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115 records · Page 7
All sourcesNASA NTRSDOE OSTI
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 NTRS2019

MODIS Reflective Solar Bands On-Orbit Calibration and Performance

The design of the MODIS instrument was driven by the scientific community's desire to have near-daily global coverage at moderate resolution (1 km) with a comprehensive spectral coverage from visible to long-wave infrared wavelengths. Since their launches in 1999 and 2002, respectively, the Terra and Aqua MODIS instruments have made continuous global observations and generated numerous data products to help users worldwide with their studies of the Earth's system and its short- and long-term changes. The 20 reflective solar bands (RSB) with wavelengths from 0.41 to 2.2 m collect data at three nadir spatial resolutions: 250 m, 500 m, and 1 km. The solar diffuser (SD) coupled with the solar diffuser stability monitor (SDSM) provide a reflectance-based calibration on-orbit. In addition, lunar observations and response trends from pseudo-invariant desert sites are used to characterize the response versus scan- angle changes on-orbit. This paper provides a brief overview of MODIS RSB calibration algorithms, as implemented in the latest Level 1B version 6.1, operational activities, on-orbit performance, remaining challenges and potential improvements. Results from the SD and SDSM measurements show a wavelength and mirror side dependent degradation in RSB responses, with the largest degradation at the shortest wavelengths, particularly for Terra MODIS. Aqua MODIS has experienced far less degradation of its optics and on-board calibrators compared to Terra MODIS, resulting in an overall better performance. With the exception of Aqua band 6, there have been no new noisy or inoperable detectors in the RSB of either instrument during post-launch operations. As the instruments age and continue to endure the space environment, the detectors and optical systems degrade. The challenges associated with incorporating these on-orbit changes to ensure a production of high-quality calibrated L1B data products are also discussed in this paper.

solar diffuser stability monitor↗
NASA NTRS2015

On-Orbit Noise Characterization of MODIS Reflective Solar Bands

The Moderate Resolution Imaging Spectroradiometer (MODIS), launched on the Terra and Aqua spacecrafts, was designed to collect complementary and comprehensive measurements of the Earth's properties on a global scale. The 20 reflective solar bands (RSBs), covering a wavelength range from 0.41 to 2.1 micrometers, are calibrated on-orbit using regularly scheduled solar diffuser (SD) observations. Although primarily used for on-orbit gain derivation, the SD observations also facilitate the characterization of the detector signal-to-noise ratio (SNR). In addition to the calibration requirement of 2% for the reflectance factors and 5% for the radiances, the required SNRs are also specified for all RSB at their typical scene radiances. A methodology to characterize the on-orbit SNR for the MODIS RSB is presented. Overall performance shows that a majority of the RSB continue to meet the specification, therefore performing well. A temporal decrease in the SNR, observed in the short-wavelength bands, is attributed primarily to the decrease in their detector responses. With the exception of the inoperable and noisy detectors in band 6 identified prelaunch, the detectors of AquaMODIS RSB perform better than TerraMODIS. The approach formulated for on-orbit SNR characterization can also be used by other sensors that use on-board SDs for their on-orbit calibration (e.g., Suomi National Polar-Orbiting Partnership [SNPP]-Visible Infrared Imaging Radiometer Suite).

Reflective↗
NASA NTRS2005

Giovanni: A System for Rapid Access, Visualization and Analysis of Earth Science Data Online

Collecting data and understanding data structures traditionally are the first steps that a user must take, before the core investigation can begin. This is a time-consuming and challenging task, especially when science objectives require users to deal with large multi-sensor data that are usually in different formats and internal structures. The Goddard Earth Sciences Data and Information Services Center (GES DISC) has created the GES DISC Interactive Online Visualization and ANalysis Infrastructure, Giovanni, to enable Web-based visualization and analysis of satellite remotely sensed meteorological, oceanographic, and hydrologic data sets, without users having to download data. The current operational Giovanni interfaces provide the capability to process a number of important satellite measurements, such as (1) ozone and other trace gases from TOMS, OMI, HALOE, and MLS; (2) air temperature, water vapor, and geopotential height from AIRS; (3) aerosols from MODIS TerrdAqua, and GOCART model; (4) precipitation from TRMM and ground measurements; (5) chlorophyll and other ocean color products from SeaWiFS and MODIS Aqua; and (6) sea surface temperature from MODIS Aqua. Depending on the input data structure, the system provides simple statistical analysis and creates time-averaged area plot, area-averaged time series, animations, Hovmoller latitude vs. time and longitude vs. time plots, as well as vertical profiles. The inter-comparison interfaces allow a user to compare observations from different instruments, to conduct anomaly analysis, and to study basic relationships between physical parameters. Giovanni handles data with different temporal and spatial resolutions and, thus, enables both regional and global long-term climate research and short-term special events investigation, as well as data validations and assessments. Because of its simplicity of usage, Giovanni is powerful and versatile, able to assist a wide range of users, from the discipline scientists conducting preliminary research in various fields, to students in the classroom learning about weather, climate, and other natural phenomena. Giovanni can be accessed from: http://disc. esfc.nasa.gov/techlab/giovanni/index.shtml

Shen, S.↗
NASA NTRSDate not supplied

Ground control points refresh for MODIS and VIIRS geolocation monitoring

The Control Point Matching (CPM) program and a set of over 1200 globally distributed ground control points (GCPs ) have been successfully used to develop more than 20 years of MODIS geolocation products. In this research, we refresh current GCP library with more than 2500 new GCPs using the latest Landsat 8 Collection 2 images. The refreshed GCPs are distributed from 56 S to 80 N latitude, with more than 2000 shoreline and 500 inland GCP chips. The size of these GCPs are extended from800*800 to 1400*1400 Landsat pixels and the CPM program correspondingly increase s t h e searching distance from 0.8 pixels to 2.5 pixels, which also extends the geolocation error measurement from +/-45 to the edge of scan at +/-55 degree in scan angle. This will allow the algorithm to catch geolocation errors that are larger than one MODIS pixel. The geolocation errors measured with the refreshed GCP library are comparable to the previous results, yet with 2-3more times of matched GCPs. The daytime Aqua ascending orbits and Terra descending orbits enable us to identify a few GCP outliers which might be due to the quality of the original Landsat images. Most importantly, the refreshed GCP library will include images from both Landsat band 4 to match with VIIRS I1, and Landsat band 6 to match with VIIRS I3. This will allow us to measure and correct on orbit band-to-band registration at both track and scan directions, which will help understanding and improving future JPSS mission’s prelaunch geometric performance.

VIIRS↗
NASA NTRS2023

Aqua MODIS: 20 Years of On-orbit Calibration and Performance

Since its launch in May 2002, Aqua MODIS has successfully operated for more than 20 years and has continuously generated a wide range of data products that have enabled and supported the remote sensing community and users worldwide for their studies of the Earth’s system by monitoring changes in its key environmental parameters. Although Aqua MODIS, designed with a lifetime requirement of 6 years, is currently operated in its extended mission phase, it continues to make high quality global observations of the Earth’s surface via its 36 spectral bands that cover wavelengths from visible to long-wave infrared. To date, all instrument on-board calibrators (OBC) remain capable of performing their design functions, providing various calibration data sets to help monitor on-orbit changes in sensor responses and performance characteristics. In addition to the OBC, regularly scheduled lunar observations and select Earth-view targets are used extensively to support sensor on-orbit calibration, especially for the calibration of the visible channels (or bands). In this paper, we provide an overview of Aqua MODIS on-orbit calibration activities and methodologies for both reflective solar bands (RSB) and thermal emissive bands (TEB), illustrate its on-orbit performance over the past 20 years using examples derived from OBC measurements, lunar observations, and Earth-view response trends, and describe various calibration improvements made over its entire mission. We focus on key issues identified since launch, such as solar diffuser degradation, electronic crosstalk, and on-orbit changes in sensor response versus scan-angle, along with approaches and strategies developed to mitigate their impact on sensor calibration quality. Also discussed in this paper are some of the key calibration enhancements incorporated recently in the Collection 6.1 and the upcoming Collection 7 Level-1B algorithms.

Polarization↗
NASA NTRS2012

Accuracy Assessment of Aqua-MODIS Aerosol Optical Depth Over Coastal Regions: Importance of Quality Flag and Sea Surface Wind Speed

Coastal regions around the globe are a major source for anthropogenic aerosols in the atmosphere, but the underlying surface characteristics are not favorable for the Moderate Resolution Imaging Spectroradiometer (MODIS) algorithms designed for retrieval of aerosols over dark land or open-ocean surfaces. Using data collected from 62 coastal stations worldwide from the Aerosol Robotic Network (AERONET) from approximately 2002-2010, accuracy assessments are made for coastal aerosol optical depth (AOD) retrieved from MODIS aboard Aqua satellite. It is found that coastal AODs (at 550 nm) characterized respectively by the MODIS Dark Land (hereafter Land) surface algorithm, the Open-Ocean (hereafter Ocean) algorithm, and AERONET all exhibit a log-normal distribution. After filtering by quality flags, the MODIS AODs respectively retrieved from the Land and Ocean algorithms are highly correlated with AERONET (with R(sup 2) is approximately equal to 0.8), but only the Land algorithm AODs fall within the expected error envelope greater than 66% of the time. Furthermore, the MODIS AODs from the Land algorithm, Ocean algorithm, and combined Land and Ocean product show statistically significant discrepancies from their respective counterparts from AERONET in terms of mean, probability density function, and cumulative density function, which suggest a need for future improvement in retrieval algorithms. Without filtering with quality flag, the MODIS Land and Ocean AOD dataset can be degraded by 30-50% in terms of mean bias. Overall, the MODIS Ocean algorithm overestimates the AERONET coastal AOD by 0.021 for AOD less than 0.25 and underestimates it by 0.029 for AOD greater than 0.25. This dichotomy is shown to be related to the ocean surface wind speed and cloud contamination effects on the satellite aerosol retrieval. The Modern Era Retrospective-Analysis for Research and Applications (MERRA) reveals that wind speeds over the global coastal region 25 (with a mean and median value of 2.94 meters per second and 2.66 meters per second, respectively) are often slower than 6 meters per second assumed in the MODIS Ocean algorithm. As a result of high correlation (R(sup 2) greater than 0.98) between the bias in binned MODIS AOD and the corresponding binned wind speed over the coastal sea surface, an empirical scheme for correcting the bias of AOD retrieved from the MODIS Ocean algorithm is formulated and is shown to be effective over the majority of the coastal AERONET stations, and hence can be used in future analysis of AOD trend and MODIS AOD data assimilation.

Anderson, J. C.↗