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NASA NTRS2003

Derivation of Aerosol Columnar Mass from MODIS Optical Depth

In order to verify performance, aerosol transport models (ATM) compare aerosol columnar mass (ACM) with those derived from satellite measurements. The comparison is inherently indirect since satellites derive optical depths and they use a proportionality constant to derive the ACM. Analogously, ATMs output a four dimensional ACM distribution and the optical depth is linearly derived. In both cases, the proportionality constant requires a direct intervention of the user by prescribing the aerosol composition and size distribution. This study introduces a method that minimizes the direct user intervention by making use of the new aerosol products of MODIS. A parameterization is introduced for the derivation of columnar aerosol mass (AMC) and CCN concentration (CCNC) and comparisons between sunphotometer, MODIS Airborne Simulator (MAS) and in-measurements are shown. The method still relies on the scaling between AMC and optical depth but the proportionality constant is dependent on the MODIS derived r$_{eff}$,\eta (contribution of the accumulation mode radiance to the total radiance), ambient RH and an assumed constant aerosol composition. The CCNC is derived fkom a recent parameterization of CCNC as a function of the retrieved aerosol volume. By comparing with in-situ data (ACE-2 and TARFOX campaigns), it is shown that retrievals in dry ambient conditions (dust) are improved when using a proportionality constant dependent on r$ {eff}$ and \eta derived in the same pixel. In high humidity environments, the improvement inthe new method is inconclusive because of the difficulty in accounting for the uneven vertical distribution of relative humidity. Additionally, two detailed comparisons of AMC and CCNC retrieved by the MAS algorithm and the new method are shown. The new method and MAS retrievals of AMC are within the same order of magnitude with respect to the in-situ measurements of aerosol mass. However, the proposed method is closer to the in-situ measurements than the MODIS retrievals. The retrievals of CCNC are also within the same order of magnitude for both methods. The new method is applied to an actual MODIS retrieval and although no in-situ data is available to compare, it is shown that the proposed method yields more credible values than the MODIS retrievals. In addition, recent data available from the PRIDE (Puerto Rico Dust Experiment, July 2000) will be shown by comparing sunphotometer, MODIS and in-situ data.

Gasso, Santiago↗
NASA NTRS2002

Towards Improved MODIS Aerosol Retrieval over the US East Coast Region: Re-examining the Aerosol Model and Surface Assumptions

The MODerate resolution Imaging Spectrometer (MODIS) aboard the Terra and recently the Aqua platform, produces a set of aerosol products over both ocean and land regions. Previous validation efforts have shown that from a global perspective, aerosol optical depth (AOD) is successfully retrieved from MODIS. Even over coastal regions, the over- land and over-ocean retrievals are consistent with each other, and well matched with ground-based sunphotometer measurements (such as AERONET). However, the East Coast of the United States is one region where there is consistently a discrepancy between land and ocean retrievals. Over the ocean, MODIS AODs are consistent with coastal sunphotometer measurements, but over land, AODs are consistently over- estimated. In this study we use field data from the Chesapeake Lighthouse and Aircraft Measurements for Satellites experiment (CLAMS), (held during summer 2001) to determine the aerosol properties at a number of sites. Using the 6-S radiative transfer package, we compute simulated satellite radiances and compare them with observed MODIS radiances. We believe that the AOD over-estimation is not likely due to an incorrect choice of the urban/industrial aerosol models. Using 6-S to do an atmospheric correction for a very low AOD case, we show rather, that the discrepancies are likely a result of incorrect assumptions about the surface reflectance properties. Understanding and improving MODIS retrievals over the East Coast will not only improve the global quality of MODIS, but also would enable the use of MODIS as a tool for monitoring regional aerosol events.

Levy, R. C.↗
NASA NTRS2003

Ocean Primary Production Estimates from Terra MODIS and Their Dependency on Satellite Chlorophyll Alpha Algorithms

Simplistic models relating global satellite ocean color, temperature, and light to ocean net primary production (ONPP) are sensitive to the accuracy and limitations of the satellite estimate of chlorophyll and other input fields, as well as the primary productivity model. The standard MODIS ONPP product uses the new semi-analytic chlorophyll algorithm as its input for two ONPP indexes. The three primary MODIS chlorophyll Q estimates from MODIS, as well as the SeaWiFS 4 chlorophyll product, were used to assess global and regional performance in estimating ONPP for the full mission, but concentrating on 2001. The two standard ONPP algorithms were examined with 8-day and 39 kilometer resolution to quantify chlorophyll algorithm dependency of ONPP. Ancillary data (MLD from FNMOC, MODIS SSTD1, and PAR from the GSFC DAO) were identical. The standard MODIS ONPP estimates for annual production in 2001 was 59 and 58 GT C for the two ONPP algorithms. Differences in ONPP using alternate chlorophylls were on the order of 10% for global annual ONPP, but ranged to 100% regionally. On all scales the differences in ONPP were smaller between MODIS and SeaWiFS than between ONPP models, or among chlorophyll algorithms within MODIS. Largest regional ONPP differences were found in the Southern Ocean (SO). In the SO, application of the semi-analytic chlorophyll resulted in not only a magnitude difference in ONPP (2x), but also a temporal shift in the time of maximum production compared to empirical algorithms when summed over standard oceanic areas. The resulting increase in global ONPP (6-7 GT) is supported by better performance of the semi-analytic chlorophyll in the SO and other high chlorophyll regions. The differences are significant in terms of understanding regional differences and dynamics of ocean carbon transformations.

Essias, Wayne E.↗
NASA NTRS2007

Impact of MODIS High-Resolution Sea-Surface Temperatures on WRF Forecasts at NWS Miami, FL

Over the past few years,studies at the Short-term Prediction Research and Transition (SPoRT) Center have suggested that the use of Moderate Resolution Imaging Spectroradiometer (MODIS) composite sea-surface temperature (SST) products in regional weather forecast models can have a significant positive impact on short-term numerical weather prediction in coastal regions. The recent paper by LaCasse et al. (2007, Monthly Weather Review) highlights lower atmospheric differences in regional numerical simulations over the Florida offshore waters using 2-km SST composites derived from the MODIS instrument aboard the polar-orbiting Aqua and Terra Earth Observing System satellites. To help quantify the value of this impact on NWS Weather Forecast Offices (WFOs), the SPoRT Center and the NWS WFO at Miami, FL (MIA) are collaborating on a project to investigate the impact of using the high-resolution MODIS SST fields within the Weather Research and Forecasting (WRF) prediction system. The scientific hypothesis being tested is: More accurate specification of the lower-boundary forcing within WRF will result in improved land/sea fluxes and hence, more accurate evolution of coastal mesoscale circulations and the associated sensible weather elements. The NWS MIA is currently running the WRF system in real-time to support daily forecast operations, using the National Centers for Environmental Prediction Nonhydrostatic Mesoscale Model dynamical core within the NWS Science and Training Resource Center's Environmental Modeling System (EMS) software; The EMS is a standalone modeling system capable of downloading the necessary daily datasets, and initializing, running and displaying WRF forecasts in the NWS Advanced Weather Interactive Processing System (AWIPS) with little intervention required by forecasters. Twenty-seven hour forecasts are run daily with start times of 0300,0900, 1500, and 2100 UTC on a domain with 4-km grid spacing covering the southern half of Florida and the far western portions of the Bahamas, the Florida Keys, the Straights of Florida, and adjacent waters of the Gulf of Mexico and Atlantic Ocean. Each model run is initialized using the Local Analysis and Prediction System (LAPS) analyses available in AWIPS, invoking the diabatic. "hot-start" capability. In this WRF model "hot-start", the LAPS-analyzed cloud and precipitation features are converted into model microphysics fields with enhanced vertical velocity profiles, effectively reducing the model spin-up time required to predict precipitation systems. The SSTs are initialized with the NCEP Real-Time Global (RTG) analyses at l/12 degree resolution (approx. 9 km); however, the RTG product does not exhibit fine-scale details consistent with its grid resolution. SPoRT is conducting parallel WRF EMS runs identical to the operational runs at NWS MIA in every respect except for the use of MODIS SST composites in place of the RTG product as the initial and boundary conditions over water. The MODIS SST composites for initializing the SPoRT WRF runs are generated on a 2-km grid four times daily at 0400, 0700, 1600, and 1900 UTC, based on the times of the overhead passes of the Aqua and Terra satellites. The incorporation of the MODIS SST composites into the SPoRTWRF runs is staggered such that the 0400UTC composite initializes the 0900 UTC WRF, the 0700 UTC composite initializes the 1500 UTC WRF, the 1600 UTC composite initializes the 2100 UTC WRF, and the 1900 UTC composite initializes the 0300 UTC WRF. A comparison of the SPoRT and Miami forecasts is underway in 2007, and includes quantitative verification of near-surface temperature, dewpoint, and wind forecasts at surface observation locations. In addition, particular days of interest are being analyzed to determine the impact of the MODIS SST data on the development and evolution of predicted sea/land-breeze circulations, clouds, and precipitation. This paper will present verification results comparing the NWS MIA forecasts the SPoRT experimental WRF forecasts, and highlight any substantial differences noted in the predicted mesoscale phenomena.

Case, Jonathan L.↗
NASA NTRS2008

On-Orbit Noise Characterization for MODIS Reflective Solar Bands

Since launch, the Moderate Resolution Imaging Spectroradiometer (MODIS) has operated successfully on-board the NASA Earth Observing System (EOS) Terra and EOS Aqua spacecraft. MODIS is a passive cross-track scanning radiometer that makes observations in 36 spectral bands with spectral wavelengths from visible (VIS) to long-wave infrared. MODIS bands 1-19 and 26 are the reflective solar bands (RSB) with wavelengths from 0.41 to 2.2 micrometers. They are calibrated on-orbit using an on-board solar diffuser (SD) and a SD stability monitor (SDSM) system. For MODIS RSB, the level 1B calibration algorithm produces top of the atmosphere reflectance factors and radiances for every pixel of the Earth view. The sensor radiometric calibration accuracy, specified at each spectral band's typical scene radiance, is 2% for the RSB reflectance factors and 5% for the RSB radiances. Also specified at the typical scene radiance is the detector signal-to-noise ratio (SNR), a key sensor performance parameter that directly impacts its radiometric calibration accuracy and stability, as well as the image quality. This paper describes an on-orbit SNR characterization approach developed to evaluate and track MODIS RSB detector performance. In order to perform on-orbit SNR characterization, MODIS RSB detector responses to the solar illumination reflected from the SD panel must be corrected for factors due to variations of the solar angles and the SD bi-directional reflectance factor. This approach enables RSB SNR characterization to be performed at different response levels for each detector. On-orbit results show that both Terra and Aqua MODIS RSB detectors have performed well since launch. Except for a few noisy or inoperable detectors which were identified pre-launch, most RSB detectors continue to meet the SNR design requirements and are able to maintain satisfactory short-term stability. A comparison of on-orbit noise characterization results with results derived from pre-launch calibration and characterization are also provided.

Xiong, X.↗
NASA NTRS2007

Characterization of MODIS Solar Diffuser On-orbit Degradation

MODIS reflective solar bands (RSB) are calibrated on-orbit by a solar diffuser (SD) and a solar diffuser stability monitor (SDSM). The SD bi-directional reflectance factor (BRF) was characterized pre-launch by the instrument vendor using reference samples traceable to NIST reflectance standards. Its on-orbit degradation is regularly monitored by the SDSM. It consists of a solar integration sphere (SIS) with 9 filtered detectors with wavelengths ranging from 0.41 to 0.94 micrometer, a rotating mirror assembly, and an electronics module. During each SD/SDSM calibration, the SDSM views the sunlight directly and the sunlight diffusely reflected from the SD panel. The time series of SDSM measurements (ratio of the SD view response to the Sun view response) is used to compute the SD BRF degradation at each SDSM detector wavelength. Since launch Terra MODIS has operated for more than seven years and Aqua for nearly five years. The SD panel on each MODIS instrument has experienced noticeable degradation with the largest changes observed in the VIS spectral region. Following a brief description of the MODIS RSB calibration methodology and SD/SDSM operational activities, this paper illustrates the SD on-orbit degradation results for both Terra and Aqua MODIS. It discusses the impacts on the SD RF degradation due to sensor operational conditions and SD solar exposure time. For Aqua MODIS, operated under the same conditions, the SD annual degradation rate is approximately 2.9% at 0.41 micrometers, 1.6% at 0.47 micrometers, and less than 1.1% at wavelengths above 0.53 micrometers. For Terra MODIS, however, an SD door (SDD) related anomaly in May 2003 had led to a decision to keep the SDD permanently at its open position. Since then its SD has experienced a much faster SD degradation rate.

Xiong, X.↗
NASA NTRS2010

Results and Lessons from a Decade of Terra MODIS On-Orbit Spectral Characterization

Since its launch in December 1999, the NASA EOS Terra MODIS has successfully operated for more than a decade. MODIS makes observations in 36 spectral bands from visible (VIS) to longwave infrared (LWIR) and at three nadir spatial resolutions: 250m (2 bands), 500m (5 bands), and 1km (29 bands). In addition to its on-board calibrators designed for the radiometric calibration, MODIS was built with a unique device, called the spectro-radiometric calibration assembly (SRCA). It can be configured in three different modes: radiometric, spatial, and spectral. When it is operated in the spectral modes, the SRCA can monitor changes in Sensor spectral performance for the VIS and near-infrared (NIR) spectral bands. For more than 10 years, the SRCA operation has continued to provide valuable information for MODIS on-orbit spectral performance. This paper briefly describes SRCA on-orbit operation and calibration activities; it presents decade-long spectral characterization results for Terra MODIS VIS and NIR spectral bands in terms of chances in their center wavelengths (CW) and bandwidths (BW). It is shown that the SRCA on-orbit wavelength calibration capability remains satisfactory. For most spectral bands, the changes in CW and BW are less than 0.5 and 1 nm, respectively. Results and lessons from Terra MODIS on-orbit spectral characterization have and will continue to benefit its successor, Aqua MODIS, and other future missions.

Xiong, X.↗
NASA NTRS2011

Reconciling Simulated and Observed Views of Clouds: MODIS, ISCCP, and the Limits or Instrument Simulators

The properties of clouds that may be observed by satellite instruments, such as optical depth and cloud top pressure, are only loosely related to the way clouds m-e represented in models of the atmosphere. One way to bridge this gap is through "instrument simulators," diagnostic tools that map the model representation to synthetic observations so that differences between simulator output and observations can be interpreted unambiguously as model error. But simulators may themselves be restricted by limited information available from the host model or by internal assumptions. This paper considers the extent to which instrument simulators are able to capture essential differences between MODIS and ISCCP, two similar but independent estimates of cloud properties. The authors review the measurements and algorithms underlying these two cloud climatologies, introduce a MODIS simulator, and detail data sets developed for comparison with global models using ISCCP and MODIS simulators, In nature MODIS observes less mid-level doudines!> than ISCCP, consistent with the different methods used to determine cloud top pressure; aspects of this difference are reproduced by the simulators running in a climate modeL But stark differences between MODIS and ISCCP observations of total cloudiness and the distribution of cloud optical thickness can be traced to different approaches to marginal pixels, which MODIS excludes and ISCCP treats as homogeneous. These pixels, which likely contain broken clouds, cover about 15 k of the planet and contain almost all of the optically thinnest clouds observed by either instrument. Instrument simulators can not reproduce these differences because the host model does not consider unresolved spatial scales and so can not produce broken pixels. Nonetheless, MODIS and ISCCP observation are consistent for all but the optically-thinnest clouds, and models can be robustly evaluated using instrument simulators by excluding ambiguous observations.

Ackerman, Steven A.↗
NASA NTRS2011

Evaluation of Detector-to-Detector and Mirror Side Differences for Terra MODIS Reflective Solar Bands Using Simultaneous MISR Observations

The Moderate Resolution Imaging Spectroradiometer (MODIS) is one of the five Earth-observing instruments on-board the National Aeronautics and Space Administration (NASA) Earth-Observing System(EOS) Terra spacecraft, launched in December 1999. It has 36 spectral bands with wavelengths ranging from 0.41 to 14.4 mm and collects data at three nadir spatial resolutions: 0.25 km for 2 bands with 40 detectors each, 0.5 km for 5 bands with 20 detectors each and 1 km for the remaining 29 bands with 10 detectors each. MODIS bands are located on four separate focal plane assemblies (FPAs) according to their spectral wavelengths and aligned in the cross-track direction. Detectors of each spectral band are aligned in the along-track direction. MODIS makes observations using a two-sided paddle-wheel scan mirror. Its on-board calibrators (OBCs) for the reflective solar bands (RSBs) include a solar diffuser (SD), a solar diffuser stability monitor (SDSM) and a spectral-radiometric calibration assembly (SRCA). Calibration is performed for each band, detector, sub-sample (for sub-kilometer resolution bands) and mirror side. In this study, a ratio approach is applied to MODIS observed Earth scene reflectances to track the detector-to-detector and mirror side differences. Simultaneous observed reflectances from the Multi-angle Imaging Spectroradiometer (MISR), also onboard the Terra spacecraft, are used with MODIS observed reflectances in this ratio approach for four closely matched spectral bands. Results show that the detector-to-detector difference between two adjacent detectors within each spectral band is typically less than 0.2% and, depending on the wavelengths, the maximum difference among all detectors varies from 0.5% to 0.8%. The mirror side differences are found to be very small for all bands except for band 3 at 0.44 mm. This is the band with the shortest wavelength among the selected matching bands, showing a time-dependent increase for the mirror side difference. This study is part of the effort by the MODIS Characterization Support Team (MCST) in order to track the RSB on-orbit performance for MODIS collection 5 data products. To support MCST efforts for future data re-processing, this analysis will be extended to include more spectral bands and temporal coverage.

Wu, Aisheng↗
NASA NTRS2012

Role of MODIS Vegetation Phenology Products in the ForWarn System for Monitoring of Forest Disturbances in the Conterminous United States

This presentation discusses MODIS vegetation phenology products used in the ForWarn Early Warning System (EWS) tool for near real time regional forest disturbance detection and surveillance at regional to national scales. The ForWarn EWS is being developed by the USDA Forest Service NASA, ORNL, and USGS to aid federal and state forest health management activities. ForWarn employs multiple historical land surface phenology products that are derived from MODIS MOD13 Normalized Difference Vegetation Index (NDVI) data. The latter is temporally processed into phenology products with the Time Series Product Tool (TSPT) and the Phenological Parameter Estimation Tool (PPET) software produced at NASA Stennis Space Center. TSPT is used to effectively noise reduce, fuse, and void interpolate MODIS NDVI data. PPET employs TSPT-processed NDVI time series data as an input, outputting multiple vegetation phenology products at a 232 meter resolution for 2000 to 2011, including NDVI magnitude and day of year products for seven key points along the growing season (peak of growing season and the minima, 20%, and 80% of the peak NDVI for both the left and right side of growing season), cumulative NDVI integral products for the most active part of the growing season and sequentially across the growing season at 8 day intervals, and maximum value NDVI products composited at 24 day intervals in which each product date has 8 days of overlap between the previous and following product dates. MODIS NDVI phenology products are also used to compute nationwide NRT forest change products refreshed every 8 days. These include percent change in forest NDVI products that compare the current NDVI from USGS eMODIS products to historical MODIS MOD13 NDVI. For each date, three forest change products are produced using three different maximum value NDVI baselines (from the previous year, three previous years, and all previous years). All change products are output with a rainbow color table in which forests with the most severe NDVI decreases are assigned hot colors (yellow to red) and forests with prominent NDVI increases are assigned cold colors (blue tones). All mentioned products have been integrated as data layers into ForWarn s geospatial data viewer known as the U.S. Forest Change Assessment Viewer (FCAV). The latter is used to view and assess the context of the mentioned forest change products with respect to ancillary data layers, such as land cover, elevation, hydrologic features, climatic data, storm data, aerial disturbance surveys, fire data, and land ownership. The FCAV also includes a temporal NDVI profiler for viewing phenological change in multi-year NDVI associated with known or suspected regionally apparent forest disturbances (e.g., from fire and insects). ForWarn forest change products have been used to detect, track, and assess several biotic and abiotic regional forest disturbance events across the country, including ephemeral and longer lasting damage from storms, drought, and insects. Such change products are most effective for viewing severe disturbances affecting multiple MODIS pixels. MODIS vegetation phenology products contribute vital current information on forest conditions to the ForWarn system and this role is expected to grow as these products are refined and derivative products are added.

Spruce, Joseph P.↗
NASA NTRS2012

Multi-Angle Implementation of Atmospheric Correction for MODIS (MAIAC). Part 3: Atmospheric Correction

This paper describes the atmospheric correction (AC) component of the Multi-Angle Implementation of Atmospheric Correction algorithm (MAIAC) which introduces a new way to compute parameters of the Ross-Thick Li-Sparse (RTLS) Bi-directional reflectance distribution function (BRDF), spectral surface albedo and bidirectional reflectance factors (BRF) from satellite measurements obtained by the Moderate Resolution Imaging Spectroradiometer (MODIS). MAIAC uses a time series and spatial analysis for cloud detection, aerosol retrievals and atmospheric correction. It implements a moving window of up to 16 days of MODIS data gridded to 1 km resolution in a selected projection. The RTLS parameters are computed directly by fitting the cloud-free MODIS top of atmosphere (TOA) reflectance data stored in the processing queue. The RTLS retrieval is applied when the land surface is stable or changes slowly. In case of rapid or large magnitude change (as for instance caused by disturbance), MAIAC follows the MODIS operational BRDF/albedo algorithm and uses a scaling approach where the BRDF shape is assumed stable but its magnitude is adjusted based on the latest single measurement. To assess the stability of the surface, MAIAC features a change detection algorithm which analyzes relative change of reflectance in the Red and NIR bands during the accumulation period. To adjust for the reflectance variability with the sun-observer geometry and allow comparison among different days (view geometries), the BRFs are normalized to the fixed view geometry using the RTLS model. An empirical analysis of MODIS data suggests that the RTLS inversion remains robust when the relative change of geometry-normalized reflectance stays below 15%. This first of two papers introduces the algorithm, a second, companion paper illustrates its potential by analyzing MODIS data over a tropical rainforest and assessing errors and uncertainties of MAIAC compared to conventional MODIS products.

Lyapustin, A.↗
NASA NTRS2012

Tropical Atlantic Dust and Smoke Aerosol Variabilities Related to the Madden-Julian Oscillation in MODIS and MISR Observations

In this study, MODIS fine mode fraction and MISR non-spherical fraction are 2used to derive dust and smoke AOT components (tau(sub dust) and tau(sub smoke)) over the tropical Atlantic, and their variabilities related to the Madden-Julian Oscillation (MJO) are then investigated. Both MODIS and MISR show a very similar dust and smoke winter climatology. tau(sub dust) is found to be the dominant aerosol component over the tropical Atlantic while tau(sub smoke) is significantly smaller than tau(sub dust). The daily MODIS and MISR tau(sub dust) are overall highly correlated, with the correlation coefficients typically about 0.7 over the North Atlantic. The consistency between the MODIS and MISR dust and smoke aerosol climatology and daily variations give us confidence to use these two data sets to investigate their relative contributions to the total AOT variation associated with the MJO. However, unlike the MISR dust discrimination, which is based on particle shape retrievals, the smoke discrimination is less certain, based on assumed partitioning of maritime aerosol for both MISR and MODIS. The temporal evolution and spatial patterns of the tau(sub dust) anomalies associated with the MJO are consistent between MODIS and MISR. The tau(sub dust) anomalies are very similar to those of tau anomalies, and are of comparable magnitude. In contrast, the MJO-related tau(sub smoke) anomalies are rather small, and the tau(sub mar) anomalies are negligible. The consistency between the MODIS and MISR results suggests that dust aerosol is the dominant component on the intra-seasonal time scale over the tropical Atlantic Ocean.

Guo, Yanjuan↗
NASA NTRS2016

Inter-Comparison of S-NPP VIIRS and Aqua MODIS Thermal Emissive Bands Using Hyperspectral Infrared Sounder Measurements as a Transfer Reference

This paper compares the calibration consistency of the spectrally-matched thermal emissive bands (TEB) between the Suomi National Polar-orbiting Partnership (S-NPP) Visible Infrared Imaging Radiometer Suite (VIIRS) and the Aqua Moderate Resolution Imaging Spectroradiometer (MODIS), using observations from their simultaneous nadir overpasses (SNO). Nearly-simultaneous hyperspectral measurements from the Aqua Atmospheric Infrared Sounder(AIRS) and the S-NPP Cross-track Infrared Sounder (CrIS) are used to account for existing spectral response differences between MODIS and VIIRS TEB. The comparison uses VIIRS Sensor Data Records (SDR) in MODIS five-minute granule format provided by the NASA Land Product and Evaluation and Test Element (PEATE) and Aqua MODIS Collection 6 Level 1 B (L1B) products. Each AIRS footprint of 13.5 km (or CrIS field of view of 14 km) is co-located with multiple MODIS (or VIIRS) pixels. The corresponding AIRS- and CrIS-simulated MODIS and VIIRS radiances are derived by convolutions based on sensor-dependent relative spectral response (RSR) functions. The VIIRS and MODIS TEB calibration consistency is evaluated and the two sensors agreed within 0.2 K in brightness temperature.Additional factors affecting the comparison such as geolocation and atmospheric water vapor content are also discussed in this paper.

Li, Yonghong↗
NASA NTRS2016

Sixteen Years of Terra MODIS On-Orbit Operation, Calibration, and Performance

Terra MODIS has successfully operated for more than 16 years since its launch in December 1999. From its observations, many science data products have been generated in support of a broad range of research activities and remote sensing applications. Terra MODIS has operated in a number of configurations and experienced a few anomalies, including spacecraft and instrument related events. MODIS collects data in 36 spectral bands that are calibrated regularly by a set of on-board calibrators for their radiometric, spectral, and spatial performance. Periodic lunar observations and long-term radiometric trending over well-characterized ground targets are also used to support sensor on-orbit calibration. Dedicated efforts made by the MODIS Characterization Support Team (MCST) and continuing support from the MODIS Science Team have contributed to the mission success, enabling well-calibrated data products to be continuously generated and routinely delivered to users worldwide. This paper presents an overview of Terra MODIS mission operations, calibration activities, and instrument performance of the past 16 years. It illustrates and describes the results of key sensor performance parameters derived from on-orbit calibration and characterization, such as signal-to-noise ratio (SNR), noise equivalent temperature difference (NEdT), solar diffuser (SD) degradation, changes in sensor responses, center wavelengths, and band-to-band registration (BBR). Also discussed in this paper are the calibration approaches and strategies developed and implemented in support of MODIS Level 1B data production and re-processing, major challenging issues, and lessons learned. (2016) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.

Xiong, X.↗
NASA NTRSDate not supplied

Short Time Scale Stability Monitoring of GOES-16 Visible Channels by Utilizing Daily Inter-Calibration Events with both VIIRS and MODIS Sensors

The CERES project relies on MODIS, VIIRS and geostationary (GEO) imager retrieved cloud properties to compute surface fluxes and convert CERES and GEO radiances into TOA fluxes. The CERES TOA and surface fluxes need to be of climate quality and any anomaly or discontinuity in the calibration of the MODIS, VIIRS, GEO radiances need to be mitigated or avoided. Due to the nature of the CERES instrument calibration, there is a lag time of 3 months before the processing of the CERES product. This allows the CERES team to investigate any unforeseen problems in the input datasets or GEO calibration discontinuities or anomalies before processing. The CERES geostationary imager calibration team is developing a daily monitoring system of GEO, MODIS and VIIRS visible channel radiances in order to detect any day to day discontinuities as part of the CERES/GEO coincident ray-matching calibration efforts. a GEO discontinuity can be detected using two MODIS and 2 VIIRS sensors simultaneously, thus increasing the sampling greatly over a single GEO/LEO radiance pairs. This method is being automated and has already detected three erroneous radiometric calibration events, which were verified with the GOES-16 event log page. One advantage of daily monitoring is that the time period needed to verify calibration drifts is reduced and the confidence to detect even smaller magnitudes of the calibration drift is increased over monthly monitoring. By utilizing Terra and Aqua MODIS and NPP and NOAA20 VIIRS imagers to inter-calibrate GOES-16, the GOES-16 calibration can be referenced to anyone of these imagers. If the CERES project transitions between the Aqua-MODIS imager to the NOAA20 VIIRS imager, the NOAA-20 VIIRS imager can be radiometrically scale to Aqua-MODIS calibration, thus avoiding a GOES-16 calibration discontinuity.

David Robert Doelling↗
NASA NTRS2012

View Angle Effects on MODIS Snow Mapping in Forests

Binary snow maps and fractional snow cover data are provided routinely from MODIS (Moderate Resolution Imaging Spectroradiometer). This paper investigates how the wide observation angles of MODIS influence the current snow mapping algorithm in forested areas. Theoretical modeling results indicate that large view zenith angles (VZA) can lead to underestimation of fractional snow cover (FSC) by reducing the amount of the ground surface that is viewable through forest canopies, and by increasing uncertainties during the gridding of MODIS data. At the end of the MODIS scan line, the total modeled error can be as much as 50% for FSC. Empirical analysis of MODIS/Terra snow products in four forest sites shows high fluctuation in FSC estimates on consecutive days. In addition, the normalized difference snow index (NDSI) values, which are the primary input to the MODIS snow mapping algorithms, decrease as VZA increases at the site level. At the pixel level, NDSI values have higher variances, and are correlated with the normalized difference vegetation index (NDVI) in snow covered forests. These findings are consistent with our modeled results, and imply that consideration of view angle effects could improve MODIS snow monitoring in forested areas.

MODIS↗
NASA NTRS2015

Effect of MODIS Terra Radiometric Calibration Improvements on Collection 6 Deep Blue Aerosol Products: Validation and Terra/Aqua Consistency

The Deep Blue (DB) algorithm's primary data product is midvisible aerosol optical depth (AOD). DB applied to Moderate Resolution Imaging Spectroradiometer (MODIS) measurements provides a data record since early 2000 for MODIS Terra and mid-2002 for MODIS Aqua. In the previous data version (Collection 5, C5), DB production from Terra was halted in 2007 due to sensor degradation; the new Collection 6 (C6) has both improved science algorithms and sensor radiometric calibration. This includes additional calibration corrections developed by the Ocean Biology Processing Group to address MODIS Terra's gain, polarization sensitivity, and detector response versus scan angle, meaning DB can now be applied to the whole Terra record. Through validation with Aerosol Robotic Network (AERONET) data, it is shown that the C6 DB Terra AOD quality is stable throughout the mission to date. Compared to the C5 calibration, in recent years the RMS error compared to AERONET is smaller by approximately 0.04 over bright (e.g., desert) and approximately 0.01-0.02 over darker (e.g., vegetated) land surfaces, and the fraction of points in agreement with AERONET within expected retrieval uncertainty higher by approximately 10% and approximately 5%, respectively. Comparisons to the Aqua C6 time series reveal a high level of correspondence between the two MODIS DB data records, with a small positive (Terra-Aqua) average AOD offset <0.01. The analysis demonstrates both the efficacy of the new radiometric calibration efforts and that the C6 MODIS Terra DB AOD data remain stable (to better than 0.01 AOD) throughout the mission to date, suitable for quantitative scientific analyses.

Collection 6 Deep Blue↗
NASA NTRS2014

Status of Terra MODIS Operation, Calibration, and Performance

Since launch in December 1999, Terra MODIS has successfully operated for nearly 15 years, making continuous observations. Data products derived from MODIS observations have significantly contributed to a wide range of studies of key geophysical parameters of the earth's eco-system of land, ocean, and atmosphere, and their changes over time. The quality of MODIS data products relies on the dedicated effort to monitor and sustain instrument health and operation, to calibrate and update sensor parameters and properties, and to improve calibration algorithms. MODIS observations are made in 36 spectral bands, covering wavelengths from visible to long-wave infrared. The reflective solar bands (1-19 and 26) are primarily calibrated by a solar diffuser (SD) panel and regularly scheduled lunar observations. The thermal emissive bands (20-25 and 27- 36) calibration is referenced to an on-board blackbody (BB) source. On-orbit changes in the sensor spectral and spatial characteristics are monitored by a spectroradiometric calibration assembly (SRCA). This paper provides an overview of Terra MODIS on-orbit operation and calibration activities and implementation strategies. It presents and summarizes sensor on-orbit performance using nearly 15 years of data from its telemetry, on-board calibrators, and lunar observations. Also discussed in this paper are changes in sensor characteristics, corrections applied to maintain MODIS level 1B (L1B) data quality, and efforts for future improvements.

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