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

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

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.

Validation of Land Cover Maps Utilizing Astronaut Acquired Imagery

NASA Technical Reports Server (NTRS)

Estes, John E.; Gebelein, Jennifer

1999-01-01

This report is produced in accordance with the requirements outlined in the NASA Research Grant NAG9-1032 titled "Validation of Land Cover Maps Utilizing Astronaut Acquired Imagery". This grant funds the Remote Sensing Research Unit of the University of California, Santa Barbara. This document summarizes the research progress and accomplishments to date and describes current on-going research activities. Even though this grant has technically expired, in a contractual sense, work continues on this project. Therefore, this summary will include all work done through and 5 May 1999. The principal goal of this effort is to test the accuracy of a sub-regional portion of an AVHRR-based land cover product. Land cover mapped to three different classification systems, in the southwestern United States, have been subjected to two specific accuracy assessments. One assessment utilizing astronaut acquired photography, and a second assessment employing Landsat Thematic Mapper imagery, augmented in some cases, high aerial photography. Validation of these three land cover products has proceeded using a stratified sampling methodology. We believe this research will provide an important initial test of the potential use of imagery acquired from Shuttle and ultimately the International Space Station (ISS) for the operational validation of the Moderate Resolution Imaging Spectrometer (MODIS) land cover products.

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.

Relationships between nocturnal winter road slipperiness, cloud cover and surface temperature

NASA Astrophysics Data System (ADS)

Grimbacher, T.; Schmid, W.

2003-04-01

Ice and Snow are important risks for road traffic. In this study we show several events of slipperiness in Switzerland, mainly caused by rain or snow falling on a frozen surface. Other reasons for slippery conditions are frost or freezing dew in clear nights and nocturnal clearing after precipitation, which goes along with radiative cooling. The main parameters of road weather forecasts are precipitation, cloudiness and surface temperature. Precipitation is well predictable with weather radars and radar nowcasting algorithms. Temperatures are often taken from numerical weather prediction models, but because of changes in cloud cover these model values are inaccurate in terms of predicting the onset of freezing. Cloudiness, especially the advection, formation and dissipation of clouds and their interaction with surface temperatures, is one of the major unsolved problems of road weather forecasts. Cloud cover and the temperature difference between air and surface temperature are important parameters of the radiation balance. In this contribution, we show the relationship between them, proved at several stations all over Switzerland. We found a quadratic correlation coefficient of typically 60% and improved it considering other meteorological parameters like wind speed and surface water. The acquired relationship may vary from one station to another, but we conclude that temperature difference is a signature for nocturnal cloudiness. We investigated nocturnal cloudiness for two cases from winters 2002 and 2003 in the canton of Lucerne in central Switzerland. There, an ultra-dense combination of two networks with together 55 stations within 50x50 km^2 is operated, measuring air and surface temperature, wind and other road weather parameters. With the aid of our equations, temperature differences detected from this network were converted into cloud maps. A comparison between precipitation seen by radar, cloud maps and surface temperatures shows that there are similar

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 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.

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

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.

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.

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.

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.

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.

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.

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.

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.

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…

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.

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.

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.

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

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

Development and Evaluation of a Cloud-Gap-Filled MODIS Daily Snow-Cover Product

NASA Technical Reports Server (NTRS)

Hall, Dorothy K.; Riggs, George A.; Foster, James L.; Kumar, Sujay V.

2010-01-01

The utility of the Moderate Resolution Imaging Spectroradiometer (MODIS) snow-cover products is limited by cloud cover which causes gaps in the daily snow-cover map products. We describe a cloud-gap-filled (CGF) daily snowcover map using a simple algorithm to track cloud persistence, to account for the uncertainty created by the age of the snow observation. Developed from the 0.050 resolution climate-modeling grid daily snow-cover product, MOD10C1, each grid cell of the CGF map provides a cloud-persistence count (CPC) that tells whether the current or a prior day was used to make the snow decision. Percentage of grid cells "observable" is shown to increase dramatically when prior days are considered. The effectiveness of the CGF product is evaluated by conducting a suite of data assimilation experiments using the community Noah land surface model in the NASA Land Information System (LIS) framework. The Noah model forecasts of snow conditions, such as snow-water equivalent (SWE), are updated based on the observations of snow cover which are obtained either from the MOD1 OC1 standard product or the new CGF product. The assimilation integrations using the CGF maps provide domain averaged bias improvement of -11 %, whereas such improvement using the standard MOD1 OC1 maps is -3%. These improvements suggest that the Noah model underestimates SWE and snow depth fields, and that the assimilation integrations contribute to correcting this systematic error. We conclude that the gap-filling strategy is an effective approach for increasing cloud-free observations of snow cover.

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

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.

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

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.

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.

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

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.

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.

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.

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.

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

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

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.

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.

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.

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

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

Seasonal Change in Titan's Cloud Activity

NASA Astrophysics Data System (ADS)

Schaller, E. L.; Brown, M. E.; Roe, H. G.

2006-12-01

We have acquired whole disk spectra of Titan on nineteen nights with IRTF/SpeX over a three-month period in the spring of 2006 and will acquire data on ~50 additional nights between September and December 2006. The data encompass the spectral range of 0.8 to 2.4 microns at a resolution of 375. These disk- integrated spectra allow us to determine Titan's total fractional cloud coverage and altitudes of clouds present. We find that Titan had less than 0.15% fractional cloud coverage on all but one of the nineteen nights. The near lack of cloud activity in these spectra is in sharp contrast to nearly every spectrum taken from 1995-1999 with UKIRT by Griffith et al. (1998 &2000) who found rapidly varying clouds covering ~0.5% of Titan's disk. The differences in these two similar datasets indicate a striking seasonal change in the behavior of Titan's clouds. Observations of the latitudes, magnitudes, altitudes, and frequencies of Titan's clouds as Titan moves toward southern autumnal equinox in 2009 will help elucidate when and how Titan's methane hydrological cycle changes with season.

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

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

Road Signs Detection and Recognition Utilizing Images and 3d Point Cloud Acquired by Mobile Mapping System

NASA Astrophysics Data System (ADS)

Li, Y. H.; Shinohara, T.; Satoh, T.; Tachibana, K.

2016-06-01

High-definition and highly accurate road maps are necessary for the realization of automated driving, and road signs are among the most important element in the road map. Therefore, a technique is necessary which can acquire information about all kinds of road signs automatically and efficiently. Due to the continuous technical advancement of Mobile Mapping System (MMS), it has become possible to acquire large number of images and 3d point cloud efficiently with highly precise position information. In this paper, we present an automatic road sign detection and recognition approach utilizing both images and 3D point cloud acquired by MMS. The proposed approach consists of three stages: 1) detection of road signs from images based on their color and shape features using object based image analysis method, 2) filtering out of over detected candidates utilizing size and position information estimated from 3D point cloud, region of candidates and camera information, and 3) road sign recognition using template matching method after shape normalization. The effectiveness of proposed approach was evaluated by testing dataset, acquired from more than 180 km of different types of roads in Japan. The results show a very high success in detection and recognition of road signs, even under the challenging conditions such as discoloration, deformation and in spite of partial occlusions.

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.

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

NASA Sees Hurricane Arthur's Cloud-Covered Eye

NASA Image and Video Library

2014-07-03

This visible image of Tropical Storm Arthur was taken by the MODIS instrument aboard NASA's Aqua satellite on July 2 at 18:50 UTC (2:50 p.m. EDT). A cloud-covered eye is clearly visible. Credit: NASA Goddard MODIS Rapid Response Team Read more: www.nasa.gov/content/goddard/arthur-atlantic/ 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

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%.

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.

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.

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.

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%).

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

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.

Traffic sign detection in MLS acquired point clouds for geometric and image-based semantic inventory

NASA Astrophysics Data System (ADS)

Soilán, Mario; Riveiro, Belén; Martínez-Sánchez, Joaquín; Arias, Pedro

2016-04-01

Nowadays, mobile laser scanning has become a valid technology for infrastructure inspection. This technology permits collecting accurate 3D point clouds of urban and road environments and the geometric and semantic analysis of data became an active research topic in the last years. This paper focuses on the detection of vertical traffic signs in 3D point clouds acquired by a LYNX Mobile Mapper system, comprised of laser scanning and RGB cameras. Each traffic sign is automatically detected in the LiDAR point cloud, and its main geometric parameters can be automatically extracted, therefore aiding the inventory process. Furthermore, the 3D position of traffic signs are reprojected on the 2D images, which are spatially and temporally synced with the point cloud. Image analysis allows for recognizing the traffic sign semantics using machine learning approaches. The presented method was tested in road and urban scenarios in Galicia (Spain). The recall results for traffic sign detection are close to 98%, and existing false positives can be easily filtered after point cloud projection. Finally, the lack of a large, publicly available Spanish traffic sign database is pointed out.

Winter sky brightness and cloud cover at Dome A, Antarctica

NASA Astrophysics Data System (ADS)

Moore, Anna M.; Yang, Yi; Fu, Jianning; Ashley, Michael C. B.; Cui, Xiangqun; Feng, Long Long; Gong, Xuefei; Hu, Zhongwen; Lawrence, Jon S.; Luong-Van, Daniel M.; Riddle, Reed; Shang, Zhaohui; Sims, Geoff; Storey, John W. V.; Tothill, Nicholas F. H.; Travouillon, Tony; Wang, Lifan; Yang, Huigen; Yang, Ji; Zhou, Xu; Zhu, Zhenxi

2013-01-01

At the summit of the Antarctic plateau, Dome A offers an intriguing location for future large scale optical astronomical observatories. The Gattini Dome A project was created to measure the optical sky brightness and large area cloud cover of the winter-time sky above this high altitude Antarctic site. The wide field camera and multi-filter system was installed on the PLATO instrument module as part of the Chinese-led traverse to Dome A in January 2008. This automated wide field camera consists of an Apogee U4000 interline CCD coupled to a Nikon fisheye lens enclosed in a heated container with glass window. The system contains a filter mechanism providing a suite of standard astronomical photometric filters (Bessell B, V, R) and a long-pass red filter for the detection and monitoring of airglow emission. The system operated continuously throughout the 2009, and 2011 winter seasons and part-way through the 2010 season, recording long exposure images sequentially for each filter. We have in hand one complete winter-time dataset (2009) returned via a manned traverse. We present here the first measurements of sky brightness in the photometric V band, cloud cover statistics measured so far and an estimate of the extinction.

Winter sky brightness & cloud cover over Dome A

NASA Astrophysics Data System (ADS)

Yang, Yi; Moore, A. M.; Fu, J.; Ashley, M.; Cui, X.; Feng, L.; Gong, X.; Hu, Z.; Laurence, J.; LuongVan, D.; Riddle, R. L.; Shang, Z.; Sims, G.; Storey, J.; Tothill, N.; Travouillon, T.; Wang, L.; Yang, H.; Yang, J.; Zhou, X.; Zhu, Z.; Burton, M. G.

2014-01-01

At the summit of the Antarctic plateau, Dome A offers an intriguing location for future large scale optical astronomical Observatories. The Gattini DomeA project was created to measure the optical sky brightness and large area cloud cover of the winter-time sky above this high altitude Antarctic site. The wide field camera and multi-filter system was installed on the PLATO instrument module as part of the Chinese-led traverse to Dome A in January 2008. This automated wide field camera consists of an Apogee U4000 interline CCD coupled to a Nikon fish-eye lens enclosed in a heated container with glass window. The system contains a filter mechanism providing a suite of standard astronomical photometric filters (Bessell B, V, R), however, the absence of tracking systems, together with the ultra large field of view 85 degrees) and strong distortion have driven us to seek a unique way to build our data reduction pipeline. We present here the first measurements of sky brightness in the photometric B, V, and R band, cloud cover statistics measured during the 2009 winter season and an estimate of the transparency. In addition, we present example light curves for bright targets to emphasize the unprecedented observational window function available from this ground-based location. A ~0.2 magnitude agreement of our simultaneous test at Palomar Observatory with NSBM(National Sky Brightness Monitor), as well as an 0.04 magnitude photometric accuracy for typical 6th magnitude stars limited by the instrument design, indicating we obtained reasonable results based on our ~7mm effective aperture fish-eye lens.

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).

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.

Effects of Varying Cloud Cover on Springtime Runoff in California's Sierra Nevada

NASA Astrophysics Data System (ADS)

Sumargo, E.; Cayan, D. R.

2017-12-01

This study investigates how cloud cover modifies snowmelt-runoff processes in Sierra Nevada watersheds during dry and wet periods. We use two of the California Department of Water Resources' (DWR's) quasi-operational models of the Tuolumne and Merced River basins developed from the USGS Precipitation-Runoff Modeling System (PRMS) hydrologic modeling system. Model simulations are conducted after a validated optimization of model performance in simulating recent (1996-2014) historical variability in the Tuolumne and Merced basins using solar radiation (Qsi) derived from Geostationary Operational Environmental Satellite (GOES) remote sensing. Specifically, the questions we address are: 1) how sensitive are snowmelt and runoff in the Tuolumne and Merced River basins to Qsi variability associated with cloud cover variations?, and 2) does this sensitivity change in dry vs. wet years? To address these question, we conduct two experiments, where: E1) theoretical clear-sky Qsi is used as an input to PRMS, and E2) the annual harmonic cycle of Qsi is used as an input to PRMS. The resulting hydrographs from these experiments exhibit changes in peak streamflow timing by several days to a few weeks and smaller streamflow variability when compared to the actual flows and the original simulations. For E1, despite some variations, this pattern persists when the result is evaluated for dry-year and wet-year subsets, reflecting the consistently higher Qsi input available. For E2, the hydrograph shows a later spring-summer streamflow peak in the dry-year subset when compared to the original simulations, indicating the relative importance of the modulating effect of cloud cover on snowmelt-runoff in drier years.

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...

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.

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.

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

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.

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

Assessing the consistency of UAV-derived point clouds and images acquired at different altitudes

NASA Astrophysics Data System (ADS)

Ozcan, O.

2016-12-01

Unmanned Aerial Vehicles (UAVs) offer several advantages in terms of cost and image resolution compared to terrestrial photogrammetry and satellite remote sensing system. Nowadays, UAVs that bridge the gap between the satellite scale and field scale applications were initiated to be used in various application areas to acquire hyperspatial and high temporal resolution imageries due to working capacity and acquiring in a short span of time with regard to conventional photogrammetry methods. UAVs have been used for various fields such as for the creation of 3-D earth models, production of high resolution orthophotos, network planning, field monitoring and agricultural lands as well. Thus, geometric accuracy of orthophotos and volumetric accuracy of point clouds are of capital importance for land surveying applications. Correspondingly, Structure from Motion (SfM) photogrammetry, which is frequently used in conjunction with UAV, recently appeared in environmental sciences as an impressive tool allowing for the creation of 3-D models from unstructured imagery. In this study, it was aimed to reveal the spatial accuracy of the images acquired from integrated digital camera and the volumetric accuracy of Digital Surface Models (DSMs) which were derived from UAV flight plans at different altitudes using SfM methodology. Low-altitude multispectral overlapping aerial photography was collected at the altitudes of 30 to 100 meters and georeferenced with RTK-GPS ground control points. These altitudes allow hyperspatial imagery with the resolutions of 1-5 cm depending upon the sensor being used. Preliminary results revealed that the vertical comparison of UAV-derived point clouds with respect to GPS measurements pointed out an average distance at cm-level. Larger values are found in areas where instantaneous changes in surface are present.

Mobile Laser Scanning along Dieppe coastal cliffs: reliability of the acquired point clouds applied to rockfall assessments

NASA Astrophysics Data System (ADS)

Michoud, Clément; Carrea, Dario; Augereau, Emmanuel; Cancouët, Romain; Costa, Stéphane; Davidson, Robert; Delacourt, Chirstophe; Derron, Marc-Henri; Jaboyedoff, Michel; Letortu, Pauline; Maquaire, Olivier

2013-04-01

Dieppe coastal cliffs, in Normandy, France, are mainly formed by sub-horizontal deposits of chalk and flintstone. Largely destabilized by an intense weathering and the Channel sea erosion, small and large rockfalls are regularly observed and contribute to retrogressive cliff processes. During autumn 2012, cliff and intertidal topographies have been acquired with a Terrestrial Laser Scanner (TLS) and a Mobile Laser Scanner (MLS), coupled with seafloor bathymetries realized with a multibeam echosounder (MBES). MLS is a recent development of laser scanning based on the same theoretical principles of aerial LiDAR, but using smaller, cheaper and portable devices. The MLS system, which is composed by an accurate dynamic positioning and orientation (INS) devices and a long range LiDAR, is mounted on a marine vessel; it is then possible to quickly acquire in motion georeferenced LiDAR point clouds with a resolution of about 15 cm. For example, it takes about 1 h to scan of shoreline of 2 km long. MLS is becoming a promising technique supporting erosion and rockfall assessments along the shores of lakes, fjords or seas. In this study, the MLS system used to acquire cliffs and intertidal areas of the Cap d'Ailly was composed by the INS Applanix POS-MV 320 V4 and the LiDAR Optech Ilirs LR. On the same day, three MLS scans with large overlaps (J1, J21 and J3) have been performed at ranges from 600 m at 4 knots (low tide) up to 200 m at 2.2 knots (up tide) with a calm sea at 2.5 Beaufort (small wavelets). Mean scan resolutions go from 26 cm for far scan (J1) to about 8.1 cm for close scan (J3). Moreover, one TLS point cloud on this test site has been acquired with a mean resolution of about 2.3 cm, using a Riegl LMS Z390i. In order to quantify the reliability of the methodology, comparisons between scans have been realized with the software Polyworks™, calculating shortest distances between points of one cloud and the interpolated surface of the reference point cloud. A Mat

Photogrammetry and photo interpretation applied to analyses of cloud cover, cloud type, and cloud motion

NASA Technical Reports Server (NTRS)

Larsen, P. A.

1972-01-01

A determination was made of the areal extent of terrain obscured by clouds and cloud shadows on a portion of an Apollo 9 photograph at the instant of exposure. This photogrammetrically determined area was then compared to the cloud coverage reported by surface weather observers at approximately the same time and location, as a check on result quality. Stereograms prepared from Apollo 9 vertical photographs, illustrating various percentages of cloud coverage, are presented to help provide a quantitative appreciation of the degradation of terrain photography by clouds and their attendant shadows. A scheme, developed for the U.S. Navy, utilizing pattern recognition techniques for determining cloud motion from sequences of satellite photographs, is summarized. Clouds, turbulence, haze, and solar altitude, four elements of our natural environment which affect aerial photographic missions, are each discussed in terms of their effects on imagery obtained by aerial photography. Data of a type useful to aerial photographic mission planners, expressing photographic ground coverage in terms of flying height above terrain and camera focal length, for a standard aerial photograph format, are provided. Two oblique orbital photographs taken during the Apollo 9 flight are shown, and photo-interpretations, discussing the cloud types imaged and certain visible geographical features, are provided.

Development of the Landsat Data Continuity Mission Cloud Cover Assessment Algorithms

USGS Publications Warehouse

Scaramuzza, Pat; Bouchard, M.A.; Dwyer, John L.

2012-01-01

The upcoming launch of the Operational Land Imager (OLI) will start the next era of the Landsat program. However, the Automated Cloud-Cover Assessment (CCA) (ACCA) algorithm used on Landsat 7 requires a thermal band and is thus not suited for OLI. There will be a thermal instrument on the Landsat Data Continuity Mission (LDCM)-the Thermal Infrared Sensor-which may not be available during all OLI collections. This illustrates a need for CCA for LDCM in the absence of thermal data. To research possibilities for full-resolution OLI cloud assessment, a global data set of 207 Landsat 7 scenes with manually generated cloud masks was created. It was used to evaluate the ACCA algorithm, showing that the algorithm correctly classified 79.9% of a standard test subset of 3.95 109 pixels. The data set was also used to develop and validate two successor algorithms for use with OLI data-one derived from an off-the-shelf machine learning package and one based on ACCA but enhanced by a simple neural network. These comprehensive CCA algorithms were shown to correctly classify pixels as cloudy or clear 88.5% and 89.7% of the time, respectively.

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

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

Spatial and temporal patterns of cloud cover and fog inundation in coastal California: Ecological implications

USGS Publications Warehouse

Rastogi, Bharat; Williams, A. Park; Fischer, Douglas T.; Iacobellis, Sam F.; McEachern, A. Kathryn; Carvalho, Leila; Jones, Charles Leslie; Baguskas, Sara A.; Still, Christopher J.

2016-01-01

The presence of low-lying stratocumulus clouds and fog has been known to modify biophysical and ecological properties in coastal California where forests are frequently shaded by low-lying clouds or immersed in fog during otherwise warm and dry summer months. Summer fog and stratus can ameliorate summer drought stress and enhance soil water budgets, and often have different spatial and temporal patterns. Here we use remote sensing datasets to characterize the spatial and temporal patterns of cloud cover over California’s northern Channel Islands. We found marine stratus to be persistent from May through September across the years 2001-2012. Stratus clouds were both most frequent and had the greatest spatial extent in July. Clouds typically formed in the evening, and dissipated by the following early afternoon. We present a novel method to downscale satellite imagery using atmospheric observations and discriminate patterns of fog from those of stratus and help explain patterns of fog deposition previously studied on the islands. The outcomes of this study contribute significantly to our ability to quantify the occurrence of coastal fog at biologically meaningful spatial and temporal scales that can improve our understanding of cloud-ecosystem interactions, species distributions and coastal ecohydrology.

Atmospheric movies acquired at the Mars Science Laboratory landing site: Cloud morphology, frequency and significance to the Gale Crater water cycle and Phoenix mission results

NASA Astrophysics Data System (ADS)

Moores, John E.; Lemmon, Mark T.; Rafkin, Scot C. R.; Francis, Raymond; Pla-Garcia, Jorge; de la Torre Juárez, Manuel; Bean, Keri; Kass, David; Haberle, Robert; Newman, Claire; Mischna, Michael; Vasavada, Ashwin; Rennó, Nilton; Bell, Jim; Calef, Fred; Cantor, Bruce; Mcconnochie, Timothy H.; Harri, Ari-Matti; Genzer, Maria; Wong, Michael; Smith, Michael D.; Javier Martín-Torres, F.; Zorzano, María-Paz; Kemppinen, Osku; McCullough, Emily

2015-05-01

We report on the first 360 sols (LS 150° to 5°), representing just over half a Martian year, of atmospheric monitoring movies acquired using the NavCam imager from the Mars Science Laboratory (MSL) Rover Curiosity. Such movies reveal faint clouds that are difficult to discern in single images. The data set acquired was divided into two different classifications depending upon the orientation and intent of the observation. Up to sol 360, 73 Zenith movies and 79 Supra-Horizon movies have been acquired and time-variable features could be discerned in 25 of each. The data set from MSL is compared to similar observations made by the Surface Stereo Imager (SSI) onboard the Phoenix Lander and suggests a much drier environment at Gale Crater (4.6°S) during this season than was observed in Green Valley (68.2°N) as would be expected based on latitude and the global water cycle. The optical depth of the variable component of clouds seen in images with features are up to 0.047 ± 0.009 with a granularity to the features observed which averages 3.8°. MCS also observes clouds during the same period of comparable optical depth at 30 and 50 km that would suggest a cloud spacing of 2.0 to 3.3 km. Multiple motions visible in atmospheric movies support the presence of two distinct layers of clouds. At Gale Crater, these clouds are likely caused by atmospheric waves given the regular spacing of features observed in many Zenith movies and decreased spacing towards the horizon in sunset movies consistent with clouds forming at a constant elevation. Reanalysis of Phoenix data in the light of the NavCam equatorial dataset suggests that clouds may have been more frequent in the earlier portion of the Phoenix mission than was previously thought.

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.

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.

Satellite remote sensing of particulate matter air quality: the cloud-cover problem.

PubMed

Christopher, Sundar A; Gupta, Pawan

2010-05-01

Satellite assessments of particulate matter (PM) air quality that use solar reflectance methods are dependent on availability of clear sky; in other words, mass concentrations of PM less than 2.5 microm in aerodynamic diameter (PM2.5) cannot be estimated from satellite observations under cloudy conditions or bright surfaces such as snow/ice. Whereas most ground monitors measure PM2.5 concentrations on an hourly basis regardless of cloud conditions, space-borne sensors can only estimate daytime PM2.5 in cloud-free conditions, therefore introducing a bias. In this study, an estimate of this clear-sky bias is provided from monthly to yearly time scales over the continental United States. One year of the Moderate Resolution Imaging Spectroradiometer (MODIS) 550-nm aerosol optical depth (AOD) retrievals from Terra and Aqua satellites, collocated with 371 U.S. Environmental Protection Agency (EPA) ground monitors, have been analyzed. The results indicate that the mean differences between PM2.5 reported by ground monitors and PM2.5 calculated from ground monitors during the satellite overpass times during cloud-free conditions are less than +/- 2.5 microg m(-3), although this value varies by season and location. The mean differences are not significant as calculated by t tests (alpha = 0.05). On the basis of this analysis, it is concluded that for the continental United States, cloud cover is not a major problem for inferring monthly to yearly PM2.5 from space-borne sensors.

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.

Coupled retrieval of water cloud and above-cloud aerosol properties using the Airborne Multiangle SpectroPolarimetric Imager (AirMSPI)

NASA Astrophysics Data System (ADS)

Xu, F.; van Harten, G.; Diner, D. J.; Rheingans, B. E.; Tosca, M.; Seidel, F. C.; Bull, M. A.; Tkatcheva, I. N.; McDuffie, J. L.; Garay, M. J.; Davis, A. B.; Jovanovic, V. M.; Brian, C.; Alexandrov, M. D.; Hostetler, C. A.; Ferrare, R. A.; Burton, S. P.

2017-12-01

The Airborne Multiangle SpectroPolarimetric Imager (AirMSPI) has been flying aboard the NASA ER-2 high altitude aircraft since October 2010. AirMSPI acquires radiance and polarization data in bands centered at 355, 380, 445, 470*, 555, 660*, 865*, and 935 nm (*denotes polarimetric bands). In sweep mode, georectified images cover an area of 80-100 km (along track) by 10-25 km (across track) between ±66° off nadir, with a map-projected spatial resolution of 25 meters. An efficient and flexible retrieval algorithm has been developed using AirMSPI polarimetric bands for simultaneous retrieval of cloud and above-cloud aerosol microphysical properties. We design a three-step retrieval approach, namely 1) estimating effective droplet size distribution using polarimetric cloudbow observations and using it as initial guess for Step 2; 2) combining water cloud and aerosol above cloud retrieval by fitting polarimetric signals at all scattering angles (e.g. from 80° to 180°); and 3) constructing a lookup table of radiance for a set of cloud optical depth grids using aerosol and cloud information retrieved from Step 2 and then estimating pixel-scale cloud optical depth based on 1D radiative transfer (RT) theory by fitting the AirMSPI radiance. Retrieval uncertainty is formulated by accounting for instrumental errors and constraints imposed on spectral variations of aerosol and cloud droplet optical properties. As the forward RT model, a hybrid approach is developed to combine the computational strengths of Markov-chain and adding-doubling methods to model polarized RT in a coupled aerosol, Rayleigh and cloud system. Our retrieval approach is tested using 134 AirMSPI datasets acquired during NASA ORACLES field campaign in 09/2016, with low to high aerosol loadings. For validation, the retrieved aerosol optical depths and cloud-top heights are compared to coincident High Spectral Resolution Lidar-2 (HSRL-2) data, and the droplet size parameters including effective radius and

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.

Point Cloud Management Through the Realization of the Intelligent Cloud Viewer Software

NASA Astrophysics Data System (ADS)

Costantino, D.; Angelini, M. G.; Settembrini, F.

2017-05-01

The paper presents a software dedicated to the elaboration of point clouds, called Intelligent Cloud Viewer (ICV), made in-house by AESEI software (Spin-Off of Politecnico di Bari), allowing to view point cloud of several tens of millions of points, also on of "no" very high performance systems. The elaborations are carried out on the whole point cloud and managed by means of the display only part of it in order to speed up rendering. It is designed for 64-bit Windows and is fully written in C ++ and integrates different specialized modules for computer graphics (Open Inventor by SGI, Silicon Graphics Inc), maths (BLAS, EIGEN), computational geometry (CGAL, Computational Geometry Algorithms Library), registration and advanced algorithms for point clouds (PCL, Point Cloud Library), advanced data structures (BOOST, Basic Object Oriented Supporting Tools), etc. ICV incorporates a number of features such as, for example, cropping, transformation and georeferencing, matching, registration, decimation, sections, distances calculation between clouds, etc. It has been tested on photographic and TLS (Terrestrial Laser Scanner) data, obtaining satisfactory results. The potentialities of the software have been tested by carrying out the photogrammetric survey of the Castel del Monte which was already available in previous laser scanner survey made from the ground by the same authors. For the aerophotogrammetric survey has been adopted a flight height of approximately 1000ft AGL (Above Ground Level) and, overall, have been acquired over 800 photos in just over 15 minutes, with a covering not less than 80%, the planned speed of about 90 knots.

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.

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.

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.

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.

Dissipation of Titans north polar cloud at northern spring equinox

USGS Publications Warehouse

Le, Mouelic S.; Rannou, P.; Rodriguez, S.; Sotin, Christophe; Griffith, C.A.; Le, Corre L.; Barnes, J.W.; Brown, R.H.; Baines, K.H.; Buratti, B.J.; Clark, R.N.; Nicholson, P.D.; Tobie, G.

2012-01-01

Saturns Moon Titan has a thick atmosphere with a meteorological cycle. We report on the evolution of the giant cloud system covering its north pole using observations acquired by the Visual and Infrared Mapping Spectrometer onboard the Cassini spacecraft. A radiative transfer model in spherical geometry shows that the clouds are found at an altitude between 30 and 65 km. We also show that the polar cloud system vanished progressively as Titan approached equinox in August 2009, revealing at optical wavelengths the underlying sea known as Kraken Mare. This decrease of activity suggests that the north-polar downwelling has begun to shut off. Such a scenario is compared with the Titan global circulation model of Rannou et al. (2006), which predicts a decrease of cloud coverage in northern latitudes at the same period of time. ?? 2011 Elsevier Ltd. All rights reserved.

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.

Multiple Satellite Observations of Cloud Cover in Extratropical Cyclones

NASA Technical Reports Server (NTRS)

Naud, Catherine M.; Booth, James F.; Posselt, Derek J.; van den Heever, Susan C.

2013-01-01

Using cloud observations from NASA Moderate Resolution Imaging Spectroradiometer, Multiangle Imaging Spectroradiometer, and CloudSat-CALIPSO, composites of cloud fraction in southern and northern hemisphere extratropical cyclones are obtained for cold and warm seasons between 2006 and 2010, to assess differences between these three data sets, and between summer and winter cyclones. In both hemispheres and seasons, over the open ocean, the cyclone-centered cloud fraction composites agree within 5% across the three data sets, but behind the cold fronts, or over sea ice and land, the differences are much larger. To supplement the data set comparison and learn more about the cyclones, we also examine the differences in cloud fraction between cold and warm season for each data set. The difference in cloud fraction between cold and warm season southern hemisphere cyclones is small for all three data sets, but of the same order of magnitude as the differences between the data sets. The cold-warm season contrast in northern hemisphere cyclone cloud fractions is similar for all three data sets: in the warm sector, the cold season cloud fractions are lower close to the low, but larger on the equator edge than their warm season counterparts. This seasonal contrast in cloud fraction within the cyclones warm sector seems to be related to the seasonal differences in moisture flux within the cyclones. Our analysis suggests that the three different data sets can all be used confidently when studying the warm sector and warm frontal zone of extratropical cyclones but caution should be exerted when studying clouds in the cold sector.

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.

Seasonal Change in Titan's Cloud Activity Observed with IRTF/SpeX

NASA Astrophysics Data System (ADS)

Schaller, Emily L.; Brown, M. E.; Roe, H. G.

2006-09-01

We have acquired whole disk spectra of Titan on nineteen nights with IRTF/SpeX over a three-month period in the spring of 2006. The data encompass the spectral range of 0.8 to 2.4 microns at a resolution of 375. These disk-integrated spectra allow us to determine Titan's total fractional cloud coverage and altitudes of clouds present. We find that Titan had less than 0.15% fractional cloud coverage on all but one of the nineteen nights. The near lack of cloud activity in these spectra is in sharp contrast to nearly every spectrum taken from 1995-1999 with UKIRT by Griffith et al. (1998 & 2000) who found rapidly varying clouds covering 0.5% of Titan's disk. The differences in these two similar datasets indicate a striking seasonal change in the behavior of Titan's clouds. Observations of the latitudes, magnitudes, altitudes, and frequencies of Titan's clouds as Titan moves toward southern autumnal equinox in 2009 will help elucidate when and how Titan's methane hydrological cycle changes with season.

Continuous Change Detection and Classification (CCDC) of Land Cover Using All Available Landsat Data

NASA Astrophysics Data System (ADS)

Zhu, Z.; Woodcock, C. E.

2012-12-01

A new algorithm for Continuous Change Detection and Classification (CCDC) of land cover using all available Landsat data is developed. This new algorithm is capable of detecting many kinds of land cover change as new images are collected and at the same time provide land cover maps for any given time. To better identify land cover change, a two step cloud, cloud shadow, and snow masking algorithm is used for eliminating "noisy" observations. Next, a time series model that has components of seasonality, trend, and break estimates the surface reflectance and temperature. The time series model is updated continuously with newly acquired observations. Due to the high variability in spectral response for different kinds of land cover change, the CCDC algorithm uses a data-driven threshold derived from all seven Landsat bands. When the difference between observed and predicted exceeds the thresholds three consecutive times, a pixel is identified as land cover change. Land cover classification is done after change detection. Coefficients from the time series models and the Root Mean Square Error (RMSE) from model fitting are used as classification inputs for the Random Forest Classifier (RFC). We applied this new algorithm for one Landsat scene (Path 12 Row 31) that includes all of Rhode Island as well as much of Eastern Massachusetts and parts of Connecticut. A total of 532 Landsat images acquired between 1982 and 2011 were processed. During this period, 619,924 pixels were detected to change once (91% of total changed pixels) and 60,199 pixels were detected to change twice (8% of total changed pixels). The most frequent land cover change category is from mixed forest to low density residential which occupies more than 8% of total land cover change pixels.

Gravity Waves Ripple over Marine Stratocumulus Clouds

NASA Technical Reports Server (NTRS)

2004-01-01

In this natural-color image from the Multi-angle Imaging SpectroRadiometer (MISR), a fingerprint-like gravity wave feature occurs over a deck of marine stratocumulus clouds. Similar to the ripples that occur when a pebble is thrown into a still pond, such 'gravity waves' sometimes appear when the relatively stable and stratified air masses associated with stratocumulus cloud layers are disturbed by a vertical trigger from the underlying terrain, or by a thunderstorm updraft or some other vertical wind shear. The stratocumulus cellular clouds that underlie the wave feature are associated with sinking air that is strongly cooled at the level of the cloud-tops -- such clouds are common over mid-latitude oceans when the air is unperturbed by cyclonic or frontal activity. This image is centered over the Indian Ocean (at about 38.9o South, 80.6o East), and was acquired on October 29, 2003.

The Multi-angle Imaging SpectroRadiometer observes the daylit Earth continuously and every 9 days views the entire globe between 82o north and 82o south latitude. These data products were generated from a portion of the imagery acquired during Terra orbit 20545. The image covers an area of 245 kilometers x 378 kilometers, and uses data from blocks 121 to 122 within World Reference System-2 path 134.

MISR was built and is managed by NASA's Jet Propulsion Laboratory, Pasadena, CA, for NASA's Office of Earth Science, Washington, DC. The Terra satellite is managed by NASA's Goddard Space Flight Center, Greenbelt, MD. JPL is a division of the California Institute of Technology.

Robust Segmentation of Planar and Linear Features of Terrestrial Laser Scanner Point Clouds Acquired from Construction Sites.

PubMed

Maalek, Reza; Lichti, Derek D; Ruwanpura, Janaka Y

2018-03-08

Automated segmentation of planar and linear features of point clouds acquired from construction sites is essential for the automatic extraction of building construction elements such as columns, beams and slabs. However, many planar and linear segmentation methods use scene-dependent similarity thresholds that may not provide generalizable solutions for all environments. In addition, outliers exist in construction site point clouds due to data artefacts caused by moving objects, occlusions and dust. To address these concerns, a novel method for robust classification and segmentation of planar and linear features is proposed. First, coplanar and collinear points are classified through a robust principal components analysis procedure. The classified points are then grouped using a new robust clustering method, the robust complete linkage method. A robust method is also proposed to extract the points of flat-slab floors and/or ceilings independent of the aforementioned stages to improve computational efficiency. The applicability of the proposed method is evaluated in eight datasets acquired from a complex laboratory environment and two construction sites at the University of Calgary. The precision, recall, and accuracy of the segmentation at both construction sites were 96.8%, 97.7% and 95%, respectively. These results demonstrate the suitability of the proposed method for robust segmentation of planar and linear features of contaminated datasets, such as those collected from construction sites.

Robust Segmentation of Planar and Linear Features of Terrestrial Laser Scanner Point Clouds Acquired from Construction Sites

PubMed Central

Maalek, Reza; Lichti, Derek D; Ruwanpura, Janaka Y

2018-01-01

Automated segmentation of planar and linear features of point clouds acquired from construction sites is essential for the automatic extraction of building construction elements such as columns, beams and slabs. However, many planar and linear segmentation methods use scene-dependent similarity thresholds that may not provide generalizable solutions for all environments. In addition, outliers exist in construction site point clouds due to data artefacts caused by moving objects, occlusions and dust. To address these concerns, a novel method for robust classification and segmentation of planar and linear features is proposed. First, coplanar and collinear points are classified through a robust principal components analysis procedure. The classified points are then grouped using a new robust clustering method, the robust complete linkage method. A robust method is also proposed to extract the points of flat-slab floors and/or ceilings independent of the aforementioned stages to improve computational efficiency. The applicability of the proposed method is evaluated in eight datasets acquired from a complex laboratory environment and two construction sites at the University of Calgary. The precision, recall, and accuracy of the segmentation at both construction sites were 96.8%, 97.7% and 95%, respectively. These results demonstrate the suitability of the proposed method for robust segmentation of planar and linear features of contaminated datasets, such as those collected from construction sites. PMID:29518062

Comparison View of Mars Cloud Cover

NASA Technical Reports Server (NTRS)

1997-01-01

These color and black and white pictures of Mars were taken by NASA's Hubble Space Telescope just two weeks after Earth made its closest approach to the Red Planet during the 1997 opposition. When the Hubble pictures were taken Mars was at a distance of 62 million miles (100 million kilometers) and the resolution at the center of the disk is 13.5 miles/pixel (22 kilometers/pixel). Both images were made with the Wide Field and Planetary Camera 2. The color composite (left image) is constructed from three images taken in red (673 nanometers), green (502 nm) and blue (410 nm) light. The right image, in blue light only, brings out details in the cloud structure and is remarkably similar to weather satellite pictures taken of Earth. A planetary-scale wave curls around the north pole, similar in behavior to high latitude cold fronts which descend over North America and Europe during springtime.

The picture was taken when Mars was near aphelion, its farthest point from the Sun. The faint sunlight results in cold atmospheric conditions which stimulate the formation of water ice clouds. The clouds themselves further reduce atmospheric temperatures. Atmospheric heating, resulting when sunlight is absorbed by the dust, is reduced when ice forms around the dust particles and causes the dust to gravitationally settle to the ground.

These images of Mars are centered at approximately 94 degrees longitude and 23 degrees N latitude (oriented with north up). The four largest Tharsis Montes (massive extinct volcanoes) are visible as dark spots extending through the clouds. The vast canyon system, Valles Marineris, stretches across the eastern (lower right) half of the image; the Pathfinder landing site is near the eastern edge of the image. It is early summer in the northern hemisphere, and the North polar cap has retreated to about 80 degrees N latitude; the 'residual' summer cap, which is composed of water ice, is about one-third the size of the 'seasonal' winter cap, which

Filament formation in wind-cloud interactions- II. Clouds with turbulent density, velocity, and magnetic fields

NASA Astrophysics Data System (ADS)

Banda-Barragán, W. E.; Federrath, C.; Crocker, R. M.; Bicknell, G. V.

2018-01-01

We present a set of numerical experiments designed to systematically investigate how turbulence and magnetic fields influence the morphology, energetics, and dynamics of filaments produced in wind-cloud interactions. We cover 3D, magnetohydrodynamic systems of supersonic winds impacting clouds with turbulent density, velocity, and magnetic fields. We find that lognormal density distributions aid shock propagation through clouds, increasing their velocity dispersion and producing filaments with expanded cross-sections and highly magnetized knots and subfilaments. In self-consistently turbulent scenarios, the ratio of filament to initial cloud magnetic energy densities is ∼1. The effect of Gaussian velocity fields is bound to the turbulence Mach number: Supersonic velocities trigger a rapid cloud expansion; subsonic velocities only have a minor impact. The role of turbulent magnetic fields depends on their tension and is similar to the effect of radiative losses: the stronger the magnetic field or the softer the gas equation of state, the greater the magnetic shielding at wind-filament interfaces and the suppression of Kelvin-Helmholtz instabilities. Overall, we show that including turbulence and magnetic fields is crucial to understanding cold gas entrainment in multiphase winds. While cloud porosity and supersonic turbulence enhance the acceleration of clouds, magnetic shielding protects them from ablation and causes Rayleigh-Taylor-driven subfilamentation. Wind-swept clouds in turbulent models reach distances ∼15-20 times their core radius and acquire bulk speeds ∼0.3-0.4 of the wind speed in one cloud-crushing time, which are three times larger than in non-turbulent models. In all simulations, the ratio of turbulent magnetic to kinetic energy densities asymptotes at ∼0.1-0.4, and convergence of all relevant dynamical properties requires at least 64 cells per cloud radius.

COMPARISON VIEW OF MARS CLOUD COVER

NASA Technical Reports Server (NTRS)

2002-01-01

These color and black and white pictures of Mars were taken by NASA's Hubble Space Telescope just two weeks after Earth made its closest approach to the Red Planet during the 1997 opposition. When the Hubble pictures were taken Mars was at a distance of 62 million miles (100 million kilometers) and the resolution at the center of the disk is 13.5 miles/pixel (22 kilometers/pixel). Both images were made with the Wide Field and Planetary Camera 2. The color composite (left image) is constructed from three images taken in red (673 nanometers), green (502 nm) and blue (410 nm) light. The right image, in blue light only, brings out details in the cloud structure and is remarkably similar to weather satellite pictures taken of Earth. A planetary-scale wave curls around the north pole, similar in behavior to high latitude cold fronts which descend over North America and Europe during springtime. The picture was taken when Mars was near aphelion, its farthest point from the Sun. The faint sunlight results in cold atmospheric conditions which stimulate the formation of water ice clouds. The clouds themselves further reduce atmospheric temperatures. Atmospheric heating, resulting when sunlight is absorbed by the dust, is reduced when ice forms around the dust particles and causes the dust to gravitationally settle to the ground. These images of Mars are centered at approximately 94 degrees longitude and 23 degrees N latitude (oriented with north up). The four largest Tharsis Montes (massive extinct volcanoes) are visible as dark spots extending through the clouds. The vast canyon system, Valles Marineris, stretches across the eastern (lower right) half of the image; the Pathfinder landing site is near the eastern edge of the image. It is early summer in the northern hemisphere, and the North polar cap has retreated to about 80 degrees N latitude; the 'residual' summer cap, which is composed of water ice, is about one-third the size of the 'seasonal' winter cap, which

The Clouds of Isidore

NASA Technical Reports Server (NTRS)

2002-01-01

of viewing angle as well as the height field. Note that over the short distances (2.2 kilometers) that the local albedo product is generated, values can be greater than 1.0 due to contributions from cloud sides. Areas where albedo could not be retrieved are shown in dark gray.

The Multi-angle Imaging SpectroRadiometer observes the daylit Earth continuously from pole to pole, and every 9 days views the entire globe between 82 degrees north and 82 degrees south latitude. These data products were generated from a portion of the imagery acquired during Terra orbit 14669. The panels cover an area of about 380 kilometers x 704 kilometers, and utilize data from blocks 70 to 79within World Reference System-2 path 17.

MISR was built and is managed by NASA's Jet Propulsion Laboratory, Pasadena, CA, for NASA's Office of Earth Science, Washington, DC. The Terra satellite is managed by NASA's Goddard Space Flight Center, Greenbelt, MD. JPL is a division of the California Institute of Technology.

A Satellite Survey of Cloud Cover and Water Vapor in the Southwestern USA and Northern Mexico

NASA Astrophysics Data System (ADS)

Carrasco, E.; Avila, R.; Erasmus, A.; Djorgovski, S. G.; Walker, A. R.; Blum, R.

2017-03-01

Cloud cover and water vapor conditions in the southwestern USA and northern Mexico were surveyed as a preparatory work for the Thirty Meter Telescope (TMT) in situ site testing program. Although the telescope site is already selected, the TMT site testing team decided to make public these results for its usefulness for the community. Using 58 months of meteorological satellite observations between 1993 July and 1999 September, different atmospheric parameters were quantified from data of the 10.7 μm and of 6.7 μm windows. In particular, cloud cover and water vapor conditions were identified in preferred areas. As a result of the aerial analysis, 15 sites of existing and potential telescope were selected, compared, and ranked in terms of their observing quality. The clearest sites are located along the spine of the Baja peninsula and into southern California on mountain peaks above the temperature inversion layer. A steep gradient of cloudiness was observed along the coast where coastal cloud and fog are trapped below the inversion layer. Moving from west to east over the continent, a significant increase in cloudiness was observed. The analysis shows that San Pedro Mártir, San Gorgonio Mountain and San Jacinto Peak have the largest fraction of clear sky conditions (˜74%). The site with the optimal combination of clear skies and low precipitable water vapor is Boundary Peak, Nevada. An approach based in satellite data provided a reliable method for sites comparison.

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.

Improving rainfall estimation from commercial microwave links using METEOSAT SEVIRI cloud cover information

NASA Astrophysics Data System (ADS)

Boose, Yvonne; Doumounia, Ali; Chwala, Christian; Moumouni, Sawadogo; Zougmoré, François; Kunstmann, Harald

2017-04-01

The number of rain gauges is declining worldwide. A recent promising method for alternative precipitation measurements is to derive rain rates from the attenuation of the microwave signal between remote antennas of mobile phone base stations, so called commercial microwave links (CMLs). In European countries, such as Germany, the CML technique can be used as a complementary method to the existing gauge and radar networks improving their products, for example, in mountainous terrain and urban areas. In West African countries, where a dense gauge or radar network is absent, the number of mobile phone users is rapidly increasing and so are the CML networks. Hence, the CML-derived precipitation measurements have high potential for applications such as flood warning and support of agricultural planning in this region. For typical CML bandwidths (10-40 GHz), the relationship of attenuation to rain rate is quasi-linear. However, also humidity, wet antennas or electronic noise can lead to signal interference. To distinguish these fluctuations from actual attenuation due to rain, a temporal wet (rain event occurred)/ dry (no rain event) classification is usually necessary. In dense CML networks this is possible by correlating neighboring CML time series. Another option is to use the correlation between signal time series of different frequencies or bidirectional signals. The CML network in rural areas is typically not dense enough for correlation analysis and often only one polarization and one frequency are available along a CML. In this work we therefore use cloud cover information derived from the Spinning Enhanced Visible and Infrared Imager (SEVIRI) radiometer onboard the geostationary satellite METEOSAT for a wet (pixels along link are cloud covered)/ dry (no cloud along link) classification. We compare results for CMLs in Burkina Faso and Germany, which differ meteorologically (rain rate and duration, droplet size distributions) and technically (CML frequencies

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.

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

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.

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

SatCam: A mobile application for coordinated ground/satellite observation of clouds and validation of satellite-derived cloud mask products.

NASA Astrophysics Data System (ADS)

Gumley, L.; Parker, D.; Flynn, B.; Holz, R.; Marais, W.

2011-12-01

SatCam is an application for iOS devices that allows users to collect observations of local cloud and surface conditions in coordination with an overpass of the Terra, Aqua, or NPP satellites. SatCam allows users to acquire images of sky conditions and ground conditions at their location anywhere in the world using the built-in iPhone or iPod Touch camera at the same time that the satellite is passing overhead and viewing their location. Immediately after the sky and ground observations are acquired, the application asks the user to rate the level of cloudiness in the sky (Completely Clear, Mostly Clear, Partly Cloudy, Overcast). For the ground observation, the user selects their assessment of the surface conditions (Urban, Green Vegetation, Brown Vegetation, Desert, Snow, Water). The sky condition and surface condition selections are stored along with the date, time, and geographic location for the images, and the images are uploaded to a central server. When the MODIS (Terra and Aqua) or VIIRS (NPP) imagery acquired over the user location becomes available, a MODIS or VIIRS true color image centered at the user's location is delivered back to the SatCam application on the user's iOS device. SSEC also proposes to develop a community driven SatCam website where users can share their observations and assessments of satellite cloud products in a collaborative environment. SSEC is developing a server side data analysis system to ingest the SatCam user observations, apply quality control, analyze the sky images for cloud cover, and collocate the observations with MODIS and VIIRS satellite products (e.g., cloud mask). For each observation that is collocated with a satellite observation, the server will determine whether the user scored a "hit", meaning their sky observation and sky assessment matched the automated cloud mask obtained from the satellite observation. The hit rate will be an objective assessment of the accuracy of the user's sky observations. Users with

Amoco unit acquires two blocks covering 2. 7 million acres in Poland

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

Not Available

1992-10-12

This paper reports that an Amoco Production Co. unit has signed the first agreement by a western company for conventional petroleum exploration rights in Poland. The agreement between Amoco Poland Ltd. and Poland's Ministry of Environmental Protection, Natural Resources, and Forestry calls for Amoco to make an initial $20 million investment to conduct seismic surveys and drill wildcats on two blocks. Block A is a 1,695,750 acre spread southwest of Warsaw in the heart of the Polish trough. Block B covers about 979,000 acres southeast of Lublin on the Polish-Ukrainian border. The state has an option to acquire as muchmore » as 30% interest in future hydrocarbon development.« less

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

Cloud Arcs in the Western Pacific

NASA Technical Reports Server (NTRS)

2002-01-01

Small cumulus clouds in this natural-color view from the Multi-angle Imaging SpectroRadiometer have formed a distinctive series of quasi-circular arcs. Clues regarding the formation of these arcs can be found by noting that larger clouds exist in the interior of each arc.

The interior clouds are thicker and likely to be more convectively active than the other clouds, causing much of the air near the centers of the arcs to rise. This air spreads out horizontally in all directions as it rises and continues to spread out as it begins to sink back to the surface. This pushes any existing small cumulus clouds away from the central region of convection.

As the air sinks, it also warms, preventing other small clouds from forming, so that the regions just inside the arcs are kept clear. At the arcs, the horizontal flow of sinking air is now quite weak and on meeting the undisturbed air it can rise again slightly -- possibly assisting in the formation of new small cumulus clouds. Although examples of the continuity of air, in which every rising air motion must be compensated by a sinking motion elsewhere, are very common, the degree of organization exhibited here is relatively rare, as the wind field at different altitudes usually disrupts such patterns. The degree of self organization of this cloud image, whereby three or four such circular events form a quasi-periodic pattern, probably also requires a relatively uncommon combination of wind, temperature and humidity conditions for it to occur.

The image was acquired by MISR's nadir camera on March 11, 2002, and is centered west of the Marshall Islands. Enewetak Atoll is discernible through thin cloud as the turquoise band near the right-hand edge of the image.

The Multi-angle Imaging SpectroRadiometer observes the daylit Earth continuously from pole to pole, and views almost the entire globe every 9 days. This image is a portion of the data acquired during Terra orbit 11863, and covers an area of about 380

Land cover mapping of North and Central America—Global Land Cover 2000

USGS Publications Warehouse

Latifovic, Rasim; Zhu, Zhi-Liang

2004-01-01

The Land Cover Map of North and Central America for the year 2000 (GLC 2000-NCA), prepared by NRCan/CCRS and USGS/EROS Data Centre (EDC) as a regional component of the Global Land Cover 2000 project, is the subject of this paper. A new mapping approach for transforming satellite observations acquired by the SPOT4/VGTETATION (VGT) sensor into land cover information is outlined. The procedure includes: (1) conversion of daily data into 10-day composite; (2) post-seasonal correction and refinement of apparent surface reflectance in 10-day composite images; and (3) extraction of land cover information from the composite images. The pre-processing and mosaicking techniques developed and used in this study proved to be very effective in removing cloud contamination, BRDF effects, and noise in Short Wave Infra-Red (SWIR). The GLC 2000-NCA land cover map is provided as a regional product with 28 land cover classes based on modified Federal Geographic Data Committee/Vegetation Classification Standard (FGDC NVCS) classification system, and as part of a global product with 22 land cover classes based on Land Cover Classification System (LCCS) of the Food and Agriculture Organisation. The map was compared on both areal and per-pixel bases over North and Central America to the International Geosphere–Biosphere Programme (IGBP) global land cover classification, the University of Maryland global land cover classification (UMd) and the Moderate Resolution Imaging Spectroradiometer (MODIS) Global land cover classification produced by Boston University (BU). There was good agreement (79%) on the spatial distribution and areal extent of forest between GLC 2000-NCA and the other maps, however, GLC 2000-NCA provides additional information on the spatial distribution of forest types. The GLC 2000-NCA map was produced at the continental level incorporating specific needs of the region.

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.

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.

Simultaneous colour visualizations of multiple ALS point cloud attributes for land cover and vegetation analysis

NASA Astrophysics Data System (ADS)

Zlinszky, András; Schroiff, Anke; Otepka, Johannes; Mandlburger, Gottfried; Pfeifer, Norbert

2014-05-01

LIDAR point clouds hold valuable information for land cover and vegetation analysis, not only in the spatial distribution of the points but also in their various attributes. However, LIDAR point clouds are rarely used for visual interpretation, since for most users, the point cloud is difficult to interpret compared to passive optical imagery. Meanwhile, point cloud viewing software is available allowing interactive 3D interpretation, but typically only one attribute at a time. This results in a large number of points with the same colour, crowding the scene and often obscuring detail. We developed a scheme for mapping information from multiple LIDAR point attributes to the Red, Green, and Blue channels of a widely used LIDAR data format, which are otherwise mostly used to add information from imagery to create "photorealistic" point clouds. The possible combinations of parameters are therefore represented in a wide range of colours, but relative differences in individual parameter values of points can be well understood. The visualization was implemented in OPALS software, using a simple and robust batch script, and is viewer independent since the information is stored in the point cloud data file itself. In our case, the following colour channel assignment delivered best results: Echo amplitude in the Red, echo width in the Green and normalized height above a Digital Terrain Model in the Blue channel. With correct parameter scaling (but completely without point classification), points belonging to asphalt and bare soil are dark red, low grassland and crop vegetation are bright red to yellow, shrubs and low trees are green and high trees are blue. Depending on roof material and DTM quality, buildings are shown from red through purple to dark blue. Erroneously high or low points, or points with incorrect amplitude or echo width usually have colours contrasting from terrain or vegetation. This allows efficient visual interpretation of the point cloud in planar

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

Covered Stent Grafts for Acquired Arterial Venous Fistulas: A Case Series.

PubMed

Sarac, Timur P; Vargas, Lina; Kashyap, Vikram; Cardella, Jonathan; Chaar, Cassius Ochoa

2018-01-01

Stent grafts have become the preferred method for treating abdominal aortic aneurysms (AAAs) but also have utility in treating other vasculopathies. In 2005, peripheral stent grafts were approved for treating superficial femoral artery occlusive disease. This report describes our experience using covered stent grafts to treat acquired arterial venous fistulae (aAVF). We reviewed the records of patients treated for aAVF with covered stent grafts. Eleven patients had 12 limbs treated with a stent graft. The data collected included presenting symptoms, mechanism of injury, vessel location, stent graft used for therapy, and patency. Eleven patients underwent successful treatment of 12 aAVF with a peripheral stent grafts. The average age was 55.6 (18-87), and there were 4 women and 7 men. The mechanisms of injuries were heart catheterization in 5 patients, penetrating trauma in 3 patients, and orthopedic injury in 3 patients. Five of the patients had concurrent pseudoaneurysms. Self-expanding expanded polytetrafluoroethelene (ePTFE) stent grafts were used in 8 patients, and balloon-expandable ePTFE stent grafts were used in 3 patients. Primary patency at 2 years is 100%, with all patients having significant relief of symptoms. Peripheral stent grafts are a useful tool for treating aAVF, with excellent patency. They provide a valuable minimally invasive approach to this disease. Copyright © 2017 Elsevier Inc. All rights reserved.

Clouds over the summertime Sahara: an evaluation of Met Office retrievals from Meteosat Second Generation using airborne remote sensing

NASA Astrophysics Data System (ADS)

Kealy, John C.; Marenco, Franco; Marsham, John H.; Garcia-Carreras, Luis; Francis, Pete N.; Cooke, Michael C.; Hocking, James

2017-05-01

Novel methods of cloud detection are applied to airborne remote sensing observations from the unique Fennec aircraft dataset, to evaluate the Met Office-derived products on cloud properties over the Sahara based on the Spinning Enhanced Visible and InfraRed Imager (SEVIRI) on-board the Meteosat Second Generation (MSG) satellite. Two cloud mask configurations are considered, as well as the retrievals of cloud-top height (CTH), and these products are compared to airborne cloud remote sensing products acquired during the Fennec campaign in June 2011 and June 2012. Most detected clouds (67 % of the total) have a horizontal extent that is smaller than a SEVIRI pixel (3 km × 3 km). We show that, when partially cloud-contaminated pixels are included, a match between the SEVIRI and aircraft datasets is found in 80 ± 8 % of the pixels. Moreover, under clear skies the datasets are shown to agree for more than 90 % of the pixels. The mean cloud field, derived from the satellite cloud mask acquired during the Fennec flights, shows that areas of high surface albedo and orography are preferred sites for Saharan cloud cover, consistent with published theories. Cloud-top height retrievals however show large discrepancies over the region, which are ascribed to limiting factors such as the cloud horizontal extent, the derived effective cloud amount, and the absorption by mineral dust. The results of the CTH analysis presented here may also have further-reaching implications for the techniques employed by other satellite applications facilities across the world.

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.

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.

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.

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

High-resolution stochastic downscaling of climate models: simulating wind advection, cloud cover and precipitation

NASA Astrophysics Data System (ADS)

Peleg, Nadav; Fatichi, Simone; Burlando, Paolo

2015-04-01

A new stochastic approach to generate wind advection, cloud cover and precipitation fields is presented with the aim of formulating a space-time weather generator characterized by fields with high spatial and temporal resolution (e.g., 1 km x 1 km and 5 min). Its use is suitable for stochastic downscaling of climate scenarios in the context of hydrological, ecological and geomorphological applications. The approach is based on concepts from the Advanced WEather GENerator (AWE-GEN) presented by Fatichi et al. (2011, Adv. Water Resour.), the Space-Time Realizations of Areal Precipitation model (STREAP) introduced by Paschalis et al. (2013, Water Resour. Res.), and the High-Resolution Synoptically conditioned Weather Generator (HiReS-WG) presented by Peleg and Morin (2014, Water Resour. Res.). Advection fields are generated on the basis of the 500 hPa u and v wind direction variables derived from global or regional climate models. The advection velocity and direction are parameterized using Kappa and von Mises distributions respectively. A random Gaussian fields is generated using a fast Fourier transform to preserve the spatial correlation of advection. The cloud cover area, total precipitation area and mean advection of the field are coupled using a multi-autoregressive model. The approach is relatively parsimonious in terms of computational demand and, in the context of climate change, allows generating many stochastic realizations of current and projected climate in a fast and efficient way. A preliminary test of the approach is presented with reference to a case study in a complex orography terrain in the Swiss Alps.

Indirect and Semi-Direct Aerosol Campaign: The Impact of Arctic Aerosols on Clouds

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

McFarquhar, Greg; Ghan, Steven J.; Verlinde, J.

2011-02-01

A comprehensive dataset of microphysical and radiative properties of aerosols and clouds in the arctic boundary layer in the vicinity of Barrow, Alaska was collected in April 2008 during the Indirect and Semi-Direct Aerosol Campaign (ISDAC) sponsored by the Department of Energy Atmospheric Radiation Measurement (ARM) and Atmospheric Science Programs. The primary aim of ISDAC was to examine indirect effects of aerosols on clouds that contain both liquid and ice water. The experiment utilized the ARM permanent observational facilities at the North Slope of Alaska (NSA) in Barrow. These include a cloud radar, a polarized micropulse lidar, and an atmosphericmore » emitted radiance interferometer as well as instruments specially deployed for ISDAC measuring aerosol, ice fog, precipitation and spectral shortwave radiation. The National Research Council of Canada Convair-580 flew 27 sorties during ISDAC, collecting data using an unprecedented 42 cloud and aerosol instruments for more than 100 hours on 12 different days. Data were obtained above, below and within single-layer stratus on 8 April and 26 April 2008. These data enable a process-oriented understanding of how aerosols affect the microphysical and radiative properties of arctic clouds influenced by different surface conditions. Observations acquired on a heavily polluted day, 19 April 2008, are enhancing this understanding. Data acquired in cirrus on transit flights between Fairbanks and Barrow are improving our understanding of the performance of cloud probes in ice. Ultimately the ISDAC data will be used to improve the representation of cloud and aerosol processes in models covering a variety of spatial and temporal scales, and to determine the extent to which long-term surface-based measurements can provide retrievals of aerosols, clouds, precipitation and radiative heating in the Arctic.« less

Evolving land cover classification algorithms for multispectral and multitemporal imagery

NASA Astrophysics Data System (ADS)

Brumby, Steven P.; Theiler, James P.; Bloch, Jeffrey J.; Harvey, Neal R.; Perkins, Simon J.; Szymanski, John J.; Young, Aaron C.

2002-01-01

The Cerro Grande/Los Alamos forest fire devastated over 43,000 acres (17,500 ha) of forested land, and destroyed over 200 structures in the town of Los Alamos and the adjoining Los Alamos National Laboratory. The need to measure the continuing impact of the fire on the local environment has led to the application of a number of remote sensing technologies. During and after the fire, remote-sensing data was acquired from a variety of aircraft- and satellite-based sensors, including Landsat 7 Enhanced Thematic Mapper (ETM+). We now report on the application of a machine learning technique to the automated classification of land cover using multi-spectral and multi-temporal imagery. We apply a hybrid genetic programming/supervised classification technique to evolve automatic feature extraction algorithms. We use a software package we have developed at Los Alamos National Laboratory, called GENIE, to carry out this evolution. We use multispectral imagery from the Landsat 7 ETM+ instrument from before, during, and after the wildfire. Using an existing land cover classification based on a 1992 Landsat 5 TM scene for our training data, we evolve algorithms that distinguish a range of land cover categories, and an algorithm to mask out clouds and cloud shadows. We report preliminary results of combining individual classification results using a K-means clustering approach. The details of our evolved classification are compared to the manually produced land-cover classification.

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.

The Impact of Changing Cloud Cover on the High Arctic's Primary Cooling-to-space Windows

NASA Astrophysics Data System (ADS)

Mariani, Zen; Rowe, Penny; Strong, Kimberly; Walden, Von; Drummond, James

2014-05-01

In the Arctic, most of the infrared energy emitted by the surface escapes to space in two atmospheric windows at 10 and 20 μm. As the Arctic warms, the 20 μm cooling-to-space window becomes increasingly opaque (or "closed"), trapping more surface infrared radiation in the atmosphere, with implications for the Arctic's radiative energy balance. Since 2006, the Canadian Network for the Detection of Atmospheric Change (CANDAC) has measured downwelling infrared radiance with an Atmospheric Emitted Radiance Interferometer (AERI) at the Polar Environment Atmospheric Research Laboratory (PEARL) at Eureka, Canada, providing the first long-term measurements of the 10 and 20 μm windows in the high Arctic. In this work, measurements of the distribution of downwelling 10 and 20 µm brightness temperatures at Eureka are separated based on cloud cover, providing a comparison to an existing climatology from the Southern Great Plains (SGP). Measurements of the downwelling radiance at both 10 and 20 μm exhibit strong seasonal variability as a result of changes in temperature and water vapour, in addition to variability with cloud cover. When separated by season, brightness temperatures in the 20 µm window are found to be independent of cloud thickness in the summertime, indicating that this window is closed in the summer. Radiance trends in three-month averages are positive and are significantly larger (factor > 5) than the trends detected at the SGP, indicating that changes in the downwelling radiance are accelerated in the high Arctic compared to lower latitudes. This statistically significant increase (> 5% / yr) in radiance at 10 μm occurs only when the 20 μm window is mostly transparent, or "open" (i.e., in all seasons except summer), and may have long-term consequences, particularly as warmer temperatures and increased water vapour "close" the dirty window for a prolonged period. These surface-based measurements of radiative forcing can be used to quantify changes in

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

Distinguishing Clouds from Ice over the East Siberian Sea, Russia

NASA Technical Reports Server (NTRS)

2002-01-01

As a consequence of its capability to retrieve cloud-top elevations, stereoscopic observations from the Multi-angle Imaging SpectroRadiometer (MISR) can discriminate clouds from snow and ice. The central portion of Russia's East Siberian Sea, including one of the New Siberian Islands, Novaya Sibir, are portrayed in these views from data acquired on May 28, 2002.

The left-hand image is a natural color view from MISR's nadir camera. On the right is a height field retrieved using automated computer processing of data from multiple MISR cameras. Although both clouds and ice appear white in the natural color view, the stereoscopic retrievals are able to identify elevated clouds based on the geometric parallax which results when they are observed from different angles. Owing to their elevation above sea level, clouds are mapped as green and yellow areas, whereas land, sea ice, and very low clouds appear blue and purple. Purple, in particular, denotes elevations very close to sea level. The island of Novaya Sibir is located in the lower left of the images. It can be identified in the natural color view as the dark area surrounded by an expanse of fast ice. In the stereo map the island appears as a blue region indicating its elevation of less than 100 meters above sea level. Areas where the automated stereo processing failed due to lack of sufficient spatial contrast are shown in dark gray. The northern edge of the Siberian mainland can be found at the very bottom of the panels, and is located a little over 250 kilometers south of Novaya Sibir. Pack ice containing numerous fragmented ice floes surrounds the fast ice, and narrow areas of open ocean are visible.

The East Siberian Sea is part of the Arctic Ocean and is ice-covered most of the year. The New Siberian Islands are almost always covered by snow and ice, and tundra vegetation is very scant. Despite continuous sunlight from the end of April until the middle of August, the ice between the island and the

An Automated Algorithm for Producing Land Cover Information from Landsat Surface Reflectance Data Acquired Between 1984 and Present

NASA Astrophysics Data System (ADS)

Rover, J.; Goldhaber, M. B.; Holen, C.; Dittmeier, R.; Wika, S.; Steinwand, D.; Dahal, D.; Tolk, B.; Quenzer, R.; Nelson, K.; Wylie, B. K.; Coan, M.

2015-12-01

Multi-year land cover mapping from remotely sensed data poses challenges. Producing land cover products at spatial and temporal scales required for assessing longer-term trends in land cover change are typically a resource-limited process. A recently developed approach utilizes open source software libraries to automatically generate datasets, decision tree classifications, and data products while requiring minimal user interaction. Users are only required to supply coordinates for an area of interest, land cover from an existing source such as National Land Cover Database and percent slope from a digital terrain model for the same area of interest, two target acquisition year-day windows, and the years of interest between 1984 and present. The algorithm queries the Landsat archive for Landsat data intersecting the area and dates of interest. Cloud-free pixels meeting the user's criteria are mosaicked to create composite images for training the classifiers and applying the classifiers. Stratification of training data is determined by the user and redefined during an iterative process of reviewing classifiers and resulting predictions. The algorithm outputs include yearly land cover raster format data, graphics, and supporting databases for further analysis. Additional analytical tools are also incorporated into the automated land cover system and enable statistical analysis after data are generated. Applications tested include the impact of land cover change and water permanence. For example, land cover conversions in areas where shrubland and grassland were replaced by shale oil pads during hydrofracking of the Bakken Formation were quantified. Analytical analysis of spatial and temporal changes in surface water included identifying wetlands in the Prairie Pothole Region of North Dakota with potential connectivity to ground water, indicating subsurface permeability and geochemistry.

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.

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

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.

Deep Clouds

NASA Image and Video Library

2008-05-27

Bright puffs and ribbons of cloud drift lazily through Saturn's murky skies. In contrast to the bold red, orange and white clouds of Jupiter, Saturn's clouds are overlain by a thick layer of haze. The visible cloud tops on Saturn are deeper in its atmosphere due to the planet's cooler temperatures. This view looks toward the unilluminated side of the rings from about 18 degrees above the ringplane. Images taken using red, green and blue spectral filters were combined to create this natural color view. The images were acquired with the Cassini spacecraft wide-angle camera on April 15, 2008 at a distance of approximately 1.5 million kilometers (906,000 miles) from Saturn. Image scale is 84 kilometers (52 miles) per pixel. http://photojournal.jpl.nasa.gov/catalog/PIA09910

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.

Development of a climatological data base to help forecast cloud cover conditions for shuttle landings at the Kennedy Space Center

NASA Technical Reports Server (NTRS)

Atchison, M. Kevin

1993-01-01

The Space Shuttle is an extremely weather sensitive vehicle with very restrictive constraints for both launches and landings. The most important difference between Shuttle and normal aircraft landings is that the Shuttle has no go-around capability once it begins its decent into the earth's atmosphere. The de-orbit burn decision is generally made approximately 90 minutes before landing requiring a forecast with little room for error. Because of the Shuttle's rapid re-entry to earth, the pilot must be able to see all runway and visual navigation aids from high altitude to land the Shuttle. In addition, the heat resistant tiles which are used to protect the Shuttle during its re-entry into the earth's atmosphere are extremely sensitive to any type of precipitation. Extensive damage to these tiles could occur if the Shuttle passes through any cloud that contains precipitation size particles. To help guard against changing weather conditions or any type of weather problems that might occur prior to landing, flight rules have been developed as guidelines for all landings. Although the rules vary depending on the location of the landing (Kennedy Space Center or Edwards AFB), length of mission, and weight of vehicle, most of the rules can be condensed into 4 major groupings. These are: (1) Cloud ceilings should not be less than 3048 m (10,000 feet), (2) Visibility should not be less than 13 km (7 nm), (3) Cross-wind no greater than 5-8 m/s (10-15 knots); and (4) No showers or thunderstorms at or within 56 km (30 nm) of the Shuttle Landing Facility. This study consisted of developing a climatological database of the Shuttle Landing Facility (SLF) surface observations and performing an analysis of observed conditions one and two hours subsequent to given conditions at the SLF to help analyze the 0.2 cloud cover rule. Particular emphasis was placed on Shuttle landing weather violations and the amounts of cloud cover below 3048 m (10,000 ft.). This analysis has helped to

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.

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

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.

Saharan Dust as a Causal Factor of Significant Cloud Cover Along the Saharan Air Layer in the Atlantic Ocean

NASA Technical Reports Server (NTRS)

Kishcha, Pavel; Da Silva, Arlindo M.; Starobinet, Boris; Alpert, Pinhas

2016-01-01

The tropical Atlantic is frequently affected by Saharan dust intrusions. Based on MODIS cloud fraction (CF) data during the ten-year study period, we found that these dust intrusions contribute to significant cloud cover along the Saharan Air Layer (SAL). Below the temperature inversion at the SAL's base, the presence of large amounts of settling dust particles, together with marine aerosols, produces meteorological conditions suitable for the formation of shallow stratocumulus clouds. The significant cloud fraction along the SAL together with clouds over the Atlantic Inter-tropical Convergence Zone contributes to the 20% hemispheric CF asymmetry between the tropical North and South Atlantic. This leads to the imbalance in strong solar radiation, which reaches the sea surface between the tropical North and South Atlantic, and, consequently, affects climate formation in the tropical Atlantic. Therefore, despite the fact that, over the global ocean, there is no noticeable hemispheric asymmetry in cloud fraction, over the significant area such as the tropical Atlantic the hemispheric asymmetry in CF takes place. Saharan dust is also the major contributor to hemispheric aerosol asymmetry over the tropical Atlantic. The NASA GEOS-5 model with aerosol data assimilation was used to extend the MERRA reanalysis with five atmospheric aerosol species (desert dust, sulfates, organic carbon, black carbon, and sea-salt). The obtained ten-year (2002 - 2012) MERRA-driven aerosol reanalysis dataset (aka MERRAero) showed that, over the tropical Atlantic, dust and carbonaceous aerosols were distributed asymmetrically relative to the equator, while other aerosol species were distributed more symmetrically.

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.

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

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.

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.

STS-56 view of freeflying SPARTAN-201 backdropped against heavy cloud cover

NASA Image and Video Library

1993-04-17

STS056-90-034 (8-17 April 1993) --- Backdropped against heavy cloud cover over the Mediterranean Sea, the SPARTAN-201 satellite was captured on 70mm by crewmembers aboard the Space Shuttle Discovery. SPARTAN is a free-flying payload designed to study the solar wind and part of the sun's corona. The project was conceived in the late 1970s to take advantage of the opportunity offered by the Space Shuttle to provide more observation time for the increasingly more sophisticated experiments than the five to ten minutes provided by sounding rocket flights. On the mission's third day, Astronaut Ellen Ochoa, Mission Specialist, used the remote manipulator system (RMS) to lift the satellite from its support structure on Discovery and release it in space. The reusable craft was later recaptured and returned to Earth with the crew. Note the tip of Discovery's vertical stabilizer at frame's edge.

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.

Effects of Digitization and JPEG Compression on Land Cover Classification Using Astronaut-Acquired Orbital Photographs

NASA Technical Reports Server (NTRS)

Robinson, Julie A.; Webb, Edward L.; Evangelista, Arlene

2000-01-01

Studies that utilize astronaut-acquired orbital photographs for visual or digital classification require high-quality data to ensure accuracy. The majority of images available must be digitized from film and electronically transferred to scientific users. This study examined the effect of scanning spatial resolution (1200, 2400 pixels per inch [21.2 and 10.6 microns/pixel]), scanning density range option (Auto, Full) and compression ratio (non-lossy [TIFF], and lossy JPEG 10:1, 46:1, 83:1) on digital classification results of an orbital photograph from the NASA - Johnson Space Center archive. Qualitative results suggested that 1200 ppi was acceptable for visual interpretive uses for major land cover types. Moreover, Auto scanning density range was superior to Full density range. Quantitative assessment of the processing steps indicated that, while 2400 ppi scanning spatial resolution resulted in more classified polygons as well as a substantially greater proportion of polygons < 0.2 ha, overall agreement between 1200 ppi and 2400 ppi was quite high. JPEG compression up to approximately 46:1 also did not appear to have a major impact on quantitative classification characteristics. We conclude that both 1200 and 2400 ppi scanning resolutions are acceptable options for this level of land cover classification, as well as a compression ratio at or below approximately 46:1. Auto range density should always be used during scanning because it acquires more of the information from the film. The particular combination of scanning spatial resolution and compression level will require a case-by-case decision and will depend upon memory capabilities, analytical objectives and the spatial properties of the objects in the image.

Cloud Spirals and Outflow in Tropical Storm Katrina

NASA Technical Reports Server (NTRS)

2005-01-01

On Tuesday, August 30, 2005, NASA's Multi-angle Imaging SpectroRadiometer retrieved cloud-top heights and cloud-tracked wind velocities for Tropical Storm Katrina, as the center of the storm was situated over the Tennessee valley. At this time Katrina was weakening and no longer classified as a hurricane, and would soon become an extratropical depression. Measurements such as these can help atmospheric scientists compare results of computer-generated hurricane simulations with observed conditions, ultimately allowing them to better represent and understand physical processes occurring in hurricanes.

Because air currents are influenced by the Coriolis force (caused by the rotation of the Earth), Northern Hemisphere hurricanes are characterized by an inward counterclockwise (cyclonic) rotation towards the center. It is less widely known that, at high altitudes, outward-spreading bands of cloud rotate in a clockwise (anticyclonic) direction. The image on the left shows the retrieved cloud-tracked winds as red arrows superimposed across the natural color view from MISR's nadir (vertical-viewing) camera. Both the counter-clockwise motion for the lower-level storm clouds and the clockwise motion for the upper clouds are apparent in these images. The speeds for the clockwise upper level winds have typical values between 40 and 45 m/s (144-162 km/hr). The low level counterclockwise winds have typical values between 7 and 24 m/s (25-86 km/hr), weakening with distance from the storm center. The image on the right displays the cloud-top height retrievals. Areas where cloud heights could not be retrieved are shown in dark gray. Both the wind velocity vectors and the cloud-top height field were produced by automated computer recognition of displacements in spatial features within successive MISR images acquired at different view angles and at slightly different times.

The Multi-angle Imaging SpectroRadiometer observes the daylit Earth continuously, viewing the

Multi-layer Clouds Over the South Indian Ocean

NASA Technical Reports Server (NTRS)

2003-01-01

The complex structure and beauty of polar clouds are highlighted by these images acquired by the Multi-angle Imaging SpectroRadiometer (MISR) on April 23, 2003. These clouds occur at multiple altitudes and exhibit a noticeable cyclonic circulation over the Southern Indian Ocean, to the north of Enderbyland, East Antarctica.

The image at left was created by overlying a natural-color view from MISR's downward-pointing (nadir) camera with a color-coded stereo height field. MISR retrieves heights by a pattern recognition algorithm that utilizes multiple view angles to derive cloud height and motion. The opacity of the height field was then reduced until the field appears as a translucent wash over the natural-color image. The resulting purple, cyan and green hues of this aesthetic display indicate low, medium or high altitudes, respectively, with heights ranging from less than 2 kilometers (purple) to about 8 kilometers (green). In the lower right corner, the edge of the Antarctic coastline and some sea ice can be seen through some thin, high cirrus clouds.

The right-hand panel is a natural-color image from MISR's 70-degree backward viewing camera. This camera looks backwards along the path of Terra's flight, and in the southern hemisphere the Sun is in front of this camera. This perspective causes the cloud-tops to be brightly outlined by the sun behind them, and enhances the shadows cast by clouds with significant vertical structure. An oblique observation angle also enhances the reflection of light by atmospheric particles, and accentuates the appearance of polar clouds. The dark ocean and sea ice that were apparent through the cirrus clouds at the bottom right corner of the nadir image are overwhelmed by the brightness of these clouds at the oblique view.

The Multi-angle Imaging SpectroRadiometer observes the daylit Earth continuously from pole to pole, and every 9 days views the entire globe between 82 degrees north and 82 degrees south latitude

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 Height Maps for Hurricanes Frances and Ivan

NASA Technical Reports Server (NTRS)

2004-01-01

acquired, clouds within Frances and Ivan had attained altitudes of 15 kilometers and 16 kilometers above sea level, respectively. The height fields pictured here are uncorrected for the effects of cloud motion. Wind-corrected heights (which have higher accuracy but sparser spatial coverage) are within about 1 kilometer of the heights shown here.

The Multi-angle Imaging SpectroRadiometer observes the daylit Earth continuously and every 9 days views the entire globe between 82o north and 82o south latitude. These data products were generated from a portion of the imagery acquired during Terra orbits 25081 and 25094. The panels cover an area of 380 kilometers x 924 kilometers, and utilize data from within blocks 65 to 87 within World Reference System-2 paths 14 and 222, respectively.

MISR was built and is managed by NASA's Jet Propulsion Laboratory, Pasadena, CA, for NASA's Office of Earth Science, Washington, DC. The Terra satellite is managed by NASA's Goddard Space Flight Center, Greenbelt, MD. JPL is a division of the California In

MODIS Views Variations in Cloud Types

NASA Technical Reports Server (NTRS)

2002-01-01

This MODIS image, centered over the Great Lakes region in North America, shows a variety of cloud types. The clouds at the top of the image, colored pink, are cold, high-level snow and ice clouds, while the neon green clouds are lower-level water clouds. Because different cloud types reflect and emit radiant energy differently, scientists can use MODIS' unique data set to measure the sizes of cloud particles and distinguish between water, snow, and ice clouds. This scene was acquired on Feb. 24, 2000, and is a red, green, blue composite of bands 1, 6, and 31 (0.66, 1.6, and 11.0 microns, respectively). Image by Liam Gumley, Space Science and Engineering Center, University of Wisconsin-Madison

A Cut in the Clouds

NASA Image and Video Library

2017-12-08

Like a ship carving its way through the sea, the South Georgia and South Sandwich Islands parted the clouds. The Moderate Resolution Imaging Spectroradiometer (MODIS) on NASA’s Terra satellite acquired this natural-color image on February 2, 2017. The ripples in the clouds are known as gravity waves. NASA image by Jeff Schmaltz, LANCE/EOSDIS Rapid Response #nasagoddard

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.

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.

How to model moon signals using 2-dimensional Gaussian function: Classroom activity for measuring nighttime cloud cover

NASA Astrophysics Data System (ADS)

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

2016-12-01

used for quantifying cloud cover as captured by ordinary cameras (Gacal et al, 2016). Cloud cover can be defined as the ratio of number of pixels whose values exceeds 0.07 and the total number of pixels. In this particular image, cloud cover value is 0.67.

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.

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.

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.

Distributed MRI reconstruction using Gadgetron-based cloud computing.

PubMed

Xue, Hui; Inati, Souheil; Sørensen, Thomas Sangild; Kellman, Peter; Hansen, Michael S

2015-03-01

To expand the open source Gadgetron reconstruction framework to support distributed computing and to demonstrate that a multinode version of the Gadgetron can be used to provide nonlinear reconstruction with clinically acceptable latency. The Gadgetron framework was extended with new software components that enable an arbitrary number of Gadgetron instances to collaborate on a reconstruction task. This cloud-enabled version of the Gadgetron was deployed on three different distributed computing platforms ranging from a heterogeneous collection of commodity computers to the commercial Amazon Elastic Compute Cloud. The Gadgetron cloud was used to provide nonlinear, compressed sensing reconstruction on a clinical scanner with low reconstruction latency (eg, cardiac and neuroimaging applications). The proposed setup was able to handle acquisition and 11 -SPIRiT reconstruction of nine high temporal resolution real-time, cardiac short axis cine acquisitions, covering the ventricles for functional evaluation, in under 1 min. A three-dimensional high-resolution brain acquisition with 1 mm(3) isotropic pixel size was acquired and reconstructed with nonlinear reconstruction in less than 5 min. A distributed computing enabled Gadgetron provides a scalable way to improve reconstruction performance using commodity cluster computing. Nonlinear, compressed sensing reconstruction can be deployed clinically with low image reconstruction latency. © 2014 Wiley Periodicals, Inc.

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.

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

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

Waves on White: Ice or Clouds?

NASA Technical Reports Server (NTRS)

2005-01-01

snow or ice-covered surfaces is important in order to adequately characterize the radiation balance of the polar regions. However, detecting clouds using spaceborne detectors over snow and ice surfaces is notoriously difficult, because the surface may often be as bright and as cold as the overlying clouds, and because polar atmospheric temperature inversions sometimes mean that clouds are warmer than the underlying snow or ice surface. The Angular Signature Cloud Mask (ASCM) was developed based on the Band-Differenced Angular Signature (BDAS) approach, introduced by Di Girolamo and Davies (1994) and updated for MISR application by Di Girolamo and Wilson (2003). BDAS uses both spectral and angular changes in reflectivity to distinguish clouds from the background, and the ASCM calculates the difference between the 446 and 866 nanometer reflectances at MISR's two most oblique cameras that view forward-scattered light. New land thresholds for the ASCM are planned for delivery later this year.

The Multi-angle Imaging SpectroRadiometer observes the daylit Earth continuously and every 9 days views the entire globe between 82o north and 82o south latitude. This image area covers about 277 kilometers by 421 kilometers in the interior of the East Antarctic ice sheet. These data products were generated from a portion of the imagery acquired during Terra orbit 26584 and utilize data from within blocks 159 to 161 within World Reference System-2 path 63.

MISR was built and is managed by NASA's Jet Propulsion Laboratory, Pasadena, CA, for NASA's Office of Earth Science, Washington, DC. The Terra satellite is managed by NASA's Goddard Space Flight Center, Greenbelt, MD. JPL is a division of the California Institute of Technology.

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.

Multi-layer Clouds Over the South Indian Ocean

NASA Image and Video Library

2003-05-07

The complex structure and beauty of polar clouds are highlighted by these images acquired by NASA Terra spacecraft on April 23, 2003. These clouds occur at multiple altitudes and exhibit a noticeable cyclonic circulation over the Southern Indian Ocean,

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

Procedures for gathering ground truth information for a supervised approach to a computer-implemented land cover classification of LANDSAT-acquired multispectral scanner data

NASA Technical Reports Server (NTRS)

Joyce, A. T.

1978-01-01

Procedures for gathering ground truth information for a supervised approach to a computer-implemented land cover classification of LANDSAT acquired multispectral scanner data are provided in a step by step manner. Criteria for determining size, number, uniformity, and predominant land cover of training sample sites are established. Suggestions are made for the organization and orientation of field team personnel, the procedures used in the field, and the format of the forms to be used. Estimates are made of the probable expenditures in time and costs. Examples of ground truth forms and definitions and criteria of major land cover categories are provided in appendixes.

UAS-SfM for coastal research: Geomorphic feature extraction and land cover classification from high-resolution elevation and optical imagery

USGS Publications Warehouse

Sturdivant, Emily; Lentz, Erika; Thieler, E. Robert; Farris, Amy; Weber, Kathryn; Remsen, David P.; Miner, Simon; Henderson, Rachel

2017-01-01

The vulnerability of coastal systems to hazards such as storms and sea-level rise is typically characterized using a combination of ground and manned airborne systems that have limited spatial or temporal scales. Structure-from-motion (SfM) photogrammetry applied to imagery acquired by unmanned aerial systems (UAS) offers a rapid and inexpensive means to produce high-resolution topographic and visual reflectance datasets that rival existing lidar and imagery standards. Here, we use SfM to produce an elevation point cloud, an orthomosaic, and a digital elevation model (DEM) from data collected by UAS at a beach and wetland site in Massachusetts, USA. We apply existing methods to (a) determine the position of shorelines and foredunes using a feature extraction routine developed for lidar point clouds and (b) map land cover from the rasterized surfaces using a supervised classification routine. In both analyses, we experimentally vary the input datasets to understand the benefits and limitations of UAS-SfM for coastal vulnerability assessment. We find that (a) geomorphic features are extracted from the SfM point cloud with near-continuous coverage and sub-meter precision, better than was possible from a recent lidar dataset covering the same area; and (b) land cover classification is greatly improved by including topographic data with visual reflectance, but changes to resolution (when <50 cm) have little influence on the classification accuracy.

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.

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

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

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.

Detection of long duration cloud contamination in hyper-temporal NDVI imagery

NASA Astrophysics Data System (ADS)

Ali, A.; de Bie, C. A. J. M.; Skidmore, A. K.; Scarrott, R. G.

2012-04-01

NDVI time series imagery are commonly used as a reliable source for land use and land cover mapping and monitoring. However long duration cloud can significantly influence its precision in areas where persistent clouds prevails. Therefore quantifying errors related to cloud contamination are essential for accurate land cover mapping and monitoring. This study aims to detect long duration cloud contamination in hyper-temporal NDVI imagery based land cover mapping and monitoring. MODIS-Terra NDVI imagery (250 m; 16-day; Feb'03-Dec'09) were used after necessary pre-processing using quality flags and upper envelope filter (ASAVOGOL). Subsequently stacked MODIS-Terra NDVI image (161 layers) was classified for 10 to 100 clusters using ISODATA. After classifications, 97 clusters image was selected as best classified with the help of divergence statistics. To detect long duration cloud contamination, mean NDVI class profiles of 97 clusters image was analyzed for temporal artifacts. Results showed that long duration clouds affect the normal temporal progression of NDVI and caused anomalies. Out of total 97 clusters, 32 clusters were found with cloud contamination. Cloud contamination was found more prominent in areas where high rainfall occurs. This study can help to stop error propagation in regional land cover mapping and monitoring, caused by long duration cloud contamination.

The Citizen CATE Experiment: Techniques to Determine Totality Coverage and Clouded Data Removal.

NASA Astrophysics Data System (ADS)

McKay, Myles A.; Ursache, Andrei; Penn, Matthew; Citizen CATE Experiment 2017 Team

2018-01-01

August 21, 2017, the Citizen Continental-America Telescopic Eclipse(CATE) Experiment observed the 2017 total solar eclipse using a network of 68 identical telescopes and camera systems along the path of totality. The result from the observation was over 90% of all sites collected totality data on the day of the eclipse. Since the volunteers had to remove the solar filter manually, there is an uncertainty between the time of totality and data acquired during totality. Some sites also experienced cloudy weather which obscured the eclipse in some of the exposures but had small breaks in the clouds during the observation, collecting clear totality data. Before we can process and analyze the eclipse data, we must carefully determine which frames cover the time of totality for each site and remove exposures with clouds blocking the FOV. In this poster, we will discuss the techniques we used to determine the extent of totality from each location using the logged GPS data and the removal of totality exposure with clouds.

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.

Trends and variability of cloud fraction cover in the Arctic, 1982-2009

NASA Astrophysics Data System (ADS)

Boccolari, Mauro; Parmiggiani, Flavio

2018-05-01

Climatology, trends and variability of cloud fraction cover (CFC) data over the Arctic (north of 70°N), were analysed over the 1982-2009 period. Data, available from the Climate Monitoring Satellite Application Facility (CM SAF), are derived from satellite measurements by AVHRR. Climatological means confirm permanent high CFC values over the Atlantic sector during all the year and during summer over the eastern Arctic Ocean. Lower values are found in the rest of the analysed area especially over Greenland and the Canadian Archipelago, nearly continuously during all the months. These results are confirmed by CFC trends and variability. Statistically significant trends were found during all the months over the Greenland Sea, particularly during the winter season (negative, less than -5 % dec -1) and over the Beaufort Sea in spring (positive, more than +5 % dec -1). CFC variability, investigated by the Empirical Orthogonal Functions, shows a substantial "non-variability" in the Northern Atlantic Ocean. Statistically significant correlations between CFC principal components elements and both the Pacific Decadal Oscillation index and Pacific North America patterns are found.

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.

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.

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

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.

Assessing the performance of aerial image point cloud and spectral metrics in predicting boreal forest canopy cover

NASA Astrophysics Data System (ADS)

Melin, M.; Korhonen, L.; Kukkonen, M.; Packalen, P.

2017-07-01

Canopy cover (CC) is a variable used to describe the status of forests and forested habitats, but also the variable used primarily to define what counts as a forest. The estimation of CC has relied heavily on remote sensing with past studies focusing on satellite imagery as well as Airborne Laser Scanning (ALS) using light detection and ranging (lidar). Of these, ALS has been proven highly accurate, because the fraction of pulses penetrating the canopy represents a direct measurement of canopy gap percentage. However, the methods of photogrammetry can be applied to produce point clouds fairly similar to airborne lidar data from aerial images. Currently there is little information about how well such point clouds measure canopy density and gaps. The aim of this study was to assess the suitability of aerial image point clouds for CC estimation and compare the results with those obtained using spectral data from aerial images and Landsat 5. First, we modeled CC for n = 1149 lidar plots using field-measured CCs and lidar data. Next, this data was split into five subsets in north-south direction (y-coordinate). Finally, four CC models (AerialSpectral, AerialPointcloud, AerialCombi (spectral + pointcloud) and Landsat) were created and they were used to predict new CC values to the lidar plots, subset by subset, using five-fold cross validation. The Landsat and AerialSpectral models performed with RMSEs of 13.8% and 12.4%, respectively. AerialPointcloud model reached an RMSE of 10.3%, which was further improved by the inclusion of spectral data; RMSE of the AerialCombi model was 9.3%. We noticed that the aerial image point clouds managed to describe only the outermost layer of the canopy and missed the details in lower canopy, which was resulted in weak characterization of the total CC variation, especially in the tails of the data.

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

Use of satellite data in runoff forecasting in the heavily forested, cloud-covered Pacific Northwest. [Upper Snake, Boise, Dworshak, Libby and Hungry Horse River Basins

NASA Technical Reports Server (NTRS)

Dillard, J. P.; Orwig, C. F. (Principal Investigator)

1980-01-01

The author has identified the following significant results. Satellite-derived snow cover data improves forecasts of stream flow but not at a statistically significant amount and should not be used exclusively because of persistent cloud cover. Based upon reconstruction runs, satellite data can be used to augment snow-flight data in the Upper Snake, Boise, Dworshak, and Hungry Horse basins. Satellite data does not compare well with aerial snow-flight data in the Libby basin.

On the relationships among cloud cover, mixed-phase partitioning, and planetary albedo in GCMs

DOE PAGES

McCoy, Daniel T.; Tan, Ivy; Hartmann, Dennis L.; ...

2016-05-06

In this study, it is shown that CMIP5 global climate models (GCMs) that convert supercooled water to ice at relatively warm temperatures tend to have a greater mean-state cloud fraction and more negative cloud feedback in the middle and high latitude Southern Hemisphere. We investigate possible reasons for these relationships by analyzing the mixed-phase parameterizations in 26 GCMs. The atmospheric temperature where ice and liquid are equally prevalent (T5050) is used to characterize the mixed-phase parameterization in each GCM. Liquid clouds have a higher albedo than ice clouds, so, all else being equal, models with more supercooled liquid water wouldmore » also have a higher planetary albedo. The lower cloud fraction in these models compensates the higher cloud reflectivity and results in clouds that reflect shortwave radiation (SW) in reasonable agreement with observations, but gives clouds that are too bright and too few. The temperature at which supercooled liquid can remain unfrozen is strongly anti-correlated with cloud fraction in the climate mean state across the model ensemble, but we know of no robust physical mechanism to explain this behavior, especially because this anti-correlation extends through the subtropics. A set of perturbed physics simulations with the Community Atmospheric Model Version 4 (CAM4) shows that, if its temperature-dependent phase partitioning is varied and the critical relative humidity for cloud formation in each model run is also tuned to bring reflected SW into agreement with observations, then cloud fraction increases and liquid water path (LWP) decreases with T5050, as in the CMIP5 ensemble.« less

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

Can Clouds replace Grids? Will Clouds replace Grids?

NASA Astrophysics Data System (ADS)

Shiers, J. D.

2010-04-01

The world's largest scientific machine - comprising dual 27km circular proton accelerators cooled to 1.9oK and located some 100m underground - currently relies on major production Grid infrastructures for the offline computing needs of the 4 main experiments that will take data at this facility. After many years of sometimes difficult preparation the computing service has been declared "open" and ready to meet the challenges that will come shortly when the machine restarts in 2009. But the service is not without its problems: reliability - as seen by the experiments, as opposed to that measured by the official tools - still needs to be significantly improved. Prolonged downtimes or degradations of major services or even complete sites are still too common and the operational and coordination effort to keep the overall service running is probably not sustainable at this level. Recently "Cloud Computing" - in terms of pay-per-use fabric provisioning - has emerged as a potentially viable alternative but with rather different strengths and no doubt weaknesses too. Based on the concrete needs of the LHC experiments - where the total data volume that will be acquired over the full lifetime of the project, including the additional data copies that are required by the Computing Models of the experiments, approaches 1 Exabyte - we analyze the pros and cons of Grids versus Clouds. This analysis covers not only technical issues - such as those related to demanding database and data management needs - but also sociological aspects, which cannot be ignored, neither in terms of funding nor in the wider context of the essential but often overlooked role of science in society, education and economy.

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

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.

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.

Geologic Mapping and Mineral Resource Assessment of the Healy and Talkeetna Mountains Quadrangles, Alaska Using Minimal Cloud- and Snow-Cover ASTER Data

USGS Publications Warehouse

Hubbard, Bernard E.; Rowan1, Lawrence C.; Dusel-Bacon, Cynthia; Eppinger, Robert G.

2007-01-01

On July 8, 2003, ASTER acquired satellite imagery of a 60 km-wide swath of parts of two 1:250,000 Alaska quadrangles, under favorable conditions of minimal cloud- and snow-cover. Rocks from eight different lithotectonic terranes are exposed within the swath of data, several of which define permissive tracts for various mineral deposit types such as: volcanic-hosted massive sulfides (VMS) and porphyry copper and molybdenum. Representative rock samples collected from 13 different lithologic units from the Bonnifield mining district within the Yukon-Tanana terrane (YTT), plus hydrothermally altered VMS material from the Red Mountain prospect, were analyzed to produce a spectral library spanning the VNIR-SWIR (0.4 - 2.5 ?m) through the TIR (8.1 - 11.7 ?m). Comparison of the five-band ASTER TIR emissivity and decorrelation stretch data to available geologic maps indicates that rocks from the YTT display the greatest range and diversity of silica composition of the mapped terranes, ranging from mafic rocks to silicic quartzites. The nine-band ASTER VNIR-SWIR reflectance data and spectral matched-filter processing were used to map several lithologic sequences characterized by distinct suites of minerals that exhibit diagnostic spectral features (e.g. chlorite, epidote, amphibole and other ferrous-iron bearing minerals); other sequences were distinguished by their weathering characteristics and associated hydroxyl- and ferric-iron minerals, such as illite, smectite, and hematite. Smectite, kaolinite, opaline silica, jarosite and/or other ferric iron minerals defined narrow (< 250 m diameter) zonal patterns around Red Mountain and other potential VMS targets. Using ASTER we identified some of the known mineral deposits in the region, as well as mineralogically similar targets that may represent potential undiscovered deposits. Some known deposits were not identified and may have been obscured by vegetation- or snow-cover, or were too small to be resolved.

Clouds on Neptune: Motions, Evolution, and Structure

NASA Technical Reports Server (NTRS)

Sromovsky, Larry A.; Morgan, Thomas (Technical Monitor)

2001-01-01

The aims of our original proposal were these: (1) improving measurements of Neptune's circulation, (2) understanding the spatial distribution of cloud features, (3) discovery of new cloud features and understanding their evolutionary process, (4) understanding the vertical structure of zonal cloud patterns, (5) defining the structure of discrete cloud features, and (6) defining the near IR albedo and light curve of Triton. Towards these aims we proposed analysis of existing 1996 groundbased NSFCAM/IRTF observations and nearly simultaneous WFPC2 observations from the Hubble Space Telescope. We also proposed to acquire new observations from both HST and the IRTF.

Lightweight Electronic Camera for Research on Clouds

NASA Technical Reports Server (NTRS)

Lawson, Paul

2006-01-01

"Micro-CPI" (wherein "CPI" signifies "cloud-particle imager") is the name of a small, lightweight electronic camera that has been proposed for use in research on clouds. It would acquire and digitize high-resolution (3- m-pixel) images of ice particles and water drops at a rate up to 1,000 particles (and/or drops) per second.

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.

Effects of cloud cover and meteorology in estimating ground-level air pollution using MAIAC AOD in the Yangtze River Delta

NASA Astrophysics Data System (ADS)

Xiao, Q.; Liu, Y.

2017-12-01

Satellite aerosol optical depth (AOD) has been used to assess fine particulate matter (PM2.5) pollution worldwide. However, non-random missing AOD due to cloud cover or high surface reflectance can cause up to 80% data loss and bias model-estimated spatial and temporal trends of PM2.5. Previous studies filled the data gap largely by spatial smoothing which ignored the impact of cloud cover and meteorology on aerosol loadings and has been shown to exhibit poor performance when monitoring stations are sparse or when there is seasonal large-scale missingness. Using the Yangtze River Delta of China as an example, we present a flexible Multiple Imputation (MI) method that combines cloud fraction, elevation, humidity, temperature, and spatiotemporal trends to impute the missing AOD. A two-stage statistical model driven by gap-filled AOD, meteorology and land use information was then fitted to estimate daily ground PM2.5 concentrations in 2013 and 2014 at 1 km resolution with complete coverage in space and time. The daily MI models have an average R2 of 0.77, with an inter-quartile range of 0.71 to 0.82 across days. The overall model 10-fold cross-validation R2 were 0.81 and 0.73 (for year 2013 and 2014, respectively. Predictions with only observational AOD or only imputed AOD showed similar accuracy. This method provides reliable PM2.5 predictions with complete coverage at high resolution. By including all the pixels of all days into model development, this method corrected the sampling bias in satellite-driven air pollution modelling due to non-random missingness in AOD. Comparing with previously reported gap-filling methods, the MI method has the strength of not relying on ground PM2.5 measurements, therefore allows the prediction of historical PM2.5 levels prior to the establishment of regular ground monitoring networks.

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.

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.

Snow Cover Mapping and Ice Avalanche Monitoring from the Satellite Data of the Sentinels

NASA Astrophysics Data System (ADS)

Wang, S.; Yang, B.; Zhou, Y.; Wang, F.; Zhang, R.; Zhao, Q.

2018-04-01

In order to monitor ice avalanches efficiently under disaster emergency conditions, a snow cover mapping method based on the satellite data of the Sentinels is proposed, in which the coherence and backscattering coefficient image of Synthetic Aperture Radar (SAR) data (Sentinel-1) is combined with the atmospheric correction result of multispectral data (Sentinel-2). The coherence image of the Sentinel-1 data could be segmented by a certain threshold to map snow cover, with the water bodies extracted from the backscattering coefficient image and removed from the coherence segment result. A snow confidence map from Sentinel-2 was used to map the snow cover, in which the confidence values of the snow cover were relatively high. The method can make full use of the acquired SAR image and multispectral image under emergency conditions, and the application potential of Sentinel data in the field of snow cover mapping is exploited. The monitoring frequency can be ensured because the areas obscured by thick clouds are remedied in the monitoring results. The Kappa coefficient of the monitoring results is 0.946, and the data processing time is less than 2 h, which meet the requirements of disaster emergency monitoring.

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.

Classification by Using Multispectral Point Cloud Data

NASA Astrophysics Data System (ADS)

Liao, C. T.; Huang, H. H.

2012-07-01

Remote sensing images are generally recorded in two-dimensional format containing multispectral information. Also, the semantic information is clearly visualized, which ground features can be better recognized and classified via supervised or unsupervised classification methods easily. Nevertheless, the shortcomings of multispectral images are highly depending on light conditions, and classification results lack of three-dimensional semantic information. On the other hand, LiDAR has become a main technology for acquiring high accuracy point cloud data. The advantages of LiDAR are high data acquisition rate, independent of light conditions and can directly produce three-dimensional coordinates. However, comparing with multispectral images, the disadvantage is multispectral information shortage, which remains a challenge in ground feature classification through massive point cloud data. Consequently, by combining the advantages of both LiDAR and multispectral images, point cloud data with three-dimensional coordinates and multispectral information can produce a integrate solution for point cloud classification. Therefore, this research acquires visible light and near infrared images, via close range photogrammetry, by matching images automatically through free online service for multispectral point cloud generation. Then, one can use three-dimensional affine coordinate transformation to compare the data increment. At last, the given threshold of height and color information is set as threshold in classification.

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.

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.

Military clouds: utilization of cloud computing systems at the battlefield

NASA Astrophysics Data System (ADS)

Süleyman, Sarıkürk; Volkan, Karaca; İbrahim, Kocaman; Ahmet, Şirzai

2012-05-01

Cloud computing is known as a novel information technology (IT) concept, which involves facilitated and rapid access to networks, servers, data saving media, applications and services via Internet with minimum hardware requirements. Use of information systems and technologies at the battlefield is not new. Information superiority is a force multiplier and is crucial to mission success. Recent advances in information systems and technologies provide new means to decision makers and users in order to gain information superiority. These developments in information technologies lead to a new term, which is known as network centric capability. Similar to network centric capable systems, cloud computing systems are operational today. In the near future extensive use of military clouds at the battlefield is predicted. Integrating cloud computing logic to network centric applications will increase the flexibility, cost-effectiveness, efficiency and accessibility of network-centric capabilities. In this paper, cloud computing and network centric capability concepts are defined. Some commercial cloud computing products and applications are mentioned. Network centric capable applications are covered. Cloud computing supported battlefield applications are analyzed. The effects of cloud computing systems on network centric capability and on the information domain in future warfare are discussed. Battlefield opportunities and novelties which might be introduced to network centric capability by cloud computing systems are researched. The role of military clouds in future warfare is proposed in this paper. It was concluded that military clouds will be indispensible components of the future battlefield. Military clouds have the potential of improving network centric capabilities, increasing situational awareness at the battlefield and facilitating the settlement of information superiority.

Point clouds segmentation as base for as-built BIM creation

NASA Astrophysics Data System (ADS)

Macher, H.; Landes, T.; Grussenmeyer, P.

2015-08-01

In this paper, a three steps segmentation approach is proposed in order to create 3D models from point clouds acquired by TLS inside buildings. The three scales of segmentation are floors, rooms and planes composing the rooms. First, floor segmentation is performed based on analysis of point distribution along Z axis. Then, for each floor, room segmentation is achieved considering a slice of point cloud at ceiling level. Finally, planes are segmented for each room, and planes corresponding to ceilings and floors are identified. Results of each step are analysed and potential improvements are proposed. Based on segmented point clouds, the creation of as-built BIM is considered in a future work section. Not only the classification of planes into several categories is proposed, but the potential use of point clouds acquired outside buildings is also considered.

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 fraction and cloud base measurements from scanning Doppler lidar during WFIP-2

NASA Astrophysics Data System (ADS)

Bonin, T.; Long, C.; Lantz, K. O.; Choukulkar, A.; Pichugina, Y. L.; McCarty, B.; Banta, R. M.; Brewer, A.; Marquis, M.

2017-12-01

The second Wind Forecast Improvement Project (WFIP-2) consisted of an 18-month field deployment of a variety of instrumentation with the principle objective of validating and improving NWP forecasts for wind energy applications in complex terrain. As a part of the set of instrumentation, several scanning Doppler lidars were installed across the study domain to primarily measure profiles of the mean wind and turbulence at high-resolution within the planetary boundary layer. In addition to these measurements, Doppler lidar observations can be used to directly quantify the cloud fraction and cloud base, since clouds appear as a high backscatter return. These supplementary measurements of clouds can then be used to validate cloud cover and other properties in NWP output. Herein, statistics of the cloud fraction and cloud base height from the duration of WFIP-2 are presented. Additionally, these cloud fraction estimates from Doppler lidar are compared with similar measurements from a Total Sky Imager and Radiative Flux Analysis (RadFlux) retrievals at the Wasco site. During mostly cloudy to overcast conditions, estimates of the cloud radiating temperature from the RadFlux methodology are also compared with Doppler lidar measured cloud base height.

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.

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.

Seasonal and interannual variations in the influence of cloud cover variability on snowpack and streamflow in the western U.S.

NASA Astrophysics Data System (ADS)

Sumargo, E.; Cayan, D. R.

2016-12-01

Solar radiation (S) is a key driver of snowmelt and water fluxes, but its effect varies depending on time of year and also upon the hydrological character (e.g., dry or wet) of a given year. In this study, we use remote sensed S to quantify cloudiness variability and its effects on snowmelt and streamflow across mountain basins in the western U.S. We utilize 20 years (1996-2015) of NASA/NOAA GOES-derived cloud albedo (αcloud) at 4-km daily samples to estimate S over relatively fine spatial and temporal resolution during Feb-Jul when snowmelt is most active. Daily snow water equivalent (SWE) records from >200 CDEC and SNOTEL locations, along with daily stream discharge (Q) from USGS HCDN records are used to compute day-to-day changes (dSWE and dQ). Multivariate linear regression models of dSWE and dQ are constructed for each month, wherein αcloud from several days prior up to the concurrent day are the predictors. In Feb-May, the results show predominantly negative correlations between αcloud and dSWE, confirming the cloud-shading effect in preserving snowpack and reducing runoff. The influence of cloudiness variability on snowpack, denoted by the coefficient of determination (R2) between the measured and modeled dSWE, amounts 4%-73% over Feb-Jul, averaging 20% in the northwest and 26% in the southwest. The dQ case exhibits similar patterns, but lower explained variance. In Jun-Jul, most locations in both dSWE and dQ cases display positive correlation but with diminished R2, presumably reflecting the drying effect of summertime. In comparing dry and wet years, the R2 is somewhat higher in dry years, suggesting that the importance of cloud cover and the associated solar insolation variability is higher in cases with greater influence from other hydrological factors, including heavy precipitation events and fluctuations associated with a higher snowpack.

Estimation of cloud optical thickness by processing SEVIRI images and implementing a semi analytical cloud property retrieval algorithm

NASA Astrophysics Data System (ADS)

Pandey, P.; De Ridder, K.; van Lipzig, N.

2009-04-01

Clouds play a very important role in the Earth's climate system, as they form an intermediate layer between Sun and the Earth. Satellite remote sensing systems are the only means to provide information about clouds on large scales. The geostationary satellite, Meteosat Second Generation (MSG) has onboard an imaging radiometer, the Spinning Enhanced Visible and Infrared Imager (SEVIRI). SEVIRI is a 12 channel imager, with 11 channels observing the earth's full disk with a temporal resolution of 15 min and spatial resolution of 3 km at nadir, and a high resolution visible (HRV) channel. The visible channels (0.6 µm and 0.81 µm) and near infrared channel (1.6µm) of SEVIRI are being used to retrieve the cloud optical thickness (COT). The study domain is over Europe covering the region between 35°N - 70°N and 10°W - 30°E. SEVIRI level 1.5 images over this domain are being acquired from the European Organisation for the Exploitation of Meteorological Satellites (EUMETSAT) archive. The processing of this imagery, involves a number of steps before estimating the COT. The steps involved in pre-processing are as follows. First, the digital count number is acquired from the imagery. Image geo-coding is performed in order to relate the pixel positions to the corresponding longitude and latitude. Solar zenith angle is determined as a function of latitude and time. The radiometric conversion is done using the values of offsets and slopes of each band. The values of radiance obtained are then used to calculate the reflectance for channels in the visible spectrum using the information of solar zenith angle. An attempt is made to estimate the COT from the observed radiances. A semi analytical algorithm [Kokhanovsky et al., 2003] is implemented for the estimation of cloud optical thickness from the visible spectrum of light intensity reflected from clouds. The asymptotical solution of the radiative transfer equation, for clouds with large optical thickness, is the basis of

Stratus Cloud Radiative Effects from Cloud Processed Bimodal CCN Distributions

NASA Astrophysics Data System (ADS)

Noble, S. R., Jr.; Hudson, J. G.

2016-12-01

Inability to understand cloud processes is a large component of climate uncertainty. Increases in cloud condensation nuclei (CCN) concentrations are known to increase cloud droplet number concentrations (Nc). This aerosol-cloud interaction (ACI) produces greater Nc at smaller sizes, which brightens clouds. A lesser understood ACI is cloud processing of CCN. This improves CCN that then more easily activate at lower cloud supersaturations (S). Bimodal CCN distributions thus ensue from these evaporated cloud droplets. Hudson et al. (2015) related CCN bimodality to Nc. In stratus clouds, bimodal CCN created greater Nc whereas in cumulus less Nc. Thus, CCN distribution shape influences cloud properties; microphysics and radiative properties. Measured uni- and bimodal CCN distributions were input into an adiabatic droplet growth model using various specified vertical wind speeds (W). Bimodal CCN produced greater Nc (Fig. 1a) and smaller mean diameters (MD; Fig. 1b) at lower W typical of stratus clouds (<70 cm/s). Improved CCN (low critical S) were more easily activated at the lower S of stratus from low W, thus, creating greater Nc. Competition for condensate thus reduced MD and drizzle. At greater W, typical of cumulus clouds (>70 cm/s), bimodal CCN made lower Nc with larger MD thus enhancing drizzle whereas unimodal CCN made greater Nc with smaller MD, thus reducing drizzle. Thus, theoretical predictions of Nc and MD for uni- and bimodal CCN agree with the sense of the observations. Radiative effects were determined using a cloud grown to a 250-meter thickness. Bimodal CCN at low W reduced cloud effective radius (re), made greater cloud optical thickness (COT), and made greater cloud albedo (Fig. 1c). At very low W changes were as much as +9% for albedo, +17% for COT, and -12% for re. Stratus clouds typically have low W and cover large areas. Thus, these changes in cloud radiative properties at low W impact climate. Stratus cloud susceptibility to CCN distribution thus

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).

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.

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.

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

Cloud cover classification through simultaneous ground-based measurements of solar and infrared radiation

NASA Astrophysics Data System (ADS)

Orsini, Antonio; Tomasi, Claudio; Calzolari, Francescopiero; Nardino, Marianna; Cacciari, Alessandra; Georgiadis, Teodoro

2002-04-01

Simultaneous measurements of downwelling short-wave solar irradiance and incoming total radiation flux were performed at the Reeves Nevè glacier station (1200 m MSL) in Antarctica on 41 days from late November 1994 to early January 1995, employing the upward sensors of an albedometer and a pyrradiometer. The downwelling short-wave radiation measurements were analysed following the Duchon and O'Malley [J. Appl. Meteorol. 38 (1999) 132] procedure for classifying clouds, using the 50-min running mean values of standard deviation and the ratio of scaled observed to scaled clear-sky irradiance. Comparing these measurements with the Duchon and O'Malley rectangular boundaries and the local human observations of clouds collected on 17 days of the campaign, we found that the Duchon and O'Malley classification method obtained a success rate of 93% for cirrus and only 25% for cumulus. New decision criteria were established for some polar cloud classes providing success rates of 94% for cirrus, 67% for cirrostratus and altostratus, and 33% for cumulus and altocumulus. The ratios of the downwelling short-wave irradiance measured for cloudy-sky conditions to that calculated for clear-sky conditions were analysed in terms of the Kasten and Czeplak [Sol. Energy 24 (1980) 177] formula together with simultaneous human observations of cloudiness, to determine the empirical relationship curves providing reliable estimates of cloudiness for each of the three above-mentioned cloud classes. Using these cloudiness estimates, the downwelling long-wave radiation measurements (obtained as differences between the downward fluxes of total and short-wave radiation) were examined to evaluate the downwelling long-wave radiation flux normalised to totally overcast sky conditions. Calculations of the long-wave radiation flux were performed with the MODTRAN 3.7 code [Kneizys, F.X., Abreu, L.W., Anderson, G.P., Chetwynd, J.H., Shettle, E.P., Berk, A., Bernstein, L.S., Robertson, D.C., Acharya, P

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

Dynamic resource allocation engine for cloud-based real-time video transcoding in mobile cloud computing environments

NASA Astrophysics Data System (ADS)

Adedayo, Bada; Wang, Qi; Alcaraz Calero, Jose M.; Grecos, Christos

2015-02-01

The recent explosion in video-related Internet traffic has been driven by the widespread use of smart mobile devices, particularly smartphones with advanced cameras that are able to record high-quality videos. Although many of these devices offer the facility to record videos at different spatial and temporal resolutions, primarily with local storage considerations in mind, most users only ever use the highest quality settings. The vast majority of these devices are optimised for compressing the acquired video using a single built-in codec and have neither the computational resources nor battery reserves to transcode the video to alternative formats. This paper proposes a new low-complexity dynamic resource allocation engine for cloud-based video transcoding services that are both scalable and capable of being delivered in real-time. Firstly, through extensive experimentation, we establish resource requirement benchmarks for a wide range of transcoding tasks. The set of tasks investigated covers the most widely used input formats (encoder type, resolution, amount of motion and frame rate) associated with mobile devices and the most popular output formats derived from a comprehensive set of use cases, e.g. a mobile news reporter directly transmitting videos to the TV audience of various video format requirements, with minimal usage of resources both at the reporter's end and at the cloud infrastructure end for transcoding services.

Modelling the Effects of Temperature and Cloud Cover Change on Mountain Permafrost Distribution, Northwest Canada

NASA Astrophysics Data System (ADS)

Bonnaventure, P. P.; Lewkowicz, A. G.

2008-12-01

Spatial models of permafrost probability for three study areas in northwest Canada between 59°N and 61°N were perturbed to investigate climate change impacts. The models are empirical-statistical in nature, based on basal temperature of snow (BTS) measurements in winter, and summer ground-truthing of the presence or absence of frozen ground. Predictions of BTS values are made using independent variables of elevation and potential incoming solar radiation (PISR), both derived from a 30 m DEM. These are then transformed into the probability of the presence or absence of permafrost through logistic regression. Under present climate conditions, permafrost percentages in the study areas are 44% for Haines Summit, British Columbia, 38% for Wolf Creek, Yukon, and 69% for part of the Ruby Range, Yukon (Bonnaventure and Lewkowicz, 2008; Lewkowicz and Bonaventure, 2008). Scenarios of air temperature change from -2K (approximating Neoglacial conditions) to +5K (possible within the next century according to the IPCC) were examined for the three sites. Manipulations were carried out by lowering or raising the terrain within the DEM assuming a mean environmental lapse rate of 6.5K/km. Under a -2K scenario, permafrost extent increased by 22-43% in the three study areas. Under a +5K warming, permafrost essentially disappeared in Haines Summit and Wolf Creek, while in the Ruby Range less than 12% of the area remained perennially frozen. It should be emphasized that these model predictions are for equilibrium conditions which might not be attained for several decades or longer in areas of cold permafrost. Cloud cover changes of -10% to +10% were examined through adjusting the partitioning of direct beam and diffuse radiation in the PISR input field. Changes to permafrost extent were small, ranging from -2% to -4% for greater cloudiness with changes of the opposite magnitude for less cloud. The results show that air temperature change has a much greater potential to affect mountain

Diurnal and Seasonal Cloud Base Patterns Highlight Small-Mountain Tropical Cloud Forest Vulnerability

NASA Astrophysics Data System (ADS)

Van Beusekom, A.; Gonzalez, G.; Scholl, M. A.

2016-12-01

The degree to which cloud immersion sustains tropical montane cloud forests (TMCFs) during rainless periods and the amount these clouds are affected by urban areas is not well understood, as cloud base is rarely quantified near mountains. We found that a healthy small-mountain TMCF in Puerto Rico had lowest cloud base during the mid-summer dry season. In addition, we observed that cloud bases were lower than the mountaintops as often in the winter dry season as in the wet seasons, based on 2.5 years of direct and 16 years of indirect observations. The low clouds during dry season appear to be explained by proximity to the oceanic cloud system where lower clouds are seasonally invariant in altitude and cover; along with orographic lifting and trade-wind control over cloud formation. These results suggest that climate change impacts on small-mountain TMCFs may not be limited to the dry season; changes in regional-scale patterns that cause drought periods during the wet seasons will likely have higher cloud base, and thus may threaten cloud water support to sensitive mountain ecosystems. Strong El Niño's can cause drought in Puerto Rico; we will report results from the summer of 2015 that examined El Niño effects on cloud base altitudes. Looking at regionally collected airport cloud data, we see indicators that diurnal urban effects may already be raising the low cloud bases.

Tharsis Limb Cloud

NASA Technical Reports Server (NTRS)

2005-01-01

[figure removed for brevity, see original site] Annotated image of Tharsis Limb Cloud

7 September 2005 This composite of red and blue Mars Global Surveyor (MGS) Mars Orbiter Camera (MOC) daily global images acquired on 6 July 2005 shows an isolated water ice cloud extending more than 30 kilometers (more than 18 miles) above the martian surface. Clouds such as this are common in late spring over the terrain located southwest of the Arsia Mons volcano. Arsia Mons is the dark, oval feature near the limb, just to the left of the 'T' in the 'Tharsis Montes' label. The dark, nearly circular feature above the 'S' in 'Tharsis' is the volcano, Pavonis Mons, and the other dark circular feature, above and to the right of 's' in 'Montes,' is Ascraeus Mons. Illumination is from the left/lower left.

Season: Northern Autumn/Southern Spring

Automated detection of cloud and cloud-shadow in single-date Landsat imagery using neural networks and spatial post-processing

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

Hughes, Michael J.; Hayes, Daniel J

2014-01-01

Use of Landsat data to answer ecological questions is contingent on the effective removal of cloud and cloud shadow from satellite images. We develop a novel algorithm to identify and classify clouds and cloud shadow, \\textsc{sparcs}: Spacial Procedures for Automated Removal of Cloud and Shadow. The method uses neural networks to determine cloud, cloud-shadow, water, snow/ice, and clear-sky membership of each pixel in a Landsat scene, and then applies a set of procedures to enforce spatial rules. In a comparison to FMask, a high-quality cloud and cloud-shadow classification algorithm currently available, \\textsc{sparcs} performs favorably, with similar omission errors for cloudsmore » (0.8% and 0.9%, respectively), substantially lower omission error for cloud-shadow (8.3% and 1.1%), and fewer errors of commission (7.8% and 5.0%). Additionally, textsc{sparcs} provides a measure of uncertainty in its classification that can be exploited by other processes that use the cloud and cloud-shadow detection. To illustrate this, we present an application that constructs obstruction-free composites of images acquired on different dates in support of algorithms detecting vegetation change.« less

Indirect and semi-direct aerosol campaign: The impact of Arctic aerosols on clouds

DOE PAGES

McFarquhar, Greg M.; Ghan, Steven; Verlinde, Johannes; ...

2011-02-01

A comprehensive dataset of microphysical and radiative properties of aerosols and clouds in the boundary layer in the vicinity of Barrow, Alaska, was collected in April 2008 during the Indirect and Semi-Direct Aerosol Campaign (ISDAC). ISDAC's primary aim was to examine the effects of aerosols, including those generated by Asian wildfires, on clouds that contain both liquid and ice. ISDAC utilized the Atmospheric Radiation Measurement Pro- gram's permanent observational facilities at Barrow and specially deployed instruments measuring aerosol, ice fog, precipitation, and radiation. The National Research Council of Canada Convair-580 flew 27 sorties and collected data using an unprecedented 41more » stateof- the-art cloud and aerosol instruments for more than 100 h on 12 different days. Aerosol compositions, including fresh and processed sea salt, biomassburning particles, organics, and sulfates mixed with organics, varied between flights. Observations in a dense arctic haze on 19 April and above, within, and below the single-layer stratocumulus on 8 and 26 April are enabling a process-oriented understanding of how aerosols affect arctic clouds. Inhomogeneities in reflectivity, a close coupling of upward and downward Doppler motion, and a nearly constant ice profile in the single-layer stratocumulus suggests that vertical mixing is responsible for its longevity observed during ISDAC. Data acquired in cirrus on flights between Barrow and Fairbanks, Alaska, are improving the understanding of the performance of cloud probes in ice. Furthermore, ISDAC data will improve the representation of cloud and aerosol processes in models covering a variety of spatial and temporal scales, and determine the extent to which surface measurements can provide retrievals of aerosols, clouds, precipitation, and radiative heating.« less

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

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.

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

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.

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

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.

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;

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

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 Computing E-Communication Services in the University Environment

ERIC Educational Resources Information Center

Babin, Ron; Halilovic, Branka

2017-01-01

The use of cloud computing services has grown dramatically in post-secondary institutions in the last decade. In particular, universities have been attracted to the low-cost and flexibility of acquiring cloud software services from Google, Microsoft and others, to implement e-mail, calendar and document management and other basic office software.…

Remote sensing of smoke, clouds, and fire using AVIRIS data

NASA Technical Reports Server (NTRS)

Gao, Bo-Cai; Kaufman, Yorman J.; Green, Robert O.

1993-01-01

Clouds remain the greatest element of uncertainty in predicting global climate change. During deforestation and biomass burning processes, a variety of atmospheric gases, including CO2 and SO2, and smoke particles are released into the atmosphere. The smoke particles can have important effects on the formation of clouds because of the increased concentration of cloud condensation nuclei. They can also affect cloud albedo through changes in cloud microphysical properties. Recently, great interest has arisen in understanding the interaction between smoke particles and clouds. We describe our studies of smoke, clouds, and fire using the high spatial and spectral resolution data acquired with the NASA/JPL Airborne Visible/Infrared Imaging Spectrometer (AVIRIS).

Looking Down Through the Clouds – Optical Attenuation through Real-Time Clouds

NASA Astrophysics Data System (ADS)

Burley, J.; Lazarewicz, A.; Dean, D.; Heath, N.

Detecting and identifying nuclear explosions in the atmosphere and on the surface of the Earth is critical for the Air Force Technical Applications Center (AFTAC) treaty monitoring mission. Optical signals, from surface or atmospheric nuclear explosions detected by satellite sensors, are attenuated by the atmosphere and clouds. Clouds present a particularly complex challenge as they cover up to seventy percent of the earth's surface. Moreover, their highly variable and diverse nature requires physics-based modeling. Determining the attenuation for each optical ray-path is uniquely dependent on the source geolocation, the specific optical transmission characteristics along that ray path, and sensor detection capabilities. This research details a collaborative AFTAC and AFIT effort to fuse worldwide weather data, from a variety of sources, to provide near-real-time profiles of atmospheric and cloud conditions and the resulting radiative transfer analysis for virtually any wavelength(s) of interest from source to satellite. AFIT has developed a means to model global clouds using the U.S. Air Force’s World Wide Merged Cloud Analysis (WWMCA) cloud data in a new toolset that enables radiance calculations through clouds from UV to RF wavelengths.

Intensification of convective extremes driven by cloud-cloud interaction

NASA Astrophysics Data System (ADS)

Moseley, Christopher; Hohenegger, Cathy; Berg, Peter; Haerter, Jan O.

2016-10-01

In a changing climate, a key role may be played by the response of convective-type cloud and precipitation to temperature changes. Yet, it is unclear if convective precipitation intensities will increase mainly due to thermodynamic or dynamical processes. Here we perform large eddy simulations of convection by imposing a realistic diurnal cycle of surface temperature. We find convective events to gradually self-organize into larger cloud clusters and those events occurring late in the day to produce the highest precipitation intensities. Tracking rain cells throughout their life cycles, we show that events which result from collisions respond strongly to changes in boundary conditions, such as temperature changes. Conversely, events not resulting from collisions remain largely unaffected by the boundary conditions. Increased surface temperature indeed leads to more interaction between events and stronger precipitation extremes. However, comparable intensification occurs when leaving temperature unchanged but simply granting more time for self-organization. These findings imply that the convective field as a whole acquires a memory of past precipitation and inter-cloud dynamics, driving extremes. For global climate model projections, our results suggest that the interaction between convective clouds must be incorporated to simulate convective extremes and the diurnal cycle more realistically.

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

Automatic Cloud Detection from Multi-Temporal Satellite Images: Towards the Use of PLÉIADES Time Series

NASA Astrophysics Data System (ADS)

Champion, N.

2012-08-01

Contrary to aerial images, satellite images are often affected by the presence of clouds. Identifying and removing these clouds is one of the primary steps to perform when processing satellite images, as they may alter subsequent procedures such as atmospheric corrections, DSM production or land cover classification. The main goal of this paper is to present the cloud detection approach, developed at the French Mapping agency. Our approach is based on the availability of multi-temporal satellite images (i.e. time series that generally contain between 5 and 10 images) and is based on a region-growing procedure. Seeds (corresponding to clouds) are firstly extracted through a pixel-to-pixel comparison between the images contained in time series (the presence of a cloud is here assumed to be related to a high variation of reflectance between two images). Clouds are then delineated finely using a dedicated region-growing algorithm. The method, originally designed for panchromatic SPOT5-HRS images, is tested in this paper using time series with 9 multi-temporal satellite images. Our preliminary experiments show the good performances of our method. In a near future, the method will be applied to Pléiades images, acquired during the in-flight commissioning phase of the satellite (launched at the end of 2011). In that context, this is a particular goal of this paper to show to which extent and in which way our method can be adapted to this kind of imagery.

Life in the clouds: are tropical montane cloud forests responding to changes in climate?

PubMed

Hu, Jia; Riveros-Iregui, Diego A

2016-04-01

The humid tropics represent only one example of the many places worldwide where anthropogenic disturbance and climate change are quickly affecting the feedbacks between water and trees. In this article, we address the need for a more long-term perspective on the effects of climate change on tropical montane cloud forests (TMCF) in order to fully assess the combined vulnerability and long-term response of tropical trees to changes in precipitation regimes, including cloud immersion. We first review the ecophysiological benefits that cloud water interception offers to trees in TMCF and then examine current climatological evidence that suggests changes in cloud base height and impending changes in cloud immersion for TMCF. Finally, we propose an experimental approach to examine the long-term dynamics of tropical trees in TMCF in response to environmental conditions on decade-to-century time scales. This information is important to assess the vulnerability and long-term response of TMCF to changes in cloud cover and fog frequency and duration.

Limits to Cloud Susceptibility

NASA Technical Reports Server (NTRS)

Coakley, James A., Jr.

2002-01-01

1-kilometer AVHRR observations of ship tracks in low-level clouds off the west coast of the U S. were used to determine limits for the degree to which clouds might be altered by increases in anthropogenic aerosols. Hundreds of tracks were analyzed to determine whether the changes in droplet radii, visible optical depths, and cloud top altitudes that result from the influx of particles from underlying ships were consistent with expectations based on simple models for the indirect effect of aerosols. The models predict substantial increases in sunlight reflected by polluted clouds due to the increases in droplet numbers and cloud liquid water that result from the elevated particle concentrations. Contrary to the model predictions, the analysis of ship tracks revealed a 15-20% reduction in liquid water for the polluted clouds. Studies performed with a large-eddy cloud simulation model suggested that the shortfall in cloud liquid water found in the satellite observations might be attributed to the restriction that the 1-kilometer pixels be completely covered by either polluted or unpolluted cloud. The simulation model revealed that a substantial fraction of the indirect effect is caused by a horizontal redistribution of cloud water in the polluted clouds. Cloud-free gaps in polluted clouds fill in with cloud water while the cloud-free gaps in the surrounding unpolluted clouds remain cloud-free. By limiting the analysis to only overcast pixels, the current study failed to account for the gap-filling predicted by the simulation model. This finding and an analysis of the spatial variability of marine stratus suggest new ways to analyze ship tracks to determine the limit to which particle pollution will alter the amount of sunlight reflected by clouds.

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.

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 ...

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.

Study of the transport parameters of cloud lightning plasmas

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

Chang, Z. S.; Yuan, P.; Zhao, N.

2010-11-15

Three spectra of cloud lightning have been acquired in Tibet (China) using a slitless grating spectrograph. The electrical conductivity, the electron thermal conductivity, and the electron thermal diffusivity of the cloud lightning, for the first time, are calculated by applying the transport theory of air plasma. In addition, we investigate the change behaviors of parameters (the temperature, the electron density, the electrical conductivity, the electron thermal conductivity, and the electron thermal diffusivity) in one of the cloud lightning channels. The result shows that these parameters decrease slightly along developing direction of the cloud lightning channel. Moreover, they represent similar suddenmore » change behavior in tortuous positions and the branch of the cloud lightning channel.« 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

A prototype for automation of land-cover products from Landsat Surface Reflectance Data Records

NASA Astrophysics Data System (ADS)

Rover, J.; Goldhaber, M. B.; Steinwand, D.; Nelson, K.; Coan, M.; Wylie, B. K.; Dahal, D.; Wika, S.; Quenzer, R.

2014-12-01

Landsat data records of surface reflectance provide a three-decade history of land surface processes. Due to the vast number of these archived records, development of innovative approaches for automated data mining and information retrieval were necessary. Recently, we created a prototype utilizing open source software libraries for automatically generating annual Anderson Level 1 land cover maps and information products from data acquired by the Landsat Mission for the years 1984 to 2013. The automated prototype was applied to two target areas in northwestern and east-central North Dakota, USA. The approach required the National Land Cover Database (NLCD) and two user-input target acquisition year-days. The Landsat archive was mined for scenes acquired within a 100-day window surrounding these target dates, and then cloud-free pixels where chosen closest to the specified target acquisition dates. The selected pixels were then composited before completing an unsupervised classification using the NLCD. Pixels unchanged in pairs of the NLCD were used for training decision tree models in an iterative process refined with model confidence measures. The decision tree models were applied to the Landsat composites to generate a yearly land cover map and related information products. Results for the target areas captured changes associated with the recent expansion of oil shale production and agriculture driven by economics and policy, such as the increase in biofuel production and reduction in Conservation Reserve Program. Changes in agriculture, grasslands, and surface water reflect the local hydrological conditions that occurred during the 29-year span. Future enhancements considered for this prototype include a web-based client, ancillary spatial datasets, trends and clustering algorithms, and the forecasting of future land cover.

Cloud Forecasting and 3-D Radiative Transfer Model Validation using Citizen-Sourced Imagery

NASA Astrophysics Data System (ADS)

Gasiewski, A. J.; Heymsfield, A.; Newman Frey, K.; Davis, R.; Rapp, J.; Bansemer, A.; Coon, T.; Folsom, R.; Pfeufer, N.; Kalloor, J.

2017-12-01

Cloud radiative feedback mechanisms are one of the largest sources of uncertainty in global climate models. Variations in local 3D cloud structure impact the interpretation of NASA CERES and MODIS data for top-of-atmosphere radiation studies over clouds. Much of this uncertainty results from lack of knowledge of cloud vertical and horizontal structure. Surface-based data on 3-D cloud structure from a multi-sensor array of low-latency ground-based cameras can be used to intercompare radiative transfer models based on MODIS and other satellite data with CERES data to improve the 3-D cloud parameterizations. Closely related, forecasting of solar insolation and associated cloud cover on time scales out to 1 hour and with spatial resolution of 100 meters is valuable for stabilizing power grids with high solar photovoltaic penetrations. Data for cloud-advection based solar insolation forecasting with requisite spatial resolution and latency needed to predict high ramp rate events obtained from a bottom-up perspective is strongly correlated with cloud-induced fluctuations. The development of grid management practices for improved integration of renewable solar energy thus also benefits from a multi-sensor camera array. The data needs for both 3D cloud radiation modelling and solar forecasting are being addressed using a network of low-cost upward-looking visible light CCD sky cameras positioned at 2 km spacing over an area of 30-60 km in size acquiring imagery on 30 second intervals. Such cameras can be manufactured in quantity and deployed by citizen volunteers at a marginal cost of 200-400 and operated unattended using existing communications infrastructure. A trial phase to understand the potential utility of up-looking multi-sensor visible imagery is underway within this NASA Citizen Science project. To develop the initial data sets necessary to optimally design a multi-sensor cloud camera array a team of 100 citizen scientists using self-owned PDA cameras is being

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 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

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.

Four years of global cirrus cloud statistics using HIRS

NASA Technical Reports Server (NTRS)

Wylie, Donald P.; Menzel, W. Paul; Woolf, Harold M.; Strabala, Kathleen I.

1994-01-01

Trends in global upper-tropospheric transmissive cirrus cloud cover are beginning to emerge from a four-year cloud climatology using NOAA polar-orbiting High-Resolution Infrared Radiation Sounder (HIRS) multispectral data. Cloud occurrence, height, and effective emissivity are determined with the CO2 slicing technique on the four years of data (June 1989-May 1993). There is a global preponderance of transmissive high clouds, 42% on the average; about three-fourths of these are above 500 hPa and presumed to be cirrus. In the Inter-tropical Convergence Zone (ITCZ), a high frequency of cirrus (greater than 50%) is found at all times; a modest seasonal movement tracks the sun. Large seasonal changes in cloud cover occur over the oceans in the storm belts at midlatitudes; the concentrations of these clouds migrate north and south with the seasons following the progressions of the subtropical highs (anticyclones). More cirrus is found in the summer than in the winter in each hemisphere. A significant change in cirrus cloud cover occurs in 1991, the third year of the study. Cirrus observations increase from 35% to 43% of the data, a change of eight percentage points. Other cloud forms, opaque to terrestrial radiation, decerase by nearly the same amount. Most of the increase is thinner cirrus with infrared optical depths below 0.7. The increase in cirrus happens at the same time as the 1991-92 El Nino/Southern Oscillation (ENSO) and the eruption of Mt. Pinatubo. The cirrus changes occur at the start of the ENSO and persist into 1993 in contrast to other climatic indicators that return to near pre-ENSO and volcanic levels in 1993.

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

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.

Pre-Dawn Clouds Over Mars

NASA Image and Video Library

1997-08-28

These are more wispy blue clouds from Sol 39 as seen by the Imager for Mars Pathfinder. The bright clouds near the bottom are about 30 degrees above the horizon. The clouds are believed to be at an altitude of 10 to 15 km, and are thought to be made of small water ice particles. The picture was taken about 35 minutes before sunrise. Sojourner spent 83 days of a planned seven-day mission exploring the Martian terrain, acquiring images, and taking chemical, atmospheric and other measurements. The final data transmission received from Pathfinder was at 10:23 UTC on September 27, 1997. Although mission managers tried to restore full communications during the following five months, the successful mission was terminated on March 10, 1998. http://photojournal.jpl.nasa.gov/catalog/PIA00919

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 over the equatorial eastern Pacific derived from July 1983 International Satellite Cloud Climatology Project data using a hybrid bispectral threshold method

NASA Technical Reports Server (NTRS)

Minnis, Patrick; Harrison, Edwin F.; Gibson, Gary G.

1987-01-01

A set of visible and IR data obtained with GOES from July 17-31, 1983 is analyzed using a modified version of the hybrid bispectral threshold method developed by Minnis and Harrison (1984). This methodology can be divided into a set of procedures or optional techniques to determine the proper contaminate clear-sky temperature or IR threshold. The various optional techniques are described; the options are: standard, low-temperature limit, high-reflectance limit, low-reflectance limit, coldest pixel and thermal adjustment limit, IR-only low-cloud temperature limit, IR clear-sky limit, and IR overcast limit. Variations in the cloud parameters and the characteristics and diurnal cycles of trade cumulus and stratocumulus clouds over the eastern equatorial Pacific are examined. It is noted that the new method produces substantial changes in about one third of the cloud amount retrieval; and low cloud retrievals are affected most by the new constraints.

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

Equine acquired multiple acyl-CoA dehydrogenase deficiency (MADD) in 14 horses associated with ingestion of Maple leaves (Acer pseudoplatanus) covered with European tar spot (Rhytisma acerinum).

PubMed

van der Kolk, J H; Wijnberg, I D; Westermann, C M; Dorland, L; de Sain-van der Velden, M G M; Kranenburg, L C; Duran, M; Dijkstra, J A; van der Lugt, J J; Wanders, R J A; Gruys, E

2010-01-01

This case-series describes fourteen horses suspected of equine acquired multiple acyl-CoA dehydrogenase deficiency (MADD) also known as atypical myopathy of which seven cases were confirmed biochemically with all horses having had access to leaves of the Maple tree (Acer pseudoplatanus) covered with European tar spot (Rhytisma acerinum). Assessment of organic acids, glycine conjugates, and acylcarnitines in urine was regarded as gold standard in the biochemical diagnosis of equine acquired multiple acyl-CoA dehydrogenase deficiency. Copyright © 2010 Elsevier Inc. All rights reserved.

Upper-Tropospheric Cloud Ice from IceCube

NASA Astrophysics Data System (ADS)

Wu, D. L.

2017-12-01

Cloud ice plays important roles in Earth's energy budget and cloud-precipitation processes. Knowledge of global cloud ice and its properties is critical for understanding and quantifying its roles in Earth's atmospheric system. It remains a great challenge to measure these variables accurately from space. Submillimeter (submm) wave remote sensing has capability of penetrating clouds and measuring ice mass and microphysical properties. In particular, the 883-GHz frequency is a highest spectral window in microwave frequencies that can be used to fill a sensitivity gap between thermal infrared (IR) and mm-wave sensors in current spaceborne cloud ice observations. IceCube is a cubesat spaceflight demonstration of 883-GHz radiometer technology. Its primary objective is to raise the technology readiness level (TRL) of 883-GHz cloud radiometer for future Earth science missions. By flying a commercial receiver on a 3U cubesat, IceCube is able to achieve fast-track maturation of space technology, by completing its development, integration and testing in 2.5 years. IceCube was successfully delivered to ISS in April 2017 and jettisoned from the International Space Station (ISS) in May 2017. The IceCube cloud-ice radiometer (ICIR) has been acquiring data since the jettison on a daytime-only operation. IceCube adopted a simple design without payload mechanism. It makes maximum utilization of solar power by spinning the spacecraft continuously about the Sun vector at a rate of 1.2° per second. As a result, the ICIR is operated under the limited resources (8.6 W without heater) and largely-varying (18°C-28°C) thermal environments. The spinning cubesat also allows ICIR to have periodical views between the Earth (atmosphere and clouds) and cold space (calibration), from which the first 883-GHz cloud map is obtained. The 883-GHz cloud radiance, sensitive to ice particle scattering, is proportional to cloud ice amount above 10 km. The ICIR cloud map acquired during June 20-July 2

Marine Layer Clouds off the California Coast

NASA Image and Video Library

2017-12-08

NASA image acquired September 27, 2012 On September 27, 2012, the Visible Infrared Imaging Radiometer Suite (VIIRS) on the Suomi NPP satellite captured this nighttime view of low-lying marine layer clouds along the coast of California. The image was captured by the VIIRS “day-night band,” which detects light in a range of wavelengths from green to near-infrared and uses filtering techniques to observe signals such as gas flares, auroras, wildfires, city lights, and reflected moonlight. An irregularly-shaped patch of high clouds hovers off the coast of California, and moonlight caused the high clouds to cast distinct shadows on the marine layer clouds below. VIIRS acquired the image when the Moon was in its waxing gibbous phase, meaning it was more than half-lit, but less than full. Low clouds pose serious hazards for air and ship traffic, but satellites have had difficulty detecting them in the past. To illustrate this, the second image shows the same scene in thermal infrared, the band that meteorologists generally use to monitor clouds at night. Only high clouds are visible; the low clouds do not show up at all because they are roughly the same temperature as the ground. NASA Earth Observatory image by Jesse Allen and Robert Simmon, using VIIRS Day-Night Band data from the Suomi National Polar-orbiting Partnership. Suomi NPP is the result of a partnership between NASA, the National Oceanic and Atmospheric Administration, and the Department of Defense. Caption by Adam Voiland. Instrument: Suomi NPP - VIIRS Credit: NASA Earth Observatory Click here to view all of the Earth at Night 2012 images Click here to read more about this image 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

Mapping with Small UAS: A Point Cloud Accuracy Assessment

NASA Astrophysics Data System (ADS)

Toth, Charles; Jozkow, Grzegorz; Grejner-Brzezinska, Dorota

2015-12-01

Interest in using inexpensive Unmanned Aerial System (UAS) technology for topographic mapping has recently significantly increased. Small UAS platforms equipped with consumer grade cameras can easily acquire high-resolution aerial imagery allowing for dense point cloud generation, followed by surface model creation and orthophoto production. In contrast to conventional airborne mapping systems, UAS has limited ground coverage due to low flying height and limited flying time, yet it offers an attractive alternative to high performance airborne systems, as the cost of the sensors and platform, and the flight logistics, is relatively low. In addition, UAS is better suited for small area data acquisitions and to acquire data in difficult to access areas, such as urban canyons or densely built-up environments. The main question with respect to the use of UAS is whether the inexpensive consumer sensors installed in UAS platforms can provide the geospatial data quality comparable to that provided by conventional systems. This study aims at the performance evaluation of the current practice of UAS-based topographic mapping by reviewing the practical aspects of sensor configuration, georeferencing and point cloud generation, including comparisons between sensor types and processing tools. The main objective is to provide accuracy characterization and practical information for selecting and using UAS solutions in general mapping applications. The analysis is based on statistical evaluation as well as visual examination of experimental data acquired by a Bergen octocopter with three different image sensor configurations, including a GoPro HERO3+ Black Edition, a Nikon D800 DSLR and a Velodyne HDL-32. In addition, georeferencing data of varying quality were acquired and evaluated. The optical imagery was processed by using three commercial point cloud generation tools. Comparing point clouds created by active and passive sensors by using different quality sensors, and finally

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.

Automatic Recognition of Indoor Navigation Elements from Kinect Point Clouds

NASA Astrophysics Data System (ADS)

Zeng, L.; Kang, Z.

2017-09-01

This paper realizes automatically the navigating elements defined by indoorGML data standard - door, stairway and wall. The data used is indoor 3D point cloud collected by Kinect v2 launched in 2011 through the means of ORB-SLAM. By contrast, it is cheaper and more convenient than lidar, but the point clouds also have the problem of noise, registration error and large data volume. Hence, we adopt a shape descriptor - histogram of distances between two randomly chosen points, proposed by Osada and merges with other descriptor - in conjunction with random forest classifier to recognize the navigation elements (door, stairway and wall) from Kinect point clouds. This research acquires navigation elements and their 3-d location information from each single data frame through segmentation of point clouds, boundary extraction, feature calculation and classification. Finally, this paper utilizes the acquired navigation elements and their information to generate the state data of the indoor navigation module automatically. The experimental results demonstrate a high recognition accuracy of the proposed method.

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.

SEMANTIC3D.NET: a New Large-Scale Point Cloud Classification Benchmark

NASA Astrophysics Data System (ADS)

Hackel, T.; Savinov, N.; Ladicky, L.; Wegner, J. D.; Schindler, K.; Pollefeys, M.

2017-05-01

This paper presents a new 3D point cloud classification benchmark data set with over four billion manually labelled points, meant as input for data-hungry (deep) learning methods. We also discuss first submissions to the benchmark that use deep convolutional neural networks (CNNs) as a work horse, which already show remarkable performance improvements over state-of-the-art. CNNs have become the de-facto standard for many tasks in computer vision and machine learning like semantic segmentation or object detection in images, but have no yet led to a true breakthrough for 3D point cloud labelling tasks due to lack of training data. With the massive data set presented in this paper, we aim at closing this data gap to help unleash the full potential of deep learning methods for 3D labelling tasks. Our semantic3D.net data set consists of dense point clouds acquired with static terrestrial laser scanners. It contains 8 semantic classes and covers a wide range of urban outdoor scenes: churches, streets, railroad tracks, squares, villages, soccer fields and castles. We describe our labelling interface and show that our data set provides more dense and complete point clouds with much higher overall number of labelled points compared to those already available to the research community. We further provide baseline method descriptions and comparison between methods submitted to our online system. We hope semantic3D.net will pave the way for deep learning methods in 3D point cloud labelling to learn richer, more general 3D representations, and first submissions after only a few months indicate that this might indeed be the case.

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.

Observation of Sea Ice Surface Thermal States Under Cloud Cover

NASA Technical Reports Server (NTRS)

Nghiem, S. V.; Perovich, D. K.; Gow, A. J.; Kwok, R.; Barber, D. G.; Comiso, J. C.; Zukor, Dorothy J. (Technical Monitor)

2001-01-01

Clouds interfere with the distribution of short-wave and long-wave radiations over sea ice, and thereby strongly affect the surface energy balance in polar regions. To evaluate the overall effects of clouds on climatic feedback processes in the atmosphere-ice-ocean system, the challenge is to observe sea ice surface thermal states under both clear sky and cloudy conditions. From laboratory experiments, we show that C-band radar (transparent to clouds) backscatter is very sensitive to the surface temperature of first-year sea ice. The effect of sea ice surface temperature on the magnitude of backscatter change depends on the thermal regimes of sea ice thermodynamic states. For the temperature range above the mirabilite (Na2SO4.10H20) crystallization point (-8.2 C), C-band data show sea ice backscatter changes by 8-10 dB for incident angles from 20 to 35 deg at both horizontal and vertical polarizations. For temperatures below the mirabilite point but above the crystallization point of MgCl2.8H2O (-18.0 C), relatively strong backwater changes between 4-6 dB are observed. These backscatter changes correspond to approximately 8 C change in temperature for both cases. The backscattering mechanism is related to the temperature which determines the thermodynamic distribution of brine volume in the sea ice surface layer. The backscatter is positively correlated to temperature and the process is reversible with thermodynamic variations such as diurnal insolation effects. From two different dates in May 1993 with clear and overcast conditions determined by the Advanced Very High Resolution Radiometer (AVHRR), concurrent Earth Resources Satellite 1 (ERS-1) C-band ice observed with increases in backscatter over first-year sea ice, and verified by increases in in-situ sea ice surface temperatures measured at the Collaborative-Interdisciplinary Cryosphere Experiment (C-ICE) site.

Measuring the Internal Structure and Physical Conditions in Star and Planet Forming Clouds Cores: Towards a Quantitative Description of Cloud Evolution

NASA Technical Reports Server (NTRS)

Lada, Charles J.

2004-01-01

This grant funds a research program to use infrared extinction measurements to probe the detailed structure of dark molecular cloud cores and investigate the physical conditions which give rise to star and planet formation. The goals of this program are to acquire, reduce and analyze deep infrared and molecular-line observations of a carefully selected sample of nearby dark clouds in order to determine the detailed initial conditions for star formation from quantitative measurements of the internal structure of starless cloud cores and to quantitatively investigate the evolution of such structure through the star and planet formation process.

Measuring the Internal Structure and Physical Conditions in Star and Planet Forming Clouds Core: Toward a Quantitative Description of Cloud Evolution

NASA Technical Reports Server (NTRS)

Lada, Charles J.

2005-01-01

This grant funds a research program to use infrared extinction measurements to probe the detailed structure of dark molecular cloud cores and investigate the physical conditions which give rise to star and planet formation. The goals of this program are to acquire, reduce and analyze deep infrared and molecular-line observations of a carefully selected sample of nearby dark clouds in order to internal structure of starless cloud cores and to quantitatively investigate the evolution of such structure through the star and planet formation process. During the second year of this grant, progress toward these goals is discussed.

DeepSAT's CloudCNN: A Deep Neural Network for Rapid Cloud Detection from Geostationary Satellites

NASA Astrophysics Data System (ADS)

Kalia, S.; Li, S.; Ganguly, S.; Nemani, R. R.

2017-12-01

Cloud and cloud shadow detection has important applications in weather and climate studies. It is even more crucial when we introduce geostationary satellites into the field of terrestrial remotesensing. With the challenges associated with data acquired in very high frequency (10-15 mins per scan), the ability to derive an accurate cloud/shadow mask from geostationary satellite data iscritical. The key to the success for most of the existing algorithms depends on spatially and temporally varying thresholds, which better capture local atmospheric and surface effects.However, the selection of proper threshold is difficult and may lead to erroneous results. In this work, we propose a deep neural network based approach called CloudCNN to classifycloud/shadow from Himawari-8 AHI and GOES-16 ABI multispectral data. DeepSAT's CloudCNN consists of an encoder-decoder based architecture for binary-class pixel wise segmentation. We train CloudCNN on multi-GPU Nvidia Devbox cluster, and deploy the prediction pipeline on NASA Earth Exchange (NEX) Pleiades supercomputer. We achieved an overall accuracy of 93.29% on test samples. Since, the predictions take only a few seconds to segment a full multi-spectral GOES-16 or Himawari-8 Full Disk image, the developed framework can be used for real-time cloud detection, cyclone detection, or extreme weather event predictions.

GEWEX cloud assessment: A review

NASA Astrophysics Data System (ADS)

Stubenrauch, Claudia; Rossow, William B.; Kinne, Stefan; Ackerman, Steve; Cesana, Gregory; Chepfer, Hélène; Di Girolamo, Larry; Getzewich, Brian; Guignard, Anthony; Heidinger, Andy; Maddux, Brent; Menzel, Paul; Minnis, Patrick; Pearl, Cindy; Platnick, Steven; Poulsen, Caroline; Riedi, Jérôme; Sayer, Andrew; Sun-Mack, Sunny; Walther, Andi; Winker, Dave; Zeng, Shen; Zhao, Guangyu

2013-05-01

Clouds cover about 70% of the Earth's surface and play a dominant role in the energy and water cycle of our planet. Only satellite observations provide a continuous survey of the state of the atmosphere over the entire globe and across the wide range of spatial and temporal scales that comprise weather and climate variability. Satellite cloud data records now exceed more than 25 years; however, climatologies compiled from different satellite datasets can exhibit systematic biases. Questions therefore arise as to the accuracy and limitations of the various sensors. The Global Energy and Water cycle Experiment (GEWEX) Cloud Assessment, initiated in 2005 by the GEWEX Radiation Panel, provides the first coordinated intercomparison of publicly available, global cloud products (gridded, monthly statistics) retrieved from measurements of multi-spectral imagers (some with multi-angle view and polarization capabilities), IR sounders and lidar. Cloud properties under study include cloud amount, cloud height (in terms of pressure, temperature or altitude), cloud radiative properties (optical depth or emissivity), cloud thermodynamic phase and bulk microphysical properties (effective particle size and water path). Differences in average cloud properties, especially in the amount of high-level clouds, are mostly explained by the inherent instrument measurement capability for detecting and/or identifying optically thin cirrus, especially when overlying low-level clouds. The study of long-term variations with these datasets requires consideration of many factors. The monthly, gridded database presented here facilitates further assessments, climate studies, and the evaluation of climate models.

Snow cover monitoring model and change over both time and space in pastoral area of northern China

NASA Astrophysics Data System (ADS)

Cui, Yan; Li, Suju; Wang, Ping; Zhang, Wei; Nie, Juan; Wen, Qi

2014-11-01

Snow disaster is a natural phenomenon owning to widespread snowfall for a long time and usually affect people's life, property and economic. During the whole disaster management circle, snow disaster in pastoral area of northern china which including Xinjiang, Inner Mongolia, Qinghai, Tibet has been paid more attention. Thus do a good job in snow cover monitoring then found snow disaster in time can help the people in disaster area to take effective rescue measures, which always been the central and local government great important work. Remote sensing has been used widely in snow cover monitoring for its wide range, high efficiency, less conditions, more methods and large information. NOAA/AVHRR data has been used for wide range, plenty bands information and timely acquired and act as an import data of Snow Cover Monitoring Model (SCMM). SCMM including functions list below: First after NOAA/AVHRR data has been acquired, geometric calibration, radiometric calibration and other pre-processing work has been operated. Second after band operation, four threshold conditions are used to extract snow spectrum information among water, cloud and other features in NOAA/AVHRR image. Third snow cover information has been analyzed one by one and the maximum snow cover from about twenty images in a week has been selected. Then selected image has been mosaic which covered the pastoral area of China. At last both time and space analysis has been carried out through this operational model ,such as analysis on the difference between this week and the same period of last year , this week and last week in three level regional. SCMM have been run successfully for three years, and the results have been take into account as one of the three factors which led to risk warning of snow disaster and analysis results from it always play an important role in disaster reduction and relief.

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

Forest Cover Estimation in Ireland Using Radar Remote Sensing: A Comparative Analysis of Forest Cover Assessment Methodologies.

PubMed

Devaney, John; Barrett, Brian; Barrett, Frank; Redmond, John; O Halloran, John

2015-01-01

Quantification of spatial and temporal changes in forest cover is an essential component of forest monitoring programs. Due to its cloud free capability, Synthetic Aperture Radar (SAR) is an ideal source of information on forest dynamics in countries with near-constant cloud-cover. However, few studies have investigated the use of SAR for forest cover estimation in landscapes with highly sparse and fragmented forest cover. In this study, the potential use of L-band SAR for forest cover estimation in two regions (Longford and Sligo) in Ireland is investigated and compared to forest cover estimates derived from three national (Forestry2010, Prime2, National Forest Inventory), one pan-European (Forest Map 2006) and one global forest cover (Global Forest Change) product. Two machine-learning approaches (Random Forests and Extremely Randomised Trees) are evaluated. Both Random Forests and Extremely Randomised Trees classification accuracies were high (98.1-98.5%), with differences between the two classifiers being minimal (<0.5%). Increasing levels of post classification filtering led to a decrease in estimated forest area and an increase in overall accuracy of SAR-derived forest cover maps. All forest cover products were evaluated using an independent validation dataset. For the Longford region, the highest overall accuracy was recorded with the Forestry2010 dataset (97.42%) whereas in Sligo, highest overall accuracy was obtained for the Prime2 dataset (97.43%), although accuracies of SAR-derived forest maps were comparable. Our findings indicate that spaceborne radar could aid inventories in regions with low levels of forest cover in fragmented landscapes. The reduced accuracies observed for the global and pan-continental forest cover maps in comparison to national and SAR-derived forest maps indicate that caution should be exercised when applying these datasets for national reporting.

Forest Cover Estimation in Ireland Using Radar Remote Sensing: A Comparative Analysis of Forest Cover Assessment Methodologies

PubMed Central

Devaney, John; Barrett, Brian; Barrett, Frank; Redmond, John; O`Halloran, John

2015-01-01

Quantification of spatial and temporal changes in forest cover is an essential component of forest monitoring programs. Due to its cloud free capability, Synthetic Aperture Radar (SAR) is an ideal source of information on forest dynamics in countries with near-constant cloud-cover. However, few studies have investigated the use of SAR for forest cover estimation in landscapes with highly sparse and fragmented forest cover. In this study, the potential use of L-band SAR for forest cover estimation in two regions (Longford and Sligo) in Ireland is investigated and compared to forest cover estimates derived from three national (Forestry2010, Prime2, National Forest Inventory), one pan-European (Forest Map 2006) and one global forest cover (Global Forest Change) product. Two machine-learning approaches (Random Forests and Extremely Randomised Trees) are evaluated. Both Random Forests and Extremely Randomised Trees classification accuracies were high (98.1–98.5%), with differences between the two classifiers being minimal (<0.5%). Increasing levels of post classification filtering led to a decrease in estimated forest area and an increase in overall accuracy of SAR-derived forest cover maps. All forest cover products were evaluated using an independent validation dataset. For the Longford region, the highest overall accuracy was recorded with the Forestry2010 dataset (97.42%) whereas in Sligo, highest overall accuracy was obtained for the Prime2 dataset (97.43%), although accuracies of SAR-derived forest maps were comparable. Our findings indicate that spaceborne radar could aid inventories in regions with low levels of forest cover in fragmented landscapes. The reduced accuracies observed for the global and pan-continental forest cover maps in comparison to national and SAR-derived forest maps indicate that caution should be exercised when applying these datasets for national reporting. PMID:26262681

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

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%).

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.

Roughness Estimation from Point Clouds - A Comparison of Terrestrial Laser Scanning and Image Matching by Unmanned Aerial Vehicle Acquisitions

NASA Astrophysics Data System (ADS)

Rutzinger, Martin; Bremer, Magnus; Ragg, Hansjörg

2013-04-01

Recently, terrestrial laser scanning (TLS) and matching of images acquired by unmanned arial vehicles (UAV) are operationally used for 3D geodata acquisition in Geoscience applications. However, the two systems cover different application domains in terms of acquisition conditions and data properties i.e. accuracy and line of sight. In this study we investigate the major differences between the two platforms for terrain roughness estimation. Terrain roughness is an important input for various applications such as morphometry studies, geomorphologic mapping, and natural process modeling (e.g. rockfall, avalanche, and hydraulic modeling). Data has been collected simultaneously by TLS using an Optech ILRIS3D and a rotary UAV using an octocopter from twins.nrn for a 900 m² test site located in a riverbed in Tyrol, Austria (Judenbach, Mieming). The TLS point cloud has been acquired from three scan positions. These have been registered using iterative closest point algorithm and a target-based referencing approach. For registration geometric targets (spheres) with a diameter of 20 cm were used. These targets were measured with dGPS for absolute georeferencing. The TLS point cloud has an average point density of 19,000 pts/m², which represents a point spacing of about 5 mm. 15 images where acquired by UAV in a height of 20 m using a calibrated camera with focal length of 18.3 mm. A 3D point cloud containing RGB attributes was derived using APERO/MICMAC software, by a direct georeferencing approach based on the aircraft IMU data. The point cloud is finally co-registered with the TLS data to guarantee an optimal preparation in order to perform the analysis. The UAV point cloud has an average point density of 17,500 pts/m², which represents a point spacing of 7.5 mm. After registration and georeferencing the level of detail of roughness representation in both point clouds have been compared considering elevation differences, roughness and representation of different grain

A simple model for the cloud adjacency effect and the apparent bluing of aerosols near clouds

NASA Astrophysics Data System (ADS)

Marshak, Alexander; Wen, Guoyong; Coakley, James A.; Remer, Lorraine A.; Loeb, Norman G.; Cahalan, Robert F.

2008-07-01

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 3-D 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 only addresses the cloud-clear sky radiative transfer interaction part. It 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. This assumption leads to a larger increase of AOT for shorter wavelengths, or to a "bluing" of aerosols near clouds. The assumption that contribution from molecular scattering dominates over aerosol scattering and surface reflection is justified for the case of shorter wavelengths, dark surfaces, and an aerosol layer below the cloud tops. 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.

Smart Point Cloud: Definition and Remaining Challenges

NASA Astrophysics Data System (ADS)

Poux, F.; Hallot, P.; Neuville, R.; Billen, R.

2016-10-01

Dealing with coloured point cloud acquired from terrestrial laser scanner, this paper identifies remaining challenges for a new data structure: the smart point cloud. This concept arises with the statement that massive and discretized spatial information from active remote sensing technology is often underused due to data mining limitations. The generalisation of point cloud data associated with the heterogeneity and temporality of such datasets is the main issue regarding structure, segmentation, classification, and interaction for an immediate understanding. We propose to use both point cloud properties and human knowledge through machine learning to rapidly extract pertinent information, using user-centered information (smart data) rather than raw data. A review of feature detection, machine learning frameworks and database systems indexed both for mining queries and data visualisation is studied. Based on existing approaches, we propose a new 3-block flexible framework around device expertise, analytic expertise and domain base reflexion. This contribution serves as the first step for the realisation of a comprehensive smart point cloud data structure.

Georeferencing UAS Derivatives Through Point Cloud Registration with Archived Lidar Datasets

NASA Astrophysics Data System (ADS)

Magtalas, M. S. L. Y.; Aves, J. C. L.; Blanco, A. C.

2016-10-01

Georeferencing gathered images is a common step before performing spatial analysis and other processes on acquired datasets using unmanned aerial systems (UAS). Methods of applying spatial information to aerial images or their derivatives is through onboard GPS (Global Positioning Systems) geotagging, or through tying of models through GCPs (Ground Control Points) acquired in the field. Currently, UAS (Unmanned Aerial System) derivatives are limited to meter-levels of accuracy when their generation is unaided with points of known position on the ground. The use of ground control points established using survey-grade GPS or GNSS receivers can greatly reduce model errors to centimeter levels. However, this comes with additional costs not only with instrument acquisition and survey operations, but also in actual time spent in the field. This study uses a workflow for cloud-based post-processing of UAS data in combination with already existing LiDAR data. The georeferencing of the UAV point cloud is executed using the Iterative Closest Point algorithm (ICP). It is applied through the open-source CloudCompare software (Girardeau-Montaut, 2006) on a `skeleton point cloud'. This skeleton point cloud consists of manually extracted features consistent on both LiDAR and UAV data. For this cloud, roads and buildings with minimal deviations given their differing dates of acquisition are considered consistent. Transformation parameters are computed for the skeleton cloud which could then be applied to the whole UAS dataset. In addition, a separate cloud consisting of non-vegetation features automatically derived using CANUPO classification algorithm (Brodu and Lague, 2012) was used to generate a separate set of parameters. Ground survey is done to validate the transformed cloud. An RMSE value of around 16 centimeters was found when comparing validation data to the models georeferenced using the CANUPO cloud and the manual skeleton cloud. Cloud-to-cloud distance computations of

Desktop Cloud Visualization: the new technology to remote access 3D interactive applications in the Cloud.

PubMed

Torterolo, Livia; Ruffino, Francesco

2012-01-01

In the proposed demonstration we will present DCV (Desktop Cloud Visualization): a unique technology that allows users to remote access 2D and 3D interactive applications over a standard network. This allows geographically dispersed doctors work collaboratively and to acquire anatomical or pathological images and visualize them for further investigations.

Changes in cloud and aerosol cover (1980-2006) from reflectivity time series using SeaWiFS, N7-TOMS, EP-TOMS, SBUV-2, and OMI radiance data

NASA Astrophysics Data System (ADS)

Herman, J. R.; Labow, G.; Hsu, N. C.; Larko, D.

2009-01-01

The amount of solar radiation reflected back to space or reaching the Earth's surface is primarily governed by the amount of cloud cover and, to a much lesser extent, by Rayleigh scattering, aerosols, and various absorbing gases (e.g., O3, NO2, H2O). A useful measure of the effect of cloud plus aerosol cover is given by the amount that the 331 nm Lambert Equivalent Reflectivity (LER) of a scene exceeds the surface reflectivity for snow/ice-free scenes after Rayleigh scattering has been removed. Twenty-eight years of reflectivity data are available by overlapping data from several satellites: N7 (Nimbus 7, TOMS; 331 nm) from 1979 to 1992, SBUV-2 series (Solar Backscatter Ultraviolet, NOAA; 331 nm) 1985 to 2007, EP (Earth-Probe, TOMS; 331 nm) 1997 to 2006, SW (SeaWiFS; 412 nm) 1998 to 2006, and OMI (Ozone Measuring Instrument; 331 nm) 2004-2007. Only N7 and SW have a sufficiently long data record, Sun-synchronous orbits, and are adequately calibrated for long-term reflectivity trend estimation. Reflectivity data derived from these instruments and the SBUV-2 series are compared during the overlapping years. Key issues in determining long-term reflectivity changes that have occurred during the N7 and SW operating periods are discussed. The largest reflectivity changes in the 412 nm SW LER and 331 nm EP LER are found to occur near the equator and are associated with a large El Nino-Southern Oscillation event. Most other changes that have occurred are regional, such as the apparent cloud decrease over northern Europe since 1998. The fractional occurrence (fraction of days) of high reflectivity values over Hudson Bay, Canada (snow/ice and clouds) appears to have decreased when comparing reflectivity data from 1980 to 1992 to 1997-2006, suggesting shorter duration of ice in Hudson Bay since 1980.

Changes in Cloud and Aerosol Cover (1980-2006) from Reflectivity Time Series Using SeaWiFS, N7-TOMS, EP-TOMS, SBUV-2, and OMI Radiance Data

NASA Technical Reports Server (NTRS)

Herman, J. R.; Labow, G.; Hsu, N. C.; Larko, D.

2009-01-01

The amount of solar radiation reflected back to space or reaching the Earth's surface is primarily governed by the amount of cloud cover and, to a much lesser extent, by Rayleigh scatteri ng, aerosols, and various absorbing gases (e.g., O3, NO2, H2O). A useful measure of the effect of cloud plus aerosol cover is given by the amount that the 331 run Lambert Equivalent Reflectivity (LER) ofa scene exceeds the surfuce reflectivity for snow/ice-free scenes after Rayleigh scattering has been removed. Twenty-eight years of reflectivity data are available by overlapping data from several satellites: N7 (Nimbus 7, TOMS; 331 nm) from 1979 to 1992, SBUV-2 series (Solar Backscatter Ultraviolet, NOAA; 331 nm) 1985 to 2007, EP (Earth-Probe, TOMS; 331 nm) 1997 to 2006, SW (SeaWiFS; 412 nm) 1998 to 2006, and OMI (Ozone Measuring Instrument; 331 nm) 2004-2007. Only N7 and SW have a sufficiently long data record, Sun-synchronous orbits, and are adequately calibrated for long-term reflectivity trend estimation. Reflectivity data derived from these instruments and the SBUV-2 series are compared during the overlapping years. Key issues in determining long-term reflecti vity changes that have occurred during the N7 and SW operating periods are discussed. The largest reflectivity changes in the 412 nm SW LER and 331 nm EP LER are found to occur near the equator and are associated with a large EI Nino-Southern Oscillation event. Most other changes that have occurred are regional, such as the apparent cloud decrease over northern Europe since 1998. The fractional occurrence (fraction of days) of high reflectivity values over Hudson Bay, Canada (snow/ice and clouds) appears to have decreased when comparing reflectivity data from 1980 to 1992 to 1997-2006, suggesting shorter duration of ice in Hudson Bay since 1980.

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

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.

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

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.

Integrating Cloud-Computing-Specific Model into Aircraft Design

NASA Astrophysics Data System (ADS)

Zhimin, Tian; Qi, Lin; Guangwen, Yang

Cloud Computing is becoming increasingly relevant, as it will enable companies involved in spreading this technology to open the door to Web 3.0. In the paper, the new categories of services introduced will slowly replace many types of computational resources currently used. In this perspective, grid computing, the basic element for the large scale supply of cloud services, will play a fundamental role in defining how those services will be provided. The paper tries to integrate cloud computing specific model into aircraft design. This work has acquired good results in sharing licenses of large scale and expensive software, such as CFD (Computational Fluid Dynamics), UG, CATIA, and so on.

Hole punch clouds over the Bahamas

NASA Image and Video Library

2017-12-08

In elementary school, students learn that water freezes at 0 degrees Celsius (32 degrees Fahrenheit). That is true most of the time, but there are exceptions to the rule. For instance, water with very few impurities (such as dust or pollution particles, fungal spores, bacteria) can be chilled to much cooler temperatures and still remain liquid—a process known as supercooling. Supercooling may sound exotic, but it occurs pretty routinely in Earth’s atmosphere. Altocumulus clouds, a common type of mid-altitude cloud, are mostly composed of water droplets supercooled to a temperature of about -15 degrees C. Altocumulus clouds with supercooled tops cover about 8 percent of Earth’s surface at any given time. Supercooled water droplets play a key role in the formation of hole-punch and canal clouds, the distinctive clouds shown in these satellite images. Hole-punch clouds usually appear as circular gaps in decks of altocumulus clouds; canal clouds look similar but the gaps are longer and thinner. This true-color image shows hole-punch and canal clouds off the coast of Florida, as observed on December 12, 2014, by the Moderate Resolution Imaging Spectroradiometer (MODIS) on NASA’s Terra satellite. Both types of cloud form when aircraft fly through cloud decks rich with supercooled water droplets and produce aerodynamic contrails. Air expands and cools as it moves around the wings and past the propeller, a process known as adiabatic cooling. Air temperatures over jet wings often cool by as much as 20 degrees Celsius, pushing supercooled water droplets to the point of freezing. As ice crystals form, they absorb nearby water droplets. Since ice crystals are relatively heavy, they tend to sink. This triggers tiny bursts of snow or rain that leave gaps in the cloud cover. Whether a cloud formation becomes a hole-punch or canal depends on the thickness of the cloud layer, the air temperature, and the degree of horizontal wind shear. Both descending and ascending

Robust relations between CCN and the vertical evolution of cloud drop size distribution in deep convective clouds

NASA Astrophysics Data System (ADS)

Freud, E.; Rosenfeld, D.; Andreae, M. O.; Costa, A. A.; Artaxo, P.

2008-03-01

In-situ measurements in convective clouds (up to the freezing level) over the Amazon basin show that smoke from deforestation fires prevents clouds from precipitating until they acquire a vertical development of at least 4 km, compared to only 1-2 km in clean clouds. The average cloud depth required for the onset of warm rain increased by ~350 m for each additional 100 cloud condensation nuclei per cm3 at a super-saturation of 0.5% (CCN0.5%). In polluted clouds, the diameter of modal liquid water content grows much slower with cloud depth (at least by a factor of ~2), due to the large number of droplets that compete for available water and to the suppressed coalescence processes. Contrary to what other studies have suggested, we did not observe this effect to reach saturation at 3000 or more accumulation mode particles per cm3. The CCN0.5% concentration was found to be a very good predictor for the cloud depth required for the onset of warm precipitation and other microphysical factors, leaving only a secondary role for the updraft velocities in determining the cloud drop size distributions. The effective radius of the cloud droplets (re) was found to be a quite robust parameter for a given environment and cloud depth, showing only a small effect of partial droplet evaporation from the cloud's mixing with its drier environment. This supports one of the basic assumptions of satellite analysis of cloud microphysical processes: the ability to look at different cloud top heights in the same region and regard their re as if they had been measured inside one well developed cloud. The dependence of re on the adiabatic fraction decreased higher in the clouds, especially for cleaner conditions, and disappeared at re≥~10 μm. We propose that droplet coalescence, which is at its peak when warm rain is formed in the cloud at re=~10 μm, continues to be significant during the cloud's mixing with the entrained air, cancelling out the decrease in re due to evaporation.

Robust relations between CCN and the vertical evolution of cloud drop size distribution in deep convective clouds

NASA Astrophysics Data System (ADS)

Freud, E.; Rosenfeld, D.; Andreae, M. O.; Costa, A. A.; Artaxo, P.

2005-10-01

In-situ measurements in convective clouds (up to the freezing level) over the Amazon basin show that smoke from deforestation fires prevents clouds from precipitating until they acquire a vertical development of at least 4 km, compared to only 1-2 km in clean clouds. The average cloud depth required for the onset of warm rain increased by ~350 m for each additional 100 cloud condensation nuclei per cm3 at a super-saturation of 0.5% (CCN0.5%). In polluted clouds, the diameter of modal liquid water content grows much slower with cloud depth (at least by a factor of ~2), due to the large number of droplets that compete for available water and to the suppressed coalescence processes. Contrary to what other studies have suggested, we did not observe this effect to reach saturation at 3000 or more accumulation mode particles per cm3. The CCN0.5% concentration was found to be a very good predictor for the cloud depth required for the onset of warm precipitation and other microphysical factors, leaving only a secondary role for the updraft velocities in determining the cloud drop size distributions. The effective radius of the cloud droplets (re) was found to be a quite robust parameter for a given environment and cloud depth, showing only a small effect of partial droplet evaporation from the cloud's mixing with its drier environment. This supports one of the basic assumptions of satellite analysis of cloud microphysical processes: the ability to look at different cloud top heights in the same region and regard their re as if they had been measured inside one well developed cloud. The dependence of re on the adiabatic fraction decreased higher in the clouds, especially for cleaner conditions, and disappeared at re≥~10 µm. We propose that droplet coalescence, which is at its peak when warm rain is formed in the cloud at re~10 µm, continues to be significant during the cloud's mixing with the entrained air, canceling out the decrease in re due to evaporation.

Liquid water content variation with altitude in clouds over Europe

NASA Astrophysics Data System (ADS)

Andreea, Boscornea; Sabina, Stefan

2013-04-01

Cloud water content is one of the most fundamental measurements in cloud physics. Knowledge of the vertical variability of cloud microphysical characteristics is important for a variety of reasons. The profile of liquid water content (LWC) partially governs the radiative transfer for cloudy atmospheres, LWC profiles improves our understanding of processes acting to form and maintain cloud systems and may lead to improvements in the representation of clouds in numerical models. Presently, in situ airborne measurements provide the most accurate information about cloud microphysical characteristics. This information can be used for verification of both numerical models and cloud remote sensing techniques. The aim of this paper was to analyze the liquid water content (LWC) measurements in clouds, in time of the aircraft flights. The aircraft and its platform ATMOSLAB - Airborne Laboratory for Environmental Atmospheric Research is property of the National Institute for Aerospace Research "Elie Carafoli" (INCAS), Bucharest, Romania. The airborne laboratory equipped for special research missions is based on a Hawker Beechcraft - King Air C90 GTx aircraft and is equipped with a sensors system CAPS - Cloud, Aerosol and Precipitation Spectrometer (30 bins, 0.51-50 m). The processed and analyzed measurements are acquired during 4 flights from Romania (Bucharest, 44°25'57″N 26°06'14″E) to Germany (Berlin 52°30'2″N 13°23'56″E) above the same region of Europe. The flight path was starting from Bucharest to the western part of Romania above Hungary, Austria at a cruse altitude between 6000-8500 m, and after 5 hours reaching Berlin. In total we acquired data during approximately 20 flight hours and we presented the vertical and horizontal LWC variations for different cloud types. The LWC values are similar for each type of cloud to values from literature. The vertical LWC profiles in the atmosphere measured during takeoff and landing of the aircraft have shown their

Aerosol-Cloud-Precipitation Interactions over Indo-Gangetic Basin

NASA Technical Reports Server (NTRS)

Tsay, S.-C.; Lau, K. .; Holben, B. N.; Hsu, N. C.; Bhartia, P. K.

2005-01-01

About 60% of world population reside in Asia, in term of which sheer population density presents a major environmental stress. Economic expansion in this region is, in fact, accompanied by increases in bio-fuel burning, industrial pollution, and land cover and land use changes. With a growth rate of approx. 8%/yr for Indian economy, more than 600 million people from Lahore, Pakistan to Calcutta, India over the Indo-Gangetic Basin have particularly witnessed increased frequencies of floods and droughts as well as a dramatic increase in atmospheric loading of aerosols (i.e., anthropogenic and natural aerosol) in recent decades. This regional change (e.g., aerosol, cloud, precipitation, etc.) will constitute a vital part of the global change in the 21st century. Better understanding of the impacts of aerosols in affecting monsoon climate and water cycles is crucial in providing the physical basis to improve monsoon climate prediction and for disaster mitigation. Based on climate model simulations, absorbing aerosols (dust and black carbon) play a critical role in affecting interannual and intraseasonal variability of the Indian monsoon. An initiative on the integrated (aerosols, clouds, and precipitation) measurements approach over the Indo-Gangetic Basin will be discussed. An array of ground-based (e.g., AERONET, MPLNET, SMART-COMMIT, etc.) and satellite (e.g., Terra, A-Train, etc.) sensors will be utilized to acquire aerosol characteristics, sources/sinks, and transport processes during the pre-monsoon (April-May, aerosol forcing) season, and to obtain cloud and precipitation properties during the monsoon (May-June, water cycle response) season. Close collaboration with other international programs, such as ABC, CLIVAR, GEWEX, and CEOP in the region is anticipated.

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.

NH4SH and cloud cover in the atmospheres of the giant planets

NASA Astrophysics Data System (ADS)

Ibragimov, K. Iu.; Solodovnik, A. A.

1991-02-01

The probability of the formation of NH4SH and (NH4)2S is examined on the basis of the Le Chatelier principle. It is shown that it is very doubtful if NH4SH can be created in the atmospheres of the giant planets in quantities sufficient for cloud formation. Thus (NH4)2S is considered as a more likely candidate for cloud formation in the atmospheres of these planets, inasmuch as the conditions for its production there are more favorable.

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.

Terrestrial laser scanning point clouds time series for the monitoring of slope movements: displacement measurement using image correlation and 3D feature tracking

NASA Astrophysics Data System (ADS)

Bornemann, Pierrick; Jean-Philippe, Malet; André, Stumpf; Anne, Puissant; Julien, Travelletti

2016-04-01

Dense multi-temporal point clouds acquired with terrestrial laser scanning (TLS) have proved useful for the study of structure and kinematics of slope movements. Most of the existing deformation analysis methods rely on the use of interpolated data. Approaches that use multiscale image correlation provide a precise and robust estimation of the observed movements; however, for non-rigid motion patterns, these methods tend to underestimate all the components of the movement. Further, for rugged surface topography, interpolated data introduce a bias and a loss of information in some local places where the point cloud information is not sufficiently dense. Those limits can be overcome by using deformation analysis exploiting directly the original 3D point clouds assuming some hypotheses on the deformation (e.g. the classic ICP algorithm requires an initial guess by the user of the expected displacement patterns). The objective of this work is therefore to propose a deformation analysis method applied to a series of 20 3D point clouds covering the period October 2007 - October 2015 at the Super-Sauze landslide (South East French Alps). The dense point clouds have been acquired with a terrestrial long-range Optech ILRIS-3D laser scanning device from the same base station. The time series are analyzed using two approaches: 1) a method of correlation of gradient images, and 2) a method of feature tracking in the raw 3D point clouds. The estimated surface displacements are then compared with GNSS surveys on reference targets. Preliminary results tend to show that the image correlation method provides a good estimation of the displacement fields at first order, but shows limitations such as the inability to track some deformation patterns, and the use of a perspective projection that does not maintain original angles and distances in the correlated images. Results obtained with 3D point clouds comparison algorithms (C2C, ICP, M3C2) bring additional information on the

Study of cloud properties using airborne and satellite measurements

NASA Astrophysics Data System (ADS)

Boscornea, Andreea; Stefan, Sabina; Vajaiac, Sorin Nicolae

2014-08-01

The present study investigates cloud microphysics properties using aircraft and satellite measurements. Cloud properties were drawn from data acquired both from in situ measurements with state of the art airborne instrumentation and from satellite products of the MODIS06 System. The used aircraft was ATMOSLAB - Airborne Laboratory for Environmental Atmospheric Research, property of the National Institute for Aerospace Research "Elie Carafoli" (INCAS), Bucharest, Romania, which is specially equipped for this kind of research. The main tool of the airborne laboratory is a Cloud, Aerosol and Precipitation Spectrometer - CAPS (30 bins, 0.51- 50 μm). The data was recorded during two flights during the winter 2013-2014, over a flat region in the south-eastern part of Romania (between Bucharest and Constanta). The analysis of cloud particle size variations and cloud liquid water content provided by CAPS can explain cloud processes, and can also indicate the extent of aerosols effects on clouds. The results, such as cloud coverage and/or cloud types, microphysical parameters of aerosols on the one side and the cloud microphysics parameters obtained from aircraft flights on the other side, was used to illustrate the importance of microphysics cloud properties for including the radiative effects of clouds in the regional climate models.

Evaluating stratiform cloud base charge remotely

NASA Astrophysics Data System (ADS)

Harrison, R. Giles; Nicoll, Keri A.; Aplin, Karen L.

2017-06-01

Stratiform clouds acquire charge at their upper and lower horizontal boundaries due to vertical current flow in the global electric circuit. Cloud charge is expected to influence microphysical processes, but understanding is restricted by the infrequent in situ measurements available. For stratiform cloud bases below 1 km in altitude, the cloud base charge modifies the surface electric field beneath, allowing a new method of remote determination. Combining continuous cloud height data during 2015-2016 from a laser ceilometer with electric field mill data, cloud base charge is derived using a horizontal charged disk model. The median daily cloud base charge density found was -0.86 nC m-2 from 43 days' data. This is consistent with a uniformly charged region 40 m thick at the cloud base, now confirming that negative cloud base charge is a common feature of terrestrial layer clouds. This technique can also be applied to planetary atmospheres and volcanic plumes.