Search NASA⌕ Search

SEARCH · Search NASA

Results for “VIIRS”

Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 361 records · Page 20
All sourcesNASA NTRSDOE OSTI
NASA NTRSDate not supplied

Creating IR-verified Gridded Fire Burn Maps using Public NASA and Satellite Data

Even though fire can be devastating, wildland fire is a natural and integral force on our landscapes, providing value by decreasing fuels at the Wildland Urban Interface (WUI) to promote safe communities. However, uncontained wildfires can devastate communities, threaten our health, and result in substantial economic losses. There has been greater than a $50B increase in wildfire insurance claims from 2017-2021, which has been exacerbated by climate change. Our partners at Kettle reinsurance are focused on building a smarter reinsurance model for protecting today’s globalized world from the catastrophic effects of climate change. Our objective is to develop a high-confidence grid-based wildfire burn product using multiple sources of satellite data to determine whether a ‘conflagration' (fire larger than 999+ acres) has ‘breached’ a grid cell. This product will substantially decrease the time it takes for homeowners to receive payouts, from over a year to a couple months. Working with our partners at Kettle reinsurance, we use VIIRS (Visible Infrared Imaging Radiometer Suite) 375 m fire detections and Sentinel-2 10 m satellite imagery to create a 20-m gridded fire burn product. Our process is based on the level of confidence in the data source and takes into account vegetation change throughout the life of the fire. For example, Sentinel-2 vegetation-change indices have a higher level of confidence when congruent with VIIRS active-fire detection data, rather than VIIRS detections alone. We have also verified our fire burn product against MODIS/ASTER Airborne Simulator (MASTER) Infrared (IR) data from the Fire Influence on Regional to Global Environments Experiment - Air Quality (FIREX-AQ) 2019 campaign, with 88% overall agreement. The first iteration has been developed for responding to wildfires in California, with the possibility to expand nationwide and globally.

Emily Gargulinski↗
NASA NTRSDate not supplied

Data Fusion and Mining Techniques to Map Water Use and Drought across Spatial and Temporal Scales

As the world’s water resources come under increasing tension due to dual stressors of climate change and population growth, accurate knowledge of water consumption through evapotranspiration (ET) over a range in spatial scales will be critical in developing adaptation strategies. Remote sensing methods for monitoring consumptive water use (e.g, ET) are becoming increasingly important, especially in areas of significant water and food insecurity. One method to estimate ET from satellite-based methods, the Atmosphere Land Exchange Inverse (ALEXI) model uses the change in mid-morning land surface temperature to estimate the partitioning of sensible and latent heat fluxes which are then used to estimate daily ET. This presentation will outline several recent enhancements to the ALEXI modeling system, with a focus on global ET and drought monitoring. Until recently, ALEXI has been limited to areas with high resolution temporal sampling of geostationary sensors. The use of geostationary sensors makes global mapping a complicated process, especially for real-time applications, as data from as many as five different sensors are required to be ingested and harmonized to create a global mosaic. However, our research team has developed a new and novel method of using twice-daily observations from polar-orbiting sensors such as MODIS and VIIRS to estimate the mid-morning rise in LST that is used to drive the energy balance estimations within ALEXI. This allows the method to be applied globally using a single sensor (in this case, initially MODIS with a planned transition to VIIRS) rather than a global compositing of all available geostationary data. Other advantages of this new method include the higher spatial resolution provided by MODIS and VIIRS and the increased sampling at high latitudes where oblique view angles limit the utility of geostationary sensors. This presentation will focus on global applications for mapping water use and drought using data mining and data fusion across spatial scales extending from 5-km to 30-m “field-scale” estimates.

Christopher Hain↗
NASA NTRSDate not supplied

Utilizing Libya-4 to Intercalibrate Overlapping Sensors in the Same Sun-Synchronous Orbit

The NASA CERES observed SW and LW broadband fluxes are utilized by the climate community for monitoring the Earth’s energy imbalance and for climate model validation. The SNPP and NOAA20 CERES instruments and associated VIIRS imagers were launched into the same 1:30 PM mean local time sun-sun-synchronous orbits as well as the future NOAA22 Libera broadband instrument and VIIRS imager. The overlapping sensor records need to be intercalibrated to enable consistent broadband fluxes and imager cloud retrievals. The overlapping satellites are typically placed a half an orbit apart, thus preventing any simultaneous nadir overpass (SNO) events required for time-matched inter-calibration strategies. A Pseudo Invariant Calibration Site (PICS), such as Libya-4, can provide overlapping sensor radiometric scaling factors without the use of SNOs. The clear-sky Libya-4 observed radiances were characterized both spectrally and angularly and corrected for atmospheric effects. The Libya-4 natural variability was found to be consistent across the CERES and VIIRS records. This fact reveals that the sensor onboard calibration anomalies are smaller than the Libya-4 natural variability. By mitigating the Libya-4 natural variability will reduce the radiometric scaling factor uncertainty needed to provide both broadband flux and cloud retrieval continuity across the overlapping sensor records.

D R Doelling↗
NASA NTRS2024

Sensitivity studies of nighttime top-of-atmosphere radiances from artificial light sources using a 3-D radiative transfer model for nighttime aerosol retrievals

By accounting for surface-based light source emissions and top-of-atmosphere (TOA) downward lunar fluxes, we adapted the spherical harmonics discrete ordinate method (SHDOM) 3-dimensional (3-D) radiative transfer model (RTM) to simulate nighttime 3-D TOA radiances as observed from the Visible Infrared Imaging Radiometer Suite (VIIRS) Day/Night Band (DNB) on board the Suomi-NPP satellite platform. Used previously for daytime 3-D applications, these new SHDOM enhancements allow for the study of the impacts of various observing conditions and aerosol properties on simulated VIIRS-DNB TOA radiances. Observations over Dakar, Senegal, selected for its bright city lights and a large range of aerosol optical depth (AOD), were investigated for potential applications and opportunities for using observed radiances containing VIIRS-DNB “bright pixels” from artificial light sources to conduct aerosol retrievals. We found that using the standard deviation (SD) of such bright pixels provided a more stable quantity for nighttime AOD retrievals than direct retrievals from TOA radiances. Further, both the mean TOA radiance and SD of TOA radiances over artificial sources are significantly impacted by satellite viewing angles. Light domes, the enhanced radiances adjacent to artificial light sources, are strong functions of aerosol properties and especially aerosol vertical distribution, which may be further utilized for retrieving aerosol layer height in future studies. Through inter-comparison with both day- and nighttime Aerosol Robotic Network (AERONET) data, the feasibility of retrieving nighttime AODs using 3-D RTM SHDOM over artificial light sources was demonstrated. Our study shows strong potential for using artificial light sources for nighttime AOD retrievals, while also highlighting larger uncertainties in quantifying surface light source emissions. This study underscores the need for surface light emission source characterizations as a key boundary condition, which is a complex task that requires enhanced input data and further research. We demonstrate how quality-controlled nighttime light data from NASA’s Black Marble product suite could serve as a primary input into estimations of surface light source emissions for nighttime aerosol retrievals.

Jianglong Zhang↗
DOE OSTI2025

Illuminating the Night: A Survey of Super-Resolution Methods for Nighttime Light Images

Nighttime Light (NTL) images provide critical insights into urbanization, disaster response, and energy consumption. The VIIRS Day/Night Band (DNB) sensor offers high-quality NTL imagery with daily revisit rates, but the available spatial resolution hinders fine-grained accurate analysis. Super-resolution techniques aim to increase the resolution of NTL images, enabling more detailed assessments of infrastructure, light pollution, economic activity, and power outages. However, existing state-of-the-art super-resolution methods designed for natural images struggle with the unique characteristics of NTL data. This work provides a comprehensive review of super-resolution methods across multiple image modalities, evaluates their effectiveness on VI-IRS DNB data, and proposes a multi-modal super-resolution approach tailored to NTL imagery. The proposed approach integrates VIIRS DNB data with road networks and land use information to improve reconstruction accuracy and spatial detail. Code is available for this project athttps://code.ornl.gov/viirs-sr/sr-demos.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
NASA NTRS2013

Requirements for a Moderate-Resolution Infrared Imaging Sounder (MIRIS)

The high cost of imaging and sounding from space warrants exploration of new methods for obtaining the required information, including changing the spectral band sets, employing new technologies and merging instruments. In some cases we must consider relaxation of the current capability. In others, we expect higher performance. In general our goal is to meet the VIIRS and CrIS requirements while providing the enhanced next generation capabilities: 1) Hyperspectral Imaging in the Vis/NIR bands, 2) High Spatial Resolution Sounding in the Infrared bands. The former will improve the accuracy of ocean color products, aerosols and water vapor, surface vegetation and geology. The latter will enable the high-impact achieved by the current suite of hyperspectral infrared sounders to be achieved by the next generation high resolution forecast models. We examine the spectral, spatial and radiometric requirements for a next generation system and technologies that can be applied from the available inventory within government and industry. A two-band grating spectrometer instrument called the Moderate-resolution Infrared Imaging Sounder (MIRIS) is conceived that, when used with the planned NASA PACE Ocean Color Instrument (OCI) will meet the vast majority of CrIS and VIIRS requirements in the all bands and provide the next generation capabilities desired. MIRIS resource requirements are modest and the Technology Readiness Level is high leading to the expectation that the cost and risk of MIRIS will be reasonable.

Atmospheric Infrared Sounder (AIRS)↗
NASA NTRS2014

On-Orbit Performance of MODIS Solar Diffuser Stability Monitor

MODIS reflective solar bands (RSB) calibration is provided by an on-board solar diffuser (SD). On-orbit changes in the SD bi-directional reflectance factor (BRF) are tracked by a solar diffuser stability monitor (SDSM). The SDSM consists of a solar integration sphere (SIS) with nine detectors covering wavelengths from 0.41 to 0.94 microns. It functions as a ratioing radiometer, making alternate observations of the sunlight through a fixed attenuation screen and the sunlight diffusely reflected from the SD during each scheduled SD/SDSM calibration event. Since launch, Terra and Aqua MODIS SD/SDSM systems have been operated regularly to support the RSB on-orbit calibration. This paper provides an overview of MODIS SDSM design functions, its operation and calibration strategies, and on-orbit performance. Changes in SDSM detector responses over time and their potential impact on tracking SD on-orbit degradation are examined. Also presented in this paper are lessons learned from MODIS SD/SDSM calibration system and improvements made to the VIIRS SD/SDSM system, including preliminary comparisons of MODIS and VIIRS SDSM on-orbit performance.

MODIS↗
NASA NTRS2017

Forecasting Ocean Chlorophyll in the Equatorial Pacific

Using a global ocean biogeochemical model combined with a forecast of physical oceanic and atmospheric variables from the NASA Global Modeling and Assimilation Office, we assess the skill of a chlorophyll concentrations forecast in the Equatorial Pacific for the period 2012-2015 with a focus on the forecast of the onset of the 2015 El Niño event. Using a series of retrospective 9-month hindcasts, we assess the uncertainties of the forecasted chlorophyll by comparing the monthly total chlorophyll concentration from the forecast with the corresponding monthly ocean chlorophyll data from the Suomi-National Polar-orbiting Partnership Visible Infrared Imaging Radiometer Suite (S-NPP VIIRS) satellite. The forecast was able to reproduce the phasing of the variability in chlorophyll concentration in the Equatorial Pacific, including the beginning of the 2015-2016 El Niño. The anomaly correlation coefficient (ACC) was significant (p less than 0.05) for forecast at 1-month (R=0.33), 8-month (R=0.42) and 9-month (R=0.41) lead times. The root mean square error (RMSE) increased from 0.0399 microgram ch1 L(exp -1) for the 1-month lead forecast to a maximum of 0.0472 microgram ch1 L(exp -1) for the 9-month lead forecast indicating that the forecast of the amplitude of chlorophyll concentration variability was getting worse. Forecasts with a 3-month lead time were on average the closest to the S-NPP VIIRS data (23% or 0.033 microgram ch1 L(exp -1)) while the forecast with a 9-month lead time were the furthest (31% or 0.042 microgram ch1 L(exp -1)). These results indicate the potential for forecasting chlorophyll concentration in this region but also highlights various deficiencies and suggestions for improvements to the current biogeochemical forecasting system. This system provides an initial basis for future applications including the effects of El Niño events on fisheries and other ocean resources given improvements identified in the analysis of these results.

Anomaly Correlation Coefficient (ACC)↗
NASA NTRS2019

Surface Roughness-Induced Spectral Degradation of Multi-Spaceborne Solar Diffusers Due to Space Radiation Exposure

Solar diffusers (SDs) have often been used as the onboard calibrators for the radiometric calibration of reflective solar band imaging sensors. After being spaceborne, the reflectance of SDs is observed to degrade with spectral dependence due to exposure to solar UV and energetic particle radiation. Long-term spectral reflectance data of SDs onboard multiple LEO imaging sensors, such as the Moderate Resolution Imaging Spectroradiometer (MODIS) on Terra and Aqua and the Visible Infrared Imaging Radiometer Suite (VIIRS) on SNPP, are analyzed. The reflectance of SDs on these three instruments degrades faster for the shorter wavelength (0.4-0.6 μm) bands than the longer wavelength bands. The Surface Roughness-induced Rayleigh Scattering (SRRS) model is applied to simulate the SD degradation on these instruments, and the growth of the surface roughness parameter of the SDs is derived. It is determined that the change of surface roughness scale length is ~tens of nanometers. To show the consistency of roughness growth rates among the SDs on Terra/Aqua MODIS and SNPP VIIRS instruments, the functional dependences of the growth rates are characterized according to the SD exposure time and the stage of surface roughness. It is also found that the flattening or reverse in the growth trend of the surface roughness for these three SDs occurred around the same interval between October 2013 and October 2015. The confirmation of the applicability of SRRS model with the long-term spectral reflectance data from three independent spaceborne SDs facilitates a better understanding of the origin and physical processes of the SD degradation.

Visible Infrared Imaging Radiometer Suite (VIIRS)↗
NASA NTRSDate not supplied

CLARREO Pathfinder as a SI-traceable Reference for Satellite Intercalibration

The Climate Absolute Radiance and Refractivity Observatory (CLARREO) Pathfinder (CPF) consists of an Earthviewing reflected solar (RS) spectrometer that will measure the Earth-reflected solar radiation from International Space Station with an SI-traceable radiometric uncertainty of 0.3% (1-sigma). The high-accuracy CPF measurements will provide an in-orbit reference for intercalibrating other spaceflight RS instruments. The CPF intercalibration team has been tasked to develop a state-of-the-art approach to calibrate the shortwave channel (300-5000 nm) of the Clouds and the Earth’s Radiant Energy System (CERES) instrument and the reflective solar bands (RSB) of the Visible Infrared Imaging Radiometer Suite (VIIRS) instrument, both onboard the NOAA-20 satellite, against the CPF benchmark measurements. The aimed intercalibration methodology uncertainty for both the target instruments is also 0.3%. To meet this stringent intercalibration accuracy, the CPF team has developed methods for mitigating the impacts of spatial, spectral, and angular differences between the intercalibration footprints from the CPF and target instruments. To further alleviate uncertainty, the CPF team will employ Polarization Distribution Models (PDMs) to characterize the polarization state of the Earth-reflected radiance as a function of the intercalibration footprint scene type, solar and viewing geometry, and wavelength. The PDMs will assist in identifying low-polarized scene radiances for meticulously intercalibrating the polarization sensitive VIIRS instrument against the significantly-less polarization-sensitive CPF instrument. This paper will highlight the CPF mission overview, the details of the CPF intercalibration approach, and additional outcomes of the CPF intercalibration studies that may benefit the broader remote sensing community.community.

Hyperspectral↗
NASA NTRSDate not supplied

The Impact of Pixel Size on the Characterization of Deep Convective Clouds for Calibration

The NASA CERES project provides the scientific community the observed TOA SW and LW fluxes for climate monitoring and climate model validation. CERES utilizes hourly geostationary imager derived broadband fluxes, which rely on the channel radiances and associated cloud retrievals, are used to estimate the broadband fluxes between CERES observations. This requires stable and consistent cross-platform imager visible channel calibration. The CERES project utilizes deep convective clouds (DCC) as an invariant Earth target to both monitor the stability of sensors and for radiometric scaling. GSICS, an international collaboration, is also evaluating and implementing the DCC invariant target calibration methodology to provide consistent calibration coefficients across geostationary imagers anchored to the AquaMODIS or the NOAA-20 VIIRS calibration reference. Tropical DCC are the brightest, coldest, most Lambertian, top of the atmosphere Earth targets. The DCC invariant target calibration methodology relies on a large ensemble of tropical D CC-identified pixel-level reflectances, which are aggregated as probability density functions (PDF). By assuming the monthly PDF shape is otherwise consistent in time excepting shifts in reflectance caused by changes in the sensor calibration, the imager stability is monitored. Radiometric scaling is accomplished by ratioing the sensor pair DCC PDF reflectance values. The success of the DCC methodology relies on consistent PDF distributions. The goal of this study is to determine the impact of pixel resolution on the DCC reflectance distribution. Single SNPP-VIIRS 750-m and Landsat 8 OLI 30-m granules are aggregated to degrade the pixel resolution from the native level. The DCC pixels are identified using a BT threshold. Most of the brightest DCC pixels are also the coldest, although there are exceptions. It was found that increasing the BT threshold exponentially increased the number of darker pixels. The pixel resolution did not seem to impact the DCC reflectance PDF distribution for pixel resolutions less than 3 km, which suggests that imagers of varying pixel resolutions may be radiometrically scaled to each other using DCC targets.

DCC↗
DOE OSTI2023

Updating and Evaluating Anthropogenic Emissions for NOAA’s Global Ensemble Forecast Systems for Aerosols (GEFS-Aerosols): Application of an SO 2 Bias-Scaling Method

We updated the anthropogenic emissions inventory in NOAA’s operational Global Ensemble Forecast for Aerosols (GEFS-Aerosols) to improve the model’s prediction of aerosol optical depth (AOD). We used a methodology to quickly update the pivotal global anthropogenic sulfur dioxide (SO 2 ) emissions using a speciated AOD bias-scaling method. The AOD bias-scaling method is based on the latest model predictions compared to NASA’s Modern-Era Retrospective analysis for Research and Applications, version 2 (MERRA2). The model bias was subsequently applied to the CEDS 2019 SO 2 emissions for adjustment. The monthly mean GEFS-Aerosols AOD predictions were evaluated against a suite of satellite observations (e.g., MISR, VIIRS, and MODIS), ground-based AERONET observations, and the International Cooperative for Aerosol Prediction (ICAP) ensemble results. The results show that transitioning from CEDS 2014 to CEDS 2019 emissions data led to a significant improvement in the operational GEFS-Aerosols model performance, and applying the bias-scaled SO 2 emissions could further improve global AOD distributions. The biases of the simulated AODs against the observed AODs varied with observation type and seasons by a factor of 3~13 and 2~10, respectively. The global AOD distributions showed that the differences in the simulations against ICAP, MISR, VIIRS, and MODIS were the largest in March–May (MAM) and the smallest in December–February (DJF). When evaluating against the ground-truth AERONET data, the bias-scaling methods improved the global seasonal correlation (r), Index of Agreement (IOA), and mean biases, except for the MAM season, when the negative regional biases were exacerbated compared to the positive regional biases. The effect of bias-scaling had the most beneficial impact on model performance in the regions dominated by anthropogenic emissions, such as East Asia. However, it showed less improvement in other areas impacted by the greater relative transport of natural emissions sources, such as India. The accuracies of the reference observation or assimilation data for the adjusted inputs and the model physics for outputs, and the selection of regions with less seasonal emissions of natural aerosols determine the success of the bias-scaling methods. A companion study on emission scaling of anthropogenic absorbing aerosols needs further improved aerosol prediction.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS2006

Remote Sensing Time Series Product Tool

The TSPT (Time Series Product Tool) software was custom-designed for NASA to rapidly create and display single-band and band-combination time series, such as NDVI (Normalized Difference Vegetation Index) images, for wide-area crop surveillance and for other time-critical applications. The TSPT, developed in MATLAB, allows users to create and display various MODIS (Moderate Resolution Imaging Spectroradiometer) or simulated VIIRS (Visible/Infrared Imager Radiometer Suite) products as single images, as time series plots at a selected location, or as temporally processed image videos. Manually creating these types of products is extremely labor intensive; however, the TSPT development tool makes the process simplified and efficient. MODIS is ideal for monitoring large crop areas because of its wide swath (2330 km), its relatively small ground sample distance (250 m), and its high temporal revisit time (twice daily). Furthermore, because MODIS imagery is acquired daily, rapid changes in vegetative health can potentially be detected. The new TSPT technology provides users with the ability to temporally process high-revisit-rate satellite imagery, such as that acquired from MODIS and from its successor, the VIIRS. The TSPT features the important capability of fusing data from both MODIS instruments onboard the Terra and Aqua satellites, which drastically improves cloud statistics. With the TSPT, MODIS metadata is used to find and optionally remove bad and suspect data. Noise removal and temporal processing techniques allow users to create low-noise time series plots and image videos and to select settings and thresholds that tailor particular output products. The TSPT GUI (graphical user interface) provides an interactive environment for crafting what-if scenarios by enabling a user to repeat product generation using different settings and thresholds. The TSPT Application Programming Interface provides more fine-tuned control of product generation, allowing experienced programmers to bypass the GUI and to create more user-specific output products, such as comparison time plots or images. This type of time series analysis tool for remotely sensed imagery could be the basis of a large-area vegetation surveillance system. The TSPT has been used to generate NDVI time series over growing seasons in California and Argentina and for hurricane events, such as Hurricane Katrina.

Predos, Don↗
NASA NTRS2007

Solutions Network Formulation Report. Aerosol Polarimetry Sensor Measurements of Diffuse-to-Global Irradiance Ratio for Improved Forecasting of Plant Productivity and Health

Studies have shown that vegetation is directly sensitive to changes in the diffuse-to-global irradiance ratio and that increased percentage of diffuse irradiation can accelerate photosynthesis. Therefore, measurements of diffuse versus global irradiance could be useful for monitoring crop productivity and overall vegetative health as they relate to the total amount of particulates in the air that result from natural disasters or anthropogenic (manmade) causes. While the components of solar irradiance are measured by satellite and surface sensors and calculated with atmospheric models, disagreement exists between the results, creating a need for more accurate and comprehensive retrievals of atmospheric aerosol parameters. Two satellite sensors--APS and VIIRS--show promise for retrieving aerosol properties at an unprecedented level of accuracy. APS is expected to be launched in December 2008. The planned launch date for VIIRS onboard NPP is September 2009. Identified partners include the USDA s ARS, North Carolina State University, Purdue Climate Change Research Center, and the Cooperative Institute for Research in the Atmosphere at Colorado State University. Although at present no formal DSSs (decision support systems) require accurate values of diffuse-to-global irradiance, this parameter is sufficiently important that models are being developed that will incorporate these measurements. This candidate solution is aligned with the Agricultural Efficiency and Air Quality National Applications.

Knowlton, Kelly↗
NASA NTRS2007

Solutions Network Formulation Report. Using NASA Sensors to Perform Crop Type Assessment for Monitoring Insect Resistance in Corn

The EPA (U.S. Environmental Protection Agency) is tasked to monitor for insect pest resistance to transgenic crops. Several models have been developed to understand the resistance properties of insects. The Population Genetics Simulator model is used in the EPA PIRDSS (Pest Infestation and Resistance Decision Support System). The EPA Office of Pesticide Programs uses the DSS to help understand the potential for insect pest resistance development and the likelihood that insect pest resistance will negatively affect transgenic corn. Once the DSS identifies areas of concern, crews are deployed to collect insect pest samples, which are tested to identify whether they have developed resistance to the toxins in transgenic corn pesticides. In this candidate solution, VIIRS (Visible/Infrared Imager/Radiometer Suite) vegetation index products will be used to build hypertemporal layerstacks for crop type and phenology assessment. The current phenology attribute is determined by using the current time of year to index the expected growth stage of the crop. VIIRS might provide more accurate crop type assessment and also might give a better estimate on the crop growth stage.

Lewis, David↗
NASA NTRS2011

A Satellite-Derived Climate-Quality Data Record of the Clear-Sky Surface Temperature of the Greenland Ice Sheet

We have developed a climate-quality data record of the clear-sky surface temperature of the Greenland Ice Sheet using the Moderate-Resolution Imaging Spectroradiometer (MODIS) Terra ice-surface temperature (1ST) algorithm. A climate-data record (CDR) is a time series of measurements of sufficient length, consistency, and continuity to determine climate variability and change. We present daily and monthly Terra MODIS ISTs of the Greenland Ice Sheet beginning on 1 March 2000 and continuing through 31 December 2010 at 6.25-km spatial resolution on a polar stereographic grid within +/-3 hours of 17:00Z or 2:00 PM Local Solar Time. Preliminary validation of the ISTs at Summit Camp, Greenland, during the 2008-09 winter, shows that there is a cold bias using the MODIS IST which underestimates the measured surface temperature by approximately 3 C when temperatures range from approximately -50 C to approximately -35 C. The ultimate goal is to develop a CDR that starts in 1981 with the Advanced Very High Resolution (AVHRR) Polar Pathfinder (APP) dataset and continues with MODIS data from 2000 to the present. Differences in the APP and MODIS cloud masks have so far precluded the current IST records from spanning both the APP and MODIS IST time series in a seamless manner though this will be revisited when the APP dataset has been reprocessed. The Greenland IST climate-quality data record is suitable for continuation using future Visible Infrared Imager Radiometer Suite (VIIRS) data and will be elevated in status to a CDR when at least 9 more years of climate-quality data become available either from MODIS Terra or Aqua, or from the VIIRS. The complete MODIS IST data record will be available online in the summer of 2011.

Hall, Dorothy K.↗
NASA NTRS2011

Requirements for an Advanced Ocean Radiometer

This document suggests requirements for an advanced ocean radiometer, such as e.g. the ACE (Aerosol/Cloud/Ecosystem) ocean radiometer. The ACE ocean biology mission objectives have been defined in the ACE Ocean Biology white paper. The general requirements presented therein were chosen as the basis for the requirements provided in this document, which have been transformed into specific, testable requirements. The overall accuracy goal for the advanced ocean radiometer is that the total radiometric uncertainties are 0.5% or smaller for all bands. Specific mission requirements of SeaWiFS, MODIS, and VIIRS were often used as a model for the requirements presented here, which are in most cases more demanding than the heritage requirements. Experience with on-orbit performance and calibration (from SeaWiFS and MODIS) and prelaunch testing (from SeaWiFS, MODIS, and VIIRS) were important considerations when formulating the requirements. This document describes requirements in terms of the science data products, with a focus on qualities that can be verified by prelaunch radiometric characterization. It is expected that a more comprehensive requirements document will be developed during mission formulation

Meister, Gerhard↗
NASA NTRS2012

A Satellite-Derived Climate-Quality Data Record of the Clear-Sky Surface Temperature of the Greenland Ice Sheet

We have developed a climate-quality data record of the clear-sky surface temperature of the Greenland Ice Sheet using the Moderate-Resolution Imaging Spectroradiometer (MODIS) ice-surface temperature (1ST) algorithm. A climate-data record (CDR) is a time series of measurements of sufficient length, consistency, and continuity to determine climate variability and change. We present daily and monthly MODIS ISTs of the Greenland Ice Sheet beginning on 1 March 2000 and continuing through 31 December 2010 at 6.25-km spatial resolution on a polar stereographic grid. This record will be elevated in status to a CDR when at least nine more years of data become available either from MODIS Terra or Aqua, or from the Visible Infrared Imager Radiometer Suite (VIIRS) to be launched in October 2011. Our ultimate goal is to develop a CDR that starts in 1981 with the Advanced Very High Resolution (AVHRR) Polar Pathfinder (APP) dataset and continues with MODIS data from 2000 to the present, and into the VIIRS era. Differences in the APP and MODIS cloud masks have so far precluded the current 1ST records from spanning both the APP and MODIS time series in a seamless manner though this will be revisited when the APP dataset has been reprocessed. The complete MODIS 1ST daily and monthly data record is available online.

Hall, Dorothy K.↗