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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.

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At least 19 records
All sourcesNASA NTRSDOE OSTI
NASA NTRS1984

Diurnal variability of regional cloud and clear-sky radiative parameters derived from GOES data. I - Analysis method. II - November 1978 cloud distributions. III - November 1978 radiative parameters

Cloud cover is one of the most important variables affecting the earth radiation budget (ERB) and, ultimately, the global climate. The present investigation is concerned with several aspects of the effects of extended cloudiness, taking into account hourly visible and infrared data from the Geostationary Operational Environmental Satelite (GOES). A methodology called the hybrid bispectral threshold method is developed to extract regional cloud amounts at three levels in the atmosphere, effective cloud-top temperatures, clear-sky temperature and cloud and clear-sky visible reflectance characteristics from GOES data. The diurnal variations are examined in low, middle, high, and total cloudiness determined with this methodology for November 1978. The bulk, broadband radiative properties of the resultant cloud and clear-sky data are estimated to determine the possible effect of the diurnal variability of regional cloudiness on the interpretation of ERB measurements.

Minnis, P.↗
NASA NTRS1983

Influence of clouds on the earth's radiation budget determined from GOES data

Estimates of the cloud radiative effects on the earth's regional and zonal radiation budgets derived from GOES data during November 1978 are presented. The diurnal cloud cover variability is shown to affect both the radiation-budget measurements and the estimation of the overall effect of clouds on the net flux. For this data set, the cloud cover causes a decrease in the net flux from the clear-sky value. Thus, the cloud albedo effect outweights the greenhouse effect of the clouds. It is found that the value of the change in the radiation balance is closely related to the amount of incident solar radiation and to the zonal distributions of low, middle, and high cloud cover.

Harrison, E. F.↗
DOE OSTI2026

Integration of GOES Data for Solar Resource Assessment of the Contiguous United States

The National Solar Radiation Database (NSRDB), produced by the National Laboratory of the Rockies (NLR), provides high-resolution solar resource data for the contiguous United States (CONUS) using Geostationary Operational Environmental Satellite (GOES) East and West observations. This study evaluates the integration of multi-satellite data within the GOES-East/West overlap regions, where conventional longitude-based selection methods often produce an artificial boundary seam. Our results demonstrate that an advanced blending algorithm, which incorporates sun-satellite scattering angles and satellite viewing zenith angles, improves NSRDB accuracy and creates a spatially continuous dataset. Validation against ground-based irradiance measurements reveals reductions in both percentage error (PE) and normalized Root Mean Square Error (nRMSE), particularly in the central United States. The dynamical integration of multi-satellite data provides a robust foundation for more precise modeling of solar resource and improved spatiotemporal analysis of solar ramp across the CONUS.

14 SOLAR ENERGY↗
NASA NTRS2001

Cloud Overlapping Detection Algorithm Using Solar and IR Wavelengths with GOES Data Over ARM/SGP Site

One of the most perplexing problems in satellite cloud remote sensing is the overlapping of cloud layers. Although most techniques assume a one layer cloud system in a given retrieval of cloud properties, many observations are affected by radiation from more than one cloud layer. As such, cloud overlap can cause errors in the retrieval of many properties including cloud height, optical depth, phase, and particle size. A variety of methods have been developed to identify overlapped clouds in a given satellite imager pixel. Baum et al used CO2 slicing and a spatial coherence method to demonstrate a possible analysis method for nighttime detection of multilayered clouds. Jin and Rossow also used a multispectral CO2 slicing technique for a global analysis of overlapped cloud amount. Lin et al. used a combination infrared (IR), visible (VIS), and microwave data to detect overlapped clouds over water. Recently, Baum and Spinhirne proposed a 1.6 and 11 micron bispectral threshold method. While all of these methods have made progress in solving this stubborn problem none have yet proven satisfactory for continuous and consistent monitoring of multilayer cloud systems. It is clear that detection of overlapping clouds from passive instruments such as satellite radiometers is in an immature stage of development and requires additional research. Overlapped cloud systems also affect the retrievals of cloud properties over the Atmospheric Radiation Measurement (ARM) domains and hence should be identified as accurately as possible. To reach this goal, it is necessary to determine which information can be exploited for detecting multilayered clouds from operational meteorological satellite data used by ARM. This paper examines the potential information available in spectral data available on the Geostationary Operational Environmental Satellite (GOES) imager and the National Oceanic Atmospheric Administration (NOAA) Advanced Very High Resolution Radiometer (AVHRR) used over the ARM Program's Southern Great Plains (SGP), and North Slope of Alaska (NSA) sites to study the capability of detecting overlapping clouds.

Kawamoto, K.↗
NASA NTRS2000

Operational Assimilation of GOES Data into a Mesoscale Model

A technique has been developed for assimilating GOES-derived skin temperature tendencies and insolation into the surface energy budget equation of a mesoscale model so that the simulated rate of temperature change closely agrees with the satellite observations. A critical assumption of the technique is that the availability of moisture (either from the soil or vegetation) is the least known term in the model's surface energy budget. Therefore, the simulated latent heat flux, which is a function of surface moisture availability, is adjusted based upon differences between the modeled and satellite- observed skin temperature tendencies. An advantage of this technique is that satellite temperature tendencies are assimilated in an energetically consistent manner that avoids energy imbalances and surface stability problems that arise from direct assimilation of surface shelter temperatures. The fact that the rate of change of the satellite skin temperature is used rather than the absolute temperature means that sensor calibration is not as critical. The technique has been employed on a semi-operational basis at the Global Hydrology and Climate Center (GHCC) within the Penn State/National Center for Atmospheric Research (PSU/NCAR) Mesoscale Model (MM5) since 1 November 1998. We performed the assimilation on a model grid centered over the Southeastern US. In addition, a control run without assimilation was performed to provide insight into the performance of the assimilation technique. Bulk verification statistics (BIAS and RMSE) of surface air temperature and relative humidity of more than 250 case days has been performed to date. Results show that assimilation of the satellite data results reduces both the bias and RMSE for simulations of surface air temperature and relative humidity. We are working with forecasters at the National Weather Service Forecast Office located in Birmingham, AL to evaluate the impact of the assimilation on precipitation forecasts. In addition, work is currently underway to determine the ability of both the assimilation technique and Early Eta to sense the significant changes that occur in both leaf expansion and soil moisture conditions during the Spring-Summer of 1999. This will be accomplished via examination of the simulated surface energy budgets from both modeling systems.

Lapenta, William↗
NASA NTRS2004

Validation of Infrared Azimuthal Model as Applied to GOES Data Over the ARM SGP

The goal of this research is to identify and reduce the GOES-8 IR temperature biases, induced by a fixed geostationary position, during the course of a day. In this study, the same CERES LW window channel model is applied to GOES-8 IR temperatures during clear days over the Atmospheric Radiation Measurement-Southern Great Plains Central Facility (SCF). The model-adjusted and observed IR temperatures are compared with topof- the-atmosphere (TOA) estimated temperatures derived from a radiative transfer algorithm based on the atmospheric profile and surface radiometer measurements. This algorithm can then be incorporated to derive more accurate Ts from real-time satellite operational products.

Gambheer, Arvind V.↗
NASA NTRS2000

Data Goes the Distance

Omni Technologies, Inc. worked with Stennis Space Center to develop the FOTR-125, a redundant fiber-optic transceiver for remote transmission of high-speed digital data. The 125-megabit-per-second transceiver can collect data for up to 25 kilometers, much longer than standard coaxial cable, which is limited to 50 meters. The Research Triangle Institute assisted in determining the commercial marketplace for the technology.

Source record↗
NASA NTRS1981

A combined visible and IR technique for the estimation of rainfall amounts from GOES data

The use of visible and infrared techniques for estimating precipitation for flash flood, hydrological, and agricultural applications is discussed. Satellite derived rainfall estimates supplement other data or are the only data available. The Scofield/Oliver convective rainfall technique is used for analyzing a half hour period of heavy rainfall during a Chicago flash flood event. The results of a real time hydrological application of the Scofield/Oliver technique for the Hurricane Allen event are also presented. Visible and IR techniques for agricultural applications are also discussed.

Austin, G. L.↗
NASA NTRS1980

GOES satellite data maps areas of extreme cold in Colorado

Geostationary Operational Environmental Satellite (GOES) enhanced infrared (IR) imagery depicted very cold temperatures over Colorado on the morning of 8 December 1978. The situation was unusual because skies were clear and the cold temperatures were not associated with high cloud tops. Instead, satellite data mapped large areas that were experiencing extremely cold surface temperatures. The GOES data were also examined using the Colorado State University interactive data processing system and it was found that the cold IR readings corresponded well with early morning low temperatures over the state. GOES data can be of use in monitoring surface temperatures and can, in certain situations, provide detailed spatial and temporal information over regions experiencing extreme temperatures.

Maddox, R. A.↗
DOE OSTI2025

GOES-16 Data for LASSO-CACTI Overview Paper

GOES-16 L1b satellite radiances have been obtained for the LASSO-CACTI case dates. Specifically, the period in the ARM subset is for select days in the period October 26, 2018 through March 15, 2019. These files were downloaded from Amazon Web Services using the GOES-2-Go library, https://blaylockbk.github.io/goes2go/_build/html/.

{"GOES-16 band 13",radiance,LASSO-CACTI}↗
NASA NTRS1986

Identifying deforestation in Brazil using multiresolution satellite data

The use of multiresolution satellite data to monitor deforestation on a continental/subcontinental scale is examined. MSS, local area coverage (LAC), global area coverage (GAC), and GOES data were applied to the study of deforestation in Rondonia, Brazil; the characteristics of these sensors are described. The probability thresholding and vegetation-index thresholding procedures used to process the data in order to differentiate between forest from nonforest are analyzed. The LAC, GAC, and GOES data are compared to MSS data. It is observed that GOES data is not useful for monitoring colonization projects due to excessive noise in the data; the GAC data is only applicable in large areas of contiguous forest clearing; the MSS data when available is applicable as a ground data reference source for differentiating cleared areas from primary; the LAC data are capable of delineating colonization clearings; and the probability thresholding procedure differentiates forest from nonforest more accurately than the vegetation-index procedure. The data reveal that the LAC data combined with the probability threshold procedure provide the best data-source/classification-procedure combination.

Nelson, R.↗
NASA NTRS2001

A 3-Year Climatology of Cloud and Radiative Properties Derived from GOES-8 Data Over the Southern Great Plains

While the various instruments maintained at the Atmospheric Radiation Measurement (ARM) Program Southern Great Plains (SGP) Central Facility (CF) provide detailed cloud and radiation measurements for a small area, satellite cloud property retrievals provide a means of examining the large-scale properties of the surrounding region over an extended period of time. Seasonal and inter-annual climatological trends can be analyzed with such a dataset. For this purpose, monthly datasets of cloud and radiative properties from December 1996 through November 1999 over the SGP region have been derived using the layered bispectral threshold method (LBTM). The properties derived include cloud optical depths (ODs), temperatures and albedos, and are produced on two grids of lower (0.5 deg) and higher resolution (0.3 deg) centered on the ARM SGP CF. The extensive time period and high-resolution of the inner grid of this dataset allows for comparison with the suite of instruments located at the ARM CF. In particular, Whole-Sky Imager (WSI) and the Active Remote Sensing of Clouds (ARSCL) cloud products can be compared to the cloud amounts and heights of the LBTM 0.3 deg grid box encompassing the CF site. The WSI provides cloud fraction and the ARSCL computes cloud fraction, base, and top heights using the algorithms by Clothiaux et al. (2001) with a combination of Belfort Laser Ceilometer (BLC), Millimeter Wave Cloud Radar (MMCR), and Micropulse Lidar (MPL) data. This paper summarizes the results of the LBTM analysis for 3 years of GOES-8 data over the SGP and examines the differences between surface and satellite-based estimates of cloud fraction.

Khaiyer, M. M.↗
NASA NTRS1998

Variations in Upper-Level Water Vapor Transport Diagnosed from Climatological Satellite Data

GOES-7 VAS measurements during the Pathfinder period (1987-88) have been analysed to reveal seasonal and interannual variations in moisture transport. Long term measurements of quality winds and humidity from satellite estimates show superior benefit in diagnosing middle and upper tropospheric large scale climate variations such as ENSO events and direct circulation systems such as the Hadley Cell. A water Vapor Transport Index (WVTI) has been developed to diagnose preferred regions of strong moisture transport and to gauge the seasonal and interannual intensities detected in the GOES viewing area. Second-order variables that may be derived from GOES winds will be also discussed on the poster.

Lerner, Jeffrey A↗
NASA NTRS1983

Case studies using GOES infrared data and a planetary boundary layer model to infer regional scale variations in soil moisture

Modeled temperature data from a one-dimensional, time-dependent, initial value, planetary boundary layer model for 16 separate model runs with varying initial values of moisture availability are applied, by the use of a regression equation, to longwave infrared GOES satellite data to infer moisture availability over a regional area in the central U.S. This was done for several days during the summers of 1978 and 1980 where a large gradient in the antecedent precipitation index (API) represented the boundary between a drought area and a region of near normal precipitation. Correlations between satellite derived moisture availability and API were found to exist. Errors from the presence of clouds, water vapor and other spatial inhomogeneities made the use of the measurement for anything except the relative degree of moisture availability dubious.

Rose, F. G.↗
NASA NTRS1999

Comparison fo CO2 Lidar Backscatter with Particle Size Distribution and GOES-7 Data in Hurricane Juliette

Two NASA/MSFC continuous wave (CW) focused Doppler lidars obtained in-situ high resolution calibrated backscatter measurements in the upper levels of Hurricane Juliette as part of the 1995 NASA/Multicenter Airborne Coherent Atmospheric Wind Sensor (MACAWS) mission on board NASA's DC8 aircraft. These were also intercompared with in-situ cloud particle size distributions obtained from NASA/Ames Research Center's forward scattering spectrometer probe (FSSP), the DC8 aircraft infrared (IR) surface temperature radiometer data, and the Geostationary Operational Environmental Satellites (GOES-7) 11 micrometer IR emission images with their corresponding estimates of cloud top temperature and height. Two traverses of Hurricane Juliette's eye were made off the west coast of Mexico at altitude approx. 11.7 km on 21 September 1995. During this DC8 flight, late stages of eyewall decay-replacement cycles were observed, giving the appearance of an annular eye with clouds in the central region.

Jarzembski, Maurice A.↗
NASA NTRS1989

Viewing zenith angle dependence of cloudiness determined from coincident GOES East and GOES West data

The effect of the viewing zenith angle (VZA) on the cloudiness values observed by a satellite was investigated using a combination of two cloud-amount data sets derived from nearly simultaneous collocated GOES-E and GOES-W radiance measurements over the Pacific Ocean during May 1979 and July 1983. A hybrid bispectral threshold method was used to analyze data for single-layer and total cloudiness. It was found that the cloud fraction values increased with increasing VZA for almost all cases. Low clouds exhibited the greatest increases with a VZA increase for cloud amounts in the 0.1 range, whereas high clouds showed greatest increases for cloud amounts around 0.5. Midlevel clouds showed only a slight dependence on VZA. Total cloudiness increased the most, reflecting its predominantly low-cloud composition.

Minnis, Patrick↗
NASA NTRS2005

GOES Satellite Data Validation Via Hand-held 4 LED Sun Photometer at Norfolk State University

Sun photometry is a passive means of measuring a quantity of light radiation. The GIFTS- IOMI/GLOBE Water Vapor/Haze Sun photometer contains four light emitting diodes (LEDs), which are used to convert photocurrent to voltage. The intensity of the incoming and outgoing radiation as detected on the Earth s surface can be affected by aerosols and gases in the atmosphere. The focus of this research is primarily on aerosol and water vapor particles that absorb and reemit energy. Two LEDs in the photometer correspond to light scattered at 530 nm (green spectrum) and 620 nm (red spectrum). They collect data pertaining to aerosols that scatter light. The other two LEDs detect the light scattered by water vapor at wavelengths of 820 nm and 920 nm. The water vapor measurements will be compared to data collected by the Geostationary Observation Environmental Satellite (GOES). Before a comparison can be made, the extraterrestrial constant (ET), which is intrinsic to each sun photometer, must be measured. This paper will present determination of the ET constant, from which the aerosol optical thickness (AOT) can be computed for comparison to the GOES satellite to ascertain the reliability of the sun photometer.

Reynolds, Arthur, Jr.↗