Cloud cover models derived from satellite radiation measurements

NASA Technical Reports Server (NTRS)

Bean, S. J.; Somerville, P. N.

1979-01-01

Using daily measurement of day and night infrared and incoming and absorbed solar radiation obtained from a TIROS satellite over a period of approximately 45 months, and integrated over 2.5 degree latitude-longitude grids, the proportion of cloud cover over each grid each day was derived for the entire period. For each of four three-month periods, estimates a and b of the two parameters of the best-fit beta distribution were obtained for each grid location. The (a,b) plane was divided into a number of regions. All the geographical locations whose (a,b) estimates were in the same region in the (a,b) plane were said to have the same cloud cover type for that season. For each season, the world was thus divided into separate cloud cover types. Using estimates of mean cloud cover for each season, the world was again divided into separate cloud cover types. The process was repeated for standard deviations. Thus for each season, three separate cloud cover models were obtained using the criteria of shape of frequency distribution, mean cloud cover, and variability of cloud cover. The cloud cover statistics were derived from once-a-day, near-local-noon satellite radiation measurements.

Temporal resolution requirements of satellite constellations for 30 m global burned area mapping

NASA Astrophysics Data System (ADS)

Melchiorre, A.; Boschetti, L.

2017-12-01

Global burned area maps have been generated systematically with daily, coarse resolution satellite data (Giglio et al. 2013). The production of moderate resolution (10 - 30 m) global burned area products would meet the needs of several user communities: improved carbon emission estimations due to heterogeneous landscapes and for local scale air quality and fire management applications (Mouillot et al. 2014; van der Werf et al. 2010). While the increased spatial resolution reduces the influence of mixed burnt/unburnt pixels and it would increase the spectral separation of burned areas, moderate resolution satellites have reduced temporal resolution (10 - 16 days). Fire causes a land-cover change spectrally visible for a period ranging from a few weeks in savannas to over a year in forested ecosystems (Roy et al. 2010); because clouds, smoke, and other optically thick aerosols limit the number of available observations (Roy et al. 2008; Smith and Wooster 2005), burned areas might disappear before they are observed by moderate resolution sensors. Data fusion from a constellation of different sensors has been proposed to overcome these limits (Boschetti et al. 2015; Roy 2015). In this study, we estimated the probability of moderate resolution satellites and virtual constellations (including Landsat-8/9, Sentinel-2A/B) to provide sufficient observations for burned area mapping globally, and by ecosystem. First, we estimated the duration of the persistence of the signal associated with burned areas by combining the MODIS Global Burned Area and the Nadir BRDF-Adjusted Reflectance Product by characterizing the post-fire trends in reflectance to determine the length of the period in which the burn class is spectrally distinct from the unburned and, therefore, detectable. The MODIS-Terra daily cloud data were then used to estimate the probability of cloud cover. The cloud probability was used at each location to estimate the minimum revisit time needed to obtain at least one cloud-free observation within the duration of the persistence of burned areas. As complementary results, the expected omission error due to insufficient observations was estimated for each of the satellite combination considered making use of the calendar and geometry of acquisition for each of the sensor included in the virtual constellation.

Coastal pollution hazards in southern California observed by SAR imagery: stormwater plumes, wastewater plumes, and natural hydrocarbon seeps

NASA Technical Reports Server (NTRS)

Digiacomo, Paul M.; Washburn, Libe; Holt, Benjamin; Jones, Burton H.

2004-01-01

Stormwater runoff plumes, municipal wastewater plumes, and natural hydrocarbon seeps are important pollution hazards for the heavily populated Southern California Bight (SCB). Due to their small size, dynamic and episodic nature, these hazards are difficult to sample adequately using traditional in situ oceanographic methods. Complex coastal circulation and persistent cloud cover can further complicate detection and monitoring of these hazards. We use imagery from space-borne synthetic aperture radar (SAR), complemented by field measurements, to examine these hazards in the SCB. The hazards are detectable in SAR imagery because they deposit surfactants on the sea surface, smoothing capillary and small gravity waves to produce areas of reduced backscatter compared with the surrounding ocean. We suggest that high-resolution SAR, which obtains useful data regardless of darkness or cloud cover, could be an important observational tool for assessment and monitoring of coastal marine pollution hazards in the SCB and other urbanized coastal regions.

Rise in the frequency of cloud cover in LANDSAT data for the period 1973 to 1981. [Brazil

NASA Technical Reports Server (NTRS)

Parada, N. D. J. (Principal Investigator); Mendonca, F. J.; Neto, G. C.

1983-01-01

Percentages of cloud cover in LANDSAT imagery were used to calculate the cloud cover monthly average statistic for each LANDSAT scene in Brazil, during the period of 1973 to 1981. The average monthly cloud cover and the monthly minimum cloud cover were also calculated for the regions of north, northeast, central west, southeast and south, separately.

Observations of temporal change of nighttime cloud cover from Himawari 8 and ground-based sky camera over Chiba, Japan

NASA Astrophysics Data System (ADS)

Lagrosas, N.; Gacal, G. F. B.; Kuze, H.

2017-12-01

Detection of nighttime cloud from Himawari 8 is implemented using the difference of digital numbers from bands 13 (10.4µm) and 7 (3.9µm). The digital number difference of -1.39x104 can be used as a threshold to separate clouds from clear sky conditions. To look at observations from the ground over Chiba, a digital camera (Canon Powershot A2300) is used to take images of the sky every 5 minutes at an exposure time of 5s at the Center for Environmental Remote Sensing, Chiba University. From these images, cloud cover values are obtained using threshold algorithm (Gacal, et al, 2016). Ten minute nighttime cloud cover values from these two datasets are compared and analyzed from 29 May to 05 June 2017 (20:00-03:00 JST). When compared with lidar data, the camera can detect thick high level clouds up to 10km. The results show that during clear sky conditions (02-03 June), both camera and satellite cloud cover values show 0% cloud cover. During cloudy conditions (05-06 June), the camera shows almost 100% cloud cover while satellite cloud cover values range from 60 to 100%. These low values can be attributed to the presence of low-level thin clouds ( 2km above the ground) as observed from National Institute for Environmental Studies lidar located inside Chiba University. This difference of cloud cover values shows that the camera can produce accurate cloud cover values of low level clouds that are sometimes not detected by satellites. The opposite occurs when high level clouds are present (01-02 June). Derived satellite cloud cover shows almost 100% during the whole night while ground-based camera shows cloud cover values that range from 10 to 100% during the same time interval. The fluctuating values can be attributed to the presence of thin clouds located at around 6km from the ground and the presence of low level clouds ( 1km). Since the camera relies on the reflected city lights, it is possible that the high level thin clouds are not observed by the camera but is observed by the satellite. Also, this condition constitutes layers of clouds that are not observed by each camera. The results of this study show that one instrument can be used to correct each other to provide better cloud cover values. These corrections is dependent on the height and thickness of the clouds. No correction is necessary when the sky is clear.

On the Nature and Extent of Optically Thin Marine low Clouds

NASA Technical Reports Server (NTRS)

Leahy, L. V.; Wood, R.; Charlson, R. J.; Hostetler, C. A.; Rogers, R. R.; Vaughan, M. A.; Winker, D. M.

2012-01-01

Macrophysical properties of optically thin marine low clouds over the nonpolar oceans (60 deg S-60 deg N) are measured using 2 years of full-resolution nighttime data from the Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP). Optically thin clouds, defined as the subset of marine low clouds that do not fully attenuate the lidar signal, comprise almost half of the low clouds over the marine domain. Regionally, the fraction of low clouds that are optically thin (f(sub thin,cld)) exhibits a strong inverse relationship with the low-cloud cover, with maxima in the tropical trades (f(sub thin,cld) greater than 0.8) and minima in regions of persistent marine stratocumulus and in midlatitudes (f(sub thin,cld) less than 0.3). Domain-wide, a power law fit describes the cloud length distribution, with exponent beta = 2.03 +/- 0.06 (+/-95% confidence interval). On average, the fraction of a cloud that is optically thin decreases from approximately 1 for clouds smaller than 2 km to less than 0.3 for clouds larger than 30 km. This relationship is found to be independent of region, so that geographical variations in the cloud length distribution explain three quarters of the variance in f(sub thin,cld). Comparing collocated trade cumulus observations from CALIOP and the airborne High Spectral Resolution Lidar reveals that clouds with lengths smaller than are resolvable with CALIOP contribute approximately half of the low clouds in the region sampled. A bounded cascade model is constructed to match the observations from the trades. The model shows that the observed optically thin cloud behavior is consistent with a power law scaling of cloud optical depth and suggests that most optically thin clouds only partially fill the CALIOP footprint.

Study and Application on Cloud Covered Rate for Agroclimatical Distribution Using In Guangxi Based on Modis Data

NASA Astrophysics Data System (ADS)

Yang, Xin; Zhong, Shiquan; Sun, Han; Tan, Zongkun; Li, Zheng; Ding, Meihua

Based on analyzing of the physical characteristics of cloud and importance of cloud in agricultural production and national economy, cloud is a very important climatic resources such as temperature, precipitation and solar radiation. Cloud plays a very important role in agricultural climate division .This paper analyzes methods of cloud detection based on MODIS data in China and Abroad . The results suggest that Quanjun He method is suitable to detect cloud in Guangxi. State chart of cloud cover in Guangxi is imaged by using Quanjun He method .We find out the approach of calculating cloud covered rate by using the frequency spectrum analysis. At last, the Guangxi is obtained. Taking Rongxian County Guangxi as an example, this article analyze the preliminary application of cloud covered rate in distribution of Rong Shaddock pomelo . Analysis results indicate that cloud covered rate is closely related to quality of Rong Shaddock pomelo.

The beta distribution: A statistical model for world cloud cover

NASA Technical Reports Server (NTRS)

Falls, L. W.

1973-01-01

Much work has been performed in developing empirical global cloud cover models. This investigation was made to determine an underlying theoretical statistical distribution to represent worldwide cloud cover. The beta distribution with probability density function is given to represent the variability of this random variable. It is shown that the beta distribution possesses the versatile statistical characteristics necessary to assume the wide variety of shapes exhibited by cloud cover. A total of 160 representative empirical cloud cover distributions were investigated and the conclusion was reached that this study provides sufficient statical evidence to accept the beta probability distribution as the underlying model for world cloud cover.

Monthly and Seasonal Cloud Cover Patterns at the Manila Observatory (14.64°N, 121.08°E)

NASA Astrophysics Data System (ADS)

Antioquia, C. T.; Lagrosas, N.; Caballa, K.

2014-12-01

A ground based sky imaging system was developed at the Manila Observatory in 2012 to measure cloud occurrence and to analyse seasonal variation of cloud cover over Metro Manila. Ground-based cloud occurrence measurements provide more reliable results compared to satellite observations. Also, cloud occurrence data aid in the analysis of radiation budget in the atmosphere. In this study, a GoPro Hero 2 with almost 180o field of view is employed to take pictures of the atmosphere. These pictures are taken continuously, having a temporal resolution of 1min. Atmospheric images from April 2012 to June 2013 (excluding the months of September, October, and November 2012) were processed to determine cloud cover. Cloud cover in an image is measured as the ratio of the number of pixels with clouds present in them to the total number of pixels. The cloud cover values were then averaged over each month to know its monthly and seasonal variation. In Metro Manila, the dry season occurs in the months of November to May of the next year, while the wet season occurs in the months of June to October of the same year. Fig 1 shows the measured monthly variation of cloud cover. No data was collected during the months of September (wherein the camera was used for the 7SEAS field campaign), October, and November 2012 (due to maintenance and repairs). Results show that there is high cloud cover during the wet season months (80% on average) while there is low cloud cover during the dry season months (62% on average). The lowest average cloud cover for a wet season month occurred in June 2012 (73%) while the highest average cloud cover for a wet season month occurred in June 2013 (86%). The variations in cloud cover average in this season is relatively smaller compared to that of the dry season wherein the lowest average cloud cover in a month was during April 2012 (38%) while the highest average cloud cover in a month was during January 2013 (77%); minimum and maximum averages being 39% apart. During the wet season, the cloud occurrence is mainly due to tropical storms, Southwest Monsoon, and local convection processes. In the dry season, less cloud is formed because of cold dry air from Northeast Monsoon (December to February) and generally dry and hot weather (March to May). Regular data collection has been implemented for further long term data analysis.

Comparative lahar hazard mapping at Volcan Citlaltépetl, Mexico using SRTM, ASTER and DTED-1 digital topographic data

USGS Publications Warehouse

Hubbard, Bernard E.; Sheridan, Michael F.; Carrasco-Nunez, Gerardo; Diaz-Castellon, Rodolfo; Rodriguez, Sergio R.

2007-01-01

Finally, ASTERs 60 km swath width and 8% duty cycle presents a challenge for mapping lahar inundation hazards at E–W oriented stream valleys in low-latitude areas with persistent cloud cover. However, its continued operations enhances its utility as a means for updating the continuous but one-time coverage of SRTM, and for filling voids in the SRTM dataset such as those that occur along steep-sided valleys prone to hazards from future lahars.

A cloud cover model based on satellite data

NASA Technical Reports Server (NTRS)

Somerville, P. N.; Bean, S. J.

1980-01-01

A model for worldwide cloud cover using a satellite data set containing infrared radiation measurements is proposed. The satellite data set containing day IR, night IR and incoming and absorbed solar radiation measurements on a 2.5 degree latitude-longitude grid covering a 45 month period was converted to estimates of cloud cover. The global area was then classified into homogeneous cloud cover regions for each of the four seasons. It is noted that the developed maps can be of use to the practicing climatologist who can obtain a considerable amount of cloud cover information without recourse to large volumes of data.

Fusion of optical and SAR remote sensing images for tropical forests monitoring

NASA Astrophysics Data System (ADS)

Wang, C.; Yu, M.; Gao, Q.; Wang, X.

2016-12-01

Although tropical deforestation prevails in South America and Southeast Asia, reforestation appeared in some tropical regions due to economic changes. After the economic shift from agriculture to industry, the tropical island of Puerto Rico has experienced rapid reforestation as well as urban expansion since the late 1940s. Continued urban growth without the guide of sustainable planning might prevent further forest regrowth. Accurate and timely mapping of LULC is of great importance for evaluating the consequences of reforestation and urban expansion on the coupled human and nature systems. However, owning to persistent cloud cover in tropics, it remains a challenge to produce reliable LULC maps in fine spatial resolution. Here, we retrieved cloud-free Landsat surface reflectance composite data by removing clouds and shades from the USGS Landsat Surface Reflectance (SR) product for each scene using the CFmask and Fmask algorithms in Google Earth Engine. We then produced high accuracy land cover classification maps using SR optical data for the year of 2000 and fused optical and ALOS SAR data for 2010 and 2015, with an overall accuracy of 92.0%, 92.5%, and 91.6%, respectively. The classification result indicated that a successive forest gain of 6.52% and 1.03% occurred between the first (2000-2010) and second (2010-2015) study periods, respectively. We also conducted a comparative spatial analysis of patterns of deforestation and reforestation based on a series of forest cover zones (50 × 50 pixels, 150 ha). The annual rates of deforestation and reforestation against forest cover presented the similar trends during two periods: decreasing with the forest cover increasing. However, the annual net forest change rate was different in the zones with forest cover less than 30%, presenting significant gain (2.2-8.4% yr-1) for the first period and significant loss (2.3-6.4% yr-1) for the second period. It indicated that both deforestation and reforestation mostly occurred near the forest edges and low density secondary forests.

The potential of using Landsat time-series to extract tropical dry forest phenology

NASA Astrophysics Data System (ADS)

Zhu, X.; Helmer, E.

2016-12-01

Vegetation phenology is the timing of seasonal developmental stages in plant life cycles. Due to the persistent cloud cover in tropical regions, current studies often use satellite data with high frequency, such as AVHRR and MODIS, to detect vegetation phenology. However, the spatial resolution of these data is from 250 m to 1 km, which does not have enough spatial details and it is difficult to relate to field observations. To produce maps of phenology at a finer spatial resolution, this study explores the feasibility of using Landsat images to detect tropical forest phenology through reconstructing a high-quality, seasonal time-series of images, and tested it in Mona Island, Puerto Rico. First, an automatic method was applied to detect cloud and cloud shadow, and a spatial interpolator was use to retrieve pixels covered by clouds, shadows, and SLC-off gaps. Second, enhanced vegetation index time-series derived from the reconstructed Landsat images were used to detect 11 phenology variables. Detected phenology is consistent with field investigations, and its spatial pattern is consistent with the rainfall distribution on this island. In addition, we may expect that phenology should correlate with forest biophysical attributes, so 47 plots with field measurement of biophysical attributes were used to indirectly validate the phenology product. Results show that phenology variables can explain a lot of variations in biophysical attributes. This study suggests that Landsat time-series has great potential to detect phenology in tropical areas.

Tropical Montane Cloud Forests: Hydrometeorological variability in three neighbouring catchments with different forest cover

NASA Astrophysics Data System (ADS)

Ramírez, Beatriz H.; Teuling, Adriaan J.; Ganzeveld, Laurens; Hegger, Zita; Leemans, Rik

2017-09-01

Mountain areas are characterized by a large heterogeneity in hydrological and meteorological conditions. This heterogeneity is currently poorly represented by gauging networks and by the coarse scale of global and regional climate and hydrological models. Tropical Montane Cloud Forests (TMCFs) are found in a narrow elevation range and are characterized by persistent fog. Their water balance depends on local and upwind temperatures and moisture, therefore, changes in these parameters will alter TMCF hydrology. Until recently the hydrological functioning of TMCFs was mainly studied in coastal regions, while continental TMCFs were largely ignored. This study contributes to fill this gap by focusing on a TMCF which is located on the northern eastern Andes at an elevation of 1550-2300 m asl, in the Orinoco river basin highlands. In this study, we describe the spatial and seasonal meteorological variability, analyse the corresponding catchment hydrological response to different land cover, and perform a sensitivity analysis on uncertainties related to rainfall interpolation, catchment area estimation and streamflow measurements. Hydro-meteorological measurements, including hourly solar radiation, temperature, relative humidity, wind speed, precipitation, soil moisture and streamflow, were collected from June 2013 to May 2014 at three gauged neighbouring catchments with contrasting TMCF/grassland cover and less than 250 m elevation difference. We found wetter and less seasonally contrasting conditions at higher elevations, indicating a positive relation between elevation and fog or rainfall persistence. This pattern is similar to that of other eastern Andean TMCFs, however, the study site had higher wet season rainfall and lower dry season rainfall suggesting that upwind contrasts in land cover and moisture can influence the meteorological conditions at eastern Andean TMCFs. Contrasting streamflow dynamics between the studied catchments reflect the overall system response as a function of the catchments' elevation and land cover. The forested catchment, located at the higher elevations, had the highest seasonal streamflows. During the wet season, different land covers at the lower elevations were important in defining the streamflow responses between the deforested catchment and the catchment with intermediate forest cover. Streamflows were higher and the rainfall-runoff responses were faster in the deforested catchment than in the intermediate forest cover catchment. During the dry season, the catchments' elevation defined streamflows due to higher water inputs and lower evaporative demand at the higher elevations.

Satellite Studies of Cirrus Clouds for Project Fire

NASA Technical Reports Server (NTRS)

1997-01-01

Examine global cloud climatologies for evidence of human caused changes in cloud cover and their effect on the Earth's heat budget through radiative processes. Quantify climatological changes in global cloud cover and estimate their effect on the Earth's heat budget. Improve our knowledge of global cloud cover and its changes through the merging of several satellite data sets.

Cloud cover detection combining high dynamic range sky images and ceilometer measurements

NASA Astrophysics Data System (ADS)

Román, R.; Cazorla, A.; Toledano, C.; Olmo, F. J.; Cachorro, V. E.; de Frutos, A.; Alados-Arboledas, L.

2017-11-01

This paper presents a new algorithm for cloud detection based on high dynamic range images from a sky camera and ceilometer measurements. The algorithm is also able to detect the obstruction of the sun. This algorithm, called CPC (Camera Plus Ceilometer), is based on the assumption that under cloud-free conditions the sky field must show symmetry. The symmetry criteria are applied depending on ceilometer measurements of the cloud base height. CPC algorithm is applied in two Spanish locations (Granada and Valladolid). The performance of CPC retrieving the sun conditions (obstructed or unobstructed) is analyzed in detail using as reference pyranometer measurements at Granada. CPC retrievals are in agreement with those derived from the reference pyranometer in 85% of the cases (it seems that this agreement does not depend on aerosol size or optical depth). The agreement percentage goes down to only 48% when another algorithm, based on Red-Blue Ratio (RBR), is applied to the sky camera images. The retrieved cloud cover at Granada and Valladolid is compared with that registered by trained meteorological observers. CPC cloud cover is in agreement with the reference showing a slight overestimation and a mean absolute error around 1 okta. A major advantage of the CPC algorithm with respect to the RBR method is that the determined cloud cover is independent of aerosol properties. The RBR algorithm overestimates cloud cover for coarse aerosols and high loads. Cloud cover obtained only from ceilometer shows similar results than CPC algorithm; but the horizontal distribution cannot be obtained. In addition, it has been observed that under quick and strong changes on cloud cover ceilometers retrieve a cloud cover fitting worse with the real cloud cover.

Farming the Tropics: Visualizing Landscape Changes Through the Clouds, in the Cloud

NASA Astrophysics Data System (ADS)

Kontgis, C.; Brumby, S. P.; Chartrand, R.; Franco, E.; Keisler, R.; Kelton, T.; Mathis, M.; Moody, D.; Raleigh, D.; Rudelis, X.; Skillman, S.; Warren, M. S.

2016-12-01

A key component of studying land cover and land use change is analyzing trends in spectral signatures through time. For vegetation, the standard method of doing this involves the normalized difference vegetation index (NDVI) or near infrared signal during a growing season, as both increase while plants grow and decrease during senescence. If temporal resolution were high and clouds did not obstruct landscape views, this approach could work across the globe. However, in tropical regions that are increasingly important for global food production, often there is not enough spectral information to monitor landscape change due to persistent cloud cover. In these instances, synthetic aperture radar (SAR) data provides a useful alternative to shorter wavelength components of the spectrum since its longer wavelengths can penetrate clouds. This analysis uses the cloud-based platform developed by Descartes Labs to explore the utility of Sentinel-1 data in cloudy tropical regions, using the Mekong River Delta in southern Vietnam as a case study. We compare phenological growing patterns derived from Sentinel-1 data with those from Landsat and MODIS imagery, which are the most commonly used sensors to map land cover and land use across the globe. Using these SAR-derived phenology curves, it is possible to monitor landscape changes in near real-time, while also visualizing and quantifying the rates of agricultural intensification. Descartes Labs is a venture-backed remote sensing startup founded in 2014 by a group of scientists from the Los Alamos National Laboratory in New Mexico. Since its inception, the team at Descartes has assembled all available satellite imagery from the USGS Landsat and NASA MODIS programs, and has analyzed over 2.8 quadrillion pixels of satellite imagery. With a focus on food security and climate change, the company has succeeded at estimating United States corn yields earlier and more accurately than USDA estimates. Now, this technology is being applied to within-season forecasting of acreage and yields in near real-time, while also branching out beyond the US to other regions including South America and Asia.

On the response of MODIS cloud coverage to global mean surface air temperature

NASA Astrophysics Data System (ADS)

Yue, Qing; Kahn, Brian H.; Fetzer, Eric J.; Wong, Sun; Frey, Richard; Meyer, Kerry G.

2017-01-01

The global surface temperature change (ΔTs) mediated cloud cover response is directly related to cloud-climate feedback. Using satellite remote sensing data to relate cloud and climate requires a well-calibrated, stable, and consistent long-term cloud data record. The Collection 5.1 (C5) Moderate Resolution Imaging Spectroradiometer (MODIS) cloud observations have been widely used for this purpose. However, the MODIS data quality varies greatly with the surface type, spectral region, cloud type, and time periods of study, which calls for additional caution when applying such data to studies on cloud cover temporal trends and variability. Using 15 years of cloud observations made by Terra and Aqua MODIS, we analyze the ΔTs-mediated cloud cover response for different cloud types by linearly regressing the monthly anomaly of cloud cover (ΔC) with the monthly anomaly of global Ts. The Collection 6 (C6) Aqua data exhibit a similar cloud response to the long-term counterpart simulated by advanced climate models. A robust increase in altitude with increasing ΔTs is found for high clouds, while a robust decrease of ΔC is noticed for optically thick low clouds. The large differences between C5 and C6 results are from improvements in calibration and cloud retrieval algorithms. The large positive cloud cover responses with data after 2010 and the strong sensitivity to time period obtained from the Terra (C5 and C6) data are likely due to calibration drift that has not been corrected, suggesting that the previous estimate of the short-term cloud cover response from the these data should be revisited.

Contrasting sea-ice and open-water boundary layers during melt and freeze-up seasons: Some result from the Arctic Clouds in Summer Experiment.

NASA Astrophysics Data System (ADS)

Tjernström, Michael; Sotiropoulou, Georgia; Sedlar, Joseph; Achtert, Peggy; Brooks, Barbara; Brooks, Ian; Persson, Ola; Prytherch, John; Salsbury, Dominic; Shupe, Matthew; Johnston, Paul; Wolfe, Dan

2016-04-01

With more open water present in the Arctic summer, an understanding of atmospheric processes over open-water and sea-ice surfaces as summer turns into autumn and ice starts forming becomes increasingly important. The Arctic Clouds in Summer Experiment (ACSE) was conducted in a mix of open water and sea ice in the eastern Arctic along the Siberian shelf during late summer and early autumn 2014, providing detailed observations of the seasonal transition, from melt to freeze. Measurements were taken over both ice-free and ice-covered surfaces, offering an insight to the role of the surface state in shaping the lower troposphere and the boundary-layer conditions as summer turned into autumn. During summer, strong surface inversions persisted over sea ice, while well-mixed boundary layers capped by elevated inversions were frequent over open-water. The former were often associated with advection of warm air from adjacent open-water or land surfaces, whereas the latter were due to a positive buoyancy flux from the warm ocean surface. Fog and stratus clouds often persisted over the ice, whereas low-level liquid-water clouds developed over open water. These differences largely disappeared in autumn, when mixed-phase clouds capped by elevated inversions dominated in both ice-free and ice-covered conditions. Low-level-jets occurred ~20-25% of the time in both seasons. The observations indicate that these jets were typically initiated at air-mass boundaries or along the ice edge in autumn, while in summer they appeared to be inertial oscillations initiated by partial frictional decoupling as warm air was advected in over the sea ice. The start of the autumn season was related to an abrupt change in atmospheric conditions, rather than to the gradual change in solar radiation. The autumn onset appeared as a rapid cooling of the whole atmosphere and the freeze up followed as the warm surface lost heat to the atmosphere. While the surface type had a pronounced impact on boundary-layer structure in summer, the surface was often warmer than the atmosphere in autumn, regardless of surface type. Hence the autumn boundary-layer structure was more dependent on synoptic scale meteorology.

Using polarimetry to retrieve the cloud coverage of Earth-like exoplanets

NASA Astrophysics Data System (ADS)

Rossi, L.; Stam, D. M.

2017-11-01

Context. Clouds have already been detected in exoplanetary atmospheres. They play crucial roles in a planet's atmosphere and climate and can also create ambiguities in the determination of atmospheric parameters such as trace gas mixing ratios. Knowledge of cloud properties is required when assessing the habitability of a planet. Aims: We aim to show that various types of cloud cover such as polar cusps, subsolar clouds, and patchy clouds on Earth-like exoplanets can be distinguished from each other using the polarization and flux of light that is reflected by the planet. Methods: We have computed the flux and polarization of reflected starlight for different types of (liquid water) cloud covers on Earth-like model planets using the adding-doubling method, that fully includes multiple scattering and polarization. Variations in cloud-top altitudes and planet-wide cloud cover percentages were taken into account. Results: We find that the different types of cloud cover (polar cusps, subsolar clouds, and patchy clouds) can be distinguished from each other and that the percentage of cloud cover can be estimated within 10%. Conclusions: Using our proposed observational strategy, one should be able to determine basic orbital parameters of a planet such as orbital inclination and estimate cloud coverage with reduced ambiguities from the planet's polarization signals along its orbit.

External Influences on Modeled and Observed Cloud Trends

NASA Technical Reports Server (NTRS)

Marvel, Kate; Zelinka, Mark; Klein, Stephen A.; Bonfils, Celine; Caldwell, Peter; Doutriaux, Charles; Santer, Benjamin D.; Taylor, Karl E.

2015-01-01

Understanding the cloud response to external forcing is a major challenge for climate science. This crucial goal is complicated by intermodel differences in simulating present and future cloud cover and by observational uncertainty. This is the first formal detection and attribution study of cloud changes over the satellite era. Presented herein are CMIP5 (Coupled Model Intercomparison Project - Phase 5) model-derived fingerprints of externally forced changes to three cloud properties: the latitudes at which the zonally averaged total cloud fraction (CLT) is maximized or minimized, the zonal average CLT at these latitudes, and the height of high clouds at these latitudes. By considering simultaneous changes in all three properties, the authors define a coherent multivariate fingerprint of cloud response to external forcing and use models from phase 5 of CMIP (CMIP5) to calculate the average time to detect these changes. It is found that given perfect satellite cloud observations beginning in 1983, the models indicate that a detectable multivariate signal should have already emerged. A search is then made for signals of external forcing in two observational datasets: ISCCP (International Satellite Cloud Climatology Project) and PATMOS-x (Advanced Very High Resolution Radiometer (AVHRR) Pathfinder Atmospheres - Extended). The datasets are both found to show a poleward migration of the zonal CLT pattern that is incompatible with forced CMIP5 models. Nevertheless, a detectable multivariate signal is predicted by models over the PATMOS-x time period and is indeed present in the dataset. Despite persistent observational uncertainties, these results present a strong case for continued efforts to improve these existing satellite observations, in addition to planning for new missions.

Application and Evaluation of an Explicit Prognostic Cloud-Cover Scheme in GRAPES Global Forecast System

NASA Astrophysics Data System (ADS)

Ma, Zhanshan; Liu, Qijun; Zhao, Chuanfeng; Shen, Xueshun; Wang, Yuan; Jiang, Jonathan H.; Li, Zhe; Yung, Yuk

2018-03-01

An explicit prognostic cloud-cover scheme (PROGCS) is implemented into the Global/Regional Assimilation and Prediction System (GRAPES) for global middle-range numerical weather predication system (GRAPES_GFS) to improve the model performance in simulating cloud cover and radiation. Unlike the previous diagnostic cloud-cover scheme (DIAGCS), PROGCS considers the formation and dissipation of cloud cover by physically connecting it to the cumulus convection and large-scale stratiform condensation processes. Our simulation results show that clouds in mid-high latitudes arise mainly from large-scale stratiform condensation processes, while cumulus convection and large-scale condensation processes jointly determine cloud cover in low latitudes. Compared with DIAGCS, PROGCS captures more consistent vertical distributions of cloud cover with the observations from Atmospheric Radiation Measurements (ARM) program at the Southern Great Plains (SGP) site and simulates more realistic diurnal cycle of marine stratocumulus with the ERA-Interim reanalysis data. The low, high, and total cloud covers that are determined via PROGCS appear to be more realistic than those simulated via DIAGCS when both are compared with satellite retrievals though the former maintains slight negative biases. In addition, the simulations of outgoing longwave radiation (OLR) at the top of the atmosphere (TOA) from PROGCS runs have been considerably improved as well, resulting in less biases in radiative heating rates at heights below 850 hPa and above 400 hPa of GRAPES_GFS. Our results indicate that a prognostic method of cloud-cover calculation has significant advantage over the conventional diagnostic one, and it should be adopted in both weather and climate simulation and forecast.

Advancing the quantification of humid tropical forest cover loss with multi-resolution optical remote sensing data: Sampling & wall-to-wall mapping

NASA Astrophysics Data System (ADS)

Broich, Mark

Humid tropical forest cover loss is threatening the sustainability of ecosystem goods and services as vast forest areas are rapidly cleared for industrial scale agriculture and tree plantations. Despite the importance of humid tropical forest in the provision of ecosystem services and economic development opportunities, the spatial and temporal distribution of forest cover loss across large areas is not well quantified. Here I improve the quantification of humid tropical forest cover loss using two remote sensing-based methods: sampling and wall-to-wall mapping. In all of the presented studies, the integration of coarse spatial, high temporal resolution data with moderate spatial, low temporal resolution data enable advances in quantifying forest cover loss in the humid tropics. Imagery from the Moderate Resolution Imaging Spectroradiometer (MODIS) are used as the source of coarse spatial resolution, high temporal resolution data and imagery from the Landsat Enhanced Thematic Mapper Plus (ETM+) sensor are used as the source of moderate spatial, low temporal resolution data. In a first study, I compare the precision of different sampling designs for the Brazilian Amazon using the annual deforestation maps derived by the Brazilian Space Agency for reference. I show that sampling designs can provide reliable deforestation estimates; furthermore, sampling designs guided by MODIS data can provide more efficient estimates than the systematic design used for the United Nations Food and Agricultural Organization Forest Resource Assessment 2010. Sampling approaches, such as the one demonstrated, are viable in regions where data limitations, such as cloud contamination, limit exhaustive mapping methods. Cloud-contaminated regions experiencing high rates of change include Insular Southeast Asia, specifically Indonesia and Malaysia. Due to persistent cloud cover, forest cover loss in Indonesia has only been mapped at a 5-10 year interval using photo interpretation of single best Landsat images. Such an approach does not provide timely results, and cloud cover reduces the utility of map outputs. In a second study, I develop a method to exhaustively mine the recently opened Landsat archive for cloud-free observations and automatically map forest cover loss for Sumatra and Kalimantan for the 2000-2005 interval. In a comparison with a reference dataset consisting of 64 Landsat sample blocks, I show that my method, using per pixel time-series, provides more accurate forest cover loss maps for multiyear intervals than approaches using image composites. In a third study, I disaggregate Landsat-mapped forest cover loss, mapped over a multiyear interval, by year using annual forest cover loss maps generated from coarse spatial, high temporal resolution MODIS imagery. I further disaggregate and analyze forest cover loss by forest land use, and provinces. Forest cover loss trends show high spatial and temporal variability. These results underline the importance of annual mapping for the quantification of forest cover loss in Indonesia, specifically in the light of the developing Reducing Emissions from Deforestation and Forest Degradation in Developing Countries policy framework (REDD). All three studies highlight the advances in quantifying forest cover loss in the humid tropics made by integrating coarse spatial, high temporal resolution data with moderate spatial, low temporal resolution data. The three methods presented can be combined into an integrated monitoring strategy.

Possible external sources of terrestrial cloud cover variability: the solar wind

NASA Astrophysics Data System (ADS)

Voiculescu, Mirela; Usoskin, Ilya; Condurache-Bota, Simona

2014-05-01

Cloud cover plays an important role in the terrestrial radiation budget. The possible influence of the solar activity on cloud cover is still an open question with contradictory answers. An extraterrestrial factor potentially affecting the cloud cover is related to fields associated with solar wind. We focus here on a derived quantity, the interplanetary electric field (IEF), defined as the product between the solar wind speed and the meridional component, Bz, of the interplanetary magnetic field (IMF) in the Geocentric Solar Magnetospheric (GSM) system. We show that cloud cover at mid-high latitudes systematically correlates with positive IEF, which has a clear energetic input into the atmosphere, but not with negative IEF, in general agreement with predictions of the global electric circuit (GEC)-related mechanism. Since the IEF responds differently to solar activity than, for instance, cosmic ray flux or solar irradiance, we also show that such a study allows distinguishing one solar-driven mechanism of cloud evolution, via the GEC, from others. We also present results showing that the link between cloud cover and IMF varies depending on composition and altitude of clouds.

Spectrometry of Pasture Condition and Biogeochemistry in the Central Amazon

NASA Technical Reports Server (NTRS)

Asner, Gregory P.; Townsend, Alan R.; Bustamante, Mercedes M. C.

1999-01-01

Regional analyses of Amazon cattle pasture biogeochemistry are difficult due to the complexity of human, edaphic, biotic and climatic factors and persistent cloud cover in satellite observations. We developed a method to estimate key biophysical properties of Amazon pastures using hyperspectral reflectance data and photon transport inverse modeling. Remote estimates of live and senescent biomass were strongly correlated with plant-available forms of soil phosphorus and calcium. These results provide a basis for monitoring pasture condition and biogeochemistry in the Amazon Basin using spaceborne hyperspectral sensors.

Resolution Enhancement of MODIS-derived Water Indices for Studying Persistent Flooding

NASA Astrophysics Data System (ADS)

Underwood, L. W.; Kalcic, M. T.; Fletcher, R. M.

2012-12-01

Monitoring coastal marshes for persistent flooding and salinity stress is a high priority issue in Louisiana. Remote sensing can identify environmental variables that can be indicators of marsh habitat conditions, and offer timely and relatively accurate information for aiding wetland vegetation management. Monitoring activity accuracy is often limited by mixed pixels which occur when areas represented by the pixel encompasses more than one cover type. Mixtures of marsh grasses and open water in 250m Moderate Resolution Imaging Spectroradiometer (MODIS) data can impede flood area estimation. Flood mapping of such mixtures requires finer spatial resolution data to better represent the cover type composition within 250m MODIS pixel. Fusion of MODIS and Landsat can improve both spectral and temporal resolution of time series products to resolve rapid changes from forcing mechanisms like hurricane winds and storm surge. For this study, using a method for estimating sub-pixel values from a MODIS time series of a Normalized Difference Water Index (NDWI), using temporal weighting, was implemented to map persistent flooding in Louisiana coastal marshes. Ordinarily NDWI computed from daily 250m MODIS pixels represents a mixture of fragmented marshes and water. Here, sub-pixel NDWI values were derived for MODIS data using Landsat 30-m data. Each MODIS pixel was disaggregated into a mixture of the eight cover types according to the classified image pixels falling inside the MODIS pixel. The Landsat pixel means for each cover type inside a MODIS pixel were computed for the Landsat data preceding the MODIS image in time and for the Landsat data succeeding the MODIS image. The Landsat data were then weighted exponentially according to closeness in date to the MODIS data. The reconstructed MODIS data were produced by summing the product of fractional cover type with estimated NDWI values within each cover type. A new daily time series was produced using both the reconstructed 250-m MODIS, with enhanced features, and the approximated daily 30-m high-resolution image based on Landsat data. The algorithm was developed and tested over the Calcasieu-Sabine Basin, which was heavily inundated by storm surge from Hurricane Ike to study the extent and duration of flooding following the storm. Time series for 2000-2009, covering flooding events by Hurricane Rita in 2005 and Hurricane Ike in 2008, were derived. High resolution images were formed for all days in 2008 between the first cloud free Landsat scene and the last cloud-free Landsat scene. To refine and validate flooding maps, each time series was compared to Louisiana Coastwide Reference Monitoring System (CRMS) station water levels adjusted to marsh to optimize thresholds for MODIS-derived time series of NDWI. Seasonal fluctuations were adjusted by subtracting ten year average NDWI for marshes, excluding the hurricane events. Results from different NDWI indices and a combination of indices were compared. Flooding persistence that was mapped with higher-resolution data showed some improvement over the original MODIS time series estimates. The advantage of this novel technique is that improved mapping of extent and duration of inundation can be provided.

Resolution Enhancement of MODIS-Derived Water Indices for Studying Persistent Flooding

NASA Technical Reports Server (NTRS)

Underwood, L. W.; Kalcic, Maria; Fletcher, Rose

2012-01-01

Monitoring coastal marshes for persistent flooding and salinity stress is a high priority issue in Louisiana. Remote sensing can identify environmental variables that can be indicators of marsh habitat conditions, and offer timely and relatively accurate information for aiding wetland vegetation management. Monitoring activity accuracy is often limited by mixed pixels which occur when areas represented by the pixel encompasses more than one cover type. Mixtures of marsh grasses and open water in 250m Moderate Resolution Imaging Spectroradiometer (MODIS) data can impede flood area estimation. Flood mapping of such mixtures requires finer spatial resolution data to better represent the cover type composition within 250m MODIS pixel. Fusion of MODIS and Landsat can improve both spectral and temporal resolution of time series products to resolve rapid changes from forcing mechanisms like hurricane winds and storm surge. For this study, using a method for estimating sub-pixel values from a MODIS time series of a Normalized Difference Water Index (NDWI), using temporal weighting, was implemented to map persistent flooding in Louisiana coastal marshes. Ordinarily NDWI computed from daily 250m MODIS pixels represents a mixture of fragmented marshes and water. Here, sub-pixel NDWI values were derived for MODIS data using Landsat 30-m data. Each MODIS pixel was disaggregated into a mixture of the eight cover types according to the classified image pixels falling inside the MODIS pixel. The Landsat pixel means for each cover type inside a MODIS pixel were computed for the Landsat data preceding the MODIS image in time and for the Landsat data succeeding the MODIS image. The Landsat data were then weighted exponentially according to closeness in date to the MODIS data. The reconstructed MODIS data were produced by summing the product of fractional cover type with estimated NDWI values within each cover type. A new daily time series was produced using both the reconstructed 250-m MODIS, with enhanced features, and the approximated daily 30-m high-resolution image based on Landsat data. The algorithm was developed and tested over the Calcasieu-Sabine Basin, which was heavily inundated by storm surge from Hurricane Ike to study the extent and duration of flooding following the storm. Time series for 2000-2009, covering flooding events by Hurricane Rita in 2005 and Hurricane Ike in 2008, were derived. High resolution images were formed for all days in 2008 between the first cloud free Landsat scene and the last cloud-free Landsat scene. To refine and validate flooding maps, each time series was compared to Louisiana Coastwide Reference Monitoring System (CRMS) station water levels adjusted to marsh to optimize thresholds for MODIS-derived time series of NDWI. Seasonal fluctuations were adjusted by subtracting ten year average NDWI for marshes, excluding the hurricane events. Results from different NDWI indices and a combination of indices were compared. Flooding persistence that was mapped with higher-resolution data showed some improvement over the original MODIS time series estimates. The advantage of this novel technique is that improved mapping of extent and duration of inundation can be provided.

Global synthesis of long-term cloud condensation nuclei observations

NASA Astrophysics Data System (ADS)

Schmale, Julia; Henning, Silvia; Stratmann, Frank; Henzing, Bas; Schlag, Patrick; Aalto, Pasi; Keskinen, Helmi; Sellegri, Karine; Ovadnevaite, Jurgita; Krüger, Mira; Jefferson, Anne; Whitehead, James; Carslaw, Ken; Yum, Seong Soo; Kristensson, Adam; Baltensperger, Urs; Gysel, Martin

2016-04-01

Cloud condensation nuclei (CCN) are aerosol particles with the ability to activate into droplets at a given super saturation and therefore influence the microphysical and optical properties of clouds. To predict cloud radiative properties understanding the spatial and temporal variability of CCN concentrations in different environments is important. However, currently, the effects of atmospheric particles on changes in cloud radiative forcing are still the largest contribution of uncertainty in climate forcing prediction (IPCC, 2013). Numerous intensive field campaigns have already explored detailed characteristics of CCN in many locations around the world. However, these rather short-term observations can generally not address seasonal or inter-annual variations and a comparison between campaign sites is difficult due to the higher influence of specific environmental circumstances on short-term measurements results. Here, we present results of more long-term CCN and aerosol number concentrations as well as size distribution data covering at least one full year between 2006 and 2014. The 12 locations include ACTRIS stations (http://www.actris.net/) in Europe, and further sites in North America, Brazil and Korea. The sites are located in different environments allowing for temporal and spatial characterization of CCN variability in different atmospheric regimes. Those include marine, remote-continental, boreal forest, rain forest, Arctic and monsoon-influenced environments, as well as boundary layer and free tropospheric conditions. The aerosol populations and their activation behavior show significant differences across the stations. While peak concentrations of CCN are observed in summer at the high altitude sites, in the Arctic the highest concentrations occur during the Haze period in spring. The rural-marine and rural-continental sites exhibit similar CCN concentration characteristics with a relatively flat annual cycle. At some stations, e.g. in the boreal environment, the annual cycle is more pronounced for higher SS. Geometric mean diameters of aerosol populations as well as the activation ratios on the basis of particles > 50 nm vary strongly among sites and throughout the seasons. Additionally, autocorrelation analysis is performed to investigate the persistence of variables over different timescales and to explore meaningful averaging periods for global modelling of CCN. In terms of CCN persistence, we find three different regimes: (1) CCN concentrations persist for a week or longer showing also seasonal patterns. (2) CCN concentrations persist for less than one week and there is little seasonal pattern. And (3) CCN concentrations are highly variable and do not persist longer than 2 days but show seasonal cycles. Several but not all sites show diurnal cycles. These different behaviors are influenced by environmental factors such as rainy seasons in the Amazon or Korea (monsoon) but also by anthropogenic pollution episodes such as during the Arctic Haze period.

Sensitivity of the southern West African mean atmospheric state to variations in low-level cloud cover as simulated by ICON

NASA Astrophysics Data System (ADS)

Kniffka, Anke; Knippertz, Peter; Fink, Andreas

2017-04-01

This contribution presents first results of numerical sensitivity experiments that are carried out in the framework of the project DACCIWA (Dynamics-Aerosol-Chemistry-Cloud Interactions in West Africa). DACCIWA aims to investigate the impact of the drastic increase in anthropogenic emissions in West Africa on the local weather and climate, for example through cloud-aerosol interactions or impacts on radiation and stability. DACCIWA organised a major international field campaign in West Africa in June-July 2016 and involves a wide range of modelling activities. Several studies have shown - and first results of the DACCIWA campaign confirm - that extensive ultra-low stratus clouds form in the southern parts of West Africa (8°W-8°E, 5-10°N) at night in connection with strong nocturnal low-level jets. The clouds persist long after sunrise and have therefore a substantial impact on the surface radiation budget and consequently on the diurnal evolution of the daytime, convectively mixed boundary layer. The objective of this study is to investigate the sensitivity of the West African monsoon system and its diurnal cycle to the radiative effects of these low clouds. The study is based on a series of daily 5-day sensitivity simulations using ICON, the operational numerical weather prediction model of the German Weather Service during the months July - September 2006. In these simulations, low clouds are made transparent, by artificially lowering the optical thickness information passed on to the model's radiation scheme. Results reveal a noticeable influence of the low-level cloud cover on the atmospheric mean state of our region of interest and beyond. Also the diurnal development of the convective boundary layer is influenced by the cloud modification. In the transparent-cloud experiments, the cloud deck tends to break up later in the day and is shifted to a higher altitude, thereby causing a short-lived intensification around 11 LT. The average rainfall patterns are modified as well, though no conclusion on the long-term impact on rainfall can be made due to the forced initial conditions in the presented experiment. In the future, the impact on the development of the West African monsoon system will be assessed.

Cloud cover estimation: Use of GOES imagery in development of cloud cover data base for insolation assessment

NASA Technical Reports Server (NTRS)

Huning, J. R.; Logan, T. L.; Smith, J. H.

1982-01-01

The potential of using digital satellite data to establish a cloud cover data base for the United States, one that would provide detailed information on the temporal and spatial variability of cloud development are studied. Key elements include: (1) interfacing GOES data from the University of Wisconsin Meteorological Data Facility with the Jet Propulsion Laboratory's VICAR image processing system and IBIS geographic information system; (2) creation of a registered multitemporal GOES data base; (3) development of a simple normalization model to compensate for sun angle; (4) creation of a variable size georeference grid that provides detailed cloud information in selected areas and summarized information in other areas; and (5) development of a cloud/shadow model which details the percentage of each grid cell that is cloud and shadow covered, and the percentage of cloud or shadow opacity. In addition, comparison of model calculations of insolation with measured values at selected test sites was accomplished, as well as development of preliminary requirements for a large scale data base of cloud cover statistics.

Changes in Andes snow cover from MODIS data, 2000-2016

NASA Astrophysics Data System (ADS)

Saavedra, Freddy A.; Kampf, Stephanie K.; Fassnacht, Steven R.; Sibold, Jason S.

2018-03-01

The Andes span a length of 7000 km and are important for sustaining regional water supplies. Snow variability across this region has not been studied in detail due to sparse and unevenly distributed instrumental climate data. We calculated snow persistence (SP) as the fraction of time with snow cover for each year between 2000 and 2016 from Moderate Resolution Imaging Spectroradiometer (MODIS) satellite sensors (500 m, 8-day maximum snow cover extent). This analysis is conducted between 8 and 36° S due to high frequency of cloud (> 30 % of the time) south and north of this range. We ran Mann-Kendall and Theil-Sens analyses to identify areas with significant changes in SP and snowline (the line at lower elevation where SP = 20 %). We evaluated how these trends relate to temperature and precipitation from Modern-Era Retrospective Analysis for Research and Applications-2 (MERRA2) and University of Delaware datasets and climate indices as El Niño-Southern Oscillation (ENSO), Southern Annular Mode (SAM), and Pacific Decadal Oscillation (PDO). Areas north of 29° S have limited snow cover, and few trends in snow persistence were detected. A large area (34 370 km2) with persistent snow cover between 29 and 36° S experienced a significant loss of snow cover (2-5 fewer days of snow year-1). Snow loss was more pronounced (62 % of the area with significant trends) on the east side of the Andes. We also found a significant increase in the elevation of the snowline at 10-30 m year-1 south of 29-30° S. Decreasing SP correlates with decreasing precipitation and increasing temperature, and the magnitudes of these correlations vary with latitude and elevation. ENSO climate indices better predicted SP conditions north of 31° S, whereas the SAM better predicted SP south of 31° S.

Historical reconstruction of climatic and elevation preferences and the evolution of cloud forest-adapted tree ferns in Mesoamerica.

PubMed

Sosa, Victoria; Ornelas, Juan Francisco; Ramírez-Barahona, Santiago; Gándara, Etelvina

2016-01-01

Cloud forests, characterized by a persistent, frequent or seasonal low-level cloud cover and fragmented distribution, are one of the most threatened habitats, especially in the Neotropics. Tree ferns are among the most conspicuous elements in these forests, and ferns are restricted to regions in which minimum temperatures rarely drop below freezing and rainfall is high and evenly distributed around the year. Current phylogeographic data suggest that some of the cloud forest-adapted species remained in situ or expanded to the lowlands during glacial cycles and contracted allopatrically during the interglacials. Although the observed genetic signals of population size changes of cloud forest-adapted species including tree ferns correspond to predicted changes by Pleistocene climate change dynamics, the observed patterns of intraspecific lineage divergence showed temporal incongruence. Here we combined phylogenetic analyses, ancestral area reconstruction, and divergence time estimates with climatic and altitudinal data (environmental space) for phenotypic traits of tree fern species to make inferences about evolutionary processes in deep time. We used phylogenetic Bayesian inference and geographic and altitudinal distribution of tree ferns to investigate ancestral area and elevation and environmental preferences of Mesoamerican tree ferns. The phylogeny was then used to estimate divergence times and ask whether the ancestral area and elevation and environmental shifts were linked to climatic events and historical climatic preferences. Bayesian trees retrieved Cyathea, Alsophyla, Gymnosphaera and Sphaeropteris in monophyletic clades. Splits for species in these genera found in Mesoamerican cloud forests are recent, from the Neogene to the Quaternary, Australia was identified as the ancestral area for the clades of these genera, except for Gymnosphaera that was Mesoamerica. Climate tolerance was not divergent from hypothesized ancestors for the most significant variables or elevation. For elevational shifts, we found repeated change from low to high elevations. Our data suggest that representatives of Cyatheaceae main lineages migrated from Australia to Mesoamerican cloud forests in different times and have persisted in these environmentally unstable areas but extant species diverged recentrly from their ancestors.

Historical reconstruction of climatic and elevation preferences and the evolution of cloud forest-adapted tree ferns in Mesoamerica

PubMed Central

2016-01-01

Background Cloud forests, characterized by a persistent, frequent or seasonal low-level cloud cover and fragmented distribution, are one of the most threatened habitats, especially in the Neotropics. Tree ferns are among the most conspicuous elements in these forests, and ferns are restricted to regions in which minimum temperatures rarely drop below freezing and rainfall is high and evenly distributed around the year. Current phylogeographic data suggest that some of the cloud forest-adapted species remained in situ or expanded to the lowlands during glacial cycles and contracted allopatrically during the interglacials. Although the observed genetic signals of population size changes of cloud forest-adapted species including tree ferns correspond to predicted changes by Pleistocene climate change dynamics, the observed patterns of intraspecific lineage divergence showed temporal incongruence. Methods Here we combined phylogenetic analyses, ancestral area reconstruction, and divergence time estimates with climatic and altitudinal data (environmental space) for phenotypic traits of tree fern species to make inferences about evolutionary processes in deep time. We used phylogenetic Bayesian inference and geographic and altitudinal distribution of tree ferns to investigate ancestral area and elevation and environmental preferences of Mesoamerican tree ferns. The phylogeny was then used to estimate divergence times and ask whether the ancestral area and elevation and environmental shifts were linked to climatic events and historical climatic preferences. Results Bayesian trees retrieved Cyathea, Alsophyla, Gymnosphaera and Sphaeropteris in monophyletic clades. Splits for species in these genera found in Mesoamerican cloud forests are recent, from the Neogene to the Quaternary, Australia was identified as the ancestral area for the clades of these genera, except for Gymnosphaera that was Mesoamerica. Climate tolerance was not divergent from hypothesized ancestors for the most significant variables or elevation. For elevational shifts, we found repeated change from low to high elevations. Conclusions Our data suggest that representatives of Cyatheaceae main lineages migrated from Australia to Mesoamerican cloud forests in different times and have persisted in these environmentally unstable areas but extant species diverged recentrly from their ancestors. PMID:27896030

Smoke and Pollution Aerosol Effect on Cloud Cover

NASA Technical Reports Server (NTRS)

Kaufman, Yoram J.; Koren, Ilan

2006-01-01

Pollution and smoke aerosols can increase or decrease the cloud cover. This duality in the effects of aerosols forms one of the largest uncertainties in climate research. Using solar measurements from Aerosol Robotic Network sites around the globe, we show an increase in cloud cover with an increase in the aerosol column concentration and an inverse dependence on the aerosol absorption of sunlight. The emerging rule appears to be independent of geographical location or aerosol type, thus increasing our confidence in the understanding of these aerosol effects on the clouds and climate. Preliminary estimates suggest an increase of 5% in cloud cover.

Representing the Seasonal Variation of Marine Stratus and Stratocumulus near the Western Coast of Continents

NASA Astrophysics Data System (ADS)

He, Y.; Dickinson, R.

2005-12-01

The seasonal variation of marine stratus and stratocumulus (MSC) plays a significant role in ocean- atmosphere-land interaction during the seasonal transition of basic climate in the Eastern Pacific. A key factor in parameterization of MSC cloud cover is atmospheric stability. In this study, we examine the importance of lower troposphere stability for Marine Stratus and Stratocumulus (MSC) cloud cover variations over subtropical oceans on monthly and seasonal timescales. Our approach is to consider a two-layer conceptual model with moist denser boundary layer air topped by dry lighter free air beneath a trade wind inversion at around 700 mb.The vertical integrated dry static energy is of central importance in the lower troposphere. The variation of dry static energy transport and latent heat release leads to the variation of cloud top radiative forcing, which is a function of low cloud cover. A diagnostic cloud cover scheme derived from the model is a nonlinear function of lower troposphere stability and large-scale subsidence. Use ERA-40 and ISCCP-FD data as input, the scheme reproduces well the seasonal variation of low cloud cover in four MSC regions near the western coast of continents. NCAR CAM linear empirical cloud cover scheme could explain 16% of the observed ISCCP monthly covariance in the southeast subtropical Pacific during 1990 to 2000 period; while the new cloud cover scheme could explain 50% of the total covariance. When implementing new scheme into NCAR CAM3.1, it is found that the seasonal phase of MSC is better simulated near the Peruvian region, but the seasonal amplitudes of MSC cloud cover in four MSC regions using both schemes have systematic problems. Possible causes for model cloud biases are investigated through numerical experiments. The importance of MSC cloud cover in the eastern Pacific on local mean climate is also discussed.

Diurnal cycle and seasonal variation of cloud cover over the Tibetan Plateau as determined from Himawari-8 new-generation geostationary satellite data.

PubMed

Shang, Huazhe; Letu, Husi; Nakajima, Takashi Y; Wang, Ziming; Ma, Run; Wang, Tianxing; Lei, Yonghui; Ji, Dabin; Li, Shenshen; Shi, Jiancheng

2018-01-18

Analysis of cloud cover and its diurnal variation over the Tibetan Plateau (TP) is highly reliant on satellite data; however, the accuracy of cloud detection from both polar-orbiting and geostationary satellites over this area remains unclear. The new-generation geostationary Himawari-8 satellites provide high-resolution spatial and temporal information about clouds over the Tibetan Plateau. In this study, the cloud detection of MODIS and AHI is investigated and validated against CALIPSO measurements. For AHI and MODIS, the false alarm rate of AHI and MODIS in cloud identification over the TP was 7.51% and 1.94%, respectively, and the cloud hit rate was 73.55% and 80.15%, respectively. Using hourly cloud-cover data from the Himawari-8 satellites, we found that at the monthly scale, the diurnal cycle in cloud cover over the TP tends to increase throughout the day, with the minimum and maximum cloud fractions occurring at 10:00 a.m. and 18:00 p.m. local time. Due to the limited time resolution of polar-orbiting satellites, the underestimation of MODIS daytime average cloud cover is approximately 4.00% at the annual scale, with larger biases during the spring (5.40%) and winter (5.90%).

Do Clouds Save the Great Barrier Reef? Satellite Imagery Elucidates the Cloud-SST Relationship at the Local Scale

PubMed Central

Leahy, Susannah M.; Kingsford, Michael J.; Steinberg, Craig R.

2013-01-01

Evidence of global climate change and rising sea surface temperatures (SSTs) is now well documented in the scientific literature. With corals already living close to their thermal maxima, increases in SSTs are of great concern for the survival of coral reefs. Cloud feedback processes may have the potential to constrain SSTs, serving to enforce an “ocean thermostat” and promoting the survival of coral reefs. In this study, it was hypothesized that cloud cover can affect summer SSTs in the tropics. Detailed direct and lagged relationships between cloud cover and SST across the central Great Barrier Reef (GBR) shelf were investigated using data from satellite imagery and in situ temperature and light loggers during two relatively hot summers (2005 and 2006) and two relatively cool summers (2007 and 2008). Across all study summers and shelf positions, SSTs exhibited distinct drops during periods of high cloud cover, and conversely, SST increases during periods of low cloud cover, with a three-day temporal lag between a change in cloud cover and a subsequent change in SST. Cloud cover alone was responsible for up to 32.1% of the variation in SSTs three days later. The relationship was strongest in both El Niño (2005) and La Niña (2008) study summers and at the inner-shelf position in those summers. SST effects on subsequent cloud cover were weaker and more variable among study summers, with rising SSTs explaining up to 21.6% of the increase in cloud cover three days later. This work quantifies the often observed cloud cooling effect on coral reefs. It highlights the importance of incorporating local-scale processes into bleaching forecasting models, and encourages the use of remote sensing imagery to value-add to coral bleaching field studies and to more accurately predict risks to coral reefs. PMID:23894649

Predicting the temporal and spatial probability of orographic cloud cover in the Luquillo Experimental Forest in Puerto Rico using generalized linear (mixed) models.

Treesearch

Wei Wu; Charlesb Hall; Lianjun Zhang

2006-01-01

We predicted the spatial pattern of hourly probability of cloud cover in the Luquillo Experimental Forest (LEF) in North-Eastern Puerto Rico using four different models. The probability of cloud cover (defined as “the percentage of the area covered by clouds in each pixel on the map” in this paper) at any hour and any place is a function of three topographic variables...

Global surface-based cloud observation for ISCCP

NASA Technical Reports Server (NTRS)

1994-01-01

Visual observations of cloud cover are hindered at night due to inadequate illumination of the clouds. This usually leads to an underestimation of the average cloud cover at night, especially for the amounts of middle and high clouds, in climatologies on surface observations. The diurnal cycles of cloud amounts, if based on all the surface observations, are therefore in error, but they can be obtained more accurately if the nighttime observations are screened to select those made under sufficient moonlight. Ten years of nighttime weather observations from the northern hemisphere in December were classified according to the illuminance of moonlight or twilight on the cloud tops, and a threshold level of illuminance was determined, above which the clouds are apparently detected adequately. This threshold corresponds to light from a full moon at an elevation angle of 6 degrees or from a partial moon at higher elevation, or twilight from the sun less than 9 degrees below the horizon. It permits the use of about 38% of the observations made with the sun below the horizon. The computed diurnal cycles of total cloud cover are altered considerably when this moonlight criterion is imposed. Maximum cloud cover over much of the ocean is now found to be at night or in the morning, whereas computations obtained without benefit of the moonlight criterion, as in our published atlases, showed the time of maximum to be noon or early afternoon in many regions. Cloud cover is greater at night than during the day over the open oceans far from the continents, particularly in summer. However, near noon maxima are still evident in the coastal regions, so that the global annual average oceanic cloud cover is still slightly greater during the day than at night, by 0.3%. Over land, where daytime maxima are still obtained but with reduced amplitude, average cloud cover is 3.3% greater during the daytime. The diurnal cycles of total cloud cover we obtain are compared with those of ISCCP for a few regions; they are generally in better agreement if the moonlight criterion is imposed on the surface observations. Using the moonlight criterion, we have analyzed ten years (1982-1991) of surface weather observations over land and ocean, worldwide, for total cloud cover and for the frequency of occurrence of clear sky, fog and precipitation The global average cloud cover (average of day and night) is about 2% higher if we impose the moonlight criterion than if we use all observations. The difference is greater in winter than in summer, because of the fewer hours of darkness in the summer. The amplitude of the annual cycle of total cloud cover over the Arctic Ocean and at the South Pole is diminished by a few percent when the moonlight criterion is imposed. The average cloud cover for 1982-1991 is found to be 55% for northern hemisphere land, 53% for southern hemisphere land, 66% for northern hemisphere ocean, and 70% for southern hemisphere ocean, giving a global average of 64%. The global average for daytime is 64.6% for nighttime 63.3%.

Clouds and the Near-Earth Environment: Possible Links

NASA Astrophysics Data System (ADS)

Condurache-Bota, Simona; Voiculescu, Mirela; Dragomir, Carmelia

2015-12-01

Climate variability is a hot topic not only for scientists and policy-makers, but also for each and every one of us. The anthropogenic activities are considered to be responsible for most climate change, however there are large uncertainties about the magnitude of effects of solar variability and other extraterrestrial influences, such as galactic cosmic rays on terrestrial climate. Clouds play an important role due to feedbacks of the radiation budget: variation of cloud cover/composition affects climate, which, in turn, affects cloud cover via atmospheric dynamics and sea temperature variations. Cloud formation and evolution are still under scientific scrutiny, since their microphysics is still not understood. Besides atmospheric dynamics and other internal climatic parameters, extraterrestrial sources of cloud cover variation are considered. One of these is the solar wind, whose effect on cloud cover might be modulated by the global atmospheric electrical circuit. Clouds height and composition, their seasonal variation and latitudinal distribution should be considered when trying to identify possible mechanisms by which solar energy is transferred to clouds. The influence of the solar wind on cloud formation can be assessed also through the ap index - the geomagnetic storm index, which can be readily connected with interplanetary magnetic field, IMF structure. This paper proposes to assess the possible relationship between both cloud cover and solar wind proxies, as the ap index, function of cloud height and composition and also through seasonal studies. The data covers almost three solar cycles (1984-2009). Mechanisms are looked for by investigating observed trends or correlation at local/seasonal scale

Cloud Cover Increase with Increasing Aerosol Absorptivity: A Counterexample to the Conventional Semidirect Aerosol Effect

NASA Technical Reports Server (NTRS)

Perlwitz, Jan; Miller, Ron L.

2010-01-01

We reexamine the aerosol semidirect effect using a general circulation model and four cases of the single-scattering albedo of dust aerosols. Contrary to the expected decrease in low cloud cover due to heating by tropospheric aerosols, we find a significant increase with increasing absorptivity of soil dust particles in regions with high dust load, except during Northern Hemisphere winter. The strongest sensitivity of cloud cover to dust absorption is found over land during Northern Hemisphere summer. Here even medium and high cloud cover increase where the dust load is highest. The cloud cover change is directly linked to the change in relative humidity in the troposphere as a result of contrasting changes in specific humidity and temperature. More absorption by aerosols leads to larger diabatic heating and increased warming of the column, decreasing relative humidity. However, a corresponding increase in the specific humidity exceeds the temperature effect on relative humidity. The net effect is more low cloud cover with increasing aerosol absorption. The higher specific humidity where cloud cover strongly increases is attributed to an enhanced convergence of moisture driven by dust radiative heating. Although in some areas our model exhibits a reduction of low cloud cover due to aerosol heating consistent with the conventional description of the semidirect effect, we conclude that the link between aerosols and clouds is more varied, depending also on changes in the atmospheric circulation and the specific humidity induced by the aerosols. Other absorbing aerosols such as black carbon are expected to have a similar effect.

Isolating the Liquid Cloud Response to Recent Arctic Sea Ice Variability Using Spaceborne Lidar Observations

NASA Astrophysics Data System (ADS)

Morrison, A. L.; Kay, J. E.; Chepfer, H.; Guzman, R.; Yettella, V.

2018-01-01

While the radiative influence of clouds on Arctic sea ice is known, the influence of sea ice cover on Arctic clouds is challenging to detect, separate from atmospheric circulation, and attribute to human activities. Providing observational constraints on the two-way relationship between sea ice cover and Arctic clouds is important for predicting the rate of future sea ice loss. Here we use 8 years of CALIPSO (Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations) spaceborne lidar observations from 2008 to 2015 to analyze Arctic cloud profiles over sea ice and over open water. Using a novel surface mask to restrict our analysis to where sea ice concentration varies, we isolate the influence of sea ice cover on Arctic Ocean clouds. The study focuses on clouds containing liquid water because liquid-containing clouds are the most important cloud type for radiative fluxes and therefore for sea ice melt and growth. Summer is the only season with no observed cloud response to sea ice cover variability: liquid cloud profiles are nearly identical over sea ice and over open water. These results suggest that shortwave summer cloud feedbacks do not slow long-term summer sea ice loss. In contrast, more liquid clouds are observed over open water than over sea ice in the winter, spring, and fall in the 8 year mean and in each individual year. Observed fall sea ice loss cannot be explained by natural variability alone, which suggests that observed increases in fall Arctic cloud cover over newly open water are linked to human activities.

A new NASA/MSFC mission analysis global cloud cover data base

NASA Technical Reports Server (NTRS)

Brown, S. C.; Jeffries, W. R., III

1985-01-01

A global cloud cover data set, derived from the USAF 3D NEPH Analysis, was developed for use in climate studies and for Earth viewing applications. This data set contains a single parameter - total sky cover - separated in time by 3 or 6 hr intervals and in space by approximately 50 n.mi. Cloud cover amount is recorded for each grid point (of a square grid) by a single alphanumeric character representing each 5 percent increment of sky cover. The data are arranged in both quarterly and monthly formats. The data base currently provides daily, 3-hr observed total sky cover for the Northern Hemisphere from 1972 through 1977 less 1976. For the Southern Hemisphere, there are data at 6-hr intervals for 1976 through 1978 and at 3-hr intervals for 1979 and 1980. More years of data are being added. To validate the data base, the percent frequency of or = 0.3 and or = 0.8 cloud cover was compared with ground observed cloud amounts at several locations with generally good agreement. Mean or other desired cloud amounts can be calculated for any time period and any size area from a single grid point to a hemisphere. The data base is especially useful in evaluating the consequence of cloud cover on Earth viewing space missions. The temporal and spatial frequency of the data allow simulations that closely approximate any projected viewing mission. No adjustments are required to account for cloud continuity.

Intra-annual variability of cloud cover over the Mediterranean region based on NCEP/NCAR, MODIS and ECAD data sets

NASA Astrophysics Data System (ADS)

Ioannidis, Eleftherios; Lolis, Christos J.; Papadimas, Christos D.; Hatzianastassiou, Nikolaos; Bartzokas, Aristides

2017-04-01

The seasonal variability of total cloud cover in the Mediterranean region is examined for the period 1948-2014 using a multivariate statistical methodology. The data used consist of: i) daily gridded (1.875°x1.905°) values of total cloud cover over the broader Mediterranean region for the 66-year period 1948-2014, obtained from NCEP/NCAR Reanalysis data set, ii) daily gridded (1°x1°) values of total cloud cover for the period 2003-2014 obtained from the Moderate resolution Imaging Spectroradiometer (MODIS) satellite data set and iii) daily station cloud cover data for the period 2003-2014 obtained from the European Climate Assessment & Dataset (ECA&D). At first, the multivariate statistical method of Factor Analysis (S-mode) with varimax rotation is applied as a dimensionality reduction tool on the mean day to day intra-annual variation of NCEP/NCAR cloud cover for the period 1948-2014. According to the results, three main modes of intra-annual variation of cloud cover are found. The first mode is characterized by a winter maximum and a summer minimum and prevails mainly over the sea; a weak see-saw teleconnection over the Alps represents the opposite intra-annual marching. The second mode presents maxima in early autumn and late spring, and minima in late summer and winter, and prevails over the SW Europe and NW Africa inland regions. The third mode shows a maximum in June and a minimum in October and prevails over the eastern part of central Europe. Next, the mean day to day intra-annual variation of NCEP/NCAR cloud cover over the core regions of the above factors is calculated for the entire period 1948-2014 and the three 22-year sub-periods 1948-70, 1970-92 and 1992-2014. A comparison is carried out between each of the three sub-periods and the total period in order to reveal possible long-term changes in seasonal march of total cloud cover. The results show that cloud cover was reduced above all regions during the last 22-year sub-period 1992-2014 throughout the year, but especially in winter. Finally, given the different nature of the utilized NCEP/NCAR (Reanalysis), MODIS (satellite) and ECAD (stations) cloud cover data sets, an inter-comparison is made among them as it concerns the intra-annual variation of cloud cover for the common period 2003-2014. The results show a nice similarity among the three datasets, with some differences in magnitude during the cold period of the year.

Reassessing the possibility of life on venus: proposal for an astrobiology mission.

PubMed

Schulze-Makuch, Dirk; Irwin, Louis N

2002-01-01

With their similar size, chemical composition, and distance from the Sun, Venus and Earth may have shared a similar early history. Though surface conditions on Venus are now too extreme for life as we know it, it likely had abundant water and favorable conditions for life when the Sun was fainter early in the Solar System. Given the persistence of life under stabilizing selection in static environments, it is possible that life could exist in restricted environmental niches, where it may have retreated after conditions on the surface became untenable. High-pressure subsurface habitats with water in the supercritical liquid state could be a potential refugium, as could be the zone of dense cloud cover where thermoacidophilic life might have retreated. Technology based on the Stardust Mission to collect comet particles could readily be adapted for a pass through the appropriate cloud layer for sample collection and return to Earth.

Reassessing the Possibility of Life on Venus: Proposal for an Astrobiology Mission

NASA Astrophysics Data System (ADS)

Schulze-Makuch, Dirk; Irwin, Louis N.

2002-06-01

With their similar size, chemical composition, and distance from the Sun, Venus and Earth may have shared a similar early history. Though surface conditions on Venus are now too extreme for life as we know it, it likely had abundant water and favorable conditions for life when the Sun was fainter early in the Solar System. Given the persistence of life under stabilizing selection in static environments, it is possible that life could exist in restricted environmental niches, where it may have retreated after conditions on the surface became untenable. High-pressure subsurface habitats with water in the supercritical liquid state could be a potential refugium, as could be the zone of dense cloud cover where thermoacidophilic life might have retreated. Technology based on the Stardust Mission to collect comet particles could readily be adapted for a pass through the appropriate cloud layer for sample collection and return to Earth.

The Importance of Habit Evolution for Maintaining Supercooled Liquid in Arctic Clouds

NASA Astrophysics Data System (ADS)

Sulia, K. J.; Harrington, J. Y.

2010-12-01

Low-level clouds cover large sections of the Arctic for much of the year, and these clouds are generally composed of supercooled liquid and contain regions of ice. These supercooled liquid clouds can persist for long periods of time with a large spatial extent. What are not well understood are the mechanisms whereby these clouds are able to maintain a supercooled liquid state rather than dissipating through the Bergeron mechanism, or the process by which ice crystals grow at the expense of liquid drops, with ice precipitation leading to cloud dissipation. Most prior research has focused on ice nucleation as providing a critical, first-order control on the glaciation rates of supercooled Arctic clouds. Ice nucleation is critical for its control over ice concentration, which then feeds into liquid depletion through its influence on the total ice mass growth rates. In addition, ice particle habit evolution can also strongly affect ice mass; however, the vapor growth rates based on habit evolution are routinely ignored in most mixed-phase methods. Most prior studies assume simple shapes or spheres as a proxy for ice habits. Recent studies have suggested that these simplified methods produce large uncertainties in estimates of the vapor growth rates, and hence the rate of glaciation, in supercooled clouds. Our studies show that these uncertainties are due to the inability of most models to predict ice particle aspect ratio. We therefore present results that help clarify the influence of ice habit on glaciation. We show that habit prediction is critical for estimates of glaciation in supercooled clouds, and that this is most important when ice concentrations are relatively low, as they appear to be in the Arctic.

Cloud shading and fog drip influence the metabolism of a coastal pine ecosystem.

PubMed

Carbone, Mariah S; Park Williams, A; Ambrose, Anthony R; Boot, Claudia M; Bradley, Eliza S; Dawson, Todd E; Schaeffer, Sean M; Schimel, Joshua P; Still, Christopher J

2013-02-01

Assessing the ecological importance of clouds has substantial implications for our basic understanding of ecosystems and for predicting how they will respond to a changing climate. This study was conducted in a coastal Bishop pine forest ecosystem that experiences regular cycles of stratus cloud cover and inundation in summer. Our objective was to understand how these clouds impact ecosystem metabolism by contrasting two sites along a gradient of summer stratus cover. The site that was under cloud cover ~15% more of the summer daytime hours had lower air temperatures and evaporation rates, higher soil moisture content, and received more frequent fog drip inputs than the site with less cloud cover. These cloud-driven differences in environmental conditions translated into large differences in plant and microbial activity. Pine trees at the site with greater cloud cover exhibited less water stress in summer, larger basal area growth, and greater rates of sap velocity. The difference in basal area growth between the two sites was largely due to summer growth. Microbial metabolism was highly responsive to fog drip, illustrated by an observed ~3-fold increase in microbial biomass C with increasing summer fog drip. In addition, the site with more cloud cover had greater total soil respiration and a larger fractional contribution from heterotrophic sources. We conclude that clouds are important to the ecological functioning of these coastal forests, providing summer shading and cooling that relieve pine and microbial drought stress as well as regular moisture inputs that elevate plant and microbial metabolism. These findings are important for understanding how these and other seasonally dry coastal ecosystems will respond to predicted changes in stratus cover, rainfall, and temperature. © 2012 Blackwell Publishing Ltd.

Cloud cover analysis associated to cut-off low-pressure systems over Europe using Meteosat Imagery

NASA Astrophysics Data System (ADS)

Delgado, G.; Redaño, A.; Lorente, J.; Nieto, R.; Gimeno, L.; Ribera, P.; Barriopedro, D.; García-Herrera, R.; Serrano, A.

2007-04-01

This paper reports a cloud cover analysis of cut-off low pressure systems (COL) using a pattern recognition method applied to IR and VIS bispectral histograms. 35 COL occurrences were studied over five years (1994-1998). Five cloud types were identified in COLs, of which high clouds (HCC) and deep convective clouds (DCC) were found to be the most relevant to characterize COL systems, though not the most numerous. Cloud cover in a COL is highly dependent on its stage of development, but a higher percentage of cloud cover is always present in the frontal zone, attributable due to higher amounts of high and deep convective clouds. These general characteristics are most marked during the first stage (when the amplitude of the geopotencial wave increases) and second stage (characterized by the development of a cold upper level low), closed cyclonic circulation minimizing differences between rearward and frontal zones during the third stage. The probability of heavy rains during this stage decreases considerably. The centres of mass of high and deep convective clouds move towards the COL-axis centre during COL evolution.

Temporal Changes in the Observed Relationship between Cloud Cover and Surface Air Temperature.

NASA Astrophysics Data System (ADS)

Sun, Bomin; Groisman, Pavel Ya.; Bradley, Raymond S.; Keimig, Frank T.

2000-12-01

The relationship between cloud cover and near-surface air temperature and its decadal changes are examined using the hourly synoptic data for the past four to six decades from five regions of the Northern Hemisphere: Canada, the United States, the former Soviet Union, China, and tropical islands of the western Pacific. The authors define the normalized cloud cover-surface air temperature relationship, NOCET or dT/dCL, as a temperature anomaly with a unit (one-tenth) deviation of total cloud cover from its average value. Then mean monthly NOCET time series (night- and daytime, separately) are area-averaged and parameterized as functions of surface air humidity and snow cover. The day- and nighttime NOCET variations are strongly anticorrelated with changes in surface humidity. Furthermore, the daytime NOCET changes are positively correlated to changes in snow cover extent. The regionally averaged nighttime NOCET varies from 0.05 K tenth1 in the wet Tropics to 1.0 K tenth1 at midlatitudes in winter. The daytime regional NOCET ranges from 0.4 K tenth1 in the Tropics to 0.7 K tenth1 at midlatitudes in winter.The authors found a general strengthening of a daytime surface cooling during the post-World War II period associated with cloud cover over the United States and China, but a minor reduction of this cooling in higher latitudes. Furthermore, since the 1970s, a prominent increase in atmospheric humidity has significantly weakened the effectiveness of the surface warming (best seen at nighttime) associated with cloud cover.The authors apportion the spatiotemporal field of interactions between total cloud cover and surface air temperature into a bivariate relationship (described by two equations, one for daytime and one for nighttime) with surface air humidity and snow cover and two constant factors. These factors are invariant in space and time domains. It is speculated that they may represent empirical estimates of the overall cloud cover effect on the surface air temperature.

Discrete post-processing of total cloud cover ensemble forecasts

NASA Astrophysics Data System (ADS)

Hemri, Stephan; Haiden, Thomas; Pappenberger, Florian

2017-04-01

This contribution presents an approach to post-process ensemble forecasts for the discrete and bounded weather variable of total cloud cover. Two methods for discrete statistical post-processing of ensemble predictions are tested. The first approach is based on multinomial logistic regression, the second involves a proportional odds logistic regression model. Applying them to total cloud cover raw ensemble forecasts from the European Centre for Medium-Range Weather Forecasts improves forecast skill significantly. Based on station-wise post-processing of raw ensemble total cloud cover forecasts for a global set of 3330 stations over the period from 2007 to early 2014, the more parsimonious proportional odds logistic regression model proved to slightly outperform the multinomial logistic regression model. Reference Hemri, S., Haiden, T., & Pappenberger, F. (2016). Discrete post-processing of total cloud cover ensemble forecasts. Monthly Weather Review 144, 2565-2577.

Clouds at CTIO and the Dark Energy Survey

DOE Office of Scientific and Technical Information (OSTI.GOV)

Neilsen, Jr., Eric

An understanding of the weather patters at Cerro-Tololo Inter-American (CTIO) Observatory, the observing site for the Dark Energy Survey (DES), is important for assessing the efciency of DES operations in using observing time and for planning future operations. CTIO has maintained records of cloud-cover by quarters of nights since 1975. A comparison between these cloud records in the 2013-2014 DES observing season (DES year 1) and achieved observing efciency and exposure quality allows the DES collaboration to make better use of the historical records in survey planning. Plots and tables here relate human recorded cloud-cover to collection of good DESmore » data, show the variation of typical cloud-cover by month, and evaluate the relationship between the El Niño weather pattern and cloud-cover at CTIO.« less

Cloud cover and solar disk state estimation using all-sky images: deep neural networks approach compared to routine methods

NASA Astrophysics Data System (ADS)

Krinitskiy, Mikhail; Sinitsyn, Alexey

2017-04-01

Shortwave radiation is an important component of surface heat budget over sea and land. To estimate them accurate observations of cloud conditions are needed including total cloud cover, spatial and temporal cloud structure. While massively observed visually, for building accurate SW radiation parameterizations cloud structure needs also to be quantified using precise instrumental measurements. While there already exist several state of the art land-based cloud-cameras that satisfy researchers needs, their major disadvantages are associated with inaccuracy of all-sky images processing algorithms which typically result in the uncertainties of 2-4 octa of cloud cover estimates with the resulting true-scoring cloud cover accuracy of about 7%. Moreover, none of these algorithms determine cloud types. We developed an approach for cloud cover and structure estimating, which provides much more accurate estimates and also allows for measuring additional characteristics. This method is based on the synthetic controlling index, namely the "grayness rate index", that we introduced in 2014. Since then this index has already demonstrated high efficiency being used along with the technique namely the "background sunburn effect suppression", to detect thin clouds. This made it possible to significantly increase the accuracy of total cloud cover estimation in various sky image states using this extension of routine algorithm type. Errors for the cloud cover estimates significantly decreased down resulting the mean squared error of about 1.5 octa. Resulting true-scoring accuracy is more than 38%. The main source of this approach uncertainties is the solar disk state determination errors. While the deep neural networks approach lets us to estimate solar disk state with 94% accuracy, the final result of total cloud estimation still isn`t satisfying. To solve this problem completely we applied the set of machine learning algorithms to the problem of total cloud cover estimation directly. The accuracy of this approach varies depending on algorithm choice. Deep neural networks demonstrated the best accuracy of more than 96%. We will demonstrate some approaches and the most influential statistical features of all-sky images that lets the algorithm reach that high accuracy. With the use of our new optical package a set of over 480`000 samples has been collected in several sea missions in 2014-2016 along with concurrent standard human observed and instrumentally recorded meteorological parameters. We will demonstrate the results of the field measurements and will discuss some still remaining problems and the potential of the further developments of machine learning approach.

Shuttle landing facility cloud cover study: Climatological analysis and two tenths cloud cover rule evaluation

NASA Technical Reports Server (NTRS)

Atchison, Michael K.; Schumann, Robin; Taylor, Greg; Warburton, John; Wheeler, Mark; Yersavich, Ann

1993-01-01

The two-tenths cloud cover rule in effect for all End Of Mission (EOM) STS landings at the Kennedy Space Center (KSC) states: 'for scattered cloud layers below 10,000 feet, cloud cover must be observed to be less than or equal to 0.2 at the de-orbit burn go/no-go decision time (approximately 90 minutes before landing time)'. This rule was designed to protect against a ceiling (below 10,000 feet) developing unexpectedly within the next 90 minutes (i.e., after the de-orbit burn decision and before landing). The Applied Meteorological Unit (AMU) developed and analyzed a database of cloud cover amounts and weather conditions at the Shuttle Landing Facility for a five-year (1986-1990) period. The data indicate the best time to land the shuttle at KSC is during the summer while the worst time is during the winter. The analysis also shows the highest frequency of landing opportunities occurs for the 0100-0600 UTC and 1300-1600 UTC time periods. The worst time of the day to land a shuttle is near sunrise and during the afternoon. An evaluation of the two-tenths cloud cover rule for most data categorizations has shown that there is a significant difference in the proportions of weather violations one and two hours subsequent to initial conditions of 0.2 and 0.3 cloud cover. However, for May, Oct., 700 mb northerly wind category, 1500 UTC category, and 1600 UTC category there is some evidence that the 0.2 cloud cover rule may be overly conservative. This possibility requires further investigation. As a result of these analyses, the AMU developed nomograms to help the Spaceflight Meteorological Group (SMG) and the Cape Canaveral Forecast Facility (CCFF) forecast cloud cover for EOM and Return to Launch Site (RTLS) at KSC. Future work will include updating the two tenths database, further analysis of the data for several categorizations, and developing a proof of concept artificial neural network to provide forecast guidance of weather constraint violations for shuttle landings.

350 Year Cloud Reconstruction Deduced from Northeast Caribbean Coral Proxies

NASA Astrophysics Data System (ADS)

Winter, A.; Sammarco, P. W.; Mikolajewicz, U.; Jury, M.; Zanchettin, D.

2014-12-01

Clouds are a major factor influencing the global climate and its response to external forcing through their implications for the global hydrological cycle, and hence for the planetary radiative budget. Clouds also contribute to regional climates and their variability through, e.g., the changes they induce in regional precipitation patterns. There have been very few studies of decadal and longer-term changes in cloud cover in the tropics and sub-tropics, both over land and the ocean. In the tropics, there is great uncertainty regarding how global warming will affect cloud cover. Observational satellite data are too short to unambiguously discern any temporal trends in cloud cover. Corals generally live in well-mixed coastal regions and can often record environmental conditions of large areas of the upper ocean. This is particularly the case at low latitudes. Scleractinian corals are sessile, epibenthic fauna, and the type of environmental information recorded at the location where the coral has been living is dependent upon the species of coral considered and proxy index of interest. Skeletons of scleractinian corals are considered to provide among the best records of high-resolution (sub-annual) environmental variability in the tropical and sub-tropical oceans. Zooxanthellate hermatypic corals in tropical and sub-tropical seas precipitate CaCO3 skeletons as they grow. This growth is made possible through the manufacture of CaCO3crystals, facilitated by the zooxanthellae. During the process of crystallization, the holobiont binds carbon of different isotopes into the crystals. Stable carbon isotope concentrations vary with a variety of environmental conditions. In the Caribbean, d13C in corals of the species Montastraea faveolata can be used as a proxy for changes in cloud cover. In this contribution, we will demonstrate that the stable isotope 13C varies concomitantly with cloud cover for the northeastern Caribbean region. Using this proxy we have been able to reconstruct cloud cover conditions back to the year 1760 and thus determine historical cloud cover prior to the recent use of instrumental records. We will also discuss how our coral proxy record of cloud cover compares to paleo-climate model runs for the same time period.

Cloud water interception and canopy water balance in the Hawaiian Islands: preliminary results and emerging patterns

NASA Astrophysics Data System (ADS)

Tseng, H.; Giambelluca, T. W.; DeLay, J. K.; Nullet, M.

2017-12-01

Steep climate gradients and diverse ecosystems make the Hawaiian Islands an ideal laboratory for ecohydrological experiments. Researchers are able to control physical and ecological variables, which is difficult for most environmental studies, by selecting sites along these gradients. Tropical montane forests, especially those situated in the cloud zone, are known to improve recharge and sustain baseflow. This is probably the result of frequent and persistent fog characteristic to these systems. During fog events, evapotranspiration is suppressed due to high humidity and reduced solar radiation. Moreover, cloud water interception by the forest canopy can produce fog drip and contribute significantly to the local water budget. Because the interception process is a complex interaction between the atmosphere and the vegetation, the effects of the meteorological conditions and canopy characteristics are equally important and sometimes hard to separate. This study aims to examine patterns in cloud water interception and canopy water balance across five tropical montane forest sites on three of the main islands of Hawaii. The sites cover a range of elevations between 1100- 2114 m, annual rainfall between 1155-3375 mm, and different dominant plant species with canopy heights ranging from 1.5 m to 30 m. We investigate the effect of climatic factors by comparing passive fog gauge measurements and other meteorological variables, then examine the differences in canopy water balance by comparing throughfall and stemflow measurements at these sites. While this study is ongoing, we present the first few months of field observations and the results of preliminary analyses. This study will improve understanding of how large-scale climate and vegetation factors interact to control cloud water interception and will inform ongoing watershed management. This is particularly important for oceanic islands such as Hawaii because they rely on precipitation entirely for water supply and are, therefore, vulnerable to impacts of altered ecohydrological functioning due to climate and land cover changes.

Remotely Sensed High-Resolution Global Cloud Dynamics for Predicting Ecosystem and Biodiversity Distributions.

PubMed

Wilson, Adam M; Jetz, Walter

2016-03-01

Cloud cover can influence numerous important ecological processes, including reproduction, growth, survival, and behavior, yet our assessment of its importance at the appropriate spatial scales has remained remarkably limited. If captured over a large extent yet at sufficiently fine spatial grain, cloud cover dynamics may provide key information for delineating a variety of habitat types and predicting species distributions. Here, we develop new near-global, fine-grain (≈1 km) monthly cloud frequencies from 15 y of twice-daily Moderate Resolution Imaging Spectroradiometer (MODIS) satellite images that expose spatiotemporal cloud cover dynamics of previously undocumented global complexity. We demonstrate that cloud cover varies strongly in its geographic heterogeneity and that the direct, observation-based nature of cloud-derived metrics can improve predictions of habitats, ecosystem, and species distributions with reduced spatial autocorrelation compared to commonly used interpolated climate data. These findings support the fundamental role of remote sensing as an effective lens through which to understand and globally monitor the fine-grain spatial variability of key biodiversity and ecosystem properties.

Sensitivity of single column model simulations of Arctic springtime clouds to different cloud cover and mixed phase cloud parameterizations

NASA Astrophysics Data System (ADS)

Zhang, Junhua; Lohmann, Ulrike

2003-08-01

The single column model of the Canadian Centre for Climate Modeling and Analysis (CCCma) climate model is used to simulate Arctic spring cloud properties observed during the Surface Heat Budget of the Arctic Ocean (SHEBA) experiment. The model is driven by the rawinsonde observations constrained European Center for Medium-Range Weather Forecasts (ECMWF) reanalysis data. Five cloud parameterizations, including three statistical and two explicit schemes, are compared and the sensitivity to mixed phase cloud parameterizations is studied. Using the original mixed phase cloud parameterization of the model, the statistical cloud schemes produce more cloud cover, cloud water, and precipitation than the explicit schemes and in general agree better with observations. The mixed phase cloud parameterization from ECMWF decreases the initial saturation specific humidity threshold of cloud formation. This improves the simulated cloud cover in the explicit schemes and reduces the difference between the different cloud schemes. On the other hand, because the ECMWF mixed phase cloud scheme does not consider the Bergeron-Findeisen process, less ice crystals are formed. This leads to a higher liquid water path and less precipitation than what was observed.

Temporal variability of total cloud cover at a Mediterranean megacity in the 20th century: Evidence from visual observations and climate models

NASA Astrophysics Data System (ADS)

Founda, Dimitra; Giannakopoulos, Christos; Pierros, Fragiskos

2013-04-01

Cloud cover is one of the major factors that determine the radiation budget and the climate system of the Earth. Moreover, the response of clouds has always been an important source of uncertainty in global climate models. Visual surface observations of clouds have been conducted at the National Observatory of Athens (NOA) since the mid 19th century. The historical archive of cloud reports at NOA since 1860 has been digitized and updated, spanning now a period of one and a half century. Mean monthly values of total cloud cover were derived by averaging subdaily observations of cloud cover (3 observations/day). Changes in observational practice (e.g. from 1/10 to 1/8 units) were considered, however, subjective measures of cloud cover from trained observers introduces some kind of uncertainty in the time series. Data before 1884 were considered unreliable, so the analysis was restricted to the series from 1884 to 2012. The time series of total cloud cover at NOA is validated and correlated with historical time series of other (physically related) variables such as the total sunshine duration as well as DTR (Diurnal Temperature Range) which are independently measured. Trend analysis was performed on the mean annual and seasonal series of total cloud cover from 1884-2012. The mean annual values show a marked temporal variability with sub periods of decreasing and increasing tendencies, however, the overall linear trend is positive and statistically significant (p <0.001) amounting to +2% per decade and implying a total increase of almost 25% for the whole analysed period. These results are in agreement qualitatively with the trends reported in other studies worldwide, especially concerning the period before the mid 20th century. On a seasonal basis, spring and summer series present outstanding positive long term trends, while in winter and autumn total cloud cover reveals also positive but less pronounced long term trends Additionally, an evaluation of cloud cover and/or sunshine duration/diurnal temperature range as depicted by regional climate models over Athens will be performed. Regional climate models are valuable tools for projections of future climate change but their performance is typically assessed only in terms of temperature and precipitation. The representation of non-standard parameters such as cloud cover and/or sunshine duration/diurnal temperature range has so far seen little or no evaluation in the models and can therefore be prone to large uncertainties. Regional climate models developed in the framework of recent EU projects, such as the ENSEMBLES (www.ensembles-eu.org) and the CIRCE (www.circeproject.eu) projects, will be used and an initial validation of these parameters against the historical archive of NOA will be performed.

Geo-spatial distribution of cloud cover and influence of cloud induced attenuation and noise temperature on satellite signal propagation over Nigeria

NASA Astrophysics Data System (ADS)

Ojo, Joseph Sunday

2017-05-01

The study of the influence of cloud cover on satellite propagation links is becoming more demanding due to the requirement of larger bandwidth for different satellite applications. Cloud attenuation is one of the major factors to consider for optimum performance of Ka/V and other higher frequency bands. In this paper, the geo-spatial distribution of cloud coverage over some chosen stations in Nigeria has been considered. The substantial scale spatial dispersion of cloud cover based on synoptic meteorological data and the possible impact on satellite communication links at higher frequency bands was also investigated. The investigation was based on 5 years (2008-2012) achieved cloud cover data collected by the Nigerian Meteorological Agency (NIMET) Federal Ministry of Aviation, Oshodi Lagos over four synoptic hours of the day covering day and night. The performances of satellite signals as they traverse through the cloud and cloud noise temperature at different seasons and over different hours of days at Ku/W-bands frequency are also examined. The overall result shows that the additional total atmospheric noise temperature due to the clear air effect and the noise temperature from the cloud reduces the signal-to-noise ratio of the satellite receiver systems, leading to more signal loss and if not adequately taken care of may lead to significant outage. The present results will be useful for Earth-space link budgeting, especially for the proposed multi-sensors communication satellite systems in Nigeria.

Atmospheric Profiles, Clouds, and the Evolution of Sea Ice Cover in the Beaufort and Chukchi Seas Atmospheric Observations and Modeling as Part of the Seasonal Ice Zone Reconnaissance Surveys

DTIC Science & Technology

2013-09-30

Cover in the Beaufort and Chukchi Seas Atmospheric Observations and Modeling as Part of the Seasonal Ice Zone Reconnaissance Surveys Axel...how changes in sea ice and sea surface conditions in the SIZ affect changes in cloud properties and cover . • Determine the role additional atmospheric...REPORT TYPE 3. DATES COVERED 00-00-2013 to 00-00-2013 4. TITLE AND SUBTITLE Atmospheric Profiles, Clouds, and the Evolution of Sea Ice Cover in the

The impact of low-level cloud over the eastern subtropical Pacific on the ``Double ITCZ'' in LASG FGCM-0

NASA Astrophysics Data System (ADS)

Dai, Fushan; Yu, Rucong; Zhang, Xuehong; Yu, Yongqiang; Li, Jianglong

2003-05-01

Like many other coupled models, the Flexible coupled General Circulation Model (FGCM-0) suffers from the spurious “Double ITCZ”. In order to understand the “Double ITCZ” in FGCM-0, this study first examines the low-level cloud cover and the bulk stability of the low troposphere over the eastern subtropical Pacific simulated by the National Center for Atmospheric Research (NCAR) Community Climate Model version 3 (CCM3), which is the atmosphere component model of FGCM-0. It is found that the bulk stability of the low troposphere simulated by CCM3 is very consistent with the one derived from the National Center for Environmental Prediction (NCEP) reanalysis, but the simulated low-level cloud cover is much less than that derived from the International Satellite Cloud Climatology Project (ISCCP) D2 data. Based on the regression equations between the low-level cloud cover from the ISCCP data and the bulk stability of the low troposphere derived from the NCEP reanalysis, the parameterization scheme of low-level cloud in CCM3 is modified and used in sensitivity experiments to examine the impact of low-level cloud over the eastern subtropical Pacific on the spurious “Double ITCZ” in FGCM-0. Results show that the modified scheme causes the simulated low-level cloud cover to be improved locally over the cold oceans. Increasing the low-level cloud cover off Peru not only significantly alleviates the SST warm biases in the southeastern tropical Pacific, but also causes the equatorial cold tongue to be strengthened and to extend further west. Increasing the low-level cloud fraction off California effectively reduces the SST warm biases in ITCZ north of the equator. In order to examine the feedback between the SST and low-level cloud cover off Peru, one additional sensitivity experiment is performed in which the SST over the cold ocean off Peru is restored. It shows that decreasing the SST results in similar impacts over the wide regions from the southeastern tropical Pacific northwestwards to the western/central equatorial Pacific as increasing the low-level cloud cover does.

The Radiative Consistency of Atmospheric Infrared Sounder and Moderate Resolution Imaging Spectroradiometer Cloud Retrievals

NASA Technical Reports Server (NTRS)

Kahn, Brian H.; Fishbein, Evan; Nasiri, Shaima L.; Eldering, Annmarie; Fetzer, Eric J.; Garay, Michael J.; Lee, Sung-Yung

2007-01-01

The consistency of cloud top temperature (Tc) and effective cloud fraction (f) retrieved by the Atmospheric Infrared Sounder (AIRS)/Advanced Microwave Sounding Unit (AMSU) observation suite and the Moderate Resolution Imaging Spectroradiometer (MODIS) on the EOS-Aqua platform are investigated. Collocated AIRS and MODIS TC and f are compared via an 'effective scene brightness temperature' (Tb,e). Tb,e is calculated with partial field of view (FOV) contributions from TC and surface temperature (TS), weighted by f and 1-f, respectively. AIRS reports up to two cloud layers while MODIS reports up to one. However, MODIS reports TC, TS, and f at a higher spatial resolution than AIRS. As a result, pixel-scale comparisons of TC and f are difficult to interpret, demonstrating the need for alternatives such as Tb,e. AIRS-MODIS Tb,e differences ((Delta)Tb,e) for identical observing scenes are useful as a diagnostic for cloud quantity comparisons. The smallest values of DTb,e are for high and opaque clouds, with increasing scatter in (Delta)Tb,e for clouds of smaller opacity and lower altitude. A persistent positive bias in DTb,e is observed in warmer and low-latitude scenes, characterized by a mixture of MODIS CO2 slicing and 11-mm window retrievals. These scenes contain heterogeneous cloud cover, including mixtures of multilayered cloudiness and misplaced MODIS cloud top pressure. The spatial patterns of (Delta)Tb,e are systematic and do not correlate well with collocated AIRS-MODIS radiance differences, which are more random in nature and smaller in magnitude than (Delta)Tb,e. This suggests that the observed inconsistencies in AIRS and MODIS cloud fields are dominated by retrieval algorithm differences, instead of differences in the observed radiances. The results presented here have implications for the validation of cloudy satellite retrieval algorithms, and use of cloud products in quantitative analyses.

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

NASA Technical Reports Server (NTRS)

Teixeira, J.; Cardoso, S.; Bonazzola, M.; Cole, J.; DeGenio, A.; DeMott, C.; Franklin, C.; Hannay, C.; Jakob, C.; Jiao, Y.;

The effect of moonlight on observation of cloud cover at night, and application to cloud climatology

NASA Technical Reports Server (NTRS)

Hahn, Carole J.; Warren, Stephen G.; London, Julius

1995-01-01

Ten years of nighttime weather observations from the Northern Hemisphere in December were classified according to the illuminance of moonlight or twilight on the cloud tops, and a threshold level of illuminance was determined, above which the clouds are apparently detected adequately. This threshold corresponds to light from a full moon at an elevation angle of 6 deg, light from a partial moon at higher elevation, or twilight from the sun less than 9 deg bvelow the horizon. It permits the use of about 38% of the observations made with the sun below the horizon. The computed diurnal cycles of total cloud cover are altered considerably when this moonlight criterion is imposed. Maximum cloud cover over much of the ocean is now found to be at night or in the morning, whereas computations obtained without benefit of the moonlight criterion, as in our published atlases, showed the time of maximum to be noon or early afternoon in many regions. The diurnal cycles of total cloud cover we obtain are compared with those of the International Satellite Cloud Climatology Project (ISCCP) for a few regions; they are generally in better agreement if the moonlight criterion is imposed on the surface observations. Using the moonlight criterion, we have analyzed 10 years (1982-91) of surface weather observations over land and ocean, worldwide, for total cloud cover and for the frequency of occurrence of clear sky, fog, and precipitation. The global average cloud cover (average of day and night) is about 2% higher if the moonlight criterion is imposed than if all observations are used. The difference is greater in winter than in summer, because of the fewer hours of darkness in summer. The amplitude of the annual cycle of total cloud cover over the Arctic Ocean and at the South Pole is diminished by a few percent when the moonlight criterion is imposed. The average cloud cover for 1982-91 is found to be 55% for Northern Hemisphere land, 53% for Southern Hemisphere land, 66% for Northern Hemisphere ocean, and 70% for Southern Hemisphere ocean, giving a global average of 64%. The global average for daytime is 64.6%; for nighttime 63.3%.

Trends and uncertainties in U.S. cloud cover from weather stations and satellite data

NASA Astrophysics Data System (ADS)

Free, M. P.; Sun, B.; Yoo, H. L.

2014-12-01

Cloud cover data from ground-based weather observers can be an important source of climate information, but the record of such observations in the U.S. is disrupted by the introduction of automated observing systems and other artificial shifts that interfere with our ability to assess changes in cloudiness at climate time scales. A new dataset using 54 National Weather Service (NWS) and 101 military stations that continued to make human-augmented cloud observations after the 1990s has been adjusted using statistical changepoint detection and visual scrutiny. The adjustments substantially reduce the trends in U.S. mean total cloud cover while increasing the agreement between the cloud cover time series and those of physically related climate variables such as diurnal temperature range and number of precipitation days. For 1949-2009, the adjusted time series give a trend in U.S. mean total cloud of 0.11 ± 0.22 %/decade for the military data, 0.55 ± 0.24 %/decade for the NWS data, and 0.31 ± 0.22 %/decade for the combined dataset. These trends are less than half those in the original data. For 1976-2004, the original data give a significant increase but the adjusted data show an insignificant trend of -0.17 (military stations) to 0.66 %/decade (NWS stations). The differences between the two sets of station data illustrate the uncertainties in the U.S. cloud cover record. We compare the adjusted station data to cloud cover time series extracted from several satellite datasets: ISCCP (International Satellite Cloud Climatology Project), PATMOS-x (AVHRR Pathfinder Atmospheres Extended) and CLARA-a1 (CM SAF cLoud Albedo and RAdiation), and the recently developed PATMOS-x diurnally corrected dataset. Like the station data, satellite cloud cover time series may contain inhomogeneities due to changes in the observing systems and problems with retrieval algorithms. Overall we find good agreement between interannual variability in most of the satellite data and that in our station data, with the diurnally corrected PATMOS-x product generally showing the best match. For the satellite period 1984-2007, trends in the U.S. mean cloud cover from satellite data vary widely among the datasets, and all are more negative than those in the station data, with PATMOS-x having the trends closest to those in the station data.

Influence of cloud fraction and snow cover to the variation of surface UV radiation at King Sejong station, Antarctica

NASA Astrophysics Data System (ADS)

Lee, Yun Gon; Koo, Ja-Ho; Kim, Jhoon

2015-10-01

This study investigated how cloud fraction and snow cover affect the variation of surface ultraviolet (UV) radiation by using surface Erythemal UV (EUV) and Near UV (NUV) observed at the King Sejong Station, Antarctica. First the Radiative Amplification Factor (RAF), the relative change of surface EUV according to the total-column ozone amount, is compared for different cloud fractions and solar zenith angles (SZAs). Generally, all cloudy conditions show that the increase of RAF as SZA becomes larger, showing the larger effects of vertical columnar ozone. For given SZA cases, the EUV transmission through mean cloud layer gradually decreases as cloud fraction increases, but sometimes the maximum of surface EUV appears under partly cloudy conditions. The high surface EUV transmittance under broken cloud conditions seems due to the re-radiation of scattered EUV by cloud particles. NUV transmission through mean cloud layer also decreases as cloud amount increases but the sensitivity to the cloud fraction is larger than EUV. Both EUV and NUV radiations at the surface are also enhanced by the snow cover, and their enhancement becomes higher as SZA increases implying the diurnal variation of surface albedo. This effect of snow cover seems large under the overcast sky because of the stronger interaction between snow surface and cloudy sky.

New optical package and algorithms for accurate estimation and interactive recording of the cloud cover information over land and sea

NASA Astrophysics Data System (ADS)

Krinitskiy, Mikhail; Sinitsyn, Alexey; Gulev, Sergey

2014-05-01

Cloud fraction is a critical parameter for the accurate estimation of short-wave and long-wave radiation - one of the most important surface fluxes over sea and land. Massive estimates of the total cloud cover as well as cloud amount for different layers of clouds are available from visual observations, satellite measurements and reanalyses. However, these data are subject of different uncertainties and need continuous validation against highly accurate in-situ measurements. Sky imaging with high resolution fish eye camera provides an excellent opportunity for collecting cloud cover data supplemented with additional characteristics hardly available from routine visual observations (e.g. structure of cloud cover under broken cloud conditions, parameters of distribution of cloud dimensions). We present operational automatic observational package which is based on fish eye camera taking sky images with high resolution (up to 1Hz) in time and a spatial resolution of 968x648px. This spatial resolution has been justified as an optimal by several sensitivity experiments. For the use of the package at research vessel when the horizontal positioning becomes critical, a special extension of the hardware and software to the package has been developed. These modules provide the explicit detection of the optimal moment for shooting. For the post processing of sky images we developed a software realizing the algorithm of the filtering of sunburn effect in case of small and moderate could cover and broken cloud conditions. The same algorithm accurately quantifies the cloud fraction by analyzing color mixture for each point and introducing the so-called "grayness rate index" for every pixel. The accuracy of the algorithm has been tested using the data collected during several campaigns in 2005-2011 in the North Atlantic Ocean. The collection of images included more than 3000 images for different cloud conditions supplied with observations of standard parameters. The system is fully autonomous and has a block for digital data collection at the hard disk. The system has been tested for a wide range of open ocean cloud conditions and we will demonstrate some pilot results of data processing and physical interpretation of fractional cloud cover estimation.

ULF geomagnetic activity effects on tropospheric temperature, specific humidity, and cloud cover in Antarctica, during 2003-2010

NASA Astrophysics Data System (ADS)

Regi, Mauro; Redaelli, Gianluca; Francia, Patrizia; De Lauretis, Marcello

2017-06-01

In the present study we investigated the possible relationship between the ULF geomagnetic activity and the variations of several atmospheric parameters. In particular, we compared the ULF activity in the Pc1-2 frequency band (100 mHz-5 Hz), computed from geomagnetic field measurements at Terra Nova Bay in Antarctica, with the tropospheric temperature T, specific humidity Q, and cloud cover (high cloud cover, medium cloud cover, and low cloud cover) obtained from reanalysis data set. The statistical analysis was conducted during the years 2003-2010, using correlation and Superposed Epoch Analysis approaches. The results show that the atmospheric parameters significantly change following the increase of geomagnetic activity within 2 days. These changes are evident in particular when the interplanetary magnetic field Bz component is oriented southward (Bz<0) and the By component duskward (By>0). We suggest that both the precipitation of electrons induced by Pc1-2 activity and the intensification of the polar cap potential difference, modulating the microphysical processes in the clouds, can affect the atmosphere conditions.

The structure of the clouds distributed operating system

NASA Technical Reports Server (NTRS)

Dasgupta, Partha; Leblanc, Richard J., Jr.

1989-01-01

A novel system architecture, based on the object model, is the central structuring concept used in the Clouds distributed operating system. This architecture makes Clouds attractive over a wide class of machines and environments. Clouds is a native operating system, designed and implemented at Georgia Tech. and runs on a set of generated purpose computers connected via a local area network. The system architecture of Clouds is composed of a system-wide global set of persistent (long-lived) virtual address spaces, called objects that contain persistent data and code. The object concept is implemented at the operating system level, thus presenting a single level storage view to the user. Lightweight treads carry computational activity through the code stored in the objects. The persistent objects and threads gives rise to a programming environment composed of shared permanent memory, dispensing with the need for hardware-derived concepts such as the file systems and message systems. Though the hardware may be distributed and may have disks and networks, the Clouds provides the applications with a logically centralized system, based on a shared, structured, single level store. The current design of Clouds uses a minimalist philosophy with respect to both the kernel and the operating system. That is, the kernel and the operating system support a bare minimum of functionality. Clouds also adheres to the concept of separation of policy and mechanism. Most low-level operating system services are implemented above the kernel and most high level services are implemented at the user level. From the measured performance of using the kernel mechanisms, we are able to demonstrate that efficient implementations are feasible for the object model on commercially available hardware. Clouds provides a rich environment for conducting research in distributed systems. Some of the topics addressed in this paper include distributed programming environments, consistency of persistent data and fault-tolerance.

A High Resolution Hydrometer Phase Classifier Based on Analysis of Cloud Radar Doppler Spectra.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Luke,E.; Kollias, P.

2007-08-06

The lifecycle and radiative properties of clouds are highly sensitive to the phase of their hydrometeors (i.e., liquid or ice). Knowledge of cloud phase is essential for specifying the optical properties of clouds, or else, large errors can be introduced in the calculation of the cloud radiative fluxes. Current parameterizations of cloud water partition in liquid and ice based on temperature are characterized by large uncertainty (Curry et al., 1996; Hobbs and Rangno, 1998; Intriery et al., 2002). This is particularly important in high geographical latitudes and temperature ranges where both liquid droplets and ice crystal phases can exist (mixed-phasemore » cloud). The mixture of phases has a large effect on cloud radiative properties, and the parameterization of mixed-phase clouds has a large impact on climate simulations (e.g., Gregory and Morris, 1996). Furthermore, the presence of both ice and liquid affects the macroscopic properties of clouds, including their propensity to precipitate. Despite their importance, mixed-phase clouds are severely understudied compared to the arguably simpler single-phase clouds. In-situ measurements in mixed-phase clouds are hindered due to aircraft icing, difficulties distinguishing hydrometeor phase, and discrepancies in methods for deriving physical quantities (Wendisch et al. 1996, Lawson et al. 2001). Satellite-based retrievals of cloud phase in high latitudes are often hindered by the highly reflecting ice-covered ground and persistent temperature inversions. From the ground, the retrieval of mixed-phase cloud properties has been the subject of extensive research over the past 20 years using polarization lidars (e.g., Sassen et al. 1990), dual radar wavelengths (e.g., Gosset and Sauvageot 1992; Sekelsky and McIntosh, 1996), and recently radar Doppler spectra (Shupe et al. 2004). Millimeter-wavelength radars have substantially improved our ability to observe non-precipitating clouds (Kollias et al., 2007) due to their excellent sensitivity that enables the detection of thin cloud layers and their ability to penetrate several non-precipitating cloud layers. However, in mixed-phase clouds conditions, the observed Doppler moments are dominated by the highly reflecting ice crystals and thus can not be used to identify the cloud phase. This limits our ability to identify the spatial distribution of cloud phase and our ability to identify the conditions under which mixed-phase clouds form.« less

Seasonal and interannual variations of top-of-atmosphere irradiance and cloud cover over polar regions derived from the CERES data set

NASA Astrophysics Data System (ADS)

Kato, Seiji; Loeb, Norman G.; Minnis, Patrick; Francis, Jennifer A.; Charlock, Thomas P.; Rutan, David A.; Clothiaux, Eugene E.; Sun-Mack, Szedung

2006-10-01

The daytime cloud fraction derived by the Clouds and the Earth's Radiant Energy System (CERES) cloud algorithm using Moderate Resolution Imaging Spectroradiometer (MODIS) radiances over the Arctic from March 2000 through February 2004 increases at a rate of 0.047 per decade. The trend is significant at an 80% confidence level. The corresponding top-of-atmosphere (TOA) shortwave irradiances derived from CERES radiance measurements show less significant trend during this period. These results suggest that the influence of reduced Arctic sea ice cover on TOA reflected shortwave radiation is reduced by the presence of clouds and possibly compensated by the increase in cloud cover. The cloud fraction and TOA reflected shortwave irradiance over the Antarctic show no significant trend during the same period.

Spatial characteristics of the tropical cloud systems: comparison between model simulation and satellite observations

NASA Astrophysics Data System (ADS)

Zhang, Guang J.; Zurovac-Jevtic, Dance; Boer, Erwin R.

1999-10-01

A Lagrangian cloud classification algorithm is applied to the cloud fields in the tropical Pacific simulated by a high-resolution regional atmospheric model. The purpose of this work is to assess the model's ability to reproduce the observed spatial characteristics of the tropical cloud systems. The cloud systems are broadly grouped into three categories: deep clouds, mid-level clouds and low clouds. The deep clouds are further divided into mesoscale convective systems and nonmesoscale convective systems. It is shown that the model is able to simulate the total cloud cover for each category reasonably well. However, when the cloud cover is broken down into contributions from cloud systems of different sizes, it is shown that the simulated cloud size distribution is biased toward large cloud systems, with contribution from relatively small cloud systems significantly under-represented in the model for both deep and mid-level clouds. The number distribution and area contribution to the cloud cover from mesoscale convective systems are very well simulated compared to the satellite observations, so are low clouds as well. The dependence of the cloud physical properties on cloud scale is examined. It is found that cloud liquid water path, rainfall, and ocean surface sensible and latent heat fluxes have a clear dependence on cloud types and scale. This is of particular interest to studies of the cloud effects on surface energy budget and hydrological cycle. The diurnal variation of the cloud population and area is also examined. The model exhibits a varying degree of success in simulating the diurnal variation of the cloud number and area. The observed early morning maximum cloud cover in deep convective cloud systems is qualitatively simulated. However, the afternoon secondary maximum is missing in the model simulation. The diurnal variation of the tropospheric temperature is well reproduced by the model while simulation of the diurnal variation of the moisture field is poor. The implication of this comparison between model simulation and observations on cloud parameterization is discussed.

Hydrologic Effects and Biogeographic Impacts of Coastal Fog, Channel Islands, California

NASA Astrophysics Data System (ADS)

Fischer, D. T.; Still, C. J.; Williams, A. P.

2006-12-01

Fog has long been recognized as an important component of the hydrological cycle in many ecosystems, including coastal desert fog belts, tropical cloud forests, and montane areas worldwide. Fog drip can be a major source of water, particularly during the dry season, and there is evidence in some ecosystems of direct fogwater uptake by foliar absorption. Fog and low clouds can also increase availability of water by reducing evaporative water losses. In the California Channel Islands, fog and low stratus clouds dramatically affect the water budget of coastal vegetation, particularly during the long summer drought. This work focuses on a population of Bishop pine (Pinus muricata D. Don) on Santa Cruz Island. This is the southernmost large stand of this species, and tree growth and survival appears to be strongly limited by water availability. We have used parallel measurement and modeling approaches to quantify the importance of fogwater inputs and persistent cloud cover to Bishop pine growth. We have modeled drought stress over the last century based on local climate records, calibrated against a dense network of 12 weather stations on a 7km coastal-inland elevation gradient. Water availability is highly variable year to year, with episodic droughts that are associated with widespread tree mortality. Frequent cloud cover near the coast reduces evapotranspiration relative to the inland site (on the order of 25%), thereby delaying the onset of, and moderating the severity of the annual summer drought. Substantial summer fog drip at higher elevations provides additional water inputs that also reduce drought severity. Beyond the theoretical availability of extra water from fog drip, tree ring analysis and xylem water isotopic data suggest that significant amounts of fog water are actually taken up by these trees. Stand boundaries appear to be driven by spatial patterns of mortality related to water availability and frequency of severe drought. These results suggest that coastal endemic forests may be particularly susceptible to climate change, particularly if it leads to changes in the fog and low stratus cloud regime, in agreement with palynological and plant macrofossil evidence from the Santa Barbara basin showing the contraction of coastal pines during warm periods over the last 160 kyrs.

Improving snow fraction spatio-temporal continuity using a combination of MODIS and Fengyun-2 satellites over China

NASA Astrophysics Data System (ADS)

Jiang, L.; Wang, G.

2017-12-01

Snow cover is one of key elements in the investigations of weather, climatic change, water resource, and snow hazard. Satellites observations from on-board optical sensors provides the ability to snow cover mapping through the discrimination of snow from other surface features and cloud. MODIS provides maximum of snow cover data using 8-day composition data in order to reduce the cloud obscuration impacts. However, snow cover mapping is often required to obtain at the temporal scale of less than one day, especially in the case of disasters. Geostationary satellites provide much higher temporal resolution measurements (typically at 15 min or half or one hour), which has a great potential to reduce cloud cover problem and observe ground surface for identifying snow. The proposed method in this work is that how to take the advantages of polar-orbiting and geostationary optical sensors to accurately map snow cover without data gaps due to cloud. FY-2 geostationary satellites have high temporal resolution observations, however, they are lacking enough spectral bands essential for snow cover monitoring, such as the 1.6 μm band. Based on our recent work (Wang et al., 2017), we improved FY-2/VISSR fractional snow cover estimation with a linear spectral unmixing analysis method. The linear approach is applied then using the reflectance observed at the certain hourly image of FY-2 to calculate pixel-wise snow cover fraction. The composition of daily factional snow cover employs the sun zenith angle, where the snow fraction under lowest sun zenith angle is considered as the most confident result. FY-2/VISSR fractional snow cover map has less cloud due to the composition of multi-temporal snow maps in a single day. In order to get an accurate and cloud-reduced fractional snow cover map, both of MODIS and FY-2/VISSR daily snow fraction maps are blended together. With the combination of FY-2E/VISSR and MODIS, there are still some cloud existing in the daily snow fraction map. Then the combination snow fraction map is temporally reconstructed using MATLAB Piecewise Cubic Hermite Interpolating Polynomial (PCHIP) function to derive a completely daily cloud-free snow cover map under all the sky conditions.

Remotely Sensed High-Resolution Global Cloud Dynamics for Predicting Ecosystem and Biodiversity Distributions

PubMed Central

Wilson, Adam M.; Jetz, Walter

2016-01-01

Cloud cover can influence numerous important ecological processes, including reproduction, growth, survival, and behavior, yet our assessment of its importance at the appropriate spatial scales has remained remarkably limited. If captured over a large extent yet at sufficiently fine spatial grain, cloud cover dynamics may provide key information for delineating a variety of habitat types and predicting species distributions. Here, we develop new near-global, fine-grain (≈1 km) monthly cloud frequencies from 15 y of twice-daily Moderate Resolution Imaging Spectroradiometer (MODIS) satellite images that expose spatiotemporal cloud cover dynamics of previously undocumented global complexity. We demonstrate that cloud cover varies strongly in its geographic heterogeneity and that the direct, observation-based nature of cloud-derived metrics can improve predictions of habitats, ecosystem, and species distributions with reduced spatial autocorrelation compared to commonly used interpolated climate data. These findings support the fundamental role of remote sensing as an effective lens through which to understand and globally monitor the fine-grain spatial variability of key biodiversity and ecosystem properties. PMID:27031693

Evaluating the feasibility of global climate models to simulate cloud cover effect controlled by Marine Stratocumulus regime transitions

NASA Astrophysics Data System (ADS)

Goren, Tom; Muelmenstaedt, Johannes; Rosenfeld, Daniel; Quaas, Johannes

2017-04-01

Marine stratocumulus clouds (MSC) occur in two main cloud regimes of open and closed cells that differ significantly by their cloud cover. Closed cells gradually get cleansed of high CCN concentrations in a process that involves initiation of drizzle that breaks the full cloud cover into open cells. The drizzle creates downdrafts that organize the convection along converging gust fronts, which in turn produce stronger updrafts that can sustain more cloud water that compensates the depletion of the cloud water by the rain. In addition, having stronger updrafts allow the clouds to grow relatively deep before rain starts to deplete its cloud water. Therefore, lower droplet concentrations and stronger rain would lead to lower cloud fraction, but not necessary also to lower liquid water path (LWP). The fundamental relationships between these key variables derived from global climate model (GCM) simulations are analyzed with respect to observations in order to determine whether the GCM parameterizations can represent well the governing physical mechanisms upon MSC regime transitions. The results are used to evaluate the feasibility of GCM's for estimating aerosol cloud-mediated radiative forcing upon MSC regime transitions, which are responsible for the largest aerosol cloud-mediated radiative forcing.

On the existence of tropical anvil clouds

NASA Astrophysics Data System (ADS)

Seeley, J.; Jeevanjee, N.; Langhans, W.; Romps, D.

2017-12-01

In the deep tropics, extensive anvil clouds produce a peak in cloud cover below the tropopause. The dominant paradigm for cloud cover attributes this anvil peak to a layer of enhanced mass convergence in the clear-sky upper-troposphere, which is presumed to force frequent detrainment of convective anvils. However, cloud cover also depends on the lifetime of cloudy air after it detrains, which raises the possibility that anvil clouds may be the signature of slow cloud decay rather than enhanced detrainment. Here we measure the cloud decay timescale in cloud-resolving simulations, and find that cloudy updrafts that detrain in the upper troposphere take much longer to dissipate than their shallower counterparts. We show that cloud lifetimes are long in the upper troposphere because the saturation specific humidity becomes orders of magnitude smaller than the typical condensed water loading of cloudy updrafts. This causes evaporative cloud decay to act extremely slowly, thereby prolonging cloud lifetimes in the upper troposphere. As a consequence, extensive anvil clouds still occur in a convecting atmosphere that is forced to have no preferential clear-sky convergence layer. On the other hand, when cloud lifetimes are fixed at a characteristic lower-tropospheric value, extensive anvil clouds do not form. Our results support a revised understanding of tropical anvil clouds, which attributes their existence to the microphysics of slow cloud decay rather than a peak in clear-sky convergence.

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

NASA Technical Reports Server (NTRS)

Susskind, Joel; Lee, Jae N.; Iredell, Lena

2013-01-01

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.

Arsia Mons Spiral Cloud

NASA Technical Reports Server (NTRS)

2002-01-01

One of the benefits of the Mars Global Surveyor (MGS) Mars Orbiter Camera (MOC) Extended Mission is the opportunity to observe how the planet's weather changes during a second full martian year. This picture of Arsia Mons was taken June 19, 2001; southern spring equinox occurred the same day. Arsia Mons is a volcano nearly large enough to cover the state of New Mexico. On this particular day (the first day of Spring), the MOC wide angle cameras documented an unusual spiral-shaped cloud within the 110 km (68 mi) diameter caldera--the summit crater--of the giant volcano. Because the cloud is bright both in the red and blue images acquired by the wide angle cameras, it probably consisted mostly of fine dust grains. The cloud's spin may have been induced by winds off the inner slopes of the volcano's caldera walls resulting from the temperature differences between the walls and the caldera floor, or by a vortex as winds blew up and over the caldera. Similar spiral clouds were seen inside the caldera for several days; we don't know if this was a single cloud that persisted throughout that time or one that regenerated each afternoon. Sunlight illuminates this scene from the left/upper left.

Malin Space Science Systems and the California Institute of Technology built the MOC using spare hardware from the Mars Observer mission. MSSS operates the camera from its facilities in San Diego, CA. The Jet Propulsion Laboratory's Mars Surveyor Operations Project operates the Mars Global Surveyor spacecraft with its industrial partner, Lockheed Martin Astronautics, from facilities in Pasadena, CA and Denver, CO.

Enhancement of Cloud Cover and Suppression of Nocturnal Drizzle in Stratocumulus Polluted by Haze

NASA Technical Reports Server (NTRS)

Ackerman, Andrew S.; Toon, O. B.; Stevens, D. E.; Coakley, J. A., Jr.; Gore, Warren J. (Technical Monitor)

2002-01-01

Recent satellite observations indicate a significant decrease of cloud water in ship tracks, in contrast to an ensemble of in situ ship-track measurements that show no average change in cloud water relative to the surrounding clouds. We find through large-eddy simulations of stratocumulus that the trend in the satellite data is likely an artifact of sampling only overcast clouds. The simulations instead show cloud cover increasing with droplet concentrations. Our simulations also show that increases in cloud water from drizzle suppression (by increasing droplet concentrations) are favored at night or at extremely low droplet concentrations.

Big data processing in the cloud - Challenges and platforms

NASA Astrophysics Data System (ADS)

Zhelev, Svetoslav; Rozeva, Anna

2017-12-01

Choosing the appropriate architecture and technologies for a big data project is a difficult task, which requires extensive knowledge in both the problem domain and in the big data landscape. The paper analyzes the main big data architectures and the most widely implemented technologies used for processing and persisting big data. Clouds provide for dynamic resource scaling, which makes them a natural fit for big data applications. Basic cloud computing service models are presented. Two architectures for processing big data are discussed, Lambda and Kappa architectures. Technologies for big data persistence are presented and analyzed. Stream processing as the most important and difficult to manage is outlined. The paper highlights main advantages of cloud and potential problems.

MODIS Snow Cover Mapping Decision Tree Technique: Snow and Cloud Discrimination

NASA Technical Reports Server (NTRS)

Riggs, George A.; Hall, Dorothy K.

2010-01-01

Accurate mapping of snow cover continues to challenge cryospheric scientists and modelers. The Moderate-Resolution Imaging Spectroradiometer (MODIS) snow data products have been used since 2000 by many investigators to map and monitor snow cover extent for various applications. Users have reported on the utility of the products and also on problems encountered. Three problems or hindrances in the use of the MODIS snow data products that have been reported in the literature are: cloud obscuration, snow/cloud confusion, and snow omission errors in thin or sparse snow cover conditions. Implementation of the MODIS snow algorithm in a decision tree technique using surface reflectance input to mitigate those problems is being investigated. The objective of this work is to use a decision tree structure for the snow algorithm. This should alleviate snow/cloud confusion and omission errors and provide a snow map with classes that convey information on how snow was detected, e.g. snow under clear sky, snow tinder cloud, to enable users' flexibility in interpreting and deriving a snow map. Results of a snow cover decision tree algorithm are compared to the standard MODIS snow map and found to exhibit improved ability to alleviate snow/cloud confusion in some situations allowing up to about 5% increase in mapped snow cover extent, thus accuracy, in some scenes.

On the merging of optical and SAR satellite imagery for surface water mapping applications

NASA Astrophysics Data System (ADS)

Markert, Kel N.; Chishtie, Farrukh; Anderson, Eric R.; Saah, David; Griffin, Robert E.

2018-06-01

Optical and Synthetic Aperture Radar (SAR) imagery from satellite platforms provide a means to discretely map surface water; however, the application of the two data sources in tandem has been inhibited by inconsistent data availability, the distinct physical properties that optical and SAR instruments sense, and dissimilar data delivery platforms. In this paper, we describe a preliminary methodology for merging optical and SAR data into a common data space. We apply our approach over a portion of the Mekong Basin, a region with highly variable surface water cover and persistent cloud cover, for surface water applications requiring dense time series analysis. The methods include the derivation of a representative index from both sensors that transforms data from disparate physical units (reflectance and backscatter) to a comparable dimensionless space applying a consistent water extraction approach to both datasets. The merging of optical and SAR data allows for increased observations in cloud prone regions that can be used to gain additional insight into surface water dynamics or flood mapping applications. This preliminary methodology shows promise for a common optical-SAR water extraction; however, data ranges and thresholding values can vary depending on data source, yielding classification errors in the resulting surface water maps. We discuss some potential future approaches to address these inconsistencies.

Optical Algorithm for Cloud Shadow Detection Over Water

DTIC Science & Technology

2013-02-01

REPORT DATE (DD-MM-YYYY) 05-02-2013 2. REPORT TYPE Journal Article 3. DATES COVERED (From ■ To) 4. TITLE AND SUBTITLE Optical Algorithm for Cloud...particularly over humid tropical regions. Throughout the year, about two-thirds of the Earth’s surface is always covered by clouds [1]. The problem...V. Khlopenkov and A. P. Trishchenko, "SPARC: New cloud, snow , cloud shadow detection scheme for historical I-km AVHHR data over Canada," / Atmos

Cloud cover determination in polar regions from satellite imagery

NASA Technical Reports Server (NTRS)

Barry, R. G.; Key, J. R.; Maslanik, J. A.

1988-01-01

The principal objectives of this project are: (1) to develop suitable validation data sets to evaluate the effectiveness of the International Satellite Cloud Climatology Project (ISCCP) operational algorithm for cloud retrieval in polar regions and to validate model simulations of polar cloud cover; (2) to identify limitations of current procedures for varying atmospheric surface conditions, and to explore potential means to remedy them using textural classifiers; and (3) to compare synoptic cloud data from a control run experiment of the GISS climate model II with typical observed synoptic cloud patterns.

Observational evidence for cloud cover enhancement over western European forests.

PubMed

Teuling, Adriaan J; Taylor, Christopher M; Meirink, Jan Fokke; Melsen, Lieke A; Miralles, Diego G; van Heerwaarden, Chiel C; Vautard, Robert; Stegehuis, Annemiek I; Nabuurs, Gert-Jan; de Arellano, Jordi Vilà-Guerau

2017-01-11

Forests impact regional hydrology and climate directly by regulating water and heat fluxes. Indirect effects through cloud formation and precipitation can be important in facilitating continental-scale moisture recycling but are poorly understood at regional scales. In particular, the impact of temperate forest on clouds is largely unknown. Here we provide observational evidence for a strong increase in cloud cover over large forest regions in western Europe based on analysis of 10 years of 15 min resolution data from geostationary satellites. In addition, we show that widespread windthrow by cyclone Klaus in the Landes forest led to a significant decrease in local cloud cover in subsequent years. Strong cloud development along the downwind edges of larger forest areas are consistent with a forest-breeze mesoscale circulation. Our results highlight the need to include impacts on cloud formation when evaluating the water and climate services of temperate forests, in particular around densely populated areas.

Observational evidence for cloud cover enhancement over western European forests

PubMed Central

Teuling, Adriaan J.; Taylor, Christopher M.; Meirink, Jan Fokke; Melsen, Lieke A.; Miralles, Diego G.; van Heerwaarden, Chiel C.; Vautard, Robert; Stegehuis, Annemiek I.; Nabuurs, Gert-Jan; de Arellano, Jordi Vilà-Guerau

2017-01-01

Forests impact regional hydrology and climate directly by regulating water and heat fluxes. Indirect effects through cloud formation and precipitation can be important in facilitating continental-scale moisture recycling but are poorly understood at regional scales. In particular, the impact of temperate forest on clouds is largely unknown. Here we provide observational evidence for a strong increase in cloud cover over large forest regions in western Europe based on analysis of 10 years of 15 min resolution data from geostationary satellites. In addition, we show that widespread windthrow by cyclone Klaus in the Landes forest led to a significant decrease in local cloud cover in subsequent years. Strong cloud development along the downwind edges of larger forest areas are consistent with a forest-breeze mesoscale circulation. Our results highlight the need to include impacts on cloud formation when evaluating the water and climate services of temperate forests, in particular around densely populated areas. PMID:28074840

Modeled Impact of Cirrus Cloud Increases Along Aircraft Flight Paths

NASA Technical Reports Server (NTRS)

Rind, David; Lonergan, P.; Shah, K.

1999-01-01

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.

Research on snow cover monitoring of Northeast China using Fengyun Geostationary Satellite

NASA Astrophysics Data System (ADS)

Wu, Tong; Gu, Lingjia; Ren, Ruizhi; Zhou, TIngting

2017-09-01

Snow cover information has great significance for monitoring and preventing snowstorms. With the development of satellite technology, geostationary satellites are playing more important roles in snow monitoring. Currently, cloud interference is a serious problem for obtaining accurate snow cover information. Therefore, the cloud pixels located in the MODIS snow products are usually replaced by cloud-free pixels around the day, which ignores snow cover dynamics. FengYun-2(FY-2) is the first generation of geostationary satellite in our country which complements the polar orbit satellite. The snow cover monitoring of Northeast China using FY-2G data in January and February 2016 is introduced in this paper. First of all, geometric and radiometric corrections are carried out for visible and infrared channels. Secondly, snow cover information is extracted according to its characteristics in different channels. Multi-threshold judgment methods for the different land types and similarity separation techniques are combined to discriminate snow and cloud. Furthermore, multi-temporal data is used to eliminate cloud effect. Finally, the experimental results are compared with the MOD10A1 and MYD10A1 (MODIS daily snow cover) product. The MODIS product can provide higher resolution of the snow cover information in cloudless conditions. Multi-temporal FY-2G data can get more accurate snow cover information in cloudy conditions, which is beneficial for monitoring snowstorms and climate changes.

The Cloud Detection and Ultraviolet Monitoring Experiment (CLUE)

NASA Technical Reports Server (NTRS)

Barbier, Louis M.; Loh, Eugene C.; Krizmanic, John F.; Sokolsky, Pierre; Streitmatter, Robert E.

2004-01-01

In this paper we describe a new balloon instrument - CLUE - which is designed to monitor ultraviolet (uv) nightglow levels and determine cloud cover and cloud heights with a CO2 slicing technique. The CO2 slicing technique is based on the MODIS instrument on NASA's Aqua and Terra spacecraft. CLUE will provide higher spatial resolution (0.5 km) and correlations between the uv and the cloud cover.

Using cloud and climate data to understand warm season hydrometeorology from diurnal to monthly timescales

NASA Astrophysics Data System (ADS)

Betts, A. K.; Tawfik, A. B.; Desjardins, R. L.

2016-12-01

We use 600 station years of hourly data from 14 stations on the Canadian Prairies to map the warm season hydrometeorology. The months from April (after snowmelt) to September, have a very similar coupling between surface thermodynamics and opaque cloud cover, which has been calibrated to give cloud radiative forcing. We can derive both the mean diurnal ranges and the diurnal imbalances as a function of opaque cloud cover. For the monthly diurnal climate, we compute the coupling coefficients with opaque cloud cover and lagged precipitation. In April the diurnal cycle climate has memory of precipitation back to freeze-up in November. During the growing season months of June, July and August, there is memory of precipitation back to March. Monthly mean temperature depends strongly on cloud but little on precipitation, while monthly mean mixing ratio depends on precipitation, but rather little on cloud. The coupling coefficients to cloud and precipitation change with increasing monthly precipitation anomaly. This observational climate analysis provides a firm basis for model evaluation.

Seasonal Synchronization of a Simple Stochastic Dynamical Model Capturing El Niño Diversity

NASA Astrophysics Data System (ADS)

Thual, S.; Majda, A.; Chen, N.

2017-12-01

The El Niño-Southern Oscillation (ENSO) has significant impact on global climate and seasonal prediction. Recently, a simple ENSO model was developed that automatically captures the ENSO diversity and intermittency in nature, where state-dependent stochastic wind bursts and nonlinear advection of sea surface temperature (SST) are coupled to simple ocean-atmosphere processes that are otherwise deterministic, linear and stable. In the present article, it is further shown that the model can reproduce qualitatively the ENSO synchronization (or phase-locking) to the seasonal cycle in nature. This goal is achieved by incorporating a cloud radiative feedback that is derived naturally from the model's atmosphere dynamics with no ad-hoc assumptions and accounts in simple fashion for the marked seasonal variations of convective activity and cloud cover in the eastern Pacific. In particular, the weak convective response to SSTs in boreal fall favors the eastern Pacific warming that triggers El Niño events while the increased convective activity and cloud cover during the following spring contributes to the shutdown of those events by blocking incoming shortwave solar radiations. In addition to simulating the ENSO diversity with realistic non-Gaussian statistics in different Niño regions, both the eastern Pacific moderate and super El Niño, the central Pacific El Niño as well as La Niña show a realistic chronology with a tendency to peak in boreal winter as well as decreased predictability in spring consistent with the persistence barrier in nature. The incorporation of other possible seasonal feedbacks in the model is also documented for completeness.

A combined spectral and object-based approach to transparent cloud removal in an operational setting for Landsat ETM+

NASA Astrophysics Data System (ADS)

Watmough, Gary R.; Atkinson, Peter M.; Hutton, Craig W.

2011-04-01

The automated cloud cover assessment (ACCA) algorithm has provided automated estimates of cloud cover for the Landsat ETM+ mission since 2001. However, due to the lack of a band around 1.375 μm, cloud edges and transparent clouds such as cirrus cannot be detected. Use of Landsat ETM+ imagery for terrestrial land analysis is further hampered by the relatively long revisit period due to a nadir only viewing sensor. In this study, the ACCA threshold parameters were altered to minimise omission errors in the cloud masks. Object-based analysis was used to reduce the commission errors from the extended cloud filters. The method resulted in the removal of optically thin cirrus cloud and cloud edges which are often missed by other methods in sub-tropical areas. Although not fully automated, the principles of the method developed here provide an opportunity for using otherwise sub-optimal or completely unusable Landsat ETM+ imagery for operational applications. Where specific images are required for particular research goals the method can be used to remove cloud and transparent cloud helping to reduce bias in subsequent land cover classifications.

Cloud cover estimation optical package: New facility, algorithms and techniques

NASA Astrophysics Data System (ADS)

Krinitskiy, Mikhail

2017-02-01

Short- and long-wave radiation is an important component of surface heat budget over sea and land. For estimating them accurate observations of the cloud cover are needed. While massively observed visually, for building accurate parameterizations cloud cover needs also to be quantified using precise instrumental measurements. Major disadvantages of the most of existing cloud-cameras are associated with their complicated design and inaccuracy of post-processing algorithms which typically result in the uncertainties of 20% to 30% in the camera-based estimates of cloud cover. The accuracy of these types of algorithm in terms of true scoring compared to human-observed values is typically less than 10%. We developed new generation package for cloud cover estimating, which provides much more accurate results and also allows for measuring additional characteristics. New algorithm, namely SAIL GrIx, based on routine approach, also developed for this package. It uses the synthetic controlling index ("grayness rate index") which allows to suppress the background sunburn effect. This makes it possible to increase the reliability of the detection of the optically thin clouds. The accuracy of this algorithm in terms of true scoring became 30%. One more approach, namely SAIL GrIx ML, we have used to increase the cloud cover estimating accuracy is the algorithm that uses machine learning technique along with some other signal processing techniques. Sun disk condition appears to be a strong feature in this kind of models. Artificial Neural Networks type of model demonstrates the best quality. This model accuracy in terms of true scoring increases up to 95,5%. Application of a new algorithm lets us to modify the design of the optical sensing package and to avoid the use of the solar trackers. This made the design of the cloud camera much more compact. New cloud-camera has already been tested in several missions across Atlantic and Indian oceans on board of IORAS research vessels.

Collaborative Research: Cloudiness transitions within shallow marine clouds near the Azores

DOE Office of Scientific and Technical Information (OSTI.GOV)

Mechem, David B.; de Szoeke, Simon P.; Yuter, Sandra E.

Marine stratocumulus clouds are low, persistent, liquid phase clouds that cover large areas and play a significant role in moderating the climate by reflecting large quantities of incoming solar radiation. The deficiencies in simulating these clouds in global climate models are widely recognized. Much of the uncertainty arises from sub-grid scale variability in the cloud albedo that is not accurately parameterized in climate models. The Clouds, Aerosol and Precipitation in the Marine Boundary Layer (CAP–MBL) observational campaign and the ongoing ARM site measurements on Graciosa Island in the Azores aim to sample the Northeast Atlantic low cloud regime. These datamore » represent, the longest continuous research quality cloud radar/lidar/radiometer/aerosol data set of open-ocean shallow marine clouds in existence. Data coverage from CAP–MBL and the series of cruises to the southeast Pacific culminating in VOCALS will both be of sufficient length to contrast the two low cloud regimes and explore the joint variability of clouds in response to several environmental factors implicated in cloudiness transitions. Our research seeks to better understand cloud system processes in an underexplored but climatologically important maritime region. Our primary goal is an improved physical understanding of low marine clouds on temporal scales of hours to days. It is well understood that aerosols, synoptic-scale forcing, surface fluxes, mesoscale dynamics, and cloud microphysics all play a role in cloudiness transitions. However, the relative importance of each mechanism as a function of different environmental conditions is unknown. To better understand cloud forcing and response, we are documenting the joint variability of observed environmental factors and associated cloud characteristics. In order to narrow the realm of likely parameter ranges, we assess the relative importance of parameter conditions based primarily on two criteria: how often the condition occurs (frequency) and to what degree varying that condition within its typically observed range affects cloud characteristics (magnitude of impact given the condition). In this manner we will be able to address the relative importance of individual factors within a multivariate range of environmental conditions. We will determine the relative roles of the thermodynamic, aerosol, and synoptic environmental factors on low cloud and drizzle formation and lifetime.« less

Snow cover detection algorithm using dynamic time warping method and reflectances of MODIS solar spectrum channels

NASA Astrophysics Data System (ADS)

Lee, Kyeong-sang; Choi, Sungwon; Seo, Minji; Lee, Chang suk; Seong, Noh-hun; Han, Kyung-Soo

2016-10-01

Snow cover is biggest single component of cryosphere. The Snow is covering the ground in the Northern Hemisphere approximately 50% in winter season and is one of climate factors that affects Earth's energy budget because it has higher reflectance than other land types. Also, snow cover has an important role about hydrological modeling and water resource management. For this reason, accurate detection of snow cover acts as an essential element for regional water resource management. Snow cover detection using satellite-based data have some advantages such as obtaining wide spatial range data and time-series observations periodically. In the case of snow cover detection using satellite data, the discrimination of snow and cloud is very important. Typically, Misclassified cloud and snow pixel can lead directly to error factor for retrieval of satellite-based surface products. However, classification of snow and cloud is difficult because cloud and snow have similar optical characteristics and are composed of water or ice. But cloud and snow has different reflectance in 1.5 1.7 μm wavelength because cloud has lower grain size and moisture content than snow. So, cloud and snow shows difference reflectance patterns change according to wavelength. Therefore, in this study, we perform algorithm for classifying snow cover and cloud with satellite-based data using Dynamic Time Warping (DTW) method which is one of commonly used pattern analysis such as speech and fingerprint recognitions and reflectance spectral library of snow and cloud. Reflectance spectral library is constructed in advance using MOD21km (MODIS Level1 swath 1km) data that their reflectance is six channels including 3 (0.466μm), 4 (0.554μm), 1 (0.647μm), 2 (0.857μm), 26 (1.382μm) and 6 (1.629μm). We validate our result using MODIS RGB image and MOD10 L2 swath (MODIS swath snow cover product). And we use PA (Producer's Accuracy), UA (User's Accuracy) and CI (Comparison Index) as validation criteria. The result of our study detect as snow cover in the several regions which are did not detected as snow in MOD10 L2 and detected as snow cover in MODIS RGB image. The result of our study can improve accuracy of other surface product such as land surface reflectance and land surface emissivity. Also it can use input data of hydrological modeling.

Extension of four-dimensional atmospheric models. [and cloud cover data bank

NASA Technical Reports Server (NTRS)

Fowler, M. G.; Lisa, A. S.; Tung, S. L.

1975-01-01

The cloud data bank, the 4-D atmospheric model, and a set of computer programs designed to simulate meteorological conditions for any location above the earth are described in turns of space vehicle design and simulation of vehicle reentry trajectories. Topics discussed include: the relationship between satellite and surface observed cloud cover using LANDSAT 1 photographs and including the effects of cloud shadows; extension of the 4-D model to the altitude of 52 km; and addition of the u and v wind components to the 4-D model of means and variances at 1 km levels from the surface to 25 km. Results of the cloud cover analysis are presented along with the stratospheric model and the tropospheric wind profiles.

Monitoring Cloud-prone Complex Landscapes At Multiple Spatial Scales Using Medium And High Resolution Optical Data: A Case Study In Central Africa

NASA Astrophysics Data System (ADS)

Basnet, Bikash

Tracking land surface dynamics over cloud-prone areas with complex mountainous terrain and a landscape that is heterogeneous at a scale of approximately 10 m, is an important challenge in the remote sensing of tropical regions in developing nations, due to the small plot sizes. Persistent monitoring of natural resources in these regions at multiple spatial scales requires development of tools to identify emerging land cover transformation due to anthropogenic causes, such as agricultural expansion and climate change. Along with the cloud cover and obstructions by topographic distortions due to steep terrain, there are limitations to the accuracy of monitoring change using available historical satellite imagery, largely due to sparse data access and the lack of high quality ground truth for classifier training. One such complex region is the Lake Kivu region in Central Africa. This work addressed these problems to create an effective process for monitoring the Lake Kivu region located in Central Africa. The Lake Kivu region is a biodiversity hotspot with a complex and heterogeneous landscape and intensive agricultural development, where individual plot sizes are often at the scale of 10m. Procedures were developed that use optical data from satellite and aerial observations at multiple scales to tackle the monitoring challenges. First, a novel processing chain was developed to systematically monitor the spatio-temporal land cover dynamics of this region over the years 1988, 2001, and 2011 using Landsat data, complemented by ancillary data. Topographic compensation was performed on Landsat reflectances to avoid the strong illumination angle impacts and image compositing was used to compensate for frequent cloud cover and thus incomplete annual data availability in the archive. A systematic supervised classification, using the state-of-the-art machine learning classifier Random Forest, was applied to the composite Landsat imagery to obtain land cover thematic maps with overall accuracies of 90% and higher. Subsequent change analysis between these years found extensive conversions of the natural environment as a result of human related activities. The gross forest cover loss for 1988--2001 and 2001--2011 periods was 216.4 and 130.5 thousand hectares, respectively, signifying significant deforestation in the period of civil war and a relatively stable and lower deforestation rate later, possibly due to conservation and reforestation efforts in the region. The other dominant land cover changes in the region were aggressive subsistence farming and urban expansion displacing natural vegetation and arable lands. Despite limited data availability, this study fills the gap of much needed detailed and updated land cover change information for this biologically important region of Central Africa. While useful on a regional scale, Landsat data can be inadequate for more detailed studies of land cover change. Based on an increasing availability of high resolution imagery and light detection and ranging (LiDAR) data from manned and unmanned aerial platforms (<1m resolution), a study was performed leading to a novel generic framework for land cover monitoring at fine spatial scales. The approach fuses high spatial resolution aerial imagery and LiDAR data to produce land cover maps with high spatial detail using object-based image analysis techniques. The classification framework was tested for a scene with both natural and cultural features and was found to be more than 90 percent accurate, sufficient for detailed land cover change studies.

The budget of biologically active ultraviolet radiation in the earth-atmosphere system

NASA Technical Reports Server (NTRS)

Frederick, John E.; Lubin, Dan

1988-01-01

This study applies the concept of a budget to describe the interaction of solar ultraviolet (UV) radiation with the earth-atmosphere system. The wavelength ranges of interest are the biologically relevant UV-B between 280 and 320 nm and the UV-A from 32000 to 400 nm. The Nimbus 7 solar backscattered ultraviolet (SBUV) instrument provides measurements of total column ozone and information concerning cloud cover which, in combination with a simple model of radiation transfer, define the fractions of incident solar irradiance absorbed in the atmosphere, reflected to space, and absorbed at the ground. Results for the month of July quantify the contribution of fractional cloud cover and cloud optical thickness to the radiation budget's three components. Scattering within a thick cloud layer makes the downward radiation field at the cloud base more isotropic than is the case for clear skies. For small solar zenith angles, typical of summer midday conditions, the effective pathlength of this diffuse irradiance through tropospheric ozone is greater than that under clear-sky conditions. The result is an enhanced absorption of UV-B radiation in the troposphere during cloud-covered conditions. Major changes in global cloud cover or cloud optical thicknesses could alter the ultraviolet radiation received by the biosphere by an amount comparable to that predicted for long-term trends in ozone.

The variability of California summertime marine stratus: impacts on surface air temperatures

USGS Publications Warehouse

Iacobellis, Sam F.; Cayan, Daniel R.

2013-01-01

This study investigates the variability of clouds, primarily marine stratus clouds, and how they are associated with surface temperature anomalies over California, especially along the coastal margin. We focus on the summer months of June to September when marine stratus are the dominant cloud type. Data used include satellite cloud reflectivity (cloud albedo) measurements, hourly surface observations of cloud cover and air temperature at coastal airports, and observed values of daily surface temperature at stations throughout California and Nevada. Much of the anomalous variability of summer clouds is organized over regional patterns that affect considerable portions of the coast, often extend hundreds of kilometers to the west and southwest over the North Pacific, and are bounded to the east by coastal mountains. The occurrence of marine stratus is positively correlated with both the strength and height of the thermal inversion that caps the marine boundary layer, with inversion base height being a key factor in determining their inland penetration. Cloud cover is strongly associated with surface temperature variations. In general, increased presence of cloud (higher cloud albedo) produces cooler daytime temperatures and warmer nighttime temperatures. Summer daytime temperature fluctuations associated with cloud cover variations typically exceed 1°C. The inversion-cloud albedo-temperature associations that occur at daily timescales are also found at seasonal timescales.

Using Space Lidar Observations to Decompose Longwave Cloud Radiative Effect Variations Over the Last Decade

NASA Astrophysics Data System (ADS)

Vaillant de Guélis, Thibault; Chepfer, Hélène; Noel, Vincent; Guzman, Rodrigo; Winker, David M.; Plougonven, Riwal

2017-12-01

Measurements of the longwave cloud radiative effect (LWCRE) at the top of the atmosphere assess the contribution of clouds to the Earth warming but do not quantify the cloud property variations that are responsible for the LWCRE variations. The CALIPSO space lidar observes directly the detailed profile of cloud, cloud opacity, and cloud cover. Here we use these observations to quantify the influence of cloud properties on the variations of the LWCRE observed between 2008 and 2015 in the tropics and at global scale. At global scale, the method proposed here gives good results except over the Southern Ocean. We find that the global LWCRE variations observed over ocean are mostly due to variations in the opaque cloud properties (82%); transparent cloud columns contributed 18%. Variation of opaque cloud cover is the first contributor to the LWCRE evolution (58%); opaque cloud temperature is the second contributor (28%).

A 350 Year Cloud Cover Reconstruction Deduced from Caribbean Coral Proxies

NASA Astrophysics Data System (ADS)

Winter, Amos; Sammarco, Paul; Mikolajewicz, Uwe; Jury, Mark; Zanchettin, Davide

2015-04-01

Clouds are a major factor contributing to climate change with respect to a variety of effects on the earth's climates, primarily radiative effects, amelioration of heating, and regional changes in precipitation patterns. There have been very few studies of decadal and longer term changes in cloud cover in the tropics and sub-tropics, both over land and the ocean. In the tropics, there is great uncertainty regarding how global warming will affect cloud cover. Observational satellite data is so short that it is difficult to discern any temporal trends. The skeletons of scleractinian corals are considered to contain among the best records of high-resolution (sub-annual) environmental variability in the tropical and sub-tropical oceans. Corals generally live in well-mixed coastal regions and can often record environmental conditions of large areas of the upper ocean. This is particularly the case at low latitudes. Scleractinian corals are sessile, epibenthic fauna, and the type of environmental information recorded at the location where the coral has been living is dependent upon the species of coral considered and proxy index of interest. Zooxanthellate hermatypic corals in tropical and sub-tropical seas precipitate CaCO3 skeletons as they grow. This growth is made possible through the manufacture of CaCO3 crystals, facilitated by the zooxanthellae. During the process of crystallization, the holobiont binds carbon of different isotopes into the crystals. Stable carbon isotope concentrations vary with a variety of environmental conditions. In the Caribbean, δ13C in corals of the species Montastraea faveolata can be used as a proxy for changes in cloud cover. In this contribution, we will demonstrate that the stable isotope 13C varies concomitantly with cloud cover and present a new reconstruction of cloud cover over the Caribbean Sea that extends back to the year 1760. We will show that there is good agreement between the main features of our coral proxy record of cloud cover and of reanalysis and climate simulations for the same time period.

Some new worldwide cloud-cover models

NASA Technical Reports Server (NTRS)

Bean, S. J.; Somerville, P. N.

1981-01-01

Using daily measurements of day and night infrared, and incoming and absorbed solar radiation obtained from a Tiros satellite over a period of approximately 45 months, and integrated over 2.5 deg latitude-longitude grids, the proportion of cloud cover over each grid each day was derived for the entire period. For each of four 3-month periods, for each grid location, estimates a and b of the two parameters of the best-fit beta distribution were obtained. The (a, b) plane was divided into a number of regions. All the geographical locations whose (a, b) estimates were in the same region in the (a, b) plane were said to have the same cloud cover type for that season. For each season, the world is thus divided into separate cloud-cover types.

Cloud types and the tropical Earth radiation budget, revised

NASA Technical Reports Server (NTRS)

Dhuria, Harbans L.; Kyle, H. Lee

1989-01-01

Nimbus-7 cloud and Earth radiation budget data are compared in a study of the effects of clouds on the tropical radiation budget. The data consist of daily averages over fixed 500 sq km target areas, and the months of July 1979 and January 1980 were chosen to show the effect of seasonal changes. Six climate regions, consisting of 14 to 24 target areas each, were picked for intensive analysis because they exemplified the range in the tropical cloud/net radiation interactions. The normal analysis was to consider net radiation as the independent variable and examine how cloud cover, cloud type, albedo and emitted radiation varied with the net radiation. Two recurring themes keep repeating on a local, regional, and zonal basis: the net radiation is strongly influenced by the average cloud type and amount present, but most net radiation values could be produced by several combinations of cloud types and amount. The regions of highest net radiation (greater than 125 W/sq m) tend to have medium to heavy cloud cover. In these cases, thin medium altitude clouds predominate. Their cloud tops are normally too warm to be classified as cirrus by the Nimbus cloud algorithm. A common feature in the tropical oceans are large regions where the total regional cloud cover varies from 20 to 90 percent, but with little regional difference in the net radiation. The monsoon and rain areas are high net radiation regions.

Intercomparison of cloud model simulations of Arctic mixed-phase boundary layer clouds observed during SHEBA/FIRE-ACE

DOE Office of Scientific and Technical Information (OSTI.GOV)

Morrison, H.; Zuidema, Paquita; Ackerman, Andrew

2011-06-16

An intercomparison of six cloud-resolving and large-eddy simulation models is presented. This case study is based on observations of a persistent mixed-phase boundary layer cloud gathered on 7 May, 1998 from the Surface Heat Budget of Arctic Ocean (SHEBA) and First ISCCP Regional Experiment - Arctic Cloud Experiment (FIRE-ACE). Ice nucleation is constrained in the simulations in a way that holds the ice crystal concentration approximately fixed, with two sets of sensitivity runs in addition to the baseline simulations utilizing different specified ice nucleus (IN) concentrations. All of the baseline and sensitivity simulations group into two distinct quasi-steady states associatedmore » with either persistent mixed-phase clouds or all-ice clouds after the first few hours of integration, implying the existence of multiple equilibria. These two states are associated with distinctly different microphysical, thermodynamic, and radiative characteristics. Most but not all of the models produce a persistent mixed-phase cloud qualitatively similar to observations using the baseline IN/crystal concentration, while small increases in the IN/crystal concentration generally lead to rapid glaciation and conversion to the all-ice state. Budget analysis indicates that larger ice deposition rates associated with increased IN/crystal concentrations have a limited direct impact on dissipation of liquid in these simulations. However, the impact of increased ice deposition is greatly enhanced by several interaction pathways that lead to an increased surface precipitation flux, weaker cloud top radiative cooling and cloud dynamics, and reduced vertical mixing, promoting rapid glaciation of the mixed-phase cloud for deposition rates in the cloud layer greater than about 1-2x10-5 g kg-1 s-1. These results indicate the critical importance of precipitation-radiative-dynamical interactions in simulating cloud phase, which have been neglected in previous fixed-dynamical parcel studies of the cloud phase parameter space. Large sensitivity to the IN/crystal concentration also suggests the need for improved understanding of ice nucleation and its parameterization in models.« less

Daytime Cloud Property Retrievals Over the Arctic from Multispectral MODIS Data

NASA Technical Reports Server (NTRS)

Spangenberg, Douglas A.; Trepte, Qing; Minnis, Patrick; Uttal, Taneil

2004-01-01

Improving climate model predictions over Earth's polar regions requires a complete understanding of polar clouds properties. Passive satellite remote sensing techniques can be used to retrieve macro and microphysical properties of polar cloud systems. However, over the Arctic, there is minimal contrast between clouds and the background snow surface observed in satellite data, especially for visible wavelengths. This makes it difficult to identify clouds and retrieve their properties from space. Variable snow and ice cover, temperature inversions, and the predominance of mixed-phase clouds further complicate cloud property identification. For this study, the operational Clouds and the Earth s Radiant Energy System (CERES) cloud mask is first used to discriminate clouds from the background surface in Terra Moderate Resolution Imaging Spectroradiometer (MODIS) data. A solar-infrared infrared nearinfrared technique (SINT) first used by Platnick et al. (2001) is used here to retrieve cloud properties over snow and ice covered regions.

Evaluation and Applications of Cloud Climatologies from CALIOP

NASA Technical Reports Server (NTRS)

Winker, David; Getzewitch, Brian; Vaughan, Mark

2008-01-01

Clouds have a major impact on the Earth radiation budget and differences in the representation of clouds in global climate models are responsible for much of the spread in predicted climate sensitivity. Existing cloud climatologies, against which these models can be tested, have many limitations. The CALIOP lidar, carried on the CALIPSO satellite, has now acquired over two years of nearly continuous cloud and aerosol observations. This dataset provides an improved basis for the characterization of 3-D global cloudiness. Global average cloud cover measured by CALIOP is about 75%, significantly higher than for existing cloud climatologies due to the sensitivity of CALIOP to optically thin cloud. Day/night biases in cloud detection appear to be small. This presentation will discuss detection sensitivity and other issues associated with producing a cloud climatology, characteristics of cloud cover statistics derived from CALIOP data, and applications of those statistics.

A Study of the Role of Clouds in the Relationship Between Land Use/Land Cover and the Climate and Air Quality of the Atlanta Area

NASA Technical Reports Server (NTRS)

Kidder, Stanley Q.; Hafner, Jan

2001-01-01

The goal of Project ATLANTA is to derive a better scientific understanding of how land cover changes associated with urbanization affect climate and air quality. In this project the role that clouds play in this relationship was studied. Through GOES satellite observations and RAMS modeling of the Atlanta area, we found that in Atlanta (1) clouds are more frequent than in the surrounding rural areas; (2) clouds cool the surface by shading and thus tend to counteract the warming effect of urbanization; (3) clouds reflect sunlight, which might other wise be used to produce ozone; and (4) clouds decrease biogenic emission of ozone precursors, and they probably decrease ozone concentration. We also found that mesoscale modeling of clouds, especially of small, summertime clouds, needs to be improved and that coupled mesoscale and air quality models are needed to completely understand the mediating role that clouds play in the relationship between land use/land cover change and the climate and air quality of Atlanta. It is strongly recommended that more cities be studied to strengthen and extend these results.

Separating Real and Apparent Effects of Cloud, Humidity, and Dynamics on Aerosol Optical Thickness near Cloud Edges

NASA Technical Reports Server (NTRS)

Jeong, Myeong-Jae; Li, Zhanqing

2010-01-01

Aerosol optical thickness (AOT) is one of aerosol parameters that can be measured on a routine basis with reasonable accuracy from Sun-photometric observations at the surface. However, AOT-derived near clouds is fraught with various real effects and artifacts, posing a big challenge for studying aerosol and cloud interactions. Recently, several studies have reported correlations between AOT and cloud cover, pointing to potential cloud contamination and the aerosol humidification effect; however, not many quantitative assessments have been made. In this study, various potential causes of apparent correlations are investigated in order to separate the real effects from the artifacts, using well-maintained observations from the Aerosol Robotic Network, Total Sky Imager, airborne nephelometer, etc., over the Southern Great Plains site operated by the U.S. Department of Energy's Atmospheric Radiation Measurement Program. It was found that aerosol humidification effects can explain about one fourth of the correlation between the cloud cover and AOT. New particle genesis, cloud-processed particles, atmospheric dynamics, and aerosol indirect effects are likely to be contributing to as much as the remaining three fourth of the relationship between cloud cover and AOT.

Antarctica Cloud Cover for October 2003 from GLAS Satellite Lidar Profiling

NASA Technical Reports Server (NTRS)

Spinhirne, J. D.; Palm, S. P.; Hart, W. D.

2005-01-01

Seeing clouds in polar regions has been a problem for the imagers used on satellites. Both clouds and snow and ice are white, which makes clouds over snow hard to see. And for thermal infrared imaging both the surface and the clouds cold. The Geoscience Laser Altimeter System (GLAS) launched in 2003 gives an entirely new way to see clouds from space. Pulses of laser light scatter from clouds giving a signal that is separated in time from the signal from the surface. The scattering from clouds is thus a sensitive and direct measure of the presence and height of clouds. The GLAS instrument orbits over Antarctica 16 times a day. All of the cloud observations for October 2003 were summarized and compared to the results from the MODIS imager for the same month. There are two basic cloud types that are observed, low stratus with tops below 3 km and high cirrus form clouds with cloud top altitude and thickness tending at 12 km and 1.3 km respectively. The average cloud cover varies from over 93 % for ocean and coastal regions to an average of 40% over the East Antarctic plateau and 60-90% over West Antarctica. When the GLAS monthly average cloud fractions are compared to the MODIS cloud fraction data product, differences in the amount of cloud cover are as much as 40% over the continent. The results will be used to improve the way clouds are detected from the imager observations. These measurements give a much improved understanding of distribution of clouds over Antarctica and may show how they are changing as a result of global warming.

The Potential Impact of Satellite-Retrieved Cloud Parameters on Ground-Level PM2.5 Mass and Composition

PubMed Central

Chang, Howard H.; Wang, Yujie; Hu, Xuefei; Lyapustin, Alexei

2017-01-01

Satellite-retrieved aerosol optical properties have been extensively used to estimate ground-level fine particulate matter (PM2.5) concentrations in support of air pollution health effects research and air quality assessment at the urban to global scales. However, a large proportion, ~70%, of satellite observations of aerosols are missing as a result of cloud-cover, surface brightness, and snow-cover. The resulting PM2.5 estimates could therefore be biased due to this non-random data missingness. Cloud-cover in particular has the potential to impact ground-level PM2.5 concentrations through complex chemical and physical processes. We developed a series of statistical models using the Multi-Angle Implementation of Atmospheric Correction (MAIAC) aerosol product at 1 km resolution with information from the MODIS cloud product and meteorological information to investigate the extent to which cloud parameters and associated meteorological conditions impact ground-level aerosols at two urban sites in the US: Atlanta and San Francisco. We find that changes in temperature, wind speed, relative humidity, planetary boundary layer height, convective available potential energy, precipitation, cloud effective radius, cloud optical depth, and cloud emissivity are associated with changes in PM2.5 concentration and composition, and the changes differ by overpass time and cloud phase as well as between the San Francisco and Atlanta sites. A case-study at the San Francisco site confirmed that accounting for cloud-cover and associated meteorological conditions could substantially alter the spatial distribution of monthly ground-level PM2.5 concentrations. PMID:29057838

The Potential Impact of Satellite-Retrieved Cloud Parameters on Ground-Level PM2.5 Mass and Composition

NASA Technical Reports Server (NTRS)

Belle, Jessica H.; Chang, Howard H.; Wang, Yujie; Hu, Xuefei; Lyapustin, Alexei; Liu, Yang

2017-01-01

Satellite-retrieved aerosol optical properties have been extensively used to estimate ground-level fine particulate matter (PM2.5) concentrations in support of air pollution health effects research and air quality assessment at the urban to global scales. However, a large proportion, approximately 70%, of satellite observations of aerosols are missing as a result of cloud-cover, surface brightness, and snow-cover. The resulting PM2.5 estimates could therefore be biased due to this non-random data missingness. Cloud-cover in particular has the potential to impact ground-level PM2.5 concentrations through complex chemical and physical processes. We developed a series of statistical models using the Multi-Angle Implementation of Atmospheric Correction (MAIAC) aerosol product at 1 km resolution with information from the MODIS cloud product and meteorological information to investigate the extent to which cloud parameters and associated meteorological conditions impact ground-level aerosols at two urban sites in the US: Atlanta and San Francisco. We find that changes in temperature, wind speed, relative humidity, planetary boundary layer height, convective available potential energy, precipitation, cloud effective radius, cloud optical depth, and cloud emissivity are associated with changes in PM2.5 concentration and composition, and the changes differ by overpass time and cloud phase as well as between the San Francisco and Atlanta sites. A case-study at the San Francisco site confirmed that accounting for cloud-cover and associated meteorological conditions could substantially alter the spatial distribution of monthly ground-level PM2.5 concentrations.

The Potential Impact of Satellite-Retrieved Cloud Parameters on Ground-Level PM2.5 Mass and Composition.

PubMed

Belle, Jessica H; Chang, Howard H; Wang, Yujie; Hu, Xuefei; Lyapustin, Alexei; Liu, Yang

2017-10-18

Satellite-retrieved aerosol optical properties have been extensively used to estimate ground-level fine particulate matter (PM 2.5 ) concentrations in support of air pollution health effects research and air quality assessment at the urban to global scales. However, a large proportion, ~70%, of satellite observations of aerosols are missing as a result of cloud-cover, surface brightness, and snow-cover. The resulting PM 2.5 estimates could therefore be biased due to this non-random data missingness. Cloud-cover in particular has the potential to impact ground-level PM 2.5 concentrations through complex chemical and physical processes. We developed a series of statistical models using the Multi-Angle Implementation of Atmospheric Correction (MAIAC) aerosol product at 1 km resolution with information from the MODIS cloud product and meteorological information to investigate the extent to which cloud parameters and associated meteorological conditions impact ground-level aerosols at two urban sites in the US: Atlanta and San Francisco. We find that changes in temperature, wind speed, relative humidity, planetary boundary layer height, convective available potential energy, precipitation, cloud effective radius, cloud optical depth, and cloud emissivity are associated with changes in PM 2.5 concentration and composition, and the changes differ by overpass time and cloud phase as well as between the San Francisco and Atlanta sites. A case-study at the San Francisco site confirmed that accounting for cloud-cover and associated meteorological conditions could substantially alter the spatial distribution of monthly ground-level PM 2.5 concentrations.

The variation of cloud amount and light rainy days under heavy pollution over South China during 1960-2009.

PubMed

Fu, Chuanbo; Dan, Li

2018-01-01

The ground observation data was used to analyze the variation of cloud amount and light precipitation over South China during 1960-2009. The total cloud cover (TCC) decreases in this period, whereas the low cloud cover (LCC) shows the obvious opposite change with increasing trends. LCP defined as low cloud cover/total cloud cover has increased, and small rainy days (< 10 mm day -1 ) decreased significantly (passing 0.001 significance level) during the past 50 years, which is attributed to the enhanced levels of air pollution in the form of anthropogenic aerosols. The horizontal visibility and sunshine duration are used to depict the anthropogenic aerosol loading. When horizontal visibility declines to 20 km or sunshine duration decreases to 5 h per day, LCC increases 52% or more and LCP increases significantly. The correlation coefficients between LCC and horizontal visibility or sunshine duration are - 0.533 and - 0.927, and the values between LCP and horizontal visibility or sunshine duration are - 0.849 and - 0.641, which pass 0.001 significance level. The results indicated that aerosols likely impacted the long-term trend of cloud amount and light precipitation over South China.

A View of Earth's Aerosol System from Space to Your Office Chair

NASA Technical Reports Server (NTRS)

Colarco, Peter

2008-01-01

Aerosols are tiny particles and droplets suspended in the air. Each day you breathe in about 10 billion of them, about a half a million per breath. They are formed in nature by volcanoes, dust storms, sea spray, and emissions from vegetation. Humans create aerosols and alter their natural sources by burning fossil fuels and modifying land cover. Fires are another important source of aerosols; some are natural, such as wildfires started by lightning strikes, while others are from human-caused burning of vegetation for cooking, heating, and land clearing. Aerosols have complex effects on Earth's climate. In general, they cool the surface by reflecting (scattering) radiation from the sun back into space. Dust and smoke absorb solar radiation and heat the atmosphere where they are concentrated. Aerosols change the properties of clouds. Indeed, it would be very difficult to form clouds in the atmosphere without aerosols to act as 'seeds' for water to condense on. In aerosol polluted environments clouds tend to have smaller droplets than clouds formed in cleaner environments; these polluted clouds appear brighter from space because they reflect more sunlight, and they may persist longer and not rain as intensely. Aerosols also affect local air quality and visibility. Data collected by NASA satellites over the past decade have provided an unprecedented view of Earth's aerosol distribution and dramatically increased our understanding of where aerosols come from and just how far they travel in the atmosphere. In this talk I will discuss observations of aerosols from space and how they inform numerical transport models attempting to simulate the global aerosol system.

Microphysical effects determine macrophysical response for aerosol impacts on deep convective clouds

NASA Astrophysics Data System (ADS)

Fan, Jiwen; Leung, L. Ruby; Rosenfeld, Daniel; Chen, Qian; Li, Zhanqing; Zhang, Jinqiang; Yan, Hongru

2013-11-01

Deep convective clouds (DCCs) play a crucial role in the general circulation, energy, and hydrological cycle of our climate system. Aerosol particles can influence DCCs by altering cloud properties, precipitation regimes, and radiation balance. Previous studies reported both invigoration and suppression of DCCs by aerosols, but few were concerned with the whole life cycle of DCC. By conducting multiple monthlong cloud-resolving simulations with spectral-bin cloud microphysics that capture the observed macrophysical and microphysical properties of summer convective clouds and precipitation in the tropics and midlatitudes, this study provides a comprehensive view of how aerosols affect cloud cover, cloud top height, and radiative forcing. We found that although the widely accepted theory of DCC invigoration due to aerosol's thermodynamic effect (additional latent heat release from freezing of greater amount of cloud water) may work during the growing stage, it is microphysical effect influenced by aerosols that drives the dramatic increase in cloud cover, cloud top height, and cloud thickness at the mature and dissipation stages by inducing larger amounts of smaller but longer-lasting ice particles in the stratiform/anvils of DCCs, even when thermodynamic invigoration of convection is absent. The thermodynamic invigoration effect contributes up to ∼27% of total increase in cloud cover. The overall aerosol indirect effect is an atmospheric radiative warming (3-5 Wṡm-2) and a surface cooling (-5 to -8 Wṡm-2). The modeling findings are confirmed by the analyses of ample measurements made at three sites of distinctly different environments.

Microphysical effects determine macrophysical response for aerosol impacts on deep convective clouds.

PubMed

Fan, Jiwen; Leung, L Ruby; Rosenfeld, Daniel; Chen, Qian; Li, Zhanqing; Zhang, Jinqiang; Yan, Hongru

2013-11-26

Deep convective clouds (DCCs) play a crucial role in the general circulation, energy, and hydrological cycle of our climate system. Aerosol particles can influence DCCs by altering cloud properties, precipitation regimes, and radiation balance. Previous studies reported both invigoration and suppression of DCCs by aerosols, but few were concerned with the whole life cycle of DCC. By conducting multiple monthlong cloud-resolving simulations with spectral-bin cloud microphysics that capture the observed macrophysical and microphysical properties of summer convective clouds and precipitation in the tropics and midlatitudes, this study provides a comprehensive view of how aerosols affect cloud cover, cloud top height, and radiative forcing. We found that although the widely accepted theory of DCC invigoration due to aerosol's thermodynamic effect (additional latent heat release from freezing of greater amount of cloud water) may work during the growing stage, it is microphysical effect influenced by aerosols that drives the dramatic increase in cloud cover, cloud top height, and cloud thickness at the mature and dissipation stages by inducing larger amounts of smaller but longer-lasting ice particles in the stratiform/anvils of DCCs, even when thermodynamic invigoration of convection is absent. The thermodynamic invigoration effect contributes up to ~27% of total increase in cloud cover. The overall aerosol indirect effect is an atmospheric radiative warming (3-5 W m(-2)) and a surface cooling (-5 to -8 W m(-2)). The modeling findings are confirmed by the analyses of ample measurements made at three sites of distinctly different environments.

Decreasing cloud cover drives the recent mass loss on the Greenland Ice Sheet.

PubMed

Hofer, Stefan; Tedstone, Andrew J; Fettweis, Xavier; Bamber, Jonathan L

2017-06-01

The Greenland Ice Sheet (GrIS) has been losing mass at an accelerating rate since the mid-1990s. This has been due to both increased ice discharge into the ocean and melting at the surface, with the latter being the dominant contribution. This change in state has been attributed to rising temperatures and a decrease in surface albedo. We show, using satellite data and climate model output, that the abrupt reduction in surface mass balance since about 1995 can be attributed largely to a coincident trend of decreasing summer cloud cover enhancing the melt-albedo feedback. Satellite observations show that, from 1995 to 2009, summer cloud cover decreased by 0.9 ± 0.3% per year. Model output indicates that the GrIS summer melt increases by 27 ± 13 gigatons (Gt) per percent reduction in summer cloud cover, principally because of the impact of increased shortwave radiation over the low albedo ablation zone. The observed reduction in cloud cover is strongly correlated with a state shift in the North Atlantic Oscillation promoting anticyclonic conditions in summer and suggests that the enhanced surface mass loss from the GrIS is driven by synoptic-scale changes in Arctic-wide atmospheric circulation.

Improved cloud parameterization for Arctic climate simulations based on satellite data

NASA Astrophysics Data System (ADS)

Klaus, Daniel; Dethloff, Klaus; Dorn, Wolfgang; Rinke, Annette

2015-04-01

The defective representation of Arctic cloud processes and properties remains a crucial problem in climate modelling and in reanalysis products. Satellite-based cloud observations (MODIS and CPR/CALIOP) and single-column model simulations (HIRHAM5-SCM) were exploited to evaluate and improve the simulated Arctic cloud cover of the atmospheric regional climate model HIRHAM5. The ECMWF reanalysis dataset 'ERA-Interim' (ERAint) was used for the model initialization, the lateral boundary forcing as well as the dynamical relaxation inside the pan-Arctic domain. HIRHAM5 has a horizontal resolution of 0.25° and uses 40 pressure-based and terrain-following vertical levels. In comparison with the satellite observations, the HIRHAM5 control run (HH5ctrl) systematically overestimates total cloud cover, but to a lesser extent than ERAint. The underestimation of high- and mid-level clouds is strongly outweighed by the overestimation of low-level clouds. Numerous sensitivity studies with HIRHAM5-SCM suggest (1) the parameter tuning, enabling a more efficient Bergeron-Findeisen process, combined with (2) an extension of the prognostic-statistical (PS) cloud scheme, enabling the use of negatively skewed beta distributions. This improved model setup was then used in a corresponding HIRHAM5 sensitivity run (HH5sens). While the simulated high- and mid-level cloud cover is improved only to a limited extent, the large overestimation of low-level clouds can be systematically and significantly reduced, especially over sea ice. Consequently, the multi-year annual mean area average of total cloud cover with respect to sea ice is almost 14% lower than in HH5ctrl. Overall, HH5sens slightly underestimates the observed total cloud cover but shows a halved multi-year annual mean bias of 2.2% relative to CPR/CALIOP at all latitudes north of 60° N. Importantly, HH5sens produces a more realistic ratio between the cloud water and ice content. The considerably improved cloud simulation manifests in a more correct radiative transfer and better energy budget in the atmospheric boundary layer and results also in a more realistic surface energy budget associated with more reasonable turbulent fluxes. All this mitigates the positive temperature, relative humidity and horizontal wind speed biases in the lower model levels.

Cloud cover determination in polar regions from satellite imagery

NASA Technical Reports Server (NTRS)

Barry, R. G.; Key, J. R.; Maslanik, J. A.

1988-01-01

The principal objectives of this project are: to develop suitable validation data sets to evaluate the effectiveness of the ISCCP operational algorithm for cloud retrieval in polar regions and to validate model simulations of polar cloud cover; to identify limitations of current procedures for varying atmospheric surface conditions, and to explore potential means to remedy them using textural classifiers: and to compare synoptic cloud data from a control run experiment of the Goddard Institute for Space Studies (GISS) climate model 2 with typical observed synoptic cloud patterns. Current investigations underway are listed and the progress made to date is summarized.

A Battlefield Obscuration Model (Smoke & Dust)

DTIC Science & Technology

1979-10-01

ia £ utace of clouds, izsclacioon (incoming radiation) during :he day ts dependent upon solar ali.::ude, which is a fuc nof time of: d&7 and time of...year. ’Irnn clouds exisc, chai~r cover and :b*ickness decrease incoming and ouzgoingS radiation. Z-a this syscea iasola:ion ts estimated b7 solar ...alzictude and =odi44ed -or existing condi:±ons of total cloud cover and cloud ceiling height. kc zig~ic, estimates of oucgoing radiacion are =ade by

Cloud Forecast Simulation Model.

DTIC Science & Technology

1981-10-01

creasing the kurtosis of the distribution, i.e., making it more negative (more platykurtic ). Case (a) might be the distribution of forecast cloud cover be...fore smoothing, and (b) might be the distribution after smoothing. Character- istically, smoothing makes cloud cover distributions less platykurtic ...19, this effect of smoothing can be described in terms of making the smoothed distribu- tion less platykurtic than the unsmoothed distribution

Cloud Response to Arctic Sea Ice Loss and Implications for Feedbacks in the CESM1 Climate Model

NASA Astrophysics Data System (ADS)

Morrison, A.; Kay, J. E.; Chepfer, H.; Guzman, R.; Bonazzola, M.

2017-12-01

Clouds have the potential to accelerate or slow the rate of Arctic sea ice loss through their radiative influence on the surface. Cloud feedbacks can therefore play into Arctic warming as clouds respond to changes in sea ice cover. As the Arctic moves toward an ice-free state, understanding how cloud - sea ice relationships change in response to sea ice loss is critical for predicting the future climate trajectory. From satellite observations we know the effect of present-day sea ice cover on clouds, but how will clouds respond to sea ice loss as the Arctic transitions to a seasonally open water state? In this study we use a lidar simulator to first evaluate cloud - sea ice relationships in the Community Earth System Model (CESM1) against present-day observations (2006-2015). In the current climate, the cloud response to sea ice is well-represented in CESM1: we see no summer cloud response to changes in sea ice cover, but more fall clouds over open water than over sea ice. Since CESM1 is credible for the current Arctic climate, we next assess if our process-based understanding of Arctic cloud feedbacks related to sea ice loss is relevant for understanding future Arctic clouds. In the future Arctic, summer cloud structure continues to be insensitive to surface conditions. As the Arctic warms in the fall, however, the boundary layer deepens and cloud fraction increases over open ocean during each consecutive decade from 2020 - 2100. This study will also explore seasonal changes in cloud properties such as opacity and liquid water path. Results thus far suggest that a positive fall cloud - sea ice feedback exists in the present-day and future Arctic climate.

Evolution of surface sensible heat over the Tibetan Plateau under the recent global warming hiatus

NASA Astrophysics Data System (ADS)

Zhu, Lihua; Huang, Gang; Fan, Guangzhou; Qu, Xia; Zhao, Guijie; Hua, Wei

2017-10-01

Based on regular surface meteorological observations and NCEP/DOE reanalysis data, this study investigates the evolution of surface sensible heat (SH) over the central and eastern Tibetan Plateau (CE-TP) under the recent global warming hiatus. The results reveal that the SH over the CE-TP presents a recovery since the slowdown of the global warming. The restored surface wind speed together with increased difference in ground-air temperature contribute to the recovery in SH. During the global warming hiatus, the persistent weakening wind speed is alleviated due to the variation of the meridional temperature gradient. Meanwhile, the ground surface temperature and the difference in ground-air temperature show a significant increasing trend in that period caused by the increased total cloud amount, especially at night. At nighttime, the increased total cloud cover reduces the surface effective radiation via a strengthening of atmospheric counter radiation and subsequently brings about a clear upward trend in ground surface temperature and the difference in ground-air temperature. Cloud-radiation feedback plays a significant role in the evolution of the surface temperature and even SH during the global warming hiatus. Consequently, besides the surface wind speed, the difference in ground-air temperature becomes another significant factor for the variation in SH since the slowdown of global warming, particularly at night.

Relevance of long term time - Series of atmospheric parameters at a mountain observatory to models for climate change

NASA Astrophysics Data System (ADS)

Kancírová, M.; Kudela, K.; Erlykin, A. D.; Wolfendale, A. W.

2016-10-01

A detailed analysis has been made based on annual meteorological and cosmic ray data from the Lomnicky stit mountain observatory (LS, 2634 masl; 49.40°N, 20.22°E; vertical cut-off rigidity 3.85 GV), from the standpoint of looking for possible solar cycle (including cosmic ray) manifestations. A comparison of the mountain data with the Global average for the cloud cover in general shows no correlation but there is a possible small correlation for low clouds (LCC in the Global satellite data). However, whereas it cannot be claimed that cloud cover observed at Lomnicky stit (LSCC) can be used directly as a proxy for the Global LCC, its examination has value because it is an independent estimate of cloud cover and one that has a different altitude weighting to that adopted in the satellite-derived LCC. This statement is derived from satellite data (http://isccp.giss.nasa.gov/climanal7.html) which shows the time series for the period 1983-2010 for 9 cloud regimes. There is a significant correlation only between cosmic ray (CR) intensity (and sunspot number (SSN)) and the cloud cover of the types cirrus and stratus. This effect is mainly confined to the CR intensity minimum during the epoch around 1990, when the SSN was at its maximum. This fact, together with the present study of the correlation of LSCC with our measured CR intensity, shows that there is no firm evidence for a significant contribution of CR induced ionization to the local (or, indeed, Global) cloud cover. Pressure effects are the preferred cause of the cloud cover changes. A consequence is that there is no evidence favouring a contribution of CR to the Global Warming problem. Our analysis shows that the LS data are consistent with the Gas Laws for a stable mass of atmosphere.

More Frequent Cloud Free Sky and Less Surface Solar Radiation in China from 1955-2000

NASA Technical Reports Server (NTRS)

Qian, Yun; Kaiser, Dale P.; Leung, L. Ruby; Xu, Ming

2006-01-01

In this study, we used newly available data frorn extended weather stations and time period to reveal that much of China has experienced significant decreases in cloud cover over the last half of the Twentieth century. This conclusion is supported by analysis of the more reliably observed frequency of cloud-free sky and overcast sky. We estimated that the total cloud cover and low cloud cover in China have decreased 0.88% and 0.33% per decade, respectively, and cloud-free days have increased 0.60% and overcast days decreased 0.78% per decade from 1954-2001. Meanwhile, both solar radiation and pan evaporation have decreased in China, with'solar radiation decreasing 3.1 w/square m and pan evaporation decreasing 39 mm per decade. Combining these results with findings of previous studies, we speculated that increased air pollution may have produced a fog-like haze that reflected/absorbed radiation from the sun and resulted in less solar radiation reaching the surface, despite concurrent increasing trends in cloud-free sky over China.

The cloud-radiative processes and its modulation by sea-ice cover and stability as derived from a merged C3M Data product.

NASA Astrophysics Data System (ADS)

Nag, B.

2016-12-01

The polar regions of the world constitute an important sector in the global energy balance. Among other effects responsible for the change in the sea-ice cover like ocean circulation and ice-albedo feedback, the cloud-radiation feedback also plays a vital role in modulation of the Arctic environment. However the annual cycle of the clouds is very poorly represented in current global circulation models. This study aims to take advantage of a merged C3M data (CALIPSO, CloudSat, CERES, and MODIS) product from the NASA's A-Train Series to explore the sea-ice and atmospheric conditions in the Arctic on a spatial coverage spanning 70N to 80N. This study is aimed at the interactions or the feedbacks processes among sea-ice, clouds and the atmosphere. Using a composite approach based on a classification due to surface type, it is found that limitation of the water vapour influx from the surface due to change in phase at the surface featuring open oceans or marginal sea-ice cover to complete sea-ice cover is a major determinant in the modulation of the atmospheric moisture and its impacts. The impact of the cloud-radiative effects in the Arctic is found to vary with sea-ice cover and seasonally. The effect of the marginal sea-ice cover becomes more and more pronounced in the winter. The seasonal variation of the dependence of the atmospheric moisture on the surface and the subsequent feedback effects is controlled by the atmospheric stability measured as a difference between the potential temperature at the surface and the 700hPa level. It is found that a stronger stability cover in the winter is responsible for the longwave cloud radiative feedback in winter which is missing during the summer. A regional analysis of the same suggests that most of the depiction of the variations observed is contributed from the North Atlantic region.

Cloud Detection by Fusing Multi-Scale Convolutional Features

NASA Astrophysics Data System (ADS)

Li, Zhiwei; Shen, Huanfeng; Wei, Yancong; Cheng, Qing; Yuan, Qiangqiang

2018-04-01

Clouds detection is an important pre-processing step for accurate application of optical satellite imagery. Recent studies indicate that deep learning achieves best performance in image segmentation tasks. Aiming at boosting the accuracy of cloud detection for multispectral imagery, especially for those that contain only visible and near infrared bands, in this paper, we proposed a deep learning based cloud detection method termed MSCN (multi-scale cloud net), which segments cloud by fusing multi-scale convolutional features. MSCN was trained on a global cloud cover validation collection, and was tested in more than ten types of optical images with different resolution. Experiment results show that MSCN has obvious advantages over the traditional multi-feature combined cloud detection method in accuracy, especially when in snow and other areas covered by bright non-cloud objects. Besides, MSCN produced more detailed cloud masks than the compared deep cloud detection convolution network. The effectiveness of MSCN make it promising for practical application in multiple kinds of optical imagery.

MISR RICO Products

Atmospheric Science Data Center

2016-11-25

... microphysics of the transition to a mature rainshaft, organization of trade wind clouds, water budget of trade wind cumulus, and the ... (MISR) mission objectives involve providing accurate information on cloud cover, cloud-track winds, stereo-derived cloud-top ...

Hydro-meteorological functioning of the Eastern Andean Tropical Montane Cloud Forests: Insight from a paired catchment study in the Orinoco river basin highlands

NASA Astrophysics Data System (ADS)

Ramirez, Beatriz; Teuling, Adriaan J.; Ganzeveld, Laurens; Leemans, Rik

2016-04-01

Tropical forests regulate large scale precipitation patterns and catchment-scale streamflow, while tropical mountains influence runoff by orographic effects and snowmelt. Along tropical elevation gradients, these climate/ecosystem/hydrological interactions are specific and heterogeneous. These interactions are poorly understood and represented in hydro-meteorological monitoring networks and regional or global earth system models. A typical case are the South American Tropical Montane Cloud Forests (TMCF), whose water balance is strongly driven by fog persistence. This also depends on local and up wind temperature and moisture, and changes in this balance alter the impacts of changes in land use and climate on hydrology. These TMCFs were until 2010 only investigated up to 350km from the coast. Continental TMCFs are largely ignored. This gap is covered by our study area, which is part of the Orinoco river basin highlands and located on the northern Eastern Andes at an altitudinal range of 1550 to 2300m a.s.l. The upwind part of our study area is dominated by lowland savannahs that are flooded seasonally. Because meteorological stations are absent in our study area, we first describe the spatial and seasonal meteorological variability and analyse the corresponding catchment hydrology. Our hydro-meteorological data set is collected at three gauged neighbouring catchments with contrasting TMCF/grassland cover from June 2013 to May 2014 and includes hourly solar radiation, temperature, relative humidity, wind speed, precipitation, soil moisture and runoff measurements. We compare our results with recent TCMF studies in the eastern Andean highlands in the Amazon basin. The studied elevational range always shows wetter conditions at higher elevations. This indicates a positive relation between elevation and fog or rainfall persistence. Lower elevations are more seasonally variable. Soil moisture data indicate that TMCFs do not use persistently more water than grasslands. Runoff data from our three catchments reflect the interaction between ecosystems and elevation. The less-forested catchment at lower elevations has a more seasonally variable runoff and present the lowest base flows during the dry season. In this season, soil water storage and the wetter conditions at higher elevations are crucial to sustain their base flow. The hydro-meteorological patterns of our study area are similar to those at the eastern Andean TMCF sites, but differences in the elevation of fog and rainfall persistence suggest that specific upwind ecosystem conditions and distance to the coast are important to explain and understand regional seasonal differences.

Role of persistent low-level clouds in mitigating air quality impacts of wintertime cold pool conditions

NASA Astrophysics Data System (ADS)

VanReken, Timothy M.; Dhammapala, Ranil S.; Jobson, B. Thomas; Bottenus, Courtney L.; VanderSchelden, Graham S.; Kaspari, Susan D.; Gao, Zhongming; Zhu, Qiurui; Lamb, Brian K.; Liu, Heping; Johnston, Jeff

2017-04-01

The Yakima Air Wintertime Nitrate Study (YAWNS) was conducted in January 2013 to investigate the drivers of elevated levels of fine particulate matter (PM2.5) frequently present in the region during winter stagnation periods. An extended stagnation period occurred during the study. For the first four days of the event, skies were clear and the strong diel variation in air pollution patterns were consistent with the expected effects of strong low-level nighttime temperature inversions with moderate mixing during daylight hours. Later in the event a low-level cloud layer formed that persisted over the Yakima Valley for the next seven days while regional conditions remained stagnant. Coincident with the onset of cloud, the levels of all measured primary pollutants, including CO2, CO, NOx, particle number concentration, and black carbon, dropped dramatically and remained low with negligible diel variation for as long as the cloud layer was present. The observed patterns for these air pollutants are consistent with decreased stability and enhanced mixing associated with the cloud-topped boundary layer. Interestingly, levels of secondary pollutants, most notably particulate ammonium nitrate, did not exhibit the same decline. This difference may be due to shifts in the chemical production of secondary pollutants during cloudy conditions, or may merely reflect a further influence of mixing. The results imply that the best strategies for managing wintertime air quality during episodes of persistent cloud are likely different from those needed during clear-sky stagnation events.

Correlation between atmospheric electric fields and cloud cover using a field mill and cloud observation data

NASA Astrophysics Data System (ADS)

Nakamori, Kota; Suzuki, Yasuki; Ohya, Hiroyo; Takano, Toshiaki; Kawamura, Yohei; Nakata, Hiroyuki; Yamashita, Kozo

2017-04-01

It is known that lightning and precipitations of rain droplets generated from thunderclouds are a generator of global atmospheric electric circuit. In the fair weather, the atmospheric electric fields (AEF) are downward (positive), while they are upward (negative) during lightning and precipitations. However, the correlations between the AEF, and the cloud parameters such as cloud cover, weather phenomenon, have been not revealed quantitatively yet. In this study, we investigate the correlations between the AEF and the cloud parameters, weather phenomenon using a field mill, the 95 GHz-FALCON (FMCW Radar for Cloud Observations)-I and all-sky camera observations. In this study, we installed a Boltek field mill on the roof of our building in Chiba University, Japan, (Geographic coordinate: 35.63 degree N, 140.10 degree E, the sea level: 55 m) on the first June, 2016. The sampling time of the AEF is 0.5 s. On the other hand, the FALCON-I has observed the cloud parameters far from about 76 m of the field mill throughout 24 hours every day. The vertical cloud profiles and the Doppler velocity of cloud particles can be derived by the FALCON-I with high distance resolutions (48.8 m) (Takano et al., 2010). In addition, the images of the clouds and precipitations are recorded with 30-s sampling by an all-sky camera using a CCD camera on the same roof during 05:00-22:00 LT every day. The distance between the field mill and the all-sky camera is 3.75 m. During 08:30 UT - 10:30 UT, on 4 July, 2016, we found the variation of the AEF due to the approach of thundercloud. The variation consisted of two patterns. One was slow variation due to the movement of thunderclouds, and the other was rapid variation associated with lightning discharges. As for the movement of thunderclouds, the AEF increased when the anvil was located over the field mill, which was opposite direction of the previous studies. This change might be due to the positive charges in the upper anvil more than 14 km altitude. As for the rapid variations of the AEF, 12 peaks of the AEF coincided with the occurrence of the lightning within 37 km. Moreover, we developed the automatic procedure to estimate the cloud cover from cloud optical images using the RGB color values. We estimated the correlation between the cloud cover and the AEF during June - November, 2016. The AEF decreased with increasing the cloud cover. This trend may be caused by the dielectric polarization due to the insert of the dielectric clouds into the global condenser. The standard deviation of AEF was small when the cloud cover increased. In this session, we will show the variations in the AEF during usual precipitations and snowing.

Cloud and surface textural features in polar regions

NASA Technical Reports Server (NTRS)

Welch, Ronald M.; Kuo, Kwo-Sen; Sengupta, Sailes K.

1990-01-01

The study examines the textural signatures of clouds, ice-covered mountains, solid and broken sea ice and floes, and open water. The textural features are computed from sum and difference histogram and gray-level difference vector statistics defined at various pixel displacement distances derived from Landsat multispectral scanner data. Polar cloudiness, snow-covered mountainous regions, solid sea ice, glaciers, and open water have distinguishable texture features. This suggests that textural measures can be successfully applied to the detection of clouds over snow-covered mountains, an ability of considerable importance for the modeling of snow-melt runoff. However, broken stratocumulus cloud decks and thin cirrus over broken sea ice remain difficult to distinguish texturally. It is concluded that even with high spatial resolution imagery, it may not be possible to distinguish broken stratocumulus and thin clouds from sea ice in the marginal ice zone using the visible channel textural features alone.

Fewer clouds in the Mediterranean: consistency of observations and climate simulations

PubMed Central

Sanchez-Lorenzo, Arturo; Enriquez-Alonso, Aaron; Calbó, Josep; González, Josep-Abel; Wild, Martin; Folini, Doris; Norris, Joel R.; Vicente-Serrano, Sergio M.

2017-01-01

Clouds play a major role in the climate system, but large uncertainties remain about their decadal variations. Here we report a widespread decrease in cloud cover since the 1970 s over the Mediterranean region, in particular during the 1970 s–1980 s, especially in the central and eastern areas and during springtime. Confidence in these findings is high due to the good agreement between the interannual variations of cloud cover provided by surface observations and several satellite-derived and reanalysis products, although some discrepancies exist in their trends. Climate model simulations of the historical experiment from the Coupled Model Intercomparison Project Phase 5 (CMIP5) also exhibit a decrease in cloud cover over the Mediterranean since the 1970 s, in agreement with surface observations, although the rate of decrease is slightly lower. The observed northward expansion of the Hadley cell is discussed as a possible cause of detected trends. PMID:28148960

Assessment of marine boundary layer cloud simulations in the CAM with CLUBB and updated microphysics scheme based on ARM observations from the Azores

DOE Office of Scientific and Technical Information (OSTI.GOV)

Zheng, Xue; Klein, S. A.; Ma, H. -Y.

To assess marine boundary layer (MBL) cloud simulations in three versions of the Community Atmosphere Model (CAM), three sets of short-term global hindcasts are performed and compared to Atmospheric Radiation Measurement Program (ARM) observations on Graciosa Island in the Azores from June 2009 to December 2010. Here, the three versions consist of CAM5.3 with default schemes (CAM5.3), CAM5.3 with Cloud Layers Unified By Binormals (CLUBB-MG1), and CAM5.3 with CLUBB and updated microphysics scheme (CLUBB-MG2). Our results show that relative to CAM5.3 default schemes, simulations with CLUBB better represent MBL cloud base height, the height of the major cloud layer, andmore » the daily cloud cover variability. CLUBB also better simulates the relationship of cloud fraction to cloud liquid water path (LWP) most likely due to CLUBB's consistent treatment of these variables through a probability distribution function (PDF) approach. Subcloud evaporation of precipitation is substantially enhanced in simulations with CLUBB-MG2 and is more realistic based on the limited observational estimate. Despite these improvements, all model versions underestimate MBL cloud cover. CLUBB-MG2 reduces biases in in-cloud LWP (clouds are not too bright) but there are still too few of MBL clouds due to an underestimate in the frequency of overcast scenes. Thus, combining CLUBB with MG2 scheme better simulates MBL cloud processes, but because biases remain in MBL cloud cover CLUBB-MG2 does not improve the simulation of the surface shortwave cloud radiative effect (CRE SW).« less

Assessment of marine boundary layer cloud simulations in the CAM with CLUBB and updated microphysics scheme based on ARM observations from the Azores

DOE PAGES

Zheng, Xue; Klein, S. A.; Ma, H. -Y.; ...

2016-07-19

To assess marine boundary layer (MBL) cloud simulations in three versions of the Community Atmosphere Model (CAM), three sets of short-term global hindcasts are performed and compared to Atmospheric Radiation Measurement Program (ARM) observations on Graciosa Island in the Azores from June 2009 to December 2010. Here, the three versions consist of CAM5.3 with default schemes (CAM5.3), CAM5.3 with Cloud Layers Unified By Binormals (CLUBB-MG1), and CAM5.3 with CLUBB and updated microphysics scheme (CLUBB-MG2). Our results show that relative to CAM5.3 default schemes, simulations with CLUBB better represent MBL cloud base height, the height of the major cloud layer, andmore » the daily cloud cover variability. CLUBB also better simulates the relationship of cloud fraction to cloud liquid water path (LWP) most likely due to CLUBB's consistent treatment of these variables through a probability distribution function (PDF) approach. Subcloud evaporation of precipitation is substantially enhanced in simulations with CLUBB-MG2 and is more realistic based on the limited observational estimate. Despite these improvements, all model versions underestimate MBL cloud cover. CLUBB-MG2 reduces biases in in-cloud LWP (clouds are not too bright) but there are still too few of MBL clouds due to an underestimate in the frequency of overcast scenes. Thus, combining CLUBB with MG2 scheme better simulates MBL cloud processes, but because biases remain in MBL cloud cover CLUBB-MG2 does not improve the simulation of the surface shortwave cloud radiative effect (CRE SW).« less

Microphysical effects determine macrophysical response for aerosol impacts on deep convective clouds

PubMed Central

Fan, Jiwen; Leung, L. Ruby; Rosenfeld, Daniel; Chen, Qian; Li, Zhanqing; Zhang, Jinqiang; Yan, Hongru

2013-01-01

Deep convective clouds (DCCs) play a crucial role in the general circulation, energy, and hydrological cycle of our climate system. Aerosol particles can influence DCCs by altering cloud properties, precipitation regimes, and radiation balance. Previous studies reported both invigoration and suppression of DCCs by aerosols, but few were concerned with the whole life cycle of DCC. By conducting multiple monthlong cloud-resolving simulations with spectral-bin cloud microphysics that capture the observed macrophysical and microphysical properties of summer convective clouds and precipitation in the tropics and midlatitudes, this study provides a comprehensive view of how aerosols affect cloud cover, cloud top height, and radiative forcing. We found that although the widely accepted theory of DCC invigoration due to aerosol’s thermodynamic effect (additional latent heat release from freezing of greater amount of cloud water) may work during the growing stage, it is microphysical effect influenced by aerosols that drives the dramatic increase in cloud cover, cloud top height, and cloud thickness at the mature and dissipation stages by inducing larger amounts of smaller but longer-lasting ice particles in the stratiform/anvils of DCCs, even when thermodynamic invigoration of convection is absent. The thermodynamic invigoration effect contributes up to ∼27% of total increase in cloud cover. The overall aerosol indirect effect is an atmospheric radiative warming (3–5 W⋅m−2) and a surface cooling (−5 to −8 W⋅m−2). The modeling findings are confirmed by the analyses of ample measurements made at three sites of distinctly different environments. PMID:24218569

A Model Evaluation Data Set for the Tropical ARM Sites

DOE Data Explorer

Jakob, Christian

2008-01-15

This data set has been derived from various ARM and external data sources with the main aim of providing modelers easy access to quality controlled data for model evaluation. The data set contains highly aggregated (in time) data from a number of sources at the tropical ARM sites at Manus and Nauru. It spans the years of 1999 and 2000. The data set contains information on downward surface radiation; surface meteorology, including precipitation; atmospheric water vapor and cloud liquid water content; hydrometeor cover as a function of height; and cloud cover, cloud optical thickness and cloud top pressure information provided by the International Satellite Cloud Climatology Project (ISCCP).

Cloud/climate sensitivity experiments

NASA Technical Reports Server (NTRS)

Roads, J. O.; Vallis, G. K.; Remer, L.

1982-01-01

A study of the relationships between large-scale cloud fields and large scale circulation patterns is presented. The basic tool is a multi-level numerical model comprising conservation equations for temperature, water vapor and cloud water and appropriate parameterizations for evaporation, condensation, precipitation and radiative feedbacks. Incorporating an equation for cloud water in a large-scale model is somewhat novel and allows the formation and advection of clouds to be treated explicitly. The model is run on a two-dimensional, vertical-horizontal grid with constant winds. It is shown that cloud cover increases with decreased eddy vertical velocity, decreased horizontal advection, decreased atmospheric temperature, increased surface temperature, and decreased precipitation efficiency. The cloud field is found to be well correlated with the relative humidity field except at the highest levels. When radiative feedbacks are incorporated and the temperature increased by increasing CO2 content, cloud amounts decrease at upper-levels or equivalently cloud top height falls. This reduces the temperature response, especially at upper levels, compared with an experiment in which cloud cover is fixed.

Trends in Upper-Level Cloud Cover and Surface Divergence Over the Tropical Indo-Pacific Ocean Between 1952 And 1997

NASA Technical Reports Server (NTRS)

Norris, Joel R.

2005-01-01

This study investigated the spatial pattern of linear trends in surface-observed upper-level (combined mid-level and High-level) cloud cover, precipitation, and surface divergence over the tropical Indo-Pacific Ocean during 1952-1957. Cloud values were obtained from the Extended Edited Cloud Report Archive (EECRA), precipitation values were obtained from the Hulme/Climate Research Unit Data Set, and surface divergence was alternatively calculated from wind reported Comprehensive Ocean-Atmosphere Data Set and from Smith and Reynolds Extended Reconstructed sea level pressure data.

Spatiotemporal changes of snow cover over the Tibetan plateau based on cloud-removed moderate resolution imaging spectroradiometer fractional snow cover product from 2001 to 2011

NASA Astrophysics Data System (ADS)

Tang, Zhiguang; Wang, Jian; Li, Hongyi; Yan, Lili

2013-01-01

Snow cover changes over the Tibetan plateau (TP) are examined using moderate resolution imaging spectroradiometer (MODIS) daily fractional snow cover (FSC) data from 2001 to 2011 as well as in situ temperature data. First, the accuracy of the MODIS FSC data under clear sky conditions is evaluated by comparing with Landsat 30-m observations. Then we describe a cloud-gap-filled (CGF) method using cubic spline interpolation algorithm to fill in data gaps caused by clouds. Finally, the spatial and temporal changes of snow cover are analyzed on the basis of the MODIS-derived snow-covered area and snow-covered days (SCD) data. Results show that the mean absolute error of MODIS FSC data under clear sky condition is about 0.098 over the TP. The CGF method is efficient in cloud reduction (overall mean absolute error of the retrieved FSC data is 0.092). There is a very high inter-annual and intra-seasonal variability of snow cover in the 11 years. The higher snow cover corresponds well with the huge mountains. The accumulation and melt periods of snow cover vary in different elevation zones. About 34.14% (5.56% with a significant decline) and 24.75% (3.9% with a significant increase) of the study area presents declining and increasing trend in SCD, respectively. The inter-annual fluctuation of snow cover can be explained by the high negative correlations observed between the snow cover and the in situ temperature, especially in some elevations of February, April, May, August, and September.

Decreasing cloud cover drives the recent mass loss on the Greenland Ice Sheet

PubMed Central

Hofer, Stefan; Tedstone, Andrew J.; Fettweis, Xavier; Bamber, Jonathan L.

2017-01-01

The Greenland Ice Sheet (GrIS) has been losing mass at an accelerating rate since the mid-1990s. This has been due to both increased ice discharge into the ocean and melting at the surface, with the latter being the dominant contribution. This change in state has been attributed to rising temperatures and a decrease in surface albedo. We show, using satellite data and climate model output, that the abrupt reduction in surface mass balance since about 1995 can be attributed largely to a coincident trend of decreasing summer cloud cover enhancing the melt-albedo feedback. Satellite observations show that, from 1995 to 2009, summer cloud cover decreased by 0.9 ± 0.3% per year. Model output indicates that the GrIS summer melt increases by 27 ± 13 gigatons (Gt) per percent reduction in summer cloud cover, principally because of the impact of increased shortwave radiation over the low albedo ablation zone. The observed reduction in cloud cover is strongly correlated with a state shift in the North Atlantic Oscillation promoting anticyclonic conditions in summer and suggests that the enhanced surface mass loss from the GrIS is driven by synoptic-scale changes in Arctic-wide atmospheric circulation. PMID:28782014

The effects of moon illumination, moon angle, cloud cover, and sky glow on night vision goggle flight performance

NASA Astrophysics Data System (ADS)

Loro, Stephen Lee

This study was designed to examine moon illumination, moon angle, cloud cover, sky glow, and Night Vision Goggle (NVG) flight performance to determine possible effects. The research was a causal-comparative design. The sample consisted of 194 Fort Rucker Initial Entry Rotary Wing NVG flight students being observed by 69 NVG Instructor Pilots. The students participated in NVG flight training from September 1992 through January 1993. Data were collected using a questionnaire. Observations were analyzed using a Kruskal-Wallis one-way analysis of variance and a Wilcox matched pairs signed-ranks test for difference. Correlations were analyzed using Pearson's r. The analyses results indicated that performance at high moon illumination levels is superior to zero moon illumination, and in most task maneuvers, superior to >0%--50% moon illumination. No differences were found in performance at moon illumination levels above 50%. Moon angle had no effect on night vision goggle flight performance. Cloud cover and sky glow have selective effects on different maneuvers. For most task maneuvers, cloud cover does not affect performance. Overcast cloud cover had a significant effect on seven of the 14 task maneuvers. Sky glow did not affect eight out of 14 task maneuvers at any level of sky glow.

Investigating mixed phase clouds using a synergy of ground based remote sensing measurements

NASA Astrophysics Data System (ADS)

Gierens, Rosa; Kneifel, Stefan; Löhnert, Ulrich

2017-04-01

Low level mixed phase clouds occur frequently in the Arctic, and can persist from hours to several days. However, the processes that lead to the commonality and persistence of these clouds are not well understood. The aim of our work is to get a more detailed understanding of the dynamics of and the processes in Arctic mixed phase clouds using a combination of instruments operating at the AWIPEV station in Svalbard. In addition, an aircraft campaign collecting in situ measurements inside mixed phase clouds above the station is planned for May-June 2017. The in situ data will be used for developing and validating retrievals for microphysical properties from Doppler cloud radar measurements. Once observational data for cloud properties is obtained, it can be used for evaluating model performance, for studies combining modeling and observational approaches, and eventually lead to developing model parameterizations of mixed phase microphysics. To describe the low-level mixed phase clouds, and the atmospheric conditions in which they occur, we present a case study of a persistent mixed phase cloud observed above the AWIPEV station. In the frame of the Arctic Amplification: Climate Relevant Atmospheric and Surface Processes and Feedback Mechanisms ((AC)3) -project, a millimeter wavelength cloud radar was installed at the site in June 2016. The high vertical (4 m in the lowest layer) and temporal (2.5 sec) resolution allows for a detailed description of the structure of the cloud. In addition to radar reflectivity and mean vertical velocity, we also utilize the higher moments of the Doppler spectra, such as skewness and kurtosis. To supplement the radar measurements, a ceilometer is used to detect liquid layers inside the cloud. Liquid water path and integrated water vapor are estimated using a microwave radiometer, which together with soundings can also provide temperature and humidity profiles in the lower troposphere. Moreover, a three-dimensional wind field is be obtained from a Doppler wind lidar. Furthermore, the Cloudnet scheme (www.cloud-net.org), that combines radar, lidar and microwave radiometer observations with a forecast model to provide a best estimate of cloud properties, is used for identifying mixed phase clouds. The continuous measurements carried out at AWIPEV make it possible to characterize the macro- and micro- physical properties of mixed-phase clouds on a long-term, statistical basis. The Arctic observations are compared to a 5-year observational data set from Jülich Observatory for Cloud Evolution (JOYCE) in Western Germany. The occurrence of different types of clouds (with focus on mixed-phase and super-cooled clouds), the distribution of ice and liquid within the clouds, the turbulent environment as well as the temperatures where the different phases are occurring are investigated.

On the impact of cloudiness on the characteristics of nocturnal downslope flows

NASA Astrophysics Data System (ADS)

Ye, Z. J.; Segal, M.; Garratt, J. R.; Pielke, R. A.

1989-10-01

The effects of cloud cover amount and the height of cloud base on nighttime thermally induced downslope flow were investigated using analytical and numerical model approaches. The conclusions obtained with the analytical and the numerical model evaluations agreed. It was concluded that, (i) as cloud cover increases and/or the height of cloud base decreases, the depth and the intensity of nighttime thermally-induced downslope flows may decrease by a factor reaching one sixth and one tenth, respectively, in the case of overcast low cloud; (ii) when skies suddenly cloud over around midnight, the development of the downslope flow is altered in different ways: a reduction in intensity; or a cessation of further development, depending on the fraction of cloud coverage, and (iii) with a sudden clearing of overcast low cloud around midnight, the depth and the intensity of the downslope flow increases significantly.

Statistics of link blockage due to cloud cover for free-space optical communications using NCDC surface weather observation data

NASA Technical Reports Server (NTRS)

Slobin, S. D.; Piazzolla, S.

2002-01-01

Cloud opacity is one of the main atmospheric physical phenomena that can jeopardize the successful completion of an optical link between a spacecraft and a ground station. Hence, the site location chosen for a telescope used for optical communications must rely on knowledge of weather and cloud cover statistics for the geographical area where the telescope itself is located.

Microphysical Characteristics of Clouds During the TRMM Field Campaign

NASA Technical Reports Server (NTRS)

Stith, Jeffrey L.

2003-01-01

Further analysis of the TRMM field campaign data was conducted to examine the growth of precipitation in updraft regions of the TRMM field campaign tropical clouds and to extend the earlier results to cover the whole TRMM data set collected by the University of North Dakota (UND). The results have been submitted for publication. In this paper, composite vertical profiles of liquid water, small particle concentration, and updraft/downdraft magnitudes were presented from each of the campaigns. They exhibited similar peak values for the two TRMM regions of LBA and Kwajalein. Updrafts were found to be favored locations for precipitation embryos in the form of liquid or frozen drizzle-sized droplets. Although liquid water concentrations decreased to undetectable levels between -5 and -18 C in most glaciating updrafts, occasional traces of liquid water were found in updrafts at colder temperatures, probably due to the persistence of liquid drizzle droplets. The updraft magnitudes where the traces of liquid water were observed at cold temperatures do not appear to be stronger than updrafts without liquid water at similar temperatures, however.

Microwave maps of the polar ice of the earth. [from Nimbus-5 satellite

NASA Technical Reports Server (NTRS)

Gloersen, P.; Wilheit, T. T.; Chang, T. C.; Nordberg, W.; Campbell, W. J.

1973-01-01

Synoptic views of the entire polar regions of earth were obtained free of the usual persistent cloud cover using a scanning microwave radiometer operating at a wavelength of 1.55 cm on board the Nimbus-5 satellite. Three different views at each pole are presented utilizing data obtained at approximately one-month intervals during the winter of 1972-1973. The major discoveries resulting from an analysis of these data are as follows: (1) Large discrepancies exist between the climatic norm ice cover depicted in various atlases and the actual extent of the canopies. (2) The distribution of multiyear ice in the north polar region is markedly different from that predicted by existing ice dynamics models. (3) Irregularities in the edge of the Antarctic sea ice pack occur that have neither been observed previously nor anticipated. (4) The brightness temperatures of the Greenland and Antarctica glaciers show interesting contours probably related to the ice and snow morphologic structure.

Preparatory studies of zero-g cloud drop coalescence experiment

NASA Technical Reports Server (NTRS)

Telford, J. W.; Keck, T. S.

1979-01-01

Experiments to be performed in a weightless environment in order to study collision and coalescence processes of cloud droplets are described. Rain formation in warm clouds, formation of larger cloud drops, ice and water collision processes, and precipitation in supercooled clouds are among the topics covered.

Cloud Detection of Optical Satellite Images Using Support Vector Machine

NASA Astrophysics Data System (ADS)

Lee, Kuan-Yi; Lin, Chao-Hung

2016-06-01

Cloud covers are generally present in optical remote-sensing images, which limit the usage of acquired images and increase the difficulty of data analysis, such as image compositing, correction of atmosphere effects, calculations of vegetation induces, land cover classification, and land cover change detection. In previous studies, thresholding is a common and useful method in cloud detection. However, a selected threshold is usually suitable for certain cases or local study areas, and it may be failed in other cases. In other words, thresholding-based methods are data-sensitive. Besides, there are many exceptions to control, and the environment is changed dynamically. Using the same threshold value on various data is not effective. In this study, a threshold-free method based on Support Vector Machine (SVM) is proposed, which can avoid the abovementioned problems. A statistical model is adopted to detect clouds instead of a subjective thresholding-based method, which is the main idea of this study. The features used in a classifier is the key to a successful classification. As a result, Automatic Cloud Cover Assessment (ACCA) algorithm, which is based on physical characteristics of clouds, is used to distinguish the clouds and other objects. In the same way, the algorithm called Fmask (Zhu et al., 2012) uses a lot of thresholds and criteria to screen clouds, cloud shadows, and snow. Therefore, the algorithm of feature extraction is based on the ACCA algorithm and Fmask. Spatial and temporal information are also important for satellite images. Consequently, co-occurrence matrix and temporal variance with uniformity of the major principal axis are used in proposed method. We aim to classify images into three groups: cloud, non-cloud and the others. In experiments, images acquired by the Landsat 7 Enhanced Thematic Mapper Plus (ETM+) and images containing the landscapes of agriculture, snow area, and island are tested. Experiment results demonstrate the detection accuracy of the proposed method is better than related methods.

Feasibility of Laser Power Transmission to a High-Altitude Unmanned Aerial Vehicle

DTIC Science & Technology

2011-01-01

DecNovSepAugJulJunMay OctAprMar Baghdad Taipei FebJan 0.8 0.5 0.4 0.3 0.2 0.1 0.9 0 0.7 0.6 Laser Power Transmission Through the Atmosphere 21 Figure 3.4...DecNovSepAugJulJunMay OctAprMar Baghdad (a) Probability of 80 percent cloud cover persisting more than 2 hours Taipei FebJan 0.25 0.20 0.15 0.10 0.05 0.40 0 0.35...than 6 hours Taipei FebJan 0.25 0.20 0.15 0.10 0.05 0.40 0 0.35 0.30 If the UAV carried sufficient batteries to endure 12 cloudy hours without laser

Retrieval of cloud cover parameters from multispectral satellite images

NASA Technical Reports Server (NTRS)

Arking, A.; Childs, J. D.

1985-01-01

A technique is described for extracting cloud cover parameters from multispectral satellite radiometric measurements. Utilizing three channels from the AVHRR (Advanced Very High Resolution Radiometer) on NOAA polar orbiting satellites, it is shown that one can retrieve four parameters for each pixel: cloud fraction within the FOV, optical thickness, cloud-top temperature and a microphysical model parameter. The last parameter is an index representing the properties of the cloud particle and is determined primarily by the radiance at 3.7 microns. The other three parameters are extracted from the visible and 11 micron infrared radiances, utilizing the information contained in the two-dimensional scatter plot of the measured radiances. The solution is essentially one in which the distributions of optical thickness and cloud-top temperature are maximally clustered for each region, with cloud fraction for each pixel adjusted to achieve maximal clustering.

Tailoring Earth Observation To Ranchers For Improved Land Management And Profitability: The VegMachine Online Project

NASA Astrophysics Data System (ADS)

Scarth, P.; Trevithick, B.; Beutel, T.

2016-12-01

VegMachine Online is a freely available browser application that allows ranchers across Australia to view and interact with satellite derived ground cover state and change maps on their property and extract this information in a graphical format using interactive tools. It supports the delivery and communication of a massive earth observation data set in an accessible, producer friendly way . Around 250,000 Landsat TM, ETM and OLI images were acquired across Australia, converted to terrain corrected surface reflectance and masked for cloud, cloud shadow, terrain shadow and water. More than 2500 field sites across the Australian rangelands were used to derive endmembers used in a constrained unmixing approach to estimate the per-pixel proportion of bare, green and non-green vegetation for all images. A seasonal metoid compositing method was used to produce national fractional cover virtual mosaics for each three month period since 1988. The time series of green fraction is used to estimate the persistent green due to tree and shrub canopies, and this estimate is used to correct the fractional cover to ground cover for our mixed tree-grass rangeland systems. Finally, deciles are produced for key metrics every season to track a pixels relativity to the entire time series. These data are delivered through time series enabled web mapping services and customised web processing services that enable the full time series over any spatial extent to be interrogated in seconds via a RESTful interface. These services interface with a front end browser application that provides product visualization for any date in the time series, tools to draw or import polygon boundaries, plot time series ground cover comparisons, look at the effect of historical rainfall and tools to run the revised universal soil loss equation in web time to assess the effect of proposed changes in cover retention. VegMachine Online is already being used by ranchers monitoring paddock condition, organisations supporting land management initiatives in Great Barrier Reef catchments, by students developing tools to understand land condition and degradation and the underlying data and APIs are supporting several other land condition mapping tools.

The clouds are hazes of Venus

NASA Technical Reports Server (NTRS)

Esposito, L. W.; Knollenberg, R. G.; Marov, M. IA.; Toon, O. B.; Turco, R. P.

1983-01-01

Pioneer Venus and Venera probe data for the clouds of Venus are considered. These clouds consist of a main cloud deck at 45-70 km altitude, with thinner hazes above and below, although the microphysical properties of the main cloud are further subdivided into upper, middle and lower cloud levels. Much of the cloud exhibits a multimodal particle size distribution, with the mode most visible from the earth being H2SO4 droplets having 2-3 micron diameters. Despite variations, the vertical structure of the clouds indicates persistent features at sites separated by years and by great distances. The clouds are more strongly affected by radiation than by latent heat release, and the small particle size and weak convective activity observed are incompatible with lightning of cloud origin.

Comparison of monthly nighttime cloud fraction products from MODIS and AIRS and ground-based camera over Manila Observatory (14.64N, 121.07E)

NASA Astrophysics Data System (ADS)

Gacal, G. F. B.; Lagrosas, N.

2017-12-01

Cloud detection nowadays is primarily achieved by the utilization of various sensors aboard satellites. These include MODIS Aqua, MODIS Terra, and AIRS with products that include nighttime cloud fraction. Ground-based instruments are, however, only secondary to these satellites when it comes to cloud detection. Nonetheless, these ground-based instruments (e.g., LIDARs, ceilometers, and sky-cameras) offer significant datasets about a particular region's cloud cover values. For nighttime operations of cloud detection instruments, satellite-based instruments are more reliably and prominently used than ground-based ones. Therefore if a ground-based instrument for nighttime operations is operated, it ought to produce reliable scientific datasets. The objective of this study is to do a comparison between the results of a nighttime ground-based instrument (sky-camera) and that of MODIS Aqua and MODIS Terra. A Canon Powershot A2300 is placed ontop of Manila Observatory (14.64N, 121.07E) and is configured to take images of the night sky at 5min intervals. To detect pixels with clouds, the pictures are converted to grayscale format. Thresholding technique is used to screen pixels with cloud and pixels without clouds. If the pixel value is greater than 17, it is considered as a cloud; otherwise, a noncloud (Gacal et al., 2016). This algorithm is applied to the data gathered from Oct 2015 to Oct 2016. A scatter plot between satellite cloud fraction in the area covering the area 14.2877N, 120.9869E, 14.7711N and 121.4539E and ground cloud cover is graphed to find the monthly correlation. During wet season (June - November), the satellite nighttime cloud fraction vs ground measured cloud cover produce an acceptable R2 (Aqua= 0.74, Terra= 0.71, AIRS= 0.76). However, during dry season, poor R2 values are obtained (AIRS= 0.39, Aqua & Terra = 0.01). The high correlation during wet season can be attributed to a high probability that the camera and satellite see the same clouds. However during dry season, the satellite sees high altitude clouds and the camera can not detect these clouds from the ground as it relies on city lights reflected from low level clouds. With this acknowledged disparity, the ground-based camera has the advantage of detecting haze and thin clouds near the ground that are hardly or not detected by the satellites.

Discrimination Between Clouds and Snow in Landsat 8 Imagery: an Assessment of Current Methods and a New Approach

NASA Astrophysics Data System (ADS)

Stillinger, T.; Dozier, J.; Phares, N.; Rittger, K.

2015-12-01

Discrimination between snow and clouds poses a serious but tractable challenge to the consistent delivery of high-quality information on mountain snow from remote sensing. Clouds obstruct the surface from the sensor's view, and the similar optical properties of clouds and snow make accurate discrimination difficult. We assess the performance of the current Landsat 8 operational snow and cloud mask products (LDCM CCA and CFmask), along with a new method, using over one million manually identified snow and clouds pixels in Landsat 8 scenes. The new method uses physically based scattering models to generate spectra in each Landsat 8 band, at that scene's solar illumination, for snow and cloud particle sizes that cover the plausible range for each. The modeled spectra are compared to pixels' spectra via several independent ways to identify snow and clouds. The results are synthesized to create a final snow/cloud mask, and the method can be applied to any multispectral imager with bands covering the visible, near-infrared, and shortwave-infrared regions. Each algorithm we tested misidentifies snow and clouds in both directions to varying degrees. We assess performance with measures of Precision, Recall, and the F statistic, which are based on counts of true and false positives and negatives. Tests for significance in differences between spectra in the measured and modeled values among incorrectly identified pixels help ascertain reasons for misidentification. A cloud mask specifically designed to separate snow from clouds is a valuable tool for those interested in remotely sensing snow cover. Given freely available remote sensing datasets and computational tools to feasibly process entire mission histories for an area of interest, enabling researchers to reliably identify and separate snow and clouds increases the usability of the data for hydrological and climatological studies.

View of Earth from Apollo 10 taken from reproduction of tv transmission

NASA Technical Reports Server (NTRS)

1969-01-01

A cloud-covered earth from about 12,800 nautical miles away is seen in this color reproduction taken from the second TV transmission made by the color television camera onboard the Apollo 10 spacecraft. The United States and Mexico are located at right center. The more cloud-free area is the western and southwestern part of the U.S. and northern Mexico. Clouds cover the eastern half of the U.S.

Cloud cover archiving on a global scale - A discussion of principles

NASA Technical Reports Server (NTRS)

Henderson-Sellers, A.; Hughes, N. A.; Wilson, M.

1981-01-01

Monitoring of climatic variability and climate modeling both require a reliable global cloud data set. Examination is made of the temporal and spatial variability of cloudiness in light of recommendations made by GARP in 1975 (and updated by JOC in 1978 and 1980) for cloud data archiving. An examination of the methods of comparing cloud cover frequency curves suggests that the use of the beta distribution not only facilitates objective comparison, but also reduces overall storage requirements. A specific study of the only current global cloud climatology (the U.S. Air Force's 3-dimensional nephanalysis) over the United Kingdom indicates that discussion of methods of validating satellite-based data sets is urgently required.

Hydrologic scales, cloud variability, remote sensing, and models: Implications for forecasting snowmelt and streamflow

USGS Publications Warehouse

Simpson, James J.; Dettinger, M.D.; Gehrke, F.; McIntire, T.J.; Hufford, Gary L.

2004-01-01

Accurate prediction of available water supply from snowmelt is needed if the myriad of human, environmental, agricultural, and industrial demands for water are to be satisfied, especially given legislatively imposed conditions on its allocation. Robust retrievals of hydrologic basin model variables (e.g., insolation or areal extent of snow cover) provide several advantages over the current operational use of either point measurements or parameterizations to help to meet this requirement. Insolation can be provided at hourly time scales (or better if needed during rapid melt events associated with flooding) and at 1-km spatial resolution. These satellite-based retrievals incorporate the effects of highly variable (both in space and time) and unpredictable cloud cover on estimates of insolation. The insolation estimates are further adjusted for the effects of basin topography using a high-resolution digital elevation model prior to model input. Simulations of two Sierra Nevada rivers in the snowmelt seasons of 1998 and 1999 indicate that even the simplest improvements in modeled insolation can improve snowmelt simulations, with 10%-20% reductions in root-mean-square errors. Direct retrieval of the areal extent of snow cover may mitigate the need to rely entirely on internal calculations of this variable, a reliance that can yield large errors that are difficult to correct until long after the season is complete and that often leads to persistent underestimates or overestimates of the volumes of the water to operational reservoirs. Agencies responsible for accurately predicting available water resources from the melt of snowpack [e.g., both federal (the National Weather Service River Forecast Centers) and state (the California Department of Water Resources)] can benefit by incorporating concepts developed herein into their operational forecasting procedures. ?? 2004 American Meteorological Society.

Mapping Urban Tree Canopy Cover Using Fused Airborne LIDAR and Satellite Imagery Data

NASA Astrophysics Data System (ADS)

Parmehr, Ebadat G.; Amati, Marco; Fraser, Clive S.

2016-06-01

Urban green spaces, particularly urban trees, play a key role in enhancing the liveability of cities. The availability of accurate and up-to-date maps of tree canopy cover is important for sustainable development of urban green spaces. LiDAR point clouds are widely used for the mapping of buildings and trees, and several LiDAR point cloud classification techniques have been proposed for automatic mapping. However, the effectiveness of point cloud classification techniques for automated tree extraction from LiDAR data can be impacted to the point of failure by the complexity of tree canopy shapes in urban areas. Multispectral imagery, which provides complementary information to LiDAR data, can improve point cloud classification quality. This paper proposes a reliable method for the extraction of tree canopy cover from fused LiDAR point cloud and multispectral satellite imagery data. The proposed method initially associates each LiDAR point with spectral information from the co-registered satellite imagery data. It calculates the normalised difference vegetation index (NDVI) value for each LiDAR point and corrects tree points which have been misclassified as buildings. Then, region growing of tree points, taking the NDVI value into account, is applied. Finally, the LiDAR points classified as tree points are utilised to generate a canopy cover map. The performance of the proposed tree canopy cover mapping method is experimentally evaluated on a data set of airborne LiDAR and WorldView 2 imagery covering a suburb in Melbourne, Australia.

The Cloud Detection and UV Monitoring Experiment (CLUE)

NASA Technical Reports Server (NTRS)

Barbier, L.; Loh, E.; Sokolsky, P.; Streitmatter, R.

2004-01-01

We propose a large-area, low-power instrument to perform CLoud detection and Ultraviolet monitoring, CLUE. CLUE will combine the W detection capabilities of the NIGHTGLOW payload, with an array of infrared sensors to perform cloud slicing measurements. Missions such as EUSO and OWL which seek to measure UHE cosmic-rays at 1W20 eV use the atmosphere as a fluorescence detector. CLUE will provide several important correlated measurements for these missions, including: monitoring the atmospheric W emissions &om 330 - 400 nm, determining the ambient cloud cover during those W measurements (with active LIDAR), measuring the optical depth of the clouds (with an array of narrow band-pass IR sensors), and correlating LIDAR and IR cloud cover measurements. This talk will describe the instrument as we envision it.

Cloud Statistics and Discrimination in the Polar Regions

NASA Astrophysics Data System (ADS)

Chan, M.; Comiso, J. C.

2012-12-01

Despite their important role in the climate system, cloud cover and their statistics are poorly known, especially in the polar regions, where clouds are difficult to discriminate from snow covered surfaces. The advent of the A-train, which included Aqua/MODIS, CALIPSO/CALIOP and CloudSat/CPR sensors has provided an opportunity to improve our ability to accurately characterize the cloud cover. MODIS provides global coverage at a relatively good temporal and spatial resolution while CALIOP and CPR provide limited nadir sampling but accurate characterization of the vertical structure and phase of the cloud cover. Over the polar regions, cloud detection from a passive sensors like MODIS is challenging because of the presence of cold and highly reflective surfaces such as snow, sea-ice, glaciers, and ice-sheet, which have surface signatures similar to those of clouds. On the other hand, active sensors such as CALIOP and CPR are not only very sensitive to the presence of clouds but can also provide information about its microphysical characteristics. However, these nadir-looking sensors have sparse spatial coverage and their global data can have data spatial gaps of up to 100 km. We developed a polar cloud detection system for MODIS that is trained using collocated data from CALIOP and CPR. In particular, we employ a machine learning system that reads the radiative profile observed by MODIS and determine whether the field of view is cloudy or clear. Results have shown that the improved cloud detection scheme performs better than typical cloud mask algorithms using a validation data set not used for training. A one-year data set was generated and results indicate that daytime cloud detection accuracies improved from 80.1% to 92.6% (over sea-ice) and 71.2% to 87.4% (over ice-sheet) with CALIOP data used as the baseline. Significant improvements are also observed during nighttime, where cloud detection accuracies increase by 19.8% (over sea-ice) and 11.6% (over ice-sheet). The immediate impact of the new algorithm is that it can minimize large biases of MODIS-derived cloud amount over the Polar Regions and thus a more realistic and high quality global cloud statistics. In particular, our results show that cloud fraction in the Arctic is typically 81.2 % during daytime and 84.0% during nighttime. This is significantly higher than the 71.8% and 58.5%, respectively, derived from standard MODIS cloud product.

An Observational Study of the Relationship between Cloud, Aerosol and Meteorology in Broken Low-Level Cloud Conditions

NASA Technical Reports Server (NTRS)

Loeb, Norman G.; Schuster, Gregory L.

2008-01-01

Global satellite analyses showing strong correlations between aerosol optical depth and 3 cloud cover have stirred much debate recently. While it is tempting to interpret the results as evidence of aerosol enhancement of cloud cover, other factors such as the influence of meteorology on both the aerosol and cloud distributions can also play a role, as both aerosols and clouds depend upon local meteorology. This study uses satellite observations to examine aerosol-cloud relationships for broken low-level cloud regions off the coast of Africa. The analysis approach minimizes the influence of large-scale meteorology by restricting the spatial and temporal domains in which the aerosol and cloud properties are compared. While distributions of several meteorological variables within 5deg 5deg latitude-longitude regions are nearly identical under low and high aerosol optical depth, the corresponding distributions of single-layer low cloud properties and top-of-atmosphere radiative fluxes differ markedly, consistent with earlier studies showing increased cloud cover with aerosol optical depth. Furthermore, fine-mode fraction and Angstrom Exponent are also larger in conditions of higher aerosol optical depth, even though no evidence of systematic latitudinal or longitudinal gradients between the low and high aerosol optical depth populations are observed. When the analysis is repeated for all 5deg 5deg latitude-longitude regions over the global oceans (after removing cases in which significant meteorological differences are found between the low and high aerosol populations), results are qualitatively similar to those off the coast of Africa.

Effective cloud optical depth and enhancement effects for broken liquid water clouds in Valencia (Spain)

NASA Astrophysics Data System (ADS)

Marín, M. J.; Serrano, D.; Utrillas, M. P.; Núñez, M.; Martínez-Lozano, J. A.

2017-10-01

Partly cloudy skies with liquid water clouds have been analysed, founding that it is essential to distinguish data if the Sun is obstructed or not by clouds. Both cases can be separated considering simultaneously the Cloud Modification Factor (CMF) and the clearness index (kt). For partly cloudy skies and the Sun obstructed the effective cloud optical depth (τ) has been obtained by the minimization method for overcast skies. This method was previously developed by the authors but, in this case, taking into account partial cloud cover. This study has been conducted for the years 2011-2015 with the multiple scattering model SBDART and irradiance measurements for the UV Erythemal Radiation (UVER) and the broadband ranges. Afterwards a statistical analysis of τ has shown that the maximum value is much lower than for overcast skies and there is more discrepancy between the two spectral ranges regarding the results for overcast skies. In order to validate these results the effective cloud optical depth has been correlated with several transmission factors, giving similar fit parameters to those obtained for overcast skies except for the clearness index in the UVER range. As our method is not applicable for partly cloudy skies with the visible Sun, the enhancement of radiation caused by clouds when the Sun is visible has been studied. Results show that the average enhancement CMF values are the same for both ranges although enhancement is more frequent for low cloud cover in the UVER and medium-high cloud cover in the broadband range and it does not depend on the solar zenith angle.

MODSNOW-Tool: an operational tool for daily snow cover monitoring using MODIS data

NASA Astrophysics Data System (ADS)

Gafurov, Abror; Lüdtke, Stefan; Unger-Shayesteh, Katy; Vorogushyn, Sergiy; Schöne, Tilo; Schmidt, Sebastian; Kalashnikova, Olga; Merz, Bruno

2017-04-01

Spatially distributed snow cover information in mountain areas is extremely important for water storage estimations, seasonal water availability forecasting, or the assessment of snow-related hazards (e.g. enhanced snow-melt following intensive rains, or avalanche events). Moreover, spatially distributed snow cover information can be used to calibrate and/or validate hydrological models. We present the MODSNOW-Tool - an operational monitoring tool offers a user-friendly application which can be used for catchment-based operational snow cover monitoring. The application automatically downloads and processes freely available daily Moderate Resolution Imaging Spectroradiometer (MODIS) snow cover data. The MODSNOW-Tool uses a step-wise approach for cloud removal and delivers cloud-free snow cover maps for the selected river basins including basin specific snow cover extent statistics. The accuracy of cloud-eliminated MODSNOW snow cover maps was validated for 84 almost cloud-free days in the Karadarya river basin in Central Asia, and an average accuracy of 94 % was achieved. The MODSNOW-Tool can be used in operational and non-operational mode. In the operational mode, the tool is set up as a scheduled task on a local computer allowing automatic execution without user interaction and delivers snow cover maps on a daily basis. In the non-operational mode, the tool can be used to process historical time series of snow cover maps. The MODSNOW-Tool is currently implemented and in use at the national hydrometeorological services of four Central Asian states - Kazakhstan, Kyrgyzstan, Uzbekistan and Turkmenistan and used for seasonal water availability forecast.

Cloud cover and horizontal plane eye damaging solar UV exposures.

PubMed

Parisi, A V; Downs, N

2004-11-01

The spectral UV and the cloud cover were measured at intervals of 5 min with an integrated cloud and spectral UV measurement system at a sub-tropical Southern Hemisphere site for a 6-month period and solar zenith angle (SZA) range of 4.7 degrees to approximately 80 degrees . The solar UV spectra were recorded between 280 nm and 400 nm in 0.5 nm increments and weighted with the action spectra for photokeratitis and cataracts in order to investigate the effect of cloud cover on the horizontal plane biologically damaging UV irradiances for cataracts (UVBE(cat)) and photokeratitis (UVBE(pker)). Eighty five percent of the recorded spectra produced a measured irradiance to a cloud free irradiance ratio of 0.6 and higher while 76% produced a ratio of 0.8 and higher. Empirical non-linear expressions as a function of SZA have been developed for all sky conditions to allow the evaluation of the biologically damaging UV irradiances for photokeratitis and cataracts from a knowledge of the unweighted UV irradiances.

Improved Modeling Tools Development for High Penetration Solar

DOE Office of Scientific and Technical Information (OSTI.GOV)

Washom, Byron; Meagher, Kevin

2014-12-11

One of the significant objectives of the High Penetration solar research is to help the DOE understand, anticipate, and minimize grid operation impacts as more solar resources are added to the electric power system. For Task 2.2, an effective, reliable approach to predicting solar energy availability for energy generation forecasts using the University of California, San Diego (UCSD) Sky Imager technology has been demonstrated. Granular cloud and ramp forecasts for the next 5 to 20 minutes over an area of 10 square miles were developed. Sky images taken every 30 seconds are processed to determine cloud locations and cloud motionmore » vectors yielding future cloud shadow locations respective to distributed generation or utility solar power plants in the area. The performance of the method depends on cloud characteristics. On days with more advective cloud conditions, the developed method outperforms persistence forecasts by up to 30% (based on mean absolute error). On days with dynamic conditions, the method performs worse than persistence. Sky Imagers hold promise for ramp forecasting and ramp mitigation in conjunction with inverter controls and energy storage. The pre-commercial Sky Imager solar forecasting algorithm was documented with licensing information and was a Sunshot website highlight.« less

Automated Visibility & Cloud Cover Measurements with a Solid State Imaging System

DTIC Science & Technology

1989-03-01

GL-TR-89-0061 SIO Ref. 89-7 MPL-U-26/89 AUTOMATED VISIBILITY & CLOUD COVER MEASUREMENTS WITH A SOLID-STATE IMAGING SYSTEM C) to N4 R. W. Johnson W. S...include Security Classification) Automated Visibility & Cloud Measurements With A Solid State Imaging System 12. PERSONAL AUTHOR(S) Richard W. Johnson...based imaging systems , their ics and control algorithms, thus they ar.L discussed sepa- initial deployment and the preliminary application of rately

To Which Extent can Aerosols Affect Alpine Mixed-Phase Clouds?

NASA Astrophysics Data System (ADS)

Henneberg, O.; Lohmann, U.

2017-12-01

Aerosol-cloud interactions constitute a high uncertainty in regional climate and changing weather patterns. Such uncertainties are due to the multiple processes that can be triggered by aerosol especially in mixed-phase clouds. Mixed-phase clouds most likely result in precipitation due to the formation of ice crystals, which can grow to precipitation size. Ice nucleating particles (INPs) determine how fast these clouds glaciate and form precipitation. The potential for INP to transfer supercooled liquid clouds to precipitating clouds depends on the available humidity and supercooled liquid. Those conditions are determined by dynamics. Moderately high updraft velocities result in persistent mixed-phase clouds in the Swiss Alps [1], which provide an ideal testbed to investigate the effect of aerosol on precipitation in mixed-phase clouds. To address the effect of aerosols in orographic winter clouds under different dynamic conditions, we run a number of real case ensembles with the regional climate model COSMO on a horizontal resolution of 1.1 km. Simulations with different INP concentrations within the range observed at the GAW research station Jungfraujoch in the Swiss Alps are conducted and repeated within the ensemble. Microphysical processes are described with a two-moment scheme. Enhanced INP concentrations enhance the precipitation rate of a single precipitation event up to 20%. Other precipitation events of similar strength are less affected by the INP concentration. The effect of CCNs is negligible for precipitation from orographic winter clouds in our case study. There is evidence for INP to change precipitation rate and location more effectively in stronger dynamic regimes due to the enhanced potential to transfer supercooled liquid to ice. The classification of the ensemble members according to their dynamics will quantify the interaction of aerosol effects and dynamics. Reference [1] Lohmann et al, 2016: Persistence of orographic mixed-phase clouds, GRL

A cloud/particle model of the interstellar medium - Galactic spiral structure

NASA Technical Reports Server (NTRS)

Levinson, F. H.; Roberts, W. W., Jr.

1981-01-01

A cloud/particle model for gas flow in galaxies is developed that incorporates cloud-cloud collisions and supernovae as dominant local processes. Cloud-cloud collisions are the main means of dissipation. To counter this dissipation and maintain local dispersion, supernova explosions in the medium administer radial snowplow pushes to all nearby clouds. The causal link between these processes is that cloud-cloud collisions will form stars and that these stars will rapidly become supernovae. The cloud/particle model is tested and used to investigate the gas dynamics and spiral structures in galaxies where these assumptions may be reasonable. Particular attention is given to whether large-scale galactic shock waves, which are thought to underlie the regular well-delineated spiral structure in some galaxies, form and persist in a cloud-supernova dominated interstellar medium; this question is answered in the affirmative.

SAR processing in the cloud for oil detection in the Arctic

NASA Astrophysics Data System (ADS)

Garron, J.; Stoner, C.; Meyer, F. J.

2016-12-01

A new world of opportunity is being thawed from the ice of the Arctic, driven by decreased persistent Arctic sea-ice cover, increases in shipping, tourism, natural resource development. Tools that can automatically monitor key sea ice characteristics and potential oil spills are essential for safe passage in these changing waters. Synthetic aperture radar (SAR) data can be used to discriminate sea ice types and oil on the ocean surface and also for feature tracking. Additionally, SAR can image the earth through the night and most weather conditions. SAR data is volumetrically large and requires significant computing power to manipulate. Algorithms designed to identify key environmental features, like oil spills, in SAR imagery require secondary processing, and are computationally intensive, which can functionally limit their application in a real-time setting. Cloud processing is designed to manage big data and big data processing jobs by means of small cycles of off-site computations, eliminating up-front hardware costs. Pairing SAR data with cloud processing has allowed us to create and solidify a processing pipeline for SAR data products in the cloud to compare operational algorithms efficiency and effectiveness when run using an Alaska Satellite Facility (ASF) defined Amazon Machine Image (AMI). The products created from this secondary processing, were compared to determine which algorithm was most accurate in Arctic feature identification, and what operational conditions were required to produce the results on the ASF defined AMI. Results will be used to inform a series of recommendations to oil-spill response data managers and SAR users interested in expanding their analytical computing power.

Students as Ground Observers for Satellite Cloud Retrieval Validation

NASA Technical Reports Server (NTRS)

Chambers, Lin H.; Costulis, P. Kay; Young, David F.; Rogerson, Tina M.

2004-01-01

The Students' Cloud Observations On-Line (S'COOL) Project was initiated in 1997 to obtain student observations of clouds coinciding with the overpass of the Clouds and the Earth's Radiant Energy System (CERES) instruments on NASA's Earth Observing System satellites. Over the past seven years we have accumulated more than 9,000 cases worldwide where student observations are available within 15 minutes of a CERES observation. This paper reports on comparisons between the student and satellite data as one facet of the validation of the CERES cloud retrievals. Available comparisons include cloud cover, cloud height, cloud layering, and cloud visual opacity. The large volume of comparisons allows some assessment of the impact of surface cover, such as snow and ice, reported by the students. The S'COOL observation database, accessible via the Internet at http://scool.larc.nasa.gov, contains over 32,000 student observations and is growing by over 700 observations each month. Some of these observations may be useful for assessment of other satellite cloud products. In particular, some observing sites have been making hourly observations of clouds during the school day to learn about the diurnal cycle of cloudiness.

Characterizing the Influence of the General Circulation on Marine Boundary Layer Clouds

NASA Technical Reports Server (NTRS)

Rozendaal, Margaret A.; Rossow, William B.; Hansen, James E. (Technical Monitor)

2001-01-01

The seasonal and intraseasonal variability of boundary layer cloud in the subtropical eastern oceans are studied using combined data from the International Satellite Cloud Climatology Project (ISCCP) and the European Centre for Medium-Range Weather Forecasts (ECMWF) reanalysis. Spectral analysis reveals that most of the time variability of cloud properties occurs on seasonal to annual time scales. The variance decreases one to two orders of magnitude for each decade of time scale decrease, indicating that daily to monthly time scales have smaller, but non-negligible variability. The length of these dominant time scales suggests that the majority of the variability is influenced by the general circulation and its interaction with boundary layer turbulence, rather than a product of boundary layer turbulence alone. Previous datasets have lacked the necessary resolution in either time or in space to properly characterize variability on synoptic scales; this is remedied by using global satellite-retrieved cloud properties. We characterize the intraseasonal subtropical cloud variability in both hemispheres and in different seasons. In addition to cloud fraction, we examine variability of cloud optical thickness - cloud top pressure frequency distributions. Despite the large concentration of research on the variability of Northern Hemisphere (NH) regions during summer, it is noted that the largest amplitude intraseasonal variability in the NH regions occurs during local winter. The effect of intraseasonal variability on the calculation and interpretation of seasonal results is investigated. Decreases in seasonally averaged cloud cover, optical thickness and cloud top pressure from the May-through-September season to the November-through-March season are most apparent in the NH regions. Further analysis indicates that these changes are due to an increase in frequency, but a decrease in the persistence of synoptic events. In addition, changes in cloud top pressure and optical thickness characteristics from the summer to winter seasons indicate that the NH subtropics undergo a change in dynamic regime with season. This change appears in the cloud fields as a shift from the more commonly seen lower-altitude, thicker optical thickness clouds to higher-altitude, thinner clouds. The latter cloud-type is associated with the lower sea level pressure, upward vertical velocity phase of the synoptic wave. Intraseasonal changes in cloud properties in the Southern Hemisphere and NH summer are much smaller in amplitude. Although they also appear to be linked to changes in the large-scale dynamics, similarly to NH winter variations, the relationships are more ambiguous due to the small amplitudes and longer time scales. We attempt to interpret some of these relationships using the results of the Betts and Ridgway (1989) box model. However, these results cannot consistently explain the patterns when results from all regions are considered, implying that this model may not adequately explain all the processes involved in the variability.

A comparison of radiometric normalization methods when filling cloud gaps in Lansat imagery.

Treesearch

E. H. Helmer

2007-01-01

Mapping persistently cloudy tropical landscapes with optical satellite imagenery usually requires assembling the clear imagery from several dates. this study compares methods for normalizing image data when filling cloud gaps in Landsat imagery with imagery from other dates.

Integrated approach using multi-platform sensors for enhanced high-resolution daily ice cover product

NASA Astrophysics Data System (ADS)

Bonev, George; Gladkova, Irina; Grossberg, Michael; Romanov, Peter; Helfrich, Sean

2016-09-01

The ultimate objective of this work is to improve characterization of the ice cover distribution in the polar areas, to improve sea ice mapping and to develop a new automated real-time high spatial resolution multi-sensor ice extent and ice edge product for use in operational applications. Despite a large number of currently available automated satellite-based sea ice extent datasets, analysts at the National Ice Center tend to rely on original satellite imagery (provided by satellite optical, passive microwave and active microwave sensors) mainly because the automated products derived from satellite optical data have gaps in the area coverage due to clouds and darkness, passive microwave products have poor spatial resolution, automated ice identifications based on radar data are not quite reliable due to a considerable difficulty in discriminating between the ice cover and rough ice-free ocean surface due to winds. We have developed a multisensor algorithm that first extracts maximum information on the sea ice cover from imaging instruments VIIRS and MODIS, including regions covered by thin, semitransparent clouds, then supplements the output by the microwave measurements and finally aggregates the results into a cloud gap free daily product. This ability to identify ice cover underneath thin clouds, which is usually masked out by traditional cloud detection algorithms, allows for expansion of the effective coverage of the sea ice maps and thus more accurate and detailed delineation of the ice edge. We have also developed a web-based monitoring system that allows comparison of our daily ice extent product with the several other independent operational daily products.

An energy balance model exploration of the impacts of interactions between surface albedo, cloud cover and water vapor on polar amplification

NASA Astrophysics Data System (ADS)

Södergren, A. Helena; McDonald, Adrian J.; Bodeker, Gregory E.

2017-11-01

We examine the effects of non-linear interactions between surface albedo, water vapor and cloud cover (referred to as climate variables) on amplified warming of the polar regions, using a new energy balance model. Our simulations show that the sum of the contributions to surface temperature changes due to any variable considered in isolation is smaller than the temperature changes from coupled feedback simulations. This non-linearity is strongest when all three climate variables are allowed to interact. Surface albedo appears to be the strongest driver of this non-linear behavior, followed by water vapor and clouds. This is because increases in longwave radiation absorbed by the surface, related to increases in water vapor and clouds, and increases in surface absorbed shortwave radiation caused by a decrease in surface albedo, amplify each other. Furthermore, our results corroborate previous findings that while increases in cloud cover and water vapor, along with the greenhouse effect itself, warm the polar regions, water vapor also significantly warms equatorial regions, which reduces polar amplification. Changes in surface albedo drive large changes in absorption of incoming shortwave radiation, thereby enhancing surface warming. Unlike high latitudes, surface albedo change at low latitudes are more constrained. Interactions between surface albedo, water vapor and clouds drive larger increases in temperatures in the polar regions compared to low latitudes. This is in spite of the fact that, due to a forcing, cloud cover increases at high latitudes and decreases in low latitudes, and that water vapor significantly enhances warming at low latitudes.

Comparison between MODIS-derived day and night cloud cover and surface observations over the North China Plain

NASA Astrophysics Data System (ADS)

Zhang, Xiao; Tan, Saichun; Shi, Guangyu

2018-02-01

Satellite and human visual observation are two of the most important observation approaches for cloud cover. In this study, the total cloud cover (TCC) observed by MODIS onboard the Terra and Aqua satellites was compared with Synop meteorological station observations over the North China Plain and its surrounding regions for 11 years during daytime and 7 years during nighttime. The Synop data were recorded eight times a day at 3-h intervals. Linear interpolation was used to interpolate the Synop data to the MODIS overpass time in order to reduce the temporal deviation between the satellite and Synop observations. Results showed that MODIS-derived TCC had good consistency with the Synop observations; the correlation coefficients ranged from 0.56 in winter to 0.73 in summer for Terra MODIS, and from 0.55 in winter to 0.71 in summer for Aqua MODIS. However, they also had certain differences. On average, the MODIS-derived TCC was 15.16% higher than the Synop data, and this value was higher at nighttime (15.58%-16.64%) than daytime (12.74%-14.14%). The deviation between the MODIS and Synop TCC had large seasonal variation, being largest in winter (29.53%-31.07%) and smallest in summer (4.46%-6.07%). Analysis indicated that cloud with low cloud-top height and small cloud optical thickness was more likely to cause observation bias. Besides, an increase in the satellite view zenith angle, aerosol optical depth, or snow cover could lead to positively biased MODIS results, and this affect differed among different cloud types.

Motion/imagery secure cloud enterprise architecture analysis

NASA Astrophysics Data System (ADS)

DeLay, John L.

2012-06-01

Cloud computing with storage virtualization and new service-oriented architectures brings a new perspective to the aspect of a distributed motion imagery and persistent surveillance enterprise. Our existing research is focused mainly on content management, distributed analytics, WAN distributed cloud networking performance issues of cloud based technologies. The potential of leveraging cloud based technologies for hosting motion imagery, imagery and analytics workflows for DOD and security applications is relatively unexplored. This paper will examine technologies for managing, storing, processing and disseminating motion imagery and imagery within a distributed network environment. Finally, we propose areas for future research in the area of distributed cloud content management enterprises.

Photogrammetric Analysis of Changes in Crater Morphology at Telica Volcano, Nicaragua from 1994 to 2016

NASA Astrophysics Data System (ADS)

Hanagan, C.; La Femina, P.

2017-12-01

Understanding processes that lead to volcanic eruptions is paramount for predicting future volcanic activity. Telica volcano, Nicaragua is a persistently active volcano with hundreds of daily, low magnitude and low frequency seismic events, high-temperature degassing, and sub-decadal VEI 1-3 eruptions. The phreatic vulcanian eruptions of 1999, 2011, and 2013, and phreatic to phreatomagmatic vulcanian eruption of 2015 are thought to have resulted by sealing of the hydrothermal system prior to the eruptions. Two mechanisms have been proposed for sealing of the volcanic system, hydrothermal mineralization and landslides covering the vent. These eruptions affect the crater morphology of Telica volcano, and therefore the exact mechanisms of change to the crater's form are of interest to provide data that may support or refute the proposed sealing mechanisms, improving our understanding of eruption mechanisms. We use a collection of photographs between February 1994 and May 2016 and a combination of qualitative and quantitative photogrammetry to detect the extent and type of changes in crater morphology associated with 2011, 2013, and 2015 eruptive activity. We produced dense point cloud models using Agisoft PhotoScan Professional for times with sufficient photographic coverage, including August 2011, March 2013, December 2015, March 2016, and May 2016. Our May 2016 model is georeferenced, and each other point cloud was differenced using the C2C tool in CloudCompare and the M3C2 method (CloudCompare plugin) Lague et al. (2013). Results of the qualitative observations and quantitative differencing reveal a general trend of material subtraction from the inner crater walls associated with eruptive activity and accumulation of material on the crater floor, often visibly sourced from the walls of the crater. Both daily activity and VEI 1-3 explosive events changed the crater morphology, and correlation between a landslide-covered vent and the 2011 and 2015 eruptive sequences exists. Though further study and integration with other date sets is required, a positive feedback mechanism between accumulation of material blocking the vent, eruption, and subsequent accumulation of material to re-block the vent remains possible.

Trends in Total Cloud Amount Over China (1951 - 1994)

DOE Data Explorer

Kaiser, Dale P. [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States).

1999-01-01

These total cloud amount time series for China are derived from the work of Kaiser (1998). The cloud data were extracted from a database of 6-hourly weather observations provided by the National Climate Center of the China Meteorological Administration (CMA) to the U.S. Department of Energy's Carbon Dioxide Information Analysis Center (CDIAC) through a bilateral research agreement. Surface-observed (visual) six-hourly observations [0200, 0800, 1400, and 2000 Beijing Time (BT)] of cloud amount (0-10 tenths of sky cover) were available from 196 Chinese stations covering the period 1954-94. Data from 1951-1953 were also available; however, they only included 0800, 1400, and 2000 BT observations.

Developing Remote Sensing Capabilities for Meter-Scale Sea Ice Properties

DTIC Science & Technology

2013-09-30

such as MODIS . APPROACH 1. Task and acquire high resolution panchromatic and multispectral optical (e.g. Quickbird, Worldview, National Assets...does not display a currently valid OMB control number. 1. REPORT DATE 30 SEP 2013 2. REPORT TYPE 3. DATES COVERED 00-00-2013 to 00-00-2013 4...cloud cover , an excessive percentage of the imagery acquired over drifting sites was cloud covered , and the vendor did not delay acquisitions or

Normalized-Difference Snow Index (NDSI)

NASA Technical Reports Server (NTRS)

Hall, Dorothy K.; Riggs, George A.

2010-01-01

The Normalized-Difference Snow Index (NDSI) has a long history. 'The use of ratioing visible (VIS) and near-infrared (NIR) or short-wave infrared (SWIR) channels to separate snow and clouds was documented in the literature beginning in the mid-1970s. A considerable amount of work on this subject was conducted at, and published by, the Air Force Geophysics Laboratory (AFGL). The objective of the AFGL work was to discriminate snow cover from cloud cover using an automated algorithm to improve global cloud analyses. Later, automated methods that relied on the VIS/NIR ratio were refined substantially using satellite data In this section we provide a brief history of the use of the NDSI for mapping snow cover.

HCMM/soil moisture experiment. [relationship between surface minus air temperature differential and available water according to crop type in Canada

NASA Technical Reports Server (NTRS)

Cihlar, J. (Principal Investigator)

1980-01-01

Progress in the compilation and analysis of airborne and ground data to determine the relationship between the maximum surface minus maximum air temperature differential (delta Tsa) and available water (PAW) is reported. Also, results of an analysis of HCMM images to determine the effect of cloud cover on the availability of HCMM-type data are presented. An inverse relationship between delta Tsa and PAW is indicated along with stable delta Tsa vs. PAW distributions for fully developed canopies. Large variations, both geographical and diurnal, in the cloud cover images are reported. The average monthly daytime cloud cover fluctuated between 40 and 60 percent.

Filling of Cloud-Induced Gaps for Land Use and Land Cover Classifications Around Refugee Camps

NASA Astrophysics Data System (ADS)

Braun, Andreas; Hagensieker, Ron; Hochschild, Volker

2016-08-01

Clouds cover is one of the main constraints in the field of optical remote sensing. Especially the use of multispectral imagery is affected by either fully obscured data or parts of the image which remain unusable. This study compares four algorithms for the filling of cloud induced gaps in classified land cover products based on Markov Random Fields (MRF), Random Forest (RF), Closest Spectral Fit (CSF) operators. They are tested on a classified image of Sentinel-2 where artificial clouds are filled by information derived from a scene of Sentinel-1. The approaches rely on different mathematical principles and therefore produced results varying in both pattern and quality. Overall accuracies for the filled areas range from 57 to 64 %. Best results are achieved by CSF, however some classes (e.g. sands and grassland) remain critical through all approaches.

Providing Diurnal Sky Cover Data at ARM Sites

DOE Office of Scientific and Technical Information (OSTI.GOV)

Klebe, Dimitri I.

2015-03-06

The Solmirus Corporation was awarded two-year funding to perform a comprehensive data analysis of observations made during Solmirus’ 2009 field campaign (conducted from May 21 to July 27, 2009 at the ARM SGP site) using their All Sky Infrared Visible Analyzer (ASIVA) instrument. The objective was to develop a suite of cloud property data products for the ASIVA instrument that could be implemented in real time and tailored for cloud modelers. This final report describes Solmirus’ research and findings enabled by this grant. The primary objective of this award was to develop a diurnal sky cover (SC) data product utilizingmore » the ASIVA’s infrared (IR) radiometrically-calibrated data and is described in detail. Other data products discussed in this report include the sky cover derived from ASIVA’s visible channel and precipitable water vapor, cloud temperature (both brightness and color), and cloud height inferred from ASIVA’s IR channels.« less

Monitoring snow cover variability (2000-2014) in the Hengduan Mountains based on cloud-removed MODIS products with an adaptive spatio-temporal weighted method

NASA Astrophysics Data System (ADS)

Li, Xinghua; Fu, Wenxuan; Shen, Huanfeng; Huang, Chunlin; Zhang, Liangpei

2017-08-01

Monitoring the variability of snow cover is necessary and meaningful because snow cover is closely connected with climate and ecological change. In this work, 500 m resolution MODIS daily snow cover products from 2000 to 2014 were adopted to analyze the status in Hengduan Mountains. In order to solve the spatial discontinuity caused by clouds in the products, we propose an adaptive spatio-temporal weighted method (ASTWM), which is based on the initial result of a Terra and Aqua combination. This novel method simultaneously considers the temporal and spatial correlations of the snow cover. The simulated experiments indicate that ASTWM removes clouds completely, with a robust overall accuracy (OA) of above 93% under different cloud fractions. The spatio-temporal variability of snow cover in the Hengduan Mountains was investigated with two indices: snow cover days (SCD) and snow fraction. The results reveal that the annual SCD gradually increases and the coefficient of variation (CV) decreases with elevation. The pixel-wise trends of SCD first rise and then drop in most areas. Moreover, intense intra-annual variability of the snow fraction occurs from October to March, during which time there is abundant snow cover. The inter-annual variability, which mainly occurs in high elevation areas, shows an increasing trend before 2004/2005 and a decreasing trend after 2004/2005. In addition, the snow fraction responds to the two climate factors of air temperature and precipitation. For the intra-annual variability, when the air temperature and precipitation decrease, the snow cover increases. Besides, precipitation plays a more important role in the inter-annual variability of snow cover than temperature.

Combined retrieval of Arctic liquid water cloud and surface snow properties using airborne spectral solar remote sensing

NASA Astrophysics Data System (ADS)

Ehrlich, André; Bierwirth, Eike; Istomina, Larysa; Wendisch, Manfred

2017-09-01

The passive solar remote sensing of cloud properties over highly reflecting ground is challenging, mostly due to the low contrast between the cloud reflectivity and that of the underlying surfaces (sea ice and snow). Uncertainties in the retrieved cloud optical thickness τ and cloud droplet effective radius reff, C may arise from uncertainties in the assumed spectral surface albedo, which is mainly determined by the generally unknown effective snow grain size reff, S. Therefore, in a first step the effects of the assumed snow grain size are systematically quantified for the conventional bispectral retrieval technique of τ and reff, C for liquid water clouds. In general, the impact of uncertainties of reff, S is largest for small snow grain sizes. While the uncertainties of retrieved τ are independent of the cloud optical thickness and solar zenith angle, the bias of retrieved reff, C increases for optically thin clouds and high Sun. The largest deviations between the retrieved and true original values are found with 83 % for τ and 62 % for reff, C. In the second part of the paper a retrieval method is presented that simultaneously derives all three parameters (τ, reff, C, reff, S) and therefore accounts for changes in the snow grain size. Ratios of spectral cloud reflectivity measurements at the three wavelengths λ1 = 1040 nm (sensitive to reff, S), λ2 = 1650 nm (sensitive to τ), and λ3 = 2100 nm (sensitive to reff, C) are combined in a trispectral retrieval algorithm. In a feasibility study, spectral cloud reflectivity measurements collected by the Spectral Modular Airborne Radiation measurement sysTem (SMART) during the research campaign Vertical Distribution of Ice in Arctic Mixed-Phase Clouds (VERDI, April/May 2012) were used to test the retrieval procedure. Two cases of observations above the Canadian Beaufort Sea, one with dense snow-covered sea ice and another with a distinct snow-covered sea ice edge are analysed. The retrieved values of τ, reff, C, and reff, S show a continuous transition of cloud properties across snow-covered sea ice and open water and are consistent with estimates based on satellite data. It is shown that the uncertainties of the trispectral retrieval increase for high values of τ, and low reff, S but nevertheless allow the effective snow grain size in cloud-covered areas to be estimated.

The effect of South American biomass burning aerosol emissions on the regional climate

NASA Astrophysics Data System (ADS)

Thornhill, Gillian D.; Ryder, Claire L.; Highwood, Eleanor J.; Shaffrey, Len C.; Johnson, Ben T.

2018-04-01

The impact of biomass burning aerosol (BBA) on the regional climate in South America is assessed using 30-year simulations with a global atmosphere-only configuration of the Met Office Unified Model. We compare two simulations of high and low emissions of biomass burning aerosol based on realistic interannual variability. The aerosol scheme in the model has hygroscopic growth and optical properties for BBA informed by recent observations, including those from the recent South American Biomass Burning Analysis (SAMBBA) intensive aircraft observations made during September 2012. We find that the difference in the September (peak biomass emissions month) BBA optical depth between a simulation with high emissions and a simulation with low emissions corresponds well to the difference in the BBA emissions between the two simulations, with a 71.6 % reduction from high to low emissions for both the BBA emissions and the BB AOD in the region with maximum emissions (defined by a box of extent 5-25° S, 40-70° W, used for calculating mean values given below). The cloud cover at all altitudes in the region of greatest BBA difference is reduced as a result of the semi-direct effect, by heating of the atmosphere by the BBA and changes in the atmospheric stability and surface fluxes. Within the BBA layer the cloud is reduced by burn-off, while the higher cloud changes appear to be responding to stability changes. The boundary layer is reduced in height and stabilized by increased BBA, resulting in reduced deep convection and reduced cloud cover at heights of 9-14 km, above the layer of BBA. Despite the decrease in cloud fraction, September downwelling clear-sky and all-sky shortwave radiation at the surface is reduced for higher emissions by 13.77 ± 0.39 W m-2 (clear-sky) and 7.37 ± 2.29 W m-2 (all-sky), whilst the upwelling shortwave radiation at the top of atmosphere is increased in clear sky by 3.32 ± 0.09 W m-2, but decreased by -1.36±1.67 W m-2 when cloud changes are included. Shortwave heating rates increase in the aerosol layer by 18 % in the high emissions case. The mean surface temperature is reduced by 0.14 ± 0.24 °C and mean precipitation is reduced by 14.5 % in the peak biomass region due to both changes in cloud cover and cloud microphysical properties. If the increase in BBA occurs in a particularly dry year, the resulting reduction in precipitation may exacerbate the drought. The position of the South Atlantic high pressure is slightly altered by the presence of increased BBA, and the strength of the southward low-level jet to the east of the Andes is increased. There is some evidence that some impacts of increased BBA persist through the transition into the monsoon, particularly in precipitation, but the differences are only statistically significant in some small regions in November. This study therefore provides an insight into how variability in deforestation, realized through variability in biomass burning emissions, may contribute to the South American climate, and consequently on the possible impacts of future changes in BBA emissions.

The Impact of Low-Level Cloud Feedback on Persistent Changes in Atmospheric Circulation in the Pacific

NASA Astrophysics Data System (ADS)

Burgman, R.; Kirtman, B. P.; Clement, A. C.; Vazquez, H.

2017-12-01

Recent studies suggest that low clouds in the Pacific play an important role in the observed decadal climate variability and future climate change. In this study, we implement a novel modeling experiment designed to isolate how interactions between local and remote feedbacks associated with low cloud, SSTs, and the largescale circulation play a significant role in the observed persistence of tropical Pacific SST and associated North American drought. The modeling approach involves the incorporation of observed patterns of satellite-derived shortwave cloud radiative effect (SWCRE) into the coupled model framework and is ideally suited for examining the role of local and large-scale coupled feedbacks and ocean heat transport in Pacific decadal variability. We show that changes in SWCRE forcing in eastern subtropical Pacific alone reproduces much of the observed changes in SST and atmospheric circulation over the past 16 years, including the observed changes in precipitation over much of the Western Hemisphere.

The Oort cloud

NASA Technical Reports Server (NTRS)

Marochnik, Leonid S.; Mukhin, Lev M.; Sagdeev, Roald Z.

1991-01-01

Views of the large-scale structure of the solar system, consisting of the Sun, the nine planets and their satellites, changed when Oort demonstrated that a gigantic cloud of comets (the Oort cloud) is located on the periphery of the solar system. The following subject areas are covered: (1) the Oort cloud's mass; (2) Hill's cloud mass; (3) angular momentum distribution in the solar system; and (4) the cometary cloud around other stars.

Phytoplankton in the Beaufort and Chukchi Seas: Distributions, Dynamics and Environmental Forcing

NASA Technical Reports Server (NTRS)

Wang, Jian; Cota, Glenn F.; Comiso, Josefino C.

2005-01-01

Time-series of remotely sensed distributions of phytoplankton, sea ice, surface temperature, albedo, and clouds were examined to evaluate the impact of the variability of environmental conditions and physical forcing on the phytoplankton distribution in the Beaufort and Chukchi Seas. Large-scale distributions of these parameters were studied for the first time using weekly and monthly composites from April 1998 through September 2002. The basic data set used in this study are phytoplankton pigment concentration derived from the Sea-viewing Wide Field-of-view Sensor (SeaWiFS), ice concentration obtained from the Special Sensor Microwave Imager (SSM/I) and surface temperature, cloud cover, and albedo derived from the Advanced Very High Resolution Radiometer (AVHRR). Seasonal variations of the sea ice cover was observed to be the dominant environmental factor as the ice edge blooms followed the retreating marginal ice zones northward. Blooms were most prominent in the southwestern Chukchi Sea, and were especially persistent immediately north of the Bering Strait in nutrient- rich Anadyr water and in some fronts. Chlorophyll concentrations are shown to increase from a nominal value during onset of melt in April to a maximum value in mid-spring or summer depending on location. Large interannual variability of ice cover and phytoplankton distributions was observed with the year 1998 being uniquely associated with an early season occurrence of a massive bloom. This is postulated to be caused in part by a rapid response of phytoplankton to an early retreat of the sea ice cover in the Beaufort Sea region. Correlation analyses showed relatively high negative correlation between chlorophyll and ice concentration with the correlation being highest in May, the correlation coefficient being -0.45. 1998 was also the warmest among the five years globally and the sea ice cover was least extensive in the Beaufort-Khukchi Sea region, partly because of the 1997-98 El Nino. Strong correlations were noted between ice extent and surface temperature, the correlation coefficient being highest at - 0.79 in April, during the onset of the bloom period

D Land Cover Classification Based on Multispectral LIDAR Point Clouds

NASA Astrophysics Data System (ADS)

Zou, Xiaoliang; Zhao, Guihua; Li, Jonathan; Yang, Yuanxi; Fang, Yong

2016-06-01

Multispectral Lidar System can emit simultaneous laser pulses at the different wavelengths. The reflected multispectral energy is captured through a receiver of the sensor, and the return signal together with the position and orientation information of sensor is recorded. These recorded data are solved with GNSS/IMU data for further post-processing, forming high density multispectral 3D point clouds. As the first commercial multispectral airborne Lidar sensor, Optech Titan system is capable of collecting point clouds data from all three channels at 532nm visible (Green), at 1064 nm near infrared (NIR) and at 1550nm intermediate infrared (IR). It has become a new source of data for 3D land cover classification. The paper presents an Object Based Image Analysis (OBIA) approach to only use multispectral Lidar point clouds datasets for 3D land cover classification. The approach consists of three steps. Firstly, multispectral intensity images are segmented into image objects on the basis of multi-resolution segmentation integrating different scale parameters. Secondly, intensity objects are classified into nine categories by using the customized features of classification indexes and a combination the multispectral reflectance with the vertical distribution of object features. Finally, accuracy assessment is conducted via comparing random reference samples points from google imagery tiles with the classification results. The classification results show higher overall accuracy for most of the land cover types. Over 90% of overall accuracy is achieved via using multispectral Lidar point clouds for 3D land cover classification.

Accuracy of Geophysical Parameters Derived from AIRS/AMSU as a Function of Fractional Cloud Cover

NASA Technical Reports Server (NTRS)

Susskind, Joel; Barnet, Chris; Blaisdell, John; Iredell, Lena; Keita, Fricky; Kouvaris, Lou; Molnar, Gyula; Chahine, Moustafa

2006-01-01

AIRS was launched on EOS Aqua on May 4,2002, together with AMSU A and HSB, to form a next generation polar orbiting infrared and microwave atmospheric sounding system. The primary products of AIRS/AMSU are twice daily global fields of atmospheric temperature-humidity profiles, ozone profiles, sea/land surface skin temperature, and cloud related parameters including OLR. The sounding goals of AIRS are to produce 1 km tropospheric layer mean temperatures with an rms error of lK, and layer precipitable water with an rms error of 20 percent, in cases with up to 80 percent effective cloud cover. The basic theory used to analyze Atmospheric InfraRed Sounder/Advanced Microwave Sounding Unit/Humidity Sounder Brazil (AIRS/AMSU/HSB) data in the presence of clouds, called the at-launch algorithm, was described previously. Pre-launch simulation studies using this algorithm indicated that these results should be achievable. Some modifications have been made to the at-launch retrieval algorithm as described in this paper. Sample fields of parameters retrieved from AIRS/AMSU/HSB data are presented and validated as a function of retrieved fractional cloud cover. As in simulation, the degradation of retrieval accuracy with increasing cloud cover is small and the RMS accuracy of lower tropospheric temperature retrieved with 80 percent cloud cover is about 0.5 K poorer than for clear cases. HSB failed in February 2003, and consequently HSB channel radiances are not used in the results shown in this paper. The AIRS/AMSU retrieval algorithm described in this paper, called Version 4, become operational at the Goddard DAAC (Distributed Active Archive Center) in April 2003 and is being used to analyze near-real time AIRS/AMSU data. Historical AIRS/AMSU data, going backwards from March 2005 through September 2002, is also being analyzed by the DAAC using the Version 4 algorithm.

Shallow cumulus rooted in photosynthesis

NASA Astrophysics Data System (ADS)

Vila-Guerau Arellano, J.; Ouwersloot, H.; Horn, G.; Sikma, M.; Jacobs, C. M.; Baldocchi, D.

2014-12-01

We investigate the interaction between plant evapotranspiration, controlled by photosynthesis (for a low vegetation cover by C3 and C4 grasses), and the moist thermals that are responsible for the formation and development of shallow cumulus clouds (SCu). We perform systematic numerical experiments at fine spatial scales using large-eddy simulations explicitly coupled to a plant-physiology model. To break down the complexity of the vegetation-atmospheric system at the diurnal scales, we design the following experiments with increasing complexity: (a) clouds that are transparent to radiation, (b) clouds that shade the surface from the incoming shortwave radiation and (c) plant stomata whose apertures react with an adjustment in time to cloud perturbations. The shading by SCu leads to a strong spatial variability in photosynthesis and the surface energy balance. As a result, experiment (b) simulates SCu that are characterized by less extreme and less skewed values of the liquid water path and cloud-base height. These findings are corroborated by the calculation of characteristics lengths scales of the thermals and clouds using autocorrelation and spectral analysis methods. We find that experiments (a) and (b) are characterized by similar cloud cover evolution, but different cloud population characteristics. Experiment (b), including cloud shading, is characterized by smaller clouds, but closer to each other. By performing a sensitivity analysis on the exchange of water vapor and carbon dioxide at the canopy level, we show that the larger water-use efficiency of C4 grass leads to two opposing effects that directly influence boundary-layer clouds: the thermals below the clouds are more vigorous and deeper driven by a larger buoyancy surface flux (positive effect), but are characterized by less moisture content (negative effect). We conclude that under the investigated mid-latitude atmospheric and well-watered soil conditions, SCu over C4 grass fields is characterized by larger cloud cover and an enhanced liquid water path compared to C3 grass fields.

Detecting long-duration cloud contamination in hyper-temporal NDVI imagery

NASA Astrophysics Data System (ADS)

Ali, Amjad; de Bie, C. A. J. M.; Skidmore, A. K.

2013-10-01

Cloud contamination impacts on the quality of hyper-temporal NDVI imagery and its subsequent interpretation. Short-duration cloud impacts are easily removed by using quality flags and an upper envelope filter, but long-duration cloud contamination of NDVI imagery remains. In this paper, an approach that goes beyond the use of quality flags and upper envelope filtering is tested to detect when and where long-duration clouds are responsible for unreliable NDVI readings, so that a user can flag those data as missing. The study is based on MODIS Terra and the combined Terra-Aqua 16-day NDVI product for the south of Ghana, where persistent cloud cover occurs throughout the year. The combined product could be assumed to have less cloud contamination, since it is based on two images per day. Short-duration cloud effects were removed from the two products through using the adaptive Savitzky-Golay filter. Then for each 'cleaned' product an unsupervised classified map was prepared using the ISODATA algorithm, and, by class, plots were prepared to depict changes over time of the means and the standard deviations in NDVI values. By comparing plots of similar classes, long-duration cloud contamination appeared to display a decline in mean NDVI below the lower limit 95% confidence interval with a coinciding increase in standard deviation above the upper limit 95% confidence interval. Regression analysis was carried out per NDVI class in two randomly selected groups in order to statistically test standard deviation values related to long-duration cloud contamination. A decline in seasonal NDVI values (growing season) were below the lower limit of 95% confidence interval as well as a concurrent increase in standard deviation values above the upper limit of the 95% confidence interval were noted in 34 NDVI classes. The regression analysis results showed that differences in NDVI class values between the Terra and the Terra-Aqua imagery were significantly correlated (p < 0.05) with the corresponding standard deviation values of the Terra imagery in case of all NDVI classes of two selected NDVI groups. The method successfully detects long-duration cloud contamination that results in unreliable NDVI values. The approach offers scientists interested in time series analysis a method of masking by area (class) the periods when pre-cleaned NDVI values remain affected by clouds. The approach requires no additional data for execution purposes but involves unsupervised classification of the imagery to carry out the evaluation of class-specific mean NDVI and standard deviation values over time.

Cloud Tolerance of Remote-Sensing Technologies to Measure Land Surface Temperature

NASA Technical Reports Server (NTRS)

Holmes, Thomas R. H.; Hain, Christopher R.; Anderson, Martha C.; Crow, Wade T.

2016-01-01

Conventional methods to estimate land surface temperature (LST) from space rely on the thermal infrared(TIR) spectral window and is limited to cloud-free scenes. To also provide LST estimates during periods with clouds, a new method was developed to estimate LST based on passive microwave(MW) observations. The MW-LST product is informed by six polar-orbiting satellites to create a global record with up to eight observations per day for each 0.25resolution grid box. For days with sufficient observations, a continuous diurnal temperature cycle (DTC) was fitted. The main characteristics of the DTC were scaled to match those of a geostationary TIR-LST product. This paper tests the cloud tolerance of the MW-LST product. In particular, we demonstrate its stable performance with respect to flux tower observation sites (four in Europe and nine in the United States), over a range of cloudiness conditions up to heavily overcast skies. The results show that TIR based LST has slightly better performance than MW-LST for clear-sky observations but suffers an increasing negative bias as cloud cover increases. This negative bias is caused by incomplete masking of cloud-covered areas within the TIR scene that affects many applications of TIR-LST. In contrast, for MW-LST we find no direct impact of clouds on its accuracy and bias. MW-LST can therefore be used to improve TIR cloud screening. Moreover, the ability to provide LST estimates for cloud-covered surfaces can help expand current clear-sky-only satellite retrieval products to all-weather applications.

A cloud mask methodology for high resolution remote sensing data combining information from high and medium resolution optical sensors

NASA Astrophysics Data System (ADS)

Sedano, Fernando; Kempeneers, Pieter; Strobl, Peter; Kucera, Jan; Vogt, Peter; Seebach, Lucia; San-Miguel-Ayanz, Jesús

2011-09-01

This study presents a novel cloud masking approach for high resolution remote sensing images in the context of land cover mapping. As an advantage to traditional methods, the approach does not rely on thermal bands and it is applicable to images from most high resolution earth observation remote sensing sensors. The methodology couples pixel-based seed identification and object-based region growing. The seed identification stage relies on pixel value comparison between high resolution images and cloud free composites at lower spatial resolution from almost simultaneously acquired dates. The methodology was tested taking SPOT4-HRVIR, SPOT5-HRG and IRS-LISS III as high resolution images and cloud free MODIS composites as reference images. The selected scenes included a wide range of cloud types and surface features. The resulting cloud masks were evaluated through visual comparison. They were also compared with ad-hoc independently generated cloud masks and with the automatic cloud cover assessment algorithm (ACCA). In general the results showed an agreement in detected clouds higher than 95% for clouds larger than 50 ha. The approach produced consistent results identifying and mapping clouds of different type and size over various land surfaces including natural vegetation, agriculture land, built-up areas, water bodies and snow.

Evidence for Limited Indirect Aerosol Forcing in Stratocumulus

NASA Technical Reports Server (NTRS)

Ackerman, Andrew S.; Toon, O. B.; Stevens, D. E.

2003-01-01

Increases in cloud cover and condensed water contribute more than half of the indirect aerosol effect in an ensemble of general circulation model (GCM) simulations estimating the global radiative forcing of anthropogenic aerosols. We use detailed simulations of marine stratocumulus clouds and airborne observations of ship tracks to show that increases in cloud cover and condensed water in reality are far less than represented by the GCM ensemble. Our results offer an explanation for recent simplified inverse climate calculations indicating that indirect aerosol effects are greatly exaggerated in GCMs.

CloudSat Takes a 3D Slice of Hurricane Matthew

NASA Image and Video Library

2016-10-07

NASA's CloudSat flew east of Hurricane Matthew's center on Oct. 6 at 11:30 a.m. PDT (2:30 p.m. EDT), intersecting parts of Matthew's outer rain bands and revealing Matthew's anvil clouds (thick cirrus cloud cover), with cumulus and cumulonimbus clouds beneath (lower image). Reds/pinks are larger water/ice droplets. http://photojournal.jpl.nasa.gov/catalog/PIA21095

The impact of atmospheric stability and wind shear on vertical cloud overlap over the Tibetan Plateau

NASA Astrophysics Data System (ADS)

Li, Jiming; Lv, Qiaoyi; Jian, Bida; Zhang, Min; Zhao, Chuanfeng; Fu, Qiang; Kawamoto, Kazuaki; Zhang, Hua

2018-05-01

Studies have shown that changes in cloud cover are responsible for the rapid climate warming over the Tibetan Plateau (TP) in the past 3 decades. To simulate the total cloud cover, atmospheric models have to reasonably represent the characteristics of vertical overlap between cloud layers. Until now, however, this subject has received little attention due to the limited availability of observations, especially over the TP. Based on the above information, the main aim of this study is to examine the properties of cloud overlaps over the TP region and to build an empirical relationship between cloud overlap properties and large-scale atmospheric dynamics using 4 years (2007-2010) of data from the CloudSat cloud product and collocated ERA-Interim reanalysis data. To do this, the cloud overlap parameter α, which is an inverse exponential function of the cloud layer separation D and decorrelation length scale L, is calculated using CloudSat and is discussed. The parameters α and L are both widely used to characterize the transition from the maximum to random overlap assumption with increasing layer separations. For those non-adjacent layers without clear sky between them (that is, contiguous cloud layers), it is found that the overlap parameter α is sensitive to the unique thermodynamic and dynamic environment over the TP, i.e., the unstable atmospheric stratification and corresponding weak wind shear, which leads to maximum overlap (that is, greater α values). This finding agrees well with the previous studies. Finally, we parameterize the decorrelation length scale L as a function of the wind shear and atmospheric stability based on a multiple linear regression. Compared with previous parameterizations, this new scheme can improve the simulation of total cloud cover over the TP when the separations between cloud layers are greater than 1 km. This study thus suggests that the effects of both wind shear and atmospheric stability on cloud overlap should be taken into account in the parameterization of decorrelation length scale L in order to further improve the calculation of the radiative budget and the prediction of climate change over the TP in the atmospheric models.

Mean winds at the cloud top of Venus obtained from two-wavelength UV imaging by Akatsuki

NASA Astrophysics Data System (ADS)

Horinouchi, Takeshi; Kouyama, Toru; Lee, Yeon Joo; Murakami, Shin-ya; Ogohara, Kazunori; Takagi, Masahiro; Imamura, Takeshi; Nakajima, Kensuke; Peralta, Javier; Yamazaki, Atsushi; Yamada, Manabu; Watanabe, Shigeto

2018-01-01

Venus is covered with thick clouds. Ultraviolet (UV) images at 0.3-0.4 microns show detailed cloud features at the cloud-top level at about 70 km, which are created by an unknown UV-absorbing substance. Images acquired in this wavelength range have traditionally been used to measure winds at the cloud top. In this study, we report low-latitude winds obtained from the images taken by the UV imager, UVI, onboard the Akatsuki orbiter from December 2015 to March 2017. UVI provides images with two filters centered at 365 and 283 nm. While the 365-nm images enable continuation of traditional Venus observations, the 283-nm images visualize cloud features at an SO2 absorption band, which is novel. We used a sophisticated automated cloud-tracking method and thorough quality control to estimate winds with high precision. Horizontal winds obtained from the 283-nm images are generally similar to those from the 365-nm images, but in many cases, westward winds from the former are faster than the latter by a few m/s. From previous studies, one can argue that the 283-nm images likely reflect cloud features at higher altitude than the 365-nm images. If this is the case, the superrotation of the Venusian atmosphere generally increases with height at the cloud-top level, where it has been thought to roughly peak. The mean winds obtained from the 365-nm images exhibit local time dependence consistent with known tidal features. Mean zonal winds exhibit asymmetry with respect to the equator in the latter half of the analysis period, significantly at 365 nm and weakly at 283 nm. This contrast indicates that the relative altitude may vary with time and latitude, and so are the observed altitudes. In contrast, mean meridional winds do not exhibit much long-term variability. A previous study suggested that the geographic distribution of temporal mean zonal winds obtained from UV images from the Venus Express orbiter during 2006-2012 can be interpreted as forced by topographically induced stationary gravity waves. However, the geographic distribution of temporal mean zonal winds we obtained is not consistent with that distribution, which suggests that the distribution may not be persistent. [Figure not available: see fulltext.

The CAUSES Model Intercomparison Project: Using hindcast approach to study the U.S. summertime surface warm temperature bias

NASA Astrophysics Data System (ADS)

Ma, H. Y.; Klein, S. A.; Xie, S.; Zhang, C.; Morcrette, C. J.; Van Weverberg, K.; Petch, J.

2016-12-01

The CAUSES (Clouds Above the United States and Errors at the Surface) is a joint GASS/RGCM/ASR model intercomparison project with an observational focus (data from the U.S. DOE ARM SGP site and other observations). The goal of this project is to evaluate the role of clouds, radiation and precipitation processes in contributing to the surface air temperature bias in the region of the central U.S., which is seen in several weather and climate models. In this project, we use a short-term hindcast approach and examine the error growth due to cloud-associated processes while the large-scale state remains close to observations. The study period is from April 1 to August 31, 2011, which also covers the entire Midlatitude Continental Convective Clouds Experiment (MC3E) campaign that provides very frequent radiosondes (8 per day) and many extensive cloud and precipitation radar observations. Our preliminary analysis indicates that the warm surface air temperature bias in the mean diurnal cycle of the whole study period is very robust across all the participating models over the ARM SGP site. During the spring season (April-May), the daytime warm bias in most models is mostly due to excessive net surface shortwave flux resulting from insufficient deep convective cloud fraction or too optically thin clouds. The nighttime warm bias is likely due to the excessive downwelling longwave flux warming resulting from the persisting deep clouds. During the summer season (June-August), bias contribution from precipitation bias becomes important. The insufficient seasonal accumulated precipitation from the propagating convective systems originated from the Rockies contributes to lower soil moisture. Such condition drives the land surface to a dry state whereby radiative input can only be balanced by sensible heat loss through an increased surface air temperature. More information about the CAUSES project can be found through the following project webpage (http://portal.nersc.gov/project/capt/CAUSES/). (This study is funded by the RGCM and ASR programs of the U.S. Department of Energy as part of the Cloud-Associated Parameterizations Testbed. This work is performed under the auspices of the U.S. Department of Energy by Lawrence Livermore National Laboratory under Contract DE-AC52-07NA27344. LLNL-ABS-688818)

Macrophysical and optical properties of midlatitude high-altitude clouds from 4 ground-based lidars and collocated CALIOP observations

NASA Astrophysics Data System (ADS)

Dupont, J. C.; Haeffelin, M.; Morille, Y.; Noel, V.; Keckhut, P.; Comstock, J.; Winker, D.; Chervet, P.; Roblin, A.

2009-04-01

Cirrus clouds not only play a major role in the energy budget of the Earth-Atmosphere system, but are also important in the hydrological cycle [Stephens et al., 1990; Webster, 1994]. According to satellite passive remote sensing, high-altitude clouds cover as much as 40% of the earth's surface on average (Liou 1986; Stubenrauch et al., 2006) and can reach 70% of cloud cover over the Tropics (Wang et al., 1996; Nazaryan et al., 2008). Hence, given their very large cloud cover, they have a major role in the climate system (Lynch et al. 2001). Cirrus clouds can be classified into three distinct families according to their optical thickness, namely subvisible clouds (OD<0.03), semi-transparent clouds (0.03

Comparasion of Cloud Cover restituted by POLDER and MODIS

NASA Astrophysics Data System (ADS)

Zeng, S.; Parol, F.; Riedi, J.; Cornet, C.; Thieuxleux, F.

2009-04-01

PARASOL and AQUA are two sun-synchronous orbit satellites in the queue of A-Train satellites that observe our earth within a few minutes apart from each other. Aboard these two platforms, POLDER and MODIS provide coincident observations of the cloud cover with very different characteristics. These give us a good opportunity to study the clouds system and evaluate strengths and weaknesses of each dataset in order to provide an accurate representation of global cloud cover properties. This description is indeed of outermost importance to quantify and understand the effect of clouds on global radiation budget of the earth-atmosphere system and their influence on the climate changes. We have developed a joint dataset containing both POLDER and MODIS level 2 cloud products collocated and reprojected on a common sinusoidal grid in order to make the data comparison feasible and veracious. Our foremost work focuses on the comparison of both spatial distribution and temporal variation of the global cloud cover. This simple yet critical cloud parameter need to be clearly understood to allow further comparison of the other cloud parameters. From our study, we demonstrate that on average these two sensors both detect the clouds fairly well. They provide similar spatial distributions and temporal variations:both sensors see high values of cloud amount associated with deep convection in ITCZ, over Indonesia, and in west-central Pacific Ocean warm pool region; they also provide similar high cloud cover associated to mid-latitude storm tracks, to Indian monsoon or to the stratocumulus along the west coast of continents; on the other hand small cloud amounts that typically present over subtropical oceans and deserts in subsidence aeras are well identified by both POLDER and MODIS. Each sensor has its advantages and inconveniences for the detection of a particular cloud types. With higher spatial resolution, MODIS can better detect the fractional clouds thus explaining as one part of a positive bias in any latitude and in any viewing angle with an order of 10% between the POLDER cloud amount and the so-called MODIS "combined" cloud amount. Nevertheless it is worthy to note that a negative bias of about 10% is obtained between the POLDER cloud amount and the MODIS "day-mean" cloud amount. Main differences between the two MODIS cloud amount values are known to be due to the filtering of remaining aerosols or cloud edges. due to both this high spatial resolution of MODIS and the fact that "combined" cloud amount filters cloud edges, we can also explain why appear the high positive bias regions over subtropical ocean in south hemisphere and over east Africa in summer. Thanks to several channels in the thermal infrared spectral domain, MODIS detects probably much better the thin cirrus especially over land, thus causing a general negative bias for ice clouds. The multi-spectral capability of MODIS also allows for a better detection of low clouds over snow or ice, Hence the (POLDER-MODIS) cloud amount difference is often negative over Greenland, Antarctica, and over the continents at middle-high latitudes in spring and autumn associated to the snow coverage. The multi-spectral capability of MODIS also makes the discrimination possible between the biomass burning aerosols and the fractional clouds over the continents. Thus a positive bias appears in central Africa in summer and autumn associated to important biomass burning events. Over transition region between desert and non-desert, the presence of large negative bias (POLDER-MODIS) of cloud amount maybe partly due to MODIS pixel falsely labeled the desert as cloudy, where MODIS algorithm uses static desert mask. This is clearly highlighted in south of Sahara in spring and summer where we find a bias negative with an order of -0.1. What is more, thanks to its multi-angular capability, POLDER can discriminate the sun-glint region thus minimizing the dependence of cloud amount on view angle. It makes the detection of high clouds easier over a black surface thanks to its polarization character.

Integration of MODIS Snow, Cloud and Land Area Coverage Data with SNOTEL to Generate Inter-Annual and Within-Season Snow Depletion Curves and Maps

NASA Astrophysics Data System (ADS)

Qualls, R. J.; Woodruff, C.

2017-12-01

The behavior of inter-annual trends in mountain snow cover would represent extremely useful information for drought and climate change assessment; however, individual data sources exhibit specific limitations for characterizing this behavior. For example, SNOTEL data provide time series point values of Snow Water Equivalent (SWE), but lack spatial content apart from that contained in a sparse network of point values. Satellite observations in the visible spectrum can provide snow covered area, but not SWE at present, and are limited by cloud cover which often obscures visibility of the ground, especially during the winter and spring in mountainous areas. Cloud cover, therefore, often limits both temporal and spatial coverage of satellite remote sensing of snow. Among the platforms providing the best combination of temporal and spatial coverage to overcome the cloud obscuration problem by providing frequent overflights, the Aqua and Terra satellites carrying the MODIS instrument package provide 500 m, daily resolution observations of snow cover. These were only launched in 1999 and the early 2000's, thus limiting the historical period over which these data are available. A hybrid method incorporating SNOTEL and MODIS data has been developed which accomplishes cloud removal, and enables determination of the time series of watershed spatial snow cover when either SNOTEL or MODIS data are available. This allows one to generate spatial snow cover information for watersheds with SNOTEL stations for periods both before and after the launch of the Aqua and Terra satellites, extending the spatial information about snow cover over the period of record of the SNOTEL stations present in a watershed. This method is used to quantify the spatial time series of snow over the 9000 km2 Upper Snake River watershed and to evaluate inter-annual trends in the timing, rate, and duration of melt over the nearly 40 year period from the early 1980's to the present, and shows promise for generating snow cover depletion maps for drought and climate change scenarios.

Cloud Physics Lidar Optical Measurements During the SAFARI-2000 Field Campaign

NASA Technical Reports Server (NTRS)

Hlavka, Dennis L.; McGill, Matt; Hart, William D.; Spinhirne, James D.; Starr, David OC. (Technical Monitor)

2002-01-01

In this presentation, we will show new optical data processing results from the Cloud Physics War during SAFARI-2000. Retrieved products include aerosol and cloud layer location and identification, layer optical depths, vertical extinction profiles, and extinction-to-backscatter (S) ratios for 532 and 1064 nm. The retrievals will focus on the persistent and smoky planetary boundary layer and occasional elevated aerosol layers found in southern Africa during August and September 2000.

Comparison of MODIS and VIIRS Snow Cover Products for the 2016 Hydrological Year

NASA Astrophysics Data System (ADS)

Klein, A. G.; Thapa, S.

2017-12-01

The VIIRS (Visible Infrared Imaging Radiometer Suite) instrument on board the Suomi-NPP satellite aims to provide long-term continuity of several environmental data series including snow cover initiated with MODIS. While it is speculated that MODIS and VIIRS snow cover products may differ because of their differing spatial resolutions and spectral coverage quantitative comparisons between their snow products are currently limited. Therefore this study intercompares MODIS and VIIRS snow products for the 2016 Hydrological Year over the Midwestern United States and southern Canada. Two hundred and forty-four swath snow products from MODIS/Aqua (MYD10L2) and the VIIRS EDR (VSCMO/binary) were intercompared using confusion matrices, comparison maps and false color imagery. Thresholding the MODIS NDSI Snow Cover product at a snow cover fraction of 30% generated binary snow maps most comparable to the NOAA VIIRS binary snow product. Overall agreement between MODIS and VIIRS was found to be approximately 98%. This exceeds the VIIRS accuracy requirements of 90% probability of correct typing. Agreement was highest during the winter but lower during late fall and spring. Comparability was lowest over forest. MODIS and VIIRS often mapped snow/no-snow transition zones as cloud. The assessment of total snow and cloud pixels and comparison snow maps of MODIS and VIIRS indicates that VIIRS is mapping more snow cover and less cloud cover compared to MODIS. This is evidenced by the average area of snow in MYD10L2 and VSCMO being 5.72% and 11.43%, no-snow 26.65% and 28.67%, and cloud 65.02% and 59.91%, respectively. Visual comparisons depict good qualitative agreement between snow cover area visible in MODIS and VIIRS false color imagery and mapped in their respective snow cover products. While VIIRS and MODIS have similar capacity to map snow cover, VIIRS has the potential to more accurately map snow cover area for the successive development of climate data records.

Assessing the accuracy of MISR and MISR-simulated cloud top heights using CloudSat- and CALIPSO-retrieved hydrometeor profiles

NASA Astrophysics Data System (ADS)

Hillman, Benjamin R.; Marchand, Roger T.; Ackerman, Thomas P.; Mace, Gerald G.; Benson, Sally

2017-03-01

Satellite retrievals of cloud properties are often used in the evaluation of global climate models, and in recent years satellite instrument simulators have been used to account for known retrieval biases in order to make more consistent comparisons between models and retrievals. Many of these simulators have seen little critical evaluation. Here we evaluate the Multiangle Imaging Spectroradiometer (MISR) simulator by using visible extinction profiles retrieved from a combination of CloudSat, CALIPSO, MODIS, and AMSR-E observations as inputs to the MISR simulator and comparing cloud top height statistics from the MISR simulator with those retrieved by MISR. Overall, we find that the occurrence of middle- and high-altitude topped clouds agrees well between MISR retrievals and the MISR-simulated output, with distributions of middle- and high-topped cloud cover typically agreeing to better than 5% in both zonal and regional averages. However, there are significant differences in the occurrence of low-topped clouds between MISR retrievals and MISR-simulated output that are due to differences in the detection of low-level clouds between MISR and the combined retrievals used to drive the MISR simulator, rather than due to errors in the MISR simulator cloud top height adjustment. This difference highlights the importance of sensor resolution and boundary layer cloud spatial structure in determining low-altitude cloud cover. The MISR-simulated and MISR-retrieved cloud optical depth also show systematic differences, which are also likely due in part to cloud spatial structure.

Clouds at Barbados are representative of clouds across the trade wind regions in observations and climate models.

PubMed

Medeiros, Brian; Nuijens, Louise

2016-05-31

Trade wind regions cover most of the tropical oceans, and the prevailing cloud type is shallow cumulus. These small clouds are parameterized by climate models, and changes in their radiative effects strongly and directly contribute to the spread in estimates of climate sensitivity. This study investigates the structure and variability of these clouds in observations and climate models. The study builds upon recent detailed model evaluations using observations from the island of Barbados. Using a dynamical regimes framework, satellite and reanalysis products are used to compare the Barbados region and the broader tropics. It is shown that clouds in the Barbados region are similar to those across the trade wind regions, implying that observational findings from the Barbados Cloud Observatory are relevant to clouds across the tropics. The same methods are applied to climate models to evaluate the simulated clouds. The models generally capture the cloud radiative effect, but underestimate cloud cover and show an array of cloud vertical structures. Some models show strong biases in the environment of the Barbados region in summer, weakening the connection between the regional biases and those across the tropics. Even bearing that limitation in mind, it is shown that covariations of cloud and environmental properties in the models are inconsistent with observations. The models tend to misrepresent sensitivity to moisture variations and inversion characteristics. These model errors are likely connected to cloud feedback in climate projections, and highlight the importance of the representation of shallow cumulus convection.

Clouds at Barbados are representative of clouds across the trade wind regions in observations and climate models

PubMed Central

Nuijens, Louise

2016-01-01

Trade wind regions cover most of the tropical oceans, and the prevailing cloud type is shallow cumulus. These small clouds are parameterized by climate models, and changes in their radiative effects strongly and directly contribute to the spread in estimates of climate sensitivity. This study investigates the structure and variability of these clouds in observations and climate models. The study builds upon recent detailed model evaluations using observations from the island of Barbados. Using a dynamical regimes framework, satellite and reanalysis products are used to compare the Barbados region and the broader tropics. It is shown that clouds in the Barbados region are similar to those across the trade wind regions, implying that observational findings from the Barbados Cloud Observatory are relevant to clouds across the tropics. The same methods are applied to climate models to evaluate the simulated clouds. The models generally capture the cloud radiative effect, but underestimate cloud cover and show an array of cloud vertical structures. Some models show strong biases in the environment of the Barbados region in summer, weakening the connection between the regional biases and those across the tropics. Even bearing that limitation in mind, it is shown that covariations of cloud and environmental properties in the models are inconsistent with observations. The models tend to misrepresent sensitivity to moisture variations and inversion characteristics. These model errors are likely connected to cloud feedback in climate projections, and highlight the importance of the representation of shallow cumulus convection. PMID:27185925

Progressive Mid-latitude Afforestation: Local and Remote Climate Impacts in the Framework of Two Coupled Earth System Models

NASA Astrophysics Data System (ADS)

Lague, Marysa

Vegetation influences the atmosphere in complex and non-linear ways, such that large-scale changes in vegetation cover can drive changes in climate on both local and global scales. Large-scale land surface changes have been shown to introduce excess energy to one hemisphere, causing a shift in atmospheric circulation on a global scale. However, past work has not quantified how the climate response scales with the area of vegetation. Here, we systematically evaluate the response of climate to linearly increasing the area of forest cover over the northern mid-latitudes. We show that the magnitude of afforestation of the northern mid-latitudes determines the climate response in a non-linear fashion, and identify a threshold in vegetation-induced cloud feedbacks - a concept not previously addressed by large-scale vegetation manipulation experiments. Small increases in tree cover drive compensating cloud feedbacks, while latent heat fluxes reach a threshold after sufficiently large increases in tree cover, causing the troposphere to warm and dry, subsequently reducing cloud cover. Increased absorption of solar radiation at the surface is driven by both surface albedo changes and cloud feedbacks. We identify how vegetation-induced changes in cloud cover further feedback on changes in the global energy balance. We also show how atmospheric cross-equatorial energy transport changes as the area of afforestation is incrementally increased (a relationship which has not previously been demonstrated). This work demonstrates that while some climate effects (such as energy transport) of large scale mid-latitude afforestation scale roughly linearly across a wide range of afforestation areas, others (such as the local partitioning of the surface energy budget) are non-linear, and sensitive to the particular magnitude of mid-latitude forcing. Our results highlight the importance of considering both local and remote climate responses to large-scale vegetation change, and explore the scaling relationship between changes in vegetation cover and the resulting climate impacts.

Ship track observations of a reduced shortwave aerosol indirect effect in mixed-phase clouds

NASA Astrophysics Data System (ADS)

Christensen, M. W.; Suzuki, K.; Zambri, B.; Stephens, G. L.

2014-10-01

Aerosol influences on clouds are a major source of uncertainty to our understanding of forced climate change. Increased aerosol can enhance solar reflection from clouds countering greenhouse gas warming. Recently, this indirect effect has been extended from water droplet clouds to other types including mixed-phase clouds. Aerosol effects on mixed-phase clouds are important because of their fundamental role on sea ice loss and polar climate change, but very little is known about aerosol effects on these clouds. Here we provide the first analysis of the effects of aerosol emitted from ship stacks into mixed-phase clouds. Satellite observations of solar reflection in numerous ship tracks reveal that cloud albedo increases 5 times more in liquid clouds when polluted and persist 2 h longer than in mixed-phase clouds. These results suggest that seeding mixed-phase clouds via shipping aerosol is unlikely to provide any significant counterbalancing solar radiative cooling effects in warming polar regions.

Physics Parameterization for Seasonal Prediction

DTIC Science & Technology

2012-09-30

comparison Project, a joint effort between the Year of Tropical Convection (YOTC) Program and the Global Energy and Water Cycle Experiment (GEWEX) Cloud...unified” representation of the water cycle in the model. One such area is the correspondence between diagnosed cloud cover and prognostic cloud

Accuracy of Geophysical Parameters Derived from AIRS/AMSU as a Function of Fractional Cloud Cover

NASA Technical Reports Server (NTRS)

Susskind, Joel; Barnet, Chris; Blaisdell, John; Iredell, Lena; Keita, Fricky; Kouvaris, Lou; Molnar, Gyula; Chahine, Moustafa

2005-01-01

AIRS was launched on EOS Aqua on May 4,2002, together with AMSU A and HSB, to form a next generation polar orbiting infrared and microwave atmospheric sounding system. The primary products of AIRS/AMSU are twice daily global fields of atmospheric temperature-humidity profiles, ozone profiles, sea/land surface skin temperature, and cloud related parameters including OLR. The sounding goals of AIRS are to produce 1 km tropospheric layer mean temperatures with an rms error of 1K, and layer precipitable water with an rms error of 20%, in cases with up to 80% effective cloud cover. The basic theory used to analyze AIRS/AMSU/HSB data in the presence of clouds, called the at-launch algorithm, was described previously. Pre-launch simulation studies using this algorithm indicated that these results should be achievable. Some modifications have been made to the at-launch retrieval algorithm as described in this paper. Sample fields of parameters retrieved from AIRS/AMSU/HSB data are presented and validated as a function of retrieved fractional cloud cover. As in simulation, the degradation of retrieval accuracy with increasing cloud cover is small. HSB failed in February 2005, and consequently HSB channel radiances are not used in the results shown in this paper. The AIRS/AMSU retrieval algorithm described in this paper, called Version 4, become operational at the Goddard DAAC in April 2005 and is being used to analyze near-real time AIRS/AMSU data. Historical AIRS/AMSU data, going backwards from March 2005 through September 2002, is also being analyzed by the DAAC using the Version 4 algorithm.

Spectral Cloud-Filtering of AIRS Data: Non-Polar Ocean

NASA Technical Reports Server (NTRS)

Aumann, Hartmut H.; Gregorich, David; Barron, Diana

2004-01-01

The Atmospheric Infrared Sounder (AIRS) is a grating array spectrometer which covers the thermal infrared spectral range between 640 and 1700/cm. In order to retain the maximum radiometric accuracy of the AIRS data, the effects of cloud contamination have to be minimized. We discuss cloud filtering which uses the high spectral resolution of AIRS to identify about 100,000 of 500,000 non-polar ocean spectra per day as relatively "cloud-free". Based on the comparison of surface channels with the NCEP provided global real time sst (rtg.sst), AIRS surface sensitive channels have a cold bias ranging from O.5K during the day to 0.8K during the night. Day and night spatial coherence tests show that the cold bias is due to cloud contamination. During the day the cloud contamination is due to a 2-3% broken cloud cover at the 1-2 km altitude, characteristic of low stratus clouds. The cloud-contamination effects surface sensitive channels only. Cloud contamination can be reduced to 0.2K by combining the spectral filter with a spatial coherence threshold, but the yield drops to 16,000 spectra per day. AIRS was launched in May 2002 on the Earth Observing System (EOS) Aqua satellite. Since September 2002 it has returned 4 million spectra of the globe each day.

The GFS Atmospheric Model description

Science.gov Websites

model has only one type of cloud cover represented by C. In the tropics the cloudiness is primarily due mainly through grid-scale condensation. The fractional cloud cover C is available at all model levels , 1996: Parameterizations for the absorption of solar radiation by water vapor and ozone. J. Atmos. Sci

Sources of variation in Landsat autocorrelation

NASA Technical Reports Server (NTRS)

Craig, R. G.; Labovitz, M. L.

1980-01-01

Analysis of sixty-four scan lines representing diverse conditions across satellites, channels, scanners, locations and cloud cover confirms that Landsat data are autocorrelated and consistently follow an Arima (1,0,1) pattern. The AR parameter varies significantly with location and the MA coefficient with cloud cover. Maximum likelihood classification functions are considerably in error unless this autocorrelation is compensated for in sampling.

Preliminary verification for application of a support vector machine-based cloud detection method to GOSAT-2 CAI-2

NASA Astrophysics Data System (ADS)

Oishi, Yu; Ishida, Haruma; Nakajima, Takashi Y.; Nakamura, Ryosuke; Matsunaga, Tsuneo

2018-05-01

The Greenhouse Gases Observing Satellite (GOSAT) was launched in 2009 to measure global atmospheric CO2 and CH4 concentrations. GOSAT is equipped with two sensors: the Thermal And Near infrared Sensor for carbon Observations (TANSO)-Fourier transform spectrometer (FTS) and TANSO-Cloud and Aerosol Imager (CAI). The presence of clouds in the instantaneous field of view of the FTS leads to incorrect estimates of the concentrations. Thus, the FTS data suspected to have cloud contamination must be identified by a CAI cloud discrimination algorithm and rejected. Conversely, overestimating clouds reduces the amount of FTS data that can be used to estimate greenhouse gas concentrations. This is a serious problem in tropical rainforest regions, such as the Amazon, where the amount of useable FTS data is small because of cloud cover. Preparations are continuing for the launch of the GOSAT-2 in fiscal year 2018. To improve the accuracy of the estimates of greenhouse gases concentrations, we need to refine the existing CAI cloud discrimination algorithm: Cloud and Aerosol Unbiased Decision Intellectual Algorithm (CLAUDIA1). A new cloud discrimination algorithm using a support vector machine (CLAUDIA3) was developed and presented in another paper. Although the use of visual inspection of clouds as a standard for judging is not practical for screening a full satellite data set, it has the advantage of allowing for locally optimized thresholds, while CLAUDIA1 and -3 use common global thresholds. Thus, the accuracy of visual inspection is better than that of these algorithms in most regions, with the exception of snow- and ice-covered surfaces, where there is not enough spectral contrast to identify cloud. In other words, visual inspection results can be used as truth data for accuracy evaluation of CLAUDIA1 and -3. For this reason visual inspection can be used for the truth metric for the cloud discrimination verification exercise. In this study, we compared CLAUDIA1-CAI and CLAUDIA3-CAI for various land cover types, and evaluated the accuracy of CLAUDIA3-CAI by comparing both CLAUDIA1-CAI and CLAUDIA3-CAI with visual inspection (400 × 400 pixels) of the same CAI images in tropical rainforests. Comparative results between CLAUDIA1-CAI and CLAUDIA3-CAI for various land cover types indicated that CLAUDIA3-CAI had a tendency to identify bright surface and optically thin clouds. However, CLAUDIA3-CAI had a tendency to misjudge the edges of clouds compared with CLAUDIA1-CAI. The accuracy of CLAUDIA3-CAI was approximately 89.5 % in tropical rainforests, which is greater than that of CLAUDIA1-CAI (85.9 %) for the test cases presented here.

Characterizing Arctic mixed-phase cloud structure and its relationship with humidity and temperature inversion using ARM NSA observations

NASA Astrophysics Data System (ADS)

Qiu, Shaoyue; Dong, Xiquan; Xi, Baike; Li, J.-L. F.

2015-08-01

In this study, the characteristics of the Arctic mixed-phase cloud (AMC) have been investigated using data collected at the Atmospheric Radiation Measurement North Slope Alaska site from October 2006 to September 2009. AMC has an annual occurrence frequency of 42.3%, which includes 18.7% of single-layered AMCs and 23.6% for multiple layers. Two cloud base heights (CBHs) are defined from ceilometer and micropulse lidar (MPL) measurements. For single-layered AMC, the ceilometer-derived CBH represents the base of the liquid-dominant layer near the cloud top, while MPL-derived CBH represents base of the lower ice-dominant layer. The annual mean CBHs from ceilometer and MPL measurements are 1.0 km and 0.6 km, respectively, with the largest difference ( 1.0 km) occurring from December to March and the smallest difference in September. The humidity inversion occurrence decreases with increasing humidity inversion intensity (stronger in summer than in winter). During the winter months, AMC occurrences increase from 15% to 35% when the inversion intensity increases from 0.1 to 0.9 g/kg. On the contrary, despite a higher frequency of strong humidity inversion in summer, AMC occurrences are nearly invariant for different inversion intensities. On average, humidity and temperature inversion frequencies of occurrence above an AMC are 5 and 8 times, respectively, as high as those below an AMC. The strong inversion occurrences for both humidity and temperature above an AMC provide the moisture sources from above for the formation and maintenance of AMCs. This result helps to reconcile the persistency of AMCs even when the Arctic surface is covered by snow and ice.

Characterizing Arctic mixed-phase cloud structure and its relationship with humidity and temperature inversion using ARM NSA observations

DOE PAGES

Qiu, Shaoyue; Dong, Xiquan; Xi, Baike; ...

2015-07-20

In this work, the characteristics of the Arctic mixed-phase cloud (AMC) have been investigated using data collected at the Atmospheric Radiation Measurement North Slope Alaska site from October 2006 to September 2009. AMC has an annual occurrence frequency of 42.3%, which includes 18.7% of single-layered AMCs and 23.6% for multiple layers. Two cloud base heights (CBHs) are defined from ceilometer and micropulse lidar (MPL) measurements. For single-layered AMC, the ceilometer-derived CBH represents the base of the liquid-dominant layer near the cloud top, while MPL-derived CBH represents base of the lower ice-dominant layer. The annual mean CBHs from ceilometer and MPLmore » measurements are 1.0 km and 0.6 km, respectively, with the largest difference (~1.0 km) occurring from December to March and the smallest difference in September. The humidity inversion occurrence decreases with increasing humidity inversion intensity (stronger in summer than in winter). During the winter months, AMC occurrences increase from 15% to 35% when the inversion intensity increases from 0.1 to 0.9 g/kg. On the contrary, despite a higher frequency of strong humidity inversion in summer, AMC occurrences are nearly invariant for different inversion intensities. On average, humidity and temperature inversion frequencies of occurrence above an AMC are 5 and 8 times, respectively, as high as those below an AMC. The strong inversion occurrences for both humidity and temperature above an AMC provide the moisture sources from above for the formation and maintenance of AMCs. In conclusion, this result helps to reconcile the persistency of AMCs even when the Arctic surface is covered by snow and ice.« less

An Investigation of Topography Modulated Low Level Moisture Convergence Patterns in the Southern Appalachians Using WRF

NASA Astrophysics Data System (ADS)

Wilson, A. M.; Duan, Y.; Barros, A.

2015-12-01

The Southern Appalachian Mountains (SAM) region is a biodiversity hot-spot that is vulnerable to land use/land cover changes due to its proximity to the rapidly growing population in the Southeast U.S. Persistent near surface moisture and associated microclimates observed in this region have been documented since the colonization of the area. The landform in this area, in particular in the inner mountain region, is highly complex with nested valleys and ridges. The geometry of the terrain causes distinct diurnal and seasonal local flow patterns that result in highly complex interactions of this low level moisture with meso- and synoptic-scale cyclones passing through the region. The Weather Research and Forecasting model (WRF) was used to conduct high resolution simulations of several case studies of warm season precipitation in the SAM with different synoptic-scale conditions to investigate this interaction between local and larger-scale flow patterns. The aim is to elucidate the microphysical interactions among these shallow orographic clouds and preexisting precipitating cloud systems and identify uncertainties in the model microphysics using in situ measurements. Findings show that ridge-valley precipitation gradients, in particular the "reverse" to the classical orographic effect observed in inner mountain valleys, is linked to horizontal heterogeneity in the vertical structure of low level cloud and precipitation promoted through landform controls on local flow. Moisture convergence patterns follow the peaks and valleys as represented by WRF terrain, and the topography effectively controls their timing and spatial structure. The simulations support the hypothesis that ridge-valley precipitation gradients, and in particular the reverse orographic enhancement effect in inner mountain valleys, is linked to horizontal heterogeneity in the vertical structure of low level clouds and precipitation promoted through landform controls on moisture convergence.

Evaluating the spatio-temporal performance of sky imager based solar irradiance analysis and forecasts

NASA Astrophysics Data System (ADS)

Schmidt, T.; Kalisch, J.; Lorenz, E.; Heinemann, D.

2015-10-01

Clouds are the dominant source of variability in surface solar radiation and uncertainty in its prediction. However, the increasing share of solar energy in the world-wide electric power supply increases the need for accurate solar radiation forecasts. In this work, we present results of a shortest-term global horizontal irradiance (GHI) forecast experiment based on hemispheric sky images. A two month dataset with images from one sky imager and high resolutive GHI measurements from 99 pyranometers distributed over 10 km by 12 km is used for validation. We developed a multi-step model and processed GHI forecasts up to 25 min with an update interval of 15 s. A cloud type classification is used to separate the time series in different cloud scenarios. Overall, the sky imager based forecasts do not outperform the reference persistence forecasts. Nevertheless, we find that analysis and forecast performance depend strongly on the predominant cloud conditions. Especially convective type clouds lead to high temporal and spatial GHI variability. For cumulus cloud conditions, the analysis error is found to be lower than that introduced by a single pyranometer if it is used representatively for the whole area in distances from the camera larger than 1-2 km. Moreover, forecast skill is much higher for these conditions compared to overcast or clear sky situations causing low GHI variability which is easier to predict by persistence. In order to generalize the cloud-induced forecast error, we identify a variability threshold indicating conditions with positive forecast skill.

Aster Global dem Version 3, and New Aster Water Body Dataset

NASA Astrophysics Data System (ADS)

Abrams, M.

2016-06-01

In 2016, the US/Japan ASTER (Advanced Spaceborne Thermal Emission and Reflection Radiometer) project released Version 3 of the Global DEM (GDEM). This 30 m DEM covers the earth's surface from 82N to 82S, and improves on two earlier versions by correcting some artefacts and filling in areas of missing DEMs by the acquisition of additional data. The GDEM was produced by stereocorrelation of 2 million ASTER scenes and operation on a pixel-by-pixel basis: cloud screening; stacking data from overlapping scenes; removing outlier values, and averaging elevation values. As previously, the GDEM is packaged in ~ 23,000 1 x 1 degree tiles. Each tile has a DEM file, and a NUM file reporting the number of scenes used for each pixel, and identifying the source for fill-in data (where persistent clouds prevented computation of an elevation value). An additional data set was concurrently produced and released: the ASTER Water Body Dataset (AWBD). This is a 30 m raster product, which encodes every pixel as either lake, river, or ocean; thus providing a global inland and shore-line water body mask. Water was identified through spectral analysis algorithms and manual editing. This product was evaluated against the Shuttle Water Body Dataset (SWBD), and the Landsat-based Global Inland Water (GIW) product. The SWBD only covers the earth between about 60 degrees north and south, so it is not a global product. The GIW only delineates inland water bodies, and does not deal with ocean coastlines. All products are at 30 m postings.

Snow driven Radiative Forcing in High Latitude Areas of Disturbance Using Higher Resolution Albedo Products from Landsat and Sentinel-2

NASA Astrophysics Data System (ADS)

Erb, A.; Li, Z.; Schaaf, C.; Wang, Z.; Rogers, B. M.

2017-12-01

Land surface albedo plays an important role in the surface energy budget and radiative forcing by determining the proportion of absorbed incoming solar radiation available to drive photosynthesis and surface heating. In Arctic regions, albedo is particularly sensitive to land cover and land use change (LCLUC) and modeling efforts have shown it to be the primary driver of effective radiative forcing from the biogeophysical effects of LCLUC. In boreal forests, the effects of these changes are complicated during snow covered periods when newly exposed, highly reflective snow can serve as the primary driver of radiative forcing. In Arctic biomes disturbance scars from fire, pest and harvest can remain in the landscape for long periods of time. As such, understanding the magnitude and persistence of these disturbances, especially in the shoulder seasons, is critical. The Landsat and Sentinel-2 Albedo Products couple 30m and 20m surface reflectances with concurrent 500m BRDF Products from the MODerate resolution Imaging Spectroradiometer (MODIS). The 12 bit radiometric fidelity of Sentinel-2 and Landsat-8 allow for the inclusion of high-quality, unsaturated albedo calculations over snow covered surfaces at scales more compatible with fragmented landscapes. Recent work on the early spring albedo of fire scars has illustrated significant post-fire spatial heterogeneity of burn severity at the landscape scale and highlights the need for a finer spatial resolution albedo record. The increased temporal resolution provided by multiple satellite instruments also allows for a better understanding of albedo dynamics during the dynamic shoulder seasons and in historically difficult high latitude locations where persistent cloud cover limits high quality retrievals. Here we present how changes in the early spring albedo of recent boreal forest disturbance in Alaska and central Canada affects landscape-scale radiative forcing. We take advantage of the long historical Landsat record to examine pre-disturbance albedo trends and to link historical land cover and disturbance history to post-disturbance early spring albedo values. We examine the impact of landscape heterogeneity on albedo in the growing and dormant seasons and quantify the effects of snow exposure changes from over-story canopy loss.

Apollo 7 Mission,Clouds

NASA Image and Video Library

1968-10-11

Apollo 7,Cumulus,alto-cumulus,cirrus clouds. Very high oblique. Cloud Cover 50%. Original film magazine was labeled S. Camera Data: Hasselblad 500-C; Lens: Zeiss Planar,F/2.8,80mm; Film Type: Kodak SO-121,Aerial Ektachrome; Filter: Wratten 2A. Flight Date: October 11-12. 1968.

An analysis of the relationship between cloud anomalies and sea surface temperature anomalies in a global circulation model

NASA Technical Reports Server (NTRS)

Peterson, Thomas C.; Barnett, Tim P.; Roeckner, Erich; Vonder Haar, Thomas H.

1992-01-01

The relationship between the sea surface temperature anomalies (SSTAs) and the anomalies of the monthly mean cloud cover (including the high-level, low-level, and total cloud cover), the outgoing longwave radiation, and the reflected solar radiation was analyzed using a least absolute deviations regression at each grid point over the open ocean for a 6-yr period. The results indicate that cloud change in association with a local 1-C increase in SSTAs cannot be used to predict clouds in a potential future world where all the oceans are 1-C warmer than at present, because much of the observed cloud changes are due to circulation changes, which in turn are related not only to changes in SSTAs but to changes in SSTA gradients. However, because SSTAs are associated with changes in the local ocean-atmosphere moisture and heat fluxes as well as significant changes in circulation (such as ENSO), SSTAs can serve as a surrogate for many aspects of global climate change.

Lidar Observations of the Optical Properties and 3-Dimensional Structure of Cirrus Clouds

NASA Technical Reports Server (NTRS)

Eloranta, E. W.

1996-01-01

The scientific research conducted under this grant have been reported in a series of journal articles, dissertations, and conference proceedings. This report consists of a compilation of these publications in the following areas: development and operation of a High Spectral Resolution Lidar, cloud physics and cloud formation, mesoscale observations of cloud phenomena, ground-based and satellite cloud cover observations, impact of volcanic aerosols on cloud formation, visible and infrared radiative relationships as measured by satellites and lidar, and scattering cross sections.

On-Board Cryospheric Change Detection By The Autonomous Sciencecraft Experiment

NASA Astrophysics Data System (ADS)

Doggett, T.; Greeley, R.; Castano, R.; Cichy, B.; Chien, S.; Davies, A.; Baker, V.; Dohm, J.; Ip, F.

2004-12-01

The Autonomous Sciencecraft Experiment (ASE) is operating on-board Earth Observing - 1 (EO-1) with the Hyperion hyper-spectral visible/near-IR spectrometer. ASE science activities include autonomous monitoring of cryopsheric changes, triggering the collection of additional data when change is detected and filtering of null data such as no change or cloud cover. This would have application to the study of cryospheres on Earth, Mars and the icy moons of the outer solar system. A cryosphere classification algorithm, in combination with a previously developed cloud algorithm [1] has been tested on-board ten times from March through August 2004. The cloud algorithm correctly screened out three scenes with total cloud cover, while the cryosphere algorithm detected alpine snow cover in the Rocky Mountains, lake thaw near Madison, Wisconsin, and the presence and subsequent break-up of sea ice in the Barrow Strait of the Canadian Arctic. Hyperion has 220 bands ranging from 400 to 2400 nm, with a spatial resolution of 30 m/pixel and a spectral resolution of 10 nm. Limited on-board memory and processing speed imposed the constraint that only partially processed Level 0.5 data with dark image subtraction and gain factors applied, but not full radiometric calibration. In addition, a maximum of 12 bands could be used for any stacked sequence of algorithms run for a scene on-board. The cryosphere algorithm was developed to classify snow, water, ice and land, using six Hyperion bands at 427, 559, 661, 864, 1245 and 1649 nm. Of these, only 427 nm does overlap with the cloud algorithm. The cloud algorithm was developed with Level 1 data, which introduces complications because of the incomplete calibration of SWIR in Level 0.5 data, including a high level of noise in the 1377 nm band used by the cloud algorithm. Development of a more robust cryosphere classifier, including cloud classification specifically adapted to Level 0.5, is in progress for deployment on EO-1 as part of continued ASE operations. [1] Griffin, M.K. et al., Cloud Cover Detection Algorithm For EO-1 Hyperion Imagery, SPIE 17, 2003.

Relationships between lower tropospheric stability, low cloud cover, and water vapor isotopic composition in the subtropical Pacific

NASA Astrophysics Data System (ADS)

Galewsky, J.

2017-12-01

Understanding the processes that govern the relationships between lower tropospheric stability and low-cloud cover is crucial for improved constraints on low-cloud feedbacks and for improving the parameterizations of low-cloud cover used in climate models. The stable isotopic composition of atmospheric water vapor is a sensitive recorder of the balance of moistening and drying processes that set the humidity of the lower troposphere and may thus provide a useful framework for improving our understanding low-cloud processes. In-situ measurements of water vapor isotopic composition collected at the NOAA Mauna Loa Observatory in Hawaii, along with twice-daily soundings from Hilo and remote sensing of cloud cover, show a clear inverse relationship between the estimated inversion strength (EIS) and the mixing ratios and water vapor δ -values, and a positive relationship between EIS, deuterium excess, and Δ δ D, defined as the difference between an observation and a reference Rayleigh distillation curve. These relationships are consistent with reduced moistening and an enhanced upper-tropospheric contribution above the trade inversion under high EIS conditions and stronger moistening under weaker EIS conditions. The cloud fraction, cloud liquid water path, and cloud-top pressure were all found to be higher under low EIS conditions. Inverse modeling of the isotopic data for the highest and lowest terciles of EIS conditions provide quantitative constraints on the cold-point temperatures and mixing fractions that govern the humidity above the trade inversion. The modeling shows the moistening fraction between moist boundary layer air and dry middle tropospheric air 24±1.5% under low EIS conditions is and 6±1.5% under high EIS conditions. A cold-point (last-saturation) temperature of -30C can match the observations for both low and high EIS conditions. The isotopic composition of the moistening source as derived from the inversion (-114±10‰ ) requires moderate fractionation from a pure marine source, indicating a link between inversion strength and moistening of the lower troposphere from the outflow of shallow convection. This approach can be applied in other settings and the results can be used to test parameterizations in climate models.

E4 True and False Color Hot Spot Mosaic

NASA Image and Video Library

1998-03-06

True and false color views of Jupiter from NASA's Galileo spacecraft show an equatorial "hotspot" on Jupiter. These images cover an area 34,000 kilometers by 11,000 kilometers (about 21,100 by 6,800 miles). The top mosaic combines the violet and near infrared continuum filter images to create an image similar to how Jupiter would appear to human eyes. Differences in coloration are due to the composition and abundances of trace chemicals in Jupiter's atmosphere. The bottom mosaic uses Galileo's three near-infrared wavelengths displayed in red, green, and blue) to show variations in cloud height and thickness. Bluish clouds are high and thin, reddish clouds are low, and white clouds are high and thick. The dark blue hotspot in the center is a hole in the deep cloud with an overlying thin haze. The light blue region to the left is covered by a very high haze layer. The multicolored region to the right has overlapping cloud layers of different heights. Galileo is the first spacecraft to distinguish cloud layers on Jupiter. North is at the top. The mosaic covers latitudes 1 to 10 degrees and is centered at longitude 336 degrees west. The smallest resolved features are tens of kilometers in size. These images were taken on December 17, 1996, at a range of 1.5 million kilometers (about 930,000 miles) by the Solid State Imaging camera system aboard Galileo. http://photojournal.jpl.nasa.gov/catalog/PIA00602

Atlantic Multidecadal Oscillation footprint on global high cloud cover

NASA Astrophysics Data System (ADS)

Vaideanu, Petru; Dima, Mihai; Voiculescu, Mirela

2017-12-01

Due to the complexity of the physical processes responsible for cloud formation and to the relatively short satellite database of continuous data records, cloud behavior in a warming climate remains uncertain. Identifying physical links between climate modes and clouds would contribute not only to a better understanding of the physical processes governing their formation and dynamics, but also to an improved representation of the clouds in climate models. Here, we identify the global footprint of the Atlantic Multidecadal Oscillation (AMO) on high cloud cover, with focus on the tropical and North Atlantic, tropical Pacific and on the circum-Antarctic sector. In the tropical band, the sea surface temperature (SST) and high cloud cover (HCC) anomalies are positively correlated, indicating a dominant role played by convection in mediating the influence of the AMO-related SST anomalies on the HCC field. The negative SST-HCC correlation observed in North Atlantic could be explained by the reduced meridional temperature gradient induced by the AMO positive phase, which would be reflected in less storms and negative HCC anomalies. A similar negative SST-HCC correlation is observed around Antarctica. The corresponding negative correlation around Antarctica could be generated dynamically, as a response to the intensified upward motion in the Ferrel cell. Despite the inherent imperfection of the observed and reanalysis data sets, the AMO footprint on HCC is found to be robust to the choice of dataset, statistical method, and specific time period considered.

Geologic interpretation of space shuttle radar images of Indonesia

DOE Office of Scientific and Technical Information (OSTI.GOV)

Sabing, F.F.

1983-11-01

The National Aeronautics and Space Administration (NASA) space shuttle mission in November 1981 acquired images of parts of the earth with a synthetic aperture radar system at a wavelength of 23.5 cm (9.3 in.) and spatial resolution of 38 m (125 ft). This report describes the geologic interpretation of 1:250,000-scale images of Irian Jaya and eastern Kalimantan, Indonesia, where the all-weather capability of radar penetrates the persistent cloud cover. The inclined look direction of radar enhances subtle topographic features that may be the expression of geologic structures. On the Indonesian images, the following terrain categories are recognizable for geologic mapping:more » carbonate, clastic, volcanic, alluvial and coastal, melange, and metamorphic, as well as undifferentiated bedrock. Regional and local geologic structures are well expressed on the images.« less

Clouds and Climate Change. Understanding Global Change: Earth Science and Human Impacts. Global Change Instruction Program.

ERIC Educational Resources Information Center

Shaw, Glenn E.

The Global Change Instruction Program was designed by college professors to fill a need for interdisciplinary materials on the emerging science of global change. This instructional module introduces the basic features and classifications of clouds and cloud cover, and explains how clouds form, what they are made of, what roles they play in…

Cloud cover determination in polar regions from satellite imagery

NASA Technical Reports Server (NTRS)

Barry, R. G.; Maslanik, J. A.; Key, J. R.

1987-01-01

A definition is undertaken of the spectral and spatial characteristics of clouds and surface conditions in the polar regions, and to the creation of calibrated, geometrically correct data sets suitable for quantitative analysis. Ways are explored in which this information can be applied to cloud classifications as new methods or as extensions to existing classification schemes. A methodology is developed that uses automated techniques to merge Advanced Very High Resolution Radiometer (AVHRR) and Scanning Multichannel Microwave Radiometer (SMMR) data, and to apply first-order calibration and zenith angle corrections to the AVHRR imagery. Cloud cover and surface types are manually interpreted, and manual methods are used to define relatively pure training areas to describe the textural and multispectral characteristics of clouds over several surface conditions. The effects of viewing angle and bidirectional reflectance differences are studied for several classes, and the effectiveness of some key components of existing classification schemes is tested.

Upper tropospheric cloud systems determined from IR Sounders and their influence on the atmosphere

NASA Astrophysics Data System (ADS)

Stubenrauch, Claudia; Protopapadaki, Sofia; Feofilov, Artem; Velasco, Carola Barrientos

2017-02-01

Covering about 30% of the Earth, upper tropospheric clouds play a key role in the climate system by modulating the Earth's energy budget and heat transport. Infrared Sounders reliably identify cirrus down to an IR optical depth of 0.1. Recently LMD has built global cloud climate data records from AIRS and IASI observations, covering the periods from 2003-2015 and 2008-2015, respectively. Upper tropospheric clouds often form mesoscale systems. Their organization and properties are being studied by (1) distinguishing cloud regimes within 2° × 2° regions and (2) applying a spatial composite technique on adjacent cloud pressures, which estimates the horizontal extent of the mesoscale cloud systems. Convective core, cirrus anvil and thin cirrus of these systems are then distinguished by their emissivity. Compared to other studies of tropical mesoscale convective systems our data include also the thinner anvil parts, which make out about 30% of the area of tropical mesoscale convective systems. Once the horizontal and vertical structure of these upper tropospheric cloud systems is known, we can estimate their radiative effects in terms of top of atmosphere and surface radiative fluxes and by computing their heating rates.

Mapping land cover change over continental Africa using Landsat and Google Earth Engine cloud computing.

PubMed

Midekisa, Alemayehu; Holl, Felix; Savory, David J; Andrade-Pacheco, Ricardo; Gething, Peter W; Bennett, Adam; Sturrock, Hugh J W

2017-01-01

Quantifying and monitoring the spatial and temporal dynamics of the global land cover is critical for better understanding many of the Earth's land surface processes. However, the lack of regularly updated, continental-scale, and high spatial resolution (30 m) land cover data limit our ability to better understand the spatial extent and the temporal dynamics of land surface changes. Despite the free availability of high spatial resolution Landsat satellite data, continental-scale land cover mapping using high resolution Landsat satellite data was not feasible until now due to the need for high-performance computing to store, process, and analyze this large volume of high resolution satellite data. In this study, we present an approach to quantify continental land cover and impervious surface changes over a long period of time (15 years) using high resolution Landsat satellite observations and Google Earth Engine cloud computing platform. The approach applied here to overcome the computational challenges of handling big earth observation data by using cloud computing can help scientists and practitioners who lack high-performance computational resources.

Mapping land cover change over continental Africa using Landsat and Google Earth Engine cloud computing

PubMed Central

Holl, Felix; Savory, David J.; Andrade-Pacheco, Ricardo; Gething, Peter W.; Bennett, Adam; Sturrock, Hugh J. W.

2017-01-01

Quantifying and monitoring the spatial and temporal dynamics of the global land cover is critical for better understanding many of the Earth’s land surface processes. However, the lack of regularly updated, continental-scale, and high spatial resolution (30 m) land cover data limit our ability to better understand the spatial extent and the temporal dynamics of land surface changes. Despite the free availability of high spatial resolution Landsat satellite data, continental-scale land cover mapping using high resolution Landsat satellite data was not feasible until now due to the need for high-performance computing to store, process, and analyze this large volume of high resolution satellite data. In this study, we present an approach to quantify continental land cover and impervious surface changes over a long period of time (15 years) using high resolution Landsat satellite observations and Google Earth Engine cloud computing platform. The approach applied here to overcome the computational challenges of handling big earth observation data by using cloud computing can help scientists and practitioners who lack high-performance computational resources. PMID:28953943

Statistical analysis of multivariate atmospheric variables. [cloud cover

NASA Technical Reports Server (NTRS)

Tubbs, J. D.

1979-01-01

Topics covered include: (1) estimation in discrete multivariate distributions; (2) a procedure to predict cloud cover frequencies in the bivariate case; (3) a program to compute conditional bivariate normal parameters; (4) the transformation of nonnormal multivariate to near-normal; (5) test of fit for the extreme value distribution based upon the generalized minimum chi-square; (6) test of fit for continuous distributions based upon the generalized minimum chi-square; (7) effect of correlated observations on confidence sets based upon chi-square statistics; and (8) generation of random variates from specified distributions.

Discharge forecasts in mountain basins based on satellite snow cover mapping. [Dinwoody Creek Basin, Wyoming and the Dischma Basin, Switzerland

NASA Technical Reports Server (NTRS)

Martinec, J.; Rango, A. (Principal Investigator)

1980-01-01

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.

Local effects of partly cloudy skies on solar and emitted radiations

NASA Technical Reports Server (NTRS)

Whitney, D. A.; Venable, D. D.

1981-01-01

Solar radiation measurements are made on a routine basis. Global solar, atmospheric emitted, downwelled diffuse solar, and direct solar radiation measurement systems are fully operational with the first two in continuous operation. Fractional cloud cover measurements are made from GOES imagery or from ground based whole sky photographs. Normalized global solar irradiance values for partly cloudy skies were correlated to fractional cloud cover.

Cassini ISS and VIMS observations of Titan's north polar region during the T120 and T121 flybys: The Curious Case of the Clouds

NASA Astrophysics Data System (ADS)

Turtle, E. P.; Barnes, J. W.; Perry, J.; Barbara, J.; Hayes, A.; Corlies, P.; Kelland, J.; West, R. A.; Del Genio, A. D.; Soderblom, J. M.; McEwen, A. S.; Sotin, C.

2016-12-01

As northern summer approaches, atmospheric circulation models predict storm activity will pick up at Titan's high northern latitudes, as was observed at high southern latitudes upon Cassini's arrival during late southern summer in 2004. Cassini's Imaging Science Subsystem (ISS) and Visual and Infrared Mapping Spectrometer (VIMS) teams have been targeting Titan to document changes in weather patterns over the course of the mission, and there is particular interest in following the onset of clouds in the north polar region where Titan's lakes and seas are concentrated. The T120 and T121 flybys of Titan, on 7 June and 25 July 2016, respectively, provided views of high northern latitudes, and each instrument performed a series of observations over more than 24 hours during both flybys. Intriguingly, at first look the ISS and VIMS observations appear strikingly different from each other: in the ISS observations made during each flyby, surface features are apparent and only a few isolated clouds are detected; however, the VIMS observations suggest widespread cloud cover at high northern latitudes during both flybys. Although the instruments achieve different resolutions, that alone cannot explain the differences. The observations were made over the same time periods, so differences in illumination geometry or changes in the clouds themselves are also unlikely to be the cause for the apparent discrepancy; VIMS shows persistent atmospheric features over the entire observation period and ISS consistently detects surface features with just a few localized clouds. Clouds with low optical depth (lower than the optical depth of Titan's atmospheric haze at the same wavelength) might be more easily apparent at the longer wavelengths of the VIMS observations, which extend out to 5 µm (haze optical depth 0.2), compared to the ISS observations at 938 nm (haze optical depth 2). However, the lack of any apparent change in the visibility of lakes and seas in the ISS images compared to previous flybys where no clouds were observed is still difficult to explain. We will present our analyses of the sequences of observations made by ISS and VIMS during T120 and T121, as well as an ongoing ground-based observing campaign (including data from 8 June and 23 July), and the implications for the behavior of Titan's atmosphere leading up to northern summer.

Two Methods for Retrieving UV Index for All Cloud Conditions from Sky Imager Products or Total SW Radiation Measurements

DOE Office of Scientific and Technical Information (OSTI.GOV)

Badosa, Jordi; Calbo, J.; McKenzie, R. L.

2014-07-01

In the present study, we assess the cloud effects on UV Index (UVI) and total solar radiation (TR) as a function of cloud cover estimations and sunny conditions (from sky imaging products) as well as of solar zenith angle (SZA). These analyses are undertaken for a southern-hemisphere mid-latitude site where a 10-years dataset is available. It is confirmed that clouds reduce TR more than UV, in particular for obscured Sun conditions, low cloud fraction (< 60%) and large SZA (> 60º). Similarly, clouds enhance TR more than UV, mainly for visible Sun conditions, large cloud fraction and large SZA. Twomore » methods to estimate UVI are developed: 1) from sky imaging cloud cover and sunny conditions, and 2) from TR measurements. Both methods may be used in practical operational applications, although Method 2 shows overall the best performance, since TR allows accounting for cloud optical properties. The mean absolute differences of Method 2 estimations with respect to measured values are 0.17 UVI units (for 1-minute data) and 0.79 Standard Erythemal Dose (SED) units (for daily integrations). Method 1 shows less accurate results but it is still suitable to estimate UVI: mean absolute differences are 0.37 UVI units and 1.6 SED.« less

Strategies for cloud-top phase determination: differentiation between thin cirrus clouds and snow in manual (ground truth) analyses

NASA Astrophysics Data System (ADS)

Hutchison, Keith D.; Etherton, Brian J.; Topping, Phillip C.

1996-12-01

Quantitative assessments on the performance of automated cloud analysis algorithms require the creation of highly accurate, manual cloud, no cloud (CNC) images from multispectral meteorological satellite data. In general, the methodology to create ground truth analyses for the evaluation of cloud detection algorithms is relatively straightforward. However, when focus shifts toward quantifying the performance of automated cloud classification algorithms, the task of creating ground truth images becomes much more complicated since these CNC analyses must differentiate between water and ice cloud tops while ensuring that inaccuracies in automated cloud detection are not propagated into the results of the cloud classification algorithm. The process of creating these ground truth CNC analyses may become particularly difficult when little or no spectral signature is evident between a cloud and its background, as appears to be the case when thin cirrus is present over snow-covered surfaces. In this paper, procedures are described that enhance the researcher's ability to manually interpret and differentiate between thin cirrus clouds and snow-covered surfaces in daytime AVHRR imagery. The methodology uses data in up to six AVHRR spectral bands, including an additional band derived from the daytime 3.7 micron channel, which has proven invaluable for the manual discrimination between thin cirrus clouds and snow. It is concluded that while the 1.6 micron channel remains essential to differentiate between thin ice clouds and snow. However, this capability that may be lost if the 3.7 micron data switches to a nighttime-only transmission with the launch of future NOAA satellites.

West Antarctic Ice Sheet cloud cover and surface radiation budget from NASA A-Train satellites

DOE Office of Scientific and Technical Information (OSTI.GOV)

Scott, Ryan C.; Lubin, Dan; Vogelmann, Andrew M.

Clouds are an essential parameter of the surface energy budget influencing the West Antarctic Ice Sheet (WAIS) response to atmospheric warming and net contribution to global sea-level rise. A four-year record of NASA A-Train cloud observations is combined with surface radiation measurements to quantify the WAIS radiation budget and constrain the three-dimensional occurrence frequency, thermodynamic phase partitioning, and surface radiative effect of clouds over West Antarctica (WA). The skill of satellite-modeled radiative fluxes is confirmed through evaluation against measurements at four Antarctic sites (WAIS Divide Ice Camp, Neumayer, Syowa, and Concordia Stations). And due to perennial high-albedo snow and icemore » cover, cloud infrared emission dominates over cloud solar reflection/absorption leading to a positive net all-wave cloud radiative effect (CRE) at the surface, with all monthly means and 99.15% of instantaneous CRE values exceeding zero. The annual-mean CRE at theWAIS surface is 34 W m -2, representing a significant cloud-induced warming of the ice sheet. Low-level liquid-containing clouds, including thin liquid water clouds implicated in radiative contributions to surface melting, are widespread and most frequent in WA during the austral summer. Clouds warm the WAIS by 26 W m -2, in summer, on average, despite maximum offsetting shortwave CRE. Glaciated cloud systems are strongly linked to orographic forcing, with maximum incidence on the WAIS continuing downstream along the Transantarctic Mountains.« less

West Antarctic Ice Sheet cloud cover and surface radiation budget from NASA A-Train satellites

DOE PAGES

Scott, Ryan C.; Lubin, Dan; Vogelmann, Andrew M.; ...

2017-04-26

Clouds are an essential parameter of the surface energy budget influencing the West Antarctic Ice Sheet (WAIS) response to atmospheric warming and net contribution to global sea-level rise. A four-year record of NASA A-Train cloud observations is combined with surface radiation measurements to quantify the WAIS radiation budget and constrain the three-dimensional occurrence frequency, thermodynamic phase partitioning, and surface radiative effect of clouds over West Antarctica (WA). The skill of satellite-modeled radiative fluxes is confirmed through evaluation against measurements at four Antarctic sites (WAIS Divide Ice Camp, Neumayer, Syowa, and Concordia Stations). And due to perennial high-albedo snow and icemore » cover, cloud infrared emission dominates over cloud solar reflection/absorption leading to a positive net all-wave cloud radiative effect (CRE) at the surface, with all monthly means and 99.15% of instantaneous CRE values exceeding zero. The annual-mean CRE at theWAIS surface is 34 W m -2, representing a significant cloud-induced warming of the ice sheet. Low-level liquid-containing clouds, including thin liquid water clouds implicated in radiative contributions to surface melting, are widespread and most frequent in WA during the austral summer. Clouds warm the WAIS by 26 W m -2, in summer, on average, despite maximum offsetting shortwave CRE. Glaciated cloud systems are strongly linked to orographic forcing, with maximum incidence on the WAIS continuing downstream along the Transantarctic Mountains.« less

Tropical High Cloud Fraction Controlled by Cloud Lifetime Rather Than Clear-sky Convergence

NASA Astrophysics Data System (ADS)

Seeley, J.; Jeevanjee, N.; Romps, D. M.

2016-12-01

Observations and simulations show a peak in cloud fraction below the tropopause. This peak is usually attributed to a roughly co-located peak in radiatively-driven clear-sky convergence, which is presumed to force convective detrainment and thus promote large cloud fraction. Using simulations of radiative-convective equilibrium forced by various radiative cooling profiles, we refute this mechanism by showing that an upper-tropospheric peak in cloud fraction persists even in simulations with no peak in clear-sky convergence. Instead, cloud fraction profiles seem to be controlled by cloud lifetimes — i.e., how long it takes for clouds to dissipate after they have detrained. A simple model of cloud evaporation shows that the small saturation deficit in the upper troposphere greatly extends cloud lifetimes there, while the large saturation deficit in the lower troposphere causes condensate to evaporate quickly. Since cloud mass flux must go to zero at the tropopause, a peak in cloud fraction emerges at a "sweet spot" below the tropopause where cloud lifetimes are long and there is still sufficient mass flux to be detrained.

Surface-Based Observations of Contrail Occurrence Over the US, Apr. 1993 to Apr. 1994

NASA Technical Reports Server (NTRS)

Minnis, Patrick; Ayers, J. Kirk; Weaver, Steven P.

1997-01-01

Surface observers stationed at 19 U.S. Air Force Bases and Army Air Stations recorded the daytime occurrence of contrails and cloud fraction on an hourly basis for the period April 1993 through April 1994. Each observation uses one of four main categories to report contrails as unobserved, non-persistent, persistent, and indeterminate. Additional classification includes the co-occurrence of cirrus with each report. The data cover much of the continental U.S. including locations near major commercial air routes. The mean annual frequency of occurrence in unobstructed viewing conditions is 13 percent for these sites. Contrail occurrence varied substantially with location and season. Most contrails occurred during the winter months and least during the summer with a pronounced minimum during July. Although nocturnal observations are not available, it appears that the contrails have a diurnal variation that peaks during mid morning over most areas. Contrails were most often observed in areas near major commercial air corridors and least often over areas far removed from the heaviest air traffic. A significant correlation exists between mean contrail frequency and aircraft fuel usage above 7 km suggesting predictive potential for assessing future contrail effects on climate.

Transit detection of a `starshade' at the inner lagrange point of an exoplanet

NASA Astrophysics Data System (ADS)

Gaidos, E.

2017-08-01

All water-covered rocky planets in the inner habitable zones of solar-type stars will inevitably experience a catastrophic runaway climate due to increasing stellar luminosity and limits to outgoing infrared radiation from wet greenhouse atmospheres. Reflectors or scatterers placed near Earth's inner Lagrange point (L_1) have been proposed as a "geoengineering' solution to anthropogenic climate change and an advanced version of this could modulate incident irradiation over many Gyr or `rescue' a planet from the interior of the habitable zone. The distance of the starshade from the planet that minimizes its mass is 1.6 times the Earth-L_1 distance. Such a starshade would have to be similar in size to the planet and the mutual occultations during planetary transits could produce a characteristic maximum at mid-transit in the light curve. Because of a fortuitous ratio of densities, Earth-size planets around G dwarf stars present the best opportunity to detect such an artefact. The signal would be persistent and is potentially detectable by a future space photometry mission to characterize transiting planets. The signal could be distinguished from natural phenomenon, I.e. starspots or cometary dust clouds, by its shape, persistence and transmission spectrum.

Evapotranspiration over spatially extensive plant communities in the Big Cypress National Preserve, southern Florida, 2007-2010

USGS Publications Warehouse

Shoemaker, W. Barclay; Lopez, Christian D.; Duever, Michael J.

2011-01-01

Net radiation and available energy explained most of the variability in ET observed at all five sites. Mean annual and monthly net radiation varied among the sites in response to cloud cover and the albedo of the land surface and plant community. Net radiation was greatest at the Cypress Swamp site, averaging about 130 W/m2 (watts per square meter) during the 3-year study. Net radiation was generally less at the Dwarf Cypress site, averaging about 115 W/m2 over 3 years. The Dwarf Cypress site apparently has the largest albedo, which likely is due to the sparse canopy and a highly reflective, calcareous, periphyton-covered land surface. Furthermore, mean annual net radiation was least in the first year of the study, which likely was due to greater cloud cover during a relatively wet year. In contrast, net radiation was greatest in the second year of the study, which likely was due to less cloud cover during a relatively dry year.

Intensification of North American Megadroughts through Surface and Dust Aerosol Forcing

NASA Technical Reports Server (NTRS)

Cook, Benjamin I.; Seager, Richard; Miller, Ron L.; Mason, Joseph A

2013-01-01

Tree-ring-based reconstructions of the Palmer drought severity index (PDSI) indicate that, during the Medieval Climate Anomaly (MCA), the central plains of North America experienced recurrent periods of drought spanning decades or longer. These megadroughts had exceptional persistence compared to more recent events, but the causes remain uncertain. The authors conducted a suite of general circulation model experiments to test the impact of sea surface temperature (SST) and land surface forcing on the MCA megadroughts over the central plains. The land surface forcing is represented as a set of dune mobilization boundary conditions, derived from available geomorphological evidence and modeled as increased bare soil area and a dust aerosol source (32deg-44degN, 105deg-95degW). In the experiments, cold tropical Pacific SST forcing suppresses precipitation over the central plains but cannot reproduce the overall drying or persistence seen in the PDSI reconstruction. Droughts in the scenario with dust aerosols, however, are amplified and have significantly longer persistence than in other model experiments, more closely matching the reconstructed PDSI. This additional drying occurs because the dust increases the shortwave planetary albedo, reducing energy inputs to the surface and boundary layer. The energy deficit increases atmospheric stability, inhibiting convection and reducing cloud cover and precipitation over the central plains. Results from this study provide the first model-based evidence that dust aerosol forcing and land surface changes could have contributed to the intensity and persistence of the central plains megadroughts, although uncertainties remain in the formulation of the boundary conditions and the future importance of these feedbacks.

Atmospheric Soundings from AIRS/AMSU/HSB

NASA Technical Reports Server (NTRS)

Susskind, Joel; Atlas, Robert

2004-01-01

AIRS was launched on EOS Aqua on May 4, 2002, together with AMSU A and HSB, to form a next generation polar orbiting infrared and microwave atmospheric sounding system. The primary products of AIRS/AMSU/HSB are twice daily global fields of atmospheric temperature-humidity profiles, ozone profiles, sea/land surface skin temperature, and cloud related parameters including OLR. The sounding goals of AIRS are to produce 1 km tropospheric layer mean temperatures with an rms error of lK, and 1 km tropospheric layer precipitable water with an rms error of 20%, in cases with up to 80% effective cloud cover. Pre-launch simulation studies indicated that these results should be achievable. Minor modifications have been made to the pre-launch retrieval algorithm as alluded to in this paper. Sample fields of parameters retrieved from AIRS/AMSU/HSB data are presented and temperature profiles are validated as a function of retrieved effective fractional cloud cover. As in simulation, the degradation of retrieval accuracy with increasing cloud cover is small. Select fields are also compared to those contained in the ECMWF analysis, done without the benefit of AIRS data, to demonstrate information that AIRS can add to that already contained in the ECMWF analysis. Assimilation of AIRS temperature soundings in up to 80% cloud cover for the month of January 2003 into the GSFC FVSSI data assimilation system resulted in improved 5 day forecasts globally, both with regard to anomaly correlation coefficients and the prediction of location and intensity of cyclones.

Current results from AlRS/AMSU/HSB

NASA Technical Reports Server (NTRS)

Susskind, Joel; Atlas, Robert; Barnet, Christopher; Blaisdell, Jon; Iredell, Lena; Bri, Genia; Jusem, Juan Carlos; Keita, Fricky; Kouvaris, Louis; Molnar, Gyula

2004-01-01

AIRS was launched on EOS Aqua on May 4,2002, together with AMSU A and HSB, to form a next generation polar orbiting infrared and microwave atmospheric sounding system. The primary products of AIRS/AMSU/HSB are twice daily global fields of atmospheric temperature-humidity profiles, ozone profiles, sea/land surface skin temperature, and cloud related parameters including OLR. The sounding goals of AIRS are to produce 1 km tropospheric layer mean temperatures with an rms error of 1K, and layer precipitable water with an rms error of 20%, in cases with up to 80% effective cloud cover. Pre-launch simulation studies indicated that these results should be achievable. Minor modifications have been made to the pre-launch retrieval algorithm as alluded to in this paper. Sample fields of parameters retrieved from AIRS/AMSU/HSB data are presented and temperature profiles are validated as a function of retrieved fractional cloud cover. As in simulation, the degradation of retrieval accuracy with increasing cloud cover is small. Select fields are also compared to those contained in the ECMWF analysis, done without the benefit of AIRS data, to demonstrate information that AIRS can add to that already contained in the ECMWF analysis. Assimilation of AIRS temperature soundings in up to 80% cloud cover for the month of January 2003 into the GSFC FVSSI data assimilation system resulted in improved 5 day forecasts globally, both with regard to anomaly correction coefficients and the prediction of location and intensity of cyclones.

Cloud Cover

ERIC Educational Resources Information Center

Schaffhauser, Dian

2012-01-01

This article features a major statewide initiative in North Carolina that is showing how a consortium model can minimize risks for districts and help them exploit the advantages of cloud computing. Edgecombe County Public Schools in Tarboro, North Carolina, intends to exploit a major cloud initiative being refined in the state and involving every…

15 CFR 908.8 - Maintenance of records.

Code of Federal Regulations, 2012 CFR

2012-01-01

... activity during each operational period (e.g., cumulus clouds between 10,000 and 30,000 feet m.s.l.; ground... weather modification activity during each operational period (e.g., cumulus clouds between 10,000 and 30... operation; for example: Percent of cloud cover, temperature, humidity, the presence of lightning, hail...

15 CFR 908.8 - Maintenance of records.

Code of Federal Regulations, 2014 CFR

2014-01-01

... activity during each operational period (e.g., cumulus clouds between 10,000 and 30,000 feet m.s.l.; ground... weather modification activity during each operational period (e.g., cumulus clouds between 10,000 and 30... operation; for example: Percent of cloud cover, temperature, humidity, the presence of lightning, hail...

15 CFR 908.8 - Maintenance of records.

Code of Federal Regulations, 2013 CFR

2013-01-01

... activity during each operational period (e.g., cumulus clouds between 10,000 and 30,000 feet m.s.l.; ground... weather modification activity during each operational period (e.g., cumulus clouds between 10,000 and 30... operation; for example: Percent of cloud cover, temperature, humidity, the presence of lightning, hail...

Atmospheric Profiles, Clouds and the Evolution of Sea Ice Cover in the Beaufort and Chukchi Seas

DTIC Science & Technology

2014-09-30

developed by incorporating the proposed IR sensors and ground-sky temperature difference algorithm into a tethered balloon borne payload (Figure 3...into the cloud base. RESULTS FROM FY 2014 • A second flight of the tethered balloon -borne IR cloud margin sensor was conducted in Colorado on...Figure 3: Tethered balloon -borne IR sensing payload IR Cloud Margin Sensor Figure 4: First successful flight validation of the IR cloud

Cloud microphysics and aerosol indirect effects in the global climate model ECHAM5-HAM

NASA Astrophysics Data System (ADS)

Lohmann, U.; Stier, P.; Hoose, C.; Ferrachat, S.; Kloster, S.; Roeckner, E.; Zhang, J.

2007-07-01

The double-moment cloud microphysics scheme from ECHAM4 that predicts both the mass mixing ratios and number concentrations of cloud droplets and ice crystals has been coupled to the size-resolved aerosol scheme ECHAM5-HAM. ECHAM5-HAM predicts the aerosol mass, number concentrations and mixing state. The simulated liquid, ice and total water content and the cloud droplet and ice crystal number concentrations as a function of temperature in stratiform mixed-phase clouds between 0 and -35° C agree much better with aircraft observations in the ECHAM5 simulations. ECHAM5 performs better because more realistic aerosol concentrations are available for cloud droplet nucleation and because the Bergeron-Findeisen process is parameterized as being more efficient. The total anthropogenic aerosol effect includes the direct, semi-direct and indirect effects and is defined as the difference in the top-of-the-atmosphere net radiation between present-day and pre-industrial times. It amounts to -1.9 W m-2 in ECHAM5, when a relative humidity dependent cloud cover scheme and aerosol emissions representative for the years 1750 and 2000 from the AeroCom emission inventory are used. The contribution of the cloud albedo effect amounts to -0.7 W m-2. The total anthropogenic aerosol effect is larger when either a statistical cloud cover scheme or a different aerosol emission inventory are employed because the cloud lifetime effect increases.

Mapping changes in the largest continuous Amazonian mangrove belt using object-based classification of multisensor satellite imagery

NASA Astrophysics Data System (ADS)

Nascimento, Wilson R.; Souza-Filho, Pedro Walfir M.; Proisy, Christophe; Lucas, Richard M.; Rosenqvist, Ake

2013-01-01

Mapping and monitoring mangrove ecosystems is a crucial objective for tropical countries, particularly where human disturbance occurs and because of uncertainties associated with sea level and climatic fluctuation. In many tropical regions, such efforts have focused largely on the use of optical data despite low capture rates because of persistent cloud cover. Recognizing the ability of Synthetic Aperture Radar (SAR) for providing cloud-free observations, this study investigated the use of JERS-1 SAR and ALOS PALSAR data, acquired in 1996 and 2008 respectively, for mapping the extent of mangroves along the Brazilian coastline, from east of the Amazon River mouth, Pará State, to the Bay of São José in Maranhão. For each year, an object-orientated classification of major land covers (mangrove, secondary vegetation, gallery and swamp forest, open water, intermittent lakes and bare areas) was performed with the resulting maps then compared to quantify change. Comparison with available ground truth data indicated a general accuracy in the 2008 image classification of all land covers of 96% (kappa = 90.6%, tau = 92.6%). Over the 12 year period, the area of mangrove increased by 718.6 km2 from 6705 m2 to 7423.60 km2, with 1931.0 km² of expansion and 1213 km² of erosion noted; 5493 km² remained unchanged in extent. The general accuracy relating to changes in mangroves was 83.3% (Kappa 66.1%; tau 66.7%). The study confirmed that these mangroves constituted the largest continuous belt globally and were experiencing significant change because of the dynamic coastal environment and the influence of sedimentation from the Amazon River along the shoreline. The study recommends continued observations using combinations of SAR and optical data to establish trends in mangrove distributions and implications for provision of ecosystem services (e.g., fish/invertebrate nurseries, carbon storage and coastal protection).

Machine learning based cloud mask algorithm driven by radiative transfer modeling

NASA Astrophysics Data System (ADS)

Chen, N.; Li, W.; Tanikawa, T.; Hori, M.; Shimada, R.; Stamnes, K. H.

2017-12-01

Cloud detection is a critically important first step required to derive many satellite data products. Traditional threshold based cloud mask algorithms require a complicated design process and fine tuning for each sensor, and have difficulty over snow/ice covered areas. With the advance of computational power and machine learning techniques, we have developed a new algorithm based on a neural network classifier driven by extensive radiative transfer modeling. Statistical validation results obtained by using collocated CALIOP and MODIS data show that its performance is consistent over different ecosystems and significantly better than the MODIS Cloud Mask (MOD35 C6) during the winter seasons over mid-latitude snow covered areas. Simulations using a reduced number of satellite channels also show satisfactory results, indicating its flexibility to be configured for different sensors.

Smoke over Hudson Bay

NASA Image and Video Library

2017-12-08

A vigorous summer fire season continued through July, 2013 as many large wildfires continued to burn in the forests of northern Canada. The high fire activity not only laid waste to thousands of hectares of boreal forest, but sent thick smoke billowing high into the atmosphere, where it was carried far across the Atlantic Ocean. On July 30, the Moderate Resolution Imaging Spectroradiometer (MODIS) aboard NASA’s Aqua satellite captured this true-color image of a river of smoke spreading south across the Hudson Bay. The blue background is formed by the waters of Hudson Bay. In the southeast the green, forest-covered land of Quebec province peeks from under a large cloud bank. Another large bank of white cloud covers the water in the southwest, and a smaller cloud bank covers the territory of Nunavut in the northwest. A bit of Baffin Island can be seen near the top center of the image. Looking closely at the image, it appears that the gray smoke mixes with whiter cloud in the south, suggesting they may be at the same level in the atmosphere. In the northeast corner of the image, a ribbon of smoke appears to blow over a bank of popcorn clouds as well as over a few lower-lying clouds, causing some of the clouds to appear gray beneath the smoky veil. Where cloud meets smoke in the northeast, however, the line of the cloud bank remains sharp, while the smoke appears to continue traveling under the edge. Although these interpretations are somewhat subjective in this true-color image, the false-color image of the same scene (not shown here) lends strength to the interpretation. Data from other NASA instruments, designed to measure cloud height and characteristics, agree that clouds vary in height, and that smoke mingles with cloud in the south. Credit: NASA/GSFC/Jeff Schmaltz/MODIS Land Rapid Response Team NASA image use policy. NASA Goddard Space Flight Center enables NASA’s mission through four scientific endeavors: Earth Science, Heliophysics, Solar System Exploration, and Astrophysics. Goddard plays a leading role in NASA’s accomplishments by contributing compelling scientific knowledge to advance the Agency’s mission. Follow us on Twitter Like us on Facebook Find us on Instagram

Constraints on the inner accretion flow of 4U/MXB 1636-53 (V 801 Arae) from a comparison of X-ray burst and persistent emission

NASA Technical Reports Server (NTRS)

Damen, E.; Wijers, R. A. M. J.; Van Paradijs, J.; Penninx, W.; Oosterbroek, T.

1990-01-01

A detailed analysis is presented of the importance of Comptonization in burst and persistent spectra of the low-mass X-ray binary 4U/MXB 1636-53, and from this analysis it is inferred that the inner accretion flow is geometrically thin. It is found that burst spectra of 1636-53 are very nearly Planckian in shape; from an upper limit to a high-energy excess in these spectra it is inferred that the Thomson scattering optical depth of a possible intervening hot cloud must be less than 1 during bursts, and that the Compton y parameter of that cloud must be less than 0.5. During persistent emission, Thomson optical depth of 4-8, an electron temperature of 2-5 keV, and a value of 0.8-1.1 for y are inferred.

Human amplification of drought-driven fire in tropical regions

NASA Astrophysics Data System (ADS)

Tosca, Michael

2015-04-01

The change in globally-measured radiative forcing from the pre-industrial to the present due to interactions between aerosol particles and cloud cover has the largest uncertainty of all anthropogenic factors. Uncertainties are largest in the tropics, where total cloud amount and incoming solar radiation are highest, and where 50% of all aerosol emissions originate from anthropogenic fire. It is well understood that interactions between smoke particles and cloud droplets modify cloud cover , which in turn affects climate, however, few studies have observed the temporal nature of aerosol-cloud interactions without the use of a model. Here we apply a novel approach to measure the effect of fire aerosols on convective clouds in tropical regions (Brazil, Africa and Indonesia) through a combination of remote sensing and meteorological data. We attribute a reduction in cloud fraction during periods of high aerosol optical depths to a smoke-driven inhibition of convection. We find that higher smoke burdens limit vertical updrafts, increase surface pressure, and increase low- level divergence-meteorological indicators of convective suppression. These results are corroborated by climate model simulations that show a smoke-driven increase in regionally averaged shortwave tropospheric heating and boundary layer stratification, and a decrease in vertical velocity and precipitation during the fire season (December-February). We then quantify the human response to decreased cloud cover using a combination of socioeconomic and climate data Our results suggest that, in tropical regions, anthropogenic fire initiates a positive feedback loop where increased aerosol emissions limit convection, dry the surface and enable increased fire activity via human ignition. This result has far-reaching implications for fire management and climate policy in emerging countries along the equator that utilize fire.

Aerosols and their influence on radiation partitioning and savanna productivity in northern Australia

DOE Office of Scientific and Technical Information (OSTI.GOV)

Kanniah, K. D.; Beringer, J.; Tapper, N. J.

2010-05-01

We investigated the effect of aerosols and clouds on the Net Ecosystem Productivity (NEP) of savannas in northern Australia using aerosol optical depth, clouds and radiation data from the Atmospheric Radiation Measurement (ARM) site in Darwin and carbon flux data measured from eddy covariance techniques from a site at Howard Springs, 35km southeast of Darwin. Generally we found that the concentration of aerosols in this region was relatively low than observed at other sites, therefore the proportion of diffuse radiation reaching the earths surface was only ~ 30%. As a result, we observed only a modest change in carbon uptakemore » under aerosol laden skies and there was no significant difference for dry season Radiation Use Efficiency (RUE) between clear sky, aerosols or thin clouds. On the other hand thick clouds in the wet season produce much more diffuse radiation than aerosols or thin clouds and therefore the initial canopy quantum efficiency was seen to increase 45 and 2.5 times more than under thin clouds and aerosols respectively. The normalized carbon uptake under thick clouds is 57% and 50% higher than under aerosols and thin clouds respectively even though the total irradiance received under thick clouds was reduced 59% and 50% than under aerosols and thin clouds respectively. However, reduction in total irradiance decreases the mean absolute carbon uptake as much as 22% under heavy cloud cover compared to thin clouds or aerosols. Thus, any increase in aerosol concentration or cloud cover that can enhance the diffuse component may have large impacts on productivity in this region.« less

Evaluation of ERA-interim and MERRA Cloudiness in the Southern Oceans

NASA Technical Reports Server (NTRS)

Naud, Catherine M.; Booth, James F.; Del Genio, Anthony D.

2014-01-01

The Southern Ocean cloud cover modeled by the Interim ECMWF Re-Analysis (ERA-Interim) and Modern- Era Retrospective Analysis for Research and Applications (MERRA) reanalyses are compared against Moderate Resolution Imaging Spectroradiometer (MODIS) and Multiangle Imaging Spectroradiometer (MISR) observations. ERA-Interim monthly mean cloud amounts match the observations within 5%, while MERRA significantly underestimates the cloud amount. For a compositing analysis of clouds in warm season extratropical cyclones, both reanalyses show a low bias in cloud cover. They display a larger bias to the west of the cyclones in the region of subsidence behind the cold fronts. This low bias is larger for MERRA than for ERA-Interim. Both MODIS and MISR retrievals indicate that the clouds in this sector are at a low altitude, often composed of liquid, and of a broken nature. The combined CloudSat-Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) cloud profiles confirm these passive observations, but they also reveal that low-level clouds in other parts of the cyclones are also not properly represented in the reanalyses. The two reanalyses are in fairly good agreement for the dynamic and thermodynamic characteristics of the cyclones, suggesting that the cloud, convection, or boundary layer schemes are the problem instead. An examination of the lower-tropospheric stability distribution in the cyclones from both reanalyses suggests that the parameterization of shallow cumulus clouds may contribute in a large part to the problem. However, the differences in the cloud schemes and in particular in the precipitation processes, which may also contribute, cannot be excluded.

Effects of Cloud Properties on PM2.5 Levels in the Southeastern United States

NASA Astrophysics Data System (ADS)

Yu, C.; Zhang, X.; Liu, Y.

2012-12-01

The spatial and temporal characteristics of fine particulate matter (PM2.5) are increasingly being derived from satellite aerosol remote sensing data. A major concern of satellite-derived PM2.5 information is cloud cover, i.e., PM2.5 mass concentrations cannot be estimated from satellite observations under cloudy conditions. There has been little research on the effects of cloud properties on PM2.5 levels. In this study, we performed a statistical analysis of relationships between various cloud parameters and PM2.5 concentrations. We used 2005-2010 PM2.5 observations from 8 sites in the Southeastern Aerosol Research and Characterization (SEARCH) Network, and cloud parameters from MODIS cloud product retrievals from Terra and Aqua satellites. We find that cloud fraction (CF) is generally negatively correlated with the mean value of PM2.5 mass concentration. However, the largest mean value occurs when the cloud fraction is between 10% and 30% instead of lower cloud cover (CF < 10%). The mean value of PM2.5 decreased from 14.3μg/m3 during 10%~30% cloud fraction to 9.3μg/m3 in cloudy days (CF=100%), and the negative correlation is more significant during the summer and fall than spring and winter. In addition, Cloud top pressure (CTP) and cloud optical thickness (COT) also influence PM2.5 mass concentration, with CTP being positively correlated with PM2.5 while COT being negatively correlated. These results suggest that cloud parameters may be used as predictor variables in satellite models of PM2.5.

The Influence of Cloud Field Uniformity on Observed Cloud Amount

NASA Astrophysics Data System (ADS)

Riley, E.; Kleiss, J.; Kassianov, E.; Long, C. N.; Riihimaki, L.; Berg, L. K.

2017-12-01

Two ground-based measurements of cloud amount include cloud fraction (CF) obtained from time series of zenith-pointing radar-lidar observations and fractional sky cover (FSC) acquired from a Total Sky Imager (TSI). In comparison with the radars and lidars, the TSI has a considerably larger field of view (FOV 100° vs. 0.2°) and therefore is expected to have a different sensitivity to inhomogeneity in a cloud field. Radiative transfer calculations based on cloud properties retrieved from narrow-FOV overhead cloud observations may differ from shortwave and longwave flux observations due to spatial variability in local cloud cover. This bias will impede radiative closure for sampling reasons rather than the accuracy of cloud microphysics retrievals or radiative transfer calculations. Furthermore, the comparison between observed and modeled cloud amount from large eddy simulations (LES) models may be affected by cloud field inhomogeneity. The main goal of our study is to estimate the anticipated impact of cloud field inhomogeneity on the level of agreement between CF and FSC. We focus on shallow cumulus clouds observed at the U.S. Department of Energy Atmospheric Radiation Measurement Facility's Southern Great Plains (SGP) site in Oklahoma, USA. Our analysis identifies cloud field inhomogeneity using a novel metric that quantifies the spatial and temporal uniformity of FSC over 100-degree FOV TSI images. We demonstrate that (1) large differences between CF and FSC are partly attributable to increases in inhomogeneity and (2) using the uniformity metric can provide a meaningful assessment of uncertainties in observed cloud amount to aide in comparing ground-based measurements to radiative transfer or LES model outputs at SGP.

Temperature Calculations in the Coastal Modeling System

DTIC Science & Technology

2017-04-01

tide) and river discharge at model boundaries, wave radiation stress, and wind forcing over a model computational domain. Physical processes calculated...calculated in the CMS using the following meteorological parameters: solar radiation, cloud cover, air temperature, wind speed, and surface water temperature...during a clear (i.e., cloudless) sky (Wm-2); CLDC is the cloud cover fraction (0-1.0); SWR is the surface reflection coefficient; and SHDf is the

Origin and causes of the mammoth steppe: a story of cloud cover, woolly mammal tooth pits, buckles, and inside-out Beringia

NASA Astrophysics Data System (ADS)

Dale Guthrie, R.

2001-01-01

To account for the vastness of the northern arid steppes during Glacial episodes, I propose the proximate key variable was simply frequent clear skies. This hitherto under-emphasized point is the hub which best explains many questions. Low maritime cloud cover best accounts for today's tundra, and in a related way, the cloudy Polar Front accounts for the whole of the taiga. Even during Glacial maxima, the proximity of the sea to the Bering isthmus created intermittent maritime cloud cover. This regional cloud cover produced an ecological interruption, or buckle, of the arid steppe belt. While this Beringian mesic buckle did not serve as an intercontinental ecological barrier to most steppe-adapted species, it does seem to have limited the distributions of woolly rhinos, camels, American kiangs, short-faced bears, badgers, and some others. At the beginning of the Holocene, this narrow refugium seems to have been a source of some mesic-adapted species which colonized westward into the now tundra vegetation of northern Asia and eastward into northern North America. This Holocene expansion from a limited and regional Pleistocene refugium created our present misconceptions about Beringia. The mid-strait mesic ecological conditions were the exception to the more extensive, arid-adapted, communities of the Mammoth Steppe.

Formation and maintenance of nocturnal low-level stratus over the southern West African monsoon region during AMMA 2006

NASA Astrophysics Data System (ADS)

Schuster, Robert; Fink, Andreas; Knippertz, Peter

2013-04-01

The southern parts of West Africa, from the coast to about 9°N, are frequently covered by an extensive deck of shallow, low (200 - 400 m above ground) stratus or stratocumulus clouds during the summer monsoon season as shown by recent studies based on ground observations and new satellite products. These clouds usually form at night in association with a nocturnal low-level jet (NLLJ) and can persist into the early afternoon hours until they are dissipated or replaced by fair-weather cumuli. Recent work suggests that the stratus deck and its effect on the surface radiation balance are unsatisfactorily represented in standard satellite retrievals and simulations by state-of-the-art climate models. Here we use high-resolution regional simulations with the Weather Research and Forecast (WRF) model and observations from the African Monsoon Multidisciplinary Analysis (AMMA) 2006 campaign to investigate (a) the spatiotemporal distribution, (b) the influence on the radiation balance, and (c) the detailed formation and maintenance mechanisms of the stratiform clouds. The model configuration used for this study has been determined following an extensive sensitivity study. The main conclusions are: (a) At least some configurations of WRF satisfactorily reproduce the diurnal cycle of the low cloud evolution. (b) The simulated stratus deck forms after sunset along the coast, spreads inland in the course of the night, and dissipates in the early afternoon. (c) The average surface net radiation balance in stratus-dominated regions is 35 W m-2 lower than in those with less clouds. (d) The cloud formation is related to a subtle balance between "stratogenic" upward (downward) fluxes of latent (sensible) heat caused by shear-driven turbulence below the NLLJ, cold advection from the ocean, forced lifting at the windward side of orography, and radiative cooling on one hand, and "stratolytic" dry advection and latent heating on the other hand. Future work should focus on the influence of the stratus on energy and moisture budgets and on the West African monsoon system as a whole.

Cloud Masking and Surface Temperature Distribution in the Polar Regions Using AVHRR and other Satellite Data

NASA Technical Reports Server (NTRS)

Comiso, Joey C.

1995-01-01

Surface temperature is one of the key variables associated with weather and climate. Accurate measurements of surface air temperatures are routinely made in meteorological stations around the world. Also, satellite data have been used to produce synoptic global temperature distributions. However, not much attention has been paid on temperature distributions in the polar regions. In the polar regions, the number of stations is very sparse. Because of adverse weather conditions and general inaccessibility, surface field measurements are also limited. Furthermore, accurate retrievals from satellite data in the region have been difficult to make because of persistent cloudiness and ambiguities in the discrimination of clouds from snow or ice. Surface temperature observations are required in the polar regions for air-sea-ice interaction studies, especially in the calculation of heat, salinity, and humidity fluxes. They are also useful in identifying areas of melt or meltponding within the sea ice pack and the ice sheets and in the calculation of emissivities of these surfaces. Moreover, the polar regions are unique in that they are the sites of temperature extremes, the location of which is difficult to identify without a global monitoring system. Furthermore, the regions may provide an early signal to a potential climate change because such signal is expected to be amplified in the region due to feedback effects. In cloud free areas, the thermal channels from infrared systems provide surface temperatures at relatively good accuracies. Previous capabilities include the use of the Temperature Humidity Infrared Radiometer (THIR) onboard the Nimbus-7 satellite which was launched in 1978. Current capabilities include the use of the Advance Very High Resolution Radiometer (AVHRR) aboard NOAA satellites. Together, these two systems cover a span of 16 years of thermal infrared data. Techniques for retrieving surface temperatures with these sensors in the polar regions have been developed. Errors have been estimated to range from 1K to 5K mainly due to cloud masking problems. With many additional channels available, it is expected that the EOS-Moderate Resolution Imaging Spectroradiometer (MODIS) will provide an improved characterization of clouds and a good discrimination of clouds from snow or ice surfaces.

Cloud Occurrence Measurements Over Sea during the 2nd 7 Southeast Asian Studies (7SEAS) Field Campaign in Palawan Archipelago

NASA Astrophysics Data System (ADS)

Antioquia, C. T.; Uy, S. N.; Caballa, K.; Lagrosas, N.

2014-12-01

Ground based sky imaging cameras have been used to measure cloud cover over an area to aid in radiation budget models. During daytime, certain clouds tend to help decrease atmospheric temperature by obstructing sunrays in the atmosphere. Thus, the detection of clouds plays an important role in the formulation of radiation budget in the atmosphere. In this study, a wide angled sky imager (GoPro Hero 2) was brought on board M/Y Vasco to detect and quantity cloud occurrence over sea during the 2nd 7SEAS field campaign. The camera is just a part of a number of scientific instruments used to measure weather, aerosol chemistry and solar radiation among others. The data collection started during the departure from Manila Bay on 05 September 2012 and went on until the end of the cruise (29 September 2012). The camera was placed in a weather-proof box that is then affixed on a steel mast where other instruments are also attached during the cruise. The data has a temporal resolution of 1 minute, and each image is 500x666 pixels in size. Fig. 1a shows the track of the ship during the cruise. The red, blue, hue, saturation, and value of the pixels are analysed for cloud occurrence. A pixel is considered to "contain" thick cloud if it passes all four threshold parameters (R-B, R/B, R-B/R+B, HSV; R is the red pixel color value, blue is the blue pixel color value, and HSV is the hue saturation value of the pixel) and considered thin cloud if it passes two or three parameters. Fig. 1b shows the daily analysis of cloud occurrence. Cloud occurrence here is quantified as the ratio of the pixels with cloud to the total number of pixels in the data image. The average cloud cover for the days included in this dataset is 87%. These measurements show a big contrast when compared to cloud cover over land (Manila Observatory) which is usually around 67%. During the duration of the cruise, only one day (September 6) has an average cloud occurrence below 50%; the rest of the days have averages of 66% or higher - 98% being the highest. This result would then give a general trend of how cloud occurrences over land and over sea differ in the South East Asian region. In this study, these cloud occurrences come from local convection and clouds brought about by Southwest Monsoon winds.

A Climatology of Midlatitude Continental Clouds from the ARM SGP Central Facility. Part II; Cloud Fraction and Radiative Forcing

NASA Technical Reports Server (NTRS)

Dong, Xiquan; Xi, Baike; Minnis, Patrick

2006-01-01

Data collected at the Department of Energy Atmospheric Radiation Measurement (ARM) Southern Great Plains (SGP) central facility are analyzed for determining the variability of cloud fraction and radiative forcing at several temporal scales between January 1997 and December 2002. Cloud fractions are estimated for total cloud cover and for single-layer low (0-3 km), middle (3-6 km), and high clouds (greater than 6 km) using ARM SGP ground-based paired lidar-radar measurements. Shortwave (SW), longwave (LW), and net cloud radiative forcings (CRF) are derived from up- and down-looking standard precision spectral pyranometers and precision infrared radiometer measurements. The annual averages of total, and single-layer, nonoverlapped low, middle and high cloud fractions are 0.49, 0.11, 0.03, and 0.17, respectively. Total and low cloud amounts were greatest from December through March and least during July and August. The monthly variation of high cloud amount is relatively small with a broad maximum from May to August. During winter, total cloud cover varies diurnally with a small amplitude, mid-morning maximum and early evening minimum, and during summer it changes by more than 0.14 over the daily cycle with a pronounced early evening minimum. The diurnal variations of mean single-layer cloud cover change with season and cloud height. Annual averages of all-sky, total, and single-layer high, middle, and low LW CRFs are 21.4, 40.2, 16.7, 27.2, and 55.0 Wm(sup -2), respectively; and their SW CRFs are -41.5, -77.2, -37.0, -47.0, and -90.5 Wm(sup -2). Their net CRFs range from -20 to -37 Wm(sup -2). For all-sky, total, and low clouds, the maximum negative net CRFs of -40.1, -70, and -69.5 Wm(sup -2), occur during April; while the respective minimum values of -3.9, -5.7, and -4.6 Wm(sup -2), are found during December. July is the month having maximum negative net CRF of -46.2 Wm(sup -2) for middle clouds, and May has the maximum value of -45.9 Wm(sup -2) for high clouds. An uncertainty analysis demonstrates that the calculated CRFs are not significantly affected by the difference between clear-sky and cloudy conditions. A more comprehensive cloud fraction study from both surface and satellite observations will follow.

Evaluating the spatio-temporal performance of sky-imager-based solar irradiance analysis and forecasts

NASA Astrophysics Data System (ADS)

Schmidt, Thomas; Kalisch, John; Lorenz, Elke; Heinemann, Detlev

2016-03-01

Clouds are the dominant source of small-scale variability in surface solar radiation and uncertainty in its prediction. However, the increasing share of solar energy in the worldwide electric power supply increases the need for accurate solar radiation forecasts. In this work, we present results of a very short term global horizontal irradiance (GHI) forecast experiment based on hemispheric sky images. A 2-month data set with images from one sky imager and high-resolution GHI measurements from 99 pyranometers distributed over 10 km by 12 km is used for validation. We developed a multi-step model and processed GHI forecasts up to 25 min with an update interval of 15 s. A cloud type classification is used to separate the time series into different cloud scenarios. Overall, the sky-imager-based forecasts do not outperform the reference persistence forecasts. Nevertheless, we find that analysis and forecast performance depends strongly on the predominant cloud conditions. Especially convective type clouds lead to high temporal and spatial GHI variability. For cumulus cloud conditions, the analysis error is found to be lower than that introduced by a single pyranometer if it is used representatively for the whole area in distances from the camera larger than 1-2 km. Moreover, forecast skill is much higher for these conditions compared to overcast or clear sky situations causing low GHI variability, which is easier to predict by persistence. In order to generalize the cloud-induced forecast error, we identify a variability threshold indicating conditions with positive forecast skill.

Cloud Statistics for NASA Climate Change Studies

NASA Technical Reports Server (NTRS)

Wylie, Donald P.

1999-01-01

The Principal Investigator participated in two field experiments and developed a global data set on cirrus cloud frequency and optical depth to aid the development of numerical models of climate. Four papers were published under this grant. The accomplishments are summarized: (1) In SUCCESS (SUbsonic aircraft: Contrail & Cloud Effects Special Study) the Principal Investigator aided weather forecasters in the start of the field program. A paper also was published on the clouds studied in SUCCESS and the use of the satellite stereographic technique to distinguish cloud forms and heights of clouds. (2) In SHEBA (Surface Heat Budget in the Arctic) FIRE/ACE (Arctic Cloud Experiment) the Principal Investigator provided daily weather and cloud forecasts for four research aircraft crews, NASA's ER-2, UCAR's C-130, University of Washington's Convert 580, and the Canadian Atmospheric Environment Service's Convert 580. Approximately 105 forecasts were written. The Principal Investigator also made daily weather summaries with calculations of air trajectories for 54 flight days in the experiment. The trajectories show where the air sampled during the flights came from and will be used in future publications to discuss the origin and history of the air and clouds sampled by the aircraft. A paper discussing how well the FIRE/ACE data represent normal climatic conditions in the arctic is being prepared. (3) The Principal Investigator's web page became the source of information for weather forecasting by the scientists on the SHEBA ship. (4) Global Cirrus frequency and optical depth is a continuing analysis of global cloud cover and frequency distribution are being made from the NOAA polar orbiting weather satellites. This analysis is sensitive to cirrus clouds because of the radiative channels used. During this grant three papers were published which describe cloud frequencies, their optical properties and compare the Wisconsin FM Cloud Analysis to other global cloud data such as the International Satellite Cloud Climatology Program (ISCCP) and the Stratospheric Aerosol and Gas Experiment (SAGE). A summary of eight years of HIRS data will be published in late 1998. Important information from this study are: 1) cirrus clouds cover most of the earth, 2) they are found about 40% of the time globally, 3) in the tropics cirrus cloud frequencies are even higher, from 80-100%, 4) there is slight evidence that cirnis cloud cover is increasing in the northern hemisphere at about 0.5% per year, and 5) cirrus clouds have an average infrared transmittance of about 40% of the terrestrial radiation. (5) Global Cloud Frequency Statistics published on the Principal Investigator's web page have been used in the planning of the future CRYSTAL experiment and have been used for refinements of a global numerical model operated at the Colorado State University.

Tropical cloud feedbacks and natural variability of climate

NASA Technical Reports Server (NTRS)

Miller, R. L.; Del Genio, A. D.

1994-01-01

Simulations of natural variability by two general circulation models (GCMs) are examined. One GCM is a sector model, allowing relatively rapid integration without simplification of the model physics, which would potentially exclude mechanisms of variability. Two mechanisms are found in which tropical surface temperature and sea surface temperature (SST) vary on interannual and longer timescales. Both are related to changes in cloud cover that modulate SST through the surface radiative flux. Over the equatorial ocean, SST and surface temperature vary on an interannual timescale, which is determined by the magnitude of the associated cloud cover anomalies. Over the subtropical ocean, variations in low cloud cover drive SST variations. In the sector model, the variability has no preferred timescale, but instead is characterized by a 'red' spectrum with increasing power at longer periods. In the terrestrial GCM, SST variability associated with low cloud anomalies has a decadal timescale and is the dominant form of global temperature variability. Both GCMs are coupled to a mixed layer ocean model, where dynamical heat transports are prescribed, thus filtering out El Nino-Southern Oscillation (ENSO) and thermohaline circulation variability. The occurrence of variability in the absence of dynamical ocean feedbacks suggests that climatic variability on long timescales can arise from atmospheric processes alone.

CO observations of dark clouds in Lupus

NASA Technical Reports Server (NTRS)

Murphy, D. C.; Cohen, R.; May, J.

1986-01-01

C-12O observations covering 170 square degrees toward the southern T Association Lupus have revealed the presence of an extended physically related complex of dark clouds which have recently formed low mass stars. The estimated mass of the clouds (about 30,000 solar masses) is comparable to that of the nearby Ophiuchus dust clouds. The Lupus clouds are projected onto a gap between two subgroups of the Scorpio-Centaurus OB association suggesting that this long accepted subgrouping may require reinterpretation.

Cloud-Scale Vertical Velocity and Turbulent Dissipation Rate Retrievals

DOE Data Explorer

Shupe, Matthew

2013-05-22

Time-height fields of retrieved in-cloud vertical wind velocity and turbulent dissipation rate, both retrieved primarily from vertically-pointing, Ka-band cloud radar measurements. Files are available for manually-selected, stratiform, mixed-phase cloud cases observed at the North Slope of Alaska (NSA) site during periods covering the Mixed-Phase Arctic Cloud Experiment (MPACE, late September through early November 2004) and the Indirect and Semi-Direct Aerosol Campaign (ISDAC, April-early May 2008). These time periods will be expanded in a future submission.

Brute Force Matching Between Camera Shots and Synthetic Images from Point Clouds

NASA Astrophysics Data System (ADS)

Boerner, R.; Kröhnert, M.

2016-06-01

3D point clouds, acquired by state-of-the-art terrestrial laser scanning techniques (TLS), provide spatial information about accuracies up to several millimetres. Unfortunately, common TLS data has no spectral information about the covered scene. However, the matching of TLS data with images is important for monoplotting purposes and point cloud colouration. Well-established methods solve this issue by matching of close range images and point cloud data by fitting optical camera systems on top of laser scanners or rather using ground control points. The approach addressed in this paper aims for the matching of 2D image and 3D point cloud data from a freely moving camera within an environment covered by a large 3D point cloud, e.g. a 3D city model. The key advantage of the free movement affects augmented reality applications or real time measurements. Therefore, a so-called real image, captured by a smartphone camera, has to be matched with a so-called synthetic image which consists of reverse projected 3D point cloud data to a synthetic projection centre whose exterior orientation parameters match the parameters of the image, assuming an ideal distortion free camera.

Quantitative Measures of Immersion in Cloud and the Biogeography of Cloud Forests

NASA Technical Reports Server (NTRS)

Lawton, R. O.; Nair, U. S.; Ray, D.; Regmi, A.; Pounds, J. A.; Welch, R. M.

2010-01-01

Sites described as tropical montane cloud forests differ greatly, in part because observers tend to differ in their opinion as to what constitutes frequent and prolonged immersion in cloud. This definitional difficulty interferes with hydrologic analyses, assessments of environmental impacts on ecosystems, and biogeographical analyses of cloud forest communities and species. Quantitative measurements of cloud immersion can be obtained on site, but the observations are necessarily spatially limited, although well-placed observers can examine 10 50 km of a mountain range under rainless conditions. Regional analyses, however, require observations at a broader scale. This chapter discusses remote sensing and modeling approaches that can provide quantitative measures of the spatiotemporal patterns of cloud cover and cloud immersion in tropical mountain ranges. These approaches integrate remote sensing tools of various spatial resolutions and frequencies of observation, digital elevation models, regional atmospheric models, and ground-based observations to provide measures of cloud cover, cloud base height, and the intersection of cloud and terrain. This combined approach was applied to the Monteverde region of northern Costa Rica to illustrate how the proportion of time the forest is immersed in cloud may vary spatially and temporally. The observed spatial variation was largely due to patterns of airflow over the mountains. The temporal variation reflected the diurnal rise and fall of the orographic cloud base, which was influenced in turn by synoptic weather conditions, the seasonal movement of the Intertropical Convergence Zone and the north-easterly trade winds. Knowledge of the proportion of the time that sites are immersed in clouds should facilitate ecological comparisons and biogeographical analyses, as well as land use planning and hydrologic assessments in areas where intensive on-site work is not feasible.

Titan's atmosphere (clouds and composition): new results

NASA Astrophysics Data System (ADS)

Griffith, C. A.

Titan's atmosphere potentially sports a cycle similar to the hydrologic one on Earth with clouds, rain and seas, but with methane playing the terrestrial role of water. Over the past ten years many independent efforts indicated no strong evidence for cloudiness until some unique spectra were analyzed in 1998 (Griffith et al.). These surprising observations displayed enhanced fluxes of 14-200 % on two nights at precisely the wavelengths (windows) that sense Titan's lower altitude where clouds might reside. The morphology of these enhancements in all 4 windows observed indicate that clouds covered ~6-9 % of Titan's surface and existed at ~15 km altitude. Here I discuss new observations recorded in 1999 aimed to further characterize Titan's clouds. While we find no evidence for a massive cloud system similar to the one observed previously, 1%-4% fluctuations in flux occur daily. These modulations, similar in wavelength and morphology to the more pronounced ones observed earlier, suggest the presence of clouds covering ≤1% of Titan's disk. The variations are too small to have been detected by most prior measurements. Repeated observations, spaced 30 minutes apart, indicate a temporal variability observable in the time scale of a couple of hours. The cloud heights hint that convection might govern their evolution. Their short lives point to the presence of rain.

Air Modeling - Observational Meteorological Data

EPA Pesticide Factsheets

Observed meteorological data for use in air quality modeling consist of physical parameters that are measured directly by instrumentation, and include temperature, dew point, wind direction, wind speed, cloud cover, cloud layer(s), ceiling height,

MODIS Collection 6 Data at the National Snow and Ice Data Center (NSIDC)

NASA Astrophysics Data System (ADS)

Fowler, D. K.; Steiker, A. E.; Johnston, T.; Haran, T. M.; Fowler, C.; Wyatt, P.

2015-12-01

For over 15 years, the NASA National Snow and Ice Data Center Distributed Active Archive Center (NSIDC DAAC) has archived and distributed snow and sea ice products derived from the Moderate Resolution Imaging Spectroradiometer (MODIS) instruments on the NASA Earth Observing System (EOS) Aqua and Terra satellites. Collection 6 represents the next revision to NSIDC's MODIS archive, mainly affecting the snow-cover products. Collection 6 specifically addresses the needs of the MODIS science community by targeting the scenarios that have historically confounded snow detection and introduced errors into the snow-cover and fractional snow-cover maps even though MODIS snow-cover maps are typically 90 percent accurate or better under good observing conditions, Collection 6 uses revised algorithms to discriminate between snow and clouds, resolve uncertainties along the edges of snow-covered regions, and detect summer snow cover in mountains. Furthermore, Collection 6 applies modified and additional snow detection screens and new Quality Assessment protocols that enhance the overall accuracy of the snow maps compared with Collection 5. Collection 6 also introduces several new MODIS snow products, including a daily Climate Modelling Grid (CMG) cloud gap-filled (CGF) snow-cover map which generates cloud-free maps by using the most recent clear observations.. The MODIS Collection 6 sea ice extent and ice surface temperature algorithms and products are much the same as Collection 5; however, Collection 6 updates to algorithm inputs—in particular, the L1B calibrated radiances, land and water mask, and cloud mask products—have improved the sea ice outputs. The MODIS sea ice products are currently available at NSIDC, and the snow cover products are soon to follow in 2016 NSIDC offers a variety of methods for obtaining these data. Users can download data directly from an online archive or use the NASA Reverb Search & Order Tool to perform spatial, temporal, and parameter subsetting, reformatting, and re-projection of the data.

Improving Forecast Skill by Assimilation of AIRS Cloud Cleared Radiances RiCC

NASA Technical Reports Server (NTRS)

Susskind, Joel; Rosenberg, Robert I.; Iredell, Lena

2015-01-01

ECMWF, NCEP, and GMAO routinely assimilate radiosonde and other in-situ observations along with satellite IR and MW Sounder radiance observations. NCEP and GMAO use the NCEP GSI Data Assimilation System (DAS).GSI DAS assimilates AIRS, CrIS, IASI channel radiances Ri on a channel-by-channel, case-by-case basis, only for those channels i thought to be unaffected by cloud cover. This test excludes Ri for most tropospheric sounding channels under partial cloud cover conditions. AIRS Version-6 RiCC is a derived quantity representative of what AIRS channel i would have seen if the AIRS FOR were cloud free. All values of RiCC have case-by-case error estimates RiCC associated with them. Our experiments present to the GSI QCd values of AIRS RiCC in place of AIRS Ri observations. GSI DAS assimilates only those values of RiCC it thinks are cloud free. This potentially allows for better coverage of assimilated QCd values of RiCC as compared to Ri.

Cloud removing method for daily snow mapping over Central Asia and Xinjiang, China

NASA Astrophysics Data System (ADS)

Yu, Xiaoqi; Qiu, Yubao; Guo, Huadong; Chen, Lijuan

2017-02-01

Central Asia and Xinjiang, China are conjunct areas, located in the hinterland of the Eurasian continent, where the snowfall is an important water resource supplement form. The induced seasonal snow cover is vita factors to the regional energy and water balance, remote sensing plays a key role in the snow mapping filed, while the daily remote sensing products are normally contaminated by the occurrence of cloud, that obviously obstacles the utility of snow cover parameters. In this paper, based on the daily snow product from Moderate Resolution Imaging Spectroradiometer (MODIS A1), a cloud removing method was developed by considering the regional snow distribution characteristics with latitude and altitude dependence respectively. In the end, the daily cloud free products was compared with the same period of eight days MODIS standard product, revealing that the cloud free snow products are reasonable, while could provide higher temporal resolution, and more details over Center Asia and Xinjiang Province.

Capturing coupled riparian and coastal disturbance from industrial mining using cloud-resilient satellite time series analysis.

PubMed

Alonzo, Michael; Van Den Hoek, Jamon; Ahmed, Nabil

2016-10-11

The socio-ecological impacts of large scale resource extraction are frequently underreported in underdeveloped regions. The open-pit Grasberg mine in Papua, Indonesia, is one of the world's largest copper and gold extraction operations. Grasberg mine tailings are discharged into the lowland Ajkwa River deposition area (ADA) leading to forest inundation and degradation of water bodies critical to indigenous peoples. The extent of the changes and temporal linkages with mining activities are difficult to establish given restricted access to the region and persistent cloud cover. Here, we introduce remote sensing methods to "peer through" atmospheric contamination using a dense Landsat time series to simultaneously quantify forest loss and increases in estuarial suspended particulate matter (SPM) concentration. We identified 138 km 2 of forest loss between 1987 and 2014, an area >42 times larger than the mine itself. Between 1987 and 1998, the rate of disturbance was highly correlated (Pearson's r = 0.96) with mining activity. Following mine expansion and levee construction along the ADA in the mid-1990s, we recorded significantly (p < 0.05) higher SPM in the Ajkwa Estuary compared to neighboring estuaries. This research provides a means to quantify multiple modes of ecological damage from mine waste disposal or other disturbance events.

Capturing coupled riparian and coastal disturbance from industrial mining using cloud-resilient satellite time series analysis

PubMed Central

Alonzo, Michael; Van Den Hoek, Jamon; Ahmed, Nabil

2016-01-01

The socio-ecological impacts of large scale resource extraction are frequently underreported in underdeveloped regions. The open-pit Grasberg mine in Papua, Indonesia, is one of the world’s largest copper and gold extraction operations. Grasberg mine tailings are discharged into the lowland Ajkwa River deposition area (ADA) leading to forest inundation and degradation of water bodies critical to indigenous peoples. The extent of the changes and temporal linkages with mining activities are difficult to establish given restricted access to the region and persistent cloud cover. Here, we introduce remote sensing methods to “peer through” atmospheric contamination using a dense Landsat time series to simultaneously quantify forest loss and increases in estuarial suspended particulate matter (SPM) concentration. We identified 138 km2 of forest loss between 1987 and 2014, an area >42 times larger than the mine itself. Between 1987 and 1998, the rate of disturbance was highly correlated (Pearson’s r = 0.96) with mining activity. Following mine expansion and levee construction along the ADA in the mid-1990s, we recorded significantly (p < 0.05) higher SPM in the Ajkwa Estuary compared to neighboring estuaries. This research provides a means to quantify multiple modes of ecological damage from mine waste disposal or other disturbance events. PMID:27725748

Capturing coupled riparian and coastal disturbance from industrial mining using cloud-resilient satellite time series analysis

NASA Astrophysics Data System (ADS)

Alonzo, Michael; van den Hoek, Jamon; Ahmed, Nabil

2016-10-01

The socio-ecological impacts of large scale resource extraction are frequently underreported in underdeveloped regions. The open-pit Grasberg mine in Papua, Indonesia, is one of the world’s largest copper and gold extraction operations. Grasberg mine tailings are discharged into the lowland Ajkwa River deposition area (ADA) leading to forest inundation and degradation of water bodies critical to indigenous peoples. The extent of the changes and temporal linkages with mining activities are difficult to establish given restricted access to the region and persistent cloud cover. Here, we introduce remote sensing methods to “peer through” atmospheric contamination using a dense Landsat time series to simultaneously quantify forest loss and increases in estuarial suspended particulate matter (SPM) concentration. We identified 138 km2 of forest loss between 1987 and 2014, an area >42 times larger than the mine itself. Between 1987 and 1998, the rate of disturbance was highly correlated (Pearson’s r = 0.96) with mining activity. Following mine expansion and levee construction along the ADA in the mid-1990s, we recorded significantly (p < 0.05) higher SPM in the Ajkwa Estuary compared to neighboring estuaries. This research provides a means to quantify multiple modes of ecological damage from mine waste disposal or other disturbance events.

Analysis of Leaf Area Index and Fraction of PAR Absorbed by Vegetation Products from the Terra MODIS Sensor: 2000-2005

NASA Technical Reports Server (NTRS)

Yang, Wenze; Huang, Dong; Tan, Bin; Stroeve, Julienne C.; Shabanov, Nikolay V.; Knyazikhin, Yuri; Nemani, Ramakrishna R.; Myneni, Ranga B.

2006-01-01

The analysis of two years of Collection 3 and five years of Collection 4 Terra Moderate Resolution Imaging Spectroradiometer (MODIS) Leaf Area Index (LAI) and Fraction of Photosynthetically Active Radiation (FPAR) data sets is presented in this article with the goal of understanding product quality with respect to version (Collection 3 versus 4), algorithm (main versus backup), snow (snow-free versus snow on the ground), and cloud (cloud-free versus cloudy) conditions. Retrievals from the main radiative transfer algorithm increased from 55% in Collection 3 to 67% in Collection 4 due to algorithm refinements and improved inputs. Anomalously high LAI/FPAR values observed in Collection 3 product in some vegetation types were corrected in Collection 4. The problem of reflectance saturation and too few main algorithm retrievals in broadleaf forests persisted in Collection 4. The spurious seasonality in needleleaf LAI/FPAR fields was traced to fewer reliable input data and retrievals during the boreal winter period. About 97% of the snow covered pixels were processed by the backup Normalized Difference Vegetation Index-based algorithm. Similarly, a majority of retrievals under cloudy conditions were obtained from the backup algorithm. For these reasons, the users are advised to consult the quality flags accompanying the LAI and FPAR product.

The Clouds distributed operating system - Functional description, implementation details and related work

NASA Technical Reports Server (NTRS)

Dasgupta, Partha; Leblanc, Richard J., Jr.; Appelbe, William F.

1988-01-01

Clouds is an operating system in a novel class of distributed operating systems providing the integration, reliability, and structure that makes a distributed system usable. Clouds is designed to run on a set of general purpose computers that are connected via a medium-of-high speed local area network. The system structuring paradigm chosen for the Clouds operating system, after substantial research, is an object/thread model. All instances of services, programs and data in Clouds are encapsulated in objects. The concept of persistent objects does away with the need for file systems, and replaces it with a more powerful concept, namely the object system. The facilities in Clouds include integration of resources through location transparency; support for various types of atomic operations, including conventional transactions; advanced support for achieving fault tolerance; and provisions for dynamic reconfiguration.

THE INFLUENCE OF NONUNIFORM CLOUD COVER ON TRANSIT TRANSMISSION SPECTRA

DOE Office of Scientific and Technical Information (OSTI.GOV)

Line, Michael R.; Parmentier, Vivien, E-mail: mrline@ucsc.edu

2016-03-20

We model the impact of nonuniform cloud cover on transit transmission spectra. Patchy clouds exist in nearly every solar system atmosphere, brown dwarfs, and transiting exoplanets. Our major findings suggest that fractional cloud coverage can exactly mimic high mean molecular weight atmospheres and vice versa over certain wavelength regions, in particular, over the Hubble Space Telescope (HST) Wide Field Camera 3 (WFC3) bandpass (1.1–1.7 μm). We also find that patchy cloud coverage exhibits a signature that is different from uniform global clouds. Furthermore, we explain analytically why the “patchy cloud-high mean molecular weight” degeneracy exists. We also explore the degeneracy ofmore » nonuniform cloud coverage in atmospheric retrievals on both synthetic and real planets. We find from retrievals on a synthetic solar composition hot Jupiter with patchy clouds and a cloud-free high mean molecular weight warm Neptune that both cloud-free high mean molecular weight atmospheres and partially cloudy atmospheres can explain the data equally well. Another key finding is that the HST WFC3 transit transmission spectra of two well-observed objects, the hot Jupiter HD 189733b and the warm Neptune HAT-P-11b, can be explained well by solar composition atmospheres with patchy clouds without the need to invoke high mean molecular weight or global clouds. The degeneracy between high molecular weight and solar composition partially cloudy atmospheres can be broken by observing the molecular Rayleigh scattering differences between the two. Furthermore, the signature of partially cloudy limbs also appears as a ∼100 ppm residual in the ingress and egress of the transit light curves, provided that the transit timing is known to seconds.« less

Bigdata Driven Cloud Security: A Survey

NASA Astrophysics Data System (ADS)

Raja, K.; Hanifa, Sabibullah Mohamed

2017-08-01

Cloud Computing (CC) is a fast-growing technology to perform massive-scale and complex computing. It eliminates the need to maintain expensive computing hardware, dedicated space, and software. Recently, it has been observed that massive growth in the scale of data or big data generated through cloud computing. CC consists of a front-end, includes the users’ computers and software required to access the cloud network, and back-end consists of various computers, servers and database systems that create the cloud. In SaaS (Software as-a-Service - end users to utilize outsourced software), PaaS (Platform as-a-Service-platform is provided) and IaaS (Infrastructure as-a-Service-physical environment is outsourced), and DaaS (Database as-a-Service-data can be housed within a cloud), where leading / traditional cloud ecosystem delivers the cloud services become a powerful and popular architecture. Many challenges and issues are in security or threats, most vital barrier for cloud computing environment. The main barrier to the adoption of CC in health care relates to Data security. When placing and transmitting data using public networks, cyber attacks in any form are anticipated in CC. Hence, cloud service users need to understand the risk of data breaches and adoption of service delivery model during deployment. This survey deeply covers the CC security issues (covering Data Security in Health care) so as to researchers can develop the robust security application models using Big Data (BD) on CC (can be created / deployed easily). Since, BD evaluation is driven by fast-growing cloud-based applications developed using virtualized technologies. In this purview, MapReduce [12] is a good example of big data processing in a cloud environment, and a model for Cloud providers.

Cloud Coverage and Height Distribution from the GLAS Polar Orbiting Lidar: Comparison to Passive Cloud Retrievals

NASA Technical Reports Server (NTRS)

Spinhime, J. D.; Palm, S. P.; Hlavka, D. L.; Hart, W. D.; Mahesh, A.

2004-01-01

The Geoscience Laser Altimeter System (GLAS) began full on orbit operations in September 2003. A main application of the two-wavelength GLAS lidar is highly accurate detection and profiling of global cloud cover. Initial analysis indicates that cloud and aerosol layers are consistently detected on a global basis to cross-sections down to 10(exp -6) per meter. Images of the lidar data dramatically and accurately show the vertical structure of cloud and aerosol to the limit of signal attenuation. The GLAS lidar has made the most accurate measurement of global cloud coverage and height to date. In addition to the calibrated lidar signal, GLAS data products include multi level boundaries and optical depth of all transmissive layers. Processing includes a multi-variable separation of cloud and aerosol layers. An initial application of the data results is to compare monthly cloud means from several months of GLAS observations in 2003 to existing cloud climatologies from other satellite measurement. In some cases direct comparison to passive cloud retrievals is possible. A limitation of the lidar measurements is nadir only sampling. However monthly means exhibit reasonably good global statistics and coverage results, at other than polar regions, compare well with other measurements but show significant differences in height distribution. For polar regions where passive cloud retrievals are problematic and where orbit track density is greatest, the GLAS results are particularly an advance in cloud cover information. Direct comparison to MODIS retrievals show a better than 90% agreement in cloud detection for daytime, but less than 60% at night. Height retrievals are in much less agreement. GLAS is a part of the NASA EOS project and data products are thus openly available to the science community (see http://glo.gsfc.nasa.gov).

Lidar Penetration Depth Observations for Constraining Cloud Longwave Feedbacks

NASA Astrophysics Data System (ADS)

Vaillant de Guelis, T.; Chepfer, H.; Noel, V.; Guzman, R.; Winker, D. M.; Kay, J. E.; Bonazzola, M.

2017-12-01

Satellite-borne active remote sensing Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations [CALIPSO; Winker et al., 2010] and CloudSat [Stephens et al., 2002] provide direct measurements of the cloud vertical distribution, with a very high vertical resolution. The penetration depth of the laser of the lidar Z_Opaque is directly linked to the LongWave (LW) Cloud Radiative Effect (CRE) at Top Of Atmosphere (TOA) [Vaillant de Guélis et al., in review]. In addition, this measurement is extremely stable in time making it an excellent observational candidate to verify and constrain the cloud LW feedback mechanism [Chepfer et al., 2014]. In this work, we present a method to decompose the variations of the LW CRE at TOA using cloud properties observed by lidar [GOCCP v3.0; Guzman et al., 2017]. We decompose these variations into contributions due to changes in five cloud properties: opaque cloud cover, opaque cloud altitude, thin cloud cover, thin cloud altitude, and thin cloud emissivity [Vaillant de Guélis et al., in review]. We apply this method, in the real world, to the CRE variations of CALIPSO 2008-2015 record, and, in climate model, to LMDZ6 and CESM simulations of the CRE variations of 2008-2015 period and of the CRE difference between a warm climate and the current climate. In climate model simulations, the same cloud properties as those observed by CALIOP are extracted from the CFMIP Observation Simulator Package (COSP) [Bodas-Salcedo et al., 2011] lidar simulator [Chepfer et al., 2008], which mimics the observations that would be performed by the lidar on board CALIPSO satellite. This method, when applied on multi-model simulations of current and future climate, could reveal the altitude of cloud opacity level observed by lidar as a strong constrain for cloud LW feedback, since the altitude feedback mechanism is physically explainable and the altitude of cloud opacity accurately observed by lidar.

Use of ERTS imagery in air pollution and marine biology studies, tasks 1 through 3

NASA Technical Reports Server (NTRS)

Copeland, G. E.; Ludwick, J. C.; Marshall, H. G. (Principal Investigator); Bandy, A. R.; Fleischer, P.; Hanna, W. J.; Gosink, T. A.; Bowker, D. W.

1972-01-01

There are no author-identified significant results in this report. The general suitability of ERTS imagery in detecting ground originated air pollution has proved to be excellent. The quality and resolution exceeded expectations and has permitted in some instances location of point sources to within a thousand feet. Suitable techniques have not yet been developed for determining or measuring area and line sources of air pollution. A major problem has been cloud cover that has persisted over the area of primary interest, the Chesapeake Bay. Work has been completed on mounting the shipboard transmissometer which will be used for investigations to relate the chlorophyll and suspended sediment content in the waters of the Lower Chesapeake Bay to ERTS-1 imagery. Water sampling, plankton analysis, and preparations for sea collection of water truth along the eastern continental shelf of the U.S. have been completed for use in comparisons with ERTS-1 data.

The role of mountain precipitation as a drought buffer in Puerto Rico: Assessing natural systems' resilience to change

NASA Astrophysics Data System (ADS)

Scholl, M. A.; Clark, K. E.; Van Beusekom, A.; Shanley, J. B.; Torres-Sanchez, A.; Murphy, S. F.; Gonzalez, G.

2017-12-01

Like many island and coastal areas, the Luquillo Mountains of Puerto Rico receive orographic precipitation (rain and cloud water), maintaining headwater streamflow and allowing diverse forest ecosystems to thrive. Although rainfall from regional-scale convective systems is greater in volume, multiple lines of evidence (stable isotope tracers; precipitation amount, frequency, and intensity; cloud immersion; regional cloud dynamics; weather analysis) show that trade-wind orographic precipitation contributes significantly to streamflow, soil water, and shallow groundwater. Ceilometer data and time-lapse photography of cloud-immersed conditions at the mountain indicated a seasonally invariant, sustained overnight regime of cloud water precipitation, in addition to the abundant rainfall in the mountains. Rising ocean temperatures and a warming tropical climate lead to questions about persistence of the trade-wind associated orographic precipitation and the resilience of similar mountain ecosystems to change. Projections for Caribbean climate change include amplification of trade winds; less frequent, more intense large convective systems; and a warming ocean. These may have opposing effects on mountain precipitation, increasing uncertainty about processes that mitigate drought. Field studies provide insights regarding these questions. Ceilometer and satellite observations showed cloud base is higher over the mountains than in the surrounding Caribbean region; with the trade-wind inversion cap, further rise in cloud base may produce shallower clouds and reduced precipitation. We analyzed the February-October 2015 drought, characterized by strong El Niño conditions, an absence of tropical storm systems, and reduced convection in easterly waves. Combined δ2H, δ18O and d-excess signatures of streamflow indicated precipitation was derived from shallow convective systems, trade-wind showers and cloud water. During severe drought on the island, streamflow-sustaining rainfall at the mountain station at 640 m persisted, albeit with 19% lower frequency and 52% fewer large (>10 mm) rain events than the 20-year average. Clearly, resilience of the mountain forest ecosystem and of streamflow to drought periods depends on orographic precipitation.

Impact of Arctic sea-ice retreat on the recent change in cloud-base height during autumn

NASA Astrophysics Data System (ADS)

Sato, K.; Inoue, J.; Kodama, Y.; Overland, J. E.

2012-12-01

Cloud-base observations over the ice-free Chukchi and Beaufort Seas in autumn were conducted using a shipboard ceilometer and radiosondes during the 1999-2010 cruises of the Japanese R/V Mirai. To understand the recent change in cloud base height over the Arctic Ocean, these cloud-base height data were compared with the observation data under ice-covered situation during SHEBA (the Surface Heat Budget of the Arctic Ocean project in 1998). Our ice-free results showed a 30 % decrease (increase) in the frequency of low clouds with a ceiling below (above) 500 m. Temperature profiles revealed that the boundary layer was well developed over the ice-free ocean in the 2000s, whereas a stable layer dominated during the ice-covered period in 1998. The change in surface boundary conditions likely resulted in the difference in cloud-base height, although it had little impact on air temperatures in the mid- and upper troposphere. Data from the 2010 R/V Mirai cruise were investigated in detail in terms of air-sea temperature difference. This suggests that stratus cloud over the sea ice has been replaced as stratocumulus clouds with low cloud fraction due to the decrease in static stability induced by the sea-ice retreat. The relationship between cloud-base height and air-sea temperature difference (SST-Ts) was analyzed in detail using special section data during 2010 cruise data. Stratus clouds near the sea surface were predominant under a warm advection situation, whereas stratocumulus clouds with a cloud-free layer were significant under a cold advection situation. The threshold temperature difference between sea surface and air temperatures for distinguishing the dominant cloud types was 3 K. Anomalous upward turbulent heat fluxes associated with the sea-ice retreat have likely contributed to warming of the lower troposphere. Frequency distribution of the cloud-base height (km) detected by a ceilometer/lidar (black bars) and radiosondes (gray bars), and profiles of potential temperature (K) for (a) ice-free cases (R/V Mirai during September) and (b) ice-covered case (SHEBA during September 1998). (c) Vertical profiles of air temperature from 1000 hPa to 150 hPa (solid lines: observations north of 75°N, and dashed lines: the ERA-Interim reanalysis over 75-82.5°N, 150-170°W). Green, blue, and red lines denote profiles derived from observations by NP stations (the 1980s), SHEBA (1998), and the R/V Mirai (the 2000s), respectively. (d) Temperature trend calculated by the ERA-Interim reanalysis over the area.

Time-cumulated visible and infrared histograms used as descriptor of cloud cover

NASA Technical Reports Server (NTRS)

Seze, G.; Rossow, W.

1987-01-01

To study the statistical behavior of clouds for different climate regimes, the spatial and temporal stability of VIS-IR bidimensional histograms is tested. Also, the effect of data sampling and averaging on the histogram shapes is considered; in particular the sampling strategy used by the International Satellite Cloud Climatology Project is tested.

Snapshots of Titan North Polar Cloud

NASA Image and Video Library

2012-02-23

This series of false-color images obtained by NASA Cassini spacecraft shows the dissolving cloud cover over the north pole of Saturn moon Titan, allowing scientists to see the underlying northern lakes and seas, including Kraken Mare.

Stratospheric Polar Freezing Belt Causes Denitrification

NASA Technical Reports Server (NTRS)

Tabazadeh, A.; Jensen, E. J.; Toon, O. B.; Drdla, K.; Schoeberl, M. R.; Gore, Warren J. (Technical Monitor)

2001-01-01

Trajectory cloud model calculations are presented to show that homogeneous freezing of nitric acid hydrates can produce a polar freezing belt in both hemispheres that can cause denitrification. While hydrate cloud microphysical properties are similar over both poles, the shorter persistence of clouds in the Arctic prevents the depth of the denitrified layers from growing beyond a few kilometers. The 1999-2000 Arctic winter is unique in showing a distinct denitrification profile with a depth of approx. 4.5 km that is nearly half as deep as that computed for a typical Antarctic winter.

Annual boom-bust cycles of polar phytoplankton biomass revealed by space-based lidar

NASA Astrophysics Data System (ADS)

Behrenfeld, Michael J.; Hu, Yongxiang; O'Malley, Robert T.; Boss, Emmanuel S.; Hostetler, Chris A.; Siegel, David A.; Sarmiento, Jorge L.; Schulien, Jennifer; Hair, Johnathan W.; Lu, Xiaomei; Rodier, Sharon; Scarino, Amy Jo

2017-02-01

Polar plankton communities are among the most productive, seasonally dynamic and rapidly changing ecosystems in the global ocean. However, persistent cloud cover, periods of constant night and prevailing low solar elevations in polar regions severely limit traditional passive satellite ocean colour measurements and leave vast areas unobserved for many consecutive months each year. Consequently, our understanding of the annual cycles of polar plankton and their interannual variations is incomplete. Here we use space-borne lidar observations to overcome the limitations of historical passive sensors and report a decade of uninterrupted polar phytoplankton biomass cycles. We find that polar phytoplankton dynamics are categorized by `boom-bust' cycles resulting from slight imbalances in plankton predator-prey equilibria. The observed seasonal-to-interannual variations in biomass are predicted by mathematically modelled rates of change in phytoplankton division. Furthermore, we find that changes in ice cover dominated variability in Antarctic phytoplankton stocks over the past decade, whereas ecological processes were the predominant drivers of change in the Arctic. We conclude that subtle and environmentally driven imbalances in polar food webs underlie annual phytoplankton boom-bust cycles, which vary interannually at each pole.

ASTER cloud coverage reassessment using MODIS cloud mask products

NASA Astrophysics Data System (ADS)

Tonooka, Hideyuki; Omagari, Kunjuro; Yamamoto, Hirokazu; Tachikawa, Tetsushi; Fujita, Masaru; Paitaer, Zaoreguli

2010-10-01

In the Advanced Spaceborne Thermal Emission and Reflection radiometer (ASTER) Project, two kinds of algorithms are used for cloud assessment in Level-1 processing. The first algorithm based on the LANDSAT-5 TM Automatic Cloud Cover Assessment (ACCA) algorithm is used for a part of daytime scenes observed with only VNIR bands and all nighttime scenes, and the second algorithm based on the LANDSAT-7 ETM+ ACCA algorithm is used for most of daytime scenes observed with all spectral bands. However, the first algorithm does not work well for lack of some spectral bands sensitive to cloud detection, and the two algorithms have been less accurate over snow/ice covered areas since April 2008 when the SWIR subsystem developed troubles. In addition, they perform less well for some combinations of surface type and sun elevation angle. We, therefore, have developed the ASTER cloud coverage reassessment system using MODIS cloud mask (MOD35) products, and have reassessed cloud coverage for all ASTER archived scenes (>1.7 million scenes). All of the new cloud coverage data are included in Image Management System (IMS) databases of the ASTER Ground Data System (GDS) and NASA's Land Process Data Active Archive Center (LP DAAC) and used for ASTER product search by users, and cloud mask images are distributed to users through Internet. Daily upcoming scenes (about 400 scenes per day) are reassessed and inserted into the IMS databases in 5 to 7 days after each scene observation date. Some validation studies for the new cloud coverage data and some mission-related analyses using those data are also demonstrated in the present paper.

Absorption of Solar Radiation by Clouds: An Overview

NASA Technical Reports Server (NTRS)

Tsay, Si-Chee; Einaudi, Franco (Technical Monitor)

2000-01-01

This talk provides an overview of the subject of absorption of solar radiation by clouds in the earth's atmosphere. The paper summarizes the available evidence which points to disagreements between theoretical and observed values of cloud absorption (and reflections). The importance of these discrepancies, particularly to remote sensing of clouds as well as to studies of cloud physics and earth radiation budgets, is emphasized. Existing cloud absorption and reflection measurements are reviewed and the persistent differences that exist between calculated and measured near-infrared cloud albedos are highlighted. Various explanations for these reflection and absorption discrepancies are discussed under two separate paths: a theoretician's approach and an experimentalist's approach. Examples for the former approach include model accuracy tests, large-droplet hypothesis, excess absorbing aerosol, enhanced water vapor continuum absorption, and effects of cloud inhomogeneity. The latter approach focuses on discussions of instrumental device, calibration, operational strategy, and signal/noise separation. A recommendation for future activities on this subject will be given.

Model-Observation Comparisons of Biomass Burning Smoke and Clouds Over the Southeast Atlantic Ocean

NASA Astrophysics Data System (ADS)

Doherty, S. J.; Saide, P.; Zuidema, P.; Shinozuka, Y.; daSilva, A.; McFarquhar, G. M.; Pfister, L.; Carmichael, G. R.; Ferrada, G. A.; Howell, S. G.; Freitag, S.; Dobracki, A. N.; Smirnow, N.; Longo, K.; LeBlanc, S. E.; Adebiyi, A. A.; Podolske, J. R.; Small Griswold, J. D.; Hekkila, A.; Ueyama, R.; Wood, R.; Redemann, J.

2017-12-01

From August through October, in the SE Atlantic a plume of biomass burning smoke from central Africa overlays a relatively persistent stratocumulus-to-cumulus cloud deck. These smoke aerosols are believed to have significant climate forcing via aerosol-radiation and aerosol-cloud interactions, though both the magnitude and sign of this forcing is highly uncertain. This is due to large model spread in simulated aerosol and cloud properties and, until now, a sparsity of observations to constrain the models. Here we will present a comparison of both aerosol and cloud properties over the region using data from the first deployment of the NASA ORACLES (ObseRvations of Aerosols above CLouds and their intEractionS) field experiment (August-September 2016). We examine both horizontal and geographic variations in a range of aerosol and cloud properties and their position relative to each other, since the degree to which aerosols and clouds coincide both horizontally and vertically is perhaps the greatest source of uncertainty in their climate forcing.

Stereoscopic, thermal, and true deep cumulus cloud top heights

NASA Astrophysics Data System (ADS)

Llewellyn-Jones, D. T.; Corlett, G. K.; Lawrence, S. P.; Remedios, J. J.; Sherwood, S. C.; Chae, J.; Minnis, P.; McGill, M.

2004-05-01

We compare cloud-top height estimates from several sensors: thermal tops from GOES-8 and MODIS, stereoscopic tops from MISR, and directly measured heights from the Goddard Cloud Physics Lidar on board the ER-2, all collected during the CRYSTAL-FACE field campaign. Comparisons reveal a persistent 1-2 km underestimation of cloud-top heights by thermal imagery, even when the finite optical extinctions near cloud top and in thin overlying cirrus are taken into account. The most severe underestimates occur for the tallest clouds. The MISR "best-sinds" and lidar estimates disagree in very similar ways with thermally estimated tops, which we take as evidence of excellent performance by MISR. Encouraged by this, we use MISR to examine variations in cloud penetration and thermal top height errors in several locations of tropical deep convection over multiple seasons. The goals of this are, first, to learn how cloud penetration depends on the near-tropopause environment; and second, to gain further insight into the mysterious underestimation of tops by thermal imagery.

Comparisons of cloud cover evaluated from LANDSAT imagery and meteorological stations across the British Isles

NASA Technical Reports Server (NTRS)

Barrett, E. C. (Principal Investigator); Grant, C. K.

1976-01-01

The author has identified the following significant results. This stage of the study has confirmed the initial supposition that LANDSAT data could be analyzed to provide useful data on cloud amount, and that useful light would be thrown thereby on the performance of the ground observer of this aspect of the state of the sky. This study, in comparison with previous studies of a similar nature using data from meteorological satellites, has benefited greatly from the much higher resolution data provided by LANDSAT. This has permitted consideration of not only the overall performance of the surface observer in estimating total cloud cover, but also his performance under different sky conditions.

E4 True and false color hot spot mosaic

NASA Technical Reports Server (NTRS)

1997-01-01

True and false color views of Jupiter from NASA's Galileo spacecraft show an equatorial 'hotspot' on Jupiter. These images cover an area 34,000 kilometers by 11,000 kilometers (about 21,100 by 6,800 miles). The top mosaic combines the violet and near infrared continuum filter images to create an image similar to how Jupiter would appear to human eyes. Differences in coloration are due to the composition and abundances of trace chemicals in Jupiter's atmosphere. The bottom mosaic uses Galileo's three near-infrared wavelengths displayed in red, green, and blue) to show variations in cloud height and thickness. Bluish clouds are high and thin, reddish clouds are low, and white clouds are high and thick. The dark blue hotspot in the center is a hole in the deep cloud with an overlying thin haze. The light blue region to the left is covered by a very high haze layer. The multicolored region to the right has overlapping cloud layers of different heights. Galileo is the first spacecraft to distinguish cloud layers on Jupiter.

North is at the top. The mosaic covers latitudes 1 to 10 degrees and is centered at longitude 336 degrees west. The smallest resolved features are tens of kilometers in size. These images were taken on December 17, 1996, at a range of 1.5 million kilometers (about 930,000 miles) by the Solid State Imaging camera system aboard Galileo. The Jet Propulsion Laboratory, Pasadena, CA manages the mission for NASA's Office of Space Science, Washington, DC.

This image and other images and data received from Galileo are posted on the World Wide Web, on the Galileo mission home page at: http://galileo.jpl.nasa.gov. Background information and educational context for the images can be found at: http:/ /www.jpl.nasa.gov/galileo/sepo.

Florida Everglades and Keys, USA

NASA Technical Reports Server (NTRS)

1991-01-01

Though much of southern Florida is covered by clouds, the Florida Everglades and Keys (25.0N, 82.0W) remain relatively clear in this nearly vertical view. The view covers the Gulf of Mexico port city of Ft. Myers, and Lake Okeechobee, at the top of the scene, in the north, The Everglades, in the center and the entire Florida Key Chain at the bottom. Even with the many popcorn clouds, ground detail and the city of Miami is easily discerned.

Validation of Local-Cloud Model Outputs With the GOES Satellite Imagery

NASA Astrophysics Data System (ADS)

Malek, E.

2005-05-01

Clouds (visible aggregations of minute droplets of water or tiny crystals of ice suspended in the air) affect the radiation budget of our planet by reflecting, absorbing and scattering solar radiation, and the re-emission of terrestrial radiation. They affect the weather and climate by positive or negative feedbacks. Many researchers have worked on the parameterization of clouds and their effects on the radiation budget. There is little information about ground-based approaches for continuous evaluation of cloud, such as cloud base height, cloud base temperature, and cloud coverage, at local and regional scales. This present article deals with the development of an algorithm for continuous (day and night) evaluation of cloud base temperature, cloud base height and percent of skies covered by cloud at local scale throughout the year. The Vaisala model CT-12K laser beam ceilometer is used at the Automated Surface Observing Systems (ASOS) to measure the cloud base height and report the sky conditions on an hourly basis or at shorter intervals. This laser ceilometer is a fixed-type whose transmitter and receiver point straight up at the cloud (if any) base. It is unable to measure clouds that are not above the sensor. To report cloudiness at the local scale, many of these type of ceilometers are needed. This is not a perfect method for cloud measurement. A single cloud hanging overhead the sensor will cause overcast readings, whereas, a hole in the clouds could cause a clear reading to be reported. To overcome this problem, we have set up a ventilated radiation station at Logan-Cache airport, Utah, U.S.A., since 1995, which is equipped with one of the above-mentioned ceilometers. This radiation station (composed of pyranometers, pyrgeometers and net radiometer) provides continuous measurements of incoming and outgoing shortwave and longwave radiation and the net radiation throughout the year. We have also measured the surface temperature and pressure, the 2-m air temperature and humidity, precipitation, and the 3-m wind and direction at this station. Having the air temperature, moisture, and the measured cloudless incoming longwave (atmospheric) radiation during 1999 through 2004, based upon the ASOS and the algorithm data, we found the appropriate formula (among four reported approaches) for computation of the cloudless-skies atmospheric emissivity. Considering the additional longwave radiation captured by the facing-up pyrgeometer during the cloudy skies, coming from the cloud in the wave band which the gaseous emission lacks (from 8-13 ìm), we developed an algorithm which provides the continuous 20-min cloud information (cloud base height, cloud base temperature, and percent of skies covered by cloud) over the Cache Valley during day and night throughout the year. The comparisons between the ASOS and the algorithm data during the period of 8-12 June, 2004 are reported in this article. The proposed algorithm is a promising approach for evaluation of the cloud base temperature, cloud base height, and percent of skies covered by cloud at the local scale throughout the year. It also reports the comparison between model outputs and GOES 10 satellite images.

Low Clouds and Cosmic Rays: Possible Reasons for Correlation Changes

NASA Astrophysics Data System (ADS)

Veretenenko, S. V.; Ogurtsov, M. G.

2015-03-01

In this work we investigated the nature of correlations between low cloud cover anomalies (LCA) and galactic cosmic ray (GCR) variations detected on the decadal time scale, as well as possible reasons for the violation of these correlations in the early 2000s. It was shown that the link between cloud cover at middle latitudes and GCR fluxes is not direct, but it is realized through GCR influence on the development of extratropical baric systems (cyclones and troughs) which form cloud field. As the sign of GCR effects on the troposphere dynamics seems to depend on the strength of the stratospheric polar vortex, a possible reason for the violation of a positive correlation between LCA and GCR fluxes in the early 2000s may be the change of the vortex state which resulted in the reversal of GCR effects on extratropical cyclone development.

Shallow convection on day 261 of GATE - Mesoscale arcs

NASA Technical Reports Server (NTRS)

Warner, C.; Simpson, J.; Martin, D. W.; Suchman, D.; Mosher, F. R.; Reinking, R. F.

1979-01-01

Cloudy convection in the moist layer of a cloud cluster growing in the GATE ship array is examined. Analyses suggest that the moist layer was dominated by features of horizontal dimension roughly 40 km and lifetime roughly 2 h, with arc patterns triggered by dense downdraft air accompanying rainfall, and composed of many small cumulus clouds. Aircraft recorded data on thermodynamic quantities and winds, indicating that the arcs persisted as mesoscale circulations driven by the release of latent heat in the clouds, rather than being driven by the original density current at the surface. It is also suggested that the mesoscale cloud patterns of the moist layer play a primary role in heat transfer upward within this layer, and contribute to the forcing of showering midtropospheric clouds.

Studies in the use of cloud type statistics in mission simulation

NASA Technical Reports Server (NTRS)

Fowler, M. G.; Willand, J. H.; Chang, D. T.; Cogan, J. L.

1974-01-01

A study to further improve NASA's global cloud statistics for mission simulation is reported. Regional homogeneity in cloud types was examined; most of the original region boundaries defined for cloud cover amount in previous studies were supported by the statistics on cloud types and the number of cloud layers. Conditionality in cloud statistics was also examined with special emphasis on temporal and spatial dependencies, and cloud type interdependence. Temporal conditionality was found up to 12 hours, and spatial conditionality up to 200 miles; the diurnal cycle in convective cloudiness was clearly evident. As expected, the joint occurrence of different cloud types reflected the dynamic processes which form the clouds. Other phases of the study improved the cloud type statistics for several region and proposed a mission simulation scheme combining the 4-dimensional atmospheric model, sponsored by MSFC, with the global cloud model.

Cloud Simulations in Response to Turbulence Parameterizations in the GISS Model E GCM

NASA Technical Reports Server (NTRS)

Yao, Mao-Sung; Cheng, Ye

2013-01-01

The response of cloud simulations to turbulence parameterizations is studied systematically using the GISS general circulation model (GCM) E2 employed in the Intergovernmental Panel on Climate Change's (IPCC) Fifth Assessment Report (AR5).Without the turbulence parameterization, the relative humidity (RH) and the low cloud cover peak unrealistically close to the surface; with the dry convection or with only the local turbulence parameterization, these two quantities improve their vertical structures, but the vertical transport of water vapor is still weak in the planetary boundary layers (PBLs); with both local and nonlocal turbulence parameterizations, the RH and low cloud cover have better vertical structures in all latitudes due to more significant vertical transport of water vapor in the PBL. The study also compares the cloud and radiation climatologies obtained from an experiment using a newer version of turbulence parameterization being developed at GISS with those obtained from the AR5 version. This newer scheme differs from the AR5 version in computing nonlocal transports, turbulent length scale, and PBL height and shows significant improvements in cloud and radiation simulations, especially over the subtropical eastern oceans and the southern oceans. The diagnosed PBL heights appear to correlate well with the low cloud distribution over oceans. This suggests that a cloud-producing scheme needs to be constructed in a framework that also takes the turbulence into consideration.

A Study of the Role of Clouds in the Relationship Between Land Use/Land Cover and the Climate and Air Quality of the Atlanta Area

NASA Technical Reports Server (NTRS)

Kidder, Stanley Q.; Hafner, Jan

1997-01-01

The goal of Project ATLANTA is to derive a better scientific understanding of how land cover changes associated with urbanization affect local and regional climate and air quality. Clouds play a significant role in this relationship. Using GOES images, we found that in a 63-day period (5 July-5 September 1996) there were zero days which were clear for the entire daylight period. Days which are cloud-free in the morning become partly cloudy with small cumulus clouds in the afternoon in response to solar heating. This result casts doubt on the applicability of California-style air quality models which run in perpetual clear skies. Days which are clear in the morning have higher ozone than those which are cloudy in the morning. Using the RAMS model, we found that urbanization increases the skin surface temperature by about 1.0-1.5 C on average under cloudy conditions, with an extreme of +3.5 C. Clouds cool the surface due to their shading effect by 1.5-2.0 C on average, with an extreme of 5.0 C. RAMS simulates well the building stage of the cumulus cloud field, but does poorly in the decaying phase. Next year's work: doing a detailed cloud climatology and developing improved RAMS cloud simulations.

Spatial and Temporal Inter-Relationships Between Anomalies of Temperature, Moisture, Cloud Cover, and OLR as Observed by AIRS/AMSU on Aqua

NASA Technical Reports Server (NTRS)

Susskind, Joel

2008-01-01

AIRS/AMSU is the advanced IR/MW atmospheric sounding system launched on EOS Aqua in May 2002. Products derived from AIRS/AMSU include surface skin temperature and atmospheric temperature profiles; atmospheric humidity profiles, percent cloud cover and cloud top pressure, and OLR. Near real time products, stating with September 2002, have been derived from AIRS/AMSU using the AIRS Science Team Version 5 retrieval algorithm. Results in this paper included products through April 2008. The time period studied is marked by a substantial warming trend of Northern Hemisphere Extropical land surface skin temperatures, as well as pronounced El Nino - La Nina episodes. These both influence the spatial and temporal anomaly patterns of atmospheric temperature and moisture profiles, as well as of cloud cover and Clear Sky and All Sky OLR The relationships between temporal and spatial anomalies of these parameters over this time period, as determined from AIRS/AMSU observations, are shown below, with particular emphasis on which contribute significantly to OLR anomalies in each of the tropics and extra-tropics. The ability to match this data represents a good test of a model's response to El Nino.

Man-Computer Interactive Data Access System (McIDAS). Continued development of McIDAS and operation in the GARP Atlantic tropical experiment

NASA Technical Reports Server (NTRS)

Suomi, V. E.

1975-01-01

The complete output of the Synchronous Meteorological Satellite was recorded on one inch magnetic tape. A quality control subsystem tests cloud track vectors against four sets of criteria: (1) rejection if best match occurs on correlation boundary; (2) rejection if major correlation peak is not distinct and significantly greater than secondary peak; (3) rejection if correlation is not persistent; and (4) rejection if acceleration is too great. A cloud height program determines cloud optical thickness from visible data and computer infrared emissivity. From infrared data and temperature profile, cloud height is determined. A functional description and electronic schematics of equipment are given.

Light availability controls ecosystem fluxes in native and non-native tropical montane wet forests in Hawai`i

NASA Astrophysics Data System (ADS)

Giambelluca, T. W.; Mudd, R. G.; Huang, M.; Nullet, M.; Asner, G. P.; Martin, R.; Ostertag, R.; Miyazawa, Y.; Litton, C. M.

2016-12-01

Uncertainty about the local and regional effects of global climate warming on terrestrial ecosystems and their ability to produce ecosystem goods and services is a serious constraint for land-based natural resource managers. In Hawai`i and other Pacific Islands, this issue is complicated by the presence of numerous and widespread non-native invasive species, including invasive trees. As warming continues and other climate variables change in response to temperature increases, how will native- and non-native-dominated ecosystems respond? To address this question, eddy covariance flux towers were established and operated for approximately a decade over native forest and at a site invaded by a non-native tree. Flux data were analyzed to determine the sensitivity of carbon exchange rates to fluctuations in ambient CO2 concentration, temperature (T), humidity, photosynthetically active radiation (PAR), and soil moisture (SM). At both sites, gross primary production (GPP) is strongly controlled by PAR and to a lesser extent by T. Ecosystem respiration (Re) responds to T and SM at both sites, as expected. Net ecosystem carbon exchange (NEE) is predominantly controlled by PAR at both sites. Higher temperature is associated with higher rates of photosynthesis and greater Re, thereby canceling the net effect of temperature on carbon exchange. Hence, no significant effect of temperature on NEE was found at either site. These results suggest that the direct effects of future warming will be small in relation to the effects of any changes in cloud cover that affect incident solar radiation. Cloud cover in Hawai`i could be affected by projected increases in atmospheric stability (reduced cloud cover) and increases in humidity (increased cloud cover). Light response (GPP sensitivity to PAR) was found to be significantly greater at the non-native site, suggesting that a future decrease in cloud cover would favor the non-native ecosystem, while increased cloudiness would cause a greater reduction in carbon uptake in the non-native forest.

Understanding Coupling of Global and Diffuse Solar Radiation with Climatic Variability

NASA Astrophysics Data System (ADS)

Hamdan, Lubna

Global solar radiation data is very important for wide variety of applications and scientific studies. However, this data is not readily available because of the cost of measuring equipment and the tedious maintenance and calibration requirements. Wide variety of models have been introduced by researchers to estimate and/or predict the global solar radiations and its components (direct and diffuse radiation) using other readily obtainable atmospheric parameters. The goal of this research is to understand the coupling of global and diffuse solar radiation with climatic variability, by investigating the relationships between these radiations and atmospheric parameters. For this purpose, we applied multilinear regression analysis on the data of National Solar Radiation Database 1991--2010 Update. The analysis showed that the main atmospheric parameters that affect the amount of global radiation received on earth's surface are cloud cover and relative humidity. Global radiation correlates negatively with both variables. Linear models are excellent approximations for the relationship between atmospheric parameters and global radiation. A linear model with the predictors total cloud cover, relative humidity, and extraterrestrial radiation is able to explain around 98% of the variability in global radiation. For diffuse radiation, the analysis showed that the main atmospheric parameters that affect the amount received on earth's surface are cloud cover and aerosol optical depth. Diffuse radiation correlates positively with both variables. Linear models are very good approximations for the relationship between atmospheric parameters and diffuse radiation. A linear model with the predictors total cloud cover, aerosol optical depth, and extraterrestrial radiation is able to explain around 91% of the variability in diffuse radiation. Prediction analysis showed that the linear models we fitted were able to predict diffuse radiation with efficiency of test adjusted R2 values equal to 0.93, using the data of total cloud cover, aerosol optical depth, relative humidity and extraterrestrial radiation. However, for prediction purposes, using nonlinear terms or nonlinear models might enhance the prediction of diffuse radiation.

A Blended Global Snow Product using Visible, Passive Microwave and Scatterometer Satellite Data

NASA Technical Reports Server (NTRS)

Foster, James L.; Hall, Dorothy K.; Eylander, John B.; Riggs, George A.; Nghiem, Son V.; Tedesco, Marco; Kim, Edward; Montesano, Paul M.; Kelly, Richard E. J.; Casey, Kimberly A.;

MODIS-based Snow Cover Variability of the Upper River Grande Basin

NASA Astrophysics Data System (ADS)

Yu, B.; Wang, X.; Xie, H.

2007-12-01

Snow cover and its spring melting in the Upper Rio Grande Basin provides a major water source for the Upper to Middle Rio Grande valley and Elephant Butte Reservoir. Thus understanding the snowpack and its variability in the context of global climate change is crucial to the sustainable water resources for the region. MODIS instruments (on Terra and Aqua) have provided time series of snow cover products since 2000, but suffering with cloud contaminations. In this study, we evaluated four newly developed cloudless snow cover products (less than 10%) and four standard products: daily (MOD10A1, MYD10A1) and 8-day (MOD10A2, MYD10A2), in comparison with in situ Snowpack Telemetry (SNOTEL) measurements for the hydrological year 2003-2004. The four new products are daily composite of Terra and Aqua (MODMYD10DC), multi-day composites of Terra (MOD10MC), Aqua (MYD10MC), and Terra and Aqua (MODMYD10MC). The standard daily and 8-day products can classify land correctly, but had fairly low accuracy in snow classification due to cloud contamination (a average of 39.4% for Terra and 45% for Aqua in the year 2003-2004). All the new multi-day composite products tended to have high accuracy in classifying both snow and land (over 90%), as the cloud cover has been reduced to less than 10% (~5% for the year) under the new algorithm . This result is consistent with a previous study in the Xinjiang area, China (Wang and Xie, 2007). Therefore, MOD10MC (before the Aqua data available) and MODMYD10MC products are used to get the mean snow cover of the Upper Rio Grande Basin from 2000 to 2007. The snow depletion curve derived from the new cloud-free snow cover map will be used to examine its effect on stream discharge.

The Rossby Centre Regional Atmospheric Climate Model part II: application to the Arctic climate.

PubMed

Jones, Colin G; Wyser, Klaus; Ullerstig, Anders; Willén, Ulrika

2004-06-01

The Rossby Centre regional climate model (RCA2) has been integrated over the Arctic Ocean as part of the international ARCMIP project. Results have been compared to observations derived from the SHEBA data set. The standard RCA2 model overpredicts cloud cover and downwelling longwave radiation, during the Arctic winter. This error was improved by introducing a new cloud parameterization, which significantly improves the annual cycle of cloud cover. Compensating biases between clear sky downwelling longwave radiation and longwave radiation emitted from cloud base were identified. Modifications have been introduced to the model radiation scheme that more accurately treat solar radiation interaction with ice crystals. This leads to a more realistic representation of cloud-solar radiation interaction. The clear sky portion of the model radiation code transmits too much solar radiation through the atmosphere, producing a positive bias at the top of the frequent boundary layer clouds. A realistic treatment of the temporally evolving albedo, of both sea-ice and snow, appears crucial for an accurate simulation of the net surface energy budget. Likewise, inclusion of a prognostic snow-surface temperature seems necessary, to accurately simulate near-surface thermodynamic processes in the Arctic.

A Jovian Hotspot in True and False Colors (Time set 3)

NASA Technical Reports Server (NTRS)

1997-01-01

True and false color views of an equatorial 'hotspot' on Jupiter. These images cover an area 34,000 kilometers by 11,000 kilometers. The top mosaic combines the violet (410 nanometers or nm) and near-infrared continuum (756 nm) filter images to create an image similar to how Jupiter would appear to human eyes. Differences in coloration are due to the composition and abundances of trace chemicals in Jupiter's atmosphere. The bottom mosaic uses Galileo's three near-infrared wavelengths (756 nm, 727 nm, and 889 nm displayed in red, green, and blue) to show variations in cloud height and thickness. Bluish clouds are high and thin, reddish clouds are low, and white clouds are high and thick. The dark blue hotspot in the center is a hole in the deep cloud with an overlying thin haze. The light blue region to the left is covered by a very high haze layer. The multicolored region to the right has overlapping cloud layers of different heights. Galileo is the first spacecraft to distinguish cloud layers on Jupiter.

North is at the top. The mosaics cover latitudes 1 to 10 degrees and are centered at longitude 336 degrees West. The planetary limb runs along the right edge of the image. Cloud patterns appear foreshortened as they approach the limb. The smallest resolved features are tens of kilometers in size. These images were taken on December 17, 1996, at a range of 1.5 million kilometers by the Solid State Imaging system aboard NASA's Galileo spacecraft.

The Jet Propulsion Laboratory, Pasadena, CA manages the mission for NASA's Office of Space Science, Washington, DC.

This image and other images and data received from Galileo are posted on the World Wide Web, on the Galileo mission home page at URL http://galileo.jpl.nasa.gov. Background information and educational context for the images can be found at URL http://www.jpl.nasa.gov/galileo/sepo

Dynamics of Venus' Southern hemisphere and South Polar Vortex from VIRTIS data obtained during the Venus Expres Mission

NASA Astrophysics Data System (ADS)

Hueso, R.; Garate-Lopez, I.; Sanchez-Lavega, A.

2011-12-01

The VIRTIS instrument onboard Venus Express observes Venus in two channels (visible and infrared) obtaining spectra and multi-wavelength images of the planet. The images have been used to trace the motions of the atmosphere at different layers of clouds [1-3]. We review the VIRTIS cloud image data and wind results obtained by different groups [1-3] and we present new results concerning the morphology and evolution of the South Polar Vortex at the upper and lower cloud levels with data covering the first 900 days of the mission. We present wind measurements of the South hemisphere obtained by cloud tracking individual cloud features and higher-resolution wind results of the polar region covering the evolution of the South polar vortex. The later were obtained by an image correlation algorithm run under human supervision to validate the data. We present day-side data of the upper clouds obtained at 380 and 980 nm sensitive to altitudes of 66-70 km, night-side data in the near infrared at 1.74 microns of the lower cloud (45-50 km) and day and night-side data obtained in the thermal infrared (wavelengths of 3.8 and 5.1 microns) which covers the dynamical evolution of Venus South Polar vortex at the cloud tops (66-70 km). We explore the different dynamics associated to the varying morphology of the vortex, its dynamical structure at different altitudes, the variability of the global wind data of the southern hemisphere and the interrelation of the polar vortex dynamics with the wind dynamics at subpolar and mid-latitudes. Acknowledgements: Work funded by Spanish MICIIN AYA2009-10701 with FEDER support and Grupos Gobierno Vasco IT-464-07. References [1] A. Sánchez-Lavega et al., Geophys. Res. Lett. 35, L13204, (2008). [2] D. Luz et al., Science, 332, 577-580 (2011). [3] R. Hueso, et al., Icarus doi:10.1016/j.icarus.2011.04.020 (2011)

A new NDVI measure that overcomes data sparsity in cloud-covered regions predicts annual variation in ground-based estimates of high arctic plant productivity

NASA Astrophysics Data System (ADS)

Rune Karlsen, Stein; Anderson, Helen B.; van der Wal, René; Bremset Hansen, Brage

2018-02-01

Efforts to estimate plant productivity using satellite data can be frustrated by the presence of cloud cover. We developed a new method to overcome this problem, focussing on the high-arctic archipelago of Svalbard where extensive cloud cover during the growing season can prevent plant productivity from being estimated over large areas. We used a field-based time-series (2000-2009) of live aboveground vascular plant biomass data and a recently processed cloud-free MODIS-Normalised Difference Vegetation Index (NDVI) data set (2000-2014) to estimate, on a pixel-by-pixel basis, the onset of plant growth. We then summed NDVI values from onset of spring to the average time of peak NDVI to give an estimate of annual plant productivity. This remotely sensed productivity measure was then compared, at two different spatial scales, with the peak plant biomass field data. At both the local scale, surrounding the field data site, and the larger regional scale, our NDVI measure was found to predict plant biomass (adjusted R 2 = 0.51 and 0.44, respectively). The commonly used ‘maximum NDVI’ plant productivity index showed no relationship with plant biomass, likely due to some years having very few cloud-free images available during the peak plant growing season. Thus, we propose this new summed NDVI from onset of spring to time of peak NDVI as a proxy of large-scale plant productivity for regions such as the Arctic where climatic conditions restrict the availability of cloud-free images.

Changes in Extratropical Storm Track Cloudiness 1983-2008: Observational Support for a Poleward Shift

NASA Technical Reports Server (NTRS)

Bender, Frida A-M.; Rananathan, V.; Tselioudis, G.

2012-01-01

Climate model simulations suggest that the extratropical storm tracks will shift poleward as a consequence of global warming. In this study the northern and southern hemisphere storm tracks over the Pacific and Atlantic ocean basins are studied using observational data, primarily from the International Satellite Cloud Climatology Project, ISCCP. Potential shifts in the storm tracks are examined using the observed cloud structures as proxies for cyclone activity. Different data analysis methods are employed, with the objective to address difficulties and uncertainties in using ISCCP data for regional trend analysis. In particular, three data filtering techniques are explored; excluding specific problematic regions from the analysis, regressing out a spurious viewing geometry effect, and excluding specific cloud types from the analysis. These adjustments all, to varying degree, moderate the cloud trends in the original data but leave the qualitative aspects of those trends largely unaffected. Therefore, our analysis suggests that ISCCP data can be used to interpret regional trends in cloudiness, provided that data and instrumental artefacts are recognized and accounted for. The variation in magnitude between trends emerging from application of different data correction methods, allows us to estimate possible ranges for the observational changes. It is found that the storm tracks, here represented by the extent of the midlatitude-centered band of maximum cloud cover over the studied ocean basins, experience a poleward shift as well as a narrowing over the 25 year period covered by ISCCP. The observed magnitudes of these effects are larger than in current generation climate models (CMIP3). The magnitude of the shift is particularly large in the northern hemisphere Atlantic. This is also the one of the four regions in which imperfect data primarily prevents us from drawing firm conclusions. The shifted path and reduced extent of the storm track cloudiness is accompanied by a regional reduction in total cloud cover. This decrease in cloudiness can primarily be ascribed to low level clouds, whereas the upper level cloud fraction actually increases, according to ISCCP. Independent satellite observations of radiative fluxes at the top of the atmosphere are consistent with the changes in total cloud cover. The shift in cloudiness is also supported by a shift in central position of the mid-troposphere meridional temperature gradient. We do not find support for aerosols playing a significant role in the satellite observed changes in cloudiness. The observed changes in storm track cloudiness can be related to local cloud-induced changes in radiative forcing, using ERBE and CERES radiative fluxes. The shortwave and the longwave components are found to act together, leading to a positive (warming) net radiative effect in response to the cloud changes in the storm track regions, indicative of positive cloud feedback. Among the CMIP3 models that simulate poleward shifts in all four storm track areas, all but one show decreasing cloud amount on a global mean scale in response to increased CO2 forcing, further consistent with positive cloud feedback. Models with low equilibrium climate sensitivity to a lesser extent than higher-sensitivity models simulate a poleward shift of the storm tracks.

Typhoon Sinlaku

Atmospheric Science Data Center

2013-04-16

... before the storm weakened as it moved inland. While the nature and formation of individual storm events is relatively well understood, ... clouds on climate is difficult to assess due to the variable nature of cloud cover at various altitudes. MISR's data products are designed ...

Complexity in Climatic Controls on Plant Species Distribution: Satellite Data Reveal Unique Climate for Giant Sequoia in the California Sierra Nevada

NASA Astrophysics Data System (ADS)

Waller, Eric Kindseth

A better understanding of the environmental controls on current plant species distribution is essential if the impacts of such diverse challenges as invasive species, changing fire regimes, and global climate change are to be predicted and important diversity conserved. Climate, soil, hydrology, various biotic factors fire, history, and chance can all play a role, but disentangling these factors is a daunting task. Increasingly sophisticated statistical models relying on existing distributions and mapped climatic variables, among others, have been developed to try to answer these questions. Any failure to explain pattern with existing mapped climatic variables is often taken as a referendum on climate as a whole, rather than on the limitations of the particular maps or models. Every location has a unique and constantly changing climate so that any distribution could be explained by some aspect of climate. Chapter 1 of this dissertation reviews some of the major flaws in species distribution modeling and addresses concerns that climate may therefore not be predictive of, or even relevant to, species distributions. Despite problems with climate-based models, climate and climate-derived variables still have substantial merit for explaining species distribution patterns. Additional generation of relevant climate variables and improvements in other climate and climate-derived variables are still needed to demonstrate this more effectively. Satellite data have a long history of being used for vegetation mapping and even species distribution mapping. They have great potential for being used for additional climatic information, and for improved mapping of other climate and climate-derived variables. Improving the characterization of cloud cover frequency with satellite data is one way in which the mapping of important climate and climate-derived variables can be improved. An important input to water balance models, solar radiation maps could be vastly improved with a better mapping of spatial and temporal patterns in cloud cover. Chapter 2 of this dissertation describes the generation of custom daily cloud cover maps from Advanced Very High Resolution Radiometer (AVHRR) satellite data from 1981-1999 at ~5 km resolution and Moderate Resolution Imagine Spectroradiomter (MODIS) satellite reflectance data at ~500 meter resolution for much of the western U.S., from 2000 to 2012. Intensive comparisons of reflectance spectra from a variety of cloud and snow-covered scenes from the southwestern United States allowed the generation of new rules for the classification of clouds and snow in both the AVHRR and MODIS data. The resulting products avoid many of the problems that plague other cloud mapping efforts, such as the tendency for snow cover and bright desert soils to be mapped as cloud. This consistency in classification across cover types is critically important for any distribution modeling of a plant species that might be dependent on cloud cover. In Chapter 3, monthly cloud frequencies derived from the daily classifications were used directly in species distribution models for giant sequoia and were found to be the strongest predictors of giant sequoia distribution. A high frequency of cloud cover, especially in the spring, differentiated the climate of the west slope of the southern Sierra Nevada, where giant sequoia are prolific, from central and northern parts of the range, where the tree is rare and generally absent. Other mapped cloud products, contaminated by confusion with high elevation snow, would likely not have found this important result. The result illustrates the importance of accuracy in mapping as well as the importance of previously overlooked aspects of climate for species distribution modeling. But it also raises new questions about why the clouds form where they do and whether they might be associated with other aspects of climate important to giant sequoia distribution. What are the exact climatic mechanisms governing the distribution? Detailed aspects of the local climate warranted more investigation. Chapter 4 investigates the climate associated with the frequent cloud formation over the western slopes of the southern Sierra Nevada: the "sequoia belt". This region is climatically distinct in a number of ways, all of which could be factors in influencing the distribution of giant sequoia and other species. Satellite and micrometeorological flux tower data reveal characteristics of the sequoia belt that were not evident with surface climate measurements and maps derived from them. Results have implications for species distributions everywhere, but especially in rugged mountains, where climates are complex and poorly mapped. Chapter 5 summarizes some of the main conclusions from the work and suggests directions for related future research. (Abstract shortened by UMI.).

Using regime analysis to identify the contribution of clouds to surface temperature errors in weather and climate models

DOE PAGES

Van Weverberg, Kwinten; Morcrette, Cyril J.; Ma, Hsi -Yen; ...

2015-06-17

Many global circulation models (GCMs) exhibit a persistent bias in the 2 m temperature over the midlatitude continents, present in short-range forecasts as well as long-term climate simulations. A number of hypotheses have been proposed, revolving around deficiencies in the soil–vegetation–atmosphere energy exchange, poorly resolved low-level boundary-layer clouds or misrepresentations of deep-convective storms. A common approach to evaluating model biases focuses on the model-mean state. However, this makes difficult an unambiguous interpretation of the origins of a bias, given that biases are the result of the superposition of impacts of clouds and land-surface deficiencies over multiple time steps. This articlemore » presents a new methodology to objectively detect the role of clouds in the creation of a surface warm bias. A unique feature of this study is its focus on temperature-error growth at the time-step level. It is shown that compositing the temperature-error growth by the coinciding bias in total downwelling radiation provides unambiguous evidence for the role that clouds play in the creation of the surface warm bias during certain portions of the day. Furthermore, the application of an objective cloud-regime classification allows for the detection of the specific cloud regimes that matter most for the creation of the bias. We applied this method to two state-of-the-art GCMs that exhibit a distinct warm bias over the Southern Great Plains of the USA. Our analysis highlights that, in one GCM, biases in deep-convective and low-level clouds contribute most to the temperature-error growth in the afternoon and evening respectively. In the second GCM, deep clouds persist too long in the evening, leading to a growth of the temperature bias. In conclusion, the reduction of the temperature bias in both models in the morning and the growth of the bias in the second GCM in the afternoon could not be assigned to a cloud issue, but are more likely caused by a land-surface deficiency.« less

Cloud cover determination in polar regions from satellite imagery

NASA Technical Reports Server (NTRS)

Barry, R. G.; Key, J.

1989-01-01

The objectives are to develop a suitable validation data set for evaluating the effectiveness of the International Satellite Cloud Climatology Project (ISCCP) algorithm for cloud retrieval in polar regions, to identify limitations of current procedures and to explore potential means to remedy them using textural classifiers, and to compare synoptic cloud data from model runs with observations. Toward the first goal, a polar data set consisting of visible, thermal, and passive microwave data was developed. The AVHRR and SMMR data were digitally merged to a polar stereographic projection with an effective pixel size of 5 sq km. With this data set, two unconventional methods of classifying the imagery for the analysis of polar clouds and surfaces were examined: one based on fuzzy sets theory and another based on a trained neural network. An algorithm for cloud detection was developed from an early test version of the ISCCP algorithm. This algorithm includes the identification of surface types with passive microwave, then temporal tests at each pixel location in the cloud detection phase. Cloud maps and clear sky radiance composites for 5 day periods are produced. Algorithm testing and validation was done with both actural AVHRR/SMMR data, and simulated imagery. From this point in the algorithm, groups of cloud pixels are examined for their spectral and textural characteristics, and a procedure is developed for the analysis of cloud patterns utilizing albedo, IR temperature, and texture. In a completion of earlier work, empirical analyses of arctic cloud cover were explored through manual interpretations of DMSP imagery and compared to U.S. Air Force 3D-nephanalysis. Comparisons of observed cloudiness from existing climatologies to patterns computed by the GISS climate model were also made.

The effect of cloud screening on MAX-DOAS aerosol retrievals.

NASA Astrophysics Data System (ADS)

Gielen, Clio; Van Roozendael, Michel; Hendrik, Francois; Fayt, Caroline; Hermans, Christian; Pinardi, Gaia; De Backer, Hugo; De Bock, Veerle; Laffineur, Quentin; Vlemmix, Tim

2014-05-01

In recent years, ground-based multi-axis differential absorption spectroscopy (MAX-DOAS) has shown to be ideally suited for the retrieval of tropospheric trace gases and deriving information on the aerosol properties. These measurements are invaluable to our understanding of the physics and chemistry of the atmospheric system, and the impact on the Earth's climate. Unfortunately, MAX-DOAS measurements are often performed under strong non-clear-sky conditions, causing strong data quality degradation and uncertainties on the retrievals. Here we present the result of our cloud-screening method, using the colour index (CI), on aerosol retrievals from MAX-DOAS measurements (AOD and vertical profiles). We focus on two large data sets, from the Brussels and Beijing area. Using the CI we define 3 different sky conditions: bad (=full thick cloud cover/extreme aerosols), mediocre (=thin clouds/aerosols) and good (=clear sky). We also flag the presence of broken/scattered clouds. We further compare our cloud-screening method with results from cloud-cover fractions derived from thermic infrared measurements. In general, our method shows good results to qualify the sky and cloud conditions of MAX-DOAS measurements, without the need for other external cloud-detection systems. Removing data under bad-sky and broken-cloud conditions results in a strongly improved agreement, in both correlation and slope, between the MAX-DOAS aerosol retrievals and data from other instruments (e.g. AERONET, Brewer). With the improved AOD retrievals, the seasonal and diurnal variations of the aerosol content and vertical distribution at both sites can be investigated in further detail. By combining with additional information derived by other instruments (Brewer, lidar, ...) operated at the stations, we will further study the observed aerosol characteristics, and their influence on and by meteorological conditions such as clouds and/or the boundary layer height.

On the Influence of Air Mass Origin on Low-Cloud Properties in the Southeast Atlantic

NASA Astrophysics Data System (ADS)

Fuchs, Julia; Cermak, Jan; Andersen, Hendrik; Hollmann, Rainer; Schwarz, Katharina

2017-10-01

This study investigates the impact of air mass origin and dynamics on cloud property changes in the Southeast Atlantic (SEA) during the biomass burning season. The understanding of clouds and their determinants at different scales is important for constraining the Earth's radiative budget and thus prominent in climate system research. In this study, the thermodynamically stable SEA stratocumulus cover is observed not only as the result of local environmental conditions but also as connected to large-scale meteorology by the often neglected but important role of spatial origins of air masses entering this region. In order to assess to what extent cloud properties are impacted by aerosol concentration, air mass history, and meteorology, a Hybrid Single-Particle Lagrangian Integrated Trajectory cluster analysis is conducted linking satellite observations of cloud properties (Spinning-Enhanced Visible and Infrared Imager), information on aerosol species (Monitoring Atmospheric Composition and Climate), and meteorological context (ERA-Interim reanalysis) to air mass clusters. It is found that a characteristic pattern of air mass origins connected to distinct synoptical conditions leads to marked cloud property changes in the southern part of the study area. Long-distance air masses are related to midlatitude weather disturbances that affect the cloud microphysics, especially in the southwestern subdomain of the study area. Changes in cloud effective radius are consistent with a boundary layer deepening and changes in lower tropospheric stability (LTS). In the southeastern subdomain cloud cover is controlled by a generally higher LTS, while air mass origin plays a minor role. This study leads to a better understanding of the dynamical drivers behind observed stratocumulus cloud properties in the SEA and frames potentially interesting conditions for aerosol-cloud interactions.

Volcanic Plume from Mt. Unzen, Dust Cloud, cloud Vortices

NASA Image and Video Library

1991-12-01

Stable, south flowing air over the western Pacific Ocean (26.0N, 131.0E) is disturbed by islands south of Korea, resulting in sinuous clouds known as von Karman vortices. The smoke plume from Japan's Mount Unzen Volcano on Kyushu, is visible just west of the large cloud mass and extending southward. A very large, purple tinged dust pall, originating in Mongolia, can be seen on the Earth's Limb, covering eastern China and extending into the East China Sea.

Microphysical Consequences of the Spatial Distribution of Ice Nucleation in Mixed-Phase Stratiform Clouds

DOE Office of Scientific and Technical Information (OSTI.GOV)

Yang, Fan; Ovchinnikov, Mikhail; Shaw, Raymond A.

Mixed-phase stratiform clouds can persist even with steady ice precipitation fluxes, and the origin and microphysical properties of the ice crystals are of interest. Vapor deposition growth and sedimentation of ice particles along with a uniform volume source of ice nucleation, leads to a power law relation between ice water content wi and ice number concentration ni with exponent 2.5. The result is independent of assumptions about the vertical velocity structure of the cloud and is therefore more general than the related expression of Yang et al. [2013]. The sensitivity of the wi-ni relationship to the spatial distribution of icemore » nucleation is confirmed by Lagrangian tracking and ice growth with cloud-volume, cloud-top, and cloud-base sources of ice particles through a time-dependent cloud field. Based on observed wi and ni from ISDAC, a lower bound of 0.006 m^3/s is obtained for the ice crystal formation rate.« less

Toward ubiquitous healthcare services with a novel efficient cloud platform.

PubMed

He, Chenguang; Fan, Xiaomao; Li, Ye

2013-01-01

Ubiquitous healthcare services are becoming more and more popular, especially under the urgent demand of the global aging issue. Cloud computing owns the pervasive and on-demand service-oriented natures, which can fit the characteristics of healthcare services very well. However, the abilities in dealing with multimodal, heterogeneous, and nonstationary physiological signals to provide persistent personalized services, meanwhile keeping high concurrent online analysis for public, are challenges to the general cloud. In this paper, we proposed a private cloud platform architecture which includes six layers according to the specific requirements. This platform utilizes message queue as a cloud engine, and each layer thereby achieves relative independence by this loosely coupled means of communications with publish/subscribe mechanism. Furthermore, a plug-in algorithm framework is also presented, and massive semistructure or unstructured medical data are accessed adaptively by this cloud architecture. As the testing results showing, this proposed cloud platform, with robust, stable, and efficient features, can satisfy high concurrent requests from ubiquitous healthcare services.

Minimalist model of ice microphysics in mixed-phase stratiform clouds

NASA Astrophysics Data System (ADS)

Yang, Fan; Ovchinnikov, Mikhail; Shaw, Raymond A.

2013-07-01

The question of whether persistent ice crystal precipitation from supercooled layer clouds can be explained by time-dependent, stochastic ice nucleation is explored using an approximate, analytical model and a large-eddy simulation (LES) cloud model. The updraft velocity in the cloud defines an accumulation zone, where small ice particles cannot fall out until they are large enough, which will increase the residence time of ice particles in the cloud. Ice particles reach a quasi-steady state between growth by vapor deposition and fall speed at cloud base. The analytical model predicts that ice water content (wi) has a 2.5 power-law relationship with ice number concentration (ni). wi and ni from a LES cloud model with stochastic ice nucleation confirm the 2.5 power-law relationship, and initial indications of the scaling law are observed in data from the Indirect and Semi-Direct Aerosol Campaign. The prefactor of the power law is proportional to the ice nucleation rate and therefore provides a quantitative link to observations of ice microphysical properties.

Minimalist Model of Ice Microphysics in Mixed-phase Stratiform Clouds

DOE Office of Scientific and Technical Information (OSTI.GOV)

Yang, F.; Ovchinnikov, Mikhail; Shaw, Raymond A.

The question of whether persistent ice crystal precipitation from super cooled layer clouds can be explained by time-dependent, stochastic ice nucleation is explored using an approximate, analytical model, and a large-eddy simulation (LES) cloud model. The updraft velocity in the cloud defines an accumulation zone, where small ice particles cannot fall out until they are large enough, which will increase the residence time of ice particles in the cloud. Ice particles reach a quasi-steady state between growth by vapor deposition and fall speed at cloud base. The analytical model predicts that ice water content (wi) has a 2.5 power lawmore » relationship with ice number concentration ni. wi and ni from a LES cloud model with stochastic ice nucleation also confirm the 2.5 power law relationship. The prefactor of the power law is proportional to the ice nucleation rate, and therefore provides a quantitative link to observations of ice microphysical properties.« less

Global, Persistent, Real-time Multi-sensor Automated Satellite Image Analysis and Crop Forecasting in Commercial Cloud

NASA Astrophysics Data System (ADS)

Brumby, S. P.; Warren, M. S.; Keisler, R.; Chartrand, R.; Skillman, S.; Franco, E.; Kontgis, C.; Moody, D.; Kelton, T.; Mathis, M.

2016-12-01

Cloud computing, combined with recent advances in machine learning for computer vision, is enabling understanding of the world at a scale and at a level of space and time granularity never before feasible. Multi-decadal Earth remote sensing datasets at the petabyte scale (8×10^15 bits) are now available in commercial cloud, and new satellite constellations will generate daily global coverage at a few meters per pixel. Public and commercial satellite observations now provide a wide range of sensor modalities, from traditional visible/infrared to dual-polarity synthetic aperture radar (SAR). This provides the opportunity to build a continuously updated map of the world supporting the academic community and decision-makers in government, finanace and industry. We report on work demonstrating country-scale agricultural forecasting, and global-scale land cover/land, use mapping using a range of public and commercial satellite imagery. We describe processing over a petabyte of compressed raw data from 2.8 quadrillion pixels (2.8 petapixels) acquired by the US Landsat and MODIS programs over the past 40 years. Using commodity cloud computing resources, we convert the imagery to a calibrated, georeferenced, multiresolution tiled format suited for machine-learning analysis. We believe ours is the first application to process, in less than a day, on generally available resources, over a petabyte of scientific image data. We report on work combining this imagery with time-series SAR collected by ESA Sentinel 1. We report on work using this reprocessed dataset for experiments demonstrating country-scale food production monitoring, an indicator for famine early warning. We apply remote sensing science and machine learning algorithms to detect and classify agricultural crops and then estimate crop yields and detect threats to food security (e.g., flooding, drought). The software platform and analysis methodology also support monitoring water resources, forests and other general indicators of environmental health, and can detect growth and changes in cities that are displacing historical agricultural zones.

Cloud classification in polar regions using AVHRR textural and spectral signatures

NASA Technical Reports Server (NTRS)

Welch, R. M.; Sengupta, S. K.; Weger, R. C.; Christopher, S. A.; Kuo, K. S.; Carsey, F. D.

1990-01-01

Arctic clouds and ice-covered surfaces are classified on the basis of textural and spectral features obtained with AVHRR 1.1-km spatial resolution imagery over the Beaufort Sea during May-October, 1989. Scenes were acquired about every 5 days, for a total of 38 cases. A list comprising 20 arctic-surface and cloud classes is compiled using spectral measures defined by Garand (1988).

Secure Cloud Computing Implementation Study For Singapore Military Operations

DTIC Science & Technology

2016-09-01

COMPUTING IMPLEMENTATION STUDY FOR SINGAPORE MILITARY OPERATIONS by Lai Guoquan September 2016 Thesis Advisor: John D. Fulp Co-Advisor...DATES COVERED Master’s thesis 4. TITLE AND SUBTITLE SECURE CLOUD COMPUTING IMPLEMENTATION STUDY FOR SINGAPORE MILITARY OPERATIONS 5. FUNDING NUMBERS...addition, from the military perspective, the benefits of cloud computing were analyzed from a study of the U.S. Department of Defense. Then, using

Global Measurements of Optically Thin Cirrus Clouds Using CALIOP

NASA Astrophysics Data System (ADS)

Ryan, R. A.; Avery, M. A.; Vaughan, M.

2017-12-01

Optically thin cirrus clouds, defined here as cold clouds consisting of randomly oriented ice crystals and having optical depths (τ) less than 0.3, are difficult to measure accurately. Thin cirrus clouds have been shown to have a net warming effect on the globe but, because passive instruments are not sensitive to optically thin clouds, the occurrence frequency of thin cirrus is greatly underestimated in historical passive sensor cloud climatology. One major strength of Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) is its ability to detect these thin cirrus clouds, thus filling an important missing piece in the historical data record. This poster examines multiple years of CALIOP Level 2 data, focusing on those CALIOP retrievals identified as being optically thin (τ < 0.3), having a cold centroid temperature (TC < -40°C), and consisting solely of randomly oriented ice crystals. Using this definition, thin cirrus are identified and counted globally within each season. By examining the spatial, and seasonal distributions of these thin clouds we hope to gain a better understanding of how thin cirrus affect the atmosphere. Understanding when and where these clouds form and persist in the global atmosphere is the topic and focus of the presented poster.

Cloud detection algorithm comparison and validation for operational Landsat data products

USGS Publications Warehouse

Foga, Steven Curtis; Scaramuzza, Pat; Guo, Song; Zhu, Zhe; Dilley, Ronald; Beckmann, Tim; Schmidt, Gail L.; Dwyer, John L.; Hughes, MJ; Laue, Brady

2017-01-01

Clouds are a pervasive and unavoidable issue in satellite-borne optical imagery. Accurate, well-documented, and automated cloud detection algorithms are necessary to effectively leverage large collections of remotely sensed data. The Landsat project is uniquely suited for comparative validation of cloud assessment algorithms because the modular architecture of the Landsat ground system allows for quick evaluation of new code, and because Landsat has the most comprehensive manual truth masks of any current satellite data archive. Currently, the Landsat Level-1 Product Generation System (LPGS) uses separate algorithms for determining clouds, cirrus clouds, and snow and/or ice probability on a per-pixel basis. With more bands onboard the Landsat 8 Operational Land Imager (OLI)/Thermal Infrared Sensor (TIRS) satellite, and a greater number of cloud masking algorithms, the U.S. Geological Survey (USGS) is replacing the current cloud masking workflow with a more robust algorithm that is capable of working across multiple Landsat sensors with minimal modification. Because of the inherent error from stray light and intermittent data availability of TIRS, these algorithms need to operate both with and without thermal data. In this study, we created a workflow to evaluate cloud and cloud shadow masking algorithms using cloud validation masks manually derived from both Landsat 7 Enhanced Thematic Mapper Plus (ETM +) and Landsat 8 OLI/TIRS data. We created a new validation dataset consisting of 96 Landsat 8 scenes, representing different biomes and proportions of cloud cover. We evaluated algorithm performance by overall accuracy, omission error, and commission error for both cloud and cloud shadow. We found that CFMask, C code based on the Function of Mask (Fmask) algorithm, and its confidence bands have the best overall accuracy among the many algorithms tested using our validation data. The Artificial Thermal-Automated Cloud Cover Algorithm (AT-ACCA) is the most accurate nonthermal-based algorithm. We give preference to CFMask for operational cloud and cloud shadow detection, as it is derived from a priori knowledge of physical phenomena and is operable without geographic restriction, making it useful for current and future land imaging missions without having to be retrained in a machine-learning environment.

Spectral Dependence of MODIS Cloud Droplet Effective Radius Retrievals for Marine Boundary Layer Clouds

NASA Technical Reports Server (NTRS)

Zhang, Zhibo; Platnick, Steven E.; Ackerman, Andrew S.; Cho, Hyoun-Myoung

2014-01-01

Low-level warm marine boundary layer (MBL) clouds cover large regions of Earth's surface. They have a significant role in Earth's radiative energy balance and hydrological cycle. Despite the fundamental role of low-level warm water clouds in climate, our understanding of these clouds is still limited. In particular, connections between their properties (e.g. cloud fraction, cloud water path, and cloud droplet size) and environmental factors such as aerosol loading and meteorological conditions continue to be uncertain or unknown. Modeling these clouds in climate models remains a challenging problem. As a result, the influence of aerosols on these clouds in the past and future, and the potential impacts of these clouds on global warming remain open questions leading to substantial uncertainty in climate projections. To improve our understanding of these clouds, we need continuous observations of cloud properties on both a global scale and over a long enough timescale for climate studies. At present, satellite-based remote sensing is the only means of providing such observations.

Global Distribution and Vertical Structure of Clouds Revealed by CALIPSO

NASA Astrophysics Data System (ADS)

Yi, Y.; Minnis, P.; Winker, D.; Huang, J.; Sun-Mack, S.; Ayers, K.

2007-12-01

Understanding the effects of clouds on Earth's radiation balance, especially on longwave fluxes within the atmosphere, depends on having accurate knowledge of cloud vertical location within the atmosphere. The Cloud- Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) satellite mission provides the opportunity to measure the vertical distribution of clouds at a greater detail than ever before possible. The CALIPSO cloud layer products from June 2006 to June 2007 are analyzed to determine the occurrence frequency and thickness of clouds as functions of time, latitude, and altitude. In particular, the latitude-longitude and vertical distributions of single- and multi-layer clouds and the latitudinal movement of cloud cover with the changing seasons are examined. The seasonal variablities of cloud frequency and geometric thickness are also analyzed and compared with similar quantities derived from the Aqua Moderate Resolution Imaging Spectroradiometer (MODIS) using the Clouds and the Earth's Radiant Energy System (CERES) cloud retrieval algorithms. The comparisons provide an estimate of the errors in cloud fraction, top height, and thickness incurred by passive algorithms.

Thirty Years of Cloud Cover Patterns from Satellite Data: Fog in California's Central Valley and Coast

NASA Astrophysics Data System (ADS)

Waller, E.; Baldocchi, D. D.

2012-12-01

In an effort to assess long term trends in winter fog in the Central Valley of California, custom maps of daily cloud cover from an approximately 30 year record of AVHRR (1981-1999) and MODIS (2000-2012) satellite data were generated. Spatial rules were then used to differentiate between fog and general cloud cover. Differences among the sensors (e.g., spectral content, spatial resolution, overpass time) presented problems of consistency, but concurrent climate station data were used to resolve systematic differences in products, and to confirm long term trends. The frequency and extent of Central Valley ("Tule") fog appear to have some periodic oscillation, but also appear to be on the decline, especially in the Sacramento Valley and in the "shoulder" months of November and February. These results may have strong implications for growers of fruit and nut trees in the Central Valley dependent on winter chill hours that are augmented by the foggy daytime conditions. Conclusions about long term trends in fog are limited to daytime patterns, as results are primarily derived from reflectance-based products. Similar analyses of daytime cloud cover are performed on other areas of concern, such as the coastal fog belt of California. Large area and long term patterns here appear to have periodic oscillation similar to that for the Central Valley. However, the relatively coarse spatial resolution of the AVHRR LTDR (Long Term Data Record) data (~5-km) may be limiting for fine-scale analysis of trends.

The Apparent Bluing of Aerosols Near Clouds

NASA Technical Reports Server (NTRS)

Marshak, Alexander

2008-01-01

Numerous studies based on satellite observations have reported that aerosol optical depths increase with increasing cloud cover. Part of the increase comes from the humidification and consequent growth of aerosol particles in the moist cloud environment, but part comes from 3D cloud-radiative transfer effects on the retrieved aerosol properties. Often, discerning whether the observed increases in aerosol optical depths are artifacts or real proves difficult. I describe a simple model that quantifies the enhanced illumination of cloud-free columns in the vicinity of clouds that are used in the aerosol retrievals. This model is based on the assumption that the enhancement in the cloud-free column radiance comes from enhanced Rayleigh scattering that results from the presence of the nearby clouds. This assumption leads to a larger increase of AOT for shorter wavelengths, or to a "bluing" of aerosols near clouds. Examples from the MODIS observations that illustrate the apparent bluing of aerosols near clouds will be discussed.

Emerging Use of Dual Channel Infrared for Remote Sensing of Sea Ice

NASA Astrophysics Data System (ADS)

Lewis, N. S.; Serreze, M. C.; Gallaher, D. W.; Koenig, L.; Schaefer, K. M.; Campbell, G. G.; Thompson, J. A.; Grant, G.; Fetterer, F. M.

2017-12-01

Using GOES-16 data as a proxy for overhead persistent infrared, we examine the feasibility of using a dual channel shortwave / midwave infrared (SWIR/MWIR) approach to detect and chart sea ice in Hudson Bay through a series of images with a temporal scale of less than fifteen minutes. While not traditionally exploited for sea ice remote sensing, the availability of near continuous shortwave and midwave infrared data streams over the Arctic from overhead persistent infrared (OPIR) satellites could provide an invaluable source of information regarding the changing Arctic climate. Traditionally used for the purpose of missile warning and strategic defense, characteristics of OPIR make it an attractive source for Arctic remote sensing as the temporal resolution can provide insight into ice edge melt and motion processes. Fundamentally, the time series based algorithm will discern water/ice/clouds using a SWIR/MWIR normalized difference index. Cloud filtering is accomplished through removing pixels categorized as clouds while retaining a cache of previous ice/water pixels to replace any cloud obscured (and therefore omitted) pixels. Demonstration of the sensitivity of GOES-16 SWIR/MWIR to detect and discern water/ice/clouds provides a justification for exploring the utility of military OPIR sensors for civil and commercial applications. Potential users include the scientific community as well as emergency responders, the fishing industry, oil and gas industries, and transportation industries that are seeking to exploit changing conditions in the Arctic but require more accurate and timely ice charting products.

A Change in the Weather

NASA Technical Reports Server (NTRS)

2007-01-01

These two Compact Reconnaissance Imaging Spectrometer for Mars (CRISM) images were acquired over the northern plains of Mars near one of the possible landing sites for NASA's Phoenix mission, set to launch in August 2007. The lower right image was acquired first, on Nov. 29, 2006, at 0720 UTC (2:20 a.m. EST), while the upper left image was acquired about one month later on Dec. 26, 2006, at 0030 UTC (or Dec. 25, 2006, at 7:30 p.m. EST). The CRISM data were taken in 544 colors covering the wavelength range from 0.36-3.92 micrometers, and show features as small as about 20 meters (66 feet) across. The images shown above are red-green-blue color composites using wavelengths 0.71, 0.6, and 0.53 micrometers, respectively (or infrared, red, and green light), and are overlain on a mosaic of Mars Odyssey Thermal Emission Imaging System (THEMIS) visible data. Each image covers a region about 11 kilometers (6.6 miles) wide at its narrowest, and they overlap near 71.0 degrees north latitude, 252.8 degrees east longitude

The Earth equivalent to the season and latitude of this site is late summer in northern Canada, above the Arctic Circle. At that season and latitude, Martian weather conditions are transitioning from summer with generally clear skies, occasional weather fronts, and infrequent dust storms, to an autumn with pervasive, thick water-ice clouds.

The striking difference in the appearance of the images is caused by the seasonal development of water-ice clouds. The earlier (lower right) image is cloud-free, and surface features can clearly be seen - like the small crater in the upper left. However, the clouds and haze in the later (upper left) image make it hard to see the surface. There are variations in the thickness and spacing of the clouds, just like clouds on Earth. On other days when nearby sites were imaged, the cloud cover varied day-to-day, but as the seasons change the trend is more and thicker clouds.

With the onset of autumn the clouds will gradually cover the area and, just as with autumn on Earth, the Martian day is getting shorter at these high northern latitudes. In a few more months this area will settle into winter darkness and be covered in a layer of frost and carbon dioxide snow.

CRISM's mission: Find the spectral fingerprints of aqueous and hydrothermal deposits and map the geology, composition and stratigraphy of surface features. The instrument will also watch the seasonal variations in Martian dust and ice aerosols, and water content in surface materials -- leading to new understanding of the climate.

The Compact Reconnaissance Imaging Spectrometer for Mars (CRISM) is one of six science instruments on NASA's Mars Reconnaissance Orbiter. Led by The Johns Hopkins University Applied Physics Laboratory, the CRISM team includes expertise from universities, government agencies and small businesses in the United States and abroad.

Radiative Forcing by Contrails

NASA Technical Reports Server (NTRS)

Meerkoetter, R.; Schumann, U.; Doelling, D. R.; Nakajima, T.; Tsushima, Y.

1999-01-01

A parametric study of the instantaneous radiative impact of contrails is presented using three different radiative transfer models for a series of model atmospheres and cloud parameters. Contrails are treated as geometrically and optically thin plane parallel homogeneous cirrus layers in a static atmospheres The ice water content is varied as a function of ambient temperature. The model atmospheres include tropical, mid-latitude, and subarctic summer and winter atmospheres Optically thin contrails cause a positive net forcing at top of the atmosphere. At the surface the radiative forcing is negative during daytime. The forcing increases with the optical depth and the amount of contrail cover. At the top of the atmosphere a mean contrail cover of 0.1% with average optical depth of 0.2 to 0.5 causes about 0.01 to 0.03 W/m(exp 2)a daily mean instantaneous radiative forcing. Contrails cool the surface during the day and heat the surface during the night, and hence reduce the daily temperature amplitude The net effect depends strongly on the daily variation of contrail cloud cover. The indirect radiative forcing due to particle changes in natural cirrus clouds may be of the same magnitude as the direct one due to additional cover.

Changes in minimum and maximum temperatures at the Pic du Midi in relation with humidity and cloudiness, 1882-1984

NASA Astrophysics Data System (ADS)

Dessens, J.; Bücher, A.

In an attempt to contribute to the investigation on a global climate change, a historical series of minimum and maximum temperature data at the Pic du Midi, a mountain observatory at 2862 m a.s.l. in the French Pyrenees, is updated after correction of a systematic deviation due to a relocation of the station in 1971. These data, which now cover the 1882-1984 period, are examined in parallel with humidity and cloud cover data for the same period. From the beginning to the end of this period, observations show that the mean night-time temperature has increased by 2.39° C/100 yr while the mean daytime temperature has decreased by 0.50° C/100 yr. In consequence, the mean annual diurnal temperature range has dropped by 36%/100 yr. The maximum seasonal decrease is 46%/100 yr in spring. Season-to-season and year-to-year inter-relationships between minimum temperature, maximum temperature, relative humidity and cloud cover suggest that the decrease in maximum temperature is related to a concomitant increase of 15%/100 yr in both relative humidity and cloud cover.

Investigation of the effects of the macrophysical and microphysical properties of cirrus clouds on the retrieval of optical properties: Results for FIRE 2

NASA Technical Reports Server (NTRS)

Stackhouse, Paul W., Jr.; Stephens, Graeme L.

1993-01-01

Due to the prevalence and persistence of cirrus cloudiness across the globe, cirrus clouds are believed to have an important effect on the climate. Stephens et al., (1990) among others have shown that the important factor determining how cirrus clouds modulate the climate is the balance between the albedo and emittance effect of the cloud systems. This factor was shown to depend in part upon the effective sizes of the cirrus cloud particles. Since effective sizes of cirrus cloud microphysical distributions are used as a basis of parameterizations in climate models, it is crucial that the relationships between effective sizes and radiative properties be clearly established. In this preliminary study, the retrieval of cirrus cloud effective sizes are examined using a two dimensional radiative transfer model for a cirrus cloud case sampled during FIRE Cirrus 11. The purpose of this paper is to present preliminary results from the SHSG model demonstrating the sensitivity of the bispectral relationships of reflected radiances and thus the retrieval of effective sizes to phase function and dimensionality.

Spatial and Temporal Inter-Relationships between Anomalies and Trends of Temperature, Moisture, Cloud Cover, and OLR as Observed by AIRS/AMSU on Aqua

NASA Technical Reports Server (NTRS)

Susskind, Joel

2008-01-01

AIRS/AMSU is the advanced IR/MW atmospheric sounding system launched on EOS Aqua in May 2002. Products derived from AIRS/AMSU by the AIRS Science Team include surface skin temperature and atmospheric temperature profiles; atmospheric humidity profiles, fractional cloud cover and cloud top pressure, and OLR. Products covering the period September 2002 through the present have been derived from AIRS/AMSU using the AIRS Science Team Version 5 retrieval algorithm. In this paper, we will show results covering the time period September 2006 - November 2008. This time period is marked by a substantial warming trend of Northern Hemisphere Extratropical land surface skin temperatures, as well as pronounced El Nino - La Nina episodes. These both influence the spatial and temporal anomaly patterns of atmospheric temperature and moisture profiles, as well as of cloud cover and Clear sky and All Sky OLR. The relationships between temporal and spatial anomalies of these parameters over this time period, as determined from AIRS/AMSU observations, will be shown, with particular emphasis on which contribute significantly to OLR anomalies in each of the tropics and extra-tropics. Results will also be shown to validate the anomalies and trends of temperature profiles and OLR as determined from analysis of AIRS/AMSU data. Global and regional trends during the 6 1/3 year period are not necessarily indicative of what has happened in the past, or what may happen in the future. Nevertheless, the inter-relationships of spatial and temporal anomalies of atmospheric geophysical parameters with those of surface skin temperature are indicative of climate processes, and can be used to test the performance of climate models when driven by changes in surface temperatures.

Evaluation of radar imagery for geological and cartographic applications

USGS Publications Warehouse

Moore, Gerald K.; Sheehan, Cynthia A.

1981-01-01

The House/Senate conference report on H.R. 4930 (96th Congress), the Department of the Interior and Related Agencies Appropriations bill, 1980, stated that the U.S. Geological Survey should "begin the use of side-looking airborne radar imagery for topographic and geological mapping, and geological resource surveys in promising areas, particularly Alaska." In response to this mandate, the Survey acquired radar data and began scientific studies to analyze and interpret these data. About 70 percent of the project funding was used to acquire radar imagery and to evaluate Alaskan applications. Results of these studies indicate that radar images have a unique incremental value for certain geologic and cartographic applications but that the images are best suited for use as supplemental information sources or as primary data sources in areas of persistent cloud cover.The value of radar data is greatest for geologic mapping and resource surveys, particularly for mineral and petroleum exploration, where the objective is to locate any single feature or group of features that may control the occurrences of these resources. Radar images are considered by oil and gas companies to be worth the cost of data acquisition within a limited area of active exploration.Radar images also have incremental value for geologic site studies and hazard mapping. The need in these cases is TO inventory all geologic hazards to human life, property, resources, and the environment. For other geologic applications, radar images have a relatively small incremental value over a combination of Landsat images and aerial photographs.The value of radar images for cartographic applications is minimal, except when they are used as a substitute for aerial photographs and topographic maps in persistently cloud-covered areas. If conventional data sources are not available, radar images provide useful information on terrain relief, landforms, drainage patterns, and land cover. Screen less lithography is a low-cost method of reproducing the images. The images from modern, commercially available radar systems have good visual quality; they also have better geometric accuracy and higher information content than images from older systems. Images from modern systems, however, also have some of the same disadvantages as those from older systems. The most serious problem is that considerable information is lost in the process of recording the radar return on film. Another problem is that the oblique radar view of the landscape results in interpretations that are biased by look direction. A compromise antenna depression angle also commonly results in inadequate or excessive shadowing in parts of the image. There is a need for high-resolution digital data, not currently available from the private sector, to significantly improve the utility of radar data for geologic and cartographic applications.

The "cholera cloud" in the nineteenth-century "British World": history of an object-without-an-essence.

PubMed

Mukharji, Projit Bihari

2012-01-01

The "cholera cloud" is one of the most persistent presences in the archives of nineteenth-century cholera in the "British World." Yet it has seldom received anything more than a passing acknowledgment from historians of cholera. Tracing the history of the cholera cloud as an object promises to open up a new dimension of the historically contingent experience of cholera, as well as make a significant contribution to the emergent literature on "thing theory." By conceptualizing the cholera cloud as an object-without-an-essence, this article demonstrates how global cholera pandemics in the nineteenth century produced globalized objects in which a near-universal recognizability and an utterly context-specific set of meanings, visions, and realities could ironically cohabit.

Variability of Cloud Cover and Its Relation to Snowmelt and Runoff in the Mountainous Western United States

NASA Astrophysics Data System (ADS)

Sumargo, E.; Cayan, D. R.; Iacobellis, S.

2014-12-01

Obtaining accurate solar radiation input to snowmelt runoff models remains a fundamental challenge for water supply forecasters in the mountainous western U.S. The variability of cloud cover is a primary source of uncertainty in estimating surface radiation, especially given that ground-based radiometer networks in mountain terrains are sparse. Thus, remote sensed cloud properties provide a way to extend in situ observations and more importantly, to understand cloud variability in montane environment. We utilize 17 years of NASA/NOAA GOES visible albedo product with 4 km spatial and half-hour temporal resolutions to investigate daytime cloud variability in the western U.S. at elevations above 800 m. REOF/PC analysis finds that the 5 leading modes account for about two-thirds of the total daily cloud albedo variability during the whole year (ALL) and snowmelt season (AMJJ). The AMJJ PCs are significantly correlated with de-seasonalized snowmelt derived from CDWR CDEC and NRCS SNOTEL SWE data and USGS stream discharge across the western conterminous states. The sum of R2 from 7 days prior to the day of snowmelt/discharge amounts to as much as ~52% on snowmelt and ~44% on discharge variation. Spatially, the correlation patterns take on broad footprints, with strongest signals in regions of highest REOF weightings. That the response of snowmelt and streamflow to cloud variation is spread across several days indicates the cumulative effect of cloud variation on the energy budget in mountain catchments.

High-resolution mapping of Martian water ice clouds using Mars Express OMEGA observations - Derivation of the diurnal cloud life cycle

NASA Astrophysics Data System (ADS)

Szantai, Andre; Audouard, Joachim; Madeleine, Jean-Baptiste; Forget, Francois; Pottier, Alizée; Millour, Ehouarn; Gondet, Brigitte; Langevin, Yves; Bibring, Jean-Pierre

2016-10-01

The mapping in space and time of water ice clouds can help to explain the Martian water cycle and atmospheric circulation. For this purpose, an ice cloud index (ICI) corresponding to the depth of a water ice absorption band at 3.4 microns is derived from a series of OMEGA images (spectels) covering 5 Martian years. The ICI values for the corresponding pixels are then binned on a high-resolution regular grid (1° longitude x 1° latitude x 5° Ls x 1 h local time) and averaged. Inside each bin, the cloud cover is calculated by dividing the number of pixels considered as cloudy (after comparison to a threshold) to the number of all (valid) pixelsWe compare the maps of clouds obtained around local time 14:00 with collocated TES cloud observations (which were only obtained around this time of the day). A good agreement is found.Averaged ICI compared to the water ice column variable from the Martian Climate Database (MCD) show a correct correlation (~0.5) , which increases when values limited to the tropics only are compared.The number of gridpoints containing ICI values is small ( ~1%), but by taking several neighbor gridpoints and over longer periods, we can observe a cloud life cycle during daytime. An example in the the tropics, around the northern summer solstice, shows a decrease of cloudiness in the morning followed by an increase in the afternoon.

The Sensitivity of Numerical Simulations of Cloud-Topped Boundary Layers to Cross-Grid Flow

NASA Astrophysics Data System (ADS)

Wyant, Matthew C.; Bretherton, Christopher S.; Blossey, Peter N.

2018-02-01

In mesoscale and global atmospheric simulations with large horizontal domains, strong horizontal flow across the grid is often unavoidable, but its effects on cloud-topped boundary layers have received comparatively little study. Here the effects of cross-grid flow on large-eddy simulations of stratocumulus and trade-cumulus marine boundary layers are studied across a range of grid resolutions (horizontal × vertical) between 500 m × 20 m and 35 m × 5 m. Three cases are simulated: DYCOMS nocturnal stratocumulus, BOMEX trade cumulus, and a GCSS stratocumulus-to-trade cumulus case. Simulations are performed with a stationary grid (with 4-8 m s-1 horizontal winds blowing through the cyclic domain) and a moving grid (equivalent to subtracting off a fixed vertically uniform horizontal wind) approximately matching the mean boundary-layer wind speed. For stratocumulus clouds, cross-grid flow produces two primary effects on stratocumulus clouds: a filtering of fine-scale resolved turbulent eddies, which reduces stratocumulus cloud-top entrainment, and a vertical broadening of the stratocumulus-top inversion which enhances cloud-top entrainment. With a coarse (20 m) vertical grid, the former effect dominates and leads to strong increases in cloud cover and LWP, especially as horizontal resolution is coarsened. With a finer (5 m) vertical grid, the latter effect is stronger and leads to small reductions in cloud cover and LWP. For the BOMEX trade cumulus case, cross-grid flow tends to produce fewer and larger clouds with higher LWP, especially for coarser vertical grid spacing. The results presented are robust to choice of scalar advection scheme and Courant number.

An eight-month climatology of marine stratocumulus cloud fraction, albedo, and integrated liquid water

NASA Technical Reports Server (NTRS)

Fairall, C. W.; Hare, J. E.; Snider, Jack B.

1990-01-01

As part of the FIRE/Extended Time Observations (ETO) program, extended time observations were made at San Nicolas Island (SNI) from March to October, 1987. Hourly averages of air temperature, relative humidity, wind speed and direction, solar irradiance, and downward longwave irradiance were recorded. The radiation sensors were standard Eppley pyranometers (shortwave) and pyrgeometers (longwave). The SNI data were processed in several ways to deduce properties of the stratocumulus covered marine boundary layer (MBL). For example, from the temperature and humidity the lifting condensation level, which is an estimate of the height of the cloud bottom, can be computed. A combination of longwave irradiance statistics can be used to estimate fractional cloud cover. An analysis technique used to estimate the integrated cloud liquid water content (W) and the cloud albedo from the measured solar irradiance is also described. In this approach, the cloud transmittance is computed by dividing the irradiance measured at some time by a clear sky value obtained at the same hour on a cloudless day. From the transmittance and the zenith angle, values of cloud albedo and W are computed using the radiative transfer parameterizations of Stephens (1978). These analysis algorithms were evaluated with 17 days of simultaneous and colocated mm-wave (20.6 and 31.65 GHz) radiometer measurements of W and lidar ceilometer measurements of cloud fraction and cloudbase height made during the FIRE IFO. The algorithms are then applied to the entire data set to produce a climatology of these cloud properties for the eight month period.

Integrating solar energy and climate research into science education

NASA Astrophysics Data System (ADS)

Betts, Alan K.; Hamilton, James; Ligon, Sam; Mahar, Ann Marie

2016-01-01

This paper analyzes multi-year records of solar flux and climate data from two solar power sites in Vermont. We show the inter-annual differences of temperature, wind, panel solar flux, electrical power production, and cloud cover. Power production has a linear relation to a dimensionless measure of the transmission of sunlight through the cloud field. The difference between panel and air temperatures reaches 24°C with high solar flux and low wind speed. High panel temperatures that occur in summer with low wind speeds and clear skies can reduce power production by as much as 13%. The intercomparison of two sites 63 km apart shows that while temperature is highly correlated on daily (R2=0.98) and hourly (R2=0.94) timescales, the correlation of panel solar flux drops markedly from daily (R2=0.86) to hourly (R2=0.63) timescales. Minimum temperatures change little with cloud cover, but the diurnal temperature range shows a nearly linear increase with falling cloud cover to 16°C under nearly clear skies, similar to results from the Canadian Prairies. The availability of these new solar and climate datasets allows local student groups, a Rutland High School team here, to explore the coupled relationships between climate, clouds, and renewable power production. As our society makes major changes in our energy infrastructure in response to climate change, it is important that we accelerate the technical education of high school students using real-world data.

Cloud microphysics and aerosol indirect effects in the global climate model ECHAM5-HAM

NASA Astrophysics Data System (ADS)

Lohmann, U.; Stier, P.; Hoose, C.; Ferrachat, S.; Roeckner, E.; Zhang, J.

2007-03-01

The double-moment cloud microphysics scheme from ECHAM4 has been coupled to the size-resolved aerosol scheme ECHAM5-HAM. ECHAM5-HAM predicts the aerosol mass and number concentrations and the aerosol mixing state. This results in a much better agreement with observed vertical profiles of the black carbon and aerosol mass mixing ratios than with the previous version ECHAM4, where only the different aerosol mass mixing ratios were predicted. Also, the simulated liquid, ice and total water content and the cloud droplet and ice crystal number concentrations as a function of temperature in stratiform mixed-phase clouds between 0 and -35°C agree much better with aircraft observations in the ECHAM5 simulations. ECHAM5 performs better because more realistic aerosol concentrations are available for cloud droplet nucleation and because the Bergeron-Findeisen process is parameterized as being more efficient. The total anthropogenic aerosol effect includes the direct, semi-direct and indirect effects and is defined as the difference in the top-of-the-atmosphere net radiation between present-day and pre-industrial times. It amounts to -1.8 W m-2 in ECHAM5, when a relative humidity dependent cloud cover scheme and present-day aerosol emissions representative for the year 2000 are used. It is larger when either a statistical cloud cover scheme or a different aerosol emission inventory are employed.

Weather on Titan

NASA Astrophysics Data System (ADS)

Griffith, C. A.; Hall, J. L.; Geballe, T. R.

2000-10-01

Titan's atmosphere potentially sports a cycle similar to the hydrologic one on Earth with clouds, rain and seas, but with methane playing the terrestrial role of water. Over the past ten years many independent efforts indicated no strong evidence for cloudiness until some unique spectra were analyzed in 1998 (Griffith et al.). These surprising observations displayed enhanced fluxes of 14-200% on two nights at precisely the wavelengths (windows) that sense Titan's lower altitude where clouds might reside. The morphology of these enhancements in all 4 windows observed indicate that clouds covered ~6-9% of Titan's surface and existed at ~15 km altitude. Here I discuss new observations recorded in 1999 aimed to further characterize Titan's clouds. While we find no evidence for a massive cloud system similar to the one observed previously, 1%-4% fluctuations in flux occur daily. These modulations, similar in wavelength and morphology to the more pronounced ones observed earlier, suggest the presence of clouds covering <=1% of Titan's disk. The variations are too small to have been detected by most prior measurements. Repeated observations, spaced 30 minutes apart, indicate a temporal variability observable in the time scale of a couple of hours. The cloud heights hint that convection governs their evolutions. Their short lives point to the presence of rain. C. A. Griffith and J. L. Hall are supported by the NASA Planetary Astronomy Program NAG5-6790.

Effects of clouds on the Earth radiation budget; Seasonal and inter-annual patterns

NASA Technical Reports Server (NTRS)

Dhuria, Harbans L.

1992-01-01

Seasonal and regional variations of clouds and their effects on the climatological parameters were studied. The climatological parameters surface temperature, solar insulation, short-wave absorbed, long wave emitted, and net radiation were considered. The data of climatological parameters consisted of about 20 parameters of Earth radiation budget and clouds of 2070 target areas which covered the globe. It consisted of daily and monthly averages of each parameter for each target area for the period, Jun. 1979 - May 1980. Cloud forcing and black body temperature at the top of the atmosphere were calculated. Interactions of clouds, cloud forcing, black body temperature, and the climatological parameters were investigated and analyzed.

Goddard Visiting Scientist Program for the Space and Earth Sciences Directorate

NASA Technical Reports Server (NTRS)

Kerr, Frank

1992-01-01

Progress reports of the Visiting Scientist Program covering the period from 1 Jul. - 30 Sep. 1992 are included. Topics covered include space science and earth science. Other topics covered include cosmic rays, magnetic clouds, solar wind, satellite data, high resolution radiometer, and microwave scattering.

Insights from a refined decomposition of cloud feedbacks

DOE Office of Scientific and Technical Information (OSTI.GOV)

Zelinka, Mark D.; Zhou, Chen; Klein, Stephen A.

Decomposing cloud feedback into components due to changes in several gross cloud properties provides valuable insights into its physical causes. Here we present a refined decomposition that separately considers changes in free tropospheric and low cloud properties, better connecting feedbacks to individual governing processes and avoiding ambiguities present in a commonly used decomposition. It reveals that three net cloud feedback components are robustly nonzero: positive feedbacks from increasing free tropospheric cloud altitude and decreasing low cloud cover and a negative feedback from increasing low cloud optical depth. Low cloud amount feedback is the dominant contributor to spread in net cloudmore » feedback but its anticorrelation with other components damps overall spread. Furthermore, the ensemble mean free tropospheric cloud altitude feedback is roughly 60% as large as the standard cloud altitude feedback because it avoids aliasing in low cloud reductions. Implications for the “null hypothesis” climate sensitivity from well-understood and robustly simulated feedbacks are discussed.« less

Insights from a refined decomposition of cloud feedbacks

DOE PAGES

Zelinka, Mark D.; Zhou, Chen; Klein, Stephen A.

2016-09-05

Decomposing cloud feedback into components due to changes in several gross cloud properties provides valuable insights into its physical causes. Here we present a refined decomposition that separately considers changes in free tropospheric and low cloud properties, better connecting feedbacks to individual governing processes and avoiding ambiguities present in a commonly used decomposition. It reveals that three net cloud feedback components are robustly nonzero: positive feedbacks from increasing free tropospheric cloud altitude and decreasing low cloud cover and a negative feedback from increasing low cloud optical depth. Low cloud amount feedback is the dominant contributor to spread in net cloudmore » feedback but its anticorrelation with other components damps overall spread. Furthermore, the ensemble mean free tropospheric cloud altitude feedback is roughly 60% as large as the standard cloud altitude feedback because it avoids aliasing in low cloud reductions. Implications for the “null hypothesis” climate sensitivity from well-understood and robustly simulated feedbacks are discussed.« less

Variability analysis of the reconstructed daily global solar radiation under all-sky and cloud-free conditions in Madrid during the period 1887-1950

NASA Astrophysics Data System (ADS)

Antón, M.; Román, R.; Sanchez-Lorenzo, A.; Calbó, J.; Vaquero, J. M.

2017-07-01

This study focuses on the analysis of the daily global solar radiation (GSR) reconstructed from sunshine duration measurements at Madrid (Spain) from 1887 to 1950. Additionally, cloud cover information recorded simultaneously by human observations for the study period was also analyzed and used to select cloud-free days. First, the day-to-day variability of reconstructed GSR data was evaluated, finding a strong relationship between GSR and cloudiness. The second step was to analyze the long-term evolution of the GSR data which exhibited two clear trends with opposite sign: a marked negative trend of - 36 kJ/m2 per year for 1887-1915 period and a moderate positive trend of + 13 kJ/m2 per year for 1916-1950 period, both statistically significant at the 95% confidence level. Therefore, there is evidence of "early dimming" and "early brightening" periods in the reconstructed GSR data for all-sky conditions in Madrid from the late 19th to the mid-20th centuries. Unlike the long-term evolution of GSR data, cloud cover showed non-statistically significant trends for the two analyzed sub-periods, 1887-1915 and 1916-1950. Finally, GSR trends were analyzed exclusively under cloud-free conditions in summer by means of the determination of the clearness index for those days with all cloud cover observations equal to zero oktas. The long-term evolution of the clearness index was in accordance with the "early dimming" and "early brightening" periods, showing smaller trends but still statistically significant. This result points out that aerosol load variability could have had a non-negligible influence on the long-term evolution of GSR even as far as from the late 19th century.

Sensitivity of thermal inertia calculations to variations in environmental factors. [in mapping of Earth's surface by remote sensing

NASA Technical Reports Server (NTRS)

Kahle, A. B.; Alley, R. E.; Schieldge, J. P.

1984-01-01

The sensitivity of thermal inertia (TI) calculations to errors in the measurement or parameterization of a number of environmental factors is considered here. The factors include effects of radiative transfer in the atmosphere, surface albedo and emissivity, variations in surface turbulent heat flux density, cloud cover, vegetative cover, and topography. The error analysis is based upon data from the Heat Capacity Mapping Mission (HCMM) satellite for July 1978 at three separate test sites in the deserts of the western United States. Results show that typical errors in atmospheric radiative transfer, cloud cover, and vegetative cover can individually cause root-mean-square (RMS) errors of about 10 percent (with atmospheric effects sometimes as large as 30-40 percent) in HCMM-derived thermal inertia images of 20,000-200,000 pixels.

Cold Episodes, Their Precursors and Teleconnections in the Central Peruvian Andes (1958-2009)

NASA Astrophysics Data System (ADS)

Sulca, J. C.; Vuille, M. F.; Trasmonte, G.; Silva, Y.; Takahashi, K.

2014-12-01

The Mantaro valley (MV) is located in the central Peruvian Andes. Occasionally, cold episodes are observed during the austral summer (January-March), which strongly damage crops. However, little is known about the causes and impacts of such cold episodes in the MV. The main goal of this study is thus to characterize cold episodes in the MV and assess their large-scale circulation and teleconnections over South America (SA) during austral summer. To identify cold events in the MV daily minimum temperature for the period 1958-2009 from Huayao station, located within the MV was used. We defined a cold episode as the period when daily minimum temperature drops below the 10-percentile for at least one day. Several gridded reanalysis and satellite products were used to characterize the large-scale circulation, cloud cover and rainfall over SA associated with these events for same period. Cold episodes in the MV are associated with positive OLR anomalies, which extend over much of the central Andes, indicating reduced convective cloud cover during these extremes, but also affirm the large-scale nature of these events. At the same time, northeastern Brazil (NEB) registers negative OLR anomalies, strong convective activity and enhanced cloud cover because displacement of the South Atlantic Convergence Zone (SACZ) toward the northeast of its climatologic position. Further, it is associated with a weakening of the Bolivian High - Nordeste Low (BH-NL) system at upper levels, but also influenced by a low-level migratory high-pressure center develops at 30°S, 50°W; propagating from mid- to low latitudes as part of an extratropical Rossby wave train. In conclusion, cold episodes in the MV appear to be caused by radiative cooling associated with reduced cloudiness, rather than cold air advection. The reduced cloud cover in turn results from a robust large-scale pattern of westerly wind anomalies over central Peruvian Andes, inhibiting moisture influx, convective activity and hence cloud formation. At the same time NEB registers strong convective activity and enhanced cloud cover. This dipole is caused by a weakening of BH-NL system at upper levels, which is associated with a low-level migratory high-pressure center, propagating from mid- to low latitudes as part of an extratropical Rossby wave train.

Earth observations taken from OV-105 during the STS-99 mission

NASA Image and Video Library

2000-02-17

S99-E-5555 (17 February 2000) --- As photographed from the Space Shuttle Endeavour, this oblique electronic still image of Earth's horizon reveals a great deal of cloud cover. In the case of the electronic still camera (ESC), as well as film-bearing instruments, clouds naturally obscure views of recognizable land masses. Much of Earth is heavily cloud covered during the current mission and meteorlogists and oceanographers are interested in studying that aspect. However, the Shuttle Radar Topography Mission's other sensing equipment, X-SAR and C-band antennae, are able to penetrate cloud cover and record important topographic data for mapmakers and scientists of other disciplines. In addition to the sensing equipment mentioned above, this mission is supporting the EarthKAM project which utilizes the services of another electronic still camera mounted in Endeavour's windows. Unlike this oblique view, EarthKAM records strictly vertical or nadir imagery of points all over the world. Students across the United States and in France, Germany and Japan are taking photos throughout the STS-99 mission. And they are using these new photos, plus all the images already available in the EarthKAM system, to enhance their classroom learning in Earth and space science, social studies, geography, mathematics and more.

Derivation of Cloud Heating Rate Profiles using observations of Mixed-Phase Arctic Clouds: Impacts of Solar Zenith Angle

NASA Astrophysics Data System (ADS)

Zhang, G.; McFarquhar, G.; Poellot, M.; Verlinde, J.; Heymsfield, A.; Kok, G.

2005-12-01

Arctic stratus clouds play an important role in the energy balance of the Arctic region. Previous studies have suggested that Arctic stratus persist due to a balance among cloud top radiation cooling, latent heating, ice crystal fall out and large scale forcing. In this study, radiative heating profiles through Arctic stratus are computed using cloud, surface and thermodynamic observations obtained during the Mixed-Phase Arctic Cloud Experiment (M-PACE) as input to the radiative transfer model STREAMER. In particular, microphysical and macrophycial cloud properties such as phase, water content, effective particle size, particle shape, cloud height and cloud thickness were derived using data collected by in-situ sensors on the University of North Dakota (UND) Citation and ground-based remote sensors at Barrow and Oliktok Point. Temperature profiles were derived from radiosonde launches and a fresh snow surface was assumed. One series of sensitivity studies explored the dependence of the heating profile on the solar zenith angle. For smaller solar zenith angles, more incoming solar radiation is received at cloud top acting to counterbalance infrared cooling. As solar zenith angle in the Arctic is large compared to low latitudes, a large solar zenith angle may contribute to the longevity of these clouds.

Validation of On-board Cloud Cover Assessment Using EO-1

NASA Technical Reports Server (NTRS)

Mandl, Dan; Miller, Jerry; Griffin, Michael; Burke, Hsiao-hua

2003-01-01

The purpose of this NASA Earth Science Technology Office funded effort was to flight validate an on-board cloud detection algorithm and to determine the performance that can be achieved with a Mongoose V flight computer. This validation was performed on the EO-1 satellite, which is operational, by uploading new flight code to perform the cloud detection. The algorithm was developed by MIT/Lincoln Lab and is based on the use of the Hyperion hyperspectral instrument using selected spectral bands from 0.4 to 2.5 microns. The Technology Readiness Level (TRL) of this technology at the beginning of the task was level 5 and was TRL 6 upon completion. In the final validation, an 8 second (0.75 Gbytes) Hyperion image was processed on-board and assessed for percentage cloud cover within 30 minutes. It was expected to take many hours and perhaps a day considering that the Mongoose V is only a 6-8 MIP machine in performance. To accomplish this test, the image taken had to have level 0 and level 1 processing performed on-board before the cloud algorithm was applied. For almost all of the ground test cases and all of the flight cases, the cloud assessment was within 5% of the correct value and in most cases within 1-2%.

Laser Pulse Bidirectional Reflectance from CALIPSO Mission

NASA Technical Reports Server (NTRS)

Lu, Xiaomei; Hu, Yongxiang; Yang, Yuekui; Liu, Zhaoyan; Vaughan, Mark; Lucker, Patricia; Trepte, Charles

2017-01-01

In this Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO) study, we present a simple way of determining laser pulse bidirectional reflectance over snow/ice surface using the Cloud-Aerosol LIdar with Orthogonal Polarization (CALIOP) 532 nanometer polarization channels' measurements. The saturated laser pulse returns from snow and ice surfaces are recovered based on surface tail information. The method overview and initial assessment of the method performance will be presented. The retrieved snow surface bidirectional reflectance is compared with reflectance from both CALIOP cloud cover regions and Moderate Resolution Imaging Spectroradiometer (Earth Observing System (EOS)) (MODIS) Bi-directional Reflectance Distribution Function (BRDF) / Albedo model parameters. The comparisons show that the snow surface bidirectional reflectance over Antarctica for saturation region are generally reliable with a mean value of about 0.90 plus or minus 0.10, while the mean surface reflectance from cloud cover region is about 0.84 plus or minus 0.13 and the calculated MODIS reflectance at 555 nanometers from the BRDF / Albedo model with near nadir illumination and viewing angles is about 0.96 plus or minus 0.04. The comparisons here demonstrate that the snow surface reflectance underneath the cloud with cloud optical depth of about 1 is significantly lower than that for a clear sky condition.

Theoretical Accuracy of Global Snow-Cover Mapping Using Satellite Data in the Earth Observing System (EOS) Era

NASA Technical Reports Server (NTRS)

Hall, D. K.; Foster, J. L.; Salomonson, V. V.; Klein, A. G.; Chien, J. Y. L.

1998-01-01

Following the launch of the Earth Observing System first morning (EOS-AM1) satellite, daily, global snow-cover mapping will be performed automatically at a spatial resolution of 500 m, cloud-cover permitting, using Moderate Resolution Imaging Spectroradiometer (MODIS) data. A technique to calculate theoretical accuracy of the MODIS-derived snow maps is presented. Field studies demonstrate that under cloud-free conditions when snow cover is complete, snow-mapping errors are small (less than 1%) in all land covers studied except forests where errors are greater and more variable. The theoretical accuracy of MODIS snow-cover maps is largely determined by percent forest cover north of the snowline. Using the 17-class International Geosphere-Biosphere Program (IGBP) land-cover maps of North America and Eurasia, the Northern Hemisphere is classified into seven land-cover classes and water. Snow-mapping errors estimated for each of the seven land-cover classes are extrapolated to the entire Northern Hemisphere for areas north of the average continental snowline for each month. Average monthly errors for the Northern Hemisphere are expected to range from 5 - 10%, and the theoretical accuracy of the future global snow-cover maps is 92% or higher. Error estimates will be refined after the first full year that MODIS data are available.

Image processing methods in two and three dimensions used to animate remotely sensed data. [cloud cover

NASA Technical Reports Server (NTRS)

Hussey, K. J.; Hall, J. R.; Mortensen, R. A.

1986-01-01

Image processing methods and software used to animate nonimaging remotely sensed data on cloud cover are described. Three FORTRAN programs were written in the VICAR2/TAE image processing domain to perform 3D perspective rendering, to interactively select parameters controlling the projection, and to interpolate parameter sets for animation images between key frames. Operation of the 3D programs and transferring the images to film is automated using executive control language and custom hardware to link the computer and camera.

CERES FM6 First Light Imagery

Atmospheric Science Data Center

2018-06-07

... Larger Image   Clouds and the Earth's Radiant Energy System Flight Model 6 (CERES FM6) opened its cover on Jan. 5, 2018 ... radiometer that NASA/NOAA has flown that measures the solar energy reflected by Earth, heat the planet emits, and the role of clouds in ...

Sun tracker for clear or cloudy weather

NASA Technical Reports Server (NTRS)

Scott, D. R.; White, P. R.

1979-01-01

Sun tracker orients solar collector so that they absorb maximum possible sunlight without being fooled by bright clouds, holes in cloud cover, or other atmospheric conditions. Tracker follows sun within 0.25 deg arc and is accurate within + or - 5 deg when sun is hidden.

Positive tropical marine low-cloud cover feedback inferred from cloud-controlling factors

DOE PAGES

Qu, Xin; Hall, Alex; Klein, Stephen A.; ...

2015-09-28

Differences in simulations of tropical marine low-cloud cover (LCC) feedback are sources of significant spread in temperature responses of climate models to anthropogenic forcing. Here we show that in models the feedback is mainly driven by three large-scale changes—a strengthening tropical inversion, increasing surface latent heat flux, and an increasing vertical moisture gradient. Variations in the LCC response to these changes alone account for most of the spread in model-projected 21st century LCC changes. A methodology is devised to constrain the LCC response observationally using sea surface temperature (SST) as a surrogate for the latent heat flux and moisture gradient.more » In models where the current climate's LCC sensitivities to inversion strength and SST variations are consistent with observed, LCC decreases systematically, which would increase absorption of solar radiation. These results support a positive LCC feedback. Finally, correcting biases in the sensitivities will be an important step toward more credible simulation of cloud feedbacks.« less

New insight of Arctic cloud parameterization from regional climate model simulations, satellite-based, and drifting station data

NASA Astrophysics Data System (ADS)

Klaus, D.; Dethloff, K.; Dorn, W.; Rinke, A.; Wu, D. L.

2016-05-01

Cloud observations from the CloudSat and CALIPSO satellites helped to explain the reduced total cloud cover (Ctot) in the atmospheric regional climate model HIRHAM5 with modified cloud physics. Arctic climate conditions are found to be better reproduced with (1) a more efficient Bergeron-Findeisen process and (2) a more generalized subgrid-scale variability of total water content. As a result, the annual cycle of Ctot is improved over sea ice, associated with an almost 14% smaller area average than in the control simulation. The modified cloud scheme reduces the Ctot bias with respect to the satellite observations. Except for autumn, the cloud reduction over sea ice improves low-level temperature profiles compared to drifting station data. The HIRHAM5 sensitivity study highlights the need for improving accuracy of low-level (<700 m) cloud observations, as these clouds exert a strong impact on the near-surface climate.

The relationship between interannual and long-term cloud feedbacks

DOE PAGES

Zhou, Chen; Zelinka, Mark D.; Dessler, Andrew E.; ...

2015-12-11

The analyses of Coupled Model Intercomparison Project phase 5 simulations suggest that climate models with more positive cloud feedback in response to interannual climate fluctuations also have more positive cloud feedback in response to long-term global warming. Ensemble mean vertical profiles of cloud change in response to interannual and long-term surface warming are similar, and the ensemble mean cloud feedback is positive on both timescales. However, the average long-term cloud feedback is smaller than the interannual cloud feedback, likely due to differences in surface warming pattern on the two timescales. Low cloud cover (LCC) change in response to interannual andmore » long-term global surface warming is found to be well correlated across models and explains over half of the covariance between interannual and long-term cloud feedback. In conclusion, the intermodel correlation of LCC across timescales likely results from model-specific sensitivities of LCC to sea surface warming.« less

Cloudy Earth

NASA Image and Video Library

2015-05-08

Decades of satellite observations and astronaut photographs show that clouds dominate space-based views of Earth. One study based on nearly a decade of satellite data estimated that about 67 percent of Earth’s surface is typically covered by clouds. This is especially the case over the oceans, where other research shows less than 10 percent of the sky is completely clear of clouds at any one time. Over land, 30 percent of skies are completely cloud free. Earth’s cloudy nature is unmistakable in this global cloud fraction map, based on data collected by the Moderate Resolution Imaging Spectroradiometer (MODIS) on the Aqua satellite. While MODIS collects enough data to make a new global map of cloudiness every day, this version of the map shows an average of all of the satellite’s cloud observations between July 2002 and April 2015. Colors range from dark blue (no clouds) to light blue (some clouds) to white (frequent clouds).

A Jovian Hotspot in True and False Colors (Time set 1)

NASA Technical Reports Server (NTRS)

1997-01-01

True and false color views of an equatorial 'hotspot' on Jupiter. These images cover an area 34,000 kilometers by 11,000 kilometers. The top mosaic combines the violet (410 nanometers or nm) and near-infrared continuum (756 nm) filter images to create an image similar to how Jupiter would appear to human eyes. Differences in coloration are due to the composition and abundances of trace chemicals in Jupiter's atmosphere. The bottom mosaic uses Galileo's three near-infrared wavelengths (756 nm, 727 nm, and 889 nm displayed in red, green, and blue) to show variations in cloud height and thickness. Bluish clouds are high and thin, reddish clouds are low, and white clouds are high and thick. The dark blue hotspot in the center is a hole in the deep cloud with an overlying thin haze. The light blue region to the left is covered by a very high haze layer. The multicolored region to the right has overlapping cloud layers of different heights. Galileo is the first spacecraft to distinguish cloud layers on Jupiter.

North is at the top. The mosaics cover latitudes 1 to 10 degrees and are centered at longitude 336 degrees West. The smallest resolved features are tens of kilometers in size. These images were taken on December 17, 1996, at a range of 1.5 million kilometers by the Solid State Imaging system aboard NASA's Galileo spacecraft.

The Jet Propulsion Laboratory, Pasadena, CA manages the mission for NASA's Office of Space Science, Washington, DC.

This image and other images and data received from Galileo are posted on the World Wide Web, on the Galileo mission home page at URL http://galileo.jpl.nasa.gov. Background information and educational context for the images can be found at URL http://www.jpl.nasa.gov/galileo/sepo

An A-Train Climatology of Extratropical Cyclone Clouds

NASA Technical Reports Server (NTRS)

Posselt, Derek J.; van den Heever, Susan C.; Booth, James F.; Del Genio, Anthony D.; Kahn, Brian; Bauer, Mike

2016-01-01

Extratropical cyclones (ETCs) are the main purveyors of precipitation in the mid-latitudes, especially in winter, and have a significant radiative impact through the clouds they generate. However, general circulation models (GCMs) have trouble representing precipitation and clouds in ETCs, and this might partly explain why current GCMs disagree on to the evolution of these systems in a warming climate. Collectively, the A-train observations of MODIS, CloudSat, CALIPSO, AIRS and AMSR-E have given us a unique perspective on ETCs: over the past 10 years these observations have allowed us to construct a climatology of clouds and precipitation associated with these storms. This has proved very useful for model evaluation as well in studies aimed at improving understanding of moist processes in these dynamically active conditions. Using the A-train observational suite and an objective cyclone and front identification algorithm we have constructed cyclone centric datasets that consist of an observation-based characterization of clouds and precipitation in ETCs and their sensitivity to large scale environments. In this presentation, we will summarize the advances in our knowledge of the climatological properties of cloud and precipitation in ETCs acquired with this unique dataset. In particular, we will present what we have learned about southern ocean ETCs, for which the A-train observations have filled a gap in this data sparse region. In addition, CloudSat and CALIPSO have for the first time provided information on the vertical distribution of clouds in ETCs and across warm and cold fronts. We will also discuss how these observations have helped identify key areas for improvement in moist processes in recent GCMs. Recently, we have begun to explore the interaction between aerosol and cloud cover in ETCs using MODIS, CloudSat and CALIPSO. We will show how aerosols are climatologically distributed within northern hemisphere ETCs, and how this relates to cloud cover.

Microphysical and macrophysical responses of marine stratocumulus polluted by underlying ships

NASA Astrophysics Data System (ADS)

Christensen, Matthew Wells

Multiple sensors flying in the A-train constellation of satellites were used to determine the extent to which aerosol plumes from ships passing below marine stratocumulus alter the microphysical and macrophysical properties of the clouds. Aerosol plumes generated by ships sometimes influence cloud microphysical properties (effective radius) and, to a largely undetermined extent, cloud macrophysical properties (liquid water path, coverage, depth, precipitation, and longevity). Aerosol indirect effects were brought into focus, using observations from the Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) and the 94-GHZ radar onboard CloudSat. To assess local cloud scale responses to aerosol, the locations of over one thousand ship tracks coinciding with the radar were meticulously logged by hand from the Moderate Resolution Imaging Spectroradiometer (MODIS) imagery. MODIS imagery was used to distinguish ship tracks that were embedded in closed, open, and unclassifiable mesoscale cellular cloud structures. The impact of aerosol on the microphysical cloud properties in both the closed and open cell regimes were consistent with the changes predicted by the Twomey hypothesis. For the macrophysical changes, differences in the sign and magnitude of these properties were observed between cloud regimes. The results demonstrate that the spatial extent of rainfall (rain cover fraction) and intensity decrease in the clouds contaminated by the ship plume compared to the ambient pristine clouds. Although reductions of precipitation were common amongst the clouds with detectable rainfall (72% of cases), a substantial fraction of ship tracks (28% of cases) exhibited the opposite response. The sign and strength of the response was tied to the type of stratocumulus (e.g., closed vs open cells), depth of the boundary layer, and humidity in the free-troposphere. When closed cellular clouds were identified, liquid water path, drizzle rate, and rain cover fraction (an average relative decrease of 61%) was significantly smaller in the ship-contaminated clouds. Differences in drizzle rate resulted primarily from the reductions in rain cover fraction (i.e., fewer pixels were identified with rain in the clouds polluted by the ship). The opposite occurred in the open cell regime. Ship plumes ingested into this regime resulted in significantly deeper and brighter clouds with higher liquid water amounts and rain rates. Enhanced rain rates (average relative increase of 89%) were primarily due to the changes in intensity (i.e., rain rates on the 1.1 km pixel scale were higher in the ship contaminated clouds) and, to a lesser extent, rain cover fraction. One implication for these differences is that the local aerosol indirect radiative forcing was more than five times larger for ship tracks observed in the open cell regime (-59 W m-2) compared to those identified in the closed cell regime (-12 W m -2). The results presented here underline the need to consider the mesoscale structure of stratocumulus when examining the cloud dynamic response to changes in aerosol concentration. In the final part of the dissertation, the focus shifted to the climate scale to examine the impact of shipping on the Earth's radiation budget. Two studies were employed, in the first; changes to the radiative properties of boundary layer clouds (i.e., cloud top heights less than 3 km) were examined in response to the substantial decreases in ship traffic that resulted from the recent world economic recession in 2008. Differences in the annually averaged droplet effective radius and top of atmosphere outgoing shortwave radiative flux between 2007 and 2009 did not manifest as a clear response in the climate system and, was probably masked either due to competing aerosol cloud feedbacks or by interannual climate variability. In the second study, a method was developed to estimate the radiative forcing from shipping by convolving lanes of densely populated ships onto the global distributions of closed and open cell stratocumulus clouds. Closed cells were observed more than twice as often as open cells. Despite the smaller abundance of open cells, a significant portion of the radiaitve forcing from shipping was claimed by this regime. On the whole, the global radiative forcing from ship tracks was small (approximately -0.45 mW m-2) compared to the radiative forcing associated with the atmospheric buildup of anthropogenic CO2.

a Cloud Boundary Detection Scheme Combined with Aslic and Cnn Using ZY-3, GF-1/2 Satellite Imagery

NASA Astrophysics Data System (ADS)

Guo, Z.; Li, C.; Wang, Z.; Kwok, E.; Wei, X.

2018-04-01

Remote sensing optical image cloud detection is one of the most important problems in remote sensing data processing. Aiming at the information loss caused by cloud cover, a cloud detection method based on convolution neural network (CNN) is presented in this paper. Firstly, a deep CNN network is used to extract the multi-level feature generation model of cloud from the training samples. Secondly, the adaptive simple linear iterative clustering (ASLIC) method is used to divide the detected images into superpixels. Finally, the probability of each superpixel belonging to the cloud region is predicted by the trained network model, thereby generating a cloud probability map. The typical region of GF-1/2 and ZY-3 were selected to carry out the cloud detection test, and compared with the traditional SLIC method. The experiment results show that the average accuracy of cloud detection is increased by more than 5 %, and it can detected thin-thick cloud and the whole cloud boundary well on different imaging platforms.

3D Radiative Aspects of the Increased Aerosol Optical Depth Near Clouds

NASA Technical Reports Server (NTRS)

Marshak, Alexander; Wen, Guoyong; Remer, Lorraine; Cahalan, Robert; Coakley, Jim

2007-01-01

To characterize aerosol-cloud interactions it is important to correctly retrieve aerosol optical depth in the vicinity of clouds. It is well reported in the literature that aerosol optical depth increases with cloud cover. Part of the increase comes from real physics as humidification; another part, however, comes from 3D cloud effects in the remote sensing retrievals. In many cases it is hard to say whether the retrieved increased values of aerosol optical depth are remote sensing artifacts or real. In the presentation, we will discuss how the 3D cloud affects can be mitigated. We will demonstrate a simple model that can assess the enhanced illumination of cloud-free columns in the vicinity of clouds. This model is based on the assumption that the enhancement in the cloud-free column radiance comes from the enhanced Rayleigh scattering due to presence of surrounding clouds. A stochastic cloud model of broken cloudiness is used to simulate the upward flux.

Identifying clouds over the Pierre Auger Observatory using infrared satellite data

NASA Astrophysics Data System (ADS)

Abreu, P.; Aglietta, M.; Ahlers, M.; Ahn, E. J.; Albuquerque, I. F. M.; Allekotte, I.; Allen, J.; Allison, P.; Almela, A.; Alvarez Castillo, J.; Alvarez-Muñiz, J.; Alves Batista, R.; Ambrosio, M.; Aminaei, A.; Anchordoqui, L.; Andringa, S.; Antičić, T.; Aramo, C.; Arqueros, F.; Asorey, H.; Assis, P.; Aublin, J.; Ave, M.; Avenier, M.; Avila, G.; Badescu, A. M.; Barber, K. B.; Barbosa, A. F.; Bardenet, R.; Baughman, B.; Bäuml, J.; Baus, C.; Beatty, J. J.; Becker, K. H.; Bellétoile, A.; Bellido, J. A.; BenZvi, S.; Berat, C.; Bertou, X.; Biermann, P. L.; Billoir, P.; Blanco, F.; Blanco, M.; Bleve, C.; Blümer, H.; Boháčová, M.; Boncioli, D.; Bonifazi, C.; Bonino, R.; Borodai, N.; Brack, J.; Brancus, I.; Brogueira, P.; Brown, W. C.; Buchholz, P.; Bueno, A.; Buroker, L.; Burton, R. E.; Buscemi, M.; Caballero-Mora, K. S.; Caccianiga, B.; Caccianiga, L.; Caramete, L.; Caruso, R.; Castellina, A.; Cataldi, G.; Cazon, L.; Cester, R.; Cheng, S. H.; Chiavassa, A.; Chinellato, J. A.; Chirinos, J.; Chudoba, J.; Cilmo, M.; Clay, R. W.; Cocciolo, G.; Colalillo, R.; Collica, L.; Coluccia, M. R.; Conceição, R.; Contreras, F.; Cook, H.; Cooper, M. J.; Coutu, S.; Covault, C. E.; Criss, A.; Cronin, J.; Curutiu, A.; Dallier, R.; Daniel, B.; Dasso, S.; Daumiller, K.; Dawson, B. R.; de Almeida, R. M.; De Domenico, M.; de Jong, S. J.; De La Vega, G.; de Mello, W. J. M.; de Mello Neto, J. R. T.; De Mitri, I.; de Souza, V.; de Vries, K. D.; del Peral, L.; Deligny, O.; Dembinski, H.; Dhital, N.; Di Giulio, C.; Diaz, J. C.; Díaz Castro, M. L.; Diep, P. N.; Diogo, F.; Dobrigkeit, C.; Docters, W.; D'Olivo, J. C.; Dong, P. N.; Dorofeev, A.; dos Anjos, J. C.; Dova, M. T.; D'Urso, D.; Ebr, J.; Engel, R.; Erdmann, M.; Escobar, C. O.; Espadanal, J.; Etchegoyen, A.; Facal San Luis, P.; Falcke, H.; Fang, K.; Farrar, G.; Fauth, A. C.; Fazzini, N.; Ferguson, A. P.; Fick, B.; Figueira, J. M.; Filevich, A.; Filipčič, A.; Fliescher, S.; Fox, B. D.; Fracchiolla, C. E.; Fraenkel, E. D.; Fratu, O.; Fröhlich, U.; Fuchs, B.; Gaior, R.; Gamarra, R. F.; Gambetta, S.; García, B.; Garcia Roca, S. T.; Garcia-Gamez, D.; Garcia-Pinto, D.; Garilli, G.; Gascon Bravo, A.; Gemmeke, H.; Ghia, P. L.; Giller, M.; Gitto, J.; Glaser, C.; Glass, H.; Golup, G.; Gomez Albarracin, F.; Gómez Berisso, M.; Gómez Vitale, P. F.; Gonçalves, P.; Gonzalez, J. G.; Gookin, B.; Gorgi, A.; Gorham, P.; Gouffon, P.; Grebe, S.; Griffith, N.; Grillo, A. F.; Grubb, T. D.; Guardincerri, Y.; Guarino, F.; Guedes, G. P.; Hansen, P.; Harari, D.; Harrison, T. A.; Harton, J. L.; Haungs, A.; Hebbeker, T.; Heck, D.; Herve, A. E.; Hill, G. C.; Hojvat, C.; Hollon, N.; Holmes, V. C.; Homola, P.; Hörandel, J. R.; Horvath, P.; Hrabovský, M.; Huber, D.; Huege, T.; Insolia, A.; Jansen, S.; Jarne, C.; Jiraskova, S.; Josebachuili, M.; Kadija, K.; Kampert, K. H.; Karhan, P.; Kasper, P.; Katkov, I.; Kégl, B.; Keilhauer, B.; Keivani, A.; Kelley, J. L.; Kemp, E.; Kieckhafer, R. M.; Klages, H. O.; Kleifges, M.; Kleinfeller, J.; Knapp, J.; Krause, R.; Krohm, N.; Krömer, O.; Kruppke-Hansen, D.; Kuempel, D.; Kulbartz, J. K.; Kunka, N.; La Rosa, G.; LaHurd, D.; Latronico, L.; Lauer, R.; Lauscher, M.; Lautridou, P.; Le Coz, S.; Leão, M. S. A. B.; Lebrun, D.; Lebrun, P.; Leigui de Oliveira, M. A.; Letessier-Selvon, A.; Lhenry-Yvon, I.; Link, K.; López, R.; Lopez Agüera, A.; Louedec, K.; Lozano Bahilo, J.; Lu, L.; Lucero, A.; Ludwig, M.; Lyberis, H.; Maccarone, M. C.; Macolino, C.; Malacari, M.; Maldera, S.; Maller, J.; Mandat, D.; Mantsch, P.; Mariazzi, A. G.; Marin, J.; Marin, V.; Mariş, I. C.; Marquez Falcon, H. R.; Marsella, G.; Martello, D.; Martin, L.; Martinez, H.; Martínez Bravo, O.; Martraire, D.; Masías Meza, J. J.; Mathes, H. J.; Matthews, J.; Matthews, J. A. J.; Matthiae, G.; Maurel, D.; Maurizio, D.; Mayotte, E.; Mazur, P. O.; Medina-Tanco, G.; Melissas, M.; Melo, D.; Menichetti, E.; Menshikov, A.; Messina, S.; Meyhandan, R.; Mićanović, S.; Micheletti, M. I.; Middendorf, L.; Minaya, I. A.; Miramonti, L.; Mitrica, B.; Molina-Bueno, L.; Mollerach, S.; Monasor, M.; Monnier Ragaigne, D.; Montanet, F.; Morales, B.; Morello, C.; Moreno, J. C.; Mostafá, M.; Moura, C. A.; Muller, M. A.; Müller, G.; Münchmeyer, M.; Mussa, R.; Navarra, G.; Navarro, J. L.; Navas, S.; Necesal, P.; Nellen, L.; Nelles, A.; Neuser, J.; Nhung, P. T.; Niechciol, M.; Niemietz, L.; Nierstenhoefer, N.; Niggemann, T.; Nitz, D.; Nosek, D.; Nožka, L.; Oehlschläger, J.; Olinto, A.; Oliveira, M.; Ortiz, M.; Pacheco, N.; Pakk Selmi-Dei, D.; Palatka, M.; Pallotta, J.; Palmieri, N.; Parente, G.; Parra, A.; Pastor, S.; Paul, T.; Pech, M.; Peķala, J.; Pelayo, R.; Pepe, I. M.; Perrone, L.; Pesce, R.; Petermann, E.; Petrera, S.; Petrolini, A.; Petrov, Y.; Pfendner, C.; Piegaia, R.; Pierog, T.; Pieroni, P.; Pimenta, M.; Pirronello, V.; Platino, M.; Plum, M.; Ponce, V. H.; Pontz, M.; Porcelli, A.; Privitera, P.; Prouza, M.; Quel, E. J.; Querchfeld, S.; Rautenberg, J.; Ravel, O.; Ravignani, D.; Revenu, B.; Ridky, J.; Riggi, S.; Risse, M.; Ristori, P.; Rivera, H.; Rizi, V.; Roberts, J.; Rodrigues de Carvalho, W.; Rodriguez Cabo, I.; Rodriguez Fernandez, G.; Rodriguez Martino, J.; Rodriguez Rojo, J.; Rodríguez-Frías, M. D.; Ros, G.; Rosado, J.; Rossler, T.; Roth, M.; Rouillé-d'Orfeuil, B.; Roulet, E.; Rovero, A. C.; Rühle, C.; Saffi, S. J.; Saftoiu, A.; Salamida, F.; Salazar, H.; Salesa Greus, F.; Salina, G.; Sánchez, F.; Santo, C. E.; Santos, E.; Santos, E. M.; Sarazin, F.; Sarkar, B.; Sato, R.; Scharf, N.; Scherini, V.; Schieler, H.; Schiffer, P.; Schmidt, A.; Scholten, O.; Schoorlemmer, H.; Schovancova, J.; Schovánek, P.; Schröder, F. G.; Schulz, J.; Schuster, D.; Sciutto, S. J.; Scuderi, M.; Segreto, A.; Settimo, M.; Shadkam, A.; Shellard, R. C.; Sidelnik, I.; Sigl, G.; Sima, O.; Śmiałkowski, A.; Šmída, R.; Snow, G. R.; Sommers, P.; Sorokin, J.; Spinka, H.; Squartini, R.; Srivastava, Y. N.; Stanič, S.; Stapleton, J.; Stasielak, J.; Stephan, M.; Straub, M.; Stutz, A.; Suarez, F.; Suomijärvi, T.; Supanitsky, A. D.; Šuša, T.; Sutherland, M. S.; Swain, J.; Szadkowski, Z.; Szuba, M.; Tapia, A.; Tartare, M.; Taşcău, O.; Tcaciuc, R.; Thao, N. T.; Thomas, D.; Tiffenberg, J.; Timmermans, C.; Tkaczyk, W.; Todero Peixoto, C. J.; Toma, G.; Tomankova, L.; Tomé, B.; Tonachini, A.; Torralba Elipe, G.; Torres Machado, D.; Travnicek, P.; Tridapalli, D. B.; Trovato, E.; Tueros, M.; Ulrich, R.; Unger, M.; Urban, M.; Valdés Galicia, J. F.; Valiño, I.; Valore, L.; van Aar, G.; van den Berg, A. M.; van Velzen, S.; van Vliet, A.; Varela, E.; Vargas Cárdenas, B.; Varner, G.; Vázquez, J. R.; Vázquez, R. A.; Veberič, D.; Verzi, V.; Vicha, J.; Videla, M.; Villaseñor, L.; Wahlberg, H.; Wahrlich, P.; Wainberg, O.; Walz, D.; Watson, A. A.; Weber, M.; Weidenhaupt, K.; Weindl, A.; Werner, F.; Westerhoff, S.; Whelan, B. J.; Widom, A.; Wieczorek, G.; Wiencke, L.; Wilczyńska, B.; Wilczyński, H.; Will, M.; Williams, C.; Winchen, T.; Wundheiler, B.; Yamamoto, T.; Yapici, T.; Younk, P.; Yuan, G.; Yushkov, A.; Zamorano Garcia, B.; Zas, E.; Zavrtanik, D.; Zavrtanik, M.; Zaw, I.; Zepeda, A.; Zhou, J.; Zhu, Y.; Zimbres Silva, M.; Ziolkowski, M.

2013-12-01

We describe a new method of identifying night-time clouds over the Pierre Auger Observatory using infrared data from the Imager instruments on the GOES-12 and GOES-13 satellites. We compare cloud identifications resulting from our method to those obtained by the Central Laser Facility of the Auger Observatory. Using our new method we can now develop cloud probability maps for the 3000 km2 of the Pierre Auger Observatory twice per hour with a spatial resolution of ˜2.4 km by ˜5.5 km. Our method could also be applied to monitor cloud cover for other ground-based observatories and for space-based observatories.

Determination of cloud fields from analysis of HIRS2/MSU sounding data. [20 channel infrared and 4 channel microwave atmospheric sounders

NASA Technical Reports Server (NTRS)

Susskind, J.; Reuter, D.

1986-01-01

IR and microwave remote sensing data collected with the HIRS2 and MSU sensors on the NOAA polar-orbiting satellites were evaluated for their effectiveness as bases for determining the cloud cover and cloud physical characteristics. Techniques employed to adjust for day-night alterations in the radiance fields are described, along with computational procedures applied to compare scene pixel values with reference values for clear skies. Sample results are provided for the mean cloud coverage detected over South America and Africa June 1979, with attention given to concurrent surface pressure and cloud top pressure values.

Identifying clouds over the Pierre Auger Observatory using infrared satellite data

DOE Office of Scientific and Technical Information (OSTI.GOV)

Abreu, Pedro; et al.,

2013-12-01

We describe a new method of identifying night-time clouds over the Pierre Auger Observatory using infrared data from the Imager instruments on the GOES-12 and GOES-13 satellites. We compare cloud identifications resulting from our method to those obtained by the Central Laser Facility of the Auger Observatory. Using our new method we can now develop cloud probability maps for the 3000 km^2 of the Pierre Auger Observatory twice per hour with a spatial resolution of ~2.4 km by ~5.5 km. Our method could also be applied to monitor cloud cover for other ground-based observatories and for space-based observatories.

Titan Mystery Clouds

NASA Image and Video Library

2016-12-21

This comparison of two views from NASA's Cassini spacecraft, taken fairly close together in time, illustrates a peculiar mystery: Why would clouds on Saturn's moon Titan be visible in some images, but not in others? In the top view, a near-infrared image from Cassini's imaging cameras, the skies above Saturn's moon Titan look relatively cloud free. But in the bottom view, at longer infrared wavelengths, Cassini sees a large field of bright clouds. Even though these views were taken at different wavelengths, researchers would expect at least a hint of the clouds to show up in the upper image. Thus they have been trying to understand what's behind the difference. As northern summer approaches on Titan, atmospheric models have predicted that clouds will become more common at high northern latitudes, similar to what was observed at high southern latitudes during Titan's late southern summer in 2004. Cassini's Imaging Science Subsystem (ISS) and Visual and Infrared Mapping Spectrometer (VIMS) teams have been observing Titan to document changes in weather patterns as the seasons change, and there is particular interest in following the onset of clouds in the north polar region where Titan's lakes and seas are concentrated. Cassini's "T120" and "T121" flybys of Titan, on June 7 and July 25, 2016, respectively, provided views of high northern latitudes over extended time periods -- more than 24 hours during both flybys. Intriguingly, the ISS and VIMS observations appear strikingly different from each other. In the ISS observations (monochrome image at top), surface features are easily identifiable and only a few small, isolated clouds were detected. In contrast, the VIMS observations (color image at bottom) suggest widespread cloud cover during both flybys. The observations were made over the same time period, so differences in illumination geometry or changes in the clouds themselves are unlikely to be the cause for the apparent discrepancy: VIMS shows persistent atmospheric features over the entire observation period and ISS consistently detects surface features with just a few localized clouds. The answer to what could be causing the discrepancy appears to lie with Titan's hazy atmosphere, which is much easier to see through at the longer infrared wavelengths that VIMS is sensitive to (up to 5 microns) than at the shorter, near-infrared wavelength used by ISS to image Titan's surface and lower atmosphere (0.94 microns). High, thin cirrus clouds that are optically thicker than the atmospheric haze at longer wavelengths, but optically thinner than the haze at the shorter wavelength of the ISS observations, could be detected by VIMS and simultaneously lost in the haze to ISS -- similar to trying to see a thin cloud layer on a hazy day on Earth. This phenomenon has not been seen again since July 2016, but Cassini has several more opportunities to observe Titan over the last months of the mission in 2017, and scientists will be watching to see if and how the weather changes. These two images were taken as part of the T120 flyby on June 7 (VIMS) and 8 (ISS), 2016. The distance to Titan was about 28,000 miles (45,000 kilometers) for the VIMS image and about 398,000 miles (640,000 kilometers) for the ISS image. The VIMS image has been processed to enhance the visibility of the clouds; in this false-color view, clouds appear nearly white, atmospheric haze is pink, and surface areas would appear green. http://photojournal.jpl.nasa.gov/catalog/PIA21054

Aerosol and Cloud Microphysical Characteristics of Rifts and Gradients in Maritime Stratocumulus Clouds

NASA Technical Reports Server (NTRS)

Sharon, Tarah M.; Albrecht, Bruce A.; Jonsson, Haflidi H.; Minnis, Patrick; Khaiyer, Mandana M.; Van Reken, Timothy; Seinfeld, John; Flagan, Rick

2008-01-01

A cloud rift is characterized as a large-scale, persistent area of broken, low reflectivity stratocumulus clouds usually surrounded by a solid deck of stratocumulus. A rift observed off the coast of Monterey Bay, California on 16 July 1999 was studied to compare the aerosol and cloud microphysical properties in the rift with those of the surrounding solid stratus deck. Variables measured from an instrumented aircraft included temperature, water vapor, and cloud liquid water. These measurements characterized the thermodynamic properties of the solid deck and rift areas. Microphysical measurements made included aerosol, cloud drop and drizzle drop concentrations and cloud condensation nuclei (CCN) concentrations. The microphysical characteristics in a solid stratus deck differ substantially from those of a broken, cellular rift where cloud droplet concentrations are a factor of 2 lower than those in the solid cloud. Further, CCN concentrations were found to be about 3 times greater in the solid cloud area compared with those in the rift and aerosol concentrations showed a similar difference as well. Although drizzle was observed near cloud top in parts of the solid stratus cloud, the largest drizzle rates were associated with the broken clouds within the rift area. In addition to marked differences in particle concentrations, evidence of a mesoscale circulation near the solid cloud rift boundary is presented. This mesoscale circulation provides a mechanism for maintaining a rift, but further study is required to understand the initiation of a rift and the conditions that may cause it to fill.

Do Southern Ocean Cloud Feedbacks Matter for 21st Century Warming?

NASA Astrophysics Data System (ADS)

Frey, W. R.; Maroon, E. A.; Pendergrass, A. G.; Kay, J. E.

2017-12-01

Cloud phase improvements in a state-of-the-art climate model produce a large 1.5 K increase in equilibrium climate sensitivity (ECS, the surface warming in response to instantaneously doubled CO2) via extratropical shortwave cloud feedbacks. Here we show that the same model improvements produce only a small surface warming increase in a realistic 21st century emissions scenario. The small 21st century warming increase is attributed to extratropical ocean heat uptake. Southern Ocean mean-state circulation takes up heat while a slowdown in North Atlantic circulation acts as a feedback to slow surface warming. Persistent heat uptake by extratropical oceans implies that extratropical cloud biases may not be as important to 21st century warming as biases in other regions. Observational constraints on cloud phase and shortwave radiation that produce a large ECS increase do not imply large changes in 21st century warming.

Variability of cirrus clouds in a convective outflow during the Hibiscus campaign

NASA Astrophysics Data System (ADS)

Fierli, F.; di Donfrancesco, G.; Cairo, F.; Marécal, V.; Zampieri, M.; Orlandi, E.; Durry, G.

2008-08-01

Light-weight microlidar and water vapour measurements were taken on-board a stratospheric balloon during the HIBISCUS 2004 campaign, held in Bauru, Brazil (49° W, 22° S). Cirrus clouds were observed throughout the flight between 12 and 15 km height with a high mesoscale variability in optical and microphysical properties. It was found that the cirrus clouds were composed of different layers characterized by marked differences in height, thickness and optical properties. Simultaneous water vapour observations show that the different layers are characterized by different values of the saturation with respect to ice. A mesoscale simulation and a trajectory analysis clearly revealed that the clouds had formed in the outflow of a large and persistent convective region and that the observed variability of the optical properties and of the cloud structure is likely linked to the different residence times of the convectively-processed air in the upper troposphere.

Use of ARM Products in Reanalysis Applications and IPCC Model Assessment

DOE Office of Scientific and Technical Information (OSTI.GOV)

Walsh, John E; Chapman, William L

2011-09-30

Year-3 of the project was spent developing an observed cloud climatology for Barrow, AK and relating the observed cloud fractions to the surface circulation patterns and locally observed winds. Armed with this information, we identified errors and sources of errors of cloud fraction simulations by numerical models in the Arctic. Specifically, we compared the cloud simulations output by the North American Regional Reanalysis (NARR) to corresponding observed cloud fractions obtained by the Department of Energy's Atmospheric Radiation Measurement (ARM) program for four mid-season months: (January, April, July, and October). Reanalyses are obtained from numerical weather prediction models that are notmore » run in real-time. Instead, a reanalysis model ingests a wide variety of historical observations for the purpose of producing a gridded dataset of many model-derived quantities that are as temporally homogeneous as possible. Therefore, reanalysis output can be used as a proxy for observations, although some biases and other errors are inevitable because of model parameterizations and observational gaps. In the observational analysis we documented the seasonality of cloudiness at the north slope including cloud base height and dependence on synoptic regime. We followed this with an evaluation of the associations of wind-speed and direction and cloud amounts in both the observational record and the reanalysis model. The Barrow cloud fraction data show that clear conditions are most often associated with anomalous high pressure to the north of Barrow, especially in spring and early summer. Overcast skies are most commonly associated with anomalous low pressure to the south. The observational analysis shows that low, boundary layer clouds are the most common type of cloud observed North Slope ARM observing site. However, these near-surface clouds are a major source of errors in the NARR simulations. When compared to observations, the NARR over-simulates the fraction of low clouds during the winter months, and under-simulates the fraction of low clouds during the summer months. The NARR wind speeds at the North Slope are correlated to the observed ARM wind speeds at Barrow. The following correlations were obtained using the 3-hourly data: Jan (0.84); Apr (0.83); Jul (0.69); Oct (0.79). A negative bias (undersimulation) exists in the reanalysis wind speeds for January through July, but is typically 3ms-1 or less in magnitude. Overall, the magnitude of the wind vector is undersimulated approximately 74% of the time in the cold season months and 85% of the time July, but only about half of the time in October. Wind direction biases in the model are generally small (10-20 degrees), but they are generally in the leftward-turning direction in all months. We also synthesized NARR atmospheric output into a composite analysis of the synoptic conditions that are present when the reanalysis model fails in its simulations of Arctic cloud fractions, and similarly, those conditions present when the model simulates accurate cloud fractions. Cold season errors were highest when high pressure was located north of Barrow favoring anomalous winds and longer fetches from the northeast. In addition, larger cloud fraction biases were found on days with relatively calm winds (2-5 m/s). The most pronounced oversimulation biases associated with poorly simulated clouds occur during conditions with very low cloud-base heights (< 50 m). In contrast, the model appears more adept at capturing cloudless conditions in the spring than the winter with oversimulations occurring just 5% of the time in spring compared to 20% in the winter months. During the warm season, low level clouds are present in 32% of the time with onshore flow and less than half this frequent in offshore wind conditions. Composite sea level pressure fields indicate that clear sky conditions typically result when high pressure is centered at or near Barrow, AK. Overcast days are associated with generally lower sea level pressures near the North Slope and onshore flow from the NW in most months. Warm season errors were highest when high pressure was persistent to the north of Barrow, AK. This synoptic situation results in onshore flow for the North Slope with persistent winds from the east and northeast. In these situations, the predominant climatological synoptic situation, the NARR model under-simulates summer clouds on the North Slope. In general, the NARR often fails to capture clouds in the lowest 200 meters of the atmosphere. We conclude that the cloud model parameterization fails to cature boundary layer clouds like Arctic stratus and fog, which are observed in 65% of the undersimulations. These NARR undersimulations occur most often during onshore flow environments, such as when high pressure is located north of Barrow and the prevailing winds are from the northeast. In these cases, the airflow is along a fetch of scattered sea ice and open ocean (ice concentrations between 0 and 100%). NARR treats sea ice as a binary function. Grid cells are either considered a slap of ice cover, or totally open ocean. We note that implementing provisions for partial sea ice concentrations in the reanalysis model may help in more accurately depicting surface moisture fluxes and associated model-derived low cloud amounts.« less

Low Clouds

Atmospheric Science Data Center

2013-04-19

article title:  Indian Ocean Clouds     View Larger ... Multi-angle Imaging SpectroRadiometer (MISR) instrument on NASA's polar-orbiting Terra spacecraft. The area covered by the image is 247.5 ... during the last decade. MISR was built and is managed by NASA's Jet Propulsion Laboratory, Pasadena, CA, for NASA's Science Mission ...

MERIS albedo climatology and its effect on the FRESCO+ O2 A-band cloud retrieval from SCIAMACHY data

NASA Astrophysics Data System (ADS)

Popp, Christoph; Wang, Ping; Brunner, Dominik; Stammes, Piet; Zhou, Yipin

2010-05-01

Accurate cloud information is an important prerequisite for the retrieval of atmospheric trace gases from spaceborne UV/VIS sensors. Errors in the estimated cloud fraction and cloud height (pressure) result in an erroneous air mass factor and thus can lead to inaccuracies in the vertical column densities of the retrieved trace gas. In ESA's TEMIS (Tropospheric Emission Monitoring Internet Service) project, the FRESCO+ (Fast Retrieval Scheme for Clouds from the Oxygen A-band) cloud retrieval is applied to, amongst others, SCIAMACHY (SCanning Imaging Absorption SpectroMeter for Atmospheric CartograpHY) data to determine these quantities. Effective cloud fraction and pressure are inverted by (i) radiative transfer simulations of top-of-atmosphere reflectance based on O2 absorption, single Rayleigh scattering, surface and cloud albedo in three spectral windows covering the O2 A-band and (ii) a subsequent fitting of the simulated to the measured spectrum. However, FRESCO+ relies on a relatively coarse resolution surface albedo climatology (1° x 1°) compiled from GOME (Global Ozone Monitoring Experiment) measurements in the 1990's which introduces several artifacts, e.g. an overestimation of cloud fraction at coastlines or over some mountainous regions. Therefore, we test the substitution of the GOME climatology with a new land surface albedo climatology compiled for every month from MEdium Resolution Imaging Spectrometer (MERIS) Albedomap data (0.05° x 0.05°) covering the period January 2003 to October 2006. The MERIS channels at 754nm and 775nm are located spectrally close to the corresponding GOME channels (758nm and 772nm) on both sides of the O2 A-band. Further, the increased spatial resolution of the MERIS product allows to better account for SCIAMACHY's pixel size of approximately 30x60km. The aim of this study is to describe and assess (i) the compilation and quality of the MERIS climatology (ii) the differences to the GOME climatology, and (iii) possible enhancements of the SCIAMACHY cloud retrieval after integrating the MERIS climatology into FRESCO+. First results indicate that in areas where FRESCO+ is overestimating cloud fraction using the GOME climatology, MERIS generally reveals higher albedo values which in turn will lead to lower cloud fractions, e.g. at coastlines, some arid or mountainous areas. The differences between the two data sets are also higher in winter than in summer. It can therefore be expected that the new data base with increased spatial resolution improves SCIAMACHY cloud retrieval with FRESCO+. The most limiting factors for the compilation of the MERIS climatology can be assigned to inappropriate snow cover masking and occasionally unfavorable illumination conditions in high northern latitudes during winter.

Atmospheric Soundings from AIRS/AMSU in Partial Cloud Cover

NASA Technical Reports Server (NTRS)

Susskind, Joel; Atlas, Robert

2005-01-01

Simultaneous use of AIRS/AMSU-A observations allow for the determination of accurate atmospheric soundings under partial cloud cover conditions. The methodology involves the determination of the radiances AIRS would have seen if the AIRS fields of view were clear, called clear column radiances, and use of these radiances to infer the atmospheric and surface conditions giving rise to these clear column radiances. Susskind et al. demonstrate via simulation that accurate temperature soundings and clear column radiances can be derived from AIRS/AMSU-A observations in cases of up to 80% partial cloud cover, with only a small degradation in accuracy compared to that obtained in clear scenes. Susskind and Atlas show that these findings hold for real AIRS/AMSU-A soundings as well. For data assimilation purposes, this small degradation in accuracy is more than offset by a significant increase in spatial coverage (roughly 50% of global cases were accepted, compared to 3.6% of the global cases being diagnosed as clear), and assimilation of AIRS temperature soundings in partially cloudy conditions resulted in a larger improvement in forecast skill than when AIRS soundings were assimilated only under clear conditions. Alternatively, derived AIRS clear column radiances under partial cloud cover could also be used for data assimilation purposes. Further improvements in AIRS sounding methodology have been made since the results shown in Susskind and Atlas . A new version of the AIRS/AMSU-A retrieval algorithm, Version 4.0, was delivered to the Goddard DAAC in February 2005 for production of AIRS derived products, including clear column radiances. The major improvement in the Version 4.0 retrieval algorithm is with regard to a more flexible, parameter dependent, quality control. Results are shown of the accuracy and spatial distribution of temperature-moisture profiles and clear column radiances derived from AIRS/AMSU-A as a function of fractional cloud cover using the Version 4.0 algorithm. Use of the Version 4.0 AIRS temperature profiles increased the positive forecast impact arising from AIRS retrievals relative to what was shown in Susskind and Atlas .

A Simple Model for the Cloud Adjacency Effect and the Apparent Bluing of Aerosols Near Clouds

NASA Technical Reports Server (NTRS)

Marshak, Alexander; Wen, Guoyong; Coakley, James A., Jr.; Remer, Lorraine A.; Loeb,Norman G.; Cahalan, Robert F.

2008-01-01

In determining aerosol-cloud interactions, the properties of aerosols must be characterized in the vicinity of clouds. Numerous studies based on satellite observations have reported that aerosol optical depths increase with increasing cloud cover. Part of the increase comes from the humidification and consequent growth of aerosol particles in the moist cloud environment, but part comes from 3D cloud-radiative transfer effects on the retrieved aerosol properties. Often, discerning whether the observed increases in aerosol optical depths are artifacts or real proves difficult. The paper provides a simple model that quantifies the enhanced illumination of cloud-free columns in the vicinity of clouds that are used in the aerosol retrievals. This model is based on the assumption that the enhancement in the cloud-free column radiance comes from enhanced Rayleigh scattering that results from the presence of the nearby clouds. The enhancement in Rayleigh scattering is estimated using a stochastic cloud model to obtain the radiative flux reflected by broken clouds and comparing this flux with that obtained with the molecules in the atmosphere causing extinction, but no scattering.

Study of UV cloud modification factors in Southern Patagonia

NASA Astrophysics Data System (ADS)

Wolfram, Elian A.; Orte, Facundo; Salvador, Jacobo; Quiroga, Jonathan; D'Elia, Raúl; Antón, Manuel; Alados-Arboledas, Lucas; Quel, Eduardo

2017-02-01

Anthropogenic perturbation of the ozone layer has induced change in the amount of UV radiation that reaches the Earth's surface, mainly through the Antarctic ozone hole, making the ozone and ultraviolet (UV) radiation two important issues in the study of Earth atmosphere in the scientific community. Also the clouds have been identified as the main modulator of UV amount in short time scales and produce the main source of uncertainty in the projection of surface UV level as consequence of projected ozone recovery. While clouds can decrease direct radiation, they can produce an increase in the diffuse component, and as consequence the surface UV radiation may be higher than an equivalent clear sky scenario for several minutes. In particular this situation can be important when low ozone column and partially cloud cover skies happen simultaneously. These situations happen frequently in southern Patagonia, where the CEILAP Lidar Division has established the Atmospheric Observatory of Southern Patagonia, an atmospheric remote sensing site near the city of Río Gallegos (51°55'S, 69°14'W). In this paper, the impact of clouds over the UV radiation is investigated by the use of ground based measurements from the passive remote sensing instruments operating at this site, mainly of broad and moderate narrow band filter radiometers. We analyzed the UV Index obtained from a multiband filter radiometer GUV-541 (UVI) [Biospherical Inc.] installed in the Observatorio Atmosférico de la Patagonia Austral, Río Gallegos, since 2005. Cloud modification factors (CMF, ratio between the measured UV radiation in a cloudy sky and the simulated radiation under cloud-free conditions) are evaluated for the study site. The database used in this work covers the period 2005-2012 for spring and summer seasons, when the ozone hole can affect these subpolar regions. CMF higher than 1 are found during spring and summer time, when lower total ozone columns, higher solar elevations and high cloud cover occur simultaneously, producing extreme erythemal irradiance at ground surface. Enhancements as high as 25% were registered. The maximum duration of the enhancement was around 30 minute. This produces dangerous sunbathing situations for the Río Gallegos citizen.

UV 380 nm reflectivity of the Earth's surface, clouds and aerosols

NASA Astrophysics Data System (ADS)

Herman, J. R.; Celarier, E.; Larko, D.

2001-03-01

The 380 nm radiance measurements of the Total Ozone Mapping Spectrometer (TOMS) have been converted into a global data set of daily (1979-1992) Lambert equivalent reflectivities R of the Earth's surface and boundary layer (clouds, aerosols, surface haze, and snow/ice) and then corrected to RPC for the presence of partly clouded scenes. Since UV surface reflectivity is between 2 and 8% for both land and water during all seasons of the year (except for ice and snow cover), reflectivities larger than the surface value indicate the presence of clouds, haze, or aerosols in the satellite field of view. A statistical analysis of 14 years of daily reflectivity data shows that most snow-/ice-free scenes observed by TOMS have a reflectivity less than 10% for the majority of days during a year. The 380 nm reflectivity data show that the true surface reflectivity is 2-3% lower than the most frequently occurring reflectivity value for each TOMS scene as seen from space. Most likely the cause is a combination of frequently occurring boundary layer water and/or aerosol haze. For most regions the observation of extremely clear conditions needed to estimate the surface reflectivity from space is a comparatively rare occurrence. Certain areas (e.g., Australia, southern Africa, portions of northern Africa) are cloud-free more than 80% of the year, which exposes these regions to larger amounts of UV radiation than at comparable latitudes in the Northern Hemisphere. Regions over rain forests, jungle areas, Europe and Russia, the bands surrounding the Arctic and Antarctic regions, and many ocean areas have significant cloud cover (R>15%) more than half of each year. In the low to middle latitudes the areas with the heaviest cloud cover (highest reflectivity for most of the year) are the forest areas of northern South America, southern Central America, the jungle areas of equatorial Africa, and high mountain regions such as the Himalayas or the Andes. The TOMS reflectivity data show both the presence of large nearly clear ocean areas and the effects of the major ocean currents on cloud production.

CAUSES: Clouds Above the United States and Errors at the Surface

NASA Astrophysics Data System (ADS)

Ma, H. Y.; Klein, S. A.; Xie, S.; Morcrette, C. J.; Van Weverberg, K.; Zhang, Y.; Lo, M. H.

2015-12-01

The Clouds Above the United States and Errors at the Surface (CAUSES) is a new joint Global Atmospheric System Studies/Regional and Global Climate model/Atmospheric System Research (GASS/RGCM/ASR) intercomparison project to evaluate the central U.S. summertime surface warm biases seen in many weather and climate models. The main focus is to identify the role of cloud, radiation, and precipitation processes in contributing to surface air temperature biases. In this project, we use short-term hindcast approach and examine the growth of the error as a function of hindcast lead time. The study period covers from April 1 to August 31, 2011, which also covers the entire Midlatitude Continental Convective Clouds Experiment (MC3E) campaign. Preliminary results from several models will be presented. (http://portal.nersc.gov/project/capt/CAUSES/) (This study is funded by the RGCM and ASR programs of the U.S. Department of Energy as part of the Cloud-Associated Parameterizations Testbed. This work is performed under the auspices of the U.S. Department of Energy by Lawrence Livermore National Laboratory under Contract DE-AC52-07NA27344. LLNL-ABS-658017)

CAUSES: Clouds Above the United States and Errors at the Surface

NASA Astrophysics Data System (ADS)

Ma, H. Y.; Klein, S. A.; Xie, S.; Zhang, Y.; Morcrette, C. J.; Van Weverberg, K.; Petch, J.; Lo, M. H.

2014-12-01

The Clouds Above the United States and Errors at the Surface (CAUSES) is a new joint Global Atmospheric System Studies/Regional and Global Climate model/Atmospheric System Research (GASS/RGCM/ASR) intercomparison project to evaluate the central U.S. summertime surface warm biases seen in many weather and climate models. The main focus is to identify the role of cloud, radiation, and precipitation processes in contributing to surface air temperature biases. In this project, we use short-term hindcast approach and examine the growth of the error as a function of hindcast lead time. The study period covers from April 1 to August 31, 2011, which also covers the entire Midlatitude Continental Convective Clouds Experiment (MC3E) campaign. Preliminary results from several models will be presented. (http://portal.nersc.gov/project/capt/CAUSES/) (This study is funded by the RGCM and ASR programs of the U.S. Department of Energy as part of the Cloud-Associated Parameterizations Testbed. This work is performed under the auspices of the U.S. Department of Energy by Lawrence Livermore National Laboratory under Contract DE-AC52-07NA27344. LLNL-ABS-658017)

Characterizing a decade of behavior at Volcán de Colima, Mexico using long term InSAR and thermal remote sensing data

NASA Astrophysics Data System (ADS)

Sorge, J.; Williams-Jones, G.; Wright, R.; Varley, N. R.

2010-12-01

Satellite imagery is playing an increasingly prominent role in volcanology as it allows for consistent monitoring of remote, dangerous, and/or under-monitored volcanoes. One such system is Volcán de Colima (Mexico), a persistently active andesitic stratovolcano. Its characteristic and hazardous activity includes lava dome growth, pyroclastic flows, explosions, and Plinian to Subplinian eruptions, which have historically occurred at the end of Volcán de Colima’s eruptive cycle. Despite the availability of large amounts of historical satellite imagery, methods to process and interpret these images over long time periods are limited. Furthermore, while time-series InSAR data from a previous study (December 2002 to August 2006) detected an overall subsidence between 1 and 3 km from the summit, there is insufficient temporal resolution to unambiguously constrain the source processes. To address this issue, a semi-automated process for time-based characterization of persistent volcanic activity at Volcán de Colima has been developed using a combination of MODIS and GOES satellite imagery to identify thermal anomalies on the volcano edifice. This satellite time-series data is then combined with available geodetic data, a detailed eruption history, and other geophysical time-series data (e.g., seismicity, explosions/day, effusion rate, environmental data, etc.) and examined for possible correlations and recurring patterns in the multiple data sets to investigate potential trigger mechanisms responsible for the changes in volcanic activity. GOES and MODIS images are available from 2000 to present at a temporal resolution of one image every 30 minutes and up to four images per day, respectively, creating a data set of approximately 180,000 images. Thermal anomalies over Volcán de Colima are identified in both night- and day-time images by applying a time-series approach to the analysis of MODIS data. Detection of false anomalies, caused by non-volcanic heat sources such as fires or solar heating (in the daytime images), is mitigated by adjusting the MODIS detection thresholds, through comparison of daytime versus nighttime results, and by observing the spatial distribution of the anomalies on the edifice. Conversely, anomalies may not be detected due to cloud cover; clouds absorb thermal radiation limiting or preventing the ability of the satellite to measure thermal events; therefore, the anomaly data is supplemented with a cloud cover time-series data set. Fast Fourier and Wavelet transforms are then applied to the continuous, uninterrupted intervals of satellite observation to compare and correlate with the multiple time-series data sets. The result is the characterization of the behavior of an individual volcano, based on an extended time period. This volcano specific, comprehensive characterization can then be used as a predictive tool in the real-time monitoring of volcanic activity.

Determination of potential solar power sites in the United States based upon satellite cloud observations

NASA Technical Reports Server (NTRS)

Hiser, H. W.; Senn, H. V.; Bukkapatnam, S. T.; Akyuzlu, K.

1977-01-01

The use of cloud images in the visual spectrum from the SMS/GOES geostationary satellites to determine the hourly distribution of sunshine on a mesoscale in the continental United States excluding Alaska is presented. Cloud coverage and density as a function of time of day and season are evaluated through the use of digital data processing techniques. Low density cirrus clouds are less detrimental to solar energy collection than other types; and clouds in the morning and evening are less detrimental than those during midday hours of maximum insolation. Seasonal geographic distributions of cloud cover/sunshine are converted to langleys of solar radiation received at the earth's surface through relationships developed from long term measurements at six widely distributed stations.

Analysis of data for LANDSAT (ERTS) follow-on

NASA Technical Reports Server (NTRS)

Sizer, J. E. (Principal Investigator)

1976-01-01

The author has identified the following significant results. Daily weather service satellite photographs of the midwest were found to be of great assistance before ordering EROS Data Center products. These weather satellite images are a quick and inexpensive record of the location of cloud masses, which supplements the percent of cloud catalogues. Savings of time and money were made because the location of cloud cover was known before any imagery was ordered.

Toward Seamless Weather-Climate Prediction with a Global Cloud Resolving Model

DTIC Science & Technology

2016-01-14

distribution is unlimited. TOWARD SEAMLESS WEATHER- CLIMATE PREDICTION WITH A GLOBAL CLOUD RESOLVING MODEL PI: Tim Li IPRC/SOEST, University of Hawaii at...Project Final Report 3. DATES COVERED (From - To) 1 May 2012 - 30 September 2015 4. TITLE AND SUBTITLE TOWARD SEAMLESS WEATHER- CLIMATE PREDICTION WITH...A GLOBAL CLOUD RESOLVING MODEL 5a. CONTRACT NUMBER 5b. GRANT NUMBER N000141210450 5c. PROGRAM ELEMENT NUMBER ONR Marine Meteorology Program 6

A multi-spectral approach to simultaneously retrieve above-cloud smoke optical depth and the optical and microphysical properties of underlying marine stratocumulus clouds using MODIS

NASA Astrophysics Data System (ADS)

Meyer, K.; Platnick, S. E.; Zhang, Z.

2013-12-01

Clouds, aerosols, and their interactions are widely considered to be key uncertainty components in our current understanding of the Earth's atmosphere and radiation budget. The work presented here is focused on the quasi-permanent marine boundary layer (MBL) clouds over the southeastern Atlantic Ocean, which underlie a near-persistent smoke layer produced from extensive biomass burning throughout the southern African savanna during austral winter. The absorption of the above-cloud smoke layer, which increases with decreasing wavelength, can introduce biases into the standard MODIS cloud optical and microphysical property retrievals of the underlying MBL clouds. This effect is more pronounced in the cloud optical thickness retrievals, which over ocean are derived from the wavelength channel centered near 0.86 μm (effective particle size retrievals are derived from the short and mid-wave IR channels at 1.6, 2.1, and 3.7 μm). Here, a new method is introduced to simultaneously retrieve the above-cloud smoke aerosol optical depth (AOD) and the unbiased cloud optical thickness (COT) and effective radius (CER) using multiple MODIS spectral channels in the visible and near- and shortwave-infrared. Preliminary retrieval results are shown, as are comparisons with other A-Train sensors.

An imager-based multispectral retrieval of above-cloud absorbing aerosol optical depth and the optical and microphysical properties of underlying marine stratocumulus clouds

NASA Astrophysics Data System (ADS)

Meyer, K.; Platnick, S. E.; Zhang, Z.

2014-12-01

Clouds, aerosols, and their interactions are widely considered to be key uncertainty components in our current understanding of the Earth's atmosphere and radiation budget. The work presented here is focused on the quasi-permanent marine boundary layer (MBL) clouds over the southeastern Atlantic Ocean, which underlie a near-persistent smoke layer produced from extensive biomass burning throughout the southern African savanna during austral winter. The absorption of the above-cloud smoke layer, which increases with decreasing wavelength, can introduce biases into imager-based cloud optical and microphysical property retrievals of the underlying MBL clouds. This effect is more pronounced for cloud optical thickness retrievals, which are typically derived from the visible or near-IR wavelength channels (effective particle size retrievals are derived from short and mid-wave IR channels that are less affected by aerosol absorption). Here, a new method is introduced to simultaneously retrieve the above-cloud smoke aerosol optical depth (AOD) and the unbiased cloud optical thickness (COT) and effective radius (CER) using multiple spectral channels in the visible and near- and shortwave-IR. The technique has been applied to MODIS, and retrieval results and statistics, as well as comparisons with other A-Train sensors, are shown.

Analysis of Co-Located MODIS and CALIPSO Observations Near Clouds

NASA Technical Reports Server (NTRS)

Varnai, Tamas; Marshak, Alexander

2011-01-01

The purpose of this paper is to help researchers combine data from different satellites and thus gain new insights into two critical yet poorly understood aspects of anthropogenic climate change, aerosol-cloud interactions and aerosol radiative effects, For this, the paper explores whether cloud information from the Aqua satellite's MODIS instrument can help characterize systematic aerosol changes near clouds by refining earlier perceptions of these changes that were based on the CALIPSO satellite's CALIOP instrument. Similar to a radar but using visible and ncar-infrared light, CALIOP sends out laser pulses and provides aerosol and cloud information along a single line that tracks the satellite orbit by measuring the reflection of its pulses. In contrast, MODIS takes images of reflected sunlight and emitted infrared radiation at several wavelengths, and covers wide areas around the satellite track. This paper analyzes a year-long global dataset covering all ice-free oceans, and finds that MODIS can greatly help the interpretation of CALIOP observations, especially by detecting clouds that lie outside the line observed by CALlPSO. The paper also finds that complications such as differences in view direction or clouds drifting in the 72 seconds that elapse between MODIS and CALIOP observations have only a minor impact. The study also finds that MODIS data helps refine but does not qualitatively alter perceptions of the systematic aerosol changes that were detected in earlier studies using only CALIOP data. It then proposes a statistical approach to account for clouds lying outside the CALIOP track even when MODIS cannot as reliably detect low clouds, for example at night or over ice. Finally, the paper finds that, because of variations in cloud amount and type, the typical distance to clouds in maritime clear areas varies with season and location. The overall median distance to clouds in maritime clear areas around 4-5 km. The fact that half of all clear areas is closer than 5 km to clouds implies that pronounced near-cloud changes in aerosol properties have significant implications for overall clear-sky characteristics, including the radiative impact of aerosols.

Single-Column Model Simulations of Subtropical Marine Boundary-Layer Cloud Transitions Under Weakening Inversions: SCM SIMULATIONS OF CLOUD TRANSITIONS

DOE Office of Scientific and Technical Information (OSTI.GOV)

Neggers, R. A. J.; Ackerman, A. S.; Angevine, W. M.

Results are presented of the GASS/EUCLIPSE single-column model inter-comparison study on the subtropical marine low-level cloud transition. A central goal is to establish the performance of state-of-the-art boundary-layer schemes for weather and climate mod- els for this cloud regime, using large-eddy simulations of the same scenes as a reference. A novelty is that the comparison covers four different cases instead of one, in order to broaden the covered parameter space. Three cases are situated in the North-Eastern Pa- cific, while one reflects conditions in the North-Eastern Atlantic. A set of variables is considered that reflects key aspects of the transitionmore » process, making use of simple met- rics to establish the model performance. Using this method some longstanding problems in low level cloud representation are identified. Considerable spread exists among models concerning the cloud amount, its vertical structure and the associated impact on radia- tive transfer. The sign and amplitude of these biases differ somewhat per case, depending on how far the transition has progressed. After cloud breakup the ensemble median ex- hibits the well-known “too few too bright” problem. The boundary layer deepening rate and its state of decoupling are both underestimated, while the representation of the thin capping cloud layer appears complicated by a lack of vertical resolution. Encouragingly, some models are successful in representing the full set of variables, in particular the verti- cal structure and diurnal cycle of the cloud layer in transition. An intriguing result is that the median of the model ensemble performs best, inspiring a new approach in subgrid pa- rameterization.« less

Single-Column Model Simulations of Subtropical Marine Boundary-Layer Cloud Transitions Under Weakening Inversions

NASA Astrophysics Data System (ADS)

Neggers, R. A. J.; Ackerman, A. S.; Angevine, W. M.; Bazile, E.; Beau, I.; Blossey, P. N.; Boutle, I. A.; de Bruijn, C.; Cheng, A.; van der Dussen, J.; Fletcher, J.; Dal Gesso, S.; Jam, A.; Kawai, H.; Cheedela, S. K.; Larson, V. E.; Lefebvre, M.-P.; Lock, A. P.; Meyer, N. R.; de Roode, S. R.; de Rooy, W.; Sandu, I.; Xiao, H.; Xu, K.-M.

2017-10-01

Results are presented of the GASS/EUCLIPSE single-column model intercomparison study on the subtropical marine low-level cloud transition. A central goal is to establish the performance of state-of-the-art boundary-layer schemes for weather and climate models for this cloud regime, using large-eddy simulations of the same scenes as a reference. A novelty is that the comparison covers four different cases instead of one, in order to broaden the covered parameter space. Three cases are situated in the North-Eastern Pacific, while one reflects conditions in the North-Eastern Atlantic. A set of variables is considered that reflects key aspects of the transition process, making use of simple metrics to establish the model performance. Using this method, some longstanding problems in low-level cloud representation are identified. Considerable spread exists among models concerning the cloud amount, its vertical structure, and the associated impact on radiative transfer. The sign and amplitude of these biases differ somewhat per case, depending on how far the transition has progressed. After cloud breakup the ensemble median exhibits the well-known "too few too bright" problem. The boundary-layer deepening rate and its state of decoupling are both underestimated, while the representation of the thin capping cloud layer appears complicated by a lack of vertical resolution. Encouragingly, some models are successful in representing the full set of variables, in particular, the vertical structure and diurnal cycle of the cloud layer in transition. An intriguing result is that the median of the model ensemble performs best, inspiring a new approach in subgrid parameterization.

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

NASA Technical Reports Server (NTRS)

Xi, Baike; Dong, Xiquan; Minnis, P.; Khaiyer, M.

2010-01-01

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.

JINR cloud infrastructure evolution

NASA Astrophysics Data System (ADS)

Baranov, A. V.; Balashov, N. A.; Kutovskiy, N. A.; Semenov, R. N.

2016-09-01

To fulfil JINR commitments in different national and international projects related to the use of modern information technologies such as cloud and grid computing as well as to provide a modern tool for JINR users for their scientific research a cloud infrastructure was deployed at Laboratory of Information Technologies of Joint Institute for Nuclear Research. OpenNebula software was chosen as a cloud platform. Initially it was set up in simple configuration with single front-end host and a few cloud nodes. Some custom development was done to tune JINR cloud installation to fit local needs: web form in the cloud web-interface for resources request, a menu item with cloud utilization statistics, user authentication via Kerberos, custom driver for OpenVZ containers. Because of high demand in that cloud service and its resources over-utilization it was re-designed to cover increasing users' needs in capacity, availability and reliability. Recently a new cloud instance has been deployed in high-availability configuration with distributed network file system and additional computing power.

Comparative verification between GEM model and official aviation terminal forecasts

NASA Technical Reports Server (NTRS)

Miller, Robert G.

1988-01-01

The Generalized Exponential Markov (GEM) model uses the local standard airways observation (SAO) to predict hour-by-hour the following elements: temperature, pressure, dew point depression, first and second cloud-layer height and amount, ceiling, total cloud amount, visibility, wind, and present weather conditions. GEM is superior to persistence at all projections for all elements in a large independent sample. A minute-by-minute GEM forecasting system utilizing the Automated Weather Observation System (AWOS) is under development.

Fast Atmosphere-Ocean Model Runs with Large Changes in CO2

NASA Technical Reports Server (NTRS)

Russell, Gary L.; Lacis, Andrew A.; Rind, David H.; Colose, Christopher; Opstbaum, Roger F.

2013-01-01

How does climate sensitivity vary with the magnitude of climate forcing? This question was investigated with the use of a modified coupled atmosphere-ocean model, whose stability was improved so that the model would accommodate large radiative forcings yet be fast enough to reach rapid equilibrium. Experiments were performed in which atmospheric CO2 was multiplied by powers of 2, from 1/64 to 256 times the 1950 value. From 8 to 32 times, the 1950 CO2, climate sensitivity for doubling CO2 reaches 8 C due to increases in water vapor absorption and cloud top height and to reductions in low level cloud cover. As CO2 amount increases further, sensitivity drops as cloud cover and planetary albedo stabilize. No water vapor-induced runaway greenhouse caused by increased CO2 was found for the range of CO2 examined. With CO2 at or below 1/8 of the 1950 value, runaway sea ice does occur as the planet cascades to a snowball Earth climate with fully ice covered oceans and global mean surface temperatures near 30 C.

Influence of Clouds On The Surface Radiative Balance For Two Mediterranean Sites

NASA Astrophysics Data System (ADS)

Bortoli, D.; Costa, M. J.; Nardino, M.

Clouds strongly affect the Earth's climate influencing the surface radiative balance by reducing the incident solar radiation and increasing the downward longwave flux. Al- though the quantitative impact of clouds on the surface radiative balance is necessarily associated with great uncertainties due to the complexity and variation of the under- lying parameters, cloud radiative forcing is one of the main regulating factors of the Earth's climate. The present work aims at determining the effect of cloud coverage on the surface radiative balance, in order to contribute for a better understanding of local variations in the Mediterranean climate. Measurements of the cloud cover index (CCI) require the presence of an observer capable of quantifying cloud amounts in the sky in sight above the measurements' site. Since such measurements are not always available the cloud cover index is re- trieved using two different methodologies. On one hand the CCI is computed from the surface radiometer measurements throughout a parameterisation. On the other it is retrieved using a bi-spectral algorithm based on the METEOSAT satellite measure- ments from the visible and infrared spectral regions. Results of the CCI are compared with co-located observations to perform a general check against the available "ground truth". At the same time the CCI values obtained from both methodologies are inter- compared. Results of the CCI and their implications on the surface radiative balance are presented for the two Mediterranean sites selected, one located in Italy and the other in the south of Portugal. The cloud radiative forcing calculations show a cooling effect of the surface in presence of clouds for both sites. Moreover, a seasonal dependence is obtained, with a stronger cooling effect during summer. Acknowledgements: The work was supported by Instituto de Cooperação Científica e Tecnológica Internacional (ICCTI) - Portugal and Consiglio Nazionale delle Ricerche (CNR) - Italy, through the bilateral agreement "Study of cloud and aerosol radiative forcing on the surface radiative balance".

Investigation of Arctic mixed-phase clouds by combining airborne remote sensing and in situ observations during VERDI, RACEPAC and ACLOUD

NASA Astrophysics Data System (ADS)

Ehrlich, André; Bierwirth, Eike; Borrmann, Stephan; Crewell, Susanne; Herber, Andreas; Hoor, Peter; Jourdan, Olivier; Krämer, Martina; Lüpkes, Christof; Mertes, Stephan; Neuber, Roland; Petzold, Andreas; Schnaiter, Martin; Schneider, Johannes; Weigel, Ralf; Weinzierl, Bernadett; Wendisch, Manfred

2016-04-01

To improve our understanding of Arctic mixed-phase clouds a series of airborne research campaigns has been initiated by a collaboration of German research institutes. Clouds in areas dominated by a close sea-ice cover were observed during the research campaign Vertical distribution of ice in Arctic mixed-phase clouds (VERDI, April/May 2012) and the Radiation-Aerosol-Cloud Experiment in the Arctic Circle (RACEPAC, April/May 2014) which both were based in Inuvik, Canada. The aircraft (Polar 5 & 6, Basler BT-67) operated by the Alfred Wegener Institute for Polar and Marine Research, Germany did cover a wide area above the Canadian Beaufort with in total 149 flight hours (62h during VERDI, 87h during RACEPAC). For May/June 2017 a third campaign ACLOUD (Arctic Clouds - Characterization of Ice, aerosol Particles and Energy fluxes) with base in Svalbard is planned within the Transregional Collaborative Research Centre TR 172 ArctiC Amplification: Climate Relevant Atmospheric and SurfaCe Processes, and Feedback Mechanisms (AC)3 to investigate Arctic clouds in the transition zone between open ocean and sea ice. The aim of all campaigns is to combine remote sensing and in-situ cloud, aerosol and trace gas measurements to investigate interactions between radiation, cloud and aerosol particles. While during VERDI remote sensing and in-situ measurements were performed by one aircraft subsequently, for RACEPAC and ACLOUD two identical aircraft are coordinated at different altitudes to horizontally collocate both remote sensing and in-situ measurements. The campaign showed that in this way radiative and microphysical processes in the clouds can by studied more reliably and remote sensing methods can be validated efficiently. Here we will illustrate the scientific strategy of the projects including the progress in instrumentation. Differences in the general synoptic and sea ice situation and related changes in cloud properties at the different locations and seasons will be addressed to illustrate the broad spectrum of the observations. Exemplary results will be highlighted.

Profiling of Atmospheric Water Vapor from the SSM/T-2 Radiometric Measurements

NASA Technical Reports Server (NTRS)

Wang, J. R.

2000-01-01

An advantage of using the millimeter-wave measurements for water vapor profiling is the ability to probe beyond a moderate cloud cover. Such a capability has been demonstrated from an airborne MIR (Millimeter-wave Imaging Radiometer) flight over the Pacific Ocean during an intense observation period of TOGA/COARE (Tropical Ocean Global Atmosphere/ Couple Ocean Atmospheric Response Experiment) in early 1993. A Cloud Lidar System (CLS) and MODIS Airborne Simulator (MAS) were on board the same aircraft to identify the presence of clouds and cloud type. The retrieval algorithm not only provides output of a water vapor profile, but also the cloud liquid water and approximate cloud altitude required to satisfy convergence of the retrieval. The validity of these cloud parameters has not been verified previously. In this document, these cloud parameters are compared with those derived from concurrent measurements from the CLS and AMPR (Advanced Microwave Precipitation Radiometer).

Approaches to Observe Anthropogenic Aerosol-Cloud Interactions.

PubMed

Quaas, Johannes

Anthropogenic aerosol particles exert an-quantitatively very uncertain-effective radiative forcing due to aerosol-cloud interactions via an immediate altering of cloud albedo on the one hand and via rapid adjustments by alteration of cloud processes and by changes in thermodynamic profiles on the other hand. Large variability in cloud cover and properties and the therefore low signal-to-noise ratio for aerosol-induced perturbations hamper the identification of effects in observations. Six approaches are discussed as a means to isolate the impact of anthropogenic aerosol on clouds from natural cloud variability to estimate or constrain the effective forcing. These are (i) intentional cloud modification, (ii) ship tracks, (iii) differences between the hemispheres, (iv) trace gases, (v) weekly cycles and (vi) trends. Ship track analysis is recommendable for detailed process understanding, and the analysis of weekly cycles and long-term trends is most promising to derive estimates or constraints on the effective radiative forcing.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Zhou, Chen; Zelinka, Mark D.; Dessler, Andrew E.

The analyses of Coupled Model Intercomparison Project phase 5 simulations suggest that climate models with more positive cloud feedback in response to interannual climate fluctuations also have more positive cloud feedback in response to long-term global warming. Ensemble mean vertical profiles of cloud change in response to interannual and long-term surface warming are similar, and the ensemble mean cloud feedback is positive on both timescales. However, the average long-term cloud feedback is smaller than the interannual cloud feedback, likely due to differences in surface warming pattern on the two timescales. Low cloud cover (LCC) change in response to interannual andmore » long-term global surface warming is found to be well correlated across models and explains over half of the covariance between interannual and long-term cloud feedback. In conclusion, the intermodel correlation of LCC across timescales likely results from model-specific sensitivities of LCC to sea surface warming.« less

Sensitivity analysis of upwelling thermal radiance in presence of clouds

NASA Technical Reports Server (NTRS)

Subramanian, S. V.; Tiwari, S. N.; Suttles, J. T.

1981-01-01

Total upwelling radiance at the top of the atmosphere is evaluated theoretically in the presence of clouds. The influence of cloud heights, thicknesses and different cloud covers on the upwelling radiance is also investigated. The characteristics of the two cloud types considered in this study closely correspond to altocumulus and cirrus with the cloud emissivity as a function of its liquid water (or ice) content. For calculation of the integrated transmittance of atmospheric gases such as, H2O, CO2, O3, and N2O, the Quasi Random Band (QRB) model approach is adopted. Results are obtained in three different spectral ranges and are compared with the clearsky radiance results. It is found that the difference between the clearsky and cloudy radiance increases with increasing cloud height and liquid water content. This difference also decreases as the surface temperature approaches the value of the cloud top temperature.

Long Term Cloud Property Datasets From MODIS and AVHRR Using the CERES Cloud Algorithm

NASA Technical Reports Server (NTRS)

Minnis, Patrick; Bedka, Kristopher M.; Doelling, David R.; Sun-Mack, Sunny; Yost, Christopher R.; Trepte, Qing Z.; Bedka, Sarah T.; Palikonda, Rabindra; Scarino, Benjamin R.; Chen, Yan;

Land cover and forest formation distributions for St. Kitts, Nevis, St. Eustatius, Grenada and Barbados from decision tree classification of cloud-cleared satellite imagery

USGS Publications Warehouse

Helmer, E.H.; Kennaway, T.A.; Pedreros, D.H.; Clark, M.L.; Marcano-Vega, H.; Tieszen, L.L.; Ruzycki, T.R.; Schill, S.R.; Carrington, C.M.S.

2008-01-01

Satellite image-based mapping of tropical forests is vital to conservation planning. Standard methods for automated image classification, however, limit classification detail in complex tropical landscapes. In this study, we test an approach to Landsat image interpretation on four islands of the Lesser Antilles, including Grenada and St. Kitts, Nevis and St. Eustatius, testing a more detailed classification than earlier work in the latter three islands. Secondly, we estimate the extents of land cover and protected forest by formation for five islands and ask how land cover has changed over the second half of the 20th century. The image interpretation approach combines image mosaics and ancillary geographic data, classifying the resulting set of raster data with decision tree software. Cloud-free image mosaics for one or two seasons were created by applying regression tree normalization to scene dates that could fill cloudy areas in a base scene. Such mosaics are also known as cloud-filled, cloud-minimized or cloud-cleared imagery, mosaics, or composites. The approach accurately distinguished several classes that more standard methods would confuse; the seamless mosaics aided reference data collection; and the multiseason imagery allowed us to separate drought deciduous forests and woodlands from semi-deciduous ones. Cultivated land areas declined 60 to 100 percent from about 1945 to 2000 on several islands. Meanwhile, forest cover has increased 50 to 950%. This trend will likely continue where sugar cane cultivation has dominated. Like the island of Puerto Rico, most higher-elevation forest formations are protected in formal or informal reserves. Also similarly, lowland forests, which are drier forest types on these islands, are not well represented in reserves. Former cultivated lands in lowland areas could provide lands for new reserves of drier forest types. The land-use history of these islands may provide insight for planners in countries currently considering lowland forest clearing for agriculture. Copyright 2008 College of Arts and Sciences.

Discovery of a Bright Equatorial Storm on Neptune

NASA Astrophysics Data System (ADS)

Molter, E. M.; De Pater, I.; Alvarez, C.; Tollefson, J.; Luszcz-Cook, S.

2017-12-01

Images of Neptune, taken with the NIRC2 instrument during testing of the new Twilight Zone observing program at Keck Observatory, revealed an extremely large bright storm system near Neptune's equator. The storm complex is ≈9,000 km across and brightened considerably between June 26 and July 2. Historically, very bright clouds have occasionally been seen on Neptune, but always in the midlatitude regions between ≈15° and ≈60° North or South. Voyager and HST observations have shown that cloud features large enough to dominate near-IR photometry are often "companion" clouds of dark anti-cyclonic vortices similar to Jupiter's Great Red Spot, interpreted as orographic clouds. In the past such clouds and their coincident dark vortices often persisted for one up to several years. However, the cloud complex we detect is unique: never before has a bright cloud been seen at, or so close to, the equator. The discovery points to a drastic departure in the dynamics of Neptune's atmosphere from what has been observed for the past several decades. Detections of the complex in multiple NIRC2 filters allows radiative transfer modeling to constrain the cloud's altitude and vertical extent.

Photolysis rates in correlated overlapping cloud fields: Cloud-J 7.3

DOE PAGES

Prather, M. J.

2015-05-27

A new approach for modeling photolysis rates ( J values) in atmospheres with fractional cloud cover has been developed and implemented as Cloud-J – a multi-scattering eight-stream radiative transfer model for solar radiation based on Fast-J. Using observed statistics for the vertical correlation of cloud layers, Cloud-J 7.3 provides a practical and accurate method for modeling atmospheric chemistry. The combination of the new maximum-correlated cloud groups with the integration over all cloud combinations represented by four quadrature atmospheres produces mean J values in an atmospheric column with root-mean-square errors of 4% or less compared with 10–20% errors using simpler approximations.more » Cloud-J is practical for chemistry-climate models, requiring only an average of 2.8 Fast-J calls per atmosphere, vs. hundreds of calls with the correlated cloud groups, or 1 call with the simplest cloud approximations. Another improvement in modeling J values, the treatment of volatile organic compounds with pressure-dependent cross sections is also incorporated into Cloud-J.« less

Photolysis rates in correlated overlapping cloud fields: Cloud-J 7.3c

DOE PAGES

Prather, M. J.

2015-08-14

A new approach for modeling photolysis rates ( J values) in atmospheres with fractional cloud cover has been developed and is implemented as Cloud-J – a multi-scattering eight-stream radiative transfer model for solar radiation based on Fast-J. Using observations of the vertical correlation of cloud layers, Cloud-J 7.3c provides a practical and accurate method for modeling atmospheric chemistry. The combination of the new maximum-correlated cloud groups with the integration over all cloud combinations by four quadrature atmospheres produces mean J values in an atmospheric column with root mean square (rms) errors of 4 % or less compared with 10–20 %more » errors using simpler approximations. Cloud-J is practical for chemistry–climate models, requiring only an average of 2.8 Fast-J calls per atmosphere vs. hundreds of calls with the correlated cloud groups, or 1 call with the simplest cloud approximations. Another improvement in modeling J values, the treatment of volatile organic compounds with pressure-dependent cross sections, is also incorporated into Cloud-J.« less

Cloud cover typing from environmental satellite imagery. Discriminating cloud structure with Fast Fourier Transforms (FFT)

NASA Technical Reports Server (NTRS)

Logan, T. L.; Huning, J. R.; Glackin, D. L.

1983-01-01

The use of two dimensional Fast Fourier Transforms (FFTs) subjected to pattern recognition technology for the identification and classification of low altitude stratus cloud structure from Geostationary Operational Environmental Satellite (GOES) imagery was examined. The development of a scene independent pattern recognition methodology, unconstrained by conventional cloud morphological classifications was emphasized. A technique for extracting cloud shape, direction, and size attributes from GOES visual imagery was developed. These attributes were combined with two statistical attributes (cloud mean brightness, cloud standard deviation), and interrogated using unsupervised clustering amd maximum likelihood classification techniques. Results indicate that: (1) the key cloud discrimination attributes are mean brightness, direction, shape, and minimum size; (2) cloud structure can be differentiated at given pixel scales; (3) cloud type may be identifiable at coarser scales; (4) there are positive indications of scene independence which would permit development of a cloud signature bank; (5) edge enhancement of GOES imagery does not appreciably improve cloud classification over the use of raw data; and (6) the GOES imagery must be apodized before generation of FFTs.

GASP cloud- and particle-encounter statistics and their application to LPC aircraft studies. Volume 1: Analysis and conclusions

NASA Technical Reports Server (NTRS)

Jasperson, W. H.; Nastrom, G. D.; Davis, R. E.; Holdeman, J. D.

1984-01-01

Summary studies are presented for the entire cloud observation archieve from the NASA Global Atmospheric Sampling Program (GASP). Studies are also presented for GASP particle concentration data gathered concurrently with the cloud observations. Cloud encounters are shown on about 15 percent of the data samples overall, but the probability of cloud encounter is shown to vary significantly with altitude, latitude, and distance from the tropopause. Several meteorological circulation features are apparent in the latitudinal distribution of cloud cover, and the cloud encounter statistics are shown to be consistent with the classical mid-latitude cyclone model. Observations of clouds spaced more closely than 90 minutes are shown to be statistically dependent. The statistics for cloud and particle encounter are utilized to estimate the frequency of cloud encounter on long range airline routes, and to assess the probability and extent of laminar flow loss due to cloud or particle encounter by aircraft utilizing laminar flow control (LFC). It is shown that the probability of extended cloud encounter is too low, of itself, to make LFC impractical.

In situ observations of Arctic cloud properties across the Beaufort Sea marginal ice zone

NASA Astrophysics Data System (ADS)

Corr, C.; Moore, R.; Winstead, E.; Thornhill, K. L., II; Crosbie, E.; Ziemba, L. D.; Beyersdorf, A. J.; Chen, G.; Martin, R.; Shook, M.; Corbett, J.; Smith, W. L., Jr.; Anderson, B. E.

2016-12-01

Clouds play an important role in Arctic climate. This is particularly true over the Arctic Ocean where feedbacks between clouds and sea-ice impact the surface radiation budget through modifications of sea-ice extent, ice thickness, cloud base height, and cloud cover. This work summarizes measurements of Arctic cloud properties made aboard the NASA C-130 aircraft over the Beaufort Sea during ARISE (Arctic Radiation - IceBridge Sea&Ice Experiment) in September 2014. The influence of surface-type on cloud properties is also investigated. Specifically, liquid water content (LWC), droplet concentrations, and droplet size distributions are compared for clouds sampled over three distinct regimes in the Beaufort Sea: 1) open water, 2) the marginal ice zone, and 3) sea-ice. Regardless of surface type, nearly all clouds intercepted during ARISE were liquid-phase clouds. However, differences in droplet size distributions and concentrations were evident for the surface types; clouds over the MIZ and sea-ice generally had fewer and larger droplets compared to those over open water. The potential implication these results have for understanding cloud-surface albedo climate feedbacks in Arctic are discussed.

Local effects of partly-cloudy skies on solar and emitted radiation

NASA Technical Reports Server (NTRS)

Whitney, D. A.; Venable, D. D.

1982-01-01

A computer automated data acquisition system for atmospheric emittance, and global solar, downwelled diffuse solar, and direct solar irradiances is discussed. Hourly-integrated global solar and atmospheric emitted radiances were measured continuously from February 1981 and hourly-integrated diffuse solar and direct solar irradiances were measured continuously from October 1981. One-minute integrated data are available for each of these components from February 1982. The results of the correlation of global insolation with fractional cloud cover for the first year's data set. A February data set, composed of one-minute integrated global insolation and direct solar irradiance, cloud cover fractions, meteorological data from nearby weather stations, and GOES East satellite radiometric data, was collected to test the theoretical model of satellite radiometric data correlation and develop the cloud dependence for the local measurement site.

U.S. Cloud Cover Five Day Flip-Flop

NASA Image and Video Library

2013-11-22

In autumn, cloud cover over the continental United States changes dramatically every few days, as these two remarkably opposite midday views show. In five days, clouds seemed to flip-flop over the U.S. These images were captured by NOAA's GOES-East satellite at 1745 UTC/12:45 p.m. EST on November 18 and 22, 2013. The images were created by Dennis Chesters of the NASA GOES Project at the NASA Goddard Space Flight Center in Greenbelt, Md. NASA image use policy. NASA Goddard Space Flight Center enables NASA’s mission through four scientific endeavors: Earth Science, Heliophysics, Solar System Exploration, and Astrophysics. Goddard plays a leading role in NASA’s accomplishments by contributing compelling scientific knowledge to advance the Agency’s mission. Follow us on Twitter Like us on Facebook Find us on Instagram

Extreme Winter/Early-Spring Temperature Anomalies in Central Europe

NASA Technical Reports Server (NTRS)

Otterman, Joseph; Atlas, Robert; Ardizzone, Joseph; Brakke, Thomas; Chou, Shu-Hsien; Jusem, Juan Carlos; Glantz, Michael; Rogers, Jeff; Sud, Yogesh; Susskind, Joel

2000-01-01

Extreme seasonal fluctuations of the surface-air temperature characterize the climate of central Europe, 45-60 deg North Temperature difference between warm 1990 and cold 1996 in the January-March period, persisting for more than two weeks at a time, amounted to 18 C for extensive areas. These anomalies in the surface-air temperature stem in the first place from differences in the low level flow from the eastern North-Atlantic: the value of the Index 1na of southwesterlies over the eastern North-Atlantic was 8.0 m/s in February 1990, but only 2.6 m/ s in February 1996. The primary forcing by warm advection to positive anomalies in monthly mean surface temperature produced strong synoptic-scale uplift at the 700 mb level over some regions in Europe. The strong uplift contributed in 1990 to a much larger cloud-cover over central Europe, which reduced heat-loss to space (greenhouse effect). Thus, spring arrived earlier than usual in 1990, but later than usual in 1996.

Incorporation of a Cumulus Fraction Scheme in the GRAPES_Meso and Evaluation of Its Performance

NASA Astrophysics Data System (ADS)

Zheng, X.

2016-12-01

Accurate simulation of cloud cover fraction is a key and difficult issue in numerical modeling studies. Preliminary evaluations have indicated that cloud fraction is generally underestimated in GRAPES_Meso simulations, while the cloud fraction scheme (CFS) of ECMWF can provide more realistic results. Therefore, the ECMWF cumulus fraction scheme is introduced into GRAPES_Meso to replace the original CFS, and the model performance with the new CFS is evaluated based on simulated three-dimensional cloud fractions and surface temperature. Results indicate that the simulated cloud fractions increase and become more accurate with the new CFS; the simulation for vertical cloud structure has improved too; errors in surface temperature simulation have decreased. The above analysis and results suggest that the new CFS has a positive impact on cloud fraction and surface temperature simulation.

Cloud effects on ultraviolet photoclimatology

NASA Technical Reports Server (NTRS)

Green, A. E. S.; Spinhirne, J. D.

1978-01-01

The purpose of this study is to quantify for the needs of photobiology the influence of clouds upon the ultraviolet spectral irradiance reaching the ground. Towards this end, analytic formulas are developed which approximately characterize the influence of clouds upon total solar radiation. These may be used in conjunction with a solar pyranometer to assign an effective visual optical depth for the cloud cover. A formula is also developed which characterizes the influence of the optical depth of clouds upon the UV spectral irradiance in the 280-340 nm region. Thus total solar energy observations to assign cloud optical properties can be used to calculate the UV spectral irradiance at the ground in the presence of these clouds. As incidental by-products of this effort, convenient formulas are found for the direct and diffuse components of total solar energy.

Cloud Radiative Effect in dependence on Cloud Type

NASA Astrophysics Data System (ADS)

Aebi, Christine; Gröbner, Julian; Kämpfer, Niklaus; Vuilleumier, Laurent

2015-04-01

Radiative transfer of energy in the atmosphere and the influence of clouds on the radiation budget remain the greatest sources of uncertainty in the simulation of climate change. Small changes in cloudiness and radiation can have large impacts on the Earth's climate. In order to assess the opposing effects of clouds on the radiation budget and the corresponding changes, frequent and more precise radiation and cloud observations are necessary. The role of clouds on the surface radiation budget is studied in order to quantify the longwave, shortwave and the total cloud radiative forcing in dependence on the atmospheric composition and cloud type. The study is performed for three different sites in Switzerland at three different altitude levels: Payerne (490 m asl), Davos (1'560 m asl) and Jungfraujoch (3'580 m asl). On the basis of data of visible all-sky camera systems at the three aforementioned stations in Switzerland, up to six different cloud types are distinguished (Cirrus-Cirrostratus, Cirrocumulus-Altocumulus, Stratus-Altostratus, Cumulus, Stratocumulus and Cumulonimbus-Nimbostratus). These cloud types are classified with a modified algorithm of Heinle et al. (2010). This cloud type classifying algorithm is based on a set of statistical features describing the color (spectral features) and the texture of an image (textural features) (Wacker et al. (2015)). The calculation of the fractional cloud cover information is based on spectral information of the all-sky camera data. The radiation data are taken from measurements with pyranometers and pyrgeometers at the different stations. A climatology of a whole year of the shortwave, longwave and total cloud radiative effect and its sensitivity to integrated water vapor, cloud cover and cloud type will be calculated for the three above-mentioned stations in Switzerland. For the calculation of the shortwave and longwave cloud radiative effect the corresponding cloud-free reference models developed at PMOD/WRC will be used (Wacker et al. (2013)). References: Heinle, A., A. Macke and A. Srivastav (2010) Automatic cloud classification of whole sky images, Atmospheric Measurement Techniques. Wacker, S., J. Gröbner and L. Vuilleumier (2013) A method to calculate cloud-free long-wave irradiance at the surface based on radiative transfer modeling and temperature lapse rate estimates, Theoretical and Applied Climatology. Wacker, S., J. Gröbner, C. Zysset, L. Diener, P. Tzoumanikis, A. Kazantzidis, L. Vuilleumier, R. Stöckli, S. Nyeki, and N. Kämpfer (2015) Cloud observations in Switzerland using hemispherical sky cameras, Journal of Geophysical Research.

A 19-Month Climatology of Marine Aerosol-Cloud-Radiation Properties Derived From DOE ARM AMF Deployment at the Azores: Part I: Cloud Fraction and Single-Layered MBL Cloud Properties

NASA Technical Reports Server (NTRS)

Dong, Xiquan; Xi, Baike; Kennedy, Aaron; Minnis, Patrick; Wood, Robert

2013-01-01

A 19-month record of total, and single-layered low (0-3 km), middle (3-6 km), and high (> 6 km) cloud fractions (CFs), and the single-layered marine boundary layer (MBL) cloud macrophysical and microphysical properties has been generated from ground-based measurements taken at the ARM Azores site between June 2009 and December 2010. It documents the most comprehensive and longest dataset on marine cloud fraction and MBL cloud properties to date. The annual means of total CF, and single-layered low, middle, and high CFs derived from ARM radar-lidar observations are 0.702, 0.271, 0.01 and 0.106, respectively. More total and single-layered high CFs occurred during winter, while single-layered low CFs were greatest during summer. The diurnal cycles for both total and low CFs are stronger during summer than during winter. The CFs are bimodally distributed in the vertical with a lower peak at approx. 1 km and higher one between 8 and 11 km during all seasons, except summer, when only the low peak occurs. The persistent high pressure and dry conditions produce more single-layered MBL clouds and fewer total clouds during summer, while the low pressure and moist air masses during winter generate more total and multilayered-clouds, and deep frontal clouds associated with midlatitude cyclones.

Climatology and dynamics of nocturnal low-level stratus over the southern West African monsoon region

NASA Astrophysics Data System (ADS)

Fink, A. H.; Schuster, R.; Knippertz, P.; van der Linden, R.

2013-12-01

The southern parts of West Africa, from the coast to about 10°N, are frequently covered by an extensive deck of shallow, low (200 - 400 m above ground) stratus or stratocumulus clouds during the summer monsoon season. These clouds usually form at night in association with a nocturnal low-level jet (NLLJ) and can persist into the early afternoon hours until they are dissipated or replaced by fair-weather cumuli. Recent work suggests that the stratus deck and its effect on the surface radiation balance are unsatisfactorily represented in standard satellite retrievals and simulations by state-of-the-art climate models. We will present the first ever climatology of the diurnal cycle of the low cloud deck based on surface observations and satellite products. In addition, we use high-resolution regional simulations with the Weather Research and Forecast (WRF) model and observations from the African Monsoon Multidisciplinary Analysis (AMMA) 2006 campaign to investigate (a) the spatiotemporal distribution, (b) the influence on the radiation balance, and (c) the detailed formation and maintenance mechanisms of the stratiform clouds as simulated by the model. The model configuration used for this study has been determined following an extensive sensitivity study, which has shown that at least some configurations of WRF satisfactorily reproduce the diurnal cycle of the low cloud evolution. The main conclusions are: (a) The observed stratus deck forms after sunset along the coast, spreads inland in the course of the night, reaches maximum poleward extent at about 10°N around 09-10 local time and dissipates in the early afternoon. (b) The average surface net radiation balance in stratus-dominated regions is 35 W m-2 lower than in those with less clouds. (c) The cloud formation is related to a subtle balance between 'stratogenic' upward (downward) fluxes of latent (sensible) heat caused by shear-driven turbulence below the NLLJ, cold advection from the ocean, forced lifting at the windward side of orography, and radiative cooling on one hand, and 'stratolytic' dry advection and latent heating on the other hand. Future work will focus on the influence of the stratus on the energy and moisture budget and on the West African monsoon system as a whole. Schematic illustration of the cloud formation process for (a) conditions close to the coast and (b) farther inland. Abbreviations are ADV: advection, E: latent heat flux, H: sensible heat flux, EV: evaporation, and NLLJ: nighttime low-level jet. Typical values for the contribution from each process are given. The effect of lifting was estimated by the difference in height and the assumption of a vertical temperature gradient of 0.65K/100 m (Fig. 12 in Schuster et al. 2013, J. Atmos. Sci, 70 (8), 2337-2355.

The GONG Site Survey. [solar oscillations

NASA Technical Reports Server (NTRS)

Hill, Frank; Ambastha, Ashok; Ball, Warren; Duhalde, Oscar; Farris, Don; Fischer, George; Hieda, Les; Zhen, Huang; Ingram, Bob; Jackson, Patty

1988-01-01

The Global Oscillation Network Group (GONG) project is planning to place six observing stations around the world to observe the solar oscillations as continuously as possible. The procedures that are being used to select the six sites are described. Results of measurements of cloud cover obtained by networks of 6 (out of 10) radiometers show a duty cycle of over 93 percent, with the first diurnal sidelobe in the window power spectrum suppressed by a factor of 400. The results are in good agreement with the predictions of a computer model of the expected cloud cover at individual sites.

Surveys of Puerto Rican screech-owl populations in large-tract and fragmented forest habitats

USGS Publications Warehouse

Pardieck, K.L.; Meyers, J.M.; Pagan, M.

1996-01-01

We conducted road surveys of Puerto Rican Screech-Owls (Otus nudipes) by playing conspecific vocalizations in secondary wet forest and fragmented secondary moist forest in rural areas of eastern Puerto Rico. Six paired surveys were conducted bi-weekly beginning in April. We recorded number of owl responses, cloud cover, wind speed, moon phase, and number of passing cars during 5-min stops at 60 locations. Owls responded in similar numbers (P > 0.05) in both habitat types. Also, we detected no association with cloud cover, wind speed, moon phase, or passing cars.

Exploration for fossil and nuclear fuels from orbital altitudes

NASA Technical Reports Server (NTRS)

Short, N. M.

1975-01-01

A review of satellite-based photographic (optical and infrared) and microwave exploration and large-area mapping of the earth's surface in the ERTS program. Synoptic cloud-free coverage of large areas has been achieved with planimetric vertical views of the earth's surface useful in compiling close-to-orthographic mosaics. Radar penetration of cloud cover and infrared penetration of forest cover have been successful to some extent. Geological applications include map editing (with corrections in scale and computer processing of images), landforms analysis, structural geology studies, lithological identification, and exploration for minerals and fuels. Limitations of the method are noted.

Analyzing the Effect of Intraseasonal Meteorological Variability and Land Cover on Aerosol-Cloud Interactions During the Amazonian Biomass Burning Season

NASA Technical Reports Server (NTRS)

TenHoeve, J. E.; Remer, L. A.; Jacobson, M. Z.

2010-01-01

High resolution aerosol, cloud, water vapor, and atmospheric profile data from the Moderate Resolution Imaging Spectroradiometer (MODIS) are utilized to examine the impact of aerosols on clouds during the Amazonian biomass burning season in Rondnia, Brazil. It is found that increasing background column water vapor (CWV) throughout this transition season between the Amazon dry and wet seasons exerts a strong effect on cloud properties. As a result, aerosol-cloud correlations should be stratified by column water vapor to achieve a more accurate assessment of the effect of aerosols on clouds. Previous studies ignored the systematic changes to meteorological factors during the transition season, leading to possible misinterpretation of their results. Cloud fraction is shown generally to increase with aerosol optical depth (AOD) for both low and high values of column water vapor, whereas the relationship between cloud optical depth (COD) and AOD exhibits a different relationship. COD increases with AOD until AOD approx. 0.25 due to the first indirect (microphysical) effect. At higher values of AOD, COD is found to decrease with increasing AOD, which may be due to: (1) the inhibition of cloud development by absorbing aerosols (radiative effect) and/or (2) a retrieval artifact in which the measured reflectance in the visible is less than expected from a cloud top either from the darkening of clouds through the addition of carbonaceous biomass burning aerosols or subpixel dark surface contamination in the measured cloud reflectance. If (1) is a contributing mechanism, as we suspect, then a linear relationship between the indirect effect and increasing AOD, assumed in a majority of GCMs, is inaccurate since these models do not include treatment of aerosol absorption in and around clouds. The effect of aerosols on both column water vapor and clouds over varying land surface types is also analyzed. The study finds that the difference in column water vapor between forest and pasture is not correlated with aerosol loading, supporting the assumption that temporal variation of column water vapor is primarily a function of the larger-scale meteorology. However, a difference in the response of cloud fraction to increasing AOD is observed between forest and pasture. This suggests that dissimilarities between other meteorological factors, such as atmospheric stability, are likely to have an impact on aerosol-cloud correlations between different land-cover types.

Low cloud properties influenced by cosmic rays

PubMed

Marsh; Svensmark

2000-12-04

The influence of solar variability on climate is currently uncertain. Recent observations have indicated a possible mechanism via the influence of solar modulated cosmic rays on global cloud cover. Surprisingly the influence of solar variability is strongest in low clouds (

Clear-Sky Narrowband Albedo Datasets Derived from Modis Data

NASA Astrophysics Data System (ADS)

Chen, Y.; Minnis, P.; Sun-Mack, S.; Arduini, R. F.; Hong, G.

2013-12-01

Satellite remote sensing of clouds requires an accurate estimate of the clear-sky radiances for a given scene to detect clouds and aerosols and to retrieve their microphysical properties. Knowing the spatial and angular variability of clear-sky albedo is essential for predicting the clear-sky radiance at solar wavelengths. The Clouds and the Earth's Radiant Energy System (CERES) Project uses the near-infrared (NIR; 1.24, 1.6 or 2.13 μm) and visible (VIS; 0.63 μm) channels available on the Terra and Aqua Moderate Resolution Imaging Spectroradiometers (MODIS) to help identify clouds and retrieve their properties. Generally, clear-sky albedo for a given surface type is determined for conditions when the vegetation is either thriving or dormant and free of snow. The clear-sky albedos are derived using a radiative transfer parameterization of the impact of the atmosphere, including aerosols, on the observed reflectances. This paper presents the method of generating monthly clear-sky overhead albedo maps for both snow-free and snow-covered surfaces of these channels using one year of MODIS (Moderate Resolution Imaging Spectroradiometer) CERES products. Maps of 1.24 and 1.6 μm are being used as the background to help retrieve cloud properties (e.g., effective particle size, optical depth) in CERES cloud retrievals in both snow-free and snow-covered conditions.

Sod-seeding to modify coastal bermuda grass on reclaimed lignite overburden in Texas

DOE Office of Scientific and Technical Information (OSTI.GOV)

Skousen, J.G.

1986-01-01

This study was conducted to investigate the ability of nine low-maintenance species to establish and persist with Coastal bermuda grass (Cynodon dactylon (L.) Pers.) established on reclaimed lignite overburden; to evaluate the establishment and persistence of seventeen low-maintenance species seeded in overburden with no vegetation cover; and to examine seeding mixtures and rates for establishing low-maintenance species into three cover types (bermuda grass, oats, (Avena fatua L.) and no cover). Seventeen low-maintenance species established and persisted in overburden without fertilization during years of low precipitation. Several seeded grasses showed sufficient stand development in monoculture for erosion control. Most of themore » other seeded species were slower in establishment, yet persisted on the site and promoted multiple use of the reclaimed area. Recommended seeding rates were generally adequate for seedling establishment in oat, bermuda grass, and no vegetation cover types. Sod-seeding into bermuda grass resulted in higher seedling densities than those in oats and no cover because of stored moisture beneath the sod during bermuda grass dormancy. Using /sup 15/N-labelled fertilizer, Coastal bermuda grass demonstrated the ability to rapidly recovery applied N. Maximilian sunflower (Helianthus maximiliani Schrad.) was suppressed by Coastal bermuda grass in mixture at all fertilizer N rates.« less

Evaluating rainfall errors in global climate models through cloud regimes

NASA Astrophysics Data System (ADS)

Tan, Jackson; Oreopoulos, Lazaros; Jakob, Christian; Jin, Daeho

2017-07-01

Global climate models suffer from a persistent shortcoming in their simulation of rainfall by producing too much drizzle and too little intense rain. This erroneous distribution of rainfall is a result of deficiencies in the representation of underlying processes of rainfall formation. In the real world, clouds are precursors to rainfall and the distribution of clouds is intimately linked to the rainfall over the area. This study examines the model representation of tropical rainfall using the cloud regime concept. In observations, these cloud regimes are derived from cluster analysis of joint-histograms of cloud properties retrieved from passive satellite measurements. With the implementation of satellite simulators, comparable cloud regimes can be defined in models. This enables us to contrast the rainfall distributions of cloud regimes in 11 CMIP5 models to observations and decompose the rainfall errors by cloud regimes. Many models underestimate the rainfall from the organized convective cloud regime, which in observation provides half of the total rain in the tropics. Furthermore, these rainfall errors are relatively independent of the model's accuracy in representing this cloud regime. Error decomposition reveals that the biases are compensated in some models by a more frequent occurrence of the cloud regime and most models exhibit substantial cancellation of rainfall errors from different regimes and regions. Therefore, underlying relatively accurate total rainfall in models are significant cancellation of rainfall errors from different cloud types and regions. The fact that a good representation of clouds does not lead to appreciable improvement in rainfall suggests a certain disconnect in the cloud-precipitation processes of global climate models.

3D cloud detection and tracking system for solar forecast using multiple sky imagers

DOE PAGES

Peng, Zhenzhou; Yu, Dantong; Huang, Dong; ...

2015-06-23

We propose a system for forecasting short-term solar irradiance based on multiple total sky imagers (TSIs). The system utilizes a novel method of identifying and tracking clouds in three-dimensional space and an innovative pipeline for forecasting surface solar irradiance based on the image features of clouds. First, we develop a supervised classifier to detect clouds at the pixel level and output cloud mask. In the next step, we design intelligent algorithms to estimate the block-wise base height and motion of each cloud layer based on images from multiple TSIs. Thus, this information is then applied to stitch images together intomore » larger views, which are then used for solar forecasting. We examine the system’s ability to track clouds under various cloud conditions and investigate different irradiance forecast models at various sites. We confirm that this system can 1) robustly detect clouds and track layers, and 2) extract the significant global and local features for obtaining stable irradiance forecasts with short forecast horizons from the obtained images. Finally, we vet our forecasting system at the 32-megawatt Long Island Solar Farm (LISF). Compared with the persistent model, our system achieves at least a 26% improvement for all irradiance forecasts between one and fifteen minutes.« less

Cloud Feedbacks on Greenhouse Warming in a Multi-Scale Modeling Framework with a Higher-Order Turbulence Closure

NASA Technical Reports Server (NTRS)

Cheng, Anning; Xu, Kuan-Man

2015-01-01

Five-year simulation experiments with a multi-scale modeling Framework (MMF) with a advanced intermediately prognostic higher-order turbulence closure (IPHOC) in its cloud resolving model (CRM) component, also known as SPCAM-IPHOC (super parameterized Community Atmospheric Model), are performed to understand the fast tropical (30S-30N) cloud response to an instantaneous doubling of CO2 concentration with SST held fixed at present-day values. SPCAM-IPHOC has substantially improved the low-level representation compared with SPCAM. It is expected that the cloud responses to greenhouse warming in SPCAM-IPHOC is more realistic. The change of rising motion, surface precipitation, cloud cover, and shortwave and longwave cloud radiative forcing in SPCAM-IPHOC from the greenhouse warming will be presented in the presentation.

Towards a Three-Dimensional Near-Real Time Cloud Product for Aviation Safety and Weather Diagnoses

NASA Technical Reports Server (NTRS)

Minnis, Patrick; Nguyen, Louis; Palikonda, Rabindra; Spangeberg, Douglas; Nordeen, Michele L.; Yi, Yu-Hong; Ayers, J. Kirk

2004-01-01

Satellite data have long been used for determining the extent of cloud cover and for estimating the properties at the cloud tops. The derived properties can also be used to estimate aircraft icing potential to improve the safety of air traffic in the region. Currently, cloud properties and icing potential are derived in near-real time over the United States of America (USA) from the Geostationary Operational Environmental Satellite GOES) imagers at 75 W and 135 W. Traditionally, the results have been given in two dimensions because of the lack of knowledge about the vertical extent of clouds and the occurrence of overlapping clouds. Aircraft fly in a three-dimensional space and require vertical as well as horizontal information about clouds, their intensity, and their potential for icing. To improve the vertical component of the derived cloud and icing parameters, this paper explores various methods and datasets for filling in the three-dimensional space over the USA with cloud water.

Methods for estimating 2D cloud size distributions from 1D observations

DOE PAGES

Romps, David M.; Vogelmann, Andrew M.

2017-08-04

The two-dimensional (2D) size distribution of clouds in the horizontal plane plays a central role in the calculation of cloud cover, cloud radiative forcing, convective entrainment rates, and the likelihood of precipitation. Here, a simple method is proposed for calculating the area-weighted mean cloud size and for approximating the 2D size distribution from the 1D cloud chord lengths measured by aircraft and vertically pointing lidar and radar. This simple method (which is exact for square clouds) compares favorably against the inverse Abel transform (which is exact for circular clouds) in the context of theoretical size distributions. Both methods also performmore » well when used to predict the size distribution of real clouds from a Landsat scene. When applied to a large number of Landsat scenes, the simple method is able to accurately estimate the mean cloud size. Finally, as a demonstration, the methods are applied to aircraft measurements of shallow cumuli during the RACORO campaign, which then allow for an estimate of the true area-weighted mean cloud size.« less

Methods for estimating 2D cloud size distributions from 1D observations

DOE Office of Scientific and Technical Information (OSTI.GOV)

Romps, David M.; Vogelmann, Andrew M.

The two-dimensional (2D) size distribution of clouds in the horizontal plane plays a central role in the calculation of cloud cover, cloud radiative forcing, convective entrainment rates, and the likelihood of precipitation. Here, a simple method is proposed for calculating the area-weighted mean cloud size and for approximating the 2D size distribution from the 1D cloud chord lengths measured by aircraft and vertically pointing lidar and radar. This simple method (which is exact for square clouds) compares favorably against the inverse Abel transform (which is exact for circular clouds) in the context of theoretical size distributions. Both methods also performmore » well when used to predict the size distribution of real clouds from a Landsat scene. When applied to a large number of Landsat scenes, the simple method is able to accurately estimate the mean cloud size. Finally, as a demonstration, the methods are applied to aircraft measurements of shallow cumuli during the RACORO campaign, which then allow for an estimate of the true area-weighted mean cloud size.« less

Climatological Data for Clouds Over the Globe from Surface Observations (1988) (NDP-026)

DOE Data Explorer

Hahn, Carole J. [Univ. of Colorado, Boulder, CO (United States). Cooperative Inst. for Research in Environmental Sciences (CIRES); Warren, Stephen G. [Department of Atmospheric Sciences, University of Washington, Seattle, Washington; London, Julius [Department of Astrophysical, Planetary, and Atmospheric Sciences, University of Colorado, Boulder, CO; Jenne, Ray L. [National Center for Atmospheric Research, Boulder, CO (United States); Chervin, Robert M. [National Center for Atmospheric Research, Boulder, CO (United States)

1988-01-01

With some data from as early as 1930, global long-term monthly and/or seasonal total cloud cover, cloud type amounts and frequencies of occurrence, low cloud base heights, harmonic analyses of annual and diurnal cycles, interannual variations and trends, and cloud type co-occurrences have been compiled and presented in two atlases (Warren et al. 1988, 1990). These data were derived from land and ship synoptic weather reports from the "SPOT" archive of the Fleet Numerical Oceanography Center (FNOC) and from Release 1 of the Comprehensive Ocean-Atmosphere Data Set (COADS) for the years 1930-1979. The data are in 12 files (one containing latitude, longitude, land-fraction, and number of land stations for grid boxes; four containing total cloud, cloud types, harmonic analyses, and interannual variations and trends for land; four containing total cloud, cloud types, harmonic analyses, and interannual variations and trends for oceans; one containing first cloud analyses for the first year of the GARP Global Experiment (FGGE); one containing cloud-type co-occurrences for land and oceans; and one containing a FORTRAN program to read and produce maps).

Changes in cloud properties over East Asia deduced from the CLARA-A2 satellite data record

NASA Astrophysics Data System (ADS)

Benas, Nikos; Fokke Meirink, Jan; Hollmann, Rainer; Karlsson, Karl-Göran; Stengel, Martin

2017-04-01

Studies on cloud properties and processes, and their role in the Earth's changing climate, have advanced during the past decades. A significant part of this advance was enabled by satellite measurements, which offer global and continuous monitoring. Lately, a new satellite-based cloud data record was released: the CM SAF cLoud, Albedo and surface RAdiation dataset from AVHRR data - second edition (CLARA-A2) includes high resolution cloud macro- and micro-physical properties derived from the AVHRR instruments on board NOAA and MetOp polar orbiters. Based on this data record, an analysis of cloud property changes over East Asia during the 12-year period 2004-2015 was performed. Significant changes were found in both optical and geometric cloud properties, including increases in cloud liquid water path and top height. The Cloud Droplet Number Concentration (CDNC) was specifically studied in order to gain further insight into possible connections between aerosol and cloud processes. To this end, aerosol and cloud observations from MODIS, covering the same area and period, were included in the analysis.

Cloud Chemistry in the United States: Problems and Prospects

NASA Astrophysics Data System (ADS)

Carlton, A. G.; Barth, M. C.; Lance, S.; Fahey, K.; McNeill, V. F.; Weber, R. J.

2017-12-01

Clouds cover 60% of the Earth's surface at a given time and are the primary means by which atmospheric trace species are lofted from the polluted boundary layer to the free troposphere. Clouds also play an important role as atmospheric aqueous phase reactors, scavenging soluble gas phase precursors and providing a medium for oxidation reactions that yield lower volatility products that contribute to increased aerosol mass when cloud drops evaporate. On a global average, most sulfate particles are formed during cloud processing, and organic particles known to form through aqueous phase pathways are found above clouds. However, atmospheric chemistry observations are generally biased for clear sky conditions. For example, aircraft field deployments typically avoid clouds. Satellite retrievals impacted by clouds are often screened from the final data products. This hinders knowledge of cloud chemistry and the impacts on tropospheric composition. In this work, we explore temporal and geospatial trends in trace species related to cloud processing in the U.S. with a focus on organic chemistry. We apply 3-dimensional and 0-dimensional models to recent campaigns and mountaintop cloud sampling sites, and compare to measurements.

A single field of view method for retrieving tropospheric temperature profiles from cloud-contaminated radiance data

NASA Technical Reports Server (NTRS)

Hodges, D. B.

1976-01-01

An iterative method is presented to retrieve single field of view (FOV) tropospheric temperature profiles directly from cloud-contaminated radiance data. A well-defined temperature profile may be calculated from the radiative transfer equation (RTE) for a partly cloudy atmosphere when the average fractional cloud amount and cloud-top height for the FOV are known. A cloud model is formulated to calculate the fractional cloud amount from an estimated cloud-top height. The method is then examined through use of simulated radiance data calculated through vertical integration of the RTE for a partly cloudy atmosphere using known values of cloud-top height(s) and fractional cloud amount(s). Temperature profiles are retrieved from the simulated data assuming various errors in the cloud parameters. Temperature profiles are retrieved from NOAA-4 satellite-measured radiance data obtained over an area dominated by an active cold front and with considerable cloud cover and compared with radiosonde data. The effects of using various guessed profiles and the number of iterations are considered.

A satellite observation test bed for cloud parameterization development

NASA Astrophysics Data System (ADS)

Lebsock, M. D.; Suselj, K.

2015-12-01

We present an observational test-bed of cloud and precipitation properties derived from CloudSat, CALIPSO, and the the A-Train. The focus of the test-bed is on marine boundary layer clouds including stratocumulus and cumulus and the transition between these cloud regimes. Test-bed properties include the cloud cover and three dimensional cloud fraction along with the cloud water path and precipitation water content, and associated radiative fluxes. We also include the subgrid scale distribution of cloud and precipitation, and radiaitive quantities, which must be diagnosed by a model parameterization. The test-bed further includes meterological variables from the Modern Era Retrospective-analysis for Research and Applications (MERRA). MERRA variables provide the initialization and forcing datasets to run a parameterization in Single Column Model (SCM) mode. We show comparisons of an Eddy-Diffusivity/Mass-FLux (EDMF) parameterization coupled to micorphsycis and macrophysics packages run in SCM mode with observed clouds. Comparsions are performed regionally in areas of climatological subsidence as well stratified by dynamical and thermodynamical variables. Comparisons demonstrate the ability of the EDMF model to capture the observed transitions between subtropical stratocumulus and cumulus cloud regimes.

Marine Stratocumulus Properties from the FPDR - PDI as a Function of Aerosol during ORACLES

NASA Astrophysics Data System (ADS)

Small Griswold, J. D.; Heikkila, A.

2016-12-01

Aerosol-cloud interactions in the southeastern Atlantic (SEA) region were investigated during year 1 of the ObseRvations of Aerosols above CLouds and their intEractionS (ORACLES) field project in Aug-Sept 2016. This region is of interest due to seasonally persistent marine stratocumulus cloud decks that are an important component of the climate system due to their radiative and hydrologic impacts. The SEA deck is unique due to the interactions between these clouds and transported biomass burning aerosol during the July-October fire season. These biomass burning aerosol play multiple roles in modifying the cloud deck through interactions with radiation as absorbing aerosol and through modifications to cloud microphysical properties as cloud condensation nuclei. This work uses in situcloud data obtained with a Flight Probe Dual Range - Phase Doppler Interferometer (FPDR - PDI), standard aerosol instrumentation on board the NASA P-3, and reanalysis data to investigate Aerosol-Cloud Interactions (ACI). The FPDR - PDI provides unique cloud microphysical observations of individual cloud drop arrivals allowing for the computation of a variety of microphysical cloud properties including individual drop size, cloud drop number concentration, cloud drop size distributions, liquid water content, and cloud thickness. The FPDR - PDI measurement technique also provides droplet spacing and drop velocity information which is used to investigate turbulence and entrainment mixing processes. We use aerosol information such as average background aerosol amount (low, mid, high) and location relative to cloud (above or mixing) to sort FPDR - PDI cloud properties. To control for meteorological co-variances we further sort the data within aerosol categories by lower tropospheric stability, vertical velocity, and surface wind direction. We then determine general marine stratocumulus cloud characteristics under each of the various aerosol categories to investigate ACI in the SEA.

Land cover changes and their biogeophysical effects on climate

Treesearch

Rezaul Mahmood; Roger A. Pielke; Kenneth G. Hubbard; Dev Niyogi; Paul A. Dirmeyer; Clive McAlpine; Andrew M. Carleton; Robert Hale; Samuel Gameda; Adriana Beltrán-Przekurat; Bruce Baker; Richard McNider; David R. Legates; Marshall Shepherd; Jinyang Du; Peter D. Blanken; Oliver W. Frauenfeld; U.S. Nair; Souleymane Fall

2013-01-01

Land cover changes (LCCs) play an important role in the climate system. Research over recent decades highlights the impacts of these changes on atmospheric temperature, humidity, cloud cover, circulation, and precipitation. These impacts range from the local- and regional-scale to sub-continental and global-scale. It has been found that the impacts of regional-scale...

Grids and clouds in the Czech NGI

NASA Astrophysics Data System (ADS)

Kundrát, Jan; Adam, Martin; Adamová, Dagmar; Chudoba, Jiří; Kouba, Tomáš; Lokajíček, Miloš; Mikula, Alexandr; Říkal, Václav; Švec, Jan; Vohnout, Rudolf

2016-09-01

There are several infrastructure operators within the Czech Republic NGI (National Grid Initiative) which provide users with access to high-performance computing facilities over a grid and cloud interface. This article focuses on those where the primary author has personal first-hand experience. We cover some operational issues as well as the history of these facilities.

Space Weather Connections to Clouds and Climate

NASA Astrophysics Data System (ADS)

Tinsley, B. A.

2004-12-01

There is now a considerable amount of observational data and theoretical work pointing to a link between space weather and atmospheric electricity, and then between atmospheric electricity and cloud cover and precipitation, which ultimately affect climate and the biosphere. Studies so far have been largely confined to the Earth, but may be applicable to all planets with clouds in their atmospheres. The current density Jz, that is the return current flowing downward through clouds in the global circuit, is modulated by the galactic cosmic ray flux; by solar energetic particles; by the dawn-dusk polar cap potential difference; and by the precipitation of relativistic electrons from the radiation belts. The flow of Jz through clouds generates unipolar space charge, which is positive at cloud tops and negative at cloud base. This charge attaches to aerosol particles, and affects their interaction with other particles and droplets. Ultrafine aerosol particles are formed around ions and are preserved from scavenging on background aerosols, and preserved for growth by vapor deposition, by space charge at the bases and tops of layer clouds. There is electro-preservation of both ultrafines and of existing CCN that leads to increases in CCN concentration, and increases in cloud cover and reduction in both droplet size and precipitation by the `indirect aerosol effect'. For cold clouds and larger aerosol particles that act as ice forming nuclei, the rate of scavenging of the IFN by large supercooled droplets varies with space charge. Changes in space weather affect both ion production and Jz in planetary atmospheres. In addition, changes in cosmic ray flux affect conductivity within thunderclouds and may affect the output of the thundercloud generators in the global circuit. Thus all four processes, (a) ion-induced nucleation, (b) electro-preservation of leading to increases in CCN concentration and the indirect aerosol effect, (c) contact ice nucleation affecting the production of ices, (d) cosmic ray effects on the generators of the global circuit, are potential links between space weather and life on planets.

Cloud and Aerosol Measurements from the GLAS Polar Orbiting Lidar: First Year Results

NASA Technical Reports Server (NTRS)

Spinhirne, J. D.; Palm, S. P.; Hlavka, D. L.; Hart, W. D.; Mahesh, A.; Welton, E. J.

2004-01-01

The Geoscience Laser Altimeter System (GLAS) launched in 2003 is the first polar orbiting satellite lidar. The instrument was designed for high performance observations of the distribution and optical scattering cross sections of clouds and aerosol. GLAS is approaching six months of on orbit data operation. These data from thousands of orbits illustrate the ability of space lidar to accurately and dramatically measure the height distribution of global cloud and aerosol to an unprecedented degree. There were many intended science applications of the GLAS data and significant results have already been realized. One application is the accurate height distribution and coverage of global cloud cover with one goal of defining the limitation and inaccuracies of passive retrievals. Comparison to MODIS cloud retrievals shows notable discrepancies. Initial comparisons to NOAA 14&15 satellite cloud retrievals show basic similarity in overall cloud coverage, but important differences in height distribution. Because of the especially poor performance of passive cloud retrievals in polar regions, and partly because of high orbit track densities, the GLAS measurements are by far the most accurate measurement of Arctic and Antarctica cloud cover from space to date. Global aerosol height profiling is a fundamentally new measurement from space with multiple applications. A most important aerosol application is providing input to global aerosol generation and transport models. Another is improved measurement of aerosol optical depth. Oceanic surface energy flux derivation from PBL and LCL height measurements is another application of GLAS data that is being pursued. A special area of work for GLAS data is the correction and application of multiple scattering effects. Stretching of surface return pulses in excess of 40 m from cloud propagation effects and other interesting multiple scattering phenomena have been observed. As an EOS project instrument, GLAS data products are openly available to the science community. First year results from GLAS are summarized.

Results from the Two-Year Infrared Cloud Imager Deployment at ARM's NSA Observatory in Barrow, Alaska

NASA Astrophysics Data System (ADS)

Shaw, J. A.; Nugent, P. W.

2016-12-01

Ground-based longwave-infrared (LWIR) cloud imaging can provide continuous cloud measurements in the Arctic. This is of particular importance during the Arctic winter when visible wavelength cloud imaging systems cannot operate. This method uses a thermal infrared camera to observe clouds and produce measurements of cloud amount and cloud optical depth. The Montana State University Optical Remote Sensor Laboratory deployed an infrared cloud imager (ICI) at the Atmospheric Radiation Monitoring North Slope of Alaska site at Barrow, AK from July 2012 through July 2014. This study was used to both understand the long-term operation of an ICI in the Arctic and to study the consistency of the ICI data products in relation to co-located active and passive sensors. The ICI was found to have a high correlation (> 0.92) with collocated cloud instruments and to produce an unbiased data product. However, the ICI also detects thin clouds that are not detected by most operational cloud sensors. Comparisons with high-sensitivity actively sensed cloud products confirm the existence of these thin clouds. Infrared cloud imaging systems can serve a critical role in developing our understanding of cloud cover in the Arctic by provided a continuous annual measurement of clouds at sites of interest.

Utilizing Multiple Datasets for Snow Cover Mapping

NASA Technical Reports Server (NTRS)

Tait, Andrew B.; Hall, Dorothy K.; Foster, James L.; Armstrong, Richard L.

1999-01-01

Snow-cover maps generated from surface data are based on direct measurements, however they are prone to interpolation errors where climate stations are sparsely distributed. Snow cover is clearly discernable using satellite-attained optical data because of the high albedo of snow, yet the surface is often obscured by cloud cover. Passive microwave (PM) data is unaffected by clouds, however, the snow-cover signature is significantly affected by melting snow and the microwaves may be transparent to thin snow (less than 3cm). Both optical and microwave sensors have problems discerning snow beneath forest canopies. This paper describes a method that combines ground and satellite data to produce a Multiple-Dataset Snow-Cover Product (MDSCP). Comparisons with current snow-cover products show that the MDSCP draws together the advantages of each of its component products while minimizing their potential errors. Improved estimates of the snow-covered area are derived through the addition of two snow-cover classes ("thin or patchy" and "high elevation" snow cover) and from the analysis of the climate station data within each class. The compatibility of this method for use with Moderate Resolution Imaging Spectroradiometer (MODIS) data, which will be available in 2000, is also discussed. With the assimilation of these data, the resolution of the MDSCP would be improved both spatially and temporally and the analysis would become completely automated.

Object Based Image Analysis Combining High Spatial Resolution Imagery and Laser Point Clouds for Urban Land Cover

NASA Astrophysics Data System (ADS)

Zou, Xiaoliang; Zhao, Guihua; Li, Jonathan; Yang, Yuanxi; Fang, Yong

2016-06-01

With the rapid developments of the sensor technology, high spatial resolution imagery and airborne Lidar point clouds can be captured nowadays, which make classification, extraction, evaluation and analysis of a broad range of object features available. High resolution imagery, Lidar dataset and parcel map can be widely used for classification as information carriers. Therefore, refinement of objects classification is made possible for the urban land cover. The paper presents an approach to object based image analysis (OBIA) combing high spatial resolution imagery and airborne Lidar point clouds. The advanced workflow for urban land cover is designed with four components. Firstly, colour-infrared TrueOrtho photo and laser point clouds were pre-processed to derive the parcel map of water bodies and nDSM respectively. Secondly, image objects are created via multi-resolution image segmentation integrating scale parameter, the colour and shape properties with compactness criterion. Image can be subdivided into separate object regions. Thirdly, image objects classification is performed on the basis of segmentation and a rule set of knowledge decision tree. These objects imagery are classified into six classes such as water bodies, low vegetation/grass, tree, low building, high building and road. Finally, in order to assess the validity of the classification results for six classes, accuracy assessment is performed through comparing randomly distributed reference points of TrueOrtho imagery with the classification results, forming the confusion matrix and calculating overall accuracy and Kappa coefficient. The study area focuses on test site Vaihingen/Enz and a patch of test datasets comes from the benchmark of ISPRS WG III/4 test project. The classification results show higher overall accuracy for most types of urban land cover. Overall accuracy is 89.5% and Kappa coefficient equals to 0.865. The OBIA approach provides an effective and convenient way to combine high resolution imagery and Lidar ancillary data for classification of urban land cover.

Using multi-source satellite data to assess snow-cover change in Qinghai-Tibetan Plateau in last decade

NASA Astrophysics Data System (ADS)

Jiang, Y.; Chen, F.; Gao, Y.; Barlage, M. J.

2017-12-01

Snow cover in Qinghai-Tibetan Plateau (QTP) is a critical component of water cycle and affects regional climate of East Asia. Satellite data from three different sources (i.e., FY3A/B/C, MODIS and IMS) were used to analyze the QTP fractional-snow-cover (FSC) change and associated uncertainties in the last decade. To reduce the high percentage of cloud in FY3A/B/C and MODIS, a four-step cloud removal procedure was applied and effectively reduced the cloud percentage from 40.8-56.1% to 2.2­-­3.3%. The averaged error introduced by the cloud removal procedure was about 2% estimated by a random sampling method. Results show that the snow cover in QTP significantly decreased in recent 5 years. Three data sets (FY3B, MODIS and IMS) showed significant decreased annual FSC at all elevation bands from 2012-2016, and a significant shorter snow season with delayed snow onset and earlier melting. Both IMS and MODIS had a slightly decline annual FSC from 2000 to 3000 m, while MODIS FSC slightly decreased in 2002-2016 and IMS FSC slightly increased from 2006-2016 in the region with elevation higher than 3000 m. Results also show significant uncertainties among the five data sets (FY3A/B/C, MODIS, IMS), although they showed similar fluctuations of daily FSC. IMS had largest snow-cover extent and highest daily FSC due to its multi data sources. FY3A/C and MODIS (observed in the morning) had around 5% higher mean FSC than FY3B (observed in the afternoon) due to the 3 hours detection time gap. The relative error of daily FSC (taking MODIS as `truth') between FY3A/B/C, IMS and MODIS is 23%, -35%, 8% and 63%, respectively, averaged in five elevation bands in 2015-2017.

Cloud vertical profiles derived from CALIPSO and CloudSat and a comparison with MODIS derived clouds

NASA Astrophysics Data System (ADS)

Kato, S.; Sun-Mack, S.; Miller, W. F.; Rose, F. G.; Minnis, P.; Wielicki, B. A.; Winker, D. M.; Stephens, G. L.; Charlock, T. P.; Collins, W. D.; Loeb, N. G.; Stackhouse, P. W.; Xu, K.

2008-05-01

CALIPSO and CloudSat from the a-train provide detailed information of vertical distribution of clouds and aerosols. The vertical distribution of cloud occurrence is derived from one month of CALIPSO and CloudSat data as a part of the effort of merging CALIPSO, CloudSat and MODIS with CERES data. This newly derived cloud profile is compared with the distribution of cloud top height derived from MODIS on Aqua from cloud algorithms used in the CERES project. The cloud base from MODIS is also estimated using an empirical formula based on the cloud top height and optical thickness, which is used in CERES processes. While MODIS detects mid and low level clouds over the Arctic in April fairly well when they are the topmost cloud layer, it underestimates high- level clouds. In addition, because the CERES-MODIS cloud algorithm is not able to detect multi-layer clouds and the empirical formula significantly underestimates the depth of high clouds, the occurrence of mid and low-level clouds is underestimated. This comparison does not consider sensitivity difference to thin clouds but we will impose an optical thickness threshold to CALIPSO derived clouds for a further comparison. The effect of such differences in the cloud profile to flux computations will also be discussed. In addition, the effect of cloud cover to the top-of-atmosphere flux over the Arctic using CERES SSF and FLASHFLUX products will be discussed.

Cloud and Sun-Glint Statistics Derived from GOES and MODIS Observations Over the Intra-Americas Sea for GEO-CAPE Mission Planning

NASA Technical Reports Server (NTRS)

Feng, Lian; Hu, Chuanmin; Barnes, Brian B.; Mannino, Antonio; Heidinger, Andrew K.; Strabala, Kathleen; Iraci, Laura T.

2017-01-01

Knowledge of cloud cover, frequency, and duration is not only important to study cloud dynamics, but also critical in determining when and where to take ocean measurements from geostationary orbits such as the Geostationary Coastal and Air Pollution Events (GEO-CAPE) mission due to the challenges in achieving complete hemispheric coverage of coastal oceans, estuaries, and inland waters at hourly frequency. Using GOES hourly measurements at 4 km nadir resolution between 2006 and 2011, the number of cloud-free hourly observations per day (N(sub cf)) for solar zenith angle Theta(sub 0) less than 80 degrees was estimated for each 0.1 degree location of the Intra-Americas Sea. The number of Sun-glint-affected hourly observations per day [Ns(sub sg)] was also calculated based on the planned GEO-CAPE observation geometry and realistic wind speed. High-latitude and equatorial oceans showed the lowest N(sub cf) (less than 2.4) in all climatological months, and highest N(sub cf) was observed in the Gulf of Mexico (GoM) and Caribbean (greater than 4.5). Different regions showed differences in seasonality of cloud-free conditions and also showed differences in the hour of a day at which the satellite observations would have the maximal cloud-free and glint-free probability (Temperature maximum). Cloud cover from Moderate Resolution Imaging Spectroradiometer (MODIS) 1 km measurements are greater than 10 degrees higher than those from the MODIS 250 m measurements, supporting ocean color missions at subkilometer resolutions to enhance both spatial coverage and temporal frequency. These findings provide valuable information for GEO-CAPE mission planning to maximize its science value through minimizing the impacts of clouds and Sun glint.

Cloud and Sun-glint statistics derived from GOES and MODIS observations over the Intra-Americas Sea for GEO-CAPE mission planning

NASA Astrophysics Data System (ADS)

Feng, Lian; Hu, Chuanmin; Barnes, Brian B.; Mannino, Antonio; Heidinger, Andrew K.; Strabala, Kathleen; Iraci, Laura T.

2017-02-01

Knowledge of cloud cover, frequency, and duration is not only important to study cloud dynamics, but also critical in determining when and where to take ocean measurements from geostationary orbits such as the Geostationary Coastal and Air Pollution Events (GEO-CAPE) mission due to the challenges in achieving complete hemispheric coverage of coastal oceans, estuaries, and inland waters at hourly frequency. Using GOES hourly measurements at 4 km nadir resolution between 2006 and 2011, the number of cloud-free hourly observations per day (Ncf) for solar zenith angle θo < 80° was estimated for each 0.1° location of the Intra-Americas Sea. The number of Sun-glint-affected hourly observations per day (Nsg) was also calculated based on the planned GEO-CAPE observation geometry and realistic wind speed. High-latitude and equatorial oceans showed the lowest Ncf (<2.4) in all climatological months, and highest Ncf was observed in the Gulf of Mexico (GoM) and Caribbean (>4.5). Different regions showed differences in seasonality of cloud-free conditions and also showed differences in the hour of a day at which the satellite observations would have the maximal cloud-free and glint-free probability (Tmax). Cloud cover from Moderate Resolution Imaging Spectroradiometer (MODIS) 1 km measurements are >10% higher than those from the MODIS 250 m measurements, supporting ocean color missions at subkilometer resolutions to enhance both spatial coverage and temporal frequency. These findings provide valuable information for GEO-CAPE mission planning to maximize its science value through minimizing the impacts of clouds and Sun glint.

Spatial and Temporal Inter-Relationship between Anomalies and Trends of Temperature, Moisture, Cloud Cover and OLR as Observed by AIRS/AMSU on Aqua

NASA Technical Reports Server (NTRS)

Susskind, Joel; Molnar, Gyula

2009-01-01

AIRS/AMSU is the advanced IR/MW atmospheric sounding system launched on EOS Aqua in May 2002. Products derived from AIRS/AMSU by the AIRS Science Team include surface skin temperature and atmospheric temperature profiled; atmospheric humidity profiles, fractional cloud clover and cloud top pressure, and OLR. Products covering the period September 2002 through the present have been derived from AIRS/AMSU using the AIRS Science Team Version 5 retrieval algorithm. In this paper, we will show results covering the time period September 2006 - November 2008. This time period is marked by a substantial warming trend of Northern Hemisphere Extra-tropical land surface skin temperatures, as well as pronounced El Nino - La Nina episodes. These both influence the spatial and temporal anomaly patterns of atmospheric temperature and moisture profiles, as well as of cloud cover and Clear Sky and All Sky OLR. The relationships between temporal and spatial anomalies of these parameters over this time period, as determined from AIRS/AMSU observations, will be shown with particular emphasis on which contribute significantly to OLR anomalies in each of the tropics and extra-tropics. Results will also be shown to evaluate the anomalies and trends of temperature profiles and OLR as determined from analysis of AIRS/AMSU data. Global and regional trends during the 6 1/3 year time period are not necessarily indicative of what has happened in the past, or what may happen in the future. Nevertheless, the inter-relationships of spatial and temporal anomalies of atmospheric geophysical parameters with those of surface skin temperature are indicative of climate processes, and can be used to test the performance of climate models when driven by changes in surface temperatures.

Chatter detection in turning using persistent homology

NASA Astrophysics Data System (ADS)

Khasawneh, Firas A.; Munch, Elizabeth

2016-03-01

This paper describes a new approach for ascertaining the stability of stochastic dynamical systems in their parameter space by examining their time series using topological data analysis (TDA). We illustrate the approach using a nonlinear delayed model that describes the tool oscillations due to self-excited vibrations in turning. Each time series is generated using the Euler-Maruyama method and a corresponding point cloud is obtained using the Takens embedding. The point cloud can then be analyzed using a tool from TDA known as persistent homology. The results of this study show that the described approach can be used for analyzing datasets of delay dynamical systems generated both from numerical simulation and experimental data. The contributions of this paper include presenting for the first time a topological approach for investigating the stability of a class of nonlinear stochastic delay equations, and introducing a new application of TDA to machining processes.

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

NASA Technical Reports Server (NTRS)

Minnis, P.; Harrison, E. F.

1984-01-01

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.

Analyses of the cloud contents of multispectral imagery from LANDSAT 2: Mesoscale assessments of cloud and rainfall over the British Isles

NASA Technical Reports Server (NTRS)

Barrett, E. C.; Grant, C. K. (Principal Investigator)

1977-01-01

The author has identified the following significant results. It was demonstrated that satellites with sufficiently high resolution capability in the visible region of the electromagnetic spectrum could be used to check the accuracy of estimates of total cloud amount assessed subjectively from the ground, and to reveal areas of performance in which corrections should be made. It was also demonstrated that, in middle latitude in summer, cloud shadow may obscure at least half as much again of the land surface covered by an individual LANDSAT frame as the cloud itself. That proportion would increase with latitude and/or time of year towards the winter solstice. Analyses of sample multispectral images for six different categories of clouds in summer revealed marked differences between the reflectance characteristics of cloud fields in the visible/near infrared region of the spectrum.

Enhancement of the MODIS Snow and Ice Product Suite Utilizing Image Segmentation

NASA Technical Reports Server (NTRS)

Tilton, James C.; Hall, Dorothy K.; Riggs, George A.

2006-01-01

A problem has been noticed with the current NODIS Snow and Ice Product in that fringes of certain snow fields are labeled as "cloud" whereas close inspection of the data indicates that the correct labeling is a non-cloud category such as snow or land. This occurs because the current MODIS Snow and Ice Product generation algorithm relies solely on the MODIS Cloud Mask Product for the labeling of image pixels as cloud. It is proposed here that information obtained from image segmentation can be used to determine when it is appropriate to override the cloud indication from the cloud mask product. Initial tests show that this approach can significantly reduce the cloud "fringing" in modified snow cover labeling. More comprehensive testing is required to determine whether or not this approach consistently improves the accuracy of the snow and ice product.

Radiative energy balance of the Venus mesosphere

NASA Astrophysics Data System (ADS)

Haus, R.; Goering, H.

1990-03-01

An accurate radiative transfer model for line-by-line gaseous absorption, as well as for cloud absorption and multiple scattering, is used in the present calculation of solar heating and thermal cooling rates for standard temperature profiles and temperatures yielded by the Venera 15 Fourier Spectrometer Experiment. A strong dependency is noted for heating and cooling rates on cloud-structure variations. The Venus mesosphere is characterized by main cloud-cover heating and overlying-haze cooling. These results are applicable to Venus atmosphere dynamical models.

Clouds Optically Gridded by Stereo COGS product

DOE Office of Scientific and Technical Information (OSTI.GOV)

Oktem, Rusen; Romps, David

COGS product is a 4D grid of cloudiness covering a 6 km × 6 km × 6 km cube centered at the central facility of SGP site at a spatial resolution of 50 meters and a temporal resolution of 20 seconds. The dimensions are X, Y, Z, and time, where X,Y, Z, correspond to east-west, north-south, and altitude of the grid point, respectively. COGS takes on values 0, 1, and -1 denoting "cloud", "no cloud", and "not available". 

A Gridded Climatology of Clouds over Land (1971-1996) and Ocean (1954-2008) from Surface Observations Worldwide (NDP-026E)*

DOE Data Explorer

Hahn, C. J. [University of Arizona; Warren, S. G. [University of Washington

2007-01-01

Surface synoptic weather reports from ships and land stations worldwide were processed to produce a global cloud climatology which includes: total cloud cover, the amount and frequency of occurrence of nine cloud types within three levels of the troposphere, the frequency of occurrence of clear sky and of precipitation, the base heights of low clouds, and the non-overlapped amounts of middle and high clouds. Synoptic weather reports are made every three hours; the cloud information in a report is obtained visually by human observers. The reports used here cover the period 1971-96 for land and 1954-2008 for ocean. This digital archive provides multi-year monthly, seasonal, and annual averages in 5x5-degree grid boxes (or 10x10-degree boxes for some quantities over the ocean). Daytime and nighttime averages, as well as the diurnal average (average of day and night), are given. Nighttime averages were computed using only those reports that met an "illuminance criterion" (i.e., made under adequate moonlight or twilight), thus minimizing the "night-detection bias" and making possible the determination of diurnal cycles and nighttime trends for cloud types. The phase and amplitude of the first harmonic of both the diurnal cycle and the annual cycle are given for the various cloud types. Cloud averages for individual years are also given for the ocean for each of 4 seasons, and for each of the 12 months (daytime-only averages for the months). [Individual years for land are not gridded, but are given for individual stations in a companion data set, CDIAC's NDP-026D).] This analysis used 185 million reports from 5388 weather stations on continents and islands, and 50 million reports from ships; these reports passed a series of quality-control checks. This analysis updates (and in most ways supercedes) the previous cloud climatology constructed by the authors in the 1980s. Many of the long-term averages described here are mapped on the University of Washington, Department of Atmospheric Sciences Web site. The Online Cloud Atlas containing NDP-026E data is available via the University of Washington.

Deployment of the third-generation infrared cloud imager: A two-year study of Arctic clouds at Barrow, Alaska

NASA Astrophysics Data System (ADS)

Nugent, Paul Winston

Cloud cover is an important but poorly understood component of current climate models, and although climate change is most easily observed in the Arctic, cloud data in the Arctic is unreliable or simply unavailable. Ground-based infrared cloud imaging has the potential to fill this gap. This technique uses a thermal infrared camera to observe cloud amount, cloud optical depth, and cloud spatial distribution at a particular location. The Montana State University Optical Remote Sensor Laboratory has developed the ground-based Infrared Cloud Imager (ICI) instrument to measure spatial and temporal cloud data. To build an ICI for Arctic sites required the system to be engineered to overcome the challenges of this environment. Of particular challenge was keeping the system calibration and data processing accurate through the severe temperature changes. Another significant challenge was that weak emission from the cold, dry Arctic atmosphere pushed the camera used in the instrument to its operational limits. To gain an understanding of the operation of the ICI systems for the Arctic and to gather critical data on Arctic clouds, a prototype arctic ICI was deployed in Barrow, AK from July 2012 through July 2014. To understand the long-term operation of an ICI in the arctic, a study was conducted of the ICI system accuracy in relation to co-located active and passive sensors. Understanding the operation of this system in the Arctic environment required careful characterization of the full optical system, including the lens, filter, and detector. Alternative data processing techniques using decision trees and support vector machines were studied to improve data accuracy and reduce dependence on auxiliary instrument data and the resulting accuracy is reported here. The work described in this project was part of the effort to develop a fourth-generation ICI ready to be deployed in the Arctic. This system will serve a critical role in developing our understanding of cloud cover in the Arctic, an important but poorly understood region of the world.

Predicting Clear-Sky Reflectance Over Snow/Ice in Polar Regions

NASA Technical Reports Server (NTRS)

Chen, Yan; Sun-Mack, Sunny; Arduini, Robert F.; Hong, Gang; Minnis, Patrick

2015-01-01

Satellite remote sensing of clouds requires an accurate estimate of the clear-sky radiances for a given scene to detect clouds and aerosols and to retrieve their microphysical properties. Knowing the spatial and angular variability of clear-sky albedo is essential for predicting clear-sky radiance at solar wavelengths. The Clouds and the Earth's Radiant Energy System (CERES) Project uses the nearinfrared (NIR; 1.24, 1.6 or 2.13 micrometers), visible (VIS; 0.63 micrometers) and vegetation (VEG; 0.86 micrometers) channels available on the Terra and Aqua Moderate Resolution Imaging Spectroradiometer (MODIS) to help identify clouds and retrieve their properties in both snow-free and snow-covered conditions. Thus, it is critical to have reliable distributions of clear-sky albedo for all of these channels. In CERES Edition 4 (Ed4), the 1.24-micrometer channel is used to retrieve cloud optical depth over snow/ice-covered surfaces. Thus, it is especially critical to accurately predict the 1.24-micrometer clear-sky albedo alpha and reflectance rho for a given location and time. Snow albedo and reflectance patterns are very complex due to surface texture, particle shapes and sizes, melt water, and vegetation protrusions from the snow surface. To minimize those effects, this study focuses on the permanent snow cover of Antarctica where vegetation is absent and melt water is minimal. Clear-sky albedos are determined as a function of solar zenith angle (SZA) from observations over all scenes determined to be cloud-free to produce a normalized directional albedo model (DRM). The DRM is used to develop alpha(SZA=0 degrees) on 10 foot grid for each season. These values provide the basis for predicting r at any location and set of viewing & illumination conditions. This paper examines the accuracy of this approach for two theoretical snow surface reflectance models.

Estimating the Direct Radiative Effect of Absorbing Aerosols Overlying Marine Boundary Layer Clouds in the Southeast Atlantic Using MODIS and CALIOP

NASA Technical Reports Server (NTRS)

Meyer, Kerry; Platnick, Steven; Oreopoulos, Lazaros; Lee, Dongmin

2013-01-01

Absorbing aerosols such as smoke strongly absorb solar radiation, particularly at ultraviolet and visible/near-infrared (VIS/NIR) wavelengths, and their presence above clouds can have considerable implications. It has been previously shown that they have a positive (i.e., warming) direct aerosol radiative effect (DARE) when overlying bright clouds. Additionally, they can cause biased passive instrument satellite retrievals in techniques that rely on VIS/NIR wavelengths for inferring the cloud optical thickness (COT) and effective radius (re) of underlying clouds, which can in turn yield biased above-cloud DARE estimates. Here we investigate Moderate Resolution Imaging Spectroradiometer (MODIS) cloud optical property retrieval biases due to overlying absorbing aerosols observed by Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) and examine the impact of these biases on above-cloud DARE estimates. The investigation focuses on a region in the southeast Atlantic Ocean during August and September (2006-2011), where smoke from biomass burning in southern Africa overlies persistent marine boundary layer stratocumulus clouds. Adjusting for above-cloud aerosol attenuation yields increases in the regional mean liquid COT (averaged over all ocean-only liquid clouds) by roughly 6%; mean re increases by roughly 2.6%, almost exclusively due to the COT adjustment in the non-orthogonal retrieval space. It is found that these two biases lead to an underestimate of DARE. For liquid cloud Aqua MODIS pixels with CALIOP-observed above-cloud smoke, the regional mean above-cloud radiative forcing efficiency (DARE per unit aerosol optical depth (AOD)) at time of observation (near local noon for Aqua overpass) increases from 50.9Wm(sup-2)AOD(sup-1) to 65.1Wm(sup-2)AOD(sup -1) when using bias-adjusted instead of nonadjusted MODIS cloud retrievals.

Jupiter Equatorial Region in a Methane Band Time Set 1

NASA Image and Video Library

1998-03-06

Mosaic of an equatorial "hotspot" on Jupiter at 889 nanometers (nm). The mosaic covers an area of 34,000 kilometers by 11,000 kilometers. Light at 889 nm is strongly absorbed by atmospheric methane. This image shows the features of a hazy cloud layer tens of kilometers above Jupiter's main visible cloud deck. This haze varies in height but appears to be present over the entire region. Small patches of very bright clouds may be similar to terrestrial thunderstorms. The dark region near the center of the mosaic is an equatorial "hotspot" similar to the Galileo Probe entry site. These features are holes in the bright, reflective, equatorial cloud layer where warmer thermal emission from Jupiter's deep atmosphere can pass through. The circulation patterns observed here along with the composition measurements from the Galileo Probe suggest that dry air may be converging and sinking over these regions, maintaining their cloud-free appearance. North is at the top. The mosaic covers latitudes 1 to 10 degrees and is centered at longitude 336 degrees West. The smallest resolved features are tens of kilometers in size. These images were taken on December 17, 1996, at a range of 1.5 million kilometers by the Solid State Imaging system aboard NASA's Galileo spacecraft. http://photojournal.jpl.nasa.gov/catalog/PIA01200

Satellite-based trends of solar radiation and cloud parameters in Europe

NASA Astrophysics Data System (ADS)

Pfeifroth, Uwe; Bojanowski, Jedrzej S.; Clerbaux, Nicolas; Manara, Veronica; Sanchez-Lorenzo, Arturo; Trentmann, Jörg; Walawender, Jakub P.; Hollmann, Rainer

2018-04-01

Solar radiation is the main driver of the Earth's climate. Measuring solar radiation and analysing its interaction with clouds are essential for the understanding of the climate system. The EUMETSAT Satellite Application Facility on Climate Monitoring (CM SAF) generates satellite-based, high-quality climate data records, with a focus on the energy balance and water cycle. Here, multiple of these data records are analyzed in a common framework to assess the consistency in trends and spatio-temporal variability of surface solar radiation, top-of-atmosphere reflected solar radiation and cloud fraction. This multi-parameter analysis focuses on Europe and covers the time period from 1992 to 2015. A high correlation between these three variables has been found over Europe. An overall consistency of the climate data records reveals an increase of surface solar radiation and a decrease in top-of-atmosphere reflected radiation. In addition, those trends are confirmed by negative trends in cloud cover. This consistency documents the high quality and stability of the CM SAF climate data records, which are mostly derived independently from each other. The results of this study indicate that one of the main reasons for the positive trend in surface solar radiation since the 1990's is a decrease in cloud coverage even if an aerosol contribution cannot be completely ruled out.

Insights into low-latitude cloud feedbacks from high-resolution models.

PubMed

Bretherton, Christopher S

2015-11-13

Cloud feedbacks are a leading source of uncertainty in the climate sensitivity simulated by global climate models (GCMs). Low-latitude boundary-layer and cumulus cloud regimes are particularly problematic, because they are sustained by tight interactions between clouds and unresolved turbulent circulations. Turbulence-resolving models better simulate such cloud regimes and support the GCM consensus that they contribute to positive global cloud feedbacks. Large-eddy simulations using sub-100 m grid spacings over small computational domains elucidate marine boundary-layer cloud response to greenhouse warming. Four observationally supported mechanisms contribute: 'thermodynamic' cloudiness reduction from warming of the atmosphere-ocean column, 'radiative' cloudiness reduction from CO2- and H2O-induced increase in atmospheric emissivity aloft, 'stability-induced' cloud increase from increased lower tropospheric stratification, and 'dynamical' cloudiness increase from reduced subsidence. The cloudiness reduction mechanisms typically dominate, giving positive shortwave cloud feedback. Cloud-resolving models with horizontal grid spacings of a few kilometres illuminate how cumulonimbus cloud systems affect climate feedbacks. Limited-area simulations and superparameterized GCMs show upward shift and slight reduction of cloud cover in a warmer climate, implying positive cloud feedbacks. A global cloud-resolving model suggests tropical cirrus increases in a warmer climate, producing positive longwave cloud feedback, but results are sensitive to subgrid turbulence and ice microphysics schemes. © 2015 The Author(s).