SEARCH · Search NASA

Results for “Geostationary”

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.

SourceResearch connectionFrom yearThrough year

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

At least 163 records · Page 9

All sources NASA NTRS DOE OSTI

NASA NTRS2011

High Impact Weather Forecasts and Warnings with the GOES-R Geostationary Lightning Mapper (GLM)

The Geostationary Operational Environmental Satellite (GOES-R) is the next series to follow the existing GOES system currently operating over the Western Hemisphere. A major advancement over the current GOES include a new capability for total lightning detection (cloud and cloud-to-ground flashes) from the Geostationary Lightning Mapper (GLM). The GLM will operate continuously day and night with near-uniform spatial resolution of 8 km with a product refresh rate of less than 20 sec over the Americas and adjacent oceanic regions. This will aid in forecasting severe storms and tornado activity, and convective weather impacts on aviation safety and efficiency. In parallel with the instrument development, a GOES-R Risk Reduction Science Team and Algorithm Working Group Lightning Applications Team have begun to develop cal/val performance monitoring tools and new applications using the GLM alone, in conjunction with other instruments, and merged or blended integrated observing system products combining satellite, radar, in-situ and numerical models. Proxy total lightning data from the NASA Lightning Imaging Sensor (LIS) on the Tropical Rainfall Measuring Mission (TRMM) satellite and regional ground-based lightning networks are being used to develop the pre-launch algorithms, test data sets, and applications, as well as improve our knowledge of thunderstorm initiation and evolution. In this presentation we review the planned implementation of the instrument and suite of operational algorithms.

Goodman, Steven J.↗

NASA NTRS2013

The Use of the Deep Convective Cloud Technique (DCCT) to Monitor On-Orbit Performance of the Geostationary Lightning Mapper (GLM): Use of Lightning Imaging Sensor (LIS) Data as Proxy

The Geostationary Lightning Mapper (GLM) on the next generation Geostationary Operational Environmental Satellite-R (GOES-R) will not have onboard calibration capability to monitor its performance. The Lightning Imaging Sensor (LIS) onboard the Tropical Rainfall Measuring Mission (TRMM) satellite has been providing observations of total lightning over the Earth's Tropics since 1997. The GLM design is based on LIS heritage, making it a good proxy dataset. This study examines the performance of LIS throughout its time in orbit. This was accomplished through application of the Deep Convective Cloud Technique (DCCT) (Doelling et al., 2004) to LIS background pixel radiance data. The DCCT identifies deep convective clouds by their cold Infrared (IR) brightness temperatures and using them as invariant targets in the solar reflective portion of the solar spectrum. The GLM and LIS operate in the near-IR at a wavelength of 777.4 nm. In the present study the IR data is obtained from the Visible Infrared Sensor (VIRS) which is collocated with LIS onboard the Tropical Rainfall Measuring Mission (TRMM) satellite. The DCCT is applied to LIS observations for July and August of each year from 1998-2010. The resulting distributions of LIS background DCC pixel radiance for each July August are very similar, indicating stable performance. The mean radiance of the DCCT analysis does not show a long term trend and the maximum deviation of the July August mean radiance for each year is within 0.7% of the overall mean. These results demonstrate that there has been no discernible change in LIS performance throughout its lifetime. A similar approach will used for monitoring the performance of GLM, with cold clouds identified using IR data from the Advanced Baseline Imager (ABI) which will also be located on GOES-R. Since GLM is based on LIS design heritage, the LIS results indicate that GLM should also experience stable performance over its lifetime.

Buechler, Dennis E.↗

NASA NTRS2013

Investigating the Use of Deep Convective Clouds (DCCT) to Monitor On-orbit Performance of the Geostationary Lightning Mapper (GLM) using Lightning Imaging Sensor (LIS) Measurements

There is a need to monitor the on-orbit performance of the Geostationary Lightning Mapper (GLM) on the Geostationary Operational Environmental Satellite R (GOES-R) for changes in instrument calibration that will affect GLM's lightning detection efficiency. GLM has no onboard calibration so GLM background radiance observations (available every 2.5 min) of Deep Convective Clouds (DCCs) are investigated as invariant targets to monitor GLM performance. Observations from the Lightning Imaging Sensor (LIS) and the Visible and Infrared Scanner (VIRS) onboard the Tropical Rainfall Measuring Mission (TRMM) satellite are used as proxy datasets for GLM and ABI 11 m measurements.

Buechler, Dennis E.↗

NASA NTRS2014

Assessment of the Pseudo Geostationary Lightning Mapper Products at the Spring Program and Summer Experiment

Since 2010, the de facto Geostationary Lightning Mapper (GLM) demonstration product has been the Pseudo‐Geostationary Lightning Mapper (PGLM) product suite. Originally prepared for the Hazardous Weather Testbed's Spring Program (specifically the Experimental Warning Program) when only four ground‐based lightning mapping arrays were available, the effort now spans collaborations with several institutions and eight collaborative networks. For 2013, NASA's Short‐term Prediction Research and Transition (SPoRT) Center and NOAA's National Severe Storms Laboratory have worked to collaborate with each network to obtain data in real‐time. This has gone into producing the SPoRT variant of the PGLM that was demonstrated in AWIPS II for the 2013 Spring Program. Alongside the PGLM products, the SPoRT / Meteorological Development Laboratory's total lightning tracking tool also was evaluated to assess not just another visualization of future GLM data but how to best extract more information while in the operational environment. Specifically, this tool addressed the leading request by forecasters during evaluations; provide a time series trend of total lightning in real‐time. In addition to the Spring Program, SPoRT is providing the PGLM "mosaic" to the Aviation Weather Center (AWC) and Storm Prediction Center. This is the same as what is used at the Hazardous Weather Testbed, but combines all available networks into one display for use at the national centers. This year, the mosaic was evaluated during the AWC's Summer Experiment. An important distinction between this and the Spring Program is that the Summer Experiment focuses on the national center perspective and not at the local forecast office level. Specifically, the Summer Experiment focuses on aviation needs and concerns and brings together operational forecaster, developers, and FAA representatives. This presentation will focus on the evaluation of SPoRT's pseudo‐GLM products in these separate test beds. The emphasis will be on how future GLM observations can support operations at both the local and national scale and how the PGLM was used in combination with other lightning data sets. Evaluations for the PGLM were quite favorable with forecasters appreciating the high temporal resolution, the ability to look for rapid increases in lightning activity ahead of severe weather, as well as situational awareness for where convection is firing and for flight routing.

Stano, Geoffrey T.↗

NASA NTRS2011

NEXRAD-In-Space: A Geostationary Orbiting Doppler Radar for Hurricane Monitoring and Studies

Under NASA's Earth Science Technology Program, a novel mission concept has been developed for detailed monitoring of hurricanes, cyclones, and severe storms from a geostationary orbit: "NEXRAD in Space" (NIS). By operating in the Geostationary Earth Orbit (GEO), NIS would enable rapid-update sampling (less than or equal to 1 hour cadence) of three dimenional fields of 35 GHz (Ka-band) radar reflectivity factor (Z) and line-of-sight Doppler velocity (VD) profiles, at mesoscale horizontal resolutions (approx. 10 km) over a circular Earth region of approximately 5300 km in diameter (equivalent to much of an oceanic basin, such as the Atlantic). NIS GEO-radar concept was chosen as one of only four potential post-2020 missions for the Weather Focus area in the 2007-2016 NASA Science Mission Directorate (SMD) Science Plan. The results of the first project aiming at developing the NIS concept highlighted the enormous potential of such mission, and the technological challenges presented by it. In essence, it is because of its rapid-cadence capability that NIS science planning is focusing on hurricane monitoring and prediction. Hurricanes, or generically tropical cyclones (TCs), have always been among the most devastating natural phenomena. This has been painfully reiterated in recent years with a number of powerful TCs landfalling in North America and elsewhere. In April 2007, the first NIS Science Workshop was convened at the University of Miami to galvanize the scientific community's interest in NIS's measurement capabilities for improved TC monitoring and prediction. The general consensus of the workshop was that a GEO Doppler radar would provide a major breakthrough in regards to the observation of TCs, and, when combined with cloud-resolving numerical weather prediction (NWP) models. This paper presents brief summaries of the instrument concept, the current technology status, the anticipated impacts on hurricane monitoring and model prediction, and the future science and technology roadmap.

precipitation↗

NASA NTRS2008

GEO/SAMS - The Geostationary Synthetic Aperture Microwave Sounder

The National Oceanic and Atmospheric Administration (NOAA) has for many years operated two weather satellite systems, the Polar-orbiting Operational Environmental Satellite system (POES), using low-earth orbiting (LEO) satellites, and the Geostationary Operational Environmental Satellite system (GOES), using geostationary earth orbiting (GEO) satellites. (Similar systems are also operated by other nations.) The POES satellites have been equipped with both infrared (IR) and microwave (MW) atmospheric sounders, which makes it possible to determine the vertical distribution of temperature and humidity in the troposphere even under cloudy conditions. Such satellite observations have had a significant impact on weather forecasting accuracy, especially in regions where in situ observations are sparse. In contrast, the GOES satellites have only been equipped with IR sounders, since it has not been feasible to build a large enough antenna to achieve sufficient spatial resolution for a MW sounder in GEO. As a result, GOES soundings can only be obtained in cloud free areas and in the less important upper atmosphere, above the cloud tops. This has hindered the effective use of GOES data in numerical weather prediction. Full sounding capabilities with the GOES system is highly desirable because of the advantageous spatial and temporal coverage that is possible from GEO. While POES satellites provide coverage in relatively narrow swaths, and with a revisit time of 12-24 hours or more, GOES satellites can provide continuous hemispheric coverage, making it possible to monitor highly dynamic phenomena such as hurricanes.

Lambrigtsen, Bjorn H.↗

NASA NTRS2015

Spatial and Temporal Variability of Trace Gas Columns Derived from WRF/Chem Regional Model Output: Planning for Geostationary Observations of Atmospheric Composition

We quantify both the spatial and temporal variability of column integrated O3, NO2, CO, SO2, and HCHO over the Baltimore / Washington, DC area using output from the Weather Research and Forecasting model with on-line chemistry (WRF/Chem) for the entire month of July 2011, coinciding with the first deployment of the NASA Earth Venture program mission Deriving Information on Surface conditions from Column and Vertically Resolved Observations Relevant to Air Quality (DISCOVER-AQ). Using structure function analyses, we find that the model reproduces the spatial variability observed during the campaign reasonably well, especially for O3. The Tropospheric Emissions: Monitoring of Pollution (TEMPO) instrument will be the first NASA mission to make atmospheric composition observations from geostationary orbit and partially fulfills the goals of the Geostationary Coastal and Air Pollution Events (GEO-CAPE) mission. We relate the simulated variability to the precision requirements defined by the science traceability matrices of these space-borne missions. Results for O3 from 0- 2 km altitude indicate that the TEMPO instrument would be able to observe O3 air quality events over the Mid-Atlantic area, even on days when the violations of the air quality standard are not widespread. The results further indicated that horizontal gradients in CO from 0-2 km would be observable over moderate distances (≥ 20 km). The spatial and temporal results for tropospheric column NO2 indicate that TEMPO would be able to observe not only the large urban plumes at times of peak production, but also the weaker gradients between rush hours. This suggests that the proposed spatial and temporal resolutions for these satellites as well as their prospective precision requirements are sufficient to answer the science questions they are tasked to address.

TEMPO↗

NASA NTRS2014

Geostationary Coastal and Air Pollution Events (GEO-CAPE) Sensitivity Analysis Experiment

Geostationary Coastal and Air pollution Events (GEO-CAPE) is a NASA decadal survey mission to be designed to provide surface reflectance at high spectral, spatial, and temporal resolutions from a geostationary orbit necessary for studying regional-scale air quality issues and their impact on global atmospheric composition processes. GEO-CAPE's Atmospheric Science Questions explore the influence of both gases and particles on air quality, atmospheric composition, and climate. The objective of the GEO-CAPE Observing System Simulation Experiment (OSSE) is to analyze the sensitivity of ozone to the global and regional NOx emissions and improve the science impact of GEO-CAPE with respect to the global air quality. The GEO-CAPE OSSE team at Jet propulsion Laboratory has developed a comprehensive OSSE framework that can perform adjoint-sensitivity analysis for a wide range of observation scenarios and measurement qualities. This report discusses the OSSE framework and presents the sensitivity analysis results obtained from the GEO-CAPE OSSE framework for seven observation scenarios and three instrument systems.

Lee, Meemong↗

NASA NTRS2016

Post Launch Calibration and Testing of the Geostationary Lightning Mapper on GOES-R Satellite

The Geostationary Operational Environmental Satellite R (GOES-R) series is the planned next generation of operational weather satellites for the United States National Oceanic and Atmospheric Administration (NOAA). The National Aeronautics and Space Administration (NASA) is procuring the GOES-R spacecraft and instruments with the first launch of the GOES-R series planned for October 2016. Included in the GOES-R Instrument suite is the Geostationary Lightning Mapper (GLM). GLM is a single-channel, near-infrared optical detector that can sense extremely brief (800 s) transient changes in the atmosphere, indicating the presence of lightning. GLM will measure total lightning activity continuously over the Americas and adjacent ocean regions with near-uniform spatial resolution of approximately 10 km. Due to its large CCD (1372x1300 pixels), high frame rate, sensitivity and onboard event filtering, GLM will require extensive post launch characterization and calibration. Daytime and nighttime images will be used to characterize both image quality criteria inherent to GLM as a space-based optic system (focus, stray light, crosstalk, solar glint) and programmable image processing criteria (dark offsets, gain, noise, linearity, dynamic range). In addition ground data filtering will be adjusted based on lightning-specific phenomenology (coherence) to isolate real from false transients with their own characteristics. These parameters will be updated, as needed, on orbit in an iterative process guided by pre-launch testing. This paper discusses the planned tests to be performed on GLM over the six-month Post Launch Test period to optimize and demonstrate GLM performance.

validation↗

NASA NTRS2016

Post Launch Calibration and Testing of the Geostationary Lightning Mapper on the GOES-R Satellite

The Geostationary Operational Environmental Satellite R (GOES-R) series is the planned next generation of operational weather satellites for the United States National Oceanic and Atmospheric Administration (NOAA). The National Aeronautics and Space Administration (NASA) is procuring the GOES-R spacecraft and instruments with the first launch of the GOES-R series planned for October 2016. Included in the GOES-R Instrument suite is the Geostationary Lightning Mapper (GLM). GLM is a single-channel, near-infrared optical detector that can sense extremely brief (800 microseconds) transient changes in the atmosphere, indicating the presence of lightning. GLM will measure total lightning activity continuously over the Americas and adjacent ocean regions with near-uniform spatial resolution of approximately 10 km. Due to its large CCD (1372x1300 pixels), high frame rate, sensitivity and onboard event filtering, GLM will require extensive post launch characterization and calibration. Daytime and nighttime images will be used to characterize both image quality criteria inherent to GLM as a space-based optic system (focus, stray light, crosstalk, solar glint) and programmable image processing criteria (dark offsets, gain, noise, linearity, dynamic range). In addition ground data filtering will be adjusted based on lightning-specific phenomenology (coherence) to isolate real from false transients with their own characteristics. These parameters will be updated, as needed, on orbit in an iterative process guided by pre-launch testing. This paper discusses the planned tests to be performed on GLM over the six-month Post Launch Test period to optimize and demonstrate GLM performance.

validation↗

NASA NTRS2016

Nitrogen Dioxide Observations from the Geostationary Trace Gas and Aerosol Sensor Optimization (GeoTaso) Airborne Instrument: Retrieval Algorithm and Measurements During DISCOVER-AQ Texas 2013

The Geostationary Trace gas and Aerosol Sensor Optimization (GeoTASO) airborne instrument is a test bed for upcoming air quality satellite instruments that will measure backscattered ultraviolet, visible and near-infrared light from geostationary orbit. GeoTASO flew on the NASA Falcon aircraft in its first intensive field measurement campaign during the Deriving Information on Surface Conditions from Column and Vertically Resolved Observations Relevant to Air Quality (DISCOVER-AQ) Earth Venture Mission over Houston, Texas, in September 2013. Measurements of backscattered solar radiation between 420 and 465 nm collected on 4 days during the campaign are used to determine slant column amounts of NO2 at 250 m x 250 m spatial resolution with a fitting precision of 2.2 x 10(exp 15) molecules/sq cm. These slant columns are converted to tropospheric NO2 vertical columns using a radiative transfer model and trace gas profiles from the Community Multiscale Air Quality (CMAQ) model. Total column NO2 from GeoTASO is well correlated with ground-based Pandora observations (r = 0.90 on the most polluted and cloud-free day of measurements and r = 0.74 overall), with GeoTASO NO2 slightly higher for the most polluted observations. Surface NO2 mixing ratios inferred from GeoTASO using the CMAQ model show good correlation with NO2 measured in situ at the surface during the campaign (r = 0.85). NO2 slant columns from GeoTASO also agree well with preliminary retrievals from the GEO-CAPE Airborne Simulator (GCAS) which flew on the NASA King Air B200 (r = 0.81, slope = 0.91). Enhanced NO2 is resolvable over areas of traffic NOx emissions and near individual petrochemical facilities.

Aerosol Sensor Optimization↗

NASA NTRS2016

Electron Flux Models for Different Energies at Geostationary Orbit

Forecast models were derived for energetic electrons at all energy ranges sampled by the third-generation Geostationary Operational Environmental Satellites (GOES). These models were based on Multi-Input Single-Output Nonlinear Autoregressive Moving Average with Exogenous inputs methodologies. The model inputs include the solar wind velocity, density and pressure, the fraction of time that the interplanetary magnetic field (IMF) was southward, the IMF contribution of a solar wind-magnetosphere coupling function proposed by Boynton et al. (2011b), and the Dst index. As such, this study has deduced five new 1 h resolution models for the low-energy electrons measured by GOES (30-50 keV, 50-100 keV, 100-200 keV, 200-350 keV, and 350-600 keV) and extended the existing >800 keV and >2 MeV Geostationary Earth Orbit electron fluxes models to forecast at a 1 h resolution. All of these models were shown to provide accurate forecasts, with prediction efficiencies ranging between 66.9% and 82.3%.

Boynton, R. J.↗

NASA NTRS2018

Flash Optical Energy from the Geostationary Lightning Mapper

The Geostationary Operational Environmental Satellite -16 (GOES-16) Geostationary Lightning Mapper (GLM) is evaluated for many months during the Post Launch Product Test (PLPT) phase in order to ensure that optimal products are available for both the operational forecasting and broader scientific research communities. The emphasis of the PLPT phase is to validate the GLM performance (i.e., lightning flash detection efficiency, geolocation and time-stamp accuracy) using an extensive network of independent ground-based, in-situ, and space-based reference lightning detection systems. However, another essential aspect of the PLPT phase is to obtain benchmarks of the GLM lightning optical amplitude, so that any long-term degradation in the nadir-staring GLM camera system can be realized and quantitatively assessed. This is accomplished in a straight-forward manner by collecting a very large sample of lightning flashes across many geographical regions in the GLM field-of-view so that statistically meaningful benchmarks of lightning optical amplitude (i.e., optical energy in units of femto-joules per flash) are obtained. The benchmarking is particularly important to follow-on studies that will attempt to incorporate the flash optical energy product into new derived products (e.g., energy-weighted lightning "jump" warning algorithms, and lightning nitrogen oxides production estimates).

Lightning↗

NASA NTRS2018

Flash Optical Energy from the Geostationary Lightning Mapper

Flash↗

NASA NTRS2018

On-orbit Validation of the Geolocation Accuracy of the GOES-16 Geostationary Lightning Mapper (GLM) Flashes Using Ground-based Laser Beacons

As part of the geolocation accuracy assessment of lightning flashes detected by the Geostationary Lightning Mapper (GLM) on the GOES-16 and GOES-17 satellites (Geostationary Operational Environmental Satellite), two satellite laser ranging stations employed laser beacon systems to generate transient light pulses that simulate natural lightning around 777.4 nm to validate the pre-launch spec of 5 km. The pulse width, repetition rate, wavelength, and power of the laser-pulses were configured to produce sufficient instrument response to be detected as synthetic lightning events by the GLM instrument. During the testing period from April 2017 to January 2018, the laser systems illuminated the GOES-16 satellite to observe diurnal variation of the GLM system response, with particular emphasis on geolocation accuracy. The final GOES-16 laser beacon tests, which used the latest updates of the geolocation algorithms implemented by the GOES-R Ground Segment, showed the offsets between the GLM geolocated location and the known laser locations were within 5 km.

Lightning↗

NASA NTRS2018

Geostationary Lightning Mapper On-Orbit Sources of False Events

The first Geostationary Lightning Mapper (GLM) was launched aboard the GOES-R Spacecraft (now GOES-East) on November 19, 2016 and is now fully operational. GLM uses a high-speed camera and onboard video processing to detect the optical emission of lightning for the full disk observed from the geostationary orbit. During the Post Launch Test period the instrument and ground processing algorithms (GPAs) were tuned to optimize the tradeoff between detection efficiency and false event rate. False events, those not due to lightning, arise from a variety of sources. A primary function of the GPAs is to remove false events prior to assembling events into groups and flashes for use by weather forecasters and scientists. Effective discrimination of false events depends on understanding the phenomenology of the various sources of false events.

GOES-R↗

NASA NTRS2019

Uncertainties in the Geostationary Ocean Color Imager (GOCI) Remote Sensing Reflectance for Assessing Diurnal Variability of Biogeochemical Processes

Short-term (sub-diurnal) biological and biogeochemical processes cannot be fully captured by the current suite of polar-orbiting satellite ocean color sensors, as their temporal resolution is limited to potentially one clear image per day. Geostationary sensors, such as the Geostationary Ocean Color Imager (GOCI) from the Republic of Korea, allow the study of these short-term processes because their orbit permit the collection of multiple images throughout each day for any area within the sensor’s field of regard. Assessing the capability to detect sub-diurnal changes in in-water properties caused by physical and biogeochemical processes characteristic of open ocean and coastal ocean ecosystems, however, requires an understanding of the uncertainties introduced by the instrument and/or geophysical retrieval algorithms. This work presents a study of the uncertainties during the daytime period for an ocean region with characteristically low-productivity with the assumption that only small and undetectable changes occur in the in-water properties due to biogeochemical processes during the daytime period. The complete GOCI mission data were processed using NASA’s SeaDAS/l2gen package. The assumption of homogeneity of the study region was tested using three-day sequences and diurnal statistics. This assumption was found to hold based on the minimal diurnal and day-to-day variability in GOCI data products. Relative differences with respect to the midday value were calculated for each hourly observation of the day in order to investigate what time of the day the variability is greater. Also, the influence of the solar zenith angle in the retrieval of remote sensing reflectances and derived products was examined. Finally, we determined that the uncertainties in water-leaving “remote-sensing” reflectance (Rrs) for the 412,443, 490, 555, 660 and 680 nm bands on GOCI are 8.05 x 10(exp -4), 5.49 x 10(exp -4), 4.48 x 10(exp -4), 2.51 x 10(exp -4), 8.83 x 10(exp -5), and 1.36 x 10(exp -4)/sr, respectively, and 1.09 x 10(exp -2)/cu.mgm for the chlorophyll-a concentration (Chl-a), 2.09 x 10(exp -3)/m for the absorption coefficient of chromophoric dissolved organic matter at 412 nm (a(sub g) (412)), and 3.7 mg/cu.m for particulate organic carbon (POC). These R(sub rs) values can be considered the threshold values for detectable changes of the in-water properties due to biological, physical or biogeochemical processes from GOCI.

Concha, Javier↗

NASA NTRS2019

GEONEX Data Products: Geostationary Satellite Derived Land Surface and Atmospheric Public Data Products

The latest generation of geostationary satellites carry sensors such as the Advanced Baseline Imager (GOES-16/17) and the Advanced Himawari Imager (Himawari-8/9) that closely mimic the spatial and spectral characteristics of MODIS and VIIRS, useful for monitoring land surface conditions. The NASA Earth Exchange (NEX) team at Ames Research Center has embarked on a collaborative effort among scientists from NASA and NOAA exploring the feasibility of producing operational land surface products similar to those from MODIS/VIIRS. The team built a processing pipeline called GEONEX that is capable of converting raw geostationary data into routine products of Fires, surface reflectances, vegetation indices, LAI/FPAR, ET and GPP/NPP using algorithms adapted from both NASA/EOS and NOAA/GOES-R programs. The GEONEX pipeline will begin to produce provisional data products to be consumed by external collaborators and the academic community. In order to better inform and introduce the GEONEX products to the science community, the provisional products shall be distributed from the NAS data portal, located at data.nas.nasa.gov, and simple webpage at www.nasa.gov/geonex has been deployed, which describes any algorithms used in deriving the products, user manuals and data file information. We will also update the status of the data processing, on the website and provide links to the latest datasets, and use a geonex mailing list, using lists.nasa.gov.

Wang, Weile↗