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NASA NTRS2017

Overview of NASA's MODIS and Visible Infrared Imaging Radiometer Suite (VIIRS) snow-cover Earth System Data Records

Knowledge of the distribution, extent, duration and timing of snowmelt is critical for characterizing the Earth's climate system and its changes. As a result, snow cover is one of the Global Climate Observing System (GCOS) essential climate variables (ECVs). Consistent, long-term datasets of snow cover are needed to study interannual variability and snow climatology. The NASA snow-cover datasets generated from the Moderate Resolution Imaging Spectroradiometer (MODIS) on the Terra and Aqua spacecraft and the Suomi National Polar-orbiting Partnership (S-NPP) Visible Infrared Imaging Radiometer Suite (VIIRS) are NASA Earth System Data Records (ESDR). The objective of the snow-cover detection algorithms is to optimize the accuracy of mapping snow-cover extent (SCE) and to minimize snow-cover detection errors of omission and commission using automated, globally applied algorithms to produce SCE data products. Advancements in snow-cover mapping have been made with each of the four major reprocessings of the MODIS data record, which extends from 2000 to the present. MODIS Collection 6 (C6) and VIIRS Collection 1 (C1) represent the state-of-the-art global snow cover mapping algorithms and products for NASA Earth science. There were many revisions made in the C6 algorithms which improved snow-cover detection accuracy and information content of the data products. These improvements have also been incorporated into the NASA VIIRS snow cover algorithms for C1. Both information content and usability were improved by including the Normalized Snow Difference Index (NDSI) and a quality assurance (QA) data array of algorithm processing flags in the data product, along with the SCE map.The increased data content allows flexibility in using the datasets for specific regions and end-user applications.Though there are important differences between the MODIS and VIIRS instruments (e.g., the VIIRS 375m native resolution compared to MODIS 500 m), the snow detection algorithms and data products are designed to be as similar as possible so that the 16C year MODIS ESDR of global SCE can be extended into the future with the S-NPP VIIRS snow products and with products from future Joint Polar Satellite System (JPSS) platforms.These NASA datasets are archived and accessible through the NASA Distributed Active Archive Center at the National Snow and Ice Data Center in Boulder, Colorado.

Earth System Data Record↗
NASA NTRS2017

MODIS Retrieval of Aerosol Optical Depth over Turbid Coastal Water

We present a new approach to retrieve Aerosol Optical Depth (AOD) using the Moderate Resolution Imaging Spectroradiometer (MODIS) over the turbid coastal water. This approach supplements the operational Dark Target (DT) aerosol retrieval algorithm that currently does not conduct AOD retrieval in shallow waters that have visible sediments or sea-floor (i.e., Class 2 waters). Over the global coastal water regions in cloud-free conditions, coastal screening leads to approx. 20% unavailability of AOD retrievals. Here, we refine the MODIS DT algorithm by considering that water-leaving radiance at 2.1 microns to be negligible regardless of water turbidity, and therefore the 2.1 microns reflectance at the top of the atmosphere is sensitive to both change of fine-mode and coarse-mode AODs. By assuming that the aerosol single scattering properties over coastal turbid water are similar to those over the adjacent open-ocean pixels, the new algorithm can derive AOD over these shallow waters. The test algorithm yields approx. 18% more MODIS-AERONET collocated pairs for six AERONET stations in the coastal water regions. Furthermore, comparison of the new retrieval with these AERONET observations show that the new AOD retrievals have equivalent or better accuracy than those retrieved by the MODIS operational algorithm's over coastal land and non-turbid coastal water product. Combining the new retrievals with the existing MODIS operational retrievals yields an overall improvement of AOD over those coastal water regions. Most importantly, this refinement extends the spatial and temporal coverage of MODIS AOD retrievals over the coastal regions where 60% of human population resides. This expanded coverage is crucial for better understanding of impact of anthropogenic aerosol particles on coastal air quality and climate.

Retrieval↗
NASA NTRS2018

Sensor Performance Assessment for Terra and Aqua MODIS Using Unscheduled Lunar Observations

The Moderate Resolution Imaging Spectroradiometer (MODIS) has been in operation for over 18 and 16 years on the Terra and Aqua spacecrafts, respectively. In order to maintain long-term calibration stability over the life of each mission, MODIS uses a set of on-board calibrators as well as observations of the Moon and selected Earth-view targets. The lunar observations nominally occur in a narrow phase angle range, 55 degrees - 56 degrees, and use scheduled spacecraft maneuvers in order to bring the Moon into alignment with the MODIS space-view port. These observations are used to help characterize the MODIS scan-mirror response versus scan-angle. In addition to these scheduled lunar observations, MODIS also views the Moon through the space-view port without a spacecraft maneuver when the geometry is appropriately aligned. This occurs over a wider phase angle range, between 51 degrees - 82 degrees, than those of the scheduled moon observations. While the phase angle restriction of our scheduled observations provides consistency between the calibration events, the unscheduled Moon data can provide a valuable assessment of many calibration related investigations that use the Moon. In this paper, we compare the results of unscheduled versus scheduled lunar observations for several sensor calibration and performance assessments. These include the lunar calibration trending used to characterize the scan-mirror response versus scan angle and the electronic crosstalk correction of bands 27-30, which are currently used in the MODIS Level-1B data products, as well as sensor performance assessments such as band-to-band and detector-to-detector spatial registration.

Aqua↗
NASA NTRS2018

Multi-Sensor Integration of Vegetation Index Products for Long-Term Monitoring of Vegetation Dynamics: A Case Study from MODIS to VIIRS

Spectral vegetation index (VI) time series data from moderate resolution sensors, such as Earth Observing System (EOS) Moderate Resolution Imaging Spectroradiometer (MODIS), have widely been used to identify "hot spot" areas of vegetation changes and to characterize long-term trends of vegetation changes. The Visible Infrared Imaging Radiometer Suite (VIIRS) sensor series of the Joint Polar Satellite System (JPSS) program is slated to continue the highly calibrated data stream initiated with MODIS. The first VIIRS sensor has operationally been acquiring Earth-reflected radiation since March 2012. The second VIIRS sensor (NOAA-20) was launched in November 2017, which is to continue the measurements made by the first VIIRS sensor. In this study, we examined an integrated use of MODIS and VIIRS VI time series data on capturing vegetation dynamics in the Asia-Pacific region using their overlapped period of observations (2013-2017). Three VIs, the "top-of-canopy (TOC)" normalized difference vegetation index (NDVI), TOC enhanced vegetation index (EVI), and TOC two-band enhanced vegetation index (EVI2), were investigated. For all the three VIs, VIIRS VIs were systematically higher than the MODIS counterparts due mainly to their spectral bandpass differences. However, both VIIRS and MODIS VIs showed the comparable spatial patterns in their temporal variations. Empirical spectral corrections allowed to merge the two data streams, which slightly improved the temporal resolution of the VI temporal profiles. These results suggest the suitability of VIIRS data to extend and merge into the MODIS VI record for long-term vegetation dynamics studies.

MODIS↗
NASA NTRS2020

Application of quasi-deep convective clouds method for MODIS and VIIRS TEB calibration assessments

A technique to use deep convective clouds (DCC) and quasi-DCC (qDCC) for the calibration assessment of the thermal emissive bands (TEB) on remote sensing instruments has proven feasible. The Terra and Aqua MODIS and S-NPP and NOAA-20 VIIRS TEB calibration uses a nonlinear algorithm whose nonlinear coefficients rely on on-orbit black body (BB) warm-up and cool-down (WUCD) activities for updates. However, the limited BB temperature range affects the calibration’s uncertainty. The DCC core, one of the coldest Earth scenes, is suitable for MODIS calibration assessments; more specifically, for the evaluation of the offset effect in its TEB quadratic calibration function. Moreover, nighttime qDCC measurements provide the advantage of removing solar reflectance effects, thus enhancing the assessment’s accuracy for the midwave infrared TEB. In this paper, the qDCC method is applied to the Terra MODIS and VIIRS TEB. Their stabilities are assessed using long-term DCC and qDCC trending measurements over the instruments’ entire missions. The measurements from bands with an approximately 11-μm wavelength are used to identify the DCC pixels. MODIS band31 (~ 11m) has demonstrated stable performance and accurate calibration for both instruments throughout their respective missions. MODIS band31 can therefore be used as a reference for the other TEB. Furthermore, it also allows for a Terra and Aqua MODIS TEB cross-comparison. The assessment results, along with the calibration uncertainty and Level 1B product impact modeling, can be quite helpful for calibration improvements.

MODIS↗
NASA NTRSDate not supplied

Evaluation of Aqua MODIS and S-NPP VIIRS Thermal Emissive Bands Calibration Stability Using Dome-C

Establishing the calibration consistency between satellite measurements is an essential step in the implementation of a long-term global monitoring plan, which often leads to sensor calibration improvements. The Suomi National Polar-Orbiting Partnership (S-NPP) Visible Infrared Imaging Radiometer Suite (VIIRS) is a polar-orbiting Earth remote sensing instrument built with a strong Moderate Resolution Imaging Spectroradiometer (MODIS) heritage. The center wavelengths of all VIIRS thermal emissive bands (TEBs) match well with those of MODIS with the exception of VIIRS TEB M15 (10.7μm). Previous work from the MODIS Characterization Support Team (MCST) at the NASA/GSFC used specific Earth surface targets to track the long-term consistency,stability, and relative bias between the two MODIS instruments onboard the Terra and Aqua satellites. Using similar methodologies, this paper evaluates the TEB calibration consistency between the MODIS instruments and S-NPP VIIRS over Dome Concordia (Dome-C). The Dome-C site is uniformly snow-covered and the atmospheric effects are small in the surrounding area. Near-surface air temperature measurements from an Automatic Weather Station (AWS) are used as a reference to track each sensor’s calibration stability and determine the relative bias between the MODIS and VIIRS instruments. The results of this study provide a quantitative assessment of the S-NPP VIIRS TEB mission-long performance.

MODIS↗
NASA NTRS2020

MODIS and VIIRS Calibration and Characterization in Support of Producing Long-Term High-Quality Data Products

Terra and Aqua Moderate Resolution Imaging Spectroradiometer (MODIS) have successfully operated since their launches in 1999 and 2002, respectively, and generated various data products to support the Earth remote sensing disciplines and users worldwide for their research activities and applications, including studies of the Earth system, and its changes over time and geographic regions. The MODIS data have also significantly contributed to the continuity of multi-decadal satellite data records and led to major advances in the Earth remote sensing field. The long-term data records from MODIS observations have been and will continue to be extended by the Visible Infrared Imaging Radiometer Suite (VIIRS) instruments, currently operated aboard the Suomi-National Polar-Orbiting Partnership (NPP) and NOAA-20 satellites. The data quality of satellite instruments strongly depends on their calibration accuracy and stability. In order to help scientists and users gain a better understanding of MODIS and VIIRS data quality, this paper provides an overview of their on-orbit calibration methodologies, approaches, and results derived from instrument on-board calibrators and lunar observations, as well as select Earth view targets. What is also discussed is the calibration consistency between MODIS and VIIRS and its potential impact on producing multi-sensor long-term data records. As illustrated, the overall performance of both MODIS and VIIRS continues to meet their design requirements.

MODIS↗
NASA NTRS2020

Continuity of MODIS and VIIRS Snow Cover Extent Data Products for Development of an Earth Science Data Record

An Earth Observing System global snow cover extent data products record at moderate spatial resolution (375–500 m) began in February 2000 with the Moderate-resolution Imaging Spectroradiometer (MODIS) instrument onboard the Terra satellite. The record continued with the Aqua MODIS in July 2002, the Suomi-National Polar Platform (S-NPP) Visible Infrared Imaging Radiometer Suite (VIIRS) in January 2012 and continues with the Joint Polar Satellite System-1 (JPSS-1) VIIRS, launched in November of 2017. The objective of this work is to develop a snow cover extent Earth Science Data Record (ESDR) using different satellites, sensors and algorithms. There are many issues to understand when data from different algorithms and sensors are used over a decade-scale time period to create a continuous dataset. Issues may also arise with sensor degradation and even differences in sensor band locations. In this paper we describe development of an ESDR derived from existing MODIS and VIIRS data products and demonstrate continuity among the products. The MODIS and VIIRS snow cover detection algorithms produce very similar daily snow cover maps, with 90–97% agreement in snow cover extent (SCE) in different landscapes. Differences in SCE between products ranged from 2–15% and are attributable to convolved factors of viewing geometry, pixel spread across a scan and time of observation. Compared at a common grid size of 1 km, there is a mean of 95% agreement in SCE and a difference range of 1–10% between the MODIS and VIIRS SCE maps. Mapping sensor observations to a coarser resolution grid reduces the effect of the factors convolved in the 500 m tile to tile comparisons. We conclude that the MODIS and VIIRS SCE data products are reliable constituents of a moderate-resolution ESDR.

snow cover extent↗
NASA NTRS2020

Terra MODIS: 20 years of on-orbit calibration and performance

Since its launch in December 1999, Terra Moderate Resolution Imaging Spectroradiometer (MODIS) has successfully operated for more than 20 years, with its observations generating a broad range of science data products that have greatly enabled the remote sensing community and users worldwide in their studies of many key geophysical parameters of the Earth’s systems. MODIS collects data in 36 spectral bands, covering wavelengths from 0.41 to 14.4 μm, which are calibrated by a set of onboard calibrators (OBCs). Also contributing to the sensor’s mission-long on-orbit calibration and characterization are near-monthly scheduled lunar observations and multiple time series of the sensor’s responses over select ground targets at a variety of scan angles. To a large extent, the quality of MODIS data products relies strongly on the dedicated efforts to operate and calibrate the instrument, to derive and update calibration parameters, and to develop and implement new calibration strategies and algorithms in response to on-orbit changes of the sensor’s characteristics and its OBC functions. We provide an overview of the Terra MODIS on-orbit operation and calibration activities over the last 20 years, including changes made to extend and preserve the instrument and OBC functions and their operation strategies. It also illustrates the sensor’s on-orbit performance with results derived from its OBC, lunar observations, and select ground targets and discusses major changes in sensor characteristics and corrections applied to the L1B algorithms as well as calibration lookup table updates. To date, the Terra MODIS instrument and its OBCs continue to operate and function normally. Except for those identified prelaunch, most spectral bands and detectors continue to meet their specified calibration requirements. Also discussed in our paper are lessons learned from Terra MODIS operation and calibration, as well as future efforts to further extend and maintain the quality of its long-term data records.

Terra↗
NASA NTRSDate not supplied

MODIS Reflective Solar Band Calibration Improvements using Pseudo-Invariant Desert Targets

To provide the best science data quality, an accurate characterization of the response versus scan angle (RVS) function is critical for the MODIS reflective solar bands (RSB) on-orbit calibration. In every MODIS operational scan, the Earth’s surface, referred to here as Earth view (EV), the space view (SV) port, and the onboard calibrators are viewed via a two-sided scan mirror. The RVS is defined as the sensor’s relative response as a function the angle of incidence (AOI) to the scan mirror. Many different approaches have been developed to derive the time-dependent RVS and its look-up table (LUT) applied to MODIS Level 1B (L1B) products since calibration Collection 4. For most MODIS RSB, the on-board calibrators can reasonably track the RVS change with time. In practice, their RVS is derived using data from on-board calibrators and the EV mirror side ratio (for mirror side 2). For Terra bands 1-4, 8-10 and Aqua bands 1-4, 8-9, an enhancement has been employed in Collections 6 and 6.1 (C6/C6.1) by using Earth scene response trending from pseudo-invariant desert sites in addition to the onboard calibrators. The current C6/C6/1 RVS algorithm is focused on fitting the EV data at each AOI over time and then deriving the relative change at different AOI. The EV response trending is currently fitted with multiple segments over time. Alternatively, the EV responses can be fit first as a function of AOI before fitting temporally in order to reduce the dependence on the stability of the desert site. These pre-treatment methods on the EV data provide improvement in the derived calibration coefficients. However, evidence of insufficient calibration is still observed in the MODIS L1B reflectance data, especially in the form of differences between the mirror sides. In this paper, we review the current methodologies that utilize the EV response trends from the pseudo-invariant Libyan desert targets to supplement the gain derived from the onboard calibrators. An improvement is then proposed and investigated such that a sliding window average (SWA) is used to pre-process the raw EV data. The SWA parameters are carefully selected using trade-off studies to accurately track the Earth scene response trending in multiple cases to overcome the reflectance differences between two mirror sides. Calibration results show improvements for both Aqua and Terra MODIS RSB L1B data products. This new adjustment has been included in the recently delivered Collection 7 LUT that will be evident in the L1B products expected to be released in late 2021.

MODIS↗
NASA NTRS2020

The MODIS TEBs Calibration and Look-up Table Delivery Process for Collections 6 and 6.1

MODIS is a cross-track, whisk-broom scanning imaging radiometer with a double-sided scan mirror that collects data in 36 spectral bands. Sixteen of the 36 MODIS spectral bands are Thermal Emissive Bands (TEBs) whose spectral wavelengths range from 3.5 μm to 14.4 μm. The TEB detectors are calibrated on a scan-by-scan basis using a quadratic calibration algorithm by observing both the MODIS on-board blackbody (BB) and a background space view reference. Blackbody warm-up/cool-down (WUCD) events are performed quarterly to track on-orbit changes associated with the TEB detectors' non-linearity. Following each WUCD, the calibration coefficients in the quadratic algorithm, and their associated contributions to the total uncertainty, are updated and delivered through separate look-up tables (LUTs) when all update criteria are met. Afterwards, the LUTs are incorporated into the Level 1B (L1B) product. Since the Terra MODIS mission began, a steady increase in electronic cross-talk has been observed for TEBs 27{30. Starting from Collection 6.1, an algorithm has been applied using correction coefficients derived from regularly-scheduled lunar observations, with the correction LUT update dependent on its impact on the current L1B product. The MODIS Characterization Support Team (MCST) has established a comprehensive set of procedures to assure timely and accurate LUT updates, and maintain the quality and accuracy of the L1B and science products. This paper provides an overview of the current calibration and LUT delivery process for the MODIS TEBs in Collections 6 and 6.1.

MODIS↗
NASA NTRS1998

Land Surface Temperature Measurements from EOD MODIS Data

We made more tests of the version 2.0 daily Level 2 and Level 3 Land-Surface Temperature (LST) code (PGE 16) jointly with the MODIS Science Data Support Team (SDST). After making minor changes a few times, the PGE16 code has been successfully integrated and tested by MODIS SDST, and recently has passed the inspection at the Goddard Distributed Active Archive Center (DAAC). We conducted a field campaign in the area of Mono Lake, California on March 10, 1998, in order to validate the MODIS LST algorithm in cold and dry conditions. Two MODIS Airborne Simulator (MAS) flights were completed during the field campaign, one before noon, and another around 10 pm PST. The weather condition for the daytime flight was perfect: clear sky, the column water vapor measured by radiosonde around 0.3 cm, and wind speed less than a half meter per second. The quality of MAS data is good for both day and night flights. We analyzed the noise equivalent temperature difference (NE(delta)T) and the calibration accuracy of the seven MAS thermal infrared (TIR) bands, that are used in the MODIS day/night LST algorithm, with daytime MAS data over four flat homogeneous study areas: two on Grant Lake (covered with ice and snow, respectively), one on Mono Lake, and another on the snow field site where we made field measurements. NE(delta)T ranges from 0.2 to 0.6 k for bands 42, 45, 46, and 48. It ranges from 0.8 to 1.1 K for bands 30-32. The day and night MAS data have been used to retrieve surface temperature and emissivities in these bands. A simple method to correct the effect of night thin cirrus has been incorporated into the day/night LST algorithm in dry atmospheric conditions. We compared the retrieved surface temperatures with those measured with TIR spectrometer, radiometers and thermistors in the snow test site, and the retrieved emissivity images with topographic map. The daytime LST values match well within 1 K. The night LST retrieved from MAS data is 3.3 K colder than those from field measurements most likely because of the effect of haze at night. The good agreement among the regional averaged surface temperatures obtained from LST values retrieved at different resolutions increased our confidence in the MODIS day/night LST algorithm.

Wan, Zheng-Ming↗
NASA NTRS1997

The Algorithm for MODIS Wavelength On-Orbit Calibration using the SRCA

The Spectro-Radiometric Calibration Assembly (SRCA) provides on-orbit spectral calibration of the MODerate resolution Imaging Spectroradiometer (MODIS) reflected solar bands and this paper describes how it is accomplished. The SRCA has two adjacent exit slits: 1) Main slit and 2) Calibration slit. The output from the main slit is measured by a reference silicon photo-diode (SIPD) and then passes through the MODIS. The output from the calibration slit passes through a piece of didymium transmission glass and then it is measured by a calibration SIPD. The centroids of the sharp spectral peaks of a didyrnium glass are utilized as wavelength standards. After normalization using the reference SIPD signal to eliminate the effects of the illuminating source spectra, the calibration SIPD establishes the relationship between the peaks of the didymium spectra and the grating angle; this is accomplished through the grating equation. In the grating equation the monochromator parameters, beta (half angle between the incident and diffractive beams) and theta(sub ff) (offset angle of the grating motor) are determined by matching, in a least square sense, the known centroid wavelengths of the didymium peaks and the calculated centroid grating angles from the calibration SIPD signals for the peaks. A displacement between the calibration SIPD and the reference SIPD complicates the signal processing. The response of the MODIS bands to the SRCA output is also normalized by the reference SIPD signal to eliminate the effect of the source spectrum. That response differs from what is measured by MODIS using the Spectral Measurements Assembly (SpMA), a laboratory double-monochromator, due to the wider slit width of the SRCA. The SRCA slit function, calculated using measurements by the SPMA and the SRCA at the same MODIS temperature, will be used to recover the MODIS spectral response using the SRCA data measured on-orbit.

Montgomery, Harry↗
NASA NTRS2001

Degradation of MODIS Optics and its Reflective Solar Bands Calibration

The MODerate Resolution Imaging Spectroradiometer (MODIS) has 36 spectral bands with wavelength ranging from 0.41 micron to 14.5 micron and spatial resolution between 0.25, 0.5, and 1.0 km at Nadir. Its ProtoFlight Model (PFM) on the NASA EOS Terra spacecraft has been providing global coverage of the Land, Ocean, and Atmosphere for the science community since the instrument opened its Nadir door on 24 February 2000. The MODIS optical system consists of a 2-sided paddle wheel scan mirror, a fold mirror, a primary mirror, and other aft optics. The sensor's 20 reflective solar bands from 0.41 to 2.1 micron are calibrated on-orbit by a solar diffuser (SD) and a solar diffuser stability monitor (SDSM). In addition to SD, degradation of the MODIS optics in the reflective solar bands has been observed, including variations in degradation between the two sides of the MODIS scan mirror. During MODIS first year of on-orbit operation, the overall degradations at the shortest wavelength (0.41 micron) are about 3% for SD, and in excess of 10% for the MODIS system. In this paper, we will present our degradation analysis results and discuss their impact on the reflective solar bands' on-orbit calibration.

Xiong, X.↗
NASA NTRS2001

Degradation of MODIS Optics During the First Year of On-Orbit Operation

The MODIS (Moderate Resolution Imaging Spectroradiometer) sensor on the NASA EOS (Earth Observing System) Terra spacecraft has completed more than one year of on-orbit operation since the instrument opened its Nadir door for the scene data collection on 24 February 2000. Its 20 reflective solar bands, from VIS (visible) to SWIR (shortwavelength infrared) (0.41 to 2.1 micron), are calibrated on-orbit by a solar diffuser (SD) and a solar diffuser stability monitor (SDSM). Degradation in the reflective solar bands has been observed in the reflectance of the on board solar diffuser and for the MODIS optics. Variations in degradation of up to 3% are evident between the two sides of the MODIS scan mirror. Degradation of the SD is tracked with the solar diffuser stability monitor, and degradation of the entire MODIS system is tracked by SD observations, adjusted for SD changes. Overall degradation at the shortest wavelengths (near 400 nm) are up to 3% for SD, and in excess of 10% for the MODIS system. Degradation of the SD and full MODIS system for the sensor's reflective solar bands will be described in this report.

Guenther, B.↗
NASA NTRS2001

Validation of MODIS Aerosol Retrieval Over Ocean

The MODerate resolution Imaging Spectroradiometer (MODIS) algorithm for determining aerosol characteristics over ocean is performing with remarkable accuracy. A two-month data set of MODIS retrievals co-located with observations from the AErosol RObotic NETwork (AERONET) ground-based sunphotometer network provides the necessary validation. Spectral radiation measured by MODIS (in the range 550 - 2100 nm) is used to retrieve the aerosol optical thickness, effective particle radius and ratio between the submicron and micron size particles. MODIS-retrieved aerosol optical thickness at 660 nm and 870 nm fall within the expected uncertainty, with the ensemble average at 660 nm differing by only 2% from the AERONET observations and having virtually no offset. MODIS retrievals of aerosol effective radius agree with AERONET retrievals to within +/- 0.10 micrometers, while MODIS-derived ratios between large and small mode aerosol show definite correlation with ratios derived from AERONET data.

Remer, Lorraine A.↗
NASA NTRS2001

MODIS Observation of Aerosols over Southern Africa During SAFARI 2000: Data, Validation, and Estimation of Aerosol Radiative Forcing

Aerosol properties, including optical thickness and size parameters, are retrieved operationally from the MODIS sensor onboard the Terra satellite launched on 18 December 1999. The predominant aerosol type over the Southern African region is smoke, which is generated from biomass burning on land and transported over the southern Atlantic Ocean. The SAFARI-2000 period experienced smoke aerosol emissions from the regular biomass burning activities as well as from the prescribed burns administered on the auspices of the experiment. The MODIS Aerosol Science Team (MAST) formulates and implements strategies for the retrieval of aerosol products from MODIS, as well as for validating and analyzing them in order to estimate aerosol effects in the radiative forcing of climate as accurately as possible. These activities are carried out not only from a global perspective, but also with a focus on specific regions identified as having interesting characteristics, such as the biomass burning phenomenon in southern Africa and the associated smoke aerosol, particulate, and trace gas emissions. Indeed, the SAFARI-2000 aerosol measurements from the ground and from aircraft, along with MODIS, provide excellent data sources for a more intensive validation and a closer study of the aerosol characteristics over Southern Africa. The SAFARI-2000 ground-based measurements of aerosol optical thickness (AOT) from both the automatic Aerosol Robotic Network (AERONET) and handheld Sun photometers have been used to validate MODIS retrievals, based on a sophisticated spatio-temporal technique. The average global monthly distribution of aerosol from MODIS has been combined with other data to calculate the southern African aerosol daily averaged (24 hr) radiative forcing over the ocean for September 2000. It is estimated that on the average, for cloud free conditions over an area of 9 million square kin, this predominantly smoke aerosol exerts a forcing of -30 W/square m C lose to the terrestrial surface and -10 W/square m at the top of the atmosphere (TOA). While cooling the surface and Earth system, the difference of 20 W/square m is energy that heats the atmosphere.

Ichoku, Charles↗
NASA NTRS2001

Remote Sensing of Cloud, Aerosol, and Water Vapor Properties from MODIS

MODIS is an earth-viewing cross-track scanning spectroradiometer launched on the Terra satellite in December 1999. MODIS scans a swath width sufficient to provide nearly complete global coverage every two days from a polar-orbiting, sun-synchronous, platform at an altitude of 705 km, and provides images in 36 spectral bands from 0.415 to 14.235 microns with spatial resolutions of 250 m (2 bands), 500 m (5 bands) and 1000 m (29 bands). These bands have been carefully selected to enable advanced studies of land, ocean, and atmospheric processes. In this presentation I will review the comprehensive set of remote sensing algorithms that have been developed for the remote sensing of atmospheric properties using MODIS data, placing primary emphasis on the principal atmospheric applications of: (1) developing a cloud mask for distinguishing clear sky from clouds, (2) retrieving global cloud radiative and microphysical properties, including cloud top pressure and temperature, effective emissivity, cloud optical thickness, thermodynamic phase, and effective radius, (3) monitoring tropospheric aerosol optical thickness over the land and ocean and aerosol size distribution over the ocean, (4) determining atmospheric profiles of moisture and temperature, and (5) estimating column water amount. The physical principles behind the determination of each of these atmospheric products will be described, together with an example of their application using MODIS observations. All products are archived into two categories: pixel-level retrievals (referred to as Level-2 products) and global gridded products at a latitude and longitude resolution of 1 deg (Level-3 products). An overview of the MODIS atmosphere algorithms and products, status, validation activities, and early level-2 and -3 results will be presented. Finally, I will present some highlights from the land and ocean algorithms developed for processing global MODIS observations, including: (1) surface reflectance, (2) vegetation indices, leaf area index, and FPAR, (3) albedo and nadir BRDF-adjusted reflectance, (4) normalized water-leaving radiance, (5) chlorophyll-a concentration, and (6) sea surface temperature.

King, Michael D.↗