Search NASA⌕ Search

SEARCH · Search NASA

Results for “Cloud cover”

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 127 records · Page 7
All sourcesNASA NTRSDOE OSTI
NASA NTRS2010

A 10-Year Climatology of Cloud Cover and Vertical Distribution Derived from Both Surface and GOES Observations Over the DOE ARM SGP Site

Analysis of a decade of ARM radar-lidar and GOES observations at the SGP site reveal that 0.5 and 4-hr averages of the surface cloud fraction correspond closely to 0.5deg and 2.5deg averages of GOES cloudiness, respectively. The long-term averaged surface and GOES cloud fractions agree to within 0.5%. Cloud frequency increases and cloud amount decreases as the temporal and spatial averaging scales increase. Clouds occurred most often during winter and spring. Single-layered clouds account for 61.5% of the total cloud frequency. There are distinct bimodal vertical distributions of clouds with a lower peak around 1 km and an upper one that varies from 7.5 to 10.8 km between winter and summer, respectively. The frequency of occurrence for nighttime GOES high-cloud tops agree well with the surface observations, but are underestimated during the day.

Xi, Baike↗
DOE OSTI2024

The influence of cloud cover on the reliability of satellite-based solar resource data

Satellite-based solar resource data are often developed and validated by using binary cloudiness categories: clear sky or overcast cloudy sky. To investigate the reliability of solar resource data in partially cloudy conditions, we estimate cloud fraction using two distinct algorithms: a physical retrieval model using surface observed global horizontal irradiance (GHI) and direct normal irradiance (DNI) and a temporal average of cloud mask data estimated by the observed DNI. Our analysis reveals a significant presence of scattered clouds, broken clouds, and mismatches between satellite- and surface-based cloud data at 17 surface sites across the contiguous United States, though confidently clear and cloudy conditions collectively account for more than 70 % of the data. Solar radiation is computed using the National Solar Radiation Database (NSRDB) algorithm and validated using surface observations. Here, our findings suggest that, in the presence of scattered clouds, NSRDB data for clear-sky conditions can be subject to significant overestimation. In cloudy-sky conditions classified by satellite data, DNI computed by the Fast All-sky Radiation Model for Solar applications with DNI (FARMS-DNI) can be underestimated when limited clouds are detected by surface observations. The bias observed in several cloudiness categories indicates that the NSRDB is exceptionally accurate in confidently clear conditions. However, clear-sky conditions with scattered clouds and mismatched cloud data contribute significantly to the overall uncertainties in the NSRDB. Therefore, future improvements in solar resource data should involve development and implementation of satellite-derived cloud fraction and should consider a novel radiative transfer model accounting for amplified cloud reflection. The evaluation within cloudiness categories also provides a physical rationale for the superior performance of FARMS-DNI compared to the Direct Insolation Simulation Code (DISC) in both cloudy-sky and all-sky conditions.

14 SOLAR ENERGY↗
NASA NTRS1983

Orbital and cloud cover sampling analyses for multisatellite earth radiation budget experiments

Computer simulations have been performed to determine the geographical and temporal coverage of various satellite orbits and scanning and nonscanning radiometers for earth radiation budget measurements. These results were used to simulate the sampling of a diurnally varying cloud and radiation field for several different satellite systems to estimate errors in regional monthly mean reflected radiation. The combined results indicate that coincient observations with a minimum of one sun-synchronous satellite and a midinclined orbit satellite are needed to obtain the required regional, zonal, and global coverage with sufficient temporal sampling for obtaining accurate estimates of monthly mean reflected solar radiation. Overall, the best sampling capability and lowest errors were obtained with a three-satellite system, i.e., two sun-synchronous satellites with different equatorial crossing times combined with either a 46 or 57-deg orbit satellite. The results from these analyses have been used in defining a joint NASA-NOAA multisatellite mission for an earth radiation budget experiment.

Harrison, E. F.↗
NASA NTRS1990

Effect of cloud cover and surface type on earth's radiation budget derived from the first year of ERBE data

One year of ERBE data is analyzed for variations in outgoing LW and absorbed solar flux. Differences in land and ocean radiation budgets as well as differences between clear-sky and total scenes, including clouds, are studied. The variation of monthly average radiative parameters is examined for February 1985 through January 1986 for selected study regions and on zonal and global scales. ERBE results show significant seasonal variations in both outgoing LW and absorbed SW flux, and a pronounced difference between oceanic and continental surfaces. The main factors determining cloud radiative forcing in a given region are solar insolation, cloud amount, cloud type, and surface properties. The strongest effects of clouds are found in the midlatitude storm tracks over the oceans. Over much of the globe, LW warming is balanced by SW cooling. The annual-global average net cloud forcing shows that clouds have a net cooling effect on the earth for the year.

Gibson, G. G.↗
NASA NTRS2004

Changes in Seasonal Cloud Cover over the Arctic Seas from Satellite and Surface Observations

Winter and spring changes in cloudiness are compared over the arctic seas (ocean areas north of 60 degrees N) from the TOVS (TIROS Operational Vertical Sounder) Polar Pathfinder retrievals and two separate datasets derived from the Advanced Very High Resolution Radiometer (AVHRR). All satellite products exhibit significant decreases in cloud fraction over the arctic seas during winter (December, January, February) on the order of 5 %/ decade. An equally striking increase in spring (March, April, May) cloudiness is evident from the TOVS Pathfinder (TPP) and the extended AVHRR Polar Pathfinder (APP-x) projects. In the Central Arctic these positive trends can be as large as 15 %/decade. Surface observations from the Russian drifting meteorological stations are consistent with satellite-observed changes during the 1980s. Negative trends in spring cloudiness reported by Comiso [2003] are in conflict with these findings. Spring changes in cloudiness are associated with changes in the atmospheric circulation. These dramatic, large-scale changes may have substantial impacts on the surface energy balance.

Schweiger, Axel J.↗
DOE OSTI2024

Computer Vision on Edge Devices for the Short Term Prediction of Cloud Cover

Edge Computing and IoT are important pieces of today's technological landscape. Here, we build a low-cost IoT sensor for sky imaging and program it using AWS GreenGrass, one of the leading IoT platforms. We demonstrate remote reprogramming of this device to load software that predicts sun shading events through the linear advection method, which is a baseline algorithm that can be used to benchmark algorithmic improvements in future work. Some future directions for sky imaging research are enumerated.

14 SOLAR ENERGY↗
NASA NTRS1976

On the remote measurement of evaporation rates from bare wet soil under variable cloud cover

Evaporation rates from a natural wet soil surface are calculated from an energy balance equation at 0.1-hour intervals. A procedure is developed for calculating the heat flux through the soil surface from a harmonic analysis of the surface temperature curve. The evaporation integrated over an entire 24-hour period is compared with daily evaporation rates obtained from published models.

Auer, S.↗
NASA NTRS1979

Worldwide cloud cover model

Classifying worldwide cloudiness into homogeneous regions, using a satellite data set containing day IR, night IR, incoming, and absorbed solar radiation measurements on a 2.5-degree latitude-longitude grid is considered. Methods of analysis are presented.

Smith, O. E.↗
NASA NTRS1982

Cloud cover sensor

An apparatus is described which provides a numerical indication of the cloudiness at a particular time of a day. The apparatus includes a frame holding several light sensors such as photovoltaic cells, with a direct sensor mounted to directly face the Sun and indirect sensors mounted to face different portions of the sky not containing the Sun. A light shield shields the direct sensor from most of the sky except a small portion containing the Sun, and also shields each of the indirect sensors from direct sunlight. The relative values of the outputs from the direct and indirect sensors, enables the generation of a numerical indication of the degree of cloudiness at a particular time of day.

Laue, E. G.↗
NASA NTRS1996

Analysis of Long-Term Cloud Cover, Radiative Fluxes, and Sea Surface Temperature in the Eastern Tropical Pacific

Grant activities accomplished during this reporting period are summarized. The contributions of the principle investigator are reported under four categories: (1) AHVRR (Advanced Very High Resolution Radiometer) data; (2) GOES (Geostationary Operational Environ Satellite) data; (3) system software design; and (4) ATSR (Along Track Scanning Radiometer) data. The contributions of the associate investigator are reported for:(1) longwave irradiance at the surface; (2) methods to derive surface short-wave irradiance; and (3) estimating PAR (photo-synthetically active radiation) surface. Several papers have resulted. Abstracts for each paper are provided.

Simpson, J. J.↗
NASA NTRS2014

Spatial Correlations of Anomalies of Tropospheric Temperature and Water Vapor, Cloud Cover, and OLR with the El Nino Index

In this presentation, we will show AIRS Version-6 area weighted anomaly time series over the time period September 2002 through August 2014 of atmospheric temperature and water vapor profiles as a function of height. These anomaly time series show very different behaviors in the stratosphere and in the troposphere. Tropical mean stratospheric temperature anomaly time series are very strongly influenced by the Quasi-Biennial Oscillation (QBO) with large anomalies that propagate downward from 1 mb to 100 mb with a period of about two years. AIRS stratospheric temperature anomalies are in good agreement with those obtained by MLS over a common period. Tropical mean tropospheric temperature profile anomalies appear to be totally disconnected from those of the stratosphere and closely follow El Nino La Nina activity.

Version-6↗