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At least 163 records · Page 9

Modeled Impact of Cirrus Cloud Increases Along Aircraft Flight Paths

The potential impact of contrails and alterations in the lifetime of background cirrus due to subsonic airplane water and aerosol emissions has been investigated in a set of experiments using the GISS GCM connected to a q-flux ocean. Cirrus clouds at a height of 12-15km, with an optical thickness of 0.33, were input to the model "x" percentage of clear-sky occasions along subsonic aircraft flight paths, where x is varied from .05% to 6%. Two types of experiments were performed: one with the percentage cirrus cloud increase independent of flight density, as long as a certain minimum density was exceeded; the other with the percentage related to the density of fuel expenditure. The overall climate impact was similar with the two approaches, due to the feedbacks of the climate system. Fifty years were run for eight such experiments, with the following conclusions based on the stable results from years 30-50 for each. The experiments show that adding cirrus to the upper troposphere results in a stabilization of the atmosphere, which leads to some decrease in cloud cover at levels below the insertion altitude. Considering then the total effect on upper level cloud cover (above 5 km altitude), the equilibrium global mean temperature response shows that altering high level clouds by 1% changes the global mean temperature by 0.43C. The response is highly linear (linear correlation coefficient of 0.996) for high cloud cover changes between 0. 1% and 5%. The effect is amplified in the Northern Hemisphere, more so with greater cloud cover change. The temperature effect maximizes around 10 km (at greater than 40C warming with a 4.8% increase in upper level clouds), again more so with greater warming. The high cloud cover change shows the flight path influence most clearly with the smallest warming magnitudes; with greater warming, the model feedbacks introduce a strong tropical response. Similarly, the surface temperature response is dominated by the feedbacks, and shows little geographical relationship to the high cloud input. Considering whether these effects would be observable, changing upper level cloud cover by as little as 0.4% produces warming greater than 2 standard deviations in the Microwave Sounding Unit (MSU) channels 4, 2 and 2r, in flight path regions and in the subtropics. Despite the simplified nature of these experiments, the results emphasize the sensitivity of the modeled climate to high level cloud cover changes, and thus the potential ability of aircraft to influence climate by altering clouds in the upper troposphere.

Rind, David↗

Transformation of surface albedo to surface: Atmosphere surface and irradiance, and their spectral and temporal averages

The dependence of the albedo at the top of a realistic atmosphere upon the surface albedo, solar zenith angle, and cloud optical thickness is examined for the cases of clear sky, total cloud cover, and fractional cloud cover. The radiative transfer calculations of Dave and Braslau (1975) for particular values of surface albedo and solar zenith angle, and a single value of cloud optical thickness are used as the basis of a parametric albedo model. The question of spectral and temporal averages of albedos and reflected irradiances is addressed, and unique weighting functions for the spectral and temporal albedo averages are developed.

Nack, M. L.↗

Tropical and Subtropical Cloud Transitions in Weather and Climate Prediction Models: The GCSS/WGNE Pacific Cross-Section Intercomparison (GPCI)

A model evaluation approach is proposed in which weather and climate prediction models are analyzed along a Pacific Ocean cross section, from the stratocumulus regions off the coast of California, across the shallow convection dominated trade winds, to the deep convection regions of the ITCZ the Global Energy and Water Cycle Experiment Cloud System Study/Working Group on Numerical Experimentation (GCSS/ WGNE) Pacific Cross-Section Intercomparison (GPCI). The main goal of GPCI is to evaluate and help understand and improve the representation of tropical and subtropical cloud processes in weather and climate prediction models. In this paper, a detailed analysis of cloud regime transitions along the cross section from the subtropics to the tropics for the season June July August of 1998 is presented. This GPCI study confirms many of the typical weather and climate prediction model problems in the representation of clouds: underestimation of clouds in the stratocumulus regime by most models with the corresponding consequences in terms of shortwave radiation biases; overestimation of clouds by the 40-yr ECMWF Re-Analysis (ERA-40) in the deep tropics (in particular) with the corresponding impact in the outgoing longwave radiation; large spread between the different models in terms of cloud cover, liquid water path and shortwave radiation; significant differences between the models in terms of vertical cross sections of cloud properties (in particular), vertical velocity, and relative humidity. An alternative analysis of cloud cover mean statistics is proposed where sharp gradients in cloud cover along the GPCI transect are taken into account. This analysis shows that the negative cloud bias of some models and ERA-40 in the stratocumulus regions [as compared to the first International Satellite Cloud Climatology Project (ISCCP)] is associated not only with lower values of cloud cover in these regimes, but also with a stratocumulus-to-cumulus transition that occurs too early along the trade wind Lagrangian trajectory. Histograms of cloud cover along the cross section differ significantly between models. Some models exhibit a quasi-bimodal structure with cloud cover being either very large (close to 100%) or very small, while other models show a more continuous transition. The ISCCP observations suggest that reality is in-between these two extreme examples. These different patterns reflect the diverse nature of the cloud, boundary layer, and convection parameterizations in the participating weather and climate prediction models.

Teixeira, J.↗

Measurement of solar radiation at the Earth's surface

The characteristics of solar energy arriving at the surface of the Earth are defined and the history of solar measurements in the United States presented. Radiation and meteorological measurements being made at solar energy meteorological research and training sites and calibration procedures used there are outlined. Data illustrating the annual variation in daily solar radiation at Ann Arbor, Michigan and the diurnal variation in radiation at Albuquerque, New Mexico are presented. Direct normal solar radiation received at Albuquerque is contrasted with that received at Maynard, Massachusetts. Average measured global radiation for a period of one year for four locations under clear skies, 50% cloud cover, and 100% cloud cover is given and compared with the solar radiation at the top of the atmosphere. The May distribution of mean daily direct solar radiation and mean daily global solar radiation over the United States is presented. The effects of turbidity on the direct and circumsolar radiation are shown.

Bartman, F. L.↗

11 micrometer emissivities and droplet radii for marine stratocumulus

The results of a new multispectral infrared retrieval scheme for obtaining fractional cloud cover and 11 micrometer emissivity with those of the spatial coherence method which obtains fractional cloud cover assuming that the clouds are opaque at infrared wavelengths. Both methods are applied to 4-km NOAA advanced very high resolution radiometer global area coverage data for 250-km-scale regions containing single-layered marine stratocumulus off the coast of South America. The average 11 micrometer emissivity for low level clouds is found to be between 0.70 and 0.85. The low emissivity is evidently due to the thinning of clouds at their edges. Semitransparent cloud edges evidently make up a substantial portion of the area covered by such clouds. This result indicates that cloud cover obtained using the spatial coherence method is underestimated by 0.1 to 0.2, as has been claimed in a previous study. The fractional cloud cover for the ensemble of 250-km-scale regions studied here increased slightly from 0.60 for daytime observations to 0.63 for nighttime observations. The 11 micrometer emissivity also increased slightly, but about half of the increase was related to the increase in cloud cover and a decrease in the relative area covered by cloud edge material. Presumably, the other half was due to an increase in cloud liquid water. Cloud height showed no significant change. The average effective droplet radius increased from 9.3 micrometers for daytime observations to 10.2 micrometers at night.

Luo, Gang↗

Seasonal and interannual changes in cirrus

Statistics on cirrus clouds using the multispectral data from the GOES/VAS satellite have been collected since 1985. The method used to diagnose cirrus clouds and a summary of the first two years of data was given in Wylie and Menzel (1989) and at the 1988 FIRE meeting in Vail, CO. This study was expanded to three years of data which allows a more detailed discussion of the geographical and seasonal changes in cloud cover. Interannual changes in cloud cover also were studied. GOES/VAS cloud retrievals also were compared to atmospheric dynamic parameters and to radiative attenuation data taken by a lidar. Some of the highlights of these studies are discussed.

Wylie, Donald P.↗

Discharge forecasts in mountain basins based on satellite snow cover mapping

The author has identified the following significant results. A snow runoff model developed for European mountain basins was used with LANDSAT imagery and air temperature data to simulate runoff in the Rocky Mountains under conditions of large elevation range and moderate cloud cover (cloud cover of 40% or less during LANDSAT passes 70% of the time during a snowmelt season). Favorable results were obtained for basins with area not exceeding serval hundred square kilometers and with a significant component of subsurface runoff.

Martinec, J.↗

Comparison of satellite based cloud retrieval methods for cirrus and stratocumulus

One difficulty in using satellite remote sensing data is the spatial variability of cloud properties on scales smaller than most meteorological satellite fields of view (approx. 4 to 8 km). The variation is examined of satellite derived cloud cover as a function of the satellite sensor spatial resolution for seven cloud cover retrieval methods: (1) Reflectance threshold; (2) Temperature threshold; (3) ISCCP; (4) HBTM (Hybrid Bispectral Threshold Method); (5) NCLE; (6) Spatial coherence; and (7) Functional Box Counting. The first two methods are simple single spectral thresholds which specify a satellite pixel as cloud filled if the measured reflectance is greater than the threshold, or if the measured equivalent blackbody temperature is less than the threshold. The next three methods are bispectral, using one visible wavelength window channel and one thermal infrared wavelength window. The final two algorithms rely on the spatial variability within the cloud field to determine cloud cover. Spatial coherence assumes only that the cloud field occurs in a single layer and that the clouds are optically thick in the infrared window. LANDSAT Thematic Mapper (TM) data is used to test the spatial resolution dependence of the cloud algorithms. The ISCCP bispectral threshold applied to the full resolution data is used as the reference or truth cloud cover, after which the retrieval methods are applied to the spatial resolutions. Studies of the fraction of pixels in the scene at cloud edge, and of the profile of reflectance and temperature near cloud edges indicate an uncertainty in the reference cloud fraction of 1 to 5 percent.

Parker, Lindsay↗

Spatial Correlations of Anomaly Time Series of AIRS Version-6 Land Surface Skin Temperatures with the Nino-4 Index

The AIRS Science Team Version-6 data set is a valuable resource for meteorological studies. Quality Controlled earth's surface skin temperatures are produced on a 45 km x 45 km spatial scale under most cloud cover conditions. The same retrieval algorithm is used for all surface types under all conditions. This study used eleven years of AIRS monthly mean surface skin temperature and cloud cover products to show that land surface skin temperatures have decreased significantly in some areas and increased significantly in other areas over the period September 2002 through August 2013. These changes occurred primarily at 1:30 PM but not at 1:30 AM. Cooling land areas contained corresponding increases in cloud cover over this time period, with the reverse being true for warming land areas. The cloud cover anomaly patterns for a given month are affected significantly by El Nino/La Nina activity, and anomalies in cloud cover are a driving force behind anomalies in land surface skin temperature.

Spatial correlations↗

Creating User-Friendly Tools for Data Analysis and Visualization in K-12 Classrooms: A Fortran Dinosaur Meets Generation Y

During the summer of 2007, as part of the second year of a NASA-funded project in partnership with Christopher Newport University called SPHERE (Students as Professionals Helping Educators Research the Earth), a group of undergraduate students spent 8 weeks in a research internship at or near NASA Langley Research Center. Three students from this group formed the Clouds group along with a NASA mentor (Chambers), and the brief addition of a local high school student fulfilling a mentorship requirement. The Clouds group was given the task of exploring and analyzing ground-based cloud observations obtained by K-12 students as part of the Students' Cloud Observations On-Line (S'COOL) Project, and the corresponding satellite data. This project began in 1997. The primary analysis tools developed for it were in FORTRAN, a computer language none of the students were familiar with. While they persevered through computer challenges and picky syntax, it eventually became obvious that this was not the most fruitful approach for a project aimed at motivating K-12 students to do their own data analysis. Thus, about halfway through the summer the group shifted its focus to more modern data analysis and visualization tools, namely spreadsheets and Google(tm) Earth. The result of their efforts, so far, is two different Excel spreadsheets and a Google(tm) Earth file. The spreadsheets are set up to allow participating classrooms to paste in a particular dataset of interest, using the standard S'COOL format, and easily perform a variety of analyses and comparisons of the ground cloud observation reports and their correspondence with the satellite data. This includes summarizing cloud occurrence and cloud cover statistics, and comparing cloud cover measurements from the two points of view. A visual classification tool is also provided to compare the cloud levels reported from the two viewpoints. This provides a statistical counterpart to the existing S'COOL data visualization tool, which is used for individual ground-to-satellite correspondences. The Google(tm) Earth file contains a set of placemarks and ground overlays to show participating students the area around their school that the satellite is measuring. This approach will be automated and made interactive by the S'COOL database expert and will also be used to help refine the latitude/longitude location of the participating schools. Once complete, these new data analysis tools will be posted on the S'COOL website for use by the project participants in schools around the US and the world.

Chambers, L. H.↗

The Temperature Humidity Infrared Radiometer (THIR) subsystem

The infrared radiation from the earth in two spectral bands during both day and night portions of the orbit is measured. Pictures of cloud cover, three dimensional mappings of cloud cover, temperature mappings of clouds, land, and ocean surface, cirrus cloud content, atmospheric contamination, and relative humidity are provided.

Cherrix, G. T.↗

Do Citizen Science Intense Observation Periods Increase Data Usability? A Deep Dive of the NASA GLOBE Clouds Data Set With Satellite Comparisons

The Global Learning and Observations to Benefit the Environment (GLOBE) citizen science program has recently conducted a series of month-long intensive observation periods (IOPs), asking the public to submit daily reports on cloud and sky conditions from all regions of Earth. This provides a wealth of crowdsourced observations from the ground, which complements other conventional scientific cloud data. In addition, the GLOBE reports are matched in space and time with geostationary and low Earth orbit satellites, which allows for a straightforward comparison of cloud properties, and minimizes the biases associated with mismatched sampling between participants and satellites. The matched GLOBE dataset is used to calculate the mean observed cloud cover by atmospheric level both worldwide and by region. The overall magnitudes of cloud cover between the GLOBE participants and the matched satellites agree within 10%, which is notable given the distinctly different natures of the data sources. The mean vertical cloud profiles show GLOBE reporting more low-level clouds and fewer high-level clouds than satellites. The low cloud disagreement is likely related to satellites missing low clouds when high clouds block their view. Conversely, the high cloud disagreement is related primarily to cloud opacity, as satellites may miss some optically thin clouds. Monte Carlo testing shows the results to be robust, and the tripled amount of IOP data reduces uncertainty by half. These findings also highlight ways in which citizen science IOP data may be used to support scientific research while accounting for their unique properties. Plain Language Summary: Citizen science is becoming an increasingly prominent aspect of scientific research, and so it important to study how citizen science data can be used effectively. For example, The GLOBE Program has recently conducted a series of special data-collecting events, or “challenges”, which gathered large numbers of reports on cloud and sky conditions. Because NASA GLOBE Clouds matches the participant reports with cloud observations from satellites, we can use these data to get a combined view of clouds from above and below. When looking at the average cloud cover for different atmospheric levels across Earth, we find that the GLOBE participants and the satellites agree quite closely. This is a surprising and fascinating find, given how different in nature volunteer ground reports are to satellite measurements. However, there are some small but notable disagreements between GLOBE participants and satellites about the distribution of cloud cover at different levels. In addition, by testing the data for uncertainty, we show that the results from the GLOBE data are reliable, and that more public participation improves the reliability. So, by carefully designing the analysis methodology, and by testing for the uncertainty of the data, citizen science can make a meaningful contribution to scientific research.

J. Brant Dodson↗

Sounder design considerations in the selection of temperature sensing channels

Simulation studies on the performance of IR sounders under varying conditions of cloud cover and cloud heights are carried out for Nimbus 6. An analytic function is derived for calculating the relative response to cloud height errors for arbitrary cloud-sensing channels. Based on the values of the response function, the best choice of channels for determining cloud amounts are obtained. An algorithm is described for determining cloud heights, and the sensitivity of cloud-height sensing channels is tested. It is found that for the HIRS instrument, the most transparent channel in the 4.3-micron band is optimal for adjusting cloud heights, while the channel in the 15-micron band peaking closest to the surface is best for determining cloud amounts

Halem, M.↗

PROCAMS - A second generation multispectral-multitemporal data processing system for agricultural mensuration

PROCAMS (Prototype Classification and Mensuration System) has been designed for the classification and mensuration of agricultural crops (specifically small grains including wheat, rye, oats, and barley) through the use of data provided by Landsat. The system includes signature extension as a major feature and incorporates multitemporal as well as early season unitemporal approaches for using multiple training sites. Also addressed are partial cloud cover and cloud shadows, bad data points and lines, as well as changing sun angle and atmospheric state variations.

Erickson, J. D.↗

A parameterized model for global insolation under partially cloudy skies

A simple and efficient parameterization of insolation under partially cloudy skies is discussed and compared with a set of exact radiative transfer results for clear skies, an empirical equation and observations. The parameterization is physically based and requires, as input variables, the ozone path length, precipitable water, Angstrom turbidity, surface air pressure and albedo, fractional cloud-cover and cloud thickness. Multiple reflection between the surface and the overlying atmosphere, and clouds are considered. The albedo of the earth-atmosphere system is also formulated and compared with a set of exact radiative transfer results. As compared to the exact radiative transfer results, the errors in the insolations are generally less than 1 percent, and in the albedo of the earth-atmosphere system less than 10 percent. The errors in the calculated insolations using climatological data are 2-3 percent when compared with many years averaged observations at Maudheim (Antarctica) and at Rockville (U.S.A.). A parametric equation for calculating directly the daily total insolation is also given.

Choudhury, B.↗

GASP cloud encounter statistics - Implications for laminar flow control flight

The cloud observation archive from the NASA Global Atmospheric Sampling Program (GASP) is analyzed in order to derive the probability of cloud encounter at altitudes normally flown by commercial airliners, for application to a determination of the feasability of Laminar Flow Control (LFC) on long-range routes. The probability of cloud encounter is found to vary significantly with season. Several meteorological circulation features are apparent in the latitudinal distribution of cloud cover. The cloud encounter data are shown to be consistent with the classical midlatitude cyclone model with more clouds encountered in highs than in lows. Aircraft measurements of route-averaged time-in-clouds fit a gamma probability distribution model which is applied to estimate the probability of extended cloud encounter, and the associated loss of LFC effectiveness along seven high-density routes. The probability is demonstrated to be low.

Jasperson, W. H.↗

The sensitivity of a one-dimensional thermodynamic sea ice model to changes in cloudiness

A thermodynamic sea ice-lead model is used to assess the importance of cloud cover changes to modeled ice thickness. For regions of either permanent multiyear ice or seasonal sea ice, the cloud amount variations have relatively little impact. However, for regions where the presence of summer ice is variable from year to year, the predicted ice thickness is strongly dependent on cloud cover. In general, with a snow covered surface, decreased cloud leads to surface cooling while increased cloud gives rise to a surface warming. For a melting bare ice surface, the reverse occurs. The ice model response time is too long for interannual variations in cloud amount to explain interannual variations in ice thickness and extent. Nevertheless, the implication of the results is that numerical modeling of sea ice distribution requires accurate cloud data or cloud prediction and that trends in cloud cover may lead to significant perturbations in sea ice extent and thickness.

Shine, K. P.↗