MODIS and SeaWIFS on-orbit lunar calibration

USGS Publications Warehouse

Sun, Jielun; Eplee, R.E.; Xiong, X.; Stone, T.; Meister, G.; McClain, C.R.

2008-01-01

The Moon plays an important role in the radiometric stability monitoring of the NASA Earth Observing System's (EOS) remote sensors. The MODIS and SeaWIFS are two of the key instruments for NASA's EOS missions. The MODIS Protoflight Model (PFM) on-board the Terra spacecraft and the MODIS Flight Model 1 (FM1) on-board the Aqua 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 Reflective 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 MODIS, the lunar view responses with corrections for the viewing geometry are used to track the gain change for its reflective 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 MODIS system response degradation is wavelength, mirror side, and AOI dependent. Time-dependent Response Versus Scan angle (RVS) Look-Up Tables (LUT) are applied in MODIS RSB calibration and lunar observations play a key role in RVS derivation. The corrections provided by the RVS in the Terra and Aqua MODIS 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 corrections to the SeaWiFS data, after more than ten years on orbit, are 19% at 865 nm, 8% at 765 nm, and 1-3% in the other bands. In this report, the lunar calibration algorithms are reviewed and the RSB gain changes observed by the lunar observations are shown for all three sensors. The lunar observations for the three instruments are compared using the USGS photometric model. The USGS lunar model facilitates the cross calibration of instruments with different spectra bandpasses whose measurements of the Moon differ in time and observing geometry.

eMODIS: A User-Friendly Data Source

USGS Publications Warehouse

Jenkerson, Calli B.; Maiersperger, Thomas; Schmidt, Gail

2010-01-01

The U.S. Geological Survey's (USGS) Earth Resources Observation and Science (EROS) Center is generating a suite of products called 'eMODIS' based on Moderate Resolution Imaging Spectroradiometer (MODIS) 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), MODIS is well suited for vegetation studies. For operational monitoring, however, the benefits of MODIS are counteracted by usability issues with the standard map projection, file format, composite interval, high-latitude 'bow-tie' effects, and production latency. eMODIS responds to a community-specific need for alternatively packaged MODIS data, addressing each of these factors for real-time monitoring and historical trend analysis. eMODIS processes calibrated radiance data (level-1B) acquired by the MODIS sensors on the EOS Terra and Aqua satellites by combining MODIS Land Science Collection 5 Atmospherically Corrected Surface Reflectance production code and USGS EROS MODIS Direct Broadcast System (DBS) software to create surface reflectance and Normalized Difference Vegetation Index (NDVI) products. eMODIS 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. eMODIS composites are projected to non-Sinusoidal mapping grids that best suit the geography in their areas of application (see eMODIS Product Description below). For eMODIS products generated over the continental United States (eMODIS CONUS), the Terra (from 2000) and Aqua (from 2002) records are available and continue through present time. eMODIS CONUS also is generated in an expedited process that delivers a 7-day rolling composite, created daily with the most recent 7 days of acquisition, to users monitoring real-time vegetation conditions. eMODIS Alaska is not part of expedited processing, but does cover the Terra mission life (2000-present). A simple file transfer protocol (FTP) distribution site currently is enabled on the Internet for direct download of eMODIS products (ftp://emodisftp.cr.usgs.gov/eMODIS), with plans to expand into an interactive portal environment.

Cross-Calibration of Earth Observing System Terra Satellite Sensors MODIS and ASTER

NASA Technical Reports Server (NTRS)

McCorkel, J.

2014-01-01

The Advanced Spaceborne Thermal Emissive and Reflection Radiometer (ASTER) and Moderate Resolution Imaging Spectrometer (MODIS) are two of the five sensors onboard the Earth Observing System's Terra satellite. These sensors share many similar spectral channels while having much different spatial and operational parameters. ASTER is a tasked sensor and sometimes referred to a zoom camera of the MODIS that collects a full-earth image every one to two days. It is important that these sensors have a consistent characterization and calibration for continued development and use of their data products. This work uses a variety of test sites to retrieve and validate intercalibration results. The refined calibration of Collection 6 of the Terra MODIS data set is leveraged to provide the up-to-date reference for trending and validation of ASTER. Special attention is given to spatially matching radiance measurements using prelaunch spatial response characterization of MODIS. Despite differences in spectral band properties and spatial scales, ASTER-MODIS is an ideal case for intercomparison since the sensors have nearly identical views and acquisitions times and therefore can be used as a baseline of intercalibration performance of other satellite sensor pairs.

Sensor On-orbit Calibration and Characterization Using Spacecraft Maneuvers

NASA Technical Reports Server (NTRS)

Xiong, X.; Butler, Jim; Barnes, W. L.; Guenther, B.

2007-01-01

Spacecraft flight operations often require activities that involve different kinds of maneuvers for orbital adjustments (pitch, yaw, and roll). Different maneuvers, when properly planned and scheduled, can also be applied to support and/or to perform on-board sensor calibration and characterization. This paper uses MODIS (Moderate Resolution Imaging Spectroradiometer) as an example to illustrate applications of spacecraft maneuvers for Earth-observing sensors on-orbit calibration and characterization. MODIS is one of the key instruments for NASA's Earth Observing System (EOS) currently operated on-board the EOS Terra and Aqua spacecraft launched in December 1999 and May 2002, respectively. Since their launch, both Terra and Aqua spacecraft have made a number of maneuvers, specially the yaw and roll maneuvers, to support the MODIS on-orbit calibration and characterization. For both Terra and Aqua MODIS, near-monthly spacecraft roll maneuvers are executed for lunar observations. These maneuvers are carefully scheduled so that the lunar phase angles are nearly identical for each sensor's lunar observations. The lunar observations are used to track MODIS reflective solar bands (RSB) calibration stability and to inter-compare Terra and Aqua MODIS RSB calibration consistency. To date, two sets of yaw maneuvers (each consists of two series of 8 consecutive yaws) by the Terra spacecraft and one set by the Aqua spacecraft have been performed to validate MODIS solar diffuser (SD) bi-directional reflectance factor (BRF) and to derive SD screen transmission. Terra spacecraft pitch maneuvers, first made on March 26, 2003 and the second on April 14, 2003 (with the Moon in the spacecraft nadir view), have been applied to characterize MODIS thermal emissive bands (TEB) response versus scan angle (RVS). This is particularly important since the pre-launch TEB RSV measurements made by the sensor vendor were not successful. Terra MODIS TEB RVS obtained from pitch maneuvers have been used in the current LIB calibration algorithm. Lunq observations from pitch maneuvers also provided information to cross-calibrate MODIS with other sensors (MISR and ASTER) on the same platform. We will provide a summary of MODIS maneuver activities and their applications for MODIS calibration and characterization. The results and lessons learned discussed in this paper from MODIS maneuver activities will provide useful insights into future spacecraft and sensor operation.

Global Space-Based Inter-Calibration System Reflective Solar Calibration Reference: From Aqua MODIS to S-NPP VIIRS

NASA Technical Reports Server (NTRS)

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

2016-01-01

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.

Scaling Gross Primary Production (GPP) over boreal and deciduous forest landscapes in support of MODIS GPP product validation.

Treesearch

David P. Turner; William D. Ritts; Warren B. Cohen; Stith T. Gower; Maosheng Zhao; Steve W. Running; Steven C. Wofsy; Shawn Urbanski; Allison L. Dunn; J.W. Munger

2003-01-01

The Moderate Resolution Imaging Radiometer (MODIS) is the primary instrument in the NASA Earth Observing System for monitoring the seasonality of global terrestrial vegetation. Estimates of 8-day mean daily gross primary production (GPP) at the 1 km spatial resolution are now operationally produced by the MODIS Land Science Team for the global terrestrial surface using...

A Prototype MODI- SSM/I Snow Mapping Algorithm

NASA Technical Reports Server (NTRS)

Tait, Andrew B.; Barton, Jonathan S.; Hall, Dorothy K.

1999-01-01

Data in the wavelength range 0.545 - 1.652 microns from the Moderate Resolution Imaging Spectroradiometer (MODIS), to be launched aboard the Earth Observing System (EOS) Terra in the fall of 1999, will be used to map daily global snow cover at 500m resolution. However, during darkness, or when the satellite's view of the surface is obscured by cloud, snow cover cannot be mapped using MODIS data. We show that during these conditions, it is possible to supplement the MODIS product by mapping the snow cover using passive microwave data from the Special Sensor Microwave Imager (SSM/I), albeit with much poorer resolution. For a 7-day time period in March 1999, a prototype MODIS snow-cover product was compared with a prototype MODIS-SSM/I product for the same area in the mid-western United States. The combined MODIS-SSM/I product mapped 9% more snow cover than the MODIS-only product.

Calibration Improvements in the Detector-to-Detector Differences for the MODIS Ocean Color Bands

NASA Technical Reports Server (NTRS)

Li, Yonghong; Angal, Amit; Wu, Aisheng; Geng, Xu; Link, Daniel; Xiong, Xiaoxiong

2016-01-01

The Moderate Resolution Imaging Spectroradiometer (MODIS), a major instrument within NASAs Earth Observation System missions, has operated for over 16 and 14 years onboard the Terra and Aqua satellites, respectively. Its reflective solar bands (RSB) covering a spectral range from 0.4 to 2.1 micrometers are primarily calibrated using the on-board solar diffuser(SD), with its on-orbit degradation monitored using the Solar Diffuser Stability Monitor. RSB calibrations are supplemented by near-monthly lunar measurements acquired from the instruments space-view port. Nine bands (bands 8-16) in the visible to near infrared spectral range from 0.412 to 0.866 micrometers are primarily used for ocean color observations.During a recent reprocessing of ocean color products, performed by the NASA Ocean Biology Processing Group, detector-to-detector differences of up to 1.5% were observed in bands 13-16 of Terra MODIS. This paper provides an overview of the current approach to characterize the MODIS detector-to-detector differences. An alternative methodology was developed to mitigate the observed impacts for bands 13-16. The results indicated an improvement in the detector residuals and in turn are expected to improve the MODIS ocean color products. This paper also discusses the limitations,subsequent enhancements, and the improvements planned for future MODIS calibration collections.

Siberian Earth System Science Cluster - A web-based Geoportal to provide user-friendly Earth Observation Products for supporting NEESPI scientists

NASA Astrophysics Data System (ADS)

Eberle, J.; Gerlach, R.; Hese, S.; Schmullius, C.

2012-04-01

To provide earth observation products in the area of Siberia, the Siberian Earth System Science Cluster (SIB-ESS-C) was established as a spatial data infrastructure at the University of Jena (Germany), Department for Earth Observation. This spatial data infrastructure implements standards published by the Open Geospatial Consortium (OGC) and the International Organizsation for Standardization (ISO) for data discovery, data access, data processing and data analysis. The objective of SIB-ESS-C is to faciliate environmental research and Earth system science in Siberia. The region for this project covers the entire Asian part of the Russian Federation approximately between 58°E - 170°W and 48°N - 80°N. To provide discovery, access and analysis services a webportal was published for searching and visualisation of available data. This webportal is based on current web technologies like AJAX, Drupal Content Management System as backend software and a user-friendly surface with Drag-n-Drop and further mouse events. To have a wide range of regular updated earth observation products, some products from sensor MODIS at the satellites Aqua and Terra were processed. A direct connection to NASA archive servers makes it possible to download MODIS Level 3 and 4 products and integrate it in the SIB-ESS-C infrastructure. These data can be downloaded in a file format called Hierarchical Data Format (HDF). For visualisation and further analysis, this data is reprojected, converted to GeoTIFF and global products clipped to the project area. All these steps are implemented as an automatic process chain. If new MODIS data is available within the infrastructure this process chain is executed. With the link to a MODIS catalogue system, the system gets new data daily. With the implemented analysis processes, timeseries data can be analysed, for example to plot a trend or different time series against one another. Scientists working in this area and working with MODIS data can make use of this service over the webportal. Both searching manually the NASA archive for MODIS data, processing these data automatically and then download it for further processing and using the regular updated products.

Moderate Resolution Imaging Spectroradiometer (MODIS) Overview

USGS Publications Warehouse

,

2008-01-01

The Moderate Resolution Imaging Spectroradiometer (MODIS) 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 MODIS instruments, the refinement of algorithms used to create higher-level products, and the ongoing product validation make MODIS 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, MODIS acquires morning (EOS-Terra) and afternoon (EOS-Aqua) views almost daily. Terra data acquisitions began in February 2000 and Aqua 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. MODIS-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 MODIS 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 MODIS 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 Aqua MODIS data products.

Intercomparisons of marine boundary layer cloud properties from the ARM CAP-MBL campaign and two MODIS cloud products

NASA Astrophysics Data System (ADS)

Zhang, Zhibo; Dong, Xiquan; Xi, Baike; Song, Hua; Ma, Po-Lun; Ghan, Steven J.; Platnick, Steven; Minnis, Patrick

2017-02-01

From April 2009 to December 2010, the Department of Energy Atmospheric Radiation Measurement (ARM) program carried out an observational field campaign on Graciosa Island, targeting the marine boundary layer (MBL) clouds over the Azores region. In this paper, we present an intercomparison of the MBL cloud properties, namely, cloud liquid water path (LWP), cloud optical thickness (COT), and cloud-droplet effective radius (CER), among retrievals from the ARM mobile facility and two Moderate Resolution Imaging Spectroradiometer (MODIS) cloud products (Goddard Space Flight Center (GSFC)-MODIS and Clouds and Earth's Radiant Energy System-MODIS). A total of 63 daytime single-layer MBL cloud cases are selected for intercomparison. Comparison of collocated retrievals indicates that the two MODIS cloud products agree well on both COT and CER retrievals, with the correlation coefficient R > 0.95, despite their significant difference in spatial sampling. In both MODIS products, the CER retrievals based on the 2.1 µm band (CER2.1) are significantly larger than those based on the 3.7 µm band (CER3.7). The GSFC-MODIS cloud product is collocated and compared with ground-based ARM observations at several temporal-spatial scales. In general, the correlation increases with more precise collocation. For the 63 selected MBL cloud cases, the GSFC-MODIS LWP and COT retrievals agree reasonably well with the ground-based observations with no apparent bias and correlation coefficient R around 0.85 and 0.70, respectively. However, GSFC-MODIS CER3.7 and CER2.1 retrievals have a lower correlation (R 0.5) with the ground-based retrievals. For the 63 selected cases, they are on average larger than ground observations by about 1.5 µm and 3.0 µm, respectively. Taking into account that the MODIS CER retrievals are only sensitive to cloud top reduces the bias only by 0.5 µm.

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.

Synergistic use of MODIS cloud products and AIRS radiance measurements for retrieval of cloud parameters

NASA Astrophysics Data System (ADS)

Li, J.; Menzel, W.; Sun, F.; Schmit, T.

2003-12-01

The Moderate-Resolution Imaging Spectroradiometer (MODIS) and Atmospheric Infrared Sounder (AIRS) measurements from the Earth Observing System's (EOS) Aqua satellite will enable global monitoring of the distribution of clouds. MODIS is able to provide at high spatial resolution (1 ~ 5km) the cloud mask, surface and cloud types, cloud phase, cloud-top pressure (CTP), effective cloud amount (ECA), cloud particle size (CPS), and cloud water path (CWP). AIRS is able to provide CTP, ECA, CPS, and CWP within the AIRS footprint with much better accuracy using its greatly enhanced hyperspectral remote sensing capability. The combined MODIS / AIRS system offers the opportunity for cloud products improved over those possible from either system alone. The algorithm developed was applied to process the AIRS longwave cloudy radiance measurements; results are compared with MODIS cloud products, as well as with the Geostationary Operational Environmental Satellite (GOES) sounder cloud products, to demonstrate the advantage of synergistic use of high spatial resolution MODIS cloud products and high spectral resolution AIRS sounder radiance measurements for optimal cloud retrieval. Data from ground-based instrumentation at the Atmospheric Radiation Measurement (ARM) Program Cloud and Radiation Test Bed (CART) in Oklahoma were used for the validation; results show that AIRS improves the MODIS cloud products in certain cases such as low-level clouds.

Operationalizing a Research Sensor: MODIS to VIIRS

NASA Astrophysics Data System (ADS)

Grant, K. D.; Miller, S. W.; Puschell, J.

2012-12-01

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 (MODIS) 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). MODIS 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. MODIS has flown on the EOS Terra satellite since 1999 and on the EOS Aqua satellite since 2002 and provided excellent data for scientific research and operational use for more than a decade. The value of MODIS-derived products for operational environmental monitoring motivated led to the development of an operational counterpart to MODIS for the next-generation polar-orbiting environmental satellites, the Visible/Infrared Imager Radiometer Suite (VIIRS). VIIRS combines the demonstrated high value spectral coverage and radiometric accuracy of MODIS with the legacy spectral bands and radiometric accuracy of the Advanced Very High Resolution Radiometer (AVHRR) and the high spatial resolution (0.75 km) of the Operational Linescan System (OLS). Except for MODIS bands designed for deriving vertical temperature and humidity structure in the atmosphere, VIIRS uses identical or very similar bands from MODIS that have the most interest and usefulness to operational customers in NOAA, the USAF and the USN. The development of VIIRS and JPSS reaps the benefit of investments in MODIS and the NASA EOS and the early development of operational algorithms by NOAA and DoD using MODIS data. This presentation will cover the different aspects of transitioning a research system into an operational system. These aspects include: (1) sensor (hardware & software) operationalization, (2) system performance operational factors, (3) science changes to algorithms reflecting the operational performance factors, and (4) the operationalization and incorporation of the science into a fully 24 x 7 production system, tasked with meeting stringent operational needs. Benefits of early operationalization are discussed along with suggested areas for improvement in this process that could benefit future work such as operationalizing Earth Science Decadal Survey missions.

Results and lessons learned from MODIS polarization sensitivity characterization

NASA Astrophysics Data System (ADS)

Sun, J.; Xiong, X.; Wang, X.; Qiu, S.; Xiong, S.; Waluschka, E.

2006-08-01

In addition to radiometric, spatial, and spectral calibration requirements, MODIS design specifications include polarization sensitivity requirements of less than 2% for all Reflective Solar Bands (RSB) except for the band centered at 412nm. To the best of our knowledge, MODIS was the first imaging radiometer that went through comprehensive system level (end-to-end) polarization characterization. MODIS polarization sensitivity was measured pre-launch at a number of sensor view angles using a laboratory Polarization Source Assembly (PSA) that consists of a rotatable source, a polarizer (Ahrens prism design), and a collimator. This paper describes MODIS polarization characterization approaches used by MODIS Characterization Support Team (MCST) at NASA/GSFC and addresses issues and concerns in the measurements. Results (polarization factor and phase angle) using different analyzing methods are discussed. Also included in this paper is a polarization characterization comparison between Terra and Aqua MODIS. Our previous and recent analysis of MODIS RSB polarization sensitivity could provide useful information for future Earth-observing sensor design, development, and characterization.

MODIS Science Algorithms and Data Systems Lessons Learned

NASA Technical Reports Server (NTRS)

Wolfe, Robert E.; Ridgway, Bill L.; Patt, Fred S.; Masuoka, Edward J.

2009-01-01

For almost 10 years, standard global products from NASA's Earth Observing System s (EOS) two Moderate Resolution Imaging Spectroradiometer (MODIS) 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 Aqua missions in less than a year. Many of the lessons learned from MODIS are already being applied to follow-on missions.

SCAR-B fires in the tropics: Properties and remote sensing from EOS-MODIS

NASA Astrophysics Data System (ADS)

Kaufman, Yoram J.; Kleidman, Richard G.; King, Michael D.

1998-12-01

Two moderate resolution imaging spectroradiometer (MODIS) instruments are planned for launch in 1999 and 2000 on the NASA Earth Observing System (EOS) AM-1 and EOS PM-1 satellites. The MODIS instrument will sense fires with designated 3.9 and 11 μm channels that saturate at high temperatures (450 and 400 K, respectively). MODIS data will be used to detect fires, to estimate the rate of emission of radiative energy from the fire, and to estimate the fraction of biomass burned in the smoldering phase. The rate of emission of radiative energy is a measure of the rate of combustion of biomass in the fires. In the Smoke, Clouds, and Radiation-Brazil (SCAR-B) experiment the NASA ER-2 aircraft flew the MODIS airborne simulator (MAS) to measure the fire thermal and mid-IR signature with a 50 m spatial resolution. These data are used to observe the thermal properties and sizes of fires in the cerrado grassland and Amazon forests of Brazil and to simulate the performance of the MODIS 1 km resolution fire observations. Although some fires saturated the MAS 3.9 μm channel, all the fires were well within the MODIS instrument saturation levels. Analysis of MAS data over different ecosystems, shows that the fire size varied from single MAS pixels (50×50 m) to over 1 km2. The 1×1 km resolution MODIS instrument can observe only 30-40% of these fires, but the observed fires are responsible for 80 to nearly 100% of the emitted radiative energy and therefore for 80 to 100% of the rate of biomass burning in the region. The rate of emission of radiative energy from the fires correlated very well with the formation of fire burn scars (correlation coefficient = 0.97). This new remotely sensed quantity should be useful in regional estimates of biomass consumption.

MODIS Solar Diffuser On-orbit Performance

NASA Technical Reports Server (NTRS)

Xiong, Xiaoxiong; Chen, H.; Choi, T.; Sun, J.; Angal, A.

2008-01-01

MODIS is a key instrument for the NASA Earth Observing System (EOS), currently operated on both the Terra and Aqua missions. Each MODIS instrument has 20 reflective solar bands (RSBs) and 16 thermal emissive bands (TEBs). MODIS RSB on-orbit calibration is reflectance based using an on-board solar diffuser (SD). The SD bi-directional reflectance factors (BRFs) were characterized pre-launch using reference diffuser samples, which are traceable to NIST reflectance standards. The SD BRF on-orbit degradation (or change) is tracked by another onboard device, called the solar diffuser stability monitor (SDSM). The SDSM is operated during each scheduled SD calibration event, making alternate observations of direct sunlight and the diffusely reflected sunlight from the SD. The time series of the ratios of SDSM's SD view to its Sun view provide SD degradation information. This paper presents and compares the Terra and Aqua MODIS SD on-orbit performance. Results show that the SD on-orbit degradation depends on the amount of solar exposure of the SD plate. In addition, it is strongly wavelengthdependent, with a larger degradation rate at shorter wavelengths. For Terra MODIS, an SD door anomaly occurred in May 2003 that led to a decision to fix the door permanently at an "open" position. Since then, the SD degradation rate has significantly increased due to more frequent solar exposure. As expected, the SD on-orbit performance directly impacts the RSB calibration performance. The lessons learned from MODIS on-orbit calibration will provide useful insights into the development and operation of future SD calibration systems.

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-daily coverage of the Earth's surface, MODIS provides comprehensive measurements that enable scientists and policy makers to better understand and effectively manage the natural resources on both regional and global scales. Terra, the first large multisensor EOS satellite, is operated in a 10:30 am (local equatorial crossing time, descending southwards) polar orbit. Aqua, the second multisensor EOS satellite is operated in a 1:30 pm (local equatorial crossing time, ascending northwards) polar orbit. With complementing morning and afternoon observations, the Terra and Aqua MODIS, together with other sensors housed on both satellites, have greatly improved our understanding of the dynamics of the global environmental system.

On-orbit Characterization of RVS for MODIS Thermal Emissive Bands

NASA Technical Reports Server (NTRS)

Xiong, X.; Salomonson, V.; Chiang, K.; Wu, A.; Guenther, B.; Barnes, W.

2004-01-01

Response versus scan angle (RVS) is a key calibration parameter for remote sensing radiometers that make observations using a scanning optical system, such as a scan mirror in MODIS and GLI or a rotating telescope in SeaWiFS and VIIRS, since the calibration is typically performed at a fixed viewing angle while the Earth scene observations are made over a range of viewing angles. Terra MODIS has been in operation for more than four years since its launch in December 1999. It has 36 spectral bands covering spectral range from visible (VIS) to long-wave infrared (LWIR). It is a cross-track scanning radiometer using a two-sided paddle wheel scan mirror, making observations over a wide field of view (FOV) of +/-55 deg from the instrument nadir. This paper describes on-orbit characterization of MODIS RVS for its thermal emissive bands (TEB), using the Earth view data collected during Terra spacecraft deep space maneuvers (DSM). Comparisons with pre-launch analysis and early on-orbit measurements are also provided.

AIRS Subpixel Cloud Characterization Using MODIS Cloud Products.

NASA Astrophysics Data System (ADS)

Li, Jun; Menzel, W. Paul; Sun, Fengying; Schmit, Timothy J.; Gurka, James

2004-08-01

The Moderate Resolution Imaging Spectroradiometer (MODIS) and the Atmospheric Infrared Sounder (AIRS) measurements from the Earth Observing System's (EOS's) Aqua satellite enable improved global monitoring of the distribution of clouds. MODIS is able to provide, at high spatial resolution (1 5 km), a cloud mask, surface and cloud types, cloud phase, cloud-top pressure (CTP), effective cloud amount (ECA), cloud particle size (CPS), and cloud optical thickness (COT). AIRS is able to provide CTP, ECA, CPS, and COT at coarser spatial resolution (13.5 km at nadir) but with much better accuracy using its high-spectral-resolution measurements. The combined MODIS AIRS system offers the opportunity for improved cloud products over those possible from either system alone. The key steps for synergistic use of imager and sounder radiance measurements are 1) collocation in space and time and 2) imager cloud amount, type, and phase determination within the sounder pixel. The MODIS and AIRS measurements from the EOS Aqua satellite provide the opportunity to study the synergistic use of advanced imager and sounder measurements. As the first step, the MODIS classification procedure is applied to identify various surface and cloud types within an AIRS footprint. Cloud-layer information (lower, midlevel, or high clouds) and phase information (water, ice, or mixed-phase clouds) within the AIRS footprint are sorted and characterized using MODIS 1-km-spatial-resolution data. The combined MODIS and AIRS data for various scenes are analyzed to study the utility of the synergistic use of high-spatial-resolution imager products and high-spectral-resolution sounder radiance measurements. There is relevance to the optimal use of data from the Advanced Baseline Imager (ABI) and Hyperspectral Environmental Suite (HES) systems, which are to fly on the Geostationary Operational Environmental Satellite (GOES)-R.

Passive and Active Detection of Clouds: Comparisons between MODIS and GLAS Observations

NASA Technical Reports Server (NTRS)

Mahesh, Ashwin; Gray, Mark A.; Palm, Stephen P.; Hart, William D.; Spinhirne, James D.

2003-01-01

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 Aqua satellite is examined along with GLAS observations of cloud layers. In more than three-quarters of the cases, MODIS 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 MODIS 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.

USAID Expands eMODIS Coverage for Famine Early Warning

NASA Astrophysics Data System (ADS)

Jenkerson, C.; Meyer, D. J.; Evenson, K.; Merritt, M.

2011-12-01

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 (MODIS) data processed by U.S. Geological Survey (USGS) into eMODIS Normalized Difference Vegetation Index (NDVI) products. Near-real time production is used comparatively with trends derived from the eMODIS archive to operationally monitor vegetation anomalies indicating threatened cropland and rangeland conditions. eMODIS production over Central America and the Caribbean (CAMCAR) began in 2009, and processes 10-day NDVI composites every 5 days from surface reflectance inputs produced using predicted spacecraft and climatology information at Land and Atmosphere Near real time Capability for Earth Observing Systems (EOS) (LANCE). These expedited eMODIS composites are backed by a parallel archive of precision-based NDVI calculated from surface reflectance data ordered through Level 1 and Atmosphere Archive and Distribution System (LAADS). Success in the CAMCAR region led to the recent expansion of eMODIS 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/eMODIS). 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 eMODIS 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.

Abstract Art or Arbiters of Energy?

NASA Technical Reports Server (NTRS)

2002-01-01

More than just the idle stuff of daydreams, clouds help control the flow of radiant energy around our world. Clouds are plentiful and widespread throughout Earth's atmosphere-covering up to 75 percent of our planet at any given time-so they play a dominant role in determining how much sunlight reaches the surface, how much sunlight is reflected back into space, how and where warmth is spread around the globe, and how much heat escapes from the surface and atmosphere back into space. Clouds are also highly variable. Clouds' myriad variations through time and space make them one of the greatest areas of uncertainty in scientists' understanding and predictions of climate change. In short, they play a central role in our world's climate system. The false-color image above shows a one-month composite of cloud optical thickness measured by the Moderate-resolution Imaging Spectroradiometer (MODIS) and averaged globally for April 2001. Optical thickness is a measure of how much solar radiation is not allowed to travel through a column of atmosphere. Areas colored red and yellow indicate very cloudy skies, on average, while areas colored green and light blue show moderately cloudy skies. Dark blue regions show where there is little or no cloud cover. This data product is an important new tool for helping scientists understand the roles clouds play in our global climate system. MODIS gives scientists new capabilities for measuring the structure and composition of clouds. MODIS observes the entire Earth almost every day in 36 spectral bands ranging from visible to thermal infrared wavelengths, enabling it to quantify a wide suite of clouds' physical and radiative properties. Specifically, MODIS can determine whether a cloud is composed of ice or water particles (or some combination of the two), it can measure the effective radius of the particles within a cloud, it can determine the temperature and altitude of cloud tops, and it can observe how much sunlight passes through a cloud. MODIS is one of five sensors flying aboard NASA's Terra satellite, the flagship in NASA's Earth Observing System, launched in December 1999. For more information about this and other new MODIS products, read NASA Unveils Spectacular Suite of New Global Data Products from MODIS. Image courtesy MODIS Atmosphere Group, NASA GSFC

Terra MODIS Band 27 Electronic Crosstalk Effect and Its Removal

NASA Technical Reports Server (NTRS)

Sun, Junqiang; Xiong, Xiaoxiong; Madhavan, Sriharsha; Wenny, Brian

2012-01-01

The MODerate-resolution Imaging Spectroradiometer (MODIS) is one of the primary instruments in the NASA Earth Observing System (EOS). The first MODIS instrument was launched in December, 1999 on-board the Terra spacecraft. MODIS has 36 bands, covering a wavelength range from 0.4 micron to 14.4 micron. MODIS band 27 (6.72 micron) is a water vapor band, which is designed to be insensitive to Earth surface features. In recent Earth View (EV) images of Terra band 27, surface feature contamination is clearly seen and striping has become very pronounced. In this paper, it is shown that band 27 is impacted by electronic crosstalk from bands 28-30. An algorithm using a linear approximation is developed to correct the crosstalk effect. The crosstalk coefficients are derived from Terra MODIS lunar observations. They show that the crosstalk is strongly detector dependent and the crosstalk pattern has changed dramatically since launch. The crosstalk contributions are positive to the instrument response of band 27 early in the mission but became negative and much larger in magnitude at later stages of the mission for most detectors of the band. The algorithm is applied to both Black Body (BB) calibration and MODIS L1B products. With the crosstalk effect removed, the calibration coefficients of Terra MODIS band 27 derived from the BB show that the detector differences become smaller. With the algorithm applied to MODIS L1B products, the Earth surface features are significantly removed and the striping is substantially reduced in the images of the band. The approach developed in this report for removal of the electronic crosstalk effect can be applied to other MODIS bands if similar crosstalk behaviors occur.

The Generation of Near-Real Time Data Products for MODIS

NASA Astrophysics Data System (ADS)

Teague, M.; Schmaltz, J. E.; Ilavajhala, S.; Ye, G.; Masuoka, E.; Murphy, K. J.; Michael, K.

2010-12-01

The GSFC Terrestrial Information Systems Branch (614.5) operate the Land and Atmospheres Near-real-time Capability for EOS (LANCE-MODIS) system. Other LANCE elements include -AIRS, -MLS, -OMI, and -AMSR-E. LANCE-MODIS incorporates the former Rapid Response system and will, in early 2011, include the Fire Information for Resource Management System (FIRMS). The purpose of LANCE is to provide applications users with a variety of products on a near-real time basis. The LANCE-MODIS data products include Level 1 (L1), L2 fire, snow, sea ice, cloud mask/profiles, aerosols, clouds, land surface reflectance, land surface temperature, and L2G and L3 gridded, daily, land surface reflectance products. Data are available either by ftp access (pull) or by subscription (push) and the L1 and L2 data products are available within an average of 2.5 hours of the observation time. The use of ancillary data products input to the standard science algorithms has been modified in order to obtain these latencies. The resulting products have been approved for applications use by the MODIS Science Team. The http://lance.nasa.gov site provides registration information and extensive information concerning the MODIS data products and imagery including a comparison between the LANCE-MODIS and the standard science-quality products generated by the MODAPS system. The LANCE-MODIS system includes a variety of tools that enable users to manipulate the data products including: parameter, band, and geographic subsetting, re-projection, mosaicing, and generation of data in the GeoTIFF format. In most instances the data resulting from use of these tools has a latency of less than 3 hours. Access to these tools is available through a Web Coverage Service. A Google Earth/Web Mapping Service is available to access image products. LANCE-MODIS supports a wide variety of applications users in civilian, military, and foreign agencies as well as universities and the private sector. Examples of applications are: Flood Mapping, Famine relief, Food and Agriculture, Hazards and Disasters, and Weather.

MODIS polarization performance and anomalous four-cycle polarization phenomenon

NASA Astrophysics Data System (ADS)

Young, James B.; Knight, Ed; Merrow, Cindy

1998-10-01

The Moderate Resolution Imaging Spectroradiometer (MODIS) will be one of the primary instruments observing the earth on the Earth Observing System (EOS) scheduled for launch in 1999. MODIS polarization performance characterization was required for the 0.4 to 0.6 micrometers (VIS), 0.6 micrometers to 1.0 micrometers (NIR), and 1.0 micrometers to 2.3 micrometers (SWIR) regions. A polarized source assembly (PSA) consisting of a collimator with a rotatable Ahrens polarizer was used to illuminate MODIS with a linearly polarized beam. MODIS signal function having two-cycles per 360 degrees prism rotation signal function was expected. However, some spectral bands had a distinct four-cycle anomalous signal. The expected two-cycle function was present in all regions with the four-cycle anomaly being limited to the NIR region. Fourier analysis was very useful tooling determining the cause of the anomaly. A simplified polarization model of the PSA and MODIS was generated using Mueller matrices-Stokes vector formalism. Parametric modeling illustrated that this anomaly could be produced by energy having multiple passes between PSA Ahrens prism and the MODIS focal plane filters. Furthermore, the model gave NIR four-cycle magnitudes that were consistent with observations. The IVS and SWIR optical trans had birefringent elements that served to scramble the multiple pass anomaly. The model validity was demonstrated with an experimental setup that had partial aperture illumination which eliminated the possibility of multiple passes. The four-cycle response was eliminated while producing the same two-cycle polarization response. Data will be shown to illustrate the four-cycle phenomenon.

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 images for the 2000 epoch. As surface reflectance likely will be a standard product for future Landsat missions, the approach developed in this study can be adapted as an operational quality assessment system for those missions.

Production and Distribution of NASA MODIS Remote Sensing Products

NASA Technical Reports Server (NTRS)

Wolfe, Robert

2007-01-01

The two Moderate Resolution Imaging Spectroradiometer (MODIS) instruments on-board NASA's Earth Observing System (EOS) Terra and Aqua satellites make key measurements for understanding the Earth's terrestrial ecosystems. Global time-series of terrestrial geophysical parameters have been produced from MODIS/Terra for over 7 years and for MODIS/Aqua 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 MODIS 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 MODIS 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 MODIS, 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 processing the lower level (Level 1) products and the higher level discipline specific Land and Atmosphere products in the MODIS Science Investigator Lead Processing System (SIPS), the MODIS Adaptive Processing System (MODAPS), and archive and distribution of the Land products to the user community by two of NASA s EOS Distributed Active Archive Centers (DAACs). Recently, a part of MODAPS, the Level 1 and Atmosphere Archive and Distribution System (LAADS), took over the role of archiving and distributing the Level 1 and Atmosphere products to the user community.

MODIS: Moderate-resolution imaging spectrometer. Earth observing system, volume 2B

NASA Technical Reports Server (NTRS)

1986-01-01

The Moderate-Resolution Imaging Spectrometer (MODIS), as presently conceived, is a system of two imaging spectroradiometer components designed for the widest possible applicability to research tasks that require long-term (5 to 10 years), low-resolution (52 channels between 0.4 and 12.0 micrometers) data sets. The system described is preliminary and subject to scientific and technological review and modification, and it is anticipated that both will occur prior to selection of a final system configuration; however, the basic concept outlined is likely to remain unchanged.

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.

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-launch calibration and characterization are also provided.

Achieving sub-pixel geolocation accuracy in support of MODIS land science

USGS Publications Warehouse

Wolfe, R.E.; Nishihama, M.; Fleig, A.J.; Kuyper, J.A.; Roy, David P.; Storey, James C.; Patt, F.S.

2002-01-01

The Moderate Resolution Imaging Spectroradiometer (MODIS) was launched in December 1999 on the polar orbiting Terra spacecraft and since February 2000 has been acquiring daily global data in 36 spectral bands—29 with 1 km, five with 500 m, and two with 250 m nadir pixel dimensions. The Terra satellite has on-board exterior orientation (position and attitude) measurement systems designed to enable geolocation of MODIS data to approximately 150 m (1σ) at nadir. A global network of ground control points is being used to determine biases and trends in the sensor orientation. Biases have been removed by updating models of the spacecraft and instrument orientation in the MODIS geolocation software several times since launch and have improved the MODIS geolocation to approximately 50 m (1σ) at nadir. This paper overviews the geolocation approach, summarizes the first year of geolocation analysis, and overviews future work. The approach allows an operational characterization of the MODIS geolocation errors and enables individual MODIS observations to be geolocated to the sub-pixel accuracies required for terrestrial global change applications.

Space environment's effect on MODIS calibration

NASA Astrophysics Data System (ADS)

Dodd, J. L.; Wenny, B. N.; Chiang, K.; Xiong, X.

2010-09-01

The MODerate resolution Imaging Spectroradiometer flies on board the Earth Observing System (EOS) satellites Terra and Aqua 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 Aqua was launched on May 4, 2002. As the MODIS instruments on board these satellites continue to operate beyond the design lifetime of six years, the cumulative effect of the space environment on MODIS 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 MODIS. 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 MODIS and the spacecraft, either directly or indirectly, possibly resulting in data loss. Efforts from the Terra and Aqua Flight Operations Teams (FOT), the MODIS Instrument Operations Team (IOT), and the MODIS Characterization Support Team (MCST) prevent or minimize external impact on the TOA calibrated data. This paper discusses specific effects of the space environment on MODIS and how they are minimized.

New Multispectral Cloud Retrievals from MODIS

NASA Technical Reports Server (NTRS)

Platnick, Steven; Tsay, Si-Chee; Ackerman, Steven A.; Gray, Mark A.; Moody, Eric G.; Li, Jason Y.; Arnold, G. T.; King, Michael D. (Technical Monitor)

2000-01-01

The Moderate Resolution Imaging Spectroradiometer (MODIS) was developed by NASA and launched onboard the Terra spacecraft on December 18, 1999. It achieved its final orbit and began Earth observations on February 24, 2000. MODIS scans a swath width sufficient to provide nearly complete global coverage every two days from a polar-orbiting, sun-synchronous, platform at an altitude of 705 km, and provides images in 36 spectral bands between 0.415 and 14.235 micrometers 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 I 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 cloud drops and ice crystals. 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.

New Multispectral Cloud Retrievals from MODIS

NASA Technical Reports Server (NTRS)

King, Michael D.; Platnick, Steven; Tsay, Si-Chee; Ackerman, Steven A.; Menzel, W. Paul; Gray, Mark A.; Moody, Eric G.; Li, Jason Y.; Arnold, G. Thomas

2001-01-01

The Moderate Resolution Imaging Spectroradiometer (MODIS) was developed by NASA and launched onboard the Terra spacecraft on December 18, 1999. It achieved its final orbit and began Earth observations on February 24, 2000. MODIS scans a swath width sufficient to provide nearly complete global coverage every two days from a polar-orbiting, sun- synchronous, platform at an altitude of 705 km, and provides images in 36 spectral bands between 0.415 and 14.235 microns with spatial resolutions of 250 m (two bands), 500 m (five 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.

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

NASA Technical Reports Server (NTRS)

Wu, Aisheng; Xiong, Xiaoxiong; Angal, A.; Barnes, W.

2011-01-01

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

Satellite-derived potential evapotranspiration for distributed hydrologic runoff modeling

NASA Astrophysics Data System (ADS)

Spies, R. R.; Franz, K. J.; Bowman, A.; Hogue, T. S.; Kim, J.

2012-12-01

Distributed models have the ability of incorporating spatially variable data, especially high resolution forcing inputs such as precipitation, temperature and evapotranspiration in hydrologic modeling. Use of distributed hydrologic models for operational streamflow prediction has been partially hindered by a lack of readily available, spatially explicit input observations. Potential evapotranspiration (PET), for example, is currently accounted for through PET input grids that are based on monthly climatological values. The goal of this study is to assess the use of satellite-based PET estimates that represent the temporal and spatial variability, as input to the National Weather Service (NWS) Hydrology Laboratory Research Distributed Hydrologic Model (HL-RDHM). Daily PET grids are generated for six watersheds in the upper Mississippi River basin using a method that applies only MODIS satellite-based observations and the Priestly Taylor formula (MODIS-PET). The use of MODIS-PET grids will be tested against the use of the current climatological PET grids for simulating basin discharge. Gridded surface temperature forcing data are derived by applying the inverse distance weighting spatial prediction method to point-based station observations from the Automated Surface Observing System (ASOS) and Automated Weather Observing System (AWOS). Precipitation data are obtained from the Climate Prediction Center's (CPC) Climatology-Calibrated Precipitation Analysis (CCPA). A-priori gridded parameters for the Sacramento Soil Moisture Accounting Model (SAC-SMA), Snow-17 model, and routing model are initially obtained from the Office of Hydrologic Development and further calibrated using an automated approach. The potential of the MODIS-PET to be used in an operational distributed modeling system will be assessed with the long-term goal of promoting research to operations transfers and advancing the science of hydrologic forecasting.

An approach for the long-term 30-m land surface snow-free albedo retrieval from historic Landsat surface reflectance and MODIS-based a priori anisotropy knowledge

USDA-ARS?s Scientific Manuscript database

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 MODIS, VIIRS, and other coarse-reso...

Comparison between MODIS-derived day and night cloud cover and surface observations over the North China Plain

NASA Astrophysics Data System (ADS)

Zhang, Xiao; Tan, Saichun; Shi, Guangyu

2018-02-01

Satellite and human visual observation are two of the most important observation approaches for cloud cover. In this study, the total cloud cover (TCC) observed by MODIS onboard the Terra and Aqua satellites was compared with Synop meteorological station observations over the North China Plain and its surrounding regions for 11 years during daytime and 7 years during nighttime. The Synop data were recorded eight times a day at 3-h intervals. Linear interpolation was used to interpolate the Synop data to the MODIS overpass time in order to reduce the temporal deviation between the satellite and Synop observations. Results showed that MODIS-derived TCC had good consistency with the Synop observations; the correlation coefficients ranged from 0.56 in winter to 0.73 in summer for Terra MODIS, and from 0.55 in winter to 0.71 in summer for Aqua MODIS. However, they also had certain differences. On average, the MODIS-derived TCC was 15.16% higher than the Synop data, and this value was higher at nighttime (15.58%-16.64%) than daytime (12.74%-14.14%). The deviation between the MODIS and Synop TCC had large seasonal variation, being largest in winter (29.53%-31.07%) and smallest in summer (4.46%-6.07%). Analysis indicated that cloud with low cloud-top height and small cloud optical thickness was more likely to cause observation bias. Besides, an increase in the satellite view zenith angle, aerosol optical depth, or snow cover could lead to positively biased MODIS results, and this affect differed among different cloud types.

MODIS Collection 6 Data at the National Snow and Ice Data Center (NSIDC)

NASA Astrophysics Data System (ADS)

Fowler, D. K.; Steiker, A. E.; Johnston, T.; Haran, T. M.; Fowler, C.; Wyatt, P.

2015-12-01

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 (MODIS) instruments on the NASA Earth Observing System (EOS) Aqua and Terra satellites. Collection 6 represents the next revision to NSIDC's MODIS archive, mainly affecting the snow-cover products. Collection 6 specifically addresses the needs of the MODIS 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 MODIS 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 MODIS 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 MODIS 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 MODIS 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 subsetting, reformatting, and re-projection of the data.

Improvement in the cloud mask for Terra MODIS mitigated by electronic crosstalk correction in the 6.7 μm and 8.5 μm channels

NASA Astrophysics Data System (ADS)

Sun, Junqiang; Madhavan, S.; Wang, M.

2016-09-01

MODerate resolution Imaging Spectroradiometer (MODIS), a remarkable 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 Aqua (A) platforms which tracks the Earth in the morning and afternoon orbits. T-MODIS has continued to operate over 15 years easily surpassing the 6 year design life time on orbit. Of the several science products derived from MODIS, one of the primary derivatives is the MODIS Cloud Mask (MOD035). The cloud mask algorithm incorporates several of the MODIS channels in both reflective and thermal infrared wavelengths to identify cloud pixels from clear sky. Two of the thermal infrared channels used in detecting clouds are the 6.7 μm and 8.5 μm. Based on a difference threshold with the 11 μm channel, the 6.7 μm channel helps in identifying thick high clouds while the 8.5 μm channel being useful for identifying thin clouds. Starting 2010, it had been observed in the cloud mask products that several pixels have been misclassified due to the change in the thermal band radiometry. The long-term radiometric changes in these thermal channels have been attributed to the electronic crosstalk contamination. In this paper, the improvement in cloud detection using the 6.7 μm and 8.5 μm channels are demonstrated using the electronic crosstalk correction. The electronic crosstalk phenomena analysis and characterization were developed using the regular moon observation of MODIS and reported in several works. The results presented in this paper should significantly help in improving the MOD035 product, maintaining the long term dataset from T-MODIS which is important for global change monitoring.

Crosstalk effect and its mitigation in Aqua MODIS middle wave infrared bands

NASA Astrophysics Data System (ADS)

Sun, Junqiang; Madhavan, Sriharsha; Wang, Menghua

2017-09-01

The MODerate-resolution Imaging Spectroradiometer (MODIS) is one of the primary instruments in the National Aeronautics and Space Administration (NASA) Earth Observing System (EOS). The first MODIS instrument was launched in December 1999 on-board the Terra spacecraft. A follow on MODIS was launched on an afternoon orbit in 2002 and is aboard the Aqua spacecraft. Both MODIS instruments are very akin, has 36 bands, among which bands 20 to 25 are Middle Wave Infrared (MWIR) bands covering a wavelength range from approximately 3.750 μm to 4.515 μm. It was found that there was severe contamination in these bands early in mission but the effect has not been characterized and mitigated at the time. The crosstalk effect induces strong striping in the Earth View (EV) images and causes significant retrieval errors in the EV Brightness Temperature (BT) in these bands. An algorithm using a linear approximation derived from on-orbit lunar observations has been developed to correct the crosstalk effect and successfully applied to mitigate the effect in both Terra and Aqua MODIS Long Wave Infrared (LWIR) Photovoltaic (PV) bands. In this paper, the crosstalk effect in the Aqua MWIR bands is investigated and characterized by deriving the crosstalk coefficients using the scheduled Aqua MODIS lunar observations for the MWIR bands. It is shown that there are strong crosstalk contaminations among the five MWIR bands and they also have significant crosstalk contaminations from Short Wave Infrared (SWIR) bands. The crosstalk correction algorithm previously developed is applied to correct the crosstalk effect in these bands. It is demonstrated that the crosstalk correction successfully reduces the striping in the EV images and improves the accuracy of the EV BT in the five bands as was done similarly for LWIR PV bands. The crosstalk correction algorithm should thus be applied to improve both the image quality and radiometric accuracy of the Aqua MODIS MWIR bands Level 1B (L1B) products.

A browser-based 3D Visualization Tool designed for comparing CERES/CALIOP/CloudSAT level-2 data sets.

NASA Astrophysics Data System (ADS)

Chu, C.; Sun-Mack, S.; Chen, Y.; Heckert, E.; Doelling, D. R.

2017-12-01

In Langley NASA, Clouds and the Earth's Radiant Energy System (CERES) and Moderate Resolution Imaging Spectroradiometer (MODIS) are merged with Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) on the Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO) and CloudSat Cloud Profiling Radar (CPR). The CERES merged product (C3M) matches up to three CALIPSO footprints with each MODIS pixel along its ground track. It then assigns the nearest CloudSat footprint to each of those MODIS pixels. The cloud properties from MODIS, retrieved using the CERES algorithms, are included in C3M with the matched CALIPSO and CloudSat products along with radiances from 18 MODIS channels. The dataset is used to validate the CERES retrieved MODIS cloud properties and the computed TOA and surface flux difference using MODIS or CALIOP/CloudSAT retrieved clouds. This information is then used to tune the computed fluxes to match the CERES observed TOA flux. A visualization tool will be invaluable to determine the cause of these large cloud and flux differences in order to improve the methodology. This effort is part of larger effort to allow users to order the CERES C3M product sub-setted by time and parameter as well as the previously mentioned visualization capabilities. This presentation will show a new graphical 3D-interface, 3D-CERESVis, that allows users to view both passive remote sensing satellites (MODIS and CERES) and active satellites (CALIPSO and CloudSat), such that the detailed vertical structures of cloud properties from CALIPSO and CloudSat are displayed side by side with horizontally retrieved cloud properties from MODIS and CERES. Similarly, the CERES computed profile fluxes whether using MODIS or CALIPSO and CloudSat clouds can also be compared. 3D-CERESVis is a browser-based visualization tool that makes uses of techniques such as multiple synchronized cursors, COLLADA format data and Cesium.

Land Surface Model Biases and their Impacts on the Assimilation of Snow-related Observations

NASA Astrophysics Data System (ADS)

Arsenault, K. R.; Kumar, S.; Hunter, S. M.; Aman, R.; Houser, P. R.; Toll, D.; Engman, T.; Nigro, J.

2007-12-01

Some recent snow modeling studies have employed a wide range of assimilation methods to incorporate snow cover or other snow-related observations into different hydrological or land surface models. These methods often include taking both model and observation biases into account throughout the model integration. This study focuses more on diagnosing the model biases and presenting their subsequent impacts on assimilating snow observations and modeled snowmelt processes. In this study, the land surface model, the Community Land Model (CLM), is used within the Land Information System (LIS) modeling framework to show how such biases impact the assimilation of MODIS snow cover observations. Alternative in-situ and satellite-based observations are used to help guide the CLM LSM in better predicting snowpack conditions and more realistic timing of snowmelt for a western US mountainous region. Also, MODIS snow cover observation biases will be discussed, and validation results will be provided. The issues faced with inserting or assimilating MODIS snow cover at moderate spatial resolutions (like 1km or less) will be addressed, and the impacts on CLM will be presented.

Improving the MODIS Global Snow-Mapping Algorithm

NASA Technical Reports Server (NTRS)

Klein, Andrew G.; Hall, Dorothy K.; Riggs, George A.

1997-01-01

An algorithm (Snowmap) is under development to produce global snow maps at 500 meter resolution on a daily basis using data from the NASA MODIS instrument. MODIS, the Moderate Resolution Imaging Spectroradiometer, will be launched as part of the first Earth Observing System (EOS) platform in 1998. Snowmap is a fully automated, computationally frugal algorithm that will be ready to implement at launch. Forests represent a major limitation to the global mapping of snow cover as a forest canopy both obscures and shadows the snow underneath. Landsat Thematic Mapper (TM) and MODIS Airborne Simulator (MAS) data are used to investigate the changes in reflectance that occur as a forest stand becomes snow covered and to propose changes to the Snowmap algorithm that will improve snow classification accuracy forested areas.

MODIS. Volume 2: MODIS level 1 geolocation, characterization and calibration algorithm theoretical basis document, version 1

NASA Technical Reports Server (NTRS)

Barker, John L.; Harnden, Joann M. K.; Montgomery, Harry; Anuta, Paul; Kvaran, Geir; Knight, ED; Bryant, Tom; Mckay, AL; Smid, Jon; Knowles, Dan, Jr.

1994-01-01

The EOS Moderate Resolution Imaging Spectrometer (MODIS) 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 MODIS 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 MODIS 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 MODIS 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 reflectance 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.

Global monitoring of atmospheric properties by the EOS MODIS

NASA Technical Reports Server (NTRS)

King, Michael D.

1993-01-01

The Moderate Resolution Imaging Spectroradiometer (MODIS) 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 MODIS 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 MODIS 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 reflectances. 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 MODIS 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 MODIS. The secondary objective is to obtain an enhanced knowledge of surface angular and spectral properties that can be inferred from airborne directional radiance measurements.

Scaling estimates of vegetation structure in Amazonian tropical forests using multi-angle MODIS observations

PubMed Central

de Moura, Yhasmin Mendes; Hilker, Thomas; Goncalves, Fabio Guimarães; Galvão, Lênio Soares; dos Santos, João Roberto; Lyapustin, Alexei; Maeda, Eduardo Eiji; de Jesus Silva, Camila Valéria

2018-01-01

Detailed knowledge of vegetation structure is required for accurate modelling of terrestrial ecosystems, but direct measurements of the three dimensional distribution of canopy elements, for instance from LiDAR, are not widely available. We investigate the potential for modelling vegetation roughness, a key parameter for climatological models, from directional scattering of visible and near-infrared (NIR) reflectance acquired from NASA’s Moderate Resolution Imaging Spectroradiometer (MODIS). We compare our estimates across different tropical forest types to independent measures obtained from: (1) airborne laser scanning (ALS), (2) spaceborne Geoscience Laser Altimeter System (GLAS)/ICESat, and (3) the spaceborne SeaWinds/QSCAT. Our results showed linear correlation between MODIS-derived anisotropy to ALS-derived entropy (r2= 0.54, RMSE=0.11), even in high biomass regions. Significant relationships were also obtained between MODIS-derived anisotropy and GLAS-derived entropy (0.52≤ r2≤ 0.61; p<0.05), with similar slopes and offsets found throughout the season, and RMSE between 0.26 and 0.30 (units of entropy). The relationships between the MODIS-derived anisotropy and backscattering measurements (σ0) from SeaWinds/QuikSCAT presented an r2 of 0.59 and a RMSE of 0.11. We conclude that multi-angular MODIS observations are suitable to extrapolate measures of canopy entropy across different forest types, providing additional estimates of vegetation structure in the Amazon. PMID:29618964

Improvement in the Characterization of MODIS Subframe Difference

NASA Technical Reports Server (NTRS)

Li, Yonghong; Angal, Amit; Chen, Na; Geng, Xu; Link, Daniel; Wang, Zhipeng; Wu, Aisheng; Xiong, Xiaoxiong

2016-01-01

MODIS is a key instrument of NASA's Earth Observing System. It has successfully operated for 16+ years on the Terra satellite and 14+ years on the Aqua satellite, respectively. MODIS has 36 spectral bands at three different nadir spatial resolutions, 250m (bands 1-2), 500m (bands 3-7), and 1km (bands 8-36). MODIS subframe measurement is designed for bands 1-7 to match their spatial resolution in the scan direction to that of the track direction. Within each 1 km frame, the MODIS 250 m resolution bands sample four subframes and the 500 m resolution bands sample two subframes. The detector gains are calibrated at a subframe level. Due to calibration differences between subframes, noticeable subframe striping is observed in the Level 1B (L1B) products, which exhibit a predominant radiance-level dependence. This paper presents results of subframe differences from various onboard and earth-view data sources (e.g. solar diffuser, electronic calibration, spectro-radiometric calibration assembly, Earth view, etc.). A subframe bias correction algorithm is proposed to minimize the subframe striping in MODIS L1B image. The algorithm has been tested using sample L1B images and the vertical striping at lower radiance value is mitigated after applying the corrections. The subframe bias correction approach will be considered for implementation in future versions of the calibration algorithm.

MODIS Observations of Smoke and Fires

NASA Technical Reports Server (NTRS)

Kaufman, Yoram; Ichoku, Charles; Remer, Lorraine; Lau, William K. M. (Technical Monitor)

2002-01-01

The MODIS (Moderate Resolution Imaging Spectroradiometer) instruments collect daily measurements of our planet since early 2000 from the Terra spaceborne polar platform. It has unique channels to observe smoke over land and ocean and to observe fires. Using unsaturated channels at 3.9 micron MODIS detects the fires and estimates the fire radiative energy. Using solar channels in the visible (0.47 and 0.66 micron) and in the mid IR (2.1 micron) MODIS measures the smoke optical thickness distribution and evolution over the land. Seven Channels in the solar spectrum are used to detect the smoke properties and distribution over the oceans. Data from the Aerosol Robotic Network, are used to validate the MODIS observations. The MODIS aerosol data presented in a movie form is used to observe the generation of smoke plumes and their dispersion around the globe. For example a key conclusion is that smoke in particular from Southern Africa can pollute significantly the 'pristine' Southern Hemisphere zonal range of 45'S-60'S, and the Northern Pacific.

Can MODIS Data Calibrate and Validate Coastal Sediment Transport Models? Rapid Prototyping Using 250 m Data and the ECOMSED Model for Lake Pontchartrain, LA USA

NASA Technical Reports Server (NTRS)

Miller, Richard L.; Georgiou, Ioannis; Glorioso, Mark V.; McCorquodale, J. Alex; Crowder, Keely

2006-01-01

Field measurements from small boats and sparse arrays of instrumented buoys often do not provide sufficient data to capture the dynamic nature of biogeophysical parameters in may coastal aquatic environments. Several investigators have shown the MODIS 250 m images can provide daily synoptic views of suspended sediment concentration in coastal waters to determine sediment transport and fate. However, the use of MODIS for coastal environments can be limited due to a lack of cloud-free images. Sediment transport models are not constrained by sky conditions but often suffer from a lack of in situ observations for model calibration or validation. We demonstrate here the utility of MODIS 250 m to calibrate (set model parameters), validate output, and set or reset initial conditions of a hydrodynamic and sediment transport model (ECOMSED) developed for Lake Pontchartrain, LA USA. We present our approach in the context of how to quickly assess of 'prototype' an application of NASA data to support environmental managers and decision makers. The combination of daily MODIS imagery and model simulations offer a more robust monitoring and prediction system of suspended sediments than available from either system alone.

On-Orbit Performance and Calibration Improvements For the Reflective Solar Bands of Terra and Aqua MODIS

NASA Technical Reports Server (NTRS)

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

2016-01-01

Moderate Resolution Imaging Spectroradiometer (MODIS) is the keystone instrument for NASAs 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 micrometers to 2.2 micrometers, 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 deg. 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 detail the recent calibration improvements implemented in the MODIS L1B C6.

Theoretical Accuracy of Global Snow-Cover Mapping Using Satellite Data in the Earth Observing System (EOS) Era

NASA Technical Reports Server (NTRS)

Hall, D. K.; Foster, J. L.; Salomonson, V. V.; Klein, A. G.; Chien, J. Y. L.

1998-01-01

Following the launch of the Earth Observing System first morning (EOS-AM1) satellite, daily, global snow-cover mapping will be performed automatically at a spatial resolution of 500 m, cloud-cover permitting, using Moderate Resolution Imaging Spectroradiometer (MODIS) data. A technique to calculate theoretical accuracy of the MODIS-derived snow maps is presented. Field studies demonstrate that under cloud-free conditions when snow cover is complete, snow-mapping errors are small (less than 1%) in all land covers studied except forests where errors are greater and more variable. The theoretical accuracy of MODIS snow-cover maps is largely determined by percent forest cover north of the snowline. Using the 17-class International Geosphere-Biosphere Program (IGBP) land-cover maps of North America and Eurasia, the Northern Hemisphere is classified into seven land-cover classes and water. Snow-mapping errors estimated for each of the seven land-cover classes are extrapolated to the entire Northern Hemisphere for areas north of the average continental snowline for each month. Average monthly errors for the Northern Hemisphere are expected to range from 5 - 10%, and the theoretical accuracy of the future global snow-cover maps is 92% or higher. Error estimates will be refined after the first full year that MODIS data are available.

Earth Observing System (EOS) Moderate Resolution Imaging Spectroradiometer (MODIS) Global Snow-Cover Maps

NASA Technical Reports Server (NTRS)

Hall, Dorothy K.; Riggs, George A.; Salomonson, Vincent V.; Scharfen, Greg R.

2000-01-01

Following the 1999 launch of the Earth Observing System (EOS) Moderate Resolution Imaging Spectroradiometer (MODIS), the capability exists to produce global snow-cover maps on a daily basis at 500-m resolution. Eight-day composite snow-cover maps will also be available. MODIS snow-cover products are produced at Goddard Space Flight Center and archived and distributed by the National Snow and Ice Data Center (NSIDC) in Boulder, Colorado. The products are available in both orbital and gridded formats. An online search and order tool and user-services staff will be available at NSIDC to assist users with the snow products. The snow maps are available at a spatial resolution of 500 m, and 1/4 degree x 1/4 degree spatial resolution, and provide information on sub-pixel (fractional) snow cover. Pre-launch validation work has shown that the MODIS snow-mapping algorithms perform best under conditions of continuous snow cover in low vegetation areas, but can also map snow cover in dense forests. Post-launch validation activities will be performed using field and aircraft measurements from a February 2000 validation mission, as well as from existing satellite-derived snow-cover maps from NOAA and Landsat-7 Enhanced Thematic Mapper Plus (ETM+).

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

NASA Technical Reports Server (NTRS)

Ackerman, Steven A.; Hemler, Richard S.; Hofman, Robert J. Patrick; Pincus, Robert; Platnick, Steven

2011-01-01

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

The GEOS-5 Neural Network Retrieval for AOD

NASA Astrophysics Data System (ADS)

Castellanos, P.; da Silva, A. M., Jr.

2017-12-01

One of the difficulties in data assimilation is the need for multi-sensor data merging that can account for temporal and spatial biases between satellite sensors. In the Goddard Earth Observing System Model Version 5 (GEOS-5) aerosol data assimilation system, a neural network retrieval (NNR) is used as a mapping between satellite observed top of the atmosphere (TOA) reflectance and AOD, which is the target variable that is assimilated in the model. By training observations of TOA reflectance from multiple sensors to map to a common AOD dataset (in this case AOD observed by the ground based Aerosol Robotic Network, AERONET), we are able to create a global, homogenous, satellite data record of AOD from MODIS observations on board the Terra and Aqua satellites. In this talk, I will present the implementation of and recent updates to the GEOS-5 NNR for MODIS collection 6 data.

The GEOS-5 Neural Network Retrieval (NNR) for AOD

NASA Technical Reports Server (NTRS)

Castellanos, Patricia; Da Silva, Arlindo

2017-01-01

One of the difficulties in data assimilation is the need for multi-sensor data merging that can account for temporal and spatial biases between satellite sensors. In the Goddard Earth Observing System Model Version 5 (GEOS-5) aerosol data assimilation system, a neural network retrieval (NNR) is used as a mapping between satellite observed top of the atmosphere (TOA) reflectance and AOD, which is the target variable that is assimilated in the model. By training observations of TOA reflectance from multiple sensors to map to a common AOD dataset (in this case AOD observed by the ground based Aerosol Robotic Network, AERONET), we are able to create a global, homogenous, satellite data record of AOD from MODIS observations on board the Terra and Aqua satellites. In this talk, I will present the implementation of and recent updates to the GEOS-5 NNR for MODIS collection 6 data.

Evaluation and sensitivity testing of a coupled Landsat-MODIS downscaling method for land surface temperature and vegetation indices in semi-arid regions

NASA Astrophysics Data System (ADS)

Kim, Jongyoun; Hogue, Terri S.

2012-01-01

The current study investigates a method to provide land surface parameters [i.e., land surface temperature (LST) and normalized difference vegetation index (NDVI)] at a high spatial (˜30 and 60 m) and temporal (daily and 8-day) resolution by combining advantages from Landsat and moderate-resolution imaging spectroradiometer (MODIS) satellites. We adopt a previously developed subtraction method that merges the spatial detail of higher-resolution imagery (Landsat) with the temporal change observed in coarser or moderate-resolution imagery (MODIS). Applying the temporal difference between MODIS images observed at two different dates to a higher-resolution Landsat image allows prediction of a combined or fused image (Landsat+MODIS) at a future date. Evaluation of the resultant merged products is undertaken within the Southeastern Arizona region where data is available from a range of flux tower sites. The Landsat+MODIS fused products capture the raw Landsat values and also reflect the MODIS temporal variation. The predicted Landsat+MODIS LST improves mean absolute error around 5°C at the more heterogeneous sites compared to the original satellite products. The fused Landsat+MODIS NDVI product also shows good correlation to ground-based data and is relatively consistent except during the acute (monsoon) growing season. The sensitivity of the fused product relative to temporal gaps in Landsat data appears to be more affected by uncertainty associated with regional precipitation and green-up, than the length of the gap associated with Landsat viewing, suggesting the potential to use a minimal number of original Landsat images during relatively stable land surface and climate conditions. Our extensive validation yields insight on the ability of the proposed method to integrate multiscale platforms and the potential for reducing costs associated with high-resolution satellite systems (e.g., SPOT, QuickBird, IKONOS).

Calibration Challenges and Improvements for Terra and Aqua MODIS Level-1B Data Product Qualit

NASA Astrophysics Data System (ADS)

Xiong, X.; Angal, A.; Chen, H.; Geng, X.; Li, Y.; Link, D.; Salomonson, V.; Twedt, K.; Wang, Z.; Wilson, T.; Wu, A.

2017-12-01

Terra and Aqua MODIS instruments launched in 1999 and 2002, respectively, have provided the remote sensing community and users worldwide a series of high quality long-term data records. They have enabled a broad range of scientific studies of the Earth's system and changes in its key geophysical and environmental parameters. To date, both MODIS instruments continue to operate nominally with all on-board calibrators (OBC) functioning properly. MODIS reflective solar bands (RSB) are currently calibrated by a solar diffuser (SD) and solar diffuser stability monitor (SDSM) system, coupled with regularly scheduled lunar observations and trending results from selected ground reference targets. The thermal emissive bands (TEB) calibration is performed using an on-board blackbody (BB) on a scan-by-scan basis. The sensor's spectral and spatial characteristics are periodically tracked by the on-board spectroradiometric calibration assembly (SRCA). On-orbit changes in sensor responses or performance characteristics, often in non-deterministic ways, underscore the need for dedicated calibration efforts to be made over the course of the sensor's entire mission. For MODIS instruments, this task has been undertaken by the MODIS Characterization Support Team (MCST). In this presentation, we provide an overview of MODIS instrument operation and calibration activities with a focus on recent challenging issues. We describe the efforts made and methodologies developed to address various challenging issues, including on-orbit characterization of sensor response versus scan angle (RVS) and polarization sensitives in the reflective solar spectral region, and electronic crosstalk impact on sensor calibration. Also discussed are the latest improvements made into the MODIS Level-1B data products as well as lessons that could benefit other instruments (e.g. VIIRS) for their on-orbit calibration and characterization.

Terrestrial remote sensing science and algorithms planned for EOS/MODIS

USGS Publications Warehouse

Running, S. W.; Justice, C.O.; Salomonson, V.V.; Hall, D.; Barker, J.; Kaufmann, Y. J.; Strahler, Alan H.; Huete, A.R.; Muller, Jan-Peter; Vanderbilt, V.; Wan, Z.; Teillet, P.; Carneggie, David M. Geological Survey (U.S.) Ohlen

1994-01-01

The Moderate Resolution Imaging Spectroradiometer (MODIS) will be the primary daily global monitoring sensor on the NASA Earth Observing System (EOS) satellites, scheduled for launch on the EOS-AM platform in June 1998 and the EOS-PM platform in December 2000. MODIS is a 36 channel radiometer covering 0·415-14·235 μm wavelengths, with spatial resolution from 250 m to 1 km at nadir. MODIS will be the primary EOS sensor for providing data on terrestrial biospheric dynamics and process activity. This paper presents the suite of global land products currently planned for EOSDIS implementation, to be developed by the authors of this paper, the MODIS land team (MODLAND). These include spectral albedo, land cover, spectral vegetation indices, snow and ice cover, surface temperature and fire, and a number of biophysical variables that will allow computation of global carbon cycles, hydrologic balances and biogeochemistry of critical greenhouse gases. Additionally, the regular global coverage of these variables will allow accurate surface change detection, a fundamental determinant of global change.

Integrating in-situ, Landsat, and MODIS data for mapping in Southern African savannas: experiences of LCCS-based land-cover mapping in the Kalahari in Namibia.

PubMed

Hüttich, Christian; Herold, Martin; Strohbach, Ben J; Dech, Stefan

2011-05-01

Integrated ecosystem assessment initiatives are important steps towards a global biodiversity observing system. Reliable earth observation data are key information for tracking biodiversity change on various scales. Regarding the establishment of standardized environmental observation systems, a key question is: What can be observed on each scale and how can land cover information be transferred? In this study, a land cover map from a dry semi-arid savanna ecosystem in Namibia was obtained based on the UN LCCS, in-situ data, and MODIS and Landsat satellite imagery. In situ botanical relevé samples were used as baseline data for the definition of a standardized LCCS legend. A standard LCCS code for savanna vegetation types is introduced. An object-oriented segmentation of Landsat imagery was used as intermediate stage for downscaling in-situ training data on a coarse MODIS resolution. MODIS time series metrics of the growing season 2004/2005 were used to classify Kalahari vegetation types using a tree-based ensemble classifier (Random Forest). The prevailing Kalahari vegetation types based on LCCS was open broadleaved deciduous shrubland with an herbaceous layer which differs from the class assignments of the global and regional land-cover maps. The separability analysis based on Bhattacharya distance measurements applied on two LCCS levels indicated a relationship of spectral mapping dependencies of annual MODIS time series features due to the thematic detail of the classification scheme. The analysis of LCCS classifiers showed an increased significance of life-form composition and soil conditions to the mapping accuracy. An overall accuracy of 92.48% was achieved. Woody plant associations proved to be most stable due to small omission and commission errors. The case study comprised a first suitability assessment of the LCCS classifier approach for a southern African savanna ecosystem.

Promise and Capability of NASA's Earth Observing System to Monitor Human-Induced Climate Variations

NASA Technical Reports Server (NTRS)

King, M. D.

2003-01-01

The Earth Observing System (EOS) is a space-based observing system comprised of a series of satellite sensors by which scientists can monitor the Earth, a Data and Information System (EOSDIS) enabling researchers worldwide to access the satellite data, and an interdisciplinary science research program to interpret the satellite data. 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. This sensor and multi-platform observing system is especially well suited to observing detailed interdisciplinary components of the Earth s surface and atmosphere in and around urban environments, including aerosol optical properties, cloud optical and microphysical properties of both liquid water and ice clouds, land surface reflectance, fire occurrence, and many other properties that influence the urban environment and are influenced by them. In this presentation I will summarize the current capabilities of MODIS and other EOS sensors currently in orbit to study human-induced climate variations.

Progress in Understanding the Impacts of 3-D Cloud Structure on MODIS Cloud Property Retrievals for Marine Boundary Layer Clouds

NASA Technical Reports Server (NTRS)

Zhang, Zhibo; Werner, Frank; Miller, Daniel; Platnick, Steven; Ackerman, Andrew; DiGirolamo, Larry; Meyer, Kerry; Marshak, Alexander; Wind, Galina; Zhao, Guangyu

2016-01-01

Theory: A novel framework based on 2-D Tayler expansion for quantifying the uncertainty in MODIS retrievals caused by sub-pixel reflectance inhomogeneity. (Zhang et al. 2016). How cloud vertical structure influences MODIS LWP retrievals. (Miller et al. 2016). Observation: Analysis of failed MODIS 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).

Near Real{time Data Assimilation for the HYSPLIT Aerosol Dispersion Model

NASA Astrophysics Data System (ADS)

Kalpakis, K.; Yang, S.; Yesha, Y.

2010-12-01

Konstantinos Kalpakis, Shiming Yang, and Yaacov Yesha Department of Computer Science and Electrical Engineering University of Maryland Baltimore County 1000 Hilltop Circle, Baltimore, MD, U.S.A. {kalpakis, shiming1, yayeshag}@csee.umbc.edu ABSTRACT We are working on an IBM-funded project seeking to develop a prototype system for real-time plume dispersion and fire and smoke detection and monitoring. Our prototype system utilizes HYSPLIT and observation data from various sources. HYSPLIT is a model developed by NOAA's Air Resources Laboratory for forecasting aerosol trajectories, dispersion, and concentration from emission sources. It is used extensively by NOAA to routinely provide a number of data products. We develop a data assimilation system for assimilating observational data into the forecasting model in order to improve its forecasting accuracy. Our system is based on the Local Ensemble Transform Kalman Filter (LETKF) algorithm and it is computationally efficient. We evaluate our data assimilation system with real in-situ observational data, and find that our system improves upon HYSPLIT's forecast by reducing the normalized mean squared error and the bias. We are also experimenting with assimilating MODIS data with HYSPLIT model forecasts. To this end, we extrapolate ground concentrations from MODIS Aerosol Optical Depth (AOD) data. Our extrapolation approach relies on spatially localized linear regressions of aerosol concentrations from ground stations in the Air Quality System (AQS) network and MODIS AOD data. We expect that assimilating the extrapolated concentrations leads into further improvements of HYSPLIT forecasts. Furthermore, we are investigating using additional sources of in-situ and remotely sensed observations, such as GOES AOD 30-minute data, and UAV data from the Ikhana AMS fire missions. These sources provide higher spatial resolution and more frequent temporal coverage. Moreover, GOES and UAVs provide near-real time data which should be useful in improving HYSPLIT forecasts of smoke from wildfires. Currently, the Ikhana AMS fire missions team provides L1B data which are very useful in themselves, but no level 2 to the best of our knowledge. For our application, it would very useful to have an AOD data product for these datasets. A possible path for deriving AOD data the AMS sensor onboard UAVs would be to utilize the DRL code for deriving the MODIS AOD from MODIS L1B data, due to the sensor similarities. Developing such code would be very useful for wildfire smoke prediction applications. Our near real-time data assimilation system helps in bridging the gap between predictions and real-time observations, for more accurate and timely aerosol dispersion forecasts. Keywords: data assimilation, HYSPLIT, forecast model performance, real-time, ensemble Kalman filter, aerosol dispersion and concentration.

A Relationship Between Visible and Near-IR Global Spectral Reflectance based on DSCOVR/EPIC

NASA Astrophysics Data System (ADS)

Wen, G.; Marshak, A.; Song, W.; Knyazikhin, Y.

2017-12-01

The launch of Deep Space Climate Observatory (DSCOVR) to the Earth's first Lagrange point (L1) allows us to see a new perspective of the Earth. The Earth Polychromatic Imaging Camera (EPIC) on the DSCOVR measures the back scattered radiation of the entire sunlit side of the Earth at 10 narrow band wavelengths ranging from ultraviolet to visible and near-infrared. We analyzed EPIC global averaged reflectance data. We found that the global averaged visible reflectance has a unique non-linear relationship with near infrared (NIR) reflectance. This non-linear relationship was not observed by any other satellite observations due to a limited spatial and temporal coverage of either low earth orbit (LEO) or geostationary satellite. The non-linear relationship is associated with the changing in the coverages of ocean, cloud, land, and vegetation as the Earth rotates. We used Terra and Aqua MODIS daily global radiance data to simulate EPIC observations. Since MODIS samples the Earth in a limited swath (2330km cross track) at a specific local time (10:30 am for Terra, 1:30 pm for Aqua) with approximately 15 orbits per day, the global average reflectance at a given time may be approximated by averaging the reflectance in the MODIS nearest-time swaths in the sunlit hemisphere. We found that MODIS simulated global visible and NIR spectral reflectance captured the major feature of the EPIC observed non-linear relationship with some errors. The difference between the two is mainly due to the sampling limitation of polar satellite. This suggests that that EPIC observations can be used to reconstruct MODIS global average reflectance time series for studying Earth system change in the past decade.

Sea Ice Surface Temperature Product from the Moderate Resolution Imaging Spectroradiometer (MODIS)

NASA Technical Reports Server (NTRS)

Hall, Dorothy K.; Key, Jeffrey R.; Casey, Kimberly A.; Riggs, George A.; Cavalieri, Donald J.

2003-01-01

Global sea ice products are produced from the Earth Observing System (EOS) Moderate Resolution Imaging Spectroradiometer (MODIS) on board both the Terra and Aqua 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 MODIS 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 MODIS 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 MODIS in the presence of even very thin clouds or fog, however using both the Advanced Microwave Scanning Radiometer-EOS (AMSR-E) and the MODIS on the Aqua satellite, it may be possible to develop a relationship between MODIS-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 MODIS IST measurements.

MODIS Data from the GES DISC DAAC: Moderate-Resolution Imaging Spectroradiometer (MODIS)

NASA Technical Reports Server (NTRS)

2002-01-01

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 MODIS 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. MODIS 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). MODIS 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 MODIS Science Teams. MODIS/Terra Level 1, and all MODIS/Terra 11 micron SST products are announced as validated. At the time of this publication, the MODIS Data Support Team (MDST) is working with the Ocean Science Team toward announcing the validated status of the remainder of MODIS/Terra Ocean products. MODIS/Aqua Level 1 and cloud mask products are released with provisional maturity.

Scaling Estimates of Vegetation Structure in Amazonian Tropical Forests Using Multi-Angle MODIS Observations

NASA Technical Reports Server (NTRS)

Mendes De Moura, Yhasmin; Hilker, Thomas; Goncalves, Fabio Guimaraes; Galvao, Lenio Soares; Roberto dos Santos, Joao; Lyapustin, Alexei; Maeda, Eduardo Eiji; de Jesus Silva, Camila Valeria

2016-01-01

Detailed knowledge of vegetation structure is required for accurate modelling of terrestrial ecosystems, but direct measurements of the three dimensional distribution of canopy elements, for instance from LiDAR, are not widely available. We investigate the potential for modelling vegetation roughness, a key parameter for climatological models, from directional scattering of visible and near-infrared (NIR) reflectance acquired from NASA's Moderate Resolution Imaging Spectroradiometer (MODIS). We compare our estimates across different tropical forest types to independent measures obtained from: (1) airborne laser scanning (ALS), (2) spaceborne Geoscience Laser Altimeter System (GLAS)/ICESat, and (3) the spaceborne SeaWinds/QSCAT. Our results showed linear correlation between MODIS-derived anisotropy to ALS-derived entropy (r(exp 2)= 0.54, RMSE= 0.11), even in high biomass regions. Significant relationships were also obtained between MODIS-derived anisotropy and GLAS-derived entropy(0.52 less than or equal to r(exp 2) less than or equal to 0.61; p less than 0.05), with similar slopes and offsets found throughout the season, and RMSE between 0.26 and 0.30 (units of entropy). The relationships between the MODIS-derived anisotropy and backscattering measurements (sigma(sup 0)) from SeaWinds/QuikSCAT presented an r(exp 2) of 0.59 and a RMSE of 0.11. We conclude that multi-angular MODIS observations are suitable to extrapolate measures of canopy entropy across different forest types, providing additional estimates of vegetation structure in the Amazon.

Multilayer Cloud Detection with the MODIS Near-Infrared Water Vapor Absorption Band

NASA Technical Reports Server (NTRS)

Wind, Galina; Platnick, Steven; King, Michael D.; Hubanks, Paul A,; Pavolonis, Michael J.; Heidinger, Andrew K.; Yang, Ping; Baum, Bryan A.

2009-01-01

Data Collection 5 processing for the Moderate Resolution Imaging Spectroradiometer (MODIS) onboard the NASA Earth Observing System EOS Terra and Aqua 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 MODIS 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 MODIS multilayered cloud algorithm is described, results of using the algorithm over example scenes are shown, and global statistics for multilayered clouds as observed by MODIS 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 MODIS multilayer cloud detection algorithm has some skill in identifying multilayered clouds with different thermodynamic phases

Near-nadir scan overlap in Earth observations from VIIRS and MODIS

NASA Astrophysics Data System (ADS)

Blonski, Slawomir; Cao, Changyong

2017-09-01

Satellite multi-detector cross-track scanners, such as MODIS (Moderate Resolution Imaging Spectroradiometer) and VIIRS (Visible-Infrared Imaging Radiometer Suite), require synchronization of optical and orbital characteristics to avoid gaps in Earth coverage between scans. Prelaunch tests have revealed that such scan-to-scan gaps will occur near nadir in VIIRS observations from the future JPSS-1 (Joint Polar Satellite System) and JPSS-2 satellites. Our analysis of VIIRS geolocation products shows that the gaps do not occur for the instrument currently on orbit onboard the S-NPP (Suomi National Polar-orbiting Partnership) spacecraft. When the same analysis is applied to the MODIS data products, it reveals that small, near-nadir gaps exist in MODIS observations from both Aqua and Terra satellites. Although magnitude of the MODIS scan overlap gaps (up to 100 m for Terra and 25/175 m for Aqua) is quite small in comparison to the 1-km pixels, it is rather significant for the bands with the 250-m and 500-m pixels. Despite the size of the gaps, it appears that their effects on scientific analyses (e.g., NDVI) have not been reported since launch of the MODIS instruments. Because the gaps currently predicted for the JPSS-1 and -2 VIIRS are similar in size to the ones occurring for MODIS, one can expect that their effects on science data will be similarly negligible. A model that uses S-NPP orbit data as well as the S-NPP VIIRS telescope's focal length and scan rate predicts the overlap that agrees very well with the analysis of the geolocation data. For JPSS-1/-2 VIIRS focal length and scan rate, the model predicts scan overlap gaps of more than 100 m. With a shorter focal length and a faster scan rate than for the JPSS-1/-2 VIIRS, the scan overlap gaps are expected to be avoided altogether for VIIRS on the future JPSS-3 and -4 satellites.

A sea surface reflectance model for (A)ATSR, and application to aerosol retrievals

NASA Astrophysics Data System (ADS)

Sayer, A. M.; Thomas, G. E.; Grainger, R. G.

2010-07-01

A model of the sea surface bidirectional reflectance distribution function (BRDF) is presented for the visible and near-IR channels (over the spectral range 550 nm to 1.6 μm) of the dual-viewing Along-Track Scanning Radiometers (ATSRs). The intended application is as part of the Oxford-RAL Aerosols and Clouds (ORAC) retrieval scheme. The model accounts for contributions to the observed reflectance from whitecaps, sun-glint and underlight. Uncertainties in the parametrisations used in the BRDF model are propagated through into the forward model and retrieved state. The new BRDF model offers improved coverage over previous methods, as retrievals are possible into the sun-glint region, through the ATSR dual-viewing system. The new model has been applied in the ORAC aerosol retrieval algorithm to process Advanced ATSR (AATSR) data from September 2004 over the south-eastern Pacific. The assumed error budget is shown to be generally appropriate, meaning the retrieved states are consistent with the measurements and a priori assumptions. The resulting field of aerosol optical depth (AOD) is compared with colocated MODIS-Terra observations, AERONET observations at Tahiti, and cruises over the oceanic region. MODIS and AATSR show similar spatial distributions of AOD, although MODIS reports values which are larger and more variable. It is suggested that assumptions in the MODIS aerosol retrieval algorithm may lead to a positive bias in MODIS AOD of order 0.01 at 550 nm over ocean regions where the wind speed is high.

A sea surface reflectance model for (A)ATSR, and application to aerosol retrievals

NASA Astrophysics Data System (ADS)

Sayer, A. M.; Thomas, G. E.; Grainger, R. G.

2010-03-01

A model of the sea surface bidirectional reflectance distribution function (BRDF) is presented for the visible and near-IR channels (over the spectral range 550 nm to 1.6 μm) of the dual-viewing Along-Track Scanning Radiometers (ATSRs). The intended application is as part of the Oxford-RAL Aerosols and Clouds (ORAC) retrieval scheme. The model accounts for contributions to the observed reflectance from whitecaps, sun-glint and underlight. Uncertainties in the parametrisations used in the BRDF model are propagated through into the forward model and retrieved state. The new BRDF model offers improved coverage over previous methods, as retrievals are possible into the sun-glint region, through the ATSR dual-viewing system. The new model has been applied in the ORAC aerosol retrieval algorithm to process Advanced ATSR (AATSR) data from September 2004 over the south-eastern Pacific. The assumed error budget is shown to be generally appropriate, meaning the retrieved states are consistent with the measurements and a priori assumptions. The resulting field of aerosol optical depth (AOD) is compared with colocated MODIS-Terra observations, AERONET observations at Tahiti, and cruises over the oceanic region. MODIS and AATSR show similar spatial distributions of AOD, although MODIS reports values which are larger and more variable. It is suggested that assumptions in the MODIS aerosol retrieval algorithm may lead to a positive bias in MODIS AOD of order 0.01 at 550 nm over ocean regions where the wind speed is high.

Three-dimensional variational assimilation of MODIS aerosol optical depth: Implementation and application to a dust storm over East Asia

NASA Astrophysics Data System (ADS)

Liu, Zhiquan; Liu, Quanhua; Lin, Hui-Chuan; Schwartz, Craig S.; Lee, Yen-Huei; Wang, Tijian

2011-12-01

Assimilation of the Moderate Resolution Imaging Spectroradiometer (MODIS) total aerosol optical depth (AOD) retrieval products (at 550 nm wavelength) from both Terra and Aqua satellites have been developed within the National Centers for Environmental Prediction (NCEP) Gridpoint Statistical Interpolation (GSI) three-dimensional variational (3DVAR) data assimilation system. This newly developed algorithm allows, in a one-step procedure, the analysis of 3-D mass concentration of 14 aerosol variables from the Goddard Chemistry Aerosol Radiation and Transport (GOCART) module. The Community Radiative Transfer Model (CRTM) was extended to calculate AOD using GOCART aerosol variables as input. Both the AOD forward model and corresponding Jacobian model were developed within the CRTM and used in the 3DVAR minimization algorithm to compute the AOD cost function and its gradient with respect to 3-D aerosol mass concentration. The impact of MODIS AOD data assimilation was demonstrated by application to a dust storm from 17 to 24 March 2010 over East Asia. The aerosol analyses initialized Weather Research and Forecasting/Chemistry (WRF/Chem) model forecasts. Results indicate that assimilating MODIS AOD substantially improves aerosol analyses and subsequent forecasts when compared to MODIS AOD, independent AOD observations from the Aerosol Robotic Network (AERONET) and Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) instrument, and surface PM10 (particulate matter with diameters less than 10 μm) observations. The newly developed AOD data assimilation system can serve as a tool to improve simulations of dust storms and general air quality analyses and forecasts.

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

NASA Technical Reports Server (NTRS)

Geogdzhayev, Igor V.; Marshak, Alexander

2018-01-01

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

An enhanced TIMESAT algorithm for estimating vegetation phenology metrics from MODIS data

USGS Publications Warehouse

Tan, B.; Morisette, J.T.; Wolfe, R.E.; Gao, F.; Ederer, G.A.; Nightingale, J.; Pedelty, J.A.

2011-01-01

An enhanced TIMESAT algorithm was developed for retrieving vegetation phenology metrics from 250 m and 500 m spatial resolution Moderate Resolution Imaging Spectroradiometer (MODIS) vegetation indexes (VI) over North America. MODIS VI data were pre-processed using snow-cover and land surface temperature data, and temporally smoothed with the enhanced TIMESAT algorithm. An objective third derivative test was applied to define key phenology dates and retrieve a set of phenology metrics. This algorithm has been applied to two MODIS VIs: Normalized Difference Vegetation Index (NDVI) and Enhanced Vegetation Index (EVI). In this paper, we describe the algorithm and use EVI as an example to compare three sets of TIMESAT algorithm/MODIS VI combinations: a) original TIMESAT algorithm with original MODIS VI, b) original TIMESAT algorithm with pre-processed MODIS VI, and c) enhanced TIMESAT and pre-processed MODIS VI. All retrievals were compared with ground phenology observations, some made available through the National Phenology Network. Our results show that for MODIS data in middle to high latitude regions, snow and land surface temperature information is critical in retrieving phenology metrics from satellite observations. The results also show that the enhanced TIMESAT algorithm can better accommodate growing season start and end dates that vary significantly from year to year. The TIMESAT algorithm improvements contribute to more spatial coverage and more accurate retrievals of the phenology metrics. Among three sets of TIMESAT/MODIS VI combinations, the start of the growing season metric predicted by the enhanced TIMESAT algorithm using pre-processed MODIS VIs has the best associations with ground observed vegetation greenup dates. ?? 2010 IEEE.

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

NASA Technical Reports Server (NTRS)

Tan, Bin; Morisette, Jeffrey T.; Wolfe, Robert E.; Gao, Feng; Ederer, Gregory A.; Nightingale, Joanne; Pedelty, Jeffrey A.

2012-01-01

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

Multi-platform comparisons of MODIS and AVHRR normalized difference vegetation index data

USGS Publications Warehouse

Gallo, Kevin P.; Ji, Lei; Reed, Bradley C.; Eidenshink, Jeffery C.; Dwyer, John L.

2005-01-01

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 (MODIS) sensor. NDVI data derived from visible and near-infrared data acquired by the MODIS (Terra and Aqua 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 MODIS 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 MODIS 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.

Validation of Satellite Snow Cover Maps in North America and Norway

NASA Technical Reports Server (NTRS)

Hall, Dorothy K.; Solberg, Rune; Riggs, George A.

2002-01-01

Satellite-derived snow maps from NASA's Earth Observing System Moderate Resolution Imaging Spectroradiometer (MODIS) have been produced since February of 2000. The global maps are available daily at 500-m resolution, and at a climate-modeling grid (CMG) resolution of 1/20 deg (approximately 5.6 km). We compared the 8-day composite CMG MODIS-derived global maps from November 1,2001, through March 21,2002, and daily CMG maps from February 26 - March 5,2002, with National Oceanic and Atmospheric Administration (NOAA) Interactive Multisensor Snow and Ice Mapping System (IMS) 25-km resolution maps for North America. For the Norwegian study area, national snow maps, based on synoptic measurements as well as visual interpretation of AVHRR images, published by the Det Norske Meteorologiske Institutt (Norwegian Meteorological Institute) (MI) maps, as well as Landsat ETM+ images were compared with the MODIS maps. The MODIS-derived maps agreed over most areas with the IMS or MI maps, however, there are important areas of disagreement between the maps, especially when the 8-day composite maps were used. It is concluded that MODIS daily CMG maps should be studied for validation purposes rather than the 8-day composite maps, despite the limitations imposed by cloud obscuration when using the daily maps.

Application-ready expedited MODIS data for operational land surface monitoring of vegetation condition

USGS Publications Warehouse

Brown, Jesslyn; Howard, Daniel M.; Wylie, Bruce K.; Friesz, Aaron M.; Ji, Lei; Gacke, Carolyn

2015-01-01

Monitoring systems benefit from high temporal frequency image data collected from the Moderate Resolution Imaging Spectroradiometer (MODIS) system. Because of near-daily global coverage, MODIS data are beneficial to applications that require timely information about vegetation condition related to drought, flooding, or fire danger. Rapid satellite data streams in operational applications have clear benefits for monitoring vegetation, especially when information can be delivered as fast as changing surface conditions. An “expedited” processing system called “eMODIS” operated by the U.S. Geological Survey provides rapid MODIS surface reflectance data to operational applications in less than 24 h offering tailored, consistently-processed information products that complement standard MODIS products. We assessed eMODIS quality and consistency by comparing to standard MODIS data. Only land data with known high quality were analyzed in a central U.S. study area. When compared to standard MODIS (MOD/MYD09Q1), the eMODIS Normalized Difference Vegetation Index (NDVI) maintained a strong, significant relationship to standard MODIS NDVI, whether from morning (Terra) or afternoon (Aqua) orbits. The Aqua eMODIS data were more prone to noise than the Terra data, likely due to differences in the internal cloud mask used in MOD/MYD09Q1 or compositing rules. Post-processing temporal smoothing decreased noise in eMODIS data.

Application of Remote Sensing to Assess the Impact of Short Term Climate Variability on Coastal Sedimentation

NASA Technical Reports Server (NTRS)

Menzel, W. Paul; Huh, Oscar K.; Walker, Nan

2004-01-01

The purpose of this joint University of Wisconsin (UW) and Louisiana State University (LSU) project has been to relate short term climate variation to response in the coastal zone of Louisiana in an attempt to better understand how the coastal zone is shaped by climate variation. Climate variation in this case largely refers to variation in surface wind conditions that affect wave action and water currents in the coastal zone. The primary region of focus was the Atchafalaya Bay and surrounding bays in the central coastal region of Louisiana. Suspended solids in the water column show response to wind systems both in quantity (through resuspension) and in the pattern of dispersement or transport. Wind systems associated with cold fronts are influenced by short term climate variation. Wind energy was used as the primary signature of climate variation in this study because winds are a significant influence on sediment transport in the micro-tidal Gilf of Mexico coastal zone. Using case studies, the project has been able to investigate the influence of short term climate variation on sediment transport. Wind energy data, collected daily for National Weather Service (NWS) stations at Lake Charles and New Orleans, LA, were used as an indicator of short term climate variation influence on seasonal time scales. A goal was to relate wind energy to coastal impact through sediment transport. This goal was partially accomplished by combining remote sensing and wind energy data. Daily high resolution remote sensing observations are needed to monitor the complex coastal zone environment, where winds, tides, and water level all interact to influence sediment transport. The NASA Earth Observing System (EOS) era brings hope for documenting and revealing response of the complex coastal transport mosaic through regular high spatial resolution observations from the Moderate resolution Imaging Spectrometer (MODIS) instrument. MODIS observations were sampled in this project for information content and should continue to be viewed as a resource for coastal zone monitoring. The project initialized the effort to transfer a suspended sediment concentration (SSC) algorithm to the MODIS platform for case 2 waters. MODIS enables monitoring of turbid coastal zones around the globe. The MODIS SSC algorithm requires refinements in the atmospheric aerosol contribution, sun glint influence, and designation of the sediment inherent optical properties (IOPs); the framework for continued development is in place with a plan to release the algorithm to the MODIS direct broadcast community.

Validation of MODIS Aerosol Retrieval Over Ocean

NASA Technical Reports Server (NTRS)

Remer, Lorraine A.; Tanre, Didier; Kaufman, Yoram J.; Ichoku, Charles; Mattoo, Shana; Levy, Robert; Chu, D. Allen; Holben, Brent N.; Dubovik, Oleg; Ahmad, Ziauddin;

Response Versus Scan-Angle Corrections for MODIS Reflective Solar Bands Using Deep Convective Clouds

NASA Technical Reports Server (NTRS)

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

2016-01-01

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 performance of the SD over time, provides the absolute reference 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 zero input radiance, respectively. The MODIS instrument views the Earths surface through a two-sided scan mirror, whose reflectance is a function of 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 assigned RVS positions. 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 RVS positions. Consequently, the MODIS Characterization Support Team (MCST) developed enhanced approaches that supplement the onboard calibrator measurements with responses from pseudo-invariant desert sites. This approach has been implemented in Level 1B (L1B) Collection 6 (C6) for selected 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 in the left side Earth-view scans.

Response Versus Scan-Angle Corrections for MODIS Reflective Solar Bands Using Deep Convective Clouds

NASA Technical Reports Server (NTRS)

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

2016-01-01

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 performance of the SD over time, provides the absolute reference 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 zero input radiance, respectively. The MODIS instrument views the Earth's surface through a two-sided scan mirror, whose reflectance is a function of 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 assigned RVS positions. 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 RVS positions. Consequently, the MODIS Characterization Support Team (MCST) developed enhanced approaches that supplement the onboard calibrator measurements with responses from pseudo-invariant desert sites. This approach has been implemented in Level 1B (L1B) Collection 6 (C6) for selected 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 in the left side Earth-view scans.

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.

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

NASA Astrophysics Data System (ADS)

Riggs, George A.; Hall, Dorothy K.; Román, Miguel O.

2017-10-01

Knowledge of the distribution, extent, duration and timing of snowmelt is critical for characterizing the Earth's climate system and its changes. As a result, snow cover is one of the Global Climate Observing System (GCOS) essential climate variables (ECVs). Consistent, long-term datasets of snow cover are needed to study interannual variability and snow climatology. The NASA snow-cover datasets generated from the Moderate Resolution Imaging Spectroradiometer (MODIS) on the Terra and Aqua spacecraft and the Suomi National Polar-orbiting Partnership (S-NPP) Visible Infrared Imaging Radiometer Suite (VIIRS) are NASA Earth System Data Records (ESDR). The objective of the snow-cover detection algorithms is to optimize the accuracy of mapping snow-cover extent (SCE) and to minimize snow-cover detection errors of omission and commission using automated, globally applied algorithms to produce SCE data products. Advancements in snow-cover mapping have been made with each of the four major reprocessings of the MODIS data record, which extends from 2000 to the present. MODIS Collection 6 (C6; https://nsidc.org/data/modis/data_summaries) and VIIRS Collection 1 (C1; https://doi.org/10.5067/VIIRS/VNP10.001) represent the state-of-the-art global snow-cover mapping algorithms and products for NASA Earth science. There were many revisions made in the C6 algorithms which improved snow-cover detection accuracy and information content of the data products. These improvements have also been incorporated into the NASA VIIRS snow-cover algorithms for C1. Both information content and usability were improved by including the Normalized Snow Difference Index (NDSI) and a quality assurance (QA) data array of algorithm processing flags in the data product, along with the SCE map. The increased data content allows flexibility in using the datasets for specific regions and end-user applications. Though there are important differences between the MODIS and VIIRS instruments (e.g., the VIIRS 375 m native resolution compared to MODIS 500 m), the snow detection algorithms and data products are designed to be as similar as possible so that the 16+ year MODIS ESDR of global SCE can be extended into the future with the S-NPP VIIRS snow products and with products from future Joint Polar Satellite System (JPSS) platforms. These NASA datasets are archived and accessible through the NASA Distributed Active Archive Center at the National Snow and Ice Data Center in Boulder, Colorado.

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 both Terra and Aqua. In certain situations, this combined analysis of Terra- and Aqua-MODIS data offers an insight into the diurnal cycle of aerosol loading.

Inversion of AMSR-E observations for land surface temperature estimation: 2. Global comparison with infrared satellite temperature

NASA Astrophysics Data System (ADS)

Ermida, S. L.; Jiménez, C.; Prigent, C.; Trigo, I. F.; DaCamara, C. C.

2017-03-01

A comparison of land surface temperature (Ts) derived from the Advanced Microwave Scanning Radiometer-Earth Observing System (AMSR-E) with infrared Ts is presented. The infrared Ts include clear-sky estimates from the Moderate Resolution Imaging Spectroradiometer (MODIS), the Spinning Enhanced Visible and Infrared Imager, the Geostationary Operational Environmental Satellite (GOES) Imager, and the Japanese Meteorological Imager. The higher discrepancies between AMSR-E and MODIS are observed over deserts and snow-covered areas. The former seems to be associated with Ts underestimation by MODIS, whereas the latter is mostly related to uncertainties in microwave emissivity over snow/ice. Ts differences between AMSR-E and MODIS are significantly reduced after masking out snow and deserts, with a bias change from 2.6/4.6 K to 3.0/1.4 K for daytime/nighttime and a standard deviation (STD) decrease from 7.3/7.9 K to 5.1/3.9 K. When comparing with all infrared sensors, the STD of the differences between microwave and infrared Ts is generally higher than between IR retrievals. However, the biases between microwave and infrared Ts are, in some cases, of the same order as the ones observed between infrared products. This is the case for GOES, with daytime biases with respect to AMSR-E and MODIS of 0.45 K and 0.60 K, respectively. While the infrared Ts are clear-sky estimates, AMSR-E also provides Ts under cloudy conditions. For frequently cloudy regions, this results in a large increase of available Ts estimates (>250%), making the microwave Ts a very powerful complement of the infrared estimates.

A Real-Time MODIS Vegetation Composite for Land Surface Models and Short-Term Forecasting

NASA Technical Reports Server (NTRS)

Case, Jonathan L.; LaFontaine, Frank J.; Kumar, Sujay V.; Jedlovec, Gary J.

2011-01-01

The NASA Short-term Prediction Research and Transition (SPoRT) Center is producing real-time, 1- km resolution Normalized Difference Vegetation Index (NDVI) gridded composites over a Continental U.S. domain. These composites are updated daily based on swath data from the Moderate Resolution Imaging Spectroradiometer (MODIS) sensor aboard the polar orbiting NASA Aqua and Terra satellites, with a product time lag of about one day. A simple time-weighting algorithm is applied to the NDVI swath data that queries the previous 20 days of data to ensure a continuous grid of data populated at all pixels. The daily composites exhibited good continuity both spatially and temporally during June and July 2010. The composites also nicely depicted high greenness anomalies that resulted from significant rainfall over southwestern Texas, Mexico, and New Mexico during July due to early-season tropical cyclone activity. The SPoRT Center is in the process of computing greenness vegetation fraction (GVF) composites from the MODIS NDVI data at the same spatial and temporal resolution for use in the NASA Land Information System (LIS). The new daily GVF dataset would replace the monthly climatological GVF database (based on Advanced Very High Resolution Radiometer [AVHRR] observations from 1992-93) currently available to the Noah land surface model (LSM) in both LIS and the public version of the Weather Research and Forecasting (WRF) model. The much higher spatial resolution (1 km versus 0.15 degree) and daily updates based on real-time satellite observations have the capability to greatly improve the simulation of the surface energy budget in the Noah LSM within LIS and WRF. Once code is developed in LIS to incorporate the daily updated GVFs, the SPoRT Center will conduct simulation sensitivity experiments to quantify the impacts and improvements realized by the MODIS real-time GVF data. This presentation will describe the methodology used to develop the 1-km MODIS NDVI composites and show sample output from summer 2010, compare the MODIS GVF data to the AVHRR monthly climatology, and illustrate the sensitivity of the Noah LSM within LIS and/or the coupled LIS/WRF system to the new MODIS GVF dataset.

Determination of the single scattering albedo and direct radiative forcing of biomass burning aerosol with data from the MODIS (Moderate Resolution Imaging Spectroradiometer) satellite instrument

NASA Astrophysics Data System (ADS)

Zhu, Li

Biomass burning aerosols absorb and scatter solar radiation and therefore affect the energy balance of the Earth-atmosphere system. The single scattering albedo (SSA), the ratio of the scattering coefficient to the extinction coefficient, is an important parameter to describe the optical properties of aerosols and to determine the effect of aerosols on the energy balance of the planet and climate. Aerosol effects on radiation also depend strongly on surface albedo. Large uncertainties remain in current estimates of radiative impacts of biomass burning aerosols, due largely to the lack of reliable measurements of aerosol and surface properties. In this work we investigate how satellite measurements can be used to estimate the direct radiative forcing of biomass burning aerosols. We developed a method using the critical reflectance technique to retrieve SSA from the Moderate Resolution Imaging Spectroradiometer (MODIS) observed reflectance at the top of the atmosphere (TOA). We evaluated MODIS retrieved SSAs with AErosol RObotic NETwork (AERONET) retrievals and found good agreements within the published uncertainty of the AERONET retrievals. We then developed an algorithm, the MODIS Enhanced Vegetation Albedo (MEVA), to improve the representations of spectral variations of vegetation surface albedo based on MODIS observations at the discrete 0.67, 0.86, 0.47, 0.55, 1.24, 1.64, and 2.12 mu-m channels. This algorithm is validated using laboratory measurements of the different vegetation types from the Amazon region, data from the Johns Hopkins University (JHU) spectral library, and data from the U.S. Geological Survey (USGS) digital spectral library. We show that the MEVA method can improve the accuracy of flux and aerosol forcing calculations at the TOA compared to more traditional interpolated approaches. Lastly, we combine the MODIS retrieved biomass burning aerosol SSA and the surface albedo spectrum determined from the MEVA technique to calculate TOA flux and aerosol direct radiative forcing over the Amazon region and compare it with Clouds and the Earth's Radiant Energy System (CERES) satellite results. The results show that MODIS based forcing calculations present similar averaged results compared to CERES, but MODIS shows greater spatial variation of aerosol forcing than CERES. Possible reasons for these differences are explored and discussed in this work. Potential future research based on these results is discussed as well.

Effect of Cloud Fraction on Near-Cloud Aerosol Behavior Based on MODIS and CALIPSO Observations

NASA Technical Reports Server (NTRS)

Marshak, A.; Varnai, T.; Yang, W.

2015-01-01

Organizers of the MODIS-VIIRS Science Team Meeting, held May 18-22, 2015 in Silver Spring, MD plan to post the presentations and posters to the NASA MODIS website: http:modis.gsfc.nasa.govsci_teammeetings201505index.php. The MODIS Science Team Meeting is held twice a year, so that the members of the science team may assemble and discuss data they have collected, ideas they have formed, and future issues that apply to the MODIS Mission.

Unmanned aerial system nadir reflectance and MODIS nadir BRDF-adjusted surface reflectances intercompared over Greenland

NASA Astrophysics Data System (ADS)

Faulkner Burkhart, John; Kylling, Arve; Schaaf, Crystal B.; Wang, Zhuosen; Bogren, Wiley; Storvold, Rune; Solbø, Stian; Pedersen, Christina A.; Gerland, Sebastian

2017-07-01

Albedo is a fundamental parameter in earth sciences, and many analyses utilize the Moderate Resolution Imaging Spectroradiometer (MODIS) bidirectional reflectance distribution function (BRDF)/albedo (MCD43) algorithms. While derivative albedo products have been evaluated over Greenland, we present a novel, direct comparison with nadir surface reflectance collected from an unmanned aerial system (UAS). The UAS was flown from Summit, Greenland, on 210 km transects coincident with the MODIS sensor overpass on board the Aqua and Terra satellites on 5 and 6 August 2010. Clear-sky acquisitions were available from the overpasses within 2 h of the UAS flights. The UAS was equipped with upward- and downward-looking spectrometers (300-920 nm) with a spectral resolution of 10 nm, allowing for direct integration into the MODIS bands 1, 3, and 4. The data provide a unique opportunity to directly compare UAS nadir reflectance with the MODIS nadir BRDF-adjusted surface reflectance (NBAR) products. The data show UAS measurements are slightly higher than the MODIS NBARs for all bands but agree within their stated uncertainties. Differences in variability are observed as expected due to different footprints of the platforms. The UAS data demonstrate potentially large sub-pixel variability of MODIS reflectance products and the potential to explore this variability using the UAS as a platform. It is also found that, even at the low elevations flown typically by a UAS, reflectance measurements may be influenced by haze if present at and/or below the flight altitude of the UAS. This impact could explain some differences between data from the two platforms and should be considered in any use of airborne platforms.

MODIS information, data and control system (MIDACS) operations concepts

NASA Technical Reports Server (NTRS)

Han, D.; Salomonson, V.; Ormsby, J.; Ardanuy, P.; Mckay, A.; Hoyt, D.; Jaffin, S.; Vallette, B.; Sharts, B.; Folta, D.

1988-01-01

The MODIS Information, Data, and Control System (MIDACS) Operations Concepts Document provides a basis for the mutual understanding between the users and the designers of the MIDACS, including the requirements, operating environment, external interfaces, and development plan. In defining the concepts and scope of the system, how the MIDACS will operate as an element of the Earth Observing System (EOS) within the EosDIS environment is described. This version follows an earlier release of a preliminary draft version. The individual operations concepts for planning and scheduling, control and monitoring, data acquisition and processing, calibration and validation, data archive and distribution, and user access do not yet fully represent the requirements of the data system needed to achieve the scientific objectives of the MODIS instruments and science teams. The teams are not yet formed; however, it is possible to develop the operations concepts based on the present concept of EosDIS, the level 1 and level 2 Functional Requirements Documents, and through interviews and meetings with key members of the scientific community. The operations concepts were exercised through the application of representative scenarios.

Adjustments to the MODIS Terra Radiometric Calibration and Polarization Sensitivity in the 2010 Reprocessing

NASA Technical Reports Server (NTRS)

Meister, Gerhard; Franz, Bryan A.

2011-01-01

The Moderate-Resolution Imaging Spectroradiometer (MODIS) 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 MODIS 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 MODIS Terra ocean color products are now in excellent agreement with those of SeaWiFS and MODIS Aqua, 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.

Assessment of Provisional MODIS-derived Surfaces Related to the Global Carbon Cycle

NASA Astrophysics Data System (ADS)

Cohen, W. B.; Maiersperger, T. K.; Turner, D. P.; Gower, S. T.; Kennedy, R. E.; Running, S. W.

2002-12-01

The global carbon cycle is one of the most important foci of an emerging global biosphere monitoring system. A key component of such a system is the MODIS sensor, onboard the Terra satellite platform. Biosphere monitoring requires an integrated program of satellite observations, Earth-system models, and in situ data. Related to the carbon cycle, MODIS science teams routinely develop a variety of global surfaces such as land cover, leaf area index, and net primary production using MODIS data and functional algorithms. The quality of these surfaces must be evaluated to determine their effectiveness for global biosphere monitoring. A project called BigFoot (http://www.fsl.orst.edu/larse/bigfoot/) is an organized effort across nine biomes to assess the quality of the abovementioned surfaces: (1) Arctic tundra; (2) boreal evergreen needle-leaved forest; temperate (3) cropland, (4) grassland, (5) evergreen needle-leaved forest, and (6) deciduous broad-leaved forest; desert (7) grassland and (8) shrubland; and (9) tropical evergreen broad-leaved forest. Each biome is represented by a site that has an eddy-covariance flux tower that measures water vapor and CO2 fluxes. Flux tower footprints are relatively small-approximately 1 km2. BigFoot characterizes 25 km2 around each tower, using field data, Landsat ETM+ image data, and ecosystem process models. Our innovative field sampling design incorporates a nested spatial series to facilitate geostatistical analyses, samples the ecological variability at a site, and is logistically efficient. Field data are used both to develop site-specific algorithms for mapping/modeling the variables of interest and to characterize the errors in derived BigFoot surfaces. Direct comparisons of BigFoot- and MODIS-derived surfaces are made to help understand the sources of error in MODIS-derived surfaces and to facilitate improvements to MODIS algorithms. Results from four BigFoot sites will be presented.

MODIS Validation, Data Merger and Other Activities Accomplished by the SIMBIOS Project: 2002-2003

NASA Technical Reports Server (NTRS)

Fargion, Giulietta S.; McClain, Charles R.

2003-01-01

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 (MODIS) on the Earth Observing System (EOS) Terra platform (similar evaluations of MODIS/Aqua 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.

Application of Remote Sensing to Assess the Impact of Short Term Climate Variability on Coastal Sedimentation

NASA Technical Reports Server (NTRS)

Moeller, Christopher C.; Gunshor, Mathew M.; Menzel, W. Paul; Huh, Oscar K.; Walker, Nan D.; Rouse, Lawrence J.; Frey, Herbert V. (Technical Monitor)

2001-01-01

The University of Wisconsin and Louisiana State University have teamed to study the forcing of winter season cold frontal wind systems on sediment distribution patterns and geomorphology in the Louisiana coastal zone. Wind systems associated with cold fronts have been shown to modify coastal circulation and resuspend sediments along the microtidal Louisiana coast. The assessment includes quantifying the influence of cumulative winter season atmospheric forcing (through surface wind observations) from year to year in response to short term climate variability, such as El Nino events. A correlation between winter cyclone frequency and the strength of El Nino events has been suggested. The atmospheric forcing data are being correlated to geomorphic measurements along western Louisiana's prograding muddy coast. Remote sensing data is being used to map and track sediment distribution patterns for various wind conditions. Transferring a suspended sediment concentration (SSC) algorithm to EOS MODIS observations will enable estimates of SSC in case 2 waters over the global domain. Progress in Year 1 of this study has included data collection and analysis of wind observations for atmospheric forcing characterization, a field activity (TX-2001) to collect in situ water samples with co-incident remote sensing measurements from the NASA ER-2 based MODIS Airborne Simulator (MAS) and the EOS Terra based MODerate resolution Imaging Spectroradiometer (MODIS) instruments, aerial photography and of sediment burial pipe field measurements along the prograding muddy Chenier Plain coast of western Louisiana for documenting coastal change in that dynamic region, and routine collection of MODIS 250 in resolution data for monitoring coastal sediment patterns. The data sets are being used in a process to transfer an SSC estimation algorithm to the MODIS platform. Work is underway on assessing coastal transport for the winter 2000-01 season. Water level data for use in a Geomorphic Impact Index, which relates wind energy, water level conditions, and geomorphic change along the microtidal western Louisiana coastline is being assembled.

Evaluation and Intercomparison of MODIS and GEOV1 Global Leaf Area Index Products over Four Sites in North China

PubMed Central

Li, Zhenwang; Tang, Huan; Zhang, Baohui; Yang, Guixia; Xin, Xiaoping

2015-01-01

This study investigated the performances of the Moderate Resolution Imaging Spectroradiometer (MODIS) 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 + Aqua MODIS and Terra MODIS 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 MODIS products performed well for biomes with low LAI values, but considerable uncertainty arose when the LAI was larger than 3. Terra + Aqua MODIS (R2 = 0.72 and RMSE = 0.68) was slightly more accurate than Terra MODIS (R2 = 0.57 and RMSE = 0.90) for producing slightly more successful observations. Both MODIS and GEOV1 products effectively followed the seasonal trajectory of the reference maps, and GEOV1 exhibited a smoother seasonal trajectory than MODIS. MODIS anomalies mainly occurred during summer and likely occurred because of surface reflectance uncertainty, shorter temporal resolutions and inconsistency between simulated and MODIS surface reflectances. This study suggests that further improvements of the MODIS LAI products should focus on finer algorithm inputs and improved seasonal variation modeling of MODIS observations. Future field work considering finer biome maps and better generation of LAI reference maps is still needed. PMID:25781509

Marine Boundary Layer Cloud Property Retrievals from High-Resolution ASTER Observations: Case Studies and Comparison with Terra MODIS

NASA Technical Reports Server (NTRS)

Werner, Frank; Wind, Galina; Zhang, Zhibo; Platnick, Steven; Di Girolamo, Larry; Zhao, Guangyu; Amarasinghe, Nandana; Meyer, Kerry

2016-01-01

A research-level retrieval algorithm for cloud optical and microphysical properties is developed for the Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) aboard the Terra satellite. It is based on the operational MODIS algorithm. This paper documents the technical details of this algorithm and evaluates the retrievals for selected marine boundary layer cloud scenes through comparisons with the operational MODIS Data Collection 6 (C6) cloud product. The newly developed, ASTERspecific cloud masking algorithm is evaluated through comparison with an independent algorithm reported in Zhao and Di Girolamo (2006). To validate and evaluate the cloud optical thickness (tau) and cloud effective radius (r(sub eff)) from ASTER, the high-spatial-resolution ASTER observations are first aggregated to the same 1000m resolution as MODIS. Subsequently, tau(sub aA) and r(sub eff, aA) retrieved from the aggregated ASTER radiances are compared with the collocated MODIS retrievals. For overcast pixels, the two data sets agree very well with Pearson's product-moment correlation coefficients of R greater than 0.970. However, for partially cloudy pixels there are significant differences between r(sub eff, aA) and the MODIS results which can exceed 10 micrometers. Moreover, it is shown that the numerous delicate cloud structures in the example marine boundary layer scenes, resolved by the high-resolution ASTER retrievals, are smoothed by the MODIS observations. The overall good agreement between the research-level ASTER results and the operational MODIS C6 products proves the feasibility of MODIS-like retrievals from ASTER reflectance measurements and provides the basis for future studies concerning the scale dependency of satellite observations and three-dimensional radiative effects.

Marine boundary layer cloud property retrievals from high-resolution ASTER observations: case studies and comparison with Terra MODIS

NASA Astrophysics Data System (ADS)

Werner, Frank; Wind, Galina; Zhang, Zhibo; Platnick, Steven; Di Girolamo, Larry; Zhao, Guangyu; Amarasinghe, Nandana; Meyer, Kerry

2016-12-01

A research-level retrieval algorithm for cloud optical and microphysical properties is developed for the Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) aboard the Terra satellite. It is based on the operational MODIS algorithm. This paper documents the technical details of this algorithm and evaluates the retrievals for selected marine boundary layer cloud scenes through comparisons with the operational MODIS Data Collection 6 (C6) cloud product. The newly developed, ASTER-specific cloud masking algorithm is evaluated through comparison with an independent algorithm reported in [Zhao and Di Girolamo(2006)]. To validate and evaluate the cloud optical thickness (τ) and cloud effective radius (reff) from ASTER, the high-spatial-resolution ASTER observations are first aggregated to the same 1000 m resolution as MODIS. Subsequently, τaA and reff, aA retrieved from the aggregated ASTER radiances are compared with the collocated MODIS retrievals. For overcast pixels, the two data sets agree very well with Pearson's product-moment correlation coefficients of R > 0.970. However, for partially cloudy pixels there are significant differences between reff, aA and the MODIS results which can exceed 10 µm. Moreover, it is shown that the numerous delicate cloud structures in the example marine boundary layer scenes, resolved by the high-resolution ASTER retrievals, are smoothed by the MODIS observations. The overall good agreement between the research-level ASTER results and the operational MODIS C6 products proves the feasibility of MODIS-like retrievals from ASTER reflectance measurements and provides the basis for future studies concerning the scale dependency of satellite observations and three-dimensional radiative effects.

Infrared Algorithm Development for Ocean Observations with EOS/MODIS

NASA Technical Reports Server (NTRS)

Brown, Otis B.

1997-01-01

Efforts continue under this contract to develop algorithms for the computation of sea surface temperature (SST) from MODIS infrared measurements. This effort includes radiative transfer modeling, comparison of in situ and satellite observations, development and evaluation of processing and networking methodologies for algorithm computation and data accession, evaluation of surface validation approaches for IR radiances, development of experimental instrumentation, and participation in MODIS (project) related activities. Activities in this contract period have focused on radiative transfer modeling, evaluation of atmospheric correction methodologies, undertake field campaigns, analysis of field data, and participation in MODIS meetings.

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

MODIS on-orbit thermal emissive bands lifetime performance

NASA Astrophysics Data System (ADS)

Madhavan, Sriharsha; Wu, Aisheng; Chen, Na; Xiong, Xiaoxiong

2016-05-01

MODerate resolution Imaging Spectroradiometer (MODIS), 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 Aqua (A) platforms. Both instruments have successfully continued to operate beyond the 6 year design life time, with the T-MODIS currently functional beyond 15 years and the A-MODIS operating beyond 13 years respectively. The MODIS 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 MODIS 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.

MODIS On-Orbit Thermal Emissive Bands Lifetime Performance

NASA Technical Reports Server (NTRS)

Madhavan, Sriharsha; Xiong, Xiaoxiong

2016-01-01

MODerate resolution Imaging Spectroradiometer (MODIS), 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 Aqua (A) platforms. Both instruments have successfully continued to operate beyond the 6 year design life time, with the T-MODIS currently functional beyond 15 years and the A-MODIS operating beyond 13 years respectively. The MODIS sensor characteristics include a spectral coverage from 0.41 micron 14.4 micron, of which wavelengths ranging from 3.7 micron 14. 4 micron 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 MODIS 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.

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.

The Radiative Consistency of Atmospheric Infrared Sounder and Moderate Resolution Imaging Spectroradiometer Cloud Retrievals

NASA Technical Reports Server (NTRS)

Kahn, Brian H.; Fishbein, Evan; Nasiri, Shaima L.; Eldering, Annmarie; Fetzer, Eric J.; Garay, Michael J.; Lee, Sung-Yung

2007-01-01

The consistency of cloud top temperature (Tc) and effective cloud fraction (f) retrieved by the Atmospheric Infrared Sounder (AIRS)/Advanced Microwave Sounding Unit (AMSU) observation suite and the Moderate Resolution Imaging Spectroradiometer (MODIS) on the EOS-Aqua platform are investigated. Collocated AIRS and MODIS TC and f are compared via an 'effective scene brightness temperature' (Tb,e). Tb,e is calculated with partial field of view (FOV) contributions from TC and surface temperature (TS), weighted by f and 1-f, respectively. AIRS reports up to two cloud layers while MODIS reports up to one. However, MODIS reports TC, TS, and f at a higher spatial resolution than AIRS. As a result, pixel-scale comparisons of TC and f are difficult to interpret, demonstrating the need for alternatives such as Tb,e. AIRS-MODIS Tb,e differences ((Delta)Tb,e) for identical observing scenes are useful as a diagnostic for cloud quantity comparisons. The smallest values of DTb,e are for high and opaque clouds, with increasing scatter in (Delta)Tb,e for clouds of smaller opacity and lower altitude. A persistent positive bias in DTb,e is observed in warmer and low-latitude scenes, characterized by a mixture of MODIS CO2 slicing and 11-mm window retrievals. These scenes contain heterogeneous cloud cover, including mixtures of multilayered cloudiness and misplaced MODIS cloud top pressure. The spatial patterns of (Delta)Tb,e are systematic and do not correlate well with collocated AIRS-MODIS radiance differences, which are more random in nature and smaller in magnitude than (Delta)Tb,e. This suggests that the observed inconsistencies in AIRS and MODIS cloud fields are dominated by retrieval algorithm differences, instead of differences in the observed radiances. The results presented here have implications for the validation of cloudy satellite retrieval algorithms, and use of cloud products in quantitative analyses.

Intercomparisons of Marine Boundary Layer Cloud Properties from the ARM CAP-MBL Campaign and Two MODIS Cloud Products

NASA Technical Reports Server (NTRS)

Zhang, Zhibo; Dong, Xiquan; Xi, Baike; Song, Hua; Ma, Po-Lun; Ghan, Steven J.; Platnick, Steven; Minnis, Patrick

2017-01-01

From April 2009 to December 2010, the Department of Energy (DOE) Atmospheric Radiation Measurement (ARM) program carried out an observational field campaign on Graciosa Island, targeting the marine boundary layer (MBL) clouds over the Azores region. In this paper, we present an inter-comparison of the MBL cloud properties, namely, cloud liquid water path (LWP), cloud optical thickness (COT) and cloud-droplet effective radius (CER), among retrievals from the ARM mobile facility (AMF) and two Moderate Resolution Spectroradiometer (MODIS) cloud products (GSFC-MODIS and CERES-MODIS). A total of 63 daytime single-layer MBL cloud cases are selected for inter-comparison. Comparison of collocated retrievals indicates that the two MODIS cloud products agree well on both COT and CER retrievals, with the correlation coefficient R greater than 0.95 despite their significant difference in spatial sampling. In both MODIS products, the CER retrievals based on the 2.1 micrometers band (CER(sub 2.1)) is significantly smaller than that based on the 3.7 micrometers band (CER(sub 3.7)). The GSFC-MODIS cloud product is collocated and compared with ground-based ARM observations at several temporal spatial scales. In general, the correlation increases with more precise collocation. For the 63 selected MBL cloud cases, the GSFC-MODIS LWP and COT retrievals agree reasonably well with the ground-based observations with no apparent bias and correlation coefficient R around 0.85 and 0.70, respectively. However, GSFC-MODIS CER(sub 3.7) and CER(sub 2.1) retrievals have a lower correlation (R is approximately 0.5) with the ground-based retrievals. For the 63 selected cases, they are on average larger than ground observations by about 1.5 micrometers and 3.0 micrometers, respectively. Taking into account that the MODIS CER retrievals are only sensitive to cloud top reduces the bias only by 0.5 micrometers.

The Blue Marble

NASA Technical Reports Server (NTRS)

2002-01-01

This spectacular Moderate Resolution Imaging Spectroradiometer (MODIS) 'blue marble' image is based on the most detailed collection of true-color imagery of the entire Earth to date. Using a collection of satellite-based observations, scientists and visualizers stitched together months of observations of the land surface, oceans, sea ice, and clouds into a seamless, true-color mosaic of every square kilometer (.386 square mile) of our planet. Most of the information contained in this image came from MODIS, illustrating MODIS' outstanding capacity to act as an integrated tool for observing a variety of terrestrial, oceanic, and atmospheric features of the Earth. The land and coastal ocean portions of this image is based on surface observations collected from June through September 2001 and combined, or composited, every eight days to compensate for clouds that might block the satellite's view on any single day. Global ocean color (or chlorophyll) data was used to simulate the ocean surface. MODIS doesn't measure 3-D features of the Earth, so the surface observations were draped over topographic data provided by the U.S. Geological Survey EROS Data Center. MODIS observations of polar sea ice were combined with observations of Antarctica made by the National Oceanic and Atmospheric Administration's AVHRR sensor-the Advanced Very High Resolution Radiometer. The cloud image is a composite of two days of MODIS imagery collected in visible light wavelengths and a third day of thermal infra-red imagery over the poles. A large collection of imagery based on the blue marble in a variety of sizes and formats, including animations and the full (1 km) resolution imagery, is available at the Blue Marble page. Image by Reto Stockli, Render by Robert Simmon. Based on data from the MODIS Science Team

Analysis of the Electronic Crosstalk Effect in Terra MODIS Long-Wave Infrared Photovoltaic Bands Using Lunar Images

NASA Technical Reports Server (NTRS)

Wilson, Truman; Wu, Aisheng; Wang, Zhipeng; Xiong, Xiaoxiong

2016-01-01

The Moderate Resolution Imaging Spectroradiometer (MODIS) is one of the key sensors among the suite of remote sensing instruments on board the Earth Observing System Terra and Aqua spacecrafts. For each MODIS spectral band, the sensor degradation has been measured using a set of on-board calibrators. MODIS also uses lunar observations from nearly monthly spacecraft maneuvers, which bring the Moon into view through the space-view port, helping to characterize the scan mirror degradation at a different angles of incidence. Throughout the Terra mission, contamination of the long-wave infrared photovoltaic band (LWIR PV, bands 27-30) signals has been observed in the form of electronic crosstalk, where signal from each of the detectors among the LWIR PV bands can leak to the other detectors, producing a false signal contribution. This contamination has had a noticeable effect on the MODIS science products since 2010 for band 27, and since 2012 for bands 28 and 29. Images of the Moon have been used effectively for determining the contaminating bands, and have also been used to derive correction coefficients for the crosstalk contamination. In this paper, we introduce an updated technique for characterizing the crosstalk contamination among the LWIR PV bands using data from lunar calibration events. This approach takes into account both the in-band and out-of-band contribution to the signal contamination for each detector in bands 27-30, which is not considered in previous works. The crosstalk coefficients can be derived for each lunar calibration event, providing the time dependence of the crosstalk contamination. Application of these coefficients to Earth-view image data results in a significant reduction in image contamination and a correction of the scene radiance for bands 27- 30. Also, this correction shows a significant improvement to certain threshold tests in the MODIS Level-2 Cloud Mask. In this paper, we will detail the methodology used to identify and correct the crosstalk contamination for the LWIR PV bands in Terra MODIS. The derived time-dependent crosstalk coefficients will also be discussed. Finally, the impact of the correction on the downstream data products will be analyzed.

Remote sensing of cloud, aerosol and water vapor properties from the Moderate Resolution Imaging Spectrometer (MODIS)

NASA Technical Reports Server (NTRS)

King, M. D.

1992-01-01

The Moderate Resolution Imaging Spectrometer (MODIS) is an Earth-viewing sensor being developed as a facility instrument for the Earth Observing System (EOS) to be launched in the late 1990s. MODIS consists of two separate instruments that scan 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. Of primary interest for studies of atmospheric physics is the MODIS-N (nadir) instrument which will provide images in 36 spectral bands between 0.415 and 14.235 micrometers with spatial resoulutions 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 atmosperhic processes. The intent of this lecture is to describe the current status of MODIS-N and its companion instrument MODIS-T (tilt), a tiltable cross-track scanning radiometer with 32 uniformly spaced channels between 0.410 and 0.875 micrometers, and to describe the physical principles behind the development of MODIS for the remote sensing of atmospheric properties. Primary emphasis will be placed on the main atmospheric applications of determining the optical, microphysical and physical properties of clouds and aerosol particles form spectral-reflection and thermal-emission measurements. In addition to cloud and aerosol properties, MODIS-N will be utilized for the determination of the total precipitable water vapor over land and atmospheric stability. The physical principles behind the determination of each of these atmospheric products will be described herein.

A Geostatistical Data Fusion Technique for Merging Remote Sensing and Ground-Based Observations of Aerosol Optical Thickness

NASA Technical Reports Server (NTRS)

Chatterjee, Abhishek; Michalak, Anna M.; Kahn, Ralph A.; Paradise, Susan R.; Braverman, Amy J.; Miller, Charles E.

2010-01-01

Particles in the atmosphere reflect incoming sunlight, tending to cool the Earth below. Some particles, such as soot, also absorb sunlight, which tens to warm the ambient atmosphere. Aerosol optical depth (AOD) is a measure of the amount of particulate matter in the atmosphere, and is a key input to computer models that simulate and predict Earth's changing climate. The global AOD products from the Multi-angle Imaging SpectroRadiometer (MISR) and the MODerate resolution Imaging Spectroradiometer (MODIS), both of which fly on the NASA Earth Observing System's Terra satellite, provide complementary views of the particles in the atmosphere. Whereas MODIS offers global coverage about four times as frequent as MISR, the multi-angle data makes it possible to separate the surface and atmospheric contributions to the observed top-of-atmosphere radiances, and also to more effectively discriminate particle type. Surface-based AERONET sun photometers retrieve AOD with smaller uncertainties than the satellite instruments, but only at a few fixed locations. So there are clear reasons to combine these data sets in a way that takes advantage of their respective strengths. This paper represents an effort at combining MISR, MODIS and AERONET AOD products over the continental US, using a common spatial statistical technique called kriging. The technique uses the correlation between the satellite data and the "ground-truth" sun photometer observations to assign uncertainty to the satellite data on a region-by-region basis. The larger fraction of the sun photometer variance that is duplicated by the satellite data, the higher the confidence assigned to the satellite data in that region. In the Western and Central US, MISR AOD correlation with AERONET are significantly higher than those with MODIS, likely due to bright surfaces in these regions, which pose greater challenges for the single-view MODIS retrievals. In the east, MODIS correlations are higher, due to more frequent sampling of the varying AOD. These results demonstrate how the MISR and MODIS aerosol products are complementary. The underlying technique also provides one method for combining these products in such a way that takes advantage of the strengths of each, in the places and times when they are maximal, and in addition, yields an estimate of the associated uncertainties in space and time.

Comparison of Envisat ASAR GM, AMSR-E Passive Microwave, and MODIS Optical Remote Sensing for Flood Monitoring in Australia

NASA Astrophysics Data System (ADS)

Ticehurst, C. J.; Bartsch, A.; Doubkova, M.; van Dijk, A. I. J. M.

2009-11-01

Continuous flood monitoring can support emergency response, water management and environmental monitoring. Optical sensors such as MODIS allow inundation mapping with high spatial and temporal resolution (250-1000 m, twice daily) but are affected by cloud cover. Passive microwave sensors also acquire observations at high temporal resolution, but coarser spatial resolution (e.g. ca. 5-70 km for AMSR-E) and smaller footprints are also affected by cloud and/or rain. ScanSAR systems allow all-weather monitoring but require spatial resolution to be traded off against coverage and/or temporal resolution; e.g. the ENVISAT ASAR Global Mode observes at ca. 1 km over large regions about twice a week. The complementary role of the AMSR-E and ASAR GM data to that of MODIS is here introduced for three flood events and locations across Australia. Additional improvements can be made by integrating digital elevation models and stream flow gauging data.

Application and Evaluation of MODIS LAI, FPAR, and Albedo Products in the WRF/CMAQ System

EPA Science Inventory

MODIS vegetation and albedo products provide a more realistic representation of surface conditions for input to the WRF/CMAQ modeling system. However, the initial evaluation of ingesting MODIS data into the system showed mixed results, with increased bias and error for 2-m temper...

MODIS Interactive Subsetting Tool (MIST)

NASA Astrophysics Data System (ADS)

McAllister, M.; Duerr, R.; Haran, T.; Khalsa, S. S.; Miller, D.

2008-12-01

In response to requests from the user community, NSIDC has teamed with the Oak Ridge National Laboratory Distributive Active Archive Center (ORNL DAAC) and the Moderate Resolution Data Center (MrDC) to provide time series subsets of satellite data covering stations in the Greenland Climate Network (GC-NET) and the International Arctic Systems for Observing the Atmosphere (IASOA) network. To serve these data NSIDC created the MODIS Interactive Subsetting Tool (MIST). MIST works with 7 km by 7 km subset time series of certain Version 5 (V005) MODIS products over GC-Net and IASOA stations. User- selected data are delivered in a text Comma Separated Value (CSV) file format. MIST also provides online analysis capabilities that include generating time series and scatter plots. Currently, MIST is a Beta prototype and NSIDC intends that user requests will drive future development of the tool. The intent of this poster is to introduce MIST to the MODIS data user audience and illustrate some of the online analysis capabilities.

Cloud and Aerosol Properties, Precipitable Water, and Profiles of Temperature and Water Vapor from MODIS

NASA Technical Reports Server (NTRS)

King, Michael D.; Menzel, W. Paul; Kaufman, Yoram J.; Tanre, Didier; Gao, Bo-Cai; Platnick, Steven; Ackerman, Steven A.; Remer, Lorraine A.; Pincus, Robert; Hubanks, Paul A.

2003-01-01

The Moderate Resolution Imaging Spectroradiometer (MODIS) is an earth-viewing sensor that flies on the Earth Observing System (EOS) Terra and Aqua satellites, launched in 1999 and 2002, respectively. MODIS scans a swath width of 2330 km that is sufficiently wide to provide nearly complete global coverage every two days from a polar-orbiting, sun-synchronous, platform at an altitude of 705 km. MODIS provides images in 36 spectral bands between 0.415 and 14.235 pm with spatial resolutions of 250 m (2 bands), 500 m (5 bands) and 1000 m (29 bands). These bands have been carefully selected to en- able advanced studies of land, ocean, and atmospheric properties. Twenty-six bands are used to derive atmospheric properties such as cloud mask, atmospheric profiles, aerosol properties, total precipitable water, and cloud properties. In this paper we describe each of these atmospheric data products, including characteristics of each of these products such as file size, spatial resolution used in producing the product, and data availability.

Near Real-time Operational Use of eMODIS Expedited NDVI for Monitoring Applications and Famine Early Warning

NASA Astrophysics Data System (ADS)

Rowland, J.; Budde, M. E.

2010-12-01

The Famine Early Warning Systems Network (FEWS NET) has requirements for near real-time monitoring of vegetation conditions for food security applications. Accurate and timely assessments of crop conditions are an important element of food security decision making. FEWS NET scientists at the U.S. Geological Survey (USGS) Earth Resources Observation and Science (EROS) Center are utilizing a new Moderate Resolution Imaging Spectroradiometer (MODIS) Normalized Difference Vegetation Index (NDVI) dataset for operational monitoring of crop and pasture conditions in parts of the world where food availability is highly dependent on subsistence agriculture and animal husbandry. The expedited MODIS, or eMODIS, production system processes NDVI data using MODIS surface reflectance provided by the Land Atmosphere Near-real-time Capability for EOS (LANCE). Benefits of this production system include customized compositing schedules, near real-time data availability, and minimized re-sampling. FEWS NET has implemented a 10-day compositing scheme every five days to accommodate the need for timely information on vegetation conditions. The data are currently being processed at 250-meter spatial resolution for Central America, Hispaniola, and Africa. Data are further enhanced by the application of a temporal smoothing filter which helps remove contamination due to clouds and other atmospheric effects. The results of this near real-time monitoring capability have been the timely provision of NDVI and NDVI anomaly maps for each of the FEWS NET monitoring regions and the availability of a consistently processed dataset to aid crop assessment missions and to facilitate customized analyses of crop production, drought, and agro-pastoral conditions.

Retrieval of ice cloud properties using an optimal estimation algorithm and MODIS infrared observations: 1. Forward model, error analysis, and information content

NASA Astrophysics Data System (ADS)

Wang, Chenxi; Platnick, Steven; Zhang, Zhibo; Meyer, Kerry; Yang, Ping

2016-05-01

An optimal estimation (OE) retrieval method is developed to infer three ice cloud properties simultaneously: optical thickness (τ), effective radius (reff), and cloud top height (h). This method is based on a fast radiative transfer (RT) model and infrared (IR) observations from the MODerate resolution Imaging Spectroradiometer (MODIS). This study conducts thorough error and information content analyses to understand the error propagation and performance of retrievals from various MODIS band combinations under different cloud/atmosphere states. Specifically, the algorithm takes into account four error sources: measurement uncertainty, fast RT model uncertainty, uncertainties in ancillary data sets (e.g., atmospheric state), and assumed ice crystal habit uncertainties. It is found that the ancillary and ice crystal habit error sources dominate the MODIS IR retrieval uncertainty and cannot be ignored. The information content analysis shows that for a given ice cloud, the use of four MODIS IR observations is sufficient to retrieve the three cloud properties. However, the selection of MODIS IR bands that provide the most information and their order of importance varies with both the ice cloud properties and the ambient atmospheric and the surface states. As a result, this study suggests the inclusion of all MODIS IR bands in practice since little a priori information is available.

Retrieval of ice cloud properties using an optimal estimation algorithm and MODIS infrared observations. Part I: Forward model, error analysis, and information content.

PubMed

Wang, Chenxi; Platnick, Steven; Zhang, Zhibo; Meyer, Kerry; Yang, Ping

2016-05-27

An optimal estimation (OE) retrieval method is developed to infer three ice cloud properties simultaneously: optical thickness ( τ ), effective radius ( r eff ), and cloud-top height ( h ). This method is based on a fast radiative transfer (RT) model and infrared (IR) observations from the MODerate resolution Imaging Spectroradiometer (MODIS). This study conducts thorough error and information content analyses to understand the error propagation and performance of retrievals from various MODIS band combinations under different cloud/atmosphere states. Specifically, the algorithm takes into account four error sources: measurement uncertainty, fast RT model uncertainty, uncertainties in ancillary datasets (e.g., atmospheric state), and assumed ice crystal habit uncertainties. It is found that the ancillary and ice crystal habit error sources dominate the MODIS IR retrieval uncertainty and cannot be ignored. The information content analysis shows that, for a given ice cloud, the use of four MODIS IR observations is sufficient to retrieve the three cloud properties. However, the selection of MODIS IR bands that provide the most information and their order of importance varies with both the ice cloud properties and the ambient atmospheric and the surface states. As a result, this study suggests the inclusion of all MODIS IR bands in practice since little a priori information is available.

Analysis of Rosetta/VIRTIS spectra of earth using observations from ENVISAT/AATSR, TERRA/MODIS and ENVISAT/SCIAMACHY, and radiative-transfer simulations

NASA Astrophysics Data System (ADS)

Hurley, J.; Irwin, P. G. J.; Adriani, A.; Moriconi, M.; Oliva, F.; Capaccioni, F.; Smith, A.; Filacchione, G.; Tosi, F.; Thomas, G.

2014-01-01

Rosetta, the Solar System cornerstone mission of ESA's Horizon 2000 programme, consists of an orbiter and a lander, and is due to arrive at the comet 67P/Churyumov-Gerasimenko in May 2014. Following its 2004 launch, Rosetta carried out a series of planetary fly-bys and gravitational assists. On these close fly-bys of the Earth, measurements were taken by the Visible Infrared Thermal Imaging Spectrometer (VIRTIS). Analysis of these spectra and comparison with spectra acquired by Earth-observing satellites can support the verification of the inflight calibration of Rosetta/VIRTIS. In this paper, measurements taken by VIRTIS in November 2009 are compared with suitable coincident data from Earth-observing instruments (ESA-ENVISAT/AATSR and SCIAMACHY, and EOS-TERRA/MODIS). Radiative transfer simulations using NEMESIS (Irwin et al., 2008) are fit to the fly-by data taken by VIRTIS, using representative atmospheric and surface parameters. VIRTIS measurements correlate 90% with AATSR's, 85-94% with MODIS, and 82-88% with SCIAMACHYs. The VIRTIS spectra are reproducible in the 1-5 μm region, except in the 1.4 μm deep water vapour spectral absorption band in the near-infrared in cases in which the radiance is very low (cloud-free topographies), where VIRTIS consistently registers more radiance than do MODIS and SCIAMACHY. Over these cloud-free regions, VIRTIS registers radiances a factor of 3-10 larger than SCIAMACHY and of 3-8 greater than MODIS. It is speculated that this discrepancy could be due to a spectral light leak originating from reflections from the order-sorting filters above the detector around 1.4 μm.

MODIS. Volume 1: MODIS level 1A software baseline requirements

NASA Technical Reports Server (NTRS)

Masuoka, Edward; Fleig, Albert; Ardanuy, Philip; Goff, Thomas; Carpenter, Lloyd; Solomon, Carl; Storey, James

1994-01-01

This document describes the level 1A software requirements for the moderate resolution imaging spectroradiometer (MODIS) instrument. This includes internal and external requirements. Internal requirements include functional, operational, and data processing as well as performance, quality, safety, and security engineering requirements. External requirements include those imposed by data archive and distribution systems (DADS); scheduling, control, monitoring, and accounting (SCMA); product management (PM) system; MODIS log; and product generation system (PGS). Implementation constraints and requirements for adapting the software to the physical environment are also included.

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

NASA Technical Reports Server (NTRS)

Riggs, George A.; Hall, Dorothy K.; Roman, Miguel O.

2017-01-01

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

Cloud Statistics and Discrimination in the Polar Regions

NASA Astrophysics Data System (ADS)

Chan, M.; Comiso, J. C.

2012-12-01

Despite their important role in the climate system, cloud cover and their statistics are poorly known, especially in the polar regions, where clouds are difficult to discriminate from snow covered surfaces. The advent of the A-train, which included Aqua/MODIS, CALIPSO/CALIOP and CloudSat/CPR sensors has provided an opportunity to improve our ability to accurately characterize the cloud cover. MODIS provides global coverage at a relatively good temporal and spatial resolution while CALIOP and CPR provide limited nadir sampling but accurate characterization of the vertical structure and phase of the cloud cover. Over the polar regions, cloud detection from a passive sensors like MODIS is challenging because of the presence of cold and highly reflective surfaces such as snow, sea-ice, glaciers, and ice-sheet, which have surface signatures similar to those of clouds. On the other hand, active sensors such as CALIOP and CPR are not only very sensitive to the presence of clouds but can also provide information about its microphysical characteristics. However, these nadir-looking sensors have sparse spatial coverage and their global data can have data spatial gaps of up to 100 km. We developed a polar cloud detection system for MODIS that is trained using collocated data from CALIOP and CPR. In particular, we employ a machine learning system that reads the radiative profile observed by MODIS and determine whether the field of view is cloudy or clear. Results have shown that the improved cloud detection scheme performs better than typical cloud mask algorithms using a validation data set not used for training. A one-year data set was generated and results indicate that daytime cloud detection accuracies improved from 80.1% to 92.6% (over sea-ice) and 71.2% to 87.4% (over ice-sheet) with CALIOP data used as the baseline. Significant improvements are also observed during nighttime, where cloud detection accuracies increase by 19.8% (over sea-ice) and 11.6% (over ice-sheet). The immediate impact of the new algorithm is that it can minimize large biases of MODIS-derived cloud amount over the Polar Regions and thus a more realistic and high quality global cloud statistics. In particular, our results show that cloud fraction in the Arctic is typically 81.2 % during daytime and 84.0% during nighttime. This is significantly higher than the 71.8% and 58.5%, respectively, derived from standard MODIS cloud product.

MODIS Snow and Ice Products from the NSIDC DAAC

NASA Technical Reports Server (NTRS)

Scharfen, Greg R.; Hall, Dorothy K.; Riggs, George A.

1997-01-01

The National Snow and Ice Data Center (NSIDC) Distributed Active Archive Center (DAAC) provides data and information on snow and ice processes, especially pertaining to interactions among snow, ice, atmosphere and ocean, in support of research on global change detection and model validation, and provides general data and information services to cryospheric and polar processes research community. The NSIDC DAAC is an integral part of the multi-agency-funded support for snow and ice data management services at NSIDC. The Moderate Resolution Imaging Spectroradiometer (MODIS) will be flown on the first Earth Observation System (EOS) platform (AM-1) in 1998. The MODIS Instrument Science Team is developing geophysical products from data collected by the MODIS instrument, including snow and ice products which will be archived and distributed by NSIDC DAAC. The MODIS snow and ice mapping algorithms will generate global snow, lake ice, and sea ice cover products on a daily basis. These products will augment the existing record of satellite-derived snow cover and sea ice products that began about 30 years ago. The characteristics of these products, their utility, and comparisons to other data set are discussed. Current developments and issues are summarized.

Clinical differences between patients with MODY-3, MODY-2 and type 2 diabetes mellitus with I27L polymorphism in the HNF1alpha gene.

PubMed

Pinés Corrales, Pedro José; López Garrido, María P; Aznar Rodríguez, Silvia; Louhibi Rubio, Lynda; López Jiménez, Luz M; Lamas Oliveira, Cristina; Alfaro Martínez, Jose J; Lozano García, Jose J; Hernández López, Antonio; Requejo Castillo, Ramón; Escribano Martínez, Julio; Botella Romero, Francisco

2010-01-01

The aim of our study was to describe and evaluate the clinical and metabolic characteristics of patients with MODY-3, MODY-2 or type 2 diabetes who presented I27L polymorphism in the HNF1alpha gene. The study included 31 previously diagnosed subjects under follow-up for MODY-3 (10 subjects from 5 families), MODY-2 (15 subjects from 9 families), or type 2 diabetes (6 subjects) with I27L polymorphism in the HNF1alpha gene. The demographic, clinical, metabolic, and genetic characteristics of all patients were analyzed. No differences were observed in distribution according to sex, age of onset, or form of diagnosis. All patients with MODY-2 or MODY-3 had a family history of diabetes. In contrast, 33.3% of patients with type 2 diabetes mellitus and I27L polymorphism in the HNF1alpha gene had no family history of diabetes (p < 0.05). No differences were observed in body mass index, prevalence of hypertension, or microvascular or macrovascular complications. Drug therapy was required by 100% of MODY-3 patients, but not required by 100% of MODY-2 patients or 16.7% of patients with type 2 diabetes mellitus and I27L polymorphism in the HNF1alpha gene (p < 0.05). Occasional difficulties may be encountered when classifying patients with MODY-2, MODY-3 or type 2 diabetes of atypical characteristics, in this case patients who present I27L polymorphism in the HNF1alpha gene. Copyright 2010 Sociedad Española de Endocrinología y Nutrición. Published by Elsevier Espana. All rights reserved.

Use of MODIS Cloud Top Pressure to Improve Assimilation Yields of AIRS Radiances in GSI

NASA Technical Reports Server (NTRS)

Zavodsky, Bradley; Srikishen, Jayanthi

2014-01-01

Radiances from hyperspectral sounders such as the Atmospheric Infrared Sounder (AIRS) are routinely assimilated both globally and regionally in operational numerical weather prediction (NWP) systems using the Gridpoint Statistical Interpolation (GSI) data assimilation system. However, only thinned, cloud-free radiances from a 281-channel subset are used, so the overall percentage of these observations that are assimilated is somewhere on the order of 5%. Cloud checks are performed within GSI to determine which channels peak above cloud top; inaccuracies may lead to less assimilated radiances or introduction of biases from cloud-contaminated radiances.Relatively large footprint from AIRS may not optimally represent small-scale cloud features that might be better resolved by higher-resolution imagers like the Moderate Resolution Imaging Spectroradiometer (MODIS). Objective of this project is to "swap" the MODIS-derived cloud top pressure (CTP) for that designated by the AIRS-only quality control within GSI to test the hypothesis that better representation of cloud features will result in higher assimilated radiance yields and improved forecasts.

AVHRR, MODIS, and VIIRS radiometric stability and consistency in SST bands

NASA Astrophysics Data System (ADS)

Liang, XingMing; Ignatov, Alexander

2013-06-01

Monitoring of IR Clear-Sky Radiances over Oceans for SST (MICROS; www.star.nesdis.noaa.gov/sod/sst/micros) is NESDIS near-real time web-based radiance monitoring system. It analyzes Model (Community Radiative Transfer Model, CRTM) minus Observation (M-O) biases in brightness temperatures (BT) in three bands centered at 3.7 (IR37), 11 (IR11), and 12 µm (IR12), for several AVHRR (NOAA-16, -17, -18, -19, Metop-A, -B), VIIRS (Suomi National Polar Partnership, S-NPP), and MODIS (Terra, Aqua) sensors. Double-differences (DD) are employed to check BTs for radiometric stability and consistency. All sensors are stable, with the exception of two AVHRRs, onboard NOAA-16 and to a lesser extent NOAA-18, and generally consistent. VIIRS onboard S-NPP, launched in October 2011, is well in-family, especially after its calibration was fine-tuned on 7 March 2012. MODIS M-O biases were initially out-of-family by up to -0.6 K, due to incorrect CRTM transmittance coefficients. Following MICROS feedback, CRTM Team updated coefficients and brought MODIS back in-family. Terra and Aqua BTs are very consistent in IR11 and IR12 but show cross-platform bias of 0.3 K in IR37, likely attributed to MODIS characterization. Work with MODIS Characterization Support Team is underway to resolve this. Initial analyses of AVHRR onboard Metop-B launched in September 2012 suggest that its BTs are offset from Metop-A by up to ˜0.3 K. Overall, MICROS DDs are well suited to evaluate the sensors stability, but dedicated effort is needed to ensure consistent radiative transfer modeling (RTM) calculations for various sensors before DDs can be used in Global Space-based Inter-Calibration System (GSICS) quantitative applications.

Global inter-comparison of microwave and infrared LST from multiple sensors (AMSR-E, MODIS, SEVIRI, GOES, and MTSAT-2)

NASA Astrophysics Data System (ADS)

Ermida, Sofia L.; Jiménez, Carlos; Prigent, Catherine; Trigo, Isabel F.; DaCamara, Carlos C.

2017-04-01

Land Surface Temperature (LST) is an important diagnostic parameter of land surface conditions. Satellite LST products generally rely on measurements in the thermal infrared (IR) atmospheric window, which only allows clear sky estimates. Microwave (MW) observations can alternatively be used to derive an all-weather LST. Here we present an inter-comparison between LST derived from the Advanced Microwave Scanning Radiometer - Earth observation system (AMSR-E), the MODerate resolution Imaging Spectroradiometer (MODIS) on-board Aqua, the Spinning Enhanced Visible and Infrared Imager (SEVIRI) on-board Meteosat Second Generation (MSG) satellites, the Geostationary Operational Environmental Satellite (GOES) and the Japanese Meteorological Imager (JAMI) on-board the Multifunction Transport SATellite (MTSAT-2). The higher discrepancies between MW and IR products are observed over snow covered areas. MW emissivity is highly variable for snow-covered ground and not always properly accounted for by the climatological emissivity used in the retrieval. There is a conspicuous bias between MODIS and AMSR-E over desert areas, which is most likely related to the underestimation of LST by MODIS as previously reported in other studies. Inter-comparison between all IR and MW retrievals shows that the STD of the differences between MW and IR LST is generally higher than between IR retrievals. However, the biases between MW and IR LST are, in some cases, of the same order as the ones observed among infrared products. In particular, GOES presents a daytime bias with respect to AMSR-E of 0.45 K whereas the bias with respect to MODIS is 0.60 K. Given that AMSR-E can provide LST under cloudy conditions, the use of microwaves, considering simultaneous overpasses with IR, represents an increase of more than 250% of the number of available LST estimates over equatorial regions. With the MW products of a comparable quality to the IR ones, the MW LST is a very powerful complement of the IR estimates.

Merging the MODIS and NESDIS Monthly Snow-Cover Records to Study Decade-Scale Changes in Northern Hemisphere Snow Cover

NASA Technical Reports Server (NTRS)

Hall, Dorothy K.; Foster, James L.; Robinson, David A.; Riggs, George A.

2004-01-01

A decade-scale record of Northern Hemisphere snow cover has been available from the National Oceanic and Atmospheric Administration (NOAA) National Environmental Satellite Data and Information Service (NESDIS) and has been reconstructed and validated by Rutgers University following adjustments for inconsistencies that were discovered in the early years of the data set. This record provides weekly, monthly (and, in recent years, daily) snow cover from 1966 to the present for the Northern Hemisphere. With the December 1999 launch of NASA's Earth observing System (EOS) Terra satellite, snow maps are being produced globally, using automated algorithms, on a daily, weekly and monthly basis from the Moderate-Resolution Imaging Spectroradiometer (MODIS) instrument. The resolution of the MODIS monthly snow maps (0.05deg or about 5 km) is an improvement over that of the NESDIS-derived monthly snow maps (>approx.10 km) the maps, it is necessary to study the datasets carefully to determine if it is possible to merge the datasets into a continuous record. The months in which data are available for both the NESDIS and MODIS maps (March 2000 to the present) will be compared quantitatively to analyze differences in North American and Eurasian snow cover. Results from the NESDIS monthly maps show that for North America (including all 12 months), there is a trend toward slightly less snow cover in each succeeding decade. Interannual snow-cover extent has varied significantly since 2000 as seen in both the NESDIS and MODIS maps. As the length of the satellite record increases through the MODIS era, and into the National Polar-orbiting Environmental Satellite System (NPOESS) era, it should become easier to identify trends in areal extent of snow cover, if present, that may have climatic significance. Thus it is necessary to analyze the validity of merging the NESDIS and MODIS, and, in the future, the NPOESS datasets for determination of long-term continuity in measurement of Northern Hemisphere snow cover.

eMODIS Expedited: Overview of a Near Real Time MODIS Production System for Operational Vegetation Monitoring

NASA Astrophysics Data System (ADS)

Jenkerson, C.; Meyer, D. J.; Werpy, J.; Evenson, K.; Merritt, M.

2010-12-01

The expedited MODIS, or eMODIS production system derives near-real time Normalized Difference Vegetation Index (NDVI) from Moderate Resolution Imaging Spectroradiometer (MODIS) surface reflectance 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 eMODIS 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/eMODIS) allows users direct access to eMODIS 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.

Reconciling Simulated and Observed Views of Clouds: MODIS, ISCCP, and the Limits of Instrument Simulators in Climate Models

NASA Technical Reports Server (NTRS)

Pincus, Robert; Platnick, Steven E.; Ackerman, Steve; Hemler, Richard; Hofmann, Patrick

2011-01-01

The properties of clouds that may be observed by satellite instruments, such as optical depth and cloud top pressure, are only loosely related to the way clouds are represented in models of the atmosphere. One way to bridge this gap is through "instrument simulators," diagnostic tools that map the model representation to synthetic observations so that differences between simulator output and observations can be interpreted unambiguously as model error. But simulators may themselves be restricted by limited information available from the host model or by internal assumptions. This work examines the extent to which instrument simulators are able to capture essential differences between MODIS and ISCCP, two similar but independent estimates of cloud properties. We focus on the stark differences between MODIS and ISCCP observations of total cloudiness and the distribution of cloud optical thickness can be traced to different approaches to marginal pixels, which MODIS excludes and ISCCP treats as homogeneous. These pixels, which likely contain broken clouds, cover about 15% of the planet and contain almost all of the optically thinnest clouds observed by either instrument. Instrument simulators can not reproduce these differences because the host model does not consider unresolved spatial scales and so can not produce broken pixels. Nonetheless, MODIS and ISCCP observation are consistent for all but the optically-thinnest clouds, and models can be robustly evaluated using instrument simulators by excluding ambiguous observations.

Comparative Analysis of Aerosol Retrievals from MODIS, OMI and MISR Over Sahara Region

NASA Technical Reports Server (NTRS)

Lyapustin, A.; Wang, Y.; Hsu, C.; Terres, O.; Leptoukh, G.; Kalashnikova, O.; Korkin, S.

2011-01-01

MODIS is a wide field-of-view sensor providing daily global observations of the Earth. Currently, global MODIS aerosol retrievals over land are performed with the main Dark Target algorithm complimented with the Deep Blue (DB) Algorithm over bright deserts. The Dark Target algorithm relies on surface parameterization which relates reflectance in MODIS visible bands with the 2.1 micrometer region, whereas the Deep Blue algorithm uses an ancillary angular distribution model of surface reflectance developed from the time series of clear-sky MODIS observations. Recently, a new Multi-Angle Implementation of Atmospheric Correction (MAIAC) algorithm has been developed for MODIS. MAIAC uses a time series and an image based processing to perform simultaneous retrievals of aerosol properties and surface bidirectional reflectance. It is a generic algorithm which works over both dark vegetative surfaces and bright deserts and performs retrievals at 1 km resolution. In this work, we will provide a comparative analysis of DB, MAIAC, MISR and OMI aerosol products over bright deserts of northern Africa.

Cloud Retrieval Intercomparisons Between SEVIRI, MODIS and VIIRS with CHIMAERA PGE06 Data Collection 6 Products

NASA Technical Reports Server (NTRS)

Wind, Galina; Riedi, Jerome; Platnick, Steven; Heidinger, Andrew

2014-01-01

The Cross-platform HIgh resolution Multi-instrument AtmosphEric Retrieval Algorithms (CHIMAERA) system allows us to perform MODIS-like cloud top, optical and microphysical properties retrievals on any sensor that possesses a minimum set of common spectral channels. The CHIMAERA system uses a shared-core architecture that takes retrieval method out of the equation when intercomparisons are made. Here we show an example of such retrieval and a comparison of simultaneous retrievals done using SEVIRI, MODIS and VIIRS sensors. All sensor retrievals are performed using CLAVR-x (or CLAVR-x based) cloud top properties algorithm. SEVIRI uses the SAF_NWC cloud mask. MODIS and VIIRS use the IFF-based cloud mask that is a shared algorithm between MODIS and VIIRS. The MODIS and VIIRS retrievals are performed using a VIIRS branch of CHIMAERA that limits available MODIS channel set. Even though in that mode certain MODIS products such as multilayer cloud map are not available, the cloud retrieval remains fully equivalent to operational Data Collection 6.

Retrieval of ice cloud properties using an optimal estimation algorithm and MODIS infrared observations. Part I: Forward model, error analysis, and information content

PubMed Central

Wang, Chenxi; Platnick, Steven; Zhang, Zhibo; Meyer, Kerry; Yang, Ping

2018-01-01

An optimal estimation (OE) retrieval method is developed to infer three ice cloud properties simultaneously: optical thickness (τ), effective radius (reff), and cloud-top height (h). This method is based on a fast radiative transfer (RT) model and infrared (IR) observations from the MODerate resolution Imaging Spectroradiometer (MODIS). This study conducts thorough error and information content analyses to understand the error propagation and performance of retrievals from various MODIS band combinations under different cloud/atmosphere states. Specifically, the algorithm takes into account four error sources: measurement uncertainty, fast RT model uncertainty, uncertainties in ancillary datasets (e.g., atmospheric state), and assumed ice crystal habit uncertainties. It is found that the ancillary and ice crystal habit error sources dominate the MODIS IR retrieval uncertainty and cannot be ignored. The information content analysis shows that, for a given ice cloud, the use of four MODIS IR observations is sufficient to retrieve the three cloud properties. However, the selection of MODIS IR bands that provide the most information and their order of importance varies with both the ice cloud properties and the ambient atmospheric and the surface states. As a result, this study suggests the inclusion of all MODIS IR bands in practice since little a priori information is available. PMID:29707470

Retrieval of Ice Cloud Properties Using an Optimal Estimation Algorithm and MODIS Infrared Observations. Part I: Forward Model, Error Analysis, and Information Content

NASA Technical Reports Server (NTRS)

Wang, Chenxi; Platnick, Steven; Zhang, Zhibo; Meyer, Kerry; Yang, Ping

2016-01-01

An optimal estimation (OE) retrieval method is developed to infer three ice cloud properties simultaneously: optical thickness (tau), effective radius (r(sub eff)), and cloud-top height (h). This method is based on a fast radiative transfer (RT) model and infrared (IR) observations from the MODerate resolution Imaging Spectroradiometer (MODIS). This study conducts thorough error and information content analyses to understand the error propagation and performance of retrievals from various MODIS band combinations under different cloud/atmosphere states. Specifically, the algorithm takes into account four error sources: measurement uncertainty, fast RT model uncertainty, uncertainties in ancillary datasets (e.g., atmospheric state), and assumed ice crystal habit uncertainties. It is found that the ancillary and ice crystal habit error sources dominate the MODIS IR retrieval uncertainty and cannot be ignored. The information content analysis shows that, for a given ice cloud, the use of four MODIS IR observations is sufficient to retrieve the three cloud properties. However, the selection of MODIS IR bands that provide the most information and their order of importance varies with both the ice cloud properties and the ambient atmospheric and the surface states. As a result, this study suggests the inclusion of all MODIS IR bands in practice since little a priori information is available.

Retrieval of Ice Cloud Properties Using an Optimal Estimation Algorithm and MODIS Infrared Observations. Part I: Forward Model, Error Analysis, and Information Content

NASA Technical Reports Server (NTRS)

Wang, Chenxi; Platnick, Steven; Zhang, Zhibo; Meyer, Kerry; Yang, Ping

2016-01-01

An optimal estimation (OE) retrieval method is developed to infer three ice cloud properties simultaneously: optical thickness (tau), effective radius (r(sub eff)), and cloud top height (h). This method is based on a fast radiative transfer (RT) model and infrared (IR) observations from the MODerate resolution Imaging Spectroradiometer (MODIS). This study conducts thorough error and information content analyses to understand the error propagation and performance of retrievals from various MODIS band combinations under different cloud/atmosphere states. Specifically, the algorithm takes into account four error sources: measurement uncertainty, fast RT model uncertainty, uncertainties in ancillary data sets (e.g., atmospheric state), and assumed ice crystal habit uncertainties. It is found that the ancillary and ice crystal habit error sources dominate the MODIS IR retrieval uncertainty and cannot be ignored. The information content analysis shows that for a given ice cloud, the use of four MODIS IR observations is sufficient to retrieve the three cloud properties. However, the selection of MODIS IR bands that provide the most information and their order of importance varies with both the ice cloud properties and the ambient atmospheric and the surface states. As a result, this study suggests the inclusion of all MODIS IR bands in practice since little a priori information is available.

Simultaneous Assimilation of AMSR-E Brightness Temperature and MODIS LST to Improve Soil Moisture with Dual Ensemble Kalman Smoother

NASA Astrophysics Data System (ADS)

Huang, Chunlin; Chen, Weijin; Wang, Weizhen; Gu, Juan

2017-04-01

Uncertainties in model parameters can easily cause systematic differences between model states and observations from ground or satellites, which significantly affect the accuracy of soil moisture estimation in data assimilation systems. In this paper, a novel soil moisture assimilation scheme is developed to simultaneously assimilate AMSR-E brightness temperature (TB) and MODIS Land Surface Temperature (LST), which can correct model bias by simultaneously updating model states and parameters with dual ensemble Kalman filter (DEnKS). The Common Land Model (CoLM) and a Q-h Radiative Transfer Model (RTM) are adopted as model operator and observation operator, respectively. The assimilation experiment is conducted in Naqu, Tibet Plateau, from May 31 to September 27, 2011. Compared with in-situ measurements, the accuracy of soil moisture estimation is tremendously improved in terms of a variety of scales. The updated soil temperature by assimilating MODIS LST as input of RTM can reduce the differences between the simulated and observed brightness temperatures to a certain degree, which helps to improve the estimation of soil moisture and model parameters. The updated parameters show large discrepancy with the default ones and the former effectively reduces the states bias of CoLM. Results demonstrate the potential of assimilating both microwave TB and MODIS LST to improve the estimation of soil moisture and related parameters. Furthermore, this study also indicates that the developed scheme is an effective soil moisture downscaling approach for coarse-scale microwave TB.

Potential for Expanding the Near Real Time ForWarn Regional Forest Monitoring System to Include Alaska

NASA Technical Reports Server (NTRS)

Spruce, Joseph P.; Gasser, Gerald; Hargrove, William; Smoot, James; Kuper, Philip D.

2014-01-01

The on-line near real time (NRT) ForWarn system is currently deployed to monitor regional forest disturbances within the conterminous United States (CONUS), using daily MODIS Aqua and Terra NDVI data to derive monitoring products. The Healthy Forest Restoration Act of 2003 mandated such a system. Work on ForWarn began in 2006 with development and validation of retrospective MODIS NDVI-based forest monitoring products. Subsequently, NRT forest disturbance monitoring products were demonstrated, leading to the actual system deployment in 2010. ForWarn provides new CONUS forest disturbance monitoring products every 8 days, using USGS eMODIS data for current NDVI. ForWarn currently does not cover Alaska, which includes extensive forest lands at risk to multiple biotic and abiotic threats. This poster discusses a case study using Alaska eMODIS Terra data to derive ForWarn like forest change products during the 2010 growing season. The eMODIS system provides current MODIS Terra NDVI products for Alaska. Resulting forest change products were assessed with ground, aerial, and Landsat reference data. When cloud and snow free, these preliminary products appeared to capture regional forest disturbances from insect defoliation and fires; however, more work is needed to mitigate cloud and snow contamination, including integration of eMODIS Aqua data.

Dynamics and Properties of Global Aerosol using MODIS, AERONET and GOCART Model

NASA Technical Reports Server (NTRS)

Kaufman, Yoram; Chin, Mian; Reme, Lorraine; Tanre, Didier; Mattoo, Shana

2002-01-01

Recently produced daily Moderate Resolution Imaging Spectroradiometer (MODIS) aerosol data for the whole year of 2001 are used to show the concentration and dynamics of aerosol over ocean and large parts of the continents. The data were validated against the Aerosol Robotic Network (AERONET) measurements over land and ocean in a special issue in GRL now in press. Monthly averages and a movie based on the daily data are produced and used to demonstrate the spatial and temporal evolution of aerosol. The MODIS wide spectral range is used to distinguish fine smoke and pollution aerosol from coarse dust and salt. The aerosol is observed above ocean and land. The movie produced from the MODIS data provides a new dimension to aerosol observations by showing the dynamics of the system. For example in February smoke and dust emitted from the Sahel and West Africa is shown to travel to the North-East Atlantic. In April heavy dust and pollution from East Asia is shown to travel to North America. In May-June pollution and dust play a dynamical dance in the Arabian Sea and Bay of Bengal. In Aug-September smoke from South Africa and South America is shown to pulsate in tandem and to periodically to be transported to the otherwise pristine Southern part of the Southern Hemisphere. The MODIS data are compared with the Georgia Tech/Goddard Global Ozone Chemistry Aerosol Radiation Transport (GOCART) model to test and adjust source and sink strengths in the model and to study the effect of clouds on the representation of the satellite data.

Land and cryosphere products from Suomi NPP VIIRS: Overview and status.

PubMed

Justice, Christopher O; Román, Miguel O; Csiszar, Ivan; Vermote, Eric F; Wolfe, Robert E; Hook, Simon J; Friedl, Mark; Wang, Zhuosen; Schaaf, Crystal B; Miura, Tomoaki; Tschudi, Mark; Riggs, George; Hall, Dorothy K; Lyapustin, Alexei I; Devadiga, Sadashiva; Davidson, Carol; Masuoka, Edward J

2013-09-16

[1] The Visible Infrared Imaging Radiometer Suite (VIIRS) instrument was launched in October 2011 as part of the Suomi National Polar-Orbiting Partnership (S-NPP). The VIIRS instrument was designed to improve upon the capabilities of the operational Advanced Very High Resolution Radiometer and provide observation continuity with NASA's Earth Observing System's Moderate Resolution Imaging Spectroradiometer (MODIS). Since the VIIRS first-light images were received in November 2011, NASA- and NOAA-funded scientists have been working to evaluate the instrument performance and generate land and cryosphere products to meet the needs of the NOAA operational users and the NASA science community. NOAA's focus has been on refining a suite of operational products known as Environmental Data Records (EDRs), which were developed according to project specifications under the National Polar-Orbiting Environmental Satellite System. The NASA S-NPP Science Team has focused on evaluating the EDRs for science use, developing and testing additional products to meet science data needs, and providing MODIS data product continuity. This paper presents to-date findings of the NASA Science Team's evaluation of the VIIRS land and cryosphere EDRs, specifically Surface Reflectance, Land Surface Temperature, Surface Albedo, Vegetation Indices, Surface Type, Active Fires, Snow Cover, Ice Surface Temperature, and Sea Ice Characterization. The study concludes that, for MODIS data product continuity and earth system science, an enhanced suite of land and cryosphere products and associated data system capabilities are needed beyond the EDRs currently available from the VIIRS.

Evaluation of MODIS Land Surface Temperature with In Situ Snow Surface Temperature from CREST-SAFE

NASA Astrophysics Data System (ADS)

Perez Diaz, C. L.; Lakhankar, T.; Romanov, P.; Munoz, J.; Khanbilvardi, R.; Yu, Y.

2016-12-01

This paper presents the procedure and results of a temperature-based validation approach for the Moderate Resolution Imaging Spectroradiometer (MODIS) Land Surface Temperature (LST) product provided by the National Aeronautics and Space Administration (NASA) Terra and Aqua Earth Observing System satellites using in situ LST observations recorded at the Cooperative Remote Sensing Science and Technology Center - Snow Analysis and Field Experiment (CREST-SAFE) during the years of 2013 (January-April) and 2014 (February-April). A total of 314 day and night clear-sky thermal images, acquired by the Terra and Aqua satellites, were processed and compared to ground-truth data from CREST-SAFE with a frequency of one measurement every 3 min. Additionally, this investigation incorporated supplementary analyses using meteorological CREST-SAFE in situ variables (i.e. wind speed, cloud cover, incoming solar radiation) to study their effects on in situ snow surface temperature (T-skin) and T-air. Furthermore, a single pixel (1km2) and several spatially averaged pixels were used for satellite LST validation by increasing the MODIS window size to 5x5, 9x9, and 25x25 windows for comparison. Several trends in the MODIS LST data were observed, including the underestimation of daytime values and nighttime values. Results indicate that, although all the data sets (Terra and Aqua, diurnal and nocturnal) showed high correlation with ground measurements, day values yielded slightly higher accuracy ( 1°C), both suggesting that MODIS LST retrievals are reliable for similar land cover classes and atmospheric conditions. Results from the CREST-SAFE in situ variables' analyses indicate that T-air is commonly higher than T-skin, and that a lack of cloud cover results in: lower T-skin and higher T-air minus T-skin difference (T-diff). Additionally, the study revealed that T-diff is inversely proportional to cloud cover, wind speed, and incoming solar radiation. Increasing the MODIS window size showed an overestimation of in situ LST and some improvement in the daytime Terra and nighttime Aqua biases, with the highest accuracy achieved with the 5x5 window. A comparison between MODIS emmisivity from bands 31, 32, and in situ emissivity showed that emissivity errors (Relative error = -.003) were insignificant.

Comparability of Red/Near-Infrared Reflectance and NDVI Based on the Spectral Response Function between MODIS and 30 Other Satellite Sensors Using Rice Canopy Spectra

PubMed Central

Huang, Weijiao; Huang, Jingfeng; Wang, Xiuzhen; Wang, Fumin; Shi, Jingjing

2013-01-01

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 reflectance 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 reflectances 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 reflectances were convoluted with the spectral response functions of various satellite instruments to simulate sensor-specific reflectances in the red and NIR channels. NDVI values were then calculated using the simulated red and NIR reflectances. The results showed that as compared to the Terra MODIS, the mean relative percentage difference (RPD) ranged from −12.67% to 36.30% for the red reflectance, −8.52% to −0.23% for the NIR reflectance, and −9.32% to 3.10% for the NDVI. The mean absolute percentage difference (APD) compared to the Terra MODIS ranged from 1.28% to 36.30% for the red reflectance, 0.84% to 8.71% for the NIR reflectance, and 0.59% to 9.32% for the NDVI. The lowest APD between MODIS and the other 30 satellite sensors was observed for Landsat5 TM for the red reflectance, CBERS02B CCD for the NIR reflectance and Landsat4 TM for the NDVI. In addition, the largest APD between MODIS and the other 30 satellite sensors was observed for IKONOS for the red reflectance, AVHRR1 onboard NOAA8 for the NIR reflectance and IKONOS for the NDVI. The results also indicated that AVHRRs onboard NOAA7-17 showed higher differences than did the other sensors with respect to MODIS. A series of optimum models were presented for remote sensing data assimilation between MODIS and other sensors. PMID:24287529

Comparability of red/near-infrared reflectance and NDVI based on the spectral response function between MODIS and 30 other satellite sensors using rice canopy spectra.

PubMed

Huang, Weijiao; Huang, Jingfeng; Wang, Xiuzhen; Wang, Fumin; Shi, Jingjing

2013-11-26

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 reflectance 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 reflectances 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 reflectances were convoluted with the spectral response functions of various satellite instruments to simulate sensor-specific reflectances in the red and NIR channels. NDVI values were then calculated using the simulated red and NIR reflectances. The results showed that as compared to the Terra MODIS, the mean relative percentage difference (RPD) ranged from -12.67% to 36.30% for the red reflectance, -8.52% to -0.23% for the NIR reflectance, and -9.32% to 3.10% for the NDVI. The mean absolute percentage difference (APD) compared to the Terra MODIS ranged from 1.28% to 36.30% for the red reflectance, 0.84% to 8.71% for the NIR reflectance, and 0.59% to 9.32% for the NDVI. The lowest APD between MODIS and the other 30 satellite sensors was observed for Landsat5 TM for the red reflectance, CBERS02B CCD for the NIR reflectance and Landsat4 TM for the NDVI. In addition, the largest APD between MODIS and the other 30 satellite sensors was observed for IKONOS for the red reflectance, AVHRR1 onboard NOAA8 for the NIR reflectance and IKONOS for the NDVI. The results also indicated that AVHRRs onboard NOAA7-17 showed higher differences than did the other sensors with respect to MODIS. A series of optimum models were presented for remote sensing data assimilation between MODIS and other sensors.

A brief comparison of radiometers at NSIDC and their potential to generate long ESDRs

NASA Astrophysics Data System (ADS)

Moth, P.; Johnston, T.; Haran, T. M.; Fowler, D. K.

2017-12-01

Radiometers have played a big part in Earth observing science. In this poster we compare three such instruments: the Advanced Very-High-resolution Radiometer (AVHRR), the Moderate Resolution Imaging Spectroradiometer (MODIS), and the Visible Infrared Imaging Radiometer Suite (VIIRS). The NASA National Snow and Ice Distributed Active Archive Center (NSIDC DAAC) has archived cryospheric data from all three of these instruments. AVHRR was a 4-channel radiometer that was first launched in 1978 aboard the TIROS-N satellite. Subsequent missions launched improved versions of AVHRR with five and six channels, observing Earth in frequencies ranging from 0.58 μm to 12.5 μm with a resolution at nadir of 1.09 km. MODIS instruments fly onboard NASA's Earth Observing System (EOS) Terra and Aqua satellites. Launched in 1999 and 2002, respectively, they still produce much sought after data observed in 36 spectral bands ranging from 0.4 μm to 14.4 μm. Two bands image Earth at a nominal resolution of 250 m at nadir, five at 500 m, and the remaining 29 bands at 1 km. A ±55-degree scanning pattern at the sun-synchronous orbit of 705 km achieves a 2,330 km swath and provides global coverage every one to two days VIIRS, NOAA's latest radiometer, was launched aboard the Suomi National Polar-orbiting Partnership satellite on October 28, 2011. Working collaboratively, NASA and NOAA are producing data that is archived and distributed via NASA DAACs. The VIIRS radiometer comprises 22 bands; five for high-resolution imagery, 16 at moderate resolution, and one panchromatic day/night band. VIIRS is a whiskbroom scanning radiometer that covers the spectrum between 0.412 μm and 12.01 μm and acquires spatial resolutions at nadir of 750 m, 375 m, and 750 m, respectively. Although these instruments are configured with different spectral bands, each was designed with an eye to the future. MODIS can be thought of as a successor to the AVHRR mission, adding capabilities that yielded better data. Similarly, VIIRS will extend the MODIS record with new, higher quality data. Starting in the early 1980s, the AVHRR-MODIS-VIIRS timeline should span at least four decades and perhaps beyond, enabling researchers to produce and gain valuable insight from very long, high-quality Earth System Data Records (ESDRs).

A web-based subsetting service for regional scale MODIS land products

DOE Office of Scientific and Technical Information (OSTI.GOV)

SanthanaVannan, Suresh K; Cook, Robert B; Holladay, Susan K

2009-12-01

The Moderate Resolution Imaging Spectroradiometer (MODIS) sensor has provided valuable information on various aspects of the Earth System since March 2000. The spectral, spatial, and temporal characteristics of MODIS products have made them an important data source for analyzing key science questions relating to Earth System processes at regional, continental, and global scales. The size of the MODIS product and native HDF-EOS format are not optimal for use in field investigations at individual sites (100 - 100 km or smaller). In order to make MODIS data readily accessible for field investigations, the NASA-funded Distributed Active Archive Center (DAAC) for Biogeochemicalmore » Dynamics at Oak Ridge National Laboratory (ORNL) has developed an online system that provides MODIS land products in an easy-to-use format and in file sizes more appropriate to field research. This system provides MODIS land products data in a nonproprietary comma delimited ASCII format and in GIS compatible formats (GeoTIFF and ASCII grid). Web-based visualization tools are also available as part of this system and these tools provide a quick snapshot of the data. Quality control tools and a multitude of data delivery options are available to meet the demands of various user communities. This paper describes the important features and design goals for the system, particularly in the context of data archive and distribution for regional scale analysis. The paper also discusses the ways in which data from this system can be used for validation, data intercomparison, and modeling efforts.« less

Data systems trade studies for a next generation sensor

NASA Astrophysics Data System (ADS)

Masuoka, Edward J.; Fleig, Albert J.

1997-01-01

Processing system designers must make substantial changes to accommodate current and anticipated improvements in remote sensing instruments.Increases in the spectral, radiometric and geometric resolution lead to data rates, processing loads and storage volumes which far exceed the ability of most current computer systems. To accommodate user expectations, the data must be processed and made available quickly in a convenient and easy to use form. This paper describes design trade-offs made in developing the processing system for the moderate resolution imaging spectroradiometer, MODIS, which will fly on the Earth Observing System's, AM-1 spacecraft to be launched in 1998. MODIS will have an average continuous date rate of 6.2 Mbps and require processing at 6.5 GFLOPS to produce 600GB of output products per day. Specific trade-offs occur in the areas of science software portability and usability of science products versus overall system performance and throughput.

The MODIS reprojection tool

USGS Publications Warehouse

Dwyer, John L.; Schmidt, Gail L.; Qu, J.J.; Gao, W.; Kafatos, M.; Murphy , R.E.; Salomonson, V.V.

2006-01-01

The MODIS Reprojection Tool (MRT) is designed to help individuals work with MODIS Level-2G, Level-3, and Level-4 land data products. These products are referenced to a global tiling scheme in which each tile is approximately 10° latitude by 10° longitude and non-overlapping (Fig. 9.1). If desired, the user may reproject only selected portions of the product (spatial or parameter subsetting). The software may also be used to convert MODIS products to file formats (generic binary and GeoTIFF) that are more readily compatible with existing software packages. The MODIS land products distributed by the Land Processes Distributed Active Archive Center (LP DAAC) are in the Hierarchical Data Format - Earth Observing System (HDF-EOS), developed by the National Center for Supercomputing Applications at the University of Illinois at Urbana Champaign for the NASA EOS Program. Each HDF-EOS file is comprised of one or more science data sets (SDSs) corresponding to geophysical or biophysical parameters. Metadata are embedded in the HDF file as well as contained in a .met file that is associated with each HDF-EOS file. The MRT supports 8-bit, 16-bit, and 32-bit integer data (both signed and unsigned), as well as 32-bit float data. The data type of the output is the same as the data type of each corresponding input SDS.

Accessing Recent Trend of Land Surface Temperature from Satellite Observations

NASA Technical Reports Server (NTRS)

Shen, Suhung; Leptoukh, Gregory G.; Romanov, Peter

2011-01-01

Land surface temperature (Ts) is an important element to measure the state of terrestrial ecosystems and to study surface energy budgets. In support of the land cover/land use change-related international program MAIRS (Monsoon Asia Integrated Regional Study), we have collected global monthly Ts measured by MODIS since the beginning of the missions. The MODIS Ts time series have approximately 11 years of data from Terra since 2000 and approximately 9 years of data from Aqua since 2002, which makes possible to study the recent climate, such as trend. In this study, monthly climatology from two platforms are calculated and compared with that from AIRS. The spatial patterns of Ts trends are accessed, focusing on the Eurasia region. Furthermore, MODIS Ts trends are compared with those from AIRS and NASA's atmospheric assimilation model, MERRA (Modern Era Retrospective-analysis for Research and Applications). The preliminary results indicate that the recent 8-year Ts trend shows an oscillation-type spatial variation over Eurasia. The pattern is consistent for data from MODIS, AIRS, and MERRA, with the positive center over Eastern Europe, and the negative center over Central Siberia. The calculated climatology and anomaly of MODIS Ts will be integrated into the online visualization system, Giovanni, at NASA GES DISC for easy use by scientists and general public.

Snowmelt runoff in the Green River basin derived from MODIS snow extent

NASA Astrophysics Data System (ADS)

Barton, J. S.; Hall, D. K.

2011-12-01

The Green River represents a vital water supply for southwestern Wyoming, northern Colorado, eastern Utah, and the Lower Colorado River Compact states (Arizona, Nevada, and California). Rapid development in the southwestern United States combined with the recent drought has greatly stressed the water supply of the Colorado River system, and concurrently increased the interest in long-term variations in stream flow. Modeling of snowmelt runoff represents a means to predict flows and reservoir storage, which is useful for water resource planning. An investigation is made into the accuracy of the Snowmelt Runoff Model of Martinec and Rango, driven by Moderate Resolution Imaging Spectroradiometer (MODIS) snow maps for predicting stream flow within the Green River basin. While the moderate resolution of the MODIS snow maps limits the spatial detail that can be captured, the daily coverage is an important advantage of the MODIS imagery. The daily MODIS snow extent is measured using the most recent clear observation for each 500-meter pixel. Auxiliary data used include temperature and precipitation time series from the Snow Telemetry (SNOTEL) and Remote Automated Weather Station (RAWS) networks as well as from National Weather Service records. Also from the SNOTEL network, snow-water equivalence data are obtained to calibrate the conversion between snow extent and runoff potential.

Mapping Daily Evapotranspiration based on Spatiotemporal Fusion of ASTER and MODIS Images over Irrigated Agricultural Areas in the Heihe River Basin, Northwest China

NASA Astrophysics Data System (ADS)

Huang, C.; LI, Y.

2017-12-01

Continuous monitoring of daily evapotranspiration (ET) is crucial for allocating and managing water resources in irrigated agricultural areas in arid regions. In this study, continuous daily ET at a 90-m spatial resolution was estimated using the Surface Energy Balance System (SEBS) by fusing Moderate Resolution Imaging Spectroradiometer (MODIS) images with high temporal resolution and Advanced Space-borne Thermal Emission Reflectance Radiometer (ASTER) images with high spatial resolution. The spatiotemporal characteristics of these sensors were obtained using the Spatial and Temporal Adaptive Reflectance Fusion Model (STARFM). The performance of this approach was validated over a heterogeneous oasis-desert region covered by cropland, residential, woodland, water, Gobi desert, sandy desert, desert steppe, and wetland areas using in situ observations from automatic meteorological systems (AMS) and eddy covariance (EC) systems in the middle reaches of the Heihe River Basin in Northwest China. The error introduced during the data fusion process based on STARFM is within an acceptable range for predicted LST at a 90-m spatial resolution. The surface energy fluxes estimated using SEBS based on predicted remotely sensed data that combined the spatiotemporal characteristics of MODIS and ASTER agree well with the surface energy fluxes observed using EC systems for all land cover types, especially for vegetated area with MAP values range from 9% to 15%, which are less than the uncertainty (18%) of the observed in this study area. Time series of daily ET modelled from SEBS were compared to that modelled from PT-JPL (one of Satellite-based Priestley-Taylor ET model) and observations from EC systems. SEBS performed generally better than PT-JPL for vegetated area, especially irrigated cropland with bias, RMSE, and MAP values of 0.29 mm/d, 0.75 mm/d, 13% at maize site, -0.33 mm/d, 0.81 mm/d, and 14% at vegetable sites.

A MODIS-based automated flood monitoring system for southeast asia

NASA Astrophysics Data System (ADS)

Ahamed, A.; Bolten, J. D.

2017-09-01

Flood disasters in Southeast Asia result in significant loss of life and economic damage. Remote sensing information systems designed to spatially and temporally monitor floods can help governments and international agencies formulate effective disaster response strategies during a flood and ultimately alleviate impacts to population, infrastructure, and agriculture. Recent destructive flood events in the Lower Mekong River Basin occurred in 2000, 2011, 2013, and 2016 (http://ffw.mrcmekong.org/historical_rec.htm, April 24, 2017). The large spatial distribution of flooded areas and lack of proper gauge data in the region makes accurate monitoring and assessment of impacts of floods difficult. Here, we discuss the utility of applying satellite-based Earth observations for improving flood inundation monitoring over the flood-prone Lower Mekong River Basin. We present a methodology for determining near real-time surface water extent associated with current and historic flood events by training surface water classifiers from 8-day, 250-m Moderate-resolution Imaging Spectroradiometer (MODIS) data spanning the length of the MODIS satellite record. The Normalized Difference Vegetation Index (NDVI) signature of permanent water bodies (MOD44W; Carroll et al., 2009) is used to train surface water classifiers which are applied to a time period of interest. From this, an operational nowcast flood detection component is produced using twice daily imagery acquired at 3-h latency which performs image compositing routines to minimize cloud cover. Case studies and accuracy assessments against radar-based observations for historic flood events are presented. The customizable system has been transferred to regional organizations and near real-time derived surface water products are made available through a web interface platform. Results highlight the potential of near real-time observation and impact assessment systems to serve as effective decision support tools for governments, international agencies, and disaster responders.

NASA Observes Super Typhoon Hagupit; Philippines Under Warnings

NASA Image and Video Library

2017-12-08

On Dec. 4 at 02:10 UTC, the MODIS instrument aboard NASA's Terra satellite took this visible image of Super Typhoon Hagupit approaching the Philippines. Image Credit: NASA Goddard's MODIS Rapid Response Team Read more: 1.usa.gov/12q3ssK NASA image use policy. NASA Goddard Space Flight Center enables NASA’s mission through four scientific endeavors: Earth Science, Heliophysics, Solar System Exploration, and Astrophysics. Goddard plays a leading role in NASA’s accomplishments by contributing compelling scientific knowledge to advance the Agency’s mission. Follow us on Twitter Like us on Facebook Find us on Instagram

Evaluation of VIIRS, GOCI, and MODIS Collection 6 AOD Retrievals Against Ground Sunphotometer Observations Over East Asia

NASA Technical Reports Server (NTRS)

Xiao, Q.; Zhang, H.; Choi, M.; Li, S.; Kondragunta, S.; Kim, J.; Holben, B.; Levy, R. C.; Liu, Y.

2016-01-01

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 Aqua Moderate Resolution Imaging Spectroradiometer (MODIS) (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 MODIS C6 3km AOD, and 16% of Aqua MODIS C6 3km AOD fell within the reference expected error (EE) envelope (+/-0.05/+/- 0.15 AOD). Comparing against AERONET AOD over the JapanSouth Korea region, 64% of EDR, 37% of IP, 61% of GOCI, 39% of Terra MODIS, and 56% of Aqua MODIS C6 3km 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 MODIS C6 3km products had positive biases.

Evaluation of VIIRS, GOCI, and MODIS Collection 6 AOD retrievals against ground sunphotometer observations over East Asia

NASA Astrophysics Data System (ADS)

Xiao, Q.; Zhang, H.; Choi, M.; Li, S.; Kondragunta, S.; Kim, J.; Holben, B.; Levy, R. C.; Liu, Y.

2016-02-01

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 Aqua Moderate Resolution Imaging Spectroradiometer (MODIS) (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 MODIS C6 3 km AOD, and 16 % of Aqua MODIS 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 MODIS, and 56 % of Aqua MODIS 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 MODIS C6 3 km products had positive biases.

Comparasion of Cloud Cover restituted by POLDER and MODIS

NASA Astrophysics Data System (ADS)

Zeng, S.; Parol, F.; Riedi, J.; Cornet, C.; Thieuxleux, F.

2009-04-01

PARASOL and AQUA are two sun-synchronous orbit satellites in the queue of A-Train satellites that observe our earth within a few minutes apart from each other. Aboard these two platforms, POLDER and MODIS provide coincident observations of the cloud cover with very different characteristics. These give us a good opportunity to study the clouds system and evaluate strengths and weaknesses of each dataset in order to provide an accurate representation of global cloud cover properties. This description is indeed of outermost importance to quantify and understand the effect of clouds on global radiation budget of the earth-atmosphere system and their influence on the climate changes. We have developed a joint dataset containing both POLDER and MODIS level 2 cloud products collocated and reprojected on a common sinusoidal grid in order to make the data comparison feasible and veracious. Our foremost work focuses on the comparison of both spatial distribution and temporal variation of the global cloud cover. This simple yet critical cloud parameter need to be clearly understood to allow further comparison of the other cloud parameters. From our study, we demonstrate that on average these two sensors both detect the clouds fairly well. They provide similar spatial distributions and temporal variations:both sensors see high values of cloud amount associated with deep convection in ITCZ, over Indonesia, and in west-central Pacific Ocean warm pool region; they also provide similar high cloud cover associated to mid-latitude storm tracks, to Indian monsoon or to the stratocumulus along the west coast of continents; on the other hand small cloud amounts that typically present over subtropical oceans and deserts in subsidence aeras are well identified by both POLDER and MODIS. Each sensor has its advantages and inconveniences for the detection of a particular cloud types. With higher spatial resolution, MODIS can better detect the fractional clouds thus explaining as one part of a positive bias in any latitude and in any viewing angle with an order of 10% between the POLDER cloud amount and the so-called MODIS "combined" cloud amount. Nevertheless it is worthy to note that a negative bias of about 10% is obtained between the POLDER cloud amount and the MODIS "day-mean" cloud amount. Main differences between the two MODIS cloud amount values are known to be due to the filtering of remaining aerosols or cloud edges. due to both this high spatial resolution of MODIS and the fact that "combined" cloud amount filters cloud edges, we can also explain why appear the high positive bias regions over subtropical ocean in south hemisphere and over east Africa in summer. Thanks to several channels in the thermal infrared spectral domain, MODIS detects probably much better the thin cirrus especially over land, thus causing a general negative bias for ice clouds. The multi-spectral capability of MODIS also allows for a better detection of low clouds over snow or ice, Hence the (POLDER-MODIS) cloud amount difference is often negative over Greenland, Antarctica, and over the continents at middle-high latitudes in spring and autumn associated to the snow coverage. The multi-spectral capability of MODIS also makes the discrimination possible between the biomass burning aerosols and the fractional clouds over the continents. Thus a positive bias appears in central Africa in summer and autumn associated to important biomass burning events. Over transition region between desert and non-desert, the presence of large negative bias (POLDER-MODIS) of cloud amount maybe partly due to MODIS pixel falsely labeled the desert as cloudy, where MODIS algorithm uses static desert mask. This is clearly highlighted in south of Sahara in spring and summer where we find a bias negative with an order of -0.1. What is more, thanks to its multi-angular capability, POLDER can discriminate the sun-glint region thus minimizing the dependence of cloud amount on view angle. It makes the detection of high clouds easier over a black surface thanks to its polarization character.

Monitoring Start of Season in Alaska

NASA Astrophysics Data System (ADS)

Robin, J.; Dubayah, R.; Sparrow, E.; Levine, E.

2006-12-01

In biomes that have distinct winter seasons, start of spring phenological events, specifically timing of budburst and green-up of leaves, coincides with transpiration. Seasons leave annual signatures that reflect the dynamic nature of the hydrologic cycle and link the different spheres of the Earth system. This paper evaluates whether continuity between AVHRR and MODIS normalized difference vegetation index (NDVI) is achievable for monitoring land surface phenology, specifically start of season (SOS), in Alaska. Additionally, two thresholds, one based on NDVI and the other on accumulated growing degree-days (GDD), are compared to determine which most accurately predicts SOS for Fairbanks. Ratio of maximum greenness at SOS was computed from biweekly AVHRR and MODIS composites for 2001 through 2004 for Anchorage and Fairbanks regions. SOS dates were determined from annual green-up observations made by GLOBE students. Results showed that different processing as well as spectral characteristics of each sensor restrict continuity between the two datasets. MODIS values were consistently higher and had less inter-annual variability during the height of the growing season than corresponding AVHRR values. Furthermore, a threshold of 131-175 accumulated GDD was a better predictor of SOS for Fairbanks than a NDVI threshold applied to AVHRR and MODIS datasets. The NDVI threshold was developed from biweekly AVHRR composites from 1982 through 2004 and corresponding annual green-up observations at University of Alaska-Fairbanks (UAF). The GDD threshold was developed from 20+ years of historic daily mean air temperature data and the same green-up observations. SOS dates computed with the GDD threshold most closely resembled actual green-up dates observed by GLOBE students and UAF researchers. Overall, biweekly composites and effects of clouds, snow, and conifers limit the ability of NDVI to monitor phenological changes in Alaska.

Using VIIRS/NPP and MODIS/Aqua data to provide a continuous record of suspended particulate matter in a highly turbid inland lake

NASA Astrophysics Data System (ADS)

Cao, Zhigang; Duan, Hongtao; Shen, Ming; Ma, Ronghua; Xue, Kun; Liu, Dong; Xiao, Qitao

2018-02-01

Inland lakes are generally an important source of drinking water, and information on their water quality needs to be obtained in real time. To date, Moderate-resolution imaging spectroradiometer (MODIS) data have played a critical, effective and long-term role in fulfilling this function. However, the MODIS instruments on board both the Terra and Aqua satellites have operated beyond their designed five-year mission lifespans (Terra was launched in 1999, whereas Aqua was launched in 2002), and these instruments may stop running at any time in the near future. The Visible Infrared Imager Radiometer Suite (VIIRS) on board the Suomi National Polar-Orbiting Partnership (Suomi NPP, which was launched in Oct 2011) is expected to provide a consistent, long-term data record and continue the series of observations initiated by MODIS. To date, few evaluations of the consistency between VIIRS and MODIS have been conducted for turbid inland waters. In this study, we first used synchronous MODIS/Aqua and VIIRS/NPP data (±1 h) collected during 2012-2015 to evaluate the consistency of Rayleigh-corrected reflectance (Rrc) observations over Lake Hongze (the fourth-largest freshwater lake in China), since accurate remote sensing reflectance (Rrs) values cannot be acquired over turbid inland waters. Second, we used recently developed algorithms based on Rrc in the red band to estimate the concentrations of suspended particulate matter (SPM) from MODIS/Aqua and VIIRS/NPP data. Finally, we assessed the consistency of the SPM products derived from MODIS/Aqua and VIIRS/NPP. The results show the following. (1) The differences in Rrc among the green (VIIRS 551 nm and MODIS 555 nm) and red bands (VIIRS 671 nm and MODIS 645 nm) indicate a satisfactory consistency, and the unbiased percentage difference (UPD) is <12%. Meanwhile, the results for the near infrared (NIR) band (MODIS 859 nm and VIIRS 862 nm) indicate relatively large differences (UPD = 21.84%). (2) The satellite-derived SPM products obtained using MODIS/Aqua and VIIRS/NPP have a satisfactory degree of consistency (0-150 mg/L SPM: R2 = 0.81, UPD < 16% and 0-80 mg/L SPM: R2 = 0.85, UPD < 12%, respectively). These results demonstrate that VIIRS/NPP can continue to record the SPM observations initiated by MODIS/Aqua for turbid inland waters and establish environmental datasets over long time periods to support water quality management endeavors.

Extending MODIS Cloud Top and Infrared Phase Climate Records with VIIRS and CrIS

NASA Astrophysics Data System (ADS)

Heidinger, A. K.; Platnick, S. E.; Ackerman, S. A.; Holz, R.; Meyer, K.; Frey, R.; Wind, G.; Li, Y.; Botambekov, D.

2015-12-01

The MODIS imagers on the NASA EOS Terra and Aqua satellites have generated accurate and well-used cloud climate data records for 15 years. Both missions are expected to continue until the end of this decade and perhaps beyond. The Visible and Infrared Imaging Radiometer Suite (VIIRS) imagers on the Suomi-NPP (SNPP) mission (launched in October 2011) and future NOAA Joint Polar Satellite System (JPSS) platforms are the successors for imager-based cloud climate records from polar orbiting satellites after MODIS. To ensure product continuity across a broad suite of EOS products, NASA has funded a SNPP science team to develop EOS-like algorithms that can be use with SNPP and JPSS observations, including two teams to work on cloud products. Cloud data record continuity between MODIS and VIIRS is particularly challenging due to the lack of VIIRS CO2-slicing channels, which reduces information content for cloud detection and cloud-top property products, as well as down-stream cloud optical products that rely on both. Here we report on our approach to providing continuity specifically for the MODIS/VIIRS cloud-top and infrared-derived thermodynamic phase products by combining elements of the NASA MODIS science team (MOD) and the NOAA Algorithm Working Group (AWG) algorithms. The combined approach is referred to as the MODAWG processing package. In collaboration with the NASA Atmospheric SIPS located at the University of Wisconsin Space Science and Engineering Center, the MODAWG code has been exercised on one year of SNPP VIIRS data. In addition to cloud-top and phase, MODAWG provides a full suite of cloud products that are physically consistent with MODIS and have a similar data format. Further, the SIPS has developed tools to allow use of Cross-track Infrared Sounder (CrIS) observations in the MODAWG processing that can ameliorate the loss of the CO2 absorption channels on VIIRS. Examples will be given that demonstrate the positive impact that the CrIS data can provide when combined with VIIRS for cloud height and IR-phase retrievals.

Impact of MODIS SWIR Band Calibration Improvements on Level-3 Atmospheric Products

NASA Technical Reports Server (NTRS)

Wald, Andrew; Levy, Robert; Angal, Amit; Geng, Xu; Xiong, Jack; Hoffman, Kurt

2016-01-01

The spectral reflectance measured by the MODIS reflective solar bands (RSB) is used for retrieving many atmospheric science products. The accuracy of these products depends on the accuracy of the calibration of the RSB. To this end, the RSB of the MODIS instruments are primarily calibrated on-orbit using regular solar diffuser (SD) observations. For lambda < 0.94 microns the SDs on-orbit bi-directional reflectance factor (BRF) change is tracked using solar diffuser stability monitor (SDSM) observations. For lambda > 0.94 microns, the MODIS Characterization Support Team (MCST) developed, in MODIS Collection 6 (C6), a time-dependent correction using observations from pseudo-invariant earth-scene targets. This correction has been implemented in C6 for the Terra MODIS 1.24 micron band over the entire mission, and for the 1.375 micron band in the forward processing. As the instruments continue to operate beyond their design lifetime of six years, a similar correction is planned for other short-wave infrared (SWIR) bands as well. MODIS SWIR bands are used in deriving atmosphere products, including aerosol optical thickness, atmospheric total column water vapor, cloud fraction and cloud optical depth. The SD degradation correction in Terra bands 5 and 26 impact the spectral radiance and therefore the retrieval of these atmosphere products. Here, we describe the corrections to Bands 5 (1.24 microns) and 26 (1.375 microns), and produce three sets (B5, B26 correction on/on, on/off, and off/off) of Terra-MODIS Level 1B (calibrated radiance product) data. By comparing products derived from these corrected and uncorrected Terra MODIS Level 1B (L1B) calibrations, dozens of L3 atmosphere products are surveyed for changes caused by the corrections, and representative results are presented. Aerosol and water vapor products show only small local changes, while some cloud products can change locally by > 10%, which is a large change.

A Blended Global Snow Product using Visible, Passive Microwave and Scatterometer Satellite Data

NASA Technical Reports Server (NTRS)

Foster, James L.; Hall, Dorothy K.; Eylander, John B.; Riggs, George A.; Nghiem, Son V.; Tedesco, Marco; Kim, Edward; Montesano, Paul M.; Kelly, Richard E. J.; Casey, Kimberly A.;

Variations of Global Terrestrial Primary Production Observed by Moderate Resolution Imaging Spectroradiometer (MODIS) From 2000 to 2005

NASA Astrophysics Data System (ADS)

Zhao, M.; Running, S.; Heinsch, F. A.

2006-12-01

Since the first Earth Observing System (EOS) satellite Terra was launched in December 1999 and Moderate Resolution Imaging Spectroradiometer (MODIS) sensor onboard Terra began to provide data in February 2000, we have had six-year MODIS global 1-km terrestrial Gross and Net Primary Production (GPP &NPP) datasets. In this article, we present the variations (seasonality and inter-annual variability) of global GPP/NPP from the latest improved Collection 4.8 (C4.8) MODIS datasets for the past six-year (2000 - 2005), as well as improvements of the algorithm, validations of GPP and NPP. Validation results show that the C4.8 data have higher accuracy and quality than the previous version. Analyses of the variations in GPP/NPP show that GPP not only can reflect strong seasonality of photosynthesis activities by plants in mid- and high-latitude, but importantly, can reveal enhanced growth of Amazon rainforests during dry season, consistent with the reports by Huete et al. (2006) on GRL. Spatially, plants over mid- and high-latitude (north to 22.5°N) are the major contributor of global GPP seasonality. Inter-annual variability of MODIS NPP for 2000 - 2005 reveals the negative effects of major droughts on carbon sequestration at the regional and continental scales. A striking phenomenon is that the severe drought in 2005 over Amazon reduced NPP, indicating water availability becomes the dominant limiting factor rather than solar radiation under normal conditions. GMAO and NCEP driven global total NPPs have the similar interannual anomalies, and they generally follow the inverted CO2 growth rate anomaly with correlation of 0.85 and 0.91, respectively, which are higher than the correlation of 0.7 found by Nemani et al. (2003) on Science. Though there are only 6 years of MODIS data, results show that global NPP decreased from 2000 to 2005, and spatially most decreased NPP areas are in tropic and south hemisphere.

Prolonged episodes of hypoglycaemia in HNF4A-MODY mutation carriers with IGT. Evidence of persistent hyperinsulinism into early adulthood.

PubMed

Bacon, S; Kyithar, M P; Condron, E M; Vizzard, N; Burke, M; Byrne, M M

2016-12-01

HNF4A is an established cause of maturity onset diabetes of the young (MODY). Congenital hyperinsulinism can also be associated with mutations in the HNF4A gene. A dual phenotype is observed in HNF4A-MODY with hyperinsulinaemic hypoglycaemia in the neonatal period progressing to diabetes in adulthood. The nature and timing of the transition remain poorly defined. We performed an observational study to establish changes in glycaemia and insulin secretion over a 6-year period. We investigated glycaemic variability and hypoglycaemia in HNF4A-MODY using a continuous glucose monitoring system (CGMS). An OGTT with measurement of glucose, insulin and C-peptide was performed in HNF4A participants with diabetes mellitus (DM) (n = 14), HNF4A-IGT (n = 7) and age- and BMI-matched MODY negative family members (n = 10). Serial assessment was performed in the HNF4A-IGT cohort. In a subset of HNF4A-MODY mutation carriers (n = 10), CGMS was applied over a 72-h period. There was no deterioration in glycaemic control in the HNF4A-IGT cohort. The fasting glucose-to-insulin ratio was significantly lower in the HNF4A-IGT cohort when compared to the normal control group (0.13 vs. 0.24, p = 0.03). CGMS profiling demonstrated prolonged periods of hypoglycaemia in the HNF4A-IGT group when compared to the HNF4A-DM group (432 vs. 138 min p = 0.04). In a young adult HNF4A-IGT cohort, we demonstrate preserved glucose, insulin and C-peptide secretory responses to oral glucose. Utilising CGMS, prolonged periods of hypoglycaemia are evident despite a median age of 21 years. We propose a prolonged hyperinsulinaemic phase into adulthood is responsible for the notable hypoglycaemic episodes.

Assimilation of MODIS Dark Target and Deep Blue Observations in the Dust Aerosol Component of NMMB-MONARCH version 1.0

NASA Technical Reports Server (NTRS)

Di Tomaso, Enza; Schutgens, Nick A. J.; Jorba, Oriol; Perez Garcia-Pando, Carlos

2017-01-01

A data assimilation capability has been built for the NMMB-MONARCH chemical weather prediction system, with a focus on mineral dust, a prominent type of aerosol. An ensemble-based Kalman filter technique (namely the local ensemble transform Kalman filter - LETKF) has been utilized to optimally combine model background and satellite retrievals. Our implementation of the ensemble is based on known uncertainties in the physical parametrizations of the dust emission scheme. Experiments showed that MODIS AOD retrievals using the Dark Target algorithm can help NMMB-MONARCH to better characterize atmospheric dust. This is particularly true for the analysis of the dust outflow in the Sahel region and over the African Atlantic coast. The assimilation of MODIS AOD retrievals based on the Deep Blue algorithm has a further positive impact in the analysis downwind from the strongest dust sources of the Sahara and in the Arabian Peninsula. An analysis-initialized forecast performs better (lower forecast error and higher correlation with observations) than a standard forecast, with the exception of underestimating dust in the long-range Atlantic transport and degradation of the temporal evolution of dust in some regions after day 1. Particularly relevant is the improved forecast over the Sahara throughout the forecast range thanks to the assimilation of Deep Blue retrievals over areas not easily covered by other observational datasets.The present study on mineral dust is a first step towards data assimilation with a complete aerosol prediction system that includes multiple aerosol species.

Assimilation of MODIS Dark Target and Deep Blue observations in the dust aerosol component of NMMB-MONARCH version 1.0

NASA Astrophysics Data System (ADS)

Di Tomaso, Enza; Schutgens, Nick A. J.; Jorba, Oriol; Pérez García-Pando, Carlos

2017-03-01

A data assimilation capability has been built for the NMMB-MONARCH chemical weather prediction system, with a focus on mineral dust, a prominent type of aerosol. An ensemble-based Kalman filter technique (namely the local ensemble transform Kalman filter - LETKF) has been utilized to optimally combine model background and satellite retrievals. Our implementation of the ensemble is based on known uncertainties in the physical parametrizations of the dust emission scheme. Experiments showed that MODIS AOD retrievals using the Dark Target algorithm can help NMMB-MONARCH to better characterize atmospheric dust. This is particularly true for the analysis of the dust outflow in the Sahel region and over the African Atlantic coast. The assimilation of MODIS AOD retrievals based on the Deep Blue algorithm has a further positive impact in the analysis downwind from the strongest dust sources of the Sahara and in the Arabian Peninsula. An analysis-initialized forecast performs better (lower forecast error and higher correlation with observations) than a standard forecast, with the exception of underestimating dust in the long-range Atlantic transport and degradation of the temporal evolution of dust in some regions after day 1. Particularly relevant is the improved forecast over the Sahara throughout the forecast range thanks to the assimilation of Deep Blue retrievals over areas not easily covered by other observational datasets. The present study on mineral dust is a first step towards data assimilation with a complete aerosol prediction system that includes multiple aerosol species.

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. In this paper, the algorithms of these approaches are described, their performance is demonstrated, and their impact on L1B products is discussed. In general, the shorter wavelength bands have experienced a larger on-orbit RVS change, which, in general, are mirror side and detector dependent. The on-orbit RVS change due to the degradation of band 8 can be as large as 35 percent for Terra MODIS and 20 percent for Aqua MODIS. Vital to maintaining the accuracy of the MODIS L1B products is an accurate characterization of the on-orbit RVS change. The derived time-independent RVS, implemented in C6, makes an important improvement to the quality of the MODIS L1B products.

Estimating Coastal Turbidity using MODIS 250 m Band Observations

NASA Technical Reports Server (NTRS)

Davies, James E.; Moeller, Christopher C.; Gunshor, Mathew M.; Menzel, W. Paul; Walker, Nan D.

2004-01-01

Terra MODIS 250 m observations are being applied to a Suspended Sediment Concentration (SSC) algorithm that is under development for coastal case 2 waters where reflectance is dominated by sediment entrained in major fluvial outflows. An atmospheric correction based on MODIS observations in the 500 m resolution 1.6 and 2.1 micron bands is used to isolate the remote sensing reflectance in the MODIS 25Om resolution 650 and 865 nanometer bands. SSC estimates from remote sensing reflectance 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.

Exploring New Methods of Displaying Bit-Level Quality and Other Flags for MODIS Data

NASA Technical Reports Server (NTRS)

Khalsa, Siri Jodha Singh; Weaver, Ron

2003-01-01

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 (MODIS) on board NASA's Terra and Aqua satellites. All MODIS standard products are in the Earth Observing System version of the Hierarchal Data Format (HDF-EOS). The MODIS 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 MODIS science products. Commercial and public domain utilities give users access, in varying degrees, to the elements inside MODIS 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 MODIS 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.

CHIMAERA System for Cloud Retrievals v 6.0.85

NASA Technical Reports Server (NTRS)

Wind, Galina; Platnick, Steven; Meyer, Kerry; Amarasinghe, Nandana; Marchant, Benjamin; Arnold, Tom; King, Michael D.

2015-01-01

Organizers of the MODIS-VIIRS Science Team Meeting, held May 18-22, 2015 in Silver Spring, MD plan to post the presentations and posters to the NASA MODIS website: http:modis.gsfc.nasa.govsci_teammeetings201505index.php. The MODIS Science Team Meeting is held twice a year, so that the members of the science team may assemble and discuss data they have collected, ideas they have formed, and future issues that apply to the MODIS Mission.

Development of Fire Emissions Inventory Using Satellite Data

EPA Science Inventory

There are multiple satellites observing and reporting fire imagery at various spatial and temporal resolutions and each system has inherent merits and deficiencies. In our study, data are acquired from the Moderate Resolution Imaging Spectro-radiometer (MODIS) aboard the Nationa...

Detecting Soil Moisture Related Impacts on Gross Primary Productivity using the MODIS-based Photochemical Reflectance Index

NASA Astrophysics Data System (ADS)

He, M.; Kimball, J. S.; Running, S. W.; Ballantyne, A.; Guan, K.; Huemmrich, K. F.

2016-12-01

Satellite remote sensing provides continuous observations of vegetation properties that can be used to estimate ecosystem gross primary production (GPP). The Photochemical Reflectance Index (PRI) has been shown to be sensitive to photosynthetic light use efficiency (LUE), GPP and canopy water-stress. The NASA EOS MODIS (Moderate Resolution Imaging Spectroradiometer) sensor provides potential PRI estimation globally at daily time step and 1-km spatial resolution for more than 10 years. Here, we use the MODIS based PRI with eddy covariance CO2 flux measurements and meteorological observations from 20 tower sites representing 5 major plant functional types (PFT) within the continental USA (CONUS) to assess GPP sensitivity to seasonal water supply variability. The sPRI (scaled PRI) derived using MODIS band 13 as a reference band (sPRI13) generally shows higher correspondence with tower GPP observations than other potential MODIS reference bands (MODIS band 1, 4, 10 and 12). The sPRI13 was used to represent soil moisture related water supply constraints to LUE within a terrestrial carbon flux model to estimate GPP (GPPPRI). The GPPPRI calculations show generally strong relationships with tower GPP observations (0.457 ≤ R2 ≤ 0.818), except for lower GPPPRI performance over evergreen needleleaf forest (ENF) sites. A regional model sensitivity analysis using the sPRI13 as a proxy for soil moisture related water supply limits indicated that water restrictions limit GPP over more than 21% of the CONUS domain, particularly in northwest and southwest CONUS subregions, and drier climate areas where atmospheric moisture deficits (VPD) alone are insufficient to represent both atmosphere demand and soil water supply controls affecting productivity. Our results indicate strong potential of the MODIS sPRI13 to represent GPP sensitivity to seasonal soil moisture related water supply variability, with enhanced (1-km resolution) delineation of these processes closer to the scale of in situ tower observations, providing an effective tool to characterize sub-grid spatial heterogeneity in soil moisture related water supply controls that inform coarser scale observations and estimates determined from other satellite observations and global carbon, and climate models.

Assessment of observed fog/low-cloud trends in central Taiwan

NASA Astrophysics Data System (ADS)

Lai, Yen-Jen; Lin, Po-Hsiung

2017-04-01

Xitou region, as the epitome of mid-elevation cloud forest ecosystems in Taiwan, it possesses a rich diversity of flora and fauna. It is also a popular forest recreation area. Due to rapid development of the local tourist industry, where tourist numbers increased from 0.3 million/year in 2000 to 2 million/year in 2015, the microclimate has changed continually. Global warming and landscape changes would be also the most likely factors. This study reports findings of monitoring systems including 4 visibility observed sites at different altitude, a self-developed atmospheric profile observation system carried by unmanned aerial vehicle (UAV) and a high temporal cloud base height observation system by a ceilometer. Besides this, the cloud top height of MODIS cloud product is evaluated as well. The results indicated the foggy day ratio in 2015 was 24% lower than that in 2005 around the district of the nursery. The foggy day ratio raised along with the increase of altitude and the sharpest increasing range happened in the summer time. The UAV-observed results showed the top heights of the nighttime atmospheric boundary layer (ABL) usually happened under 1300m a.s.l. (250m above ground) and the top heights of daytime ABL rose to 1500m - 2100m a.s.l. Unfortunately, it was difficult to observe the inversion layer/ABL in summer due to the fly height limitation of UAV. The ceilometer-observed results indicated the highest foggy ratio happened around 17:00 (local standard time). The daytime cloudy based height ratio was higher than nighttime and the cloud based height was usually located during 1150m - 1750m a.s.l. which was under the top heights of ABL. In addition, the higher cloud-based-heights-happened ratios were found at 1200m - 1250m a.s.l. and 1350m - 1400m a.s.l.. These results indicated the cloud based height uplifted from ground to at least 150m above ground-level causing the foggy ratio decrease. The MODIS cloud product showed the top height of low cloud uplifted or even became clear sky along with the increase of Xitou tourist numbers. Both ceilometer and MODIS data suggested the low cloud was uplifting. In order to clarify the seasonal characters of cloud thickness, the validation of MODIS cloud top height by atmospheric profiles are on-going. Furthermore, an adapted land-atmospheric model (WRF model is now under testing) will be implemented in order to discover the major factors causing the decrease of foggy ratio and assess the impacts on cloud forest.

MODIS Retrieval of Dust Aerosol

NASA Technical Reports Server (NTRS)

Remer, Lorraine A.; Kaufman, Yoram J.; Tanre, Didier

2003-01-01

The MODerate resolution Imaging Spectroradiometer (MODIS) currently aboard both the Terra and Aqua 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-MODIS 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 MODIS 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 MODIS algorithm tends to under predict particle size because the reflectances at top of atmosphere measured by MODIS 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 MODIS Look-Up Tables were constructed from Mie theory, assuming a spherical shape. Using a combination of MODIS 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 MODIS algorithm, in lieu of the original options for large dust-like particles. The results will be analyzed and examined.

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

NASA Technical Reports Server (NTRS)

Madhavan, Sriharsha; Brinkmann, Jake; Wenny, Brian N.; Wu, Aisheng; Xiong, Xiaoxiong

2017-01-01

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

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

NASA Technical Reports Server (NTRS)

Case, Jonathan L.; LaCasse, Katherine M.; Dembek, Scott R.; Santos, Pablo; Lapenta, William M.

2007-01-01

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

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.

Modeling the Impact of Drizzle and 3D Cloud Structure on Remote Sensing of Effective Radius

NASA Technical Reports Server (NTRS)

Platnick, Steven; Zinner, Tobias; Ackerman, S.

2008-01-01

Remote sensing of cloud particle size with passive sensors like MODIS is an important tool for cloud microphysical studies. As a measure of the radiatively relevant droplet size, effective radius can be retrieved with different combinations of visible through shortwave infrared channels. MODIS observations sometimes show significantly larger effective radii in marine boundary layer cloud fields derived from the 1.6 and 2.1 pm channel observations than for 3.7 pm retrievals. Possible explanations range from 3D radiative transport effects and sub-pixel cloud inhomogeneity to the impact of drizzle formation on the droplet distribution. To investigate the potential influence of these factors, we use LES boundary layer cloud simulations in combination with 3D Monte Carlo simulations of MODIS observations. LES simulations of warm cloud spectral microphysics for cases of marine stratus and broken stratocumulus, each for two different values of cloud condensation nuclei density, produce cloud structures comprising droplet size distributions with and without drizzle size drops. In this study, synthetic MODIS observations generated from 3D radiative transport simulations that consider the full droplet size distribution will be generated for each scene. The operational MODIS effective radius retrievals will then be applied to the simulated reflectances and the results compared with the LES microphysics.

Land and cryosphere products from Suomi NPP VIIRS: Overview and status

PubMed Central

Justice, Christopher O; Román, Miguel O; Csiszar, Ivan; Vermote, Eric F; Wolfe, Robert E; Hook, Simon J; Friedl, Mark; Wang, Zhuosen; Schaaf, Crystal B; Miura, Tomoaki; Tschudi, Mark; Riggs, George; Hall, Dorothy K; Lyapustin, Alexei I; Devadiga, Sadashiva; Davidson, Carol; Masuoka, Edward J

2013-01-01

[1] The Visible Infrared Imaging Radiometer Suite (VIIRS) instrument was launched in October 2011 as part of the Suomi National Polar-Orbiting Partnership (S-NPP). The VIIRS instrument was designed to improve upon the capabilities of the operational Advanced Very High Resolution Radiometer and provide observation continuity with NASA’s Earth Observing System’s Moderate Resolution Imaging Spectroradiometer (MODIS). Since the VIIRS first-light images were received in November 2011, NASA- and NOAA-funded scientists have been working to evaluate the instrument performance and generate land and cryosphere products to meet the needs of the NOAA operational users and the NASA science community. NOAA’s focus has been on refining a suite of operational products known as Environmental Data Records (EDRs), which were developed according to project specifications under the National Polar-Orbiting Environmental Satellite System. The NASA S-NPP Science Team has focused on evaluating the EDRs for science use, developing and testing additional products to meet science data needs, and providing MODIS data product continuity. This paper presents to-date findings of the NASA Science Team’s evaluation of the VIIRS land and cryosphere EDRs, specifically Surface Reflectance, Land Surface Temperature, Surface Albedo, Vegetation Indices, Surface Type, Active Fires, Snow Cover, Ice Surface Temperature, and Sea Ice Characterization. The study concludes that, for MODIS data product continuity and earth system science, an enhanced suite of land and cryosphere products and associated data system capabilities are needed beyond the EDRs currently available from the VIIRS. PMID:25821661

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.

Satellite Observation Highlights of the 2010 Russian Wildfires

NASA Technical Reports Server (NTRS)

Witte, Jacquelyn C.; Douglass, Anne R.; Duncan, Bryan N.; daSilva, Arlindo; Torres, Omar

2010-01-01

From late-July through mid-August 2010, wildfires raged in western Russia. The resulting thick smoke and biomass burning products were transported over the highly populated Moscow city and surrounding regions, seriously impairing visibility and affecting human health. We demonstrate the uniqueness of the 2010 Russian wildfires by using satellite observations from NASA's Earth Observing System (EOS) platforms. Over Moscow and the region of major fire activity to the southeast, we calculate unprecedented increases in the MODIS fire count record of 178 %, an order of magnitude increase in the MODIS fire radiative power (308%) and OMI absorbing aerosols (255%), and a 58% increase in AIRS total carbon monoxide (CO). The exceptionally high levels of CO are shown to be of comparable strength to the 2006 El Nino wildfires over Indonesia. Both events record CO values exceeding 30x10(exp 7) molec/ square cm.

MODIS-VIIRS Intercalibration for Dark Target Aerosol Retrieval Over Ocean

NASA Astrophysics Data System (ADS)

Sawyer, V. R.; Levy, R. C.; Mattoo, S.; Quinn, G.; Veglio, P.

2016-12-01

Any future climate record for satellite aerosol retrieval will require continuity over multiple decades, longer than the lifespan of an individual satellite instrument. The Dark Target algorithm was developed for MODIS, which began taking observations in 1999; the two MODIS instruments currently in orbit are not expected to continue taking observations beyond the early 2020s. However, the algorithm is portable, and a Dark Target product for VIIRS is scheduled for release December 2016. Because MODIS and VIIRS operate at different wavelengths, resolutions, fields of view and orbital timing, the transition can introduce artifacts that must be corrected. Without these corrections, it will be difficult to find any changes that may occur in the global aerosol climate record over time periods that span the transition from MODIS to VIIRS retrievals. The University of Wisconsin-Madison SIPS team found thousands of matches between 2012 and 2016 in which Aqua-MODIS and Suomi-NPP VIIRS observe the same location at similar times and view angles. These matched cases are used to identify corresponding matches in the Intermediate File Format (IFF) aerosol retrievals for MODIS and VIIRS, which are compared to one another in turn. Because most known sources of disagreement between the two instruments have already been corrected during the IFF retrieval, the direct comparison between near-collocated cases shows only the differences that remain at local and regional scales. The comparison is further restricted to clear-sky cases over ocean, so that the investigation of seasonal, diurnal and geographic variation is not affected by uncertainties in the land surface or cloud contamination.

Global Aerosol Remote Sensing from MODIS

NASA Technical Reports Server (NTRS)

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)

2002-01-01

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 (MODIS) sensors aboard the Earth Observing System (EOS) Terra and Aqua polar-orbiting satellites ushers in a new era in aerosol remote sensing from space. 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 (level 2) from MODIS daytime data. The MODIS 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-MODIS 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 Aqua-MODIS aerosol products. The MODIS level 2 aerosol products are operationally aggregated to generate global daily, eight-day (weekly), and monthly products at one-degree spatial resolution (level 3). MODIS aerosol data are used for the detailed study of local, regional, and global aerosol concentration, distribution, and temporal dynamics, as well as for radiative forcing calculations. We show several examples of these results and comparisons with model output.

An ontological system based on MODIS images to assess ecosystem functioning of Natura 2000 habitats: A case study for Quercus pyrenaica forests

NASA Astrophysics Data System (ADS)

Pérez-Luque, A. J.; Pérez-Pérez, R.; Bonet-García, F. J.; Magaña, P. J.

2015-05-01

The implementation of the Natura 2000 network requires methods to assess the conservation status of habitats. This paper shows a methodological approach that combines the use of (satellite) Earth observation with ontologies to monitor Natura 2000 habitats and assess their functioning. We have created an ontological system called Savia that can describe both the ecosystem functioning and the behaviour of abiotic factors in a Natura 2000 habitat. This system is able to automatically download images from MODIS products, create indicators and compute temporal trends for them. We have developed an ontology that takes into account the different concepts and relations about indicators and temporal trends, and the spatio-temporal components of the datasets. All the information generated from datasets and MODIS images, is stored into a knowledge base according to the ontology. Users can formulate complex questions using a SPARQL end-point. This system has been tested and validated in a case study that uses Quercus pyrenaica Willd. forests as a target habitat in Sierra Nevada (Spain), a Natura 2000 site. We assess ecosystem functioning using NDVI. The selected abiotic factor is snow cover. Savia provides useful data regarding these two variables and reflects relationships between them.

Bio-Optical Data Assimilation With Observational Error Covariance Derived From an Ensemble of Satellite Images

NASA Astrophysics Data System (ADS)

Shulman, Igor; Gould, Richard W.; Frolov, Sergey; McCarthy, Sean; Penta, Brad; Anderson, Stephanie; Sakalaukus, Peter

2018-03-01

An ensemble-based approach to specify observational error covariance in the data assimilation of satellite bio-optical properties is proposed. The observational error covariance is derived from statistical properties of the generated ensemble of satellite MODIS-Aqua chlorophyll (Chl) images. The proposed observational error covariance is used in the Optimal Interpolation scheme for the assimilation of MODIS-Aqua Chl observations. The forecast error covariance is specified in the subspace of the multivariate (bio-optical, physical) empirical orthogonal functions (EOFs) estimated from a month-long model run. The assimilation of surface MODIS-Aqua Chl improved surface and subsurface model Chl predictions. Comparisons with surface and subsurface water samples demonstrate that data assimilation run with the proposed observational error covariance has higher RMSE than the data assimilation run with "optimistic" assumption about observational errors (10% of the ensemble mean), but has smaller or comparable RMSE than data assimilation run with an assumption that observational errors equal to 35% of the ensemble mean (the target error for satellite data product for chlorophyll). Also, with the assimilation of the MODIS-Aqua Chl data, the RMSE between observed and model-predicted fractions of diatoms to the total phytoplankton is reduced by a factor of two in comparison to the nonassimilative run.

Inter-Comparison of MODIS and VIIRS Vegetation Indices Using One-Year Global Data

NASA Astrophysics Data System (ADS)

Miura, T.; Muratsuchi, J.; Obata, K.; Kato, A.; Vargas, M.; Huete, A. R.

2016-12-01

The Visible Infrared Imaging Radiometer Suite (VIIRS) sensor series of the Joint Polar Satellite System program is slated to continue the highly calibrated data stream initiated with the Earth Observing System Moderate Resolution Imaging Spectroradiometer (MODIS) sensors. A number of geophysical products are being/to be produced from VIIRS data, including the "Top-of-the-Atmosphere (TOA)" Normalized Difference Vegetation Index (NDVI), "Top-of-Canopy (TOC)" Enhanced Vegetation Index (EVI), and TOC NDVI. In this study, we cross-compared vegetation indices (VIs) from the first VIIRS sensor aboard the Suomi National Polar-orbiting Partnership satellite with the Aqua MODIS counterparts using one-year global data. This study was aimed at developing a thorough understanding of radiometric compatibility between the two VI datasets across globe, seasons, a range of viewing angle, and land cover types. VIIRS and MODIS VI data of January-December 2015 were obtained at monthly intervals when their orbital tracks coincided. These data were projected and spatially-aggregated into a .0036-degree grid while screening for cloud and aerosol contaminations using their respective quality flags. VIIRS-MODIS observation pairs with near-identical sun-target-view angles were extracted from each of these monthly image pairs for cross-comparison. The four VIs of TOA NDVI, TOC NDVI, TOC EVI, and TOC EVI2 (a two-band version of the EVI) were analyzed. Between MODIS and VIIRS, TOA NDVI, TOC NDVI, and TOC EVI2 had very small overall mean differences (MD) of .014, .013, and .013 VI units, respectively, whereas TOC EVI had a slightly larger overall MD of 0.023 EVI units attributed to the disparate blue bands of the two sensors. These systematic differences were consistent across the one-year period. With respect to sun-target-viewing geometry, MDs were also consistent across the view zenith angle range, but always lower for forward- than backward-viewing geometry. MDs showed large land cover dependencies for TOA NDVI and TOC NDVI, varying 10 folds from .002 for forests to .02 for sparsely-vegetated areas. They were consistent across land cover types for TOC EVI and TOC EVI2. Future studies should address the impact of sun-target-view geometry on corss-sensor VI comparisons.

Impact of the Dubai Coastline Intensive Urbanization on the Atmosphere Employing MODIS Data (2001-2014)

NASA Astrophysics Data System (ADS)

Elhacham, Emily; Alpert, Pinhas

2017-04-01

Over the last 20 years Dubai landscape has dramatically changed - artificial islands have been constructed as well as residential and industrial facilities along with roads systems. This rapid and massive construction placed Dubai urban growth rate at the top of the global list. Here, we investigate the impact of those constructions on the local atmosphere, both in land and sea based on MODIS data. It was found that, over the tested time period, temperature decreases and albedo increases were observed in the sea area of the artificial islands. In land, albedo decreases along with temperature increases of up to 2C were observed in the areas along the coast where intensive constructions occurred. In addition, the coast of Dubai was found to have urban heat island characteristics, where the urban center point at Deira area exhibits higher temperature than surrounding points along the coast. Nonetheless, the largest temperature trends were observed in the coastal area in between Palm Jumeirah and Palm Jebel Ali, where massive construction was performed during the tested time frame. Reference: E.Elhacham and P. Alpert ,"Impact of coastline-intensive anthropogenic activities on the atmosphere from moderate resolution imaging spectroradiometer (MODIS) data in Dubai (2001-2014)", Earth's Future, 4, 2016.

Phenotypical aspects of maturity-onset diabetes of the young (MODY diabetes) in comparison with Type 2 diabetes mellitus (T2DM) in children and adolescents: experience from a large multicentre database.

PubMed

Schober, E; Rami, B; Grabert, M; Thon, A; Kapellen, Th; Reinehr, Th; Holl, R W

2009-05-01

To analyse and compare clinical characteristics in young patients with maturity-onset diabetes of the young (MODY) and Type 2 diabetes mellitus (T2DM). We conducted an observational investigation using the DPV-Wiss database containing clinical data on 40 757 diabetic patients < 20 years of age from Germany and Austria. Three hundred and thirty-nine cases were clinically categorized as MODY (0.83%); 562 patients were diagnosed as T2DM (1.4%). In 20% of cases, the diagnosis of MODY was based on clinical findings only. Of the 272 subjects where genetic testing was available, 3% did not carry mutations in the three examined MODY genes. Glucokinase-MODY was commoner than HNF1A-MODY and HNF4A-MODY. Age at diagnosis was younger in MODY patients. The body mass index of T2DM was significantly higher compared with all MODY subgroups. Macrovascular risk factors such as dyslipidaemia and hypertension were commoner in T2DM, but 23% of MODY patients had dyslipidaemia and 10% hypertension. Glycaemic control was within the therapeutic target (HbA(1c) < 7.5%) in 86% of MODY and 70% of T2DM patients. The prevalence of MODY in children and adolescents in Germany and Austria is lower than that of T2DM in this age group. Dyslipidaemia and hypertension are less frequent in MODY compared with T2DM patients, but do occur.

Operational Observation of Australian Bioregions with Bands 8-19 of Modis

NASA Astrophysics Data System (ADS)

McAtee, B. K.; Gray, M.; Broomhall, M.; Lynch, M.; Fearns, P.

2012-07-01

Data from bands 1-7 are the most common bands of the MODIS instrument used for near-real time terrestrial earth observation operations in Australia. However, many of Australia's bioregions present unique scenarios which constitute a challenge for quantitative environmental remote sensing. We believe that data from MODIS bands 8-19 may provide significant benefit to Earth observation over particular bioregions of the Australian continent. Examples here include the use of band 8 in characterising aerosol optical depth over typically bright land surfaces and accounting for anomalous retrievals of atmospheric water vapour obtained using MOD05 based on the abundance of Australia's 'red dirt', which exhibits absorption features in the near infrared bands 17-19 of MODIS. Bioregion-focused applications such as those mentioned above have driven the development of automated processing, infrastructure for the atmospheric and BRDF correction of the first 19 bands of MODIS rather than only the first 7, which is more often the case. This work has been facilitated by the AusCover project which is the remote sensing component of the Terrestrial Ecosystem Research Network (TERN), itself a program designed to create a new generation of infrastructure for ecological study of the Australian landscape.

Surveillance of waste disposal activity at sea using satellite ocean color imagers: GOCI and MODIS

NASA Astrophysics Data System (ADS)

Hong, Gi Hoon; Yang, Dong Beom; Lee, Hyun-Mi; Yang, Sung Ryull; Chung, Hee Woon; Kim, Chang Joon; Kim, Young-Il; Chung, Chang Soo; Ahn, Yu-Hwan; Park, Young-Je; Moon, Jeong-Eon

2012-09-01

Korean Geostationary Ocean Color Imager (GOCI) and Moderate Resolution Imaging Spectroradiometer (MODIS) Aqua observations of the variation in ocean color at the sea surface were utilized to monitor the impact of nutrient-rich sewage sludge disposal in the oligotrophic area of the Yellow Sea. MODIS revealed that algal blooms persisted in the spring annually at the dump site in the Yellow Sea since year 2000 to the present. A number of implications of using products of the satellite ocean color imagers were exploited here based on the measurements in the Yellow Sea. GOCI observes almost every hour during the daylight period, every day since June 2011. Therefore, GOCI provides a powerful tool to monitor waste disposal at sea in real time. Tracking of disposal activity from a large tanker was possible hour by hour from the GOCI timeseries images compared to MODIS. Smaller changes in the color of the ocean surface can be easily observed, as GOCI resolves images at smaller scales in space and time in comparison to polar orbiting satellites, e.g., MODIS. GOCI may be widely used to monitor various marine activities in the sea, including waste disposal activity from ships.

Characterization of seasonal variation of forest canopy in a temperate deciduous broadleaf forest, using daily MODIS data

Treesearch

Qingyuan Zhang; Xiangming Xiao; Bobby Braswell; Ernst Linder; Scott Ollinger; Marie-Louise Smith; Julian P. Jenkins; Fred Baret; Andrew D. Richardson; Berrien III Moore; Rakesh Minocha

2006-01-01

In this paper, we present an improved procedure for collecting no or little atmosphere- and snow-contaminated observations from the Moderate Resolution Imaging Spectroradiometer (MODIS) sensor. The resultant time series of daily MODIS data of a temperate deciduous broadleaf forest (the Bartlett Experimental Forest) in 2004 show strong seasonal dynamics of surface...

Global Aerosol Optical Models and Lookup Tables for the New MODIS Aerosol Retrieval over Land

NASA Technical Reports Server (NTRS)

Levy, Robert C.; Remer, Loraine A.; Dubovik, Oleg

2007-01-01

Since 2000, MODIS has been deriving aerosol properties over land from MODIS observed spectral reflectance, by matching the observed reflectance with that simulated for selected aerosol optical models, aerosol loadings, wavelengths and geometrical conditions (that are contained in a lookup table or 'LUT'). Validation exercises have showed that MODIS tends to under-predict aerosol optical depth (tau) in cases of large tau (tau greater than 1.0), signaling errors in the assumed aerosol optical properties. Using the climatology of almucantur retrievals from the hundreds of global AERONET sunphotometer sites, we found that three spherical-derived models (describing fine-sized dominated aerosol), and one spheroid-derived model (describing coarse-sized dominated aerosol, presumably dust) generally described the range of observed global aerosol properties. The fine dominated models were separated mainly by their single scattering albedo (omega(sub 0)), ranging from non-absorbing aerosol (omega(sub 0) approx. 0.95) in developed urban/industrial regions, to neutrally absorbing aerosol (omega(sub 0) approx.90) in forest fire burning and developing industrial regions, to absorbing aerosol (omega(sub 0) approx. 0.85) in regions of savanna/grassland burning. We determined the dominant model type in each region and season, to create a 1 deg. x 1 deg. grid of assumed aerosol type. We used vector radiative transfer code to create a new LUT, simulating the four aerosol models, in four MODIS channels. Independent AERONET observations of spectral tau agree with the new models, indicating that the new models are suitable for use by the MODIS aerosol retrieval.

Updated MISR Dark Water Research Aerosol Retrieval Algorithm - Part 1: Coupled 1.1 km Ocean Surface Chlorophyll a Retrievals with Empirical Calibration Corrections

NASA Technical Reports Server (NTRS)

Limbacher, James A.; Kahn, Ralph A.

2017-01-01

As aerosol amount and type are key factors in the 'atmospheric correction' required for remote-sensing chlorophyll alpha concentration (Chl) retrievals, the Multi-angle Imaging SpectroRadiometer (MISR) can contribute to ocean color analysis despite a lack of spectral channels optimized for this application. Conversely, an improved ocean surface constraint should also improve MISR aerosol-type products, especially spectral single-scattering albedo (SSA) retrievals. We introduce a coupled, self-consistent retrieval of Chl together with aerosol over dark water. There are time-varying MISR radiometric calibration errors that significantly affect key spectral reflectance ratios used in the retrievals. Therefore, we also develop and apply new calibration corrections to the MISR top-of-atmosphere (TOA) reflectance data, based on comparisons with coincident MODIS (Moderate Resolution Imaging Spectroradiometer) observations and trend analysis of the MISR TOA bidirectional reflectance factors (BRFs) over three pseudo-invariant desert sites. We run the MISR research retrieval algorithm (RA) with the corrected MISR reflectances to generate MISR-retrieved Chl and compare the MISR Chl values to a set of 49 coincident SeaBASS (SeaWiFS Bio-optical Archive and Storage System) in situ observations. Where Chl(sub in situ) less than 1.5 mg m(exp -3), the results from our Chl model are expected to be of highest quality, due to algorithmic assumption validity. Comparing MISR RA Chl to the 49 coincident SeaBASS observations, we report a correlation coefficient (r) of 0.86, a root-mean-square error (RMSE) of 0.25, and a median absolute error (MAE) of 0.10. Statistically, a two-sample Kolmogorov- Smirnov test indicates that it is not possible to distinguish between MISR Chl and available SeaBASS in situ Chl values (p greater than 0.1). We also compare MODIS-Terra and MISR RA Chl statistically, over much broader regions. With about 1.5 million MISR-MODIS collocations having MODIS Chl less than 1.5 mg m(exp -3), MISR and MODIS show very good agreement: r = 0.96, MAE = 0.09, and RMSE = 0.15. The new dark water aerosol/Chl RA can retrieve Chl in low-Chl, case I waters, independent of other imagers such as MODIS, via a largely physical algorithm, compared to the commonly applied statistical ones. At a minimum, MISR's multi-angle data should help reduce uncertainties in the MODIS-Terra ocean color retrieval where coincident measurements are made, while also allowing for a more robust retrieval of particle properties such as spectral single-scattering albedo.

Updated MISR dark water research aerosol retrieval algorithm - Part 1: Coupled 1.1 km ocean surface chlorophyll a retrievals with empirical calibration corrections

NASA Astrophysics Data System (ADS)

Limbacher, James A.; Kahn, Ralph A.

2017-04-01

As aerosol amount and type are key factors in the atmospheric correction required for remote-sensing chlorophyll a concentration (Chl) retrievals, the Multi-angle Imaging SpectroRadiometer (MISR) can contribute to ocean color analysis despite a lack of spectral channels optimized for this application. Conversely, an improved ocean surface constraint should also improve MISR aerosol-type products, especially spectral single-scattering albedo (SSA) retrievals. We introduce a coupled, self-consistent retrieval of Chl together with aerosol over dark water. There are time-varying MISR radiometric calibration errors that significantly affect key spectral reflectance ratios used in the retrievals. Therefore, we also develop and apply new calibration corrections to the MISR top-of-atmosphere (TOA) reflectance data, based on comparisons with coincident MODIS (Moderate Resolution Imaging Spectroradiometer) observations and trend analysis of the MISR TOA bidirectional reflectance factors (BRFs) over three pseudo-invariant desert sites. We run the MISR research retrieval algorithm (RA) with the corrected MISR reflectances to generate MISR-retrieved Chl and compare the MISR Chl values to a set of 49 coincident SeaBASS (SeaWiFS Bio-optical Archive and Storage System) in situ observations. Where Chlin situ < 1.5 mg m-3, the results from our Chl model are expected to be of highest quality, due to algorithmic assumption validity. Comparing MISR RA Chl to the 49 coincident SeaBASS observations, we report a correlation coefficient (r) of 0.86, a root-mean-square error (RMSE) of 0.25, and a median absolute error (MAE) of 0.10. Statistically, a two-sample Kolmogorov-Smirnov test indicates that it is not possible to distinguish between MISR Chl and available SeaBASS in situ Chl values (p > 0.1). We also compare MODIS-Terra and MISR RA Chl statistically, over much broader regions. With about 1.5 million MISR-MODIS collocations having MODIS Chl < 1.5 mg m-3, MISR and MODIS show very good agreement: r = 0. 96, MAE = 0.09, and RMSE = 0.15. The new dark water aerosol/Chl RA can retrieve Chl in low-Chl, case I waters, independent of other imagers such as MODIS, via a largely physical algorithm, compared to the commonly applied statistical ones. At a minimum, MISR's multi-angle data should help reduce uncertainties in the MODIS-Terra ocean color retrieval where coincident measurements are made, while also allowing for a more robust retrieval of particle properties such as spectral single-scattering albedo.

Using MODIS and GRACE to assess water storage in regional Wetlands: Iraqi and Sudd Marsh systems

NASA Astrophysics Data System (ADS)

Becker, R.

2015-12-01

Both The Iraqi (Mesopotamian) Marshes, an extensive wetlands system in Iraq, and the Sudd Marshlands, located in Sudan have been heavily impacted by both human and climate forces over the past decades. The Sudd wetlands are highly variable in size, averaging roughly 30,000 km2, but extending to as large as ~130,000 km2 during the wet seasons, while the Iraqi marshes are smaller, at ~15,000 km2, without the same extent of intra-annual variability. A combination of MODIS and GRACE images from 2003-2015 for the study areas were used to determine the time dependent change in surface water area (SWA) in the marshes, marshland extent and variability in total water storage. Combined open water area and vegetation abundance and cover, as determined by MODIS (NDVI and MNDWI), is highly correlated with total mass variability observed by GRACE (RL05 Tellus land grid). Annual variability in the Iraqi marshes correlates well with combined SWA and vegetation extent. Variability of vegetation in the Sudd marshes is seen to correlate well on an annual basis with water storage variation, and with a 2 month lag (water mass increases and decreases lead vegetation increases and decreases) when examined on a monthly basis. As a result, in both systems, the overall wetlands extent and health is observed to be water limited. Predictions for precipitation variability and human diversions of water through either dam storage or navigation modifications are predicted to lower water availability and lower variability in these systems. These two regional wetlands systems will shrink, with resulting loss in habitat and other ecosystem services.

Crop Surveillance Demonstration Using a Near-Daily MODIS Derived Vegetation Index Time Series

NASA Technical Reports Server (NTRS)

McKellip, Rodney; Ryan, Robert E.; Blonski, Slawomir; Prados, Don

2005-01-01

Effective response to crop disease outbreaks requires rapid identification and diagnosis of an event. A near-daily vegetation index product, such as a Normalized Difference Vegetation Index (NDVI), at moderate spatial resolution may serve as a good method for monitoring quick-acting diseases. NASA s Moderate Resolution Imaging Spectroradiometer (MODIS) instrument flown on the Terra and Aqua satellites has the temporal, spatial, and spectral properties to make it an excellent coarse-resolution data source for rapid, comprehensive surveillance of agricultural areas. A proof-of-concept wide area crop surveillance system using daily MODIS imagery was developed and tested on a set of San Joaquin cotton fields over a growing season. This area was chosen in part because excellent ground truth data were readily available. Preliminary results indicate that, at least in the southwestern part of the United States, near-daily NDVI products can be generated that show the natural variations in the crops as well as specific crop practices. Various filtering methods were evaluated and compared with standard MOD13 NDVI MODIS products. We observed that specific chemical applications that produce defoliation, which would have been missed using the standard 16-day product, were easily detectable with the filtered daily NDVI products.

A Marine Boundary Layer Water Vapor Climatology Derived from Microwave and Near-Infrared Imagery

NASA Astrophysics Data System (ADS)

Millan Valle, L. F.; Lebsock, M. D.; Teixeira, J.

2017-12-01

The synergy of the collocated Advanced Microwave Scanning Radiometer (AMSR) and the Moderate Resolution Imaging Spectroradiometer (MODIS) provides daily global estimates of partial marine planetary boundary layer water vapor. AMSR microwave radiometry provides the total column water vapor, while MODIS near-infrared imagery provides the water vapor above the cloud layers. The difference between the two gives the vapor between the surface and the cloud top, which may be interpreted as the boundary layer water vapor. Comparisons against radiosondes, and GPS-Radio occultation data demonstrate the robustness of these boundary layer water vapor estimates. We exploit the 14 years of AMSR-MODIS synergy to investigate the spatial, seasonal, and inter-annual variations of the boundary layer water vapor. Last, it is shown that the measured AMSR-MODIS partial boundary layer water vapor can be generally prescribed using sea surface temperature, cloud top pressure and the lifting condensation level. The multi-sensor nature of the analysis demonstrates that there exists more information on boundary layer water vapor structure in the satellite observing system than is commonly assumed when considering the capabilities of single instruments. 2017 California Institute of Technology. U.S. Government sponsorship acknowledged.

Integrated Cloud-Aerosol-Radiation Product using CERES, MODIS, CALIPSO and CloudSat Data

NASA Technical Reports Server (NTRS)

Sun-Mack, Sunny; Minnis, Patrick; Chen, Yan; Gibson, Sharon; Yi, Yuhong; Trepte, Qing; Wielicki, Bruce; Kato, Seiji; Winker, Dave

2007-01-01

This paper documents the development of the first integrated data set of global vertical profiles of clouds, aerosols, and radiation using the combined NASA A-Train data from the Aqua Clouds and Earth's Radiant Energy System (CERES) and Moderate Resolution Imaging Spectroradiometer (MODIS), Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO), and CloudSat. As part of this effort, cloud data from the CALIPSO lidar and the CloudSat radar are merged with the integrated column cloud properties from the CERES-MODIS analyses. The active and passive datasets are compared to determine commonalities and differences in order to facilitate the development of a 3- dimensional cloud and aerosol dataset that will then be integrated into the CERES broadband radiance footprint. Preliminary results from the comparisons for April 2007 reveal that the CERES-MODIS global cloud amounts are, on average, 0.14 less and 0.15 greater than those from CALIPSO and CloudSat, respectively. These new data will provide unprecedented ability to test and improve global cloud and aerosol models, to investigate aerosol direct and indirect radiative forcing, and to validate the accuracy of global aerosol, cloud, and radiation data sets especially in polar regions and for multi-layered cloud conditions.

Integrated cloud-aerosol-radiation product using CERES, MODIS, CALIPSO, and CloudSat data

NASA Astrophysics Data System (ADS)

Sun-Mack, Sunny; Minnis, Patrick; Chen, Yan; Gibson, Sharon; Yi, Yuhong; Trepte, Qing; Wielicki, Bruce; Kato, Seiji; Winker, Dave; Stephens, Graeme; Partain, Philip

2007-10-01

This paper documents the development of the first integrated data set of global vertical profiles of clouds, aerosols, and radiation using the combined NASA A-Train data from the Aqua Clouds and Earth's Radiant Energy System (CERES) and Moderate Resolution Imaging Spectroradiometer (MODIS), Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO), and CloudSat. As part of this effort, cloud data from the CALIPSO lidar and the CloudSat radar are merged with the integrated column cloud properties from the CERES-MODIS analyses. The active and passive datasets are compared to determine commonalities and differences in order to facilitate the development of a 3-dimensional cloud and aerosol dataset that will then be integrated into the CERES broadband radiance footprint. Preliminary results from the comparisons for April 2007 reveal that the CERES-MODIS global cloud amounts are, on average, 0.14 less and 0.15 greater than those from CALIPSO and CloudSat, respectively. These new data will provide unprecedented ability to test and improve global cloud and aerosol models, to investigate aerosol direct and indirect radiative forcing, and to validate the accuracy of global aerosol, cloud, and radiation data sets especially in polar regions and for multi-layered cloud conditions.

Global Agricultural Monitoring (GLAM) using MODAPS and LANCE Data Products

NASA Astrophysics Data System (ADS)

Anyamba, A.; Pak, E. E.; Majedi, A. H.; Small, J. L.; Tucker, C. J.; Reynolds, C. A.; Pinzon, J. E.; Smith, M. M.

2012-12-01

The Global Inventory Modeling and Mapping Studies / Global Agricultural Monitoring (GIMMS GLAM) system is a web-based geographic application that offers Moderate Resolution Imaging Spectroradiometer (MODIS) imagery and user interface tools to data query and plot MODIS NDVI time series. The system processes near real-time and science quality Terra and Aqua MODIS 8-day composited datasets. These datasets are derived from the MOD09 and MYD09 surface reflectance products which are generated and provided by NASA/GSFC Land and Atmosphere Near Real-time Capability for EOS (LANCE) and NASA/GSFC MODIS Adaptive Processing System (MODAPS). The GIMMS GLAM system is developed and provided by the NASA/GSFC GIMMS group for the U.S. Department of Agriculture / Foreign Agricultural Service / International Production Assessment Division (USDA/FAS/IPAD) Global Agricultural Monitoring project (GLAM). The USDA/FAS/IPAD mission is to provide objective, timely, and regular assessment of the global agricultural production outlook and conditions affecting global food security. This system was developed to improve USDA/FAS/IPAD capabilities for making operational quantitative estimates for crop production and yield estimates based on satellite-derived data. The GIMMS GLAM system offers 1) web map imagery including Terra & Aqua MODIS 8-day composited NDVI, NDVI percent anomaly, and SWIR-NIR-Red band combinations, 2) web map overlays including administrative and 0.25 degree Land Information System (LIS) shape boundaries, and crop land cover masks, and 3) user interface tools to select features, data query, plot, and download MODIS NDVI time series.

Relating a Spectral Index from MODIS and Tower-based Measurements to Ecosystem Light Use Efficiency for a Fluxnet-Canada Coniferous Forest

NASA Technical Reports Server (NTRS)

Middleton, Elizabeth M.; Cheng, Yen-Ben; Hilker, Thomas; Huemmrich, Karl F.; Black, T. Andrew; Krishnan, Praveena; Coops, Nicholas C.

2008-01-01

As part of the North American Carbon Program effort to quantify the terrestrial carbon budget of North America, we have been examining the possibility of retrieving ecosystem light use efficiency (LUE, the carbon sequestered per unit photosynthetically active radiation) directly from satellite observations. Our novel approach has been to compare LUE derived from tower fluxes with LUE estimated using spectral indices computed from MODIS satellite observations over forests in the Fluxnet-Canada Research Network, using the MODIS narrow ocean bands acquired over land. We matched carbon flux data collected around the time of the MODIS mid-day overpass for over one hundred relatively clear days in five years (2001-2006) from a mature Douglas fir forest in British Columbia. We also examined hyperspectral reflectance data collected diurnally from the tower in conjunction with the eddy correlation fluxes and meteorological measurements made throughout the 2006 growing season at this site. The tower-based flux data provided an opportunity to examine diurnal and seasonal LUE processes and their relationship to spectral indices at the scale of the forest stand. We evaluated LUE in conjunction with the Photochemical Reflectance Index (PRI), a normalized difference spectral index that uses 531 nm and a reference band to capture responses to high light induced stress afforded by the xanthophyll cycle. Canopy structure information, retrieved from airborne laser scanning radar (LiDAR) observations, was used to partition the forest canopy into sunlit and shaded fractions throughout the day, on numerous days during 2006. At each observation period throughout a day, the PRI was examined for the sunlit, shaded, and intermediate canopy segments defined by their instantaneous position relative to the solar principal plane (SPP). The sunlit sector was associated with the illumination "hotspot" (the reflectance backscatter maximum), the shaded sector with the "cold or dark spot" (the reflectance forward scatter minimum), while the intermediate, mixed sunlit/shade sector was located in the cross-plane to the SPP. The PRI indices clearly captured the differences in leaf groups, with sunlit foliage exhibiting the lowest values on sunny days throughout the 2006 season. When tower-based canopy-level LUE was recalculated to estimate foliage-based values (LUE(sub foilage) for the three foliage groups under their incident light environments, a strong linear relationship for PRI:LUE(sub foilage) was demonstrated (0.6 less than or equal to r(sup 2) less than or equal to 0.8, n=822, P<0.0001). The MODIS data represent relatively large areas when acquired at nadir (approx.1 sq km) or at variable off-nadir view angles (greater than or equal to 1 sq km) looking forward or aft. Nevertheless, a similar relationship between MODIS PRI and tower-based LUE was obtained from satellite observations (r(sup 2) = 0.76, n=105, P= 0.026) when the azimuth offsets from the SPP for off-nadir observations were considered. At this relatively high latitude of 50 degrees, the MODIS directional observations were offset from the SPP by approximately 50 degrees, but still represented backscatter or forward scatter sectors of the bidirectional reflectance distribution function (BRDF). The backscatter observations sampled the sunlit forest and provided lower PRI values, in general, than the forward scatter observations from the shaded forest. Since the hotspot and darkspot were not typically directly observed, the dynamic range for MODIS PRI was less than that observed in the SPP at the canopy level; therefore, MODIS PRI values were more similar to those observed in sifu in the BRDF cross-plane. While not ideal in terms of spatial resolution or optimal viewing configuration, the MODIS observations nevertheless provide a means to monitor forest under stress using narrow spectral band indices and off-nadir observations. This research has stimulated several spin-off studies for remote sensinf LUE, and demonstrates the importance of the connection between ecosystem structure and physiological function.

Satellite and Surface Perspectives of Snow Extent in the Southern Appalachian Mountains

NASA Technical Reports Server (NTRS)

Sugg, Johnathan W.; Perry, Baker L.; Hall, Dorothy K.

2012-01-01

Assessing snow cover patterns in mountain regions remains a challenge for a variety of reasons. Topography (e.g., elevation, exposure, aspect, and slope) strongly influences snowfall accumulation and subsequent ablation processes, leading to pronounced spatial variability of snow cover. In-situ observations are typically limited to open areas at lower elevations (<1000 m). In this paper, we use several products from the Moderate Resolution Imaging Spectroradiometer (MODIS) to assess snow cover extent in the Southern Appalachian Mountains (SAM). MODIS daily snow cover maps and true color imagery are analyzed after selected snow events (e.g., Gulf/Atlantic Lows, Alberta Clippers, and Northwest Upslope Flow) from 2006 to 2012 to assess the spatial patterns of snowfall across the SAM. For each event, we calculate snow cover area across the SAM using MODIS data and compare with the Interactive Multi-sensor Snow and ice mapping system (IMS) and available in-situ observations. Results indicate that Gulf/Atlantic Lows are typically responsible for greater snow extent across the entire SAM region due to intensified cyclogenesis associated with these events. Northwest Upslope Flow events result in snow cover extent that is limited to higher elevations (>1000 m) across the SAM, but also more pronounced along NW aspects. Despite some limitations related to the presence of ephemeral snow or cloud cover immediately after each event, we conclude that MODIS products are useful for assessing the spatial variability of snow cover in heavily forested mountain regions such as the SAM.

Assessment of Terra MODIS On-Orbit Polarization Sensitivity Using Pseudoinvariant Desert Sites

NASA Technical Reports Server (NTRS)

Wu, Aisheng; Geng, Xu; Wald, Andrew; Angal, Amit; Xiong, Xiaoxiong

2017-01-01

The Moderate Resolution Imaging Spectroradiometer (MODIS) is currently flying on NASA's Earth Observing System Terra and Aqua satellites, launched in 1999 and 2002, respectively. MODIS reflective solar bands in the visible wavelength range are known to be sensitive to polarized light based on prelaunch polarization sensitivity tests. After about five years of on-orbit operations, it was discovered that the polarization sensitivity at short wavelengths had shown a noticeable increase. In this paper, we examine the impact of polarization on measured top-of-atmosphere (TOA) reflectance based on MODIS Collection-6 L1B over pseudo invariant desert sites. The standard polarization correction equation is used in combination with simulated at-sensor radiances using the second simulation of a satellite signal in the Solar Spectrum, Vector Radiative Transfer Code (6SV). We ignore the polarization contribution from the surface and a ratio approach is used for both 6SV-derived in put parameters and observed TOA reflectance. Results indicate that significant gain corrections up to 25% are required near the end of scan for the 412 and 443 nm bands. The polarization correction reduces the seasonal fluctuations in reflectance trends and mirror side ratios from 30% and 12% to 10% and 5%, respectively, for the two bands. Comparison of the effectiveness of the polarization correction with the results from the NASA Ocean Biology Processing Group shows a good agreement in the corrected reflectance trending results and their seasonal fluctuations.

N-MODY: A Code for Collisionless N-body Simulations in Modified Newtonian Dynamics

NASA Astrophysics Data System (ADS)

Londrillo, Pasquale; Nipoti, Carlo

2011-02-01

N-MODY is a parallel particle-mesh code for collisionless N-body simulations in modified Newtonian dynamics (MOND). N-MODY is based on a numerical potential solver in spherical coordinates that solves the non-linear MOND field equation, and is ideally suited to simulate isolated stellar systems. N-MODY can be used also to compute the MOND potential of arbitrary static density distributions. A few applications of N-MODY indicate that some astrophysically relevant dynamical processes are profoundly different in MOND and in Newtonian gravity with dark matter.

Two decades of satellite observations of AOD over mainland China using ATSR-2, AATSR and MODIS/Terra: data set evaluation and large-scale patterns

NASA Astrophysics Data System (ADS)

de Leeuw, Gerrit; Sogacheva, Larisa; Rodriguez, Edith; Kourtidis, Konstantinos; Georgoulias, Aristeidis K.; Alexandri, Georgia; Amiridis, Vassilis; Proestakis, Emmanouil; Marinou, Eleni; Xue, Yong; van der A, Ronald

2018-02-01

The retrieval of aerosol properties from satellite observations provides their spatial distribution over a wide area in cloud-free conditions. As such, they complement ground-based measurements by providing information over sparsely instrumented areas, albeit that significant differences may exist in both the type of information obtained and the temporal information from satellite and ground-based observations. In this paper, information from different types of satellite-based instruments is used to provide a 3-D climatology of aerosol properties over mainland China, i.e., vertical profiles of extinction coefficients from the Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP), a lidar flying aboard the Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO) satellite and the column-integrated extinction (aerosol optical depth - AOD) available from three radiometers: the European Space Agency (ESA)'s Along-Track Scanning Radiometer version 2 (ATSR-2), Advanced Along-Track Scanning Radiometer (AATSR) (together referred to as ATSR) and NASA's Moderate Resolution Imaging Spectroradiometer (MODIS) aboard the Terra satellite, together spanning the period 1995-2015. AOD data are retrieved from ATSR using the ATSR dual view (ADV) v2.31 algorithm, while for MODIS Collection 6 (C6) the AOD data set is used that was obtained from merging the AODs obtained from the dark target (DT) and deep blue (DB) algorithms, further referred to as the DTDB merged AOD product. These data sets are validated and differences are compared using Aerosol Robotic Network (AERONET) version 2 L2.0 AOD data as reference. The results show that, over China, ATSR slightly underestimates the AOD and MODIS slightly overestimates the AOD. Consequently, ATSR AOD is overall lower than that from MODIS, and the difference increases with increasing AOD. The comparison also shows that neither of the ATSR and MODIS AOD data sets is better than the other one everywhere. However, ATSR ADV has limitations over bright surfaces which the MODIS DB was designed for. To allow for comparison of MODIS C6 results with previous analyses where MODIS Collection 5.1 (C5.1) data were used, also the difference between the C6 and C5.1 merged DTDB data sets from MODIS/Terra over China is briefly discussed. The AOD data sets show strong seasonal differences and the seasonal features vary with latitude and longitude across China. Two-decadal AOD time series, averaged over all of mainland China, are presented and briefly discussed. Using the 17 years of ATSR data as the basis and MODIS/Terra to follow the temporal evolution in recent years when the environmental satellite Envisat was lost requires a comparison of the data sets for the overlapping period to show their complementarity. ATSR precedes the MODIS time series between 1995 and 2000 and shows a distinct increase in the AOD over this period. The two data series show similar variations during the overlapping period between 2000 and 2011, with minima and maxima in the same years. MODIS extends this time series beyond the end of the Envisat period in 2012, showing decreasing AOD.

Improving Access to MODIS Biophysical Science Products for NACP Investigators

NASA Technical Reports Server (NTRS)

Wolfe, Robert E.; Gao, Feng; Morisette, Jeffrey T.; Ederer, Gregory A.; Pedelty, Jeffrey A.

2007-01-01

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

Simultaneous inversion of multiple land surface parameters from MODIS optical-thermal observations

NASA Astrophysics Data System (ADS)

Ma, Han; Liang, Shunlin; Xiao, Zhiqiang; Shi, Hanyu

2017-06-01

Land surface parameters from remote sensing observations are critical in monitoring and modeling of global climate change and biogeochemical cycles. Current methods for estimating land surface variables usually focus on individual parameters separately even from the same satellite observations, resulting in inconsistent products. Moreover, no efforts have been made to generate global products from integrated observations from the optical to Thermal InfraRed (TIR) spectrum. Particularly, Middle InfraRed (MIR) observations have received little attention due to the complexity of the radiometric signal, which contains both reflected and emitted radiation. In this paper, we propose a unified algorithm for simultaneously retrieving six land surface parameters - Leaf Area Index (LAI), Fraction of Absorbed Photosynthetically Active Radiation (FAPAR), land surface albedo, Land Surface Emissivity (LSE), Land Surface Temperature (LST), and Upwelling Longwave radiation (LWUP) by exploiting MODIS visible-to-TIR observations. We incorporate a unified physical radiative transfer model into a data assimilation framework. The MODIS visible-to-TIR time series datasets include the daily surface reflectance product and MIR-to-TIR surface radiance, which are atmospherically corrected from the MODIS data using the Moderate Resolution Transmittance program (MODTRAN, ver. 5.0). LAI was first estimated using a data assimilation method that combines MODIS daily reflectance data and a LAI phenology model, and then the LAI was input to the unified radiative transfer model to simulate spectral surface reflectance and surface emissivity for calculating surface broadband albedo and emissivity, and FAPAR. LST was estimated from the MIR-TIR surface radiance data and the simulated emissivity, using an iterative optimization procedure. Lastly, LWUP was estimated using the LST and surface emissivity. The retrieved six parameters were extensively validated across six representative sites with different biome types, and compared with MODIS, GLASS, and GlobAlbedo land surface products. The results demonstrate that the unified inversion algorithm can retrieve temporally complete and physically consistent land surface parameters, and provides more accurate estimates of surface albedo, LST, and LWUP than existing products, with R2 values of 0.93 and 0.62, RMSE of 0.029 and 0.037, and BIAS values of 0.016 and 0.012 for the retrieved and MODIS albedo products, respectively, compared with field albedo measurements; R2 values of 0.95 and 0.93, RMSE of 2.7 and 4.2 K, and BIAS values of -0.6 and -2.7 K for the retrieved and MODIS LST products, respectively, compared with field LST measurements; and R2 values of 0.93 and 0.94, RMSE of 18.2 and 22.8 W/m2, and BIAS values of -2.7 and -14.6 W/m2 for the retrieved and MODIS LWUP products, respectively, compared with field LWUP measurements.

Initial Verification of GEOS-4 Aerosols Using CALIPSO and MODIS: Scene Classification

NASA Technical Reports Server (NTRS)

Welton, Ellsworth J.; Colarco, Peter R.; Hlavka, Dennis; Levy, Robert C.; Vaughan, Mark A.; daSilva, Arlindo

2007-01-01

A-train sensors such as MODIS and MISR provide column aerosol properties, and in the process a means of estimating aerosol type (e.g. smoke vs. dust). Correct classification of aerosol type is important because retrievals are often dependent upon selection of the right aerosol model. In addition, aerosol scene classification helps place the retrieved products in context for comparisons and analysis with aerosol transport models. The recent addition of CALIPSO to the A-train now provides a means of classifying aerosol distribution with altitude. CALIPSO level 1 products include profiles of attenuated backscatter at 532 and 1064 nm, and depolarization at 532 nm. Backscatter intensity, wavelength ratio, and depolarization provide information on the vertical profile of aerosol concentration, size, and shape. Thus similar estimates of aerosol type using MODIS or MISR are possible with CALIPSO, and the combination of data from all sensors provides a means of 3D aerosol scene classification. The NASA Goddard Earth Observing System general circulation model and data assimilation system (GEOS-4) provides global 3D aerosol mass for sulfate, sea salt, dust, and black and organic carbon. A GEOS-4 aerosol scene classification algorithm has been developed to provide estimates of aerosol mixtures along the flight track for NASA's Geoscience Laser Altimeter System (GLAS) satellite lidar. GLAS launched in 2003 and did not have the benefit of depolarization measurements or other sensors from the A-train. Aerosol typing from GLAS data alone was not possible, and the GEOS-4 aerosol classifier has been used to identify aerosol type and improve the retrieval of GLAS products. Here we compare 3D aerosol scene classification using CALIPSO and MODIS with the GEOS-4 aerosol classifier. Dust, smoke, and pollution examples will be discussed in the context of providing an initial verification of the 3D GEOS-4 aerosol products. Prior model verification has only been attempted with surface mass comparisons and column optical depth from AERONET and MODIS.

Observation of angular effects on thermal infrared emissivity derived with the MODTES algorithm and MODIS data

NASA Astrophysics Data System (ADS)

García-Santos, Vicente; Niclòs, Raquel; Coll, César; Valor, Enric; Caselles, Vicente

2015-04-01

The MOD21 Land Surface Temperature and Emissivity (LST&E) product will be included in forthcoming MODIS Collection 6. Surface temperature and emissivities for thermal infrared (TIR) bands 29 (8.55 μm), 31 (11 μm) and 32 (12 μm) will be retrieved using the ASTER TES method adapted to MODIS at-sensor spectral radiances, previously corrected with the Water Vapor Scaling method (MODTES algorithm). LSE of most natural surfaces changes with soil moisture content, type of surface cover, surface roughness or sensor viewing geometry. The present study addresses the observation of anisotropy effects on LSE of bare soils using MODIS data and a processor simulator of the MOD21 product, since it is not available yet. Two highly homogeneous and quasi-invariant desert sites were selected to carry out the present study. The first one is the White Sands National Monument, located in Tularosa Valley (South-central New Mexico, USA), which is a dune system desert at 1216 m above sea level, with an area of 704 km2 and a maximum dune height of 10 m. The grain size is considered fine sand and the major mineralogy component is gypsum. The second site selected was the Great Sands National Park, located in the San Luis Valley (Colorado, USA). Great Sands is also a sand dune system desert, created from quartz and volcanic fragments derived from Santa Fe and Alamosa formations. The major mineral is quartz, with minor traces of potassium and feldspar. The grain size of the sand is medium to coarse according to the X-Ray Diffraction measurements. Great Sands covers an area of 104 km2 at 2560 m above sea level and the maximum dune height is 230 m. The obtained LSEs and their dependence on azimuth and zenith viewing angles were analyzed, based on series of MODIS scenes from 2010 to 2013. MODTES nadir and off-nadir LSEs showed a good agreement with laboratory emissivity measurements. Results show that band 29 LSE decreases with the zenithal angle up to 0.041 from its nadir value, while LSEs for bands 31 and 32 do not show significant changes with zenith angle.

Verification and Validation of NASA-Supported Enhancements to the Near Real Time Harmful Algal Blooms Observing System (HABSOS)

NASA Technical Reports Server (NTRS)

Spruce, Joseph P.; Hall, Calllie; McPherson, Terry; Spiering, Bruce; Brown, Richard; Estep, Lee; Lunde, Bruce; Guest, DeNeice; Navard, Andy; Pagnutti, Mary;

Biospheric Monitoring and Ecological Forecasting using EOS/MODIS data, ecosystem modeling, planning and scheduling technologies

NASA Astrophysics Data System (ADS)

Nemani, R. R.; Votava, P.; Golden, K.; Hashimoto, H.; Jolly, M.; White, M.; Running, S.; Coughlan, J.

2003-12-01

The latest generation of NASA Earth Observing System satellites has brought a new dimension to continuous monitoring of the living part of the Earth System, the Biosphere. EOS data can now provide weekly global measures of vegetation productivity and ocean chlorophyll, and many related biophysical factors such as land cover changes or snowmelt rates. However, information with the highest economic value would be forecasting impending conditions of the biosphere that would allow advanced decision-making to mitigate dangers, or exploit positive trends. We have developed a software system called the Terrestrial Observation and Prediction System (TOPS) to facilitate rapid analysis of ecosystem states/functions by integrating EOS data with ecosystem models, surface weather observations and weather/climate forecasts. Land products from MODIS (Moderate Resolution Imaging Spectroradiometer) including land cover, albedo, snow, surface temperature, leaf area index are ingested into TOPS for parameterization of models and for verifying model outputs such as snow cover and vegetation phenology. TOPS is programmed to gather data from observing networks such as USDA soil moisture, AMERIFLUX, SNOWTEL to further enhance model predictions. Key technologies enabling TOPS implementation include the ability to understand and process heterogeneous-distributed data sets, automated planning and execution of ecosystem models, causation analysis for understanding model outputs. Current TOPS implementations at local (vineyard) to global scales (global net primary production) can be found at http://www.ntsg.umt.edu/tops.

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

NASA Technical Reports Server (NTRS)

Xiong, X.; Angal, A.; Wu, A.; Link, D.; Geng, X.; Barnes, W.; Solomonson, V.

2016-01-01

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

Monitoring Reservoir Storage in South Asia from Satellite Remote Sensing

NASA Astrophysics Data System (ADS)

Zhang, S.; Gao, H.; Naz, B.

2013-12-01

Realtime reservoir storage information is essential for accurate flood monitoring and prediction in South Asia, where the fatality rate (by area) due to floods is among the highest in the world. However, South Asia is dominated by international river basins where communications among neighboring countries about reservoir storage and management are extremely limited. In this study, we use a suite of NASA satellite observations to achieve high quality estimation of reservoir storage and storage variations at near realtime in South Asia. The monitoring approach employs vegetation indices from the Moderate Resolution Imaging Spectroradiometer (MODIS) 16-day 250 m MOD13Q1 product and the surface elevation data from the Geoscience Laser Altimeter System (GLAS) on board the Ice, Cloud and land Elevation Satellite (ICESat). This approach contains four steps: 1) identifying the reservoirs with ICESat GLAS overpasses and extracting the elevation data for these locations; 2) using the K-means method for water classification from MODIS andapplying a novel post-classification algorithm to enhance water area estimation accuracy; 3) deriving the relationship between the MODIS water surface area and the ICESat elevation; and 4) estimating the storage of reservoirs over time based on the elevation-area relationship and the MODIS water area time series. For evaluation purposes, we compared the satellite-based reservoir storage with gauge observations for 16 reservoirs in South Asia. The storage estimates were highly correlated with observations (R = 0.92 to 0.98), with values for the normalized root mean square error (NRMSE) ranging from 8.7% to 25.2%. Using this approach, storage and storage variations were estimated for 16 South Asia reservoirs from 2000 to 2012.

Exploring the potential of optical remote sensing for oil spill detection in shallow coastal waters--a case study in the Arabian Gulf.

PubMed

Zhao, Jun; Temimi, Marouane; Ghedira, Hosni; Hu, Chuanmin

2014-06-02

Remote sensing provides an effective tool for timely oil pollution response. In this paper, the spectral signature in the optical and infrared domains of oil slicks observed in shallow coastal waters of the Arabian Gulf was investigated with MODIS, MERIS, and Landsat data. Images of the Floating Algae Index (FAI) and estimates of sea currents from hydrodynamic models supported the multi-sensor oil tracking technique. Scenes with and without sunglint were studied as the spectral signature of oil slicks in the optical domain depends upon the viewing geometry and the solar angle in addition to the type of oil and its thickness. Depending on the combination of those factors, oil slicks may exhibit dark or bright contrasts with respect to oil-free waters. Three oil spills events were thoroughly analyzed, namely, those detected on May 26 2000 by Landsat 7 ETM + and MODIS/Terra, on October 21 2007 by MERIS and MODIS, and on August 17 2013 by Landsat 8 and MODIS/Aqua. The oil slick with bright contrast observed by Landsat 7 ETM + on May 26 2000 showed lower temperature than oil-free areas. The spectral Rayleigh-corrected reflectance (R(rc)) signature of oil-covered areas indicated higher variability due to differences in oil fractions while the R(rc) spectra of the oil-free area were persistent. Combined with RGB composites, FAI images showed potentials in differentiating oil slicks from algal blooms. Ocean circulation and wind data were used to track oil slicks and forecast their potential landfall. The developed oil spill maps were in agreement with official records. The synergistic use of satellite observations and hydrodynamic modeling is recommended for establishing an early warning and decision support system for oil pollution response.

Application and Evaluation of MODIS LAI, FPAR, and Albedo ...

EPA Pesticide Factsheets

MODIS vegetation and albedo products provide a more realistic representation of surface conditions for input to the WRF/CMAQ modeling system. However, the initial evaluation of ingesting MODIS data into the system showed mixed results, with increased bias and error for 2-m temperature and reduced bias and error for 2-m mixing ratio. Recently, the WRF/CMAQ land surface and boundary laywer processes have been updated. In this study, MODIS vegetation and albedo data are input to the updated WRF/CMAQ meteorology and air quality simulations for 2006 over a North American (NA) 12-km domain. The evaluation of the simulation results shows that the updated WRF/CMAQ system improves 2-m temperature estimates over the pre-update base modeling system estimates. The MODIS vegetation input produces a realistic spring green-up that progresses through time from the south to north. Overall, MODIS input reduces 2-m mixing ration bias during the growing season. The NA west shows larger positive O3 bias during the growing season because of reduced gas phase deposition resulting from lower O3 deposition velocities driven by reduced vegetation cover. The O3 bias increase associated with the realistic vegetation representation indicates that further improvement may be needed in the WRF/CMAQ system. The National Exposure Research Laboratory’s Atmospheric Modeling Division (AMAD) conducts research in support of EPA’s mission to protect human health and the environment. AMAD’s rese

Enhanced clear sky reflectance near clouds: What can be learned from it about aerosol properties?

NASA Astrophysics Data System (ADS)

Marshak, A.; Varnai, T.; Wen, G.; Chiu, J.

2009-12-01

Studies on aerosol direct and indirect effects require a precise separation of cloud-free and cloudy air. However, separation between cloud-free and cloudy areas from remotely-sensed measurements is ambiguous. The transition zone in the regions around clouds often stretches out tens of km, which are neither precisely clear nor precisely cloudy. We study the transition zone between cloud-free and cloudy air using MODerate-resolution Imaging Spectroradiometer (MODIS) and Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO) measurements. Both instruments show enhanced clear-sky reflectance (MODIS) and clear-sky backscatterer (CALIPSO) near clouds. Analyzing a large dataset of MODIS observations, we examine the effect of three-dimensional radiative interactions between clouds and cloud-free areas, also known as a cloud adjacency effect. The cloud adjacency effect is well observed in MODIS clear-sky data in the vicinity of clouds. Comparing with CALIPSO clear-sky backscatterer measurements, we show that this effect may be responsible for a large portion of the enhanced clear-sky reflectance observed by MODIS. Finally, we describe a simple model that estimates the cloud-induced enhanced reflectances of cloud-free areas in the vicinity of clouds. The model assumes that the enhancement is due entirely to Rayleigh scattering and is therefore bigger at shorter wavelengths, thus creating a so-called apparent “bluing” of aerosols in remote sensing retrievals.

Characterizing LEDAPS surface reflectance products by comparisons with AERONET, field spectrometer, and MODIS data

USGS Publications Warehouse

Maiersperger, Tom; Scaramuzza, Pat; Leigh, Larry; Shrestha, S.; Gallo, Kevin; Jenkerson, Calli B.; Dwyer, John L.

2013-01-01

This study provides a baseline quality check on provisional Landsat Surface Reflectance (SR) products as generated by the U.S. Geological Survey (USGS) Earth Resources Observation and Science (EROS) Center using Landsat Ecosystem Disturbance Adaptive Processing System (LEDAPS) software. Characterization of the Landsat SR products leveraged comparisons between aerosol optical thickness derived from LEDAPS and measured by Aerosol Robotic Network (AERONET), as well as reflectance correlations with field spectrometer and Moderate Resolution Imaging Spectroradiometer (MODIS) data. Results consistently indicated similarity between LEDAPS and alternative data products in longer wavelengths over vegetated areas with no adjacent water, while less reliable performance was observed in shorter wavelengths and sparsely vegetated areas. This study demonstrates the strengths and weaknesses of the atmospheric correction methodology used in LEDAPS, confirming its successful implementation to generate Landsat SR products.

Blue Marble Eastern Hemisphere

NASA Technical Reports Server (NTRS)

2002-01-01

Drawing on data from multiple satellite missions (not all collected at the same time), a team of NASA scientists and graphic artists created layers of global data for everything from the land surface, to polar sea ice, to the light reflected by the chlorophyll in the billions of microscopic plants that grow in the ocean. They wrapped these layers around a globe, set it against a black background, and simulated the hazy edge of the Earth's atmosphere (the limb) that appears in astronaut photography of the Earth. The land surface layer is based on photo-like surface reflectance observations (reflected sunlight) measured by the Moderate Resolution Imaging Spectroradiometer (MODIS) on NASA's Terra satellite in July 2004. The sea ice layer near the poles comes from Terra MODIS observations of daytime sea ice observed between August 28 and September 6, 2001. The ocean layer is a composite. In shallow water areas, the layer shows surface reflectances observed by Terra MODIS in July 2004. In the open ocean, the photo-like layer is overlaid with observations of the average ocean chlorophyll content for 2004. NASA's Aqua MODIS collected the chlorophyll data. The cloud layer shows a single-day snapshot of clouds observed by Terra MODIS across the planet on July 29, 2001. City lights on Earth's night side are visualized from data collected by the Defense Meteorological Satellite Program mission between 1994-1995. The topography layer is based on radar data collected by the Space Shuttle Endeavour during an 11-day mission in February of 2000. Topography over Antarctica comes from the Radarsat Antarctic Mapping Project, version 2.

Blue Marble Western Hemisphere

NASA Technical Reports Server (NTRS)

2002-01-01

Drawing on data from multiple satellite missions (not all collected at the same time), a team of NASA scientists and graphic artists created layers of global data for everything from the land surface, to polar sea ice, to the light reflected by the chlorophyll in the billions of microscopic plants that grow in the ocean. They wrapped these layers around a globe, set it against a black background, and simulated the hazy edge of the Earth's atmosphere (the limb) that appears in astronaut photography of the Earth. The land surface layer is based on photo-like surface reflectance observations (reflected sunlight) measured by the Moderate Resolution Imaging Spectroradiometer (MODIS) on NASA's Terra satellite in July 2004. The sea ice layer near the poles comes from Terra MODIS observations of daytime sea ice observed between August 28 and September 6, 2001. The ocean layer is a composite. In shallow water areas, the layer shows surface reflectances observed by Terra MODIS in July 2004. In the open ocean, the photo-like layer is overlaid with observations of the average ocean chlorophyll content for 2004. NASA's Aqua MODIS collected the chlorophyll data. The cloud layer shows a single-day snapshot of clouds observed by Terra MODIS across the planet on July 29, 2001. City lights on Earth's night side are visualized from data collected by the Defense Meteorological Satellite Program mission between 1994-1995. The topography layer is based on radar data collected by the Space Shuttle Endeavour during an 11-day mission in February of 2000. Topography over Antarctica comes from the Radarsat Antarctic Mapping Project, version 2.

Simulating Visible/Infrared Imager Radiometer Suite Normalized Difference Vegetation Index Data Using Hyperion and MODIS

NASA Technical Reports Server (NTRS)

Ross, Kenton W.; Russell, Jeffrey; Ryan, Robert E.

2006-01-01

The success of MODIS (the Moderate Resolution Imaging Spectrometer) in creating unprecedented, timely, high-quality data for vegetation and other studies has created great anticipation for data from VIIRS (the Visible/Infrared Imager Radiometer Suite). VIIRS will be carried onboard the joint NASA/Department of Defense/National Oceanic and Atmospheric Administration NPP (NPOESS (National Polar-orbiting Operational Environmental Satellite System) Preparatory Project). Because the VIIRS instruments will have lower spatial resolution than the current MODIS instruments 400 m versus 250 m at nadir for the channels used to generate Normalized Difference Vegetation Index data, scientists need the answer to this question: how will the change in resolution affect vegetation studies? By using simulated VIIRS measurements, this question may be answered before the VIIRS instruments are deployed in space. Using simulated VIIRS products, the U.S. Department of Agriculture and other operational agencies can then modify their decision support systems appropriately in preparation for receipt of actual VIIRS data. VIIRS simulations and validations will be based on the ART (Application Research Toolbox), an integrated set of algorithms and models developed in MATLAB(Registerd TradeMark) that enables users to perform a suite of simulations and statistical trade studies on remote sensing systems. Specifically, the ART provides the capability to generate simulated multispectral image products, at various scales, from high spatial hyperspectral and/or multispectral image products. The ART uses acquired ( real ) or synthetic datasets, along with sensor specifications, to create simulated datasets. For existing multispectral sensor systems, the simulated data products are used for comparison, verification, and validation of the simulated system s actual products. VIIRS simulations will be performed using Hyperion and MODIS datasets. The hyperspectral and hyperspatial properties of Hyperion data will be used to produce simulated MODIS and VIIRS products. Hyperion-derived MODIS data will be compared with near-coincident MODIS collects to validate both spectral and spatial synthesis, which will ascertain the accuracy of converting from MODIS to VIIRS. MODIS-derived VIIRS data is needed for global coverage and for the generation of time series for regional and global investigations. These types of simulations will have errors associated with aliasing for some scene types. This study will help quantify these errors and will identify cases where high-quality, MODIS-derived VIIRS data will be available.

A System for Monitoring and Forecasting Land Surface Phenology Using Time Series of JPSS VIIRS Observations and Its Applications

NASA Astrophysics Data System (ADS)

Zhang, X.; Yu, Y.; Liu, L.

2015-12-01

Land surface phenology quantifies seasonal dynamics of vegetation properties including the timing and magnitude of vegetation greenness from satellite observations. Over the last decade, historical time series of AVHRR and MODIS data has been used to characterize the seasonal and interannual variation in terrestrial ecosystems and their responses to a changing and variable climate. The Visible Infrared Imaging Radiometer Suite (VIIRS) instrument on board the operational JPSS satellites provides land surface observations in a timely fashion, which has the capability to monitor phenological development in near real time. This capability is particularly important for assisting agriculture, natural resource management, and land modeling for weather prediction systems. Here we introduce a system to monitor in real time and forecast in the short term phenological development based on daily VIIRS observations available with a one-day latency. The system integrates a climatological land surface phenology from long-term MODIS data and available VIIRS observations to simulate a set of potential temporal trajectories of greenness development at a given time and pixel. The greenness trajectories, which are qualified using daily two-band Enhanced Vegetation Index (EVI2), are applied to identify spring green leaf development and autumn color foliage status in real time and to predict the occurrence of future phenological events. This system currently monitors vegetation development across the North America every three days and makes prediction to 10 days ahead. We further introduce the applications of near real time spring green leaf and fall color foliage. Specifically, this system is used for tracing the crop progress across the United States, guiding the field observations in US National Phenology Network, servicing tourists for the observation of color fall foliage, and parameterizing seasonal surface physical conditions for numerical weather prediction models.

Improvement of Operational Streamflow Prediction with MODIS-derived Fractional Snow Covered Area Observations

NASA Astrophysics Data System (ADS)

Bender, S.; Burgess, A.; Goodale, C. E.; Mattmann, C. A.; Miller, W. P.; Painter, T. H.; Rittger, K. E.; Stokes, M.; Werner, K.

2013-12-01

Water managers in the western United States depend heavily on the timing and magnitude of snowmelt-driven runoff for municipal supply, irrigation, maintenance of environmental flows, and power generation. The Colorado Basin River Forecast Center (CBRFC) of the National Weather Service issues operational forecasts of snowmelt-driven streamflow for watersheds within the Colorado River Basin (CRB) and eastern Great Basin (EGB), across a wide variety of scales. Therefore, the CBRFC and its stakeholders consider snowpack observations to be highly valuable. Observations of fractional snow covered area (fSCA) from satellite-borne instrumentation can better inform both forecasters and water users with respect to subsequent snowmelt runoff, particularly when combined with observations from ground-based station networks and/or airborne platforms. As part of a multi-year collaborative effort, CBRFC has partnered with the Jet Propulsion Laboratory (JPL) under funding from NASA to incorporate observations of fSCA from NASA's Moderate Resolution Imaging Spectroradiometer (MODIS) into the operational CBRFC hydrologic forecasting and modeling process. In the first year of the collaboration, CBRFC and NASA/JPL integrated snow products into the forecasting and decision making processes of the CBRFC and showed preliminary improvement in operational streamflow forecasts. In late 2012, CBRFC and NASA/JPL began retrospective analysis of relationships between the MODIS Snow Covered Area and Grain size (MODSCAG) fSCA and streamflow patterns for several watersheds within the CRB and the EGB. During the 2013 snowmelt runoff season, CBRFC forecasters used MODIS-derived fSCA semi-quantitatively as a binary indicator of the presence or lack of snow. Indication of the presence or lack of snow by MODIS assisted CBRFC forecasters in determining the cause of divergence between modeled and recently observed streamflow. Several examples of improved forecasts from across the CRB and EGB, informed by MODIS-derived fSCA, are described. Our analysis shows the value of MODIS fSCA to CBRFC and to users of CBRFC's streamflow forecasts. The relationships between the MODIS fSCA and the melt season streamflow vary with the magnitude of runoff, which is important to resource managers. The analysis also emphasizes the importance of the invaluable collaboration between an operational forecasting agency (CBRFC) and a research-oriented agency (NASA/JPL) specializing in remote sensing science. The collaboration is expected to continue over the next several years as CBRFC and JPL work to further improve modeling of snowmelt and prediction of snowmelt-driven streamflow in the CRB and EGB.

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 MODIS and the mirror side differences are much smaller. Overall, Aqua MODIS RSB on-orbit performance is better than Terra MODIS.

A multi-scale assessment of forest primary production across the eastern USA using Forest Inventory and Analysis (FIA) and MODIS data

NASA Astrophysics Data System (ADS)

Kwon, Youngsang

As evidence of global warming continues to increase, being able to predict the relationship between forest growth rate and climate factors will be vital to maintain the sustainability and productivity of forests. Comprehensive analyses of forest primary production across the eastern US were conducted using remotely sensed MODIS and field-based FIA datasets. This dissertation primarily explored spatial patterns of gross and net carbon uptake in the eastern USA, and addressed three objectives. 1) Examine the use of pixel- and plot-scale screening variables to validate MODIS GPP predictions with Forest Inventory and Analysis (FIA) NPP measures. 2) Assess the net primary production (NPP) from MODIS and FIA at increasing levels of spatial aggregation using a hexagonal tiling system. 3) Assess the carbon use efficiency (CUE) calculated using a direct ratio of MODIS NPP to MODIS GPP and a standardized ratio of FIA NPP to MODIS GPP. The first objective was analyzed using total of 54,969 MODIS pixels and co-located FIA plots to validate MODIS GPP estimates. Eight SVs were used to test six hypotheses about the conditions under which MODIS GPP would be most strongly validated. SVs were assessed in terms of the tradeoff between improved relations and reduced number of samples. MODIS seasonal variation and FIA tree density were the two most efficient SVs followed by basic quality checks for each data set. The sequential application of SVs provided an efficient dataset of 17,090 co-located MODIS pixels and FIA plots, that raised the Pearson's correlation coefficient from 0.01 for the complete dataset of 54,969 plots to 0.48 for this screened subset of 17,090 plots. The second objective was addressed by aggregating data over increasing spatial extents so as to not lose plot- and pixel-level information. These data were then analyzed to determine the optimal scale with which to represent the spatial pattern of NPP. The results suggested an optimal scale of 390 km2. At that scale MODIS and FIA were most strongly correlated while maximizing the number of observation. The maps conveyed both local-scale spatial structure from FIA and broad-scale climatic trends from MODIS. The third objective examined whether carbon use efficiency (CUE) was constant or variable in relation to forest types, and to geographic and climatic variables. The results indicated that while CUEs exhibited unclear patterns by forest types, CUEs are variable to other environmental variables. CUEs are most strongly related to the climatic factors of precipitation followed by temperature. More complex and weaker relationships were found for the geographic factors of latitude and altitude, as they reflected a combination of phenomenological driving forces. The results of the three objectives will help us to identify factors that control carbon cycles and to quantify forest productivity. This will help improve our knowledge about how forest primary productivity may change in relation to ongoing climate change.

NLCD - MODIS albedo data

EPA Pesticide Factsheets

The NLCD-MODIS land cover-albedo database integrates high-quality MODIS albedo observations with areas of homogeneous land cover from NLCD. The spatial resolution (pixel size) of the database is 480m-x-480m aligned to the standardized UGSG Albers Equal-Area projection. The spatial extent of the database is the continental United States. This dataset is associated with the following publication:Wickham , J., C.A. Barnes, and T. Wade. Combining NLCD and MODIS to Create a Land Cover-Albedo Dataset for the Continental United States. REMOTE SENSING OF ENVIRONMENT. Elsevier Science Ltd, New York, NY, USA, 170(0): 143-153, (2015).

An Approach for the Long-Term 30-m Land Surface Snow-Free Albedo Retrieval from Historic Landsat Surface Reflectance and MODIS-based A Priori Anisotropy Knowledge

NASA Technical Reports Server (NTRS)

Shuai, Yanmin; Masek, Jeffrey G.; Gao, Feng; Schaaf, Crystal B.; He, Tao

2014-01-01

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 MODIS, 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 "MODIS-concurrent" approach for the 30-meter albedo estimation which relied on combining post-2000 Landsat data with MODIS Bidirectional Reflectance Distribution Function (BRDF) information. Here we present a "pre-MODIS 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 reflects 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 MODIS 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 reflectance ratios as a bridge between the Landsat and MODIS 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 respectively with that from the "concurrent" approach and the coincident MODIS operational surface albedo products. Using the tower measurements as reference, the derived Landsat 30-m snow-free shortwave broadband albedo yields an absolute accuracy of 0.02 with a root mean square error less than 0.016 and a bias of no more than 0.007. A further cross-comparison over individual scenes shows that the retrieved white sky shortwave albedo from the "pre-MODIS era" LUT approach is highly consistent (R(exp 2) = 0.988, the scene-averaged low RMSE = 0.009 and bias = -0.005) with that generated by the earlier "concurrent" approach. The Landsat albedo also exhibits more detailed landscape texture and a wider dynamic range of albedo values than the coincident 500-m MODIS operational products (MCD43A3), especially in the heterogeneous regions. Collectively, the "pre-MODIS" LUT and "concurrent" approaches provide a practical way to retrieve long-term Landsat albedo from the historic Landsat archives as far back as the 1980s, as well as the current Landsat-8 mission, and thus support investigations into the evolution of the albedo of terrestrial biomes at fine resolution.

Near-real-time Estimation and Forecast of Total Precipitable Water in Europe

NASA Astrophysics Data System (ADS)

Bartholy, J.; Kern, A.; Barcza, Z.; Pongracz, R.; Ihasz, I.; Kovacs, R.; Ferencz, C.

2013-12-01

Information about the amount and spatial distribution of atmospheric water vapor (or total precipitable water) is essential for understanding weather and the environment including the greenhouse effect, the climate system with its feedbacks and the hydrological cycle. Numerical weather prediction (NWP) models need accurate estimations of water vapor content to provide realistic forecasts including representation of clouds and precipitation. In the present study we introduce our research activity for the estimation and forecast of atmospheric water vapor in Central Europe using both observations and models. The Eötvös Loránd University (Hungary) operates a polar orbiting satellite receiving station in Budapest since 2002. This station receives Earth observation data from polar orbiting satellites including MODerate resolution Imaging Spectroradiometer (MODIS) Direct Broadcast (DB) data stream from satellites Terra and Aqua. The received DB MODIS data are automatically processed using freely distributed software packages. Using the IMAPP Level2 software total precipitable water is calculated operationally using two different methods. Quality of the TPW estimations is a crucial question for further application of the results, thus validation of the remotely sensed total precipitable water fields is presented using radiosonde data. In a current research project in Hungary we aim to compare different estimations of atmospheric water vapor content. Within the frame of the project we use a NWP model (DBCRAS; Direct Broadcast CIMSS Regional Assimilation System numerical weather prediction software developed by the University of Wisconsin, Madison) to forecast TPW. DBCRAS uses near real time Level2 products from the MODIS data processing chain. From the wide range of the derived Level2 products the MODIS TPW parameter found within the so-called mod07 results (Atmospheric Profiles Product) and the cloud top pressure and cloud effective emissivity parameters from the so-called mod06 results (Cloud Product) are assimilated twice a day (at 00 and 12 UTC) by DBCRAS. DBCRAS creates 72 hours long weather forecasts with 48 km horizontal resolution. DBCRAS is operational at the University since 2009 which means that by now sufficient data is available for the verification of the model. In the present study verification results for the DBCRAS total precipitable water forecasts are presented based on analysis data from the European Centre for Medium-Range Weather Forecasts (ECMWF). Numerical indices are calculated to quantify the performance of DBCRAS. During a limited time period DBCRAS was also ran without assimilating MODIS products which means that there is possibility to quantify the effect of assimilating MODIS physical products on the quality of the forecasts. For this limited time period verification indices are compared to decide whether MODIS data improves forecast quality or not.

N-MODY: a code for collisionless N-body simulations in modified Newtonian dynamics.

NASA Astrophysics Data System (ADS)

Londrillo, P.; Nipoti, C.

We describe the numerical code N-MODY, a parallel particle-mesh code for collisionless N-body simulations in modified Newtonian dynamics (MOND). N-MODY is based on a numerical potential solver in spherical coordinates that solves the non-linear MOND field equation, and is ideally suited to simulate isolated stellar systems. N-MODY can be used also to compute the MOND potential of arbitrary static density distributions. A few applications of N-MODY indicate that some astrophysically relevant dynamical processes are profoundly different in MOND and in Newtonian gravity with dark matter.

Radiative effects of global MODIS cloud regimes

PubMed Central

Oreopoulos, Lazaros; Cho, Nayeong; Lee, Dongmin; Kato, Seiji

2018-01-01

We update previously published MODIS global cloud regimes (CRs) using the latest MODIS cloud retrievals in the Collection 6 dataset. 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 datasets. Our results clearly show 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 Aqua 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 datasets 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. PMID:29619289

Radiative effects of global MODIS cloud regimes.

PubMed

Oreopoulos, Lazaros; Cho, Nayeong; Lee, Dongmin; Kato, Seiji

2016-03-16

We update previously published MODIS global cloud regimes (CRs) using the latest MODIS cloud retrievals in the Collection 6 dataset. 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 datasets. Our results clearly show 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 Aqua 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 datasets 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.

Radiative Effects of Global MODIS Cloud Regimes

NASA Technical Reports Server (NTRS)

Oraiopoulos, Lazaros; Cho, Nayeong; Lee, Dong Min; Kato, Seiji

2016-01-01

We update previously published MODIS global cloud regimes (CRs) using the latest MODIS cloud retrievals in the Collection 6 dataset. 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 datasets. Our results clearly show 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 Aqua 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 datasets 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.

Seasonal Surface Spectral Emissivity Derived from Terra MODIS Data

NASA Technical Reports Server (NTRS)

Sun-Mack, Sunny; Chen, Yan; Minnis, Patrick; Young, DavidF.; Smith, William J., Jr.

2004-01-01

The CERES (Clouds and the Earth's Radiant Energy System) Project is measuring broadband shortwave and longwave radiances and deriving cloud properties form various images to produce a combined global radiation and cloud property data set. In this paper, simultaneous data from Terra MODIS (Moderate Resolution Imaging Spectroradiometer) taken at 3.7, 8.5, 11.0, and 12.0 m are used to derive the skin temperature and the surface emissivities at the same wavelengths. The methodology uses separate measurements of clear sky temperature in each channel determined by scene classification during the daytime and at night. The relationships between the various channels at night are used during the day when solar reflectance affects the 3.7- m radiances. A set of simultaneous equations is then solved to derive the emissivities. Global monthly emissivity maps are derived from Terra MODIS data while numerical weather analyses provide soundings for correcting the observed radiances for atmospheric absorption. These maps are used by CERES and other cloud retrieval algorithms.

Examination of Regional Trends in Cloud Properties over Surface Sites Derived from MODIS and AVHRR using the CERES Cloud Algorithm

NASA Astrophysics Data System (ADS)

Smith, W. L., Jr.; Minnis, P.; Bedka, K. M.; Sun-Mack, S.; Chen, Y.; Doelling, D. R.; Kato, S.; Rutan, D. A.

2017-12-01

Recent studies analyzing long-term measurements of surface insolation at ground sites suggest that decadal-scale trends of increasing (brightening) and decreasing (dimming) downward solar flux have occurred at various times over the last century. Regional variations have been reported that range from near 0 Wm-2/decade to as large as 9 Wm-2/decade depending on the location and time period analyzed. The more significant trends have been attributed to changes in overhead clouds and aerosols, although quantifying their relative impacts using independent observations has been difficult, owing in part to a lack of consistent long-term measurements of cloud properties. This paper examines new satellite based records of cloud properties derived from MODIS (2000-present) and AVHRR (1981- present) data to infer cloud property trends over a number of surface radiation sites across the globe. The MODIS cloud algorithm was developed for the NASA Clouds and the Earth's Radiant Energy System (CERES) project to provide a consistent record of cloud properties to help improve broadband radiation measurements and to better understand cloud radiative effects. The CERES-MODIS cloud algorithm has been modified to analyze other satellites including the AVHRR on the NOAA satellites. Compared to MODIS, obtaining consistent cloud properties over a long period from AVHRR is a much more significant challenge owing to the number of different satellites, instrument calibration uncertainties, orbital drift and other factors. Nevertheless, both the MODIS and AVHRR cloud properties will be analyzed to determine trends, and their level of consistency and correspondence with surface radiation trends derived from the ground-based radiometer data. It is anticipated that this initial study will contribute to an improved understanding of surface solar radiation trends and their relationship to clouds.

Reconnoitering the effect of shallow groundwater on land surface temperature and surface energy balance using MODIS and SEBS

USDA-ARS?s Scientific Manuscript database

The possibility of observing shallow groundwater depth and areal extent using satellite measurements can support groundwater models and vast irrigation systems management. Besides, these measurements help to integrate groundwater effects on surface energy balance within land surface models and clima...

Using MODIS Cloud Regimes to Sort Diagnostic Signals of Aerosol-Cloud-Precipitation Interactions

PubMed Central

Oreopoulos, Lazaros; Cho, Nayeong; Lee, Dongmin

2018-01-01

Coincident multi-year measurements of aerosol, cloud, precipitation and radiation at near-global scales are analyzed to diagnose their apparent relationships as suggestive of interactions previously proposed based on theoretical, observational, and model constructs. Specifically, we examine whether differences in aerosol loading in separate observations go along with consistently different precipitation, cloud properties, and cloud radiative effects. Our analysis uses a cloud regime (CR) framework to dissect and sort the results. The CRs come from the Moderate Resolution Imaging Spectroradiometer (MODIS) sensor and are defined as distinct groups of cloud systems with similar co-variations of cloud top pressure and cloud optical thickness. Aerosol optical depth used as proxy for aerosol loading comes from two sources, MODIS observations, and the MERRA-2 re-analysis, and its variability is defined with respect to local seasonal climatologies. The choice of aerosol dataset impacts our results substantially. We also find that the responses of the marine and continental component of a CR are frequently quite disparate. Overall, CRs dominated by warm clouds tend to exhibit less ambiguous signals, but also have more uncertainty with regard to precipitation changes. Finally, we find weak, but occasionally systematic co-variations of select meteorological indicators and aerosol, which serves as a sober reminder that ascribing changes in cloud and cloud-affected variables solely to aerosol variations is precarious. PMID:29651373

Using MODIS Cloud Regimes to Sort Diagnostic Signals of Aerosol-Cloud-Precipitation Interactions.

PubMed

Oreopoulos, Lazaros; Cho, Nayeong; Lee, Dongmin

2017-05-27

Coincident multi-year measurements of aerosol, cloud, precipitation and radiation at near-global scales are analyzed to diagnose their apparent relationships as suggestive of interactions previously proposed based on theoretical, observational, and model constructs. Specifically, we examine whether differences in aerosol loading in separate observations go along with consistently different precipitation, cloud properties, and cloud radiative effects. Our analysis uses a cloud regime (CR) framework to dissect and sort the results. The CRs come from the Moderate Resolution Imaging Spectroradiometer (MODIS) sensor and are defined as distinct groups of cloud systems with similar co-variations of cloud top pressure and cloud optical thickness. Aerosol optical depth used as proxy for aerosol loading comes from two sources, MODIS observations, and the MERRA-2 re-analysis, and its variability is defined with respect to local seasonal climatologies. The choice of aerosol dataset impacts our results substantially. We also find that the responses of the marine and continental component of a CR are frequently quite disparate. Overall, CRs dominated by warm clouds tend to exhibit less ambiguous signals, but also have more uncertainty with regard to precipitation changes. Finally, we find weak, but occasionally systematic co-variations of select meteorological indicators and aerosol, which serves as a sober reminder that ascribing changes in cloud and cloud-affected variables solely to aerosol variations is precarious.

Current NASA Earth Remote Sensing Observations

NASA Technical Reports Server (NTRS)

Luvall, Jeffrey C.; Sprigg, William A.; Huete, Alfredo; Pejanovic, Goran; Nickovic, Slobodan; Ponce-Campos, Guillermo; Krapfl, Heide; Budge, Amy; Zelicoff, Alan; Myers, Orrin;

Dust transport model validation using satellite- and ground-based methods in the southwestern United States

NASA Astrophysics Data System (ADS)

Mahler, Anna-Britt; Thome, Kurt; Yin, Dazhong; Sprigg, William A.

2006-08-01

Dust is known to aggravate respiratory diseases. This is an issue in the desert southwestern United States, where windblown dust events are common. The Public Health Applications in Remote Sensing (PHAiRS) project aims to address this problem by using remote-sensing products to assist in public health decision support. As part of PHAiRS, a model for simulating desert dust cycles, the Dust Regional Atmospheric Modeling (DREAM) system is employed to forecast dust events in the southwestern US. Thus far, DREAM has been validated in the southwestern US only in the lower part of the atmosphere by comparison with measurement and analysis products from surface synoptic, surface Meteorological Aerodrome Report (METAR), and upper-air radiosonde. This study examines the validity of the DREAM algorithm dust load prediction in the desert southwestern United States by comparison with satellite-based MODIS level 2 and MODIS Deep Blue aerosol products, and ground-based observations from the AERONET network of sunphotometers. Results indicate that there are difficulties obtaining MODIS L2 aerosol optical thickness (AOT) data in the desert southwest due to low AOT algorithm performance over areas with high surface reflectances. MODIS Deep Blue aerosol products show improvement, but the temporal and vertical resolution of MODIS data limit its utility for DREAM evaluation. AERONET AOT data show low correlation to DREAM dust load predictions. The potential contribution of space- or ground-based lidar to the PHAiRS project is also examined.

Ocean Data from MODIS at the NASA Goddard DAAC

NASA Technical Reports Server (NTRS)

Leptoukh, Gregory G.; Wharton, Stephen (Technical Monitor)

2000-01-01

Terra satellite carrying the Moderate Resolution Imaging Spectroradiometer (MODIS) was successfully launched on December 18, 1999. Some of the 36 different wavelengths that MODIS samples have never before been measured from space. New ocean data products, which have not been derived on a global scale before, are made available for research to the scientific community. For example, MODIS uses a new split window in the four-micron region for the better measurement of Sea Surface Temperature (SST), and provides the unprecedented ability (683 nm band) to measure chlorophyll fluorescence. At full ocean production, more than a thousand different ocean products in three major categories (ocean color, sea surface temperature, and ocean primary production) are archived at the NASA Goddard Earth Sciences (GES) Distributed Active Archive Center (DAAC) at the rate of approx. 230GB/day. The challenge is to distribute such large volumes of data to the ocean community. It is achieved through a combination of public and restricted EOS Data Gateways, the GES DAAC Search and Order WWW interface, and an FTP site that contains samples of MODIS data. A new Search and Order WWW interface at http://acdisx.gsfc.nasa.gov/data/ developed at the GES DAAC is based on a hierarchical organization of data, will always return non-zero results. It has a very convenient geographical representation of five-minute data granule coverage for each day MODIS Data Support Team (MDST) continues the tradition of quality support at the GES DAAC for the ocean color data from the Coastal Zone Color Scanner (CZCS) and the Sea Viewing Wide Field-of-View Sensor (SeaWiFS) by providing expert assistance to users in accessing data products, information on visualization tools, documentation for data products and formats (Hierarchical Data Format-Earth Observing System (HDF-EOS)), information on the scientific content of products and metadata. Visit the MDST website at http://daac.gsfc.nasa.gov/CAMPAIGN DOCS/MODIS/index.html

View Angle Effects on MODIS Snow Mapping in Forests

NASA Technical Reports Server (NTRS)

Xin, Qinchuan; Woodcock, Curtis E.; Liu, Jicheng; Tan, Bin; Melloh, Rae A.; Davis, Robert E.

2012-01-01

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

Recent Monitoring of Suspended Sediment Patterns along Louisiana's Coastal Zone using ER-2 based MAS Data and Terra Based MODIS Data

NASA Technical Reports Server (NTRS)

Moeller, Christopher C.; Gunshor, M. M.; Menzel, W. P.; Huh, O. K.; Walker, N. D.; Rouse, L. J.

2001-01-01

The University nf Wisconsin and Louisiana State University have teamed to study the forcing of winter season cold frontal wind systems on sediment distribution patterns and geomorphology in the Louisiana coastal zone. Wind systems associated with cold fronts have been shown to model coastal circulation and resuspend sediments along the micro tidal Louisiana coast (Roberts et at. 1987, Moeller et al. 1993). Remote sensing data is being used to map and track sediment distribution patterns for various wind conditions. Suspended sediment is a building material for coastal progradation and wetlands renewal, but also restricts access to marine nursery environments and impacts oyster bed health. Transferring a suspended sediment concentration (SSC) algorithm to EOS MODerate resolution Imaging Spectroradiometer (MODIS; Barnes et al. 1998) observations may enable estimates of SSC globally.

Characterization of east Asian dust outbreaks in the spring of 2001 using ground-based and satellite data

NASA Astrophysics Data System (ADS)

Darmenova, Kremena; Sokolik, Irina N.; Darmenov, Anton

2005-01-01

This study presents a detailed examination of east Asian dust events during March-April of 2001, by combining satellite multisensor observation (Total Ozone Mapping Spectrometer (TOMS), Moderate-Resolution Imaging Spectroradiometer (MODIS), and Sea-Viewing Wide Field-of-View Sensor (SeaWiFS)) meteorological data from weather stations in China and Mongolia and the Pennsylania State University/National Center for Atmospheric Research Mesoscale Modeling System (MM5) driven by the National Centers for Environmental Prediction Reanalysis data. The main goal is to determine the extent to which the routine surface meteorological observations (including visibility) and satellite data can be used to characterize the spatiotemporal distribution of dust plumes at a range of scales. We also examine the potential of meteorological time series for constraining the dust emission schemes used in aerosol transport models. Thirty-five dust events were identified in the source region during March and April of 2001 and characterized on a case-by-case basis. The midrange transport routes were reconstructed on the basis of visibility observations and observed and MM5-predicted winds with further validation against satellite data. We demonstrate that the combination of visibility data, TOMS aerosol index, MODIS aerosol optical depth over the land, and a qualitative analysis of MODIS and SeaWiFS imagery enables us to constrain the regions of origin of dust outbreaks and midrange transport, though various limitations of individual data sets were revealed in detecting dust over the land. Only two long-range transport episodes were found. The transport routes and coverage of these dust episodes were reconstructed by using MODIS aerosol optical depth and TOMS aerosol index. Our analysis reveals that over the oceans the presence of persistent clouds poses a main problem in identifying the regions affected by dust transport, so only partial reconstruction of dust transport routes reaching the west coast of the United States was possible.

Potential of VIIRS Data for Regional Monitoring of Gypsy Moth Defoliation: Implications for Forest Threat Early Warning System

NASA Technical Reports Server (NTRS)

Spruce, Joseph P.; Ryan, Robert E.; Smoot, James C.; Prados, Donald; McKellip, Rodney; Sader. Steven A.; Gasser, Jerry; May, George; Hargrove, William

2007-01-01

A NASA RPC (Rapid Prototyping Capability) experiment was conducted to assess the potential of VIIRS (Visible/Infrared Imager/Radiometer Suite) data for monitoring non-native gypsy moth (Lymantria dispar) defoliation of forests. This experiment compares defoliation detection products computed from simulated VIIRS and from MODIS (Moderate Resolution Imaging Spectroradiometer) time series products as potential inputs to a forest threat EWS (Early Warning System) being developed for the USFS (USDA Forest Service). Gypsy moth causes extensive defoliation of broadleaved forests in the United States and is specifically identified in the Healthy Forest Restoration Act (HFRA) of 2003. The HFRA mandates development of a national forest threat EWS. This system is being built by the USFS and NASA is aiding integration of needed satellite data products into this system, including MODIS products. This RPC experiment enabled the MODIS follow-on, VIIRS, to be evaluated as a data source for EWS forest monitoring products. The experiment included 1) assessment of MODIS-simulated VIIRS NDVI products, and 2) evaluation of gypsy moth defoliation mapping products from MODIS-simulated VIIRS and from MODIS NDVI time series data. This experiment employed MODIS data collected over the approximately 15 million acre mid-Appalachian Highlands during the annual peak defoliation time frame (approximately June 10 through July 27) during 2000-2006. NASA Stennis Application Research Toolbox software was used to produce MODIS-simulated VIIRS data and NASA Stennis Time Series Product Tool software was employed to process MODIS and MODIS-simulated VIIRS time series data scaled to planetary reflectance. MODIS-simulated VIIRS data was assessed through comparison to Hyperion-simulated VIIRS data using data collected during gypsy moth defoliation. Hyperion-simulated MODIS data showed a high correlation with actual MODIS data (NDVI R2 of 0.877 and RMSE of 0.023). MODIS-simulated VIIRS data for the same date showed moderately high correlation with Hyperion-simulated VIIRS data (NDVI R2 of 0.62 and RMSE of 0.035), even though the datasets were collected about a half an hour apart during changing weather conditions. MODIS products (MOD02, MOD09, and MOD13) and MOD02-simulated VIIRS time series data were used to generate defoliation mapping products based on image classification and image differencing change detection techniques. Accuracy of final defoliation mapping products was assessed by image interpreting over 170 randomly sampled locations found on Landsat and ASTER data in conjunction with defoliation map data from the USFS. The MOD02-simulated VIIRS 400-meter NDVI classification produced a similar overall accuracy (87.28 percent with 0.72 Kappa) to the MOD02 250-meter NDVI classification (86.71 percent with 0.71 Kappa). In addition, the VIIRS 400-meter NDVI, MOD02 250-meter NDVI, and MOD02 500-meter NDVI showed good user and producer accuracies for the defoliated forest class (70 percent) and acceptable Kappa values (0.66). MOD02 and MOD02-simulated VIIRS data both showed promise as data sources for regional monitoring of forest disturbance due to insect defoliation.

Evaluation of NCAR CAM5 Simulated Marine Boundary Layer Cloud Properties Using a Combination of Satellite and Surface Observations

NASA Astrophysics Data System (ADS)

Zhang, Z.; Song, H.; Wang, M.; Ghan, S. J.; Dong, X.

2016-12-01

he main objective of this study is to systematically evaluate the MBL cloud properties simulated in CAM5 family models using a combination of satellite-based CloudSat/MODIS observations and ground-based observations from the ARM Azores site, with a special focus on MBL cloud microphysics and warm rain process. First, we will present a global evaluation based on satellite observations and retrievals. We will compare global cloud properties (e.g., cloud fraction, cloud vertical structure, cloud CER, COT, and LWP, as well as drizzle frequency and intensity diagnosed using the CAM5-COSP instrumental simulators) simulated in the CAM5 models with the collocated CloudSat and MODIS observations. We will also present some preliminary results from a regional evaluation based mainly on ground observations from ARM Azores site. We will compare MBL cloud properties simulated in CAM5 models over the ARM Azores site with collocated satellite (MODIS and CloudSat) and ground-based observations from the ARM site.

Vegetation chlorophyll estimates in the Amazon from multi-angle MODIS observations and canopy reflectance model

NASA Astrophysics Data System (ADS)

Hilker, Thomas; Galvão, Lênio Soares; Aragão, Luiz E. O. C.; de Moura, Yhasmin M.; do Amaral, Cibele H.; Lyapustin, Alexei I.; Wu, Jin; Albert, Loren P.; Ferreira, Marciel José; Anderson, Liana O.; dos Santos, Victor A. H. F.; Prohaska, Neill; Tribuzy, Edgard; Barbosa Ceron, João Vitor; Saleska, Scott R.; Wang, Yujie; de Carvalho Gonçalves, José Francisco; de Oliveira Junior, Raimundo Cosme; Cardoso Rodrigues, João Victor Figueiredo; Garcia, Maquelle Neves

2017-06-01

As a preparatory study for future hyperspectral missions that can measure canopy chemistry, we introduce a novel approach to investigate whether multi-angle Moderate Resolution Imaging Spectroradiometer (MODIS) data can be used to generate a preliminary database with long-term estimates of chlorophyll. MODIS monthly chlorophyll estimates between 2000 and 2015, derived from a fully coupled canopy reflectance model (ProSAIL), were inspected for consistency with eddy covariance fluxes, tower-based hyperspectral images and chlorophyll measurements. MODIS chlorophyll estimates from the inverse model showed strong seasonal variations across two flux-tower sites in central and eastern Amazon. Marked increases in chlorophyll concentrations were observed during the early dry season. Remotely sensed chlorophyll concentrations were correlated to field measurements (r2 = 0.73 and r2 = 0.98) but the data deviated from the 1:1 line with root mean square errors (RMSE) ranging from 0.355 μg cm-2 (Tapajós tower) to 0.470 μg cm-2 (Manaus tower). The chlorophyll estimates were consistent with flux tower measurements of photosynthetically active radiation (PAR) and net ecosystem productivity (NEP). We also applied ProSAIL to mono-angle hyperspectral observations from a camera installed on a tower to scale modeled chlorophyll pigments to MODIS observations (r2 = 0.73). Chlorophyll pigment concentrations (ChlA+B) were correlated to changes in the amount of young and mature leaf area per month (0.59 ≤ r2 ≤ 0.64). Increases in MODIS observed ChlA+B were preceded by increased PAR during the dry season (0.61 ≤ r2 ≤ 0.62) and followed by changes in net carbon uptake. We conclude that, at these two sites, changes in LAI, coupled with changes in leaf chlorophyll, are comparable with seasonality of plant productivity. Our results allowed the preliminary development of a 15-year time series of chlorophyll estimates over the Amazon to support canopy chemistry studies using future hyperspectral sensors.

Next Generation of Air Quality Measurements from Geo Orbits: Breaking The Temporal Barrier

NASA Astrophysics Data System (ADS)

Gupta, P.; Levy, R. C.; Mattoo, S.; Remer, L.; Heidinger, A.

2017-12-01

NASA's dark target (DT) aerosol algorithm provides operational retrieval of atmospheric aerosols from multiple polar orbiting satellites. The DT algorithm, initially developed for MODIS observations, has been continuously improved since the first MODIS launch in early 2000. Now, we are adapting the DT algorithm to retrieve on new-generation geostationary (GEO) sensors, including the Advanced Himawari Imager (AHI) on Japan's Himawari-8 (H8) satellite and Advanced Baseline Imager (ABI) on NOAA's GOES-16 (or GOES-R). H8 is a weather geostationary satellite operating since July 2015, and AHI observes earth-atmosphere system over the Asia-Pacific region at spatial resolutions of 1km or less. GOES-R is launched in Nov 2016 and provides high temporal resolution observations over Americas. With 16 spectral channels, including 7 bands that observe similar wavelengths as the MODIS bands used for DT aerosol retrieval. Most exciting, however, is that both ABI and AHI provides full disk observations every 10-15 minutes and zoom mode observations every 30 second to 2.5 minutes. Therefore, spectral, spatial and temporal resolution observations from these GEO satellites provide opportunity to monitor atmospheric aerosols in the region, plus a new capability to monitor aerosol transport and aerosol/cloud diurnal cycles. In this paper, we will introduce retrieval results from AHI using the DT algorithm during the KORUS-AQ field campaign during summer 2016. These results are evaluated against surface measurements (e.g. AERONET). . We will also discuss, its potential applications in monitoring diurnal cycles of urban pollution, smoke and dust in the region. The same DT algorithm will also be adapted to retrieve aerosol properties using GOES-16 over Americas.

Monitoring the On-Orbit Calibration of Terra MODIS Reflective Solar Bands Using Simultaneous Terra MISR Observations

NASA Technical Reports Server (NTRS)

Angal, Amit; Xiong, Xiaoxiong; Wu, Aisheng

2016-01-01

On December 18, 2015, the Terra spacecraft completed 16 years of successful operation in space. Terra has five instruments designed to facilitate scientific measurements of the earths land, ocean, and atmosphere. The Moderate Resolution Imaging Spectroradiometer (MODIS) and the Multiangle Imaging Spectroradiometer (MISR) instruments provide information for the temporal studies of the globe. After providing over 16 years of complementary measurements, a synergistic use of the measurements obtained from these sensors is beneficial for various science products. The 20 reflective solar bands (RSBs) of MODIS are calibrated using a combination of solar diffuser and lunar measurements, supplemented by measurements from pseudoinvariant desert sites. MODIS views the on-board calibrators and the earth via a two-sided scan mirror at three spatial resolutions: 250 m using 40 detectors in bands 1 and 2, 500 m using 20 detectors in bands 3 and 4, and 1000 m using 10 detectors in bands 819 and 26. Simultaneous measurements of the earths surface are acquired in a push-broom fashion by MISR at nine view angles spreading out in the forward and backward directions along the flight path. While the swath width for MISR acquisitions is 360 km, MODIS scans a wider swath of 2330 km via its two-sided scan mirror. The reflectance of the MODIS scan mirror has an angle dependence characterized by the response versus scan angle (RVS). Its on-orbit change is derived using the gain from a combination of on-board and earth-view measurements. The on-orbit RVS for MODIS has experienced a significant change, especially for the short-wavelength bands. The on-orbit RVS change for the short-wavelength bands (bands 3, 8, and 9) at nadir is observed to be greater than 10 over the mission lifetime. Due to absence of a scanning mechanism, MISR can serve as an effective tool to evaluate and monitor the on-orbit performance of the MODIS RVS. Furthermore, it can also monitor the detector and scan-mirror differences for the MODIS bands using simultaneous measurements from earth-scene targets, e.g., North Atlantic Ocean and North African desert. Simultaneous measurements provide the benefit of minimizing the impact of earth-scene features while comparing the radiometric performance using vicarious techniques. Long-term observations of both instruments using select ground targets also provide an evaluation of the long-term calibration stability. The goal of this paper is to demonstrate the use of MISR to monitor and enhance the on-orbit calibration of the MODIS RSB. The radiometric calibration requirements for the MODIS RSB are +/- 2% in reflectance and +/- 5% in radiance at typical radiance levels within +/- 45 deg. of nadir. The results show that the long-term changes in the MODIS reflectance at nadir frames are generally within 1. The MODIS level 1B calibrated products, generated after correcting for the on-orbit changes in the gain and RVS, do not have any correction for changes in the instruments polarization sensitivity. The mirror-side-dependent polarization sensitivity exhibits an on-orbit change, primarily in the blue bands, that manifests in noticeable mirror side differences in the MODIS calibrated products. The mirror side differences for other RSB are observed to be less than 1%, therefore demonstrating an excellent on-orbit performance. The detector differences in the blue bands of MODIS exhibit divergence in recent years beyond 1%, and a calibration algorithm improvement has been identified to mitigate this effect. Short-term variations in the recent year caused by the forward updates were identified in bands 1 and 2 and are planned to be corrected in the next reprocess.

Development of a MODIS-Derived Surface Albedo Data Set: An Improved Model Input for Processing the NSRDB

DOE Office of Scientific and Technical Information (OSTI.GOV)

Maclaurin, Galen; Sengupta, Manajit; Xie, Yu

A significant source of bias in the transposition of global horizontal irradiance to plane-of-array (POA) irradiance arises from inaccurate estimations of surface albedo. The current physics-based model used to produce the National Solar Radiation Database (NSRDB) relies on model estimations of surface albedo from a reanalysis climatalogy produced at relatively coarse spatial resolution compared to that of the NSRDB. As an input to spectral decomposition and transposition models, more accurate surface albedo data from remotely sensed imagery at finer spatial resolutions would improve accuracy in the final product. The National Renewable Energy Laboratory (NREL) developed an improved white-sky (bi-hemispherical reflectance)more » broadband (0.3-5.0 ..mu..m) surface albedo data set for processing the NSRDB from two existing data sets: a gap-filled albedo product and a daily snow cover product. The Moderate Resolution Imaging Spectroradiometer (MODIS) sensors onboard the Terra and Aqua satellites have provided high-quality measurements of surface albedo at 30 arc-second spatial resolution and 8-day temporal resolution since 2001. The high spatial and temporal resolutions and the temporal coverage of the MODIS sensor will allow for improved modeling of POA irradiance in the NSRDB. However, cloud and snow cover interfere with MODIS observations of ground surface albedo, and thus they require post-processing. The MODIS production team applied a gap-filling methodology to interpolate observations obscured by clouds or ephemeral snow. This approach filled pixels with ephemeral snow cover because the 8-day temporal resolution is too coarse to accurately capture the variability of snow cover and its impact on albedo estimates. However, for this project, accurate representation of daily snow cover change is important in producing the NSRDB. Therefore, NREL also used the Integrated Multisensor Snow and Ice Mapping System data set, which provides daily snow cover observations of the Northern Hemisphere for the temporal extent of the NSRDB (1998-2015). We provide a review of validation studies conducted on these two products and describe the methodology developed by NREL to remap the data products to the NSRDB grid and integrate them into a seamless daily data set.« less

Internally Consistent MODIS Estimate of Aerosol Clear-Sky Radiative Effect Over the Global Oceans

NASA Technical Reports Server (NTRS)

Remer, Lorraine A.; Kaufman, Yoram J.

2004-01-01

Modern satellite remote sensing, and in particular the MODerate resolution Imaging Spectroradiometer (MODIS), offers a measurement-based pathway to estimate global aerosol radiative effects and aerosol radiative forcing. Over the Oceans, MODIS retrieves the total aerosol optical thickness, but also reports which combination of the 9 different aerosol models was used to obtain the retrieval. Each of the 9 models is characterized by a size distribution and complex refractive index, which through Mie calculations correspond to a unique set of single scattering albedo, assymetry parameter and spectral extinction for each model. The combination of these sets of optical parameters weighted by the optical thickness attributed to each model in the retrieval produces the best fit to the observed radiances at the top of the atmosphere. Thus the MODIS Ocean aerosol retrieval provides us with (1) An observed distribution of global aerosol loading, and (2) An internally-consistent, observed, distribution of aerosol optical models that when used in combination will best represent the radiances at the top of the atmosphere. We use these two observed global distributions to initialize the column climate model by Chou and Suarez to calculate the aerosol radiative effect at top of the atmosphere and the radiative efficiency of the aerosols over the global oceans. We apply the analysis to 3 years of MODIS retrievals from the Terra satellite and produce global and regional, seasonally varying, estimates of aerosol radiative effect over the clear-sky oceans.

Synergetic use of Aerosol Robotic Network (AERONET) and Moderate Image Spectrometer (MODIS)

NASA Technical Reports Server (NTRS)

Kaufman, Y.

2004-01-01

I shall describe several distinct modes in which AERONET data are used in conjunction with MODIS data to evaluate the global aerosol system and its impact on climate. These includes: 1) Evaluation of the aerosol diurnal cycle not available from MODIS, and the relationship between the aerosol properties derived from MODIS and the daily average of these properties; 2) Climatology of the aerosol size distribution and single scattering albedo. The climatology is used to formulate the assumptions used in the MODIS look up tables used in the inversion of MODIS data; 3) Measurement of the aerosol effect on irradiation of the surface, this is used in conjunction with the MODIS evaluation of the aerosol effect at the TOA; and 4) Assessment of the aerosol baseline on top off which the satellite data are used to find the amount of dust or anthropogenic aerosol.

Using multi-source satellite data to assess snow-cover change in Qinghai-Tibetan Plateau in last decade

NASA Astrophysics Data System (ADS)

Jiang, Y.; Chen, F.; Gao, Y.; Barlage, M. J.

2017-12-01

Snow cover in Qinghai-Tibetan Plateau (QTP) is a critical component of water cycle and affects regional climate of East Asia. Satellite data from three different sources (i.e., FY3A/B/C, MODIS and IMS) were used to analyze the QTP fractional-snow-cover (FSC) change and associated uncertainties in the last decade. To reduce the high percentage of cloud in FY3A/B/C and MODIS, a four-step cloud removal procedure was applied and effectively reduced the cloud percentage from 40.8-56.1% to 2.2­-­3.3%. The averaged error introduced by the cloud removal procedure was about 2% estimated by a random sampling method. Results show that the snow cover in QTP significantly decreased in recent 5 years. Three data sets (FY3B, MODIS and IMS) showed significant decreased annual FSC at all elevation bands from 2012-2016, and a significant shorter snow season with delayed snow onset and earlier melting. Both IMS and MODIS had a slightly decline annual FSC from 2000 to 3000 m, while MODIS FSC slightly decreased in 2002-2016 and IMS FSC slightly increased from 2006-2016 in the region with elevation higher than 3000 m. Results also show significant uncertainties among the five data sets (FY3A/B/C, MODIS, IMS), although they showed similar fluctuations of daily FSC. IMS had largest snow-cover extent and highest daily FSC due to its multi data sources. FY3A/C and MODIS (observed in the morning) had around 5% higher mean FSC than FY3B (observed in the afternoon) due to the 3 hours detection time gap. The relative error of daily FSC (taking MODIS as `truth') between FY3A/B/C, IMS and MODIS is 23%, -35%, 8% and 63%, respectively, averaged in five elevation bands in 2015-2017.

Applications of MODIS Fluorescence Line Height Measurements to Monitor Water Quality Trends and Algal Bloom Activity in Coastal and Estuarine Waters

NASA Astrophysics Data System (ADS)

Fischer, A.; Ryan, J. P.; Moreno-Madriñán, M. J.

2012-12-01

Recent advances in satellite and airborne remote sensing, such as improvements in sensor and algorithm calibrations and atmospheric correction procedures have provided for increased coverage of remote-sensing, ocean color products for coastal regions. In particular, for the Moderate Resolution Imaging Spectrometer (MODIS), calibration updates, improved aerosol retrievals, and new aerosol models have led to improved atmospheric correction algorithms for turbid waters and have improved the retrieval of ocean-color. This has opened the way for studying coastal ocean phenomena and processes at finer spatial scales. Human population growth and changes in coastal management practices have brought about significant changes in the concentrations of organic and inorganic, particulate and dissolved substances entering the coastal ocean. There is increasing concern that these inputs have led to declines in water quality and increases in local concentrations of phytoplankton, which could result in harmful algal blooms. In two case studies we present improved and validated MODIS coastal observations of fluorescence line height (FLH) to: (1) assess trends in water quality for Tampa Bay, Florida; and (2) illustrate seasonal and annual variability of algal bloom activity in Monterey Bay, California, as well as document estuarine/riverine plume induced red tide events. In a comprehensive analysis of long term (2003-2011) in situ monitoring data and imagery from Tampa Bay, we assess the validity of the MODIS FLH product against chlorophyll-a and a suite of water quality parameters taken in a variety of conditions throughout this large, optically complex estuarine system. A systematic analysis of sampling sites throughout the bay illustrates that the correlations between FLH and in situ chlorophyll-a are influenced by water quality parameters of total nitrogen, total phosphorous, turbidity and biological oxygen demand. Sites that correlated well with satellite imagery were in depths greater than seven meters and were located over five kilometers from shore. Satellite FLH estimates show improving water quality from 2003-2007 with a slight decline up through 2011. Dinoflagellate blooms in Monterey Bay, California have recently increased in frequency and intensity. Nine years of MODIS FLH observations are used to describe the annual and seasonal variability of bloom activity within the Bay. Three classes of MODIS algorithms were correlated against in situ chlorophyll measurements. The FLH algorithm provided the most robust estimate of bloom activity. Elevated concentrations of phytoplankton were evident during the months of August-November, a period during which increased occurrences of dinoflagellate blooms have been observed in situ. Seasonal patterns of FLH show the on- and offshore movement of areas of high phytoplankton biomass between oceanographic seasons. Higher concentrations of phytoplankton are also evident in the vicinity of the land-based nutrient sources and outflows, and cyclonic bay-wide circulation transports these nutrients to a northern Bay bloom incubation region. Both of these case studies illustrate the utility of improved MODIS FLH observations in supporting management decisions in coastal and estuarine waters.

Data sets for snow cover monitoring and modelling from the National Snow and Ice Data Center

NASA Astrophysics Data System (ADS)

Holm, M.; Daniels, K.; Scott, D.; McLean, B.; Weaver, R.

2003-04-01

A wide range of snow cover monitoring and modelling data sets are pending or are currently available from the National Snow and Ice Data Center (NSIDC). In-situ observations support validation experiments that enhance the accuracy of remote sensing data. In addition, remote sensing data are available in near-real time, providing coarse-resolution snow monitoring capability. Time series data beginning in 1966 are valuable for modelling efforts. NSIDC holdings include SMMR and SSM/I snow cover data, MODIS snow cover extent products, in-situ and satellite data collected for NASA's recent Cold Land Processes Experiment, and soon-to-be-released ASMR-E passive microwave products. The AMSR-E and MODIS sensors are part of NASA's Earth Observing System flying on the Terra and Aqua satellites Characteristics of these NSIDC-held data sets, appropriateness of products for specific applications, and data set access and availability will be presented.

Development of an Operational Land Water Mask for MODIS Collection 6, and Influence on Downstream Data Products

NASA Technical Reports Server (NTRS)

Carroll, M. L.; DiMiceli, C. M.; Townshend, J. R. G.; Sohlberg, R. A.; Elders, A. I.; Devadiga, S.; Sayer, A. M.; Levy, R. C.

2016-01-01

Data from the Moderate Resolution Imaging Spectro-radiometer (MODIS)on-board the Earth Observing System Terra and Aqua satellites are processed using a land water mask to determine when an algorithm no longer needs to be run or when an algorithm needs to follow a different pathway. Entering the fourth reprocessing (Collection 6 (C6)) the MODIS team replaced the 1 km water mask with a 500 m water mask for improved representation of the continental surfaces. The new water mask represents more small water bodies for an overall increase in water surface from 1 to 2 of the continental surface. While this is still a small fraction of the overall global surface area the increase is more dramatic in certain areas such as the Arctic and Boreal regions where there are dramatic increases in water surface area in the new mask. MODIS products generated by the on-going C6 reprocessing using the new land water mask show significant impact in areas with high concentrations of change in the land water mask. Here differences between the Collection 5 (C5) and C6 water masks and the impact of these differences on the MOD04 aerosol product and the MOD11 land surface temperature product are shown.

Example MODIS Global Cloud Optical and Microphysical Properties: Comparisons between Terra and Aqua

NASA Technical Reports Server (NTRS)

Hubanks, P. A.; Platnick, S.; King, M. D.; Ackerman, S. A.; Frey, R. A.

2003-01-01

MODIS observations from the NASA EOS Terra spacecraft (launched in December 1999, 1030 local time equatorial crossing) have provided a unique data set of Earth observations. With the launch of the NASA Aqua spacecraft in May 2002 (1330 local time), two MODIS daytime (sunlit) and nighttime observations are now available in a 24 hour period, allowing for some measure of diurnal variability. We report on an initial analysis of several operational global (Level-3) cloud products from the two platforms. The MODIS atmosphere Level-3 products, which include clear-sky and aerosol products in addition to cloud products, are available as three separate files providing daily, eight-day, and monthly aggregations; each temporal aggregation is spatially aggregated to a 1 degree grid. The files contain approximately 600 statisitical datasets (from simple means and standard deviations to 1 - and 2-dimensional histograms). Operational cloud products include detection (cloud fraction), cloud-top properties, and daytimeonly cloud optical thickness and particle effective radius for both water and ice clouds. We will compare example global Terra and Aqua cloud fraction, optical thickness, and effective radius aggregations.

Applications of Near Real-Time Image and Fire Products from MODIS

NASA Astrophysics Data System (ADS)

Schmaltz, J. E.; Ilavajhala, S.; Teague, M.; Ye, G.; Masuoka, E.; Davies, D.; Murphy, K. J.; Michael, K.

2010-12-01

NASA’s MODIS Rapid Response Project (http://rapidfire.sci.gsfc.nasa.gov/) has been providing MODIS fire detections and imagery in near real-time since 2001. The Rapid Response system is part of the Land and Atmospheres Near-real time Capability for EOS (LANCE-MODIS) system. Current capabilities include providing MODIS imagery in true color and false color band combinations, a vegetation index, and temperature - in both uncorrected swath format and geographically corrected subset regions. The geographically-corrected subsets images cover the world's land areas and adjoining waters, as well as the entire Arctic and Antarctic. These data are available within a few hours of data acquisition. The images are accessed by large number of user communities to obtain a rapid, 250 meter-resolution overview of ground conditions for fire management, crop and famine monitoring and forecasting, disaster response (fires, oil spills, floods, storms), dust and aerosol monitoring, aviation (tracking volcanic ash), monitoring sea ice conditions, environmental monitoring, and more. In addition, the scientific community uses imagery to locate phenomena of interest prior to ordering and processing data and to support the day-to-day planning of field campaigns. The MODIS Rapid Response project has also been providing a near real-time data feed on fire locations and MODIS imagery subsets to the Fire Information for Resource Management System (FIRMS) project (http://maps.geog.umd.edu/firms). FIRMS provides timely availability of fire location information, which is essential in preventing and fighting large forest/wild fires. Products are available through a WebGIS for visualizing MODIS hotspots and MCD45 Burned Area images, an email alerting tool to deliver fire data on daily/weekly/near real-time basis, active data downloads in formats such as shape, KML, CSV, WMS, etc., along with MODIS imagery subsets. FIRMS’ user base covers more than 100 countries and territories. A recent user survey showed that a majority of people use FIRMS for the purposes of conservation, fire-fighting, natural hazard monitoring, land cover change monitoring, and climate change. FIRMS has also developed a cellphone-based text (SMS) alerting of MODIS and MSG-detected fires in near real-time in South Africa, in partnership with the South African power company ESKOM and Council of Scientific and Industrial Research, South Africa. FIRMS was transitioned to the United Nations Food and Agricultural Organization (UN-FAO) in Rome, Italy in Spring 2010 and is scheduled to become a part of the LANCE-MODIS data system (http://lance.nasa.gov/) in Spring 2011.

A Comparison of MODIS and DOAS Sulfur Dioxide Measurements of the April 24, 2004 Eruption of Anatahan Volcano, Mariana Islands

NASA Astrophysics Data System (ADS)

Meier, V. L.; Scuderi, L.; Fischer, T.; Realmuto, V.; Hilton, D.

2006-12-01

Measurements of volcanic SO2 emissions provide insight into the processes working below a volcano, which can presage volcanic events. Being able to measure SO2 in near real-time is invaluable for the planning and response of hazard mitigation teams. Currently, there are several methods used to quantify the SO2 output of degassing volcanoes. Ground and aerial-based measurements using the differential optical absorption spectrometer (mini-DOAS) provide real-time estimates of SO2 output. Satellite-based measurements, which can provide similar estimates in near real-time, have increasingly been used as a tool for volcanic monitoring. Direct Broadcast (DB) real-time processing of remotely sensed data from NASA's Earth Observing System (EOS) satellites (MODIS Terra and Aqua) presents volcanologists with a range of spectral bands and processing options for the study of volcanic emissions. While the spatial resolution of MODIS is 1 km in the Very Near Infrared (VNIR) and Thermal Infrared (TIR), a high temporal resolution and a wide range of radiance measurements in 32 channels between VNIR and TIR combine to provide a versatile space borne platform to monitor SO2 emissions from volcanoes. An important question remaining to be answered is how well do MODIS SO2 estimates compare with DOAS estimates? In 2004 ground-based plume measurements were collected on April 24th and 25th at Anatahan volcano in the Mariana Islands using a mini-DOAS (Fischer and Hilton). SO2 measurements for these same dates have also been calculated using MODIS images and SO2 mapping software (Realmuto). A comparison of these different approaches to the measurement of SO2 for the same plume is presented. Differences in these observations are used to better quantify SO2 emissions, to assess the current mismatch between ground based and remotely sensed retrievals, and to develop an approach to continuously and accurately monitor volcanic activity from space in near real-time.

Applications of MODIS satellite data and products for monitoring air quality in the state of Texas

NASA Astrophysics Data System (ADS)

Hutchison, Keith D.

The Center for Space Research (CSR), in conjunction with the Monitoring Operations Division (MOD) of the Texas Commission on Environmental Quality (TCEQ), is evaluating the use of remotely sensed satellite data to assist in monitoring and predicting air quality in Texas. The challenges of meeting air quality standards established by the US Environmental Protection Agency (US EPA) are impacted by the transport of pollution into Texas that originates from outside our borders and are cumulative with those generated by local sources. In an attempt to quantify the concentrations of all pollution sources, MOD has installed ground-based monitoring stations in rural regions along the Texas geographic boundaries including the Gulf coast, as well as urban regions that are the predominant sources of domestic pollution. However, analysis of time-lapse GOES satellite imagery at MOD, clearly demonstrates the shortcomings of using only ground-based observations for monitoring air quality across Texas. These shortcomings include the vastness of State borders, that can only be monitored with a large number of ground-based sensors, and gradients in pollution concentration that depend upon the location of the point source, the meteorology governing its transport to Texas, and its diffusion across the region. With the launch of NASA's MODerate resolution Imaging Spectroradiometer (MODIS), the transport of aerosol-borne pollutants can now be monitored over land and ocean surfaces. Thus, CSR and MOD personnel have applied MODIS data to several classes of pollution that routinely impact Texas air quality. Results demonstrate MODIS data and products can detect and track the migration of pollutants. This paper presents one case study in which continental haze from the northeast moved into the region and subsequently required health advisories to be issued for 150 counties in Texas. It is concluded that MODIS provides the basis for developing advanced data products that will, when used in conjunction with ground-based observations, create a cost-effective and accurate pollution monitoring system for the entire state of Texas.

Suomi NPP VIIRS active fire product status

NASA Astrophysics Data System (ADS)

Ellicott, E. A.; Csiszar, I. A.; Schroeder, W.; Giglio, L.; Wind, B.; Justice, C. O.

2012-12-01

We provide an overview of the evaluation and development of the Active Fires product derived from the Visible Infrared Imager Radiometer Suite (VIIRS) sensor on the Suomi National Polar-orbiting Partnership (SNPP) satellite during the first year of on-orbit data. Results from the initial evaluation of the standard SNPP Active Fires product, generated by the SNPP Interface Data Processing System (IDPS), supported the stabilization of the VIIRS Sensor Data Record (SDR) product. This activity focused in particular on the processing of the dual-gain 4 micron VIIRS M13 radiometric measurements into 750m aggregated data, which are fundamental for active fire detection. Following the VIIRS SDR product's Beta maturity status in April 2012, correlative analysis between VIIRS and near-simultaneous fire detections from the Moderate Resolution Imaging Spectroradiometer (MODIS) on the NASA Earth Observing System Aqua satellite confirmed the expected relative detection rates driven primarily by sensor differences. The VIIRS Active Fires Product Development and Validation Team also developed a science code that is based on the latest MODIS Collection 6 algorithm and provides a full spatially explicit fire mask to replace the sparse array output of fire locations from a MODIS Collection 4 equivalent algorithm in the current IDPS product. The Algorithm Development Library (ADL) was used to support the planning for the transition of the science code into IDPS operations in the future. Product evaluation and user outreach was facilitated by a product website that provided end user access to fire data in user-friendly format over North America as well as examples of VIIRS-MODIS comparisons. The VIIRS fire team also developed an experimental product based on 375m VIIRS Imagery band measurements and provided high quality imagery of major fire events in US. By August 2012 the IDPS product achieved Beta maturity, with some known and documented shortfalls related to the processing of incorrect SDR input data and to apparent algorithm deficiencies in select observing and environmental conditions.

CALIPSO IIR Version 2 Level 1b calibrated radiances: analysis and reduction of residual biases in the Northern Hemisphere

NASA Astrophysics Data System (ADS)

Garnier, Anne; Trémas, Thierry; Pelon, Jacques; Lee, Kam-Pui; Nobileau, Delphine; Gross-Colzy, Lydwine; Pascal, Nicolas; Ferrage, Pascale; Scott, Noëlle A.

2018-04-01

Version 2 of the Level 1b calibrated radiances of the Imaging Infrared Radiometer (IIR) on board the Cloud-Aerosol Lidar and Infrared Satellite Observation (CALIPSO) satellite has been released recently. This new version incorporates corrections of small but systematic seasonal calibration biases previously revealed in Version 1 data products mostly north of 30° N. These biases - of different amplitudes in the three IIR channels 8.65 µm (IIR1), 10.6 µm (IIR2), and 12.05 µm (IIR3) - were made apparent by a striping effect in images of IIR inter-channel brightness temperature differences (BTDs) and through seasonal warm biases of nighttime IIR brightness temperatures in the 30-60° N latitude range. The latter were highlighted through observed and simulated comparisons with similar channels of the Moderate Resolution Imaging Spectroradiometer (MODIS) on board the Aqua spacecraft. To characterize the calibration biases affecting Version 1 data, a semi-empirical approach is developed, which is based on the in-depth analysis of the IIR internal calibration procedure in conjunction with observations such as statistical comparisons with similar MODIS/Aqua channels. Two types of calibration biases are revealed: an equalization bias affecting part of the individual IIR images and a global bias affecting the radiometric level of each image. These biases are observed only when the temperature of the instrument increases, and they are found to be functions of elapsed time since night-to-day transition, regardless of the season. Correction coefficients of Version 1 radiances could thus be defined and implemented in the Version 2 code. As a result, the striping effect seen in Version 1 is significantly attenuated in Version 2. Systematic discrepancies between nighttime and daytime IIR-MODIS BTDs in the 30-60° N latitude range in summer are reduced from 0.2 K in Version 1 to 0.1 K in Version 2 for IIR1-MODIS29. For IIR2-MODIS31 and IIR3-MODIS32, they are reduced from 0.4 K to close to zero, except for IIR3-MODIS32 in June, where the night-minus-day difference is around -0.1 K.

Analysis of Co-Located MODIS and CALIPSO Observations Near Clouds

NASA Technical Reports Server (NTRS)

Varnai, Tamas; Marshak, Alexander

2011-01-01

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 Aqua satellite's MODIS 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 reflection of its pulses. In contrast, MODIS takes images of reflected 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 MODIS 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 MODIS and CALIOP observations have only a minor impact. The study also finds that MODIS 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 MODIS 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 closer than 5 km to clouds implies that pronounced near-cloud changes in aerosol properties have significant implications for overall clear-sky characteristics, including the radiative impact of aerosols.

JPSS application in a near real time regional numerical forecast system at CIMSS

NASA Astrophysics Data System (ADS)

Li, J.; Wang, P.; Han, H.; Zhu, F.; Schmit, T. J.; Goldberg, M.

2015-12-01

Observations from next generation of environmental sensors onboard the Suomi National Polar-Orbiting Parnership (S-NPP) and its successor, the Joint Polar Satellite System (JPSS), provide us the critical information for numerical weather forecast (NWP). How to better represent these satellite observations and how to get value added information into NWP system still need more studies. Recently scientists from Cooperative Institute of Meteorological Satellite Studies (CIMSS) at University of Wisconsin-Madison have developed a near realtime regional Satellite Data Assimilation system for Tropical storm forecasts (SDAT) (http://cimss.ssec.wisc.edu/sdat). The system is built with the community Gridpoint Statistical Interpolation (GSI) assimilation and advanced Weather Research Forecast (WRF) model. With GSI, SDAT can assimilate all operational available satellite data including GOES, AMSUA/AMSUB, HIRS, MHS, ATMS, AIRS and IASI radiances and some satellite derived products. In addition, some research products, such as hyperspectral IR retrieved temperature and moisture profiles, GOES imager atmospheric motion vector (AMV) and GOES sounder layer precipitable water (LPW), are also added into the system. Using SDAT as a research testbed, studies have been conducted to show how to improve high impact weather forecast by better handling cloud information in satellite data. Previously by collocating high spatial resolution MODIS data with hyperspectral resolution AIRS data, precise clear pixels of AIRS can be identified and some partially or thin cloud contamination from pixels can be removed by taking advantage of high spatial resolution and high accurate MODIS cloud information. The results have demonstrated that both of these strategies have greatly improved the hurricane track and intensity forecast. We recently have extended these methodologies into processing CrIS/VIIRS data. We also tested similar ideas in microwave sounders by the collocation of AMSU/MODIS and ATMS/VIIRS data. The experiments along with other SDAT progresses will be presented in the meeting.

Improving Aerosol and Visibility Forecasting Capabilities Using Current and Future Generations of Satellite Observations

DTIC Science & Technology

2015-08-27

Shi et al. (2011) suggested that large spatial discrepancies exist in operational satellite aerosol products such as MODIS and MISR. Thus, before...to be fully evaluated. In the past few years of the project period, MODIS Deep Blue (DB) and MISR aerosol products have been studied, and schemes for...constructing DA-grade MODIS DB and MISR aerosol products have been developed and transitioned to the Naval Research Laboratory (NRL). Continuing

Improvements of VIIRS and MODIS Solar Diffuser and Lunar Calibration

NASA Technical Reports Server (NTRS)

Xiong, Xiaoxiong; Butler, James J.; Lei, Ning; Sun, Junqiang; Fulbright, Jon; Wang, Zhipeng; McIntire, Jeff; Angal, Amit Avinash

2013-01-01

Both VIIRS and MODIS instruments use solar diffuser (SD) and lunar observations to calibrate their reflective 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 MODIS instruments. In general, the MODIS 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 MODIS 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 MODIS SD and lunar calibrations and efforts that could be made for future improvements.

Correcting for trace gas absorption when retrieving aerosol optical depth from satellite observations of reflected shortwave radiation

NASA Astrophysics Data System (ADS)

Patadia, Falguni; Levy, Robert C.; Mattoo, Shana

2018-06-01

Retrieving aerosol optical depth (AOD) from top-of-atmosphere (TOA) satellite-measured radiance requires separating the aerosol signal from the total observed signal. Total TOA radiance includes signal from the underlying surface and from atmospheric constituents such as aerosols, clouds and gases. Multispectral retrieval algorithms, such as the dark-target (DT) algorithm that operates upon the Moderate Resolution Imaging Spectroradiometer (MODIS, on board Terra and Aqua satellites) and Visible Infrared Imaging Radiometer Suite (VIIRS, on board Suomi-NPP) sensors, use wavelength bands in window regions. However, while small, the gas absorptions in these bands are non-negligible and require correction. In this paper, we use the High-resolution TRANsmission (HITRAN) database and Line-By-Line Radiative Transfer Model (LBLRTM) to derive consistent gas corrections for both MODIS and VIIRS wavelength bands. Absorptions from H2O, CO2 and O3 are considered, as well as other trace gases. Even though MODIS and VIIRS bands are similar, they are different enough that applying MODIS-specific gas corrections to VIIRS observations results in an underestimate of global mean AOD (by 0.01), but with much larger regional AOD biases of up to 0.07. As recent studies have been attempting to create a long-term data record by joining multiple satellite data sets, including MODIS and VIIRS, the consistency of gas correction has become even more crucial.

Validation of CERES-MODIS Arctic cloud properties using CloudSat/CALIPSO and ARM NSA observations

NASA Astrophysics Data System (ADS)

Giannecchini, K.; Dong, X.; Xi, B.; Minnis, P.; Kato, S.

2011-12-01

The traditional passive satellite studies of cloud properties in the Arctic are often affected by the complex surface features present across the region. Nominal visual and thermal contrast exists between Arctic clouds and the snow- and ice-covered surfaces beneath them, which can lead to difficulties in satellite retrievals of cloud properties. However, the addition of active sensors to the A-Train constellation of satellites has increased the availability of validation sources for cloud properties derived from passive sensors in the data-sparse high-latitude regions. In this study, Arctic cloud fraction and cloud heights derived from the NASA CERES team (CERES-MODIS) have been compared with CloudSat/CALIPSO and DOE ARM NSA radar-lidar observations over Barrow, AK, for the two-year period from 2007 to 2008. An Arctic-wide comparison of cloud fraction and height between CERES-MODIS and CloudSat/CALIPSO was then conducted for the same time period. The CERES-MODIS cloud properties, which include cloud fraction and cloud effective heights, were retrieved using the 4-channel VISST (Visible Infrared Solar-Infrared Split-window Technique) [Minnis et al.,1995]. CloudSat/CALIPSO cloud fraction and cloud-base and -top heights were from version RelB1 data products determined by both the 94 GHz radar onboard CloudSat and the lidar on CALIPSO with a vertical resolution of 30 m below 8.2 km and 60 m above. To match the surface and satellite observations/retrievals, the ARM surface observations were averaged into 3-hour intervals centered at the time of the satellite overpass, while satellite observations were averaged within a 3°x3° grid box centered on the Barrow site. The preliminary results have shown that all observed CFs have peaks during April-May and September-October, and dips during winter months (January-February) and summer months (June-July) during the study period of 2007-2008. ARM radar-lidar and CloudSat/CALIPSO show generally good agreement in CF (0.79 vs. 0.74), while CERES-MODIS derived values are much lower (0.60). CERES-MODIS derived cloud effective height (2.7 km) falls between the CloudSat/CALIPSO derived cloud base (0.6 km) and top (6.4 km) and the ARM ceilometers and MMCR derived cloud base (0.9 km) and radar derived cloud top (5.8 km). When extended to the entire Arctic, although the CERES-MODIS and Cloudsat/CALIPSO derived annual mean CFs agree within a few percents, there are significant differences over several regions, and the maximum cloud heights derived from CloudSat/CALIPSO (13.4 km) and CERES-MODIS (10.7 km) show the largest disagreement during early spring.

Impact of Sensor Degradation on the MODIS NDVI Time Series

NASA Technical Reports Server (NTRS)

Wang, Dongdong; Morton, Douglas Christopher; Masek, Jeffrey; Wu, Aisheng; Nagol, Jyoteshwar; Xiong, Xiaoxiong; Levy, Robert; Vermote, Eric; Wolfe, Robert

2012-01-01

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 (MODIS) sensors on the Terra and Aqua platforms. For Terra MODIS, the impact of blue band (Band 3, 470 nm) degradation on simulated surface reflectance 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 MODIS NDVI over North America were consistentwith simulated results,with nearly a threefold difference in negative NDVI trends derived from Terra (17.4%) and Aqua (6.7%) MODIS sensors during 2002-2010. Planned adjustments to Terra MODIS calibration for Collection 6 data reprocessing will largely eliminate this negative bias in detection of NDVI trends.

Impact of Sensor Degradation on the MODIS NDVI Time Series

NASA Technical Reports Server (NTRS)

Wang, Dongdong; Morton, Douglas; Masek, Jeffrey; Wu, Aisheng; Nagol, Jyoteshwar; Xiong, Xiaoxiong; Levy, Robert; Vermote, Eric; Wolfe, Robert

2011-01-01

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 (MODIS) sensors on the Terra and Aqua platforms. For Terra MODIS, the impact of blue band (Band 3, 470nm) degradation on simulated surface reflectance 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 MODIS NDVI over North America were consistent with simulated results, with nearly a threefold difference in negative NDVI trends derived from Terra (17.4%) and Aqua (6.7%) MODIS sensors during 2002-2010. Planned adjustments to Terra MODIS calibration for Collection 6 data reprocessing will largely eliminate this negative bias in NDVI trends over vegetation.

The Transition of High-Resolution NASA MODIS Sea Surface Temperatures into the WRF Environmental Modeling System

NASA Technical Reports Server (NTRS)

Case, Jonathan L.; Jedlove, Gary J.; Santos, Pablo; Medlin, Jeffrey M.; Rozumalski, Robert A.

2009-01-01

The NASA Short-term Prediction Research and Transition (SPoRT) Center has developed a Moderate Resolution Imaging Spectroradiometer (MODIS) sea surface temperature (SST) composite at 2-km resolution that has been implemented in version 3 of the National Weather Service (NWS) Weather Research and Forecasting (WRF) Environmental Modeling System (EMS). The WRF EMS is a complete, full physics numerical weather prediction package that incorporates dynamical cores from both the Advanced Research WRF (ARW) and the Non-hydrostatic Mesoscale Model (NMM). The installation, configuration, and execution of either the ARW or NMM models is greatly simplified by the WRF EMS to encourage its use by NWS Weather Forecast Offices (WFOs) and the university community. The WRF EMS is easy to run on most Linux workstations and clusters without the need for compilers. Version 3 of the WRF EMS contains the most recent public release of the WRF-NMM and ARW modeling system (version 3 of the ARW is described in Skamarock et al. 2008), the WRF Pre-processing System (WPS) utilities, and the WRF Post-Processing program. The system is developed and maintained by the NWS National Science Operations Officer Science and Training Resource Coordinator. To initialize the WRF EMS with high-resolution MODIS SSTs, SPoRT developed the composite product consisting of MODIS SSTs over oceans and large lakes with the NCEP Real-Time Global (RTG) filling data over land points. Filling the land points is required due to minor inconsistencies between the WRF land-sea mask and that used to generate the MODIS SST composites. This methodology ensures a continuous field that adequately initializes all appropriate arrays in WRF. MODIS composites covering the Gulf of Mexico, western Atlantic Ocean and the Caribbean are generated daily at 0400, 0700, 1600, and 1900 UTC corresponding to overpass times of the NASA Aqua and Terra polar orbiting satellites. The MODIS SST product is output in gridded binary-1 (GRIB-1) data format for a seamless incorporation into WRF via the WPS utilities. The full-resolution, 1-km MODIS product is sub-sampled to 2-km grid spacing due to limitations in handling very large dimensions in the GRIB-1 data format. The GRIB-1 files are posted online at ftp://ftp.nsstc.org/sstcomp/WRF/, which is directly accessed by the WRF EMS scripts. The MODIS SST composites are also downloaded to the EMS data server, which is accessible by the WRF EMS users and NWS WFOs. The SPoRT MODIS SST composite provides the model with superior detail of the ocean gradients around Florida and surrounding waters, whereas the operational RTG SST typically depicts a relatively smooth field and is not able to capture sharp horizontal gradients in SST. Differences of 2-3 C are common over small horizontal distances, leading to enhanced SST gradients on either side of the Gulf Stream and along the edges of the cooler shelf waters. These sharper gradients can in turn produce atmospheric responses in simulated temperature and wind fields as depicted in LaCasse et al. Differences in atmospheric verification statistics over a several month study were generally small in the vicinity of south Florida; however, the validation of SSTs at specific buoy locations revealed important improvements in the biases and RMS errors, especially in the vicinity of the cooler shelf waters off the east-central Florida coast. A current weakness in the MODIS SST product is the occurrence of occasional discontinuities caused by high latency in SST coverage due to persistent cloud cover. An enhanced method developed by Jedlovec et al. (2009, GHRSST User Symposium) reduces the occurrence of these problems by adding Advanced Microwave Scanning Radiometer -- EOS (AMSR-E) SST data to the compositing process. Enhanced SST composites are produced over the ocean regions surrounding the Continental U.S. at four times each day corresponding to Terra and Aqua equator crossing times. For a given day and overpass time, both MODInd AMSR-E data from the previous seven days form a collection used in the compositing. At each MODIS pixel, cloud-free SST values from the collection are used to form a weighted average based on their latency (number of days from the current day). In this way, recent SST data are given more weight than older data. One of the primary issues involved in incorporating the AMSR-E microwave data in the composites is the tradeoff between the decreased spatial resolution of the AMSR-E data (25 km) and the increased coverage due to its near all-weather capability. Currently, the AMSR-E is given a weight of 20% compared to MODIS data, thereby preserving the spatial structure observed in the MODIS data. Day-time (night-time) AMSR-E SST data from Aqua are used with both Terra and Aqua MODIS day-time (night-time) SST data sets.

Extending MODIS Deep Blue Aerosol Retrieval Coverage to Cases of Absorbing Aerosols Above Clouds: First Results

NASA Technical Reports Server (NTRS)

Sayer, A. M.; Hsu, N. C.; Bettenhausen, C.; Lee, J.; Redemann, J.; Shinozuka, Y.; Schmid, B.

2015-01-01

Absorbing smoke or mineral dust aerosols above clouds (AAC) are a frequent occurrence in certain regions and seasons. Operational aerosol retrievals from sensors like MODIS omit AAC because they are designed to work only over cloud-free scenes. However, AAC can in principle be quantified by these sensors in some situations (e.g. Jethva et al., 2013; Meyer et al., 2013). We present a summary of some analyses of the potential of MODIS-like instruments for this purpose, along with two case studies using airborne observations from the Ames Airborne Tracking Sunphotometer (AATS; http://geo.arc.nasa.gov/sgg/AATS-website/) as a validation data source for a preliminary AAC algorithm applied to MODIS measurements. AAC retrievals will eventually be added to the MODIS Deep Blue (Hsu et al., 2013) processing chain.

MEaSUREs Land Surface Temperature from GOES Satellites

NASA Astrophysics Data System (ADS)

Pinker, Rachel T.; Chen, Wen; Ma, Yingtao; Islam, Tanvir; Borbas, Eva; Hain, Chris; Hulley, Glynn; Hook, Simon

2017-04-01

Information on Land Surface Temperature (LST) can be generated from observations made from satellites in low Earth orbit (LEO) such as MODIS and ASTER and by sensors in geostationary Earth orbit (GEO) such as GOES. Under a project titled: "A Unified and Coherent Land Surface Temperature and Emissivity Earth System Data Record for Earth Science" led by Jet Propulsion Laboratory, an effort is underway to develop long term consistent information from both such systems. In this presentation we will describe an effort to derive LST information from GOES satellites. Results will be presented from two approaches: 1) based on regression developed from a wide range of simulations using MODTRAN, SeeBor Version 5.0 global atmospheric profiles and the CAMEL (Combined ASTER and MODIS Emissivity for Land) product based on the standard University of Wisconsin 5 km emissivity values (UWIREMIS) and the ASTER Global Emissivity Database (GED) product; 2) RTTOV radiative transfer model driven with MERRA-2 reanalysis fields. We will present results of evaluation of these two methods against various products, such as MOD11, and ground observations for the five year period of (2004-2008).

Hazard Mapping System Fire and Smoke Product - Office of Satellite and

Science.gov Websites

Floater Imagery NASA MODIS NASA MODIS Rapid Response NESDIS Products Archived Fire Products (6 months OMI SO2 NASA data portal NRL Aerosol page NRL Aerosol links NOAA Earth System Research Lab RAMSDIS G

Improved meteorology from an updated WRF/CMAQ modeling system with MODIS vegetation and albedo

EPA Science Inventory

Realistic vegetation characteristics and phenology from the Moderate Resolution Imaging Spectroradiometer (MODIS) products improve the simulation for the meteorology and air quality modeling system WRF/CMAQ (Weather Research and Forecasting model and Community Multiscale Air Qual...

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

NASA Technical Reports Server (NTRS)

Li, Yonghong; Wu, Aisheng; Xiong, Xiaoxiong

2016-01-01

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

HDL cholesterol as a diagnostic tool for clinical differentiation of GCK-MODY from HNF1A-MODY and type 1 diabetes in children and young adults.

PubMed

Fendler, Wojciech; Borowiec, Maciej; Antosik, Karolina; Szadkowska, Agnieszka; Deja, Grazyna; Jarosz-Chobot, Przemyslawa; Mysliwiec, Malgorzata; Wyka, Krystyna; Pietrzak, Iwona; Skupien, Jan; Malecki, Maciej T; Mlynarski, Wojciech

2011-09-01

Confirmation of monogenic diabetes caused by glucokinase mutations (GCK-MODY) allows pharmacogenetic intervention in the form of insulin discontinuation. This is especially important among paediatric and young adult populations where GCK-MODY is most prevalent. The study evaluated the utility of lipid parameters in screening for patients with GCK-MODY. Eighty-nine children with type 1 diabetes and 68 with GCK-MODY were screened for triglyceride (TG), total and HDL cholesterol levels. Standardization against a control group of 171 healthy children was applied to eliminate the effect of development. Clinical applicability and cut-off value were evaluated in all available patients with GCK-MODY (n = 148), hepatocyte nuclear factor 1-alpha-MODY (HNF1A MODY) (n = 37) or type 1 diabetes (n = 221). Lower lipid parameter values were observed in GCK-MODY than in patients with type 1 diabetes. Standard deviation scores were -0·22 ± 2·24 vs 1·31 ± 2·17 for HDL cholesterol (P < 0·001), -0·16 ± 2·14 vs 0·60 ± 1·77 for total cholesterol (P = 0·03) and -0·57 ± 0·97 vs-0·22 ± 0·97 for TG (P = 0·05). Validation analysis confirmed that HDL cholesterol was the best parameter for GCK-MODY selection [sensitivity 87%, specificity 54%, negative predictive value (NPV) 86%, positive PV 56%]. A threshold HDL concentration of 1·56 mm offered significantly better diagnostic efficiency than total cholesterol (cut-off value 4·51 mm; NPV 80%; PPV 38%; P < 0·001). TG did not offer a meaningful cut-off value. HDL cholesterol levels measured in individuals with likely monogenic diabetes may be useful in screening for GCK-MODY and differentiation from T1DM and HNF1A-MODY, regardless of treatment or metabolic control. © 2011 Blackwell Publishing Ltd.

Daytime Cloud Property Retrievals Over the Arctic from Multispectral MODIS Data

NASA Technical Reports Server (NTRS)

Spangenberg, Douglas A.; Trepte, Qing; Minnis, Patrick; Uttal, Taneil

2004-01-01

Improving climate model predictions over Earth's polar regions requires a complete understanding of polar clouds properties. Passive satellite remote sensing techniques can be used to retrieve macro and microphysical properties of polar cloud systems. However, over the Arctic, there is minimal contrast between clouds and the background snow surface observed in satellite data, especially for visible wavelengths. This makes it difficult to identify clouds and retrieve their properties from space. Variable snow and ice cover, temperature inversions, and the predominance of mixed-phase clouds further complicate cloud property identification. For this study, the operational Clouds and the Earth s Radiant Energy System (CERES) cloud mask is first used to discriminate clouds from the background surface in Terra Moderate Resolution Imaging Spectroradiometer (MODIS) data. A solar-infrared infrared nearinfrared technique (SINT) first used by Platnick et al. (2001) is used here to retrieve cloud properties over snow and ice covered regions.

Can MODIS AOD be employed to derive PM2.5 in Beijing-Tianjin-Hebei over China?

NASA Astrophysics Data System (ADS)

Ma, Xiaoyan; Wang, Jianying; Yu, Fangqun; Jia, Hailing; Hu, Yanan

2016-11-01

The fine particular matter (PM) concentrations in China have increased considerably due to the rapid economic growth and urbanization in the last few decades, especially in the most populated and industrialized regions. Beijing-Tianjin-Hebei is one of the most polluted regions in China, so to monitor the PM2.5 concentrations over this region is quite critical for human health. By making use the new released hourly PM2.5 mass concentration from ground-based observations in Beijing-Tianjin-Hebei over China, and collocated MODIS level 2 AOD data from April 2014 to March 2015, we explored the relation between surface PM2.5 mass concentration and MODIS AOD and possibility to derive the surface PM2.5 from satellite retrieval in the region. Our study show that the relation strongly depend on the seasons due to distinct seasonal characteristics of PM2.5 and AOD, with a relatively better correlation in spring and summertime (correlation coefficient r ranging from 0.52 to 0.79) than autumn and wintertime (r can be low as to 0.23 in site Baoding). Our analysis gave evidence that worse relationship and/or smaller number of sample in wintertime is associated with the significantly high PM2.5 concentration and a lot of missing data occurring in MODIS AOD, implying that current MODIS AOD retrieval scheme does not work very well in highly polluted cases. The derived PM2.5 mass concentration from MODIS AOD in summertime can basically capture the major observed features of the time series and about 20% large bias of the derived values compared to the observation is expected to be reduced if longer time period data is available and used for analysis.

Can MODIS AOD be employed to derive PM2.5 in Beijing-Tianjin-Hebei over China?

NASA Astrophysics Data System (ADS)

Ma, Xiaoyan

2017-04-01

The fine particular matter (PM) concentrations in China have increased considerably due to the rapid economic growth and urbanization in the last few decades, especially in the most populated and industrialized regions. The Beijing-Tianjin-Hebei is one of the most polluted regions in China, so to monitor the PM2.5 concentrations over this region is quite critical for human health. By making use the new released hourly PM2.5 mass concentration from ground-based observations in Beijing-Tianjin-Hebei over China, and the collocated MODIS level 2 AOD data from April 2014 to March 2015, we explored the relation between surface PM2.5 mass concentration and MODIS AOD and possibility to derive the surface PM2.5 from satellite retrieval in the region. Our study show that the relation strongly depend on the seasons due to distinct seasonal characteristics of PM2.5 and AOD, with a relatively better correlation in spring and summertime than autumn and wintertime. Our analysis give an evidence that worse relationship and/or smaller number of sample in wintertime is associated with the significantly high PM2.5 concentration and a lot of missing data occurring in MODIS AOD, implying that current MODIS AOD retrieval scheme does not work very well in highly polluted cases. The derived PM2.5 mass concentration from MODIS AOD in summertime can basically capture the major observed features of the time series and about 20% large bias of the derived values compared to the observation is expected to be reduced once longer time period data is available and used for analysis.

MODIS Snow and Sea Ice Products

NASA Technical Reports Server (NTRS)

Hall, Dorothy K.; Riggs, George A.; Salomonson, Vincent V.

2004-01-01

In this chapter, we describe the suite of Earth Observing System (EOS) Moderate-Resolution Imaging Spectroradiometer (MODIS) Terra and Aqua 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.

Optimal interpolation analysis of leaf area index using MODIS data

USGS Publications Warehouse

Gu, Yingxin; Belair, Stephane; Mahfouf, Jean-Francois; Deblonde, Godelieve

2006-01-01

A simple data analysis technique for vegetation leaf area index (LAI) using Moderate Resolution Imaging Spectroradiometer (MODIS) data is presented. The objective is to generate LAI data that is appropriate for numerical weather prediction. A series of techniques and procedures which includes data quality control, time-series data smoothing, and simple data analysis is applied. The LAI analysis is an optimal combination of the MODIS observations and derived climatology, depending on their associated errors σo and σc. The “best estimate” LAI is derived from a simple three-point smoothing technique combined with a selection of maximum LAI (after data quality control) values to ensure a higher quality. The LAI climatology is a time smoothed mean value of the “best estimate” LAI during the years of 2002–2004. The observation error is obtained by comparing the MODIS observed LAI with the “best estimate” of the LAI, and the climatological error is obtained by comparing the “best estimate” of LAI with the climatological LAI value. The LAI analysis is the result of a weighting between these two errors. Demonstration of the method described in this paper is presented for the 15-km grid of Meteorological Service of Canada (MSC)'s regional version of the numerical weather prediction model. The final LAI analyses have a relatively smooth temporal evolution, which makes them more appropriate for environmental prediction than the original MODIS LAI observation data. They are also more realistic than the LAI data currently used operationally at the MSC which is based on land-cover databases.

Is It Possible to Distinguish Between Dust and Salt Aerosol Over Waters with Unknown Chlorophyll Concentrations Using Spectral Remote Sensing?

NASA Technical Reports Server (NTRS)

Levy, R. C.; Kaufman, Y. J.

1999-01-01

Atmospheric aerosol has uncertain impacts on the global climate system, as well as on atmospheric and bio-geo-chemical processes of regional and local scales. EOS-MODIS is one example of a satellite sensor designed to improve understanding of the aerosols' type, size and distribution at all temporal and spatial scales. Ocean scientists also plan to use data from EOS-MODIS to assess the temporal and spatial coverage of in-water chlorophyll. MODIS is the first sensor planned to observe the combined ocean-atmosphere system with a wide spectral range (from 410 to 2200 nm). Dust aerosol and salt aerosol have similar spectral signals for wavelengths longer than 550 nm, but because dust selectively absorbs blue light, they have divergent signals in the blue wavelength regions (412 to 490 nm). Chlorophyll also selectively absorbs blue radiation, so that varying chlorophyll concentrations produces a highly varying signal in the blue regions, but less variability in the green, and almost no signal in the red to mid-infrared regions. Thus, theoretically, it may be difficult to differentiate dust and salt in the presence of unknown chlorophyll in the ocean. This study attempts to address the cases in which aerosol and chlorophyll signals can and cannot be separated. For the aerosol spectra, we use the aerosol lookup table from the operational MODIS aerosol-over-ocean algorithm, and for chlorophyll spectra, we use the SeaBAM data set (created for SeaWiFS). We compare the signals using Principal Component Analysis and attempt to retrieve both chlorophyll and aerosol properties using a variant of the operational MODIS aerosol-over-ocean algorithm. Results show that for small optical depths, less than 0.5, it is not possible to differentiate between dust and salt and to determine the chlorophyll concentration at the same time. For larger aerosol optical depths, the chlorophyll signals are comparatively insignificant, and we can hope to distinguish between dust and salt.

Improved meteorology from an updated WRF/CMAQ modeling ...

EPA Pesticide Factsheets

Realistic vegetation characteristics and phenology from the Moderate Resolution Imaging Spectroradiometer (MODIS) products improve the simulation for the meteorology and air quality modeling system WRF/CMAQ (Weather Research and Forecasting model and Community Multiscale Air Quality model) that employs the Pleim-Xiu land surface model (PX LSM). Recently, PX LSM WRF/CMAQ has been updated in vegetation, soil, and boundary layer processes resulting in improved 2 m temperature (T) and mixing ratio (Q), 10 m wind speed, and surface ozone simulations across the domain compared to the previous version for a period around August 2006. Yearlong meteorology simulations with the updated system demonstrate that MODIS input helps reduce bias of the 2 m Q estimation during the growing season from April to September. Improvements follow the green-up in the southeast from April and move toward the west and north through August. From October to March, MODIS input does not have much influence on the system because vegetation is not as active. The greatest effects of MODIS input include more accurate phenology, better representation of leaf area index (LAI) for various forest ecosystems and agricultural areas, and realistically sparse vegetation coverage in the western drylands. Despite the improved meteorology, MODIS input causes higher bias for the surface O3 simulation in April, August, and October in areas where MODIS LAI is much less than the base LAI. Thus, improvement

Study on ice cloud optical thickness retrieval with MODIS IR spectral bands

NASA Astrophysics Data System (ADS)

Zhang, Hong; Li, Jun

2005-01-01

The operational Moderate-Resolution Imaging Spectroradiometer (MODIS) products for cloud properties such as cloud-top pressure (CTP), effective cloud amount (ECA), cloud particle size (CPS), cloud optical thickness (COT), and cloud phase (CP) have been available for users globally. An approach to retrieve COT is investigated using MODIS infrared (IR) window spectral bands (8.5 mm, 11mm, and 12 mm). The COT retrieval from MODIS IR bands has the potential to provide microphysical properties with high spatial resolution during night. The results are compared with those from operational MODIS products derived from the visible (VIS) and near-infrared (NIR) bands during day. Sensitivity of COT to MODIS spectral brightness temperature (BT) and BT difference (BTD) values is studied. A look-up table is created from the cloudy radiative transfer model accounting for the cloud absorption and scattering for the cloud microphysical property retrieval. The potential applications and limitations are also discussed. This algorithm can be applied to the future imager systems such as Visible/Infrared Imager/Radiometer Suite (VIIRS) on the National Polar-orbiting Operational Environmental Satellite System (NPOESS) and Advanced Baseline Imager (ABI) on the Geostationary Operational Environmental Satellite (GOES)-R.

A Modeling and Verification Study of Summer Precipitation Systems Using NASA Surface Initialization Datasets

NASA Technical Reports Server (NTRS)

Jonathan L. Case; Kumar, Sujay V.; Srikishen, Jayanthi; Jedlovec, Gary J.

2010-01-01

One of the most challenging weather forecast problems in the southeastern U.S. is daily summertime pulse-type convection. During the summer, atmospheric flow and forcing are generally weak in this region; thus, convection typically initiates in response to local forcing along sea/lake breezes, and other discontinuities often related to horizontal gradients in surface heating rates. Numerical simulations of pulse convection usually have low skill, even in local predictions at high resolution, due to the inherent chaotic nature of these precipitation systems. Forecast errors can arise from assumptions within parameterization schemes, model resolution limitations, and uncertainties in both the initial state of the atmosphere and land surface variables such as soil moisture and temperature. For this study, it is hypothesized that high-resolution, consistent representations of surface properties such as soil moisture, soil temperature, and sea surface temperature (SST) are necessary to better simulate the interactions between the surface and atmosphere, and ultimately improve predictions of summertime pulse convection. This paper describes a sensitivity experiment using the Weather Research and Forecasting (WRF) model. Interpolated land and ocean surface fields from a large-scale model are replaced with high-resolution datasets provided by unique NASA assets in an experimental simulation: the Land Information System (LIS) and Moderate Resolution Imaging Spectroradiometer (MODIS) SSTs. The LIS is run in an offline mode for several years at the same grid resolution as the WRF model to provide compatible land surface initial conditions in an equilibrium state. The MODIS SSTs provide detailed analyses of SSTs over the oceans and large lakes compared to current operational products. The WRF model runs initialized with the LIS+MODIS datasets result in a reduction in the overprediction of rainfall areas; however, the skill is almost equally as low in both experiments using traditional verification methodologies. Output from object-based verification within NCAR s Meteorological Evaluation Tools reveals that the WRF runs initialized with LIS+MODIS data consistently generated precipitation objects that better matched observed precipitation objects, especially at higher precipitation intensities. The LIS+MODIS runs produced on average a 4% increase in matched precipitation areas and a simultaneous 4% decrease in unmatched areas during three months of daily simulations.

The Global Aerosol System As Viewed By MODIS Today

NASA Technical Reports Server (NTRS)

Remer, Lorraine

2008-01-01

The MODerate resolution Imaging Spectroradiometer (MODIS) aerosol algorithms have been working steadily since early 2000 to transform the MODIS-measured spectral solar reflectance from the Earth's surface and atmosphere into a variety of aerosol products. In this lecture I will proceed through a survey of these products, answering the following questions as I proceed. What are the products? How do they compare with ground truth? How do we use these products to describe the global aerosol system? Are aerosols increasing or decreasing? How do aerosols affect climate and clouds?

Reconstructed Solar-Induced Fluorescence: A Machine Learning Vegetation Product Based on MODIS Surface Reflectance to Reproduce GOME-2 Solar-Induced Fluorescence

NASA Astrophysics Data System (ADS)

Gentine, P.; Alemohammad, S. H.

2018-04-01

Solar-induced fluorescence (SIF) observations from space have resulted in major advancements in estimating gross primary productivity (GPP). However, current SIF observations remain spatially coarse, infrequent, and noisy. Here we develop a machine learning approach using surface reflectances from Moderate Resolution Imaging Spectroradiometer (MODIS) channels to reproduce SIF normalized by clear sky surface irradiance from the Global Ozone Monitoring Experiment-2 (GOME-2). The resulting product is a proxy for ecosystem photosynthetically active radiation absorbed by chlorophyll (fAPARCh). Multiplying this new product with a MODIS estimate of photosynthetically active radiation provides a new MODIS-only reconstruction of SIF called Reconstructed SIF (RSIF). RSIF exhibits much higher seasonal and interannual correlation than the original SIF when compared with eddy covariance estimates of GPP and two reference global GPP products, especially in dry and cold regions. RSIF also reproduces intense productivity regions such as the U.S. Corn Belt contrary to typical vegetation indices and similarly to SIF.

Using the Sonoran Desert test site to monitor the long-term radiometric stability of the Landsat TM/ETM+ and Terra MODIS sensors

USGS Publications Warehouse

Angal, A.; Xiong, X.; Choi, T.; Chander, G.; Wu, A.

2009-01-01

Pseudo-invariant ground targets have been extensively used to monitor the long-term radiometric calibration stability of remote sensing instruments. The NASA MODIS Characterization Support Team (MCST), in collaboration with members from the U.S. Geological Survey (USGS) Earth Resources Observation and Science (EROS) Center, has previously demonstrated the use of pseudo-invariant ground sites for the long-term stability monitoring of Terra MODIS and Landsat 7 ETM+ sensors. This paper focuses on the results derived from observations made over the Sonoran Desert. Additionally, Landsat 5 TM data over the Sonoran Desert site were used to evaluate the temporal stability of this site. Top-ofatmosphere (TOA) reflectances were computed for the closely matched TM, ETM+, and MODIS spectral bands over selected regions of interest. The impacts due to different viewing geometries, or the effect of test site Bi-directional Reflectance Distribution Function (BRDF), are also presented. ?? 2009 SPIE.

Contribution of Modis Satellite Image to Estimate the Daily Air Temperature in the Casablanca City, Morocco

NASA Astrophysics Data System (ADS)

Bahi, Hicham; Rhinane, Hassan; Bensalmia, Ahmed

2016-10-01

Air temperature is considered to be an essential variable for the study and analysis of meteorological regimes and chronics. However, the implementation of a daily monitoring of this variable is very difficult to achieve. It requires sufficient of measurements stations density, meteorological parks and favourable logistics. The present work aims to establish relationship between day and night land surface temperatures from MODIS data and the daily measurements of air temperature acquired between [2011-20112] and provided by the Department of National Meteorology [DMN] of Casablanca, Morocco. The results of the statistical analysis show significant interdependence during night observations with correlation coefficient of R2=0.921 and Root Mean Square Error RMSE=1.503 for Tmin while the physical magnitude estimated from daytime MODIS observation shows a relatively coarse error with R2=0.775 and RMSE=2.037 for Tmax. A method based on Gaussian process regression was applied to compute the spatial distribution of air temperature from MODIS throughout the city of Casablanca.

High spatial resolution satellite observations for validation of MODIS land products: IKONOS observations acquired under the NASA scientific data purchase.

Treesearch

Jeffrey T. Morisette; Jaime E. Nickeson; Paul Davis; Yujie Wang; Yuhong Tian; Curtis E. Woodcock; Nikolay Shabanov; Matthew Hansen; Warren B. Cohen; Doug R. Oetter; Robert E. Kennedy

2003-01-01

Phase 1I of the Scientific Data Purchase (SDP) has provided NASA investigators access to data from four different satellite and airborne data sources. The Moderate Resolution Imaging Spectrometer (MODIS) land discipline team (MODLAND) sought to utilize these data in support of land product validation activities with a lbcus on tile EOS Land Validation Core Sites. These...

A Simple Technique for Creating Regional Composites of Sea Surface Temperature from MODIS for Use in Operational Mesoscale NWP

NASA Technical Reports Server (NTRS)

Knievel, Jason C.; Rife, Daran L.; Grim, Joseph A.; Hahmann, Andrea N.; Hacker, Joshua P.; Ge, Ming; Fisher, Henry H.

2010-01-01

This paper describes a simple technique for creating regional, high-resolution, daytime and nighttime composites of sea surface temperature (SST) for use in operational numerical weather prediction (NWP). The composites are based on observations from NASA s Moderate Resolution Imaging Spectroradiometer (MODIS) aboard Aqua and Terra. The data used typically are available nearly in real time, are applicable anywhere on the globe, and are capable of roughly representing the diurnal cycle in SST. The composites resolution is much higher than that of many other standard SST products used for operational NWP, including the low- and high-resolution Real-Time Global (RTG) analyses. The difference in resolution is key because several studies have shown that highly resolved SSTs are important for driving the air sea interactions that shape patterns of static stability, vertical and horizontal wind shear, and divergence in the planetary boundary layer. The MODIS-based composites are compared to in situ observations from buoys and other platforms operated by the National Data Buoy Center (NDBC) off the coasts of New England, the mid-Atlantic, and Florida. Mean differences, mean absolute differences, and root-mean-square differences between the composites and the NDBC observations are all within tenths of a degree of those calculated between RTG analyses and the NDBC observations. This is true whether or not one accounts for the mean offset between the skin temperatures of the MODIS dataset and the bulk temperatures of the NDBC observations and RTG analyses. Near the coast, the MODIS-based composites tend to agree more with NDBC observations than do the RTG analyses. The opposite is true away from the coast. All of these differences in point-wise comparisons among the SST datasets are small compared to the 61.08C accuracy of the NDBC SST sensors. Because skin-temperature variations from land to water so strongly affect the development and life cycle of the sea breeze, this phenomenon was chosen for demonstrating the use of the MODIS-based composite in an NWP model. A simulated sea breeze in the vicinity of New York City and Long Island shows a small, net, but far from universal improvement when MODIS-based composites are used in place of RTG analyses. The timing of the sea breeze s arrival is more accurate at some stations, and the near-surface temperature, wind, and humidity within the breeze are more realistic.

Assimilation of MODIS and VIIRS AOD to improve aerosols forecasts with FV3-GOCART

NASA Astrophysics Data System (ADS)

Pagowski, M.

2017-12-01

In 2016 NOAA chose the FV3 dynamical core as a basis for its future global modeling system. We present an implementation of aerosol module in the FV3 model and its assimilation framework. The parameterization of aerosols is based on the GOCART scheme. The assimilation methodology relies on hybrid 3D-Var and EnKF methods. Aerosol observations include aerosol optical depth at 550 nm from VIIRS satellite. Results and evaluation of the system against independent observations and NASA's MERRA-2 is shown.

Influence of crop type specification and spatial resolution on empirical modeling of field-scale Maize and Soybean carbon fluxes in the US Great Plains

NASA Astrophysics Data System (ADS)

McCombs, A. G.; Hiscox, A.; Wang, C.; Desai, A. R.

2016-12-01

A challenge in satellite land surface remote-sensing models of ecosystem carbon dynamics in agricultural systems is the lack of differentiation by crop type and management. This generalization can lead to large discrepancies between model predictions and eddy covariance flux tower observations of net ecosystem exchange of CO2 (NEE). Literature confirms that NEE varies remarkably among different crop types making the generalization of agriculture in remote sensing based models inaccurate. Here, we address this inaccuracy by identifying and mapping net ecosystem exchange (NEE) in agricultural fields by comparing bulk modeling and modeling by crop type, and using this information to develop empirical models for future use. We focus on mapping NEE in maize and soybean fields in the US Great Plains at higher spatial resolution using the fusion of MODIS and LandSAT surface reflectance. MODIS observed reflectance was downscaled using the ESTARFM downscaling methodology to match spatial scales to those found in LandSAT and that are more appropriate for carbon dynamics in agriculture fields. A multiple regression model was developed from surface reflectance of the downscaled MODIS and LandSAT remote sensing values calibrated against five FLUXNET/AMERIFLUX flux towers located on soybean and/or maize agricultural fields in the US Great Plains with multi-year NEE observations. Our new methodology improves upon bulk approximates to map and model carbon dynamics in maize and soybean fields, which have significantly different photosynthetic capacities.

Examining the NZESM Cloud representation with Self Organizing Maps

NASA Astrophysics Data System (ADS)

Schuddeboom, Alex; McDonald, Adrian; Parsons, Simon; Morgenstern, Olaf; Harvey, Mike

2017-04-01

Several different cloud regimes are identified from MODIS satellite data and the representation of these regimes within the New Zealand Earth System Model (NZESM) is examined. For the development of our cloud classification we utilize a neural network algorithm known as self organizing maps (SOMs) on MODIS cloud top pressure - cloud optical thickness joint histograms. To evaluate the representation of the cloud within NZESM, the frequency and geographical distribution of the regimes is compared between the NZESM and satellite data. This approach has the advantage of not only identifying differences, but also potentially giving additional information about the discrepancy such as in which regions or phases of cloud the differences are most prominent. To allow for a more direct comparison between datasets, the COSP satellite simulation software is applied to NZESM output. COSP works by simulating the observational processes linked to a satellite, within the GCM, so that data can be generated in a way that shares the particular observational bias of specific satellites. By taking the COSP joint histograms and comparing them to our existing classifications we can easily search for discrepancies between the observational data and the simulations without having to be cautious of biases introduced by the satellite. Preliminary results, based on data for 2008, show a significant decrease in overall cloud fraction in the NZESM compared to the MODIS satellite data. To better understand the nature of this discrepancy, the cloud fraction related to different cloud heights and phases were also analysed.

Estimation of Biomass Burning Emissions by Fusing Fire Radiative Power Observed from Polar-orbiting and Geostationary Satellites across the Continental United States

NASA Astrophysics Data System (ADS)

Li, F.; Zhang, X.; Kondragunta, S.

2016-12-01

Trace gases and aerosols released from biomass burning significantly disturb the energy balance of the Earth and also degrade regional air quality. However, biomass burning emissions (BBE) have been poorly estimated using the traditional bottom-up approach because of the substantial uncertainties in the burned area and fuel loads. Recently, Fire Radiative Power (FRP) derived from satellite fire observations enables the estimation of BBE at multiple spatial scales in near real time. Nonetheless, it is very challenging to accurately produce reliable FRP diurnal cycles from either polar-orbiting satellites or geostationary satellites for the calculation of the temporally integrated FRP, Fire Radiative Energy (FRE). Here we reconstruct FRP diurnal cycles by fusing FRP observed from polar-orbiting and geostationary satellites and estimate BBE from 2011 to 2015 across the Continental United States. Specifically, FRP from the Geostationary Operational Environmental Satellite (GOES) is preprocessed and calibrated using the collocated and concurred observations from the Moderate Resolution Imaging Spectroradiometer (MODIS) over Landsat TM burn scars. The climatologically diurnal FRP curves are then calculated from the calibrated GOES FRP for the 25 Bailey's ecoregions. By fitting MODIS FRP and the calibrated GOES FRP to the climatological curves, FRP diurnal cycles are further reconstructed for individual days at a 0.25-degree grid. Both FRE estimated from FRP diurnal cycles and ecoregion specified FRE combustion rates are used to estimate hourly BBE. The estimated BBE is finally evaluated using QFED and GFED4.0 inventories and emissions modeled using Landsat TM 30m burn severities and 30m fuel loading from Fuel Characteristic Classification System. The results show that BBE estimates are greatly improved by using the reconstructed FRP diurnal cycles from high temporal (GOES) and high spatial resolution (MODIS) FRP observations.

Viirs Land Science Investigator-Led Processing System

NASA Astrophysics Data System (ADS)

Devadiga, S.; Mauoka, E.; Roman, M. O.; Wolfe, R. E.; Kalb, V.; Davidson, C. C.; Ye, G.

2015-12-01

The objective of the NASA's Suomi National Polar Orbiting Partnership (S-NPP) Land Science Investigator-led Processing System (Land SIPS), housed at the NASA Goddard Space Flight Center (GSFC), is to produce high quality land products from the Visible Infrared Imaging Radiometer Suite (VIIRS) to extend the Earth System Data Records (ESDRs) developed from NASA's heritage Earth Observing System (EOS) Moderate Resolution Imaging Spectroradiometer (MODIS) onboard the EOS Terra and Aqua satellites. In this paper we will present the functional description and capabilities of the S-NPP Land SIPS, including system development phases and production schedules, timeline for processing, and delivery of land science products based on coordination with the S-NPP Land science team members. The Land SIPS processing stream is expected to be operational by December 2016, generating land products either using the NASA science team delivered algorithms, or the "best-of" science algorithms currently in operation at NASA's Land Product Evaluation and Algorithm Testing Element (PEATE). In addition to generating the standard land science products through processing of the NASA's VIIRS Level 0 data record, the Land SIPS processing system is also used to produce a suite of near-real time products for NASA's application community. Land SIPS will also deliver the standard products, ancillary data sets, software and supporting documentation (ATBDs) to the assigned Distributed Active Archive Centers (DAACs) for archival and distribution. Quality assessment and validation will be an integral part of the Land SIPS processing system; the former being performed at Land Data Operational Product Evaluation (LDOPE) facility, while the latter under the auspices of the CEOS Working Group on Calibration & Validation (WGCV) Land Product Validation (LPV) Subgroup; adopting the best-practices and tools used to assess the quality of heritage EOS-MODIS products generated at the MODIS Adaptive Processing System (MODAPS).

Recent Weather Extremes and Impacts on Agricultural Production and Vector-Borne Disease Outbreak Patterns

NASA Technical Reports Server (NTRS)

Anyamba, Assaf; Small, Jennifer L.; Britch, Seth C.; Tucker, Compton J.; Pak, Edwin W.; Reynolds, Curt A.; Crutchfield, James; Linthicum, Kenneth J.

2014-01-01

We document significant worldwide weather anomalies that affected agriculture and vector-borne disease outbreaks during the 2010-2012 period. We utilized 2000-2012 vegetation index and land surface temperature data from NASA's satellite-based Moderate Resolution Imaging Spectroradiometer (MODIS) to map the magnitude and extent of these anomalies for diverse regions including the continental United States, Russia, East Africa, Southern Africa, and Australia. We demonstrate that shifts in temperature and/or precipitation have significant impacts on vegetation patterns with attendant consequences for agriculture and public health. Weather extremes resulted in excessive rainfall and flooding as well as severe drought, which caused,10 to 80% variation in major agricultural commodity production (including wheat, corn, cotton, sorghum) and created exceptional conditions for extensive mosquito-borne disease outbreaks of dengue, Rift Valley fever, Murray Valley encephalitis, and West Nile virus disease. Analysis of MODIS data provided a standardized method for quantifying the extreme weather anomalies observed during this period. Assessments of land surface conditions from satellite-based systems such as MODIS can be a valuable tool in national, regional, and global weather impact determinations.

Surface spectral emissivity derived from MODIS data

NASA Astrophysics Data System (ADS)

Chen, Yan; Sun-Mack, Sunny; Minnis, Patrick; Smith, William L.; Young, David F.

2003-04-01

Surface emissivity is essential for many remote sensing applications including the retrieval of the surface skin temperature from satellite-based infrared measurements, determining thresholds for cloud detection and for estimating the emission of longwave radiation from the surface, an important component of the energy budget of the surface-atmosphere interface. In this paper, data from the Terra MODIS (MODerate-resolution Imaging Spectroradiometer) taken at 3.7, 8.5, 10.8, 12.0 micron are used to simultaneously derive the skin temperature and the surface emissivities at the same wavelengths. The methodology uses separate measurements of the clear-sky temperatures that are determined by the CERES (Clouds and Earth's Radiant Energy System) scene classification in each channel during the daytime and at night. The relationships between the various channels at night are used during the day when solar reflectance affects the 3.7 micron data. A set of simultaneous equations is then solved to derive the emissivities. Global results are derived from MODIS. Numerical weather analyses are used to provide soundings for correcting the observed radiances for atmospheric absorption. These results are verified and will be available for remote sensing applications.

Recent weather extremes and impacts on agricultural production and vector-borne disease outbreak patterns.

PubMed

Anyamba, Assaf; Small, Jennifer L; Britch, Seth C; Tucker, Compton J; Pak, Edwin W; Reynolds, Curt A; Crutchfield, James; Linthicum, Kenneth J

2014-01-01

We document significant worldwide weather anomalies that affected agriculture and vector-borne disease outbreaks during the 2010-2012 period. We utilized 2000-2012 vegetation index and land surface temperature data from NASA's satellite-based Moderate Resolution Imaging Spectroradiometer (MODIS) to map the magnitude and extent of these anomalies for diverse regions including the continental United States, Russia, East Africa, Southern Africa, and Australia. We demonstrate that shifts in temperature and/or precipitation have significant impacts on vegetation patterns with attendant consequences for agriculture and public health. Weather extremes resulted in excessive rainfall and flooding as well as severe drought, which caused ∼10 to 80% variation in major agricultural commodity production (including wheat, corn, cotton, sorghum) and created exceptional conditions for extensive mosquito-borne disease outbreaks of dengue, Rift Valley fever, Murray Valley encephalitis, and West Nile virus disease. Analysis of MODIS data provided a standardized method for quantifying the extreme weather anomalies observed during this period. Assessments of land surface conditions from satellite-based systems such as MODIS can be a valuable tool in national, regional, and global weather impact determinations.

Validating MODIS and Sentinel-2 NDVI Products at a Temperate Deciduous Forest Site Using Two Independent Ground-Based Sensors.

PubMed

Lange, Maximilian; Dechant, Benjamin; Rebmann, Corinna; Vohland, Michael; Cuntz, Matthias; Doktor, Daniel

2017-08-11

Quantifying the accuracy of remote sensing products is a timely endeavor given the rapid increase in Earth observation missions. A validation site for Sentinel-2 products was hence established in central Germany. Automatic multispectral and hyperspectral sensor systems were installed in parallel with an existing eddy covariance flux tower, providing spectral information of the vegetation present at high temporal resolution. Normalized Difference Vegetation Index (NDVI) values from ground-based hyperspectral and multispectral sensors were compared with NDVI products derived from Sentinel-2A and Moderate-resolution Imaging Spectroradiometer (MODIS). The influence of different spatial and temporal resolutions was assessed. High correlations and similar phenological patterns between in situ and satellite-based NDVI time series demonstrated the reliability of satellite-based phenological metrics. Sentinel-2-derived metrics showed better agreement with in situ measurements than MODIS-derived metrics. Dynamic filtering with the best index slope extraction algorithm was nevertheless beneficial for Sentinel-2 NDVI time series despite the availability of quality information from the atmospheric correction procedure.

Validating MODIS and Sentinel-2 NDVI Products at a Temperate Deciduous Forest Site Using Two Independent Ground-Based Sensors

PubMed Central

Lange, Maximilian; Rebmann, Corinna; Cuntz, Matthias; Doktor, Daniel

2017-01-01

Quantifying the accuracy of remote sensing products is a timely endeavor given the rapid increase in Earth observation missions. A validation site for Sentinel-2 products was hence established in central Germany. Automatic multispectral and hyperspectral sensor systems were installed in parallel with an existing eddy covariance flux tower, providing spectral information of the vegetation present at high temporal resolution. Normalized Difference Vegetation Index (NDVI) values from ground-based hyperspectral and multispectral sensors were compared with NDVI products derived from Sentinel-2A and Moderate-resolution Imaging Spectroradiometer (MODIS). The influence of different spatial and temporal resolutions was assessed. High correlations and similar phenological patterns between in situ and satellite-based NDVI time series demonstrated the reliability of satellite-based phenological metrics. Sentinel-2-derived metrics showed better agreement with in situ measurements than MODIS-derived metrics. Dynamic filtering with the best index slope extraction algorithm was nevertheless beneficial for Sentinel-2 NDVI time series despite the availability of quality information from the atmospheric correction procedure. PMID:28800065

Photosynthetic Efficiency of Northern Forest Ecosystems Using a MODIS-Derived Photochemical Reflectance Index (PRI)

NASA Technical Reports Server (NTRS)

Middleton, E. M.; Huemmrich, K. F.; Landis, D. R.; Black, T. A.; Barr, A. G.; McCaughey, J. H.

2016-01-01

This study evaluates a direct remote sensing approach from space for the determination of ecosystem photosynthetic light use efficiency (LUE), through measurement of vegetation reflectance changes expressed with the Photochemical Reflectance Index (PRI). The PRI is a normalized difference index based on spectral changes at a physiologically active wavelength (approximately 531 nanometers) as compared to a reference waveband, and is only available from a very few satellites. These include the two Moderate-Resolution Imaging Spectroradiometers (MODIS) on the Aqua and Terra satellites each of which have a narrow (10-nanometer) ocean band centered at 531 nanometers. We examined several PRI variations computed with candidate reference bands, since MODIS lacks the traditional 570-nanometer reference band. The PRI computed using MODIS land band 1 (620-670 nanometers) gave the best performance for daily LUE estimation. Through rigorous statistical analyses over a large image collection (n equals 420), the success of relating in situ daily tower-derived LUE to MODIS observations for northern forests was strongly influenced by satellite viewing geometry. LUE was calculated from CO2 fluxes (moles per moles of carbon absorbed quanta) measured at instrumented Canadian Carbon Program flux towers in four Canadian forests: a mature fir site in British Columbia, mature aspen and black spruce sites in Saskatchewan, and a mixed deciduous/coniferous forest site in Ontario. All aspects of the viewing geometry had significant effects on the MODIS-PRI, including the view zenith angle (VZA), the view azimuth angle, and the displacement of the view azimuth relative to the solar principal plane, in addition to illumination related variables.Nevertheless, we show that forward scatter sector views (VZA, 16 degrees-45 degrees) provided the strongest relationships to daily LUE, especially those collected in the early afternoon by Aqua (r squared = 0.83, RMSE (root mean square error) equals 0.003 moles per moles of carbon absorbed quanta). Nadir (VZA, 0 degrees plus or minus 15 degrees) and backscatter views (VZA, -16 degrees to -45 degrees) had lower performance in estimating LUE (nadir: r squared approximately equal to 0.62-0.67; backscatter: r squared approximately equal to 0.54-0.59) and similar estimation error (RMSE equals 0.004-0.005).When directional effects were not considered, only a moderately successful MODIS-PRI vs. LUE relationship (r squared equals 0.34, RMSE equals 0.007) was obtained in the full dataset (all views & sites, both satellites), but site-specific relationships were able to discriminate between coniferous and deciduous forests. Overall, MODIS-PRI values from Terra (late morning) were higher than those from Aqua (early afternoon), before/after the onset of diurnal stress responses expressed spectrally. Therefore, we identified ninety-two Terra-Aqua "same day" pairs, for which the sum of Terra morning and Aqua afternoon MODIS-PRI values (PRI (sub sum) using all available directional observations was linearly correlated with daily tower LUE (r squared equals 0.622, RMSE equals 0.013) and independent of site differences or meteorological information. Our study highlights the value of off-nadir directional reflectance observations, and the value of pairing morning and afternoon satellite observations to monitor stress responses that inhibit carbon uptake in Canadian forest ecosystems. In addition, we show that MODIS-PRI values, when derived from either: (i) forward views only, or (ii) Terra/Aqua same day (any view) combined observations, provided more accurate estimates of tower-measured daily LUE than those derived from either nadir or backscatter views or those calculated by the widely used semi-operational MODIS GPP model (MOD17) which is based on a theoretical maximum LUE and environmental data. Consequently, we demonstrate the importance of diurnal as well as off-nadir satellite observations for detecting vegetation physiological processes.

The 2006 lava dome eruption of Merapi Volcano (Indonesia): Detailed analysis using MODIS TIR

NASA Astrophysics Data System (ADS)

Carr, Brett B.; Clarke, Amanda B.; Vanderkluysen, Loÿc

2016-02-01

Merapi is one of Indonesia's most active and dangerous volcanoes. Prior to the 2010 VEI 4 eruption, activity at Merapi during the 20th century was characterized by the growth and collapse of a series of lava domes. Periods of very slow growth were punctuated by short episodes of increased eruption rates characterized by dome collapse-generated pyroclastic density currents (PDCs). An eruptive event of this type occurred in May-June, 2006. For effusive eruptions such as this, detailed extrusion rate records are important for understanding the processes driving the eruption and the hazards presented by the eruption. We use thermal infrared (TIR) images from the Moderate Resolution Imaging Spectrometer (MODIS) instrument on NASA's Aqua and Terra satellites to estimate extrusion rates at Merapi Volcano during the 2006 eruption using the method of Harris and Ripepe (2007). We compile a set of 75 nighttime MODIS images of the eruptive period to produce a detailed time series of thermal radiance and extrusion rate that reveal multiple phases of the 2006 eruption. These data closely correspond to the published ground-based observational record and improve observation density and detail during the eruption sequence. Furthermore, additional analysis of radiance values for thermal anomalies in Band 21 (λ = 3.959 μm) of MODIS images results in a new framework for detecting different styles of activity. We successfully discriminate among slow dome growth, rapid dome growth, and PDC-producing dome collapse. We also demonstrate a positive correlation between PDC frequency and extrusion rate, and provide evidence that extrusion rate can increase in response to external events such as dome collapses or tectonic earthquakes. This study represents a new method of documenting volcanic activity that can be applied to other similar volcanic systems.

Retrieval of radiative and microphysical properties of clouds from multispectral infrared measurements

NASA Astrophysics Data System (ADS)

Iwabuchi, Hironobu; Saito, Masanori; Tokoro, Yuka; Putri, Nurfiena Sagita; Sekiguchi, Miho

2016-12-01

Satellite remote sensing of the macroscopic, microphysical, and optical properties of clouds are useful for studying spatial and temporal variations of clouds at various scales and constraining cloud physical processes in climate and weather prediction models. Instead of using separate independent algorithms for different cloud properties, a unified, optimal estimation-based cloud retrieval algorithm is developed and applied to moderate resolution imaging spectroradiometer (MODIS) observations using ten thermal infrared bands. The model considers sensor configurations, background surface and atmospheric profile, and microphysical and optical models of ice and liquid cloud particles and radiative transfer in a plane-parallel, multilayered atmosphere. Measurement and model errors are thoroughly quantified from direct comparisons of clear-sky observations over the ocean with model calculations. Performance tests by retrieval simulations show that ice cloud properties are retrieved with high accuracy when cloud optical thickness (COT) is between 0.1 and 10. Cloud-top pressure is inferred with uncertainty lower than 10 % when COT is larger than 0.3. Applying the method to a tropical cloud system and comparing the results with the MODIS Collection 6 cloud product shows good agreement for ice cloud optical thickness when COT is less than about 5. Cloud-top height agrees well with estimates obtained by the CO2 slicing method used in the MODIS product. The present algorithm can detect optically thin parts at the edges of high clouds well in comparison with the MODIS product, in which these parts are recognized as low clouds by the infrared window method. The cloud thermodynamic phase in the present algorithm is constrained by cloud-top temperature, which tends not to produce results with an ice cloud that is too warm and liquid cloud that is too cold.

Crop Phenology Detection Using High Spatio-Temporal Resolution Data Fused from SPOT5 and MODIS Products.

PubMed

Zheng, Yang; Wu, Bingfang; Zhang, Miao; Zeng, Hongwei

2016-12-10

Timely and efficient monitoring of crop phenology at a high spatial resolution are crucial for the precise and effective management of agriculture. Recently, satellite-derived vegetation indices (VIs), such as the Normalized Difference Vegetation Index (NDVI), have been widely used for the phenology detection of terrestrial ecosystems. In this paper, a framework is proposed to detect crop phenology using high spatio-temporal resolution data fused from Systeme Probatoire d'Observation de la Tarre5 (SPOT5) and Moderate Resolution Imaging Spectroradiometer (MODIS) images. The framework consists of a data fusion method to produce a synthetic NDVI dataset at SPOT5's spatial resolution and at MODIS's temporal resolution and a phenology extraction algorithm based on NDVI time-series analysis. The feasibility of our phenology detection approach was evaluated at the county scale in Shandong Province, China. The results show that (1) the Spatial and Temporal Adaptive Reflectance Fusion Model (STARFM) algorithm can accurately blend SPOT5 and MODIS NDVI, with an R ² of greater than 0.69 and an root mean square error (RMSE) of less than 0.11 between the predicted and referenced data; and that (2) the estimated phenology parameters, such as the start and end of season (SOS and EOS), were closely correlated with the field-observed data with an R ² of the SOS ranging from 0.68 to 0.86 and with an R ² of the EOS ranging from 0.72 to 0.79. Our research provides a reliable approach for crop phenology mapping in areas with high fragmented farmland, which is meaningful for the implementation of precision agriculture.

A Synthesis of VIIRS Solar and Lunar Calibrations

NASA Technical Reports Server (NTRS)

Eplee, Robert E.; Turpie, Kevin R.; Meister, Gerhard; Patt, Frederick S.; Fireman, Gwyn F.; Franz, Bryan A.; McClain, Charles R.

2013-01-01

The NASA VIIRS Ocean Science Team (VOST) has developed two independent calibrations of the SNPP VIIRS moderate resolution reflective solar bands using solar diffuser and lunar observations through June 2013. Fits to the solar calibration time series show mean residuals per band of 0.078-0.10%. There are apparent residual lunar libration correlations in the lunar calibration time series that are not accounted for by the ROLO photometric model of the Moon. Fits to the lunar time series that account for residual librations show mean residuals per band of 0.071-0.17%. Comparison of the solar and lunar time series shows that the relative differences in the two calibrations are 0.12-0.31%. Relative uncertainties in the VIIRS solar and lunar calibration time series are comparable to those achieved for SeaWiFS, Aqua MODIS, and Terra MODIS. Intercomparison of the VIIRS lunar time series with those from SeaWiFS, Aqua MODIS, and Terra MODIS shows that the scatter in the VIIRS lunar observations is consistent with that observed for the heritage instruments. Based on these analyses, the VOST has derived a calibration lookup table for VIIRS ocean color data based on fits to the solar calibration time series.

Global statistics of liquid water content and effective number concentration of water clouds over ocean derived from combined CALIPSO and MODIS measurements

NASA Astrophysics Data System (ADS)

Hu, Y.; Vaughan, M.; McClain, C.; Behrenfeld, M.; Maring, H.; Anderson, D.; Sun-Mack, S.; Flittner, D.; Huang, J.; Wielicki, B.; Minnis, P.; Weimer, C.; Trepte, C.; Kuehn, R.

2007-06-01

This study presents an empirical relation that links the volume extinction coefficients of water clouds, the layer integrated depolarization ratios measured by lidar, and the effective radii of water clouds derived from collocated passive sensor observations. Based on Monte Carlo simulations of CALIPSO lidar observations, this method combines the cloud effective radius reported by MODIS with the lidar depolarization ratios measured by CALIPSO to estimate both the liquid water content and the effective number concentration of water clouds. The method is applied to collocated CALIPSO and MODIS measurements obtained during July and October of 2006, and January 2007. Global statistics of the cloud liquid water content and effective number concentration are presented.

Production and Distribution of Global Products From MODIS

NASA Technical Reports Server (NTRS)

Masuoka, Edward; Smith, David E. (Technical Monitor)

2000-01-01

The Moderate Resolution Imaging Spectroradiometer was launched on the EOS Terra spacecraft in December 1999 and will also fly on EOS Aqua in December 2000. With 36 spectral bands from the visible through thermal infrared and spatial resolution of 250m to 1 kilometer, each MODIS instrument will image the entire Earth surface in 2 days. This paper traces the flow of MODIS 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 MODIS products. As most components of the ground system are severely limited in their capacity to distribute MODIS products, it also describes the key characteristics of MODIS products and their metadata that allow a user to optimize their selection of products given anticipate bottlenecks in distribution.

A Multi-Season Study of the Effects of MODIS Sea-Surface Temperatures on Operational WRF Forecasts at NWS Miami, FL

NASA Technical Reports Server (NTRS)

Case, Jonathan L.; Santos, Pablo; Lazarus, Steven M.; Splitt, Michael E.; Haines, Stephanie L.; Dembek, Scott R.; Lapenta, William M.

2008-01-01

Studies at the Short-term Prediction Research and Transition (SPORT) Center have suggested that the use of Moderate Resolution Imaging Spectroradiometer (MODIS) sea-surface temperature (SST) composites in regional weather forecast models can have a significant positive impact on short-term numerical weather prediction in coastal regions. Recent work by LaCasse et al (2007, Monthly Weather Review) highlights lower atmospheric differences in regional numerical simulations over the Florida offshore waters using 2-km SST composites derived from the MODIS instrument aboard the polar-orbiting Aqua and Terra Earth Observing System satellites. To help quantify the value of this impact on NWS Weather Forecast Offices (WFOs), the SPORT Center and the NWS WFO at Miami, FL (MIA) are collaborating on a project to investigate the impact of using the high-resolution MODIS SST fields within the Weather Research and Forecasting (WRF) prediction system. The project's goal is to determine whether more accurate specification of the lower-boundary forcing within WRF will result in improved land/sea fluxes and hence, more accurate evolution of coastal mesoscale circulations and the associated sensible weather elements. The NWS MIA is currently running WRF in real-time to support daily forecast operations, using the National Centers for Environmental Prediction Nonhydrostatic Mesoscale Model dynamical core within the NWS Science and Training Resource Center's Environmental Modeling System (EMS) software. Twenty-seven hour forecasts are run dally initialized at 0300, 0900, 1500, and 2100 UTC on a domain with 4-km grid spacing covering the southern half of Florida and adjacent waters of the Gulf of Mexico and Atlantic Ocean. Each model run is initialized using the Local Analysis and Prediction System (LAPS) analyses available in AWIPS. The SSTs are initialized with the NCEP Real-Time Global (RTG) analyses at 1/12deg resolution (approx.9 km); however, the RTG product does not exhibit fine-scale details consistent with its grid resolution. SPORT is conducting parallel WRF EMS runs identical to the operational runs at NWS MIA except for the use of MODIS SST composites in place of the RTG product as the initial and boundary conditions over water, The MODIS SST composites for initializing the SPORT WRF runs are generated on a 2-km grid four times daily at 0400, 0700, 1600, and 1900 UTC, based on the times of the overhead passes of the Aqua and Terra satellites. The incorporation of the MODIS SST data into the SPORT WRF runs is staggered such that SSTs are updated with a new composite every six hours in each of the WRF runs. From mid-February to July 2007, over 500 parallel WRF simulations have been collected for analysis and verification. This paper will present verification results comparing the NWS MIA operational WRF runs to the SPORT experimental runs, and highlight any substantial differences noted in the predicted mesoscale phenomena for specific cases.

Monitoring start of season in Alaska with GLOBE, AVHRR, and MODIS data

NASA Astrophysics Data System (ADS)

Robin, Jessica; Dubayah, Ralph; Sparrow, Elena; Levine, Elissa

2008-03-01

This work evaluates whether continuity between Advanced Very High Resolution Radiometer (AVHRR) and Moderate Resolution Imaging Spectroradiometer (MODIS) normalized difference vegetation index (NDVI) is achievable for monitoring phenological changes in Alaska. This work also evaluates whether NDVI can detect changes in start of the growing season (SOS) in this region. Six quadratic regression models with NDVI as a function of accumulated growing degree days (AGDD) were developed from 2001 through 2004 AVHRR and MODIS NDVI data sets for urban, mixed, and forested land covers. Model parameters determined NDVI values for start of the observational period as well as peak and length of the growing season. NDVI values for start of the growing season were determined from the model equations and field observations of SOS made by GLOBE students and researchers at University of Alaska Fairbanks. AGDD was computed from daily air temperature. AVHRR and MODIS models were significantly different from one another with differences in the start of the observational season as well as start, peak, and length of the growing season. Furthermore, AGDD for SOS was significantly lower during the 1990s than the 1980s. NDVI values at SOS did not detect this change. There are limitations with using NDVI to monitor phenological changes in these regions because of snow, the large extent of conifers, and clouds, which restrict the composite period. In addition, differing processing and spectral characteristics restrict continuity between AVHRR and MODIS NDVI data sets.

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

NASA Technical Reports Server (NTRS)

Xiong, X.; Choi, T.; Che, N.; Wang, Z.; Dodd, J.

2010-01-01

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

Monitoring land surface albedo and vegetation dynamics using high spatial and temporal resolution synthetic data from Landsat and MODIS BRDF/albedo product

USDA-ARS?s Scientific Manuscript database

Climate warming over the past half century has led to observable changes in vegetation phenology and growing season length; which can be measured globally using remote sensing derived vegetation indices. Previous studies in mid- and high northern latitude systems show temperature driven earlier spri...

Comparison of Cloud Detection Using the CERES-MODIS Ed4 and LaRC AVHRR Cloud Masks and CALIPSO Vertical Feature Mask

NASA Astrophysics Data System (ADS)

Trepte, Q. Z.; Minnis, P.; Palikonda, R.; Bedka, K. M.; Sun-Mack, S.

2011-12-01

Accurate detection of cloud amount and distribution using satellite observations is crucial in determining cloud radiative forcing and earth energy budget. The CERES-MODIS (CM) Edition 4 cloud mask is a global cloud detection algorithm for application to Terra and Aqua MODIS data with the aid of other ancillary data sets. It is used operationally for the NASA's Cloud and Earth's Radiant Energy System (CERES) project. The LaRC AVHRR cloud mask, which uses only five spectral channels, is based on a subset of the CM cloud mask which employs twelve MODIS channels. The LaRC mask is applied to AVHRR data for the NOAA Climate Data Record Program. Comparisons among the CM Ed4, and LaRC AVHRR cloud masks and the CALIPSO Vertical Feature Mask (VFM) constitute a powerful means for validating and improving cloud detection globally. They also help us understand the strengths and limitations of the various cloud retrievals which use either active and passive satellite sensors. In this paper, individual comparisons will be presented for different types of clouds over various surfaces, including daytime and nighttime, and polar and non-polar regions. Additionally, the statistics of the global, regional, and zonal cloud occurrence and amount from the CERES Ed4, AVHRR cloud masks and CALIPSO VFM will be discussed.

History and Future for the Happy Marriage between the MODIS Land team and Fluxnet

NASA Astrophysics Data System (ADS)

Running, S. W.

2015-12-01

When I wrote the proposal to NASA in 1988 for daily global evapotranspiration and gross primary production algorithms for the MODIS sensor, I had no validation plan. Fluxnet probably saved my MODIS career by developing a global network of rigorously calibrated towers measuring water and carbon fluxes over a wide variety of ecosystems that I could not even envision at the time that first proposal was written. However my enthusiasm for Fluxnet was not reciprocated by the Fluxnet community until we began providing 7 x 7 pixel MODIS Land datasets exactly over each of their towers every 8 days, without them having to crawl thru the global datasets and make individual orders. This system, known informally as the MODIS ASCII cutouts, began in 2002 and operates at the Oak Ridge DAAC to this day, cementing a mutually beneficial data interchange between the Fluxnet and remote sensing communities. This talk will briefly discuss the history of MODIS validation with flux towers, and flux spatial scaling with MODIS data. More importantly I will detail the future continuity of global biophysical datasets in the post-MODIS era, and what next generation sensors will provide.

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

NASA Technical Reports Server (NTRS)

Ichoku, Charles; Kaufman, Yoram; Remer, Lorraine; Chu, D. Allen; Mattoo, Shana; Tanre, Didier; Levy, Robert; Li, Rong-Rong; Kleidman, Richard; Lau, William K. M. (Technical Monitor)

2001-01-01

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

Frequency and causes of failed MODIS cloud property retrievals for liquid phase clouds over global oceans.

PubMed

Cho, Hyoun-Myoung; Zhang, Zhibo; Meyer, Kerry; Lebsock, Matthew; Platnick, Steven; Ackerman, Andrew S; Di Girolamo, Larry; C-Labonnote, Laurent; Cornet, Céline; Riedi, Jerome; Holz, Robert E

2015-05-16

Moderate Resolution Imaging Spectroradiometer (MODIS) retrieves cloud droplet effective radius ( r e ) and optical thickness ( τ ) by projecting observed cloud reflectances 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 reflectances. In this study, the frequency and potential causes of failed MODIS retrievals for marine liquid phase (MLP) clouds are analyzed based on 1 year of Aqua MODIS Collection 6 products and collocated CALIOP and CloudSat observations. The retrieval based on the 0.86 µm and 2.1 µm MODIS 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 reflectivity 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.

Frequency and causes of failed MODIS cloud property retrievals for liquid phase clouds over global oceans

PubMed Central

Cho, Hyoun‐Myoung; Meyer, Kerry; Lebsock, Matthew; Platnick, Steven; Ackerman, Andrew S.; Di Girolamo, Larry; C.‐Labonnote, Laurent; Cornet, Céline; Riedi, Jerome; Holz, Robert E.

2015-01-01

Abstract Moderate Resolution Imaging Spectroradiometer (MODIS) retrieves cloud droplet effective radius (r e) and optical thickness (τ) by projecting observed cloud reflectances 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 reflectances. In this study, the frequency and potential causes of failed MODIS retrievals for marine liquid phase (MLP) clouds are analyzed based on 1 year of Aqua MODIS Collection 6 products and collocated CALIOP and CloudSat observations. The retrieval based on the 0.86 µm and 2.1 µm MODIS 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 reflectivity 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. PMID:27656330

Terrestrial Carbon Sinks in the Brazilian Amazon and Cerrado Region Predicted from MODIS Satellite Data and Ecosystem Modeling

EPA Science Inventory

A simulation model based on satellite observations of monthly vegetation cover from the Moderate Resolution Imaging Spectroradiometer (MODIS) was used to estimate monthly carbon fluxes in terrestrial ecosystems of Brazilian Amazon and Cerrado regions over the period 2000-2004. Pr...

LINKING IN SITU TIME SERIES FOREST CANOPY LAI AND PHENOLOGY METRICS WITH MODIS AND LANDSAT NDVI AND LAI PRODUCTS

EPA Science Inventory

The subject of this presentation is forest vegetation dynamics as observed by the TERRA spacecraft's Moderate-Resolution Imaging Spectroradiometer (MODIS) and Landsat Thematic Mapper, and complimentary in situ time series measurements of forest canopy metrics related to Leaf Area...

MODIS On-Board Blackbody Function and Performance

NASA Technical Reports Server (NTRS)

Xiaoxiong, Xiong; Wenny, Brian N.; Wu, Aisheng; Barnes, William

2009-01-01

Two MODIS instruments are currently in orbit, making continuous global observations in visible to long-wave infrared wavelengths. Compared to heritage sensors, MODIS 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 MODIS and 285K for Aqua MODIS, 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 MODIS 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 Aqua MODIS on-board BB. The on-orbit BB temperature uncertainty is estimated to be 10mK for Terra MODIS at 290K and 5mK for Aqua MODIS 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 Aqua MODIS.

[Humoral response markers in GCK MODY].

PubMed

Skała-Zamorowska, Eliza; Deja, Grażyna; Borowiec, Maciej; Fendler, Wojciech; Małachowska, Beata; Kamińska, Halla; Wyka, Krystyna; Młynarski, Wojciech; Jarosz-Chobot, Przemysława

2016-01-01

The prevalence of antibodies to pancreatic islets in monogenic diabetes remains unknown and the incidence estimation is difficult as the occurrence of autoantibodies in patient is one of the well-known exclusion criteria for further genetic diagnostics. They has been found not only among patients with type 1 diabetes, but also in other types of diabetes: Type 2 diabetes, Latent Autoimmune Diabetes in Adults (LADA) (16) and monogenic diabetes (MD). Immunological characteristic of GCK MODY patients. The study group included families of 27 adolescent patients with GCK MODY (39 parents and 19 siblings) monitored in the Department of Pediatrics, Endocrinology and Diabetes and in the Diabetes Clinic of John Paul II Upper Silesian Child Health Centre in Katowice in the years 2007-2012. All patients and family members with GCK MODY underwent a blood sample drawing for immunological (classic humoral response markers: ICA, GAD, IA-2, IAA) and biochemical diagnostics. Pediatric, diabetes and family medical history was collected from the subjects and parents. Immunological diagnostics was performed in all patients except 1 (96.3%). Immunological diagnostics included 17 (89.5%) parents and 7 (87.5%) siblings with diagnosed GCK MODY. 8 (30.8%) adolescent patients with GCK MODY, 3 subjects (17.64%) among parents (with GCK MODY), as well as 2 subjects (28.57%) among siblings (with GCK MODY) showed a positive antibodies screen. The results of our study in children with GCK MODY and their family members suggest that the occurrence of classic antibodies directed against pancreatic islets antigens is fairly common in patients with GCK MODY. Despite various observations and many legitimate discussions, it is difficult to clarify the pathogenesis of the occurrence of autoantibodies in monogenic diabetes. © Polish Society for Pediatric Endocrinology and Diabetology.

Recent Progress on Deep Blue Aerosol Algorithm as Applied TO MODIS, SEA WIFS, and VIIRS, and Their Intercomparisons with Ground Based and Other Satellite Measurements

NASA Technical Reports Server (NTRS)

Hsu, N. Christina; Bettenhausen, Corey; Sawyer, Andrew; Tsay, Si-Chee

2012-01-01

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/MODIS in 1999, and Aqua/MODIS 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/MODIS 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 / MODIS 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-reflecting surfaces into Sea WiFS / MODIS as well as VIIRS data suite will also be addressed. We will also show the intercomparison results of SeaWiFS/MODIS 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 loadings of both natural and anthropogenic sources based upon more than a decade of combined MODIS/SeaWiFS data (1997-2011) will be discussed. We will also address the importance of various key issues such as differences in spatial-temporal sampling rates and observation time between different satellite measurements could potentially impact these intercomparisons results, especially for using the monthly mean data, and thus on estimates of long-term aerosol trends.

Long-term assessment of the CALIPSO Imaging Infrared Radiometer (IIR) calibration and stability through simulated and observed comparisons with MODIS/Aqua and SEVIRI/Meteosat

NASA Astrophysics Data System (ADS)

Garnier, Anne; Scott, Noëlle A.; Pelon, Jacques; Armante, Raymond; Crépeau, Laurent; Six, Bruno; Pascal, Nicolas

2017-04-01

The quality of the calibrated radiances of the medium-resolution Imaging Infrared Radiometer (IIR) on-board the CALIPSO (Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation) satellite is quantitatively evaluated from the beginning of the mission in June 2006. Two complementary relative and stand-alone approaches are used, which are related to comparisons of measured brightness temperatures and to model-to-observations comparisons, respectively. In both cases, IIR channels 1 (8.65 µm), 2 (10.6 µm), and 3 (12.05 µm) are paired with the Moderate Resolution Imaging Spectroradiometer (MODIS)/Aqua Collection 5 companion channels 29, 31, and 32, respectively, as well as with the Spinning Enhanced Visible and Infrared Imager (SEVIRI)/Meteosat companion channels IR8.7, IR10.8, and IR12, respectively. These pairs were selected before launch to meet radiometric, geometric, and space-time constraints. The prelaunch studies were based on simulations and sensitivity studies using the 4A/OP radiative transfer model and the more than 2300 atmospheres of the climatological Thermodynamic Initial Guess Retrieval (TIGR) input dataset further sorted into five air mass types. Using data from over 9.5 years of on-orbit operation, and following the relative approach technique, collocated measurements of IIR and of its companion channels have been compared at all latitudes over ocean, during day and night, and for all types of scenes in a wide range of brightness temperatures. The relative approach shows an excellent stability of IIR2-MODIS31 and IIR3-MODIS32 brightness temperature differences (BTDs) since launch. A slight trend within the IIR1-MODIS29 BTD, that equals -0.02 K yr-1 on average over 9.5 years, is detected when using the relative approach at all latitudes and all scene temperatures. For very cold scene temperatures (190-200 K) in the tropics, each IIR channel is warmer than its MODIS companion channel by 1.6 K on average. For the stand-alone approach, clear sky measurements only are considered, which are directly compared with simulations using 4A/OP and collocated ERA-Interim (ERA-I) reanalyses. The clear sky mask is derived from collocated observations from IIR and the CALIPSO lidar. Simulations for clear sky pixels in the tropics reproduce the differences between IIR1 and MODIS29 within 0.02 K and between IIR2 and MODIS31 within 0.04 K, whereas IIR3-MODIS32 is larger than simulated by 0.26 K. The stand-alone approach indicates that the trend identified from the relative approach originates from MODIS29, whereas no trend (less than ±0.004 K yr-1) is identified for any of the IIR channels. Finally, using the relative approach, a year-by-year seasonal bias between nighttime and daytime IIR-MODIS BTD was found at mid-latitude in the Northern Hemisphere. It is due to a nighttime IIR bias as determined by the stand-alone approach, which originates from a calibration drift during day-to-night transitions. The largest bias is in June and July when IIR2 and IIR3 are warmer by 0.4 K on average, and IIR1 is warmer by 0.2 K.

Co-variability of smoke and fire in the Amazon basin

NASA Astrophysics Data System (ADS)

Mishra, Amit Kumar; Lehahn, Yoav; Rudich, Yinon; Koren, Ilan

2015-05-01

The Amazon basin is a hot spot of anthropogenically-driven biomass burning, accounting for approximately 15% of total global fire emissions. It is essential to accurately measure these fires for robust regional and global modeling of key environmental processes. Here we have explored the link between spatio-temporal variability patterns in the Amazon basin's fires and the resulting smoke loading using 11 years (2002-2012) of data from the Moderate Resolution Imaging Spectroradiometer (MODIS) and the Aerosol Robotic Network (AERONET) observations. Focusing on the peak burning season (July-October), our analysis shows strong inter-annual correlation between aerosol optical depth (AOD) and two MODIS fire products: fire radiative power (FRP) and fire pixel counts (FC). Among these two fire products, the FC better indicates the amount of smoke in the basin, as represented in remotely sensed AOD data. This fire product is significantly correlated both with regional AOD retrievals from MODIS and with point AOD measurements from the AERONET stations, pointing to spatial homogenization of the smoke over the basin on a seasonal time scale. However, MODIS AODs are found better than AERONET AODs observation for linking between smoke and fire. Furthermore, MODIS AOD measurements are strongly correlated with number of fires ∼10-20 to the east, most likely due to westward advection of smoke by the wind. These results can be rationalized by the regional topography and the wind regimes. Our analysis can improve data assimilation of satellite and ground-based observations into regional and global model studies, thus improving the assessment of the environmental and climatic impacts of frequency and distribution variability of the Amazon basin's fires. We also provide the optimal spatial and temporal scales for ground-based observations, which could be used for such applications.

Detecting Inter-Annual Variations in the Phenology of Evergreen Conifers Using Long-Term MODIS Vegetation Index Time Series

NASA Technical Reports Server (NTRS)

Ulsig, Laura; Nichol, Caroline J.; Huemmrich, Karl F.; Landis, David R.; Middleton, Elizabeth M.; Lyapustin, Alexei I.; Mammarella, Ivan; Levula, Janne; Porcar-Castell, Albert

2017-01-01

Long-term observations of vegetation phenology can be used to monitor the response of terrestrial ecosystems to climate change. Satellite remote sensing provides the most efficient means to observe phenological events through time series analysis of vegetation indices such as the Normalized Difference Vegetation Index (NDVI). This study investigates the potential of a Photochemical Reflectance Index (PRI), which has been linked to vegetation light use efficiency, to improve the accuracy of MODIS-based estimates of phenology in an evergreen conifer forest. Timings of the start and end of the growing season (SGS and EGS) were derived from a 13-year-long time series of PRI and NDVI based on a MAIAC (multi-angle implementation of atmospheric correction) processed MODIS dataset and standard MODIS NDVI product data. The derived dates were validated with phenology estimates from ground-based flux tower measurements of ecosystem productivity. Significant correlations were found between the MAIAC time series and ground-estimated SGS (R (sup 2) equals 0.36-0.8), which is remarkable since previous studies have found it difficult to observe inter-annual phenological variations in evergreen vegetation from satellite data. The considerably noisier NDVI product could not accurately predict SGS, and EGS could not be derived successfully from any of the time series. While the strongest relationship overall was found between SGS derived from the ground data and PRI, MAIAC NDVI exhibited high correlations with SGS more consistently (R (sup 2) is greater than 0.6 in all cases). The results suggest that PRI can serve as an effective indicator of spring seasonal transitions, however, additional work is necessary to confirm the relationships observed and to further explore the usefulness of MODIS PRI for detecting phenology.

Mapping Historic Gypsy Moth Defoliation with MODIS Satellite Data: Implications for Forest Threat Early Warning System

NASA Technical Reports Server (NTRS)

Spurce, Joseph P.; Hargrove, William; Ryan, Robert E.; Smooth, James C.; Prados, Don; McKellip, Rodney; Sader, Steven A.; Gasser, Jerry; May, George

2008-01-01

This viewgraph presentation reviews a project, the goal of which is to study the potential of MODIS data for monitoring historic gypsy moth defoliation. A NASA/USDA Forest Service (USFS) partnership was formed to perform the study. NASA is helping USFS to implement satellite data products into its emerging Forest Threat Early Warning System. The latter system is being developed by the USFS Eastern and Western Forest Threat Assessment Centers. The USFS Forest Threat Centers want to use MODIS time series data for regional monitoring of forest damage (e.g., defoliation) preferably in near real time. The study's methodology is described, and the results of the study are shown.

Comparison of snow melt properties across multiple spatial scales and landscape units in interior sub-Arctic boreal Alaskan watersheds

NASA Astrophysics Data System (ADS)

Bennett, K. E.; Cherry, J. E.; Hiemstra, C. A.; Bolton, W. R.

2013-12-01

Interior sub-Arctic Alaskan snow cover is rapidly changing and requires further study for correct parameterization in physically based models. This project undertook field studies during the 2013 snow melt season to capture snow depth, snow temperature profiles, and snow cover extent to compare with observations from the Moderate Resolution Imaging Spectroradiometer (MODIS) sensor at four different sites underlain by discontinuous permafrost. The 2013 melt season, which turned out to be the latest snow melt period on record, was monitored using manual field measurements (SWE, snow depth data collection), iButtons to record temperature of the snow pack, GoPro cameras to capture time lapse of the snow melt, and low level orthoimagery collected at ~1500 m using a Navion L17a plane mounted with a Nikon D3s camera. Sites were selected across a range of landscape conditions, including a north facing black spruce hill slope, a south facing birch forest, an open tundra site, and a high alpine meadow. Initial results from the adjacent north and south facing sites indicate a highly sensitive system where snow cover melts over just a few days, illustrating the importance of high resolution temporal data capture at these locations. Field observations, iButtons and GoPro cameras show that the MODIS data captures the melt conditions at the south and the north site with accuracy (2.5% and 6.5% snow cover fraction present on date of melt, respectively), but MODIS data for the north site is less variable around the melt period, owing to open conditions and sparse tree cover. However, due to the rapid melt rate trajectory, shifting the melt date estimate by a day results in a doubling of the snow cover fraction estimate observed by MODIS. This information can assist in approximating uncertainty associated with remote sensing data that is being used to populate hydrologic and snow models (the Sacramento Soil Moisture Accounting model, coupled with SNOW-17, and the Variable Infiltration Capacity hydrologic model) and provide greater understanding of error and resultant model sensitivities associated with regional observations of snow cover across the sub-Arctic boreal landscape.

BRDF Characterization and Calibration Inter-Comparison between Terra MODIS, Aqua MODIS, and S-NPP VIIRS

NASA Technical Reports Server (NTRS)

Chang, Tiejun; Xiong, Xiaoxiong (Jack); Angal, Amit; Wu, Aisheng

2016-01-01

The inter-comparison of reflective solar bands (RSB) between Terra MODIS, Aqua MODIS, and SNPP VIIRS is very important for assessment of each instrument's calibration and to identify calibration improvements. One of the limitations of using their ground observations for the assessment is a lack of the simultaneous nadir overpasses (SNOs) over selected pseudo-invariant targets. In addition, their measurements over a selected Earth view target have significant difference in solar and view angles, and these differences magnify the effects of Bidirectional Reflectance Distribution Function (BRDF). In this work, an inter-comparison technique using a semi-empirical BRDF model is developed for reflectance correction. BRDF characterization requires a broad coverage of solar and view angles in the measurements over selected pseudo-invariant targets. Reflectance measurements over Libya 1, 2, and 4 desert sites from both the Aqua and Terra MODIS are regressed to a BRDF model with an adjustable coefficient accounting for the calibration difference between the two instruments. The BRDF coefficients for three desert sites for MODIS bands 1 to 9 are derived and the wavelength dependencies are presented. The analysis and inter-comparison are for MODIS bands 1 to 9 and VIIRS moderate resolution radiometric bands (M bands) M1, M2, M4, M5, M7, M8, M10 and imaging bands (I bands) I1-I3. Results show that the ratios from different sites are in good agreement. The ratios between Terra and Aqua MODIS from year 2003 to 2014 are presented. The inter-comparison between MODIS and VIIRS are analyzed for year 2014.

Spatial and Temporal Distribution of Cloud Properties Observed by MODIS: Preliminary Level-3 Results from the Collection 5 Reprocessing

NASA Technical Reports Server (NTRS)

King, Michael D.; Platnick, Steven; Hubanks, Paul; Pincus, Robert

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 operational algorithms for the retrieval of cloud physical and optical properties (optical thickness, effective particle radius, water path, thermodynamic phase) have recently been updated and are being used in the new "Collection 5" processing stream being produced by the MODIS Adaptive Processing System (MODAPS) at NASA GSFC. All Terra and Aqua data are undergoing Collection 5 reprocessing with an expected completion date by the end of 2006. The archived products from these algorithms include 1 km pixel-level (Level-2) and global gridded Level-3 products. The cloud products have applications in climate change studies, climate modeling, numerical weather prediction, as well as fundamental atmospheric research. In this talk, we will summarize the available Level-3 cloud properties and their associated statistical data sets, and show preliminary Terra and Aqua results from the available Collection 5 reprocessing effort. Anticipated results include the latitudinal distribution of cloud optical and radiative properties for 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.

Possible influences of Asian dust aerosols on cloud properties and radiative forcing observed from MODIS and CERES

NASA Astrophysics Data System (ADS)

Huang, Jianping; Minnis, Patrick; Lin, Bing; Wang, Tianhe; Yi, Yuhong; Hu, Yongxiang; Sun-Mack, Sunny; Ayers, Kirk

2006-03-01

The effects of dust storms on cloud properties and Radiative Forcing (RF) are analyzed over Northwestern China from April 2001 to June 2004 using data collected by the MODerate Resolution Imaging Spectroradiometer (MODIS) and Clouds and the Earth's Radiant Energy System (CERES) instruments on the Aqua and Terra satellites. On average, ice cloud effective particle diameter, optical depth and ice water path of cirrus clouds under dust polluted conditions are 11%, 32.8%, and 42% less, respectively, than those derived from ice clouds in dust-free atmospheric environments. Due to changes in cloud microphysics, the instantaneous net RF is increased from -161.6 W/m2 for dust-free clouds to -118.6 W/m2 for dust-contaminated clouds.

Tornadoes Strike Northern Wisconsin

NASA Technical Reports Server (NTRS)

2007-01-01

A series of tornadoes ripped through the Upper Midwest region of the United States in the evening of June 7, 2007. At least five different tornadoes touched down in Wisconsin, according to the Associated Press, one of which tore through the Bear Paw Resort in northern Wisconsin. Despite dropping as much as fifteen centimeters (six inches) of rain in some places and baseball-size hail in others, authorities were reporting no deaths attributable to the storm system, and only a smattering of injuries, but considerable property damage in some areas. When the MODIS instrument on NASA's Terra satellite observed the area on June 9, 2007, the track torn through the woods by one of the tornadoes stands out quite clearly. This photo-like image uses data collected by MODIS in the normal human vision range to give a familiar natural-looking appearance. The landscape is largely a checkerboard of farms, towns, roads, and cities. The pale land is predominantly farmland where crops have not fully grown in yet. Dark blue shows the winding path of rivers and lakes dotting the landscape. The large blue lake on the east (right) side of the image is Lake Michigan. Towns and cities, including the city of Green Bay, are gray. To the north side, farmland gives way to dark green as land use shifts from agriculture to the Menominee Indian Reservation and Nicolet National Forest. The diagonal slash through the dark green forested land shows the tornado track. Bare land was revealed where the tornado tore down trees or stripped vegetation off the branches. The high-resolution image provided above is at MODIS' full spatial resolution (level of detail) of 250 meters per pixel. The MODIS Rapid Response System provides this image at additional resolutions.

Investigation of the Fire Radiative Energy Biomass Combustion Coefficient: A Comparison of Polar and Geostationary Satellite Retrievals Over the Conterminous United States

NASA Astrophysics Data System (ADS)

Li, Fangjun; Zhang, Xiaoyang; Kondragunta, Shobha; Roy, David P.

2018-02-01

Biomass burning substantially contributes to atmospheric aerosol and greenhouse gas emissions that influence climate and air quality. Fire radiative energy (FRE) (units: MJ) has been demonstrated to be linearly related to biomass consumption (units: kg) with potential for improving biomass burning emission estimation. The scalar constant, termed herein as the FRE biomass combustion coefficient (FBCC) (units: kg/MJ), which converts FRE to biomass consumption, has been estimated using field and laboratory experiments, varying from 0.368 to 0.453 kg/MJ. However, quite different FBCC values, especially for satellite-based approaches, have been reported. This study investigated the FBCC with respect to 445 wildfires that occurred from 2011 to 2012 across the Conterminous United States (CONUS) considering both polar-orbiting and geostationary satellite data. The FBCC was derived by comparing satellite FRE estimates with biomass consumption for the CONUS. FRE was estimated using observations from the Moderate Resolution Imaging Spectroradiometer (MODIS) and the Geostationary Operational Environmental Satellite (GOES); biomass consumption was estimated using Landsat-derived burned areas with fuel loadings from the Fuel Characteristic Classification System and using combustion completeness parameterized by Landsat burn severity and Fuel Characteristic Classification System fuelbed type. The reported results confirm the linearity of the empirical relationship between FRE and biomass consumption for wildfires. The CONUS FBCC was 0.374 kg/MJ for GOES FRE, 0.266 kg/MJ for MODIS FRE, and 0.320 kg/MJ considering both GOES and MODIS FRE. Limited sensitivity analyses, comparing MODIS and GOES FRE with biomass consumption estimated in three different ways, indicated that the FBCC varied from 0.301 to 0.458 kg/MJ.

Multiyear On-orbit Calibration and Performance of Terra MODIS Thermal Emissive Bands

NASA Technical Reports Server (NTRS)

Xiong, Xiaoxiong; Chiang, Kwo-Fu; Wu, Aisheng; Barnes, William; Guenther, Bruce; Salomonson, Vincent

2007-01-01

Since launch in December 1999, Terra MODIS has been making continuous Earth observations for more than seven years. It has produced a broad range of land, ocean, and atmospheric science data products for improvements in studies of global climate and environmental change. Among its 36 spectral bands, there are 20 reflective solar bands (RSB) and 16 thermal emissive bands (TEB). MODIS thermal emissive bands cover the mid-wave infrared (MWIR) and long-wave infrared (LWIR) spectral regions with wavelengths from 3.7 to 14.4pm. They are calibrated on-orbit using an on-board blackbody (BB) with its temperature measured by a set of thermistors on a scan-by-scan basis. This paper will provide a brief overview of MODIS TEB calibration and characterization methodologies and illustrate on-board BB functions and TEB performance over more than seven years of on-orbit operation and calibration. Discussions will be focused on TEB detector short-term stability and noise characterization, and changes in long-term response (or system gain). Results show that Terra MODIS BB operation has been extremely stable since launch. When operated at its nominal controlled temperature of 290K, the BB temperature variation is typically less than +0.30mK on a scan-by-scan basis and there has been no time-dependent temperature drift. In addition to excellent short-term stability, most TEB detectors continue to meet or exceed their specified noise characterization requirements, thus enabling calibration accuracy and science data product quality to be maintained. Excluding the noisy detectors identified pre-launch and those that occurred post-launch, the changes in TEB responses have been less than 0.7% on an annual basis. The optical leak corrections applied to bands 32-36 have been effective and stable over the entire mission

Towards 250 m mapping of terrestrial primary productivity over Canada

NASA Astrophysics Data System (ADS)

Gonsamo, A.; Chen, J. M.

2011-12-01

Terrestrial ecosystems are an important part of the climate and global change systems. Their role in climate change and in the global carbon cycle is yet to be well understood. Dataset from satellite earth observation, coupled with numerical models provide the unique tools for monitoring the spatial and temporal dynamics of territorial carbon cycle. The Boreal Ecosystems Productivity Simulator (BEPS) is a remote sensing based approach to quantifying the terrestrial carbon cycle by that gross and net primary productivity (GPP and NPP) and terrestrial carbon sinks and sources expressed as net ecosystem productivity (NEP). We have currently implemented a scheme to map the GPP, NPP and NEP at 250 m for first time over Canada using BEPS model. This is supplemented by improved mapping of land cover and leaf area index (LAI) at 250 m over Canada from MODIS satellite dataset. The results from BEPS are compared with MODIS GPP product and further evaluated with estimated LAI from various sources to evaluate if the results capture the trend in amount of photosynthetic biomass distributions. Final evaluation will be to validate both BEPS and MODIS primary productivity estimates over the Fluxnet sites over Canada. The primary evaluation indicate that BEPS GPP estimates capture the over storey LAI variations over Canada very well compared to MODIS GPP estimates. There is a large offset of MODIS GPP, over-estimating the lower GPP value compared to BEPS GPP estimates. These variations will further be validated based on the measured values from the Fluxnet tower measurements over Canadian. The high resolution GPP (NPP) products at 250 m will further be used to scale the outputs between different ecosystem productivity models, in our case the Canadian carbon budget model of Canadian forest sector CBM-CFS) and the Integrated Terrestrial Ecosystem Carbon model (InTEC).

An Operational Assessment of the MODIS False Color Composite with the Great Falls, Montana National Weather Service

NASA Technical Reports Server (NTRS)

Loss, GIna; Mercer, Michael; Fuell, Kevin K.; Stano, Geoffrey T.

2009-01-01

The close and productive collaborations between the NWS Warning and Forecast Office (WFO) in Great Falls, MT and the Short Term Prediction and Research Transition (SPORT) Center at NASA/Marshall Space Flight Center have provided a unique opportunity for science sharing and technology transfer. In particular, SPoRT has provided a false color composite product derived from MODIS data, which is part of NASA's Earth Observing System. This product is designed to delineate snow and ice covered ground, bare ground and clouds. The Great Falls WFO has been a test bed of the MODIS false color composite as a tool in operations to monitor the development and dissipation of snow cover In particular, preliminary applications have shown that the product can be used to monitor snow cover in remote locations as well as ice in rivers. This information can lead to improved assessments of flooding potential during post event conditions where rapid melting and runoff are anticipated. The potential of this product on future geostationary satellites may substantially contribute to the NWS mission by providing enhanced situational awareness. The operational use of this product has been transitioned at WFO Great Falls through a process of product implementation, discussions with the service hydrologist and forecasters, and post event analysis. A concentrated assessment period from January to March, 2008 was initiated to investigate the impact of the MODIS false color product on WFO Great Falls' operations. This presentation will emphasize the impact the MODIS false color product had in the WFO's situational awareness and how best this information can be used to influence operational decisions.

Creating a consistent dark-target aerosol optical depth record from MODIS and VIIRS

NASA Astrophysics Data System (ADS)

Levy, R. C.; Mattoo, S.; Munchak, L. A.; Patadia, F.; Holz, R.

2014-12-01

To answer fundamental questions about our changing climate, we must quantify how aerosols are changing over time. This is a global question that requires regional characterization, because in some places aerosols are increasing and in others they are decreasing. Although NASA's Moderate resolution Imaging Spectrometer (MODIS) sensors have provided quantitative information about global aerosol optical depth (AOD) for more than a decade, the creation of an aerosol climate data record (CDR) requires consistent multi-decadal data. With the Visible and Infrared Imaging Radiometer Suite (VIIRS) aboard Suomi-NPP, there is potential to continue the MODIS aerosol time series. Yet, since the operational VIIRS aerosol product is produced by a different algorithm, it is not suitable to continue MODIS to create an aerosol CDR. Therefore, we have applied the MODIS Dark-target (DT) algorithm to VIIRS observations, taking into account the slight differences in wavelengths, resolutions and geometries between the two sensors. More specifically, we applied the MODIS DT algorithm to a dataset known as the Intermediate File Format (IFF), created by the University of Wisconsin. The IFF is produced for both MODIS and VIIRS, with the idea that a single (MODIS-like or ML) algorithm can be run either dataset, which can in turn be compared to the MODIS Collection 6 (M6) retrieval that is run on standard MODIS data. After minimizing or characterizing remaining differences between ML on MODIS-IFF (or ML-M) and M6, we have performed apples-to-apples comparison between ML-M and ML on VIIRS IFF (ML-V). Examples of these comparisons include time series of monthly global mean, monthly and seasonal global maps at 1° resolution, and collocations as compared to AERONET. We concentrate on the overlapping period January 2012 through June 2014, and discuss some of the remaining discrepancies between the ML-V and ML-M datasets.

Longwave Radiative Forcing of Saharan Dust Aerosols Estimated from MODIS, MISR and CERES Observations on Terra

NASA Technical Reports Server (NTRS)

Zhang, Jiang-Long; Christopher, Sundar A.

2003-01-01

Using observations from the Multi-angle Imaging Spectroradiometer (MISR), the Moderate Resolution Imaging Spectroradiometer (MODIS), and the Clouds and the Earth's Radiant Energy System (CERES) instruments onboard the Terra satellite; we present a new technique for studying longwave (LW) radiative forcing of dust aerosols over the Saharan desert for cloud-free conditions. The monthly-mean LW forcing for September 2000 is 7 W/sq m and the LW forcing efficiency' (LW(sub eff)) is 15 W/sq m. Using radiative transfer calculations, we also show that the vertical distribution of aerosols and water vapor are critical to the understanding of dust aerosol forcing. Using well calibrated, spatially and temporally collocated data sets, we have combined the strengths of three sensors from the same satellite to quantify the LW radiative forcing, and show that dust aerosols have a "warming" effect over the Saharan desert that will counteract the shortwave "cooling effect" of aerosols.

Detection of single and multilayer clouds in an artificial neural network approach

NASA Astrophysics Data System (ADS)

Sun-Mack, Sunny; Minnis, Patrick; Smith, William L.; Hong, Gang; Chen, Yan

2017-10-01

Determining whether a scene observed with a satellite imager is composed of a thin cirrus over a water cloud or thick cirrus contiguous with underlying layers of ice and water clouds is often difficult because of similarities in the observed radiance values. In this paper an artificial neural network (ANN) algorithm, employing several Aqua MODIS infrared channels and the retrieved total cloud visible optical depth, is trained to detect multilayer ice-over-water cloud systems as identified by matched April 2009 CloudSat and CALIPSO (CC) data. The CC lidar and radar profiles provide the vertical structure that serves as output truth for a multilayer ANN, or MLANN, algorithm. Applying the trained MLANN to independent July 2008 MODIS data resulted in a combined ML and single layer hit rate of 75% (72%) for nonpolar regions during the day (night). The results are comparable to or more accurate than currently available methods. Areas of improvement are identified and will be addressed in future versions of the MLANN.

Transitions of cloud-topped marine boundary layers characterized by AIRS, MODIS, and a large eddy simulation model

DOE Office of Scientific and Technical Information (OSTI.GOV)

Yue, Qing; Kahn, Brian; Xiao, Heng

2013-08-16

Cloud top entrainment instability (CTEI) is a hypothesized positive feedback between entrainment mixing and evaporative cooling near the cloud top. Previous theoretical and numerical modeling studies have shown that the persistence or breakup of marine boundary layer (MBL) clouds may be sensitive to the CTEI parameter. Collocated thermodynamic profile and cloud observations obtained from the Atmospheric Infrared Sounder (AIRS) and Moderate Resolution Imaging Spectroradiometer (MODIS) instruments are used to quantify the relationship between the CTEI parameter and the cloud-topped MBL transition from stratocumulus to trade cumulus in the northeastern Pacific Ocean. Results derived from AIRS and MODIS are compared withmore » numerical results from the UCLA large eddy simulation (LES) model for both well-mixed and decoupled MBLs. The satellite and model results both demonstrate a clear correlation between the CTEI parameter and MBL cloud fraction. Despite fundamental differences between LES steady state results and the instantaneous snapshot type of observations from satellites, significant correlations for both the instantaneous pixel-scale observations and the long-term averaged spatial patterns between the CTEI parameter and MBL cloud fraction are found from the satellite observations and are consistent with LES results. This suggests the potential of using AIRS and MODIS to quantify global and temporal characteristics of the cloud-topped MBL transition.« less

Observation of Mountain Lee Waves with MODIS NIR Column Water Vapor

NASA Technical Reports Server (NTRS)

Lyapustin, A.; Alexander, M. J.; Ott, L.; Molod, A.; Holben, B.; Susskind, J.; Wang, Y.

2014-01-01

Mountain lee waves have been previously observed in data from the Moderate Resolution Imaging Spectroradiometer (MODIS) "water vapor" 6.7 micrometers channel which has a typical peak sensitivity at 550 hPa in the free troposphere. This paper reports the first observation of mountain waves generated by the Appalachian Mountains in the MODIS total column water vapor (CWV) product derived from near-infrared (NIR) (0.94 micrometers) measurements, which indicate perturbations very close to the surface. The CWV waves are usually observed during spring and late fall or some summer days with low to moderate CWV (below is approx. 2 cm). The observed lee waves display wavelengths from3-4 to 15kmwith an amplitude of variation often comparable to is approx. 50-70% of the total CWV. Since the bulk of atmospheric water vapor is confined to the boundary layer, this indicates that the impact of thesewaves extends deep into the boundary layer, and these may be the lowest level signatures of mountain lee waves presently detected by remote sensing over the land.

MODIS In-flight Calibration Methodologies

NASA Technical Reports Server (NTRS)

Xiong, X.; Barnes, W.

2004-01-01

MODIS is a key instrument for the NASA's Earth Observing System (EOS) currently operating on the Terra spacecraft launched in December 1999 and Aqua 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 reflective 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 MODIS 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.

A single dose of dapagliflozin, an SGLT-2 inhibitor, induces higher glycosuria in GCK- and HNF1A-MODY than in type 2 diabetes mellitus.

PubMed

Hohendorff, J; Szopa, M; Skupien, J; Kapusta, M; Zapala, B; Platek, T; Mrozinska, S; Parpan, T; Glodzik, W; Ludwig-Galezowska, A; Kiec-Wilk, B; Klupa, T; Malecki, M T

2017-08-01

SGLT2 inhibitors are a new class of oral hypoglycemic agents used in type 2 diabetes (T2DM). Their effectiveness in maturity onset diabetes of the young (MODY) is unknown. We aimed to assess the response to a single dose of 10 mg dapagliflozin in patients with Hepatocyte Nuclear Factor 1 Alpha (HNF1A)-MODY, Glucokinase (GCK)-MODY, and type 2 diabetes. We examined 14 HNF1A-MODY, 19 GCK-MODY, and 12 type 2 diabetes patients. All studied individuals received a single morning dose of 10 mg of dapagliflozin added to their current therapy of diabetes. To assess the response to dapagliflozin we analyzed change in urinary glucose to creatinine ratio and serum 1,5-Anhydroglucitol (1,5-AG) level. There were only four patients with positive urine glucose before dapagliflozin administration (one with HNF1A-MODY, two with GCK-MODY, and one with T2DM), whereas after SGLT-2 inhibitor use, glycosuria occurred in all studied participants. Considerable changes in mean glucose to creatinine ratio after dapagliflozin administration were observed in all three groups (20.51 ± 12.08, 23.19 ± 8.10, and 9.84 ± 6.68 mmol/mmol for HNF1A-MODY, GCK-MODY, and T2DM, respectively, p < 0.001 for all comparisons). Post-hoc analysis revealed significant differences in mean glucose to creatinine ratio change between type 2 diabetes and each monogenic diabetes in response to dapagliflozin (p = 0.02, p = 0.003 for HNF1-A and GCK MODY, respectively), but not between the two MODY forms (p = 0.7231). Significant change in serum 1,5-AG was noticed only in T2DM and it was -6.57 ± 7.34 mg/ml (p = 0.04). A single dose of dapagliflozin, an SGLT-2 inhibitor, induces higher glycosuria in GCK- and HNF1A-MODY than in T2DM. Whether flozins are a valid therapeutic option in these forms of MODY requires long-term clinical studies.

SatCam: A mobile application for coordinated ground/satellite observation of clouds and validation of satellite-derived cloud mask products.

NASA Astrophysics Data System (ADS)

Gumley, L.; Parker, D.; Flynn, B.; Holz, R.; Marais, W.

2011-12-01

SatCam is an application for iOS devices that allows users to collect observations of local cloud and surface conditions in coordination with an overpass of the Terra, Aqua, or NPP satellites. SatCam allows users to acquire images of sky conditions and ground conditions at their location anywhere in the world using the built-in iPhone or iPod Touch camera at the same time that the satellite is passing overhead and viewing their location. Immediately after the sky and ground observations are acquired, the application asks the user to rate the level of cloudiness in the sky (Completely Clear, Mostly Clear, Partly Cloudy, Overcast). For the ground observation, the user selects their assessment of the surface conditions (Urban, Green Vegetation, Brown Vegetation, Desert, Snow, Water). The sky condition and surface condition selections are stored along with the date, time, and geographic location for the images, and the images are uploaded to a central server. When the MODIS (Terra and Aqua) or VIIRS (NPP) imagery acquired over the user location becomes available, a MODIS or VIIRS true color image centered at the user's location is delivered back to the SatCam application on the user's iOS device. SSEC also proposes to develop a community driven SatCam website where users can share their observations and assessments of satellite cloud products in a collaborative environment. SSEC is developing a server side data analysis system to ingest the SatCam user observations, apply quality control, analyze the sky images for cloud cover, and collocate the observations with MODIS and VIIRS satellite products (e.g., cloud mask). For each observation that is collocated with a satellite observation, the server will determine whether the user scored a "hit", meaning their sky observation and sky assessment matched the automated cloud mask obtained from the satellite observation. The hit rate will be an objective assessment of the accuracy of the user's sky observations. Users with high hit rates will be identified automatically and their observations will be used globally to evaluate the performance of the MODIS cloud mask algorithm for Terra and Aqua and the VIIRS cloud mask algorithm for NPP. The user's assessment of the ground conditions will also be used to evaluate the cloud mask accuracy in selecting the correct surface type at the user's location, which is an important element in the decision path used internally by the cloud mask algorithm. This presentation will describe the SatCam application, how it is used, and show examples of SatCam observations.

Monitoring 2009 Forest Disturbance across the Conterminous United States, Based on Near-Real Time and Historical MODIS 250 Meter NDVI Products

NASA Astrophysics Data System (ADS)

Spruce, J.; Hargrove, W. W.; Gasser, G.; Smoot, J. C.; Kuper, P.

2009-12-01

This presentation discusses a study on the use of MODIS NDVI data for viewing regional patterns of forest disturbance across the conterminous United States. This capability is a part of a national forest threat early warning system (EWS) being developed by the USDA Forest Service’s Eastern and Western Environmental Threat Centers with help from NASA Stennis Space Center and the Oak Ridge National Laboratory. The viewing capability of the EWS was recently demonstrated for 2009, using near-real time (NRT) MODIS NDVI data from the USGS eMODIS Web site and historical NDVI data from standard MOD13 products. For this study, a historical maximum NDVI baseline for CONUS was computed from fused Aqua and Terra MOD13 data for June 10-July 27 of each year during 2000-2006. Comparable 2009 MODIS NDVI imagery was computed from fusion and re-compositing of eMODIS NRT Aqua and Terra 7-day products. For the historical data, time series data processing software was used to remove poor quality data and to mitigate data gaps mainly due to clouds. Although the NRT component was not as rigorously processed to mitigate noise, the processing still yielded largely cloud-free clean, coherent CONUS NDVI imagery initially with only 21-days of compositing. The principal end product of the study was a forest disturbance visualization product based on an NDVI RGB image that combines data from 2 dates (i.e. time frames). For this RGB, the historical maximum NDVI for the observed temporal window was assigned to the red color gun and the 2009 NRT product for the same time frame was assigned to the blue and green guns. The resulting image was masked with a USFS FIA 250-m type map to include only forested areas. The forest disturbance areas on the forest-masked 2-date NDVI RGB are shown in red tones with non-disturbed closed canopy forest generally shown in medium to bright gray tones. This product highlighted several broad-scaled forest canopy disturbances for the observed time in 2009, including damage from caterpillars, bark beetles, ice storms, hail and wind storms, and wildfire. The MODIS forest disturbance products compared well with reference data (e.g., Landsat, aerial sketch maps, and news accounts). These products have been useful in aiding development of the forest threat EWS. Information on location and extent of regional forest disturbance is important to Federal, State, and private sector forest managers. The 2-date RGB product for 2009 was also processed into a classification of forest disturbance for the Colorado Front Range. Validation of this classification is underway. Regional forest disturbance classifications in conjunction with available CONUS forest biomass products could be useful for assessing carbon impacts from biotic threats such as mountain pine beetle and from abiotic threats related to climate change. The latency of the NRT eMODIS products addresses an important need of the USFS EWS.

FLUXNET to MODIS: Connecting the dots to capture heterogenious biosphere metabolism

NASA Astrophysics Data System (ADS)

Woods, K. D.; Schwalm, C.; Huntzinger, D. N.; Massey, R.; Poulter, B.; Kolb, T.

2015-12-01

Eddy co-variance flux towers provide our most widely distributed network of direct observations for land-atmosphere carbon exchange. Carbon flux sensitivity analysis is a method that uses in situ networks to understand how ecosystems respond to changes in climatic variables. Flux towers concurrently observe key ecosystem metabolic processes (e..g. gross primary productivity) and micrometeorological variation, but only over small footprints. Remotely sensed vegetation indices from MODIS offer continuous observations of the vegetated land surface, but are less direct, as they are based on light use efficiency algorithms, and not on the ground observations. The marriage of these two data products offers an opportunity to validate remotely sensed indices with in situ observations and translate information derived from tower sites to globally gridded products. Here we provide correlations between Enhanced Vegetation Index (EVI), Leaf Area Index (LAI) and MODIS gross primary production with FLUXNET derived estimates of gross primary production, respiration and net ecosystem exchange. We demonstrate remotely sensed vegetation products which have been transformed to gridded estimates of terrestrial biosphere metabolism on a regional-to-global scale. We demonstrate anomalies in gross primary production, respiration, and net ecosystem exchange as predicted by both MODIS-carbon flux sensitivities and meteorological driver-carbon flux sensitivities. We apply these sensitivities to recent extreme climatic events and demonstrate both our ability to capture changes in biosphere metabolism, and differences in the calculation of carbon flux anomalies based on method. The quantification of co-variation in these two methods of observation is important as it informs both how remotely sensed vegetation indices are correlated with on the ground tower observations, and with what certainty we can expand these observations and relationships.

Verification of NWP Cloud Properties using A-Train Satellite Observations

NASA Astrophysics Data System (ADS)

Kucera, P. A.; Weeks, C.; Wolff, C.; Bullock, R.; Brown, B.

2011-12-01

Recently, the NCAR Model Evaluation Tools (MET) has been enhanced to incorporate satellite observations for the verification of Numerical Weather Prediction (NWP) cloud products. We have developed tools that match fields spatially (both in the vertical and horizontal dimensions) to compare NWP products with satellite observations. These matched fields provide diagnostic evaluation of cloud macro attributes such as vertical distribution of clouds, cloud top height, and the spatial and seasonal distribution of cloud fields. For this research study, we have focused on using CloudSat, CALIPSO, and MODIS observations to evaluate cloud fields for a variety of NWP fields and derived products. We have selected cases ranging from large, mid-latitude synoptic systems to well-organized tropical cyclones. For each case, we matched the observed cloud field with gridded model and/or derived product fields. CloudSat and CALIPSO observations and model fields were matched and compared in the vertical along the orbit track. MODIS data and model fields were matched and compared in the horizontal. We then use MET to compute the verification statistics to quantify the performance of the models in representing the cloud fields. In this presentation we will give a summary of our comparison and show verification results for both synoptic and tropical cyclone cases.

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.

The SeaDAS Processing and Analysis System: SeaWiFS, MODIS, and Beyond

NASA Astrophysics Data System (ADS)

MacDonald, M. D.; Ruebens, M.; Wang, L.; Franz, B. A.

2005-12-01

The SeaWiFS Data Analysis System (SeaDAS) is a comprehensive software package for the processing, display, and analysis of ocean data from a variety of satellite sensors. Continuous development and user support by programmers and scientists for more than a decade has helped to make SeaDAS the most widely used software package in the world for ocean color applications, with a growing base of users from the land and sea surface temperature community. Full processing support for past (CZCS, OCTS, MOS) and present (SeaWiFS, MODIS) sensors, and anticipated support for future missions such as NPP/VIIRS, enables end users to reproduce the standard ocean archive product suite distributed by NASA's Ocean Biology Processing Group (OBPG), as well as a variety of evaluation and intermediate ocean, land, and atmospheric products. Availability of the processing algorithm source codes and a software build environment also provide users with the tools to implement custom algorithms. Recent SeaDAS enhancements include synchronization of MODIS processing with the latest code and calibration updates from the MODIS Calibration Support Team (MCST), support for all levels of MODIS processing including Direct Broadcast, a port to the Macintosh OS X operating system, release of the display/analysis-only SeaDAS-Lite, and an extremely active web-based user support forum.

Global Validation of MODIS Atmospheric Profile-Derived Near-Surface Air Temperature and Dew Point Estimates

NASA Astrophysics Data System (ADS)

Famiglietti, C.; Fisher, J.; Halverson, G. H.

2017-12-01

This study validates a method of remote sensing near-surface meteorology that vertically interpolates MODIS atmospheric profiles to surface pressure level. The extraction of air temperature and dew point observations at a two-meter reference height from 2001 to 2014 yields global moderate- to fine-resolution near-surface temperature distributions that are compared to geographically and temporally corresponding measurements from 114 ground meteorological stations distributed worldwide. This analysis is the first robust, large-scale validation of the MODIS-derived near-surface air temperature and dew point estimates, both of which serve as key inputs in models of energy, water, and carbon exchange between the land surface and the atmosphere. Results show strong linear correlations between remotely sensed and in-situ near-surface air temperature measurements (R2 = 0.89), as well as between dew point observations (R2 = 0.77). Performance is relatively uniform across climate zones. The extension of mean climate-wise percent errors to the entire remote sensing dataset allows for the determination of MODIS air temperature and dew point uncertainties on a global scale.

Contribution of National near Real Time MODIS Forest Maximum Percentage NDVI Change Products to the U.S. ForWarn System

NASA Technical Reports Server (NTRS)

Spruce, Joseph P.; Hargrove, William; Gasser, Gerald; Smoot, James; Kuper, Philip D.

2012-01-01

This presentation reviews the development, integration, and testing of Near Real Time (NRT) MODIS forest % maximum NDVI change products resident to the USDA Forest Service (USFS) ForWarn System. ForWarn is an Early Warning System (EWS) tool for detection and tracking of regionally evident forest change, which includes the U.S. Forest Change Assessment Viewer (FCAV) (a publically available on-line geospatial data viewer for visualizing and assessing the context of this apparent forest change). NASA Stennis Space Center (SSC) is working collaboratively with the USFS, ORNL, and USGS to contribute MODIS forest change products to ForWarn. These change products compare current NDVI derived from expedited eMODIS data, to historical NDVI products derived from MODIS MOD13 data. A new suite of forest change products are computed every 8 days and posted to the ForWarn system; this includes three different forest change products computed using three different historical baselines: 1) previous year; 2) previous three years; and 3) all previous years in the MODIS record going back to 2000. The change product inputs are maximum value NDVI that are composited across a 24 day interval and refreshed every 8 days so that resulting images for the conterminous U.S. are predominantly cloud-free yet still retain temporally relevant fresh information on changes in forest canopy greenness. These forest change products are computed at the native nominal resolution of the input reflectance bands at 231.66 meters, which equates to approx 5.4 hectares or 13.3 acres per pixel. The Time Series Product Tool, a MATLAB-based software package developed at NASA SSC, is used to temporally process, fuse, reduce noise, interpolate data voids, and re-aggregate the historical NDVI into 24 day composites, and then custom MATLAB scripts are used to temporally process the eMODIS NDVIs so that they are in synch with the historical NDVI products. Prior to posting, an in-house snow mask classification product is computed for the current compositing period and integrated into the change images to account for snow related NDVI drops. The supplemental snow classification product was needed because other available QA cloud/snow mask typically underestimates snow cover. MODIS true and false color composites were also computed from eMODIS reflectance data and the true color RGBs are also posted on ForWarn?s FCAV; this data is used for assessing apparent occasional quality issues on the change products due to residual unmasked cloud cover. New forest change products are posted with typical latencies of 1-2 days after the last input eMODIS data collection date for a given 24 day compositing period.

TERRA/MODIS Data Products and Data Management at the GES-DAAC

NASA Astrophysics Data System (ADS)

Sharma, A. K.; Ahmad, S.; Eaton, P.; Koziana, J.; Leptoukh, G.; Ouzounov, D.; Savtchenko, A.; Serafino, G.; Sikder, M.; Zhou, B.

2001-05-01

Since February 2000, the Earth Sciences Distributed Active Archive Center (GES-DAAC) at the NASA/Goddard Space Flight Center has been successfully ingesting, processing, archiving, and distributing the Moderate Resolution Imaging Spectroradiometer (MODIS) data. MODIS is the key instrument aboard the Terra satellite, viewing the entire Earth's surface every 1 to 2 days, acquiring data in 36 channels in the visible and infrared spectral bands (0.4 to 14.4 microns). Higher resolution (250m, 500m, and 1km pixel) data are improving our understanding of global dynamics and processes occurring on the land, in the oceans, and in the lower atmosphere and will play a vital role in the future development of validated, global, interactive Earth-system models. MODIS calibrated and uncalibrated radiances, and geolocation products were released to the public in April 2000, and a suite of oceans products and an entire suite of atmospheric products were released by early January 2001. The suite of ocean products is grouped into three categories Ocean Color, SST and Primary Productivity. The suite of atmospheric products includes Aerosol, Total Precipitable Water, Cloud Optical and Physical properties, Atmospheric Profiles and Cloud Mask. The MODIS Data Support Team (MDST) at the GES-DAAC has been providing support for enabling basic scientific research and assistance in accessing the scientific data and information to the Earth Science User Community. Support is also provided for data formats (HDF-EOS), information on visualization tools, documentation for data products, information on the scientific content of products and metadata. Visit the MDST website at http://daac.gsfc.nasa.gov/CAMPAIGN_DOCS/MODIS/index.html The task to process archive and distribute enormous volumes of MODIS data to users (more than 0.5 TB a day) has led to the development of an unique world wide web based GES DAAC Search and Order system http://acdisx.gsfc.nasa.gov/data/, data handling software and tools, as well as a FTP site that contains sample of browse images and MODIS data products. This paper is intended to inform the user community about the data system and services available at the GES-DAAC in support of these information-rich data products. MDST provides support to MODIS data users to access and process data and information for research, applications and educational purposes. This paper will present an overview of the MODIS data products released to public including the suite of atmosphere and oceans data products that can be ordered from the GES-DAAC. Different mechanisms for search and ordering the data, determining data product sizes, data distribution policy, User Assistance System (UAS), and data subscription services will be described.

MODIS Near real-time (NRT) data for fire applications

NASA Astrophysics Data System (ADS)

Wong, M.; Davies, D.; Ilavajhala, S.; Molinario, G.; Justice, C.; Latham, J.; Martucci, A.; Murphy, K. J.

2011-12-01

This paper describes the lessons learned from the development of the Fire Information for Resource Management System (FIRMS) prototype and its transition to an operational system, the Global Fire Information Management System (GFIMS), at the United Nations Food and Agriculture Organization (FAO) in August 2010. These systems provide active fire data from the MODIS sensor, on board NASA's Terra and Aqua Earth Observing Satellites, to users at no cost, in near-real time and in easy-to-use formats. The FIRMS prototype evolved from simply providing daily active fire text files via FTP, to include services such as providing fire data in various data formats, an interactive WebGIS allowing users to view and query the data and an email alert service enabling users to receive emails of near real-time fire data of their chosen area of interest. FIRMS was designed to remove obstacles to the uptake and use of fire data by addressing issues often associated with satellite data: cost, timeliness of delivery, limited data formats and the need for technical expertise to process and analyze the data. We also illustrate how the MODIS active fire data are routinely used for firefighting and conservation monitoring. We present results from a user survey, completed by approximately 345 people from 65 countries, and provide case studies highlighting how the provision of MODIS active fire data have made an impact on conservation and firefighting, especially in remote areas where it is difficult to have on-the-ground surveillance. We highlight the gaps in current capabilities, both with users and the data. A major obstacle still for some users is having low or no internet connectivity and a possible solution is through the use of cell phone technologies such as SMS text messaging of fire locations and information. GFIMS, and its precursor, FIRMS, were developed by the University of Maryland with funding from NASA's Applied Sciences Program. With GFIMS established at FAO as an operational system, FIRMS will become part of NASA's Land Atmosphere Near-real-time Capability for EOS (LANCE), to continue to meet NASA data-user needs.

A cross comparison of spatiotemporally enhanced springtime phenological measurements from satellites and ground in a northern U.S. mixed forest

USGS Publications Warehouse

Liang, Liang; Schwartz, Mark D.; Zhuosen Wang,; Gao, Feng; Schaaf, Crystal B.; Bin Tan,; Morisette, Jeffrey T.; Zhang, Xiaoyang

2014-01-01

Cross comparison of satellite-derived land surface phenology (LSP) and ground measurements is useful to ensure the relevance of detected seasonal vegetation change to the underlying biophysical processes. While standard 16-day and 250-m Moderate Resolution Imaging Spectroradiometer (MODIS) vegetation index (VI)-based springtime LSP has been evaluated in previous studies, it remains unclear whether LSP with enhanced temporal and spatial resolutions can capture additional details of ground phenology. In this paper, we compared LSP derived from 500-m daily MODIS and 30-m MODIS-Landsat fused VI data with landscape phenology (LP) in a northern U.S. mixed forest. LP was previously developed from intensively observed deciduous and coniferous tree phenology using an upscaling approach. Results showed that daily MODIS-based LSP consistently estimated greenup onset dates at the study area (625 m × 625 m) level with 4.48 days of mean absolute error (MAE), slightly better than that of using 16-day standard VI (4.63 days MAE). For the observed study areas, the time series with increased number of observations confirmed that post-bud burst deciduous tree phenology contributes the most to vegetation reflectance change. Moreover, fused VI time series demonstrated closer correspondences with LP at the community level (0.1-20 ha) than using MODIS alone at the study area level (390 ha). The fused LSP captured greenup onset dates for respective forest communities of varied sizes and compositions with four days of the overall MAE. This study supports further use of spatiotemporally enhanced LSP for more precise phenological monitoring.

Comparison of MODIS-derived land surface temperature with air temperature measurements

NASA Astrophysics Data System (ADS)

Georgiou, Andreas; Akçit, Nuhcan

2017-09-01

Air surface temperature is an important parameter for a wide range of applications such as agriculture, hydrology and climate change studies. Air temperature data is usually obtained from measurements made in meteorological stations, providing only limited information about spatial patterns over wide areas. The use of remote sensing data can help overcome this problem, particularly in areas with low station density, having the potential to improve the estimation of air surface temperature at both regional and global scales. Land Surface (skin) Temperatures (LST) derived from Moderate Resolution Imaging Spectroradiometer (MODIS) sensor aboard the Terra and Aqua satellite platforms provide spatial estimates of near-surface temperature values. In this study, LST values from MODIS are compared to groundbased near surface air (Tair) measurements obtained from 14 observational stations during 2011 to 2015, covering coastal, mountainous and urban areas over Cyprus. Combining Terra and Aqua LST-8 Day and Night acquisitions into a mean monthly value, provide a large number of LST observations and a better overall agreement with Tair. Comparison between mean monthly LSTs and mean monthly Tair for all sites and all seasons pooled together yields a very high correlation and biases. In addition, the presented high standard deviation can be explained by the influence of surface heterogeneity within MODIS 1km2 grid cells, the presence of undetected clouds and the inherent difference between LST and Tair. However, MODIS LST data proved to be a reliable proxy for surface temperature and mostly for studies requiring temperature reconstruction in areas with lack of observational stations.

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 MODIS c005 algorithm. The discrepancy between SAERand AERONET AOT is, however, substantially larger for the wavelength 488 nm, which means that several of the AOT values are without the MODIS expected uncertainty range. Both algorithms are unable to estimate Ångström exponent accurately, although the MODIS c005 algorithm performs a better job. Based on the inter-comparison of the SAER and MODIS c005 algorithms it was found here that the former estimation of AOT is for values up to 1on the whole within the expected uncertainties for one standard deviation of the MODIS retrievals, considering both Aqua and Terra and periods 1 and 3. The latter also occurs for Aqua and period 2, while then for AOT values lower than 0.5. The present algorithms were, beside aerosols emitted from clean sources and continental sources in Europe, also applied with favor on aerosol particles transported from agricultural fires in Russia and Ukraine. The latter events were associated with high aerosol loadings, although probably with similar single scattering albedo as the days classified as clean. We also present observations performed with space borne and ground-based lidars in the area investigated. From the latter platforms the vertical distribution of aerosol extinction in the atmosphere can be measured. This study suggests that the present satellite retrievals of AOT, particularly obtained with the MODIS c005 algorithm, will, in combination with the lidar measurements, be very useful in validation of regional and climate models over Europe.

Multi-Spectral Cloud Retrievals from Moderate Image Spectrometer (MODIS)

NASA Technical Reports Server (NTRS)

Platnick, Steven

2004-01-01

MODIS observations from the NASA EOS Terra spacecraft (1030 local time equatorial sun-synchronous crossing) launched in December 1999 have provided a unique set of Earth observation data. With the launch of the NASA EOS Aqua spacecraft (1330 local time crossing! in May 2002: two MODIS daytime (sunlit) and nighttime observations are now available in a 24-hour period allowing some measure of diurnal variability. 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 modeling, climate change studies, 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. An overview of the instrument and cloud algorithms will be presented along with various examples, including an initial analysis of several operational global gridded (Level-3) cloud products from the two platforms. Statistics of cloud optical and microphysical properties as a function of latitude for land and Ocean regions will be shown. Current algorithm research efforts will also be discussed.

Cloud property datasets retrieved from AVHRR, MODIS, AATSR and MERIS in the framework of the Cloud_cci project

NASA Astrophysics Data System (ADS)

Stengel, Martin; Stapelberg, Stefan; Sus, Oliver; Schlundt, Cornelia; Poulsen, Caroline; Thomas, Gareth; Christensen, Matthew; Carbajal Henken, Cintia; Preusker, Rene; Fischer, Jürgen; Devasthale, Abhay; Willén, Ulrika; Karlsson, Karl-Göran; McGarragh, Gregory R.; Proud, Simon; Povey, Adam C.; Grainger, Roy G.; Fokke Meirink, Jan; Feofilov, Artem; Bennartz, Ralf; Bojanowski, Jedrzej S.; Hollmann, Rainer

2017-11-01

New cloud property datasets based on measurements from the passive imaging satellite sensors AVHRR, MODIS, ATSR2, AATSR and MERIS are presented. Two retrieval systems were developed that include components for cloud detection and cloud typing followed by cloud property retrievals based on the optimal estimation (OE) technique. The OE-based retrievals are applied to simultaneously retrieve cloud-top pressure, cloud particle effective radius and cloud optical thickness using measurements at visible, near-infrared and thermal infrared wavelengths, which ensures spectral consistency. The retrieved cloud properties are further processed to derive cloud-top height, cloud-top temperature, cloud liquid water path, cloud ice water path and spectral cloud albedo. The Cloud_cci products are pixel-based retrievals, daily composites of those on a global equal-angle latitude-longitude grid, and monthly cloud properties such as averages, standard deviations and histograms, also on a global grid. All products include rigorous propagation of the retrieval and sampling uncertainties. Grouping the orbital properties of the sensor families, six datasets have been defined, which are named AVHRR-AM, AVHRR-PM, MODIS-Terra, MODIS-Aqua, ATSR2-AATSR and MERIS+AATSR, each comprising a specific subset of all available sensors. The individual characteristics of the datasets are presented together with a summary of the retrieval systems and measurement records on which the dataset generation were based. Example validation results are given, based on comparisons to well-established reference observations, which demonstrate the good quality of the data. In particular the ensured spectral consistency and the rigorous uncertainty propagation through all processing levels can be considered as new features of the Cloud_cci datasets compared to existing datasets. In addition, the consistency among the individual datasets allows for a potential combination of them as well as facilitates studies on the impact of temporal sampling and spatial resolution on cloud climatologies.

For each dataset a digital object identifier has been issued:

Cloud_cci AVHRR-AM: https://doi.org/10.5676/DWD/ESA_Cloud_cci/AVHRR-AM/V002

Cloud_cci AVHRR-PM: https://doi.org/10.5676/DWD/ESA_Cloud_cci/AVHRR-PM/V002

Cloud_cci MODIS-Terra: https://doi.org/10.5676/DWD/ESA_Cloud_cci/MODIS-Terra/V002

Cloud_cci MODIS-Aqua: https://doi.org/10.5676/DWD/ESA_Cloud_cci/MODIS-Aqua/V002

Cloud_cci ATSR2-AATSR: https://doi.org/10.5676/DWD/ESA_Cloud_cci/ATSR2-AATSR/V002

Cloud_cci MERIS+AATSR: https://doi.org/10.5676/DWD/ESA_Cloud_cci/MERIS+AATSR/V002

Multi-sensor cloud and aerosol retrieval simulator and remote sensing from model parameters - Part 2: Aerosols

NASA Astrophysics Data System (ADS)

Wind, Galina; da Silva, Arlindo M.; Norris, Peter M.; Platnick, Steven; Mattoo, Shana; Levy, Robert C.

2016-07-01

The Multi-sensor Cloud Retrieval Simulator (MCRS) produces a "simulated radiance" product from any high-resolution general circulation model with interactive aerosol as if a specific sensor such as the Moderate Resolution Imaging Spectroradiometer (MODIS) were viewing a combination of the atmospheric column and land-ocean surface at a specific location. Previously the MCRS code only included contributions from atmosphere and clouds in its radiance calculations and did not incorporate properties of aerosols. In this paper we added a new aerosol properties module to the MCRS code that allows users to insert a mixture of up to 15 different aerosol species in any of 36 vertical layers.This new MCRS code is now known as MCARS (Multi-sensor Cloud and Aerosol Retrieval Simulator). Inclusion of an aerosol module into MCARS not only allows for extensive, tightly controlled testing of various aspects of satellite operational cloud and aerosol properties retrieval algorithms, but also provides a platform for comparing cloud and aerosol models against satellite measurements. This kind of two-way platform can improve the efficacy of model parameterizations of measured satellite radiances, allowing the assessment of model skill consistently with the retrieval algorithm. The MCARS code provides dynamic controls for appearance of cloud and aerosol layers. Thereby detailed quantitative studies of the impacts of various atmospheric components can be controlled.In this paper we illustrate the operation of MCARS by deriving simulated radiances from various data field output by the Goddard Earth Observing System version 5 (GEOS-5) model. The model aerosol fields are prepared for translation to simulated radiance using the same model subgrid variability parameterizations as are used for cloud and atmospheric properties profiles, namely the ICA technique. After MCARS computes modeled sensor radiances equivalent to their observed counterparts, these radiances are presented as input to operational remote-sensing algorithms.Specifically, the MCARS-computed radiances are input into the processing chain used to produce the MODIS Data Collection 6 aerosol product (M{O/Y}D04). The M{O/Y}D04 product is of course normally produced from M{O/Y}D021KM MODIS Level-1B radiance product directly acquired by the MODIS instrument. MCARS matches the format and metadata of a M{O/Y}D021KM product. The resulting MCARS output can be directly provided to MODAPS (MODIS Adaptive Processing System) as input to various operational atmospheric retrieval algorithms. Thus the operational algorithms can be tested directly without needing to make any software changes to accommodate an alternative input source.We show direct application of this synthetic product in analysis of the performance of the MOD04 operational algorithm. We use biomass-burning case studies over Amazonia employed in a recent Working Group on Numerical Experimentation (WGNE)-sponsored study of aerosol impacts on numerical weather prediction (Freitas et al., 2015). We demonstrate that a known low bias in retrieved MODIS aerosol optical depth appears to be due to a disconnect between actual column relative humidity and the value assumed by the MODIS aerosol product.

Multi-Sensor Cloud and Aerosol Retrieval Simulator and Remote Sensing from Model Parameters . Part 2; Aerosols

NASA Technical Reports Server (NTRS)

Wind, Galina; Da Silva, Arlindo M.; Norris, Peter M.; Platnick, Steven; Mattoo, Shana; Levy, Robert C.

2016-01-01

The Multi-sensor Cloud Retrieval Simulator (MCRS) produces a simulated radiance product from any high-resolution general circulation model with interactive aerosol as if a specific sensor such as the Moderate Resolution Imaging Spectroradiometer (MODIS) were viewing a combination of the atmospheric column and land ocean surface at a specific location. Previously the MCRS code only included contributions from atmosphere and clouds in its radiance calculations and did not incorporate properties of aerosols. In this paper we added a new aerosol properties module to the MCRS code that allows users to insert a mixture of up to 15 different aerosol species in any of 36 vertical layers. This new MCRS code is now known as MCARS (Multi-sensor Cloud and Aerosol Retrieval Simulator). Inclusion of an aerosol module into MCARS not only allows for extensive, tightly controlled testing of various aspects of satellite operational cloud and aerosol properties retrieval algorithms, but also provides a platform for comparing cloud and aerosol models against satellite measurements. This kind of two-way platform can improve the efficacy of model parameterizations of measured satellite radiances, allowing the assessment of model skill consistently with the retrieval algorithm. The MCARS code provides dynamic controls for appearance of cloud and aerosol layers. Thereby detailed quantitative studies of the impacts of various atmospheric components can be controlled. In this paper we illustrate the operation of MCARS by deriving simulated radiances from various data field output by the Goddard Earth Observing System version 5 (GEOS-5) model. The model aerosol fields are prepared for translation to simulated radiance using the same model sub grid variability parameterizations as are used for cloud and atmospheric properties profiles, namely the ICA technique. After MCARS computes modeled sensor radiances equivalent to their observed counterparts, these radiances are presented as input to operational remote-sensing algorithms. Specifically, the MCARS-computed radiances are input into the processing chain used to produce the MODIS Data Collection 6 aerosol product (MOYD04). TheMOYD04 product is of course normally produced from MOYD021KM MODIS Level-1B radiance product directly acquired by the MODIS instrument. MCARS matches the format and metadata of a MOYD021KM product. The resulting MCARS output can be directly provided to MODAPS (MODIS Adaptive Processing System) as input to various operational atmospheric retrieval algorithms. Thus the operational algorithms can be tested directly without needing to make any software changes to accommodate an alternative input source. We show direct application of this synthetic product in analysis of the performance of the MOD04 operational algorithm. We use biomass-burning case studies over Amazonia employed in a recent Working Group on Numerical Experimentation (WGNE)-sponsored study of aerosol impacts on numerical weather prediction (Freitas et al., 2015). We demonstrate that a known low bias in retrieved MODIS aerosol optical depth appears to be due to a disconnect between actual column relative humidity and the value assumed by the MODIS aerosol product.

Statistical Inter-comparison Analysis of MODIS, MISR, and AERONET Over the Middle East and North Africa

NASA Astrophysics Data System (ADS)

Farahat, A.; El-Askary, H. M.; Kalashnikova, O. V.; Garay, M. J.

2016-12-01

Several space-borne and ground based sensors can provide long-standing monitoring of aerosols characteristics, but inconsistencies among different sensors reduce data reliability and lead to uncertainty in analysing long-term data. In this study, we perform statistical inter-comparison of the Aerosol Optical Depth (AOD) among MISR, MODIS/Terra, MODIS/Aqua and Aerosol Robotic Network (AERONET) over seven sites located in the Middle East and North Africa during the period (1995 -2015). The sites are categorized into two regions based on their geographic location and possible dominate particles composition. Compared to MISR, MODIS and AERONET AOD data retrievals indicate larger uncertainty over all sites with a larger daily variability in MODIS measurements. In general, MISR and MODIS AOD matches during high dust seasons but MODIS tends to under estimate the AOD values on low dust seasons. While Terra measurements give a negative trend over the time series at the dust-dominated sites, Aqua, MISR and AERONET show a positive trend. In general, MODIS/Aqua displays stable measurements over the time line at the dust dominated sites. MODIS/Terra, MODIS/Aqua and MISR display a positive trend over Cairo_EMA site while AERONET shows a negative trend over the time line. Terra was found to overestimate AOD during 2002 - 2004 and underestimates it after 2004. We also observe a deviation between Aqua and Terra regardless of the region and data sampling. Excluding Bahrain and Cairo_EMA for low data retrievals the performance of MODIS tends to be similar over all region with 68 % of the retrieved AOD values fall within the confidence range of the AERONET matched data, within global averaged level (> 66 %). MISR indicated better data performance with 72 % falls within the same confidence range. Complimentary MISR and MODIS data was found to provide a better picture of dust storms evolution over Arabian Peninsula and the Middle East. Acknowledgement The authors would like to acknowledge the support provided by the Deanship of Scientific Research (DSR) at the King Fahd University of Petroleum and Minerals (KFUPM) for funding this work through project No. IN141051.

Multisensor Analysis of Ice Crystals Backscatter Peak From 5 Years of Collocated POLDER, MODIS and CALIOP Observations.

NASA Astrophysics Data System (ADS)

Riedi, J.; Labonnote, L. C.; Contaut, F.; Platnick, S. E.; Yang, P.

2016-12-01

Realistic assumptions for representation of ice crystal optical properties are key in deriving meaningful information on ice clouds from spaceborne observations. With the increasing number of multi-sensor analysis it is also of paramount importance that ice crystal models be consistents for the interpretation of both passive and active observations in the solar and thermal infrared spectral domains. There has been significant evidences in the past few years that roughened particles might represent an overall good proxy for ice crystal models being able to simultaneously explain visible and infrared observations obtained from either active or passive sensors (Holz et al, 2016). Nevertheless, details of the exact phase function remain very informative fingerprints of ice crystal shapes and can also be critical parameters for retrievals performed under specific viewing geometries. Analysis of lidar observation for instance remains very sensitive to details of phase function in and around the backscatter direction. The relative magnitude and width of the backscatter peak intensity that appears in phase functions of ice crystal has been shown to carry useful information for characterization of ice crystal habits (Zhou & Yang, 2015). Based on these theoretical results we are revisiting here our previous analysis of coincident POLDER, MODIS and CALIOP observations whereby we were able to study the angular variability of ice clouds reflectance in and around the exact backscatter direction. Statistics from 5 years of observations of peak intensities derived from POLDER have been established in relation to coincident MODIS cloud optical thickness and effective radius retrievals as well as CALIOP layer integrated depolarization ratio and attenuated backscatter. Those are analyzed in view of the theoretical results from Zhou & Yang (2015). In particular, correlation of peak intensity and width with particle size retrieved from MODIS will be presented and implications for ice cloud microphysical properties and remote sensing applications will be discussed. Chen Zhou and Ping Yang : Backscattering peak of ice cloud particles, Opt. Express 23, 11995-12003 (2015) Holz, R. E. et al : Resolving ice cloud optical thickness biases between CALIOP and MODIS using infrared retrievals, Atmos. Chem. Phys., 16, 5075-5090 (2016)

Two cases of diabetic ketoacidosis in HNF1A-MODY linked to severe dehydration: is it time to change the diagnostic criteria for MODY?

PubMed

Pruhova, Stepanka; Dusatkova, Petra; Neumann, David; Hollay, Erik; Cinek, Ondrej; Lebl, Jan; Sumnik, Zdenek

2013-09-01

Hepatocyte nuclear factor-1A maturity-onset diabetes of the young (HNF1A-MODY) is a monogenic form of diabetes caused by heterozygous mutations in HNF1A. Currently, a history of diabetic ketoacidosis (DKA) is an exclusion criterion for genetic testing for MODY. In this article, we describe two unrelated patients aged 17 and 24 years with severe DKA developed several years after the diagnosis of HNF1A-MODY. Both patients were treated with insulin, but their metabolic control was poor (HbA1c 15%, 140 mmol/mol and 13%, 119 mmol/mol, respectively) due to noncompliance and missed insulin injections. In both patients, DKA followed a course of recurrent vomiting with dehydration and prerenal acute kidney injury. Their glycemia, blood pH, and base excess at admission were 97 mmol/L [1,748 mg/dL], 6.80, and -33 mmol/L (patient 1) and 34 mmol/L [613 mg/dL], 7.03, and -14 mmol/L (patient 2). This anecdotal observation supports the notion that a history of DKA does not exclude MODY.

The Time Series Technique for Aerosol Retrievals over Land from MODIS: Algorithm MAIAC

NASA Technical Reports Server (NTRS)

Lyapustin, Alexei; Wang, Yujie

2008-01-01

Atmospheric aerosols interact with sun light by scattering and absorbing radiation. By changing irradiance of the Earth surface, modifying cloud fractional cover and microphysical properties and a number of other mechanisms, they affect the energy balance, hydrological cycle, and planetary climate [IPCC, 2007]. In many world regions there is a growing impact of aerosols on air quality and human health. The Earth Observing System [NASA, 1999] initiated high quality global Earth observations and operational aerosol retrievals over land. With the wide swath (2300 km) of MODIS instrument, the MODIS Dark Target algorithm [Kaufman et al., 1997; Remer et al., 2005; Levy et al., 2007] currently complemented with the Deep Blue method [Hsu et al., 2004] provides daily global view of planetary atmospheric aerosol. The MISR algorithm [Martonchik et al., 1998; Diner et al., 2005] makes high quality aerosol retrievals in 300 km swaths covering the globe in 8 days. With MODIS aerosol program being very successful, there are still several unresolved issues in the retrieval algorithms. The current processing is pixel-based and relies on a single-orbit data. Such an approach produces a single measurement for every pixel characterized by two main unknowns, aerosol optical thickness (AOT) and surface reflectance (SR). This lack of information constitutes a fundamental problem of the remote sensing which cannot be resolved without a priori information. For example, MODIS Dark Target algorithm makes spectral assumptions about surface reflectance, whereas the Deep Blue method uses ancillary global database of surface reflectance composed from minimal monthly measurements with Rayleigh correction. Both algorithms use Lambertian surface model. The surface-related assumptions in the aerosol retrievals may affect subsequent atmospheric correction in unintended way. For example, the Dark Target algorithm uses an empirical relationship to predict SR in the Blue (B3) and Red (B1) bands from the 2.1 m channel (B7) for the purpose of aerosol retrieval. Obviously, the subsequent atmospheric correction will produce the same SR in the red and blue bands as predicted, i.e. an empirical function of 2.1. In other words, the spectral, spatial and temporal variability of surface reflectance in the Blue and Red bands appears borrowed from band B7. This may have certain implications for the vegetation and global carbon analysis because the chlorophyll-sensing bands B1, B3 are effectively substituted in terms of variability by band B7, which is sensitive to the plant liquid water. This chapter describes a new recently developed generic aerosol-surface retrieval algorithm for MODIS. The Multi-Angle Implementation of Atmospheric Correction (MAIAC) algorithm simultaneously retrieves AOT and surface bi-directional reflection factor (BRF) using the time series of MODIS measurements.

Geospatiotemporal Data Mining of Remotely Sensed Phenology for Unsupervised Forest Threat Detection

NASA Astrophysics Data System (ADS)

Mills, R. T.; Hoffman, F. M.; Kumar, J.; Vulli, S. S.; Hargrove, W. W.; Spruce, J.

2010-12-01

Hargrove and Hoffman have previously developed and applied a scalable geospatiotemporal data mining approach to define a set of categorical, multivariate classes or states for describing and tracking the behavior of ecosystem properties through time within a multi-dimensional phase or state space. The method employs a standard k-means cluster analysis with enhancements that reduce the number of required comparisons, dramatically accelerating iterative convergence. In support of efforts by the USDA Forest Service to develop a National Early Warning System for Forest Disturbances, we have applied this geospatiotemporal cluster analysis procedure to annual phenology patterns derived from Moderate Resolution Imaging Spectroradiometer (MODIS) Normalized Difference Vegetation Index (NDVI) for unsupervised change detection. We will present initial results from the analysis of seven years of 250-m MODIS NDVI data for the conterminous United States. While determining what constitutes a "normal" phenological pattern for any given location is challenging due to interannual climate variability, a spatially varying climate change trend, and the relatively short record of MODIS NDVI observations, these results demonstrate the utility of the method for detecting significant mortality events, like the progressive damage from mountain pine beetle, and suggest that the technique may be successfully implemented as a key component in an early warning system for identifying forest threats from natural and anthropogenic disturbances at a continental scale.

Massive Cloud-Based Big Data Processing for Ocean Sensor Networks and Remote Sensing

NASA Astrophysics Data System (ADS)

Schwehr, K. D.

2017-12-01

Until recently, the work required to integrate and analyze data for global-scale environmental issues was prohibitive both in cost and availability. Traditional desktop processing systems are not able to effectively store and process all the data, and super computer solutions are financially out of the reach of most people. The availability of large-scale cloud computing has created tools that are usable by small groups and individuals regardless of financial resources or locally available computational resources. These systems give scientists and policymakers the ability to see how critical resources are being used across the globe with little or no barrier to entry. Google Earth Engine has the Moderate Resolution Imaging Spectroradiometer (MODIS) Terra, MODIS Aqua, and Global Land Data Assimilation Systems (GLDAS) data catalogs available live online. Here we demonstrate these data to calculate the correlation between lagged chlorophyll and rainfall to identify areas of eutrophication, matching these events to ocean currents from datasets like HYbrid Coordinate Ocean Model (HYCOM) to check if there are constraints from oceanographic configurations. The system can provide addition ground truth with observations from sensor networks like the International Comprehensive Ocean-Atmosphere Data Set / Voluntary Observing Ship (ICOADS/VOS) and Argo floats. This presentation is intended to introduce users to the datasets, programming idioms, and functionality of Earth Engine for large-scale, data-driven oceanography.

NASA Polar Imagery: Have It Your Way or Have It Our Way

NASA Astrophysics Data System (ADS)

Schmaltz, J. E.; Alarcon, C.; Boller, R. A.; Cechini, M. F.; Davies, D.; Ilavajhala, S.; Hall, J. R.; Huang, T.; Joshi, T.; McGann, J. M.; Murphy, K. J.; Plesea, L.; Roberts, J. T.; Thompson, C. K.; Timmons, E.

2013-12-01

The MODIS Rapid Response project has been providing complete near real-time imagery coverage of Antarctica since December 2008 and the Arctic since March 2009. In late 2009, the Land Atmosphere Near real-time Capability for EOS (LANCE) was created to greatly expand the range of near real-time data products from a variety of Earth Observing System (EOS) instruments. NASA's Earth Observing System Data and Information System (EOSDIS) began exploring methods to distribute these data as imagery in an intuitive, geo-referenced format, which would be available within three hours of acquisition. Toward this end, EOSDIS has developed the Global Imagery Browse Services (GIBS, http://earthdata.nasa.gov/gibs) to provide highly responsive, scalable, and expandable imagery services. To meet these performance goals, the Open Geospatial Consortium (OGC) Web Map Tile Service (WMTS) was chosen as the standard interface for these services. GIBS has been one of the pioneers in providing tiled image services for the polar regions and also in the clarification of the time and elevation dimensions as used within the WMTS specification. Currently, there are more than a dozen MODIS imagery products available in polar stereographic projections for each pole, including four daily one kilometer 11 micron thermal infrared band images during all seasons. Imagery back to mid-2013 is currently available and reprocessing of imagery from the entire MODIS record is underway and community input is being solicited on recommendations for additional imagery layers from MODIS and other NASA instruments. A variety of geo-spatial client software is able to access these WMTS services. In addition, users can write their own interfaces using OpenLayers or the GDAL library. An OpenLayers demonstration client, Worldview (http://earthdata.nasa.gov/worldview), was developed at Goddard to showcase GIBS imagery. Worldview provides easy viewing of the entire imagery record. A search function allows discovery and selection of the different layers provided. Screen captures may be downloaded in a variety of formats. A catalog of current events helps users find interesting imagery. Data granules can be selected and downloaded from within the Worldview application. This provides an easy way to perform further analysis based on areas of interest discovered while browsing the imagery. Worldview also adapts for use on mobile devices, including both tablets and smart phones.

On the Use of Deep Convective Clouds to Characterize Response versus Scan-angle for MODIS Reflective Solar Bands

NASA Astrophysics Data System (ADS)

Bhatt, R.; Doelling, D. R.; Scarino, B. R.; Gopalan, A.; Haney, C.

2016-12-01

MODIS is a cross-track scanning radiometer with a two-sided scan mirror that images the Earth with an angular field of view of 55° on either side of the nadir. The reflectance of the scan mirror is not uniform and is a function of angle of incidence (AOI), as well as wavelength. This feature of the scan mirror is described by response versus scan-angle (RVS), and was characterized for all reflective solar bands (RSBs), for both MODIS instruments prior to launch. The RVS characteristic of the two MODIS instruments has changed on orbit and, therefore, must be tracked precisely over time to ensure high-quality data in the MODIS products. The MODIS Characterization Support Team (MCST) utilizes the onboard solar diffuser (SD) and lunar measurements to track the RVS changes at two fixed AOIs. The RVS at the remaining AOIs is characterized using the earth view (EV) responses from multiple pseudo-invariant desert sites located in Northern Africa. The drawback of this approach is the assumption that all of the desert sites imaged by the MODIS sensors at different AOIs are radiometrically stable during the same period of time. In addition, the desert samples do not always have continuous AOI coverage as they are limited by the 16-day repeat cycle of the satellite orbit, and by clear-sky conditions over the deserts. This paper proposes a novel and robust approach of characterizing the MODIS RVS using tropical deep convective clouds (DCCs) as an invariant calibration target. The method tracks the monthly DCC response at specified sets of AOIs to compute the temporal RVS changes. Because DCCs are distributed across the entirety of the tropics, they provide a continuum of AOI measurements. Initial results have shown that the Aqua-MODIS Collection 6 band 1 level 1b radiances show considerable residual, or artifact, RVS dependencies, especially on the left side of the cross-track scan. Long-term drifts, up to 2.3%, have been observed at certain AOIs. Temporal correction factors are computed using the DCC trends from 12 scan intervals encompassing all AOIs, and their effectiveness in correcting the observed RVS artifact is evaluated using the Libya-1 pseudo-invariant desert site. The desert and DCC temporal scan dependent trends are reduced to less than 1 standard error after the RVS correction.

Rapid dispersal of saltcedar (Tamarix spp.) biocontrol beetles (Diorhabda carinulata) on a desert river detected by phenocams, MODIS imagery and ground observations

USGS Publications Warehouse

Nagler, Pamela L.; Pearlstein, Susanna; Glenn, Edward P.; Brown, Tim B.; Bateman, Heather L.; Bean, Dan W.; Hultine, Kevin R.

2013-01-01

We measured the rate of dispersal of saltcedar leaf beetles (Diorhabda carinulata), a defoliating insect released on western rivers to control saltcedar shrubs (Tamarix spp.), on a 63 km reach of the Virgin River, U.S. Dispersal was measured by satellite imagery, ground surveys and phenocams. Pixels from the Moderate Resolution Imaging Spectrometer (MODIS) sensors on the Terra satellite showed a sharp drop in NDVI in midsummer followed by recovery, correlated with defoliation events as revealed in networked digital camera images and ground surveys. Ground surveys and MODIS imagery showed that beetle damage progressed downstream at a rate of about 25 km yr−1 in 2010 and 2011, producing a 50% reduction in saltcedar leaf area index and evapotranspiration by 2012, as estimated by algorithms based on MODIS Enhanced Vegetation Index values and local meteorological data for Mesquite, Nevada. This reduction is the equivalent of 10.4% of mean annual river flows on this river reach. Our results confirm other observations that saltcedar beetles are dispersing much faster than originally predicted in pre-release biological assessments, presenting new challenges and opportunities for land, water and wildlife managers on western rivers. Despite relatively coarse resolution (250 m) and gridding artifacts, single MODIS pixels can be useful in tracking the effects of defoliating insects in riparian corridors.

Intercalibration of Two Polar Satellite Instruments Without Simultaneous Nadir Observations

NASA Astrophysics Data System (ADS)

Manninen, Terhikki; Riihela, Aku; Schaaf, Crystal; Key, Jeffrey; Lattanzio, Alessio

2016-08-01

A new intercalibration method for two polar satellite instruments is presented. It is based on statistical fitting of two data sets covering the same area during the same period, but not simultaneously. Deming regression with iterative weights is used. The accuracy of the method was better than about 0.5 % for the MODIS vs. MODIS and AVHRR vs. AVHRR test data sets. The intercalibration of AVHRR vs. MODIS red and NIR channels is carried out and showed a difference of reflectance values of 2% (red) and 6 % (NIR). The red channel intercalibration has slightly higher accuracy for all cases studied.

Observations of Ocean Primary Productivity Using MODIS

NASA Technical Reports Server (NTRS)

Esaias, Wayne E.; Abbott, Mark R.; Koblinsky, Chester J. (Technical Monitor)

2001-01-01

Measuring the magnitude and variability of oceanic net primary productivity (NPP) represents a key advancement toward our understanding of the dynamics of marine ecosystems and the role of the ocean in the global carbon cycle. MODIS observations make two new contributions in addition to continuing the bio-optical time series begun with Orbview-2's SeaWiFS sensor. First, MODIS provides weekly estimates of global ocean net primary productivity on weekly and annual time periods, and annual empirical estimates of carbon export production. Second, MODIS provides additional insight into the spatial and temporal variations in photosynthetic efficiency through the direct measurements of solar-stimulated chlorophyll fluorescence. The two different weekly productivity indexes (first developed by Behrenfeld & Falkowski and by Yoder, Ryan and Howard) are used to derive daily productivity as a function of chlorophyll biomass, incident daily surface irradiance, temperature, euphotic depth, and mixed layer depth. Comparisons between these two estimates using both SeaWiFS and MODIS data show significant model differences in spatial distribution after allowance for the different integration depths. Both estimates are strongly dependence on the accuracy of the chlorophyll determination. In addition, an empirical approach is taken on annual scales to estimate global NPP and export production. Estimates of solar stimulated fluorescence efficiency from chlorophyll have been shown to be inversely related to photosynthetic efficiency by Abbott and co-workers. MODIS provides the first global estimates of oceanic chlorophyll fluorescence, providing an important proof of concept. MODIS observations are revealing spatial patterns of fluorescence efficiency which show expected variations with phytoplankton photo-physiological parameters as measured during in-situ surveys. This has opened the way for research into utilizing this information to improve our understanding of oceanic NPP variability. Deriving the ocean bio-optical properties places severe demands on instrument performance (especially band to band precision) and atmospheric correction. Improvements in MODIS instrument characterization and calibration over the first 16 mission months have greatly improved the accuracy of the chlorophyll input fields and FLH, and therefore the estimates of NPP and fluorescence efficiency. Annual estimates now show the oceanic NPP accounts for 40-50% of the global total NPP, with significant interannual variations related to large scale ocean processes. Spatial variations in ocean NPP, and exported production, have significant effects on exchange of CO2 between the ocean and atmosphere. Further work is underway to improve both the primary productivity model functions, and to refine our understanding of the relationships between fluorescence efficiency and NPP estimates. We expect that the MODIS instruments will prove extremely useful in assessing the time dependencies of oceanic carbon uptake and effects of iron enrichment, within the global carbon cycle.

A Disk-Based System for Producing and Distributing Science Products from MODIS

NASA Technical Reports Server (NTRS)

Masuoka, Edward; Wolfe, Robert; Sinno, Scott; Ye Gang; Teague, Michael

2007-01-01

Since beginning operations in 1999, the MODIS Adaptive Processing System (MODAPS) has evolved to take advantage of trends in information technology, such as the falling cost of computing cycles and disk storage and the availability of high quality open-source software (Linux, Apache and Perl), to achieve substantial gains in processing and distribution capacity and throughput while driving down the cost of system operations.

Improvement of aerosol optical properties modeling over Eastern Asia with MODIS AOD assimilation in a global non-hydrostatic icosahedral aerosol transport model.

PubMed

Dai, Tie; Schutgens, Nick A J; Goto, Daisuke; Shi, Guangyu; Nakajima, Teruyuki

2014-12-01

A new global aerosol assimilation system adopting a more complex icosahedral grid configuration is developed. Sensitivity tests for the assimilation system are performed utilizing satellite retrieved aerosol optical depth (AOD) from the Moderate Resolution Imaging Spectroradiometer (MODIS), and the results over Eastern Asia are analyzed. The assimilated results are validated through independent Aerosol Robotic Network (AERONET) observations. Our results reveal that the ensemble and local patch sizes have little effect on the assimilation performance, whereas the ensemble perturbation method has the largest effect. Assimilation leads to significantly positive effect on the simulated AOD field, improving agreement with all of the 12 AERONET sites over the Eastern Asia based on both the correlation coefficient and the root mean square difference (assimilation efficiency). Meanwhile, better agreement of the Ångström Exponent (AE) field is achieved for 8 of the 12 sites due to the assimilation of AOD only. Copyright © 2014 Elsevier Ltd. All rights reserved.

Large scale maps of cropping intensity in Asia from MODIS

NASA Astrophysics Data System (ADS)

Gray, J. M.; Friedl, M. A.; Frolking, S. E.; Ramankutty, N.; Nelson, A.

2013-12-01

Agricultural systems are geographically extensive, have profound significance to society, and also affect regional energy, carbon, and water cycles. Since most suitable lands worldwide have been cultivated, there is growing pressure to increase yields on existing agricultural lands. In tropical and sub-tropical regions, multi-cropping is widely used to increase food production, but regional-to-global information related to multi-cropping practices is poor. Such information is of critical importance to ensure sustainable food production while mitigating against negative environmental impacts associated with agriculture such as contamination and depletion of freshwater resources. Unfortunately, currently available large-area inventory statistics are inadequate because they do not capture important spatial patterns in multi-cropping, and are generally not available in a timeframe that can be used to help manage cropping systems. High temporal resolution sensors such as MODIS provide an excellent source of information for addressing this need. However, relative to studies that document agricultural extensification, systematic assessment of agricultural intensification via multi-cropping has received relatively little attention. The goal of this work is to help close this methodological and information gap by developing methods that use multi-temporal remote sensing to map multi-cropping systems in Asia. Image time series analysis is especially challenging in Asia because atmospheric conditions including clouds and aerosols lead to high frequencies of missing or low quality remote sensing observations, especially during the Asian Monsoon. The methodology that we use for this work builds upon the algorithm used to produce the MODIS Land Cover Dynamics product (MCD12Q2), but employs refined methods to segment, smooth, and gap-fill 8-day EVI time series calculated from MODIS BRDF corrected surface reflectances. Crop cycle segments are identified based on changes in slope for linear regressions estimated for local windows, and constrained by the EVI amplitude and length of crop cycles that are identified. The procedure can be used to map seasonal or long-term average cropping strategies, and to characterize changes in cropping intensity over longer time periods. The datasets produced using this method therefore provide information related to global cropping systems, and more broadly, provide important information that is required to ensure sustainable management of Earth's resources and ensure food security. To test our algorithm, we applied it to time series of MODIS EVI images over Asia from 2000-2012. Our results demonstrate the utility of multi-temporal remote sensing for characterizing multi-cropping practices in some of the most important and intensely agricultural regions in the world. To evaluate our approach, we compared results from MODIS to field-scale survey data at the pixel scale, and agricultural inventory statistics at sub-national scales. We then mapped changes in multi-cropped area in Asia from the early MODIS period (2001-2004) to present (2009-2012), and characterizes the magnitude and location of changes in cropping intensity over the last 12 years. We conclude with a discussion of the challenges, future improvements, and broader impacts of this work.

A SOAP Web Service for accessing MODIS land product subsets

DOE Office of Scientific and Technical Information (OSTI.GOV)

SanthanaVannan, Suresh K; Cook, Robert B; Pan, Jerry Yun

2011-01-01

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 (MODIS) sensor on board NASA s Terra and Aqua 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 MODIS data make it difficult for users wanting to extract small but valuable amounts of information from the MODIS record. Tomore » 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 MODIS land products using Simple Object Access Protocol (SOAP). The ORNL DAAC MODIS 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 MODIS 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 MODIS land parameters for real time data integration into models, decision support tools or connect to workflow software. Information regarding the MODIS SOAP subsetting Web service is available on the World Wide Web (WWW) at http://daac.ornl.gov/modiswebservice.« less

Downscaling 250-m MODIS growing season NDVI based on multiple-date landsat images and data mining approaches

USGS Publications Warehouse

Gu, Yingxin; Wylie, Bruce K.

2015-01-01

The satellite-derived growing season time-integrated Normalized Difference Vegetation Index (GSN) has been used as a proxy for vegetation biomass productivity. The 250-m GSN data estimated from the Moderate Resolution Imaging Spectroradiometer (MODIS) sensors have been used for terrestrial ecosystem modeling and monitoring. High temporal resolution with a wide range of wavelengths make the MODIS land surface products robust and reliable. The long-term 30-m Landsat data provide spatial detailed information for characterizing human-scale processes and have been used for land cover and land change studies. The main goal of this study is to combine 250-m MODIS GSN and 30-m Landsat observations to generate a quality-improved high spatial resolution (30-m) GSN database. A rule-based piecewise regression GSN model based on MODIS and Landsat data was developed. Results show a strong correlation between predicted GSN and actual GSN (r = 0.97, average error = 0.026). The most important Landsat variables in the GSN model are Normalized Difference Vegetation Indices (NDVIs) in May and August. The derived MODIS-Landsat-based 30-m GSN map provides biophysical information for moderate-scale ecological features. This multiple sensor study retains the detailed seasonal dynamic information captured by MODIS and leverages the high-resolution information from Landsat, which will be useful for regional ecosystem studies.

Comparison of CALIPSO-Like, LaRC, and MODIS Retrievals of Ice Cloud Properties over SIRTA in France and Florida during CRYSTAL-FACE

NASA Technical Reports Server (NTRS)

Chiriaco, M.; Chepfer, H.; Haeffelin, M.; Minnis, P.; Noel, V.; Platnick, S.; McGill, M.; Baumgardner, D.; Dubuisson, P.; Pelon, J.;

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

NASA Technical Reports Server (NTRS)

King, Michael D.

2001-01-01

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

Applications of MODIS Fluorescent Line Height Measurements to Monitor Water Quality Trends and Algal Bloom Activity

NASA Technical Reports Server (NTRS)

Fischer, Andrew; Moreno-Mardinan, Max; Ryan, John P.

2012-01-01

Recent advances in satellite and airborne remote sensing, such as improvements in sensor and algorithm calibrations, processing techniques and atmospheric correction procedures have provided for increased coverage of remote-sensing, ocean-color products for coastal regions. In particular, for the Moderate Resolution Imaging Spectrometer (MODIS) sensor calibration updates, improved aerosol retrievals and new aerosol models has led to improved atmospheric correction algorithms for turbid waters and have improved the retrieval of ocean color in coastal waters. This has opened the way for studying ocean phenomena and processes at finer spatial scales, such as the interactions at the land-sea interface, trends in coastal water quality and algal blooms. Human population growth and changes in coastal management practices have brought about significant changes in the concentrations of organic and inorganic, particulate and dissolved substances entering the coastal ocean. There is increasing concern that these inputs have led to declines in water quality and have increase local concentrations of phytoplankton, which cause harmful algal blooms. In two case studies we present MODIS observations of fluorescence line height (FLH) to 1) assess trends in water quality for Tampa Bay, Florida and 2) illustrate seasonal and annual variability of algal bloom activity in Monterey Bay, California as well as document estuarine/riverine plume induced red tide events. In a comprehensive analysis of long term (2003-2011) in situ monitoring data and satellite imagery from Tampa Bay we assess the validity of the MODIS FLH product against chlorophyll-a and a suite of water quality parameters taken in a variety of conditions throughout a large optically complex estuarine system. A systematic analysis of sampling sites throughout the bay is undertaken to understand how the relationship between FLH and in situ chlorophyll-a responds to varying conditions and to develop a near decadal trend in water quality changes. In situ monitoring locations that correlated well with satellite imagery were in depths greater than seven meters and were located over five kilometers from shore. Water quality parameter of total nitrogen, phosphorous, turbidity and biological oxygen demand had high correlations with these sites, as well. Satellite FLH estimates show improving water quality from 2003-2007 with a slight decline up through 2011. Dinoflagellate blooms in Monterey Bay, California (USA) have recently increased in frequency and intensity. Nine years of MODIS FLH observations are used to describe the annual and seasonal variability of bloom activity within the Bay. Three classes of MODIS algorithms were correlated against in situ chlorophyll measurements. The FLH algorithm provided the most robust estimate of bloom activity. Elevated concentrations of phytoplankton were evident during the months of August-November, a period during which increased occurrences of dinoflagellate blooms have been observed in situ. Seasonal patterns of FLH show the on- and offshore movement of areas of high phytoplankton biomass between oceanographic seasons. Higher concentrations of phytoplankton are also evident in the vicinity of the land-based nutrient sources and outflows, and the cyclonic bay-wide circulation can transport these nutrients to the northern Bay bloom incubation region. Both of these case studies illustrate the utility MODIS FLH observations in supporting management decisions in coastal and estuarine waters.

A consideration of the availableness of MODIS data to assess a volcanic ash fall

NASA Astrophysics Data System (ADS)

Tomiyama, N.; Yonezawa, C.; Yamakoshi, T.

It is important to grasp the situation of the ash fall at short interval for a volcanic disaster-prevention. Clouds and volcanic smokes reduce the opportunities to observe a volcano by a satellite's optical sensor. Therefore it is preferable to use data of a sensor that is able to observe same area with high frequency. MODIS sees every point on the earth every 1-2 days and provides NDVI data with 250m spatial resolutions. The purpose of this study is to consider the availableness of MODIS data to assess the situation of the volcanic ash fall. The test site is Miyake-jima, one of the active volcanic island in Japan. It is verified that a rate of change of NDVI between before and after erruptions correlates with the amounts of ash fall.

Using Lunar Observations for Calibration Stability and Data Continuity for SNPP VIIRS and MODIS Reflected Solar Bands

NASA Astrophysics Data System (ADS)

Xiong, X.; Stone, T. C.

2017-12-01

To meet objectives for assembling continuous Earth environmental data records from multiple satellite instruments, a key consideration is to assure consistent and stable sensor calibration across platforms and spanning mission lifetimes. Maintaining and verifying calibration stability in orbit is particularly challenging for reflected solar band (RSB) radiometer instruments, as options for stable references are limited. The Moon is used regularly as a calibration target, which has capabilities for long-term sensor performance monitoring and for use as a common reference for RSB sensor inter-calibration. Suomi NPP VIIRS has viewed the Moon nearly every month since launch, utilizing spacecraft roll maneuvers to acquire lunar observations within a small range of phase angles. The VIIRS Characterization Support Team (VCST) at NASA GSFC has processed the Moon images acquired by SNPP VIIRS into irradiance measurements for calibration purposes; however, the variations in the Moon's brightness still require normalizing the VIIRS lunar measurements using radiometric reference values generated by the USGS lunar calibration system, i.e. the ROLO model. Comparison of the lunar irradiance time series to the calibration f-factors derived from the VIIRS on-board solar diffuser system shows similar overall trends in sensor response, but also reveals residual geometric anomalies in the lunar model results. The excellent lunar radiometry achieved by SNPP VIIRS is actively being used to advance lunar model development at USGS. Both MODIS instruments also have viewed the Moon regularly since launch, providing a practical application of sensor inter-calibration using the Moon as a common reference. This paper discusses ongoing efforts aimed toward demonstrating and utilizing the full potential of lunar observations to support long-term calibration stability and consistency for SNPP VIIRS and MODIS, thus contributing to level-1B data quality assurance for continuity and monitoring global environmental changes.

A case study of aerosol data assimilation with the Community Multi-scale Air Quality Model over the contiguous United States using 3D-Var and optimal interpolation methods

NASA Astrophysics Data System (ADS)

Tang, Youhua; Pagowski, Mariusz; Chai, Tianfeng; Pan, Li; Lee, Pius; Baker, Barry; Kumar, Rajesh; Delle Monache, Luca; Tong, Daniel; Kim, Hyun-Cheol

2017-12-01

This study applies the Gridpoint Statistical Interpolation (GSI) 3D-Var assimilation tool originally developed by the National Centers for Environmental Prediction (NCEP), to improve surface PM2.5 predictions over the contiguous United States (CONUS) by assimilating aerosol optical depth (AOD) and surface PM2.5 in version 5.1 of the Community Multi-scale Air Quality (CMAQ) modeling system. An optimal interpolation (OI) method implemented earlier (Tang et al., 2015) for the CMAQ modeling system is also tested for the same period (July 2011) over the same CONUS. Both GSI and OI methods assimilate surface PM2.5 observations at 00:00, 06:00, 12:00 and 18:00 UTC, and MODIS AOD at 18:00 UTC. The assimilations of observations using both GSI and OI generally help reduce the prediction biases and improve correlation between model predictions and observations. In the GSI experiments, assimilation of surface PM2.5 (particle matter with diameter < 2.5 µm) leads to stronger increments in surface PM2.5 compared to its MODIS AOD assimilation at the 550 nm wavelength. In contrast, we find a stronger OI impact of the MODIS AOD on surface aerosols at 18:00 UTC compared to the surface PM2.5 OI method. GSI produces smoother result and yields overall better correlation coefficient and root mean squared error (RMSE). It should be noted that the 3D-Var and OI methods used here have several big differences besides the data assimilation schemes. For instance, the OI uses relatively big model uncertainties, which helps yield smaller mean biases, but sometimes causes the RMSE to increase. We also examine and discuss the sensitivity of the assimilation experiments' results to the AOD forward operators.

Ocean observations with EOS/MODIS: Algorithm development and post launch studies

NASA Technical Reports Server (NTRS)

Gordon, Howard R.

1995-01-01

Several significant accomplishments were made during the present reporting period. (1) Initial simulations to understand the applicability of the MODerate Resolution Imaging Spectrometer (MODIS) 1380 nm band for removing the effects of stratospheric aerosols and thin cirrus clouds were completed using a model for an aged volcanic aerosol. The results suggest that very simple procedures requiring no a priori knowledge of the optical properties of the stratospheric aerosol may be as effective as complex procedures requiring full knowledge of the aerosol properties, except the concentration which is estimated from the reflectance at 1380 nm. The limitations of this conclusion will be examined in the next reporting period; (2) The lookup tables employed in the implementation of the atmospheric correction algorithm have been modified in several ways intended to improve the accuracy and/or speed of processing. These have been delivered to R. Evans for implementation into the MODIS prototype processing algorithm for testing; (3) A method was developed for removal of the effects of the O2 'A' absorption band from SeaWiFS band 7 (745-785 nm). This is important in that SeaWiFS imagery will be used as a test data set for the MODIS atmospheric correction algorithm over the oceans; and (4) Construction of a radiometer, and associated deployment boom, for studying the spectral reflectance of oceanic whitecaps at sea was completed. The system was successfully tested on a cruise off Hawaii on which whitecaps were plentiful during October-November. This data set is now under analysis.

Estimation of Surface Air Temperature Over Central and Eastern Eurasia from MODIS Land Surface Temperature

NASA Technical Reports Server (NTRS)

Shen, Suhung; Leptoukh, Gregory G.

2011-01-01

Surface air temperature (T(sub a)) is a critical variable in the energy and water cycle of the Earth.atmosphere system and is a key input element for hydrology and land surface models. This is a preliminary study to evaluate estimation of T(sub a) from satellite remotely sensed land surface temperature (T(sub s)) by using MODIS-Terra data over two Eurasia regions: northern China and fUSSR. High correlations are observed in both regions between station-measured T(sub a) and MODIS T(sub s). The relationships between the maximum T(sub a) and daytime T(sub s) depend significantly on land cover types, but the minimum T(sub a) and nighttime T(sub s) have little dependence on the land cover types. The largest difference between maximum T(sub a) and daytime T(sub s) appears over the barren and sparsely vegetated area during the summer time. Using a linear regression method, the daily maximum T(sub a) were estimated from 1 km resolution MODIS T(sub s) under clear-sky conditions with coefficients calculated based on land cover types, while the minimum T(sub a) were estimated without considering land cover types. The uncertainty, mean absolute error (MAE), of the estimated maximum T(sub a) varies from 2.4 C over closed shrublands to 3.2 C over grasslands, and the MAE of the estimated minimum Ta is about 3.0 C.

Recent Weather Extremes and Impacts on Agricultural Production and Vector-Borne Disease Outbreak Patterns

PubMed Central

Anyamba, Assaf; Small, Jennifer L.; Britch, Seth C.; Tucker, Compton J.; Pak, Edwin W.; Reynolds, Curt A.; Crutchfield, James; Linthicum, Kenneth J.

2014-01-01

We document significant worldwide weather anomalies that affected agriculture and vector-borne disease outbreaks during the 2010–2012 period. We utilized 2000–2012 vegetation index and land surface temperature data from NASA's satellite-based Moderate Resolution Imaging Spectroradiometer (MODIS) to map the magnitude and extent of these anomalies for diverse regions including the continental United States, Russia, East Africa, Southern Africa, and Australia. We demonstrate that shifts in temperature and/or precipitation have significant impacts on vegetation patterns with attendant consequences for agriculture and public health. Weather extremes resulted in excessive rainfall and flooding as well as severe drought, which caused ∼10 to 80% variation in major agricultural commodity production (including wheat, corn, cotton, sorghum) and created exceptional conditions for extensive mosquito-borne disease outbreaks of dengue, Rift Valley fever, Murray Valley encephalitis, and West Nile virus disease. Analysis of MODIS data provided a standardized method for quantifying the extreme weather anomalies observed during this period. Assessments of land surface conditions from satellite-based systems such as MODIS can be a valuable tool in national, regional, and global weather impact determinations. PMID:24658301

Half-Life of Sulfonylureas in HNF1A and HNF4A Human MODY Patients is not Prolonged as Suggested by the Mouse Hnf1a(-/-) Model.

PubMed

Urbanova, Jana; Andel, Michal; Potockova, Jana; Klima, Josef; Macek, Jan; Ptacek, Pavel; Mat'oska, Vaclav; Kumstyrova, Tereza; Heneberg, Petr

2015-01-01

Sulfonylurea derivatives are widely used for clinical treatment of human subjects with Maturity Onset Diabetes of the Young (MODY) caused by mutations in HNF-1α or HNF-4α despite the mechanism leading to their hypersensitivity is incompletely understood. In Hnf1a(-/-) mice, serum concentrations and half-life of sulfonylurea derivatives are strongly increased. We thus hypothesized that reduced sulfonylurea derivatives clearance stands behind their therapeutic potential in human HNF1A/HNF4A MODY subjects. Single doses of 3 mg glipizide and 5 mg glibenclamide/glyburide were administered sequentially to seven HNF1A/HNF4A MODY subjects and six control individuals matched for their age, BMI and CYP2C9 genotype. Pharmacokinetic (plasma concentration levels, Cmax, tmax, t1/2, AUC) and pharmacodynamic parameters (glycemia, C-peptide and insulin plasma levels) were followed for 24 hours after drug administration. We provide the first evidence on the pharmacokinetics and pharmacodynamics of sulfonylurea derivatives in human MODY subjects. The half-life of glipizide did not change, and reached 3.8±0.7 and 3.7±1.8 h in the MODY and control subjects, respectively. The half-life of glibenclamide was increased only in some MODY subjects (t1/2 9.5±6.7 and 5.0±1.4 h, respectively). Importantly, the intra- individual responses of MODY (but control) subjects to glipizide and glibenclamide treatment were highly correlated. With regards to pharmacodynamics, we observed a differential response of control but not MODY subjects to the doses of glipizide and glibenclamide applied. We rejected the hypothesis that all human MODY-associated mutations in HNF1A / HNF4A induce changes in the pharmacokinetics of sulfonylureas in humans analogically to the Hnf1a(-/-) mouse model.

Remote Sensing of Ecosystem Light Use Efficiency Using MODIS

NASA Astrophysics Data System (ADS)

Huemmrich, K. F.; Middleton, E.; Landis, D.; Black, T. A.; Barr, A. G.; McCaughey, J. H.; Hall, F.

2009-12-01

Understanding the dynamics of the global carbon cycle requires an accurate determination of the spatial and temporal distribution of photosynthetic CO2 uptake by terrestrial vegetation. Optimal photosynthetic function is negatively affected by stress factors that cause down-regulation (i.e., reduced rate of photosynthesis). Present modeling approaches to determine ecosystem carbon exchange rely on meteorological data as inputs to models that predict the relative photosynthetic function in response to environmental conditions inducing stress (e.g., drought, high/low temperatures). This study examines the determination of ecosystem photosynthetic light use efficiency (LUE) from remote sensing, through measurement of vegetation spectral reflectance changes associated with physiologic stress responses exhibited by photosynthetic pigments. This approach uses the Moderate-Resolution Spectroradiometer (MODIS) on Aqua and Terra to provide frequent, narrow-band measurements. The reflective ocean MODIS bands were used to calculate the Photochemical Reflectance Index (PRI), an index that is sensitive to reflectance changes near 531nm associated with vegetation stress responses exhibited by photosynthetic pigments in the xanthophyll cycle. MODIS PRI values were compared with LUE calculated from CO2 flux measured at four Canadian forest sites: A mature Douglas fir site in British Columbia, mature aspen and black spruce sites in Saskatchewan, and a mixed forest site in Ontario, all part of the Canadian Carbon Program network. The relationships between LUE and MODIS PRI were different among forest types, with clear differences in the slopes of the relationships for conifer and deciduous forests. The MODIS based LUE measurements provide a more accurate estimation of observed LUE than the values calculated in the MODIS GPP model. This suggests the possibility of a GPP model that uses MODIS LUE instead of modeled LUE. This type of model may provide a useful contrast to existing models driven by meteorological data. The main impediment to developing such a model is the lack of a MODIS product that provides surface reflectance for the MODIS ocean bands over land.

Cross-comparison of the IRS-P6 AWiFS sensor with the L5 TM, L7 ETM+, & Terra MODIS sensors

USGS Publications Warehouse

Chander, G.; Xiong, X.; Angal, A.; Choi, T.; Malla, R.

2009-01-01

As scientists and decision makers increasingly rely on multiple Earth-observing satellites to address urgent global issues, it is imperative that they can rely on the accuracy of Earth-observing data products. This paper focuses on the crosscomparison of the Indian Remote Sensing (IRS-P6) Advanced Wide Field Sensor (AWiFS) with the Landsat 5 (L5) Thematic Mapper (TM), Landsat 7 (L7) Enhanced Thematic Mapper Plus (ETM+), and Terra Moderate Resolution Imaging Spectroradiometer (MODIS) sensors. The cross-comparison was performed using image statistics based on large common areas observed by the sensors within 30 minutes. Because of the limited availability of simultaneous observations between the AWiFS and the Landsat and MODIS sensors, only a few images were analyzed. These initial results are presented. Regression curves and coefficients of determination for the top-of-atmosphere (TOA) trends from these sensors were generated to quantify the uncertainty in these relationships and to provide an assessment of the calibration differences between these sensors. ?? 2009 SPIE.

Mapping and Visualization of The Deepwater Horizon Oil Spill Using Satellite Imagery

NASA Astrophysics Data System (ADS)

Ferreira Pichardo, E.

2017-12-01

Satellites are man-made objects hovering around the Earth's orbit and are essential for Earth observation, i.e. the monitoring and gathering of data about the Earth's vital systems. Environmental Satellites are used for atmospheric research, weather forecasting, and warning as well as monitoring extreme weather events. These satellites are categorized into Geosynchronous and Low Earth (Polar) orbiting satellites. Visualizing satellite data is critical to understand the Earth's systems and changes to our environment. The objective of this research is to examine satellite-based remotely sensed data that needs to be processed and rendered in the form of maps or other forms of visualization to understand and interpret the satellites' observations to monitor the status, changes and evolution of the mega-disaster Deepwater Horizon Spill that occurred on April 20, 2010 in the Gulf of Mexico. In this project, we will use an array of tools and programs such as Python, CSPP and Linux. Also, we will use data from the National Oceanic and Atmospheric Administration (NOAA): Polar-Orbiting Satellites Terra Earth Observing System AM-1 (EOS AM-1), and Aqua EOS PM-1 to investigate the mega-disaster. Each of these satellites carry a variety of instruments, and we will use the data obtained from the remote sensor Moderate-Resolution Imaging Spectroradiometer (MODIS). Ultimately, this study shows the importance of mapping and visualizing data such as satellite data (MODIS) to understand the extents of environmental impacts disasters such as the Deepwater Horizon Oil spill.

Monitoring Fires from Space: a case study in transitioning from research to applications

NASA Astrophysics Data System (ADS)

Justice, C. O.; Giglio, L.; Vadrevu, K. P.; Csiszar, I. A.; Schroeder, W.; Davies, D.

2012-12-01

This paper discusses the heritage and relationships between science and applications in the context of global satellite-based fire monitoring. The development of algorithms for satellite-based fire detection has been supported primarily by NASA for the polar orbiters with a global focus, and initially by NOAA and more recently by EUMETSAT for the geostationary satellites, with a regional focus. As the feasibility and importance of space-based fire monitoring was recognized, satellite missions were designed to include fire detection capabilities. As a result, the algorithms and accuracy of the detections have improved. Due to the role of fire in the Earth System and its relevance to society, at each step in the development of the sensing capability the research has made a transition into fire-related applications to such an extent that there is now broad use of these data worldwide. The origin of the polar-orbiting satellite fire detection capability was with the AVHRR sensor beginning in the early 1980s, but was transformed with the launch of the EOS MODIS instruments, which included sensor characteristics specifically for fire detection. NASA gave considerable emphasis on the accuracy assessment of the fire detection and the development of fire characterization and burned area products from MODIS. Collaboration between the MODIS Fire Team and the RSAC USFS, initiated in the context of the Montana wildfires of 2001, prompted the development of a Rapid Response System for fire data and eventually led to operational use of MODIS data by the USFS for strategic fire monitoring. Building on this success, the Fire Information for Resource Management Systems (FIRMS) project was funded by NASA Applications to further develop products and services for the fire information community. The FIRMS was developed as a web-based geospatial tool, offering a range of geospatial data services, including SMS text messaging and is now widely used. This system, developed in the research domain, has now been successfully moved to an operational home at the UN FAO, as the Global Fire Information Management System (GFIMS). With a view to operational data continuity, the Suomi-NPP/JPSS VIIRS system was also designed with a fire detection capability, and is providing promising results for fire monitoring both from the standard operational production system and experimental product enhancements. International coordination on fire observations and outreach has been successfully developed under the GOFC GOLD program.

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.

Deriving Albedo from Coupled MERIS and MODIS Surface Products

NASA Technical Reports Server (NTRS)

Gao, Feng; Schaaf, Crystal; Jin, Yu-Fang; Lucht, Wolfgang; Strahler, Alan

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.

Aerosol Remote Sensing from Space -- What We've Learned, Where We're Heading

NASA Technical Reports Server (NTRS)

Kahn, Ralph

2010-01-01

The MISR and MODIS instruments aboard the NASA Earth Observing System's Terra Satellite have been collecting data containing information about the state of Earth's atmosphere and surface for over ten years. Among the retrieved quantities are amount and type of wildfire smoke, desert dust, volcanic effluent, urban and industrial pollution particles, and other aerosols. However, the broad scientific challenges of understanding aerosol impacts on climate and health place different, and very exacting demands on our measurement capabilities. And these data sets, though much more advanced in many respects than previous aerosol data records, are imperfect. In this presentation, I will summarize current understanding of MISR and MODIS aerosol product strengths and limitations, discuss how they relate to the bigger aerosol science questions we must address, and give my view of what we will need to do to progress.

Aerosol Remote Sensing from Space - Where We Stand, Where We're Heading

NASA Technical Reports Server (NTRS)

Kahn, Ralph

2011-01-01

The MISR and MODIS instruments aboard the NASA Earth Observing System's Terra Satellite have been collecting data containing information about the state of Earth's atmosphere and surface for over eleven years. Among the retrieved quantities are amount and type of wildfire smoke, desert dust, volcanic effluent, urban and industrial pollution particles, and other aerosols. However, the broad scientific challenges of understanding aerosol impacts on climate and health place different, and very exacting demands on our measurement capabilities. And these data sets, though much more advanced in many respects than previous aerosol data records, are imperfect. In this presentation, I will summarize current understanding of MISR and MODIS aerosol product strengths and limitations, discuss how they relate to the bigger aerosol science questions we must address, and give my view of the way forward.

Aerosol Remote Sensing from Space - Where We Stand, Where We're Heading

NASA Technical Reports Server (NTRS)

Kahn, Ralph A.

2013-01-01

The MISR and MODIS instruments aboard the NASA Earth Observing System's Terra Satellite have been collecting data containing information about the state of Earth's atmosphere and surface for over eleven years. Among the retrieved quantities are amount and type of wildfire smoke, desert dust, volcanic effluent, urban and industrial pollution particles, and other aerosols. However, the broad scientific challenges of understanding aerosol impacts on climate and health place different, and very exacting demands on our measurement capabilities. And these data sets, though much more advanced in many respects than previous aerosol data records, are imperfect. In this presentation, I will summarize current understanding of MISR and MODIS aerosol product strengths and limitations, discuss how they relate to the bigger aerosol science questions we must address, and give my view of the way forward.

Validation of MODIS aerosol optical depth over the Mediterranean Coast

NASA Astrophysics Data System (ADS)

Díaz-Martínez, J. Vicente; Segura, Sara; Estellés, Víctor; Utrillas, M. Pilar; Martínez-Lozano, J. Antonio

2013-04-01

Atmospheric aerosols, due to their high spatial and temporal variability, are considered one of the largest sources of uncertainty in different processes affecting visibility, air quality, human health, and climate. Among their effects on climate, they play an important role in the energy balance of the Earth. On one hand they have a direct effect by scattering and absorbing solar radiation; on the other, they also have an impact in precipitation, modifying clouds, or affecting air quality. The application of remote sensing techniques to investigate aerosol effects on climate has advanced significatively over last years. In this work, the products employed have been obtained from the Moderate Resolution Imaging Spectroradiometer (MODIS). MODIS is a sensor located onboard both Earth Observing Systems (EOS) Terra and Aqua satellites, which provide almost complete global coverage every day. These satellites have been acquiring data since early 2000 (Terra) and mid 2002 (Aqua) and offer different products for land, ocean and atmosphere. Atmospheric aerosol products are presented as level 2 products with a pixel size of 10 x 10 km2 in nadir. MODIS aerosol optical depth (AOD) is retrieved by different algorithms depending on the pixel surface, distinguishing between land and ocean. For its validation, ground based sunphotometer data from AERONET (Aerosol Robotic Network) has been employed. AERONET is an international operative network of Cimel CE318 sky-sunphotometers that provides the most extensive aerosol data base globally available of ground-based measurements. The ground sunphotometric technique is considered the most accurate for the retrieval of radiative properties of aerosols in the atmospheric column. In this study we present a validation of MODIS C051 AOD employing AERONET measurements over different Mediterranean coastal sites centered over an area of 50 x 50 km2, which includes both pixels over land and ocean. The validation is done comparing spatial statistics from MODIS with corresponding temporal statistics from AERONET, as proposed by Ichoku et al. (2002). Eight Mediterranean coastal sites (in Spain, France, Italy, Crete, Turkey and Israel) with available AERONET and MODIS data have been used. These stations have been selected following QA criteria (minimum 1000 days of level 2.0 data) and a maximum distance of 8 km from the coast line. Results of the validation over each site show analogous behaviour, giving similar results regarding to the accuracy of the algorithms. Greatest differences are found for the AOD obtained over land, especially for drier regions, where the surface tends to be brighter. In general, the MODIS AOD has better a agreement with AERONET retrievals for the ocean algorithm than the land algorithm when validated over coastal sites, and the agreement is within the expected uncertainty estimated for MODIS data. References: - C. Ichoku et al., "A spatio-temporal approach for global validation and analysis of MODIS aerosol products", Geophysical Research Letters, 219, 12, 10.1029/2001GL013206, 2002.

Recent Efforts to Improve the Near Real Time Forest Disturbance Monitoring Capabilities of the ForWarn System

NASA Technical Reports Server (NTRS)

Spruce, Joseph; Hargrove, William; Gasser, Gerald

2013-01-01

This presentation discusses the development of anew method for computing NDVI temporal composites from near real time eMODIS data This research is being conducted to improve forest change products used in the ForWarn system for monitoring regional forest disturbances in the United States. ForWarn provides nation-wide NDVI-based forest disturbance detection products that are refreshed every 8 days. Current eMODIS and historical MOD13 24 day NDVI data are used to compute the disturbance detection products. The eMODIS 24 day NDVI data re-aggregated from 7 day NDVI products. The 24 day eMODIS NDVIs are generally cloud free, but do not necessarily use the freshest quality data. To shorten the disturbance detection time, a method has been developed that performs adaptive length/maximum value compositing of eMODIS NDVI, along with cloud and shadow "noise" mitigation. Tests indicate that this method can reduce detection rates by 8-16 days for known recent disturbance events, depending on the cloud frequencies and disturbance type. The noise mitigation in these tests, though imperfect, helped to improve quality of the resulting NDVI and forest change products.

Land product validation of MODIS derived FPAR product over the tropical dry-forest of Santa Rosa National Park, Guanacaste, Costa Rica.

NASA Astrophysics Data System (ADS)

Sharp, Iain; Sanchez, Arturo

2017-04-01

Land-product validation of the MODIS derived FPAR product over the tropical dry-forest of Santa Rosa National Park, Guanacaste, Costa Rica. By Iain Sharp & Dr. Arturo Sanchez-Azofeifa In remote sensing, being able to ensure the accuracy of the satellite data being produced remains an issue; this is especially true for phenological variables such as the Fraction of Photosynthetically Active Radiation (FPAR). FPAR, which is considered an essential climate variable by the Global Terrestrial Observation System (GTOS), utilizes the 400-700 nm wavelength range to quantify the total amount of solar radiation available for photosynthetic use. It is a variable that is strongly influenced by the seasonal, diurnal, and optic properties of vegetation making it an accurate representation of vegetation health. Measurements of ground level FPAR can be completed using flux towers along with a limited number of wireless ground sensors, but due to the finite number and location of these towers, many research initiatives instead use the Moderate resolution Imaging Spectroradiometer (MODIS) FPAR product, which converts Leaf Area Index (LAI) to a FPAR value using Beer's Law. This is done despite there being little consensus on whether this is the best method to use for all ecosystems and vegetation types. One particular ecosystem that has had limited study to determine the accuracy of the MODIS derived FPAR products are the Tropical Dry Forests (TDFs) of Latin America. This ecosystem undergoes drastic seasonal changes from leaf off during the dry season to green-up during the wet seasons. This study aims to test the congruency between the MODIS derived FPAR values and ground-based FPAR values in relation to growing season length, growing season start and end dates, the peak and mean of FPAR values, and overall growth/phenological trends at the Santa Rosa National Park Environmental Monitoring Super Site (SR-EMSS) in Costa Rica and FPAR MODIS products. We derive our FPAR from a Wireless Sensor Network (WSN) consisting of more than 50 nodes measuring transmitted PAR, temperature, relative humidity, and soil moisture over custom time intervals ranging from 2-Hz to 15 min since 2013. Our fundamental goal is to demonstrate how accurate and reflective the MODIS derived FPAR product is of TDF phenology. This will be the first step taken in identifying potential problems with the MODIS derived FPAR products over TDFs in the Americas.

Improving correlations between MODIS aerosol optical thickness and ground-based PM 2.5 observations through 3D spatial analyses

NASA Astrophysics Data System (ADS)

Hutchison, Keith D.; Faruqui, Shazia J.; Smith, Solar

The Center for Space Research (CSR) continues to focus on developing methods to improve correlations between satellite-based aerosol optical thickness (AOT) values and ground-based, air pollution observations made at continuous ambient monitoring sites (CAMS) operated by the Texas commission on environmental quality (TCEQ). Strong correlations and improved understanding of the relationships between satellite and ground observations are needed to formulate reliable real-time predictions of air quality using data accessed from the moderate resolution imaging spectroradiometer (MODIS) at the CSR direct-broadcast ground station. In this paper, improvements in these correlations are demonstrated first as a result of the evolution in the MODIS retrieval algorithms. Further improvement is then shown using procedures that compensate for differences in horizontal spatial scales between the nominal 10-km MODIS AOT products and CAMS point measurements. Finally, airborne light detection and ranging (lidar) observations, collected during the Texas Air Quality Study of 2000, are used to examine aerosol profile concentrations, which may vary greatly between aerosol classes as a result of the sources, chemical composition, and meteorological conditions that govern transport processes. Further improvement in correlations is demonstrated with this limited dataset using insights into aerosol profile information inferred from the vertical motion vectors in a trajectory-based forecast model. Analyses are ongoing to verify these procedures on a variety of aerosol classes using data collected by the Cloud-Aerosol Lidar and Infrared Pathfinder Satellite (Calipso) lidar.

Deteriorating water clarity in shallow waters: Evidence from long term MODIS and in-situ observations

NASA Astrophysics Data System (ADS)

Shi, Kun; Zhang, Yunlin; Zhu, Guangwei; Qin, Boqiang; Pan, Delu

2018-06-01

Water clarity (Secchi disk depth: SDD), as a proxy of water transparency, provides important information on the light availability to the water or lake ecosystem. Shallow lakes have been experienced dramatic environmental and climatic change. This study demonstrated using combination of long-term MODIS and in-situ measurements to track the dynamics of SDD with these environmental and climate changes in shallow water environments. We selected a typical turbid shallow Lake Taihu as our case study. Based on MODIS-Aqua data, an empirical model for estimating SDD was developed and validated. Subsequently, we employed the proposed model to derive the spatial and temporal SDD distribution patterns of Lake Taihu from 2003 to 2015. Combining MODIS-derived SDD time series of 2003-2015 and long-term in-situ SDD observations dated back to 1993, we elucidated SDD long-term variation trends and driving mechanism. Deteriorating water clarity from the long-term SDD observations indicated that Lake Taihu became more and more turbid and water quality was decreasing. Increasing in cyanobacterial bloom area, as a result of decreasing in wind speed and eutrophication, may partially be responsible for the decreasing trend. A predicted future decrease in the wind speed in Lake Taihu region could enhance the formation of cyanobacterial blooms and consequently lead to a further decrease in water clarity. This study suggested that coupling remote sensing monitoring and long-term in-situ observations could provide robust evidence and new insights to elucidate long-term dynamics in aquatic ecosystem evolution.

SCOPE model applied for rapeseed in Spain.

PubMed

Pardo, Nuria; Sánchez, M Luisa; Su, Zhongbo; Pérez, Isidro A; García, M Angeles

2018-06-15

The integrated SCOPE (Soil, Canopy Observation, Photochemistry and Energy balance) model, coupling radiative transfer theory and biochemistry, was applied to a biodiesel crop grown in a Spanish agricultural area. Energy fluxes and CO 2 exchange were simulated with this model for the period spanning January 2008 to October 2008. Results were compared to experimental measurements performed using eddy covariance and meteorological instrumentation. The reliability of the model was proven by simulating latent (LE) and sensible (H) heat fluxes, soil heat flux (G), and CO 2 exchanges (NEE and GPP). LAI data used as input in the model were retrieved from the MODIS and MERIS sensors. SCOPE was able to reproduce similar seasonal trends to those measured for NEE, GPP and LE. When considering H, the modelled values were underestimated for the period covering July 2008 to mid-September 2008. The modelled fluxes reproduced the observed seasonal evolution with determination coefficients of over 0.77 when LE and H were evaluated. The modelled results offered good agreement with observed data for NEE and GPP, regardless of whether LAI data belonged to MODIS or MERIS, showing slopes of 0.87 and 0.91 for NEE-MODIS and NEE-MERIS, and 0.91 and 0.94 for GPP-MODIS and GPP-MERIS, respectively. Moreover, SCOPE was able to reproduce similar seasonal behaviours to those observed for the experimental carbon fluxes, clearly showing the CO 2 sink/source behaviour for the whole period studied. Copyright © 2018 Elsevier B.V. All rights reserved.

Using Airborne High Spectral Resolution Lidar Data to Evaluate Combined Active Plus Passive Retrievals of Aerosol Extinction Profiles

NASA Technical Reports Server (NTRS)

Burton, S. P.; Ferrare, R. A.; Hostetler, C. A.; Hair, J. W.; Kittaka, C.; Vaughn, M. A.; Remer, L. A.

2010-01-01

We derive aerosol extinction profiles from airborne and space-based lidar backscatter signals by constraining the retrieval with column aerosol optical thickness (AOT), with no need to rely on assumptions about aerosol type or lidar ratio. The backscatter data were acquired by the NASA Langley Research Center airborne High Spectral Resolution Lidar (HSRL) and by the Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) instrument on the Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO) satellite. The HSRL also simultaneously measures aerosol extinction coefficients independently using the high spectral resolution lidar technique, thereby providing an ideal data set for evaluating the retrieval. We retrieve aerosol extinction profiles from both HSRL and CALIOP attenuated backscatter data constrained with HSRL, Moderate-Resolution Imaging Spectroradiometer (MODIS), and Multiangle Imaging Spectroradiometer column AOT. The resulting profiles are compared with the aerosol extinction measured by HSRL. Retrievals are limited to cases where the column aerosol thickness is greater than 0.2 over land and 0.15 over water. In the case of large AOT, the results using the Aqua MODIS constraint over water are poorer than Aqua MODIS over land or Terra MODIS. The poorer results relate to an apparent bias in Aqua MODIS AOT over water observed in August 2007. This apparent bias is still under investigation. Finally, aerosol extinction coefficients are derived from CALIPSO backscatter data using AOT from Aqua MODIS for 28 profiles over land and 9 over water. They agree with coincident measurements by the airborne HSRL to within +/-0.016/km +/- 20% for at least two-thirds of land points and within +/-0.028/km +/- 20% for at least two-thirds of ocean points.

Spatiotemporal fusion of multiple-satellite aerosol optical depth (AOD) products using Bayesian maximum entropy method

NASA Astrophysics Data System (ADS)

Tang, Qingxin; Bo, Yanchen; Zhu, Yuxin

2016-04-01

Merging multisensor aerosol optical depth (AOD) products is an effective way to produce more spatiotemporally complete and accurate AOD products. A spatiotemporal statistical data fusion framework based on a Bayesian maximum entropy (BME) method was developed for merging satellite AOD products in East Asia. The advantages of the presented merging framework are that it not only utilizes the spatiotemporal autocorrelations but also explicitly incorporates the uncertainties of the AOD products being merged. The satellite AOD products used for merging are the Moderate Resolution Imaging Spectroradiometer (MODIS) Collection 5.1 Level-2 AOD products (MOD04_L2) and the Sea-viewing Wide Field-of-view Sensor (SeaWiFS) Deep Blue Level 2 AOD products (SWDB_L2). The results show that the average completeness of the merged AOD data is 95.2%,which is significantly superior to the completeness of MOD04_L2 (22.9%) and SWDB_L2 (20.2%). By comparing the merged AOD to the Aerosol Robotic Network AOD records, the results show that the correlation coefficient (0.75), root-mean-square error (0.29), and mean bias (0.068) of the merged AOD are close to those (the correlation coefficient (0.82), root-mean-square error (0.19), and mean bias (0.059)) of the MODIS AOD. In the regions where both MODIS and SeaWiFS have valid observations, the accuracy of the merged AOD is higher than those of MODIS and SeaWiFS AODs. Even in regions where both MODIS and SeaWiFS AODs are missing, the accuracy of the merged AOD is also close to the accuracy of the regions where both MODIS and SeaWiFS have valid observations.

Using High-Resolution Airborne Remote Sensing to Study Aerosol Near Clouds

NASA Technical Reports Server (NTRS)

Levy, Robert; Munchak, Leigh; Mattoo, Shana; Marshak, Alexander; Wilcox, Eric; Gao, Lan; Yorks, John; Platnick, Steven

2016-01-01

The horizontal space in between clear and cloudy air is very complex. This so-called twilight zone includes activated aerosols that are not quite clouds, thin cloud fragments that are not easily observable, and dying clouds that have not quite disappeared. This is a huge challenge for satellite remote sensing, specifically for retrieval of aerosol properties. Identifying what is cloud versus what is not cloud is critically important for attributing radiative effects and forcings to aerosols. At the same time, the radiative interactions between clouds and the surrounding media (molecules, surface and aerosols themselves) will contaminate retrieval of aerosol properties, even in clear skies. Most studies on aerosol cloud interactions are relevant to moderate resolution imagery (e.g. 500 m) from sensors such as MODIS. Since standard aerosol retrieval algorithms tend to keep a distance (e.g. 1 km) from the nearest detected cloud, it is impossible to evaluate what happens closer to the cloud. During Studies of Emissions, Atmospheric Composition, Clouds and Climate Coupling by Regional Surveys (SEAC4RS), the NASA ER-2 flew with the enhanced MODIS Airborne Simulator (eMAS), providing MODIS-like spectral observations at high (50 m) spatial resolution. We have applied MODIS-like aerosol retrieval for the eMAS data, providing new detail to characterization of aerosol near clouds. Interpretation and evaluation of these eMAS aerosol retrievals is aided by independent MODIS-like cloud retrievals, as well as profiles from the co-flying Cloud Physics Lidar (CPL). Understanding aerosolcloud retrieval at high resolution will lead to better characterization and interpretation of long-term, global products from lower resolution (e.g.MODIS) satellite retrievals.

NASA Blue Marble 2007 West

NASA Image and Video Library

2010-03-12

RELEASE DATE: OCTOBER 9, 2007 Credit: NASA/Goddard Space Flight Center/Reto Stöckli A day’s clouds. The shape and texture of the land. The living ocean. City lights as a beacon of human presence across the globe. This amazingly beautiful view of Earth from space is a fusion of science and art, a showcase for the remote-sensing technology that makes such views possible, and a testament to the passion and creativity of the scientists who devote their careers to understanding how land, ocean, and atmosphere—even life itself—interact to generate Earth’s unique (as far as we know!) life-sustaining environment. Drawing on data from multiple satellite missions (not all collected at the same time), a team of NASA scientists and graphic artists created layers of global data for everything from the land surface, to polar sea ice, to the light reflected by the chlorophyll in the billions of microscopic plants that grow in the ocean. They wrapped these layers around a globe, set it against a black background, and simulated the hazy edge of the Earth’s atmosphere (the limb) that appears in astronaut photography of the Earth. The land surface layer is based on photo-like surface reflectance observations (reflected sunlight) measured by the Moderate Resolution Imaging Spectroradiometer (MODIS) on NASA’s Terra satellite in July 2004. The sea ice layer near the poles comes from Terra MODIS observations of daytime sea ice observed between August 28 and September 6, 2001. The ocean layer is a composite. In shallow water areas, the layer shows surface reflectances observed by Terra MODIS in July 2004. In the open ocean, the photo-like layer is overlaid with observations of the average ocean chlorophyll content for 2004. NASA’s Aqua MODIS collected the chlorophyll data. The cloud layer shows a single-day snapshot of clouds observed by Terra MODIS across the planet on July 29, 2001. City lights on Earth’s night side are visualized from data collected by the Defense Meteorological Satellite Program mission between 1994–1995. The topography layer is based on radar data collected by the Space Shuttle Endeavour during an 11-day mission in February of 2000. Topography over Antarctica comes from the Radarsat Antarctic Mapping Project, version 2. Most of the data layers in this visualization are available as monthly composites as part of NASA’s Blue Marble Next Generation image collection. The images in the collection appear in cylindrical projection (rectangular maps), and they are available at 500-meter resolution. The large images provided above are the full-size versions of these globes. In their hope that these images will inspire people to appreciate the beauty of our home planet and to learn about the Earth system, the developers of these images encourage readers to re-use and re-publish the images freely. NASA images by Reto Stöckli, based on data from NASA and NOAA. To learn the history of the Blue Marble go here: earthobservatory.nasa.gov/Features/BlueMarble/BlueMarble_... To learn more about the Blue Marble go here: earthobservatory.nasa.gov/IOTD/view.php?id=8108 NASA Goddard Space Flight Center is home to the nation's largest organization of combined scientists, engineers and technologists that build spacecraft, instruments and new technology to study the Earth, the sun, our solar system, and the universe. Follow us on Twitter Join us on Facebook

Evaluation and Validation of Updated MODIS C6 and VIIRS LAI/FPAR

NASA Astrophysics Data System (ADS)

Yan, K.; Park, T.; Chen, C.; Yang, B.; Yan, G.; Knyazikhin, Y.; Myneni, R. B.; CHOI, S.

2015-12-01

Leaf Area Index (LAI) and Fraction of Photosynthetically Active Radiation (0.4-0.7 μm) absorbed by vegetation (FPAR) play a key role in characterizing vegetation canopy functioning and energy absorption capacity. With radiative transfer realization, MODIS onboard NASA EOS Terra and Aqua satellites has provided globally continuous LAI/FPAR since 2000 and continuously updated the products with better quality. And NPP VIIRS shows the measurement capability to extend high-quality LAI/FPAR time series data records as a successor of MODIS. The primary objectives of this study are 1) to evaluate and validate newly updated MODIS Collection 6 (C6) LAI/FPAR product which has finer resolution (500m) and improved biome type input, and 2) to examine and adjust VIIRS LAI/FPAR algorithm for continuity with MODIS'. For MODIS C6 investigation, we basically measure the spatial coverage (i.e., main radiative transfer algorithm execution), continuity and consistency with Collection 5 (C5), and accuracy with field measured LAI/FPAR. And we also validate C6 LAI/FPAR via comparing other possible global LAI/FPAR products (e.g., GLASS and CYCLOPES) and capturing co-varying seasonal signatures with climatic variables (e.g., temperature and precipitation). For VIIRS evaluation and adjustment, we first quantify possible difference between C5 and MODIS heritage based VIIRS LAI/FPAR. Then based on the radiative transfer theory of canopy spectral invariants, we find VIIRS- and biome-specific configurable parameters (single scattering albedo and uncertainty). These two practices for MODIS C6 and VIIRS LAI/FPAR products clearly suggest that (a) MODIS C6 has better coverage and accuracy than C5, (b) C6 shows consistent spatiotemporal pattern with C5, (c) VIIRS has the potential for producing MODIS-like global LAI/FPAR Earth System Data Records.

An Evaluation of Marine Boundary Layer Cloud Property Simulations in the Community Atmosphere Model Using Satellite Observations: Conventional Subgrid Parameterization versus CLUBB

DOE Office of Scientific and Technical Information (OSTI.GOV)

Song, Hua; Zhang, Zhibo; Ma, Po-Lun

This paper presents a two-step evaluation of the marine boundary layer (MBL) cloud properties from two Community Atmospheric Model (version 5.3, CAM5) simulations, one based on the CAM5 standard parameterization schemes (CAM5-Base), and the other on the Cloud Layers Unified By Binormals (CLUBB) scheme (CAM5-CLUBB). In the first step, we compare the cloud properties directly from model outputs between the two simulations. We find that the CAM5-CLUBB run produces more MBL clouds in the tropical and subtropical large-scale descending regions. Moreover, the stratocumulus (Sc) to cumulus (Cu) cloud regime transition is much smoother in CAM5-CLUBB than in CAM5-Base. In addition,more » in CAM5-Base we find some grid cells with very small low cloud fraction (<20%) to have very high in-cloud water content (mixing ratio up to 400mg/kg). We find no such grid cells in the CAM5-CLUBB run. However, we also note that both simulations, especially CAM5-CLUBB, produce a significant amount of “empty” low cloud cells with significant cloud fraction (up to 70%) and near-zero in-cloud water content. In the second step, we use satellite observations from CERES, MODIS and CloudSat to evaluate the simulated MBL cloud properties by employing the COSP satellite simulators. We note that a feature of the COSP-MODIS simulator to mimic the minimum detection threshold of MODIS cloud masking removes much more low clouds from CAM5-CLUBB than it does from CAM5-Base. This leads to a surprising result — in the large-scale descending regions CAM5-CLUBB has a smaller COSP-MODIS cloud fraction and weaker shortwave cloud radiative forcing than CAM5-Base. A sensitivity study suggests that this is because CAM5-CLUBB suffers more from the above-mentioned “empty” clouds issue than CAM5-Base. The COSP-MODIS cloud droplet effective radius in CAM5-CLUBB shows a spatial increase from coastal St toward Cu, which is in qualitative agreement with MODIS observations. In contrast, COSP-MODIS cloud droplet effective radius in CAM5-Base almost remains a constant. In comparison with CloudSat observations, the histogram of the radar reflectivity from modeled MBL clouds is too narrow without a distinct separation between cloud and drizzle modes. Moreover, the probability of drizzle in both simulations is almost twice as high as the observation. Future studies are needed to understand the causes of these differences and their potential connection with the “empty” cloud issues in the model.« less

Evaluation of Enhanced High Resolution MODIS/AMSR-E SSTs and the Impact on Regional Weather Forecast

NASA Technical Reports Server (NTRS)

Schiferl, Luke D.; Fuell, Kevin K.; Case, Jonathan L.; Jedlovec, Gary J.

2010-01-01

Over the last few years, the NASA Short-term Prediction Research and Transition (SPoRT) Center has been generating a 1-km sea surface temperature (SST) composite derived from retrievals of the Moderate Resolution Imaging Spectroradiometer (MODIS) for use in operational diagnostics and regional model initialization. With the assumption that the day-to-day variation in the SST is nominal, individual MODIS passes aboard the Earth Observing System (EOS) Aqua and Terra satellites are used to create and update four composite SST products each day at 0400, 0700, 1600, and 1900 UTC, valid over the western Atlantic and Caribbean waters. A six month study from February to August 2007 over the marine areas surrounding southern Florida was conducted to compare the use of the MODIS SST composite versus the Real-Time Global SST analysis to initialize the Weather Research and Forecasting (WRF) model. Substantial changes in the forecast heat fluxes were seen at times in the marine boundary layer, but relatively little overall improvement was measured in the sensible weather elements. The limited improvement in the WRF model forecasts could be attributed to the diurnal changes in SST seen in the MODIS SST composites but not accounted for by the model. Furthermore, cloud contamination caused extended periods when individual passes of MODIS were unable to update the SSTs, leading to substantial SST latency and a cool bias during the early summer months. In order to alleviate the latency problems, the SPoRT Center recently enhanced its MODIS SST composite by incorporating information from the Advanced Microwave Scanning Radiometer-EOS (AMSR-E) instruments as well as the Operational Sea Surface Temperature and Sea Ice Analysis. These enhancements substantially decreased the latency due to cloud cover and improved the bias and correlation of the composites at available marine point observations. While these enhancements improved upon the modeled cold bias using the original MODIS SSTs, the discernable impacts on the WRF model were still somewhat limited. This paper explores several factors that may have contributed to this result. First, the original methodology to initialize the model used the most recent SST composite available in a hypothetical real ]time configuration, often matching the forecast initial time with an SST field that was 5-8 hours offset. To minimize the differences that result from the diurnal variations in SST, the previous day fs SST composite is incorporated at a time closest to the model initialization hour (e.g. 1600 UTC composite at 1500 UTC model initialization). Second, the diurnal change seen in the MODIS SST composites was not represented by the WRF model in previous simulations, since the SSTs were held constant throughout the model integration. To address this issue, we explore the use of a water skin-temperature diurnal cycle prediction capability within v3.1 of the WRF model to better represent fluctuations in marine surface forcing. Finally, the verification of the WRF model is limited to very few over-water sites, many of which are located near the coastlines. In order to measure the open ocean improvements from the AMSR-E, we could use an independent 2-dimensional, satellite-derived data set to validate the forecast model by applying an object-based verification method. Such a validation technique could aid in better understanding the benefits of the mesoscale SST spatial structure to regional models applications.

Land surface temperature measurements from EOS MODIS data

NASA Technical Reports Server (NTRS)

Wan, Zhengming

1993-01-01

The task objectives of this reporting phase included: (1) completing the draft of the LST Algorithms Theoretical Basic Document by July 30, 1993; (2) making a detailed characterization of the thermal infrared measurement system including spectrometer, blackbody, and radiation sources; (3) making TIR spectral measurements of water and snow-cover surfaces with the MIDAC M2401 spectrometer; and (4) making conceptual and engineering design of an accessory system for spectrometric measurements at variable angles. These objectives are based on the requirements by the MODIS Science Team and the unique challenge in the development of MODIS LST algorithms: to acquire accurate spectral emissivity data of land covers in the near-term and to make ground validations of the LST product in the long-term with a TIR measurement system.

MODIS Sees Hurricane Gonzalo

NASA Image and Video Library

2017-12-08

On Oct. 18 at 17:35 UTC (1:35 p.m EDT) the MODIS instrument aboard NASA's Aqua satellite saw Hurricane Gonzalo approaching Newfoundland. ..Credit: NASA Goddard MODIS Rapid Response Team..NASA image use policy. NASA Goddard Space Flight Center enables NASA’s mission through four scientific endeavors: Earth Science, Heliophysics, Solar System Exploration, and Astrophysics. Goddard plays a leading role in NASA’s accomplishments by contributing compelling scientific knowledge to advance the Agency’s mission. Follow us on Twitter Like us on Facebook Find us on Instagram

Impact of Lake Okeechobee Sea Surface Temperatures on Numerical Predictions of Summertime Convective Systems over South Florida

NASA Technical Reports Server (NTRS)

Case, Jonathan L.; Splitt, Michael E.; Fuell, Kevin K.; Santos, Pablo; Lazarus, Steven M.; Jedlovec, Gary J.

2009-01-01

The NASA Short-term Prediction Research and Transition (SPoRT) Center, the Florida Institute of Technology, and the NOAA/NWS Weather Forecast Office at Miami, FL (MFL) are collaborating on a project to investigate the impact of using high-resolution, 2-km Moderate Resolution Imaging Spectroradiometer (MODIS) sea surface temperature (SST) composites within the Weather Research and Forecasting (WRF) prediction system. The NWS MFL is currently running WRF in real-time to support daily forecast operations, using the National Centers for Environmental Prediction Nonhydrostatic Mesoscale Model dynamical core within the NWS Science and Training Resource Center's Environmental Modeling System (EMS) software. Twenty-seven hour forecasts are run daily initialized at 0300, 0900, 1500, and 2100 UTC on a domain with 4-km grid spacing covering the southern half of Florida and adjacent waters of the Gulf of Mexico and Atlantic Ocean. The SSTs are initialized with the NCEP Real-Time Global (RTG) analyses at 1/12deg resolution. The project objective is to determine whether more accurate specification of the lower-boundary forcing over water using the MODIS SST composites within the 4-km WRF runs will result in improved sea fluxes and hence, more accurate e\\olutiono f coastal mesoscale circulations and the associated sensible weather elements. SPoRT conducted parallel WRF EMS runs from February to August 2007 identical to the operational runs at NWS MFL except for the use of MODIS SST composites in place of the RTG product as the initial and boundary conditions over water. During the course of this evaluation, an intriguing case was examined from 6 May 2007, in which lake breezes and convection around Lake Okeechobee evolved quite differently when using the high-resolution SPoRT MODIS SST composites versus the lower-resolution RTG SSTs. This paper will analyze the differences in the 6 May simulations, as well as examine other cases from the summer 2007 in which the WRF-simulated Lake Okeechobee breezes evolved differently due to the SST initialization. The effects on wind fields and precipitation systems will be emphasized, including validation against surface mesonet observations and Stage IV precipitation grids.

Dust Transport, Deposition and Radiative Effects Observed from MODIS

NASA Technical Reports Server (NTRS)

Kaufman, Y. J.; Koren, I.; Remer, L. A.; Tanre, D.; Ginoux, P.; Fan, S.

2003-01-01

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. MODIS 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 MODIS 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 MODIS 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 Aqua 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 MODIS of 100 tg for the same latitude range and monthly period.

Land surface temperature over global deserts: Means, variability, and trends

NASA Astrophysics Data System (ADS)

Zhou, Chunlüe; Wang, Kaicun

2016-12-01

Land surface air temperature (LSAT) has been a widely used metric to study climate change. Weather observations of LSAT are the fundamental data for climate change studies and provide key evidence of global warming. However, there are very few meteorological observations over deserts due to their uninhabitable environment. This study fills this gap and provides independent evidence using satellite-derived land surface temperatures (LSTs), benefiting from their global coverage. The frequency of clear sky from MODerate Resolution Imaging Spectroradiometer (MODIS) LST data over global deserts was found to be greater than 94% for the 2002-2015 period. Our results show that MODIS LST has a bias of 1.36°C compared to ground-based observations collected at 31 U.S. Climate Reference Network (USCRN) stations, with a standard deviation of 1.83°C. After bias correction, MODIS LST was used to evaluate existing reanalyses, including ERA-Interim, Japanese 55-year Reanalysis (JRA-55), Modern-Era Retrospective Analysis for Research and Applications (MERRA), MERRA-land, National Centers for Environmental Prediction (NCEP)-R1, and NCEP-R2. The reanalyses accurately reproduce the seasonal cycle and interannual variability of the LSTs, but their multiyear means and trends of LSTs exhibit large uncertainties. The multiyear averaged LST over global deserts is 23.5°C from MODIS and varies from 20.8°C to 24.5°C in different reanalyses. The MODIS LST over global deserts increased by 0.25°C/decade from 2002 to 2015, whereas the reanalyses estimated a trend varying from -0.14 to 0.10°C/decade. The underestimation of the LST trend by the reanalyses occurs for approximately 70% of the global deserts, likely due to the imperfect performance of the reanalyses in reproducing natural climate variability.

Fire Monitoring from the New Generation of US Polar and Geostationary Satellites

NASA Astrophysics Data System (ADS)

Csiszar, I.; Justice, C. O.; Prins, E.; Schroeder, W.; Schmidt, C.; Giglio, L.

2012-04-01

Sensors on the new generation of US operational environmental satellites will provide measurements suitable for active fire detection and characterization. The NPOESS Preparatory Project (NPP) satellite, launched on October 28, 2011, carries the Visible Infrared Imager Radiometer Suite (VIIRS), which is expected to continue the active fire data record from the Moderate Resolution Imaging Spectroradiometer (MODIS) on the NASA Earth Observing System Terra and Aqua Satellites. Early evaluation of the VIIRS active fire product, including comparison to near-simultaneous MODIS data, is underway. The new generation of Geostationary Operational Environmental Satellite (GOES) series, starting with GOES-R to be launched in 2015, will carry the Advanced Baseline Imager (ABI), providing higher spatial and temporal resolution than the current GOES imager. The ABI will also include a dedicated band to provide radiance observations over a wider dynamic range to detect and characterize hot targets. In this presentation we discuss details of the monitoring capabilities from both VIIRS and ABI and the current status of the corresponding algorithm development and testing efforts. An integral part of this activity is explicit product validation, utilizing high resolution satellite and airborne imagery as reference data. The new capabilities also represent challenges to establish continuity with data records from heritage missions, and to coordinate compatible international missions towards a global multi-platform fire monitoring system. These objectives are pursued by the Fire Mapping and Monitoring Implementation Team of the Global Observation of Forest and Land Cover Dynamics (GOFC-GOLD) program, which also provides coordinated contribution to relevant initiatives by the Committee on Earth Observation Satellites (CEOS), the Coordination Group for Meteorological Satellites (CGMS) and the Global Climate Observing System (GCOS).

Estimation of time-series properties of gourd observed solar irradiance data using cloud properties derived from satellite observations

NASA Astrophysics Data System (ADS)

Watanabe, T.; Nohara, D.

2017-12-01

The shorter temporal scale variation in the downward solar irradiance at the ground level (DSI) is not understood well because researches in the shorter-scale variation in the DSI is based on the ground observation and ground observation stations are located coarsely. Use of dataset derived from satellite observation will overcome such defect. DSI data and MODIS cloud properties product are analyzed simultaneously. Three metrics: mean, standard deviation and sample entropy, are used to evaluate time-series properties of the DSI. Three metrics are computed from two-hours time-series centered at the observation time of MODIS over the ground observation stations. We apply the regression methods to design prediction models of each three metrics from cloud properties. The validation of the model accuracy show that mean and standard deviation are predicted with a higher degree of accuracy and that the accuracy of prediction of sample entropy, which represents the complexity of time-series, is not high. One of causes of lower prediction skill of sample entropy is the resolution of the MODIS cloud properties. Higher sample entropy is corresponding to the rapid fluctuation, which is caused by the small and unordered cloud. It seems that such clouds isn't retrieved well.

Comparison of CERES-MODIS cloud microphysical properties with surface observations over Loess Plateau

NASA Astrophysics Data System (ADS)

Yan, Hongru; Huang, Jianping; Minnis, Patrick; Yi, Yuhong; Sun-Mack, Sunny; Wang, Tianhe; Nakajima, Takashi Y.

2015-03-01

To enhance the utility of satellite-derived cloud properties for studying the role of clouds in climate change and the hydrological cycle in semi-arid areas, it is necessary to know their uncertainties. This paper estimates the uncertainties of several cloud properties by comparing those derived over the China Loess Plateau from the MODerate-resolution Imaging Spectroradiometer (MODIS) on Terra and Aqua by the Clouds and Earth's Radiant Energy System (CERES) with surface observations at the Semi-Arid Climate and Environment Observatory of Lanzhou University (SACOL). The comparisons use data from January 2008 to June 2010 limited to single layer and overcast stratus conditions during daytime. Cloud optical depths (τ) and liquid water paths (LWP) from both Terra and Aqua generally track the variation of the surface counterparts with modest correlation, while cloud effective radius (re) is only weakly correlated with the surface retrievals. The mean differences between Terra and the SACOL retrievals are -4.7±12.9, 2.1±3.2 μm and 30.2±85.3 g m-2 for τ, re and LWP, respectively. The corresponding differences for Aqua are 2.1±8.4, 1.2±2.9 μm and 47.4±79.6 g m-2, respectively. Possible causes for biases of satellite retrievals are discussed through statistical analysis and case studies. Generally, the CERES-MODIS cloud properties have a bit larger biases over the Loess Plateau than those in previous studies over other locations.

A Spatio-Temporal Approach for Global Validation and Analysis of MODIS Aerosol Products

NASA Technical Reports Server (NTRS)

Ichoku, Charles; Chu, D. Allen; Mattoo, Shana; Kaufman, Yoram J.; Remer, Lorraine A.; Tanre, Didier; Slutsker, Ilya; Holben, Brent N.; Lau, William K. M. (Technical Monitor)

2001-01-01

With the launch of the MODIS sensor on the Terra spacecraft, new data sets of the global distribution and properties of aerosol are being retrieved, and need to be validated and analyzed. A system has been put in place to generate spatial statistics (mean, standard deviation, direction and rate of spatial variation, and spatial correlation coefficient) of the MODIS aerosol parameters over more than 100 validation sites spread around the globe. Corresponding statistics are also computed from temporal subsets of AERONET-derived aerosol data. The means and standard deviations of identical parameters from MOMS and AERONET are compared. Although, their means compare favorably, their standard deviations reveal some influence of surface effects on the MODIS aerosol retrievals over land, especially at low aerosol loading. The direction and rate of spatial variation from MODIS are used to study the spatial distribution of aerosols at various locations either individually or comparatively. This paper introduces the methodology for generating and analyzing the data sets used by the two MODIS aerosol validation papers in this issue.

Application of a new leaf area index algorithm to China's landmass using MODIS data for carbon cycle research.

PubMed

Liu, R; Chen, J M; Liu, J; Deng, F; Sun, R

2007-11-01

An operational system was developed for mapping the leaf area index (LAI) for carbon cycle models from the moderate resolution imaging spectroradiometer (MODIS) data. The LAI retrieval algorithm is based on Deng et al. [2006. Algorithm for global leaf area index retrieval using satellite imagery. IEEE Transactions on Geoscience and Remote Sensing, 44, 2219-2229], which uses the 4-scale radiative transfer model [Chen, J.M., Leblancs, 1997. A 4-scale bidirectional reflection model based on canopy architecture. IEEE Transactions on Geoscience and Remote Sensing, 35, 1316-1337] to simulate the relationship of LAI with vegetated surface reflectance measured from space for various spectral bands and solar and view angles. This algorithm has been integrated to the MODISoft platform, a software system designed for processing MODIS data, to generate 250 m, 500 m and 1 km resolution LAI products covering all of China from MODIS MOD02 or MOD09 products. The multi-temporal interpolation method was implemented to remove the residual cloud and other noise in the final LAI product so that it can be directly used in carbon models without further processing. The retrieval uncertainties from land cover data were evaluated using five different data sets available in China. The results showed that mean LAI discrepancies can reach 27%. The current product was also compared with the NASA MODIS MOD15 LAI product to determine the agreement and disagreement of two different product series. LAI values in the MODIS product were found to be 21% larger than those in the new product. These LAI products were compared against ground TRAC measurements in forests in Qilian Mountain and Changbaishan. On average, the new LAI product agrees with the field measurement in Changbaishan within 2%, but the MODIS product is positively biased by about 20%. In Qilian Mountain, where forests are sparse, the new product is lower than field measurements by about 38%, while the MODIS product is larger by about 65%.

Variability of albedo and utility of the MODIS albedo product in forested wetlands

USGS Publications Warehouse

Sumner, David M.; Wu, Qinglong; Pathak, Chandra S.

2011-01-01

Albedo was monitored over a two-year period (beginning April 2008) at three forested wetland sites in Florida, USA using up- and down-ward facing pyranometers. Water level, above and below land surface, is the primary control on the temporal variability of daily albedo. Relatively low reflectivity of water accounts for the observed reductions in albedo with increased inundation of the forest floor. Enhanced canopy shading of the forest floor was responsible for lower sensitivity of albedo to water level at the most dense forest site. At one site, the most dramatic reduction in daily albedo was observed during the inundation of a highly-reflective, calcareous periphyton-covered land surface. Satellite-based Moderate-Resolution Imaging Spectroradiometer (MODIS) estimates of albedo compare favorably with measured albedo. Use of MODIS albedo values in net radiation computations introduced a root mean squared error of less than 4.7 W/m2 and a mean, annual bias of less than 2.3 W/m2 (1.7%). These results suggest that MODIS-estimated albedo values can reliably be used to capture areal and temporal variations in albedo that are important to the surface energy balance.

Multiplatform observations enabling albedo retrievals with high temporal resolution

NASA Astrophysics Data System (ADS)

Riihelä, Aku; Manninen, Terhikki; Key, Jeffrey; Sun, Qingsong; Sütterlin, Melanie; Lattanzio, Alessio; Schaaf, Crystal

2017-04-01

In this paper we show that combining observations from different polar orbiting satellite families (such as AVHRR and MODIS) is physically justifiable and technically feasible. Our proposed approach will lead to surface albedo retrievals at higher temporal resolution than the state of the art, with comparable or better accuracy. This study is carried out in the World Meteorological Organization (WMO) Sustained and coordinated processing of Environmental Satellite data for Climate Monitoring (SCOPE-CM) project SCM-02 (http://www.scope-cm.org/projects/scm-02/). Following a spectral homogenization of the Top-of-Atmosphere reflectances of bands 1 & 2 from AVHRR and MODIS, both observation datasets are atmospherically corrected with a coherent atmospheric profile and algorithm. The resulting surface reflectances are then fed into an inversion of the RossThick-LiSparse-Reciprocal surface bidirectional reflectance distribution function (BRDF) model. The results of the inversion (BRDF kernels) may then be integrated to estimate various surface albedo quantities. A key principle here is that the larger number of valid surface observations with multiple satellites allows us to invert the BRDF coefficients within a shorter time span, enabling the monitoring of relatively rapid surface phenomena such as snowmelt. The proposed multiplatform approach is expected to bring benefits in particular to the observation of the albedo of the polar regions, where persistent cloudiness and long atmospheric path lengths present challenges to satellite-based retrievals. Following a similar logic, the retrievals over tropical regions with high cloudiness should also benefit from the method. We present results from a demonstrator dataset of a global combined AVHRR-GAC and MODIS dataset covering the year 2010. The retrieved surface albedo is compared against quality-monitored in situ albedo observations from the Baseline Surface Radiation Network (BSRN). Additionally, the combined retrieval dataset is compared against MODIS C6 albedo/BRDF datasets to assess the quality of the multiplatform approach against current state of the art. This approach is not limited to AHVRR and MODIS observations. Provided that the spectral homogenization produces an acceptably good match, any instrument observing the Earth's surface in the visible and near-infrared wavelengths could, in principal, be included to further enhance the temporal resolution and accuracy of the retrievals. The SCOPE-CM initiative provides a potential framework for such expansion in the future.

New capabilities for characterizing smoke and dust aerosol over land using MODIS

NASA Astrophysics Data System (ADS)

Levy, R. C.; Remer, L. A.

2006-12-01

Smoke and dust aerosol have different chemical, optical and physical properties and both types affect many processes within the climate system. As earth's surface and atmosphere are continuously altered by natural and anthropogenic processes, the emission and presumably the effects of these aerosols are also changing. Thus it is necessary to observe and characterize aerosols on a global and climatic scale. While MODIS has been reporting characteristics of smoke and dust aerosol over land and ocean since shortly after Terra launch, the uncertainties in the over-land retrieval have been larger than expected. To better characterize different aerosol types closer to their source regions with greater accuracy, we have developed a new operational algorithm for retrieving aerosol properties over dark land surfaces from MODIS-observed visible (VIS) and infrared (IR) reflectance. Like earlier versions, this algorithm estimates the total loading (aerosol optical depth-τ) and relative weighting of fine (non-dust) and coarse (dust) -dominated aerosol to the total τ (fine weighting-η) over dark land surfaces. However, the fundamental mathematics and major assumptions have been overhauled. The new algorithm performs simultaneous multi-channel inversion that includes information about coarse aerosol in the IR channels, while assuming a fine-tuned relationship between VIS and IR surface reflectances, that is itself a function of scattering angle and vegetation condition. Finally, the suite of expected aerosol optical models described by the lookup table have been revised to closer resemble the AERONET climatology, including for smoke and dust aerosol. Beginning in April 2006, this algorithm has been used for forward processing and backward re- processing of the entire MODIS dataset observed from both Terra and Aqua. "Collection 5" products were completed for Aqua reprocessing by July 2006 and should be complete for Terra by December 2006. In this study, we used the complete Aqua dataset (July 2002-Aug 2006) and two years of Terra (2005-Aug 2006) data to evaluate the products in regions known to be dominated by smoke and/or dust. We compared with sunphotometer data at selected AERONET sites and found improved τ retrievals,within prescribed accuracy.

[Retrieval of the Optical Thickness and Cloud Top Height of Cirrus Clouds Based on AIRS IR High Spectral Resolution Data].

PubMed

Cao, Ya-nan; Wei, He-li; Dai, Cong-ming; Zhang, Xue-hai

2015-05-01

A study was carried out to retrieve optical thickness and cloud top height of cirrus clouds from the Atmospheric Infrared Sounder (AIRS) high spectral resolution data in 1070~1135 cm-1 IR band using a Combined Atmospheric Radiative Transfer model (CART) by brightness temperature difference between model simulation and AIRS observation. The research is based on AIRS LIB high spectral infrared observation data combined with Moderate Resolution Imaging Spectroradiometer (MODIS) cloud product data. Brightness temperature spectra based, on the retrieved cirrus optical thickness and cloud top height were simulated and compared with brightness temperature spectra of AIRS observation in the 650~1150 cm-1 band. The cirrus optical thickness and cloud top height retrieved were compared with brightness temperature of AIRS for channel 760 (900.56 cm-1, 11. 1 µm) and cirrus reflectance of MODIS cloud product. And cloud top height retrieved was compared with cloud top height from MODIS. Results show that the brightness temperature spectra simulated were basically consistent with AIRS observation under the condition of retrieval in the 650~1150 cm-1 band. It means that CART can be used to simulate AIRS brightness temperature spectra. The retrieved cirrus parameters are consistent with brightness temperature of AIRS for channel 11. 1 µm with low brightness temperature corresponding to large cirrus optical thickness and high cloud top height. And the retrieved cirrus parameters are consistent with cirrus reflectance of MODIS cloud product with high cirrus reflectance corresponding to large cirrus optical thickness and high cloud top height. Correlation coefficient of brightness temperature between retrieved cloud top height and MODIS cloud top height was relatively high. They are mostly located in the range of 8. 5~11.5 km, and their probability distribution trend is approximately identical. CART model is feasible to retrieve cirrus properties, and the retrieval is reliable.

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.

Moderate Imaging Resolution Spectroradiometer (MODIS) Aerosol Optical Depth Retrieval for Aerosol Radiative Forcing

NASA Astrophysics Data System (ADS)

Asmat, A.; Jalal, K. A.; Ahmad, N.

2018-02-01

The present study uses the Aerosol Optical Depth (AOD) retrieved from Moderate Imaging Resolution Spectroradiometer (MODIS) data for the period from January 2011 until December 2015 over an urban area in Kuching, Sarawak. The results show the minimum AOD value retrieved from MODIS is -0.06 and the maximum value is 6.0. High aerosol loading with high AOD value observed during dry seasons and low AOD monitored during wet seasons. Multi plane regression technique used to retrieve AOD from MODIS (AODMODIS) and different statistics parameter is proposed by using relative absolute error for accuracy assessment in spatial and temporal averaging approach. The AODMODIS then compared with AOD derived from Aerosol Robotic Network (AERONET) Sunphotometer (AODAERONET) and the results shows high correlation coefficient (R2) for AODMODIS and AODAERONET with 0.93. AODMODIS used as an input parameters into Santa Barbara Discrete Ordinate Radiative Transfer (SBDART) model to estimate urban radiative forcing at Kuching. The observed hourly averaged for urban radiative forcing is -0.12 Wm-2 for top of atmosphere (TOA), -2.13 Wm-2 at the surface and 2.00 Wm-2 in the atmosphere. There is a moderate relationship observed between urban radiative forcing calculated using SBDART and AERONET which are 0.75 at the surface, 0.65 at TOA and 0.56 in atmosphere. Overall, variation in AOD tends to cause large bias in the estimated urban radiative forcing.

Evaluation of the MODIS Aerosol Retrievals over Ocean and Land during CLAMS.

NASA Astrophysics Data System (ADS)

Levy, R. C.; Remer, L. A.; Martins, J. V.; Kaufman, Y. J.; Plana-Fattori, A.; Redemann, J.; Wenny, B.

2005-04-01

The Chesapeake Lighthouse Aircraft Measurements for Satellites (CLAMS) experiment took place from 10 July to 2 August 2001 in a combined ocean-land region that included the Chesapeake Lighthouse [Clouds and the Earth's Radiant Energy System (CERES) Ocean Validation Experiment (COVE)] and the Wallops Flight Facility (WFF), both along coastal Virginia. This experiment was designed mainly for validating instruments and algorithms aboard the Terra satellite platform, including the Moderate Resolution Imaging Spectroradiometer (MODIS). Over the ocean, MODIS retrieved aerosol optical depths (AODs) at seven wavelengths and an estimate of the aerosol size distribution. Over the land, MODIS retrieved AOD at three wavelengths plus qualitative estimates of the aerosol size. Temporally coincident measurements of aerosol properties were made with a variety of sun photometers from ground sites and airborne sites just above the surface. The set of sun photometers provided unprecedented spectral coverage from visible (VIS) to the solar near-infrared (NIR) and infrared (IR) wavelengths. In this study, AOD and aerosol size retrieved from MODIS is compared with similar measurements from the sun photometers. Over the nearby ocean, the MODIS AOD in the VIS and NIR correlated well with sun-photometer measurements, nearly fitting a one-to-one line on a scatterplot. As one moves from ocean to land, there is a pronounced discontinuity of the MODIS AOD, where MODIS compares poorly to the sun-photometer measurements. Especially in the blue wavelength, MODIS AOD is too high in clean aerosol conditions and too low under larger aerosol loadings. Using the Second Simulation of the Satellite Signal in the Solar Spectrum (6S) radiative code to perform atmospheric correction, the authors find inconsistency in the surface albedo assumptions used by the MODIS lookup tables. It is demonstrated how the high bias at low aerosol loadings can be corrected. By using updated urban/industrial aerosol climatology for the MODIS lookup table over land, it is shown that the low bias for larger aerosol loadings can also be corrected. Understanding and improving MODIS retrievals over the East Coast may point to strategies for correction in other locations, thus improving the global quality of MODIS. Improvements in regional aerosol detection could also lead to the use of MODIS for monitoring air pollution.

Maturity onset diabetes of the young (MODY)--history, first case reports and recent advances.

PubMed

Siddiqui, Khalid; Musambil, Mohthash; Nazir, Nyla

2015-01-15

The world is seemingly facing a global increase in people suffering from diabetes especially in developing countries. The worldwide occurrence of diabetes for all age groups in year 2000 was estimated to be 2.8% and this number is most certainly expected to rise to 4.4% by 2030. Maturity-onset of diabetes of the young, or MODY, is a form of monogenic diabetes that is caused by mutations occurring in a number of different genes. Mutations in different genes tend to cause a slightly different variant of diabetes. MODY is typically diagnosed during late childhood, adolescence, or early adulthood and is usually observed to develop in adults during their late 50's. One of the main drawbacks in its diagnosis is that many people with MODY are misdiagnosed as having type 1 or type 2 diabetes. However, a molecular and genetic diagnosis can result in a better treatment and could also help in identifying other family members with MODY. This article explores the historical prospect and the genetic background of MODY, a brief summary of the first case reported and the significant factors that differentiate it from type 1 and type 2 diabetes. Copyright © 2014 Elsevier B.V. All rights reserved.

Agreement evaluation of AVHRR and MODIS 16-day composite NDVI data sets

USGS Publications Warehouse

Ji, Lei; Gallo, Kevin P.; Eidenshink, Jeffery C.; Dwyer, John L.

2008-01-01

Satellite-derived normalized difference vegetation index (NDVI) data have been used extensively to detect and monitor vegetation conditions at regional and global levels. A combination of NDVI data sets derived from AVHRR and MODIS can be used to construct a long NDVI time series that may also be extended to VIIRS. Comparative analysis of NDVI data derived from AVHRR and MODIS is critical to understanding the data continuity through the time series. In this study, the AVHRR and MODIS 16-day composite NDVI products were compared using regression and agreement analysis methods. The analysis shows a high agreement between the AVHRR-NDVI and MODIS-NDVI observed from 2002 and 2003 for the conterminous United States, but the difference between the two data sets is appreciable. Twenty per cent of the total difference between the two data sets is due to systematic difference, with the remainder due to unsystematic difference. The systematic difference can be eliminated with a linear regression-based transformation between two data sets, and the unsystematic difference can be reduced partially by applying spatial filters to the data. We conclude that the continuity of NDVI time series from AVHRR to MODIS is satisfactory, but a linear transformation between the two sets is recommended.

Capability of Integrated MODIS Imagery and ALOS for Oil Palm, Rubber and Forest Areas Mapping in Tropical Forest Regions

PubMed Central

Razali, Sheriza Mohd; Marin, Arnaldo; Nuruddin, Ahmad Ainuddin; Shafri, Helmi Zulhaidi Mohd; Hamid, Hazandy Abdul

2014-01-01

Various classification methods have been applied for low resolution of the entire Earth's surface from recorded satellite images, but insufficient study has determined which method, for which satellite data, is economically viable for tropical forest land use mapping. This study employed Iterative Self Organizing Data Analysis Techniques (ISODATA) and K-Means classification techniques to classified Moderate Resolution Imaging Spectroradiometer (MODIS) Surface Reflectance satellite image into forests, oil palm groves, rubber plantations, mixed horticulture, mixed oil palm and rubber and mixed forest and rubber. Even though frequent cloud cover has been a challenge for mapping tropical forests, our MODIS land use classification map found that 2008 ISODATA-1 performed well with overall accuracy of 94%, with the highest Producer's Accuracy of Forest with 86%, and were consistent with MODIS Land Cover 2008 (MOD12Q1), respectively. The MODIS land use classification was able to distinguish young oil palm groves from open areas, rubber and mature oil palm plantations, on the Advanced Land Observing Satellite (ALOS) map, whereas rubber was more easily distinguished from an open area than from mixed rubber and forest. This study provides insight on the potential for integrating regional databases and temporal MODIS data, in order to map land use in tropical forest regions. PMID:24811079

Capability of integrated MODIS imagery and ALOS for oil palm, rubber and forest areas mapping in tropical forest regions.

PubMed

Razali, Sheriza Mohd; Marin, Arnaldo; Nuruddin, Ahmad Ainuddin; Shafri, Helmi Zulhaidi Mohd; Hamid, Hazandy Abdul

2014-05-07

Various classification methods have been applied for low resolution of the entire Earth's surface from recorded satellite images, but insufficient study has determined which method, for which satellite data, is economically viable for tropical forest land use mapping. This study employed Iterative Self Organizing Data Analysis Techniques (ISODATA) and K-Means classification techniques to classified Moderate Resolution Imaging Spectroradiometer (MODIS) Surface Reflectance satellite image into forests, oil palm groves, rubber plantations, mixed horticulture, mixed oil palm and rubber and mixed forest and rubber. Even though frequent cloud cover has been a challenge for mapping tropical forests, our MODIS land use classification map found that 2008 ISODATA-1 performed well with overall accuracy of 94%, with the highest Producer's Accuracy of Forest with 86%, and were consistent with MODIS Land Cover 2008 (MOD12Q1), respectively. The MODIS land use classification was able to distinguish young oil palm groves from open areas, rubber and mature oil palm plantations, on the Advanced Land Observing Satellite (ALOS) map, whereas rubber was more easily distinguished from an open area than from mixed rubber and forest. This study provides insight on the potential for integrating regional databases and temporal MODIS data, in order to map land use in tropical forest regions.

New Physical Algorithms for Downscaling SMAP Soil Moisture

NASA Astrophysics Data System (ADS)

Sadeghi, M.; Ghafari, E.; Babaeian, E.; Davary, K.; Farid, A.; Jones, S. B.; Tuller, M.

2017-12-01

The NASA Soil Moisture Active Passive (SMAP) mission provides new means for estimation of surface soil moisture at the global scale. However, for many hydrological and agricultural applications the spatial SMAP resolution is too low. To address this scale issue we fused SMAP data with MODIS observations to generate soil moisture maps at 1-km spatial resolution. In course of this study we have improved several existing empirical algorithms and introduced a new physical approach for downscaling SMAP data. The universal triangle/trapezoid model was applied to relate soil moisture to optical/thermal observations such as NDVI, land surface temperature and surface reflectance. These algorithms were evaluated with in situ data measured at 5-cm depth. Our results demonstrate that downscaling SMAP soil moisture data based on physical indicators of soil moisture derived from the MODIS satellite leads to higher accuracy than that achievable with empirical downscaling algorithms. Keywords: Soil moisture, microwave data, downscaling, MODIS, triangle/trapezoid model.

Use of MODIS Satellite Images and an Atmospheric Dust Transport Model to Evaluate Juniperus spp. Pollen Phenology and Dispersal

NASA Technical Reports Server (NTRS)

Luvall, J. C.; Sprigg, W. A.; Levetin, E.; Huete, A.; Nickovic, S.; Pejanovic, G. A.; Vukovic, A.; VandeWater, P. K.; Myers, O. B.; Budge, A. M.;

[Retrieve of red tide distributions from MODIS data based on the characteristics of water spectrum].

PubMed

Qiu, Zhong-Feng; Cui, Ting-Wei; He, Yi-Jun

2011-08-01

After comparing the spectral differences between red tide water and normal water, we developed a method to retrieve red tide distributions from MODIS data based on the characteristics of red tide water spectrum. The authors used the 119 series of in situ observations to validate the method and found that only one observation has not been detected correctly. The authors then applied this method to MODIS data on April 4, 2005. In the research areas three locations of red tide water were apparently detected with the total areas about 2 000 km2. The retrieved red tide distributions are in good agreement with the distributions of high chlorophyll a concentrations. The research suggests that the method is available to eliminating the influence of suspended sediments and can be used to retrieve the locations and areas of red tide water.

Resolving model parameter values from carbon and nitrogen stock measurements in a wide range of tropical mature forests using nonlinear inversion and regression trees

USGS Publications Warehouse

Liu, S.; Anderson, P.; Zhou, G.; Kauffman, B.; Hughes, F.; Schimel, D.; Watson, Vicente; Tosi, Joseph

2008-01-01

Objectively assessing the performance of a model and deriving model parameter values from observations are critical and challenging in landscape to regional modeling. In this paper, we applied a nonlinear inversion technique to calibrate the ecosystem model CENTURY against carbon (C) and nitrogen (N) stock measurements collected from 39 mature tropical forest sites in seven life zones in Costa Rica. Net primary productivity from the Moderate-Resolution Imaging Spectroradiometer (MODIS), C and N stocks in aboveground live biomass, litter, coarse woody debris (CWD), and in soils were used to calibrate the model. To investigate the resolution of available observations on the number of adjustable parameters, inversion was performed using nine setups of adjustable parameters. Statistics including observation sensitivity, parameter correlation coefficient, parameter sensitivity, and parameter confidence limits were used to evaluate the information content of observations, resolution of model parameters, and overall model performance. Results indicated that soil organic carbon content, soil nitrogen content, and total aboveground biomass carbon had the highest information contents, while measurements of carbon in litter and nitrogen in CWD contributed little to the parameter estimation processes. The available information could resolve the values of 2-4 parameters. Adjusting just one parameter resulted in under-fitting and unacceptable model performance, while adjusting five parameters simultaneously led to over-fitting. Results further indicated that the MODIS NPP values were compressed as compared with the spatial variability of net primary production (NPP) values inferred from inverse modeling. Using inverse modeling to infer NPP and other sensitive model parameters from C and N stock observations provides an opportunity to utilize data collected by national to regional forest inventory systems to reduce the uncertainties in the carbon cycle and generate valuable databases to validate and improve MODIS NPP algorithms.

Earth Observations for Early Detection of Agricultural Drought: Contributions of the Famine Early Warning Systems Network (FEWS NET)

NASA Astrophysics Data System (ADS)

Budde, M. E.; Funk, C.; Husak, G. J.; Peterson, P.; Rowland, J.; Senay, G. B.; Verdin, J. P.

2016-12-01

The U.S. Geological Survey (USGS) has a long history of supporting the use of Earth observation data for food security monitoring through its role as an implementing partner of the Famine Early Warning Systems Network (FEWS NET) program. The use of remote sensing and crop modeling to address food security threats in the form of drought, floods, pests, and changing climatic regimes has been a core activity in monitoring FEWS NET countries. In recent years, it has become a requirement that FEWS NET apply monitoring and modeling frameworks at global scales to assess emerging crises in regions that FEWS NET does not traditionally monitor. USGS FEWS NET, in collaboration with the University of California, Santa Barbara, has developed a number of new global applications of satellite observations, derived products, and efficient tools for visualization and analyses to address these requirements. (1) A 35-year quasi-global (+/- 50 degrees latitude) time series of gridded rainfall estimates, the Climate Hazards Infrared Precipitation with Stations (CHIRPS) dataset, based on infrared satellite imagery and station observations. Data are available as 5-day (pentadal) accumulations at 0.05 degree spatial resolution. (2) Global actual evapotranspiration data based on application of the Simplified Surface Energy Balance (SSEB) model using 10-day MODIS Land Surface Temperature composites at 1-km resolution. (3) Production of global expedited MODIS (eMODIS) 10-day NDVI composites updated every 5 days. (4) Development of an updated Early Warning eXplorer (EWX) tool for data visualization, analysis, and sharing. (5) Creation of stand-alone tools for enhancement of gridded rainfall data and trend analyses. (6) Establishment of an agro-climatology analysis tool and knowledge base for more than 90 countries of interest to FEWS NET. In addition to these new products and tools, FEWS NET has partnered with the GEOGLAM community to develop a Crop Monitor for Early Warning (CM4EW) which brings together global expertise in agricultural monitoring to reach consensus on growing season status of "countries at risk". Such engagements will result in enhanced capabilities for extending our monitoring efforts globally.

DEA-I: A Globally Configurable Open Source Software Package in Support of Air Quality Forecasts

NASA Astrophysics Data System (ADS)

Davies, J.; Strabala, K.; Pierce, R.; Huang, H.; Schiffer, E.

2012-12-01

During September 2003, a team of NASA, NOAA, and EPA researchers demonstrated a prototype for using Moderate Resolution Imaging Spectroradiometer (MODIS) aerosol optical depth retrievals in daily air quality forecasts; this became known as IDEA (Infusing satellite Data into Environmental Applications). IDEA was part of the NASA Applied Sciences Program strategy to demonstrate practical uses of NASA-sponsored observations from space and predictions. Following its successful demonstration an export version of IDEA, known as IDEA International (IDEA-I), has now been released. IDEA-I supports the Global Earth Observation Systems of Systems (GEOSS) Group on Earth Observations (GEO) Health Societal Benefit Area (SBA) and is being developed within the framework of the GEO Earth Observations in Decision Support Call for Proposals. The vehicle for IDEA-I release is the International MODIS and AIRS (Atmospheric Infrared Sounder) Processing Package (IMAPP), developed at the Space Science and Engineering Center, University of Wisconsin-Madison (SSEC/UW-Madison). IMAPP is a NASA-funded and freely-distributed software package which allows any ground station capable of receiving direct broadcast from Terra or Aqua to produce calibrated and geolocated radiances, and a suite of environmental products, of which the IDEA-I 48-hour forward trajectory prediction of high aerosol events is now a part. IDEA-I provides a tool for linking ground-based and satellite capabilities to support international air quality forecasting activities and is to be demonstrated internationally through user training and impact evaluation via a series of IMAPP workshops. This presentation describes the IMAPP implementation of IDEA-I in terms of its simple installation and configuration, and through examples of its operation in several regions known for periodic high aerosol events.; Screen capture of the University of Wisconsin implementation of the real-time direct broadcast IDEA-I Air Quality monitoring website. This example uses Terra MODIS Aerosol Optical Depth retrievals to identify regions of high aerosol concentrations. A trajectory model is then run that provide a forecast of the horizontal and vertical movement of the aerosols over the next 48 hours.

Estimating trace gas and aerosol emissions over South America: Relationship between fire radiative energy released and aerosol optical depth observations

NASA Astrophysics Data System (ADS)

Pereira, Gabriel; Freitas, Saulo R.; Moraes, Elisabete Caria; Ferreira, Nelson Jesus; Shimabukuro, Yosio Edemir; Rao, Vadlamudi Brahmananda; Longo, Karla M.

2009-12-01

Contemporary human activities such as tropical deforestation, land clearing for agriculture, pest control and grassland management lead to biomass burning, which in turn leads to land-cover changes. However, biomass burning emissions are not correctly measured and the methods to assess these emissions form a part of current research area. The traditional methods for estimating aerosols and trace gases released into the atmosphere generally use emission factors associated with fuel loading and moisture characteristics and other parameters that are hard to estimate in near real-time applications. In this paper, fire radiative power (FRP) products were extracted from Moderate Resolution Imaging Spectroradiometer (MODIS) and from the Geostationary Operational Environmental Satellites (GOES) fire products and new South America generic biomes FRE-based smoke aerosol emission coefficients were derived and applied in 2002 South America fire season. The inventory estimated by MODIS and GOES FRP measurements were included in Coupled Aerosol-Tracer Transport model coupled to the Brazilian developments on the Regional Atmospheric Modeling System (CATT-BRAMS) and evaluated with ground truth collected in Large Scale Biosphere-Atmosphere Smoke, Aerosols, Clouds, rainfall, and Climate (SMOCC) and Radiation, Cloud, and Climate Interactions (RaCCI). Although the linear regression showed that GOES FRP overestimates MODIS FRP observations, the use of a common external parameter such as MODIS aerosol optical depth product could minimize the difference between sensors. The relationship between the PM 2.5μm (Particulate Matter with diameter less than 2.5 μm) and CO (Carbon Monoxide) model shows a good agreement with SMOCC/RaCCI data in the general pattern of temporal evolution. The results showed high correlations, with values between 0.80 and 0.95 (significant at 0.5 level by student t test), for the CATT-BRAMS simulations with PM 2.5μm and CO.

Can MODIS detect trends in aerosol optical depth over land?

NASA Astrophysics Data System (ADS)

Fan, Xuehua; Xia, Xiang'ao; Chen, Hongbin

2018-02-01

The Moderate Resolution Imaging Spectroradiometer (MODIS) sensor onboard NASA's Aqua satellite has been collecting valuable data about the Earth system for more than 14 years, and one of the benefits of this is that it has made it possible to detect the long-term variation in aerosol loading across the globe. However, the long-term aerosol optical depth (AOD) trends derived from MODIS need careful validation and assessment, especially over land. Using AOD products with at least 70 months' worth of measurements collected during 2002-15 at 53 Aerosol Robotic Network (AERONET) sites over land, Mann-Kendall (MK) trends in AOD were derived and taken as the ground truth data for evaluating the corresponding results from MODIS onboard Aqua. The results showed that the AERONET AOD trends over all sites in Europe and North America, as well as most sites in Africa and Asia, can be reproduced by MODIS/Aqua. However, disagreement in AOD trends between MODIS and AERONET was found at a few sites in Australia and South America. The AOD trends calculated from AERONET instantaneous data at the MODIS overpass times were consistent with those from AERONET daily data, which suggests that the AOD trends derived from satellite measurements of 1-2 overpasses may be representative of those from daily measurements.

The impact of aerosol vertical distribution on aerosol optical depth retrieval using CALIPSO and MODIS data: Case study over dust and smoke regions

NASA Astrophysics Data System (ADS)

Wu, Yerong; de Graaf, Martin; Menenti, Massimo

2017-08-01

Global quantitative aerosol information has been derived from MODerate Resolution Imaging SpectroRadiometer (MODIS) observations for decades since early 2000 and widely used for air quality and climate change research. However, the operational MODIS Aerosol Optical Depth (AOD) products Collection 6 (C6) can still be biased, because of uncertainty in assumed aerosol optical properties and aerosol vertical distribution. This study investigates the impact of aerosol vertical distribution on the AOD retrieval. We developed a new algorithm by considering dynamic vertical profiles, which is an adaptation of MODIS C6 Dark Target (C6_DT) algorithm over land. The new algorithm makes use of the aerosol vertical profile extracted from Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO) measurements to generate an accurate top of the atmosphere (TOA) reflectance for the AOD retrieval, where the profile is assumed to be a single layer and represented as a Gaussian function with the mean height as single variable. To test the impact, a comparison was made between MODIS DT and Aerosol Robotic Network (AERONET) AOD, over dust and smoke regions. The results show that the aerosol vertical distribution has a strong impact on the AOD retrieval. The assumed aerosol layers close to the ground can negatively bias the retrievals in C6_DT. Regarding the evaluated smoke and dust layers, the new algorithm can improve the retrieval by reducing the negative biases by 3-5%.

Cloud Photogrammetry from Space

NASA Astrophysics Data System (ADS)

Zaksek, K.; Gerst, A.; von der Lieth, J.; Ganci, G.; Hort, M.

2015-04-01

The most commonly used method for satellite cloud top height (CTH) compares brightness temperature of the cloud with the atmospheric temperature profile. Because of the uncertainties of this method, we propose a photogrammetric approach. As clouds can move with high velocities, even instruments with multiple cameras are not appropriate for accurate CTH estimation. Here we present two solutions. The first is based on the parallax between data retrieved from geostationary (SEVIRI, HRV band; 1000 m spatial resolution) and polar orbiting satellites (MODIS, band 1; 250 m spatial resolution). The procedure works well if the data from both satellites are retrieved nearly simultaneously. However, MODIS does not retrieve the data at exactly the same time as SEVIRI. To compensate for advection in the atmosphere we use two sequential SEVIRI images (one before and one after the MODIS retrieval) and interpolate the cloud position from SEVIRI data to the time of MODIS retrieval. CTH is then estimated by intersection of corresponding lines-of-view from MODIS and interpolated SEVIRI data. The second method is based on NASA program Crew Earth observations from the International Space Station (ISS). The ISS has a lower orbit than most operational satellites, resulting in a shorter minimal time between two images, which is needed to produce a suitable parallax. In addition, images made by the ISS crew are taken by a full frame sensor and not a push broom scanner that most operational satellites use. Such data make it possible to observe also short time evolution of clouds.

Improving Scene Classifications with Combined Active/Passive Measurements

NASA Astrophysics Data System (ADS)

Hu, Y.; Rodier, S.; Vaughan, M.; McGill, M.

The uncertainties in cloud and aerosol physical properties derived from passive instruments such as MODIS are not insignificant And the uncertainty increases when the optical depths decrease Lidar observations do much better for the thin clouds and aerosols Unfortunately space-based lidar measurements such as the one onboard CALIPSO satellites are limited to nadir view only and thus have limited spatial coverage To produce climatologically meaningful thin cloud and aerosol data products it is necessary to combine the spatial coverage of MODIS with the highly sensitive CALIPSO lidar measurements Can we improving the quality of cloud and aerosol remote sensing data products by extending the knowledge about thin clouds and aerosols learned from CALIPSO-type of lidar measurements to a larger portion of the off-nadir MODIS-like multi-spectral pixels To answer the question we studied the collocated Cloud Physics Lidar CPL with Modis-Airborne-Simulation MAS observations and established an effective data fusion technique that will be applied in the combined CALIPSO MODIS cloud aerosol product algorithms This technique performs k-mean and Kohonen self-organized map cluster analysis on the entire swath of MAS data as well as on the combined CPL MAS data at the nadir track Interestingly the clusters generated from the two approaches are almost identical It indicates that the MAS multi-spectral data may have already captured most of the cloud and aerosol scene types such as cloud ice water phase multi-layer information aerosols

Ten Years of Cloud Properties from MODIS: Global Statistics and Use in Climate Model Evaluation

NASA Technical Reports Server (NTRS)

Platnick, Steven E.

2011-01-01

The NASA Moderate Resolution Imaging Spectroradiometer (MODIS), launched onboard the Terra and Aqua 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 MODIS Collection 5 cloud climatologies derived from global spatial . and temporal aggregations provided in the archived gridded Level-3 MODIS atmosphere team product (product names MOD08 and MYD08 for MODIS Terra and Aqua, 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 MODIS cloud properties, as well as the time required for detection given assumed trends. To assist in climate model evaluation, we have developed a MODIS 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.

Glucokinase MODY and implications for treatment goals of common forms of diabetes.

PubMed

Ajjan, Ramzi A; Owen, Katharine R

2014-12-01

Treatment goals in diabetes concentrate on reducing the risk of vascular complications, largely through setting targets for glycated haemoglobin (HbA1c). These targets are based on epidemiological studies of complication development, but so far have not adequately addressed the adverse effects associated with lowering HbA1c towards the normal range. Glucokinase (GCK) mutations cause a monogenic form of hyperglycaemia (GCK-MODY) characterised by fasting hyperglycaemia with low postprandial glucose excursions and a marginally elevated HbA1c. Minimal levels of vascular complications (comparable with nondiabetic individuals) are observed in GCK-MODY, leading to the hypothesis that GCK-MODY may represent a useful paradigm for assessing treatment goals in all forms of diabetes. In this review, we discuss the evidence behind this concept, suggest ways of translating this hypothesis into clinical practice and address some of the caveats of such an approach.

Validation of satellite-retrieved MBL cloud properties using DOE ARM AMF measurements at the Azores

NASA Astrophysics Data System (ADS)

Xi, B.; Dong, X.; Minnis, P.; Sun-Mack, S.

2013-05-01

Marine Boundary Layer (MBL) cloud properties derived for the Clouds and the Earth's Radiant Energy System (CERES) Project using Terra and Aqua Moderate Resolution Imaging Spectroradiometer (MODIS) data are compared with observations taken at the Atmospheric Radiation Measurement (ARM) AMF AZORES site from June 2009 through December 2010. Retrievals from ARM surface-based data were averaged over a 1-hour interval centered at the time of each satellite overpass, and the CERES-MODIS Ed4 cloud properties were averaged within a 30-km x 30-km box centered on the ARM AZORES site. Two datasets were analyzed: all of the single-layered unbroken decks (SL) and those cases without temperature inversions. The CERES-MODIS cloud top/base heights were determined from cloud top/base temperature by using a lapse rate method normalized to the 24-h mean surface air temperature. The preliminary results show: for all SL MBL at daytime, they are, on average, 0.148 km (cloud top) and 0.087 km (cloud base) higher than the ARM radar-lidar observed cloud top and base, respectively. At nighttime, they are 0.446 km (cloud top) and 0.334 km (cloud base). For those cases without temperature inversions, the comparisons are close to their SL counterparts. For cloud temperatures, the MODIS-derived cloud-top and -base temperatures are 1.6 K lower and 0.4 K higher than the surface values with correlations of 0.92 during daytime. At nighttime, the differences are slightly larger and correlations are lower than daytime comparisons. Variations in the height difference are mainly caused by uncertainties in the surface air temperatures and lapse rates. Based on a total of 61 daytime and 87 nighttime samples (ALL SL cases), the temperature inversion layers occur about 72% during daytime and 83% during nighttime. The difference of surface-observed lapse rate and the satellite derived lapse rate can be 1.6 K/km for daytime and 3.3K/km for nighttime. From these lapse rates, we can further analyze the surface air temperature difference that used to calculate these lapse rate, which are ~3K difference between surface-observed and the satellite derived during the daytime and 5.1 K during nighttime. Further studies of the cause of the temperature inversions that may help the cloud heights retrievals by satellite. The preliminary comparisons in MBL microphysical properties have shown that the averaged CERES-MODIS derived MBL cloud-droplet effective radius is only 1.5 μm larger than ARM retrieval (13.2 μm), and LWP values are also very close to each other (112 vs. 124 gm-2) with a relative large difference in optical depth (10.6 vs. 14.4).

Clouds and the Earth's Radiant Energy System (CERES) Data Products for Climate Research

NASA Technical Reports Server (NTRS)

Kato, Seiji; Loeb, Norman G.; Rutan, David A.; Rose, Fred G.

2015-01-01

NASA's Clouds and the Earth's Radiant Energy System (CERES) project integrates CERES, Moderate Resolution Imaging Spectroradiometer (MODIS), and geostationary satellite observations to provide top-of-atmosphere (TOA) irradiances derived from broadband radiance observations by CERES instruments. It also uses snow cover and sea ice extent retrieved from microwave instruments as well as thermodynamic variables from reanalysis. In addition, these variables are used for surface and atmospheric irradiance computations. The CERES project provides TOA, surface, and atmospheric irradiances in various spatial and temporal resolutions. These data sets are for climate research and evaluation of climate models. Long-term observations are required to understand how the Earth system responds to radiative forcing. A simple model is used to estimate the time to detect trends in TOA reflected shortwave and emitted longwave irradiances.

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

NASA Technical Reports Server (NTRS)

Guo, Yanjuan; Tian, Baijun; Kahn, Ralph A.; Kalashnikova, Olga; Wong, Sun; Waliser, Duane E.

2012-01-01

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

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

NASA Technical Reports Server (NTRS)

Lyapustin, A.; Wang, Y.; Laszlo, I.; Hilker, T.; Hall, F.; Sellers, P.; Tucker, J.; Korkin, S.

2012-01-01

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

Evaluation of MODIS aerosol optical depth for semi­-arid environments in complex terrain

NASA Astrophysics Data System (ADS)

Holmes, H.; Loria Salazar, S. M.; Panorska, A. K.; Arnott, W. P.; Barnard, J.

2015-12-01

The use of satellite remote sensing to estimate spatially resolved ground level air pollutant concentrations is increasing due to advancements in remote sensing technology and the limited number of surface observations. Satellite retrievals provide global, spatiotemporal air quality information and are used to track plumes, estimate human exposures, model emissions, and determine sources (i.e., natural versus anthropogenic) in regulatory applications. Ground level PM2.5 concentrations can be estimated using columnar aerosol optical depth (AOD) from MODIS, where the satellite retrieval serves as a spatial surrogate to simulate surface PM2.5 gradients. The spatial statistical models and MODIS AOD retrieval algorithms have been evaluated for the dark, vegetated eastern US, while the semi-arid western US continues to be an understudied region with associated complexity due to heterogeneous emissions, smoke from wildfires, and complex terrain. The objective of this work is to evaluate the uncertainty of MODIS AOD retrievals by comparing with columnar AOD and surface PM2.5 measurements from AERONET and EPA networks. Data is analyzed from multiple stations in California and Nevada for three years where four major wildfires occurred. Results indicate that MODIS retrievals fail to estimate column-integrated aerosol pollution in the summer months. This is further investigated by quantifying the statistical relationships between MODIS AOD, AERONET AOD, and surface PM2.5 concentrations. Data analysis indicates that the distribution of MODIS AOD is significantly (p<0.05) different than AERONET AOD. Further, using the results of distributional and association analysis the impacts of MODIS AOD uncertainties on the spatial gradients are evaluated. Additionally, the relationships between these uncertainties and physical parameters in the retrieval algorithm (e.g., surface reflectance, Ångström Extinction Exponent) are discussed.

System for Continuous Delivery of MODIS Imagery to Internet Mapping Applications

NASA Technical Reports Server (NTRS)

Plesea, Lucian

2008-01-01

This software represents a complete, unsupervised processing chain that generates a continuously updating global image of the Earth from the most recent available MODIS Level 1B scenes. The software constantly updates a global image of the Earth at 250 m per pixel.

Retrievals of Profiles of Fine And Coarse Aerosols Using Lidar And Radiometric Space Measurements

NASA Technical Reports Server (NTRS)

Kaufman, Yoram; Tanre, Didier; Leon, Jean-Francois; Pelon, Jacques; Lau, William K. M. (Technical Monitor)

2002-01-01

In couple of years we expect the launch of the CALIPSO lidar spaceborne mission designed to observe aerosols and clouds. CALIPSO will collect profiles of the lidar attenuated backscattering coefficients in two spectral wavelengths (0.53 and 1.06 microns). Observations are provided along the track of the satellite around the globe from pole to pole. The attenuated backscattering coefficients are sensitive to the vertical distribution of aerosol particles, their shape and size. However the information is insufficient to be mapped into unique aerosol physical properties and vertical distribution. Infinite number of physical solutions can reconstruct the same two wavelength backscattered profile measured from space. CALIPSO will fly in formation with the Aqua satellite and the MODIS spectro-radiometer on board. Spectral radiances measured by MODIS in six channels between 0.55 and 2.13 microns simultaneously with the CALIPSO observations can constrain the solutions and resolve this ambiguity, albeit under some assumptions. In this paper we describe the inversion method and apply it to aircraft lidar and MODIS data collected over a dust storm off the coast of West Africa during the SHADE experiment. It is shown that the product of the single scattering albedo, omega, and the phase function, P, for backscattering can be retrieved from the synergism between measurements avoiding a priori hypotheses required for inverting lidar measurements alone. The resultant value of (omega)P(180 deg.) = 0.016/sr are significantly different from what is expected using Mie theory, but are in good agreement with recent results obtained from lidar observations of dust episodes. The inversion is robust in the presence of noise of 10% and 20% in the lidar signal in the 0.53 and 1.06 pm channels respectively. Calibration errors of the lidar of 5 to 10% can cause an error in optical thickness of 20 to 40% respectively in the tested cases. The lidar calibration errors cause degradation in the ability to fit the MODIS data. Therefore the MODIS measurements can be used to identify the calibration problem and correct for it. The CALIPSO-MODIS measurements of the profiles of fine and coarse aerosols, together with CALIPSO measurements of clouds vertical distribution, is expected to be critically important in understanding aerosol transport across continents and political boundaries, and to study aerosol-cloud interaction and its effect on precipitation and global forcing of climate.

Spatial and Temporal Analysis of Winter Fog Episodes over South Asia by exploiting ground-based and satellite observations

NASA Astrophysics Data System (ADS)

Fahim Khokhar, Muhammad; Yasmin, Naila; Zaib, Naila; Murtaza, Rabia; Noreen, Asma; Ishtiaq, Hira; Khayyam, Junaid; Panday, Arnico

2016-04-01

The South Asian region in general and the Indo-Gangetic Plains (IGP) in particular hold about 1/6th of the world's population and is considered as one of the major hotspots with increasing air pollution. Due to growing population and globalization, South Asia is experiencing high transformations in the urban and industrial sectors. Fog is one of the meteorological/environmental phenomena which can generate significant social and economic problems especially havoc to air and road traffic. Meteorological stations provide information about the fog episodes only on the basis of point observation. Continuous monitoring as well as a spatially coherent picture of fog distribution can only be possible through the use of satellite imagery. Current study focus on winter fog episodes over South Asian region using Moderate Resolution Image Spectrometer (MODIS) Level 2 Terra Product and other MODIS Aerosol Product in addition to ground-based sampling and AERONET measurements. MODIS Corrected Reflectance RGBs are used to analyse the spatial extent of fog over study area. MOD04 level 2 Collection 6 data is used to study aerosol load and distribution which are further characterised by using aerosol type land product of MODIS. In order to study the variation of ground based observations from satellite data MODIS, AERONET and high volume air Sampler were used. Main objective of this study was to explore the spatial extent of fog, its causes and to analyse the Aerosol Optical Depth (AOD) over South Asia with particular focus over Indo-Gangetic Plains (IGP). Current studies show a descent increase in AOD from past few decades over South Asia and is contributing to poor air quality in the region due to growing population, urbanization, and industrialization. Smoke and absorbing aerosol are major constituent of fog over South Asia. Furthermore, winter 2014-15 extended span of Fog was also observed over South Asia. A significant correlation between MODIS (AOD) and AERONET Station (AOD) data was identified. Mass concentration of PM2.5 and PM10 over sampling sites exceeded the Pak-NEQS at most occasions. However, during the current winter of 2015-16 the number of fog days has substantially reduced. Although, reasons are not clear yet but may be attributed to the atmospheric changes induced by the onset El-NINO.

[Monitoring "green tide" in the Yellow Sea and the East China Sea using multi-temporal and multi-source remote sensing images].

PubMed

Xing, Qian-Guo; Zheng, Xiang-Yang; Shi, Ping; Hao, Jia-Jia; Yu, Ding-Feng; Liang, Shou-Zhen; Liu, Dong-Yan; Zhang, Yuan-Zhi

2011-06-01

Landsat-TM (Theme Mapper) and EOS (Earth Observing System)-MODIS (MODerate resolution Imaging Spectrora-diometer) Terra/Aqua images were used to monitor the macro-algae (Ulva prolifera) bloom since 2007 at the Yellow Sea and the East China Sea. At the turbid waters of Northern Jiangsu Shoal, there is strong spectral mixing behavior, and satellite images with finer spatical resolution are more effective in detection of macro-algae patches. Macro-algae patches were detected by the Landsat images for the first time at the Sheyang estuary where is dominated by very turbid waters. The MODIS images showed that the macro-algae from the turbid waters near the Northern Jiangsu Shoal drifted southwardly in the early of May and affected the East China Sea waters; with the strengthening east-asian Summer Monsoon, macro-algae patches mainly drifted in a northward path which was mostly observed at the Yellow Sea. Macro-algae patches were also found to drift eastwardly towards the Korea Peninsular, which are supposed to be driven by the sea surface wind.

LSA SAF Meteosat FRP Products: Part 2 - Evaluation and demonstration of use in the Copernicus Atmosphere Monitoring Service (CAMS)

NASA Astrophysics Data System (ADS)

Roberts, G.; Wooster, M. J.; Xu, W.; Freeborn, P. H.; Morcrette, J.-J.; Jones, L.; Benedetti, A.; Kaiser, J.

2015-06-01

Characterising the dynamics of landscape scale wildfires at very high temporal resolutions is best achieved using observations from Earth Observation (EO) sensors mounted onboard geostationary satellites. As a result, a number of operational active fire products have been developed from the data of such sensors. An example of which are the Fire Radiative Power (FRP) products, the FRP-PIXEL and FRP-GRID products, generated by the Land Surface Analysis Satellite Applications Facility (LSA SAF) from imagery collected by the Spinning Enhanced Visible and Infrared Imager (SEVIRI) on-board the Meteosat Second Generation (MSG) series of geostationary EO satellites. The processing chain developed to deliver these FRP products detects SEVIRI pixels containing actively burning fires and characterises their FRP output across four geographic regions covering Europe, part of South America and northern and southern Africa. The FRP-PIXEL product contains the highest spatial and temporal resolution FRP dataset, whilst the FRP-GRID product contains a spatio-temporal summary that includes bias adjustments for cloud cover and the non-detection of low FRP fire pixels. Here we evaluate these two products against active fire data collected by the Moderate Resolution Imaging Spectroradiometer (MODIS), and compare the results to those for three alternative active fire products derived from SEVIRI imagery. The FRP-PIXEL product is shown to detect a substantially greater number of active fire pixels than do alternative SEVIRI-based products, and comparison to MODIS on a per-fire basis indicates a strong agreement and low bias in terms of FRP values. However, low FRP fire pixels remain undetected by SEVIRI, with errors of active fire pixel detection commission and omission compared to MODIS ranging between 9-13 and 65-77% respectively in Africa. Higher errors of omission result in greater underestimation of regional FRP totals relative to those derived from simultaneously collected MODIS data, ranging from 35% over the Northern Africa region to 89% over the European region. High errors of active fire omission and FRP underestimation are found over Europe and South America, and result from SEVIRI's larger pixel area over these regions. An advantage of using FRP for characterising wildfire emissions is the ability to do so very frequently and in near real time (NRT). To illustrate the potential of this approach, wildfire fuel consumption rates derived from the SEVIRI FRP-PIXEL product are used to characterise smoke emissions of the 2007 Peloponnese wildfires within the European Centre for Medium-Range Weather Forecasting (ECMWF) Integrated Forecasting System (IFS), as a demonstration of what can be achieved when using geostationary active fire data within the Copernicus Atmosphere Monitoring System (CAMS). Qualitative comparison of the modelled smoke plumes with MODIS optical imagery illustrates that the model captures the temporal and spatial dynamics of the plume very well, and that high temporal resolution emissions estimates such as those available from geostationary orbit are important for capturing the sub-daily variability in smoke plume parameters such as aerosol optical depth (AOD), which are increasingly less well resolved using daily or coarser temporal resolution emissions datasets. Quantitative comparison of modelled AOD with coincident MODIS and AERONET AOD indicates that the former is overestimated by ∼ 20-30%, but captures the observed AOD dynamics with a high degree of fidelity. The case study highlights the potential of using geostationary FRP data to drive fire emissions estimates for use within atmospheric transport models such as those currently implemented as part of the Monitoring Atmospheric Composition and Climate (MACC) programme within the CAMS.

NASA Blue Marble 2007 East

NASA Image and Video Library

2010-03-12

RELEASE DATE: OCTOBER 9, 2007 Credit: NASA/Goddard Space Flight Center/Reto Stöckli A day’s clouds. The shape and texture of the land. The living ocean. City lights as a beacon of human presence across the globe. This amazingly beautiful view of Earth from space is a fusion of science and art, a showcase for the remote-sensing technology that makes such views possible, and a testament to the passion and creativity of the scientists who devote their careers to understanding how land, ocean, and atmosphere—even life itself—interact to generate Earth’s unique (as far as we know!) life-sustaining environment. Drawing on data from multiple satellite missions (not all collected at the same time), a team of NASA scientists and graphic artists created layers of global data for everything from the land surface, to polar sea ice, to the light reflected by the chlorophyll in the billions of microscopic plants that grow in the ocean. They wrapped these layers around a globe, set it against a black background, and simulated the hazy edge of the Earth’s atmosphere (the limb) that appears in astronaut photography of the Earth. The land surface layer is based on photo-like surface reflectance observations (reflected sunlight) measured by the Moderate Resolution Imaging Spectroradiometer (MODIS) on NASA’s Terra satellite in July 2004. The sea ice layer near the poles comes from Terra MODIS observations of daytime sea ice observed between August 28 and September 6, 2001. The ocean layer is a composite. In shallow water areas, the layer shows surface reflectances observed by Terra MODIS in July 2004. In the open ocean, the photo-like layer is overlaid with observations of the average ocean chlorophyll content for 2004. NASA’s Aqua MODIS collected the chlorophyll data. The cloud layer shows a single-day snapshot of clouds observed by Terra MODIS across the planet on July 29, 2001. City lights on Earth’s night side are visualized from data collected by the Defense Meteorological Satellite Program mission between 1994–1995. The topography layer is based on radar data collected by the Space Shuttle Endeavour during an 11-day mission in February of 2000. Topography over Antarctica comes from the Radarsat Antarctic Mapping Project, version 2. Most of the data layers in this visualization are available as monthly composites as part of NASA’s Blue Marble Next Generation image collection. The images in the collection appear in cylindrical projection (rectangular maps), and they are available at 500-meter resolution. The large images provided above are the full-size versions of these globes. In their hope that these images will inspire people to appreciate the beauty of our home planet and to learn about the Earth system, the developers of these images encourage readers to re-use and re-publish the images freely. NASA images by Reto Stöckli, based on data from NASA and NOAA. To learn the history of the Blue Marble go here: earthobservatory.nasa.gov/Features/BlueMarble/BlueMarble_... To learn more about the Blue Marble go here: earthobservatory.nasa.gov/IOTD/view.php?id=8108 To learn more about NASA's Goddard Space Flight Center go here: www.nasa.gov/centers/goddard/home/index.html NASA Goddard Space Flight Center is home to the nation's largest organization of combined scientists, engineers and technologists that build spacecraft, instruments and new technology to study the Earth, the sun, our solar system, and the universe. NASA Goddard Space Flight Center is home to the nation's largest organization of combined scientists, engineers and technologists that build spacecraft, instruments and new technology to study the Earth, the sun, our solar system, and the universe. Follow us on Twitter Join us on Facebook

Use of MODIS Satellite Images and an Atmospheric Dust Transport Model to Evaluate Juniperus spp. Pollen Phenology and Transport

NASA Technical Reports Server (NTRS)

Luvall, J. C.; Sprigg, W. A.; Levetin, E.; Huete, A.; Nickovic, S.; Pejanovic, G. A.; Vukovic, A.; Van de Water, P. K.; Myers, O. B.; Budge, A. M.;

Use Of MODIS Satellite Images And An Atmospheric Dust Transport Model To Evaluate Juniperus Spp. Pollen Phenology And Transport

NASA Astrophysics Data System (ADS)

Luvall, J. C.; Sprigg, W. A.; Levetin, E.; Huete, A. R.; Nickovic, S.; Crimmins, T. M.; Van De Water, P. K.; Pejanovic, G.; Vukovic, A. J.; Myers, O.; Budge, A.; Zelicoff, A.; Bunderson, L.; Ponce-Campos, G.

2011-12-01

Pollen can be transported great distances. Van de Water et al., 2003 reported Juniperus spp. pollen, a significant aeroallergen was transported 200-600 km. Hence local observations of plant phenology may not be consistent with the timing and source of pollen collected by pollen sampling instruments. Direct detection of pollen via satellite is not practical. A practical alternative combines modeling and phenological observations using ground based sampling and satellite data. The DREAM (Dust REgional Atmospheric Model) is a verified model for atmospheric dust transport modeling using MODIS data products to identify source regions and quantities of dust (Nickovic et al. 2001). The use of satellite data products for studying phenology is well documented (White and Nemani 2006). In the current project MODIS data will provide critical input to the PREAM model providing pollen source location, timing of pollen release, and vegetation type. We are modifying the DREAM model (PREAM - Pollen REgional Atmospheric Model) to incorporate pollen transport. The linkages already exist with DREAM through PHAiRS (Public Health Applications in Remote Sensing) to the public health community. This linkage has the potential to fill this data gap so that the potential association of health effects of pollen can better be tracked for possible linkage with health outcome data which may be associated with asthma, respiratory effects, myocardial infarction, and lost workdays. Juniperus spp. pollen phenology may respond to a wide range of environmental factors such as day length, growing degree-days, precipitation patterns and soil moisture. Species differences are also important. These environmental factors vary over both time and spatial scales. Ground based networks such as the USA National Phenology Network have been established to provide national wide observations of vegetation phenology. However, the density of observers is not adequate to sufficiently document the phenology variability over large regions. Hence the use of satellite data is critical to observe Juniperus spp. pollen phenology. MODIS data was used to observe Juniperus spp. pollen phenology. The MODIS surface reflectance product(MOD09) provided information on the Juniper spp. cone formation and cone density. Ground based observational records of pollen release timing and quantities were used as verification. Techniques developed using MOD09 surface reflectance products will be directly applicable to the next generation sensors such as VIIRS.

Evolution in the lineament patterns associated to strong earthquakes revealed by satellite observations

NASA Astrophysics Data System (ADS)

Soto-Pinto, C. A.; Arellano-Baeza, A. A.; Ouzounov, D. P.

2011-12-01

We study the temporal evolution of the stress patterns in the crust by using high-resolution (10-300 m) satellite images from MODIS and ASTER satellite sensors. We are able to detect some changes in density and orientation of lineaments preceding earthquake events. A lineament is generally defined as a straight or a somewhat curved feature in the landscape visible in a satellite image as an aligned sequence of pixels of a contrasting intensity compared to the background. The system of lineaments extracted from the satellite images is not identical to the geological lineaments; nevertheless, it generally reflects the structure of the faults and fractures in the Earth's crust. Our analysis has shown that the system of lineaments is very dynamical, and the significant number of lineaments appeared approximately one month before an earthquake, while one month after the earthquake the lineament configuration returned to its initial state. These features were not observed in the test areas that are free of any seismic activity in that period (null hypothesis). We have designed a computational prototype capable to detect lineament evolution and to utilize both ASTER and MODIS satellite L1/L2. We will demonstrate the first successful test results for several Mw> 5 earthquakes in Chile, Peru, China, and California (USA).

Multitemporal cross-calibration of the Terra MODIS and Landsat 7 ETM+ reflective solar bands

USGS Publications Warehouse

Angal, Amit; Xiong, Xiaoxiong; Wu, Aisheng; Chander, Gyanesh; Choi, Taeyoung

2013-01-01

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 (MODIS) 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 MODIS 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) reflectance due to surface and atmospheric bidirectional reflectance distribution function (BRDF), a semiempirical BRDF model was adopted to normalize the TOA reflectance 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 MODIS and ETM+ spectral bands. As EO-1 Hyperion scenes were not available for all MODIS 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 MODIS 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 MODIS 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 MODIS band 3 being the largest of about 6% over 10 years, a change that will be corrected in Collection 6 MODIS processing.

Multitemporal Cross-Calibration of the Terra MODIS and Landsat 7 ETM+ Reflective Solar Bands

NASA Technical Reports Server (NTRS)

Angal, Amit; Xiong, Xiaoxiong; Wu, Aisheng; Changler, Gyanesh; Choi, Taeyoyung

2013-01-01

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 (MODIS) 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 MODIS 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) reflectance due to surface and atmospheric bidirectional reflectance distribution function (BRDF), a semiempirical BRDF model was adopted to normalize the TOA reflectance 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 MODIS and ETM+ spectral bands. As EO-1 Hyperion scenes were not available for all MODIS 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 MODIS 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 MODIS 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 MODIS band 3 being the largest of about 6% over 10 years, a change that will be corrected in Collection 6 MODIS processing.

Intercomparison of terrestrial carbon fluxes and carbon use efficiency simulated by CMIP5 Earth System Models

NASA Astrophysics Data System (ADS)

Kim, Dongmin; Lee, Myong-In; Jeong, Su-Jong; Im, Jungho; Cha, Dong Hyun; Lee, Sanggyun

2017-12-01

This study compares historical simulations of the terrestrial carbon cycle produced by 10 Earth System Models (ESMs) that participated in the fifth phase of the Coupled Model Intercomparison Project (CMIP5). Using MODIS satellite estimates, this study validates the simulation of gross primary production (GPP), net primary production (NPP), and carbon use efficiency (CUE), which depend on plant function types (PFTs). The models show noticeable deficiencies compared to the MODIS data in the simulation of the spatial patterns of GPP and NPP and large differences among the simulations, although the multi-model ensemble (MME) mean provides a realistic global mean value and spatial distributions. The larger model spreads in GPP and NPP compared to those of surface temperature and precipitation suggest that the differences among simulations in terms of the terrestrial carbon cycle are largely due to uncertainties in the parameterization of terrestrial carbon fluxes by vegetation. The models also exhibit large spatial differences in their simulated CUE values and at locations where the dominant PFT changes, primarily due to differences in the parameterizations. While the MME-simulated CUE values show a strong dependence on surface temperatures, the observed CUE values from MODIS show greater complexity, as well as non-linear sensitivity. This leads to the overall underestimation of CUE using most of the PFTs incorporated into current ESMs. The results of this comparison suggest that more careful and extensive validation is needed to improve the terrestrial carbon cycle in terms of ecosystem-level processes.

Monitoring the spatio-temporal evolution of the snow cover in the eastern Alps from MODIS data

NASA Astrophysics Data System (ADS)

Cianfarra, P.; Salvini, F.; Valt, M.

2009-04-01

Estimating the snow cover extent in mountain ranges is important for a wide variety purposes including of scientific studies, environmental and meteo-climatic applications, as well as predicting water availability for energy resource and agriculture. Moreover, the monitoring of the spatio-temporal variation of the snow cover thickness, coupled with ground data from weather stations, allows to identify avalanche risk areas after heavy snowfall. The aim of this study is to test an automatic procedure to identify and map the snow coverage for different altitude interval in the eastern part of the Alpine range. There has been much progress since 1966 when the first operational snow mapping was done by NOAA with spaceborne sensors that provide daily, global observations to monitor the variability in space and time in the extent of snow cover. MODIS sensors offer increased improvements relative to the AVHRR that has been operational for many years on the NOAA Polar Operational Environmental Satellite System. In this context the MODIS provides observations at a nominal spatial resolution of 500 m versus the 1.1 km spatial resolution of the AVHRR and continuously available (spatially and temporally), spectral band observation that span the visible and short-wave infrared wavelengths, including those useful for recognize snow cover. The other advantage of using MODIS data is its availability and cost by the NASA's server. In this work we used MOD02 (L1B) data providing calibrated radiance values at the sensor (without atmospheric correction). Snow cover map production included the following steps: selection of the images with clear sky conditions, geometric correction and georeferencing to UTM zone 32 ,WSG 84 ellipsoid, to eliminate the distortion of and the typical bow-tie effect that produces the observed not alignment of the scan lines in the row image; spatial sub setting to produce an image covering an area of about 200 x 120 km; identification of the snow cover was done by computing the Normalised Difference Snow Index (NDSI) knowing that snow reflectance is higher in the visible (0.5-0.7 mm) wavelengths and has lower reflectance in the short wave infrared (1-4 mm) wavelengths. This allowed to separate snow from clouds and other non-snow-covered pixels. The NDSI for MODIS images is defined as the difference of reflectances observed in the visible band 4 (0.555 mm) and the short wave infrared band 6 (1.640 mm) divided by the sum of the two reflectances: NDSI=(B4 - B6)/ (B4 + B6) This approach allowed to reduce (yet not totally eliminate) the influence of the atmospheric effects and lighting conditions. A series of thresholds were tested to the ratio image to establish the best value for snow cover identification. Eventually, the snow cover extent was computed for 6 altitude intervals. Results from the different processed images were compared and statistically analysed. A complete set of ground truth of these preliminary results is still missing; yet we are confident that once the tuning of the processing will be completed, the automated processing of MODIS data will provide low cost, near real-time estimates of the snow cover distribution over the eastern Alps. This product would be a valuable tool for public administrations and authorities for environmental protection, control and risk management.

Cloud Properties of CERES-MODIS Edition 4 and CERES-VIIRS Edition 1

NASA Technical Reports Server (NTRS)

Sun-Mack, Sunny; Minnis, Patrick; Chang, Fu-Lung; Hong, Gang; Arduini, Robert; Chen, Yan; Trepte, Qing; Yost, Chris; Smith, Rita; Brown, Ricky;

Use of EOS Data in AWIPS for Weather Forecasting

NASA Technical Reports Server (NTRS)

Jedlovec, Gary J.; Haines, Stephanie L.; Suggs, Ron J.; Bradshaw, Tom; Darden, Chris; Burks, Jason

2003-01-01

Operational weather forecasting relies heavily on real time data and modeling products for forecast preparation and dissemination of significant weather information to the public. The synthesis of this information (observations and model products) by the meteorologist is facilitated by a decision support system to display and integrate the information in a useful fashion. For the NWS this system is called Advanced Weather Interactive Processing System (AWIPS). Over the last few years NASA has launched a series of new Earth Observation Satellites (EOS) for climate monitoring that include several instruments that provide high-resolution measurements of atmospheric and surface features important for weather forecasting and analysis. The key to the utilization of these unique new measurements by the NWS is the real time integration of the EOS data into the AWIPS system. This is currently being done in the Huntsville and Birmingham NWS Forecast Offices under the NASA Short-term Prediction Research and Transition (SPORT) Program. This paper describes the use of near real time MODIS and AIRS data in AWIPS to improve the detection of clouds, moisture variations, atmospheric stability, and thermal signatures that can lead to significant weather development. The paper and the conference presentation will focus on several examples where MODIS and AIRS data have made a positive impact on forecast accuracy. The results of an assessment of the utility of these products for weather forecast improvement made at the Huntsville NWS Forecast Office will be presented.

Monitoring and modeling agricultural drought for famine early warning (Invited)

NASA Astrophysics Data System (ADS)

Verdin, J. P.; Funk, C.; Budde, M. E.; Lietzow, R.; Senay, G. B.; Smith, R.; Pedreros, D.; Rowland, J.; Artan, G. A.; Husak, G. J.; Michaelsen, J.; Adoum, A.; Galu, G.; Magadzire, T.; Rodriguez, M.

2009-12-01

The Famine Early Warning Systems Network (FEWS NET) makes quantitative estimates of food insecure populations, and identifies the places and periods during which action must be taken to assist them. Subsistence agriculture and pastoralism are the predominant livelihood systems being monitored, and they are especially drought-sensitive. At the same time, conventional climate observation networks in developing countries are often sparse and late in reporting. Consequently, remote sensing has played a significant role since FEWS NET began in 1985. Initially there was heavy reliance on vegetation index imagery from AVHRR to identify anomalies in landscape greenness indicative of drought. In the latter part of the 1990s, satellite rainfall estimates added a second, independent basis for identification of drought. They are used to force crop water balance models for the principal rainfed staple crops in twenty FEWS NET countries. Such models reveal seasonal moisture deficits associated with yield reduction on a spatially continuous basis. In 2002, irrigated crops in southwest Asia became a concern, and prompted the implementation of a gridded energy balance model to simulate the seasonal mountain snow pack, the main source of irrigation water. MODIS land surface temperature data are also applied in these areas to directly estimate actual seasonal evapotranspiration on the irrigated lands. The approach reveals situations of reduced irrigation water supply and crop production due to drought. The availability of MODIS data after 2000 also brought renewed interest in vegetation index imagery. MODIS NDVI data have proven to be of high quality, thanks to significant spectral and spatial resolution improvements over AVHRR. They are vital to producing rapid harvest assessments for drought-impacted countries in Africa and Asia. The global food crisis that emerged in 2008 has led to expansion of FEWS NET monitoring to over 50 additional countries. Unlike previous practice, these new countries have no local FEWS NET analysts, requiring increased reliance on remote sensing for detection of agricultural drought and potential food insecurity. USGS is increasing its cooperation with NASA, NOAA, and university partners to meet this challenge. New servers for near real time delivery of MODIS NDVI, satellite rainfall estimates, and gridded snow pack estimates are being established. A custom instance of NASA's Land Information System software is also being developed to create a land data assimilation system specifically for FEWS NET domains, data streams, and monitoring and forecast requirements. The system will take better advantage of remote sensing data, including promising new products from the Soil Moisture Active-Passive (SMAP) mission, by integrating them with surface observations for simulation of land surface processes. In this way, the continuous improvement of monitoring and modeling for famine early warning will advance to a new level of sophistication and effectiveness.

Role of MODIS Vegetation Phenology Products in the U.S. for Warn Early Warning System for Forest Threats

NASA Technical Reports Server (NTRS)

Spruce, Joseph; Hargrove, William; Norman, Steve; Gasser, Gerald; Smoot, James; Kuper, Philip

2012-01-01

U.S. forests occupy approx 751 million acres (approx 1/3 of total land). Several abiotic and biotic damage agents disturb, damage, kill, and/or threaten these forests. Regionally extensive forest disturbances can also threaten human life and property, bio-diversity and water supplies. timely regional forest disturbance monitoring products are needed to aid forest health management work at finer scales. daily MODIS data provide a means to monitor regional forest disturbances on a weekly basis, leveraging vegetation phenology. In response, the USFS and NASA began collaborating in 2006 to develop a Near Real Time (NRT) forest monitoring capability, based on MODIS NDVI data, as part of a national forest threat Early Warning System (EWS).

Validation of MODIS 3 km land aerosol optical depth from NASA's EOS Terra and Aqua missions

NASA Astrophysics Data System (ADS)

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

2018-05-01

In addition to the standard resolution product (10 km), the MODerate resolution Imaging Spectroradiometer (MODIS) Collection 6 (C006) data release included a higher resolution (3 km). Other than accommodations for the two different resolutions, the 10 and 3 km Dark Target (DT) algorithms are basically the same. In this study, we perform global validation of the higher-resolution aerosol optical depth (AOD) over global land by comparing against AErosol RObotic NETwork (AERONET) measurements. The MODIS-AERONET collocated data sets consist of 161 410 high-confidence AOD pairs from 2000 to 2015 for Terra MODIS and 2003 to 2015 for Aqua MODIS. We find that 62.5 and 68.4 % of AODs retrieved from Terra MODIS and Aqua MODIS, respectively, fall within previously published expected error bounds of ±(0.05 + 0.2 × AOD), with a high correlation (R = 0.87). The scatter is not random, but exhibits a mean positive bias of ˜ 0.06 for Terra and ˜ 0.03 for Aqua. These biases for the 3 km product are approximately 0.03 larger than the biases found in similar validations of the 10 km product. The validation results for the 3 km product did not have a relationship to aerosol loading (i.e., true AOD), but did exhibit dependence on quality flags, region, viewing geometry, and aerosol spatial variability. Time series of global MODIS-AERONET differences show that validation is not static, but has changed over the course of both sensors' lifetimes, with Terra MODIS showing more change over time. The likely cause of the change of validation over time is sensor degradation, but changes in the distribution of AERONET stations and differences in the global aerosol system itself could be contributing to the temporal variability of validation.

Estimating Irrigation Water Requirements using MODIS Vegetation Indices and Inverse Biophysical Modeling

NASA Technical Reports Server (NTRS)

Imhoff, Marc L.; Bounoua, Lahouari; Harriss, Robert; Harriss, Robert; Wells, Gordon; Glantz, Michael; Dukhovny, Victor A.; Orlovsky, Leah

2007-01-01

An inverse process approach using satellite-driven (MODIS) biophysical modeling was used to quantitatively assess water resource demand in semi-arid and arid agricultural lands by comparing the carbon and water flux modeled under both equilibrium (in balance with prevailing climate) and non-equilibrium (irrigated) conditions. Since satellite observations of irrigated areas show higher leaf area indices (LAI) than is supportable by local precipitation, we postulate that the degree to which irrigated lands vary from equilibrium conditions is related to the amount of irrigation water used. For an observation year we used MODIS vegetation indices, local climate data, and the SiB2 photosynthesis-conductance model to examine the relationship between climate and the water stress function for a given grid-cell and observed leaf area. To estimate the minimum amount of supplemental water required for an observed cell, we added enough precipitation to the prevailing climatology at each time step to minimize the water stress function and bring the soil to field capacity. The experiment was conducted on irrigated lands on the U.S. Mexico border and Central Asia and compared to estimates of irrigation water used.

Exploiting Satellite Remote-Sensing Data in Fine Particulate Matter Characterization for Serving the Environmental Public Health Tracking Network (EPHTN): The HELIX-Atlanta Experience and NPOESS Implications

NASA Technical Reports Server (NTRS)

Al-Hamdan, Mohammad Z.; Crosson, William L.; Limaye, Ashutosh S.; Rickman, Douglas L.; Quattrochi, Dale A.; Estes, Maurice G.; Qualters, Judith R.; Sinclair, Amber H.; Tolsma, Dennis D.; Adeniyi, Kafayat A.

2008-01-01

As part of the U.S. National Environmental Public Health Tracking Network (EPHTN), the National Center for Environmental Health (NCEH) at the U.S. Centers for Disease Control and Prevention (CDC) led a project in collaboration with the National Aeronautics and Space Administration (NASA) Marshall Space Flight Center (MSFC) called Health and Environment Linked for Information Exchange (HELIX-Atlanta). Under HELIX-Atlanta, pilot projects were conducted to develop methods to better characterize exposure; link health and environmental datasets; and analyze spatial/temporal relationships. This paper describes and demonstrates different techniques for surfacing daily environmental hazards data of particulate matter with aerodynamic diameter less than or equal to 2.5 micrometers (PM(sub 2.5) for the purpose of integrating respiratory health and environmental data for the CDC's pilot study of HELIX-Atlanta. It describes a methodology for estimating ground-level continuous PM(sub 2.5) concentrations using spatial surfacing techniques and leveraging NASA Moderate Resolution Imaging Spectrometer (MODIS) data to complement the U.S. Environmental Protection Agency (EPA) ground observation data. The study used measurements of ambient PM(sub 2.5) from the EPA database for the year 2003 as well as PM(sub 2.5) estimates derived from NASA's MODIS data. Hazard data have been processed to derive the surrogate exposure PM(sub 2.5) estimates. The paper has shown that merging MODIS remote sensing data with surface observations of PM(sub 2.5), may provide a more complete daily representation of PM(sub 2.5), than either data set alone would allow, and can reduce the errors in the PM(sub 2.5) estimated surfaces. Future work in this area should focus on combining MODIS column measurements with profile information provided by satellites like the National Polar-orbiting Operational Environmental Satellite System (NPOESS). The Visible Infrared Imager/Radiometer Suite (VIIRS) and the Aerosol Polarimeter Sensor (APS) NPOESS sensors will provide first-order information on aerosol particle size and are anticipated to provide information on aerosol products at higher resolution and accuracy than MODIS. Use of the NPOESS remote sensing data should result in more robust remotely sensed data that can be coupled with the methods discussed in this paper to generate surface concentrations of PM(2.5) for linkage with health data in Environmental Public Health Tracking.

How Often and Why MODIS Cloud Property Retrievals Fail for Liquid-Phase Clouds over Ocean? a Comprehensive Analysis Based on a-Train Observations

NASA Astrophysics Data System (ADS)

Zhang, Z.; Cho, H. M.; Platnick, S. E.; Meyer, K.; Lebsock, M. D.

2014-12-01

The cloud optical thickness (τ) and droplet effective radius (re) are two key cloud parameters retrieved by MODIS (Moderate Resolution Imaging Spectroradiometer). These MODIS cloud products are widely used in a broad range of earth system science applications. In this paper, we present a comprehensive analysis of the failed cloud τ and/or re retrievals for liquid-phase clouds over ocean in the Collection 6 MODIS cloud product. The main findings from this study are summarized as follows: MODIS retrieval failure rates for marine boundary layer (MBL) clouds have a strong dependence on the spectral combination used for retrieval (e.g., 0.86 + 2.1 µm vs. 0.8 + 3.7 µm) and the cloud morphology (i.e., "good" pixels vs. partly cloudy (PCL) pixels). Combining all clear-sky-restoral (CSR) categories (CSR=0,1 and 3), the 0.86 + 2.1 µm and 0.86 + 3.7 µm spectral combinations have an overall failure rate of about 20% and 12%, respectively (See figure below). The PCL pixels (CSR=1 & 3) have significantly higher failure rates and contribute more to the total failure population than the "good" (CSR=0) pixels. The majority of the failed retrievals are caused by the re too large failure, which explains about 85% and 70% of the failed 0.86 + 2.1 µm and 0.86 + 3.7 µm retrievals, respectively. The remaining failures are either due to the re too small failure or τ retrieval failure. The geographical distribution of failure rates has a significant dependence on cloud regime, lower over the coastal stratocumulus cloud regime and higher over the broken trade-wind cumulus cloud regime over open oceans. Enhanced retrieval failure rates are found when MBL clouds have high sub-pixel inhomogeneity , or are located at special Sun-satellite viewing geometries, such as sunglint, large viewing or solar zenith angle, or cloudbow and glory angles, or subject to cloud masking, cloud overlapping and/or cloud phase retrieval issues. About 80% of the failure retrievals can be attributed to at least one or more potential reasons mentioned above. Collocated radar reflectivity observations from CloudSat suggest that the remaining 20% are unlikely to be retrieval artifacts, but reflection of true cloud microphysics, i.e., the true is either truly very small or very large.

Characterization of MODIS and SeaWiFS Solar Diffuser On-Orbit Degradation

NASA Technical Reports Server (NTRS)

Xiong, X.; Eplee, R. E., Jr.; Sun, J.; Patt, F. S.; Angal, A.; McClain, C. R.

2009-01-01

MODIS has 20 reflective solar bands (RSB), covering the VIS, NIR, and SWIR spectral regions. They are calibrated on-orbit using a solar diffuser (SD) panel, made of space-grade Spectralon. The SD bi-directional reflectance factor (BRF) was characterized pre-launch by the instrument vendor reference to the NIST reflectance standard. Its on-orbit degradation is tracked by an on-board solar diffuser stability monitor (SDSM). The SeaWifS on-orbit calibration strategy uses monthly lunar observations to monitor the long-term radiometric stability of the instrument and applies daily observations of its solar diffuser (an aluminum plate coated with YB71 paint) to track the short-term changes in the instrument response. This paper provides an overview of MODIS and SeaWiFS SD observations, applications, and approaches used to track their on-orbit degradations. Results from sensors are presented with emphasis on the spectral dependence and temporal trends of the SD degradation. Lessons and challenges from the use of SD for sensor on-orbit calibration are also discussed.

Retrieval of aerosol optical depth over bare soil surfaces using time series of MODIS imagery

NASA Astrophysics Data System (ADS)

Yuan, Zhengwu; Yuan, Ranyin; Zhong, Bo

2014-11-01

Aerosol Optical Depth (AOD) is one of the key parameters which can not only reflect the characterization of atmospheric turbidity, but also identify the climate effects of aerosol. The current MODIS aerosol estimation algorithm over land is based on the "dark-target" approach which works only over densely vegetated surfaces. For non-densely vegetated surfaces (such as snow/ice, desert, and bare soil surfaces), this method will be failed. In this study, we develop an algorithm to derive AOD over the bare soil surfaces. Firstly, this method uses the time series of MODIS imagery to detect the " clearest" observations during the non-growing season in multiple years for each pixel. Secondly, the "clearest" observations after suitable atmospheric correction are used to fit the bare soil's bidirectional reflectance distribution function (BRDF) using Kernel model. As long as the bare soil's BRDF is established, the surface reflectance of "hazy" observations can be simulated. Eventually, the AOD over the bare soil surfaces are derived. Preliminary validation results by comparing with the ground measurements from AERONET at Xianghe sites show a good agreement.

The Impacts of Bowtie Effect and View Angle Discontinuity on MODIS Swath Data Gridding

NASA Technical Reports Server (NTRS)

Wang, Yujie; Lyapustin, Alexei

2007-01-01

We have analyzed two effects of the MODIS viewing geometry on the quality of gridded imagery. First, the fact that the MODIS scans a swath of the Earth 10 km wide at nadir, causes abrupt change of the view azimuth angle at the boundary of adjacent scans. This discontinuity appears as striping of the image clearly visible in certain cases with viewing geometry close to principle plane over the snow of the glint area of water. The striping is a true surface Bi-directional Reflectance Factor (BRF) effect and should be preserved during gridding. Second, due to bowtie effect, the observations in adjacent scans overlap each other. Commonly used method of calculating grid cell value by averaging all overlapping observations may result in smearing of the image. This paper describes a refined gridding algorithm that takes the above two effects into account. By calculating the grid cell value by averaging the overlapping observations from a single scan, the new algorithm preserves the measured BRF signal and enhances sharpness of the image.

Progress towards MODIS and VIIRS Cloud Fraction Data Record Continuity

NASA Astrophysics Data System (ADS)

Ackerman, S. A.; Frey, R.; Holz, R.; Platnick, S. E.; Heidinger, A. K.

2016-12-01

Satellite-derived clear-sky vs. cloudy-sky discrimination at the pixel scale is an important input parameter used in many real-time applications. Cloud fractions, resulting from integrating over time and space, are also critical to the study of recent decadal climate changes. The NASA NPOESS Preparatory Project (NPP) has funded a science team to develop and study the ability to make continuous climate records from MODIS (2000-2020) and VIIRS (2012-2030). The MODAWG project, led by Dr. Steve Platnick of NASA/GSFC, combines elements of the MODIS processing system and the NOAA Algorithm Working Group (AWG) to achieve this goal. This presentation will focus on the cloud masking aspects of MODAWG, derived primarily from the MODIS cloud mask (MOD35). Challenges to continuity of cloud detection due to differences in instrument characteristics will be discussed. Cloud mask results from use of the same (continuity) algorithm will be shown for both MODIS and VIIRS, including comparisons to collocated CALIOP (Cloud-Aerosol Lidar with Orthogonal Polarization) cloud data.

Detection and characterization of small hot fires: Comparing FireBird, BIRD, S-NPP VIIRS and MODIS capacities over gas flares

NASA Astrophysics Data System (ADS)

Ruecker, Gernot; Schroeder, Wilfrid; Lorenz, Eckehard; Kaiser, Johannes; Caseiro, Alexandre

2016-04-01

According to recent research, black carbon has the second strongest effect on the earth climate system after carbon dioxide. In high Northern latitudes, industrial gas flares are an important source of black carbon, especially in winter. This fact is particularly relevant for the relatively fast observed climate change in the Arctic since deposition of black carbon changes the albedo of snow and ice, thus leading to a positive feedback cycle. Here we explore gas flare detection and Fire Radiative Power (FRP) retrievals of the German FireBird TET-1 and BIRD Hotspot Recognition Systems (HSRS), the VIIRS sensor on board of the S-NPP satellite, and the MODIS sensor using temporally close to near coincident data acquisitions. Comparison is based on level 2 products developed for fire detection for the different sensors; in the case of S-NPP VIIRS we use two products: the new VIIRS 750m algorithm based on MODIS collection 6, and the 350 m algorithm based on the VIIRS mid-infrared I (Imaging) band, which offers high resolution, but no FRP retrievals. Results indicate that the highest resolution FireBird sensors offer the best detection capacities, though the level two product shows false alarms, followed by the VIIRS 350 m and 750 m algorithms. MODIS has the lowest detection rate. Preliminary results of FRP retrievals show that FireBird and VIIRS algorithms have a good agreement. Given the fact that most gas flaring is at the detection limit for medium to coarse resolution space borne sensors - and hence measurement errors may be high - our results indicates that a quantitative evaluation of gas flaring using these sensors is feasible. Results shall be used to develop a gas flare detection algorithm for Sentinel-3, and a similar methodology will be employed to validate the capacity of Sentinel 3 to detect and characterize small high temperature sources such as gas flares.

Noise Characterization and Performance of MODIS Thermal Emissive Bands

NASA Technical Reports Server (NTRS)

Madhavan, Sriharsha; Xiong, Xiaoxiong; Wu, Aisheng; Wenny, Brian; Chiang, Kwofu; Chen, Na; Wang, Zhipeng; Li, Yonghong

2016-01-01

The MODerate-resolution Imaging Spectroradiometer (MODIS) is a premier Earth-observing sensor of the early 21st century, flying onboard the Terra (T) and Aqua (A) spacecraft. Both instruments far exceeded their six-year design life and continue to operate satisfactorily for more than 15 and 13 years, respectively. The MODIS instrument is designed to make observations at nearly a 100% duty cycle covering the entire Earth in less than two days. The MODIS sensor characteristics include a spectral coverage from 0.41micrometers to 14.4 micrometers, of which those wavelengths ranging from 3.7 micrometers to 14.4 micrometers cover the thermal infrared region which is interspaced in 16 thermal emissive bands (TEBs). Each of the TEB contains ten detectors which record samples at a spatial resolution of 1 km. In order to ensure a high level of accuracy for the TEB-measured top-of-atmosphere radiances, an onboard blackbody (BB) is used as the calibration source. This paper reports the noise characterization and performance of the TEB on various counts. First, the stability of the onboard BB is evaluated to understand the effectiveness of the calibration source. Next, key noise metrics such as the noise equivalent temperature difference and the noise equivalent dn difference (NEdN) for the various TEBs are determined from multiple temperature sources. These sources include the nominally controlled BB temperature of 290 K for T-MODIS and 285 K for A-MODIS, as well as a BB warm up-cool down cycle that is performed over a temperature range from roughly 270 to 315 K. The space-view port that measures the background signal serves as a viable cold temperature source for measuring noise. In addition, a well characterized Earth-view target, the Dome Concordia site located in the Antarctic plateau, is used for characterizing the stability of the sensor, indirectly providing a measure of the NEdN. Based on this rigorous characterization, a list of the noisy and inoperable detectors for the TEB for both instruments is reported to provide the science user communities quality control of the MODIS Level 1B calibrated product.

Verification and Validation of NASA-Supported Enhancements to PECAD's Decision Support Tools

NASA Technical Reports Server (NTRS)

McKellipo, Rodney; Ross, Kenton W.

2006-01-01

The NASA Applied Sciences Directorate (ASD), part of the Earth-Sun System Division of NASA's Science Mission Directorate, has partnered with the U.S. Department of Agriculture (USDA) to enhance decision support in the area of agricultural efficiency-an application of national importance. The ASD integrated the results of NASA Earth science research into USDA decision support tools employed by the USDA Foreign Agricultural Service (FAS) Production Estimates and Crop Assessment Division (PECAD), which supports national decision making by gathering, analyzing, and disseminating global crop intelligence. Verification and validation of the following enhancements are summarized: 1) Near-real-time Moderate Resolution Imaging Spectroradiometer (MODIS) products through PECAD's MODIS Image Gallery; 2) MODIS Normalized Difference Vegetation Index (NDVI) time series data through the USDA-FAS MODIS NDVI Database; and 3) Jason-1 and TOPEX/Poseidon lake level estimates through PECAD's Global Reservoir and Lake Monitor. Where possible, each enhanced product was characterized for accuracy, timeliness, and coverage, and the characterized performance was compared to PECAD operational requirements. The MODIS Image Gallery and the GRLM are more mature and have achieved a semi-operational status, whereas the USDA-FAS MODIS NDVI Database is still evolving and should be considered

Ocean Observations with EOS/MODIS: Algorithm Development and Post Launch Studies

NASA Technical Reports Server (NTRS)

Gordon, Howard R.

1997-01-01

The following accomplishments were made during the present reporting period: (1) We expanded our new method, for identifying the presence of absorbing aerosols and simultaneously performing atmospheric correction, to the point where it could be added as a subroutine to the MODIS water-leaving radiance algorithm; (2) We successfully acquired micro pulse lidar (MPL) data at sea during a cruise in February; (3) We developed a water-leaving radiance algorithm module for an approximate correction of the MODIS instrument polarization sensitivity; and (4) We participated in one cruise to the Gulf of Maine, a well known region for mesoscale coccolithophore blooms. We measured coccolithophore abundance, production and optical properties.

Comparison of different methods to retrieve optical-equivalent snow grain size in central Antarctica

NASA Astrophysics Data System (ADS)

Carlsen, Tim; Birnbaum, Gerit; Ehrlich, André; Freitag, Johannes; Heygster, Georg; Istomina, Larysa; Kipfstuhl, Sepp; Orsi, Anaïs; Schäfer, Michael; Wendisch, Manfred

2017-11-01

The optical-equivalent snow grain size affects the reflectivity of snow surfaces and, thus, the local surface energy budget in particular in polar regions. Therefore, the specific surface area (SSA), from which the optical snow grain size is derived, was observed for a 2-month period in central Antarctica (Kohnen research station) during austral summer 2013/14. The data were retrieved on the basis of ground-based spectral surface albedo measurements collected by the COmpact RAdiation measurement System (CORAS) and airborne observations with the Spectral Modular Airborne Radiation measurement sysTem (SMART). The snow grain size and pollution amount (SGSP) algorithm, originally developed to analyze spaceborne reflectance measurements by the MODerate Resolution Imaging Spectroradiometer (MODIS), was modified in order to reduce the impact of the solar zenith angle on the retrieval results and to cover measurements in overcast conditions. Spectral ratios of surface albedo at 1280 and 1100 nm wavelength were used to reduce the retrieval uncertainty. The retrieval was applied to the ground-based and airborne observations and validated against optical in situ observations of SSA utilizing an IceCube device. The SSA retrieved from CORAS observations varied between 27 and 89 m2 kg-1. Snowfall events caused distinct relative maxima of the SSA which were followed by a gradual decrease in SSA due to snow metamorphism and wind-induced transport of freshly fallen ice crystals. The ability of the modified algorithm to include measurements in overcast conditions improved the data coverage, in particular at times when precipitation events occurred and the SSA changed quickly. SSA retrieved from measurements with CORAS and MODIS agree with the in situ observations within the ranges given by the measurement uncertainties. However, SSA retrieved from the airborne SMART data slightly underestimated the ground-based results.

ASTER cloud coverage reassessment using MODIS cloud mask products

NASA Astrophysics Data System (ADS)

Tonooka, Hideyuki; Omagari, Kunjuro; Yamamoto, Hirokazu; Tachikawa, Tetsushi; Fujita, Masaru; Paitaer, Zaoreguli

2010-10-01

In the Advanced Spaceborne Thermal Emission and Reflection radiometer (ASTER) Project, two kinds of algorithms are used for cloud assessment in Level-1 processing. The first algorithm based on the LANDSAT-5 TM Automatic Cloud Cover Assessment (ACCA) algorithm is used for a part of daytime scenes observed with only VNIR bands and all nighttime scenes, and the second algorithm based on the LANDSAT-7 ETM+ ACCA algorithm is used for most of daytime scenes observed with all spectral bands. However, the first algorithm does not work well for lack of some spectral bands sensitive to cloud detection, and the two algorithms have been less accurate over snow/ice covered areas since April 2008 when the SWIR subsystem developed troubles. In addition, they perform less well for some combinations of surface type and sun elevation angle. We, therefore, have developed the ASTER cloud coverage reassessment system using MODIS cloud mask (MOD35) products, and have reassessed cloud coverage for all ASTER archived scenes (>1.7 million scenes). All of the new cloud coverage data are included in Image Management System (IMS) databases of the ASTER Ground Data System (GDS) and NASA's Land Process Data Active Archive Center (LP DAAC) and used for ASTER product search by users, and cloud mask images are distributed to users through Internet. Daily upcoming scenes (about 400 scenes per day) are reassessed and inserted into the IMS databases in 5 to 7 days after each scene observation date. Some validation studies for the new cloud coverage data and some mission-related analyses using those data are also demonstrated in the present paper.

Maritime Aerosol Network optical depth measurements and comparison with satellite retrievals from various different sensors

NASA Astrophysics Data System (ADS)

Smirnov, Alexander; Petrenko, Maksym; Ichoku, Charles; Holben, Brent N.

2017-10-01

The paper reports on the current status of the Maritime Aerosol Network (MAN) which is a component of the Aerosol Robotic Network (AERONET). A public domain web-based data archive dedicated to MAN activity can be found at https://aeronet.gsfc.nasa.gov/new_web/maritime_aerosol_network.html . Since 2006 over 450 cruises were completed and the data archive consists of more than 6000 measurement days. In this work, we present MAN observations collocated with MODIS Terra, MODIS Aqua, MISR, POLDER, SeaWIFS, OMI, and CALIOP spaceborne aerosol products using a modified version of the Multi-Sensor Aerosol Products Sampling System (MAPSS) framework. Because of different spatio-temporal characteristics of the analyzed products, the number of MAN data points collocated with spaceborne retrievals varied between 1500 matchups for MODIS to 39 for CALIOP (as of August 2016). Despite these unavoidable sampling biases, latitudinal dependencies of AOD differences for all satellite sensors, except for SeaWIFS and POLDER, showed positive biases against ground truth (i.e. MAN) in the southern latitudes (<50° S), and substantial scatter in the Northern Atlantic "dust belt" (5°-15° N). Our analysis did not intend to determine whether satellite retrievals are within claimed uncertainty boundaries, but rather show where bias exists and corrections are needed.

Evaluating the Assumptions of Surface Reflectance and Aerosol Type Selection Within the MODIS Aerosol Retrieval Over Land: The Problem of Dust Type Selection

NASA Technical Reports Server (NTRS)

Mielonen, T.; Levy, R. C.; Aaltonen, V.; Komppula, M.; de Leeuw, G.; Huttunen, J.; Lihavainen, H.; Kolmonen, P.; Lehtinen, K. E. J.; Arola, A.

2011-01-01

Aerosol Optical Depth (AOD) and Angstrom exponent (AE) values derived with the MODIS 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 MODIS 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, MODIS indicates AE values close to 0.6 and zero fine model weighting (FMW), i.e. dust model provides the best fitting to the MODIS observed reflectance. 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 MODIS 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 reflectance at 660 and 2130 nm.

Optimization of a Deep Convective Cloud Technique in Evaluating the Long-Term Radiometric Stability of MODIS Reflective Solar Bands

NASA Technical Reports Server (NTRS)

Mu, Qiaozhen; Wu, Aisheng; Xiong, Xiaoxiong; Doelling, David R.; Angal, Amit; Chang, Tiejun; Bhatt, Rajendra

2017-01-01

MODIS reflective solar bands are calibrated on-orbit using a solar diffuser and near-monthly lunar observations. To monitor the performance and effectiveness of the on-orbit calibrations, pseudo-invariant targets such as deep convective clouds (DCCs), Libya-4, and Dome-C are used to track the long-term stability of MODIS Level 1B product. However, the current MODIS operational DCC technique (DCCT) simply uses the criteria set for the 0.65- m band. We optimize several critical DCCT parameters including the 11- micrometer IR-band Brightness Temperature (BT11) threshold for DCC identification, DCC core size and uniformity to help locate DCCs at convection centers, data collection time interval, and probability distribution function (PDF) bin increment for each channel. The mode reflectances corresponding to the PDF peaks are utilized as the DCC reflectances. Results show that the BT11 threshold and time interval are most critical for the Short Wave Infrared (SWIR) bands. The Bidirectional Reflectance Distribution Function model is most effective in reducing the DCC anisotropy for the visible channels. The uniformity filters and PDF bin size have minimal impacts on the visible channels and a larger impact on the SWIR bands. The newly optimized DCCT will be used for future evaluation of MODIS on-orbit calibration by MODIS Characterization Support Team.

A Comparison of Aerosol Measurements from OCO-2 and MODIS

NASA Astrophysics Data System (ADS)

Nelson, R. R.; O'Dell, C.

2016-12-01

The goal of OCO-2 is to use hyperspectral measurements of reflected near-infrared sunlight to retrieve carbon dioxide with high accuracy and precision. This is only possible, however, if the light-path modification effects caused by clouds and aerosols are properly quantified. Even tiny amounts of clouds or aerosols can induce sufficient light-path modifications to lead to large errors in the estimated CO2 column-mean (XCO2). Therefore, it is imperative to evaluate the accuracy of the OCO-2 retrieved aerosol parameters. In this study, we compare OCO-2 retrieved aerosol parameters to Aqua-MODIS observations co-located in time and space. We find that there are significant disagreements between the aerosol information derived from MODIS and the retrieved aerosol parameters from OCO-2. These results are unsurprising, as previous comparisons to AERONET have also been poor. However, the tight co-location between Aqua and OCO-2 in the Afternoon Constellation allows us to examine the potential synergistic use of OCO-2 and MODIS measurements to more accurately constrain aerosol properties, potentially leading to a more accurate CO2 measurement. Specifically, we used select MODIS aerosol properties as the a priori for the OCO-2 retrievals and present the results here. Future studies include investigating the possibility of ingesting the MODIS radiances directly into the OCO-2 retrieval algorithm to further improve OCO-2's aerosol scheme and the resulting measurements.

Estimating the Effect of Gypsy Moth Defloiation Using MODIS

NASA Technical Reports Server (NTRS)

deBeurs, K. M.; Townsend, P. A.

2008-01-01

The area of North American forests affected by gypsy moth defoliation continues to expand despite efforts to slow the spread. With the increased area of infestation, ecological, environmental and economic concerns about gypsy moth disturbance remain significant, necessitating coordinated, repeatable and comprehensive monitoring of the areas affected. In this study, our primary objective was to estimate the magnitude of defoliation using Moderate Resolution Imaging Spectroradiometer (MODIS) imagery for a gypsy moth outbreak that occurred in the US central Appalachian Mountains in 2000 and 2001. We focused on determining the appropriate spectral MODIS indices and temporal compositing method to best monitor the effects of gypsy moth defoliation. We tested MODIS-based Normalized Difference Vegetation Index (NDVI), Enhanced Vegetation Index (EVI), Normalized Difference Water Index (NDWI), and two versions of the Normalized Difference Infrared index (NDIIb6 and NDIIb7, using the channels centered on 1640 nm and 2130 nm respectively) for their capacity to map defoliation as estimated by ground observations. In addition, we evaluated three temporal resolutions: daily, 8-day and 16-day data. We validated the results through quantitative comparison to Landsat based defoliation estimates and traditional sketch maps. Our MODIS based defoliation estimates based on NDIIb6 and NDIIb7 closely matched Landsat defoliation estimates derived from field data as well as sketch maps. We conclude that daily MODIS data can be used with confidence to monitor insect defoliation on an annual time scale, at least for larger patches (greater than 0.63 km2). Eight-day and 16-day MODIS composites may be of lesser use due to the ephemeral character of disturbance by the gypsy moth.

Comparison of MODIS and VIIRS On-board Blackbody Performance

NASA Technical Reports Server (NTRS)

Xiong, Jack; Butler, Jim; Wu, Aisheng; Chiang, Vincent; McIntire, Jeff; Oudari, Hassan

2012-01-01

MODIS has 16 thermal emissive bands (TEBs), covering wavelengths from 3.7 to 14.4 microns. MODIS TEBs are calibrated on-orbit by a v-grooved blackbody (BB) on a scan-by-scan basis. The BB temperatures are measured by a set of 12 thennistors. As expected, the BB temperature uncertainty and stability have direct impact on the quality of TEB calibration and, therefore, the quality of the science products derived from TEB observations. Since launch, Terra and Aqua MODIS have successfully operated for more than 12 and 10 years, respectively. Their on-board BB performance has been satisfactory in meeting the TEB calibration requirements. The first VIIRS, launched on-board the Suomi NPP spacecraft on October 28, 2011, has successfully completed its initial Intensive Calibration and Validation (ICV) phase. VIIRS has 7 thermal emissive bands (TEBs), covering wavelengths from 3.7 to 12.4 microns. Designed with strong MODIS heritage, VIIRS uses a similar BB for its TEB calibration. Like MODIS, VIIRS BB is nominally controlled at a pre-determined temperature (set point). Periodically, a BB Warm-Up and Cool-Down (WUCD) operation is performed, during which the BB temperatures vary from instrument ambient (temperature) to 315K. This paper examines NPP VIIRS BB on-orbit performance. It focuses on its BB temperature scan-to-scan variations at nominally controlled temperature as well as during its WUCD operation and their impact on TEB calibration uncertainty. Comparisons of VIIRS (NPP) and MODIS (Terra and Aqua) BB on-orbit performance and lessons learned for future improvements are also presented in this paper.

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.