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Spatially Varying Spectrally Thresholds for MODIS Cloud Detection

The EOS science team has developed an elaborate global MODIS cloud detection procedure, and the resulting MODIS product (MOD35) is used in the retrieval process of several geophysical parameters to mask out clouds. While the global application of the cloud detection approach appears quite robust, the product has some shortcomings on the regional scale, often over determining clouds in a variety of settings, particularly at night. This over-determination of clouds can cause a reduction in the spatial coverage of MODIS derived clear-sky products. To minimize this problem, a new regional cloud detection method for use with MODIS data has been developed at NASA's Global Hydrology and Climate Center (GHCC). The approach is similar to that used by the GHCC for GOES data over the continental United States. Several spatially varying thresholds are applied to MODIS spectral data to produce a set of tests for detecting clouds. The thresholds are valid for each MODIS orbital pass, and are derived from 20-day composites of GOES channels with similar wavelengths to MODIS. This paper and accompanying poster will introduce the GHCC MODIS cloud mask, provide some examples, and present some preliminary validation.

Haines, S. L.↗

Improving Access to MODIS Biophysical Science Products for NACP Investigators

MODIS 4 NACP is a NASA-funded project supporting the North American Carbon Program (NACP). The purpose of this Advancing Collaborative Connections for Earth-Sun System Science (ACCESS) project is to provide researchers with Moderate Resolution Imaging Spectroradiometer (MODIS) biophysical data products that are custom tailored for use in NACP model studies. Standard MODIS biophysical products provide used to improve our understanding on the climate and ecosystem changes. However, direct uses of the MODIS biophysical parameters are constrained by retrieval quality and cloud contamination. Another challenge that NACP users face is acquiring MODIS data in formats and at spatial-temporal resolutions consistent with other data sets they use. We have been working closely with key NACP users to tailor the MODIS products to fit their needs. First, we provide new temporally smoothed and spatially continuous MODIS biophysical data sets. Second, we are distributing MODIS data at suitable spatial-temporal resolutions and in formats consistent with other data integration into model studies.

Wolfe, Robert E.↗

Evaluation of Aerosol Properties over Ocean from Moderate Resolution Imaging Spectroradiometer (MODIS) during ACE-Asia

The Aerosol Characterization Experiment-Asia (ACE-Asia) was conducted in March-May 2001 in the western North Pacific in order to characterize the complex mix of dust, smoke, urban/industrial pollution, and background marine aerosol that is observed in that region in springtime. The Moderate Resolution Imaging Spectroradiometer (MODIS) provides a large-scale regional view of the aerosol during the ACE-Asia time period. Focusing only on aerosol retrievals over ocean, MODIS data show latitudinal and longitudinal variation in the aerosol characteristics. Typically, aerosol optical depth (tau(sub a)) values at 0.55 micrometers are highest in the 30 deg. - 50 deg. latitude band associated with dust outbreaks. Monthly mean tau(sub a) in this band ranges approx. 0.40-70, although large differences between monthly mean and median values indicate the periodic nature of these dust outbreaks. The size parameters, fine mode fraction (eta), and effective radius (r(sub eff)) vary between monthly mean values of eta = 0.47 and r(sub eff)= 0.75 micrometers in the cleanest regions far offshore to approximately eta = 0.85 and r(sub eff) =.30 micrometers in near-shore regions dominated by biomass burning smoke. The collocated MODIS retrievals with airborne, ship-based, and ground-based radiometers measurements suggest that MODIS retrievals of spectral optical depth fall well within expected error (DELTA tau(sub a) = plus or minus 0.03 plus or minus 0.05 tau(sub a)) except in situations dominated by dust, in which cases MODIS overestimate both the aerosol loading and the aerosol spectral dependence. Such behavior is consistent with issues related to particle nonsphericity. Comparisons of MODIS-derived r(sub eff) with AERONET retrievals at the few occurrences of collocations show MODIS systematically underestimates particle size by 0.2 micrometers. Multiple-year analysis of MODIS aerosol size parameters suggests systematic differences between the year 2001 and the years 2000 and 2002, which are traced to instrumental electronic cross talk. Sensitivity studies show that such calibration errors are negligible in tau(sub a) retrievals but are more pronounced in size parameter retrievals, especially for dust and sea salt.

Chu, D. A.↗

Assessment of MODIS Scan Mirror Reflectance Changes On-Orbit

Since launch, the NASA EOS Terra and Aqua MODIS have operated successfully for more than 8 and 6 years, respectively. MODIS collects data using a two-sided scan mirror over a large scan angular range. The scan mirror is made of a polished, nickel-plated beryllium base coated with high purity silver, which is then over-coated with the Denton proprietary silicon monoxide and silicon dioxide mixture. The scan mirror's reflectance was characterized pre-launch using its witness samples, and the response versus scan angle was measured at the sensor system level. In this study, we present an assessment of MODIS scan mirror on-orbit degradation by examining changes of spectral band response over each sensor's mission lifetime. Results show that the scan mirror's optical properties for both Terra and Aqua MODIS have experienced significant degradation since launch in the VIS spectral region, which is mirror side dependent as well as scan angle dependent. In general, the mirror degradation is more severe for Terra MODIS than Aqua MODIS, especially during recent years. For Terra MODIS, the degradation rate is noticeably different between the mirror sides. On the other hand, there has been little mirror side dependent difference for Aqua MODIS.

Xiong, Xiaoxiong↗

Mapping Snow Grain Size over Greenland from MODIS

This paper presents a new automatic algorithm to derive optical snow grain size (SGS) at 1 km resolution using Moderate Resolution Imaging Spectroradiometer (MODIS) measurements. Differently from previous approaches, snow grains are not assumed to be spherical but a fractal approach is used to account for their irregular shape. The retrieval is conceptually based on an analytical asymptotic radiative transfer model which predicts spectral bidirectional snow reflectance as a function of the grain size and ice absorption. The analytical form of solution leads to an explicit and fast retrieval algorithm. The time series analysis of derived SGS shows a good sensitivity to snow metamorphism, including melting and snow precipitation events. Preprocessing is performed by a Multi-Angle Implementation of Atmospheric Correction (MAIAC) algorithm, which includes gridding MODIS data to 1 km resolution, water vapor retrieval, cloud masking and an atmospheric correction. MAIAC cloud mask (CM) is a new algorithm based on a time series of gridded MODIS measurements and an image-based rather than pixel-based processing. Extensive processing of MODIS TERRA data over Greenland shows a robust performance of CM algorithm in discrimination of clouds over bright snow and ice. As part of the validation analysis, SGS derived from MODIS over selected sites in 2004 was compared to the microwave brightness temperature measurements of SSM\I radiometer, which is sensitive to the amount of liquid water in the snowpack. The comparison showed a good qualitative agreement, with both datasets detecting two main periods of snowmelt. Additionally, MODIS SGS was compared with predictions of the snow model CROCUS driven by measurements of the automatic whether stations of the Greenland Climate Network. We found that CROCUS grain size is on average a factor of two larger than MODIS-derived SGS. Overall, the agreement between CROCUS and MODIS results was satisfactory, in particular before and during the first melting period in mid-June. Following detailed time series analysis of SGS for four permanent sites, the paper presents SGS maps over the Greenland ice sheet for the March-September period of 2004.

Lyapustin, Alexei↗

Estimate of the Impact of Absorbing Aerosol Over Cloud on the MODIS Retrievals of Cloud Optical Thickness and Effective Radius Using Two Independent Retrievals of Liquid Water Path

Two independent satellite retrievals of cloud liquid water path (LWP) from the NASA Aqua satellite are used to diagnose the impact of absorbing biomass burning aerosol overlaying boundary-layer marine water clouds on the Moderate Resolution Imaging Spectrometer (MODIS) retrievals of cloud optical thickness (tau) and cloud droplet effective radius (r(sub e)). In the MODIS retrieval over oceans, cloud reflectance in the 0.86-micrometer and 2.13-micrometer bands is used to simultaneously retrieve tau and r(sub e). A low bias in the MODIS tau retrieval may result from reductions in the 0.86-micrometer reflectance, which is only very weakly absorbed by clouds, owing to absorption by aerosols in cases where biomass burning aerosols occur above water clouds. MODIS LWP, derived from the product of the retrieved tau and r(sub e), is compared with LWP ocean retrievals from the Advanced Microwave Scanning Radiometer-EOS (AMSR-E), determined from cloud microwave emission that is transparent to aerosols. For the coastal Atlantic southern African region investigated in this study, a systematic difference between AMSR-E and MODIS LWP retrievals is found for stratocumulus clouds over three biomass burning months in 2005 and 2006 that is consistent with above-cloud absorbing aerosols. Biomass burning aerosol is detected using the ultraviolet aerosol index from the Ozone Monitoring Instrument (OMI) on the Aura satellite. The LWP difference (AMSR-E minus MODIS) increases both with increasing tau and increasing OMI aerosol index. During the biomass burning season the mean LWP difference is 14 g per square meters, which is within the 15-20 g per square meter range of estimated uncertainties in instantaneous LWP retrievals. For samples with only low amounts of overlaying smoke (OMI AI less than or equal to 1) the difference is 9.4, suggesting that the impact of smoke aerosols on the mean MODIS LWP is 5.6 g per square meter. Only for scenes with OMI aerosol index greater than 2 does the average LWP difference and the estimated bias in MODIS cloud optical thickness attributable to the impact of overlaying biomass burning aerosol exceed the instantaneous uncertainty in the retrievals.

Wilcox, Eric M.↗

Aqua MODIS Thermal Emissive Band On-Orbit Calibration, Characterization, and Performance

The NASA's Earth Observing System Aqua Moderate Resolution Imaging Spectroradiometer (MODIS) has continued to operate with satisfactory performance since its launch in May 2002, exceeding its nominal six-year design lifetime. Its continuous Earth observations have been used to generate many science data products for studies of the Earth's, system. MODIS has 36 spectral bands; 20 reflective solar bands and 16 thermal emissive bands (TEBs). All TEB observations are made at 1-km nadir spatial resolution with spectral wavelengths from 3.7 to 14.4 pm. Primary applications of MODIS TEB 'include surface, cloud, and atmospheric temperatures, water vapor, and cloud top altitude. MODIS TEB on-orbit calibration uses a quadratic algorithm with its calibration coefficients derived using an onboard blackbody (BB). This paper will present Aqua MODIS TEB on-orbit calibration, characterization, and performance over its six-year mission. Examples of instrument thermal behavior, BB temperature stability, detector short-term stability, and changes in long-term response (or system gain) will be presented. Comparisons will also be made with Terra MODIS, launched in December 1999. On-orbit results show that Aqua MODIS and its focal plane temperatures have behaved normally. BB temperature has remained extremely stable with typical scan -to-scan variations of less than +/-0.15 mK. Most TEB detectors continue to exceed their specified signal-to-noise ratio requirements, exhibiting excellent short-term stability and calibration accuracy. Excluding a few noisy detectors, either identified prelaunch or occurring postlaunch, on-orbit changes in TEB responses have been less than 0.5% on an annual basis. By comparison; the overall Aqua TEB performance has been better than that of Terra MODIS,

Xiong, Xiaoxiong↗

Validation of MODIS Aerosol Optical Depth Retrievals over a Tropical Urban Site, Pune, India

In the present paper, MODIS (Terra and Aqua; level 2, collection 5) derived aerosoloptical depths (AODs) are compared with the ground-based measurements obtained from AERONET (level 2.0) and Microtops - II sun-photometer over a tropical urban station, Pune (18 deg 32'N; 73 deg 49'E, 559 m amsl). This is the first ever systematic validation of the MODIS aerosol products over Pune. Analysis of the data indicates that the Terra and Aqua MODIS AOD retrievals at 550 nm have good correlations with the AERONET and Microtops - II sun-photometer AOD measurements. During winter the linear regression correlation coefficients for MODIS products against AERONET measurements are 0.79 for Terra and 0.62 for Aqua; however for premonsoon, the corresponding coefficients are 0.78 and 0.74. Similarly, the linear regression correlation coefficients for Microtops measurements against MODIS products are 0.72 and 0.93 for Terra and Aqua data respectively during winter and are 0.78 and 0.75 during pre-monsoon. On yearly basis in 2008-2009, correlation coefficients for MODIS products against AERONET measurements are 0.80 and 0.78 for Terra and Aqua respectively while the corresponding coefficients are 0.70 and 0.73 during 2009-2010. The regressed intercepts with MODIS vs. AERONET are 0.09 for Terra and 0.05 for Aqua during winter whereas their values are 0.04 and 0.07 during pre-monsoon. However, MODIS AODs are found to underestimate during winter and overestimate during pre-monsoon with respect to AERONET and Microtops measurements having slopes 0.63 (Terra) and 0.74 (Aqua) during winter and 0.97 (Terra) and 0.94 (Aqua) during pre-monsoon. Wavelength dependency of Single Scattering Albedo (SSA) shows presence of absorbing and scattering aerosol particles. For winter, SSA decreases with wavelength with the values 0.86 +/- 0.03 at 440 nm and 0.82 +/- 0.04 at 1020nm. In pre-monsoon, it increases with wavelength (SSA is 0.87 +/- 0.02 at 440nm; and 0.88 +/-0.04 at 1020 nm).

More, Sanjay↗

MODIS Radiometric Calibration and Uncertainty Assessment

Since launch, Terra and Aqua MODIS have collected more than II and 9 years of datasets for comprehensive studies of the Earth's land, ocean, and atmospheric properties. MODIS observations are made in 36 spectral bands: 20 reflective solar bands (RSB) and 16 thermal emissive bands (TEB). Compared to its heritage sensors, MODIS was developed with very stringent calibration and uncertainty requirements. As a result, MODIS was designed and built with a set of state of the art on-board calibrators (OBC), which allow key sensor performance parameters and on-orbit calibration coefficients to be monitored and updated if necessary. In terms of its calibration traceability, MODIS RSB calibration is reflectance based using an on-board solar diffuser (SD) and the TEB calibration is radiance based using an on-board blackbody (BB). In addition to on-orbit calibration coefficients derived from its OBC, calibration parameters determined from sensor pre-launch calibration and characterization are used in both the RSB and TEB calibration and retrieval algorithms. This paper provides a brief description of MODIS calibration methodologies and discusses details of its on-orbit calibration uncertainties. It assesses uncertainty contributions from individual components and differences between Terra and Aqua MODIS due to their design characteristics and on-orbit periormance. Also discussed in this paper is the use of MODIS LIB uncertainty index CUI) product.

Xiong, Xiaoxiong↗

An Enhanced TIMESAT Algorithm for Estimating Vegetation Phenology Metrics from MODIS Data

An enhanced TIMESAT algorithm was developed for retrieving vegetation phenology metrics from 250 m and 500 m spatial resolution Moderate Resolution Imaging Spectroradiometer (MODIS) vegetation indexes (VI) over North America. MODIS VI data were pre-processed using snow-cover and land surface temperature data, and temporally smoothed with the enhanced TIMESAT algorithm. An objective third derivative test was applied to define key phenology dates and retrieve a set of phenology metrics. This algorithm has been applied to two MODIS VIs: Normalized Difference Vegetation Index (NDVI) and Enhanced Vegetation Index (EVI). In this paper, we describe the algorithm and use EVI as an example to compare three sets of TIMESAT algorithm/MODIS VI combinations: a) original TIMESAT algorithm with original MODIS VI, b) original TIMESAT algorithm with pre-processed MODIS VI, and c) enhanced TIMESAT and pre-processed MODIS VI. All retrievals were compared with ground phenology observations, some made available through the National Phenology Network. Our results show that for MODIS data in middle to high latitude regions, snow and land surface temperature information is critical in retrieving phenology metrics from satellite observations. The results also show that the enhanced TIMESAT algorithm can better accommodate growing season start and end dates that vary significantly from year to year. The TIMESAT algorithm improvements contribute to more spatial coverage and more accurate retrievals of the phenology metrics. Among three sets of TIMESAT/MODIS VI combinations, the start of the growing season metric predicted by the enhanced TIMESAT algorithm using pre-processed MODIS VIs has the best associations with ground observed vegetation greenup dates.

Tan, Bin↗

MODIS On-Orbit Calibration and Lessons Learned

The Moderate Resolution Imaging Spectroradiometer (MODIS) is a key instrument for NASA's Earth Observing System (EOS) Terra and Aqua missions. Since launch, Terra and Aqua MODIS have successfully operated for more than 12 and 10 years, respectively, and generated an unprecedented amount of data products for the science and user community over a wide range of applications. MODIS was developed with improved design and stringent calibration requirements over its heritage sensors in order . to extend and enhance their long-term data records. Its follow-on instrument, the Visible/Infrared Imager Radiometer Suite (VIIRS), was launched on-board the Suomi National Polar-orbiting Partnership (NPP) spacecraft October 28, 2011. MODIS collects data in 36 spectral bands, covering wavelengths from 0.41 to 14.S!Jlll, and at 250m, SOOm, and lkm spatial resolutions (nadir). MODIS on-orbit calibration is provided by a set of onboard calibrators (OBC), including a solar diffuser (SO), a solar diffuser stability monitor (SDSM), a blackbody (BB), and a spectroradiometric calibration assembly (SRCA). In addition to the onboard calibrators, regular lunar observations are made by both Terra and Aqua MODIS to track their calibration stability in the reflective solar region. This tutorial session provides an overview of MODIS on-orbit calibration and characterization methodologies. It discusses challenging issues and lessons learned from sensor design, operation, calibration, and inter-comparisons. Examples of instrument on-orbit performance are illustrated with a focus on the improvements made based on various lessons learned. It is expected that MODIS experience and lessons will continue to provide valuable information for future earth observing missions/sensors.

Xiong, Jack↗

Monitoring Land Surface Albedo and Vegetation Dynamics Using High Spatial and Temporal Resolution Synthetic Time Series from Landsat and the MODIS BRDF/NBAR/Albedo Product

Seasonal vegetation phenology can significantly alter surface albedo which in turn affects the global energy balance and the albedo warmingcooling feedbacks that impact climate change. To monitor and quantify the surface dynamics of heterogeneous landscapes, high temporal and spatial resolution synthetic time series of albedo and the enhanced vegetation index (EVI) were generated from the 500-meter Moderate Resolution Imaging Spectroradiometer (MODIS) operational Collection V006 daily BRDF (Bidirectional Reflectance Distribution Function) / NBAR (Nadir BRDF-Adjusted Reflectance) / albedo products and 30-meter Landsat 5 albedo and near-nadir reflectance data through the use of the Spatial and Temporal Adaptive Reflectance Fusion Model (STARFM). The traditional Landsat Albedo (Shuai et al., 2011) makes use of the MODIS BRDFAlbedo products (MCD43) by assigning appropriate BRDFs from coincident MODIS products to each Landsat image to generate a 30-meter Landsat albedo product for that acquisition date. The available cloud free Landsat 5 albedos (due to clouds, generated every 16 days at best) were used in conjunction with the daily MODIS albedos to determine the appropriate 30-meter albedos for the intervening daily time steps in this study. These enhanced daily 30-meter spatial resolution synthetic time series were then used to track albedo and vegetation phenology dynamics over three Ameriflux tower sites (Harvard Forest in 2007, Santa Rita in 2011 and Walker Branch in 2005). These Ameriflux sites were chosen as they are all quite nearby new towers coming on line for the National Ecological Observatory Network (NEON), and thus represent locations which will be served by spatially paired albedo measures in the near future. The availability of data from the NEON towers will greatly expand the sources of tower albedometer data available for evaluation of satellite products. At these three Ameriflux tower sites the synthetic time series of broadband shortwave albedos were evaluated using the tower albedo measurements with a Root Mean Square Error (RMSE) less than 0.013 and a bias within the range of 0.006. These synthetic time series provide much greater spatial detail than the 500 meter gridded MODIS data, especially over more heterogeneous surfaces, which improves the efforts to characterize and monitor the spatial variation across species and communities. The mean of the difference between maximum and minimum synthetic time series of albedo within the MODIS pixels over a subset of satellite data of Harvard Forest (16 kilometers by 14 kilometers) was as high as 0.2 during the snow-covered period and reduced to around 0.1 during the snow-free period. Similarly, we have used STARFM to also couple MODIS Nadir BRDF-Adjusted Reflectances (NBAR) values with Landsat 5 reflectances to generate daily synthetic times series of NBAR and thus Enhanced Vegetation Index (NBAR-EVI) at a 30-meter resolution. While normally STARFM is used with directional reflectances, the use of the view angle corrected daily MODIS NBAR values will provide more consistent time series. These synthetic times series of EVI are shown to capture seasonal vegetation dynamics with finer spatial and temporal details, especially over heterogeneous land surfaces.

Vegetation Index↗

Cross-Calibration of the Oceansat-2 Ocean Colour Monitor (OCM) with Terra and Aqua MODIS

The Ocean Colour Monitor (OCM) sensor on-board the Oceansat-2 spacecraft has been operational since its launch in September, 2009. The Oceansat 2 OCM primary design goal is to provide continuity to Oceansat-1 OCM to obtain information regarding various ocean-colour variables. OCM acquires Earth scene measurements in eight multi-spectral bands in the range from 402 to 885 nm. The MODIS sensor on the Terra and Aqua spacecraft has been successfully operating for over a decade collecting measurements of the earth's land, ocean surface and atmosphere. The MODIS spectral bands, designed for land and ocean applications, cover the spectral range from 412 to 869 nm. This study focuses on comparing the radiometric calibration stability of OCM using near-simultaneous TOA measurements with Terra and Aqua MODIS acquired over the Libya 4 target. Same-day scene-pairs from all three sensors (OCM, Terra and Aqua MODIS) between August, 2014 and September, 2015 were chosen for this analysis. On a given day, the OCM overpass is approximately an hour after the Terra overpass and an hour before the Aqua overpass. Due to the orbital differences between Terra and Aqua, MODIS images the Libya 4 site at different scan-angles on a given day. Some of the high-gain ocean bands for MODIS tend to saturate while viewing the bright Libya 4 target, but bands 8-10 (412 nm - 486 nm) provide an unsaturated response and are used for comparison with the spectrally similar OCM bands. All the standard corrections such as bidirectional reflectance factor (BRDF), relative spectral response mismatch, and impact for atmospheric water-vapor are applied to obtain the reflectance differences between OCM and the two MODIS instruments. Furthermore, OCM is used as a transfer radiometer to obtain the calibration differences between Terra and Aqua MODIS reflective solar bands.

Angal, Amit↗

Evaluation of VIIRS and MODIS Thermal Emissive Band Calibration Stability Using Ground Target

The S-NPP Visible Infrared Imaging Radiometer Suite (VIIRS) instrument, a polar orbiting Earth remote sensing instrument built using a strong MODIS background, employs a similarly designed on-board calibrating source - a V-grooved blackbody for the thermal emissive bands (TEB). The central wavelengths of most VIIRS TEBs are very close to those of MODIS with the exception of the 10.7 micron channel. To ensure the long term continuity of climate data records derived using VIIRS and MODIS TEB, it is necessary to assess any systematic differences between the two instruments, including scenes with temperatures significantly lower than blackbody operating temperatures at approximately 290 K. Previous work performed by the MODIS Characterization Support Team (MCST) at NASAGSFC used the frequent observations of the Dome Concordia site located in Antarctica to evaluate the calibration stability and consistency of Terra and Aqua MODIS over the mission lifetime. The near-surface temperature measurements from an automatic weather station (AWS) provide a direct reference useful for tracking the stability and determining the relative bias between the two MODIS instruments. In this study, the same technique is applied to the VIIRS TEB and the results are compared with those from the matched MODIS TEB. The results of this study show a small negative bias when comparing the matching VIIRS and Aqua MODIS TEB, implying a higher scene temperature retrieval for S-VIIRS at the cold end. Statistically no significant drift is observed for VIIRS TEB performance over the first 3.5 years of the mission.

Madhavan, Sriharsha↗

Calibration of the DSCOVR EPIC Visible and NIR Channels using MODIS Terra and Aqua Data and EPIC Lunar Observations

The unique position of the Deep Space Climate Observatory (DSCOVR) Earth Polychromatic Imaging Camera (EPIC) at the Lagrange 1 point makes an important addition to the data from currently operating low Earth orbit observing instruments. EPIC instrument does not have an onboard calibration facility. One approach to its calibration is to compare EPIC observations to the measurements from polar-orbiting radiometers. Moderate Resolution Imaging Spectroradiometer (MODIS) is a natural choice for such comparison due to its well-established calibration record and wide use in remote sensing. We use MODIS Aqua and Terra L1B 1km reflectances to infer calibration coefficients for four EPIC visible and NIR channels: 443, 551, 680 and 780 nm. MODIS and EPIC measurements made between June 2015 and 2016 are employed for comparison. We first identify favorable MODIS pixels with scattering angle matching temporarily collocated EPIC observations. Each EPIC pixel is then spatially collocated to a subset of the favorable MODIS pixels within 25 km radius. Standard deviation of the selected MODIS pixels as well as of the adjacent EPIC pixels is used to find the most homogeneous scenes. These scenes are then used to determine calibration coefficients using a linear regression between EPIC counts/sec and reflectances in the close MODIS spectral channels. We present thus inferred EPIC calibration coefficients and discuss sources of uncertainties. The lunar EPIC observations are used to calibrate EPIC O2 absorbing channels (688 and 764 nm), assuming that there is a small difference between moon reflectances separated by approx.10 nm in wavelength provided the calibration factors of the red (680 nm) and near-IR (780 nm) are known from comparison between EPIC and MODIS.

Geogdzhayev, Igor V.↗

Improvements in the On-Orbit Response Versus Scan Angle Characterization of the Aqua MODIS Reflective Solar Bands

The Aqua Moderate Resolution Imaging Spectroradiometer (MODIS) has been chosen by the Global Space-based Inter-Calibration System operational community as the reference sensor in cross-sensor calibration. A number of geostationary orbit and low-earth orbit sensors use the 0.64-μm band from Aqua MODIS as a calibration reference. After over 15 years on-orbit, the performance characteristics of the MODIS instrument have changed, with effects evident at short wavelengths. MODIS employs a reflectance-based calibration using the solar diffuser measurements with the monthly lunar observations facilitating a response versus scan angle characterization on-orbit. As the instrument continues to operate beyond its design lifetime of 6 years, the on-board calibrators alone are insufficient to accurately characterize the instrument's response at all scan angles. This results in a long-term reflectance drift, particularly observed in the 0.64- and 0.85-μm bands, while observing the temporally invariant desert sites. Long-term reflectance drifts of up to 2% and 3% are observed at the beginning of scan for the 0.64- and 0.85-μm bands, respectively. An approach using earth-view response to supplement the on-board calibrator measurements has been shown to overcome these inadequacies and is now implemented for the 0.64-, 0.85-, 0.46-, and 0.55-μm land bands of Aqua MODIS. This paper presents the details related to the algorithm implementation and an independent evaluation using the Dome Concordia site and deep-convective clouds. This approach has been reviewed, tested, and approved by the MODIS science team and has been implemented in the forward production of the MODIS L1B Collection 6 starting July 9, 2016. This enhanced approach has also been adopted in the MODIS L1B Collection 6.1 reprocess for the entire mission to facilitate an improved quality of downstream science products. The results with the enhanced approach reduce the reflectance drifts to within 0.5% for most cases.

Angal, Amit↗

Validation of MODIS 3 km Land Aerosol Optical Depth from NASA's EOS Terra and Aqua Missions

In addition to the standard resolution product (10km), the MODerate resolution Imaging Spectroradiometer (MODIS) Collection 6 (C006) data release included a higher resolution (3km). Other than accommodations for the two different resolutions, the 10 and 3km Dark Target (DT) algorithms are basically the same. In this study, we perform global validation of the higher-resolution aerosol optical depth (AOD) over global land by comparing against AErosol RObotic NETwork (AERONET) measurements. The MODIS-AERONET collocated data sets consist of 161410 high-confidence AOD pairs from 2000 to 2015 for Terra MODIS and 2003 to 2015 for Aqua MODIS. We find that 62.5 and 68.4% of AODs retrieved from Terra MODIS and Aqua MODIS, respectively, fall within previously published expected error bounds of +/-(0.05+0.2 × AOD), with a high correlation (R = 0.87). The scatter is not random, but exhibits a mean positive bias of ∼ 0.06 for Terra and ∼ 0.03 for Aqua. These biases for the 3km product are approximately 0.03 larger than the biases found in similar validations of the 10km product. The validation results for the 3km product did not have a relationship to aerosol loading (i.e., true AOD), but did exhibit dependence on quality flags, region, viewing geometry, and aerosol spatial variability. Time series of global MODIS-AERONET differences show that validation is not static, but has changed over the course of both sensors' lifetimes, with Terra MODIS showing more change over time. The likely cause of the change of validation over time is sensor degradation, but changes in the distribution of AERONET stations and differences in the global aerosol system itself could be contributing to the temporal variability of validation.

Gupta, Pawan↗

Evaluating the Calibration of Aqua MODIS Bands 33, 35, and 36 During Blackbody Warm-Up Cool-Down Events

Aqua MODIS is the second MODIS instrument of NASA's Earth Observation System and has operated for over sixteen years since its launch in 2002. MODIS has sixteen thermal emissive bands (TEBs) located on two separate cold focal plane assemblies (CFPA). The TEBs are calibrated every scan using observations of an onboard blackbody (BB) and a space view port. Low saturation temperatures (Tsat) of Aqua MODIS bands 33, 35, and 36 cause these bands to saturate when the BB temperature is higher than their Tsat values during a BB warm-up cool-down (WUCD) cycle, therefore impacting the ability to perform nominal calibration. In addition, starting from around 2006, the CFPA temperature showed gradual variation from its nominally-controlled operating temperature due to a loss of its radiative cooler margin and the magnitude of its fluctuation reaching a maximum in 2013. The MODIS Characterization Support Team currently uses a correction that is dependent on the CFPA temperature to provide a gain estimate for the saturated scans during the BB WUCD. This gain estimation has been implemented in the Aqua MODIS Collection 6 (C6) and C6.1 L1B products. This paper evaluates the quality of the calibrated radiance of Aqua MODIS bands 33, 35, and 36 using simultaneous nadir observations from the Atmospheric Infrared Sounder (AIRS), which is also onboard the Aqua satellite. Our analysis results show that the differences between AIRS and Aqua MODIS can be controlled well within the fluctuation range compared to the periods when the BB signals for these bands are not saturated.

Li, Yonghong↗