted linear combination of a few geometry-dependent kernels, each devised to describe a particular scattering mechanism. The information content of these measurements is overwhelmed by that of instruments with polarization capabilities: proposed models in this case are based on the Fresnel reflectance of an isotropic distribution of facets. Because of its remarkable lack of spectral contrast, the polarized reflectance of land surfaces in the shortwave infrared spectral region, where atmospheric scattering is minimal, can be used to model the surface also at shorter wavelengths, where aerosol retrievals are attempted based on well-established scattering theories.In radiative transfer simulations, straightforward separation of the surface and atmospheric contributions is not possible without approximations because of the coupling introduced by multiple reflections. Within a general inversion framework, the problem can be eliminated by linearizing the radiative transfer calculation, and making the Jacobian (i.e., the derivative expressing the sensitivity of the reflectance with respect to model parameters) available at output. We present a general methodology based on a Gauss–Newton iterative search, which automates this procedure and eliminates de facto the need of an ad hoc atmospheric correction.In this case study we analyze the color variations in the polarized reflectance measured by the NASA Goddard Institute of Space Studies Research Scanning Polarimeter during a survey of late-season snowfields in the High Sierra. This insofar unique dataset presents challenges linked to the rugged topography associated with the alpine environment and a likely high water content due to melting. The analysis benefits from ancillary information provided by the NASA Langley High Spectral Resolution Lidar deployed on the same aircraft.The results obtained from the iterative scheme are contrasted against the surface polarized reflectance obtained ignoring multiple reflections, via the simplistic subtraction of the atmospheric scattering contribution. Finally, the retrieved reflectance is modeled after the scattering properties of a dense collection of ice crystals at the surface. Confirming that the polarized reflectance of snow is spectrally flat would allow to extend the techniques already in use for polarimetric retrievals of aerosol properties over land to the large portion of snow-covered pixels plaguing orbital and suborbital observations.

Assessment of a bidirectional reflectance distribution correction of above-water and satellite water-leaving radiance in coastal waters

Water-leaving radiances, retrieved from in situ or satellite measurements, need to be corrected for the bidirectional properties of the measured light in order to standardize the data and make them comparable with each other. The current operational algorithm for the correction of bidirectional effects from the satellite ocean color data is optimized for typical oceanic waters. However, versions of bidirectional reflectance correction algorithms specifically tuned for typical coastal waters and other case 2 conditions are particularly needed to improve the overall quality of those data. In order to analyze the bidirectional reflectance distribution function (BRDF) of case 2 waters, a dataset of typical remote sensing reflectances was generated through radiative transfer simulations for a large range of viewing and illumination geometries. Based on this simulated dataset, a case 2 water focused remote sensing reflectance model is proposed to correct above-water and satellite water-leaving radiance data for bidirectional effects. The proposed model is first validated with a one year time series of in situ above-water measurements acquired by collocated multispectral and hyperspectral radiometers, which have different viewing geometries installed at the Long Island Sound Coastal Observatory (LISCO). Match-ups and intercomparisons performed on these concurrent measurements show that the proposed algorithm outperforms the algorithm currently in use at all wavelengths, with average improvement of 2.4% over the spectral range. LISCO's time series data have also been used to evaluate improvements in match-up comparisons of Moderate Resolution Imaging Spectroradiometer satellite data when the proposed BRDF correction is used in lieu of the current algorithm. It is shown that the discrepancies between coincident in-situ sea-based and satellite data decreased by 3.15% with the use of the proposed algorithm. This confirms the advantages of the proposed model over the current one, demonstrating the need for a specific case 2 water BRDF correction algorithm as well as the feasibility of enhancing performance of current and future satellite ocean color remote sensing missions for monitoring of typical coastal waters.

Iterative atmospheric correction scheme and the polarization color of alpine snow

Proper characterization of the Earth's surface is crucial to remote sensing, both to map geomorphological features and because subtracting this signal is essential during retrievals of the atmospheric constituents located between the surface and the sensor. Current operational algorithms model the surface total reflectance through a weighted linear combination of geometry-dependent kernels, each devised to describe a particular scattering mechanism. The information content of intensity-only measurements is overwhelmed by instruments with polarization capabilities. Because of their remarkable lack of spectral contrast, the polarized reflectances of land surfaces in the shortwave infrared spectral region (where atmospheric scattering is minimal) can be used to model the surface at shorter wavelengths, where aerosol retrievals are performed.

New perspectives on the synoptic development of the severe October 1992 Nome storm

Understanding the characteristics of storms that impact the Alaska region is of importance to emergency planning. The 5–7 October 1992 storm was a severe event which cost Nome, a town in Alaska, $6 million dollars. We will explore its characteristics with the aid of two established cyclone tracking schemes: the NOAA CPC current operational algorithm and the University of Melbourne algorithm. Manual tracking was performed as a control. The essential features are captured by both algorithms, but they differ in the genesis and lysis location. The NOAA algorithm broke the storm into two separate events. Synoptic development of the storm was influenced by a blocking high that affected how the tracking algorithms handled the event. A synoptic re‐examination of this storm is presented in terms of the depth, Laplacian and radius of the system. These new results present a fresh perspective on the intensity and longevity of this dramatic storm.

Improved Physically Based Oceanic Rainfall Algorithm From AMSR-E Data

An improved oceanic rainfall algorithm based on a radiative transfer model that reduces many uncertainties of rainfall retrieval was developed using advanced microwave scanning radiometer for Earth Observing System data. Error models were embedded to quantify rainfall uncertainties and to reduce net uncertainties. Six channels (37, 18, and 10 GHz with dual polarization) were utilized in the algorithm. Several developments such as improvement of the freezing-level (FL) retrieval, a weighted average scheme, and enhanced offset correction were implemented in this paper. As a result, rain rate uncertainties were substantially reduced and quantified. To establish error models, drop-size-distribution uncertainty, beam filling error, data calibration uncertainty, and instrument noise were taken into account. These error models were used to compute proper weights of each channel to combine the six rain rates. The algorithm was evaluated with respect to the current operational algorithm (NASA Level 3 rainfall algorithm). It showed more reasonable mean FLs and rain rate estimation than the operational algorithm. Furthermore, pixel-by-pixel-based quantitative error estimates were conducted through the error model

Retrieval of mineral aerosol optical depth and size information from Meteosat Second Generation SEVIRI solar reflectance bands

The current operational algorithm used to retrieve aerosol optical depth and Ångström exponent over ocean from the solar reflectance bands of the Advanced Very High Resolution Radiometer (AVHRR) flown onboard NOAA polar orbiting satellites was adapted to the corresponding channels of the Spinning Enhanced Visible and Infra-Red Imager (SEVIRI) flown onboard the Meteosat Second Generation (MSG) geostationary platform. By examining two specific dust events from 3–5 March and 12–13 October 2004 we show how a detailed description of the dust loading through the diurnal cycle can be obtained. Snapshot comparisons with spatially resolved retrievals from the MODerate resolution Imaging Spectrometer (MODIS) instruments flown on the Terra and Aqua polar platforms show qualitative agreement with SEVIRI retrievals. In addition to the generic aerosol model used in the NOAA/NESDIS algorithm, which was tuned to optimize retrievals over global ocean, three microphysical models, specifically proposed in the aerosol literature for desert dust, have also been tested. However, comparison of the diurnal variation seen in these SEVIRI retrievals with available ground based Aerosol Robotic Network (AERONET) observations from two coastal stations suggests that the phase functions associated with two of these dust representations, obtained under the assumption of particle sphericity, result in unrealistic time dependent behaviour. This tendency is removed when either the generic aerosol representation used in the NOAA/NESDIS algorithm is employed, or a more physically based non-spherical dust representation is used.

On the relationship between Stokes parameters Q and U of atmospheric ultraviolet/visible/near‐infrared radiation

On the basis of both spaceborne measurements (Polarization and Directionality of the Earth's Reflectances (POLDER)) and radiative transfer modeling, it is shown that the polarization of reflected solar light (300–900 nm) at the top of the atmosphere is most often perpendicular and less often parallel to the plane of single scattering. In terms of the elements of the Stokes vector, ∣U∣ is typically much smaller than ∣Q∣ when using the single‐scattering plane as reference. When using any other plane, U(λ) ≈ Q(λ) tan 2χss, with χss being the angle of the plane of polarization with the reference plane in the case of single Rayleigh scattering. Exceptions to these findings are noted, and an error analysis of U(λ) ≈ Q(λ) tan 2χss is presented. A simplified polarization calibration algorithm for spaceborne spectrometers like the Spectrometer for Atmospheric Cartography (SCIAMACHY) is presented using the U‐Q relation studied in this paper. It is shown to be just as accurate but less sensitive to measurement error than the current operational algorithm.

SCIAMACHY advanced data retrieval algorithm development

The atmospheric chemistry instrument SCIAMACHY is a joint German-Dutch-Belgian contribution to the European Space Agency environmental satellite ENVISAT scheduled for launch in mid 2001. Instrument performance and calibration measurements recently carried out under thermal vacuum conditions have confirmed predicted performance. Algorithm development at SRON using the UV and visible part of the solar spectrum for ozone profile retrieval and the near infrared for carbon monoxide and methane retrieval has shown good progress. In particular, new avenues have been explored for the development of a fast operational algorithm for the retrieval of ozone profiles, including a new forward model based on perturbation theory that is faster than the current operational algorithm, coupled to a new inversion scheme with no use of a-priori ozone profile information. The near-infrared retrieval of CO and CH 4 is expected to yield higher accuracy data products based on the optimization of retrieval using micro-windows. New and advanced SCIAMACHY data products will be piloted in the Netherlands SCIAMACHY Data Centre that complements the operational ENVISAT payload data segment.