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Jiang L.,The Center for Satellite Applications and Research | Jiang L.,Colorado State University | Wang M.,The Center for Satellite Applications and Research
Optics Express | Year: 2014

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. Express 18, 7521 (2010)], Ruddick et al. (2000) [Appl. Opt. 39, 897 (2000)], and Wang et al. (2012) [Opt. Express 20, 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. ©2014 Optical Society of America.

Sun J.,The Center for Satellite Applications and Research | Wang M.,The Center for Satellite Applications and Research
Applied Optics | Year: 2014

The reflective solar bands (RSB) of the Visible Infrared Imaging Radiometer Suite (VIIRS) on board the Suomi National Polar-orbiting Partnership (SNPP) satellite is calibrated by a solar diffuser (SD) whose performance is itself monitored by a solar diffuser stability monitor (SDSM). In this study, we describe the calibration algorithm of the SDSM, analyze the current two and a half years of calibration data, and derive the performance result for the SD, commonly called SD degradation or H-factors. The application of the newly derived vignetting functions for both the SD screen and the SDSM sun-view screen effectively removes the seasonal oscillations in the derived SD degradation and significantly improves the quality of the H-factors. The full illumination region, the so-called "sweet spot," for both SD view and SDSM sun view is carefully examined and selected to ensure a consistent and an optimal number of valid data samples to reduce the sample noise owing to inconsistent or lack of samples. The result shows that SD degrades much faster at short wavelength as expected, about 28.5% at 412 nm but only 1.2% at 935 nm up to date. The performance of the SD degrades exponentially with time until 7 November 2013 but has since become flat. This sudden flattening of the SD degradation is a new phenomenon never previously observed for the degradations of the SD on VIIRS or other satellite sensors. The overall result shows that SDSM is essentially functioning without flaws in catching the on-orbit degradation of the SD. The most significant and direct impact of this work would be on the quality of the ocean color products that depend sensitively on moderate RSB (RSB) (M1-M8, M10, and M11). Two very important and key questions on the performance of the SD are also raised. One pertains to the directional dependence of the SD degradation result, and it is shown that the SD does not degrade uniformly in all directions as has been assumed by all SD calibration analyses. This has a definitive impact on the RSB calibration. Another is on the degradation of the SD at the shortwave infrared (SWIR) wavelengths, and it is shown that the zero degradation input for the RSB calibration would be erroneous. Last, the impact of the stray light on the SD since "first light" is cleanly exhibited in the improved SD degradation result. © 2014 Optical Society of America

Mo T.,The Center for Satellite Applications and Research
Journal of Atmospheric and Oceanic Technology | Year: 2010

Daily mean brightness temperatures over Antarctica derived from measurements by three Advanced Microwave Sounding Unit-A (AMSU-A) radiometers on board NOAA-18, NOAA-19, and MetOp-A satellites are studied. To demonstrate the characteristics of the data over this test site, time series of daily averages of the brightness temperatures are constructed. These time series provide a useful pattern of annual variation of the AMSU-A measurements for intercalibration of microwave radiometers on board multiple satellites. To investigate the diurnal effect on the measurements, the time series of daily averaged brightness temperatures are constructed separately for the ascending and descending passes. Results show that there are little diurnal differences in measurements during the Antarctic winter months from each satellite. Therefore these measurements provide a practical approach to obtain relative channel biases of intersatellite data. The monthly averages of the measurements over July 2009 are employed to obtain the relative channel biases because it is the coldest month in Antarctica. The resultant channel biases for the three satellites are within the range of 60.1 K for channels 1-5 and 60.3 K for channels 6-15. This is strong evidence that Antarctica is a potentially good test site for intercalibration of microwave radiometers on board multiple satellites. The small relative biases at channels 1-5 indicate that Antarctica is a very stable test site that is particularly useful for intercalibration of measurements from the window channels. The establishment of a natural test site for calibration references is important for calibration and validation of spaceborne microwave instruments. © 2010 American Meteorological Society.

Pavolonis M.J.,The Center for Satellite Applications and Research
Journal of Applied Meteorology and Climatology | Year: 2010

Infrared measurements can be used to obtain quantitative information on cloud microphysics, including cloud composition (ice, liquid water, ash, dust, etc.), with the advantage that the measurements are independent of solar zenith angle. As such, infrared brightness temperatures (BT) and brightness temperature differences (BTD) have been used extensively in quantitative remote sensing applications for inferring cloud composition. In this study it is shown that BTDs are fundamentally limited and that a more physically based infrared approach can lead to significant increases in sensitivity to cloud microphysics, especially for optically thin clouds. In lieu of BTDs, a derived radiative parameter b, which is directly related to particle size, habit, and composition, is used. Although the concept of effective absorption optical depth ratios b has been around since the mid-1980s, this is the first study to explore the use of b for inferring cloud composition in the total absence of cloud vertical boundary information. The results showed that, even in the absence of cloud vertical boundary information, one could significantly increase the sensitivity to cloud microphysics by converting the measured radiances to effective emissivity and constructing effective absorption optical depth ratios from a pair of spectral emissivities in the 8-12-μm "window." This increase in sensitivity to cloud microphysics is relative to BTDs constructed from the same spectral pairs. In this article, the focus is on describing the physical concepts (which can be applied to narrowband or hyperspectral infrared measurements) used in constructing the β data space. © 2010 American Meteorological Society.

Zou C.-Z.,The Center for Satellite Applications and Research | Wang W.,The Center for Satellite Applications and Research
Journal of Geophysical Research: Atmospheres | Year: 2011

Long-term observations from the Advanced Microwave Sounding Unit-A (AMSU-A) onboard polar-orbiting satellites NOAA 15, 16, 17, and 18 and European Meteorological Operational satellite program-A (MetOp-A) were intercalibrated using their overlap observations. Simultaneous nadir overpasses (SNOs) and global ocean mean differences between these satellites were used to characterize calibration errors and to obtain calibration coefficients. Calibration errors were found manifesting themselves as certain scatter or temporal patterns of intersatellite biases, such as well-defined seasonal cycles in the Arctic and Antarctic SNO difference time series or a unique pattern closely correlated to the instrument temperature variability induced by Solar Beta Angle (SBA) variations in global ocean mean difference time series. Analyses of these patterns revealed five different types of biases that need to be removed from existing prelaunch-calibrated AMSU-A observations, which include relatively stable intersatellite biases between most satellite pairs, bias drifts on NOAA 16 and channel 7 of MetOp-A, sun-heating-induced instrument temperature variability in radiances, scene temperature dependency in biases due to inaccurate calibration nonlinearity, and biases due to channel frequency shift from its prelaunch measurement in certain satellite channels. Level-1c time-dependent calibration offsets and nonlinear coefficients were introduced and determined from SNO and global ocean mean temperature regressions to remove or minimize the first four types of biases. Channel frequency shift in NOAA 15 channel 6 was obtained from the radiative transfer model simulation experiments. The new calibration coefficients and channel frequency values have significantly reduced the five different types of biases and resulted in more consistent multisatellite radiance observations for intercalibrated satellite channels. The intercalibrated AMSU-A observations have been merged with its precursor, the intercalibrated microwave sounding unit (MSU), to generate the NOAA/Center for Satellite Applications and Research (STAR) version 2.0 upper-air temperature climate data record (CDR) for climate trend and variability monitoring from 1979 to the present. The intercalibrated AMSU-A radiance data are expected to further improve accuracies of numerical weather prediction and consistencies in climate reanalysis and CDR developments. Copyright 2011 by the American Geophysical Union.

Sun J.,The Center for Satellite Applications and Research | Wang M.,The Center for Satellite Applications and Research
Applied Optics | Year: 2015

We analyze bidirectional reflectance factors (BRF) of the solar diffuser (SD) and vignetting function (VF) of the SD screen (SDS) for on-board calibration of the visible infrared imaging radiometer suite (VIIRS). Specific focus is placed on the products of the BRFand VF, which are the main inputs for calibration of the SD and its accompanying solar diffuser stability monitor (SDSM), which tracks SD degradation. A set of 14 spacecraft yaw maneuvers for the Suomi National Polar-Orbiting Partnership satellite, which houses the VIIRS instrument, was carefully planned and carried out over many orbits to provide the necessary information on the dependence of VIIRS instrument response on solar angles. Along with the prelaunch measurements for the SDS VF and SD BRF, the absolute form of the BRF-VF product is determined for each of the reflective solar bands (RSB) and the SDSM detectors. Consequently, the absolute form of the SDS VF also is obtained from the RSB and SDSM detectors using the yaw maneuver data. The results show that the BRF-VF product for an RSB is independent of the detector, gain status, and half-angle mirror side. The derived VFs from the RSB and the SDSM detectors also show reasonable agreement with each other, as well as with the prelaunch VF measurements, and further demonstrate only geometrical dependence, which, in this work, is characterized by solar angles. The derived calibration coefficients, called the F-factors, from the application of the derived functions in this study show a significantly improved pattern. A small band-dependent residual seasonal fluctuation on the level of ∼0.2%-0.4% remains in the F-factors for each RSB and is further improved by a corrective function with linear dependence on the solar azimuth angle in the nominal attitude instrument coordinate system to the VF. For satellite ocean color remote sensing, on-orbit instrument calibration and characterization are particularly important for producing accurate and consistent ocean color products. The result of this work has the most significant and direct impact on ocean color products. © 2015 Optical Society of America.

Foster M.J.,University of Wisconsin - Madison | Heidinger A.,The Center for Satellite Applications and Research
Journal of Climate | Year: 2013

Satellite drift is a historical issue affecting the consistency of those few satellite records capable of being used for studies on climate time scales. Here, the authors address this issue for the Pathfinder Atmospheres Extended (PATMOS-x)/Advanced Very High Resolution Radiometer (AVHRR) cloudiness record, which spans three decades and 11 disparatesensors.Atwo-harmonic sinusoidal function is fit to a mean diurnal cycle of cloudiness derived over the course of the entire AVHRRrecord. The authors validate this function against measurements from Geostationary Operational Environmental Satellite (GOES) sensors, finding good agreement, and then test the stability of the diurnal cycle over the course ofthe AVHRR record. It is found that the diurnal cycle is subject to some interannual variability over land but that the differences are somewhat offset when averaged over an entire day. The fit function is used to generate daily averaged time series of ice, water, andtotal cloudiness over the tropics, where it is found that the diurnal correction affects the magnitude and even the sign of long-term cloudiness trends. A statistical method is applied to determine the minimum length of time required to detect significant trends, andthe authors find that only recently have they begun generating satellite records of sufficient length to detect trends in cloudiness. © 2013 American Meteorological Society.

Gao S.,CAS Institute of Atmospheric Physics | Li X.,The Center for Satellite Applications and Research
Quarterly Journal of the Royal Meteorological Society | Year: 2011

The precipitation efficiencies (RMPE, CMPE, and LSPE) can be defined as the ratio of rain rate to rainfall sources in the rain microphysical budget, the cloud microphysical budget, and the surface rainfall budget, respectively. The estimate of RMPE from grid-scale data serves as the true precipitation efficiency since the rain rate is a diagnostic term in the tropical rain microphysical budget. The accuracy of precipitation efficiency estimates with CMPE and LSPE is compared to that of RMPE by analyzing data from a 21-day two-dimensional cloud-resolving model simulation with imposed large-scale vertical velocity, zonal wind, and horizontal advection obtained from the Tropical Ocean Global Atmosphere Coupled Ocean-Atmosphere Response Experiment. The results show CMPE is generally smaller than RMPE. The root-mean-squared difference between RMPE and LSPE is larger than the standard deviation of RMPE. Thus, water vapour process data cannot be used to estimate precipitation efficiency. Copyright © 2011 Royal Meteorological Society.

Son S.,The Center for Satellite Applications and Research | Son S.,Colorado State University | Wang M.,The Center for Satellite Applications and Research
Remote Sensing of Environment | Year: 2012

This study evaluates the performance of ocean color products derived from measurements of the Moderate Resolution Imaging Spectroradiometer (MODIS) on the satellite Aqua using the standard near-infrared (NIR) and the shortwave infrared (SWIR)-based atmospheric correction algorithms in the Chesapeake Bay. The MODIS-Aqua-derived normalized water-leaving radiances, nL w(λ), and chlorophyll-a (Chl-a) data are compared with in situ radiometric measurements from the NASA SeaWiFS Bio-optical Archive and Storage System (SeaBASS) database and Chl-a data from the Chesapeake Bay Water Quality Database. Results show that, using the NIR-SWIR combined ocean color data processing, improved nL w(λ) and Chl-a data products can be produced in the Chesapeake Bay. However, Chl-a data are still overestimated in some Chesapeake Bay regions, in particular, in the upper bay region where waters are strongly influenced by the total suspended sediment (TSS) concentration. Specifically, using the NIR-SWIR approach, mean ratios of MODIS-derived and in situ-measured nL w(λ) at wavelengths of 412, 443, 488, 531, 551, and 667nm for the Chesapeake Bay are 1.288, 1.093, 0.998, 0.946, 0.908, and 0.865, respectively, while mean Chl-a values over the region from satellite-derived and in situ-measure data are 11.14 and 10.28mg·m -3, respectively. Based on a strong correlation relationship between TSS and water diffuse attenuation coefficient, a regional TSS algorithm for the Chesapeake Bay has been developed and validated, with mean ratio of 1.064 between MODIS-derived and in situ-measured TSS data. Therefore, using the NIR-SWIR algorithm for MODIS-Aqua ocean color data processing, nL w(λ), Chl-a, and TSS data from 2002 to 2010 for the Chesapeake Bay have been generated and used for characterizing the water properties in the region, showing strong seasonal and interannual variability, as well as important spatial variations in the region. © 2012.

Walther A.,University of Wisconsin - Madison | Heidinger A.K.,The Center for Satellite Applications and Research
Journal of Applied Meteorology and Climatology | Year: 2012

This paper describes the daytime cloud optical and microphysical properties (DCOMP) retrieval for the Pathfinder Atmosphere's Extended (PATMOS-x) climate dataset. Within PATMOS-x, DCOMP is applied to observations from the Advanced Very High Resolution Radiometer and employs the standard bispectral approach to estimate cloud optical depth and particle size. The retrievals are performed within the optimal estimation framework. Atmospheric-correction and forward-model parameters, such as surface albedo and gaseous absorber amounts, are obtained from numerical weather prediction reanalysis data and other climate datasets. DCOMP is set up to run on sensors with similar channel settings and has been successfully exercised on most current meteorological imagers. This quality makes DCOMP particularly valuable for climate research. Comparisons with the Moderate Resolution Imaging Spectroradiometer (MODIS) collection-5 dataset are used to estimate the performance of DCOMP. © 2012 American Meteorological Society.

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