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.
AIRS Subpixel Cloud Characterization Using MODIS Cloud Products.
NASA Astrophysics Data System (ADS)
Li, Jun; Menzel, W. Paul; Sun, Fengying; Schmit, Timothy J.; Gurka, James
2004-08-01
The Moderate Resolution Imaging Spectroradiometer (MODIS) and the Atmospheric Infrared Sounder (AIRS) measurements from the Earth Observing System's (EOS's) Aqua satellite enable improved global monitoring of the distribution of clouds. MODIS is able to provide, at high spatial resolution (1 5 km), a cloud mask, surface and cloud types, cloud phase, cloud-top pressure (CTP), effective cloud amount (ECA), cloud particle size (CPS), and cloud optical thickness (COT). AIRS is able to provide CTP, ECA, CPS, and COT at coarser spatial resolution (13.5 km at nadir) but with much better accuracy using its high-spectral-resolution measurements. The combined MODIS AIRS system offers the opportunity for improved cloud products over those possible from either system alone. The key steps for synergistic use of imager and sounder radiance measurements are 1) collocation in space and time and 2) imager cloud amount, type, and phase determination within the sounder pixel. The MODIS and AIRS measurements from the EOS Aqua satellite provide the opportunity to study the synergistic use of advanced imager and sounder measurements. As the first step, the MODIS classification procedure is applied to identify various surface and cloud types within an AIRS footprint. Cloud-layer information (lower, midlevel, or high clouds) and phase information (water, ice, or mixed-phase clouds) within the AIRS footprint are sorted and characterized using MODIS 1-km-spatial-resolution data. The combined MODIS and AIRS data for various scenes are analyzed to study the utility of the synergistic use of high-spatial-resolution imager products and high-spectral-resolution sounder radiance measurements. There is relevance to the optimal use of data from the Advanced Baseline Imager (ABI) and Hyperspectral Environmental Suite (HES) systems, which are to fly on the Geostationary Operational Environmental Satellite (GOES)-R.
NASA Astrophysics Data System (ADS)
Li, J.; Menzel, W.; Sun, F.; Schmit, T.
2003-12-01
The Moderate-Resolution Imaging Spectroradiometer (MODIS) and Atmospheric Infrared Sounder (AIRS) measurements from the Earth Observing System's (EOS) Aqua satellite will enable global monitoring of the distribution of clouds. MODIS is able to provide at high spatial resolution (1 ~ 5km) the cloud mask, surface and cloud types, cloud phase, cloud-top pressure (CTP), effective cloud amount (ECA), cloud particle size (CPS), and cloud water path (CWP). AIRS is able to provide CTP, ECA, CPS, and CWP within the AIRS footprint with much better accuracy using its greatly enhanced hyperspectral remote sensing capability. The combined MODIS / AIRS system offers the opportunity for cloud products improved over those possible from either system alone. The algorithm developed was applied to process the AIRS longwave cloudy radiance measurements; results are compared with MODIS cloud products, as well as with the Geostationary Operational Environmental Satellite (GOES) sounder cloud products, to demonstrate the advantage of synergistic use of high spatial resolution MODIS cloud products and high spectral resolution AIRS sounder radiance measurements for optimal cloud retrieval. Data from ground-based instrumentation at the Atmospheric Radiation Measurement (ARM) Program Cloud and Radiation Test Bed (CART) in Oklahoma were used for the validation; results show that AIRS improves the MODIS cloud products in certain cases such as low-level clouds.
NASA Technical Reports Server (NTRS)
Putman, William P.
2012-01-01
Using a high-resolution non-hydrostatic version of GEOS-5 with the cubed-sphere finite-volume dynamical core, the impact of spatial and temporal resolution on cloud properties will be evaluated. There are indications from examining convective cluster development in high resolution GEOS-5 forecasts that the temporal resolution within the model may playas significant a role as horizontal resolution. Comparing modeled convective cloud clusters versus satellite observations of brightness temperature, we have found that improved. temporal resolution in GEOS-S accounts for a significant portion of the improvements in the statistical distribution of convective cloud clusters. Using satellite simulators in GEOS-S we will compare the cloud optical properties of GEOS-S at various spatial and temporal resolutions with those observed from MODIS. The potential impact of these results on tropical cyclone formation and intensity will be examined as well.
Cloud properties inferred from 8-12 micron data
NASA Technical Reports Server (NTRS)
Strabala, Kathleen I.; Ackerman, Steven A.; Menzel, W. Paul
1994-01-01
A trispectral combination of observations at 8-, 11-, and 12-micron bands is suggested for detecting cloud and cloud properties in the infrared. Atmospheric ice and water vapor absorption peak in opposite halves of the window region so that positive 8-minus-11-micron brightness temperature differences indicate cloud, while near-zero or negative differences indicate clear regions. The absorption coefficient for water increases more between 11 and 12 microns than between 8 and 11 microns, while for ice, the reverse is true. Cloud phases is determined by a scatter diagram of 8-minus-11-micron versus 11-minus-12-micron brightness temperature differences; ice cloud shows a slope greater than 1 and water cloud less than 1. The trispectral brightness temperature method was tested upon high-resolution interferometer data resulting in clear-cloud and cloud-phase delineation. Simulations using differing 8-micron bandwidths revealed no significant degradation of cloud property detection. Thus, the 8-micron bandwidth for future satellites can be selected based on the requirements of other applications, such as surface characterization studies. Application of the technique to current polar-orbiting High-Resolution Infrared Sounder (HIRS)-Advanced Very High Resolution Radiometer (AVHRR) datasets is constrained by the nonuniformity of the cloud scenes sensed within the large HIRS field of view. Analysis of MAS (MODIS Airborne Simulator) high-spatial resolution (500 m) data with all three 8-, 11-, and 12-micron bands revealed sharp delineation of differing cloud and background scenes, from which a simple automated threshold technique was developed. Cloud phase, clear-sky, and qualitative differences in cloud emissivity and cloud height were identified on a case study segment from 24 November 1991, consistent with the scene. More rigorous techniques would allow further cloud parameter clarification. The opportunities for global cloud delineation with the Moderate-Resolution Imaging Spectrometer (MODIS) appear excellent. The spectral selection, the spatial resolution, and the global coverage are all well suited for significant advances.
Cloud radiative properties and aerosol - cloud interaction
NASA Astrophysics Data System (ADS)
Viviana Vladutescu, Daniela; Gross, Barry; Li, Clement; Han, Zaw
2015-04-01
The presented research discusses different techniques for improvement of cloud properties measurements and analysis. The need for these measurements and analysis arises from the high errors noticed in existing methods that are currently used in retrieving cloud properties and implicitly cloud radiative forcing. The properties investigated are cloud fraction (cf) and cloud optical thickness (COT) measured with a suite of collocated remote sensing instruments. The novel approach makes use of a ground based "poor man's camera" to detect cloud and sky radiation in red, green, and blue with a high spatial resolution of 30 mm at 1km. The surface-based high resolution photography provides a new and interesting view of clouds. As the cloud fraction cannot be uniquely defined or measured, it depends on threshold and resolution. However as resolution decreases, cloud fraction tends to increase if the threshold is below the mean, and vice versa. Additionally cloud fractal dimension also depends on threshold. Therefore these findings raise concerns over the ability to characterize clouds by cloud fraction or fractal dimension. Our analysis indicate that Principal Component analysis may lead to a robust means of quantifying cloud contribution to radiance. The cloud images are analyzed in conjunction with a collocated CIMEL sky radiometer, Microwave Radiometer and LIDAR to determine homogeneity and heterogeneity. Additionally, MFRSR measurements are used to determine the cloud radiative properties as a validation tool to the results obtained from the other instruments and methods. The cloud properties to be further studied are aerosol- cloud interaction, cloud particle radii, and vertical homogeneity.
NASA Technical Reports Server (NTRS)
Welch, R. M.; Sengupta, S. K.; Chen, D. W.
1988-01-01
Stratocumulus, cumulus, and cirrus clouds were identified on the basis of cloud textural features which were derived from a single high-resolution Landsat MSS NIR channel using a stepwise linear discriminant analysis. It is shown that, using this method, it is possible to distinguish high cirrus clouds from low clouds with high accuracy on the basis of spatial brightness patterns. The largest probability of misclassification is associated with confusion between the stratocumulus breakup regions and the fair-weather cumulus.
The effect of spatial resolution upon cloud optical property retrievals. I - Optical thickness
NASA Technical Reports Server (NTRS)
Feind, Rand E.; Christopher, Sundar A.; Welch, Ronald M.
1992-01-01
High spectral and spatial resolution Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) imagery is used to study the effects of spatial resolution upon fair weather cumulus cloud optical thickness retrievals. As a preprocessing step, a variation of the Gao and Goetz three-band ratio technique is used to discriminate clouds from the background. The combination of the elimination of cloud shadow pixels and using the first derivative of the histogram allows for accurate cloud edge discrimination. The data are progressively degraded from 20 m to 960 m spatial resolution. The results show that retrieved cloud area increases with decreasing spatial resolution. The results also show that there is a monotonic decrease in retrieved cloud optical thickness with decreasing spatial resolution. It is also demonstrated that the use of a single, monospectral reflectance threshold is inadequate for identifying cloud pixels in fair weather cumulus scenes and presumably in any inhomogeneous cloud field. Cloud edges have a distribution of reflectance thresholds. The incorrect identification of cloud edges significantly impacts the accurate retrieval of cloud optical thickness values.
Structures observed on the spot radiance fields during the FIRE experiment
NASA Technical Reports Server (NTRS)
Seze, Genevieve; Smith, Leonard; Desbois, Michel
1990-01-01
Three Spot images taken during the FIRE experiment on stratocumulus are analyzed. From this high resolution data detailed observations of the true cloud radiance field may be made. The structure and inhomogeneity of these radiance fields hold important implications for the radiation budget, while the fine scale structure in radiance field provides information on cloud dynamics. Wieliki and Welsh, and Parker et al., have quantified the inhomogeneities of the cumulus clouds through a careful examination of the distribution of cloud (and hole) size as functions of an effective cloud diameter and radiance threshold. Cahalan (1988) has compared for different cloud types of (stratocumulus, fair weather cumulus, convective clouds in the ITCZ) the distributions of clouds (and holes) sizes, the relation between the size and the perimeter of these clouds (and holes), and examining the possibility of scale invariance. These results are extended from LANDSAT resolution (57 m and 30 m) to the Spot resolution (10 m) resolution in the case of boundary layer clouds. Particular emphasis is placed on the statistics of zones of high and low reflectivity as a function of a threshold reflectivity.
NASA Astrophysics Data System (ADS)
Bley, S.; Deneke, H.
2013-10-01
A threshold-based cloud mask for the high-resolution visible (HRV) channel (1 × 1 km2) of the Meteosat SEVIRI (Spinning Enhanced Visible and Infrared Imager) instrument is introduced and evaluated. It is based on operational EUMETSAT cloud mask for the low-resolution channels of SEVIRI (3 × 3 km2), which is used for the selection of suitable thresholds to ensure consistency with its results. The aim of using the HRV channel is to resolve small-scale cloud structures that cannot be detected by the low-resolution channels. We find that it is of advantage to apply thresholds relative to clear-sky reflectance composites, and to adapt the threshold regionally. Furthermore, the accuracy of the different spectral channels for thresholding and the suitability of the HRV channel are investigated for cloud detection. The case studies show different situations to demonstrate the behavior for various surface and cloud conditions. Overall, between 4 and 24% of cloudy low-resolution SEVIRI pixels are found to contain broken clouds in our test data set depending on considered region. Most of these broken pixels are classified as cloudy by EUMETSAT's cloud mask, which will likely result in an overestimate if the mask is used as an estimate of cloud fraction. The HRV cloud mask aims for small-scale convective sub-pixel clouds that are missed by the EUMETSAT cloud mask. The major limit of the HRV cloud mask is the minimum cloud optical thickness (COT) that can be detected. This threshold COT was found to be about 0.8 over ocean and 2 over land and is highly related to the albedo of the underlying surface.
Using High-Resolution Airborne Remote Sensing to Study Aerosol Near Clouds
NASA Technical Reports Server (NTRS)
Levy, Robert; Munchak, Leigh; Mattoo, Shana; Marshak, Alexander; Wilcox, Eric; Gao, Lan; Yorks, John; Platnick, Steven
2016-01-01
The horizontal space in between clear and cloudy air is very complex. This so-called twilight zone includes activated aerosols that are not quite clouds, thin cloud fragments that are not easily observable, and dying clouds that have not quite disappeared. This is a huge challenge for satellite remote sensing, specifically for retrieval of aerosol properties. Identifying what is cloud versus what is not cloud is critically important for attributing radiative effects and forcings to aerosols. At the same time, the radiative interactions between clouds and the surrounding media (molecules, surface and aerosols themselves) will contaminate retrieval of aerosol properties, even in clear skies. Most studies on aerosol cloud interactions are relevant to moderate resolution imagery (e.g. 500 m) from sensors such as MODIS. Since standard aerosol retrieval algorithms tend to keep a distance (e.g. 1 km) from the nearest detected cloud, it is impossible to evaluate what happens closer to the cloud. During Studies of Emissions, Atmospheric Composition, Clouds and Climate Coupling by Regional Surveys (SEAC4RS), the NASA ER-2 flew with the enhanced MODIS Airborne Simulator (eMAS), providing MODIS-like spectral observations at high (50 m) spatial resolution. We have applied MODIS-like aerosol retrieval for the eMAS data, providing new detail to characterization of aerosol near clouds. Interpretation and evaluation of these eMAS aerosol retrievals is aided by independent MODIS-like cloud retrievals, as well as profiles from the co-flying Cloud Physics Lidar (CPL). Understanding aerosolcloud retrieval at high resolution will lead to better characterization and interpretation of long-term, global products from lower resolution (e.g.MODIS) satellite retrievals.
Ultra-High Spectral Resolution Observations of Fragmentation in Dark Cloud Cores
NASA Technical Reports Server (NTRS)
Velusamy, T.; Langer, W.; Kuiper, T; Levin, S.; Olsen, E.
1993-01-01
This paper presents new evidence of the fragmentary structure of dense cores in dark clouds using the high resolution spectra of the carbon chain molecule CCS transition (J subscript N = 2 subscript 1 - 1 subscript o) at 22.344033 GHz with 0.008 km s superscript -1 resolution.
NASA Astrophysics Data System (ADS)
Shi, Cheng; Liu, Fang; Li, Ling-Ling; Hao, Hong-Xia
2014-01-01
The goal of pan-sharpening is to get an image with higher spatial resolution and better spectral information. However, the resolution of the pan-sharpened image is seriously affected by the thin clouds. For a single image, filtering algorithms are widely used to remove clouds. These kinds of methods can remove clouds effectively, but the detail lost in the cloud removal image is also serious. To solve this problem, a pan-sharpening algorithm to remove thin cloud via mask dodging and nonsampled shift-invariant shearlet transform (NSST) is proposed. For the low-resolution multispectral (LR MS) and high-resolution panchromatic images with thin clouds, a mask dodging method is used to remove clouds. For the cloud removal LR MS image, an adaptive principal component analysis transform is proposed to balance the spectral information and spatial resolution in the pan-sharpened image. Since the clouds removal process causes the detail loss problem, a weight matrix is designed to enhance the details of the cloud regions in the pan-sharpening process, but noncloud regions remain unchanged. And the details of the image are obtained by NSST. Experimental results over visible and evaluation metrics demonstrate that the proposed method can keep better spectral information and spatial resolution, especially for the images with thin clouds.
NASA Technical Reports Server (NTRS)
Shenk, W. E.; Adler, R. F.; Chesters, D.; Susskind, J.; Uccellini, L.
1984-01-01
The measurements from current and planned geosynchronous satellites provide quantitative estimates of temperature and moisture profiles, surface temperature, wind, cloud properties, and precipitation. A number of significant observation characteristics remain, they include: (1) temperature and moisture profiles in cloudy areas; (2) high vertical profile resolution; (3) definitive precipitation area mapping and precipitation rate estimates on the convective cloud scale; (4) winds from low level cloud motions at night; (5) the determination of convective cloud structure; and (6) high resolution surface temperature determination. Four major new observing capabilities are proposed to overcome these deficiencies: a microwave sounder/imager, a high resolution visible and infrared imager, a high spectral resolution infrared sounder, and a total ozone mapper. It is suggested that the four sensors are flown together and used to support major mesoscale and short range forecasting field experiments.
MISR Level 2 TOA/Cloud Classifier parameters (MIL2TCCL_V2)
NASA Technical Reports Server (NTRS)
Diner, David J. (Principal Investigator)
The TOA/Cloud Classifiers contain the Angular Signature Cloud Mask (ASCM), a scene classifier calculated using support vector machine technology (SVM) both of which are on a 1.1 km grid, and cloud fractions at 17.6 km resolution that are available in different height bins (low, middle, high) and are also calculated on an angle-by-angle basis. [Location=GLOBAL] [Temporal_Coverage: Start_Date=2000-02-24; Stop_Date=] [Spatial_Coverage: Southernmost_Latitude=-90; Northernmost_Latitude=90; Westernmost_Longitude=-180; Easternmost_Longitude=180] [Data_Resolution: Latitude_Resolution=17.6 km; Longitude_Resolution=17.6 km; Horizontal_Resolution_Range=10 km - < 50 km or approximately .09 degree - < .5 degree; Temporal_Resolution=about 15 orbits/day; Temporal_Resolution_Range=Daily - < Weekly, Daily - < Weekly].
MISR Level 2 TOA/Cloud Classifier parameters (MIL2TCCL_V3)
NASA Technical Reports Server (NTRS)
Diner, David J. (Principal Investigator)
The TOA/Cloud Classifiers contain the Angular Signature Cloud Mask (ASCM), a scene classifier calculated using support vector machine technology (SVM) both of which are on a 1.1 km grid, and cloud fractions at 17.6 km resolution that are available in different height bins (low, middle, high) and are also calculated on an angle-by-angle basis. [Temporal_Coverage: Start_Date=2000-02-24; Stop_Date=] [Spatial_Coverage: Southernmost_Latitude=-90; Northernmost_Latitude=90; Westernmost_Longitude=-180; Easternmost_Longitude=180] [Data_Resolution: Latitude_Resolution=1.1 km; Longitude_Resolution=1.1 km; Temporal_Resolution=about 15 orbits/day].
NASA Astrophysics Data System (ADS)
Snodgrass, E. R.; di Girolamo, L.; Rauber, R.; Zhao, G.
2005-12-01
During the RICO field campaign, the EOS Terra Spacecraft and NCAR's S-POLKa radar collected coincident high-resolution visible and near-IR satellite data and dual-polarized S-band and Ka-band radar reflectivity data to understand trade wind cumuli cloud distribution and precipitation. In this paper, the comparison of the trade wind cloud field's satellite-derived cloud properties and radar-derived precipitation characteristics are presented. Specifically, these results focus on the relationship between radar reflectivity and derived rain rate to the satellite visible radiance, cloud fraction, height and thickness. Also results concerning the relationship between cloud area estimated by satellite and cloud boundary estimated by radar Bragg and Rayleigh scattering will be presented. The resolution effects between visible satellite data from the ASTER instrument at 15m ground-resolution and the S-POLKa radar data will be reviewed. The potential applications of these results to the estimation of trade wind cumuli's role in returning water to the ocean through precipitation, and to cloud and climate model parameterization will be discussed.
Clouds in ECMWF's 30 KM Resolution Global Atmospheric Forecast Model (TL639)
NASA Technical Reports Server (NTRS)
Cahalan, R. F.; Morcrette, J. J.
1999-01-01
Global models of the general circulation of the atmosphere resolve a wide range of length scales, and in particular cloud structures extend from planetary scales to the smallest scales resolvable, now down to 30 km in state-of-the-art models. Even the highest resolution models do not resolve small-scale cloud phenomena seen, for example, in Landsat and other high-resolution satellite images of clouds. Unresolved small-scale disturbances often grow into larger ones through non-linear processes that transfer energy upscale. Understanding upscale cascades is of crucial importance in predicting current weather, and in parameterizing cloud-radiative processes that control long term climate. Several movie animations provide examples of the temporal and spatial variation of cloud fields produced in 4-day runs of the forecast model at the European Centre for Medium-Range Weather Forecasts (ECMWF) in Reading, England, at particular times and locations of simultaneous measurement field campaigns. model resolution is approximately 30 km horizontally (triangular truncation TL639) with 31 vertical levels from surface to stratosphere. Timestep of the model is about 10 minutes, but animation frames are 3 hours apart, at timesteps when the radiation is computed. The animations were prepared from an archive of several 4-day runs at the highest available model resolution, and archived at ECMWF. Cloud, wind and temperature fields in an approximately 1000 km X 1000 km box were retrieved from the archive, then approximately 60 Mb Vis5d files were prepared with the help of Graeme Kelly of ECMWF, and were compressed into MPEG files each less than 3 Mb. We discuss the interaction of clouds and radiation in the model, and compare the variability of cloud liquid as a function of scale to that seen in cloud observations made in intensive field campaigns. Comparison of high-resolution global runs to cloud-resolving models, and to lower resolution climate models is leading to better understanding of the upscale cascade and suggesting new cloud-radiation parameterizations for climate models.
Automated, per pixel Cloud Detection from High-Resolution VNIR Data
NASA Technical Reports Server (NTRS)
Varlyguin, Dmitry L.
2007-01-01
CASA is a fully automated software program for the per-pixel detection of clouds and cloud shadows from medium- (e.g., Landsat, SPOT, AWiFS) and high- (e.g., IKONOS, QuickBird, OrbView) resolution imagery without the use of thermal data. CASA is an object-based feature extraction program which utilizes a complex combination of spectral, spatial, and contextual information available in the imagery and the hierarchical self-learning logic for accurate detection of clouds and their shadows.
NASA Technical Reports Server (NTRS)
Mathews, M. L.
1983-01-01
The development of the cloud indicator index (CII) for use with METSAT's advanced very high resolution radiometer (AVHRR) is described. The CII is very effective at identification of clouds. Also, explored are different solar correction and standard techniques and the impact of these corrections have on the information content of AVHRR data.
NASA Technical Reports Server (NTRS)
Berendes, Todd; Sengupta, Sailes K.; Welch, Ron M.; Wielicki, Bruce A.; Navar, Murgesh
1992-01-01
A semiautomated methodology is developed for estimating cumulus cloud base heights on the basis of high spatial resolution Landsat MSS data, using various image-processing techniques to match cloud edges with their corresponding shadow edges. The cloud base height is then estimated by computing the separation distance between the corresponding generalized Hough transform reference points. The differences between the cloud base heights computed by these means and a manual verification technique are of the order of 100 m or less; accuracies of 50-70 m may soon be possible via EOS instruments.
NASA Astrophysics Data System (ADS)
Jayakumar, A.; Sethunadh, Jisesh; Rakhi, R.; Arulalan, T.; Mohandas, Saji; Iyengar, Gopal R.; Rajagopal, E. N.
2017-05-01
National Centre for Medium Range Weather Forecasting high-resolution regional convective-scale Unified Model with latest tropical science settings is used to evaluate vertical structure of cloud and precipitation over two prominent monsoon regions: Western Ghats (WG) and Monsoon Core Zone (MCZ). Model radar reflectivity generated using Cloud Feedback Model Intercomparison Project Observation Simulator Package along with CloudSat profiling radar reflectivity is sampled for an active synoptic situation based on a new method using Budyko's index of turbulence (BT). Regime classification based on BT-precipitation relationship is more predominant during the active monsoon period when convective-scale model's resolution increases from 4 km to 1.5 km. Model predicted precipitation and vertical distribution of hydrometeors are found to be generally in agreement with Global Precipitation Measurement products and BT-based CloudSat observation, respectively. Frequency of occurrence of radar reflectivity from model implies that the low-level clouds below freezing level is underestimated compared to the observations over both regions. In addition, high-level clouds in the model predictions are much lesser over WG than MCZ.
Cao, Ya-nan; Wei, He-li; Dai, Cong-ming; Zhang, Xue-hai
2015-05-01
A study was carried out to retrieve optical thickness and cloud top height of cirrus clouds from the Atmospheric Infrared Sounder (AIRS) high spectral resolution data in 1070~1135 cm-1 IR band using a Combined Atmospheric Radiative Transfer model (CART) by brightness temperature difference between model simulation and AIRS observation. The research is based on AIRS LIB high spectral infrared observation data combined with Moderate Resolution Imaging Spectroradiometer (MODIS) cloud product data. Brightness temperature spectra based, on the retrieved cirrus optical thickness and cloud top height were simulated and compared with brightness temperature spectra of AIRS observation in the 650~1150 cm-1 band. The cirrus optical thickness and cloud top height retrieved were compared with brightness temperature of AIRS for channel 760 (900.56 cm-1, 11. 1 µm) and cirrus reflectance of MODIS cloud product. And cloud top height retrieved was compared with cloud top height from MODIS. Results show that the brightness temperature spectra simulated were basically consistent with AIRS observation under the condition of retrieval in the 650~1150 cm-1 band. It means that CART can be used to simulate AIRS brightness temperature spectra. The retrieved cirrus parameters are consistent with brightness temperature of AIRS for channel 11. 1 µm with low brightness temperature corresponding to large cirrus optical thickness and high cloud top height. And the retrieved cirrus parameters are consistent with cirrus reflectance of MODIS cloud product with high cirrus reflectance corresponding to large cirrus optical thickness and high cloud top height. Correlation coefficient of brightness temperature between retrieved cloud top height and MODIS cloud top height was relatively high. They are mostly located in the range of 8. 5~11.5 km, and their probability distribution trend is approximately identical. CART model is feasible to retrieve cirrus properties, and the retrieval is reliable.
Development of lidar sensor for cloud-based measurements during convective conditions
NASA Astrophysics Data System (ADS)
Vishnu, R.; Bhavani Kumar, Y.; Rao, T. Narayana; Nair, Anish Kumar M.; Jayaraman, A.
2016-05-01
Atmospheric convection is a natural phenomena associated with heat transport. Convection is strong during daylight periods and rigorous in summer months. Severe ground heating associated with strong winds experienced during these periods. Tropics are considered as the source regions for strong convection. Formation of thunder storm clouds is common during this period. Location of cloud base and its associated dynamics is important to understand the influence of convection on the atmosphere. Lidars are sensitive to Mie scattering and are the suitable instruments for locating clouds in the atmosphere than instruments utilizing the radio frequency spectrum. Thunder storm clouds are composed of hydrometers and strongly scatter the laser light. Recently, a lidar technique was developed at National Atmospheric Research Laboratory (NARL), a Department of Space (DOS) unit, located at Gadanki near Tirupati. The lidar technique employs slant path operation and provides high resolution measurements on cloud base location in real-time. The laser based remote sensing technique allows measurement of atmosphere for every second at 7.5 m range resolution. The high resolution data permits assessment of updrafts at the cloud base. The lidar also provides real-time convective boundary layer height using aerosols as the tracers of atmospheric dynamics. The developed lidar sensor is planned for up-gradation with scanning facility to understand the cloud dynamics in the spatial direction. In this presentation, we present the lidar sensor technology and utilization of its technology for high resolution cloud base measurements during convective conditions over lidar site, Gadanki.
Synergistic Use of MODIS and AIRS in a Variational Retrieval of Cloud Parameters.
NASA Astrophysics Data System (ADS)
Li, Jun; Menzel, W. Paul; Zhang, Wenjian; Sun, Fengying; Schmit, Timothy J.; Gurka, James J.; Weisz, Elisabeth
2004-11-01
The Moderate Resolution Imaging Spectroradiometer (MODIS) and the Atmospheric Infrared Sounder (AIRS) measurements from the Earth Observing System's (EOS's) Aqua satellite enable global monitoring of the distribution of clouds. MODIS is able to provide a cloud mask, surface and cloud types, cloud phase, cloud-top pressure (CTP), effective cloud amount (ECA), cloud particle size, and cloud optical thickness at high spatial resolution (1 5 km). The combined MODIS AIRS system offers the opportunity for improved cloud products, better than from either system alone; this improvement is demonstrated in this paper with both simulated and real radiances. A one-dimensional variational (1DVAR) methodology is used to retrieve the CTP and ECA from AIRS longwave (650 790 cm-1 or 15.38 12.65 μm) cloudy radiance measurements (hereinafter referred to as MODIS AIRS 1DVAR). The MODIS AIRS 1DVAR cloud properties show significant improvement over the MODIS-alone cloud properties and slight improvement over AIRS-alone cloud properties in a simulation study, while MODIS AIRS 1DVAR is much more computationally efficient than the AIRS-alone 1DVAR; comparisons with radiosonde observations show that CTPs improve by 10 40 hPa for MODIS AIRS CTPs over those from MODIS alone. The 1DVAR approach is applied to process the AIRS longwave cloudy radiance measurements; results are compared with MODIS and Geostationary Operational Environmental Satellite sounder cloud products. Data from ground-based instrumentation at the Atmospheric Radiation Measurement Program Cloud and Radiation Test Bed in Oklahoma are used for validation; results show that MODIS AIRS improves the MODIS CTP, especially in low-level clouds. The operational use of a high-spatial-resolution imager, along with information from a high-spectral-resolution sounder will be possible with instruments planned for the next-generation geostationary operational instruments.
Arcmimute scale HI and IRAS observations toward high latitude cloud G86.5+59.6
NASA Technical Reports Server (NTRS)
Martin, Peter G.; Rogers, C.; Reach, W. T.; Dewdney, P. E.; Heiles, C. E.
1994-01-01
G86.5+59.6 is a degree-sized high latitude cloud originally selected for investigation by Heiles, Reach, and Koo (1988) on the basis of its appearance on the IRAS Skyflux images at 60 and 100 micrometers. Because of the interesting possibility that this is an intermediate velocity cloud colliding with HI in the Galactic plane, we have examined this region further, both at low resolution over an extended field to provide some context and at higher (arcminute) resolution within the cloud.
Global spectroscopic survey of cloud thermodynamic phase at high spatial resolution, 2005-2015
NASA Astrophysics Data System (ADS)
Thompson, David R.; Kahn, Brian H.; Green, Robert O.; Chien, Steve A.; Middleton, Elizabeth M.; Tran, Daniel Q.
2018-02-01
The distribution of ice, liquid, and mixed phase clouds is important for Earth's planetary radiation budget, impacting cloud optical properties, evolution, and solar reflectivity. Most remote orbital thermodynamic phase measurements observe kilometer scales and are insensitive to mixed phases. This under-constrains important processes with outsize radiative forcing impact, such as spatial partitioning in mixed phase clouds. To date, the fine spatial structure of cloud phase has not been measured at global scales. Imaging spectroscopy of reflected solar energy from 1.4 to 1.8 µm can address this gap: it directly measures ice and water absorption, a robust indicator of cloud top thermodynamic phase, with spatial resolution of tens to hundreds of meters. We report the first such global high spatial resolution survey based on data from 2005 to 2015 acquired by the Hyperion imaging spectrometer onboard NASA's Earth Observer 1 (EO-1) spacecraft. Seasonal and latitudinal distributions corroborate observations by the Atmospheric Infrared Sounder (AIRS). For extratropical cloud systems, just 25 % of variance observed at GCM grid scales of 100 km was related to irreducible measurement error, while 75 % was explained by spatial correlations possible at finer resolutions.
An Airborne A-Band Spectrometer for Remote Sensing Of Aerosol and Cloud Optical Properties
NASA Technical Reports Server (NTRS)
Pitts, Michael; Hostetler, Chris; Poole, Lamont; Holden, Carl; Rault, Didier
2000-01-01
Atmospheric remote sensing with the O2 A-band has a relatively long history, but most of these studies were attempting to estimate surface pressure or cloud-top pressure. Recent conceptual studies have demonstrated the potential of spaceborne high spectral resolution O2 A-band spectrometers for retrieval of aerosol and cloud optical properties. The physical rationale of this new approach is that information on the scattering properties of the atmosphere is embedded in the detailed line structure of the O2 A-band reflected radiance spectrum. The key to extracting this information is to measure the radiance spectrum at very high spectral resolution. Instrument performance requirement studies indicate that, in addition to high spectral resolution, the successful retrieval of aerosol and cloud properties from A-band radiance spectra will also require high radiometric accuracy, instrument stability, and high signal-to-noise measurements. To experimentally assess the capabilities of this promising new remote sensing application, the NASA Langley Research Center is developing an airborne high spectral resolution A-band spectrometer. The spectrometer uses a plane holographic grating with a folded Littrow geometry to achieve high spectral resolution (0.5 cm-1) and low stray light in a compact package. This instrument will be flown in a series of field campaigns beginning in 2001 to evaluate the overall feasibility of this new technique. Results from these campaigns should be particularly valuable for future spaceborne applications of A-band spectrometers for aerosol and cloud retrievals.
Unraveling the martian water cycle with high-resolution global climate simulations
NASA Astrophysics Data System (ADS)
Pottier, Alizée; Forget, François; Montmessin, Franck; Navarro, Thomas; Spiga, Aymeric; Millour, Ehouarn; Szantai, André; Madeleine, Jean-Baptiste
2017-07-01
Global climate modeling of the Mars water cycle is usually performed at relatively coarse resolution (200 - 300km), which may not be sufficient to properly represent the impact of waves, fronts, topography effects on the detailed structure of clouds and surface ice deposits. Here, we present new numerical simulations of the annual water cycle performed at a resolution of 1° × 1° (∼ 60 km in latitude). The model includes the radiative effects of clouds, whose influence on the thermal structure and atmospheric dynamics is significant, thus we also examine simulations with inactive clouds to distinguish the direct impact of resolution on circulation and winds from the indirect impact of resolution via water ice clouds. To first order, we find that the high resolution does not dramatically change the behavior of the system, and that simulations performed at ∼ 200 km resolution capture well the behavior of the simulated water cycle and Mars climate. Nevertheless, a detailed comparison between high and low resolution simulations, with reference to observations, reveal several significant changes that impact our understanding of the water cycle active today on Mars. The key northern cap edge dynamics are affected by an increase in baroclinic wave strength, with a complication of northern summer dynamics. South polar frost deposition is modified, with a westward longitudinal shift, since southern dynamics are also influenced. Baroclinic wave mode transitions are observed. New transient phenomena appear, like spiral and streak clouds, already documented in the observations. Atmospheric circulation cells in the polar region exhibit a large variability and are fine structured, with slope winds. Most modeled phenomena affected by high resolution give a picture of a more turbulent planet, inducing further variability. This is challenging for long-period climate studies.
Ship detection from high-resolution imagery based on land masking and cloud filtering
NASA Astrophysics Data System (ADS)
Jin, Tianming; Zhang, Junping
2015-12-01
High resolution satellite images play an important role in target detection application presently. This article focuses on the ship target detection from the high resolution panchromatic images. Taking advantage of geographic information such as the coastline vector data provided by NOAA Medium Resolution Coastline program, the land region is masked which is a main noise source in ship detection process. After that, the algorithm tries to deal with the cloud noise which appears frequently in the ocean satellite images, which is another reason for false alarm. Based on the analysis of cloud noise's feature in frequency domain, we introduce a windowed noise filter to get rid of the cloud noise. With the help of morphological processing algorithms adapted to target detection, we are able to acquire ship targets in fine shapes. In addition, we display the extracted information such as length and width of ship targets in a user-friendly way i.e. a KML file interpreted by Google Earth.
Towards Continuity in Cloud Properties from MODIS and Suomi-NPP Polar-Orbiting Sensors
NASA Astrophysics Data System (ADS)
Baum, B. A.; Menzel, P.; Gladkova, I.; Heidinger, A. K.
2015-12-01
The intent of this talk is to discuss the progress and issues involved with developing a continuous record of cloud properties since 1978, beginning with the High Resolution Infrared Radiation Sounder (HIRS), then MODIS on the NASA Terra/Aqua platforms, and into the future from merged CrIS and VIIRS data. The MODIS measurements include infrared (IR) window radiances at 8.5-, 11- and 12-μm and four 15-μm channels in the broad CO2 absorption band. Cloud top pressure/height and emissivity are derived using a technique in which the strength is in retrievals for mid-to-high clouds but less so for low clouds where there is little thermal contrast with the surface. Additionally, MODIS provides a decadal IR cloud phase product. The goal now is to extend this continuity from HIRS and MODIS to the S-NPP era. However, there is one large drawback to consider: VIIRS has no infrared (IR) absorption channels. The lack of at least one IR absorption channel on VIIRS degrades the accuracy of the cloud properties. There is a solution: we can construct a 13.3-μm channel from a combination of VIIRS and CrIS (Cross-track Infrared Sounder). The approach involves using the high spatial resolution VIIRS IR window channels in combination with a lower spatial resolution 13.3-μm channel derived using CrIS high spectral resolution measurements. The result is a 13.3-μm pseudo-channel at the VIIRS pixel spatial resolution of 750 m (i.e., M-band resolution). The radiometric accuracy of this approach was tested using MODIS and AIRS, and found to be within 1-2%. The availability of the pseudo-channel increases the potential for achieving continuity between MODIS and S-NPP. Since future platforms will likely continue with a pairing of an imager and hyperspectral sounder, this work lays a foundation for future cloud product continuity. We will show how the use of this new channel will impact the cloud height and phase products.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Schwartz, Stephen E.; Huang, Dong; Vladutescu, Daniela Viviana
This article describes the approach and presents initial results, for a period of several minutes in north central Oklahoma, of an examination of clouds by high resolution digital photography from the surface looking vertically upward. A commercially available camera having 35-mm equivalent focal length up to 1200 mm (nominal resolution as fine as 6 µrad, which corresponds to 9 mm for cloud height 1.5 km) is used to obtain a measure of zenith radiance of a 30 m × 30 m domain as a two-dimensional image consisting of 3456 × 3456 pixels (12 million pixels). Downwelling zenith radiance varies substantiallymore » within single images and between successive images obtained at 4-s intervals. Variation in zenith radiance found on scales down to about 10 cm is attributed to variation in cloud optical depth (COD). Attention here is directed primarily to optically thin clouds, COD less than about 2. A radiation transfer model used to relate downwelling zenith radiance to COD and to relate the counts in the camera image to zenith radiance, permits determination of COD on a pixel-by-pixel basis. COD for thin clouds determined in this way exhibits considerable variation, for example, an order of magnitude within 15 m, a factor of 2 within 4 m, and 25% (0.12 to 0.15) over 14 cm. In conclusion, this approach, which examines cloud structure on scales 3 to 5 orders of magnitude finer than satellite products, opens new avenues for examination of cloud structure and evolution.« less
Schwartz, Stephen E.; Huang, Dong; Vladutescu, Daniela Viviana
2017-03-08
This article describes the approach and presents initial results, for a period of several minutes in north central Oklahoma, of an examination of clouds by high resolution digital photography from the surface looking vertically upward. A commercially available camera having 35-mm equivalent focal length up to 1200 mm (nominal resolution as fine as 6 µrad, which corresponds to 9 mm for cloud height 1.5 km) is used to obtain a measure of zenith radiance of a 30 m × 30 m domain as a two-dimensional image consisting of 3456 × 3456 pixels (12 million pixels). Downwelling zenith radiance varies substantiallymore » within single images and between successive images obtained at 4-s intervals. Variation in zenith radiance found on scales down to about 10 cm is attributed to variation in cloud optical depth (COD). Attention here is directed primarily to optically thin clouds, COD less than about 2. A radiation transfer model used to relate downwelling zenith radiance to COD and to relate the counts in the camera image to zenith radiance, permits determination of COD on a pixel-by-pixel basis. COD for thin clouds determined in this way exhibits considerable variation, for example, an order of magnitude within 15 m, a factor of 2 within 4 m, and 25% (0.12 to 0.15) over 14 cm. In conclusion, this approach, which examines cloud structure on scales 3 to 5 orders of magnitude finer than satellite products, opens new avenues for examination of cloud structure and evolution.« less
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.
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
The GCM-Oriented CALIPSO Cloud Product (CALIPSO-GOCCP)
NASA Astrophysics Data System (ADS)
Chepfer, H.; Bony, S.; Winker, D.; Cesana, G.; Dufresne, J. L.; Minnis, P.; Stubenrauch, C. J.; Zeng, S.
2010-01-01
This article presents the GCM-Oriented Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO) Cloud Product (GOCCP) designed to evaluate the cloudiness simulated by general circulation models (GCMs). For this purpose, Cloud-Aerosol Lidar with Orthogonal Polarization L1 data are processed following the same steps as in a lidar simulator used to diagnose the model cloud cover that CALIPSO would observe from space if the satellite was flying above an atmosphere similar to that predicted by the GCM. Instantaneous profiles of the lidar scattering ratio (SR) are first computed at the highest horizontal resolution of the data but at the vertical resolution typical of current GCMs, and then cloud diagnostics are inferred from these profiles: vertical distribution of cloud fraction, horizontal distribution of low, middle, high, and total cloud fractions, instantaneous SR profiles, and SR histograms as a function of height. Results are presented for different seasons (January-March 2007-2008 and June-August 2006-2008), and their sensitivity to parameters of the lidar simulator is investigated. It is shown that the choice of the vertical resolution and of the SR threshold value used for cloud detection can modify the cloud fraction by up to 0.20, particularly in the shallow cumulus regions. The tropical marine low-level cloud fraction is larger during nighttime (by up to 0.15) than during daytime. The histograms of SR characterize the cloud types encountered in different regions. The GOCCP high-level cloud amount is similar to that from the TIROS Operational Vertical Sounder (TOVS) and the Atmospheric Infrared Sounder (AIRS). The low-level and middle-level cloud fractions are larger than those derived from passive remote sensing (International Satellite Cloud Climatology Project, Moderate-Resolution Imaging Spectroradiometer-Cloud and Earth Radiant Energy System Polarization and Directionality of Earth Reflectances, TOVS Path B, AIRS-Laboratoire de Météorologie Dynamique) because the latter only provide information on the uppermost cloud layer.
Global Single and Multiple Cloud Classification with a Fuzzy Logic Expert System
NASA Technical Reports Server (NTRS)
Welch, Ronald M.; Tovinkere, Vasanth; Titlow, James; Baum, Bryan A.
1996-01-01
An unresolved problem in remote sensing concerns the analysis of satellite imagery containing both single and multiple cloud layers. While cloud parameterizations are very important both in global climate models and in studies of the Earth's radiation budget, most cloud retrieval schemes, such as the bispectral method used by the International Satellite Cloud Climatology Project (ISCCP), have no way of determining whether overlapping cloud layers exist in any group of satellite pixels. Coakley (1983) used a spatial coherence method to determine whether a region contained more than one cloud layer. Baum et al. (1995) developed a scheme for detection and analysis of daytime multiple cloud layers using merged AVHRR (Advanced Very High Resolution Radiometer) and HIRS (High-resolution Infrared Radiometer Sounder) data collected during the First ISCCP Regional Experiment (FIRE) Cirrus 2 field campaign. Baum et al. (1995) explored the use of a cloud classification technique based on AVHRR data. This study examines the feasibility of applying the cloud classifier to global satellite imagery.
A robust threshold-based cloud mask for the HRV channel of MSG SEVIRI
NASA Astrophysics Data System (ADS)
Bley, S.; Deneke, H.
2013-03-01
A robust threshold-based cloud mask for the high-resolution visible (HRV) channel (1 × 1 km2) of the METEOSAT SEVIRI instrument is introduced and evaluated. It is based on operational EUMETSAT cloud mask for the low resolution channels of SEVIRI (3 × 3 km2), which is used for the selection of suitable thresholds to ensure consistency with its results. The aim of using the HRV channel is to resolve small-scale cloud structures which cannot be detected by the low resolution channels. We find that it is of advantage to apply thresholds relative to clear-sky reflectance composites, and to adapt the threshold regionally. Furthermore, the accuracy of the different spectral channels for thresholding and the suitability of the HRV channel are investigated for cloud detection. The case studies show different situations to demonstrate the behaviour for various surface and cloud conditions. Overall, between 4 and 24% of cloudy low-resolution SEVIRI pixels are found to contain broken clouds in our test dataset depending on considered region. Most of these broken pixels are classified as cloudy by EUMETSAT's cloud mask, which will likely result in an overestimate if the mask is used as estimate of cloud fraction.
Aerosol and Cloud Interaction Observed From High Spectral Resolution Lidar Data
NASA Technical Reports Server (NTRS)
Su, Wenying; Schuster, Gregory L.; Loeb, Norman G.; Rogers, Raymond R.; Ferrare, Richard A.; Hostetler, Chris A.; Hair, Johnathan W.; Obland, Michael D.
2008-01-01
Recent studies utilizing satellite retrievals have shown a strong correlation between aerosol optical depth (AOD) and cloud cover. However, these retrievals from passive sensors are subject to many limitations, including cloud adjacency (or 3D) effects, possible cloud contamination, uncertainty in the AOD retrieval. Some of these limitations do not exist in High Spectral Resolution Lidar (HSRL) observations; for instance, HSRL observations are not a ected by cloud adjacency effects, are less prone to cloud contamination, and offer accurate aerosol property measurements (backscatter coefficient, extinction coefficient, lidar ratio, backscatter Angstrom exponent,and aerosol optical depth) at a neospatial resolution (less than 100 m) in the vicinity of clouds. Hence, the HSRL provides an important dataset for studying aerosol and cloud interaction. In this study, we statistically analyze aircraft-based HSRL profiles according to their distance from the nearest cloud, assuring that all profile comparisons are subject to the same large-scale meteorological conditions. Our results indicate that AODs from HSRL are about 17% higher in the proximity of clouds (approximately 100 m) than far away from clouds (4.5 km), which is much smaller than the reported cloud 3D effect on AOD retrievals. The backscatter and extinction coefficients also systematically increase in the vicinity of clouds, which can be explained by aerosol swelling in the high relative humidity (RH) environment and/or aerosol growth through in cloud processing (albeit not conclusively). On the other hand, we do not observe a systematic trend in lidar ratio; we hypothesize that this is caused by the opposite effects of aerosol swelling and aerosol in-cloud processing on the lidar ratio. Finally, the observed backscatter Angstrom exponent (BAE) does not show a consistent trend because of the complicated relationship between BAE and RH. We demonstrate that BAE should not be used as a surrogate for Angstrom exponent, especially at high RH.
A Robust Multi-Scale Modeling System for the Study of Cloud and Precipitation Processes
NASA Technical Reports Server (NTRS)
Tao, Wei-Kuo
2012-01-01
During the past decade, numerical weather and global non-hydrostatic models have started using more complex microphysical schemes originally developed for high resolution cloud resolving models (CRMs) with 1-2 km or less horizontal resolutions. These microphysical schemes affect the dynamic through the release of latent heat (buoyancy loading and pressure gradient) the radiation through the cloud coverage (vertical distribution of cloud species), and surface processes through rainfall (both amount and intensity). Recently, several major improvements of ice microphysical processes (or schemes) have been developed for cloud-resolving model (Goddard Cumulus Ensemble, GCE, model) and regional scale (Weather Research and Forecast, WRF) model. These improvements include an improved 3-ICE (cloud ice, snow and graupel) scheme (Lang et al. 2010); a 4-ICE (cloud ice, snow, graupel and hail) scheme and a spectral bin microphysics scheme and two different two-moment microphysics schemes. The performance of these schemes has been evaluated by using observational data from TRMM and other major field campaigns. In this talk, we will present the high-resolution (1 km) GeE and WRF model simulations and compared the simulated model results with observation from recent field campaigns [i.e., midlatitude continental spring season (MC3E; 2010), high latitude cold-season (C3VP, 2007; GCPEx, 2012), and tropical oceanic (TWP-ICE, 2006)].
Hao, Liqing; Romakkaniemi, Sami; Kortelainen, Aki; Jaatinen, Antti; Portin, Harri; Miettinen, Pasi; Komppula, Mika; Leskinen, Ari; Virtanen, Annele; Smith, James N; Sueper, Donna; Worsnop, Douglas R; Lehtinen, Kari E J; Laaksonen, Ari
2013-03-19
This study presents results of direct observations of aerosol chemical composition in clouds. A high-resolution time-of-flight aerosol mass spectrometer was used to make measurements of cloud interstitial particles (INT) and mixed cloud interstitial and droplet residual particles (TOT). The differences between these two are the cloud droplet residuals (RES). Positive matrix factorization analysis of high-resolution mass spectral data sets and theoretical calculations were performed to yield distributions of chemical composition of the INT and RES particles. We observed that less oxidized hydrocarbon-like organic aerosols (HOA) were mainly distributed into the INT particles, whereas more oxidized low-volatile oxygenated OA (LVOOA) mainly in the RES particles. Nitrates existed as organic nitrate and in chemical form of NH(4)NO(3). Organic nitrates accounted for 45% of total nitrates in the INT particles, in clear contrast to 26% in the RES particles. Meanwhile, sulfates coexist in forms of acidic NH(4)HSO(4) and neutralized (NH(4))(2)SO(4). Acidic sulfate made up 64.8% of total sulfates in the INT particles, much higher than 10.7% in the RES particles. The results indicate a possible joint effect of activation ability of aerosol particles, cloud processing, and particle size effects on cloud formation.
NASA Technical Reports Server (NTRS)
Holz, Robert E.; Ackerman, Steve; Antonelli, Paolo; Nagle, Fred; McGill, Matthew; Hlavka, Dennis L.; Hart, William D.
2005-01-01
This paper presents a comparison of cloud-top altitude retrieval methods applied to S-HIS (Scanning High Resolution Interferometer Sounder) measurements. Included in this comparison is an improvement to the traditional CO2 Slicing method. The new method, CO2 Sorting, determines optimal channel pairs to apply the CO2 Slicing. Measurements from collocated samples of the Cloud Physics Lidar (CPL) and Modis Airborne Simulator (MAS) instruments assist in the comparison. For optically thick clouds good correlation between the S-HIS and lidar cloud-top retrievals are found. For tenuous ice clouds there can be large differences between lidar (CPL) and S-HIS retrieved cloud-tops. It is found that CO2 Sorting significantly reduces the cloud height biases for the optically thin cloud (total optical depths less then 1.0). For geometrically thick but optically thin cirrus clouds large differences between the S-HIS infrared cloud top retrievals and the CPL detected cloud top where found. For these cases the cloud height retrieved by the S-HIS cloud retrievals correlated closely with the level the CPL integrated cloud optical depth was approximately 1.0.
Analyzing and leveraging self-similarity for variable resolution atmospheric models
NASA Astrophysics Data System (ADS)
O'Brien, Travis; Collins, William
2015-04-01
Variable resolution modeling techniques are rapidly becoming a popular strategy for achieving high resolution in a global atmospheric models without the computational cost of global high resolution. However, recent studies have demonstrated a variety of resolution-dependent, and seemingly artificial, features. We argue that the scaling properties of the atmosphere are key to understanding how the statistics of an atmospheric model should change with resolution. We provide two such examples. In the first example we show that the scaling properties of the cloud number distribution define how the ratio of resolved to unresolved clouds should increase with resolution. We show that the loss of resolved clouds, in the high resolution region of variable resolution simulations, with the Community Atmosphere Model version 4 (CAM4) is an artifact of the model's treatment of condensed water (this artifact is significantly reduced in CAM5). In the second example we show that the scaling properties of the horizontal velocity field, combined with the incompressibility assumption, necessarily result in an intensification of vertical mass flux as resolution increases. We show that such an increase is present in a wide variety of models, including CAM and the regional climate models of the ENSEMBLES intercomparision. We present theoretical arguments linking this increase to the intensification of precipitation with increasing resolution.
Hayman, Matthew; Spuler, Scott
2017-11-27
We present a demonstration of a diode-laser-based high spectral resolution lidar. It is capable of performing calibrated retrievals of aerosol and cloud optical properties at a 150 m range resolution with less than 1 minute integration time over an approximate range of 12 km during day and night. This instrument operates at 780 nm, a wavelength that is well established for reliable semiconductor lasers and detectors, and was chosen because it corresponds to the D2 rubidium absorption line. A heated vapor reference cell of isotopic rubidium 87 is used as an effective and reliable aerosol signal blocking filter in the instrument. In principle, the diode-laser-based high spectral resolution lidar can be made cost competitive with elastic backscatter lidar systems, yet delivers a significant improvement in data quality through direct retrieval of quantitative optical properties of clouds and aerosols.
NASA Technical Reports Server (NTRS)
Schwemmer, Geary K.; Miller, David O.
2005-01-01
Clouds have a powerful influence on atmospheric radiative transfer and hence are crucial to understanding and interpreting the exchange of radiation between the Earth's surface, the atmosphere, and space. Because clouds are highly variable in space, time and physical makeup, it is important to be able to observe them in three dimensions (3-D) with sufficient resolution that the data can be used to generate and validate parameterizations of cloud fields at the resolution scale of global climate models (GCMs). Simulation of photon transport in three dimensionally inhomogeneous cloud fields show that spatial inhomogeneities tend to decrease cloud reflection and absorption and increase direct and diffuse transmission, Therefore it is an important task to characterize cloud spatial structures in three dimensions on the scale of GCM grid elements. In order to validate cloud parameterizations that represent the ensemble, or mean and variance of cloud properties within a GCM grid element, measurements of the parameters must be obtained on a much finer scale so that the statistics on those measurements are truly representative. High spatial sampling resolution is required, on the order of 1 km or less. Since the radiation fields respond almost instantaneously to changes in the cloud field, and clouds changes occur on scales of seconds and less when viewed on scales of approximately 100m, the temporal resolution of cloud properties should be measured and characterized on second time scales. GCM time steps are typically on the order of an hour, but in order to obtain sufficient statistical representations of cloud properties in the parameterizations that are used as model inputs, averaged values of cloud properties should be calculated on time scales on the order of 10-100 s. The Holographic Airborne Rotating Lidar Instrument Experiment (HARLIE) provides exceptional temporal (100 ms) and spatial (30 m) resolution measurements of aerosol and cloud backscatter in three dimensions. HARLIE was used in a ground-based configuration in several recent field campaigns. Principal data products include aerosol backscatter profiles, boundary layer heights, entrainment zone thickness, cloud fraction as a function of altitude and horizontal wind vector profiles based on correlating the motions of clouds and aerosol structures across portions of the scan. Comparisons will be made between various cloud detecting instruments to develop a baseline performance metric.
NASA Astrophysics Data System (ADS)
Tang, Wenjun; Qin, Jun; Yang, Kun; Liu, Shaomin; Lu, Ning; Niu, Xiaolei
2016-03-01
Cloud parameters (cloud mask, effective particle radius, and liquid/ice water path) are the important inputs in estimating surface solar radiation (SSR). These parameters can be derived from MODIS with high accuracy, but their temporal resolution is too low to obtain high-temporal-resolution SSR retrievals. In order to obtain hourly cloud parameters, an artificial neural network (ANN) is applied in this study to directly construct a functional relationship between MODIS cloud products and Multifunctional Transport Satellite (MTSAT) geostationary satellite signals. In addition, an efficient parameterization model for SSR retrieval is introduced and, when driven with MODIS atmospheric and land products, its root mean square error (RMSE) is about 100 W m-2 for 44 Baseline Surface Radiation Network (BSRN) stations. Once the estimated cloud parameters and other information (such as aerosol, precipitable water, ozone) are input to the model, we can derive SSR at high spatiotemporal resolution. The retrieved SSR is first evaluated against hourly radiation data at three experimental stations in the Haihe River basin of China. The mean bias error (MBE) and RMSE in hourly SSR estimate are 12.0 W m-2 (or 3.5 %) and 98.5 W m-2 (or 28.9 %), respectively. The retrieved SSR is also evaluated against daily radiation data at 90 China Meteorological Administration (CMA) stations. The MBEs are 9.8 W m-2 (or 5.4 %); the RMSEs in daily and monthly mean SSR estimates are 34.2 W m-2 (or 19.1 %) and 22.1 W m-2 (or 12.3 %), respectively. The accuracy is comparable to or even higher than two other radiation products (GLASS and ISCCP-FD), and the present method is more computationally efficient and can produce hourly SSR data at a spatial resolution of 5 km.
NASA Astrophysics Data System (ADS)
Tang, W.; Qin, J.; Yang, K.; Liu, S.; Lu, N.; Niu, X.
2015-12-01
Cloud parameters (cloud mask, effective particle radius and liquid/ice water path) are the important inputs in determining surface solar radiation (SSR). These parameters can be derived from MODIS with high accuracy but their temporal resolution is too low to obtain high temporal resolution SSR retrievals. In order to obtain hourly cloud parameters, the Artificial Neural Network (ANN) is applied in this study to directly construct a functional relationship between MODIS cloud products and Multi-functional Transport Satellite (MTSAT) geostationary satellite signals. Meanwhile, an efficient parameterization model for SSR retrieval is introduced and, when driven with MODIS atmospheric and land products, its root mean square error (RMSE) is about 100 W m-2 for 44 Baseline Surface Radiation Network (BSRN) stations. Once the estimated cloud parameters and other information (such as aerosol, precipitable water, ozone and so on) are input to the model, we can derive SSR at high spatio-temporal resolution. The retrieved SSR is first evaluated against hourly radiation data at three experimental stations in the Haihe River Basin of China. The mean bias error (MBE) and RMSE in hourly SSR estimate are 12.0 W m-2 (or 3.5 %) and 98.5 W m-2 (or 28.9 %), respectively. The retrieved SSR is also evaluated against daily radiation data at 90 China Meteorological Administration (CMA) stations. The MBEs are 9.8 W m-2 (5.4 %); the RMSEs in daily and monthly-mean SSR estimates are 34.2 W m-2 (19.1 %) and 22.1 W m-2 (12.3 %), respectively. The accuracy is comparable or even higher than other two radiation products (GLASS and ISCCP-FD), and the present method is more computationally efficient and can produce hourly SSR data at a spatial resolution of 5 km.
NASA Astrophysics Data System (ADS)
Krinitskiy, Mikhail; Sinitsyn, Alexey; Gulev, Sergey
2014-05-01
Cloud fraction is a critical parameter for the accurate estimation of short-wave and long-wave radiation - one of the most important surface fluxes over sea and land. Massive estimates of the total cloud cover as well as cloud amount for different layers of clouds are available from visual observations, satellite measurements and reanalyses. However, these data are subject of different uncertainties and need continuous validation against highly accurate in-situ measurements. Sky imaging with high resolution fish eye camera provides an excellent opportunity for collecting cloud cover data supplemented with additional characteristics hardly available from routine visual observations (e.g. structure of cloud cover under broken cloud conditions, parameters of distribution of cloud dimensions). We present operational automatic observational package which is based on fish eye camera taking sky images with high resolution (up to 1Hz) in time and a spatial resolution of 968x648px. This spatial resolution has been justified as an optimal by several sensitivity experiments. For the use of the package at research vessel when the horizontal positioning becomes critical, a special extension of the hardware and software to the package has been developed. These modules provide the explicit detection of the optimal moment for shooting. For the post processing of sky images we developed a software realizing the algorithm of the filtering of sunburn effect in case of small and moderate could cover and broken cloud conditions. The same algorithm accurately quantifies the cloud fraction by analyzing color mixture for each point and introducing the so-called "grayness rate index" for every pixel. The accuracy of the algorithm has been tested using the data collected during several campaigns in 2005-2011 in the North Atlantic Ocean. The collection of images included more than 3000 images for different cloud conditions supplied with observations of standard parameters. The system is fully autonomous and has a block for digital data collection at the hard disk. The system has been tested for a wide range of open ocean cloud conditions and we will demonstrate some pilot results of data processing and physical interpretation of fractional cloud cover estimation.
NASA Technical Reports Server (NTRS)
Mannucci, A.J.; Wu, D.L.; Teixeira, J.; Ao, C.O.; Xie, F.; Diner, D.J.; Wood, R.; Turk, Joe
2012-01-01
Objective: significant progress in understanding low-cloud boundary layer processes. This is the Single largest uncertainty in climate projections. Radio occultation has unique features suited to boundary layer remote sensing (1) Cloud penetrating (2) Very high vertical resolution (approximately 50m-100m) (3) Sensitivity to thermodynamic variables
A CERES-like Cloud Property Climatology Using AVHRR Data
NASA Astrophysics Data System (ADS)
Minnis, P.; Bedka, K. M.; Yost, C. R.; Trepte, Q.; Bedka, S. T.; Sun-Mack, S.; Doelling, D.
2015-12-01
Clouds affect the climate system by modulating the radiation budget and distributing precipitation. Variations in cloud patterns and properties are expected to accompany changes in climate. The NASA Clouds and the Earth's Radiant Energy System (CERES) Project developed an end-to-end analysis system to measure broadband radiances from a radiometer and retrieve cloud properties from collocated high-resolution MODerate-resolution Imaging Spectroradiometer (MODIS) data to generate a long-term climate data record of clouds and clear-sky properties and top-of-atmosphere radiation budget. The first MODIS was not launched until 2000, so the current CERES record is only 15 years long at this point. The core of the algorithms used to retrieve the cloud properties from MODIS is based on the spectral complement of the Advanced Very High Resolution Radiometer (AVHRR), which has been aboard a string of satellites since 1978. The CERES cloud algorithms were adapted for application to AVHRR data and have been used to produce an ongoing CERES-like cloud property and surface temperature product that includes an initial narrowband-based radiation budget. This presentation will summarize this new product, which covers nearly 37 years, and its comparability with cloud parameters from CERES, CALIPSO, and other satellites. Examples of some applications of this dataset are given and the potential for generating a long-term radiation budget CDR is also discussed.
NASA Astrophysics Data System (ADS)
Jayakumar, A.; Mamgain, Ashu; Jisesh, A. S.; Mohandas, Saji; Rakhi, R.; Rajagopal, E. N.
2016-05-01
Representation of rainfall distribution and monsoon circulation in the high resolution versions of NCMRWF Unified model (NCUM-REG) for the short-range forecasting of extreme rainfall event is vastly dependent on the key factors such as vertical cloud distribution, convection and convection/cloud relationship in the model. Hence it is highly relevant to evaluate the vertical structure of cloud and precipitation of the model over the monsoon environment. In this regard, we utilized the synergy of the capabilities of CloudSat data for long observational period, by conditioning it for the synoptic situation of the model simulation period. Simulations were run at 4-km grid length with the convective parameterization effectively switched off and on. Since the sample of CloudSat overpasses through the monsoon domain is small, the aforementioned methodology may qualitatively evaluate the vertical cloud structure for the model simulation period. It is envisaged that the present study will open up the possibility of further improvement in the high resolution version of NCUM in the tropics for the Indian summer monsoon associated rainfall events.
Atmospheric parameterization schemes for satellite cloud property retrieval during FIRE IFO 2
NASA Technical Reports Server (NTRS)
Titlow, James; Baum, Bryan A.
1993-01-01
Satellite cloud retrieval algorithms generally require atmospheric temperature and humidity profiles to determine such cloud properties as pressure and height. For instance, the CO2 slicing technique called the ratio method requires the calculation of theoretical upwelling radiances both at the surface and a prescribed number (40) of atmospheric levels. This technique has been applied to data from, for example, the High Resolution Infrared Radiometer Sounder (HIRS/2, henceforth HIRS) flown aboard the NOAA series of polar orbiting satellites and the High Resolution Interferometer Sounder (HIS). In this particular study, four NOAA-11 HIRS channels in the 15-micron region are used. The ratio method may be applied to various channel combinations to estimate cloud top heights using channels in the 15-mu m region. Presently, the multispectral, multiresolution (MSMR) scheme uses 4 HIRS channel combination estimates for mid- to high-level cloud pressure retrieval and Advanced Very High Resolution Radiometer (AVHRR) data for low-level (is greater than 700 mb) cloud level retrieval. In order to determine theoretical upwelling radiances, atmospheric temperature and water vapor profiles must be provided as well as profiles of other radiatively important gas absorber constituents such as CO2, O3, and CH4. The assumed temperature and humidity profiles have a large effect on transmittance and radiance profiles, which in turn are used with HIRS data to calculate cloud pressure, and thus cloud height and temperature. For large spatial scale satellite data analysis, atmospheric parameterization schemes for cloud retrieval algorithms are usually based on a gridded product such as that provided by the European Center for Medium Range Weather Forecasting (ECMWF) or the National Meteorological Center (NMC). These global, gridded products prescribe temperature and humidity profiles for a limited number of pressure levels (up to 14) in a vertical atmospheric column. The FIRE IFO 2 experiment provides an opportunity to investigate current atmospheric profile parameterization schemes, compare satellite cloud height results using both gridded products (ECMWF) and high vertical resolution sonde data from the National Weather Service (NWS) and Cross Chain Loran Atmospheric Sounding System (CLASS), and suggest modifications in atmospheric parameterization schemes based on these results.
Lidar Data Products and Applications Enabled by Conical Scanning
NASA Technical Reports Server (NTRS)
Schwemmer, Geary K.; Miller, David O.; Wilkerson, Thomas D.; Lee, Sang-Woo
2004-01-01
Several new data products and applications for elastic backscatter lidar are achieved using simple conical scanning. Atmospheric boundary layer spatial and temporal structure is revealed with resolution not possible with static pointing lidars. Cloud fractional coverage as a function of altitude is possible with high temporal resolution. Wind profiles are retrieved from the cloud and aerosol structure motions revealed by scanning. New holographic technology will soon allow quasi-conical scanning and push-broom lidar imaging without mechanical scanning, high resolution, on the order of seconds.
NASA Technical Reports Server (NTRS)
Werner, Frank; Wind, Galina; Zhang, Zhibo; Platnick, Steven; Di Girolamo, Larry; Zhao, Guangyu; Amarasinghe, Nandana; Meyer, Kerry
2016-01-01
A research-level retrieval algorithm for cloud optical and microphysical properties is developed for the Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) aboard the Terra satellite. It is based on the operational MODIS algorithm. This paper documents the technical details of this algorithm and evaluates the retrievals for selected marine boundary layer cloud scenes through comparisons with the operational MODIS Data Collection 6 (C6) cloud product. The newly developed, ASTERspecific cloud masking algorithm is evaluated through comparison with an independent algorithm reported in Zhao and Di Girolamo (2006). To validate and evaluate the cloud optical thickness (tau) and cloud effective radius (r(sub eff)) from ASTER, the high-spatial-resolution ASTER observations are first aggregated to the same 1000m resolution as MODIS. Subsequently, tau(sub aA) and r(sub eff, aA) retrieved from the aggregated ASTER radiances are compared with the collocated MODIS retrievals. For overcast pixels, the two data sets agree very well with Pearson's product-moment correlation coefficients of R greater than 0.970. However, for partially cloudy pixels there are significant differences between r(sub eff, aA) and the MODIS results which can exceed 10 micrometers. Moreover, it is shown that the numerous delicate cloud structures in the example marine boundary layer scenes, resolved by the high-resolution ASTER retrievals, are smoothed by the MODIS observations. The overall good agreement between the research-level ASTER results and the operational MODIS C6 products proves the feasibility of MODIS-like retrievals from ASTER reflectance measurements and provides the basis for future studies concerning the scale dependency of satellite observations and three-dimensional radiative effects.
NASA Astrophysics Data System (ADS)
Werner, Frank; Wind, Galina; Zhang, Zhibo; Platnick, Steven; Di Girolamo, Larry; Zhao, Guangyu; Amarasinghe, Nandana; Meyer, Kerry
2016-12-01
A research-level retrieval algorithm for cloud optical and microphysical properties is developed for the Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) aboard the Terra satellite. It is based on the operational MODIS algorithm. This paper documents the technical details of this algorithm and evaluates the retrievals for selected marine boundary layer cloud scenes through comparisons with the operational MODIS Data Collection 6 (C6) cloud product. The newly developed, ASTER-specific cloud masking algorithm is evaluated through comparison with an independent algorithm reported in [Zhao and Di Girolamo(2006)]. To validate and evaluate the cloud optical thickness (τ) and cloud effective radius (reff) from ASTER, the high-spatial-resolution ASTER observations are first aggregated to the same 1000 m resolution as MODIS. Subsequently, τaA and reff,
NASA Astrophysics Data System (ADS)
Torii, K.; Hattori, Y.; Hasegawa, K.; Ohama, A.; Haworth, T. J.; Shima, K.; Habe, A.; Tachihara, K.; Mizuno, N.; Onishi, T.; Mizuno, A.; Fukui, Y.
2017-02-01
Understanding high-mass star formation is one of the top-priority issues in astrophysics. Recent observational studies have revealed that cloud-cloud collisions may play a role in high-mass star formation in several places in the Milky Way and the Large Magellanic Cloud. The Trifid Nebula M20 is a well-known Galactic H II region ionized by a single O7.5 star. In 2011, based on the CO observations with NANTEN2, we reported that the O star was formed by the collision between two molecular clouds ˜0.3 Myr ago. Those observations identified two molecular clouds toward M20, traveling at a relative velocity of 7.5 {km} {{{s}}}-1. This velocity separation implies that the clouds cannot be gravitationally bound to M20, but since the clouds show signs of heating by the stars there they must be spatially coincident with it. A collision is therefore highly possible. In this paper we present the new CO J = 1-0 and J = 3-2 observations of the colliding clouds in M20 performed with the Mopra and ASTE telescopes. The high-resolution observations revealed that the two molecular clouds have peculiar spatial and velocity structures, I.e., a spatially complementary distribution between the two clouds and a bridge feature that connects the two clouds in velocity space. Based on a new comparison with numerical models, we find that this complementary distribution is an expected outcome of cloud-cloud collisions, and that the bridge feature can be interpreted as the turbulent gas excited at the interface of the collision. Our results reinforce the cloud-cloud collision scenario in M20.
NASA Technical Reports Server (NTRS)
Goldsmith, Paul F.
2012-01-01
Surveys of all different types provide basic data using different tracers. Molecular clouds have structure over a very wide range of scales. Thus, "high resolution" surveys and studies of selected nearby clouds add critical information. The combination of large-area and high resolution allows Increased spatial dynamic range, which in turn enables detection of new and perhaps critical morphology (e.g. filaments). Theoretical modeling has made major progress, and suggests that multiple forces are at work. Galactic-scale modeling also progressing - indicates that stellar feedback is required. Models must strive to reproduce observed cloud structure at all scales. Astrochemical observations are not unrelated to questions of cloud evolution and star formation but we are still learning how to use this capability.
NASA Technical Reports Server (NTRS)
Grund, Christian John; Eloranta, Edwin W.
1990-01-01
Cirrus clouds reflect incoming solar radiation and trap outgoing terrestrial radiation; therefore, accurate estimation of the global energy balance depends upon knowledge of the optical and physical properties of these clouds. Scattering and absorption by cirrus clouds affect measurements made by many satellite-borne and ground based remote sensors. Scattering of ambient light by the cloud, and thermal emissions from the cloud can increase measurement background noise. Multiple scattering processes can adversely affect the divergence of optical beams propagating through these clouds. Determination of the optical thickness and the vertical and horizontal extent of cirrus clouds is necessary to the evaluation of all of these effects. Lidar can be an effective tool for investigating these properties. During the FIRE cirrus IFO in Oct. to Nov. 1986, the High Spectral Resolution Lidar (HSRL) was operated from a rooftop site on the campus of the University of Wisconsin at Madison, Wisconsin. Approximately 124 hours of fall season data were acquired under a variety of cloud optical thickness conditions. Since the IFO, the HSRL data set was expanded by more than 63.5 hours of additional data acquired during all seasons. Measurements are presented for the range in optical thickness and backscattering phase function of the cirrus clouds, as well as contour maps of extinction corrected backscatter cross sections indicating cloud morphology. Color enhanced images of range-time indicator (RTI) displays a variety of cirrus clouds with approximately 30 sec time resolution are presented. The importance of extinction correction on the interpretation of cloud height and structure from lidar observations of optically thick cirrus are demonstrated.
Optimal Exploitation of the Temporal and Spatial Resolution of SEVIRI for the Nowcasting of Clouds
NASA Astrophysics Data System (ADS)
Sirch, Tobias; Bugliaro, Luca
2015-04-01
Optimal Exploitation of the Temporal and Spatial Resolution of SEVIRI for the Nowcasting of Clouds An algorithm was developed to forecast the development of water and ice clouds for the successive 5-120 minutes separately using satellite data from SEVIRI (Spinning Enhanced Visible and Infrared Imager) aboard Meteosat Second Generation (MSG). In order to derive cloud cover, optical thickness and cloud top height of high ice clouds "The Cirrus Optical properties derived from CALIOP and SEVIRI during day and night" (COCS, Kox et al. [2014]) algorithm is applied. For the determination of the liquid water clouds the APICS ("Algorithm for the Physical Investigation of Clouds with SEVIRI", Bugliaro e al. [2011]) cloud algorithm is used, which provides cloud cover, optical thickness and effective radius. The forecast rests upon an optical flow method determining a motion vector field from two satellite images [Zinner et al., 2008.] With the aim of determining the ideal time separation of the satellite images that are used for the determination of the cloud motion vector field for every forecast horizon time the potential of the better temporal resolution of the Meteosat Rapid Scan Service (5 instead of 15 minutes repetition rate) has been investigated. Therefore for the period from March to June 2013 forecasts up to 4 hours in time steps of 5 min based on images separated by a time interval of 5 min, 10 min, 15 min, 30 min have been created. The results show that Rapid Scan data produces a small reduction of errors for a forecast horizon up to 30 minutes. For the following time steps forecasts generated with a time interval of 15 min should be used and for forecasts up to several hours computations with a time interval of 30 min provide the best results. For a better spatial resolution the HRV channel (High Resolution Visible, 1km instead of 3km maximum spatial resolution at the subsatellite point) has been integrated into the forecast. To detect clouds the difference of the measured albedo from SEVIRI and the clear-sky albedo provided by MODIS has been used and additionally the temporal development of this quantity. A pre-requisite for this work was an adjustment of the geolocation accuracy for MSG and MODIS by shifting the MODIS data and quantifying the correlation between both data sets.
Estimation of Cirrus and Stratus Cloud Heights Using Landsat Imagery
NASA Technical Reports Server (NTRS)
Inomata, Yasushi; Feind, R. E.; Welch, R. M.
1996-01-01
A new method based upon high-spatial-resolution imagery is presented that matches cloud and shadow regions to estimate cirrus and stratus cloud heights. The distance between the cloud and the matching shadow pattern is accomplished using the 2D cross-correlation function from which the cloud height is derived. The distance between the matching cloud-shadow patterns is verified manually. The derived heights also are validated through comparison with a temperature-based retrieval of cloud height. It is also demonstrated that an estimate of cloud thickness can be retrieved if both the sunside and anti-sunside of the cloud-shadow pair are apparent. The technique requires some intepretation to determine the cloud height level retrieved (i.e., the top, base, or mid-level). It is concluded that the method is accurate to within several pixels, equivalent to cloud height variations of about +/- 250 m. The results show that precise placement of the templates is unnecessary, so that the development of a semi-automated procedure is possible. Cloud templates of about 64 pixels on a side or larger produce consistent results. The procedure was repeated for imagery degraded to simulate lower spatial resolutions. The results suggest that spatial resolution of 150-200 m or better is necessary in order to obtain stable cloud height retrievals.
NASA Astrophysics Data System (ADS)
Henneberger, J.; Fugal, J. P.; Stetzer, O.; Lohmann, U.
2013-05-01
Measurements of the microphysical properties of mixed-phase clouds with high spatial resolution are important to understand the processes inside these clouds. This work describes the design and characterization of the newly developed ground-based field instrument HOLIMO II (HOLographic Imager for Microscopic Objects II). HOLIMO II uses digital in-line holography to in-situ image cloud particles in a well defined sample volume. By an automated algorithm, two-dimensional images of single cloud particles between 6 and 250 μm in diameter are obtained and the size spectrum, the concentration and water content of clouds are calculated. By testing the sizing algorithm with monosized beads a systematic overestimation near the resolution limit was found, which has been used to correct the measurements. Field measurements from the high altitude research station Jungfraujoch, Switzerland, are presented. The measured number size distributions are in good agreement with parallel measurements by a fog monitor (FM-100, DMT, Boulder USA). The field data shows that HOLIMO II is capable of measuring the number size distribution with a high spatial resolution and determines ice crystal shape, thus providing a method of quantifying variations in microphysical properties. A case study over a period of 8 h has been analyzed, exploring the transition from a liquid to a mixed-phase cloud, which is the longest observation of a cloud with a holographic device. During the measurement period, the cloud does not completely glaciate, contradicting earlier assumptions of the dominance of the Wegener-Bergeron-Findeisen (WBF) process.
NASA Astrophysics Data System (ADS)
Henneberger, J.; Fugal, J. P.; Stetzer, O.; Lohmann, U.
2013-11-01
Measurements of the microphysical properties of mixed-phase clouds with high spatial resolution are important to understand the processes inside these clouds. This work describes the design and characterization of the newly developed ground-based field instrument HOLIMO II (HOLographic Imager for Microscopic Objects II). HOLIMO II uses digital in-line holography to in situ image cloud particles in a well-defined sample volume. By an automated algorithm, two-dimensional images of single cloud particles between 6 and 250 μm in diameter are obtained and the size spectrum, the concentration and water content of clouds are calculated. By testing the sizing algorithm with monosized beads a systematic overestimation near the resolution limit was found, which has been used to correct the measurements. Field measurements from the high altitude research station Jungfraujoch, Switzerland, are presented. The measured number size distributions are in good agreement with parallel measurements by a fog monitor (FM-100, DMT, Boulder USA). The field data shows that HOLIMO II is capable of measuring the number size distribution with a high spatial resolution and determines ice crystal shape, thus providing a method of quantifying variations in microphysical properties. A case study over a period of 8 h has been analyzed, exploring the transition from a liquid to a mixed-phase cloud, which is the longest observation of a cloud with a holographic device. During the measurement period, the cloud does not completely glaciate, contradicting earlier assumptions of the dominance of the Wegener-Bergeron-Findeisen (WBF) process.
NASA Technical Reports Server (NTRS)
Hostetler, Chris A.; Hair, John W.; Cook, Anthony L.
2002-01-01
We are in the process of developing a nadir-viewing, aircraft-based high spectral resolution lidar (HSRL) at NASA Langley Research Center. The system is designed to measure backscatter and extinction of aerosols and tenuous clouds. The primary uses of the instrument will be to validate spaceborne aerosol and cloud observations, carry out regional process studies, and assess the predictions of chemical transport models. In this paper, we provide an overview of the instrument design and present the results of simulations showing the instrument's capability to accurately measure extinction and extinction-to-backscatter ratio.
NASA Technical Reports Server (NTRS)
Weisz, Elisabeth; Li, Jun; Li, Jinlong; Zhou, Daniel K.; Huang, Hung-Lung; Goldberg, Mitchell D.; Yang, Ping
2007-01-01
High-spectral resolution measurements from the Atmospheric Infrared Sounder (AIRS) onboard the EOS (Earth Observing System) Aqua satellite provide unique information about atmospheric state, surface and cloud properties. This paper presents an AIRS alone single field-of-view (SFOV) retrieval algorithm to simultaneously retrieve temperature, humidity and ozone profiles under all weather conditions, as well as cloud top pressure (CTP) and cloud optical thickness (COT) under cloudy skies. For optically thick cloud conditions the above-cloud soundings are derived, whereas for clear skies and optically thin cloud conditions the profiles are retrieved from 0.005 hPa down to the earth's surface. Initial validation has been conducted by using the operational MODIS (Moderate Resolution Imaging Spectroradiometer) product, ECMWF (European Center of Medium range Weather Forecasts) analysis fields and radiosonde observations (RAOBs). These inter-comparisons clearly demonstrate the potential of this algorithm to process data from 38 high-spectral infrared (IR) sounder instruments.
NASA Technical Reports Server (NTRS)
Zhang, Zhibo; Ackerman, Andrew S.; Feingold, Graham; Platnick, Steven; Pincus, Robert; Xue, Huiwen
2012-01-01
This study investigates effects of drizzle and cloud horizontal inhomogeneity on cloud effective radius (re) retrievals from the Moderate Resolution Imaging Spectroradiometer (MODIS). In order to identify the relative importance of various factors, we developed a MODIS cloud property retrieval simulator based on the combination of large-eddy simulations (LES) and radiative transfer computations. The case studies based on synthetic LES cloud fields indicate that at high spatial resolution (100 m) 3-D radiative transfer effects, such as illumination and shadowing, can induce significant differences between retrievals ofre based on reflectance at 2.1 m (re,2.1) and 3.7 m (re,3.7). It is also found that 3-D effects tend to have stronger impact onre,2.1 than re,3.7, leading to positive difference between the two (re,3.72.1) from illumination and negative re,3.72.1from shadowing. The cancellation of opposing 3-D effects leads to overall reasonable agreement betweenre,2.1 and re,3.7 at high spatial resolution as far as domain averages are concerned. At resolutions similar to MODIS, however, re,2.1 is systematically larger than re,3.7when averaged over the LES domain, with the difference exhibiting a threshold-like dependence on bothre,2.1and an index of the sub-pixel variability in reflectance (H), consistent with MODIS observations. In the LES cases studied, drizzle does not strongly impact reretrievals at either wavelength. It is also found that opposing 3-D radiative transfer effects partly cancel each other when cloud reflectance is aggregated from high spatial resolution to MODIS resolution, resulting in a weaker net impact of 3-D radiative effects onre retrievals. The large difference at MODIS resolution between re,3.7 and re,2.1 for highly inhomogeneous pixels with H 0.4 can be largely attributed to what we refer to as the plane-parallelrebias, which is attributable to the impact of sub-pixel level horizontal variability of cloud optical thickness onre retrievals and is greater for re,2.1 than re,3.7. These results suggest that there are substantial uncertainties attributable to 3-D radiative effects and plane-parallelre bias in the MODIS re,2.1retrievals for pixels with strong sub-pixel scale variability, and theH index can be used to identify these uncertainties.
Norris, Peter M; da Silva, Arlindo M
2016-07-01
A method is presented to constrain a statistical model of sub-gridcolumn moisture variability using high-resolution satellite cloud data. The method can be used for large-scale model parameter estimation or cloud data assimilation. The gridcolumn model includes assumed probability density function (PDF) intra-layer horizontal variability and a copula-based inter-layer correlation model. The observables used in the current study are Moderate Resolution Imaging Spectroradiometer (MODIS) cloud-top pressure, brightness temperature and cloud optical thickness, but the method should be extensible to direct cloudy radiance assimilation for a small number of channels. The algorithm is a form of Bayesian inference with a Markov chain Monte Carlo (MCMC) approach to characterizing the posterior distribution. This approach is especially useful in cases where the background state is clear but cloudy observations exist. In traditional linearized data assimilation methods, a subsaturated background cannot produce clouds via any infinitesimal equilibrium perturbation, but the Monte Carlo approach is not gradient-based and allows jumps into regions of non-zero cloud probability. The current study uses a skewed-triangle distribution for layer moisture. The article also includes a discussion of the Metropolis and multiple-try Metropolis versions of MCMC.
NASA Technical Reports Server (NTRS)
Norris, Peter M.; Da Silva, Arlindo M.
2016-01-01
A method is presented to constrain a statistical model of sub-gridcolumn moisture variability using high-resolution satellite cloud data. The method can be used for large-scale model parameter estimation or cloud data assimilation. The gridcolumn model includes assumed probability density function (PDF) intra-layer horizontal variability and a copula-based inter-layer correlation model. The observables used in the current study are Moderate Resolution Imaging Spectroradiometer (MODIS) cloud-top pressure, brightness temperature and cloud optical thickness, but the method should be extensible to direct cloudy radiance assimilation for a small number of channels. The algorithm is a form of Bayesian inference with a Markov chain Monte Carlo (MCMC) approach to characterizing the posterior distribution. This approach is especially useful in cases where the background state is clear but cloudy observations exist. In traditional linearized data assimilation methods, a subsaturated background cannot produce clouds via any infinitesimal equilibrium perturbation, but the Monte Carlo approach is not gradient-based and allows jumps into regions of non-zero cloud probability. The current study uses a skewed-triangle distribution for layer moisture. The article also includes a discussion of the Metropolis and multiple-try Metropolis versions of MCMC.
Norris, Peter M.; da Silva, Arlindo M.
2018-01-01
A method is presented to constrain a statistical model of sub-gridcolumn moisture variability using high-resolution satellite cloud data. The method can be used for large-scale model parameter estimation or cloud data assimilation. The gridcolumn model includes assumed probability density function (PDF) intra-layer horizontal variability and a copula-based inter-layer correlation model. The observables used in the current study are Moderate Resolution Imaging Spectroradiometer (MODIS) cloud-top pressure, brightness temperature and cloud optical thickness, but the method should be extensible to direct cloudy radiance assimilation for a small number of channels. The algorithm is a form of Bayesian inference with a Markov chain Monte Carlo (MCMC) approach to characterizing the posterior distribution. This approach is especially useful in cases where the background state is clear but cloudy observations exist. In traditional linearized data assimilation methods, a subsaturated background cannot produce clouds via any infinitesimal equilibrium perturbation, but the Monte Carlo approach is not gradient-based and allows jumps into regions of non-zero cloud probability. The current study uses a skewed-triangle distribution for layer moisture. The article also includes a discussion of the Metropolis and multiple-try Metropolis versions of MCMC. PMID:29618847
First Results of AirMSPI Imaging Polarimetry at ORACLES 2016: Aerosol and Water Cloud Retrievals
NASA Astrophysics Data System (ADS)
van Harten, G.; Xu, F.; Diner, D. J.; Rheingans, B. E.; Tosca, M.; Seidel, F.; Bull, M. A.; Tkatcheva, I. N.; McDuffie, J. L.; Garay, M. J.; Jovanovic, V. M.; Cairns, B.; Alexandrov, M. D.; Hostetler, C. A.; Ferrare, R. A.; Burton, S. P.
2017-12-01
The Airborne Multiangle SpectroPolarimetric Imager (AirMSPI) is a remote sensing instrument for the characterization of atmospheric aerosols and clouds. We will report on the successful deployment and resulting data products of AirMSPI in the 2016 field campaign as part of NASA's ObseRvations of Aerosols above CLouds and their intEractionS (ORACLES). The goal of this five-year investigation is to study the impacts of African biomass burning aerosols on the radiative properties of the subtropical stratocumulus cloud deck over the southeast Atlantic Ocean. On board the NASA ER-2 high-altitude aircraft, AirMSPI collected over 4000 high-resolution images on 16 days. The observations are performed in two different modes: step-and-stare mode, in which a 10x10 km target is observed from 9 view angles at 10 m resolution, and sweep mode, where a 80-100 km along-track by 10-25 km across-track target is observed with continuously changing view angle between ±67° at 25 m resolution. This Level 1B2 calibrated and georectified imagery is publically available at the NASA Langley Atmospheric Science Data Center (ASDC)*. We will then describe the Level 2 water cloud products that will be made publically available, viz. optical depth and droplet size distribution, which are retrieved using a polarimetric algorithm. Finally, we will present the results of a recently developed research algorithm for the simultaneous retrieval of these cloud properties and above-cloud aerosols, and validations using collocated High Spectral Resolution Lidar-2 (HSRL-2) and Research Scanning Polarimeter (RSP) products. * https://eosweb.larc.nasa.gov/project/airmspi/airmspi_table
Classification of cloud fields based on textural characteristics
NASA Technical Reports Server (NTRS)
Welch, R. M.; Sengupta, S. K.; Chen, D. W.
1987-01-01
The present study reexamines the applicability of texture-based features for automatic cloud classification using very high spatial resolution (57 m) Landsat multispectral scanner digital data. It is concluded that cloud classification can be accomplished using only a single visible channel.
Applications of low altitude photogrammetry for morphometry, displacements, and landform modeling
NASA Astrophysics Data System (ADS)
Gomez, F. G.; Polun, S. G.; Hickcox, K.; Miles, C.; Delisle, C.; Beem, J. R.
2016-12-01
Low-altitude aerial surveying is emerging as a tool that greatly improves the ease and efficiency of measuring landforms for quantitative geomorphic analyses. High-resolution, close-range photogrammetry produces dense, 3-dimensional point clouds that facilitate the construction of digital surface models, as well as a potential means of classifying ground targets using spatial structure. This study presents results from recent applications of UAS-based photogrammetry, including high resolution surface morphometry of a lava flow, repeat-pass applications to mass movements, and fault scarp degradation modeling. Depending upon the desired photographic resolution and the platform/payload flown, aerial photos are typically acquired at altitudes of 40 - 100 meters above the ground surface. In all cases, high-precision ground control points are key for accurate (and repeatable) orientation - relying on low-precision GPS coordinates (whether on the ground or geotags in the aerial photos) typically results in substantial rotations (tilt) of the reference frame. Using common ground control points between repeat surveys results in matching point clouds with RMS residuals better than 10 cm. In arid regions, the point cloud is used to assess lava flow surface roughness using multi-scale measurements of point cloud dimensionality. For the landslide study, the point cloud provides a basis for assessing possible displacements. In addition, the high resolution orthophotos facilitate mapping of fractures and their growth. For neotectonic applications, we compare fault scarp modeling results from UAV-derived point clouds versus field-based surveys (kinematic GPS and electronic distance measurements). In summary, there is a wide ranging toolbox of low-altitude aerial platforms becoming available for field geoscientists. In many instances, these tools will present convenience and reduced cost compared with the effort and expense to contract acquisitions of aerial imagery.
NASA Astrophysics Data System (ADS)
Palaseanu, M.; Thatcher, C.; Danielson, J.; Gesch, D. B.; Poppenga, S.; Kottermair, M.; Jalandoni, A.; Carlson, E.
2016-12-01
Coastal topographic and bathymetric (topobathymetric) data with high spatial resolution (1-meter or better) and high vertical accuracy are needed to assess the vulnerability of Pacific Islands to climate change impacts, including sea level rise. According to the Intergovernmental Panel on Climate Change reports, low-lying atolls in the Pacific Ocean are extremely vulnerable to king tide events, storm surge, tsunamis, and sea-level rise. The lack of coastal topobathymetric data has been identified as a critical data gap for climate vulnerability and adaptation efforts in the Republic of the Marshall Islands (RMI). For Majuro Atoll, home to the largest city of RMI, the only elevation dataset currently available is the Shuttle Radar Topography Mission data which has a 30-meter spatial resolution and 16-meter vertical accuracy (expressed as linear error at 90%). To generate high-resolution digital elevation models (DEMs) in the RMI, elevation information and photographic imagery have been collected from field surveys using GNSS/total station and unmanned aerial vehicles for Structure-from-Motion (SfM) point cloud generation. Digital Globe WorldView II imagery was processed to create SfM point clouds to fill in gaps in the point cloud derived from the higher resolution UAS photos. The combined point cloud data is filtered and classified to bare-earth and georeferenced using the GNSS data acquired on roads and along survey transects perpendicular to the coast. A total station was used to collect elevation data under tree canopies where heavy vegetation cover blocked the view of GNSS satellites. A subset of the GPS / total station data was set aside for error assessment of the resulting DEM.
A high-resolution oxygen A-band spectrometer (HABS) and its radiation closure
NASA Astrophysics Data System (ADS)
Min, Q.; Yin, B.; Li, S.; Berndt, J.; Harrison, L.; Joseph, E.; Duan, M.; Kiedron, P.
2014-06-01
Various studies indicate that high-resolution oxygen A-band spectrum has the capability to retrieve the vertical profiles of aerosol and cloud properties. To improve the understanding of oxygen A-band inversions and utility, we developed a high-resolution oxygen A-band spectrometer (HABS), and deployed it at Howard University Beltsville site during the NASA Discover Air-Quality Field Campaign in July, 2011. By using a single telescope, the HABS instrument measures the direct solar and the zenith diffuse radiation subsequently. HABS exhibits excellent performance: stable spectral response ratio, high signal-to-noise ratio (SNR), high-spectrum resolution (0.016 nm), and high out-of-band rejection (10-5). For the spectral retrievals of HABS measurements, a simulator is developed by combining a discrete ordinates radiative transfer code (DISORT) with the High Resolution Transmission (HITRAN) database HITRAN2008. The simulator uses a double-k approach to reduce the computational cost. The HABS-measured spectra are consistent with the related simulated spectra. For direct-beam spectra, the discrepancies between measurements and simulations, indicated by confidence intervals (95%) of relative difference, are (-0.06, 0.05) and (-0.08, 0.09) for solar zenith angles of 27 and 72°, respectively. For zenith diffuse spectra, the related discrepancies between measurements and simulations are (-0.06, 0.05) and (-0.08, 0.07) for solar zenith angles of 27 and 72°, respectively. The main discrepancies between measurements and simulations occur at or near the strong oxygen absorption line centers. They are mainly due to two kinds of causes: (1) measurement errors associated with the noise/spikes of HABS-measured spectra, as a result of combined effects of weak signal, low SNR, and errors in wavelength registration; (2) modeling errors in the simulation, including the error of model parameters setting (e.g., oxygen absorption line parameters, vertical profiles of temperature and pressure) and the lack of treatment of the rotational Raman scattering. The high-resolution oxygen A-band measurements from HABS can constrain the active radar retrievals for more accurate cloud optical properties (e.g., cloud optical depth, effective radius), particularly for multi-layer clouds and for mixed-phase clouds.
NASA Astrophysics Data System (ADS)
Hair, J. W.; Hostetler, C. A.; Brian, C.; Ziemba, L. D.; Alexandrov, M. D.; Hu, Y.; Crosbie, E.; Scarino, A. J.; Butler, C. F.; Moore, R.; Berkoff, T.; Harper, D. B.; Cook, A. L.; Hare, R. J.; Lee, J.; Anderson, B. E.
2017-12-01
The NASA Langley High Spectral Resolution lidar (HSRL) and the NASA GISS Research Scanning Polarimeter (RSP) were deployed onboard the NASA C-130 during two field campaigns as part of the NASA's Earth Venture-Suborbital (EVS) North Atlantic Aerosol and Marine Ecosystems Study (NAAMES) during November 2015 and May 2016. The main objectives of NAAMES are to study the phases of the North Atlantic annual plankton cycle and to investigate remote marine aerosols and their impact on boundary layer clouds. Lidar retrievals of the cloud-top extinction and lidar ratio (extinction/backscatter ratio) of boundary layer clouds are presented. These retrievals are unique and are enabled by two characteristics of the lidar: employment of the high-spectral-resolution lidar technique and the high-vertical-resolution (1.25 m) the Langley HSRL instrument. The HSRL lidar ratio retrievals are compared to estimates derived from Research Scanning Polarimeter data to assess consistency between the two remote sensors. The measurements of effective size and variance from RSP are combined with the HSRL cloud top extinction to retrieve the cloud droplet number concentrations (CDNC). The lidar+polarimeter CDNC estimates are compared to those from the Cloud Droplet Probe (CDP) that is part of the NASA Langley Aerosol Research Group Experiment (LARGE) instrument suite. Histograms of the CNDC measurements from remote sensors are shown to highlight the observed differences in CDNC between the November and May deployments.
Continuous All-Sky Cloud Measurements: Cloud Fraction Analysis Based on a Newly Developed Instrument
NASA Astrophysics Data System (ADS)
Aebi, C.; Groebner, J.; Kaempfer, N.; Vuilleumier, L.
2017-12-01
Clouds play an important role in the climate system and are also a crucial parameter for the Earth's surface energy budget. Ground-based measurements of clouds provide data in a high temporal resolution in order to quantify its influence on radiation. The newly developed all-sky cloud camera at PMOD/WRC in Davos (Switzerland), the infrared cloud camera (IRCCAM), is a microbolometer sensitive in the 8 - 14 μm wavelength range. To get all-sky information the camera is located on top of a frame looking downward on a spherical gold-plated mirror. The IRCCAM has been measuring continuously (day and nighttime) with a time resolution of one minute in Davos since September 2015. To assess the performance of the IRCCAM, two different visible all-sky cameras (Mobotix Q24M and Schreder VIS-J1006), which can only operate during daytime, are installed in Davos. All three camera systems have different software for calculating fractional cloud coverage from images. Our study analyzes mainly the fractional cloud coverage of the IRCCAM and compares it with the fractional cloud coverage calculated from the two visible cameras. Preliminary results of the measurement accuracy of the IRCCAM compared to the visible camera indicate that 78 % of the data are within ± 1 octa and even 93 % within ± 2 octas. An uncertainty of 1-2 octas corresponds to the measurement uncertainty of human observers. Therefore, the IRCCAM shows similar performance in detection of cloud coverage as the visible cameras and the human observers, with the advantage that continuous measurements with high temporal resolution are possible.
Evaluating Global Aerosol Models and Aerosol and Water Vapor Properties Near Clouds
DOE Office of Scientific and Technical Information (OSTI.GOV)
Richard A. Ferrare; David D. Turner
Project goals: (1) Use the routine surface and airborne measurements at the ARM SGP site, and the routine surface measurements at the NSA site, to continue our evaluations of model aerosol simulations; (2) Determine the degree to which the Raman lidar measurements of water vapor and aerosol scattering and extinction can be used to remotely characterize the aerosol humidification factor; (3) Use the high temporal resolution CARL data to examine how aerosol properties vary near clouds; and (4) Use the high temporal resolution CARL and Atmospheric Emitted Radiance Interferometer (AERI) data to quantify entrainment in optically thin continental cumulus clouds.
Stochastic Convection Parameterizations
NASA Technical Reports Server (NTRS)
Teixeira, Joao; Reynolds, Carolyn; Suselj, Kay; Matheou, Georgios
2012-01-01
computational fluid dynamics, radiation, clouds, turbulence, convection, gravity waves, surface interaction, radiation interaction, cloud and aerosol microphysics, complexity (vegetation, biogeochemistry, radiation versus turbulence/convection stochastic approach, non-linearities, Monte Carlo, high resolutions, large-Eddy Simulations, cloud structure, plumes, saturation in tropics, forecasting, parameterizations, stochastic, radiation-clod interaction, hurricane forecasts
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%).
A high-resolution oxygen A-band spectrometer (HABS) and its radiation closure
NASA Astrophysics Data System (ADS)
Min, Q.; Yin, B.; Li, S.; Berndt, J.; Harrison, L.; Joseph, E.; Duan, M.; Kiedron, P.
2014-02-01
The pressure dependence of oxygen A-band absorption enables the retrieval of the vertical profiles of aerosol and cloud properties from oxygen A-band spectrometry. To improve the understanding of oxygen A-band inversions and utility, we developed a high-resolution oxygen A-band spectrometer (HABS), and deployed it at Howard University Beltsville site during the NASA Discover Air-Quality Field Campaign in July 2011. The HABS has the ability to measure solar direct-beam and zenith diffuse radiation through a telescope automatically. It exhibits excellent performance: stable spectral response ratio, high signal-to-noise ratio (SNR), high spectrum resolution (0.16 nm), and high Out-of-Band Rejection (10-5). To evaluate the spectra performance of HABS, a HABS simulator has been developed by combing the discrete ordinates radiative transfer (DISORT) code with the High Resolution Transmission (HTRAN) database HITRAN2008. The simulator uses double-k approach to reduce the computational cost. The HABS measured spectra are consistent with the related simulated spectra. For direct-beam spectra, the confidence intervals (95%) of relative difference between measurements and simulation are (-0.06, 0.05) and (-0.08, 0.09) for solar zenith angles of 27° and 72°, respectively. The main differences between them occur at or near the strong oxygen absorption line centers. They are mainly caused by the noise/spikes of HABS measured spectra, as a result of combined effects of weak signal, low SNR, and errors in wavelength registration and absorption line parameters. The high-resolution oxygen A-band measurements from HABS can constrain the active radar retrievals for more accurate cloud optical properties, particularly for multi-layer clouds and for mixed-phase clouds.
NASA Astrophysics Data System (ADS)
Rauser, F.
2013-12-01
We present results from the German BMBF initiative 'High Definition Cloud and Precipitation for advancing Climate Prediction -HD(CP)2'. This initiative addresses most of the problems that are discussed in this session in one, unified approach: cloud physics, convection, boundary layer development, radiation and subgrid variability are approached in one organizational framework. HD(CP)2 merges both observation and high performance computing / model development communities to tackle a shared problem: how to improve the understanding of the most important subgrid-scale processes of cloud and precipitation physics, and how to utilize this knowledge for improved climate predictions. HD(CP)2 is a coordinated initiative to: (i) realize; (ii) evaluate; and (iii) statistically characterize and exploit for the purpose of both parameterization development and cloud / precipitation feedback analysis; ultra-high resolution (100 m in the horizontal, 10-50 m in the vertical) regional hind-casts over time periods (3-15 y) and spatial scales (1000-1500 km) that are climatically meaningful. HD(CP)2 thus consists of three elements (the model development and simulations, their observational evaluation and exploitation/synthesis to advance CP prediction) and its first three-year phase has started on October 1st 2012. As a central part of HD(CP)2, the HD(CP)2 Observational Prototype Experiment (HOPE) has been carried out in spring 2013. In this campaign, high resolution measurements with a multitude of instruments from all major centers in Germany have been carried out in a limited domain, to allow for unprecedented resolution and precision in the observation of microphysics parameters on a resolution that will allow for evaluation and improvement of ultra-high resolution models. At the same time, a local area version of the new climate model ICON of the Max Planck Institute and the German weather service has been developed that allows for LES-type simulations on high resolutions on limited domains. The advantage of modifying an existing, evolving climate model is to share insights from high resolution runs directly with the large-scale modelers and to allow for easy intercomparison and evaluation later on. Within this presentation, we will give a short overview on HD(CP)2 , show results from the observation campaign HOPE and the LES simulations of the same domain and conditions and will discuss how these will lead to an improved understanding and evaluation background for the efforts to improve fast physics in our climate model.
NASA Technical Reports Server (NTRS)
Grund, C. J.; Eloranta, E. W.
1996-01-01
During the First ISCCP Region Experiment (FIRE) cirrus intensive field observation (IFO) the High Spectral Resolution Lidar was operated from a roof top site on the University of Wisconsin-Madison campus. Because the HSRL technique separately measures the molecular and cloud particle backscatter components of the lidar return, the optical thickness is determined independent of particle backscatter. This is accomplished by comparing the known molecular density distribution to the observed decrease in molecular backscatter signal with altitude. The particle to molecular backscatter ratio yields calibrated measurements of backscatter cross sections that can be plotted ro reveal cloud morphology without distortion due to attenuation. Changes in cloud particle size, shape, and phase affect the backscatter to extinction ratio (backscatter-phase function). The HSRL independently measures cloud particle backscatter phase function. This paper presents a quantitative analysis of the HSRL cirrus cloud data acquired over an approximate 33 hour period of continuous near zenith observations. Correlations between small scale wind structure and cirrus cloud morphology have been observed. These correlations can bias the range averaging inherent in wind profiling lidars of modest vertical resolution, leading to increased measurement errors at cirrus altitudes. Extended periods of low intensity backscatter were noted between more strongly organized cirrus cloud activity. Optical thicknesses ranging from 0.01-1.4, backscatter phase functions between 0.02-0.065 sr (exp -1) and backscatter cross sections spanning 4 orders of magnitude were observed. the altitude relationship between cloud top and bottom boundaries and the cloud optical center altitude was dependent on the type of formation observed Cirrus features were observed with characteristic wind drift estimated horizontal sizes of 5-400 km. The clouds frequently exhibited cellular structure with vertical to horizontal dimension ratios of 1:5-1:1.
NASA Technical Reports Server (NTRS)
Eloranta, E. W.; Piironen, P. K.
1992-01-01
A new implementation of the High Spectral Resolution Lidar (HSRL) in an instrument van which allows measurements during field experiments is described. The instrument was modified to provide measurements of depolarization. In addition, both the signal amplitude and depolarization variations with receiver field of view are simultaneously measured. These modifications allow discrimination of ice clouds from water clouds and observation of multiple scattering contributions to the lidar return.
Mechanisms and Model Diversity of Trade-Wind Shallow Cumulus Cloud Feedbacks: A Review.
Vial, Jessica; Bony, Sandrine; Stevens, Bjorn; Vogel, Raphaela
2017-01-01
Shallow cumulus clouds in the trade-wind regions are at the heart of the long standing uncertainty in climate sensitivity estimates. In current climate models, cloud feedbacks are strongly influenced by cloud-base cloud amount in the trades. Therefore, understanding the key factors controlling cloudiness near cloud-base in shallow convective regimes has emerged as an important topic of investigation. We review physical understanding of these key controlling factors and discuss the value of the different approaches that have been developed so far, based on global and high-resolution model experimentations and process-oriented analyses across a range of models and for observations. The trade-wind cloud feedbacks appear to depend on two important aspects: (1) how cloudiness near cloud-base is controlled by the local interplay between turbulent, convective and radiative processes; (2) how these processes interact with their surrounding environment and are influenced by mesoscale organization. Our synthesis of studies that have explored these aspects suggests that the large diversity of model responses is related to fundamental differences in how the processes controlling trade cumulus operate in models, notably, whether they are parameterized or resolved. In models with parameterized convection, cloudiness near cloud-base is very sensitive to the vigor of convective mixing in response to changes in environmental conditions. This is in contrast with results from high-resolution models, which suggest that cloudiness near cloud-base is nearly invariant with warming and independent of large-scale environmental changes. Uncertainties are difficult to narrow using current observations, as the trade cumulus variability and its relation to large-scale environmental factors strongly depend on the time and/or spatial scales at which the mechanisms are evaluated. New opportunities for testing physical understanding of the factors controlling shallow cumulus cloud responses using observations and high-resolution modeling on large domains are discussed.
Mechanisms and Model Diversity of Trade-Wind Shallow Cumulus Cloud Feedbacks: A Review
NASA Astrophysics Data System (ADS)
Vial, Jessica; Bony, Sandrine; Stevens, Bjorn; Vogel, Raphaela
2017-11-01
Shallow cumulus clouds in the trade-wind regions are at the heart of the long standing uncertainty in climate sensitivity estimates. In current climate models, cloud feedbacks are strongly influenced by cloud-base cloud amount in the trades. Therefore, understanding the key factors controlling cloudiness near cloud-base in shallow convective regimes has emerged as an important topic of investigation. We review physical understanding of these key controlling factors and discuss the value of the different approaches that have been developed so far, based on global and high-resolution model experimentations and process-oriented analyses across a range of models and for observations. The trade-wind cloud feedbacks appear to depend on two important aspects: (1) how cloudiness near cloud-base is controlled by the local interplay between turbulent, convective and radiative processes; (2) how these processes interact with their surrounding environment and are influenced by mesoscale organization. Our synthesis of studies that have explored these aspects suggests that the large diversity of model responses is related to fundamental differences in how the processes controlling trade cumulus operate in models, notably, whether they are parameterized or resolved. In models with parameterized convection, cloudiness near cloud-base is very sensitive to the vigor of convective mixing in response to changes in environmental conditions. This is in contrast with results from high-resolution models, which suggest that cloudiness near cloud-base is nearly invariant with warming and independent of large-scale environmental changes. Uncertainties are difficult to narrow using current observations, as the trade cumulus variability and its relation to large-scale environmental factors strongly depend on the time and/or spatial scales at which the mechanisms are evaluated. New opportunities for testing physical understanding of the factors controlling shallow cumulus cloud responses using observations and high-resolution modeling on large domains are discussed.
C3Winds: A Novel 3D Wind Observing System to Characterize Severe Weather Events
NASA Astrophysics Data System (ADS)
Kelly, M. A.; Wu, D. L.; Yee, J. H.; Boldt, J.; Demajistre, R.; Reynolds, E.; Tripoli, G. J.; Oman, L.; Prive, N.; Heidinger, A. K.; Wanzong, S.
2015-12-01
The CubeSat Constellation Cloud Winds (C3Winds) is a NASA Earth Venture Instrument (EV-I) concept with the primary objective to resolve high-resolution 3D dynamic structures of severe wind events. Rapid evolution of severe weather events highlights the need for high-resolution mesoscale wind observations. Yet mesoscale observations of severe weather dynamics are quite rare, especially over the ocean where extratropical and tropical cyclones (ETCs and TCs) can undergo explosive development. Measuring wind velocity at the mesoscale from space remains a great challenge, but is critically needed to understand and improve prediction of severe weather and tropical cyclones. Based on compact, visible/IR imagers and a mature stereoscopic technique, C3Winds has the capability to measure high-resolution (~2 km) cloud motion vectors and cloud geometric heights accurately by tracking cloud features from two formation-flying CubeSats, separated by 5-15 minutes. Complementary to lidar wind measurements from space, C3Winds will provide high-resolution wind fields needed for detailed investigations of severe wind events in occluded ETCs, rotational structures inside TC eyewalls, and ozone injections associated with tropopause folding events. Built upon mature imaging technologies and long history of stereoscopic remote sensing, C3Winds provides an innovative, cost-effective solution to global wind observations with the potential for increased diurnal sampling via CubeSat constellation.
“Lidar Investigations of Aerosol, Cloud, and Boundary Layer Properties Over the ARM ACRF Sites”
DOE Office of Scientific and Technical Information (OSTI.GOV)
Ferrare, Richard; Turner, David
2015-01-13
Project goals; Characterize the aerosol and ice vertical distributions over the ARM NSA site, and in particular to discriminate between elevated aerosol layers and ice clouds in optically thin scattering layers; Characterize the water vapor and aerosol vertical distributions over the ARM Darwin site, how these distributions vary seasonally, and quantify the amount of water vapor and aerosol that is above the boundary layer; Use the high temporal resolution Raman lidar data to examine how aerosol properties vary near clouds; Use the high temporal resolution Raman lidar and Atmospheric Emitted Radiance Interferometer (AERI) data to quantify entrainment in optically thinmore » continental cumulus clouds; and Use the high temporal Raman lidar data to continue to characterize the turbulence within the convective boundary layer and how the turbulence statistics (e.g., variance, skewness) is correlated with larger scale variables predicted by models.« less
Theoretical Models of Protostellar Binary and Multiple Systems with AMR Simulations
NASA Astrophysics Data System (ADS)
Matsumoto, Tomoaki; Tokuda, Kazuki; Onishi, Toshikazu; Inutsuka, Shu-ichiro; Saigo, Kazuya; Takakuwa, Shigehisa
2017-05-01
We present theoretical models for protostellar binary and multiple systems based on the high-resolution numerical simulation with an adaptive mesh refinement (AMR) code, SFUMATO. The recent ALMA observations have revealed early phases of the binary and multiple star formation with high spatial resolutions. These observations should be compared with theoretical models with high spatial resolutions. We present two theoretical models for (1) a high density molecular cloud core, MC27/L1521F, and (2) a protobinary system, L1551 NE. For the model for MC27, we performed numerical simulations for gravitational collapse of a turbulent cloud core. The cloud core exhibits fragmentation during the collapse, and dynamical interaction between the fragments produces an arc-like structure, which is one of the prominent structures observed by ALMA. For the model for L1551 NE, we performed numerical simulations of gas accretion onto protobinary. The simulations exhibit asymmetry of a circumbinary disk. Such asymmetry has been also observed by ALMA in the circumbinary disk of L1551 NE.
NASA Astrophysics Data System (ADS)
Porto da Silveira, I.; Zuidema, P.; Kirtman, B. P.
2017-12-01
The rugged topography of the Andes Cordillera along with strong coastal upwelling, strong sea surface temperatures (SST) gradients and extensive but geometrically-thin stratocumulus decks turns the Southeast Pacific (SEP) into a challenge for numerical modeling. In this study, hindcast simulations using the Community Climate System Model (CCSM4) at two resolutions were analyzed to examine the importance of resolution alone, with the parameterizations otherwise left unchanged. The hindcasts were initialized on January 1 with the real-time oceanic and atmospheric reanalysis (CFSR) from 1982 to 2003, forming a 10-member ensemble. The two resolutions are (0.1o oceanic and 0.5o atmospheric) and (1.125o oceanic and 0.9o atmospheric). The SST error growth in the first six days of integration (fast errors) and those resulted from model drift (saturated errors) are assessed and compared towards evaluating the model processes responsible for the SST error growth. For the high-resolution simulation, SST fast errors are positive (+0.3oC) near the continental borders and negative offshore (-0.1oC). Both are associated with a decrease in cloud cover, a weakening of the prevailing southwesterly winds and a reduction of latent heat flux. The saturated errors possess a similar spatial pattern, but are larger and are more spatially concentrated. This suggests that the processes driving the errors already become established within the first week, in contrast to the low-resolution simulations. These, instead, manifest too-warm SSTs related to too-weak upwelling, driven by too-strong winds and Ekman pumping. Nevertheless, the ocean surface tends to be cooler in the low-resolution simulation than the high-resolution due to a higher cloud cover. Throughout the integration, saturated SST errors become positive and could reach values up to +4oC. These are accompanied by upwelling dumping and a decrease in cloud cover. High and low resolution models presented notable differences in how SST errors variability drove atmospheric changes, especially because the high resolution is sensitive to resurgence regions. This allows the model to resolve cloud heights and establish different radiative feedbacks.
Evaluation of AIRS cloud properties using MPACE data
NASA Astrophysics Data System (ADS)
Wu, Xuebao; Li, Jun; Menzel, W. Paul; Huang, Allen; Baggett, Kevin; Revercomb, Henry
2005-12-01
Retrieval of cloud properties from the Atmospheric Infrared Sounder (AIRS) aboard the NASA Aqua satellite has been investigated. The cloud products from the collocated MODerate resolution Imaging Spectroradiometer (MODIS) data are used to characterize the AIRS sub-pixel cloud information such as cloud phase, cloud coverage, and cloud layer information. A Minimum Residual (MR) approach is used to retrieve cloud microphysical properties once the cloud top pressure (CTP) and effective cloud amount (ECA) are determined from AIRS CO2 absorption channels between 720 and 790 cm-1. The cloud microphysical properties can be retrieved by minimizing the differences between the observations and the calculations using AIRS longwave window channels between 790 and 1130 cm-1. AIRS is used to derive cloud properties during the Mixed Phase Arctic Cloud Experiment (MPACE) field campaign. Comparison with measurements obtained from lidar data is made for a test day, showing that AIRS cloud property retrievals agree with in situ lidar observations. Due to the large solar zenith angle, the MODIS operational retrieval approach is not able to provide cloud microphysics north of Barrow, Alaska; however, AIRS provides cloud microphysical properties with its high spectral resolution IR measurements.
NASA Astrophysics Data System (ADS)
Zhong, Bo; Chen, Wuhan; Wu, Shanlong; Liu, Qinhuo
2016-10-01
Cloud detection of satellite imagery is very important for quantitative remote sensing research and remote sensing applications. However, many satellite sensors don't have enough bands for a quick, accurate, and simple detection of clouds. Particularly, the newly launched moderate to high spatial resolution satellite sensors of China, such as the charge-coupled device on-board the Chinese Huan Jing 1 (HJ-1/CCD) and the wide field of view (WFV) sensor on-board the Gao Fen 1 (GF-1), only have four available bands including blue, green, red, and near infrared bands, which are far from the requirements of most could detection methods. In order to solve this problem, an improved and automated cloud detection method for Chinese satellite sensors called OCM (Object oriented Cloud and cloud-shadow Matching method) is presented in this paper. It firstly modified the Automatic Cloud Cover Assessment (ACCA) method, which was developed for Landsat-7 data, to get an initial cloud map. The modified ACCA method is mainly based on threshold and different threshold setting produces different cloud map. Subsequently, a strict threshold is used to produce a cloud map with high confidence and large amount of cloud omission and a loose threshold is used to produce a cloud map with low confidence and large amount of commission. Secondly, a corresponding cloud-shadow map is also produced using the threshold of near-infrared band. Thirdly, the cloud maps and cloud-shadow map are transferred to cloud objects and cloud-shadow objects. Cloud and cloud-shadow are usually in pairs; consequently, the final cloud and cloud-shadow maps are made based on the relationship between cloud and cloud-shadow objects. OCM method was tested using almost 200 HJ-1/CCD images across China and the overall accuracy of cloud detection is close to 90%.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Blanchard, Yann; Royer, Alain; O'Neill, Norman T.
Multiband downwelling thermal measurements of zenith sky radiance, along with cloud boundary heights, were used in a retrieval algorithm to estimate cloud optical depth and effective particle diameter of thin ice clouds in the Canadian High Arctic. Ground-based thermal infrared (IR) radiances for 150 semitransparent ice clouds cases were acquired at the Polar Environment Atmospheric Research Laboratory (PEARL) in Eureka, Nunavut, Canada (80° N, 86° W). We analyzed and quantified the sensitivity of downwelling thermal radiance to several cloud parameters including optical depth, effective particle diameter and shape, water vapor content, cloud geometric thickness and cloud base altitude. A lookupmore » table retrieval method was used to successfully extract, through an optimal estimation method, cloud optical depth up to a maximum value of 2.6 and to separate thin ice clouds into two classes: (1) TIC1 clouds characterized by small crystals (effective particle diameter ≤ 30 µm), and (2) TIC2 clouds characterized by large ice crystals (effective particle diameter > 30 µm). The retrieval technique was validated using data from the Arctic High Spectral Resolution Lidar (AHSRL) and Millimeter Wave Cloud Radar (MMCR). Inversions were performed over three polar winters and results showed a significant correlation ( R 2 = 0.95) for cloud optical depth retrievals and an overall accuracy of 83 % for the classification of TIC1 and TIC2 clouds. A partial validation relative to an algorithm based on high spectral resolution downwelling IR radiance measurements between 8 and 21µm was also performed. It confirms the robustness of the optical depth retrieval and the fact that the broadband thermal radiometer retrieval was sensitive to small particle (TIC1) sizes.« less
NASA Astrophysics Data System (ADS)
Blanchard, Yann; Royer, Alain; O'Neill, Norman T.; Turner, David D.; Eloranta, Edwin W.
2017-06-01
Multiband downwelling thermal measurements of zenith sky radiance, along with cloud boundary heights, were used in a retrieval algorithm to estimate cloud optical depth and effective particle diameter of thin ice clouds in the Canadian High Arctic. Ground-based thermal infrared (IR) radiances for 150 semitransparent ice clouds cases were acquired at the Polar Environment Atmospheric Research Laboratory (PEARL) in Eureka, Nunavut, Canada (80° N, 86° W). We analyzed and quantified the sensitivity of downwelling thermal radiance to several cloud parameters including optical depth, effective particle diameter and shape, water vapor content, cloud geometric thickness and cloud base altitude. A lookup table retrieval method was used to successfully extract, through an optimal estimation method, cloud optical depth up to a maximum value of 2.6 and to separate thin ice clouds into two classes: (1) TIC1 clouds characterized by small crystals (effective particle diameter ≤ 30 µm), and (2) TIC2 clouds characterized by large ice crystals (effective particle diameter > 30 µm). The retrieval technique was validated using data from the Arctic High Spectral Resolution Lidar (AHSRL) and Millimeter Wave Cloud Radar (MMCR). Inversions were performed over three polar winters and results showed a significant correlation (R2 = 0.95) for cloud optical depth retrievals and an overall accuracy of 83 % for the classification of TIC1 and TIC2 clouds. A partial validation relative to an algorithm based on high spectral resolution downwelling IR radiance measurements between 8 and 21 µm was also performed. It confirms the robustness of the optical depth retrieval and the fact that the broadband thermal radiometer retrieval was sensitive to small particle (TIC1) sizes.
Blanchard, Yann; Royer, Alain; O'Neill, Norman T.; ...
2017-06-09
Multiband downwelling thermal measurements of zenith sky radiance, along with cloud boundary heights, were used in a retrieval algorithm to estimate cloud optical depth and effective particle diameter of thin ice clouds in the Canadian High Arctic. Ground-based thermal infrared (IR) radiances for 150 semitransparent ice clouds cases were acquired at the Polar Environment Atmospheric Research Laboratory (PEARL) in Eureka, Nunavut, Canada (80° N, 86° W). We analyzed and quantified the sensitivity of downwelling thermal radiance to several cloud parameters including optical depth, effective particle diameter and shape, water vapor content, cloud geometric thickness and cloud base altitude. A lookupmore » table retrieval method was used to successfully extract, through an optimal estimation method, cloud optical depth up to a maximum value of 2.6 and to separate thin ice clouds into two classes: (1) TIC1 clouds characterized by small crystals (effective particle diameter ≤ 30 µm), and (2) TIC2 clouds characterized by large ice crystals (effective particle diameter > 30 µm). The retrieval technique was validated using data from the Arctic High Spectral Resolution Lidar (AHSRL) and Millimeter Wave Cloud Radar (MMCR). Inversions were performed over three polar winters and results showed a significant correlation ( R 2 = 0.95) for cloud optical depth retrievals and an overall accuracy of 83 % for the classification of TIC1 and TIC2 clouds. A partial validation relative to an algorithm based on high spectral resolution downwelling IR radiance measurements between 8 and 21µm was also performed. It confirms the robustness of the optical depth retrieval and the fact that the broadband thermal radiometer retrieval was sensitive to small particle (TIC1) sizes.« less
Optical instruments synergy in determination of optical depth of thin clouds
NASA Astrophysics Data System (ADS)
Viviana Vlăduţescu, Daniela; Schwartz, Stephen E.; Huang, Dong
2018-04-01
Optically thin clouds have a strong radiative effect and need to be represented accurately in climate models. Cloud optical depth of thin clouds was retrieved using high resolution digital photography, lidar, and a radiative transfer model. The Doppler Lidar was operated at 1.5 μm, minimizing return from Rayleigh scattering, emphasizing return from aerosols and clouds. This approach examined cloud structure on scales 3 to 5 orders of magnitude finer than satellite products, opening new avenues for examination of cloud structure and evolution.
Optical Instruments Synergy in Determination of Optical Depth of Thin Clouds
DOE Office of Scientific and Technical Information (OSTI.GOV)
Vladutescu, Daniela V.; Schwartz, Stephen E.
Optically thin clouds have a strong radiative effect and need to be represented accurately in climate models. Cloud optical depth of thin clouds was retrieved using high resolution digital photography, lidar, and a radiative transfer model. The Doppler Lidar was operated at 1.5 μm, minimizing return from Rayleigh scattering, emphasizing return from aerosols and clouds. This approach examined cloud structure on scales 3 to 5 orders of magnitude finer than satellite products, opening new avenues for examination of cloud structure and evolution.
LSAH: a fast and efficient local surface feature for point cloud registration
NASA Astrophysics Data System (ADS)
Lu, Rongrong; Zhu, Feng; Wu, Qingxiao; Kong, Yanzi
2018-04-01
Point cloud registration is a fundamental task in high level three dimensional applications. Noise, uneven point density and varying point cloud resolutions are the three main challenges for point cloud registration. In this paper, we design a robust and compact local surface descriptor called Local Surface Angles Histogram (LSAH) and propose an effectively coarse to fine algorithm for point cloud registration. The LSAH descriptor is formed by concatenating five normalized sub-histograms into one histogram. The five sub-histograms are created by accumulating a different type of angle from a local surface patch respectively. The experimental results show that our LSAH is more robust to uneven point density and point cloud resolutions than four state-of-the-art local descriptors in terms of feature matching. Moreover, we tested our LSAH based coarse to fine algorithm for point cloud registration. The experimental results demonstrate that our algorithm is robust and efficient as well.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Wang, Hailong; Burleyson, Casey D.; Ma, Po-Lun
We use the long-term Atmospheric Radiation Measurement (ARM) datasets collected at the three Tropical Western Pacific (TWP) sites as a tropical testbed to evaluate the ability of the Community Atmosphere Model (CAM5) to simulate the various types of clouds, their seasonal and diurnal variations, and their impact on surface radiation. We conducted a series of CAM5 simulations at various horizontal grid spacing (around 2°, 1°, 0.5°, and 0.25°) with meteorological constraints from reanalysis. Model biases in the seasonal cycle of cloudiness are found to be weakly dependent on model resolution. Positive biases (up to 20%) in the annual mean totalmore » cloud fraction appear mostly in stratiform ice clouds. Higher-resolution simulations do reduce the positive bias in the frequency of ice clouds, but they inadvertently increase the negative biases in convective clouds and low-level liquid clouds, leading to a positive bias in annual mean shortwave fluxes at the sites, as high as 65 W m-2 in the 0.25° simulation. Such resolution-dependent biases in clouds can adversely lead to biases in ambient thermodynamic properties and, in turn, feedback on clouds. Both the CAM5 model and ARM observations show distinct diurnal cycles in total, stratiform and convective cloud fractions; however, they are out-of-phase by 12 hours and the biases vary by site. Our results suggest that biases in deep convection affect the vertical distribution and diurnal cycle of stratiform clouds through the transport of vapor and/or the detrainment of liquid and ice. We also found that the modelled gridmean surface longwave fluxes are systematically larger than site measurements when the grid that the ARM sites reside in is partially covered by ocean. The modeled longwave fluxes at such sites also lack a discernable diurnal cycle because the ocean part of the grid is warmer and less sensitive to radiative heating/cooling compared to land. Higher spatial resolution is more helpful is this regard. Our testbed approach can be easily adapted for the evaluation of new parameterizations being developed for CAM5 or other global or regional model simulations at high spatial resolutions.« less
Ground truth spectrometry and imagery of eruption clouds to maximize utility of satellite imagery
NASA Technical Reports Server (NTRS)
Rose, William I.
1993-01-01
Field experiments with thermal imaging infrared radiometers were performed and a laboratory system was designed for controlled study of simulated ash clouds. Using AVHRR (Advanced Very High Resolution Radiometer) thermal infrared bands 4 and 5, a radiative transfer method was developed to retrieve particle sizes, optical depth and particle mass involcanic clouds. A model was developed for measuring the same parameters using TIMS (Thermal Infrared Multispectral Scanner), MODIS (Moderate Resolution Imaging Spectrometer), and ASTER (Advanced Spaceborne Thermal Emission and Reflection Radiometer). Related publications are attached.
a New Approach for Subway Tunnel Deformation Monitoring: High-Resolution Terrestrial Laser Scanning
NASA Astrophysics Data System (ADS)
Li, J.; Wan, Y.; Gao, X.
2012-07-01
With the improvement of the accuracy and efficiency of laser scanning technology, high-resolution terrestrial laser scanning (TLS) technology can obtain high precise points-cloud and density distribution and can be applied to high-precision deformation monitoring of subway tunnels and high-speed railway bridges and other fields. In this paper, a new approach using a points-cloud segmentation method based on vectors of neighbor points and surface fitting method based on moving least squares was proposed and applied to subway tunnel deformation monitoring in Tianjin combined with a new high-resolution terrestrial laser scanner (Riegl VZ-400). There were three main procedures. Firstly, a points-cloud consisted of several scanning was registered by linearized iterative least squares approach to improve the accuracy of registration, and several control points were acquired by total stations (TS) and then adjusted. Secondly, the registered points-cloud was resampled and segmented based on vectors of neighbor points to select suitable points. Thirdly, the selected points were used to fit the subway tunnel surface with moving least squares algorithm. Then a series of parallel sections obtained from temporal series of fitting tunnel surfaces were compared to analysis the deformation. Finally, the results of the approach in z direction were compared with the fiber optical displacement sensor approach and the results in x, y directions were compared with TS respectively, and comparison results showed the accuracy errors of x, y, z directions were respectively about 1.5 mm, 2 mm, 1 mm. Therefore the new approach using high-resolution TLS can meet the demand of subway tunnel deformation monitoring.
High-resolution imaging and target designation through clouds or smoke
Perry, Michael D.
2003-01-01
A method and system of combining gated intensifiers and advances in solid-state, short-pulse laser technology, compact systems capable of producing high resolution (i.e., approximately less than 20 centimeters) optical images through a scattering medium such as dense clouds, fog, smoke, etc. may be achieved from air or ground based platforms. Laser target designation through a scattering medium is also enabled by utilizing a short pulse illumination laser and a relatively minor change to the detectors on laser guided munitions.
High spectral resolution observations of fluorescent molecular hydrogen in molecular clouds
NASA Technical Reports Server (NTRS)
Burton, Michael G.; Geballe, T. R.; Brand, P. W. J. L.; Moorhouse, A.
1990-01-01
The 1-0 S(1) line of molecular hydrogen has been observed at high spectral resolution in several sources where the emission was suspected of being fluorescent. In NGC 2023, the Orion Bar, and Parsamyan 18, the S(1) line is unresolved, and the line center close to the rest velocity of the ambient molecular cloud. Such behavior is expected for UV-excited line emission. The H2 line widths in molecular clouds thus can serve as diagnostic for shocked and UV-excitation mechanisms. If the lines are broader than several km/s or velocity shifts are observed across a source it is likely that shocks are responsible for the excitation of the gas.
Classification of Clouds and Deep Convection from GEOS-5 Using Satellite Observations
NASA Technical Reports Server (NTRS)
Putman, William; Suarez, Max
2010-01-01
With the increased resolution of global atmospheric models and the push toward global cloud resolving models, the resemblance of model output to satellite observations has become strikingly similar. As we progress with our adaptation of the Goddard Earth Observing System Model, Version 5 (GEOS-5) as a high resolution cloud system resolving model, evaluation of cloud properties and deep convection require in-depth analysis beyond a visual comparison. Outgoing long-wave radiation (OLR) provides a sufficient comparison with infrared (IR) satellite imagery to isolate areas of deep convection. We have adopted a binning technique to generate a series of histograms for OLR which classify the presence and fraction of clear sky versus deep convection in the tropics that can be compared with a similar analyses of IR imagery from composite Geostationary Operational Environmental Satellite (GOES) observations. We will present initial results that have been used to evaluate the amount of deep convective parameterization required within the model as we move toward cloud system resolving resolutions of 10- to 1-km globally.
Gridless, pattern-driven point cloud completion and extension
NASA Astrophysics Data System (ADS)
Gravey, Mathieu; Mariethoz, Gregoire
2016-04-01
While satellites offer Earth observation with a wide coverage, other remote sensing techniques such as terrestrial LiDAR can acquire very high-resolution data on an area that is limited in extension and often discontinuous due to shadow effects. Here we propose a numerical approach to merge these two types of information, thereby reconstructing high-resolution data on a continuous large area. It is based on a pattern matching process that completes the areas where only low-resolution data is available, using bootstrapped high-resolution patterns. Currently, the most common approach to pattern matching is to interpolate the point data on a grid. While this approach is computationally efficient, it presents major drawbacks for point clouds processing because a significant part of the information is lost in the point-to-grid resampling, and that a prohibitive amount of memory is needed to store large grids. To address these issues, we propose a gridless method that compares point clouds subsets without the need to use a grid. On-the-fly interpolation involves a heavy computational load, which is met by using a GPU high-optimized implementation and a hierarchical pattern searching strategy. The method is illustrated using data from the Val d'Arolla, Swiss Alps, where high-resolution terrestrial LiDAR data are fused with lower-resolution Landsat and WorldView-3 acquisitions, such that the density of points is homogeneized (data completion) and that it is extend to a larger area (data extension).
Spectral band passes for a high precision satellite sounder
NASA Technical Reports Server (NTRS)
Kaplan, L. D.; Chahine, M. T.; Susskind, J.; Searl, J. E.
1977-01-01
Atmospheric temperature soundings with significantly improved vertical resolution can be obtained from carefully chosen narrow band-pass measurements in the 4.3-micron band of CO2 by taking advantage of the variation of the absorption coefficients, and thereby the weighting functions, with pressure and temperature. A set of channels has been found in the 4.2-micron region that is capable of yielding about 2-km vertical resolution in the troposphere. The concept of a complete system is presented for obtaining high resolution retrievals of temperature and water vapor distribution, as well as surface and cloud top temperatures, even in the presence of broken clouds.
High-resolution measurement of cloud microphysics and turbulence at a mountaintop station
NASA Astrophysics Data System (ADS)
Siebert, H.; Shaw, R. A.; Ditas, J.; Schmeissner, T.; Malinowski, S. P.; Bodenschatz, E.; Xu, H.
2015-08-01
Mountain research stations are advantageous not only for long-term sampling of cloud properties but also for measurements that are prohibitively difficult to perform on airborne platforms due to the large true air speed or adverse factors such as weight and complexity of the equipment necessary. Some cloud-turbulence measurements, especially Lagrangian in nature, fall into this category. We report results from simultaneous, high-resolution and collocated measurements of cloud microphysical and turbulence properties during several warm cloud events at the Umweltforschungsstation Schneefernerhaus (UFS) on Zugspitze in the German Alps. The data gathered were found to be representative of observations made with similar instrumentation in free clouds. The observed turbulence shared all features known for high-Reynolds-number flows: it exhibited approximately Gaussian fluctuations for all three velocity components, a clearly defined inertial subrange following Kolmogorov scaling (power spectrum, and second- and third-order Eulerian structure functions), and highly intermittent velocity gradients, as well as approximately lognormal kinetic energy dissipation rates. The clouds were observed to have liquid water contents on the order of 1 g m-3 and size distributions typical of continental clouds, sometimes exhibiting long positive tails indicative of large drop production through turbulent mixing or coalescence growth. Dimensionless parameters relevant to cloud-turbulence interactions, the Stokes number and settling parameter are in the range typically observed in atmospheric clouds. Observed fluctuations in droplet number concentration and diameter suggest a preference for inhomogeneous mixing. Finally, enhanced variance in liquid water content fluctuations is observed at high frequencies, and the scale break occurs at a value consistent with the independently estimated phase relaxation time from microphysical measurements.
Time Evolution of the Giant Molecular Cloud Mass Functions across Galactic Disks
NASA Astrophysics Data System (ADS)
Kobayashi, Masato I. N.; Inutsuka, Shu-Ichiro; Kobayashi, Hiroshi; Hasegawa, Kenji
2017-01-01
We formulate and conduct the time-integration of time evolution equation for the giant molecular cloud mass function (GMCMF) including the cloud-cloud collision (CCC) effect. Our results show that the CCC effect is only limited in the massive-end of the GMCMF and indicate that future high resolution and sensitivity radio observations may constrain giant molecular cloud (GMC) timescales by observing the GMCMF slope in the lower mass regime.
NASA Astrophysics Data System (ADS)
Zou, Xiaoliang; Zhao, Guihua; Li, Jonathan; Yang, Yuanxi; Fang, Yong
2016-06-01
With the rapid developments of the sensor technology, high spatial resolution imagery and airborne Lidar point clouds can be captured nowadays, which make classification, extraction, evaluation and analysis of a broad range of object features available. High resolution imagery, Lidar dataset and parcel map can be widely used for classification as information carriers. Therefore, refinement of objects classification is made possible for the urban land cover. The paper presents an approach to object based image analysis (OBIA) combing high spatial resolution imagery and airborne Lidar point clouds. The advanced workflow for urban land cover is designed with four components. Firstly, colour-infrared TrueOrtho photo and laser point clouds were pre-processed to derive the parcel map of water bodies and nDSM respectively. Secondly, image objects are created via multi-resolution image segmentation integrating scale parameter, the colour and shape properties with compactness criterion. Image can be subdivided into separate object regions. Thirdly, image objects classification is performed on the basis of segmentation and a rule set of knowledge decision tree. These objects imagery are classified into six classes such as water bodies, low vegetation/grass, tree, low building, high building and road. Finally, in order to assess the validity of the classification results for six classes, accuracy assessment is performed through comparing randomly distributed reference points of TrueOrtho imagery with the classification results, forming the confusion matrix and calculating overall accuracy and Kappa coefficient. The study area focuses on test site Vaihingen/Enz and a patch of test datasets comes from the benchmark of ISPRS WG III/4 test project. The classification results show higher overall accuracy for most types of urban land cover. Overall accuracy is 89.5% and Kappa coefficient equals to 0.865. The OBIA approach provides an effective and convenient way to combine high resolution imagery and Lidar ancillary data for classification of urban land cover.
Lidar Observations of the Optical Properties and 3-Dimensional Structure of Cirrus Clouds
NASA Technical Reports Server (NTRS)
Eloranta, E. W.
1996-01-01
The scientific research conducted under this grant have been reported in a series of journal articles, dissertations, and conference proceedings. This report consists of a compilation of these publications in the following areas: development and operation of a High Spectral Resolution Lidar, cloud physics and cloud formation, mesoscale observations of cloud phenomena, ground-based and satellite cloud cover observations, impact of volcanic aerosols on cloud formation, visible and infrared radiative relationships as measured by satellites and lidar, and scattering cross sections.
NASA Astrophysics Data System (ADS)
Schneider, Tapio; Lan, Shiwei; Stuart, Andrew; Teixeira, João.
2017-12-01
Climate projections continue to be marred by large uncertainties, which originate in processes that need to be parameterized, such as clouds, convection, and ecosystems. But rapid progress is now within reach. New computational tools and methods from data assimilation and machine learning make it possible to integrate global observations and local high-resolution simulations in an Earth system model (ESM) that systematically learns from both and quantifies uncertainties. Here we propose a blueprint for such an ESM. We outline how parameterization schemes can learn from global observations and targeted high-resolution simulations, for example, of clouds and convection, through matching low-order statistics between ESMs, observations, and high-resolution simulations. We illustrate learning algorithms for ESMs with a simple dynamical system that shares characteristics of the climate system; and we discuss the opportunities the proposed framework presents and the challenges that remain to realize it.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Kassianov, Evgueni I.; Riley, Erin A.; Kleiss, Jessica
Cloud amount is an essential and extensively used macrophysical parameter of cumulus clouds. It is commonly defined as a cloud fraction (CF) from zenith-pointing ground-based active and passive remote sensing. However, conventional retrievals of CF from the remote sensing data with very narrow field-of-view (FOV) may not be representative of the surrounding area. Here we assess its representativeness using an integrated dataset collected at the U.S. Department of Energy (DOE) Atmospheric Radiation Measurement (ARM) program's Southern Great Plains (SGP) site in Oklahoma, USA. For our assessment with focus on selected days with single-layer cumulus clouds (2005-2016), we include the narrow-FOVmore » ARM Active Remotely Sensed Clouds Locations (ARSCL) and large-FOV Total Sky Imager (TSI) cloud products, the 915-MHz Radar Wind Profiler (RWP) measurements of wind speed and direction, and also high-resolution satellite images from Landsat and the Moderate Resolution Imaging Spectroradiometer (MODIS). We demonstrate that a root-mean-square difference (RMSD) between the 15-min averaged ARSCL cloud fraction (CF) and the 15-min averaged TSI fractional sky cover (FSC) is large (up to 0.3). We also discuss how the horizontal distribution of clouds can modify the obtained large RMSD using a new uniformity metric. The latter utilizes the spatial distribution of the FSC over the 100° FOV TSI images obtained with high temporal resolution (30 sec sampling). We demonstrate that cases with more uniform spatial distribution of FSC show better agreement between the narrow-FOV CF and large-FOV FSC, reducing the RMSD by up to a factor of 2.« less
Characterizing the structure of an unusually cold high latitude cloud
NASA Astrophysics Data System (ADS)
Veneziani, Marcella; Paladini, Roberta; Noriega-Crespo, Alberto; Carey, Sean; Tibbs, Christopher; Flagey, Nicolas; Piacentini, Francesco
2012-10-01
Recently the BOOMERanG 2003 experiment, with an angular resolution of 10', has detected an unusually cold cloud (T = 9 K) located at high Galactic latitudes and with an area of 0.25 deg^2. The low temperature of this object has been confirmed by a follow-up in the with Herschel which measured T = 15.3 in the range 100-500micron and with a resolution 20 times higher than BOOMERanG. Despite the cold temperature of the cloud, the measured extinction (Av=0.15 mag) seems to indicate a fairly low amount of shielding material which could justify the dust cooling. Surprisingly, while the dust content in the cloud is well constrained by a substantial amount of data, no - or very little information - is available for its gas counterpart. Therefore, we request 5hrs of 21-cm spectral line observations with the Parkes telescopes. The observations will allow us to accurately estimate the cloud HI column density, as well as to derive information about its kinematics.
Norris, Peter M.; da Silva, Arlindo M.
2018-01-01
Part 1 of this series presented a Monte Carlo Bayesian method for constraining a complex statistical model of global circulation model (GCM) sub-gridcolumn moisture variability using high-resolution Moderate Resolution Imaging Spectroradiometer (MODIS) cloud data, thereby permitting parameter estimation and cloud data assimilation for large-scale models. This article performs some basic testing of this new approach, verifying that it does indeed reduce mean and standard deviation biases significantly with respect to the assimilated MODIS cloud optical depth, brightness temperature and cloud-top pressure and that it also improves the simulated rotational–Raman scattering cloud optical centroid pressure (OCP) against independent (non-assimilated) retrievals from the Ozone Monitoring Instrument (OMI). Of particular interest, the Monte Carlo method does show skill in the especially difficult case where the background state is clear but cloudy observations exist. In traditional linearized data assimilation methods, a subsaturated background cannot produce clouds via any infinitesimal equilibrium perturbation, but the Monte Carlo approach allows non-gradient-based jumps into regions of non-zero cloud probability. In the example provided, the method is able to restore marine stratocumulus near the Californian coast, where the background state has a clear swath. This article also examines a number of algorithmic and physical sensitivities of the new method and provides guidance for its cost-effective implementation. One obvious difficulty for the method, and other cloud data assimilation methods as well, is the lack of information content in passive-radiometer-retrieved cloud observables on cloud vertical structure, beyond cloud-top pressure and optical thickness, thus necessitating strong dependence on the background vertical moisture structure. It is found that a simple flow-dependent correlation modification from Riishojgaard provides some help in this respect, by better honouring inversion structures in the background state. PMID:29618848
NASA Technical Reports Server (NTRS)
Norris, Peter M.; da Silva, Arlindo M.
2016-01-01
Part 1 of this series presented a Monte Carlo Bayesian method for constraining a complex statistical model of global circulation model (GCM) sub-gridcolumn moisture variability using high-resolution Moderate Resolution Imaging Spectroradiometer (MODIS) cloud data, thereby permitting parameter estimation and cloud data assimilation for large-scale models. This article performs some basic testing of this new approach, verifying that it does indeed reduce mean and standard deviation biases significantly with respect to the assimilated MODIS cloud optical depth, brightness temperature and cloud-top pressure and that it also improves the simulated rotational-Raman scattering cloud optical centroid pressure (OCP) against independent (non-assimilated) retrievals from the Ozone Monitoring Instrument (OMI). Of particular interest, the Monte Carlo method does show skill in the especially difficult case where the background state is clear but cloudy observations exist. In traditional linearized data assimilation methods, a subsaturated background cannot produce clouds via any infinitesimal equilibrium perturbation, but the Monte Carlo approach allows non-gradient-based jumps into regions of non-zero cloud probability. In the example provided, the method is able to restore marine stratocumulus near the Californian coast, where the background state has a clear swath. This article also examines a number of algorithmic and physical sensitivities of the new method and provides guidance for its cost-effective implementation. One obvious difficulty for the method, and other cloud data assimilation methods as well, is the lack of information content in passive-radiometer-retrieved cloud observables on cloud vertical structure, beyond cloud-top pressure and optical thickness, thus necessitating strong dependence on the background vertical moisture structure. It is found that a simple flow-dependent correlation modification from Riishojgaard provides some help in this respect, by better honouring inversion structures in the background state.
Norris, Peter M; da Silva, Arlindo M
2016-07-01
Part 1 of this series presented a Monte Carlo Bayesian method for constraining a complex statistical model of global circulation model (GCM) sub-gridcolumn moisture variability using high-resolution Moderate Resolution Imaging Spectroradiometer (MODIS) cloud data, thereby permitting parameter estimation and cloud data assimilation for large-scale models. This article performs some basic testing of this new approach, verifying that it does indeed reduce mean and standard deviation biases significantly with respect to the assimilated MODIS cloud optical depth, brightness temperature and cloud-top pressure and that it also improves the simulated rotational-Raman scattering cloud optical centroid pressure (OCP) against independent (non-assimilated) retrievals from the Ozone Monitoring Instrument (OMI). Of particular interest, the Monte Carlo method does show skill in the especially difficult case where the background state is clear but cloudy observations exist. In traditional linearized data assimilation methods, a subsaturated background cannot produce clouds via any infinitesimal equilibrium perturbation, but the Monte Carlo approach allows non-gradient-based jumps into regions of non-zero cloud probability. In the example provided, the method is able to restore marine stratocumulus near the Californian coast, where the background state has a clear swath. This article also examines a number of algorithmic and physical sensitivities of the new method and provides guidance for its cost-effective implementation. One obvious difficulty for the method, and other cloud data assimilation methods as well, is the lack of information content in passive-radiometer-retrieved cloud observables on cloud vertical structure, beyond cloud-top pressure and optical thickness, thus necessitating strong dependence on the background vertical moisture structure. It is found that a simple flow-dependent correlation modification from Riishojgaard provides some help in this respect, by better honouring inversion structures in the background state.
Constraints on the Profiles of Total Water PDF in AGCMs from AIRS and a High-Resolution Model
NASA Technical Reports Server (NTRS)
Molod, Andrea
2012-01-01
Atmospheric general circulation model (AGCM) cloud parameterizations generally include an assumption about the subgrid-scale probability distribution function (PDF) of total water and its vertical profile. In the present study, the Atmospheric Infrared Sounder (AIRS) monthly-mean cloud amount and relative humidity fields are used to compute a proxy for the second moment of an AGCM total water PDF called the RH01 diagnostic, which is the AIRS mean relative humidity for cloud fractions of 0.1 or less. The dependence of the second moment on horizontal grid resolution is analyzed using results from a high-resolution global model simulation.The AIRS-derived RH01 diagnostic is generally larger near the surface than aloft, indicating a narrower PDF near the surface, and varies with the type of underlying surface. High-resolution model results show that the vertical structure of profiles of the AGCM PDF second moment is unchanged as the grid resolution changes from 200 to 100 to 50 km, and that the second-moment profiles shift toward higher values with decreasing grid spacing.Several Goddard Earth Observing System, version 5 (GEOS-5), AGCM simulations were performed with several choices for the profile of the PDF second moment. The resulting cloud and relative humidity fields were shown to be quite sensitive to the prescribed profile, and the use of a profile based on the AIRS-derived proxy results in improvements relative to observational estimates. The AIRS-guided total water PDF profiles, including their dependence on underlying surface type and on horizontal resolution, have been implemented in the version of the GEOS-5 AGCM used for publicly released simulations.
NASA Astrophysics Data System (ADS)
Putman, W. M.; Suarez, M.
2009-12-01
The Goddard Earth Observing System Model (GEOS-5), an earth system model developed in the NASA Global Modeling and Assimilation Office (GMAO), has integrated the non-hydrostatic finite-volume dynamical core on the cubed-sphere grid. The extension to a non-hydrostatic dynamical framework and the quasi-uniform cubed-sphere geometry permits the efficient exploration of global weather and climate modeling at cloud permitting resolutions of 10- to 4-km on today's high performance computing platforms. We have explored a series of incremental increases in global resolution with GEOS-5 from it's standard 72-level 27-km resolution (~5.5 million cells covering the globe from the surface to 0.1 hPa) down to 3.5-km (~3.6 billion cells). We will present results from a series of forecast experiments exploring the impact of the non-hydrostatic dynamics at transition resolutions of 14- to 7-km, and the influence of increased horizontal/vertical resolution on convection and physical parameterizations within GEOS-5. Regional and mesoscale features of 5- to 10-day weather forecasts will be presented and compared with satellite observations. Our results will highlight the impact of resolution on the structure of cloud features including tropical convection and tropical cyclone predicability, cloud streets, von Karman vortices, and the marine stratocumulus cloud layer. We will also present experiment design and early results from climate impact experiments for global non-hydrostatic models using GEOS-5. Our climate experiments will focus on support for the Year of Tropical Convection (YOTC). We will also discuss a seasonal climate time-slice experiment design for downscaling coarse resolution century scale climate simulations to global non-hydrostatic resolutions of 14- to 7-km with GEOS-5.
NASA Astrophysics Data System (ADS)
Hong, Yang
Precipitation estimation from satellite information (VISIBLE , IR, or microwave) is becoming increasingly imperative because of its high spatial/temporal resolution and board coverage unparalleled by ground-based data. After decades' efforts of rainfall estimation using IR imagery as basis, it has been explored and concluded that the limitations/uncertainty of the existing techniques are: (1) pixel-based local-scale feature extraction; (2) IR temperature threshold to define rain/no-rain clouds; (3) indirect relationship between rain rate and cloud-top temperature; (4) lumped techniques to model high variability of cloud-precipitation processes; (5) coarse scales of rainfall products. As continuing studies, a new version of Precipitation Estimation from Remotely Sensed Information using Artificial Neural Network (PERSIANN), called Cloud Classification System (CCS), has been developed to cope with these limitations in this dissertation. CCS includes three consecutive components: (1) a hybrid segmentation algorithm, namely Hierarchically Topographical Thresholding and Stepwise Seeded Region Growing (HTH-SSRG), to segment satellite IR images into separated cloud patches; (2) a 3D feature extraction procedure to retrieve both pixel-based local-scale and patch-based large-scale features of cloud patch at various heights; (3) an ANN model, Self-Organizing Nonlinear Output (SONO) network, to classify cloud patches into similarity-based clusters, using Self-Organizing Feature Map (SOFM), and then calibrate hundreds of multi-parameter nonlinear functions to identify the relationship between every cloud types and their underneath precipitation characteristics using Probability Matching Method and Multi-Start Downhill Simplex optimization techniques. The model was calibrated over the Southwest of United States (100°--130°W and 25°--45°N) first and then adaptively adjusted to the study region of North America Monsoon Experiment (65°--135°W and 10°--50°N) using observations from Geostationary Operational Environmental Satellite (GOES) IR imagery, Next Generation Radar (NEXRAD) rainfall network, and Tropical Rainfall Measurement Mission (TRMM) microwave rain rate estimates. CCS functions as a distributed model that first identifies cloud patches and then dispatches different but the best matching cloud-precipitation function for each cloud patch to estimate instantaneous rain rate at high spatial resolution (4km) and full temporal resolution of GOES IR images (every 30-minute). Evaluated over a range of spatial and temporal scales, the performance of CCS compared favorably with GOES Precipitation Index (GPI), Universal Adjusted GPI (UAGPI), PERSIANN, and Auto-Estimator (AE) algorithms, consistently. Particularly, the large number of nonlinear functions and optimum IR-rain rate thresholds of CCS model are highly variable, reflecting the complexity of dominant cloud-precipitation processes from cloud patch to cloud patch over various regions. As a result, CCS can more successfully capture variability in rain rate at small scales than existing algorithms and potentially provides rainfall product from GOES IR-NEXARD-TRMM TMI (SSM/I) at 0.12° x 0.12° and 3-hour resolution with relative low standard error (˜=3.0mm/hr) and high correlation coefficient (˜=0.65).
Improved Cloud and Snow Screening in MAIAC Aerosol Retrievals Using Spectral and Spatial Analysis
NASA Technical Reports Server (NTRS)
Lyapustin, A.; Wang, Y.; Laszlo, I.; Kokrkin, S.
2012-01-01
An improved cloud/snow screening technique in the Multi-Angle Implementation of Atmospheric Correction (MAIAC) algorithm is described. It is implemented as part of MAIAC aerosol retrievals based on analysis of spectral residuals and spatial variability. Comparisons with AERONET aerosol observations and a large-scale MODIS data analysis show strong suppression of aerosol optical thickness outliers due to unresolved clouds and snow. At the same time, the developed filter does not reduce the aerosol retrieval capability at high 1 km resolution in strongly inhomogeneous environments, such as near centers of the active fires. Despite significant improvement, the optical depth outliers in high spatial resolution data are and will remain the problem to be addressed by the application-dependent specialized filtering techniques.
Diagnosing Cloud Biases in the GFDL AM3 Model With Atmospheric Classification
DOE Office of Scientific and Technical Information (OSTI.GOV)
Evans, Stuart; Marchand, Roger; Ackerman, Thomas
In this paper, we define a set of 21 atmospheric states, or recurring weather patterns, for a region surrounding the Atmospheric Radiation Measurement Program's Southern Great Plains site using an iterative clustering technique. The states are defined using dynamic and thermodynamic variables from reanalysis, tested for statistical significance with cloud radar data from the Southern Great Plains site, and are determined every 6 h for 14 years, creating a time series of atmospheric state. The states represent the various stages of the progression of synoptic systems through the region (e.g., warm fronts, warm sectors, cold fronts, cold northerly advection, andmore » high-pressure anticyclones) with a subset of states representing summertime conditions with varying degrees of convective activity. We use the states to classify output from the NOAA/Geophysical Fluid Dynamics Laboratory AM3 model to test the model's simulation of the frequency of occurrence of the states and of the cloud occurrence during each state. The model roughly simulates the frequency of occurrence of the states but exhibits systematic cloud occurrence biases. Comparison of observed and model-simulated International Satellite Cloud Climatology Project histograms of cloud top pressure and optical thickness shows that the model lacks high thin cloud under all conditions, but biases in thick cloud are state-dependent. Frontal conditions in the model do not produce enough thick cloud, while fair-weather conditions produce too much. Finally, we find that increasing the horizontal resolution of the model improves the representation of thick clouds under all conditions but has little effect on high thin clouds. However, increasing resolution also changes the distribution of states, causing an increase in total cloud occurrence bias.« less
Diagnosing Cloud Biases in the GFDL AM3 Model With Atmospheric Classification
NASA Astrophysics Data System (ADS)
Evans, Stuart; Marchand, Roger; Ackerman, Thomas; Donner, Leo; Golaz, Jean-Christophe; Seman, Charles
2017-12-01
We define a set of 21 atmospheric states, or recurring weather patterns, for a region surrounding the Atmospheric Radiation Measurement Program's Southern Great Plains site using an iterative clustering technique. The states are defined using dynamic and thermodynamic variables from reanalysis, tested for statistical significance with cloud radar data from the Southern Great Plains site, and are determined every 6 h for 14 years, creating a time series of atmospheric state. The states represent the various stages of the progression of synoptic systems through the region (e.g., warm fronts, warm sectors, cold fronts, cold northerly advection, and high-pressure anticyclones) with a subset of states representing summertime conditions with varying degrees of convective activity. We use the states to classify output from the NOAA/Geophysical Fluid Dynamics Laboratory AM3 model to test the model's simulation of the frequency of occurrence of the states and of the cloud occurrence during each state. The model roughly simulates the frequency of occurrence of the states but exhibits systematic cloud occurrence biases. Comparison of observed and model-simulated International Satellite Cloud Climatology Project histograms of cloud top pressure and optical thickness shows that the model lacks high thin cloud under all conditions, but biases in thick cloud are state-dependent. Frontal conditions in the model do not produce enough thick cloud, while fair-weather conditions produce too much. We find that increasing the horizontal resolution of the model improves the representation of thick clouds under all conditions but has little effect on high thin clouds. However, increasing resolution also changes the distribution of states, causing an increase in total cloud occurrence bias.
Diagnosing Cloud Biases in the GFDL AM3 Model With Atmospheric Classification
Evans, Stuart; Marchand, Roger; Ackerman, Thomas; ...
2017-11-16
In this paper, we define a set of 21 atmospheric states, or recurring weather patterns, for a region surrounding the Atmospheric Radiation Measurement Program's Southern Great Plains site using an iterative clustering technique. The states are defined using dynamic and thermodynamic variables from reanalysis, tested for statistical significance with cloud radar data from the Southern Great Plains site, and are determined every 6 h for 14 years, creating a time series of atmospheric state. The states represent the various stages of the progression of synoptic systems through the region (e.g., warm fronts, warm sectors, cold fronts, cold northerly advection, andmore » high-pressure anticyclones) with a subset of states representing summertime conditions with varying degrees of convective activity. We use the states to classify output from the NOAA/Geophysical Fluid Dynamics Laboratory AM3 model to test the model's simulation of the frequency of occurrence of the states and of the cloud occurrence during each state. The model roughly simulates the frequency of occurrence of the states but exhibits systematic cloud occurrence biases. Comparison of observed and model-simulated International Satellite Cloud Climatology Project histograms of cloud top pressure and optical thickness shows that the model lacks high thin cloud under all conditions, but biases in thick cloud are state-dependent. Frontal conditions in the model do not produce enough thick cloud, while fair-weather conditions produce too much. Finally, we find that increasing the horizontal resolution of the model improves the representation of thick clouds under all conditions but has little effect on high thin clouds. However, increasing resolution also changes the distribution of states, causing an increase in total cloud occurrence bias.« less
Yang, Xiaomei; Zhou, Chenghu; Li, Zhi
2017-01-01
Cloud cover is inevitable in optical remote sensing (RS) imagery on account of the influence of observation conditions, which limits the availability of RS data. Therefore, it is of great significance to be able to reconstruct the cloud-contaminated ground information. This paper presents a sparse dictionary learning-based image inpainting method for adaptively recovering the missing information corrupted by thick clouds patch-by-patch. A feature dictionary was learned from exemplars in the cloud-free regions, which was later utilized to infer the missing patches via sparse representation. To maintain the coherence of structures, structure sparsity was brought in to encourage first filling-in of missing patches on image structures. The optimization model of patch inpainting was formulated under the adaptive neighborhood-consistency constraint, which was solved by a modified orthogonal matching pursuit (OMP) algorithm. In light of these ideas, the thick-cloud removal scheme was designed and applied to images with simulated and true clouds. Comparisons and experiments show that our method can not only keep structures and textures consistent with the surrounding ground information, but also yield rare smoothing effect and block effect, which is more suitable for the removal of clouds from high-spatial resolution RS imagery with salient structures and abundant textured features. PMID:28914787
Meng, Fan; Yang, Xiaomei; Zhou, Chenghu; Li, Zhi
2017-09-15
Cloud cover is inevitable in optical remote sensing (RS) imagery on account of the influence of observation conditions, which limits the availability of RS data. Therefore, it is of great significance to be able to reconstruct the cloud-contaminated ground information. This paper presents a sparse dictionary learning-based image inpainting method for adaptively recovering the missing information corrupted by thick clouds patch-by-patch. A feature dictionary was learned from exemplars in the cloud-free regions, which was later utilized to infer the missing patches via sparse representation. To maintain the coherence of structures, structure sparsity was brought in to encourage first filling-in of missing patches on image structures. The optimization model of patch inpainting was formulated under the adaptive neighborhood-consistency constraint, which was solved by a modified orthogonal matching pursuit (OMP) algorithm. In light of these ideas, the thick-cloud removal scheme was designed and applied to images with simulated and true clouds. Comparisons and experiments show that our method can not only keep structures and textures consistent with the surrounding ground information, but also yield rare smoothing effect and block effect, which is more suitable for the removal of clouds from high-spatial resolution RS imagery with salient structures and abundant textured features.
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.
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.
A Multi-Year Data Set of Cloud Properties Derived for CERES from Aqua, Terra, and TRMM
NASA Technical Reports Server (NTRS)
Minnis, Patrick; Sunny Sun-Mack; Trepte, Quinz Z.; Yan Chen; Brown, Richard R.; Gibson, Sharon C.; Heck, Michael L.; Dong, Xiquan; Xi, Baike
2007-01-01
The Clouds and Earth's Radiant Energy System (CERES) Project is producing a suite of cloud properties from high-resolution imagers on several satellites and matching them precisely with broadband radiance data to study the influence of clouds and radiation on climate. The cloud properties generally compare well with independent validation sources. Distinct differences are found between the CERES cloud properties and those derived with other algorithms from the same imager data. CERES products will be updated beginning in late 2006.
Physical conditions in molecular clouds
NASA Technical Reports Server (NTRS)
Evans, Neal J., II
1989-01-01
Recent developments have complicated the picture of the physical conditions in molecular clouds. The discoveries of widespread emission from high-J lines of CD and 12-micron IRAS emission have revealed the presence of considerably hotter gas and dust near the surfaces of molecular clouds. These components can complicate interpretation of the bulk of the cloud gas. Commonly assumed relations between column density or mean density and cloud size are called into question by conflicting results and by consideration of selection effects. Analysis of density and density structure through molecular excitation has shown that very high densities exist in star formation regions, but unresolved structure and possible chemical effects complicate the interpretation. High resolution far-IR and submillimeter observations offer a complementary approach and are beginning to test theoretical predictions of density gradients in clouds.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Lin, Guangxing; Qian, Yun; Yan, Huiping
One limitation of most global climate models (GCMs) is that with the horizontal resolutions they typically employ, they cannot resolve the subgrid variability (SGV) of clouds and aerosols, adding extra uncertainties to the aerosol radiative forcing estimation. To inform the development of an aerosol subgrid variability parameterization, here we analyze the aerosol SGV over the southern Pacific Ocean simulated by the high-resolution Weather Research and Forecasting model coupled to Chemistry. We find that within a typical GCM grid, the aerosol mass subgrid standard deviation is 15% of the grid-box mean mass near the surface on a 1 month mean basis.more » The fraction can increase to 50% in the free troposphere. The relationships between the sea-salt mass concentration, meteorological variables, and sea-salt emission rate are investigated in both the clear and cloudy portion. Under clear-sky conditions, marine aerosol subgrid standard deviation is highly correlated with the standard deviations of vertical velocity, cloud water mixing ratio, and sea-salt emission rates near the surface. It is also strongly connected to the grid box mean aerosol in the free troposphere (between 2 km and 4 km). In the cloudy area, interstitial sea-salt aerosol mass concentrations are smaller, but higher correlation is found between the subgrid standard deviations of aerosol mass and vertical velocity. Additionally, we find that decreasing the model grid resolution can reduce the marine aerosol SGV but strengthen the correlations between the aerosol SGV and the total water mixing ratio (sum of water vapor, cloud liquid, and cloud ice mixing ratios).« less
NASA Technical Reports Server (NTRS)
Zhou, Daniel K.; Liu, Xu; Larar, Allen M.; Smith, WIlliam L.; Taylor, Jonathan P.; Schluessel, Peter; Strow, L. Larrabee; Mango, Stephen A.
2008-01-01
The Joint Airborne IASI Validation Experiment (JAIVEx) was conducted during April 2007 mainly for validation of the IASI on the MetOp satellite. IASI possesses an ultra-spectral resolution of 0.25/cm and a spectral coverage from 645 to 2760/cm. Ultra-spectral resolution infrared spectral radiance obtained from near nadir observations provide atmospheric, surface, and cloud property information. An advanced retrieval algorithm with a fast radiative transfer model, including cloud effects, is used for atmospheric profile and cloud parameter retrieval. This physical inversion scheme has been developed, dealing with cloudy as well as cloud-free radiance observed with ultraspectral infrared sounders, to simultaneously retrieve surface, atmospheric thermodynamic, and cloud microphysical parameters. A fast radiative transfer model, which applies to the cloud-free and/or clouded atmosphere, is used for atmospheric profile and cloud parameter retrieval. A one-dimensional (1-d) variational multi-variable inversion solution is used to improve an iterative background state defined by an eigenvector-regression-retrieval. The solution is iterated in order to account for non-linearity in the 1-d variational solution. It is shown that relatively accurate temperature and moisture retrievals are achieved below optically thin clouds. For optically thick clouds, accurate temperature and moisture profiles down to cloud top level are obtained. For both optically thin and thick cloud situations, the cloud top height can be retrieved with relatively high accuracy (i.e., error < 1 km). Preliminary retrievals of atmospheric soundings, surface properties, and cloud optical/microphysical properties with the IASI observations are obtained and presented. These retrievals will be further inter-compared with those obtained from airborne FTS system, such as the NPOESS Airborne Sounder Testbed - Interferometer (NAST-I), dedicated dropsondes, radiosondes, and ground based Raman Lidar. The capabilities of satellite ultra-spectral sounder such as the IASI are investigated indicating a high vertical structure of atmosphere is retrieved.
Rapid, semi-automatic fracture and contact mapping for point clouds, images and geophysical data
NASA Astrophysics Data System (ADS)
Thiele, Samuel T.; Grose, Lachlan; Samsu, Anindita; Micklethwaite, Steven; Vollgger, Stefan A.; Cruden, Alexander R.
2017-12-01
The advent of large digital datasets from unmanned aerial vehicle (UAV) and satellite platforms now challenges our ability to extract information across multiple scales in a timely manner, often meaning that the full value of the data is not realised. Here we adapt a least-cost-path solver and specially tailored cost functions to rapidly interpolate structural features between manually defined control points in point cloud and raster datasets. We implement the method in the geographic information system QGIS and the point cloud and mesh processing software CloudCompare. Using these implementations, the method can be applied to a variety of three-dimensional (3-D) and two-dimensional (2-D) datasets, including high-resolution aerial imagery, digital outcrop models, digital elevation models (DEMs) and geophysical grids. We demonstrate the algorithm with four diverse applications in which we extract (1) joint and contact patterns in high-resolution orthophotographs, (2) fracture patterns in a dense 3-D point cloud, (3) earthquake surface ruptures of the Greendale Fault associated with the Mw7.1 Darfield earthquake (New Zealand) from high-resolution light detection and ranging (lidar) data, and (4) oceanic fracture zones from bathymetric data of the North Atlantic. The approach improves the consistency of the interpretation process while retaining expert guidance and achieves significant improvements (35-65 %) in digitisation time compared to traditional methods. Furthermore, it opens up new possibilities for data synthesis and can quantify the agreement between datasets and an interpretation.
Near-Cloud Aerosol Properties from the 1 Km Resolution MODIS Ocean Product
NASA Technical Reports Server (NTRS)
Varnai, Tamas; Marshak, Alexander
2014-01-01
This study examines aerosol properties in the vicinity of clouds by analyzing high-resolution atmospheric correction parameters provided in the MODIS (Moderate Resolution Imaging Spectroradiometer) ocean color product. The study analyzes data from a 2 week long period of September in 10 years, covering a large area in the northeast Atlantic Ocean. The results indicate that on the one hand, the Quality Assessment (QA) flags of the ocean color product successfully eliminate cloud-related uncertainties in ocean parameters such as chlorophyll content, but on the other hand, using the flags introduces a sampling bias in atmospheric products such as aerosol optical thickness (AOT) and Angstrom exponent. Therefore, researchers need to select QA flags by balancing the risks of increased retrieval uncertainties and sampling biases. Using an optimal set of QA flags, the results reveal substantial increases in optical thickness near clouds-on average the increase is 50% for the roughly half of pixels within 5 km from clouds and is accompanied by a roughly matching increase in particle size. Theoretical simulations show that the 50% increase in 550nm AOT changes instantaneous direct aerosol radiative forcing by up to 8W/m2 and that the radiative impact is significantly larger if observed near-cloud changes are attributed to aerosol particles as opposed to undetected cloud particles. These results underline that accounting for near-cloud areas and understanding the causes of near-cloud particle changes are critical for accurate calculations of direct aerosol radiative forcing.
NASA Astrophysics Data System (ADS)
Lague, D.
2014-12-01
High Resolution Topographic (HRT) datasets are predominantly stored and analyzed as 2D raster grids of elevations (i.e., Digital Elevation Models). Raster grid processing is common in GIS software and benefits from a large library of fast algorithms dedicated to geometrical analysis, drainage network computation and topographic change measurement. Yet, all instruments or methods currently generating HRT datasets (e.g., ALS, TLS, SFM, stereo satellite imagery) output natively 3D unstructured point clouds that are (i) non-regularly sampled, (ii) incomplete (e.g., submerged parts of river channels are rarely measured), and (iii) include 3D elements (e.g., vegetation, vertical features such as river banks or cliffs) that cannot be accurately described in a DEM. Interpolating the raw point cloud onto a 2D grid generally results in a loss of position accuracy, spatial resolution and in more or less controlled interpolation. Here I demonstrate how studying earth surface topography and processes directly on native 3D point cloud datasets offers several advantages over raster based methods: point cloud methods preserve the accuracy of the original data, can better handle the evaluation of uncertainty associated to topographic change measurements and are more suitable to study vegetation characteristics and steep features of the landscape. In this presentation, I will illustrate and compare Point Cloud based and Raster based workflows with various examples involving ALS, TLS and SFM for the analysis of bank erosion processes in bedrock and alluvial rivers, rockfall statistics (including rockfall volume estimate directly from point clouds) and the interaction of vegetation/hydraulics and sedimentation in salt marshes. These workflows use 2 recently published algorithms for point cloud classification (CANUPO) and point cloud comparison (M3C2) now implemented in the open source software CloudCompare.
Nocturnal low-level clouds over southern West Africa analysed using high-resolution simulations
NASA Astrophysics Data System (ADS)
Adler, Bianca; Kalthoff, Norbert; Gantner, Leonhard
2017-01-01
We performed a high-resolution numerical simulation to study the development of extensive low-level clouds that frequently form over southern West Africa during the monsoon season. This study was made in preparation for a field campaign in 2016 within the Dynamics-aerosol-chemistry-cloud interactions in West Africa (DACCIWA) project and focuses on an area around the city of Savè in southern Benin. Nocturnal low-level clouds evolve a few hundred metres above the ground around the same level as a distinct low-level jet. Several processes are found to determine the spatio-temporal evolution of these clouds including (i) significant cooling of the nocturnal atmosphere caused by horizontal advection with the south-westerly monsoon flow during the first half of the night, (ii) vertical cold air advection due to gravity waves leading to clouds in the wave crests and (iii) enhanced convergence and upward motion upstream of existing clouds that trigger new clouds. The latter is caused by an upward shift of the low-level jet in cloudy areas leading to horizontal convergence in the lower part and to horizontal divergence in the upper part of the cloud layer. Although this single case study hardly allows for a generalisation of the processes found, the results added to the optimisation of the measurements strategy for the field campaign and the observations will be used to test the hypotheses for cloud formation resulting from this study.
Structurally Resolved Abundances and Depletions in the Rho OPH Cloud
NASA Astrophysics Data System (ADS)
Seab, C.
1995-07-01
The mechanism that determines the pattern of depletion ofelements in the interstellar medium has been a problem for along time. It is clear that some of the most refractoryelements such as Si, Fe, and Mg, are heavily depleted onto theinterstellar grains. On the other hand, some elements such asS and Zn are normally either undepleted or very lightlydepleted. The difference between the two cases is notunderstood. We propose to address this question with adetailed study of the depletion patterns in the Rho Ophiuchicloud. This study is strongly based on a combination of thecapabilities of two modern instruments: the GHRS for high-resolution UV data, and the Ultra High Resolution Facility(UHRF) of the AAT. This instrument has been used to obtain NaI line profiles in the Rho Oph cloud with a resolution ofR=1,000,000. The combination of these two types of data willbe used to resolve the velocity structure of the elementdepletions in the cloud.
NASA Astrophysics Data System (ADS)
Lamer, K.; Fridlind, A. M.; Luke, E. P.; Tselioudis, G.; Ackerman, A. S.; Kollias, P.; Clothiaux, E. E.
2016-12-01
The presence of supercooled liquid in clouds affects surface radiative and hydrological budgets, especially at high latitudes. Capturing these effects is crucial to properly quantifying climate sensitivity. Currently, a number of CGMs disagree on the distribution of cloud phase. Adding to the challenge is a general lack of observations on the continuum of clouds, from high to low-level and from warm to cold. In the current study, continuous observations from 2011 to 2014 are used to evaluate all clouds produced by the GISS ModelE GCM over the ARM North Slope of Alaska site. The International Satellite Cloud Climatology Project (ISCCP) Global Weather State (GWS) approach reveals that fair-weather (GWS 7, 32% occurrence rate), as well as mid-level storm related (GWS 5, 28%) and polar (GWS 4, 14%) clouds, dominate the large-scale cloud patterns at this high latitude site. At higher spatial and temporal resolutions, ground-based cloud radar observations reveal a majority of single layer cloud vertical structures (CVS). While clear sky and low-level clouds dominate (each with 30% occurrence rate) a fair amount of shallow ( 10%) to deep ( 5%) convection are observed. Cloud radar Doppler spectra are used along with depolarization lidar observations in a neural network approach to detect the presence, layering and inhomogeneity of supercooled liquid layers. Preliminary analyses indicate that most of the low-level clouds sampled contain one or more supercooled liquid layers. Furthermore, the relationship between CVS and the presence of supercooled liquid is established, as is the relationship between the presence of supercool liquid and precipitation susceptibility. Two approaches are explored to bridge the gap between large footprint GCM simulations and high-resolution ground-based observations. The first approach consists of comparing model output and ground-based observations that exhibit the same column CVS type (i.e. same cloud depth, height and layering). Alternatively, the second approach consists of comparing model output and ground-based observations that exhibit the same large-scale GWS type (i.e. same cloud top pressure and optical depth patterns) where ground-based observations are associated to large-scale GWS every 3 hours using the closest satellite overpass.
NASA Astrophysics Data System (ADS)
Fomin, Boris; Falaleeva, Victoria
2016-07-01
A polarized high-resolution 1-D model has been presented for TIR (Thermal Infrared) remote sensing application. It is based on the original versions of MC (Monte Carlo) and LbL (Line-by-Line) algorithms, which have shown their effectiveness when modelling the thermal radiation atmospheric transfer, taking into account, the semi-transparent Ci-type and polar clouds scattering, as well as the direct consideration of the spectra of molecular absorption. This model may be useful in the planning of satellite experiments and in the validation of similar models, which use the "k-distribution" or other approximations, to account for gaseous absorption. The example simulations demonstrate that, the selective gas absorption does not only significantly affect the absorption and emission of radiation, but also, its polarization in the Ci-type clouds. As a result, the spectra of polarized radiation contain important information about the clouds, and а high-resolution polarized limb sounding in the TIR, seems to be a useful tool in obtaining information on cloud types and their vertical structures.
Simulating return signals of a spaceborne high-spectral resolution lidar channel at 532 nm
NASA Astrophysics Data System (ADS)
Xiao, Yu; Binglong, Chen; Min, Min; Xingying, Zhang; Lilin, Yao; Yiming, Zhao; Lidong, Wang; Fu, Wang; Xiaobo, Deng
2018-06-01
High spectral resolution lidar (HSRL) system employs a narrow spectral filter to separate the particulate (cloud/aerosol) and molecular scattering components in lidar return signals, which improves the quality of the retrieved cloud/aerosol optical properties. To better develop a future spaceborne HSRL system, a novel simulation technique was developed to simulate spaceborne HSRL return signals at 532 nm using the Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO) cloud/aerosol extinction coefficients product and numerical weather prediction data. For validating simulated data, a mathematical particulate extinction coefficient retrieval method for spaceborne HSRL return signals is described here. We compare particulate extinction coefficient profiles from the CALIPSO operational product with simulated spaceborne HSRL data. Further uncertainty analysis shows that relative uncertainties are acceptable for retrieving the optical properties of cloud and aerosol. The final results demonstrate that they agree well with each other. It indicates that the return signals of the spaceborne HSRL molecular channel at 532 nm will be suitable for developing operational algorithms supporting a future spaceborne HSRL system.
NASA Technical Reports Server (NTRS)
Grund, C. J.; Eloranta, E. W.
1990-01-01
The High Spectral Resolution Lidar (HSRL) was operated from a roof-top site in Madison, Wisconsin. The transmitter configuration used to acquire the case study data produces about 50 mW of ouput power and achieved eye-safe, direct optical depth, and backscatter cross section measurements with 10 min averaging times. A new continuously pumped, injection seeded, frequency doubled Nd:YAG laser transmitter reduces time-averaging constraints by a factor of about 10, while improving the aerosol-molecular signal separation capabilities and wavelength stability of the instrument. The cirrus cloud backscatter-phase functions have been determined for the October 27-28, 1986 segment of the HSRL FIRE dataset. Features exhibiting backscatter cross sections ranging over four orders of magnitude have been observed within this 33 h period. During this period, cirrus clouds were observed with optical thickness ranging from 0.01 to 1.4. The altitude relationship between cloud top and bottom boundaries and the optical center of the cloud is influenced by the type of formation observed.
NASA Technical Reports Server (NTRS)
Duda, David P.; Khlopenkov, Konstantin V.; Thiemann, Mandana; Palikonda, Rabindra; Sun-Mack, Sunny; Minnis, Patrick; Su, Wenying
2016-01-01
With the launch of the Deep Space Climate Observatory (DSCOVR), new estimates of the daytime Earth radiation budget can be computed from a combination of measurements from the two Earth-observing sensors onboard the spacecraft, the Earth Polychromatic Imaging Camera (EPIC) and the National Institute of Standards and Technology Advanced Radiometer (NISTAR). Although these instruments can provide accurate top-of-atmosphere (TOA) radiance measurements, they lack sufficient resolution to provide details on small-scale surface and cloud properties. Previous studies have shown that these properties have a strong influence on the anisotropy of the radiation at the TOA, and ignoring such effects can result in large TOA-flux errors. To overcome these effects, high-resolution scene identification is needed for accurate Earth radiation budget estimation. Selected radiance and cloud property data measured and derived from several low earth orbit (LEO, including NASA Terra and Aqua MODIS, NOAA AVHRR) and geosynchronous (GEO, including GOES (east and west), METEOSAT, INSAT-3D, MTSAT-2, and HIMAWARI-8) satellite imagers were collected to create hourly 5-km resolution global composites of data necessary to compute angular distribution models (ADM) for reflected shortwave (SW) and longwave (LW) radiation. The satellite data provide an independent source of radiance measurements and scene identification information necessary to construct ADMs that are used to determine the daytime Earth radiation budget. To optimize spatial matching between EPIC measurements and the high-resolution composite cloud properties, LEO/GEO retrievals within the EPIC fields of view (FOV) are convolved to the EPIC point spread function (PSF) in a similar manner to the Clouds and the Earth's Radiant Energy System (CERES) Single Scanner Footprint TOA/Surface Fluxes and Clouds (SSF) product. Examples of the merged LEO/GEO/EPIC product will be presented, describing the chosen radiance and cloud properties and details of how data from the multi-satellite measurements are selected.
NASA Astrophysics Data System (ADS)
Duda, D. P.; Khlopenkov, K. V.; Palikonda, R.; Khaiyer, M. M.; Minnis, P.; Su, W.; Sun-Mack, S.
2016-12-01
With the launch of the Deep Space Climate Observatory (DSCOVR), new estimates of the daytime Earth radiation budget can computed from a combination of measurements from the two Earth-observing sensors onboard the spacecraft, the Earth Polychromatic Imaging Camera (EPIC) and the National Institute of Standards and Technology Advanced Radiometer (NISTAR). Although these instruments can provide accurate top-of-atmosphere (TOA) radiance measurements, they lack sufficient resolution to provide details on small-scale surface and cloud properties. Previous studies have shown that these properties have a strong influence on the anisotropy of the radiation at the TOA, and ignoring such effects can result in large TOA-flux errors. To overcome these effects, high-resolution scene identification is needed for accurate Earth radiation budget estimation. Selected radiance and cloud property data measured and derived from several low earth orbit (LEO, including NASA Terra and Aqua MODIS, NOAA AVHRR) and geosynchronous (GEO, including GOES (east and west), METEOSAT, INSAT-3D, MTSAT-2, and HIMAWARI-8) satellite imagers were collected to create hourly 5-km resolution global composites of data necessary to compute angular distribution models (ADM) for reflected shortwave (SW) and longwave (LW) radiation. The satellite data provide an independent source of radiance measurements and scene identification information necessary to construct ADMs that are used to determine the daytime Earth radiation budget. To optimize spatial matching between EPIC measurements and the high-resolution composite cloud properties, LEO/GEO retrievals within the EPIC fields of view (FOV) are convolved to the EPIC point spread function (PSF) in a similar manner to the Clouds and the Earth's Radiant Energy System (CERES) Single Scanner Footprint TOA/Surface Fluxes and Clouds (SSF) product. Examples of the merged LEO/GEO/EPIC product will be presented, describing the chosen radiance and cloud properties and details of how data from the multi-satellite measurements are selected.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Zhang, Guang; Fan, Jiwen; Xu, Kuan-Man
2015-06-01
Arakawa and Wu (2013, hereafter referred to as AW13) recently developed a formal approach to a unified parameterization of atmospheric convection for high-resolution numerical models. The work is based on ideas formulated by Arakawa et al. (2011). It lays the foundation for a new parameterization pathway in the era of high-resolution numerical modeling of the atmosphere. The key parameter in this approach is convective cloud fraction. In conventional parameterization, it is assumed that <<1. This assumption is no longer valid when horizontal resolution of numerical models approaches a few to a few tens kilometers, since in such situations convective cloudmore » fraction can be comparable to unity. Therefore, they argue that the conventional approach to parameterizing convective transport must include a factor 1 - in order to unify the parameterization for the full range of model resolutions so that it is scale-aware and valid for large convective cloud fractions. While AW13’s approach provides important guidance for future convective parameterization development, in this note we intend to show that the conventional approach already has this scale awareness factor 1 - built in, although not recognized for the last forty years. Therefore, it should work well even in situations of large convective cloud fractions in high-resolution numerical models.« less
NASA Astrophysics Data System (ADS)
Zhou, Y.; Tao, W.; Hou, A. Y.; Zeng, X.; Shie, C.
2007-12-01
The cloud and precipitation statistics simulated by 3D Goddard Cumulus Ensemble (GCE) model for different environmental conditions, i.e., the South China Sea Monsoon Experiment (SCSMEX), CRYSTAL-FACE, and KAWJEX are compared with Tropical Rainfall Measuring Mission (TRMM) TMI and PR rainfall measurements and as well as cloud observations from the Earth's Radiant Energy System (CERES) and the Moderate Resolution Imaging Spectroradiometer (MODIS) instruments. It is found that GCE is capable of simulating major convective system development and reproducing total surface rainfall amount as compared with rainfall estimated from the soundings. The model presents large discrepancies in rain spectrum and vertical hydrometer profiles. The discrepancy in the precipitation field is also consistent with the cloud and radiation observations. The study will focus on the effects of large scale forcing and microphysics to the simulated model- observation discrepancies.
NASA Astrophysics Data System (ADS)
Kelly, M. A.; Boldt, J.; Wilson, J. P.; Yee, J. H.; Stoffler, R.
2017-12-01
The multi-spectral STereo Atmospheric Remote Sensing (STARS) concept has the objective to provide high-spatial and -temporal-resolution observations of 3D cloud structures related to hurricane development and other severe weather events. The rapid evolution of severe weather demonstrates a critical need for mesoscale observations of severe weather dynamics, but such observations are rare, particularly over the ocean where extratropical and tropical cyclones can undergo explosive development. Coincident space-based measurements of wind velocity and cloud properties at the mesoscale remain a great challenge, but are critically needed to improve the understanding and prediction of severe weather and cyclogenesis. STARS employs a mature stereoscopic imaging technique on two satellites (e.g. two CubeSats, two hosted payloads) to simultaneously retrieve cloud motion vectors (CMVs), cloud-top temperatures (CTTs), and cloud geometric heights (CGHs) from multi-angle, multi-spectral observations of cloud features. STARS is a pushbroom system based on separate wide-field-of-view co-boresighted multi-spectral cameras in the visible, midwave infrared (MWIR), and longwave infrared (LWIR) with high spatial resolution (better than 1 km). The visible system is based on a pan-chromatic, low-light imager to resolve cloud structures under nighttime illumination down to ¼ moon. The MWIR instrument, which is being developed as a NASA ESTO Instrument Incubator Program (IIP) project, is based on recent advances in MWIR detector technology that requires only modest cooling. The STARS payload provides flexible options for spaceflight due to its low size, weight, power (SWaP) and very modest cooling requirements. STARS also meets AF operational requirements for cloud characterization and theater weather imagery. In this paper, an overview of the STARS concept, including the high-level sensor design, the concept of operations, and measurement capability will be presented.
Direct Observations of Isoprene Secondary Organic Aerosol Formation in Ambient Cloud Droplets
NASA Astrophysics Data System (ADS)
Zelenyuk, A.; Bell, D.; Thornton, J. A.; Fast, J. D.; Shrivastava, M. B.; Berg, L. K.; Imre, D. G.; Mei, F.; Shilling, J.; Suski, K. J.; Liu, J.; Tomlinson, J. M.; Wang, J.
2017-12-01
Multiphase chemistry of isoprene photooxidation products has been shown to be one of the major sources of secondary organic aerosol (SOA) in the atmosphere. A number of recent studies indicate that aqueous aerosol phase provides a medium for reactive uptake of isoprene photooxidation products, and in particular, isomeric isoprene epoxydiols (IEPOX), with reaction rates and yields being dependent on aerosol acidity, water content, sulfate concentration, and organic coatings. However, very few studies focused on chemistry occurring within actual cloud droplets. We will present data acquired during recent Holistic Interactions of Shallow Clouds, Aerosols, and Land Ecosystems (HI-SCALE) Campaign, which provide direct evidence for IEPOX-SOA formation in cloud droplets. Single particle mass spectrometer, miniSPLAT, and a high-resolution, time-of-flight aerosol mass spectrometer were used to characterize the composition of aerosol particles and cloud droplet residuals, while a high-resolution, time-of-flight chemical ionization mass spectrometer (HR-ToF-CIMS) was used to characterize gas-phase compounds. We find that the composition of cloud droplet residuals was markedly different than that of aerosol particles sampled outside the cloud. Cloud droplet residuals were comprised of individual particles with high relative fractions of sulfate and nitrate and significant fraction of particles with mass spectra that are nearly identical to those of laboratory-generated IEPOX-SOA particles. The observed cloud-induced formation of IEPOX-SOA was accompanied by simultaneous decrease in measured concentrations of IEPOX and other gas-phase isoprene photooxidation products. Ultimately, the combined cloud, aerosol, and gas-phase measurements conducted during HI-SCALE will be used to develop and evaluate model treatments of aqueous-phase isoprene SOA formation.
NASA Astrophysics Data System (ADS)
Trishchenko, Alexander P.; Khlopenkov, Konstantin V.; Wang, Shusen; Luo, Yi; Kruzelecky, Roman V.; Jamroz, Wes; Kroupnik, Guennadi
2007-10-01
Among all trace gases, the carbon dioxide and methane provide the largest contribution to the climate radiative forcing and together with carbon monoxide also to the global atmospheric carbon budget. New Micro Earth Observation Satellite (MEOS) mission is proposed to obtain information about these gases along with some other mission's objectives related to studying cloud and aerosol interactions. The miniature suit of instruments is proposed to make measurements with reduced spectral resolution (1.2nm) over wide NIR range 0.9μm to 2.45μm and with high spectral resolution (0.03nm) for three selected regions: oxygen A-band, 1.5μm-1.7μm band and 2.2μm-2.4μm band. It is also planned to supplement the spectrometer measurements with high spatial resolution imager for detailed characterization of cloud and surface albedo distribution within spectrometer field of view. The approaches for cloud/clear-sky identification and column retrievals of above trace gases are based on differential absorption technique and employ the combination of coarse and high-resolution spectral data. The combination of high and coarse resolution spectral data is beneficial for better characterization of surface spectral albedo and aerosol effects. An additional capability for retrieval of the vertical distribution amounts is obtained from the combination of nadir and limb measurements. Oxygen A-band path length will be used for normalization of trace gas retrievals.
Study on ice cloud optical thickness retrieval with MODIS IR spectral bands
NASA Astrophysics Data System (ADS)
Zhang, Hong; Li, Jun
2005-01-01
The operational Moderate-Resolution Imaging Spectroradiometer (MODIS) products for cloud properties such as cloud-top pressure (CTP), effective cloud amount (ECA), cloud particle size (CPS), cloud optical thickness (COT), and cloud phase (CP) have been available for users globally. An approach to retrieve COT is investigated using MODIS infrared (IR) window spectral bands (8.5 mm, 11mm, and 12 mm). The COT retrieval from MODIS IR bands has the potential to provide microphysical properties with high spatial resolution during night. The results are compared with those from operational MODIS products derived from the visible (VIS) and near-infrared (NIR) bands during day. Sensitivity of COT to MODIS spectral brightness temperature (BT) and BT difference (BTD) values is studied. A look-up table is created from the cloudy radiative transfer model accounting for the cloud absorption and scattering for the cloud microphysical property retrieval. The potential applications and limitations are also discussed. This algorithm can be applied to the future imager systems such as Visible/Infrared Imager/Radiometer Suite (VIIRS) on the National Polar-orbiting Operational Environmental Satellite System (NPOESS) and Advanced Baseline Imager (ABI) on the Geostationary Operational Environmental Satellite (GOES)-R.
NASA Technical Reports Server (NTRS)
Platnick, Steven E.
2010-01-01
Though the emphasis of the Southern Africa Regional Science Initiative 2000 (SAFARI-2000) dry season campaign was largely on emission sources and transport, the assemblage of aircraft (including the high altitude NASA ER-2 remote sensing platform and the University of Washington CV-580, UK MRF C-130, and South African Weather Bureau JRA in situ aircrafts) provided a unique opportunity for cloud studies. Therefore, as part of the SAFARI initiative, investigations were undertaken to assess regional aerosol-cloud interactions and cloud remote sensing algorithms. In particular, the latter part of the experiment concentrated on marine boundary layer stratocumulus clouds off the southwest coast of Africa. Associated with cold water upwelling along the Benguela current, the Namibian stratocumulus regime has received limited attention but appears to be unique for several reasons. During the dry season, outflow of continental fires and industrial pollution over this area can be extreme. From below, upwelling provides a rich nutrient source for phytoplankton (a source of atmospheric sulfur through DMS production as well as from decay processes). The impact of these natural and anthropogenic sources on the microphysical and optical properties of the stratocumulus is unknown. Continental and Indian Ocean cloud systems of opportunity were also studied during the campaign. SAFARI 2000 aircraft flights off the coast of Namibia were coordinated with NASA Terra Satellite overpasses for synergy with the Moderate Resolution Imaging Spectroradiometer (MODIS) and other Terra instruments. MODIS was developed by NASA and launched onboard the Terra spacecraft on December 18, 1999 (and Aqua spacecraft on May 4, 2002). Among the remote sensing algorithms developed and applied to this sensor are cloud optical and microphysical properties that include cloud thermodynamic phase, optical thickness, and effective particle radius of both liquid water and ice clouds. The archived products from these algorithms have applications in climate change studies, climate modeling, numerical weather prediction, and fundamental atmospheric research. The archived MODIS Collection 5 cloud products processing stream will be used to analyze low water cloud scenes off the Namibian and Angolan coasts during SAFARI 2000 time period, as well as other years. Pixel-level Terra and Aqua MODIS retrievals (l. km spatial resolution at nadir) and gridded (1' uniform grid) statistics of cloud optical thickness and effective particle radius will be presented, including joint probability distributions between the two quantities. In addition, perspectives from the MODIS Airborne Simulator, which flew on the ER-2 during SAFARI 2000 providing high spatial resolution retrievals (50 m at nadir), will be presented as appropriate. The H-SAF Program requires an experimental operational European-centric Satellite Precipitation Algorithm System (E-SPAS) that produces medium spatial resolution and high temporal resolution surface rainfall and snowfall estimates over the Greater European Region including the Greater Mediterranean Basin. Currently, there are various types of experimental operational algorithm methods of differing spatiotemporal resolutions that generate global precipitation estimates. This address will first assess the current status of these methods and then recommend a methodology for the H-SAF Program that deviates somewhat from the current approach under development but one that takes advantage of existing techniques and existing software developed for the TRMM Project and available through the public domain.
NASA Astrophysics Data System (ADS)
Ai, Yufei; Li, Jun; Shi, Wenjing; Schmit, Timothy J.; Cao, Changyong; Li, Wanbiao
2017-02-01
Deep convective storms have contributed to airplane accidents, making them a threat to aviation safety. The most common method to identify deep convective clouds (DCCs) is using the brightness temperature difference (BTD) between the atmospheric infrared (IR) window band and the water vapor (WV) absorption band. The effectiveness of the BTD method for DCC detection is highly related to the spectral resolution and signal-to-noise ratio (SNR) of the WV band. In order to understand the sensitivity of BTD to spectral resolution and SNR for DCC detection, a BTD to noise ratio method using the difference between the WV and IR window radiances is developed to assess the uncertainty of DCC identification for different instruments. We examined the case of AirAsia Flight QZ8501. The brightness temperatures (Tbs) over DCCs from this case are simulated for BTD sensitivity studies by a fast forward radiative transfer model with an opaque cloud assumption for both broadband imager (e.g., Multifunction Transport Satellite imager, MTSAT-2 imager) and hyperspectral IR sounder (e.g., Atmospheric Infrared Sounder) instruments; we also examined the relationship between the simulated Tb and the cloud top height. Results show that despite the coarser spatial resolution, BTDs measured by a hyperspectral IR sounder are much more sensitive to high cloud tops than broadband BTDs. As demonstrated in this study, a hyperspectral IR sounder can identify DCCs with better accuracy.
Retrieval of Cloud Properties for Partially Cloud-Filled Pixels During CRYSTAL-FACE
NASA Astrophysics Data System (ADS)
Nguyen, L.; Minnis, P.; Smith, W. L.; Khaiyer, M. M.; Heck, P. W.; Sun-Mack, S.; Uttal, T.; Comstock, J.
2003-12-01
Partially cloud-filled pixels can be a significant problem for remote sensing of cloud properties. Generally, the optical depth and effective particle sizes are often too small or too large, respectively, when derived from radiances that are assumed to be overcast but contain radiation from both clear and cloud areas within the satellite imager field of view. This study presents a method for reducing the impact of such partially cloud field pixels by estimating the cloud fraction within each pixel using higher resolution visible (VIS, 0.65mm) imager data. Although the nominal resolution for most channels on the Geostationary Operational Environmental Satellite (GOES) imager and the Moderate Resolution Imaging Spectroradiometer (MODIS) on Terra are 4 and 1 km, respectively, both instruments also take VIS channel data at 1 km and 0.25 km, respectively. Thus, it may be possible to obtain an improved estimate of cloud fraction within the lower resolution pixels by using the information contained in the higher resolution VIS data. GOES and MODIS multi-spectral data, taken during the Cirrus Regional Study of Tropical Anvils and Cirrus Layers - Florida Area Cirrus Experiment (CRYSTAL-FACE), are analyzed with the algorithm used for the Atmospheric Radiation Measurement Program (ARM) and the Clouds and Earth's Radiant Energy System (CERES) to derive cloud amount, temperature, height, phase, effective particle size, optical depth, and water path. Normally, the algorithm assumes that each pixel is either entirely clear or cloudy. In this study, a threshold method is applied to the higher resolution VIS data to estimate the partial cloud fraction within each low-resolution pixel. The cloud properties are then derived from the observed low-resolution radiances using the cloud cover estimate to properly extract the radiances due only to the cloudy part of the scene. This approach is applied to both GOES and MODIS data to estimate the improvement in the retrievals for each resolution. Results are compared with the radar reflectivity techniques employed by the NOAA ETL MMCR and the PARSL 94 GHz radars located at the CRYSTAL-FACE Eastern & Western Ground Sites, respectively. This technique is most likely to yield improvements for low and midlevel layer clouds that have little thermal variability in cloud height.
NASA Astrophysics Data System (ADS)
de Michele, Marcello; Raucoules, Daniel; Corradini, Stefano; Merucci, Luca; spinetti, claudia
2017-04-01
Accurate and spatially-detailed knowledge of Volcanic Cloud Top Height (VCTH) and velocity is crucial in volcanology. As an example, the ash/gas dispersion in the atmosphere, their impact and lifetime around the globe, greatly depends on the injection altitude. The VCTH is critical for ash dispersion modelling and air traffic security. Furthermore, the volcanic plume height during explosive volcanism is the primary parameter for estimating mass eruption rate. Satellite remote sensing offers a comprehensive and safe way to estimate VCTH. Recently, it has been shown that high spatial resolution optical imagery from Landsat-8 OLI sensor can be used to extract Volcanic Cloud Top Height with a precision of 250 meters and an accuracy or 300m (de Michele et al., 2016). This method allows to extract a Plume Elevation Model (PEM) by jointly measuring the parallax between two optical bands acquired with a time lag varying from 0.1 to 2.5 seconds depending on the bands chosen and the sensors employed. The measure of the parallax is biased because the volcanic cloud is moving between the two images acquisitions, even if the time lag is short. The precision of our measurements is enhanced by compensating the parallax by measuring the velocity of the volcanic cloud in the perpendicular-to-epipolar direction (which is height independent) and correcting the initial parallax measurement. In this study, we push this methodology forward. We apply it to the very high spatial resolution Pleiades data (1m pixel spacing) provided by the French Space Agency (CNES). We apply the method on Mount Etna, during the 05 September 2015 eruptive episode and on Mount Ontake eruption occurring on 30 September 2014. We are able to extract VCTH as a PEM with high spatial resolution and improved precision. Since Pléiades has an improved revisit time (1day), our method has potential for routine monitoring of volcanic plumes in clear sky conditions and when the VCTH is higher than meteo clouds.
Global cloud database from VIRS and MODIS for CERES
NASA Astrophysics Data System (ADS)
Minnis, Patrick; Young, David F.; Wielicki, Bruce A.; Sun-Mack, Sunny; Trepte, Qing Z.; Chen, Yan; Heck, Patrick W.; Dong, Xiquan
2003-04-01
The NASA CERES Project has developed a combined radiation and cloud property dataset using the CERES scanners and matched spectral data from high-resolution imagers, the Visible Infrared Scanner (VIRS) on the Tropical Rainfall Measuring Mission (TRMM) satellite and the Moderate Resolution Imaging Spectroradiometer (MODIS) on Terra and Aqua. The diurnal cycle can be well-characterized over most of the globe using the combinations of TRMM, Aqua, and Terra data. The cloud properties are derived from the imagers using state-of-the-art methods and include cloud fraction, height, optical depth, phase, effective particle size, emissivity, and ice or liquid water path. These cloud products are convolved into the matching CERES fields of view to provide simultaneous cloud and radiation data at an unprecedented accuracy. Results are available for at least 3 years of VIRS data and 1 year of Terra MODIS data. The various cloud products are compared with similar quantities from climatological sources and instantaneous active remote sensors. The cloud amounts are very similar to those from surface observer climatologies and are 6-7% less than those from a satellite-based climatology. Optical depths are 2-3 times smaller than those from the satellite climatology, but are within 5% of those from the surface remote sensing. Cloud droplet sizes and liquid water paths are within 10% of the surface results on average for stratus clouds. The VIRS and MODIS retrievals are very consistent with differences that usually can be explained by sampling, calibration, or resolution differences. The results should be extremely valuable for model validation and improvement and for improving our understanding of the relationship between clouds and the radiation budget.
From large-eddy simulation to multi-UAVs sampling of shallow cumulus clouds
NASA Astrophysics Data System (ADS)
Lamraoui, Fayçal; Roberts, Greg; Burnet, Frédéric
2016-04-01
In-situ sampling of clouds that can provide simultaneous measurements at satisfying spatio-temporal resolutions to capture 3D small scale physical processes continues to present challenges. This project (SKYSCANNER) aims at bringing together cloud sampling strategies using a swarm of unmanned aerial vehicles (UAVs) based on Large-eddy simulation (LES). The multi-UAV-based field campaigns with a personalized sampling strategy for individual clouds and cloud fields will significantly improve the understanding of the unresolved cloud physical processes. An extensive set of LES experiments for case studies from ARM-SGP site have been performed using MesoNH model at high resolutions down to 10 m. The carried out simulations led to establishing a macroscopic model that quantifies the interrelationship between micro- and macrophysical properties of shallow convective clouds. Both the geometry and evolution of individual clouds are critical to multi-UAV cloud sampling and path planning. The preliminary findings of the current project reveal several linear relationships that associate many cloud geometric parameters to cloud related meteorological variables. In addition, the horizontal wind speed indicates a proportional impact on cloud number concentration as well as triggering and prolonging the occurrence of cumulus clouds. In the framework of the joint collaboration that involves a Multidisciplinary Team (including institutes specializing in aviation, robotics and atmospheric science), this model will be a reference point for multi-UAVs sampling strategies and path planning.
High-Resolution Imaging of the Multiphase Interstellar Thick Disk in Two Edge-On Spiral Galaxies
NASA Astrophysics Data System (ADS)
Howk, J. Christopher; Rueff, K.
2009-01-01
We present broadband and narrow-band images, acquired from Hubble Space Telescope WFPC2 and WIYN 3.5 m telescope respectively, of two edge-on spiral galaxies, NGC 4302 and NGC 4013. These high-resolution images (BVI + H-alpha) provide a detailed view of the thick disk interstellar medium (ISM) in these galaxies. Both galaxies show prominent extraplanar dust-bearing clouds viewed in absorption against the background stellar light. Individual clouds are found to z 2 kpc in each galaxy. These clouds each contain >10^4 to >10^5 solar masses of gas. Both galaxies have extraplanar diffuse ionized gas (DIG), as seen in our H-alpha images and earlier work. In addition to the DIG, discrete H II regions are found at heights up to 1 kpc from both galaxies. We compare the morphologies of the dusty clouds with the DIG in these galaxies and discuss the relationship between these components of the thick disk ISM.
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
Cloud optical properties from satellites over Europe: CM SAF vs CERES
NASA Astrophysics Data System (ADS)
Konstantinou, Athanasia; Alexandri, Georgia; Balis, Dimitris
2017-04-01
In this work, the macro and micro physical properties of liquid and ice clouds over Europe are examined for the 8-year period 2004-2011. For the scopes of this research, high resolution (0.05x0.05 degree) satellite-based observations from CM SAF (Satellite Application Facility on Climate Monitoring) and coarse resolution (1x1 degree) data from CERES (Clouds and the Earth's Radiant Energy System) are utilized. The spatial and temporal patterns of the bias between the two products are examined. It is found that the difference between CM SAF and CERES cloud fractional cover (CFC) is 10% while cloud optical thickness (COT) from CM SAF is generally lower than CERES by 10 %. The effective radius of liquid (Rel) and ice (Rei) clouds is also examined. For the region of interest, CM SAF Rel is 12% higher while CM SAF Rei is lower by 20% than that of CERES. Intercomparison studies like the one presented here help us to get an insight into the capabilities and limitation of the cloud satellite products which are currently in use by the scientific community.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Bogenschutz, Peter; Moeng, Chin-Hoh
2015-10-13
The PI’s at the National Center for Atmospheric Research (NCAR), Chin-Hoh Moeng and Peter Bogenschutz, have primarily focused their time on the implementation of the Simplified-Higher Order Turbulence Closure (SHOC; Bogenschutz and Krueger 2013) to the Multi-scale Modeling Framework (MMF) global model and testing of SHOC on deep convective cloud regimes.
Dynamical Zodiacal Cloud Models Constrained by High Resolution Spectroscopy of the Zodiacal Light
NASA Technical Reports Server (NTRS)
Ipatov, S. I.; Kutyrev, A. S.; Madsen, G. J.; Mather, J. C.; Moseley, S. H.; Reynolds, R. J.
2005-01-01
We have developed a set of self-consistent dynamical models of the Zodiacal cloud, following the orbital evolution of dust particles. Three populations were considered, originating from the Kuiper belt, asteroids and comets. Using the models developed, we investigated how the solar spectrum is changed by scattering by the zodiacal cloud grains and compared the obtained spectra with the observations.
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).
A synthetic data set of high-spectral-resolution infrared spectra for the Arctic atmosphere
NASA Astrophysics Data System (ADS)
Cox, Christopher J.; Rowe, Penny M.; Neshyba, Steven P.; Walden, Von P.
2016-05-01
Cloud microphysical and macrophysical properties are critical for understanding the role of clouds in climate. These properties are commonly retrieved from ground-based and satellite-based infrared remote sensing instruments. However, retrieval uncertainties are difficult to quantify without a standard for comparison. This is particularly true over the polar regions, where surface-based data for a cloud climatology are sparse, yet clouds represent a major source of uncertainty in weather and climate models. We describe a synthetic high-spectral-resolution infrared data set that is designed to facilitate validation and development of cloud retrieval algorithms for surface- and satellite-based remote sensing instruments. Since the data set is calculated using pre-defined cloudy atmospheres, the properties of the cloud and atmospheric state are known a priori. The atmospheric state used for the simulations is drawn from radiosonde measurements made at the North Slope of Alaska (NSA) Atmospheric Radiation Measurement (ARM) site at Barrow, Alaska (71.325° N, 156.615° W), a location that is generally representative of the western Arctic. The cloud properties for each simulation are selected from statistical distributions derived from past field measurements. Upwelling (at 60 km) and downwelling (at the surface) infrared spectra are simulated for 260 cloudy cases from 50 to 3000 cm-1 (3.3 to 200 µm) at monochromatic (line-by-line) resolution at a spacing of ˜ 0.01 cm-1 using the Line-by-line Radiative Transfer Model (LBLRTM) and the discrete-ordinate-method radiative transfer code (DISORT). These spectra are freely available for interested researchers from the NSF Arctic Data Center data repository (doi:10.5065/D61J97TT).
NASA Technical Reports Server (NTRS)
Savage, Blair D.; Cardelli, Jason A.; Sofia, Ulysses J.
1992-01-01
Goddard High Resolution Spectrograph echelle mode measurements at 3.5 km/s resolution are presented for interstellar absorption produced by C II, O I, Mg I, Mg II, Al III, P II, Cr II, Mn II, Fe II, Ni II, Cu II, Zn II, Ga II, Ge II, and Kr I. The absorption line measurements are converted into representations of apparent column density per unit velocity in order to study the multicomponent nature of the absorption. The high spectral resolution of the measurements allows a comparative study of gas phase abundances for many species in the absorbing clouds near -27 and -15 km/s with a typical precision of about 0.05 dex. The matter absorbing near -27 km/s is situated in the local interstellar medium and has log N(H I) of about 19.74. This absorption provides information about the modest 'base' depletion associated with the lower density interstellar medium. The depletion results suggest that accretion processes are operating interstellar clouds that exhibit similar depletion efficiencies for some elements but much higher depletion efficiencies for others.
Cloud feedback mechanisms and their representation in global climate models
Ceppi, Paulo; Brient, Florent; Zelinka, Mark D.; ...
2017-05-11
Cloud feedback—the change in top-of-atmosphere radiative flux resulting from the cloud response to warming—constitutes by far the largest source of uncertainty in the climate response to CO 2 forcing simulated by global climate models (GCMs). In this paper, we review the main mechanisms for cloud feedbacks, and discuss their representation in climate models and the sources of intermodel spread. Global-mean cloud feedback in GCMs results from three main effects: (1) rising free-tropospheric clouds (a positive longwave effect); (2) decreasing tropical low cloud amount (a positive shortwave [SW] effect); (3) increasing high-latitude low cloud optical depth (a negative SW effect). Thesemore » cloud responses simulated by GCMs are qualitatively supported by theory, high-resolution modeling, and observations. Rising high clouds are consistent with the fixed anvil temperature (FAT) hypothesis, whereby enhanced upper-tropospheric radiative cooling causes anvil cloud tops to remain at a nearly fixed temperature as the atmosphere warms. Tropical low cloud amount decreases are driven by a delicate balance between the effects of vertical turbulent fluxes, radiative cooling, large-scale subsidence, and lower-tropospheric stability on the boundary-layer moisture budget. High-latitude low cloud optical depth increases are dominated by phase changes in mixed-phase clouds. Finally, the causes of intermodel spread in cloud feedback are discussed, focusing particularly on the role of unresolved parameterized processes such as cloud microphysics, turbulence, and convection.« less
Cloud feedback mechanisms and their representation in global climate models
DOE Office of Scientific and Technical Information (OSTI.GOV)
Ceppi, Paulo; Brient, Florent; Zelinka, Mark D.
Cloud feedback—the change in top-of-atmosphere radiative flux resulting from the cloud response to warming—constitutes by far the largest source of uncertainty in the climate response to CO 2 forcing simulated by global climate models (GCMs). In this paper, we review the main mechanisms for cloud feedbacks, and discuss their representation in climate models and the sources of intermodel spread. Global-mean cloud feedback in GCMs results from three main effects: (1) rising free-tropospheric clouds (a positive longwave effect); (2) decreasing tropical low cloud amount (a positive shortwave [SW] effect); (3) increasing high-latitude low cloud optical depth (a negative SW effect). Thesemore » cloud responses simulated by GCMs are qualitatively supported by theory, high-resolution modeling, and observations. Rising high clouds are consistent with the fixed anvil temperature (FAT) hypothesis, whereby enhanced upper-tropospheric radiative cooling causes anvil cloud tops to remain at a nearly fixed temperature as the atmosphere warms. Tropical low cloud amount decreases are driven by a delicate balance between the effects of vertical turbulent fluxes, radiative cooling, large-scale subsidence, and lower-tropospheric stability on the boundary-layer moisture budget. High-latitude low cloud optical depth increases are dominated by phase changes in mixed-phase clouds. Finally, the causes of intermodel spread in cloud feedback are discussed, focusing particularly on the role of unresolved parameterized processes such as cloud microphysics, turbulence, and convection.« less
NASA Technical Reports Server (NTRS)
da Silva, Arlindo M.; Norris, Peter M.
2013-01-01
Part I presented a Monte Carlo Bayesian method for constraining a complex statistical model of GCM sub-gridcolumn moisture variability using high-resolution MODIS cloud data, thereby permitting large-scale model parameter estimation and cloud data assimilation. This part performs some basic testing of this new approach, verifying that it does indeed significantly reduce mean and standard deviation biases with respect to the assimilated MODIS cloud optical depth, brightness temperature and cloud top pressure, and that it also improves the simulated rotational-Ramman scattering cloud optical centroid pressure (OCP) against independent (non-assimilated) retrievals from the OMI instrument. Of particular interest, the Monte Carlo method does show skill in the especially difficult case where the background state is clear but cloudy observations exist. In traditional linearized data assimilation methods, a subsaturated background cannot produce clouds via any infinitesimal equilibrium perturbation, but the Monte Carlo approach allows finite jumps into regions of non-zero cloud probability. In the example provided, the method is able to restore marine stratocumulus near the Californian coast where the background state has a clear swath. This paper also examines a number of algorithmic and physical sensitivities of the new method and provides guidance for its cost-effective implementation. One obvious difficulty for the method, and other cloud data assimilation methods as well, is the lack of information content in the cloud observables on cloud vertical structure, beyond cloud top pressure and optical thickness, thus necessitating strong dependence on the background vertical moisture structure. It is found that a simple flow-dependent correlation modification due to Riishojgaard (1998) provides some help in this respect, by better honoring inversion structures in the background state.
NASA Technical Reports Server (NTRS)
1995-01-01
The theoretical bases for the Release 1 algorithms that will be used to process satellite data for investigation of the Clouds and Earth's Radiant Energy System (CERES) are described. The architecture for software implementation of the methodologies is outlined. Volume 3 details the advanced CERES methods for performing scene identification and inverting each CERES scanner radiance to a top-of-the-atmosphere (TOA) flux. CERES determines cloud fraction, height, phase, effective particle size, layering, and thickness from high-resolution, multispectral imager data. CERES derives cloud properties for each pixel of the Tropical Rainfall Measuring Mission (TRMM) visible and infrared scanner and the Earth Observing System (EOS) moderate-resolution imaging spectroradiometer. Cloud properties for each imager pixel are convolved with the CERES footprint point spread function to produce average cloud properties for each CERES scanner radiance. The mean cloud properties are used to determine an angular distribution model (ADM) to convert each CERES radiance to a TOA flux. The TOA fluxes are used in simple parameterization to derive surface radiative fluxes. This state-of-the-art cloud-radiation product will be used to substantially improve our understanding of the complex relationship between clouds and the radiation budget of the Earth-atmosphere system.
Comparison of CERES Cloud Properties Derived from Aqua and Terra MODIS Data and TRMM VIRS Radiances
NASA Astrophysics Data System (ADS)
Minnis, P.; Young, D. F.; Sun-Mack, S.; Trepte, Q. Z.; Chen, Y.; Heck, P. W.; Wielicki, B. A.
2003-12-01
The Clouds and Earth's Radiant Energy System (CERES) Project is obtaining Earth radiation budget measurements of unprecedented accuracy as a result of improved instruments and an analysis system that combines simultaneous, high-resolution cloud property retrievals with the broadband radiance data. The cloud properties are derived from three different satellite imagers: the Visible Infrared Scanner (VIRS) on the Tropical Rainfall Measuring Mission (TRMM) and the Moderate Resolution Imaging Spectroradiometers (MODIS) on the Aqua and Terra satellites. A single set of consistent algorithms using the 0.65, 1.6 or 2.1, 3.7, 10.8, and 12.0-æm channels are applied to all three imagers. The cloud properties include, cloud coverage, height, thickness, temperature, optical depth, phase, effective particle size, and liquid or ice water path. Because each satellite is in a different orbit, the results provide information on the diurnal cycle of cloud properties. Initial intercalibrations show excellent consistency between the three images except for some differences of ~ 1K between the 3.7-æm channel on Terra and those on VIRS and Aqua. The derived cloud properties are consistent with the known diurnal characteristics of clouds in different areas. These datasets should be valuable for exploring the role of clouds in the radiation budget and hydrological cycle.
Influence of Meteorological Regimes on Cloud Microphysics Over Ross Island, Antarctica
NASA Astrophysics Data System (ADS)
Glennon, C.; Wang, S. H.; Scott, R. C.; Bromwich, D. H.; Lubin, D.
2017-12-01
The Antarctic provides a sharp contrast in cloud microphysics from the high Arctic, due to orographic lifting and resulting strong vertical motions induced by mountain ranges and other varying terrain on several spatial scales. The Atmospheric Radiation Measurement (ARM) West Antarctic Radiation Experiment (AWARE) deployed advanced cloud remote sensing equipment to Ross Island, Antarctica, from December 2015 until January 2016. This equipment included scanning and zenith radars operating in the Ka and X bands, a high spectral resolution lidar (HSRL), and a polarized micropulse lidar (MPL). A major AWARE objective is to provide state-of-the-art data for improving cloud microphysical parameterizations in climate models. To further this objective we have organized and classified the local Ross Island meteorology into distinct regimes using k-means clustering on ERA-Interim reanalysis data. We identify synoptic categories producing unique regimes of cloud cover and cloud microphysical properties over Ross Island. Each day of observations can then be associated with a specific meteorological regime, thus assisting modelers with identifying case studies. High-resolution (1 km) weather forecasts from the Antarctic Mesoscale Prediction System (AMPS) are sorted into these categories. AMPS-simulated anomalies of cloud fraction, near-surface air temperature, and vertical velocity at 500-mb are composited and compared with ground-based radar and lidar-derived cloud properties to identify mesoscale meteorological processes driving Antarctic cloud formation. Synoptic lows over the Ross and Amundsen Seas drive anomalously warm conditions at Ross Island by injecting marine air masses inland over the West Antarctic Ice Sheet (WAIS). This results in ice and mixed-phase orographic cloud systems arriving at Ross Island from the south to southeast along the Transantarctic Mountains. In contrast, blocking over the Amundsen Sea region brings classical liquid-dominated mixed-phase and thin liquid water clouds from the Southern Ocean. Low pressure systems over the Bellingshausen Sea produce outflow of cold, dry continental polar air, yielding predominantly tenuous ice cloud at Ross Island.
NASA Technical Reports Server (NTRS)
Fisher, Brad; Joiner, Joanna; Vasilkov, Alexander; Veefkind, Pepijn; Platnick, Steven; Wind, Galina
2014-01-01
Clouds cover approximately 60% of the earth's surface. When obscuring the satellite's field of view (FOV), clouds complicate the retrieval of ozone, trace gases and aerosols from data collected by earth observing satellites. Cloud properties associated with optical thickness, cloud pressure, water phase, drop size distribution (DSD), cloud fraction, vertical and areal extent can also change significantly over short spatio-temporal scales. The radiative transfer models used to retrieve column estimates of atmospheric constituents typically do not account for all these properties and their variations. The OMI science team is preparing to release a new data product, OMMYDCLD, which combines the cloud information from sensors on board two earth observing satellites in the NASA A-Train: Aura/OMI and Aqua/MODIS. OMMYDCLD co-locates high resolution cloud and radiance information from MODIS onto the much larger OMI pixel and combines it with parameters derived from the two other OMI cloud products: OMCLDRR and OMCLDO2. The product includes histograms for MODIS scientific data sets (SDS) provided at 1 km resolution. The statistics of key data fields - such as effective particle radius, cloud optical thickness and cloud water path - are further separated into liquid and ice categories using the optical and IR phase information. OMMYDCLD offers users of OMI data cloud information that will be useful for carrying out OMI calibration work, multi-year studies of cloud vertical structure and in the identification and classification of multi-layer clouds.
ALMA Observations of a Quiescent Molecular Cloud in the Large Magellanic Cloud
NASA Astrophysics Data System (ADS)
Wong, Tony; Hughes, Annie; Tokuda, Kazuki; Indebetouw, Rémy; Bernard, Jean-Philippe; Onishi, Toshikazu; Wojciechowski, Evan; Bandurski, Jeffrey B.; Kawamura, Akiko; Roman-Duval, Julia; Cao, Yixian; Chen, C.-H. Rosie; Chu, You-hua; Cui, Chaoyue; Fukui, Yasuo; Montier, Ludovic; Muller, Erik; Ott, Juergen; Paradis, Deborah; Pineda, Jorge L.; Rosolowsky, Erik; Sewiło, Marta
2017-12-01
We present high-resolution (subparsec) observations of a giant molecular cloud in the nearest star-forming galaxy, the Large Magellanic Cloud. ALMA Band 6 observations trace the bulk of the molecular gas in 12CO(2-1) and the high column density regions in 13CO(2-1). Our target is a quiescent cloud (PGCC G282.98-32.40, which we refer to as the “Planck cold cloud” or PCC) in the southern outskirts of the galaxy where star formation activity is very low and largely confined to one location. We decompose the cloud into structures using a dendrogram and apply an identical analysis to matched-resolution cubes of the 30 Doradus molecular cloud (located near intense star formation) for comparison. Structures in the PCC exhibit roughly 10 times lower surface density and five times lower velocity dispersion than comparably sized structures in 30 Dor, underscoring the non-universality of molecular cloud properties. In both clouds, structures with relatively higher surface density lie closer to simple virial equilibrium, whereas lower surface-density structures tend to exhibit supervirial line widths. In the PCC, relatively high line widths are found in the vicinity of an infrared source whose properties are consistent with a luminous young stellar object. More generally, we find that the smallest resolved structures (“leaves”) of the dendrogram span close to the full range of line widths observed across all scales. As a result, while the bulk of the kinetic energy is found on the largest scales, the small-scale energetics tend to be dominated by only a few structures, leading to substantial scatter in observed size-line-width relationships.
Low cost, high performance processing of single particle cryo-electron microscopy data in the cloud.
Cianfrocco, Michael A; Leschziner, Andres E
2015-05-08
The advent of a new generation of electron microscopes and direct electron detectors has realized the potential of single particle cryo-electron microscopy (cryo-EM) as a technique to generate high-resolution structures. Calculating these structures requires high performance computing clusters, a resource that may be limiting to many likely cryo-EM users. To address this limitation and facilitate the spread of cryo-EM, we developed a publicly available 'off-the-shelf' computing environment on Amazon's elastic cloud computing infrastructure. This environment provides users with single particle cryo-EM software packages and the ability to create computing clusters with 16-480+ CPUs. We tested our computing environment using a publicly available 80S yeast ribosome dataset and estimate that laboratories could determine high-resolution cryo-EM structures for $50 to $1500 per structure within a timeframe comparable to local clusters. Our analysis shows that Amazon's cloud computing environment may offer a viable computing environment for cryo-EM.
Ubiquity and impact of thin mid-level clouds in the tropics
Bourgeois, Quentin; Ekman, Annica M. L.; Igel, Matthew R.; Krejci, Radovan
2016-01-01
Clouds are crucial for Earth's climate and radiation budget. Great attention has been paid to low, high and vertically thick tropospheric clouds such as stratus, cirrus and deep convective clouds. However, much less is known about tropospheric mid-level clouds as these clouds are challenging to observe in situ and difficult to detect by remote sensing techniques. Here we use Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) satellite observations to show that thin mid-level clouds (TMLCs) are ubiquitous in the tropics. Supported by high-resolution regional model simulations, we find that TMLCs are formed by detrainment from convective clouds near the zero-degree isotherm. Calculations using a radiative transfer model indicate that tropical TMLCs have a cooling effect on climate that could be as large in magnitude as the warming effect of cirrus. We conclude that more effort has to be made to understand TMLCs, as their influence on cloud feedbacks, heat and moisture transport, and climate sensitivity could be substantial. PMID:27530236
Ubiquity and impact of thin mid-level clouds in the tropics.
Bourgeois, Quentin; Ekman, Annica M L; Igel, Matthew R; Krejci, Radovan
2016-08-17
Clouds are crucial for Earth's climate and radiation budget. Great attention has been paid to low, high and vertically thick tropospheric clouds such as stratus, cirrus and deep convective clouds. However, much less is known about tropospheric mid-level clouds as these clouds are challenging to observe in situ and difficult to detect by remote sensing techniques. Here we use Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) satellite observations to show that thin mid-level clouds (TMLCs) are ubiquitous in the tropics. Supported by high-resolution regional model simulations, we find that TMLCs are formed by detrainment from convective clouds near the zero-degree isotherm. Calculations using a radiative transfer model indicate that tropical TMLCs have a cooling effect on climate that could be as large in magnitude as the warming effect of cirrus. We conclude that more effort has to be made to understand TMLCs, as their influence on cloud feedbacks, heat and moisture transport, and climate sensitivity could be substantial.
NASA Astrophysics Data System (ADS)
Barrera Verdejo, M.; Crewell, S.; Loehnert, U.; Di Girolamo, P.
2016-12-01
Continuous monitoring of thermodynamic atmospheric profiles is important for many applications, e.g. assessment of atmospheric stability and cloud formation. Nowadays there is a wide variety of ground-based sensors for atmospheric profiling. However, no single instrument is able to simultaneously provide measurements with complete vertical coverage, high vertical and temporal resolution, and good performance under all weather conditions. For this reason, instrument synergies of a wide range of complementary measurements are more and more considered for improving the quality of atmospheric observations. The current work presents synergetic use of a microwave radiometer (MWR) and Raman lidar (RL) within a physically consistent optimal estimation approach. On the one hand, lidar measurements provide humidity and temperature measurements with a high vertical resolution albeit with limited vertical coverage, due to overlapping function problems, sunlight contamination and the presence of clouds. On the other hand, MWRs obtain humidity, temperature and cloud information throughout the troposphere, with however only a very limited vertical resolution. The benefits of MWR+RL synergy have been previously demonstrated for clear sky cases. This work expands this approach to cloudy scenarios. Consistent retrievals of temperature, absolute and relative humidity as well as liquid water path are analyzed. In addition, different measures are presented to demonstrate the improvements achieved via the synergy compared to individual retrievals, e.g. degrees of freedom or theoretical error. We also demonstrate that, compared to the lidar, the higher temporal resolution of the MWR presents a strong advantage for capturing the high temporal variability of the liquid water cloud.. Finally, the results are compared with independent information sources, e.g. GPS or radiosondes, showing good consistency. The study demonstrates the benefits of the sensor combination, being especially strong in regions where lidar data is not available, whereas if both instruments are available, the lidar measurements dominate the retrieval.
NASA Technical Reports Server (NTRS)
Putnam, William M.
2011-01-01
Earth system models like the Goddard Earth Observing System model (GEOS-5) have been pushing the limits of large clusters of multi-core microprocessors, producing breath-taking fidelity in resolving cloud systems at a global scale. GPU computing presents an opportunity for improving the efficiency of these leading edge models. A GPU implementation of GEOS-5 will facilitate the use of cloud-system resolving resolutions in data assimilation and weather prediction, at resolutions near 3.5 km, improving our ability to extract detailed information from high-resolution satellite observations and ultimately produce better weather and climate predictions
NASA Astrophysics Data System (ADS)
Ticehurst, C. J.; Bartsch, A.; Doubkova, M.; van Dijk, A. I. J. M.
2009-11-01
Continuous flood monitoring can support emergency response, water management and environmental monitoring. Optical sensors such as MODIS allow inundation mapping with high spatial and temporal resolution (250-1000 m, twice daily) but are affected by cloud cover. Passive microwave sensors also acquire observations at high temporal resolution, but coarser spatial resolution (e.g. ca. 5-70 km for AMSR-E) and smaller footprints are also affected by cloud and/or rain. ScanSAR systems allow all-weather monitoring but require spatial resolution to be traded off against coverage and/or temporal resolution; e.g. the ENVISAT ASAR Global Mode observes at ca. 1 km over large regions about twice a week. The complementary role of the AMSR-E and ASAR GM data to that of MODIS is here introduced for three flood events and locations across Australia. Additional improvements can be made by integrating digital elevation models and stream flow gauging data.
Cloud-Top Entrainment in Stratocumulus Clouds
NASA Astrophysics Data System (ADS)
Mellado, Juan Pedro
2017-01-01
Cloud entrainment, the mixing between cloudy and clear air at the boundary of clouds, constitutes one paradigm for the relevance of small scales in the Earth system: By regulating cloud lifetimes, meter- and submeter-scale processes at cloud boundaries can influence planetary-scale properties. Understanding cloud entrainment is difficult given the complexity and diversity of the associated phenomena, which include turbulence entrainment within a stratified medium, convective instabilities driven by radiative and evaporative cooling, shear instabilities, and cloud microphysics. Obtaining accurate data at the required small scales is also challenging, for both simulations and measurements. During the past few decades, however, high-resolution simulations and measurements have greatly advanced our understanding of the main mechanisms controlling cloud entrainment. This article reviews some of these advances, focusing on stratocumulus clouds, and indicates remaining challenges.
Satellite-derived vertical profiles of temperature and dew point for mesoscale weather forecast
NASA Astrophysics Data System (ADS)
Masselink, Thomas; Schluessel, P.
1995-12-01
Weather forecast-models need spatially high resolutioned vertical profiles of temperature and dewpoint for their initialisation. These profiles can be supplied by a combination of data from the Tiros-N Operational Vertical Sounder (TOVS) and the imaging Advanced Very High Resolution Radiometer (AVHRR) on board the NOAA polar orbiting sate!- lites. In cloudy cases the profiles derived from TOVS data only are of insufficient accuracy. The stanthrd deviations from radiosonde ascents or numerical weather analyses likely exceed 2 K in temperature and 5Kin dewpoint profiles. It will be shown that additional cloud information as retrieved from AVHIRR allows a significant improvement in theaccuracy of vertical profiles. The International TOVS Processing Package (ITPP) is coupled to an algorithm package called AVHRR Processing scheme Over cLouds, Land and Ocean (APOLLO) where parameters like cloud fraction and cloud-top temperature are determined with higher accuracy than obtained from TOVS retrieval alone. Furthermore, a split-window technique is applied to the cloud-free AVHRR imagery in order to derive more accurate surface temperatures than can be obtained from the pure TOVS retrieval. First results of the impact of AVHRR cloud detection on the quality of the profiles are presented. The temperature and humidity profiles of different retrieval approaches are validated against analyses of the European Centre for Medium-Range Weatherforecasts.
OT1_mputman_1: ASCII: All Sky observations of Galactic CII
NASA Astrophysics Data System (ADS)
Putman, M.
2010-07-01
The Milky Way and other galaxies require a significant source of ongoing star formation fuel to explain their star formation histories. A new ubiquitous population of discrete, cold clouds have recently been discovered at the disk-halo interface of our Galaxy that could potentially provide this source of fuel. We propose to observe a small sample of these disk-halo clouds with HIFI to determine if the level of [CII] emission detected suggests they represent the cooling of warm clouds at the interface between the star forming disk and halo. These cooling clouds are predicted by simulations of warm clouds moving into the disk-halo interface region. We target 5 clouds in this proposal for which we have high resolution HI maps and can observe the densest core of the cloud. The results of our observations will also be used to interpret the surprisingly high detections of [CII] for low HI column density clouds in the Galactic Plane by the GOT C+ Key Program by extending the clouds probed to high latitude environments.
A comparison of measured radiances from AIRS and HIRS across different cloud types
NASA Astrophysics Data System (ADS)
Schreier, M. M.; Kahn, B. H.; Staten, P.
2015-12-01
The observation of Earth's atmosphere with passive remote sensing instruments is ongoing for decades and resulting in a long-term global dataset. Two prominent examples are operational satellite platforms from the National Oceanic and Atmospheric Administration (NOAA) or research platforms like NASA's Earth Observing System (EOS). The observed spectral ranges of these observations are often similar among the different platforms, but have large differences when it comes to resolution, accuracy and quality control. Our approach is to combine different kinds of instruments at the pixel-scale to improve the characterization of infrared radiances. We focus on data from the High-resolution Infrared Radiation Sounder (HIRS) and compare the observations to radiances from the Atmospheric Infrared Sounder (AIRS) on Aqua. The high spectral resolution of AIRS is used to characterize and possibly recalibrate the observed radiances from HIRS. Our approach is unique in that we use additional information from other passive instruments on the same platforms including the Advanced Very High Resolution Radiometer (AVHRR) and the MODerate resolution Imaging Spectroradiometer (MODIS). We will present comparisons of radiances from HIRS and AIRS within different types of clouds that are determined from the imagers. In this way, we can analyze and select the most homogeneous conditions for radiance comparisons and a possible re-calibration of HIRS. We hope to achieve a cloud-type-dependent calibration and quality control for HIRS, which can be extrapolated into the past via inter-calibration of the different HIRS instruments beyond the time of AIRS.
Secondary organic aerosol (SOA) is a substantial component of total atmospheric organic particulate matter, but little is known about the composition of SOA formed through cloud processing. We conducted aqueous phase photooxidation experiments of methylglyoxal and hydroxyl radica...
NASA Astrophysics Data System (ADS)
Norris, P. M.; da Silva, A. M., Jr.
2016-12-01
Norris and da Silva recently published a method to constrain a statistical model of sub-gridcolumn moisture variability using high-resolution satellite cloud data. The method can be used for large-scale model parameter estimation or cloud data assimilation (CDA). The gridcolumn model includes assumed-PDF intra-layer horizontal variability and a copula-based inter-layer correlation model. The observables used are MODIS cloud-top pressure, brightness temperature and cloud optical thickness, but the method should be extensible to direct cloudy radiance assimilation for a small number of channels. The algorithm is a form of Bayesian inference with a Markov chain Monte Carlo (MCMC) approach to characterizing the posterior distribution. This approach is especially useful in cases where the background state is clear but cloudy observations exist. In traditional linearized data assimilation methods, a subsaturated background cannot produce clouds via any infinitesimal equilibrium perturbation, but the Monte Carlo approach is not gradient-based and allows jumps into regions of non-zero cloud probability. In the example provided, the method is able to restore marine stratocumulus near the Californian coast where the background state has a clear swath. The new approach not only significantly reduces mean and standard deviation biases with respect to the assimilated observables, but also improves the simulated rotational-Ramman scattering cloud optical centroid pressure against independent (non-assimilated) retrievals from the OMI instrument. One obvious difficulty for the method, and other CDA methods, is the lack of information content in passive cloud observables on cloud vertical structure, beyond cloud-top and thickness, thus necessitating strong dependence on the background vertical moisture structure. It is found that a simple flow-dependent correlation modification due to Riishojgaard is helpful, better honoring inversion structures in the background state.
NASA Technical Reports Server (NTRS)
Alexandrov, Mikhail D.; Cairns, Brian; Emde, Claudia; Ackerman, Andrew S.; Ottaviani, Matteo; Wasilewski, Andrzej P.
2016-01-01
The Research Scanning Polarimeter (RSP) is an airborne instrument, whose measurements have been extensively used for retrievals of microphysical properties of clouds. In this study we show that for cumulus clouds the information content of the RSP data can be extended by adding the macroscopic parameters of the cloud, such as its geometric shape, dimensions, and height above the ground. This extension is possible by virtue of the high angular resolution and high frequency of the RSP measurements, which allow for geometric constraint of the cloud's 2D cross section between a number of tangent lines of view. The retrieval method is tested on realistic 3D radiative transfer simulations and applied to actual RSP data.
High resolution radiometric measurements of convective storms during the GATE experiment
NASA Technical Reports Server (NTRS)
Fowler, G.; Lisa, A. S.
1976-01-01
Using passive microwave data from the NASA CV-990 aircraft and radar data collected during the Global Atmospheric Research Program Atlantic Tropical Experiment (GATE), an empirical model was developed relating brightness temperatures sensed at 19.35 GHz to surface rainfall rates. This model agreed well with theoretical computations of the relationship between microwave radiation and precipitation in the tropics. The GATE aircraft microwave data was then used to determine the detailed structure of convective systems. The high spatial resolution of the data permitted identification of individual cells which retained unique identities throughout their lifetimes in larger cloud masses and allowed analysis of the effects of cloud merger.
NASA Technical Reports Server (NTRS)
Molthan, Andrew L.; Case, Jonathan L.; Venner, Jason; Moreno-Madrinan, Max. J.; Delgado, Francisco
2012-01-01
Over the past two years, scientists in the Earth Science Office at NASA fs Marshall Space Flight Center (MSFC) have explored opportunities to apply cloud computing concepts to support near real ]time weather forecast modeling via the Weather Research and Forecasting (WRF) model. Collaborators at NASA fs Short ]term Prediction Research and Transition (SPoRT) Center and the SERVIR project at Marshall Space Flight Center have established a framework that provides high resolution, daily weather forecasts over Mesoamerica through use of the NASA Nebula Cloud Computing Platform at Ames Research Center. Supported by experts at Ames, staff at SPoRT and SERVIR have established daily forecasts complete with web graphics and a user interface that allows SERVIR partners access to high resolution depictions of weather in the next 48 hours, useful for monitoring and mitigating meteorological hazards such as thunderstorms, heavy precipitation, and tropical weather that can lead to other disasters such as flooding and landslides. This presentation will describe the framework for establishing and providing WRF forecasts, example applications of output provided via the SERVIR web portal, and early results of forecast model verification against available surface ] and satellite ]based observations.
NASA Astrophysics Data System (ADS)
Molthan, A.; Case, J.; Venner, J.; Moreno-Madriñán, M. J.; Delgado, F.
2012-12-01
Over the past two years, scientists in the Earth Science Office at NASA's Marshall Space Flight Center (MSFC) have explored opportunities to apply cloud computing concepts to support near real-time weather forecast modeling via the Weather Research and Forecasting (WRF) model. Collaborators at NASA's Short-term Prediction Research and Transition (SPoRT) Center and the SERVIR project at Marshall Space Flight Center have established a framework that provides high resolution, daily weather forecasts over Mesoamerica through use of the NASA Nebula Cloud Computing Platform at Ames Research Center. Supported by experts at Ames, staff at SPoRT and SERVIR have established daily forecasts complete with web graphics and a user interface that allows SERVIR partners access to high resolution depictions of weather in the next 48 hours, useful for monitoring and mitigating meteorological hazards such as thunderstorms, heavy precipitation, and tropical weather that can lead to other disasters such as flooding and landslides. This presentation will describe the framework for establishing and providing WRF forecasts, example applications of output provided via the SERVIR web portal, and early results of forecast model verification against available surface- and satellite-based observations.
Global distributions of cloud properties for CERES
NASA Astrophysics Data System (ADS)
Sun-Mack, S.; Minnis, P.; Heck, P.; Young, D.
2003-04-01
The microphysical and macrophysical properties of clouds play a crucial role in the earth's radiation budget. Simultaneous measurement of the radiation and cloud fields on a global basis has long been recognized as a key component in understanding and modeling the interaction between clouds and radiation at the top of the atmosphere, at the surface, and within the atmosphere. With the implementation of the NASA Clouds and Earth's Radiant Energy System (CERES) in 1998, this need is being met. Broadband shortwave and longwave radiance measurements taken by the CERES scanners at resolutions between 10 and 20 km on the Tropical Rainfall Measuring Mission (TRMM), Terra, and Aqua satellites are matched to simultaneous retrievals of cloud height, phase, particle size, water path, and optical depth from the TRMM Visible Infrared Scanner and the Moderate Resolution Imaging Spectroradiometer (MODIS) on Terra and Aqua. The combined cloud-radiation product has already been used for developing new, highly accurate anisotropic directional models for converting broadband radiances to flux. They also provide a consistent measure of cloud properties at different times of day over the globe since January 1998. These data will be valuable for determining the indirect effects of aerosols and for linking cloud water to cloud radiation. This paper provides an overview of the CERES cloud products from the three satellites including the retrieval methodology, validation, and global distributions. Availability and access to the datasets will also be discussed.
NASA Astrophysics Data System (ADS)
Szantai, Andre; Audouard, Joachim; Madeleine, Jean-Baptiste; Forget, Francois; Pottier, Alizée; Millour, Ehouarn; Gondet, Brigitte; Langevin, Yves; Bibring, Jean-Pierre
2016-10-01
The mapping in space and time of water ice clouds can help to explain the Martian water cycle and atmospheric circulation. For this purpose, an ice cloud index (ICI) corresponding to the depth of a water ice absorption band at 3.4 microns is derived from a series of OMEGA images (spectels) covering 5 Martian years. The ICI values for the corresponding pixels are then binned on a high-resolution regular grid (1° longitude x 1° latitude x 5° Ls x 1 h local time) and averaged. Inside each bin, the cloud cover is calculated by dividing the number of pixels considered as cloudy (after comparison to a threshold) to the number of all (valid) pixelsWe compare the maps of clouds obtained around local time 14:00 with collocated TES cloud observations (which were only obtained around this time of the day). A good agreement is found.Averaged ICI compared to the water ice column variable from the Martian Climate Database (MCD) show a correct correlation (~0.5) , which increases when values limited to the tropics only are compared.The number of gridpoints containing ICI values is small ( ~1%), but by taking several neighbor gridpoints and over longer periods, we can observe a cloud life cycle during daytime. An example in the the tropics, around the northern summer solstice, shows a decrease of cloudiness in the morning followed by an increase in the afternoon.
Cloud masking and removal in remote sensing image time series
NASA Astrophysics Data System (ADS)
Gómez-Chova, Luis; Amorós-López, Julia; Mateo-García, Gonzalo; Muñoz-Marí, Jordi; Camps-Valls, Gustau
2017-01-01
Automatic cloud masking of Earth observation images is one of the first required steps in optical remote sensing data processing since the operational use and product generation from satellite image time series might be hampered by undetected clouds. The high temporal revisit of current and forthcoming missions and the scarcity of labeled data force us to cast cloud screening as an unsupervised change detection problem in the temporal domain. We introduce a cloud screening method based on detecting abrupt changes along the time dimension. The main assumption is that image time series follow smooth variations over land (background) and abrupt changes will be mainly due to the presence of clouds. The method estimates the background surface changes using the information in the time series. In particular, we propose linear and nonlinear least squares regression algorithms that minimize both the prediction and the estimation error simultaneously. Then, significant differences in the image of interest with respect to the estimated background are identified as clouds. The use of kernel methods allows the generalization of the algorithm to account for higher-order (nonlinear) feature relations. After the proposed cloud masking and cloud removal, cloud-free time series at high spatial resolution can be used to obtain a better monitoring of land cover dynamics and to generate more elaborated products. The method is tested in a dataset with 5-day revisit time series from SPOT-4 at high resolution and with Landsat-8 time series. Experimental results show that the proposed method yields more accurate cloud masks when confronted with state-of-the-art approaches typically used in operational settings. In addition, the algorithm has been implemented in the Google Earth Engine platform, which allows us to access the full Landsat-8 catalog and work in a parallel distributed platform to extend its applicability to a global planetary scale.
NASA Astrophysics Data System (ADS)
Wang, Yang; Zhao, Chuanfeng
2016-04-01
Clouds play essential roles in the Earth's energy and water cycle, and Cloud Fraction (CF) is one of the most important cloud parameters. The CF from Moderate Resolution Imaging Spectroradiometer (MODIS) has been widely used, whereas the time representation of these instantaneous CF values is not clear. In this study, we evaluate MODIS-derived CF by using continuous, day-and-night radar/lidar CF from the Atmospheric Radiation Measurement (ARM) program Active Remote Sensing of CLouds (ARSCL) product and the total sky cover (TSC) day-time CF datasets. Inter-comparisons between MODIS and surface CFs for time period from 2000 to 2011 are performed for three climate regimes as represented by the ARM sites of Southern Great Plains (SGP), Manus, Papua New Guinea (PNG) and North Slope of Alaska (NSA). We first choose both the TSC and ARSCL CFs averaged over 1 hour around the two passing time of satellite, which are around 10:30 AM and 1:30 PM local time. Then two kind of analyses have been done. One is the spatial variation analysis and the other is temporal variation analysis. For the spatial variation analysis, we compare the 1-hour averaged cloud fractions from TSC and ARSCL around 10:30 AM and 1:30 PM with the instantaneous cloud fractions from MODIS but with different spatial resolution. By obtaining the RMS errors and ratio of average values of CFs for these inter-comparisons, the optimal CF-matching spatial resolutions for MODIS regarding to TSC and ARSCL are obtained which are both 30 km radius of circle. We also find that the optimal matching spatial resolution increases when the ground observation average time increases. For the temporal analysis, we first analyze the diurnal variation of the cloud fraction based on the surface CFs from TSC and ARSCL from which we can see the daily representation of cloud fraction observed at 10:30 AM and 1:30 PM. Then we make a statistical comparison of daily and monthly cloud fraction between using all time observation and using the 1-hour averaged observations at both 10:30 AM and 1:30 PM. Comparison results will be shown in our paper. It shows a high correlation coefficient of 0.95 (0.93) for observations from TSC (ARSCL). The ratios of daily (monthly) averaged cloud fraction between using all time and using the time satellite passes are 0.87(0.92) and 0.86(0.97) for TSC and ARSCL, respectively. This suggests that considerable errors could be introduced while using the cloud fraction at two fixed time points (10:30 AM and 1:30 PM) to represent the daily cloud fraction.
CloudSat Image of Tropical Thunderstorms Over Africa
NASA Technical Reports Server (NTRS)
2006-01-01
[figure removed for brevity, see original site] Figure 1 CloudSat image of a horizontal cross-section of tropical clouds and thunderstorms over east Africa. The red colors are indicative of highly reflective particles such as water (rain) or ice crystals, which the blue indicates thinner clouds (such as cirrus). The flat green/blue lines across the bottom represent the ground signal. The vertical scale on the CloudS at Cloud Profiling Radar image is approximately 30 kilometers (19 miles). The brown line below the image indicates the relative elevation of the land surface. The inset image shows the CloudSat track relative to a Moderate Resolution Imaging Spectroradiometer (MODIS) visible image taken at nearly the same time.NASA Technical Reports Server (NTRS)
Minnis, Patrick; Hong, Gang; Ayers, Kirk; Smith, William L., Jr.; Yost, Christopher R.; Heymsfield, Andrew J.; Heymsfield, Gerald M.; Hlavka, Dennis L.; King, Michael D.; Korn, Errol;
2012-01-01
Retrievals of ice cloud properties using infrared measurements at 3.7, 6.7, 7.3, 8.5, 10.8, and 12.0 microns can provide consistent results regardless of solar illumination, but are limited to cloud optical thicknesses tau < approx.6. This paper investigates the variations in radiances at these wavelengths over a deep convective cloud system for their potential to extend retrievals of tau and ice particle size D(sub e) to optically thick clouds. Measurements from the Moderate Resolution Imaging Spectroradiometer Airborne Simulator--ASTER, the Scanning High-resolution Interferometer Sounder, the Cloud Physics Lidar (CPL), and the Cloud Radar System (CRS) aboard the NASA ER-2 aircraft during the NASA TC4 (Tropical Composition, Cloud and Climate Coupling) experiment flight during 5 August 2007, are used to examine the retrieval capabilities of infrared radiances over optically thick ice clouds. Simulations based on coincident in-situ measurements and combined cloud tau from CRS and CPL measurements are comparable to the observations. They reveal that brightness temperatures at these bands and their differences (BTD) are sensitive to tau up to approx.20 and that for ice clouds having tau > 20, the 3.7 - 10.8 microns and 3.7 - 6.7 microns BTDs are the most sensitive to D(sub e). Satellite imagery appears consistent with these results. Keywords: clouds; optical depth; particle size; satellite; TC4; multispectral thermal infrared
NASA Technical Reports Server (NTRS)
Minnis, Patrick; Hong, Gang; Ayers, Jeffrey Kirk; Smith, William L.; Yost, Christopher R.; Heymsfield, Andrew J.; Heymsfield, Gerald M.; Hlavka, Dennis L.; King, Michael D.; Korn, Errol M.;
2012-01-01
Retrievals of ice cloud properties using infrared measurements at 3.7, 6.7, 7.3, 8.5, 10.8, and 12.0 microns can provide consistent results regardless of solar illumination, but are limited to cloud optical thicknesses tau < approx.6. This paper investigates the variations in radiances at these wavelengths over a deep convective cloud system for their potential to extend retrievals of tau and ice particle size D(sub e) to optically thick clouds. Measurements from the Moderate Resolution Imaging Spectroradiometer Airborne Simulator--ASTER, the Scanning High-resolution Interferometer Sounder, the Cloud Physics Lidar (CPL), and the Cloud Radar System (CRS) aboard the NASA ER-2 aircraft during the NASA TC4 (Tropical Composition, Cloud and Climate Coupling) experiment flight during 5 August 2007, are used to examine the retrieval capabilities of infrared radiances over optically thick ice clouds. Simulations based on coincident in-situ measurements and combined cloud tau from CRS and CPL measurements are comparable to the observations. They reveal that brightness temperatures at these bands and their differences (BTD) are sensitive to tau up to approx.20 and that for ice clouds having tau > 20, the 3.7 - 10.8 microns and 3.7 - 6.7 microns BTDs are the most sensitive to D(sub e). Satellite imagery appears consistent with these results. Keywords: clouds; optical depth; particle size; satellite; TC4; multispectral thermal infrared
Cloud and Radiation Studies during SAFARI 2000
NASA Technical Reports Server (NTRS)
Platnick, Steven; King, M. D.; Hobbs, P. V.; Osborne, S.; Piketh, S.; Bruintjes, R.; Lau, William K. M. (Technical Monitor)
2001-01-01
Though the emphasis of the Southern Africa Regional Science Initiative 2000 (SAFARI-2000) dry season campaign was largely on emission sources and transport, the assemblage of aircraft (including the high altitude NASA ER-2 remote sensing platform and the University of Washington CV-580, UK MRF C130, and South African Weather Bureau JRA in situ aircrafts) provided a unique opportunity for cloud studies. Therefore, as part of the SAFARI initiative, investigations were undertaken to assess regional aerosol-cloud interactions and cloud remote sensing algorithms. In particular, the latter part of the experiment concentrated on marine boundary layer stratocumulus clouds off the southwest coast of Africa. Associated with cold water upwelling along the Benguela current, the Namibian stratocumulus regime has received limited attention but appears to be unique for several reasons. During the dry season, outflow of continental fires and industrial pollution over this area can be extreme. From below, upwelling provides a rich nutrient source for phytoplankton (a source of atmospheric sulphur through DMS production as well as from decay processes). The impact of these natural and anthropogenic sources on the microphysical and optical properties of the stratocumulus is unknown. Continental and Indian Ocean cloud systems of opportunity were also studied during the campaign. Aircraft flights were coordinated with NASA Terra Satellite overpasses for synergy with the Moderate Resolution Imaging Spectroradiometer (MODIS) and other Terra instruments. An operational MODIS algorithm for the retrieval of cloud optical and physical properties (including optical thickness, effective particle radius, and water path) has been developed. Pixel-level MODIS retrievals (11 km spatial resolution at nadir) and gridded statistics of clouds in th SAFARI region will be presented. In addition, the MODIS Airborne Simulator flown on the ER-2 provided high spatial resolution retrievals (50 m at nadir). These retrievals will be discussed and compared with in situ observations.
NASA Astrophysics Data System (ADS)
Thompson, D. R.; Kahn, B. H.; Green, R. O.; Chien, S.; Middleton, E.; Tran, D. Q.
2017-12-01
Clouds' variable ice and liquid content significantly influences their optical properties, evolution, and radiative forcing potential (Tan and Storelvmo, J. Atmos. Sci, 73, 2016). However, most remote measurements of thermodynamic phase have spatial resolutions of 1 km or more and are insensitive to mixed phases. This under-constrains important processes, such as spatial partitioning within mixed phase clouds, that carry outsize radiative forcing impacts. These uncertainties could shift Global Climate Model (GCM) predictions of future warming by over 1 degree Celsius (Tan et al., Science 352:6282, 2016). Imaging spectroscopy of reflected solar energy from the 1.4 - 1.8 μm shortwave infrared (SWIR) spectral range can address this observational gap. These observations can distinguish ice and water absorption, providing a robust and sensitive measurement of cloud top thermodynamic phase including mixed phases. Imaging spectrometers can resolve variations at scales of tens to hundreds of meters (Thompson et al., JGR-Atmospheres 121, 2016). We report the first such global high spatial resolution (30 m) survey, based on data from 2005-2015 acquired by the Hyperion imaging spectrometer onboard NASA's EO-1 spacecraft (Pearlman et al., Proc. SPIE 4135, 2001). Estimated seasonal and latitudinal distributions of cloud thermodynamic phase generally agree with observations made by other satellites such as the Atmospheric Infrared Sounder (AIRS). Variogram analyses reveal variability at different spatial scales. Our results corroborate previously observed zonal distributions, while adding insight into the spatial scales of processes governing cloud top thermodynamic phase. Figure: Thermodynamic phase retrievals. Top: Example of a cloud top thermodynamic phase map from the EO-1/Hyperion. Bottom: Latitudinal distributions of pure and mixed phase clouds, 2005-2015, showing Liquid Thickness Fraction (LTF). LTF=0 corresponds to pure ice absorption, while LTF=1 is pure liquid. The archive contains over 45,000 scenes. Copyright 2017, California Institute of Technology. Government Support Acknowledged.
Fast rockfall hazard assessment along a road section using the new LYNX Mobile Mapper Lidar
NASA Astrophysics Data System (ADS)
Dario, Carrea; Celine, Longchamp; Michel, Jaboyedoff; Marc, Choffet; Marc-Henri, Derron; Clement, Michoud; Andrea, Pedrazzini; Dario, Conforti; Michael, Leslar; William, Tompkinson
2010-05-01
The terrestrial laser scanning (TLS) is an active remote sensing technique providing high resolution point clouds of the topography. The high resolution digital elevations models (HRDEM) derived of these point clouds are an important tool for the stability analysis of slopes. The LYNX Mobile Mapper is a new TLS generation developed by Optech. Its particularity is to be mounted on a vehicle and providing a 360° high density point cloud at 200-khz measurement rate in a very short acquisition time. It is composed of two sensors improving the resolution and reducing the laser shadowing. The spatial resolution is better than 10 cm at 10 m range and at a velocity of 50 km/h and the reflectivity of the signal is around 20% at a distance of 200 m. The Lidar is also equipped with a DGPS and an inertial measurement unit (IMU) which gives real time position and georeferences directly the point cloud. Thanks to its ability to provide a continuous data set from an extended area along a road, this TLS system is useful for rockfall hazard assessment. In addition, this new scanner decrease considerably the time spent in the field and the postprocessing is reduced thanks to resultant georeferenced data. Nevertheless, its application is limited to an area close to the road. The LYNX has been tested near Pontarlier (France) along roads sections affected by rockfall. Regarding to the tectonic context, the studied area is located in the Folded Jura mainly composed of limestone. The result is a very detailed point cloud with a point spacing of 4 cm. The LYNX presents detailed topography on which a structural analysis has been carried out using COLTOP-3D. It allows obtaining a full structural description along the road. In addition, kinematic tests coupled with probabilistic analysis give a susceptibility map of the road cut or natural cliffs above the road. Comparisons with field survey confirm the Lidar approach.
High-resolution weather forecasting is affected by many aspects, i.e. model initial conditions, subgrid-scale cumulus convection and cloud microphysics schemes. Recent 12km grid studies using the Weather Research and Forecasting (WRF) model have identified the importance of inco...
Observations of specular reflective particles and layers in crystal clouds.
Balin, Yurii S; Kaul, Bruno V; Kokhanenko, Grigorii P; Penner, Ioganes E
2011-03-28
In the present article, results of observations of high crystal clouds with high spatial and temporal resolution using the ground-based polarization LOSA-S lidar are described. Cases of occurrence of specularly reflective layers formed by particles oriented predominantly in the horizontal plane are demonstrated. Results of measuring echo-signal depolarization are compared for linear and circular polarization states of the initial laser beam.
Techniques for the measurements of the line of sight velocity of high altitude Barium clouds
NASA Technical Reports Server (NTRS)
Mende, S. B.
1981-01-01
It is demonstrated that for maximizing the scientific output of future ion cloud release experiments a new type of instrument is required which will measure the line of sight velocity of the ion cloud by the Doppler Technique. A simple instrument was constructed using a 5 cm diameter solid Fabry-Perot etalon coupled to a low light level integrating television camera. It was demonstrated that the system has both the sensitivity and spectral resolution for the detection of ion clouds and the measurement of their line of sight Doppler velocity. The tests consisted of (1) a field experiment using a rocket barium cloud release to check the sensitivity, (2) laboratory experiments to show the spectral resolving capabilities of the system. The instrument was found to be operational if the source was brighter than about 1 kilorayleigh and it had a wavelength resolution much better than .2A which corresponds to about 12 km/sec or an acceleration potential of 100 volts.
The interstellar D1 line at high resolution
NASA Technical Reports Server (NTRS)
Hobbs, L. M.; Welty, D. E.
1990-01-01
Observations at a resolving power or a velocity resolution are reported of the interstellar D(sub 1) line of Na I in the spectra of gamma Cas, delta Ori, epsilon Ori, pi Sco, delta Cyg, and alpha Cyg. An echelle grating was used in a double-pass configuration with a CCD detector in the coude spectrograph of the 2.7 m reflector at McDonald Observatory. At least 42 kinematically distinct clouds are detected along the light paths to the five more distant stars, in addition to a single cloud seen toward delta Cyg. The absorption lines arising in 13 of the clouds are sufficiently narrow and unblended to reveal clearly resolved hyperfine structure components split by 1.05 km/s. An additional 13 clouds apparently show comparably narrow, but more strongly blended, lines. For each individual cloud, upper limits T(sub max) and (v sub t)(sub max) on the temperature and the turbulent velocity, respectively, are derived by fitting the observed lines with theoretical absorption profiles.
The parsec-scale relationship between ICO and AV in local molecular clouds
NASA Astrophysics Data System (ADS)
Lee, Cheoljong; Leroy, Adam K.; Bolatto, Alberto D.; Glover, Simon C. O.; Indebetouw, Remy; Sandstrom, Karin; Schruba, Andreas
2018-03-01
We measure the parsec-scale relationship between integrated CO intensity (ICO) and visual extinction (AV) in 24 local molecular clouds using maps of CO emission and dust optical depth from Planck. This relationship informs our understanding of CO emission across environments, but clean Milky Way measurements remain scarce. We find uniform ICO for a given AV, with the results bracketed by previous studies of the Pipe and Perseus clouds. Our measured ICO-AV relation broadly agrees with the standard Galactic CO-to-H2 conversion factor, the relation found for the Magellanic clouds at coarser resolution, and numerical simulations by Glover & Clark (2016). This supports the idea that CO emission primarily depends on shielding, which protects molecules from dissociating radiation. Evidence for CO saturation at high AV and a threshold for CO emission at low AV varies remains uncertain due to insufficient resolution and ambiguities in background subtraction. Resolution of order 0.1 pc may be required to measure these features. We use this ICO-AV relation to predict how the CO-to-H2 conversion factor (XCO) would change if the Solar Neighbourhood clouds had different dust-to-gas ratio (metallicity). The calculations highlight the need for improved observations of the CO emission threshold and H I shielding layer depth. They are also sensitive to the shape of the column density distribution. Because local clouds collectively show a self-similar distribution, we predict a shallow metallicity dependence for XCO down to a few tenths of solar metallicity. However, our calculations also imply dramatic variations in cloud-to-cloud XCO at subsolar metallicity.
Cloud-Based Tools to Support High-Resolution Modeling (Invited)
NASA Astrophysics Data System (ADS)
Jones, N.; Nelson, J.; Swain, N.; Christensen, S.
2013-12-01
The majority of watershed models developed to support decision-making by water management agencies are simple, lumped-parameter models. Maturity in research codes and advances in the computational power from multi-core processors on desktop machines, commercial cloud-computing resources, and supercomputers with thousands of cores have created new opportunities for employing more accurate, high-resolution distributed models for routine use in decision support. The barriers for using such models on a more routine basis include massive amounts of spatial data that must be processed for each new scenario and lack of efficient visualization tools. In this presentation we will review a current NSF-funded project called CI-WATER that is intended to overcome many of these roadblocks associated with high-resolution modeling. We are developing a suite of tools that will make it possible to deploy customized web-based apps for running custom scenarios for high-resolution models with minimal effort. These tools are based on a software stack that includes 52 North, MapServer, PostGIS, HT Condor, CKAN, and Python. This open source stack provides a simple scripting environment for quickly configuring new custom applications for running high-resolution models as geoprocessing workflows. The HT Condor component facilitates simple access to local distributed computers or commercial cloud resources when necessary for stochastic simulations. The CKAN framework provides a powerful suite of tools for hosting such workflows in a web-based environment that includes visualization tools and storage of model simulations in a database to archival, querying, and sharing of model results. Prototype applications including land use change, snow melt, and burned area analysis will be presented. This material is based upon work supported by the National Science Foundation under Grant No. 1135482
NASA Technical Reports Server (NTRS)
Obland, Michael D.; Hostetler, Chris A.; Ferrare, Richard A.; Hair, John W.; Roers, Raymond R.; Burton, Sharon P.; Cook, Anthony L.; Harper, David B.
2008-01-01
Since achieving first light in December of 2005, the NASA Langley Research Center (LaRC) Airborne High Spectral Resolution Lidar (HSRL) has been involved in seven field campaigns, accumulating over 450 hours of science data across more than 120 flights. Data from the instrument have been used in a variety of studies including validation and comparison with the Cloud- Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO) satellite mission, aerosol property retrievals combining passive and active instrument measurements, aerosol type identification, aerosol-cloud interactions, and cloud top and planetary boundary layer (PBL) height determinations. Measurements and lessons learned from the HSRL are leading towards next-generation HSRL instrument designs that will enable even further studies of aerosol intensive and extensive parameters and the effects of aerosols on the climate system. This paper will highlight several of the areas in which the NASA Airborne HSRL is making contributions to climate science.
NASA Astrophysics Data System (ADS)
Boichu, Marie; Clarisse, Lieven; Khvorostyanov, Dmitry; Clerbaux, Cathy
2014-04-01
Forecasting the dispersal of volcanic clouds during an eruption is of primary importance, especially for ensuring aviation safety. As volcanic emissions are characterized by rapid variations of emission rate and height, the (generally) high level of uncertainty in the emission parameters represents a critical issue that limits the robustness of volcanic cloud dispersal forecasts. An inverse modeling scheme, combining satellite observations of the volcanic cloud with a regional chemistry-transport model, allows reconstructing this source term at high temporal resolution. We demonstrate here how a progressive assimilation of freshly acquired satellite observations, via such an inverse modeling procedure, allows for delivering robust sulfur dioxide (SO2) cloud dispersal forecasts during the eruption. This approach provides a computationally cheap estimate of the expected location and mass loading of volcanic clouds, including the identification of SO2-rich parts.
Graphics Processing Unit (GPU) Acceleration of the Goddard Earth Observing System Atmospheric Model
NASA Technical Reports Server (NTRS)
Putnam, Williama
2011-01-01
The Goddard Earth Observing System 5 (GEOS-5) is the atmospheric model used by the Global Modeling and Assimilation Office (GMAO) for a variety of applications, from long-term climate prediction at relatively coarse resolution, to data assimilation and numerical weather prediction, to very high-resolution cloud-resolving simulations. GEOS-5 is being ported to a graphics processing unit (GPU) cluster at the NASA Center for Climate Simulation (NCCS). By utilizing GPU co-processor technology, we expect to increase the throughput of GEOS-5 by at least an order of magnitude, and accelerate the process of scientific exploration across all scales of global modeling, including: The large-scale, high-end application of non-hydrostatic, global, cloud-resolving modeling at 10- to I-kilometer (km) global resolutions Intermediate-resolution seasonal climate and weather prediction at 50- to 25-km on small clusters of GPUs Long-range, coarse-resolution climate modeling, enabled on a small box of GPUs for the individual researcher After being ported to the GPU cluster, the primary physics components and the dynamical core of GEOS-5 have demonstrated a potential speedup of 15-40 times over conventional processor cores. Performance improvements of this magnitude reduce the required scalability of 1-km, global, cloud-resolving models from an unfathomable 6 million cores to an attainable 200,000 GPU-enabled cores.
NASA Astrophysics Data System (ADS)
Wong, J.; Barth, M. C.; Noone, D. C.
2012-12-01
Lightning-generated nitrogen oxides (LNOx) is an important precursor to tropospheric ozone production. With a meteorological time-scale variability similar to that of the ozone chemical lifetime, it can nonlinearly perturb tropospheric ozone concentration. Coupled with upper-air circulation patterns, LNOx can accumulate in significant amount in the upper troposphere with other precursors, thus enhancing ozone production (see attached figure). While LNOx emission has been included and tuned extensively in global climate models, its inclusions in regional chemistry models are seldom tested. Here we present a study that evaluates the frequently used Price and Rind parameterization based on cloud-top height at resolutions that partially resolve deep convection using the Weather Research and Forecasting model with Chemistry (WRF-Chem) over the contiguous United States. With minor modifications, the parameterization is shown to generate integrated flash counts close to those observed. However, the modeled frequency distribution of cloud-to-ground flashes do not represent well for storms with high flash rates, bringing into question the applicability of the intra-cloud/ground partitioning (IC:CG) formulation of Price and Rind in some studies. Resolution dependency also requires attention when sub-grid cloud-tops are used instead of the originally intended grid-averaged cloud-top. LNOx passive tracers being gathered by monsoonal upper tropospheric anticyclone.
Automatic Matching of Large Scale Images and Terrestrial LIDAR Based on App Synergy of Mobile Phone
NASA Astrophysics Data System (ADS)
Xia, G.; Hu, C.
2018-04-01
The digitalization of Cultural Heritage based on ground laser scanning technology has been widely applied. High-precision scanning and high-resolution photography of cultural relics are the main methods of data acquisition. The reconstruction with the complete point cloud and high-resolution image requires the matching of image and point cloud, the acquisition of the homonym feature points, the data registration, etc. However, the one-to-one correspondence between image and corresponding point cloud depends on inefficient manual search. The effective classify and management of a large number of image and the matching of large image and corresponding point cloud will be the focus of the research. In this paper, we propose automatic matching of large scale images and terrestrial LiDAR based on APP synergy of mobile phone. Firstly, we develop an APP based on Android, take pictures and record related information of classification. Secondly, all the images are automatically grouped with the recorded information. Thirdly, the matching algorithm is used to match the global and local image. According to the one-to-one correspondence between the global image and the point cloud reflection intensity image, the automatic matching of the image and its corresponding laser radar point cloud is realized. Finally, the mapping relationship between global image, local image and intensity image is established according to homonym feature point. So we can establish the data structure of the global image, the local image in the global image, the local image corresponding point cloud, and carry on the visualization management and query of image.
Lagrangian large eddy simulations of boundary layer clouds on ERA-Interim and ERA5 trajectories
NASA Astrophysics Data System (ADS)
Kazil, J.; Feingold, G.; Yamaguchi, T.
2017-12-01
This exploratory study examines Lagrangian large eddy simulations of boundary layer clouds along wind trajectories from the ERA-Interim and ERA5 reanalyses. The study is motivated by the need for statistically representative sets of high resolution simulations of cloud field evolution in realistic meteorological conditions. The study will serve as a foundation for the investigation of biomass burning effects on the transition from stratocumulus to shallow cumulus clouds in the South-East Atlantic. Trajectories that pass through a location with radiosonde data (St. Helena) and which exhibit a well-defined cloud structure and evolution were identified in satellite imagery, and sea surface temperature and atmospheric vertical profiles along the trajectories were extracted from the reanalysis data sets. The System for Atmospheric Modeling (SAM) simulated boundary layer turbulence and cloud properties along the trajectories. Mean temperature and moisture (in the free troposphere) and mean wind speed (at all levels) were nudged towards the reanalysis data. Atmospheric and cloud properties in the large eddy simulations were compared with those from the reanalysis products, and evaluated with satellite imagery and radiosonde data. Simulations using ERA-Interim data and the higher resolution ERA5 data are contrasted.
NASA Astrophysics Data System (ADS)
De Haan, D. O.; Riva, M.; Surratt, J. D.; Cazaunau, M.; Doussin, J. F.
2016-12-01
Minimal organic aerosol forms when aerosol particles are exposed to gas-phase methylglyoxal, but condensed phase laboratory studies of aerosol chemistry have suggested that methylglyoxal is a significant source of oligomerized aerosol material. In this study, various types of seed particles were exposed to gaseous methylglyoxal and then cloud-processed in the CESAM chamber. The gas phase was continuously probed by high-resolution PTR-MS during the experiments, and the particle phase WSOC was chemically characterized by high-resolution UPLC/ESI-DAD-QTOFMS. Uptake of methylglyoxal to dry particles caused optical rather than size changes, along with the release of imine products to the gas phase. High RH and cloud processing released some particle-bound methylglyoxal back to the gas phase but triggered an uptake of imine products. Analysis of the particle phase identified N-containing aldol condensation products derived from methylglyoxal, imine (produced from methylglyoxal and amine reactions), acetaldehyde (produced by methylglyoxal photolysis) and hydroxyacetone (produced by methylglyoxal disproportionation) monomers.
NASA Astrophysics Data System (ADS)
Siebenmorgen, R.; Voshchinnikov, N. V.; Bagnulo, S.; Cox, N. L. J.; Cami, J.; Peest, C.
2018-03-01
It is well known that the dust properties of the diffuse interstellar medium exhibit variations towards different sight-lines on a large scale. We have investigated the variability of the dust characteristics on a small scale, and from cloud-to-cloud. We use low-resolution spectro-polarimetric data obtained in the context of the Large Interstellar Polarisation Survey (LIPS) towards 59 sight-lines in the Southern Hemisphere, and we fit these data using a dust model composed of silicate and carbon particles with sizes from the molecular to the sub-micrometre domain. Large (≥6 nm) silicates of prolate shape account for the observed polarisation. For 32 sight-lines we complement our data set with UVES archive high-resolution spectra, which enable us to establish the presence of single-cloud or multiple-clouds towards individual sight-lines. We find that the majority of these 35 sight-lines intersect two or more clouds, while eight of them are dominated by a single absorbing cloud. We confirm several correlations between extinction and parameters of the Serkowski law with dust parameters, but we also find previously undetected correlations between these parameters that are valid only in single-cloud sight-lines. We find that interstellar polarisation from multiple-clouds is smaller than from single-cloud sight-lines, showing that the presence of a second or more clouds depolarises the incoming radiation. We find large variations of the dust characteristics from cloud-to-cloud. However, when we average a sufficiently large number of clouds in single-cloud or multiple-cloud sight-lines, we always retrieve similar mean dust parameters. The typical dust abundances of the single-cloud cases are [C]/[H] = 92 ppm and [Si]/[H] = 20 ppm.
On the Nature and Extent of Optically Thin Marine low Clouds
NASA Technical Reports Server (NTRS)
Leahy, L. V.; Wood, R.; Charlson, R. J.; Hostetler, C. A.; Rogers, R. R.; Vaughan, M. A.; Winker, D. M.
2012-01-01
Macrophysical properties of optically thin marine low clouds over the nonpolar oceans (60 deg S-60 deg N) are measured using 2 years of full-resolution nighttime data from the Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP). Optically thin clouds, defined as the subset of marine low clouds that do not fully attenuate the lidar signal, comprise almost half of the low clouds over the marine domain. Regionally, the fraction of low clouds that are optically thin (f(sub thin,cld)) exhibits a strong inverse relationship with the low-cloud cover, with maxima in the tropical trades (f(sub thin,cld) greater than 0.8) and minima in regions of persistent marine stratocumulus and in midlatitudes (f(sub thin,cld) less than 0.3). Domain-wide, a power law fit describes the cloud length distribution, with exponent beta = 2.03 +/- 0.06 (+/-95% confidence interval). On average, the fraction of a cloud that is optically thin decreases from approximately 1 for clouds smaller than 2 km to less than 0.3 for clouds larger than 30 km. This relationship is found to be independent of region, so that geographical variations in the cloud length distribution explain three quarters of the variance in f(sub thin,cld). Comparing collocated trade cumulus observations from CALIOP and the airborne High Spectral Resolution Lidar reveals that clouds with lengths smaller than are resolvable with CALIOP contribute approximately half of the low clouds in the region sampled. A bounded cascade model is constructed to match the observations from the trades. The model shows that the observed optically thin cloud behavior is consistent with a power law scaling of cloud optical depth and suggests that most optically thin clouds only partially fill the CALIOP footprint.
1984-07-01
aerosols and sub pixel-sized clouds all tend to increase Channel 1 with respect to Channel 2 and reduce the computed VIN. Further, the Guide states that... computation of the VIN. Large scale cloud contamination of pixels, while diffi- cult to correct for, can at least be monitored and affected pixels...techniques have been developed for computer cloud screening. See, for example, Horvath et al. (1982), Gray and McCrary (1981a) and Nixon et al. (1983
NASA Astrophysics Data System (ADS)
Parishani, H.; Pritchard, M. S.; Bretherton, C. S.; Wyant, M. C.; Khairoutdinov, M.; Singh, B.
2017-12-01
Biases and parameterization formulation uncertainties in the representation of boundary layer clouds remain a leading source of possible systematic error in climate projections. Here we show the first results of cloud feedback to +4K SST warming in a new experimental climate model, the ``Ultra-Parameterized (UP)'' Community Atmosphere Model, UPCAM. We have developed UPCAM as an unusually high-resolution implementation of cloud superparameterization (SP) in which a global set of cloud resolving arrays is embedded in a host global climate model. In UP, the cloud-resolving scale includes sufficient internal resolution to explicitly generate the turbulent eddies that form marine stratocumulus and trade cumulus clouds. This is computationally costly but complements other available approaches for studying low clouds and their climate interaction, by avoiding parameterization of the relevant scales. In a recent publication we have shown that UP, while not without its own complexity trade-offs, can produce encouraging improvements in low cloud climatology in multi-month simulations of the present climate and is a promising target for exascale computing (Parishani et al. 2017). Here we show results of its low cloud feedback to warming in multi-year simulations for the first time. References: Parishani, H., M. S. Pritchard, C. S. Bretherton, M. C. Wyant, and M. Khairoutdinov (2017), Toward low-cloud-permitting cloud superparameterization with explicit boundary layer turbulence, J. Adv. Model. Earth Syst., 9, doi:10.1002/2017MS000968.
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 effective variance and cloud optical thickness are compared to coincident Research Scanning Polarimeter (RSP) data.
Doppler lidar for measurement of atmospheric wind fields
NASA Technical Reports Server (NTRS)
Menzies, Robert T.
1991-01-01
Measurements of wind fields in the earth's troposphere with daily global coverage is widely considered as a significant advance for forecasting and transport studies. For optimal use by NWP (Numerical Weather Prediction) models the horizontal and vertical resolutions should be approximately 100 km and 1 km, respectively. For boundary layer studies vertical resolution of a few hundred meters seems essential. Earth-orbiting Doppler lidar has a unique capability to measure global winds in the troposphere with the high vertical resolution required. The lidar approach depends on transmission of pulses with high spectral purity and backscattering from the atmospheric aerosol particles or layered clouds to provide a return signal. Recent field measurement campaigns using NASA research aircraft have resulted in collection of aerosol and cloud data which can be used to optimize the Doppler lidar instrument design and measurement strategy.
2012-09-30
package developed by the Cloud Feedback Model Intercomparison Project (CFMIP), COSP (BODAS- SALCEDO et al. 2011). COSP will convert the model hydrometers ...and infrared data at high spatial and temporal resolution. J. Hydromet ., 5, 487-503. Kay, J. E. et al., 2012: Exposing global cloud biases in the
On estimating scale invariance in stratocumulus cloud fields
NASA Technical Reports Server (NTRS)
Seze, Genevieve; Smith, Leonard A.
1990-01-01
Examination of cloud radiance fields derived from satellite observations sometimes indicates the existence of a range of scales over which the statistics of the field are scale invariant. Many methods were developed to quantify this scaling behavior in geophysics. The usefulness of such techniques depends both on the physics of the process being robust over a wide range of scales and on the availability of high resolution, low noise observations over these scales. These techniques (area perimeter relation, distribution of areas, estimation of the capacity, d0, through box counting, correlation exponent) are applied to the high resolution satellite data taken during the FIRE experiment and provides initial estimates of the quality of data required by analyzing simple sets. The results of the observed fields are contrasted with those of images of objects with known characteristics (e.g., dimension) where the details of the constructed image simulate current observational limits. Throughout when cloud elements and cloud boundaries are mentioned; it should be clearly understood that by this structures in the radiance field are meant: all the boundaries considered are defined by simple threshold arguments.
Erosion and Channel Incision Analysis with High-Resolution Lidar
NASA Astrophysics Data System (ADS)
Potapenko, J.; Bookhagen, B.
2013-12-01
High-resolution LiDAR (LIght Detection And Ranging) provides a new generation of sub-meter topographic data that is still to be fully exploited by the Earth science communities. We make use of multi-temporal airborne and terrestrial lidar scans in the south-central California and Santa Barbara area. Specifically, we have investigated the Mission Canyon and Channel Islands regions from 2009-2011 to study changes in erosion and channel incision on the landscape. In addition to gridding the lidar data into digital elevation models (DEMs), we also make use of raw lidar point clouds and triangulated irregular networks (TINs) for detailed analysis of heterogeneously spaced topographic data. Using recent advancements in lidar point cloud processing from information technology disciplines, we have employed novel lidar point cloud processing and feature detection algorithms to automate the detection of deeply incised channels and gullies, vegetation, and other derived metrics (e.g. estimates of eroded volume). Our analysis compares topographically-derived erosion volumes to field-derived cosmogenic radionuclide age and in-situ sediment-flux measurements. First results indicate that gully erosion accounts for up to 60% of the sediment volume removed from the Mission Canyon region. Furthermore, we observe that gully erosion and upstream arroyo propagation accelerated after fires, especially in regions where vegetation was heavily burned. The use of high-resolution lidar point cloud data for topographic analysis is still a novel method that needs more precedent and we hope to provide a cogent example of this approach with our research.
Cloud characterization and clear-sky correction from Landsat-7
Cahalan, Robert F.; Oreopoulos, L.; Wen, G.; Marshak, S.; Tsay, S. -C.; DeFelice, Tom
2001-01-01
Landsat, with its wide swath and high resolution, fills an important mesoscale gap between atmospheric variations seen on a few kilometer scale by local surface instrumentation and the global view of coarser resolution satellites such as MODIS. In this important scale range, Landsat reveals radiative effects on the few hundred-meter scale of common photon mean-free-paths, typical of scattering in clouds at conservative (visible) wavelengths, and even shorter mean-free-paths of absorptive (near-infrared) wavelengths. Landsat also reveals shadowing effects caused by both cloud and vegetation that impact both cloudy and clear-sky radiances. As a result, Landsat has been useful in development of new cloud retrieval methods and new aerosol and surface retrievals that account for photon diffusion and shadowing effects. This paper discusses two new cloud retrieval methods: the nonlocal independent pixel approximation (NIPA) and the normalized difference nadir radiance method (NDNR). We illustrate the improvements in cloud property retrieval enabled by the new low gain settings of Landsat-7 and difficulties found at high gains. Then, we review the recently developed “path radiance” method of aerosol retrieval and clear-sky correction using data from the Department of Energy Atmospheric Radiation Measurement (ARM) site in Oklahoma. Nearby clouds change the solar radiation incident on the surface and atmosphere due to indirect illumination from cloud sides. As a result, if clouds are nearby, this extra side-illumination causes clear pixels to appear brighter, which can be mistaken for extra aerosol or higher surface albedo. Thus, cloud properties must be known in order to derive accurate aerosol and surface properties. A three-dimensional (3D) Monte Carlo (MC) radiative transfer simulation illustrates this point and suggests a method to subtract the cloud effect from aerosol and surface retrievals. The main conclusion is that cloud, aerosol, and surface retrievals are linked and must be treated as a combined system. Landsat provides the range of scales necessary to observe the 3D cloud radiative effects that influence joint surface-atmospheric retrievals.
Building a LiDAR point cloud simulator: Testing algorithms for high resolution topographic change
NASA Astrophysics Data System (ADS)
Carrea, Dario; Abellán, Antonio; Derron, Marc-Henri; Jaboyedoff, Michel
2014-05-01
Terrestrial laser technique (TLS) is becoming a common tool in Geosciences, with clear applications ranging from the generation of a high resolution 3D models to the monitoring of unstable slopes and the quantification of morphological changes. Nevertheless, like every measurement techniques, TLS still has some limitations that are not clearly understood and affect the accuracy of the dataset (point cloud). A challenge in LiDAR research is to understand the influence of instrumental parameters on measurement errors during LiDAR acquisition. Indeed, different critical parameters interact with the scans quality at different ranges: the existence of shadow areas, the spatial resolution (point density), and the diameter of the laser beam, the incidence angle and the single point accuracy. The objective of this study is to test the main limitations of different algorithms usually applied on point cloud data treatment, from alignment to monitoring. To this end, we built in MATLAB(c) environment a LiDAR point cloud simulator able to recreate the multiple sources of errors related to instrumental settings that we normally observe in real datasets. In a first step we characterized the error from single laser pulse by modelling the influence of range and incidence angle on single point data accuracy. In a second step, we simulated the scanning part of the system in order to analyze the shifting and angular error effects. Other parameters have been added to the point cloud simulator, such as point spacing, acquisition window, etc., in order to create point clouds of simple and/or complex geometries. We tested the influence of point density and vitiating point of view on the Iterative Closest Point (ICP) alignment and also in some deformation tracking algorithm with same point cloud geometry, in order to determine alignment and deformation detection threshold. We also generated a series of high resolution point clouds in order to model small changes on different environments (erosion, landslide monitoring, etc) and we then tested the use of filtering techniques using 3D moving windows along the space and time, which considerably reduces data scattering due to the benefits of data redundancy. In conclusion, the simulator allowed us to improve our different algorithms and to understand how instrumental error affects final results. And also, improve the methodology of scans acquisition to find the best compromise between point density, positioning and acquisition time with the best accuracy possible to characterize the topographic change.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Kollias, Pavlos
2017-08-08
This is a multi-institutional, collaborative project using observations and modeling to study the evolution (e.g. formation and growth) of hydrometeors in continental convective clouds. Our contribution was in data analysis for the generation of high-value cloud and precipitation products and derive cloud statistics for model validation. There are two areas in data analysis that we contributed: i) the development of novel, state-of-the-art dual-wavelength radar algorithms for the retrieval of cloud microphysical properties and ii) the evaluation of large domain, high-resolution models using comprehensive multi-sensor observations. Our research group developed statistical summaries from numerous sensors and developed retrievals of vertical airmore » motion in deep convection.« less
Thermodynamic and cloud parameter retrieval using infrared spectral data
NASA Technical Reports Server (NTRS)
Zhou, Daniel K.; Smith, William L., Sr.; Liu, Xu; Larar, Allen M.; Huang, Hung-Lung A.; Li, Jun; McGill, Matthew J.; Mango, Stephen A.
2005-01-01
High-resolution infrared radiance spectra obtained from near nadir observations provide atmospheric, surface, and cloud property information. A fast radiative transfer model, including cloud effects, is used for atmospheric profile and cloud parameter retrieval. The retrieval algorithm is presented along with its application to recent field experiment data from the NPOESS Airborne Sounding Testbed - Interferometer (NAST-I). The retrieval accuracy dependence on cloud properties is discussed. It is shown that relatively accurate temperature and moisture retrievals can be achieved below optically thin clouds. For optically thick clouds, accurate temperature and moisture profiles down to cloud top level are obtained. For both optically thin and thick cloud situations, the cloud top height can be retrieved with an accuracy of approximately 1.0 km. Preliminary NAST-I retrieval results from the recent Atlantic-THORPEX Regional Campaign (ATReC) are presented and compared with coincident observations obtained from dropsondes and the nadir-pointing Cloud Physics Lidar (CPL).
NASA Astrophysics Data System (ADS)
Stöcker, Claudia; Eltner, Anette
2016-04-01
Advances in computer vision and digital photogrammetry (i.e. structure from motion) allow for fast and flexible high resolution data supply. Within geoscience applications and especially in the field of small surface topography, high resolution digital terrain models and dense 3D point clouds are valuable data sources to capture actual states as well as for multi-temporal studies. However, there are still some limitations regarding robust registration and accuracy demands (e.g. systematic positional errors) which impede the comparison and/or combination of multi-sensor data products. Therefore, post-processing of 3D point clouds can heavily enhance data quality. In this matter the Iterative Closest Point (ICP) algorithm represents an alignment tool which iteratively minimizes distances of corresponding points within two datasets. Even though tool is widely used; it is often applied as a black-box application within 3D data post-processing for surface reconstruction. Aiming for precise and accurate combination of multi-sensor data sets, this study looks closely at different variants of the ICP algorithm including sub-steps of point selection, point matching, weighting, rejection, error metric and minimization. Therefore, an agricultural utilized field was investigated simultaneously by terrestrial laser scanning (TLS) and unmanned aerial vehicle (UAV) sensors two times (once covered with sparse vegetation and once bare soil). Due to different perspectives both data sets show diverse consistency in terms of shadowed areas and thus gaps so that data merging would provide consistent surface reconstruction. Although photogrammetric processing already included sub-cm accurate ground control surveys, UAV point cloud exhibits an offset towards TLS point cloud. In order to achieve the transformation matrix for fine registration of UAV point clouds, different ICP variants were tested. Statistical analyses of the results show that final success of registration and therefore data quality depends particularly on parameterization and choice of error metric, especially for erroneous data sets as in the case of sparse vegetation cover. At this, the point-to-point metric is more sensitive to data "noise" than the point-to-plane metric which results in considerably higher cloud-to-cloud distances. Concluding, in order to comply with accuracy demands of high resolution surface reconstruction and the aspect that ground control surveys can reach their limits both in time exposure and terrain accessibility ICP algorithm represents a great tool to refine rough initial alignment. Here different variants of registration modules allow for individual application according to the quality of the input data.
NASA Technical Reports Server (NTRS)
Kahn, Brian H.; Fishbein, Evan; Nasiri, Shaima L.; Eldering, Annmarie; Fetzer, Eric J.; Garay, Michael J.; Lee, Sung-Yung
2007-01-01
The consistency of cloud top temperature (Tc) and effective cloud fraction (f) retrieved by the Atmospheric Infrared Sounder (AIRS)/Advanced Microwave Sounding Unit (AMSU) observation suite and the Moderate Resolution Imaging Spectroradiometer (MODIS) on the EOS-Aqua platform are investigated. Collocated AIRS and MODIS TC and f are compared via an 'effective scene brightness temperature' (Tb,e). Tb,e is calculated with partial field of view (FOV) contributions from TC and surface temperature (TS), weighted by f and 1-f, respectively. AIRS reports up to two cloud layers while MODIS reports up to one. However, MODIS reports TC, TS, and f at a higher spatial resolution than AIRS. As a result, pixel-scale comparisons of TC and f are difficult to interpret, demonstrating the need for alternatives such as Tb,e. AIRS-MODIS Tb,e differences ((Delta)Tb,e) for identical observing scenes are useful as a diagnostic for cloud quantity comparisons. The smallest values of DTb,e are for high and opaque clouds, with increasing scatter in (Delta)Tb,e for clouds of smaller opacity and lower altitude. A persistent positive bias in DTb,e is observed in warmer and low-latitude scenes, characterized by a mixture of MODIS CO2 slicing and 11-mm window retrievals. These scenes contain heterogeneous cloud cover, including mixtures of multilayered cloudiness and misplaced MODIS cloud top pressure. The spatial patterns of (Delta)Tb,e are systematic and do not correlate well with collocated AIRS-MODIS radiance differences, which are more random in nature and smaller in magnitude than (Delta)Tb,e. This suggests that the observed inconsistencies in AIRS and MODIS cloud fields are dominated by retrieval algorithm differences, instead of differences in the observed radiances. The results presented here have implications for the validation of cloudy satellite retrieval algorithms, and use of cloud products in quantitative analyses.
NASA Astrophysics Data System (ADS)
Satyanarayana, M.; Radhakrishnan, S.-R.; Krishnakumar, V.; Mahadevan Pillai, V. P.; Raghunath, K.
2008-12-01
Cirrus clouds have been identified as one of the most uncertain component in the atmospheric research. It is known that cirrus clouds modulate the earth's climate through direct and indirect modification of radiation. The role of cirrus clouds depends mainly on their microphysical properties. To understand cirrus clouds better, we must observe and characterize their properties. In-situ observation of such clouds is a challenging experiment, as the clouds are located at high altitudes. Active remote sensing method based on lidar can detect high and thin cirrus clouds with good spatial and temporal resolution. We present the result obtained on the microphysical properties of the cirrus clouds at two Tropical stations namely Gadhanki, Tirupati (13.50 N, 79.20 E), India and Trivandrum (13.50 N, 770 E) Kerala, India from the ground based pulsed Nd: YAG lidar systems installed at the stations. A variant of the widely used Klett's lidar inversion method with range dependent scattering ratio is used for the present study for the retrieval of aerosol extinction and microphysical parameters of cirrus cloud.
Improved Thin Cirrus and Terminator Cloud Detection in CERES Cloud Mask
NASA Technical Reports Server (NTRS)
Trepte, Qing; Minnis, Patrick; Palikonda, Rabindra; Spangenberg, Doug; Haeffelin, Martial
2006-01-01
Thin cirrus clouds account for about 20-30% of the total cloud coverage and affect the global radiation budget by increasing the Earth's albedo and reducing infrared emissions. Thin cirrus, however, are often underestimated by traditional satellite cloud detection algorithms. This difficulty is caused by the lack of spectral contrast between optically thin cirrus and the surface in techniques that use visible (0.65 micron ) and infrared (11 micron ) channels. In the Clouds and the Earth s Radiant Energy System (CERES) Aqua Edition 1 (AEd1) and Terra Edition 3 (TEd3) Cloud Masks, thin cirrus detection is significantly improved over both land and ocean using a technique that combines MODIS high-resolution measurements from the 1.38 and 11 micron channels and brightness temperature differences (BTDs) of 11-12, 8.5-11, and 3.7-11 micron channels. To account for humidity and view angle dependencies, empirical relationships were derived with observations from the 1.38 micron reflectance and the 11-12 and 8.5-11 micron BTDs using 70 granules of MODIS data in 2002 and 2003. Another challenge in global cloud detection algorithms occurs near the day/night terminator where information from the visible 0.65 micron channel and the estimated solar component of 3.7 micron channel becomes less reliable. As a result, clouds are often underestimated or misidentified near the terminator over land and ocean. Comparisons between the CLAVR-x (Clouds from Advanced Very High Resolution Radiometer [AVHRR]) cloud coverage and Geoscience Laser Altimeter System (GLAS) measurements north of 60 N indicate significant amounts of missing clouds from CLAVR-x because this part of the world was near the day/night terminator viewed by AVHRR. Comparisons between MODIS cloud products (MOD06) and GLAS in the same region also show similar difficulties with MODIS cloud retrievals. The consistent detection of clouds through out the day is needed to provide reliable cloud and radiation products for CERES and other research efforts involving the modeling of clouds and their interaction with the radiation budget.
Submillimeter heterodyne detection of interstellar carbon monoxide at 434 micrometers
NASA Technical Reports Server (NTRS)
Fetterman, H. R.; Clifton, B. J.; Peck, D. D.; Tannenwald, P. E.; Koepf, G. A.; Goldsmith, P. F.; Erickson, N. R.; Buhl, D.; Mcavoy, N.
1981-01-01
Laser heterodyne observations of submillimeter emissions from carbon monoxide in the Orion molecular cloud are reported. High frequency and spatial resolution observations were made at the NASA Infrared Telescope Facility on Mauna Kea by the use of an optically pumped laser local oscillator and quasi-optical Schottky diode mixer for heterodyne detection of the J = 6 - 5 rotational transition of CO at 434 microns. Spectral analysis of the 434-micron emission indicates that the emitting gas is optically thin and is at a temperature above 180 K. Results thus demonstrate the potential contributions of ground-based high-resolution submillimeter astronomy to the study of active regions in interstellar molecular clouds.
NASA Technical Reports Server (NTRS)
Wu, D. L.; Kelly, M.A.; Yee, J.-H.; Boldt, J.; Demajistre, R.; Reynolds, E. L.; Tripoli, G. J.; Oman, L. D.; Prive, N.; Heidinger, A. K.;
2016-01-01
The CubeSat Constellation Cloud Winds (C3Winds) is a NASA Earth Venture Instrument (EV-I) concept with the primary objective to better understand mesoscale dynamics and their structures in severe weather systems. With potential catastrophic damage and loss of life, strong extratropical and tropical cyclones (ETCs and TCs) have profound three-dimensional impacts on the atmospheric dynamic and thermodynamic structures, producing complex cloud precipitation patterns, strong low-level winds, extensive tropopause folds, and intense stratosphere-troposphere exchange. Employing a compact, stereo IR-visible imaging technique from two formation-flying CubeSats, C3Winds seeks to measure and map high-resolution (2 km) cloud motion vectors (CMVs) and cloud geometric height (CGH) accurately by tracking cloud features within 5-15 min. Complementary to lidar wind observations from space, the high-resolution wind fields from C3Winds will allow detailed investigations on strong low-level wind formation in an occluded ETC development, structural variations of TC inner-core rotation, and impacts of tropopause folding events on tropospheric ozone and air quality. Together with scatterometer ocean surface winds, C3Winds will provide a more comprehensive depiction of atmosphere-boundary-layer dynamics and interactive processes. Built upon mature imaging technologies and long history of stereoscopic remote sensing, C3Winds provides an innovative, cost-effective solution to global wind observations with potential of increased diurnal sampling via CubeSat constellation.
NASA Technical Reports Server (NTRS)
Molthan, A. L.; Haynes, J. A.; Case, J. L.; Jedlovec, G. L.; Lapenta, W. M.
2008-01-01
As computational power increases, operational forecast models are performing simulations with higher spatial resolution allowing for the transition from sub-grid scale cloud parameterizations to an explicit forecast of cloud characteristics and precipitation through the use of single- or multi-moment bulk water microphysics schemes. investments in space-borne and terrestrial remote sensing have developed the NASA CloudSat Cloud Profiling Radar and the NOAA National Weather Service NEXRAD system, each providing observations related to the bulk properties of clouds and precipitation through measurements of reflectivity. CloudSat and NEXRAD system radars observed light to moderate snowfall in association with a cold-season, midlatitude cyclone traversing the Central United States in February 2007. These systems are responsible for widespread cloud cover and various types of precipitation, are of economic consequence, and pose a challenge to operational forecasters. This event is simulated with the Weather Research and Forecast (WRF) Model, utilizing the NASA Goddard Cumulus Ensemble microphysics scheme. Comparisons are made between WRF-simulated and observed reflectivity available from the CloudSat and NEXRAD systems. The application of CloudSat reflectivity is made possible through the QuickBeam radiative transfer model, with cautious application applied in light of single scattering characteristics and spherical target assumptions. Significant differences are noted within modeled and observed cloud profiles, based upon simulated reflectivity, and modifications to the single-moment scheme are tested through a supplemental WRF forecast that incorporates a temperature dependent snow crystal size distribution.
Clouds Aerosols Internal Affaires: Increasing Cloud Fraction and Enhancing the Convection
NASA Technical Reports Server (NTRS)
Koren, Ilan; Kaufman, Yoram; Remer, Lorraine; Rosenfeld, Danny; Rudich, Yinon
2004-01-01
Clouds developing in a polluted environment have more numerous, smaller cloud droplets that can increase the cloud lifetime and liquid water content. Such changes in the cloud droplet properties may suppress low precipitation allowing development of a stronger convection and higher freezing level. Delaying the washout of the cloud water (and aerosol), and the stronger convection will result in higher clouds with longer life time and larger anvils. We show these effects by using large statistics of the new, 1km resolution data from MODIS on the Terra satellite. We isolate the aerosol effects from meteorology by regression and showing that aerosol microphysical effects increases cloud fraction by average of 30 presents for all cloud types and increases convective cloud top pressure by average of 35mb. We analyze the aerosol cloud interaction separately for high pressure trade wind cloud systems and separately for deep convective cloud systems. The resultant aerosol radiative effect on climate for the high pressure cloud system is: -10 to -13 W/sq m at the top of the atmosphere (TOA) and -11 to -14 W/sq m at the surface. For deeper convective clouds the forcing is: -4 to -5 W/sq m at the TOA and -6 to -7 W/sq m at the surface.
On the effective turbulence driving mode of molecular clouds formed in disc galaxies
NASA Astrophysics Data System (ADS)
Jin, Keitaro; Salim, Diane M.; Federrath, Christoph; Tasker, Elizabeth J.; Habe, Asao; Kainulainen, Jouni T.
2017-07-01
We determine the physical properties and turbulence driving mode of molecular clouds formed in numerical simulations of a Milky Way-type disc galaxy with parsec-scale resolution. The clouds form through gravitational fragmentation of the gas, leading to average values for mass, radii and velocity dispersion in good agreement with observations of Milky Way clouds. The driving parameter (b) for the turbulence within each cloud is characterized by the ratio of the density contrast (σ _{ρ /ρ _0}) to the average Mach number (M) within the cloud, b=σ _{ρ /ρ _0}/M. As shown in previous works, b ˜ 1/3 indicates solenoidal (divergence-free) driving and b ˜ 1 indicates compressive (curl-free) driving. We find that the average b value of all the clouds formed in the simulations has a lower limit of b > 0.2. Importantly, we find that b has a broad distribution, covering values from purely solenoidal to purely compressive driving. Tracking the evolution of individual clouds reveals that the b value for each cloud does not vary significantly over their lifetime. Finally, we perform a resolution study with minimum cell sizes of 8, 4, 2 and 1 pc and find that the average b value increases with increasing resolution. Therefore, we conclude that our measured b values are strictly lower limits and that a resolution better than 1 pc is required for convergence. However, regardless of the resolution, we find that b varies by factors of a few in all cases, which means that the effective driving mode alters significantly from cloud to cloud.
NASA Astrophysics Data System (ADS)
Rothmund, Sabrina; Niethammer, Uwe; Walter, Marco; Joswig, Manfred
2013-04-01
In recent years, the high-resolution and multi-temporal 3D mapping of the Earth's surface using terrestrial laser scanning (TLS), ground-based optical images and especially low-cost UAV-based aerial images (Unmanned Aerial Vehicle) has grown in importance. This development resulted from the progressive technical improvement of the imaging systems and the freely available multi-view stereo (MVS) software packages. These different methods of data acquisition for the generation of accurate, high-resolution digital surface models (DSMs) were applied as part of an eight-week field campaign at the Super-Sauze landslide (South French Alps). An area of approximately 10,000 m² with long-term average displacement rates greater than 0.01 m/day has been investigated. The TLS-based point clouds were acquired at different viewpoints with an average point spacing between 10 to 40 mm and at different dates. On these days, more than 50 optical images were taken on points along a predefined line on the side part of the landslide by a low-cost digital compact camera. Additionally, aerial images were taken by a radio-controlled mini quad-rotor UAV equipped with another low-cost digital compact camera. The flight altitude ranged between 20 m and 250 m and produced a corresponding ground resolution between 0.6 cm and 7 cm. DGPS measurements were carried out as well in order to geo-reference and validate the point cloud data. To generate unscaled photogrammetric 3D point clouds from a disordered and tilted image set, we use the widespread open-source software package Bundler and PMVS2 (University of Washington). These multi-temporal DSMs are required on the one hand to determine the three-dimensional surface deformations and on the other hand it will be required for differential correction for orthophoto production. Drawing on the example of the acquired data at the Super-Sauze landslide, we demonstrate the potential but also the limitations of the photogrammetric point clouds. To determine the quality of the photogrammetric point cloud, these point clouds are compared with the TLS-based DSMs. The comparison shows that photogrammetric points accuracies are in the range of cm to dm, therefore don't reach the quality of the high-resolution TLS-based DSMs. Further, the validation of the photogrammetric point clouds reveals that some of them have internal curvature effects. The advantage of the photogrammetric 3D data acquisition is the use of low-cost equipment and less time-consuming data collection in the field. While the accuracy of the photogrammetric point clouds is not as high as TLS-based DSMs, the advantages of the former method are seen when applied in areas where dm-range is sufficient.
Low cost, high performance processing of single particle cryo-electron microscopy data in the cloud
Cianfrocco, Michael A; Leschziner, Andres E
2015-01-01
The advent of a new generation of electron microscopes and direct electron detectors has realized the potential of single particle cryo-electron microscopy (cryo-EM) as a technique to generate high-resolution structures. Calculating these structures requires high performance computing clusters, a resource that may be limiting to many likely cryo-EM users. To address this limitation and facilitate the spread of cryo-EM, we developed a publicly available ‘off-the-shelf’ computing environment on Amazon's elastic cloud computing infrastructure. This environment provides users with single particle cryo-EM software packages and the ability to create computing clusters with 16–480+ CPUs. We tested our computing environment using a publicly available 80S yeast ribosome dataset and estimate that laboratories could determine high-resolution cryo-EM structures for $50 to $1500 per structure within a timeframe comparable to local clusters. Our analysis shows that Amazon's cloud computing environment may offer a viable computing environment for cryo-EM. DOI: http://dx.doi.org/10.7554/eLife.06664.001 PMID:25955969
The structure and phase of cloud tops as observed by polarization lidar
NASA Technical Reports Server (NTRS)
Spinhirne, J. D.; Hansen, M. Z.; Simpson, J.
1983-01-01
High-resolution observations of the structure of cloud tops have been obtained with polarization lidar operated from a high altitude aircraft. Case studies of measurements acquired from cumuliform cloud systems are presented, two from September 1979 observations in the area of Florida and adjacent waters and a third during the May 1981 CCOPE experiment in southeast Montana. Accurate cloud top height structure and relative density of hydrometers are obtained from the lidar return signal intensity. Correlation between the signal return intensity and active updrafts was noted. Thin cirrus overlying developing turrets was observed in some cases. Typical values of the observed backscatter cross section were 0.1-5 (km/sr) for cumulonimbus tops. The depolarization ratio of the lidar signals was a function of the thermodynamic phase of cloud top areas. An increase of the cloud top depolarization with decreasing temperature was found for temperatures above and below -40 C.
Pattern recognition analysis of polar clouds during summer and winter
NASA Technical Reports Server (NTRS)
Ebert, Elizabeth E.
1992-01-01
A pattern recognition algorithm is demonstrated which classifies eighteen surface and cloud types in high-latitude AVHRR imagery based on several spectral and textural features, then estimates the cloud properties (fractional coverage, albedo, and brightness temperature) using a hybrid histogram and spatial coherence technique. The summertime version of the algorithm uses both visible and infrared data (AVHRR channels 1-4), while the wintertime version uses only infrared data (AVHRR channels 3-5). Three days of low-resolution AVHRR imagery from the Arctic and Antarctic during January and July 1984 were analyzed for cloud type and fractional coverage. The analysis showed significant amounts of high cloudiness in the Arctic during one day in winter. The Antarctic summer scene was characterized by heavy cloud cover in the southern ocean and relatively clear conditions in the continental interior. A large region of extremely low brightness temperatures in East Antarctica during winter suggests the presence of polar stratospheric cloud.
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.
Compression and ablation of the photo-irradiated molecular cloud the Orion Bar.
Goicoechea, Javier R; Pety, Jérôme; Cuadrado, Sara; Cernicharo, José; Chapillon, Edwige; Fuente, Asunción; Gerin, Maryvonne; Joblin, Christine; Marcelino, Nuria; Pilleri, Paolo
2016-09-08
The Orion Bar is the archetypal edge-on molecular cloud surface illuminated by strong ultraviolet radiation from nearby massive stars. Our relative closeness to the Orion nebula (about 1,350 light years away from Earth) means that we can study the effects of stellar feedback on the parental cloud in detail. Visible-light observations of the Orion Bar show that the transition between the hot ionized gas and the warm neutral atomic gas (the ionization front) is spatially well separated from the transition between atomic and molecular gas (the dissociation front), by about 15 arcseconds or 6,200 astronomical units (one astronomical unit is the Earth-Sun distance). Static equilibrium models used to interpret previous far-infrared and radio observations of the neutral gas in the Orion Bar (typically at 10-20 arcsecond resolution) predict an inhomogeneous cloud structure comprised of dense clumps embedded in a lower-density extended gas component. Here we report one-arcsecond-resolution millimetre-wave images that allow us to resolve the molecular cloud surface. In contrast to stationary model predictions, there is no appreciable offset between the peak of the H 2 vibrational emission (delineating the H/H 2 transition) and the edge of the observed CO and HCO + emission. This implies that the H/H 2 and C + /C/CO transition zones are very close. We find a fragmented ridge of high-density substructures, photoablative gas flows and instabilities at the molecular cloud surface. The results suggest that the cloud edge has been compressed by a high-pressure wave that is moving into the molecular cloud, demonstrating that dynamical and non-equilibrium effects are important for the cloud evolution.
Compression and ablation of the photo-irradiated molecular cloud the Orion Bar
NASA Astrophysics Data System (ADS)
Goicoechea, Javier R.; Pety, Jérôme; Cuadrado, Sara; Cernicharo, José; Chapillon, Edwige; Fuente, Asunción; Gerin, Maryvonne; Joblin, Christine; Marcelino, Nuria; Pilleri, Paolo
2016-09-01
The Orion Bar is the archetypal edge-on molecular cloud surface illuminated by strong ultraviolet radiation from nearby massive stars. Our relative closeness to the Orion nebula (about 1,350 light years away from Earth) means that we can study the effects of stellar feedback on the parental cloud in detail. Visible-light observations of the Orion Bar show that the transition between the hot ionized gas and the warm neutral atomic gas (the ionization front) is spatially well separated from the transition between atomic and molecular gas (the dissociation front), by about 15 arcseconds or 6,200 astronomical units (one astronomical unit is the Earth-Sun distance). Static equilibrium models used to interpret previous far-infrared and radio observations of the neutral gas in the Orion Bar (typically at 10-20 arcsecond resolution) predict an inhomogeneous cloud structure comprised of dense clumps embedded in a lower-density extended gas component. Here we report one-arcsecond-resolution millimetre-wave images that allow us to resolve the molecular cloud surface. In contrast to stationary model predictions, there is no appreciable offset between the peak of the H2 vibrational emission (delineating the H/H2 transition) and the edge of the observed CO and HCO+ emission. This implies that the H/H2 and C+/C/CO transition zones are very close. We find a fragmented ridge of high-density substructures, photoablative gas flows and instabilities at the molecular cloud surface. The results suggest that the cloud edge has been compressed by a high-pressure wave that is moving into the molecular cloud, demonstrating that dynamical and non-equilibrium effects are important for the cloud evolution.
NASA Astrophysics Data System (ADS)
Broich, Mark
Humid tropical forest cover loss is threatening the sustainability of ecosystem goods and services as vast forest areas are rapidly cleared for industrial scale agriculture and tree plantations. Despite the importance of humid tropical forest in the provision of ecosystem services and economic development opportunities, the spatial and temporal distribution of forest cover loss across large areas is not well quantified. Here I improve the quantification of humid tropical forest cover loss using two remote sensing-based methods: sampling and wall-to-wall mapping. In all of the presented studies, the integration of coarse spatial, high temporal resolution data with moderate spatial, low temporal resolution data enable advances in quantifying forest cover loss in the humid tropics. Imagery from the Moderate Resolution Imaging Spectroradiometer (MODIS) are used as the source of coarse spatial resolution, high temporal resolution data and imagery from the Landsat Enhanced Thematic Mapper Plus (ETM+) sensor are used as the source of moderate spatial, low temporal resolution data. In a first study, I compare the precision of different sampling designs for the Brazilian Amazon using the annual deforestation maps derived by the Brazilian Space Agency for reference. I show that sampling designs can provide reliable deforestation estimates; furthermore, sampling designs guided by MODIS data can provide more efficient estimates than the systematic design used for the United Nations Food and Agricultural Organization Forest Resource Assessment 2010. Sampling approaches, such as the one demonstrated, are viable in regions where data limitations, such as cloud contamination, limit exhaustive mapping methods. Cloud-contaminated regions experiencing high rates of change include Insular Southeast Asia, specifically Indonesia and Malaysia. Due to persistent cloud cover, forest cover loss in Indonesia has only been mapped at a 5-10 year interval using photo interpretation of single best Landsat images. Such an approach does not provide timely results, and cloud cover reduces the utility of map outputs. In a second study, I develop a method to exhaustively mine the recently opened Landsat archive for cloud-free observations and automatically map forest cover loss for Sumatra and Kalimantan for the 2000-2005 interval. In a comparison with a reference dataset consisting of 64 Landsat sample blocks, I show that my method, using per pixel time-series, provides more accurate forest cover loss maps for multiyear intervals than approaches using image composites. In a third study, I disaggregate Landsat-mapped forest cover loss, mapped over a multiyear interval, by year using annual forest cover loss maps generated from coarse spatial, high temporal resolution MODIS imagery. I further disaggregate and analyze forest cover loss by forest land use, and provinces. Forest cover loss trends show high spatial and temporal variability. These results underline the importance of annual mapping for the quantification of forest cover loss in Indonesia, specifically in the light of the developing Reducing Emissions from Deforestation and Forest Degradation in Developing Countries policy framework (REDD). All three studies highlight the advances in quantifying forest cover loss in the humid tropics made by integrating coarse spatial, high temporal resolution data with moderate spatial, low temporal resolution data. The three methods presented can be combined into an integrated monitoring strategy.
NASA Astrophysics Data System (ADS)
Bonev, George; Gladkova, Irina; Grossberg, Michael; Romanov, Peter; Helfrich, Sean
2016-09-01
The ultimate objective of this work is to improve characterization of the ice cover distribution in the polar areas, to improve sea ice mapping and to develop a new automated real-time high spatial resolution multi-sensor ice extent and ice edge product for use in operational applications. Despite a large number of currently available automated satellite-based sea ice extent datasets, analysts at the National Ice Center tend to rely on original satellite imagery (provided by satellite optical, passive microwave and active microwave sensors) mainly because the automated products derived from satellite optical data have gaps in the area coverage due to clouds and darkness, passive microwave products have poor spatial resolution, automated ice identifications based on radar data are not quite reliable due to a considerable difficulty in discriminating between the ice cover and rough ice-free ocean surface due to winds. We have developed a multisensor algorithm that first extracts maximum information on the sea ice cover from imaging instruments VIIRS and MODIS, including regions covered by thin, semitransparent clouds, then supplements the output by the microwave measurements and finally aggregates the results into a cloud gap free daily product. This ability to identify ice cover underneath thin clouds, which is usually masked out by traditional cloud detection algorithms, allows for expansion of the effective coverage of the sea ice maps and thus more accurate and detailed delineation of the ice edge. We have also developed a web-based monitoring system that allows comparison of our daily ice extent product with the several other independent operational daily products.
NASA Technical Reports Server (NTRS)
Feng, Lian; Hu, Chuanmin; Barnes, Brian B.; Mannino, Antonio; Heidinger, Andrew K.; Strabala, Kathleen; Iraci, Laura T.
2017-01-01
Knowledge of cloud cover, frequency, and duration is not only important to study cloud dynamics, but also critical in determining when and where to take ocean measurements from geostationary orbits such as the Geostationary Coastal and Air Pollution Events (GEO-CAPE) mission due to the challenges in achieving complete hemispheric coverage of coastal oceans, estuaries, and inland waters at hourly frequency. Using GOES hourly measurements at 4 km nadir resolution between 2006 and 2011, the number of cloud-free hourly observations per day (N(sub cf)) for solar zenith angle Theta(sub 0) less than 80 degrees was estimated for each 0.1 degree location of the Intra-Americas Sea. The number of Sun-glint-affected hourly observations per day [Ns(sub sg)] was also calculated based on the planned GEO-CAPE observation geometry and realistic wind speed. High-latitude and equatorial oceans showed the lowest N(sub cf) (less than 2.4) in all climatological months, and highest N(sub cf) was observed in the Gulf of Mexico (GoM) and Caribbean (greater than 4.5). Different regions showed differences in seasonality of cloud-free conditions and also showed differences in the hour of a day at which the satellite observations would have the maximal cloud-free and glint-free probability (Temperature maximum). Cloud cover from Moderate Resolution Imaging Spectroradiometer (MODIS) 1 km measurements are greater than 10 degrees higher than those from the MODIS 250 m measurements, supporting ocean color missions at subkilometer resolutions to enhance both spatial coverage and temporal frequency. These findings provide valuable information for GEO-CAPE mission planning to maximize its science value through minimizing the impacts of clouds and Sun glint.
NASA Astrophysics Data System (ADS)
Feng, Lian; Hu, Chuanmin; Barnes, Brian B.; Mannino, Antonio; Heidinger, Andrew K.; Strabala, Kathleen; Iraci, Laura T.
2017-02-01
Knowledge of cloud cover, frequency, and duration is not only important to study cloud dynamics, but also critical in determining when and where to take ocean measurements from geostationary orbits such as the Geostationary Coastal and Air Pollution Events (GEO-CAPE) mission due to the challenges in achieving complete hemispheric coverage of coastal oceans, estuaries, and inland waters at hourly frequency. Using GOES hourly measurements at 4 km nadir resolution between 2006 and 2011, the number of cloud-free hourly observations per day (Ncf) for solar zenith angle θo < 80° was estimated for each 0.1° location of the Intra-Americas Sea. The number of Sun-glint-affected hourly observations per day (Nsg) was also calculated based on the planned GEO-CAPE observation geometry and realistic wind speed. High-latitude and equatorial oceans showed the lowest Ncf (<2.4) in all climatological months, and highest Ncf was observed in the Gulf of Mexico (GoM) and Caribbean (>4.5). Different regions showed differences in seasonality of cloud-free conditions and also showed differences in the hour of a day at which the satellite observations would have the maximal cloud-free and glint-free probability (Tmax). Cloud cover from Moderate Resolution Imaging Spectroradiometer (MODIS) 1 km measurements are >10% higher than those from the MODIS 250 m measurements, supporting ocean color missions at subkilometer resolutions to enhance both spatial coverage and temporal frequency. These findings provide valuable information for GEO-CAPE mission planning to maximize its science value through minimizing the impacts of clouds and Sun glint.
NASA Astrophysics Data System (ADS)
Schmid, H. M.; Bazzon, A.; Milli, J.; Roelfsema, R.; Engler, N.; Mouillet, D.; Lagadec, E.; Sissa, E.; Sauvage, J.-F.; Ginski, C.; Baruffolo, A.; Beuzit, J. L.; Boccaletti, A.; Bohn, A. J.; Claudi, R.; Costille, A.; Desidera, S.; Dohlen, K.; Dominik, C.; Feldt, M.; Fusco, T.; Gisler, D.; Girard, J. H.; Gratton, R.; Henning, T.; Hubin, N.; Joos, F.; Kasper, M.; Langlois, M.; Pavlov, A.; Pragt, J.; Puget, P.; Quanz, S. P.; Salasnich, B.; Siebenmorgen, R.; Stute, M.; Suarez, M.; Szulágyi, J.; Thalmann, C.; Turatto, M.; Udry, S.; Vigan, A.; Wildi, F.
2017-06-01
Context. R Aqr is a symbiotic binary system consisting of a mira variable, a hot companion with a spectacular jet outflow, and an extended emission line nebula. Because of its proximity to the Sun, this object has been studied in much detail with many types of high resolution imaging and interferometric techniques. We have used R Aqr as test target for the visual camera subsystem ZIMPOL, which is part of the new extreme adaptive optics (AO) instrument SPHERE at the Very Large Telescope (VLT). Aims: We describe SPHERE/ZIMPOL test observations of the R Aqr system taken in Hα and other filters in order to demonstrate the exceptional performance of this high resolution instrument. We compare our observations with data from the Hubble Space Telescope (HST) and illustrate the complementarity of the two instruments. We use our data for a detailed characterization of the inner jet region of R Aqr. Methods: We analyze the high resolution ≈ 25 mas images from SPHERE/ZIMPOL and determine from the Hα emission the position, size, geometric structure, and line fluxes of the jet source and the clouds in the innermost region <2'' (<400 AU) of R Aqr. The data are compared to simultaneous HST line filter observations. The Hα fluxes and the measured sizes of the clouds yield Hα emissivities for many clouds from which one can derive the mean density, mass, recombination time scale, and other cloud parameters. Results: Our Hα data resolve for the first time the R Aqr binary and we measure for the jet source a relative position 45 mas West (position angle -89.5°) of the mira. The central jet source is the strongest Hα component with a flux of about 2.5 × 10-12 erg cm-2 s-1. North east and south west from the central source there are many clouds with very diverse structures. Within 0.5'' (100 AU) we see in the SW a string of bright clouds arranged in a zig-zag pattern and, further out, at 1''-2'', fainter and more extended bubbles. In the N and NE we see a bright, very elongated filamentary structure between 0.2''-0.7'' and faint perpendicular "wisps" further out. Some jet clouds are also detected in the ZIMPOL [O I] and He I filters, as well as in the HST-WFC3 line filters for Hα, [O III], [N II], and [O I]. We determine jet cloud parameters and find a very well defined correlation Ne ∝ r-1.3 between cloud density and distance to the central binary. Densities are very high with typical values of Ne ≈ 3 × 105 cm-3 for the "outer" clouds around 300 AU, Ne ≈ 3 × 106 cm-3 for the "inner" clouds around 50 AU, and even higher for the central jet source. The high Ne of the clouds implies short recombination or variability timescales of a year or shorter. Conclusions: Hα high resolution data provide a lot of diagnostic information for the ionized jet gas in R Aqr. Future Hα observations will provide the orientation of the orbital plane of the binary and allow detailed hydrodynamical investigations of this jet outflow and its interaction with the wind of the red giant companion. The reduced Hα image given in Fig. 6 is only available at the CDS via anonymous ftp to http://cdsarc.u-strasbg.fr (http://130.79.128.5) or via http://cdsarc.u-strasbg.fr/viz-bin/qcat?J/A+A/602/A53
Cloud Type Classification (cldtype) Value-Added Product
DOE Office of Scientific and Technical Information (OSTI.GOV)
Flynn, Donna; Shi, Yan; Lim, K-S
The Cloud Type (cldtype) value-added product (VAP) provides an automated cloud type classification based on macrophysical quantities derived from vertically pointing lidar and radar. Up to 10 layers of clouds are classified into seven cloud types based on predetermined and site-specific thresholds of cloud top, base and thickness. Examples of thresholds for selected U.S. Department of Energy (DOE) Atmospheric Radiation Measurement (ARM) Climate Research Facility sites are provided in Tables 1 and 2. Inputs for the cldtype VAP include lidar and radar cloud boundaries obtained from the Active Remotely Sensed Cloud Location (ARSCL) and Surface Meteorological Systems (MET) data. Rainmore » rates from MET are used to determine when radar signal attenuation precludes accurate cloud detection. Temporal resolution and vertical resolution for cldtype are 1 minute and 30 m respectively and match the resolution of ARSCL. The cldtype classification is an initial step for further categorization of clouds. It was developed for use by the Shallow Cumulus VAP to identify potential periods of interest to the LASSO model and is intended to find clouds of interest for a variety of users.« less
Time-resolved High Spectral Resolution Observation of 2MASSW J0746425+200032AB
DOE Office of Scientific and Technical Information (OSTI.GOV)
Wang, Ji; Mawet, Dimitri; Prato, Lisa, E-mail: ji.wang@caltech.edu
Many brown dwarfs (BDs) exhibit photometric variability at levels from tenths to tens of percents. The photometric variability is related to magnetic activity or patchy cloud coverage, characteristic of BDs near the L–T transition. Time-resolved spectral monitoring of BDs provides diagnostics of cloud distribution and condensate properties. However, current time-resolved spectral studies of BDs are limited to low spectral resolution ( R ∼ 100) with the exception of the study of Luhman 16 AB at a resolution of 100,000 using the VLT+CRIRES. This work yielded the first map of BD surface inhomogeneity, highlighting the importance and unique contribution of highmore » spectral resolution observations. Here, we report on the time-resolved high spectral resolution observations of a nearby BD binary, 2MASSW J0746425+200032AB. We find no coherent spectral variability that is modulated with rotation. Based on simulations, we conclude that the coverage of a single spot on 2MASSW J0746425+200032AB is smaller than 1% or 6.25% if spot contrast is 50% or 80% of its surrounding flux, respectively. Future high spectral resolution observations aided by adaptive optics systems can put tighter constraints on the spectral variability of 2MASSW J0746425+200032AB and other nearby BDs.« less
NASA Astrophysics Data System (ADS)
Davis, A. B.; von Allmen, P. A.; Marshak, A.; Bal, G.
2010-12-01
The geometrical assumption in all operational cloud remote sensing algorithms is that clouds are plane-parallel slabs, which applies relatively well to the most uniform stratus layers. Its benefit is to justify using classic 1D radiative transfer (RT) theory, where angular details (solar, viewing, azimuthal) are fully accounted for and precise phase functions can be used, to generate the look-up tables used in the retrievals. Unsurprisingly, these algorithms catastrophically fail when applied to cumulus-type clouds, which are highly 3D. This is unfortunate for the cloud-process modeling community that may thrive on in situ airborne data, but would very much like to use satellite data for more than illustrations in their presentations and publications. So, how can we obtain quantitative information from space-based observations of finite aspect ratio clouds? Cloud base/top heights, vertically projected area, mean liquid water content (LWC), and volume-averaged droplet size would be a good start. Motivated by this science need, we present a new approach suitable for sparse cumulus fields where we turn the tables on the standard procedure in cloud remote sensing. We make no a priori assumption about cloud shape, save an approximately flat base, but use brutal approximations about the RT that is necessarily 3D. Indeed, the first order of business is to roughly determine the cloud's outer shape in one of two ways, which we will frame as competing initial guesses for the next phase of shape refinement and volume-averaged microphysical parameter estimation. Both steps use multi-pixel/multi-angle techniques amenable to MISR data, the latter adding a bi-spectral dimension using collocated MODIS data. One approach to rough cloud shape determination is to fit the multi-pixel/multi-angle data with a geometric primitive such as a scalene hemi-ellipsoid with 7 parameters (translation in 3D space, 3 semi-axes, 1 azimuthal orientation); for the radiometry, a simple radiosity-type model is used where the cloud surface "emits" either reflected (sunny-side) or transmitted (shady-side) light at different levels. As it turns out, the reflected/transmitted light ratio yields an approximate cloud optical thickness. Another approach is to invoke tomography techniques to define the volume occupied by the cloud using, as it were, cloud masks for each direction of observation. In the shape and opacity refinement phase, initial guesses along with solar and viewing geometry information are used to predict radiance in each pixel using a fast diffusion model for the 3D RT in MISR's non-absorbing red channel (275 m resolution). Refinement is constrained and stopped when optimal resolution is reached. Finally, multi-pixel/mono-angle MODIS data for the same cloud (at comparable 250 m resolution) reveals the desired droplet size information, hence the volume-averaged LWC. This is an ambitious remote sensing science project drawing on cross-disciplinary expertise gained in medical imaging using both X-ray and near-IR sources and detectors. It is high risk but with potentially high returns not only for the cloud modeling community but also aerosol and surface characterization in the presence of broken 3D clouds.
Venus' night side atmospheric dynamics using near infrared observations from VEx/VIRTIS and TNG/NICS
NASA Astrophysics Data System (ADS)
Mota Machado, Pedro; Peralta, Javier; Luz, David; Gonçalves, Ruben; Widemann, Thomas; Oliveira, Joana
2016-10-01
We present night side Venus' winds based on coordinated observations carried out with Venus Express' VIRTIS instrument and the Near Infrared Camera (NICS) of the Telescopio Nazionale Galileo (TNG). With NICS camera, we acquired images of the continuum K filter at 2.28 μm, which allows to monitor motions at the Venus' lower cloud level, close to 48 km altitude. We will present final results of cloud tracked winds from ground-based TNG observations and from coordinated space-based VEx/VIRTIS observations.The Venus' lower cloud deck is centred at 48 km of altitude, where fundamental dynamical exchanges that help maintain superrotation are thought to occur. The lower Venusian atmosphere is a strong source of thermal radiation, with the gaseous CO2 component allowing radiation to escape in windows at 1.74 and 2.28 μm. At these wavelengths radiation originates below 35 km and unit opacity is reached at the lower cloud level, close to 48 km. Therefore, it is possible to observe the horizontal cloud structure, with thicker clouds seen silhouetted against the bright thermal background from the low atmosphere. By continuous monitoring of the horizontal cloud structure at 2.28 μm (NICS Kcont filter), it is possible to determine wind fields using the technique of cloud tracking. We acquired a series of short exposures of the Venus disk. Cloud displacements in the night side of Venus were computed taking advantage of a phase correlation semi-automated technique. The Venus apparent diameter at observational dates was greater than 32" allowing a high spatial precision. The 0.13" pixel scale of the NICS narrow field camera allowed to resolve ~3-pixel displacements. The absolute spatial resolution on the disk was ~100 km/px at disk center, and the (0.8-1") seeing-limited resolution was ~400 km/px. By co-adding the best images and cross-correlating regions of clouds the effective resolution was significantly better than the seeing-limited resolution. In order to correct for scattered light from the (saturated) day side crescent into the night side, a set of observations with a Br Υ filter were performed. Cloud features are invisible at this wavelength, and this technique allowed for a good correction of scattered light.
HIGH-VELOCITY CLOUDS IN THE GALACTIC ALL SKY SURVEY. I. CATALOG
DOE Office of Scientific and Technical Information (OSTI.GOV)
Moss, V. A.; Kummerfeld, J. K.; McClure-Griffiths, N. M.
2013-11-01
We present a catalog of high-velocity clouds (HVCs) from the Galactic All Sky Survey (GASS) of southern sky neutral hydrogen, which has 57 mK sensitivity and 1 km s{sup –1} velocity resolution and was obtained with the Parkes Telescope. Our catalog has been derived from the stray-radiation-corrected second release of GASS. We describe the data and our method of identifying HVCs and analyze the overall properties of the GASS population. We catalog a total of 1693 HVCs at declinations <0°, including 1111 positive velocity HVCs and 582 negative velocity HVCs. Our catalog also includes 295 anomalous velocity clouds (AVCs). Themore » cloud line-widths of our HVC population have a median FWHM of ∼19 km s{sup –1}, which is lower than that found in previous surveys. The completeness of our catalog is above 95% based on comparison with the HIPASS catalog of HVCs upon which we improve by an order of magnitude in spectral resolution. We find 758 new HVCs and AVCs with no HIPASS counterpart. The GASS catalog will shed unprecedented light on the distribution and kinematic structure of southern sky HVCs, as well as delve further into the cloud populations that make up the anomalous velocity gas of the Milky Way.« less
NASA Astrophysics Data System (ADS)
Wing, Allison; Camargo, Suzana; Sobel, Adam; Kim, Daehyun; Murakami, Hiroyuki; Reed, Kevin; Vecchi, Gabriel; Wehner, Michael; Zarzycki, Colin; Zhao, Ming
2017-04-01
In recent years, climate models have improved such that high-resolution simulations are able to reproduce the climatology of tropical cyclone activity with some fidelity and show some skill in seasonal forecasting. However biases remain in many models, motivating a better understanding of what factors control the representation of tropical cyclone activity in climate models. We explore the tropical cyclogenesis processes in five high-resolution climate models, including both coupled and uncoupled configurations. Our analysis framework focuses on how convection, moisture, clouds and related processes are coupled and employs budgets of column moist static energy and the spatial variance of column moist static energy. The latter was originally developed to study the mechanisms of tropical convective organization in idealized cloud-resolving models, and allows us to quantify the different feedback processes responsible for the amplification of moist static energy anomalies associated with the organization of convection and cyclogenesis. We track the formation and evolution of tropical cyclones in the climate model simulations and apply our analysis both along the individual tracks and composited over many tropical cyclones. We then compare the genesis processes; in particular, the role of cloud-radiation interactions, to those of spontaneous tropical cyclogenesis in idealized cloud-resolving model simulations.
Ice clouds optical properties in the Far Infrared from the ECOWAR-COBRA Experiment
NASA Astrophysics Data System (ADS)
Rizzi, Rolando; Tosi, Ennio
ECOWAR-COBRA (Earth COoling by WAter vapouR emission -Campagna di Osservazioni della Banda Rotazionale del vapor d'Acqua) field campaign took place in Italy from 3 to 17 March 2007 with the main goal of studying the scarcely sensed atmospheric emission occurring beyond 17 microns. Instrumentation involved in the campaign included two different Fourier Transforms Spectrometers (FTS) : REFIR-PAD (at Testa Grigia Station, 3500 m a.s.l.) and FTIR-ABB (at Cervinia Station, 1990 m a.s.l.). In this work cloudy sky data have been ana-lyzed. A cloud properties retrieval methodology (RT-RET), based on high spectral resolution measurements in the atmospheric window (800-1000 cm-1), is applied to both FTS sensors. Cloud properties determined from the infrared retrievals are compared with those obtained from Raman lidar taken by the BASIL Lidar system that was operating at Cervinia station. Cloud microphysical and optical properties retrieved by RT-RET are used to perform forward simulations over the entire FTSs measurements spectral interval. Results are compared to FTS data to test the ability of single scattering ice crystals models to reproduce cloudy sky radiances in the Far Infra-Red (FIR) part of the spectrum. New methods to retrieve cloud optical and microphysical properties exploiting high spectral resolution FIR measurements are also investigated.
Cloud archiving and data mining of High-Resolution Rapid Refresh forecast model output
NASA Astrophysics Data System (ADS)
Blaylock, Brian K.; Horel, John D.; Liston, Samuel T.
2017-12-01
Weather-related research often requires synthesizing vast amounts of data that need archival solutions that are both economical and viable during and past the lifetime of the project. Public cloud computing services (e.g., from Amazon, Microsoft, or Google) or private clouds managed by research institutions are providing object data storage systems potentially appropriate for long-term archives of such large geophysical data sets. We illustrate the use of a private cloud object store developed by the Center for High Performance Computing (CHPC) at the University of Utah. Since early 2015, we have been archiving thousands of two-dimensional gridded fields (each one containing over 1.9 million values over the contiguous United States) from the High-Resolution Rapid Refresh (HRRR) data assimilation and forecast modeling system. The archive is being used for retrospective analyses of meteorological conditions during high-impact weather events, assessing the accuracy of the HRRR forecasts, and providing initial and boundary conditions for research simulations. The archive is accessible interactively and through automated download procedures for researchers at other institutions that can be tailored by the user to extract individual two-dimensional grids from within the highly compressed files. Characteristics of the CHPC object storage system are summarized relative to network file system storage or tape storage solutions. The CHPC storage system is proving to be a scalable, reliable, extensible, affordable, and usable archive solution for our research.
Predicting Decade-to-Century Climate Change: Prospects for Improving Models
NASA Technical Reports Server (NTRS)
Somerville, Richard C. J.
1999-01-01
Recent research has led to a greatly increased understanding of the uncertainties in today's climate models. In attempting to predict the climate of the 21st century, we must confront not only computer limitations on the affordable resolution of global models, but also a lack of physical realism in attempting to model key processes. Until we are able to incorporate adequate treatments of critical elements of the entire biogeophysical climate system, our models will remain subject to these uncertainties, and our scenarios of future climate change, both anthropogenic and natural, will not fully meet the requirements of either policymakers or the public. The areas of most-needed model improvements are thought to include air-sea exchanges, land surface processes, ice and snow physics, hydrologic cycle elements, and especially the role of aerosols and cloud-radiation interactions. Of these areas, cloud-radiation interactions are known to be responsible for much of the inter-model differences in sensitivity to greenhouse gases. Recently, we have diagnostically evaluated several current and proposed model cloud-radiation treatments against extensive field observations. Satellite remote sensing provides an indispensable component of the observational resources. Cloud-radiation parameterizations display a strong sensitivity to vertical resolution, and we find that vertical resolutions typically used in global models are far from convergence. We also find that newly developed advanced parameterization schemes with explicit cloud water budgets and interactive cloud radiative properties are potentially capable of matching observational data closely. However, it is difficult to evaluate the realism of model-produced fields of cloud extinction, cloud emittance, cloud liquid water content and effective cloud droplet radius until high-quality measurements of these quantities become more widely available. Thus, further progress will require a combination of theoretical and modeling research, together with intensified emphasis on both in situ and space-based remote sensing observations.
High-Resolution Surface Reconstruction from Imagery for Close Range Cultural Heritage Applications
NASA Astrophysics Data System (ADS)
Wenzel, K.; Abdel-Wahab, M.; Cefalu, A.; Fritsch, D.
2012-07-01
The recording of high resolution point clouds with sub-mm resolution is a demanding and cost intensive task, especially with current equipment like handheld laser scanners. We present an image based approached, where techniques of image matching and dense surface reconstruction are combined with a compact and affordable rig of off-the-shelf industry cameras. Such cameras provide high spatial resolution with low radiometric noise, which enables a one-shot solution and thus an efficient data acquisition while satisfying high accuracy requirements. However, the largest drawback of image based solutions is often the acquisition of surfaces with low texture where the image matching process might fail. Thus, an additional structured light projector is employed, represented here by the pseudo-random pattern projector of the Microsoft Kinect. Its strong infrared-laser projects speckles of different sizes. By using dense image matching techniques on the acquired images, a 3D point can be derived for almost each pixel. The use of multiple cameras enables the acquisition of a high resolution point cloud with high accuracy for each shot. For the proposed system up to 3.5 Mio. 3D points with sub-mm accuracy can be derived per shot. The registration of multiple shots is performed by Structure and Motion reconstruction techniques, where feature points are used to derive the camera positions and rotations automatically without initial information.
NASA Astrophysics Data System (ADS)
Xue, L.; Newman, A. J.; Ikeda, K.; Rasmussen, R.; Clark, M. P.; Monaghan, A. J.
2016-12-01
A high-resolution (a 1.5 km grid spacing domain nested within a 4.5 km grid spacing domain) 10-year regional climate simulation over the entire Hawaiian archipelago is being conducted at the National Center for Atmospheric Research (NCAR) using the Weather Research and Forecasting (WRF) model version 3.7.1. Numerical sensitivity simulations of the Hawaiian Rainband Project (HaRP, a filed experiment from July to August in 1990) showed that the simulated precipitation properties are sensitive to initial and lateral boundary conditions, sea surface temperature (SST), land surface models, vertical resolution and cloud droplet concentration. The validations of model simulated statistics of the trade wind inversion, temperature, wind field, cloud cover, and precipitation over the islands against various observations from soundings, satellites, weather stations and rain gauges during the period from 2003 to 2012 will be presented at the meeting.
NASA Astrophysics Data System (ADS)
Lopez-Gonzaga, N.
2015-09-01
The high resolution achieved by the instrument MIDI at the VLTI allowed to obtain more detail information about the geometry and structure of the nuclear mid-infrared emission of AGNs, but due to the lack of real images, the interpretation of the results is not an easy task. To profit more from the high resolution data, we developed a statistical tool that allows interpret these data using clumpy torus models. A statistical approach is needed to overcome effects such as, the randomness in the position of the clouds and the uncertainty of the true position angle on the sky. Our results, obtained by studying the mid-infrared emission at the highest resolution currently available, suggest that the dusty environment of Type I objects is formed by a lower number of clouds than Type II objects.
Land, Ocean and Ice sheet surface elevation retrieval from CALIPSO lidar measurements
NASA Astrophysics Data System (ADS)
Lu, X.; Hu, Y.
2013-12-01
Since launching in April 2006 the main objective of the Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) mission has been studying the climate impact of clouds and aerosols in the atmosphere. However, CALIPSO also collects information about other components of the Earth's ecosystem, such as lands, oceans and polar ice sheets. The objective of this study is to propose a Super-Resolution Altimetry (SRA) technique to provide high resolution of land, ocean and polar ice sheet surface elevation from CALIPSO single shot lidar measurements (70 m spot size). The land surface results by the new technique agree with the United States Geological Survey (USGS) National Elevation Database (NED) high-resolution elevation maps, and the ice sheet surface results in the region of Greenland and Antarctic compare very well with the Ice, Cloud and land Elevation Satellite (ICESat) laser altimetry measurements. The comparisons suggest that the obtained CALIPSO surface elevation information by the new technique is accurate to within 1 m. The effects of error sources on the retrieved surface elevation are discussed. Based on the new technique, the preliminary data products of along-track topography retrieved from the CALIPSO lidar measurements is available to the altimetry community for evaluation.
An efficient cloud detection method for high resolution remote sensing panchromatic imagery
NASA Astrophysics Data System (ADS)
Li, Chaowei; Lin, Zaiping; Deng, Xinpu
2018-04-01
In order to increase the accuracy of cloud detection for remote sensing satellite imagery, we propose an efficient cloud detection method for remote sensing satellite panchromatic images. This method includes three main steps. First, an adaptive intensity threshold value combined with a median filter is adopted to extract the coarse cloud regions. Second, a guided filtering process is conducted to strengthen the textural features difference and then we conduct the detection process of texture via gray-level co-occurrence matrix based on the acquired texture detail image. Finally, the candidate cloud regions are extracted by the intersection of two coarse cloud regions above and we further adopt an adaptive morphological dilation to refine them for thin clouds in boundaries. The experimental results demonstrate the effectiveness of the proposed method.
Spectral Invariant Behavior of Zenith Radiance Around Cloud Edges Observed by ARM SWS
NASA Technical Reports Server (NTRS)
Marshak, A.; Knyazikhin, Y.; Chiu, J. C.; Wiscombe, W. J.
2009-01-01
The ARM Shortwave Spectrometer (SWS) measures zenith radiance at 418 wavelengths between 350 and 2170 nm. Because of its 1-sec sampling resolution, the SWS provides a unique capability to study the transition zone between cloudy and clear sky areas. A spectral invariant behavior is found between ratios of zenith radiance spectra during the transition from cloudy to cloud-free. This behavior suggests that the spectral signature of the transition zone is a linear mixture between the two extremes (definitely cloudy and definitely clear). The weighting function of the linear mixture is a wavelength-independent characteristic of the transition zone. It is shown that the transition zone spectrum is fully determined by this function and zenith radiance spectra of clear and cloudy regions. An important result of these discoveries is that high temporal resolution radiance measurements in the clear-to-cloud transition zone can be well approximated by lower temporal resolution measurements plus linear interpolation.
NASA Astrophysics Data System (ADS)
Esmaili, Rebekah Bradley
Global climate models, numerical weather prediction, and flood models rely on accurate satellite precipitation products, which are the only datasets that are continuous in time and space across the globe. While there are more earth observing satellites than ever before, gaps in precipitation retrievals exist due to sensor and orbital limitations of low-earth (LEO) satellites, which are overcome by merging data from different sensors in satellite precipitation products (SPPs). Using cloud tracking at higher resolutions than the spatio-temporal scales of LEO satellites, this thesis examines how clouds typically form in the atmosphere, the rate that cloud size and temperature evolve over the life cycle, and the time of day that cloud development take place. This thesis found that cloud evolution was non-linear, which disagrees with the linear interpolation schemes used in SPPs. Longer lasting clouds tended to achieve their temperature and size maturity milestones at different times, while these stages often occurred simultaneously in shorter lasting clouds. Over the ocean, longer lasting clouds were found to occur more frequently at night, while shorter lasting clouds were more common during the daytime. This thesis also examines whether large-scale Saharan dust outbreaks can impact the trajectories and intensity of cloud clusters in the tropical Atlantic, which is predicted by modeling studies. The presented results show that proximity to Saharan dust outbreaks shifts Atlantic cloud development northward and intense storms becoming more common, whereas on days with low dust loading small-scale, warmer clouds are more common. A simplified view of cloud evolution in merged rainfall retrievals is a possible source of errors, which can propagate into higher level analysis. This thesis investigates the difference in the intensity, duration, and frequency of precipitation in IMERG, a next-generation satellite precipitation product with ground radar observations over the contiguous United States. There was agreement on seasonal totals, but closer examination shows that the average intensity and duration of events is too high, and too infrequent compared to events detected on the ground. Awareness of the strengths and limitations, particularly in context of high-resolution cloud development, can enhance SPPs and can complement climate model simulations.
Sinnige, Tessa; Daniëls, Mark; Baldus, Marc; Weingarth, Markus
2014-03-26
We show that selective labeling of proteins with protonated amino acids embedded in a perdeuterated matrix, dubbed 'proton clouds', provides general access to long-range contacts between nonexchangeable side chain protons in proton-detected solid-state NMR, which is important to study protein tertiary structure. Proton-cloud labeling significantly improves spectral resolution by simultaneously reducing proton line width and spectral crowding despite a high local proton density in clouds. The approach is amenable to almost all canonical amino acids. Our method is demonstrated on ubiquitin and the β-barrel membrane protein BamA.
NASA Astrophysics Data System (ADS)
Baars, Holger; Seifert, Patric; Engelmann, Ronny; Wandinger, Ulla
2017-09-01
Absolute calibrated signals at 532 and 1064 nm and the depolarization ratio from a multiwavelength lidar are used to categorize primary aerosol but also clouds in high temporal and spatial resolution. Automatically derived particle backscatter coefficient profiles in low temporal resolution (30 min) are applied to calibrate the lidar signals. From these calibrated lidar signals, new atmospheric parameters in temporally high resolution (quasi-particle-backscatter coefficients) are derived. By using thresholds obtained from multiyear, multisite EARLINET (European Aerosol Research Lidar Network) measurements, four aerosol classes (small; large, spherical; large, non-spherical; mixed, partly non-spherical) and several cloud classes (liquid, ice) are defined. Thus, particles are classified by their physical features (shape and size) instead of by source. The methodology is applied to 2 months of continuous observations (24 h a day, 7 days a week) with the multiwavelength-Raman-polarization lidar PollyXT during the High-Definition Clouds and Precipitation for advancing Climate Prediction (HD(CP)2) Observational Prototype Experiment (HOPE) in spring 2013. Cloudnet equipment was operated continuously directly next to the lidar and is used for comparison. By discussing three 24 h case studies, it is shown that the aerosol discrimination is very feasible and informative and gives a good complement to the Cloudnet target categorization. Performing the categorization for the 2-month data set of the entire HOPE campaign, almost 1 million pixel (5 min × 30 m) could be analysed with the newly developed tool. We find that the majority of the aerosol trapped in the planetary boundary layer (PBL) was composed of small particles as expected for a heavily populated and industrialized area. Large, spherical aerosol was observed mostly at the top of the PBL and close to the identified cloud bases, indicating the importance of hygroscopic growth of the particles at high relative humidity. Interestingly, it is found that on several days non-spherical particles were dispersed from the ground into the atmosphere.
Integrating expert- and algorithm-derived data to generate a hemispheric ice edge
NASA Astrophysics Data System (ADS)
Tsatsoulis, C.; Komp, E.
The Arctic ice edge is the area of the Arctic where sea ice concentration is less than 15%, and is considered navigable by most vessels. Experts at the National Ice Center generate a daily ice edge product that is available to the public. Data of preference is that of active, high resolution satellite sensors such as RADARSAT which yields all-weather images of 100m resolution, and a second source is OLS data with 550m resolution. Unfortunately, RADARSAT does not provide full, daily coverage of the Arctic and OLS can be obscured by clouds. The SSM/I sensor provides complete coverage of the Arctic at 25km resolution and is independent of cloud cover and solar illumination during the Arctic winter. SSM/I data is analyzed by the NASA Team algorithm to establish ice concentration. Our work integrates the ice edge created by experts using high resolution data with the ice edge generated out of the coarser SSM/I microwave data. The result is a product that combines human and algorithmic outputs, deals with gross differences in resolution of the underlying data sets, and results in a useful, operational product.
Mapping Mexico's Forest Lands with Advanced Very High Resolution Radiometer
David J. Evans; Zhiliang Zhu; Susan Eggen-McIntosh; Pedro García Mayoral; Jose Luis Ornelas de Anda
1992-01-01
Data from the Advanced Very High Resolution Radiometer (AVHRR) were used in a program sponsored by the U.S. Department of Agriculture, Forest Service, and the United Nations Food and Agriculture Organization to help scientists from Mexico generate forest-cover maps of that country. Two near-cloud-free composite images were generated for December and March 1990 from...
NASA Technical Reports Server (NTRS)
Putman, William M.
2010-01-01
The Goddard Earth Observing System Model (GEOS-S), an earth system model developed in the NASA Global Modeling and Assimilation Office (GMAO), has integrated the non-hydrostatic finite-volume dynamical core on the cubed-sphere grid. The extension to a non-hydrostatic dynamical framework and the quasi-uniform cubed-sphere geometry permits the efficient exploration of global weather and climate modeling at cloud permitting resolutions of 10- to 4-km on today's high performance computing platforms. We have explored a series of incremental increases in global resolution with GEOS-S from irs standard 72-level 27-km resolution (approx.5.5 million cells covering the globe from the surface to 0.1 hPa) down to 3.5-km (approx. 3.6 billion cells).
Discrimination of Biomass Burning Smoke and Clouds in MAIAC Algorithm
NASA Technical Reports Server (NTRS)
Lyapustin, A.; Korkin, S.; Wang, Y.; Quayle, B.; Laszlo, I.
2012-01-01
The multi-angle implementation of atmospheric correction (MAIAC) algorithm makes aerosol retrievals from MODIS data at 1 km resolution providing information about the fine scale aerosol variability. This information is required in different applications such as urban air quality analysis, aerosol source identification etc. The quality of high resolution aerosol data is directly linked to the quality of cloud mask, in particular detection of small (sub-pixel) and low clouds. This work continues research in this direction, describing a technique to detect small clouds and introducing the smoke test to discriminate the biomass burning smoke from the clouds. The smoke test relies on a relative increase of aerosol absorption at MODIS wavelength 0.412 micrometers as compared to 0.47-0.67 micrometers due to multiple scattering and enhanced absorption by organic carbon released during combustion. This general principle has been successfully used in the OMI detection of absorbing aerosols based on UV measurements. This paper provides the algorithm detail and illustrates its performance on two examples of wildfires in US Pacific North-West and in Georgia/Florida of 2007.
NASA Astrophysics Data System (ADS)
Williams, B. P.; Kjellstrand, B.; Jones, G.; Reimuller, J. D.; Fritts, D. C.; Miller, A.; Geach, C.; Limon, M.; Hanany, S.; Kaifler, B.; Wang, L.; Taylor, M. J.
2017-12-01
PMC-Turbo is a NASA long-duration, high-altitude balloon mission that will deploy 7 high-resolution cameras to image polar mesospheric clouds (PMC) and measure gravity wave breakdown and turbulence. The mission has been enhanced by the addition of the DLR Balloon Lidar Experiment (BOLIDE) and an OH imager from Utah State University. This instrument suite will provide high horizontal and vertical resolution of the wave-modified PMC structure along a several thousand kilometer flight track. We have requested a flight from Kiruna, Sweden to Canada in June 2017 or McMurdo Base, Antarctica in Dec 2017. Three of the PMC camera systems were deployed on an aircraft and two tomographic ground sites for the High Level campaign in Canada in June/July 2017. On several nights the cameras observed PMC's with strong gravity wave breaking signatures. One PMC camera will piggyback on the Super Tiger mission scheduled to be launched in Dec 2017 from McMurdo, so we will obtain PMC images and wave/turbulence data from both the northern and southern hemispheres.
NASA Astrophysics Data System (ADS)
Salach, A.; Markiewicza, J. S.; Zawieska, D.
2016-06-01
An orthoimage is one of the basic photogrammetric products used for architectural documentation of historical objects; recently, it has become a standard in such work. Considering the increasing popularity of photogrammetric techniques applied in the cultural heritage domain, this research examines the two most popular measuring technologies: terrestrial laser scanning, and automatic processing of digital photographs. The basic objective of the performed works presented in this paper was to optimize the quality of generated high-resolution orthoimages using integration of data acquired by a Z+F 5006 terrestrial laser scanner and a Canon EOS 5D Mark II digital camera. The subject was one of the walls of the "Blue Chamber" of the Museum of King Jan III's Palace at Wilanów (Warsaw, Poland). The high-resolution images resulting from integration of the point clouds acquired by the different methods were analysed in detail with respect to geometric and radiometric correctness.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Larson, Vincent
2016-11-25
The Multiscale Modeling Framework (MMF) embeds a cloud-resolving model in each grid column of a General Circulation Model (GCM). A MMF model does not need to use a deep convective parameterization, and thereby dispenses with the uncertainties in such parameterizations. However, MMF models grossly under-resolve shallow boundary-layer clouds, and hence those clouds may still benefit from parameterization. In this grant, we successfully created a climate model that embeds a cloud parameterization (“CLUBB”) within a MMF model. This involved interfacing CLUBB’s clouds with microphysics and reducing computational cost. We have evaluated the resulting simulated clouds and precipitation with satellite observations. Themore » chief benefit of the project is to provide a MMF model that has an improved representation of clouds and that provides improved simulations of precipitation.« less
Mechanisms and Model Diversity of Trade-Wind Shallow Cumulus Cloud Feedbacks: A Review
NASA Astrophysics Data System (ADS)
Vial, Jessica; Bony, Sandrine; Stevens, Bjorn; Vogel, Raphaela
Shallow cumulus clouds in the trade-wind regions are at the heart of the long standing uncertainty in climate sensitivity estimates. In current climate models, cloud feedbacks are strongly influenced by cloud-base cloud amount in the trades. Therefore, understanding the key factors controlling cloudiness near cloud-base in shallow convective regimes has emerged as an important topic of investigation. We review physical understanding of these key controlling factors and discuss the value of the different approaches that have been developed so far, based on global and high-resolution model experimentations and process-oriented analyses across a range of models and for observations. The trade-wind cloud feedbacks appear to depend on two important aspects: (1) how cloudiness near cloud-base is controlled by the local interplay between turbulent, convective and radiative processes; (2) how these processes interact with their surrounding environment and are influenced by mesoscale organization. Our synthesis of studies that have explored these aspects suggests that the large diversity of model responses is related to fundamental differences in how the processes controlling trade cumulus operate in models, notably, whether they are parameterized or resolved. In models with parameterized convection, cloudiness near cloud-base is very sensitive to the vigor of convective mixing in response to changes in environmental conditions. This is in contrast with results from high-resolution models, which suggest that cloudiness near cloud-base is nearly invariant with warming and independent of large-scale environmental changes. Uncertainties are difficult to narrow using current observations, as the trade cumulus variability and its relation to large-scale environmental factors strongly depend on the time and/or spatial scales at which the mechanisms are evaluated. New opportunities for testing physical understanding of the factors controlling shallow cumulus cloud responses using observations and highresolution modeling on large domains are discussed.
NASA Technical Reports Server (NTRS)
Minnis, Patrick; Young, David F.; Heck, Patrick W.; Liou, Kuo-Nan; Takano, Yoshihide
1992-01-01
The First ISCCP (International Satellite Cloud Climatology Project) Regional Experiment (FIRE) Phase II Intensive Field Observations (IFO) were taken over southeastern Kansas between November 13 and December 7,1991, to determine cirrus cloud properties. The observations include in situ microphysical data; surface, aircraft, and satellite remote sensing; and measurements of divergence over meso- and smaller-scale areas using wind profilers. Satellite remote sensing of cloud characteristics is an essential aspect for understanding and predicting the role of clouds in climate variations. The objectives of the satellite cloud analysis during FIRE are to validate cloud property retrievals, develop advanced methods for extracting cloud information from satellite-measured radiances, and provide multiscale cloud data for cloud process studies and for verification of cloud generation models. This paper presents the initial results of cloud property analyses during FIRE-II using Geostationary Operational Environmental Satellite (GOES) data and NOAA Advanced Very High Resolution Radiometer (AVHRR) radiances.
Detection of Multi-Layer and Vertically-Extended Clouds Using A-Train Sensors
NASA Technical Reports Server (NTRS)
Joiner, J.; Vasilkov, A. P.; Bhartia, P. K.; Wind, G.; Platnick, S.; Menzel, W. P.
2010-01-01
The detection of mUltiple cloud layers using satellite observations is important for retrieval algorithms as well as climate applications. In this paper, we describe a relatively simple algorithm to detect multiple cloud layers and distinguish them from vertically-extended clouds. The algorithm can be applied to coincident passive sensors that derive both cloud-top pressure from the thermal infrared observations and an estimate of solar photon pathlength from UV, visible, or near-IR measurements. Here, we use data from the A-train afternoon constellation of satellites: cloud-top pressure, cloud optical thickness, the multi-layer flag from the Aqua MODerate-resolution Imaging Spectroradiometer (MODIS) and the optical centroid cloud pressure from the Aura Ozone Monitoring Instrument (OMI). For the first time, we use data from the CloudSat radar to evaluate the results of a multi-layer cloud detection scheme. The cloud classification algorithms applied with different passive sensor configurations compare well with each other as well as with data from CloudSat. We compute monthly mean fractions of pixels containing multi-layer and vertically-extended clouds for January and July 2007 at the OMI spatial resolution (l2kmx24km at nadir) and at the 5kmx5km MODIS resolution used for infrared cloud retrievals. There are seasonal variations in the spatial distribution of the different cloud types. The fraction of cloudy pixels containing distinct multi-layer cloud is a strong function of the pixel size. Globally averaged, these fractions are approximately 20% and 10% for OMI and MODIS, respectively. These fractions may be significantly higher or lower depending upon location. There is a much smaller resolution dependence for fractions of pixels containing vertically-extended clouds (approx.20% for OMI and slightly less for MODIS globally), suggesting larger spatial scales for these clouds. We also find higher fractions of vertically-extended clouds over land as compared with ocean, particularly in the tropics and summer hemisphere.
Smoothing and gap-filling of high resolution multi-spectral time series: Example of Landsat data
NASA Astrophysics Data System (ADS)
Vuolo, Francesco; Ng, Wai-Tim; Atzberger, Clement
2017-05-01
This paper introduces a novel methodology for generating 15-day, smoothed and gap-filled time series of high spatial resolution data. The approach is based on templates from high quality observations to fill data gaps that are subsequently filtered. We tested our method for one large contiguous area (Bavaria, Germany) and for nine smaller test sites in different ecoregions of Europe using Landsat data. Overall, our results match the validation dataset to a high degree of accuracy with a mean absolute error (MAE) of 0.01 for visible bands, 0.03 for near-infrared and 0.02 for short-wave-infrared. Occasionally, the reconstructed time series are affected by artefacts due to undetected clouds. Less frequently, larger uncertainties occur as a result of extended periods of missing data. Reliable cloud masks are highly warranted for making full use of time series.
A new all-sky map of Galactic high-velocity clouds from the 21-cm HI4PI survey
NASA Astrophysics Data System (ADS)
Westmeier, Tobias
2018-02-01
High-velocity clouds (HVCs) are neutral or ionized gas clouds in the vicinity of the Milky Way that are characterized by high radial velocities inconsistent with participation in the regular rotation of the Galactic disc. Previous attempts to create a homogeneous all-sky H I map of HVCs have been hampered by a combination of poor angular resolution, limited surface brightness sensitivity and suboptimal sampling. Here, a new and improved H I map of Galactic HVCs based on the all-sky HI4PI survey is presented. The new map is fully sampled and provides significantly better angular resolution (16.2 versus 36 arcmin) and column density sensitivity (2.3 versus 3.7 × 1018 cm-2 at the native resolution) than the previously available LAB survey. The new HVC map resolves many of the major HVC complexes in the sky into an intricate network of narrow H I filaments and clumps that were not previously resolved by the LAB survey. The resulting sky coverage fraction of high-velocity H I emission above a column density level of 2 × 1018 cm-2 is approximately 15 per cent, which reduces to about 13 per cent when the Magellanic Clouds and other non-HVC emission are removed. The differential sky coverage fraction as a function of column density obeys a truncated power law with an exponent of -0.93 and a turnover point at about 5 × 1019 cm-2. H I column density and velocity maps of the HVC sky are made publicly available as FITS images for scientific use by the community.
NASA Astrophysics Data System (ADS)
Evrard, Rebecca L.; Ding, Yifeng
2018-01-01
Clouds play a large role in the Earth's global energy budget, but the impact of cirrus clouds is still widely questioned and researched. Cirrus clouds reside high in the atmosphere and due to cold temperatures are comprised of ice crystals. Gaining a better understanding of ice cloud optical properties and the distribution of cirrus clouds provides an explanation for the contribution of cirrus clouds to the global energy budget. Using radiative transfer models (RTMs), accurate simulations of cirrus clouds can enhance the understanding of the global energy budget as well as improve the use of global climate models. A newer, faster RTM such as the visible infrared imaging radiometer suite (VIIRS) fast radiative transfer model (VFRTM) is compared to a rigorous RTM such as the line-by-line radiative transfer model plus the discrete ordinates radiative transfer program. By comparing brightness temperature (BT) simulations from both models, the accuracy of the VFRTM can be obtained. This study shows root-mean-square error <0.2 K for BT difference using reanalysis data for atmospheric profiles and updated ice particle habit information from the moderate-resolution imaging spectroradiometer collection 6. At a higher resolution, the simulated results of the VFRTM are compared to the observations of VIIRS resulting in a <1.5 % error from the VFRTM for all cases. The VFRTM is validated and is an appropriate RTM to use for global cloud retrievals.
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 organized to collect distributed cloud data sets suitable for MODIS-CERES cloud radiation science and solar forecasting algorithm development. A low-cost and robust sensor design suitable for large scale fabrication and long term deployment has been developed during the project prototyping phase.
Instantaneous Coastline Extraction from LIDAR Point Cloud and High Resolution Remote Sensing Imagery
NASA Astrophysics Data System (ADS)
Li, Y.; Zhoing, L.; Lai, Z.; Gan, Z.
2018-04-01
A new method was proposed for instantaneous waterline extraction in this paper, which combines point cloud geometry features and image spectral characteristics of the coastal zone. The proposed method consists of follow steps: Mean Shift algorithm is used to segment the coastal zone of high resolution remote sensing images into small regions containing semantic information;Region features are extracted by integrating LiDAR data and the surface area of the image; initial waterlines are extracted by α-shape algorithm; a region growing algorithm with is taking into coastline refinement, with a growth rule integrating the intensity and topography of LiDAR data; moothing the coastline. Experiments are conducted to demonstrate the efficiency of the proposed method.
MISR CMVs and Multiangular Views of Tropical Cyclone Inner-Core Dynamics
NASA Technical Reports Server (NTRS)
Wu, Dong L.; Diner, David J.; Garay, Michael J; Jovanovic, Veljko M.; Lee, Jae N.; Moroney, Catherine M.; Mueller, Kevin J.; Nelson, David L.
2010-01-01
Multi-camera stereo imaging of cloud features from the MISR (Multiangle Imaging SpectroRadiometer) instrument on NASA's Terra satellite provides accurate and precise measurements of cloud top heights (CTH) and cloud motion vector (CMV) winds. MISR observes each cloudy scene from nine viewing angles (Nadir, +/-26(sup o), +/-46(sup o), +/-60(sup o), +/-70(sup o)) with approximatel 275-m pixel resolution. This paper provides an update on MISR CMV and CTH algorithm improvements, and explores a high-resolution retrieval of tangential winds inside the eyewall of tropical cyclones (TC). The MISR CMV and CTH retrievals from the updated algorithm are significantly improved in terms of spatial coverage and systematic errors. A new product, the 1.1-km cross-track wind, provides high accuracy and precision in measuring convective outflows. Preliminary results obtained from the 1.1-km tangential wind retrieval inside the TC eyewall show that the inner-core rotation is often faster near the eyewall, and this faster rotation appears to be related linearly to cyclone intensity.
Properties of the +70 kilometers per second cloud toward HD 203664
NASA Technical Reports Server (NTRS)
Sembach, Kenneth R.
1995-01-01
I present high-resolution International Ultraviolet Explorer (IUE) spectra of the ultraviolet absorption in an intermediate-velocity interstellar cloud (nu(sub LSR) approximately equal to +70 km/s) toward HD 203664. The combined, multiple IUE images result in spectra with S/N = 15-40 and resolutions of approximately 20-25 km/s. The intermediate-velocity cloud absorption is present in ultraviolet lines of C II, C II(sup *), C IV, N I, O I, Mg I, Mg II, Al II, Al III, Si II, Si III, Si IV, S II, Cr II, Mn II, Fe II, and Zn II. The relative abundances of low-ionization species suggest an electron density of 0.15-0.34/cu cm and a temperature of 5300-6100 K in the neutral and weakly ionized gas. Given the presence of high-ionization gas tracers such as Si IV and C IV, ionized portions of the cloud probably contribute to the relatively large values of n(sub e) derived from measurements of the lower ionization species. The high-ionization species in the cloud have an abundance ratio, N(C IV)/N(Si IV) approximately equal to 4.5, similar to that inferred for collisionally ionized cloud interfaces at temperatures near 10(exp 5) K along other sight lines. When referenced to sulfur, the abundances of most elements in the cloud are within a factor of 5 of their solar values, which suggests that the +70 km/s gas has a previous origin in the Galactic disk despite a recent determination by Little et al. that the cloud lies at a distance of 200-1500 pc below the Galactic plane. I have checked this result against a model of the ionization for the diffuse ionized gas layer of the Galaxy and find that this conclusion is essentially unchanged as long as the ionization parameter is low as implied by the abundances of adjoining ionization states of aluminum and silicon. The processes responsible for the production of highly ionized gas in the +70 km/s cloud appear to be able to account for the inferred dust grain destruction as well.
The Carbon Isotope Ratio in Local Molecular Clouds
NASA Astrophysics Data System (ADS)
Goto, Miwa; Usuda, Tomonori; Takato, Naruhisa; Masahiko, Hayashi; Sakamoto, Seiichi; Mitchell, George
We report the carbon isotope ratio in nearby molecular clouds LkHα 101, AFGL 490, and Mon R2 IRS 3. The vibrational transition bands of 12CO ν = 2 ← 0 and 13CO ν = 1 ← 0 were observed with high resolution near-infrared spectroscopy (R = 23,000) to measure the relative abundance of 13CO to 12CO. The isotopic ratios are 12CO/13CO = 1379 (LkHα 101), 8649 (AFGL 490), and 158 (Mon R2 IRS 3), which is twice higher than in the solar neighborhood. The molecular clouds are with high visible extinction (AV = 10 70 mag), well shielded from destructive FUV field. It is questionable that the selective photo-destruction of 13CO plays a major role in biasing isotope ratio. Uncertainty in the Doppler parameters of the unresolved absorption lines, and possible emission filling of fundamental transitions are suspected to account for the high 12CO/13CO ratio. Higher resolution spectroscopy (R ~ 100,000) is the key to go for the accurate measurement of isotope ratio.
Active Raman sounding of the earth's water vapor field.
Tratt, David M; Whiteman, David N; Demoz, Belay B; Farley, Robert W; Wessel, John E
2005-08-01
The typically weak cross-sections characteristic of Raman processes has historically limited their use in atmospheric remote sensing to nighttime application. However, with advances in instrumentation and techniques, it is now possible to apply Raman lidar to the monitoring of atmospheric water vapor, aerosols and clouds throughout the diurnal cycle. Upper tropospheric and lower stratospheric measurements of water vapor using Raman lidar are also possible but are limited to nighttime and require long integration times. However, boundary layer studies of water vapor variability can now be performed with high temporal and spatial resolution. This paper will review the current state-of-the-art of Raman lidar for high-resolution measurements of the atmospheric water vapor, aerosol and cloud fields. In particular, we describe the use of Raman lidar for mapping the vertical distribution and variability of atmospheric water vapor, aerosols and clouds throughout the evolution of dynamic meteorological events. The ability of Raman lidar to detect and characterize water in the region of the tropopause and the importance of high-altitude water vapor for climate-related studies and meteorological satellite performance are discussed.
Photogrammetric Analysis of Rotor Clouds Observed during T-REX
NASA Astrophysics Data System (ADS)
Romatschke, U.; Grubišić, V.
2017-12-01
Stereo photogrammetric analysis is a rarely utilized but highly valuable tool for studying smaller, highly ephemeral clouds. In this study, we make use of data that was collected during the Terrain-induced Rotor Experiment (T-REX), which took place in Owens Valley, eastern California, in the spring of 2006. The data set consists of matched digital stereo photographs obtained at high temporal (on the order of seconds) and spatial resolution (limited by the pixel size of the cameras). Using computer vision techniques we have been able to develop algorithms for camera calibration, automatic feature matching, and ultimately reconstruction of 3D cloud scenes. Applying these techniques to images from different T-REX IOPs we capture the motion of clouds in several distinct mountain wave scenarios ranging from short lived lee wave clouds on an otherwise clear sky day to rotor clouds formed in an extreme turbulence environment with strong winds and high cloud coverage. Tracking the clouds in 3D space and time allows us to quantify phenomena such as vertical and horizontal movement of clouds, turbulent motion at the upstream edge of rotor clouds, the structure of the lifting condensation level, extreme wind shear, and the life cycle of clouds in lee waves. When placed into context with the existing literature that originated from the T-REX field campaign, our results complement and expand our understanding of the complex dynamics observed in a variety of different lee wave settings.
NASA Astrophysics Data System (ADS)
Welch, R. M.; Sengupta, S. K.; Kuo, K. S.
1988-04-01
Statistical measures of the spatial distributions of gray levels (cloud reflectivities) are determined for LANDSAT Multispectral Scanner digital data. Textural properties for twelve stratocumulus cloud fields, seven cumulus fields, and two cirrus fields are examined using the Spatial Gray Level Co-Occurrence Matrix method. The co-occurrence statistics are computed for pixel separations ranging from 57 m to 29 km and at angles of 0°, 45°, 90° and 135°. Nine different textual measures are used to define the cloud field spatial relationships. However, the measures of contrast and correlation appear to be most useful in distinguishing cloud structure.Cloud field macrotexture describes general cloud field characteristics at distances greater than the size of typical cloud elements. It is determined from the spatial asymptotic values of the texture measures. The slope of the texture curves at small distances provides a measure of the microtexture of individual cloud cells. Cloud fields composed primarily of small cells have very steep slopes and reach their asymptotic values at short distances from the origin. As the cells composing the cloud field grow larger, the slope becomes more gradual and the asymptotic distance increases accordingly. Low asymptotic values of correlation show that stratocumulus cloud fields have no large scale organized structure.Besides the ability to distinguish cloud field structure, texture appears to be a potentially valuable tool in cloud classification. Stratocumulus clouds are characterized by low values of angular second moment and large values of entropy. Cirrus clouds appear to have extremely low values of contrast, low values of entropy, and very large values of correlation.Finally, we propose that sampled high spatial resolution satellite data be used in conjunction with coarser resolution operational satellite data to detect and identify cloud field structure and directionality and to locate regions of subresolution scale cloud contamination.
NASA Technical Reports Server (NTRS)
Hasler, A. F.
1981-01-01
Observations of cloud geometry using scan-synchronized stereo geostationary satellites having images with horizontal spatial resolution of approximately 0.5 km, and temporal resolution of up to 3 min are presented. The stereo does not require a cloud with known emissivity to be in equilibrium with an atmosphere with a known vertical temperature profile. It is shown that absolute accuracies of about 0.5 km are possible. Qualitative and quantitative representations of atmospheric dynamics were shown by remapping, display, and stereo image analysis on an interactive computer/imaging system. Applications of stereo observations include: (1) cloud top height contours of severe thunderstorms and hurricanes, (2) cloud top and base height estimates for cloud-wind height assignment, (3) cloud growth measurements for severe thunderstorm over-shooting towers, (4) atmospheric temperature from stereo heights and infrared cloud top temperatures, and (5) cloud emissivity estimation. Recommendations are given for future improvements in stereo observations, including a third GOES satellite, operational scan synchronization of all GOES satellites and better resolution sensors.
Lunar and Planetary Science XXXVI, Part 9
NASA Technical Reports Server (NTRS)
2005-01-01
The following topics were discussed: Monitoring floods with NASA's ST6 autonomous spacecraft experiment; Dynamical cloud models constrained by high resolution spectroscopy of zodiacal light; The oxygen isotopic composition of the sun and implications for oxygen processing in molecular clouds; A nochian/hisperian hiatus and erosive reactivation of martian valley networks; Hard x-ray spectro-microscopy techniques; Thermoluminescence studies of carbonaceous chondrites, etc.
Ozone Research with Advanced Cooperative Lidar Experiment (ORACLE) Implementation Study
NASA Technical Reports Server (NTRS)
Stadler, John H.; Browell, Edward V.; Ismail, Syed; Dudelzak, Alexander E.; Ball, Donald J.
1998-01-01
New technological advances have made possible new active remote sensing capabilities from space. Utilizing these technologies, the Ozone Research with Advanced Cooperative Lidar Experiment (ORACLE) will provide high spatial resolution measurements of ozone, clouds and aerosols in the stratosphere and lower troposphere. Simultaneous measurements of ozone, clouds and aerosols will assist in the understanding of global change, atmospheric chemistry and meteorology.
Distributed MRI reconstruction using Gadgetron-based cloud computing.
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.
An efficient framework for modeling clouds from Landsat8 images
NASA Astrophysics Data System (ADS)
Yuan, Chunqiang; Guo, Jing
2015-03-01
Cloud plays an important role in creating realistic outdoor scenes for video game and flight simulation applications. Classic methods have been proposed for cumulus cloud modeling. However, these methods are not flexible for modeling large cloud scenes with hundreds of clouds in that the user must repeatedly model each cloud and adjust its various properties. This paper presents a meteorologically based method to reconstruct cumulus clouds from high resolution Landsat8 satellite images. From these input satellite images, the clouds are first segmented from the background. Then, the cloud top surface is estimated from the temperature of the infrared image. After that, under a mild assumption of flat base for cumulus cloud, the base height of each cloud is computed by averaging the top height for pixels on the cloud edge. Then, the extinction is generated from the visible image. Finally, we enrich the initial shapes of clouds using a fractal method and represent the recovered clouds as a particle system. The experimental results demonstrate our method can yield realistic cloud scenes resembling those in the satellite images.
NASA Technical Reports Server (NTRS)
Hlavka, Dennis L.; Palm, S. P.; Welton, E. J.; Hart, W. D.; Spinhirne, J. D.; McGill, M.; Mahesh, A.; Starr, David OC. (Technical Monitor)
2001-01-01
The Geoscience Laser Altimeter System (GLAS) is scheduled for launch on the ICESat satellite as part of the NASA EOS mission in 2002. GLAS will be used to perform high resolution surface altimetry and will also provide a continuously operating atmospheric lidar to profile clouds, aerosols, and the planetary boundary layer with horizontal and vertical resolution of 175 and 76.8 m, respectively. GLAS is the first active satellite atmospheric profiler to provide global coverage. Data products include direct measurements of the heights of aerosol and cloud layers, and the optical depth of transmissive layers. In this poster we provide an overview of the GLAS atmospheric data products, present a simulated GLAS data set, and show results from the simulated data set using the GLAS data processing algorithm. Optical results from the ER-2 Cloud Physics Lidar (CPL), which uses many of the same processing algorithms as GLAS, show algorithm performance with real atmospheric conditions during the Southern African Regional Science Initiative (SAFARI 2000).
CERES Monthly Gridded Single Satellite Fluxes and Clouds (FSW) in HDF (CER_FSW_TRMM-PFM-VIRS_Beta1)
NASA Technical Reports Server (NTRS)
Wielicki, Bruce A. (Principal Investigator); Barkstrom, Bruce R. (Principal Investigator)
The Monthly Gridded Radiative Fluxes and Clouds (FSW) product contains a month of space and time averaged Clouds and the Earth's Radiant Energy System (CERES) data for a single scanner instrument. The FSW is also produced for combinations of scanner instruments. All instantaneous fluxes from the CERES CRS product for a month are sorted by 1-degree spatial regions and by the Universal Time (UT) hour of observation. The mean of the instantaneous fluxes for a given region-hour bin is determined and recorded on the FSW along with other flux statistics and scene information. The mean adjusted fluxes at the four atmospheric levels defined by CRS are also included for both clear-sky and total-sky scenes. In addition, four cloud height categories are defined by dividing the atmosphere into four intervals with boundaries at the surface, 700-, 500-, 300-hPa, and the Top-of-the-Atmosphere (TOA). The cloud layers from CRS are put into one of the cloud height categories and averaged over the region. The cloud properties are also column averaged and included on the FSW. [Location=GLOBAL] [Temporal_Coverage: Start_Date=1998-01-01; Stop_Date=2000-03-31] [Spatial_Coverage: Southernmost_Latitude=-90; Northernmost_Latitude=90; Westernmost_Longitude=-180; Easternmost_Longitude=180] [Data_Resolution: Latitude_Resolution=1 degree; Longitude_Resolution=1 degree; Horizontal_Resolution_Range=100 km - < 250 km or approximately 1 degree - < 2.5 degrees; Temporal_Resolution=1 month; Temporal_Resolution_Range=Monthly - < Annual].
NASA Technical Reports Server (NTRS)
Wielicki, Bruce A. (Principal Investigator); Barkstrom, Bruce R. (Principal Investigator)
The Monthly Gridded Radiative Fluxes and Clouds (FSW) product contains a month of space and time averaged Clouds and the Earth's Radiant Energy System (CERES) data for a single scanner instrument. The FSW is also produced for combinations of scanner instruments. All instantaneous fluxes from the CERES CRS product for a month are sorted by 1-degree spatial regions and by the Universal Time (UT) hour of observation. The mean of the instantaneous fluxes for a given region-hour bin is determined and recorded on the FSW along with other flux statistics and scene information. The mean adjusted fluxes at the four atmospheric levels defined by CRS are also included for both clear-sky and total-sky scenes. In addition, four cloud height categories are defined by dividing the atmosphere into four intervals with boundaries at the surface, 700-, 500-, 300-hPa, and the Top-of-the-Atmosphere (TOA). The cloud layers from CRS are put into one of the cloud height categories and averaged over the region. The cloud properties are also column averaged and included on the FSW. [Location=GLOBAL] [Temporal_Coverage: Start_Date=1998-01-01; Stop_Date=2005-12-31] [Spatial_Coverage: Southernmost_Latitude=-90; Northernmost_Latitude=90; Westernmost_Longitude=-180; Easternmost_Longitude=180] [Data_Resolution: Latitude_Resolution=1 degree; Longitude_Resolution=1 degree; Horizontal_Resolution_Range=100 km - < 250 km or approximately 1 degree - < 2.5 degrees; Temporal_Resolution=1 month; Temporal_Resolution_Range=Monthly - < Annual].
NASA Technical Reports Server (NTRS)
Wielicki, Bruce A. (Principal Investigator); Barkstrom, Bruce R. (Principal Investigator)
The Monthly Gridded Radiative Fluxes and Clouds (FSW) product contains a month of space and time averaged Clouds and the Earth's Radiant Energy System (CERES) data for a single scanner instrument. The FSW is also produced for combinations of scanner instruments. All instantaneous fluxes from the CERES CRS product for a month are sorted by 1-degree spatial regions and by the Universal Time (UT) hour of observation. The mean of the instantaneous fluxes for a given region-hour bin is determined and recorded on the FSW along with other flux statistics and scene information. The mean adjusted fluxes at the four atmospheric levels defined by CRS are also included for both clear-sky and total-sky scenes. In addition, four cloud height categories are defined by dividing the atmosphere into four intervals with boundaries at the surface, 700-, 500-, 300-hPa, and the Top-of-the-Atmosphere (TOA). The cloud layers from CRS are put into one of the cloud height categories and averaged over the region. The cloud properties are also column averaged and included on the FSW. [Location=GLOBAL] [Temporal_Coverage: Start_Date=1998-01-01; Stop_Date=2001-10-31] [Spatial_Coverage: Southernmost_Latitude=-90; Northernmost_Latitude=90; Westernmost_Longitude=-180; Easternmost_Longitude=180] [Data_Resolution: Latitude_Resolution=1 degree; Longitude_Resolution=1 degree; Horizontal_Resolution_Range=100 km - < 250 km or approximately 1 degree - < 2.5 degrees; Temporal_Resolution=1 month; Temporal_Resolution_Range=Monthly - < Annual].
The interpretation of remotely sensed cloud properties from a model paramterization perspective
NASA Technical Reports Server (NTRS)
HARSHVARDHAN; Wielicki, Bruce A.; Ginger, Kathryn M.
1994-01-01
A study has been made of the relationship between mean cloud radiative properties and cloud fraction in stratocumulus cloud systems. The analysis is of several Land Resources Satellite System (LANDSAT) images and three hourly International Satellite Cloud Climatology Project (ISCCP) C-1 data during daylight hours for two grid boxes covering an area typical of a general circulation model (GCM) grid increment. Cloud properties were inferred from the LANDSAT images using two thresholds and several pixel resolutions ranging from roughly 0.0625 km to 8 km. At the finest resolution, the analysis shows that mean cloud optical depth (or liquid water path) increases somewhat with increasing cloud fraction up to 20% cloud coverage. More striking, however, is the lack of correlation between the two quantities for cloud fractions between roughly 0.2 and 0.8. When the scene is essentially overcast, the mean cloud optical tends to be higher. Coarse resolution LANDSAT analysis and the ISCCP 8-km data show lack of correlation between mean cloud optical depth and cloud fraction for coverage less than about 90%. This study shows that there is perhaps a local mean liquid water path (LWP) associated with partly cloudy areas of stratocumulus clouds. A method has been suggested to use this property to construct the cloud fraction paramterization in a GCM when the model computes a grid-box-mean LWP.
A cloud-based multimodality case file for mobile devices.
Balkman, Jason D; Loehfelm, Thomas W
2014-01-01
Recent improvements in Web and mobile technology, along with the widespread use of handheld devices in radiology education, provide unique opportunities for creating scalable, universally accessible, portable image-rich radiology case files. A cloud database and a Web-based application for radiologic images were developed to create a mobile case file with reasonable usability, download performance, and image quality for teaching purposes. A total of 75 radiology cases related to breast, thoracic, gastrointestinal, musculoskeletal, and neuroimaging subspecialties were included in the database. Breast imaging cases are the focus of this article, as they best demonstrate handheld display capabilities across a wide variety of modalities. This case subset also illustrates methods for adapting radiologic content to cloud platforms and mobile devices. Readers will gain practical knowledge about storage and retrieval of cloud-based imaging data, an awareness of techniques used to adapt scrollable and high-resolution imaging content for the Web, and an appreciation for optimizing images for handheld devices. The evaluation of this software demonstrates the feasibility of adapting images from most imaging modalities to mobile devices, even in cases of full-field digital mammograms, where high resolution is required to represent subtle pathologic features. The cloud platform allows cases to be added and modified in real time by using only a standard Web browser with no application-specific software. Challenges remain in developing efficient ways to generate, modify, and upload radiologic and supplementary teaching content to this cloud-based platform. Online supplemental material is available for this article. ©RSNA, 2014.
Investigating the scale-adaptivity of a shallow cumulus parameterization scheme with LES
NASA Astrophysics Data System (ADS)
Brast, Maren; Schemann, Vera; Neggers, Roel
2017-04-01
In this study we investigate the scale-adaptivity of a new parameterization scheme for shallow cumulus clouds in the gray zone. The Eddy-Diffusivity Multiple Mass-Flux (or ED(MF)n ) scheme is a bin-macrophysics scheme, in which subgrid transport is formulated in terms of discretized size densities. While scale-adaptivity in the ED-component is achieved using a pragmatic blending approach, the MF-component is filtered such that only the transport by plumes smaller than the grid size is maintained. For testing, ED(MF)n is implemented in a large-eddy simulation (LES) model, replacing the original subgrid-scheme for turbulent transport. LES thus plays the role of a non-hydrostatic testing ground, which can be run at different resolutions to study the behavior of the parameterization scheme in the boundary-layer gray zone. In this range convective cumulus clouds are partially resolved. We find that at high resolutions the clouds and the turbulent transport are predominantly resolved by the LES, and the transport represented by ED(MF)n is small. This partitioning changes towards coarser resolutions, with the representation of shallow cumulus clouds becoming exclusively carried by the ED(MF)n. The way the partitioning changes with grid-spacing matches the results of previous LES studies, suggesting some scale-adaptivity is captured. Sensitivity studies show that a scale-inadaptive ED component stays too active at high resolutions, and that the results are fairly insensitive to the number of transporting updrafts in the ED(MF)n scheme. Other assumptions in the scheme, such as the distribution of updrafts across sizes and the value of the area fraction covered by updrafts, are found to affect the location of the gray zone.
Analysis of cloud top height and cloud coverage from satellites using the O2 A and B bands
NASA Technical Reports Server (NTRS)
Kuze, Akihiko; Chance, Kelly V.
1994-01-01
Cloud height and cloud coverage detection are important for total ozone retrieval using ultraviolet and visible scattered light. Use of the O2 A and B bands, around 761 and 687 nm, by a satellite-borne instrument of moderately high spectral resolution viewing in the nadir makes it possible to detect cloud top height and related parameters, including fractional coverage. The measured values of a satellite-borne spectrometer are convolutions of the instrument slit function and the atmospheric transmittance between cloud top and satellite. Studies here determine the optical depth between a satellite orbit and the Earth or cloud top height to high accuracy using FASCODE 3. Cloud top height and a cloud coverage parameter are determined by least squares fitting to calculated radiance ratios in the oxygen bands. A grid search method is used to search the parameter space of cloud top height and the coverage parameter to minimize an appropriate sum of squares of deviations. For this search, nonlinearity of the atmospheric transmittance (i.e., leverage based on varying amounts of saturation in the absorption spectrum) is important for distinguishing between cloud top height and fractional coverage. Using the above-mentioned method, an operational cloud detection algorithm which uses minimal computation time can be implemented.
NASA Technical Reports Server (NTRS)
Remer, Lorraine A.; Mattoo, Shana; Levy, Robert C.; Heidinger, Andrew; Pierce, R. Bradley; Chin, Mian
2011-01-01
The challenge of using satellite observations to retrieve aerosol properties in a cloudy environment is to prevent contamination of the aerosol signal from clouds, while maintaining sufficient aerosol product yield to satisfy specific applications. We investigate aerosol retrieval availability at different instrument pixel resolutions, using the standard MODIS aerosol cloud mask applied to MODIS data and a new GOES-R cloud mask applied to GOES data for a domain covering North America and surrounding oceans. Aerosol availability is not the same as the cloud free fraction and takes into account the technqiues used in the MODIS algorithm to avoid clouds, reduce noise and maintain sufficient numbers of aerosol retrievals. The inherent spatial resolution of each instrument, 0.5x0.5 km for MODIS and 1x1 km for GOES, is systematically degraded to 1x1 km, 2x2 km, 4x4 km and 8x8 km resolutions and then analyzed as to how that degradation would affect the availability of an aerosol retrieval, assuming an aerosol product resolution at 8x8 km. The results show that as pixel size increases, availability decreases until at 8x8 km 70% to 85% of the retrievals available at 0.5 km have been lost. The diurnal pattern of aerosol retrieval availability examined for one day in the summer suggests that coarse resolution sensors (i.e., 4x4 km or 8x8 km) may be able to retrieve aerosol early in the morning that would otherwise be missed at the time of current polar orbiting satellites, but not the diurnal aerosol properties due to cloud cover developed during the day. In contrast finer resolution sensors (i.e., 1x1 km or 2x2 km) have much better opportunity to retrieve aerosols in the partly cloudy scenes and better chance of returning the diurnal aerosol properties. Large differences in the results of the two cloud masks designed for MODIS aerosol and GOES cloud products strongly reinforce that cloud masks must be developed with specific purposes in mind and that a generic cloud mask applied to an independent aerosol retrieval will likely fail.
NASA Technical Reports Server (NTRS)
Menzel, W. Paul; Moeller, Christopher C.; Smith, William L.
1991-01-01
This program has applied Multispectral Atmospheric Mapping Sensor (MAMS) high resolution data to the problem of monitoring atmospheric quantities of moisture and radiative flux at small spatial scales. MAMS, with 100-m horizontal resolution in its four infrared channels, was developed to study small scale atmospheric moisture and surface thermal variability, especially as related to the development of clouds, precipitation, and severe storms. High-resolution Interferometer Sounder (HIS) data has been used to develop a high spectral resolution retrieval algorithm for producing vertical profiles of atmospheric temperature and moisture. The results of this program are summarized and a list of publications resulting from this contract is presented. Selected publications are attached as an appendix.
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.
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;
2015-01-01
Cloud properties play a critical role in climate change. Monitoring cloud properties over long time periods is needed to detect changes and to validate and constrain models. The Clouds and the Earth's Radiant Energy System (CERES) project has developed several cloud datasets from Aqua and Terra MODIS data to better interpret broadband radiation measurements and improve understanding of the role of clouds in the radiation budget. The algorithms applied to MODIS data have been adapted to utilize various combinations of channels on the Advanced Very High Resolution Radiometer (AVHRR) on the long-term time series of NOAA and MetOp satellites to provide a new cloud climate data record. These datasets can be useful for a variety of studies. This paper presents results of the MODIS and AVHRR analyses covering the period from 1980-2014. Validation and comparisons with other datasets are also given.
CloudSat First Image of a Warm Front Storm Over the Norwegian Sea
NASA Technical Reports Server (NTRS)
2006-01-01
[figure removed for brevity, see original site] Figure 1 CloudSat's first image, of a warm front storm over the Norwegian Sea, was obtained on May 20, 2006. In this horizontal cross-section of clouds, warm air is seen rising over colder air as the satellite travels from right to left. The red colors are indicative of highly reflective particles such as water droplets (or rain) or larger ice crystals (or snow), while the blue indicates thinner clouds (such as cirrus). The flat green/blue lines across the bottom represent the ground signal. The vertical scale on the CloudSat Cloud Profiling Radar image is approximately 30 kilometers (19 miles). The blue line below the Cloud Profiling Radar image indicates that the data were taken over water. The inset image shows the CloudSat track relative to a Moderate Resolution Imaging Spectroradiometer (MODIS) infrared image taken at nearly the same time.CloudSat Image of a Polar Night Storm Near Antarctica
NASA Technical Reports Server (NTRS)
2006-01-01
[figure removed for brevity, see original site] Figure 1 CloudSat image of a horizontal cross-section of a polar night storm near Antarctica. Until now, clouds have been hard to observe in polar regions using remote sensing, particularly during the polar winter or night season. The red colors are indicative of highly reflective particles such as water (rain) or ice crystals, while the blue indicates thinner clouds (such as cirrus). The flat green/blue lines across the bottom represent the ground signal. The vertical scale on the CloudSat Cloud Profiling Radar image is approximately 30 kilometers (19 miles). The blue line below the Cloud Profiling Radar image indicates that the data were taken over water; the brown line below the image indicates the relative elevation of the land surface. The inset image shows the CloudSat track relative to a Moderate Resolution Imaging Spectroradiometer (MODIS) infrared image taken at nearly the same time.Diurnal, Seasonal, and Interannual Variations of Cloud Properties Derived for CERES From Imager Data
NASA Technical Reports Server (NTRS)
Minnis, Patrick; Young, David F.; Sun-Mack, Sunny; Trepte, Qing Z.; Chen, Yan; Brown, Richard R.; Gibson, Sharon; Heck, Patrick W.
2004-01-01
Simultaneous measurement of the radiation and cloud fields on a global basis is a key component in the effort to understand and model the interaction between clouds and radiation at the top of the atmosphere, at the surface, and within the atmosphere. The NASA Clouds and Earth s Radiant Energy System (CERES) Project, begun in 1998, is meeting this need. Broadband shortwave (SW) and longwave radiance measurements taken by the CERES scanners at resolutions between 10 and 20 km on the Tropical Rainfall Measuring Mission (TRMM), Terra, and Aqua satellites are matched to simultaneous retrievals of cloud height, phase, particle size, water path, and optical depth OD from the TRMM Visible Infrared Scanner (VIRS) and the Moderate Resolution Imaging Spectroradiometer (MODIS) on Terra and Aqua. Besides aiding the interpretation of the broadband radiances, the CERES cloud properties are valuable for understanding cloud variations at a variety of scales. In this paper, the resulting CERES cloud data taken to date are averaged at several temporal scales to examine the temporal and spatial variability of the cloud properties on a global scale at a 1 resolution.
Inference of Ice Cloud Properties from High-spectral Resolution Infrared Observations. Appendix 4
NASA Technical Reports Server (NTRS)
Huang, Hung-Lung; Yang, Ping; Wei, Heli; Baum, Bryan A.; Hu, Yongxiang; Antonelli, Paolo; Ackerman, Steven A.
2005-01-01
The theoretical basis is explored for inferring the microphysical properties of ice crystal from high-spectral resolution infrared observations. A radiative transfer model is employed to simulate spectral radiances to address relevant issues. The extinction and absorption efficiencies of individual ice crystals, assumed as hexagonal columns for large particles and droxtals for small particles, are computed from a combination of the finite- difference time-domain (FDTD) technique and a composite method. The corresponding phase functions are computed from a combination of FDTD and an improved geometric optics method (IGOM). Bulk scattering properties are derived by averaging the single- scattering properties of individual particles for 30 particle size distributions developed from in situ measurements and for additional four analytical Gamma size distributions for small particles. The non-sphericity of ice crystals is shown to have a significant impact on the radiative signatures in the infrared (IR) spectrum; the spherical particle approximation for inferring ice cloud properties may result in an overest&ation of the optical thickness and an inaccurate retrieval of effective particle size. Furthermore, we show that the error associated with the use of the Henyey-Greenstein phase function can be as larger as 1 K in terms of brightness temperature for larger particle effective size at some strong scattering wavenumbers. For small particles, the difference between the two phase functions is much less, with brightness temperatures generally differing by less than 0.4 K. The simulations undertaken in this study show that the slope of the IR brightness temperature spectrum between 790-960/cm is sensitive to the effective particle size. Furthermore, a strong sensitivity of IR brightness temperature to cloud optical thickness is noted within the l050-1250/cm region. Based on this spectral feature, a technique is presented for the simultaneous retrieval of the visible optical thickness and effective particle size from high spectral resolution infrared data under ice cloudy con&tion. The error analysis shows that the uncertainty of the retrieved optical thickness and effective particle size has a small range of variation. The error for retrieving particle size in conjunction with an uncertainty of 5 K in cloud'temperature, or a surface temperature uncertainty of 2.5 K, is less than 15%. The corresponding e m r in the uncertainty of optical thickness is within 5-2096, depending on the value of cloud optical thickness. The applicability of the technique is demonstrated using the aircraft-based High- resolution Interferometer Sounder (HIS) data from the Subsonic Aircraft: Contrail and Cloud Effects Special Study (SUCCESS) in 1996 and the First ISCCP Regional Experiment - Arctic Clouds Experiment (FIRE-ACE) in 1998.
Assessment of simulation of radiation in NCEP Climate Forecasting System (CFS V2)
NASA Astrophysics Data System (ADS)
Goswami, Tanmoy; Rao, Suryachandra A.; Hazra, Anupam; Chaudhari, Hemantkumar S.; Dhakate, Ashish; Salunke, Kiran; Mahapatra, Somnath
2017-09-01
The objective of this study is to identify and document the radiation biases in the latest National Centers for Environment Prediction (NCEP), Climate Forecasting System (CFSv2) and to investigate the probable reasons for these biases. This analysis is made over global and Indian domain under all-sky and clear-sky conditions. The impact of increasing the horizontal resolution of the atmospheric model on these biases is also investigated by comparing results of two different horizontal resolution versions of CFSv2 namely T126 and T382. The difference between the top of the atmosphere and surface energy imbalance in T126 (T382) is 3.49 (2.78) W/m2. This reduction of bias in the high resolution model is achieved due to lesser low cloud cover, resulting more surface insolation, and due to more latent heat fluxes at the surface. Compared to clear sky simulations, all sky simulations exhibit larger biases suggesting that the cloud covers are not simulated well in the model. The annual mean high level cloud cover is over estimated over the global as well as the Indian domain. This overestimation over the Indian domain is also present during JJAS. There is also evidence that both of the models have insufficient water vapour in their atmosphere. This study suggests that in order to improve the model's mean radiation climatology, simulation of clouds in the model also needs to be improved, and future model development activities should focus on this aspect.
NASA Astrophysics Data System (ADS)
Sturdivant, E. J.; Lentz, E. E.; Thieler, E. R.; Remsen, D.; Miner, S.
2016-12-01
Characterizing the vulnerability of coastal systems to storm events, chronic change and sea-level rise can be improved with high-resolution data that capture timely snapshots of biogeomorphology. Imagery acquired with unmanned aerial systems (UAS) coupled with structure from motion (SfM) photogrammetry can produce high-resolution topographic and visual reflectance datasets that rival or exceed lidar and orthoimagery. Here we compare SfM-derived data to lidar and visual imagery for their utility in a) geomorphic feature extraction and b) land cover classification for coastal habitat assessment. At a beach and wetland site on Cape Cod, Massachusetts, we used UAS to capture photographs over a 15-hectare coastal area with a resulting pixel resolution of 2.5 cm. We used standard SfM processing in Agisoft PhotoScan to produce an elevation point cloud, an orthomosaic, and a digital elevation model (DEM). The SfM-derived products have a horizontal uncertainty of +/- 2.8 cm. Using the point cloud in an extraction routine developed for lidar data, we determined the position of shorelines, dune crests, and dune toes. We used the output imagery and DEM to map land cover with a pixel-based supervised classification. The dense and highly precise SfM point cloud enabled extraction of geomorphic features with greater detail than with lidar. The feature positions are reported with near-continuous coverage and sub-meter accuracy. The orthomosaic image produced with SfM provides visual reflectance with higher resolution than those available from aerial flight surveys, which enables visual identification of small features and thus aids the training and validation of the automated classification. We find that the high-resolution and correspondingly high density of UAS data requires some simple modifications to existing measurement techniques and processing workflows, and that the types of data and the quality provided is equivalent to, and in some cases surpasses, that of data collected using other methods.
Measurement needs guided by synthetic radar scans in high-resolution model output
NASA Astrophysics Data System (ADS)
Varble, A.; Nesbitt, S. W.; Borque, P.
2017-12-01
Microphysical and dynamical process interactions within deep convective clouds are not well understood, partly because measurement strategies often focus on statistics of cloud state rather than cloud processes. While processes cannot be directly measured, they can be inferred with sufficiently frequent and detailed scanning radar measurements focused on the life cycleof individual cloud regions. This is a primary goal of the 2018-19 DOE ARM Cloud, Aerosol, and Complex Terrain Interactions (CACTI) and NSF Remote sensing of Electrification, Lightning, And Mesoscale/microscale Processes with Adaptive Ground Observations (RELAMPAGO) field campaigns in central Argentina, where orographic deep convective initiation is frequent with some high-impact systems growing into the tallest and largest in the world. An array of fixed and mobile scanning multi-wavelength dual-polarization radars will be coupled with surface observations, sounding systems, multi-wavelength vertical profilers, and aircraft in situ measurements to characterize convective cloud life cycles and their relationship with environmental conditions. While detailed cloud processes are an observational target, the radar scan patterns that are most ideal for observing them are unclear. They depend on the locations and scales of key microphysical and dynamical processes operating within the cloud. High-resolution simulations of clouds, while imperfect, can provide information on these locations and scales that guide radar measurement needs. Radar locations are set in the model domain based on planned experiment locations, and simulatedorographic deep convective initiation and upscale growth are sampled using a number of different scans involving RHIs or PPIs with predefined elevation and azimuthal angles that approximately conform with radar range and beam width specifications. Each full scan pattern is applied to output atsingle model time steps with time step intervals that depend on the length of time required to complete each scan in the real world. The ability of different scans to detect key processes within the convective cloud life cycle are examined in connection with previous and subsequent dynamical and microphysical transitions. This work will guide strategic scan patterns that will be used during CACTI and RELAMPAGO.
The EOS CERES Global Cloud Mask
NASA Technical Reports Server (NTRS)
Berendes, T. A.; Welch, R. M.; Trepte, Q.; Schaaf, C.; Baum, B. A.
1996-01-01
To detect long-term climate trends, it is essential to produce long-term and consistent data sets from a variety of different satellite platforms. With current global cloud climatology data sets, such as the International Satellite Cloud Climatology Experiment (ISCCP) or CLAVR (Clouds from Advanced Very High Resolution Radiometer), one of the first processing steps is to determine whether an imager pixel is obstructed between the satellite and the surface, i.e., determine a cloud 'mask.' A cloud mask is essential to studies monitoring changes over ocean, land, or snow-covered surfaces. As part of the Earth Observing System (EOS) program, a series of platforms will be flown beginning in 1997 with the Tropical Rainfall Measurement Mission (TRMM) and subsequently the EOS-AM and EOS-PM platforms in following years. The cloud imager on TRMM is the Visible/Infrared Sensor (VIRS), while the Moderate Resolution Imaging Spectroradiometer (MODIS) is the imager on the EOS platforms. To be useful for long term studies, a cloud masking algorithm should produce consistent results between existing (AVHRR) data, and future VIRS and MODIS data. The present work outlines both existing and proposed approaches to detecting cloud using multispectral narrowband radiance data. Clouds generally are characterized by higher albedos and lower temperatures than the underlying surface. However, there are numerous conditions when this characterization is inappropriate, most notably over snow and ice of the cloud types, cirrus, stratocumulus and cumulus are the most difficult to detect. Other problems arise when analyzing data from sun-glint areas over oceans or lakes over deserts or over regions containing numerous fires and smoke. The cloud mask effort builds upon operational experience of several groups that will now be discussed.
NASA Technical Reports Server (NTRS)
Khaiyer, M. M.; Rapp, A. D.; Doelling, D. R.; Nordeen, M. L.; Minnis, P.; Smith, W. L., Jr.; Nguyen, L.
2001-01-01
While the various instruments maintained at the Atmospheric Radiation Measurement (ARM) Program Southern Great Plains (SGP) Central Facility (CF) provide detailed cloud and radiation measurements for a small area, satellite cloud property retrievals provide a means of examining the large-scale properties of the surrounding region over an extended period of time. Seasonal and inter-annual climatological trends can be analyzed with such a dataset. For this purpose, monthly datasets of cloud and radiative properties from December 1996 through November 1999 over the SGP region have been derived using the layered bispectral threshold method (LBTM). The properties derived include cloud optical depths (ODs), temperatures and albedos, and are produced on two grids of lower (0.5 deg) and higher resolution (0.3 deg) centered on the ARM SGP CF. The extensive time period and high-resolution of the inner grid of this dataset allows for comparison with the suite of instruments located at the ARM CF. In particular, Whole-Sky Imager (WSI) and the Active Remote Sensing of Clouds (ARSCL) cloud products can be compared to the cloud amounts and heights of the LBTM 0.3 deg grid box encompassing the CF site. The WSI provides cloud fraction and the ARSCL computes cloud fraction, base, and top heights using the algorithms by Clothiaux et al. (2001) with a combination of Belfort Laser Ceilometer (BLC), Millimeter Wave Cloud Radar (MMCR), and Micropulse Lidar (MPL) data. This paper summarizes the results of the LBTM analysis for 3 years of GOES-8 data over the SGP and examines the differences between surface and satellite-based estimates of cloud fraction.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Giangrande, Scott E.; Feng, Zhe; Jensen, Michael P.
Routine cloud, precipitation and thermodynamic observations collected by the Atmospheric Radiation Measurement (ARM) Mobile Facility (AMF) and Aerial Facility (AAF) during the 2-year US Department of Energy (DOE) ARM Observations and Modeling of the Green Ocean Amazon (GoAmazon2014/5) campaign are summarized. These observations quantify the diurnal to large-scale thermodynamic regime controls on the clouds and precipitation over the undersampled, climatically important Amazon basin region. The extended ground deployment of cloud-profiling instrumentation enabled a unique look at multiple cloud regimes at high temporal and vertical resolution. This longer-term ground deployment, coupled with two short-term aircraft intensive observing periods, allowed new opportunitiesmore » to better characterize cloud and thermodynamic observational constraints as well as cloud radiative impacts for modeling efforts within typical Amazon wet and dry seasons.« less
A Survey of Near-infrared Diffuse Interstellar Bands
NASA Astrophysics Data System (ADS)
Hamano, Satochi; Kobayashi, Naoto; Kawakita, Hideyo; Ikeda, Yuji; Kondo, Sohei; Sameshima, Hiroaki; Arai, Akira; Matsunaga, Noriyuki; Yasui, Chikako; Mizumoto, Misaki; Fukue, Kei; Izumi, Natsuko; Otsubo, Shogo; Takenada, Keiichi
2018-04-01
We propose a study of interstellar molecules with near-infrared (NIR) high-resolution spectroscopy as a science case for the 3.6-m Devasthal Optical Telescope (DOT). In particular, we present the results obtained on-going survey of diffuse interstellar bands (DIBs) in NIR with the newly developed NIR high-resolution spectrograph WINERED, which offers a high sensitivity in the wavelength range of 0.91-1.36 µm. Using the WINERED spectrograph attached to the 1.3-m Araki telescope in Japan, we obtained high-quality spectra of a number of early-type stars in various environments, such as diffuse interstellar clouds, dark clouds and star-forming regions, to investigate the properties of NIR DIBs and constrain their carriers. As a result, we successfully identified about 50 new NIR DIBs, where only five fairly strong DIBs had been identified previously. Also, some properties of DIBs in the NIR are discussed to constrain the carriers of DIBs.
Hämmerle, Martin; Höfle, Bernhard
2014-01-01
3D geodata play an increasingly important role in precision agriculture, e.g., for modeling in-field variations of grain crop features such as height or biomass. A common data capturing method is LiDAR, which often requires expensive equipment and produces large datasets. This study contributes to the improvement of 3D geodata capturing efficiency by assessing the effect of reduced scanning resolution on crop surface models (CSMs). The analysis is based on high-end LiDAR point clouds of grain crop fields of different varieties (rye and wheat) and nitrogen fertilization stages (100%, 50%, 10%). Lower scanning resolutions are simulated by keeping every n-th laser beam with increasing step widths n. For each iteration step, high-resolution CSMs (0.01 m2 cells) are derived and assessed regarding their coverage relative to a seamless CSM derived from the original point cloud, standard deviation of elevation and mean elevation. Reducing the resolution to, e.g., 25% still leads to a coverage of >90% and a mean CSM elevation of >96% of measured crop height. CSM types (maximum elevation or 90th-percentile elevation) react differently to reduced scanning resolutions in different crops (variety, density). The results can help to assess the trade-off between CSM quality and minimum requirements regarding equipment and capturing set-up. PMID:25521383
Modelled and measured effects of clouds on UV Aerosol Indices on a local, regional, and global scale
NASA Astrophysics Data System (ADS)
Penning de Vries, M.; Wagner, T.
2010-10-01
The UV Aerosol Indices (UVAI) form one of very few available tools in satellite remote sensing that provide information on aerosol absorption. The UVAI are also quite insensitive to surface type and are determined in the presence of clouds - situations where most aerosol retrieval algorithms do not work. The UVAI are most sensitive to elevated layers of absorbing aerosols, such as mineral dust and smoke from biomass burning, but they can also be used to study non-absorbing aerosols, such as sulphate and secondary organic aerosols. Although UVAI are determined for cloud-contaminated pixels, clouds do affect the value of UVAI in several ways. One way to correct for these effects is to remove clouded pixels using a cloud filter. However, this causes a large loss of data, biases the results towards clear skies, and removes all potentially very interesting pixels where aerosols and clouds co-exist. We here propose to correct the effects of clouds on UVAI in a more sophisticated way, namely by simulating the contribution of clouds to UVAI, and then subtracting it from the measured data. To this aim, we modelled UVAI from clouds by using measured cloud optical parameters - either with low spatial resolution from SCIAMACHY, or high resolution from MERIS - as input. The modelled UVAI were compared with UVAI measured by SCIAMACHY on different spatial (local, regional and global) and temporal scales (single measurement, daily means and seasonal means). The general dependencies of UVAI on cloud parameters were quite well reproduced, but several issues remain unclear: compared to the modelled UVAI, measured UVAI show a bias, in particular for large cloud fractions, and much larger scatter. Also, the viewing angle dependence differs for measured and modelled UVAI. The modelled UVAI from clouds will be used to correct measured UVAI for the effect of clouds, thus allowing a more quantitative analysis of UVAI and enabling investigations of aerosol-cloud interactions.
NASA Astrophysics Data System (ADS)
Beyer, Hans Georg
2016-04-01
With the increasing availability of satellite derived irradiance information, this type of data set is more and more in use for the design and operation of solar energy systems, most notably PV- and CSP-systems. By this, the need for data measured on-site is reduced. However, due to basic limitations of the satellite-derived data, several requirements put by the intended application cannot be coped with this data type directly. Traw satellite information has to be enhanced in both space and time resolution by additional information to be fully applicable for all aspects of the modelling od solar energy systems. To cope with this problem, several individual and collaborative projects had been performed in the recent years or are ongoing. Approaches are on one hand based on pasting synthesized high-resolution data into the low-resolution original sets. Pre-requite is an appropriate model, validated against real world data. For the case of irradiance data, these models can be extracted either directly from ground measured data sets or from data referring to the cloud situation as gained from the images of sky cameras or from monte -carlo initialized physical models. The current models refer to the spatial structure of the cloud fields. Dynamics are imposed by moving the cloud structures according to a large scale cloud motion vector, either extracted from the dynamics interfered from consecutive satellite images or taken from a meso-scale meteorological model. Dynamic irradiance information is then derived from the cloud field structure and the cloud motion vector. This contribution, which is linked to subtask A - Solar Resource Applications for High Penetration of Solar Technologies - of IEA SHC task 46, will present the different approaches and discuss examples in view of validation, need for auxiliary information and respective general applicability.
NASA Technical Reports Server (NTRS)
TenHoeve, J. E.; Remer, L. A.; Jacobson, M. Z.
2010-01-01
High resolution aerosol, cloud, water vapor, and atmospheric profile data from the Moderate Resolution Imaging Spectroradiometer (MODIS) are utilized to examine the impact of aerosols on clouds during the Amazonian biomass burning season in Rondnia, Brazil. It is found that increasing background column water vapor (CWV) throughout this transition season between the Amazon dry and wet seasons exerts a strong effect on cloud properties. As a result, aerosol-cloud correlations should be stratified by column water vapor to achieve a more accurate assessment of the effect of aerosols on clouds. Previous studies ignored the systematic changes to meteorological factors during the transition season, leading to possible misinterpretation of their results. Cloud fraction is shown generally to increase with aerosol optical depth (AOD) for both low and high values of column water vapor, whereas the relationship between cloud optical depth (COD) and AOD exhibits a different relationship. COD increases with AOD until AOD approx. 0.25 due to the first indirect (microphysical) effect. At higher values of AOD, COD is found to decrease with increasing AOD, which may be due to: (1) the inhibition of cloud development by absorbing aerosols (radiative effect) and/or (2) a retrieval artifact in which the measured reflectance in the visible is less than expected from a cloud top either from the darkening of clouds through the addition of carbonaceous biomass burning aerosols or subpixel dark surface contamination in the measured cloud reflectance. If (1) is a contributing mechanism, as we suspect, then a linear relationship between the indirect effect and increasing AOD, assumed in a majority of GCMs, is inaccurate since these models do not include treatment of aerosol absorption in and around clouds. The effect of aerosols on both column water vapor and clouds over varying land surface types is also analyzed. The study finds that the difference in column water vapor between forest and pasture is not correlated with aerosol loading, supporting the assumption that temporal variation of column water vapor is primarily a function of the larger-scale meteorology. However, a difference in the response of cloud fraction to increasing AOD is observed between forest and pasture. This suggests that dissimilarities between other meteorological factors, such as atmospheric stability, are likely to have an impact on aerosol-cloud correlations between different land-cover types.
Refinements to HIRS CO2 Slicing Algorithm with Results Compared to CALIOP and MODIS
NASA Astrophysics Data System (ADS)
Frey, R.; Menzel, P.
2012-12-01
This poster reports on the refinement of a cloud top property algorithm using High-resolution Infrared Radiation Sounder (HIRS) measurements. The HIRS sensor has been flown on fifteen satellites from TIROS-N through NOAA-19 and MetOp-A forming a continuous 30 year cloud data record. Cloud Top Pressure and effective emissivity (cloud fraction multiplied by cloud emissivity) are derived using the 15 μm spectral bands in the CO2 absorption band, implementing the CO2 slicing technique which is strong for high semi-transparent clouds but weak for low clouds with little thermal contrast from clear skies. We report on algorithm adjustments suggested from MODIS cloud record validations and the inclusion of collocated AVHRR cloud fraction data from the PATMOS-x algorithm. Reprocessing results for 2008 are shown using NOAA-18 HIRS and collocated CALIOP data for validation, as well as comparisons to MODIS monthly mean values. Adjustments to the cloud algorithm include (a) using CO2 slicing for all ice and mixed phase clouds and infrared window determinations for all water clouds, (b) determining the cloud top pressure from the most opaque CO2 spectral band pair seeing the cloud, (c) reducing the cloud detection threshold for the CO2 slicing algorithm to include conditions of smaller radiance differences that are often due to thin ice clouds, and (d) identifying stratospheric clouds when an opaque band is warmer than a less opaque band.
Characteristics of tropical cyclones and overshooting from GPS radio occultation data
NASA Astrophysics Data System (ADS)
Biondi, Riccardo; Rieckh, Therese; Steiner, Andrea; Kirchengast, Gottfried
2014-05-01
Tropical cyclones (TCs) are extreme weather events causing every year huge damages and several deaths. In some countries they are the natural catastrophes accounting for the major economic damages. The thermal structure of TCs gives important information on the cloud top height allowing for a better understanding of the troposphere-stratosphere transport, which is still poorly understood. The measurement of atmospheric parameters (such as temperature, pressure and humidity) with high vertical resolution and accuracy in the upper troposphere and lower stratosphere (UTLS) is difficult especially during severe weather events (e.g TCs). Satellite remote sensing has improved the TC forecast and monitoring accuracy. In the last decade the Global Positioning Systems (GPS) Radio Occultation (RO) technique contributed to improve our knowledge especially at high troposphere altitudes and in remote regions of the globe thanks to the high vertical resolution, avoiding temperature smoothing issues (given by microwave and infrared instruments) in the UTLS and improving the poor temporal resolution and global coverage given by lidars and radars. We selected more than twenty-thousand GPS RO profiles co-located with TC best tracks for the period 2001 to 2012 and computed temperature anomaly profiles relative to a RO background climatology in order to detect TC cloud tops. We characterized the thermal structure for different ocean basins and for different TC intensities, distinguishing between tropical and extra-tropical cases. The analysis shows that all investigated storms have a common feature: they warm the troposphere and cool the UTLS near the cloud top. This behavior is amplified in the extra-tropical areas. Results reveal that the storms' cloud tops in the southern hemisphere basins reach higher altitudes and lower temperatures than in the northern hemisphere basins. We furthermore compared the cloud top height of each profile with the mean tropopause altitude (from the RO archive) in order to detect overshooting. We present a map of TC overshooting events indicating tropical areas which contribute most to UTLS transport and the large-scale atmospheric circulation.
Cloud-Free Satellite Image Mosaics with Regression Trees and Histogram Matching.
E.H. Helmer; B. Ruefenacht
2005-01-01
Cloud-free optical satellite imagery simplifies remote sensing, but land-cover phenology limits existing solutions to persistent cloudiness to compositing temporally resolute, spatially coarser imagery. Here, a new strategy for developing cloud-free imagery at finer resolution permits simple automatic change detection. The strategy uses regression trees to predict...
NASA Technical Reports Server (NTRS)
Matsui, Toshihisa; Masunaga, Hirohiko; Kreidenweis, Sonia M.; Pielke, Roger A., Sr.; Tao, Wei-Kuo; Chin, Mian; Kaufman, Yoram J.
2006-01-01
This study examines variability in marine low cloud properties derived from semi-global observations by the Tropical Rainfall Measuring Mission (TRMM) satellite, as linked to the aerosol index (AI) and lower-tropospheric stability (LTS). AI is derived from the Moderate Resolution Imaging Spectroradiometer (Terra MODIS) sensor and the Goddard Chemistry Aerosol Radiation and Transportation (GOCART) model, and is used to represent column-integrated aerosol concentrations. LTS is derived from the NCEP/NCAR reanalysis, and represents the background thermodynamic environment in which the clouds form. Global statistics reveal that cloud droplet size tends to be smallest in polluted (high-AI) and strong inversion (high-LTS) environments. Statistical quantification shows that cloud droplet size is better correlated with AI than it is with LTS. Simultaneously, the cloud liquid water path (CLWP) tends to decrease as AI increases. This correlation does not support the hypothesis or assumption that constant or increased CLWP is associated with high aerosol concentrations. Global variability in corrected cloud albedo (CCA), the product of cloud optical depth and cloud fraction, is very well explained by LTS, while both AI and LTS are needed to explain local variability in CCA. Most of the local correlations between AI and cloud properties are similar to the results from the global statistics, while weak anomalous aerosol-cloud correlations appear locally in the regions where simultaneous high (low) AI and low (high) LTS compensate each other. Daytime diurnal cycles explain additional variability in cloud properties. CCA has the largest diurnal cycle in high-LTS regions. Cloud droplet size and CLWP have weak diurnal cycles that differ between clean and polluted environments. The combined results suggest that investigations of marine low cloud radiative forcing and its relationship to hypothesized aerosol indirect effects must consider the combined effects of aerosols, thermodynamics, and the diurnal cycle.
Galileo infrared imaging spectroscopy measurements at venus
Carlson, R.W.; Baines, K.H.; Encrenaz, Th.; Taylor, F.W.; Drossart, P.; Kamp, L.W.; Pollack, James B.; Lellouch, E.; Collard, A.D.; Calcutt, S.B.; Grinspoon, D.; Weissman, P.R.; Smythe, W.D.; Ocampo, A.C.; Danielson, G.E.; Fanale, F.P.; Johnson, T.V.; Kieffer, H.H.; Matson, D.L.; McCord, T.B.; Soderblom, L.A.
1991-01-01
During the 1990 Galileo Venus flyby, the Near Infrared Mapping Spectrometer investigated the night-side atmosphere of Venus in the spectral range 0.7 to 5.2 micrometers. Multispectral images at high spatial resolution indicate substantial cloud opacity variations in the lower cloud levels, centered at 50 kilometers altitude. Zonal and meridional winds were derived for this level and are consistent with motion of the upper branch of a Hadley cell. Northern and southern hemisphere clouds appear to be markedly different. Spectral profiles were used to derive lower atmosphere abundances of water vapor and other species.
NASA Technical Reports Server (NTRS)
Mahoney, M. J.; Ismail, S.; Browell, E. V.; Ferrare, R. A.; Kooi, S. A.; Brasseur, L.; Notari, A.; Petway, L.; Brackett, V.; Clayton, M.;
2002-01-01
LASE measures high resolution moisture, aerosol, and cloud distributions not available from conventional observations. LASE water vapor measurements were compared with dropsondes to evaluate their accuracy. LASE water vapor measurements were used to assess the capability of hurricane models to improve their track accuracy by 100 km on 3 day forecasts using Florida State University models.
NASA Technical Reports Server (NTRS)
Ho, Paul
1997-01-01
The research concentrated on high angular resolution (arc-second scale) studies of molecular cloud cores associated with very young star formation. New ways to study disks and protoplanetary systems were explored. Findings from the areas studied are briefly summarized: (1) molecular clouds; (2) gravitational contraction; (3) jets, winds, and outflows; (4) Circumstellar Disks (5) Extrasolar Planetary Systems. A bibliography of publications and submitted papers produced during the grant period is included.
NASA Technical Reports Server (NTRS)
Platnick, Steven; Zhang, Zhibo
2011-01-01
The Moderate Resolution Imaging Spectroradiometer (MODIS) cloud product provides three separate 1 km resolution retrievals of cloud particle effective radii (r (sub e)), derived from 1.6, 2.1 and 3.7 micron band observations. In this study, differences among the three size retrievals for maritime water clouds (designated as r (sub e), 1.6 r (sub e), 2.1 and r (sub e),3.7) were systematically investigated through a series of case studies and global analyses. Substantial differences are found between r (sub e),3.7 and r (sub e),2.1 retrievals (delta r (sub e),3.7-2.l), with a strong dependence on cloud regime. The differences are typically small, within +/- 2 micron, over relatively spatially homogeneous coastal stratocumulus cloud regions. However, for trade wind cumulus regimes, r (sub e),3.7 was found to be substantially smaller than r (sub e),2.1, sometimes by more than 10 micron. The correlation of delta r(sub e),3.7-2.1 with key cloud parameters, including the cloud optical thickness (tau), r (sub e) and a cloud horizontal heterogeneity index (H-sigma) derived from 250 m resolution MODIS 0.86 micron band observations, were investigated using one month of MODIS Terra data. It was found that differences among the three r (sub e) retrievals for optically thin clouds (tau <5) are highly variable, ranging from - 15 micron to 10 micron, likely due to the large MODIS retrieval uncertainties when the cloud is thin. The delta r (sub e),3.7-2.1 exhibited a threshold-like dependence on both r (sub e),2.l and H-sigma. The re,3.7 is found to agree reasonably well with re,2.! when re,2.l is smaller than about 15J-Lm, but becomes increasingly smaller than re,2.1 once re,2.! exceeds this size. All three re retrievals showed little dependence when H-sigma < 0.3 (defined as standard deviation divided by the mean for the 250 m pixels within a 1 km pixel retrieval). However, for H-=sigma >0.3, both r (sub e),1.6 and r (sub e),2.1 were seen to increase quickly with H-sigma. On the other hand, r (sub e),3.7 statistics showed little dependence on H-sigma and remained relatively stable over the whole range of H-sigma values. Potential contributing causes to the substantial r (sub e),3.7 and r (sub e),2.1 differences are discussed. In particular, based on both 1-D and 3-D radiative transfer simulations, we have elucidated mechanisms by which cloud heterogeneity and 3-D radiative effects can cause large differences between r (sub e),3.7 and r (sub e),2.l retrievals for highly inhomogeneous clouds. Our results suggest that the contrast in observed delta r (sub e)3.7-2.1 between cloud regimes is correlated with increases in both cloud r (sub e) and H-sigma. We also speculate that in some highly inhomogeneous drizzling clouds, vertical structure induced by drizzle and 3-D radiative effects might operate together to cause dramatic differences between r (sub e),3.7 and r (sub e),2.1 retrievals.
MERIS albedo climatology and its effect on the FRESCO+ O2 A-band cloud retrieval from SCIAMACHY data
NASA Astrophysics Data System (ADS)
Popp, Christoph; Wang, Ping; Brunner, Dominik; Stammes, Piet; Zhou, Yipin
2010-05-01
Accurate cloud information is an important prerequisite for the retrieval of atmospheric trace gases from spaceborne UV/VIS sensors. Errors in the estimated cloud fraction and cloud height (pressure) result in an erroneous air mass factor and thus can lead to inaccuracies in the vertical column densities of the retrieved trace gas. In ESA's TEMIS (Tropospheric Emission Monitoring Internet Service) project, the FRESCO+ (Fast Retrieval Scheme for Clouds from the Oxygen A-band) cloud retrieval is applied to, amongst others, SCIAMACHY (SCanning Imaging Absorption SpectroMeter for Atmospheric CartograpHY) data to determine these quantities. Effective cloud fraction and pressure are inverted by (i) radiative transfer simulations of top-of-atmosphere reflectance based on O2 absorption, single Rayleigh scattering, surface and cloud albedo in three spectral windows covering the O2 A-band and (ii) a subsequent fitting of the simulated to the measured spectrum. However, FRESCO+ relies on a relatively coarse resolution surface albedo climatology (1° x 1°) compiled from GOME (Global Ozone Monitoring Experiment) measurements in the 1990's which introduces several artifacts, e.g. an overestimation of cloud fraction at coastlines or over some mountainous regions. Therefore, we test the substitution of the GOME climatology with a new land surface albedo climatology compiled for every month from MEdium Resolution Imaging Spectrometer (MERIS) Albedomap data (0.05° x 0.05°) covering the period January 2003 to October 2006. The MERIS channels at 754nm and 775nm are located spectrally close to the corresponding GOME channels (758nm and 772nm) on both sides of the O2 A-band. Further, the increased spatial resolution of the MERIS product allows to better account for SCIAMACHY's pixel size of approximately 30x60km. The aim of this study is to describe and assess (i) the compilation and quality of the MERIS climatology (ii) the differences to the GOME climatology, and (iii) possible enhancements of the SCIAMACHY cloud retrieval after integrating the MERIS climatology into FRESCO+. First results indicate that in areas where FRESCO+ is overestimating cloud fraction using the GOME climatology, MERIS generally reveals higher albedo values which in turn will lead to lower cloud fractions, e.g. at coastlines, some arid or mountainous areas. The differences between the two data sets are also higher in winter than in summer. It can therefore be expected that the new data base with increased spatial resolution improves SCIAMACHY cloud retrieval with FRESCO+. The most limiting factors for the compilation of the MERIS climatology can be assigned to inappropriate snow cover masking and occasionally unfavorable illumination conditions in high northern latitudes during winter.
NASA Astrophysics Data System (ADS)
Moustaoui, Mohamed; Joseph, Binson; Teitelbaum, Hector
2004-12-01
A plausible mechanism for the formation of mixing layers in the lower stratosphere above regions of tropical convection is demonstrated numerically using high-resolution, two-dimensional (2D), anelastic, nonlinear, cloud-resolving simulations. One noteworthy point is that the mixing layer simulated in this study is free of anvil clouds and well above the cloud anvil top located in the upper troposphere. Hence, the present mechanism is complementary to the well-known process by which overshooting cloud turrets causes mixing within stratospheric anvil clouds. The paper is organized as a case study verifying the proposed mechanism using atmospheric soundings obtained during the Central Equatorial Pacific Experiment (CEPEX), when several such mixing layers, devoid of anvil clouds, had been observed. The basic dynamical ingredient of the present mechanism is (quasi stationary) gravity wave critical level interactions, occurring in association with a reversal of stratospheric westerlies to easterlies below the tropopause region. The robustness of the results is shown through simulations at different resolutions. The insensitivity of the qualitative results to the details of the subgrid scheme is also evinced through further simulations with and without subgrid mixing terms. From Lagrangian reconstruction of (passive) ozone fields, it is shown that the mixing layer is formed kinematically through advection by the resolved-scale (nonlinear) velocity field.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Ma, Po-Lun; Rasch, Philip J.; Fast, Jerome D.
A suite of physical parameterizations (deep and shallow convection, turbulent boundary layer, aerosols, cloud microphysics, and cloud fraction) from the global climate model Community Atmosphere Model version 5.1 (CAM5) has been implemented in the regional model Weather Research and Forecasting with chemistry (WRF-Chem). A downscaling modeling framework with consistent physics has also been established in which both global and regional simulations use the same emissions and surface fluxes. The WRF-Chem model with the CAM5 physics suite is run at multiple horizontal resolutions over a domain encompassing the northern Pacific Ocean, northeast Asia, and northwest North America for April 2008 whenmore » the ARCTAS, ARCPAC, and ISDAC field campaigns took place. These simulations are evaluated against field campaign measurements, satellite retrievals, and ground-based observations, and are compared with simulations that use a set of common WRF-Chem Parameterizations. This manuscript describes the implementation of the CAM5 physics suite in WRF-Chem provides an overview of the modeling framework and an initial evaluation of the simulated meteorology, clouds, and aerosols, and quantifies the resolution dependence of the cloud and aerosol parameterizations. We demonstrate that some of the CAM5 biases, such as high estimates of cloud susceptibility to aerosols and the underestimation of aerosol concentrations in the Arctic, can be reduced simply by increasing horizontal resolution. We also show that the CAM5 physics suite performs similarly to a set of parameterizations commonly used in WRF-Chem, but produces higher ice and liquid water condensate amounts and near-surface black carbon concentration. Further evaluations that use other mesoscale model parameterizations and perform other case studies are needed to infer whether one parameterization consistently produces results more consistent with observations.« less
Advances in Volcanic Ash Cloud Photogrammetry from Space
NASA Astrophysics Data System (ADS)
Zaksek, K.; von der Lieth, J.; Merucci, L.; Hort, M. K.; Gerst, A.; Carboni, E.; Corradini, S.
2015-12-01
The quality of ash dispersion prediction is limited by the lack of high quality information on eruption source parameters. One of the most important one is the ash cloud top height (ACTH). Because of well-known uncertainties of currently operational methods, photogrammetric methods can be used to improve height estimates. Some satellites have on board multiangular instruments that can be used for photogrammetrical observations. Volcanic ash clouds, however, can move with velocities over several m/s making these instruments inappropriate for accurate ACTH estimation. Thus we propose here two novel methods tested on different case studies (Etna 2013/11/23, Zhupanovsky 2014/09/10). The first method is based on NASA program Crew Earth observations from International Space Station (ISS). ISS has a lower orbit than most operational satellites, resulting in a shorter minimal time between two images required to produce a suitable parallax. In addition, images made by the ISS crew are taken by a full frame sensor and not a line scanner that most operational satellites use. Such data make possible to observe also short time evolution of clouds. The second method is based on the parallax between data retrieved from two geostationary instruments. We implemented a combination of MSG SEVIRI (HRV band; 1000 m nadir spatial resolution, 5 min temporal resolution) and METEOSAT7 MVIRI (VIS band, 2500 m nadir spatial resolution, 30 min temporal resolution). The procedure works well if the data from both satellites are retrieved nearly simultaneously. However, MVIRI does not retrieve the data at exactly the same time as SEVIRI. To compensate for advection in the atmosphere we use two sequential SEVIRI images (one before and one after the MVIRI retrieval) and interpolate the cloud position from SEVIRI data to the time of MVIRI retrieval.
West Antarctica as a Natural Laboratory for Single- and Mixed-Phase Cloud Microphysics
NASA Astrophysics Data System (ADS)
Wilson, A.; Scott, R. C.; Lubin, D.
2016-12-01
As part of the ARM West Antarctic Radiation Experiment (AWARE), a micropulse lidar (MPL) and a shortwave spectroradiometer were deployed to the West Antarctic Ice Sheet (WAIS) Divide Ice Camp during December 2015 and January 2016. Contrasting meteorological conditions gave rise to several distinct episodes of mixed-phase clouds, liquid water clouds, and entirely glaciated clouds. These phases were readily distinguished in the polarization signature from the MPL. The spectroradiometer measured downwelling hemispheric irradiance in the wavelength interval 0.35-2.2 microns, with 3-nanometer resolution at visible and 10-nanometer resolution at near-infrared wavelengths. Under overcast sky conditions, this measured irradiance is sensitive to total cloud optical depth for wavelengths shorter than 1.1 microns, and is sensitive at both cloud phase and effective particle size in the 1.6-micron window. For single-phase clouds, the spectral irradiance in the 1.6-micron window shows marked contrasts between liquid and ice water. For mixed phase clouds, this spectral dependence of the 1.6-micron irradiance is consistent with the prevailing phase, but in all cases the irradiance is small than that under a liquid water cloud having the same total optical depth. Radiative transfer retrievals of effective particle size from the 1.6-micron irradiance data reveal liquid water effective radii typically 2 microns smaller than found in the spring and summertime high Arctic. Most of the clouds sampled here were within 2 km of the surface, and there are comprehensive ancillary data including sondes four times daily, additional microwave radiometer data, and broadband radiometry. This AWARE data set from WAIS Divide provides a unique opportunity for testing and improving cloud microphysical parameterizations in extreme cold and pristine conditions.
OCRA radiometric cloud fractions for GOME-2 on MetOp-A/B
NASA Astrophysics Data System (ADS)
Lutz, Ronny; Loyola, Diego; Gimeno García, Sebastián; Romahn, Fabian
2016-05-01
This paper describes an approach for cloud parameter retrieval (radiometric cloud-fraction estimation) using the polarization measurements of the Global Ozone Monitoring Experiment-2 (GOME-2) onboard the MetOp-A/B satellites. The core component of the Optical Cloud Recognition Algorithm (OCRA) is the calculation of monthly cloud-free reflectances for a global grid (resolution of 0.2° in longitude and 0.2° in latitude) to derive radiometric cloud fractions. These cloud fractions will serve as a priori information for the retrieval of cloud-top height (CTH), cloud-top pressure (CTP), cloud-top albedo (CTA) and cloud optical thickness (COT) with the Retrieval Of Cloud Information using Neural Networks (ROCINN) algorithm. This approach is already being implemented operationally for the GOME/ERS-2 and SCIAMACHY/ENVISAT sensors and here we present version 3.0 of the OCRA algorithm applied to the GOME-2 sensors. Based on more than five years of GOME-2A data (April 2008 to June 2013), reflectances are calculated for ≈ 35 000 orbits. For each measurement a degradation correction as well as a viewing-angle-dependent and latitude-dependent correction is applied. In addition, an empirical correction scheme is introduced in order to remove the effect of oceanic sun glint. A comparison of the GOME-2A/B OCRA cloud fractions with colocated AVHRR (Advanced Very High Resolution Radiometer) geometrical cloud fractions shows a general good agreement with a mean difference of -0.15 ± 0.20. From an operational point of view, an advantage of the OCRA algorithm is its very fast computational time and its straightforward transferability to similar sensors like OMI (Ozone Monitoring Instrument), TROPOMI (TROPOspheric Monitoring Instrument) on Sentinel 5 Precursor, as well as Sentinel 4 and Sentinel 5. In conclusion, it is shown that a robust, accurate and fast radiometric cloud-fraction estimation for GOME-2 can be achieved with OCRA using polarization measurement devices (PMDs).
1989-08-26
P-34709 Range: 157,000 kilometers (98,000 miles) This Voyager 2 high resolution color image, taken 2 hours before closest approach, provides obvious evidence of vertical relief in Neptune's bright cloud streaks. These clouds were observed at a latitude of 29° N near Neptune's east terminator. The linear cloud forms are stretched approximately along lines of constant latitude and the sun is toward the lower left. The bright sides of the clouds that face the sun are brighter than the surrounding cloud deck because they are more directly exposed to the sun. Shadows can be seen on the side directly opposite the sun. These shadows are less distinct at short wavelengths (violet filter) and more distinct at long wavelengths (orange filter). This can be understood if the underlying cloud deck on which the shadow is cast is at a relatively great depth, in which case scattering by molecules in the overlying atmopsphere will diffuse light into the shadow. Because molecules scatter blue light much more efficiently than red light, the shadows will be darkest at the longest (reddest) wavelengths, and will appear blue under white illumination. The resolution of this image is 11 kilometers (6.8 miles per pixel). The width of the cloud streaks range from 50 to 200 kilometers (31 to 124 miles), and their shadow widths range from 30 to 50 kilometers (18 to 31 miles). Cloud heights appear to be of the order of 50 kilometers (31 miles). This corresponds to 2 scale heights.
Multilevel Cloud Structures above Svalbard
NASA Astrophysics Data System (ADS)
Dörnbrack, Andreas; Pitts, Micheal; Poole, Lamont; Gisinger, Sonja; Maturlli, Marion
2017-04-01
The presentation focusses on the reslts recently published by the authors under the heading "picture of the month" in Monthly Weather Review. The presented picture of the month is a superposition of space-borne lidar observations and high-resolution temperature fields of the ECMWF integrated forecast system (IFS). It displays complex tropospheric and stratospheric clouds in the Arctic winter 2015/16. Near the end of December 2015, the unusual northeastward propagation of warm and humid subtropical air masses as far north as 80°N lifted the tropopause by more than 3 km in 24 h and cooled the stratosphere on a large scale. A widespread formation of thick cirrus clouds near the tropopause and of synoptic-scale polar stratospheric clouds (PSCs) occurred as the temperature dropped below the thresholds for the existence of cloud particles. Additionally, mountain waves were excited by the strong flow at the western edge of the ridge across Svalbard, leading to the formation of mesoscale ice PSCs. The most recent IFS cycle using a horizontal resolution of 8 km globally reproduces the large-scale and mesoscale flow features and leads to a remarkable agreement with the wave structure revealed by the space-borne observations.
NASA Astrophysics Data System (ADS)
Goodson, Matthew D.; Heitsch, Fabian; Eklund, Karl; Williams, Virginia A.
2017-07-01
Turbulence models attempt to account for unresolved dynamics and diffusion in hydrodynamical simulations. We develop a common framework for two-equation Reynolds-averaged Navier-Stokes turbulence models, and we implement six models in the athena code. We verify each implementation with the standard subsonic mixing layer, although the level of agreement depends on the definition of the mixing layer width. We then test the validity of each model into the supersonic regime, showing that compressibility corrections can improve agreement with experiment. For models with buoyancy effects, we also verify our implementation via the growth of the Rayleigh-Taylor instability in a stratified medium. The models are then applied to the ubiquitous astrophysical shock-cloud interaction in three dimensions. We focus on the mixing of shock and cloud material, comparing results from turbulence models to high-resolution simulations (up to 200 cells per cloud radius) and ensemble-averaged simulations. We find that the turbulence models lead to increased spreading and mixing of the cloud, although no two models predict the same result. Increased mixing is also observed in inviscid simulations at resolutions greater than 100 cells per radius, which suggests that the turbulent mixing begins to be resolved.
On the Use of Deep Convective Clouds to Calibrate AVHRR Data
NASA Technical Reports Server (NTRS)
Doelling, David R.; Nguyen, Louis; Minnis, Patrick
2004-01-01
Remote sensing of cloud and radiation properties from National Oceanic and Atmospheric Administration (NOAA) Advanced Very High Resolution Radiometer (AVHRR) satellites requires constant monitoring of the visible sensors. NOAA satellites do not have onboard visible calibration and need to be calibrated vicariously in order to determine the calibration and the degradation rate. Deep convective clouds are extremely bright and cold, are at the tropopause, have nearly a Lambertian reflectance, and provide predictable albedos. The use of deep convective clouds as calibration targets is developed into a calibration technique and applied to NOAA-16 and NOAA-17. The technique computes the relative gain drift over the life-span of the satellite. This technique is validated by comparing the gain drifts derived from inter-calibration of coincident AVHRR and Moderate-Resolution Imaging Spectroradiometer (MODIS) radiances. A ray-matched technique, which uses collocated, coincident, and co-angled pixel satellite radiance pairs is used to intercalibrate MODIS and AVHRR. The deep convective cloud calibration technique was found to be independent of solar zenith angle, by using well calibrated Visible Infrared Scanner (VIRS) radiances onboard the Tropical Rainfall Measuring Mission (TRMM) satellite, which precesses through all solar zenith angles in 23 days.
NASA Technical Reports Server (NTRS)
Gibson, Harold M.; Vonder Haar, Thomas H.
1990-01-01
Based on relatively high spatial and temporal resolution satelite data collected at 0700 CST and at each hour from 1000 CST to 1700 CST during the summer of 1986, cloud and convection variations over the area from Mississippi east to Georgia and from the Gulf of Mexico north to Tennessee are discussed. The data analyses show an average maximum cloud frequency over the land areas at 1400 local time and a maximum of deep convection one hour later. Both cloudiness and deep convection are found to be at a maximum during the nocturnal hours over the Gulf of Mexico. Cloud frequency shows a strong relationship to small terrain features. Small fresh water bodies have cloud minima relative to the surroundings in the afternoon hours. Higher, steep terrain shows cloud maxima and the adjacent lower terrain exhibits afternoon cloud minima due to a divergence of mountain breeze caused by the valley.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Giangrande, Scott E.; Feng, Zhe; Jensen, Michael P.
Routine cloud, precipitation and thermodynamic observations collected by the Atmospheric Radiation Measurement (ARM) Mobile Facility (AMF) and Aerial Facility (AAF) during the 2-year US Department of Energy (DOE) ARM Observations and Modeling of the Green Ocean Amazon (GoAmazon2014/5) campaign are summarized. These observations quantify the diurnal to large-scale thermodynamic regime controls on the clouds and precipitation over the undersampled, climatically important Amazon basin region. The extended ground deployment of cloud-profiling instrumentation enabled a unique look at multiple cloud regimes at high temporal and vertical resolution. This longer-term ground deployment, coupled with two short-term aircraft intensive observing periods, allowed new opportunitiesmore » to better characterize cloud and thermodynamic observational constraints as well as cloud radiative impacts for modeling efforts within typical Amazon wet and dry seasons.« less
NASA Technical Reports Server (NTRS)
Barrett, E. C.; Grant, C. K. (Principal Investigator)
1977-01-01
The author has identified the following significant results. It was demonstrated that satellites with sufficiently high resolution capability in the visible region of the electromagnetic spectrum could be used to check the accuracy of estimates of total cloud amount assessed subjectively from the ground, and to reveal areas of performance in which corrections should be made. It was also demonstrated that, in middle latitude in summer, cloud shadow may obscure at least half as much again of the land surface covered by an individual LANDSAT frame as the cloud itself. That proportion would increase with latitude and/or time of year towards the winter solstice. Analyses of sample multispectral images for six different categories of clouds in summer revealed marked differences between the reflectance characteristics of cloud fields in the visible/near infrared region of the spectrum.
Giangrande, Scott E.; Feng, Zhe; Jensen, Michael P.; ...
2017-12-06
Routine cloud, precipitation and thermodynamic observations collected by the Atmospheric Radiation Measurement (ARM) Mobile Facility (AMF) and Aerial Facility (AAF) during the 2-year US Department of Energy (DOE) ARM Observations and Modeling of the Green Ocean Amazon (GoAmazon2014/5) campaign are summarized. These observations quantify the diurnal to large-scale thermodynamic regime controls on the clouds and precipitation over the undersampled, climatically important Amazon basin region. The extended ground deployment of cloud-profiling instrumentation enabled a unique look at multiple cloud regimes at high temporal and vertical resolution. This longer-term ground deployment, coupled with two short-term aircraft intensive observing periods, allowed new opportunitiesmore » to better characterize cloud and thermodynamic observational constraints as well as cloud radiative impacts for modeling efforts within typical Amazon wet and dry seasons.« less
NASA Astrophysics Data System (ADS)
Kahn, B. H.; Yue, Q.; Davis, S. M.; Fetzer, E. J.; Schreier, M. M.; Tian, B.; Wong, S.
2016-12-01
We will quantify the time and space dependence of ice cloud effective radius (CER), optical thickness (COT), cloud top temperature (CTT), effective cloud fraction (ECF), and cloud thermodynamic phase (ice, liquid, or unknown) with the Version 6 Atmospheric Infrared Sounder (AIRS) satellite observational data set from September 2002 until present. We show that cloud frequency, CTT, COT, and ECF have substantially different responses to ENSO variations. Large-scale changes in ice CER are also observed with a several micron tropics-wide increase during the 2015-2016 El Niño and similar decreases during the La Niña phase. We show that the ice CER variations reflect fundamental changes in the spatial distributions and relative frequencies of different ice cloud types. Lastly, the high spatial and temporal resolution variability of the cloud fields are explored and we show that these data capture a multitude of convectively coupled tropical waves such as Kelvin, westward and eastward intertio-gravity, equatorial Rossby, and mixed Rossby-gravity waves.
Using Himawari-8, estimation of SO2 cloud altitude at Aso volcano eruption, on October 8, 2016
NASA Astrophysics Data System (ADS)
Ishii, Kensuke; Hayashi, Yuta; Shimbori, Toshiki
2018-02-01
It is vital to detect volcanic plumes as soon as possible for volcanic hazard mitigation such as aviation safety and the life of residents. Himawari-8, the Japan Meteorological Agency's (JMA's) geostationary meteorological satellite, has high spatial resolution and sixteen observation bands including the 8.6 μm band to detect sulfur dioxide (SO2). Therefore, Ash RGB composite images (RED: brightness temperature (BT) difference between 12.4 and 10.4 μm, GREEN: BT difference between 10.4 and 8.6 μm, BLUE: 10.4 μm) discriminate SO2 clouds and volcanic ash clouds from meteorological clouds. Since the Himawari-8 has also high temporal resolution, the real-time monitoring of ash and SO2 clouds is of great use. A phreatomagmatic eruption of Aso volcano in Kyushu, Japan, occurred at 01:46 JST on October 8, 2016. For this eruption, the Ash RGB could detect SO2 cloud from Aso volcano immediately after the eruption and track it even 12 h after. In this case, the Ash RGB images every 2.5 min could clearly detect the SO2 cloud that conventional images such as infrared and split window could not detect sufficiently. Furthermore, we could estimate the height of the SO2 cloud by comparing the Ash RGB images and simulations of the JMA Global Atmospheric Transport Model with a variety of height parameters. As a result of comparison, the top and bottom height of the SO2 cloud emitted from the eruption was estimated as 7 and 13-14 km, respectively. Assuming the plume height was 13-14 km and eruption duration was 160-220 s (as estimated by seismic observation), the total emission mass of volcanic ash from the eruption was estimated as 6.1-11.8 × 108 kg, which is relatively consistent with 6.0-6.5 × 108 kg from field survey. [Figure not available: see fulltext.
NASA Astrophysics Data System (ADS)
Ishida, H.; Ota, Y.; Sekiguchi, M.; Sato, Y.
2016-12-01
A three-dimensional (3D) radiative transfer calculation scheme is developed to estimate horizontal transport of radiation energy in a very high resolution (with the order of 10 m in spatial grid) simulation of cloud evolution, especially for horizontally inhomogeneous clouds such as shallow cumulus and stratocumulus. Horizontal radiative transfer due to inhomogeneous clouds seems to cause local heating/cooling in an atmosphere with a fine spatial scale. It is, however, usually difficult to estimate the 3D effects, because the 3D radiative transfer often needs a large resource for computation compared to a plane-parallel approximation. This study attempts to incorporate a solution scheme that explicitly solves the 3D radiative transfer equation into a numerical simulation, because this scheme has an advantage in calculation for a sequence of time evolution (i.e., the scene at a time is little different from that at the previous time step). This scheme is also appropriate to calculation of radiation with strong absorption, such as the infrared regions. For efficient computation, this scheme utilizes several techniques, e.g., the multigrid method for iteration solution, and a correlated-k distribution method refined for efficient approximation of the wavelength integration. For a case study, the scheme is applied to an infrared broadband radiation calculation in a broken cloud field generated with a large eddy simulation model. The horizontal transport of infrared radiation, which cannot be estimated by the plane-parallel approximation, and its variation in time can be retrieved. The calculation result elucidates that the horizontal divergences and convergences of infrared radiation flux are not negligible, especially at the boundaries of clouds and within optically thin clouds, and the radiative cooling at lateral boundaries of clouds may reduce infrared radiative heating in clouds. In a future work, the 3D effects on radiative heating/cooling will be able to be included into atmospheric numerical models.
NASA Technical Reports Server (NTRS)
Atlas, Robert (Technical Monitor); Joiner, Joanna; Vasikov, Alexander; Flittner, David; Gleason, James; Bhartia, P. K.
2002-01-01
Reliable cloud pressure estimates are needed for accurate retrieval of ozone and other trace gases using satellite-borne backscatter ultraviolet (buv) instruments such as the global ozone monitoring experiment (GOME). Cloud pressure can be derived from buv instruments by utilizing the properties of rotational-Raman scattering (RRS) and absorption by O2-O2. In this paper we estimate cloud pressure from GOME observations in the 355-400 nm spectral range using the concept of a Lambertian-equivalent reflectivity (LER) surface. GOME has full spectral coverage in this range at relatively high spectral resolution with a very high signal-to-noise ratio. This allows for much more accurate estimates of cloud pressure than were possible with its predecessors SBUV and TOMS. We also demonstrate the potential capability to retrieve chlorophyll content with full-spectral buv instruments. We compare our retrieved LER cloud pressure with cloud top pressures derived from the infrared ATSR instrument on the same satellite. The findings confirm results from previous studies that showed retrieved LER cloud pressures from buv observations are systematically higher than IR-derived cloud-top pressure. Simulations using Mie-scattering radiative transfer algorithms that include O2-O2 absorption and RRS show that these differences can be explained by increased photon path length within and below cloud.
NASA Astrophysics Data System (ADS)
Meenu, S.; Rajeev, K.; Parameswaran, K.; Suresh Raju, C.
2006-12-01
Quantitative estimates of the spatio-temporal variations in deep convective events over the Indian subcontinent, Arabian Sea, Bay of Bengal, and tropical Indian Ocean are carried out using the data obtained from Advanced Very High Resolution Radiometer (AVHRR) onboard NOAA-14 and NOAA-16 during the period 1996-2003. Pixels having thermal IR brightness temperature (BT) less than 245K are considered as high altitude clouds and those having BT<220 K are considered as very high altitude clouds. Very deep convective clouds are observed over north Bay of Bengal during the Asian summer monsoon season when the mean cloud top temperature reaches as low as 190K. Over the Head Bay of Bengal (HBoB) from June to September, more than 50% of the observed clouds are deep convective type and more than half of these deep convective clouds are very deep convective clouds. Histogram analysis of the cloud top temperatures during this period shows that over HBoB the most prominent cloud top temperature of the deep convective clouds is ~205K over the HBoB while that over southeast Arabian Sea (SEAS) is ~220K. This indicates that most probably the cloud top altitude over HBoB is ~2 km larger than that over SEAS during the Asian summer monsoon period. Another remarkable feature observed during the Asian summer monsoon period is the significantly low values of deep convective clouds observed over the south Bay of Bengal close to Srilanka, which appears as a large pool of reduced cloud amount surrounded by regions of large-scale deep convection. Over both SEAS and HBoB, the total, deep convective and very deep convective cloud amounts as well as their corresponding cloud top temperatures (or the altitude of the cloud top) undergo large seasonal variations, while such variations are less prominent over the eastern equatorial Indian Ocean.
Li, Zhijin; Vogelmann, Andrew M.; Feng, Sha; ...
2015-01-20
We produce fine-resolution, three-dimensional fields of meteorological and other variables for the U.S. Department of Energy’s Atmospheric Radiation Measurement (ARM) Southern Great Plains site. The Community Gridpoint Statistical Interpolation system is implemented in a multiscale data assimilation (MS-DA) framework that is used within the Weather Research and Forecasting model at a cloud-resolving resolution of 2 km. The MS-DA algorithm uses existing reanalysis products and constrains fine-scale atmospheric properties by assimilating high-resolution observations. A set of experiments show that the data assimilation analysis realistically reproduces the intensity, structure, and time evolution of clouds and precipitation associated with a mesoscale convective system.more » Evaluations also show that the large-scale forcing derived from the fine-resolution analysis has an overall accuracy comparable to the existing ARM operational product. For enhanced applications, the fine-resolution fields are used to characterize the contribution of subgrid variability to the large-scale forcing and to derive hydrometeor forcing, which are presented in companion papers.« less
Neptune Clouds Showing Vertical Relief
1996-01-29
NASA's Voyager 2 high resolution color image, taken 2 hours before closest approach, provides obvious evidence of vertical relief in Neptune's bright cloud streaks. These clouds were observed at a latitude of 29 degrees north near Neptune's east terminator. The linear cloud forms are stretched approximately along lines of constant latitude and the sun is toward the lower left. The bright sides of the clouds which face the sun are brighter than the surrounding cloud deck because they are more directly exposed to the sun. Shadows can be seen on the side opposite the sun. These shadows are less distinct at short wavelengths (violet filter) and more distinct at long wavelengths (orange filter). This can be understood if the underlying cloud deck on which the shadow is cast is at a relatively great depth, in which case scattering by molecules in the overlying atmosphere will diffuse light into the shadow. Because molecules scatter blue light much more efficiently than red light, the shadows will be darkest at the longest (reddest) wavelengths, and will appear blue under white light illumination. The resolution of this image is 11 kilometers (6.8 miles per pixel) and the range is only 157,000 kilometers (98,000 miles). The width of the cloud streaks range from 50 to 200 kilometers (31 to 124 miles), and their shadow widths range from 30 to 50 kilometers (18 to 31 miles). Cloud heights appear to be of the order of 50 kilometers (31 miles). This corresponds to 2 scale heights. http://photojournal.jpl.nasa.gov/catalog/PIA00058
Neptune Clouds Showing Vertical Relief
NASA Technical Reports Server (NTRS)
1989-01-01
This Voyager 2 high resolution color image, taken 2 hours before closest approach, provides obvious evidence of vertical relief in Neptune's bright cloud streaks. These clouds were observed at a latitude of 29 degrees north near Neptune's east terminator. The linear cloud forms are stretched approximately along lines of constant latitude and the sun is toward the lower left. The bright sides of the clouds which face the sun are brighter than the surrounding cloud deck because they are more directly exposed to the sun. Shadows can be seen on the side opposite the sun. These shadows are less distinct at short wavelengths (violet filter) and more distinct at long wavelengths (orange filter). This can be understood if the underlying cloud deck on which the shadow is cast is at a relatively great depth, in which case scattering by molecules in the overlying atmosphere will diffuse light into the shadow. Because molecules scatter blue light much more efficiently than red light, the shadows will be darkest at the longest (reddest) wavelengths, and will appear blue under white light illumination. The resolution of this image is 11 kilometers (6.8 miles per pixel) and the range is only 157,000 kilometers (98,000 miles). The width of the cloud streaks range from 50 to 200 kilometers (31 to 124 miles), and their shadow widths range from 30 to 50 kilometers (18 to 31 miles). Cloud heights appear to be of the order of 50 kilometers (31 miles). This corresponds to 2 scale heights. The Voyager Mission is conducted by JPL for NASA's Office of Space Science and Applications.
Measuring cloud thermodynamic phase with shortwave infrared imaging spectroscopy
DOE Office of Scientific and Technical Information (OSTI.GOV)
Thompson, David R.; McCubbin, Ian; Gao, Bo Cai
Shortwave Infrared imaging spectroscopy enables accurate remote mapping of cloud thermodynamic phase at high spatial resolution. We describe a measurement strategy to exploit signatures of liquid and ice absorption in cloud top apparent reflectance spectra from 1.4 to 1.8 μm. This signal is generally insensitive to confounding factors such as solar angles, view angles, and surface albedo. We first evaluate the approach in simulation and then apply it to airborne data acquired in the Calwater-2/ACAPEX campaign of Winter 2015. Here NASA’s “Classic” Airborne Visible Infrared Imaging Spectrometer (AVIRIS-C) remotely observed diverse cloud formations while the U.S. Department of Energy ARMmore » Aerial Facility G-1 aircraft measured cloud integral and microphysical properties in situ. Finally, the coincident measurements demonstrate good separation of the thermodynamic phases for relatively homogeneous clouds.« less
A High Resolution Hydrometer Phase Classifier Based on Analysis of Cloud Radar Doppler Spectra.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Luke,E.; Kollias, P.
2007-08-06
The lifecycle and radiative properties of clouds are highly sensitive to the phase of their hydrometeors (i.e., liquid or ice). Knowledge of cloud phase is essential for specifying the optical properties of clouds, or else, large errors can be introduced in the calculation of the cloud radiative fluxes. Current parameterizations of cloud water partition in liquid and ice based on temperature are characterized by large uncertainty (Curry et al., 1996; Hobbs and Rangno, 1998; Intriery et al., 2002). This is particularly important in high geographical latitudes and temperature ranges where both liquid droplets and ice crystal phases can exist (mixed-phasemore » cloud). The mixture of phases has a large effect on cloud radiative properties, and the parameterization of mixed-phase clouds has a large impact on climate simulations (e.g., Gregory and Morris, 1996). Furthermore, the presence of both ice and liquid affects the macroscopic properties of clouds, including their propensity to precipitate. Despite their importance, mixed-phase clouds are severely understudied compared to the arguably simpler single-phase clouds. In-situ measurements in mixed-phase clouds are hindered due to aircraft icing, difficulties distinguishing hydrometeor phase, and discrepancies in methods for deriving physical quantities (Wendisch et al. 1996, Lawson et al. 2001). Satellite-based retrievals of cloud phase in high latitudes are often hindered by the highly reflecting ice-covered ground and persistent temperature inversions. From the ground, the retrieval of mixed-phase cloud properties has been the subject of extensive research over the past 20 years using polarization lidars (e.g., Sassen et al. 1990), dual radar wavelengths (e.g., Gosset and Sauvageot 1992; Sekelsky and McIntosh, 1996), and recently radar Doppler spectra (Shupe et al. 2004). Millimeter-wavelength radars have substantially improved our ability to observe non-precipitating clouds (Kollias et al., 2007) due to their excellent sensitivity that enables the detection of thin cloud layers and their ability to penetrate several non-precipitating cloud layers. However, in mixed-phase clouds conditions, the observed Doppler moments are dominated by the highly reflecting ice crystals and thus can not be used to identify the cloud phase. This limits our ability to identify the spatial distribution of cloud phase and our ability to identify the conditions under which mixed-phase clouds form.« less
NASA Technical Reports Server (NTRS)
Grecu, Mircea; Anagnostou, Emmanouil N.; Olson, William S.; Starr, David OC. (Technical Monitor)
2002-01-01
In this study, a technique for estimating vertical profiles of precipitation from multifrequency, multiresolution active and passive microwave observations is investigated using both simulated and airborne data. The technique is applicable to the Tropical Rainfall Measuring Mission (TRMM) satellite multi-frequency active and passive observations. These observations are characterized by various spatial and sampling resolutions. This makes the retrieval problem mathematically more difficult and ill-determined because the quality of information decreases with decreasing resolution. A model that, given reflectivity profiles and a small set of parameters (including the cloud water content, the intercept drop size distribution, and a variable describing the frozen hydrometeor properties), simulates high-resolution brightness temperatures is used. The high-resolution simulated brightness temperatures are convolved at the real sensor resolution. An optimal estimation procedure is used to minimize the differences between simulated and observed brightness temperatures. The retrieval technique is investigated using cloud model synthetic and airborne data from the Fourth Convection And Moisture Experiment. Simulated high-resolution brightness temperatures and reflectivities and airborne observation strong are convolved at the resolution of the TRMM instruments and retrievals are performed and analyzed relative to the reference data used in observations synthesis. An illustration of the possible use of the technique in satellite rainfall estimation is presented through an application to TRMM data. The study suggests improvements in combined active and passive retrievals even when the instruments resolutions are significantly different. Future work needs to better quantify the retrievals performance, especially in connection with satellite applications, and the uncertainty of the models used in retrieval.
The 94 GHz Cloud Radar System on a NASA ER-2 Aircraft
NASA Technical Reports Server (NTRS)
Li, Lihua; Heymsfield, Gerald M.; Racette, Paul E.; Tian, Lin; Zenker, Ed
2003-01-01
The 94-GHz (W-band) Cloud Radar System (CRS) has been developed and flown on a NASA ER-2 high-altitude (20 km) aircraft. The CRS is a fully coherent, polarimeteric Doppler radar that is capable of detecting clouds and precipitation from the surface up to the aircraft altitude in the lower stratosphere. The radar is especially well suited for cirrus cloud studies because of its high sensitivity and fine spatial resolution. This paper describes the CRS motivation, instrument design, specifications, calibration, and preliminary data &om NASA s Cirrus Regional Study of Tropical Anvils and Cirrus Layers - Florida Area Cirrus Experiment (CRYSTAL-FACE) field campaign. The unique combination of CRS with other sensors on the ER-2 provides an unprecedented opportunity to study cloud radiative effects on the global energy budget. CRS observations are being used to improve our knowledge of atmospheric scattering and attenuation characteristics at 94 GHz, and to provide datasets for algorithm implementation and validation for the upcoming NASA CloudSat mission that will use a 94-GHz spaceborne cloud radar to provide the first direct global survey of the vertical structure of cloud systems.
The Aerosol/Cloud/Ecosystems Mission (ACE)
NASA Technical Reports Server (NTRS)
Schoeberl, Mark
2008-01-01
The goals and measurement strategy of the Aerosol/Cloud/Ecosystems Mission (ACE) are described. ACE will help to answer fundamental science questions associated with aerosols, clouds, air quality and global ocean ecosystems. Specifically, the goals of ACE are: 1) to quantify aerosol-cloud interactions and to assess the impact of aerosols on the hydrological cycle and 2) determine Ocean Carbon Cycling and other ocean biological processes. It is expected that ACE will: narrow the uncertainty in aerosol-cloud-precipitation interaction and quantify the role of aerosols in climate change; measure the ocean ecosystem changes and precisely quantify ocean carbon uptake; and, improve air quality forecasting by determining the height and type of aerosols being transported long distances. Overviews are provided of the aerosol-cloud community measurement strategy, aerosol and cloud observations over South Asia, and ocean biology research goals. Instruments used in the measurement strategy of the ACE mission are also highlighted, including: multi-beam lidar, multiwavelength high spectra resolution lidar, the ocean color instrument (ORCA)--a spectroradiometer for ocean remote sensing, dual frequency cloud radar and high- and low-frequency micron-wave radiometer. Future steps for the ACE mission include refining measurement requirements and carrying out additional instrument and payload studies.
Aerosol midlatitude cyclone indirect effects in observations and high-resolution simulations
NASA Astrophysics Data System (ADS)
McCoy, Daniel T.; Field, Paul R.; Schmidt, Anja; Grosvenor, Daniel P.; Bender, Frida A.-M.; Shipway, Ben J.; Hill, Adrian A.; Wilkinson, Jonathan M.; Elsaesser, Gregory S.
2018-04-01
Aerosol-cloud interactions are a major source of uncertainty in inferring the climate sensitivity from the observational record of temperature. The adjustment of clouds to aerosol is a poorly constrained aspect of these aerosol-cloud interactions. Here, we examine the response of midlatitude cyclone cloud properties to a change in cloud droplet number concentration (CDNC). Idealized experiments in high-resolution, convection-permitting global aquaplanet simulations with constant CDNC are compared to 13 years of remote-sensing observations. Observations and idealized aquaplanet simulations agree that increased warm conveyor belt (WCB) moisture flux into cyclones is consistent with higher cyclone liquid water path (CLWP). When CDNC is increased a larger LWP is needed to give the same rain rate. The LWP adjusts to allow the rain rate to be equal to the moisture flux into the cyclone along the WCB. This results in an increased CLWP for higher CDNC at a fixed WCB moisture flux in both observations and simulations. If observed cyclones in the top and bottom tercile of CDNC are contrasted it is found that they have not only higher CLWP but also cloud cover and albedo. The difference in cyclone albedo between the cyclones in the top and bottom third of CDNC is observed by CERES to be between 0.018 and 0.032, which is consistent with a 4.6-8.3 Wm-2 in-cyclone enhancement in upwelling shortwave when scaled by annual-mean insolation. Based on a regression model to observed cyclone properties, roughly 60 % of the observed variability in CLWP can be explained by CDNC and WCB moisture flux.
Balloon-borne three-meter telescope for far-infrared and submillimeter astronomy
NASA Technical Reports Server (NTRS)
Fazio, G. G.
1985-01-01
Presented are scientific objectives, engineering analysis and design, and results of technology development for a Three-Meter Balloon-Borne Far-Infrared and Submillimeter Telescope. The scientific rationale is based on two crucial instrumental capabilities: high angular resolution which approaches eight arcseconds at one hundred micron wavelength, and high resolving power spectroscopy with good sensitivity throughout the telescope's 30-micron to 1-mm wavelength range. The high angular resolution will allow us to resolve and study in detail such objects as collapsing protostellar condensations in our own galaxy, clusters of protostars in the Magellanic clouds, giant molecular clouds in nearby galaxies, and spiral arms in distant galaxies. The large aperture of the telescope will permit sensitive spectral line measurements of molecules, atoms, and ions, which can be used to probe the physical, chemical, and dynamical conditions in a wide variety of objects.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Frick, G.M.; Hoppel, W.A.
1993-11-01
The use of an airship as a platform to conduct atmospheric chemistry, aerosol, and cloud microphysical research is described, and results from demonstration flights made off the Oregon coast are presented. The slow speed of the airship makes it an ideal platform to do high-spatial resolution profiling both vertically and horizontally, and to measure large aerosol and cloud droplet distributions without the difficulties caused by high-speed aircraft sampling. A unique set of data obtained during the demonstration flights show the effect that processing marine boundary layer aerosol through stratus clouds has on the aerosol size distribution. Evidence of new particlemore » formation (nucleation of particles) was also observed on about half the days on which flights were made. 11 refs., 9 figs., 1 tab.« less
Changes in cloud properties over East Asia deduced from the CLARA-A2 satellite data record
NASA Astrophysics Data System (ADS)
Benas, Nikos; Fokke Meirink, Jan; Hollmann, Rainer; Karlsson, Karl-Göran; Stengel, Martin
2017-04-01
Studies on cloud properties and processes, and their role in the Earth's changing climate, have advanced during the past decades. A significant part of this advance was enabled by satellite measurements, which offer global and continuous monitoring. Lately, a new satellite-based cloud data record was released: the CM SAF cLoud, Albedo and surface RAdiation dataset from AVHRR data - second edition (CLARA-A2) includes high resolution cloud macro- and micro-physical properties derived from the AVHRR instruments on board NOAA and MetOp polar orbiters. Based on this data record, an analysis of cloud property changes over East Asia during the 12-year period 2004-2015 was performed. Significant changes were found in both optical and geometric cloud properties, including increases in cloud liquid water path and top height. The Cloud Droplet Number Concentration (CDNC) was specifically studied in order to gain further insight into possible connections between aerosol and cloud processes. To this end, aerosol and cloud observations from MODIS, covering the same area and period, were included in the analysis.
A novel technique for evaluating the volcanic cloud top altitude using GPS Radio Occultation data
NASA Astrophysics Data System (ADS)
Biondi, Riccardo; Corradini, Stefano; Guerrieri, Lorenzo; Merucci, Luca; Stelitano, Dario; Pugnaghi, Sergio
2017-04-01
Volcanic ash and sulfuric gases are a major hazards to aviation since they damage the aircraft engines also at large distance from the eruption. Many challenges given by volcanic explosive eruptions are still discussed and several issues are far from being solved. The cloud top altitude can be detected with different techniques, but the accuracy is still quite coarse. This parameter is important for the air traffic to know what altitude can be ash free, and it assumes a key role for the contribution of the eruption to the climate change. Moreover, the cloud top altitude is also strictly related to the mass ejected by the eruption and represent a key parameter for the ash and SO2 retrievals by using several techniques. The Global Positioning System (GPS) Radio Occultation (RO) technique enables real time measurement of atmospheric density structure in any meteorological condition, in remote areas and during extreme atmospheric events with high vertical resolution and accuracy and this makes the RO an interesting tool for this kind of studies. In this study we have tracked the Eyjafjöll 2010 eruption by using MODIS satellite measurements and retrieved the volcanic cloud top altitudes by using two different procedures exploiting the thermal infrared CO2 absorption bands around 13.4 micrometers. The first approach is a modification of the standard CO2 slicing method while the second is based on look up tables computations. We have then selected all the RO profiles co-located with the volcanic cloud and implemented an algorithm based on the variation of the bending angle for detecting the cloud top altitude with high accuracy. The results of the comparison between the MODIS and RO volcanic height retrievals are encouraging and suggesting that, due to their independence from weather conditions and due to their high vertical resolution, the RO observations can contribute to improved detection and monitoring of volcanic clouds and to support warning systems.
NASA Technical Reports Server (NTRS)
Rossow, William B. (Principal Investigator)
Since 1983 an international group of institutions has collected and analyzed satellite radiance measurements from up to five geostationary and two polar orbiting satellites to infer the global distribution of cloud properties and their diurnal, seasonal and interannual variations. The primary focus of the first phase of the project (1983-1995) was the elucidation of the role of clouds in the radiation budget (top of the atmosphere and surface). In the second phase of the project (1995 onwards) the analysis also concerns improving understanding of clouds in the global hydrological cycle. [Location=GLOBAL] [Temporal_Coverage: Start_Date=1983-07-01; Stop_Date=] [Spatial_Coverage: Southernmost_Latitude=-90; Northernmost_Latitude=90; Westernmost_Longitude=-180; Easternmost_Longitude=180] [Data_Resolution: Latitude_Resolution=112 Km; Longitude_Resolution=112 Km; Temporal_Resolution=5-day].
Relating Solar Resource Variability to Cloud Type
NASA Astrophysics Data System (ADS)
Hinkelman, L. M.; Sengupta, M.
2012-12-01
Power production from renewable energy (RE) resources is rapidly increasing. Generation of renewable energy is quite variable since the solar and wind resources that form the inputs are, themselves, inherently variable. There is thus a need to understand the impact of renewable generation on the transmission grid. Such studies require estimates of high temporal and spatial resolution power output under various scenarios, which can be created from corresponding solar resource data. Satellite-based solar resource estimates are the best source of long-term solar irradiance data for the typically large areas covered by transmission studies. As satellite-based resource datasets are generally available at lower temporal and spatial resolution than required, there is, in turn, a need to downscale these resource data. Downscaling in both space and time requires information about solar irradiance variability, which is primarily a function of cloud types and properties. In this study, we analyze the relationship between solar resource variability and satellite-based cloud properties. One-minute resolution surface irradiance data were obtained from a number of stations operated by the National Oceanic and Atmospheric Administration (NOAA) under the Surface Radiation (SURFRAD) and Integrated Surface Irradiance Study (ISIS) networks as well as from NREL's Solar Radiation Research Laboratory (SRRL) in Golden, Colorado. Individual sites were selected so that a range of meteorological conditions would be represented. Cloud information at a nominal 4 km resolution and half hour intervals was derived from NOAA's Geostationary Operation Environmental Satellite (GOES) series of satellites. Cloud class information from the GOES data set was then used to select and composite irradiance data from the measurement sites. The irradiance variability for each cloud classification was characterized using general statistics of the fluxes themselves and their variability in time, as represented by ramps computed for time scales from 10 s to 0.5 hr. The statistical relationships derived using this method will be presented, comparing and contrasting the statistics computed for the different cloud types. The implications for downscaling irradiances from satellites or forecast models will also be discussed.
Vladimirov, Gleb; Hendrickson, Christopher L; Blakney, Greg T; Marshall, Alan G; Heeren, Ron M A; Nikolaev, Eugene N
2012-02-01
Particle-in-Cell (PIC) ion trajectory calculations provide the most realistic simulation of Fourier transform ion cyclotron resonance (FT-ICR) experiments by efficient and accurate calculation of the forces acting on each ion in an ensemble (cloud), including Coulomb interactions (space charge), the electric field of the ICR trap electrodes, image charges on the trap electrodes, the magnetic field, and collisions with neutral gas molecules. It has been shown recently that ion cloud collective behavior is required to generate an FT-ICR signal and that two main phenomena influence mass resolution and dynamic range. The first is formation of an ellipsoidal ion cloud (termed "condensation") at a critical ion number (density), which facilitates signal generation in an FT-ICR cell of arbitrary geometry because the condensed cloud behaves as a quasi-ion. The second phenomenon is peak coalescence. Ion resonances that are closely spaced in m/z coalesce into one resonance if the ion number (density) exceeds a threshold that depends on magnetic field strength, ion cyclotron radius, ion masses and mass difference, and ion initial spatial distribution. These two phenomena decrease dynamic range by rapid cloud dephasing at small ion density and by cloud coalescence at high ion density. Here, we use PIC simulations to quantitate the dependence of coalescence on each critical parameter. Transitions between independent and coalesced motion were observed in a series of the experiments that systematically varied ion number, magnetic field strength, ion radius, ion m/z, ion m/z difference, and ion initial spatial distribution (the present simulations begin from elliptically-shaped ion clouds with constant ion density distribution). Our simulations show that mass resolution is constant at a given magnetic field strength with increasing ion number until a critical value (N) is reached. N dependence on magnetic field strength, cyclotron radius, ion mass, and difference between ion masses was determined for two ion ensembles of different m/z, equal abundance, and equal cyclotron radius. We find that N and dynamic range depend quadratically on magnetic field strength in the range 1-21 Tesla. Dependences on cyclotron radius and Δm/z are linear. N depends on m/z as (m/z)(-2). Empirical expressions for mass resolution as a function of each of the experimental parameters are presented. Here, we provide the first exposition of the origin and extent of trade-off between FT-ICR MS dynamic range and mass resolution (defined not as line width, but as the separation between the most closely resolved masses). © American Society for Mass Spectrometry, 2011
NASA Astrophysics Data System (ADS)
Davis, A. B.; Bal, G.; Chen, J.
2015-12-01
Operational remote sensing of microphysical and optical cloud properties is invariably predicated on the assumption of plane-parallel slab geometry for the targeted cloud. The sole benefit of this often-questionable assumption about the cloud is that it leads to one-dimensional (1D) radiative transfer (RT)---a textbook, computationally tractable model. We present new results as evidence that, thanks to converging advances in 3D RT, inverse problem theory, algorithm implementation, and computer hardware, we are at the dawn of a new era in cloud remote sensing where we can finally go beyond the plane-parallel paradigm. Granted, the plane-parallel/1D RT assumption is reasonable for spatially extended stratiform cloud layers, as well as the smoothly distributed background aerosol layers. However, these 1D RT-friendly scenarios exclude cases that are critically important for climate physics. 1D RT---whence operational cloud remote sensing---fails catastrophically for cumuliform clouds that have fully 3D outer shapes and internal structures driven by shallow or deep convection. For these situations, the first order of business in a robust characterization by remote sensing is to abandon the slab geometry framework and determine the 3D geometry of the cloud, as a first step toward bone fide 3D cloud tomography. With this specific goal in mind, we deliver a proof-of-concept for an entirely new kind of remote sensing applicable to 3D clouds. It is based on highly simplified 3D RT and exploits multi-angular suites of cloud images at high spatial resolution. Airborne sensors like AirMSPI readily acquire such data. The key element of the reconstruction algorithm is a sophisticated solution of the nonlinear inverse problem via linearization of the forward model and an iteration scheme supported, where necessary, by adaptive regularization. Currently, the demo uses a 2D setting to show how either vertical profiles or horizontal slices of the cloud can be accurately reconstructed. Extension to 3D volumes is straightforward but the next challenge is to accommodate images at lower spatial resolution, e.g., from MISR/Terra. G. Bal, J. Chen, and A.B. Davis (2015). Reconstruction of cloud geometry from multi-angle images, Inverse Problems in Imaging (submitted).
Operational processing and cloud boundary detection from micro pulse lidar data
NASA Technical Reports Server (NTRS)
Campbell, James R.; Hlavka, Dennis L.; Spinhirne, James D.; Scott, V. Stanley., III; Turner, David D.
1998-01-01
Micro Pulse Lidar (MPL) was developed at NASA Goddard Space Flight Center (GSFC) as the result of research on space-borne lidar techniques. It was designed to provide continuous, unattended observations of all significant atmospheric cloud and aerosol structure with a rugged, compact system design and the benefit of eye safety (Spinhirne 1993). The significant eye safety feature is achieved by using low pulse energies and high pulse repetition rates compared to standard lidar systems. MPL systems use a diode pumped 10 microj, 2500 Hz doubled Nd:YLF laser. In addition, a solid state Geiger mode avalanche photo diode (GAPD) photon counting detector is used allowing for quantum efficiencies approaching 70%. Other design features have previously been noted by Spinhirne (1995). Though a commercially available instrument, with nearly 20 systems operating around the world, the most extensive MPL work has come from those operated by the Atmospheric Radiation Measurement (ARM) (Stokes and Schwartz 1994) program. The diverse ability of the instrument relating to the measurement of basic cloud macrophysical structure and both cloud and aerosol radiative properties well suits the ARM research philosophy. MPL data can be used to yield many parameters including cloud boundary heights to the limit of signal attenuation, cloud scattering cross sections and optical thicknesses, planetary boundary layer heights and aerosol scattering profiles, including those into the stratosphere in nighttime cases (Hlavka et al 1996). System vertical resolution ranges from 30 m to 300 m (i.e. high and low resolution respectively) depending on system design. The lidar research group at GSFC plays an advisory role in the operation, calibration and maintenance of NASA and ARM owned MPL systems. Over the past three years, processing software and system correction techniques have been developed in anticipation of the increasing population of systems amongst the community. Datasets produced by three ARM-owned systems have served as the basis for this development. With two operating at the southern Great Plains Cloud and Radiation Testbed Site (SGP CART) since December 1993 and another at the Manus Island Atmospheric Radiation and Cloud Station (TWP ARCS) location in the tropical western Pacific since February 1997, the ARM archive contains over 4 years of observations. In addition, high resolution systems planning to come on-line at the North Slope, AK CART shortly with another scheduled to follow at the TWP ARCS-II will diversify this archive with more extensive observations.
The Chandra HRC View of the Subarcsecond Structures in the Nuclear Region of NGC 1068
NASA Astrophysics Data System (ADS)
Wang, Junfeng; Fabbiano, Giuseppina; Karovska, Margarita; Elvis, Martin; Risaliti, Guido
2012-09-01
We have obtained a high spatial resolution X-ray image of the nucleus of NGC 1068 using the High Resolution Camera (HRC-I) on board the Chandra X-ray Observatory, which provides an unprecedented view of the innermost 1 arcsec radius region of this galaxy. The HRC image resolves the narrow-line region into X-ray emission clumps matching bright emission-line clouds in the HST [OIII] λ5007 images and allows comparison with subarcsecond-scale radio jet for the first time. Two distinct X-ray knots are revealed at 1.3-1.4 arcsec northeast and southwest of the nucleus. Based on the combined X-ray, [O III], and radio continuum morphology, we identify the locations of intense radio jet-cloud interaction. The [O III] to soft X-ray ratios show that some of these clouds are strongly affected by shock heating, whereas in other locations the jet simply thrusts through with no signs of strong interaction. This is further strengthened by the presence of a kT ~ 1 keV collisionally ionized component in the ACIS spectrum of a shock-heated cloud HST-G. We estimate that the kinematic luminosity of the jet-driven shocks is 6 × 1038 erg s-1, a negligible fraction (10-4) of the estimated total jet power.
NASA Astrophysics Data System (ADS)
Gong, K.; Fritsch, D.
2018-05-01
Nowadays, multiple-view stereo satellite imagery has become a valuable data source for digital surface model generation and 3D reconstruction. In 2016, a well-organized multiple view stereo publicly benchmark for commercial satellite imagery has been released by the John Hopkins University Applied Physics Laboratory, USA. This benchmark motivates us to explore the method that can generate accurate digital surface models from a large number of high resolution satellite images. In this paper, we propose a pipeline for processing the benchmark data to digital surface models. As a pre-procedure, we filter all the possible image pairs according to the incidence angle and capture date. With the selected image pairs, the relative bias-compensated model is applied for relative orientation. After the epipolar image pairs' generation, dense image matching and triangulation, the 3D point clouds and DSMs are acquired. The DSMs are aligned to a quasi-ground plane by the relative bias-compensated model. We apply the median filter to generate the fused point cloud and DSM. By comparing with the reference LiDAR DSM, the accuracy, the completeness and the robustness are evaluated. The results show, that the point cloud reconstructs the surface with small structures and the fused DSM generated by our pipeline is accurate and robust.
Discrete Angle Radiative Transfer in Uniform and Extremely Variable Clouds.
NASA Astrophysics Data System (ADS)
Gabriel, Philip Mitri
The transfer of radiant energy in highly inhomogeneous media is a difficult problem that is encountered in many geophysical applications. It is the purpose of this thesis to study some problems connected with the scattering of solar radiation in natural clouds. Extreme variability in the optical density of these clouds is often believed to occur regularly. In order to facilitate study of very inhomogeneous optical media such as clouds, the difficult angular part of radiative transfer calculations is simplified by considering a series of models in which conservative scattering only occurs in discrete directions. Analytic and numerical results for the radiative properties of these Discrete Angle Radiative Transfer (DART) systems are obtained in the limits of both optically thin and thick media. Specific results include: (a) In thick homogeneous media, the albedo (reflection coefficient), unlike the transmission, cannot be obtained by a diffusion equation. (b) With the aid of an exact analogy with an early model of conductor/superconductor mixtures, it is argued that inhomogeneous media with embedded holes, neither the transmission, nor the albedo can be described by diffusive random walks. (c) Using renormalization methods, it is shown that thin cloud behaviour is sensitive to the scattering phase functions since it is associated with a repelling fixed point, whereas, the thick cloud limit is universal in that it is phase function independent, and associated with an attracting fixed point. (d) In fractal media, the optical thickness required for a given albedo or transmission can differ by large factors from that required in the corresponding plane parallel geometry. The relevant scaling exponents have been calculated in a very simple example. (e) Important global meteorological and climatological implications of the above are discussed when applied to the scattering of visible light in clouds. In the remote sensing context, an analysis of satellite data reveals that augmenting a satellite's resolution reveals increasingly detailed structures that are found to occupy a decreasing fraction of the image, while simultaneously brightening to compensate. By systematically degrading the resolution of visible and infra red satellite cloud and surface data as well as radar rain data, resolution -independent co-dimension functions were defined which were useful in describing the spatial distribution of image features as well as the resolution dependence of the intensities themselves. The scale invariant functions so obtained fit into theoretically predicted functional forms. These multifractal techniques have implications for our ability to meaningfully estimate cloud brightness fraction, total cloud amount, as well as other remotely sensed quantities.
The Role of Moist Processes in the Intrinsic Predictability of Indian Ocean Cyclones
DOE Office of Scientific and Technical Information (OSTI.GOV)
Taraphdar, Sourav; Mukhopadhyay, P.; Leung, Lai-Yung R.
The role of moist processes and the possibility of error cascade from cloud scale processes affecting the intrinsic predictable time scale of a high resolution convection permitting model within the environment of tropical cyclones (TCs) over the Indian region are investigated. Consistent with past studies of extra-tropical cyclones, it is demonstrated that moist processes play a major role in forecast error growth which may ultimately limit the intrinsic predictability of the TCs. Small errors in the initial conditions may grow rapidly and cascades from smaller scales to the larger scales through strong diabatic heating and nonlinearities associated with moist convection.more » Results from a suite of twin perturbation experiments for four tropical cyclones suggest that the error growth is significantly higher in cloud permitting simulation at 3.3 km resolutions compared to simulations at 3.3 km and 10 km resolution with parameterized convection. Convective parameterizations with prescribed convective time scales typically longer than the model time step allows the effects of microphysical tendencies to average out so convection responds to a smoother dynamical forcing. Without convective parameterizations, the finer-scale instabilities resolved at 3.3 km resolution and stronger vertical motion that results from the cloud microphysical parameterizations removing super-saturation at each model time step can ultimately feed the error growth in convection permitting simulations. This implies that careful considerations and/or improvements in cloud parameterizations are needed if numerical predictions are to be improved through increased model resolution. Rapid upscale error growth from convective scales may ultimately limit the intrinsic mesoscale predictability of the TCs, which further supports the needs for probabilistic forecasts of these events, even at the mesoscales.« less
Study on super-resolution three-dimensional range-gated imaging technology
NASA Astrophysics Data System (ADS)
Guo, Huichao; Sun, Huayan; Wang, Shuai; Fan, Youchen; Li, Yuanmiao
2018-04-01
Range-gated three dimensional imaging technology is a hotspot in recent years, because of the advantages of high spatial resolution, high range accuracy, long range, and simultaneous reflection of target reflectivity information. Based on the study of the principle of intensity-related method, this paper has carried out theoretical analysis and experimental research. The experimental system adopts the high power pulsed semiconductor laser as light source, gated ICCD as the imaging device, can realize the imaging depth and distance flexible adjustment to achieve different work mode. The imaging experiment of small imaging depth is carried out aiming at building 500m away, and 26 group images were obtained with distance step 1.5m. In this paper, the calculation method of 3D point cloud based on triangle method is analyzed, and 15m depth slice of the target 3D point cloud are obtained by using two frame images, the distance precision is better than 0.5m. The influence of signal to noise ratio, illumination uniformity and image brightness on distance accuracy are analyzed. Based on the comparison with the time-slicing method, a method for improving the linearity of point cloud is proposed.
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.
Airborne Spectral Measurements of Ocean Directional Reflectance
NASA Technical Reports Server (NTRS)
Gatebe, Charles K.; King, Michael D.; Lyapustin, Alexei; Arnold, G. Thomas; Redemann, Jens
2004-01-01
During summer of 2001 NASA's Cloud Absorption Radiometer (CAR) obtained measurement of ocean angular distribution of reflected radiation or BRDF (bidirectional reflectance distribution function) aboard the University of Washington Convair CV-580 research aircraft under cloud-free conditions. The measurements took place aver the Atlantic Ocean off the eastern seaboard of the U.S. in the vicinity of the Chesapeake Light Tower and at nearby National Oceanic and Atmospheric Administration (NOAA) Buoy Stations. The measurements were in support of CLAMS, Chesapeake Lighthouse and Aircraft Measurements for Satellites, field campaign that was primarily designed to validate and improve NASA's Earth Observing System (EOS) satellite data products being derived from three sensors: MODIS (MODerate Resolution Imaging Spectro-Radiometer), MISR (Multi-angle Imaging Spectro-Radiometer) and CERES (Clouds and Earth s Radiant Energy System). Because of the high resolution of the CAR measurements and its high sensitivity to detect weak ocean signals against a noisy background, results of radiance field above the ocean are seen in unprecedented detail. The study also attempts to validate the widely used Cox-Munk model for predicting reflectance from a rough ocean surface.
NASA Technical Reports Server (NTRS)
Hostetler, Chris; Hair, Johnathan; Liu, Zhaoyan; Ferrare, Rich; Harper, David; Cook, Anthony; Vaughan, Mark; Trepte, Chip; Winker, David
2006-01-01
This poster focuses on preliminary comparisons of data from the Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) instrument on the Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) spacecraft with data acquired by the NASA Langley Airborne High Spectral Resolution Lidar (HSRL). A series of 20 aircraft validation flights was conducted from 14 June through 27 September 2006, under both day and night lighting conditions and a variety of aerosol and cloud conditions. This poster presents comparisons of CALIOP measurements of attenuated backscatter at 532 and 1064 nm and depolarization at 532 nm with near coincident measurements from the Airborne HSRL as a preliminary assessment of CALIOP calibration accuracy. Note that the CALIOP data presented here are the pre-release version. These data have known artifacts in calibration which have been corrected in the December 8 CALIPSO data release which was not available at the time the comparisons were conducted for this poster. The HSRL data are also preliminary. No artifacts are known to exist; however, refinements in calibration and algorithms are likely to be implemented before validation comparisons are made final.
NASA Technical Reports Server (NTRS)
Hillger, D. W.; Vonder Haar, T. H.
1977-01-01
The ability to provide mesoscale temperature and moisture fields from operational satellite infrared sounding radiances over the United States is explored. High-resolution sounding information for mesoscale analysis and forecasting is shown to be obtainable in mostly clear areas. An iterative retrieval algorithm applied to NOAA-VTPR radiances uses a mean radiosonde sounding as a best initial-guess profile. Temperature soundings are then retrieved at a horizontal resolution of about 70 km, as is an indication of the precipitable water content of the vertical sounding columns. Derived temperature values may be biased in general by the initial-guess sounding or in certain areas by the cloud correction technique, but the resulting relative temperature changes across the field when not contaminated by clouds will be useful for mesoscale forecasting and models. The derived moisture, affected only by high clouds, proves to be reliable to within 0.5 cm of precipitable water and contains valuable horizontal information. Present-day applications from polar-orbiting satellites as well as possibilities from upcoming temperature and moisture sounders on geostationary satellites are noted.
High Spectral Resolution Lidar Measurements of Multiple Scattering
NASA Technical Reports Server (NTRS)
Eloranta, E. W.; Piironen, P.
1996-01-01
The University of Wisconsin High Spectral Resolution Lidar (HSRL) provides unambiguous measurements of backscatter cross section, backscatter phase function, depolarization, and optical depth. This is accomplished by dividing the lidar return into separate particulate and molecular contributions. The molecular return is then used as a calibration target. We have modified the HSRL to use an I2 molecular absorption filter to separate aerosol and molecular signals. This allows measurement in dense clouds. Useful profiles extend above the cloud base until the two way optical depth reaches values between 5 and 6; beyond this, photon counting errors become large. In order to observe multiple scattering, the HSRL includes a channel which records the combined aerosol and molecular lidar return simultaneously with the spectrometer channel measurements of optical properties. This paper describes HSRL multiple scattering measurements from both water and ice clouds. These include signal strengths and depolarizations as a function of receiver field of view. All observations include profiles of extinction and backscatter cross sections. Measurements are also compared to predictions of a multiple scattering model based on small angle approximations.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Zelenyuk, Alla; Imre, D.; Earle, Michael
2010-10-01
Aerosol indirect effect remains the most uncertain aspect of climate change modeling because proper test requires knowledge of individual particles sizes and compositions with high spatial and temporal resolution. We present the first deployment of a single particle mass spectrometer (SPLAT II) that is operated in a dual data acquisition mode to measure all the required individual particle properties with sufficient temporal resolution to definitively resolve the aerosol-cloud interaction in this exemplary case. We measured particle number concentrations, asphericity, and individual particle size, composition, and density with better than 60 seconds resolution. SPLAT II measured particle number concentrations between 70more » particles cm-3and 300 particles cm-3, an average particle density of 1.4 g cm-3. Found that most particles are composed of oxygenated organics, many of which are mixed with sulfates. Biomass burn particles some with sulfates were prevalent, particularly at higher altitudes, and processed sea-salt was observed over the ocean. Analysis of cloud residuals shows that with time cloud droplets acquire sulfate by the reaction of peroxide with SO2. Based on the particle mass spectra and densities we find that the compositions of cloud condensation nuclei are similar to those of background aerosol but, contain on average ~7% more sulfate, and do not include dust and metallic particles. A comparison between the size distributions of background, activated, and interstitial particles shows that while nearly none of the activated particles is smaller than 115 nm, more than 80% of interstitial particles are smaller than 115 nm. We conclude that for this cloud the most important difference between CCN and background aerosol is particle size although having more sulfate also helps.« less
NASA Astrophysics Data System (ADS)
Fauchez, T.; Platnick, S. E.; Meyer, K.; Zhang, Z.; Cornet, C.; Szczap, F.; Dubuisson, P.
2015-12-01
Cirrus clouds are an important part of the Earth radiation budget but an accurate assessment of their role remains highly uncertain. Cirrus optical properties such as Cloud Optical Thickness (COT) and ice crystal effective particle size are often retrieved with a combination of Visible/Near InfraRed (VNIR) and ShortWave-InfraRed (SWIR) reflectance channels. Alternatively, Thermal InfraRed (TIR) techniques, such as the Split Window Technique (SWT), have demonstrated better accuracy for thin cirrus effective radius retrievals with small effective radii. However, current global operational algorithms for both retrieval methods assume that cloudy pixels are horizontally homogeneous (Plane Parallel Approximation (PPA)) and independent (Independent Pixel Approximation (IPA)). The impact of these approximations on ice cloud retrievals needs to be understood and, as far as possible, corrected. Horizontal heterogeneity effects in the TIR spectrum are mainly dominated by the PPA bias that primarily depends on the COT subpixel heterogeneity; for solar reflectance channels, in addition to the PPA bias, the IPA can lead to significant retrieval errors due to a significant photon horizontal transport between cloudy columns, as well as brightening and shadowing effects that are more difficult to quantify. Furthermore TIR retrievals techniques have demonstrated better retrieval accuracy for thin cirrus having small effective radii over solar reflectance techniques. The TIR range is thus particularly relevant in order to characterize, as accurately as possible, thin cirrus clouds. Heterogeneity effects in the TIR are evaluated as a function of spatial resolution in order to estimate the optimal spatial resolution for TIR retrieval applications. These investigations are performed using a cirrus 3D cloud generator (3DCloud), a 3D radiative transfer code (3DMCPOL), and two retrieval algorithms, namely the operational MODIS retrieval algorithm (MOD06) and a research-level SWT algorithm.
NASA Astrophysics Data System (ADS)
Ohama, Akio; Kohno, Mikito; Fujita, Shinji; Tsutsumi, Daichi; Hattori, Yusuke; Torii, Kazufumi; Nishimura, Atsushi; Sano, Hidetoshi; Yamamoto, Hiroaki; Tachihara, Kengo; Fukui, Yasuo
2018-05-01
Young H II regions are an important site for the study of O star formation based on distributions of ionized and molecular gas. We reveal that two molecular clouds at ˜48 km s-1 and ˜53 km s-1 are associated with the H II regions G018.149-00.283 in RCW 166 by using the JCMT CO High-Resolution Survey (COHRS) of the 12CO(J = 3-2) emission. G018.149-00.283 comprises a bright ring at 8 μm and an extended H II region inside the ring. The ˜48 km s-1 cloud delineates the ring, and the ˜53 km s-1 cloud is located within the ring, indicating a complementary distribution between the two molecular components. We propose a hypothesis that high-mass stars within G018.149-00.283 were formed by triggering during cloud-cloud collision at a projected velocity separation of ˜5 km s-1. We argue that G018.149-00.283 is in an early evolutionary stage, ˜0.1 Myr after the collision according to the scheme detailed by Habe and Ohta (1992, PASJ, 44, 203), which will be followed by a bubble formation stage like RCW 120. We also suggest that nearby H II regions N21 and N22 are candidates for bubbles possibly formed by cloud-cloud collision. Inoue and Fukui (2013, ApJ, 774, L31) showed that the interface gas becomes highly turbulent and realizes a high-mass accretion rate of 10-3-10-4 M⊙ yr-1 by magnetohydrodynamical numerical simulations, which offers an explanation of the O-star formation. The fairly high frequency of cloud-cloud collision in RCW 166 is probably due to the high cloud density in this part of the Scutum arm.
NASA Astrophysics Data System (ADS)
Li, Weijun; Li, Peiren; Sun, Guode; Zhou, Shengzhen; Yuan, Qi; Wang, Wenxing
2011-05-01
Most studies of aerosol-cloud interactions have been conducted in remote locations; few have investigated the characterization of cloud condensation nuclei (CCN) over highly polluted urban and industrial areas. The present work, based on samples collected at Mt. Tai, a site in northern China affected by nearby urban and industrial air pollutant emissions, illuminates CCN properties in a polluted atmosphere. High-resolution transmission electron microscopy (TEM) was used to obtain the size, composition, and mixing state of individual cloud residues and interstitial aerosols. Most of the cloud residues displayed distinct rims which were found to consist of soluble organic matter (OM). Nearly all (91.7%) cloud residues were attributed to sulfate-related salts (the remainder was mostly coarse crustal dust particles with nitrate coatings). Half the salt particles were internally mixed with two or more refractory particles (e.g., soot, fly ash, crustal dust, CaSO 4, and OM). A comparison between cloud residues and interstitial particles shows that the former contained more salts and were of larger particle size than the latter. In addition, a somewhat high number scavenging ratio of 0.54 was observed during cloud formation. Therefore, the mixtures of salts with OMs account for most of the cloud-nucleating ability of the entire aerosol population in the polluted air of northern China. We advocate that both size and composition - the two influential, controlling factors for aerosol activation - should be built into all regional climate models of China.
NASA Technical Reports Server (NTRS)
Zhou, Daniel K.; Liu, Xu; Larar, Allen M.; Smith, William L.; Taylor, Jonathan P.; Schluessel, L. Peter; Strow, Larrybee; Mango, Stephen A.
2008-01-01
The Infrared Atmospheric Sounding Interferometer (IASI) on the MetOp satellite was launched on October 19, 2006. The Joint Airborne IASI Validation Experiment (JAIVEx) was conducted during April 2007 mainly for validation of the IASI on the MetOp satellite. IASI possesses an ultra-spectral resolution of 0.25 cm(exp -1) and a spectral coverage from 645 to 2760 cm(exp -1). Ultra-spectral resolution infrared spectral radiance obtained from near nadir observations provide atmospheric, surface, and cloud property information. An advanced retrieval algorithm with a fast radiative transfer model, including cloud effects, is used for atmospheric profile and cloud parameter retrieval. Preliminary retrievals of atmospheric soundings, surface properties, and cloud optical/microphysical properties with the IASI observations are obtained and presented. These retrievals are further inter-compared with those obtained from airborne FTS system, such as the NPOESS Airborne Sounder Testbed - Interferometer (NAST-I), dedicated dropsondes, radiosondes, and ground based Raman Lidar. The capabilities of satellite ultra-spectral sounder such as the IASI are investigated to benefit future NPOESS operation.
Cirrus Cloud Optical and Morphological Variations within a Mesoscale Volume
NASA Technical Reports Server (NTRS)
Wolf, Walter W.
1996-01-01
Cirrus cloud optical and structural properties were measured above southern Wisconsin in two time segments between 18:07 and 21:20 GMT on December 1, 1989 by the volume imaging lidar (VIL) and the High Spectral Resolution Lidar (HSRL) and the visible infrared spin scan radiometer (VISSR) atmospheric sounder (VAS) on GOES. A new technique was used to calculate the cirrus cloud visible aerosol backscatter cross sections for a single channel elastic backscatter lidar. Cirrus clouds were viewed simultaneously by the VIL and the HSRL. This allowed the HSRL aerosol backscatter cross sections to be directly compared to the VIL single channel backscattered signal. This first attempt resulted in an adequate calibration. The calibration was extended to all the cirrus clouds in the mesoscale volume imaged by the VIL.
Assessment of different models for computing the probability of a clear line of sight
NASA Astrophysics Data System (ADS)
Bojin, Sorin; Paulescu, Marius; Badescu, Viorel
2017-12-01
This paper is focused on modeling the morphological properties of the cloud fields in terms of the probability of a clear line of sight (PCLOS). PCLOS is defined as the probability that a line of sight between observer and a given point of the celestial vault goes freely without intersecting a cloud. A variety of PCLOS models assuming the cloud shape hemisphere, semi-ellipsoid and ellipsoid are tested. The effective parameters (cloud aspect ratio and absolute cloud fraction) are extracted from high-resolution series of sunshine number measurements. The performance of the PCLOS models is evaluated from the perspective of their ability in retrieving the point cloudiness. The advantages and disadvantages of the tested models are discussed, aiming to a simplified parameterization of PCLOS models.
Compact high-power shipborne doppler lidar based on high spectral resolution techniques
NASA Astrophysics Data System (ADS)
Wu, Songhua; Liu, Bingyi; Dai, Guangyao; Qin, Shenguang; Liu, Jintao; Zhang, Kailin; Feng, Changzhong; Zhai, Xiaochun; Song, Xiaoquan
2018-04-01
The Compact High-Power Shipborne Doppler Wind Lidar (CHiPSDWiL) based on highspectral-resolution technique has been built up at the Ocean University of China for the measurement of the wind field and the properties of the aerosol and clouds in the troposphere. The design of the CHiPSDWiL including the transceiver, the injection seeding, the locking and the frequency measurement will be presented. Preliminary results measured by the CHiPSDWiL are provided.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Abramson, Anne; Kenney, Jeffrey D. P., E-mail: anne.abramson@yale.edu, E-mail: jeff.kenney@yale.edu
We present the highest-resolution study to date of the interstellar medium (ISM) in galaxies undergoing ram pressure stripping, using Hubble Space Telescope BVI imaging of NGC 4522 and NGC 4402, Virgo Cluster spirals that are well known to be experiencing intracluster medium (ICM) ram pressure. We find that throughout most of both galaxies, the main dust lane has a fairly well-defined edge, with a population of giant molecular cloud (GMC) sized (tens- to hundreds-of-pc scale), isolated, highly extincting dust clouds located up to ∼1.5 kpc radially beyond it. Outside of these dense clouds, the area has little or no diffusemore » dust extinction, indicating that the clouds have decoupled from the lower-density ISM material that has already been stripped. Several of the dust clouds have elongated morphologies that indicate active ram pressure, including two large (kpc scale) filaments in NGC 4402 that are elongated in the projected ICM wind direction. We calculate a lower limit on the H I + H{sub 2} masses of these clouds based on their dust extinctions and find that a correction factor of ∼10 gives cloud masses consistent with those measured in CO for clouds of similar diameters, probably due to the complicating factors of foreground light, cloud substructure, and resolution limitations. Assuming that the clouds' actual masses are consistent with those of GMCs of similar diameters (∼10{sup 4}-10{sup 5} M {sub ☉}), we estimate that only a small fraction (∼1%-10%) of the original H I + H{sub 2} remains in the parts of the disks with decoupled clouds. Based on Hα images, a similar fraction of star formation persists in these regions, 2%-3% of the estimated pre-stripping star formation rate. We find that the decoupled cloud lifetimes may be up to 150-200 Myr.« less
NASA Technical Reports Server (NTRS)
Key, J.
1990-01-01
The spectral and textural characteristics of polar clouds and surfaces for a 7-day summer series of AVHRR data in two Arctic locations are examined, and the results used in the development of a cloud classification procedure for polar satellite data. Since spatial coherence and texture sensitivity tests indicate that a joint spectral-textural analysis based on the same cell size is inappropriate, cloud detection with AVHRR data and surface identification with passive microwave data are first done on the pixel level as described by Key and Barry (1989). Next, cloud patterns within 250-sq-km regions are described, then the spectral and local textural characteristics of cloud patterns in the image are determined and each cloud pixel is classified by statistical methods. Results indicate that both spectral and textural features can be utilized in the classification of cloudy pixels, although spectral features are most useful for the discrimination between cloud classes.
Can High-resolution WRF Simulations Be Used for Short-term Forecasting of Lightning?
NASA Technical Reports Server (NTRS)
Goodman, S. J.; Lapenta, W.; McCaul, E. W., Jr.; LaCasse, K.; Petersen, W.
2006-01-01
A number of research teams have begun to make quasi-operational forecast simulations at high resolution with models such as the Weather Research and Forecast (WRF) model. These model runs have used horizontal meshes of 2-4 km grid spacing, and thus resolved convective storms explicitly. In the light of recent global satellite-based observational studies that reveal robust relationships between total lightning flash rates and integrated amounts of precipitation-size ice hydrometeors in storms, it is natural to inquire about the capabilities of these convection-resolving models in representing the ice hydrometeor fields faithfully. If they do, this might make operational short-term forecasts of lightning activity feasible. We examine high-resolution WRF simulations from several Southeastern cases for which either NLDN or LMA lightning data were available. All the WRF runs use a standard microphysics package that depicts only three ice species, cloud ice, snow and graupel. The realism of the WRF simulations is examined by comparisons with both lightning and radar observations and with additional even higher-resolution cloud-resolving model runs. Preliminary findings are encouraging in that they suggest that WRF often makes convective storms of the proper size in approximately the right location, but they also indicate that higher resolution and better hydrometeor microphysics would be helpful in improving the realism of the updraft strengths, reflectivity and ice hydrometeor fields.
NASA Astrophysics Data System (ADS)
Iwabuchi, Hironobu; Saito, Masanori; Tokoro, Yuka; Putri, Nurfiena Sagita; Sekiguchi, Miho
2016-12-01
Satellite remote sensing of the macroscopic, microphysical, and optical properties of clouds are useful for studying spatial and temporal variations of clouds at various scales and constraining cloud physical processes in climate and weather prediction models. Instead of using separate independent algorithms for different cloud properties, a unified, optimal estimation-based cloud retrieval algorithm is developed and applied to moderate resolution imaging spectroradiometer (MODIS) observations using ten thermal infrared bands. The model considers sensor configurations, background surface and atmospheric profile, and microphysical and optical models of ice and liquid cloud particles and radiative transfer in a plane-parallel, multilayered atmosphere. Measurement and model errors are thoroughly quantified from direct comparisons of clear-sky observations over the ocean with model calculations. Performance tests by retrieval simulations show that ice cloud properties are retrieved with high accuracy when cloud optical thickness (COT) is between 0.1 and 10. Cloud-top pressure is inferred with uncertainty lower than 10 % when COT is larger than 0.3. Applying the method to a tropical cloud system and comparing the results with the MODIS Collection 6 cloud product shows good agreement for ice cloud optical thickness when COT is less than about 5. Cloud-top height agrees well with estimates obtained by the CO2 slicing method used in the MODIS product. The present algorithm can detect optically thin parts at the edges of high clouds well in comparison with the MODIS product, in which these parts are recognized as low clouds by the infrared window method. The cloud thermodynamic phase in the present algorithm is constrained by cloud-top temperature, which tends not to produce results with an ice cloud that is too warm and liquid cloud that is too cold.
Cloud Physics Lidar: Instrument Description and Initial Measurement Results
NASA Technical Reports Server (NTRS)
McGill, Matthew; Hlavka, Dennis; Hart, William; Scott, V. Stanley; Spinhirne, James; Schmid, Beat
2002-01-01
The Cloud Physics Lidar (CPL) is a new custom-built instrument for the NASA ER-2 high-altitude aircraft. The CPL can provide multiwavelength measurements of cirrus, subvisual cirrus, and aerosols with high temporal and spatial resolution. Its state-of-the-art technology gives it a high repetition rate, and photon-counting detection, and includes a low-pulse-energy laser. The CPL was first deployed at the Southern African Regional Science Initiative's 2000 field campaign during August and September 2000. This paper provides an overview of the instrument and initial data results to illustrate the measurement capability of the CPL.
The Cloud Physics Lidar: Instrument Description and Initial Measurement Results
NASA Technical Reports Server (NTRS)
McGill, Matthew; Hlavka, Dennis; Hart, William; Spinhirne, James; Scott, V. Stanley; Starr, David OC. (Technical Monitor)
2001-01-01
The new Cloud Physics Lidar (CPL) has been built for use on the NASA ER-2 high altitude aircraft. The purpose of the CPL is to provide multi-wavelength measurements of cirrus, subvisual cirrus, and aerosols with high temporal and spatial resolution. The CPL utilizes state-of-the-art technology with a high repetition rate, a low pulse energy laser, and photon-counting detection. The first deployment for the CPL was the SAFARI-2000 field campaign during August-September 2000. We provide here an overview of the instrument and initial data results to illustrate the measurement capability of the CPL.
Simulation of Deep Convective Clouds with the Dynamic Reconstruction Turbulence Closure
NASA Astrophysics Data System (ADS)
Shi, X.; Chow, F. K.; Street, R. L.; Bryan, G. H.
2017-12-01
The terra incognita (TI), or gray zone, in simulations is a range of grid spacing comparable to the most energetic eddy diameter. Spacing in mesoscale and simulations is much larger than the eddies, and turbulence is parameterized with one-dimensional vertical-mixing. Large eddy simulations (LES) have grid spacing much smaller than the energetic eddies, and use three-dimensional models of turbulence. Studies of convective weather use convection-permitting resolutions, which are in the TI. Neither mesoscale-turbulence nor LES models are designed for the TI, so TI turbulence parameterization needs to be discussed. Here, the effects of sub-filter scale (SFS) closure schemes on the simulation of deep tropical convection are evaluated by comparing three closures, i.e. Smagorinsky model, Deardorff-type TKE model and the dynamic reconstruction model (DRM), which partitions SFS turbulence into resolvable sub-filter scales (RSFS) and unresolved sub-grid scales (SGS). The RSFS are reconstructed, and the SGS are modeled with a dynamic eddy viscosity/diffusivity model. The RSFS stresses/fluxes allow backscatter of energy/variance via counter-gradient stresses/fluxes. In high-resolution (100m) simulations of tropical convection use of these turbulence models did not lead to significant differences in cloud water/ice distribution, precipitation flux, or vertical fluxes of momentum and heat. When model resolutions are coarsened, the Smagorinsky and TKE models overestimate cloud ice and produces large-amplitude downward heat flux in the middle troposphere (not found in the high-resolution simulations). This error is a result of unrealistically large eddy diffusivities, i.e., the eddy diffusivity of the DRM is on the order of 1 for the coarse resolution simulations, the eddy diffusivity of the Smagorinsky and TKE model is on the order of 100. Splitting the eddy viscosity/diffusivity scalars into vertical and horizontal components by using different length scales and strain rate components helps to reduce the errors, but does not completely remedy the problem. In contrast, the coarse resolution simulations using the DRM produce results that are more consistent with the high-resolution results, suggesting that the DRM is a more appropriate turbulence model for simulating convection in the TI.
The One to Multiple Automatic High Accuracy Registration of Terrestrial LIDAR and Optical Images
NASA Astrophysics Data System (ADS)
Wang, Y.; Hu, C.; Xia, G.; Xue, H.
2018-04-01
The registration of ground laser point cloud and close-range image is the key content of high-precision 3D reconstruction of cultural relic object. In view of the requirement of high texture resolution in the field of cultural relic at present, The registration of point cloud and image data in object reconstruction will result in the problem of point cloud to multiple images. In the current commercial software, the two pairs of registration of the two kinds of data are realized by manually dividing point cloud data, manual matching point cloud and image data, manually selecting a two - dimensional point of the same name of the image and the point cloud, and the process not only greatly reduces the working efficiency, but also affects the precision of the registration of the two, and causes the problem of the color point cloud texture joint. In order to solve the above problems, this paper takes the whole object image as the intermediate data, and uses the matching technology to realize the automatic one-to-one correspondence between the point cloud and multiple images. The matching of point cloud center projection reflection intensity image and optical image is applied to realize the automatic matching of the same name feature points, and the Rodrigo matrix spatial similarity transformation model and weight selection iteration are used to realize the automatic registration of the two kinds of data with high accuracy. This method is expected to serve for the high precision and high efficiency automatic 3D reconstruction of cultural relic objects, which has certain scientific research value and practical significance.
New insights about cloud vertical structure from CloudSat and CALIPSO observations
NASA Astrophysics Data System (ADS)
Oreopoulos, Lazaros; Cho, Nayeong; Lee, Dongmin
2017-09-01
Active cloud observations from A-Train's CloudSat and CALIPSO satellites offer new opportunities to examine the vertical structure of hydrometeor layers. We use the 2B-CLDCLASS-LIDAR merged CloudSat-CALIPSO product to examine global aspects of hydrometeor vertical stratification. We group the data into major cloud vertical structure (CVS) classes based on our interpretation of how clouds in three standard atmospheric layers overlap and provide their global frequency of occurrence. The two most frequent CVS classes are single-layer (per our definition) low and high clouds that represent 53% of cloudy skies, followed by high clouds overlying low clouds, and vertically extensive clouds that occupy near-contiguously a large portion of the troposphere. The prevalence of these configurations changes seasonally and geographically, between daytime and nighttime, and between continents and oceans. The radiative effects of the CVS classes reveal the major radiative warmers and coolers from the perspective of the planet as a whole, the surface, and the atmosphere. Single-layer low clouds dominate planetary and atmospheric cooling and thermal infrared surface warming. We also investigate the consistency between passive and active views of clouds by providing the CVS breakdowns of Moderate Resolution Imaging Spectroradiometer cloud regimes for spatiotemporally coincident MODIS-Aqua (also on the A-Train) and CloudSat-CALIPSO daytime observations. When the analysis is expanded for a more in-depth look at the most heterogeneous of the MODIS cloud regimes, it ultimately confirms previous interpretations of their makeup that did not have the benefit of collocated active observations.
NASA Astrophysics Data System (ADS)
Kim, Hye-Won; Yeom, Jong-Min; Shin, Daegeun; Choi, Sungwon; Han, Kyung-Soo; Roujean, Jean-Louis
2017-08-01
In this study, a new assessment of thin cloud detection with the application of bidirectional reflectance distribution function (BRDF) model-based background surface reflectance was undertaken by interpreting surface spectra characterized using the Geostationary Ocean Color Imager (GOCI) over a land surface area. Unlike cloud detection over the ocean, the detection of cloud over land surfaces is difficult due to the complicated surface scattering characteristics, which vary among land surface types. Furthermore, in the case of thin clouds, in which the surface and cloud radiation are mixed, it is difficult to detect the clouds in both land and atmospheric fields. Therefore, to interpret background surface reflectance, especially underneath cloud, the semiempirical BRDF model was used to simulate surface reflectance by reflecting solar angle-dependent geostationary sensor geometry. For quantitative validation, Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO) data were used to make a comparison with the proposed cloud masking result. As a result, the new cloud masking scheme resulted in a high probability of detection (POD = 0.82) compared with the Moderate Resolution Imaging Spectroradiometer (MODIS) (POD = 0.808) for all cloud cases. In particular, the agreement between the CALIPSO cloud product and new GOCI cloud mask was over 94% when detecting thin cloud (e.g., altostratus and cirrus) from January 2014 to June 2015. This result is relatively high in comparison with the result from the MODIS Collection 6 cloud mask product (MYD35).
NASA Astrophysics Data System (ADS)
Siebert, H.; Shaw, R. A.; Ditas, J.; Schmeissner, T.; Malinowski, S. P.; Bodenschatz, E.; Xu, H.
2015-01-01
Mountain research stations are advantageous not only for long-term sampling of cloud properties, but also for measurements that prohibitively difficult to perform on airborne platforms due to the true air speed or adverse factors such as weight and complexity of the equipment necessary. Some cloud-turbulence measurements, especially Lagrangian in nature, fall into this category. We report results from simultaneous, high-resolution and collocated measurements of cloud microphysical and turbulence properties during several warm cloud events at the Umweltforschungsstation Schneefernerhaus (UFS) on Zugspitze in the German Alps. The data gathered was found to be representative of observations made with similar instrumentation in free clouds. The turbulence observed, shared all features known for high Reynolds number flows: it exhibited approximately Gaussian fluctuations for all three velocity components, a clearly defined inertial subrange following Kolmogorov scaling (power spectrum, and second and third order Eulerian structure functions), and highly intermittent velocity gradients, as well as approximately lognormal kinetic energy dissipation rates. The clouds were observed to have liquid water contents of order 1 g m-3, and size distributions typical of continental clouds, sometimes exhibiting long positive tails indicative of large drop production through turbulent mixing or coalescence growth. Dimensionless parameters relevant to cloud-turbulence interactions, the Stokes number and settling parameter, are in the range typically observed in atmospheric clouds. Observed fluctuations in droplet number concentration and diameter suggest a preference for inhomogeneous mixing. Finally, enhanced variance in liquid water content fluctuations is observed at high frequencies, and the scale break occurs at a value consistent with the independently estimated phase relaxation time from microphysical measurements.
NASA Astrophysics Data System (ADS)
Choudhury, Devanil; Das, Someshwar
2017-06-01
The Advanced Research WRF (ARW) model is used to simulate Very Severe Cyclonic Storms (VSCS) Hudhud (7-13 October, 2014), Phailin (8-14 October, 2013) and Lehar (24-29 November, 2013) to investigate the sensitivity to microphysical schemes on the skill of forecasting track and intensity of the tropical cyclones for high-resolution (9 and 3 km) 120-hr model integration. For cloud resolving grid scale (<5 km) cloud microphysics plays an important role. The performance of the Goddard, Thompson, LIN and NSSL schemes are evaluated and compared with observations and a CONTROL forecast. This study is aimed to investigate the sensitivity to microphysics on the track and intensity with explicitly resolved convection scheme. It shows that the Goddard one-moment bulk liquid-ice microphysical scheme provided the highest skill on the track whereas for intensity both Thompson and Goddard microphysical schemes perform better. The Thompson scheme indicates the highest skill in intensity at 48, 96 and 120 hr, whereas at 24 and 72 hr, the Goddard scheme provides the highest skill in intensity. It is known that higher resolution domain produces better intensity and structure of the cyclones and it is desirable to resolve the convection with sufficiently high resolution and with the use of explicit cloud physics. This study suggests that the Goddard cumulus ensemble microphysical scheme is suitable for high resolution ARW simulation for TC's track and intensity over the BoB. Although the present study is based on only three cyclones, it could be useful for planning real-time predictions using ARW modelling system.
NASA Astrophysics Data System (ADS)
Camarero, R.; Thiebaut, C.; Dejean, Ph.; Speciel, A.
2010-08-01
Future CNES high resolution instruments for remote sensing missions will lead to higher data-rates because of the increase in resolution and dynamic range. For example, the ground resolution improvement has induced a data-rate multiplied by 8 from SPOT4 to SPOT5 [1] and by 28 to PLEIADES-HR [2]. Innovative "smart" compression techniques will be then required, performing different types of compression inside a scene, in order to reach higher global compression ratios while complying with image quality requirements. This socalled "selective compression", allows important compression gains by detecting and then differently compressing the regions-of-interest (ROI) and non-interest in the image (e.g. higher compression ratios are assigned to the non-interesting data). Given that most of CNES high resolution images are cloudy [1], significant mass-memory and transmission gain could be reached by just detecting and suppressing (or compressing significantly) the areas covered by clouds. Since 2007, CNES works on a cloud detection module [3] as a simplification for on-board implementation of an already existing module used on-ground for PLEIADES-HR album images [4]. The different steps of this Support Vector Machine classifier have already been analyzed, for simplification and optimization, during this on-board implementation study: reflectance computation, characteristics vector computation (based on multispectral criteria) and computation of the SVM output. In order to speed up the hardware design phase, a new approach based on HLS [5] tools is being tested for the VHDL description stage. The aim is to obtain a bit-true VDHL design directly from a high level description language as C or Matlab/Simulink [6].
Physical properties and evolution of GMCs in the Galaxy and the Magellanic Clouds
NASA Astrophysics Data System (ADS)
Onishi, Toshikazu
2015-08-01
Most stars are born as clusters in Giant Molecular Clouds (hereafter GMCs), and therefore the understanding of the evolution of GMCs in a galaxy is one of the key issues to investigate the evolution of the galaxy. The recent state-of-the-art radio telescopes have been enabling us to reveal the distribution of GMCs extensively in the Galaxy as well as in the nearby galaxies, and the physical properties and the evolution of the GMCs leading to cluster formations are actively being investigated. Here we present a review of studies of spatially resolved GMCs in the Galaxy and in the Large Magellanic Cloud (LMC), aiming at providing a template of GMC properties. For the Galactic GMCs, we will focus on the recent extensive survey of GMCs along the Galactic plane; the recent studies suggest cloud-cloud collision as mechanism of massive star formation. For the extra galactic GMCs, we will present recent high-resolution observations of GMCs in the LMC.The LMC is among the nearest star-forming galaxy (distance ~ 50kpc) and is almost face-on. From these aspects, it is becoming the most popular region for studying interstellar medium over an entire galaxy. For molecular gas, the NANTEN covered the entire LMC with a spatial resolution of 40 pc, revealing 272 molecular clouds whose mass ranges from ~104 to ~107 M⊙, which is the first uniform sample of GMCs in a single galaxy. Our Spitzer SAGE and Herschel HERITAGE surveys show that the interstellar medium has much smaller scale structures; full of filamentary and shell-like structures. In order to resolve the filamentary distributions and pre-stellar cores we definitely need to resolve clouds at sub-pc resolutions with ALMA and to cover regions of active cluster formation which are to be selected based on the Spitzer and Hershel data. Our ALMA targets in Cycle 1 and Cycle 2 include N159, which is the most intense and concentrated molecular cloud as shown by the brightest CO J=3-2 source in the LMC, and GMCs with different evolutionary stages. We present the maps of pre-stellar cores and linking filaments at sub-pc resolution and discuss the formation process of massive clusters.
Applications and Improvement of a Coupled, Global and Cloud-Resolving Modeling System
NASA Technical Reports Server (NTRS)
Tao, W.-K.; Chern, J.; Atlas, R.
2005-01-01
Recently Grabowski (2001) and Khairoutdinov and Randall (2001) have proposed the use of 2D CFWs as a "super parameterization" [or multi-scale modeling framework (MMF)] to represent cloud processes within atmospheric general circulation models (GCMs). In the MMF, a fine-resolution 2D CRM takes the place of the single-column parameterization used in conventional GCMs. A prototype Goddard MMF based on the 2D Goddard Cumulus Ensemble (GCE) model and the Goddard finite volume general circulation model (fvGCM) is now being developed. The prototype includes the fvGCM run at 2.50 x 20 horizontal resolution with 32 vertical layers from the surface to 1 mb and the 2D (x-z) GCE using 64 horizontal and 32 vertical grid points with 4 km horizontal resolution and a cyclic lateral boundary. The time step for the 2D GCE would be 15 seconds, and the fvGCM-GCE coupling frequency would be 30 minutes (i.e. the fvGCM physical time step). We have successfully developed an fvGCM-GCE coupler for this prototype. Because the vertical coordinate of the fvGCM (a terrain-following floating Lagrangian coordinate) is different from that of the GCE (a z coordinate), vertical interpolations between the two coordinates are needed in the coupler. In interpolating fields from the GCE to fvGCM, we use an existing fvGCM finite- volume piecewise parabolic mapping (PPM) algorithm, which conserves the mass, momentum, and total energy. A new finite-volume PPM algorithm, which conserves the mass, momentum and moist static energy in the z coordinate, is being developed for interpolating fields from the fvGCM to the GCE. In the meeting, we will discuss the major differences between the two MMFs (i.e., the CSU MMF and the Goddard MMF). We will also present performance and critical issues related to the MMFs. In addition, we will present multi-dimensional cloud datasets (i.e., a cloud data library) generated by the Goddard MMF that will be provided to the global modeling community to help improve the representation and performance of moist processes in climate models and to improve our understanding of cloud processes globally (the software tools needed to produce cloud statistics and to identify various types of clouds and cloud systems from both high-resolution satellite and model data will be also presented).
NASA Technical Reports Server (NTRS)
Steffen, Konrad; Key, J.; Maslanik, J.; Schweiger, A.
1993-01-01
This is the third annual report on: Sea Ice-Atmosphere Interaction - Application of Multispectral Satellite Data in Polar Surface Energy Flux Estimates. The main emphasis during the past year was on: radiative flux estimates from satellite data; intercomparison of satellite and ground-based cloud amounts; radiative cloud forcing; calibration of the Advanced Very High Resolution Radiometer (AVHRR) visible channels and comparison of two satellite derived albedo data sets; and on flux modeling for leads. Major topics covered are arctic clouds and radiation; snow and ice albedo, and leads and modeling.
Offner, Stella S. R.; Klein, Richard I.; McKee, Christopher F.
2008-10-20
Molecular clouds are observed to be turbulent, but the origin of this turbulence is not well understood. As a result, there are two different approaches to simulating molecular clouds, one in which the turbulence is allowed to decay after it is initialized, and one in which it is driven. We use the adaptive mesh refinement (AMR) code, Orion, to perform high-resolution simulations of molecular cloud cores and protostars in environments with both driven and decaying turbulence. We include self-gravity, use a barotropic equation of state, and represent regions exceeding the maximum grid resolution with sink particles. We analyze the propertiesmore » of bound cores such as size, shape, line width, and rotational energy, and we find reasonable agreement with observation. At high resolution the different rates of core accretion in the two cases have a significant effect on protostellar system development. Clumps forming in a decaying turbulence environment produce high-multiplicity protostellar systems with Toomre Q unstable disks that exhibit characteristics of the competitive accretion model for star formation. In contrast, cores forming in the context of continuously driven turbulence and virial equilibrium form smaller protostellar systems with fewer low-mass members. Furthermore, our simulations of driven and decaying turbulence show some statistically significant differences, particularly in the production of brown dwarfs and core rotation, but the uncertainties are large enough that we are not able to conclude whether observations favor one or the other.« less
SAGE III L2 Monthly Cloud Presence Data (Binary)
Atmospheric Science Data Center
2016-06-14
... degrees South Spatial Resolution: 1 km vertical Temporal Coverage: 02/27/2002 - 12/31/2005 ... Parameters: Cloud Amount/Frequency Cloud Height Cloud Vertical Distribution Order Data: Search and ...
NASA Astrophysics Data System (ADS)
Alidoost, F.; Arefi, H.
2017-11-01
Nowadays, Unmanned Aerial System (UAS)-based photogrammetry offers an affordable, fast and effective approach to real-time acquisition of high resolution geospatial information and automatic 3D modelling of objects for numerous applications such as topography mapping, 3D city modelling, orthophoto generation, and cultural heritages preservation. In this paper, the capability of four different state-of-the-art software packages as 3DSurvey, Agisoft Photoscan, Pix4Dmapper Pro and SURE is examined to generate high density point cloud as well as a Digital Surface Model (DSM) over a historical site. The main steps of this study are including: image acquisition, point cloud generation, and accuracy assessment. The overlapping images are first captured using a quadcopter and next are processed by different software to generate point clouds and DSMs. In order to evaluate the accuracy and quality of point clouds and DSMs, both visual and geometric assessments are carry out and the comparison results are reported.
Environmental dependence of star formation induced by cloud collisions in a barred galaxy
NASA Astrophysics Data System (ADS)
Fujimoto, Yusuke; Tasker, Elizabeth J.; Habe, Asao
2014-11-01
Cloud collision has been proposed as a way to link the small-scale star formation process with the observed global relation between the surface star formation rate and gas surface density. We suggest that this model can be improved further by allowing the productivity of such collisions to depend on the relative velocity of the two clouds. Our adjustment implements a simple step function that results in the most successful collisions being at the observed velocities for triggered star formation. By applying this to a high-resolution simulation of a barred galaxy, we successfully reproduce the observational result that the star formation efficiency (SFE) in the bar is lower than that in the spiral arms. This is not possible when we use an efficiency dependent on the internal turbulence properties of the clouds. Our results suggest that high-velocity collisions driven by the gravitational pull of the clouds are responsible for the low bar SFE.
GIANT MOLECULAR CLOUDS AND STAR FORMATION IN THE NON-GRAND DESIGN SPIRAL GALAXY NGC 6946
DOE Office of Scientific and Technical Information (OSTI.GOV)
Rebolledo, David; Wong, Tony; Leroy, Adam
We present high spatial resolution observations of giant molecular clouds (GMCs) in the eastern part of the nearby spiral galaxy NGC 6946 obtained with the Combined Array for Research in Millimeter-wave Astronomy (CARMA). We have observed CO(1 {yields} 0), CO(2 {yields} 1) and {sup 13}CO(1 {yields} 0), achieving spatial resolutions of 5.''4 Multiplication-Sign 5.''0, 2.''5 Multiplication-Sign 2.''0, and 5.''6 Multiplication-Sign 5.''4, respectively, over a region of 6 Multiplication-Sign 6 kpc. This region extends from 1.5 kpc to 8 kpc galactocentric radius, thus avoiding the intense star formation in the central kpc. We have recovered short-spacing u-v components by using singlemore » dish observations from the Nobeyama 45 m and IRAM 30 m telescopes. Using the automated CPROPS algorithm, we identified 45 CO cloud complexes in the CO(1 {yields} 0) map and 64 GMCs in the CO(2 {yields} 1) maps. The sizes, line widths, and luminosities of the GMCs are similar to values found in other extragalactic studies. We have classified the clouds into on-arm and inter-arm clouds based on the stellar mass density traced by the 3.6 {mu}m map. Clouds located on-arm present in general higher star formation rates than clouds located in inter-arm regions. Although the star formation efficiency shows no systematic trend with galactocentric radius, some on-arm clouds-which are more luminous and more massive compared to inter-arm GMCs-are also forming stars more efficiently than the rest of the identified GMCs. We find that these structures appear to be located in two specific regions in the spiral arms. One of them shows a strong velocity gradient, suggesting that this region of high star formation efficiency may be the result of gas flow convergence.« less
Using Multi-Scale Modeling Systems and Satellite Data to Study the Precipitation Processes
NASA Technical Reports Server (NTRS)
Tao, Wei-Kuo; Chern, J.; Lamg, S.; Matsui, T.; Shen, B.; Zeng, X.; Shi, R.
2011-01-01
In recent years, exponentially increasing computer power has extended Cloud Resolving Model (CRM) integrations from hours to months, the number of computational grid points from less than a thousand to close to ten million. Three-dimensional models are now more prevalent. Much attention is devoted to precipitating cloud systems where the crucial 1-km scales are resolved in horizontal domains as large as 10,000 km in two-dimensions, and 1,000 x 1,000 km2 in three-dimensions. Cloud resolving models now provide statistical information useful for developing more realistic physically based parameterizations for climate models and numerical weather prediction models. It is also expected that NWP and mesoscale model can be run in grid size similar to cloud resolving model through nesting technique. Recently, a multi-scale modeling system with unified physics was developed at NASA Goddard. It consists of (l) a cloud-resolving model (Goddard Cumulus Ensemble model, GCE model), (2) a regional scale model (a NASA unified weather research and forecast, WRF), (3) a coupled CRM and global model (Goddard Multi-scale Modeling Framework, MMF), and (4) a land modeling system. The same microphysical processes, long and short wave radiative transfer and land processes and the explicit cloud-radiation, and cloud-land surface interactive processes are applied in this multi-scale modeling system. This modeling system has been coupled with a multi-satellite simulator to use NASA high-resolution satellite data to identify the strengths and weaknesses of cloud and precipitation processes simulated by the model. In this talk, the recent developments and applications of the multi-scale modeling system will be presented. In particular, the results from using multi-scale modeling system to study the precipitating systems and hurricanes/typhoons will be presented. The high-resolution spatial and temporal visualization will be utilized to show the evolution of precipitation processes. Also how to use of the multi-satellite simulator tqimproy precipitation processes will be discussed.
NASA Astrophysics Data System (ADS)
Vasilkov, Alexander; Qin, Wenhan; Krotkov, Nickolay; Lamsal, Lok; Spurr, Robert; Haffner, David; Joiner, Joanna; Yang, Eun-Su; Marchenko, Sergey
2017-01-01
Most satellite nadir ultraviolet and visible cloud, aerosol, and trace-gas algorithms make use of climatological surface reflectivity databases. For example, cloud and NO2 retrievals for the Ozone Monitoring Instrument (OMI) use monthly gridded surface reflectivity climatologies that do not depend upon the observation geometry. In reality, reflection of incoming direct and diffuse solar light from land or ocean surfaces is sensitive to the sun-sensor geometry. This dependence is described by the bidirectional reflectance distribution function (BRDF). To account for the BRDF, we propose to use a new concept of geometry-dependent Lambertian equivalent reflectivity (LER). Implementation within the existing OMI cloud and NO2 retrieval infrastructure requires changes only to the input surface reflectivity database. The geometry-dependent LER is calculated using a vector radiative transfer model with high spatial resolution BRDF information from the Moderate Resolution Imaging Spectroradiometer (MODIS) over land and the Cox-Munk slope distribution over ocean with a contribution from water-leaving radiance. We compare the geometry-dependent and climatological LERs for two wavelengths, 354 and 466 nm, that are used in OMI cloud algorithms to derive cloud fractions. A detailed comparison of the cloud fractions and pressures derived with climatological and geometry-dependent LERs is carried out. Geometry-dependent LER and corresponding retrieved cloud products are then used as inputs to our OMI NO2 algorithm. We find that replacing the climatological OMI-based LERs with geometry-dependent LERs can increase NO2 vertical columns by up to 50 % in highly polluted areas; the differences include both BRDF effects and biases between the MODIS and OMI-based surface reflectance data sets. Only minor changes to NO2 columns (within 5 %) are found over unpolluted and overcast areas.
NASA Astrophysics Data System (ADS)
Planche, C.; Flossmann, A. I.; Wobrock, W.
2009-04-01
A 3D cloud model with detailed microphysics for ice, water and aerosol particles (AP) is used to study the role of AP on the evolution of summertime convective mixed phase clouds and the subsequent precipitation. The model couples the dynamics of the NCAR Clark-Hall cloud scale model (Clark et al., 1996) with the detailed scavenging model (DESCAM) of Flossmann and Pruppacher (1988) and the ice phase module of Leroy et al. (2007). The microphysics follows the evolution of AP, drop, and ice crystal spectra each with 39 bins. Aerosol mass in drops and ice crystals is also predicted by two distribution functions to close the aerosol budget. The simulated cases are compared with radar observations over the northern Vosges mountains and the Rhine valley which were performed on 12 and 13 August 2007 during the COPS field campaign. Using a 3D grid resolution of 250m, our model, called DESCAM-3D, is able to simulate very well the dynamical, cloud and precipitation features observed for the two different cloud systems. The high horizontal grid resolution provides new elements for the understanding of the formation of orographic convection. In addition the fine numerical scale compares well with the high resolved radar observation given by the LaMP X-band radar and Poldirad. The prediction of the liquid and ice hydrometeor spectra allows a detailed calculation of the cloud radar reflectivity. Sensitivity studies realized by the use of different mass-diameter relationships for ice crystals demonstrate the role of the crystal habits on the simulated reflectivities. In order to better understand the role of AP on cloud evolution and precipitation formation several sensitivity studies were performed by modifying not only aerosol number concentration but also their physico-chemical properties. The numerical results show a strong influence of the aerosol number concentration on the precipitation intensity but no effect of the aerosol particle solubility on the rain formation can be found.
NASA Technical Reports Server (NTRS)
Vasilkov, Alexander; Qin, Wenhan; Krotkov, Nickolay; Lamsal, Lok; Spurr, Robert; Haffner, David; Joiner, Joanna; Yang, Eun-Su; Marchenko, Sergey
2017-01-01
Most satellite nadir ultraviolet and visible cloud, aerosol, and trace-gas algorithms make use of climatological surface reflectivity databases. For example, cloud and NO2 retrievals for the Ozone Monitoring Instrument (OMI) use monthly gridded surface reflectivity climatologies that do not depend upon the observation geometry. In reality, reflection of incoming direct and diffuse solar light from land or ocean surfaces is sensitive to the sun-sensor geometry. This dependence is described by the bidirectional reflectance distribution function (BRDF). To account for the BRDF, we propose to use a new concept of geometry-dependent Lambertian equivalent reflectivity (LER). Implementation within the existing OMI cloud and NO2 retrieval infrastructure requires changes only to the input surface reflectivity database. The geometry-dependent LER is calculated using a vector radiative transfer model with high spatial resolution BRDF information from the Moderate Resolution Imaging Spectroradiometer (MODIS) over land and the Cox-Munk slope distribution over ocean with a contribution from water-leaving radiance. We compare the geometry-dependent and climatological LERs for two wavelengths, 354 and 466 nm, that are used in OMI cloud algorithms to derive cloud fractions. A detailed comparison of the cloud fractions and pressures derived with climatological and geometry-dependent LERs is carried out. Geometry-dependent LER and corresponding retrieved cloud products are then used as inputs to our OMI NO2 algorithm. We find that replacing the climatological OMI-based LERs with geometry-dependent LERs can increase NO2 vertical columns by up to 50% in highly polluted areas; the differences include both BRDF effects and biases between the MODIS and OMI-based surface reflectance data sets. Only minor changes to NO2 columns (within 5 %) are found over unpolluted and overcast areas.
NASA Astrophysics Data System (ADS)
Cook, Ryan D.; Lin, Ying-Hsuan; Peng, Zhuoyu; Boone, Eric; Chu, Rosalie K.; Dukett, James E.; Gunsch, Matthew J.; Zhang, Wuliang; Tolic, Nikola; Laskin, Alexander; Pratt, Kerri A.
2017-12-01
Organic aerosol formation and transformation occurs within aqueous aerosol and cloud droplets, yet little is known about the composition of high molecular weight organic compounds in cloud water. Cloud water samples collected at Whiteface Mountain, New York, during August-September 2014 were analyzed by ultra-high-resolution mass spectrometry to investigate the molecular composition of dissolved organic carbon, with a focus on sulfur- and nitrogen-containing compounds. Organic molecular composition was evaluated in the context of cloud water inorganic ion concentrations, pH, and total organic carbon concentrations to gain insights into the sources and aqueous-phase processes of the observed high molecular weight organic compounds. Cloud water acidity was positively correlated with the average oxygen : carbon ratio of the organic constituents, suggesting the possibility for aqueous acid-catalyzed (prior to cloud droplet activation or during/after cloud droplet evaporation) and/or radical (within cloud droplets) oxidation processes. Many tracer compounds recently identified in laboratory studies of bulk aqueous-phase reactions were identified in the cloud water. Organosulfate compounds, with both biogenic and anthropogenic volatile organic compound precursors, were detected for cloud water samples influenced by air masses that had traveled over forested and populated areas. Oxidation products of long-chain (C10-12) alkane precursors were detected during urban influence. Influence of Canadian wildfires resulted in increased numbers of identified sulfur-containing compounds and oligomeric species, including those formed through aqueous-phase reactions involving methylglyoxal. Light-absorbing aqueous-phase products of syringol and guaiacol oxidation were observed in the wildfire-influenced samples, and dinitroaromatic compounds were observed in all cloud water samples (wildfire, biogenic, and urban-influenced). Overall, the cloud water molecular composition depended on air mass source influence and reflected aqueous-phase reactions involving biogenic, urban, and biomass burning precursors.
NASA Astrophysics Data System (ADS)
Küchler, N.; Kneifel, S.; Kollias, P.; Loehnert, U.
2017-12-01
Cumulus and stratocumulus clouds strongly affect the Earth's radiation budget and are a major uncertainty source in weather and climate prediction models. To improve and evaluate models, a comprehensive understanding of cloud processes is necessary and references are needed. Therefore active and passive microwave remote sensing of clouds can be used to derive cloud properties such as liquid water path and liquid water content (LWC), which can serve as a reference for model evaluation. However, both the measurements and the assumptions when retrieving physical quantities from the measurements involve uncertainty sources. Frisch et al. (1998) combined radar and radiometer observations to derive LWC profiles. Assuming their assumptions are correct, there will be still uncertainties regarding the measurement setup. We investigate how varying beam width, temporal and vertical resolutions, frequency combinations, and beam overlap of and between the two instruments influence the retrieval of LWC profiles. Especially, we discuss the benefit of combining vertically, high resolved radar and radiometer measurements using the same antenna, i.e. having ideal beam overlap. Frisch, A. S., G. Feingold, C. W. Fairall, T. Uttal, and J. B. Snider, 1998: On cloud radar and microwave radiometer measurements of stratus cloud liquid water profiles. J. Geophys. Res.: Atmos., 103 (18), 23 195-23 197, doi:0148-0227/98/98JD-01827509.00.
Retrievals of Cloud Droplet Size from the RSP Data: Validation Using in Situ Measurements
NASA Technical Reports Server (NTRS)
Alexandrov, Mikhail D.; Cairns, Brian; Sinclair, Kenneth; Wasilewski, Andrzej P.; Ziemba, Luke; Crosbie, Ewan; Hair, John; Hu, Yongxiang; Hostetler, Chris; Stamnes, Snorre
2016-01-01
We present comparisons of cloud droplet size distributions retrieved from the Research Scanning Polarimeter (RSP) data with correlative in situ measurements made during the North Atlantic Aerosols and Marine Ecosystems Study (NAAMES). This field experiment was based at St. Johns airport, Newfoundland, Canada with the latest deployment in May - June 2016. RSP was onboard the NASA C-130 aircraft together with an array of in situ and other remote sensing instrumentation. The RSP is an along-track scanner measuring polarized and total reflectances in9 spectral channels. Its unique high angular resolution allows for characterization of liquid water droplet size using the rainbow structure observed in the polarized reflectances in the scattering angle range between 135 and 165 degrees. A parametric fitting algorithm applied to the polarized reflectances provides retrievals of the droplet effective radius and variance assuming a prescribed size distribution shape (gamma distribution). In addition to this, we use a non-parametric method, Rainbow Fourier Transform (RFT), which allows us to retrieve the droplet size distribution (DSD) itself. The latter is important in the case of clouds with complex structure, which results in multi-modal DSDs. During NAAMES the aircraft performed a number of flight patterns specifically designed for comparison of remote sensing retrievals and in situ measurements. These patterns consisted of two flight segments above the same straight ground track. One of these segments was flown above clouds allowing for remote sensing measurements, while the other was at the cloud top where cloud droplets were sampled. We compare the DSDs retrieved from the RSP data with in situ measurements made by the Cloud Droplet Probe (CDP). The comparisons show generally good agreement with deviations explainable by the position of the aircraft within cloud and by presence of additional cloud layers in RSP view that do not contribute to the in situ DSDs. In the latter case the distributions retrieved from the RSP data were consistent with the multi-layer cloud structures observed in the correlative High Spectral Resolution Lidar (HSRL) profiles. The comparison results provide a rare validation of polarimetric droplet size retrieval techniques, which can be used for analysis of satellite data on global scale.
Developing Remote Sensing Capabilities for Meter-Scale Sea Ice Properties
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
Evolution of Satellite Imagers and Sounders for Low Earth Orbit and Technology Directions at NASA
NASA Technical Reports Server (NTRS)
Pagano, Thomas S.; McClain, Charles R.
2010-01-01
Imagers and Sounders for Low Earth Orbit (LEO) provide fundamental global daily observations of the Earth System for scientists, researchers, and operational weather agencies. The imager provides the nominal 1-2 km spatial resolution images with global coverage in multiple spectral bands for a wide range of uses including ocean color, vegetation indices, aerosol, snow and cloud properties, and sea surface temperature. The sounder provides vertical profiles of atmospheric temperature, water vapor cloud properties, and trace gases including ozone, carbon monoxide, methane and carbon dioxide. Performance capabilities of these systems has evolved with the optical and sensing technologies of the decade. Individual detectors were incorporated on some of the first imagers and sounders that evolved to linear array technology in the '80's. Signal-to-noise constraints limited these systems to either broad spectral resolution as in the case of the imager, or low spatial resolution as in the case of the sounder. Today's area 2-dimensional large format array technology enables high spatial and high spectral resolution to be incorporated into a single instrument. This places new constraints on the design of these systems and enables new capabilities for scientists to examine the complex processes governing the Earth System.
Cloud-free resolution element statistics program
NASA Technical Reports Server (NTRS)
Liley, B.; Martin, C. D.
1971-01-01
Computer program computes number of cloud-free elements in field-of-view and percentage of total field-of-view occupied by clouds. Human error is eliminated by using visual estimation to compute cloud statistics from aerial photographs.
SAGE III L2 Monthly Cloud Presence Data (HDF-EOS)
Atmospheric Science Data Center
2016-06-14
... degrees South Spatial Resolution: 1 km vertical Temporal Coverage: 02/27/2002 - 12/31/2005 ... Parameters: Cloud Amount/Frequency Cloud Height Cloud Vertical Distribution Order Data: Search and ...
NASA Astrophysics Data System (ADS)
Xu, Y.; Sun, Z.; Boerner, R.; Koch, T.; Hoegner, L.; Stilla, U.
2018-04-01
In this work, we report a novel way of generating ground truth dataset for analyzing point cloud from different sensors and the validation of algorithms. Instead of directly labeling large amount of 3D points requiring time consuming manual work, a multi-resolution 3D voxel grid for the testing site is generated. Then, with the help of a set of basic labeled points from the reference dataset, we can generate a 3D labeled space of the entire testing site with different resolutions. Specifically, an octree-based voxel structure is applied to voxelize the annotated reference point cloud, by which all the points are organized by 3D grids of multi-resolutions. When automatically annotating the new testing point clouds, a voting based approach is adopted to the labeled points within multiple resolution voxels, in order to assign a semantic label to the 3D space represented by the voxel. Lastly, robust line- and plane-based fast registration methods are developed for aligning point clouds obtained via various sensors. Benefiting from the labeled 3D spatial information, we can easily create new annotated 3D point clouds of different sensors of the same scene directly by considering the corresponding labels of 3D space the points located, which would be convenient for the validation and evaluation of algorithms related to point cloud interpretation and semantic segmentation.
NASA Astrophysics Data System (ADS)
Abdelmonem, A.; Schnaiter, M.; Amsler, P.; Hesse, E.; Meyer, J.; Leisner, T.
2011-10-01
Studying the radiative impact of cirrus clouds requires knowledge of the relationship between their microphysics and the single scattering properties of cloud particles. Usually, this relationship is obtained by modeling the optical scattering properties from in situ measurements of ice crystal size distributions. The measured size distribution and the assumed particle shape might be erroneous in case of non-spherical ice particles. We present here a novel optical sensor (the Particle Habit Imaging and Polar Scattering probe, PHIPS) designed to measure simultaneously the 3-D morphology and the corresponding optical and microphysical parameters of individual cloud particles. Clouds containing particles ranging from a few micrometers to about 800 μm diameter in size can be characterized systematically with an optical resolution power of 2 μm and polar scattering resolution of 1° for forward scattering directions (from 1° to 10°) and 8° for side and backscattering directions (from 18° to 170°). The maximum acquisition rates for scattering phase functions and images are 262 KHz and 10 Hz, respectively. Some preliminary results collected in two ice cloud campaigns conducted in the AIDA cloud simulation chamber are presented. PHIPS showed reliability in operation and produced size distributions and images comparable to those given by other certified cloud particles instruments. A 3-D model of a hexagonal ice plate is constructed and the corresponding scattering phase function is compared to that modeled using the Ray Tracing with Diffraction on Facets (RTDF) program. PHIPS is a highly promising novel airborne optical sensor for studying the radiative impact of cirrus clouds and correlating the particle habit-scattering properties which will serve as a reference for other single, or multi-independent, measurement instruments.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Latham, John; Bower, Keith; Choularton, Tom
2012-09-07
The idea behind the marine cloud-brightening (MCB) geoengineering technique is that seeding marine stratocumulus clouds with copious quantities of roughly monodisperse sub-micrometre sea water particles might significantly enhance the cloud droplet number concentration, and thereby the cloud albedo and possibly longevity. This would produce a cooling, which general circulation model (GCM) computations suggest could - subject to satisfactory resolution of technical and scientific problems identified herein - have the capacity to balance global warming up to the carbon dioxide-doubling point. We describe herein an account of our recent research on a number of critical issues associated with MCB. This involvesmore » (i) GCM studies, which are our primary tools for evaluating globally the effectiveness of MCB, and assessing its climate impacts on rainfall amounts and distribution, and also polar sea-ice cover and thickness; (ii) high-resolution modelling of the effects of seeding on marine stratocumulus, which are required to understand the complex array of interacting processes involved in cloud brightening; (iii) microphysical modelling sensitivity studies, examining the influence of seeding amount, seedparticle salt-mass, air-mass characteristics, updraught speed and other parameters on cloud-albedo change; (iv) sea water spray-production techniques; (v) computational fluid dynamics studies of possible large-scale periodicities in Flettner rotors; and (vi) the planning of a three-stage limited-area field research experiment, with the primary objectives of technology testing and determining to what extent, if any, cloud albedo might be enhanced by seeding marine stratocumulus clouds on a spatial scale of around 100 km. We stress that there would be no justification for deployment of MCB unless it was clearly established that no significant adverse consequences would result. There would also need to be an international agreement firmly in favour of such action.« less
Latham, John; Bower, Keith; Choularton, Tom; Coe, Hugh; Connolly, Paul; Cooper, Gary; Craft, Tim; Foster, Jack; Gadian, Alan; Galbraith, Lee; Iacovides, Hector; Johnston, David; Launder, Brian; Leslie, Brian; Meyer, John; Neukermans, Armand; Ormond, Bob; Parkes, Ben; Rasch, Phillip; Rush, John; Salter, Stephen; Stevenson, Tom; Wang, Hailong; Wang, Qin; Wood, Rob
2012-09-13
The idea behind the marine cloud-brightening (MCB) geoengineering technique is that seeding marine stratocumulus clouds with copious quantities of roughly monodisperse sub-micrometre sea water particles might significantly enhance the cloud droplet number concentration, and thereby the cloud albedo and possibly longevity. This would produce a cooling, which general circulation model (GCM) computations suggest could-subject to satisfactory resolution of technical and scientific problems identified herein-have the capacity to balance global warming up to the carbon dioxide-doubling point. We describe herein an account of our recent research on a number of critical issues associated with MCB. This involves (i) GCM studies, which are our primary tools for evaluating globally the effectiveness of MCB, and assessing its climate impacts on rainfall amounts and distribution, and also polar sea-ice cover and thickness; (ii) high-resolution modelling of the effects of seeding on marine stratocumulus, which are required to understand the complex array of interacting processes involved in cloud brightening; (iii) microphysical modelling sensitivity studies, examining the influence of seeding amount, seed-particle salt-mass, air-mass characteristics, updraught speed and other parameters on cloud-albedo change; (iv) sea water spray-production techniques; (v) computational fluid dynamics studies of possible large-scale periodicities in Flettner rotors; and (vi) the planning of a three-stage limited-area field research experiment, with the primary objectives of technology testing and determining to what extent, if any, cloud albedo might be enhanced by seeding marine stratocumulus clouds on a spatial scale of around 100×100 km. We stress that there would be no justification for deployment of MCB unless it was clearly established that no significant adverse consequences would result. There would also need to be an international agreement firmly in favour of such action.
NASA Astrophysics Data System (ADS)
Biercamp, Joachim; Adamidis, Panagiotis; Neumann, Philipp
2017-04-01
With the exa-scale era approaching, length and time scales used for climate research on one hand and numerical weather prediction on the other hand blend into each other. The Centre of Excellence in Simulation of Weather and Climate in Europe (ESiWACE) represents a European consortium comprising partners from climate, weather and HPC in their effort to address key scientific challenges that both communities have in common. A particular challenge is to reach global models with spatial resolutions that allow simulating convective clouds and small-scale ocean eddies. These simulations would produce better predictions of trends and provide much more fidelity in the representation of high-impact regional events. However, running such models in operational mode, i.e with sufficient throughput in ensemble mode clearly will require exa-scale computing and data handling capability. We will discuss the ESiWACE initiative and relate it to work-in-progress on high-resolution simulations in Europe. We present recent strong scalability measurements from ESiWACE to demonstrate current computability in weather and climate simulation. A special focus in this particular talk is on the Icosahedal Nonhydrostatic (ICON) model used for a comparison of high resolution regional and global simulations with high quality observation data. We demonstrate that close-to-optimal parallel efficiency can be achieved in strong scaling global resolution experiments on Mistral/DKRZ, e.g. 94% for 5km resolution simulations using 36k cores on Mistral/DKRZ. Based on our scalability and high-resolution experiments, we deduce and extrapolate future capabilities for ICON that are expected for weather and climate research at exascale.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Smith, Donald F.; Schulz, Carl; Konijnenburg, Marco
High-resolution Fourier transform ion cyclotron resonance (FT-ICR) mass spectrometry imaging enables the spatial mapping and identification of biomolecules from complex surfaces. The need for long time-domain transients, and thus large raw file sizes, results in a large amount of raw data (“big data”) that must be processed efficiently and rapidly. This can be compounded by largearea imaging and/or high spatial resolution imaging. For FT-ICR, data processing and data reduction must not compromise the high mass resolution afforded by the mass spectrometer. The continuous mode “Mosaic Datacube” approach allows high mass resolution visualization (0.001 Da) of mass spectrometry imaging data, butmore » requires additional processing as compared to featurebased processing. We describe the use of distributed computing for processing of FT-ICR MS imaging datasets with generation of continuous mode Mosaic Datacubes for high mass resolution visualization. An eight-fold improvement in processing time is demonstrated using a Dutch nationally available cloud service.« less
Guo, Zhun; Wang, Minghuai; Qian, Yun; ...
2014-08-13
In this study, we investigate the sensitivity of simulated shallow cumulus and stratocumulus clouds to selected tunable parameters of Cloud Layers Unified by Binormals (CLUBB) in the single column version of Community Atmosphere Model version 5 (SCAM5). A quasi-Monte Carlo (QMC) sampling approach is adopted to effectively explore the high-dimensional parameter space and a generalized linear model is adopted to study the responses of simulated cloud fields to tunable parameters. One stratocumulus and two shallow convection cases are configured at both coarse and fine vertical resolutions in this study.. Our results show that most of the variance in simulated cloudmore » fields can be explained by a small number of tunable parameters. The parameters related to Newtonian and buoyancy-damping terms of total water flux are found to be the most influential parameters for stratocumulus. For shallow cumulus, the most influential parameters are those related to skewness of vertical velocity, reflecting the strong coupling between cloud properties and dynamics in this regime. The influential parameters in the stratocumulus case are sensitive to the choice of the vertical resolution while little sensitivity is found for the shallow convection cases, as eddy mixing length (or dissipation time scale) plays a more important role and depends more strongly on the vertical resolution in stratocumulus than in shallow convections. The influential parameters remain almost unchanged when the number of tunable parameters increases from 16 to 35. This study improves understanding of the CLUBB behavior associated with parameter uncertainties.« less
Fractal Analyses of High-Resolution Cloud Droplet Measurements.
NASA Astrophysics Data System (ADS)
Malinowski, Szymon P.; Leclerc, Monique Y.; Baumgardner, Darrel G.
1994-02-01
Fractal analyses of individual cloud droplet distributions using aircraft measurements along one-dimensional horizontal cross sections through clouds are performed. Box counting and cluster analyses are used to determine spatial scales of inhomogeneity of cloud droplet spacing. These analyses reveal that droplet spatial distributions do not exhibit a fractal behavior. A high variability in local droplet concentration in cloud volumes undergoing mixing was found. In these regions, thin filaments of cloudy air with droplet concentration close to those observed in cloud cores were found. Results suggest that these filaments may be anisotropic. Additional box counting analyses performed for various classes of cloud droplet diameters indicate that large and small droplets are similarly distributed, except for the larger characteristic spacing of large droplets.A cloud-clear air interface defined by a certain threshold of total droplet count (TDC) was investigated. There are indications that this interface is a convoluted surface of a fractal nature, at least in actively developing cumuliform clouds. In contrast, TDC in the cloud interior does not have fractal or multifractal properties. Finally a random Cantor set (RCS) was introduced as a model of a fractal process with an ill-defined internal scale. A uniform measure associated with the RCS after several generations was introduced to simulate the TDC records. Comparison of the model with real TDC records indicates similar properties of both types of data series.
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.
Insights into low-latitude cloud feedbacks from high-resolution models.
Bretherton, Christopher S
2015-11-13
Cloud feedbacks are a leading source of uncertainty in the climate sensitivity simulated by global climate models (GCMs). Low-latitude boundary-layer and cumulus cloud regimes are particularly problematic, because they are sustained by tight interactions between clouds and unresolved turbulent circulations. Turbulence-resolving models better simulate such cloud regimes and support the GCM consensus that they contribute to positive global cloud feedbacks. Large-eddy simulations using sub-100 m grid spacings over small computational domains elucidate marine boundary-layer cloud response to greenhouse warming. Four observationally supported mechanisms contribute: 'thermodynamic' cloudiness reduction from warming of the atmosphere-ocean column, 'radiative' cloudiness reduction from CO2- and H2O-induced increase in atmospheric emissivity aloft, 'stability-induced' cloud increase from increased lower tropospheric stratification, and 'dynamical' cloudiness increase from reduced subsidence. The cloudiness reduction mechanisms typically dominate, giving positive shortwave cloud feedback. Cloud-resolving models with horizontal grid spacings of a few kilometres illuminate how cumulonimbus cloud systems affect climate feedbacks. Limited-area simulations and superparameterized GCMs show upward shift and slight reduction of cloud cover in a warmer climate, implying positive cloud feedbacks. A global cloud-resolving model suggests tropical cirrus increases in a warmer climate, producing positive longwave cloud feedback, but results are sensitive to subgrid turbulence and ice microphysics schemes. © 2015 The Author(s).
NASA Technical Reports Server (NTRS)
Varnai, Tamas; Marshak, Alexander; Lau, William K. M. (Technical Monitor)
2001-01-01
This paper examines three-dimensional (3D) radiative effects, which arise from horizontal radiative interactions between areas that have different cloud properties. Earlier studies have argued that these effects can cause significant uncertainties in current satellite retrievals of cloud properties, because the retrievals rely on one-dimensional (1D) theory and do not consider the effects of horizontal changes in cloud properties. This study addresses two questions: which retrieved cloud properties are influenced by 3D radiative effects, and where 3D effects tend to occur? The influence of 3D effects is detected from the wayside illumination and shadowing make clouds appear asymmetric: Areas appear brighter if the cloud top surface is tilted toward, rather than away from, the Sun. The analysis of 30 images by the Moderate Resolution Imaging Spectroradiometer (MODIS) reveals that retrievals of cloud optical thickness and cloud water content are most influenced by 3D effects, whereas retrievals of cloud particle size are much less affected. The results also indicate that while 3D effects are strongest at cloud edges, cloud top variability in cloud interiors, even in overcast regions, also produces considerable 3D effects. Finally, significant 3D effects are found in a wide variety of situations, ranging from thin clouds to thick ones and from low clouds to high ones.
Comparasion of Cloud Cover restituted by POLDER and MODIS
NASA Astrophysics Data System (ADS)
Zeng, S.; Parol, F.; Riedi, J.; Cornet, C.; Thieuxleux, F.
2009-04-01
PARASOL and AQUA are two sun-synchronous orbit satellites in the queue of A-Train satellites that observe our earth within a few minutes apart from each other. Aboard these two platforms, POLDER and MODIS provide coincident observations of the cloud cover with very different characteristics. These give us a good opportunity to study the clouds system and evaluate strengths and weaknesses of each dataset in order to provide an accurate representation of global cloud cover properties. This description is indeed of outermost importance to quantify and understand the effect of clouds on global radiation budget of the earth-atmosphere system and their influence on the climate changes. We have developed a joint dataset containing both POLDER and MODIS level 2 cloud products collocated and reprojected on a common sinusoidal grid in order to make the data comparison feasible and veracious. Our foremost work focuses on the comparison of both spatial distribution and temporal variation of the global cloud cover. This simple yet critical cloud parameter need to be clearly understood to allow further comparison of the other cloud parameters. From our study, we demonstrate that on average these two sensors both detect the clouds fairly well. They provide similar spatial distributions and temporal variations:both sensors see high values of cloud amount associated with deep convection in ITCZ, over Indonesia, and in west-central Pacific Ocean warm pool region; they also provide similar high cloud cover associated to mid-latitude storm tracks, to Indian monsoon or to the stratocumulus along the west coast of continents; on the other hand small cloud amounts that typically present over subtropical oceans and deserts in subsidence aeras are well identified by both POLDER and MODIS. Each sensor has its advantages and inconveniences for the detection of a particular cloud types. With higher spatial resolution, MODIS can better detect the fractional clouds thus explaining as one part of a positive bias in any latitude and in any viewing angle with an order of 10% between the POLDER cloud amount and the so-called MODIS "combined" cloud amount. Nevertheless it is worthy to note that a negative bias of about 10% is obtained between the POLDER cloud amount and the MODIS "day-mean" cloud amount. Main differences between the two MODIS cloud amount values are known to be due to the filtering of remaining aerosols or cloud edges. due to both this high spatial resolution of MODIS and the fact that "combined" cloud amount filters cloud edges, we can also explain why appear the high positive bias regions over subtropical ocean in south hemisphere and over east Africa in summer. Thanks to several channels in the thermal infrared spectral domain, MODIS detects probably much better the thin cirrus especially over land, thus causing a general negative bias for ice clouds. The multi-spectral capability of MODIS also allows for a better detection of low clouds over snow or ice, Hence the (POLDER-MODIS) cloud amount difference is often negative over Greenland, Antarctica, and over the continents at middle-high latitudes in spring and autumn associated to the snow coverage. The multi-spectral capability of MODIS also makes the discrimination possible between the biomass burning aerosols and the fractional clouds over the continents. Thus a positive bias appears in central Africa in summer and autumn associated to important biomass burning events. Over transition region between desert and non-desert, the presence of large negative bias (POLDER-MODIS) of cloud amount maybe partly due to MODIS pixel falsely labeled the desert as cloudy, where MODIS algorithm uses static desert mask. This is clearly highlighted in south of Sahara in spring and summer where we find a bias negative with an order of -0.1. What is more, thanks to its multi-angular capability, POLDER can discriminate the sun-glint region thus minimizing the dependence of cloud amount on view angle. It makes the detection of high clouds easier over a black surface thanks to its polarization character.
Reducing Surface Clutter in Cloud Profiling Radar Data
NASA Technical Reports Server (NTRS)
Tanelli, Simone; Pak, Kyung; Durden, Stephen; Im, Eastwood
2008-01-01
An algorithm has been devised to reduce ground clutter in the data products of the CloudSat Cloud Profiling Radar (CPR), which is a nadir-looking radar instrument, in orbit around the Earth, that measures power backscattered by clouds as a function of distance from the instrument. Ground clutter contaminates the CPR data in the lowest 1 km of the atmospheric profile, heretofore making it impossible to use CPR data to satisfy the scientific interest in studying clouds and light rainfall at low altitude. The algorithm is based partly on the fact that the CloudSat orbit is such that the geodetic altitude of the CPR varies continuously over a range of approximately 25 km. As the geodetic altitude changes, the radar timing parameters are changed at intervals defined by flight software in order to keep the troposphere inside a data-collection time window. However, within each interval, the surface of the Earth continuously "scans through" (that is, it moves across) a few range bins of the data time window. For each radar profile, only few samples [one for every range-bin increment ((Delta)r = 240 m)] of the surface-clutter signature are available around the range bin in which the peak of surface return is observed, but samples in consecutive radar profiles are offset slightly (by amounts much less than (Delta)r) with respect to each other according to the relative change in geodetic altitude. As a consequence, in a case in which the surface area under examination is homogenous (e.g., an ocean surface), a sequence of consecutive radar profiles of the surface in that area contains samples of the surface response with range resolution (Delta)p much finer than the range-bin increment ((Delta)p << r). Once the high-resolution surface response has thus become available, the profile of surface clutter can be accurately estimated by use of a conventional maximum-correlation scheme: A translated and scaled version of the high-resolution surface response is fitted to the observed low-resolution profile. The translation and scaling factors that optimize the fit in a maximum-correlation sense represent (1) the true position of the surface relative to the sampled surface peak and (2) the magnitude of the surface backscatter. The performance of this algorithm has been tested on CloudSat data acquired over an ocean surface. A preliminary analysis of the test data showed a surface-clutter-rejection ratio over flat surfaces of >10 dB and a reduction of the contaminated altitude over ocean from about 1 km to about 0.5 km (over the ocean). The algorithm has been embedded in CloudSat L1B processing as of Release 04 (July 2007), and the estimated flat surface clutter is removed in L2B-GEOPROF product from the observed profile of reflectivity (see CloudSat product documentation for details and performance at http://www.cloudsat.cira.colostate.edu/ dataSpecs.php?prodid=1).
NASA Astrophysics Data System (ADS)
Gasiewski, A. J.; Sanders, B. T.; Gallaher, D. W.; Periasamy, L.; Alvarenga, G.; Weaver, R.; Scambos, T. A.
2014-12-01
PolarCube is a 3U CubeSat based on the CU ALL-STAR bus hosting an eight-channel passive microwave scanning spectrometer operating at the 118.7503 GHz (1-) O2 resonance. The anticipated launch date is in late 2015. It is being designed to operate for 12 months on orbit to provide global 118-GHz spectral imagery of the Earth over a full seasonal cycle. The mission will focus on the study of Arctic vertical temperature structure and its relation to sea ice coverage, but include the secondary goals of assessing the potential for convective cloud mass detection and cloud top altitude measurement and hurricane warm core sounding. The principles used by PolarCube for sounding and cloud measurement have been well established in number of peer-reviewed papers, although measurements using the 118 GHz oxygen line over the dry polar regions (unaffected by water vapor) have never been demonstrated from space. The PolarCube channels are selected to probe clear-air emission over vertical levels from the surface to the lower stratosphere. Operational spaceborne microwave soundings have available for decades but using lower frequencies (50-57 GHz) and from higher altitudes. While the JPSS ATMS sensor provides global coverage at ~32 km resolution PolarCube will improve on this resolution by a factor of two (~16 km), thus facilitating a key science goal of mapping sea ice concentration and extent while obtaining temperature profile data. Additionally, we seek to correlate freeze-thaw line data from the NASA SMAP mission with atmospheric temperature structure to help understand the relationship between clouds, temperature, and surface energy fluxes during seasonal transitions. PolarCube will also provide the first demonstration of a very low cost passive microwave sounder that if operated in a fleet configuration would have the potential to fulfill the goals of the Precipitation Atmospheric Temperature and Humidity (PATH) mission, as defined in the NRC Decadal Survey.
Evaluation of a Mesoscale Convective System in Variable-Resolution CESM
NASA Astrophysics Data System (ADS)
Payne, A. E.; Jablonowski, C.
2017-12-01
Warm season precipitation over the Southern Great Plains (SGP) follows a well observed diurnal pattern of variability, peaking at night-time, due to the eastward propagation of mesoscale convection systems that develop over the eastern slopes of the Rockies in the late afternoon. While most climate models are unable to adequately capture the organization of convection and characteristic pattern of precipitation over this region, models with high enough resolution to explicitly resolve convection show improvement. However, high resolution simulations are computationally expensive and, in the case of regional climate models, are subject to boundary conditions. Newly developed variable resolution global climate models strike a balance between the benefits of high-resolution regional climate models and the large-scale dynamics of global climate models and low computational cost. Recently developed parameterizations that are insensitive to the model grid scale provide a way to improve model performance. Here, we present an evaluation of the newly available Cloud Layers Unified by Binormals (CLUBB) parameterization scheme in a suite of variable-resolution CESM simulations with resolutions ranging from 110 km to 7 km within a regionally refined region centered over the SGP Atmospheric Radiation Measurement (ARM) site. Simulations utilize the hindcast approach developed by the Department of Energy's Cloud-Associated Parameterizations Testbed (CAPT) for the assessment of climate models. We limit our evaluation to a single mesoscale convective system that passed over the region on May 24, 2008. The effects of grid-resolution on the timing and intensity of precipitation, as well as, on the transition from shallow to deep convection are assessed against ground-based observations from the SGP ARM site, satellite observations and ERA-Interim reanalysis.
2010-11-18
This image from the High-Resolution Instrument on NASA EPOXI mission spacecraft shows part of the nucleus of comet Hartley 2. The sun is illuminating the nucleus from the right. A distinct cloud of individual particles is visible.
Measurement of the line-of-sight velocity of high-altitude barium clouds A technique
NASA Technical Reports Server (NTRS)
Mende, S. B.; Harris, S. E.
1982-01-01
It is demonstrated that for maximizing the scientific output of future ionospheric and magnetospheric ion cloud release experiments a new type of instrument is required which will measure the line-of-sight velocity of the ion cloud by the Doppler technique. A simple instrument was constructed using a 5-cm diam solid Fabry-Perot etalon coupled to a low-light-level integrating TV camera. It was demonstrated that the system has both the sensitivity and spectral resolution for detection of ion clouds and measurement of their line-of-sight Doppler velocity. The tests consisted of (1) a field experiment using a rocket barium cloud release to check sensitivity, and (2) laboratory experiments to show the spectral resolving capabilities of the system. The instrument was found to be operational if the source was brighter than approximately 1 kR, and it had a wavelength resolution much better than 0.2 A, which corresponds to approximately 12 km/sec or in the case of barium ion an acceleration potential of 100 V. The instrument is rugged and, therefore, simple to use in field experiments or on flight instruments. The sensitivity limit of the instrument can be increased by increasing the size of the etalon.
Evaluation of Decision Trees for Cloud Detection from AVHRR Data
NASA Technical Reports Server (NTRS)
Shiffman, Smadar; Nemani, Ramakrishna
2005-01-01
Automated cloud detection and tracking is an important step in assessing changes in radiation budgets associated with global climate change via remote sensing. Data products based on satellite imagery are available to the scientific community for studying trends in the Earth's atmosphere. The data products include pixel-based cloud masks that assign cloud-cover classifications to pixels. Many cloud-mask algorithms have the form of decision trees. The decision trees employ sequential tests that scientists designed based on empirical astrophysics studies and simulations. Limitations of existing cloud masks restrict our ability to accurately track changes in cloud patterns over time. In a previous study we compared automatically learned decision trees to cloud masks included in Advanced Very High Resolution Radiometer (AVHRR) data products from the year 2000. In this paper we report the replication of the study for five-year data, and for a gold standard based on surface observations performed by scientists at weather stations in the British Islands. For our sample data, the accuracy of automatically learned decision trees was greater than the accuracy of the cloud masks p < 0.001.
Aqueous Processing of Atmospheric Organic Particles in Cloud Water Collected via Aircraft Sampling
DOE Office of Scientific and Technical Information (OSTI.GOV)
Boone, Eric J.; Laskin, Alexander; Laskin, Julia
2015-07-21
Cloud water and below-cloud atmospheric particle samples were collected onboard a research aircraft during the Southern Oxidant and Aerosol Study (SOAS) over a forested region of Alabama in June 2013. The organic molecular composition of the samples was studied to gain insights into the aqueous-phase processing of organic compounds within cloud droplets. High resolution mass spectrometry with nanospray desorption electrospray ionization and direct infusion electrospray ionization were utilized to compare the organic composition of the particle and cloud water samples, respectively. Isoprene and monoterpene-derived organosulfates and oligomers were identified in both the particles and cloud water, showing the significant influencemore » of biogenic volatile organic compound oxidation above the forested region. While the average O:C ratios of the organic compounds were similar between the atmospheric particle and cloud water samples, the chemical composition of these samples was quite different. Specifically, hydrolysis of organosulfates and formation of nitrogen-containing compounds were observed for the cloud water when compared to the atmospheric particle samples, demonstrating that cloud processing changes the composition of organic aerosol.« less
Could geoengineering research help answer one of the biggest questions in climate science?
NASA Astrophysics Data System (ADS)
Wood, Robert; Ackerman, Thomas; Rasch, Philip; Wanser, Kelly
2017-07-01
Anthropogenic aerosol impacts on clouds constitute the largest source of uncertainty in quantifying the radiative forcing of climate, and hinders our ability to determine Earth's climate sensitivity to greenhouse gas increases. Representation of aerosol-cloud interactions in global models is particularly challenging because these interactions occur on typically unresolved scales. Observational studies show influences of aerosol on clouds, but correlations between aerosol and clouds are insufficient to constrain aerosol forcing because of the difficulty in separating aerosol and meteorological impacts. In this commentary, we argue that this current impasse may be overcome with the development of approaches to conduct control experiments whereby aerosol particle perturbations can be introduced into patches of marine low clouds in a systematic manner. Such cloud perturbation experiments constitute a fresh approach to climate science and would provide unprecedented data to untangle the effects of aerosol particles on cloud microphysics and the resulting reflection of solar radiation by clouds. The control experiments would provide a critical test of high-resolution models that are used to develop an improved representation aerosol-cloud interactions needed to better constrain aerosol forcing in global climate models.
Effects of instrument characteristics on cloud properties retrieved from satellite imagery data
NASA Technical Reports Server (NTRS)
Baldwin, D. G.; Coakley, J. A., Jr.; Zhang, M. S.
1986-01-01
The relationships between sensor resolution and derived cloud properties in satellite remote sensing were studied by comparisons of cloud characteristics determined by spatial coherence analysis of AVHRR and GOES data. The latter data were simulated from 11 microns AVHRR data and were assigned a resolution (8 sq km) half that of the AVHRR. Day and nighttime passes were considered for single-layer maritime cloud systems. Sample radiance vs local standard deviation plots of 1024 points are provided for the same area from AVHRR and GOES-East sensors, demonstrating a qualitative agreement.
NASA Astrophysics Data System (ADS)
Sato, T.; Kasaba, Y.; Takahashi, Y.; Murata, I.; Uno, T.; Tokimasa, N.; Sakamoto, M.
2008-12-01
We conducted ground-based observation of Jupiter with the liquid crystal tunable filter (LCTF) and EM-CCD camera in two methane absorption bands (700-757nm, 872-950nm at 3 nm step: total of 47 wavelengths) to derive detailed Jupiter's vertical cloud structure. The 2-meter reflector telescope at Nishi-Harima astronomical observatory in Japan was used for our observation on 26-30 May, 2008. After a series of image processing (composition of high quality images in each wavelength and geometry calibration), we converted observed intensity to absolute reflectivity at each pixel using standard star. As a result, we acquired Jupiter's data cubes with high-spatial resolution (about 1") and narrow band imaging (typically 7nm) in each methane absorption band by superimposing 30 Jupiter's images obtained in short exposure time (50 ms per one image). These data sets enable us to probe different altitudes of Jupiter from 100 mbar down to 1bar level with higher vertical resolution than using convectional interference filters. To interpret observed center-limb profiles, we developed radiative transfer code based on layer adding doubling algorithm to treat multiple scattering of solar light theoretically and extracted information on aerosol altitudes and optical properties using two-cloud model. First, we fit 5 different profiles simultaneously in continuum data (745-757 nm) to retrieve information on optical thickness of haze and single scattering albedo of cloud. Second, we fit 15 different profiles around 727nm methane absorption band and 13 different profiles around 890 nm methane absorption band to retrieve information on the aerosol altitude location and optical thickness of cloud. In this presentation, we present the results of these modeling simulations and discuss the latitudinal variations of Jupiter's vertical cloud structure.
Pre-Juno Optical Analysis of Jupiter's Atmosphere with the NMSU Acousto-optic Imaging Camera
NASA Astrophysics Data System (ADS)
Dahl, Emma; Chanover, Nancy J.; Voelz, David; Kuehn, David M.; Strycker, Paul D.
2016-10-01
Jupiter's upper atmosphere is a highly dynamic system in which clouds and storms change color, shape, and size on variable timescales. The exact mechanism by which the deep atmosphere affects these changes in the uppermost cloud deck is still unknown. With Juno's arrival at Jupiter in July 2016, the thermal radiation from the deep atmosphere will be measurable with the spacecraft's Microwave Radiometer. By taking detailed optical measurements of Jupiter's uppermost cloud deck in conjunction with Juno's microwave observations, we can provide a context in which to better understand these observations. This data will also provide a complement to the near-IR sensitivity of the Jovian InfraRed Auroral Mapper and will expand on the limited spectral coverage of JunoCam. Ultimately, we can utilize the two complementary datasets in order to thoroughly characterize Jupiter's atmosphere in terms of its vertical cloud structure, color distribution, and dynamical state throughout the Juno era. In order to obtain high spectral resolution images of Jupiter's atmosphere in the optical regime, we use the New Mexico State University Acousto-optic Imaging Camera (NAIC). NAIC contains an acousto-optic tunable filter, which allows us to take hyperspectral image cubes of Jupiter from 450-950 nm at an average spectral resolution (λ/dλ) of 242. We present an analysis of our pre-Juno dataset obtained with NAIC at the Apache Point Observatory 3.5-m telescope during the night of March 28, 2016. Under primarily photometric conditions, we obtained 6 hyperspectral image cubes of Jupiter over the course of the night, totaling approximately 2,960 images. From these data we derive low-resolution optical spectra of the Great Red Spot and a representative belt and zone to compare with previous work and laboratory measurements of candidate chromophore materials. Future work will focus on radiative transfer modeling to elucidate the Jovian cloud structure during the Juno era. This work was supported by NASA through award number NNX15AP34A.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Cook, Ryan D.; Lin, Ying-Hsuan; Peng, Zhuoyu
Organic aerosol formation and transformation occurs within aqueous aerosol and cloud droplets, yet little is known about the composition of high molecular weight organic compounds in cloud water. Cloud water samples collected at Whiteface Mountain, New York, during August-September 2014 were analyzed by ultra-high-resolution mass spectrometry to investigate the molecular composition of dissolved organic carbon, with a focus on sulfur- and nitrogen-containing compounds. Organic molecular composition was evaluated in the context of cloud water inorganic ion concentrations, pH, and total organic carbon concentrations to gain insights into the sources and aqueous-phase processes of the observed high molecular weight organic compounds.more » Cloud water acidity was positively correlated with the average oxygen : carbon ratio of the organic constituents, suggesting the possibility for aqueous acid-catalyzed (prior to cloud droplet activation or during/after cloud droplet evaporation) and/or radical (within cloud droplets) oxidation processes. Many tracer compounds recently identified in laboratory studies of bulk aqueous-phase reactions were identified in the cloud water. Organosulfate compounds, with both biogenic and anthropogenic volatile organic compound precursors, were detected for cloud water samples influenced by air masses that had traveled over forested and populated areas. Oxidation products of long-chain (C 10-12) alkane precursors were detected during urban influence. Influence of Canadian wildfires resulted in increased numbers of identified sulfur-containing compounds and oligomeric species, including those formed through aqueous-phase reactions involving methylglyoxal. Light-absorbing aqueous-phase products of syringol and guaiacol oxidation were observed in the wildfire-influenced samples, and dinitroaromatic compounds were observed in all cloud water samples (wildfire, biogenic, and urban-influenced). Overall, the cloud water molecular composition depended on air mass source influence and reflected aqueous-phase reactions involving biogenic, urban, and biomass burning precursors.« less
Similar complex kinematics within two massive, filamentary infrared dark clouds
NASA Astrophysics Data System (ADS)
Barnes, A. T.; Henshaw, J. D.; Caselli, P.; Jiménez-Serra, I.; Tan, J. C.; Fontani, F.; Pon, A.; Ragan, S.
2018-04-01
Infrared dark clouds (IRDCs) are thought to be potential hosts of the elusive early phases of high-mass star formation. Here, we conduct an in-depth kinematic analysis of one such IRDC, G034.43+00.24 (Cloud F), using high sensitivity and high spectral resolution IRAM-30m N2H+ (1-0) and C18O (1-0) observations. To disentangle the complex velocity structure within this cloud, we use Gaussian decomposition and hierarchical clustering algorithms. We find that four distinct coherent velocity components are present within Cloud F. The properties of these components are compared to those found in a similar IRDC, G035.39-00.33 (Cloud H). We find that the components in both clouds have high densities (inferred by their identification in N2H+), trans-to-supersonic non-thermal velocity dispersions with Mach numbers of ˜1.5-4, a separation in velocity of ˜3 km s-1, and a mean red-shift of ˜0.3 km s-1 between the N2H+ (dense gas) and C18O emission (envelope gas). The latter of these could suggest that these clouds share a common formation scenario. We investigate the kinematics of the larger-scale Cloud F structures, using lower-density-tracing 13CO(1-0) observations. A good correspondence is found between the components identified in the IRAM-30m observations and the most prominent component in the 13CO data. We find that the IRDC Cloud F is only a small part of a much larger structure, which appears to be an inter-arm filament of the Milky Way.
An evaluation of atmospheric corrections to advanced very high resolution radiometer data
Meyer, David; Hood, Joy J.
1993-01-01
A data set compiled to analyze vegetation indices is used to evaluate the effect of atmospheric correction to AVHRR measurement in the solar spectrum. Such corrections include cloud screening and "clear sky" corrections. We used the "clouds from AVHRR" (CLAVR) method for cloud detection and evaluated its performance over vegetated targets. Clear sky corrections, designed to reduce the effects of molecular scattering and absorption due to ozone, water vapor, carbon dioxide, and molecular oxygen, were applied to data values determine to be cloud free. Generally, it was found that the screening and correction of the AVHRR data did not affect the maximum NDVI compositing process adversely, while at the same time improving estimates of the land-surface radiances over a compositing period.
Comparison of TOMS and AVHRR volcanic ash retrievals from the August 1992 eruption of Mt. Spurr
Krotkov, N.A.; Torres, O.; Seftor, C.; Krueger, A.J.; Kostinski, A.; Rose, William I.; Bluth, G.J.S.; Schneider, D.; Schaefer, S.J.
1999-01-01
On August 19, 1992, the Advanced Very High Resolution Radiometer (AVHRR) onboard NOAA-12 and NASA's Total Ozone Mapping Spectrometer (TOMS) onboard the Nimbus-7 satellite simultaneously detected and mapped the ash cloud from the eruption of Mt. Spurr, Alaska. The spatial extent and geometry of the cloud derived from the two datasets are in good agreement and both AVHRR split window IR (11-12??m brightness temperature difference) and the TOMS UV Aerosol Index (0.34-0.38??m ultraviolet backscattering and absorption) methods give the same range of total cloud ash mass. Redundant methods for determination of ash masses in drifting volcanic clouds offer many advantages for potential application to the mitigation of aircraft hazards.
Lu, Chunsong; Liu, Yangang; Niu, Shengjie; ...
2017-10-12
In the paper of warm clouds, there are many outstanding questions. Cloud droplet size distributions are much wider, and warm rain is initiated in a shorter time and with a shallower cloud depth than theoretical expectations. This review summarizes the studies related to the effects of turbulent fluctuations and turbulent entrainment-mixing on the broadening of droplet size distributions and warm rain initiation, including observational, laboratorial, numerical, and theoretical achievements. Particular attention is paid to studies by Chinese scientists since the 1950s, since most results have been published in Chinese. The review reveals that high-resolution observations and simulations, and laboratory experimentsmore » are needed because knowledge of the detailed physical processes involved in the effects of turbulence and entrainment-mixing on cloud microphysics still remains elusive.« less
DOE Office of Scientific and Technical Information (OSTI.GOV)
Lu, Chunsong; Liu, Yangang; Niu, Shengjie
In the paper of warm clouds, there are many outstanding questions. Cloud droplet size distributions are much wider, and warm rain is initiated in a shorter time and with a shallower cloud depth than theoretical expectations. This review summarizes the studies related to the effects of turbulent fluctuations and turbulent entrainment-mixing on the broadening of droplet size distributions and warm rain initiation, including observational, laboratorial, numerical, and theoretical achievements. Particular attention is paid to studies by Chinese scientists since the 1950s, since most results have been published in Chinese. The review reveals that high-resolution observations and simulations, and laboratory experimentsmore » are needed because knowledge of the detailed physical processes involved in the effects of turbulence and entrainment-mixing on cloud microphysics still remains elusive.« less
NASA Technical Reports Server (NTRS)
Wind, Galina; Riedi, Jerome; Platnick, Steven; Heidinger, Andrew
2014-01-01
The Cross-platform HIgh resolution Multi-instrument AtmosphEric Retrieval Algorithms (CHIMAERA) system allows us to perform MODIS-like cloud top, optical and microphysical properties retrievals on any sensor that possesses a minimum set of common spectral channels. The CHIMAERA system uses a shared-core architecture that takes retrieval method out of the equation when intercomparisons are made. Here we show an example of such retrieval and a comparison of simultaneous retrievals done using SEVIRI, MODIS and VIIRS sensors. All sensor retrievals are performed using CLAVR-x (or CLAVR-x based) cloud top properties algorithm. SEVIRI uses the SAF_NWC cloud mask. MODIS and VIIRS use the IFF-based cloud mask that is a shared algorithm between MODIS and VIIRS. The MODIS and VIIRS retrievals are performed using a VIIRS branch of CHIMAERA that limits available MODIS channel set. Even though in that mode certain MODIS products such as multilayer cloud map are not available, the cloud retrieval remains fully equivalent to operational Data Collection 6.
Information content of OCO-2 oxygen A-band channels for retrieving marine liquid cloud properties
NASA Astrophysics Data System (ADS)
Richardson, Mark; Stephens, Graeme L.
2018-03-01
Information content analysis is used to select channels for a marine liquid cloud retrieval using the high-spectral-resolution oxygen A-band instrument on NASA's Orbiting Carbon Observatory-2 (OCO-2). Desired retrieval properties are cloud optical depth, cloud-top pressure and cloud pressure thickness, which is the geometric thickness expressed in hectopascals. Based on information content criteria we select a micro-window of 75 of the 853 functioning OCO-2 channels spanning 763.5-764.6 nm and perform a series of synthetic retrievals with perturbed initial conditions. We estimate posterior errors from the sample standard deviations and obtain ±0.75 in optical depth and ±12.9 hPa in both cloud-top pressure and cloud pressure thickness, although removing the 10 % of samples with the highest χ2 reduces posterior error in cloud-top pressure to ±2.9 hPa and cloud pressure thickness to ±2.5 hPa. The application of this retrieval to real OCO-2 measurements is briefly discussed, along with limitations and the greatest caution is urged regarding the assumption of a single homogeneous cloud layer, which is often, but not always, a reasonable approximation for marine boundary layer clouds.
NASA Technical Reports Server (NTRS)
Wielicki, Bruce A. (Principal Investigator)
The Monthly Gridded TOA/Surface Fluxes and Clouds (SFC) product contains a month of space and time averaged Clouds and the Earth's Radiant Energy System (CERES) data for a single scanner instrument. The SFC is also produced for combinations of scanner instruments. All instantaneous shortwave, longwave, and window fluxes at the Top-of-the-Atmosphere (TOA) and surface from the CERES SSF product for a month are sorted by 1-degree spatial regions and by the local hour of observation. The mean of the instantaneous fluxes for a given region-hour bin is determined and recorded on the SFC along with other flux statistics and scene information. These average fluxes are given for both clear-sky and total-sky scenes. The regional cloud properties are column averaged and are included on the SFC. [Location=GLOBAL] [Temporal_Coverage: Start_Date=1998-01-01; Stop_Date=2000-03-31] [Spatial_Coverage: Southernmost_Latitude=-90; Northernmost_Latitude=90; Westernmost_Longitude=-180; Easternmost_Longitude=100] [Data_Resolution: Latitude_Resolution=1 degree; Longitude_Resolution=1 degree; Horizontal_Resolution_Range=100 km - < 250 km or approximately 1 degree - < 2.5 degrees; Temporal_Resolution=1 hour; Temporal_Resolution_Range=Hourly - < Daily].
NASA Astrophysics Data System (ADS)
Ludwig, V. S.; Istomina, L.; Spreen, G.
2017-12-01
Arctic sea ice concentration (SIC), the fraction of a grid cell that is covered by sea ice, is relevant for a multitude of branches: physics (heat/momentum exchange), chemistry (gas exchange), biology (photosynthesis), navigation (location of pack ice) and others. It has been observed from passive microwave (PMW) radiometers on satellites continuously since 1979, providing an almost 40-year time series. However, the resolution is limited to typically 25 km which is good enough for climate studies but too coarse to properly resolve the ice edge or to show leads. The highest resolution from PMW sensors today is 5 km of the AMSR2 89 GHz channels. Thermal infrared (TIR) and visible (VIS) measurements provide much higher resolutions between 1 km (TIR) and 30 m (VIS, regional daily coverage). The higher resolutions come at the cost of depending on cloud-free fields of view (TIR and VIS) and daylight (VIS). We present a merged product of ASI-AMSR2 SIC (PMW) and MODIS SIC (TIR) at a nominal resolution of 1 km. This product benefits from both the independence of PMW towards cloud coverage and the high resolution of TIR data. An independent validation data set has been produced from manually selected, cloud-free Landsat VIS data at 30 m resolution. This dataset is used to evaluate the performance of the merged SIC dataset. Our results show that the merged product resolves features which are smeared out by the PMW data while benefitting from the PMW data in cloudy cases and is thus indeed more than the sum of its parts.
NASA Technical Reports Server (NTRS)
Olson, William S.; Kummerow, Christian D.; Yang, Song; Petty, Grant W.; Tao, Wei-Kuo; Bell, Thomas L.; Braun, Scott A.; Wang, Yansen; Lang, Stephen E.; Johnson, Daniel E.
2004-01-01
A revised Bayesian algorithm for estimating surface rain rate, convective rain proportion, and latent heating/drying profiles from satellite-borne passive microwave radiometer observations over ocean backgrounds is described. The algorithm searches a large database of cloud-radiative model simulations to find cloud profiles that are radiatively consistent with a given set of microwave radiance measurements. The properties of these radiatively consistent profiles are then composited to obtain best estimates of the observed properties. The revised algorithm is supported by an expanded and more physically consistent database of cloud-radiative model simulations. The algorithm also features a better quantification of the convective and non-convective contributions to total rainfall, a new geographic database, and an improved representation of background radiances in rain-free regions. Bias and random error estimates are derived from applications of the algorithm to synthetic radiance data, based upon a subset of cloud resolving model simulations, and from the Bayesian formulation itself. Synthetic rain rate and latent heating estimates exhibit a trend of high (low) bias for low (high) retrieved values. The Bayesian estimates of random error are propagated to represent errors at coarser time and space resolutions, based upon applications of the algorithm to TRMM Microwave Imager (TMI) data. Errors in instantaneous rain rate estimates at 0.5 deg resolution range from approximately 50% at 1 mm/h to 20% at 14 mm/h. These errors represent about 70-90% of the mean random deviation between collocated passive microwave and spaceborne radar rain rate estimates. The cumulative algorithm error in TMI estimates at monthly, 2.5 deg resolution is relatively small (less than 6% at 5 mm/day) compared to the random error due to infrequent satellite temporal sampling (8-35% at the same rain rate).
Progress towards NASA MODIS and Suomi NPP Cloud Property Data Record Continuity
NASA Astrophysics Data System (ADS)
Platnick, S.; Meyer, K.; Holz, R.; Ackerman, S. A.; Heidinger, A.; Wind, G.; Platnick, S. E.; Wang, C.; Marchant, B.; Frey, R.
2017-12-01
The Suomi NPP VIIRS imager provides an opportunity to extend the 17+ year EOS MODIS climate data record into the next generation operational era. Similar to MODIS, VIIRS provides visible through IR observations at moderate spatial resolution with a 1330 LT equatorial crossing consistent with the MODIS on the Aqua platform. However, unlike MODIS, VIIRS lacks key water vapor and CO2 absorbing channels used for high cloud detection and cloud-top property retrievals. In addition, there is a significant mismatch in the spectral location of the 2.2 μm shortwave-infrared channels used for cloud optical/microphysical retrievals and cloud thermodynamic phase. Given these instrument differences between MODIS EOS and VIIRS S-NPP/JPSS, a merged MODIS-VIIRS cloud record to serve the science community in the coming decades requires different algorithm approaches than those used for MODIS alone. This new approach includes two parallel efforts: (1) Imager-only algorithms with only spectral channels common to VIIRS and MODIS (i.e., eliminate use of MODIS CO2 and NIR/IR water vapor channels). Since the algorithms are run with similar spectral observations, they provide a basis for establishing a continuous cloud data record across the two imagers. (2) Merged imager and sounder measurements (i.e.., MODIS-AIRS, VIIRS-CrIS) in lieu of higher-spatial resolution MODIS absorption channels absent on VIIRS. The MODIS-VIIRS continuity algorithm for cloud optical property retrievals leverages heritage algorithms that produce the existing MODIS cloud mask (MOD35), optical and microphysical properties product (MOD06), and the NOAA AWG Cloud Height Algorithm (ACHA). We discuss our progress towards merging the MODIS observational record with VIIRS in order to generate cloud optical property climate data record continuity across the observing systems. In addition, we summarize efforts to reconcile apparent radiometric biases between analogous imager channels, a critical consideration for obtaining inter-sensor climate data record continuity.
NASA Astrophysics Data System (ADS)
Dipankar, A.; Stevens, B. B.; Zängl, G.; Pondkule, M.; Brdar, S.
2014-12-01
The effect of clouds on large scale dynamics is represented in climate models through parameterization of various processes, of which the parameterization of shallow and deep convection are particularly uncertain. The atmospheric boundary layer, which controls the coupling to the surface, and which defines the scale of shallow convection, is typically 1 km in depth. Thus, simulations on a O(100 m) grid largely obviate the need for such parameterizations. By crossing this threshold of O(100m) grid resolution one can begin thinking of large-eddy simulation (LES), wherein the sub-grid scale parameterization have a sounder theoretical foundation. Substantial initiatives have been taken internationally to approach this threshold. For example, Miura et al., 2007 and Mirakawa et al., 2014 approach this threshold by doing global simulations, with (gradually) decreasing grid resolution, to understand the effect of cloud-resolving scales on the general circulation. Our strategy, on the other hand, is to take a big leap forward by fixing the resolution at O(100 m), and gradually increasing the domain size. We believe that breaking this threshold would greatly help in improving the parameterization schemes and reducing the uncertainty in climate predictions. To take this forward, the German Federal Ministry of Education and Research has initiated a project on HD(CP)2 that aims for a limited area LES at resolution O(100 m) using the new unified modeling system ICON (Zängl et al., 2014). In the talk, results from the HD(CP)2 evaluation simulation will be shown that targets high resolution simulation over a small domain around Jülich, Germany. This site is chosen because high resolution HD(CP)2 Observational Prototype Experiment took place in this region from 1.04.2013 to 31.05.2013, in order to critically evaluate the model. Nesting capabilities of ICON is used to gradually increase the resolution from the outermost domain, which is forced from the COSMO-DE data, to the innermost and finest resolution domain centered around Jülich (see Fig. 1 top panel). Furthermore, detailed analyses of the simulation results against the observation data will be presented. A reprsentative figure showing time series of column integrated water vapor (IWV) for both model and observation on 24.04.2013 is shown in bottom panel of Fig. 1.
Comparison between two lidar methods to retrieve microphysical properties of liquid-water clouds
NASA Astrophysics Data System (ADS)
Jimenez, Cristofer; Ansmann, Albert; Donovan, David; Engelmann, Ronny; Schmidt, Jörg; Wandinger, Ulla
2018-04-01
Since 2010, the Raman dual-FOV lidar system permits the retrieval of microphysical properties of liquid-water clouds during nighttime. A new robust lidar depolarization approach was recently introduced, which permits the retrieval of these properties as well, with high temporal resolution and during daytime. To implement this approach, the lidar system was upgraded, by adding a three channel depolarization receiver. The first preliminary retrieval results and a comparison between both methods is presented.
A new high resolution permafrost map of Iceland from Earth Observation data
NASA Astrophysics Data System (ADS)
Barnie, Talfan; Conway, Susan; Balme, Matt; Graham, Alastair
2017-04-01
High resolution maps of permafrost are required for ongoing monitoring of environmental change and the resulting hazards to ecosystems, people and infrastructure. However, permafrost maps are difficult to construct - direct observations require maintaining networks of sensors and boreholes in harsh environments and are thus limited in extent in space and time, and indirect observations require models or assumptions relating the measurements (e.g. weather station air temperature, basal snow temperature) to ground temperature. Operationally produced Land Surface Temperature maps from Earth Observation data can be used to make spatially contiguous estimates of mean annual skin temperature, which has been used a proxy for the presence of permafrost. However these maps are subject to biases due to (i) selective sampling during the day due to limited satellite overpass times, (ii) selective sampling over the year due to seasonally varying cloud cover, (iii) selective sampling of LST only during clearsky conditions, (iv) errors in cloud masking (v) errors in temperature emissivity separation (vi) smoothing over spatial variability. In this study we attempt to compensate for some of these problems using a bayesian modelling approach and high resolution topography-based downscaling.
Star formation: Sibling rivalry begins at birth
NASA Astrophysics Data System (ADS)
Kratter, Kaitlin M.
2015-02-01
High-resolution astronomical observations of a nearby molecular gas cloud have revealed a quadruplet of stars in the act of formation. The system is arguably the youngest multiple star system detected so far. See Letter p.213
Satellite Remote Sensing of Cirrus: An Overview
NASA Technical Reports Server (NTRS)
Minnis, Patrick
1998-01-01
The determination of cirrus properties over relatively large spatial and temporal scales will, in most instances, require the use of satellite data. Global coverage, at resolutions as high as several meters are attainable with Landsat, while temporal coverage at 1-min intervals is now available with the latest Geostationary Operational Environmental Satellite (GOES) imagers. Cirrus can be analyzed via interpretation of the radiation that they reflect or emit over a wide range of the electromagnetic spectrum. Many of these spectra and high-resolution satellite data can be used to understand certain aspects of cirrus clouds in particular situations. Production of a global climatology of cirrus clouds, however, requires compromises in spatial, temporal, and spectral coverage. This paper summarizes the state of the art and the potential for future passive remote sensing systems for both understanding cirrus formation and acquiring sufficient statistics to constrain and refine weather and climate models.
NASA Technical Reports Server (NTRS)
Katsuda, Satoru; Tsunemi, Hiroshi; Mori, Koji; Uchida, Hiroyuki; Petre, Robert; Yamada, Shinya; Akamatsu, Hiroki; Konami, Saori; Tamagawa, Toru
2012-01-01
We present high-resolution X-ray spectra of cloud-shock interaction regions in the eastern and northern rims of the Galactic supernova remnant Puppis A, using the Reflection Grating Spectrometer onboard the XMM-Newton satellite. A number of emission lines including K(alpha) triplets of He-like N, O , and Ne are clearly resolved for the first time. Intensity ratios of forbidden to resonance lines in the triplets are found to be higher than predictions by thermal emission models having plausible plasma parameters. The anomalous line ratios cannot be reproduced by effects of resonance scattering, recombination, or inner-shell ionization processes, but could be explained by charge-exchange emission that should arise at interfaces between the cold/warm clouds and the hot plasma. Our observations thus provide observational support for charge-exchange X-ray emission in supernova remnants.
NASA Astrophysics Data System (ADS)
Cho, N.; Oreopoulos, L.; Lee, D.
2017-12-01
The presentation will examine whether the diagnostic relationships between aerosol and cloud-affected quantities (precipitation, radiation) obtained from sparse temporal resolution measurements from polar orbiting satellites can potentially demonstrate actual aerosol effects on clouds with appropriate analysis. The analysis relies exclusively on Level-3 (gridded) data and comprises systematic cloud classification in terms of "microphysical cloud regimes" (µCRs), aerosol optical depth (AOD) variations relative to a region's local seasonal climatology, and exploitation of the 3-hour difference between Terra (morning) and Aqua (afternoon) overpasses. Specifically, our presentation will assess whether Aerosol-Cloud-Precipitation-Radiation interactions (ACPRI) can be diagnosed by investigating: (a) The variations with AOD of afternoon cloud-affected quantities composited by afternoon or morning µCRs; (b) µCR transition diagrams composited by morning AOD quartiles; (c) whether clouds represented by ensemble cloud effective radius - cloud optical thickness joint histograms look distinct under low and high AOD conditions when preceded or followed by specific µCRs. We will explain how our approach addresses long-standing themes of the ACPRI problem such as the optimal ways to decompose the problem by cloud class, the prevalence and detectability of 1st/2nd aerosol indirect effects and invigoration, and the effectiveness of aerosol changes in inducing cloud modification at different segments of the AOD distribution.
NASA Technical Reports Server (NTRS)
Khlopenkov, Konstantin V.; Duda, David; Thieman, Mandana; Sun-mack, Szedung; Su, Wenying; Minnis, Patrick; Bedka, Kristopher
2017-01-01
The Deep Space Climate Observatory (DSCOVR) enables analysis of the daytime Earth radiation budget via the onboard Earth Polychromatic Imaging Camera (EPIC) and National Institute of Standards and Technology Advanced Radiometer (NISTAR). EPIC delivers adequate spatial resolution imagery but only in shortwave bands (317-780 nm), while NISTAR measures the top-of-atmosphere (TOA) whole-disk radiance in shortwave and longwave broadband windows. Accurate calculation of albedo and outgoing longwave flux requires a high-resolution scene identification such as the radiance observations and cloud properties retrievals from low earth orbit (LEO, including NASA Terra and Aqua MODIS, Suomi-NPP VIIRS, and NOAA AVHRR) and geosynchronous (GEO, including GOES east and west, METEOSAT, INSAT-3D, MTSAT-2, and Himawari-8) satellite imagers. The cloud properties are derived using the Clouds and the Earth's Radiant Energy System (CERES) mission Cloud Subsystem group algorithms. These properties have to be co-located with EPIC pixels to provide the scene identification and to select anisotropic directional models (ADMs), which are then used to adjust the NISTAR-measured radiance and subsequently obtain the global daytime shortwave and longwave fluxes. This work presents an algorithm for optimal merging of selected radiance and cloud property parameters derived from multiple satellite imagers to obtain seamless global hourly composites at 5-km resolution. Selection of satellite data for each 5-km pixel is based on an aggregated rating that incorporates five parameters: nominal satellite resolution, pixel time relative to the EPIC time, viewing zenith angle, distance from day/night terminator, and probability of sun glint. To provide a smoother transition in the merged output, in regions where candidate pixel data from two satellite sources have comparable aggregated rating, the selection decision is defined by the cumulative function of the normal distribution so that abrupt changes in the visual appearance of the composite data are avoided. Higher spatial accuracy in the composite product is achieved by using the inverse mapping with gradient search during reprojection and bicubic interpolation for pixel resampling.
Cloud physics lidar: instrument description and initial measurement results.
McGill, Matthew; Hlavka, Dennis; Hart, William; Scott, V Stanley; Spinhirne, James; Schmid, Beat
2002-06-20
The new Cloud Physics Lidar (CPL) has been built for use on the NASA ER-2 high-altitude aircraft. The purpose of the CPL is to provide multiwavelength measurements of cirrus, subvisual cirrus, and aerosols with high temporal and spatial resolution. The CPL utilizes state-of-the-art technology with a high repetition rate, a low-pulse-energy laser, and photon-counting detection. The first deployment for the CPL was the Southern African Regional Science Initiative's 2000 field campaign during August and September 2000. We provide here an overview of the instrument and initial data results to illustrate the measurement capability of the CPL.
NASA Technical Reports Server (NTRS)
Molthan, Andrew; Case, Jonathan; Venner, Jason; Moreno-Madrinan, Max J.; Delgado, Francisco
2012-01-01
Two projects at NASA Marshall Space Flight Center have collaborated to develop a high resolution weather forecast model for Mesoamerica: The NASA Short-term Prediction Research and Transition (SPoRT) Center, which integrates unique NASA satellite and weather forecast modeling capabilities into the operational weather forecasting community. NASA's SERVIR Program, which integrates satellite observations, ground-based data, and forecast models to improve disaster response in Central America, the Caribbean, Africa, and the Himalayas.
NASA Langley Airborne High Spectral Resolution Lidar Instrument Description
NASA Technical Reports Server (NTRS)
Harper, David B.; Cook, Anthony; Hostetler, Chris; Hair, John W.; Mack, Terry L.
2006-01-01
NASA Langley Research Center (LaRC) recently developed the LaRC Airborne High Spectral Resolution Lidar (HSRL) to make measurements of aerosol and cloud distribution and optical properties. The Airborne HSRL has undergone as series of test flights and was successfully deployed on the Megacity Initiative: Local and Global Research Observations (MILAGRO) field mission in March 2006 (see Hair et al. in these proceedings). This paper provides an overview of the design of the Airborne HSRL and descriptions of some key subsystems unique to this instrument.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Newsom, R. K.; Sivaraman, C.; Shippert, T. R.
Accurate height-resolved measurements of higher-order statistical moments of vertical velocity fluctuations are crucial for improved understanding of turbulent mixing and diffusion, convective initiation, and cloud life cycles. The Atmospheric Radiation Measurement (ARM) Climate Research Facility operates coherent Doppler lidar systems at several sites around the globe. These instruments provide measurements of clear-air vertical velocity profiles in the lower troposphere with a nominal temporal resolution of 1 sec and height resolution of 30 m. The purpose of the Doppler lidar vertical velocity statistics (DLWSTATS) value-added product (VAP) is to produce height- and time-resolved estimates of vertical velocity variance, skewness, and kurtosismore » from these raw measurements. The VAP also produces estimates of cloud properties, including cloud-base height (CBH), cloud frequency, cloud-base vertical velocity, and cloud-base updraft fraction.« less
Surface Downward Longwave Radiation Retrieval Algorithm for GEO-KOMPSAT-2A/AMI
NASA Astrophysics Data System (ADS)
Ahn, Seo-Hee; Lee, Kyu-Tae; Rim, Se-Hun; Zo, Il-Sung; Kim, Bu-Yo
2018-05-01
This study contributes to the development of an algorithm to retrieve the Earth's surface downward longwave radiation (DLR) for 2nd Geostationary Earth Orbit KOrea Multi-Purpose SATellite (GEO-KOMPSAT-2A; GK-2A)/Advanced Meteorological Imager (AMI). Regarding simulation data for algorithm development, we referred to Clouds and the Earth's Radiant Energy System (CERES), and the European Centre for Medium-Range Weather Forecasts (ECMWF) ERA-interim reanalysis data. The clear sky DLR calculations were in good agreement with the Gangneung-Wonju National University (GWNU) Line-By-Line (LBL) model. Compared with CERES data, the Root Mean Square Error (RMSE) was 10.14Wm-2. In the case of cloudy sky DLR, we estimated the cloud base temperature empirically by utilizing cloud liquid water content (LWC) according to the cloud type. As a result, the correlation coefficients with CERES all sky DLRs were greater than 0.99. However, the RMSE between calculated DLR and CERES data was about 16.67Wm-2, due to ice clouds and problems of mismatched spatial and temporal resolutions for input data. This error may be reduced when GK-2A is launched and its products can be used as input data. Accordingly, further study is needed to improve the accuracy of DLR calculation by using high-resolution input data. In addition, when compared with BSRN surface-based observational data and retrieved DLR for all sky, the correlation coefficient was 0.86 and the RMSE was 31.55 Wm-2, which indicates relatively high accuracy. It is expected that increasing the number of experimental Cases will reduce the error.
Evaluating statistical cloud schemes: What can we gain from ground-based remote sensing?
NASA Astrophysics Data System (ADS)
Grützun, V.; Quaas, J.; Morcrette, C. J.; Ament, F.
2013-09-01
Statistical cloud schemes with prognostic probability distribution functions have become more important in atmospheric modeling, especially since they are in principle scale adaptive and capture cloud physics in more detail. While in theory the schemes have a great potential, their accuracy is still questionable. High-resolution three-dimensional observational data of water vapor and cloud water, which could be used for testing them, are missing. We explore the potential of ground-based remote sensing such as lidar, microwave, and radar to evaluate prognostic distribution moments using the "perfect model approach." This means that we employ a high-resolution weather model as virtual reality and retrieve full three-dimensional atmospheric quantities and virtual ground-based observations. We then use statistics from the virtual observation to validate the modeled 3-D statistics. Since the data are entirely consistent, any discrepancy occurring is due to the method. Focusing on total water mixing ratio, we find that the mean ratio can be evaluated decently but that it strongly depends on the meteorological conditions as to whether the variance and skewness are reliable. Using some simple schematic description of different synoptic conditions, we show how statistics obtained from point or line measurements can be poor at representing the full three-dimensional distribution of water in the atmosphere. We argue that a careful analysis of measurement data and detailed knowledge of the meteorological situation is necessary to judge whether we can use the data for an evaluation of higher moments of the humidity distribution used by a statistical cloud scheme.
NASA Astrophysics Data System (ADS)
Peers, F.; Haywood, J. M.; Francis, P. N.; Meyer, K.; Platnick, S. E.
2017-12-01
Over the South East Atlantic Ocean, biomass burning aerosols from Southern Africa are frequently observed above clouds during fire season. However, the quantification of their interactions with both radiations and clouds remains uncertain because of a lack of information on aerosol properties and on their interaction process. In the last decade, methods have been developed to retrieve aerosol optical properties above clouds from satellite measurements, especially over the South East Atlantic Ocean. Most of these methods have been applied to polar orbiting instruments which prevent the analysis of aerosols and clouds at a sub-daily scale. With its wide spatial coverage and its high temporal resolution, the geostationary instrument SEVIRI, on board the MSG platform, offers a unique opportunity to monitor aerosols in this region and to evaluate their impact on clouds and their radiative effects. In this study, we will investigate the possibility of retrieving simultaneously aerosol and cloud properties (i.e. aerosol and cloud optical thicknesses and cloud droplet effective radius) when aerosols are located above clouds. The retrieved properties will then be compared with the ones obtained from MODIS [Meyer et al., 2015] as well as observations from the CLARIFY-2017 field campaign.
NASA Technical Reports Server (NTRS)
Vogelmann, Andrew M.; Fridlind, Ann M.; Toto, Tami; Endo, Satoshi; Lin, Wuyin; Wang, Jian; Feng, Sha; Zhang, Yunyan; Turner, David D.; Liu, Yangang;
2015-01-01
Observation-based modeling case studies of continental boundary layer clouds have been developed to study cloudy boundary layers, aerosol influences upon them, and their representation in cloud- and global-scale models. Three 60 h case study periods span the temporal evolution of cumulus, stratiform, and drizzling boundary layer cloud systems, representing mixed and transitional states rather than idealized or canonical cases. Based on in situ measurements from the Routine AAF (Atmospheric Radiation Measurement (ARM) Aerial Facility) CLOWD (Clouds with Low Optical Water Depth) Optical Radiative Observations (RACORO) field campaign and remote sensing observations, the cases are designed with a modular configuration to simplify use in large-eddy simulations (LES) and single-column models. Aircraft measurements of aerosol number size distribution are fit to lognormal functions for concise representation in models. Values of the aerosol hygroscopicity parameter, kappa, are derived from observations to be approximately 0.10, which are lower than the 0.3 typical over continents and suggestive of a large aerosol organic fraction. Ensemble large-scale forcing data sets are derived from the ARM variational analysis, European Centre for Medium-Range Weather Forecasts, and a multiscale data assimilation system. The forcings are assessed through comparison of measured bulk atmospheric and cloud properties to those computed in "trial" large-eddy simulations, where more efficient run times are enabled through modest reductions in grid resolution and domain size compared to the full-sized LES grid. Simulations capture many of the general features observed, but the state-of-the-art forcings were limited at representing details of cloud onset, and tight gradients and high-resolution transients of importance. Methods for improving the initial conditions and forcings are discussed. The cases developed are available to the general modeling community for studying continental boundary clouds.
NASA Astrophysics Data System (ADS)
Vogelmann, Andrew M.; Fridlind, Ann M.; Toto, Tami; Endo, Satoshi; Lin, Wuyin; Wang, Jian; Feng, Sha; Zhang, Yunyan; Turner, David D.; Liu, Yangang; Li, Zhijin; Xie, Shaocheng; Ackerman, Andrew S.; Zhang, Minghua; Khairoutdinov, Marat
2015-06-01
Observation-based modeling case studies of continental boundary layer clouds have been developed to study cloudy boundary layers, aerosol influences upon them, and their representation in cloud- and global-scale models. Three 60 h case study periods span the temporal evolution of cumulus, stratiform, and drizzling boundary layer cloud systems, representing mixed and transitional states rather than idealized or canonical cases. Based on in situ measurements from the Routine AAF (Atmospheric Radiation Measurement (ARM) Aerial Facility) CLOWD (Clouds with Low Optical Water Depth) Optical Radiative Observations (RACORO) field campaign and remote sensing observations, the cases are designed with a modular configuration to simplify use in large-eddy simulations (LES) and single-column models. Aircraft measurements of aerosol number size distribution are fit to lognormal functions for concise representation in models. Values of the aerosol hygroscopicity parameter, κ, are derived from observations to be 0.10, which are lower than the 0.3 typical over continents and suggestive of a large aerosol organic fraction. Ensemble large-scale forcing data sets are derived from the ARM variational analysis, European Centre for Medium-Range Weather Forecasts, and a multiscale data assimilation system. The forcings are assessed through comparison of measured bulk atmospheric and cloud properties to those computed in "trial" large-eddy simulations, where more efficient run times are enabled through modest reductions in grid resolution and domain size compared to the full-sized LES grid. Simulations capture many of the general features observed, but the state-of-the-art forcings were limited at representing details of cloud onset, and tight gradients and high-resolution transients of importance. Methods for improving the initial conditions and forcings are discussed. The cases developed are available to the general modeling community for studying continental boundary clouds.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Xie, B; Dong, X; Xie, S
2012-05-18
To support the LLNL ARM infrastructure team Climate Modeling Best Estimate (CMBE) data development, the University of North Dakota (UND)'s group will provide the LLNL team the NASA CERES and ISCCP satellite retrieved cloud and radiative properties for the periods when they are available over the ARM permanent research sites. The current available datasets, to date, are as follows: the CERES/TERRA during 200003-200812; the CERES/AQUA during 200207-200712; and the ISCCP during 199601-200806. The detailed parameters list below: (1) CERES Shortwave radiative fluxes (net and downwelling); (2) CERES Longwave radiative fluxes (upwelling) - (items 1 & 2 include both all-sky andmore » clear-sky fluxes); (3) CERES Layered clouds (total, high, middle, and low); (4) CERES Cloud thickness; (5) CERES Effective cloud height; (6) CERES cloud microphysical/optical properties; (7) ISCCP optical depth cloud top pressure matrix; (8) ISCCP derived cloud types (r.g., cirrus, stratus, etc.); and (9) ISCCP infrared derived cloud top pressures. (10) The UND group shall apply necessary quality checks to the original CERES and ISCCP data to remove suspicious data points. The temporal resolution for CERES data should be all available satellite overpasses over the ARM sites; for ISCCP data, it should be 3-hourly. The spatial resolution is the closest satellite field of view observations to the ARM surface sites. All the provided satellite data should be in a format that is consistent with the current ARM CMBE dataset so that the satellite data can be easily merged into the CMBE dataset.« less
Latham, John; Bower, Keith; Choularton, Tom; Coe, Hugh; Connolly, Paul; Cooper, Gary; Craft, Tim; Foster, Jack; Gadian, Alan; Galbraith, Lee; Iacovides, Hector; Johnston, David; Launder, Brian; Leslie, Brian; Meyer, John; Neukermans, Armand; Ormond, Bob; Parkes, Ben; Rasch, Phillip; Rush, John; Salter, Stephen; Stevenson, Tom; Wang, Hailong; Wang, Qin; Wood, Rob
2012-01-01
The idea behind the marine cloud-brightening (MCB) geoengineering technique is that seeding marine stratocumulus clouds with copious quantities of roughly monodisperse sub-micrometre sea water particles might significantly enhance the cloud droplet number concentration, and thereby the cloud albedo and possibly longevity. This would produce a cooling, which general circulation model (GCM) computations suggest could—subject to satisfactory resolution of technical and scientific problems identified herein—have the capacity to balance global warming up to the carbon dioxide-doubling point. We describe herein an account of our recent research on a number of critical issues associated with MCB. This involves (i) GCM studies, which are our primary tools for evaluating globally the effectiveness of MCB, and assessing its climate impacts on rainfall amounts and distribution, and also polar sea-ice cover and thickness; (ii) high-resolution modelling of the effects of seeding on marine stratocumulus, which are required to understand the complex array of interacting processes involved in cloud brightening; (iii) microphysical modelling sensitivity studies, examining the influence of seeding amount, seed-particle salt-mass, air-mass characteristics, updraught speed and other parameters on cloud–albedo change; (iv) sea water spray-production techniques; (v) computational fluid dynamics studies of possible large-scale periodicities in Flettner rotors; and (vi) the planning of a three-stage limited-area field research experiment, with the primary objectives of technology testing and determining to what extent, if any, cloud albedo might be enhanced by seeding marine stratocumulus clouds on a spatial scale of around 100×100 km. We stress that there would be no justification for deployment of MCB unless it was clearly established that no significant adverse consequences would result. There would also need to be an international agreement firmly in favour of such action. PMID:22869798
Cloud properties and bulk microphysical properties of semi-transparent cirrus from IR Sounders
NASA Astrophysics Data System (ADS)
Stubenrauch, Claudia; Feofilov, Artem; Armante, Raymond; Guignard, Anthony
2013-04-01
Satellite observations provide a continuous survey of the atmosphere over the whole globe. IR sounders have been observing our planet since 1979. The spectral resolution has improved from TIROS-N Operational Vertical Sounders (TOVS) to the Atmospheric InfraRed Sounder (AIRS), and to the InfraRed Atmospheric Sounding Interferometer (IASI); resolution within the CO2 absorption band makes these passive sounders most sensitive to semi-transparent cirrus (about 30% of all clouds), day and night. The LMD cloud property retrieval method developed for TOVS, has been adapted to the second generation of IR sounders like AIRS and, recently, IASI. It is based on a weighted χ2 method using different channels within the 15 micron CO2 absorption band. Once the cloud physical properties (cloud pressure and IR emissivity) are retrieved, cirrus bulk microphysical properties (De and IWP) are determined from spectral emissivity differences between 8 and 12 μm. The emissivities are determined using the retrieved cloud pressure and are then compared to those simulated by the radiative transfer model. For IASI, we use the latest version of the radiative transfer model 4A (http://4aop.noveltis.com), which has been coupled with the DISORT algorithm to take into account multiple scattering of ice crystals. The code incorporates single scattering properties of column-like or aggregate-like ice crystals provided by MetOffice (Baran et al. (2001); Baran and Francis (2004)). The synergy of AIRS and two active instruments of the A-Train (lidar and radar of the CALIPSO and CloudSat missions), which provide accurate information on vertical cloud structure, allowed the evaluation of cloud properties retrieved by the weighted χ2 method. We present first results for cloud properties obtained with IASI/ Metop-A and compare them with those of AIRS and other cloud climatologies having participated in the GEWEX cloud assessment. The combination of IASI observations at 9:30 AM and 9:30 PM complement the AIRS observations at 1:30 AM and 1:30 PM local time, giving information on the diurnal cycle of clouds. References: Baran, A.J. and Francis, P.N. and Havemann, S. and Yang, P: A study of the absorption and extinction properties of hexagonal ice columns and plates in random and preferred orientation, using exact T-matrix theory and aircraft observations of cirrus, J. Quant. Spectrosc. Ra., 70, 505-518, 2001 Baran, A. J. and Francis, P. N.: On the radiative properties of cirrus cloud at solar and thermal wavelengths:A test of model consistency using high-resolution airborne radiance measurements, Q. J. Roy. Meteor. Soc.,130, 763-778, 2004.
NASA Technical Reports Server (NTRS)
Bortolot, V. J., Jr.
1972-01-01
Thirty-one high dispersion Coude spectrograms of zeta Ophiuchi and seven of zeta Persei were numerically synthesized to produce high resolution, low noise spectra in the interval 3650 A to 4350 that yield data on atomic and molecular absorption in well-defined regions of the interstellar medium. The detection threshold is improved by as much as a factor 5 over single plates. Several interstellar lines were discovered in the zeta Oph - 15km/sec cloud and the zeta Per + 13 km/sec cloud.
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.
NASA Technical Reports Server (NTRS)
Limaye, Ashutosh S.; Molthan, Andrew L.; Srikishen, Jayanthi
2010-01-01
The development of the Nebula Cloud Computing Platform at NASA Ames Research Center provides an open-source solution for the deployment of scalable computing and storage capabilities relevant to the execution of real-time weather forecasts and the distribution of high resolution satellite data to the operational weather community. Two projects at Marshall Space Flight Center may benefit from use of the Nebula system. The NASA Short-term Prediction Research and Transition (SPoRT) Center facilitates the use of unique NASA satellite data and research capabilities in the operational weather community by providing datasets relevant to numerical weather prediction, and satellite data sets useful in weather analysis. SERVIR provides satellite data products for decision support, emphasizing environmental threats such as wildfires, floods, landslides, and other hazards, with interests in numerical weather prediction in support of disaster response. The Weather Research and Forecast (WRF) model Environmental Modeling System (WRF-EMS) has been configured for Nebula cloud computing use via the creation of a disk image and deployment of repeated instances. Given the available infrastructure within Nebula and the "infrastructure as a service" concept, the system appears well-suited for the rapid deployment of additional forecast models over different domains, in response to real-time research applications or disaster response. Future investigations into Nebula capabilities will focus on the development of a web mapping server and load balancing configuration to support the distribution of high resolution satellite data sets to users within the National Weather Service and international partners of SERVIR.
NASA Technical Reports Server (NTRS)
Rogers, Raymond R.; Hostetler, Chris A.; Hair, Johnathan W.; Ferrare, Richard A.; Liu, Zhaoyan; Obland, Michael D.; Harper, David B.; Cook, Anthony L.; Powell, Kathleen A.; Vaughan, Mark A.;
2011-01-01
The Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) instrument on the Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) spacecraft has provided global, high-resolution vertical profiles of aerosols and clouds since it became operational on 13 June 2006. On 14 June 2006, the NASA Langley Research Center (LaRC) High Spectral Resolution Lidar (HSRL) was deployed aboard the NASA Langley B-200 aircraft for the first of a series of 86 underflights of the CALIPSO satellite to provide validation measurements for the CALIOP data products. To better assess the range of conditions under which CALIOP data products are produced, these validation flights were conducted under both daytime and nighttime lighting conditions, in multiple seasons, and over a large range of latitudes and aerosol and cloud conditions. This paper presents a quantitative assessment of the CALIOP 532 nm calibration (through the 532 nm total attenuated backscatter) using an internally calibrated airborne HSRL underflight data and is the most extensive study of CALIOP 532 nm calibration. Results show that average HSRL and CALIOP 532 nm total attenuated backscatter agree on average within 2.7% +/- 2.1% (CALIOP lower) at night and within 2.9 % +/- 3.9% (CALIOP lower) during the day., demonstrating the accuracy of the CALIOP 532 nm calibration algorithms. Additionally, comparisons with HSRL show consistency of the CALIOP calibration before and after the laser switch in 2009 as well as improvements in the daytime version 3 calibration scheme compared with the version 2 calibration scheme. Potential systematic uncertainties in the methodology relevant to validating satellite lidar measurements with an airborne lidar system are discussed and found to be less than 3.7% for this validation effort with HSRL. Results from this study are also compared to those from prior assessments of CALIOP calibration and attenuated backscatter.
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.
Unusually high rotational temperature of the CN radical
NASA Astrophysics Data System (ADS)
Krełowski, J.; Galazutdinov, G.; Beletsky, Y.
2011-07-01
We analyse a high-resolution, high signal-to-noise spectrogram of the hot reddened star Trumpler 16 112 to find relationships between the physical parameters of the intervening interstellar medium (e.g., the rotational temperature of the CN radical) and the intensities of interstellar lines/bands. We report on the discovery of an interstellar cloud that shows an exceptionally high rotational temperature of CN (4.5 K) and unusually strong Ca I and Fe I interstellar lines. This rare CaFe-type cloud seemingly contains no diffuse band carriers. Based on observations collected at the European Organisation for Astronomical Research in the Southern Hemisphere, Chile. Programs 073.D-0609(A) and 082.C-0566(A).
Cloud Photogrammetry from Space
NASA Astrophysics Data System (ADS)
Zaksek, K.; Gerst, A.; von der Lieth, J.; Ganci, G.; Hort, M.
2015-04-01
The most commonly used method for satellite cloud top height (CTH) compares brightness temperature of the cloud with the atmospheric temperature profile. Because of the uncertainties of this method, we propose a photogrammetric approach. As clouds can move with high velocities, even instruments with multiple cameras are not appropriate for accurate CTH estimation. Here we present two solutions. The first is based on the parallax between data retrieved from geostationary (SEVIRI, HRV band; 1000 m spatial resolution) and polar orbiting satellites (MODIS, band 1; 250 m spatial resolution). The procedure works well if the data from both satellites are retrieved nearly simultaneously. However, MODIS does not retrieve the data at exactly the same time as SEVIRI. To compensate for advection in the atmosphere we use two sequential SEVIRI images (one before and one after the MODIS retrieval) and interpolate the cloud position from SEVIRI data to the time of MODIS retrieval. CTH is then estimated by intersection of corresponding lines-of-view from MODIS and interpolated SEVIRI data. The second method is based on NASA program Crew Earth observations from the International Space Station (ISS). The ISS has a lower orbit than most operational satellites, resulting in a shorter minimal time between two images, which is needed to produce a suitable parallax. In addition, images made by the ISS crew are taken by a full frame sensor and not a push broom scanner that most operational satellites use. Such data make it possible to observe also short time evolution of clouds.
Ship trail/cloud dynamic effects from Apollo-Soyuz photograph July 16, 1975
DOE Office of Scientific and Technical Information (OSTI.GOV)
Porch, W.M.; Kao, Chih-yue J.; Kyle, T.G.
1988-01-01
We describe in this paper the results of a preliminary analysis of a ship trail photograph taken by the Apollo-Soyuz crew at 22:21 GMT on 16 July 1975. The photograph was taken from an altitude of 174 km and shows three separate ship trails with two of the trails intersecting. Because these photographs were taken from a non-geosynchronous satellite with a high-resolution camera, the quality of the photograph provides more detail than is usually obtained from meteorological satellites (minimum spatial resolution 14 m compared to 57 m from Landsat). The photograph not only shows enhanced detail of the ship trailsmore » themselves, but also cloud free bands generated by the ship trails. The ship trails have maximum photographed widths of 3--6 km. These cloud free bands are an obvious indication of the importance of ship trail cloud dynamics to ship trial development. These cloud dynamical effects are driven both by the initial energy release of the ship's power plant and by latent heat release from the aerosol nucleation process. Since the aerosol nucleation process is the key to understanding ocean aerosol/cloud interactions, it is important to partition these two processes in the ship trial development. We will describe in this paper preliminary numerical modeling efforts to simulate the ship trails using only the energy release from the ship and thereby give an indication of how much more energy input may be required from the nucleation process. 12 refs., 6 figs.« less
Optimizing UV Index determination from broadband irradiances
NASA Astrophysics Data System (ADS)
Tereszchuk, Keith A.; Rochon, Yves J.; McLinden, Chris A.; Vaillancourt, Paul A.
2018-03-01
A study was undertaken to improve upon the prognosticative capability of Environment and Climate Change Canada's (ECCC) UV Index forecast model. An aspect of that work, and the topic of this communication, was to investigate the use of the four UV broadband surface irradiance fields generated by ECCC's Global Environmental Multiscale (GEM) numerical prediction model to determine the UV Index. The basis of the investigation involves the creation of a suite of routines which employ high-spectral-resolution radiative transfer code developed to calculate UV Index fields from GEM forecasts. These routines employ a modified version of the Cloud-J v7.4 radiative transfer model, which integrates GEM output to produce high-spectral-resolution surface irradiance fields. The output generated using the high-resolution radiative transfer code served to verify and calibrate GEM broadband surface irradiances under clear-sky conditions and their use in providing the UV Index. A subsequent comparison of irradiances and UV Index under cloudy conditions was also performed. Linear correlation agreement of surface irradiances from the two models for each of the two higher UV bands covering 310.70-330.0 and 330.03-400.00 nm is typically greater than 95 % for clear-sky conditions with associated root-mean-square relative errors of 6.4 and 4.0 %. However, underestimations of clear-sky GEM irradiances were found on the order of ˜ 30-50 % for the 294.12-310.70 nm band and by a factor of ˜ 30 for the 280.11-294.12 nm band. This underestimation can be significant for UV Index determination but would not impact weather forecasting. Corresponding empirical adjustments were applied to the broadband irradiances now giving a correlation coefficient of unity. From these, a least-squares fitting was derived for the calculation of the UV Index. The resultant differences in UV indices from the high-spectral-resolution irradiances and the resultant GEM broadband irradiances are typically within 0.2-0.3 with a root-mean-square relative error in the scatter of ˜ 6.6 % for clear-sky conditions. Similar results are reproduced under cloudy conditions with light to moderate clouds, with a relative error comparable to the clear-sky counterpart; under strong attenuation due to clouds, a substantial increase in the root-mean-square relative error of up to 35 % is observed due to differing cloud radiative transfer models.
NASA Astrophysics Data System (ADS)
Ghedira, H.; Eissa, Y.
2012-12-01
Global horizontal irradiance (GHI) retrievals at the surface of any given location could be used for preliminary solar resource assessments. More accurately, the direct normal irradiance (DNI) and diffuse horizontal irradiance (DHI) are also required to estimate the global tilt irradiance, mainly used for fixed flat plate collectors. Two different satellite-based models for solar irradiance retrievals have been applied over the desert environment of the United Arab Emirates (UAE). Both models employ channels of the SEVIRI instrument, onboard the geostationary satellite Meteosat Second Generation, as their main inputs. The satellite images used in this study have a temporal resolution of 15-min and a spatial resolution of 3-km. The objective of this study is to compare between the GHI retrieved using the Heliosat-2 method and an artificial neural network (ANN) ensemble method over the UAE. The high-resolution visible channel of SEVIRI is used in the Heliosat-2 method to derive the cloud index. The cloud index is then used to compute the cloud transmission, while the cloud-free GHI is computed from the Linke turbidity factor. The product of the cloud transmission and the cloud-free GHI denotes the estimated GHI. A constant underestimation is observed in the estimated GHI over the dataset available in the UAE. Therefore, the cloud-free DHI equation in the model was recalibrated to fix the bias. After recalibration, results over the UAE show a root mean square error (RMSE) value of 10.1% and a mean bias error (MBE) of -0.5%. As for the ANN approach, six thermal channels of SEVIRI were used to estimate the DHI and the total optical depth of the atmosphere (δ). An ensemble approach is employed to obtain a better generalizability of the results, as opposed to using one single weak network. The DNI is then computed from the estimated δ using the Beer-Bouguer-Lambert law. The GHI is computed from the DNI and DHI estimates. The RMSE for the estimated GHI obtained over an independent dataset over the UAE is 7.2% and the MBE is +1.9%. The results obtained by the two methods have shown that both the recalibrated Heliosat-2 and the ANN ensemble methods estimate the GHI at a 15-min resolution with high accuracy. The advantage of the ANN ensemble approach is that it derives the GHI from accurate DNI and DHI estimates. The DNI and DHI estimates are valuable when computing the global tilt irradiance. Also, accurate DNI estimates are beneficial for preliminary site selection for concentrating solar powered plants.
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.
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.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Nicoll, Ken A.; O'Connor, E.
Large-scale properties of clouds such as lifetime, optical thickness, and precipitation are all dependent on small-scale cloud microphysical processes. Such processes determine when droplets will grow or shrink, their size, and the number of cloud droplets. Although our understanding of cloud microphysics has vastly improved over the past several decades with the development of remote sensing methods such as lidar and radar, there remain a number of processes that are not well understood, such as the effect of electrical charge on cloud microphysics. To understand the various processes and feedback mechanisms, high-vertical–resolution observations are required. Radiosondes provide an ideal platformmore » for providing routine vertical profiles of in situ measurements at any location (with a vertical resolution of a few meters). Modified meteorological radiosondes have been extensively developed at the University of Reading for measuring cloud properties, to allow measurements beyond the traditional thermodynamic quantities (pressure, temperature and relative humidity) to be obtained cost-effectively. This project aims to investigate a number of cloud processes in which in situ cloud observations from these modified radiosondes can provide information either complementary to or not obtainable by lidar/radar systems. During two intensive operational periods (IOPs) in May and August 2014 during deployment to Hyytiälä, Finland, the Atmospheric Radiation Measurement (ARM) Climate Research Facility’s Second ARM Mobile Facility (AMF2) launched a total of 24 instrumented radiosondes through a number of different cloud types ranging from low-level stratiform cloud to cumulonimbus. Twelve balloon flights of an accelerometer turbulence sensor were made, which detected significant turbulence on eleven of these flights. Most of the turbulent episodes encountered were due to convective processes, but several were associated with the transition from troposphere to stratosphere at the tropopause. Similarities in the location of turbulent layers were generally found between the balloon turbulence sensor and the Ka-band radar, but with discrepancies between the orders of magnitude of turbulence detected. The reason for these discrepancies is the subject of future work.« less
NASA Technical Reports Server (NTRS)
Smith, William L.; Revercomb, H. E.; Howell, H. B.; Lin, M.-X.
1990-01-01
High resolution infrared radiance spectra achieved from the NASA ER2 airborne HIS experiment are used to analyze the spectral emissivity properties of cirrus clouds within the 8 to 12 micron atmospheric window region. Observations show that the cirrus emissivity generally decreases with increasing wavenumber (i.e., decreasing wavelength) within this band. A very abrupt decrease in emissivity (increase in brightness temperature) exists between 930/cm (10.8 microns) and 1000/cm (10.0 microns), the magnitude of the change being associated with the cirrus optical thickness as observed by lidar. The HIS observations are consistent with theoretical calculations of the spectral absorption coefficient for ice. The HIS observations imply that cirrus clouds can be detected unambiguously from the difference in brightness temperatures observed within the 8.2 and 11.0 micron window regions of the HIRS sounding radiometer flying on the operational NOAA satellites. This ability is demonstrated using simultaneous 25 km resolution HIRS observations and 1 km resolution AVHRR imagery achieved from the NOAA-9 satellite. Finally, the cirrus cloud location estimates combined with the 6.7 micron channel moisture imagery portray the boundaries of the ice/vapor phase of the upper troposphere moisture. This phase distinction is crucial for infrared radiative transfer considerations for weather and climate models, since upper tropospheric water vapor has little effect on the Earth's outgoing radiation whereas cirrus clouds have a very large attenuating effect.
NASA Technical Reports Server (NTRS)
Zhou, Daniel K.; Liu, Xu; Larar, Allen M.
2008-01-01
Ultraspectral resolution infrared spectral radiance obtained from near nadir observations provide atmospheric, surface, and cloud property information. The intent of the measurement of tropospheric thermodynamic state and trace abundances is the initialization of climate models and the monitoring of air quality. The NPOESS Airborne Sounder Testbed-Interferometer (NAST-I), designed to support the development of future satellite temperature and moisture sounders, aboard high altitude aircraft has been collecting data throughout many field campaigns. An advanced retrieval algorithm developed with NAST-I is now applied to satellite data collected with the Atmospheric InfraRed Sounder (AIRS) on the Aqua satellite launched on 4 May 2002 and the Infrared Atmospheric Sounding Interferometer (IASI) on the MetOp satellite launched on October 19, 2006. These instruments possess an ultra-spectral resolution, for example, both IASI and NAST-I have 0.25 cm-1 and a spectral coverage from 645 to 2760 cm-1. The retrieval algorithm with a fast radiative transfer model, including cloud effects, is used for atmospheric profile and cloud parameter retrieval. The physical inversion scheme has been developed, dealing with cloudy as well as cloud-free radiance observed with ultraspectral infrared sounders, to simultaneously retrieve surface, atmospheric thermodynamic, and cloud microphysical parameters. A fast radiative transfer model, which applies to the clouded atmosphere, is used for atmospheric profile and cloud parameter retrieval. A one-dimensional (1-d) variational multi-variable inversion solution is used to improve an iterative background state defined by an eigenvector-regression-retrieval. The solution is iterated in order to account for non-linearity in the 1-d variational solution. It is shown that relatively accurate temperature and moisture retrievals can be achieved below optically thin clouds. For optically thick clouds, accurate temperature and moisture profiles down to cloud top level are obtained. For both optically thin and thick cloud situations, the cloud top height can be retrieved with relatively high accuracy (i.e., error less than 1 km). Retrievals of atmospheric soundings, surface properties, and cloud microphysical properties with the AIRS and IASI observations are obtained and presented. These retrievals are further inter-compared with those obtained from airborne FTS system, such as the NPOESS Airborne Sounder Testbed? Interferometer (NAST I), dedicated dropsondes, radiosondes, and ground based Raman Lidar. The capabilities of satellite ultra-spectral sounder such as the AIRS and IASI are investigated. These advanced satellite ultraspectral infrared instruments are now playing an important role in satellite meteorological observation for numerical weather prediction.
NASA Astrophysics Data System (ADS)
Neubauer, David; Christensen, Matthew W.; Poulsen, Caroline A.; Lohmann, Ulrike
2017-11-01
Aerosol-cloud interactions (ACIs) are uncertain and the estimates of the ACI effective radiative forcing (ERFaci) magnitude show a large variability. Within the Aerosol_cci project the susceptibility of cloud properties to changes in aerosol properties is derived from the high-resolution AATSR (Advanced Along-Track Scanning Radiometer) data set using the Cloud-Aerosol Pairing Algorithm (CAPA) (as described in our companion paper) and compared to susceptibilities from the global aerosol climate model ECHAM6-HAM2 and MODIS-CERES (Moderate Resolution Imaging Spectroradiometer - Clouds and the Earth's Radiant Energy System) data. For ECHAM6-HAM2 the dry aerosol is analysed to mimic the effect of CAPA. Furthermore the analysis is done for different environmental regimes. The aerosol-liquid water path relationship in ECHAM6-HAM2 is systematically stronger than in AATSR-CAPA data and cannot be explained by an overestimation of autoconversion when using diagnostic precipitation but rather by aerosol swelling in regions where humidity is high and clouds are present. When aerosol water is removed from the analysis in ECHAM6-HAM2 the strength of the susceptibilities of liquid water path, cloud droplet number concentration and cloud albedo as well as ERFaci agree much better with those of AATSR-CAPA or MODIS-CERES. When comparing satellite-derived to model-derived susceptibilities, this study finds it more appropriate to use dry aerosol in the computation of model susceptibilities. We further find that the statistical relationships inferred from different satellite sensors (AATSR-CAPA vs. MODIS-CERES) as well as from ECHAM6-HAM2 are not always of the same sign for the tested environmental conditions. In particular the susceptibility of the liquid water path is negative in non-raining scenes for MODIS-CERES but positive for AATSR-CAPA and ECHAM6-HAM2. Feedback processes like cloud-top entrainment that are missing or not well represented in the model are therefore not well constrained by satellite observations. In addition to aerosol swelling, wet scavenging and aerosol processing have an impact on liquid water path, cloud albedo and cloud droplet number susceptibilities. Aerosol processing leads to negative liquid water path susceptibilities to changes in aerosol index (AI) in ECHAM6-HAM2, likely due to aerosol-size changes by aerosol processing. Our results indicate that for statistical analysis of aerosol-cloud interactions the unwanted effects of aerosol swelling, wet scavenging and aerosol processing need to be minimised when computing susceptibilities of cloud variables to changes in aerosol.
Polar cloud observatory at Ny-Ålesund in GRENE Arctic Climate Change Research Project
NASA Astrophysics Data System (ADS)
Yamanouchi, Takashi; Takano, Toshiaki; Shiobara, Masataka; Okamoto, Hajime; Koike, Makoto; Ukita, Jinro
2016-04-01
Cloud is one of the main processes in the climate system and especially a large feed back agent for Arctic warming amplification (Yoshimori et al., 2014). From this reason, observation of polar cloud has been emphasized and 95 GHz cloud profiling radar in high precision was established at Ny-Ålesund, Svalbard in 2013 as one of the basic infrastructure in the GRENE (Green Network of Excellence Program) Arctic Climate Change Research Project. The radar, "FALCON-A", is a FM-CW (frequency modulated continuous wave) Doppler radar, developed for Arctic use by Chiba University (PI: T. Takano) in 2012, following its prototype, "FALCON-1" which was developed in 2006 (Takano et al., 2010). The specifications of the radar are, central frequency: 94.84 GHz; antenna power: 1 W; observation height: up to 15 km; range resolution: 48 m; beam width: 0.2 degree (15 m at 5 km); Doppler width: 3.2 m/s; time interval: 10 sec, and capable of archiving high sensitivity and high spatial and time resolution. An FM-CW type radar realizes similar sensitivity with much smaller parabolic antennas separated 1.4 m from each other used for transmitting and receiving the wave. Polarized Micro-Pulse Lidar (PMPL, Sigma Space MPL-4B-IDS), which is capable to measure the backscatter and depolarization ratio, has also been deployed to Ny-Ålesund in March 2012, and now operated to perform collocated measurements with FALCON-A. Simultaneous measurement data from collocated PMPL and FALCON-A are available for synergetic analyses of cloud microphysics. Cloud mycrophysics, such as effective radius of ice particles and ice water content, are obtained from the analysis based on algorithm, which is modified for ground-based measurements from Okamoto's retrieval algorithm for satellite based cloud profiling radar and lidar (CloudSat and CALIPSO; Okamoto et al., 2010). Results of two years will be shown in the presentation. Calibration is a point to derive radar reflectivity (dBZ) from original intensity data. Degradation of transmission power was monitored and sensitivity of receiving system was derived with estimating antenna gain by using radio wave absorber and considering antenna geometry of two antenna system. In order to estimate final results, altitude dependent detection limit curve was also calculated. Original intensity data in real time and calibrated radar reflectivity data are archived on "Arctic Data archive System (ADS)". Other collocated observations were made with fog monitor (particle size distribution), MPS (particle image) for continuous measurements at Zeppelin Mountain, 450 m height a. s. l., and tethered balloon for intense observing period. From these measurements together with aerosol and meteorological monitoring made by collaborating institutes (Stockholm University, University of Florence, AWI, NILU, NCAR and NPI) microphysics of low level cloud and aerosol-cloud interactions are discussed. Ground based remote sensors provide a powerful validation for satellite cloud observations. Radar reflectivity (dBZ) by FALCON-A was compared with that by CPR on CloudSAT during several overpasses around Ny-Ålesund, and though some difference due to the different vertical resolution was seen, overall agreement was confirmed. We are planning to establish Ny-Ålesund observatory as the super site for validation for EarthCARE (JAXA-ESA) mission.
A Post-AGB Star in the Small Magellanic Cloud Observed with the Spitzer Infrared Spectrograph
2006-10-23
spectral features, MSX SMC 029, in the Small Magellanic Cloud (SMC) usimg the low-resolution modules of the Infrared Spectrograph on the Spitzer Space ...029, in the Small Magellanic Cloud (SMC) using the low-resolution modules of the Infrared Spectrograph on the Spitzer Space Telescope. A cool dust... outer atmosphere expands and pulsates, pushing gas away from the star where it can cool and condense into dust grains. The resulting circumstellar dust
Technical development to improve satellite sounding over radiatively complex terrain
NASA Technical Reports Server (NTRS)
Schreiner, A. J.
1985-01-01
High resolution topography was acquired and applied on the McIDAS system. A technique for finding the surface skin temperature in the presence of cloud and reflected sunlight was implemented in the ALPEX retrieval software and the variability of surface emissivity at microwave wavelength was examined. Data containing raw radiances for all HIRS and MSU channels for NOAA-6 and 7 were used. METEOSAT data were used to derive cloud drift and water vapor winds over the Alpine region.
Use of MODIS Cloud Top Pressure to Improve Assimilation Yields of AIRS Radiances in GSI
NASA Technical Reports Server (NTRS)
Zavodsky, Bradley; Srikishen, Jayanthi
2014-01-01
Radiances from hyperspectral sounders such as the Atmospheric Infrared Sounder (AIRS) are routinely assimilated both globally and regionally in operational numerical weather prediction (NWP) systems using the Gridpoint Statistical Interpolation (GSI) data assimilation system. However, only thinned, cloud-free radiances from a 281-channel subset are used, so the overall percentage of these observations that are assimilated is somewhere on the order of 5%. Cloud checks are performed within GSI to determine which channels peak above cloud top; inaccuracies may lead to less assimilated radiances or introduction of biases from cloud-contaminated radiances.Relatively large footprint from AIRS may not optimally represent small-scale cloud features that might be better resolved by higher-resolution imagers like the Moderate Resolution Imaging Spectroradiometer (MODIS). Objective of this project is to "swap" the MODIS-derived cloud top pressure (CTP) for that designated by the AIRS-only quality control within GSI to test the hypothesis that better representation of cloud features will result in higher assimilated radiance yields and improved forecasts.
Assessment of dust aerosol effect on cloud properties over Northwest China using CERES SSF data
NASA Astrophysics Data System (ADS)
Huang, J.; Wang, X.; Wang, T.; Su, J.; Minnis, P.; Lin, B.; Hu, Y.; Yi, Y.
Dust aerosols not only have direct effects on the climate through reflection and absorption of the short and long wave radiation but also modify cloud properties such as the number concentration and size of cloud droplets indirect effect and contribute to diabatic heating in the atmosphere that often enhances cloud evaporation and reduces the cloud water path In this study indirect and semi-direct effects of dust aerosols are analyzed over eastern Asia using two years June 2002 to June 2004 of CERES Clouds and the Earth s Radiant Energy Budget Scanner and MODIS MODerate Resolution Imaging Spectroradiometer Aqua Edition 1B SSF Single Scanner Footprint data sets The statistical analysis shows evidence for both indirect and semi-direct effect of Asia dust aerosols The dust appears to reduce the ice cloud effective particle diameter and increase high cloud amount On average ice cloud effective particle diameters of cirrus clouds under dust polluted conditions dusty cloud are 11 smaller than those derived from ice clouds in dust-free atmospheric environments The water paths of dusty clouds are also considerably smaller than those of dust-free clouds Dust aerosols could warm clouds thereby increasing the evaporation of cloud droplets resulting in reduced cloud water path semi-direct effect The semi-direct effect may be dominated the interaction between dust aerosols and clouds over arid and semi-arid areas and partly contribute to reduced precipitation
NASA Technical Reports Server (NTRS)
Wielicki, Bruce A. (Principal Investigator)
The Monthly Gridded TOA/Surface Fluxes and Clouds (SFC) product contains a month of space and time averaged Clouds and the Earth's Radiant Energy System (CERES) data for a single scanner instrument. The SFC is also produced for combinations of scanner instruments. All instantaneous shortwave, longwave, and window fluxes at the Top-of-the-Atmosphere (TOA) and surface from the CERES SSF product for a month are sorted by 1-degree spatial regions and by the local hour of observation. The mean of the instantaneous fluxes for a given region-hour bin is determined and recorded on the SFC along with other flux statistics and scene information. These average fluxes are given for both clear-sky and total-sky scenes. The regional cloud properties are column averaged and are included on the SFC. [Location=GLOBAL] [Temporal_Coverage: Start_Date=1998-01-01; Stop_Date=2003-12-31] [Spatial_Coverage: Southernmost_Latitude=-90; Northernmost_Latitude=90; Westernmost_Longitude=-180; Easternmost_Longitude=100] [Data_Resolution: Latitude_Resolution=1 degree; Longitude_Resolution=1 degree; Horizontal_Resolution_Range=100 km - < 250 km or approximately 1 degree - < 2.5 degrees; Temporal_Resolution=1 hour; Temporal_Resolution_Range=Hourly - < Daily].
NASA Technical Reports Server (NTRS)
Wielicki, Bruce A. (Principal Investigator)
The Monthly Gridded TOA/Surface Fluxes and Clouds (SFC) product contains a month of space and time averaged Clouds and the Earth's Radiant Energy System (CERES) data for a single scanner instrument. The SFC is also produced for combinations of scanner instruments. All instantaneous shortwave, longwave, and window fluxes at the Top-of-the-Atmosphere (TOA) and surface from the CERES SSF product for a month are sorted by 1-degree spatial regions and by the local hour of observation. The mean of the instantaneous fluxes for a given region-hour bin is determined and recorded on the SFC along with other flux statistics and scene information. These average fluxes are given for both clear-sky and total-sky scenes. The regional cloud properties are column averaged and are included on the SFC. [Location=GLOBAL] [Temporal_Coverage: Start_Date=1998-01-01; Stop_Date=2005-12-31] [Spatial_Coverage: Southernmost_Latitude=-90; Northernmost_Latitude=90; Westernmost_Longitude=-180; Easternmost_Longitude=100] [Data_Resolution: Latitude_Resolution=1 degree; Longitude_Resolution=1 degree; Horizontal_Resolution_Range=100 km - < 250 km or approximately 1 degree - < 2.5 degrees; Temporal_Resolution=1 hour; Temporal_Resolution_Range=Hourly - < Daily].
NASA Technical Reports Server (NTRS)
Wielicki, Bruce A. (Principal Investigator)
The Monthly Gridded TOA/Surface Fluxes and Clouds (SFC) product contains a month of space and time averaged Clouds and the Earth's Radiant Energy System (CERES) data for a single scanner instrument. The SFC is also produced for combinations of scanner instruments. All instantaneous shortwave, longwave, and window fluxes at the Top-of-the-Atmosphere (TOA) and surface from the CERES SSF product for a month are sorted by 1-degree spatial regions and by the local hour of observation. The mean of the instantaneous fluxes for a given region-hour bin is determined and recorded on the SFC along with other flux statistics and scene information. These average fluxes are given for both clear-sky and total-sky scenes. The regional cloud properties are column averaged and are included on the SFC. [Location=GLOBAL] [Temporal_Coverage: Start_Date=1998-01-01; Stop_Date=2003-10-31] [Spatial_Coverage: Southernmost_Latitude=-90; Northernmost_Latitude=90; Westernmost_Longitude=-180; Easternmost_Longitude=100] [Data_Resolution: Latitude_Resolution=1 degree; Longitude_Resolution=1 degree; Horizontal_Resolution_Range=100 km - < 250 km or approximately 1 degree - < 2.5 degrees; Temporal_Resolution=1 hour; Temporal_Resolution_Range=Hourly - < Daily].
NASA Technical Reports Server (NTRS)
Wielicki, Bruce A. (Principal Investigator)
The Monthly Gridded TOA/Surface Fluxes and Clouds (SFC) product contains a month of space and time averaged Clouds and the Earth's Radiant Energy System (CERES) data for a single scanner instrument. The SFC is also produced for combinations of scanner instruments. All instantaneous shortwave, longwave, and window fluxes at the Top-of-the-Atmosphere (TOA) and surface from the CERES SSF product for a month are sorted by 1-degree spatial regions and by the local hour of observation. The mean of the instantaneous fluxes for a given region-hour bin is determined and recorded on the SFC along with other flux statistics and scene information. These average fluxes are given for both clear-sky and total-sky scenes. The regional cloud properties are column averaged and are included on the SFC. [Location=GLOBAL] [Temporal_Coverage: Start_Date=1998-01-01; Stop_Date=2005-12-31] [Spatial_Coverage: Southernmost_Latitude=-90; Northernmost_Latitude=90; Westernmost_Longitude=-180; Easternmost_Longitude=100] [Data_Resolution: Latitude_Resolution=1 degree; Longitude_Resolution=1 degree; Horizontal_Resolution_Range=100 km - < 250 km or approximately 1 degree - < 2.5 degrees; Temporal_Resolution=1 hour; Temporal_Resolution_Range=Hourly - < Daily].
Spatial and Temporal Distribution of Clouds Observed by MODIS Onboard the Terra and Aqua Satellites
NASA Technical Reports Server (NTRS)
King, Michael D.; Platnick, Steven; Menzel, W. Paul; Ackerman, Steven A.; Hubanks, Paul A.
2012-01-01
The Moderate Resolution Imaging Spectroradiometer (MODIS) was developed by NASA and launched aboard the Terra spacecraft on December 18, 1999 and Aqua spacecraft on May 4, 2002. A comprehensive set of remote sensing algorithms for the retrieval of cloud physical and optical properties have enabled over twelve years of continuous observations of cloud properties from Terra and over nine years from Aqua. The archived products from these algorithms include 1 km pixel-level (Level-2) and global gridded Level-3 products. In addition to an extensive cloud mask, products include cloud-top properties (temperature, pressure, effective emissivity), cloud thermodynamic phase, cloud optical and microphysical parameters (optical thickness, effective particle radius, water path), as well as derived statistics. Results include the latitudinal distribution of cloud optical and radiative properties for both liquid water and ice clouds, as well as latitudinal distributions of cloud top pressure and cloud top temperature. MODIS finds the cloud fraction, as derived by the cloud mask, is nearly identical during the day and night, with only modest diurnal variation. Globally, the cloud fraction derived by the MODIS cloud mask is approx.67%, with somewhat more clouds over land during the afternoon and less clouds over ocean in the afternoon, with very little difference in global cloud cover between Terra and Aqua. Overall, cloud fraction over land is approx.55%, with a distinctive seasonal cycle, whereas the ocean cloudiness is much higher, around 72%, with much reduced seasonal variation. Cloud top pressure and temperature have distinct spatial and temporal patterns, and clearly reflect our understanding of the global cloud distribution. High clouds are especially prevalent over the northern hemisphere continents between 30 and 50 . Aqua and Terra have comparable zonal cloud top pressures, with Aqua having somewhat higher clouds (cloud top pressures lower by 100 hPa) over land due to afternoon deep convection. The coldest cloud tops (colder than 230 K) generally occur over Antarctica and the high clouds in the tropics (ITCZ and the deep convective clouds over the western tropical Pacific and Indian sub-continent).
NASA Technical Reports Server (NTRS)
Farrugia, C. J.; Burlaga, L. F.; Osherovich, V. A.; Richardson, I. G.; Freeman, M. P.; Lepping, R. P.; Lazarus, A. J.
1993-01-01
High time resolution interplanetary magnetic field and plasma measurements of an interplanetary magnetic cloud and its interaction with the earth's magnetosphere on January 14/15, 1988 are interpreted and discussed. It is argued that the data are consistent with the theoretical model of magnetic clouds as flux ropes of local straight cylindrical geometry. The data also suggest that this cloud is aligned with its axis in the ecliptic plane and pointing in the east-west direction. Evidence consisting of the intensity and directional distribution of energetic particle in the magnetic cloud argues in favor of the connectedness of the magnetic field lines to the sun's surface. The intensities of about 0.5 MeV ions is rapidly enhanced and the particles stream in a collimated beam along the magnetic field preferentially from the west of the sun. The particles travel form a flare site along the cloud magnetic field lines, which are thus presumably still attached to the sun.
Virtual Sensors: Using Data Mining to Efficiently Estimate Spectra
NASA Technical Reports Server (NTRS)
Srivastava, Ashok; Oza, Nikunj; Stroeve, Julienne
2004-01-01
Detecting clouds within a satellite image is essential for retrieving surface geophysical parameters, such as albedo and temperature, from optical and thermal imagery because the retrieval methods tend to be valid for clear skies only. Thus, routine satellite data processing requires reliable automated cloud detection algorithms that are applicable to many surface types. Unfortunately, cloud detection over snow and ice is difficult due to the lack of spectral contrast between clouds and snow. Snow and clouds are both highly reflective in the visible wavelen,ats and often show little contrast in the thermal Infrared. However, at 1.6 microns, the spectral signatures of snow and clouds differ enough to allow improved snow/ice/cloud discrimination. The recent Terra and Aqua Moderate Resolution Imaging Spectro-Radiometer (MODIS) sensors have a channel (channel 6) at 1.6 microns. Presently the most comprehensive, long-term information on surface albedo and temperature over snow- and ice-covered surfaces comes from the Advanced Very High Resolution Radiometer ( AVHRR) sensor that has been providing imagery since July 1981. The earlier AVHRR sensors (e.g. AVHRR/2) did not however have a channel designed for discriminating clouds from snow, such as the 1.6 micron channel available on the more recent AVHRR/3 or the MODIS sensors. In the absence of the 1.6 micron channel, the AVHRR Polar Pathfinder (APP) product performs cloud detection using a combination of time-series analysis and multispectral threshold tests based on the satellite's measuring channels to produce a cloud mask. The method has been found to work reasonably well over sea ice, but not so well over the ice sheets. Thus, improving the cloud mask in the APP dataset would be extremely helpful toward increasing the accuracy of the albedo and temperature retrievals, as well as extending the time-series of albedo and temperature retrievals from the more recent sensors to the historical ones. In this work, we use data mining methods to construct a model of MODIS channel 6 as a function of other channels that are common to both MODIS and AVHRR. The idea is to use the model to generate the equivalent of MODIS channel 6 for AVHRR as a function of the AVHRR equivalents to MODIS channels. We call this a Virtual Sensor because it predicts unmeasured spectra. The goal is to use this virtual channel 6. to yield a cloud mask superior to what is currently used in APP . Our results show that several data mining methods such as multilayer perceptrons (MLPs), ensemble methods (e.g., bagging), and kernel methods (e.g., support vector machines) generate channel 6 for unseen MODIS images with high accuracy. Because the true channel 6 is not available for AVHRR images, we qualitatively assess the virtual channel 6 for several AVHRR images.
NASA Astrophysics Data System (ADS)
Vadman, M.; Bemis, S. P.
2017-12-01
Even at high tectonic rates, detection of possible off-fault plastic/aseismic deformation and variability in far-field strain accumulation requires high spatial resolution data and likely decades of measurements. Due to the influence that variability in interseismic deformation could have on the timing, size, and location of future earthquakes and the calculation of modern geodetic estimates of strain, we attempt to use historical aerial photographs to constrain deformation through time across a locked fault. Modern photo-based 3D reconstruction techniques facilitate the creation of dense point clouds from historical aerial photograph collections. We use these tools to generate a time series of high-resolution point clouds that span 10-20 km across the Carrizo Plain segment of the San Andreas fault. We chose this location due to the high tectonic rates along the San Andreas fault and lack of vegetation, which may obscure tectonic signals. We use ground control points collected with differential GPS to establish scale and georeference the aerial photograph-derived point clouds. With a locked fault assumption, point clouds can be co-registered (to one another and/or the 1.7 km wide B4 airborne lidar dataset) along the fault trace to calculate relative displacements away from the fault. We use CloudCompare to compute 3D surface displacements, which reflect the interseismic strain accumulation that occurred in the time interval between photo collections. As expected, we do not observe clear surface displacements along the primary fault trace in our comparisons of the B4 lidar data against the aerial photograph-derived point clouds. However, there may be small scale variations within the lidar swath area that represent near-fault plastic deformation. With large-scale historical photographs available for the Carrizo Plain extending back to at least the 1940s, we can potentially sample nearly half the interseismic period since the last major earthquake on this portion of this fault (1857). Where sufficient aerial photograph coverage is available, this approach has the potential to illuminate complex fault zone processes for this and other major strike-slip faults.
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.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Leroy, Adam K.; Hughes, Annie; Schruba, Andreas
2016-11-01
The cloud-scale density, velocity dispersion, and gravitational boundedness of the interstellar medium (ISM) vary within and among galaxies. In turbulent models, these properties play key roles in the ability of gas to form stars. New high-fidelity, high-resolution surveys offer the prospect to measure these quantities across galaxies. We present a simple approach to make such measurements and to test hypotheses that link small-scale gas structure to star formation and galactic environment. Our calculations capture the key physics of the Larson scaling relations, and we show good correspondence between our approach and a traditional “cloud properties” treatment. However, we argue thatmore » our method is preferable in many cases because of its simple, reproducible characterization of all emission. Using, low- J {sup 12}CO data from recent surveys, we characterize the molecular ISM at 60 pc resolution in the Antennae, the Large Magellanic Cloud (LMC), M31, M33, M51, and M74. We report the distributions of surface density, velocity dispersion, and gravitational boundedness at 60 pc scales and show galaxy-to-galaxy and intragalaxy variations in each. The distribution of flux as a function of surface density appears roughly lognormal with a 1 σ width of ∼0.3 dex, though the center of this distribution varies from galaxy to galaxy. The 60 pc resolution line width and molecular gas surface density correlate well, which is a fundamental behavior expected for virialized or free-falling gas. Varying the measurement scale for the LMC and M31, we show that the molecular ISM has higher surface densities, lower line widths, and more self-gravity at smaller scales.« less
Impact of High Resolution SST Data on Regional Weather Forecasts
NASA Technical Reports Server (NTRS)
Jedlovec, Gary J.; Case, Jonathon; LaFontaine, Frank; Vazquez, Jorge; Mattocks, Craig
2010-01-01
Past studies have shown that the use of coarse resolution SST products such as from the real-time global (RTG) SST analysis[1] or other coarse resolution once-a-day products do not properly portray the diurnal variability of fluxes of heat and moisture from the ocean that drive the formation of low level clouds and precipitation over the ocean. For example, the use of high resolution MODIS SST composite [2] to initialize the Advanced Research Weather Research and Forecast (WRF) (ARW) [3] has been shown to improve the prediction of sensible weather parameters in coastal regions [4][5}. In an extend study, [6] compared the MODIS SST composite product to the RTG SST analysis and evaluated forecast differences for a 6 month period from March through August 2007 over the Florida coastal regions. In a comparison to buoy data, they found that that the MODIS SST composites reduced the bias and standard deviation over that of the RTG data. These improvements led to significant changes in the initial and forecasted heat fluxes and the resulting surface temperature fields, wind patterns, and cloud distributions. They also showed that the MODIS composite SST product, produced for the Terra and Aqua satellite overpass times, captured a component of the diurnal cycle in SSTs not represented in the RTG or other one-a-day SST analyses. Failure to properly incorporate these effects in the WRF initialization cycle led to temperature biases in the resulting short term forecasts. The forecast impact was limited in some situations however, due to composite product inaccuracies brought about by data latency during periods of long-term cloud cover. This paper focuses on the forecast impact of an enhanced MODIS/AMSR-E composite SST product designed to reduce inaccuracies due data latency in the MODIS only composite product.
NASA Astrophysics Data System (ADS)
Costa-Surós, M.; Calbó, J.; González, J. A.; Long, C. N.
2013-06-01
The cloud vertical distribution and especially the cloud base height, which is linked to cloud type, is an important characteristic in order to describe the impact of clouds in a changing climate. In this work several methods to estimate the cloud vertical structure (CVS) based on atmospheric sounding profiles are compared, considering number and position of cloud layers, with a ground based system which is taken as a reference: the Active Remote Sensing of Clouds (ARSCL). All methods establish some conditions on the relative humidity, and differ on the use of other variables, the thresholds applied, or the vertical resolution of the profile. In this study these methods are applied to 125 radiosonde profiles acquired at the ARM Southern Great Plains site during all seasons of year 2009 and endorsed by GOES images, to confirm that the cloudiness conditions are homogeneous enough across their trajectory. The overall agreement for the methods ranges between 44-88%; four methods produce total agreements around 85%. Further tests and improvements are applied on one of these methods. In addition, we attempt to make this method suitable for low resolution vertical profiles, which could be useful in atmospheric modeling. The total agreement, even when using low resolution profiles, can be improved up to 91% if the thresholds for a moist layer to become a cloud layer are modified to minimize false negatives with the current data set, thus improving overall agreement.
Validation of AIRS/AMSU Cloud Retrievals Using MODIS Cloud Analyses
NASA Technical Reports Server (NTRS)
Molnar, Gyula I.; Susskind, Joel
2005-01-01
The AIRS/AMSU (flying on the EOS-AQUA satellite) sounding retrieval methodology allows for the retrieval of key atmospheric/surface parameters under partially cloudy conditions (Susskind et al.). In addition, cloud parameters are also derived from the AIRS/AMSU observations. Within each AIRS footprint, cloud parameters at up to 2 cloud layers are determined with differing cloud top pressures and effective (product of infrared emissivity at 11 microns and physical cloud fraction) cloud fractions. However, so far the AIRS cloud product has not been rigorously evaluated/validated. Fortunately, collocated/coincident radiances measured by MODIS/AQUA (at a much lower spectral resolution but roughly an order of-magnitude higher spatial resolution than that of AIRS) are used to determine analogous cloud products from MODIS. This allows us for a rather rare and interesting possibility: the intercomparisons and mutual validation of imager vs. sounder-based cloud products obtained from the same satellite positions. First, we present results of small-scale (granules) instantaneous intercomparisons. Next, we will evaluate differences of temporally averaged (monthly) means as well as the representation of inter-annual variability of cloud parameters as presented by the two cloud data sets. In particular, we present statistical differences in the retrieved parameters of cloud fraction and cloud top pressure. We will investigate what type of cloud systems are retrieved most consistently (if any) with both retrieval schemes, and attempt to assess reasons behind statistically significant differences.
Distant Supernova Remnant Imaged by Chandra's High Resolution Camera
NASA Astrophysics Data System (ADS)
1999-09-01
The High Resolution Camera (HRC), one of the two X-ray cameras on NASA's Chandra X-ray Observatory, was placed into the focus for the first time on Monday, August 30. The first target was LMC X-1, a point-like source of X rays in the Large Magellanic Cloud. The Large Magellanic Cloud, a companion galaxy to the Milky Way, is 160,000 light years from Earth. After checking the focus with LMC X-1, Chandra observed N132D, a remnant of an exploded star in the Large Magellanic Cloud. "These were preliminary test observations," emphasized Dr. Stephen Murray, of the Harvard-Smithsonian Center for Astrophysics, principal investigator for the High Resolution Camera. "But we are very pleased with the results. All indications are that the HRC will produce X-ray images of unprecedented clarity." The N132D image shows a highly structured remnant, or shell, of 10-million-degree gas that is 80 light years across. Such a shell in the vicinity of the Sun would encompass more than fifty nearby stars. The amount of material in the N132D hot gas remnant is equal to that of 600 suns. The N132D supernova remnant appears to be colliding with a giant molecular cloud, which produces the brightening on the southern rim of the remnant. The molecular cloud, visible with a radio telescope, has the mass of 300,000 suns. The relatively weak x-radiation on the upper left shows that the shock wave is expanding into a less dense region on the edge of the molecular cloud. A number of small circular structures are visible in the central regions and a hint of a large circular loop can be seen in the upper part of the remnant. Whether the peculiar shape of the supernova remnant can be fully explained in terms of these effects, or whether they point to a peculiar cylindrically shaped explosion remains to be seen. -more- "The image is so rich in structure that it will take a while to sort out what is really going on," Murray said. "It could be multiple supernovas, or absorbing clouds in the vicinity of the supernova." The unique capabilities of the HRC stem from the close match of its imaging capability to the focusing power of the mirrors. When used with the Chandra mirrors, the HRC will make images that reveal detail as small as one-half an arc second. This is equivalent to the ability to read a stop sign at a distance of twelve miles. The checkout period for the HRC will continue for the next few weeks, during which time the team expects to acquire images of other supernova remnants, star clusters, and starburst galaxies. To follow Chandra's progress, visit the Chandra News Web site at: http://chandra.harvard.edu AND http://chandra.nasa.gov NASA's Marshall Space Flight Center in Huntsville, Alabama, manages the Chandra X-ray Observatory for NASA's Office of Space Science, NASA Headquarters, Washington, D.C. The Smithsonian Astrophysical Observatory's Chandra X-ray Center in Cambridge, Mass., manages the Chandra science program and controls the observatory for NASA. TRW Space and Electronics Group of Redondo Beach, Calif., leads the contractor team that built Chandra. High resolution digital versions of the X-ray image (300 dpi JPG, TIFF) and other information associated with this release are available on the Internet at: http://chandra.harvard.edu/photo/0050/ or via links in: http://chandra.harvard.edu
A Legacy Imaging Survey of M33.
NASA Astrophysics Data System (ADS)
Dalcanton, Julianne
2016-10-01
We propose a panoramic imaging survey of M33 to extend the M31 PHAT survey to regions with 10x higher star formation intensity and markedly lower metallicity. Deep six-filter UV/optical/IR stellar photometry will provide (1) precision measurement of the high-mass IMF slope; (2) spatially-resolved maps of the recent star formation history (SFH) with 5-10 Myr resolution; (3) maps of the cool, dusty ISM with 25 pc resolution; (4) temperatures and luminosities for 15 million stars; (5) maps of extinction law variations; and (6) 1000 star clusters with well-measured ages and masses. We will combine these products with archival multi-wavelength data to elucidate the astrophysics of the interstellar medium (ISM). We will constrain the energetics of the ISM by linking the history of stellar energy input to the observed properties of the ISM; reconcile widely-used, but discrepant, dust emission models; disentangle the drivers that control dust composition; and measure lifetimes of molecular clouds. We will survey nearly all the molecular clouds and high extinction (A_V>1) regions in M33, as well as regimes of star formation rate intensity, spiral arm strength, metallicity, and ISM pressure that are distinct from those in comparable surveys of M31 and the Magellanic Clouds. This survey adds M33 to the Milky Way, M31, and Magellanic Clouds as the fundamental calibrators of ISM physics, star-formation processes, and stellar evolution. The resulting data set will be comprehensive, highly versatile, and have tremendous legacy value. This program can only be accomplished with HST.
Wood, Robert; Ackerman, Thomas; Rasch, Philip J.; ...
2017-06-22
Anthropogenic aerosol impacts on clouds constitute the largest source of uncertainty in quantifying the radiative forcing of climate, and hinders our ability to determine Earth's climate sensitivity to greenhouse gas increases. Representation of aerosol–cloud interactions in global models is particularly challenging because these interactions occur on typically unresolved scales. Observational studies show influences of aerosol on clouds, but correlations between aerosol and clouds are insufficient to constrain aerosol forcing because of the difficulty in separating aerosol and meteorological impacts. In this commentary, we argue that this current impasse may be overcome with the development of approaches to conduct control experimentsmore » whereby aerosol particle perturbations can be introduced into patches of marine low clouds in a systematic manner. Such cloud perturbation experiments constitute a fresh approach to climate science and would provide unprecedented data to untangle the effects of aerosol particles on cloud microphysics and the resulting reflection of solar radiation by clouds. Here, the control experiments would provide a critical test of high-resolution models that are used to develop an improved representation aerosol–cloud interactions needed to better constrain aerosol forcing in global climate models.« less
G-band atmospheric radars: new frontiers in cloud physics
NASA Astrophysics Data System (ADS)
Battaglia, A.; Westbrook, C. D.; Kneifel, S.; Kollias, P.; Humpage, N.; Löhnert, U.; Tyynelä, J.; Petty, G. W.
2014-01-01
Clouds and associated precipitation are the largest source of uncertainty in current weather and future climate simulations. Observations of the microphysical, dynamical and radiative processes that act at cloud-scales are needed to improve our understanding of clouds. The rapid expansion of ground-based super-sites and the availability of continuous profiling and scanning multi-frequency radar observations at 35 and 94 GHz have significantly improved our ability to probe the internal structure of clouds in high temporal-spatial resolution, and to retrieve quantitative cloud and precipitation properties. However, there are still gaps in our ability to probe clouds due to large uncertainties in the retrievals. The present work discusses the potential of G-band (frequency between 110 and 300 GHz) Doppler radars in combination with lower frequencies to further improve the retrievals of microphysical properties. Our results show that, thanks to a larger dynamic range in dual-wavelength reflectivity, dual-wavelength attenuation and dual-wavelength Doppler velocity (with respect to a Rayleigh reference), the inclusion of frequencies in the G-band can significantly improve current profiling capabilities in three key areas: boundary layer clouds, cirrus and mid-level ice clouds, and precipitating snow.