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At least 253 records · Page 14

Recent Progress on Deep Blue Aerosol Algorithm as Applied TO MODIS, SEA WIFS, and VIIRS, and Their Intercomparisons with Ground Based and Other Satellite Measurements

The impact of natural and anthropogenic sources of aerosols has gained increasing attention from scientific communities in recent years. Indeed, tropospheric aerosols not only perturb radiative energy balance by interacting with solar and terrestrial radiation, but also by changing cloud properties and lifetime. Furthermore, these anthropogenic and natural air particles, once generated over the source regions, can be transported out of the boundary layer into the free troposphere and can travel thousands of kilometers across oceans and continents resulting in important biogeochemical impacts on the ecosystem. With the launch of SeaWiFS in 1997, Terra/MODIS in 1999, and Aqua/MODIS in 2002, high quality comprehensive aerosol climatology is becoming feasible for the first time. As a result of these unprecedented data records, studies of the radiative and biogeochemical effects due to tropospheric aerosols are now possible. In this talk, we will demonstrate how this newly available SeaWiFS/MODIS aerosol climatology can provide an important piece of puzzles in reducing the uncertainty of estimated climatic forcing due to aerosols. We will start with the global distribution of aerosol loading and their variabilities over both land and ocean on short- and long-term temporal scales observed over the last decade. The recent progress made in Deep Blue aerosol algorithm on improving accuracy of these Sea WiFS / MODIS aerosol products in particular over land will be discussed. The impacts on quantifying physical and optical processes of aerosols over source regions of adding the Deep Blue products of aerosol properties over bright-reflecting surfaces into Sea WiFS / MODIS as well as VIIRS data suite will also be addressed. We will also show the intercomparison results of SeaWiFS/MODIS retrieved aerosol optical thickness with data from ground based AERONET sunphotometers over land and ocean as well as with other satellite measurements. The trends observed in global aerosol loadings of both natural and anthropogenic sources based upon more than a decade of combined MODIS/SeaWiFS data (1997-2011) will be discussed. We will also address the importance of various key issues such as differences in spatial-temporal sampling rates and observation time between different satellite measurements could potentially impact these intercomparisons results, especially for using the monthly mean data, and thus on estimates of long-term aerosol trends.

Hsu, N. Christina↗

Characterization and Performance of the Suomi-NPP VIIRS Solar Diffuser Stability Monitor

We describe the on-orbit characterization and performance of the Solar Diffuser Stability Monitor (SDSM) on-board Suomi-NPP/VIIRS. This description includes the observing procedure of each SDSM event, the algorithms used to generate the Solar Diffuser degradation corrective factors, and the results for the mission to date. We will also compare the performance of the VIIRS SDSM and SD to the similar components operating on the MODIS instrument on the EOS Terra and Aqua satellites

Fulbright, Jon P.↗

Calibration of VIIRS F1 Sensor Fire Detection Band Using lunar Observations

Visible Infrared Imager Radiometer Suite (VIIRS) Fight 1 (Fl) sensor includes a fire detection band at roughly 4 microns. This spectral band has two gain states; fire detection occurs in the low gain state above approximately 345 K. The thermal bands normally utilize an on-board blackbody to provide on-orbit calibration. However, as the maximum temperature of this blackbody is 315 K, the low gain state of the 4 micron band cannot be calibrated in the same manner as the rest of the thermal bands. Regular observations of the moon provide an alternative calibration source. The lunar surface temperature has been recently mapped by the DIVINER sensor on the LRO platform. The periodic on-board high gain calibration along with the DIVINER surface temperatures was used to determine the emissivity and solar reflectance of the lunar surface at 4 microns; these factors and the lunar data are then used to fit the low gain calibration coefficients of the 4 micron band. Furthermore, the emissivity of the lunar surface is well known near 8.5 microns due to the Christiansen feature (an emissivity maximum associated with Si-O stretching vibrations) and the solar reflectance is negligible. Thus, the 8.5 micron band is used for relative calibration with the 4 micron band to de-trend any temporal variations. In addition, the remaining thermal bands are analyzed in a similar fashion, with both calculated emissivities and solar reflectances produced.

McIntire, Jeff↗

A Simplified Approach to Cloud Masking with VIIRS in the S-NPP/JPSS Era

The quantitative detection of clouds in satellite imagery has a number of important applications in weather analysis. The proper interpretation of satellite imagery for improved situational awareness depends on knowing where the clouds are at all times of the day. Additionally, many products derived from infrared measurements need accurate cloud information to mask out regions where retrieval of geophysical parameters in the atmosphere or on the surface are not possible. Thus, the accurate detection of the presence of clouds in satellite imagery on a global basis is important to the product developers and the operational weather community to support their decision‐making process. This abstract describes an application of a two‐channel bispectral composite threshold (BCT) approach applied to VIIRS imagery. The simplified BCT approach uses only the 10.76 and 3.75 micrometer spectral channels in two spectral tests; a straightforward infrared threshold test with the longwave channel and a shortwave minus longwave channel difference test. The key to the success of this approach as demonstrated in past applications to GOES and MODIS data is the generation of temporally and spatially dependent thresholds used in the tests from a previous number of days at similar observations to the current data. The presentation will present an overview of the approach and intercomparison results with other satellites, methods, and against verification data.

Jedlovec, Gary J.↗

Validation of Cloud Parameters Derived from Geostationary Satellites, AVHRR, MODIS, and VIIRS Using SatCORPS Algorithms

Validation is a key component of remote sensing that can take many different forms. The NASA LaRC Satellite ClOud and Radiative Property retrieval System (SatCORPS) is applied to many different imager datasets including those from the geostationary satellites, Meteosat, Himiwari-8, INSAT-3D, GOES, and MTSAT, as well as from the low-Earth orbiting satellite imagers, MODIS, AVHRR, and VIIRS. While each of these imagers have similar sets of channels with wavelengths near 0.65, 3.7, 11, and 12 micrometers, many differences among them can lead to discrepancies in the retrievals. These differences include spatial resolution, spectral response functions, viewing conditions, and calibrations, among others. Even when analyzed with nearly identical algorithms, it is necessary, because of those discrepancies, to validate the results from each imager separately in order to assess the uncertainties in the individual parameters. This paper presents comparisons of various SatCORPS-retrieved cloud parameters with independent measurements and retrievals from a variety of instruments. These include surface and space-based lidar and radar data from CALIPSO and CloudSat, respectively, to assess the cloud fraction, height, base, optical depth, and ice water path; satellite and surface microwave radiometers to evaluate cloud liquid water path; surface-based radiometers to evaluate optical depth and effective particle size; and airborne in-situ data to evaluate ice water content, effective particle size, and other parameters. The results of comparisons are compared and contrasted and the factors influencing the differences are discussed.

Minnis, P.↗

Product of the SNPP VIIRS SD Screen Transmittance and the SD BRDF (RSB) From Both Yaw Maneuver and Regular On-Orbit Data

To assure data quality, the Earth-observing Visible Infrared Imaging Radiometer Suite (VIIRS) regularly performs on-orbit radiometric calibrations of its 22 spectral bands. The primary calibration radiance source for the reflective solar bands (RSBs) is a sunlit solar diffuser (SD). During the calibration process, sunlight goes through a perforated plate (the SD screen) and then strikes the SD. The SD scattered sunlight is used for the calibration, with the spectral radiance proportional to the product of the SD screen transmittance and the SD bidirectional reflectance distribution function (BRDF). The BRDF is decomposed to the product of its value at launch and a numerical factor quantifying its change since launch. Therefore, the RSB calibration requires accurate knowledge of the product of the SD screen transmittance and the BRDF (RSB; launch time). Previously, we calculated the product with yaw maneuver data and found that the product had improved accuracy over the prelaunch one. With both yaw maneuver and regular on orbit data, we were able to improve the accuracy of the SDSM screen transmittance and the product for the solar diffuser stability monitor SD view. In this study, we use both yaw maneuver and a small portion of regular on-orbit data to determine the product for the RSB SD view.

Lei, Ning↗

LaSRC (Land Surface Reflectance Code): Overview, Application and Validation Using MODIS, VIIRS, LANDSAT and Sentinel 2 Data's

This paper presents a generic approach developed to derive surface reflectance over land from a variety of sensors. This technique builds on the extensive dataset acquired by the Terra platform by combining MODIS and MISR to derivean explicit and dynamic map of band ratio's between blue and red channels and is a refinement of the operational approach used for MODIS and LANDSAT over the past 15 years. We will present the generic approach and the application to MODIS VIIRS, LANDSAT and Sentinel 2 data's and its validation using the AERONET data.

validation↗

Determination of the NOAA-20 VIIRS screen transmittance functions with both the yaw maneuver and regular on-orbit calibration data

The Visible Infrared Imaging Radiometer Suite (VIIRS) aboard theNOAA-20 satellite regularly performs on-orbit radiometric calibration of its reflective solar bands (RSBs) through observations of an onboard sunlit solar diffuser (SD). The incident sunlight passes through an attenuation screen (the SD screen) and then scatters off the SD to provide a radiance source for the calibration. The on-orbit change of the SD’s bidirectional reflectance distribution function (BRDF), referred to as the H-factor, is determined by an onboard solar diffuser stability monitor (SDSM) whose eight detectors alternately observe the Sun through another attenuation screen (the SDSM screen) and the sunlit SD. The products of the SD screen transmittance and the BRDF at the mission start for both the SDSM and RSBs and the SDSM screen effective transmittance were measured prelaunch. Large unrealistic undulations in the retrieved H-factor were seen when using the prelaunch screen functions. To improve the accuracy of the retrieved H-factor, shortly after the satellite launch, 15 yaw maneuvers were performed to further characterize the screens. Although significantly improved, the H-factor derived using the screen functions determined fromthe yaw maneuver data still has large unrealistic undulations, revealing that the solar azimuth angular step size of the yaw maneuvers is too large. In this paper,we add high-quality regular on-orbitSDcalibration data to the yaw maneuver data to further improve the relative product of the SD screen effective transmittance and the BRDF at the mission start for the SDSM and the SDSM screen relative effective transmittance. The H-factor time series derived from the newly determined screen transmittance functions is much smoother than that derived from using only the yaw maneuver data and thus considerably improves the radiometric calibration accuracy.

Ning Lei↗

Monitoring the Calibration of the DSCOVR EPIC Instrument’s Visible Cchannels Using MODIS and VIIRS as a Reference

The Earth Polychromatic Imaging Camera (EPIC) instrument aboard the Deep Space Climate Observatory (DSCOVR) satellite has a constant unique view of the sunlit disk of the Earth from the Lagrange-1 (L1) point nearly a million miles away from the Earth. Due to EPIC not having any on-board calibration systems, the ten spectral channels of EPIC must be inter-calibrated using vicarious on-orbit methods, such as ray-matching with well-calibrated low Earth orbiting satellites like the Aqua-MODIS and SNPP-VIIRS radiometers. The recently released EPIC version 3 L1B data has greatly enhanced the residual navigation errors found in prior versions, thereby decreasing the calibration uncertainty in the aforementioned ray-matching calibration techniques. The automated navigation correction used by these ray-matching methods for further improving the EPIC geolocation will be compared with a new navigation correction method utilizing optical flow between the EPIC and MODIS/VIIRS images. The DSCOVR satellite went into safe mode on June 27, 2019 due to an anomaly with the satellite’s attitude control system, but operations recommenced on March 2, 2020. The calibration of the EPIC instrument before it went into safe mode and after it resumed will be analyzed in order to investigate any potential calibration shifts or discontinuities caused by the spacecraft anomaly.

Conor Haney↗

SNPP VIIRS RSB on-orbit radiometric calibration algorithms Version 2.0 and the performances. Part I: The algorithms

The first VIIRS instrument is aboard the Suomi National Polar-orbiting Partnership satellite. The instrument has 14 reflective solar bands (RSBs) to passively collect photons reflected from the Earth surface in the design wavelengths from 412 to 2250 nm. The instrument uses a solar diffuser (SD) to radiometrically calibrate its RSBs. When lit by the Sun through an attenuation screen (the SD screen), the SD diffusely reflects off the incident sunlight to act as a radiance source for the calibration. An onboard solar diffuser stability monitor (SDSM) yields the on-orbit change of the SD bidirectional reflectance distribution function (BRDF) by comparing the signal strength from the SD with that from the Sun attenuated by another attenuation screen (the SDSM screen). Complications arise due to the discovery that the on-orbit change of the BRDF is angle dependent. Additionally, the SDSM does not cover the wavelengths for the short-wave infrared bands in the RSBs. Furthermore, satellite yaw maneuvers were performed in the early mission to yield data for refining the prelaunch SDSM screen relative effective transmittance and the relative product of the SD screen transmittance and the BRDF at the mission start. But the yaw maneuver data are coarse in the solar azimuth angles and thus are unable to yield accurate values between the measurement angles. Over the years of performing on-orbit radiometric calibration through the SD for the VIIRSRSBs, we have developed several highly effective calibration algorithms to address the issues mentioned above. This paper reviews these algorithms.

Ning Lei↗

Short timescale stability monitoring of GOES-16 visible channels based on daily inter-calibration events with VIIRS and MODIS

The CERES project uses geostationary (GEO) imager derived broadband fluxes to estimate the diurnal flux variations between the Terra (10:30 LT) and Aqua (1:30 LT) flux obs. The GEO derived cloud properties are utilized for narrowband to broadband and angular directional model (ADM) algorithms. The GEO imager channels are first inter-calibrated to the Aqua-MODIS C6.1 calibration reference to ensure that the retrieved clouds and fluxes will be consistent. The CERES project has a 2-month latency, all GEO, MODIS and VIIRS calibration anomalies must be identified and mitigated. Convert the monthly GEO ray-matching algorithm into a daily monitoring algorithm to catch any daily calibration anomalies.

geostationary sensor calibration↗

Sensor Calibration Impacts on Dust Detection Based On MODIS And VIIRS Thermal Emissive Bands

Dust detection using remotely sensed measurements has been one of the challenging problems encountered by atmospheric scientists. MODerate Resolution Imaging Spectroradiometer (MODIS) on the Terra (T)and Aqua (A) platforms have been a versatile sensor for well over 21 and 18 years respectively and have been extremely useful in the retrieval of aerosol information over the entire globe. The MODIS radiances from the Level1B in general are expected to be within 5% accuracy in the reflective wavelengths and within 1% in the thermal emissive wavelengths. In this paper, we evaluate the sensitivity of previously developed dust detection technique based on thermal emissive wavelengths, which correspond to MODIS bands 20, 29, 31, and 32 respectively. The Thermal Emissive Dust Index (TEDI) performed very comparably to the traditional Aerosol Optical Thickness (AOT) retrievals by MODIS reflective channels. Since the MODIS Thermal Emissive Bands (TEB) are well calibrated on-orbit using a BlackBody (BB) source, the calibration of these long wave infrared bands is quite robust. As A-MODIS continues to perform well beyond its designed lifetime of 6 years, the instrument has undergone various levels of degradation during its mission time. As a consequence, it is imperative to check the impacts of calibration on the higher-level retrievals. In this paper, we rigorously analyze the sensitivity of TEDI due to the impact of calibration by the afore-mentioned TEB. The perturbation of the dominant (linear) calibration term demonstrated the following: first, there was a correlation in the sensitivity of the TEDI due to the uncertainty in the linear calibration term. Based on a perturbation in the linear calibration term for all aforementioned bands over a range of ± 5 % yielded the TEDI sensitivity to vary from approximately -3.2 % to about -3.6 %. When considering the uncertainty in each individual band significant changes were observed. The least change was observed for the perturbation in the calibration of band 20 with the TEDI sensitivity and the largest sensitivity in TEDI was observed in the perturbation of band 31 calibration. Thus, in the case of TEDI, noticeable sensitivity due to calibration uncertainty was observed in bands 29, 31, and 32, reiterating the importance of the TEB calibration in these bands. Also, the dust detection scheme based on A-MODIS was successfully transferred to the follow-on sensors such as Suomi (SNPP) and NOAA 20 (N20) VIIRS. The results presented in this paper would be extremely helpful in understanding impacts of calibration on the higher-level products for both current and future missions based on the MODIS heritage. Finally, the work also identifies the importance of radiometric fidelity in maintaining the accuracy of the dust detection. Results presented will show drastic improvement of the Saharan dust detection after the reduction of the electronic crosstalk in the 8.5 μm channel of T-MODIS.

Sriharsha Madhavan↗

Validation, Comparison, and Integration of GOCI, AHI, MODIS, MISR, and VIIRS Aerosol Optical Depth Over East Asia During the 2016 KORUS-AQ Campaign

Recently launched multichannel geostationary Earth orbit (GEO) satellite sensors, such as the Geostationary Ocean Color Imager (GOCI) and the Advanced Himawari Imager (AHI), provide aerosol products over East Asia with high accuracy, which enables the monitoring of rapid diurnal variations and the transboundary transport of aerosols. Most aerosol studies to date have used low Earth orbit (LEO) satellite sensors, such as the Moderate Resolution Imaging Spectroradiometer (MODIS) and the Multi-angle Imaging Spectroradiometer (MISR), with a maximum of one or two overpass daylight times per day from midlatitudes to low latitudes. Thus, the demand for new GEO observations with high temporal resolution and improved accuracy has been significant. In this study the latest versions of aerosol optical depth (AOD) products from three LEO sensors – MODIS (Dark Target, Deep Blue, and MAIAC), MISR, and the Visible/Infrared Imager Radiometer Suite (VIIRS), along with two GEO sensors (GOCI and AHI), are validated, compared, and integrated for a period during the Korea–United States Air Quality Study (KORUS-AQ) field campaign from 1 May to 12 June 2016 over East Asia. The AOD products analyzed here generally have high accuracy with high R (0.84–0.93) and low RMSE (0.12–0.17), but their error characteristics differ according to the use of several different surface-reflectance estimation methods. High-accuracy near-real-time GOCI and AHI measurements facilitate the detection of rapid AOD changes, such as smoke aerosol transport from Russia to Japan on 18–21 May 2016, heavy pollution transport from China to the Korean Peninsula on 25 May 2016, and local emission transport from the Seoul Metropolitan Area to the Yellow Sea in South Korea on 5 June 2016. These high-temporal-resolution GEO measurements result in more representative daily AOD values and make a greater contribution to a combined daily AOD product assembled by median value selection with a 0.5∘×0.5∘ grid resolution. The combined AOD is spatially continuous and has a greater number of pixels with high accuracy (fraction within expected error range of 0.61) than individual products. This study characterizes aerosol measurements from LEO and GEO satellites currently in operation over East Asia, and the results presented here can be used to evaluate satellite measurement bias and air quality models.

Myungje Choi↗

Calibrating CERES and VIIRS using CLARREO Pathfinder: Adjustment for the Viewing Geometry Mismatch

The Climate Absolute Radiance and Refractivity Observatory Pathfinder (CPF) mission on the International Space Station (ISS) will provide, for the first-time, an SI-traceable on-orbit calibration reference with a reflectance uncertainty of 0.3% (1 sigma). One major mission objective is to demonstrate the capability of transferring CPF’s radiometric accuracy to other satellite-based instruments, such as Clouds and Earth's Radiant Energy System (CERES) and Visible Infrared Imaging Radiometer Suite (VIIRS) on NOAA-20. CPF inter-calibration measurements will be planned to obtain inter-calibration samples that closely match satellite-based target sensor observations in time, space, angle, and wavelength. The inter-calibration event observations cover a wide range of viewing geometry angles with potential angular mismatch between CPF and the target sensors which can introduce non-negligible errors against the mission’s inter-calibration uncertainty budget. We will introduce the CPF approach to adjust for angular mismatch differences, thereby reducing the incurred uncertainties to within the inter-calibration uncertainty budget. The angular adjustment algorithm has been developed and validated based on the high-fidelity simulations of the CPF spectra using the Principal Component based Radiative Transfer Model (PCRTM). The implementation of the algorithm on event simulation data and the characterization for the angular adjustment uncertainty will be presented.

Wan Wu↗

Long-Term Variation of Aerosol Optical Properties Associated With Aerosol Types Over East Asia Using AERONET and Satellite (VIIRS, OMI) Data (2012–2019)

We analyzed annual and seasonal frequency in aerosol type over an 8-year period (2012–2019) to identify aerosol parameter trends over four ground sites and country regions in Korea, China, and Japan by using the Aerosol Robotic Network (AERONET), and the satellite-based Visible Infrared Imaging Radiometer Suite (VIIRS) and Ozone Monitoring Instrument (OMI). Decreasing trends are shown for aerosol optical depth (AOD), Ångstr¨om exponent (AE), and fine mode fraction (FMF) in all countries. The decreasing trend in these data is considered to be due to a decrease in anthropogenic emissions. For the aerosol type frequency, decreases in the proportions of carbonaceous aerosols (CA) and non-absorbing aerosols (NA) were shown in the ground and satellite data, respectively. At most sites, the fractions of low AOD case (LOW) increased, whereas those of the Black and Brown Carbon (BC + BrC) category decreased. In Seoul, the fraction of LOW increased from 48.9% to 70.0%, and that of BC + BrC decreased continuously from 20.4% to 11.1% during 2012–2019. Beijing, on the other hand, showed decreasing LOW from 83.3% (2012) to 52.0% (2019), and that of BC + BrC increased significantly, from 2.4% to 26.2%. The satellite data showed that the percentage of LOW increased continuously, while that of NA aerosols decreased continuously in East Asia. A noticeable decrease in the fraction of CA was detected in China [21.5% (2013) to 11.2% (2019)]. In all countries, CA and NA aerosols had the greatest effect in winter and summer, respectively. We also detected significant differences between the fractions of NA and BC between the ground and satellite data. Changes in aerosol type and properties were observed concurrently in all ground and satellite data, and changes in aerosol type may explain the increasing and decreasing trends that we recorded for most parameters. Consistent results from both ground and satellite data suggest a steady decreasing in fine aerosol pollution in East Asia.

Sujin Eom↗

Creating Near Real-time Hourly VIIRS Radiance Mosaic over Polar Regions from SatCORPS Global Cloud Composite (GCC)

While polar orbiting satellites are essential in providing the needed observations over polar regions for data assimilation, weather diagnoses/forecasting, and flight guidance and situation awareness in airborne field campaigns, there is limited temporal coverage. Often, polar mosaics are created by overlaying multiple satellite imagers on top of each other which can lead to transition lines and discontinuities in the data products. To help ease some of these shortcomings, we utilize the NASA Langley Satellite ClOud and Radiation Property retrieval System (SatCORPS) Mosaic algorithm for optimally fusing and merging selected imager radiances from the Visible Infrared Imaging Radiometer Suite (VIIRS) instrument onboard the Suomi National polar-orbiting Partnership (SNPP), Joint Polar Satellite System (JPSS-1), and JPSS-2 satellites, and the MODerate resolution Imaging Spectroradiometer (MODIS) instruments onboard AQUA and TERRA satellites. Since multiple satellites overpasses and instruments are used in creating hourly 3-km composites over the polar regions, selection of the best satellite data for each 3-km composite pixel is based on aggregated ranking of satellite resolution, time, viewing zenith angle, and distance from terminator. This ranking system provides a smoother transition and improves data discontinuity in the merged output resulting in a more seamless polar region dataset. We will discuss the use of this near real-time dataset to support polar airborne field campaigns and SatCORPS satellite-derived Global Cloud Composite (GCC) generation.

Satellite composites↗

Extending the Deep Blue aerosol record from SeaWiFS and MODIS to NPP-VIIRS

Deep Blue expands AOD coverage to deserts and other bright surfaces. Using multiple similar satellite sensors enables us to obtain a long data record. The Deep Blue family consists of three separate aerosol optical depth (AOD) retrieval algorithms: 1. Bright Land: Surface reflectance database, BRDF correction. AOD retrieved separately at each of 412, 470/490, (650) nm. SSA retrieved for heavy dust events. 2. Dark Land: Spectral/directional surface reflectance relationship. AOD retrieved separately at 470/490 and 650 nm. 3. Water: Surface BRDF including glint, foam, underlight. Multispectral inversion (Not present in MODISdataset) All report the AOD at 550 nm, and Ångström exponent (AE).

SeaWiFS and MODIS↗