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Sample records for aqua modis reflectance

  1. On-Orbit Calibration and Performance of Aqua MODIS Reflective Solar Bands

    NASA Technical Reports Server (NTRS)

    Xiong, Xiaoxiong; Sun, Junqiang; Xie, Xiaobo; Barnes, William; Salomonson, Vincent

    2009-01-01

    Aqua MODIS has successfully operated on-orbit for more than 6 years since its launch in May 2002, continuously making global observations and improving studies of changes in the Earth's climate and environment. 20 of the 36 MODIS spectral bands, covering wavelengths from 0.41 to 2.2 microns, are the reflective solar bands (RSB). They are calibrated on-orbit using an on-board solar diffuser (SD) and a solar diffuser stability monitor (SDSM). In addition, regularly scheduled lunar observations are made to track the RSB calibration stability. This paper presents Aqua MODIS RSB on-orbit calibration and characterization activities, methodologies, and performance. Included in this study are characterizations of detector signal-to-noise ratio (SNR), short-term stability, and long-term response change. Spectral wavelength dependent degradation of the SD bidirectional reflectance factor (BRF) and scan mirror reflectance, which also varies with angle of incidence (AOI), are examined. On-orbit results show that Aqua MODIS onboard calibrators have performed well, enabling accurate calibration coefficients to be derived and updated for the Level 1B (L1B) production and assuring high quality science data products to be continuously generated and distributed. Since launch, the short-term response, on a scan-by-scan basis, has remained extremely stable for most RSB detectors. With the exception of band 6, there have been no new RSB noisy or inoperable detectors. Like its predecessor, Terra MODIS, launched in December 1999, the Aqua MODIS visible (VIS) spectral bands have experienced relatively large changes, with an annual response decrease (mirror side 1) of 3.6% for band 8 at 0.412 microns, 2.3% for band 9 at 0.443 microns, 1.6% for band 3 at 0.469 microns, and 1.2% for band 10 at 0.488 microns. For other RSB bands with wavelengths greater than 0.5 microns, the annual response changes are typically less than 0.5%. In general, Aqua MODIS optics degradation is smaller than Terra

  2. Global space-based inter-calibration system reflective solar calibration reference: from Aqua MODIS to S-NPP VIIRS

    NASA Astrophysics Data System (ADS)

    Xiong, Xiaoxiong; Angal, Amit; Butler, James; Cao, Changyong; Doelling, David; Wu, Aisheng; Wu, Xiangqian

    2016-05-01

    The MODIS has successfully operated on-board the NASA's EOS Terra and Aqua spacecraft for more than 16 and 14 years, respectively. MODIS instrument was designed with stringent calibration requirements and comprehensive on-board calibration capability. In the reflective solar spectral region, Aqua MODIS has performed better than Terra MODIS and, therefore, has been chosen by the Global Space-based Inter- Calibration System (GSICS) operational community as the calibration reference sensor in cross-sensor calibration and calibration inter-comparisons. For the same reason, it has also been used by a number of earth-observing sensors as their calibration reference. Considering that Aqua MODIS has already operated for nearly 14 years, it is essential to transfer its calibration to a follow-on reference sensor with a similar calibration capability and stable performance. The VIIRS is a follow-on instrument to MODIS and has many similar design features as MODIS, including their on-board calibrators (OBC). As a result, VIIRS is an ideal candidate to replace MODIS to serve as the future GSICS reference sensor. Since launch, the S-NPP VIIRS has already operated for more than 4 years and its overall performance has been extensively characterized and demonstrated to meet its overall design requirements. This paper provides an overview of Aqua MODIS and S-NPP VIIRS reflective solar bands (RSB) calibration methodologies and strategies, traceability, and their on-orbit performance. It describes and illustrates different methods and approaches that can be used to facilitate the calibration reference transfer, including the use of desert and Antarctic sites, deep convective clouds (DCC), and the lunar observations.

  3. On-orbit performance and calibration improvements for the reflective solar bands of Terra and Aqua MODIS

    NASA Astrophysics Data System (ADS)

    Angal, Amit; Xiong, Xiaoxiong (Jack); Wu, Aisheng; Chen, Hongda; Geng, Xu; Link, Daniel; Li, Yonghong; Wald, Andrew; Brinkmann, Jake

    2016-05-01

    Moderate Resolution Imaging Spectroradiometer (MODIS) is the keystone instrument for NASA's EOS Terra and Aqua missions, designed to extend and improve heritage sensor measurements and data records of the land, oceans and atmosphere. The reflective solar bands (RSB) of MODIS covering wavelengths from 0.41 μm to 2.2 μm, are calibrated on-orbit using a solar diffuser (SD), with its on-orbit bi-directional reflectance factor (BRF) changes tracked using a solar diffuser stability monitor (SDSM). MODIS is a scanning radiometer using a two-sided paddle-wheel mirror to collect earth view (EV) data over a range of +/-55° off instrument nadir. In addition to the solar calibration provided by the SD and SDSM system, lunar observations at nearly constant phase angles are regularly scheduled to monitor the RSB calibration stability. For both Terra and Aqua MODIS, the SD and lunar observations are used together to track the on-orbit changes of RSB response versus scan angle (RVS) as the SD and SV port are viewed at different angles of incidence (AOI) on the scan mirror. The MODIS Level 1B (L1B) Collection 6 (C6) algorithm incorporated several enhancements over its predecessor Collection 5 (C5) algorithm. A notable improvement was the use of the earth-view (EV) response trends from pseudo-invariant desert targets to characterize the on-orbit RVS for select RSB (Terra bands 1-4, 8, 9 and Aqua bands 8, 9) and the time, AOI, and wavelength-dependent uncertainty. The MODIS Characterization Support Team (MCST) has been maintaining and enhancing the C6 algorithm since its first update in November, 2011 for Aqua MODIS, and February, 2012 for Terra MODIS. Several calibration improvements have been incorporated that include extending the EV-based RVS approach to other RSB, additional correction for SD degradation at SWIR wavelengths, and alternative approaches for on-orbit RVS characterization. In addition to the on-orbit performance of the MODIS RSB, this paper also discusses in

  4. Vicarious calibration of Aqua and Terra MODIS

    NASA Astrophysics Data System (ADS)

    Thome, Kurtis J.; Czapla-Myers, Jeffrey S.; Biggar, Stuart F.

    2003-11-01

    The Moderate Resolution Imaging Spectroradiometer (MODIS) is onboard both the Terra and Aqua platforms. An important aspect of the use of MODIS, and other Earth Science Enterprise sensors, has been the characterization and calibration of the sensors and validation of their data products. The Remote Sensing Group at the University of Arizona has been active in this area through the use of ground- based test sites. This paper presents the results from the reflectance-base approach using the Railroad Valley Playa test site in Nevada for both Aqua and Terra MODIS. The key to the approach is the measurement of surface reflectance over a 1-km2 area of the playa and results from this method shows agreement with both MODIS sensors to better than 5%. Early results indicate that while the two sensors both agree with the ground-based measurements to within the uncertainties of the reflectance-based approach, there were significant differences between the Aqua and Terra MODIS for data prior to September 2002. Recent results indicate that this bias, if any, is now within the uncertainties of the reflectance-based method of calibration.

  5. Aqua MODIS 8-Year On-Orbit Operation and Calibration

    NASA Technical Reports Server (NTRS)

    Xiong, Xiaoxiong; Angal, Amit; Madhavan, Sriharsha; Choi, Taeyoung; Dodd, Jennifer; Geng, Xu; Wang, Zhipeng; Toller, Gary; Barnes, William

    2010-01-01

    Launched in May 2002, the NASA EOS Aqua MODIS has successfully operated for more than 8 years. Observations from Aqua MODIS and its predecessor, Terra MODIS, have generated an unprecedented amount of data products and made significant contributions to studies of changes in the Earth s system of land, oceans, and atmosphere. MODIS collects data in 36 spectral bands: 20 reflective solar bands (RSB) and 16 thermal emissive bands (TEB). It has a set of on-board calibrators (OBC), providing sensor on-orbit radiometric, spectral, and spatial calibration and characterization. This paper briefly summarizes Aqua MODIS on-orbit operation and calibration activities and illustrates instrument on-orbit performance from launch to present. Discussions are focused on OBC functions and changes in detector radiometric gains, spectral responses, and spatial registrations. With ongoing calibration effort, Aqua MODIS will continue serving the science community with high quality data products

  6. Summary of Terra and Aqua MODIS Long-Term Performance

    NASA Technical Reports Server (NTRS)

    Xiong, Xiaoxiong (Jack); Wenny, Brian N.; Angal, Amit; Barnes, William; Salomonson, Vincent

    2011-01-01

    Since launch in December 1999, the MODIS ProtoFlight Model (PFM) onboard the Terra spacecraft has successfully operated for more than 11 years. Its Flight Model (FM) onboard the Aqua spacecraft, launched in May 2002, has also successfully operated for over 9 years. MODIS observations are made in 36 spectral bands at three nadir spatial resolutions and are calibrated and characterized regularly by a set of on-board calibrators (OBC). Nearly 40 science products, supporting a variety of land, ocean, and atmospheric applications, are continuously derived from the calibrated reflectances and radiances of each MODIS instrument and widely distributed to the world-wide user community. Following an overview of MODIS instrument operation and calibration activities, this paper provides a summary of both Terra and Aqua MODIS long-term performance. Special considerations that are critical to maintaining MODIS data quality and beneficial for future missions are also discussed.

  7. Status of Terra and Aqua MODIS Instrument Operation and Calibration

    NASA Astrophysics Data System (ADS)

    Xiong, X.; Wenny, B. N.; Sun, J.; Angal, A.; Salomonson, V. V.

    2013-12-01

    Terra and Aqua MODIS have successfully operated for more than 13 and 11 years since their respective launches in 1999 and 2002. Nearly 40 data products, developed for studies of the earth's land, ocean, and atmosphere, have been routinely generated from calibrated and geo-located MODIS observations and widely distributed to the science and user community. MODIS on-orbit calibration is performed by a set of on-board calibrators, which include a solar diffuser for the reflective solar bands calibration and a blackbody for the thermal emissive bands calibration. MODIS on-board calibrators are regularly operated to monitor on-orbit changes in sensor responses and key performance parameters, such as radiometric calibration coefficients. Since launch, extensive instrument calibration and characterization activities have been scheduled and executed by the MODIS Characterization Support Team (MCST). This presentation provides an overview of both Terra and Aqua MODIS instrument status, their on-orbit operation and calibration activities, and overall long-term performance. It reports calibration improvements (algorithms and look-up tables) made in the latest MODIS data collection (C6). Lessons learned from both Terra and Aqua MODIS and their applications to the S-NPP VIIRS on-orbit calibration are also discussed.

  8. Comparison of Reflected Solar Radiance Using Aqua Modis and Airborne Remote Sensing (case : Deep Convective Clouds and Cirrus Clouds)

    NASA Astrophysics Data System (ADS)

    Krisna, T. C.; Ehrlich, A.; Werner, F.; Wendisch, M.

    2015-12-01

    Deep Convective Clouds (DCCs) have key role in the tropical region. Despite they only have small spatial coverage, but they account most of the total precipitation in these region which often make flooding. There are such of aviation accidents caused by strong vertical wind, hailing, icing and lightning inside the clouds. Pollutions caused by biomass burning and land degradation can change the aerosol properties as well as cloud properties, therefore will influence the radiation and formation of the DCCs. Those are the major reasons that better understanding of DCCs formation and life cycle are necessary. Between Sept. 01 - Oct. 14, ACRIDICON (Aerosol, Cloud, Precipitation, and Radiation Interactions and Dynamics of Concevtive Clouds Systems) campaign was conducted over Amazonia. It is suitable area to be the site-study due to has strong contrast environtment (pristine and polluted), regular convection activities and stable meteorological condition. In this study we focus on the 2 satellite validation missions designed to fly collocated but in different altitude with A-TRAIN constellation. In order to study DCCs-solar radiation interaction, we use SMART (Spectral Modular Airborne Radiation Measurements System) installed on HALO (High Altitude and Long-Range Research Aircraft) which measures spectral Irradiance (F) and Radiance (I) at the wavelength between 300-2200 nm corresponding to satellite. Due to the limitation in spatial and temporal, airborne measurements only give snapshots of atmosphere condition and DCCs formation, therefore we use multi-satellite data as DCCs have high vertical and horizontal distance, long temporal development and complex form. The comparison of AQUA MODIS and SMART Radiance at 645 nm (non-absorbing) in the clear-sky condition gives strong agreement, but in the multilayer-cloud condition gives worse and results in high underestimation (-86%) in SMART data especially at lower altitude. The bias is caused by interference from clouds

  9. Corrections to the MODIS Aqua Calibration Derived From MODIS Aqua Ocean Color Products

    NASA Technical Reports Server (NTRS)

    Meister, Gerhard; Franz, Bryan Alden

    2013-01-01

    Ocean color products such as, e.g., chlorophyll-a concentration, can be derived from the top-of-atmosphere radiances measured by imaging sensors on earth-orbiting satellites. There are currently three National Aeronautics and Space Administration sensors in orbit capable of providing ocean color products. One of these sensors is the Moderate Resolution Imaging Spectroradiometer (MODIS) on the Aqua satellite, whose ocean color products are currently the most widely used of the three. A recent improvement to the MODIS calibration methodology has used land targets to improve the calibration accuracy. This study evaluates the new calibration methodology and describes further calibration improvements that are built upon the new methodology by including ocean measurements in the form of global temporally averaged water-leaving reflectance measurements. The calibration improvements presented here mainly modify the calibration at the scan edges, taking advantage of the good performance of the land target trending in the center of the scan.

  10. Status of time-dependent response versus scan-angle (RVS) for Terra and Aqua MODIS reflective solar bands

    NASA Astrophysics Data System (ADS)

    Geng, Xu; Angal, Amit; Sun, Junqiang; Chen, Hongda; Wu, Aisheng; Li, Yonghong; Link, Daniel; Xiong, Xiaoxiong

    2014-09-01

    The MODerate resolution Imaging Spectroradiometer (MODIS) has 20 reflective solar bands (RSB), which are calibrated using a solar diffuser (SD) and near-monthly scheduled lunar observations via a space view (SV) port. The sensor responses observed at two different angles of incidence (AOI) from the SD and lunar measurements are used to track the on-orbit RSB gain changes as well as the response versus scan-angle (RVS) changes. The MODIS RSB have experienced wavelength dependent degradation since launch with the larger degradation observed at the shorter wavelengths. In addition to the SD and lunar observations, the MODIS Characterization Support Team (MCST) regularly monitors the response trending at multiple AOI over selected desert sites. In Collection 6 (C6), a new algorithm using the EV measurements from pseudoinvariant desert sites was developed to better characterize the MODIS scan-angle dependence and it led to a significant improvement in the long-term calibration consistency of the MODIS Level 1B (L1B) products. This approach is formulated for all RSB, and its application was recently extended to Terra band 10, leading to a significant improvement in the ocean-color products. This paper discusses the current status and performance of the on-orbit RVS characterization as applied in C6. Also, the various challenges and future improvement strategies associated with trending the EV response for the high-gain ocean bands are discussed.

  11. Status of Aqua MODIS On-orbit Calibration and Characterization

    NASA Technical Reports Server (NTRS)

    Xiong, X.; Barnes, W.; Chiang, K.; Erives, H.; Che, N.; Sun, J.; Isaacman, A.; Salomonson, V.

    2004-01-01

    The MODIS Flight Model 1 (FM1) has been in operation for more than two years since its launch onboard the NASA's Earth Observing System (EOS) Aqua spacecraft on May 4, 2002. The MODIS has 36 spectral bands: 20 reflective solar bands (RSB) with center wavelengths from 0.41 to 2.2 micron and 16 thermal emissive bands (TEB) from 3.7 to 14.5 micron. It provides the science community observations (data products) of the Earth's land, oceans, and atmosphere for a board range of applications. Its primary on-orbit calibration and characterization activities are performed using a solar diffuser (SD) and a solar diffuser stability monitor (SDSM) system for the RSB and a blackbody for the TEB. Another on-board calibrator (OBC) known as the spectro-radiometric calibration assembly (SRCA) is used for the instrument's spatial (TEB and RSB) and spectral (RSB only) characterization. We present in this paper the status of Aqua MODIS calibration and characterization during its first two years of on-orbit operation. Discussions will be focused on the calibration activities executed on-orbit in order to maintain and enhance the instrument's performance and the quality of its Level 1B (L1B) data products. We also provide comparisons between Aqua MODIS and Terra MODIS (launched in December, 1999), including their similarity and difference in response trending and optics degradation. Existing data and results show that Aqua MODIS bands 8 (0.412 micron) and 9 (0.443 micron) have much smaller degradation than Terra MODIS bands 8 and 9. The most noticeable feature shown in the RSB trending is that the mirror side differences in Aqua MODIS are extremely small and stable (<0.1%) while the Terra MODIS RSB trending has shown significant mirror side difference and wavelength dependent degradation. The overall stability of the Aqua MODIS TEB is also better than that of the Terra MODIS during their first two years of on-orbit operation.

  12. Surface Albedo/BRDF Parameters (Terra/Aqua MODIS)

    DOE Data Explorer

    Trishchenko, Alexander

    2008-01-15

    Spatially and temporally complete surface spectral albedo/BRDF products over the ARM SGP area were generated using data from two Moderate Resolution Imaging Spectroradiometer (MODIS) sensors on Terra and Aqua satellites. A landcover-based fitting (LBF) algorithm is developed to derive the BRDF model parameters and albedo product (Luo et al., 2004a). The approach employs a landcover map and multi-day clearsky composites of directional surface reflectance. The landcover map is derived from the Landsat TM 30-meter data set (Trishchenko et al., 2004a), and the surface reflectances are from MODIS 500m-resolution 8-day composite products (MOD09/MYD09). The MOD09/MYD09 data are re-arranged into 10-day intervals for compatibility with other satellite products, such as those from the NOVA/AVHRR and SPOT/VGT sensors. The LBF method increases the success rate of the BRDF fitting process and enables more accurate monitoring of surface temporal changes during periods of rapid spring vegetation green-up and autumn leaf-fall, as well as changes due to agricultural practices and snowcover variations (Luo et al., 2004b, Trishchenko et al., 2004b). Albedo/BRDF products for MODIS on Terra and MODIS on Aqua, as well as for Terra/Aqua combined dataset, are generated at 500m spatial resolution and every 10-day since March 2000 (Terra) and July 2002 (Aqua and combined), respectively. The purpose for the latter product is to obtain a more comprehensive dataset that takes advantages of multi-sensor observations (Trishchenko et al., 2002). To fill data gaps due to cloud presence, various interpolation procedures are applied based on a multi-year observation database and referring to results from other locations with similar landcover property. Special seasonal smoothing procedure is also applied to further remove outliers and artifacts in data series.

  13. Early on-orbit calibration results from Aqua MODIS

    NASA Astrophysics Data System (ADS)

    Xiong, Xiaoxiong; Barnes, William L.

    2003-04-01

    Aqua MODIS, also known as the MODIS Flight Model 1 (FM1), was launched on May 4, 2002. It opened its nadir aperture door (NAD) on June 24, 2002, beginning its Earth observing mission. In this paper, we present early results from Aqua MODIS on-orbit calibration and characterization and assess the instrument's overall performance. MODIS has 36 spectral bands located on four focal plane assemblies (FPAs). Bands 1-19, and 26 with wavelengths from 0.412 to 2.1 microns are the reflective solar bands (RSB) that are calibrated on-orbit by a solar diffuser (SD). The degradation of the SD is tracked using a solar diffuser stability monitor (SDSM). The bands 20-25, and 27-36 with wavelengths from 3.75 to 14.5 microns are the thermal emissive bands (TEB) that are calibrated on-orbit by a blackbody (BB). Early results indicate that the on-orbit performance has been in good agreement with the predications determined from pre-launch measurements. Except for band 21, the low gain fire band, band 6, known to have some inoperable detectors from pre-launch characterization, and one noisy detector in band 36, all of the detectors' noise characterizations are within their specifications. Examples of the sensor's short-term and limited long-term responses in both TEB and RSB will be provided to illustrate the sensor's on-orbit stability. In addition, we will show some of the improvements that Aqua MODIS made over its predecessor, Terra MODIS (Protoflight Model - PFM), such as removal of the optical leak into the long-wave infrared (LWIR) photoconductive (PC) bands and reduction of electronic crosstalk and out-of-band (OOB) thermal leak into the short-wave infrared (SWIR) bands.

  14. Calibration Adjustments to the MODIS Aqua Ocean Color Bands

    NASA Technical Reports Server (NTRS)

    Meister, Gerhard

    2012-01-01

    After the end of the SeaWiFS mission in 2010 and the MERIS mission in 2012, the ocean color products of the MODIS on Aqua are the only remaining source to continue the ocean color climate data record until the VIIRS ocean color products become operational (expected for summer 2013). The MODIS on Aqua is well beyond its expected lifetime, and the calibration accuracy of the short wavelengths (412nm and 443nm) has deteriorated in recent years_ Initially, SeaWiFS data were used to improve the MODIS Aqua calibration, but this solution was not applicable after the end of the SeaWiFS mission_ In 2012, a new calibration methodology was applied by the MODIS calibration and support team using desert sites to improve the degradation trending_ This presentation presents further improvements to this new approach. The 2012 reprocessing of the MODIS Aqua ocean color products is based on the new methodology.

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

    NASA Astrophysics Data System (ADS)

    Angal, Amit; Brinkmann, Jake; Kumar, A. Senthil; Xiong, Xiaoxiong

    2016-05-01

    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.

  16. Retrieval of Aerosol Properties from MODIS Terra, MODIS Aqua, and VIIRS SNPP: Calibration Focus

    NASA Technical Reports Server (NTRS)

    Levy, Robert C.; Mattoo, Shana; Sawyer, Virginia; Kleidman, Richard; Patadia, Falguni; Zhou, Yaping; Gupta, Pawan; Shi, Yingxi; Remer, Lorraine; Holz, Robert

    2016-01-01

    MODIS-DT Collection 6 - Aqua/Terra level 2, 3; entire record processed - "Trending" issues reduced - Still a 15% or 0.02 Terra vs Aqua offset. - Terra/Aqua convergence improved with C6+, but bias remains. - Other calibration efforts yield mixed results. VIIRS-­-DT in development - VIIRS is similar, yet different then MODIS - With 50% wider swath, VIIRS has daily coverage - Ensures algorithm consistency with MODIS. - Currently: 20% NPP vs Aqua offset over ocean. - Only small bias (%) over land (2012-­-2016) - Can VIIRS/MODIS create aerosol CDR? Calibration for MODIS - VIIRS continues to fundamentally important. It's not just Terra, or just Aqua, or just NPP-­-VIIRS, I really want to push synergistic calibration.

  17. MODIS solar reflective calibration traceability

    NASA Astrophysics Data System (ADS)

    Xiong, Xiaoxiong; Butler, Jim

    2009-08-01

    Long-term climate data records often consist of observations made by multiple sensors. It is, therefore, extremely important to have instrument overlap, to be able to track instrument stability, to quantify measurement uncertainties, and to establish an absolute measurement scale traceable to the International System of Units (SI). The Moderate Resolution Imaging Spectroradiometer (MODIS) is a key instrument for both the Terra and Aqua missions, which were launched in December 1999 and May 2002, respectively. It has 20 reflective solar bands (RSB) with wavelengths from 0.41 to 2.2μm and observes the Earth at three nadir spatial resolutions: 0.25km, 0.5km, and 1km. MODIS RSB on-orbit calibration is reflectance based with reference to the bi-directional reflectance factor (BRF) of its on-board solar diffuser (SD). The SD BRF characterization was made pre-launch by the instrument vendor using reference samples traceable directly to the National Institute of Standards and Technology (NIST). On-orbit SD reflectance degradation is tracked by an on-board solar diffuser stability monitor (SDSM). This paper provides details of this calibration chain, from pre-launch to on-orbit operation, and associated uncertainty assessments. Using MODIS as an example, this paper also discusses challenges and key design requirements for future missions developed for accurate climate studies.

  18. MODIS Solar Reflective Calibration Traceability

    NASA Technical Reports Server (NTRS)

    Xiong, Xiaoxiong; Butler, Jim

    2009-01-01

    Long-term climate data records often consist of observations made by multiple sensors. It is, therefore, extremely important to have instrument overlap, to be able to track instrument stability, to quantify, measurement uncertainties, and to establish absolute scale traceable to the International System of Units (SI). The Moderate Resolution Imaging Spectroradiometer (MODIS) is a key instrument for both the Terra and Aqua missions, which were launched in December 1999 and May 2002, respectively. It has 20 reflective solar bands (RSB) with wavelengths from 0.41 to 2.2 micrometers and observes the Earth at three nadir spatial resolutions: 0.25km, 0.5km, and 1km. MODIS RSB on-orbit calibration is reflectance based with reference to the bidirectional reflectance factor (BRF) of its on-board solar diffuser (SD). The SD BRF characterization was made pre-launch by the instrument vendor using reference samples traceable directly to the National Institute of Standards and Technology (NIST). On-orbit SD reflectance degradation is tracked by an on-board solar diffuser monitor (SDSM). This paper provides details of this calibration chain, from prelaunch to on-orbit operation, and associated uncertainty assessments. Using MODIS as an example, this paper also discusses challenges and key design requirements for future missions developed for accurate climate studies.

  19. Synergism of MODIS Aerosol Remote Sensing from Terra and Aqua

    NASA Technical Reports Server (NTRS)

    Ichoku, Charles; Kaufman, Yoram J.; Remer, Lorraine A.

    2003-01-01

    The MODerate-resolution Imaging Spectro-radiometer (MODIS) sensors, aboard the Earth Observing System (EOS) Terra and Aqua satellites, are showing excellent competence at measuring the global distribution and properties of aerosols. Terra and Aqua were launched on December 18, 1999 and May 4, 2002 respectively, with daytime equator crossing times of approximately 10:30 am and 1:30 pm respectively. Several aerosol parameters are retrieved at 10-km spatial resolution from MODIS daytime data over land and ocean surfaces. The parameters retrieved include: aerosol optical thickness (AOT) at 0.47, 0.55 and 0.66 micron wavelengths over land, and at 0.47, 0.55, 0.66, 0.87, 1.2, 1.6, and 2.1 microns over ocean; Angstrom exponent over land and ocean; and effective radii, and the proportion of AOT contributed by the small mode aerosols over ocean. Since the beginning of its operation, the quality of Terra-MODIS aerosol products (especially AOT) have been evaluated periodically by cross-correlation with equivalent data sets acquired by ground-based (and occasionally also airborne) sunphotometers, particularly those coordinated within the framework of the AErosol Robotic NETwork (AERONET). Terra-MODIS AOT data have been found to meet or exceed pre-launch accuracy expectations, and have been applied to various studies dealing with local, regional, and global aerosol monitoring. The results of these Terra-MODIS aerosol data validation efforts and studies have been reported in several scientific papers and conferences. Although Aqua-MODIS is still young, it is already yielding formidable aerosol data products, which are also subjected to careful periodic evaluation similar to that implemented for the Terra-MODIS products. This paper presents results of validation of Aqua-MODIS aerosol products with AERONET, as well as comparative evaluation against corresponding Terra-MODIS data. In addition, we show interesting independent and synergistic applications of MODIS aerosol data from

  20. Assessment of MODIS Reflected Solar Calibration Uncertainty

    NASA Technical Reports Server (NTRS)

    Xiong, Xiaoxiong; Sun, Junqiang; Butler, James

    2011-01-01

    Determination of the calibration accuracy and traceability of a remote sensing instrument is a driving issue in the use of satellite data for calibration inter-comparisons and studying climate change. The Terra and Aqua MODerate Resolution Imaging Spectroradiometer (MODIS) instruments have successfully operated for more than 11 and 9 years, respectively. Twenty of the thirty six MODIS spectral bands are in the reflected solar region with center wavelengths ranging from 0.41 to 2.2 microns. MODIS reflective solar band (RSB) on-orbit calibration is reflectance based through the use of an on-board solar diffuser (SO). The calibration uncertainty requirements are +/-2.0% for the RSB reflectance factors at sensor specified typical scene reflectances or radiances. The SO bi-directional reflectance factor (BRF) was characterized pre-launch and its on-orbit changes are tracked by an on-board solar diffuser stability monitor (SDSM). This paper provides an assessment of MODIS RSB on-orbit calibration traceability and uncertainty for its Level 1B (L1B) reflectance factors. It examines in details each of the uncertainty contributors, including those from pre-launch measurements as well as on-orbit observations. Common challenging issues and differences due to individual sensors' specific characteristics and on-orbit performance are also discussed in this paper. Guidance and recommendations are presented, based on lessons from MODIS RSB calibration uncertainty assessment, for the development of future instrument calibration and validation plans.

  1. Assessment of MODIS Scan Mirror Reflectance Changes On-Orbit

    NASA Technical Reports Server (NTRS)

    Xiong, Xiaoxiong; Wu, A.; Angal, A.

    2008-01-01

    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.

  2. An Overview of Lunar Calibration and Characterization for the EOS Terra and Aqua MODIS

    NASA Technical Reports Server (NTRS)

    Xiong, X.; Salomonson, V. V.; Sun, J.; Chiang, K.; Xiong, S.; Humphries, S.; Barnes, W.; Guenther, B.

    2004-01-01

    The Moon can be used as a stable source for Earth-observing sensors on-orbit radiometric and spatial stability monitoring in the VIS and NIR spectral regions. It can also serve as a calibration transfer vehicle among multiple sensors. Nearly identical copies of the Moderate Resolution Imaging Spectroradiometer (MODE) have been operating on-board the NASA's Earth Observing System (EOS) Terra and Aqua satellites since their launches in December 1999 and May 2002, respectively. Terra and Aqua MODIS each make observations in 36 spectral bands covering the spectral range from 0.41 to 14.5 microns and are calibrated on-orbit by a set of on-board calibrations (OBCs) including: 1) a solar diffuser (SD), 2) a solar diffuser stability monitor (SDSM), 3) a blackbody (BB), and 4) a spectro-radiometric calibration assembly (SRCA). In addition to fully utilizing the OBCs, the Moon has been used extensively by both Terra and Aqua MODIS to support their on-orbit calibration and characterization. A 4 This paper provides an overview of applications of lunar calibration and characterization from the MODIS perspective, including monitoring radiometric calibration stability for the reflective solar bands (RSBs), tracking changes of the sensors response versus scan-angle (RVS), examining the sensors spatial performance , and characterizing optical leaks and electronic crosstalk among different spectral bands and detectors. On-orbit calibration consistency between the two MODIS instruments is also addressed. Based on the existing on-orbit time series of the Terra and Aqua MODIS lunar observations, the radiometric difference between the two sensors is less than +/-1% for the RSBs. This method provides a powerful means of performing calibration comparisons among Earth-observing sensors and assures consistent data and science products for the long-term studies of climate and environmental changes.

  3. Multispectral Cloud Retrievals from MODIS on Terra and Aqua

    NASA Technical Reports Server (NTRS)

    King, Michael D.; Platnick, Steven; Ackerman, Steven A.; Menzel, W. Paul; Gray, Mark A.; Moody, Eric G.

    2002-01-01

    The Moderate Resolution Imaging Spectroradiometer (MODIS) was developed by NASA and launched onboard the Terra spacecraft on December 18, 1999 and the Aqua spacecraft on April 26, 2002. MODIS scans a swath width sufficient to provide nearly complete global coverage every two days from each polar-orbiting, sun-synchronous, platform at an altitude of 705 km, and provides images in 36 spectral bands between 0.415 and 14.235 microns with spatial resolutions of 250 m (2 bands), 500 m (5 bands) and 1000 m (29 bands). In this paper we will describe the various methods being used for the remote sensing of cloud properties using MODIS data, focusing primarily on the MODIS cloud mask used to distinguish clouds, clear sky, heavy aerosol, and shadows on the ground, and on the remote sensing of cloud optical properties, especially cloud optical thickness and effective radius of water drops and ice crystals. Additional properties of clouds derived from multispectral thermal infrared measurements, especially cloud top pressure and emissivity, will also be described. Results will be presented of MODIS cloud properties both over the land and over the ocean, showing the consistency in cloud retrievals over various ecosystems used in the retrievals. The implications of this new observing system on global analysis of the Earth's environment will be discussed.

  4. Assessment of the Visible Channel Calibrations of the TRMM VIRS and MODIS on Aqua and Terra

    NASA Technical Reports Server (NTRS)

    Minnis, Patrick; Doelling, David R.; Nguyen, Louis; Miller, Walter F.; Chakrapani, Venketesan

    2007-01-01

    Several recent research satellites carry self-calibrating multispectral imagers that can be used for calibrating operational imagers lacking complete self-calibrating capabilities. In particular, the visible (VIS, 0.65 m) channels on operational meteorological satellites are generally calibrated before launch, but require vicarious calibration techniques to monitor the gains and offsets once they are in orbit. To ensure that the self-calibrating instruments are performing as expected, this paper examines the consistencies between the VIS channel (channel 1) reflectances of the Moderate Resolution Imaging Spectroradiometer (MODIS) instruments on the Terra and Aqua satellites and the Version 5a and 6 reflectances of the Visible Infrared Scanner (VIRS) on the Tropical Rainfall Measuring Mission using a variety of techniques. These include comparisons of Terra and Aqua VIS radiances with coincident broadband shortwave radiances from the well-calibrated Clouds and the Earth s Radiant Energy System (CERES), time series of deep convective cloud (DCC) albedos, and ray-matching intercalibrations between each of the three satellites. Time series of matched Terra and VIRS data, Aqua and VIRS data, and DCC reflected fluxes reveal that an older version (Version 5a, ending in early 2004) of the VIRS calibration produced a highly stable record, while the latest version (Version 6) appears to overestimate the sensor gain change by approx.1%/y as the result of a manually induced gain adjustment. Comparisons with the CERES shortwave radiances unearthed a sudden change in the Terra MODIS calibration that caused a 1.17% decrease in the gain on 19 November 2003 that can be easily reversed. After correction for these manual adjustments, the trends in the VIRS and Terra channels are no greater than 0.1%/y. Although the results were more ambiguous, no statistically significant trends were found in the Aqua MODIS channel-1 gain. The Aqua radiances are 1% greater, on average, than their

  5. Overview of Aqua MODIS 10-year On-orbit Calibration and Performance

    NASA Technical Reports Server (NTRS)

    Xiong, X.; Wenny, B.; Sun, J.; Wu, A.; Chen, H.; Angal, A.; Choi, T.; Madhavan, S.; Geng, X.; Link, D.; Toller, G.; Barnes, W.; Salomonson, V.

    2012-01-01

    Since launch in May 2002, Aqua MODIS has successfully operated for nearly 10 years, continuously collecting global datasets for scientific studies of key parameters of the earth's land, ocean, and atmospheric properties and their changes over time. The quality of these geophysical parameters relies on the input quality of sensor calibrated radiances. MODIS observations are made in 36 spectral bands with wavelengths ranging from visible (VIS) to longwave infrared (LWIR). Its reflective solar bands (RSB) are calibrated using data collected from its on-board solar diffuser and regularly scheduled lunar views. The thermal emissive bands (TEB) are calibrated using an on-board blackbody (BB). The changes in the sensor's spectral and spatial characteristics are monitored by an on-board spectroradiometric calibration assembly (SRCA). This paper presents an overview of Aqua MODIS 10-year on-orbit operation and calibration activities, from launch to present, and summarizes its on-orbit radiometric, spectral, and spatial calibration and characterization performance. In addition, it will illustrate and discuss on-orbit changes in sensor characteristics and corrections applied to continuously maintain the sensor level 1B (L1B) data quality, as well as lessons learned that could benefit future calibration efforts.

  6. A Comparison of Cirrus Clouds Retrieved From POLDER-3/PARASOL and MODIS/Aqua

    NASA Astrophysics Data System (ADS)

    Zhang, Z.; Yang, P.; Riedi, J.; Kattawar, G.

    2007-12-01

    MODIS on board Aqua and POLDER-3 on board PARASOL are two key instruments in the A-Train constellation of satellites. MODIS has 36 spectral bands with wavelength ranging from 0.41 to 14.5 μm, but makes measurement at only one direction without information about polarization. POLDER performs multidirectional measurements, of both reflectance and polarization, at nine spectral channels (from 443 to 1020 nm). The two instruments offer different, and somehow complementary, advantages for the remote sensing of microphysical and optical properties of cirrus clouds. In this study, a comparison of cirrus clouds retrieved from the two instruments is made to obtain understanding of the possibility, advantages and limitations of synergetic retrieval. First, the comparison is made between the single scattering properties of "Inhomogeneous Hexagonal Monocrystals" (IHM) used in POLDER retrieval algorithm and the ice-crystal ensemble model used for MODIS. Substantial differences are found in the scattering phase matrix. Co-located cloud mask and cloud top height retrievals are compared, with the emphasis on high and thin cirrus clouds. The optical thicknesses of cirrus clouds retrieved by POLDER are compared with those by MODIS, with and without the constraint that the cloud effective particle size retrieved by MODIS must be similar to that of IHM.

  7. NPP VIIRS and Aqua MODIS RSB Comparison Using Observations from Simultaneous Nadir Overpasses (SNO)

    NASA Technical Reports Server (NTRS)

    Xiong, X.; Wu, A.

    2012-01-01

    Suomi NPP (National Polar-orbiting Partnership) satellite (http://npp.gsfc.nasa.gov/viirs.html) began to daily collect global data following its successful launch on October 28, 2011. The Visible Infrared Imaging Radiometer Suite (VIIRS) is a key NPP sensor. Similar to the design of the OLS, SeaWiFS and MODIS instruments, VIIRS has on-board calibration components including a solar diffuser (SD) and a solar diffuser stability monitor (SDSM) for the reflective solar bands (RSB), a V-groove blackbody for the thermal emissive bands (TEB), and a space view (SV) port for background subtraction. Immediately after the VIIRS nadir door s opening on November 21, 2011, anomalously large degradation in the SD response was identified in the near-IR wavelength region, which was unexpected as decreases in the SD reflectance usually occur gradually in the blue (0.4 m) wavelength region based on past experience. In this study, we use a well-calibrated Aqua MODIS as reference to track and evaluate VIIRS RSB stability and performance. Reflectances observed by both sensors from simultaneous nadir overpasses (SNO) are used to determine VIIRS to MODIS reflectance ratios for their spectral matching bands. Results of this study provide an immediate post-launch assessment, independent validation of the anomalous degradation observed in SD measurements at near-IR wavelengths and initial analysis of calibration stability and consistency.

  8. NPP VIIRS and Aqua MODIS RSB comparison using observations from simultaneous nadir overpasses (SNO)

    NASA Astrophysics Data System (ADS)

    Wu, Aisheng; Xiong, Xiaoxiong

    2012-09-01

    Suomi NPP (National Polar-orbiting Partnership) satellite (http://npp.gsfc.nasa.gov/viirs.html) began to daily collect global data following its successful launch on October 28, 2011. The Visible Infrared Imaging Radiometer Suite (VIIRS) is a key NPP sensor. Similar to the design of the OLS, SeaWiFS and MODIS instruments, VIIRS has on-board calibration components including a solar diffuser (SD) and a solar diffuser stability monitor (SDSM) for the reflective solar bands (RSB), a V-groove blackbody for the thermal emissive bands (TEB), and a space view (SV) port for background subtraction. Immediately after the VIIRS nadir door's opening on November 21, 2011, anomalously large degradation in the SD response was identified in the near-IR wavelength region, which was unexpected as decreases in the SD reflectance usually occur gradually in the blue (~0.4 μm) wavelength region based on past experience. In this study, we use a well-calibrated Aqua MODIS as reference to track and evaluate VIIRS RSB stability and performance. Reflectances observed by both sensors from simultaneous nadir overpasses (SNO) are used to determine VIIRS to MODIS reflectance ratios for their spectral matching bands. Results of this study provide an immediate post-launch assessment, independent validation of the anomalous degradation observed in SD measurements at near-IR wavelengths and initial analysis of calibration stability and consistency.

  9. Spatial and Temporal Distribution of Clouds Observed by MODIS Onboard the Terra and Aqua Satellites

    NASA Technical Reports Server (NTRS)

    King, Michael D.; Platnick, Steven; Menzel, W. Paul; Ackerman, Steven A.; Hubanks, Paul A.

    2012-01-01

    The Moderate Resolution Imaging Spectroradiometer (MODIS) was developed by NASA and launched aboard the Terra spacecraft on December 18, 1999 and Aqua spacecraft on May 4, 2002. A comprehensive set of remote sensing algorithms for the retrieval of cloud physical and optical properties have enabled over twelve years of continuous observations of cloud properties from Terra and over nine years from Aqua. The archived products from these algorithms include 1 km pixel-level (Level-2) and global gridded Level-3 products. In addition to an extensive cloud mask, products include cloud-top properties (temperature, pressure, effective emissivity), cloud thermodynamic phase, cloud optical and microphysical parameters (optical thickness, effective particle radius, water path), as well as derived statistics. Results include the latitudinal distribution of cloud optical and radiative properties for both liquid water and ice clouds, as well as latitudinal distributions of cloud top pressure and cloud top temperature. MODIS finds the cloud fraction, as derived by the cloud mask, is nearly identical during the day and night, with only modest diurnal variation. Globally, the cloud fraction derived by the MODIS cloud mask is approx.67%, with somewhat more clouds over land during the afternoon and less clouds over ocean in the afternoon, with very little difference in global cloud cover between Terra and Aqua. Overall, cloud fraction over land is approx.55%, with a distinctive seasonal cycle, whereas the ocean cloudiness is much higher, around 72%, with much reduced seasonal variation. Cloud top pressure and temperature have distinct spatial and temporal patterns, and clearly reflect our understanding of the global cloud distribution. High clouds are especially prevalent over the northern hemisphere continents between 30 and 50 . Aqua and Terra have comparable zonal cloud top pressures, with Aqua having somewhat higher clouds (cloud top pressures lower by 100 hPa) over land due to

  10. Terra and Aqua MODIS Thermal Emissive Bands On-Orbit Calibration and Performance

    NASA Technical Reports Server (NTRS)

    Xiong, Xiaoxiong; Wu, Aisheng; Wenny, Brian N.; Madhavan, Sriharsha; Wang, Zhipeng; Li, Yonghong; Chen, Na; Barnes, William L.; Salomonson, Vincent V.

    2015-01-01

    Since launch, the Moderate Resolution Imaging Spectroradiometer (MODIS) instruments on the Terra and Aqua spacecraft have operated successfully for more than 14 and 12 years, respectively. A key instrument for National Aeronautics and Space Administration Earth Observing System missions, MODIS was designed to make continuous observations for studies of Earth's land, ocean, and atmospheric properties and to extend existing data records from heritage Earth observing sensors. The 16 thermal emissive bands (TEBs) (3.75-14.24 micrometers) are calibrated on orbit using a temperature controlled blackbody (BB). Both Terra and Aqua MODIS BBs have displayed minimal drift over the mission lifetime, and the seasonal variations of the BB temperature are extremely small in Aqua MODIS. The long-term gain and noise equivalent difference in temperature performance of the 160 TEB detectors on both MODIS instruments have been well behaved and generally very stable. Small but noticeable variations of Aqua MODIS bands 33-36 (13.34-14.24 micrometer) response in recent years are primarily due to loss of temperature control margin of its passive cryoradiative cooler. As a result, fixed calibration coefficients, previously used by bands when the BB temperature is above their saturation temperatures, are replaced by the focal-plane-temperature-dependent calibration coefficients. This paper presents an overview of the MODIS TEB calibration, the on-orbit performance, and the challenging issues likely to impact the instruments as they continue operating well past their designed lifetime of six years.

  11. Status of Aqua MODIS Instrument On-Orbit Operation and Calibration

    NASA Technical Reports Server (NTRS)

    Xiong, Jack; Angal, Amit; Madhaven, Sri; Choi, Jason; Wenny, Brian; Sun, Junqiang; Wu, Aisheng; Chen, Hongda; Salomonson, Vincent; Barnes, William

    2011-01-01

    The Aqua MOderate resolution Imaging Spectroradiometer (MODIS) has successfully operated for nearly a decade, since its launch in May 2002. MODIS was developed and designed with improvements over its heritage sensors in terms of its overall spectral, spatial, and temporal characteristics, and with more stringent calibration requirements. MODIS carries a set of on-board calibrators that can be used to track and monitor its on-orbit radiometric, spectral, and spatial performance. Since launch, extensive instrument calibration and characterization activities have been scheduled and executed by the MODIS Characterization Support Team (MCST). These efforts are made to assure the quality of instrument calibration and L 1B data products, as well as support all science disciplines (land, ocean, and atmospheric) for continuous improvements of science data product quality. MODIS observations from both Terra and Aqua have significantly contributed to the science and user community over a wide range of research activities and applications. This paper provides an overview of Aqua MODIS on-orbit operation and calibration activities, instrument health status, and on-board calibrators (OBC) performance. On-orbit changes of key sensor parameters, such as spectral band radiometric responses, center wavelengths, and bandwidth, are illustrated and compared with those derived from its predecessor, Terra MODIS. Lessons and challenges identified from Aqua MODIS performance are also discussed in this paper. These lessons are not only critical to future improvements of Aqua MODIS on-orbit operation and calibration but also beneficial to its follow-on instrument, the Visible Infrared Imager Radiometer Suite (VIIRS) to be launched on NPOESS Preparatory Project (NPP) spacecraft.

  12. Lidar Ratios for Dust Aerosols Derived From Retrievals of CALIPSO Visible Extinction Profiles Constrained by Optical Depths from MODIS-Aqua and CALIPSO/CloudSat Ocean Surface Reflectance Measurements

    NASA Technical Reports Server (NTRS)

    Young, Stuart A.; Josset, Damien B.; Vaughan, Mark A.

    2010-01-01

    CALIPSO's (Cloud Aerosol Lidar Infrared Pathfinder Satellite Observations) analysis algorithms generally require the use of tabulated values of the lidar ratio in order to retrieve aerosol extinction and optical depth from measured profiles of attenuated backscatter. However, for any given time or location, the lidar ratio for a given aerosol type can differ from the tabulated value. To gain some insight as to the extent of the variability, we here calculate the lidar ratio for dust aerosols using aerosol optical depth constraints from two sources. Daytime measurements are constrained using Level 2, Collection 5, 550-nm aerosol optical depth measurements made over the ocean by the MODIS (Moderate Resolution Imaging Spectroradiometer) on board the Aqua satellite, which flies in formation with CALIPSO. We also retrieve lidar ratios from night-time profiles constrained by aerosol column optical depths obtained by analysis of CALIPSO and CloudSat backscatter signals from the ocean surface.

  13. On-orbit noise characterization of MODIS reflective solar bands

    NASA Astrophysics Data System (ADS)

    Angal, Amit; Xiong, Xiaoxiong; Sun, Junqiang; Geng, Xu

    2015-01-01

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

  14. On-Orbit Noise Characterization of MODIS Reflective Solar Bands

    NASA Technical Reports Server (NTRS)

    Angal, Amit; Xiong, Xiaoxiong; Sun, Junqiang; Geng, Xu

    2015-01-01

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

  15. Terra and Aqua MODIS Design, Radiometry, and Geometry in Support of Land Remote Sensing

    NASA Technical Reports Server (NTRS)

    Xiong, Xiaoxiong; Wolfe, Robert; Barnes, William; Guenther, Bruce; Vermote, Eric; Saleous, Nazmi; Salomonson, Vincent

    2011-01-01

    The NASA Earth Observing System (EOS) mission includes the construction and launch of two nearly identical Moderate Resolution Imaging Spectroradiometer (MODIS) instruments. The MODIS proto-flight model (PFM) is onboard the EOS Terra satellite (formerly EOS AM-1) launched on December 18, 1999 and hereafter referred to as Terra MODIS. Flight model-1 (FM1) is onboard the EOS Aqua satellite (formerly EOS PM-1) launched on May 04, 2002 and referred to as Aqua MODIS. MODIS was developed based on the science community s desire to collect multiyear continuous datasets for monitoring changes in the Earth s land, oceans and atmosphere, and the human contributions to these changes. It was designed to measure discrete spectral bands, which includes many used by a number of heritage sensors, and thus extends the heritage datasets to better understand both long- and short-term changes in the global environment (Barnes and Salomonson 1993; Salomonson et al. 2002; Barnes et al. 2002). The MODIS development, launch, and operation were managed by NASA/Goddard Space Flight Center (GSFC), Greenbelt, Maryland. The sensors were designed, built, and tested by Raytheon/ Santa Barbara Remote Sensing (SBRS), Goleta, California. Each MODIS instrument offers 36 spectral bands, which span the spectral region from the visible (0.41 m) to long-wave infrared (14.4 m). MODIS collects data at three different nadir spatial resolutions: 0.25, 0.5, and 1 km. Key design specifications, such as spectral bandwidths, typical scene radiances, required signal-to-noise ratios (SNR) or noise equivalent temperature differences (NEDT), and primary applications of each MODIS spectral band are summarized in Table 7.1. These parameters were the basis for the MODIS design. More details on the evolution of the NASA EOS and development of the MODIS instruments are provided in Chap. 1. This chapter focuses on the MODIS sensor design, radiometry, and geometry as they apply to land remote sensing. With near

  16. Seasonal and Diurnal Tropical Forest Greenness Observed and Modeled Using MODIS Terra and Aqua Sensors

    NASA Astrophysics Data System (ADS)

    Huete, A. R.; Davies, K.; Restrepo-Coupe, N.; Ratana, P.; Sun, Q.; Saleska, S. R.; Schaaf, C.

    2014-12-01

    Recent studies on satellite measures of Amazon forest greening suggest that observed seasonalities are optical artefacts resulting from shifting sun- sensor view geometries between solstice and equinox periods. The degree and extent of sun geometry influences on satellite observations have important implications on the utility of multi-sensor time series for generating accurate long-term data records. Here we investigate sun angle interactions on tropical forest greening using Terra- and Aqua-MODIS, and combined Terra-Aqua Nadir BRDF Adjusted Reflectance (NBAR) vegetation index (VI) time series, with distinct seasonal and daily sun angle conditions for 10:30 a.m., 1:30 p.m. overpasses, and local solar noon times, respectively. This was compared with modeled, sun angle corrected data from the MODIS MCD43A1 product for fixed sun angles. The interactions between sun angle and forest greening were analyzed along an equatorial forest transect of constant sun-earth geometry but variable annual rainfall and dry season length, as well as a latitudinal transect ranging from equatorial to dry southern forests. In equatorial forests, seasonality in sun angle geometry was synchronous with drought seasonality and resulted in broad scale, forest greening consistent with the duration of the dry season and light availability. The sun angle corrected data showed a reduction in the magnitude of seasonal greening, but also revealed an extended greening period well beyond the equinox. On the other hand, across the latitudinal gradient there were shifts in the start and duration of the dry season that resulted in greening patterns that were asynchronous with sun angle geometries. Sun angle influences became significant and were more pronounced at greater latitudes, demonstrating need to normalize cross-sensor satellite data for sun geometry effects, especially with the recent and upcoming launches of new satellite systems.

  17. Two MODIS Aerosol Products Over Ocean on the Terra and Aqua CERES SSF Datasets

    NASA Technical Reports Server (NTRS)

    Ignatov, Alexander; Minnis, Patrick; Loeb, Norman; Wielicki, Bruce; Miller, Walter; Sun-Mack, Sunny; Tanre, Didier; Remer, Lorraine; Laszlo, Istvan; Geier, Erika

    2004-01-01

    Over ocean, two aerosol products are reported on the Terra and Aqua CERES SSFs. Both are derived from MODIS, but using different sampling and aerosol algorithms. This study briefly summarizes these products, and compares using 2 weeks of global Terra data from 15-21 December 2000, and 1-7 June 2001.

  18. Analog and digital saturation in the MODIS reflective solar bands

    NASA Astrophysics Data System (ADS)

    Madhavan, S.; Angal, A.; Dodd, J.; Sun, J.; Xiong, X.

    2012-09-01

    The MODIS instrument on the Terra and Aqua spacecrafts is a 12 bit sensor with an analog-to-digital (A/D) range of 0 to 4095 DN. Each sensor system is limited by a range at the low and high ends of the dynamic scale. At the low end, quantization noise is the limiting factor whereas at the high end the maximum value is limited by the capability of the amplifier, 4095 in the case of MODIS. However, in both Terra and Aqua MODIS certain detectors in the Reflective Solar Bands (RSB) tend to pre-saturate at a value lower than 4095. This paper serves as a comprehensive report on the algorithms developed to characterize the pre-saturation limit in the RSB. The paper also provides the digital and pre-saturation (analog saturation) limits for the RSB that are currently being used in the Level 1B (L1B) products. The digital and analog saturation limits are well characterized using the Level 1A (L1A) raw Earth-View (EV) data and through the on-board Electronic Calibration (E-CAL). Also, in this paper an analysis is done to study the sensors dynamic range due to the long term changes in the instrument response. In summary, the algorithms and results reported in this paper are important as the radiometric accuracy / uncertainty for instruments such as MODIS, VIIRS (NPP) tends to be coupled to pre-saturation.

  19. On-Orbit Noise Characterization for MODIS Reflective Solar Bands

    NASA Technical Reports Server (NTRS)

    Xiong, X.; Xie, X.; Angal, A.

    2008-01-01

    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

  20. Validation of MODIS Terra and Aqua Ice Surface Temperatures at Summit, Greenland

    NASA Astrophysics Data System (ADS)

    Hall, D. K.; Shuman, C. A.; Xiong, X.; Wenny, B. N.; DiGirolamo, N. E.

    2014-12-01

    Ice-surface temperature (IST) is used in many studies, for example for validation of model output and for detection of leads and thin ice in sea ice. The MODerate-resolution Imaging Spectroradiometer (MODIS) instruments on the Terra and Aqua satellites are useful for mapping IST of sea ice and the Greenland ice sheet (Hall et al., 2012), and validation of the ISTs derived from MODIS has been an ongoing effort (e.g., Koenig & Hall, 2010; Shuman et al., 2014). Recent results call into question the calibration of the MODIS-derived ISTs at very cold temperatures that are characteristic of the Greenland ice sheet high interior during winter (Shuman et al., 2014). In the present work, we investigate the calibration of MODIS IR bands 31 (10.780 - 11.280 µm) and 32 (11.770 - 12.270 µm) under very cold conditions. MODIS IR bands are calibrated using a quadratic algorithm. In Collection 6 (C6), the offset and nonlinear calibration coefficients are computed from data collected during the blackbody cool-down vs the warm-up data used in Collection 5 (C5). To improve the calibration accuracy for low-temperature scenes, the offset terms are set to 0. In general, Aqua MODIS bands 31 and 32 perform better than Terra MODIS bands 31 and 32. One of the reasons is that the Aqua bands have a lower saturation temperature (~340 K) than the Terra (~380 K) bands, and lower saturation or smaller dynamic range means better resolution. As compared to ~2-m NOAA air temperatures (TA) at Summit, Greenland, Shuman et al. (2014) show a small (~0.5°C) offset in Terra MODIS-derived IST vs TA near 0°C, and an increasingly larger offset (up to ~5°C) as TA drops to -60°C. To investigate this further, we compare Terra and Aqua C5 and C6 ISTs with TA data from Summit. This work will document the calibration of bands 31 and 32 at very low temperatures in C5 and C6. Hall, D.K., et al., 2012: Satellite-Derived Climate-Quality Data Record of the Clear-Sky Surface Temperature of the Greenland Ice Sheet

  1. Using the Moon to Track MODIS Reflective Solar Bands Calibration Stability

    NASA Technical Reports Server (NTRS)

    Xiong, Xiaoxiong; Geng, Xu; Angal, Amit; Sun, Junqiang; Barnes, William

    2011-01-01

    MODIS has 20 reflective solar bands (RSB) in the visible (VIS), near infrared (NIR), and short-wave infrared (SWIR) spectral regions. In addition to instrument on-board calibrators (OBC), lunar observations have been used by both Terra and Aqua MODIS to track their reflective solar bands (RSB) on-orbit calibration stability. On a near monthly basis, lunar observations are scheduled and implemented for each instrument at nearly the same lunar phase angles. A time series of normalized detector responses to the Moon is used to monitor its on-orbit calibration stability. The normalization is applied to correct the differences of lunar viewing geometries and the Sun-Moon-Sensor distances among different lunar observations. Initially, the lunar calibration stability monitoring was only applied to MODIS bands (1-4 and 8-12) that do not saturate while viewing the Moon. As the mission continued, we extended the lunar calibration stability monitoring to other RSB bands (bands 13-16) that contain saturated pixels. For these bands, the calibration stability is monitored by referencing their non-saturated pixels to the matched pixels in a non-saturation band. In this paper, we describe this relative approach and apply it to MODIS regularly scheduled lunar observations. We present lunar trending results for both Terra and Aqua MODIS over their entire missions. Also discussed in the paper are the advantages and limitations of this approach and its potential applications to other earth-observing sensors. Keywords: Terra, Aqua, MODIS, sensor, Moon, calibration, stability

  2. Spatial and Temporal Distribution of Clouds as Observed by MODIS Onboard the Terra and Aqua Satellites

    NASA Technical Reports Server (NTRS)

    King, Michael D.; Platnick, Steven; Menzel, Paul; Ackerman, Steven A.

    2006-01-01

    The Moderate Resolution Imaging Spectroradiometer (MODIS) was developed by NASA and launched onboard the Terra spacecraft on December 18,1999 and Aqua spacecraft on May 4, 2002. It achieved its final orbit and began Earth observations on February 24,2000 for Terra and June 24,2002 for Aqua. A comprehensive set of remote sensing algorithms for cloud masking and the retrieval of cloud physical and optical properties has been developed by members of the MODIS atmosphere science team. The archived products from these algorithms have applications in climate change studies, climate modeling, numerical weather prediction, and fundamental atmospheric research. In addition to an extensive cloud mask, products include cloud-top properties (temperature, pressure, effective emissivity), cloud thermodynamic phase, cloud optical and microphysical parameters (optical thickness, effective particle radius, water path), as well as derived statistics. Over the last year, extensive improvements and enhancements in the global cloud products have been implemented, and reprocessing of all MODIS data on Terra has commenced since first light in February 2000. In the cloud mask algorithm, the most extensive improvements were in distinguishing clouds at nighttime, including the challenging polar darkness regions of the world. Additional improvements have been made to properly distinguish sunglint from clouds in the tropical ocean regions, and to improve the identification of clouds from snow during daytime in Polar Regions. We will show global monthly mean cloud fraction for both Terra and Aqua, and show how similar the global daytime cloud fraction is from these morning and afternoon orbits, respectively. We will also show the zonal distribution of cloud fraction over land and ocean regions for both Terra and Aqua, and show the time series of global cloud fraction from July 2002 through June 2006.

  3. Assessment of diverse algorithms applied on MODIS Aqua and Terra data over land surfaces in Europe

    NASA Astrophysics Data System (ADS)

    Glantz, P.; Tesche, M.

    2012-04-01

    Beside an increase of greenhouse gases (e.g., carbon dioxide, methane and nitrous oxide) human activities (for instance fossil fuel and biomass burning) have lead to perturbation of the atmospheric content of aerosol particles. Aerosols exhibits high spatial and temporal variability in the atmosphere. Therefore, aerosol investigation for climate research and environmental control require the identification of source regions, their strength and aerosol type, which can be retrieved based on space-borne observations. The aim of the present study is to validate and evaluate AOT (aerosol optical thickness) and Ångström exponent, obtained with the SAER (Satellite AErosol Retrieval) algorithm for MODIS (MODerate resolution Imaging Spectroradiometer) Aqua and Terra calibrated level 1 data (1 km horizontal resolution at ground), against AERONET (AErosol RObotic NETwork) observations and MODIS Collection 5 (c005) standard product retrievals (10 km), respectively, over land surfaces in Europe for the seasons; early spring (period 1), mid spring (period 2) and summer (period 3). For several of the cases analyzed here the Aqua and Terra satellites passed the investigation area twice during a day. Thus, beside a variation in the sun elevation the satellite aerosol retrievals have also on a daily basis been performed with a significant variation in the satellite-viewing geometry. An inter-comparison of the two algorithms has also been performed. The validation with AERONET shows that the MODIS c005 retrieved AOT is, for the wavelengths 0.469 and 0.500 nm, on the whole within the expected uncertainty for one standard deviation of the MODIS retrievals over Europe (Δτ = ±0.05 ± 0.15τ). The SAER estimated AOT for the wavelength 0.443 nm also agree reasonable well with AERONET. Thus, the majority of the SAER AOT values are within the MODIS expected uncertainty range, although somewhat larger RMSD (root mean square deviation) occurs compared to the results obtained with the

  4. Spatial and Temporal Distribution of Tropospheric Clouds Observed by MODIS Onboard the Terra and Aqua Satellites

    NASA Technical Reports Server (NTRS)

    King, Michael D.

    2005-01-01

    The Moderate Resolution Imaging Spectroradiometer (MODIS) was developed by NASA and launched onboard the Terra spacecraft on December 18, 1999 and Aqua spacecraft on May 4, 2002. It achieved its final orbit and began Earth observations on February 24, 2000 for Terra and June 24, 2002 for Aqua. A comprehensive set of remote sensing algorithms for cloud masking and the retrieval of cloud physical and optical properties has been developed by members of the MODIS atmosphere science team. The archived products from these algorithms have applications in climate change studies, climate modeling, numerical weather prediction, as well as fundamental atmospheric research. In addition to an extensive cloud mask, products include cloud-top properties (temperature, pressure, effective emissivity), cloud thermodynamic phase, cloud optical and microphysical parameters (optical thickness, effective particle radius, water path), as well as derived statistics. We will describe the various cloud properties being analyzed on a global basis from both Terra and Aqua. These include the latitudinal distribution of cloud optical and radiative properties of both liquid water and ice clouds, as well as joint histograms of cloud optical thickness and effective radius for selected geographical locations around the world.

  5. Spatial and Temporal Distribution of Tropospheric Clouds Observed by MODIS Onboard the Terra and Aqua Satellites

    NASA Technical Reports Server (NTRS)

    King, Michael D.; Platnick, Steven

    2005-01-01

    The Moderate Resolution Imaging Spectroradiometer (MODIS) was developed by NASA and launched onboard the Terra spacecraft on December 18,1999 and Aqua spacecraft on May 4, 2002. It achieved its final orbit and began Earth observations on February 24, 2000 for Terra and June 24, 2002 for Aqua. A comprehensive set of remote sensing algorithms for cloud masking and the retrieval of cloud physical and optical properties has been developed by members of the MODIS atmosphere science team. The archived products from these algorithms have applications in climate change studies, climate modeling, numerical weather prediction, as well as fundamental atmospheric research. In addition to an extensive cloud mask, products include cloud-top properties (temperature, pressure, effective emissivity), cloud thermodynamic phase, cloud optical and microphysical parameters (optical thickness, effective particle radius, water path), as well as derived statistics. We will describe the various cloud properties being analyzed on a global basis from both Terra and Aqua. These include the latitudinal distribution of cloud optical and radiative properties of both liquid water and ice clouds, as well as joint histograms of cloud optical thickness and effective radius for selected geographical locations around the world.

  6. Consistency of Global Modis Aerosol Optical Depths over Ocean on Terra and Aqua Ceres SSF Datasets

    NASA Technical Reports Server (NTRS)

    Ignatov, Alexander; Minnis, Patrick; Miller, Walter F.; Wielicki, Bruce A.; Remer, Lorraine

    2006-01-01

    Aerosol retrievals over ocean from the Moderate Resolution Imaging Spectroradiometer (MODIS) onboard Terra and Aqua platforms are available from the Clouds and the Earth's Radiant Energy System (CERES) Single Scanner Footprint (SSF) datasets generated at NASA Langley Research Center (LaRC). Two aerosol products are reported side-by-side. The primary M product is generated by sub-setting and remapping the multi-spectral (0.47-2.1 micrometer) MODIS produced oceanic aerosol (MOD04/MYD04 for Terra/Aqua) onto CERES footprints. M*D04 processing uses cloud screening and aerosol algorithms developed by the MODIS science team. The secondary AVHRR-like A product is generated in only two MODIS bands 1 and 6 (on Aqua, bands 1 and 7). The A processing uses the CERES cloud screening algorithm, and NOAA/NESDIS glint identification, and single-channel aerosol retrieval algorithms. The M and A products have been documented elsewhere and preliminarily compared using 2 weeks of global Terra CERES SSF Edition 1A data in which the M product was based on MOD04 collection 3. In this study, the comparisons between the M and A aerosol optical depths (AOD) in MODIS band 1 (0.64 micrometers), tau(sub 1M) and tau(sub 1A) are re-examined using 9 days of global CERES SSF Terra Edition 2A and Aqua Edition 1B data from 13 - 21 October 2002, and extended to include cross-platform comparisons. The M and A products on the new CERES SSF release are generated using the same aerosol algorithms as before, but with different preprocessing and sampling procedures, lending themselves to a simple sensitivity check to non-aerosol factors. Both tau(sub 1M) and tau(sub 1A) generally compare well across platforms. However, the M product shows some differences, which increase with ambient cloud amount and towards the solar side of the orbit. Three types of comparisons conducted in this study - cross-platform, cross-product, and cross-release confirm the previously made observation that the major area for

  7. MODIS Cloud Products Derived from Terra and Aqua During CRYSTAL-FACE

    NASA Technical Reports Server (NTRS)

    King, Michael D.; Platnick, S.; Riedi, J. C.; Ackerman, S. A.; Menzel, W. P.

    2003-01-01

    The Moderate Resolution Imaging Spectroradiometer (MODIS), developed as part of the Earth Observing System (EOS) and launched on Terra in December 1999 and Aqua in May 2002, is designed to meet the scientific needs for satellite remote sensing of clouds, aerosols, water vapor, and land and ocean surface properties. During the CRYSTAL-FACE experiment, numerous aircraft coordinated both in situ and remote sensing observations with the Terra and Aqua spacecraft. In this paper we will emphasize the optical, microphysical, and physical properties of both liquid water and ice clouds obtained from an analysis of the satellite observations over Florida and the Gulf of Mexico during July 2002. We will present the frequency distribution of liquid water and ice cloud microphysical properties throughout the region, separating the results over land and ocean. Probability distributions of effective radius and cloud optical thickness will also be shown.

  8. Urban vegetation land covers change detection using multi-temporal MODIS Terra/Aqua data

    NASA Astrophysics Data System (ADS)

    Zoran, Maria A.; Savastru, Roxana S.; Savastru, Dan M.; Dida, Adrian I.; Ionescu, Ovidiu M.

    2013-10-01

    Urban vegetation land cover change is a direct measure of quantitative increase or decrease in sources of urban pollution and the dimension of extreme climate events and changes that determine environment quality. Spatio- temporal monitoring of urban vegetation land cover changes is a very important task for establishing the links between policy decisions, regulatory actions and subsequent land use activities. Former studies incorporating two-date change detection using Landsat TM/ETM data had limited performance for urban biophysically complex systems applications. In this paper, we describe recent results using data from NASA's Moderate Resolution Imaging Spectroradiometer and NOAA/AVHRR satellite to study urban vegetation land cover dynamics. This study explored the use of time-series MODIS Terra/Aqua Normalized Difference Vegetation Index (NDVI) and Leaf Area Index (LAI), data to provide change detection information for metropolitan area of Bucharest in Romania. Training and validation are based on a reference dataset collected from IKONOS high resolution remote sensing data. The mean detection accuracy for period 2002- 2012 was assessed to be of 89%, with a reasonable balance between change commission errors (21.7%), change omission errors (28.5%), and Kappa coefficient of 0.69. Annual change detection rates across the urban/periurban areas over the study period (2002-2012) were estimated at 0.78% per annum in the range of 0.45% (2002) to 0.75% (2012).Vegetation dynamics in urban areas at seasonal and longer timescales reflect large-scale interactions between the terrestrial biosphere and the climate system.

  9. Evaluation of monthwise and overall trends of AOD over Indian cities using MODIS Aqua and Terra retrievals

    NASA Astrophysics Data System (ADS)

    Banerjee, Subhasis; Ghosh, Sanjay

    2016-07-01

    Atmospheric aerosols have been shown to have profound impact on climate system and human health. Regular and systematic monitoring of ambient air is thus necessary in order to asses its impact. There are several ground based stations worldwide employed in this service but still their numbers are inadequate and it is even almost impossible to have such stations at difficult geographical terrains and take measurement throughout the year. Aerosol optical depth or AOD, which is a measure of extinction of incoming solar radiation, serves as proxy to atmospheric aerosol loading. Various sensors onboard different satellites take routine measurement of AOD throughout the year. Satellite based AOD is used in many studies due to their wide coverage and availability for a longer time period. Satellite measures reflected solar radiation at the top of the atmosphere. Column integrated value of aerosol are routinely estimated from those measurements using suitable inversion algorithms. MODIS instrument onboard Aqua and Terra satellites of Earth Observing System takes routine measurement in wide spectral range. We used those data to evaluate trend of AOD over almost fifty Indian cities having population more than a million. The cities we have chosen spread over almost entire length and breadth of the country. Few such studies have already been conducted using MODIS data. They typically used level 3 data. Since Level 3 data comes in 1x 1 degree gridded form they provide average value over a vast geographical region. We used level 2 dataset to enable us taking smaller region(1/2 x 1/2 degree here) centering the region of our interest . We used seasonal Mann-Kendall (M-K) statistics coupled with Sen's non-parametric slope estimation procedure to estimate monthwise and overall(i.e., yearly trend taking seasonality into account) AOD trend. We used median AOD for each month of every year to discard very high AOD's which we often get due to cloud contamination. Seasonal M-K test takes

  10. Evaluation of Terra and Aqua MODIS thermal emissive band response versus scan angle

    NASA Astrophysics Data System (ADS)

    Wenny, B. N.; Wu, A.; Madhavan, S.; Xiong, X.

    2014-10-01

    Terra and Aqua MODIS have operated near-continuously for over 14 and 12 years, respectively, and are key instruments for NASA's Earth Observing System. Observations from the 16 thermal emissive bands (TEB), covering wavelengths from 3.5 to 14.4 μm with a nadir spatial resolution of 1 km are used to regularly generate a variety of atmosphere, ocean and land science products. The TEB detectors are calibrated using scan-by-scan observations of an on-board blackbody (BB). The current response versus scan angle (RVS) of the scan mirror was derived using a spacecraft deep-space pitch maneuver for Terra MODIS and characterized during prelaunch for Aqua MODIS. Earth view (EV) data over the complete range of angles of incidence (AOI) can be used to evaluate the on-orbit performance of the TEB RVS over the mission lifetime. Three approaches for tracking the TEB RVS on-orbit using EV observations are formulated. The first approach uses the multiple daily observations of Dome C BT at different AOI and their trend relative to coincident measurements from a ground temperature sensor. The second approach uses brightness temperatures (BT) retrieved over the cloud-free ocean to derive the trends at 13 AOI over the mission lifetime. The third approach tracks the dn response (normalized to the BB AOI) across the full swath width for Antarctic granules with the Dome C site at nadir. The viability of the three approaches is assessed and the long-term stability of the TEB RVS for both MODIS instruments is determined.

  11. Fractional Snowcover Estimates from Earth Observing System (EOS) Terra and Aqua Moderate Resolution Imaging Spectroradiometer (MODIS)

    NASA Technical Reports Server (NTRS)

    Salomonson, Vincent V.

    2002-01-01

    The Moderate Resolution Imaging Spectroradiometer (MODIS) on the NASA Earth Observing System (EOS) Terra and Aqua missions has shown considerable capability for mapping snowcover. The typical approach that has used, along with other criteria, the Normalized Snow Difference Index (NDSI) that takes the difference between 500 meter observations at 1.64 micrometers (MODIS band 6) and 0.555 micrometers (MODIS band 4) over the sum of these observations to determine whether MODIS pixels are snowcovered or not in mapping the extent of snowcover. For many hydrological and climate studies using remote sensing of snowcover, it is desirable to assess if the MODIS snowcover observations could not be enhanced by providing the fraction of snowcover in each MODIS observation (pixel). Pursuant to this objective studies have been conducted to assess whether there is sufficient "signal%o in the NDSI parameter to provide useful estimates of fractional snowcover in each MODIS 500 meter pixel. To accomplish this objective high spatial resolution (30 meter) Landsat snowcover observations were used and co-registered with MODIS 500 meter pixels. The NDSI approach was used to assess whether a Landsat pixel was or was not snowcovered. Then the number of snowcovered Landsat pixels within a MODIS pixel was used to determine the fraction of snowcover within each MODIS pixel. The e results were then used to develop statistical relationships between the NDSI value for each 500 meter MODIS pixel and the fraction of snowcover in the MODIS pixel. Such studies were conducted for three widely different areas covered by Landsat scenes in Alaska, Russia, and the Quebec Province in Canada. The statistical relationships indicate that a 10 percent accuracy can be attained. The variability in the statistical relationship for the three areas was found to be remarkably similar (-0.02 for mean error and less than 0.01 for mean absolute error and standard deviation). Independent tests of the relationships were

  12. Surface circulation patterns in the Gulf of California derived from MODIS Aqua 250 m

    NASA Astrophysics Data System (ADS)

    Martínez-Flores, G.; Salinas-González, F.; Gutiérrez de Velasco-Sanromán, G.; Godínez-Orta, L.

    2009-04-01

    The Gulf of California (GC) is a marginal elongated and semi-enclosed sea located at northwest of Mexico, between the Peninsula of Baja California and the mainland Mexico. The considered area average 150 km in width and 1500 km in length, from the mouth of the Colorado River to Cabo Corrientes, Jalisco. It has a maximum depth of 3600 m at the southern inlet and the northern region average 200 m in deep. The study of superficial circulation patterns in the GC is of interest because its relevance to the mechanisms of transport for distribution of a variety of materials -plankton, contaminants, microalgae, etc.- and its association with areas of sedimentary deposits, zones where there is a higher probability for fishing or related to the presence of certain species of marine life. Recent studies explain the circulation of the GC as a result of the Pacific Ocean's forcing, wind, heat fluxes on the sea surface and the interaction between the flow produced by these agents and bathymetry. The objective of this work was to obtain evidence of the patterns of surface circulation using a spatial resolution of 250 m over a period of two to seven days (depending on cloud cover), which offered images from the MODIS Level 1B. This essay is an attempt to contribute with more information to the understanding of the regional dynamics of the GC and its local influence on the zones bordering the coast. Thus, MODIS Aqua 250 m data was used, to which algorithms were applied in order to enhance the contrast of reflectance levels of these bands (0.620-0.670 and 0.841-0.876 µm) within the marine environment. The results are associated with suspended particulate matter (SPM), which we used as tracers of the surface circulation, using a sequence of images from January 2004 to December 2008. Algorithms for dust and cloud detection were used and incorporated with thermal band images, in which zones of terrigenous contribution by eolian transport were identified. Furthermore, pluvial

  13. Response versus scan-angle corrections for MODIS reflective solar bands using deep convective clouds

    NASA Astrophysics Data System (ADS)

    Bhatt, Rajendra; Angal, Amit; Doelling, David R.; Xiong, Xiaoxiong; Wu, Aisheng; Haney, Conor O.; Scarino, Benjamin R.; Gopalan, Arun

    2016-05-01

    The absolute radiometric calibration of the reflective solar bands (RSBs) of Aqua- and Terra-MODIS is performed using on-board calibrators. A solar diffuser (SD) panel along with a solar diffuser stability monitor (SDSM) system, which tracks the degradation of the SD over time, provides the baseline for calibrating the MODIS sensors. MODIS also views the moon and deep space through its space view (SV) port for lunar-based calibration and computing the background, respectively. The MODIS instrument views the Earth's surface using a two-sided scan mirror, whose reflectance is a function of the angle of incidence (AOI) and is described by response versus scan-angle (RVS). The RVS for both MODIS instruments was characterized prior to launch. MODIS also views the SD and the moon at two different AOIs. There is sufficient evidence that the RVS is changing on orbit over time and as a function of wavelength. The SD and lunar observation scans can only track the RVS variation at two AOIs. Consequently, the MODIS Characterization Support Team (MCST) developed enhanced approaches that supplement the onboard calibrator measurements with responses from the pseudo-invariant desert sites. This approach has been implemented in Level 1B (L1B) Collection 6 (C6) for select short-wavelength bands. This paper presents an alternative approach of characterizing the mirror RVS to derive the time-dependent RVS correction factors for MODIS RSBs using tropical deep convective cloud (DCC) targets. An initial assessment of the DCC response from Aqua-MODIS band 1 C6 data indicates evidence of RVS artifacts, which are not uniform across the scans and are more prevalent at the beginning of the earth-view scan.

  14. Characterization of MODIS mirror side difference in the reflective solar spectral region

    NASA Astrophysics Data System (ADS)

    Geng, X.; Angal, A.; Sun, J.; Wu, A.; Choi, T.; Xiong, X.

    2011-10-01

    The MODIS instruments onboard the Terra and Aqua spacecraft, launched in December 1999 and May 2002, respectively, have successfully operated through the present time. MODIS collects the Earth view (EV) data via a twosided paddle wheel scan mirror at angles of incidence (AOI) from 10.5 to 65.5 degrees. Reflective properties between the two mirror sides are not identical with large differences seen in Terra MODIS reflective solar bands (RSB). This paper describes a methodology to calculate and monitor MODIS RSB mirror side differences using EV observations. The longterm trends of response differences between two mirror sides are evaluated using different EV targets. Results show that the on-orbit changes in the properties of the scan mirror are wavelength and AOI dependent with large mirror side differences observed at shorter wavelengths in larger AOI. Starting from 2005, the mirror side difference has gradually exhibited a seasonally dependent feature in Terra MODIS visible spectral bands, which is mainly due to the changes in the scan mirror polarization property. In addition to fully characterizing on-orbit changes of the MODIS scan mirror properties, results and discussions provided in this paper will help clarify their impacts on the Level 1B data products and support future efforts to maintain MODIS data quality.

  15. The NASA Earth Observing System (EOS) Terra and Aqua Mission Moderate Resolution Imaging Spectroradiometer (MODIS: Science and Applications

    NASA Technical Reports Server (NTRS)

    Salomnson, Vincent V.

    2003-01-01

    The Moderate Resolution Imaging Spectroradiometer (MODIS) on the Earth Observing System (EOS) Terra Mission began to produce data in February 2000. The EOS Aqua mission was launched successfully May 4,2002 with another MODIS on it and "first light" observations occurred on June 24,2002. The Terra MODIS is in a sun-synchronous orbit going north to south in the daylight portion of the orbit crossing the equator at about 1030 hours local time. The Aqua spacecraft operates in a sun-synchronous orbit going south to north in the daylight portion of the orbit crossing the equator at approximately 1330 hours local time. The spacecraft, instrument, and data systems for both MODIS instruments are performing well and are producing a wide variety of data products useful for scientific and applications studies in relatively consistent fashion extending from November 2000 to the present. Within the approximately 40 MODIS data products, several are new and represent powerful and exciting capabilities such the ability to provide observations over the globe of fire occurrences, microphysical properties of clouds and sun-stimulated fluorescence from phytoplankton in the surface waters of the ocean. The remainder of the MODIS products exceeds or, at a minimum, matches the capabilities of products from heritage sensors such as, for example, the Advanced Very High Resolution Radiometer (AVHRR). Efforts are underway to provide data sets for the greater Earth science community and to improve access to these products at the various Distributed Active Archive Centers (DAAC's) or through Direct Broadcast (DB) stations.

  16. Progress on alternative method of the on-orbit RVS characterization for MODIS reflective solar bands

    NASA Astrophysics Data System (ADS)

    Chen, H.; Xiong, X.; Angal, A.; Geng, X.; Wu, A.

    2014-09-01

    MODIS Reflective Solar Bands (RSB) are calibrated on-orbit using its onboard calibrators, including a Solar Diffuser (SD), a Solar Diffuser Stability Monitor (SDSM), and a Spectroradiometric Calibration Assembly (SRCA). A Space View (SV) port is used to provide a background reference, and also facilitate near monthly lunar observations via a spacecraft roll. In every scan, the earth's surface, SV and onboard calibrators are viewed via a two sided scan mirror, whose reflectance depends on the angles of the incidence (AOI) as well as the wavelength of the incident light. Response versus Scan angle (RVS) is defined as a dependence function of the scan mirror's reflectance over AOI. An initial RVS for each RSB was measured prelaunch for both Terra and Aqua MODIS. Algorithms have been developed to track the on-orbit RVS variation using the measurements from the onboard calibrators, supplemented with the Earth View (EV) response from pseudo-invariant desert targets obtained at different AOI. The current approach, as implemented in Collection 6 (C6), uses EV responses from the Libyan desert sites to track the on-orbit RVS change. It strongly depends on the long-term temporal stability of the desert sites. As an effort to validate and, if necessary, to improve MODIS RSB RVS characterization for future applications, the MODIS Characterization Support Team (MCST) has developed and tested an alternative approach to monitor the on-orbit RVS change, using a response from a single desert site. The purpose of using data from one site is to avoid the impact of possible differences in the long-term temporal stability among multiple sites on the calculation of the on-orbit RVS. This paper updates recent progress in the formulation of the alternative RVS approach. Comprehensive comparisons were also performed with current C6 RVS results for both Terra and Aqua MODIS. Results demonstrate that this alternative method provides a supplemental means to track the on-orbit RVS for MODIS RSB.

  17. Effect of MODIS Terra radiometric calibration improvements on Collection 6 Deep Blue aerosol products: Validation and Terra/Aqua consistency

    NASA Astrophysics Data System (ADS)

    Sayer, A. M.; Hsu, N. C.; Bettenhausen, C.; Jeong, M.-J.; Meister, G.

    2015-12-01

    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 ˜0.04 over bright (e.g., desert) and ˜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 ˜10% and ˜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.

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

    NASA Technical Reports Server (NTRS)

    Sayer, A. M.; Hsu, N. C.; Bettenhausen, C.; Jeong, M.-J.; Meister, G.

    2015-01-01

    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.

  19. The Characterization of Deep Convective Cloud Albedo as a Calibration Target Using MODIS Reflectances

    NASA Technical Reports Server (NTRS)

    Doelling, David R.; Hong, Gang; Morstad, Daniel; Bhatt, Rajendra; Gopalan, Arun; Xiong, Jack

    2010-01-01

    There are over 25 years of historical satellite data available to climate analysis. The historical satellite data needs to be well calibrated, especially in the visible, where there is no onboard calibration on operational satellites. The key to the vicarious calibration of historical satellites relies on invariant targets, such as the moon, Dome C, and deserts. Deep convective clouds (DCC) also show promise of being a stable invariant or predictable target viewable by all satellites, since they behave as solar diffusers. However DCC have not been well characterized for calibration. Ten years of well-calibrated MODIS is now available. DCC can easily be identified using IR thresholds, where the IR calibration can be traced to the onboard black-bodies. The natural variability of DCC albedo will be analyzed geographically and seasonally, especially difference of convection initiated over land or ocean. Functionality between particle size and ozone absorption with DCC albedo will be examined. Although DCC clouds are nearly Lambertion, the angular distribution of reflectances will be sampled and compared with theoretical models. Both Aqua and Terra MODIS DCC angular models will be compared for consistency. Normalizing angular geostationary DCC reflectances, which were calibrated against MODIS, with SCIAMACHY spectral reflectances and comparing them to MODIS DCC reflectances will inspect the usage of DCC albedos as an absolute calibration target.

  20. Use of spaceborne lidar for the evaluation of thin cirrus contamination and screening in the Aqua MODIS Collection 5 aerosol products

    NASA Astrophysics Data System (ADS)

    Huang, Jingfeng; Hsu, N. Christina; Tsay, Si-Chee; Liu, Zhaoyan; Jeong, Myeong-Jae; Hansell, Richard A.; Lee, Jaehwa

    2013-06-01

    Cloud contamination from subvisual thin cirrus clouds is still a challenging issue for operational satellite aerosol retrievals. In the A-Train constellation, concurrent high-sensitivity cirrus observations from the Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) provide us with an unprecedented opportunity to examine the susceptibility of the Aqua Moderate Resolution Imaging Spectroradiometer (MODIS) aerosol retrievals to thin cirrus contamination and to evaluate the robustness of various cirrus screening techniques. Quantitative evaluations indicate that the current cirrus screening schemes in the MODIS Dark Target and Deep Blue Collection 5 aerosol retrievals can effectively remove most cirrus signals while some residual thin cirrus signals still exist with strong spatial and seasonal variability. Results also show significant linkage between thin cirrus occurrence frequency and the susceptibility of aerosol retrievals to thin cirrus contamination. Using the CALIPSO cirrus observations as a reference, we also examined the effectiveness and robustness of eight MODIS-derived cirrus screening parameters. These parameters include apparent reflectance at 1.38 µm (R1.38), cirrus reflectance at 0.66 µm (CR0.66), CR0.66 cirrus flag (CF), reflectance ratio between 1.38 µm and 0.66 µm (RR1.38/0.66), reflectance ratio between 1.38 µm and 1.24 µm (RR1.38/1.24), brightness temperature difference between 8.6 µm and 11 µm (BTD8.6-11), brightness temperature difference between 11 µm and 12 µm (BTD11-12), and cloud phase infrared approach (CPIR). Among these parameters, RR1.38/0.66 achieves the best overall performance, followed by the BTD11-12. Results from several test cases suggest that the cirrus screening schemes in the operational MODIS aerosol retrieval algorithms can be further improved to reduce thin cirrus contamination.

  1. Tracking daily land surface albedo and reflectance anisotropy with moderate-resolution imaging spectroradiometer (MODIS)

    NASA Astrophysics Data System (ADS)

    Shuai, Yanmin

    A new algorithm provides daily values of land surface albedo and angular reflectance at a 500-m spatial resolution using data from the Moderate Resolution Imaging Spectroradiometer (MODIS) instruments currently in orbit on NASA's Terra and Aqua satellite platforms. To overcome the day-to-day variance in observed surface reflectance induced by differences in view and solar illumination angles, the algorithm uses the RossThickLiSparse-Reciprocal bidirectional reflectance model, which is fitted to all MODIS observations of a 500-m resolution cell acquired during a 16-day moving window. Individual observations are weighted by their quality, observation coverage, and proximity to the production date of interest. Product quality is measured by (1) the root mean square error (RMSE) of observations against the best model fit; and (2) the ability of the angular sampling pattern of the observations at hand to determine reflectance model parameters accurately. A regional analysis of model fits to data from selected MODIS data tiles establishes the bounds of these quality measures for application in the daily algorithm. The algorithm, which is now available to users of direct broadcast satellite data from MODIS, allows daily monitoring of rapid surface radiation and land surface change phenomena such as crop development and forest foliage cycles. In two demonstrations, the daily algorithm captured rapid change in plant phenology. The growth phases of a winter wheat crop, as monitored at the Yucheng agricultural research station in Yucheng, China, matched MODIS daily multispectral reflectance data very well, especially during the flowering and heading stages. The daily algorithm also captured the daily change in autumn leaf color in New England, documenting the ability of the algorithm to work well over large regions with varying degrees of cloud cover and atmospheric conditions. Daily surface albedos measured using ground-based instruments on towers at the agricultural and

  2. Spatial and Temporal Characteristics of Aerosols from Collection 6 Aqua and Terra MODIS e-Deep Blue Products

    NASA Astrophysics Data System (ADS)

    Bettenhausen, C.; Hsu, N. Y. C.; Sayer, A. M.; Lee, J.; Carletta, N.

    2015-12-01

    Aerosols continue to attract a significant amount of attention from researchers worldwide due to their extensive effects on Earth's climate, ecology, public health, and even energy production. In order to truly understand these effects, a long, stable, and well-calibrated data record is required. Since 2000 and 2002, the Moderate Resolution Imaging Spectroradiometer (MODIS) instruments aboard the Terra and Aqua satellites together with the e-Deep Blue aerosol retrieval algorithm have been providing such a data record. After a multi-year development effort, the production of both Aqua and Terra MODIS Collection 6 (C6) atmosphere products successfully completed earlier this year and the data was released to the public shortly thereafter. The C6 Deep Blue products (now enhanced Deep Blue or e-Deep Blue) have been significantly improved over the previous Collection 5.1 version. In this poster we provide an overview of the latest C6 e-Deep Blue products and the improvements implemented since the previous collection including coverage over dark surfaces and updates to the Terra calibration. Validation results utilizing Aerosol Robotic Network (AERONET) data are also summarized. We then use the C6 e-Deep Blue products from both Aqua and Terra to explore the spatial characteristics in addition to the seasonal and inter-annual variability of aerosols on both regional and global scales. We also use this as an opportunity to compare these results and investigate any differences found between the two instruments.

  3. Modeling and Mapping Oyster Norovirus Outbreak Risks in Gulf of Mexico Using NASA MODIS Aqua Data

    NASA Astrophysics Data System (ADS)

    Deng, Z.; Wang, J.

    2015-12-01

    Norovirus is a highly infectious virus and the leading cause of foodborne disease outbreaks such as oyster norovirus outbreaks. Currently, there is no vaccine to prevent norovirus infection and no drug to treat it. This paper presents an integrated modeling and mapping framework for predicting the risk of norovirus outbreaks in oyster harvesting waters in the Northern Gulf of Mexico coast. The framework involves (1) the construction of three novel remote sensing algorithms for the retrieval of sea surface salinity, sea surface temperature, and gage height (tide level) using NASA MODIS Aqua data; (2) the development of probability-based Artificial Neural Network (ANN) model for the prediction of oyster norovirus outbreak risk, and (3) the application of the Local Indicators of Spatial Association (LISA) for mapping norovirus outbreak risks in oyster harvesting areas in the Northern Gulf of Mexico using the remotely sensed NASA data, retrieved data from the three remote sensing algorithms, and the ANN model predictions. The three remote sensing algorithms are able to correctly retrieve 94.1% of sea surface salinity, 94.0% of sea surface temperature, and 77.8% of gage height observed along the US coast, including the Pacific coast, the Gulf of Mexico coast, and the Atlantic coast. The gage height, temperature, and salinity are the three most important explanatory variables of the ANN model in terms of spatially distributed input variables. The ANN model is capable of hindcasting/predicting all oyster norovirus outbreaks occurred in oyster growing areas along the Gulf of Mexico coast where environmental data are available. The integrated modeling and mapping framework makes it possible to map daily risks of norovirus outbreaks in all oyster harvesting waters and particularly the oyster growing areas where no in-situ environmental data are available, greatly improving the safety of seafood and reducing outbreaks of foodborne disease.

  4. Monitoring ice break-up on the Mackenzie River, Canada, from MODIS Aqua and Terra observations

    NASA Astrophysics Data System (ADS)

    Muhammad, P.; Duguay, C. R.; Kang, K.

    2013-12-01

    Monitoring the response of river ice phenology to variability and changes in high-latitude climate conditions is critical for improving our understanding of northern hydrology and related impacts on geochemical and biological processes. Shorter ice cover duration, thinner ice, and earlier break-up also influence the winter road season, thereby influencing industrial development and the delivery of goods to northern communities. Increased upstream temperatures over the Mackenzie River Basin have caused shorter ice cover seasons, consequently changing the timing and severity of river ice flow in this high-latitude region. This study involves the analysis of Moderate Resolution Imaging Spectroradiometer (MODIS) Level 3 500-m snow products (Aqua and Terra), complemented with 250-m Level 1b data, to monitor ice cover during the break-up period on the Mackenzie River over the 2001-2013 period. Results from the analysis of 10 ice seasons (2003-2012) show that first day ice-off was observed between day of year (DY) 115-125 and ended between DY 145-155, resulting in average melt durations of about 30-40 days. Additional ice-on and ice-off days observed during 2003-2012 resulted from northern flowing entrained river ice that extended the break-up season until DY 155-163. Floating ice flowing northbound could therefore generate multiple periods of ice-cover and ice-free days at the same geographic location. During the ice break-up seasons from 2003-2012, ice melt was initiated by in situ melt over drainage basin (thermodynamic), especially between 61-62o N. However, ice break-up above the 62o N was more dynamically driven. In addition, ice jams were found to be largely controlled by river morphology.

  5. MODIS-Aqua detects Noctiluca scintillans and hotspots in the central Arabian Sea.

    PubMed

    Dwivedi, R; Priyaja, P; Rafeeq, M; Sudhakar, M

    2016-01-01

    Northern Arabian Sea is considered as an ecologically sensitive area as it experiences a massive upwelling and long-lasting algal bloom, Noctiluca scintillans (green tide) during summer and spring-winter, respectively. Diatom bloom is also found to be co-located with N. scintillans and both have an impact on ecology of the basin. In-house technique of detecting species of these blooms from Moderate Resolution Imaging Spectroradiometer (MODIS)-Aqua data was used to generate a time-series of images revealing their spatial distribution. A study of spatial-temporal variability of these blooms using satellite data expressed a cyclic pattern of their spread over a period of 13 years. An average distribution of the blooms for January-March period revealed a peak in 2015 and minimum in 2013. Subsequently, a time-series of phytoplankton species images were generated for these 2 years to study their inter-annual variability and the associated factors. Species images during active phase of the bloom (February) in 2015 indicated development of N. scintillans and diatom in the central Arabian Sea also, up to 12° N. This observation was substantiated with relevant oceanic parameters measured from the ship as well as satellite data and the same is highlight of the paper. While oxygen depletion and release of ammonia associated with N. scintillans are detrimental for waters on the western side; it is relatively less extreme and supports the entire food chain on the eastern side. In view of these contrasting eco-sensitive events, it is a matter of concern to identify biologically active persistent areas, hot spots, in order to study their ecology in detail. An ecological index, persistence of the bloom, was derived from the time-series of species images and it is another highlight of our study. PMID:26690080

  6. Relative spectral response corrected calibration inter-comparison of S-NPP VIIRS and Aqua MODIS thermal emissive bands

    NASA Astrophysics Data System (ADS)

    Efremova, Boryana; Wu, Aisheng; Xiong, Xiaoxiong

    2014-09-01

    The S-NPP Visible Infrared Imaging Radiometer Suite (VIIRS) instrument is built with strong heritage from EOS MODIS, and has very similar thermal emissive bands (TEB) calibration algorithm and on-board calibrating source - a V-grooved blackbody. The calibration of the two instruments can be assessed by comparing the brightness temperatures retrieved from VIIRS and Aqua MODIS simultaneous nadir observations (SNO) from their spectrally matched TEB. However, even though the VIIRS and MODIS bands are similar there are still relative spectral response (RSR) differences and thus some differences in the retrieved brightness temperatures are expected. The differences depend on both the type and the temperature of the observed scene, and contribute to the bias and the scatter of the comparison. In this paper we use S-NPP Cross-track Infrared Sounder (CrIS) data taken simultaneously with the VIIRS data to derive a correction for the slightly different spectral coverage of VIIRS and MODIS TEB bands. An attempt to correct for RSR differences is also made using MODTRAN models, computed with physical parameters appropriate for each scene, and compared to the value derived from actual CrIS spectra. After applying the CrIS-based correction for RSR differences we see an excellent agreement between the VIIRS and Aqua MODIS measurements in the studied band pairs M13-B23, M15-B31, and M16- B32. The agreement is better than the VIIRS uncertainty at cold scenes, and improves with increasing scene temperature up to about 290K.

  7. Time-Dependent Response Versus Scan Angle for MODIS Reflective Solar Bands

    NASA Technical Reports Server (NTRS)

    Sun, Junqiang; Xiong, Xiaoxiong; Angal, Amit; Chen, Hongda; Wu, Aisheng; Geng, Xu

    2014-01-01

    The Moderate Resolution Imaging Spectroradiometer (MODIS) instruments currently operate onboard the National Aeronautics and Space Administration (NASA's) Terra and Aqua spacecraft, launched on December 18, 1999 and May 4, 2002, respectively. MODIS has 36 spectral bands, among which 20 are reflective solar bands (RSBs) covering a spectral range from 0.412 to 2.13 µm. The RSBs are calibrated on orbit using a solar diffuser (SD) and an SD stability monitor and with additional measurements from lunar observations via a space view (SV) port. Selected pseudo-invariant desert sites are also used to track the RSB on-orbit gain change, particularly for short-wavelength bands. MODIS views the Earth surface, SV, and the onboard calibrators using a two-sided scan mirror. The response versus scan angle (RVS) of the scan mirror was characterized prior to launch, and its changes are tracked using observations made at different angles of incidence from onboard SD, lunar, and Earth view (EV) measurements. These observations show that the optical properties of the scan mirror have experienced large wavelength-dependent degradation in both the visible and near infrared spectral regions. Algorithms have been developed to track the on-orbit RVS change using the calibrators and the selected desert sites. These algorithms have been applied to both Terra and Aqua MODIS Level 1B (L1B) to improve the EV data accuracy since L1B Collection 4, refined in Collection 5, and further improved in the latest Collection 6 (C6). In C6, two approaches have been used to derive the time-dependent RVS for MODIS RSB. The first approach relies on data collected from sensor onboard calibrators and mirror side ratios from EV observations. The second approach uses onboard calibrators and EV response trending from selected desert sites. This approach is mainly used for the bands with much larger changes in their time-dependent RVS, such as the Terra MODIS bands 1-4, 8, and 9 and the Aqua MODIS bands 8- and 9

  8. MODIS On-orbit Spectral Calibration for the Reflective Solar Bands

    NASA Technical Reports Server (NTRS)

    Xiong, X.; Che, N.; Barnes, W.

    2004-01-01

    The Moderate Resolution Imaging Spectroradiometer (MODIS) makes observations in 36 spectral bands with wavelengths from 0.41 to 14.5 microns. The bands with center wavelengths below 2.2 microns are referred as the reflective solar bands (RSB) with their radiometric calibration performed by a solar diffuser (SD) and a solar diffuser stability monitor (SDSM). This paper focuses on the MODIS spectral calibration performed by its unique on-board calibrator (OBC): the Spectro-Radiometric Calibration Assembly (SRCA). When operated in the spectral mode, the SRCA acts as a monochromator with internal spherical integration source (SIS) that measures the spectral responses for all the reflective solar bands. A wavelength calibrator, a didymium filter with known spectral profile, is utilized to calibrate the wavelength scale for the grating positions during each SRCA spectral calibration activity. The capability of self-wavelength calibration allows the SRCA to track the center wavelength shifts and to monitor the spectral response changes throughout the instruments lifetime. The MODIS spectral calibration, same for both Terra and Aqua missions, is performed every three months on-orbit. An overview of MODIS spectral characterization approach and a summary of the on-orbit results will be presented in this paper.

  9. The regime of aerosol optical depth over Central Asia based on MODIS Aqua Deep Blue data

    NASA Astrophysics Data System (ADS)

    Floutsi, Athina; KorrasCarraca, Marios; Matsoukas, Christos; Biskos, George

    2015-04-01

    Atmospheric aerosols, both natural and anthropogenic, can affect the regional and global climate through their direct, indirect, and semi-direct effects on the radiative energy budget of the Earth-atmosphere system. To quantify these effects it is therefore important to determine the aerosol load, and an effective way to do that is by measuring the aerosol optical depth (AOD). In this study we investigate the spatial and temporal variability of the AOD over the climatically sensitive region of Central Asia (36° N - 50° N, 46° E - 75° E), which has significant sources of both natural and anthropogenic particles. The primary source of anthropogenic particles is fossil fuel combustion occurring mainly at oil refineries in the Caspian Sea basin. Natural particles originate mostly from the two deserts in the region (namely Kara-Kum and Kyzyl-Kum), where persistent dust activity is observed. Another source is the Aral Sea region, which due to its phenomenal desertification also drives an intense salt and dust transport from the exposed sea-bed to the surrounding regions. This transport is of particular interest because of health-hazardous materials contained in the Aral Sea sea-bed. For our analysis we use Level-3 daily MODIS - Aqua Dark Target - Deep Blue combined product, from the latest MODIS collection (006), available in 1° x 1° resolution (about 100 km x 100 km) over the period 2002-2014.Our first results indicate a significant spatial variability of the aerosol load over the study region. The data also show a clear seasonal cycle, with large aerosol load being associated with strong dust activity during spring and summer (AOD up to 0.5), and low during autumn and winter (AOD up to 0.4). In spring and summer significant aerosol load is observed in the Garabogazköl basin, Northeast and South-southeast Caspian Sea (offshore North Iran and Azerbaijan), as well as southwest of the Aral Sea. In the later region, the high AOD values can be explained by export of

  10. Aerosol optical depth over central north Asia based on MODIS-Aqua data

    NASA Astrophysics Data System (ADS)

    Avgousta Foutsi, Athina; Korras Carraca, Marios Bruno; Matsoukas, Christos; Biskos, George

    2016-04-01

    Atmospheric aerosols, both natural and anthropogenic, can affect the regional and global climate through their direct, indirect, and semi-direct effects on the radiative energy budget of the Earth-atmosphere system. To quantify these effects it is important to determine the aerosol load, and an effective way to do that is by measuring the aerosol optical depth (AOD). The central Asia region (mainly the Caspian and Aral sea basins), the arid and semi-arid regions of Western China as well as Siberia are of great interest due to the significant natural sources of mineral aerosols originating from local deserts and biomass burning from wildfires in boreal forests. What is of particular interest in the region is the phenomenal shrinking and desertification of the Aral Sea that drives an intense salt and dust transport from the exposed sea-bed to the surrounding regions with important implications in regional air quality. Anthropogenic particles are also observed due to fossil-fuel combustion occurring mainly at oil refineries in the Caspian Sea basin. Here we investigate the spatial and temporal variability of the AOD at 550 nm over central Asia, Siberia and western China, in the region located between 35° N - 65° N and 45° E - 110° E. For our analysis we use Level-3 daily MODIS - Aqua Dark Target - Deep Blue combined product, from the latest collection (006), available in a 1°×1° resolution (ca. 100 km × 100 km) over the period 2002-2014. Our results indicate a significant spatial variability of the aerosol load over the study region. The highest AODs are observed over the Aral Sea year-round, with extreme values reaching 2.1 during July. In the rest of our study region a clear seasonal cycle with highest AOD values (up to 1.2 over the Taklamakan Desert) during spring and summer is observed. The arid parts of central north Asia are characterized by larger aerosol loads during spring, lower but still high AOD in summer and much lower values in autumn and spring

  11. Degradation of MODIS Optics and its Reflective Solar Bands Calibration

    NASA Technical Reports Server (NTRS)

    Xiong, X.; Sun, J.; Esposito, J.; Pan, C.; Xiong, S.; Guenther, B.; Barnes, W. L.; Degnan, John (Technical Monitor)

    2001-01-01

    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.

  12. An Assessment of Diurnal and Seasonal Cloud Cover Changes Over the Hawaiian Islands Using Terra and Aqua MODIS

    NASA Astrophysics Data System (ADS)

    Barnes, M.; Miura, T.; Giambelluca, T. W.; Chen, Q.

    2012-12-01

    To date, there has not yet been a spatial and temporal analysis of cloud cover over the Hawaiian Islands using high spatial resolution data. An understanding of patterns in cloud cover is essential to analyzing and understanding atmospheric and hydrologic processes, including evapotranspiration. The MODIS instruments aboard the Terra and Aqua satellites provide observations with the high spatial resolution necessary to determine patterns of cloud cover over the Hawaiian Islands. The objective of this study was to determine how spatial patterns of cloudiness change diurnally and seasonally over the Hawaiian Islands using high resolution cloud cover data generated from the Terra and Aqua MODIS satellite sensors. The MODIS cloud mask products (MOD35 and MYD35) were obtained for the entire MODIS time series over the major Hawaiian Islands. Monthly statistics including mean cloud cover probability at the daytime and nighttime overpasses for each instrument were generated from the daily MOD35 and MYD35 cloudiness time series. The derived monthly statistics for January and June (the wet and dry season, respectively) were analyzed for diurnal (morning vs. afternoon and late evening vs. early morning) changes in total amount and spatial patterns of cloudiness. They were also compared to analyze seasonal changes in cloudiness. Cloud probability generally increased with elevation until the elevation of the inversion layer. The lowest cloud cover probability was observed above the inversion layer on the islands of Maui and Hawaii. This elevational gradient varied in relation to the facings of slopes; cloud cover probability was higher on the windward (northeastern) sides than on the leeward (southwestern) sides of the mountains. Both morning and afternoon observations indicate that the Hawaiian Islands were cloudier in June than in January. This is the opposite of what we might expect as January is in the wet season and June is in the dry season. Both late evening and early

  13. Land Surface Albedo from MERIS Reflectances Using MODIS Directional Factors

    NASA Technical Reports Server (NTRS)

    Schaaf, Crystal L. B.; Gao, Feng; Strahler, Alan H.

    2004-01-01

    MERIS Level 2 surface reflectance products are now available to the scientific community. This paper demonstrates the production of MERIS-derived surface albedo and Nadir Bidirectional Reflectance Distribution Function (BRDF) adjusted reflectances by coupling the MERIS data with MODIS BRDF products. Initial efforts rely on the specification of surface anisotropy as provided by the global MODIS BRDF product for a first guess of the shape of the BRDF and then make use all of the coincidently available, partially atmospherically corrected, cloud cleared, MERIS observations to generate MERIS-derived BRDF and surface albedo quantities for each location. Comparisons between MODIS (aerosol-corrected) and MERIS (not-yet aerosol-corrected) surface values from April and May 2003 are also presented for case studies in Spain and California as well as preliminary comparisons with field data from the Devil's Rock Surfrad/BSRN site.

  14. Radiance validation of the solar reflective bands of MODIS

    NASA Astrophysics Data System (ADS)

    Thome, K.

    The Moderate Resolution Imaging Spectroradiometer (MODIS) is a key sensor onboard NASA's Terra platform launched in 1999. An important aspect of the use of MODIS, and other Terra sensors, has been the characterization and calibration of the sensors and validation of their data products. The Remote Sensing Group at the University of Arizona has been active in this area through the use of ground-based test sites for the radiance validation of MODIS. This paper presents the results from this work using the Railroad Valley Playa test site in Nevada. The paper describes the test site that is now used in the radiance validation and calibration of at least 10 current airborne and satellite based sensors. Two methods are described for the- radiance validation of MODIS. The first relies on ground-based measurements of atmospheric and surface parameters to predict the at -sensor radiance of MODIS. The key to the approach is the measurement of surface reflectance over a 1 km' area of- the playa and results from this method show agreement with MODIS to better than 7%. The second method is a cross-comparison approach to other sensors with footprint sizes and sensor geometries that differ from MODIS. This calibration takes into account the changes in solar zenith and sensor view angle due to any time separation between the sensors as well as spectral differences between the sensors. Early results show that MODIS and ETM+ agree to better than 5% in the solar reflective for bands not affected by atmospheric absorption. The comparisons have also been used to indicate differences in excess of the calibration uncertainties of several other sensors. The paper concludes with an accuracy assessment of the two approaches indicating that cross-comparisons with precision better than 3% can be achieved.

  15. Characterization of turbidity in Florida's Lake Okeechobee and Caloosahatchee and St. Lucie estuaries using MODIS-Aqua measurements.

    PubMed

    Wang, Menghua; Nim, Carl J; Son, Seunghyun; Shi, Wei

    2012-10-15

    This paper describes the use of ocean color remote sensing data from the Moderate Resolution Imaging Spectroradiometer (MODIS) onboard the Aqua satellite to characterize turbidity in Lake Okeechobee and its primary drainage basins, the Caloosahatchee and St. Lucie estuaries from 2002 to 2010. Drainage modification and agricultural development in southern Florida transport sediments and nutrients from watershed agricultural areas to Lake Okeechobee. As a result of development around Lake Okeechobee and the estuaries that are connected to Lake Okeechobee, estuarine conditions have also been adversely impacted, resulting in salinity and nutrient fluctuations. The measurement of water turbidity in lacustrine and estuarine ecosystems allows researchers to understand important factors such as light limitation and the potential release of nutrients from re-suspended sediments. Based on a strong correlation between water turbidity and normalized water-leaving radiance at the near-infrared (NIR) band (nL(w)(869)), a new satellite water turbidity algorithm has been developed for Lake Okeechobee. This study has shown important applications with satellite-measured nL(w)(869) data for water quality monitoring and measurements for turbid inland lakes. MODIS-Aqua-measured water property data are derived using the shortwave infrared (SWIR)-based atmospheric correction algorithm in order to remotely obtain synoptic turbidity data in Lake Okeechobee and normalized water-leaving radiance using the red band (nL(w)(645)) in the Caloosahatchee and St. Lucie estuaries. We found varied, but distinct seasonal, spatial, and event driven turbidity trends in Lake Okeechobee and the Caloosahatchee and St. Lucie estuary regions. Wind waves and hurricanes have the largest influence on turbidity trends in Lake Okeechobee, while tides, currents, wind waves, and hurricanes influence the Caloosahatchee and St. Lucie estuarine areas. PMID:22858282

  16. Ocean Color Data at the Goddard Earth Sciences (GES) DAAC: CZCS, SeaWiFS, OCTS, MODIS-Terra, MODIS-Aqua

    NASA Technical Reports Server (NTRS)

    2002-01-01

    The Goddard Earth Sciences Distributed Active Archive Center (DAAC) is the designated archive for all of the ocean color data produced by NASA satellite missions. The DAAC is a long-term, high volume, secure repository for many different kinds of environmental data. With respect to ocean color, the Goddard DAAC holds all the data obtained during the eight-year mission of the Coastal Zone Color Scanner (CZCS). The DAAC is currently receiving data from the Sea-viewing Wide Field-of-view Sensor (SeaWiFS), and the MODIS-Terra instrument. The DAAC recently received reformatted data from the Ocean Color and Temperature Scanner (OCTS) and will also archive MODIS-Aqua Ocean products. In addition to its archive and distribution services, the Goddard DAAC strives to improve data access, ease-of-use, and data applicability for a broad spectrum of customers. The DAAC's data support teams practice dual roles, both insuring the integrity of the DAAC data archive and serving the user community with answers to user inquiries, online and print documentation, and customized data services.

  17. Trend Analysis of global AOT based on various Polar Orbiting Satellite Observations: MODIS (Terra), MISR (Terra), SeaWiFS (OrbView-2), and MODIS (Aqua)

    NASA Astrophysics Data System (ADS)

    Yoon, J.; Vountas, M.; von Hoyningen-Huene, W.; Chang, D. Y.; Burrows, J. P.

    2012-04-01

    Many studies have investigated temporal trends of cloud-free AOTs derived from polar orbiting satellite observations since aerosol retrieval accuracy has been improved substantially. However, only few studies have discussed the fundamental limitation of incomplete sampling originated from frequent cloud disturbance and restricted temporal coverage. Furthermore, the AOT trends derived from various polar orbiting satellite observations are hardly comparable due to different sensor calibration, retrieval accuracy, and cloud screening. Therefore, the present paper integrates various analyses of AOT trends derived from multiple observations (i.e. MODIS-Terra (MOD) from 2000/03 to 2009/12, MISR-Terra (MIS) from 2000/03 to 2010/12, SeaWiFS-OrbView-2 (SEA) from 1998/01 to 2007/12, and MODIS-Aqua (MYD) from 2003/01 to 2008/12) using a weighted least squares regression in order to minimize the above mentioned issues. With high statistical confidence, the weighted trends of MOD AOT (550 nm), MIS AOT (558 nm), SEA AOT (510 nm), and MYD AOT (550 nm) over OECD Europe showed a significant decrease (-0.00274±0.00126, -0.00303±0.00169, -0.00077±0.00044, and -0.00530±0.00304 per year respectively) while increasing over East Asia (+0.00727±0.00385, +0.00673±0.00401, +0.00342±0.00171, and +0.01939±0.00986 per year respectively).

  18. CERES Single Satellite Footprint, TOA and Surface Fluxes, Clouds (SSF) data in HDF (CER_SSF_Aqua-FM3-MODIS_Edition2A)

    NASA Technical Reports Server (NTRS)

    Wielicki, Bruce A. (Principal Investigator)

    The Single Scanner Footprint TOA/Surface Fluxes and Clouds (SSF) product contains one hour of instantaneous Clouds and the Earth's Radiant Energy System (CERES) data for a single scanner instrument. The SSF combines instantaneous CERES data with scene information from a higher-resolution imager such as Visible/Infrared Scanner (VIRS) on TRMM or Moderate-Resolution Imaging Spectroradiometer (MODIS) on Terra and Aqua. Scene identification and cloud properties are defined at the higher imager resolution and these data are averaged over the larger CERES footprint. For each CERES footprint, the SSF contains the number of cloud layers and for each layer the cloud amount, height, temperature, pressure, optical depth, emissivity, ice and liquid water path, and water particle size. The SSF also contains the CERES filtered radiances for the total, shortwave (SW), and window (WN) channels and the unfiltered SW, longwave (LW), and WN radiances. The SW, LW, and WN radiances at spacecraft altitude are converted to Top-of-the-Atmosphere (TOA) fluxes based on the imager defined scene. These TOA fluxes are used to estimate surface fluxes. Only footprints with adequate imager coverage are included on CER_SSF_TRMM-PFM-VIRS_Subset_Edition1the SSF which is much less than the full set of footprints on the CERES ES-8 product. The following CERES SSF data sets are currently available: CER_SSF_TRMM-PFM-VIRS_Edition1 CER_SSF_TRMM-PFM-VIRS_Subset_Edition1 CER_SSF_TRMM-PFM-VIRS_Edition2A CER_SSF_TRMM-SIM-VIRS_Edition2_VIRSonly CER_SSF_TRMM-PFM-VIRS_Edition2A-TransOps CER_SSF_TRMM-PFM-VIRS_Edition2B-TransOps CER_SSF_TRMM-PFM-VIRS_Edition2B CER_SSF_Terra-FM1-MODIS_Edition1A CER_SSF_Terra-FM1-MODIS_Edition1A CER_SSF_Terra-FM1-MODIS_Edition2A CER_SSF_Terra-FM2-MODIS_Edition2A CER_SSF_Terra-FM1-MODIS_Edition2B CER_SSF_Terra-FM2-MODIS_Edition2B CER_SSF_Aqua-FM4-MODIS_Beta1 CER_SSF_Aqua-FM3-MODIS_Beta2 CER_SSF_Aqua-FM4-MODIS_Beta2. [Location=GLOBAL] [Temporal_Coverage: Start_Date=1998-01-01; Stop

  19. CERES Single Satellite Footprint, TOA and Surface Fluxes, Clouds (SSF) data in HDF (CER_SSF_Aqua-FM4-MODIS_Edition2A)

    NASA Technical Reports Server (NTRS)

    Wielicki, Bruce A. (Principal Investigator)

    The Single Scanner Footprint TOA/Surface Fluxes and Clouds (SSF) product contains one hour of instantaneous Clouds and the Earth's Radiant Energy System (CERES) data for a single scanner instrument. The SSF combines instantaneous CERES data with scene information from a higher-resolution imager such as Visible/Infrared Scanner (VIRS) on TRMM or Moderate-Resolution Imaging Spectroradiometer (MODIS) on Terra and Aqua. Scene identification and cloud properties are defined at the higher imager resolution and these data are averaged over the larger CERES footprint. For each CERES footprint, the SSF contains the number of cloud layers and for each layer the cloud amount, height, temperature, pressure, optical depth, emissivity, ice and liquid water path, and water particle size. The SSF also contains the CERES filtered radiances for the total, shortwave (SW), and window (WN) channels and the unfiltered SW, longwave (LW), and WN radiances. The SW, LW, and WN radiances at spacecraft altitude are converted to Top-of-the-Atmosphere (TOA) fluxes based on the imager defined scene. These TOA fluxes are used to estimate surface fluxes. Only footprints with adequate imager coverage are included on CER_SSF_TRMM-PFM-VIRS_Subset_Edition1the SSF which is much less than the full set of footprints on the CERES ES-8 product. The following CERES SSF data sets are currently available: CER_SSF_TRMM-PFM-VIRS_Edition1 CER_SSF_TRMM-PFM-VIRS_Subset_Edition1 CER_SSF_TRMM-PFM-VIRS_Edition2A CER_SSF_TRMM-SIM-VIRS_Edition2_VIRSonly CER_SSF_TRMM-PFM-VIRS_Edition2A-TransOps CER_SSF_TRMM-PFM-VIRS_Edition2B-TransOps CER_SSF_TRMM-PFM-VIRS_Edition2B CER_SSF_Terra-FM1-MODIS_Edition1A CER_SSF_Terra-FM1-MODIS_Edition1A CER_SSF_Terra-FM1-MODIS_Edition2A CER_SSF_Terra-FM2-MODIS_Edition2A CER_SSF_Terra-FM1-MODIS_Edition2B CER_SSF_Terra-FM2-MODIS_Edition2B CER_SSF_Aqua-FM4-MODIS_Beta1 CER_SSF_Aqua-FM3-MODIS_Beta2 CER_SSF_Aqua-FM4-MODIS_Beta2. [Location=GLOBAL] [Temporal_Coverage: Start_Date=1998-01-01; Stop

  20. CERES Single Satellite Footprint, TOA and Surface Fluxes, Clouds (SSF) data in HDF (CER_SSF_Aqua-FM4-MODIS_Ed2A-NoSW)

    NASA Technical Reports Server (NTRS)

    Wielicki, Bruce A. (Principal Investigator)

    The Single Scanner Footprint TOA/Surface Fluxes and Clouds (SSF) product contains one hour of instantaneous Clouds and the Earth's Radiant Energy System (CERES) data for a single scanner instrument. The SSF combines instantaneous CERES data with scene information from a higher-resolution imager such as Visible/Infrared Scanner (VIRS) on TRMM or Moderate-Resolution Imaging Spectroradiometer (MODIS) on Terra and Aqua. Scene identification and cloud properties are defined at the higher imager resolution and these data are averaged over the larger CERES footprint. For each CERES footprint, the SSF contains the number of cloud layers and for each layer the cloud amount, height, temperature, pressure, optical depth, emissivity, ice and liquid water path, and water particle size. The SSF also contains the CERES filtered radiances for the total, shortwave (SW), and window (WN) channels and the unfiltered SW, longwave (LW), and WN radiances. The SW, LW, and WN radiances at spacecraft altitude are converted to Top-of-the-Atmosphere (TOA) fluxes based on the imager defined scene. These TOA fluxes are used to estimate surface fluxes. Only footprints with adequate imager coverage are included on CER_SSF_TRMM-PFM-VIRS_Subset_Edition1the SSF which is much less than the full set of footprints on the CERES ES-8 product. The following CERES SSF data sets are currently available: CER_SSF_TRMM-PFM-VIRS_Edition1 CER_SSF_TRMM-PFM-VIRS_Subset_Edition1 CER_SSF_TRMM-PFM-VIRS_Edition2A CER_SSF_TRMM-SIM-VIRS_Edition2_VIRSonly CER_SSF_TRMM-PFM-VIRS_Edition2A-TransOps CER_SSF_TRMM-PFM-VIRS_Edition2B-TransOps CER_SSF_TRMM-PFM-VIRS_Edition2B CER_SSF_Terra-FM1-MODIS_Edition1A CER_SSF_Terra-FM1-MODIS_Edition1A CER_SSF_Terra-FM1-MODIS_Edition2A CER_SSF_Terra-FM2-MODIS_Edition2A CER_SSF_Terra-FM1-MODIS_Edition2B CER_SSF_Terra-FM2-MODIS_Edition2B CER_SSF_Aqua-FM4-MODIS_Beta1 CER_SSF_Aqua-FM3-MODIS_Beta2 CER_SSF_Aqua-FM4-MODIS_Beta2. [Location=GLOBAL] [Temporal_Coverage: Start_Date=1998-01-01; Stop

  1. CERES Single Scanner Satellite Footprint, TOA, Surface Fluxes and Clouds (SSF) data in HDF (CER_SSF_Aqua-FM4-MODIS_Edition1B)

    NASA Technical Reports Server (NTRS)

    Wielicki, Bruce A. (Principal Investigator)

    The Single Scanner Footprint TOA/Surface Fluxes and Clouds (SSF) product contains one hour of instantaneous Clouds and the Earth's Radiant Energy System (CERES) data for a single scanner instrument. The SSF combines instantaneous CERES data with scene information from a higher-resolution imager such as Visible/Infrared Scanner (VIRS) on TRMM or Moderate-Resolution Imaging Spectroradiometer (MODIS) on Terra and Aqua. Scene identification and cloud properties are defined at the higher imager resolution and these data are averaged over the larger CERES footprint. For each CERES footprint, the SSF contains the number of cloud layers and for each layer the cloud amount, height, temperature, pressure, optical depth, emissivity, ice and liquid water path, and water particle size. The SSF also contains the CERES filtered radiances for the total, shortwave (SW), and window (WN) channels and the unfiltered SW, longwave (LW), and WN radiances. The SW, LW, and WN radiances at spacecraft altitude are converted to Top-of-the-Atmosphere (TOA) fluxes based on the imager defined scene. These TOA fluxes are used to estimate surface fluxes. Only footprints with adequate imager coverage are included on CER_SSF_TRMM-PFM-VIRS_Subset_Edition1the SSF which is much less than the full set of footprints on the CERES ES-8 product. The following CERES SSF data sets are currently available: CER_SSF_TRMM-PFM-VIRS_Edition1 CER_SSF_TRMM-PFM-VIRS_Subset_Edition1 CER_SSF_TRMM-PFM-VIRS_Edition2A CER_SSF_TRMM-SIM-VIRS_Edition2_VIRSonly CER_SSF_TRMM-PFM-VIRS_Edition2A-TransOps CER_SSF_TRMM-PFM-VIRS_Edition2B-TransOps CER_SSF_TRMM-PFM-VIRS_Edition2B CER_SSF_Terra-FM1-MODIS_Edition1A CER_SSF_Terra-FM1-MODIS_Edition1A CER_SSF_Terra-FM1-MODIS_Edition2A CER_SSF_Terra-FM2-MODIS_Edition2A CER_SSF_Terra-FM1-MODIS_Edition2B CER_SSF_Terra-FM2-MODIS_Edition2B CER_SSF_Aqua-FM4-MODIS_Beta1 CER_SSF_Aqua-FM3-MODIS_Beta2 CER_SSF_Aqua-FM4-MODIS_Beta2. [Location=GLOBAL] [Temporal_Coverage: Start_Date=1998-01-01; Stop

  2. CERES Single Scanner Satellite Footprint, TOA, Surface Fluxes and Clouds (SSF) data in HDF (CER_SSF_Aqua-FM3-MODIS_Edition1B)

    NASA Technical Reports Server (NTRS)

    Wielicki, Bruce A. (Principal Investigator)

    The Single Scanner Footprint TOA/Surface Fluxes and Clouds (SSF) product contains one hour of instantaneous Clouds and the Earth's Radiant Energy System (CERES) data for a single scanner instrument. The SSF combines instantaneous CERES data with scene information from a higher-resolution imager such as Visible/Infrared Scanner (VIRS) on TRMM or Moderate-Resolution Imaging Spectroradiometer (MODIS) on Terra and Aqua. Scene identification and cloud properties are defined at the higher imager resolution and these data are averaged over the larger CERES footprint. For each CERES footprint, the SSF contains the number of cloud layers and for each layer the cloud amount, height, temperature, pressure, optical depth, emissivity, ice and liquid water path, and water particle size. The SSF also contains the CERES filtered radiances for the total, shortwave (SW), and window (WN) channels and the unfiltered SW, longwave (LW), and WN radiances. The SW, LW, and WN radiances at spacecraft altitude are converted to Top-of-the-Atmosphere (TOA) fluxes based on the imager defined scene. These TOA fluxes are used to estimate surface fluxes. Only footprints with adequate imager coverage are included on CER_SSF_TRMM-PFM-VIRS_Subset_Edition1the SSF which is much less than the full set of footprints on the CERES ES-8 product. The following CERES SSF data sets are currently available: CER_SSF_TRMM-PFM-VIRS_Edition1 CER_SSF_TRMM-PFM-VIRS_Subset_Edition1 CER_SSF_TRMM-PFM-VIRS_Edition2A CER_SSF_TRMM-SIM-VIRS_Edition2_VIRSonly CER_SSF_TRMM-PFM-VIRS_Edition2A-TransOps CER_SSF_TRMM-PFM-VIRS_Edition2B-TransOps CER_SSF_TRMM-PFM-VIRS_Edition2B CER_SSF_Terra-FM1-MODIS_Edition1A CER_SSF_Terra-FM1-MODIS_Edition1A CER_SSF_Terra-FM1-MODIS_Edition2A CER_SSF_Terra-FM2-MODIS_Edition2A CER_SSF_Terra-FM1-MODIS_Edition2B CER_SSF_Terra-FM2-MODIS_Edition2B CER_SSF_Aqua-FM4-MODIS_Beta1 CER_SSF_Aqua-FM3-MODIS_Beta2 CER_SSF_Aqua-FM4-MODIS_Beta2. [Location=GLOBAL] [Temporal_Coverage: Start_Date=1998-01-01; Stop

  3. Daily Operational MODIS BRDF, Albedo and Nadir Reflectance Products (V006)

    NASA Astrophysics Data System (ADS)

    Schaaf, C.; Wang, Z.; Shuai, Y.; Strahler, A. H.

    2012-12-01

    The operational surface Bidirectional Reflectance Distribution Function (BRDF) and Albedo product (MCD43) has been produced for more than a decade from the MODerate resolution Imaging Spectroradiometer (MODIS) sensors aboard NASA's Terra and Aqua satellites. The Collection V005 operational product, reprocessed for the entire record, provides BRDF models, surface albedo quantities, and Nadir BRDF-Adjusted Reflectances (NBAR) globally on a 500m grid in a sinusoidal projection every 8 days (based on a 16 day window). As surface albedo is an essential climate variable (ECV), the accurate global estimations of terrestrial albedo provided by this product are used by numerous climate and biogeochemical modeling efforts. Of equal utility, the NBAR values are used as the primary inputs to the MODIS Land Cover product and (in the form of NBAR vegetation indices) are used for a variety of vegetation monitoring and phenological studies. Furthermore, the retrieved BRDF model parameters are increasingly being used to provide estimates of vegetation canopy variability and clumping. In the Collection V006 reprocessing effort, the standard global MODIS BRDF/Albedo product will finally be produced as a daily product (based on a 16 day moving window). The daily algorithm will rely on rolling multi-date directional surface reflectances to establish a general surface reflectance anisotropy model of the surface, while emphasizing the daily observation in an attempt to capture rapidly changing surface conditions. In order to improve retrievals over high latitudes and better capture snow covered and dormant vegetation conditions, more surface reflectances per day will be used in V006. Furthermore, the backup database (used to produce poorer quality magnitude inversions when high quality full retrievals are not possible) will now be continuously updated from the latest high quality full inversion for improved accuracy. The availability of daily V006 BRDF/albedo products will allow more

  4. Seasonal nitrate algorithms for nitrate retrieval using OCEANSAT-2 and MODIS-AQUA satellite data.

    PubMed

    Durairaj, Poornima; Sarangi, Ranjit Kumar; Ramalingam, Shanthi; Thirunavukarassu, Thangaradjou; Chauhan, Prakash

    2015-04-01

    In situ datasets of nitrate, sea surface temperature (SST), and chlorophyll a (chl a) collected during the monthly coastal samplings and organized cruises along the Tamilnadu and Andhra Pradesh coast between 2009 and 2013 were used to develop seasonal nitrate algorithms. The nitrate algorithms have been built up based on the three-dimensional regressions between SST, chl a, and nitrate in situ data using linear, Gaussian, Lorentzian, and paraboloid function fittings. Among these four functions, paraboloid was found to be better with the highest co-efficient of determination (postmonsoon: R2=0.711, n=357; summer: R2=0.635, n=302; premonsoon: R2=0.829, n=249; and monsoon: R2=0.692, n=272) for all seasons. Based on these fittings, seasonal nitrate images were generated using the concurrent satellite data of SST from Moderate Resolution Imaging Spectroradiometer (MODIS) and chlorophyll (chl) from Ocean Color Monitor (OCM-2) and MODIS. The best retrieval of modeled nitrate (R2=0.527, root mean square error (RMSE)=3.72, and mean normalized bias (MNB)=0.821) was observed for the postmonsoon season due to the better retrieval of both SST MODIS (28 February 2012, R2=0.651, RMSE=2.037, and MNB=0.068) and chl OCM-2 (R2=0.534, RMSE=0.317, and MNB=0.27). Present results confirm that the chl OCM-2 and SST MODIS retrieve nitrate well than the MODIS-derived chl and SST largely due to the better retrieval of chl by OCM-2 than MODIS. PMID:25762424

  5. Quality assessment of Landsat surface reflectance products using MODIS data

    NASA Astrophysics Data System (ADS)

    Feng, Min; Huang, Chengquan; Channan, Saurabh; Vermote, Eric F.; Masek, Jeffrey G.; Townshend, John R.

    2012-01-01

    Surface reflectance adjusted for atmospheric effects is a primary input for land cover change detection and for developing many higher level surface geophysical parameters. With the development of automated atmospheric correction algorithms, it is now feasible to produce large quantities of surface reflectance products using Landsat images. Validation of these products requires in situ measurements, which either do not exist or are difficult to obtain for most Landsat images. The surface reflectance products derived using data acquired by the Moderate Resolution Imaging Spectroradiometer (MODIS), however, have been validated more comprehensively. Because the MODIS on the Terra platform and the Landsat 7 are only half an hour apart following the same orbit, and each of the 6 Landsat spectral bands overlaps with a MODIS band, good agreements between MODIS and Landsat surface reflectance values can be considered indicators of the reliability of the Landsat products, while disagreements may suggest potential quality problems that need to be further investigated. Here we develop a system called Landsat-MODIS Consistency Checking System (LMCCS). This system automatically matches Landsat data with MODIS observations acquired on the same date over the same locations and uses them to calculate a set of agreement metrics. To maximize its portability, Java and open-source libraries were used in developing this system, and object-oriented programming (OOP) principles were followed to make it more flexible for future expansion. As a highly automated system designed to run as a stand-alone package or as a component of other Landsat data processing systems, this system can be used to assess the quality of essentially every Landsat surface reflectance image where spatially and temporally matching MODIS data are available. The effectiveness of this system was demonstrated using it to assess preliminary surface reflectance products derived using the Global Land Survey (GLS) Landsat

  6. Quality Assessment of Landsat Surface Reflectance Products Using MODIS Data

    NASA Technical Reports Server (NTRS)

    Feng, Min; Huang, Chengquan; Channan, Saurabh; Vermote, Eric; Masek, Jeffrey G.; Townshend, John R.

    2012-01-01

    Surface reflectance adjusted for atmospheric effects is a primary input for land cover change detection and for developing many higher level surface geophysical parameters. With the development of automated atmospheric correction algorithms, it is now feasible to produce large quantities of surface reflectance products using Landsat images. Validation of these products requires in situ measurements, which either do not exist or are difficult to obtain for most Landsat images. The surface reflectance products derived using data acquired by the Moderate Resolution Imaging Spectroradiometer (MODIS), however, have been validated more comprehensively. Because the MODIS on the Terra platform and the Landsat 7 are only half an hour apart following the same orbit, and each of the 6 Landsat spectral bands overlaps with a MODIS band, good agreements between MODIS and Landsat surface reflectance values can be considered indicators of the reliability of the Landsat products, while disagreements may suggest potential quality problems that need to be further investigated. Here we develop a system called Landsat-MODIS Consistency Checking System (LMCCS). This system automatically matches Landsat data with MODIS observations acquired on the same date over the same locations and uses them to calculate a set of agreement metrics. To maximize its portability, Java and open-source libraries were used in developing this system, and object-oriented programming (OOP) principles were followed to make it more flexible for future expansion. As a highly automated system designed to run as a stand-alone package or as a component of other Landsat data processing systems, this system can be used to assess the quality of essentially every Landsat surface reflectance image where spatially and temporally matching MODIS data are available. The effectiveness of this system was demonstrated using it to assess preliminary surface reflectance products derived using the Global Land Survey (GLS) Landsat

  7. The Global Impact of Clouds on the Production of MODIS Bidirectional Reflectance Model-based Composites for Terrestrial Monitoring

    NASA Technical Reports Server (NTRS)

    Roy, D. P.; Lewis, P.; Schaaf, C. B.; Devadiga, S.; Boschetti, L.

    2006-01-01

    A global data set of cloud occurrence probability derived from Moderate Resolution Imaging Spectroradiometer (MODIS) Terra and Aqua gridded daily data is analyzed to investigate the probability of obtaining at least a minimum number of cloud-free observations within various compositing periods. The probabilities derived from Terra and Aqua, with morning and afternoon overpass times, respectively, are similar and increase with compositing period. Compositing both Terra and Aqua observations results is considerably higher probabilities of obtaining a sufficient number of observations for bidirectional reflectance model-based compositing. Given that the only alternative is obtaining sufficient samples to extend the observation period, which can cause significant problems when the surface state changes, it is concluded that using data from the two MODIS sensors provides the most effective way of generating composited products. Findings with respect to the availability of cloud free composites when n-day composites are generated on a temporally overlapping daily rolling basis, i.e., every day, rather than every n-days, are also discussed for regional and global applications.

  8. Comparison of C5 and C6 Aqua-MODIS Dark Target Aerosol Validation

    NASA Technical Reports Server (NTRS)

    Munchak, Leigh A.; Levy, Robert C.; Mattoo, Shana

    2014-01-01

    We compare C5 and C6 validation to compare the C6 10 km aerosol product against the well validated and trusted aerosol product on global and regional scales. Only the 10 km aerosol product is evaluated in this study, validation of the new C6 3 km aerosol product still needs to be performed. Not all of the time series has processed yet for C5 or C6, and the years processed for the 2 products is not exactly the same (this work is preliminary!). To reduce the impact of outlier observations, MODIS is spatially averaged within 27.5 km of the AERONET site, and AERONET is temporatally averaged within 30 minutes of the MODIS overpass time. Only high quality (QA = 3 over land, QA greater than 0 over ocean) pixels are included in the mean.

  9. Constraining canopy biophysical simulations with daily MODIS reflectance data ensuring pixel-target adequacy

    NASA Astrophysics Data System (ADS)

    Drewry, D.; Duveiller, G.

    2013-12-01

    Aqua platforms. As a whiskbroom imaging instrument, MODIS has a complex viewing geometry which affects its spatial response, i.e. the way the electromagnetic radiation reflected from the surface is ultimately encoded in the remotely-sensed image. A model of this spatial response is used here to ensure that the footprint of the satellite observations matches adequately with the coupled model simulations of the target fields. The relationship between the purity of the remote sensing observation, with respect to the target field, and the quality of the biophysical variable inversion is also investigated.

  10. Climatology and trends of aerosol optical depth over the Mediterranean basin during the last 12years (2002-2014) based on Collection 006 MODIS-Aqua data.

    PubMed

    Floutsi, A A; Korras-Carraca, M B; Matsoukas, C; Hatzianastassiou, N; Biskos, G

    2016-05-01

    The Mediterranean basin is a region of particular interest for studying atmospheric aerosols due to the large variety of air masses it receives, and its sensitivity to climate change. In this study we use the newest collection (C006) of aerosol optical depth from MODIS-Aqua, from which we also derived the fine-mode fraction and Ångström exponent over the last 12years (i.e., from 2002 to 2014), providing the longest analyzed dataset for this region. The long-term regional optical depth average is 0.20±0.05, with the indicated uncertainty reflecting the inter-annual variability. Overall, the aerosol optical depth exhibits a south-to-north decreasing gradient and an average decreasing trend of 0.0030 per year (19% total decrease over the study period). The correlation between the reported AOD observations with measurements from the ground AERONET stations is high (R=0.76-0.80 depending on the wavelength), with the MODIS-Aqua data being slightly overestimated. Both fine-fraction and Ångström exponent data highlight the dominance of anthropogenic aerosols over the northern, and of desert aerosols over the southern part of the region. Clear intrusions of desert dust over the Eastern Mediterranean are observed principally in spring, and in some cases in winter. Dust intrusions dominate the Western Mediterranean in the summer (and sometimes in autumn), whereas anthropogenic aerosols dominate the sub-region of the Black Sea in all seasons but especially during summer. Fine-mode optical depth is found to decrease over almost all areas of the study region during the 12-year period, marking the decreasing contribution of anthropogenic particulate matter emissions over the study area. Coarse-mode aerosol load also exhibits an overall decreasing trend. However, its decrease is smaller than that of fine aerosols and not as uniformly distributed, underlining that the overall decrease in the region arises mainly from reduced anthropogenic emissions. PMID:26878641

  11. Understanding Differences Between Co-Incident CloudSat, Aqua/MODIS and NOAA18 MHS Ice water Path Retrievals Over the Tropical Oceans

    NASA Technical Reports Server (NTRS)

    Pittman, Jasna; Robertson, Franklin; Blankenship, Clay

    2008-01-01

    Accurate measurement of the physical and radiative properties of clouds and their representation in climate models continues to be a challe nge. Model parameterizations are still subject to a large number of t unable parameters; furthermore, accurate and representative in situ o bservations are very sparse, and satellite observations historically have significant quantitative uncertainties, particularly with respect to particle size distribution (PSD) and cloud phase. Ice Water Path (IWP), or amount of ice present in a cloud column, is an important cl oud property to accurately quantify, because it is an integral measur e of the microphysical properties of clouds and the cloud feedback pr ocesses in the climate system. This paper investigates near co-incident retrievals of IWP over tropical oceans using three diverse measurem ent systems: radar from CloudSat, Vis/IR from Aqua/MODIS, and microwa ve from NOAA-18IMHS. CloudSat 94 GHz radar measurements provide high resolution vertical and along-orbit structure of cloud reflectivity a nd enable IWP (and IWC) retrievals. Overlapping MODIS measurements of cloud optical thickness and phase allow estimates of IWP when cloud tops are identified as being ice. Periodically, NOAA18 becomes co-inci dent in space I time to enable comparison of A-Train measurements to IWP inferred from the 157 and 89 GHz channel radiances. This latter m easurement is effective only for thick convective anvil systems. We s tratify these co-incident data (less than 4 minutes separation) into cirrus only, cirrus overlying liquid water clouds, and precipitating d eep convective clouds. Substantial biases in IWP and ice effective ra dius are found. Systematic differences in these retrievals are consid ered in light of the uncertainties in a priori assumptions ofPSDs, sp ectral sensitivity and algorithm strategies, which have a direct impact on the IWP product.

  12. Analysis of the influence of river discharge and wind on the Ebro turbid plume using MODIS-Aqua and MODIS-Terra data

    NASA Astrophysics Data System (ADS)

    Fernández-Nóvoa, D.; Mendes, R.; deCastro, M.; Dias, J. M.; Sánchez-Arcilla, A.; Gómez-Gesteira, M.

    2015-02-01

    The turbid plume formed at many river mouths influences the adjacent coastal area because it transports sediments, nutrients, and pollutants. The effects of the main forcings affecting the Ebro turbid plume were analyzed using data obtained from the Moderate Resolution Imaging Spectroradiometer (MODIS) sensor onboard the Aqua and Terra satellites over the period 2003-2011. Composite images were obtained for days under certain river discharge conditions (different flow regimes) and different types of wind (alongshore and cross-shore winds) in order to obtain a representative plume pattern for each situation. River discharge was the main driver of the Ebro River plume, followed by wind as the secondary force and regional oceanic circulation as the third one. Turbid plume extension increased monotonically with increased river discharge. Under high river discharge conditions (> 355 m3 s- 1), wind distributed the plume in the dominant wind direction. Seaward winds (mistral) produced the largest extension of the plume (1893 km2), whereas southern alongshore winds produced the smallest one (1325 km2). Northern alongshore winds induced the highest mean turbid value of the plume, and southern alongshore winds induced the lowest one. Regardless of the wind condition, more than 70% of the plume extension was located south of the river mouth influenced by the regional oceanic circulation.

  13. A surface reflectance scheme for retrieving aerosol optical depth over urban surfaces in MODIS Dark Target retrieval algorithm

    NASA Astrophysics Data System (ADS)

    Gupta, Pawan; Levy, Robert C.; Mattoo, Shana; Remer, Lorraine A.; Munchak, Leigh A.

    2016-07-01

    The MODerate resolution Imaging Spectroradiometer (MODIS) instruments, aboard the two Earth Observing System (EOS) satellites Terra and Aqua, provide aerosol information with nearly daily global coverage at moderate spatial resolution (10 and 3 km). Almost 15 years of aerosol data records are now available from MODIS that can be used for various climate and air-quality applications. However, the application of MODIS aerosol products for air-quality concerns is limited by a reduction in retrieval accuracy over urban surfaces. This is largely because the urban surface reflectance behaves differently than that assumed for natural surfaces. In this study, we address the inaccuracies produced by the MODIS Dark Target (MDT) algorithm aerosol optical depth (AOD) retrievals over urban areas and suggest improvements by modifying the surface reflectance scheme in the algorithm. By integrating MODIS Land Surface Reflectance and Land Cover Type information into the aerosol surface parameterization scheme for urban areas, much of the issues associated with the standard algorithm have been mitigated for our test region, the continental United States (CONUS). The new surface scheme takes into account the change in underlying surface type and is only applied for MODIS pixels with urban percentage (UP) larger than 20 %. Over the urban areas where the new scheme has been applied (UP > 20 %), the number of AOD retrievals falling within expected error (EE %) has increased by 20 %, and the strong positive bias against ground-based sun photometry has been eliminated. However, we note that the new retrieval introduces a small negative bias for AOD values less than 0.1 due to the ultra-sensitivity of the AOD retrieval to the surface parameterization under low atmospheric aerosol loadings. Global application of the new urban surface parameterization appears promising, but further research and analysis are required before global implementation.

  14. Spatial and Temporal Distribution of Tropospheric Clouds and Aerosols Observed by MODIS Onboard the Terra and Aqua Satellites

    NASA Technical Reports Server (NTRS)

    King, Michael D.; Platnick, Steven; Menzel, W. Paul; Ackerman, Steven A.; Remer, Lorraine A.

    2006-01-01

    Remote sensing of cloud and aerosol optical properties is routinely obtained using the Moderate Resolution Imaging Spectroradiometer (MODIS) onboard the Terra and Aqua satellites. Instruments that are being used to enhance our ability to characterize the global distribution of cloud and aerosol properties include well-calibrated multispectral radiometers that measure in the visible, near-infrared, and thermal infrared. The availability of thermal channels to enhance detection of cloud when estimating aerosol properties is an important improvement. In this paper, we describe the radiative properties of clouds as currently determined from satellites (cloud fraction, optical thickness, cloud top pressure, and cloud particle effective radius) and highlight the global/regional cloud microphysical properties currently available for assessing climate variability and forcing. These include the latitudinal distribution of cloud optical and radiative properties of both liquid water and ice clouds, as well as joint histograms of cloud optical thickness and effective particle radius for selected geographical locations around the world. In addition, we will illustrate the radiative and microphysical properties of aerosol particles (in cloud free regions) that are currently available from space-based observations, and show the latitudinal distribution of aerosol optical properties over both land and ocean surfaces.

  15. Contrail radiative forcing over the Northern Hemisphere from 2006 Aqua MODIS data

    NASA Astrophysics Data System (ADS)

    Spangenberg, Douglas A.; Minnis, Patrick; Bedka, Sarah T.; Palikonda, Rabindra; Duda, David P.; Rose, Fred G.

    2013-02-01

    Abstract Radiative forcing due to linear-shaped jet contrails is calculated over the Northern Hemisphere for four seasonal months using 2006 <span class="hlt">Aqua</span> Moderate-resolution Imaging Spectroradiometer cloud and contrail property retrieval data in a radiative transfer model. The 4 month mean shortwave, longwave, and net radiative forcings normalized to 100% contrail cover are -5.7, 14.2, and 8.5 Wm-2. Mean total net forcing over the northern half of the globe varies from 9.1 mW m-2 during October to 12.1 mW m-2 in January and is only representative at 01:30 and 13:30 LT in nonpolar regions. In some dense flight traffic corridors, the mean net forcing approaches 80 mW m-2. Scaling the 4 month average of 10.6 mW m-2 to the Southern Hemisphere air traffic yields global mean net forcing of 5.7 mW m-2, which is smaller than most model estimates. Nighttime net forcing is 3.6 times greater than during daytime, when net forcing is greatest over low clouds. Effects from contrail cirrus clouds that evolve from linear contrails are not considered in these results.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/20070017450','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20070017450"><span id="translatedtitle">A New Algorithm for Retrieving Aerosol Properties Over Land from <span class="hlt">MODIS</span> Spectral <span class="hlt">Reflectance</span></span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Levy, Robert C.; Remer, Lorraine A.; Mattoo, Shana; Vermote, Eric F.; Kaufman, Yoram J.</p> <p>2006-01-01</p> <p>Since first light in early 2000, operational global quantitative retrievals of aerosol properties over land have been made from <span class="hlt">MODIS</span> observed spectral <span class="hlt">reflectance</span>. These products have been continuously evaluated and validated, and opportunities for improvements have been noted. We have replaced the original algorithm by improving surface <span class="hlt">reflectance</span> assumptions, the aerosol model optical properties and the radiative transfer code used to create the lookup tables. The new algorithm (known as Version 5.2 or V5.2) performs a simultaneous inversion of two visible (0.47 and 0.66 micron) and one shortwave-IR (2.12 micron) channel, making use of the coarse aerosol information content contained in the 2.12 micron channel. Inversion of the three channels yields three nearly independent parameters, the aerosol optical depth (tau) at 0.55 micron, the non-dust or fine weighting (eta) and the surface <span class="hlt">reflectance</span> at 2.12 micron. Finally, retrievals of small magnitude negative tau values (down to -0.05) are considered valid, thus normalizing the statistics of tau in near zero tau conditions. On a 'test bed' of 6300 granules from Terra and <span class="hlt">Aqua</span>, the products from V5.2 show marked improvement over those from the previous versions, including much improved retrievals of tau, where the <span class="hlt">MODIS</span>/AERONET tau (at 0.55 micron) regression has an equation of: y = 1.01+0.03, R = 0.90. Mean tau for the test bed is reduced from 0.28 to 0.21.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2003AGUFM.H32B0562G','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2003AGUFM.H32B0562G"><span id="translatedtitle">Exploring the feasibility of using the <span class="hlt">MODIS</span> 1 km by 1 km cloud mask product to generate a lower resolution product suitable for use with other instruments (e.g AIRS) on the EOS-<span class="hlt">Aqua</span> satellite.</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Gopalan, A.; Leptoukh, G.; Savtchenko, A.; Ouzounov, D.</p> <p>2003-12-01</p> <p>The <span class="hlt">MODIS</span> Level-2 Cloud Mask Products MOD35_L2 (<span class="hlt">MODIS</span> -TERRA) and MYD35_L2 (<span class="hlt">MODIS-AQUA</span>) are available globally day and night at a pixel resolution of 1 km by 1 km. The cloud mask is based on a series of spectral cloud detection tests and estimates the probability of a pixel being clear with varying degrees of confidence (Platnick et al). We attempt to explore the possibility of adapting the <span class="hlt">MODIS</span> Cloud Mask Product to other instruments on the Terra and <span class="hlt">Aqua</span> Satellites that have a coarser pixel resolution as compared to the <span class="hlt">MODIS</span> pixel. From a data center (e.g. GES-DAAC) perspective, this could potentially have a positive impact on the distribution system and better serve end users who require a lower resolution cloud mask product for their applications.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2016ISPAr41B7..219F','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2016ISPAr41B7..219F"><span id="translatedtitle">Global Land Cover Classification Using <span class="hlt">Modis</span> Surface <span class="hlt">Reflectance</span> Prosucts</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Fukue, Kiyonari; Shimoda, Haruhisa</p> <p>2016-06-01</p> <p>The objective of this study is to develop high accuracy land cover classification algorithm for Global scale by using multi-temporal <span class="hlt">MODIS</span> land <span class="hlt">reflectance</span> products. In this study, time-domain co-occurrence matrix was introduced as a classification feature which provides time-series signature of land covers. Further, the non-parametric minimum distance classifier was introduced for timedomain co-occurrence matrix, which performs multi-dimensional pattern matching for time-domain co-occurrence matrices of a classification target pixel and each classification classes. The global land cover classification experiments have been conducted by applying the proposed classification method using 46 multi-temporal(in one year) SR(Surface <span class="hlt">Reflectance</span>) and NBAR(Nadir BRDF-Adjusted <span class="hlt">Reflectance</span>) products, respectively. IGBP 17 land cover categories were used in our classification experiments. As the results, SR and NBAR products showed similar classification accuracy of 99%.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/20120015718','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20120015718"><span id="translatedtitle">Accuracy Assessment of <span class="hlt">Aqua-MODIS</span> Aerosol Optical Depth Over Coastal Regions: Importance of Quality Flag and Sea Surface Wind Speed</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Anderson, J. C.; Wang, J.; Zeng, J.; Petrenko, M.; Leptoukh, G. G.; Ichoku, C.</p> <p>2012-01-01</p> <p>Coastal regions around the globe are a major source for anthropogenic aerosols in the atmosphere, but the underlying surface characteristics are not favorable for the Moderate Resolution Imaging Spectroradiometer (<span class="hlt">MODIS</span>) algorithms designed for retrieval of aerosols over dark land or open-ocean surfaces. Using data collected from 62 coastal stations worldwide from the Aerosol Robotic Network (AERONET) from approximately 2002-2010, accuracy assessments are made for coastal aerosol optical depth (AOD) retrieved from <span class="hlt">MODIS</span> aboard <span class="hlt">Aqua</span> satellite. It is found that coastal AODs (at 550 nm) characterized respectively by the <span class="hlt">MODIS</span> Dark Land (hereafter Land) surface algorithm, the Open-Ocean (hereafter Ocean) algorithm, and AERONET all exhibit a log-normal distribution. After filtering by quality flags, the <span class="hlt">MODIS</span> AODs respectively retrieved from the Land and Ocean algorithms are highly correlated with AERONET (with R(sup 2) is approximately equal to 0.8), but only the Land algorithm AODs fall within the expected error envelope greater than 66% of the time. Furthermore, the <span class="hlt">MODIS</span> AODs from the Land algorithm, Ocean algorithm, and combined Land and Ocean product show statistically significant discrepancies from their respective counterparts from AERONET in terms of mean, probability density function, and cumulative density function, which suggest a need for future improvement in retrieval algorithms. Without filtering with quality flag, the <span class="hlt">MODIS</span> Land and Ocean AOD dataset can be degraded by 30-50% in terms of mean bias. Overall, the <span class="hlt">MODIS</span> Ocean algorithm overestimates the AERONET coastal AOD by 0.021 for AOD less than 0.25 and underestimates it by 0.029 for AOD greater than 0.25. This dichotomy is shown to be related to the ocean surface wind speed and cloud contamination effects on the satellite aerosol retrieval. The Modern Era Retrospective-Analysis for Research and Applications (MERRA) reveals that wind speeds over the global coastal region 25 (with a mean and median</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/cgi-bin/nph-data_query?bibcode=2016JARS...10.4004C&link_type=ABSTRACT','NASAADS'); return false;" href="http://adsabs.harvard.edu/cgi-bin/nph-data_query?bibcode=2016JARS...10.4004C&link_type=ABSTRACT"><span id="translatedtitle">Alternative method of on-orbit response-versus-scan-angle characterization for <span class="hlt">MODIS</span> <span class="hlt">reflective</span> solar bands</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Chen, Hongda; Xiong, Xiaoxiong; Angal, Amit; Geng, Xu; Wu, Aisheng</p> <p>2016-04-01</p> <p>The moderate resolution imaging spectroradiometer (<span class="hlt">MODIS</span>) has 20 <span class="hlt">reflective</span> solar bands (RSB), covering a spectral range from 0.41 to 2.2 μm, which are calibrated on-orbit using its onboard calibrators, which include a solar diffuser, a solar diffuser stability monitor, and a spectroradiometric calibration assembly. A space view (SV) port is used to provide a background reference and also facilitates near-monthly lunar observations through a spacecraft roll. In every scan, the Earth's surface, SV, and onboard calibrators are viewed via a two-sided scan mirror, the <span class="hlt">reflectance</span> of which depends on the angle of incidence (AOI) as well as the wavelength of the incident light. Response-versus-scan-angle (RVS) is defined as a dependence function of the scan mirror's <span class="hlt">reflectance</span> over AOI. An initial RVS for each RSB was measured prelaunch for both Terra and <span class="hlt">Aqua</span> <span class="hlt">MODIS</span>. Algorithms have been developed to track the on-orbit RVS variation using the measurements from the onboard calibrators, supplemented with the earth view (EV) trends from pseudoinvariant desert targets obtained at different AOI. Since the mission beginning, the <span class="hlt">MODIS</span> characterization support team (MCST) has dedicated efforts in evaluating approaches of characterizing the on-orbit RVS. A majority of the approaches focused on fitting the data at each AOI over time and then deriving the relative change at different AOI. The current version of the on-orbit RVS algorithm, as implemented in the collection 6 (C6) level-1B (L1B), is also based on the above rationale. It utilizes the EV response trends from the pseudoinvariant Libyan desert targets to supplement the gain derived from the onboard calibrators. The primary limitation of this approach is the assumption of the temporal stability of these desert sites. Consequently, MCST developed an approach that derives the on-orbit RVS change using measurements from a single desert site, combined with the on-orbit lunar measurements. In addition, the EV and onboard</p> </li> </ol> <div class="pull-right"> <ul class="pagination"> <li><a href="#" onclick='return showDiv("page_1");'>«</a></li> <li><a href="#" onclick='return showDiv("page_3");'>3</a></li> <li><a href="#" onclick='return showDiv("page_4");'>4</a></li> <li class="active"><span>5</span></li> <li><a href="#" onclick='return showDiv("page_6");'>6</a></li> <li><a href="#" onclick='return showDiv("page_7");'>7</a></li> <li><a href="#" onclick='return showDiv("page_25");'>»</a></li> </ul> </div> </div><!-- col-sm-12 --> </div><!-- row --> </div><!-- page_5 --> <div id="page_6" class="hiddenDiv"> <div class="row"> <div class="col-sm-12"> <div class="pull-right"> <ul class="pagination"> <li><a href="#" onclick='return showDiv("page_1");'>«</a></li> <li><a href="#" onclick='return showDiv("page_4");'>4</a></li> <li><a href="#" onclick='return showDiv("page_5");'>5</a></li> <li class="active"><span>6</span></li> <li><a href="#" onclick='return showDiv("page_7");'>7</a></li> <li><a href="#" onclick='return showDiv("page_8");'>8</a></li> <li><a href="#" onclick='return showDiv("page_25");'>»</a></li> </ul> </div> </div> </div> <div class="row"> <div class="col-sm-12"> <ol class="result-class" start="101"> <li> <p><a target="_blank" onclick="trackOutboundLink('http://ntrs.nasa.gov/search.jsp?R=20160008400&hterms=methods&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D30%26Ntt%3Dmethods','NASA-TRS'); return false;" href="http://ntrs.nasa.gov/search.jsp?R=20160008400&hterms=methods&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D30%26Ntt%3Dmethods"><span id="translatedtitle">Alternative Method of On-Orbit Response-Versus-Scan-Angle Characterization for <span class="hlt">MODIS</span> <span class="hlt">Reflective</span> Solar Bands</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Chen, Hongda; Xiong, Xiaoxiong; Angal, Amit; Geng, Xu; Wu, Aisheng</p> <p>2016-01-01</p> <p>The moderate resolution imaging spectroradiometer (<span class="hlt">MODIS</span>) has 20 <span class="hlt">reflective</span> solar bands (RSB), covering a spectral range from 0.41 to 2.2 microns, which are calibrated on-orbit using its onboard calibrators, which include a solar diffuser, a solar diffuser stability monitor, and a spectroradiometric calibration assembly. A space view (SV) port is used to provide a background reference and also facilitates near-monthly lunar observations through a spacecraft roll. In every scan, the Earth's surface, SV, and onboard calibrators are viewed via a two-sided scan mirror, the <span class="hlt">reflectance</span> of which depends on the angle of incidence (AOI) as well as the wavelength of the incident light. Response-versus-scan-angle (RVS) is defined as a dependence function of the scan mirror's <span class="hlt">reflectance</span> over AOI. An initial RVS for each RSB was measured prelaunch for both Terra and <span class="hlt">Aqua</span> <span class="hlt">MODIS</span>. Algorithms have been developed to track the on-orbit RVS variation using the measurements from the onboard calibrators, supplemented with the earth view (EV) trends from pseudoinvariant desert targets obtained at different AOI. Since the mission beginning, the <span class="hlt">MODIS</span> characterization support team (MCST) has dedicated efforts in evaluating approaches of characterizing the on-orbit RVS. A majority of the approaches focused on fitting the data at each AOI over time and then deriving the relative change at different AOI. The current version of the on-orbit RVS algorithm, as implemented in the collection 6 (C6) level-1B (L1B), is also based on the above rationale. It utilizes the EV response trends from the pseudoinvariant Libyan desert targets to supplement the gain derived from the onboard calibrators. The primary limitation of this approach is the assumption of the temporal stability of these desert sites. Consequently, MCST developed an approach that derives the on-orbit RVS change using measurements from a single desert site, combined with the on-orbit lunar measurements. In addition, the EV and onboard</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2013AGUSM.B51A..02D','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2013AGUSM.B51A..02D"><span id="translatedtitle">Constraining canopy biophysical simulations with <span class="hlt">MODIS</span> <span class="hlt">reflectance</span> data</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Drewry, D. T.; Duveiller, G.</p> <p>2013-05-01</p> <p>Modern vegetation models incorporate ecophysiological details that allow for accurate estimates of carbon dioxide uptake, water use and energy exchange, but require knowledge of dynamic structural and biochemical traits. Variations in these traits are controlled by genetic factors as well as growth stage and nutrient and moisture availability, making them difficult to predict and prone to significant error. Here we explore the use of <span class="hlt">MODIS</span> optical <span class="hlt">reflectance</span> data for constraining key canopy- and leaf-level traits required by forward biophysical models. A multi-objective optimization algorithm is used to invert the PROSAIL canopy radiation transfer model, which accounts for the effects of leaf-level optical properties, foliage distribution and orientation on canopy <span class="hlt">reflectance</span> across the optical range. Inversions are conducted for several growing seasons for both soybean and maize at several sites in the Central US agro-ecosystem. These inversions provide estimates of seasonal variations, and associated uncertainty, of variables such as leaf area index (LAI) that are then used as inputs into the MLCan biophysical model to conduct forward simulations. MLCan characterizes the ecophysiological functioning of a plant canopy at a half-hourly timestep, and has been rigorously validated for both C3 and C4 crops against observations of canopy CO2 uptake, evapotranspiration and sensible heat exchange across a wide range of meteorological conditions. The inversion-derived canopy properties are used to examine the ability of <span class="hlt">MODIS</span> data to characterize seasonal variations in canopy properties in the context of a detailed forward canopy biophysical model, and the uncertainty induced in forward model estimates as a function of the uncertainty in the inverted parameters. Special care is made to ensure that the satellite observations match adequately, in both time and space, with the coupled model simulations. To do so, daily <span class="hlt">MODIS</span> observations are used and a validated model of</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/cgi-bin/nph-data_query?bibcode=2012ACPD...1211733Z&link_type=ABSTRACT','NASAADS'); return false;" href="http://adsabs.harvard.edu/cgi-bin/nph-data_query?bibcode=2012ACPD...1211733Z&link_type=ABSTRACT"><span id="translatedtitle">A better understanding of cloud optical thickness derived from the passive sensors <span class="hlt">MODIS/AQUA</span> and POLDER/PARASOL in the A-train constellation</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Zeng, S.; Cornet, C.; Parol, F.; Riedi, J.; Thieuleux, F.</p> <p>2012-05-01</p> <p>Cloud optical thickness (COT) is one of the most important parameter for the characterization of cloud in the Earth radiative budget. Its retrieval strongly depends on instrument characteristics and on many cloud and environment factors. Using coincident observations from POLDER/PARASOL and <span class="hlt">MODIS/AQUA</span> in the A-train constellation, geographical distributions and seasonal changes of COT are presented, in good agreement with general cloud climatology characteristics. Retrieval uncertainties mainly associated to sensor spatial resolution, cloud inhomogeneity and microphysical assumptions are also discussed. Comparisons of COT derived from POLDER and <span class="hlt">MODIS</span> illustrate that as the primary factor, the sensor spatial resolution impacts COT retrievals and statistics through both cloud detection and sub-pixel cloud inhomogeneity sensitivity. The uncertainties associated to cloud microphysics assumptions, namely cloud phase, particle size and shape, also impact significantly COT retrievals. For clouds with unambiguous cloud phase, strong correlations exist between the two COTs, with <span class="hlt">MODIS</span> values comparable to POLDER ones for liquid clouds and <span class="hlt">MODIS</span> values larger than POLDER ones for ice clouds. The large differences observed in ice phase cases are due to the use of different microphysical models in the two retrieval schemes. In cases when the two sensors disagree on cloud phase decision, COT retrieved assuming liquid phase are systematically larger. The angular biases related to specific observation geometries are also quantified and discussed in particular based on POLDER observations. Those exhibit a clear increase of COT with decreasing sun elevation and a decrease of COT in forward scattering directions due to sub-pixel inhomogeneities and shadowing effects, this especially for lower sun. It also demonstrates unrealistic COT variations in the rainbow and backward directions due to inappropriate cloud optical properties representation and an important increase of COT in the</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=4554528','PMC'); return false;" href="http://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=4554528"><span id="translatedtitle">Spatio-Temporal Variations in the Associations between Hourly PM2.5 and Aerosol Optical Depth (AOD) from <span class="hlt">MODIS</span> Sensors on Terra and <span class="hlt">Aqua</span>*</span></a></p> <p><a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pmc">PubMed Central</a></p> <p>Kim, Minho; Zhang, Xingyou; Holt, James B.; Liu, Yang</p> <p>2015-01-01</p> <p>Recent studies have explored the relationship between aerosol optical depth (AOD) measurements by satellite sensors and concentrations of particulate matter with aerodynamic diameters less than 2.5 μm (PM2.5). However, relatively little is known about spatial and temporal patterns in this relationship across the contiguous United States. In this study, we investigated the relationship between US Environmental Protection Agency estimates of PM2.5 concentrations and Moderate Resolution Imaging Spectroradiometer (<span class="hlt">MODIS</span>) AOD measurements provided by two NASA satellites (Terra and <span class="hlt">Aqua</span>) across the contiguous United States during 2005. We found that the combined use of both satellite sensors provided more AOD coverage than the use of either satellite sensor alone, that the correlation between AOD measurements and PM2.5 concentrations varied substantially by geographic location, and that this correlation was stronger in the summer and fall than that in the winter and spring. PMID:26336576</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://ntrs.nasa.gov/search.jsp?R=20120010478&hterms=snow&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D80%26Ntt%3Dsnow','NASA-TRS'); return false;" href="http://ntrs.nasa.gov/search.jsp?R=20120010478&hterms=snow&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D80%26Ntt%3Dsnow"><span id="translatedtitle">An Algorithm for the Retrieval of 30-m Snow-Free Albedo from Landsat Surface <span class="hlt">Reflectance</span> and <span class="hlt">MODIS</span> BRDF</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Shuai, Yanmin; Masek, Jeffrey G.; Gao, Feng; Schaaf, Crystal B.</p> <p>2011-01-01</p> <p>We present a new methodology to generate 30-m resolution land surface albedo using Landsat surface <span class="hlt">reflectance</span> and anisotropy information from concurrent <span class="hlt">MODIS</span> 500-m observations. Albedo information at fine spatial resolution is particularly useful for quantifying climate impacts associated with land use change and ecosystem disturbance. The derived white-sky and black-sky spectral albedos maybe used to estimate actual spectral albedos by taking into account the proportion of direct and diffuse solar radiation arriving at the ground. A further spectral-to-broadband conversion based on extensive radiative transfer simulations is applied to produce the broadband albedos at visible, near infrared, and shortwave regimes. The accuracy of this approach has been evaluated using 270 Landsat scenes covering six field stations supported by the SURFace RADiation Budget Network (SURFRAD) and Atmospheric Radiation Measurement Southern Great Plains (ARM/SGP) network. Comparison with field measurements shows that Landsat 30-m snow-free shortwave albedos from all seasons generally achieve an absolute accuracy of +/-0.02 - 0.05 for these validation sites during available clear days in 2003-2005,with a root mean square error less than 0.03 and a bias less than 0.02. This level of accuracy has been regarded as sufficient for driving global and regional climate models. The Landsat-based retrievals have also been compared to the operational 16-day <span class="hlt">MODIS</span> albedo produced every 8-days from <span class="hlt">MODIS</span> on Terra and <span class="hlt">Aqua</span> (MCD43A). The Landsat albedo provides more detailed landscape texture, and achieves better agreement (correlation and dynamic range) with in-situ data at the validation stations, particularly when the stations include a heterogeneous mix of surface covers.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2008SPIE.7081E..0AC','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2008SPIE.7081E..0AC"><span id="translatedtitle">On-orbit <span class="hlt">aqua</span> <span class="hlt">MODIS</span> modulation transfer function trending in along-scan from the Spectro-Radiometric Calibration Assembly</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Choi, Taeyoung; Che, Nianzeng; Xiong, Xiaoxiong</p> <p>2008-08-01</p> <p>The Spectro-Radiometric Calibration Assembly (SRCA) is one of the on-board calibrators for the <span class="hlt">MODIS</span> instrument. The SRCA is operated in three modes: spectral, spatial, and radiometric. The spatial mode is used to track the changes in band-to-band registration both along-scan (band and detector) and along-track (band) and the MTF in the along-scan direction for all 36 <span class="hlt">MODIS</span> bands over the <span class="hlt">MODIS</span> lifetime. In the SRCA spatial mode, a rectangular knife-edge reticle, located at the focus of the SRCA collimator, is imaged onto four <span class="hlt">MODIS</span> Focal Plane Assemblies (FPA). The reticle is illuminated by a spherical integration sphere and a glow-bar so that all bands can have an appropriate signal level. When the <span class="hlt">MODIS</span> scan mirror rotates, the illuminated knife-edge scans across the bands/detectors. In addition, there are five electronic phase-delays so that the sampling spacing is reduced to 1/5 of the detector size, which results in dense data points. After combining detector responses from all phase-delays, a combined bell-shaped response profile is formed. The derivative of the detector response to the knife-edge is the Line Spread Function (LSF). In the frequency domain, the Modulation Transfer Functions (MTF) are calculated from the normalized Fourier transform of the LSF. The MTF results from the SRCA are validated by the pre-launch results from the Integrated Alignment Collimator (IAC) and a SRCA collection performed in the Thermal Vacuum (TV). The six-year plus on-orbit MTF trending results show very stable responses in the VIS and NIR FPAs, and meet the design specifications. Although there are noticeable MTF degradations over the instrument lifetime in bands 1 and 2, they are negligible with the large specification margins. In addition, a similar relationship is found between the band locations in the VIS and NIR FPAs versus MTF values.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://www.youtube.com/watch?v=P0uVV40Y2Pc','SCIGOVIMAGE-NASA'); return false;" href="http://www.youtube.com/watch?v=P0uVV40Y2Pc"><span id="translatedtitle"><span class="hlt">Aqua</span> satellite orbiting the Earth</span></a></p> <p><a target="_blank" href="http://www.nasa.gov/multimedia/videogallery/index.html">NASA Video Gallery</a></p> <p></p> <p></p> <p>This animation shows the <span class="hlt">Aqua</span> satellite orbiting the Earth on August 27, 2005 by revealing <span class="hlt">MODIS</span> true-color imagery for that day. This animation is on a cartesian map projection, so the satellite w...</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://www.ars.usda.gov/research/publications/publication/?seqNo115=328370','TEKTRAN'); return false;" href="http://www.ars.usda.gov/research/publications/publication/?seqNo115=328370"><span id="translatedtitle">Compositing <span class="hlt">MODIS</span> Terra and <span class="hlt">Aqua</span> 250m daily surface <span class="hlt">reflectance</span> data sets for vegetation monitoring</span></a></p> <p><a target="_blank" href="http://www.ars.usda.gov/services/TekTran.htm">Technology Transfer Automated Retrieval System (TEKTRAN)</a></p> <p></p> <p></p> <p>Remote sensing based vegetation Indices have been proven valuable in providing a spatially complete view of crop’s vegetation condition, which also manifests the impact of the disastrous events such as massive flood and drought. VegScape, a web GIS application for crop vegetation condition monitorin...</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2013EGUGA..15..705G','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2013EGUGA..15..705G"><span id="translatedtitle">Inter-annual variability of aerosol optical depth over the tropical Atlantic Ocean based on <span class="hlt">MODIS-Aqua</span> observations over the period 2002-2012</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Gkikas, Antonis; Hatzianastassiou, Nikolaos</p> <p>2013-04-01</p> <p>The tropical Atlantic Ocean is affected by dust and biomass burning aerosol loads transported from the western parts of the Saharan desert and the sub-Sahel regions, respectively. The spatial and temporal patterns of this transport are determined by the aerosol emission rates, their deposition (wet and dry), by the latitudinal shift of the Intertropical Convergence Zone (ITCZ) and the prevailing wind fields. More specifically, in summer, Saharan dust aerosols are transported towards the Atlantic Ocean, even reaching the Gulf of Mexico, while in winter the Atlantic Ocean transport takes place in more southern latitudes, near the equator, sometimes reaching the northern parts of South America. In the later case, dust is mixed with biomass burning aerosols originating from agricultural activities in the sub-Sahel, associated with prevailing north-easterly airflow (Harmattan winds). Satellite observations are the appropriate tool for describing this African aerosol export, which is important to atmospheric, oceanic and climate processes, offering the advantage of complete spatial coverage. In the present study, we use satellite measurements of aerosol optical depth at 550nm (AOD550nm), on a daily and monthly basis, derived from <span class="hlt">MODIS-Aqua</span> platform, at 1ox1o spatial resolution (Level 3), for the period 2002-2012. The primary objective is to determine the pixel-level and regional mean anomalies of AOD550nm over the entire study period. The regime of the anomalies of African export is interpreted in relation to the aerosol source areas, precipitation, wind patterns and temporal variability of the North Atlantic Oscillation Index (NAOI). In order to ensure availability of AOD over the Sahara desert, <span class="hlt">MODIS-Aqua</span> Deep Blue products are also used. As for precipitation, Global Precipitation Climatology Project (GPCP) data at 2.5ox2.5o are used. The wind fields are taken from the National Center for Environmental Prediction (NCEP). Apart from the regime of African aerosol export</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/20110023376','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20110023376"><span id="translatedtitle"><span class="hlt">MODIS</span> Radiometric Calibration and Uncertainty Assessment</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Xiong, Xiaoxiong; Chiang, Vincent; Sun, Junqiang; Wu, Aisheng</p> <p>2011-01-01</p> <p>Since launch, Terra and <span class="hlt">Aqua</span> <span class="hlt">MODIS</span> have collected more than II and 9 years of datasets for comprehensive studies of the Earth's land, ocean, and atmospheric properties. <span class="hlt">MODIS</span> observations are made in 36 spectral bands: 20 <span class="hlt">reflective</span> solar bands (RSB) and 16 thermal emissive bands (TEB). Compared to its heritage sensors, <span class="hlt">MODIS</span> was developed with very stringent calibration and uncertainty requirements. As a result, <span class="hlt">MODIS</span> 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, <span class="hlt">MODIS</span> RSB calibration is <span class="hlt">reflectance</span> 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 <span class="hlt">MODIS</span> calibration methodologies and discusses details of its on-orbit calibration uncertainties. It assesses uncertainty contributions from individual components and differences between Terra and <span class="hlt">Aqua</span> <span class="hlt">MODIS</span> due to their design characteristics and on-orbit periormance. Also discussed in this paper is the use of <span class="hlt">MODIS</span> LIB uncertainty index CUI) product.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/20140013366','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20140013366"><span id="translatedtitle">Multitemporal Cross-Calibration of the Terra <span class="hlt">MODIS</span> and Landsat 7 ETM+ <span class="hlt">Reflective</span> Solar Bands</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Angal, Amit; Xiong, Xiaoxiong; Wu, Aisheng; Changler, Gyanesh; Choi, Taeyoyung</p> <p>2013-01-01</p> <p>In recent years, there has been a significant increase in the use of remotely sensed data to address global issues. With the open data policy, the data from the Moderate Resolution Imaging Spectroradiometer (<span class="hlt">MODIS</span>) and Enhanced Thematic Mapper Plus (ETM+) sensors have become a critical component of numerous applications. These two sensors have been operational for more than a decade, providing a rich archive of multispectral imagery for analysis of mutitemporal remote sensing data. This paper focuses on evaluating the radiometric calibration agreement between <span class="hlt">MODIS</span> and ETM+ using the near-simultaneous and cloud-free image pairs over an African pseudo-invariant calibration site, Libya 4. To account for the combined uncertainties in the top-of-atmosphere (TOA) <span class="hlt">reflectance</span> due to surface and atmospheric bidirectional <span class="hlt">reflectance</span> distribution function (BRDF), a semiempirical BRDF model was adopted to normalize the TOA <span class="hlt">reflectance</span> to the same illumination and viewing geometry. In addition, the spectra from the Earth Observing-1 (EO-1) Hyperion were used to compute spectral corrections between the corresponding <span class="hlt">MODIS</span> and ETM+ spectral bands. As EO-1 Hyperion scenes were not available for all <span class="hlt">MODIS</span> and ETM+ data pairs, MODerate resolution atmospheric TRANsmission (MODTRAN) 5.0 simulations were also used to adjust for differences due to the presence or lack of absorption features in some of the bands. A <span class="hlt">MODIS</span> split-window algorithm provides the atmospheric water vapor column abundance during the overpasses for the MODTRAN simulations. Additionally, the column atmospheric water vapor content during the overpass was retrieved using the <span class="hlt">MODIS</span> precipitable water vapor product. After performing these adjustments, the radiometric cross-calibration of the two sensors was consistent to within 7%. Some drifts in the response of the bands are evident, with <span class="hlt">MODIS</span> band 3 being the largest of about 6% over 10 years, a change that will be corrected in Collection 6 <span class="hlt">MODIS</span> processing.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2006SPIE.6296E..12D','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2006SPIE.6296E..12D"><span id="translatedtitle">Validation of large-footprint <span class="hlt">reflectance</span>-based calibration using coincident <span class="hlt">MODIS</span> and ASTER data</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>D'Amico, J.; Thome, K.; Czapla-Myers, J.</p> <p>2006-08-01</p> <p>The Remote Sensing Group at the University of Arizona has been using <span class="hlt">reflectance</span>-based vicarious calibration of earth-observing satellites since the 1980s. Among the sensors characterized by the group are the Advanced Spaceborne Thermal Emission and <span class="hlt">Reflection</span> Radiometer (ASTER) and the MODerate Resolution Imaging Spectroradiometer (<span class="hlt">MODIS</span>) that are both on NASA's Terra platform. The spatial resolution of <span class="hlt">MODIS</span> requires that the group use a large-sized site such as Railroad Valley Playa, Nevada as a test site. In addition, the large footprint size of <span class="hlt">MODIS</span> forced a modification to the ground-sampling scheme for the surface <span class="hlt">reflectance</span> retrieval. This work examines the impact of the new sampling scheme through coincident ASTER and <span class="hlt">MODIS</span> imagery making use of the higher resolution spatial resolution of ASTER. ASTER and <span class="hlt">MODIS</span> imagery were obtained for dates on which both sensors imaged the Railroad Valley test site and ground-based data were collected at the site. The results of the comparison between the sensors shows differences in the radiometric calibration that exceed the accuracy requirements of the sensors, but that the sampling strategy for large-footprint sensors produces <span class="hlt">reflectance</span>-based results at the same 3% level of accuracy as that for small-footprint sensors.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/20130014484','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20130014484"><span id="translatedtitle">Comparison Between NPP-VIIRS Aerosol Data Products and the <span class="hlt">MODIS</span> <span class="hlt">AQUA</span> Deep Blue Collection 6 Dataset Over Land</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Sayer, Andrew M.; Hsu, N. C.; Bettenhausen, C.; Lee, J.; Kondragunta, S.</p> <p>2013-01-01</p> <p>Aerosols are small particles suspended in the atmosphere and have a variety of natural and man-made sources. Knowledge of aerosol optical depth (AOD), which is a measure of the amount of aerosol in the atmosphere, and its change over time, is important for multiple reasons. These include climate change, air quality (pollution) monitoring, monitoring hazards such as dust storms and volcanic ash, monitoring smoke from biomass burning, determining potential energy yields from solar plants, determining visibility at sea, estimating fertilization of oceans and rainforests by transported mineral dust, understanding changes in weather brought upon by the interaction of aerosols and clouds, and more. The Suomi-NPP satellite was launched late in 2011. The Visible Infrared Imaging Radiometer Suite (VIIRS) aboard Suomi-NPP is being used, among other things, to determine AOD. This study compares the VIIRS dataset to ground-based measurements of AOD, along with a state-of-the-art satellite AOD dataset (the new version of the Moderate Resolution Imaging Spectrometer Deep Blue algorithm) to assess its reliability. The Suomi-NPP satellite was launched late in 2011, carrying several instruments designed to continue the biogeophysical data records of current and previous satellite sensors. The Visible Infrared Imaging Radiometer Suite (VIIRS) aboard Suomi-NPP is being used, among other things, to determine aerosol optical depth (AOD), and related activities since launch have been focused towards validating and understanding this new dataset through comparisons with other satellite and ground-based products. The operational VIIRS AOD product is compared over land with AOD derived from Moderate Resolution Imaging Spectrometer (<span class="hlt">MODIS</span>) observations using the Deep Blue (DB) algorithm from the forthcoming Collection 6 of <span class="hlt">MODIS</span> data</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/20110008491','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20110008491"><span id="translatedtitle">Biomass Burning Aerosol Absorption Measurements with <span class="hlt">MODIS</span> Using the Critical <span class="hlt">Reflectance</span> Method</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Zhu, Li; Martins, Vanderlei J.; Remer, Lorraine A.</p> <p>2010-01-01</p> <p>This research uses the critical <span class="hlt">reflectance</span> technique, a space-based remote sensing method, to measure the spatial distribution of aerosol absorption properties over land. Choosing two regions dominated by biomass burning aerosols, a series of sensitivity studies were undertaken to analyze the potential limitations of this method for the type of aerosol to be encountered in the selected study areas, and to show that the retrieved results are relatively insensitive to uncertainties in the assumptions used in the retrieval of smoke aerosol. The critical <span class="hlt">reflectance</span> technique is then applied to Moderate Resolution Imaging Spectrometer (<span class="hlt">MODIS</span>) data to retrieve the spectral aerosol single scattering albedo (SSA) in South African and South American 35 biomass burning events. The retrieved results were validated with collocated Aerosol Robotic Network (AERONET) retrievals. One standard deviation of mean <span class="hlt">MODIS</span> retrievals match AERONET products to within 0.03, the magnitude of the AERONET uncertainty. The overlap of the two retrievals increases to 88%, allowing for measurement variance in the <span class="hlt">MODIS</span> retrievals as well. The ensemble average of <span class="hlt">MODIS</span>-derived SSA for the Amazon forest station is 0.92 at 670 nm, and 0.84-0.89 for the southern African savanna stations. The critical <span class="hlt">reflectance</span> technique allows evaluation of the spatial variability of SSA, and shows that SSA in South America exhibits higher spatial variation than in South Africa. The accuracy of the retrieved aerosol SSA from <span class="hlt">MODIS</span> data indicates that this product can help to better understand 44 how aerosols affect the regional and global climate.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/20140010301','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20140010301"><span id="translatedtitle">The Normalization of Surface Anisotropy Effects Present in SEVIRI <span class="hlt">Reflectances</span> by Using the <span class="hlt">MODIS</span> BRDF Method</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Proud, Simon Richard; Zhang, Qingling; Schaaf, Crystal; Fensholt, Rasmus; Rasmussen, Mads Olander; Shisanya, Chris; Mutero, Wycliffe; Mbow, Cheikh; Anyamba, Assaf; Pak, Ed; Sandholt, Inge</p> <p>2014-01-01</p> <p>A modified version of the MODerate resolution Imaging Spectroradiometer (<span class="hlt">MODIS</span>) bidirectional <span class="hlt">reflectance</span> distribution function (BRDF) algorithm is presented for use in the angular normalization of surface <span class="hlt">reflectance</span> data gathered by the Spinning Enhanced Visible and InfraRed Imager (SEVIRI) aboard the geostationary Meteosat Second Generation (MSG) satellites. We present early and provisional daily nadir BRDFadjusted <span class="hlt">reflectance</span> (NBAR) data in the visible and near-infrared MSG channels. These utilize the high temporal resolution of MSG to produce BRDF retrievals with a greatly reduced acquisition period than the comparable <span class="hlt">MODIS</span> products while, at the same time, removing many of the angular perturbations present within the original MSG data. The NBAR data are validated against <span class="hlt">reflectance</span> data from the <span class="hlt">MODIS</span> instrument and in situ data gathered at a field location in Africa throughout 2008. It is found that the MSG retrievals are stable and are of high-quality across much of the SEVIRI disk while maintaining a higher temporal resolution than the <span class="hlt">MODIS</span> BRDF products. However, a number of circumstances are discovered whereby the BRDF model is unable to function correctly with the SEVIRI observations-primarily because of an insufficient spread of angular data due to the fixed sensor location or localized cloud contamination.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://www.ncbi.nlm.nih.gov/pubmed/22473302','PUBMED'); return false;" href="http://www.ncbi.nlm.nih.gov/pubmed/22473302"><span id="translatedtitle">Variation of <span class="hlt">MODIS</span> <span class="hlt">reflectance</span> and vegetation indices with viewing geometry and soybean development.</span></a></p> <p><a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a></p> <p>Breunig, Fábio M; Galvão, Lênio S; Formaggio, Antônio R; Epiphanio, José C N</p> <p>2012-06-01</p> <p>Directional effects introduce a variability in <span class="hlt">reflectance</span> and vegetation index determination, especially when large field-of-view sensors are used (e.g., Moderate Resolution Imaging Spectroradiometer - <span class="hlt">MODIS</span>). In this study, we evaluated directional effects on <span class="hlt">MODIS</span> <span class="hlt">reflectance</span> and four vegetation indices (Normalized Difference Vegetation Index - NDVI; Enhanced Vegetation Index - EVI; Normalized Difference Water Index - NDWI(1640) and NDWI(2120)) with the soybean development in two growing seasons (2004-2005 and 2005-2006). To keep the reproductive stage for a given cultivar as a constant factor while varying viewing geometry, pairs of images obtained in close dates and opposite view angles were analyzed. By using a non-parametric statistics with bootstrapping and by normalizing these indices for angular differences among viewing directions, their sensitivities to directional effects were studied. Results showed that the variation in <span class="hlt">MODIS</span> <span class="hlt">reflectance</span> between consecutive phenological stages was generally smaller than that resultant from viewing geometry for closed canopies. The contrary was observed for incomplete canopies. The <span class="hlt">reflectance</span> of the first seven <span class="hlt">MODIS</span> bands was higher in the backscattering. Except for the EVI, the other vegetation indices had larger values in the forward scattering direction. Directional effects decreased with canopy closure. The NDVI was lesser affected by directional effects than the other indices, presenting the smallest differences between viewing directions for fixed phenological stages. PMID:22473302</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/20150019885','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20150019885"><span id="translatedtitle"><span class="hlt">MODIS</span> Instrument Operation and Calibration Improvements</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Xiong, X.; Angal, A.; Madhavan, S.; Link, D.; Geng, X.; Wenny, B.; Wu, A.; Chen, H.; Salomonson, V.</p> <p>2014-01-01</p> <p>Terra and <span class="hlt">Aqua</span> <span class="hlt">MODIS</span> have successfully operated for over 14 and 12 years since their respective launches in 1999 and 2002. The <span class="hlt">MODIS</span> on-orbit calibration is performed using a set of on-board calibrators, which include a solar diffuser for calibrating the <span class="hlt">reflective</span> solar bands (RSB) and a blackbody for the thermal emissive bands (TEB). On-orbit changes in the sensor responses as well as key performance parameters are monitored using the measurements of these on-board calibrators. This paper provides an overview of <span class="hlt">MODIS</span> on-orbit operation and calibration activities, and instrument long-term performance. It presents a brief summary of the calibration enhancements made in the latest <span class="hlt">MODIS</span> data collection 6 (C6). Future improvements in the <span class="hlt">MODIS</span> calibration and their potential applications to the S-NPP VIIRS are also discussed.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2013AGUFM.H34A..07M','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2013AGUFM.H34A..07M"><span id="translatedtitle">Detection of Harmful Algal Blooms in the Optically Complex Coastal Waters of the Kuwait Bay using <span class="hlt">Aqua-MODIS</span> data</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Manche, C. J.; Sultan, M.; Uddin, S.; Al-Dousari, A.; Chouinard, K.</p> <p>2013-12-01</p> <p>In the optically complex coastal marine waters of the Kuwait Bay, the propagation of Harmful Algal Blooms (HABs) has become a severe issue over the last decade affecting aquaculture a primary component of the Kuwaiti economy. Although several remote sensing based methods of algal bloom detection exist today, few may accurately detect the concentration and identify the type of HABs in Case II waters. The purpose of this study is: (1) assessment of the method that best detects and identifies algal blooms in general and HABs in particular, in the Kuwait Bay, and (2) identification of the factors controlling the occurrence of HABs. Fluorescence Line Height (FLH), Empirical, Bio-Optical, and Operational Methods as well as Ocean Colour 3 Band Ratio (OC3M), Garver-Siegel-Maritorena Model (GSM), and General Inherent Optical Property (GIOP) Chlorophyll-a (Chl-a) algorithms were applied to Moderate Resolution Imaging Spectroradiometer (<span class="hlt">MODIS</span>) images acquired (07/2002 to 07/2012) over the Kuwait Bay and areas as far east as Shatt Al-Arab and as far south as N. 29.284 (Lat.), E. 50.047 (Long.) decimal degrees. In-situ data (bloom days: 50; sampling locations: 64) collected (09/1999 to 07/2011) from the Kuwait Bay was provided by the Kuwait Institute for Scientific Research and was used to test the reliability of the satellite-based inferences. Tasks accomplished and findings reached include: (1) comparison of in situ to estimated OC3M, GSM, and GIOP chlorophyll concentrations over the sampling locations for the time period 2002 to 2009 showed that OC3M outperformed the two other techniques in predicting the observed distribution and in replicating the measured concentration of the in-situ Chl-a data; (2) applying the OC3M algorithm to a total of 4039 scenes and using threshold values of 3, 4, and 5 mg/m3 Chl-a concentrations we inferred 371, 202, and 124 occurrences in the Kuwait Bay that met their respective threshold; (3) applying the operational method we successfully</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2012AGUFM.B54C..04D','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2012AGUFM.B54C..04D"><span id="translatedtitle">Validating the simulation of optical <span class="hlt">reflectance</span> by a vertically resolved canopy biophysics model with <span class="hlt">MODIS</span> daily observations</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Drewry, D. T.; Duveiller, G.</p> <p>2012-12-01</p> <p>Agricultural modeling and yield forecasting are complicated by seasonal variability in traits controlled by factors such as growth stage, nutrient availability and moisture status. While a new generation of vegetation models incorporate ecophysiological details that allow for accurate estimates of carbon uptake, water use and energy exchange, these increases in process-level detail have resulted in the requirement to estimate a broader set of model parameters. Constraining uncertainties in model estimates of productivity and water use requires periodic updates as the structural and physiological status of the vegetation varies over the growing season. Here we explore the utilization of remote sensing <span class="hlt">reflectance</span> observations in the optical domain collected from the <span class="hlt">MODIS</span> sensors onboard the Terra and <span class="hlt">Aqua</span> satellites for constraining key canopy states and reducing the uncertainty in modeled CO2, water and energy exchange with the atmosphere. At the core of this approach is a vertically discretized model (MLCan) that characterizes the ecophysiological functioning of a plant canopy and its biophysical coupling to the ambient environment at a half-hourly timestep. Above-ground vegetation is partially controlled by a root system model that simulates moisture uptake in a multi-layer soil system. MLCan has been rigorously validated for both C3 and C4 crops against field- and leaf-scale observations of canopy CO2 uptake, evapotranspiration and sensible heat exchange across a wide range of meteorological conditions in both ambient and elevated CO2 environments. A widely utilized radiation transfer model (PROSAIL) that accounts for the effects of leaf-level optical properties and foliage distribution and orientation on canopy <span class="hlt">reflectance</span> is coupled to MLCan. This coupling provides the capability of expanding the spectral resolution of the model to nm-scale over the optical range. The coupled model will provide a system for testing the links between plant canopy biochemical</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2011lrsg.book..533V','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2011lrsg.book..533V"><span id="translatedtitle"><span class="hlt">MODIS</span> Directional Surface <span class="hlt">Reflectance</span> Product: Method, Error Estimates and Validation</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Vermote, Eric; Kotchenova, Svetlana</p> <p></p> <p>The surface bidirectional <span class="hlt">reflectance</span> factor (BRF) is the ratio between <span class="hlt">reflected</span> radiance measured in specific observation geometry (zenith and azimuth) within an infinitely small solid angle and irradiance incident on the surface from a direct source of illumination (zenith and azimuth). The BRF is determined from satellite observations through an atmospheric correction (AC) process. When properly retrieved, the surface BRF is fully decoupled from an atmospheric signal, and thus represents the value as measured by an ideal sensor held at the same view geometry and located just above the Earth's surface assuming an absence of atmosphere.</p> </li> </ol> <div class="pull-right"> <ul class="pagination"> <li><a href="#" onclick='return showDiv("page_1");'>«</a></li> <li><a href="#" onclick='return showDiv("page_4");'>4</a></li> <li><a href="#" onclick='return showDiv("page_5");'>5</a></li> <li class="active"><span>6</span></li> <li><a href="#" onclick='return showDiv("page_7");'>7</a></li> <li><a href="#" onclick='return showDiv("page_8");'>8</a></li> <li><a href="#" onclick='return showDiv("page_25");'>»</a></li> </ul> </div> </div><!-- col-sm-12 --> </div><!-- row --> </div><!-- page_6 --> <div id="page_7" class="hiddenDiv"> <div class="row"> <div class="col-sm-12"> <div class="pull-right"> <ul class="pagination"> <li><a href="#" onclick='return showDiv("page_1");'>«</a></li> <li><a href="#" onclick='return showDiv("page_5");'>5</a></li> <li><a href="#" onclick='return showDiv("page_6");'>6</a></li> <li class="active"><span>7</span></li> <li><a href="#" onclick='return showDiv("page_8");'>8</a></li> <li><a href="#" onclick='return showDiv("page_9");'>9</a></li> <li><a href="#" onclick='return showDiv("page_25");'>»</a></li> </ul> </div> </div> </div> <div class="row"> <div class="col-sm-12"> <ol class="result-class" start="121"> <li> <p><a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/20140010322','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20140010322"><span id="translatedtitle">Daily <span class="hlt">MODIS</span> 500 m <span class="hlt">Reflectance</span> Anisotropy Direct Broadcast (DB) Products for Monitoring Vegetation Phenology Dynamics</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Shuai, Yanmin; Schaaf, Crystal; Zhang, Xiaoyang; Strahler, Alan; Roy, David; Morisette, Jeffrey; Wang, Zhuosen; Nightingale, Joanne; Nickeson, Jaime; Richardson, Andrew D.; Xie, Donghui; Wang, Jindi; Li, Xiaowen; Strabala, Kathleen; Davies, James E.</p> <p>2013-01-01</p> <p>Land surface vegetation phenology is an efficient bio-indicator for monitoring ecosystem variation in response to changes in climatic factors. The primary objective of the current article is to examine the utility of the daily <span class="hlt">MODIS</span> 500 m <span class="hlt">reflectance</span> anisotropy direct broadcast (DB) product for monitoring the evolution of vegetation phenological trends over selected crop, orchard, and forest regions. Although numerous model-fitted satellite data have been widely used to assess the spatio-temporal distribution of land surface phenological patterns to understand phenological process and phenomena, current efforts to investigate the details of phenological trends, especially for natural phenological variations that occur on short time scales, are less well served by remote sensing challenges and lack of anisotropy correction in satellite data sources. The daily <span class="hlt">MODIS</span> 500 m <span class="hlt">reflectance</span> anisotropy product is employed to retrieve daily vegetation indices (VI) of a 1 year period for an almond orchard in California and for a winter wheat field in northeast China, as well as a 2 year period for a deciduous forest region in New Hampshire, USA. Compared with the ground records from these regions, the VI trajectories derived from the cloud-free and atmospherically corrected <span class="hlt">MODIS</span> Nadir BRDF (bidirectional <span class="hlt">reflectance</span> distribution function) adjusted <span class="hlt">reflectance</span> (NBAR) capture not only the detailed footprint and principal attributes of the phenological events (such as flowering and blooming) but also the substantial inter-annual variability. This study demonstrates the utility of the daily 500 m <span class="hlt">MODIS</span> <span class="hlt">reflectance</span> anisotropy DB product to provide daily VI for monitoring and detecting changes of the natural vegetation phenology as exemplified by study regions comprising winter wheat, almond trees, and deciduous forest.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=4435130','PMC'); return false;" href="http://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=4435130"><span id="translatedtitle">Evaluation and Intercomparison of <span class="hlt">MODIS</span> and GEOV1 Global Leaf Area Index Products over Four Sites in North China</span></a></p> <p><a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pmc">PubMed Central</a></p> <p>Li, Zhenwang; Tang, Huan; Zhang, Baohui; Yang, Guixia; Xin, Xiaoping</p> <p>2015-01-01</p> <p>This study investigated the performances of the Moderate Resolution Imaging Spectroradiometer (<span class="hlt">MODIS</span>) and GEOLAND2 Version 1 (GEOV1) Leaf Area Index (LAI) products using ground measurements and LAI reference maps over four sites in North China for 2011–2013. The Terra + <span class="hlt">Aqua</span> <span class="hlt">MODIS</span> and Terra <span class="hlt">MODIS</span> LAI retrieved by the main algorithm and GEOV1 LAI within the valid range were evaluated and intercompared using LAI reference maps to assess their uncertainty and seasonal variability The results showed that GEOV1 LAI is the most similar product with the LAI reference maps (R2 = 0.78 and RMSE = 0.59). The <span class="hlt">MODIS</span> products performed well for biomes with low LAI values, but considerable uncertainty arose when the LAI was larger than 3. Terra + <span class="hlt">Aqua</span> <span class="hlt">MODIS</span> (R2 = 0.72 and RMSE = 0.68) was slightly more accurate than Terra <span class="hlt">MODIS</span> (R2 = 0.57 and RMSE = 0.90) for producing slightly more successful observations. Both <span class="hlt">MODIS</span> and GEOV1 products effectively followed the seasonal trajectory of the reference maps, and GEOV1 exhibited a smoother seasonal trajectory than <span class="hlt">MODIS</span>. <span class="hlt">MODIS</span> anomalies mainly occurred during summer and likely occurred because of surface <span class="hlt">reflectance</span> uncertainty, shorter temporal resolutions and inconsistency between simulated and <span class="hlt">MODIS</span> surface <span class="hlt">reflectances</span>. This study suggests that further improvements of the <span class="hlt">MODIS</span> LAI products should focus on finer algorithm inputs and improved seasonal variation modeling of <span class="hlt">MODIS</span> observations. Future field work considering finer biome maps and better generation of LAI reference maps is still needed. PMID:25781509</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://www.ncbi.nlm.nih.gov/pubmed/25781509','PUBMED'); return false;" href="http://www.ncbi.nlm.nih.gov/pubmed/25781509"><span id="translatedtitle">Evaluation and intercomparison of <span class="hlt">MODIS</span> and GEOV1 global leaf area index products over four sites in North China.</span></a></p> <p><a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a></p> <p>Li, Zhenwang; Tang, Huan; Zhang, Baohui; Yang, Guixia; Xin, Xiaoping</p> <p>2015-01-01</p> <p>This study investigated the performances of the Moderate Resolution Imaging Spectroradiometer (<span class="hlt">MODIS</span>) and GEOLAND2 Version 1 (GEOV1) Leaf Area Index (LAI) products using ground measurements and LAI reference maps over four sites in North China for 2011-2013. The Terra + <span class="hlt">Aqua</span> <span class="hlt">MODIS</span> and Terra <span class="hlt">MODIS</span> LAI retrieved by the main algorithm and GEOV1 LAI within the valid range were evaluated and intercompared using LAI reference maps to assess their uncertainty and seasonal variability The results showed that GEOV1 LAI is the most similar product with the LAI reference maps (R2 = 0.78 and RMSE = 0.59). The <span class="hlt">MODIS</span> products performed well for biomes with low LAI values, but considerable uncertainty arose when the LAI was larger than 3. Terra + <span class="hlt">Aqua</span> <span class="hlt">MODIS</span> (R2 = 0.72 and RMSE = 0.68) was slightly more accurate than Terra <span class="hlt">MODIS</span> (R2 = 0.57 and RMSE = 0.90) for producing slightly more successful observations. Both <span class="hlt">MODIS</span> and GEOV1 products effectively followed the seasonal trajectory of the reference maps, and GEOV1 exhibited a smoother seasonal trajectory than <span class="hlt">MODIS</span>. <span class="hlt">MODIS</span> anomalies mainly occurred during summer and likely occurred because of surface <span class="hlt">reflectance</span> uncertainty, shorter temporal resolutions and inconsistency between simulated and <span class="hlt">MODIS</span> surface <span class="hlt">reflectances</span>. This study suggests that further improvements of the <span class="hlt">MODIS</span> LAI products should focus on finer algorithm inputs and improved seasonal variation modeling of <span class="hlt">MODIS</span> observations. Future field work considering finer biome maps and better generation of LAI reference maps is still needed. PMID:25781509</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2015EGUGA..1715789K','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2015EGUGA..1715789K"><span id="translatedtitle">The regime of aerosol asymmetry parameter and Angstrom exponent over Europe, Mediterranean and Middle East based on <span class="hlt">MODIS</span> satellite data. Intercomparison of <span class="hlt">MODIS-Aqua</span> C051 and C006 retrievals</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Korras-Carraca, Marios Bruno; Hatzianastassiou, Nikolaos; Matsoukas, Christos; Gkikas, Antonis; Papadimas, Christos; Sayers, Andy</p> <p>2015-04-01</p> <p>Atmospheric aerosols, both natural and anthropogenic, can cause climate change through their direct, indirect, and semi-direct effects on the radiative energy budget of the Earth-atmosphere system. In the present work, we study two of the most important optical properties of aerosols, the asymmetry parameter (gaer) and the Angstrom exponent (α). Both gaer and α are related with aerosol size, which is a very important parameter for climate and human health. The study region comprises North Africa, the Arabian peninsula, Europe, and the Mediterranean basin. These areas are of great interest, because of the variety of aerosol types they host, both anthropogenic and natural. Urban, industrial or biomass-burning aerosols are usually fine, while desert dust or sea-salt are basically coarse, making thus possible the establishment of a relationship between the type and the size of aerosols. Using satellite data from the collection 051 of <span class="hlt">MODIS</span> (MODerate resolution Imaging Spectroradiometer, <span class="hlt">Aqua</span>), we investigate the spatio-temporal characteristics of the asymmetry parameter and Angstrom exponent. We generally find significant spatial variability, with larger gaer values over regions dominated by larger size particles, e.g. outside the Atlantic coasts of north-western Africa, where desert-dust outflow is taking place. The gaer values tend to decrease with increasing wavelength, especially over areas dominated by small particulates. The intra-annual variability is found to be small in desert-dust areas, with maximum values during summer, while in all other areas larger values are reported during the cold season and smaller during the warm. Significant intra-annual and inter-annual variability is observed around the Black Sea. However, the inter-annual trends of gaer are found to be generally small. The geographical distributions for α (given for the pair of wavelengths 550-865 nm) affirm the conclusions drawn from the asymmetry parameter as regards the aerosol size over</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2016EGUGA..1812221C','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2016EGUGA..1812221C"><span id="translatedtitle">On the assimilation of <span class="hlt">MODIS</span> <span class="hlt">reflectance</span> into a detailed snowpack model</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Charrois, Luc; Dumont, Marie; Cosme, Emmanuel; Lafaysse, Matthieu; Morin, Samuel; Libois, Quentin; Picard, Ghislain</p> <p>2016-04-01</p> <p>One of the major sources of uncertainty in detailed snowpack simulations lies in the quality of meteorological forcings. The limited spatial resolution of common reanalysis and forecast data used as inputs for snowpack models usually makes it difficult to simulate the local horizontal heterogeneity of snowpack physical properties, especially in mountainous areas. Using satellite data to incorporate snowpack state observations into the simulations appears as an alluring way to improve the snow simulations, to account for spatial variability and to mitigate the impact of meteorological forcings uncertainties. This work presents an original study of the impact of the assimilation of visible and near-infrared <span class="hlt">reflectances</span> into the detailed snowpack model SURFEX/ISBA-Crocus. We performed ensemble simulations by perturbing the atmospheric forcing consistently with its estimated uncertainty. In a first step, we performed assimilation experiments with synthetic imager (<span class="hlt">MODIS</span> like) observations and a particle filter. The experiments were carried out at Col du Lautaret area (2100 m altitude, French Alps) over 5 hydrologic seasons. They provide a good insight about the potential and limitations of assimilating imager data to improve the representation of the snowpack. In particular, they demonstrate the significance of the temporal distribution of the observation to assimilate. In a second step, we assimilated actual <span class="hlt">MODIS</span> data and evaluated the impact of the assimilation using snow measurements acquired during one winter season at Col du Lautaret. These real experiments enlighten the need for a relevant screening method for <span class="hlt">MODIS</span> <span class="hlt">reflectances</span>.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://pubs.usgs.gov/of/2010/1055/','USGSPUBS'); return false;" href="http://pubs.usgs.gov/of/2010/1055/"><span id="translatedtitle">e<span class="hlt">MODIS</span>: A User-Friendly Data Source</span></a></p> <p><a target="_blank" href="http://pubs.er.usgs.gov/pubs/index.jsp?view=adv">USGS Publications Warehouse</a></p> <p>Jenkerson, Calli; Maiersperger, Thomas; Schmidt, Gail</p> <p>2010-01-01</p> <p>The U.S. Geological Survey's (USGS) Earth Resources Observation and Science (EROS) Center is generating a suite of products called 'e<span class="hlt">MODIS</span>' based on Moderate Resolution Imaging Spectroradiometer (<span class="hlt">MODIS</span>) data acquired by the National Aeronautics and Space Administration's (NASA) Earth Observing System (EOS). With a more frequent repeat cycle than Landsat and higher spatial resolutions than the Advanced Very High Resolution Spectroradiometer (AVHRR), <span class="hlt">MODIS</span> is well suited for vegetation studies. For operational monitoring, however, the benefits of <span class="hlt">MODIS</span> are counteracted by usability issues with the standard map projection, file format, composite interval, high-latitude 'bow-tie' effects, and production latency. e<span class="hlt">MODIS</span> responds to a community-specific need for alternatively packaged <span class="hlt">MODIS</span> data, addressing each of these factors for real-time monitoring and historical trend analysis. e<span class="hlt">MODIS</span> processes calibrated radiance data (level-1B) acquired by the <span class="hlt">MODIS</span> sensors on the EOS Terra and <span class="hlt">Aqua</span> satellites by combining <span class="hlt">MODIS</span> Land Science Collection 5 Atmospherically Corrected Surface <span class="hlt">Reflectance</span> production code and USGS EROS <span class="hlt">MODIS</span> Direct Broadcast System (DBS) software to create surface <span class="hlt">reflectance</span> and Normalized Difference Vegetation Index (NDVI) products. e<span class="hlt">MODIS</span> is produced over the continental United States and over Alaska extending into Canada to cover the Yukon River Basin. The 250-meter (m), 500-m, and 1,000-m products are delivered in Geostationary Earth Orbit Tagged Image File Format (Geo- TIFF) and composited in 7-day intervals. e<span class="hlt">MODIS</span> composites are projected to non-Sinusoidal mapping grids that best suit the geography in their areas of application (see e<span class="hlt">MODIS</span> Product Description below). For e<span class="hlt">MODIS</span> products generated over the continental United States (e<span class="hlt">MODIS</span> CONUS), the Terra (from 2000) and <span class="hlt">Aqua</span> (from 2002) records are available and continue through present time. e<span class="hlt">MODIS</span> CONUS also is generated in an expedited process that delivers a 7-day rolling composite</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2015AGUFM.A33E0223X','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2015AGUFM.A33E0223X"><span id="translatedtitle">Status of <span class="hlt">MODIS</span> Instruments and Future Calibration Improvements</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Xiong, X.; Angal, A.; Wu, A.; Salomonson, V. V.</p> <p>2015-12-01</p> <p><span class="hlt">MODIS</span> is one of the key instruments currently operated on two major missions for the NASA's Earth Observing System (EOS) program: Terra and <span class="hlt">Aqua</span> launched in 1999 and 2002, respectively. Nearly 40 data products have been routinely generated from both Terra and <span class="hlt">Aqua</span> <span class="hlt">MODIS</span> observations and widely distributed to the science community and users worldwide for their studies of the earth's system and changes in its geophysical properties. To date, each <span class="hlt">MODIS</span> instrument operation remains nominal and its on-board calibrators (OBC) continue to function satisfactorily. On a regular basis, <span class="hlt">MODIS</span> <span class="hlt">reflective</span> solar bands (RSB) calibration is performed by a solar diffuser (SD) and a solar diffuser stability monitor (SDSM). For the thermal emissive bands (TEB), an on-board blackbody (BB) provides a scan-by-scan calibration reference. Since launch, extensive calibration and characterization activities have been scheduled and implemented by the <span class="hlt">MODIS</span> Characterization Support Team (MCST) to produce and update calibration look-up tables (LUT). This presentation provides an overview of both Terra and <span class="hlt">Aqua</span> <span class="hlt">MODIS</span> instrument status, their on-orbit operation and calibration activities, and radiometric, spectral, and spatial performance. It describes calibration changes (algorithms and look-up tables) made for the <span class="hlt">MODIS</span> Level 1B (L1B) data collection 6 (C6) and discusses remaining challenging issues and ongoing effort for future improvements. As expected, lessons from both Terra and <span class="hlt">Aqua</span> <span class="hlt">MODIS</span> have benefitted and will continue to help the S-NPP and JPSS VIIRS instruments in terms of on-orbit operation strategies and calibration enhancements.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2015AGUFM.A14C..05V','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2015AGUFM.A14C..05V"><span id="translatedtitle">Transitioning <span class="hlt">MODIS</span> to VIIRS observations for Land: Surface <span class="hlt">Reflectance</span> results, Status and Long-term Prospective</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Vermote, E.</p> <p>2015-12-01</p> <p>Surface <span class="hlt">reflectance</span> is one of the key products from VIIRS and as with <span class="hlt">MODIS</span>, is used in developing several higher-order land products. The VIIRS Surface <span class="hlt">Reflectance</span> (SR) IP is based on the heritage <span class="hlt">MODIS</span> Collection 5 product (Vermote et al. 2002). The quality and character of surface <span class="hlt">reflectance</span> depends on the accuracy of the VIIRS Cloud Mask (VCM) and aerosol algorithms and of course on the adequate calibration of the sensor. Early evaluation of the VIIRS SR product in the context of the maturity of the operational processing system known as the Interface Data Processing System (IDPS), has been a major focus of work to-date, but is now evolving into the development of a VIIRS suite of Climate Data Records produced by the NASA Land Science Investigator Processing System (SIPS). We will present the calibration performance and the role of the surface <span class="hlt">reflectance</span> in calibration monitoring, the performance of the cloud mask with a focus on vegetation monitoring (no snow conditions), the performance of the aerosol input used in the atmospheric correction with quantitative results of the performance of the SR product over AERONET sites. Based on those elements and further assessment, we will address the readiness of the SR product for the production of higher-order land products such as Vegetation Indices, Albedo and LAI/FPAR, the its application to agricultural monitoring and in particular the integration of VIIRS data into the global agricultural monitoring (GLAM) system developed at UMd. Finally from the lessons learned, we will articulate a set of critical recommendations to ensure consistency and continuity of the JPSS mission with the <span class="hlt">MODIS</span> data record.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2008AGUFM.B41C0387S','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2008AGUFM.B41C0387S"><span id="translatedtitle">Collection 5 <span class="hlt">MODIS</span> LAI/FPAR Products</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Samanta, A.; Ganguly, S.; Schull, M. A.; Shabanov, N. V.; Knyazikhin, Y.; Myneni, R. B.</p> <p>2008-12-01</p> <p><span class="hlt">MODIS</span> LAI algorithm was substantially refined for the Collection 5 reprocessing to optimally use suite of <span class="hlt">MODIS</span> observations from Terra and <span class="hlt">Aqua</span> sensors. Refinements are based on advancements in RT theory, analysis of former versions of global time series of LAI product and product validation with field measurements. The Look-up-tables were regenerated for all vegetation types based on a new Stochastic RT model. The Collection 5 suite of LAI/FPAR products possesses higher quality retrievals than previous versions. The following 1-km products are operationally generated at NASA Science Computing Facilities (SCF): 8-day Terra and <span class="hlt">Aqua</span> products, 8-days Combined Terra and <span class="hlt">Aqua</span> product, and 4-day Combined Terra and <span class="hlt">Aqua</span> product. In addition, monthly Collection 5 Terra products are processed and archived at the Boston University (BU) SCF. In this study, we analyzed Collection 5 LAI/FPAR products over a range of spatial scales: Global, North American continent (single composite during the growing season), at scale of <span class="hlt">MODIS</span> tile (annual time series for three <span class="hlt">MODIS</span> tiles), and at the scale of validation sites (annual time series for three sites). For analysis we used Collection 5 BU monthly Terra products. The LAI retrieval algorithm consists of two parts: main (Radiative Transfer based) and back-up (empirical). The BU monthly compositing scheme consists of 3 main steps: 1) selection of data from 8-day MOD15A2 product; 2) assembling tile data into global map based on a global land cover; and 3) degrading from 1km resolution to 4km resolution. We focused on the following: 1) Enhancement in the number of high quality retrievals in Collection 5; 2) Utility of the product to improve retrievals under atmospheric contamination of surface <span class="hlt">reflectance</span> (clouds, aerosols) and for dense vegetation under saturation of surface <span class="hlt">reflectance</span>; 3) Utility of the product to improve temporal resolution of retrievals.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/1998SPIE.3439..257P','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/1998SPIE.3439..257P"><span id="translatedtitle">Bidirectional <span class="hlt">reflectance</span> factor (BRF) characterization of the <span class="hlt">MODIS</span> flight solar diffuser</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Pavlov, Milutin M.; Byers, Michael L.; Walker, Joe A., Jr.</p> <p>1998-10-01</p> <p>The Moderate Resolution Imaging Spectroradiometer (<span class="hlt">MODIS</span>) will be one of the primary instruments observing the earth on the Earth Observing System (EOS) scheduled for launch in late 1999. The solar diffuser BRF characterization is required for <span class="hlt">MODIS</span> on-orbit <span class="hlt">reflectance</span> calibration. The system <span class="hlt">reflectance</span> calibration accuracy requirement is 2 percent covering a spectral region of 400 to 2300 nm. An internal flow down specification of 1 percent was allotted to characterization of the BRF. The SBRS scattering goniometer will be described. The source is a quartz-halogen lamp. Multiple field stops, aperture stops, and baffle masks were experimentally optimized to reduce scattered light to acceptable levels. In addition the room was made 'light tight'. Glan Thompson and Wollaston polarizers were used in the illuminating and viewing arms, respectively. Three sets of detectors were used to cover the 400 to 2300 nm range: PMT, Ge, and PbS. The rotary and translation stages used to move the solar diffuser, polarizers, optical filters, and detectors being computer controlled, which permitted measurements to be made remotely. This scattering goniometer is a relative device, so the flight solar diffuser is characterized by measuring it relative to a diffuser which was characterized by NIST. The transfer to the NIST standard was done before and after solar diffuser characterization. BRF measurements were made at five wavelengths and nine illumination angles with one out-of-plane observation angle. Multiple BRF measurements were made to determine repeatability and spatial uniformity. Measured BRF data will be presented.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://ntrs.nasa.gov/search.jsp?R=20040035547&hterms=aerosols+desert&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D70%26Ntt%3Daerosols%2Bdesert','NASA-TRS'); return false;" href="http://ntrs.nasa.gov/search.jsp?R=20040035547&hterms=aerosols+desert&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D70%26Ntt%3Daerosols%2Bdesert"><span id="translatedtitle"><span class="hlt">MODIS</span> Retrieval of Dust Aerosol</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Remer, Lorraine A.; Kaufman, Yoram J.; Tanre, Didier</p> <p>2003-01-01</p> <p>The MODerate resolution Imaging Spectroradiometer (<span class="hlt">MODIS</span>) currently aboard both the Terra and <span class="hlt">Aqua</span> satellites produces a suite of products designed to characterize global aerosol distribution, optical thickness and particle size. Never before has a space-borne instrument been able to provide such detailed information, operationally, on a nearly global basis every day. The three years of Terra-<span class="hlt">MODIS</span> data have been validated by comparing with co-located AERONET observations of aerosol optical thickness and derivations of aerosol size parameters. Some 8000 comparison points located at 133 AERONET sites around the globe show that the <span class="hlt">MODIS</span> aerosol optical thickness retrievals are accurate to within the pre-launch expectations. However, the validation in regions dominated by desert dust is less accurate than in regions dominated by fine mode aerosol or background marine sea salt. The discrepancy is most apparent in retrievals of aerosol size parameters over ocean. In dust situations, the <span class="hlt">MODIS</span> algorithm tends to under predict particle size because the <span class="hlt">reflectances</span> at top of atmosphere measured by <span class="hlt">MODIS</span> exhibit the stronger spectral signature expected by smaller particles. This pattern is consistent with the angular and spectral signature of non-spherical particles. All possible aerosol models in the <span class="hlt">MODIS</span> Look-Up Tables were constructed from Mie theory, assuming a spherical shape. Using a combination of <span class="hlt">MODIS</span> and AERONET observations, in regimes dominated by desert dust, we construct phase functions, empirically, with no assumption of particle shape. These new phase functions are introduced into the <span class="hlt">MODIS</span> algorithm, in lieu of the original options for large dust-like particles. The results will be analyzed and examined.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2009EGUGA..1111496C','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2009EGUGA..1111496C"><span id="translatedtitle">Actual evapotranspiration estimation in a Mediterranean mountain region by means of Landsat-5 TM and TERRA/<span class="hlt">AQUA</span> <span class="hlt">MODIS</span> imagery and Sap Flow measurements in Pinus sylvestris forest stands.</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Cristóbal, J.; Poyatos, R.; Ninyerola, M.; Pons, X.; Llorens, P.</p> <p>2009-04-01</p> <p>Evapotranspiration monitoring has important implications on global and regional climate modelling, as well as in the knowledge of the hydrological cycle and in the assessment of environmental stress that affects forest and agricultural ecosystems. An increase of evapotranspiration while precipitation remains constant, or is reduced, could decrease water availability for natural and agricultural systems and human needs. Consequently, water balance methods, as the evapotranspiration modelling, have been widely used to estimate crop and forest water needs, as well as the global change effects. Nowadays, radiometric measurements provided by Remote Sensing and GIS analysis are the technologies used to compute evapotranspiration at regional scales in a feasible way. Currently, the 38% of Catalonia (NE of the Iberian Peninsula) is covered by forests, and one of the most important forest species is Scots Pine (Pinus sylvestris) which represents the 18.4% of the area occupied by forests. The aim of this work is to model actual evapotranspiration in Pinus sylvestris forest stands, in a Mediterranean mountain region, using remote sensing data, and compare it with stand-scale sap flow measurements measured in the Vallcebre research area (42° 12' N, 1° 49' E), in the Eastern Pyrenees. To perform this study a set of 30 cloud-free TERRA-<span class="hlt">MODIS</span> images and 10 Landsat-5 TM images of path 198 and rows 31 and 32 from June 2003 to January 2005 have been selected to perform evapotranspiration modelling in Pinus sylvestris forest stands. TERRA/<span class="hlt">AQUA</span> <span class="hlt">MODIS</span> images have been downloaded by means of the EOS Gateway. We have selected two different types of products which contain the remote sensing data we have used to model daily evapotranspiration, daily LST product and daily calibrated <span class="hlt">reflectances</span> product. Landsat-5 TM images have been corrected by means of conventional techniques based on first order polynomials taking into account the effect of land surface relief using a Digital</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://ntrs.nasa.gov/search.jsp?R=20040031528&hterms=Siri&qs=N%3D0%26Ntk%3DAll%26Ntx%3Dmode%2Bmatchall%26Ntt%3DSiri','NASA-TRS'); return false;" href="http://ntrs.nasa.gov/search.jsp?R=20040031528&hterms=Siri&qs=N%3D0%26Ntk%3DAll%26Ntx%3Dmode%2Bmatchall%26Ntt%3DSiri"><span id="translatedtitle">Accessing and Understanding <span class="hlt">MODIS</span> Data</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Leptoukh, Gregory; Jenkerson, Calli B.; Jodha, Siri</p> <p>2003-01-01</p> <p>The National Aeronautics and Space Administration (NASA) launched the Terra satellite in December 1999, as part of the Earth Science Enterprise promotion of interdisciplinary studies of the integrated Earth system. <span class="hlt">Aqua</span>, the second satellite from the series of EOS constellation, was launched in May 2002. Both satellites carry the MODerate resolution Imaging Spectroradiometer (<span class="hlt">MODIS</span>) instrument. <span class="hlt">MODIS</span> data are processed at the Goddard Space Flight Center, Greenbelt, MD, and then archived and distributed by the Distributed Active Archive Centers (DAACs). Data products from the <span class="hlt">MODIS</span> sensors present new challenges to remote sensing scientists due to specialized production level, data format, and map projection. <span class="hlt">MODIS</span> data are distributed as calibrated radiances and as higher level products such as: surface <span class="hlt">reflectance</span>, water-leaving radiances, ocean color and sea surface temperature, land surface kinetic temperature, vegetation indices, leaf area index, land cover, snow cover, sea ice extent, cloud mask, atmospheric profiles, aerosol properties, and many other geophysical parameters. <span class="hlt">MODIS</span> data are stored in HDF- EOS format in both swath format and in several different map projections. This tutorial guides users through data set characteristics as well as search and order interfaces, data unpacking, data subsetting, and potential applications of the data. A CD-ROM with sample data sets, and software tools for working with the data will be provided to the course participants.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2007SPIE.6677E..0OX','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2007SPIE.6677E..0OX"><span id="translatedtitle">Characterization of <span class="hlt">MODIS</span> solar diffuser on-orbit degradation</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Xiong, X.; Xie, X.; Angal, A.; Choi, J.; Sun, J.; Barnes, W. L.</p> <p>2007-09-01</p> <p><span class="hlt">MODIS</span> has 20 <span class="hlt">reflective</span> solar bands (RSB) that are calibrated on-orbit using a solar diffuser (SD) and a solar diffuser stability monitor (SDSM). The <span class="hlt">MODIS</span> SD bi-directional <span class="hlt">reflectance</span> factor (BRF) was characterized pre-launch. Its on-orbit degradation is regularly monitored by the SDSM at wavelengths ranging from 0.41 to 0.94μm. During each SD/SDSM calibration event, the SDSM views alternately the sunlight directly through a fixed attenuation screen and the sunlight diffusely <span class="hlt">reflected</span> from the SD panel. The time series of SDSM measurements (ratios of the SD view response to the Sun view response) is used to determine the SD BRF degradation at SDSM wavelengths. Since launch Terra <span class="hlt">MODIS</span> has operated for more than seven years and <span class="hlt">Aqua</span> for over five years. The SD panel on each <span class="hlt">MODIS</span> instrument has experienced noticeable degradation with the largest changes observed in the VIS spectral region. This paper provides a brief description of <span class="hlt">MODIS</span> RSB calibration methodology and SD/SDSM operational activities, and illustrates the SD on-orbit degradation results for both Terra and <span class="hlt">Aqua</span> <span class="hlt">MODIS</span>. It also discusses the impact on the SD degradation due to sensor operational activities and SD solar exposure time. <span class="hlt">Aqua</span> <span class="hlt">MODIS</span> has been operated under nearly the same condition for more than five years. Its SD annual degradation rate is estimated to be 2.7% at 0.41μm, 1.7% at 0.47μm, and less than 1.0% at wavelengths above 0.53μm. Terra <span class="hlt">MODIS</span>, on the other hand, has experienced two different SD solar exposure conditions due to an SD door (SDD) operation related anomaly that occurred in May 2003 that had led to a decision to keep the SDD permanently at its "open" position. Prior to this event, Terra <span class="hlt">MODIS</span> SD degradation rates were very similar to <span class="hlt">Aqua</span> <span class="hlt">MODIS</span>. Since then its SD has experienced much faster degradation rates due to more frequent solar exposure.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/20120015385','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20120015385"><span id="translatedtitle"><span class="hlt">MODIS</span> On-Orbit Calibration and Lessons Learned</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Xiong, Jack</p> <p>2012-01-01</p> <p>The Moderate Resolution Imaging Spectroradiometer (<span class="hlt">MODIS</span>) is a key instrument for NASA's Earth Observing System (EOS) Terra and <span class="hlt">Aqua</span> missions. Since launch, Terra and <span class="hlt">Aqua</span> <span class="hlt">MODIS</span> 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. <span class="hlt">MODIS</span> 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. <span class="hlt">MODIS</span> collects data in 36 spectral bands, covering wavelengths from 0.41 to 14.S!Jlll, and at 250m, SOOm, and lkm spatial resolutions (nadir). <span class="hlt">MODIS</span> 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 <span class="hlt">Aqua</span> <span class="hlt">MODIS</span> to track their calibration stability in the <span class="hlt">reflective</span> solar region. This tutorial session provides an overview of <span class="hlt">MODIS</span> 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 <span class="hlt">MODIS</span> experience and lessons will continue to provide valuable information for future earth observing missions/sensors.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2012SPIE.8528E..09X','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2012SPIE.8528E..09X"><span id="translatedtitle">Comparison of <span class="hlt">MODIS</span> and VIIRS solar diffuser stability monitor performance</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Xiong, Xiaoxiong; Fulbright, Jon; Angal, Amit; Sun, Junqiang; Wang, Zhipeng</p> <p>2012-11-01</p> <p>Launched in December 1999 and May 2002, Terra and <span class="hlt">Aqua</span> <span class="hlt">MODIS</span> have successfully operated for more than 12 and 10 years, respectively. <span class="hlt">MODIS</span> <span class="hlt">reflective</span> solar bands (RSB) are calibrated on-orbit by a solar diffuser (SD). Its on-orbit degradation, or the change in its bi-directional <span class="hlt">reflectance</span> factor (BRF), is tracked by a solar diffuser stability monitor (SDSM). The <span class="hlt">MODIS</span> SDSM makes alternate observations of direct sunlight through an attenuation screen (Sun view) and of sunlight <span class="hlt">reflected</span> diffusely off the SD (SD view) during each SDSM calibration event. The <span class="hlt">MODIS</span> SDSM has 9 detectors, covering wavelengths from 0.41 to 0.94 μm. Due to a design error in <span class="hlt">MODIS</span> SDSM sub-system (identified post-launch), relatively large ripples were noticed in its Sun view responses. As a result, an alternative approach was developed by the <span class="hlt">MODIS</span> calibration team to minimize the uncertainty in determining the SD on-orbit degradation. The first VIIRS, on-board the Suomi NPP spacecraft, was successfully launched in October 2011. It carries a <span class="hlt">MODIS</span>-like SD and SDSM system for its RSB on-orbit calibration. Its design was improved based on lessons learned from <span class="hlt">MODIS</span>. Operationally, the VIIRS SDSM is used more frequently than <span class="hlt">MODIS</span>. VIIRS SDSM collects data using 8 individual detectors, covering a similar wavelength range as <span class="hlt">MODIS</span>. This paper provides an overview of <span class="hlt">MODIS</span> and VIIRS SDSM design features, their on-orbit operations, and calibration strategies. It illustrates their on-orbit performance in terms of on-orbit changes in SDSM detector on-orbit responses and on-orbit degradations of their SD. Results show that on-orbit changes of both <span class="hlt">MODIS</span> and VIIRS SD BRF and SDSM response have similar wavelength dependency: the SD degradation is faster at shorter visible wavelengths while the decrease of SDSM detector responses (gains) is greater at longer near-infrared wavelengths.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/20110020728','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20110020728"><span id="translatedtitle"><span class="hlt">MODIS</span> On-orbit Calibration Uncertainty Assessment</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Chiang, Vincent; Sun, Junqiang; Wu, Aisheng</p> <p>2011-01-01</p> <p><span class="hlt">MODIS</span> has 20 <span class="hlt">reflective</span> solar bands (RSB) and 16 thermal emissive bands (TEB). Compared to its heritage sensors, <span class="hlt">MODIS</span> was developed with very stringent calibration uncertainty requirements. As a result, <span class="hlt">MODIS</span> was designed and built with a set of on-board calibrators (OBC), which allow key sensor performance parameters and on-orbit calibration coefficients to be monitored and updated. In terms of its calibration traceability, <span class="hlt">MODIS</span> RSB calibration is <span class="hlt">reflectance</span> 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 <span class="hlt">MODIS</span> calibration methodologies and an in-depth analysis of its on-orbit calibration uncertainties. Also discussed in this paper are uncertainty contributions from individual components and differences due to Terra and <span class="hlt">Aqua</span> <span class="hlt">MODIS</span> instrument characteristics and on-orbit performance.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2014IJAEO..33..243P','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2014IJAEO..33..243P"><span id="translatedtitle">Automatic and improved radiometric correction of Landsat imagery using reference values from <span class="hlt">MODIS</span> surface <span class="hlt">reflectance</span> images</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Pons, X.; Pesquer, L.; Cristóbal, J.; González-Guerrero, O.</p> <p>2014-12-01</p> <p>Radiometric correction is a prerequisite for generating high-quality scientific data, making it possible to discriminate between product artefacts and real changes in Earth processes as well as accurately produce land cover maps and detect changes. This work contributes to the automatic generation of surface <span class="hlt">reflectance</span> products for Landsat satellite series. Surface <span class="hlt">reflectances</span> are generated by a new approach developed from a previous simplified radiometric (atmospheric + topographic) correction model. The proposed model keeps the core of the old model (incidence angles and cast-shadows through a digital elevation model [DEM], Earth-Sun distance, etc.) and adds new characteristics to enhance and automatize ground <span class="hlt">reflectance</span> retrieval. The new model includes the following new features: (1) A fitting model based on reference values from pseudoinvariant areas that have been automatically extracted from existing <span class="hlt">reflectance</span> products (Terra <span class="hlt">MODIS</span> MOD09GA) that were selected also automatically by applying quality criteria that include a geostatistical pattern model. This guarantees the consistency of the internal and external series, making it unnecessary to provide extra atmospheric data for the acquisition date and time, dark objects or dense vegetation. (2) A spatial model for atmospheric optical depth that uses detailed DEM and MODTRAN simulations. (3) It is designed so that large time-series of images can be processed automatically to produce consistent Landsat surface <span class="hlt">reflectance</span> time-series. (4) The approach can handle most images, acquired now or in the past, regardless of the processing system, with the exception of those with extremely high cloud coverage. The new methodology has been successfully applied to a series of near 300 images of the same area including MSS, TM and ETM+ imagery as well as to different formats and processing systems (LPGS and NLAPS from the USGS; CEOS from ESA) for different degrees of cloud coverage (up to 60%) and SLC</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/cgi-bin/nph-data_query?bibcode=2009EGUGA..1111496C&link_type=ABSTRACT','NASAADS'); return false;" href="http://adsabs.harvard.edu/cgi-bin/nph-data_query?bibcode=2009EGUGA..1111496C&link_type=ABSTRACT"><span id="translatedtitle">Actual evapotranspiration estimation in a Mediterranean mountain region by means of Landsat-5 TM and TERRA/<span class="hlt">AQUA</span> <span class="hlt">MODIS</span> imagery and Sap Flow measurements in Pinus sylvestris forest stands.</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Cristóbal, J.; Poyatos, R.; Ninyerola, M.; Pons, X.; Llorens, P.</p> <p>2009-04-01</p> <p>Evapotranspiration monitoring has important implications on global and regional climate modelling, as well as in the knowledge of the hydrological cycle and in the assessment of environmental stress that affects forest and agricultural ecosystems. An increase of evapotranspiration while precipitation remains constant, or is reduced, could decrease water availability for natural and agricultural systems and human needs. Consequently, water balance methods, as the evapotranspiration modelling, have been widely used to estimate crop and forest water needs, as well as the global change effects. Nowadays, radiometric measurements provided by Remote Sensing and GIS analysis are the technologies used to compute evapotranspiration at regional scales in a feasible way. Currently, the 38% of Catalonia (NE of the Iberian Peninsula) is covered by forests, and one of the most important forest species is Scots Pine (Pinus sylvestris) which represents the 18.4% of the area occupied by forests. The aim of this work is to model actual evapotranspiration in Pinus sylvestris forest stands, in a Mediterranean mountain region, using remote sensing data, and compare it with stand-scale sap flow measurements measured in the Vallcebre research area (42° 12' N, 1° 49' E), in the Eastern Pyrenees. To perform this study a set of 30 cloud-free TERRA-<span class="hlt">MODIS</span> images and 10 Landsat-5 TM images of path 198 and rows 31 and 32 from June 2003 to January 2005 have been selected to perform evapotranspiration modelling in Pinus sylvestris forest stands. TERRA/<span class="hlt">AQUA</span> <span class="hlt">MODIS</span> images have been downloaded by means of the EOS Gateway. We have selected two different types of products which contain the remote sensing data we have used to model daily evapotranspiration, daily LST product and daily calibrated <span class="hlt">reflectances</span> product. Landsat-5 TM images have been corrected by means of conventional techniques based on first order polynomials taking into account the effect of land surface relief using a Digital</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2009AGUSM.H34C..04P','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2009AGUSM.H34C..04P"><span id="translatedtitle">Radiative Forcing of Dust in Mountain Snow from <span class="hlt">MODIS</span> surface <span class="hlt">reflectance</span> data</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Painter, T. H.</p> <p>2009-05-01</p> <p>Here I present an algorithm that retrieves the radiative forcing by desert dust in mountain snow cover from surface <span class="hlt">reflectance</span> data from NASA Moderate Resolution Imaging Spectroradiometer (<span class="hlt">MODIS</span>). Dust emitted from natural and disturbed lands frequently deposits to mountain snow cover through dry and wet deposition, particularly in spring when synoptic scale storms entrain material from recently dried surfaces. Dust decreases snow spectral albedo, primarily in the visible wavelengths where the imaginary parts of the complex refractive indices of dust and ice have the greatest contrast. This surface radiative forcing accelerates melt and contributes to the snow-albedo feedback. In the Rocky Mountains of Colorado, this has been shown to shorten the duration of snow cover by approximately a month. The algorithm presented here, <span class="hlt">MODIS</span> Dust Radiative Forcing in Snow (MOD-DRFS), determines the per pixel radiative forcing by dust in snow from a coupled radiative transfer model that infers the <span class="hlt">reflectance</span> difference between clean snow spectra and dust- laden snow spectra according to a grain size matching in the near infrared and shortwave infrared wavelengths that are not affected by dust absorption. The spectral residuals are splined to a high spectral resolution and convolved with the at surface spectral irradiance modulated by local topography, and subsequently integrated to the instantaneous surface radiative forcing. I demonstrate the model with retrievals in the Zagros Mountains, Iran and the San Juan Mountains, Colorado, USA. Preliminary validation of the model with in situ detailed pyranometer measurements in the San Juan Mountains indicates that the model has uncertainties of < 7 W/m2.</p> </li> </ol> <div class="pull-right"> <ul class="pagination"> <li><a href="#" onclick='return showDiv("page_1");'>«</a></li> <li><a href="#" onclick='return showDiv("page_5");'>5</a></li> <li><a href="#" onclick='return showDiv("page_6");'>6</a></li> <li class="active"><span>7</span></li> <li><a href="#" onclick='return showDiv("page_8");'>8</a></li> <li><a href="#" onclick='return showDiv("page_9");'>9</a></li> <li><a href="#" onclick='return showDiv("page_25");'>»</a></li> </ul> </div> </div><!-- col-sm-12 --> </div><!-- row --> </div><!-- page_7 --> <div id="page_8" class="hiddenDiv"> <div class="row"> <div class="col-sm-12"> <div class="pull-right"> <ul class="pagination"> <li><a href="#" onclick='return showDiv("page_1");'>«</a></li> <li><a href="#" onclick='return showDiv("page_6");'>6</a></li> <li><a href="#" onclick='return showDiv("page_7");'>7</a></li> <li class="active"><span>8</span></li> <li><a href="#" onclick='return showDiv("page_9");'>9</a></li> <li><a href="#" onclick='return showDiv("page_10");'>10</a></li> <li><a href="#" onclick='return showDiv("page_25");'>»</a></li> </ul> </div> </div> </div> <div class="row"> <div class="col-sm-12"> <ol class="result-class" start="141"> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2014AGUFM.A21F3096B','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2014AGUFM.A21F3096B"><span id="translatedtitle">In-Depth Evaluation of <span class="hlt">Aqua</span> <span class="hlt">MODIS</span> Collection 6 AOD Parameters Over the Contintinental U.S. Via Comparison to Both Ground-Truth and Modeled Data</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Belle, J. H.; Liu, Y.</p> <p>2014-12-01</p> <p>We evaluated all four <span class="hlt">MODIS</span> Collection 6 aerosol AOD parameters: 10 km Dark-Target, 3 km Dark-Target, 10 km Deep-Blue, and 10 km merged Dark-Target and Deep-Blue over the continental U.S. for the years 2011-2013 using AERONET observations. General results of this evaluation are illustrated in the attached figure, which includes data from 84 permanent AERONET sites and 64 DRAGON sites. There are indications of positive retrieval error in the AOD over the continental U.S. for Dark-Target and merged AOD parameters, such that slopes are greater than one, and the percentage of observations above the error envelope (EE, ±(0.05 + 0.15*AERONET AOD) is greater than the percentage below. In contrast, Deep-Blue has a large number of values within the error envelope. However, the correlation with ground observations is poor (r=0.73), the bias is relatively high (0.03) and the slope is below 1 (0.77). While coverage for Deep-Blue retrievals has been improved in Collection 6, the 10 km merged parameter, while partially dependent on Deep-Blue retrievals, performs poorly with regards to coverage, particularly for lower confidence values. For this parameter, an average of only 40.2% of pixels in a valid AERONET-<span class="hlt">MODIS</span> collocation has any retrieved values. This is in comparison to 72.9% of Deep-Blue pixels and 59.5% of Dark-Target pixels in the same 10 km product. Correlation coefficients between <span class="hlt">MODIS</span> and AERONET AOD over the Western U.S. are significantly lower (between 0.67 and 0.71) than those in the East, (between 0.84 and 0.93). However, Dark-Target and merged AOD parameters from the West do not show overall positive retrieval errors, and have regression slopes against AERONET observations between 0.98 and 1.02. <span class="hlt">MODIS</span> aerosol products are further combined with information from the <span class="hlt">MODIS</span> 16-day gridded NDVI (Normalized Difference Vegetation Index) product, Global Multi-resolution Terrain Elevation Data (GMTED2010), and the National Land Cover Database (NLCD) to elucidate ground</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/20110015244','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20110015244"><span id="translatedtitle">Using Lunar Observations to Assess Terra <span class="hlt">MODIS</span> Thermal Emissive Bands Calibration</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Xiong, Xiaoxiong; Chen, Hongda</p> <p>2010-01-01</p> <p><span class="hlt">MODIS</span> collects data in both the <span class="hlt">reflected</span> solar and thermal emissive regions using 36 spectral bands. The center wavelengths of these bands cover the3.7 to 14.24 micron region. In addition to using its on-board calibrators (OBC), which include a full aperture solar diffuser (SD) and a blackbody (BB), lunar observations have been scheduled on a regular basis to support both Terra and <span class="hlt">Aqua</span> <span class="hlt">MODIS</span> on-orbit calibration and characterization. This paper provides an overview of <span class="hlt">MODIS</span> lunar observations and their applications for the <span class="hlt">reflective</span> solar bands (RSB) and thermal emissive bands (TEB) with an emphasis on potential calibration improvements of <span class="hlt">MODIS</span> band 21 at 3.96 microns. This spectral band has detectors set with low gains to enable fire detection. Methodologies are proposed and examined on the use of lunar observations for the band 21 calibration. Also presented in this paper are preliminary results derived from Terra <span class="hlt">MODIS</span> lunar observations and remaining challenging issues.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=3673426','PMC'); return false;" href="http://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=3673426"><span id="translatedtitle">Inter-Comparison of ASTER and <span class="hlt">MODIS</span> Surface <span class="hlt">Reflectance</span> and Vegetation Index Products for Synergistic Applications to Natural Resource Monitoring</span></a></p> <p><a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pmc">PubMed Central</a></p> <p>Miura, Tomoaki; Yoshioka, Hiroki; Fujiwara, Kayo; Yamamoto, Hirokazu</p> <p>2008-01-01</p> <p>Synergistic applications of multi-resolution satellite data have been of a great interest among user communities for the development of an improved and more effective operational monitoring system of natural resources, including vegetation and soil. In this study, we conducted an inter-comparison of two remote sensing products, namely, visible/near-infrared surface <span class="hlt">reflectances</span> and spectral vegetation indices (VIs), from the high resolution Advanced Thermal Emission and <span class="hlt">Reflection</span> Radiometer (ASTER) (15 m) and lower resolution Moderate Resolution Imaging Spectroradiometer (<span class="hlt">MODIS</span>) (250 m – 500 m) sensors onboard the Terra platform. Our analysis was aimed at understanding the degree of radiometric compatibility between the two sensors' products due to sensor spectral bandpasses and product generation algorithms. Multiple pairs of ASTER and <span class="hlt">MODIS</span> standard surface <span class="hlt">reflectance</span> products were obtained at randomly-selected, globally-distributed locations, from which two types of VIs were computed: the normalized difference vegetation index and the enhanced vegetation indices with and without a blue band. Our results showed that these surface <span class="hlt">reflectance</span> products and the derived VIs compared well between the two sensors at a global scale, but subject to systematic differences, of which magnitudes varied among scene pairs. An independent assessment of the accuracy of ASTER and <span class="hlt">MODIS</span> standard products, in which “in-house” surface <span class="hlt">reflectances</span> were obtained using in situ Aeronet atmospheric data for comparison, suggested that the performance of the ASTER atmospheric correction algorithm may be variable, reducing overall quality of its standard <span class="hlt">reflectance</span> product. Atmospheric aerosols, which were not corrected for in the ASTER algorithm, were found not to impact the quality of the derived <span class="hlt">reflectances</span>. Further investigation is needed to identify the sources of inconsistent atmospheric correction results associated with the ASTER algorithm, including additional quality</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/20120010372','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20120010372"><span id="translatedtitle">Evaluation of Detector-to-Detector and Mirror Side Differences for Terra <span class="hlt">MODIS</span> <span class="hlt">Reflective</span> Solar Bands Using Simultaneous MISR Observations</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Wu, Aisheng; Xiong, Xiaoxiong; Angal, A.; Barnes, W.</p> <p>2011-01-01</p> <p>The Moderate Resolution Imaging Spectroradiometer (<span class="hlt">MODIS</span>) 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. <span class="hlt">MODIS</span> 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. <span class="hlt">MODIS</span> makes observations using a two-sided paddle-wheel scan mirror. Its on-board calibrators (OBCs) for the <span class="hlt">reflective</span> 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 <span class="hlt">MODIS</span> observed Earth scene <span class="hlt">reflectances</span> to track the detector-to-detector and mirror side differences. Simultaneous observed <span class="hlt">reflectances</span> from the Multi-angle Imaging Spectroradiometer (MISR), also onboard the Terra spacecraft, are used with <span class="hlt">MODIS</span> observed <span class="hlt">reflectances</span> 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</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2015AMT.....8.5237J','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2015AMT.....8.5237J"><span id="translatedtitle">Adaption of the <span class="hlt">MODIS</span> aerosol retrieval algorithm using airborne spectral surface <span class="hlt">reflectance</span> measurements over urban areas: a case study</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Jäkel, E.; Mey, B.; Levy, R.; Gu, X.; Yu, T.; Li, Z.; Althausen, D.; Heese, B.; Wendisch, M.</p> <p>2015-12-01</p> <p><span class="hlt">MODIS</span> (MOderate-resolution Imaging Spectroradiometer) retrievals of aerosol optical depth (AOD) are biased over urban areas, primarily because the <span class="hlt">reflectance</span> characteristics of urban surfaces are different than that assumed by the retrieval algorithm. Specifically, the operational "dark-target" retrieval is tuned towards vegetated (dark) surfaces and assumes a spectral relationship to estimate the surface <span class="hlt">reflectance</span> in blue and red wavelengths. From airborne measurements of surface <span class="hlt">reflectance</span> over the city of Zhongshan, China, were collected that could replace the assumptions within the <span class="hlt">MODIS</span> retrieval algorithm. The subsequent impact was tested upon two versions of the operational algorithm, Collections 5 and 6 (C5 and C6). AOD retrieval results of the operational and modified algorithms were compared for a specific case study over Zhongshan to show minor differences between them all. However, the Zhongshan-based spectral surface relationship was applied to a much larger urban sample, specifically to the <span class="hlt">MODIS</span> data taken over Beijing between 2010 and 2014. These results were compared directly to ground-based AERONET (AErosol RObotic NETwork) measurements of AOD. A significant reduction of the differences between the AOD retrieved by the modified algorithms and AERONET was found, whereby the mean difference decreased from 0.27±0.14 for the operational C5 and 0.19±0.12 for the operational C6 to 0.10±0.15 and -0.02±0.17 by using the modified C5 and C6 retrievals. Since the modified algorithms assume a higher contribution by the surface to the total measured <span class="hlt">reflectance</span> from <span class="hlt">MODIS</span>, consequently the overestimation of AOD by the operational methods is reduced. Furthermore, the sensitivity of the <span class="hlt">MODIS</span> AOD retrieval with respect to different surface types was investigated. Radiative transfer simulations were performed to model <span class="hlt">reflectances</span> at top of atmosphere for predefined aerosol properties. The <span class="hlt">reflectance</span> data were used as input for the retrieval methods. It</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/20160006614','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20160006614"><span id="translatedtitle">Consistency of CERES Radiances and Fluxes from <span class="hlt">Aqua</span> and Suomi-NPP</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Liang, Lusheng; Miller, Walter; Su, Wenying; Loeb, Norman</p> <p>2015-01-01</p> <p>The Clouds and Earth's Radiant Energy System (CERES) instruments on board Terra, <span class="hlt">Aqua</span>, and Suomi-NPP have been providing data products critical to advancing our understanding of the effects of clouds and aerosols on radiative energy within the Earth-atmosphere system. The CERES instrument consists of a threechannel broadband scanning radiometer. The scanning radiometer measures radiances in shortwave (SW, 0.3-5 micron), window (WN, 8-12 micron), and total (0.3-200 micron) channels. The longwave (LW) component is derived as the difference between total and SW channels. These measured radiances at a given sun-Earthsatellite geometry are converted to outgoing <span class="hlt">reflected</span> solar and emitted thermal TOA radiative fluxes by using CERES scene-type dependent angular distribution models (ADMs). The CERES instruments must remain radiometrically stable and correctly inter-calibrated to accurately capture changes in Earth"s radiation budget from interannual to decadal timescales. This presentation will focus on comparisons between collocated radiance measurements from CERES instruments on <span class="hlt">Aqua</span> and on Suomi-NPP. As we do not have a set of ADMs that is constructed specifically for the CERES instrument on Suomi-NPP, CERES <span class="hlt">Aqua</span> ADMs are used to invert fluxes from radiance measurements on Suomi-NPP. But the CERES <span class="hlt">Aqua</span> footprint size is smaller than the CERES Suomi-NPP footprint size and the scene identifications provided by <span class="hlt">MODIS</span> and VIIRS can also be different from each other. Will using <span class="hlt">Aqua</span> ADMs for Suomi-NPP flux inversion increase the flux uncertainty? We will examine the deseasonalized flux anomaly time series using <span class="hlt">Aqua</span> data alone and using combined <span class="hlt">Aqua</span> and Suomi-NPP data. We will also present a simulation study to assess the Suomi-NPP flux uncertainty from using <span class="hlt">Aqua</span> ADMs for the flux inversion.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://ntrs.nasa.gov/search.jsp?R=20160005757&hterms=scientific&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D10%26Ntt%3Dscientific','NASA-TRS'); return false;" href="http://ntrs.nasa.gov/search.jsp?R=20160005757&hterms=scientific&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D10%26Ntt%3Dscientific"><span id="translatedtitle">Scientific Impact of <span class="hlt">MODIS</span> C5 Calibration Degradation and C6+ Improvements</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Lyapustin, A.; Wang, Y.; Xiong, X.; Meister, G.; Platnick, S.; Levy, R.; Franz, B.; Korkin, S.; Hilker, T.; Tucker, J.; Hall, F.; Sellers, P.; Wu, A.; Angal, A.</p> <p>2014-01-01</p> <p>The Collection 6 (C6) <span class="hlt">MODIS</span> (Moderate Resolution Imaging Spectroradiometer) land and atmosphere data sets are scheduled for release in 2014. C6 contains significant revisions of the calibration approach to account for sensor aging. This analysis documents the presence of systematic temporal trends in the visible and near-infrared (500 m) bands of the Collection 5 (C5) <span class="hlt">MODIS</span> Terra and, to lesser extent, in <span class="hlt">MODIS</span> <span class="hlt">Aqua</span> geophysical data sets. Sensor degradation is largest in the blue band (B3) of the <span class="hlt">MODIS</span> sensor on Terra and decreases with wavelength. Calibration degradation causes negative global trends in multiple <span class="hlt">MODIS</span> C5 products including the dark target algorithm's aerosol optical depth over land and Ångstrom exponent over the ocean, global liquid water and ice cloud optical thickness, as well as surface <span class="hlt">reflectance</span> and vegetation indices, including the normalized difference vegetation index (NDVI) and enhanced vegetation index (EVI). As the C5 production will be maintained for another year in parallel with C6, one objective of this paper is to raise awareness of the calibration-related trends for the broad <span class="hlt">MODIS</span> user community. The new C6 calibration approach removes major calibrations trends in the Level 1B (L1B) data. This paper also introduces an enhanced C6C calibration of the <span class="hlt">MODIS</span> data set which includes an additional polarization correction (PC) to compensate for the increased polarization sensitivity of <span class="hlt">MODIS</span> Terra since about 2007, as well as detrending and Terra- <span class="hlt">Aqua</span> cross-calibration over quasi-stable desert calibration sites. The PC algorithm, developed by the <span class="hlt">MODIS</span> ocean biology processing group (OBPG), removes residual scan angle, mirror side and seasonal biases from aerosol and surface <span class="hlt">reflectance</span> (SR) records along with spectral distortions of SR. Using the multiangle implementation of atmospheric correction (MAIAC) algorithm over deserts, we have also developed a detrending and cross-calibration method which removes residual decadal trends on</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2014AMT.....7.4353L','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2014AMT.....7.4353L"><span id="translatedtitle">Scientific impact of <span class="hlt">MODIS</span> C5 calibration degradation and C6+ improvements</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Lyapustin, A.; Wang, Y.; Xiong, X.; Meister, G.; Platnick, S.; Levy, R.; Franz, B.; Korkin, S.; Hilker, T.; Tucker, J.; Hall, F.; Sellers, P.; Wu, A.; Angal, A.</p> <p>2014-12-01</p> <p>The Collection 6 (C6) <span class="hlt">MODIS</span> (Moderate Resolution Imaging Spectroradiometer) land and atmosphere data sets are scheduled for release in 2014. C6 contains significant revisions of the calibration approach to account for sensor aging. This analysis documents the presence of systematic temporal trends in the visible and near-infrared (500 m) bands of the Collection 5 (C5) <span class="hlt">MODIS</span> Terra and, to lesser extent, in <span class="hlt">MODIS</span> <span class="hlt">Aqua</span> geophysical data sets. Sensor degradation is largest in the blue band (B3) of the <span class="hlt">MODIS</span> sensor on Terra and decreases with wavelength. Calibration degradation causes negative global trends in multiple <span class="hlt">MODIS</span> C5 products including the dark target algorithm's aerosol optical depth over land and Ångström exponent over the ocean, global liquid water and ice cloud optical thickness, as well as surface <span class="hlt">reflectance</span> and vegetation indices, including the normalized difference vegetation index (NDVI) and enhanced vegetation index (EVI). As the C5 production will be maintained for another year in parallel with C6, one objective of this paper is to raise awareness of the calibration-related trends for the broad <span class="hlt">MODIS</span> user community. The new C6 calibration approach removes major calibrations trends in the Level 1B (L1B) data. This paper also introduces an enhanced C6+ calibration of the <span class="hlt">MODIS</span> data set which includes an additional polarization correction (PC) to compensate for the increased polarization sensitivity of <span class="hlt">MODIS</span> Terra since about 2007, as well as detrending and Terra-<span class="hlt">Aqua</span> cross-calibration over quasi-stable desert calibration sites. The PC algorithm, developed by the <span class="hlt">MODIS</span> ocean biology processing group (OBPG), removes residual scan angle, mirror side and seasonal biases from aerosol and surface <span class="hlt">reflectance</span> (SR) records along with spectral distortions of SR. Using the multiangle implementation of atmospheric correction (MAIAC) algorithm over deserts, we have also developed a detrending and cross-calibration method which removes residual decadal trends on</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2014AMTD....7.7281L','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2014AMTD....7.7281L"><span id="translatedtitle">Science impact of <span class="hlt">MODIS</span> C5 calibration degradation and C6+ improvements</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Lyapustin, A.; Wang, Y.; Xiong, X.; Meister, G.; Platnick, S.; Levy, R.; Franz, B.; Korkin, S.; Hilker, T.; Tucker, J.; Hall, F.; Sellers, P.; Wu, A.; Angal, A.</p> <p>2014-07-01</p> <p>The Collection 6 (C6) <span class="hlt">MODIS</span> land and atmosphere datasets are scheduled for release in 2014. C6 contains significant revisions of the calibration approach to account for sensor aging. This analysis documents the presence of systematic temporal trends in the visible and near-infrared (500 m) bands of the Collection 5 (C5) <span class="hlt">MODIS</span> Terra, and to lesser extent, in <span class="hlt">MODIS</span> <span class="hlt">Aqua</span> geophysical datasets. Sensor degradation is largest in the Blue band (B3) of the <span class="hlt">MODIS</span> sensor on Terra and decreases with wavelength. Calibration degradation causes negative global trends in multiple <span class="hlt">MODIS</span> C5 products including the dark target algorithm's aerosol optical depth over land and Ångström Exponent over the ocean, global liquid water and ice cloud optical thickness, as well as surface <span class="hlt">reflectance</span> and vegetation indices, including the normalized difference vegetation index (NDVI) and enhanced vegetation index (EVI). As the C5 production will be maintained for another year in parallel with C6, one objective of this paper is to raise awareness of the calibration-related trends for the broad <span class="hlt">MODIS</span> user community. The new C6 calibration approach removes major calibrations trends in the Level 1B (L1B) data. This paper also introduces an enhanced C6+ calibration of the <span class="hlt">MODIS</span> dataset which includes an additional polarization correction (PC) to compensate for the increased polarization sensitivity of <span class="hlt">MODIS</span> Terra since about 2007, as well as de-trending and Terra-<span class="hlt">Aqua</span> cross-calibration over quasi-stable desert calibration sites. The PC algorithm, developed by the <span class="hlt">MODIS</span> ocean biology processing group (OBPG), removes residual scan angle, mirror side and seasonal biases from aerosol and surface <span class="hlt">reflectance</span> (SR) records along with spectral distortions of SR. Using the Multi-Angle Implementation of Atmospheric Correction (MAIAC) algorithm over deserts, we have also developed a de-trending and cross-calibration method which removes residual decadal trends on the order of several tenths of one percent of</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/20110015444','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20110015444"><span id="translatedtitle">Impact of Sensor Degradation on the <span class="hlt">MODIS</span> NDVI Time Series</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Wang, Dongdong; Morton, Douglas; Masek, Jeffrey; Wu, Aisheng; Nagol, Jyoteshwar; Xiong, Xiaoxiong; Levy, Robert; Vermote, Eric; Wolfe, Robert</p> <p>2011-01-01</p> <p>Time series of satellite data provide unparalleled information on the response of vegetation to climate variability. Detecting subtle changes in vegetation over time requires consistent satellite-based measurements. Here, we evaluated the impact of sensor degradation on trend detection using Collection 5 data from the Moderate Resolution Imaging Spectroradiometer (<span class="hlt">MODIS</span>) sensors on the Terra and <span class="hlt">Aqua</span> platforms. For Terra <span class="hlt">MODIS</span>, the impact of blue band (Band 3, 470nm) degradation on simulated surface <span class="hlt">reflectance</span> was most pronounced at near-nadir view angles, leading to a 0.001-0.004/yr decline in Normalized Difference Vegetation Index (NDVI) under a range of simulated aerosol conditions and surface types. Observed trends <span class="hlt">MODIS</span> NDVI over North America were consistent with simulated results, with nearly a threefold difference in negative NDVI trends derived from Terra (17.4%) and <span class="hlt">Aqua</span> (6.7%) <span class="hlt">MODIS</span> sensors during 2002-2010. Planned adjustments to Terra <span class="hlt">MODIS</span> calibration for Collection 6 data reprocessing will largely eliminate this negative bias in NDVI trends over vegetation.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/20140009143','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20140009143"><span id="translatedtitle">Impact of Sensor Degradation on the <span class="hlt">MODIS</span> NDVI Time Series</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Wang, Dongdong; Morton, Douglas Christopher; Masek, Jeffrey; Wu, Aisheng; Nagol, Jyoteshwar; Xiong, Xiaoxiong; Levy, Robert; Vermote, Eric; Wolfe, Robert</p> <p>2012-01-01</p> <p>Time series of satellite data provide unparalleled information on the response of vegetation to climate variability. Detecting subtle changes in vegetation over time requires consistent satellite-based measurements. Here, the impact of sensor degradation on trend detection was evaluated using Collection 5 data from the Moderate Resolution Imaging Spectroradiometer (<span class="hlt">MODIS</span>) sensors on the Terra and <span class="hlt">Aqua</span> platforms. For Terra <span class="hlt">MODIS</span>, the impact of blue band (Band 3, 470 nm) degradation on simulated surface <span class="hlt">reflectance</span> was most pronounced at near-nadir view angles, leading to a 0.001-0.004 yr-1 decline in Normalized Difference Vegetation Index (NDVI) under a range of simulated aerosol conditions and surface types. Observed trends in <span class="hlt">MODIS</span> NDVI over North America were consistentwith simulated results,with nearly a threefold difference in negative NDVI trends derived from Terra (17.4%) and <span class="hlt">Aqua</span> (6.7%) <span class="hlt">MODIS</span> sensors during 2002-2010. Planned adjustments to Terra <span class="hlt">MODIS</span> calibration for Collection 6 data reprocessing will largely eliminate this negative bias in detection of NDVI trends.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/20120010660','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20120010660"><span id="translatedtitle">Critical <span class="hlt">Reflectance</span> Derived from <span class="hlt">MODIS</span>: Application for the Retrieval of Aerosol Absorption over Desert Regions</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Wells, Kelley C.; Martins, J. Vanderlei; Remer, Lorraine A.; Kreidenweis, Sonia M.; Stephens, Graeme L.</p> <p>2012-01-01</p> <p>Aerosols are tiny suspended particles in the atmosphere that scatter and absorb sunlight. Smoke particles are aerosols, as are sea salt, particulate pollution and airborne dust. When you look down at the earth from space sometimes you can see vast palls of whitish smoke or brownish dust being transported by winds. The reason that you can see these aerosols is because they are <span class="hlt">reflecting</span> incoming sunlight back to the view in space. The reason for the difference in color between the different types of aerosol is that the particles arc also absorbing sunlight at different wavelengths. Dust appears brownish or reddish because it absorbs light in the blue wavelengths and scatters more reddish light to space, Knowing how much light is scattered versus how much is absorbed, and knowin that as a function of wavelength is essential to being able to quantify the role aerosols play in the energy balance of the earth and in climate change. It is not easy measuring the absorption properties of aerosols when they are suspended in the atmosphere. People have been doing this one substance at a time in the laboratory, but substances mix when they are in the atmosphere and the net absorption effect of all the particles in a column of air is a goal of remote sensing that has not yet been completely successful. In this paper we use a technique based on observing the point at which aerosols change from brightening the surface beneath to darkening it. If aerosols brighten a surface. they must scatter more light to space. If they darken the surface. they must be absorbing more. That cross over point is called the critical <span class="hlt">reflectance</span> and in this paper we show that critical <span class="hlt">reflectance</span> is a monotonic function of the intrinsic absorption properties of the particles. This parameter we call the single scattering albedo. We apply the technique to <span class="hlt">MODIS</span> imagery over the Sahara and Sahel regions to retrieve the single scattering albedo in seven wavelengths, compare these retrievals to ground</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://www.ncbi.nlm.nih.gov/pubmed/23038327','PUBMED'); return false;" href="http://www.ncbi.nlm.nih.gov/pubmed/23038327"><span id="translatedtitle">Validation of <span class="hlt">MODIS</span>-derived bidirectional <span class="hlt">reflectivity</span> retrieval algorithm in mid-infrared channel with field measurements.</span></a></p> <p><a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a></p> <p>Tang, Bo-Hui; Wu, Hua-; Li, Zhao-Liang; Nerry, Françoise</p> <p>2012-07-30</p> <p>This work addressed the validation of the <span class="hlt">MODIS</span>-derived bidirectional <span class="hlt">reflectivity</span> retrieval algorithm in mid-infrared (MIR) channel, proposed by Tang and Li [Int. J. Remote Sens. 29, 4907 (2008)], with ground-measured data, which were collected from a field campaign that took place in June 2004 at the ONERA (Office National d'Etudes et de Recherches Aérospatiales) center of Fauga-Mauzac, on the PIRRENE (Programme Interdisciplinaire de Recherche sur la Radiométrie en Environnement Extérieur) experiment site [Opt. Express 15, 12464 (2007)]. The leaving-surface spectral radiances measured by a BOMEM (MR250 Series) Fourier transform interferometer were used to calculate the ground brightness temperatures with the combination of the inversion of the Planck function and the spectral response functions of <span class="hlt">MODIS</span> channels 22 and 23, and then to estimate the ground brightness temperature without the contribution of the solar direct beam and the bidirectional <span class="hlt">reflectivity</span> by using Tang and Li's proposed algorithm. On the other hand, the simultaneously measured atmospheric profiles were used to obtain the atmospheric parameters and then to calculate the ground brightness temperature without the contribution of the solar direct beam, based on the atmospheric radiative transfer equation in the MIR region. Comparison of those two kinds of brightness temperature obtained by two different methods indicated that the Root Mean Square Error (RMSE) between the brightness temperatures estimated respectively using Tang and Li's algorithm and the atmospheric radiative transfer equation is 1.94 K. In addition, comparison of the hemispherical-directional <span class="hlt">reflectances</span> derived by Tang and Li's algorithm with those obtained from the field measurements showed that the RMSE is 0.011, which indicates that Tang and Li's algorithm is feasible to retrieve the bidirectional <span class="hlt">reflectivity</span> in MIR channel from <span class="hlt">MODIS</span> data. PMID:23038327</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://ntrs.nasa.gov/search.jsp?R=20020006092&hterms=Franco&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAuthor-Name%26N%3D0%26No%3D70%26Ntt%3DFranco','NASA-TRS'); return false;" href="http://ntrs.nasa.gov/search.jsp?R=20020006092&hterms=Franco&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAuthor-Name%26N%3D0%26No%3D70%26Ntt%3DFranco"><span id="translatedtitle">The <span class="hlt">Aqua</span>-Aura Train</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Schoeberl, Mark; Einaudi, Franco (Technical Monitor)</p> <p>2001-01-01</p> <p>This talk will focus on the afternoon constellation of EOS platforms and the scientific benefits that arise from this formation. The afternoon EOS constellation or the "A-train" will provide unprecedented information on clouds and aerosols. At 1:30 PM crossing time EOS-<span class="hlt">Aqua</span> begins the train with the <span class="hlt">MODIS</span>, CERES and AIRS instruments making aerosol, cloud, radiation budget , temperature and water vapor measurements. AMSR-E will also make total column water measurements. Following <span class="hlt">Aqua</span> by one minute, Cloudsat will make active radar precipitation measurements as and PICASSOCENA will make lidar measurements of clouds and aerosols. Fourteen minutes later, EOS-Aura will pass through the same space making upper troposphere water vapor and ice profiles as well as some key trace gases associated with convective processes (MLS and HIRDLS). Additional measurements of aerosols will be made by Aura's OMI instrument.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://ntrs.nasa.gov/search.jsp?R=20040171530&hterms=Measuring+instruments&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D80%26Ntt%3DMeasuring%2Binstruments','NASA-TRS'); return false;" href="http://ntrs.nasa.gov/search.jsp?R=20040171530&hterms=Measuring+instruments&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D80%26Ntt%3DMeasuring%2Binstruments"><span id="translatedtitle">Polarization Ray Trace Model of the <span class="hlt">MODIS</span> Instrument</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Waluschka, Eugene; Xiong, Jack; Esaias, Wayne E.; Voss, Kenneth; Souaidia, Nordine; Pellicori, Samuel; Moyer, David; Guenther, Bruce; Barnes, William</p> <p>2004-01-01</p> <p>Sunlight <span class="hlt">reflected</span> from the earth is, to a certain extent, polarized. Radiometers, such as the <span class="hlt">MODIS</span> instrument on board the TERRA and <span class="hlt">AQUA</span> spacecraft, are to a certain extent polarizers. Accurate radiometric measurements must take into account both the polarization state of the scene and the polarization sensitivity of the measuring instrument. The measured polarization characteristics of the <span class="hlt">MODIS</span> instruments are contained in various radiometric models. Continued use of these radiometric math models, over a number of years, have shown where these models can be improved. Currently a <span class="hlt">MODIS</span> polarization ray trace model has been created which models the thin film structure on the optical elements. This approach is described and modeled and measured instrument polarization sensitivity results presented.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2016JGRD..121.6273Z','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2016JGRD..121.6273Z"><span id="translatedtitle">Intercalibration of CERES, <span class="hlt">MODIS</span>, and MISR <span class="hlt">reflected</span> solar radiation and its application to albedo trends</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Zhan, Yizhe; Davies, Roger</p> <p>2016-06-01</p> <p>Measurements on the Terra satellite by the Cloud and the Earth's Radiant Energy System (CERES), the Moderate Resolution Imaging Spectroradiometer (<span class="hlt">MODIS</span>), and the Multiangle Imaging Spectroradiometer (MISR), between 2001 and 2015 over the polar regions, are analyzed in order to investigate the intercalibration differences between these instruments. Direct comparisons of colocated near-nadir radiances from CERES, <span class="hlt">MODIS</span>, and MISR show relative agreement within 2.4% decade-1. By comparison with the CERES shortwave broadband, <span class="hlt">MODIS</span> Collection 6 is getting brighter, by 1.0 ± 0.7% decade-1 in the red band and 1.4 ± 0.7% decade-1 in the near infrared. MISR's red and near-infrared bands, however, show darkening trends of -1.0 ± 0.6% decade-1 and -1.1 ± 0.6% decade-1, respectively. The CERES/<span class="hlt">MODIS</span> or CERES/MISR visible and near IR radiance ratio is shown to have a significant negative correlation with precipitable water content over the Antarctic Plateau. The intercalibration results successfully correct the differential top-of-atmosphere trends in zonal albedos between CERES and MISR.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/20020083259','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20020083259"><span id="translatedtitle">Relationship Between Surface <span class="hlt">Reflectance</span> in the Visible and Mid-IR used in <span class="hlt">MODIS</span> Aerosol Algorithm-Theory</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Kaufman, Yoram J.; Gobron, Nadine; Pinty, Bernard; Widlowski, Jean-Luc; Verstraete, Michel M.; Lau, William K. M. (Technical Monitor)</p> <p>2002-01-01</p> <p>Data from the Moderate Resolution Imaging Spectroradiometer (<span class="hlt">MODIS</span>) instrument that flies in polar orbit on the Terra platform, are used to derive the aerosol optical thickness and properties over land and ocean. The relationships between visible <span class="hlt">reflectance</span> (at blue, rho(sub blue), and red, rho(sub red)) and mid-infrared (at 2.1 microns, rho(sub 2.1)) are used in the <span class="hlt">MODIS</span> aerosol retrieval algorithm to derive global distribution of aerosols over the land. These relations have been established from a series of measurements indicating that rho(sub blue) is approximately 0.5 rho(sub red) is approximately 0.25 rho(sub 2.1). Here we use a model to describe the transfer of radiation through a vegetation canopy composed of randomly oriented leaves to assess the theoretical foundations for these relationships. Calculations for a wide range of leaf area indices and vegetation fractions show that rho(sub blue) is consistently about 1/4 of rho(sub 2.1) as used by <span class="hlt">MODIS</span> for the whole range of analyzed cases, except for very dark soils, such as those found in burn scars. For its part, the ratio rho(sub red)/rho(sub 2.1) varies from less than the empirically derived value of 1/2 for dense and dark vegetation, to more than 1/2 for bright mixture of soil and vegetation. This is in agreement with measurements over uniform dense vegetation, but not with measurements over mixed dark scenes. In the later case the discrepancy is probably mitigated by shadows due to uneven canopy and terrain on a large scale. It is concluded that the value of this ratio should ideally be made dependent on the land cover type in the operational processing of <span class="hlt">MODIS</span> data, especially over dense forests.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://ntrs.nasa.gov/search.jsp?R=20160005180&hterms=orbit&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D80%26Ntt%3Dorbit','NASA-TRS'); return false;" href="http://ntrs.nasa.gov/search.jsp?R=20160005180&hterms=orbit&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D80%26Ntt%3Dorbit"><span id="translatedtitle">On-Orbit Performance of <span class="hlt">MODIS</span> Solar Diffuser Stability Monitor</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Xiong, Xiaoxiong; Angal, Amit; Choi, Taeyoung; Sun, Jungiang; Johnson, Eric</p> <p>2014-01-01</p> <p><span class="hlt">MODIS</span> <span class="hlt">reflective</span> solar bands (RSB) calibration is provided by an on-board solar diffuser (SD). On-orbit changes in the SD bi-directional <span class="hlt">reflectance</span> factor (BRF) are tracked by a solar diffuser stability monitor (SDSM). The SDSM consists of a solar integration sphere (SIS) with nine detectors covering wavelengths from 0.41 to 0.94 microns. It functions as a ratioing radiometer, making alternate observations of the sunlight through a fixed attenuation screen and the sunlight diffusely <span class="hlt">reflected</span> from the SD during each scheduled SD/SDSM calibration event. Since launch, Terra and <span class="hlt">Aqua</span> <span class="hlt">MODIS</span> SD/SDSM systems have been operated regularly to support the RSB on-orbit calibration. This paper provides an overview of <span class="hlt">MODIS</span> SDSM design functions, its operation and calibration strategies, and on-orbit performance. Changes in SDSM detector responses over time and their potential impact on tracking SD on-orbit degradation are examined. Also presented in this paper are lessons learned from <span class="hlt">MODIS</span> SD/SDSM calibration system and improvements made to the VIIRS SD/SDSM system, including preliminary comparisons of <span class="hlt">MODIS</span> and VIIRS SDSM on-orbit performance.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2012SPIE.8510E..0HX','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2012SPIE.8510E..0HX"><span id="translatedtitle">On-orbit performance of <span class="hlt">MODIS</span> solar diffuser stability monitor</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Xiong, Xiaoxiong (Jack); Angal, Amit; Choi, Taeyoung; Sun, Junqiang; Johnson, Eric</p> <p>2012-09-01</p> <p><span class="hlt">MODIS</span> <span class="hlt">reflective</span> solar bands (RSB) calibration is provided by an on-board solar diffuser (SD). On-orbit changes in the SD bi-directional <span class="hlt">reflectance</span> factor (BRF) are tracked by a solar diffuser stability monitor (SDSM). The SDSM consists of a solar integration sphere (SIS) with nine detectors covering wavelengths from 0.41 to 0.94 μm. It functions as a ratioing radiometer, making alternate observations of the sunlight through a fixed attenuation screen and the sunlight diffusely <span class="hlt">reflected</span> from the SD during each scheduled SD/SDSM calibration event. Since launch, Terra and <span class="hlt">Aqua</span> <span class="hlt">MODIS</span> SD/SDSM systems have been operated regularly to support the RSB on-orbit calibration. This paper provides an overview of <span class="hlt">MODIS</span> SDSM design functions, its operation and calibration strategies, and on-orbit performance. Changes in SDSM detector responses over time and their potential impact on tracking SD on-orbit degradation are examined. Also presented in this paper are lessons learned from <span class="hlt">MODIS</span> SD/SDSM calibration system and improvements made to the VIIRS SD/SDSM system, including preliminary comparisons of <span class="hlt">MODIS</span> and VIIRS SDSM on-orbit performance.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/20100020136','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20100020136"><span id="translatedtitle">Remote Sensing of the Absorption Coefficients and Chlorophyll a Concentration in the U.S. Southern Middle Atlantic Bight from SeaWiFS and <span class="hlt">MODIS-Aqua</span></span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Pan, Xiaoju; Mannino, Antonio; Russ, Mary E.; Hooker, Stanford B.</p> <p>2008-01-01</p> <p>At present, satellite remote sensing of coastal water quality and constituent concentration is subject to large errors as compared to the capability of satellite sensors in oceanic waters. In this study, field measurements collected on a series of cruises within U.S. southern Middle Atlantic Bight (SMAB) were applied to improve retrievals of satellite ocean color products in order to examine the factors that regulate the bio-optical properties within the continental shelf waters of the SMAB. The first objective was to develop improvements in satellite retrievals of absorption coefficients of phytoplankton (a(sub ph)), colored dissolved organic matter (CDOM) (a(sub g)), non-pigmented particles (a(sub d)), and non-pigmented particles plus CDOM (a(sub dg)), and chlorophyll a concentration ([Chl_a]). Several algorithms were compared to derive constituent absorption coefficients from remote sensing <span class="hlt">reflectance</span> (R(sub rs)) ratios. The validation match-ups showed that the mean absolute percent differences (MAPD) were typically less than 35%, although higher errors were found for a(sub d) retrievals. Seasonal and spatial variability of satellite-derived absorption coefficients and [Chl_a] was apparent and consistent with field data. CDOM is a major contributor to the bio-optical properties of the SMAB, accounting for 35-70% of total light absorption by particles plus CDOM at 443 nm, as compared to 30-45% for phytoplankton and 0-20% for non-pigmented particles. The overestimation of [Chl_a] from the operational satellite algorithms may be attributed to the strong CDOM absorption in this region. River discharge is important in controlling the bio-optical environment, but cannot explain all of the regional and seasonal variability of biogeochemical constituents in the SMAB.</p> </li> </ol> <div class="pull-right"> <ul class="pagination"> <li><a href="#" onclick='return showDiv("page_1");'>«</a></li> <li><a href="#" onclick='return showDiv("page_6");'>6</a></li> <li><a href="#" onclick='return showDiv("page_7");'>7</a></li> <li class="active"><span>8</span></li> <li><a href="#" onclick='return showDiv("page_9");'>9</a></li> <li><a href="#" onclick='return showDiv("page_10");'>10</a></li> <li><a href="#" onclick='return showDiv("page_25");'>»</a></li> </ul> </div> </div><!-- col-sm-12 --> </div><!-- row --> </div><!-- page_8 --> <div id="page_9" class="hiddenDiv"> <div class="row"> <div class="col-sm-12"> <div class="pull-right"> <ul class="pagination"> <li><a href="#" onclick='return showDiv("page_1");'>«</a></li> <li><a href="#" onclick='return showDiv("page_7");'>7</a></li> <li><a href="#" onclick='return showDiv("page_8");'>8</a></li> <li class="active"><span>9</span></li> <li><a href="#" onclick='return showDiv("page_10");'>10</a></li> <li><a href="#" onclick='return showDiv("page_11");'>11</a></li> <li><a href="#" onclick='return showDiv("page_25");'>»</a></li> </ul> </div> </div> </div> <div class="row"> <div class="col-sm-12"> <ol class="result-class" start="161"> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2015EGUGA..1713537G','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2015EGUGA..1713537G"><span id="translatedtitle">Intercomparison of <span class="hlt">MODIS-Aqua</span> C051 and C006 Level 3 Deep Blue AOD and Ångström exponent retrievals over the Sahara desert and the Arabian Peninsula during the period 2002-2014</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Gkikas, Antonis; Basart, Sara; Korras-Carraca, Marios; Papadimas, Christos; Hatzianastassiou, Nikos; Sayer, Andrew; Hsu, Christina; Baldasano, Jose Maria</p> <p>2015-04-01</p> <p>Dust loads emitted from the arid regions of Northern Africa and the Arabian Peninsula account for the major portion of the global dust aerosol burden. Depending on prevailing atmospheric circulation they can be transported far away from their source areas. Considering the key role of dust aerosols to weather and climate a better description of their spatial and temporal variability it is an issue of great importance. The main target of the present study is to describe aerosols' regime over Northern Africa and Arabian Peninsula using Deep Blue aerosol optical depth (AOD550nm) and Ångström exponent (α412-470nm) measurements. Given the applied changes to the retrieval algorithm, emphasis is also given to the inter-comparison between the data from Collections 051 and 006. The analysis is performed using <span class="hlt">MODIS-Aqua</span> daily Level 3 data at 1°x1° spatial resolution over the period 2002-2014. The study region extends from 20°W to 60°E and from 0° to 40°N. The obtained long-term geographical distributions reveal many similarities between C051 and C006 AOD retrievals. They both indicate a zone of high AODs along the parallel of 15°N, extending from the western coasts of Africa to Chad where the maximum values (~1.3) are recorded. In the Arabian Peninsula, the maximum AODs (up to 0.6) are found in Iraq. On the contrary, more apparent differences between the two collections are found for α412-470nm. It is evident a reduction of C006 retrievals, which is more pronounced across the Sahara desert. In C006, the α412-470nm values over the deserts of Northern Africa and Middle East mostly vary from 0 to 0.6 while higher values (up to 1.5) are observed in sub-sahel regions, west coasts of Saudi Arabia and Iran. During the study period, in both collections, AOD has decreased by up to 93% in N. Africa (northern parts of Algeria) while it has increased by up to 70% in the Middle East (northern parts of Iraq). Reversed tendencies are found for the α412-470nm retrievals. For</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/20150023337','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20150023337"><span id="translatedtitle"><span class="hlt">MODIS</span> and VIIRS Lunar Observations and Applications</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Xiong, Xiaoxiong; Wang, Zhipeng; Sun, Junqiang; Angal, Amit Avinash; Fulbright, Jon; Butler, James</p> <p>2013-01-01</p> <p>Terra and <span class="hlt">Aqua</span> <span class="hlt">MODIS</span> have successfully operated for more than 13 and 11 years since their launch in 1999 and 2002, respectively. The VIIRS instrument on-board the S-NPP launched in 2011 has also operated for nearly 2 years. Both <span class="hlt">MODIS</span> and VIIRS make observations in the <span class="hlt">reflective</span> solar and thermal emissive regions and their on-orbit calibration and characterization are provided by a set of on-board calibrators (OBC). In addition, lunar observations have been made on a regular basis to support sensor on-orbit calibration. This paper provides a brief overview of <span class="hlt">MODIS</span> and VIIRS instrument on-orbit calibration and characterization activities. It describes the approaches and strategies developed to schedule and perform on-orbit lunar observations. Specific applications of <span class="hlt">MODIS</span> and VIIRS lunar observations discussed in this paper include radiometric calibration stability monitoring and performance assessment of sensor spatial characterization. Results derived from lunar observations, such as sensor response (or gain) trending and band-to-band registration, are compared with that derived from sensor OBC. The methodologies and applications presented in this paper can also be applied to other earth observing sensors.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2016JGRG..121..855P','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2016JGRG..121..855P"><span id="translatedtitle">Retrieval of seasonal dynamics of forest understory <span class="hlt">reflectance</span> from semiarid to boreal forests using <span class="hlt">MODIS</span> BRDF data</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Pisek, Jan; Chen, Jing M.; Kobayashi, Hideki; Rautiainen, Miina; Schaepman, Michael E.; Karnieli, Arnon; Sprinstin, Michael; Ryu, Youngryel; Nikopensius, Maris; Raabe, Kairi</p> <p>2016-03-01</p> <p>Spatial and temporal patterns of forest background (understory) <span class="hlt">reflectance</span> are crucial for retrieving biophysical parameters of forest canopies (overstory) and subsequently for ecosystem modeling. In this communication, we retrieved seasonal courses of understory normalized difference vegetation index (NDVI) from multiangular Moderate Resolution Imaging Spectroradiometer bidirectional <span class="hlt">reflectance</span> distribution function (<span class="hlt">MODIS</span> BRDF)/albedo data. We compared satellite-based seasonal courses of understory NDVI to understory NDVI values measured in different types of forests distributed along a wide latitudinal gradient (65.12°N-31.35°N). Our results indicated that the retrieval method performs well particularly over open forests of different types. We also demonstrated the limitations of the method for closed canopies, where the understory signal retrieval is much attenuated.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/20020043308','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20020043308"><span id="translatedtitle">Theoretical Basis for the Surface Spectral <span class="hlt">Reflectance</span> Relationships Used in the <span class="hlt">MODIS</span> Aerosol Algorithm</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Kaufman, Yoram J.; Gobron, Nadine; Pinty, Bernard; Widlowski, Jean-Luc; Verstraete, Michel M.; Lau, William K. M. (Technical Monitor)</p> <p>2001-01-01</p> <p>The analysis of data from the <span class="hlt">MODIS</span> instrument on the Terra platform to derive global distribution of aerosols assumes a set of relationships between the blue, rho (sub blue), the red, rho (sub red), and 2.1 micrometers, rho (sub 2.1), spectral channels. These relations have been established from a series of measurements indicating that rho (sub blue) approximately 0.5 rho (sub red) approximately 0.25 rho (sub 2.1). Here we use a model to describe the transfer of radiation through a vegetation canopy composed of randomly oriented leaves to assess the theoretical foundations for these relationships. The influence of varying fractional vegetation coverage is simulated simply as a linear combination of pure soil and pure vegetation conditions, also known as Independent Pixel Approximation (IPA). Calculations for a wide range of leaf area indices and vegetation fractions show that rho (sub blue) is consistently about 1/4 of rho (sub 2.1) as used by <span class="hlt">MODIS</span> for the whole range of analyzed cases, except for very dark soils, such as those found in burn scars. For its part, the ratio rho (sub red)/rho (sub 2.1) varies from less than the empirically derived value of 1/2 for dense and dark vegetation (rho (sub 2.1) less than 0.1), to more than 1/2 for bright mixture of soil and vegetation. This is in agreement with measurements over uniform dense vegetation, but not with measurements over mixed dark scenes. In the later case, the discrepancy is probably mitigated by shadows due to uneven canopy and terrain on a large scale. It is concluded that the value of this ratio should ideally be made dependent on the land cover type in the operational processing of <span class="hlt">MODIS</span> data, especially over dense forests.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/20030102194','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20030102194"><span id="translatedtitle">The <span class="hlt">MODIS</span> Aerosol Algorithm, Products and Validation</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Remer, L. A.; Kaufman, Y. J.; Tanre, D.; Mattoo, S.; Chu, D. A.; Martins, J. V.; Li, R.-R.; Ichoku, C.; Levy, R. C.; Kleidman, R. G.</p> <p>2003-01-01</p> <p>The MODerate resolution Imaging Spectroradiometer (<span class="hlt">MODIS</span>) aboard both NASA's Terra and <span class="hlt">Aqua</span> satellites is making near global daily observations of the earth in a wide spectral range. These measurements are used to derive spectral aerosol optical thickness and aerosol size parameters over both land and ocean. The aerosol products available over land include aerosol optical thickness at three visible wavelengths, a measure of the fraction of aerosol optical thickness attributed to the fine mode and several derived parameters including <span class="hlt">reflected</span> spectral solar flux at top of atmosphere. Over ocean, the aerosol optical thickness is provided in seven wavelengths from 0.47 microns to 2.13 microns. In addition, quantitative aerosol size information includes effective radius of the aerosol and quantitative fraction of optical thickness attributed to the fine mode. Spectral aerosol flux, mass concentration and number of cloud condensation nuclei round out the list of available aerosol products over the ocean. The spectral optical thickness and effective radius of the aerosol over the ocean are validated by comparison with two years of AERONET data gleaned from 133 AERONET stations. 8000 <span class="hlt">MODIS</span> aerosol retrievals colocated with AERONET measurements confirm that one-standard deviation of <span class="hlt">MODIS</span> optical thickness retrievals fall within the predicted uncertainty of delta tauapproximately equal to plus or minus 0.03 plus or minus 0.05 tau over ocean and delta tay equal to plus or minus 0.05 plus or minus 0.15 tau over land. 271 <span class="hlt">MODIS</span> aerosol retrievals co-located with AERONET inversions at island and coastal sites suggest that one-standard deviation of <span class="hlt">MODIS</span> effective radius retrievals falls within delta r_eff approximately equal to 0.11 microns. The accuracy of the <span class="hlt">MODIS</span> retrievals suggests that the product can be used to help narrow the uncertainties associated with aerosol radiative forcing of global climate.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2012AGUFMIN11A1452C','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2012AGUFMIN11A1452C"><span id="translatedtitle">Uncertainty analysis of the SPOT 4 VEGETATION and <span class="hlt">MODIS</span> surface <span class="hlt">reflectance</span> products, and its impact on vegetation indices</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Czapla-Myers, J.</p> <p>2012-12-01</p> <p>Vegetation indices (VIs) are used to monitor the spatial and temporal variations of global vegetation. They provide essential measurements for climate, phenology, and land cover change detection. VIs are typically determined from surface <span class="hlt">reflectance</span> data that are collected using spaceborne platforms. In order to understand the uncertainty of long-term data records, it is important to understand the uncertainty of the inputs that are used to determine the VIs. The Remote Sensing Group (RSG) at the University of Arizona uses the <span class="hlt">reflectance</span>-based approach to perform the absolute radiometric calibration of airborne and satellite sensors in the solar-<span class="hlt">reflective</span> regime. During a typical field campaign, measurements of the atmosphere and surface are made during a sensor overpass. The surface <span class="hlt">reflectance</span> is measured using a portable spectroradiometer that operates from 400-2500 nm. This work uses in situ data that were obtained at White Sands Missile Range, New Mexico, and Railroad Valley, Nevada. The surface <span class="hlt">reflectance</span> data are compared to those reported by SPOT 4 VEGETATION and both <span class="hlt">MODIS</span> sensors to acquire an understanding of the uncertainty in the VI data product.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2015SPIE.9639E..11A','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2015SPIE.9639E..11A"><span id="translatedtitle">Cross-calibration of the <span class="hlt">reflective</span> solar bands of Terra <span class="hlt">MODIS</span> and Landsat 7 Enhanced Thematic Mapper plus over PICS using different approaches</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Angal, Amit; Brinkmann, Jake; Mishra, Nischal; Link, Daniel; Xiong, Xiaoxiong J.; Helder, Dennis</p> <p>2015-10-01</p> <p>Both Terra <span class="hlt">MODIS</span> and Landsat 7 (L7) Enhanced Thematic Mapper Plus (ETM+) have been successfully operating for over 15 years to collect valuable measurements of the earth's land, ocean, and atmosphere. The land-viewing bands of both sensors are widely used in several scientific products such as surface <span class="hlt">reflectance</span>, normalized difference vegetation index, enhanced vegetation index etc. A synergistic use of the multi-temporal measurements from both sensors can greatly benefit the science community. Previous effort from the <span class="hlt">MODIS</span> Characterization Support Team (MCST) was focused on comparing the top-of-atmosphere <span class="hlt">reflectance</span> of the two sensors over Libya 4 desert target. Uncertainties caused by the site/atmospheric BRDF, spectral response mismatch, and atmospheric water-vapor were also characterized. In parallel, an absolute calibration approach based on empirical observation was also developed for the Libya 4 site by the South Dakota State University's (SDSU) Image Processing Lab. Observations from Terra <span class="hlt">MODIS</span> and Earth Observing One (EO-1) Hyperion were used to model the Landsat ETM+ TOA <span class="hlt">reflectance</span>. Recently, there has been an update to the <span class="hlt">MODIS</span> calibration algorithm, which has resulted in the newly reprocessed Collection 6 Level 1B calibrated products. Similarly, a calibration update to some ETM+ bands has also resulted in long-term improvements of its calibration accuracy. With these updates, calibration differences between the spectrally matching bands of Terra <span class="hlt">MODIS</span> and L7 ETM+ over the Libya 4 site are evaluated using both approaches.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://www.ncbi.nlm.nih.gov/pubmed/24287529','PUBMED'); return false;" href="http://www.ncbi.nlm.nih.gov/pubmed/24287529"><span id="translatedtitle">Comparability of red/near-infrared <span class="hlt">reflectance</span> and NDVI based on the spectral response function between <span class="hlt">MODIS</span> and 30 other satellite sensors using rice canopy spectra.</span></a></p> <p><a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a></p> <p>Huang, Weijiao; Huang, Jingfeng; Wang, Xiuzhen; Wang, Fumin; Shi, Jingjing</p> <p>2013-01-01</p> <p>Long-term monitoring of regional and global environment changes often depends on the combined use of multi-source sensor data. The most widely used vegetation index is the normalized difference vegetation index (NDVI), which is a function of the red and near-infrared (NIR) spectral bands. The <span class="hlt">reflectance</span> and NDVI data sets derived from different satellite sensor systems will not be directly comparable due to different spectral response functions (SRF), which has been recognized as one of the most important sources of uncertainty in the multi-sensor data analysis. This study quantified the influence of SRFs on the red and NIR <span class="hlt">reflectances</span> and NDVI derived from 31 Earth observation satellite sensors. For this purpose, spectroradiometric measurements were performed for paddy rice grown under varied nitrogen levels and at different growth stages. The rice canopy <span class="hlt">reflectances</span> were convoluted with the spectral response functions of various satellite instruments to simulate sensor-specific <span class="hlt">reflectances</span> in the red and NIR channels. NDVI values were then calculated using the simulated red and NIR <span class="hlt">reflectances</span>. The results showed that as compared to the Terra <span class="hlt">MODIS</span>, the mean relative percentage difference (RPD) ranged from -12.67% to 36.30% for the red <span class="hlt">reflectance</span>, -8.52% to -0.23% for the NIR <span class="hlt">reflectance</span>, and -9.32% to 3.10% for the NDVI. The mean absolute percentage difference (APD) compared to the Terra <span class="hlt">MODIS</span> ranged from 1.28% to 36.30% for the red <span class="hlt">reflectance</span>, 0.84% to 8.71% for the NIR <span class="hlt">reflectance</span>, and 0.59% to 9.32% for the NDVI. The lowest APD between <span class="hlt">MODIS</span> and the other 30 satellite sensors was observed for Landsat5 TM for the red <span class="hlt">reflectance</span>, CBERS02B CCD for the NIR <span class="hlt">reflectance</span> and Landsat4 TM for the NDVI. In addition, the largest APD between <span class="hlt">MODIS</span> and the other 30 satellite sensors was observed for IKONOS for the red <span class="hlt">reflectance</span>, AVHRR1 onboard NOAA8 for the NIR <span class="hlt">reflectance</span> and IKONOS for the NDVI. The results also indicated that AVHRRs onboard NOAA7-17 showed</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=3892887','PMC'); return false;" href="http://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=3892887"><span id="translatedtitle">Comparability of Red/Near-Infrared <span class="hlt">Reflectance</span> and NDVI Based on the Spectral Response Function between <span class="hlt">MODIS</span> and 30 Other Satellite Sensors Using Rice Canopy Spectra</span></a></p> <p><a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pmc">PubMed Central</a></p> <p>Huang, Weijiao; Huang, Jingfeng; Wang, Xiuzhen; Wang, Fumin; Shi, Jingjing</p> <p>2013-01-01</p> <p>Long-term monitoring of regional and global environment changes often depends on the combined use of multi-source sensor data. The most widely used vegetation index is the normalized difference vegetation index (NDVI), which is a function of the red and near-infrared (NIR) spectral bands. The <span class="hlt">reflectance</span> and NDVI data sets derived from different satellite sensor systems will not be directly comparable due to different spectral response functions (SRF), which has been recognized as one of the most important sources of uncertainty in the multi-sensor data analysis. This study quantified the influence of SRFs on the red and NIR <span class="hlt">reflectances</span> and NDVI derived from 31 Earth observation satellite sensors. For this purpose, spectroradiometric measurements were performed for paddy rice grown under varied nitrogen levels and at different growth stages. The rice canopy <span class="hlt">reflectances</span> were convoluted with the spectral response functions of various satellite instruments to simulate sensor-specific <span class="hlt">reflectances</span> in the red and NIR channels. NDVI values were then calculated using the simulated red and NIR <span class="hlt">reflectances</span>. The results showed that as compared to the Terra <span class="hlt">MODIS</span>, the mean relative percentage difference (RPD) ranged from −12.67% to 36.30% for the red <span class="hlt">reflectance</span>, −8.52% to −0.23% for the NIR <span class="hlt">reflectance</span>, and −9.32% to 3.10% for the NDVI. The mean absolute percentage difference (APD) compared to the Terra <span class="hlt">MODIS</span> ranged from 1.28% to 36.30% for the red <span class="hlt">reflectance</span>, 0.84% to 8.71% for the NIR <span class="hlt">reflectance</span>, and 0.59% to 9.32% for the NDVI. The lowest APD between <span class="hlt">MODIS</span> and the other 30 satellite sensors was observed for Landsat5 TM for the red <span class="hlt">reflectance</span>, CBERS02B CCD for the NIR <span class="hlt">reflectance</span> and Landsat4 TM for the NDVI. In addition, the largest APD between <span class="hlt">MODIS</span> and the other 30 satellite sensors was observed for IKONOS for the red <span class="hlt">reflectance</span>, AVHRR1 onboard NOAA8 for the NIR <span class="hlt">reflectance</span> and IKONOS for the NDVI. The results also indicated that AVHRRs onboard NOAA7</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/20120015744','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20120015744"><span id="translatedtitle">Evaluating the Assumptions of Surface <span class="hlt">Reflectance</span> and Aerosol Type Selection Within the <span class="hlt">MODIS</span> Aerosol Retrieval Over Land: The Problem of Dust Type Selection</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Mielonen, T.; Levy, R. C.; Aaltonen, V.; Komppula, M.; de Leeuw, G.; Huttunen, J.; Lihavainen, H.; Kolmonen, P.; Lehtinen, K. E. J.; Arola, A.</p> <p>2011-01-01</p> <p>Aerosol Optical Depth (AOD) and Angstrom exponent (AE) values derived with the <span class="hlt">MODIS</span> retrieval algorithm over land (Collection 5) are compared with ground based sun photometer measurements at eleven sites spanning the globe. Although, in general, total AOD compares well at these sites (R2 values generally over 0.8), there are cases (from 2 to 67% of the measurements depending on the site) where <span class="hlt">MODIS</span> clearly retrieves the wrong spectral dependence, and hence, an unrealistic AE value. Some of these poor AE retrievals are due to the aerosol signal being too small (total AOD<0.3) but in other cases the AOD should have been high enough to derive accurate AE. However, in these cases, <span class="hlt">MODIS</span> indicates AE values close to 0.6 and zero fine model weighting (FMW), i.e. dust model provides the best fitting to the <span class="hlt">MODIS</span> observed <span class="hlt">reflectance</span>. Yet, according to evidence from the collocated sun photometer measurements and back-trajectory analyses, there should be no dust present. This indicates that the assumptions about aerosol model and surface properties made by the <span class="hlt">MODIS</span> algorithm may have been incorrect. Here we focus on problems related to parameterization of the land-surface optical properties in the algorithm, in particular the relationship between the surface <span class="hlt">reflectance</span> at 660 and 2130 nm.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/1997JGR...10229529P','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/1997JGR...10229529P"><span id="translatedtitle">Estimating spectral albedo and nadir <span class="hlt">reflectance</span> through inversion of simple BRDF models with AVHRR/<span class="hlt">MODIS</span>-like data</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Privette, Jeffrey L.; Eck, Thomas F.; Deering, Donald W.</p> <p>1997-12-01</p> <p>In recent years, many computationally efficient bidirectional <span class="hlt">reflectance</span> models have been developed to account for angular effects in land remote sensing data, particularly those from the NOAA advanced very high resolution radiometer (AVHRR), polarization and directionality of the Earth's <span class="hlt">reflectances</span> (POLDER), and the planned EOS moderate-resolution imaging spectrometer (<span class="hlt">MODIS</span>) and multi-angle imaging spectroradiometer (MISR) sensors. In this study, we assessed the relative ability of 10 such models to predict commonly used remote sensing products (nadir <span class="hlt">reflectance</span> and albedo). Specifically, we inverted each model with ground-based data from the portable apparatus for rapid acquisition of bidirectional observations of the land and atmosphere (PARABOLA) arranged in subsets representative of satellite sampling geometries. We used data from nine land cover types, ranging from soil to grassland (First International Satellite Land Surface Climatology Project (ISLSCP) Field Experiment (FIFE)) to forest (Boreal Ecosystem-Atmosphere Study (BOREAS)). Retrieved parameters were used in forward model runs to estimate nadir <span class="hlt">reflectance</span> and spectral albedo over a wide range of solar angles. We rank the models by the accuracy of the estimated products and find results to be strongly dependent on the view azimuth angle range of the inversion data, and less dependent on the spectral band and land cover type. Overall, the nonlinear model of Rahman et al. [993] and the linear kernel-driven RossThickLiSparse model [Wanner et al., 1995] were most accurate. The latter was at least 25 times faster to invert than the former. Interestingly, we found these two models were not able to match the various bidirectional <span class="hlt">reflectance</span> distribution function (BRDF) shapes as well as other models, suggesting their superior performance lies in their ability to be more reliably inverted with sparse data sets. These results should be useful to those interested in the computationally fast normalization</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/20120007859','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20120007859"><span id="translatedtitle">An Overview of <span class="hlt">MODIS</span> On-orbit Operation, Calibration, and Lessons</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Xiong, Jack; Barnes, William; Salomonson, Vincent</p> <p>2012-01-01</p> <p>Two nearly identical copies of the Moderate Resolution Imaging Spectroradiometer (<span class="hlt">MODIS</span>) have successfully operated onboard the Terra and <span class="hlt">Aqua</span> spacecraft for more than II years and 9 years since their launch in December 1999 and May 2002, respectively. <span class="hlt">MODIS</span> is a key instrument for the NASA's Earth Observing System (EOS) missions. <span class="hlt">MODIS</span> observations have produced an unprecedented amount and a broad range of data products and significantly benefited the science and user community. Its follow-on instrument, the Visible/Infrared Imager Radiometer Suite (VIIRS) on-board the NPOESS Preparatory Project (NPP) spacecraft, is currently scheduled for launch in late October, 2011. The NPP serves as a bridge mission between EOS and the Joint Polar Satellite System (JPSS). <span class="hlt">MODIS</span> collects data in 36 spectral bands, covering spectral regions from visible (VIS) to long-wave infrared (L WIR), and at three different spatial resolutions. Because of its stringent design requirements, <span class="hlt">MODIS</span> was built with a complete set of onboard calibrators, including a solar diffuser (SO), a solar diffuser stability monitor (SDSM), a blackbody (BB), a spectroradiometric calibration assembly (SRCA), and a space view (SV) port. Except for tbe SRCA, VIlRS carries the same set of onboard calibrators as <span class="hlt">MODIS</span>. The SD/SDSM system is used together to calibrate tbe <span class="hlt">reflective</span> solar bands (RSB). The BB is designed for the thermal emissive bands (TEB) calibration. Similar to Terra and <span class="hlt">Aqua</span> <span class="hlt">MODIS</span>, VIlRS will also make regular lunar observations to monitor RSB radiometric calibration stability. In this paper, we provide an overview of <span class="hlt">MODIS</span> on-orbit operation and calibration activities and present issues identified and lessons learned from mission-long instrument operations and implementation of various calibration and characterization strategies. Examples of both Terra and <span class="hlt">Aqua</span> <span class="hlt">MODIS</span> instrument on-orbit performance, including their similarities and unique characteristics, are discussed in tbe context of what</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://ntrs.nasa.gov/search.jsp?R=20070031724&hterms=Pressure+products&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D30%26Ntt%3DPressure%2Bproducts','NASA-TRS'); return false;" href="http://ntrs.nasa.gov/search.jsp?R=20070031724&hterms=Pressure+products&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D30%26Ntt%3DPressure%2Bproducts"><span id="translatedtitle">Introduction to <span class="hlt">MODIS</span> Cloud Products. Chapter 5</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Baum, Bryan A.; Platnick, Steven</p> <p>2006-01-01</p> <p>The Earth's radiative energy balance and hydrological cycle are fundamentally coupled with the distribution and properties of clouds. Therefore, the ability to remotely infer cloud properties and their variation in space and time is crucial for establishing climatologies as a reference for validation of present-day climate models and in assessing future climate change. Remote cloud observations also provide data sets useful for testing and improving cloud model physics, and for assimilation into numerical weather prediction models. The MODerate Resolution Imaging Spectroradiometer (<span class="hlt">MODIS</span>) imagers on the Terra and <span class="hlt">Aqua</span> Earth Observing System (EOS) platforms provide the capability for globally retrieving these properties using passive solar <span class="hlt">reflectance</span> and infrared techniques. In addition to providing measurements similar to those offered on a suite of historical operational weather platforms such as the Advanced Very High Resolution Radiometer (AVHRR), the High-resolution Infrared Radiation Sounder (HIRS), and the Geostationary Operational Environmental Satellite (GOES), <span class="hlt">MODIS</span> provides additional spectral and/or spatial resolution in key atmospheric bands, along with on-board calibration, to expand the capability for global cloud property retrievals. The core <span class="hlt">MODIS</span> operational cloud products include cloud top pressure, thermodynamic phase, optical thickness, particle size, and water path, and are derived globally at spatial resolutions of either 1- or 5-km (referred to as Level-2 or pixel-level products). In addition, the <span class="hlt">MODIS</span> atmosphere team (collectively providing cloud, aerosol, and clear sky products) produces a combined gridded product (referred to as Level-3) aggregated to a 1 equal-angle grid, available for daily, eight-day, and monthly time periods. The wealth of information available from these products provides critical information for climate studies as well as the continuation and improved understanding of existing satellite-based cloud climatologies</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2010SPIE.7807E..1FW','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2010SPIE.7807E..1FW"><span id="translatedtitle"><span class="hlt">MODIS</span> calibration algorithm improvements developed for Collection 6 Level-1B</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Wenny, Brian N.; Sun, Junqiang; Xiong, Xiaoxiong; Wu, Aisheng; Chen, Hongda; Angal, Amit; Choi, Taeyoung; Chen, Na; Madhavan, Sriharsha; Geng, Xu; Kuyper, James; Tan, Liqin</p> <p>2010-09-01</p> <p>The Moderate Resolution Imaging Spectroradiometer (<span class="hlt">MODIS</span>) has been operating on both the Terra and <span class="hlt">Aqua</span> spacecraft for over 10.5 and 8 years, respectively. Over 40 science products are generated routinely from <span class="hlt">MODIS</span> Earth images and used extensively by the global science community for a wide variety of land, ocean, and atmosphere applications. Over the mission lifetime, several versions of the <span class="hlt">MODIS</span> data set have been in use as the calibration and data processing algorithms evolved. Currently Version 5 <span class="hlt">MODIS</span> data is the baseline Level-1B calibrated science product. The <span class="hlt">MODIS</span> Characterization Support Team (MCST), with input from the <span class="hlt">MODIS</span> Science Team, developed and delivered a number of improvements and enhancements to the calibration algorithms, Level-1B processing code and Look-up Tables for the Version 6 Level-1B <span class="hlt">MODIS</span> data. Version 6 implements a number of changes in the calibration methodology for both the <span class="hlt">Reflective</span> Solar Bands (RSB) and Thermal Emissive Bands (TEB). This paper describes the improvements introduced in Collection 6 to the RSB and TEB calibration and detector Quality Assurance (QA) handling.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2013AGUFM.H43G1568J','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2013AGUFM.H43G1568J"><span id="translatedtitle">Blending and Downscaling of Landsat and <span class="hlt">MODIS</span> Surface <span class="hlt">Reflectance</span> for Water Body Delineation: A Comparison of Index-Simulate and Simulate-Index Methods</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Jarihani, A.; Callow, J. N.; McVicar, T.; Van Niel, T.; Johansen, K.; Emelyanova, I.</p> <p>2013-12-01</p> <p>Single-sensor satellite remotely sensed data are typically either high temporal and low spatial resolution (e.g. <span class="hlt">MODIS</span>) or low temporal and high spatial resolution (e.g. Landsat). Blending algorithms have been developed to overcome this limitation by predicting the composition of higher spatial and temporal resolution band data by blending individual corresponding bands of two sensors. The objective of this paper was to evaluate the accuracy of two advanced algorithms (STARFM and ESTARFM) in blending single bands and indices to downscale <span class="hlt">MODIS</span> pixels (250-500 m) to Landsat resolution (28.5 m). We test two approaches to predicting indices: i) Index-Simulate (IS)-(i.e., indices directly predicted including EVI, NDVI NDWI24 and NDWI 27) from Landsat-<span class="hlt">MODIS</span> pairs) and ii) Simulate- Index (SI)-(i.e. indices were calculated from five predicted bands (Blue, Green, Red, Near-Infrared and Mid-Infrared). Landsat-like images and indices (IS and SI) were predicted for 18 dates by using 20 pairs of cloud-free Landsat 5 TM and <span class="hlt">Aqua</span> <span class="hlt">MODIS</span> images and compared with observed Landsat images and indices. Based on RMSD (accuracy of predicted and observed bands and indices), pixel-to-pixel accuracy of each prediction and R-squared differences of predicted and observed pixels, ESTARFM produced a lower error than STARFM in predicting all four tested indices. Results of IS and SI methods showed that, both algorithms predict indices in IS method with higher accuracy than using SI method. That is, if interested in using indices in applications it best to calculate the index at the two resolutions then use the algorithms to simulate the index as opposed to simulating the individual bands then subsequently calculating the index. This study shows that, the high spatio-temporal resolution predicted water index (NDWI) can be used in water resources applications. Landsat-like daily water indices simulated by using blending Landsat and <span class="hlt">MODIS</span> data provided daily flood inundation footprint. These</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/cgi-bin/nph-data_query?bibcode=2016EGUGA..18.5138P&link_type=ABSTRACT','NASAADS'); return false;" href="http://adsabs.harvard.edu/cgi-bin/nph-data_query?bibcode=2016EGUGA..18.5138P&link_type=ABSTRACT"><span id="translatedtitle">Retrieval of seasonal dynamics of forest understory <span class="hlt">reflectance</span> from semi-arid to boreal forests using <span class="hlt">MODIS</span> BRDF data</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Pisek, Jan; Chen, Jing; Kobayashi, Hideki; Rautiainen, Miina; Schaepman, Michael; Karnieli, Arnon; Sprintsin, Michael; Ryu, Youngryel; Nikopensius, Maris; Raabe, Kairi</p> <p>2016-04-01</p> <p>Ground vegetation (understory) provides an essential contribution to the whole-stand <span class="hlt">reflectance</span> signal in many boreal, sub-boreal, and temperate forests. Accurate knowledge about forest understory <span class="hlt">reflectance</span> is urgently needed in various forest <span class="hlt">reflectance</span> modelling efforts. However, systematic collections of understory <span class="hlt">reflectance</span> data covering different sites and ecosystems are almost missing. Measurement of understory <span class="hlt">reflectance</span> is a real challenge because of an extremely high variability of irradiance at the forest floor, weak signal in some parts of the spectrum, spectral separability issues of over- and understory and its variable nature. Understory can consist of several sub-layers (regenerated tree, shrub, grasses or dwarf shrub, mosses, lichens, litter, bare soil), it has spatially-temporally variable species composition and ground coverage. Additional challenges are introduced by patchiness of ground vegetation, ground surface roughness, and understory-overstory relations. Due to this variability, remote sensing might be the only means to provide consistent data at spatially relevant scales. In this presentation, we report on retrieving seasonal courses of understory Normalized Difference Vegetation Index (NDVI) from multi-angular <span class="hlt">MODIS</span> BRDF/Albedo data. We compared satellite-based seasonal courses of understory NDVI against an extended collection of different types of forest sites with available in-situ understory <span class="hlt">reflectance</span> measurements. These sites are distributed along a wide latitudinal gradient on the Northern hemisphere: a sparse and dense black spruce forests in Alaska and Canada, a northern European boreal forest in Finland, hemiboreal needleleaf and deciduous stands in Estonia, a mixed temperate forest in Switzerland, a cool temperate deciduous broadleaf forest in Korea, and a semi-arid pine plantation in Israel. Our results indicated the retrieval method performs well particularly over open forests of different types. We also demonstrated</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2012AGUFM.B41E0376R','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2012AGUFM.B41E0376R"><span id="translatedtitle">Understanding QA: The Key to Defining the Usability and Usefulness of <span class="hlt">MODIS</span> Land Products</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Ramachandran, B.; Meyer, D. J.</p> <p>2012-12-01</p> <p>NASA's Earth Observing System (EOS) ushered in an era of global Earth system science that benefits those studying all aspects of Earth's land, atmosphere, and oceans components. The Terra and <span class="hlt">Aqua</span> missions support nearly identical Moderate Resolution Imaging Spectroradiometer (<span class="hlt">MODIS</span>) instruments that have helped spawn an entirely new array of validated geophysical products at multiple spatial and temporal resolutions. The <span class="hlt">MODIS</span> land products continue to contribute to address key requirements for monitoring land surface processes and dynamics. The public has access to a <span class="hlt">MODIS</span> land product's archive that contains over 27 million granules (~590 TB in volume). Given such an access to a huge data collection, the usability and usefulness of those products can pose serious challenges to end-users attempting to use them in various applications. To address these challenges, the <span class="hlt">MODIS</span> mission incorporates in-depth pixel-level quality assurance (QA) layers that provide a wealth of information for those who know how to tap it. This study focuses on QA information that is encapsulated with the different <span class="hlt">MODIS</span> land products. Following a descriptive preamble of <span class="hlt">MODIS</span> land products and QA, a sizable portion is devoted to identifying why it is important for users to consult and use the QA information. Next, guidelines to identify the specific QA metadata sources in different <span class="hlt">MODIS</span> product suites are provided. The following section addresses the mechanics of deconstructing pixel-level QA, which is deemed extremely vital for applied science users. Examples of how QA information is handled and interpreted in three <span class="hlt">MODIS</span> land product suites are provided, including Land Surface <span class="hlt">Reflectance</span>, Bi-directional <span class="hlt">Reflectance</span> Distribution Function and Albedo, and Vegetation Indices. It closes with a variety of information on <span class="hlt">MODIS</span> QA-specific tools and online resources deemed helpful to end-users.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://pubs.er.usgs.gov/publication/70010012','USGSPUBS'); return false;" href="http://pubs.er.usgs.gov/publication/70010012"><span id="translatedtitle"><span class="hlt">MODIS</span> and SeaWIFS on-orbit lunar calibration</span></a></p> <p><a target="_blank" href="http://pubs.er.usgs.gov/pubs/index.jsp?view=adv">USGS Publications Warehouse</a></p> <p>Sun, Jielun; Eplee, R.E., Jr.; Xiong, X.; Stone, T.; Meister, G.; McClain, C.R.</p> <p>2008-01-01</p> <p>The Moon plays an important role in the radiometric stability monitoring of the NASA Earth Observing System's (EOS) remote sensors. The <span class="hlt">MODIS</span> and SeaWIFS are two of the key instruments for NASA's EOS missions. The <span class="hlt">MODIS</span> Protoflight Model (PFM) on-board the Terra spacecraft and the <span class="hlt">MODIS</span> Flight Model 1 (FM1) on-board the <span class="hlt">Aqua</span> spacecraft were launched on December 18, 1999 and May 4, 2002, respectively. They view the Moon through the Space View (SV) port approximately once a month to monitor the long-term radiometric stability of their <span class="hlt">Reflective</span> Solar Bands (RSB). SeaWIFS was launched on-board the OrbView-2 spacecraft on August 1, 1997. The SeaWiFS lunar calibrations are obtained once a month at a nominal phase angle of 7??. The lunar irradiance observed by these instruments depends on the viewing geometry. The USGS photometric model of the Moon (the ROLO model) has been developed to provide the geometric corrections for the lunar observations. For <span class="hlt">MODIS</span>, the lunar view responses with corrections for the viewing geometry are used to track the gain change for its <span class="hlt">reflective</span> solar bands (RSB). They trend the system response degradation at the Angle Of Incidence (AOI) of sensor's SV port. With both the lunar observation and the on-board Solar Diffuser (SD) calibration, it is shown that the <span class="hlt">MODIS</span> system response degradation is wavelength, mirror side, and AOI dependent. Time-dependent Response Versus Scan angle (RVS) Look-Up Tables (LUT) are applied in <span class="hlt">MODIS</span> RSB calibration and lunar observations play a key role in RVS derivation. The corrections provided by the RVS in the Terra and <span class="hlt">Aqua</span> <span class="hlt">MODIS</span> data from the 412 nm band are as large as 16% and 13%, respectively. For SeaWIFS lunar calibrations, the spacecraft is pitched across the Moon so that the instrument views the Moon near nadir through the same optical path as it views the Earth. The SeaWiFS system gain changes for its eight bands are calibrated using the geometrically-corrected lunar observations. The radiometric</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/20000033817','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20000033817"><span id="translatedtitle">Sensitivity of Cirrus Bidirectional <span class="hlt">Reflectance</span> at <span class="hlt">MODIS</span> Bands to Vertical Inhomogeneity of Ice Crystal Habits and Size Distribution</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Yang, P.; Gao, B.-C.; Baum, B. A.; Wiscombe, W.; Hu, Y.; Nasiri, S. L.; Soulen, P. F.; Heymsfield, A. J.; McFarquhar, G. M.; Miloshevich, L. M.</p> <p>2000-01-01</p> <p>A common assumption in satellite imager-based cirrus retrieval algorithms is that the radiative properties of a cirrus cloud may be represented by those associated with a specific ice crystal shape (or habit) and a single particle size distribution. However, observations of cirrus clouds have shown that the shapes and sizes of ice crystals may vary substantially with height within the clouds. In this study we investigate the sensitivity of the top-of-atmosphere bidirectional <span class="hlt">reflectances</span> at two <span class="hlt">MODIS</span> bands centered at 0.65 micron and 2.11 micron to the cirrus models assumed to be either a single homogeneous layer or three distinct but contiguous, layers. First, we define the single- and three-layer cirrus cloud models with respect to ice crystal habit and size distribution on the basis of in situ replicator data acquired during the First ISCCP Regional Experiment (FIRE-II), held in Kansas during the fall of 1991. Subsequently, fundamental light scattering and radiative transfer theory is employed to determine the single scattering and the bulk radiative properties of the cirrus cloud. Regarding the radiative transfer computations, we present a discrete form of the adding/doubling principle by introducing a direct transmission function, which is computationally straightforward and efficient an improvement over previous methods. For the 0.65 micron band, at which absorption by ice is negligible, there is little difference between the bidirectional <span class="hlt">reflectances</span> calculated for the one- and three-layer cirrus models, suggesting that the vertical inhomogeneity effect is relatively unimportant. At the 2.11 micron band, the bidirectional <span class="hlt">reflectances</span> computed for both optically thin (tau = 1) and thick (tau = 10) cirrus clouds show significant differences between the results for the one- and three-layer models. The <span class="hlt">reflectances</span> computed for the three-layer cirrus model are substantially larger than those computed for the single-layer cirrus. Finally, we find that cloud</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://ntrs.nasa.gov/search.jsp?R=20160005181&hterms=assessment&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D80%26Ntt%3Dassessment','NASA-TRS'); return false;" href="http://ntrs.nasa.gov/search.jsp?R=20160005181&hterms=assessment&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D80%26Ntt%3Dassessment"><span id="translatedtitle">Assessment of <span class="hlt">MODIS</span> and VIIRS Solar Diffuser On-Orbit Degradation</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Xiong, Xiaoxiong; Fulbright, Jon; Angal, Amit; Wang, Zhipeng; Geng, Xu; Butler, Jim</p> <p>2015-01-01</p> <p>Both <span class="hlt">MODIS</span> and VIIRS instruments use a solar diffuser (SD) for their <span class="hlt">reflective</span> solar bands (RSB) on-orbit calibration. On-orbit changes in SD bi-directional <span class="hlt">reflectance</span> factor (BRF) are tracked by a solar diffuser stability monitor (SDSM) using its alternate measurements of the sunlight <span class="hlt">reflected</span> off the SD panel and direct sunlight through a fixed attenuation screen. The SDSM calibration data are collected by a number of filtered detectors, covering wavelengths from 0.41 to 0.94 micrometers. In this paper we describe briefly the Terra and <span class="hlt">Aqua</span> <span class="hlt">MODIS</span> and S-NPP VIIRS SDSM on-orbit operation and calibration activities and strategies, provide an overall assessment of their SDSM on-orbit performance, including wavelength-dependent changes in the SDSM detector responses and changes in their SD BRF, and discuss remaining challenging issues and their potential impact on RSB calibration quality. Due to different launch dates, operating configurations, and calibration frequencies, the Terra and <span class="hlt">Aqua</span> <span class="hlt">MODIS</span> and S-NPP VIIRS SD have experienced different amount of SD degradation. However, in general the shorter the wavelength, the larger is the SD on-orbit degradation. On the other hand, the larger changes in SDSM detector responses are observed at longer wavelengths in the near infrared (NIR).</p> </li> </ol> <div class="pull-right"> <ul class="pagination"> <li><a href="#" onclick='return showDiv("page_1");'>«</a></li> <li><a href="#" onclick='return showDiv("page_7");'>7</a></li> <li><a href="#" onclick='return showDiv("page_8");'>8</a></li> <li class="active"><span>9</span></li> <li><a href="#" onclick='return showDiv("page_10");'>10</a></li> <li><a href="#" onclick='return showDiv("page_11");'>11</a></li> <li><a href="#" onclick='return showDiv("page_25");'>»</a></li> </ul> </div> </div><!-- col-sm-12 --> </div><!-- row --> </div><!-- page_9 --> <div id="page_10" class="hiddenDiv"> <div class="row"> <div class="col-sm-12"> <div class="pull-right"> <ul class="pagination"> <li><a href="#" onclick='return showDiv("page_1");'>«</a></li> <li><a href="#" onclick='return showDiv("page_8");'>8</a></li> <li><a href="#" onclick='return showDiv("page_9");'>9</a></li> <li class="active"><span>10</span></li> <li><a href="#" onclick='return showDiv("page_11");'>11</a></li> <li><a href="#" onclick='return showDiv("page_12");'>12</a></li> <li><a href="#" onclick='return showDiv("page_25");'>»</a></li> </ul> </div> </div> </div> <div class="row"> <div class="col-sm-12"> <ol class="result-class" start="181"> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2015SPIE.9607E..1TX','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2015SPIE.9607E..1TX"><span id="translatedtitle">Assessment of <span class="hlt">MODIS</span> and VIIRS solar diffuser on-orbit degradation</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Xiong, Xiaoxiong; Fulbright, Jon; Angal, Amit; Wang, Zhipeng; Geng, Xu; Butler, Jim</p> <p>2015-09-01</p> <p>Both <span class="hlt">MODIS</span> and VIIRS instruments use a solar diffuser (SD) for their <span class="hlt">reflective</span> solar bands (RSB) on-orbit calibration. On-orbit changes in SD bi-directional <span class="hlt">reflectance</span> factor (BRF) are tracked by a solar diffuser stability monitor (SDSM) using its alternate measurements of the sunlight <span class="hlt">reflected</span> off the SD panel and direct sunlight through a fixed attenuation screen. The SDSM calibration data are collected by a number of filtered detectors, covering wavelengths from 0.41 to 0.94μm. In this paper we describe briefly the Terra and <span class="hlt">Aqua</span> <span class="hlt">MODIS</span> and S-NPP VIIRS SDSM on-orbit operation and calibration activities and strategies, provide an overall assessment of their SDSM on-orbit performance, including wavelength-dependent changes in the SDSM detector responses and changes in their SD BRF, and discuss remaining challenging issues and their potential impact on RSB calibration quality. Due to different launch dates, operating configurations, and calibration frequencies, the Terra and <span class="hlt">Aqua</span> <span class="hlt">MODIS</span> and S-NPP VIIRS SD have experienced different amount of SD degradation. However, in general the shorter the wavelength, the larger is the SD on-orbit degradation. On the other hand, the larger changes in SDSM detector responses are observed at longer wavelengths in the near infrared (NIR).</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2012SPIE.8510E..0IC','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2012SPIE.8510E..0IC"><span id="translatedtitle">Recent progress of <span class="hlt">MODIS</span> solar diffuser on-orbit degradation characterization</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Chen, H.; Wang, Z.; Sun, J.; Angal, A.; Xiong, X.</p> <p>2012-09-01</p> <p>An on-board Solar Diffuser (SD) is used for the <span class="hlt">MODIS</span> <span class="hlt">reflective</span> solar bands (RSB) calibration. Its on-orbit bidirectional <span class="hlt">reflectance</span> factor (BRF) degradation is tracked using an on-board Solar Diffuser Stability Monitor (SDSM). The SDSM is a ratioing radiometer with nine detectors, covering wavelengths from 412 nm to 936 nm. During each scheduled SD calibration event, the SDSM makes alternate observations of the Sun and the sunlight <span class="hlt">reflected</span> by the SD. To best match the SDSM detector signals from its Sun view and SD view, a fix attenuation screen is placed in its Sun view path. This paper provides a brief description of <span class="hlt">MODIS</span> RSB on-orbit calibration and the use of its on-board SD and SDSM subsystem, including different approaches developed and used to track <span class="hlt">MODIS</span> SD on-orbit degradation. It reports recent progress made to better characterize <span class="hlt">MODIS</span> SD on-orbit degradation and to support <span class="hlt">MODIS</span> Level 1B (L1B) calibration look-up table (LUT) updates for the upcoming collection 6 (C6) reprocessing. Results of both Terra and <span class="hlt">Aqua</span> SD on-orbit degradation derived from newly improved SDSM Sun view screen vignetting function and response fitting strategy, and their impact on RSB calibration uncertainties are also presented.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2010SPIE.7807E..0GD','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2010SPIE.7807E..0GD"><span id="translatedtitle">Space environment's effect on <span class="hlt">MODIS</span> calibration</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Dodd, J. L.; Wenny, B. N.; Chiang, K.; Xiong, X.</p> <p>2010-09-01</p> <p>The MODerate resolution Imaging Spectroradiometer flies on board the Earth Observing System (EOS) satellites Terra and <span class="hlt">Aqua</span> in a sun-synchronous orbit that crosses the equator at 10:30 AM and 2:30 PM, respectively, at a low earth orbit (LEO) altitude of 705 km. Terra was launched on December 18,1999 and <span class="hlt">Aqua</span> was launched on May 4, 2002. As the <span class="hlt">MODIS</span> instruments on board these satellites continue to operate beyond the design lifetime of six years, the cumulative effect of the space environment on <span class="hlt">MODIS</span> and its calibration is of increasing importance. There are several aspects of the space environment that impact both the top of atmosphere (TOA) calibration and, therefore, the final science products of <span class="hlt">MODIS</span>. The south Atlantic anomaly (SAA), spacecraft drag, extreme radiative and thermal environment, and the presence of orbital debris have the potential to significantly impact both <span class="hlt">MODIS</span> and the spacecraft, either directly or indirectly, possibly resulting in data loss. Efforts from the Terra and <span class="hlt">Aqua</span> Flight Operations Teams (FOT), the <span class="hlt">MODIS</span> Instrument Operations Team (IOT), and the <span class="hlt">MODIS</span> Characterization Support Team (MCST) prevent or minimize external impact on the TOA calibrated data. This paper discusses specific effects of the space environment on <span class="hlt">MODIS</span> and how they are minimized.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2015AGUFM.H51G1461C','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2015AGUFM.H51G1461C"><span id="translatedtitle">Towards the assimilation of <span class="hlt">MODIS</span> <span class="hlt">reflectance</span> into the detailed snowpack model SURFEX/ISBA-Crocus.</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Charrois, L.; Cosme, E.; Dumont, M.; Lafaysse, M.; Morin, S.; Libois, Q.; Picard, G.</p> <p>2015-12-01</p> <p>Numerical simulations of snow on the ground are used for numerous scientific and operational applications such as avalanche hazard forecasting. Although the chain of models used in French mountain ranges for meteorological analysis and forecast (SAFRAN) and detailed snowpack modeling (SURFEX/ISBA-Crocus) usually perform reasonably well, significant differences with snowpack observations are common and are primarily attributed to the uncertainties in meteorological input and to the heterogeneity of snowpack conditions at all scales. So far, no snow observation is assimilated into this model chain, so that simulation errors can accumulate over the winter season. Current efforts are devoted to the assimilation of data from visible and near-infrared imagers into the snowpack model. These efforts rely on the recently developed "TARTES" optical scheme that computes <span class="hlt">reflectances</span> at various wavelengths using the vertical profile of the physical properties of snow predicted by the snowpack model. In a first step, we performed ensemble simulations by perturbing the atmospheric forcing consistently with its estimated uncertainty. These experiments showed that the simulated snowpack evolution is extremely sensitive to this uncertainty, and that the assimilation of observations can greatly improve model results. In a second step, we performed assimilation experiments using synthetic imager observations and a particle filter. The experiments were carried out for the location of Col du Lautaret area (French Alps) over 5 hydrologic seasons. They provide a good insight about the potential and limitations of assimilating imager data to improve the representation of the snowpack.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://ntrs.nasa.gov/search.jsp?R=20030112964&hterms=clam&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D10%26Ntt%3Dclam','NASA-TRS'); return false;" href="http://ntrs.nasa.gov/search.jsp?R=20030112964&hterms=clam&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D10%26Ntt%3Dclam"><span id="translatedtitle">Towards Improved <span class="hlt">MODIS</span> Aerosol Retrieval over the US East Coast Region: Re-examining the Aerosol Model and Surface Assumptions</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Levy, R. C.; Remer, L. A.; Kaufman, Y. J.; Holben, B. N.</p> <p>2002-01-01</p> <p>The MODerate resolution Imaging Spectrometer (<span class="hlt">MODIS</span>) aboard the Terra and recently the <span class="hlt">Aqua</span> 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 <span class="hlt">MODIS</span>. 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, <span class="hlt">MODIS</span> 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 <span class="hlt">MODIS</span> 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 <span class="hlt">reflectance</span> properties. Understanding and improving <span class="hlt">MODIS</span> retrievals over the East Coast will not only improve the global quality of <span class="hlt">MODIS</span>, but also would enable the use of <span class="hlt">MODIS</span> as a tool for monitoring regional aerosol events.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2004SPIE.5542...14B','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2004SPIE.5542...14B"><span id="translatedtitle"><span class="hlt">MODIS</span> instrument status and operational activities</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Barnes, William L.; Xiong, Xiaoxiong; Salomonson, Vincent V.</p> <p>2004-10-01</p> <p>The Terra <span class="hlt">MODIS</span> and <span class="hlt">Aqua</span> <span class="hlt">MODIS</span> have been successfully operated on-orbit for a total of more than six and a half years, collecting data for the science and applications communities to develop and enhance their understanding of the Earth/atmosphere system and to support studies of the climate and climate changes. Since its launch in December 1999, the Terra <span class="hlt">MODIS</span> has experienced several changes of its operational configuration either caused by the failure of individual electronics subsystems or purposely switched for better signal response or data quality. Excluding minor anomalies related to instrument reset events during initial on-orbit operation, the <span class="hlt">Aqua</span> <span class="hlt">MODIS</span> has been operating in a single configuration since its launch in May 2002. There are approximately 40 science products that are being produced using the calibrated data sets from each instrument. In addition, several products are generated using the combined observations from both instruments. This paper provides an overview of Terra and <span class="hlt">Aqua</span> <span class="hlt">MODIS</span> instrument status and summarizes those on-orbit operational activities designed and implemented to provide and support instrument calibration and characterization. The assessments of instrument performance are based on the use of on-board calibrators (OBC) and other activities specially developed and implemented by the <span class="hlt">MODIS</span> Characterization Support Team (MCST) at NASA/GSFC. Both instruments are performing well. During four and a half years of Terra <span class="hlt">MODIS</span> on-orbit operation, 11 detectors became noisy and one inoperable out of a total of 490 detectors. Except for band 6 at 1.6m that had many inoperable detectors (identified pre-launch and immediately after launch), there have been no new noisy or inoperable detectors in <span class="hlt">Aqua</span> <span class="hlt">MODIS</span> during its two years of on-orbit operation. The sensors' spectral and spatial performance have also been very stable.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2015SPIE.9607E..1ZX','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2015SPIE.9607E..1ZX"><span id="translatedtitle">Calibration improvements for <span class="hlt">MODIS</span> and VIIRS SWIR spectral bands</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Xiong, Xiaoxiong; Angal, Amit; Fulbright, Jon; Lei, Ning; Mu, Qiaozhen; Wang, Zhipeng; Wu, Aisheng</p> <p>2015-09-01</p> <p>Both <span class="hlt">MODIS</span> and VIIRS use a solar diffuser (SD) to calibrate their <span class="hlt">reflective</span> solar bands (RSB), covering wavelengths from 0.41 to 2.3 μm. On-orbit changes of the SD bi-directional <span class="hlt">reflectance</span> factor (BRF) are tracked by an on-board solar diffuser stability monitor (SDSM). The current SDSM design only covers the spectral range from 0.41 to 0.93 μm. In general, the SD degradation is strongly wavelength-dependent with larger degradation occurring at shorter wavelengths, and the degradation in the SWIR region is expected to be extremely small. As each mission continues, however, the impact due to SD degradation at SWIR needs to be carefully examined and the correction if necessary should be applied in order to maintain the calibration quality. For Terra <span class="hlt">MODIS</span>, alternative approaches have been developed and used to estimate the SD degradation for its band 5 at 1.24 μm and a time-dependent correction has already been applied to the current level 1B (L1B) collection 6 (C6). In this paper, we present different methodologies that can be used to examine the SD degradation and their applications for both Terra and <span class="hlt">Aqua</span> <span class="hlt">MODIS</span> and S-NPP VIIRS SWIR calibration. These methodologies include but not limited to the use of lunar observations, Pseudo Invariant Calibration Sites (PICS), and deep convective clouds (DCC). A brief description of relative approaches and their use is also provided in this paper.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/cgi-bin/nph-data_query?bibcode=2012AGUFM.A33M0338G&link_type=ABSTRACT','NASAADS'); return false;" href="http://adsabs.harvard.edu/cgi-bin/nph-data_query?bibcode=2012AGUFM.A33M0338G&link_type=ABSTRACT"><span id="translatedtitle">Operationalizing a Research Sensor: <span class="hlt">MODIS</span> to VIIRS</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Grant, K. D.; Miller, S. W.; Puschell, J.</p> <p>2012-12-01</p> <p>The National Oceanic and Atmospheric Administration (NOAA) and NASA are jointly acquiring the next-generation civilian environmental satellite system: the Joint Polar Satellite System (JPSS). JPSS will replace the afternoon orbit component and ground processing system of the current Polar-orbiting Operational Environmental Satellites (POES) managed by NOAA. The JPSS satellite will carry a suite of sensors designed to collect meteorological, oceanographic, climatological, and solar-geophysical observations of the earth, atmosphere, and space. The primary sensor for the JPSS mission is the Visible/Infrared Imager Radiometer Suite (VIIRS) developed by Raytheon Space and Airborne Systems (SAS). The ground processing system for the JPSS mission is known as the Common Ground System (JPSS CGS), and consists of a Command, Control, and Communications Segment (C3S) and the Interface Data Processing Segment (IDPS) which are both developed by Raytheon Intelligence and Information Systems (IIS). The Moderate Resolution Imaging Spectroradiometer (<span class="hlt">MODIS</span>) was developed by Raytheon SAS for the NASA Earth Observing System (EOS) as a research instrument to capture data in 36 spectral bands, ranging in wavelength from 0.4 μm to 14.4 μm and at varying spatial resolutions (2 bands at 250 m, 5 bands at 500 m and 29 bands at 1 km). <span class="hlt">MODIS</span> data provides unprecedented insight into large-scale Earth system science questions related to cloud and aerosol characteristics, surface emissivity and processes occurring in the oceans, on land, and in the lower atmosphere. <span class="hlt">MODIS</span> has flown on the EOS Terra satellite since 1999 and on the EOS <span class="hlt">Aqua</span> satellite since 2002 and provided excellent data for scientific research and operational use for more than a decade. The value of <span class="hlt">MODIS</span>-derived products for operational environmental monitoring motivated led to the development of an operational counterpart to <span class="hlt">MODIS</span> for the next-generation polar-orbiting environmental satellites, the Visible/Infrared Imager</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://ntrs.nasa.gov/search.jsp?R=20030020719&hterms=classification+ecosystems&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D90%26Ntt%3Dclassification%2Becosystems','NASA-TRS'); return false;" href="http://ntrs.nasa.gov/search.jsp?R=20030020719&hterms=classification+ecosystems&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D90%26Ntt%3Dclassification%2Becosystems"><span id="translatedtitle">Remote Sensing of Cloud, Aerosol, and Land Properties from <span class="hlt">MODIS</span>: Applications to the East Asia Region</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>King, Michael D.; Platnick, Steven; Moody, Eric G.</p> <p>2002-01-01</p> <p><span class="hlt">MODIS</span> is an earth-viewing cross-track scanning spectroradiometer launched on the Terra satellite in December 1999 and the <span class="hlt">Aqua</span> satellite in May 2002. <span class="hlt">MODIS</span> 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 between 0.415 and 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 paper we will describe the various methods being used for the remote sensing of cloud, aerosol, and surface properties using <span class="hlt">MODIS</span> data, focusing primarily on (i) the <span class="hlt">MODIS</span> cloud mask used to distinguish clouds, clear sky, heavy aerosol, and shadows on the ground, (ii) cloud optical properties, especially cloud optical thickness and effective radius of water drops and ice crystals, (iii) aerosol optical thickness and size characteristics both over land and ocean, and (iv) ecosystem classification and surface spectral <span class="hlt">reflectance</span>. The physical principles behind the determination of each of these products will be described, together with an example of their application using <span class="hlt">MODIS</span> observations to the east Asian region. 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 min (Level-3 products).</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2013AGUFM.B33L..07D','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2013AGUFM.B33L..07D"><span id="translatedtitle">Identifying crop specific signals for global agricultural monitoring based on the stability of daily multi-angular <span class="hlt">MODIS</span> <span class="hlt">reflectance</span> time series</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Duveiller, G.; Lopez-Lozano, R.</p> <p>2013-12-01</p> <p>Global agricultural monitoring requires satellite Earth Observation systems that maximize the observation revisit frequency over the largest possible geographical coverage. Such compromise has thus far resulted in using a spatial resolution that is often coarser than desired. As a consequence, for many agricultural landscapes across the world, crop status can only be inferred from a mixed signal of the landscape (with a pixel size typically close to 1 km), composed of <span class="hlt">reflectance</span> from neighbouring fields with potentially different crops, variable phenological behaviours and distinct management practices. <span class="hlt">MODIS</span> has been providing, since 2000, a higher spatial resolution (~250m) that is closer to the size of individual fields in many agro-ecological landscapes. However, the challenge for operational crop specific monitoring remains to identify in time where a given crop has been sown during the current growing season. An innovative use of <span class="hlt">MODIS</span> daily data is proposed for crop identification based on the stability of the multi-angular signal. <span class="hlt">MODIS</span> is a whiskbroom sensor with a large swath. For any given place, consecutive <span class="hlt">MODIS</span> observations are made with considerably different viewing angles according to the daily change in orbit. Consequently, the footprint of the observation varies considerably, thereby sampling the vicinity around the centre of the grid cell in which the time series is ultimately recorded in. If the consecutive observations that have sampled the vicinity provide similar NDVI values (for which BRDF effects are reduced), the resulting temporal signal is relatively stable. This stability indicated that the signal comes from a spatially homogeneous surface, such as a single large field covered by the same crop with similar agro-management practices. If the resulting temporal signal is noisy, it is probable that the consecutive daily observations have sampled different land uses, thus contaminating the signal. Such time series can therefore be</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://pubs.usgs.gov/fs/2008/3061/','USGSPUBS'); return false;" href="http://pubs.usgs.gov/fs/2008/3061/"><span id="translatedtitle">Moderate Resolution Imaging Spectroradiometer (<span class="hlt">MODIS</span>) Overview</span></a></p> <p><a target="_blank" href="http://pubs.er.usgs.gov/pubs/index.jsp?view=adv">USGS Publications Warehouse</a></p> <p>U.S. Geological Survey</p> <p>2008-01-01</p> <p>The Moderate Resolution Imaging Spectroradiometer (<span class="hlt">MODIS</span>) is an instrument that collects remotely sensed data used by scientists for monitoring, modeling, and assessing the effects of natural processes and human actions on the Earth's surface. The continual calibration of the <span class="hlt">MODIS</span> instruments, the refinement of algorithms used to create higher-level products, and the ongoing product validation make <span class="hlt">MODIS</span> images a valuable time series (2000-present) of geophysical and biophysical land-surface measurements. Carried on two National Aeronautics and Space Administration (NASA) Earth Observing System (EOS) satellites, <span class="hlt">MODIS</span> acquires morning (EOS-Terra) and afternoon (EOS-<span class="hlt">Aqua</span>) views almost daily. Terra data acquisitions began in February 2000 and <span class="hlt">Aqua</span> data acquisitions began in July 2002. Land data are generated only as higher-level products, removing the burden of common types of data processing from the user community. <span class="hlt">MODIS</span>-based products describing ecological dynamics, radiation budget, and land cover are projected onto a sinusoidal mapping grid and distributed as 10- by 10-degree tiles at 250-, 500-, or 1,000-meter spatial resolution. Some products are also created on a 0.05-degree geographic grid to support climate modeling studies. All <span class="hlt">MODIS</span> products are distributed in the Hierarchical Data Format-Earth Observing System (HDF-EOS) file format and are available through file transfer protocol (FTP) or on digital video disc (DVD) media. Versions 4 and 5 of <span class="hlt">MODIS</span> land data products are currently available and represent 'validated' collections defined in stages of accuracy that are based on the number of field sites and time periods for which the products have been validated. Version 5 collections incorporate the longest time series of both Terra and <span class="hlt">Aqua</span> <span class="hlt">MODIS</span> data products.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/20110007087','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20110007087"><span id="translatedtitle">Trends in <span class="hlt">MODIS</span> Geolocation Error Analysis</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Wolfe, R. E.; Nishihama, Masahiro</p> <p>2009-01-01</p> <p>Data from the two <span class="hlt">MODIS</span> instruments have been accurately geolocated (Earth located) to enable retrieval of global geophysical parameters. The authors describe the approach used to geolocate with sub-pixel accuracy over nine years of data from M0DIS on NASA's E0S Terra spacecraft and seven years of data from <span class="hlt">MODIS</span> on the <span class="hlt">Aqua</span> spacecraft. The approach uses a geometric model of the <span class="hlt">MODIS</span> instruments, accurate navigation (orbit and attitude) data and an accurate Earth terrain model to compute the location of each <span class="hlt">MODIS</span> pixel. The error analysis approach automatically matches <span class="hlt">MODIS</span> imagery with a global set of over 1,000 ground control points from the finer-resolution Landsat satellite to measure static biases and trends in the MO0lS geometric model parameters. Both within orbit and yearly thermally induced cyclic variations in the pointing have been found as well as a general long-term trend.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2008AGUFM.H32B..04U','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2008AGUFM.H32B..04U"><span id="translatedtitle">The <span class="hlt">MODIS</span> Vegetation Canopy Water Content product</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Ustin, S. L.; Riano, D.; Trombetti, M.</p> <p>2008-12-01</p> <p>Vegetation water stress drives wildfire behavior and risk, having important implications for biogeochemical cycling in natural ecosystems, agriculture, and forestry. Water stress limits plant transpiration and carbon gain. The regulation of photosynthesis creates close linkages between the carbon, water, and energy cycles and through metabolism to the nitrogen cycle. We generated systematic weekly CWC estimated for the USA from 2000-2006. <span class="hlt">MODIS</span> measures the sunlit <span class="hlt">reflectance</span> of the vegetation in the visible, near-infrared, and shortwave infrared. Radiative transfer models, such as PROSPECT-SAILH, determine how sunlight interacts with plant and soil materials. These models can be applied over a range of scales and ecosystem types. Artificial Neural Networks (ANN) were used to optimize the inversion of these models to determine vegetation water content. We carried out multi-scale validation of the product using field data, airborne and satellite cross-calibration. An Algorithm Theoretical Basis Document (ATBD) of the product is under evaluation by NASA. The CWC product inputs are 1) The <span class="hlt">MODIS</span> Terra/<span class="hlt">Aqua</span> surface <span class="hlt">reflectance</span> product (MOD09A1/MYD09A1) 2) The <span class="hlt">MODIS</span> land cover map product (MOD12Q1) reclassified to grassland, shrub-land and forest canopies; 3) An ANN trained with PROSPECT-SAILH; 4) A calibration file for each land cover type. The output is an ENVI file with the CWC values. The code is written in Matlab environment and is being adapted to read not only the 8 day <span class="hlt">MODIS</span> composites, but also daily surface <span class="hlt">reflectance</span> data. We plan to incorporate the cloud and snow mask and generate as output a geotiff file. Vegetation water content estimates will help predicting linkages between biogeochemical cycles, which will enable further understanding of feedbacks to atmospheric concentrations of greenhouse gases. It will also serve to estimate primary productivity of the biosphere; monitor/assess natural vegetation health related to drought, pollution or diseases</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/20110006383','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20110006383"><span id="translatedtitle">On-Orbit Operation and Performance of <span class="hlt">MODIS</span> Blackbody</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Xiong, X.; Chang, T.; Barnes, W.</p> <p>2009-01-01</p> <p><span class="hlt">MODIS</span> collects data in 36 spectral bands, including 20 <span class="hlt">reflective</span> solar bands (RSB) and 16 thermal emissive bands (TES). The TEB on-orbit calibration is performed on a scan-by-scan basis using a quadratic algorithm that relates the detector response with the calibration radiance from the sensor on-board blackbody (BB). The calibration radiance is accurately determined each scan from the BB temperature measured using a set of 12 thermistors. The BB thermistors were calibrated pre-launch with traceability to the NIST temperature standard. Unlike many heritage sensors, the <span class="hlt">MODIS</span> BB can be operated at a constant temperature or with the temperature continuously varying between instrument ambient (about 270K) and 315K. In this paper, we provide an overview of both Terra and <span class="hlt">Aqua</span> <span class="hlt">MODIS</span> on-board BB operations, functions, and on-orbit performance. We also examine the impact of key calibration parameters, such as BB emissivity and temperature (stability and gradient) determined from its thermistors, on the TEB calibration and Level I (LIB) data product uncertainty.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2013AGUFM.B41D0430W','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2013AGUFM.B41D0430W"><span id="translatedtitle">Improvements to the <span class="hlt">MODIS</span> Land Products in Collection Version 6</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Wolfe, R. E.; Devadiga, S.; Masuoka, E. J.; Running, S. W.; Vermote, E.; Giglio, L.; Wan, Z.; Riggs, G. A.; Schaaf, C.; Myneni, R. B.; Friedl, M. A.; Wang, Z.; Sulla-menashe, D. J.; Zhao, M.</p> <p>2013-12-01</p> <p>The <span class="hlt">MODIS</span> (Moderate Resolution Imaging Spectroradiometer) Adaptive Processing System (MODAPS), housed at the NASA Goddard Space Flight Center (GSFC), has been processing the earth view data acquired by the <span class="hlt">MODIS</span> instrument aboard the Terra (EOS AM) and <span class="hlt">Aqua</span> (EOS PM) satellites to generate suite of land and atmosphere data products using the science algorithms developed by the <span class="hlt">MODIS</span> Science Team. These data products are used by diverse set of users in research and other applications from both government and non-government agencies around the world. These validated global products are also being used in interactive Earth system models able to predict global change accurately enough to assist policy makers in making sound decisions concerning the protection of our environment. Hence an increased emphasis is being placed on generation of high quality consistent data records from the <span class="hlt">MODIS</span> data through reprocessing of the records using improved science algorithms. Since the launch of Terra in December 1999, <span class="hlt">MODIS</span> land data records have been reprocessed four times. The Collection Version 6 (C6) reprocessing of <span class="hlt">MODIS</span> Land and Atmosphere products is scheduled to start in Fall 2013 and is expected to complete in Spring 2014. This presentation will describe changes made to the C6 science algorithms to correct issues in the C5 products, additional improvements made to the products as deemed necessary by the data users and science teams, and new products introduced in this reprocessing. In addition to the improvements from product specific changes to algorithms, the C6 products will also see significant improvement in the calibration by the <span class="hlt">MODIS</span> Calibration Science Team (MCST) of the C6 L1B Top of the Atmosphere (TOA) <span class="hlt">reflectance</span> and radiance product, more accurate geolocation, and an improved Land Water mask. For the a priori land cover input, this reprocessing will use the multi-year land cover product generated with three years of <span class="hlt">MODIS</span> data as input as opposed to one</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/20060047447','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20060047447"><span id="translatedtitle">Status of the <span class="hlt">MODIS</span> Level 1B Algorithms and Calibration Tables</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Xiong, X; Salomonson, V V; Kuyper, J; Tan, L; Chiang, K; Sun, J; Barnes, W L</p> <p>2005-01-01</p> <p>The Moderate Resolution Imaging Spectroradiometer (<span class="hlt">MODIS</span>) makes observations using 36 spectral bands with wavelengths from 0.41 to 14.4 m and nadir spatial resolutions of 0.25km, 0.5km, and 1km. It is currently operating onboard the NASA Earth Observing System (EOS) Terra and <span class="hlt">Aqua</span> satellites, launched in December 1999 and May 2002, respectively. The <span class="hlt">MODIS</span> Level 1B (L1B) program converts the sensor's on-orbit responses in digital numbers to radiometrically calibrated and geo-located data products for the duration of each mission. Its primary data products are top of the atmosphere (TOA) <span class="hlt">reflectance</span> factors for the sensor's <span class="hlt">reflective</span> solar bands (RSB) and TOA spectral radiances for the thermal emissive bands (TEB). The L1B algorithms perform the TEB calibration on a scan-by-scan basis using the sensor's response to the on-board blackbody (BB) and other parameters which are stored in Lookup Tables (LUTs). The RSB calibration coefficients are processed offline and regularly updated through LUTs. In this paper we provide a brief description of the <span class="hlt">MODIS</span> L1B calibration algorithms and associated LUTs with emphasis on their recent improvements and updates developed for the <span class="hlt">MODIS</span> collection 5 processing. We will also discuss sensor on-orbit calibration and performance issues that are critical to maintaining L1B data product quality, such as changes in the sensor's response versus scan-angle.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://ntrs.nasa.gov/search.jsp?R=20160007849&hterms=clouds&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D10%26Ntt%3Dclouds','NASA-TRS'); return false;" href="http://ntrs.nasa.gov/search.jsp?R=20160007849&hterms=clouds&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D10%26Ntt%3Dclouds"><span id="translatedtitle">Assessment of <span class="hlt">MODIS</span> RSB Detector Uniformity Using Deep Convective Clouds</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Chang, Tiejun; Xiong, Xiaoxiong (Jack); Angal, Amit; Mu, Qiaozhen</p> <p>2016-01-01</p> <p>For satellite sensor, the striping observed in images is typically associated with the relative multiple detector gain difference derived from the calibration. A method using deep convective cloud (DCC) measurements to assess the difference among detectors after calibration is proposed and demonstrated for select <span class="hlt">reflective</span> solar bands (RSBs) of the Moderate Resolution Imaging Spectroradiometer (<span class="hlt">MODIS</span>). Each detector of <span class="hlt">MODIS</span> RSB is calibrated independently using a solar diffuser (SD). Although the SD is expected to accurately characterize detector response, the uncertainties associated with the SD degradation and characterization result in inadequacies in the estimation of each detector's gain. This work takes advantage of the DCC technique to assess detector uniformity and scan mirror side difference for RSB. The detector differences for Terra <span class="hlt">MODIS</span> Collection 6 are less than 1% for bands 1, 3-5, and 18 and up to 2% for bands 6, 19, and 26. The largest difference is up to 4% for band 7. Most <span class="hlt">Aqua</span> bands have detector differences less than 0.5% except bands 19 and 26 with up to 1.5%. Normally, large differences occur for edge detectors. The long-term trending shows seasonal oscillations in detector differences for some bands, which are correlated with the instrument temperature. The detector uniformities were evaluated for both unaggregated and aggregated detectors for <span class="hlt">MODIS</span> band 1 and bands 3-7, and their consistencies are verified. The assessment results were validated by applying a direct correction to <span class="hlt">reflectance</span> images. These assessments can lead to improvements to the calibration algorithm and therefore a reduction in striping observed in the calibrated imagery.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2016JGRD..121.4783C','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2016JGRD..121.4783C"><span id="translatedtitle">Assessment of <span class="hlt">MODIS</span> RSB detector uniformity using deep convective clouds</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Chang, Tiejun; Xiong, Xiaoxiong (Jack); Angal, Amit; Mu, Qiaozhen</p> <p>2016-05-01</p> <p>For satellite sensor, the striping observed in images is typically associated with the relative multiple detector gain difference derived from the calibration. A method using deep convective cloud (DCC) measurements to assess the difference among detectors after calibration is proposed and demonstrated for select <span class="hlt">reflective</span> solar bands (RSBs) of the Moderate Resolution Imaging Spectroradiometer (<span class="hlt">MODIS</span>). Each detector of <span class="hlt">MODIS</span> RSB is calibrated independently using a solar diffuser (SD). Although the SD is expected to accurately characterize detector response, the uncertainties associated with the SD degradation and characterization result in inadequacies in the estimation of each detector's gain. This work takes advantage of the DCC technique to assess detector uniformity and scan mirror side difference for RSB. The detector differences for Terra <span class="hlt">MODIS</span> Collection 6 are less than 1% for bands 1, 3-5, and 18 and up to 2% for bands 6, 19, and 26. The largest difference is up to 4% for band 7. Most <span class="hlt">Aqua</span> bands have detector differences less than 0.5% except bands 19 and 26 with up to 1.5%. Normally, large differences occur for edge detectors. The long-term trending shows seasonal oscillations in detector differences for some bands, which are correlated with the instrument temperature. The detector uniformities were evaluated for both unaggregated and aggregated detectors for <span class="hlt">MODIS</span> band 1 and bands 3-7, and their consistencies are verified. The assessment results were validated by applying a direct correction to <span class="hlt">reflectance</span> images. These assessments can lead to improvements to the calibration algorithm and therefore a reduction in striping observed in the calibrated imagery.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=2171368','PMC'); return false;" href="http://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=2171368"><span id="translatedtitle">Global Data for Ecology and Epidemiology: A Novel Algorithm for Temporal Fourier Processing <span class="hlt">MODIS</span> Data</span></a></p> <p><a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pmc">PubMed Central</a></p> <p>Scharlemann, Jörn P. W.; Benz, David; Hay, Simon I.; Purse, Bethan V.; Tatem, Andrew J.; Wint, G. R. William; Rogers, David J.</p> <p>2008-01-01</p> <p>Background Remotely-sensed environmental data from earth-orbiting satellites are increasingly used to model the distribution and abundance of both plant and animal species, especially those of economic or conservation importance. Time series of data from the MODerate-resolution Imaging Spectroradiometer (<span class="hlt">MODIS</span>) sensors on-board NASA's Terra and <span class="hlt">Aqua</span> satellites offer the potential to capture environmental thermal and vegetation seasonality, through temporal Fourier analysis, more accurately than was previously possible using the NOAA Advanced Very High Resolution Radiometer (AVHRR) sensor data. <span class="hlt">MODIS</span> data are composited over 8- or 16-day time intervals that pose unique problems for temporal Fourier analysis. Applying standard techniques to <span class="hlt">MODIS</span> data can introduce errors of up to 30% in the estimation of the amplitudes and phases of the Fourier harmonics. Methodology/Principal Findings We present a novel spline-based algorithm that overcomes the processing problems of composited <span class="hlt">MODIS</span> data. The algorithm is tested on artificial data generated using randomly selected values of both amplitudes and phases, and provides an accurate estimate of the input variables under all conditions. The algorithm was then applied to produce layers that capture the seasonality in <span class="hlt">MODIS</span> data for the period from 2001 to 2005. Conclusions/Significance Global temporal Fourier processed images of 1 km <span class="hlt">MODIS</span> data for Middle Infrared <span class="hlt">Reflectance</span>, day- and night-time Land Surface Temperature (LST), Normalised Difference Vegetation Index (NDVI), and Enhanced Vegetation Index (EVI) are presented for ecological and epidemiological applications. The finer spatial and temporal resolution, combined with the greater geolocational and spectral accuracy of the <span class="hlt">MODIS</span> instruments, compared with previous multi-temporal data sets, mean that these data may be used with greater confidence in species' distribution modelling. PMID:18183289</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/cgi-bin/nph-data_query?bibcode=2011AGUFM.U41B0013G&link_type=ABSTRACT','NASAADS'); return false;" href="http://adsabs.harvard.edu/cgi-bin/nph-data_query?bibcode=2011AGUFM.U41B0013G&link_type=ABSTRACT"><span id="translatedtitle"><span class="hlt">Aqua</span> Education and Public Outreach</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Graham, S. M.; Parkinson, C. L.; Chambers, L. H.; Ray, S. E.</p> <p>2011-12-01</p> <p>NASA's <span class="hlt">Aqua</span> satellite was launched on May 4, 2002, with six instruments designed to collect data about the Earth's atmosphere, biosphere, hydrosphere, and cryosphere. Since the late 1990s, the <span class="hlt">Aqua</span> mission has involved considerable education and public outreach (EPO) activities, including printed products, formal education, an engineering competition, webcasts, and high-profile multimedia efforts. The printed products include <span class="hlt">Aqua</span> and instrument brochures, an <span class="hlt">Aqua</span> lithograph, <span class="hlt">Aqua</span> trading cards, NASA Fact Sheets on <span class="hlt">Aqua</span>, the water cycle, and weather forecasting, and an <span class="hlt">Aqua</span> science writers' guide. On-going formal education efforts include the Students' Cloud Observations On-Line (S'COOL) Project, the MY NASA DATA Project, the Earth System Science Education Alliance, and, in partnership with university professors, undergraduate student research modules. Each of these projects incorporates <span class="hlt">Aqua</span> data into its inquiry-based framework. Additionally, high school and undergraduate students have participated in summer internship programs. An earlier formal education activity was the <span class="hlt">Aqua</span> Engineering Competition, which was a high school program sponsored by the NASA Goddard Space Flight Center, Morgan State University, and the Baltimore Museum of Industry. The competition began with the posting of a Round 1 <span class="hlt">Aqua</span>-related engineering problem in December 2002 and concluded in April 2003 with a final round of competition among the five finalist teams. The <span class="hlt">Aqua</span> EPO efforts have also included a wide range of multimedia products. Prior to launch, the <span class="hlt">Aqua</span> team worked closely with the Special Projects Initiative (SPI) Office to produce a series of live webcasts on <span class="hlt">Aqua</span> science and the Cool Science website <span class="hlt">aqua</span>.nasa.gov/coolscience, which displays short video clips of <span class="hlt">Aqua</span> scientists and engineers explaining the many aspects of the <span class="hlt">Aqua</span> mission. These video clips, the <span class="hlt">Aqua</span> website, and numerous presentations have benefited from dynamic visualizations showing the <span class="hlt">Aqua</span> launch</p> </li> </ol> <div class="pull-right"> <ul class="pagination"> <li><a href="#" onclick='return showDiv("page_1");'>«</a></li> <li><a href="#" onclick='return showDiv("page_8");'>8</a></li> <li><a href="#" onclick='return showDiv("page_9");'>9</a></li> <li class="active"><span>10</span></li> <li><a href="#" onclick='return showDiv("page_11");'>11</a></li> <li><a href="#" onclick='return showDiv("page_12");'>12</a></li> <li><a href="#" onclick='return showDiv("page_25");'>»</a></li> </ul> </div> </div><!-- col-sm-12 --> </div><!-- row --> </div><!-- page_10 --> <div id="page_11" class="hiddenDiv"> <div class="row"> <div class="col-sm-12"> <div class="pull-right"> <ul class="pagination"> <li><a href="#" onclick='return showDiv("page_1");'>«</a></li> <li><a href="#" onclick='return showDiv("page_9");'>9</a></li> <li><a href="#" onclick='return showDiv("page_10");'>10</a></li> <li class="active"><span>11</span></li> <li><a href="#" onclick='return showDiv("page_12");'>12</a></li> <li><a href="#" onclick='return showDiv("page_13");'>13</a></li> <li><a href="#" onclick='return showDiv("page_25");'>»</a></li> </ul> </div> </div> </div> <div class="row"> <div class="col-sm-12"> <ol class="result-class" start="201"> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2009GeoRL..36.9811L','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2009GeoRL..36.9811L"><span id="translatedtitle">View-angle consistency in <span class="hlt">reflectance</span>, optical thickness and spherical albedo of marine water-clouds over the northeastern Pacific through MISR-<span class="hlt">MODIS</span> fusion</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Liang, Lusheng; Di Girolamo, Larry; Platnick, Steven</p> <p>2009-05-01</p> <p>View-angle consistency in bidirectional <span class="hlt">reflectance</span> factor (BRF), optical thickness and spherical albedo is examined for marine water clouds over a region of the northeastern Pacific using six years of fused Moderate Resolution Imaging Spectroradiometer (<span class="hlt">MODIS</span>) and Multiangle Imaging SpectroRadiometer (MISR) data. Consistency is quantified by the root-mean-square of relative differences between MISR-measured BRF and their plane-parallel values and variation of plane-parallel retrieved optical thickness and spherical albedo across multiple view-angles. Probability distribution functions of consistency show that, for example, these clouds are angularly consistent within 5% in BRF, optical thickness and spherical albedo 72.2%, 39.0% and 81.1% of the time, respectively. We relate angular consistency to the spatial variability of nadir-BRF, thus allowing us to potentially identify, with a prescribed confidence level, which <span class="hlt">MODIS</span> microphysical retrievals within the MISR swath meet the plane-parallel assumption to within any desired range in view-angle consistency.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2008SPIE.7081E..0CX','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2008SPIE.7081E..0CX"><span id="translatedtitle">Characterization of <span class="hlt">MODIS</span> VIS/NIR spectral band detector-to-detector differences</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Xiong, X.; Sun, J.; Meister, G.; Kwiatkowska, E.; Barnes, W. L.</p> <p>2008-08-01</p> <p><span class="hlt">MODIS</span> has 36 spectral bands with wavelengths in the visible (VIS), near-infrared (NIR), short-wave infrared (SWIR), mid-wave infrared (MWIR), and long-wave infrared (LWIR). It makes observations at three nadir spatial resolutions: 0.25km for bands 1-2 (40 detectors per band), 0.5km for bands 3-7 (20 detectors per band), and 1km for bands 8-36 (10 detectors per band). The VIS, NIR, and SWIR are the <span class="hlt">reflective</span> solar bands (RSB), which are calibrated on-orbit by a solar diffuser (SD) and a solar diffuser stability monitor (SDSM). The bi-directional <span class="hlt">reflectance</span> factor (BRF) of the SD provides a RSB calibration reference and its on-orbit changes are tracked by the SDSM. In addition, <span class="hlt">MODIS</span> lunar observations are regularly scheduled and used to track the RSB calibration stability. On-orbit observations show that the changes in detector response are wavelength and scan angle dependent. In this study, we focus on detector-to-detector calibration differences in the <span class="hlt">MODIS</span> VIS/NIR spectral bands, which are determined using SD and lunar observations, while the calibration performance is evaluated using the Earth view (EV) level 1B (L1B) data products. For <span class="hlt">Aqua</span> <span class="hlt">MODIS</span>, the detector calibration differences and their impact are also characterized using standard ocean color data products. The current calibration approach for <span class="hlt">MODIS</span> RSB carries a band-averaged response versus scan angle (RVS) correction. The results from this study suggest that a detector-based RVS correction should, due to changes in the scan mirror's optical properties, be implemented in order to maintain and improve the current RSB L1B data product quality, particularly, for several VIS bands in Terra <span class="hlt">MODIS</span>.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2008AGUFM.A33C0251J','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2008AGUFM.A33C0251J"><span id="translatedtitle">Investigating Correlations Between Satellite-Derived Aerosol Optical Depth And Ground PM2.5 Measurements in Californias San Joaquin Valley with <span class="hlt">MODIS</span> Deep Blue</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Justice, E.; Huston, L.; Krauth, D.; Mack, J.; Oza, S.; Strawa, A.; Legg, M.; Schmidt, C.; Skiles, J.</p> <p>2008-12-01</p> <p>Air quality in the San Joaquin Valley has failed to meet state and federal particulate matter (PM) attainment standards for the past several years. Air quality agencies currently use ground sensors to monitor the region's air. While this method provides accurate information at specific locations, it does not provide a clear indication of conditions over large regions. Measurements from satellite imagery have the potential to provide timely air quality data for large swaths of land. While previous studies show strong correlations between <span class="hlt">MODIS</span>-derived Aerosol Optical Depth (AOD) and surface PM measurements on the East Coast of the United States, only weak correlations have been found in the West. Specific causes of this discrepancy have not been identified, nor has a solution been found. This study compares hourly and daily surface PM measurements to both traditional and Deep Blue-derived <span class="hlt">Aqua</span> <span class="hlt">MODIS</span> AOD data. Deep Blue is a newly developed algorithm that was recently applied to all <span class="hlt">Aqua</span> <span class="hlt">MODIS</span> data. Additionally, we analyzed the effects of relative humidity, surface <span class="hlt">reflectance</span>, and aerosol vertical distribution, from CALIPSO's CALIOP sensor, on differences in PM and AOD measurements. Results show hourly PM2.5 data improved correlations with satellite AOD values. Also PM2.5 data, corresponding to sites in Bakersfield and Fresno, correlate better with Deep Blue-derived AOD values than with traditional <span class="hlt">MODIS</span> AOD. Further investigation into the affects of seasonal variation, particle distribution and speciation is needed.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2014AGUFMIN11B3609R','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2014AGUFMIN11B3609R"><span id="translatedtitle">Protocol for Validation of the Land Surface <span class="hlt">Reflectance</span> Fundamental Climate Data Record using AERONET: Application to the Global <span class="hlt">MODIS</span> and VIIRS Data Records</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Roger, J. C.; Vermote, E.; Holben, B. N.</p> <p>2014-12-01</p> <p>The land surface <span class="hlt">reflectance</span> is a fundamental climate data record at the basis of the derivation of other climate data records (Albedo, LAI/Fpar, Vegetation indices) and a key parameter in the understanding of the land-surface-climate processes. It is essential that a careful validation of its uncertainties is performed on a global and continuous basis. One approach is the direct comparison of this product with ground measurements but that approach presents several issues related to scale, the episodic nature of ground measurements and the global representativeness. An alternative is to compare the surface <span class="hlt">reflectance</span> product to reference <span class="hlt">reflectance</span> determined from Top of atmosphere <span class="hlt">reflectance</span> corrected using accurate radiative transfer code and very detailed measurements of the atmosphere obtained over the AERONET sites (Vermote and al, 2014, RSE) which allows to test for a large range of aerosol characteristics; formers being important inputs for atmospheric corrections. However, the application of this method necessitates the definition of a very detailed protocol for the use of AERONET data especially as far as size distribution and absorption are concerned, so that alternative validation methods or protocols could be compared. This paper describes the protocol we have been working on based on our experience with the AERONET data and its application to the <span class="hlt">MODIS</span> and VIIRS record.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2003SPIE.5151..375X','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2003SPIE.5151..375X"><span id="translatedtitle">On-orbit characterization of a solar diffuser"s bidirectional <span class="hlt">reflectance</span> factor using spacecraft maneuvers</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Xiong, Xiaoxiong; Sun, Junqiang; Esposito, Joe; Liu, Xiaojin; Barnes, William L.; Guenther, B.</p> <p>2003-11-01</p> <p>The MODerate Resolution Imaging Spectroradiometer (<span class="hlt">MODIS</span>) uses an on-board solar diffuser (SD) panel made of Spectralon for the radiometric calibration of its 20 <span class="hlt">reflective</span> solar bands (RSB). The spectral wavelengths of the RSB range from 0.41 to 2.1 micrometers. The on-orbit calibration coefficients are determined from the sensor s responses to the diffusely <span class="hlt">reflected</span> solar illumination from the SD. This method requires an accurate pre-launch characterization of solar diffuser s bi-directional <span class="hlt">reflectance</span> factors (BRF) that should cover the sensor s spectral range and illumination/viewing angles and accurate on-orbit monitoring of SD degradation over time. The <span class="hlt">MODIS</span> SD panel s bi-directional <span class="hlt">reflectance</span> factors were characterized prior to the sensor s final system integration (pre-launch by the instrument vendor using reference samples traceable to the NIST <span class="hlt">reflectance</span> standards at a number of wavelengths and carefully selected combinations of the illumination/viewing angles. The measured BRF values were fitted into smooth surfaces and then interpolated for each of the <span class="hlt">MODIS</span> <span class="hlt">reflective</span> solar bands. In this paper, we describe an approach designed for the <span class="hlt">MODIS</span> on-orbit characterization and validation of its SD BRF using multiple SD solar observations at several spacecraft yaw angels. This approach has been successfully applied to both the Terra and <span class="hlt">Aqua</span> <span class="hlt">MODIS</span>. This paper presents the algorithm used to derive the SD s relative BRF from observations during spacecraft yaws and compares the on-orbit results with corresponding pre-launch values.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/20100020840','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20100020840"><span id="translatedtitle"><span class="hlt">MODIS</span> On-Board Blackbody Function and Performance</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Xiaoxiong, Xiong; Wenny, Brian N.; Wu, Aisheng; Barnes, William</p> <p>2009-01-01</p> <p>Two <span class="hlt">MODIS</span> instruments are currently in orbit, making continuous global observations in visible to long-wave infrared wavelengths. Compared to heritage sensors, <span class="hlt">MODIS</span> was built with an advanced set of on-board calibrators, providing sensor radiometric, spectral, and spatial calibration and characterization during on-orbit operation. For the thermal emissive bands (TEB) with wavelengths from 3.7 m to 14.4 m, a v-grooved blackbody (BB) is used as the primary calibration source. The BB temperature is accurately measured each scan (1.47s) using a set of 12 temperature sensors traceable to NIST temperature standards. The onboard BB is nominally operated at a fixed temperature, 290K for Terra <span class="hlt">MODIS</span> and 285K for <span class="hlt">Aqua</span> <span class="hlt">MODIS</span>, to compute the TEB linear calibration coefficients. Periodically, its temperature is varied from 270K (instrument ambient) to 315K in order to evaluate and update the nonlinear calibration coefficients. This paper describes <span class="hlt">MODIS</span> on-board BB functions with emphasis on on-orbit operation and performance. It examines the BB temperature uncertainties under different operational conditions and their impact on TEB calibration and data product quality. The temperature uniformity of the BB is also evaluated using TEB detector responses at different operating temperatures. On-orbit results demonstrate excellent short-term and long-term stability for both the Terra and <span class="hlt">Aqua</span> <span class="hlt">MODIS</span> on-board BB. The on-orbit BB temperature uncertainty is estimated to be 10mK for Terra <span class="hlt">MODIS</span> at 290K and 5mK for <span class="hlt">Aqua</span> <span class="hlt">MODIS</span> at 285K, thus meeting the TEB design specifications. In addition, there has been no measurable BB temperature drift over the entire mission of both Terra and <span class="hlt">Aqua</span> <span class="hlt">MODIS</span>.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2012EGUGA..14.3132T','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2012EGUGA..14.3132T"><span id="translatedtitle">Using <span class="hlt">MODIS</span> data to estimate river discharge in ungauged sites</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Tarpanelli, A.; Brocca, L.; Lacava, T.; Faruolo, M.; Melone, F.; Moramarco, T.; Pergola, N.; Tramutoli, V.</p> <p>2012-04-01</p> <p>The discharge prediction at a river site is fundamental for water resources management and flood risk prevention. An accurate discharge estimation depends on local hydraulic conditions which are usually detected by recording water level and carrying out flow measurements, which are costly and sometimes impractical for high flows. Over the last decade, the possibility to obtain river discharge estimates from satellite sensors data has become of considerable interest. For large river basins, the use of satellite data derived by altimeter and microwave sensors, characterized by a daily temporal resolution, has proven to be a useful tool to integrate or even increase the discharge monitoring. For smaller basins, Synthetic Aperture Radars (SARs) have been usually employed for the indirect estimation of water elevation but their low temporal resolution (from a few days up to 30 days) might be considered not suitable for discharge prediction. The Moderate Resolution Imaging Spectroradiometer (<span class="hlt">MODIS</span>) aboard of Terra and <span class="hlt">Aqua</span> Earth Observing System (EOS) satellites, can provide a proper tradeoff between temporal and spatial resolution useful for discharge estimation. It assures, in fact, at least a daily temporal resolution and a spatial resolution up to 250 m in the first two channels. In this study, the capability of <span class="hlt">MODIS</span> data for discharge prediction is investigated. Specifically, the different spectral behavior of water and land in the Near Infrared (NIR) portion of the electromagnetic spectrum (<span class="hlt">MODIS</span> channel 2) is exploited by computing the ratio of the <span class="hlt">MODIS</span> channel 2 <span class="hlt">reflectance</span> values between two pixels located within and outside the river. Values of such a ratio should increase when more water and, hence, discharge, is present. Time series of daily water level, velocity and discharge between 2002 and 2010 measured at different gauging stations located along the Upper Tiber River (central Italy) and the Po River (North Italy), as well as <span class="hlt">MODIS</span> channel 2 data for</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/20080023286','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20080023286"><span id="translatedtitle"><span class="hlt">MODIS</span> Land Data Products: Generation, Quality Assurance and Validation</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Masuoka, Edward; Wolfe, Robert; Morisette, Jeffery; Sinno, Scott; Teague, Michael; Saleous, Nazmi; Devadiga, Sadashiva; Justice, Christopher; Nickeson, Jaime</p> <p>2008-01-01</p> <p>The Moderate Resolution Imaging Spectrometer (<span class="hlt">MODIS</span>) on-board NASA's Earth Observing System (EOS) Terra and <span class="hlt">Aqua</span> Satellites are key instruments for providing data on global land, atmosphere, and ocean dynamics. Derived <span class="hlt">MODIS</span> land, atmosphere and ocean products are central to NASA's mission to monitor and understand the Earth system. NASA has developed and generated on a systematic basis a suite of <span class="hlt">MODIS</span> products starting with the first Terra <span class="hlt">MODIS</span> data sensed February 22, 2000 and continuing with the first <span class="hlt">MODIS-Aqua</span> data sensed July 2, 2002. The <span class="hlt">MODIS</span> Land products are divided into three product suites: radiation budget products, ecosystem products, and land cover characterization products. The production and distribution of the <span class="hlt">MODIS</span> Land products are described, from initial software delivery by the <span class="hlt">MODIS</span> Land Science Team, to operational product generation and quality assurance, delivery to EOS archival and distribution centers, and product accuracy assessment and validation. Progress and lessons learned since the first <span class="hlt">MODIS</span> data were in early 2000 are described.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/cgi-bin/nph-data_query?bibcode=2016AMT.....9.3193S&link_type=ABSTRACT','NASAADS'); return false;" href="http://adsabs.harvard.edu/cgi-bin/nph-data_query?bibcode=2016AMT.....9.3193S&link_type=ABSTRACT"><span id="translatedtitle">Comparison of <span class="hlt">MODIS</span> and VIIRS cloud properties with ARM ground-based observations over Finland</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Sporre, Moa K.; O'Connor, Ewan J.; Håkansson, Nina; Thoss, Anke; Swietlicki, Erik; Petäjä, Tuukka</p> <p>2016-07-01</p> <p>Cloud retrievals from the Moderate Resolution Imaging Spectroradiometer (<span class="hlt">MODIS</span>) instruments aboard the satellites Terra and <span class="hlt">Aqua</span> and the Visible Infrared Imaging Radiometer Suite (VIIRS) instrument aboard the Suomi-NPP satellite are evaluated using a combination of ground-based instruments providing vertical profiles of clouds. The ground-based measurements are obtained from the Atmospheric Radiation Measurement (ARM) programme mobile facility, which was deployed in Hyytiälä, Finland, between February and September 2014 for the Biogenic Aerosols - Effects on Clouds and Climate (BAECC) campaign. The satellite cloud parameters cloud top height (CTH) and liquid water path (LWP) are compared with ground-based CTH obtained from a cloud mask created using lidar and radar data and LWP acquired from a multi-channel microwave radiometer. Clouds from all altitudes in the atmosphere are investigated. The clouds are diagnosed as single or multiple layer using the ground-based cloud mask. For single-layer clouds, satellites overestimated CTH by 326 m (14 %) on average. When including multilayer clouds, satellites underestimated CTH by on average 169 m (5.8 %). <span class="hlt">MODIS</span> collection 6 overestimated LWP by on average 13 g m-2 (11 %). Interestingly, LWP for <span class="hlt">MODIS</span> collection 5.1 is slightly overestimated by <span class="hlt">Aqua</span> (4.56 %) but is underestimated by Terra (14.3 %). This underestimation may be attributed to a known issue with a drift in the <span class="hlt">reflectance</span> bands of the <span class="hlt">MODIS</span> instrument on Terra. This evaluation indicates that the satellite cloud parameters selected show reasonable agreement with their ground-based counterparts over Finland, with minimal influence from the large solar zenith angle experienced by the satellites in this high-latitude location.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://pubs.er.usgs.gov/publication/70173626','USGSPUBS'); return false;" href="http://pubs.er.usgs.gov/publication/70173626"><span id="translatedtitle">High-frequency remote monitoring of large lakes with <span class="hlt">MODIS</span> 500 m imagery</span></a></p> <p><a target="_blank" href="http://pubs.er.usgs.gov/pubs/index.jsp?view=adv">USGS Publications Warehouse</a></p> <p>McCullough, Ian M.; Loftin, Cynthia S.; Sader, Steven A.</p> <p>2012-01-01</p> <p>Satellite-based remote monitoring programs of regional lake water quality largely have relied on Landsat Thematic Mapper (TM) owing to its long image archive, moderate spatial resolution (30 m), and wide sensitivity in the visible portion of the electromagnetic spectrum, despite some notable limitations such as temporal resolution (i.e., 16 days), data pre-processing requirements to improve data quality, and aging satellites. Moderate-Resolution Imaging Spectroradiometer (<span class="hlt">MODIS</span>) sensors on <span class="hlt">Aqua</span>/Terra platforms compensate for these shortcomings, although at the expense of spatial resolution. We developed and evaluated a remote monitoring protocol for water clarity of large lakes using <span class="hlt">MODIS</span> 500 m data and compared <span class="hlt">MODIS</span> utility to Landsat-based methods. <span class="hlt">MODIS</span> images captured during May–September 2001, 2004 and 2010 were analyzed with linear regression to identify the relationship between lake water clarity and satellite-measured surface <span class="hlt">reflectance</span>. Correlations were strong (R² = 0.72–0.94) throughout the study period; however, they were the most consistent in August, <span class="hlt">reflecting</span> seasonally unstable lake conditions and inter-annual differences in algal productivity during the other months. The utility of <span class="hlt">MODIS</span> data in remote water quality estimation lies in intra-annual monitoring of lake water clarity in inaccessible, large lakes, whereas Landsat is more appropriate for inter-annual, regional trend analyses of lakes ≥ 8 ha. Model accuracy is improved when ancillary variables are included to <span class="hlt">reflect</span> seasonal lake dynamics and weather patterns that influence lake clarity. The identification of landscape-scale drivers of regional water quality is a useful way to supplement satellite-based remote monitoring programs relying on spectral data alone.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://ntrs.nasa.gov/search.jsp?R=20090027813&hterms=art+performance&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D30%26Ntt%3Dart%2Bperformance','NASA-TRS'); return false;" href="http://ntrs.nasa.gov/search.jsp?R=20090027813&hterms=art+performance&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D30%26Ntt%3Dart%2Bperformance"><span id="translatedtitle">Performance of <span class="hlt">MODIS</span> Thermal Emissive Bands On-orbit Calibration Algorithms</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Xiong, Xiaoxiong; Chang, T.</p> <p>2009-01-01</p> <p>Two nearly identical copies of the Moderate Resolution Imaging Spectroradiometer (<span class="hlt">MODIS</span>) are currently operated on-board the Terra and <span class="hlt">Aqua</span> spacecrafts, launched in December 1999 and May 2002, respectively. Together, they have produced an unprecedented amount of science data products, which are widely used for the studies of changes in the Earth's system of land, oceans, and atmosphere. <span class="hlt">MODIS</span> is a cross-track scanning radiometer, which uses a two-sided scan mirror and collects data continuously over a wide scan angle range (+/-55 degree relative to the instrument nadir) each scan of 1.47 seconds. It has 36 spectral bands with wavelengths ranging from visible (VIS) to long-wave infrared (LWIR). <span class="hlt">MODIS</span> bands 1-19 and 26 are the <span class="hlt">reflective</span> solar bands (RSB) and bands 20-25 and 27-36 are the thermal emissive bands (TEB). <span class="hlt">MODIS</span> was developed and designed with improvements made over its heritage sensors (such as AVHRR and Landsat) and, in particular, with more stringent calibration requirements. Because of this, <span class="hlt">MODIS</span> was built with a set of state-of-art on-board calibrators (OBC), which include a solar diffuser (SD), a solar diffuser stability monitor (SDSM), a blackbody (BB), a spectroradiometric calibration assembly (SRCA), and a space view (SV) port. With the exception of view angle differences, <span class="hlt">MODIS</span> OBC measurements and the Earth View (EV) observations are made via the same optical path. <span class="hlt">MODIS</span> TEB have a total of 160 individual TEB detectors (10 per band), which are located on two cold focal plane assemblies (CFPA). For nominal on-orbit operation, the CFPA temperature is controlled at 83K via a passive radiative cooler. For the TEB, the calibration requirements at specified typical scene radiances are less than or equal to 1% with an exception for the fire detection (low gain) band. <span class="hlt">MODIS</span> TEB on-orbit calibration is performed on a scan-by-scan basis using a quadratic calibration algorithm, and data collected from sensor responses to the onboard BB and SV. The BB</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2014E%26ES...17a2112Y','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2014E%26ES...17a2112Y"><span id="translatedtitle">Retrieval of Secchi disk depth in the Yellow Sea and East China Sea using 8-day <span class="hlt">MODIS</span> data</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Yu, D. F.; Xing, Q. G.; Lou, M. J.; Shi, P.</p> <p>2014-03-01</p> <p>Secchi disk depth (SDD), is widely used as an indicator of water clarity. The traditional sampling method is not only time-consuming and labor-intensive but also limited in terms of temporal and spatial coverage. Remote sensing technology may deal with these limitations. In this paper, the applicability of 8-day <span class="hlt">MODIS-Aqua</span> remote sensing <span class="hlt">reflectance</span> data with 4 km spatial resolution for estimating water clarity in the Yellow Sea and the East China Sea was investigated. Field data such as Secchi depths were collected from two cruises conducted in the Yellow Sea and the East China Sea from 5 May to 7 June 2009. A three-band algorithm to retrieve SDD was developed based on remote sensing <span class="hlt">reflectance</span> at bands of 488, 555, and 678 nm, which performed better than single-band model and band ratio algorithm, with a determination coefficient of 0.72 and a mean relative error of 19%. This suggests that 8-day <span class="hlt">MODIS-Aqua</span> products of remote sensing <span class="hlt">reflectance</span> could be used to assess water transparency in the study area.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2012AGUFM.A13J0305L','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2012AGUFM.A13J0305L"><span id="translatedtitle">Introduction to <span class="hlt">MODIS</span> Collection 6 'Deep Blue' aerosol products and strategy for cirrus-signal correction in AOD retrievals using 1.38 μm <span class="hlt">reflectance</span> data</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Lee, J.; Hsu, N. C.; Sayer, A. M.; Bettenhausen, C.</p> <p>2012-12-01</p> <p>This study shows the characteristics of the Moderate Resolution Imaging Spectroradiometer (<span class="hlt">MODIS</span>) Collection 6 Deep Blue aerosol products (hereafter, C006 DB products) and a strategy for correcting cirrus-signal in the aerosol optical depth (AOD) retrievals. The C006 DB products have several changes over the C005, including extended coverage, surface <span class="hlt">reflectance</span> model, aerosol microphysical model, and cloud screening, etc. One of the new features is the inclusion of pixel-level uncertainty estimates on the retrieved AOD. These uncertainty estimates have been determined based on a validation against Aerosol Robotic Network (AERONET) direct-Sun AOD measurements, and are parameterized as a function of AOD, viewing geometry, and retrieval quality flag. This will provide users with a simple way to assess the uncertainty on Deep Blue AOD data for their particular application of interest. Preliminary results show strong agreement with AERONET, suggesting that the Deep Blue algorithm performs as well as other state-of-the-art satellite AOD datasets. In addition, a strategy for cirrus-signal correction in the retrieved AOD is presented. The cirrus <span class="hlt">reflectance</span> at each wavelength to be used in the aerosol retrieval algorithms is determined by the relationships between <span class="hlt">reflectances</span> at 1.38 μm and the aerosol bands and subtracted from the original TOA <span class="hlt">reflectance</span> values assuming linear relationship for the optically thin case (ρ1.38 < 0.05). Since the 1.38 μm band is located in the strong water vapor absorption band, thus representing cirrus signal only, the slope between the 1.38 μm <span class="hlt">reflectance</span> values and minimum <span class="hlt">reflectance</span> values at each aerosol band for the corresponding values at 1.38 μm can be used to convert the 1.38 μm <span class="hlt">reflectance</span> to the cirrus <span class="hlt">reflectance</span> at each wavelength. Then, the cirrus-signal-corrected AOD can be retrieved by using the corrected <span class="hlt">reflectance</span> data as input data into the aerosol retrieval algorithms. The retrieval results show that the AOD</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://ntrs.nasa.gov/search.jsp?R=20040171173&hterms=Methodology+Research&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D70%26Ntt%3DMethodology%2Bof%2BResearch%2B','NASA-TRS'); return false;" href="http://ntrs.nasa.gov/search.jsp?R=20040171173&hterms=Methodology+Research&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D70%26Ntt%3DMethodology%2Bof%2BResearch%2B"><span id="translatedtitle"><span class="hlt">MODIS</span> In-flight Calibration Methodologies</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Xiong, X.; Barnes, W.</p> <p>2004-01-01</p> <p><span class="hlt">MODIS</span> is a key instrument for the NASA's Earth Observing System (EOS) currently operating on the Terra spacecraft launched in December 1999 and <span class="hlt">Aqua</span> spacecraft launched in May 2002. It is a cross-track scanning radiometer, making measurements over a wide field of view in 36 spectral bands with wavelengths from 0.41 to 14.5 micrometers and providing calibrated data products for science and research communities in their studies of the Earth s system of land, oceans, and atmosphere. A complete suite of on-board calibrators (OBC) have been designed for the instruments in-flight calibration and characterization, including a solar diffuser (SD) and solar diffuser stability monitor (SDSM) system for the radiometric calibration of the 20 <span class="hlt">reflective</span> solar bands (RSB), a blackbody (BB) for the radiometric calibration of the 16 thermal emissive bands (TEB), and a spectro-radiometric calibration assembly (SRCA) for the spatial (all bands) and spectral (RSB only) characterization. This paper discusses <span class="hlt">MODIS</span> in-flight Cali bration methodologies of using its on-board calibrators. Challenging issues and examples of tracking and correcting instrument on-orbit response changes are presented, including SD degradation (20% at 412nm, 12% at 466nm, and 7% at 530nm over four and a half years) and response versus scan angle changes (10%, 4%, and 1% differences between beginning of the scan and end of the scan at 412nm, 466nm, and 530nm) in the VIS spectral region. Current instrument performance and lessons learned are also provided.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2013AMT.....6.2989L','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2013AMT.....6.2989L"><span id="translatedtitle">The Collection 6 <span class="hlt">MODIS</span> aerosol products over land and ocean</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Levy, R. C.; Mattoo, S.; Munchak, L. A.; Remer, L. A.; Sayer, A. M.; Patadia, F.; Hsu, N. C.</p> <p>2013-11-01</p> <p>The twin Moderate resolution Imaging Spectroradiometer (<span class="hlt">MODIS</span>) sensors have been flying on Terra since 2000 and <span class="hlt">Aqua</span> since 2002, creating an extensive data set of global Earth observations. Here, we introduce the Collection 6 (C6) algorithm to retrieve aerosol optical depth (AOD) and aerosol size parameters from <span class="hlt">MODIS</span>-observed spectral <span class="hlt">reflectance</span>. While not a major overhaul from the previous Collection 5 (C5) version, there are enough changes that there are significant impacts to the products and their interpretation. The C6 aerosol data set will be created from three separate retrieval algorithms that operate over different surface types. These are the two "Dark Target" (DT) algorithms for retrieving (1) over ocean (dark in visible and longer wavelengths) and (2) over vegetated/dark-soiled land (dark in the visible), plus the "Deep Blue" (DB) algorithm developed originally for retrieving (3) over desert/arid land (bright in the visible). Here, we focus on DT-ocean and DT-land (#1 and #2). We have updated assumptions for central wavelengths, Rayleigh optical depths and gas (H2O, O3, CO2, etc.) absorption corrections, while relaxing the solar zenith angle limit (up to ≤ 84°) to increase poleward coverage. For DT-land, we have updated the cloud mask to allow heavy smoke retrievals, fine-tuned the assignments for aerosol type as function of season/location, corrected bugs in the Quality Assurance (QA) logic, and added diagnostic parameters such topographic altitude. For DT-ocean, improvements include a revised cloud mask for thin-cirrus detection, inclusion of wind speed dependence on the surface <span class="hlt">reflectance</span>, updates to logic of QA Confidence flag (QAC) assignment, and additions of important diagnostic information. At the same time, we quantified how "upstream" changes to instrument calibration, land/sea masking and cloud masking will also impact the statistics of global AOD, and affect Terra and <span class="hlt">Aqua</span> differently. For <span class="hlt">Aqua</span>, all changes will result in reduced</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2009AGUFMIN21A1040C','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2009AGUFMIN21A1040C"><span id="translatedtitle">Ground-based vicarious radiometric calibration of Terra <span class="hlt">MODIS</span></span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Czapla-Myers, J.; Thome, K.</p> <p>2009-12-01</p> <p>Accurate radiometric calibration is required by Earth-observing systems to ensure that the derived data products are of the highest quality. Preflight calibration is used as a baseline to understand the system before it is launched on orbit, while post-launch calibration is used to understand changes that may have occurred due to the nature of launching an instrument into space. On-orbit radiometric calibration ensures that changes in the system, including any onboard calibration sources, can be monitored. The Remote Sensing Group at the University of Arizona has been directly involved in the ground-based vicarious calibration of both Terra and <span class="hlt">Aqua</span> <span class="hlt">MODIS</span> since their respective launches in 1999 and 2002. RSG personnel are present at a test site during sensor overpass, and surface <span class="hlt">reflectance</span> and atmospheric attenuation measurements are used as inputs to a radiative transfer code to determine the top-of-atmosphere radiance for the sensor under test. In the case of Terra <span class="hlt">MODIS</span>, a 1-km2 site at Railroad Valley, Nevada, is used as a test site. This work presents results obtained using the <span class="hlt">reflectance</span>-based approach at RSG’s Railroad Valley test site. Results from 10 years of in situ data collection at Railroad Valley show a percent difference in the seven land spectral channels between RSG and Terra <span class="hlt">MODIS</span> ranging from 1.6 % in channel 6 (1632 nm), to 5.1% in channel 4 (553 nm). The average percent difference for Terra MODIS’s seven land channels and RSG is 3.5%. The uncertainty is within the 3-5% predicted for ground-based vicarious calibration.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2009SPIE.7452E..17W','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2009SPIE.7452E..17W"><span id="translatedtitle">Characterization of <span class="hlt">MODIS</span> SD screen vignetting function using observations from spacecraft yaw maneuvers</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Wang, Zhipeng; Xiong, Xiaoxiong</p> <p>2009-08-01</p> <p>The <span class="hlt">MODIS</span> <span class="hlt">reflective</span> solar bands (RSB) include both the low-gain and high-gain spectral bands depending on their specific applications. <span class="hlt">MODIS</span> RSBs are calibrated on-orbit by an on-board solar diffuser. In order to avoid detector response saturation when calibrating the high-gain bands, an optional attenuation screen, made of a metal plate with pinhole arrays, is placed in front of the SD panel. Since no pre-launch system-level characterization was made for the SD screen (SDS) vignetting function (VF), a series of spacecraft (Terra and <span class="hlt">Aqua</span>) yaw maneuvers were carried out to perform on-orbit characterization of the VF. Assuming that the low-gain bands and the high-gain bands have the same VF, the current VF was derived from yaw observations using the <span class="hlt">MODIS</span> low-gain bands through taking the ratio of their SD responses with and without the SDS in place. In this study, we attempt to characterize the SDS VF directly using detector responses of individual high-gain bands with the SDS in place only. The corresponding SD responses without the SDS, not available from measurements due to saturation, are calculated using detector gains, the SD bi-directional <span class="hlt">reflectance</span> factor (BRF), and the view geometry that matches the yaw observations with the SDS in place. Results and discussions are focused on the band dependent and detector dependent features of the SDS VF, and their potential impact on the RSB calibration.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://ntrs.nasa.gov/search.jsp?R=20070034809&hterms=html&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D60%26Ntt%3Dhtml','NASA-TRS'); return false;" href="http://ntrs.nasa.gov/search.jsp?R=20070034809&hterms=html&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D60%26Ntt%3Dhtml"><span id="translatedtitle">Generating a Long-Term Land Data Record from the AVHRR and <span class="hlt">MODIS</span> Instruments</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Pedelty, Jeffrey; Devadiga, Sadashiva; Masuoka, Edward; Brown, Molly; Pinzon, Jorge; Tucker, Compton; Vermote, Eric; Prince, Stephen; Nagol, Jyotheshwar; Justice, Christopher; Roy, David; Ju, Junchang; Schaaf, Crystal; Liu, Jicheng; Privette, Jeffrey; Pincheiro, Ana</p> <p>2007-01-01</p> <p>The goal of NASA's Land Long Term Iiata Record (LTDR) project is to produce a consistent long term data set from the AVHRR and <span class="hlt">MODIS</span> instruments for land climate studies. The project will create daily surface <span class="hlt">reflectance</span> and normalized difference vegetation index (NDVI) products at a resolution of 0.05 deg., which is identical to the Climate Modeling Grid (CMG) used for <span class="hlt">MODIS</span> products from EOS Terra and <span class="hlt">Aqua</span>. Higher order products such as burned area, land surface temperature, albedo, bidirectional <span class="hlt">reflectance</span> distribution function (BRDF) correction, leaf area index (LAI), and fraction of photosyntheticalIy active radiation absorbed by vegetation (fPAR), will be created. The LTDR project will reprocess Global Area Coverage (GAC) data from AVHRR sensors onboard NOAA satellites by applying the preprocessing improvements identified in the AVHRR Pathfinder Il project and atmospheric and BRDF corrections used in <span class="hlt">MODIS</span> processing. The preprocessing improvements include radiometric in-flight vicarious calibration for the visible and near infrared channels and inverse navigation to relate an Earth location to each sensor instantaneous field of view (IFOV). Atmospheric corrections for Rayleigh scattering, ozone, and water vapor are undertaken, with aerosol correction being implemented. The LTDR also produces a surface <span class="hlt">reflectance</span> product for channel 3 (3.75 micrometers). Quality assessment (QA) is an integral part of the LTDR production system, which is monitoring temporal trands in the AVHRR products using time-series approaches developed for <span class="hlt">MODIS</span> land product quality assessment. The land surface <span class="hlt">reflectance</span> products have been evaluated at AERONET sites. The AVHRR data record from LTDR is also being compared to products from the PAL (Pathfinder AVHRR Land) and GIMMS (Global Inventory Modeling and Mapping Studies) systems to assess the relative merits of this reprocessing vis-a-vis these existing data products. The LTDR products and associated information can be found at</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://ntrs.nasa.gov/search.jsp?R=20110007300&hterms=ecosystem+marine&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D80%26Ntt%3Decosystem%2Bmarine','NASA-TRS'); return false;" href="http://ntrs.nasa.gov/search.jsp?R=20110007300&hterms=ecosystem+marine&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D80%26Ntt%3Decosystem%2Bmarine"><span id="translatedtitle">Remote Sensing of Radiative and Microphysical Properties of Clouds During TC (sup 4): Results from MAS, MASTER, <span class="hlt">MODIS</span>, and MISR</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>King, Michael D.; Platnick, Steven; Wind, Galina; Arnold, G. Thomas; Dominguez, Roseanne T.</p> <p>2010-01-01</p> <p>The Moderate Resolution Imaging Spectroradiometer (<span class="hlt">MODIS</span>) Airborne Simulator (MAS) and <span class="hlt">MODIS</span>/Advanced Spaceborne Thermal Emission and <span class="hlt">Reflection</span> Radiometer (ASTER) Airborne Simulator (MASTER) were used to obtain measurements of the bidirectional <span class="hlt">reflectance</span> and brightness temperature of clouds at 50 discrete wavelengths between 0.47 and 14.2 microns (12.9 microns for MASTER). These observations were obtained from the NASA ER-2 aircraft as part of the Tropical Composition, Cloud and Climate Coupling (TC4) experiment conducted over Central America and surrounding Pacific and Atlantic Oceans between 17 July and 8 August 2007. Multispectral images in eleven distinct bands were used to derive a confidence in clear sky (or alternatively the probability Of cloud) over land and ocean ecosystems. Based on the results of individual tests run as part of the cloud mask, an algorithm was developed to estimate the phase of the clouds (liquid water, ice, or undetermined phase). The cloud optical thickness and effective radius were derived for both liquid water and ice clouds that were detected during each flight, using a nearly identical algorithm to that implemented operationally to process <span class="hlt">MODIS</span> Cloud data from the <span class="hlt">Aqua</span> and Terra satellites (Collection 5). This analysis shows that the cloud mask developed for operational use on <span class="hlt">MODIS</span>, and tested using MAS and MASTER data in TC(sup 4), is quite capable of distinguishing both liquid water and ice clouds during daytime conditions over both land and ocean. The cloud optical thickness and effective radius retrievals use five distinct bands of the MAS (or MASTER), and these results were compared with nearly simultaneous retrievals of marine liquid water clouds from <span class="hlt">MODIS</span> on the Terra spacecraft. Finally, this <span class="hlt">MODIS</span>-based algorithm was adapted to Multiangle Imaging SpectroRadiometer (MISR) data to infer the cloud optical thickness Of liquid water clouds from MISR. Results of this analysis are compared and contrasted.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/20130014411','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20130014411"><span id="translatedtitle">A Full Snow Season in Yellowstone: A Database of Restored <span class="hlt">Aqua</span> Band 6</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Gladkova, Irina; Grossberg, Michael; Bonev, George; Romanov, Peter; Riggs, George; Hall, Dorothy</p> <p>2013-01-01</p> <p>The algorithms for estimating snow extent for the Moderate Resolution Imaging Spectroradiometer (<span class="hlt">MODIS</span>) optimally use the 1.6- m channel which is unavailable for <span class="hlt">MODIS</span> on <span class="hlt">Aqua</span> due to detector damage. As a test bed to demonstrate that <span class="hlt">Aqua</span> band 6 can be restored, we chose the area surrounding Yellowstone and Grand Teton national parks. In such rugged and difficult-to-access terrain, satellite images are particularly important for providing an estimation of snow-cover extent. For the full 2010-2011 snow season covering the Yellowstone region, we have used quantitative image restoration to create a database of restored <span class="hlt">Aqua</span> band 6. The database includes restored radiances, normalized vegetation index, normalized snow index, thermal data, and band-6-based snow-map products. The restored <span class="hlt">Aqua</span>-band-6 data have also been regridded and combined with Terra data to produce a snow-cover map that utilizes both Terra and <span class="hlt">Aqua</span> snow maps. Using this database, we show that the restored <span class="hlt">Aqua</span>-band-6-based snow-cover extent has a comparable performance with respect to ground stations to the one based on Terra. The result of a restored band 6 from <span class="hlt">Aqua</span> is that we have an additional band-6 image of the Yellowstone region each day. This image can be used to mitigate cloud occlusion, using the same algorithms used for band 6 on Terra. We show an application of this database of restored band-6 images to illustrate the value of creating a cloud gap filling using the National Aeronautics and Space Administration s operational cloud masks and data from both <span class="hlt">Aqua</span> and Terra.</p> </li> </ol> <div class="pull-right"> <ul class="pagination"> <li><a href="#" onclick='return showDiv("page_1");'>«</a></li> <li><a href="#" onclick='return showDiv("page_9");'>9</a></li> <li><a href="#" onclick='return showDiv("page_10");'>10</a></li> <li class="active"><span>11</span></li> <li><a href="#" onclick='return showDiv("page_12");'>12</a></li> <li><a href="#" onclick='return showDiv("page_13");'>13</a></li> <li><a href="#" onclick='return showDiv("page_25");'>»</a></li> </ul> </div> </div><!-- col-sm-12 --> </div><!-- row --> </div><!-- page_11 --> <div id="page_12" class="hiddenDiv"> <div class="row"> <div class="col-sm-12"> <div class="pull-right"> <ul class="pagination"> <li><a href="#" onclick='return showDiv("page_1");'>«</a></li> <li><a href="#" onclick='return showDiv("page_10");'>10</a></li> <li><a href="#" onclick='return showDiv("page_11");'>11</a></li> <li class="active"><span>12</span></li> <li><a href="#" onclick='return showDiv("page_13");'>13</a></li> <li><a href="#" onclick='return showDiv("page_14");'>14</a></li> <li><a href="#" onclick='return showDiv("page_25");'>»</a></li> </ul> </div> </div> </div> <div class="row"> <div class="col-sm-12"> <ol class="result-class" start="221"> <li> <p><a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/20110007875','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20110007875"><span id="translatedtitle">Validation of the <span class="hlt">MODIS</span> "Clear-Sky" Surface Temperature of the Greenland Ice Sheet</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Hall, Dorothy K.; Koenig, L. S.; DiGirolamo, N. E.; Comiso, J.; Shuman, C. A.</p> <p>2011-01-01</p> <p>Surface temperatures on the Greenland Ice Sheet have been studied on the ground, using automatic weather station (AWS) data from the Greenland-Climate Network (GC-Net), and from analysis of satellite sensor data. Using Advanced Very High Frequency Radiometer (AVHRR) weekly surface temperature maps, warming of the surface of the Greenland Ice Sheet has been documented from 1981 to present. We extend and refine this record using higher-resolution Moderate-Resolution Imaging Spectroradiometer (<span class="hlt">MODIS</span>) data from March 2000 to the present. To permit changes to be observed over time, we are developing a well-characterized monthly climate-data record (CDR) of the "clear-sky" surface temperature of the Greenland Ice Sheet using data from both the Terra and <span class="hlt">Aqua</span> satellites. We use the <span class="hlt">MODIS</span> ice-surface temperature (IST) algorithm. Validation of the CDR consists of several facets: 1) comparisons between the Terra and <span class="hlt">Aqua</span> IST maps; 2) comparisons between ISTs and in-situ measurements; 3) comparisons between ISTs and AWS data; and 4) comparisons of ISTs with surface temperatures derived from other satellite instruments such as the Thermal Emission and <span class="hlt">Reflection</span> Radiometer. In this work, we focus on 1) and 2) above. Surface temperatures on the Greenland Ice Sheet have been studied on the ground, using automatic weather station (AWS) data from the Greenland-Climate Network (GC-Net), and from analysis of satellite sensor data. Using Advanced Very High Frequency Radiometer (AVHRR) weekly surface temperature maps, warming of the surface of the Greenland Ice Sheet has been documented from 1981 to present. We extend and refine this record using higher-resolution Moderate-Resolution Imaging Spectroradiometer (<span class="hlt">MODIS</span>) data from March 2000 to the present. To permit changes to be observed over time, we are developing a well-characterized monthly climate-data record (CDR) of the "clear-sky" surface temperature of the Greenland Ice Sheet using data from both the Terra and <span class="hlt">Aqua</span> satellites</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/cgi-bin/nph-data_query?bibcode=2016PhDT........43M&link_type=ABSTRACT','NASAADS'); return false;" href="http://adsabs.harvard.edu/cgi-bin/nph-data_query?bibcode=2016PhDT........43M&link_type=ABSTRACT"><span id="translatedtitle">Estimation of suspended particulate matter concentration in the Mississippi Sound using <span class="hlt">MODIS</span> imagery</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Merritt, Danielle</p> <p></p> <p>The discharge of sediment-laden rivers into the Mississippi Sound increases the turbidity of coastal waters. The concentration of suspended particulates is an important parameter in the analysis of coastal water quality factors. The spatiotemporal resolution associated with satellite sensors makes remote sensing an ideal tool to monitor suspended particulate concentrations. Accordingly, the presented research evaluated the validity of published algorithms that relate remote sensing <span class="hlt">reflectance</span> (Rrs) with suspended particulate matter for the Mississippi Sound. Additionally, regression analysis was used to correlate in situ SPM concentrations with coincident observations of visible and nearinfrared band <span class="hlt">reflectance</span> collected by the <span class="hlt">MODIS</span> <span class="hlt">Aqua</span> sensor in order to develop a predictive model for SPM. The most robust algorithm yielded an RMSE of 15.53% (n = 86) in the determination of SPM concentrations. The application of this algorithm allows for the rapid assessment of water quality issues related to elevated SPM concentrations in the Mississippi Sound.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://pubs.er.usgs.gov/publication/70032007','USGSPUBS'); return false;" href="http://pubs.er.usgs.gov/publication/70032007"><span id="translatedtitle">Detection rates of the <span class="hlt">MODIS</span> active fire product in the United States</span></a></p> <p><a target="_blank" href="http://pubs.er.usgs.gov/pubs/index.jsp?view=adv">USGS Publications Warehouse</a></p> <p>Hawbaker, T.J.; Radeloff, V.C.; Syphard, A.D.; Zhu, Z.; Stewart, S.I.</p> <p>2008-01-01</p> <p><span class="hlt">MODIS</span> active fire data offer new information about global fire patterns. However, uncertainties in detection rates can render satellite-derived fire statistics difficult to interpret. We evaluated the <span class="hlt">MODIS</span> 1??km daily active fire product to quantify detection rates for both Terra and <span class="hlt">Aqua</span> <span class="hlt">MODIS</span> sensors, examined how cloud cover and fire size affected detection rates, and estimated how detection rates varied across the United States. <span class="hlt">MODIS</span> active fire detections were compared to 361 reference fires (??? 18??ha) that had been delineated using pre- and post-fire Landsat imagery. Reference fires were considered detected if at least one <span class="hlt">MODIS</span> active fire pixel occurred within 1??km of the edge of the fire. When active fire data from both <span class="hlt">Aqua</span> and Terra were combined, 82% of all reference fires were found, but detection rates were less for <span class="hlt">Aqua</span> and Terra individually (73% and 66% respectively). Fires not detected generally had more cloudy days, but not when the <span class="hlt">Aqua</span> data were considered exclusively. <span class="hlt">MODIS</span> detection rates decreased with fire size, and the size at which 50% of all fires were detected was 105??ha when combining <span class="hlt">Aqua</span> and Terra (195??ha for <span class="hlt">Aqua</span> and 334??ha for Terra alone). Across the United States, detection rates were greatest in the West, lower in the Great Plains, and lowest in the East. The <span class="hlt">MODIS</span> active fire product captures large fires in the U.S. well, but may under-represent fires in areas with frequent cloud cover or rapidly burning, small, and low-intensity fires. We recommend that users of the <span class="hlt">MODIS</span> active fire data perform individual validations to ensure that all relevant fires are included. ?? 2008 Elsevier Inc. All rights reserved.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2010ACP....1010949Z','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2010ACP....1010949Z"><span id="translatedtitle">A decadal regional and global trend analysis of the aerosol optical depth using a data-assimilation grade over-water <span class="hlt">MODIS</span> and Level 2 MISR aerosol products</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Zhang, J.; Reid, J. S.</p> <p>2010-11-01</p> <p>Using the ten-year (2000-2009) Data-Assimilation (DA) quality Terra <span class="hlt">MODIS</span> and MISR aerosol products, as well as 7 years of <span class="hlt">Aqua</span> <span class="hlt">MODIS</span>, we studied both regional and global aerosol trends over oceans. This included both operational and data assimilation grade versions of the products. After correcting for what appears to be aerosol signal drift from the radiometric calibration of both <span class="hlt">MODIS</span> instruments, we found <span class="hlt">MODIS</span> and MISR agreed on a statistically negligible global trend of ±0.003/per decade. Our study also suggests that AODs over the Indian Bay of Bengal, east coast of Asia, and Arabian Sea show increasing trends of 0.07, 0.06, and 0.06 per decade for <span class="hlt">MODIS</span>, respectively. These regional trends are considered as significant with a confidence level above 95%. Similar increasing trends were found from MISR, but with less relative magnitude. These trends <span class="hlt">reflect</span> respective increases in the optical intensity of aerosol events in each region: anthropogenic aerosols over the east coast of China and Indian Bay of Bengal; and a stronger influence from dust events over the Arabian Sea. Negative AOD trends, low in confidence levels, are found off Central America, the east coast of North America, and the west coast of Africa, which indicate that longer periods of observation are necessary to be conclusive.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2010ACPD...1018879Z','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2010ACPD...1018879Z"><span id="translatedtitle">A decadal regional and global trend analysis of the aerosol optical depth using a data-assimilation grade over-water <span class="hlt">MODIS</span> and Level 2 MISR aerosol products</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Zhang, J.; Reid, J. S.</p> <p>2010-08-01</p> <p>Using the ten-year (2000-2009) DA quality Terra <span class="hlt">MODIS</span> and MISR aerosol products, as well as 7 years of <span class="hlt">Aqua</span> <span class="hlt">MODIS</span>, we studied both regional and global aerosol trends over oceans. This included both natural and data assimilation grade versions of the products. Contrary to some of the previous studies that showed a decreasing trend in aerosol optical depth (AOD) over global oceans, after correcting for what appears to be aerosol signal drift from the radiometric calibration of both <span class="hlt">MODIS</span> instruments, we found <span class="hlt">MODIS</span> and MISR agreed on a statistically negligible global trend of 0.0003/per year. Our study also suggests that AODs over the Indian Bay of Bengal, east coast of Asia, and Arabian Sea show statistically significant increasing trends of 0.07, 0.06, and 0.06 per ten years for <span class="hlt">MODIS</span>, respectively. Similar increasing trends were found from MISR, but with less relative magnitude. These trends <span class="hlt">reflect</span> respective increases in the optical intensity of aerosol events in each region: anthropogenic aerosols over the east coast of China and Indian Bay of Bengal; and a stronger influence from dust events over the Arabian Sea. Negative AOD trends are found off Central America, the east coast of North America, and the west coast of Africa. However, confidence levels are low in these regions, which indicate that longer periods of observation are necessary to be conclusive.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2015JGRD..120.4132C','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2015JGRD..120.4132C"><span id="translatedtitle">Frequency and causes of failed <span class="hlt">MODIS</span> cloud property retrievals for liquid phase clouds over global oceans</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Cho, Hyoun-Myoung; Zhang, Zhibo; Meyer, Kerry; Lebsock, Matthew; Platnick, Steven; Ackerman, Andrew S.; Di Girolamo, Larry; -Labonnote, Laurent C.; Cornet, Céline; Riedi, Jerome; Holz, Robert E.</p> <p>2015-05-01</p> <p>Moderate Resolution Imaging Spectroradiometer (<span class="hlt">MODIS</span>) retrieves cloud droplet effective radius (r_e) and optical thickness (τ) by projecting observed cloud <span class="hlt">reflectances</span> onto a precomputed look-up table (LUT). When observations fall outside of the LUT, the retrieval is considered "failed" because no combination of τ and r_e within the LUT can explain the observed cloud <span class="hlt">reflectances</span>. In this study, the frequency and potential causes of failed <span class="hlt">MODIS</span> retrievals for marine liquid phase (MLP) clouds are analyzed based on 1 year of <span class="hlt">Aqua</span> <span class="hlt">MODIS</span> Collection 6 products and collocated CALIOP and CloudSat observations. The retrieval based on the 0.86 μm and 2.1 μm <span class="hlt">MODIS</span> channel combination has an overall failure rate of about 16% (10% for the 0.86 μm and 3.7 μm combination). The failure rates are lower over stratocumulus regimes and higher over the broken trade wind cumulus regimes. The leading type of failure is the "r_e too large" failure accounting for 60%-85% of all failed retrievals. The rest is mostly due to the "r_e too small" or τ retrieval failures. Enhanced retrieval failure rates are found when MLP cloud pixels are partially cloudy or have high subpixel inhomogeneity, are located at special Sun-satellite viewing geometries such as sunglint, large viewing or solar zenith angles, or cloudbow and glory angles, or are subject to cloud masking, cloud overlapping, and/or cloud phase retrieval issues. The majority (more than 84%) of failed retrievals along the CALIPSO track can be attributed to at least one or more of these potential reasons. The collocated CloudSat radar <span class="hlt">reflectivity</span> observations reveal that the remaining failed retrievals are often precipitating. It remains an open question whether the extremely large r_e values observed in these clouds are the consequence of true cloud microphysics or still due to artifacts not included in this study.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://ntrs.nasa.gov/search.jsp?R=20030108344&hterms=Water+Africa&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D40%26Ntt%3DWater%2BAfrica','NASA-TRS'); return false;" href="http://ntrs.nasa.gov/search.jsp?R=20030108344&hterms=Water+Africa&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D40%26Ntt%3DWater%2BAfrica"><span id="translatedtitle">A Technique for Remote Sensing of Suspended Sediments and Shallow Coastal Waters Using <span class="hlt">MODIS</span> Visible and Near-IR Channels</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Li, Rong-Rong; Kaufman, Yoram J.</p> <p>2002-01-01</p> <p>We have developed an algorithm to detect suspended sediments and shallow coastal waters using imaging data acquired with the Moderate Resolution Imaging SpectroRadiometer (<span class="hlt">MODIS</span>). The <span class="hlt">MODIS</span> instruments on board the NASA Terra and <span class="hlt">Aqua</span> Spacecrafts are equipped with one set of narrow channels located in a wide 0.4 - 2.5 micron spectral range. These channels were designed primarily for remote sensing of the land surface and atmosphere. We have found that the set of land and cloud channels are also quite useful for remote sensing of the bright coastal waters. We have developed an empirical algorithm, which uses the narrow <span class="hlt">MODIS</span> channels in this wide spectral range, for identifying areas with suspended sediments in turbid waters and shallow waters with bottom <span class="hlt">reflections</span>. In our algorithm, we take advantage of the strong water absorption at wavelengths longer than 1 micron that does not allow illumination of sediments in the water or a shallow ocean floor. <span class="hlt">MODIS</span> data acquired over the east coast of China, west coast of Africa, Arabian Sea, Mississippi Delta, and west coast of Florida are used in this study.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/20150001339','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20150001339"><span id="translatedtitle">An Approach for the Long-Term 30-m Land Surface Snow-Free Albedo Retrieval from Historic Landsat Surface <span class="hlt">Reflectance</span> and <span class="hlt">MODIS</span>-based A Priori Anisotropy Knowledge</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Shuai, Yanmin; Masek, Jeffrey G.; Gao, Feng; Schaaf, Crystal B.; He, Tao</p> <p>2014-01-01</p> <p>Land surface albedo has been recognized by the Global Terrestrial Observing System (GTOS) as an essential climate variable crucial for accurate modeling and monitoring of the Earth's radiative budget. While global climate studies can leverage albedo datasets from <span class="hlt">MODIS</span>, VIIRS, and other coarse-resolution sensors, many applications in heterogeneous environments can benefit from higher-resolution albedo products derived from Landsat. We previously developed a "<span class="hlt">MODIS</span>-concurrent" approach for the 30-meter albedo estimation which relied on combining post-2000 Landsat data with <span class="hlt">MODIS</span> Bidirectional <span class="hlt">Reflectance</span> Distribution Function (BRDF) information. Here we present a "pre-<span class="hlt">MODIS</span> era" approach to extend 30-m surface albedo generation in time back to the 1980s, through an a priori anisotropy Look-Up Table (LUT) built up from the high quality MCD43A BRDF estimates over representative homogenous regions. Each entry in the LUT <span class="hlt">reflects</span> a unique combination of land cover, seasonality, terrain information, disturbance age and type, and Landsat optical spectral bands. An initial conceptual LUT was created for the Pacific Northwest (PNW) of the United States and provides BRDF shapes estimated from <span class="hlt">MODIS</span> observations for undisturbed and disturbed surface types (including recovery trajectories of burned areas and non-fire disturbances). By accepting the assumption of a generally invariant BRDF shape for similar land surface structures as a priori information, spectral white-sky and black-sky albedos are derived through albedo-to-nadir <span class="hlt">reflectance</span> ratios as a bridge between the Landsat and <span class="hlt">MODIS</span> scale. A further narrow-to-broadband conversion based on radiative transfer simulations is adopted to produce broadband albedos at visible, near infrared, and shortwave regimes.We evaluate the accuracy of resultant Landsat albedo using available field measurements at forested AmeriFlux stations in the PNW region, and examine the consistency of the surface albedo generated by this approach</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://ntrs.nasa.gov/search.jsp?R=20050156603&hterms=effect+climatic+changes+db&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D30%26Ntt%3Deffect%2Bclimatic%2Bchanges%2Bdb','NASA-TRS'); return false;" href="http://ntrs.nasa.gov/search.jsp?R=20050156603&hterms=effect+climatic+changes+db&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D30%26Ntt%3Deffect%2Bclimatic%2Bchanges%2Bdb"><span id="translatedtitle"><span class="hlt">MODIS</span> Direct Broadcast and Remote Sensing Applications</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Tsay, Si-Chee</p> <p>2004-01-01</p> <p>The Moderate Resolution Imaging Spectroradiometer (<span class="hlt">MODIS</span>) was developed by NASA and launched onboard both Terra spacecraft on December 18, 1999 and <span class="hlt">Aqua</span> spacecraft on May 4, 2002. <span class="hlt">MODIS</span> 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 between 0.415 and 14.235 microns with spatial resolutions of 250 m (2 bands), 500 m (5 bands) and 1000 m (29 bands). Equipped with direct broadcast capability, the <span class="hlt">MODIS</span> measurements can be received worldwide real time. There are 82 ingest sites (over 900 users, listed on the Direct Readout Portal) around the world for Terra/<span class="hlt">Aqua-MODIS</span> Direct Broadcast DB) downlink. This represents 27 (6 from EOS science team members) science research organizations for DB land, ocean and atmospheric processing, and 53 companies that base their application algorithms and value added products on DB data. In this paper we will describe the various methods being used for the remote sensing of cloud properties using <span class="hlt">MODIS</span> data, focusing primarily on the <span class="hlt">MODIS</span> cloud mask used to distinguish clouds, clear sky, heavy aerosol, and shadows on the ground, and on the remote sensing of aerosol/cloud optical properties, especially optical thickness and effective particle size. Additional properties of clouds derived from multispectral thermal infrared measurements, especially cloud top pressure and emissivity, will also be described. Preliminary results will be presented and discussed their implications in regional-to-global climatic effects.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://ntrs.nasa.gov/search.jsp?R=20000105141&hterms=bottleneck&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D90%26Ntt%3Dbottleneck','NASA-TRS'); return false;" href="http://ntrs.nasa.gov/search.jsp?R=20000105141&hterms=bottleneck&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D90%26Ntt%3Dbottleneck"><span id="translatedtitle">Production and Distribution of Global Products From <span class="hlt">MODIS</span></span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Masuoka, Edward; Smith, David E. (Technical Monitor)</p> <p>2000-01-01</p> <p>The Moderate Resolution Imaging Spectroradiometer was launched on the EOS Terra spacecraft in December 1999 and will also fly on EOS <span class="hlt">Aqua</span> in December 2000. With 36 spectral bands from the visible through thermal infrared and spatial resolution of 250m to 1 kilometer, each <span class="hlt">MODIS</span> instrument will image the entire Earth surface in 2 days. This paper traces the flow of <span class="hlt">MODIS</span> data products from the receipt of Level 0 data at the EDOS facility, through the production and quality assurance process to the Distributed Active Archive Centers (DAACs), which ship products to the user community. It describes where to obtain products and plans for reprocessing <span class="hlt">MODIS</span> products. As most components of the ground system are severely limited in their capacity to distribute <span class="hlt">MODIS</span> products, it also describes the key characteristics of <span class="hlt">MODIS</span> products and their metadata that allow a user to optimize their selection of products given anticipate bottlenecks in distribution.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/20040171375','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20040171375"><span id="translatedtitle">Cloud Inhomogeneity from <span class="hlt">MODIS</span></span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Oreopoulos, Lazaros; Cahalan, Robert F.</p> <p>2004-01-01</p> <p>Two full months (July 2003 and January 2004) of <span class="hlt">MODIS</span> Atmosphere Level-3 data from the Terra and <span class="hlt">Aqua</span> satellites are analyzed in order to characterize the horizontal variability of cloud optical thickness and water path at global scales. Various options to derive cloud variability parameters are discussed. The climatology of cloud inhomogeneity is built by first calculating daily parameter values at spatial scales of l degree x 1 degree, and then at zonal and global scales, followed by averaging over monthly time scales. Geographical, diurnal, and seasonal changes of inhomogeneity parameters are examined separately for the two cloud phases, and separately over land and ocean. We find that cloud inhomogeneity is weaker in summer than in winter, weaker over land than ocean for liquid clouds, weaker for local morning than local afternoon, about the same for liquid and ice clouds on a global scale, but with wider probability distribution functions (PDFs) and larger latitudinal variations for ice, and relatively insensitive to whether water path or optical thickness products are used. Typical mean values at hemispheric and global scales of the inhomogeneity parameter nu (roughly the mean over the standard deviation of water path or optical thickness), range from approximately 2.5 to 3, while for the inhomogeneity parameter chi (the ratio of the logarithmic to linear mean) from approximately 0.7 to 0.8. Values of chi for zonal averages can occasionally fall below 0.6 and for individual gridpoints below 0.5. Our results demonstrate that <span class="hlt">MODIS</span> is capable of revealing significant fluctuations in cloud horizontal inhomogenity and stress the need to model their global radiative effect in future studies.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/cgi-bin/nph-data_query?bibcode=2009EGUGA..1112835C&link_type=ABSTRACT','NASAADS'); return false;" href="http://adsabs.harvard.edu/cgi-bin/nph-data_query?bibcode=2009EGUGA..1112835C&link_type=ABSTRACT"><span id="translatedtitle">Regional scale net radiation estimation by means of Landsat and TERRA/<span class="hlt">AQUA</span> imagery and GIS modeling</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Cristóbal, J.; Ninyerola, M.; Pons, X.; Llorens, P.; Poyatos, R.</p> <p>2009-04-01</p> <p>Net radiation (Rn) is one of the most important variables for the estimation of surface energy budget and is used for various applications including agricultural meteorology, climate monitoring and weather prediction. Moreover, net radiation is an essential input variable for potential as well as actual evapotranspiration modeling. Nowadays, radiometric measurements provided by Remote Sensing and GIS analysis are the technologies used to compute net radiation at regional scales in a feasible way. In this study we present a regional scale estimation of the daily Rn on clear days, (Catalonia, NE of the Iberian Peninsula), using a set of 22 Landsat images (17 Landsat-5 TM and 5 Landsat-7 ETM+) and 171 TERRA/<span class="hlt">AQUA</span> images <span class="hlt">MODIS</span> from 2000 to 2007 period. TERRA/<span class="hlt">AQUA</span> <span class="hlt">MODIS</span> images have been downloaded by means of the EOS Gateway. We have selected three different types of products which contain the remote sensing data we have used to model daily Rn: daily LST product, daily calibrated <span class="hlt">reflectances</span> product and daily atmospheric water vapour product. Landsat-5 TM images have been corrected by means of conventional techniques based on first order polynomials taking into account the effect of land surface relief using a Digital Elevation Model, obtaining an RMS less than 30 m. Radiometric correction of Landsat non-thermal bands has been done following the methodology proposed by Pons and Solé (1994), which allows to reduce the number of undesired artifacts that are due to the effects of the atmosphere or to the differential illumination which is, in turn, due to the time of the day, the location in the Earth and the relief (zones being more illuminated than others, shadows, etc). Atmospheric correction of Landsat thermal band has been carried out by means of a single-channel algorithm improvement developed by Cristóbal et al. (2009) and the land surface emissivity computed by means of the methodology proposed by Sobrino and Raissouni (2000). Rn has been estimated through the</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://ntrs.nasa.gov/search.jsp?R=20020081319&hterms=usher&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D30%26Ntt%3Dusher','NASA-TRS'); return false;" href="http://ntrs.nasa.gov/search.jsp?R=20020081319&hterms=usher&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D30%26Ntt%3Dusher"><span id="translatedtitle">Global Aerosol Remote Sensing from <span class="hlt">MODIS</span></span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Ichoku, Charles; Kaufman, Yoram J.; Remer, Lorraine A.; Chu, D. Allen; Mattoo, Shana; Tanre, Didier; Levy, Robert; Li, Rong-Rong; Martins, Jose V.; Lau, William K. M. (Technical Monitor)</p> <p>2002-01-01</p> <p>The physical characteristics, composition, abundance, spatial distribution and dynamics of global aerosols are still very poorly known, and new data from satellite sensors have long been awaited to improve current understanding and to give a boost to the effort in future climate predictions. The derivation of aerosol parameters from the MODerate resolution Imaging Spectro-radiometer (<span class="hlt">MODIS</span>) sensors aboard the Earth Observing System (EOS) Terra and <span class="hlt">Aqua</span> polar-orbiting satellites ushers in a new era in aerosol remote sensing from space. Terra and <span class="hlt">Aqua</span> were launched on December 18, 1999 and May 4, 2002 respectively, with daytime equator crossing times of approximately 10:30 am and 1:30 pm respectively. Several aerosol parameters are retrieved at 10-km spatial resolution (level 2) from <span class="hlt">MODIS</span> daytime data. The <span class="hlt">MODIS</span> aerosol algorithm employs different approaches to retrieve parameters over land and ocean surfaces, because of the inherent differences in the solar spectral radiance interaction with these surfaces. The parameters retrieved include: aerosol optical thickness (AOT) at 0.47, 0.55 and 0.66 micron wavelengths over land, and at 0.47, 0.55, 0.66, 0.87, 1.2, 1.6, and 2.1 micron over ocean; Angstrom exponent over land and ocean; and effective radii, and the proportion of AOT contributed by the small mode aerosols over ocean. To ensure the quality of these parameters, a substantial part of the Terra-<span class="hlt">MODIS</span> aerosol products were validated globally and regionally, based on cross correlation with corresponding parameters derived from ground-based measurements from AERONET (AErosol RObotic NETwork) sun photometers. Similar validation efforts are planned for the <span class="hlt">Aqua-MODIS</span> aerosol products. The <span class="hlt">MODIS</span> level 2 aerosol products are operationally aggregated to generate global daily, eight-day (weekly), and monthly products at one-degree spatial resolution (level 3). <span class="hlt">MODIS</span> aerosol data are used for the detailed study of local, regional, and global aerosol concentration</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2014AGUFM.B33C0193L','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2014AGUFM.B33C0193L"><span id="translatedtitle">Mapping Crop Cycles in China Using <span class="hlt">MODIS</span>-EVI Time Series</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Li, L.; Friedl, M. A.; Xin, Q.; Gray, J. M.; Pan, Y.; Frolking, S. E.</p> <p>2014-12-01</p> <p>As the Earth's population continues to grow and demand for food increases, multiple cropping is an effective way to increase crop production. Cropping intensity, which we define here as the number of cropping cycles per year, is an important dimension of land use that is strongly influences water demand and agricultural production. Satellite data provide global land cover maps with indispensable information regarding areal extent of global croplands and its distribution. However, the land use information such as cropping intensity is not routinely provided by global land cover products from instruments such as <span class="hlt">MODIS</span>, because mapping this information from remote sensing is challenging. We present a straight forward but efficient algorithm for automated mapping of agricultural intensity over large geographic regions using 8-day <span class="hlt">MODIS</span> EVI time series data derived from Terra and <span class="hlt">Aqua</span> <span class="hlt">MODIS</span> surface <span class="hlt">reflectance</span> products. The proposed algorithm first applies an adaptive Savitzky-Golay filter to smooth Enhanced Vegetation Index (EVI) time series derived from <span class="hlt">MODIS</span> surface <span class="hlt">reflectance</span> data, and then uses an iterative moving-window methodology to identify cropping cycles from the smoothed EVI time series. Comparison of results from our algorithm with national survey data at both the provincial and prefectural level in China show that the algorithm provides estimates of gross sown area that agree well with inventory data. Accuracy assessment using data generated by expert classification of randomly selected pixel samples indicates an overall accuracy of 91.0% for three agricultural intensity classes. More generally, the algorithm shows significant potential to automatically estimate reliable cropping intensity information in support of large-scale studies of agricultural land use and land cover dynamics.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://ntrs.nasa.gov/search.jsp?R=20040031769&hterms=cloud+bases&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D90%26Ntt%3Dcloud%2Bbases','NASA-TRS'); return false;" href="http://ntrs.nasa.gov/search.jsp?R=20040031769&hterms=cloud+bases&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D90%26Ntt%3Dcloud%2Bbases"><span id="translatedtitle">Global Multispectral Cloud Retrievals from <span class="hlt">MODIS</span></span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>King, Michael D.</p> <p>2003-01-01</p> <p>The Moderate Resolution Imaging Spectroradiometer (<span class="hlt">MODIS</span>) was developed by NASA and launched onboard the Terra spacecraft on December 18,1999 and <span class="hlt">Aqua</span> spacecraft on May 4,2002. It achieved its final orbit and began Earth observations on February 24, 2000 for Terra and June 24, 2002 for <span class="hlt">Aqua</span>. A comprehensive set of remote sensing algorithms for cloud masking and the retrieval of cloud physical and optical properties has been developed by members of the <span class="hlt">MODIS</span> atmosphere science team. The archived products from these algorithms have applications in climate change studies, climate modeling, numerical weather prediction, as well as fundamental atmospheric research. In addition to an extensive cloud mask, products include cloud-top properties (temperature, pressure, effective emissivity), cloud thermodynamic phase, cloud optical and microphysical parameters (optical thickness, effective particle radius, water path), as well as derived statistics. We will describe the various cloud properties being analyzed on a global basis from both Terra and <span class="hlt">Aqua</span>, and will show characteristics of cloud optical and microphysical properties as a function of latitude for land and ocean separately, and contrast the statistical properties of similar cloud types in various parts of the world.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/20120008715','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20120008715"><span id="translatedtitle">The Operational <span class="hlt">MODIS</span> Cloud Optical and Microphysical Property Product: Overview of the Collection 6 Algorithm and Preliminary Results</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Platnick, Steven; King, Michael D.; Wind, Galina; Amarasinghe, Nandana; Marchant, Benjamin; Arnold, G. Thomas</p> <p>2012-01-01</p> <p>Operational Moderate Resolution Imaging Spectroradiometer (<span class="hlt">MODIS</span>) retrievals of cloud optical and microphysical properties (part of the archived products MOD06 and MYD06, for <span class="hlt">MODIS</span> Terra and <span class="hlt">Aqua</span>, respectively) are currently being reprocessed along with other <span class="hlt">MODIS</span> Atmosphere Team products. The latest "Collection 6" processing stream, which is expected to begin production by summer 2012, includes updates to the previous cloud retrieval algorithm along with new capabilities. The 1 km retrievals, based on well-known solar <span class="hlt">reflectance</span> techniques, include cloud optical thickness, effective particle radius, and water path, as well as thermodynamic phase derived from a combination of solar and infrared tests. Being both global and of high spatial resolution requires an algorithm that is computationally efficient and can perform over all surface types. Collection 6 additions and enhancements include: (i) absolute effective particle radius retrievals derived separately from the 1.6 and 3.7 !-lm bands (instead of differences relative to the standard 2.1 !-lm retrieval), (ii) comprehensive look-up tables for cloud <span class="hlt">reflectance</span> and emissivity (no asymptotic theory) with a wind-speed interpolated Cox-Munk BRDF for ocean surfaces, (iii) retrievals for both liquid water and ice phases for each pixel, and a subsequent determination of the phase based, in part, on effective radius retrieval outcomes for the two phases, (iv) new ice cloud radiative models using roughened particles with a specified habit, (v) updated spatially-complete global spectral surface albedo maps derived from <span class="hlt">MODIS</span> Collection 5, (vi) enhanced pixel-level uncertainty calculations incorporating additional radiative error sources including the <span class="hlt">MODIS</span> L1 B uncertainty index for assessing band and scene-dependent radiometric uncertainties, (v) and use of a new 1 km cloud top pressure/temperature algorithm (also part of MOD06) for atmospheric corrections and low cloud non-unity emissivity temperature adjustments.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://ntrs.nasa.gov/search.jsp?R=20040171680&hterms=land+cover+change&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D90%26Ntt%3Dland%2Bcover%2Bchange','NASA-TRS'); return false;" href="http://ntrs.nasa.gov/search.jsp?R=20040171680&hterms=land+cover+change&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D90%26Ntt%3Dland%2Bcover%2Bchange"><span id="translatedtitle">Spatially Complete Surface Albedo Data Sets: Value-Added Products Derived from Terra <span class="hlt">MODIS</span> Land Products</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Moody, Eric G.; King, Michael D.; Platnick, Steven; Schaaf, Crystal B.; Gao, Feng</p> <p>2004-01-01</p> <p>Spectral land surface albedo is an important parameter for describing the radiative properties of the Earth. Accordingly it <span class="hlt">reflects</span> the consequences of natural and human interactions, such as anthropogenic, meteorological, and phenological effects, on global and local climatological trends. Consequently, albedos are integral parts in a variety of research areas, such as general circulation models (GCMs), energy balance studies, modeling of land use and land use change, and biophysical, oceanographic, and meteorological studies. Recent observations of diffuse bihemispherical (white-sky) and direct beam directional hemispherical (black-sky ) land surface albedo included in the MOD43B3 product from <span class="hlt">MODIS</span> instruments aboard NASA's Terra and <span class="hlt">Aqua</span> satellite platforms have provided researchers with unprecedented spatial, spectral, and temporal characteristics. Cloud and seasonal snow cover, however, curtail retrievals to approximately half the global land surfaces on an annual equal-angle basis, precluding MOD43B3 albedo products from direct inclusion in some research projects and production environments.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/20160005113','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20160005113"><span id="translatedtitle">EOS <span class="hlt">Aqua</span> Mission Status at Earth Science Constellation MOWG Meeting @ LASP April 13, 2016</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Guit, William J.</p> <p>2016-01-01</p> <p>This presentation <span class="hlt">reflects</span> the EOS <span class="hlt">Aqua</span> mission status, spacecraft subsystem summary, recent and planned activities, inclination adjust maneuvers, propellant usage and lifetime estimate, orbital maintenance maneuvers, conjunction assessment high interest events, ground track error, spacecraft orbital parameters trends and predictions.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2012AGUFM.A33M0335C','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2012AGUFM.A33M0335C"><span id="translatedtitle">Adapting <span class="hlt">MODIS</span> Dust Mask Algorithm to Suomi NPP VIIRS for Air Quality Applications</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Ciren, P.; Liu, H.; Kondragunta, S.; Laszlo, I.</p> <p>2012-12-01</p> <p>Despite pollution reduction control strategies enforced by the Environmental Protection Agency (EPA), large regions of the United States are often under exceptional events such as biomass burning and dust outbreaks that lead to non-attainment of particulate matter standards. This has warranted the National Weather Service (NWS) to provide smoke and dust forecast guidance to the general public. The monitoring and forecasting of dust outbreaks relies on satellite data. Currently, <span class="hlt">Aqua/MODIS</span> (MODerate resolution Imaging Spectrometer) and Terra/<span class="hlt">MODIS</span> provide measurements needed to derive dust mask and Aerosol Optical Thickness (AOT) products. The newly launched Suomi NPP VIIRS (Visible/Infrared Imaging Radiometer Suite) instrument has a Suspended Matter (SM) product that indicates the presence of dust, smoke, volcanic ash, sea salt, and unknown aerosol types in a given pixel. The algorithm to identify dust is different over land and ocean but for both, the information comes from AOT retrieval algorithm. Over land, the selection of dust aerosol model in the AOT retrieval algorithm indicates the presence of dust and over ocean a fine mode fraction smaller than 20% indicates dust. Preliminary comparisons of VIIRS SM to CALIPSO Vertical Feature Mask (VFM) aerosol type product indicate that the Probability of Detection (POD) is at ~10% and the product is not mature for operational use. As an alternate approach, NESDIS dust mask algorithm developed for NWS dust forecast verification that uses <span class="hlt">MODIS</span> deep blue, visible, and mid-IR channels using spectral differencing techniques and spatial variability tests was applied to VIIRS radiances. This algorithm relies on the spectral contrast of dust absorption at 412 and 440 nm and an increase in <span class="hlt">reflectivity</span> at 2.13 μm when dust is present in the atmosphere compared to a clear sky. To avoid detecting bright desert surface as airborne dust, the algorithm uses the <span class="hlt">reflectances</span> at 1.24 μm and 2.25 μm to flag bright pixels. The</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/20130013087','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20130013087"><span id="translatedtitle"><span class="hlt">Aqua</span> 10 Years After Launch</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Parkinson, Claire L.</p> <p>2013-01-01</p> <p>A little over ten years ago, in the early morning hours of May 4, 2002, crowds of spectators stood anxiously watching as the Delta II rocket carrying NASA's <span class="hlt">Aqua</span> spacecraft lifted off from its launch pad at Vandenberg Air Force Base in California at 2:55 a.m. The rocket quickly went through a low-lying cloud cover, after which the main portion of the rocket fell to the waters below and the rockets second stage proceeded to carry <span class="hlt">Aqua</span> south across the Pacific, onward over Antarctica, and north to Africa, where the spacecraft separated from the rocket 59.5 minutes after launch. Then, 12.5 minutes later, the solar array unfurled over Europe, and <span class="hlt">Aqua</span> was on its way in the first of what by now have become over 50,000 successful orbits of the Earth.</p> </li> </ol> <div class="pull-right"> <ul class="pagination"> <li><a href="#" onclick='return showDiv("page_1");'>«</a></li> <li><a href="#" onclick='return showDiv("page_10");'>10</a></li> <li><a href="#" onclick='return showDiv("page_11");'>11</a></li> <li class="active"><span>12</span></li> <li><a href="#" onclick='return showDiv("page_13");'>13</a></li> <li><a href="#" onclick='return showDiv("page_14");'>14</a></li> <li><a href="#" onclick='return showDiv("page_25");'>»</a></li> </ul> </div> </div><!-- col-sm-12 --> </div><!-- row --> </div><!-- page_12 --> <div id="page_13" class="hiddenDiv"> <div class="row"> <div class="col-sm-12"> <div class="pull-right"> <ul class="pagination"> <li><a href="#" onclick='return showDiv("page_1");'>«</a></li> <li><a href="#" onclick='return showDiv("page_11");'>11</a></li> <li><a href="#" onclick='return showDiv("page_12");'>12</a></li> <li class="active"><span>13</span></li> <li><a href="#" onclick='return showDiv("page_14");'>14</a></li> <li><a href="#" onclick='return showDiv("page_15");'>15</a></li> <li><a href="#" onclick='return showDiv("page_25");'>»</a></li> </ul> </div> </div> </div> <div class="row"> <div class="col-sm-12"> <ol class="result-class" start="241"> <li> <p><a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/20030032934','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20030032934"><span id="translatedtitle"><span class="hlt">MODIS</span> Data from the GES DISC DAAC: Moderate-Resolution Imaging Spectroradiometer (<span class="hlt">MODIS</span>)</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p></p> <p>2002-01-01</p> <p>The Goddard Earth Sciences (GES) Distributed Active Archive Center (DAAC) is responsible for the distribution of the Level 1 data, and the higher levels of all Ocean and Atmosphere products (Land products are distributed through the Land Processes (LP) DAAC DAAC, and the Snow and Ice products are distributed though the National Snow and Ice Data Center (NSIDC) DAAC). Ocean products include sea surface temperature (SST), concentrations of chlorophyll, pigment and coccolithophores, fluorescence, absorptions, and primary productivity. Atmosphere products include aerosols, atmospheric water vapor, clouds and cloud masks, and atmospheric profiles from 20 layers. While most <span class="hlt">MODIS</span> data products are archived in the Hierarchical Data Format-Earth Observing System (HDF-EOS 2.7) format, the ocean binned products and primary productivity products (Level 4) are in the native HDF4 format. <span class="hlt">MODIS</span> Level 1 and 2 data are of the Swath type and are packaged in files representing five minutes of Files for Level 3 and 4 are global products at daily, weekly, monthly or yearly resolutions. Apart from the ocean binned and Level 4 products, these are in Grid type, and the maps are in the Cylindrical Equidistant projection with rectangular grid. Terra viewing (scenes of approximately 2000 by 2330 km). <span class="hlt">MODIS</span> data have several levels of maturity. Most products are released with a provisional level of maturity and only announced as validated after rigorous testing by the <span class="hlt">MODIS</span> Science Teams. <span class="hlt">MODIS</span>/Terra Level 1, and all <span class="hlt">MODIS</span>/Terra 11 micron SST products are announced as validated. At the time of this publication, the <span class="hlt">MODIS</span> Data Support Team (MDST) is working with the Ocean Science Team toward announcing the validated status of the remainder of <span class="hlt">MODIS</span>/Terra Ocean products. <span class="hlt">MODIS/Aqua</span> Level 1 and cloud mask products are released with provisional maturity.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2015AMTD....8.6877L','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2015AMTD....8.6877L"><span id="translatedtitle">Towards a long-term global aerosol optical depth record: applying a consistent aerosol retrieval algorithm to <span class="hlt">MODIS</span> and VIIRS-observed <span class="hlt">reflectance</span></span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Levy, R. C.; Munchak, L. A.; Mattoo, S.; Patadia, F.; Remer, L. A.; Holz, R. E.</p> <p>2015-07-01</p> <p>To answer fundamental questions about aerosols in our changing climate, we must quantify both the current state of aerosols and how they are changing. Although NASA's Moderate resolution Imaging Spectroradiometer (<span class="hlt">MODIS</span>) sensors have provided quantitative information about global aerosol optical depth (AOD) for more than a decade, this period is still too short to create an aerosol climate data record (CDR). The Visible Infrared Imaging Radiometer Suite (VIIRS) was launched on the Suomi-NPP satellite in late 2011, with additional copies planned for future satellites. Can the <span class="hlt">MODIS</span> aerosol data record be continued with VIIRS to create a consistent CDR? When compared to ground-based AERONET data, the VIIRS Environmental Data Record (V_EDR) has similar validation statistics as the <span class="hlt">MODIS</span> Collection 6 (M_C6) product. However, the V_EDR and M_C6 are offset in regards to global AOD magnitudes, and tend to provide different maps of 0.55 μm AOD and 0.55/0.86 μm-based Ångstrom Exponent (AE). One reason is that the retrieval algorithms are different. Using the Intermediate File Format (IFF) for both <span class="hlt">MODIS</span> and VIIRS data, we have tested whether we can apply a single <span class="hlt">MODIS</span>-like (ML) dark-target algorithm on both sensors that leads to product convergence. Except for catering the radiative transfer and aerosol lookup tables to each sensor's specific wavelength bands, the ML algorithm is the same for both. We run the ML algorithm on both sensors between March 2012 and May 2014, and compare monthly mean AOD time series with each other and with M_C6 and V_EDR products. Focusing on the March-April-May (MAM) 2013 period, we compared additional statistics that include global and gridded 1° × 1° AOD and AE, histograms, sampling frequencies, and collocations with ground-based AERONET. Over land, use of the ML algorithm clearly reduces the differences between the <span class="hlt">MODIS</span> and VIIRS-based AOD. However, although global offsets are near zero, some regional biases remain, especially in</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2015AMT.....8.4083L','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2015AMT.....8.4083L"><span id="translatedtitle">Towards a long-term global aerosol optical depth record: applying a consistent aerosol retrieval algorithm to <span class="hlt">MODIS</span> and VIIRS-observed <span class="hlt">reflectance</span></span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Levy, R. C.; Munchak, L. A.; Mattoo, S.; Patadia, F.; Remer, L. A.; Holz, R. E.</p> <p>2015-10-01</p> <p>To answer fundamental questions about aerosols in our changing climate, we must quantify both the current state of aerosols and how they are changing. Although NASA's Moderate Resolution Imaging Spectroradiometer (<span class="hlt">MODIS</span>) sensors have provided quantitative information about global aerosol optical depth (AOD) for more than a decade, this period is still too short to create an aerosol climate data record (CDR). The Visible Infrared Imaging Radiometer Suite (VIIRS) was launched on the Suomi-NPP satellite in late 2011, with additional copies planned for future satellites. Can the <span class="hlt">MODIS</span> aerosol data record be continued with VIIRS to create a consistent CDR? When compared to ground-based AERONET data, the VIIRS Environmental Data Record (V_EDR) has similar validation statistics as the <span class="hlt">MODIS</span> Collection 6 (M_C6) product. However, the V_EDR and M_C6 are offset in regards to global AOD magnitudes, and tend to provide different maps of 0.55 μm AOD and 0.55/0.86 μm-based Ångström Exponent (AE). One reason is that the retrieval algorithms are different. Using the Intermediate File Format (IFF) for both <span class="hlt">MODIS</span> and VIIRS data, we have tested whether we can apply a single <span class="hlt">MODIS</span>-like (ML) dark-target algorithm on both sensors that leads to product convergence. Except for catering the radiative transfer and aerosol lookup tables to each sensor's specific wavelength bands, the ML algorithm is the same for both. We run the ML algorithm on both sensors between March 2012 and May 2014, and compare monthly mean AOD time series with each other and with M_C6 and V_EDR products. Focusing on the March-April-May (MAM) 2013 period, we compared additional statistics that include global and gridded 1° × 1° AOD and AE, histograms, sampling frequencies, and collocations with ground-based AERONET. Over land, use of the ML algorithm clearly reduces the differences between the <span class="hlt">MODIS</span> and VIIRS-based AOD. However, although global offsets are near zero, some regional biases remain, especially in</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/19990004142','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/19990004142"><span id="translatedtitle">[<span class="hlt">MODIS</span> Investigation</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Abbott, Mark R.</p> <p>1996-01-01</p> <p>The objectives of the last six months were: (1) Complete sensitivity analysis of fluorescence; line height algorithms (2) Deliver fluorescence algorithm code and test data to the University of Miami for integration; (3) Complete analysis of bio-optical data from Southern Ocean cruise; (4) Conduct laboratory experiments based on analyses of field data; (5) Analyze data from bio-optical mooring off Hawaii; (6) Develop calibration/validation plan for <span class="hlt">MODIS</span> fluorescence data; (7) Respond to the Japanese Research Announcement for GLI; and (8) Continue to review plans for EOSDIS and assist ECS contractor.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/20110023024','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20110023024"><span id="translatedtitle">Validation of <span class="hlt">MODIS</span> Aerosol Optical Depth Retrievals over a Tropical Urban Site, Pune, India</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>More, Sanjay; Kuman, P. Pradeep; Gupta, Pawan; Devara, P. C. S.; Aher, G. R.</p> <p>2011-01-01</p> <p>In the present paper, <span class="hlt">MODIS</span> (Terra and <span class="hlt">Aqua</span>; 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 <span class="hlt">MODIS</span> aerosol products over Pune. Analysis of the data indicates that the Terra and <span class="hlt">Aqua</span> <span class="hlt">MODIS</span> 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 <span class="hlt">MODIS</span> products against AERONET measurements are 0.79 for Terra and 0.62 for <span class="hlt">Aqua</span>; however for premonsoon, the corresponding coefficients are 0.78 and 0.74. Similarly, the linear regression correlation coefficients for Microtops measurements against <span class="hlt">MODIS</span> products are 0.72 and 0.93 for Terra and <span class="hlt">Aqua</span> data respectively during winter and are 0.78 and 0.75 during pre-monsoon. On yearly basis in 2008-2009, correlation coefficients for <span class="hlt">MODIS</span> products against AERONET measurements are 0.80 and 0.78 for Terra and <span class="hlt">Aqua</span> respectively while the corresponding coefficients are 0.70 and 0.73 during 2009-2010. The regressed intercepts with <span class="hlt">MODIS</span> vs. AERONET are 0.09 for Terra and 0.05 for <span class="hlt">Aqua</span> during winter whereas their values are 0.04 and 0.07 during pre-monsoon. However, <span class="hlt">MODIS</span> 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 (<span class="hlt">Aqua</span>) during winter and 0.97 (Terra) and 0.94 (<span class="hlt">Aqua</span>) 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).</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://ntrs.nasa.gov/search.jsp?R=20000080269&hterms=aerosols+desert&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D80%26Ntt%3Daerosols%2Bdesert','NASA-TRS'); return false;" href="http://ntrs.nasa.gov/search.jsp?R=20000080269&hterms=aerosols+desert&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D80%26Ntt%3Daerosols%2Bdesert"><span id="translatedtitle">New Satellite Measurements of Aerosol Direct Radiative Forcing from <span class="hlt">MODIS</span>, MISR, and POLDER</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Kaufman, Y.</p> <p>2000-01-01</p> <p>New set of satellites, <span class="hlt">MODIS</span> and MISR launched on EOS-Terra and POLDER launched on ADEOS-1, and scheduled for ADEOS-II and PARASOL in orbit with EOS-<span class="hlt">AQUA</span>, open exciting opportunities to measure aerosol and their radiative forcing of climate. Each of these instruments has a different approach to invert remote sensing data to derive the aerosol properties. <span class="hlt">MODIS</span> is using wide spectral range 0.47-2.1 micron. MISR is using narrower spectral range (0.44 to 0.87 micron) but observing the same spot from 9 different angles along the satellite track. POLDER using similar wavelengths, uses two dimensional view with a wide angle optics and adds polarization to the inversion process. Among these instruments, we expect to measure the global distribution of aerosol, to distinguish small pollution particles from large particles from deserts and ocean spray. We shall try to measure the aerosol absorption of solar radiation, and their refractive index that indicates the effect of liquid water on the aerosol size and interaction with sunlight. The radiation field measured by these instruments in variety of wavelengths and angles, is also used to derive the effect of the aerosol on <span class="hlt">reflection</span> of sunlight spectral fluxes to space. When combined with flux measurements at the ground, it gives a complete characterization of the effect of aerosol on solar illumination, heating in the atmosphere and <span class="hlt">reflection</span> to space.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://www.osti.gov/scitech/biblio/1045215','SCIGOV-STC'); return false;" href="http://www.osti.gov/scitech/biblio/1045215"><span id="translatedtitle">A SOAP Web Service for accessing <span class="hlt">MODIS</span> land product subsets</span></a></p> <p><a target="_blank" href="http://www.osti.gov/scitech">SciTech Connect</a></p> <p>SanthanaVannan, Suresh K; Cook, Robert B; Pan, Jerry Yun; Wilson, Bruce E</p> <p>2011-01-01</p> <p>Remote sensing data from satellites have provided valuable information on the state of the earth for several decades. Since March 2000, the Moderate Resolution Imaging Spectroradiometer (<span class="hlt">MODIS</span>) sensor on board NASA s Terra and <span class="hlt">Aqua</span> satellites have been providing estimates of several land parameters useful in understanding earth system processes at global, continental, and regional scales. However, the HDF-EOS file format, specialized software needed to process the HDF-EOS files, data volume, and the high spatial and temporal resolution of <span class="hlt">MODIS</span> data make it difficult for users wanting to extract small but valuable amounts of information from the <span class="hlt">MODIS</span> record. To overcome this usability issue, the NASA-funded Distributed Active Archive Center (DAAC) for Biogeochemical Dynamics at Oak Ridge National Laboratory (ORNL) developed a Web service that provides subsets of <span class="hlt">MODIS</span> land products using Simple Object Access Protocol (SOAP). The ORNL DAAC <span class="hlt">MODIS</span> subsetting Web service is a unique way of serving satellite data that exploits a fairly established and popular Internet protocol to allow users access to massive amounts of remote sensing data. The Web service provides <span class="hlt">MODIS</span> land product subsets up to 201 x 201 km in a non-proprietary comma delimited text file format. Users can programmatically query the Web service to extract <span class="hlt">MODIS</span> land parameters for real time data integration into models, decision support tools or connect to workflow software. Information regarding the <span class="hlt">MODIS</span> SOAP subsetting Web service is available on the World Wide Web (WWW) at http://daac.ornl.gov/modiswebservice.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/cgi-bin/nph-data_query?bibcode=2016EGUGA..1811679M&link_type=ABSTRACT','NASAADS'); return false;" href="http://adsabs.harvard.edu/cgi-bin/nph-data_query?bibcode=2016EGUGA..1811679M&link_type=ABSTRACT"><span id="translatedtitle">Global land surface albedo maps from <span class="hlt">MODIS</span> using the Google Earth Engine</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Mitraka, Zina; Benas, Nikolaos; Gorelick, Noel; Chrysoulakis, Nektarios</p> <p>2016-04-01</p> <p>The land surface albedo (LSA) is a critical physical variable, which influences the Earth's climate by affecting the energy budget and distribution in the Earth-atmosphere system. Its role is highly significant in both global and local scales; hence, LSA measurements provide a quantitative means for better constraining global and regional scale climate modelling efforts. The Moderate Resolution Imaging Spectroradiometer (<span class="hlt">MODIS</span>) sensor, on board NASA's Terra and <span class="hlt">Aqua</span> platforms, provides the parameters needed for the computation of LSA on an 8-day temporal scale and a variety of spatial scales (ranging between 0.5 - 5 km). This dataset was used here for the LSA estimation and its changes over the study area at 0.5 km spatial resolution. More specifically, the <span class="hlt">MODIS</span> albedo product was used, which includes both the directional-hemispherical surface <span class="hlt">reflectance</span> (black-sky albedo) and the bi-hemispherical surface <span class="hlt">reflectance</span> (white-sky albedo). The LSA was estimated for the whole globe on an 8-day basis for the whole time period covered by <span class="hlt">MODIS</span> acquisitions (i.e. 2000 until today). To estimate LSA from black-sky and white-sky albedos, the fraction of the diffused radiation is needed, a function of the Aerosol Optical Thickness (AOT). Required AOT information was acquired from the <span class="hlt">MODIS</span> AOT product at 1̊ × 1̊ spatial resolution. Since LSA also depends on solar zenith angle (SZA), 8-day mean LSA values were computed as averages of corresponding LSA values for representative SZAs covering the 24-hour day. The estimated LSA was analysed in terms of both spatial and seasonal characteristics, while LSA changes during the period examined were assessed. All computation were performed using the Google Earth Engine (GEE). The GEE provided access to all the <span class="hlt">MODIS</span> products needed for the analysis without the need of searching or downloading. Moreover, the combination of <span class="hlt">MODIS</span> products in both temporal and spatial terms was fast and effecting using the GEE API (Application</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/20120002030','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20120002030"><span id="translatedtitle">Analysis of Co-Located <span class="hlt">MODIS</span> and CALIPSO Observations Near Clouds</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Varnai, Tamas; Marshak, Alexander</p> <p>2011-01-01</p> <p>The purpose of this paper is to help researchers combine data from different satellites and thus gain new insights into two critical yet poorly understood aspects of anthropogenic climate change, aerosol-cloud interactions and aerosol radiative effects, For this, the paper explores whether cloud information from the <span class="hlt">Aqua</span> satellite's <span class="hlt">MODIS</span> instrument can help characterize systematic aerosol changes near clouds by refining earlier perceptions of these changes that were based on the CALIPSO satellite's CALIOP instrument. Similar to a radar but using visible and ncar-infrared light, CALIOP sends out laser pulses and provides aerosol and cloud information along a single line that tracks the satellite orbit by measuring the <span class="hlt">reflection</span> of its pulses. In contrast, <span class="hlt">MODIS</span> takes images of <span class="hlt">reflected</span> sunlight and emitted infrared radiation at several wavelengths, and covers wide areas around the satellite track. This paper analyzes a year-long global dataset covering all ice-free oceans, and finds that <span class="hlt">MODIS</span> can greatly help the interpretation of CALIOP observations, especially by detecting clouds that lie outside the line observed by CALlPSO. The paper also finds that complications such as differences in view direction or clouds drifting in the 72 seconds that elapse between <span class="hlt">MODIS</span> and CALIOP observations have only a minor impact. The study also finds that <span class="hlt">MODIS</span> data helps refine but does not qualitatively alter perceptions of the systematic aerosol changes that were detected in earlier studies using only CALIOP data. It then proposes a statistical approach to account for clouds lying outside the CALIOP track even when <span class="hlt">MODIS</span> cannot as reliably detect low clouds, for example at night or over ice. Finally, the paper finds that, because of variations in cloud amount and type, the typical distance to clouds in maritime clear areas varies with season and location. The overall median distance to clouds in maritime clear areas around 4-5 km. The fact that half of all clear areas is</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/19980236657','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/19980236657"><span id="translatedtitle">[<span class="hlt">MODIS</span> Investigation</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Abbott, Mark R.</p> <p>1996-01-01</p> <p>Our first activity is based on delivery of code to Bob Evans (University of Miami) for integration and eventual delivery to the <span class="hlt">MODIS</span> Science Data Support Team. As we noted in our previous semi-annual report, coding required the development and analysis of an end-to-end model of fluorescence line height (FLH) errors and sensitivity. This model is described in a paper in press in Remote Sensing of the Environment. Once the code was delivered to Miami, we continue to use this error analysis to evaluate proposed changes in <span class="hlt">MODIS</span> sensor specifications and performance. Simply evaluating such changes on a band by band basis may obscure the true impacts of changes in sensor performance that are manifested in the complete algorithm. This is especially true with FLH that is sensitive to band placement and width. The error model will be used by Howard Gordon (Miami) to evaluate the effects of absorbing aerosols on the FLH algorithm performance. Presently, FLH relies only on simple corrections for atmospheric effects (viewing geometry, Rayleigh scattering) without correcting for aerosols. Our analysis suggests that aerosols should have a small impact relative to changes in the quantum yield of fluorescence in phytoplankton. However, the effect of absorbing aerosol is a new process and will be evaluated by Gordon.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/20110007985','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20110007985"><span id="translatedtitle">Observed Differences in Spectral Microphysical Retrievals from <span class="hlt">MODIS</span></span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Platnick, Steven E.; Zhang, Zhibo; Maddox, Brent; Ackeman, Steven A.</p> <p>2010-01-01</p> <p>The microphysical structure of clouds is of fundamental importance for understanding a variety of cloud radiation and physical processes. With the advent of <span class="hlt">MODIS</span> (Moderate Resolution Imaging Spectroradiometer) on the NASA EOS Terra and <span class="hlt">Aqua</span> platforms, simultaneous global/daily 1km retrievals of cloud effective particle size are available using the heritage 3.7 an band from AVHRR as well as the 1.6 and 2.1 m shortwave IR bands. The <span class="hlt">MODIS</span> cloud product (MOD06/MYD06 for <span class="hlt">MODIS</span> Terra and <span class="hlt">Aqua</span>, respectively) provides separate effective radii results using each of these spectral bands. It has been found that significant differences can occur between the three size retrievals, mainly for liquid water marine boundary layer clouds and especially in broken (low cloud fraction) regimes. In particular, for such regimes, effective radii derived from the <span class="hlt">MODIS</span> 2.1 lim band can be substantially larger than retrievals from the Heritage 3.7 lam band. In this paper, we present global and regional results of the differences, including correlations, view angle dependencies, and algorithm sensitivities for the existing <span class="hlt">MODIS</span> Collection 5 product.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2009SPIE.7474E..0WW','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2009SPIE.7474E..0WW"><span id="translatedtitle"><span class="hlt">MODIS</span> thermal emissive band calibration stability derived from surface targets</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Wenny, B. N.; Xiong, X.; Dodd, J.</p> <p>2009-09-01</p> <p>The 16 <span class="hlt">MODIS</span> Thermal Emissive Bands (TEB), with wavelengths covering from 3.7μm to 14.4μm, are calibrated using scan-by-scan observations of an on-orbit blackbody (BB). Select Earth surface targets can be used to track the long-term consistency, stability and relative bias between the two <span class="hlt">MODIS</span> instruments currently in orbit. Measurements at Dome C, Antarctica have shown a relative bias of less than 0.01K over a 5 year period between Terra and <span class="hlt">Aqua</span> <span class="hlt">MODIS</span> Band 31 (11μm). Dome C surface temperatures are typically outside the <span class="hlt">MODIS</span> BB calibration range. Sea surface temperature (SST) measurements from data buoys provide a useful reference at higher scene temperatures. This paper extends the techniques previously applied only to Band 31 to the remaining TEB using both Dome C and SST sites. The long-term calibration stability and relative bias between Terra and <span class="hlt">Aqua</span> <span class="hlt">MODIS</span> is discussed.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://ntrs.nasa.gov/search.jsp?R=20040012843&hterms=modis&qs=N%3D0%26Ntk%3DTitle%26Ntx%3Dmode%2Bmatchall%26Ntt%3Dmodis','NASA-TRS'); return false;" href="http://ntrs.nasa.gov/search.jsp?R=20040012843&hterms=modis&qs=N%3D0%26Ntk%3DTitle%26Ntx%3Dmode%2Bmatchall%26Ntt%3Dmodis"><span id="translatedtitle">Remote Sensing of Aerosol using <span class="hlt">MODIS</span>, <span class="hlt">MODIS</span>+CALIPSO and with the AEROSAT Concept</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Kaufman, Yoram J.</p> <p>2002-01-01</p> <p>In the talk I shall review the <span class="hlt">MODIS</span> use of spectral information to derive aerosol size distribution, optical thickness and <span class="hlt">reflected</span> spectral flux. The accuracy and validation of the <span class="hlt">MODIS</span> products will be discussed. A few applications will be shown: inversion of combined <span class="hlt">MODIS</span>+lidar data, aerosol Anthropogenic direct forcing, and dust deposition in the Atlantic Ocean. I shall also discuss the aerosol information that <span class="hlt">MODIS</span> is measuring: real ref index, single scattering albedo, size of fine and coarse modes, and describe the AEROSAT concept that uses bright desert and glint to derive aerosol absorption.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2015AGUFM.A43B0273L','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2015AGUFM.A43B0273L"><span id="translatedtitle">Evaluation of interregional variability in <span class="hlt">MODIS</span> cloud regimes</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Leinonen, J. S.; Lebsock, M. D.; Oreopoulos, L.; Cho, N.</p> <p>2015-12-01</p> <p>Clustering techniques have been used in the last few decades to classify cloud types automatically from satellite observations, most commonly using cloud top pressure and cloud optical depth. The underlying assumption is that the resulting clusters, called "cloud regimes" or "weather states", represent some type of basic states of the atmosphere, and thus that their occurrence can be used as a proxy for related variables such as radiative balance or precipitation. We have examined the validity of these assumptions by using independent measurements from the CloudSat and CALIPSO satellites. The CloudSat radar yields a <span class="hlt">reflectivity</span> product that is sensitive to many aspects of the physics of the clouds, while CloudSat together with the CALIPSO lidar can retrieve the vertical structure of the cloud column, including multi-layer clouds. These observations have been separated into groups according to the recently published cloud regimes based on data from the <span class="hlt">MODIS</span> instrument, deployed on the <span class="hlt">Aqua</span> satellite orbiting in the same constellation with CloudSat and CALIPSO. The distributions of these observations have been constructed both globally and in a number of regions in different parts of the Earth. By analyzing the differences in the distributions between these regions, we can evaluate the usefulness of the cloud regimes as a proxy for the measured variables. Some cloud regimes have been found to be rather stable between regions, while others display considerable variability. Moreover, some cloud regimes appear much more similar to each other in CloudSat observations than they do using the <span class="hlt">MODIS</span> regimes. We analyze the implications of these differences for the usability of the cloud regimes as climate indicators. We also explore various filtering techniques and different clustering methods that can potentially be used to reduce these differences, and thus to improve the universality of the cloud regimes.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/20110015418','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20110015418"><span id="translatedtitle">Evaluation and Windspeed Dependence of <span class="hlt">MODIS</span> Aerosol Retrievals Over Open Ocean</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Kleidman, Richard G.; Smirnov, Alexander; Levy, Robert C.; Mattoo, Shana; Tanre, Didier</p> <p>2011-01-01</p> <p>The Maritime Aerosol Network (MAN) data set provides high quality ground-truth to validate the <span class="hlt">MODIS</span> aerosol product over open ocean. Prior validation of the ocean aerosol product has been limited to coastal and island sites. Comparing <span class="hlt">MODIS</span> Collection 5 ocean aerosol retrieval products with collocated MAN measurements from ships shows that <span class="hlt">MODIS</span> is meeting the pre-launch uncertainty estimates for aerosol optical depth (AOD) with 64% and 67% of retrievals at 550 nm, and 74% and 78% of retrievals at 870 nm, falling within expected uncertainty for Terra and <span class="hlt">Aqua</span>, respectively. Angstrom Exponent comparisons show a high correlation between <span class="hlt">MODIS</span> retrievals and shipboard measurements (R= 0.85 Terra, 0.83 <span class="hlt">Aqua</span>), although the <span class="hlt">MODIS</span> aerosol algorithm tends to underestimate particle size for large particles and overestimate size for small particles, as seen in earlier Collections. Prior analysis noted an offset between Terra and <span class="hlt">Aqua</span> ocean AOD, without concluding which sensor was more accurate. The simple linear regression reported here, is consistent with other anecdotal evidence that <span class="hlt">Aqua</span> agreement with AERONET is marginally better. However we cannot claim based on the current study that the better <span class="hlt">Aqua</span> comparison is statistically significant. Systematic increase of error as a function of wind speed is noted in both Terra and <span class="hlt">Aqua</span> retrievals. This wind speed dependency enters the retrieval when winds deviate from the 6 m/s value assumed in the rough ocean surface and white cap parameterizations. Wind speed dependency in the results can be mitigated by using auxiliary NCEP wind speed information in the retrieval process.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2009TrSpT...7..Pn1K','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2009TrSpT...7..Pn1K"><span id="translatedtitle">Comparison of ASTER TOA Radiance with <span class="hlt">MODIS</span></span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Kanno, Hiroto; Iwasaki, Akira</p> <p></p> <p>Synergistic fusion of multi-resolution remote sensing images is important to data users that require observation frequency, spatial resolution and observation wavelength. However, it requires compatibility of these data products. Top of Atmosphere (TOA) radiances of the Advanced Spaceborne Thermal Emission and <span class="hlt">Reflection</span> Radiometer (ASTER) and the Moderate Resolution Imaging Spectroradiometer (<span class="hlt">MODIS</span>) are compared in the shortwave infrared (SWIR) and it is found that the sensitivity of <span class="hlt">MODIS</span> is slightly higher and that the ASTER radiance is higher at the lower <span class="hlt">reflectance</span> regions. ASTER suffers from stray light phenomena because of the nature of a pushbroom sensor, which stands out for SWIR. In contrast, <span class="hlt">MODIS</span> is free from ghost phenomena in <span class="hlt">reflective</span> bands, although existence of stray light is known in thermal bands. In this work, correction of stray light in ASTER is carried out using <span class="hlt">MODIS</span> images with a wider swath, which makes the correction of full scene of ASTER images.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://www.ncbi.nlm.nih.gov/pubmed/18817116','PUBMED'); return false;" href="http://www.ncbi.nlm.nih.gov/pubmed/18817116"><span id="translatedtitle">Monitoring agricultural burning in the Mississippi River Valley region from the moderate resolution imaging spectroradiometer (<span class="hlt">MODIS</span>).</span></a></p> <p><a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a></p> <p>Korontzi, Stefania; McCarty, Jessica; Justice, Christopher</p> <p>2008-09-01</p> <p>The 2003 active fire observations from the Moderate Resolution Imaging Spectroradiometer (<span class="hlt">MODIS</span>), on board NASA's Terra and <span class="hlt">Aqua</span> satellites, were analyzed to assess burning activity in the cropland areas of the Mississippi River Valley region. Agricultural burning was found to be an important contributor to fire activity in this region, accounting for approximately one-third of all burning. Agricultural fire activity showed two seasonal peaks: the first, smaller peak, occurring in June during the spring harvesting of wheat; and the second, bigger peak, in October during the fall harvesting of rice and soy. The seasonal signal in agricultural burning was predominantly evident in the early afternoon <span class="hlt">MODIS</span> <span class="hlt">Aqua</span> fire detections. A strong diurnal agricultural fire signal was prevalent during the fall harvesting months, as suggested by the substantially higher number (approximately 3.5 times) of fires detected by <span class="hlt">MODIS</span> <span class="hlt">Aqua</span> in the early afternoon, compared with those detected by <span class="hlt">MODIS</span> Terra in the morning. No diurnal variations in agricultural fire activity were apparent during the springtime wheat-harvesting season. The seasonal and diurnal patterns in agricultural fire activity detected by <span class="hlt">MODIS</span> are supported by known crop management practices in this region. <span class="hlt">MODIS</span> data provide an important means to characterize and monitor agricultural fire dynamics and management practices. PMID:18817116</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2009AGUFM.A41D0150L','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2009AGUFM.A41D0150L"><span id="translatedtitle">Comparison of Deep Blue and Land Surface <span class="hlt">Reflectance</span> in the San Joaquin Valley</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Lehmuth, S.; Agrawal, P.; Fisher, D.; Nguyen, A.; Roberts, K.; Strawa, A. W.; Johnson, L. F.; Skiles, J. W.</p> <p>2009-12-01</p> <p>lation standards for the past several years. While previous studies show strong correlations between the Moderate Resolution Imaging Spectroradiometer (<span class="hlt">MODIS</span>) derived Aerosol Optical Thickness (AOT) and surface PM measurements on the East Coast of the United States, weak correlations have been found on the West Coast. Specific causes for this discrepancy have not been identified. The Deep Blue algorithm was created in order to correct AOT calculations over arid, non-vegetated regions. Although slight improvements were seen, numbers over California remained problematic. This study aims to understand the poor correlation on the West Coast, specifically in the SJV, by targeting surface <span class="hlt">reflectance</span> as a factor for the inaccuracy. This was done by comparing land surface <span class="hlt">reflectances</span> derived from <span class="hlt">MODIS</span> <span class="hlt">Aqua</span> to ground <span class="hlt">reflectance</span> measurements for the region, in order to examine their correlation. Presumably, an undesirable effect on AOT calculations would occur if these surface <span class="hlt">reflectance</span> values are imprecise. Results show that there is little correlation between the data sets. <span class="hlt">MODIS</span> Land Surface <span class="hlt">Reflectance</span> matched closest to the mixed ground measurements. In all products, the red band (0.620 - 0.670 μm) values vary more than the blue band (0.459 - 0.479 μm) values. Most data fall in a horizontal linear trend line, not the expected 1:1 line.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2011AGUFM.B51M0586S','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2011AGUFM.B51M0586S"><span id="translatedtitle">Detecting Forest Disturbance in the Pacific Northwest From <span class="hlt">MODIS</span> Time Series Using Temporal Segmentation</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Sulla-Menashe, D. J.; Yang, Z.; Braaten, J.; Krankina, O. N.; Kennedy, R. E.; Friedl, M. A.</p> <p>2011-12-01</p> <p>Changes to the land surface of the Earth are occurring at unprecedented rates with significant implications for surface energy balance and regional to global scale cycles of carbon and water. Data from the Moderate Resolution Imaging Spectroradiometer (<span class="hlt">MODIS</span>) aboard the <span class="hlt">Aqua</span> and Terra satellite platforms provide over 11 years of consistent, synoptic observations of the biosphere. New methods have recently emerged to analyze time series of remote sensing images, thereby providing ecologically important information about disturbance and succession over large regions. In particular, the Landtrendr algorithm was developed to characterize long-term trends, including punctual and gradual disturbance events and subsequent vegetation regrowth, in dense time series of Landsat imagery. While this approach has shown to be useful and robust in a wide range of ecosystems, its application is limited to areas with sufficient Landsat archive depth and relatively cloud-free periods. Additionally, the approach requires significant effort in atmospheric correction and normalization steps, increasing the cost for large-area application. Here we present an adaptation of the Landtrendr algorithm to an 11-year time series of <span class="hlt">MODIS</span> Normalized BRDF-Adjusted <span class="hlt">Reflectance</span> (NBAR) data to detect forest disturbance in the Northwest Forest Plan (NWFP) area of Washington, Oregon, and California. The NWFP area represents a dynamic zone of forest management with an active disturbance regime that includes insect defoliation, wildfires, and logging. This work aims to explore how the size and severity of disturbance events influence detection and characterization of such events using <span class="hlt">MODIS</span> data. We sampled disturbance events across gradients of size and severity that occurred during the <span class="hlt">MODIS</span> era (2000-present) using a high-quality database of forest disturbance information derived from Landsat. One-third of these disturbance records were used to calibrate the model using <span class="hlt">MODIS</span> NBAR time series, and</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://www.osti.gov/scitech/biblio/22098723','SCIGOV-STC'); return false;" href="http://www.osti.gov/scitech/biblio/22098723"><span id="translatedtitle">In <span class="hlt">aqua</span> vivo EPID dosimetry</span></a></p> <p><a target="_blank" href="http://www.osti.gov/scitech">SciTech Connect</a></p> <p>Wendling, Markus; McDermott, Leah N.; Mans, Anton; Olaciregui-Ruiz, Igor; Pecharroman-Gallego, Raul; Sonke, Jan-Jakob; Stroom, Joep; Herk, Marcel J.; Mijnheer, Ben van</p> <p>2012-01-15</p> <p>Purpose: At the Netherlands Cancer Institute-Antoni van Leeuwenhoek Hospital in vivo dosimetry using an electronic portal imaging device (EPID) has been implemented for almost all high-energy photon treatments of cancer with curative intent. Lung cancer treatments were initially excluded, because the original back-projection dose-reconstruction algorithm uses water-based scatter-correction kernels and therefore does not account for tissue inhomogeneities accurately. The aim of this study was to test a new method, in <span class="hlt">aqua</span> vivo EPID dosimetry, for fast dose verification of lung cancer irradiations during actual patient treatment. Methods: The key feature of our method is the dose reconstruction in the patient from EPID images, obtained during the actual treatment, whereby the images have been converted to a situation as if the patient consisted entirely of water; hence, the method is termed in <span class="hlt">aqua</span> vivo. This is done by multiplying the measured in vivo EPID image with the ratio of two digitally reconstructed transmission images for the unit-density and inhomogeneous tissue situation. For dose verification, a comparison is made with the calculated dose distribution with the inhomogeneity correction switched off. IMRT treatment verification is performed for each beam in 2D using a 2D {gamma} evaluation, while for the verification of volumetric-modulated arc therapy (VMAT) treatments in 3D a 3D {gamma} evaluation is applied using the same parameters (3%, 3 mm). The method was tested using two inhomogeneous phantoms simulating a tumor in lung and measuring its sensitivity for patient positioning errors. Subsequently five IMRT and five VMAT clinical lung cancer treatments were investigated, using both the conventional back-projection algorithm and the in <span class="hlt">aqua</span> vivo method. The verification results of the in <span class="hlt">aqua</span> vivo method were statistically analyzed for 751 lung cancer patients treated with IMRT and 50 lung cancer patients treated with VMAT. Results: The improvements by</p> </li> </ol> <div class="pull-right"> <ul class="pagination"> <li><a href="#" onclick='return showDiv("page_1");'>«</a></li> <li><a href="#" onclick='return showDiv("page_11");'>11</a></li> <li><a href="#" onclick='return showDiv("page_12");'>12</a></li> <li class="active"><span>13</span></li> <li><a href="#" onclick='return showDiv("page_14");'>14</a></li> <li><a href="#" onclick='return showDiv("page_15");'>15</a></li> <li><a href="#" onclick='return showDiv("page_25");'>»</a></li> </ul> </div> </div><!-- col-sm-12 --> </div><!-- row --> </div><!-- page_13 --> <div id="page_14" class="hiddenDiv"> <div class="row"> <div class="col-sm-12"> <div class="pull-right"> <ul class="pagination"> <li><a href="#" onclick='return showDiv("page_1");'>«</a></li> <li><a href="#" onclick='return showDiv("page_12");'>12</a></li> <li><a href="#" onclick='return showDiv("page_13");'>13</a></li> <li class="active"><span>14</span></li> <li><a href="#" onclick='return showDiv("page_15");'>15</a></li> <li><a href="#" onclick='return showDiv("page_16");'>16</a></li> <li><a href="#" onclick='return showDiv("page_25");'>»</a></li> </ul> </div> </div> </div> <div class="row"> <div class="col-sm-12"> <ol class="result-class" start="261"> <li> <p><a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/20070017429','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20070017429"><span id="translatedtitle">The Plane-parallel Albedo Bias of Liquid Clouds from <span class="hlt">MODIS</span> Observations</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Oreopoulos, Lazaros; Cahalan, Robert F.; Platnick, Steven</p> <p>2007-01-01</p> <p>In our most advanced modeling tools for climate change prediction, namely General Circulation Models (GCMs), the schemes used to calculate the budget of solar and thermal radiation commonly assume that clouds are horizontally homogeneous at scales as large as a few hundred kilometers. However, this assumption, used for convenience, computational speed, and lack of knowledge on cloud small scale variability, leads to erroneous estimates of the radiation budget. This paper provides a global picture of the solar radiation errors at scales of approximately 100 km due to warm (liquid phase) clouds only. To achieve this, we use cloud retrievals from the instrument <span class="hlt">MODIS</span> on the Terra and <span class="hlt">Aqua</span> satellites, along with atmospheric and surface information, as input into a GCM-style radiative transfer algorithm. Since the <span class="hlt">MODIS</span> product contains information on cloud variability below 100 km we can run the radiation algorithm both for the variable and the (assumed) homogeneous clouds. The difference between these calculations for <span class="hlt">reflected</span> or transmitted solar radiation constitutes the bias that GCMs would commit if they were able to perfectly predict the properties of warm clouds, but then assumed they were homogeneous for radiation calculations. We find that the global average of this bias is approx.2-3 times larger in terms of energy than the additional amount of thermal energy that would be trapped if we were to double carbon dioxide from current concentrations. We should therefore make a greater effort to predict horizontal cloud variability in GCMs and account for its effects in radiation calculations.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/20040008406','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20040008406"><span id="translatedtitle">A Study of Uncertainties for <span class="hlt">MODIS</span> Cloud Retrievals of Optical Thickness and Effective Radius</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Platnick, Steven; Pincus, Robert</p> <p>2002-01-01</p> <p>The investigation spanned four linked components as summarized in section III, each relating to some aspect of uncertainty assessment in the retrieval of cloud optical and microphysical properties using solar <span class="hlt">reflectance</span> algorithms such as the <span class="hlt">MODIS</span> operational cloud product (product IDS MOD06, MDY06 for Terra and <span class="hlt">Aqua</span>, respectively). As discussed, three of these components have been fully completed (items (l), (2), and (3) while item (4) has been partially completed. These efforts have resulted in peer-reviewed publications and/or information delivered to the <span class="hlt">MODIS</span> P.I. (M. D. King) for inclusion in the cloud product Quality Assessment (QA) output, a portion of the product output used, in part, for retrieval error assignments. This final report begins with a synopsis of the proposed investigation (section III) followed by a summary of work performed up through the last report including updates (section IV). Section V describes new activities. Publications from the efforts are listed in section VI. Figures (available in powerpoint format) are found in section VII.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/19980219482','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/19980219482"><span id="translatedtitle">[<span class="hlt">MODIS</span> Investigation</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Abbott, Mark R.</p> <p>1998-01-01</p> <p>The objectives of the last six months were: (1) Revise the algorithms for the Fluorescence Line Height (FLH) and Chlorophyll Fluorescence Efficiency (CFE) products, especially the data quality flags; (2) Revise the MOCEAN validation plan; (3) Deploy and recover bio-optical instrumentation at the Hawaii Ocean Time-series (HOT) site as part of the Joint Global Ocean Flux Study (JGOFS); (4) Prepare for field work in the Antarctic Polar Frontal Zone as part of JGOFS; (5) Submit manuscript on bio-optical time scales as estimated from Lagrangian drifters; (6) Conduct chemostat experiments on fluorescence; (7) Interface with the Global Imager (GLI) science team; and (8) Continue development of advanced data system browser. We are responsible for the delivery of two at-launch products for AM-1: Fluorescence line height (FLH) and chlorophyll fluorescence efficiency (CFE). We also considered revising the input chlorophyll, which is used to determine the degree of binning. We have refined the quality flags for the Version 2 algorithms. We have acquired and installed a Silicon Graphics Origin 200. We are working with the University of Miami team to develop documentation that will describe how the <span class="hlt">MODIS</span> ocean components are linked together.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2005JApMe..44..221M','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2005JApMe..44..221M"><span id="translatedtitle">Evaluation of Cirrus Cloud Properties Derived from <span class="hlt">MODIS</span> Data Using Cloud Properties Derived from Ground-Based Observations Collected at the ARM SGP Site.</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Mace, Gerald G.; Zhang, Yuying; Platnick, Steven; King, Michael D.; Minnis, Patrick; Yang, Ping</p> <p>2005-02-01</p> <p>The Moderate Resolution Imaging Spectroradiometer (<span class="hlt">MODIS</span>) on board the NASA Terra satellite has been collecting global data since March 2000 and the one on the <span class="hlt">Aqua</span> satellite since June 2002. In this paper, cirrus cloud properties derived from ground-based remote sensing data are compared with similar cloud properties derived from <span class="hlt">MODIS</span> data on Terra. To improve the space-time correlation between the satellite and ground-based observations, data from a wind profiler are used to define the cloud advective streamline along which the comparisons are made. In this paper, approximately two dozen cases of cirrus are examined and a statistical approach to the comparison that relaxes the requirement that clouds occur over the ground-based instruments during the overpass instant is explored. The statistical comparison includes 168 cloudy <span class="hlt">MODIS</span> overpasses of the Southern Great Plains (SGP) region and approximately 300 h of ground-based cirrus observations. The physical and radiative properties of cloud layers are derived from <span class="hlt">MODIS</span> data separately by the <span class="hlt">MODIS</span> Atmospheres Team and the Clouds and the Earth's Radiant Energy System (CERES) Science Team using multiwavelength <span class="hlt">reflected</span> solar and emitted thermal radiation measurements. Using two ground-based cloud property retrieval algorithms and the two <span class="hlt">MODIS</span> algorithms, a positive correlation in the effective particle size, the optical thickness, the ice water path, and the cloud-top pressure between the various methods is shown, although sometimes there are significant biases. Classifying the clouds by optical thickness, it is demonstrated that the regionally averaged cloud properties derived from <span class="hlt">MODIS</span> are similar to those diagnosed from the ground. Because of a conservative approach toward identifying thin cirrus pixels over this region, the area-averaged cloud properties derived from the <span class="hlt">MODIS</span> Atmospheres MOD06 product tend to be biased slightly toward the optically thicker pixels. This bias tendency has implications for</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://www.ars.usda.gov/research/publications/publication/?seqNo115=294400','TEKTRAN'); return false;" href="http://www.ars.usda.gov/research/publications/publication/?seqNo115=294400"><span id="translatedtitle">Comparison of different <span class="hlt">MODIS</span> data product collections over an agricultural area</span></a></p> <p><a target="_blank" href="http://www.ars.usda.gov/services/TekTran.htm">Technology Transfer Automated Retrieval System (TEKTRAN)</a></p> <p></p> <p></p> <p>Standard data products from NASA's Moderate Resolution Imaging Spectroradiometer (<span class="hlt">MODIS</span>) were available at launch (Collection 3) and have undergone two revisions (Collections 4 and 5) during the continuing Terra and <span class="hlt">Aqua</span> missions. In 2000, a research project was conducted in large fields of corn an...</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://ntrs.nasa.gov/search.jsp?R=20100034941&hterms=Wilcox&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D60%26Ntt%3DWilcox','NASA-TRS'); return false;" href="http://ntrs.nasa.gov/search.jsp?R=20100034941&hterms=Wilcox&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D60%26Ntt%3DWilcox"><span id="translatedtitle">Estimate of the Impact of Absorbing Aerosol Over Cloud on the <span class="hlt">MODIS</span> Retrievals of Cloud Optical Thickness and Effective Radius Using Two Independent Retrievals of Liquid Water Path</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Wilcox, Eric M.; Harshvardhan; Platnick, Steven</p> <p>2009-01-01</p> <p>Two independent satellite retrievals of cloud liquid water path (LWP) from the NASA <span class="hlt">Aqua</span> satellite are used to diagnose the impact of absorbing biomass burning aerosol overlaying boundary-layer marine water clouds on the Moderate Resolution Imaging Spectrometer (<span class="hlt">MODIS</span>) retrievals of cloud optical thickness (tau) and cloud droplet effective radius (r(sub e)). In the <span class="hlt">MODIS</span> retrieval over oceans, cloud <span class="hlt">reflectance</span> 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 <span class="hlt">MODIS</span> tau retrieval may result from reductions in the 0.86-micrometer <span class="hlt">reflectance</span>, which is only very weakly absorbed by clouds, owing to absorption by aerosols in cases where biomass burning aerosols occur above water clouds. <span class="hlt">MODIS</span> 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 <span class="hlt">MODIS</span> 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 <span class="hlt">MODIS</span>) 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 <span class="hlt">MODIS</span> LWP is 5.6 g per square meter. Only for scenes with OMI aerosol index greater than 2 does the</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2013SPIE.8866E..0QW','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2013SPIE.8866E..0QW"><span id="translatedtitle">Monitoring NPP VIIRS on-orbit radiometric performance from TOA <span class="hlt">reflectance</span> time series</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Wu, A.; Xiong, X.; Cao, C.; Sun, C.</p> <p>2013-09-01</p> <p>The recently launched (October 28, 2011) Suomi NPP (National Polar-orbiting Partnership) satellite has been operating nominally to daily collect global data. The Visible Infrared Imaging Radiometer Suite (VIIRS) is a key NPP sensor onboard the spacecraft. Similar to the heritage sensor <span class="hlt">MODIS</span>, VIIRS has on-board calibration components including a solar diffuser (SD) and a solar diffuser stability monitor (SDSM) for the <span class="hlt">reflective</span> solar bands (RSB), a V-groove blackbody for the thermal emissive bands (TEB), and a space view (SV) port for background. This study examines VIIRS <span class="hlt">reflective</span> solar bands (RSB) calibration stability and performance using observed top-of-atmosphere (TOA) <span class="hlt">reflectance</span> time series collected from two approaches. The first is from comparison with a well-calibrated <span class="hlt">Aqua</span> <span class="hlt">MODIS</span> and the second is from overpasses over the widely used Liby-4 desert site. The VIIRS and <span class="hlt">MODIS</span> comparison data is obtained from simultaneous nadir overpasses (SNO) for their spectrally matched bands. The <span class="hlt">reflectance</span> trends over the Libya-4 site are extracted from 16-day repeatable orbits so each data point has the same viewing geometry relative to the site. The impact due to the band spectral differences between the two instruments is corrected based on MODTRAN5 simulations. Results of this study provide useful information on NPP VIIRS post-launch calibration assessment and preliminary analysis of its calibration stability and consistency for the first 1.5 years.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://ntrs.nasa.gov/search.jsp?R=20100017716&hterms=pagano&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D30%26Ntt%3Dpagano','NASA-TRS'); return false;" href="http://ntrs.nasa.gov/search.jsp?R=20100017716&hterms=pagano&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D30%26Ntt%3Dpagano"><span id="translatedtitle">Advanced Remote-Sensing Imaging Emission Spectrometer (ARIES): AIRS Spectral Resolution with <span class="hlt">MODIS</span> Spatial Resolution</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Pagano, Thomas S.; Chahine, Moustafa T.; Aumann, Hartmut H.; OCallaghan, Fred</p> <p>2006-01-01</p> <p>The Advanced Remote-sensing Imaging Emission Spectrometer (ARIES) will measure a wide range of earth quantities fundamental to the study of global climate change. It will build upon the success of the Moderate Resolution Imaging Spectroradiometer (<span class="hlt">MODIS</span>) and the Atmospheric Infrared Sounder (AIRS) instruments currently flying on the EOS <span class="hlt">Aqua</span> Spacecraft. Both instruments are facility instruments for NASA providing data to thousands of scientists investigating land, ocean and atmospheric Earth System processes. ARIES will meet all the requirements of AIRS and <span class="hlt">MODIS</span> in a single compact instrument, while providing the next-generation capability of improved spatial resolution for AIRS and improved spectral resolution for <span class="hlt">MODIS</span>.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2007AGUSM.B41B..05D','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2007AGUSM.B41B..05D"><span id="translatedtitle">Mapping the Distribution of Cloud Forests Using <span class="hlt">MODIS</span> Imagery</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Douglas, M. W.; Mejia, J.; Murillo, J.; Orozco, R.</p> <p>2007-05-01</p> <p>Tropical cloud forests - those forests that are frequently immersed in clouds or otherwise very humid, are extremely difficult to map from the ground, and are not easily distinguished in satellite imagery from other forest types, but they have a very different flora and fauna than lowland rainforest. Cloud forests, although found in many parts of the tropics, have a very restricted vertical extent and thus are also restricted horizontally. As a result, they are subject to both human disturbance (coffee growing for example) and the effects of possible climate change. Motivated by a desire to seek meteorological explanations for the distribution of cloud forests, we have begun to map cloudiness using <span class="hlt">MODIS</span> Terra and <span class="hlt">Aqua</span> visible imagery. This imagery, at ~1030 LT and 1330 LT, is an approximation for mid-day cloudiness. In tropical regions the amount of mid-day cloudiness strongly controls the shortwave radiation and thus the potential for evaporation (and aridity). We have mapped cloudiness using a simple algorithm that distinguishes between the cloud-free background brightness and the generally more <span class="hlt">reflective</span> clouds to separate clouds from the underlying background. A major advantage of <span class="hlt">MODIS</span> imagery over many other sources of satellite imagery is its high spatial resolution (~250m). This, coupled with precisely navigated images, means that detailed maps of cloudiness can be produced. The cloudiness maps can then be related to the underlying topography to further refine the location of the cloud forests. An advantage of this technique is that we are mapping the potential cloud forest, based on cloudiness, rather than the actual cloud forest, which are commonly based on forest estimates from satellite and digital elevation data. We do not derive precipitation, only estimates of daytime cloudiness. Although only a few years of <span class="hlt">MODIS</span> imagery has been used in our studies, we will show that this is sufficient to describe the climatology of cloudiness with acceptable</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/20030096002','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20030096002"><span id="translatedtitle">Sea Ice Surface Temperature Product from the Moderate Resolution Imaging Spectroradiometer (<span class="hlt">MODIS</span>)</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Hall, Dorothy K.; Key, Jeffrey R.; Casey, Kimberly A.; Riggs, George A.; Cavalieri, Donald J.</p> <p>2003-01-01</p> <p>Global sea ice products are produced from the Earth Observing System (EOS) Moderate Resolution Imaging Spectroradiometer (<span class="hlt">MODIS</span>) on board both the Terra and <span class="hlt">Aqua</span> satellites. Daily sea ice extent and ice-surface temperature (IST) products are available at 1- and 4-km resolution. Validation activities have been undertaken to assess the accuracy of the <span class="hlt">MODIS</span> IST product at the South Pole station in Antarctica and in the Arctic Ocean using near-surface air-temperature data from a meteorological station and drifting buoys. Results from the study areas show that under clear skies, the <span class="hlt">MODIS</span> ISTs are very close to those of the near-surface air temperatures with a bias of -1.1 and -1.2 K, and an uncertainty of 1.6 and 1.7 K, respectively. It is shown that the uncertainties would be reduced if the actual temperature of the ice surface were reported instead of the near-surface air temperature. It is not possible to get an accurate IST from <span class="hlt">MODIS</span> in the presence of even very thin clouds or fog, however using both the Advanced Microwave Scanning Radiometer-EOS (AMSR-E) and the <span class="hlt">MODIS</span> on the <span class="hlt">Aqua</span> satellite, it may be possible to develop a relationship between <span class="hlt">MODIS</span>-derived IST and ice temperature derived from the AMSR-E. Since the AMSR-E measurements are generally unaffected by cloud cover, they may be used to complement the <span class="hlt">MODIS</span> IST measurements.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/19980219481','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/19980219481"><span id="translatedtitle">[<span class="hlt">MODIS</span> Investigation</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Abbott, Mark R.</p> <p>1998-01-01</p> <p>The objective of the last six months were: (1) Continue analysis of Hawaii Ocean Time-series (HOT) bio-optical mooring data, and Southern Ocean bio-optical drifter data; (2) Complete development of documentation of MOCEAN algorithms and software for use by MOCEAN team and GLI team; (3) Deploy instrumentation during JGOFS cruises in the Southern Ocean; (4) Participate in test cruise for Fast Repetition Rate (FRR) fluorometer; (5) Continue chemostat experiments on the relationship of fluorescence quantum yield to environmental factors; and (6) Continue to develop and expand browser-based information system for in situ bio-optical data. We are continuing to analyze bio-optical data collected at the Hawaii Ocean Time Series mooring as well as data from bio-optical drifters that were deployed in the Southern Ocean. A draft manuscript has now been prepared and is being revised. A second manuscript is also in preparation that explores the vector wind fields derived from NSCAT measurements. The HOT bio-optical mooring was recovered in December 1997. After retrieving the data, the sensor package was serviced and redeployed. We have begun preliminary analysis of these data, but we have only had the data for 3 weeks. However, all of the data were recovered, and there were no obvious anomalies. We will add second sensor package to the mooring when it is serviced next spring. In addition, Ricardo Letelier is funded as part of the SeaWiFS calibration/validation effort (through a subcontract from the University of Hawaii, Dr. John Porter), and he will be collecting bio-optical and fluorescence data as part of the HOT activity. This will provide additional in situ measurements for <span class="hlt">MODIS</span> validation. As noted in the previous quarterly report, we have been analyzing data from three bio-optical drifters that were deployed in the Southern Ocean in September 1996. We presented results on chlorophyll and drifter speed. For the 1998 Ocean Sciences meeting, a paper will be presented on</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2013AGUFM.A41C0078M','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2013AGUFM.A41C0078M"><span id="translatedtitle">Assessing <span class="hlt">MODIS</span> Macrophysical Cloud Property Uncertainties</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Maddux, B. C.; Ackerman, S. A.; Frey, R.; Holz, R.</p> <p>2013-12-01</p> <p>Cloud, being multifarious and ephemeral, is difficult to observe and quantify in a systematic way. Even basic terminology used to describe cloud observations is fraught with ambiguity in the scientific literature. Any observational technique, method, or platform will contain inherent and unavoidable measurement uncertainties. Quantifying these uncertainties in cloud observations is a complex task that requires an understanding of all aspects of the measurement. We will use cloud observations obtained from the Moderate Resolution Imaging Spectroradiameter(<span class="hlt">MODIS</span>) to obtain metrics of the uncertainty of its cloud observations. Our uncertainty analyses will contain two main components, 1) an attempt to create a bias or uncertainty with respect to active measurements from CALIPSO and 2) a relative uncertainty within the <span class="hlt">MODIS</span> cloud climatologies themselves. Our method will link uncertainty to the physical observation and its environmental/scene characteristics. Our aim is to create statistical uncertainties that are based on the cloud observational values, satellite view geometry, surface type, etc, for cloud amount and cloud top pressure. The <span class="hlt">MODIS</span> instruments on the NASA Terra and <span class="hlt">Aqua</span> satellites provide observations over a broad spectral range (36 bands between 0.415 and 14.235 micron) and high spatial resolution (250 m for two bands, 500 m for five bands, 1000 m for 29 bands), which the <span class="hlt">MODIS</span> cloud mask algorithm (MOD35) utilizes to provide clear/cloud determinations over a wide array of surface types, solar illuminations and view geometries. For this study we use the standard <span class="hlt">MODIS</span> products, MOD03, MOD06 and MOD35, all of which were obtained from the NASA Level 1 and Atmosphere Archive and Distribution System.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://www.ars.usda.gov/research/publications/Publications.htm?seq_no_115=306261','TEKTRAN'); return false;" href="http://www.ars.usda.gov/research/publications/Publications.htm?seq_no_115=306261"><span id="translatedtitle">Irrigation modeling with <span class="hlt">Aqua</span>Crop</span></a></p> <p><a target="_blank" href="http://www.ars.usda.gov/services/TekTran.htm">Technology Transfer Automated Retrieval System (TEKTRAN)</a></p> <p></p> <p></p> <p><span class="hlt">Aqua</span>Crop is a crop water productivity model developed by the Land and Water Division of UN-FAO. It simulates yield response to water of herbaceous crops, and is suited to address conditions where water is a key limiting factor in crop production. <span class="hlt">Aqua</span>Crop attempts to balance accuracy, simplicity, an...</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/20110007354','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20110007354"><span id="translatedtitle">Comparison of the <span class="hlt">MODIS</span> Collection 5 Multilayer Cloud Detection Product with CALIPSO</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Platnick, Steven; Wind, Gala; King, Michael D.; Holz, Robert E.; Ackerman, Steven A.; Nagle, Fred W.</p> <p>2010-01-01</p> <p>CALIPSO, launched in June 2006, provides global active remote sensing measurements of clouds and aerosols that can be used for validation of a variety of passive imager retrievals derived from instruments flying on the <span class="hlt">Aqua</span> spacecraft and other A-Train platforms. The most recent processing effort for the <span class="hlt">MODIS</span> Atmosphere Team, referred to as the Collection 5 scream, includes a research-level multilayer cloud detection algorithm that uses both thermodynamic phase information derived from a combination of solar and thermal emission bands to discriminate layers of different phases, as well as true layer separation discrimination using a moderately absorbing water vapor band. The multilayer detection algorithm is designed to provide a means of assessing the applicability of 1D cloud models used in the <span class="hlt">MODIS</span> cloud optical and microphysical product retrieval, which are generated at a 1 km resolution. Using pixel-level collocations of <span class="hlt">MODIS</span> <span class="hlt">Aqua</span>, CALIOP, we investigate the global performance of multilayer cloud detection algorithms (and thermodynamic phase).</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/20120009270','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20120009270"><span id="translatedtitle"><span class="hlt">Aqua</span>'s First 10 Years: An Overview</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Parkinson, Claire L.</p> <p>2012-01-01</p> <p>NASA's <span class="hlt">Aqua</span> spacecraft was launched at 2:55 a.m. on May 4, 2002, from Vandenberg Air Force Base in California, into a near-polar, sun-synchronous orbit at an altitude of 705 km. <span class="hlt">Aqua</span> carries six Earth-observing instruments to collect data on water in all its forms (liquid, vapor, and solid) and on a wide variety of additional Earth system variables (Parkinson 2003). The design lifetime for <span class="hlt">Aqua</span>'s prime mission was 6 years, and <span class="hlt">Aqua</span> is now well into its extended mission, approaching 10 years of successful operations. The <span class="hlt">Aqua</span> data have been used for hundreds of scientific studies and continue to be used for scientific discovery and numerous practical applications.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2013AGUFM.B41D0439O','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2013AGUFM.B41D0439O"><span id="translatedtitle">Landsat and <span class="hlt">MODIS</span> Fusion for Disturbance Analysis in New Zealand</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Owsley, B.; de Beurs, K.; Julian, J.</p> <p>2013-12-01</p> <p>Land management is a key driver of land change in many parts of the world. Activities such as livestock farming and timber production can have a dramatic impact on the environment and are often guided by local and regional policies. Evaluation of these impacts is particularly important in a country like New Zealand, where since 1991 political boundaries have largely coincided with environmental boundaries (catchments). In this study we look at the entire north island of New Zealand and identify disturbance trends at high spatial and temporal resolution using widely available remote sensing data, with the eventual goal of analyzing the effect of land management practices on local ecosystems. Existing remote sensing capabilities are limited in the type of analysis they allow. Free access to the entire Landsat archive provides a valuable resource for analyzing land change across large areas and extended time periods. Landsat images, at 30m spatial resolution, provide a useful tool for monitoring small changes in land cover; however, the 16-day temporal cycle, which is often lengthened considerably by cloud cover, limits the observation of short term changes that can result from disturbance events. The revisit cycle of the <span class="hlt">MODIS</span> sensors aboard Terra and <span class="hlt">Aqua</span> provides a surface <span class="hlt">reflectance</span> dataset at much higher temporal resolution, yet at 500m spatial resolution, it lacks the detail necessary to accurately track small changes in the landscape. A combination of the two products offers researchers the ideal tool for disturbance analysis. Here we utilize both Landsat TM/ETM surface <span class="hlt">reflectance</span> data and <span class="hlt">MODIS</span> Nadir BRDF-adjusted <span class="hlt">reflectance</span> (NBAR) covering the north island of New Zealand (13 Landsat path/rows) for the period 2000-2012. We calculate a disturbance index for both datasets based on normalized values of the Tasseled Cap transformation and then create a fused 8-day, 30m disturbance time series. We then investigate the time series to assess the subtle changes in</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2008AGUFMIN54A..02H','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2008AGUFMIN54A..02H"><span id="translatedtitle">Understanding the Differences Between AIRS, <span class="hlt">MODIS</span> and ASTER Land Surface Emissivity Products</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Hook, S.; Hulley, G.</p> <p>2008-12-01</p> <p>One of the key Earth Science Data Records identified by NASA is Land Surface Temperature and Emissivity (LST&E). LST&E data are key parameters in global climate change studies that involve climate modeling, ice dynamic analyses, surface-atmosphere interactions and land use, land cover change. The errors in retrievals of atmospheric temperature and moisture profiles from hyperspectral infrared radiances, such as those from the Atmospheric Infrared Sounder (AIRS) on NASA's <span class="hlt">Aqua</span> satellite, are strongly dependent on using constant or inaccurate surface emissivities, particularly over arid and semi-arid regions where the variation in emissivity is large, both spatially and spectrally. LST&E standard products are available from spaceborne sensors such as AIRS, <span class="hlt">MODIS</span> and ASTER at varying spatial, spectral, and temporal resolutions. Although these emissivity products represent the same measure, there are frequently discrepancies between the products associated with different scientific approaches used that need to be better understood. For example, ASTER provides LST&E data with the highest spatial resolution (90 m), compared with AIRS (50 km) and <span class="hlt">MODIS</span> (1 and 5 km). AIRS has the highest spectral sampling and both AIRS and <span class="hlt">MODIS</span> acquire data at much higher temporal frequencies (every 2-3 days) compared with ASTER (16 days). In this paper we present validation and intercomparisons of AIRS, <span class="hlt">MODIS</span> and ASTER gridded emissivity products over North America. <span class="hlt">MODIS</span> and ASTER data will be upsampled to the AIRS spatial resolution, and then compared to laboratory measured emissivities of in-situ rock/sand samples collected at ten validation sites in the Western USA during 2008. The directional hemispherical <span class="hlt">reflectance</span> of the in-situ samples are measured in the laboratory using a Nicolet Fourier Transform Interferometer (FTIR), converted to emissivity using Kirchoff's law, and convolving to the appropriate sensor's spectral response functions. We present here some of the first</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2014AGUFMIN13C3652P','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2014AGUFMIN13C3652P"><span id="translatedtitle">Development of an Algorithm Suite for <span class="hlt">MODIS</span> and VIIRS Cloud Data Record Continuity</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Platnick, S. E.; Holz, R.; Heidinger, A. K.; Ackerman, S. A.; Meyer, K.; Frey, R.; Wind, G.; Amarasinghe, N.</p> <p>2014-12-01</p> <p>The launch of Suomi NPP in the fall of 2011 began the next generation of the U.S. operational polar orbiting environmental observations. Similar to <span class="hlt">MODIS</span>, the VIIRS imager provides visible through IR observations at moderate spatial resolution with a 1330 LT equatorial crossing consistent with <span class="hlt">MODIS</span> on the <span class="hlt">Aqua</span> platform. However, unlike <span class="hlt">MODIS</span>, VIIRS lacks key water vapor and CO2 absorbing channels used by the <span class="hlt">MODIS</span> cloud algorithms for high cloud detection and cloud-top property retrievals (including emissivity), as well as multilayer cloud detection. In addition, there is a significant change in the spectral location of the 2.1 μm shortwave-infrared channel used by <span class="hlt">MODIS</span> for cloud microphysical retrievals. The climate science community will face an interruption in the continuity of key global cloud data sets once the NASA EOS Terra and <span class="hlt">Aqua</span> sensors cease operation. Given the instrument differences between <span class="hlt">MODIS</span> EOS and VIIRS S-NPP/JPSS, we discuss methods for merging the 14+ year <span class="hlt">MODIS</span> observational record with VIIRS/CrIS observations in order to generate cloud climate data record continuity across the observing systems. The main approach used by our team was to develop a cloud retrieval algorithm suite that is applied only to the common <span class="hlt">MODIS</span> and VIIRS spectral channels. The suite uses heritage algorithms that produce the existing <span class="hlt">MODIS</span> cloud mask (MOD35), <span class="hlt">MODIS</span> cloud optical and microphysical properties (MOD06), and NOAA AWG/CLAVR-x cloud-top property products. Global monthly results from this hybrid algorithm suite (referred to as MODAWG) will be shown. Collocated CALIPSO comparisons will be shown that can independently evaluate inter-instrument product consistency for a subset of the MODAWG datasets.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/cgi-bin/nph-data_query?bibcode=2015AGUFM.A21C0138M&link_type=ABSTRACT','NASAADS'); return false;" href="http://adsabs.harvard.edu/cgi-bin/nph-data_query?bibcode=2015AGUFM.A21C0138M&link_type=ABSTRACT"><span id="translatedtitle">Development of an Algorithm for <span class="hlt">MODIS</span> and VIIRS Cloud Optical Property Data Record Continuity</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Meyer, K.; Platnick, S. E.; Ackerman, S. A.; Heidinger, A. K.; Holz, R.; Wind, G.; Amarasinghe, N.; Marchant, B.</p> <p>2015-12-01</p> <p>The launch of Suomi NPP in the fall of 2011 began the next generation of U.S. operational polar orbiting environmental observations. Similar to <span class="hlt">MODIS</span>, the VIIRS imager provides visible through IR observations at moderate spatial resolution with a 1330 LT equatorial crossing consistent with <span class="hlt">MODIS</span> on the <span class="hlt">Aqua</span> platform. However, unlike <span class="hlt">MODIS</span>, VIIRS lacks key water vapor and CO2 absorbing channels used by the <span class="hlt">MODIS</span> cloud algorithms for high cloud detection and cloud-top property retrievals. In addition, there is a significant change in the spectral location of the 2.1μm shortwave-infrared channel used by <span class="hlt">MODIS</span> for cloud optical/microphysical retrievals. Given the instrument differences between <span class="hlt">MODIS</span> EOS and VIIRS S-NPP/JPSS, we discuss our adopted method for merging the 15+ year <span class="hlt">MODIS</span> observational record with VIIRS in order to generate cloud optical property data record continuity across the observing systems. The optical property retrieval code uses heritage algorithms that produce the existing <span class="hlt">MODIS</span> cloud optical and microphysical properties product (MOD06). As explained in other presentations submitted to this session, the NOAA AWG/CLAVR-x cloud-top property algorithm and a common <span class="hlt">MODIS</span>-VIIRS cloud mask feed into the optical property algorithm to account for the different channel sets of the two imagers. Data granule and aggregated examples for the current version of the algorithm will be shown.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2014AGUFM.A33A3149S','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2014AGUFM.A33A3149S"><span id="translatedtitle">Validation of <span class="hlt">MODIS</span> Total Precipitable Water Using Surface GPS Technology</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Serra, Y. L.; Fears, A. J.; Moker, J.</p> <p>2014-12-01</p> <p>In this research we validate estimates of atmospheric total precipitable water (TPW) from the <span class="hlt">MODIS</span> (Moderate Resolution Imaging Spectroradiometer) instruments onboard the Terra and <span class="hlt">Aqua</span> satellites using surface Global Positioning System (GPS) derived TPW collected at ten stations across northwest Mexico during the 2013 North American monsoon (NAM) season. The <span class="hlt">MODIS</span> Level 2 products provide TPW estimated from both the infrared (IR) and near-infrared (NIR) spectral bands and are available over the NAM region approximately twice per day. Our comparisons indicate that the correlations of Terra and <span class="hlt">Aqua</span> IR TPW with the GPS observations are all significant at the 95% confidence level, while the NIR correlations show little or no significance. The analysis also finds that Terra and <span class="hlt">Aqua</span> have significant seasonal biases with respect to the GPS for both the IR and NIR estimates at several locations, with the IR estimates showing better agreement than the NIR estimates. The dependence of the errors on elevation and time of overpass will be discussed to help identify contributing factors to the observed errors.</p> </li> </ol> <div class="pull-right"> <ul class="pagination"> <li><a href="#" onclick='return showDiv("page_1");'>«</a></li> <li><a href="#" onclick='return showDiv("page_12");'>12</a></li> <li><a href="#" onclick='return showDiv("page_13");'>13</a></li> <li class="active"><span>14</span></li> <li><a href="#" onclick='return showDiv("page_15");'>15</a></li> <li><a href="#" onclick='return showDiv("page_16");'>16</a></li> <li><a href="#" onclick='return showDiv("page_25");'>»</a></li> </ul> </div> </div><!-- col-sm-12 --> </div><!-- row --> </div><!-- page_14 --> <div id="page_15" class="hiddenDiv"> <div class="row"> <div class="col-sm-12"> <div class="pull-right"> <ul class="pagination"> <li><a href="#" onclick='return showDiv("page_1");'>«</a></li> <li><a href="#" onclick='return showDiv("page_13");'>13</a></li> <li><a href="#" onclick='return showDiv("page_14");'>14</a></li> <li class="active"><span>15</span></li> <li><a href="#" onclick='return showDiv("page_16");'>16</a></li> <li><a href="#" onclick='return showDiv("page_17");'>17</a></li> <li><a href="#" onclick='return showDiv("page_25");'>»</a></li> </ul> </div> </div> </div> <div class="row"> <div class="col-sm-12"> <ol class="result-class" start="281"> <li> <p><a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/20080013490','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20080013490"><span id="translatedtitle">Earth System Science Research Using Datra and Products from Terra, <span class="hlt">Aqua</span>, and ACRIM Satellites</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Hutchison, Keith D.</p> <p>2007-01-01</p> <p>The report describes the research conducted at CSR to extend <span class="hlt">MODIS</span> data and products to the applications required by users in the State of Texas. This research presented in this report was completed during the timeframe of August 2004 - December 31, 2007. However, since annual reports were filed in December 2005 and 2006, results obtained during calendar year 2007 are emphasized in the report. The stated goals of the project were to complete the fundamental research needed to create two types of new, Level 3 products for the air quality community in Texas from data collected by NASA s EOS Terra and <span class="hlt">Aqua</span> missions.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/20110010238','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20110010238"><span id="translatedtitle">Ten Years of Cloud Properties from <span class="hlt">MODIS</span>: Global Statistics and Use in Climate Model Evaluation</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Platnick, Steven E.</p> <p>2011-01-01</p> <p>The NASA Moderate Resolution Imaging Spectroradiometer (<span class="hlt">MODIS</span>), launched onboard the Terra and <span class="hlt">Aqua</span> spacecrafts, began Earth observations on February 24, 2000 and June 24,2002, respectively. Among the algorithms developed and applied to this sensor, a suite of cloud products includes cloud masking/detection, cloud-top properties (temperature, pressure), and optical properties (optical thickness, effective particle radius, water path, and thermodynamic phase). All cloud algorithms underwent numerous changes and enhancements between for the latest Collection 5 production version; this process continues with the current Collection 6 development. We will show example <span class="hlt">MODIS</span> Collection 5 cloud climatologies derived from global spatial . and temporal aggregations provided in the archived gridded Level-3 <span class="hlt">MODIS</span> atmosphere team product (product names MOD08 and MYD08 for <span class="hlt">MODIS</span> Terra and <span class="hlt">Aqua</span>, respectively). Data sets in this Level-3 product include scalar statistics as well as 1- and 2-D histograms of many cloud properties, allowing for higher order information and correlation studies. In addition to these statistics, we will show trends and statistical significance in annual and seasonal means for a variety of the <span class="hlt">MODIS</span> cloud properties, as well as the time required for detection given assumed trends. To assist in climate model evaluation, we have developed a <span class="hlt">MODIS</span> cloud simulator with an accompanying netCDF file containing subsetted monthly Level-3 statistical data sets that correspond to the simulator output. Correlations of cloud properties with ENSO offer the potential to evaluate model cloud sensitivity; initial results will be discussed.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/20110022975','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20110022975"><span id="translatedtitle">Results of <span class="hlt">MODIS</span> Band-to-Band Registration Characterization Using On-Orbit Lunar Observations</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Xiong, Xiaoxiong; Sun, Junqiang; Angal,Amit</p> <p>2011-01-01</p> <p>Since launch, lunar observations have been made regularly by both Terra and <span class="hlt">Aqua</span> <span class="hlt">MODIS</span> and used for a number of sensor calibration and characterization related applications, including radiometric stability monitoring, spatial characterization, optical leak and electronic cross-talk characterization, and calibration inter-comparison. <span class="hlt">MODIS</span> has 36 spectral bands with a total of 490 individual detectors. They are located on four focal plane assemblies (FPA). This paper focuses on the use of <span class="hlt">MODIS</span> lunar observations to characterize its band-to-band registration (BBR). In addition to BBR, the approach developed by the <span class="hlt">MODIS</span> Characterization Support Team (MCST) can be used to characterize <span class="hlt">MODIS</span> detector-to-detector registration (DDR). Long-term BBR results developed from this approach are presented and compared with that derived from a unique on-board calibrator (OBC). Results show that on-orbit changes of BBR have been very small for both Terra and <span class="hlt">Aqua</span> <span class="hlt">MODIS</span> and this approach can be applied to other remote sensing instruments.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2016EGUGA..1817822L','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2016EGUGA..1817822L"><span id="translatedtitle">New methods for reducing cloud obscuration based on combination products of <span class="hlt">MODIS</span> and AMSR2</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Li, Muyi; Pan, Yaozhong; Zhu, Xiufang; Yin, Heyang</p> <p>2016-04-01</p> <p>As one of the main sources for water availability in semi-arid mountain regions, snow melt provides runoff and water supply for the downstream population and is of great importance for both human and environmental systems. For this reason, snow data such as snow cover (SCA) and snow depth (SD) is especially important. Snow cover has been mapped using many remote sensors in the visible, near-infrared, thermal, and microwave wavelengths. Since 1966, optical remote sensors such as AVHRR, Landsat and <span class="hlt">MODIS</span> have obtained critically important data for observing the earth's snow cover. The Moderate Resolution Imaging Spectroradiometer (<span class="hlt">MODIS</span>) employed by Terra and <span class="hlt">Aqua</span> satellites provides spatially snow covered data with 500 m and daily temporal resolution. However the utility of the <span class="hlt">MODIS</span> snow-cover products is limited by cloud cover which causes gaps in the daily snow-cover map products. In this paper, we developed a new method in order to reduce cloud obscuration. This method includes four parts: A) Combining various <span class="hlt">MODIS</span> Terra and <span class="hlt">Aqua</span> products; B) Temporal and spatial filtering; C) Zonal snowline approach and D) Combining the product deriving from the above three parts and the AMSR2 passive microwave snow depth product (with a spatial resolution of 10 km). In part D, the consistency of two different data (optical remote sensing data with spatial resolution of 500 m and passive microwave remote sensing data with a spatial resolution of 10 km) was evaluated. This study was carried out for Qinghai Province located in northwestern part of China during 1st, October, 2013 to 31st, March, 2015. In order to evaluate the performance of the proposed methodology, 14 <span class="hlt">MODIS</span> snow cover product tiles (with cloud coverage less than 10%) were selected as possible "ground truth" data and cloud mask was generated for each tile randomly. The results show successful performances arising from the methods applied, which resulted in all cloud coverage being removed. The overall accuracy of</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/19980219479','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/19980219479"><span id="translatedtitle">[<span class="hlt">MODIS</span> Investigation</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Abbott, Mark R.</p> <p>1997-01-01</p> <p>We are responsible for the delivery of two at-launch products for AM-1: Fluorescence line height (FLH) and chlorophyll fluorescence efficiency (CFE). In our last report we had planned to combine the two separate algorithms into a single piece of code. However, after discussions with Bob Evans, it was decided that it was best to leave the two algorithms separate. They have been integrated into the MOCEAN processing system, and given their low computational requirements, it easier to keep them separate. In addition, there remain questions concerning the specific chlorophyll product that will be used for the CFE calculation. Presently, the CFE algorithm relies on the chlorophyll product produced by Ken Carder. This product is based on a <span class="hlt">reflectance</span> model, and is theoretically different than the chlorophyll product being provided by Dennis Clark (NOAA). These two products will be compared systematically in the coming months. If we decide to switch to the Clark product, then it will be simpler to modify the CFE algorithm if it remains separate from the FLH algorithm. Our focus for the next six months is to refine the quality flags that were delivered as part of the algorithm last summer. A description of these flags was provided to Evans for the MOCEAN processing system. A summary was included in the revised ATBD. Some of the flags depend on flags produced by the input products so coordination will be required.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2014AGUFM.A21F3094M','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2014AGUFM.A21F3094M"><span id="translatedtitle">Global and regional validation of the Collection 6 <span class="hlt">MODIS</span> dark target aerosol products, and comparison to Collection 5</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Munchak, L. A.; Levy, R. C.; Mattoo, S.</p> <p>2014-12-01</p> <p>The <span class="hlt">MODIS</span> Collection 6 (C6) dark targets aerosol algorithms include several updates, including multiple wind speed look up tables over ocean and improved sensor calibration. We analyze the entirety of the <span class="hlt">MODIS-Aqua</span> aerosol record against AERONET to characterize uncertainty in the products, and relate the new collection to the well-characterized Collection 5 (C5) products to understand specific improvements. Over land, ~70% of high quality AOD retrievals at 0.55 μm are within the C5 expected error bounds, which is comparable to C5; however, a slight overestimation of AOD at low optical depths and a slight underestimation at high optical depths that was observed in C5 has been eliminated in C6. The highest agreement with AERONET occurs in the Eastern U.S. and Europe. Regions with large surface <span class="hlt">reflectance</span>, such as the Western U.S., or higher aerosol loading, including much of Africa and South America, remain a challenge. Over ocean, the inclusion of wind speed in the surface characterization has removed a wind speed dependant bias, and globally, ~63% of high quality AOD retrievals at 0.55 μm are within the C5 expected error bounds. The dust outflow regions off the coast of Africa show the poorest agreement with AERONET. The aerosol products validate acceptably for science, though users should be aware of some regional biases we present in this work.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2011AGUFM.A53C0371A','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2011AGUFM.A53C0371A"><span id="translatedtitle"><span class="hlt">MODIS</span> Aerosol Optical Depth Bias Adjustment Using Machine Learning Algorithms</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Albayrak, A.; Wei, J. C.; Petrenko, M.; Lary, D. J.; Leptoukh, G. G.</p> <p>2011-12-01</p> <p>Over the past decade, global aerosol observations have been conducted by space-borne sensors, airborne instruments, and ground-base network measurements. Unfortunately, quite often we encounter the differences of aerosol measurements by different well-calibrated instruments, even with a careful collocation in time and space. The differences might be rather substantial, and need to be better understood and accounted for when merging data from many sensors. The possible causes for these differences come from instrumental bias, different satellite viewing geometries, calibration issues, dynamically changing atmospheric and the surface conditions, and other "regressors", resulting in random and systematic errors in the final aerosol products. In this study, we will concentrate on the subject of removing biases and the systematic errors from <span class="hlt">MODIS</span> (both Terra and <span class="hlt">Aqua</span>) aerosol product, using Machine Learning algorithms. While we are assessing our regressors in our system when comparing global aerosol products, the Aerosol Robotic Network of sun-photometers (AERONET) will be used as a baseline for evaluating the <span class="hlt">MODIS</span> aerosol products (Dark Target for land and ocean, and Deep Blue retrieval algorithms). The results of bias adjustment for <span class="hlt">MODIS</span> Terra and <span class="hlt">Aqua</span> are planned to be incorporated into the AeroStat Giovanni as part of the NASA ACCESS funded AeroStat project.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/cgi-bin/nph-data_query?bibcode=2016SPIE.9881E..1XM&link_type=ABSTRACT','NASAADS'); return false;" href="http://adsabs.harvard.edu/cgi-bin/nph-data_query?bibcode=2016SPIE.9881E..1XM&link_type=ABSTRACT"><span id="translatedtitle"><span class="hlt">MODIS</span> on-orbit thermal emissive bands lifetime performance</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Madhavan, Sriharsha; Wu, Aisheng; Chen, Na; Xiong, Xiaoxiong</p> <p>2016-05-01</p> <p>MODerate resolution Imaging Spectroradiometer (<span class="hlt">MODIS</span>), a leading heritage sensor in the fleet of Earth Observing System for the National Aeronautics and Space Administration (NASA) is in space orbit on two spacecrafts. They are the Terra (T) and <span class="hlt">Aqua</span> (A) platforms. Both instruments have successfully continued to operate beyond the 6 year design life time, with the T-<span class="hlt">MODIS</span> currently functional beyond 15 years and the A-<span class="hlt">MODIS</span> operating beyond 13 years respectively. The <span class="hlt">MODIS</span> sensor characteristics include a spectral coverage from 0.41 μm - 14.4 μm, of which wavelengths ranging from 3.7 μm - 14. 4 μm cover the thermal infrared region also referred to as the Thermal Emissive Bands (TEBs). The TEBs is calibrated using a v-grooved BlackBody (BB) whose temperature measurements are traceable to the National Institute of Standards and Technology temperature scales. The TEBs calibration based on the onboard BB is extremely important for its high radiometric fidelity. In this paper, we provide a complete characterization of the lifetime instrument performance of both <span class="hlt">MODIS</span> instruments in terms of the sensor gain, the Noise Equivalent difference Temperature, key instrument telemetry such as the BB lifetime trends, the instrument temperature trends, the Cold Focal Plane telemetry and finally, the total assessed calibration uncertainty of the TEBs.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2015SPIE.9639E..10L','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2015SPIE.9639E..10L"><span id="translatedtitle">Assessment of <span class="hlt">MODIS</span> on-orbit spatial performance</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Link, Daniel; Xiong, Xiaoxiong J.; Wang, Zhipeng</p> <p>2015-10-01</p> <p>The Terra and <span class="hlt">Aqua</span> satellites are part of NASA's Earth Observing System and both satellites host a nearly-identical Moderate Resolution Imaging Spectroradiometer (<span class="hlt">MODIS</span>). Of the 36 <span class="hlt">MODIS</span> spectral bands mounted among four Focal Plane Assemblies (FPAs) two have a 250 meter spatial resolution at nadir. Five bands have a spatial resolution of 500 meters, while the remaining bands make observations at 1 kilometer resolution. <span class="hlt">MODIS</span> is equipped with a suite of onboard calibrators to track on-orbit changes in key sensor performance parameters. The Spectro-Radiometric Calibration Assembly (SRCA) contains a calibration source that allows on-orbit assessment of <span class="hlt">MODIS</span> spatial performance, providing information on current band-to-band registration (BBR), FPA-to-FPA registration (FFR), detector-to-detector registration (DDR), modulation transfer function (MTF), and instantaneous field-of-view (IFOV). In this paper, we present the methodology of the on-orbit spatial calibrations using SRCA and the results of these key spatial parameters. The <span class="hlt">MODIS</span> spatial characteristics, measured on-orbit, are compared against design specifications and pre-launch measurements.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/20040171197','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20040171197"><span id="translatedtitle"><span class="hlt">MODIS</span> Snow and Sea Ice Products</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Hall, Dorothy K.; Riggs, George A.; Salomonson, Vincent V.</p> <p>2004-01-01</p> <p>In this chapter, we describe the suite of Earth Observing System (EOS) Moderate-Resolution Imaging Spectroradiometer (<span class="hlt">MODIS</span>) Terra and <span class="hlt">Aqua</span> snow and sea ice products. Global, daily products, developed at Goddard Space Flight Center, are archived and distributed through the National Snow and Ice Data Center at various resolutions and on different grids useful for different communities Snow products include binary snow cover, snow albedo, and in the near future, fraction of snow in a 5OO-m pixel. Sea ice products include ice extent determined with two different algorithms, and sea ice surface temperature. The algorithms used to develop these products are described. Both the snow and sea ice products, available since February 24,2000, are useful for modelers. Validation of the products is also discussed.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://ntrs.nasa.gov/search.jsp?R=20080002214&hterms=mineral&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D80%26Ntt%3Dmineral','NASA-TRS'); return false;" href="http://ntrs.nasa.gov/search.jsp?R=20080002214&hterms=mineral&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D80%26Ntt%3Dmineral"><span id="translatedtitle">Assessment of <span class="hlt">MODIS</span>-Derived Visible and Near-IR Aerosol Optical Properties and their Spatial Variability in the Presence of Mineral Dust</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Redemann, J.; Zhang, Q.; Schmid, B.; Russell, P. B.; Livingston, J. M.; Jonsson, H.; Remer, L. A.</p> <p>2006-01-01</p> <p>Mineral dust aerosol is among the most difficult aerosol species to measure quantitatively from space. In this paper, we evaluate <span class="hlt">MODIS</span> retrievals of spectral aerosol optical depth (AOD) from the visible to the near-IR off the US West Coast using measurements taken by the NASA Ames Airborne Tracking Sunphotometer, AATS-14, during the EVE (Extended-<span class="hlt">MODIS</span>-lambda Validation Experiment, 2004) campaign in April of 2004. In EVE, a total of 35 and 49 coincident over-ocean suborbital measurements at the nominal level-2 retrieval scale of 10 km x 10 km were collected for Terra and <span class="hlt">Aqua</span>, respectively. For <span class="hlt">MODIS</span>-Terra about 80% of the AOD retrievals are within the estimated uncertainty, DELTA tau = plus or minus 0.03 plus or minus 0.05 tau; this is true for both the visible (here defined to include 466-855 nm) and near-IR (here defined to include 1243-2119 nm) retrievals. For <span class="hlt">MODIS-Aqua</span> about 45% of the AOD retrievals are within DELTA tau = plus or minus 0.03 plus or minus 0.05 tau; the fraction of near-IR retrievals that fall within this uncertainty range is about 27%. We found an rms difference of 0.71 between the sunphotometer snd <span class="hlt">MODIS-Aqua</span> estimates of the visible (553-855 nm) Angstrom exponent, while the <span class="hlt">MODIS</span>-Terra visible Angstrom exponents show an rms difference of only 0.29 when compared to AATS. The cause of the differences in performance between <span class="hlt">MODIS</span>-Terra and <span class="hlt">MODIS-Aqua</span> could be instrument calibration and needs to be explored further. The spatial variability of AOD between retrieval boxes as derived by <span class="hlt">MODIS</span> is generally larger than that indicated by the sunphotometer data.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/20120011581','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20120011581"><span id="translatedtitle">Recent Progress on Deep Blue Aerosol Algorithm as Applied TO <span class="hlt">MODIS</span>, SEA WIFS, and VIIRS, and Their Intercomparisons with Ground Based and Other Satellite Measurements</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Hsu, N. Christina; Bettenhausen, Corey; Sawyer, Andrew; Tsay, Si-Chee</p> <p>2012-01-01</p> <p>The impact of natural and anthropogenic sources of aerosols has gained increasing attention from scientific communities in recent years. Indeed, tropospheric aerosols not only perturb radiative energy balance by interacting with solar and terrestrial radiation, but also by changing cloud properties and lifetime. Furthermore, these anthropogenic and natural air particles, once generated over the source regions, can be transported out of the boundary layer into the free troposphere and can travel thousands of kilometers across oceans and continents resulting in important biogeochemical impacts on the ecosystem. With the launch of SeaWiFS in 1997, Terra/<span class="hlt">MODIS</span> in 1999, and <span class="hlt">Aqua/MODIS</span> in 2002, high quality comprehensive aerosol climatology is becoming feasible for the first time. As a result of these unprecedented data records, studies of the radiative and biogeochemical effects due to tropospheric aerosols are now possible. In this talk, we will demonstrate how this newly available SeaWiFS/<span class="hlt">MODIS</span> aerosol climatology can provide an important piece of puzzles in reducing the uncertainty of estimated climatic forcing due to aerosols. We will start with the global distribution of aerosol loading and their variabilities over both land and ocean on short- and long-term temporal scales observed over the last decade. The recent progress made in Deep Blue aerosol algorithm on improving accuracy of these Sea WiFS / <span class="hlt">MODIS</span> aerosol products in particular over land will be discussed. The impacts on quantifying physical and optical processes of aerosols over source regions of adding the Deep Blue products of aerosol properties over bright-<span class="hlt">reflecting</span> surfaces into Sea WiFS / <span class="hlt">MODIS</span> as well as VIIRS data suite will also be addressed. We will also show the intercomparison results of SeaWiFS/<span class="hlt">MODIS</span> retrieved aerosol optical thickness with data from ground based AERONET sunphotometers over land and ocean as well as with other satellite measurements. The trends observed in global aerosol</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://ntrs.nasa.gov/search.jsp?R=20080037745&hterms=new+product+development&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D50%26Ntt%3Dnew%2Bproduct%2Bdevelopment','NASA-TRS'); return false;" href="http://ntrs.nasa.gov/search.jsp?R=20080037745&hterms=new+product+development&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D50%26Ntt%3Dnew%2Bproduct%2Bdevelopment"><span id="translatedtitle">Production and Distribution of NASA <span class="hlt">MODIS</span> Remote Sensing Products</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Wolfe, Robert</p> <p>2007-01-01</p> <p>The two Moderate Resolution Imaging Spectroradiometer (<span class="hlt">MODIS</span>) instruments on-board NASA's Earth Observing System (EOS) Terra and <span class="hlt">Aqua</span> satellites make key measurements for understanding the Earth's terrestrial ecosystems. Global time-series of terrestrial geophysical parameters have been produced from <span class="hlt">MODIS</span>/Terra for over 7 years and for <span class="hlt">MODIS/Aqua</span> for more than 4 1/2 years. These well calibrated instruments, a team of scientists and a large data production, archive and distribution systems have allowed for the development of a new suite of high quality product variables at spatial resolutions as fine as 250m in support of global change research and natural resource applications. This talk describes the <span class="hlt">MODIS</span> Science team's products, with a focus on the terrestrial (land) products, the data processing approach and the process for monitoring and improving the product quality. The original <span class="hlt">MODIS</span> science team was formed in 1989. The team's primary role is the development and implementation of the geophysical algorithms. In addition, the team provided feedback on the design and pre-launch testing of the instrument and helped guide the development of the data processing system. The key challenges the science team dealt with before launch were the development of algorithms for a new instrument and provide guidance of the large and complex multi-discipline processing system. Land, Ocean and Atmosphere discipline teams drove the processing system requirements, particularly in the area of the processing loads and volumes needed to daily produce geophysical maps of the Earth at resolutions as fine as 250 m. The processing system had to handle a large number of data products, large data volumes and processing loads, and complex processing requirements. Prior to <span class="hlt">MODIS</span>, daily global maps from heritage instruments, such as Advanced Very High Resolution Radiometer (AVHRR), were not produced at resolutions finer than 5 km. The processing solution evolved into a combination of</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/20140005684','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20140005684"><span id="translatedtitle">The <span class="hlt">Aqua</span>-Planet Experiment (APE): CONTROL SST Simulation</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Blackburn, Michael; Williamson, David L.; Nakajima, Kensuke; Ohfuchi, Wataru; Takahashi, Yoshiyuki O.; Hayashi, Yoshi-Yuki; Nakamura, Hisashi; Ishiwatari, Masaki; Mcgregor, John L.; Borth, Hartmut; Wirth, Volkmar; Frank, Helmut; Bechtold, Peter; Wedi, Nils P.; Tomita, Hirofumi; Satoh, Masaki; Zhao, Ming; Held, Isaac M.; Suarez, Max J.; Lee, Myong-In; Watanabe, Masahiro; Kimoto, Masahide; Liu, Yimin; Wang, Zaizhi; Molod, Andrea M.; Rajendran, Kavirajan; Kotoh, Akio; Stratton, Rachel</p> <p>2013-01-01</p> <p>Climate simulations by 16 atmospheric general circulation models (AGCMs) are compared on an <span class="hlt">aqua</span>-planet, a water-covered Earth with prescribed sea surface temperature varying only in latitude. The idealised configuration is designed to expose differences in the circulation simulated by different models. Basic features of the <span class="hlt">aqua</span>-planet climate are characterised by comparison with Earth. The models display a wide range of behaviour. The balanced component of the tropospheric mean flow, and mid-latitude eddy covariances subject to budget constraints, vary relatively little among the models. In contrast, differences in damping in the dynamical core strongly influence transient eddy amplitudes. Historical uncertainty in modelled lower stratospheric temperatures persists in APE.Aspects of the circulation generated more directly by interactions between the resolved fluid dynamics and parameterized moist processes vary greatly. The tropical Hadley circulation forms either a single or double inter-tropical convergence zone (ITCZ) at the equator, with large variations in mean precipitation. The equatorial wave spectrum shows a wide range of precipitation intensity and propagation characteristics. Kelvin mode-like eastward propagation with remarkably constant phase speed dominates in most models. Westward propagation, less dispersive than the equatorial Rossby modes, dominates in a few models or occurs within an eastward propagating envelope in others. The mean structure of the ITCZ is related to precipitation variability, consistent with previous studies.The <span class="hlt">aqua</span>-planet global energy balance is unknown but the models produce a surprisingly large range of top of atmosphere global net flux, dominated by differences in shortwave <span class="hlt">reflection</span> by clouds. A number of newly developed models, not optimised for Earth climate, contribute to this. Possible reasons for differences in the optimised models are discussed.The <span class="hlt">aqua</span>-planet configuration is intended as one component of an</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2015AGUFM.A32C..02M','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2015AGUFM.A32C..02M"><span id="translatedtitle">Determining the accuracies of sea-surface temperatures derived from measurements of <span class="hlt">MODIS</span> and VIIRS</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Minnett, P. J.; Kilpatrick, K. A.; Podesta, G. P.; Izaguirre, M.; Williams, E.; Walsh, S.</p> <p>2015-12-01</p> <p>The appropriate application of sea-surface temperatures (SSTs) derived from <span class="hlt">MODIS</span> and VIIRS requires knowledge of the errors and uncertainties of the SST fields. The accuracies of the SSTs are determined by comparison with independent measurements, usually derived from drifting and moored buoys, and ship-board radiometers. By using similar cloud detection and clear-sky atmospheric correction algorithms to derived SST from both <span class="hlt">MODIS</span>'s on Terra and <span class="hlt">Aqua</span>, and the VIIRS on S-NPP a consistent time series of SSTs can be derived from the first useful Terra <span class="hlt">MODIS</span> data in 2000 to the present, and by using the same approach to assess their accuracies, a consistent set of errors and uncertainties can also be derived. The presentation will provide a summary of recently modified algorithms used to derive SSTs from the <span class="hlt">MODIS</span>'s and VIIRS, and discuss the accuracies of the derived fields, including recent improvements to the VIIRS atmospheric correction algorithm to reduce the effects of instrumental artifacts.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2013EGUGA..1510810P','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2013EGUGA..1510810P"><span id="translatedtitle">Sensitivity of cloud retrieval statistics to algorithm choices: Lessons learned from <span class="hlt">MODIS</span> product development</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Platnick, Steven; Ackerman, Steven; King, Michael; Zhang, Zhibo; Wind, Galina</p> <p>2013-04-01</p> <p>Cloud detection algorithms search for measurement signatures that differentiate a cloud-contaminated or "not-clear" pixel from the clear-sky background. These signatures can be spectral, textural or temporal in nature. The magnitude of the difference between the cloud and the background must exceed a threshold value for the pixel to be classified having a not-clear FOV. All detection algorithms employ multiple tests ranging across some portion of the solar <span class="hlt">reflectance</span> and/or infrared spectrum. However, a cloud is not a single, uniform object, but rather has a distribution of optical thickness and morphology. As a result, problems can arise when the distributions of cloud and clear-sky background characteristics overlap, making some test results indeterminate and/or leading to some amount of detection misclassification. Further, imager cloud retrieval statistics are highly sensitive to how a pixel identified as not-clear by a cloud mask is determined to be useful for cloud-top and optical retrievals based on 1-D radiative models. This presentation provides an overview of the different 'choices' algorithm developers make in cloud detection algorithms and the impact on regional and global cloud amounts and fractional coverage, cloud type and property distributions. Lessons learned over the course of the <span class="hlt">MODIS</span> cloud product development history are discussed. As an example, we will focus on the 1km <span class="hlt">MODIS</span> Collection 5 cloud optical retrieval algorithm (product MOD06/MYD06 for Terra and <span class="hlt">Aqua</span>, respectively) which removed pixels associated with cloud edges as defined by immediate adjacency to clear FOV <span class="hlt">MODIS</span> cloud mask (MOD35/MYD35) pixels as well as ocean pixels with partly cloudy elements in the 250m <span class="hlt">MODIS</span> cloud mask - part of the so-called Clear Sky Restoral algorithm. The Collection 6 algorithm attempts retrievals for these two types of partly cloudy pixel populations, but allows a user to isolate or filter out the populations. Retrieval sensitivities for these</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2014EGUGA..16.9581U','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2014EGUGA..16.9581U"><span id="translatedtitle">Contribution of <span class="hlt">MODIS</span> Derived Snow Cover Satellite Data into Artificial Neural Network for Streamflow Estimation</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Uysal, Gokcen; Arda Sorman, Ali; Sensoy, Aynur</p> <p>2014-05-01</p> <p>Contribution of snowmelt and correspondingly snow observations are highly important in mountainous basins for modelers who deal with conceptual, physical or soft computing models in terms of effective water resources management. Long term archived continuous data are needed for appropriate training and testing of data driven approaches like artificial neural networks (ANN). Data is scarce at the upper elevations due to the difficulty of installing sufficient automated SNOTEL stations; thus in literatures many attempts are made on the rainfall dominated basins for streamflow estimation studies. On the other hand, optical satellites can easily detect snow because of its high <span class="hlt">reflectance</span> property. <span class="hlt">MODIS</span> (Moderate Resolution Imaging Spectroradiometer) satellite that has two platforms (Terra and <span class="hlt">Aqua</span>) provides daily and 8-daily snow images for different time periods since 2000, therefore snow cover data (SCA) may be useful as an input layer for ANN applications. In this study, a multi-layer perceptron (MLP) model is trained and tested with precipitation, temperature, radiation, previous day discharges as well as <span class="hlt">MODIS</span> daily SCA data. The weights and biases are optimized with fastest and robust Levenberg-Marquardt backpropagation algorithm. <span class="hlt">MODIS</span> snow cover images are removed from cloud coverage using certain filtering techniques. The Upper Euphrates River Basin in eastern part of Turkey (10 250 km2) is selected as the application area since it is fed by snowmelt approximately 2/3 of total annual volume during spring and early summer. Several input models and ANN structures are investigated to see the effect of the contributions using 10 years of data (2001-2010) for training and validation. The accuracy of the streamflow estimations is checked with statistical criteria (coefficient of determination, Nash-Sutcliffe model efficiency, root mean square error, mean absolute error) and the results seem to improve when SCA data is introduced. Furthermore, a forecast study is</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/cgi-bin/nph-data_query?bibcode=2013AGUFM.A31K..08M&link_type=ABSTRACT','NASAADS'); return false;" href="http://adsabs.harvard.edu/cgi-bin/nph-data_query?bibcode=2013AGUFM.A31K..08M&link_type=ABSTRACT"><span id="translatedtitle">Bias Correction of high resolution <span class="hlt">MODIS</span> Aerosol Optical Depth in urban areas using the Dragon AERONET Network</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Malakar, N. K.; Atia, A.; Gross, B.; Moshary, F.; Ahmed, S. A.; Lary, D. J.</p> <p>2013-12-01</p> <p>Aerosol optical depth (AOD) is widely used parameter used to quantify aerosol abundance. Satellite retrievals of aerosols over land is fundamentally more complex than aerosol retrieval over oceans. Due to wide coverage and the extensive validation the Moderate Resolution Imaging Spectroradiometer (<span class="hlt">MODIS</span>), on board the Terra and <span class="hlt">Aqua</span> satellites is the workhorse instrument used to retrieve AOD from space. However, satellite algorithms of AOD are extremely complex and depends strongly on sun/view geometry, spectral surface albedo, aerosol model assumptions and surface heterogeneity. This issue becomes even more severe when considering the new <span class="hlt">MODIS</span> 3 km aerosol retrieval products within version 6. To assess satellite retrievals of these high resolution 3 km products, we use the summer 2011 Dragon AERONET data to assess accuracy as well as major retrieval bias that can occur in <span class="hlt">MODIS</span> measurements. In this study, we explore in detail the factors that can drive these biases statistically. As discussed above, our considers multiple conditions such as surface <span class="hlt">reflectivity</span> at various wavelengths, solar and sensor zenith angles, the solar and sensor azimuth, scattering angles as well as meteorological factors and aerosol type (angstrom coefficient) etc which are used inputs are used to train neural network in regression mode to compensate for biases against the Dragon AERONET AOD values. In particular, we confirm the results of previous studies where the land cover (urban fraction) appears to be a strong factor in AOD bias and develop a NN estimator which includes land cover directly. The algorithm will be tested not only in the Baltimore/Washington area but assessed in the general North East US where urban biases in the NYC area have been previously identified.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/20040016318','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20040016318"><span id="translatedtitle">Earth Observing System (EOS) <span class="hlt">Aqua</span> Launch and Early Mission Attitude Support Experiences</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Tracewell, D.; Glickman, J.; Hashmall, J.; Natanson, G.; Sedlak, J.</p> <p>2003-01-01</p> <p>The Earth Observing System (EOS) <span class="hlt">Aqua</span> satellite was successfully launched on May 4,2002. <span class="hlt">Aqua</span> is the second in the series of EOS satellites. EOS is part of NASA s Earth Science Enterprise Program, whose goals are to advance the scientific understanding of the Earth system. <span class="hlt">Aqua</span> is a three-axis stabilized, Earth-pointing spacecraft in a nearly circular, sun-synchronous orbit at an altitude of 705 km. The Goddard Space Flight Center (GSFC) Flight Dynamics attitude team supported all phases of the launch and early mission. This paper presents the main results and lessons learned during this period, including: real-time attitude mode transition support, sensor calibration, onboard computer attitude validation, response to spacecraft emergencies, postlaunch attitude analyses, and anomaly resolution. In particular, Flight Dynamics support proved to be invaluable for successful Earth acquisition, fine-point mode transition, and recognition and correction of several anomalies, including support for the resolution of problems observed with the <span class="hlt">MODIS</span> instrument.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2016JGRD..121.2299O','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2016JGRD..121.2299O"><span id="translatedtitle">Radiative effects of global <span class="hlt">MODIS</span> cloud regimes</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Oreopoulos, Lazaros; Cho, Nayeong; Lee, Dongmin; Kato, Seiji</p> <p>2016-03-01</p> <p>We update previously published Moderate Resolution Imaging Spectroradiometer (<span class="hlt">MODIS</span>) global cloud regimes (CRs) using the latest <span class="hlt">MODIS</span> cloud retrievals in the Collection 6 data set. We implement a slightly different derivation method, investigate the composition of the regimes, and then proceed to examine several aspects of CR radiative appearance with the aid of various radiative flux data sets. Our results clearly show that the CRs are radiatively distinct in terms of shortwave, longwave, and their combined (total) cloud radiative effect. We show that we can clearly distinguish regimes based on whether they radiatively cool or warm the atmosphere, and thanks to radiative heating profiles, to discern the vertical distribution of cooling and warming. Terra and <span class="hlt">Aqua</span> comparisons provide information about the degree to which morning and afternoon occurrences of regimes affect the symmetry of CR radiative contribution. We examine how the radiative discrepancies among multiple irradiance data sets suffering from imperfect spatiotemporal matching depend on CR and whether they are therefore related to the complexity of cloud structure, its interpretation by different observational systems, and its subsequent representation in radiative transfer calculations.</p> </li> </ol> <div class="pull-right"> <ul class="pagination"> <li><a href="#" onclick='return showDiv("page_1");'>«</a></li> <li><a href="#" onclick='return showDiv("page_13");'>13</a></li> <li><a href="#" onclick='return showDiv("page_14");'>14</a></li> <li class="active"><span>15</span></li> <li><a href="#" onclick='return showDiv("page_16");'>16</a></li> <li><a href="#" onclick='return showDiv("page_17");'>17</a></li> <li><a href="#" onclick='return showDiv("page_25");'>»</a></li> </ul> </div> </div><!-- col-sm-12 --> </div><!-- row --> </div><!-- page_15 --> <div id="page_16" class="hiddenDiv"> <div class="row"> <div class="col-sm-12"> <div class="pull-right"> <ul class="pagination"> <li><a href="#" onclick='return showDiv("page_1");'>«</a></li> <li><a href="#" onclick='return showDiv("page_14");'>14</a></li> <li><a href="#" onclick='return showDiv("page_15");'>15</a></li> <li class="active"><span>16</span></li> <li><a href="#" onclick='return showDiv("page_17");'>17</a></li> <li><a href="#" onclick='return showDiv("page_18");'>18</a></li> <li><a href="#" onclick='return showDiv("page_25");'>»</a></li> </ul> </div> </div> </div> <div class="row"> <div class="col-sm-12"> <ol class="result-class" start="301"> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2011AMTD....4.6861V','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2011AMTD....4.6861V"><span id="translatedtitle">Analysis of co-located <span class="hlt">MODIS</span> and CALIPSO observations near clouds</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Várnai, T.; Marshak, A.</p> <p>2011-11-01</p> <p>This paper aims at helping synergistic studies in combining data from different satellites for gaining new insights into two critical yet poorly understood aspects of anthropogenic climate change, aerosol-cloud interactions and aerosol radiative effects. In particular, the paper examines the way cloud information from the <span class="hlt">MODIS</span> imager can refine our perceptions based on CALIOP lidar measurements about the systematic aerosol changes that occur near clouds. The statistical analysis of a yearlong dataset of co-located global maritime observations from the <span class="hlt">Aqua</span> and CALIPSO satellites reveals that <span class="hlt">MODIS</span>'s multispectral imaging ability can greatly help the interpretation of CALIOP observations. The results show that imagers on <span class="hlt">Aqua</span> and CALIPSO yield very similar pictures, and that the discrepancies - due mainly to wind drift and differences in view angle - do not significantly hinder aerosol measurements near clouds. By detecting clouds outside the CALIOP track, <span class="hlt">MODIS</span> reveals that clouds are usually closer to clear areas than CALIOP data alone would suggest. The paper finds statistical relationships between the distances to clouds in <span class="hlt">MODIS</span> and CALIOP data, and proposes a rescaling approach to statistically account for the impact of clouds outside the CALIOP track even when <span class="hlt">MODIS</span> cannot reliably detect low clouds, for example at night or over sea ice. Finally, the results show that the typical distance to clouds depends on both cloud coverage and cloud type, and accordingly varies with location and season. The global median distance to clouds in maritime clear-sky areas is in the 4-5 km range.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/20110011127','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20110011127"><span id="translatedtitle"><span class="hlt">MODIS</span> Science Algorithms and Data Systems Lessons Learned</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Wolfe, Robert E.; Ridgway, Bill L.; Patt, Fred S.; Masuoka, Edward J.</p> <p>2009-01-01</p> <p>For almost 10 years, standard global products from NASA's Earth Observing System s (EOS) two Moderate Resolution Imaging Spectroradiometer (<span class="hlt">MODIS</span>) sensors are being used world-wide for earth science research and applications. This paper discusses the lessons learned in developing the science algorithms and the data systems needed to produce these high quality data products for the earth sciences community. Strong science team leadership and communication, an evolvable and scalable data system, and central coordination of QA and validation activities enabled the data system to grow by two orders of magnitude from the initial at-launch system to the current system able to reprocess data from both the Terra and <span class="hlt">Aqua</span> missions in less than a year. Many of the lessons learned from <span class="hlt">MODIS</span> are already being applied to follow-on missions.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/20040171588','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20040171588"><span id="translatedtitle">Application of <span class="hlt">MODIS</span>-Derived Active Fire Radiative Energy to Fire Disaster and Smoke Pollution Monitoring</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Ichoku, Charles; Kaufman, Yoram J.; Hao, Wei Min; Habib, Shahid</p> <p>2004-01-01</p> <p>The radiative energy emitted by large fires and the corresponding smoke aerosol loading are simultaneously measured from the <span class="hlt">MODIS</span> sensor from both the Terra and <span class="hlt">Aqua</span> satellites. Quantitative relationships between the rates of emission of fire radiative energy and smoke are being developed for different fire-prone regions of the globe. Preliminary results are presented. When fully developed, the system will enable the use of <span class="hlt">MODIS</span> direct broadcast fire data for near real-time monitoring of fire strength and smoke emission as well as forecasting of fire progression and smoke dispersion, several hours to a few days in advance.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=3337546','PMC'); return false;" href="http://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=3337546"><span id="translatedtitle">Terra and <span class="hlt">Aqua</span>: new data for epidemiology and public health</span></a></p> <p><a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pmc">PubMed Central</a></p> <p>Tatem, Andrew J.; Goetz, Scott J.; Hay, Simon I.</p> <p>2012-01-01</p> <p>Earth-observing satellites have only recently been exploited for the measurement of environmental variables of relevance to epidemiology and public health. Such work has relied on sensors with spatial, spectral and geometric constraints that have allowed large-area questions associated with the epidemiology of vector-borne diseases to be addressed. Moving from pretty maps to pragmatic control tools requires a suite of satellite-derived environmental data of higher fidelity, spatial resolution, spectral depth and at similar temporal resolutions to existing meteorological satellites. Information derived from sensors onboard the next generation of moderate-resolution Earth-observing sensors may provide the key. The <span class="hlt">MODIS</span> and ASTER sensors onboard the Terra and <span class="hlt">Aqua</span> platforms provide substantial improvements in spatial resolution, number of spectral channels, choices of bandwidths, radiometric calibration and a much-enhanced set of pre-processed and freely available products. These sensors provide an important advance in moderate-resolution remote sensing and the data available to those concerned with improving public health. PMID:22545030</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://ntrs.nasa.gov/search.jsp?R=20060013201&hterms=classification+ecosystems&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D90%26Ntt%3Dclassification%2Becosystems','NASA-TRS'); return false;" href="http://ntrs.nasa.gov/search.jsp?R=20060013201&hterms=classification+ecosystems&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D90%26Ntt%3Dclassification%2Becosystems"><span id="translatedtitle">Spatially Complete Global Surface Albedos Derived from Terra/<span class="hlt">MODIS</span> Data</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>King, Michael D.; Moody, Eric G.; Schaaf, Crystal B.; Platnick, Steven</p> <p>2006-01-01</p> <p>Spectral land surface albedo is an important parameter for describing the radiative properties of the Earth. Accordingly it <span class="hlt">reflects</span> the consequences of natural and human interactions, such as anthropogenic, meteorological, and phenological effects, on global and local climatological trends. Consequently, albedos are integral parts in a variety of research areas, such as general circulation models (GCMs), energy balance studies, modeling of land use and land use change, and biophysical, oceanographic, and meteorological studies. , Over five years of land surface anisotropy, diffuse bihemispherical (white-sky) albedo and direct beam directional hemispherical (black-sky) albedo from observations acquired by the <span class="hlt">MODIS</span> instruments aboard NASA s Terra and <span class="hlt">Aqua</span> satellite platforms have provided researchers with unprecedented spatial, spectral, and temporal information on the land surface s radiative characteristics. However, roughly 30% of the global land surface, on an annual equal-angle basis, is obscured due to persistent and transient cloud cover, while another 207% is obscured due to ephemeral and seasonal snow effects. This precludes the MOD43B3 albedo products from being directly used in some remote sensing and ground-based applications, climate models, and global change research projects. To provide researchers with the requisite spatially complete global snow-free land surface albedo dataset, an ecosystem-dependent temporal interpolation technique was developed to fill missing or lower quality data and snow covered values from the official MOD43B3 dataset with geophysically realistic values. The method imposes pixel-level and local regional ecosystem-dependent phenological behavior onto retrieved pixel temporal data in such a way as to maintain pixel-level spatial and spectral detail and integrity. The phenological curves are derived from statistics based on the <span class="hlt">MODIS</span> MOD12Q1 IGBP land cover classification product geolocated with the MOD43B3 data.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/20150001429','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20150001429"><span id="translatedtitle"><span class="hlt">MODIS</span> Cloud Microphysics Product (MOD_PR06OD) Data Collection 6 Updates</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Wind, Gala; Platnick, Steven; King, Michael D.</p> <p>2014-01-01</p> <p>The <span class="hlt">MODIS</span> Cloud Optical and Microphysical Product (MOD_PR060D) for Data Collection 6 has entered full scale production. <span class="hlt">Aqua</span> reprocessing is almost completed and Terra reprocessing will begin shortly. Unlike previous collections, the CHIMAERA code base allows for simultaneous processing for multiple sensors and the operational CHIMAERA 6.0.76 stream is also available for VIIRS and SEVIRI sensors and for our E-MAS airborne platform.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/cgi-bin/nph-data_query?bibcode=2015AGUFM.B32D..02D&link_type=ABSTRACT','NASAADS'); return false;" href="http://adsabs.harvard.edu/cgi-bin/nph-data_query?bibcode=2015AGUFM.B32D..02D&link_type=ABSTRACT"><span id="translatedtitle">Urban Area Monitoring using <span class="hlt">MODIS</span> Time Series Data</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Devadiga, S.; Sarkar, S.; Mauoka, E.</p> <p>2015-12-01</p> <p>Growing urban sprawl and its impact on global climate due to urban heat island effects has been an active area of research over the recent years. This is especially significant in light of rapid urbanization that is happening in some of the first developing nations across the globe. But so far study of urban area growth has been largely restricted to local and regional scales, using high to medium resolution satellite observations, taken at distinct time periods. In this presentation we propose a new approach to detect and monitor urban area expansion using long time series of <span class="hlt">MODIS</span> data. This work characterizes data points using a vector of several annual metrics computed from the <span class="hlt">MODIS</span> 8-day and 16-day composite L3 data products, at 250M resolution and over several years and then uses a vector angle mapping classifier to detect and segment the urban area. The classifier is trained using a set of training points obtained from a reference vector point and polygon pre-filtered using the <span class="hlt">MODIS</span> VI product. This work gains additional significance, given that, despite unprecedented urban growth since 2000, the area covered by the urban class in the <span class="hlt">MODIS</span> Global Land Cover (MCD12Q1, MCDLCHKM and MCDLC1KM) product hasn't changed since the launch of Terra and <span class="hlt">Aqua</span>. The proposed approach was applied to delineate the urban area around several cities in Asia known to have maximum growth in the last 15 years. Results were verified using high resolution Landsat data.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/20110007001','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20110007001"><span id="translatedtitle">Detailed Evaluation of <span class="hlt">MODIS</span> Fire Radiative Power Measurements</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Ichoku, Charles</p> <p>2010-01-01</p> <p>Satellite remote sensing is providing us tremendous opportunities to measure the fire radiative energy (FRE) release rate or power (FRP) from open biomass burning, which affects many vegetated regions of the world on a seasonal basis. Knowledge of the biomass burning characteristics and emission source strengths of different (particulate and gaseous) smoke constituents is one of the principal ingredients upon which the assessment, modeling, and forecasting of their distribution and impacts depend. This knowledge can be gained through accurate measurement of FRP, which has been shown to have a direct relationship with the rates of biomass consumption and emissions of major smoke constituents. Over the last decade or so, FRP has been routinely measured from space by both the <span class="hlt">MODIS</span> sensors aboard the polar orbiting Terra and <span class="hlt">Aqua</span> satellites, and the SEVIRI sensor aboard the Meteosat Second Generation (MSG) geostationary satellite. During the last few years, FRP has been gaining recognition as an important parameter for facilitating the development of various scientific studies relating to the quantitative characterization of biomass burning and their emissions. Therefore, we are conducting a detailed analysis of the FRP products from <span class="hlt">MODIS</span> to characterize the uncertainties associated with them, such as those due to the <span class="hlt">MODIS</span> bow-tie effects and other factors, in order to establish their error budget for use in scientific research and applications. In this presentation, we will show preliminary results of the <span class="hlt">MODIS</span> FRP data analysis, including comparisons with airborne measurements.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2015JGRD..12012237M','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2015JGRD..12012237M"><span id="translatedtitle">Investigating the impact of haze on <span class="hlt">MODIS</span> cloud detection</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Mao, Feiyue; Duan, Miaomiao; Min, Qilong; Gong, Wei; Pan, Zengxin; Liu, Guangyi</p> <p>2015-12-01</p> <p>The cloud detection algorithm for passive sensors is usually based on a fuzzy logic system with thresholds determined from previous observations. In recent years, haze and high aerosol concentrations with high aerosol optical depth (AOD) occur frequently in China and may critically impact the accuracy of the Moderate Resolution Imaging Spectroradiometer (<span class="hlt">MODIS</span>) cloud detection. Thus, we comprehensively explore this impact by comparing the results from <span class="hlt">MODIS/Aqua</span> (passive sensor), Cloud-Aerosol Lidar with Orthogonal Polarization/CALIPSO (lidar sensor), and Cloud Profiling Radar/CloudSat (microwave sensor) of the A-Train suite of instruments using an averaged AOD as an index for an aerosol concentration value. Case studies concerning the comparison of the three sensors indicate that <span class="hlt">MODIS</span> cloud detection is reduced during haze events. In addition, statistical studies show that an increase in AOD creates an increase in the percentage of uncertain flags and a decrease in hit rate, a consistency index between consecutive sets of cloud retrievals. On average, AOD values lower than 0.1 give hit rate values up to 80.0% and uncertainty values lower than 16.8%, while AOD values greater than 1.0 reduce the hit rate below to 66.6% and increase the percentage of uncertain flags up to 46.6%. Therefore, we can conclude that the ability of <span class="hlt">MODIS</span> cloud detection is weakened by large concentrations of aerosols. This suggests that use of the <span class="hlt">MODIS</span> cloud mask, and derived higher-level products, in situations with haze requires caution. Further improvement of this retrieval algorithm is desired as haze studies based on <span class="hlt">MODIS</span> products are of great interest in a number of related fields.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://ntrs.nasa.gov/search.jsp?R=20040016045&hterms=lille&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D70%26Ntt%3Dlille','NASA-TRS'); return false;" href="http://ntrs.nasa.gov/search.jsp?R=20040016045&hterms=lille&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D70%26Ntt%3Dlille"><span id="translatedtitle">The <span class="hlt">MODIS</span> Aerosol Algorithm, Products, Validation and Applications</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Remer, L. A.; Kaufman, Y. J.; Tanre, D.</p> <p>2003-01-01</p> <p>The MODerate resolution Imaging Spectroradiometer (<span class="hlt">MODIS</span>) currently aboard both the Terra and <span class="hlt">Aqua</span> satellites produces a suite of products designed to characterize global aerosol distribution, optical thickness and particle size. Never before has a space-borne instrument been able to provide such detailed information, complementing field and modeling efforts to produce a comprehensive picture of aerosol characteristics. The three years of Terra-<span class="hlt">MODIS</span> data have been validated by comparing with co-located AERONET observations of aerosol optical thickness and derivations of aerosol size parameters. Some 8000 comparison points located at 133 AERONET sites around the globe show that the <span class="hlt">MODIS</span> aerosol optical thickness retrievals are accurate to within the pre-launch expectations. <span class="hlt">MODIS</span>-derived size parameters are also compared with AERONET retrievals and found to agree well for fine-mode dominated aerosol regimes. Aerosol regimes dominated by dust aerosol are less accurate, attributed to what is thought to be nonsphericity. Errors due to nonsphericity will be reduced by introducing a new set of empirical phase functions, derived without any assumptions of particle shape. The major innovation that <span class="hlt">MODIS</span> bring to the field of remote sensing of aerosol is the measure of particle size and the separation of finemode and coarsemode dominated aerosol regimes. Particle size can separate finemode man-made aerosols created during combustion, from larger natural aerosols originating from salt spray or wind erosion. This separation allows for the calculation of aerosol radiative effect and the estimation of the man-made aerosol radiative forcing. <span class="hlt">MODIS</span> can also be used in regional studies of aerosol-cloud interaction that affect the global radiative and hydrological cycles.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/20110006352','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20110006352"><span id="translatedtitle">Results and Lessons from a Decade of Terra <span class="hlt">MODIS</span> On-Orbit Spectral Characterization</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Xiong, X.; Choi, T.; Che, N.; Wang, Z.; Dodd, J.</p> <p>2010-01-01</p> <p>Since its launch in December 1999, the NASA EOS Terra <span class="hlt">MODIS</span> has successfully operated for more than a decade. <span class="hlt">MODIS</span> 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, <span class="hlt">MODIS</span> 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 <span class="hlt">MODIS</span> on-orbit spectral performance. This paper briefly describes SRCA on-orbit operation and calibration activities; it presents decade-long spectral characterization results for Terra <span class="hlt">MODIS</span> 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 <span class="hlt">MODIS</span> on-orbit spectral characterization have and will continue to benefit its successor, <span class="hlt">Aqua</span> <span class="hlt">MODIS</span>, and other future missions.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/cgi-bin/nph-data_query?bibcode=2014AGUFM.B11A0003M&link_type=ABSTRACT','NASAADS'); return false;" href="http://adsabs.harvard.edu/cgi-bin/nph-data_query?bibcode=2014AGUFM.B11A0003M&link_type=ABSTRACT"><span id="translatedtitle">Multiangular Contributions for Discriminate Seasonal Structural Changes in the Amazon Rainforest Using <span class="hlt">MODIS</span> MAIAC Data</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Moura, Y. M.; Hilker, T.; Galvão, L. S.; Santos, J. R.; Lyapustin, A.; Sousa, C. H. R. D.; McAdam, E.</p> <p>2014-12-01</p> <p>The sensitivity of the Amazon rainforests to climate change has received great attention by the scientific community due to the important role that this vegetation plays in the global carbon, water and energy cycle. The spatial and temporal variability of tropical forests across Amazonia, and their phenological, ecological and edaphic cycles are still poorly understood. The objective of this work was to infer seasonal and spatial variability of forest structure in the Brazilian Amazon based on anisotropy of multi-angle satellite observations. We used observations from the Moderate Resolution Imaging Spectroradiometer (<span class="hlt">MODIS</span>/Terra and <span class="hlt">Aqua</span>) processed by a new Multi-Angle Implementation Atmospheric Correction Algorithm (MAIAC) to investigate how multi-angular spectral response from satellite imagery can be used to analyze structural variability of Amazon rainforests. We calculated differences acquired from forward and backscatter <span class="hlt">reflectance</span> by modeling the bi-directional <span class="hlt">reflectance</span> distribution function to infer seasonal and spatial changes in vegetation structure. Changes in anisotropy were larger during the dry season than during the wet season, suggesting intra-annual changes in vegetation structure and density. However, there were marked differences in timing and amplitude depending on forest type. For instance differences between <span class="hlt">reflectance</span> hotspot and darkspot showed more anisotropy in the open Ombrophilous forest than in the dense Ombrophilous forest. Our results show that multi-angle data can be useful for analyzing structural differences in various forest types and for discriminating different seasonal effects within the Amazon basin. Also, multi-angle data could help solve uncertainties about sensitivity of different tropical forest types to light versus rainfall. In conclusion, multi-angular information, as expressed by the anisotropy of spectral <span class="hlt">reflectance</span>, may complement conventional studies and provide significant improvements over approaches that</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2001AGUFMOS52A0517K','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2001AGUFMOS52A0517K"><span id="translatedtitle"><span class="hlt">MODIS</span> Ocean Color, SST and Primary Productivity Products at the NASA Goddard Earth Sciences DAAC</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Koziana, J.; Leptoukh, G.; Savtchenko, A.; Serafino, G.; Sharma, A. K.</p> <p>2001-12-01</p> <p>The Goddard Earth Science (GES) Distributed Active Archive Center (DAAC) plays a major role in enabling basic scientific research and providing access to scientific data for the user community through the ingest, processing, archive and distribution of <span class="hlt">MODIS</span> data. <span class="hlt">MODIS</span> is part of the instrument package on the Terra (formally AM-1) satellite that was launched on December 18. 1999. Global scale ocean products are derived from many of the 36 different wavelengths measured by the <span class="hlt">MODIS</span>/Terra instrument and are archived at a rate of about 230 GB/day. This paper will provide a description of the <span class="hlt">MODIS</span> Ocean data products and associated geophysical parameters, data access, data availability and tools. The full suite of ocean products is grouped into three categories: ocean color, SST and primary productivity. The amount of <span class="hlt">MODIS</span> ocean data being archived at the DAAC will increase dramatically in the near future when the data from the <span class="hlt">MODIS</span> instrument onboard the <span class="hlt">Aqua</span> (formally PM-1) spacecraft begins transmission. This will result in a significant increase in the volume of ocean data being ingested, archived and distributed at the GES DAAC. The current suite of products will be generated for both Terra and <span class="hlt">Aqua</span>. In addition, joint Terra/<span class="hlt">Aqua</span> ocean products will be derived. The challenge, to distribute such large volumes of data to the ocean community, is achieved through a combination of GES DAAC Hierarchical Search and Order Tool known as, WHOM, and EOS Data Gateway (EDG) World Wide Web (WWW) interfaces and an FTP site that contains samples of <span class="hlt">MODIS</span> data. The <span class="hlt">MODIS</span> Data Support Team (MDST) continues the tradition of quality support at the GES DAAC for the ocean color data from CZCS and SeaWiFS by providing expert assistance to users in accessing data products, information on visualization tools, documentation for data products and formats (HDF-EOS), information on the scientific content of products and metadata. Visit the MDST website at http://daac.gsfc.nasa.gov/CAMPAIGN_DOCS/<span class="hlt">MODIS</span>/index.html</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://eosweb.larc.nasa.gov/project/ceres/es4_aqua-xtrk_ed3_table','SCIGOV-ASDC'); return false;" href="https://eosweb.larc.nasa.gov/project/ceres/es4_aqua-xtrk_ed3_table"><span id="translatedtitle">ES4 <span class="hlt">Aqua</span>-Xtrk Ed3</span></a></p> <p><a target="_blank" href="http://eosweb.larc.nasa.gov/">Atmospheric Science Data Center </a></p> <p></p> <p>2016-06-08</p> <p>... Order:  Reverb   Reverb Tutorial Order Data:  Reverb:  Order Data Guide Documents:  ... for Terra and <span class="hlt">Aqua</span>; Edition2 for TRMM) are approved for science publications.  Additional Info:  a SCAR-B ...</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2013AGUFM.A44B..04A','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2013AGUFM.A44B..04A"><span id="translatedtitle"><span class="hlt">Modis</span> Bits: when a Byte Isn't Enough</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Ackerman, S. A.; Frey, R.; Holz, R.</p> <p>2013-12-01</p> <p>Assessments of the final results of the Moderate Resolution Imaging Spectrometer (<span class="hlt">MODIS</span>) cloud mask have been studied and published. In this presentation, we present an assessment of the individual and group tests using the bit output structure of the <span class="hlt">MODIS</span> cloud mask algorithm. The <span class="hlt">MODIS</span>) on the NASA Terra and <span class="hlt">Aqua</span> satellites provides an unprecedented opportunity for earth remote sensing. Its broad spectral range (36 bands between 0.415-14.235 microns), high spatial resolution (250 m for two bands, 500 m for 5 bands, 1000 m for 29 bands), frequent observations of polar regions (28 times a day), and low thermal band instrument noise (roughly 0.1 K for a 300 K scene) provide a number of possibilities for improving cloud detection. <span class="hlt">MODIS</span> scans a swath width sufficient for providing global coverage every two days from a polar-orbiting, sun-synchronous platform at an altitude of 705 km. The <span class="hlt">MODIS</span> products, including MOD021KM, MOD03 and the cloud mask (MOD35), were obtained from the NASA Goddard Space Flight Center Distributed Active Archive Center (GDAAC). The <span class="hlt">MODIS</span> cloud mask algorithm includes several domains defined according to latitude, surface type and solar illumination, including land, water, snow/ice, desert, and coast for both day and night. A series of spectral tests is applied to identify the presence of clouds. There are several groups of tests, with differing numbers of tests in each group depending on the domain. A clear-sky confidence level ranging from 1 (high) to 0 (low) is returned for each test. The minimum confidence from all tests within a group is taken to be representative of that group. The Nth root of the product of all the group confidences (Q) determines the final confidence, where N is the number of groups. A fused data set of the Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) onboard NASA's Cloud Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO; data retrieved from the NASA CALIOPSO DAAC) and observations</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/20040055392','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20040055392"><span id="translatedtitle">Land Surface Temperature Measurements from EOS <span class="hlt">MODIS</span> Data</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Wan, Zheng-Ming</p> <p>2004-01-01</p> <p>This report summarizes the accomplishments made by the <span class="hlt">MODIS</span> LST (Land-Surface Temperature) group at University of California, Santa Barbara, under NASA Contract. Version 1 of the <span class="hlt">MODIS</span> Land-Surface Temperature Algorithm Theoretical Basis Document (ATBD) was reviewed in June 1994, version 2 reviewed in November 1994, version 3.1 in August 1996, and version 3.3 updated in April 1999. Based on the ATBD, two LST algorithms were developed, one is the generalized split-window algorithm and another is the physics-based day/night LST algorithm. These two LST algorithms were implemented into the production generation executive code (PGE 16) for the daily standard <span class="hlt">MODIS</span> LST products at level-2 (MODII-L2) and level-3 (MODIIA1 at 1 km resolution and MODIIB1 at 5km resolution). PGE codes for 8-day 1 km LST product (MODIIA2) and the daily, 8-day and monthly LST products at 0.05 degree latitude/longitude climate model grids (CMG) were also delivered. Four to six field campaigns were conducted each year since 2000 to validate the daily LST products generated by PGE16 and the calibration accuracies of the <span class="hlt">MODIS</span> TIR bands used for the LST/emissivity retrieval from versions 2-4 of Terra <span class="hlt">MODIS</span> data and versions 3-4 of <span class="hlt">Aqua</span> <span class="hlt">MODIS</span> data. Validation results from temperature-based and radiance-based methods indicate that the <span class="hlt">MODIS</span> LST accuracy is better than 1 C in most clear-sky cases in the range from -10 to 58 C. One of the major lessons learn from multi- year temporal analysis of the consistent V4 daily Terra <span class="hlt">MODIS</span> LST products in 2000-2003 over some selected target areas including lakes, snow/ice fields, and semi-arid sites is that there are variable numbers of cloud-contaminated LSTs in the <span class="hlt">MODIS</span> LST products depending on surface elevation, land cover types, and atmospheric conditions. A cloud-screen scheme with constraints on spatial and temporal variations in LSTs was developed to remove cloud-contaminated LSTs. The 5km LST product was indirectly validated through comparisons to</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://ntrs.nasa.gov/search.jsp?R=20120010373&hterms=Asters&qs=N%3D0%26Ntk%3DAll%26Ntx%3Dmode%2Bmatchall%26Ntt%3DAsters','NASA-TRS'); return false;" href="http://ntrs.nasa.gov/search.jsp?R=20120010373&hterms=Asters&qs=N%3D0%26Ntk%3DAll%26Ntx%3Dmode%2Bmatchall%26Ntt%3DAsters"><span id="translatedtitle">On-Orbit Spatial Characterization of <span class="hlt">MODIS</span> with ASTER Aboard the Terra Spacecraft</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Xie, Yong; Xiong, Xiaoxiong</p> <p>2011-01-01</p> <p>This letter presents a novel approach for on-orbit characterization of MODerate resolution Imaging Spectroradiometer (<span class="hlt">MODIS</span>) band-to-band registration (BBR) using Advanced Spaceborne Thermal Emission and <span class="hlt">Reflection</span> Radiometer (ASTER) aboard the Terra spacecraft. The spatial resolution of ASTER spectral bands is much higher than that of <span class="hlt">MODIS</span>, making it feasible to characterize <span class="hlt">MODIS</span> on-orbit BBR using their simultaneous observations. The ground target selected for on-orbit <span class="hlt">MODIS</span> BBR characterization in this letter is a water body, which is a uniform scene with high signal contrast relative to its neighbor areas. A key step of this approach is to accurately localize the measurements of each <span class="hlt">MODIS</span> band in an ASTER measurement plane coordinate (AMPC). The ASTER measurements are first interpolated and aggregated to simulate the measurements of each <span class="hlt">MODIS</span> band. The best measurement match between ASTER and each <span class="hlt">MODIS</span> band is obtained when the measurement difference reaches its weighted minimum. The position of each <span class="hlt">MODIS</span> band in the AMPC is then used to calculate the BBR. The results are compared with those derived from <span class="hlt">MODIS</span> onboard Spectro-Radiometric Calibration Assembly. They are in good agreement, generally less than 0.1 <span class="hlt">MODIS</span> pixel. This approach is useful for other sensors without onboard spatial characterization capability. Index Terms Advanced Spaceborne Thermal Emission and <span class="hlt">Reflection</span> Radiometer (ASTER), band-to-band registration (BBR), MODerate resolution Imaging Spectroradiometer (<span class="hlt">MODIS</span>), spatial characterization.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2001AGUSM...U21A24D','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2001AGUSM...U21A24D"><span id="translatedtitle">The <span class="hlt">MODIS</span> Reprojection Tool</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Dwyer, J.; Weiss, J.; Schmidt, G.; Logar, T.; Burrel, R.; Stubbendieck, G.; Rishea, J.; Misterek, B.; Jia, S.; Heuser, K.</p> <p>2001-05-01</p> <p>A software tool has been developed to reproject and reformat Moderate Resolution Imaging Spectroradiometer (<span class="hlt">MODIS</span>) level-3 science data products in order to ease their use with commercial-off-the-shelf software applications. The <span class="hlt">MODIS</span> instrument onboard NASA's Terra satellite collects mesurements of the Earth's lands, oceans, atmosphere, and cryosphere that are used to study Earth system processes and the impacts of human interactions with the planet's environment. The USGS Earth Resources Observation Systems (EROS) Data Center (EDC) serves as the Land Processes Distributed Active Archive Center (DAAC) in support of NASA's Earth Observing System (EOS) Data and Information System (EOSDIS). The EDC DAAC archive and distributes the <span class="hlt">MODIS</span> land science data products and provides support services to the users of these data. A second <span class="hlt">MODIS</span> instrument, scheduled for launch in late 2001, will yield a secnd suite of product types identical to those generated from the Terra <span class="hlt">MODIS</span>. The <span class="hlt">MODIS</span> land products are distributed in the hierarchical data format (HDF-EOS) which is the common data format distributed by the EOSDIS. Many of the <span class="hlt">MODIS</span> land products are distributed as geophysical or biophysical parameters formatted as numerical arrays in the Integerized Sinusoidal (ISIN) projection. Neither the HDF-EOS format nor the ISIN projection are broadly supported by the types of applications software commonly used by the land science community. The EDC DAAC and the South Dakota School of Mines and Technology Department of Computer Sciences collaborated to develop a software tool that would reproject and reformat the data to enhance the ease of use of these <span class="hlt">MODIS</span> products. The <span class="hlt">MODIS</span> Reprojection Tool (MRT) enables a user to perform various combinations of the following functions: read HDF-EOS file formats; view metadata; process selective subsets of the data; reproject and resample data to different output projections and grid spacing; and generate alternative file formats to HDF</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/20080039625','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20080039625"><span id="translatedtitle">An Emerging Global Aerosol Climatology from the <span class="hlt">MODIS</span> Satellite Sensors</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Remer, Lorraine A.; Kleidman, Richard G.; Levy, Robert C.; Kaufman, Yoram J.; Tanre, Didier; Mattoo, Shana; Martins, J. Vandelei; Ichoku, Charles; Koren, Ilan; Hongbin, Yu; Holben, Brent N.</p> <p>2008-01-01</p> <p>The recently released Collection 5 <span class="hlt">MODIS</span> aerosol products provide a consistent record of the Earth's aerosol system. Comparison with ground-based AERONET observations of aerosol optical depth (AOD) we find that Collection 5 <span class="hlt">MODIS</span> aerosol products estimate AOD to within expected accuracy more than 60% of the time over ocean and more than 72% of the time over land. This is similar to previous results for ocean, and better than the previous results for land. However, the new Collection introduces a 0.01 5 offset between the Terra and <span class="hlt">Aqua</span> global mean AOD over ocean, where none existed previously. <span class="hlt">Aqua</span> conforms to previous values and expectations while Terra is high. The cause of the offset is unknown, but changes to calibration are a possible explanation. We focus the climatological analysis on the better understood <span class="hlt">Aqua</span> retrievals. We find that global mean AOD at 550 nm over oceans is 0.13 and over land 0.19. AOD in situations with 80% cloud fraction are twice the global mean values, although such situations occur only 2% of the time over ocean and less than 1% of the time over land. There is no drastic change in aerosol particle size associated with these very cloudy situations. Regionally, aerosol amounts vary from polluted areas such as East Asia and India, to the cleanest regions such as Australia and the northern continents. In almost all oceans fine mode aerosol dominates over dust, except in the tropical Atlantic downwind of the Sahara and in some months the Arabian Sea.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://ntrs.nasa.gov/search.jsp?R=20120002594&hterms=Cirrus+clouds&qs=N%3D0%26Ntk%3DAll%26Ntx%3Dmode%2Bmatchall%26Ntt%3D%2528Cirrus%2Bclouds%2529','NASA-TRS'); return false;" href="http://ntrs.nasa.gov/search.jsp?R=20120002594&hterms=Cirrus+clouds&qs=N%3D0%26Ntk%3DAll%26Ntx%3Dmode%2Bmatchall%26Ntt%3D%2528Cirrus%2Bclouds%2529"><span id="translatedtitle">Utilizing the <span class="hlt">MODIS</span> 1.38 micrometer Channel for Cirrus Cloud Optical Thickness Retrievals: Algorithm and Retrieval Uncertainties</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Meyer, Kerry; Platnick, Steven</p> <p>2010-01-01</p> <p>The cloud products from the Moderate Resolution Imaging Spectroradiometers (<span class="hlt">MODIS</span>) on Terra and <span class="hlt">Aqua</span> have been widely used within the atmospheric research community. The retrieval algorithms, however, oftentimes have difficulty detecting and retrieving thin cirrus, due to sensitivities to surface <span class="hlt">reflectance</span>. Conversely, the 1.38 micron channel, located within a strong water vapor absorption band, is quite useful for detecting thin cirrus clouds since the signal from the surface can be blocked or substantially attenuated by the absorption of atmospheric water vapor below cirrus. This channel, however, suffers from nonnegligible attenuation due to the water vapor located above and within the cloud layer. Here we provide details of a new technique pairing the 1.38 micron and 1.24 micron channels to estimate the above/in-cloud water vapor attenuation and to subsequently retrieve thin cirrus optical thickness (tau) from attenuation-corrected 1.38 p.m <span class="hlt">reflectance</span> measurements. In selected oceanic cases, this approach is found to increase cirrus retrievals by up to 38% over MOD06. For these cases, baseline 1.38 micron retrieval uncertainties are estimated to be between 15 and 20% for moderately thick cirrus (tau > 1), with the largest error source being the unknown cloud effective particle radius, which is not retrieved with the described technique. Uncertainties increase to around 90% for the thinnest clouds (tau < 0.5) where instrument and surface uncertainties dominate.</p> </li> </ol> <div class="pull-right"> <ul class="pagination"> <li><a href="#" onclick='return showDiv("page_1");'>«</a></li> <li><a href="#" onclick='return showDiv("page_14");'>14</a></li> <li><a href="#" onclick='return showDiv("page_15");'>15</a></li> <li class="active"><span>16</span></li> <li><a href="#" onclick='return showDiv("page_17");'>17</a></li> <li><a href="#" onclick='return showDiv("page_18");'>18</a></li> <li><a href="#" onclick='return showDiv("page_25");'>»</a></li> </ul> </div> </div><!-- col-sm-12 --> </div><!-- row --> </div><!-- page_16 --> <div id="page_17" class="hiddenDiv"> <div class="row"> <div class="col-sm-12"> <div class="pull-right"> <ul class="pagination"> <li><a href="#" onclick='return showDiv("page_1");'>«</a></li> <li><a href="#" onclick='return showDiv("page_15");'>15</a></li> <li><a href="#" onclick='return showDiv("page_16");'>16</a></li> <li class="active"><span>17</span></li> <li><a href="#" onclick='return showDiv("page_18");'>18</a></li> <li><a href="#" onclick='return showDiv("page_19");'>19</a></li> <li><a href="#" onclick='return showDiv("page_25");'>»</a></li> </ul> </div> </div> </div> <div class="row"> <div class="col-sm-12"> <ol class="result-class" start="321"> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2010AGUFMIN21C1344C','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2010AGUFMIN21C1344C"><span id="translatedtitle">Ground-based vicarious radiometric calibration of Landsat 7 ETM+ and Terra <span class="hlt">MODIS</span> using an automated test site</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Czapla-Myers, J.; Leisso, N.</p> <p>2010-12-01</p> <p>The Remote Sensing Group at the University of Arizona has operated the Radiometric Calibration Test Site (RadCaTS) at Railroad Valley, Nevada, since 2004. It is an approach to ground-based vicarious calibration that does not require on-site personnel to make surface and atmospheric measurements during a satellite overpass. It was originally developed in 2002 in an attempt to increase the amount of data collected throughout the year while maintaining the accuracy of in-situ measurements. RadCaTS currently consists of four ground-viewing radiometers to measure surface <span class="hlt">reflectance</span>, a Cimel sun photometer to make atmospheric measurements, and a weather station to measure ambient conditions. The data from these instruments are used in MODTRAN 5 to determine the top-of-atmosphere (TOA) spectral radiance for a given overpass time, and the results are compared to the sensor under test. The work presented here describes the RadCaTS instrumentation suite and automated processing scheme used to determine the surface <span class="hlt">reflectance</span> and TOA spectral radiance. The instruments used to measure surface and atmospheric properties are presented, followed by a discussion of their spatial layout and their radiometric calibration. The RadCaTS ground-based results are compared to those from <span class="hlt">Aqua</span> and Terra <span class="hlt">MODIS</span> overpasses in 2008, and Landsat 7 ETM+ overpasses in 2009.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2009AIPC.1100..105D','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2009AIPC.1100..105D"><span id="translatedtitle">Surface Albedo Assessment in Clear Sky and Dense Smoke Atmospheres Using a Shortwave Radiation Stochastic Model and <span class="hlt">MODIS</span> 1B Image</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>de Souza, Juarez D.; Ceballos, Juan C.; da Silva, Bernardo B.</p> <p>2009-03-01</p> <p>The surface albedo, which is a fundamental parameter in the estimation of the radiation balance, corresponds to the <span class="hlt">reflectance</span> integrated in the solar spectrum. It can be obtained through satellite images that have great spatial coverage. A stochastic model of two-flux, presented by Ceballos [1] and developed by Souza and Ceballos [2], is used to establish a direct relationship between the <span class="hlt">reflectance</span> of the surface and the radiance measured by <span class="hlt">MODIS-Terra/Aqua</span> sensor. The propagation of radiation, in the solar spectrum from 0.3 to 3.0 μm, is described by an scheme of 16 layers. In such scheme, it is obtained the necessary parameters to establish the radiation balance in the top of the atmosphere. The optical properties of the atmospheric layers are defined by aerosol, ozone and water vapor. In this way, to determine the surface albedo, it is considered that the radiance originated from the system earth-atmosphere, measured by the satellite, is isotropic. A simple adjustment factor is introduced to compensate anisotropic and multiple <span class="hlt">reflections</span> effects between the surface and the atmosphere. An application for Amazonian region in conditions of low and high aerosol load due to smoke caused by forest burning, is presented. The results show similarity in the assessed surface <span class="hlt">reflectance</span>, with and without burning in the region.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://www.ars.usda.gov/research/publications/Publications.htm?seq_no_115=276026','TEKTRAN'); return false;" href="http://www.ars.usda.gov/research/publications/Publications.htm?seq_no_115=276026"><span id="translatedtitle">Forest structure and aboveground biomass in the southwestern United States from <span class="hlt">MODIS</span> and MISR</span></a></p> <p><a target="_blank" href="http://www.ars.usda.gov/services/TekTran.htm">Technology Transfer Automated Retrieval System (TEKTRAN)</a></p> <p></p> <p></p> <p>Red band bidirectional <span class="hlt">reflectance</span> factor data from the NASA MODerate resolution Imaging Spectroradiometer (<span class="hlt">MODIS</span>) acquired over the southwestern United States were interpreted through a simple geometric–optical (GO) canopy <span class="hlt">reflectance</span> model to provide maps of fractional crown cover (dimensionless),...</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/20160006433','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20160006433"><span id="translatedtitle">Cloud Properties of CERES-<span class="hlt">MODIS</span> Edition 4 and CERES-VIIRS Edition 1</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Sun-Mack, Sunny; Minnis, Patrick; Chang, Fu-Lung; Hong, Gang; Arduini, Robert; Chen, Yan; Trepte, Qing; Yost, Chris; Smith, Rita; Brown, Ricky; Chu, Churngwei; Heckert, Elizabeth; Gibson, Sharon; Heck, Patrick W.</p> <p>2015-01-01</p> <p>The Clouds and Earth's Radiant Energy System (CERES) analyzes MODerate-resolution Imaging Spectroradiometer (<span class="hlt">MODIS</span>) data and Visible Infrared Imaging Radiometer Suite (VIIRS) to derive cloud properties that are combine with aerosol and CERES broadband flux data to create a multi-parameter data set for climate study. CERES has produced over 15 years of data from Terra and over 13 years of data from <span class="hlt">Aqua</span> using the CERES-<span class="hlt">MODIS</span> Edition-2 cloud retrieval algorithm. A recently revised algorithm, CERESMODIS Edition 4, has been developed and is now generating enhanced cloud data for climate research (over 10 years for Terra and 8 years for <span class="hlt">Aqua</span>). New multispectral retrievals of properties are included along with a multilayer cloud retrieval system. Cloud microphysical properties are reported at 3 wavelengths, 0.65, 1.24, and 2.1 microns to enable better estimates of the vertical profiles of cloud water contents. Cloud properties over snow are retrieved using the 1.24-micron channel. A new CERES-VIIRS cloud retrieval package was developed for the VIIRS spectral complement and is currently producing the CERES-VIIRS Edition 1 cloud dataset. The results from CERES-<span class="hlt">MODIS</span> Edition 4 and CERES-VIIRS Edition 1 are presented and compared with each other and other datasets, including CALIPSO, CloudSat and the CERES-<span class="hlt">MODIS</span> Edition-2 results.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://ntrs.nasa.gov/search.jsp?R=20050131686&hterms=classification+ecosystems&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D90%26Ntt%3Dclassification%2Becosystems','NASA-TRS'); return false;" href="http://ntrs.nasa.gov/search.jsp?R=20050131686&hterms=classification+ecosystems&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D90%26Ntt%3Dclassification%2Becosystems"><span id="translatedtitle">Spatially Complete Global Surface Albedos Derived from Terra/<span class="hlt">MODIS</span> Data</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>King, Michael D.; Moody, Eric G.; Platnick, Steven; Schaaf, Crystal B.</p> <p>2004-01-01</p> <p>Spectral land surface albedo is an important parameter for describing the radiative properties of the Earth. Accordingly it <span class="hlt">reflects</span> the consequences of natural and human interactions, such as anthropogenic, meteorological, and phenological effects, on global and local climatological trends. Consequently, albedos are integral parts in a variety of research areas, such as general circulation models (GCMs), energy balance studies, modeling of land use and land use change, and biophysical, oceanographic, and meteorological studies. Recent production of land surface anisotropy, diffuse bihemispherical (white-sky) albedo and direct beam directional hemispherical (black-sky) albedo from observations acquired by the <span class="hlt">MODIS</span> instruments aboard NASA s Terra and <span class="hlt">Aqua</span> satellite platforms have provided researchers with unprecedented spatial, spectral, and temporal information on the land surface's radiative characteristics. Cloud cover, which cutails retrievals, and the presence of ephemeral and seasonal snow limit the snow-free data to approximately half the global land surfaces on an annual equal-angle basis. This precludes the MOD43B3 albedo products from being used in some remote sensing and ground-based applications, climate models, and global change research projects. An ecosystem-dependent temporal interpolation technique is described that has been developed to fill missing or seasonally snow-covered data in the official MOD43B3 albedo product. The method imposes pixel-level and local regional ecosystem-dependent phenological behavior onto retrieved pixel temporal data in such a way as to maintain pixel-level spatial and spectral detail and integrity. The phenological curves are derived from statistics based on the <span class="hlt">MODIS</span> MOD12Q1 IGBP land cover classification product geolocated with the MOD43B3 data. The resulting snow-free value-added products provide the scientific community with spatially and temporally complete global white- and black-sky surface albedo maps and</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2012AGUFM.A13J0315L','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2012AGUFM.A13J0315L"><span id="translatedtitle">From <span class="hlt">MODIS</span> to VIIRS: Steps toward continuing the dark-target aerosol climate data record</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Levy, R. C.; Mattoo, S.; Liu, H.; Munchak, L. A.; Laszlo, I.; Cronk, H.</p> <p>2012-12-01</p> <p>By this fall-2012 AGU meeting, the Moderate Resolution Imaging Spectrometer (<span class="hlt">MODIS</span>) has been flying on NASA's Terra and <span class="hlt">Aqua</span> satellites for 13 years and 10.5 years, respectively. During this time, the <span class="hlt">MODIS</span> Aerosol Science Team has fine-tuned the aerosol retrieval algorithms and data processing protocols, resulting in a highly robust, stable and usable aerosol product. The aerosol optical depth (AOD) product has been validated extensively, and the <span class="hlt">MODIS</span>-retrieved environmental data record (EDR) is becoming a strong foundation for creating an aerosol climate data record (CDR). With last year's launch of the Visible and Infrared Imaging Radiometer Suite (VIIRS) aboard Suomi-NPP, the VIIRS-derived aerosol product has been designed to continue that provided by <span class="hlt">MODIS</span>. VIIRS and <span class="hlt">MODIS</span> have similar orbital mechanics and provide similar spectral resolution with similar spatial resolution. At the same time, the VIIRS and <span class="hlt">MODIS</span> aerosol algorithms have similar physical assumptions. In fact, the initial validation exercises suggest that, in general, the VIIRS aerosol product is performing well, and that the expected error for the VIIRS-derived AOD is similar to that reported by <span class="hlt">MODIS</span>. Although VIIRS should be able to derive an aerosol product similar in quality to <span class="hlt">MODIS</span>, can the VIIRS aerosol record be "stitched" together with the <span class="hlt">MODIS</span> record? To answer this question, instead of qualifying how similar they are, we need to quantify how their differences can and do impact the resulting aerosol products. There are instrumental differences, such as orbit altitude (805km versus 705km), spatial resolution (375m/750m versus 250m/500m/1000m), spectral differences, and sampling differences). There are pre-processing differences (cloud masking, gas correction assumptions, pixel selection protocols). There are retrieval algorithm differences, and of course final processing and quality control differences. Although we expect that most of differences have little or no impact, some may be</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2015AGUFM.A41N..06W','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2015AGUFM.A41N..06W"><span id="translatedtitle">Interpretation of <span class="hlt">MODIS</span> Cloud Images by CloudSat/CALIPSO Cloud Vertical Profiles</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Wang, T.; Fetzer, E. J.; Wong, S.; Yue, Q.</p> <p>2015-12-01</p> <p>Clouds observed by passive remote-sensing imager (<span class="hlt">Aqua-MODIS</span>) are collocated to cloud vertical profiles observed by active profiling sensors (CloudSat radar and CALIPSO lidar) at the pixel-scale. By comparing different layers of cloud types classified in the 2B-CLDCLASS-LIDAR product from CloudSat+CALIPSO to those cloud properties observed by <span class="hlt">MODIS</span>, we evaluate the occurrence frequencies of cloud types and cloud-overlap in CloudSat+CALIPSO for each <span class="hlt">MODIS</span> cloud regime defined by cloud optical depth (τ) and cloud-top pressure (P) histograms. We find that about 70% of <span class="hlt">MODIS</span> clear sky agrees with the clear category in CloudSat+CALIPSO; whereas the remainder is either single layer (~25%) cirrus (Ci), low-level cumulus (Cu), stratocumulus (Sc), or multi-layer (<5%) clouds in CloudSat+CALIPSO. Under <span class="hlt">MODIS</span> cloudy conditions, 60%, 28%, and 8% of the occurrences show single-, double-, and triple-layer clouds, respectively in CloudSat+CALIPSO. When <span class="hlt">MODIS</span> identifies single-layer clouds, 50-60% of the <span class="hlt">MODIS</span> low-level clouds are categorized as stratus (Sc) in CloudSat+CALIPSO. Over the tropics, ~70% of <span class="hlt">MODIS</span> high and optically thin clouds (considered as cirrus in the histogram) is also identified as Ci in CloudSat+CALIPSO, and ~40% of <span class="hlt">MODIS</span> high and optically thick clouds (considered as convective in the histogram) agrees with CloudSat+CALIPSO deep convections (DC). Over mid-latitudes these numbers drop to 45% and 10%, respectively. The best agreement occurs in tropical single-layer cloud regimes, where 90% of <span class="hlt">MODIS</span> high-thin clouds are identified as Ci by CloudSat+CALIPSO and 60% of <span class="hlt">MODIS</span> high-thick clouds are identified as DC. Worst agreement is found for multi-layer clouds, where cirrus on top of low- and mid-level clouds in <span class="hlt">MODIS</span> are frequently categorized as high-thick clouds by passive imaging - among these only 5-12% are DC in CloudSat+CALIPSO. It is encouraging that both <span class="hlt">MODIS</span> low-level clouds (regardless of optical thickness) and high-level thin clouds are consistently</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://ntrs.nasa.gov/search.jsp?R=20000118270&hterms=Urbanization&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D90%26Ntt%3DUrbanization','NASA-TRS'); return false;" href="http://ntrs.nasa.gov/search.jsp?R=20000118270&hterms=Urbanization&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D90%26Ntt%3DUrbanization"><span id="translatedtitle">Remote Sensing of Aerosol Over the Land from the Earth Observing System <span class="hlt">MODIS</span> Instrument</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Kaufman, Yoram; Tanre, Didier; Remer, Lorraine; Einaudi, Franco (Technical Monitor)</p> <p>2000-01-01</p> <p>On Dec 18, 1999, NASA launched the Moderate-Resolution Imaging Spectroradiometer (<span class="hlt">MODIS</span>) instrument on the Earth Observing System (EOS) Terra mission, in a spectacular launch. The mission will provide morning (10:30 AM) global observations of aerosol and other related parameters. It will be followed a year later by a <span class="hlt">MODIS</span> instrument on EOS <span class="hlt">Aqua</span> for afternoon observations (1:30 PM). <span class="hlt">MODIS</span> will measure aerosol over land and ocean with its eight 500 m and 250 m channels in the solar spectrum (0-41 to 2.2 micrometers). Over the land <span class="hlt">MODIS</span> will measure the total column aerosol loading, and distinguish between submicron pollution particles and large soil particles. Standard daily products of resolution of ten kilometers and global mapped eight day and monthly products on a 1x1 degree global scale will be produced routinely and make available for no or small reproduction charge to the international community. Though the aerosol products will not be available everywhere over the land, it is expected that they will be useful for assessments of the presence, sources and transport of urban pollution, biomass burning aerosol, and desert dust. Other measurements from <span class="hlt">MODIS</span> will supplement the aerosol information, e.g., land use change, urbanization, presence and magnitude of biomass burning fires, and effect of aerosol on cloud microphysics. Other instruments on Terra, e.g. Multi-angle Imaging SpectroRadiometer (MISR) and the Clouds and the Earth's Radiant Energy System (CERES), will also measure aerosol, its properties and radiative forcing in tandem with the <span class="hlt">MODIS</span> measurements. During the <span class="hlt">Aqua</span> period, there are plans to launch in 2003 the Pathfinder Instruments for Cloud and Aerosol Spaceborne Observations (PICASSO) mission for global measurements of the aerosol vertical structure, and the PARASOL mission for aerosol characterization. <span class="hlt">Aqua-MODIS</span>, PICASSO and PARASOL will fly in formation for detailed simultaneous characterization of the aerosol three-dimensional field, which</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2016EGUGA..1815907B','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2016EGUGA..1815907B"><span id="translatedtitle">Assessment of the <span class="hlt">MODIS</span>-Terra Collection 006 aerosol optical depth data over the greater Mediterranean basin and inter-comparison against <span class="hlt">MODIS</span> C005 and AERONET</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Betsikas, Marios; Hatzianastassiou, Nikos; Papadimas, Christos D.; Gkikas, Antonis; Matsoukas, Christos; Sayer, Andrew; Hsu, Christina; Vardavas, Ilias</p> <p>2016-04-01</p> <p>Aerosols are one of the key factors determining the Earth's solar radiation budget. The aerosol radiative effects are strongly dependent on aerosol optical depth (AOD) which is a good measure of atmospheric aerosol loading. Therefore, understanding better the spatial and temporal patterns of AOD at both global and regional scales is important for more accurate estimations of aerosol radiative effects. Nowadays, improved globally distributed AOD products are available largely based on satellite observations. Currently, one of the most acknowledged accurate AOD dataset is the one derived from measurements of the MODerate resolution Imaging Spectroradiometer (<span class="hlt">MODIS</span>) instrument onboard the twin Earth Observing System (EOS) Terra and <span class="hlt">Aqua</span> satellite platforms. The <span class="hlt">MODIS</span> aerosol retrieval algorithm, which is used to produce AOD data, is continuously improved and updated, leading to releases of successive series, named as Collections. Recently, <span class="hlt">MODIS</span> Collection 6 (C006) dataset has been made available. Despite their advantages, satellite AOD products have to be assessed through comparisons against ground based AOD products, such as those from AERosol Robotic Network (AERONET). The aim of the present study is to assess the newest <span class="hlt">MODIS</span> C006 AOD product over the greater Mediterranean basin. The assessment is performed through comparisons of the <span class="hlt">MODIS</span>-Terra C006 Level-3 AOD data against corresponding data from the previous C005 <span class="hlt">MODIS</span> dataset, as well as versus AOD data from AERONET stations within the study region. The study period extends from 2001 to 2012 and our comparisons are performed on a monthly basis. Emphasis is given on differences between the <span class="hlt">MODIS</span> C006 AOD data and corresponding previous C005 data, as to their spatial and temporal, seasonal and inter-annual, patterns. The results show a better agreement of <span class="hlt">MODIS</span> C006 than C005 AOD data with AERONET, while the C006 data offer a complete spatial coverage of the study region, specifically over the northern African</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2015EGUGA..17.4354K','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2015EGUGA..17.4354K"><span id="translatedtitle">Improvement of GOCI Yonsei Aerosol retrieval algorithm and validation during DRAGON campaign: Surface <span class="hlt">reflectance</span> issue according to land, clear water and turbid water</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Kim, Jhoon; Choi, Myungje; Lee, Jaehwa</p> <p>2015-04-01</p> <p>Aerosol optical properties (AOPs) over East Asia are retrieved hourly from the first Geostationary Ocean Color Imager (GOCI). GOCI Yonsei aerosol retrieval (YAER) algorithm was developed and improved continuously. Final products of GOCI YAER are aerosol optical depth (AOD), fine-mode fraction (FMF), single scattering albedo (SSA), Angstrom exponent (AE) and aerosol type in high spatial and temporal resolution. Previous aerosol retrieval algorithm over ocean adopts surface <span class="hlt">reflectance</span> using cox and munk technique as fixed wind speed or the minimum <span class="hlt">reflectivity</span> technique for continuous characteristics between ocean and land. This study adopt cox and munk technique using real time ECMWF wind speed data over clear water and the minimum <span class="hlt">reflectivity</span> technique over turbid water. For detecting turbid water, TOA <span class="hlt">reflectance</span> of 412, 660, and 865nm was used. Over the turbid water, TOA <span class="hlt">reflectance</span> at 660nm increases more than 412 and 865nm. It also shows more sensitivity over turbid water than dust aerosol. We evaluated the accuracy of GOCI aerosol products using ground-based AERONET Level 2.0 products from total 38 East Asia sites and satellite-based <span class="hlt">MODIS-Aqua</span> aerosol C6 products. The period of assessment is 3 months from March to May, 2012. Comparison results show that a correlation coefficient between the AODs at 550 nm of AERONET and GOCI is 0.884. Comparison results over ocean between GOCI and <span class="hlt">MODIS</span> DT algorithm shows good agreement as R = 0.915.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/20160006671','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20160006671"><span id="translatedtitle">Long Term Cloud Property Datasets From <span class="hlt">MODIS</span> and AVHRR Using the CERES Cloud Algorithm</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Minnis, Patrick; Bedka, Kristopher M.; Doelling, David R.; Sun-Mack, Sunny; Yost, Christopher R.; Trepte, Qing Z.; Bedka, Sarah T.; Palikonda, Rabindra; Scarino, Benjamin R.; Chen, Yan; Hong, Gang; Bhatt, Rajendra</p> <p>2015-01-01</p> <p>Cloud properties play a critical role in climate change. Monitoring cloud properties over long time periods is needed to detect changes and to validate and constrain models. The Clouds and the Earth's Radiant Energy System (CERES) project has developed several cloud datasets from <span class="hlt">Aqua</span> and Terra <span class="hlt">MODIS</span> data to better interpret broadband radiation measurements and improve understanding of the role of clouds in the radiation budget. The algorithms applied to <span class="hlt">MODIS</span> data have been adapted to utilize various combinations of channels on the Advanced Very High Resolution Radiometer (AVHRR) on the long-term time series of NOAA and MetOp satellites to provide a new cloud climate data record. These datasets can be useful for a variety of studies. This paper presents results of the <span class="hlt">MODIS</span> and AVHRR analyses covering the period from 1980-2014. Validation and comparisons with other datasets are also given.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2014EGUGA..1610660N','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2014EGUGA..1610660N"><span id="translatedtitle">MSG-SEVIRI and EOS-<span class="hlt">MODIS</span> LST Product Validation by Using a Developed Thermal-Infrared Data Acquisition System</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Niclòs, Raquel; Valiente, José Antonio; Jesús Barberà, María; Sánchez, Juan Manuel</p> <p>2014-05-01</p> <p>Multidirectional thermal infrared (TIR) measurements are convenient to describe the radiative characteristics of natural surfaces and to obtain accurate Land Surface Temperature (LST). An autonomous system for field angular thermal-infrared (TIR) radiometric data acquisition was developed with the aim of being easily deployed at any traditional meteorological tower station. The device scans land and sky hemispheres at several angular steps to attain remotely sensed land and sky temperatures by means of a single infrared radiometer. Apogee radiometers were selected to be included in the prototype not only by their reduced size and easy functioning but also by their measurement accuracies as proved in calibrations against NIST blackbodies (± 0.2 K at 293-303 K). During the 2012 summer, a prototype of the device was deployed at an extensive, homogeneous and flat cultivated-rice area widely used in experimental CAL/VAL campaigns of satellite TIR sensors (39.274°N, -0.317°E in WGS-84; 2.5 m above sea level). The measured TIR data were processed to obtain ground-truth LST and compared with the operational LST products provided by two satellite TIR instruments: <span class="hlt">MODIS</span> on board EOS-Terra and EOS-<span class="hlt">Aqua</span> platforms and SEVIRI on board of the geostationary MSG. Both the MSG-SEVIRI and the EOS-<span class="hlt">MODIS</span> LST products were shown to work with uncertainties within those expected, but a general overestimation was observed for the MSG-SEVIRI product (with a median between product and ground LST data of + 0.6 K and a robust standard deviation (RSD) of ± 1.0K) and a slight underestimation, especially for off-nadir observation angles, was observed for the EOS-<span class="hlt">MODIS</span> LST product (i.e., a median of -0.10 K and a RSD of ± 1.2K for all the <span class="hlt">MODIS</span>-viewing angles, but a median of -0.7 K and a RSD of ± 1.5 K for angles larger than 40°). Satellite LST product validation will be extended by using data collected by the autonomous and angular system setup at different sites in Eastern Spain. This</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/cgi-bin/nph-data_query?bibcode=2014AGUFM.B53B0178S&link_type=ABSTRACT','NASAADS'); return false;" href="http://adsabs.harvard.edu/cgi-bin/nph-data_query?bibcode=2014AGUFM.B53B0178S&link_type=ABSTRACT"><span id="translatedtitle">Recent Shift of Deforestation to High Elevation Areas from 2001 to 2013 in Borneo Detected by <span class="hlt">MODIS</span> Data</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Suzuki, R.; Nagai, S.</p> <p>2014-12-01</p> <p>The biomass of tropical forests sequestrates tons of carbon and plays an important role in the global carbon cycle regulating the climate. Also its high biodiversity ecosystems bring us many valuable resources and cultural and educational ecosystem services. However, large areas of the tropical forest are deforested and converted to oil palm or acacia plantation for the economic benefit of the local society mainly in Southeast Asia. Monitoring of the tropical forest from satellites provides us the information about the deforestation for decadal time period over extensive areas and enables us to discuss it from a scientific point of view. The purpose of this study is to reveal the interannual change and recent trend of deforestation in relation to the land elevation for decadal time period over Borneo by using data from Moderate Resolution Imaging Spectroradiometer (<span class="hlt">MODIS</span>). We acquired the atmospherically corrected and cloud free Terra-<span class="hlt">MODIS</span> and <span class="hlt">Aqua-MODIS</span> daily data products (MOD09GA and MYD09GA; collection 5) from 2001 to 2013 for Borneo. We extracted the pixel values in the 500m surface <span class="hlt">reflectance</span> bands 1 (red) and 4 (green) products and calculated the green-red vegetation index (GRVI), (band 4 - band 1) / (band 4 + band 1), at a daily time step. GRVI shows a positive value for the land prevailed by green vegetation, while it shows a negative value for the land prevailed by no-green components such as bare land. As for the elevation data, ASTER Global Digital Elevation Model (GDEM) which has 33.3m spatial resolution was employed. The original resolution was resampled to the grid system of <span class="hlt">MODIS</span> data (i.e. 500m resolution). Pixels which had a negative GRVI ratio more than 80 % (termed as "no green pixel") in each year were regarded as the land characterized by no vegetation, and mapped the distribution for each year. Throughout the 13 years, no green pixels mainly found over the coastal low land below 20m of the elevation and the area was almost constant (around</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/cgi-bin/nph-data_query?bibcode=2015AGUFM.B53E0620N&link_type=ABSTRACT','NASAADS'); return false;" href="http://adsabs.harvard.edu/cgi-bin/nph-data_query?bibcode=2015AGUFM.B53E0620N&link_type=ABSTRACT"><span id="translatedtitle">Recent Shift of Deforestation to High Elevation Areas from 2001 to 2013 in Borneo Detected by <span class="hlt">MODIS</span> Data</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Nagai, S.; Suzuki, R.</p> <p>2015-12-01</p> <p>The biomass of tropical forests sequestrates tons of carbon and plays an important role in the global carbon cycle regulating the climate. Also its high biodiversity ecosystems bring us many valuable resources and cultural and educational ecosystem services. However, large areas of the tropical forest are deforested and converted to oil palm or acacia plantation for the economic benefit of the local society mainly in Southeast Asia. Monitoring of the tropical forest from satellites provides us the information about the deforestation for decadal time period over extensive areas and enables us to discuss it from a scientific point of view. The purpose of this study is to reveal the interannual change and recent trend of deforestation in relation to the land elevation for decadal time period over Borneo by using data from Moderate Resolution Imaging Spectroradiometer (<span class="hlt">MODIS</span>). We acquired the atmospherically corrected and cloud free Terra-<span class="hlt">MODIS</span> and <span class="hlt">Aqua-MODIS</span> daily data products (MOD09GA and MYD09GA; collection 5) from 2001 to 2013 for Borneo. We extracted the pixel values in the 500m surface <span class="hlt">reflectance</span> bands 1 (red) and 4 (green) products and calculated the green-red vegetation index (GRVI), (band 4 - band 1) / (band 4 + band 1), at a daily time step. GRVI shows a positive value for the land prevailed by green vegetation, while it shows a negative value for the land prevailed by no-green components such as bare land. As for the elevation data, ASTER Global Digital Elevation Model (GDEM) which has 33.3m spatial resolution was employed. The original resolution was resampled to the grid system of <span class="hlt">MODIS</span> data (i.e. 500m resolution). Pixels which had a negative GRVI ratio more than 80 % (termed as "no green pixel") in each year were regarded as the land characterized by no vegetation, and mapped the distribution for each year. Throughout the 13 years, no green pixels mainly found over the coastal low land below 20m of the elevation and the area was almost constant (around</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2004SPIE.5652..219F','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2004SPIE.5652..219F"><span id="translatedtitle">Recent improvements in the <span class="hlt">MODIS</span> cloud mask</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Frey, Richard A.; Ackerman, Steven A.; Liu, Yinghui; Strabala, Kathleen I.; Zhang, Hong</p> <p>2004-12-01</p> <p>Significant improvements have been made to the <span class="hlt">MODIS</span> cloud mask (MOD35) in preparation for Collection 5 reprocessing and forward stream data production. Most of the modifications are realized for nighttime scenes where polar and oceanic regions will see marked improvement. For polar night scenes, two new spectral tests using the 7.2 μm water vapor absorption band have been added as well as updates to the 3.9-12 μm and 11-12 μm cloud tests. More non-<span class="hlt">MODIS</span> ancillary data has been added for nighttime processing. Land and sea surface temperature maps provide crucial information for middle and low-level cloud detection and lessen dependence on ocean variability tests. Sun-glint areas are also improved by use of sea surface temperatures to aid in resolving observations with conflicting cloud vs. clear-sky signals, where visible and NIR <span class="hlt">reflectances</span> are high, but infrared brightness temperatures are relatively warm. Details and examples of new and modified cloud tests are shown and various methods employed to evaluate the new cloud mask results. Day vs. night sea surface temperatures derived from <span class="hlt">MODIS</span> radiances and using only the <span class="hlt">MODIS</span> cloud mask for cloud screening are contrasted. Frequencies of cloud from sun-glint regions will be shown as a function of sun-glint angle to gain a sense of cloud mask quality in those regions.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://ntrs.nasa.gov/search.jsp?R=20110023848&hterms=spectroradiometer+MODIS&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D70%26Ntt%3Dspectroradiometer%2BMODIS','NASA-TRS'); return false;" href="http://ntrs.nasa.gov/search.jsp?R=20110023848&hterms=spectroradiometer+MODIS&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D70%26Ntt%3Dspectroradiometer%2BMODIS"><span id="translatedtitle">Discrepancies Between <span class="hlt">MODIS</span> and ISCCP Land Surface Temperature Products Analyzed with Microwave Measurements</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Moncet, Jean-Luc; Liang, Pan; Lipton, Alan E.; Galantowicz, John F.; Prigent, Catherine</p> <p>2011-01-01</p> <p>This paper compares land surface temperature (LST) products from the Moderate Resolution Imaging Spectroradiometer (<span class="hlt">MODIS</span>) and the International Satellite Cloud Climatology Project (ISCCP). With both sources, the LST data are derived from infrared measurements. For ISCCP, LST is a secondary product in support of the primary cloud analyses, but the LST data have been used for several other purposes. The <span class="hlt">MODIS</span> measurements from the <span class="hlt">Aqua</span> spacecraft are taken at about 01:30 and 13:30 local time, and the ISCCP three-hourly data, based on several geostationary and polar orbiting satellites. were interpolated to the <span class="hlt">MODIS</span> measurement times. For July 2003 monthly averages over all clear-sky locations, the ISCCP-<span class="hlt">MODIS</span> differences were +5.0 K and +2.5 K for day and night, respectively, and there were areas with differences as large as 25 K. The day-night differences were as much as approximately 10 K higher for ISCCP than for <span class="hlt">MODIS</span>. The <span class="hlt">MODIS</span> measurements were more consistent with independent microwave measurements from AMSR-E, by several measures, with respect to day-night differences and day-to-day variations.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2014AGUFM.A21F3093S','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2014AGUFM.A21F3093S"><span id="translatedtitle">Evaluating <span class="hlt">MODIS</span> Collection 6 Dark Target Over Water Aerosol Products for Multi-sensor Data Fusion</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Shi, Y.; Zhang, J.; Reid, J. S.; Hyer, E. J.; McHardy, T. M.; Lee, L.</p> <p>2014-12-01</p> <p>The Moderate Resolution Imaging Spectroradiometer (<span class="hlt">MODIS</span>) aerosol products have been widely used in aerosol related climate, visibility, and air quality studies for more than a decade. Recently, the <span class="hlt">MODIS</span> collection 6 (c6) aerosol products from <span class="hlt">MODIS-Aqua</span> have been released. The reported changes between Collection 5 and Collection 6 include updates in the retrieving algorithms and a new cloud filtering process for the over-ocean products. Thus it is necessary to fully evaluate the collection 6 products for applications that require high quality <span class="hlt">MODIS</span> aerosol optical depth data, such as operational aerosol data assimilation. The uncertainties in the <span class="hlt">MODIS</span> c6 DT over ocean products are studied through both inter-comparing with the Multi-angle Imaging Spectroradiometer (MISR) aerosol products and by evaluation against ground truth. Special attention is given to the low bias in <span class="hlt">MODIS</span> DT products due to the misclassifications of heavy aerosol plumes as clouds. Finally, a quality assured data assimilation grade aerosol optical product is constructed for aerosol data assimilation related applications.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/cgi-bin/nph-data_query?bibcode=2016ACP....16.1255X&link_type=ABSTRACT','NASAADS'); return false;" href="http://adsabs.harvard.edu/cgi-bin/nph-data_query?bibcode=2016ACP....16.1255X&link_type=ABSTRACT"><span id="translatedtitle">Evaluation of VIIRS, GOCI, and <span class="hlt">MODIS</span> Collection 6 AOD retrievals against ground sunphotometer observations over East Asia</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Xiao, Q.; Zhang, H.; Choi, M.; Li, S.; Kondragunta, S.; Kim, J.; Holben, B.; Levy, R. C.; Liu, Y.</p> <p>2016-02-01</p> <p>Persistent high aerosol loadings together with extremely high population densities have raised serious air quality and public health concerns in many urban centers in East Asia. However, ground-based air quality monitoring is relatively limited in this area. Recently, satellite-retrieved Aerosol Optical Depth (AOD) at high resolution has become a powerful tool to characterize aerosol patterns in space and time. Using ground AOD observations from the Aerosol Robotic Network (AERONET) and the Distributed Regional Aerosol Gridded Observation Networks (DRAGON)-Asia Campaign, as well as from handheld sunphotometers, we evaluated emerging aerosol products from the Visible Infrared Imaging Radiometer Suite (VIIRS) aboard the Suomi National Polar-orbiting Partnership (S-NPP), the Geostationary Ocean Color Imager (GOCI) aboard the Communication, Ocean, and Meteorology Satellite (COMS), and Terra and <span class="hlt">Aqua</span> Moderate Resolution Imaging Spectroradiometer (<span class="hlt">MODIS</span>) (Collection 6) in East Asia in 2012 and 2013. In the case study in Beijing, when compared with AOD observations from handheld sunphotometers, 51 % of VIIRS Environmental Data Record (EDR) AOD, 37 % of GOCI AOD, 33 % of VIIRS Intermediate Product (IP) AOD, 26 % of Terra <span class="hlt">MODIS</span> C6 3 km AOD, and 16 % of <span class="hlt">Aqua</span> <span class="hlt">MODIS</span> C6 3 km AOD fell within the reference expected error (EE) envelope (±0.05 ± 0.15 AOD). Comparing against AERONET AOD over the Japan-South Korea region, 64 % of EDR, 37 % of IP, 61 % of GOCI, 39 % of Terra <span class="hlt">MODIS</span>, and 56 % of <span class="hlt">Aqua</span> <span class="hlt">MODIS</span> C6 3 km AOD fell within the EE. In general, satellite aerosol products performed better in tracking the day-to-day variability than tracking the spatial variability at high resolutions. The VIIRS EDR and GOCI products provided the most accurate AOD retrievals, while VIIRS IP and <span class="hlt">MODIS</span> C6 3 km products had positive biases.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://www.ars.usda.gov/research/publications/publication/?seqNo115=309901','TEKTRAN'); return false;" href="http://www.ars.usda.gov/research/publications/publication/?seqNo115=309901"><span id="translatedtitle">An approach for the long-term 30-m land surface snow-free albedo retrieval from historic Landsat surface <span class="hlt">reflectance</span> and <span class="hlt">MODIS</span>-based a priori anisotropy knowledge</span></a></p> <p><a target="_blank" href="http://www.ars.usda.gov/services/TekTran.htm">Technology Transfer Automated Retrieval System (TEKTRAN)</a></p> <p></p> <p></p> <p>Land surface albedo has been recognized by the Global Terrestrial Observing System (GTOS) as an essential climate variable crucial for accurate modeling and monitoring of the Earth’s radiative budget. While global climate studies can leverage albedo datasets from <span class="hlt">MODIS</span>, VIIRS, and other coarse-reso...</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2012AGUFM.H32D..07N','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2012AGUFM.H32D..07N"><span id="translatedtitle">Identifying false rain in satellite precipitation products using CloudSat and <span class="hlt">MODIS</span></span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Nasrollahi, N.; Hsu, K.; Sorooshian, S.</p> <p>2012-12-01</p> <p>Moderate Resolution Imaging Spectroradiometer (<span class="hlt">MODIS</span>) instrument on board NASA Earth Observing System <span class="hlt">Aqua</span> and Terra platform with 36 spectral bands provides valuable information about cloud microphysical characteristics. Additionally, CloudSat, selected as a NASA Earth Sciences Systems Pathfinder (ESSP) satellite mission, is designed to measure vertical structure of clouds. The CloudSat radar flies in formation with <span class="hlt">Aqua</span> with only an average of 60 second delay. In this study, the application of <span class="hlt">MODIS</span> multispectral images and CloudSat Level 2-C Precipitation Column Algorithm in false rain identification is investigated. Using a machine learning technique, the presence of precipitation will be assigned to textural and spectral features of clouds observed by the <span class="hlt">MODIS</span> satellite, whenever CloudSat surface rainfall retrieval is available. This information for different regions and seasons create a training data set. The training database will then be used as a reference to find if any pixel in the <span class="hlt">MODIS</span> retrieval window is falsely identified as rainy pixel for the times that CloudSat data is not available. The input to the Artificial Neural Networks (ANN) model is a combination of 8 <span class="hlt">MODIS</span> visible, water vapor and infrared channels. The performance of model with combination of different <span class="hlt">MODIS</span> channels is estimated. The results of ANN model are used to filter out false rainy pixels from satellite precipitation estimates (e.g. PERSIANN). The outcome of the new corrected precipitation data is compared to ground based radar measurements (Stage IV radar data). The results show a 64 percent reduction in false rain in PERSIANN satellite data for 100 cases investigated in summer 2008 and 24 percent false rain reduction in more than 50 cases studied in winter 2010.</p> </li> </ol> <div class="pull-right"> <ul class="pagination"> <li><a href="#" onclick='return showDiv("page_1");'>«</a></li> <li><a href="#" onclick='return showDiv("page_15");'>15</a></li> <li><a href="#" onclick='return showDiv("page_16");'>16</a></li> <li class="active"><span>17</span></li> <li><a href="#" onclick='return showDiv("page_18");'>18</a></li> <li><a href="#" onclick='return showDiv("page_19");'>19</a></li> <li><a href="#" onclick='return showDiv("page_25");'>»</a></li> </ul> </div> </div><!-- col-sm-12 --> </div><!-- row --> </div><!-- page_17 --> <div id="page_18" class="hiddenDiv"> <div class="row"> <div class="col-sm-12"> <div class="pull-right"> <ul class="pagination"> <li><a href="#" onclick='return showDiv("page_1");'>«</a></li> <li><a href="#" onclick='return showDiv("page_16");'>16</a></li> <li><a href="#" onclick='return showDiv("page_17");'>17</a></li> <li class="active"><span>18</span></li> <li><a href="#" onclick='return showDiv("page_19");'>19</a></li> <li><a href="#" onclick='return showDiv("page_20");'>20</a></li> <li><a href="#" onclick='return showDiv("page_25");'>»</a></li> </ul> </div> </div> </div> <div class="row"> <div class="col-sm-12"> <ol class="result-class" start="341"> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2016JHyd..534..466D','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2016JHyd..534..466D"><span id="translatedtitle">Improving the accuracy of <span class="hlt">MODIS</span> 8-day snow products with in situ temperature and precipitation data</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Dong, Chunyu; Menzel, Lucas</p> <p>2016-03-01</p> <p><span class="hlt">MODIS</span> snow data are appropriate for a wide range of eco-hydrological studies and applications in the fields of snow-related hazards, early warning systems and water resources management. However, the high spatio-temporal resolution of the remotely sensed data is often biased by snow misclassifications, and cloud cover frequently limits the availability of the <span class="hlt">MODIS</span>-based snow cover information. In this study, we applied a four-step methodology that aims to optimize the accuracy of <span class="hlt">MODIS</span> snow data. To reduce the cloud fraction, 8-day <span class="hlt">MODIS</span> data from both the <span class="hlt">Aqua</span> and Terra satellites were combined. Neighborhood analysis was applied as well for this purpose, and it also contributed to the retrieval of some omitted snow. Two meteorological filters were then applied to combine information from station-based measurements of minimum ground temperature, precipitation and air temperature. This procedure helped to reduce the overestimation of snow cover. To test this technique, the methodology was applied to the Rhineland-Palatinate region in southwestern Germany (approximately 20,000 km2), where cloud cover is especially high during winter and surface heterogeneity is complex. The results show that mean annual cloud coverage (reference period 2002-2013) of the 8-day <span class="hlt">MODIS</span> snow maps could be reduced using this methodology from approximately 14% to 4.5%. During the snow season, obstruction by clouds could be reduced by even a higher degree, but still remains at about 11%. Further, the overall snow overestimation declined from 11.0-11.9% (using the original <span class="hlt">Aqua</span>-Terra data) to 1.0-1.5%. The method is able to improve the overall accuracy of the 8-day <span class="hlt">MODIS</span> snow product from originally 78% to 89% and even to 93% during cloud free periods.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/20080048051','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20080048051"><span id="translatedtitle"><span class="hlt">MODIS</span> Atmospheric Data Handler</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Anantharaj, Valentine; Fitzpatrick, Patrick</p> <p>2008-01-01</p> <p>The Moderate Resolution Imaging Spectroradiometer (<span class="hlt">MODIS</span>) Atmosphere Data Handler software converts the HDF data to ASCII format, and outputs: (1) atmospheric profiles of temperature and dew point and (2) total precipitable water. Quality-control data are also considered in the export procedure.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2011lrsg.book..635Z','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2011lrsg.book..635Z"><span id="translatedtitle"><span class="hlt">MODIS</span>-Derived Terrestrial Primary Production</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Zhao, Maosheng; Running, Steven; Heinsch, Faith Ann; Nemani, Ramakrishna</p> <p></p> <p>Temporal and spatial changes in terrestrial biological productivity have a large impact on humankind because terrestrial ecosystems not only create environments suitable for human habitation, but also provide materials essential for survival, such as food, fiber and fuel. A recent study estimated that consumption of terrestrial net primary production (NPP; a list of all the acronyms is available in the appendix at the end of the chapter) by the human population accounts for about 14-26% of global NPP (Imhoff et al. 2004). Rapid global climate change is induced by increased atmospheric greenhouse gas concentration, especially CO2, which results from human activities such as fossil fuel combustion and deforestation. This directly impacts terrestrial NPP, which continues to change in both space and time (Melillo et al. 1993; Prentice et al. 2001; Nemani et al. 2003), and ultimately impacts the well-being of human society (Milesi et al. 2005). Additionally, substantial evidence show that the oceans and the biosphere, especially terrestrial ecosystems, currently play a major role in reducing the rate of the atmospheric CO2 increase (Prentice et al. 2001; Schimel et al. 2001). NPP is the first step needed to quantify the amount of atmospheric carbon fixed by plants and accumulated as biomass. Continuous and accurate measurements of terrestrial NPP at the global scale are possible using satellite data. Since early 2000, for the first time, the <span class="hlt">MODIS</span> sensors onboard the Terra and <span class="hlt">Aqua</span> satellites, have operationally provided scientists with near real-time global terrestrial gross primary production (GPP) and net photosynthesis (PsnNet) data. These data are provided at 1 km spatial resolution and an 8-day interval, and annual NPP covers 109,782,756 km2 of vegetated land. These GPP, PsnNet and NPP products are collectively known as MOD17 and are part of a larger suite of <span class="hlt">MODIS</span> land products (Justice et al. 2002), one of the core Earth System or Climate Data Records (ESDR or</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/cgi-bin/nph-data_query?bibcode=2015AMTD....8.2409C&link_type=ABSTRACT','NASAADS'); return false;" href="http://adsabs.harvard.edu/cgi-bin/nph-data_query?bibcode=2015AMTD....8.2409C&link_type=ABSTRACT"><span id="translatedtitle">A cautionary use of DCC as a solar calibration target: explaining the regional difference in DCC <span class="hlt">reflectivity</span></span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Choi, M.-J.; Sohn, B. J.</p> <p>2015-03-01</p> <p>This study attempted to explain why deep convective clouds (DCCs) over the western Pacific are generally darker than those found over tropical African and South American land regions. For defining 1 km pixel DCCs in this study, 205 K of <span class="hlt">Aqua-MODIS</span> brightness temperature at 11 μm (TB11) was used as a criterion. Corresponding <span class="hlt">MODIS</span>-measured <span class="hlt">reflectivities</span> at 0.645 μm were examined, and an analysis of collocated Cloud Profile Radar (CPR) onboard CloudSat and Cloud Aerosol Lidar Infrared Pathfinder Satellite Observation (CALIPSO) measurements and derived cloud products was conducted. From an analysis of the four January months of 2007-2010, a distinct difference in ice water path (IWP) between the western Pacific and the two tropical land regions was demonstrated. Small but meaningful differences in the effective radius were also found. The results led to a conjecture that smaller IWP over the western Pacific than over the tropical land regions is the main cause of smaller <span class="hlt">reflectivity</span> there. This finding suggests that regionally different <span class="hlt">reflectivity</span> of DCCs over the tropics up to 5% on average are to be counted when those DCCs are used for the solar channel calibration.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://www.ncbi.nlm.nih.gov/pubmed/26158600','PUBMED'); return false;" href="http://www.ncbi.nlm.nih.gov/pubmed/26158600"><span id="translatedtitle">Intercomparison of Aerosol Optical Thickness Derived from <span class="hlt">MODIS</span> and in Situ Ground Datasets over Jaipur, a Semi-arid Zone in India.</span></a></p> <p><a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a></p> <p>Payra, Swagata; Soni, Manish; Kumar, Anikender; Prakash, Divya; Verma, Sunita</p> <p>2015-08-01</p> <p>The first detailed seasonal validation has been carried out for the Moderate Resolution Imaging Spectroradiometer (<span class="hlt">MODIS</span>) Terra and <span class="hlt">Aqua</span> satellites Level 2.0 Collection Version 5.1 AOT (τ<span class="hlt">MODIS</span>) with Aerosol Robotic Network (AERONET) Level 2.0 AOT (τAERONET) for the years 2009-2012 over semi-arid region Jaipur, northwestern India. The correlation between τ<span class="hlt">MODIS</span> versus τAERONET at 550 nm is determined with different spatial and temporal size windows. The τ<span class="hlt">MODIS</span> overestimates τAERONET within a range of +0.06 ± 0.24 during the pre-monsoon (April-June) season, while it underestimates the τAERONET with -0.04 ± 0.12 and -0.05 ± 0.18 during dry (December-March) and post-monsoon (October-November) seasons, respectively. Correlation without (with) error envelope has been found for pre-monsoon at 0.71 (0.89), post-monsoon at 0.76 (0.94), and dry season at 0.78 (0.95). τ<span class="hlt">MODIS</span> is compared to τAERONET at three more ground AERONET stations in India, i.e., Kanpur, Gual Pahari, and Pune. Furthermore, the performance of <span class="hlt">MODIS</span> Deep Blue and <span class="hlt">Aqua</span> AOT550 nm (τDB550 nm and τ<span class="hlt">Aqua</span>550 nm) with τAERONET is also evaluated for all considered sites over India along with a U.S. desert site at White Sand, Tularosa Basin, NM. The statistical results reveal that τ<span class="hlt">Aqua</span>550 nm performs better over Kanpur and Pune, whereas τDB550 nm performs better over Jaipur, Gual Pahari, and White Sand High Energy Laser Systems Test Facility (HELSTF) (U.S. site). PMID:26158600</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2008AGUFM.A53F0332H','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2008AGUFM.A53F0332H"><span id="translatedtitle">Intercomparison and Validation of AIRS, <span class="hlt">MODIS</span>, and ASTER Land Surface Emissivity Products over the Namib and Kalahari Deserts in Southern Africa</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Hulley, G.; Hook, S.</p> <p>2008-12-01</p> <p>Land surface emissivity is a critical parameter for retrieving land surface temperatures from spaceborne Thermal Infrared (TIR) measurements. Land Surface Temperature and Emissivity (LST&E) data are key parameters in global climate change studies that involve climate modeling, ice dynamic analyses, surface- atmosphere interactions and land use, land cover change. The errors in retrievals of atmospheric temperature and moisture profiles from hyperspectral infrared radiances, such as those from the Atmospheric Infrared Sounder (AIRS) on NASA's <span class="hlt">Aqua</span> satellite, are strongly dependent on using constant or inaccurate surface emissivities, particularly over arid and semi-arid regions where the variation in emissivity is large, both spatially and spectrally. LST&E products are available from spaceborne sensors such as AIRS, <span class="hlt">MODIS</span> and ASTER at varying spatial, spectral, temporal resolutions, and using different retrieval algorithms. ASTER provides LST&E data with the highest spatial resolution (90 m), compared with AIRS (50 km) and <span class="hlt">MODIS</span> (1 and 5 km). AIRS has the highest spectral sampling and both AIRS and <span class="hlt">MODIS</span> acquire data at much higher temporal frequencies (every 2-3 days) compared with ASTER (every 16 days). In this paper we present validation and intercomparisons of AIRS, <span class="hlt">MODIS</span> and ASTER emissivity products over the Namib and Kalahari deserts in Southern Africa. The Namib, Africa's second largest desert, and the Kalahari cover areas of 80,900 and 900, 000 km² respectively and consist of pure quartz, giving the sand a deep red color. The dunes provide excellent areas for validation as they have little or no vegetation, are spatially homogeneous with known composition, and have large spectral variations in TIR emissivity. <span class="hlt">MODIS</span> and ASTER data will be upsampled to the AIRS spatial resolution, and then compared to the emissivities of in-situ sand samples collected at designated areas at Sossusvlei in the Namib dunes and Kgalagadi Transfrontier Park in the Kalahari. The</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2005AGUFM.A33E..08S','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2005AGUFM.A33E..08S"><span id="translatedtitle">Detection of Mixed-Phase Clouds over the Arctic Using <span class="hlt">MODIS</span> 6.7-12 micron Data</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Spangenberg, D. A.; Minnis, P.; Shupe, M. D.; Poellot, M. R.; Wang, Z.</p> <p>2005-12-01</p> <p>Over the Arctic, clouds containing both ice crystals and supercooled liquid droplets are a common occurrence and need to be taken into account in determining cloud microphysical properties. Presently, these mixed-phase (MIXP) clouds are detected fairly well by ground-based techniques, however, no information on their spatial extent is available. Satellite data has excellent spatial coverage and provides a means to extend the information on cloud phase away from the ground sites. To accomplish this goal, an Arctic cloud phase model is developed to detect MIXP clouds using Moderate Resolution Imaging Spectroradiometer (<span class="hlt">MODIS</span>) data taken onboard the Terra and <span class="hlt">Aqua</span> satellites. The model utilizes three water vapor and two cloud-top temperature channels in the 6.7-12 μm wavelength range. To develop the model, a wide range of cloud systems were sampled where the brightness temperature (BT) data from <span class="hlt">MODIS</span> was compared to surface-based phase retrievals at the Atmospheric Radiation Measurement (ARM) North Slope of Alaska (NSA) Barrow site. Cloud phase can be linked to specific sets of thermal and moisture structures existing between the upper part of the cloud and the upper troposphere. These structures are, in turn, <span class="hlt">reflected</span> in the <span class="hlt">MODIS</span> BT data. Results from the ARM <span class="hlt">MODIS</span> cloud-phase model (AMCPM) are compared to surface-based retrievals over the ARM-NSA Barrow site and to in-situ data from the Citation aircraft which flew during the ARM Mixed-Phase Arctic Cloud Experiment. Since the AMCPM only uses channels in the infrared part of the spectrum, it can be applied to both daytime and nighttime scenes with no discontinuities in the output phase. Preliminary results are encouraging with an agreement between <span class="hlt">MODIS</span> and the surface-based retrievals of over 75 %. The MIXP clouds considered here are those having generally between 10 and 90 % liquid water out of the total water content. The model should be applied to high-latitude regions only and even there, it is unclear how</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/20140010295','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20140010295"><span id="translatedtitle">Uncertainty of Passive Imager Cloud Optical Property Retrievals to Instrument Radiometry and Model Assumptions: Examples from <span class="hlt">MODIS</span></span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Platnick, Steven; Wind, Galina; Meyer, Kerry; Amarasinghe, Nandana; Arnold, G. Thomas; Zhang, Zhibo; King, Michael D.</p> <p>2013-01-01</p> <p>The optical and microphysical structure of clouds is of fundamental importance for understanding a variety of cloud radiation and precipitation processes. With the advent of <span class="hlt">MODIS</span> on the NASA EOS Terra and <span class="hlt">Aqua</span> platforms, simultaneous global-daily 1 km retrievals of cloud optical thickness (COT) and effective particle radius (CER) are provided, as well as the derived water path (WP). The cloud product (MOD06/MYD06 for <span class="hlt">MODIS</span> Terra and <span class="hlt">Aqua</span>, respectively) provides separate retrieval datasets for various two-channel retrievals, typically a VISNIR channel paired with a 1.6, 2.1, and 3.7 m spectral channel. The MOD06 forward model is derived from on a homogeneous plane-parallel cloud. In Collection 5 processing (completed in 2007 with a modified Collection 5.1 completed in 2010), pixel-level retrieval uncertainties were calculated for the following non-3-D error sources: radiometry, surface spectral albedo, and atmospheric corrections associated with model analysis uncertainties (water vapor only). The latter error source includes error correlation across the retrieval spectral channels. Estimates of uncertainty in 1 aggregated (Level-3) means were also provided assuming unity correlation between error sources for all pixels in a grid for a single day, and zero correlation of error sources from one day to the next. I n Collection 6 (expected to begin in late summer 2013) we expanded the uncertainty analysis to include: (a) scene-dependent calibration uncertainty that depends on new band and detector-specific Level 1B uncertainties, (b) new model error sources derived from the look-up tables which includes sensitivities associated with wind direction over the ocean and uncertainties in liquid water and ice effective variance, (c) thermal emission uncertainties in the 3.7 m band associated with cloud and surface temperatures that are needed to extract <span class="hlt">reflected</span> solar radiation from the total radiance signal, (d) uncertainty in the solar spectral irradiance at 3.7 m, and</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://pubs.er.usgs.gov/publication/70023443','USGSPUBS'); return false;" href="http://pubs.er.usgs.gov/publication/70023443"><span id="translatedtitle"><span class="hlt">MODIS</span> land data at the EROS data center DAAC</span></a></p> <p><a target="_blank" href="http://pubs.er.usgs.gov/pubs/index.jsp?view=adv">USGS Publications Warehouse</a></p> <p>Jenkerson, C.B.; Reed, B.C.</p> <p>2001-01-01</p> <p>The US Geological Survey's (USGS) Earth Resources Observation Systems (EROS) Data Center (EDC) in Sioux Falls, SD, USA, is the primary national archive for land processes data and one of the National Aeronautics and Space Administration's (NASA) Distributed Active Archive Centers (DAAC) for the Earth Observing System (EOS). One of EDC's functions as a DAAC is the archival and distribution of Moderate Resolution Spectroradiometer (<span class="hlt">MODIS</span>) Land Data collected from the Earth Observing System (EOS) satellite Terra. More than 500,000 publicly available <span class="hlt">MODIS</span> land data granules totaling 25 Terabytes (Tb) are currently stored in the EDC archive. This collection is managed, archived, and distributed by EOS Data and Information System (EOSDIS) Core System (ECS) at EDC. EDC User Services support the use of <span class="hlt">MODIS</span> Land data, which include land surface <span class="hlt">reflectance</span>/albedo, temperature/emissivity, vegetation characteristics, and land cover, by responding to user inquiries, constructing user information sites on the EDC web page, and presenting <span class="hlt">MODIS</span> materials worldwide.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/20040070915','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20040070915"><span id="translatedtitle">Deriving Albedo from Coupled MERIS and <span class="hlt">MODIS</span> Surface Products</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Gao, Feng; Schaaf, Crystal; Jin, Yu-Fang; Lucht, Wolfgang; Strahler, Alan</p> <p>2004-01-01</p> <p>MERIS Level 2 surface <span class="hlt">reflectance</span> products are now available to the scientific community. This paper demonstrates the production of MERIS-derived surface albedo and Nadir Bidirectional <span class="hlt">Reflectance</span> Distribution Function (BRDF) adjusted <span class="hlt">reflectances</span> by coupling the MERIS data with <span class="hlt">MODIS</span> BRDF products. Initial efforts rely on the specification of surface anisotropy as provided by the global <span class="hlt">MODIS</span> BRDF product for a first guess of the shape of the BRDF and then make use all of the coincidently available, partially atmospherically corrected, cloud cleared, MERIS observations to generate MERIS-derived BRDF and surface albedo quantities for each location. Comparisons between <span class="hlt">MODIS</span> (aerosol-corrected) and MERIS (not-yet aerosol-corrected) surface values from April and May 2003 are also presented for case studies in Spain and California as well as preliminary comparisons with field data from the Devil's Rock Surfrad/BSRN site.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/20050060913','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20050060913"><span id="translatedtitle">Estimating Coastal Turbidity using <span class="hlt">MODIS</span> 250 m Band Observations</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Davies, James E.; Moeller, Christopher C.; Gunshor, Mathew M.; Menzel, W. Paul; Walker, Nan D.</p> <p>2004-01-01</p> <p>Terra <span class="hlt">MODIS</span> 250 m observations are being applied to a Suspended Sediment Concentration (SSC) algorithm that is under development for coastal case 2 waters where <span class="hlt">reflectance</span> is dominated by sediment entrained in major fluvial outflows. An atmospheric correction based on <span class="hlt">MODIS</span> observations in the 500 m resolution 1.6 and 2.1 micron bands is used to isolate the remote sensing <span class="hlt">reflectance</span> in the <span class="hlt">MODIS</span> 25Om resolution 650 and 865 nanometer bands. SSC estimates from remote sensing <span class="hlt">reflectance</span> are based on accepted inherent optical properties of sediment types known to be prevalent in the U.S. Gulf of Mexico coastal zone. We present our findings for the Atchafalaya Bay region of the Louisiana Coast, in the form of processed imagery over the annual cycle. We also apply our algorithm to selected sites worldwide with a goal of extending the utility of our approach to the global direct broadcast community.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2011AGUFM.C51A0638R','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2011AGUFM.C51A0638R"><span id="translatedtitle">Cryosphere Broadband Surface Albedo Derivation with <span class="hlt">MODIS</span>-to-CERES Conversion</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Radkevich, A.; Rose, F. G.; Charlock, T. P.; Kato, S.</p> <p>2011-12-01</p> <p>Clouds and the Earth's Radiant Energy System (CERES) instruments on NASA's Earth Observing System (EOS) Terra and <span class="hlt">Aqua</span> satellites measure broadband shortwave and longwave radiation <span class="hlt">reflected</span> and emitted at the Top of the atmosphere (TOA). CERES synthesizes broadband observations with other EOS data streams. The CERES Surface and Atmospheric Radiation Budget (SARB) group matches observations with a radiative transfer code to determine fluxes at several levels. The presentation describes how the next edition of CERES will improve the retrieval of cryosphere surface albedo. Surface albedo is one of the input parameters of numerous models such cloud-resolving model (CRM) simulation, general circulation models (GCMs) and transient climate change simulations. It was recently showed by Park and Wu (2010) that CRM simulation well represents the SW radiative budget during winter because the radiation calculation for the snow-covered period is improved by using prescribed evolving surface albedo. Qu and Hall (2007) analyzed snow albedo feedback (SAF) in several transient climate change models. They stated that high quality observations of albedo of snow-covered surfaces would be extremely useful in reducing SAF spread in the next generation of models. CERES measures radiance and infers flux by applying scene-dependent, empirically based angular distribution models (ADMs). The ADMs are obtained from the complex CERES rotating azimuth plane scan mode to establish BRDF on the scale of 30 km broadband footprints. While CERES has much coarser spatial resolution than <span class="hlt">MODIS</span>, the CERES measurement-based BRDF provides a keen advantage in accuracy over complex surfaces. CERES SARB retrievals of surface albedo have to date been based on only those 30 km footprints that are completely clear; there are too few (~5%) such footprints over sea ice. The upcoming edition of CERES will include <span class="hlt">MODIS</span> radiances in 7 SW bands (currently 4), which are point spread function weighted to both a whole</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2011AGUFMIN14A..01J','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2011AGUFMIN14A..01J"><span id="translatedtitle">USAID Expands e<span class="hlt">MODIS</span> Coverage for Famine Early Warning</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Jenkerson, C.; Meyer, D. J.; Evenson, K.; Merritt, M.</p> <p>2011-12-01</p> <p>Food security in countries at risk is monitored by U.S. Agency for International Development (USAID) through its Famine Early Warning Systems Network (FEWS NET) using many methods including Moderate Resolution Imaging Spectroradiometer (<span class="hlt">MODIS</span>) data processed by U.S. Geological Survey (USGS) into e<span class="hlt">MODIS</span> Normalized Difference Vegetation Index (NDVI) products. Near-real time production is used comparatively with trends derived from the e<span class="hlt">MODIS</span> archive to operationally monitor vegetation anomalies indicating threatened cropland and rangeland conditions. e<span class="hlt">MODIS</span> production over Central America and the Caribbean (CAMCAR) began in 2009, and processes 10-day NDVI composites every 5 days from surface <span class="hlt">reflectance</span> inputs produced using predicted spacecraft and climatology information at Land and Atmosphere Near real time Capability for Earth Observing Systems (EOS) (LANCE). These expedited e<span class="hlt">MODIS</span> composites are backed by a parallel archive of precision-based NDVI calculated from surface <span class="hlt">reflectance</span> data ordered through Level 1 and Atmosphere Archive and Distribution System (LAADS). Success in the CAMCAR region led to the recent expansion of e<span class="hlt">MODIS</span> production to include Africa in 2010, and Central Asia in 2011. Near-real time 250-meter products are available for each region on the last day of an acquisition interval (generally before midnight) from an anonymous file transfer protocol (FTP) distribution site (ftp://emodisftp.cr.usgs.gov/e<span class="hlt">MODIS</span>). The FTP site concurrently hosts the regional historical collections (2000 to present) which are also searchable using the USGS Earth Explorer (http://edcsns17.cr.usgs.gov/NewEarthExplorer). As e<span class="hlt">MODIS</span> coverage continues to grow, these geographically gridded, georeferenced tagged image file format (GeoTIFF) NDVI composites increase their utility as effective tools for operational monitoring of near-real time vegetation data against historical trends.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2006AGUFM.B41A0171L','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2006AGUFM.B41A0171L"><span id="translatedtitle">Mapping Africa Biomass with <span class="hlt">MODIS</span> Imagery</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Laporte, N.; Baccini, A.; Houghton, R.</p> <p>2006-12-01</p> <p>Central Africa contains the second largest block of tropical forest remaining in the world, and is one of the largest carbon reservoirs on Earth. The carbon dynamics of the region differ substantially from other tropical forests because most deforestation and land use is associated with selective logging and small-scale landholders practicing traditional "slash-and-burn" agriculture. Despite estimates of 1-2 PgC/yr released to the atmosphere from tropical deforestation, the amount released from Central Africa is highly uncertain relative to the amounts released from other tropical forest areas. The uncertainty in carbon fluxes results from inadequate estimates of both rates of deforestation and standing stocks of carbon (forest biomass). Here we present new results mapping above-ground forest biomass for tropical Africa using machine learning techniques to integrate <span class="hlt">MODIS</span> 1km spectral <span class="hlt">reflectance</span> with forest inventory measurements to calibrate an empirical relationship. The derived forest biomass at each <span class="hlt">MODIS</span> pixel shows the spatial distribution of forest biomass over the entire tropical forest region. The model has been tested in Uganda, Mali and part of Republic of Congo where field data were available. The regression tree model based on <span class="hlt">MODIS</span> NBAR surface <span class="hlt">reflectance</span> for Uganda, Mali and Republic of Congo explains 94 percent of the variance in above-ground biomass with a root mean square error (RMSE) of 27 Tons/ha. The approach shows promise for use of optical remote sensing data in mapping the spatial distribution of forest biomass across the region.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2012JGRC..117.1011H','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2012JGRC..117.1011H"><span id="translatedtitle">Chlorophyll a algorithms for oligotrophic oceans: A novel approach based on three-band <span class="hlt">reflectance</span> difference</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Hu, Chuanmin; Lee, Zhongping; Franz, Bryan</p> <p>2012-01-01</p> <p>A new empirical algorithm is proposed to estimate surface chlorophyll a (Chl) concentrations in the global ocean for Chl ≤ 0.25 mg m-3(˜78% of the global ocean area). The algorithm is based on a color index (CI), defined as the difference between remote-sensing <span class="hlt">reflectance</span> (Rrs, sr-1) in the green and a reference formed linearly between Rrsin the blue and red. For low-Chl waters, in situ data showed a tighter (and therefore better) relationship between CI and Chl than between traditional band ratios and Chl, which was further validated using global data collected concurrently by ship-borne and Sea-viewing Wide Field-of-view Sensor (SeaWiFS) and Moderate Resolution Imaging Spectroradiometer (<span class="hlt">MODIS)/Aqua</span> instruments. Model simulations showed that for low-Chl waters, compared with the band-ratio algorithm, the CI-based algorithm (CIA) was more tolerant to changes in chlorophyll-specific backscattering coefficient and performed similarly for different relative contributions of nonphytoplankton absorption. Simulations using existing atmospheric correction approaches further demonstrated that the CIA was much less sensitive than band-ratio algorithms to various errors induced by instrument noise and imperfect atmospheric correction (including sun glint and whitecap corrections). Image and time series analyses of SeaWiFS and <span class="hlt">MODIS/Aqua</span> data also showed improved performance in terms of reduced image noise, more coherent spatial and temporal patterns, and better consistency between the two sensors. The reduction in noise and other errors is particularly useful to improve the detection of various ocean features such as eddies. Preliminary tests over Medium-Resolution Imaging Spectrometer and Coastal Zone Color Scanner data indicate that the new approach should be generally applicable to all past, current, and future ocean color instruments.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://ntrs.nasa.gov/search.jsp?R=20080012084&hterms=hdf&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D10%26Ntt%3Dhdf','NASA-TRS'); return false;" href="http://ntrs.nasa.gov/search.jsp?R=20080012084&hterms=hdf&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D10%26Ntt%3Dhdf"><span id="translatedtitle">CERES Single Scanner Satellite Footprint, TOA, Surface Fluxes and Clouds (SSF) data in HDF (CER_SSF_Terra-FM1-<span class="hlt">MODIS</span>_Edition2A)</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Wielicki, Bruce A. (Principal Investigator)</p> <p></p> <p>The Single Scanner Footprint TOA/Surface Fluxes and Clouds (SSF) product contains one hour of instantaneous Clouds and the Earth's Radiant Energy System (CERES) data for a single scanner instrument. The SSF combines instantaneous CERES data with scene information from a higher-resolution imager such as Visible/Infrared Scanner (VIRS) on TRMM or Moderate-Resolution Imaging Spectroradiometer (<span class="hlt">MODIS</span>) on Terra and <span class="hlt">Aqua</span>. Scene identification and cloud properties are defined at the higher imager resolution and these data are averaged over the larger CERES footprint. For each CERES footprint, the SSF contains the number of cloud layers and for each layer the cloud amount, height, temperature, pressure, optical depth, emissivity, ice and liquid water path, and water particle size. The SSF also contains the CERES filtered radiances for the total, shortwave (SW), and window (WN) channels and the unfiltered SW, longwave (LW), and WN radiances. The SW, LW, and WN radiances at spacecraft altitude are converted to Top-of-the-Atmosphere (TOA) fluxes based on the imager defined scene. These TOA fluxes are used to estimate surface fluxes. Only footprints with adequate imager coverage are included on CER_SSF_TRMM-PFM-VIRS_Subset_Edition1the SSF which is much less than the full set of footprints on the CERES ES-8 product. The following CERES SSF data sets are currently available: CER_SSF_TRMM-PFM-VIRS_Edition1 CER_SSF_TRMM-PFM-VIRS_Subset_Edition1 CER_SSF_TRMM-PFM-VIRS_Edition2A CER_SSF_TRMM-SIM-VIRS_Edition2_VIRSonly CER_SSF_TRMM-PFM-VIRS_Edition2A-TransOps CER_SSF_TRMM-PFM-VIRS_Edition2B-TransOps CER_SSF_TRMM-PFM-VIRS_Edition2B CER_SSF_Terra-FM1-<span class="hlt">MODIS</span>_Edition1A CER_SSF_Terra-FM1-<span class="hlt">MODIS</span>_Edition1A CER_SSF_Terra-FM1-<span class="hlt">MODIS</span>_Edition2A CER_SSF_Terra-FM2-<span class="hlt">MODIS</span>_Edition2A CER_SSF_Terra-FM1-<span class="hlt">MODIS</span>_Edition2B CER_SSF_Terra-FM2-<span class="hlt">MODIS</span>_Edition2B CER_SSF_<span class="hlt">Aqua</span>-FM4-<span class="hlt">MODIS</span>_Beta1 CER_SSF_<span class="hlt">Aqua</span>-FM3-<span class="hlt">MODIS</span>_Beta2 CER_SSF_<span class="hlt">Aqua</span>-FM4-<span class="hlt">MODIS</span>_Beta2. [Location=GLOBAL] [Temporal_Coverage: Start_Date=1998-01-01; Stop</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://ntrs.nasa.gov/search.jsp?R=20080012063&hterms=hdf&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D70%26Ntt%3Dhdf','NASA-TRS'); return false;" href="http://ntrs.nasa.gov/search.jsp?R=20080012063&hterms=hdf&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D70%26Ntt%3Dhdf"><span id="translatedtitle">CERES Single Scanner Satellite Footprint, TOA, Surface Fluxes and Clouds (SSF) data in HDF (CER_SSF_Terra-FM1-<span class="hlt">MODIS</span>_Edition1A)</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Wielicki, Bruce A. (Principal Investigator)</p> <p></p> <p>The Single Scanner Footprint TOA/Surface Fluxes and Clouds (SSF) product contains one hour of instantaneous Clouds and the Earth's Radiant Energy System (CERES) data for a single scanner instrument. The SSF combines instantaneous CERES data with scene information from a higher-resolution imager such as Visible/Infrared Scanner (VIRS) on TRMM or Moderate-Resolution Imaging Spectroradiometer (<span class="hlt">MODIS</span>) on Terra and <span class="hlt">Aqua</span>. Scene identification and cloud properties are defined at the higher imager resolution and these data are averaged over the larger CERES footprint. For each CERES footprint, the SSF contains the number of cloud layers and for each layer the cloud amount, height, temperature, pressure, optical depth, emissivity, ice and liquid water path, and water particle size. The SSF also contains the CERES filtered radiances for the total, shortwave (SW), and window (WN) channels and the unfiltered SW, longwave (LW), and WN radiances. The SW, LW, and WN radiances at spacecraft altitude are converted to Top-of-the-Atmosphere (TOA) fluxes based on the imager defined scene. These TOA fluxes are used to estimate surface fluxes. Only footprints with adequate imager coverage are included on CER_SSF_TRMM-PFM-VIRS_Subset_Edition1the SSF which is much less than the full set of footprints on the CERES ES-8 product. The following CERES SSF data sets are currently available: CER_SSF_TRMM-PFM-VIRS_Edition1 CER_SSF_TRMM-PFM-VIRS_Subset_Edition1 CER_SSF_TRMM-PFM-VIRS_Edition2A CER_SSF_TRMM-SIM-VIRS_Edition2_VIRSonly CER_SSF_TRMM-PFM-VIRS_Edition2A-TransOps CER_SSF_TRMM-PFM-VIRS_Edition2B-TransOps CER_SSF_TRMM-PFM-VIRS_Edition2B CER_SSF_Terra-FM1-<span class="hlt">MODIS</span>_Edition1A CER_SSF_Terra-FM1-<span class="hlt">MODIS</span>_Edition1A CER_SSF_Terra-FM1-<span class="hlt">MODIS</span>_Edition2A CER_SSF_Terra-FM2-<span class="hlt">MODIS</span>_Edition2A CER_SSF_Terra-FM1-<span class="hlt">MODIS</span>_Edition2B CER_SSF_Terra-FM2-<span class="hlt">MODIS</span>_Edition2B CER_SSF_<span class="hlt">Aqua</span>-FM4-<span class="hlt">MODIS</span>_Beta1 CER_SSF_<span class="hlt">Aqua</span>-FM3-<span class="hlt">MODIS</span>_Beta2 CER_SSF_<span class="hlt">Aqua</span>-FM4-<span class="hlt">MODIS</span>_Beta2. [Location=GLOBAL] [Temporal_Coverage: Start_Date=1998-01-01; Stop</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://ntrs.nasa.gov/search.jsp?R=20080012102&hterms=hdf&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D40%26Ntt%3Dhdf','NASA-TRS'); return false;" href="http://ntrs.nasa.gov/search.jsp?R=20080012102&hterms=hdf&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D40%26Ntt%3Dhdf"><span id="translatedtitle">CERES Single Scanner Satellite Footprint, TOA, Surface Fluxes and Clouds (SSF) data in HDF (CER_SSF_Terra-FM1-<span class="hlt">MODIS</span>_Edition2B)</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Wielicki, Bruce A. (Principal Investigator)</p> <p></p> <p>The Single Scanner Footprint TOA/Surface Fluxes and Clouds (SSF) product contains one hour of instantaneous Clouds and the Earth's Radiant Energy System (CERES) data for a single scanner instrument. The SSF combines instantaneous CERES data with scene information from a higher-resolution imager such as Visible/Infrared Scanner (VIRS) on TRMM or Moderate-Resolution Imaging Spectroradiometer (<span class="hlt">MODIS</span>) on Terra and <span class="hlt">Aqua</span>. Scene identification and cloud properties are defined at the higher imager resolution and these data are averaged over the larger CERES footprint. For each CERES footprint, the SSF contains the number of cloud layers and for each layer the cloud amount, height, temperature, pressure, optical depth, emissivity, ice and liquid water path, and water particle size. The SSF also contains the CERES filtered radiances for the total, shortwave (SW), and window (WN) channels and the unfiltered SW, longwave (LW), and WN radiances. The SW, LW, and WN radiances at spacecraft altitude are converted to Top-of-the-Atmosphere (TOA) fluxes based on the imager defined scene. These TOA fluxes are used to estimate surface fluxes. Only footprints with adequate imager coverage are included on CER_SSF_TRMM-PFM-VIRS_Subset_Edition1the SSF which is much less than the full set of footprints on the CERES ES-8 product. The following CERES SSF data sets are currently available: CER_SSF_TRMM-PFM-VIRS_Edition1 CER_SSF_TRMM-PFM-VIRS_Subset_Edition1 CER_SSF_TRMM-PFM-VIRS_Edition2A CER_SSF_TRMM-SIM-VIRS_Edition2_VIRSonly CER_SSF_TRMM-PFM-VIRS_Edition2A-TransOps CER_SSF_TRMM-PFM-VIRS_Edition2B-TransOps CER_SSF_TRMM-PFM-VIRS_Edition2B CER_SSF_Terra-FM1-<span class="hlt">MODIS</span>_Edition1A CER_SSF_Terra-FM1-<span class="hlt">MODIS</span>_Edition1A CER_SSF_Terra-FM1-<span class="hlt">MODIS</span>_Edition2A CER_SSF_Terra-FM2-<span class="hlt">MODIS</span>_Edition2A CER_SSF_Terra-FM1-<span class="hlt">MODIS</span>_Edition2B CER_SSF_Terra-FM2-<span class="hlt">MODIS</span>_Edition2B CER_SSF_<span class="hlt">Aqua</span>-FM4-<span class="hlt">MODIS</span>_Beta1 CER_SSF_<span class="hlt">Aqua</span>-FM3-<span class="hlt">MODIS</span>_Beta2 CER_SSF_<span class="hlt">Aqua</span>-FM4-<span class="hlt">MODIS</span>_Beta2. [Location=GLOBAL] [Temporal_Coverage: Start_Date=1998-01-01; Stop</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://ntrs.nasa.gov/search.jsp?R=20080012085&hterms=hdf&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D10%26Ntt%3Dhdf','NASA-TRS'); return false;" href="http://ntrs.nasa.gov/search.jsp?R=20080012085&hterms=hdf&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D10%26Ntt%3Dhdf"><span id="translatedtitle">CERES Single Scanner Satellite Footprint, TOA, Surface Fluxes and Clouds (SSF) data in HDF (CER_SSF_Terra-FM2-<span class="hlt">MODIS</span>_Edition2A)</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Wielicki, Bruce A. (Principal Investigator)</p> <p></p> <p>The Single Scanner Footprint TOA/Surface Fluxes and Clouds (SSF) product contains one hour of instantaneous Clouds and the Earth's Radiant Energy System (CERES) data for a single scanner instrument. The SSF combines instantaneous CERES data with scene information from a higher-resolution imager such as Visible/Infrared Scanner (VIRS) on TRMM or Moderate-Resolution Imaging Spectroradiometer (<span class="hlt">MODIS</span>) on Terra and <span class="hlt">Aqua</span>. Scene identification and cloud properties are defined at the higher imager resolution and these data are averaged over the larger CERES footprint. For each CERES footprint, the SSF contains the number of cloud layers and for each layer the cloud amount, height, temperature, pressure, optical depth, emissivity, ice and liquid water path, and water particle size. The SSF also contains the CERES filtered radiances for the total, shortwave (SW), and window (WN) channels and the unfiltered SW, longwave (LW), and WN radiances. The SW, LW, and WN radiances at spacecraft altitude are converted to Top-of-the-Atmosphere (TOA) fluxes based on the imager defined scene. These TOA fluxes are used to estimate surface fluxes. Only footprints with adequate imager coverage are included on CER_SSF_TRMM-PFM-VIRS_Subset_Edition1the SSF which is much less than the full set of footprints on the CERES ES-8 product. The following CERES SSF data sets are currently available: CER_SSF_TRMM-PFM-VIRS_Edition1 CER_SSF_TRMM-PFM-VIRS_Subset_Edition1 CER_SSF_TRMM-PFM-VIRS_Edition2A CER_SSF_TRMM-SIM-VIRS_Edition2_VIRSonly CER_SSF_TRMM-PFM-VIRS_Edition2A-TransOps CER_SSF_TRMM-PFM-VIRS_Edition2B-TransOps CER_SSF_TRMM-PFM-VIRS_Edition2B CER_SSF_Terra-FM1-<span class="hlt">MODIS</span>_Edition1A CER_SSF_Terra-FM1-<span class="hlt">MODIS</span>_Edition1A CER_SSF_Terra-FM1-<span class="hlt">MODIS</span>_Edition2A CER_SSF_Terra-FM2-<span class="hlt">MODIS</span>_Edition2A CER_SSF_Terra-FM1-<span class="hlt">MODIS</span>_Edition2B CER_SSF_Terra-FM2-<span class="hlt">MODIS</span>_Edition2B CER_SSF_<span class="hlt">Aqua</span>-FM4-<span class="hlt">MODIS</span>_Beta1 CER_SSF_<span class="hlt">Aqua</span>-FM3-<span class="hlt">MODIS</span>_Beta2 CER_SSF_<span class="hlt">Aqua</span>-FM4-<span class="hlt">MODIS</span>_Beta2. [Location=GLOBAL] [Temporal_Coverage: Start_Date=1998-01-01; Stop</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://ntrs.nasa.gov/search.jsp?R=20080012103&hterms=hdf&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D70%26Ntt%3Dhdf','NASA-TRS'); return false;" href="http://ntrs.nasa.gov/search.jsp?R=20080012103&hterms=hdf&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D70%26Ntt%3Dhdf"><span id="translatedtitle">CERES Single Scanner Satellite Footprint, TOA, Surface Fluxes and Clouds (SSF) data in HDF (CER_SSF_Terra-FM2-<span class="hlt">MODIS</span>_Edition2B)</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Wielicki, Bruce A. (Principal Investigator)</p> <p></p> <p>The Single Scanner Footprint TOA/Surface Fluxes and Clouds (SSF) product contains one hour of instantaneous Clouds and the Earth's Radiant Energy System (CERES) data for a single scanner instrument. The SSF combines instantaneous CERES data with scene information from a higher-resolution imager such as Visible/Infrared Scanner (VIRS) on TRMM or Moderate-Resolution Imaging Spectroradiometer (<span class="hlt">MODIS</span>) on Terra and <span class="hlt">Aqua</span>. Scene identification and cloud properties are defined at the higher imager resolution and these data are averaged over the larger CERES footprint. For each CERES footprint, the SSF contains the number of cloud layers and for each layer the cloud amount, height, temperature, pressure, optical depth, emissivity, ice and liquid water path, and water particle size. The SSF also contains the CERES filtered radiances for the total, shortwave (SW), and window (WN) channels and the unfiltered SW, longwave (LW), and WN radiances. The SW, LW, and WN radiances at spacecraft altitude are converted to Top-of-the-Atmosphere (TOA) fluxes based on the imager defined scene. These TOA fluxes are used to estimate surface fluxes. Only footprints with adequate imager coverage are included on CER_SSF_TRMM-PFM-VIRS_Subset_Edition1the SSF which is much less than the full set of footprints on the CERES ES-8 product. The following CERES SSF data sets are currently available: CER_SSF_TRMM-PFM-VIRS_Edition1 CER_SSF_TRMM-PFM-VIRS_Subset_Edition1 CER_SSF_TRMM-PFM-VIRS_Edition2A CER_SSF_TRMM-SIM-VIRS_Edition2_VIRSonly CER_SSF_TRMM-PFM-VIRS_Edition2A-TransOps CER_SSF_TRMM-PFM-VIRS_Edition2B-TransOps CER_SSF_TRMM-PFM-VIRS_Edition2B CER_SSF_Terra-FM1-<span class="hlt">MODIS</span>_Edition1A CER_SSF_Terra-FM1-<span class="hlt">MODIS</span>_Edition1A CER_SSF_Terra-FM1-<span class="hlt">MODIS</span>_Edition2A CER_SSF_Terra-FM2-<span class="hlt">MODIS</span>_Edition2A CER_SSF_Terra-FM1-<span class="hlt">MODIS</span>_Edition2B CER_SSF_Terra-FM2-<span class="hlt">MODIS</span>_Edition2B CER_SSF_<span class="hlt">Aqua</span>-FM4-<span class="hlt">MODIS</span>_Beta1 CER_SSF_<span class="hlt">Aqua</span>-FM3-<span class="hlt">MODIS</span>_Beta2 CER_SSF_<span class="hlt">Aqua</span>-FM4-<span class="hlt">MODIS</span>_Beta2. [Location=GLOBAL] [Temporal_Coverage: Start_Date=1998-01-01; Stop</p> </li> </ol> <div class="pull-right"> <ul class="pagination"> <li><a href="#" onclick='return showDiv("page_1");'>«</a></li> <li><a href="#" onclick='return showDiv("page_16");'>16</a></li> <li><a href="#" onclick='return showDiv("page_17");'>17</a></li> <li class="active"><span>18</span></li> <li><a href="#" onclick='return showDiv("page_19");'>19</a></li> <li><a href="#" onclick='return showDiv("page_20");'>20</a></li> <li><a href="#" onclick='return showDiv("page_25");'>»</a></li> </ul> </div> </div><!-- col-sm-12 --> </div><!-- row --> </div><!-- page_18 --> <div id="page_19" class="hiddenDiv"> <div class="row"> <div class="col-sm-12"> <div class="pull-right"> <ul class="pagination"> <li><a href="#" onclick='return showDiv("page_1");'>«</a></li> <li><a href="#" onclick='return showDiv("page_17");'>17</a></li> <li><a href="#" onclick='return showDiv("page_18");'>18</a></li> <li class="active"><span>19</span></li> <li><a href="#" onclick='return showDiv("page_20");'>20</a></li> <li><a href="#" onclick='return showDiv("page_21");'>21</a></li> <li><a href="#" onclick='return showDiv("page_25");'>»</a></li> </ul> </div> </div> </div> <div class="row"> <div class="col-sm-12"> <ol class="result-class" start="361"> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2013AIPC.1553...69M','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2013AIPC.1553...69M"><span id="translatedtitle">Towards identification of relevant variables in the observed aerosol optical depth bias between <span class="hlt">MODIS</span> and AERONET observations</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Malakar, N. K.; Lary, D. J.; Gencaga, D.; Albayrak, A.; Wei, J.</p> <p>2013-08-01</p> <p>Measurements made by satellite remote sensing, Moderate Resolution Imaging Spectroradiometer (<span class="hlt">MODIS</span>), and globally distributed Aerosol Robotic Network (AERONET) are compared. Comparison of the two datasets measurements for aerosol optical depth values show that there are biases between the two data products. In this paper, we present a general framework towards identifying relevant set of variables responsible for the observed bias. We present a general framework to identify the possible factors influencing the bias, which might be associated with the measurement conditions such as the solar and sensor zenith angles, the solar and sensor azimuth, scattering angles, and surface <span class="hlt">reflectivity</span> at the various measured wavelengths, etc. Specifically, we performed analysis for remote sensing <span class="hlt">Aqua</span>-Land data set, and used machine learning technique, neural network in this case, to perform multivariate regression between the ground-truth and the training data sets. Finally, we used mutual information between the observed and the predicted values as the measure of similarity to identify the most relevant set of variables. The search is brute force method as we have to consider all possible combinations. The computations involves a huge number crunching exercise, and we implemented it by writing a job-parallel program.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2014AGUFM.C43D0433M','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2014AGUFM.C43D0433M"><span id="translatedtitle"><span class="hlt">MODIS</span> Data and Services at the National Snow and Ice Data Center (NSIDC)</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>McAllister, M.; Booker, L.; Fowler, D. K.; Haran, T. M.</p> <p>2014-12-01</p> <p>For close to 15 years, the National Snow and Ice Data Center (NSIDC) NASA Distributed Active Archive Center (NDAAC) has archived and distributed snow and sea ice products derived from the Moderate Resolution Imaging Spectroradiometer (<span class="hlt">MODIS</span>) instruments on the NASA Earth Observing System (EOS) <span class="hlt">Aqua</span> and Terra satellites. The archive contains a wide selection of snow and sea ice data products relevant to cryospheric science. NSIDC offers a variety of methods for obtaining these data. Users can ftp data directly from an online archive which allows for a very quick download. The Reverb Search & Order Tool contains a complete set of metadata for all products which can be searched for and ordered. Reverb allows a user to order spatial, temporal, and parameter subsets of the data. Users can also request that they be added to our subscription list which makes it possible to have new <span class="hlt">MODIS</span> data automatically ftp'd or staged on a local server as it is archived at NSIDC. Since <span class="hlt">MODIS</span> products are in HDF-EOS format, a number of tools have been developed to assist with browsing, editing, reprojection, resampling, and format conversion. One such service, Data Access, can be accessed through Reverb and performs subsetting, reformatting, and reprojection. This service can also be accessed via an Application Programming Interface (API) from a user-written client. Other tools include the <span class="hlt">MODIS</span> Swath-to-Grid Toolbox (MS2GT) and the <span class="hlt">MODIS</span> Interactive Subsetting Tool (MIST). MS2GT was created to produce a seamless output grid from multiple input files corresponding to successively acquired, 5-minute <span class="hlt">MODIS</span> scenes. NSIDC also created the MIST to provide subsets of certain Version 5 <span class="hlt">MODIS</span> products, over the Greenland Climate Network (GC-Net) and the International Arctic Systems for Observing the Atmosphere (IASOA) stations. Tools from other sources include HDFView from the National Center for Supercomputing Applications (NCSA), and the <span class="hlt">MODIS</span> Reprojection Tool (MRT) and MRT Swath developed</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://ntrs.nasa.gov/search.jsp?R=GL-2002-001441&hterms=Wisconsin+Madison&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D80%26Ntt%3DWisconsin%2BMadison','NASA-TRS'); return false;" href="http://ntrs.nasa.gov/search.jsp?R=GL-2002-001441&hterms=Wisconsin+Madison&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D80%26Ntt%3DWisconsin%2BMadison"><span id="translatedtitle"><span class="hlt">MODIS</span> Views Variations in Cloud Types</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p></p> <p>2002-01-01</p> <p>This <span class="hlt">MODIS</span> image, centered over the Great Lakes region in North America, shows a variety of cloud types. The clouds at the top of the image, colored pink, are cold, high-level snow and ice clouds, while the neon green clouds are lower-level water clouds. Because different cloud types <span class="hlt">reflect</span> and emit radiant energy differently, scientists can use <span class="hlt">MODIS</span>' unique data set to measure the sizes of cloud particles and distinguish between water, snow, and ice clouds. This scene was acquired on Feb. 24, 2000, and is a red, green, blue composite of bands 1, 6, and 31 (0.66, 1.6, and 11.0 microns, respectively). Image by Liam Gumley, Space Science and Engineering Center, University of Wisconsin-Madison</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://ntrs.nasa.gov/search.jsp?R=GL-2002-001462&hterms=North+pole&qs=N%3D0%26Ntk%3DAll%26Ntx%3Dmode%2Bmatchall%26Ntt%3DNorth%2Bpole','NASA-TRS'); return false;" href="http://ntrs.nasa.gov/search.jsp?R=GL-2002-001462&hterms=North+pole&qs=N%3D0%26Ntk%3DAll%26Ntx%3Dmode%2Bmatchall%26Ntt%3DNorth%2Bpole"><span id="translatedtitle"><span class="hlt">MODIS</span> Views North Pole</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p></p> <p>2002-01-01</p> <p>This true-color image over the North Pole was acquired by the MODerate-resolution Imaging Spectroradiometer (<span class="hlt">MODIS</span>), flying aboard the Terra spacecraft, on May 5, 2000. The scene was received and processed by Norway's <span class="hlt">MODIS</span> Direct Broadcast data receiving station, located in Svalbard, within seconds of photons hitting the sensor's detectors. (Click for more details about <span class="hlt">MODIS</span> Direct Broadcast data.) In this image, the sea ice appears white and areas of open water, or recently refrozen sea surface, appear black. The irregular whitish shapes toward the bottom of the image are clouds, which are often difficult to distinguish from the white Arctic surface. Notice the considerable number of cracks, or 'leads,' in the ice that appear as dark networks of lines. Throughout the region within the Arctic Circle leads are continually opening and closing due to the direction and intensity of shifting wind and ocean currents. Leads are particularly common during the summer, when temperatures are higher and the ice is thinner. In this image, each pixel is one square kilometer. Such true-color views of the North Pole are quite rare, as most of the time much of the region within the Arctic Circle is cloaked in clouds. Image by Allen Lunsford, NASA GSFC Direct Readout Laboratory; Data courtesy Tromso receiving station, Svalbard, Norway</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2013GeoRL..40..772B','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2013GeoRL..40..772B"><span id="translatedtitle">Properties of linear contrails in the Northern Hemisphere derived from 2006 <span class="hlt">Aqua</span> <span class="hlt">MODIS</span> observations</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Bedka, Sarah T.; Minnis, Patrick; Duda, David P.; Chee, Thad L.; Palikonda, Rabindra</p> <p>2013-02-01</p> <p>Understanding the role of contrails in the Earth's radiation budget requires an accurate characterization of their macrophysical and microphysical properties, such as cloud top temperature, optical depth, and effective particle size. These properties are derived from 2006 MODerate-resolution Imaging Spectroradiometer data over the Northern Hemisphere using a bi-spectral, infrared-only retrieval technique. Contrail temperature is estimated using a quadratic relationship of flight track pressure with latitude. The results reveal distinct seasonal trends in contrail microphysical properties, with slightly greater mean optical depths and slightly smaller particle sizes during summer. The average contrail optical depth and particle effective diameter are 0.216 and 35.7 µm, respectively. Although fewer contrails occurred at night, there are no appreciable diurnal differences in their retrieved properties. These results should help to fill the gap in our knowledge of contrail properties and will be valuable for model validation.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://ntrs.nasa.gov/search.jsp?R=20030052219&hterms=spectroradiometer+MODIS&qs=N%3D0%26Ntk%3DAll%26Ntx%3Dmode%2Bmatchall%26Ntt%3Dspectroradiometer%2BMODIS','NASA-TRS'); return false;" href="http://ntrs.nasa.gov/search.jsp?R=20030052219&hterms=spectroradiometer+MODIS&qs=N%3D0%26Ntk%3DAll%26Ntx%3Dmode%2Bmatchall%26Ntt%3Dspectroradiometer%2BMODIS"><span id="translatedtitle">An Overview of the Earth Observing System Moderate Resolution Imaging Spectroradiometer (<span class="hlt">MODIS</span>) Data Products and Availability for Environmental Applications and Global Change Studies</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Salomonson, V. V.</p> <p>2003-01-01</p> <p>The Moderate Resolution Imaging Spectroradiometer (<span class="hlt">MODIS</span>) on the Earth Observing System (EOS) Terra Mission began to produce data in February 2000. The Terra <span class="hlt">MODIS</span> is in a sun-synchronous orbit going north to south in the daylight portion of the orbit crossing the equator at about 1030 hours local time. The spacecraft, instrument, and data systems are performing well and are producing a wide variety of data products useful for scientific and applications studies in relatively consistent fashion extending from November 2000 to the present. Within the approximately 40 <span class="hlt">MODIS</span> data products, several are new and represent powerful and exciting capabilities such the ability to provide observations over the globe of fire occurrences, microphysical properties of clouds and sun-stimulated fluorescence from phytoplankton in the surface waters of the ocean. The remainder of the <span class="hlt">MODIS</span> products exceeds or, at a minimum, matches the capabilities of products from heritage sensors such as, for example, the Advanced Very High Resolution Radiometer (AVHRR). Efforts are underway to provide data sets for the greater Earth science community and to improve access to these products at the various Distributed Active Archive Centers (DAACs) or through Direct Broadcast (DB) stations. The EOS <span class="hlt">Aqua</span> mission was launched successfully May 4,2002 with another <span class="hlt">MODIS</span> on it. The <span class="hlt">Aqua</span> spacecraft operates in a sun-synchronous orbit going south to north in the daylight portion of the orbit crossing the equator at approximately 1330 hours local time. Subsequently the <span class="hlt">Aqua</span> <span class="hlt">MODIS</span> observations will substantially add to the capabilities of the Terra <span class="hlt">MODIS</span> for environmental applications and global change studies.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://ntrs.nasa.gov/search.jsp?R=20020060730&hterms=spectroradiometer+MODIS&qs=N%3D0%26Ntk%3DAll%26Ntx%3Dmode%2Bmatchall%26Ntt%3Dspectroradiometer%2BMODIS','NASA-TRS'); return false;" href="http://ntrs.nasa.gov/search.jsp?R=20020060730&hterms=spectroradiometer+MODIS&qs=N%3D0%26Ntk%3DAll%26Ntx%3Dmode%2Bmatchall%26Ntt%3Dspectroradiometer%2BMODIS"><span id="translatedtitle">An Overview of the Earth Observing System Moderate Resolution Imaging Spectroradiometer (<span class="hlt">MODIS</span>) Data Products Status and Availability for Environmental Applications and Global Change Studies</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Salomonson, Vincent V.; Houser, Paul (Technical Monitor)</p> <p>2002-01-01</p> <p>The Moderate Resolution Imaging Spectroradiometer (<span class="hlt">MODIS</span>) on the Earth Observing System (EOS) Terra Mission began to produce data in February 2000. The Terra <span class="hlt">MODIS</span> is in a sun-synchronous orbit going north to south in the daylight portion of the orbit crossing the equator at about 1030 hours local time. The spacecraft, instrument, and data systems are performing well and are producing a wide variety of data products useful for scientific and applications studies in relatively consistent fashion extending from November 2000 to the present. Within the approximately 40 <span class="hlt">MODIS</span> data products, several are new and represent powerful and exciting capabilities such the ability to provide observations over the globe of fire occurrences, microphysical properties of clouds and sun-stimulated fluorescence from phytoplankton in the surface waters of the ocean. The remainder of the <span class="hlt">MODIS</span> products exceed or, at a minimum, match the capabilities of products from heritage sensors such as, for example, the Advanced Very High Resolution Radiometer (AVHRR). Efforts are underway to provide data sets for the greater Earth science community and to improve access to these products at the various Distributed Active Archive Centers (DAAC's) or through Direct Broadcast (DB) stations. The <span class="hlt">MODIS</span> instrument on the EOS <span class="hlt">Aqua</span> mission should also be expected to be in orbit and functioning in the Spring of 2002. The <span class="hlt">Aqua</span> spacecraft will operate in a sun-synchronous orbit going south to north in the daylight portion of the orbit crossing the equator at approximately 1330 hours local time. Subsequently the <span class="hlt">Aqua</span> <span class="hlt">MODIS</span> observations will substantially add to the capabilities of the Terra <span class="hlt">MODIS</span> for environmental applications and global change studies.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://ntrs.nasa.gov/search.jsp?R=20040013413&hterms=lille&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D70%26Ntt%3Dlille','NASA-TRS'); return false;" href="http://ntrs.nasa.gov/search.jsp?R=20040013413&hterms=lille&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D70%26Ntt%3Dlille"><span id="translatedtitle">Dust Transport, Deposition and Radiative Effects Observed from <span class="hlt">MODIS</span></span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Kaufman, Y. J.; Koren, I.; Remer, L. A.; Tanre, D.; Ginoux, P.; Fan, S.</p> <p>2003-01-01</p> <p>Carlson (1977) used satellite (AVHRR) observation of dust episodes 3 estimate that 90 tg of dust are emitted from Africa (0-30 N) to the Atlantic Ocean between June and August. <span class="hlt">MODIS</span> systematic measurements of aerosol optical thickness (AOT) and the fraction of the AOT (f) due to the fine mode (see Remer et al abstract), are used to derive the column concentration, flux and deposition of African dust over the Atlantic Ocean. The main data set is for 2001 but the results are consistent with <span class="hlt">MODIS</span> measurements from 2002. The analysis first determines the properties of maritime baseline aerosol (AOT=0.06, f=0.5); followed by linear scaling of the dust AOT and the anthropogenic AOT, based on <span class="hlt">MODIS</span> measured values of the fraction "f" being 0.9 for anthropogenic aerosol and 0.5 for dust. NCEP winds are used in the analysis and are evaluated against observed dust movements between the Terra and <span class="hlt">Aqua</span> passes (see Koren et al. abstract). Monthly values of dust transport and deposition are calculated. Preliminary results show that 280 tg of dust are emitted annually from Africa to the Atlantic Ocean between 20s and 30N, with 40 tg returning to Africa and Europe between 30N and 50N. 85 tg reach the Americas, with 130-150 tg are deposited in the Atlantic Ocean. The results are compared with dust transport models that indicate 110-230 tg of dust being deposited in the Ocean. It is interesting to note that the early estimates of Carlson (1977) and Carlson & Prosper0 (1972) are very close to our estimate from <span class="hlt">MODIS</span> of 100 tg for the same latitude range and monthly period.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2012AMT.....5..389V','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2012AMT.....5..389V"><span id="translatedtitle">Analysis of co-located <span class="hlt">MODIS</span> and CALIPSO observations near clouds</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Várnai, T.; Marshak, A.</p> <p>2012-02-01</p> <p>This paper aims at helping synergistic studies in combining data from different satellites for gaining new insights into two critical yet poorly understood aspects of anthropogenic climate change, aerosol-cloud interactions and aerosol radiative effects. In particular, the paper examines the way cloud information from the <span class="hlt">MODIS</span> (MODerate resolution Imaging Spectroradiometer) imager can refine our perceptions based on CALIOP (Cloud-Aerosol Lidar with Orthogonal Polarization) lidar measurements about the systematic aerosol changes that occur near clouds. The statistical analysis of a yearlong dataset of co-located global maritime observations from the <span class="hlt">Aqua</span> and CALIPSO (Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation) satellites reveals that <span class="hlt">MODIS</span>'s multispectral imaging ability can greatly help the interpretation of CALIOP observations. The results show that imagers on <span class="hlt">Aqua</span> and CALIPSO yield very similar pictures, and that the discrepancies - due mainly to wind drift and differences in view angle - do not significantly hinder aerosol measurements near clouds. By detecting clouds outside the CALIOP track, <span class="hlt">MODIS</span> reveals that clouds are usually closer to clear areas than CALIOP data alone would suggest. The paper finds statistical relationships between the distances to clouds in <span class="hlt">MODIS</span> and CALIOP data, and proposes a rescaling approach to statistically account for the impact of clouds outside the CALIOP track even when <span class="hlt">MODIS</span> cannot reliably detect low clouds, for example at night or over sea ice. Finally, the results show that the typical distance to clouds depends on both cloud coverage and cloud type, and accordingly varies with location and season. In maritime areas perceived cloud free, the global median distance to clouds below 3 km altitude is in the 4-5 km range.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2013AMTD....6..159L','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2013AMTD....6..159L"><span id="translatedtitle">The Collection 6 <span class="hlt">MODIS</span> aerosol products over land and ocean</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Levy, R. C.; Mattoo, S.; Munchak, L. A.; Remer, L. A.; Sayer, A. M.; Hsu, N. C.</p> <p>2013-01-01</p> <p>The twin Moderate Imaging resolution Spectroradiometer (<span class="hlt">MODIS</span>) sensors have been flying on Terra since 2000 and <span class="hlt">Aqua</span> since 2002, creating an incredible dataset of global Earth observations. Here, we introduce the Collection 6 (C6) algorithm to retrieve aerosol optical depth (AOD) and aerosol size parameters from <span class="hlt">MODIS</span>-observed spectral <span class="hlt">reflectance</span>. While not a major overhaul from the previous Collection 5 (C5) version, there are enough changes that there is significant impact on the products and their interpretation. The C6 algorithm is comprised of three sub-algorithms for retrieving aerosol properties (1) over ocean (dark in visible and near-IR wavelengths), (2) over vegetated/dark-soiled land (dark in the visible) and (3) over desert/arid land (bright in the visible). Here, we focus on the changes to both "dark target" algorithms (#1 and #2; DT-ocean and DT-land). Affecting both DT algorithms, we have updated assumptions for central wavelengths, Rayleigh optical depths and gas (H2O, O3, CO2, etc.) absorption corrections, and relaxed the solar zenith angle limit (up to ≤ 84°) to increase pole-ward coverage. For DT-land, we have updated the cloud mask to allow heavy smoke retrievals, fine-tuned the assignments for aerosol type as function of season/location, corrected bugs in the Quality Assurance (QA) logic, and added diagnostic parameters such topographic altitude. For DT-ocean, improvements include a revised cloud mask for thin-cirrus detection, inclusion of wind speed dependence in the retrieval, updates to logic of QA Confidence flag (QAC) assignment, and additions of important diagnostic information. All together, the changes to the DT algorithms result in reduced global AOD (by 0.02) over ocean and increased AOD (by 0.01) over land, along with some changes in spatial coverage. Preliminary validation shows that compared to surface-based sunphotometer data, the C6 DT-products should compare at least as well as those from C5. However, at the same time as we</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/20120015808','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20120015808"><span id="translatedtitle">Application of <span class="hlt">MODIS</span> Products to Infer Possible Relationships Between Basin Land Cover and Coastal Waters Turbidity Using the Magdalena River, Colombia, as a Case Study</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Madrinan, Max Jacobo Moreno; Cordova, Africa Flores; Olivares, Francisco Delgado; Irwin, Dan</p> <p>2012-01-01</p> <p>Basin development and consequent change in basin land cover have been often associated with an increased turbidity in coastal waters because of sediment yield and nutrients loading. The later leads to phytoplankton abundance further exacerbating water turbidity. This subsequently affects biological and physical processes in coastal estuaries by interfering with sun light penetration to coral reefs and sea grass, and even affecting public health. Therefore, consistent estimation of land cover changes and turbidity trend lines is crucial to design environmental and restoration management plans, to predict fate of possible pollutants, and to estimate sedimentary fluxes into the ocean. Ground solely methods to estimate land cover change would be unpractical and traditional methods of monitoring in situ water turbidity can be very expensive and time consuming. Accurate monitoring on the status and trends of basin land cover as well as the water quality of the receiving water bodies are required for analysis of relationships between the two variables. Use of remote sensing (RS) technology provides a great benefit for both fields of study, facilitating monitoring of changes in a timely and cost effective manner and covering wide areas with long term measurements. In this study, the Magdalena River basin and fixed geographical locations in the estuarine waters of its delta are used as a case to study the temporal trend lines of both, land cover change and the <span class="hlt">reflectance</span> of the water turbidity using satellite technology. Land cover data from a combined product between sensors Terra and <span class="hlt">Aqua</span> (MCD12Q1) from <span class="hlt">MODIS</span> will be adapted to the conditions in the Magdalena basin to estimate changes in land cover since year 2000 to 2009. Surface <span class="hlt">reflectance</span> data from a <span class="hlt">MODIS</span>, Terra (MOD09GQ), band 1, will be used in lieu of in situ water turbidity for the time period between 2000 and present. Results will be compared with available existing data.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/20060047785','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20060047785"><span id="translatedtitle">Aerosol Lidar and <span class="hlt">MODIS</span> Satellite Comparisons for Future Aerosol Loading Forecast</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>DeYoung, Russell; Szykman, James; Severance, Kurt; Chu, D. Allen; Rosen, Rebecca; Al-Saadi, Jassim</p> <p>2006-01-01</p> <p>Knowledge of the concentration and distribution of atmospheric aerosols using both airborne lidar and satellite instruments is a field of active research. An aircraft based aerosol lidar has been used to study the distribution of atmospheric aerosols in the California Central Valley and eastern US coast. Concurrently, satellite aerosol retrievals, from the <span class="hlt">MODIS</span> (Moderate Resolution Imaging Spectroradiometer) instrument aboard the Terra and <span class="hlt">Aqua</span> satellites, were take over the Central Valley. The <span class="hlt">MODIS</span> Level 2 aerosol data product provides retrieved ambient aerosol optical properties (e.g., optical depth (AOD) and size distribution) globally over ocean and land at a spatial resolution of 10 km. The Central Valley topography was overlaid with <span class="hlt">MODIS</span> AOD (5x5 sq km resolution) and the aerosol scattering vertical profiles from a lidar flight. Backward air parcel trajectories for the lidar data show that air from the Pacific and northern part of the Central Valley converge confining the aerosols to the lower valley region and below the mixed layer. Below an altitude of 1 km, the lidar aerosol and <span class="hlt">MODIS</span> AOD exhibit good agreement. Both data sets indicate a high presence of aerosols near Bakersfield and the Tehachapi Mountains. These and other results to be presented indicate that the majority of the aerosols are below the mixed layer such that the <span class="hlt">MODIS</span> AOD should correspond well with surface measurements. Lidar measurements will help interpret satellite AOD retrievals so that one day they can be used on a routine basis for prediction of boundary layer aerosol pollution events.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/20110007302','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20110007302"><span id="translatedtitle">Multilayer Cloud Detection with the <span class="hlt">MODIS</span> Near-Infrared Water Vapor Absorption Band</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Wind, Galina; Platnick, Steven; King, Michael D.; Hubanks, Paul A,; Pavolonis, Michael J.; Heidinger, Andrew K.; Yang, Ping; Baum, Bryan A.</p> <p>2009-01-01</p> <p>Data Collection 5 processing for the Moderate Resolution Imaging Spectroradiometer (<span class="hlt">MODIS</span>) onboard the NASA Earth Observing System EOS Terra and <span class="hlt">Aqua</span> spacecraft includes an algorithm for detecting multilayered clouds in daytime. The main objective of this algorithm is to detect multilayered cloud scenes, specifically optically thin ice cloud overlying a lower-level water cloud, that presents difficulties for retrieving cloud effective radius using single layer plane-parallel cloud models. The algorithm uses the <span class="hlt">MODIS</span> 0.94 micron water vapor band along with CO2 bands to obtain two above-cloud precipitable water retrievals, the difference of which, in conjunction with additional tests, provides a map of where multilayered clouds might potentially exist. The presence of a multilayered cloud results in a large difference in retrievals of above-cloud properties between the CO2 and the 0.94 micron methods. In this paper the <span class="hlt">MODIS</span> multilayered cloud algorithm is described, results of using the algorithm over example scenes are shown, and global statistics for multilayered clouds as observed by <span class="hlt">MODIS</span> are discussed. A theoretical study of the algorithm behavior for simulated multilayered clouds is also given. Results are compared to two other comparable passive imager methods. A set of standard cloudy atmospheric profiles developed during the course of this investigation is also presented. The results lead to the conclusion that the <span class="hlt">MODIS</span> multilayer cloud detection algorithm has some skill in identifying multilayered clouds with different thermodynamic phases</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/20110007890','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20110007890"><span id="translatedtitle">Estimation of Surface Air Temperature from <span class="hlt">MODIS</span> 1km Resolution Land Surface Temperature Over Northern China</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Shen, Suhung; Leptoukh, Gregory G.; Gerasimov, Irina</p> <p>2010-01-01</p> <p>Surface air temperature is a critical variable to describe the energy and water cycle of the Earth-atmosphere system and is a key input element for hydrology and land surface models. It is a very important variable in agricultural applications and climate change studies. This is a preliminary study to examine statistical relationships between ground meteorological station measured surface daily maximum/minimum air temperature and satellite remotely sensed land surface temperature from <span class="hlt">MODIS</span> over the dry and semiarid regions of northern China. Studies were conducted for both <span class="hlt">MODIS</span>-Terra and <span class="hlt">MODIS-Aqua</span> by using year 2009 data. Results indicate that the relationships between surface air temperature and remotely sensed land surface temperature are statistically significant. The relationships between the maximum air temperature and daytime land surface temperature depends significantly on land surface types and vegetation index, but the minimum air temperature and nighttime land surface temperature has little dependence on the surface conditions. Based on linear regression relationship between surface air temperature and <span class="hlt">MODIS</span> land surface temperature, surface maximum and minimum air temperatures are estimated from 1km <span class="hlt">MODIS</span> land surface temperature under clear sky conditions. The statistical errors (sigma) of the estimated daily maximum (minimum) air temperature is about 3.8 C(3.7 C).</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://ntrs.nasa.gov/search.jsp?R=20160005182&hterms=modis&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DTitle%26N%3D0%26No%3D40%26Ntt%3Dmodis','NASA-TRS'); return false;" href="http://ntrs.nasa.gov/search.jsp?R=20160005182&hterms=modis&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DTitle%26N%3D0%26No%3D40%26Ntt%3Dmodis"><span id="translatedtitle">Status of Terra <span class="hlt">MODIS</span> Operation, Calibration, and Performance</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Xiong, X.; Wenny, B.; Wu, A.; Angal, A.; Geng, X.; Chen, H.; Dodd, J.; Link, D.; Madhavan, S.; Chen, N.; Li, Y.; Iacangelo, S.; Barnes, W.; Salomonson, V.</p> <p>2014-01-01</p> <p>Since launch in December 1999, Terra <span class="hlt">MODIS</span> has successfully operated for nearly 15 years, making continuous observations. Data products derived from <span class="hlt">MODIS</span> 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 <span class="hlt">MODIS</span> 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. <span class="hlt">MODIS</span> observations are made in 36 spectral bands, covering wavelengths from visible to long-wave infrared. The <span class="hlt">reflective</span> 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 <span class="hlt">MODIS</span> 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 <span class="hlt">MODIS</span> level 1B (L1B) data quality, and efforts for future improvements.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2010cosp...38..167R','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2010cosp...38..167R"><span id="translatedtitle">Ground based measurements on <span class="hlt">reflectance</span> towards validating atmospheric correction algorithms on IRS-P6 AWiFS data</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Rani Sharma, Anu; Kharol, Shailesh Kumar; Kvs, Badarinath; Roy, P. S.</p> <p></p> <p> aggregated ground measurements which showed a very good correlation of 0.96 in all four spectral bands (i.e. green, red, NIR and SWIR). In order to quantify the accuracy of the proposed method in the estimation of the surface <span class="hlt">reflectance</span>, the root mean square error (RMSE) associated to the proposed method was evaluated. The analysis of the ground measured versus retrieved AWiFS <span class="hlt">reflectance</span> yielded smaller RMSE values in case of all four spectral bands. EOS TERRA/<span class="hlt">AQUA</span> <span class="hlt">MODIS</span> derived AOD exhibited very good correlation of 0.92 and the data sets provides an effective means for carrying out atmospheric corrections in an operational way. Keywords: Atmospheric correction, 6S code, <span class="hlt">MODIS</span>, Spectroradiometer, Sun-Photometer</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://www.osti.gov/scitech/servlets/purl/1110474','SCIGOV-STC'); return false;" href="http://www.osti.gov/scitech/servlets/purl/1110474"><span id="translatedtitle">Visual Modeling for <span class="hlt">Aqua</span> Ventus I off Monhegan Island, ME</span></a></p> <p><a target="_blank" href="http://www.osti.gov/scitech">SciTech Connect</a></p> <p>Hanna, Luke A.; Whiting, Jonathan M.; Copping, Andrea E.</p> <p>2013-11-27</p> <p>To assist the University of Maine in demonstrating a clear pathway to project completion, PNNL has developed visualization models of the <span class="hlt">Aqua</span> Ventus I project that accurately depict the <span class="hlt">Aqua</span> Ventus I turbines from various points on Monhegain Island, ME and the surrounding area. With a hub height of 100 meters, the <span class="hlt">Aqua</span> Ventus I turbines are large and may be seen from many areas on Monhegan Island, potentially disrupting important viewsheds. By developing these visualization models, which consist of actual photographs taken from Monhegan Island and the surrounding area with the <span class="hlt">Aqua</span> Ventus I turbines superimposed within each photograph, PNNL intends to support the project’s siting and permitting process by providing the Monhegan Island community and various other stakeholders with a probable glimpse of how the <span class="hlt">Aqua</span> Ventus I project will appear.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/19940028783','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/19940028783"><span id="translatedtitle"><span class="hlt">MODIS</span>. Volume 2: <span class="hlt">MODIS</span> level 1 geolocation, characterization and calibration algorithm theoretical basis document, version 1</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Barker, John L.; Harnden, Joann M. K.; Montgomery, Harry; Anuta, Paul; Kvaran, Geir; Knight, ED; Bryant, Tom; Mckay, AL; Smid, Jon; Knowles, Dan, Jr.</p> <p>1994-01-01</p> <p>The EOS Moderate Resolution Imaging Spectrometer (<span class="hlt">MODIS</span>) is being developed by NASA for flight on the Earth Observing System (EOS) series of satellites, the first of which (EOS-AM-1) is scheduled for launch in 1998. This document describes the algorithms and their theoretical basis for the <span class="hlt">MODIS</span> Level 1B characterization, calibration, and geolocation algorithms which must produce radiometrically, spectrally, and spatially calibrated data with sufficient accuracy so that Global change research programs can detect minute changes in biogeophysical parameters. The document first describes the geolocation algorithm which determines geodetic latitude, longitude, and elevation of each <span class="hlt">MODIS</span> pixel and the determination of geometric parameters for each observation (satellite zenith angle, satellite azimuth, range to the satellite, solar zenith angle, and solar azimuth). Next, the utilization of the <span class="hlt">MODIS</span> onboard calibration sources, which consist of the Spectroradiometric Calibration Assembly (SRCA), Solar Diffuser (SD), Solar Diffuser Stability Monitor (SDSM), and the Blackbody (BB), is treated. Characterization of these sources and integration of measurements into the calibration process is described. Finally, the use of external sources, including the Moon, instrumented sites on the Earth (called vicarious calibration), and unsupervised normalization sites having invariant <span class="hlt">reflectance</span> and emissive properties is treated. Finally, algorithms for generating utility masks needed for scene-based calibration are discussed. Eight appendices are provided, covering instrument design and additional algorithm details.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/cgi-bin/nph-data_query?bibcode=2013JARS....7.3557T&link_type=ABSTRACT','NASAADS'); return false;" href="http://adsabs.harvard.edu/cgi-bin/nph-data_query?bibcode=2013JARS....7.3557T&link_type=ABSTRACT"><span id="translatedtitle">Terra and <span class="hlt">Aqua</span> moderate-resolution imaging spectroradiometer collection 6 level 1B algorithm</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Toller, Gary; Xiong, Xiaoxiong; Sun, Junqiang; Wenny, Brian N.; Geng, Xu; Kuyper, James; Angal, Amit; Chen, Hongda; Madhavan, Sriharsha; Wu, Aisheng</p> <p>2013-01-01</p> <p>The moderate-resolution imaging spectroradiometer (<span class="hlt">MODIS</span>) was launched on the Terra spacecraft on Dec.18, 1999 and on Aquaon May 4, 2002. The data acquired by these instruments have contributed to the long-term climate data record for more than a decade and represent a key component of NASA's Earth observing system. Each <span class="hlt">MODIS</span> instrument observes nearly the whole Earth each day, enabling the scientific characterization of the land, ocean, and atmosphere. The <span class="hlt">MODIS</span> Level 1B (L1B) algorithms input uncalibrated geo-located observations and convert instrument response into calibrated <span class="hlt">reflectance</span> and radiance, which are used to generate science data products. The instrument characterization needed to run the L1B code is currently implemented using time-dependent lookup tables. The <span class="hlt">MODIS</span> characterization support team, working closely with the <span class="hlt">MODIS</span> Science Team, has improved the product quality with each data reprocessing. We provide an overview of the new L1B algorithm release, designated collection 6. Recent improvements made as a consequence of on-orbit calibration, on-orbit analyses, and operational considerations are described. Instrument performance and the expected impact of L1B changes on the collection 6 L1B products are discussed.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2016CSR...112...14C','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2016CSR...112...14C"><span id="translatedtitle">Estimation of water turbidity and analysis of its spatio-temporal variability in the Danube River plume (Black Sea) using <span class="hlt">MODIS</span> satellite data</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Constantin, Sorin; Doxaran, David; Constantinescu, Ștefan</p> <p>2016-01-01</p> <p>Ocean colour remote sensing information brings important insights for monitoring coastal areas. These regions are home to important natural ecosystems and changes that occur here can have important impacts not only on the local environment, but also on connected wetlands or offshore areas. The present study proposes a new regional methodology for water turbidity retrieval using the <span class="hlt">MODIS</span> red band at 250 m spatial resolution in the Danube Delta coastal area. For this purpose, multiple in-situ turbidity observations were used in order to determine a valid relationship between data collected with turbidity meters and remote sensing <span class="hlt">reflectance</span> obtained from satellite data. A special attention is given to the atmospheric correction of satellite data, since complex optical waters require adapted methodologies for accurate remote sensing <span class="hlt">reflectance</span> computation. Based on products derived using the proposed algorithm, the dynamics of turbidity is evaluated for multiple time periods: from local Terra to <span class="hlt">Aqua</span> overpasses (couple of hours), daily and monthly. Results show a clear strong connection between the Danube discharge and water turbidity in the coastal area. However other environmental parameters (e.g., wind stress) also play an important role and contribute to the magnitude of the river plume extension.</p> </li> </ol> <div class="pull-right"> <ul class="pagination"> <li><a href="#" onclick='return showDiv("page_1");'>«</a></li> <li><a href="#" onclick='return showDiv("page_17");'>17</a></li> <li><a href="#" onclick='return showDiv("page_18");'>18</a></li> <li class="active"><span>19</span></li> <li><a href="#" onclick='return showDiv("page_20");'>20</a></li> <li><a href="#" onclick='return showDiv("page_21");'>21</a></li> <li><a href="#" onclick='return showDiv("page_25");'>»</a></li> </ul> </div> </div><!-- col-sm-12 --> </div><!-- row --> </div><!-- page_19 --> <div id="page_20" class="hiddenDiv"> <div class="row"> <div class="col-sm-12"> <div class="pull-right"> <ul class="pagination"> <li><a href="#" onclick='return showDiv("page_1");'>«</a></li> <li><a href="#" onclick='return showDiv("page_18");'>18</a></li> <li><a href="#" onclick='return showDiv("page_19");'>19</a></li> <li class="active"><span>20</span></li> <li><a href="#" onclick='return showDiv("page_21");'>21</a></li> <li><a href="#" onclick='return showDiv("page_22");'>22</a></li> <li><a href="#" onclick='return showDiv("page_25");'>»</a></li> </ul> </div> </div> </div> <div class="row"> <div class="col-sm-12"> <ol class="result-class" start="381"> <li> <p><a target="_blank" onclick="trackOutboundLink('http://ntrs.nasa.gov/search.jsp?R=20010090333&hterms=science+direct&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D70%26Ntt%3Dscience%2Bdirect','NASA-TRS'); return false;" href="http://ntrs.nasa.gov/search.jsp?R=20010090333&hterms=science+direct&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D70%26Ntt%3Dscience%2Bdirect"><span id="translatedtitle">Level 1 Processing of <span class="hlt">MODIS</span> Direct Broadcast Data at the GSFC DAAC</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Lynnes, Christopher; Kempler, Steven J. (Technical Monitor)</p> <p>2001-01-01</p> <p>The GSFC DAAC is working to test and package the <span class="hlt">MODIS</span> Level 1 Processing software for <span class="hlt">Aqua</span> Direct Broadcast data. This entails the same code base, but different lookup tables for <span class="hlt">Aqua</span> and Terra. However, the most significant change is the use of ancillary attitude and ephemeris files instead of orbit/attitude information within the science data stream (as with Terra). In addition, we are working on Linux: ports of the algorithms, which could eventually enable processing on PC clusters. Finally, the GSFC DAAC is also working with the GSFC Direct Readout laboratory to ingest Level 0 data from the GSFC DB antenna into the main DAAC, enabling level 1 production in near real time in support of applications users, such as the Synergy project. The mechanism developed for this could conceivably be extended to other participating stations.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2010AGUFMIN31A1258J','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2010AGUFMIN31A1258J"><span id="translatedtitle">e<span class="hlt">MODIS</span> Expedited: Overview of a Near Real Time <span class="hlt">MODIS</span> Production System for Operational Vegetation Monitoring</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Jenkerson, C.; Meyer, D. J.; Werpy, J.; Evenson, K.; Merritt, M.</p> <p>2010-12-01</p> <p>The expedited <span class="hlt">MODIS</span>, or e<span class="hlt">MODIS</span> production system derives near-real time Normalized Difference Vegetation Index (NDVI) from Moderate Resolution Imaging Spectroradiometer (<span class="hlt">MODIS</span>) surface <span class="hlt">reflectance</span> provided by the Land and Atmosphere Near-real time Capability for EOS (LANCE). There are currently three regions covered by this U.S. Geological Survey (USGS) capability, including the continental U.S., Africa, and the Central America/Caribbean regions. Each of the e<span class="hlt">MODIS</span> production streams is configured to output its data in map projections, compositing intervals, spatial resolutions, and file formats specific to its region and user community. The challenges of processing 1,000-meter, 500-m, and especially 250-m products by midnight on the last day of a product interval have been met with increasingly effective software and system architecture. An anonymous file transfer protocol (FTP) distribution site (ftp://emodisftp.cr.usgs.gov/e<span class="hlt">MODIS</span>) allows users direct access to e<span class="hlt">MODIS</span> NDVI products for operational (near-real time) monitoring of vegetation conditions like drought, crop failure, insect infestation, and other threats, thus supporting subsequent early warning of famine and the targeting of vulnerable populations for insecure food situations.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/20140011354','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20140011354"><span id="translatedtitle">Improvement of Aerosol Optical Depth Retrieval from <span class="hlt">MODIS</span> Spectral <span class="hlt">Reflectance</span> over the Global Ocean Using New Aerosol Models Archived from AERONET Inversion Data and Tri-axial Ellipsoidal Dust Database</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Lee, J.; Kim, J.; Yang, P.; Hsu, N. C.</p> <p>2012-01-01</p> <p>New over-ocean aerosol models are developed by integrating the inversion data from the Aerosol Robotic Network (AERONET) sun/sky radiometers with a database for the optical properties of tri-axial ellipsoid particles. The new aerosol models allow more accurate retrieval of aerosol optical depth (AOD) from the Moderate Resolution Imaging Spectroradiometer (<span class="hlt">MODIS</span>) in the case of high AOD (AOD greater than 0.3). The aerosol models are categorized by using the fine-mode fraction (FMF) at 550 nm and the singlescattering albedo (SSA) at 440 nm from the AERONET inversion data to include a variety of aerosol types found around the globe. For each aerosol model, the changes in the aerosol optical properties (AOPs) as functions of AOD are considered to better represent aerosol characteristics. Comparisons of AODs between AERONET and <span class="hlt">MODIS</span> for the period from 2003 to 2010 show that the use of the new aerosol models enhances the AOD accuracy with a Pearson coefficient of 0.93 and a regression slope of 0.99 compared to 0.92 and 0.85 calculated using the <span class="hlt">MODIS</span> Collection 5 data. Moreover, the percentage of data within an expected error of +/-(0.03 + 0.05xAOD) is increased from 62 percent to 64 percent for overall data and from 39 percent to 51 percent for AOD greater than 0.3. Errors in the retrieved AOD are further characterized with respect to the Angstrom exponent (AE), scattering angle, SSA, and air mass factor (AMF). Due to more realistic AOPs assumptions, the new algorithm generally reduces systematic errors in the retrieved AODs compared with the current operational algorithm. In particular, the underestimation of fine-dominated AOD and the scattering angle dependence of dust-dominated AOD are significantly mitigated as results of the new algorithm's improved treatment of aerosol size distribution and dust particle nonsphericity.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/20060046366','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20060046366"><span id="translatedtitle">Multilayered Clouds Identification and Retrieval for CERES Using <span class="hlt">MODIS</span></span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Sun-Mack, Sunny; Minnis, Patrick; Chen, Yan; Yi, Yuhong; Huang, Jainping; Lin, Bin; Fan, Alice; Gibson, Sharon; Chang, Fu-Lung</p> <p>2006-01-01</p> <p>Traditionally, analyses of satellite data have been limited to interpreting the radiances in terms of single layer clouds. Generally, this results in significant errors in the retrieved properties for multilayered cloud systems. Two techniques for detecting overlapped clouds and retrieving the cloud properties using satellite data are explored to help address the need for better quantification of cloud vertical structure. The first technique was developed using multispectral imager data with secondary imager products (infrared brightness temperature differences, BTD). The other method uses microwave (MWR) data. The use of BTD, the 11-12 micrometer brightness temperature difference, in conjunction with tau, the retrieved visible optical depth, was suggested by Kawamoto et al. (2001) and used by Pavlonis et al. (2004) as a means to detect multilayered clouds. Combining visible (VIS; 0.65 micrometer) and infrared (IR) retrievals of cloud properties with microwave (MW) retrievals of cloud water temperature Tw and liquid water path LWP retrieved from satellite microwave imagers appears to be a fruitful approach for detecting and retrieving overlapped clouds (Lin et al., 1998, Ho et al., 2003, Huang et al., 2005). The BTD method is limited to optically thin cirrus over low clouds, while the MWR method is limited to ocean areas only. With the availability of VIS and IR data from the Moderate Resolution Imaging Spectroradiometer (<span class="hlt">MODIS</span>) and MW data from the Advanced Microwave Scanning Radiometer EOS (AMSR-E), both on <span class="hlt">Aqua</span>, it is now possible to examine both approaches simultaneously. This paper explores the use of the BTD method as applied to <span class="hlt">MODIS</span> and AMSR-E data taken from the <span class="hlt">Aqua</span> satellite over non-polar ocean surfaces.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2015AGUFMIN21A1682M','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2015AGUFMIN21A1682M"><span id="translatedtitle">Quality Assessment of Collection 6 <span class="hlt">MODIS</span> Atmospheric Science Products</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Manoharan, V. S.; Ridgway, B.; Platnick, S. E.; Devadiga, S.; Mauoka, E.</p> <p>2015-12-01</p> <p>Since the launch of the NASA Terra and <span class="hlt">Aqua</span> satellites in December 1999 and May 2002, respectively, atmosphere and land data acquired by the <span class="hlt">MODIS</span> (Moderate Resolution Imaging Spectroradiometer) sensor on-board these satellites have been reprocessed five times at the MODAPS (<span class="hlt">MODIS</span> Adaptive Processing System) located at NASA GSFC. The global land and atmosphere products use science algorithms developed by the NASA <span class="hlt">MODIS</span> science team investigators. MODAPS completed Collection 6 reprocessing of <span class="hlt">MODIS</span> Atmosphere science data products in April 2015 and is currently generating the Collection 6 products using the latest version of the science algorithms. This reprocessing has generated one of the longest time series of consistent data records for understanding cloud, aerosol, and other constituents in the earth's atmosphere. It is important to carefully evaluate and assess the quality of this data and remove any artifacts to maintain a useful climate data record. Quality Assessment (QA) is an integral part of the processing chain at MODAPS. This presentation will describe the QA approaches and tools adopted by the <span class="hlt">MODIS</span> Land/Atmosphere Operational Product Evaluation (LDOPE) team to assess the quality of <span class="hlt">MODIS</span> operational Atmospheric products produced at MODAPS. Some of the tools include global high resolution images, time series analysis and statistical QA metrics. The new high resolution global browse images with pan and zoom have provided the ability to perform QA of products in real time through synoptic QA on the web. This global browse generation has been useful in identifying production error, data loss, and data quality issues from calibration error, geolocation error and algorithm performance. A time series analysis for various science datasets in the Level-3 monthly product was recently developed for assessing any long term drifts in the data arising from instrument errors or other artifacts. This presentation will describe and discuss some test cases from the</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2010AGUFM.C51A0477M','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2010AGUFM.C51A0477M"><span id="translatedtitle"><span class="hlt">MODIS</span> Data and Services at the National Snow and Ice Data Center (NSIDC)</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>McAllister, M.; Fowler, D. K.</p> <p>2010-12-01</p> <p>For nearly a decade, the National Snow and Ice Data Center (NSIDC) has archived and distributed snow and sea ice products derived from the Moderate Resolution Imaging Spectroradiometer (<span class="hlt">MODIS</span>) instruments on the NASA Earth Observing System (EOS) <span class="hlt">Aqua</span> and Terra satellites. The archive contains a wide selection of data products relevant to cryospheric science, including snow and sea ice. NSIDC offers a variety of methods for obtaining these data. Our Data Pool is an online archive which allows a user to very quickly download desired products and also has a spatial and temporal search capability. The Warehouse Inventory Search Tool (WIST) contains a complete set of metadata for all products which can be searched for and ordered. WIST also allows a user to order spatial, temporal, and parameter subsets of the data. Users can also request that they be added to our subscription list which makes it possible to have new <span class="hlt">MODIS</span> data automatically ftp’d or staged on a local server as it is archived at NSIDC. Since <span class="hlt">MODIS</span> products are in HDF-EOS format, NSIDC has developed a number of tools to assist with browsing, editing, reprojection, resampling, and format conversion including <span class="hlt">MODIS</span> Swath-to-Grid Toolbox (MS2GT) and the <span class="hlt">MODIS</span> Interactive Subsetting Tool (MIST). MS2GT was created to produce a seamless output grid from multiple input files corresponding to successively acquired, 5-minute <span class="hlt">MODIS</span> scenes. NSIDC created the MIST to also provide subsets of certain Version 5 <span class="hlt">MODIS</span> products, over the Greenland Climate Network (GC-Net) and the International Arctic Systems for Observing the Atmosphere (IASOA) stations.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2015AGUFM.C41D0750F','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2015AGUFM.C41D0750F"><span id="translatedtitle"><span class="hlt">MODIS</span> Collection 6 Data at the National Snow and Ice Data Center (NSIDC)</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Fowler, D. K.; Steiker, A. E.; Johnston, T.; Haran, T. M.; Fowler, C.; Wyatt, P.</p> <p>2015-12-01</p> <p>For over 15 years, the NASA National Snow and Ice Data Center Distributed Active Archive Center (NSIDC DAAC) has archived and distributed snow and sea ice products derived from the Moderate Resolution Imaging Spectroradiometer (<span class="hlt">MODIS</span>) instruments on the NASA Earth Observing System (EOS) <span class="hlt">Aqua</span> and Terra satellites. Collection 6 represents the next revision to NSIDC's <span class="hlt">MODIS</span> archive, mainly affecting the snow-cover products. Collection 6 specifically addresses the needs of the <span class="hlt">MODIS</span> science community by targeting the scenarios that have historically confounded snow detection and introduced errors into the snow-cover and fractional snow-cover maps even though <span class="hlt">MODIS</span> snow-cover maps are typically 90 percent accurate or better under good observing conditions, Collection 6 uses revised algorithms to discriminate between snow and clouds, resolve uncertainties along the edges of snow-covered regions, and detect summer snow cover in mountains. Furthermore, Collection 6 applies modified and additional snow detection screens and new Quality Assessment protocols that enhance the overall accuracy of the snow maps compared with Collection 5. Collection 6 also introduces several new <span class="hlt">MODIS</span> snow products, including a daily Climate Modelling Grid (CMG) cloud gap-filled (CGF) snow-cover map which generates cloud-free maps by using the most recent clear observations.. The <span class="hlt">MODIS</span> Collection 6 sea ice extent and ice surface temperature algorithms and products are much the same as Collection 5; however, Collection 6 updates to algorithm inputs—in particular, the L1B calibrated radiances, land and water mask, and cloud mask products—have improved the sea ice outputs. The <span class="hlt">MODIS</span> sea ice products are currently available at NSIDC, and the snow cover products are soon to follow in 2016 NSIDC offers a variety of methods for obtaining these data. Users can download data directly from an online archive or use the NASA Reverb Search & Order Tool to perform spatial, temporal, and parameter</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2006PhDT........27Y','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2006PhDT........27Y"><span id="translatedtitle">Analysis, improvement and application of the <span class="hlt">MODIS</span> leaf area index products</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Yang, Wenze</p> <p></p> <p>Green leaf area governs the exchanges of energy, mass and momentum between the Earth's surface and the atmosphere. Therefore, leaf area index (LAI) and fraction of incident photosynthetically active radiation (0.4-0.7 mum) absorbed by the vegetation canopy (FPAR) are widely used in vegetation monitoring and modeling. The launch of Terra and <span class="hlt">Aqua</span> satellites with the moderate resolution imaging spectroradiometer (<span class="hlt">MODIS</span>) instrument onboard provided the first global products of LAI and FPAR, derived mainly from an algorithm based on radiative transfer. The objective of this research is to comprehensively evaluate the Terra and <span class="hlt">Aqua</span> <span class="hlt">MODIS</span> LAI/FPAR products. Large volumes of these products have been analyzed with the goal of understanding product quality with respect to version (Collection 3 versus 4), algorithm (main versus back-up), snow (snow-free versus snow on the ground) and cloud (cloud-free versus cloudy) conditions. Field validation efforts identified several key factors that influence the accuracy of algorithm retrievals. The strategy of validation efforts guiding algorithm refinements has led to progressively more accurate LAI/FPAR products. The combination of products derived from the Terra and <span class="hlt">Aqua</span> <span class="hlt">MODIS</span> sensors increases the success rate of the main radiative transfer algorithm by 10-20 percent over woody vegetation. The Terra Collection 4 LAI data reveal seasonal swings in green leaf area of about 25 percent in a majority of the Amazon rainforests caused by variability in cloud cover and light. The timing and the influence of this seasonal cycle are critical to understanding tropical plant adaptation patterns and ecological processes. The results presented in this dissertation suggest how the product quality has gradually improved largely through the efforts of validation activities. The Amazon case study highlights the utility of these data sets for monitoring global vegetation dynamics. Thus, these results can be seen as a benchmark for evaluation of</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://www.ncbi.nlm.nih.gov/pubmed/27505382','PUBMED'); return false;" href="http://www.ncbi.nlm.nih.gov/pubmed/27505382"><span id="translatedtitle">Degradation nonuniformity in the solar diffuser bidirectional <span class="hlt">reflectance</span> distribution function.</span></a></p> <p><a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a></p> <p>Sun, Junqiang; Chu, Mike; Wang, Menghua</p> <p>2016-08-01</p> <p>The assumption of angular dependence stability of the solar diffuser (SD) throughout degradation is critical to the on-orbit calibration of the <span class="hlt">reflective</span> solar bands (RSBs) in many satellite sensors. Recent evidence has pointed to the contrary, and in this work, we present a thorough investigative effort into the angular dependence of the SD degradation for the Visible Infrared Imaging Radiometer Suite (VIIRS) onboard the Suomi National Polar-orbiting Partnership (SNPP) satellite and for the twin Moderate-resolution Imaging Spectroradiometer (<span class="hlt">MODIS</span>) onboard Terra and <span class="hlt">Aqua</span> spacecrafts. One common key step in the RSB calibration is the use of the SD degradation performance measured by an accompanying solar diffuser stability monitor (SDSM) as a valid substitute for the SD degradation factor in the direction of the RSB view. If SD degradations between these two respective directions do not maintain the same relative relationship over time, then the unmitigated use of the SDSM-measured SD degradation factor in the RSB calibration calculation will generate bias, and consequently, long-term drift in derived science products. We exploit the available history of the on-orbit calibration events to examine the response of the SDSM and the RSB detectors to the incident illumination <span class="hlt">reflecting</span> off SD versus solar declination angle and show that the angular dependency, particularly at short wavelengths, evolves with respect to time. The generalized and the decisive conclusion is that the bidirectional <span class="hlt">reflectance</span> distribution function (BRDF) of the SD degrades nonuniformly with respect to both incident and outgoing directions. Thus, the SDSM-based measurements provide SD degradation factors that are biased relative to the RSB view direction with respect to the SD. The analysis also reveals additional interesting phenomena, for example, the sharp behavioral change in the evolving angular dependence observed in Terra <span class="hlt">MODIS</span> and SNPP VIIRS. For SNPP VIIRS the mitigation for this</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/cgi-bin/nph-data_query?bibcode=2015AGUFM.A23G..02G&link_type=ABSTRACT','NASAADS'); return false;" href="http://adsabs.harvard.edu/cgi-bin/nph-data_query?bibcode=2015AGUFM.A23G..02G&link_type=ABSTRACT"><span id="translatedtitle">Investigating the impact of haze on cloud detection of passive satellite by comparing <span class="hlt">MODIS</span>, CloudSat and CALIPSO</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Gong, W.; Mao, F.</p> <p>2015-12-01</p> <p>The cloud detection algorithm for passive sensors is usually based on a fuzzy logic system with thresholds determined from previous observations. In recent years, haze and high aerosol concentrations with high AOD occur frequently in China and may critically impact the accuracy of the <span class="hlt">MODIS</span> cloud detection. Thus, we comprehensively explore this impact by comparing the results from <span class="hlt">MODIS/Aqua</span> (passive sensor), CALIOP/CALIPSO (lidar sensor), and CPR/CloudSat (microwave sensor) of the A-Train suite of instruments using an averaged AOD as an index for an aerosol concentration value. Case studies concerning the comparison of the three sensors indicate that <span class="hlt">MODIS</span> cloud detection is reduced during haze events. In addition, statistical studies show that an increase in AOD creates an increase in the percentage of uncertain flags and a decrease in hit rate, a consistency index between consecutive sets of cloud retrievals. Therefore, we can conclude that the ability of <span class="hlt">MODIS</span> cloud detection is weakened by large concentrations of aerosols. This suggests that use of the <span class="hlt">MODIS</span> cloud mask, and derived higher level products, in situations with haze requires caution. Further improvement of this retrieval algorithm, is desired as haze studies based on <span class="hlt">MODIS</span> products are of great interest in a number of related fields.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2010EGUGA..12.9210D','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2010EGUGA..12.9210D"><span id="translatedtitle">Evaluation of Aerosol Optical Depth by AERONET, <span class="hlt">MODIS</span> and MISR over the Mediterranean and Middle East in 2006.</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>de Meij, Alexander; Lelieveld, Jos</p> <p>2010-05-01</p> <p>The objective of this study is to evaluate the spatial and temporal variation of the aerosol optical depth (AOD) and to identify the main characteristics of the aerosol episodes for the Mediterranean area, with the focus on the year 2006. We evaluate aerosol optical properties of <span class="hlt">MODIS</span> and MISR instruments with AERONET. In general the yearly mean <span class="hlt">MODIS</span> and MISR AOD is in good agreement with AERONET and the temporal AOD variation is also in good agreement. High AODs observed by AERONET, <span class="hlt">MODIS</span> and MISR are caused by natural dust events or high anthropogenic aerosol concentrations in the combination with stagnant meteorological conditions. The comparison of <span class="hlt">MODIS</span> and MISR aerosol optical properties with AERONET for June reveals that the AODs, Angstrom coefficients and single scattering albedos agree well with AERONET and indicate the presence of natural dust in the Mediterranean. In general MISR AOD is lower than <span class="hlt">MODIS</span> AOD during summer. Comparing <span class="hlt">MODIS</span> <span class="hlt">Aqua</span> Deep Blue with MISR for June over the Saharan desert reveals some differences in the location and the maxima of the AOD values. The seasonal AOD variation by MISR over the Mediterranean and Middle East shows substantial differences in the AODs for each season. Higher dust loads during spring and autumn time in the eastern part of the Mediterranean. Biomass burning activities around the Black Sea during July and August (e.g. agricultural waste burning) cause high AODs and the particles are transported to the eastern part of the Mediterranean, because of the dominant northerly wind direction during summer.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/20120003696','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20120003696"><span id="translatedtitle">Improvements in Night-Time Low Cloud Detection and <span class="hlt">MODIS</span>-Style Cloud Optical Properties from MSG SEVIRI</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Wind, Galina (Gala); Platnick, Steven; Riedi, Jerome</p> <p>2011-01-01</p> <p>The <span class="hlt">MODIS</span> cloud optical properties algorithm (MOD06IMYD06 for Terra and <span class="hlt">Aqua</span> <span class="hlt">MODIS</span>, respectively) slated for production in Data Collection 6 has been adapted to execute using available channels on MSG SEVIRI. Available <span class="hlt">MODIS</span>-style retrievals include IR Window-derived cloud top properties, using the new Collection 6 cloud top properties algorithm, cloud optical thickness from VISINIR bands, cloud effective radius from 1.6 and 3.7Jlm and cloud ice/water path. We also provide pixel-level uncertainty estimate for successful retrievals. It was found that at nighttime the SEVIRI cloud mask tends to report unnaturally low cloud fraction for marine stratocumulus clouds. A correction algorithm that improves detection of such clouds has been developed. We will discuss the improvements to nighttime low cloud detection for SEVIRI and show examples and comparisons with <span class="hlt">MODIS</span> and CALIPSO. We will also show examples of <span class="hlt">MODIS</span>-style pixel-level (Level-2) cloud retrievals for SEVIRI with comparisons to <span class="hlt">MODIS</span>.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://www.ncbi.nlm.nih.gov/pubmed/26197587','PUBMED'); return false;" href="http://www.ncbi.nlm.nih.gov/pubmed/26197587"><span id="translatedtitle">[Impact of Vegetation Structure on Drought Indices Based on <span class="hlt">MODIS</span> Spectrum].</span></a></p> <p><a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a></p> <p>Du, Ling-tong; Tian, Qing-jiu; Wang, Lei</p> <p>2015-04-01</p> <p>The drought indices based on <span class="hlt">MODIS</span> spectral <span class="hlt">reflectance</span> data are widely used for drought characterization and monitoring in agricultural context. Based on the PROSAIL model and <span class="hlt">MODIS</span> observational data in Shandong in 2010, the present paper studied the impact of vegetation structure of leaf area index and physiological growth cycle on <span class="hlt">MODIS</span> spectral drought index. The results showed that the <span class="hlt">reflectance</span> of three <span class="hlt">MODIS</span> bands in spectrum of near-infrared and shortwave infrared changes significantly with leaf water content of vegetation. Therefore, the five kinds of <span class="hlt">MODIS</span> spectral drought index constructed by those <span class="hlt">MODIS</span> bands can be used to monitor the leaf water content of vegetation. However, all drought indices are affected by leaf area index. In general, the impact is serious in the case of low LAI values and is weakened with the increase in LAI value. The study found that physiological vegetation growth cycle also affects the magnitude of <span class="hlt">MODIS</span> spectral drought indices. In conclusion, the impact of vegetation structure must be carefully considered when using <span class="hlt">MODIS</span> spectral drought indices to monitor drought. The conclusion of this study provides a theoretical basis for remote sensing of drought monitoring. PMID:26197587</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/20160010516','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20160010516"><span id="translatedtitle">Progress in Understanding the Impacts of 3-D Cloud Structure on <span class="hlt">MODIS</span> Cloud Property Retrievals for Marine Boundary Layer Clouds</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Zhang, Zhibo; Werner, Frank; Miller, Daniel; Platnick, Steven; Ackerman, Andrew; DiGirolamo, Larry; Meyer, Kerry; Marshak, Alexander; Wind, Galina; Zhao, Guangyu</p> <p>2016-01-01</p> <p>Theory: A novel framework based on 2-D Tayler expansion for quantifying the uncertainty in <span class="hlt">MODIS</span> retrievals caused by sub-pixel <span class="hlt">reflectance</span> inhomogeneity. (Zhang et al. 2016). How cloud vertical structure influences <span class="hlt">MODIS</span> LWP retrievals. (Miller et al. 2016). Observation: Analysis of failed <span class="hlt">MODIS</span> cloud property retrievals. (Cho et al. 2015). Cloud property retrievals from 15m resolution ASTER observations. (Werner et al. 2016). Modeling: LES-Satellite observation simulator (Zhang et al. 2012, Miller et al. 2016).</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2009AGUFM.U33A0045P','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2009AGUFM.U33A0045P"><span id="translatedtitle">Ten Years of Cloud Optical and Microphysical Retrievals from <span class="hlt">MODIS</span></span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Platnick, S. E.; King, M. D.; Wind, G.; Hubanks, P.; Arnold, G. T.; Amarasinghe, N.</p> <p>2009-12-01</p> <p>The <span class="hlt">MODIS</span> cloud optical properties algorithm (MOD06/MYD06 for Terra and <span class="hlt">Aqua</span> <span class="hlt">MODIS</span>, respectively) has undergone extensive improvements and enhancements since the launch of Terra. These changes have included: improvements in the cloud thermodynamic phase algorithm; substantial changes in the ice cloud light scattering look up tables (LUTs); a clear-sky restoral algorithm for flagging heavy aerosol and sunglint; greatly improved spectral surface albedo maps, including the spectral albedo of snow by ecosystem; inclusion of pixel-level uncertainty estimates for cloud optical thickness, effective radius, and water path derived for three error sources that includes the sensitivity of the retrievals to solar and viewing geometries. To improve overall retrieval quality, we have also implemented cloud edge removal and partly cloudy detection (using MOD35 cloud mask 250m tests), added a supplementary cloud optical thickness and effective radius algorithm over snow and sea ice surfaces and over the ocean, which enables comparison with the “standard” 2.1 µm effective radius retrieval, and added a multi-layer cloud detection algorithm. We will discuss the status of the MOD06 algorithm and show examples of pixel-level (Level-2) cloud retrievals for selected data granules, as well as gridded (Level-3) statistics, notably monthly means and histograms (1D and 2D, with the latter giving correlations between cloud optical thickness and effective radius, and other cloud product pairs).</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://ntrs.nasa.gov/search.jsp?R=20100014358&hterms=tens&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D10%26Ntt%3Dtens','NASA-TRS'); return false;" href="http://ntrs.nasa.gov/search.jsp?R=20100014358&hterms=tens&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D10%26Ntt%3Dtens"><span id="translatedtitle">Ten Years of Cloud Optical and Microphysical Retrievals from <span class="hlt">MODIS</span></span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Platnick, Steven; King, Michael D.; Wind, Galina; Hubanks, Paul; Arnold, G. Thomas; Amarasinghe, Nandana</p> <p>2010-01-01</p> <p>The <span class="hlt">MODIS</span> cloud optical properties algorithm (MOD06/MYD06 for Terra and <span class="hlt">Aqua</span> <span class="hlt">MODIS</span>, respectively) has undergone extensive improvements and enhancements since the launch of Terra. These changes have included: improvements in the cloud thermodynamic phase algorithm; substantial changes in the ice cloud light scattering look up tables (LUTs); a clear-sky restoral algorithm for flagging heavy aerosol and sunglint; greatly improved spectral surface albedo maps, including the spectral albedo of snow by ecosystem; inclusion of pixel-level uncertainty estimates for cloud optical thickness, effective radius, and water path derived for three error sources that includes the sensitivity of the retrievals to solar and viewing geometries. To improve overall retrieval quality, we have also implemented cloud edge removal and partly cloudy detection (using MOD35 cloud mask 250m tests), added a supplementary cloud optical thickness and effective radius algorithm over snow and sea ice surfaces and over the ocean, which enables comparison with the "standard" 2.1 11m effective radius retrieval, and added a multi-layer cloud detection algorithm. We will discuss the status of the MOD06 algorithm and show examples of pixellevel (Level-2) cloud retrievals for selected data granules, as well as gridded (Level-3) statistics, notably monthly means and histograms (lD and 2D, with the latter giving correlations between cloud optical thickness and effective radius, and other cloud product pairs).</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/20140013289','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20140013289"><span id="translatedtitle">An Examination of the Nature of Global <span class="hlt">MODIS</span> Cloud Regimes</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Oreopoulos, Lazaros; Cho, Nayeong; Lee, Dongmin; Kato, Seiji; Huffman, George J.</p> <p>2014-01-01</p> <p>We introduce global cloud regimes (previously also referred to as "weather states") derived from cloud retrievals that use measurements by the Moderate Resolution Imaging Spectroradiometer (<span class="hlt">MODIS</span>) instrument aboard the <span class="hlt">Aqua</span> and Terra satellites. The regimes are obtained by applying clustering analysis on joint histograms of retrieved cloud top pressure and cloud optical thickness. By employing a compositing approach on data sets from satellites and other sources, we examine regime structural and thermodynamical characteristics. We establish that the <span class="hlt">MODIS</span> cloud regimes tend to form in distinct dynamical and thermodynamical environments and have diverse profiles of cloud fraction and water content. When compositing radiative fluxes from the Clouds and the Earth's Radiant Energy System instrument and surface precipitation from the Global Precipitation Climatology Project, we find that regimes with a radiative warming effect on the atmosphere also produce the largest implied latent heat. Taken as a whole, the results of the study corroborate the usefulness of the cloud regime concept, reaffirm the fundamental nature of the regimes as appropriate building blocks for cloud system classification, clarify their association with standard cloud types, and underscore their distinct radiative and hydrological signatures.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/20040015040','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20040015040"><span id="translatedtitle"><span class="hlt">MODIS</span> Validation, Data Merger and Other Activities Accomplished by the SIMBIOS Project: 2002-2003</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Fargion, Giulietta S.; McClain, Charles R.</p> <p>2003-01-01</p> <p>The purpose of this technical report is to provide current documentation of the Sensor Intercomparison and Merger for Biological and Interdisciplinary Oceanic Studies (SIMBIOS) Project activities, satellite data processing, and data product validation. This documentation is necessary to ensure that critical information is related to the scientific community and NASA management. This critical information includes the technical difficulties and challenges of validating and combining ocean color data from an array of independent satellite systems to form consistent and accurate global bio-optical time series products. This technical report focuses on the SIMBIOS Project s efforts in support of the Moderate-Resolution Imaging Spectroradiometer (<span class="hlt">MODIS</span>) on the Earth Observing System (EOS) Terra platform (similar evaluations of <span class="hlt">MODIS/Aqua</span> are underway). This technical report is not meant as a substitute for scientific literature. Instead, it will provide a ready and responsive vehicle for the multitude of technical reports issued by an operational project.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/20140012657','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20140012657"><span id="translatedtitle">Comparing <span class="hlt">MODIS</span> C6 'Deep Blue' and 'Dark Target' Aerosol Data</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Hsu, N. C.; Sayer, A. M.; Bettenhausen, C.; Lee, J.; Levy, R. C.; Mattoo, S.; Munchak, L. A.; Kleidman, R.</p> <p>2014-01-01</p> <p>The <span class="hlt">MODIS</span> Collection 6 Atmospheres product suite includes refined versions of both 'Deep Blue' (DB) and 'Dark Target' (DT) aerosol algorithms, with the DB dataset now expanded to include coverage over vegetated land surfaces. This means that, over much of the global land surface, users will have both DB and DT data to choose from. A 'merged' dataset is also provided, primarily for visualization purposes, which takes retrievals from either or both algorithms based on regional and seasonal climatologies of normalized difference vegetation index (NDVI). This poster present some comparisons of these two C6 aerosol algorithms, focusing on AOD at 550 nm derived from <span class="hlt">MODIS</span> <span class="hlt">Aqua</span> measurements, with each other and with Aerosol Robotic Network (AERONET) data, with the intent to facilitate user decisions about the suitability of the two datasets for their desired applications.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/20110015306','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20110015306"><span id="translatedtitle">Radiometric Quality of the <span class="hlt">MODIS</span> Bands at 667 and 678nm</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Meister, Gerhard; Franz, Bryan A.</p> <p>2010-01-01</p> <p>The <span class="hlt">MODIS</span> instruments on Terra and <span class="hlt">Aqua</span> were designed to allow the measurement of chlorophyll fluorescence effects over ocean. The retrieval algorithm is based on the difference between the water-leaving radiances at 667nm and 678nm. The water-leaving radiances at these wavelengths are usually very low relative to the top- of-atmosphere radiances. The high radiometric accuracy needed to retrieve the small fluorescence signal lead to a dual gain design for the 667 and 678nm bands. This paper discusses the benefits obtained from this design choice and provides justification for the use of only one set of gains for global processing of ocean color products. Noise characteristics of the two bands and their related products are compared to other products of bands from 412nm to 2130nm. The impact of polarization on the two bands is discussed. In addition, the impact of stray light on the two bands is compared to other <span class="hlt">MODIS</span> bands.</p> </li> </ol> <div class="pull-right"> <ul class="pagination"> <li><a href="#" onclick='return showDiv("page_1");'>«</a></li> <li><a href="#" onclick='return showDiv("page_18");'>18</a></li> <li><a href="#" onclick='return showDiv("page_19");'>19</a></li> <li class="active"><span>20</span></li> <li><a href="#" onclick='return showDiv("page_21");'>21</a></li> <li><a href="#" onclick='return showDiv("page_22");'>22</a></li> <li><a href="#" onclick='return showDiv("page_25");'>»</a></li> </ul> </div> </div><!-- col-sm-12 --> </div><!-- row --> </div><!-- page_20 --> <div id="page_21" class="hiddenDiv"> <div class="row"> <div class="col-sm-12"> <div class="pull-right"> <ul class="pagination"> <li><a href="#" onclick='return showDiv("page_1");'>«</a></li> <li><a href="#" onclick='return showDiv("page_19");'>19</a></li> <li><a href="#" onclick='return showDiv("page_20");'>20</a></li> <li class="active"><span>21</span></li> <li><a href="#" onclick='return showDiv("page_22");'>22</a></li> <li><a href="#" onclick='return showDiv("page_23");'>23</a></li> <li><a href="#" onclick='return showDiv("page_25");'>»</a></li> </ul> </div> </div> </div> <div class="row"> <div class="col-sm-12"> <ol class="result-class" start="401"> <li> <p><a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/20110022522','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20110022522"><span id="translatedtitle">Radiometric Quality of the <span class="hlt">MODIS</span> Bands at 667 and 678nm</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Meister, Gerhard; Franz, Bryan A.</p> <p>2011-01-01</p> <p>The <span class="hlt">MODIS</span> instruments on Terra and <span class="hlt">Aqua</span> were designed to allow the measurement of chlorophyll fluorescence effects over ocean. The retrieval algorithm is based on the difference between the water-leaving radiances at 667nm and 678nm. The water-leaving radiances at these wavelengths are usually very low relative to the top-of-atmosphere radiances. The high radiometric accuracy needed to retrieve the small fluorescence signal lead to a dual gain design for the 667 and 678nm bands. This paper discusses the benefits obtained from this design choice and provides justification for the use of only one set of gains for global processing of ocean color products. Noise characteristics of the two bands and their related products are compared to other products of bands from 412nm to 2130nm. The impact of polarization on the two bands is discussed. In addition, the impact of stray light on the two bands is compared to other <span class="hlt">MODIS</span> bands.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/20040034204','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20040034204"><span id="translatedtitle">Passive and Active Detection of Clouds: Comparisons between <span class="hlt">MODIS</span> and GLAS Observations</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Mahesh, Ashwin; Gray, Mark A.; Palm, Stephen P.; Hart, William D.; Spinhirne, James D.</p> <p>2003-01-01</p> <p>The Geoscience Laser Altimeter System (GLAS), launched on board the Ice, Cloud and Land Elevation Satellite in January 2003 provides space-borne laser observations of atmospheric layers. GLAS provides opportunities to validate passive observations of the atmosphere for the first time from space with an active optical instrument. Data from the Moderate Resolution Imaging Spectrometer aboard the <span class="hlt">Aqua</span> satellite is examined along with GLAS observations of cloud layers. In more than three-quarters of the cases, <span class="hlt">MODIS</span> scene identification from spectral radiances agrees with GLAS. Disagreement between the two platforms is most significant over snow-covered surfaces in the northern hemisphere. Daytime clouds detected by GLAS are also more easily seen in the <span class="hlt">MODIS</span> data as well, compared to observations made at night. These comparisons illustrate the capabilities of active remote sensing to validate and assess passive measurements, and also to complement them in studies of atmospheric layers.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://ntrs.nasa.gov/search.jsp?R=GL-2002-001596&hterms=plants+absorb&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D80%26Ntt%3Dplants%2Babsorb','NASA-TRS'); return false;" href="http://ntrs.nasa.gov/search.jsp?R=GL-2002-001596&hterms=plants+absorb&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D80%26Ntt%3Dplants%2Babsorb"><span id="translatedtitle"><span class="hlt">MODIS</span> Measures Total U.S. Leaf Area</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p></p> <p>2002-01-01</p> <p>This composite image over the continental United States was produced with data acquired by the Moderate-resolution Imaging Spectroradiometer (<span class="hlt">MODIS</span>) during the period March 24 - April 8, 2000. The image is a map of the density of the plant canopy covering the ground. It is the first in a series of images over the continental U.S. produced by the <span class="hlt">MODIS</span> Land Discipline Group (refer to this site June 2 and 5 for the next two images in the series). The image is a <span class="hlt">MODIS</span> data product called 'Leaf Area Index,' which is produced by radiometrically measuring the visible and near infrared energy <span class="hlt">reflected</span> by vegetation. The Leaf Area Index provides information on the structure of plant canopy, showing how much surface area is covered by green foliage relative to total land surface area. In this image, dark green pixels indicate areas where more than 80 percent of the land surface is covered by green vegetation, light green pixels show where leaves cover about 10 to 50 percent of the land surface, and brown pixels show virtually no leaf coverage. The more leaf area a plant has, the more sunlight it can absorb for photosynthesis. Leaf Area Index is one of a new suite of measurements that scientists use to understand how the Earth's land surfaces are changing over time. Their goal is to use these measurements to refine computer models well enough to simulate how the land biosphere influences the natural cycles of water, carbon, and energy throughout the Earth system. This image is the first of its kind from the <span class="hlt">MODIS</span> instrument, which launched in December 1999 aboard the Terra spacecraft. <span class="hlt">MODIS</span> began acquiring scientific data on February 24, 2000, when it first opened its aperture door. The <span class="hlt">MODIS</span> instrument and Terra spacecraft are both managed by NASA's Goddard Space Flight Center, Greenbelt, MD. Image courtesy Steven Running, <span class="hlt">MODIS</span> Land Group Member, University of Montana</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2014JGRC..119.8646L','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2014JGRC..119.8646L"><span id="translatedtitle">River runoff effect on the suspended sediment property in the upper Chesapeake Bay using <span class="hlt">MODIS</span> observations and ROMS simulations</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Liu, Xiaoming; Wang, Menghua</p> <p>2014-12-01</p> <p>Ocean color data derived from the Moderate Resolution Imaging Spectroradiometer (<span class="hlt">MODIS</span>) on the satellite <span class="hlt">Aqua</span> from 2002 to 2012 and simulations from the Regional Ocean Modeling System (ROMS) are used to study the impact of the Susquehanna River discharge on the total suspended sediment (TSS) concentration in the upper Chesapeake Bay. Since the water in the upper Chesapeake Bay is highly turbid, the shortwave infrared (SWIR)-based atmospheric correction algorithm is used for deriving the normalized water-leaving radiance nLw(λ) spectra from <span class="hlt">MODIS-Aqua</span> measurements. nLw(λ) spectra are further processed into the diffuse attenuation coefficient at the wavelength of 490 nm Kd(490) and TSS. <span class="hlt">MODIS-Aqua</span>-derived monthly TSS concentration in the upper Chesapeake Bay and in situ Susquehanna River discharge data show similar patterns in seasonal variations. The TSS monthly temporal variation in the upper Chesapeake Bay is also found in phase with the monthly averaged river discharge data. Since the Susquehanna River discharge is mainly dominated by a few high discharge events due to winter-spring freshets or tropical storms in each year, the impact of these high discharge events on the upper Chesapeake Bay TSS is investigated. Both <span class="hlt">MODIS</span>-measured daily TSS images and sediment data derived from ROMS simulations show that the Susquehanna River discharge is the dominant factor for the variations of TSS concentration in the upper Chesapeake Bay. Although the high river discharge event usually lasts for only a few days, its induced high TSS concentration in the upper Chesapeake Bay can sustain for ˜10-20 days. The elongated TSS rebounding stage is attributed to horizontal advection of slowly settling fine sediment from the Susquehanna River.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://eosweb.larc.nasa.gov/project/ceres/ssf_aqua-fm3_ed3a_table','SCIGOV-ASDC'); return false;" href="https://eosweb.larc.nasa.gov/project/ceres/ssf_aqua-fm3_ed3a_table"><span id="translatedtitle">SSF <span class="hlt">Aqua</span>-FM3 Ed3A</span></a></p> <p><a target="_blank" href="http://eosweb.larc.nasa.gov/">Atmospheric Science Data Center </a></p> <p></p> <p>2016-07-13</p> <p>SSF <span class="hlt">Aqua</span>-FM3 Ed3A Project Title:  CERES Discipline:  Clouds Radiation Budget ...   Reverb Tutorial Subset/Visualization Tool: CERES Order Tool Subset Data:  CERES Search and Subset Tool (HDF4 & ...</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('//www.loc.gov/pictures/collection/hh/item/ca2039.photos.323803p/','SCIGOV-HHH'); return false;" href="//www.loc.gov/pictures/collection/hh/item/ca2039.photos.323803p/"><span id="translatedtitle">Building No. 905, showing typical <span class="hlt">aqua</span> medias or rain hoods ...</span></a></p> <p><a target="_blank" href="http://www.loc.gov/pictures/collection/hh/">Library of Congress Historic Buildings Survey, Historic Engineering Record, Historic Landscapes Survey</a></p> <p></p> <p></p> <p>Building No. 905, showing typical <span class="hlt">aqua</span> medias or rain hoods - Presidio of San Francisco, Enlisted Men's Barracks Type, West end of Crissy Field, between Pearce & Maudlin Streets, San Francisco, San Francisco County, CA</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2004SPIE.5542..290T','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2004SPIE.5542..290T"><span id="translatedtitle">Vicarious calibration of Terra ASTER, MISR, and <span class="hlt">MODIS</span></span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Thome, Kurtis J.; Biggar, Stuart F.; Choi, Hyun J.</p> <p>2004-10-01</p> <p>The Advanced Spaceborne Thermal Emission and <span class="hlt">Reflection</span> and Radiometer (ASTER), Multi-angle Imaging Spectroradiometer (MISR) and Moderate Resolution Imaging Spectroradiometer (<span class="hlt">MODIS</span>) are all onboard the Terra platform. An important aspect of the use of <span class="hlt">MODIS</span>, and other Earth Science Enterprise sensors, has been the characterization and calibration of the sensors and validation of their data products. The Remote Sensing Group at the University of Arizona has been active in this area through the use of ground-based test sites. This paper presents the results from the <span class="hlt">reflectance</span>-base approach using the Railroad Valley Playa test site in Nevada for ASTER, MISR, and <span class="hlt">MODIS</span> and thus effectively a cross-calibration between all three sensors. The key to the approach is the measurement of surface <span class="hlt">reflectance</span> over a 1-km2 area of the playa and results from this method shows agreement with <span class="hlt">MODIS</span> to better than 5%. The paper examines biases between ASTER and the other two sensors in the VNIR due to uncertainties in the onboard calibrator for ASTER and in the SWIR due to an optical crosstalk effect.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2012AGUFM.A44B..04P','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2012AGUFM.A44B..04P"><span id="translatedtitle">Sensitivity of Marine Warm Cloud Retrieval Statistics to Algorithm Choices: Examples from <span class="hlt">MODIS</span> Collection 6</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Platnick, S.; Wind, G.; Zhang, Z.; Ackerman, S. A.; Maddux, B. C.</p> <p>2012-12-01</p> <p>The optical and microphysical structure of warm boundary layer marine clouds is of fundamental importance for understanding a variety of cloud radiation and precipitation processes. With the advent of <span class="hlt">MODIS</span> (Moderate Resolution Imaging Spectroradiometer) on the NASA EOS Terra and <span class="hlt">Aqua</span> platforms, simultaneous global/daily 1km retrievals of cloud optical thickness and effective particle size are provided, as well as the derived water path. In addition, the cloud product (MOD06/MYD06 for <span class="hlt">MODIS</span> Terra and <span class="hlt">Aqua</span>, respectively) provides separate effective radii results using the 1.6, 2.1, and 3.7 μm spectral channels. Cloud retrieval statistics are highly sensitive to how a pixel identified as being "not-clear" by a cloud mask (e.g., the MOD35/MYD35 product) is determined to be useful for an optical retrieval based on a 1-D cloud model. The Collection 5 <span class="hlt">MODIS</span> retrieval algorithm removed pixels associated with cloud edges (defined by immediate adjacency to "clear" MOD/MYD35 pixels) as well as ocean pixels with partly cloudy elements in the 250m <span class="hlt">MODIS</span> cloud mask - part of the so-called Clear Sky Restoral (CSR) algorithm. Collection 6 attempts retrievals for those two pixel populations, but allows a user to isolate or filter out the populations via CSR pixel-level Quality Assessment (QA) assignments. In this paper, using the preliminary Collection 6 MOD06 product, we present global and regional statistical results of marine warm cloud retrieval sensitivities to the cloud edge and 250m partly cloudy pixel populations. As expected, retrievals for these pixels are generally consistent with a breakdown of the 1D cloud model. While optical thickness for these suspect pixel populations may have some utility for radiative studies, the retrievals should be used with extreme caution for process and microphysical studies.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/20120014239','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20120014239"><span id="translatedtitle">Sensitivity of Marine Warm Cloud Retrieval Statistics to Algorithm Choices: Examples from <span class="hlt">MODIS</span> Collection 6</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Platnick, Steven; Wind, Galina; Zhang, Zhibo; Ackerman, Steven A.; Maddux, Brent</p> <p>2012-01-01</p> <p>The optical and microphysical structure of warm boundary layer marine clouds is of fundamental importance for understanding a variety of cloud radiation and precipitation processes. With the advent of <span class="hlt">MODIS</span> (Moderate Resolution Imaging Spectroradiometer) on the NASA EOS Terra and <span class="hlt">Aqua</span> platforms, simultaneous global/daily 1km retrievals of cloud optical thickness and effective particle size are provided, as well as the derived water path. In addition, the cloud product (MOD06/MYD06 for <span class="hlt">MODIS</span> Terra and <span class="hlt">Aqua</span>, respectively) provides separate effective radii results using the l.6, 2.1, and 3.7 m spectral channels. Cloud retrieval statistics are highly sensitive to how a pixel identified as being "notclear" by a cloud mask (e.g., the MOD35/MYD35 product) is determined to be useful for an optical retrieval based on a 1-D cloud model. The Collection 5 <span class="hlt">MODIS</span> retrieval algorithm removed pixels associated with cloud'edges as well as ocean pixels with partly cloudy elements in the 250m <span class="hlt">MODIS</span> cloud mask - part of the so-called Clear Sky Restoral (CSR) algorithm. Collection 6 attempts retrievals for those two pixel populations, but allows a user to isolate or filter out the populations via CSR pixel-level Quality Assessment (QA) assignments. In this paper, using the preliminary Collection 6 MOD06 product, we present global and regional statistical results of marine warm cloud retrieval sensitivities to the cloud edge and 250m partly cloudy pixel populations. As expected, retrievals for these pixels are generally consistent with a breakdown of the ID cloud model. While optical thickness for these suspect pixel populations may have some utility for radiative studies, the retrievals should be used with extreme caution for process and microphysical studies.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2015AGUFM.A51N0281M','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2015AGUFM.A51N0281M"><span id="translatedtitle">Aerosol Characterisitics Over Alberta Using <span class="hlt">Modis</span> and OMI Satellite Data</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Marey, H. S.; Hashisho, Z., Sr.; Fu, L.; Gille, J. C.</p> <p>2015-12-01</p> <p>We present the first detailed analysis of optical aerosol characterization over Alberta based on satellite data analysis. Aerosol optical depth (AOD) at 550 nm for 11 years (2003-2013), derived from the Moderate Resolution Imaging Spectroradiometer (<span class="hlt">MODIS</span>) sensor onboard NASA's <span class="hlt">Aqua</span> satellite, was analyzed. Additionally, UV aerosol index (AI) data for 9 years (2005-2013) retrieved from the Ozone Monitoring Instrument (OMI) onboard NASA's Aura satellite was used to examine absorbing aerosols. Comparing AERONET to <span class="hlt">MODIS</span> 3 km and 10 km products indicated a stronger correlation (r=0.9 for the latter vs 0.7 for the former) thus 10 km product has been utilized for this study. Overall, gridded seasonal maps (0.1 deg.) of the 11 yr averaged AOD illustrate the highest AOD during summer, followed by spring, with the lowest observed values during fall (there is no enough valid <span class="hlt">MODIS</span> data in winter due to cloud cover). Aerosol optical properties exhibited large spatio-temporal heterogeneity in the summer with mean AOD of 0.25, followed by spring, while the fall had less variability with mean AOD below 0.1 for the entire region. However, the spatial analysis indicated hot spots around Edmonton and Calgary cities even in the fall when AODs are very low (close to background). All of the datasets showed interannual variability with no significant trend. The AI values ranged from 0.5 during winter to as high as 5 during summer suggesting mid- and long range transport of boreal fire emissions. Map correlation between AOD and UV AI showed large variability (0.2 to 0.7) indicating presence of different types of aerosols. These low correlations imply the presence of non-absorbing particles (e.g. sulfate) that comprise a relatively large mass fraction of AOD and/or low altitude particles.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2013SPIE.8866E..1MX','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2013SPIE.8866E..1MX"><span id="translatedtitle">Improvements of VIIRS and <span class="hlt">MODIS</span> solar diffuser and lunar calibration</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Xiong, Xiaoxiong; Butler, James; Lei, Ning; Sun, Junqiang; Fulbright, Jon; Wang, Zhipeng; McIntire, Jeff; Angal, Amit</p> <p>2013-09-01</p> <p>Both VIIRS and <span class="hlt">MODIS</span> instruments use solar diffuser (SD) and lunar observations to calibrate their <span class="hlt">reflective</span> solar bands (RSB). A solar diffuser stability monitor (SDSM) is used to track the SD on-orbit degradation. On-orbit observations have shown similar wavelength-dependent SD degradation (larger at shorter VIS wavelengths) and SDSM detector response degradation (larger at longer NIR wavelengths) for both VIIRS and <span class="hlt">MODIS</span> instruments. In general, the <span class="hlt">MODIS</span> scan mirror has experienced more degradation in the VIS spectral region whereas the VIIRS rotating telescope assembly (RTA) mirrors have seen more degradation in the NIR and SWIR spectral region. Because of this wavelength dependent mirror degradation, the sensor's relative spectral response (RSR) needs to be modulated. Due to differences between the solar and lunar spectral irradiance, the modulated RSR could have different effects on the SD and lunar calibration. In this paper, we identify various factors that should be considered for the improvements of VIIRS and <span class="hlt">MODIS</span> solar and lunar calibration and examine their potential impact. Specifically, we will characterize and assess the calibration impact due to SD and SDSM attenuation screen transmission (uncertainty), SD BRF uncertainty and onorbit degradation, SDSM detector response degradation, and modulated RSR resulting from the sensor's optics degradation. Also illustrated and discussed in this paper are the calibration strategies implemented in the VIIRS and <span class="hlt">MODIS</span> SD and lunar calibrations and efforts that could be made for future improvements.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/19940007013','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/19940007013"><span id="translatedtitle">Global monitoring of atmospheric properties by the EOS <span class="hlt">MODIS</span></span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>King, Michael D.</p> <p>1993-01-01</p> <p>The Moderate Resolution Imaging Spectroradiometer (<span class="hlt">MODIS</span>) being developed for the Earth Observing System (EOS) is well suited to the global monitoring of atmospheric properties from space. Among the atmospheric properties to be examined using <span class="hlt">MODIS</span> observations, clouds are especially important, since they are a strong modulator of the shortwave and longwave components of the earth's radiation budget. A knowledge of cloud properties (such as optical thickness and effective radius) and their variation in space and time, which are our task objectives, is also crucial to studies of global climate change. In addition, with the use of related airborne instrumentation, such as the Cloud Absorption Radiometer (CAR) and <span class="hlt">MODIS</span> Airborne Simulator (MAS) in intensive field experiments (both national and international campaigns, see below), various types of surface and cloud properties can be derived from the measured bidirectional <span class="hlt">reflectances</span>. These missions have provided valuable experimental data to determine the capability of narrow bandpass channels in examining the Earth's atmosphere and to aid in defining algorithms and building an understanding of the ability of <span class="hlt">MODIS</span> to remotely sense atmospheric conditions for assessing global change. Therefore, the primary task objective is to extend and expand our algorithm for retrieving the optical thickness and effective radius of clouds from radiation measurements to be obtained from <span class="hlt">MODIS</span>. The secondary objective is to obtain an enhanced knowledge of surface angular and spectral properties that can be inferred from airborne directional radiance measurements.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/20150023340','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20150023340"><span id="translatedtitle">Improvements of VIIRS and <span class="hlt">MODIS</span> Solar Diffuser and Lunar Calibration</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Xiong, Xiaoxiong; Butler, James J.; Lei, Ning; Sun, Junqiang; Fulbright, Jon; Wang, Zhipeng; McIntire, Jeff; Angal, Amit Avinash</p> <p>2013-01-01</p> <p>Both VIIRS and <span class="hlt">MODIS</span> instruments use solar diffuser (SD) and lunar observations to calibrate their <span class="hlt">reflective</span> solar bands (RSB). A solar diffuser stability monitor (SDSM) is used to track the SD on-orbit degradation. On-orbit observations have shown similar wavelength-dependent SD degradation (larger at shorter VIS wavelengths) and SDSM detector response degradation (larger at longer NIR wavelengths) for both VIIRS and <span class="hlt">MODIS</span> instruments. In general, the <span class="hlt">MODIS</span> scan mirror has experienced more degradation in the VIS spectral region whereas the VIIRS rotating telescope assembly (RTA) mirrors have seen more degradation in the NIR and SWIR spectral region. Because of this wavelength dependent mirror degradation, the sensor's relative spectral response (RSR) needs to be modulated. Due to differences between the solar and lunar spectral irradiance, the modulated RSR could have different effects on the SD and lunar calibration. In this paper, we identify various factors that should be considered for the improvements of VIIRS and <span class="hlt">MODIS</span> solar and lunar calibration and examine their potential impact. Specifically, we will characterize and assess the calibration impact due to SD and SDSM attenuation screen transmission (uncertainty), SD BRF uncertainty and onorbit degradation, SDSM detector response degradation, and modulated RSR resulting from the sensor's optics degradation. Also illustrated and discussed in this paper are the calibration strategies implemented in the VIIRS and <span class="hlt">MODIS</span> SD and lunar calibrations and efforts that could be made for future improvements.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/cgi-bin/nph-data_query?bibcode=2014AGUFM.A41J3201R&link_type=ABSTRACT','NASAADS'); return false;" href="http://adsabs.harvard.edu/cgi-bin/nph-data_query?bibcode=2014AGUFM.A41J3201R&link_type=ABSTRACT"><span id="translatedtitle">Investigating Correlations of Horizontally Oriented Ice and Precipitation in North and South Pacific Maritime Clouds Using Collocated CloudSat, CALIOP, and <span class="hlt">MODIS</span> Observations</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Ross, A.; Holz, R.; Ackerman, S. A.</p> <p>2014-12-01</p> <p>In late 2007, the Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) aboard the A-train changed its nadir-viewing angle. The original viewing angle of 0.3° (changed to 3° in 2007) allowed the polarization capabilities of the Lidar to determine the orientation of ice crystals. This is because viewing ice clouds at a nadir angle closer to 0° will yield specular <span class="hlt">reflection</span> due to horizontally oriented ice. Similarly to how a vertical mirror will <span class="hlt">reflect</span> a laser that is pointed vertically, oriented ice crystals return a strong integrated attenuated backscatter while also returning low depolarization values. This results in a distinguished depolarization and attenuated backscatter signature for horizontally oriented ice crystals as opposed to ice crystals that have no pattern in orientation (i.e. randomly oriented ice). In a preliminary search, it is found that up to 20% of warm (250 - 270 K) mid-latitude middle level clouds contain horizontally oriented ice. By taking advantage of the nearly synchronous orbits of the A-train constellation, an opportune dataset from 2006 and 2007 is compiled. This dataset includes collocated products from the CloudSat Cloud Profiling Radar (CPR), CALIOP, and the <span class="hlt">Aqua</span> Moderate-resolution Imaging Spectroradiometer (<span class="hlt">MODIS</span>). The Lidar capabilities of CALIOP in conjunction with the microwave sensitivity to precipitation provided by the CloudSat CPR give a unique point of view to explore the connection between these two physical phenomena. Similarly, the spatial imaging from <span class="hlt">MODIS</span> yields insights into the phase of cloud layer tops and particles' effective radii. <span class="hlt">MODIS</span> aerosol optical depths may also shed light upon the cloud ice nucleation mechanisms that also may play a large role in the precipitation process. Preliminary results suggest that not all marine regions have the same occurrences of HOIC; the Northern Hemisphere demonstrates a strong seasonal dependence with a maximum in the winter months while the Southern Hemisphere is</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://ntrs.nasa.gov/search.jsp?R=19930063699&hterms=spectroradiometer+MODIS&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D10%26Ntt%3Dspectroradiometer%2BMODIS','NASA-TRS'); return false;" href="http://ntrs.nasa.gov/search.jsp?R=19930063699&hterms=spectroradiometer+MODIS&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D10%26Ntt%3Dspectroradiometer%2BMODIS"><span id="translatedtitle">Moderate resolution imaging spectroradiometer (<span class="hlt">MODIS</span>) and observations of the land surface</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Salomonson, V. V.; Toll, D. L.; Lawrence, W. T.</p> <p>1992-01-01</p> <p>The moderate resolution imaging spectroradiometer (<span class="hlt">MODIS</span>) is a NASA facility instrument that is being designed for flight on the Earth Observing System (EOS) series of missions. It is designed to measure biophysical states and dynamics of the land, atmosphere, and ocean. Plans are required for use of other instruments that will be accompanying <span class="hlt">MODIS</span> on the EOS missions, such as the High-Resolution Imaging Spectrometer (HIRIS) and the Multi-angle Imaging Spectro-Radiometer (MISR). The HIRIS instrument, a spectrometer operating in the visible to shortwave infrared parts of the spectrum, would be employed in combination with the <span class="hlt">MODIS</span> to understand the impact of sampling the spectrum and the effects of land cover mixtures within the <span class="hlt">MODIS</span> pixel. The MISR will help in understanding the effects of anisotropy in <span class="hlt">reflected</span> solar radiation. Both instruments will work in combination with <span class="hlt">MODIS</span> to better quantify the effects of the atmosphere on observations of surface properties.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://ntrs.nasa.gov/search.jsp?R=20020090884&hterms=EC&qs=N%3D0%26Ntk%3DAll%26Ntx%3Dmode%2Bmatchall%26Ntt%3DEC','NASA-TRS'); return false;" href="http://ntrs.nasa.gov/search.jsp?R=20020090884&hterms=EC&qs=N%3D0%26Ntk%3DAll%26Ntx%3Dmode%2Bmatchall%26Ntt%3DEC"><span id="translatedtitle"><span class="hlt">MODIS</span> Snow and Ice Production</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Hall, Dorthoy K.; Hoser, Paul (Technical Monitor)</p> <p>2002-01-01</p> <p>Daily, global snow cover maps, and sea ice cover and sea ice surface temperature (IST) maps are derived from NASA's Moderate Resolution Imaging Spectroradiometer (<span class="hlt">MODIS</span>), are available at no cost through the National Snow and Ice Data Center (NSIDC). Included on this CD-ROM are samples of the <span class="hlt">MODIS</span> snow and ice products. In addition, an animation, done by the Scientific Visualization studio at Goddard Space Flight Center, is also included.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/20140017659','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20140017659"><span id="translatedtitle">Corrections to <span class="hlt">MODIS</span> Terra Calibration and Polarization Trending Derived from Ocean Color Products</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Meister, Gerhard; Eplee, Robert E.; Franz, Bryan A.</p> <p>2014-01-01</p> <p>Remotely sensed ocean color products require highly accurate top-of-atmosphere (TOA) radiances, on the order of 0.5% or better. Due to incidents both prelaunch and on-orbit, meeting this requirement has been a consistent problem for the <span class="hlt">MODIS</span> instrument on the Terra satellite, especially in the later part of the mission. The NASA Ocean Biology Processing Group (OBPG) has developed an approach to correct the TOA radiances of <span class="hlt">MODIS</span> Terra using spatially and temporally averaged ocean color products from other ocean color sensors (such as the SeaWiFS instrument on Orbview-2 or the <span class="hlt">MODIS</span> instrument on the <span class="hlt">Aqua</span> satellite). The latest results suggest that for <span class="hlt">MODIS</span> Terra, both linear polarization parameters of the Mueller matrix are temporally evolving. A change to the functional form of the scan angle dependence improved the quality of the derived coefficients. Additionally, this paper demonstrates that simultaneously retrieving polarization and gain parameters improves the gain retrieval (versus retrieving the gain parameter only).</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://pubs.er.usgs.gov/publication/70027625','USGSPUBS'); return false;" href="http://pubs.er.usgs.gov/publication/70027625"><span id="translatedtitle">Multi-platform comparisons of <span class="hlt">MODIS</span> and AVHRR normalized difference vegetation index data</span></a></p> <p><a target="_blank" href="http://pubs.er.usgs.gov/pubs/index.jsp?view=adv">USGS Publications Warehouse</a></p> <p>Gallo, K.; Ji, L.; Reed, B.; Eidenshink, J.; Dwyer, J.</p> <p>2005-01-01</p> <p>The relationship between AVHRR-derived normalized difference vegetation index (NDVI) values and those of future sensors is critical to continued long-term monitoring of land surface properties. The follow-on operational sensor to the AVHRR, the Visible/Infrared Imager/Radiometer Suite (VIIRS), will be very similar to the NASA Earth Observing System's Moderate Resolution Imaging Spectroradiometer (<span class="hlt">MODIS</span>) sensor. NDVI data derived from visible and near-infrared data acquired by the <span class="hlt">MODIS</span> (Terra and <span class="hlt">Aqua</span> platforms) and AVHRR (NOAA-16 and NOAA-17) sensors were compared over the same time periods and a variety of land cover classes within the conterminous United States. The results indicate that the 16-day composite NDVI values are quite similar over the composite intervals of 2002 and 2003, and linear relationships exist between the NDVI values from the various sensors. The composite AVHRR NDVI data included water and cloud masks and adjustments for water vapor as did the <span class="hlt">MODIS</span> NDVI data. When analyzed over a variety of land cover types and composite intervals, the AVHRR derived NDVI data were associated with 89% or more of the variation in the <span class="hlt">MODIS</span> NDVI values. The results suggest that it may be possible to successfully reprocess historical AVHRR data sets to provide continuity of NDVI products through future sensor systems. ?? 2005 Elsevier Inc. All rights reserved.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/20110015305','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20110015305"><span id="translatedtitle">Adjustments to the <span class="hlt">MODIS</span> Terra Radiometric Calibration and Polarization Sensitivity in the 2010 Reprocessing</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Meister, Gerhard; Franz, Bryan A.</p> <p>2011-01-01</p> <p>The Moderate-Resolution Imaging Spectroradiometer (<span class="hlt">MODIS</span>) on NASA s Earth Observing System (EOS) satellite Terra provides global coverage of top-of-atmosphere (TOA) radiances that have been successfully used for terrestrial and atmospheric research. The <span class="hlt">MODIS</span> Terra ocean color products, however, have been compromised by an inadequate radiometric calibration at the short wavelengths. The Ocean Biology Processing Group (OBPG) at NASA has derived radiometric corrections using ocean color products from the SeaWiFS sensor as truth fields. In the R2010.0 reprocessing, these corrections have been applied to the whole mission life span of 10 years. This paper presents the corrections to the radiometric gains and to the instrument polarization sensitivity, demonstrates the improvement to the Terra ocean color products, and discusses issues that need further investigation. Although the global averages of <span class="hlt">MODIS</span> Terra ocean color products are now in excellent agreement with those of SeaWiFS and <span class="hlt">MODIS</span> <span class="hlt">Aqua</span>, and image quality has been significantly improved, the large corrections applied to the radiometric calibration and polarization sensitivity require additional caution when using the data.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2016AMT.....9..711S','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2016AMT.....9..711S"><span id="translatedtitle">Evaluation of cloud base height measurements from Ceilometer CL31 and <span class="hlt">MODIS</span> satellite over Ahmedabad, India</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Sharma, Som; Vaishnav, Rajesh; Shukla, Munn V.; Kumar, Prashant; Kumar, Prateek; Thapliyal, Pradeep K.; Lal, Shyam; Acharya, Yashwant B.</p> <p>2016-02-01</p> <p>Clouds play a tangible role in the Earth's atmosphere and in particular, the cloud base height (CBH), which is linked to cloud type, is one of the most important characteristics to describe the influence of clouds on the environment. In the present study, CBH observations from Ceilometer CL31 were extensively studied during May 2013 to January 2015 over Ahmedabad (23.03° N, 72.54° E), India. A detailed comparison has been performed with the use of ground-based CBH measurements from Ceilometer CL31 and CBH retrieved from <span class="hlt">MODIS</span> (Moderate Resolution Imaging Spectroradiometer) onboard <span class="hlt">Aqua</span> and Terra satellite. CBH retrieved from <span class="hlt">MODIS</span> is ˜ 1.955 and ˜ 1.093 km on 25 July 2014 and 1 January 2015 respectively, which matches well with ceilometer-measured CBH ( ˜ 1.92 and ˜ 1.097 km). Some interesting features of cloud dynamics viz. strong downdraft and updraft have been observed over Ahmedabad which revealed different cloud characteristics during monsoon and post-monsoon periods. CBH shows seasonal variation during the Indian summer monsoon and post-monsoon period. Results indicate that the ceilometer is an excellent instrument to precisely detect low- and mid-level clouds, and the <span class="hlt">MODIS</span> satellite provides accurate retrieval of high-level clouds over this region. The CBH algorithm used for the <span class="hlt">MODIS</span> satellite is also able to capture the low-level clouds.</p> </li> </ol> <div class="pull-right"> <ul class="pagination"> <li><a href="#" onclick='return showDiv("page_1");'>«</a></li> <li><a href="#" onclick='return showDiv("page_19");'>19</a></li> <li><a href="#" onclick='return showDiv("page_20");'>20</a></li> <li class="active"><span>21</span></li> <li><a href="#" onclick='return showDiv("page_22");'>22</a></li> <li><a href="#" onclick='return showDiv("page_23");'>23</a></li> <li><a href="#" onclick='return showDiv("page_25");'>»</a></li> </ul> </div> </div><!-- col-sm-12 --> </div><!-- row --> </div><!-- page_21 --> <div id="page_22" class="hiddenDiv"> <div class="row"> <div class="col-sm-12"> <div class="pull-right"> <ul class="pagination"> <li><a href="#" onclick='return showDiv("page_1");'>«</a></li> <li><a href="#" onclick='return showDiv("page_20");'>20</a></li> <li><a href="#" onclick='return showDiv("page_21");'>21</a></li> <li class="active"><span>22</span></li> <li><a href="#" onclick='return showDiv("page_23");'>23</a></li> <li><a href="#" onclick='return showDiv("page_24");'>24</a></li> <li><a href="#" onclick='return showDiv("page_25");'>»</a></li> </ul> </div> </div> </div> <div class="row"> <div class="col-sm-12"> <ol class="result-class" start="421"> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2007SPIE.6684E..07C','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2007SPIE.6684E..07C"><span id="translatedtitle">Calibration of AVHRR sensors using the <span class="hlt">reflectance</span>-based method</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Czapla-Myers, Jeffrey S.; Thome, Kurtis J.; Leisso, Nathan P.</p> <p>2007-09-01</p> <p>The Remote Sensing Group at the University of Arizona has been active in the vicarious calibration of numerous sensors through the use of ground-based test sites. Recent efforts have included work to develop cross-calibration information between these sensors using the results from the <span class="hlt">reflectance</span>-based approach. The current work extends the cross-calibration to the AVHRR series of sensors, specifically NOAA-17, and NOAA-18. The results include work done based on data collected by ground-based personnel nearly coincident with the sensor overpasses. The available number of calibrations for the AVHRR series is increased through a set of ground-based radiometers that are deployed without the need for on-site personnel and have been operating for more than three years at Railroad Valley Playa. The spectral, spatial, and temporal characteristics of the 1-km2 large-footprint site at Railroad Valley are well understood. It is therefore well suited for the radiometric calibration of AVHRR, which has a nadir-viewing footprint of 1.1 x 1.1 km. The at-sensor radiance is predicted via a radiative transfer code using atmospheric data from a fully-automated solar radiometer. The results for AVHRR show that errors are currently larger for the automated data sets, but results indicate that the AVHRR sensors studied in this work are consistent with the <span class="hlt">Aqua</span> and Terra <span class="hlt">MODIS</span> sensors to within the uncertainties of each sensor.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://www.ncbi.nlm.nih.gov/pubmed/26458381','PUBMED'); return false;" href="http://www.ncbi.nlm.nih.gov/pubmed/26458381"><span id="translatedtitle">Undiagnosed <span class="hlt">MODY</span>: Time for Action.</span></a></p> <p><a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a></p> <p>Kleinberger, Jeffrey W; Pollin, Toni I</p> <p>2015-12-01</p> <p>Maturity-onset diabetes of the young (<span class="hlt">MODY</span>) is a monogenic form of diabetes that accounts for at least 1 % of all cases of diabetes mellitus. <span class="hlt">MODY</span> classically presents as non-insulin-requiring diabetes in lean individuals typically younger than 25 with evidence of autosomal dominant inheritance, but these criteria do not capture all cases and can also overlap with other diabetes types. Genetic diagnosis of <span class="hlt">MODY</span> is important for selecting the right treatment, yet ~95 % of <span class="hlt">MODY</span> cases in the USA are misdiagnosed. <span class="hlt">MODY</span> prevalence and characteristics have been well-studied in some populations, such as the UK and Norway, while other ethnicities, like African and Latino, need much more study. Emerging next-generation sequencing methods are making more widespread study and clinical diagnosis increasingly feasible; at the same time, they are detecting other mutations in the same genes of unknown clinical significance. This review will cover the current epidemiological studies of <span class="hlt">MODY</span> and barriers and opportunities for moving toward a goal of access to an appropriate diagnosis for all affected individuals. PMID:26458381</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://ntrs.nasa.gov/search.jsp?R=GL-2002-001471&hterms=colder+ocean&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D90%26Ntt%3Dcolder%2Bnear%2Bocean','NASA-TRS'); return false;" href="http://ntrs.nasa.gov/search.jsp?R=GL-2002-001471&hterms=colder+ocean&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D90%26Ntt%3Dcolder%2Bnear%2Bocean"><span id="translatedtitle"><span class="hlt">MODIS</span> Global Sea Surface Temperature</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p></p> <p>2002-01-01</p> <p>Every day the Moderate-resolution Imaging Spectroradiometer (<span class="hlt">MODIS</span>) measures sea surface temperature over the entire globe with high accuracy. This false-color image shows a one-month composite for May 2001. Red and yellow indicates warmer temperatures, green is an intermediate value, while blues and then purples are progressively colder values. The new <span class="hlt">MODIS</span> sea surface temperature product will be particularly useful in studies of temperature anomalies, such as El Nino, as well as research into how air-sea interactions drive changes in weather and climate patterns. In the high resolution image, notice the amazing detail in some of the regional current patterns. For instance, notice the cold water currents that move from Antarctica northward along South America's west coast. These cold, deep waters upwell along an equatorial swath around and to the west of the Galapagos Islands. Note the warm, wide currents of the Gulf Stream moving up the United States' east coast, carrying Caribbean warmth toward Newfoundland and across the Atlantic toward Western Europe. Note the warm tongue of water extending from Africa's east coast to well south of the Cape of Good Hope. <span class="hlt">MODIS</span> was launched in December 1999 aboard NASA's Terra satellite. For more details on this and other <span class="hlt">MODIS</span> data products, please see NASA Unveils Spectacular Suite of New Global Data Products from <span class="hlt">MODIS</span>. Image courtesy <span class="hlt">MODIS</span> Ocean Group, NASA GSFC, and the University of Miami</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/20030054535','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20030054535"><span id="translatedtitle">Exploring New Methods of Displaying Bit-Level Quality and Other Flags for <span class="hlt">MODIS</span> Data</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Khalsa, Siri Jodha Singh; Weaver, Ron</p> <p>2003-01-01</p> <p>The NASA Distributed Active Archive Center (DAAC) at the National Snow and Ice Data Center (NSIDC) archives and distributes snow and sea ice products derived from the MODerate resolution Imaging Spectroradiometer (<span class="hlt">MODIS</span>) on board NASA's Terra and <span class="hlt">Aqua</span> satellites. All <span class="hlt">MODIS</span> standard products are in the Earth Observing System version of the Hierarchal Data Format (HDF-EOS). The <span class="hlt">MODIS</span> science team has packed a wealth of information into each HDF-EOS file. In addition to the science data arrays containing the geophysical product, there are often pixel-level Quality Assurance arrays which are important for understanding and interpreting the science data. Currently, researchers are limited in their ability to access and decode information stored as individual bits in many of the <span class="hlt">MODIS</span> science products. Commercial and public domain utilities give users access, in varying degrees, to the elements inside <span class="hlt">MODIS</span> HDF-EOS files. However, when attempting to visualize the data, users are confronted with the fact that many of the elements actually represent eight different 1-bit arrays packed into a single byte array. This project addressed the need for researchers to access bit-level information inside <span class="hlt">MODIS</span> data files. In an previous NASA-funded project (ESDIS Prototype ID 50.0) we developed a visualization tool tailored to polar gridded HDF-EOS data set. This tool,called the Polar researchers to access, geolocate, visualize, and subset data that originate from different sources and have different spatial resolutions but which are placed on a common polar grid. The bit-level visualization function developed under this project was added to PHDIS, resulting in a versatile tool that serves a variety of needs. We call this the EOS Imaging Tool.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/20140011189','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20140011189"><span id="translatedtitle"><span class="hlt">MODIS</span> 3 Km Aerosol Product: Applications over Land in an Urban/suburban Region</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Munchak, L. A.; Levy, R. C.; Mattoo, S.; Remer, L. A.; Holben, B. N.; Schafer, J. S.; Hostetler, C. A.; Ferrare, R. A.</p> <p>2013-01-01</p> <p>MODerate resolution Imaging Spectroradiometer (<span class="hlt">MODIS</span>) instruments aboard the Terra and <span class="hlt">Aqua</span> satellites have provided a rich dataset of aerosol information at a 10 km spatial scale. Although originally intended for climate applications, the air quality community quickly became interested in using the <span class="hlt">MODIS</span> aerosol data. However, 10 km resolution is not sufficient to resolve local scale aerosol features. With this in mind, <span class="hlt">MODIS</span> Collection 6 is including a global aerosol product with a 3 km resolution. Here, we evaluate the 3 km product over the Baltimore/Washington D.C., USA, corridor during the summer of 2011, by comparing with spatially dense data collected as part of the DISCOVER-AQ campaign these data were measured by the NASA Langley Research Center airborne High Spectral Resolution Lidar (HSRL) and a network of 44 sun photometers (SP) spaced approximately 10 km apart. The HSRL instrument shows that AOD can vary by up to 0.2 within a single 10 km <span class="hlt">MODIS</span> pixel, meaning that higher resolution satellite retrievals may help to characterize aerosol spatial distributions in this region. Different techniques for validating a high-resolution aerosol product against SP measurements are considered. Although the 10 km product is more statistically reliable than the 3 km product, the 3 km product still performs acceptably, with more than two-thirds of <span class="hlt">MODIS</span>/SP collocations falling within the expected error envelope with high correlation (R > 0.90). The 3 km product can better resolve aerosol gradients and retrieve closer to clouds and shorelines than the 10 km product, but tends to show more significant noise especially in urban areas. This urban degradation is quantified using ancillary land cover data. Overall, we show that the <span class="hlt">MODIS</span> 3 km product adds new information to the existing set of satellite derived aerosol products and validates well over the region, but due to noise and problems in urban areas, should be treated with some degree of caution.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2010AGUFM.B33C0418S','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2010AGUFM.B33C0418S"><span id="translatedtitle">Detection of irrigation timing using <span class="hlt">MODIS</span> and SAR: Effect of land cover heterogeneity</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Seungtaek, J.; Keunchang, J.; Lee, H.; Seokyeong, H.; Kang, S.</p> <p>2010-12-01</p>