Polarimetric Interferometry - Remote Sensing Applications

DTIC Science & Technology

2007-02-01

This lecture is mainly based on the work of S.R. Cloude and presents examples for remote sensing applications Polarimetric SAR Interferometry...PolInSAR). PolInSAR has its origins in remote sensing and was first developed for applications in 1997 using SIRC L-Band data [1,2]. In its original form it

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

NASA Astrophysics Data System (ADS)

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

2011-09-01

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

Reconstruction of 3D Shapes of Opaque Cumulus Clouds from Airborne Multiangle Imaging: A Proof-of-Concept

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).

[Investigation on remote measurement of air pollution by a method of infrared passive scanning imaging].

PubMed

Jiao, Yang; Xu, Liang; Gao, Min-Guang; Feng, Ming-Chun; Jin, Ling; Tong, Jing-Jing; Li, Sheng

2012-07-01

Passive remote sensing by Fourier-transform infrared (FTIR) spectrometry allows detection of air pollution. However, for the localization of a leak and a complete assessment of the situation in the case of the release of a hazardous cloud, information about the position and the distribution of a cloud is essential. Therefore, an imaging passive remote sensing system comprising an interferometer, a data acquisition and processing software, scan system, a video system, and a personal computer has been developed. The remote sensing of SF6 was done. The column densities of all directions in which a target compound has been identified may be retrieved by a nonlinear least squares fitting algorithm and algorithm of radiation transfer, and a false color image is displayed. The results were visualized by a video image, overlaid by false color concentration distribution image. The system has a high selectivity, and allows visualization and quantification of pollutant clouds.

Boundary Layer Remote Sensing with Combined Active and Passive Techniques: GPS Radio Occultation and High-Resolution Stereo Imaging (WindCam) Small Satellite Concept

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

Remote Sensing of Aerosols from Satellites: Why Has It Been Do Difficult to Quantify Aerosol-Cloud Interactions for Climate Assessment, and How Can We Make Progress?

NASA Technical Reports Server (NTRS)

Kahn, Ralph A.

2015-01-01

The organizers of the National Academy of Sciences Arthur M. Sackler Colloquia Series on Improving Our Fundamental Understanding of the Role of Aerosol-Cloud Interactions in the Climate System would like to post Ralph Kahn's presentation entitled Remote Sensing of Aerosols from Satellites: Why has it been so difficult to quantify aerosol-cloud interactions for climate assessment, and how can we make progress? to their public website.

Cloud Optical Depth Measured with Ground-Based, Uncooled Infrared Imagers

NASA Technical Reports Server (NTRS)

Shaw, Joseph A.; Nugent, Paul W.; Pust, Nathan J.; Redman, Brian J.; Piazzolla, Sabino

2012-01-01

Recent advances in uncooled, low-cost, long-wave infrared imagers provide excellent opportunities for remotely deployed ground-based remote sensing systems. However, the use of these imagers in demanding atmospheric sensing applications requires that careful attention be paid to characterizing and calibrating the system. We have developed and are using several versions of the ground-based "Infrared Cloud Imager (ICI)" instrument to measure spatial and temporal statistics of clouds and cloud optical depth or attenuation for both climate research and Earth-space optical communications path characterization. In this paper we summarize the ICI instruments and calibration methodology, then show ICI-derived cloud optical depths that are validated using a dual-polarization cloud lidar system for thin clouds (optical depth of approximately 4 or less).

Remote sensing of three-dimensional cirrus clouds from satellites: application to continuous-wave laser atmospheric transmission and backscattering.

PubMed

Liou, K N; Ou, Szu-Cheng; Takano, Yoshihide; Cetola, Jeffrey

2006-09-10

A satellite remote sensing methodology has been developed to retrieve 3D ice water content (IWC) and mean effective ice crystal size of cirrus clouds from satellite data on the basis of a combination of the conventional retrieval of cloud optical depth and particle size in a horizontal plane and a parameterization of the vertical cloud profile involving temperature from sounding and/or analysis. The inferred 3D cloud fields of IWC and mean effective ice crystal size associated with two impressive cirrus clouds that occurred in the vicinity of northern Oklahoma on 18 April 1997 and 9 March 2000, obtained from the Department of Energy's Atmospheric Radiation Measurement Program, have been validated against the ice crystal size distributions that were collected independently from collocated and coincident aircraft optical probe measurements. The 3D cloud results determined from satellite data have been applied to the simulation of cw laser energy propagation, and we show the significance of 3D cloud geometry and inhomogeneity and spherical atmosphere on the transmitted and backscattered laser powers. Finally, we demonstrate that the 3D cloud fields derived from satellite remote sensing can be used for the 3D laser transmission and backscattering model for tactical application.

Remote sensing of three-dimensional cirrus clouds from satellites: application to continuous-wave laser atmospheric transmission and backscattering

NASA Astrophysics Data System (ADS)

Liou, K. N.; Ou, Szu-Cheng; Takano, Yoshihide; Cetola, Jeffrey

2006-09-01

A satellite remote sensing methodology has been developed to retrieve 3D ice water content (IWC) and mean effective ice crystal size of cirrus clouds from satellite data on the basis of a combination of the conventional retrieval of cloud optical depth and particle size in a horizontal plane and a parameterization of the vertical cloud profile involving temperature from sounding and/or analysis. The inferred 3D cloud fields of IWC and mean effective ice crystal size associated with two impressive cirrus clouds that occurred in the vicinity of northern Oklahoma on 18 April 1997 and 9 March 2000, obtained from the Department of Energy's Atmospheric Radiation Measurement Program, have been validated against the ice crystal size distributions that were collected independently from collocated and coincident aircraft optical probe measurements. The 3D cloud results determined from satellite data have been applied to the simulation of cw laser energy propagation, and we show the significance of 3D cloud geometry and inhomogeneity and spherical atmosphere on the transmitted and backscattered laser powers. Finally, we demonstrate that the 3D cloud fields derived from satellite remote sensing can be used for the 3D laser transmission and backscattering model for tactical application.

Remote Sensing of Crystal Shapes in Ice Clouds

NASA Technical Reports Server (NTRS)

van Diedenhoven, Bastiaan

2017-01-01

Ice crystals in clouds exist in a virtually limitless variation of geometries. The most basic shapes of ice crystals are columnar or plate-like hexagonal prisms with aspect ratios determined by relative humidity and temperature. However, crystals in ice clouds generally display more complex structures owing to aggregation, riming and growth histories through varying temperature and humidity regimes. Crystal shape is relevant for cloud evolution as it affects microphysical properties such as fall speeds and aggregation efficiency. Furthermore, the scattering properties of ice crystals are affected by their general shape, as well as by microscopic features such as surface roughness, impurities and internal structure. To improve the representation of ice clouds in climate models, increased understanding of the global variation of crystal shape and how it relates to, e.g., location, cloud temperature and atmospheric state is crucial. Here, the remote sensing of ice crystal macroscale and microscale structure from airborne and space-based lidar depolarization observations and multi-directional measurements of total and polarized reflectances is reviewed. In addition, a brief overview is given of in situ and laboratory observations of ice crystal shape as well as the optical properties of ice crystals that serve as foundations for the remote sensing approaches. Lidar depolarization is generally found to increase with increasing cloud height and to vary with latitude. Although this variation is generally linked to the variation of ice crystal shape, the interpretation of the depolarization remains largely qualitative and more research is needed before quantitative conclusions about ice shape can be deduced. The angular variation of total and polarized reflectances of ice clouds has been analyzed by numerous studies in order to infer information about ice crystal shapes from them. From these studies it is apparent that pristine crystals with smooth surfaces are generally inconsistent with the data and thus crystal impurity, distortion or surface roughness is prevalent. However, conclusions about the dominating ice shapes are often inconclusive and contradictory and are highly dependent on the limited selection of shapes included in the investigations. Since ice crystal optical properties are mostly determined by the aspect ratios of the crystal components and their microscale structure, it is advised that remote sensing applications focus on the variation of these ice shape characteristics, rather than on the macroscale shape or habit. Recent studies use databases with nearly continuous ranges of crystal component aspect ratio and-or roughness levels to infer the variation of ice crystal shape from satellite and airborne remote sensing measurements. Here, the rationale and results of varying strategies for the remote sensing of ice crystal shape are reviewed. Observed systematic variations of ice crystal geometry with location, cloud height and atmospheric state suggested by the data are discussed. Finally, a prospective is given on the future of the remote sensing of ice cloud particle shapes.

Future of Land Remote Sensing: What is Needed

NASA Technical Reports Server (NTRS)

Goward, Samuel N.

2007-01-01

A viewgraph presentation describing the future of land remote sensing and the new technologies needed for clear views of the Earth is shown. The contents include: 1) Viewing the Earth; 2) Multi-Imagery; 3) May Missions and Sensors; 4) What is Needed; 5) Things to Think About; 6) Global Land Remote Sensing in Landsat 7 Era; 7) Seasonality; 8) Cloud Contamination; 9) NRC Decadal Study; 10) Atmospheric Attenuation; 11) Geo-Registration; 12) Orthorectification Required; 13) Band Registration with OLI; and 14) Things to Do. A viewgraph presentation describing the future of land remote sensing and the new technologies needed for clear views of the Earth is shown. The contents include: 1) Viewing the Earth; 2) Multi-Imagery; 3) May Missions and Sensors; 4) What is Needed; 5) Things to Think About; 6) Global Land Remote Sensing in Landsat 7 Era; 7) Seasonality; 8) Cloud Contamination; 9) NRC Decadal Study; 10) Atmospheric Attenuation; 11) Geo-Registration; 12) Orthorectification Required; 13) Band Registration with OLI; and 14) Things to Do.

NASA Icing Remote Sensing System Comparisons From AIRS II

NASA Technical Reports Server (NTRS)

Reehorst, Andrew L.; Brinker, David J.; Ratvasky, Thomas P.

2005-01-01

NASA has an on-going activity to develop remote sensing technologies for the detection and measurement of icing conditions aloft. A multiple instrument approach is the current emphasis of this activity. Utilizing radar, radiometry, and lidar, a region of supercooled liquid is identified. If the liquid water content (LWC) is sufficiently high, then the region of supercooled liquid cloud is flagged as being an aviation hazard. The instruments utilized for the current effort are an X-band vertical staring radar, a radiometer that measures twelve frequencies between 22 and 59 GHz, and a lidar ceilometer. The radar data determine cloud boundaries, the radiometer determines the sub-freezing temperature heights and total liquid water content, and the ceilometer refines the lower cloud boundary. Data is post-processed with a LabVIEW program with a resultant supercooled LWC profile and aircraft hazard identification. Individual remotely sensed measurements gathered during the 2003-2004 Alliance Icing Research Study (AIRS II) were compared to aircraft in-situ measurements. Comparisons between the remote sensing system s fused icing product and in-situ measurements from the research aircraft are reviewed here. While there are areas where improvement can be made, the cases examined indicate that the fused sensor remote sensing technique appears to be a valid approach.

Possibility of Cloudless Optical Remote Sensing Images Acquisition Study by Using Meteorological Satellite Observations

NASA Astrophysics Data System (ADS)

Zhang, T.; Lei, B.; Hu, Y.; Liu, K.; Gan, Y.

2018-04-01

Optical remote sensing images have been widely used in feature interpretation and geo-information extraction. All the fundamental applications of optical remote sensing, are greatly influenced by cloud coverage. Generally, the availability of cloudless images depends on the meteorological conditions for a given area. In this study, the cloud total amount (CTA) products of the Fengyun (FY) satellite were introduced to explore the meteorological changes in a year over China. The cloud information of CTA products were tested by using ZY-3 satellite images firstly. CTA products from 2006 to 2017 were used to get relatively reliable results. The window period of cloudless images acquisition for different areas in China was then determined. This research provides a feasible way to get the cloudless images acquisition window by using meteorological observations.

The Mixed-Phase Arctic Cloud Experiment (M-PACE)

NASA Technical Reports Server (NTRS)

Verlinde, J.; Harrington, J. Y.; McFarquhar, G. M.; Yannuzzi, V. T.; Avramov, A.; Greenberg, S.; Johnson, N.; Zhang, G.; Poellot, M. R.; Mather, J. H.;

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

NASA Astrophysics Data System (ADS)

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

2017-05-01

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

Satellite Analyses of Cirrus Cloud Properties During the FIRE Phase 2 Cirrus Intensive Field Observations over Kansas

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.

Validation of Cloud Optical Parameters from Passive Remote Sensing in the Arctic by using the Aircraft Measurements

NASA Astrophysics Data System (ADS)

Chen, H.; Schmidt, S.; Coddington, O.; Wind, G.; Bucholtz, A.; Segal-Rosenhaimer, M.; LeBlanc, S. E.

2017-12-01

Cloud Optical Parameters (COPs: e.g., cloud optical thickness and cloud effective radius) and surface albedo are the most important inputs for determining the Cloud Radiative Effect (CRE) at the surface. In the Arctic, the COPs derived from passive remote sensing such as from the Moderate Resolution Imaging Spectroradiometer (MODIS) are difficult to obtain with adequate accuracy owing mainly to insufficient knowledge about the snow/ice surface, but also because of the low solar zenith angle. This study aims to validate COPs derived from passive remote sensing in the Arctic by using aircraft measurements collected during two field campaigns based in Fairbanks, Alaska. During both experiments, ARCTAS (Arctic Research of the Composition of the Troposphere from Aircraft and Satellites) and ARISE (Arctic Radiation-IceBridge Sea and Ice Experiment), the Solar Spectral Flux Radiometer (SSFR) measured upwelling and downwelling shortwave spectral irradiances, which can be used to derive surface and cloud albedo, as well as the irradiance transmitted by clouds. We assess the variability of the Arctic sea ice/snow surfaces albedo through these aircraft measurements and incorporate this variability into cloud retrievals for SSFR. We then compare COPs as derived from SSFR and MODIS for all suitable aircraft underpasses of the satellites. Finally, the sensitivities of the COPs to surface albedo and solar zenith angle are investigated.

Toward the Characterization of Mixed-Phase Clouds Using Remote Sensing

NASA Astrophysics Data System (ADS)

Andronache, C.

2015-12-01

Mixed-phase clouds consist of a mixture of ice particles and liquid droplets at temperatures below 0 deg C. They are present in all seasons in many regions of the world, account for about 30% of the global cloud coverage, and are linked to cloud electrification and aircraft icing. The mix of ice particles, liquid droplets, and water vapor is unstable, and such clouds are thought to have a short lifetime. A characteristic parameter is the phase composition of mixed-phase clouds. It affects the cloud life cycle and the rate of precipitation. This parameter is important for cloud parameters retrievals by radar, lidar, and satellite and is relevant for climate modeling. The phase transformation includes the remarkable Wegener-Bergeron-Findeisen (WBF) process. The direction and the rate of the phase transformations depend on the local thermodynamic and microphysical properties. Cloud condensation nuclei (CCN) and ice nuclei (IN) particles determine to a large extent cloud microstructure and the dynamic response of clouds to aerosols. The complexity of dynamics and microphysics involved in mixed-phase clouds requires a set of observational and modeling tools that continue to be refined. Among these techniques, the remote sensing methods provide an increasing number of parameters, covering large regions of the world. Thus, a series of studies were dedicated to stratiform mixed-phase clouds revealing longer lifetime than previously thought. Satellite data and aircraft in situ measurements in deep convective clouds suggest that highly supercooled water often occurs in vigorous continental convective storms. In this study, we use cases of convective clouds to discuss the feasibility of mixed-phase clouds characterization and potential advantages of remote sensing.

Remote rainfall sensing for landslide hazard analysis

USGS Publications Warehouse

Wieczorek, Gerald F.; McWreath, Harry; Davenport, Clay

2001-01-01

Methods of assessing landslide hazards and providing warnings are becoming more advanced as remote sensing of rainfall provides more detailed temporal and spatial data on rainfall distribution. Two recent landslide disasters are examined noting the potential for using remotely sensed rainfall data for landslide hazard analysis. For the June 27, 1995, storm in Madison County, Virginia, USA, National Weather Service WSR-88D Doppler radar provided rainfall estimates based on a relation between cloud reflectivity and moisture content on a 1 sq. km. resolution every 6 minutes. Ground-based measurements of rainfall intensity and precipitation total, in addition to landslide timing and distribution, were compared with the radar-derived rainfall data. For the December 14-16, 1999, storm in Vargas State, Venezuela, infrared sensing from the GOES-8 satellite of cloud top temperatures provided the basis for NOAA/NESDIS rainfall estimates on a 16 sq. km. resolution every 30 minutes. These rainfall estimates were also compared with ground-based measurements of rainfall and landslide distribution. In both examples, the remotely sensed data either overestimated or underestimated ground-based values by up to a factor of 2. The factors that influenced the accuracy of rainfall data include spatial registration and map projection, as well as prevailing wind direction, cloud orientation, and topography.

a Cloud Boundary Detection Scheme Combined with Aslic and Cnn Using ZY-3, GF-1/2 Satellite Imagery

NASA Astrophysics Data System (ADS)

Guo, Z.; Li, C.; Wang, Z.; Kwok, E.; Wei, X.

2018-04-01

Remote sensing optical image cloud detection is one of the most important problems in remote sensing data processing. Aiming at the information loss caused by cloud cover, a cloud detection method based on convolution neural network (CNN) is presented in this paper. Firstly, a deep CNN network is used to extract the multi-level feature generation model of cloud from the training samples. Secondly, the adaptive simple linear iterative clustering (ASLIC) method is used to divide the detected images into superpixels. Finally, the probability of each superpixel belonging to the cloud region is predicted by the trained network model, thereby generating a cloud probability map. The typical region of GF-1/2 and ZY-3 were selected to carry out the cloud detection test, and compared with the traditional SLIC method. The experiment results show that the average accuracy of cloud detection is increased by more than 5 %, and it can detected thin-thick cloud and the whole cloud boundary well on different imaging platforms.

Aerosol effect on cloud droplet size as monitored from surface-based remote sensing over East China Sea region

NASA Astrophysics Data System (ADS)

Pandithurai, G.; Takamura, T.; Yamaguchi, J.; Miyagi, K.; Takano, T.; Ishizaka, Y.; Dipu, S.; Shimizu, A.

2009-07-01

The effect of increased aerosol concentrations on the low-level, non-precipitating, ice-free stratus clouds is examined using a suite of surface-based remote sensing systems. Cloud droplet effective radius and liquid water path are retrieved using cloud radar and microwave radiometer. Collocated measurements of aerosol scattering coefficient, size distribution and cloud condensation nuclei (CCN) concentrations were used to examine the response of cloud droplet size and optical thickness to increased CCN proxies. During the episodic events of increase in aerosol accumulation-mode volume distribution, the decrease in droplet size and increase in cloud optical thickness is observed. The indirect effect estimates are made for both droplet effective radius and cloud optical thickness for different liquid water path ranges and they range 0.02-0.18 and 0.005-0.154, respectively. Data are also categorized into thin and thick clouds based on cloud geometric thickness (Δz) and estimates show IE values are relatively higher for thicker clouds.

3D Radiative Aspects of the Increased Aerosol Optical Depth Near Clouds

NASA Technical Reports Server (NTRS)

Marshak, Alexander; Wen, Guoyong; Remer, Lorraine; Cahalan, Robert; Coakley, Jim

2007-01-01

To characterize aerosol-cloud interactions it is important to correctly retrieve aerosol optical depth in the vicinity of clouds. It is well reported in the literature that aerosol optical depth increases with cloud cover. Part of the increase comes from real physics as humidification; another part, however, comes from 3D cloud effects in the remote sensing retrievals. In many cases it is hard to say whether the retrieved increased values of aerosol optical depth are remote sensing artifacts or real. In the presentation, we will discuss how the 3D cloud affects can be mitigated. We will demonstrate a simple model that can assess the enhanced illumination of cloud-free columns in the vicinity of clouds. This model is based on the assumption that the enhancement in the cloud-free column radiance comes from the enhanced Rayleigh scattering due to presence of surrounding clouds. A stochastic cloud model of broken cloudiness is used to simulate the upward flux.

The NASA Icing Remote Sensing System

NASA Technical Reports Server (NTRS)

Reehorst, Andrew L.; Brinker, David J.; Ratvasky, Thomas P.; Ryerson, Charles C.; Koenig, George G.

2005-01-01

NASA and the U.S. Army Cold Regions Research and Engineering Laboratory (CRREL) have an on-going activity to develop remote sensing technologies for the detection and measurement of icing conditions aloft. A multiple instrument approach is the current emphasis of this activity. Utilizing radar, radiometry, and lidar, a region of supercooled liquid is identified. If the liquid water content (LWC) is sufficiently high, then the region of supercooled liquid cloud is flagged as being an aviation hazard. The instruments utilized for the current effort are an X-band vertical staring radar, a radiometer that measures twelve frequencies between 22 and 59 GHz, and a lidar ceilometer. The radar data determine cloud boundaries, the radiometer determines the sub-freezing temperature heights and total liquid water content, and the ceilometer refines the lower cloud boundary. Data are post-processed with a LabVIEW program with a resultant supercooled LWC profile and aircraft hazard identification. Remotely sensed measurements gathered during the 2003-2004 Alliance Icing Research Study (AIRS II) were compared to aircraft in-situ measurements. Although the comparison data set is quite small, the cases examined indicate that the remote sensing technique appears to be an acceptable approach.

Ice phase in altocumulus clouds over Leipzig: remote sensing observations and detailed modeling

NASA Astrophysics Data System (ADS)

Simmel, M.; Bühl, J.; Ansmann, A.; Tegen, I.

2015-09-01

The present work combines remote sensing observations and detailed cloud modeling to investigate two altocumulus cloud cases observed over Leipzig, Germany. A suite of remote sensing instruments was able to detect primary ice at rather high temperatures of -6 °C. For comparison, a second mixed phase case at about -25 °C is introduced. To further look into the details of cloud microphysical processes, a simple dynamics model of the Asai-Kasahara (AK) type is combined with detailed spectral microphysics (SPECS) forming the model system AK-SPECS. Vertical velocities are prescribed to force the dynamics, as well as main cloud features, to be close to the observations. Subsequently, sensitivity studies with respect to ice microphysical parameters are carried out with the aim to quantify the most important sensitivities for the cases investigated. For the cases selected, the liquid phase is mainly determined by the model dynamics (location and strength of vertical velocity), whereas the ice phase is much more sensitive to the microphysical parameters (ice nucleating particle (INP) number, ice particle shape). The choice of ice particle shape may induce large uncertainties that are on the same order as those for the temperature-dependent INP number distribution.

Ice phase in altocumulus clouds over Leipzig: remote sensing observations and detailed modelling

NASA Astrophysics Data System (ADS)

Simmel, M.; Bühl, J.; Ansmann, A.; Tegen, I.

2015-01-01

The present work combines remote sensing observations and detailed cloud modeling to investigate two altocumulus cloud cases observed over Leipzig, Germany. A suite of remote sensing instruments was able to detect primary ice at rather warm temperatures of -6 °C. For comparison, a second mixed phase case at about -25 °C is introduced. To further look into the details of cloud microphysical processes a simple dynamics model of the Asai-Kasahara type is combined with detailed spectral microphysics forming the model system AK-SPECS. Vertical velocities are prescribed to force the dynamics as well as main cloud features to be close to the observations. Subsequently, sensitivity studies with respect to ice microphysical parameters are carried out with the aim to quantify the most important sensitivities for the cases investigated. For the cases selected, the liquid phase is mainly determined by the model dynamics (location and strength of vertical velocity) whereas the ice phase is much more sensitive to the microphysical parameters (ice nuclei (IN) number, ice particle shape). The choice of ice particle shape may induce large uncertainties which are in the same order as those for the temperature-dependent IN number distribution.

Mixed-phase altocumulus clouds over Leipzig: Remote sensing measurements and spectral cloud microphysics simulations

NASA Astrophysics Data System (ADS)

Simmel, Martin; Bühl, Johannes; Ansmann, Albert; Tegen, Ina

2015-04-01

The present work combines remote sensing observations and detailed microphysics cloud modeling to investigate two altocumulus cloud cases observed over Leipzig, Germany. A suite of remote sensing instruments was able to detect primary ice at rather warm temperatures of -6°C. For comparison, a second mixed phase case at about -25°C is introduced. To further look into the details of cloud microphysical processes a simple dynamics model of the Asai-Kasahara type is combined with detailed spectral microphysics forming the model system AK-SPECS. Temperature and humidity profiles are taken either from observation (radiosonde) or GDAS reanalysis. Vertical velocities are prescribed to force the dynamics as well as main cloud features to be close to the observations. Subsequently, sensitivity studies with respect to dynamical as well as ice microphysical parameters are carried out with the aim to quantify the most important sensitivities for the cases investigated. For the cases selected, the liquid phase is mainly determined by the model dynamics (location and strength of vertical velocity) whereas the ice phase is much more sensitive to the microphysical parameters (ice nuclei (IN) number, ice particle shape). The choice of ice particle shape may induce large uncertainties which are in the same order as those for the temperature-dependent IN number distribution.

FIRE Arctic Clouds Experiment

NASA Technical Reports Server (NTRS)

Curry, J. A.; Hobbs, P. V.; King, M. D.; Randall, D. A.; Minnis, P.; Issac, G. A.; Pinto, J. O.; Uttal, T.; Bucholtz, A.; Cripe, D. G.;

Quality of remote sensing measurements of cloud physical parameters in the cooperative convective precipitation experiment

NASA Technical Reports Server (NTRS)

Wu, M.-L.

1985-01-01

In order to develop the remote sensing techniques to infer cloud physical parameters, a multispectral cloud radiometer (MCR) was mounted on a NASA high-altitude aircraft in conjunction with the Cooperative Convective Precipitation Experiment in 1981. The MCR has seven spectral channels, of which three are centered near windows associated with water vapor bands in the near infrared, two are centered near the oxygen A band at 0.76 microns, one is centered at the 1.14-micron water vapor band, and one is centered in the thermal infrared. The reflectance and temperature measured on May 31, 1981, are presented together with theoretical calculations. The results indicate that the MCR produces quality measurements. Therefore several cloud parameters can be derived with good accuracy. The parameters are the cloud-scaled optical thickness, cloud top pressure, volume scattering coefficient, particle thermodynamic phase, effective mean particle size, and cloud-top temperature.

Research Status and Development Trend of Remote Sensing in China Using Bibliometric Analysis

NASA Astrophysics Data System (ADS)

Zeng, Y.; Zhang, J.; Niu, R.

2015-06-01

Remote sensing was introduced into China in 1970s and then began to flourish. At present, China has developed into a big remote sensing country, and remote sensing is increasingly playing an important role in various fields of national economic construction and social development. Based on China Academic Journals Full-text Database and China Citation Database published by China National Knowledge Infrastructure, this paper analyzed academic characteristics of 963 highly cited papers published by 16 professional and academic journals in the field of surveying and mapping from January 2010 to December 2014 in China, which include hot topics, literature authors, research institutions, and fundations. At the same time, it studied a total of 51,149 keywords published by these 16 journals during the same period. Firstly by keyword selection, keyword normalization, keyword consistency and keyword incorporation, and then by analysis of high frequency keywords, the progress and prospect of China's remote sensing technology in data acquisition, data processing and applications during the past five years were further explored and revealed. It can be seen that: highly cited paper analysis and word frequency analysis is complementary on subject progress analysis; in data acquisition phase, research focus is new civilian remote sensing satellite systems and UAV remote sensing system; research focus of data processing and analysis is multi-source information extraction and classification, laser point cloud data processing, objectoriented high resolution image analysis, SAR data and hyper-spectral image processing, etc.; development trend of remote sensing data processing is quantitative, intelligent, automated, and real-time, and the breadth and depth of remote sensing application is gradually increased; parallel computing, cloud computing and geographic conditions monitoring and census are the new research focuses to be paid attention to.

Atmospheric Radiative Transfer for Satellite Remote Sensing

NASA Technical Reports Server (NTRS)

Marshak, Alexander

2008-01-01

I will discuss the science of satellite remote sensing which involves the interpretation and inversion of radiometric measurements made from space. The goal of remote sensing is to retrieve some physical aspects of the medium which are sensitive to the radiation at specific wavelengths. This requires the use of fundamentals of atmospheric radiative transfer. I will talk about atmospheric radiation or, more specifically, about the interactions of solar radiation with aerosols and cloud particles. The focus will be more on cloudy atmospheres. I will also show how a standard one-dimensional approach, that is traced back at least 100 years, can fail to interpret the complexity of real clouds. I n these cases, three-dimensional radiative transfer should be used. Examples of satellite retrievals will illustrate the cases.

Observations in the solar spectrum interest for remote sensing purposes

NASA Technical Reports Server (NTRS)

Herman, M.; Vanderbilt, V.

1994-01-01

The polarization of the sunlight scattered by atmospheric aerosols or cloud droplets and reflected from ground surfaces or plant canopies may convey much information when used for remote sensing purposes. The typical polarization features of aerosols, cloud droplets, and plant canopies, as observed by ground based and airborne sensors, are investigated, looking especially for those invariant properties amenable to description by simple models when possible. The question of polarization measurements from space is addressed. The interest of such measurements for remote sensing purposes is investigated, and their feasibility is tested by using results obtained during field campaigns of the airborne POLDER instrument, a radiometer designed to measure the directionality and polarization of the sunlight scattered by the ground atmosphere system.

A physically based algorithm for non-blackbody correction of the cloud top temperature for the convective clouds

NASA Astrophysics Data System (ADS)

Wang, C.; Luo, Z. J.; Chen, X.; Zeng, X.; Tao, W.; Huang, X.

2012-12-01

Cloud top temperature is a key parameter to retrieval in the remote sensing of convective clouds. Passive remote sensing cannot directly measure the temperature at the cloud tops. Here we explore a synergistic way of estimating cloud top temperature by making use of the simultaneous passive and active remote sensing of clouds (in this case, CloudSat and MODIS). Weighting function of the MODIS 11μm band is explicitly calculated by feeding cloud hydrometer profiles from CloudSat retrievals and temperature and humidity profiles based on ECMWF ERA-interim reanalysis into a radiation transfer model. Among 19,699 tropical deep convective clouds observed by the CloudSat in 2008, the averaged effective emission level (EEL, where the weighting function attains its maximum) is at optical depth 0.91 with a standard deviation of 0.33. Furthermore, the vertical gradient of CloudSat radar reflectivity, an indicator of the fuzziness of convective cloud top, is linearly proportional to, d_{CTH-EEL}, the distance between the EEL of 11μm channel and cloud top height (CTH) determined by the CloudSat when d_{CTH-EEL}<0.6km. Beyond 0.6km, the distance has little sensitivity to the vertical gradient of CloudSat radar reflectivity. Based on these findings, we derive a formula between the fuzziness in the cloud top region, which is measurable by CloudSat, and the MODIS 11μm brightness temperature assuming that the difference between effective emission temperature and the 11μm brightness temperature is proportional to the cloud top fuzziness. This formula is verified using the simulated deep convective cloud profiles by the Goddard Cumulus Ensemble model. We further discuss the application of this formula in estimating cloud top buoyancy as well as the error characteristics of the radiative calculation within such deep-convective clouds.

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

NASA Astrophysics Data System (ADS)

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

2015-12-01

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

Comparative evaluation of polarimetric and bi-spectral cloud microphysics retrievals: Retrieval closure experiments and comparisons based on idealized and LES case studies

NASA Astrophysics Data System (ADS)

Miller, D. J.; Zhang, Z.; Ackerman, A. S.; Platnick, S. E.; Cornet, C.

2016-12-01

A remote sensing cloud retrieval simulator, created by coupling an LES cloud model with vector radiative transfer (RT) models is the ideal framework for assessing cloud remote sensing techniques. This simulator serves as a tool for understanding bi-spectral and polarimetric retrievals by comparing them directly to LES cloud properties (retrieval closure comparison) and for comparing the retrieval techniques to one another. Our simulator utilizes the DHARMA LES [Ackerman et al., 2004] with cloud properties based on marine boundary layer (MBL) clouds observed during the DYCOMS-II and ATEX field campaigns. The cloud reflectances are produced by the vectorized RT models based on polarized doubling adding and monte carlo techniques (PDA, MCPOL). Retrievals are performed utilizing techniques as similar as possible to those implemented on their corresponding well known instruments; polarimetric retrievals are based on techniques implemented for polarimeters (POLDER, AirMSPI, and RSP) and bi-spectral retrievals are performed using the Nakajima-King LUT method utilized on a number of spectral instruments (MODIS and VIIRS). Retrieval comparisons focus on cloud droplet effective radius (re), effective variance (ve), and cloud optical thickness (τ). This work explores the sensitivities of these two retrieval techniques to various observation limitations, such as spatial resolution/cloud inhomogeneity, impact of 3D radiative effects, and angular resolution requirements. With future remote sensing missions like NASA's Aerosols/Clouds/Ecosystems (ACE) planning to feature advanced polarimetric instruments it is important to understand how these retrieval techniques compare to one another. The cloud retrieval simulator we've developed allows us to probe these important questions in a realistically relevant test bed.

Six years of surface remote sensing of stratiform warm clouds in marine and continental air over Mace Head, Ireland

NASA Astrophysics Data System (ADS)

Preißler, Jana; Martucci, Giovanni; Saponaro, Giulia; Ovadnevaite, Jurgita; Vaishya, Aditya; Kolmonen, Pekka; Ceburnis, Darius; Sogacheva, Larisa; de Leeuw, Gerrit; O'Dowd, Colin

2016-12-01

A total of 118 stratiform water clouds were observed by ground-based remote sensing instruments at the Mace Head Atmospheric Research Station on the west coast of Ireland from 2009 to 2015. Microphysical and optical characteristics of these clouds were studied as well as the impact of aerosols on these properties. Microphysical and optical cloud properties were derived using the algorithm SYRSOC (SYnergistic Remote Sensing Of Clouds). Ground-based in situ measurements of aerosol concentrations and the transport path of air masses at cloud level were investigated as well. The cloud properties were studied in dependence of the prevailing air mass at cloud level and season. We found higher cloud droplet number concentrations (CDNC) and smaller effective radii (reff) with greater pollution. Median CDNC ranged from 60 cm-3 in marine air masses to 160 cm-3 in continental air. Median reff ranged from 8 μm in polluted conditions to 10 μm in marine air. Effective droplet size distributions were broader in marine than in continental cases. Cloud optical thickness (COT) and albedo were lower in cleaner air masses and higher in more polluted conditions, with medians ranging from 2.1 to 4.9 and 0.22 to 0.39, respectively. However, calculation of COT and albedo was strongly affected by liquid water path (LWP) and departure from adiabatic conditions. A comparison of SYRSOC results with MODIS (Moderate-Resolution Imaging Spectroradiometer) observations showed large differences for LWP and COT but good agreement for reff with a linear fit with slope near 1 and offset of -1 μm.

An Examination of the Impact of Drizzle Drops on Satellite-Retrieved Effective Particle Sizes

NASA Technical Reports Server (NTRS)

Minnis, Patrick; Arduini, Robert F.; Young, David F.; Ayers, J, Kirk; Albrecht, Bruce A.; Sharon, Tarah; Stevens, Bjorn

2004-01-01

In general, cloud effective droplet radii are remotely sensed in the near-infrared using the assumption of a monomodal droplet size distribution. It has been observed in many instances, especially in relatively pristine marine environments, that cloud effective droplet radii derived from satellite data often exceed 15 m or more. Comparisons of remotely sensed and in situ retrievals indicate that the former often overestimates the latter in clouds with drizzle-size droplets. To gain a better understanding of this discrepancy, this paper performs a theoretical and empirical evaluation of the impact of drizzle drops on the derived effective radius.

Ground-based remote sensing scheme for monitoring aerosol–cloud interactions

DOE PAGES

Sarna, Karolina; Russchenberg, Herman W. J.

2016-03-14

A new method for continuous observation of aerosol–cloud interactions with ground-based remote sensing instruments is presented. The main goal of this method is to enable the monitoring of the change of the cloud droplet size due to the change in the aerosol concentration. We use high-resolution measurements from a lidar, a radar and a radiometer, which allow us to collect and compare data continuously. This method is based on a standardised data format from Cloudnet and can be implemented at any observatory where the Cloudnet data set is available. Two example case studies were chosen from the Atmospheric Radiation Measurementmore » (ARM) Program deployment on Graciosa Island, Azores, Portugal, in 2009 to present the method. We use the cloud droplet effective radius ( r e) to represent cloud microphysical properties and an integrated value of the attenuated backscatter coefficient (ATB) below the cloud to represent the aerosol concentration. All data from each case study are divided into bins of the liquid water path (LWP), each 10 g m -2 wide. For every LWP bin we present the correlation coefficient between ln r e and ln ATB, as well as ACI r (defined as ACI r = -d ln r e d ln ATB, change in cloud droplet effective radius with aerosol concentration). Obtained values of ACI r are in the range 0.01–0.1. In conclusion, we show that ground-based remote sensing instruments used in synergy can efficiently and continuously monitor aerosol–cloud interactions.« less

Radiative transfer model for aerosols in infrared wavelengths for passive remote sensing applications.

PubMed

Ben-David, Avishai; Embury, Janon F; Davidson, Charles E

2006-09-10

A comprehensive analytical radiative transfer model for isothermal aerosols and vapors for passive infrared remote sensing applications (ground-based and airborne sensors) has been developed. The theoretical model illustrates the qualitative difference between an aerosol cloud and a chemical vapor cloud. The model is based on two and two/four stream approximations and includes thermal emission-absorption by the aerosols; scattering of diffused sky radiances incident from all sides on the aerosols (downwelling, upwelling, left, and right); and scattering of aerosol thermal emission. The model uses moderate resolution transmittance ambient atmospheric radiances as boundary conditions and provides analytical expressions for the information on the aerosol cloud that is contained in remote sensing measurements by using thermal contrasts between the aerosols and diffused sky radiances. Simulated measurements of a ground-based sensor viewing Bacillus subtilis var. niger bioaerosols and kaolin aerosols are given and discussed to illustrate the differences between a vapor-only model (i.e., only emission-absorption effects) and a complete model that adds aerosol scattering effects.

Cloud Properties Derived from Surface-Based Near-Infrared Spectral Transmission

NASA Technical Reports Server (NTRS)

Pilewskie, Peter; Twomey, S.; Gore, Warren J. Y. (Technical Monitor)

1996-01-01

Surface based near-infrared cloud spectral transmission measurements from a recent precipitation/cloud physics field study are used to determine cloud physical properties and relate them to other remote sensing and in situ measurements. Asymptotic formulae provide an effective means of closely approximating the qualitative and quantitative behavior of transmission computed by more laborious detailed methods. Relationships derived from asymptotic formulae are applied to measured transmission spectra to test objectively the internal consistency of data sets acquired during the field program and they confirmed the quality of the measurements. These relationships appear to be very useful in themselves, not merely as a quality control measure, but also a potentially valuable remote-sensing technique in its own right. Additional benefits from this analysis have been the separation of condensed water (cloud) transmission and water vapor transmission and the development of a method to derive cloud liquid water content.

Progress in the Development of Practical Remote Detection of Icing Conditions

NASA Technical Reports Server (NTRS)

Reehorst, Andrew; Politovich, Marcia K.; Zednik, Stephan; Isaac, George A.; Cober, Stewart

2006-01-01

The NASA Icing Remote Sensing System (NIRSS) has been under definition and development at NASA Glenn Research Center since 1997. The goal of this development activity is to produce and demonstrate the required sensing and data processing technologies required to accurately remotely detect and measure icing conditions aloft. As part of that effort NASA has teamed with NCAR to develop software to fuse data from multiple instruments into a single detected icing condition product. The multiple instrument approach utilizes a X-band vertical staring radar, a multifrequency microwave, and a lidar ceilometer. The radar data determine cloud boundaries, the radiometer determines the sub-freezing temperature heights and total liquid water content, and the ceilometer refines the lower cloud boundary. Data is post-processed with a LabVIEW program with a resultant supercooled liquid water profile and aircraft hazard depiction. Ground-based, remotely-sensed measurements and in-situ measurements from research aircraft were gathered during the international 2003-2004 Alliance Icing Research Study (AIRS II). Comparisons between the remote sensing system s fused icing product and the aircraft measurements are reviewed here. While there are areas where improvement can be made, the cases examined suggest that the fused sensor remote sensing technique appears to be a valid approach.

Remote sensing of smoke, clouds, and radiation using AVIRIS during SCAR experiments

NASA Technical Reports Server (NTRS)

Gao, Bo-Cai; Remer, Lorraine; Kaufman, Yorman J.

1995-01-01

During the past two years, researchers from several institutes joined together to take part in two SCAR experiments. The SCAR-A (Sulfates, Clouds And Radiation - Atlantic) took place in the mid-Atlantic region of the United States in July, 1993. remote sensing data were acquired with the Airborne Visible Infrared Imaging Spectrometer (AVIRIS), the MODIS Airborne Simulator (MAS), and a RC-10 mapping camera from an ER-2 aircraft at 20 km. In situ measurements of aerosol and cloud microphysical properties were made with a variety of instruments equipped on the University of Washington's C-131A research aircraft. Ground based measurements of aerosol optical depths and particle size distributions were made using a network of sunphotometers. The main purpose of SCAR-A experiment was to study the optical, physical and chemical properties of sulfate aerosols and their interaction with clouds and radiation. Sulfate particles are believed to affect the energy balance of the earth by directly reflecting solar radiation back to space and by increasing the cloud albedo. The SCAR-C (Smoke, Clouds And Radiation - California) took place on the west coast areas during September - October of 1994. Sets of aircraft and ground-based instruments, similar to those used during SCAR-A, were used during SCAR-C. Remote sensing of fires and smoke from AVIRIS and MAS imagers on the ER-2 aircraft was combined with a complete in situ characterization of the aerosol and trace gases from the C-131A aircraft of the University of Washington and the Cesna aircraft from the U.S. Forest Service. The comprehensive data base acquired during SCAR-A and SCAR-C will contribute to a better understanding of the role of clouds and aerosols in global change studies. The data will also be used to develop satellite remote sensing algorithms from MODIS on the Earth Observing System.

Tephra dispersal and fallout reconstructed integrating field, ground-based and satellite-based data: Application to the 23rd November 2013 Etna paroxysm

NASA Astrophysics Data System (ADS)

Poret, M.; Corradini, S.; Merucci, L.; Costa, A.; Andronico, D.; Montopoli, M.; Vulpiani, G.; Scollo, S.; Freret-Lorgeril, V.

2017-12-01

On the 23rd November 2013, Etna erupted giving one of the most intense lava fountain recorded. The eruption produced a buoyant plume that rose higher than 10 km a.s.l. from which two volcanic clouds were observed from satellite at two different atmospheric levels. A Previous study described one of the two clouds as mainly composed by ash making use of remote sensing instruments. Besides, the second cloud is made of ice/SO2 droplets and is not measurable in terms of ash mass. Both clouds spread out under north-easterly winds transporting the tephra from Etna towards the Puglia region. The untypical meteorological conditions permit to collect tephra samples in proximal areas to the Etna emission source as well as far away in the Calabria region. The eruption was observed by satellite (MSG-SEVIRI, MODIS) and ground-based (X-band weather radar, VIS/IR cameras and L-band Doppler radar) remote sensing systems. This study uses the FALL3D code to model the evolution of the plume and the tephra deposition by constraining the simulation results with remote sensing products for volcanic cloud (cloud height, fine ash Mass - Ma, Aerosol Optical Depth at 0.55 mm - AOD). Among the input parameters, the Total Grain-Size Distribution (TGSD) is reconstructed by integrating field deposits with estimations from the X-band radar data. The optimal TGSD was selected through an inverse problem method that best-fits both the field deposits and airborne measurements. The results of the simulations capture the main behavior of the two volcanic clouds at their altitudes. The best agreement between the simulated Ma and AOD and the SEVIRI retrievals indicates a PM20 fraction of 3.4 %. The total erupted mass is estimated at 1.6 × 109 kg in consistency with the estimations made from remote sensing data (3.0 × 109 kg) and ground deposit (1.3 × 109 kg).

Remote sensing of atmosphere and oceans; Proceedings of Symposium 1 and of the Topical Meeting of the 27th COSPAR Plenary Meeting, Espoo, Finland, July 18-29, 1988

NASA Technical Reports Server (NTRS)

Raschke, E. (Editor); Ghazi, A. (Editor); Gower, J. F. R. (Editor); Mccormick, P. (Editor); Gruber, A. (Editor); Hasler, A. F. (Editor)

1989-01-01

Papers are presented on the contribution of space remote sensing observations to the World Climate Research Program and the Global Change Program, covering topics such as space observations for global environmental monitoring, experiments related to land surface fluxes, studies of atmospheric composition, structure, motions, and precipitation, and remote sensing for oceanography, observational studies of the atmosphere, clouds, and the earth radiation budget. Also, papers are given on results from space observations for meteorology, oceanography, and mesoscale atmospheric and ocean processes. The topics include vertical atmospheric soundings, surface water temperature determination, sea level variability, data on the prehurricane atmosphere, linear and circular mesoscale convective systems, Karman vortex clouds, and temporal patterns of phytoplankton abundance.

IceCube: CubeSat 883-GHz Radiometry for Future Ice Cloud Remote Sensing

NASA Technical Reports Server (NTRS)

Wu, Dongliang; Esper, Jaime; Ehsan, Negar; Johnson, Thomas; Mast, William; Piepmeier, Jeffery R.; Racette, Paul E.

2015-01-01

Ice clouds play a key role in the Earth's radiation budget, mostly through their strong regulation of infrared radiation exchange. Accurate observations of global cloud ice and its distribution have been a challenge from space, and require good instrument sensitivities to both cloud mass and microphysical properties. Despite great advances from recent spaceborne radar and passive sensors, uncertainty of current ice water path (IWP) measurements is still not better than a factor of 2. Submillimeter (submm) wave remote sensing offers great potential for improving cloud ice measurements, with simultaneous retrievals of cloud ice and its microphysical properties. The IceCube project is to enable this cloud ice remote sensing capability in future missions, by raising 874-GHz receiver technology TRL from 5 to 7 in a spaceflight demonstration on 3-U CubeSat in a low Earth orbit (LEO) environment. The NASAs Goddard Space Flight Center (GSFC) is partnering with Virginia Diodes Inc (VDI) on the 874-GHz receiver through its Vector Network Analyzer (VNA) extender module product line, to develop an instrument with precision of 0.2 K over 1-second integration and accuracy of 2.0 K or better. IceCube is scheduled to launch to and subsequent release from the International Space Station (ISS) in mid-2016 for nominal operation of 28 plus days. We will present the updated design of the payload and spacecraft systems, as well as the operation concept. We will also show the simulated 874-GHz radiances from the ISS orbits and cloud scattering signals as expected for the IceCube cloud radiometer.

Clouds, Wind and the Biogeography of Central American Cloud Forests: Remote Sensing, Atmospheric Modeling, and Walking in the Jungle

NASA Astrophysics Data System (ADS)

Lawton, R.; Nair, U. S.

2011-12-01

Cloud forests stand at the core of the complex of montane ecosystems that provide the backbone to the multinational Mesoamerican Biological Corridor, which seeks to protect a biodiversity conservation "hotspot" of global significance in an area of rapidly changing land use. Although cloud forests are generally defined by frequent and prolonged immersion in cloud, workers differ in their feelings about "frequent" and "prolonged", and quantitative assessments are rare. Here we focus on the dry season, in which the cloud and mist from orographic cloud plays a critical role in forest water relations, and discuss remote sensing of orographic clouds, and regional and atmospheric modeling at several scales to quantitatively examine the distribution of the atmospheric conditions that characterize cloud forests. Remote sensing using data from GOES reveals diurnal and longer scale patterns in the distribution of dry season orographic clouds in Central America at both regional and local scales. Data from MODIS, used to calculate the base height of orographic cloud banks, reveals not only the geographic distributon of cloud forest sites, but also striking regional variation in the frequency of montane immersion in orographic cloud. At a more local scale, wind is known to have striking effects on forest structure and species distribution in tropical montane ecosystems, both as a general mechanical stress and as the major agent of ecological disturbance. High resolution regional atmospheric modeling using CSU RAMS in the Monteverde cloud forests of Costa Rica provides quantitative information on the spatial distribution of canopy level winds, insight into the spatial structure and local dynamics of cloud forest communities. This information will be useful in not only in local conservation planning and the design of the Mesoamerican Biological Corridor, but also in assessments of the sensitivity of cloud forests to global and regional climate changes.

Estimating Water Levels with Google Earth Engine

NASA Astrophysics Data System (ADS)

Lucero, E.; Russo, T. A.; Zentner, M.; May, J.; Nguy-Robertson, A. L.

2016-12-01

Reservoirs serve multiple functions and are vital for storage, electricity generation, and flood control. For many areas, traditional ground-based reservoir measurements may not be available or data dissemination may be problematic. Consistent monitoring of reservoir levels in data-poor areas can be achieved through remote sensing, providing information to researchers and the international community. Estimates of trends and relative reservoir volume can be used to identify water supply vulnerability, anticipate low power generation, and predict flood risk. Image processing with automated cloud computing provides opportunities to study multiple geographic areas in near real-time. We demonstrate the prediction capability of a cloud environment for identifying water trends at reservoirs in the US, and then apply the method to data-poor areas in North Korea, Iran, Azerbaijan, Zambia, and India. The Google Earth Engine cloud platform hosts remote sensing data and can be used to automate reservoir level estimation with multispectral imagery. We combine automated cloud-based analysis from Landsat image classification to identify reservoir surface area trends and radar altimetry to identify reservoir level trends. The study estimates water level trends using three years of data from four domestic reservoirs to validate the remote sensing method, and five foreign reservoirs to demonstrate the method application. We report correlations between ground-based reservoir level measurements in the US and our remote sensing methods, and correlations between the cloud analysis and altimetry data for reservoirs in data-poor areas. The availability of regular satellite imagery and an automated, near real-time application method provides the necessary datasets for further temporal analysis, reservoir modeling, and flood forecasting. All statements of fact, analysis, or opinion are those of the author and do not reflect the official policy or position of the Department of Defense or any of its components or the U.S. Government

Thin Cloud Detection Method by Linear Combination Model of Cloud Image

NASA Astrophysics Data System (ADS)

Liu, L.; Li, J.; Wang, Y.; Xiao, Y.; Zhang, W.; Zhang, S.

2018-04-01

The existing cloud detection methods in photogrammetry often extract the image features from remote sensing images directly, and then use them to classify images into cloud or other things. But when the cloud is thin and small, these methods will be inaccurate. In this paper, a linear combination model of cloud images is proposed, by using this model, the underlying surface information of remote sensing images can be removed. So the cloud detection result can become more accurate. Firstly, the automatic cloud detection program in this paper uses the linear combination model to split the cloud information and surface information in the transparent cloud images, then uses different image features to recognize the cloud parts. In consideration of the computational efficiency, AdaBoost Classifier was introduced to combine the different features to establish a cloud classifier. AdaBoost Classifier can select the most effective features from many normal features, so the calculation time is largely reduced. Finally, we selected a cloud detection method based on tree structure and a multiple feature detection method using SVM classifier to compare with the proposed method, the experimental data shows that the proposed cloud detection program in this paper has high accuracy and fast calculation speed.

Toward Global Harmonization of Derived Cloud Products

NASA Technical Reports Server (NTRS)

Wu, Dong L.; Baum, Bryan A.; Choi, Yong-Sang; Foster, Michael J.; Karlsson, Karl-Goeran; Heidinger, Andrew; Poulsen, Caroline; Pavolonis, Michael; Riedi, Jerome; Roebeling, Robert

2017-01-01

Formerly known as the Cloud Retrieval Evaluation Workshop (CREW; see the list of acronyms used in this paper below) group (Roebeling et al. 2013, 2015), the International Cloud Working Group (ICWG) was created and endorsed during the 42nd Meeting of CGMS. The CGMS-ICWG provides a forum for space agencies to seek coherent progress in science and applications and also to act as a bridge between space agencies and the cloud remote sensing and applications community. The ICWG plans to serve as a forum to exchange and enhance knowledge on state-of-the-art cloud parameter retrievals algorithms, to stimulate support for training in the use of cloud parameters, and to encourage space agencies and the cloud remote sensing community to share knowledge. The ICWG plans to prepare recommendations to guide the direction of future research-for example, on observing severe weather events or on process studies-and to influence relevant programs of the WMO, WCRP, GCOS, and the space agencies.

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

PubMed

Wilson, Adam M; Jetz, Walter

2016-03-01

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

Image processing methods in two and three dimensions used to animate remotely sensed data. [cloud cover

NASA Technical Reports Server (NTRS)

Hussey, K. J.; Hall, J. R.; Mortensen, R. A.

1986-01-01

Image processing methods and software used to animate nonimaging remotely sensed data on cloud cover are described. Three FORTRAN programs were written in the VICAR2/TAE image processing domain to perform 3D perspective rendering, to interactively select parameters controlling the projection, and to interpolate parameter sets for animation images between key frames. Operation of the 3D programs and transferring the images to film is automated using executive control language and custom hardware to link the computer and camera.

New Observational Technologies Scientific and Societal Impacts

NASA Astrophysics Data System (ADS)

Fabry, F.; Zawadzki, I.

INTRODUCTION REMOTE SENSING OF THE ATMOSPHERE REMOTE SENSORS AND THEIR SCIENTIFIC IMPACTS Air Temperature and Moisture Clouds and Precipitation Wind Others Related Scientific Considerations SOCIETAL IMPACTS CONCLUSIONS REFERENCES

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

MODIS Cloud Products Derived from Terra and Aqua During CRYSTAL-FACE

NASA Technical Reports Server (NTRS)

King, Michael D.; Platnick, S.; Riedi, J. C.; Ackerman, S. A.; Menzel, W. P.

2003-01-01

The Moderate Resolution Imaging Spectroradiometer (MODIS), developed as part of the Earth Observing System (EOS) and launched on Terra in December 1999 and Aqua in May 2002, is designed to meet the scientific needs for satellite remote sensing of clouds, aerosols, water vapor, and land and ocean surface properties. During the CRYSTAL-FACE experiment, numerous aircraft coordinated both in situ and remote sensing observations with the Terra and Aqua spacecraft. In this paper we will emphasize the optical, microphysical, and physical properties of both liquid water and ice clouds obtained from an analysis of the satellite observations over Florida and the Gulf of Mexico during July 2002. We will present the frequency distribution of liquid water and ice cloud microphysical properties throughout the region, separating the results over land and ocean. Probability distributions of effective radius and cloud optical thickness will also be shown.

A preliminary study of the statistical analyses and sampling strategies associated with the integration of remote sensing capabilities into the current agricultural crop forecasting system

NASA Technical Reports Server (NTRS)

Sand, F.; Christie, R.

1975-01-01

Extending the crop survey application of remote sensing from small experimental regions to state and national levels requires that a sample of agricultural fields be chosen for remote sensing of crop acreage, and that a statistical estimate be formulated with measurable characteristics. The critical requirements for the success of the application are reviewed in this report. The problem of sampling in the presence of cloud cover is discussed. Integration of remotely sensed information about crops into current agricultural crop forecasting systems is treated on the basis of the USDA multiple frame survey concepts, with an assumed addition of a new frame derived from remote sensing. Evolution of a crop forecasting system which utilizes LANDSAT and future remote sensing systems is projected for the 1975-1990 time frame.

[Small unmanned aerial vehicles for low-altitude remote sensing and its application progress in ecology.

PubMed

Sun, Zhong Yu; Chen, Yan Qiao; Yang, Long; Tang, Guang Liang; Yuan, Shao Xiong; Lin, Zhi Wen

2017-02-01

Low-altitude unmanned aerial vehicles (UAV) remote sensing system overcomes the deficiencies of space and aerial remote sensing system in resolution, revisit period, cloud cover and cost, which provides a novel method for ecological research on mesoscale. This study introduced the composition of UAV remote sensing system, reviewed its applications in species, population, community and ecosystem ecology research. Challenges and opportunities of UAV ecology were identified to direct future research. The promising research area of UAV ecology includes the establishment of species morphology and spectral characteristic data base, species automatic identification, the revelation of relationship between spectral index and plant physiological processes, three-dimension monitoring of ecosystem, and the integration of remote sensing data from multi resources and multi scales. With the development of UAV platform, data transformation and sensors, UAV remote sensing technology will have wide application in ecology research.

Preliminary Findings of Inflight Icing Field Test to Support Icing Remote Sensing Technology Assessment

NASA Technical Reports Server (NTRS)

King, Michael; Reehorst, Andrew; Serke, Dave

2015-01-01

NASA and the National Center for Atmospheric Research have developed an icing remote sensing technology that has demonstrated skill at detecting and classifying icing hazards in a vertical column above an instrumented ground station. This technology has recently been extended to provide volumetric coverage surrounding an airport. Building on the existing vertical pointing system, the new method for providing volumetric coverage will utilize a vertical pointing cloud radar, a multifrequency microwave radiometer with azimuth and elevation pointing, and a NEXRAD radar. The new terminal area icing remote sensing system processes the data streams from these instruments to derive temperature, liquid water content, and cloud droplet size for each examined point in space. These data are then combined to ultimately provide icing hazard classification along defined approach paths into an airport.

The science benefits of and the antenna requirements for microwave remote sensing from geostationary orbit

NASA Technical Reports Server (NTRS)

Stutzman, Warren L. (Editor); Brown, Gary S. (Editor)

1991-01-01

The primary objective of the Large Space Antenna (LSA) Science Panel was to evaluate the science benefits that can be realized with a 25-meter class antenna in a microwave/millimeter wave remote sensing system in geostationary orbit. The panel concluded that a 25-meter or larger antenna in geostationary orbit can serve significant passive remote sensing needs in the 10 to 60 GHz frequency range, including measurements of precipitation, water vapor, atmospheric temperature profile, ocean surface wind speed, oceanic cloud liquid water content, and snow cover. In addition, cloud base height, atmospheric wind profile, and ocean currents can potentially be measured using active sensors with the 25-meter antenna. Other environmental parameters, particularly those that do not require high temporal resolution, are better served by low Earth orbit based sensors.

Multichannel scanning radiometer for remote sensing cloud physical parameters

NASA Technical Reports Server (NTRS)

Curran, R. J.; Kyle, H. L.; Blaine, L. R.; Smith, J.; Clem, T. D.

1981-01-01

A multichannel scanning radiometer developed for remote observation of cloud physical properties is described. Consisting of six channels in the near infrared and one channel in the thermal infrared, the instrument can observe cloud physical parameters such as optical thickness, thermodynamic phase, cloud top altitude, and cloud top temperature. Measurement accuracy is quantified through flight tests on the NASA CV-990 and the NASA WB-57F, and is found to be limited by the harsh environment of the aircraft at flight altitude. The electronics, data system, and calibration of the instrument are also discussed.

Effect of the revisit interval on the accuracy of remote sensing-based estimates of evapotranspiration at field scales

USDA-ARS?s Scientific Manuscript database

Accurate spatially distributed estimates of evapotranspiration (ET) derived from remotely sensed data are critical to a broad range of practical and operational applications. However, due to lengthy return intervals and cloud cover, data acquisition is not continuous over time. To fill the data gaps...

An intercomparison of available soil moisture estimates from thermal-infrared and passive microwave remote sensing and land-surface modeling

USDA-ARS?s Scientific Manuscript database

Remotely-sensed soil moisture studies have mainly focused on retrievals using active and passive microwave (MW) sensors whose measurements provided a direct relationship to soil moisture (SM). MW sensors present obvious advantages such as the ability to retrieve through non-precipitating cloud cover...

Validation of Satellite Derived Cloud Properties Over the Southeastern Pacific

NASA Astrophysics Data System (ADS)

Ayers, J.; Minnis, P.; Zuidema, P.; Sun-Mack, S.; Palikonda, R.; Nguyen, L.; Fairall, C.

2005-12-01

Satellite measurements of cloud properties and the radiation budget are essential for understanding meso- and large-scale processes that determine the variability in climate over the southeastern Pacific. Of particular interest in this region is the prevalent stratocumulus cloud deck. The stratocumulus albedos are directly related to cloud microphysical properties that need to be accurately characterized in Global Climate Models (GCMs) to properly estimate the Earth's radiation budget. Meteorological observations in this region are sparse causing large uncertainties in initialized model fields. Remote sensing from satellites can provide a wealth of information about the clouds in this region, but it is vital to validate the remotely sensed parameters and to understand their relationship to other parameters that are not directly observed by the satellites. The variety of measurements from the R/V Roger Revelle during the 2003 STRATUS cruise and from the R/V Ron Brown during EPIC 2001 and the 2004 STRATUS cruises are suitable for validating and improving the interpretation of the satellite derived cloud properties. In this study, satellite-derived cloud properties including coverage, height, optical depth, and liquid water path are compared with in situ measurements taken during the EPIC and STRATUS cruises. The remotely sensed values are derived from Geostationary Operational Environmental Satellite (GOES) imager data, Moderate Resolution Imaging Spectroradiometer (MODIS) data from the Terra and Aqua satellites, and from the Visible and Infrared Scanner (VIRS) aboard the Tropical Rainfall Measuring Mission (TRMM) satellite. The products from this study will include regional monthly cloud climatologies derived from the GOES data for the 2003 and 2004 cruises as well as micro and macro physical cloud property retrievals centered over the ship tracks from MODIS and VIRS.

ARM Radar Contoured Frequency by Altitude Diagram (CFAD) Data Products

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

Zhang, Yuying

2017-03-10

To compare with ARM cloud radar simulator outputs, observational reflectivity-height joint histograms, i.e., CFADs, are constructed from the operational ARM Active Remote Sensing of CLouds (ARSCL) Value-Added Product.

MODIS Direct Broadcast and Remote Sensing Applications

NASA Technical Reports Server (NTRS)

Tsay, Si-Chee

2004-01-01

The Moderate Resolution Imaging Spectroradiometer (MODIS) was developed by NASA and launched onboard both Terra spacecraft on December 18, 1999 and Aqua spacecraft on May 4, 2002. MODIS scans a swath width sufficient to provide nearly complete global coverage every two days from a polar-orbiting, sun-synchronous, platform at an altitude of 705 km, and provides images in 36 spectral bands between 0.415 and 14.235 microns with spatial resolutions of 250 m (2 bands), 500 m (5 bands) and 1000 m (29 bands). Equipped with direct broadcast capability, the MODIS measurements can be received worldwide real time. There are 82 ingest sites (over 900 users, listed on the Direct Readout Portal) around the world for Terra/Aqua-MODIS Direct Broadcast DB) downlink. This represents 27 (6 from EOS science team members) science research organizations for DB land, ocean and atmospheric processing, and 53 companies that base their application algorithms and value added products on DB data. In this paper we will describe the various methods being used for the remote sensing of cloud properties using MODIS data, focusing primarily on the MODIS cloud mask used to distinguish clouds, clear sky, heavy aerosol, and shadows on the ground, and on the remote sensing of aerosol/cloud optical properties, especially optical thickness and effective particle size. Additional properties of clouds derived from multispectral thermal infrared measurements, especially cloud top pressure and emissivity, will also be described. Preliminary results will be presented and discussed their implications in regional-to-global climatic effects.

The Real-Time Monitoring Service Platform for Land Supervision Based on Cloud Integration

NASA Astrophysics Data System (ADS)

Sun, J.; Mao, M.; Xiang, H.; Wang, G.; Liang, Y.

2018-04-01

Remote sensing monitoring has become the important means for land and resources departments to strengthen supervision. Aiming at the problems of low monitoring frequency and poor data currency in current remote sensing monitoring, this paper researched and developed the cloud-integrated real-time monitoring service platform for land supervision which enhanced the monitoring frequency by acquiring the domestic satellite image data overall and accelerated the remote sensing image data processing efficiency by exploiting the intelligent dynamic processing technology of multi-source images. Through the pilot application in Jinan Bureau of State Land Supervision, it has been proved that the real-time monitoring technical method for land supervision is feasible. In addition, the functions of real-time monitoring and early warning are carried out on illegal land use, permanent basic farmland protection and boundary breakthrough in urban development. The application has achieved remarkable results.

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

PubMed Central

Wilson, Adam M.; Jetz, Walter

2016-01-01

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

On the remote sensing of cloud properties from satellite infrared sounder data

NASA Technical Reports Server (NTRS)

Yeh, H. Y. M.

1984-01-01

A method for remote sensing of cloud parameters by using infrared sounder data has been developed on the basis of the parameterized infrared transfer equation applicable to cloudy atmospheres. The method is utilized for the retrieval of the cloud height, amount, and emissivity in 11 micro m region. Numerical analyses and retrieval experiments have been carried out by utilizing the synthetic sounder data for the theoretical study. The sensitivity of the numerical procedures to the measurement and instrument errors are also examined. The retrieved results are physically discussed and numerically compared with the model atmospheres. Comparisons reveal that the recovered cloud parameters agree reasonably well with the pre-assumed values. However, for cases when relatively thin clouds and/or small cloud fractional cover within a field of view are present, the recovered cloud parameters show considerable fluctuations. Experiments on the proposed algorithm are carried out utilizing High Resolution Infrared Sounder (HIRS/2) data of NOAA 6 and TIROS-N. Results of experiments show reasonably good comparisons with the surface reports and GOES satellite images.

Concept, Simulation, and Instrumentation for Radiometric Inflight Icing Detection

NASA Technical Reports Server (NTRS)

Ryerson, Charles; Koenig, George G.; Reehorst, Andrew L.; Scott, Forrest R.

2009-01-01

The multi-agency Flight in Icing Remote Sensing Team (FIRST), a consortium of the National Aeronautics and Space Administration (NASA), the Federal Aviation Administration (FAA), the National Center for Atmospheric Research (NCAR), the National Oceanographic and Atmospheric Administration (NOAA), and the Army Corps of Engineers (USACE), has developed technologies for remotely detecting hazardous inflight icing conditions. The USACE Cold Regions Research and Engineering Laboratory (CRREL) assessed the potential of onboard passive microwave radiometers for remotely detecting icing conditions ahead of aircraft. The dual wavelength system differences the brightness temperature of Space and clouds, with greater differences potentially indicating closer and higher magnitude cloud liquid water content (LWC). The Air Force RADiative TRANsfer model (RADTRAN) was enhanced to assess the flight track sensing concept, and a 'flying' RADTRAN was developed to simulate a radiometer system flying through simulated clouds. Neural network techniques were developed to invert brightness temperatures and obtain integrated cloud liquid water. In addition, a dual wavelength Direct-Detection Polarimeter Radiometer (DDPR) system was built for detecting hazardous drizzle drops. This paper reviews technology development to date and addresses initial polarimeter performance.

Cloud tolerance of remote sensing technologies to measure land surface temperature

USDA-ARS?s Scientific Manuscript database

Conventional means to estimate land surface temperature (LST) from space relies on the thermal infrared (TIR) spectral window and is limited to cloud-free scenes. To also provide LST estimates during periods with clouds, a new method was developed to estimate LST based on passive microwave (MW) obse...

Final Report fir DE-SC0005507 (A1618): The Development of an Improved Cloud Microphysical Product for Model and Remote Sensing Evaluation using RACORO Observations

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

McFarquhar, Greg M.

2012-09-21

We proposed to analyze data collected during the Routine Aerial Facilities (AAF) Clouds with Low Optical Water Depths (CLOWD) Optical Radiative Observations (RACORO) in order to develop an integrated product of cloud microphysical properties (number concentration of drops in different size bins, total liquid drop concentration integrated over all bin sizes, liquid water content LWC, extinction of liquid clouds, effective radius of water drops, and radar reflectivity factor) that could be used to evaluate large-eddy simulations (LES), general circulation models (GCMs) and ground-based remote sensing retrievals, and to develop cloud parameterizations with the end goal of improving the modeling ofmore » cloud processes and properties and their impact on atmospheric radiation. We have completed the development of this microphysical database. We investigated the differences in the size distributions measured by the Cloud and Aerosol Spectrometer (CAS) and the Forward Scattering Probe (FSSP), between the one dimensional cloud imaging probe (1DC) and the two-dimensional cloud imaging probe (2DC), and between the bulk LWCs measured by the Gerber probe against those derived from the size resolved probes.« less

Grid workflow validation using ontology-based tacit knowledge: A case study for quantitative remote sensing applications

NASA Astrophysics Data System (ADS)

Liu, Jia; Liu, Longli; Xue, Yong; Dong, Jing; Hu, Yingcui; Hill, Richard; Guang, Jie; Li, Chi

2017-01-01

Workflow for remote sensing quantitative retrieval is the ;bridge; between Grid services and Grid-enabled application of remote sensing quantitative retrieval. Workflow averts low-level implementation details of the Grid and hence enables users to focus on higher levels of application. The workflow for remote sensing quantitative retrieval plays an important role in remote sensing Grid and Cloud computing services, which can support the modelling, construction and implementation of large-scale complicated applications of remote sensing science. The validation of workflow is important in order to support the large-scale sophisticated scientific computation processes with enhanced performance and to minimize potential waste of time and resources. To research the semantic correctness of user-defined workflows, in this paper, we propose a workflow validation method based on tacit knowledge research in the remote sensing domain. We first discuss the remote sensing model and metadata. Through detailed analysis, we then discuss the method of extracting the domain tacit knowledge and expressing the knowledge with ontology. Additionally, we construct the domain ontology with Protégé. Through our experimental study, we verify the validity of this method in two ways, namely data source consistency error validation and parameters matching error validation.

Remote sensing of severe convective storms over Qinghai-Xizang Plateau

NASA Technical Reports Server (NTRS)

Hung, R. J.; Liu, J. M.; Tsao, D. Y.; Smith, R. E.

1984-01-01

The American satellite, GOES-1 was moved to the Indian Ocean at 58 deg E during the First GARP Global Experiment (FGGE). The Qinghai-Xizang Plateau significantly affects the initiation and development of heavy rainfall and severe storms in China, just as the Rocky Mountains influence the local storms in the United States. Satelite remote sensing of short-lived, meso-scale convective storms is particularly important for covering a huge area of a high elevation with a low population density, such as the Qinghai-Xizang Plateau. Results of this study show that a high growth rate of the convective clouds, followed by a rapid collapse of the cloud top, is associated with heavy rainfall in the area. The tops of the convective clouds developed over the Plateau lie between the altitudes of the two tropopauses, while the tops of convective clouds associated with severe storms in the United States usually extend much above the tropopause.

Combined Infrared Stereo and Laser Ranging Cloud Measurements from Shuttle Mission STS-85

NASA Technical Reports Server (NTRS)

Lancaster, R. S.; Spinhirne, J. D.; Manizade, K. F.

2004-01-01

Multiangle remote sensing provides a wealth of information for earth and climate monitoring, such as the ability to measure the height of cloud tops through stereoscopic imaging. As technology advances so do the options for developing spacecraft instrumentation versatile enough to meet the demands associated with multiangle measurements. One such instrument is the infrared spectral imaging radiometer, which flew as part of mission STS-85 of the space shuttle in 1997 and was the first earth- observing radiometer to incorporate an uncooled microbolometer array detector as its image sensor. Specifically, a method for computing cloud-top height with a precision of +/- 620 m from the multispectral stereo measurements acquired during this flight has been developed, and the results are compared with coincident direct laser ranging measurements from the shuttle laser altimeter. Mission STS-85 was the first space flight to combine laser ranging and thermal IR camera systems for cloud remote sensing.

Microwave remote sensing: Active and passive. Volume 1 - Microwave remote sensing fundamentals and radiometry

NASA Technical Reports Server (NTRS)

Ulaby, F. T.; Moore, R. K.; Fung, A. K.

1981-01-01

The three components of microwave remote sensing (sensor-scene interaction, sensor design, and measurement techniques), and the applications to geoscience are examined. The history of active and passive microwave sensing is reviewed, along with fundamental principles of electromagnetic wave propagation, antennas, and microwave interaction with atmospheric constituents. Radiometric concepts are reviewed, particularly for measurement problems for atmospheric and terrestrial sources of natural radiation. Particular attention is given to the emission by atmospheric gases, clouds, and rain as described by the radiative transfer function. Finally, the operation and performance characteristics of radiometer receivers are discussed, particularly for measurement precision, calibration techniques, and imaging considerations.

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

NASA Astrophysics Data System (ADS)

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

2017-02-01

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

Lidar Remote Sensing for Industry and Environment Monitoring

NASA Technical Reports Server (NTRS)

Singh, Upendra N. (Editor); Itabe, Toshikazu (Editor); Sugimoto, Nobuo (Editor)

2000-01-01

Contents include the following: 1. Keynote paper: Overview of lidar technology for industrial and environmental monitoring in Japan. 2. lidar technology I: NASA's future active remote sensing mission for earth science. Geometrical detector consideration s in laser sensing application (invited paper). 3. Lidar technology II: High-power femtosecond light strings as novel atmospheric probes (invited paper). Design of a compact high-sensitivity aerosol profiling lidar. 4. Lasers for lidars: High-energy 2 microns laser for multiple lidar applications. New submount requirement of conductively cooled laser diodes for lidar applications. 5. Tropospheric aerosols and clouds I: Lidar monitoring of clouds and aerosols at the facility for atmospheric remote sensing (invited paper). Measurement of asian dust by using multiwavelength lidar. Global monitoring of clouds and aerosols using a network of micropulse lidar systems. 6. Troposphere aerosols and clouds II: Scanning lidar measurements of marine aerosol fields at a coastal site in Hawaii. 7. Tropospheric aerosols and clouds III: Formation of ice cloud from asian dust particles in the upper troposphere. Atmospheric boundary layer observation by ground-based lidar at KMITL, Thailand (13 deg N, 100 deg. E). 8. Boundary layer, urban pollution: Studies of the spatial correlation between urban aerosols and local traffic congestion using a slant angle scanning on the research vessel Mirai. 9. Middle atmosphere: Lidar-observed arctic PSC's over Svalbard (invited paper). Sodium temperature lidar measurements of the mesopause region over Syowa Station. 10. Differential absorption lidar (dIAL) and DOAS: Airborne UV DIAL measurements of ozone and aerosols (invited paper). Measurement of water vapor, surface ozone, and ethylene using differential absorption lidar. 12. Space lidar I: Lightweight lidar telescopes for space applications (invited paper). Coherent lidar development for Doppler wind measurement from the International Space Station. 13. Space lidar II: Using coherent Doppler lidar to estimate river discharge. 14. Poster session: Lidar technology, optics for lidar. Laser for lidar. Middle atmosphere observations. Tropospheric observations (aerosols, clouds). Boundary layer, urban pollution. Differential absorption lidar. Doppler lidar. and Space lidar.

Flood warnings, flood disaster assessments, and flood hazard reduction: the roles of orbital remote sensing

NASA Technical Reports Server (NTRS)

Brakenridge, G. R.; Anderson, E.; Nghiem, S. V.; Caquard, S.; Shabaneh, T. B.

2003-01-01

Orbital remote sensing of the Earth is now poised to make three fundamental contributions towards reducing the detrimental effects of extreme floods. Effective Flood warning requires frequent radar observation of the Earth's surface through cloud cover. In contrast, both optical and radar wavelengths will increasingly be used for disaster assessment and hazard reduction.

Emerging Use of Dual Channel Infrared for Remote Sensing of Sea Ice

NASA Astrophysics Data System (ADS)

Lewis, N. S.; Serreze, M. C.; Gallaher, D. W.; Koenig, L.; Schaefer, K. M.; Campbell, G. G.; Thompson, J. A.; Grant, G.; Fetterer, F. M.

2017-12-01

Using GOES-16 data as a proxy for overhead persistent infrared, we examine the feasibility of using a dual channel shortwave / midwave infrared (SWIR/MWIR) approach to detect and chart sea ice in Hudson Bay through a series of images with a temporal scale of less than fifteen minutes. While not traditionally exploited for sea ice remote sensing, the availability of near continuous shortwave and midwave infrared data streams over the Arctic from overhead persistent infrared (OPIR) satellites could provide an invaluable source of information regarding the changing Arctic climate. Traditionally used for the purpose of missile warning and strategic defense, characteristics of OPIR make it an attractive source for Arctic remote sensing as the temporal resolution can provide insight into ice edge melt and motion processes. Fundamentally, the time series based algorithm will discern water/ice/clouds using a SWIR/MWIR normalized difference index. Cloud filtering is accomplished through removing pixels categorized as clouds while retaining a cache of previous ice/water pixels to replace any cloud obscured (and therefore omitted) pixels. Demonstration of the sensitivity of GOES-16 SWIR/MWIR to detect and discern water/ice/clouds provides a justification for exploring the utility of military OPIR sensors for civil and commercial applications. Potential users include the scientific community as well as emergency responders, the fishing industry, oil and gas industries, and transportation industries that are seeking to exploit changing conditions in the Arctic but require more accurate and timely ice charting products.

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.

Volcanic eruptions, hazardous ash clouds and visualization tools for accessing real-time infrared remote sensing data

NASA Astrophysics Data System (ADS)

Webley, P.; Dehn, J.; Dean, K. G.; Macfarlane, S.

2010-12-01

Volcanic eruptions are a global hazard, affecting local infrastructure, impacting airports and hindering the aviation community, as seen in Europe during Spring 2010 from the Eyjafjallajokull eruption in Iceland. Here, we show how remote sensing data is used through web-based interfaces for monitoring volcanic activity, both ground based thermal signals and airborne ash clouds. These ‘web tools’, http://avo.images.alaska.edu/, provide timely availability of polar orbiting and geostationary data from US National Aeronautics and Space Administration, National Oceanic and Atmosphere Administration and Japanese Meteorological Agency satellites for the North Pacific (NOPAC) region. This data is used operationally by the Alaska Volcano Observatory (AVO) for monitoring volcanic activity, especially at remote volcanoes and generates ‘alarms’ of any detected volcanic activity and ash clouds. The webtools allow the remote sensing team of AVO to easily perform their twice daily monitoring shifts. The web tools also assist the National Weather Service, Alaska and Kamchatkan Volcanic Emergency Response Team, Russia in their operational duties. Users are able to detect ash clouds, measure the distance from the source, area and signal strength. Within the web tools, there are 40 x 40 km datasets centered on each volcano and a searchable database of all acquired data from 1993 until present with the ability to produce time series data per volcano. Additionally, a data center illustrates the acquired data across the NOPAC within the last 48 hours, http://avo.images.alaska.edu/tools/datacenter/. We will illustrate new visualization tools allowing users to display the satellite imagery within Google Earth/Maps, and ArcGIS Explorer both as static maps and time-animated imagery. We will show these tools in real-time as well as examples of past large volcanic eruptions. In the future, we will develop the tools to produce real-time ash retrievals, run volcanic ash dispersion models from detected ash clouds and develop the browser interfaces to display other remote sensing datasets, such as volcanic sulfur dioxide detection.

Enhanced clear sky reflectance near clouds: What can be learned from it about aerosol properties?

NASA Astrophysics Data System (ADS)

Marshak, A.; Varnai, T.; Wen, G.; Chiu, J.

2009-12-01

Studies on aerosol direct and indirect effects require a precise separation of cloud-free and cloudy air. However, separation between cloud-free and cloudy areas from remotely-sensed measurements is ambiguous. The transition zone in the regions around clouds often stretches out tens of km, which are neither precisely clear nor precisely cloudy. We study the transition zone between cloud-free and cloudy air using MODerate-resolution Imaging Spectroradiometer (MODIS) and Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO) measurements. Both instruments show enhanced clear-sky reflectance (MODIS) and clear-sky backscatterer (CALIPSO) near clouds. Analyzing a large dataset of MODIS observations, we examine the effect of three-dimensional radiative interactions between clouds and cloud-free areas, also known as a cloud adjacency effect. The cloud adjacency effect is well observed in MODIS clear-sky data in the vicinity of clouds. Comparing with CALIPSO clear-sky backscatterer measurements, we show that this effect may be responsible for a large portion of the enhanced clear-sky reflectance observed by MODIS. Finally, we describe a simple model that estimates the cloud-induced enhanced reflectances of cloud-free areas in the vicinity of clouds. The model assumes that the enhancement is due entirely to Rayleigh scattering and is therefore bigger at shorter wavelengths, thus creating a so-called apparent “bluing” of aerosols in remote sensing retrievals.

On the division of contribution of the atmosphere and ocean in the radiation of the earth for the tasks of remote sensing and climate

NASA Astrophysics Data System (ADS)

Sushkevich, T. A.; Strelkov, S. A.; Maksakova, S. V.

2017-11-01

We are talking about the national achievements of the world level in theory of radiation transfer in the system atmosphere-oceans and about the modern scientific potential developing in Russia, which adequately provides a methodological basis for theoretical and computational studies of radiation processes and radiation fields in the natural environments with the use of supercomputers and massively parallel processing for problems of remote sensing and the climate of Earth. A model of the radiation field in system "clouds cover the atmosphere-ocean" to the separation of the contributions of clouds, atmosphere and ocean.

Determination of the optical thickness and effective particle radius of clouds from reflected solar radiation measurements. II - Marine stratocumulus observations

NASA Technical Reports Server (NTRS)

Nakajima, Teruyuki; King, Michael D.; Spinhirne, James D.; Radke, Lawrence F.

1991-01-01

A multispectral scanning radiometer has been used to obtain measurements of the reflection function of marine stratocumulus clouds at 0.75 micron and at 1.65 and 2.16 microns. These observations were obtained from the NASA ER-2 aircraft as part of the FIRE, conducted off the coast of southern California during July 1987. Multispectral images of the reflection function were used to derive the optical thickness and the effective particle radius of stratiform cloud layers on four days. In addition to the radiation measurements, in situ microphysical measurements were obtained from an aircraft. In this paper, the remote sensing results are compared with in situ observations, which show a good spatial correlation for both optical thickness and effective radius. These comparisons further show systematic differences between remote sensing and in situ values, with a tendency for remote sensing to overestimate the effective radius by about 2-3 microns, independent of particle radius. The optical thickness, in contrast, is somewhat overestimated for small optical thicknesses and underestimated for large optical thicknesses. An introduction of enhanced gaseous absorption at a wavelength of 2.16 microns successfully explains some of these observed discrepancies.

Cloud-Free Satellite Image Mosaics with Regression Trees and Histogram Matching.

Treesearch

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...

Remote observations of eruptive clouds and surface thermal activity during the 2009 eruption of Redoubt volcano

NASA Astrophysics Data System (ADS)

Webley, P. W.; Lopez, T. M.; Ekstrand, A. L.; Dean, K. G.; Rinkleff, P.; Dehn, J.; Cahill, C. F.; Wessels, R. L.; Bailey, J. E.; Izbekov, P.; Worden, A.

2013-06-01

Volcanoes often erupt explosively and generate a variety of hazards including volcanic ash clouds and gaseous plumes. These clouds and plumes are a significant hazard to the aviation industry and the ground features can be a major hazard to local communities. Here, we provide a chronology of the 2009 Redoubt Volcano eruption using frequent, low spatial resolution thermal infrared (TIR), mid-infrared (MIR) and ultraviolet (UV) satellite remote sensing data. The first explosion of the 2009 eruption of Redoubt Volcano occurred on March 15, 2009 (UTC) and was followed by a series of magmatic explosive events starting on March 23 (UTC). From March 23-April 4 2009, satellites imaged at least 19 separate explosive events that sent ash clouds up to 18 km above sea level (ASL) that dispersed ash across the Cook Inlet region. In this manuscript, we provide an overview of the ash clouds and plumes from the 19 explosive events, detailing their cloud-top heights and discussing the variations in infrared absorption signals. We show that the timing of the TIR data relative to the event end time was critical for inferring the TIR derived height and true cloud top height. The ash clouds were high in water content, likely in the form of ice, which masked the negative TIR brightness temperature difference (BTD) signal typically used for volcanic ash detection. The analysis shown here illustrates the utility of remote sensing data during volcanic crises to measure critical real-time parameters, such as cloud-top heights, changes in ground-based thermal activity, and plume/cloud location.

A Cloud Hydrology and Albedo Synthesis Mission (CHASM)

NASA Technical Reports Server (NTRS)

Davies, Roger

2004-01-01

This slide presentation reviews the Cloud Hydrology and Albedo Synthesis Mission (CHASM). The interaction of clouds with radiation and the hydrological cycle represents a huge uncertainty in our understanding of climate science and the modeling of climate system feedbacks. Despite the recognized need for a unified treatment of cloud processes, the present global average values of remotely sensed cloud liquid water and theoretically accepted values used for cloud physics and precipitation modeling differ by an order of magnitude. This is due in part to sampling and saturation effects, as well as to threedimensional cloud structure effects. In recent work with the Multiangle Imaging SpectroRadiometer (MISR) on Terra, we have gained new insights as to how the remote sensing approach could be significantly improved using a new instrument that combines passive optical (visible and near infrared) and microwave measurements, both as pushbroom scanners with multiple viewing angles, to the degree that measurements of liquid water path over deep convective clouds over land also become possible. This instrument would also have the ability of measuring height-resolved cloud-tracked winds using a hyper stereo retrieval technique. Deployment into a precessing low earth orbit would be optimal for measuring diurnal cloud activity. We have explored an instrument design concept for this that looks promising if we can establish partnerships that provide launch and bus capabilities.

Multispectral Cloud Retrievals from MODIS on Terra and Aqua

NASA Technical Reports Server (NTRS)

King, Michael D.; Platnick, Steven; Ackerman, Steven A.; Menzel, W. Paul; Gray, Mark A.; Moody, Eric G.

2002-01-01

The Moderate Resolution Imaging Spectroradiometer (MODIS) was developed by NASA and launched onboard the Terra spacecraft on December 18, 1999 and the Aqua spacecraft on April 26, 2002. MODIS scans a swath width sufficient to provide nearly complete global coverage every two days from each polar-orbiting, sun-synchronous, platform at an altitude of 705 km, and provides images in 36 spectral bands between 0.415 and 14.235 microns with spatial resolutions of 250 m (2 bands), 500 m (5 bands) and 1000 m (29 bands). In this paper we will describe the various methods being used for the remote sensing of cloud properties using MODIS data, focusing primarily on the MODIS cloud mask used to distinguish clouds, clear sky, heavy aerosol, and shadows on the ground, and on the remote sensing of cloud optical properties, especially cloud optical thickness and effective radius of water drops and ice crystals. Additional properties of clouds derived from multispectral thermal infrared measurements, especially cloud top pressure and emissivity, will also be described. Results will be presented of MODIS cloud properties both over the land and over the ocean, showing the consistency in cloud retrievals over various ecosystems used in the retrievals. The implications of this new observing system on global analysis of the Earth's environment will be discussed.

New Multispectral Cloud Retrievals from MODIS

NASA Technical Reports Server (NTRS)

King, Michael D.; Platnick, Steven; Tsay, Si-Chee; Ackerman, Steven A.; Menzel, W. Paul; Gray, Mark A.; Moody, Eric G.; Li, Jason Y.; Arnold, G. Thomas

2001-01-01

The Moderate Resolution Imaging Spectroradiometer (MODIS) was developed by NASA and launched onboard the Terra spacecraft on December 18, 1999. It achieved its final orbit and began Earth observations on February 24, 2000. MODIS scans a swath width sufficient to provide nearly complete global coverage every two days from a polar-orbiting, sun- synchronous, platform at an altitude of 705 km, and provides images in 36 spectral bands between 0.415 and 14.235 microns with spatial resolutions of 250 m (two bands), 500 m (five bands) and 1000 m (29 bands). In this paper we will describe the various methods being used for the remote sensing of cloud properties using MODIS data, focusing primarily on the MODIS cloud mask used to distinguish clouds, clear sky, heavy aerosol, and shadows on the ground, and on the remote sensing of cloud optical properties, especially cloud optical thickness and effective radius of water drops and ice crystals. Additional properties of clouds derived from multispectral thermal infrared measurements, especially cloud top pressure and emissivity, will also be described. Results will be presented of MODIS cloud properties both over the land and over the ocean, showing the consistency in cloud retrievals over various ecosystems used in the retrievals. The implications of this new observing system on global analysis of the Earth's environment will be discussed.

A feasibility study of using remotely sensed data for water resource models

NASA Technical Reports Server (NTRS)

Ruff, J. F.

1973-01-01

Remotely sensed data were collected to demonstrate the feasibility of applying the results to water resource problems. Photographs of the Wolf Creek watershed in southwestern Colorado were collected over a one year period. Cloud top temperatures were measured using a radiometer. Thermal imagery of the Wolf Creek Pass area was obtained during one pre-dawn flight. Remote sensing studies of water resource problems for user agencies were also conducted. The results indicated that: (1) remote sensing techniques could be used to assist in the solution of water resource problems; (2) photogrammetric determination of snow depths is feasible; (3) changes in turbidity or suspended material concentration can be observed; and (4) surface turbulence can be related to bed scour; and (5) thermal effluents into rivers can be monitored.

Improving our fundamental understanding of the role of aerosol-cloud interactions in the climate system.

PubMed

Seinfeld, John H; Bretherton, Christopher; Carslaw, Kenneth S; Coe, Hugh; DeMott, Paul J; Dunlea, Edward J; Feingold, Graham; Ghan, Steven; Guenther, Alex B; Kahn, Ralph; Kraucunas, Ian; Kreidenweis, Sonia M; Molina, Mario J; Nenes, Athanasios; Penner, Joyce E; Prather, Kimberly A; Ramanathan, V; Ramaswamy, Venkatachalam; Rasch, Philip J; Ravishankara, A R; Rosenfeld, Daniel; Stephens, Graeme; Wood, Robert

2016-05-24

The effect of an increase in atmospheric aerosol concentrations on the distribution and radiative properties of Earth's clouds is the most uncertain component of the overall global radiative forcing from preindustrial time. General circulation models (GCMs) are the tool for predicting future climate, but the treatment of aerosols, clouds, and aerosol-cloud radiative effects carries large uncertainties that directly affect GCM predictions, such as climate sensitivity. Predictions are hampered by the large range of scales of interaction between various components that need to be captured. Observation systems (remote sensing, in situ) are increasingly being used to constrain predictions, but significant challenges exist, to some extent because of the large range of scales and the fact that the various measuring systems tend to address different scales. Fine-scale models represent clouds, aerosols, and aerosol-cloud interactions with high fidelity but do not include interactions with the larger scale and are therefore limited from a climatic point of view. We suggest strategies for improving estimates of aerosol-cloud relationships in climate models, for new remote sensing and in situ measurements, and for quantifying and reducing model uncertainty.

Improving Our Fundamental Understanding of the Role of Aerosol Cloud Interactions in the Climate System

NASA Technical Reports Server (NTRS)

Seinfeld, John H.; Bretherton, Christopher; Carslaw, Kenneth S.; Coe, Hugh; DeMott, Paul J.; Dunlea, Edward J.; Feingold, Graham; Ghan, Steven; Guenther, Alex B.; Kahn, Ralph;

Improving our fundamental understanding of the role of aerosol-cloud interactions in the climate system

DOE PAGES

Seinfeld, John H.; Bretherton, Christopher; Carslaw, Kenneth S.; ...

2016-05-24

The effect of an increase in atmospheric aerosol concentrations on the distribution and radiative properties of Earth’s clouds is the most uncertain component of the overall global radiative forcing from pre-industrial time. General Circulation Models (GCMs) are the tool for predicting future climate, but the treatment of aerosols, clouds, and aerosol-cloud radiative effects carries large uncertainties that directly affect GCM predictions, such as climate sensitivity. Predictions are hampered by the large range of scales of interaction between various components that need to be captured. Observation systems (remote sensing, in situ) are increasingly being used to constrain predictions but significant challengesmore » exist, to some extent because of the large range of scales and the fact that the various measuring systems tend to address different scales. Fine-scale models represent clouds, aerosols, and aerosol-cloud interactions with high fidelity but do not include interactions with the larger scale and are therefore limited from a climatic point of view. Lastly, we suggest strategies for improving estimates of aerosol-cloud relationships in climate models, for new remote sensing and in situ measurements, and for quantifying and reducing model uncertainty.« less

Improving our fundamental understanding of the role of aerosol−cloud interactions in the climate system

PubMed Central

Seinfeld, John H.; Bretherton, Christopher; Carslaw, Kenneth S.; Coe, Hugh; DeMott, Paul J.; Dunlea, Edward J.; Feingold, Graham; Ghan, Steven; Guenther, Alex B.; Kraucunas, Ian; Molina, Mario J.; Nenes, Athanasios; Penner, Joyce E.; Prather, Kimberly A.; Ramanathan, V.; Ramaswamy, Venkatachalam; Rasch, Philip J.; Ravishankara, A. R.; Rosenfeld, Daniel; Stephens, Graeme; Wood, Robert

2016-01-01

The effect of an increase in atmospheric aerosol concentrations on the distribution and radiative properties of Earth’s clouds is the most uncertain component of the overall global radiative forcing from preindustrial time. General circulation models (GCMs) are the tool for predicting future climate, but the treatment of aerosols, clouds, and aerosol−cloud radiative effects carries large uncertainties that directly affect GCM predictions, such as climate sensitivity. Predictions are hampered by the large range of scales of interaction between various components that need to be captured. Observation systems (remote sensing, in situ) are increasingly being used to constrain predictions, but significant challenges exist, to some extent because of the large range of scales and the fact that the various measuring systems tend to address different scales. Fine-scale models represent clouds, aerosols, and aerosol−cloud interactions with high fidelity but do not include interactions with the larger scale and are therefore limited from a climatic point of view. We suggest strategies for improving estimates of aerosol−cloud relationships in climate models, for new remote sensing and in situ measurements, and for quantifying and reducing model uncertainty. PMID:27222566

Expading fluvial remote sensing to the riverscape: Mapping depth and grain size on the Merced River, California

NASA Astrophysics Data System (ADS)

Richardson, Ryan T.

This study builds upon recent research in the field of fluvial remote sensing by applying techniques for mapping physical attributes of rivers. Depth, velocity, and grain size are primary controls on the types of habitat present in fluvial ecosystems. This thesis focuses on expanding fluvial remote sensing to larger spatial extents and sub-meter resolutions, which will increase our ability to capture the spatial heterogeneity of habitat at a resolution relevant to individual salmonids and an extent relevant to species. This thesis consists of two chapters, one focusing on expanding the spatial extent over which depth can be mapped using Optimal Band Ratio Analysis (OBRA) and the other developing general relations for mapping grain size from three-dimensional topographic point clouds. The two chapters are independent but connected by the overarching goal of providing scientists and managers more useful tools for quantifying the amount and quality of salmonid habitat via remote sensing. The OBRA chapter highlights the true power of remote sensing to map depths from hyperspectral images as a central component of watershed scale analysis, while also acknowledging the great challenges involved with increasing spatial extent. The grain size mapping chapter establishes the first general relations for mapping grain size from roughness using point clouds. These relations will significantly reduce the time needed in the field by eliminating the need for independent measurements of grain size for calibrating the roughness-grain size relationship and thus making grain size mapping with SFM more cost effective for river restoration and monitoring. More data from future studies are needed to refine these relations and establish their validity and generality. In conclusion, this study adds to the rapidly growing field of fluvial remote sensing and could facilitate river research and restoration.

Super-cooled liquid water topped sub-arctic clouds and precipitation - investigation based on combination of ground-based in-situ and remote-sensing observations

NASA Astrophysics Data System (ADS)

Hirsikko, Anne; Brus, David; O'Connor, Ewan J.; Filioglou, Maria; Komppula, Mika; Romakkaniemi, Sami

2017-04-01

In the high and mid latitudes super-cooled liquid water layers are frequently observed on top of clouds. These layers are difficult to forecast with numerical weather prediction models, even though, they have strong influence on atmospheric radiative properties, cloud microphysical properties, and subsequently, precipitation. This work investigates properties of super-cooled liquid water layer topped sub-arctic clouds and precipitation observed with ground-based in-situ (cloud probes) and remote-sensing (a cloud radar, Doppler and multi-wavelength lidars) instrumentation during two-month long Pallas Cloud Experiment (PaCE 2015) in autumn 2015. Analysis is based on standard Cloudnet scheme supplemented with new retrieval products of the specific clouds and their properties. Combination of two scales of observation provides new information on properties of clouds and precipitation in the sub-arctic Pallas region. Current status of results will be presented during the conference. The authors acknowledge financial support by the Academy of Finland (Centre of Excellence Programme, grant no 272041; and ICINA project, grant no 285068), the ACTRIS2 - European Union's Horizon 2020 research and innovation programme under grant agreement No 654109, the KONE foundation, and the EU FP7 project BACCHUS (grant no 603445).

New Multispectral Cloud Retrievals from MODIS

NASA Technical Reports Server (NTRS)

Platnick, Steven; Tsay, Si-Chee; Ackerman, Steven A.; Gray, Mark A.; Moody, Eric G.; Li, Jason Y.; Arnold, G. T.; King, Michael D. (Technical Monitor)

2000-01-01

The Moderate Resolution Imaging Spectroradiometer (MODIS) was developed by NASA and launched onboard the Terra spacecraft on December 18, 1999. It achieved its final orbit and began Earth observations on February 24, 2000. MODIS scans a swath width sufficient to provide nearly complete global coverage every two days from a polar-orbiting, sun-synchronous, platform at an altitude of 705 km, and provides images in 36 spectral bands between 0.415 and 14.235 micrometers with spatial resolutions of 250 m (2 bands), 500 m (5 bands) and 1000 m (29 bands). These bands have been carefully selected to enable advanced studies of land, ocean, and atmospheric processes. In this paper I will describe the various methods being used for the remote sensing of cloud properties using MODIS data, focusing primarily on the MODIS cloud mask used to distinguish clouds, clear sky, heavy aerosol, and shadows on the ground, and on the remote sensing of cloud optical properties, especially cloud optical thickness and effective radius of cloud drops and ice crystals. Results will be presented of MODIS cloud properties both over the land and over the ocean, showing the consistency in cloud retrievals over various ecosystems used in the retrievals. The implications of this new observing system on global analysis of the Earth's environment will be discussed.

Modeling the Impact of Drizzle and 3D Cloud Structure on Remote Sensing of Effective Radius

NASA Technical Reports Server (NTRS)

Platnick, Steven; Zinner, Tobias; Ackerman, S.

2008-01-01

Remote sensing of cloud particle size with passive sensors like MODIS is an important tool for cloud microphysical studies. As a measure of the radiatively relevant droplet size, effective radius can be retrieved with different combinations of visible through shortwave infrared channels. MODIS observations sometimes show significantly larger effective radii in marine boundary layer cloud fields derived from the 1.6 and 2.1 pm channel observations than for 3.7 pm retrievals. Possible explanations range from 3D radiative transport effects and sub-pixel cloud inhomogeneity to the impact of drizzle formation on the droplet distribution. To investigate the potential influence of these factors, we use LES boundary layer cloud simulations in combination with 3D Monte Carlo simulations of MODIS observations. LES simulations of warm cloud spectral microphysics for cases of marine stratus and broken stratocumulus, each for two different values of cloud condensation nuclei density, produce cloud structures comprising droplet size distributions with and without drizzle size drops. In this study, synthetic MODIS observations generated from 3D radiative transport simulations that consider the full droplet size distribution will be generated for each scene. The operational MODIS effective radius retrievals will then be applied to the simulated reflectances and the results compared with the LES microphysics.

ARM KAZR-ARSCL Value Added Product

DOE Data Explorer

Jensen, Michael

2012-09-28

The Ka-band ARM Zenith Radars (KAZRs) have replaced the long-serving Millimeter Cloud Radars, or MMCRs. Accordingly, the primary MMCR Value Added Product (VAP), the Active Remote Sensing of CLouds (ARSCL) product, is being replaced by a KAZR-based version, the KAZR-ARSCL VAP. KAZR-ARSCL provides cloud boundaries and best-estimate time-height fields of radar moments.

Remote Sensing of Cloud, Aerosol, and Land Properties from MODIS: Applications to the East Asia Region

NASA Technical Reports Server (NTRS)

King, Michael D.; Platnick, Steven; Chu, D. Allen; Moody, Eric G.

2001-01-01

MODIS is an earth-viewing cross-track scanning spectroradiometer launched on the Terra satellite in December 1999. MODIS scans a swath width sufficient to provide nearly complete global coverage every two days from a polar-orbiting, sun-synchronous platform at an altitude of 705 km, and provides images in 36 spectral bands between 0.415 and 14.235 microns with spatial resolutions of 250 m (two bands), 500 m (five bands) and 1000 m (29 bands). These bands have been carefully selected to enable advanced studies of land, ocean, and atmospheric processes. In this presentation we review the comprehensive set of remote sensing algorithms that have been developed for the remote sensing of atmospheric properties using MODIS data, placing primary emphasis on the principal atmospheric applications of (i) developing a cloud mask for distinguishing clear sky from clouds, (ii) retrieving global cloud radiative and microphysical properties, including cloud top pressure and temperature, effective emissivity, cloud optical thickness, thermodynamic phase, and effective radius, (iii) monitoring tropospheric aerosol optical thickness over the land and ocean and aerosol size distribution over the ocean, (iv) determining atmospheric profiles of moisture and temperature, and (v) estimating column water amount. The physical principles behind the determination of each of these atmospheric products will be described, together with an example of their application using MODIS observations to the east Asian region in Spring 2001. All products are archived into two categories: pixel-level retrievals (referred to as Level-2 products) and global gridded products at a latitude and longitude resolution of 1 degree (Level-3 products). An overview of the MODIS atmosphere algorithms and products, status, validation activities, and early level-2 and -3 results will be presented.

Remote Sensing of Cloud, Aerosol, and Water Vapor Properties from MODIS

NASA Technical Reports Server (NTRS)

King, Michael D.; Platnick, Steven; Menzel, W. Paul; Kaufman, Yoram J.; Ackerman, Steven A.; Tanre, Didier; Gao, Bo-Cai

2001-01-01

MODIS is an earth-viewing cross-track scanning spectroradiometer launched on the Terra satellite in December 1999. MODIS scans a swath width sufficient to provide nearly complete global coverage every two days from a polar orbiting, sun-synchronous, platform at an altitude of 705 kilometers, and provides images in 36 spectral bands between 0.415 and 14.235 micrometers with spatial resolutions of 250 meters (2 bands), 500 meters (5 bands) and 1000 meters (29 bands). These bands have been carefully selected to enable advanced studies of land, ocean, and atmospheric processes. In this presentation we review the comprehensive set of remote sensing algorithms that have been developed for the remote sensing of atmospheric properties using MODIS data, placing primary emphasis on the principal atmospheric applications of (i) developing a cloud mask for distinguishing clear sky from clouds, (ii) retrieving global cloud radiative and microphysical properties, including cloud top pressure and temperature, effective emissivity, cloud optical thickness, thermodynamic phase, and effective radius, (iii) monitoring tropospheric aerosol optical thickness over the land and ocean and aerosol size distribution over the ocean, (iv) determining atmospheric profiles of moisture and temperature, and (v) estimating column water amount. The physical principles behind the determination of each of these atmospheric products will be described, together with an example of their application using MODIS observations. All products are archived into two categories: pixel-level retrievals (referred to as Level-2 products) and global gridded products at a latitude and longitude resolution of 1 degree (Level-3 products). An overview of the MODIS atmosphere algorithms and products, status, validation activities, and early level-2 and -3 results will be presented.

Preliminary Analysis of X-Band and Ka-Band Radar for Use in the Detection of Icing Conditions Aloft

NASA Technical Reports Server (NTRS)

Reehorst, Andrew L.; Koenig, George G.

2004-01-01

NASA and the U.S. Army Cold Regions Research and Engineering Laboratory (CRREL) have an on-going activity to develop remote sensing technologies for the detection and measurement of icing conditions aloft. Radar has been identified as a strong tool for this work. However, since the remote detection of icing conditions with the intent to identify areas of icing hazard is a new and evolving capability, there are no set requirements for radar sensitivity. This work is an initial attempt to quantify, through analysis, the sensitivity requirements for an icing remote sensing radar. The primary radar of interest for cloud measurements is Ka-band, however, since NASA is currently using an X-band unit, this frequency is also examined. Several aspects of radar signal analysis were examined. Cloud reflectivity was calculated for several forms of cloud using two different techniques. The Air Force Geophysical Laboratory (AFGL) cloud models, with different drop spectra represented by a modified gamma distribution, were utilized to examine several categories of cloud formation. Also a fundamental methods approach was used to allow manipulation of the cloud droplet size spectra. And an analytical icing radar simulator was developed to examine the complete radar system response to a configurable multi-layer cloud environment. Also discussed is the NASA vertical pointing X-band radar. The radar and its data system are described, and several summer weather events are reviewed.

Exploration of Data Fusion between Polarimetric Radar and Multispectral Image Data

DTIC Science & Technology

2012-09-01

target decomposition theorems in radar polarimetry . Transactions on Geoscience and Remote Sensing, 34(2), 498–518. Cloude, S. R. (1985). Target...Proceedings of the Journees Internationales De La Polarimetrie Radar (JIPR ‘90), Nantes, France. Huynen, J. R. (1965). Measurement of theTarget scattering...J. A. (2006). Review of passive imaging polarimetry for remote sensing applications. Applied Optics, 45(22), 5453–5469. Vanzyl, J., Zebker, H

Fitting the multitemporal curve: a fourier series approach to the missing data problem in remote sensing analysis

Treesearch

Evan Brooks; Valerie Thomas; Wynne Randolph; John Coulston

2012-01-01

With the advent of free Landsat data stretching back decades, there has been a surge of interest in utilizing remotely sensed data in multitemporal analysis for estimation of biophysical parameters. Such analysis is confounded by cloud cover and other image-specific problems, which result in missing data at various aperiodic times of the year. While there is a wealth...

Remote sensing of atmospheric particulates: Technological innovation and physical limitations in applications to short-range weather prediction

NASA Technical Reports Server (NTRS)

Curran, R. J.; Kropfil, R.; Hallett, J.

1984-01-01

Techniques for remote sensing of particles, from cloud droplet to hailstone size, using optical and microwave frequencies are reviewed. The inherent variability of atmospheric particulates is examined to delineate conditions when the signal can give information to be effectively utilized in a forecasting context. The physical limitations resulting from the phase, size, orientation and concentration variability of the particulates are assessed.

Spectra of polarized thermal radiation in a cloudy atmosphere: Line-by-Line and Monte Carlo model for passive remote sensing of cirrus and polar clouds

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.

Improvements in Cloud Remote Sensing from Fusing VIIRS and CrIS data

NASA Astrophysics Data System (ADS)

Heidinger, A. K.; Walther, A.; Lindsey, D. T.; Li, Y.; NOH, Y. J.; Botambekov, D.; Miller, S. D.; Foster, M. J.

2016-12-01

In the fall of 2016, NOAA began the operational production of cloud products from the S-NPP Visible and Infrared Imaging Radiometer Suite (VIIRS) using the NOAA Enterprise Algorithms. VIIRS, while providing unprecedented spatial resolution and imaging clarity, does lack certain IR channels that are beneficial to cloud remote sensing. At the UW Space Science and Engineering Center (SSEC), tools were written to generate the missing IR channels from the Cross Track Infrared Sounder (CrIS) and to map them into the VIIRS swath. The NOAA Enterprise Algorithms are also implemented into the NESDIS CLAVR-x system. CLAVR-x has been modified to use the fused VIIRS and CrIS data. This presentation will highlight the benefits offered by the CrIS data to the NOAA Enterprise Algorithms. In addition, these benefits also have enabled the generation of 3D cloud retrievals to support the request from the National Weather Service (NWS) for a Cloud Cover Layers product. Lastly, the benefits of using VIIRS and CrIS for achieving consistency with GOES-R will also be demonstrated.

A Sparse Dictionary Learning-Based Adaptive Patch Inpainting Method for Thick Clouds Removal from High-Spatial Resolution Remote Sensing Imagery

PubMed Central

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

A Sparse Dictionary Learning-Based Adaptive Patch Inpainting Method for Thick Clouds Removal from High-Spatial Resolution Remote Sensing Imagery.

PubMed

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.

Analysis of 2015 Winter In-Flight Icing Case Studies with Ground-Based Remote Sensing Systems Compared to In-Situ SLW Sondes

NASA Technical Reports Server (NTRS)

Serke, David J.; King, Michael Christopher; Hansen, Reid; Reehorst, Andrew L.

2016-01-01

National Aeronautics and Space Administration (NASA) and the National Center for Atmospheric Research (NCAR) have developed an icing remote sensing technology that has demonstrated skill at detecting and classifying icing hazards in a vertical column above an instrumented ground station. This technology has recently been extended to provide volumetric coverage surrounding an airport. Building on the existing vertical pointing system, the new method for providing volumetric coverage utilizes a vertical pointing cloud radar, a multi-frequency microwave radiometer with azimuth and elevation pointing, and a NEXRAD radar. The new terminal area icing remote sensing system processes the data streams from these instruments to derive temperature, liquid water content, and cloud droplet size for each examined point in space. These data are then combined to ultimately provide icing hazard classification along defined approach paths into an airport. To date, statistical comparisons of the vertical profiling technology have been made to Pilot Reports and Icing Forecast Products. With the extension into relatively large area coverage and the output of microphysical properties in addition to icing severity, the use of these comparators is not appropriate and a more rigorous assessment is required. NASA conducted a field campaign during the early months of 2015 to develop a database to enable the assessment of the new terminal area icing remote sensing system and further refinement of terminal area icing weather information technologies in general. In addition to the ground-based remote sensors listed earlier, in-situ icing environment measurements by weather balloons were performed to produce a comprehensive comparison database. Balloon data gathered consisted of temperature, humidity, pressure, super-cooled liquid water content, and 3-D position with time. Comparison data plots of weather balloon and remote measurements, weather balloon flight paths, bulk comparisons of integrated liquid water content and icing cloud extent agreement, and terminal-area hazard displays are presented. Discussions of agreement quality and paths for future development are also included.

Methods for Validation and Intercomparison of Remote Sensing and In situ Ice Water Measurements: Case Studies from CRYSTAL-FACE and Model Results

NASA Technical Reports Server (NTRS)

Sayres, D.S.; Pittman, J. V.; Smith, J. B.; Weinstock, E. M.; Anderson, J. G.; Heymsfield, G.; Li, L.; Fridlind, A.; Ackerman, A. S.

2004-01-01

Remote sensing observations, such as those from AURA, are necessary to understand the role of cirrus in determining the radiative and humidity budgets of the upper troposphere. Using these measurements quantitatively requires comparisons with in situ measurements that have previously been validated. However, a direct comparison of remote and in situ measurements is difficult due to the requirement that the spatial and temporal overlap be sufficient in order to guarantee that both instruments are measuring the same air parcel. A difficult as this might be for gas phase intercomparisons, cloud inhomogeneities significantly exacerbate the problem for cloud ice water content measurements. The CRYSTAL-FACE mission provided an opportunity to assess how well such intercomparisons can be performed and to establish flight plans that will be necessary for validation of future satellite instruments. During CRYSTAL-FACE, remote and in situ instruments were placed on different aircraft (NASA's ER-2 and WB-59, and the two planes flew in tandem so that the in situ payload flew in the field of view of the remote instruments. We show here that, even with this type of careful flight planning, it is not always possible to guarantee that remote and in situ instruments are viewing the same air parcel. We use ice water data derived from the in situ Harvard Total Water (HV-TW) instrument, and the remote Goddard Cloud Radar System (CRS) and show that agreement between HV-TW and CRS is a strong function of the horizontal separation and the time delay between the aircraft transects. We also use a cloud model to simulate possible trajectories through a cloud and evaluate the use of statistical analysis in determining the agreement between the two instruments. This type of analysis should guide flight planning for future intercomparison efforts, whether for aircraft or satellite-borne instrumentation.

Intercomparison of Microphysical Properties Derived from In-Situ Cloud and Remote Sensing Probes over the South East Atlantic Ocean

NASA Astrophysics Data System (ADS)

Miller, R.; McFarquhar, G. M.; Gupta, S.; Poellot, M.; O'Brien, J.; Delene, D. J.

2017-12-01

During the Observations of Aerosols Above Clouds and their Interactions (ORACLES) field campaigns, the NASA P3-Orion was equipped with in-situ probes measuring aerosol and cloud microphysical properties, while the NASA ER-2 was equipped with remote sensors retrieving cloud and aerosol quantities. During ORACLES 2017, the P-3 aircraft was equipped with two Clouds Droplet Probes (CDPs) sizing droplets with diameters (D) between 2 and 50µm. The two CDPs were mounted on pylons with different designs, the CDP on the newly designed left wing pylon positioned further below and ahead of the wing, whereas that on the right wing pylon directly below the wing. The P-3 was also equipped with a Cloud and Aerosol Spectrometer (CAS) sizing droplets with 0.51 µm < D < 50 µm, and three optical array probes: a 2D-stero probe (2DS) for 10 µm < D < 1280 µm; a High Volume Precipitation Sampler (HVPS-3), for 150 µm < D < 1.92 cm; and a Cloud Imaging Probe (CIP) for 25 µm < D < 1600 µm. In addition, a Phase Doppler Interferometer (PDI) for 0.5 µm < D < 2500 µm was included. In this presentation, the number distribution functions n(D) derived from different probes in their overlap ranges and bulk quantities, such as liquid water content (LWC), effective radius (re), total number concentration, extinction, skewness, dispersion and kurtosis derived by different probes over equivalent size ranges are compared. Additional comparison with bulk parameters (e.g., LWC measured by King and hot wire probes) and remotely sensed values are also made. The effect of the software package used to process the data is also examined by using two different packages, the National Center for Atmospheric Research Software for OAP Data Analysis (SODA2), and the University of Oklahoma/Illinois' Processing Software (UIOOPS) to process the optical array probe data. These intercomparisons, as a function of aircraft parameters and environmental conditions, help quantify uncertainties in measurements, improve our understanding of conditions under which the probes best function, assist in the development of a probe-independent best estimate of cloud microphysical parameters, and evaluate the quality of remote sensing retrievals. This in turn, will allow the use of these data sets to quantify cloud-aerosol relationships in the southeast Atlantic.

Validation of a radiosonde-based cloud layer detection method against a ground-based remote sensing method at multiple ARM sites

NASA Astrophysics Data System (ADS)

Zhang, Jinqiang; Li, Zhanqing; Chen, Hongbin; Cribb, Maureen

2013-01-01

Cloud vertical structure is a key quantity in meteorological and climate studies, but it is also among the most difficult quantities to observe. In this study, we develop a long-term (10 years) radiosonde-based cloud profile product for the U.S. Department of Energy's Atmospheric Radiation Measurement (ARM) program Southern Great Plains (SGP), Tropical Western Pacific (TWP), and North Slope of Alaska (NSA) sites and a shorter-term product for the ARM Mobile Facility (AMF) deployed in Shouxian, Anhui Province, China (AMF-China). The AMF-China site was in operation from 14 May to 28 December 2008; the ARM sites have been collecting data for over 15 years. The Active Remote Sensing of Cloud (ARSCL) value-added product (VAP), which combines data from the 95-GHz W-band ARM Cloud Radar (WACR) and/or the 35-GHz Millimeter Microwave Cloud Radar (MMCR), is used in this study to validate the radiosonde-based cloud layer retrieval method. The performance of the radiosonde-based cloud layer retrieval method applied to data from different climate regimes is evaluated. Overall, cloud layers derived from the ARSCL VAP and radiosonde data agree very well at the SGP and AMF-China sites. At the TWP and NSA sites, the radiosonde tends to detect more cloud layers in the upper troposphere.

Parameterization of Cirrus Cloud Vertical Profiles and Geometrical Thickness Using CALIPSO and CloudSat Data

NASA Astrophysics Data System (ADS)

Khatri, P.; Iwabuchi, H.; Saito, M.

2017-12-01

High-level cirrus clouds, which normally occur over more than 20% of the globe, are known to have profound impacts on energy budget and climate change. The scientific knowledge regarding the vertical structure of such high-level cirrus clouds and their geometrical thickness are relatively poorer compared to low-level water clouds. Knowledge regarding cloud vertical structure is especially important in passive remote sensing of cloud properties using infrared channels or channels strongly influenced by gaseous absorption when clouds are geometrically thick and optically thin. Such information is also very useful for validating cloud resolving numerical models. This study analyzes global scale data of ice clouds identified by Cloud profiling Radar (CPR) onboard CloudSat and Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) onboard CALIPSO to parameterize (i) vertical profiles of ice water content (IWC), cloud-particle effective radius (CER), and ice-particle number concentration for varying ice water path (IWP) values and (ii) the relation of cloud geometrical thickness (CGT) with IWP and CER for varying cloud top temperature (CTT) values. It is found that the maxima in IWC and CER profile shifts towards cloud base with the increase of IWP. Similarly, if the cloud properties remain same, CGT shows an increasing trend with the decrease of CTT. The implementation of such cloud vertical inhomogeneity parameterization in the forward model used in the Integrated Cloud Analysis System ICAS (Iwabuchi et al., 2016) generally shows increase of brightness temperatures in infrared channels compared to vertically homogeneous cloud assumption. The cloud vertical inhomogeneity is found to bring noticeable changes in retrieved cloud properties. Retrieved CER and cloud top height become larger for optically thick cloud. We will show results of comparison of cloud properties retrieved from infrared measurements and active remote sensing.

Overview of Mount Washington Icing Sensors Project

NASA Technical Reports Server (NTRS)

Ryerson, Charles C.; Politovich, Marcia K.; Rancourt, Kenneth L.; Koenig, George G.; Reinking, Roger F.; Miller, Dean R.

2003-01-01

NASA, the FAA, the Department of Defense, the National Center for Atmospheric Research and NOAA are developing techniques for retrieving cloud microphysical properties from a variety of remote sensing technologies. The intent is to predict aircraft icing conditions ahead of aircraft. The Mount Washington Icing Sensors Project MWISP), conducted in April, 1999 at Mt. Washington, NH, was organized to evaluate technologies for the prediction of icing conditions ahead of aircraft in a natural environment, and to characterize icing cloud and drizzle environments. April was selected for operations because the Summit is typically in cloud, generally has frequent freezing precipitation in spring, and the clouds have high liquid water contents. Remote sensing equipment, consisting of radars, radiometers and a lidar, was placed at the base of the mountain, and probes measuring cloud particles, and a radiometer, were operated from the Summit. NASA s Twin Otter research aircraft also conducted six missions over the site. Operations spanned the entire month of April, which was dominated by wrap-around moisture from a low pressure center stalled off the coast of Labrador providing persistent upslope clouds with relatively high liquid water contents and mixed phase conditions. Preliminary assessments indicate excellent results from the lidar, radar polarimetry, radiosondes and summit and aircraft measurements.

Observations of Stratiform Lightning Flashes and Their Microphysical and Kinematic Environments

NASA Technical Reports Server (NTRS)

Lang, Timothy J.; Williams, Earle

2016-01-01

During the Midlatitude Continental Convective Clouds Experiment (MC3E), combined observations of clouds and precipitation were made from airborne and ground-based in situ and remote sensing platforms. These observations were coordinated for multiple mesoscale convective systems (MCSs) that passed over the MC3E domain in northern Oklahoma. Notably, during a storm on 20 May 2011 in situ and remote sensing airborne observations were made near the times and locations of stratiform positive cloud-to-ground (+CG) lightning flashes. These +CGs resulted from extremely large stratiform lightning flashes that were hundreds of km in length and lasted several seconds. This dataset provides an unprecedented look at kinematic and microphysical environments in the vicinity of large, powerful, and long-lived stratiform lightning flashes. We will use this dataset to understand the influence of low liquid water contents (LWCs) in the electrical charging of MCS stratiform regions.

Observations of Stratiform Lightning Flashes and Their Microphysical and Kinematic Environments

NASA Technical Reports Server (NTRS)

Lang, Timothy J.; Williams, Earle

2017-01-01

During the Midlatitude Continental Convective Clouds Experiment (MC3E), combined observations of clouds and precipitation were made from airborne and ground-based in situ and remote sensing platforms. These observations were coordinated for multiple mesoscale convective systems (MCSs) that passed over the MC3E domain in northern Oklahoma. Notably, during a storm on 20 May 2011 in situ and remote sensing airborne observations were made near the times and locations of stratiform positive cloud-to-ground (+CG) lightning flashes. These +CGs resulted from extremely large stratiform lightning flashes that were hundreds of km in length and lasted several seconds. This dataset provides an unprecedented look at kinematic and microphysical environments in the vicinity of large, powerful, and long-lived stratiform lightning flashes. We will use this dataset to understand the influence of low liquid water contents (LWCs) in the electrical charging of MCS stratiform regions.

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.

Satellite Remote Sensing of Aerosol Forcing

NASA Technical Reports Server (NTRS)

Remer, Lorraine; Kaufman, Yoram; Ramaprasad, Jaya; Procopio, Aline; Levin, Zev

1999-01-01

The role of aerosol forcing remains one of the largest uncertainties in estimating man's impact on the global climate system. One school of thought suggests that remote sensing by satellite sensors will provide the data necessary to narrow these uncertainties. While satellite measurements of direct aerosol forcing appear to be straightforward, satellite measurements of aerosol indirect forcing will be more complicated. Pioneering studies identified indirect aerosol forcing using AVHRR data in the biomass burning regions of Brazil. We have expanded this analysis with AVHRR to include an additional year of data and assimilated water vapor fields. The results show similar latitudinal dependence as reported by Kaufman and Fraser, but by using water vapor observations we conclude that latitude is not a proxy for water vapor and the strength of the indirect effect is not correlated to water vapor amounts. In addition to the AVHRR study we have identified indirect aerosol forcing in Brazil at much smaller spatial scales using the MODIS Airborne Simulator. The strength of the indirect effect appears to be related to cloud type and cloud dynamics. There is a suggestion that some of the cloud dynamics may be influenced by smoke destabilization of the atmospheric column. Finally, this study attempts to quantify remote sensing limitations due to the accuracy limits of the retrieval algorithms. We use a combination of numerical aerosol transport models, ground-based AERONET data and ISCCP cloud climatology to determine how much of the forcing occurs in regions too clean to determine from satellite retrievals.

Active and Passive 3D Vector Radiative Transfer with Preferentially-Aligned Ice Particles

NASA Technical Reports Server (NTRS)

Adams, Ian S.; Munchak, Stephen J.; Pelissier, Craig S.; Kuo, Kwo-Sen; Heymsfield, Gerald M.

2017-01-01

For the purposes of interpreting active (radar) and passive (radiometer) microwave and millimeter wave remote sensing data, we have constructed a consistent radiative transfer modeling framework to simulate the responses for arbitrary sensors with differing sensing geometries and hardware configurations. As part of this work, we have implemented a recent method for calculating the electromagnetic properties of individual ice crystals and snow flakes. These calculations will allow us to exploit polarized remote sensing observations to discriminate different particles types and elucidate dynamics of cloud and precipitating systems.

PolarBRDF: A general purpose Python package for visualization and quantitative analysis of multi-angular remote sensing measurements

NASA Astrophysics Data System (ADS)

Singh, Manoj K.; Gautam, Ritesh; Gatebe, Charles K.; Poudyal, Rajesh

2016-11-01

The Bidirectional Reflectance Distribution Function (BRDF) is a fundamental concept for characterizing the reflectance property of a surface, and helps in the analysis of remote sensing data from satellite, airborne and surface platforms. Multi-angular remote sensing measurements are required for the development and evaluation of BRDF models for improved characterization of surface properties. However, multi-angular data and the associated BRDF models are typically multidimensional involving multi-angular and multi-wavelength information. Effective visualization of such complex multidimensional measurements for different wavelength combinations is presently somewhat lacking in the literature, and could serve as a potentially useful research and teaching tool in aiding both interpretation and analysis of BRDF measurements. This article describes a newly developed software package in Python (PolarBRDF) to help visualize and analyze multi-angular data in polar and False Color Composite (FCC) forms. PolarBRDF also includes functionalities for computing important multi-angular reflectance/albedo parameters including spectral albedo, principal plane reflectance and spectral reflectance slope. Application of PolarBRDF is demonstrated using various case studies obtained from airborne multi-angular remote sensing measurements using NASA's Cloud Absorption Radiometer (CAR). Our visualization program also provides functionalities for untangling complex surface/atmosphere features embedded in pixel-based remote sensing measurements, such as the FCC imagery generation of BRDF measurements of grasslands in the presence of wildfire smoke and clouds. Furthermore, PolarBRDF also provides quantitative information of the angular distribution of scattered surface/atmosphere radiation, in the form of relevant BRDF variables such as sunglint, hotspot and scattering statistics.

PolarBRDF: A general purpose Python package for visualization and quantitative analysis of multi-angular remote sensing measurements

NASA Astrophysics Data System (ADS)

Poudyal, R.; Singh, M.; Gautam, R.; Gatebe, C. K.

2016-12-01

The Bidirectional Reflectance Distribution Function (BRDF) is a fundamental concept for characterizing the reflectance property of a surface, and helps in the analysis of remote sensing data from satellite, airborne and surface platforms. Multi-angular remote sensing measurements are required for the development and evaluation of BRDF models for improved characterization of surface properties. However, multi-angular data and the associated BRDF models are typically multidimensional involving multi-angular and multi-wavelength information. Effective visualization of such complex multidimensional measurements for different wavelength combinations is presently somewhat lacking in the literature, and could serve as a potentially useful research and teaching tool in aiding both interpretation and analysis of BRDF measurements. This article describes a newly developed software package in Python (PolarBRDF) to help visualize and analyze multi-angular data in polar and False Color Composite (FCC) forms. PolarBRDF also includes functionalities for computing important multi-angular reflectance/albedo parameters including spectral albedo, principal plane reflectance and spectral reflectance slope. Application of PolarBRDF is demonstrated using various case studies obtained from airborne multi-angular remote sensing measurements using NASA's Cloud Absorption Radiometer (CAR)- http://car.gsfc.nasa.gov/. Our visualization program also provides functionalities for untangling complex surface/atmosphere features embedded in pixel-based remote sensing measurements, such as the FCC imagery generation of BRDF measurements of grasslands in the presence of wildfire smoke and clouds. Furthermore, PolarBRDF also provides quantitative information of the angular distribution of scattered surface/atmosphere radiation, in the form of relevant BRDF variables such as sunglint, hotspot and scattering statistics.

Polarbrdf: A General Purpose Python Package for Visualization Quantitative Analysis of Multi-Angular Remote Sensing Measurements

NASA Technical Reports Server (NTRS)

Singh, Manoj K.; Gautam, Ritesh; Gatebe, Charles K.; Poudyal, Rajesh

2016-01-01

The Bidirectional Reflectance Distribution Function (BRDF) is a fundamental concept for characterizing the reflectance property of a surface, and helps in the analysis of remote sensing data from satellite, airborne and surface platforms. Multi-angular remote sensing measurements are required for the development and evaluation of BRDF models for improved characterization of surface properties. However, multi-angular data and the associated BRDF models are typically multidimensional involving multi-angular and multi-wavelength information. Effective visualization of such complex multidimensional measurements for different wavelength combinations is presently somewhat lacking in the literature, and could serve as a potentially useful research and teaching tool in aiding both interpretation and analysis of BRDF measurements. This article describes a newly developed software package in Python (PolarBRDF) to help visualize and analyze multi-angular data in polar and False Color Composite (FCC) forms. PolarBRDF also includes functionalities for computing important multi-angular reflectance/albedo parameters including spectral albedo, principal plane reflectance and spectral reflectance slope. Application of PolarBRDF is demonstrated using various case studies obtained from airborne multi-angular remote sensing measurements using NASA's Cloud Absorption Radiometer (CAR). Our visualization program also provides functionalities for untangling complex surface/atmosphere features embedded in pixel-based remote sensing measurements, such as the FCC imagery generation of BRDF measurements of grasslands in the presence of wild fire smoke and clouds. Furthermore, PolarBRDF also provides quantitative information of the angular distribution of scattered surface/atmosphere radiation, in the form of relevant BRDF variables such as sunglint, hotspot and scattering statistics.

Added Value of Far-Infrared Radiometry for Ice Cloud Remote Sensing

NASA Astrophysics Data System (ADS)

Libois, Q.; Blanchet, J. P.; Ivanescu, L.; S Pelletier, L.; Laurence, C.

2017-12-01

Several cloud retrieval algorithms based on satellite observations in the infrared have been developed in the last decades. However, most of these observations only cover the midinfrared (MIR, λ < 15 μm) part of the spectrum, and none are available in the far-infrared (FIR, λ ≥ 15 μm). Recent developments in FIR sensors technology, though, now make it possible to consider spaceborne remote sensing in the FIR. Here we show that adding a few FIR channels with realistic radiometric performances to existing spaceborne narrowband radiometers would significantly improve their ability to retrieve ice cloud radiative properties. For clouds encountered in the polar regions and the upper troposphere, where the atmosphere above clouds is sufficiently transparent in the FIR, using FIR channels would reduce by more than 50% the uncertainties on retrieved values of optical thickness, effective particle diameter, and cloud top altitude. This would somehow extend the range of applicability of current infrared retrieval methods to the polar regions and to clouds with large optical thickness, where MIR algorithms perform poorly. The high performance of solar reflection-based algorithms would thus be reached in nighttime conditions. Using FIR observations is a promising venue for studying ice cloud microphysics and precipitation processes, which is highly relevant for cirrus clouds and convective towers, and for investigating the water cycle in the driest regions of the atmosphere.

Remote Sensing of Energy Distribution Characteristics over the Tibet

NASA Astrophysics Data System (ADS)

Shi, J.; Husi, L.; Wang, T.

2017-12-01

The overall objective of our study is to quantify the spatiotemporal characteristics and changes of typical factors dominating water and energy cycles in the Tibet region. Especially, we focus on variables of clouds optical & microphysical parameters, surface shortwave and longwave radiation. Clouds play a key role in the Tibetan region's water and energy cycles. They seriously impact the precipitation, temperature and surface energy distribution. Considering that proper cloud products with relatively higher spatial and temporal sampling and with satisfactory accuracy are serious lacking in the Tibet region, except cloud optical thickness, cloud effective radius and liquid/ice water content, the cloud coverage dynamics at hourly scales also analyzed jointly based on measurements of Himawari-8, and MODIS. Surface radiation, as an important energy source in perturbating the Tibet's evapotranspiration, snow and glacier melting, is a controlling factor in energy balance in the Tibet region. All currently available radiation products in this area are not suitable for regional scale study of water and energy exchange and snow/glacier melting due to their coarse resolution and low accuracies because of cloud and topography. A strategy for deriving land surface upward and downward radiation by fusing optical and microwave remote sensing data is proposed. At the same time, the big topographic effect on the surface radiation are also modelled and analyzed over the Tibet region.

Remote Sensing the Vertical Profile of Cloud Droplet Effective Radius, Thermodynamic Phase, and Temperature

NASA Technical Reports Server (NTRS)

Martins, J. V.; Marshak, A.; Remer, L. A.; Rosenfeld, D.; Kaufman, Y. J.; Fernandez-Borda, R.; Koren, I.; Correia, A. L.; Zubko, V.; Artaxo, P.

2011-01-01

Cloud-aerosol interaction is a key issue in the climate system, affecting the water cycle, the weather, and the total energy balance including the spatial and temporal distribution of latent heat release. Information on the vertical distribution of cloud droplet microphysics and thermodynamic phase as a function of temperature or height, can be correlated with details of the aerosol field to provide insight on how these particles are affecting cloud properties and their consequences to cloud lifetime, precipitation, water cycle, and general energy balance. Unfortunately, today's experimental methods still lack the observational tools that can characterize the true evolution of the cloud microphysical, spatial and temporal structure in the cloud droplet scale, and then link these characteristics to environmental factors and properties of the cloud condensation nuclei. Here we propose and demonstrate a new experimental approach (the cloud scanner instrument) that provides the microphysical information missed in current experiments and remote sensing options. Cloud scanner measurements can be performed from aircraft, ground, or satellite by scanning the side of the clouds from the base to the top, providing us with the unique opportunity of obtaining snapshots of the cloud droplet microphysical and thermodynamic states as a function of height and brightness temperature in clouds at several development stages. The brightness temperature profile of the cloud side can be directly associated with the thermodynamic phase of the droplets to provide information on the glaciation temperature as a function of different ambient conditions, aerosol concentration, and type. An aircraft prototype of the cloud scanner was built and flew in a field campaign in Brazil.

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.

Probability theory for 3-layer remote sensing radiative transfer model: univariate case.

PubMed

Ben-David, Avishai; Davidson, Charles E

2012-04-23

A probability model for a 3-layer radiative transfer model (foreground layer, cloud layer, background layer, and an external source at the end of line of sight) has been developed. The 3-layer model is fundamentally important as the primary physical model in passive infrared remote sensing. The probability model is described by the Johnson family of distributions that are used as a fit for theoretically computed moments of the radiative transfer model. From the Johnson family we use the SU distribution that can address a wide range of skewness and kurtosis values (in addition to addressing the first two moments, mean and variance). In the limit, SU can also describe lognormal and normal distributions. With the probability model one can evaluate the potential for detecting a target (vapor cloud layer), the probability of observing thermal contrast, and evaluate performance (receiver operating characteristics curves) in clutter-noise limited scenarios. This is (to our knowledge) the first probability model for the 3-layer remote sensing geometry that treats all parameters as random variables and includes higher-order statistics. © 2012 Optical Society of America

Kriging in the Shadows: Geostatistical Interpolation for Remote Sensing

NASA Technical Reports Server (NTRS)

Rossi, Richard E.; Dungan, Jennifer L.; Beck, Louisa R.

1994-01-01

It is often useful to estimate obscured or missing remotely sensed data. Traditional interpolation methods, such as nearest-neighbor or bilinear resampling, do not take full advantage of the spatial information in the image. An alternative method, a geostatistical technique known as indicator kriging, is described and demonstrated using a Landsat Thematic Mapper image in southern Chiapas, Mexico. The image was first classified into pasture and nonpasture land cover. For each pixel that was obscured by cloud or cloud shadow, the probability that it was pasture was assigned by the algorithm. An exponential omnidirectional variogram model was used to characterize the spatial continuity of the image for use in the kriging algorithm. Assuming a cutoff probability level of 50%, the error was shown to be 17% with no obvious spatial bias but with some tendency to categorize nonpasture as pasture (overestimation). While this is a promising result, the method's practical application in other missing data problems for remotely sensed images will depend on the amount and spatial pattern of the unobscured pixels and missing pixels and the success of the spatial continuity model used.

Exploring the Effects of Cloud Vertical Structure on Cloud Microphysical Retrievals based on Polarized Reflectances

NASA Astrophysics Data System (ADS)

Miller, D. J.; Zhang, Z.; Platnick, S. E.; Ackerman, A. S.; Cornet, C.; Baum, B. A.

2013-12-01

A polarized cloud reflectance simulator was developed by coupling an LES cloud model with a polarized radiative transfer model to assess the capabilities of polarimetric cloud retrievals. With future remote sensing campaigns like NASA's Aerosols/Clouds/Ecosystems (ACE) planning to feature advanced polarimetric instruments it is important for the cloud remote sensing community to understand the retrievable information available and the related systematic/methodical limitations. The cloud retrieval simulator we have developed allows us to probe these important questions in a realistically relevant test bed. Our simulator utilizes a polarized adding-doubling radiative transfer model and an LES cloud field from a DHARMA simulation (Ackerman et al. 2004) with cloud properties based on the stratocumulus clouds observed during the DYCOMS-II field campaign. In this study we will focus on how the vertical structure of cloud microphysics can influence polarized cloud effective radius retrievals. Numerous previous studies have explored how retrievals based on total reflectance are affected by cloud vertical structure (Platnick 2000, Chang and Li 2002) but no such studies about the effects of vertical structure on polarized retrievals exist. Unlike the total cloud reflectance, which is predominantly multiply scattered light, the polarized reflectance is primarily the result of singly scattered photons. Thus the polarized reflectance is sensitive to only the uppermost region of the cloud (tau~<1) where photons can scatter once and still escape before being scattered again. This means that retrievals based on polarized reflectance have the potential to reveal behaviors specific to the cloud top. For example cloud top entrainment of dry air, a major influencer on the microphysical development of cloud droplets, can be potentially studied with polarimetric retrievals.

Recent Progress in the Remote Detection of Vapours and Gaseous Pollutants.

ERIC Educational Resources Information Center

Moffat, A. J.; And Others

Work has been continuing on the correlation spectrometry techniques described at previous remote sensing symposiums. Advances in the techniques are described which enable accurate quantitative measurements of diffused atmospheric gases to be made using controlled light sources, accurate quantitative measurements of gas clouds relative to…

Remote sensing of cirrus cloud vertical size profile using MODIS data

NASA Astrophysics Data System (ADS)

Wang, Xingjuan; Liou, K. N.; Ou, Steve S. C.; Mace, G. G.; Deng, M.

2009-05-01

This paper describes an algorithm for inferring cirrus cloud top and cloud base effective particle sizes and cloud optical thickness from the Moderate Resolution Imaging Spectroradiometer (MODIS) 0.645, 1.64 and 2.13, and 3.75 μm band reflectances/radiances. This approach uses a successive minimization method based on a look-up library of precomputed reflectances/radiances from an adding-doubling radiative transfer program, subject to corrections for Rayleigh scattering at the 0.645 μm band, above-cloud water vapor absorption, and 3.75 μm thermal emission. The algorithmic accuracy and limitation of the retrieval method were investigated by synthetic retrievals subject to the instrument noise and the perturbation of input parameters. The retrieval algorithm was applied to three MODIS cirrus scenes over the Atmospheric Radiation Measurement Program's southern Great Plain site, north central China, and northeast Asia. The reliability of retrieved cloud optical thicknesses and mean effective particle sizes was evaluated by comparison with MODIS cloud products and qualitatively good correlations were obtained for all three cases, indicating that the performance of the vertical sizing algorithm is comparable with the MODIS retrieval program. Retrieved cloud top and cloud base ice crystal effective sizes were also compared with those derived from the collocated ground-based millimeter wavelength cloud radar for the first case and from the Cloud Profiling Radar onboard CloudSat for the other two cases. Differences between retrieved and radar-derived cloud properties are discussed in light of assumptions made in the collocation process and limitations in radar remote sensing characteristics.

Cloud remote sensing from space in the era of the A-Train

NASA Astrophysics Data System (ADS)

Stephens, Graeme L.; Vane, Deborah G.

2006-09-01

The clouds of Earth are fundamental to most aspects of human life. Through production of precipitation, they are essential for delivering and sustaining the supplies of fresh water upon which human life depends. Clouds further exert a principal influence on the planet's energy balance. It is in clouds that latent heat is released through the process of condensation and the formation of precipitation affecting the development and evolution of the planet's storm systems. Clouds further exert a profound influence on the solar and infrared radiation that enters and leaves the atmosphere, further exerting profound effects on climate and on forces that affect climate change (Stephens, 2005). It is for these reasons, among others, that the need to observe the distribution and variability of the properties of clouds and precipitation has emerged as a priority in Earth observations. Most past and current observational programs are contructed in such a way that clouds and precipitation are treated as separate entities. Nature does not work this way and there is much to be gained scientifically in moving away from these artificial practices toward observing clouds and precipitation properties jointly. We are now embarking on a new age of remote sensing of clouds and precipitation using active sensors, starting with the tropical rainfall measurement mission (TRMM) and continuing on with the A-Train (described below). This new age provides us with the opportunity to move away from past and present artificial observing practices offering a more unified approach to observing clouds and precipitation properties jointly.

Probing Clouds in Planets with a Simple Radiative Transfer Model: The Jupiter Case

ERIC Educational Resources Information Center

Mendikoa, Inigo; Perez-Hoyos, Santiago; Sanchez-Lavega, Agustin

2012-01-01

Remote sensing of planets evokes using expensive on-orbit satellites and gathering complex data from space. However, the basic properties of clouds in planetary atmospheres can be successfully estimated with small telescopes even from an urban environment using currently available and affordable technology. This makes the process accessible for…

Climbing the Slope of Enlightenment during NASA's Arctic Boreal Vulnerability Experiment

NASA Astrophysics Data System (ADS)

Griffith, P. C.; Hoy, E.; Duffy, D.; McInerney, M.

2015-12-01

The Arctic Boreal Vulnerability Experiment (ABoVE) is a new field campaign sponsored by NASA's Terrestrial Ecology Program and designed to improve understanding of the vulnerability and resilience of Arctic and boreal social-ecological systems to environmental change (http://above.nasa.gov). ABoVE is integrating field-based studies, modeling, and data from airborne and satellite remote sensing. The NASA Center for Climate Simulation (NCCS) has partnered with the NASA Carbon Cycle and Ecosystems Office (CCEO) to create a high performance science cloud for this field campaign. The ABoVE Science Cloud combines high performance computing with emerging technologies and data management with tools for analyzing and processing geographic information to create an environment specifically designed for large-scale modeling, analysis of remote sensing data, copious disk storage for "big data" with integrated data management, and integration of core variables from in-situ networks. The ABoVE Science Cloud is a collaboration that is accelerating the pace of new Arctic science for researchers participating in the field campaign. Specific examples of the utilization of the ABoVE Science Cloud by several funded projects will be presented.

Relations Between Cloud Condensation Nuclei And Aerosol Optical Properties Relevant to Remote Sensing: Airborne Measurements in Biomass Burning, Pollution and Dust Aerosol Over North America

NASA Astrophysics Data System (ADS)

Shinozuka, Y.; Clarke, A.; Howell, S.; Kapustin, V.; McNaughton, C.; Zhou, J.; Decarlo, P.; Jimenez, J.; Roberts, G.; Tomlinson, J.; Collins, D.

2008-12-01

Remote sensing of the concentration of cloud condensation nuclei (CCN) would help investigate the indirect effect of tropospheric aerosols on clouds and climate. In order to assess its feasibility, this paper evaluates the spectral-based retrieval technique for aerosol number and seeks one for aerosol solubility, using in-situ aircraft measurements of aerosol size distribution, chemical composition, hygroscopicity, CCN activity and optical properties. Our statistical analysis reveals that the CCN concentration over Mexico can be optically determined to a relative error of <20%, smaller than that for the mainland US and the surrounding oceans (~a factor of 2). Mexico's advantage is four-fold. Firstly, many particles originating from the lightly regulated industrial combustion and biomass burning are large enough to significantly affect light extinction, elevating the correlation between extinction and CCN number in absence of substantial dust. Secondly, the generally low ambient humidity near the major aerosol sources limits the error in the estimated response of particle extinction to humidity changes. Thirdly, because many CCN contain black carbon, light absorption also provides a measure of the CCN concentration. Fourthly, the organic fraction of volatile mass of submicron particles (OMF) is anti-correlated with the wavelength dependence of extinction due to preferential anion uptake by coarse dust, which provides a potential tool for remote-sensing OMF and the particle solubility.

Examining the Impact of Overlying Aerosols on the Retrieval of Cloud Optical Properties from Passive Remote Sensing

NASA Technical Reports Server (NTRS)

Coddington, O. M.; Pilewskie, P.; Redemann, J.; Platnick, S.; Russell, P. B.; Schmidt, K. S.; Gore, W. J.; Livingston, J.; Wind, G.; Vukicevic, T.

2010-01-01

Haywood et al. (2004) show that an aerosol layer above a cloud can cause a bias in the retrieved cloud optical thickness and effective radius. Monitoring for this potential bias is difficult because space ]based passive remote sensing cannot unambiguously detect or characterize aerosol above cloud. We show that cloud retrievals from aircraft measurements above cloud and below an overlying aerosol layer are a means to test this bias. The data were collected during the Intercontinental Chemical Transport Experiment (INTEX-A) study based out of Portsmouth, New Hampshire, United States, above extensive, marine stratus cloud banks affected by industrial outflow. Solar Spectral Flux Radiometer (SSFR) irradiance measurements taken along a lower level flight leg above cloud and below aerosol were unaffected by the overlying aerosol. Along upper level flight legs, the irradiance reflected from cloud top was transmitted through an aerosol layer. We compare SSFR cloud retrievals from below ]aerosol legs to satellite retrievals from the Moderate Resolution Imaging Spectroradiometer (MODIS) in order to detect an aerosol ]induced bias. In regions of small variation in cloud properties, we find that SSFR and MODIS-retrieved cloud optical thickness compares within the uncertainty range for each instrument while SSFR effective radius tend to be smaller than MODIS values (by 1-2 microns) and at the low end of MODIS uncertainty estimates. In regions of large variation in cloud properties, differences in SSFR and MODIS ]retrieved cloud optical thickness and effective radius can reach values of 10 and 10 microns, respectively. We include aerosols in forward modeling to test the sensitivity of SSFR cloud retrievals to overlying aerosol layers. We find an overlying absorbing aerosol layer biases SSFR cloud retrievals to smaller effective radii and optical thickness while nonabsorbing aerosols had no impact.

Farm Management Support on Cloud Computing Platform: A System for Cropland Monitoring Using Multi-Source Remotely Sensed Data

NASA Astrophysics Data System (ADS)

Coburn, C. A.; Qin, Y.; Zhang, J.; Staenz, K.

2015-12-01

Food security is one of the most pressing issues facing humankind. Recent estimates predict that over one billion people don't have enough food to meet their basic nutritional needs. The ability of remote sensing tools to monitor and model crop production and predict crop yield is essential for providing governments and farmers with vital information to ensure food security. Google Earth Engine (GEE) is a cloud computing platform, which integrates storage and processing algorithms for massive remotely sensed imagery and vector data sets. By providing the capabilities of storing and analyzing the data sets, it provides an ideal platform for the development of advanced analytic tools for extracting key variables used in regional and national food security systems. With the high performance computing and storing capabilities of GEE, a cloud-computing based system for near real-time crop land monitoring was developed using multi-source remotely sensed data over large areas. The system is able to process and visualize the MODIS time series NDVI profile in conjunction with Landsat 8 image segmentation for crop monitoring. With multi-temporal Landsat 8 imagery, the crop fields are extracted using the image segmentation algorithm developed by Baatz et al.[1]. The MODIS time series NDVI data are modeled by TIMESAT [2], a software package developed for analyzing time series of satellite data. The seasonality of MODIS time series data, for example, the start date of the growing season, length of growing season, and NDVI peak at a field-level are obtained for evaluating the crop-growth conditions. The system fuses MODIS time series NDVI data and Landsat 8 imagery to provide information of near real-time crop-growth conditions through the visualization of MODIS NDVI time series and comparison of multi-year NDVI profiles. Stakeholders, i.e., farmers and government officers, are able to obtain crop-growth information at crop-field level online. This unique utilization of GEE in combination with advanced analytic and extraction techniques provides a vital remote sensing tool for decision makers and scientists with a high-degree of flexibility to adapt to different uses.

Remote Sensing of Cloud, Aerosol, and Water Vapor Properties from MODIS

NASA Technical Reports Server (NTRS)

King, Michael D.

2001-01-01

MODIS is an earth-viewing cross-track scanning spectroradiometer launched on the Terra satellite in December 1999. MODIS scans a swath width sufficient to provide nearly complete global coverage every two days from a polar-orbiting, sun-synchronous, platform at an altitude of 705 km, and provides images in 36 spectral bands from 0.415 to 14.235 microns with spatial resolutions of 250 m (2 bands), 500 m (5 bands) and 1000 m (29 bands). These bands have been carefully selected to enable advanced studies of land, ocean, and atmospheric processes. In this presentation I will review the comprehensive set of remote sensing algorithms that have been developed for the remote sensing of atmospheric properties using MODIS data, placing primary emphasis on the principal atmospheric applications of: (1) developing a cloud mask for distinguishing clear sky from clouds, (2) retrieving global cloud radiative and microphysical properties, including cloud top pressure and temperature, effective emissivity, cloud optical thickness, thermodynamic phase, and effective radius, (3) monitoring tropospheric aerosol optical thickness over the land and ocean and aerosol size distribution over the ocean, (4) determining atmospheric profiles of moisture and temperature, and (5) estimating column water amount. The physical principles behind the determination of each of these atmospheric products will be described, together with an example of their application using MODIS observations. All products are archived into two categories: pixel-level retrievals (referred to as Level-2 products) and global gridded products at a latitude and longitude resolution of 1 deg (Level-3 products). An overview of the MODIS atmosphere algorithms and products, status, validation activities, and early level-2 and -3 results will be presented. Finally, I will present some highlights from the land and ocean algorithms developed for processing global MODIS observations, including: (1) surface reflectance, (2) vegetation indices, leaf area index, and FPAR, (3) albedo and nadir BRDF-adjusted reflectance, (4) normalized water-leaving radiance, (5) chlorophyll-a concentration, and (6) sea surface temperature.

Sensitivity of MODIS 2.1-(micrometers) Channel for Off-Nadir View Angles for Use in Remote Sensing of Aerosol

NASA Technical Reports Server (NTRS)

Gatebe, C. K.; King, M. D.; Tsay, S.-C.; Ji, Q.; Arnold, T.

2000-01-01

In this sensitivity study, we examined the ratio technique, the official method for remote sensing of aerosols over land from Moderate Resolution Imaging Spectroradiometer (MODIS) DATA, for view angles from nadir to 65 deg. off-nadir using Cloud Absorption Radiometer (CAR) data collected during the Smoke, Clouds, and Radiation-Brazil (SCAR-B) experiment conducted in 1995. For the data analyzed and for the view angles tested, results seem to suggest that the reflectance (rho)0.47 and (rho)0.67 are predictable from (rho)2.1 using: (rho)0.47 = (rho)2.1/6, which is a slight modification and (rho)0.67 = (rho)2.1/2. These results hold for target viewed from backscattered direction, but not for the forward direction.

Utilizing multisource remotely sensed data to dynamically monitor drought in China

NASA Astrophysics Data System (ADS)

Liu, Sanchao; Li, Wenbo

2011-12-01

Drought is one of major nature disaster in the world and China. China has a vast territory and very different spatio-temporal distribution weather condition. Therefore, drought disasters occur frequently throughout China, which may affect large areas and cause great economic loss every year. In this paper, geostationary meteorological remote sensing data, FY-2C/D/E VISSR and three quantitative remotely sensed models including Cloud Parameters Method (CPM), Vegetation Supply Water Index (VSWI), and Temperature Vegetation Dryness Index (TVDI) have been used to dynamically monitor severe drought in southwest China from 2009 to 2010. The results have effectively revealed the occurrence, development and disappearance of this drought event. The monitoring results can be used for the relevant disaster management departments' decision-making works.

Proceedings of a Workshop on Polar Stratospheric Clouds: Their Role in Atmospheric Processes

NASA Technical Reports Server (NTRS)

Hamill, P. (Editor); Mcmaster, L. R. (Editor)

1984-01-01

The potential role of polar stratospheric clouds in atmospheric processes was assessed. The observations of polar stratospheric clouds with the Nimbus 7 SAM II satellite experiment were reviewed and a preliminary analysis of their formation, impact on other remote sensing experiments, and potential impact on climate were presented. The potential effect of polar stratospheric clouds on climate, radiation balance, atmospheric dynamics, stratospheric chemistry and water vapor budget, and cloud microphysics was assessed. Conclusions and recommendations, a synopsis of materials and complementary material to support those conclusions and recommendations are presented.

Remote sensing for detection of termite infestations—Proof of Concept

Treesearch

Frederick Green III; Rachel A. Arango; Charles R. Boardman; Keith J. Bourne; John C. Hermanson; Robert A. Munson

2015-01-01

This paper reports the results of a search to discover the most cost effective and robust method of detecting Reticulitermes flavipes infestations in structural members of remote bridges, homes and other wooden structures and transmitting these results to internet cloud storage thus obviating routine travel to these structures for periodic visual...

Vertical Photon Transport in Cloud Remote Sensing Problems

NASA Technical Reports Server (NTRS)

Platnick, S.

1999-01-01

Photon transport in plane-parallel, vertically inhomogeneous clouds is investigated and applied to cloud remote sensing techniques that use solar reflectance or transmittance measurements for retrieving droplet effective radius. Transport is couched in terms of weighting functions which approximate the relative contribution of individual layers to the overall retrieval. Two vertical weightings are investigated, including one based on the average number of scatterings encountered by reflected and transmitted photons in any given layer. A simpler vertical weighting based on the maximum penetration of reflected photons proves useful for solar reflectance measurements. These weighting functions are highly dependent on droplet absorption and solar/viewing geometry. A superposition technique, using adding/doubling radiative transfer procedures, is derived to accurately determine both weightings, avoiding time consuming Monte Carlo methods. Superposition calculations are made for a variety of geometries and cloud models, and selected results are compared with Monte Carlo calculations. Effective radius retrievals from modeled vertically inhomogeneous liquid water clouds are then made using the standard near-infrared bands, and compared with size estimates based on the proposed weighting functions. Agreement between the two methods is generally within several tenths of a micrometer, much better than expected retrieval accuracy. Though the emphasis is on photon transport in clouds, the derived weightings can be applied to any multiple scattering plane-parallel radiative transfer problem, including arbitrary combinations of cloud, aerosol, and gas layers.

Interactions between biomass-burning aerosols and clouds over Southeast Asia: current status, challenges, and perspectives.

PubMed

Lin, Neng-Huei; Sayer, Andrew M; Wang, Sheng-Hsiang; Loftus, Adrian M; Hsiao, Ta-Chih; Sheu, Guey-Rong; Hsu, N Christina; Tsay, Si-Chee; Chantara, Somporn

2014-12-01

The interactions between aerosols, clouds, and precipitation remain among the largest sources of uncertainty in the Earth's energy budget. Biomass-burning aerosols are a key feature of the global aerosol system, with significant annually-repeating fires in several parts of the world, including Southeast Asia (SEA). SEA in particular provides a "natural laboratory" for these studies, as smoke travels from source regions downwind in which it is coupled to persistent stratocumulus decks. However, SEA has been under-exploited for these studies. This review summarizes previous related field campaigns in SEA, with a focus on the ongoing Seven South East Asian Studies (7-SEAS) and results from the most recent BASELInE deployment. Progress from remote sensing and modeling studies, along with the challenges faced for these studies, are also discussed. We suggest that improvements to our knowledge of these aerosol/cloud effects require the synergistic use of field measurements with remote sensing and modeling tools. Copyright © 2014 Elsevier Ltd. All rights reserved.

Light Scattering by Gaussian Particles: A Solution with Finite-Difference Time Domain Technique

NASA Technical Reports Server (NTRS)

Sun, W.; Nousiainen, T.; Fu, Q.; Loeb, N. G.; Videen, G.; Muinonen, K.

2003-01-01

The understanding of single-scattering properties of complex ice crystals has significance in atmospheric radiative transfer and remote-sensing applications. In this work, light scattering by irregularly shaped Gaussian ice crystals is studied with the finite-difference time-domain (FDTD) technique. For given sample particle shapes and size parameters in the resonance region, the scattering phase matrices and asymmetry factors are calculated. It is found that the deformation of the particle surface can significantly smooth the scattering phase functions and slightly reduce the asymmetry factors. The polarization properties of irregular ice crystals are also significantly different from those of spherical cloud particles. These FDTD results could provide a reference for approximate light-scattering models developed for irregular particle shapes and can have potential applications in developing a much simpler practical light scattering model for ice clouds angular-distribution models and for remote sensing of ice clouds and aerosols using polarized light. (copyright) 2003 Elsevier Science Ltd. All rights reserved.

Combined Infrared Stereo and Laser Ranging Cloud Measurements from Shuttle Mission STS-85

NASA Technical Reports Server (NTRS)

Lancaster, Redgie S.; Spinhirne, James D.; OCStarr, David (Technical Monitor)

2001-01-01

Multi-angle remote sensing provides a wealth of information for earth and climate monitoring. And, as technology advances so do the options for developing instrumentation versatile enough to meet the demands associated with these types of measurements. In the current work, the multiangle measurement capability of the Infrared Spectral Imaging Radiometer is demonstrated. This instrument flew as part of mission STS-85 of the space shuttle Columbia in 1997 and was the first earth-observing radiometer to incorporate an uncooled microbolometer array detector as its image sensor. Specifically, a method for computing cloud-top height from the multi-spectral stereo measurements acquired during this flight has been developed and the results demonstrate that a vertical precision of 10.6 km was achieved. Further, the accuracy of these measurements is confirmed by comparison with coincident direct laser ranging measurements from the Shuttle Laser Altimeter. Mission STS-85 was the first space flight to combine laser ranging and thermal IR camera systems for cloud remote sensing.

Quantifying the impact of anthropogenic pollution on cloud properties derived from ground based remote sensors at the North Slope of Alaska

NASA Astrophysics Data System (ADS)

Maahn, M.; Acquistapace, C.; de Boer, G.; Cox, C.; Feingold, G.; Marke, T.; Williams, C. R.

2017-12-01

When acting as cloud condensation nuclei (CCN) or ice nucleating particles (INPs), aerosols have a strong potential to influence cloud properties. In particular, they can impact the number, size, and phase of cloud particles and potentially cloud lifetime through aerosol indirect and semi-direct effects. In polar regions, these effects are of great importance for the radiation budget due to the shortwave albedo and longwave emissivity of mixed-phase clouds. The Department of Energy (DOE) Atmospheric Radiation Measurement (ARM) program operates two super sites equipped with state of the art ground-based remote sensing instruments in northern Alaska. The sites are both coastal and are highly correlated with respect to large scale synoptic patterns. While the site at Utqiaġvik (formerly known as Barrow) generally represents a relatively pristine Arctic environment lacking significant anthropogenic sources, the site at Oliktok Point, approximately 250 km to the east, is surrounded by the Prudhoe Bay Oil Field, which is the largest oil field in North America. Based on aircraft measurement, the authors recently showed that differences in the properties of liquid clouds properties between the sites can be attributed to local emissions associated with the industrial activities in the Prudhoe Bay region (Maahn et al. 2017, ACPD). However, aircraft measurements do not provide a representative sample of cloud properties due to temporal limitations in the amount of data. In order to investigate how frequently and to what extent liquid cloud properties and processes are modified, we use ground based remote sensing observations such as e.g., cloud radar, Doppler lidar, and microwave radiometer obtained continuously at the two sites. In this way, we are able to quantify inter-site differences with respect to cloud drizzle production, liquid water path, frequency of cloud occurrence, and cloud radiative properties. Turbulence and the coupling of clouds to the boundary layer is investigated in order to infer the potential role of locally emitted aerosols in modulating the observed differences.

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

NASA Technical Reports Server (NTRS)

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

2010-01-01

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

Polar clouds and radiation in satellite observations, reanalyses, and climate models

NASA Astrophysics Data System (ADS)

Lenaerts, Jan T. M.; Van Tricht, Kristof; Lhermitte, Stef; L'Ecuyer, Tristan S.

2017-04-01

Clouds play a pivotal role in the surface energy budget of the polar regions. Here we use two largely independent data sets of cloud and surface downwelling radiation observations derived by satellite remote sensing (2007-2010) to evaluate simulated clouds and radiation over both polar ice sheets and oceans in state-of-the-art atmospheric reanalyses (ERA-Interim and Modern Era Retrospective-Analysis for Research and Applications-2) and the Coupled Model Intercomparison Project Phase 5 (CMIP5) climate model ensemble. First, we show that, compared to Clouds and the Earth's Radiant Energy System-Energy Balanced and Filled, CloudSat-CALIPSO better represents cloud liquid and ice water path over high latitudes, owing to its recent explicit determination of cloud phase that will be part of its new R05 release. The reanalyses and climate models disagree widely on the amount of cloud liquid and ice in the polar regions. Compared to the observations, we find significant but inconsistent biases in the model simulations of cloud liquid and ice water, as well as in the downwelling radiation components. The CMIP5 models display a wide range of cloud characteristics of the polar regions, especially with regard to cloud liquid water, limiting the representativeness of the multimodel mean. A few CMIP5 models (CNRM, GISS, GFDL, and IPSL_CM5b) clearly outperform the others, which enhances credibility in their projected future cloud and radiation changes over high latitudes. Given the rapid changes in polar regions and global feedbacks involved, future climate model developments should target improved representation of polar clouds. To that end, remote sensing observations are crucial, in spite of large remaining observational uncertainties, which is evidenced by the substantial differences between the two data sets.

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.

Remote sensing, hydrological modeling and in situ observations in snow cover research: A review

NASA Astrophysics Data System (ADS)

Dong, Chunyu

2018-06-01

Snow is an important component of the hydrological cycle. As a major part of the cryosphere, snow cover also represents a valuable terrestrial water resource. In the context of climate change, the dynamics of snow cover play a crucial role in rebalancing the global energy and water budgets. Remote sensing, hydrological modeling and in situ observations are three techniques frequently utilized for snow cover investigations. However, the uncertainties caused by systematic errors, scale gaps, and complicated snow physics, among other factors, limit the usability of these three approaches in snow studies. In this paper, an overview of the advantages, limitations and recent progress of the three methods is presented, and more effective ways to estimate snow cover properties are evaluated. The possibility of improving remotely sensed snow information using ground-based observations is discussed. As a rapidly growing source of volunteered geographic information (VGI), web-based geotagged photos have great potential to provide ground truth data for remotely sensed products and hydrological models and thus contribute to procedures for cloud removal, correction, validation, forcing and assimilation. Finally, this review proposes a synergistic framework for the future of snow cover research. This framework highlights the cross-scale integration of in situ and remotely sensed snow measurements and the assimilation of improved remote sensing data into hydrological models.

Cloud detection method for Chinese moderate high resolution satellite imagery (Conference Presentation)

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%.

Remote Sensing of Supercooled Cloud Layers in Cold Climate Using Ground Based Integrated Sensors System and Comparison with Pilot Reports and model forecasts

NASA Astrophysics Data System (ADS)

Boudala, Faisal; Wu, Di; Gultepe, Ismail; Anderson, Martha; turcotte, marie-france

2017-04-01

In-flight aircraft icing is one of the major weather hazards to aviation . It occurs when an aircraft passes through a cloud layer containing supercooled drops (SD). The SD in contact with the airframe freezes on the surface which degrades the performance of the aircraft.. Prediction of in-flight icing requires accurate prediction of SD sizes, liquid water content (LWC), and temperature. The current numerical weather predicting (NWP) models are not capable of making accurate prediction of SD sizes and associated LWC. Aircraft icing environment is normally studied by flying research aircraft, which is quite expensive. Thus, developing a ground based remote sensing system for detection of supercooled liquid clouds and characterization of their impact on severity of aircraft icing one of the important tasks for improving the NWPs based predictions and validations. In this respect, Environment and Climate Change Canada (ECCC) in cooperation with the Department of National Defense (DND) installed a number of specialized ground based remote sensing platforms and present weather sensors at Cold Lake, Alberta that includes a multi-channel microwave radiometer (MWR), K-band Micro Rain radar (MRR), Ceilometer, Parsivel distrometer and Vaisala PWD22 present weather sensor. In this study, a number of pilot reports confirming icing events and freezing precipitation that occurred at Cold Lake during the 2014-2016 winter periods and associated observation data for the same period are examined. The icing events are also examined using aircraft icing intensity estimated using ice accumulation model which is based on a cylindrical shape approximation of airfoil and the Canadian High Resolution Regional Deterministic Prediction System (HRDPS) model predicted LWC, median volume diameter and temperature. The results related to vertical atmospheric profiling conditions, surface observations, and the Canadian High Resolution Regional Deterministic Prediction System (HRDPS) model predictions are given. Preliminary results suggest that remote sensing and present weather sensors based observations of cloud SD regions can be used to describe micro and macro physical characteristics of the icing conditions. The model based icing intensity prediction reasonably agreed with the PIREPs and MWR observations.

Atmospheric particles retrieval using satellite remote sensing: Applications for sandstorms and volcanic clouds

NASA Astrophysics Data System (ADS)

Gu, Yingxin

This thesis is concerned with atmospheric particles produced by sandstorms and volcanic eruptions. Three studies were conducted in order to examine particle retrieval methodology, and apply these towards an improved understanding of large-scale sandstorms. A thermal infrared remote sensing retrieval method developed by Wen and Rose [1994], which retrieves particle sizes, optical depth, and total masses of silicate particles in the volcanic cloud, was applied to an April 07, 2001 sandstorm over northern China, using MODIS. Results indicate that the area of the dust cloud observed was 1.34 million km2, the mean particle radius of the dust was 1.44 mum, and the mean optical depth at 11 mum was 0.79. The mean burden of dust was approximately 4.8 tons/km2 and the main portion of the dust storm on April 07, 2001 contained 6.5 million tons of dust. The results are supported by both independent remote sensing data (TOMS) and in-situ data for a similar event in 1998, therefore suggesting that the technique is appropriate for quantitative analysis of silicate dust clouds. This is the first quantitative evaluation of annual and seasonal dust loading in 2003 produced by Saharan dust storms by satellite remote sensing analysis. The retrieved mean particle effective radii of 2003 dust events are between 1.7--2.6 mum which is small enough to be inhaled and is hazardous to human health. The retrieved yearly dust mass load is 658--690 Tg, which is ˜45% of the annual global mineral dust production. Winter is the heaviest dust loading season in the year 2003, which is more than 5 times larger than that in the summer season in 2003.The mean optical depths at 11 mum in the winter season (around 0.7) are higher than those in the summer season (around 0.5). The results could help both meteorologists and environmental scientists to evaluate and predict the hazard degree caused by Saharan dust storms. (Abstract shortened by UMI.)

Investigating the differences of cirrus cloud properties in nucleation, growth and sublimation regions based on airborne water vapor lidar measurements

NASA Astrophysics Data System (ADS)

Urbanek, Benedikt; Groß, Silke; Wirth, Martin

2017-04-01

Cirrus clouds impose high uncertainties on weather and climate prediction, as knowledge on important processes is still incomplete. For instance it remains unclear how cloud optical, microphysical, and radiative properties change as the cirrus evolves. To gain better understanding of cirrus clouds, their optical and microphysical properties and their changes with cirrus cloud evolution the ML-CIRRUS campaign was conducted in March and April 2014. Measurements with a combined in-situ and remote sensing payload were performed with the German research aircraft HALO based in Oberpfaffenhofen. 16 research flights with altogether 88 flight hours were performed over the North-Atlantic, western and central Europe to probe different cirrus cloud regimes and cirrus clouds at different stages of evolution. One of the key remotes sensing instruments during ML-CIRRUS was the airborne differential absorption and high spectral lidar system WALES. It measures the 2-dimensional distribution of water vapor inside and outside of cirrus clouds as well as the optical properties of the clouds. Bases on these airborne lidar measurements a novel classification scheme to derive the stage of cirrus cloud evolution was developed. It identifies regions of ice nucleation, particle growth by deposition of water vapor, and ice sublimation. This method is used to investigate differences in the distribution and value of optical properties as well as in the distribution of water vapor and relative humidity depending on the stage of evolution of the cloud. We will present the lidar based classification scheme and its application on a wave driven cirrus cloud case, and we will show first results of the dependence of optical cloud properties and relative humidity distributions on the determined stage of evolution.

Studies on remote sensing method of particle size and water density distribution in mists and clouds using laser radar techniques

NASA Technical Reports Server (NTRS)

Shimizu, H.; Kobayasi, T.; Inaba, H.

1979-01-01

A method of remote measurement of the particle size and density distribution of water droplets was developed. In this method, the size of droplets is measured from the Mie scattering parameter which is defined as the total-to-backscattering ratio of the laser beam. The water density distribution is obtained by a combination of the Mie scattering parameter and the extinction coefficient of the laser beam. This method was examined experimentally for the mist generated by an ultrasonic mist generator and applied to clouds containing rain and snow. Compared with the conventional sampling method, the present method has advantages of remote measurement capability and improvement in accuracy.

An improvement of the retrieval of temperature and relative humidity profiles from a combination of active and passive remote sensing

NASA Astrophysics Data System (ADS)

Che, Yunfei; Ma, Shuqing; Xing, Fenghua; Li, Siteng; Dai, Yaru

2018-03-01

This paper focuses on an improvement of the retrieval of atmospheric temperature and relative humidity profiles through combining active and passive remote sensing. Ground-based microwave radiometer and millimeter-wavelength cloud radar were used to acquire the observations. Cloud base height and cloud thickness determinations from cloud radar were added into the atmospheric profile retrieval process, and a back-propagation neural network method was used as the retrieval tool. Because a substantial amount of data are required to train a neural network, and as microwave radiometer data are insufficient for this purpose, 8 years of radiosonde data from Beijing were used as the database. The monochromatic radiative transfer model was used to calculate the brightness temperatures in the same channels as the microwave radiometer. Parts of the cloud base heights and cloud thicknesses in the training data set were also estimated using the radiosonde data. The accuracy of the results was analyzed through a comparison with L-band sounding radar data and quantified using the mean bias, root-mean-square error (RMSE), and correlation coefficient. The statistical results showed that an inversion with cloud information was the optimal method. Compared with the inversion profiles without cloud information, the RMSE values after adding cloud information reduced to varying degrees for the vast majority of height layers. These reductions were particularly clear in layers with clouds. The maximum reduction in the RMSE for the temperature profile was 2.2 K, while that for the humidity profile was 16%.

Understanding Effective Diameter and Its Application to Terrestrial Radiation in Ice Clouds

NASA Technical Reports Server (NTRS)

Mitchell, D. L.; Lawson, R. P.; Baker, B.

2011-01-01

The cloud property known as "effective diameter" or "effective radius", which in essence is the cloud particle size distribution (PSD) volume at bulk density divided by its projected area, is used extensively in atmospheric radiation transfer, climate modeling and remote sensing. This derives from the assumption that PSD optical properties can be uniquely described in terms of their effective diameter, D(sub e), and their cloud water content (CWC), henceforth referred to as the D(sub e)-CWC assumption. This study challenges this assumption, showing that while the D(sub e)-CWC assumption appears generally valid for liquid water clouds, it appears less valid for ice clouds in regions where (1) absorption is not primarily a function of either the PSD ice water content (IWC) or the PSD projected area, and (2) where wave resonance (i.e. photon tunneling) contributes significantly to absorption. These two regions often strongly coincide at terrestrial wavelengths when De less than 60 m, which is where this D(sub e)-CWC assumption appears poorest. Treating optical properties solely in terms of D(sub e) and IWC may lead to errors up to 24%, 26% and 20% for terrestrial radiation in the window region regarding the absorption and extinction coefficients and the single scattering albedo, respectively. Outside the window region, errors may reach 33% and 42% regarding absorption and extinction. The magnitude and sign of these errors can change rapidly with wavelength, which may produce significant errors in climate modeling, remote sensing and other applications concerned with the wavelength dependence of radiation. Where the D(sub e)-CWC assumption breaks down, ice cloud optical properties appear to depend on D(sub e), IWC and the PSD shape. Optical property parameterizations in climate models and remote sensing algorithms based on historical PSD measurements may exhibit errors due to previously unknown PSD errors (i.e. the presence of ice artifacts due to the shattering of larger ice particles on the probe inlet tube during sampling). More recently developed cloud probes are designed to mitigate this shattering problem. Using realistic PSD shapes for a given temperature (and/or IWC) and cloud type may minimize errors associated with PSD shape in ice optics parameterizations and remote sensing algorithms. While this topic was investigated using two ice optics schemes (the Yang et al., 2005 database and the modified anomalous diffraction approximation, or MADA), a physical understanding of the limitations of the D(sub e)-IWC assumption was made possible by using MADA. MADA allows one to approximate the contribution of photon tunneling to absorption relative to other optical processes, which reveals that part of the error regarding the D(sub e)-IWC assumption can be associated with tunneling. By relating the remaining error to the radiation penetration depth in bulk ice (DELTA L) due to absorption, the domain where the D(sub e)-IWC assumption is weakest was described in terms of D(sub e) and DELTA L.

Understanding effective diameter and its application to terrestrial radiation in ice clouds

NASA Astrophysics Data System (ADS)

Mitchell, D. L.; Lawson, R. P.; Baker, B.

2010-12-01

The cloud property known as "effective diameter" or "effective radius", which in essence is the cloud particle size distribution (PSD) volume at bulk density divided by its projected area, is used extensively in atmospheric radiation transfer, climate modeling and remote sensing. This derives from the assumption that PSD optical properties can be uniquely described in terms of their effective diameter, De, and their cloud water content (CWC), henceforth referred to as the De-CWC assumption. This study challenges this assumption, showing that while the De-CWC assumption appears generally valid for liquid water clouds, it appears less valid for ice clouds in regions where (1) absorption is not primarily a function of either the PSD ice water content (IWC) or the PSD projected area, and (2) where wave resonance (i.e. photon tunneling) contributes significantly to absorption. These two regions often strongly coincide at terrestrial wavelengths when De<∼60 μm, which is where this De-CWC assumption appears poorest. Treating optical properties solely in terms of De and IWC may lead to errors up to 24%, 26% and 20% for terrestrial radiation in the window region regarding the absorption and extinction coefficients and the single scattering albedo, respectively. Outside the window region, errors may reach 33% and 42% regarding absorption and extinction. The magnitude and sign of these errors can change rapidly with wavelength, which may produce significant errors in climate modeling, remote sensing and other applications concerned with the wavelength dependence of radiation. Where the De-CWC assumption breaks down, ice cloud optical properties appear to depend on De, IWC and the PSD shape. Optical property parameterizations in climate models and remote sensing algorithms based on historical PSD measurements may exhibit errors due to previously unknown PSD errors (i.e. the presence of ice artifacts due to the shattering of larger ice particles on the probe inlet tube during sampling). More recently developed cloud probes are designed to mitigate this shattering problem. Using realistic PSD shapes for a given temperature (and/or IWC) and cloud type may minimize errors associated with PSD shape in ice optics parameterizations and remote sensing algorithms. While this topic was investigated using two ice optics schemes (the Yang et al. (2005) database and the modified anomalous diffraction approximation, or MADA), a physical understanding of the limitations of the De-IWC assumption was made possible by using MADA. MADA allows one to separate the photon tunneling process from the other optical processes, which reveals that much of the error regarding the De-IWC assumption can be associated with tunneling. By relating the remaining error to the radiation penetration depth in bulk ice (ΔL) due to absorption, the domain where the De-IWC assumption is weakest was described in terms of De and ΔL.

Visualizing Airborne and Satellite Imagery

NASA Technical Reports Server (NTRS)

Bierwirth, Victoria A.

2011-01-01

Remote sensing is a process able to provide information about Earth to better understand Earth's processes and assist in monitoring Earth's resources. The Cloud Absorption Radiometer (CAR) is one remote sensing instrument dedicated to the cause of collecting data on anthropogenic influences on Earth as well as assisting scientists in understanding land-surface and atmospheric interactions. Landsat is a satellite program dedicated to collecting repetitive coverage of the continental Earth surfaces in seven regions of the electromagnetic spectrum. Combining these two aircraft and satellite remote sensing instruments will provide a detailed and comprehensive data collection able to provide influential information and improve predictions of changes in the future. This project acquired, interpreted, and created composite images from satellite data acquired from Landsat 4-5 Thematic Mapper (TM) and Landsat 7 Enhanced Thematic Mapper plus (ETM+). Landsat images were processed for areas covered by CAR during the Arctic Research of the Composition of the Troposphere from Aircraft and Satellites (ARCT AS), Cloud and Land Surface Interaction Campaign (CLASIC), Intercontinental Chemical Transport Experiment-Phase B (INTEXB), and Southern African Regional Science Initiative (SAFARI) 2000 missions. The acquisition of Landsat data will provide supplemental information to assist in visualizing and interpreting airborne and satellite imagery.

Impacts of Subgrid Heterogeneous Mixing between Cloud Liquid and Ice on the Wegner-Bergeron-Findeisen Process and Mixed-phase Clouds in NCAR CAM5

NASA Astrophysics Data System (ADS)

Liu, X.; Zhang, M.; Zhang, D.; Wang, Z.; Wang, Y.

2017-12-01

Mixed-phase clouds are persistently observed over the Arctic and the phase partitioning between cloud liquid and ice hydrometeors in mixed-phase clouds has important impacts on the surface energy budget and Arctic climate. In this study, we test the NCAR Community Atmosphere Model Version 5 (CAM5) with the single-column and weather forecast configurations and evaluate the model performance against observation data from the DOE Atmospheric Radiation Measurement (ARM) Program's M-PACE field campaign in October 2004 and long-term ground-based multi-sensor remote sensing measurements. Like most global climate models, we find that CAM5 also poorly simulates the phase partitioning in mixed-phase clouds by significantly underestimating the cloud liquid water content. Assuming pocket structures in the distribution of cloud liquid and ice in mixed-phase clouds as suggested by in situ observations provides a plausible solution to improve the model performance by reducing the Wegner-Bergeron-Findeisen (WBF) process rate. In this study, the modification of the WBF process in the CAM5 model has been achieved with applying a stochastic perturbation to the time scale of the WBF process relevant to both ice and snow to account for the heterogeneous mixture of cloud liquid and ice. Our results show that this modification of WBF process improves the modeled phase partitioning in the mixed-phase clouds. The seasonal variation of mixed-phase cloud properties is also better reproduced in the model in comparison with the long-term ground-based remote sensing observations. Furthermore, the phase partitioning is insensitive to the reassignment time step of perturbations.

Cloud Properties under Different Synoptic Circulations: Comparison of Radiosonde and Ground-Based Active Remote Sensing Measurements

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

Zhang, Jinqiang; Li, Jun; Xia, Xiangao

In this study, long-term (10 years) radiosonde-based cloud data are compared with the ground-based active remote sensing product under six prevailing large-scale synoptic patterns, i.e., cyclonic center (CC), weak pressure pattern (WP), the southeast bottom of cyclonic center (CB), cold front (CF), anticyclone edge (AE) and anticyclone center (AC) over the Southern Great Plains (SGP) site. The synoptic patterns are generated by applying the self-organizing map weather classification method to the daily National Centers for Environmental Protection mean sea level pressure records from the North American Regional Reanalysis. It reveals that the large-scale synoptic circulations can strongly influence the regionalmore » cloud formation, and thereby have impact on the consistency of cloud retrievals from the radiosonde and ground-based cloud product. The total cloud cover at the SGP site is characterized by the least in AC and the most in CF. The minimum and maximum differences between the two cloud methods are 10.3% for CC and 13.3% for WP. Compared to the synoptic patterns characterized by scattered cloudy and clear skies (AE and AC), the agreement of collocated cloud boundaries between the two cloud approaches tends to be better under the synoptic patterns dominated by overcast and cloudy skies (CC, WP and CB). The rainy and windy weather conditions in CF synoptic pattern influence the consistency of the two cloud retrieval methods associated with the limited capabilities inherent to the instruments. As a result, the cloud thickness distribution from the two cloud datasets compares favorably with each other in all synoptic patterns, with relative discrepancy of ≤0.3 km.« less

Cloud Properties under Different Synoptic Circulations: Comparison of Radiosonde and Ground-Based Active Remote Sensing Measurements

DOE PAGES

Zhang, Jinqiang; Li, Jun; Xia, Xiangao; ...

2016-11-28

In this study, long-term (10 years) radiosonde-based cloud data are compared with the ground-based active remote sensing product under six prevailing large-scale synoptic patterns, i.e., cyclonic center (CC), weak pressure pattern (WP), the southeast bottom of cyclonic center (CB), cold front (CF), anticyclone edge (AE) and anticyclone center (AC) over the Southern Great Plains (SGP) site. The synoptic patterns are generated by applying the self-organizing map weather classification method to the daily National Centers for Environmental Protection mean sea level pressure records from the North American Regional Reanalysis. It reveals that the large-scale synoptic circulations can strongly influence the regionalmore » cloud formation, and thereby have impact on the consistency of cloud retrievals from the radiosonde and ground-based cloud product. The total cloud cover at the SGP site is characterized by the least in AC and the most in CF. The minimum and maximum differences between the two cloud methods are 10.3% for CC and 13.3% for WP. Compared to the synoptic patterns characterized by scattered cloudy and clear skies (AE and AC), the agreement of collocated cloud boundaries between the two cloud approaches tends to be better under the synoptic patterns dominated by overcast and cloudy skies (CC, WP and CB). The rainy and windy weather conditions in CF synoptic pattern influence the consistency of the two cloud retrieval methods associated with the limited capabilities inherent to the instruments. As a result, the cloud thickness distribution from the two cloud datasets compares favorably with each other in all synoptic patterns, with relative discrepancy of ≤0.3 km.« less

Scattering by Atmospheric Particles: From Aerosols to Clouds with the Point-Spread Function ... using Water, Milk, Plastic Cups, and a Laser Pointer

NASA Astrophysics Data System (ADS)

Davis, A. B.

2015-12-01

Planetary atmospheres are made primarily of molecules, and their optical properties are well known. They scatter sunlight across the spectrum, but far more potently at shorter wavelengths. Consequently, they redden the Sun as it sets and, at the same time, endow the daytime sky with its characteristic blue hue. There are also microscopic atmospheric particulates that are equally omnipresent because small enough (up to ~10s of microns) to remain lofted for long periods of time. However, in contrast with molecules of the major gases, their concentrations are highly variable in space and time. Their optical properties are also far more interesting. These airborne particles are either solid---hence the word "aerosols"---or liquid, most notably in the form of cloud droplets. Needless to say that both aerosols and clouds have major impacts on the balance of the Earth's climate system. Harder to understand, but nonetheless true, is that their climate impacts are much harder to assess by Earth system modelers than those of greenhouse gases such as CO2. That makes them prime targets of study by multiple approaches, including ground- and space-based remote sensing. To characterize aerosols and clouds quantitatively by optical remote sensing methods, either passive (sunlight-based) or active (laser-based), we need predictive capability for the signals recorded by sensors, whether ground-based, airborne, or carried by satellites. This in turn draws on the physical theory of "radiative transfer" that describes how the light propagates and scatters in the molecular-and-particulate atmosphere. This is a challenge for remote sensing scientists. I will show why by simulating with simple means the point spread function or "PSF" of scattering particulate atmospheres with varying opacity, thus covering tabletop analogs of the pristine air, the background aerosol, all the way to optically thick cloudy airmasses. I will also show PSF measurements of real clouds over New Mexico and Oklahoma. These were used as a piece of the Multiple Scattering Cloud Lidar (MuSCL) observations from which cloud properties where derived and compared against independent determinations. For the STEM-hungry, I will show how to derive the dependence of the cloud PSF on cloud geometry and opacity.

Use of In Situ Cloud Condensation Nuclei, Extinction, and Aerosol Size Distribution Measurements to Test a Method for Retrieving Cloud Condensation Nuclei Profiles From Surface Measurements

NASA Technical Reports Server (NTRS)

Ghan, Stephen J.; Rissman, Tracey A.; Ellman, Robert; Ferrare, Richard A.; Turner, David; Flynn, Connor; Wang, Jian; Ogren, John; Hudson, James; Jonsson, Haflidi H.;

Quantifying uncertainties in radar forward models through a comparison between CloudSat and SPartICus reflectivity factors

NASA Astrophysics Data System (ADS)

Mascio, Jeana; Mace, Gerald G.

2017-02-01

Interpretations of remote sensing measurements collected in sample volumes containing ice-phase hydrometeors are very sensitive to assumptions regarding the distributions of mass with ice crystal dimension, otherwise known as mass-dimensional or m-D relationships. How these microphysical characteristics vary in nature is highly uncertain, resulting in significant uncertainty in algorithms that attempt to derive bulk microphysical properties from remote sensing measurements. This uncertainty extends to radar reflectivity factors forward calculated from model output because the statistics of the actual m-D in nature is not known. To investigate the variability in m-D relationships in cirrus clouds, reflectivity factors measured by CloudSat are combined with particle size distributions (PSDs) collected by coincident in situ aircraft by using an optimal estimation-based (OE) retrieval of the m-D power law. The PSDs were collected by 12 flights of the Stratton Park Engineering Company Learjet during the Small Particles in Cirrus campaign. We find that no specific habit emerges as preferred, and instead, we find that the microphysical characteristics of ice crystal populations tend to be distributed over a continuum-defying simple categorization. With the uncertainties derived from the OE algorithm, the uncertainties in forward-modeled backscatter cross section and, in turn, radar reflectivity is calculated by using a bootstrapping technique, allowing us to infer the uncertainties in forward-modeled radar reflectivity that would be appropriately applied to remote sensing simulator algorithms.

Combined Lidar-Radar Remote Sensing: Initial Results from CRYSTAL-FACE and Implications for Future Spaceflight Missions

NASA Technical Reports Server (NTRS)

McGill, Matthew J.; Li, Li-Hua; Hart, William D.; Heymsfield, Gerald M.; Hlavka, Dennis L.; Vaughan, Mark A.; Winker, David M.

2003-01-01

In the near future NASA plans to fly satellites carrying a multi-wavelength backscatter lidar and a 94-GHz cloud profiling radar in formation to provide complete global profiling of cloud and aerosol properties. The CRYSTAL-FACE field campaign, conducted during July 2002, provided the first high-altitude colocated measurements from lidar and cloud profiling radar to simulate these spaceborne sensors. The lidar and radar provide complementary measurements with varying degrees of measurement overlap. This paper presents initial results of the combined airborne lidar-radar measurements during CRYSTAL-FACE. The overlap of instrument sensitivity is presented, within the context of particular CRYSTAL-FACE conditions. Results are presented to quantify the portion of atmospheric profiles sensed independently by each instrument and the portion sensed simultaneously by the two instruments.

ETO cloud studies for FIRE 2, part 1

NASA Technical Reports Server (NTRS)

Sassen, Kenneth

1992-01-01

This research program in support of Project FIRE (First ISCCP Regional Experiment) involved two efforts. The results of the first effort, which were in direct support of the Extended Time Observations (ETO) component, are described here. Over the period from June 1990 through May 1991, our remote sensing systems were applied to providing ground-truth cirrus cloud observations for a total of 71 NOAA polar orbiting satellite overpasses. (Chronological tables of this effort are provided.) The primary remote sensor was a dual-polarization ruby (0.694 microns wavelength) lidar, although mid-way through the program we added a number of radiometers to assess the surface radiation budget and cirrus cloud infrared emittance, and some supplemental observations from a Ka-band (8.6 mm) radar were also collected. These studies were conducted from the Facility for Atmospheric Remote Sensing (FARS) at 40 degrees 46 minutes 00 seconds north latitude and 111 degrees 49 minutes 38 seconds east longitude. We also investigated the unusual characteristics of a subset of ETO case studies involving cirrus that generated solar and lunar corona displays. As we reported recently (reprint attached), these cirrus were atypically high and cold in relation to our total midlatitude cloud sample, and were comprised of unexpectedly small ice crystals from 10 to 30 microns in dimension. This finding lends some credence to the so-called cirrus small particle radiative anomaly, but only for very cold (less than -60 C) cirrus clouds. In a supplement, we will describe the design and testing of a prototype cirrus cloud polar nephelometer, which we constructed as part of our second research effort, to allow scattering phase functions to be obtained in future in situ cirrus research.

Monitoring Snow Using Geostationary Satellite Retrievals During the SAAWSO Project

NASA Astrophysics Data System (ADS)

Rabin, Robert M.; Gultepe, Ismail; Kuligowski, Robert J.; Heidinger, Andrew K.

2016-09-01

The SAAWSO (Satellite Applications for Arctic Weather and SAR (Search And Rescue) Operations) field programs were conducted by Environment Canada near St. Johns, NL and Goose Bay, NL in the winters of 2012-13 and 2013-14, respectively. The goals of these programs were to validate satellite-based nowcasting products, including snow amount, wind intensity, and cloud physical parameters (e.g., cloud cover), over northern latitudes with potential applications to Search And Rescue (SAR) operations. Ground-based in situ sensors and remote sensing platforms were used to measure microphysical properties of precipitation, clouds and fog, radiation, temperature, moisture and wind profiles. Multi-spectral infrared observations obtained from Geostationary Operational Environmental Satellite (GOES)-13 provided estimates of cloud top temperature and height, phase (water, ice), hydrometer size, extinction, optical depth, and horizontal wind patterns at 15 min intervals. In this work, a technique developed for identifying clouds capable of producing high snowfall rates and incorporating wind information from the satellite observations is described. The cloud top physical properties retrieved from operational satellite observations are validated using measurements obtained from the ground-based in situ and remote sensing platforms collected during two precipitation events: a blizzard heavy snow storm case and a moderate snow event. The retrieved snow precipitation rates are found to be comparable to those of ground-based platform measurements in the heavy snow event.

Developing and bounding ice particle mass- and area-dimension expressions for use in atmospheric models and remote sensing

DOE PAGES

Erfani, Ehsan; Mitchell, David L.

2016-04-07

Here, ice particle mass- and projected area-dimension ( m- D and A- D) power laws are commonly used in the treatment of ice cloud microphysical and optical properties and the remote sensing of ice cloud properties. Although there has long been evidence that a single m- D or A- D power law is often not valid over all ice particle sizes, few studies have addressed this fact. This study develops self-consistent m- D and A- D expressions that are not power laws but can easily be reduced to power laws for the ice particle size (maximum dimension or D) rangemore » of interest, and they are valid over a much larger D range than power laws. This was done by combining ground measurements of individual ice particle m and D formed at temperature T < –20 °C during a cloud seeding field campaign with 2-D stereo (2D-S) and cloud particle imager (CPI) probe measurements of D and A, and estimates of m, in synoptic and anvil ice clouds at similar temperatures. The resulting m- D and A- D expressions are functions of temperature and cloud type (synoptic vs. anvil), and are in good agreement with m- D power laws developed from recent field studies considering the same temperature range (–60 °C < T < –20 °C).« less

New Directions: Emerging Satellite Observations of Above-cloud Aerosols and Direct Radiative Forcing

NASA Technical Reports Server (NTRS)

Yu, Hongbin; Zhang, Zhibo

2013-01-01

Spaceborne lidar and passive sensors with multi-wavelength and polarization capabilities onboard the A-Train provide unprecedented opportunities of observing above-cloud aerosols and direct radiative forcing. Significant progress has been made in recent years in exploring these new aerosol remote sensing capabilities and generating unique datasets. The emerging observations will advance the understanding of aerosol climate forcing.

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.

Several thoughts for using new satellite remote sensing and global modeling for aerosol and cloud climate studies

NASA Astrophysics Data System (ADS)

Nakajima, Teruyuki; Hashimoto, Makiko; Takenaka, Hideaki; Goto, Daisuke; Oikawa, Eiji; Suzuki, Kentaroh; Uchida, Junya; Dai, Tie; Shi, Chong

2017-04-01

The rapid growth of satellite remote sensing technologies in the last two decades widened the utility of satellite data for understanding climate impacts of aerosols and clouds. The climate modeling community also has received the benefit of the earth observation and nowadays closed-collaboration of the two communities make us possible to challenge various applications for societal problems, such as for global warming and global-scale air pollution and others. I like to give several thoughts of new algorithm developments, model use of satellite data for climate impact studies and societal applications related with aerosols and clouds. Important issues are 1) Better aerosol detection and solar energy application using expanded observation ability of the third generation geostationary satellites, i.e. Himawari-8, GOES-R and future MTG, 2) Various observation functions by directional, polarimetric, and high resolution near-UV band by MISR, POLDER&PARASOL, GOSAT/CAI and future GOSAT2/CAI2, 3) Various applications of general purpose-imagers, MODIS, VIIRS and future GCOM-C/SGLI, and 4) Climate studies of aerosol and cloud stratification and convection with active and passive sensors, especially climate impact of BC aerosols using CLOUDSAT&CALIPSO and future Earth Explorer/EarthCARE.

Quantifying the microphysical impacts of fire aerosols on clouds in Indonesia using remote sensing observations

NASA Astrophysics Data System (ADS)

Tosca, M. G.; Diner, D. J.; Garay, M. J.; Kalashnikova, O. V.

2012-12-01

Fire-emitted aerosols modify cloud and precipitation dynamics by acting as cloud condensation nuclei in what is known as the first and second aerosol indirect effect. The cloud response to the indirect effect varies regionally and is not well understood in the highly convective tropics. We analyzed nine years (2003-2011) of aerosol data from the Multi-angle Imaging SpectroRadiometer (MISR), and fire emissions data from the Global Fire Emissions Database, version 3 (GFED3) over southeastern tropical Asia (Indonesia), and identified scenes that contained both a high atmospheric aerosol burden and large surface fire emissions. We then collected scenes from the Cloud Profiling Radar (CPR) on board the CLOUDSAT satellite that corresponded both spatially and temporally to the high-burning scenes from MISR, and identified differences in convective cloud dynamics over areas with varying aerosol optical depths. Differences in overpass times (MISR in the morning, CLOUDSAT in the afternoon) improved our ability to infer that changes in cloud dynamics were a response to increased or decreased aerosol emissions. Our results extended conclusions from initial studies over the Amazon that used remote sensing techniques to identify cloud fraction reductions in high burning areas (Koren et al., 2004; Rosenfeld, 1999) References Koren, I., Y.J. Kaufman, L.A. Remer and J.V. Martins (2004), Measurement of the effect of Amazon smoke on inhibition of cloud formation, Science, 303, 1342-1345 Rosenfeld, D. (1999), TRMM observed first direct evidence of smoke from forest fires inhibiting rainfall, Gephys. Res. Lett., 26, 3105.

Trade cumulus clouds embedded in a deep regional haze: Results from Indian Ocean CARDEX experiment

NASA Astrophysics Data System (ADS)

Wilcox, E. M.; Thomas, R. M.; Praveen, P. S.; Pistone, K.; Bender, F.; Feng, Y.; Ramanathan, V.

2013-12-01

During the winter monsoon, trade cumulus clouds over the North Indian Ocean are embedded within a deep regional haze described as an atmospheric brown cloud. While the trade-cu clouds are largely confined to the marine boundary layer, the sooty brown cloud extends from the boundary layer to as high as 3 km; well above the tops of the cumulus. The boundary layer pollution is persistent and limits drizzle in the cumulus over a period of greater than a month at the Maldives Climate Observatory located at Hanimaadhoo Island. The elevated haze from 1 to 3 km altitude is episodic and strongly modulated by synoptic variability in the 700 hPa flow. The elevated plume enhances heating above the marine boundary layer through daytime absorption of sunlight by the haze particles. The interplay between the microphysical modification of clouds by boundary layer pollution and the episodic elevated heating by the atmospheric brown cloud are explored in in-situ observations from UAVs and surface remote sensing during the CARDEX field campaign of winter 2012 and supported by multi-year analysis of satellite remote sensing observations. These observations document the variability in pollution at the surface and above the marine boundary layer and the effects of pollution on the microphysics of the trade-cu clouds, the depth of the marine boundary layer, the liquid water path of trade-cu clouds, and the profile of turbulent moisture flux through the boundary layer. The consequences of these effects for the radiative forcing of regional climate will be discussed.

Relationship between convective clouds and precipitation over the Qinghai-Xizang Plateau area from satellite remote sensing and ground-based observations

NASA Technical Reports Server (NTRS)

Hung, R. J.; Liu, J. M.; Tsao, D. Y.; Smith, R. E.

1985-01-01

Results of this study show that heavy rainfall in the Qinghai-Xizang Plateau area is usually preceded by a high growth rate of the convective clouds followed by a rapid collapse of the cloud top. The tops of the convective clouds associated with heavy rainfall over the plateau usually lie between the altitudes of the two tropopauses which exist over the plateau. Undoubtedly the double tropopause restricts the vertical growth of the clouds and this may be the reason why tornadoes rarely occur there.

The Prospect for Remote Sensing of Cirrus Clouds with a Submillimeter-Wave Spectrometer

NASA Technical Reports Server (NTRS)

Evans, K. Franklin; Evans, Aaron H.; Nolt, Ira G.; Marshall, B. Thomas

1999-01-01

Given the substantial radiative effects of cirrus clouds and the need to validate cirrus cloud mass in climate models, it is important to measure the global distribution of cirrus properties with satellite remote sensing. Existing cirrus remote sensing techniques, such as solar reflectance methods, measure cirrus ice water path (IWP) rather indirectly and with limited accuracy. Submillimeter/wave radiometry is an independent method of cirrus remote sensing based on ice particles scattering the upwelling radiance emitted by the lower atmosphere. A new aircraft instrument, the Far Infrared Sensor for Cirrus (FIRSC), is described. The FIRSC employs a Fourier Transform Spectrometer (FTS). which measures the upwelling radiance across the whole submillimeter region (0.1 1.0-mm wavelength). This wide spectral coverage gives high sensitivity to most cirrus particle sizes and allows accurate determination of the characteristic particle size. Radiative transfer modeling is performed to analyze the capabilities of the submillimeter FTS technique. A linear inversion analysis is done to show that cirrus IWP, particle size, and upper-tropospheric temperature and water vapor may be accurately measured, A nonlinear statistical algorithm is developed using a database of 20000 spectra simulated by randomly varying most relevant cirrus and atmospheric parameters. An empirical orthogonal function analysis reduces the 500-point spectrum (20 - 70/cm) to 15 "pseudo-channels" that are then input to a neural network to retrieve cirrus IWP and median particle diameter. A Monte Carlo accuracy study is performed with simulated spectra having realistic noise. The retrieval errors are low for IWP (rms less than a factor of 1.5) and for particle sizes (rins less than 30%) for IWP greater than 5 g/sq m and a wide range of median particle sizes. This detailed modeling indicates that there is good potential to accurately measure cirrus properties with a submillimeter FTS.

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).

Satellite remote sensing and cloud modeling of St. Anthony, Minnesota storm clouds and dew point depression

NASA Technical Reports Server (NTRS)

Hung, R. J.; Tsao, Y. D.

1988-01-01

Rawinsonde data and geosynchronous satellite imagery were used to investigate the life cycles of St. Anthony, Minnesota's severe convective storms. It is found that the fully developed storm clouds, with overshooting cloud tops penetrating above the tropopause, collapsed about three minutes before the touchdown of the tornadoes. Results indicate that the probability of producing an outbreak of tornadoes causing greater damage increases when there are higher values of potential energy storage per unit area for overshooting cloud tops penetrating the tropopause. It is also found that there is less chance for clouds with a lower moisture content to be outgrown as a storm cloud than clouds with a higher moisture content.

FIRE Cirrus on October 28, 1986: LANDSAT; ER-2; King Air; theory

NASA Technical Reports Server (NTRS)

Wielicki, Bruce A.; Suttles, John T.; Heymsfield, Andrew J.; Welch, Ronald M.; Spinhirne, James D.; Parker, Lindsay; Arduini, Robert F.

1990-01-01

A simultaneous examination was conducted of cirrus clouds in the FIRE Cirrus IFO-I on 10/28/86 using a multitude of remote sensing and in-situ measurements. The focus is cirrus cloud radiative properties and their relationship to cloud microphysics. A key element is the comparison of radiative transfer model calculations and varying measured cirrus radiative properties (emissivity, reflectance vs. wavelength, reflectance vs. viewing angle). As the number of simultaneously measured cloud radiative properties and physical properties increases, more sharply focused tests of theoretical models are possible.

Estimation of Microphysical and Radiative Parameters of Precipitating Cloud Systems Using mm-Wavelength Radars

NASA Astrophysics Data System (ADS)

Matrosov, Sergey Y.

2009-03-01

A remote sensing approach is described to retrieve cloud and rainfall parameters within the same precipitating system. This approach is based on mm-wavelength radar signal attenuation effects which are observed in a layer of liquid precipitation containing clouds and rainfall. The parameters of ice clouds in the upper part of startiform precipitating systems are then retrieved using the absolute measurements of radar reflectivity. In case of the ground-based radar location, these measurements are corrected for attenuation in the intervening layer of liquid hydrometers.

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.

Development of GK-2A cloud optical and microphysical properties retrieval algorithm

NASA Astrophysics Data System (ADS)

Yang, Y.; Yum, S. S.; Um, J.

2017-12-01

Cloud and aerosol radiative forcing is known to be one of the the largest uncertainties in climate change prediction. To reduce this uncertainty, remote sensing observation of cloud radiative and microphysical properties have been used since 1970s and the corresponding remote sensing techniques and instruments have been developed. As a part of such effort, Geo-KOMPSAT-2A (Geostationary Korea Multi-Purpose Satellite-2A, GK-2A) will be launched in 2018. On the GK-2A, the Advanced Meteorological Imager (AMI) is primary instrument which have 3 visible, 3 near-infrared, and 10 infrared channels. To retrieve optical and microphysical properties of clouds using AMI measurements, the preliminary version of new cloud retrieval algorithm for GK-2A was developed and several validation tests were conducted. This algorithm retrieves cloud optical thickness (COT), cloud effective radius (CER), liquid water path (LWP), and ice water path (IWP), so we named this algorithm as Daytime Cloud Optical thickness, Effective radius and liquid and ice Water path (DCOEW). The DCOEW uses cloud reflectance at visible and near-infrared channels as input data. An optimal estimation (OE) approach that requires appropriate a-priori values and measurement error information is used to retrieve COT and CER. LWP and IWP are calculated using empirical relationships between COT/CER and cloud water path that were determined previously. To validate retrieved cloud properties, we compared DCOEW output data with other operational satellite data. For COT and CER validation, we used two different data sets. To compare algorithms that use cloud reflectance at visible and near-IR channels as input data, MODIS MYD06 cloud product was selected. For the validation with cloud products that are based on microwave measurements, COT(2B-TAU)/CER(2C-ICE) data retrieved from CloudSat cloud profiling radar (W-band, 94 GHz) was used. For cloud water path validation, AMSR-2 Level-3 Cloud liquid water data was used. Detailed results will be shown at the conference.

On remote sounding of the upper atmosphere of Venus

NASA Technical Reports Server (NTRS)

Houghton, J. T.; Taylor, F. W.

1975-01-01

Some of the possibilities for remote sensing of the upper atmosphere of Venus from an orbiting spacecraft are studied quantitatively. Temperature sounding over a wide vertical range, from the main cloud top near 60 km altitude to the nanobar level near 160 km, is shown to be feasible. Techniques which deconvolve the cloud structure from the temperature profile measurements are examined. Humidity measurements by simple radiometry are feasible for column abundances greater than or equal to 10 precipitable micrometers. The information content of limb radiance measurements, in different wavelengths and for various viewing geometries, is also analyzed.

Reconciling Ground-Based and Space-Based Estimates of the Frequency of Occurrence and Radiative Effect of Clouds around Darwin, Australia

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

Protat, Alain; Young, Stuart; McFarlane, Sally A.

2014-02-01

The objective of this paper is to investigate whether estimates of the cloud frequency of occurrence and associated cloud radiative forcing as derived from ground-based and satellite active remote sensing and radiative transfer calculations can be reconciled over a well instrumented active remote sensing site located in Darwin, Australia, despite the very different viewing geometry and instrument characteristics. It is found that the ground-based radar-lidar combination at Darwin does not detect most of the cirrus clouds above 10 km (due to limited lidar detection capability and signal obscuration by low-level clouds) and that the CloudSat radar - Cloud-Aerosol Lidar withmore » Orthogonal Polarization (CALIOP) combination underreports the hydrometeor frequency of occurrence below 2 km height, due to instrument limitations at these heights. The radiative impact associated with these differences in cloud frequency of occurrence is large on the surface downwelling shortwave fluxes (ground and satellite) and the top-of atmosphere upwelling shortwave and longwave fluxes (ground). Good agreement is found for other radiative fluxes. Large differences in radiative heating rate as derived from ground and satellite radar-lidar instruments and RT calculations are also found above 10 km (up to 0.35 Kday-1 for the shortwave and 0.8 Kday-1 for the longwave). Given that the ground-based and satellite estimates of cloud frequency of occurrence and radiative impact cannot be fully reconciled over Darwin, caution should be exercised when evaluating the representation of clouds and cloud-radiation interactions in large-scale models and limitations of each set of instrumentation should be considered when interpreting model-observations differences.« less

The application of time series models to cloud field morphology analysis

NASA Technical Reports Server (NTRS)

Chin, Roland T.; Jau, Jack Y. C.; Weinman, James A.

1987-01-01

A modeling method for the quantitative description of remotely sensed cloud field images is presented. A two-dimensional texture modeling scheme based on one-dimensional time series procedures is adopted for this purpose. The time series procedure used is the seasonal autoregressive, moving average (ARMA) process in Box and Jenkins. Cloud field properties such as directionality, clustering and cloud coverage can be retrieved by this method. It has been demonstrated that a cloud field image can be quantitatively defined by a small set of parameters and synthesized surrogates can be reconstructed from these model parameters. This method enables cloud climatology to be studied quantitatively.

Remote sensing based crop type mapping and evapotranspiration estimates at the farm level in arid regions of the globe

NASA Astrophysics Data System (ADS)

Ozdogan, M.; Serrat-Capdevila, A.; Anderson, M. C.

2017-12-01

Despite increasing scarcity of freshwater resources, there is dearth of spatially explicit information on irrigation water consumption through evapotranspiration, particularly in semi-arid and arid geographies. Remote sensing, either alone or in combination with ground surveys, is increasingly being used for irrigation water management by quantifying evaporative losses at the farm level. Increased availability of observations, sophisticated algorithms, and access to cloud-based computing is also helping this effort. This presentation will focus on crop-specific evapotranspiration estimates at the farm level derived from remote sensing in a number of water-scarce regions of the world. The work is part of a larger effort to quantify irrigation water use and improve use efficiencies associated with several World Bank projects. Examples will be drawn from India, where groundwater based irrigation withdrawals are monitored with the help of crop type mapping and evapotranspiration estimates from remote sensing. Another example will be provided from a northern irrigation district in Mexico, where remote sensing is used for detailed water accounting at the farm level. These locations exemplify the success stories in irrigation water management with the help of remote sensing with the hope that spatially disaggregated information on evapotranspiration can be used as inputs for various water management decisions as well as for better water allocation strategies in many other water scarce regions.

Mobile-Cloud Assisted Video Summarization Framework for Efficient Management of Remote Sensing Data Generated by Wireless Capsule Sensors

PubMed Central

Mehmood, Irfan; Sajjad, Muhammad; Baik, Sung Wook

2014-01-01

Wireless capsule endoscopy (WCE) has great advantages over traditional endoscopy because it is portable and easy to use, especially in remote monitoring health-services. However, during the WCE process, the large amount of captured video data demands a significant deal of computation to analyze and retrieve informative video frames. In order to facilitate efficient WCE data collection and browsing task, we present a resource- and bandwidth-aware WCE video summarization framework that extracts the representative keyframes of the WCE video contents by removing redundant and non-informative frames. For redundancy elimination, we use Jeffrey-divergence between color histograms and inter-frame Boolean series-based correlation of color channels. To remove non-informative frames, multi-fractal texture features are extracted to assist the classification using an ensemble-based classifier. Owing to the limited WCE resources, it is impossible for the WCE system to perform computationally intensive video summarization tasks. To resolve computational challenges, mobile-cloud architecture is incorporated, which provides resizable computing capacities by adaptively offloading video summarization tasks between the client and the cloud server. The qualitative and quantitative results are encouraging and show that the proposed framework saves information transmission cost and bandwidth, as well as the valuable time of data analysts in browsing remote sensing data. PMID:25225874

Mobile-cloud assisted video summarization framework for efficient management of remote sensing data generated by wireless capsule sensors.

PubMed

Mehmood, Irfan; Sajjad, Muhammad; Baik, Sung Wook

2014-09-15

Wireless capsule endoscopy (WCE) has great advantages over traditional endoscopy because it is portable and easy to use, especially in remote monitoring health-services. However, during the WCE process, the large amount of captured video data demands a significant deal of computation to analyze and retrieve informative video frames. In order to facilitate efficient WCE data collection and browsing task, we present a resource- and bandwidth-aware WCE video summarization framework that extracts the representative keyframes of the WCE video contents by removing redundant and non-informative frames. For redundancy elimination, we use Jeffrey-divergence between color histograms and inter-frame Boolean series-based correlation of color channels. To remove non-informative frames, multi-fractal texture features are extracted to assist the classification using an ensemble-based classifier. Owing to the limited WCE resources, it is impossible for the WCE system to perform computationally intensive video summarization tasks. To resolve computational challenges, mobile-cloud architecture is incorporated, which provides resizable computing capacities by adaptively offloading video summarization tasks between the client and the cloud server. The qualitative and quantitative results are encouraging and show that the proposed framework saves information transmission cost and bandwidth, as well as the valuable time of data analysts in browsing remote sensing data.

Effects of Cloud Particles on Remote Sensing from Space in the 10-Micrometer Infrared Region.

DTIC Science & Technology

1977-01-01

ayers , that is , a plane-parallel atmosphere wi th infinite hori zontal extent . As a matter of fact, this is how the planeta ry atmosphere is being...Remote Probin g of the Atmosphe re, 1973. 43 . Hansen , J. E. and L. D. Travis , 1974 , “Light Scattering in Planeta ry • Atmospheres ,” Goddard

The Development Of Enabling Technologies For Submillimeter-Wave Remote Sensing of Ice Clouds From Space

NASA Technical Reports Server (NTRS)

Racette, Paul; Wang, James R.; Ackerman, Steven; Skofronick-Jackson, Gail; Evans, K. Frank; O'CStarr, David

2006-01-01

This paper presents the chronological development of technologies and techniques that have led to a satellite mission concept aimed at quantifying the temporal and spatial distributions of upper tropospheric ice clouds. The Submillimeter-wave and Infrared Ice Cloud Experiment (SIRICE) is an Earth System Science Pathfinder mission concept designed to improve our understanding of the upper tropospheric water cycle and its coupling to the Earth s radiation budget. Ice outflow from convective storm systems is known to play an important role in regional energy budgets; however, ice generation and subsequent precipitation and sublimation are poorly quantified. SIRICE will provide measurements of ice cloud distributions and microphysical properties which are needed for understanding the crucial link between the hydrologic and energy cycles. The SIRICE measurement platform is comprised of two integrated instruments, the Submillimeter/millimeter-wave radiometer (SM4) and the Infrared Cloud Ice Radiometer (IRCIR). The primary instrument is the SM4, a conical scanner that provides a 1600 km swath of the Earth's surface at 53 degree incidence. The SM4 has 6 linearly polarized receivers measuring 12 spectral bands centered at 183 GHz, 325 GHz, 448 GHz, 643 GHz and 874 GHz; two receivers at 643 GHz measure horizontal and vertical polarizations. Submillimeter-wavelengths are well suited to the remote sensing of ice clouds due to the relative size of the wavelengths to particle sizes. Upwelling emission from lower tropospheric water vapor is scattered by the ice clouds thus causing a brightness temperature depression at submillimeter wavelengths. The IRCIR is a push broom imager with approximately 1500 km swath and spectral channels at 11 and 12 micrometers. This combination of coincident infrared and submillimeter-wavelength measurements were chosen because of its ability to provide retrieval of ice water path and median particle size for a wide range of ice clouds from thin cirrus to thick anvil structures. Over the past decade there has been a parallel development of submillimeter-wave technologies, demonstration instruments, and remote sensing techniques that have led to the present SIRICE mission concept. Mapping of these developmental paths reveals the origins, rational and maturity of features of the SIRICE payload such as its channel selection, compact design, and multipoint calibration. This presentation traces the evolution of the SIRICE mission concept from the early 1990's to its present status.

Monitoring of "all-weather" evapotranspiration using optical and passive microwave remote sensing imagery over the River Source Region in Southwest China

NASA Astrophysics Data System (ADS)

Ma, Y.; Liu, S.

2017-12-01

Accurate estimation of surface evapotranspiration (ET) with high quality is one of the biggest obstacles for routine applications of remote sensing in eco-hydrological studies and water resource management at basin scale. However, many aspects urgently need to deeply research, such as the applicability of the ET models, the parameterization schemes optimization at the regional scale, the temporal upscaling, the selecting and developing of the spatiotemporal data fusion method and ground-based validation over heterogeneous land surfaces. This project is based on the theoretically robust surface energy balance system (SEBS) model, which the model mechanism need further investigation, including the applicability and the influencing factors, such as local environment, and heterogeneity of the landscape, for improving estimation accuracy. Due to technical and budget limitations, so far, optical remote sensing data is missing due to frequent cloud contamination and other poor atmospheric conditions in Southwest China. Here, a multi-source remote sensing data fusion method (ESTARFM: Enhanced Spatial and Temporal Adaptive Reflectance Fusion Model) method will be proposed through blending multi-source remote sensing data acquired by optical, and passive microwave remote sensors on board polar satellite platforms. The accurate "all-weather" ET estimation will be carried out for daily ET of the River Source Region in Southwest China, and then the remotely sensed ET results are overlapped with the footprint-weighted images of EC (eddy correlation) for ground-based validation.

Satellite remote sensing of dust aerosol indirect effects on ice cloud formation.

PubMed

Ou, Steve Szu-Cheng; Liou, Kuo-Nan; Wang, Xingjuan; Hansell, Richard; Lefevre, Randy; Cocks, Stephen

2009-01-20

We undertook a new approach to investigate the aerosol indirect effect of the first kind on ice cloud formation by using available data products from the Moderate-Resolution Imaging Spectrometer (MODIS) and obtained physical understanding about the interaction between aerosols and ice clouds. Our analysis focused on the examination of the variability in the correlation between ice cloud parameters (optical depth, effective particle size, cloud water path, and cloud particle number concentration) and aerosol optical depth and number concentration that were inferred from available satellite cloud and aerosol data products. Correlation results for a number of selected scenes containing dust and ice clouds are presented, and dust aerosol indirect effects on ice clouds are directly demonstrated from satellite observations.

A Case Study of Ship Track Formation in a Polluted Marine Boundary Layer.

NASA Astrophysics Data System (ADS)

Noone, Kevin J.; Johnson, Doug W.; Taylor, Jonathan P.; Ferek, Ronald J.; Garrett, Tim; Hobbs, Peter V.; Durkee, Philip A.; Nielsen, Kurt; Öström, Elisabeth; O'Dowd, Colin; Smith, Michael H.; Russell, Lynn M.; Flagan, Richard C.; Seinfeld, John H.; de Bock, Lieve; van Grieken, René E.; Hudson, James G.; Brooks, Ian;  Gasparovic, Richard F.;  Pockalny, Robert A.

2000-08-01

A case study of the effects of ship emissions on the microphysical, radiative, and chemical properties of polluted marine boundary layer clouds is presented. Two ship tracks are discussed in detail. In situ measurements of cloud drop size distributions, liquid water content, and cloud radiative properties, as well as aerosol size distributions (outside-cloud, interstitial, and cloud droplet residual particles) and aerosol chemistry, are presented. These are related to remotely sensed measurements of cloud radiative properties.The authors examine the processes behind ship track formation in a polluted marine boundary layer as an example of the effects of anthropogenic particulate pollution on the albedo of marine stratiform clouds.

Multi-Spectral Stereo Atmospheric Remote Sensing (STARS) for Retrieval of Cloud Properties and Cloud-Motion Vectors

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.

Comparing the cloud vertical structure derived from several methods based on radiosonde profiles and ground-based remote sensing measurements

NASA Astrophysics Data System (ADS)

Costa-Surós, M.; Calbó, J.; González, J. A.; Long, C. N.

2014-08-01

The cloud vertical distribution and especially the cloud base height, which is linked to cloud type, are important characteristics in order to describe the impact of clouds on climate. In this work, several methods for estimating the cloud vertical structure (CVS) based on atmospheric sounding profiles are compared, considering the number and position of cloud layers, with a ground-based system that is taken as a reference: the Active Remote Sensing of Clouds (ARSCL). All methods establish some conditions on the relative humidity, and differ in the use of other variables, the thresholds applied, or the vertical resolution of the profile. In this study, these methods are applied to 193 radiosonde profiles acquired at the Atmospheric Radiation Measurement (ARM) Southern Great Plains site during all seasons of the year 2009 and endorsed by Geostationary Operational Environmental Satellite (GOES) images, to confirm that the cloudiness conditions are homogeneous enough across their trajectory. The perfect agreement (i.e., when the whole CVS is estimated correctly) for the methods ranges between 26 and 64%; the methods show additional approximate agreement (i.e., when at least one cloud layer is assessed correctly) from 15 to 41%. Further tests and improvements are applied to one of these methods. In addition, we attempt to make this method suitable for low-resolution vertical profiles, like those from the outputs of reanalysis methods or from the World Meteorological Organization's (WMO) Global Telecommunication System. The perfect agreement, even when using low-resolution profiles, can be improved by up to 67% (plus 25% of the approximate agreement) 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.

Cloud Properties and Radiative Heating Rates for TWP

DOE Data Explorer

Comstock, Jennifer

2013-11-07

A cloud properties and radiative heating rates dataset is presented where cloud properties retrieved using lidar and radar observations are input into a radiative transfer model to compute radiative fluxes and heating rates at three ARM sites located in the Tropical Western Pacific (TWP) region. The cloud properties retrieval is a conditional retrieval that applies various retrieval techniques depending on the available data, that is if lidar, radar or both instruments detect cloud. This Combined Remote Sensor Retrieval Algorithm (CombRet) produces vertical profiles of liquid or ice water content (LWC or IWC), droplet effective radius (re), ice crystal generalized effective size (Dge), cloud phase, and cloud boundaries. The algorithm was compared with 3 other independent algorithms to help estimate the uncertainty in the cloud properties, fluxes, and heating rates (Comstock et al. 2013). The dataset is provided at 2 min temporal and 90 m vertical resolution. The current dataset is applied to time periods when the MMCR (Millimeter Cloud Radar) version of the ARSCL (Active Remotely-Sensed Cloud Locations) Value Added Product (VAP) is available. The MERGESONDE VAP is utilized where temperature and humidity profiles are required. Future additions to this dataset will utilize the new KAZR instrument and its associated VAPs.

Observations of Aerosol-Radiation-Cloud Interactions in the South-East Atlantic: First Results from the ORACLES Deployments in 2016 and 2017

NASA Technical Reports Server (NTRS)

Redemann, Jens; Wood, R.; Zuidema, P.; Diner, D.; Van Harten, G.; Xu, F.; Cairns, B.; Knobelspiesse, K.; Segal Rozenhaimer, M.

2017-01-01

Southern Africa produces almost a third of the Earths biomass burning (BB) aerosol particles. Particles lofted into the mid-troposphere are transported westward over the South-East (SE) Atlantic, home to one of the three permanent subtropical stratocumulus (Sc) cloud decks in the world. The SE Atlantic stratocumulus deck interacts with the dense layers of BB aerosols that initially overlay the cloud deck, but later subside and often mix into the clouds. These interactions include adjustments to aerosol-induced solar heating and microphysical effects, and their global representation in climate models remains one of the largest uncertainties in estimates of future climate. Hence, new observations over the SE Atlantic have significant implications for regional and global climate change predictions.The low-level clouds in the SE Atlantic have limited vertical extent and therefore present favorable conditions for their exploration with remote sensing. On the other hand, the normal coexistence of BB aerosols and Sc clouds in the same scene also presents significant challenges to conventional remote sensing techniques. We describe first results from NASAs airborne ORACLES (ObseRvations of Aerosols Above Clouds and Their IntEractionS) deployments in September 2016 and August 2017. We emphasize the unique role of polarimetric observations by two instruments, the Research Scanning Polarimeter (RSP) and the Airborne Multi-angle SpectroPolarimeter Imager (AirMSPI), and describe how these instruments help address specific ORACLES science objectives. Initial assessments of polarimetric observation accuracy for key cloud and aerosol properties will be presented, in as far as the preliminary nature of measurements permits.

Reconstructing spatial-temporal continuous MODIS land surface temperature using the DINEOF method

NASA Astrophysics Data System (ADS)

Zhou, Wang; Peng, Bin; Shi, Jiancheng

2017-10-01

Land surface temperature (LST) is one of the key states of the Earth surface system. Remote sensing has the capability to obtain high-frequency LST observations with global coverage. However, mainly due to cloud cover, there are always gaps in the remotely sensed LST product, which hampers the application of satellite-based LST in data-driven modeling of surface energy and water exchange processes. We explored the suitability of the data interpolating empirical orthogonal functions (DINEOF) method in moderate resolution imaging spectroradiometer LST reconstruction around Ali on the Tibetan Plateau. To validate the reconstruction accuracy, synthetic clouds during both daytime and nighttime are created. With DINEOF reconstruction, the root mean square error and bias under synthetic clouds in daytime are 4.57 and -0.0472 K, respectively, and during the nighttime are 2.30 and 0.0045 K, respectively. The DINEOF method can well recover the spatial pattern of LST. Time-series analysis of LST before and after DINEOF reconstruction from 2002 to 2016 shows that the annual and interannual variabilities of LST can be well reconstructed by the DINEOF method.

A two-step framework for reconstructing remotely sensed land surface temperatures contaminated by cloud

NASA Astrophysics Data System (ADS)

Zeng, Chao; Long, Di; Shen, Huanfeng; Wu, Penghai; Cui, Yaokui; Hong, Yang

2018-07-01

Land surface temperature (LST) is one of the most important parameters in land surface processes. Although satellite-derived LST can provide valuable information, the value is often limited by cloud contamination. In this paper, a two-step satellite-derived LST reconstruction framework is proposed. First, a multi-temporal reconstruction algorithm is introduced to recover invalid LST values using multiple LST images with reference to corresponding remotely sensed vegetation index. Then, all cloud-contaminated areas are temporally filled with hypothetical clear-sky LST values. Second, a surface energy balance equation-based procedure is used to correct for the filled values. With shortwave irradiation data, the clear-sky LST is corrected to the real LST under cloudy conditions. A series of experiments have been performed to demonstrate the effectiveness of the developed approach. Quantitative evaluation results indicate that the proposed method can recover LST in different surface types with mean average errors in 3-6 K. The experiments also indicate that the time interval between the multi-temporal LST images has a greater impact on the results than the size of the contaminated area.

Global radiation maps and their modulation by clouds. - An assessment of limitations and deficiencies in global modelling

NASA Astrophysics Data System (ADS)

Kinne, Stefan; Stubenrauch, Claudia; Raschke, Erhard

2010-05-01

Satellite sensed solar and infrared broadband radiation maps at the top of the atmosphere (ToA) usually serve as reference and constrains to global modelling. Complimentary radiation maps at the surface are less certain, as they require accurate knowledge about atmospheric and environmental properties. Despite differences among multi-decadal data-projects of ISCCP, the SRB and the CERES, their diversity is small in comparison to efforts in global modelling. Based on simulations for the IPCC fourth assessment, clear biases on a regional and seasonal basis are identified and illustrate deficiencies in the representation of clouds. These deficiencies are explored in the context of available cloud data from passive and active remote sensing from space.

Remote real-time monitoring of subsurface landfill gas migration.

PubMed

Fay, Cormac; Doherty, Aiden R; Beirne, Stephen; Collins, Fiachra; Foley, Colum; Healy, John; Kiernan, Breda M; Lee, Hyowon; Maher, Damien; Orpen, Dylan; Phelan, Thomas; Qiu, Zhengwei; Zhang, Kirk; Gurrin, Cathal; Corcoran, Brian; O'Connor, Noel E; Smeaton, Alan F; Diamond, Dermot

2011-01-01

The cost of monitoring greenhouse gas emissions from landfill sites is of major concern for regulatory authorities. The current monitoring procedure is recognised as labour intensive, requiring agency inspectors to physically travel to perimeter borehole wells in rough terrain and manually measure gas concentration levels with expensive hand-held instrumentation. In this article we present a cost-effective and efficient system for remotely monitoring landfill subsurface migration of methane and carbon dioxide concentration levels. Based purely on an autonomous sensing architecture, the proposed sensing platform was capable of performing complex analytical measurements in situ and successfully communicating the data remotely to a cloud database. A web tool was developed to present the sensed data to relevant stakeholders. We report our experiences in deploying such an approach in the field over a period of approximately 16 months.

Remote Real-Time Monitoring of Subsurface Landfill Gas Migration

PubMed Central

Fay, Cormac; Doherty, Aiden R.; Beirne, Stephen; Collins, Fiachra; Foley, Colum; Healy, John; Kiernan, Breda M.; Lee, Hyowon; Maher, Damien; Orpen, Dylan; Phelan, Thomas; Qiu, Zhengwei; Zhang, Kirk; Gurrin, Cathal; Corcoran, Brian; O’Connor, Noel E.; Smeaton, Alan F.; Diamond, Dermot

2011-01-01

The cost of monitoring greenhouse gas emissions from landfill sites is of major concern for regulatory authorities. The current monitoring procedure is recognised as labour intensive, requiring agency inspectors to physically travel to perimeter borehole wells in rough terrain and manually measure gas concentration levels with expensive hand-held instrumentation. In this article we present a cost-effective and efficient system for remotely monitoring landfill subsurface migration of methane and carbon dioxide concentration levels. Based purely on an autonomous sensing architecture, the proposed sensing platform was capable of performing complex analytical measurements in situ and successfully communicating the data remotely to a cloud database. A web tool was developed to present the sensed data to relevant stakeholders. We report our experiences in deploying such an approach in the field over a period of approximately 16 months. PMID:22163975

Advantageous GOES IR results for ash mapping at high latitudes: Cleveland eruptions 2001

USGS Publications Warehouse

Gu, Yingxin; Rose, William I.; Schneider, D.J.; Bluth, G.J.S.; Watson, I.M.

2005-01-01

The February 2001 eruption of Cleveland Volcano, Alaska allowed for comparisons of volcanic ash detection using two-band thermal infrared (10-12 ??m) remote sensing from MODIS, AVHRR, and GOES 10. Results show that high latitude GOES volcanic cloud sensing the range of about 50 to 65??N is significantly enhanced. For the Cleveland volcanic clouds the MODIS and AVHRR data have zenith angles 6-65 degrees and the GOES has zenith angles that are around 70 degrees. The enhancements are explained by distortion in the satellite view of the cloud's lateral extent because the satellite zenith angles result in a "side-looking" aspect and longer path lengths through the volcanic cloud. The shape of the cloud with respect to the GOES look angle also influences the results. The MODIS and AVHRR data give consistent retrievals of the ash cloud evolution over time and are good corrections for the GOES data. Copyright 2005 by the American Geophysical Union.

Atmospheric boundary layer CO2 remote sensing with a direct detection LIDAR instrument based on a widely tunable optical parametric source.

PubMed

Cadiou, Erwan; Mammez, Dominique; Dherbecourt, Jean-Baptiste; Gorju, Guillaume; Pelon, Jacques; Melkonian, Jean-Michel; Godard, Antoine; Raybaut, Myriam

2017-10-15

We report on the capability of a direct detection differential absorption lidar (DIAL) for range resolved and integrated path (IPDIAL) remote sensing of CO 2 in the atmospheric boundary layer (ABL). The laser source is an amplified nested cavity optical parametric oscillator (NesCOPO) emitting approximately 8 mJ at the two measurement wavelengths selected near 2050 nm. Direct detection atmospheric measurements are taken from the ground using a 30 Hz frequency switching between emitted wavelengths. Results show that comparable precision measurements are achieved in DIAL and IPDIAL modes (not better than a few ppm) on high SNR targets such as near range ABL aerosol and clouds, respectively. Instrumental limitations are analyzed and degradation due to cloud scattering variability is discussed to explain observed DIAL and IPDIAL limitations.

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.

IOCCG Report Number 16, 2015 Ocean Colour Remote Sensing in Polar Seas . Chapter 2; The Polar Environment: Sun, Clouds, and Ice

NASA Technical Reports Server (NTRS)

Comiso, Josefino C.; Perovich, Don; Stamnes, Knut; Stuart, Venetia (Editor)

2015-01-01

The polar regions are places of extremes. There are months when the regions are enveloped in unending darkness, and months when they are in continuous daylight. During the daylight months the sun is low on the horizon and often obscured by clouds. In the dark winter months temperatures are brutally cold, and high winds and blowing snow are common. Even in summer, temperatures seldom rise above 0degC. The cold winter temperatures cause the ocean to freeze, forming sea ice. This sea ice cover acts as a barrier limiting the transfer of heat, moisture, and momentum between the atmosphere and the ocean. It also greatly complicates the optical signature of the surface. Taken together, these factors make the polar regions a highly challenging environment for optical remote sensing of the ocean.

Microwave (SSM/I) Estimates of the Precipitation Rate to Improve Numerical Atmospheric Model Forecasts

NASA Technical Reports Server (NTRS)

Raymond, William H.; Olson, William S.

1990-01-01

Delay in the spin-up of precipitation early in numerical atmospheric forecasts is a deficiency correctable by diabatic initialization combined with diabatic forcing. For either to be effective requires some knowledge of the magnitude and vertical placement of the latent heating fields. Until recently the best source of cloud and rain water data was the remotely sensed vertical integrated precipitation rate or liquid water content. Vertical placement of the condensation remains unknown. Some information about the vertical distribution of the heating rates and precipitating liquid water and ice can be obtained from retrieval techniques that use a physical model of precipitating clouds to refine and improve the interpretation of the remotely sensed data. A description of this procedure and an examination of its 3-D liquid water products, along with improved modeling methods that enhance or speed-up storm development is discussed.

A multi-year data set on aerosol-cloud-precipitation-meteorology interactions for marine stratocumulus clouds.

PubMed

Sorooshian, Armin; MacDonald, Alexander B; Dadashazar, Hossein; Bates, Kelvin H; Coggon, Matthew M; Craven, Jill S; Crosbie, Ewan; Hersey, Scott P; Hodas, Natasha; Lin, Jack J; Negrón Marty, Arnaldo; Maudlin, Lindsay C; Metcalf, Andrew R; Murphy, Shane M; Padró, Luz T; Prabhakar, Gouri; Rissman, Tracey A; Shingler, Taylor; Varutbangkul, Varuntida; Wang, Zhen; Woods, Roy K; Chuang, Patrick Y; Nenes, Athanasios; Jonsson, Haflidi H; Flagan, Richard C; Seinfeld, John H

2018-02-27

Airborne measurements of meteorological, aerosol, and stratocumulus cloud properties have been harmonized from six field campaigns during July-August months between 2005 and 2016 off the California coast. A consistent set of core instruments was deployed on the Center for Interdisciplinary Remotely-Piloted Aircraft Studies Twin Otter for 113 flight days, amounting to 514 flight hours. A unique aspect of the compiled data set is detailed measurements of aerosol microphysical properties (size distribution, composition, bioaerosol detection, hygroscopicity, optical), cloud water composition, and different sampling inlets to distinguish between clear air aerosol, interstitial in-cloud aerosol, and droplet residual particles in cloud. Measurements and data analysis follow documented methods for quality assurance. The data set is suitable for studies associated with aerosol-cloud-precipitation-meteorology-radiation interactions, especially owing to sharp aerosol perturbations from ship traffic and biomass burning. The data set can be used for model initialization and synergistic application with meteorological models and remote sensing data to improve understanding of the very interactions that comprise the largest uncertainty in the effect of anthropogenic emissions on radiative forcing.

A multi-year data set on aerosol-cloud-precipitation-meteorology interactions for marine stratocumulus clouds

PubMed Central

Sorooshian, Armin; MacDonald, Alexander B.; Dadashazar, Hossein; Bates, Kelvin H.; Coggon, Matthew M.; Craven, Jill S.; Crosbie, Ewan; Hersey, Scott P.; Hodas, Natasha; Lin, Jack J.; Negrón Marty, Arnaldo; Maudlin, Lindsay C.; Metcalf, Andrew R.; Murphy, Shane M.; Padró, Luz T.; Prabhakar, Gouri; Rissman, Tracey A.; Shingler, Taylor; Varutbangkul, Varuntida; Wang, Zhen; Woods, Roy K.; Chuang, Patrick Y.; Nenes, Athanasios; Jonsson, Haflidi H.; Flagan, Richard C.; Seinfeld, John H.

2018-01-01

Airborne measurements of meteorological, aerosol, and stratocumulus cloud properties have been harmonized from six field campaigns during July-August months between 2005 and 2016 off the California coast. A consistent set of core instruments was deployed on the Center for Interdisciplinary Remotely-Piloted Aircraft Studies Twin Otter for 113 flight days, amounting to 514 flight hours. A unique aspect of the compiled data set is detailed measurements of aerosol microphysical properties (size distribution, composition, bioaerosol detection, hygroscopicity, optical), cloud water composition, and different sampling inlets to distinguish between clear air aerosol, interstitial in-cloud aerosol, and droplet residual particles in cloud. Measurements and data analysis follow documented methods for quality assurance. The data set is suitable for studies associated with aerosol-cloud-precipitation-meteorology-radiation interactions, especially owing to sharp aerosol perturbations from ship traffic and biomass burning. The data set can be used for model initialization and synergistic application with meteorological models and remote sensing data to improve understanding of the very interactions that comprise the largest uncertainty in the effect of anthropogenic emissions on radiative forcing. PMID:29485627

A multi-year data set on aerosol-cloud-precipitation-meteorology interactions for marine stratocumulus clouds

NASA Astrophysics Data System (ADS)

Sorooshian, Armin; MacDonald, Alexander B.; Dadashazar, Hossein; Bates, Kelvin H.; Coggon, Matthew M.; Craven, Jill S.; Crosbie, Ewan; Hersey, Scott P.; Hodas, Natasha; Lin, Jack J.; Negrón Marty, Arnaldo; Maudlin, Lindsay C.; Metcalf, Andrew R.; Murphy, Shane M.; Padró, Luz T.; Prabhakar, Gouri; Rissman, Tracey A.; Shingler, Taylor; Varutbangkul, Varuntida; Wang, Zhen; Woods, Roy K.; Chuang, Patrick Y.; Nenes, Athanasios; Jonsson, Haflidi H.; Flagan, Richard C.; Seinfeld, John H.

2018-02-01

Airborne measurements of meteorological, aerosol, and stratocumulus cloud properties have been harmonized from six field campaigns during July-August months between 2005 and 2016 off the California coast. A consistent set of core instruments was deployed on the Center for Interdisciplinary Remotely-Piloted Aircraft Studies Twin Otter for 113 flight days, amounting to 514 flight hours. A unique aspect of the compiled data set is detailed measurements of aerosol microphysical properties (size distribution, composition, bioaerosol detection, hygroscopicity, optical), cloud water composition, and different sampling inlets to distinguish between clear air aerosol, interstitial in-cloud aerosol, and droplet residual particles in cloud. Measurements and data analysis follow documented methods for quality assurance. The data set is suitable for studies associated with aerosol-cloud-precipitation-meteorology-radiation interactions, especially owing to sharp aerosol perturbations from ship traffic and biomass burning. The data set can be used for model initialization and synergistic application with meteorological models and remote sensing data to improve understanding of the very interactions that comprise the largest uncertainty in the effect of anthropogenic emissions on radiative forcing.

Objected-oriented remote sensing image classification method based on geographic ontology model

NASA Astrophysics Data System (ADS)

Chu, Z.; Liu, Z. J.; Gu, H. Y.

2016-11-01

Nowadays, with the development of high resolution remote sensing image and the wide application of laser point cloud data, proceeding objected-oriented remote sensing classification based on the characteristic knowledge of multi-source spatial data has been an important trend on the field of remote sensing image classification, which gradually replaced the traditional method through improving algorithm to optimize image classification results. For this purpose, the paper puts forward a remote sensing image classification method that uses the he characteristic knowledge of multi-source spatial data to build the geographic ontology semantic network model, and carries out the objected-oriented classification experiment to implement urban features classification, the experiment uses protégé software which is developed by Stanford University in the United States, and intelligent image analysis software—eCognition software as the experiment platform, uses hyperspectral image and Lidar data that is obtained through flight in DaFeng City of JiangSu as the main data source, first of all, the experiment uses hyperspectral image to obtain feature knowledge of remote sensing image and related special index, the second, the experiment uses Lidar data to generate nDSM(Normalized DSM, Normalized Digital Surface Model),obtaining elevation information, the last, the experiment bases image feature knowledge, special index and elevation information to build the geographic ontology semantic network model that implement urban features classification, the experiment results show that, this method is significantly higher than the traditional classification algorithm on classification accuracy, especially it performs more evidently on the respect of building classification. The method not only considers the advantage of multi-source spatial data, for example, remote sensing image, Lidar data and so on, but also realizes multi-source spatial data knowledge integration and application of the knowledge to the field of remote sensing image classification, which provides an effective way for objected-oriented remote sensing image classification in the future.

Effects of Ocean Ecosystem on Marine Aerosol-Cloud Interaction

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

Meskhidze, Nicholas; Nenes, Athanasios

Using smore » atellite data for the surface ocean, aerosol optical depth (AOD), and cloud microphysical parameters, we show that statistically significant positive correlations exist between ocean ecosystem productivity, the abundance of submicron aerosols, and cloud microphysical properties over different parts of the remote oceans. The correlation coefficient for remotely sensed surface chlorophyll a concentration ([Chl- a ]) and liquid cloud effective radii over productive areas of the oceans varies between − 0.2 and − 0.6 . Special attention is given to identifying (and addressing) problems from correlation analysis used in the previous studies that can lead to erroneous conclusions. A new approach (using the difference between retrieved AOD and predicted sea salt aerosol optical depth, AOD diff ) is developed to explore causal links between ocean physical and biological systems and the abundance of cloud condensation nuclei (CCN) in the remote marine atmosphere. We have found that over multiple time periods, 550 nm AOD diff (sensitive to accumulation mode aerosol, which is the prime contributor to CCN) correlates well with [Chl- a ] over the productive waters of the Southern Ocean. Since [Chl- a ] can be used as a proxy of ocean biological productivity, our analysis demonstrates the role of ocean ecology in contributing CCN, thus shaping the microphysical properties of low-level marine clouds.« less

Effects of Ocean Ecosystem on Marine Aerosol-Cloud Interaction

DOE PAGES

Meskhidze, Nicholas; Nenes, Athanasios

2010-01-01

Using smore » atellite data for the surface ocean, aerosol optical depth (AOD), and cloud microphysical parameters, we show that statistically significant positive correlations exist between ocean ecosystem productivity, the abundance of submicron aerosols, and cloud microphysical properties over different parts of the remote oceans. The correlation coefficient for remotely sensed surface chlorophyll a concentration ([Chl- a ]) and liquid cloud effective radii over productive areas of the oceans varies between − 0.2 and − 0.6 . Special attention is given to identifying (and addressing) problems from correlation analysis used in the previous studies that can lead to erroneous conclusions. A new approach (using the difference between retrieved AOD and predicted sea salt aerosol optical depth, AOD diff ) is developed to explore causal links between ocean physical and biological systems and the abundance of cloud condensation nuclei (CCN) in the remote marine atmosphere. We have found that over multiple time periods, 550 nm AOD diff (sensitive to accumulation mode aerosol, which is the prime contributor to CCN) correlates well with [Chl- a ] over the productive waters of the Southern Ocean. Since [Chl- a ] can be used as a proxy of ocean biological productivity, our analysis demonstrates the role of ocean ecology in contributing CCN, thus shaping the microphysical properties of low-level marine clouds.« less

Determination of cloud fields from analysis of HIRS2/MSU sounding data. [20 channel infrared and 4 channel microwave atmospheric sounders

NASA Technical Reports Server (NTRS)

Susskind, J.; Reuter, D.

1986-01-01

IR and microwave remote sensing data collected with the HIRS2 and MSU sensors on the NOAA polar-orbiting satellites were evaluated for their effectiveness as bases for determining the cloud cover and cloud physical characteristics. Techniques employed to adjust for day-night alterations in the radiance fields are described, along with computational procedures applied to compare scene pixel values with reference values for clear skies. Sample results are provided for the mean cloud coverage detected over South America and Africa June 1979, with attention given to concurrent surface pressure and cloud top pressure values.

Foreword to the Special Issue on the 11th Specialist Meeting on Microwave Radiometry and Remote Sensing Applications (MicroRad 2010)

NASA Technical Reports Server (NTRS)

Le Vine, David M; Jackson, Thomas J.; Kim, Edward J.; Lang, Roger H.

2011-01-01

The Specialist Meeting on Microwave Radiometry and Remote Sensing of the Environment (MicroRad 2010) was held in Washington, DC from March 1 to 4, 2010. The objective of MicroRad 2010 was to provide an open forum to report and discuss recent advances in the field of microwave radiometry, particularly with application to remote sensing of the environment. The meeting was highly successful, with more than 200 registrations representing 48 countries. There were 80 oral presentations and more than 100 posters. MicroRad has become a venue for the microwave radiometry community to present new research results, instrument designs, and applications to an audience that is conversant in these issues. The meeting was divided into 16 sessions (listed in order of presentation): 1) SMOS Mission; 2) Future Passive Microwave Remote Sensing Missions; 3) Theory and Physical Principles of Electromagnetic Models; 4) Field Experiment Results; 5) Soil Moisture and Vegetation; 6) Snow and Cryosphere; 7) Passive/Active Microwave Remote Sensing Synergy; 8) Oceans; 9) Atmospheric Sounding and Assimilation; 10) Clouds and Precipitation; 11) Instruments and Advanced Techniques I; 12) Instruments and Advanced Techniques II; 13) Cross Calibration of Satellite Radiometers; 14) Calibration Theory and Methodology; 15) New Technologies for Microwave Radiometry; 16) Radio Frequency Interference.

Multitask SVM learning for remote sensing data classification

NASA Astrophysics Data System (ADS)

Leiva-Murillo, Jose M.; Gómez-Chova, Luis; Camps-Valls, Gustavo

2010-10-01

Many remote sensing data processing problems are inherently constituted by several tasks that can be solved either individually or jointly. For instance, each image in a multitemporal classification setting could be taken as an individual task but relation to previous acquisitions should be properly considered. In such problems, different modalities of the data (temporal, spatial, angular) gives rise to changes between the training and test distributions, which constitutes a difficult learning problem known as covariate shift. Multitask learning methods aim at jointly solving a set of prediction problems in an efficient way by sharing information across tasks. This paper presents a novel kernel method for multitask learning in remote sensing data classification. The proposed method alleviates the dataset shift problem by imposing cross-information in the classifiers through matrix regularization. We consider the support vector machine (SVM) as core learner and two regularization schemes are introduced: 1) the Euclidean distance of the predictors in the Hilbert space; and 2) the inclusion of relational operators between tasks. Experiments are conducted in the challenging remote sensing problems of cloud screening from multispectral MERIS images and for landmine detection.

Comparison of Balloonsonde and Remote Sensing Atmospheric Measurements

NASA Technical Reports Server (NTRS)

Brinker, David J.; Reehorst, Andrew L.; Power, Jack

2006-01-01

As part of its aircraft icing research program, the NASA Glenn Research Center is conducting a program to develop technologies for the remote sensing of atmospheric conditions. A suite of instruments, currently ground-based, are used to identify a region of supercooled liquid water which is labeled as hazardous if its liquid water content is sufficiently high. During the recently completed Alliance Icing Research Study (AIRS II), these instruments were deployed in conjunction with those of other U.S. and Canadian researchers at the Mirabel Airport near Montreal. As part of the study, balloonsondes were employed to provide in-situ measurement of the atmospheric conditions that were being concurrently remotely sensed. Balloonsonde launches occurred daily at 1200 GMT to provide AIRS forecasters with local data and additionally when research aircraft were present in the airspace. In this paper, we compare the processed data from the NASA remote sensing instruments, which included an X-band radar, lidar and two radiometers, to the data gathered from the 70 soundings conducted while the NASA instruments were active. Among the parameters compared are cloud upper and lower boundaries, temperature and humidity profiles and freezing levels.

Advances in U.S. Land Imaging Capabilities

NASA Astrophysics Data System (ADS)

Stryker, T. S.

2017-12-01

Advancements in Earth observations, cloud computing, and data science are improving everyday life. Information from land-imaging satellites, such as the U.S. Landsat system, helps us to better understand the changing landscapes where we live, work, and play. This understanding builds capacity for improved decision-making about our lands, waters, and resources, driving economic growth, protecting lives and property, and safeguarding the environment. The USGS is fostering the use of land remote sensing technology to meet local, national, and global challenges. A key dimension to meeting these challenges is the full, free, and open provision of land remote sensing observations for both public and private sector applications. To achieve maximum impact, these data must also be easily discoverable, accessible, and usable. The presenter will describe the USGS Land Remote Sensing Program's current capabilities and future plans to collect and deliver land remote sensing information for societal benefit. He will discuss these capabilities in the context of national plans and policies, domestic partnerships, and international collaboration. The presenter will conclude with examples of how Landsat data is being used on a daily basis to improve lives and livelihoods.

Remote Sensing of Smoke, Land and Clouds from the NASA ER-2 during SAFARI 2000

NASA Technical Reports Server (NTRS)

King, Michael D.; Platnick, Steven; Moeller, Christopher C.; Revercomb, Henry E.; Chu, D. Allen

2002-01-01

The NASA ER-2 aircraft was deployed to southern Africa between August 17 and September 25, 2000 as part of the Southern Africa Regional Science Initiative (SAFARI) 2000. This aircraft carried a sophisticated array of multispectral scanners, multiangle spectroradiometers, a monostatic lidar, a gas correlation radiometer, upward and downward spectral flux radiometers, and two metric mapping cameras. These observations were obtained over a 3200 x 2800 km region of savanna, woody savanna, open shrubland, and grassland ecosystems throughout southern Africa, and were quite often coordinated with overflights by NASA's Terra and Landsat 7 satellites. The primary purpose of this sophisticated high altitude observing platform was to obtain independent observations of smoke, clouds, and land surfaces that could be used to check the validity of various remote sensing measurements derived by Earth-orbiting satellites. These include such things as the accuracy of the Moderate Resolution Imaging Spectro-radiometer (MODIS) cloud mask for distinguishing clouds and heavy aerosol from land and ocean surfaces, and Terra analyses of cloud optical and micro-physical properties, aerosol properties, leaf area index, vegetation index, fire occurrence, carbon monoxide, and surface radiation budget. In addition to coordination with Terra and Landsat 7 satellites, numerous flights were conducted over surface AERONET sites, flux towers in South Africa, Botswana, and Zambia, and in situ aircraft from the University of Washington, South Africa, and the United Kingdom.

Predicting decadal trends in cloud droplet number concentration using reanalysis and satellite data

NASA Astrophysics Data System (ADS)

McCoy, Daniel T.; Bender, Frida A.-M.; Grosvenor, Daniel P.; Mohrmann, Johannes K.; Hartmann, Dennis L.; Wood, Robert; Field, Paul R.

2018-02-01

Cloud droplet number concentration (CDNC) is the key state variable that moderates the relationship between aerosol and the radiative forcing arising from aerosol-cloud interactions. Uncertainty related to the effect of anthropogenic aerosol on cloud properties represents the largest uncertainty in total anthropogenic radiative forcing. Here we show that regionally averaged time series of the Moderate-Resolution Imaging Spectroradiometer (MODIS) observed CDNC of low, liquid-topped clouds is well predicted by the MERRA2 reanalysis near-surface sulfate mass concentration over decadal timescales. A multiple linear regression between MERRA2 reanalyses masses of sulfate (SO4), black carbon (BC), organic carbon (OC), sea salt (SS), and dust (DU) shows that CDNC across many different regimes can be reproduced by a simple power-law fit to near-surface SO4, with smaller contributions from BC, OC, SS, and DU. This confirms previous work using a less sophisticated retrieval of CDNC on monthly timescales. The analysis is supported by an examination of remotely sensed sulfur dioxide (SO2) over maritime volcanoes and the east coasts of North America and Asia, revealing that maritime CDNC responds to changes in SO2 as observed by the ozone monitoring instrument (OMI). This investigation of aerosol reanalysis and top-down remote-sensing observations reveals that emission controls in Asia and North America have decreased CDNC in their maritime outflow on a decadal timescale.

Remote sensing of cloud radiation and microphysical parameters

NASA Technical Reports Server (NTRS)

Wu, M.-L. C.; Curran, R. J.

1983-01-01

Multispectral cloud radiometer (MCR) data, retrieved from a radiometer installed in a nadir viewing position on a high-altitude aircraft flying at 200 m/s and at an altitude of 60,000 ft above the mean sea level, are analyzed. The data discussed were obtained in the 0.754, 0.7609, 0.7634, 1.626, 2.125, and 11.38-micron channels, and are compared to lidar-derived profiles. Among the cloud parameters under consideration are the cloud scaled optical thickness, cloudtop altitude, scaled volume scattering coefficient, particle thermodynamic phase, mean particle size, and cloudtop temperature.

Remote Sensing of Cloud, Aerosol, and Land Properties from MODIS: Applications to the East Asia Region

NASA Technical Reports Server (NTRS)

King, Michael D.; Platnick, Steven; Moody, Eric G.

2002-01-01

MODIS is an earth-viewing cross-track scanning spectroradiometer launched on the Terra satellite in December 1999 and the Aqua satellite in May 2002. MODIS scans a swath width sufficient to provide nearly complete global coverage every two days from a polar-orbiting, sun-synchronous, platform at an altitude of 705 km, and provides images in 36 spectral bands between 0.415 and 14.235 microns with spatial resolutions of 250 m (2 bands), 500 m (5 bands) and 1000 m (29 bands). These bands have been carefully selected to enable advanced studies of land, ocean, and atmospheric processes. In this paper we will describe the various methods being used for the remote sensing of cloud, aerosol, and surface properties using MODIS data, focusing primarily on (i) the MODIS cloud mask used to distinguish clouds, clear sky, heavy aerosol, and shadows on the ground, (ii) cloud optical properties, especially cloud optical thickness and effective radius of water drops and ice crystals, (iii) aerosol optical thickness and size characteristics both over land and ocean, and (iv) ecosystem classification and surface spectral reflectance. The physical principles behind the determination of each of these products will be described, together with an example of their application using MODIS observations to the east Asian region. All products are archived into two categories: pixel-level retrievals (referred to as Level-2 products) and global gridded products at a latitude and longitude resolution of 1 min (Level-3 products).

Polar Ozone Workshop. Abstracts

NASA Technical Reports Server (NTRS)

Aikin, Arthur C.

1988-01-01

Results of the proceedings of the Polar Ozone Workshop held in Snowmass, CO, on May 9 to 13, 1988 are given. Topics covered include ozone depletion, ozonometry, polar meteorology, polar stratospheric clouds, remote sensing of trace gases, atmospheric chemistry and dynamical simulations.

NASA/MSFC FY90 Global Scale Atmospheric Processes Research Program Review

NASA Technical Reports Server (NTRS)

Leslie, Fred W. (Editor)

1990-01-01

Research supported by the Global Atmospheric Research Program at the Marshall Space Flight Center on atmospheric remote sensing, meteorology, numerical weather forecasting, satellite data analysis, cloud precipitation, atmospheric circulation, atmospheric models and related topics is discussed.

Optimizing a remote sensing instrument to measure atmospheric surface pressure

NASA Technical Reports Server (NTRS)

Peckham, G. E.; Gatley, C.; Flower, D. A.

1983-01-01

Atmospheric surface pressure can be remotely sensed from a satellite by an active instrument which measures return echoes from the ocean at frequencies near the 60 GHz oxygen absorption band. The instrument is optimized by selecting its frequencies of operation, transmitter powers and antenna size through a new procedure baesd on numerical simulation which maximizes the retrieval accuracy. The predicted standard deviation error in the retrieved surface pressure is 1 mb. In addition the measurements can be used to retrieve water vapor, cloud liquid water and sea state, which is related to wind speed.

Supporting Remote Sensing Research with Small Unmanned Aerial Systems

NASA Astrophysics Data System (ADS)

Anderson, R. C.; Shanks, P. C.; Kritis, L. A.; Trani, M. G.

2014-11-01

We describe several remote sensing research projects supported with small Unmanned Aerial Systems (sUAS) operated by the NGA Basic and Applied Research Office. These sUAS collections provide data supporting Small Business Innovative Research (SBIR), NGA University Research Initiative (NURI), and Cooperative Research And Development Agreements (CRADA) efforts in addition to inhouse research. Some preliminary results related to 3D electro-optical point clouds are presented, and some research goals discussed. Additional details related to the autonomous operational mode of both our multi-rotor and fixed wing small Unmanned Aerial System (sUAS) platforms are presented.

Macroscopic impacts of cloud and precipitation processes on maritime shallow convection as simulated by a large eddy simulation model with bin microphysics

DOE PAGES

Grabowski, W. W.; Wang, L. -P.; Prabha, T. V.

2015-01-27

This paper discusses impacts of cloud and precipitation processes on macrophysical properties of shallow convective clouds as simulated by a large eddy model applying warm-rain bin microphysics. Simulations with and without collision–coalescence are considered with cloud condensation nuclei (CCN) concentrations of 30, 60, 120, and 240 mg -1. Simulations with collision–coalescence include either the standard gravitational collision kernel or a novel kernel that includes enhancements due to the small-scale cloud turbulence. Simulations with droplet collisions were discussed in Wyszogrodzki et al. (2013) focusing on the impact of the turbulent collision kernel. The current paper expands that analysis and puts modelmore » results in the context of previous studies. Despite a significant increase of the drizzle/rain with the decrease of CCN concentration, enhanced by the effects of the small-scale turbulence, impacts on the macroscopic cloud field characteristics are relatively minor. Model results show a systematic shift in the cloud-top height distributions, with an increasing contribution of deeper clouds for stronger precipitating cases. We show that this is consistent with the explanation suggested in Wyszogrodzki et al. (2013); namely, the increase of drizzle/rain leads to a more efficient condensate offloading in the upper parts of the cloud field. A second effect involves suppression of the cloud droplet evaporation near cloud edges in low-CCN simulations, as documented in previous studies (e.g., Xue and Feingold, 2006). We pose the question whether the effects of cloud turbulence on drizzle/rain formation in shallow cumuli can be corroborated by remote sensing observations, for instance, from space. Although a clear signal is extracted from model results, we argue that the answer is negative due to uncertainties caused by the temporal variability of the shallow convective cloud field, sampling and spatial resolution of the satellite data, and overall accuracy of remote sensing retrievals.« less

Spaceborne Microwave Imagers

NASA Technical Reports Server (NTRS)

Stacey, J. M.

1991-01-01

Monograph presents comprehensive overview of science and technology of spaceborne microwave-imaging systems. Microwave images used as versatile orbiting, remote-sensing systems to investigate atmospheres and surfaces of planets. Detect surface objects through canopies of clouds, measure distributions of raindrops in clouds that their views penetrate, find meandering rivers in rain forests and underground water in arid regions, and provide information on ocean currents, wakes, ice/water boundaries, aircraft, ships, buoys, and bridges.

Observations of marine stratocumulus clouds during FIRE

NASA Technical Reports Server (NTRS)

Albrecht, Bruce A.; Randall, David A.; Nicholls, Stephen

1988-01-01

The First International Satellite Cloud Climatology Project Regional Experiment (FIRE) to study extensive fields of stratocumulus clouds off the coast of California is presented. Measurements on the regional and detailed local scales were taken, allowing for a wide interpretation of the mean, turbulent, microphysical, radiative, and chemical characteristics of stratocumulus. Multiple aircraft and ground-based remote-sensing systems were used to study the time evolution of the boundary layer structure over a three-week period, and probes from tethered balloons were used to measure turbulence and to collect cloud-microphysical and cloud-radiative data. The observations provide a base for studying the generation maintenance and dissipation of stratocumulus clouds, and could aid in developing numerical models and improved methods for retrieving cloud properties by satellite.

a 33GHZ and 95GHZ Cloud Profiling Radar System (cprs): Preliminary Estimates of Particle Size in Precipitation and Clouds.

NASA Astrophysics Data System (ADS)

Sekelsky, Stephen Michael

1995-11-01

The Microwave Remote Sensing Laboratory (MIRSL) st the University of Massachusetts has developed a unique single antenna, dual-frequency polarimetric Cloud Profiling Radar System (CPRS). This project was funded by the Department of Energy's Atmospheric Radiation Measurement (ARM) program, and was intended to help fill the void of ground-based remote sensors capable of characterizing cloud microphysical properties. CPRS is unique in that it can simultaneously measure the complex power backscattered from clouds at 33 GHz and 95 GHz through the same aperture. Both the 33 GHz and 95 GHz channels can transmit pulse-to-pulse selectable vertical or horizontal polarization, and simultaneously record both the copolarized and crosspolarized backscatter. CPRS Doppler, polarimetric and dual-wavelength reflectivity measurements combined with in situ cloud measurements should lead to the development of empirical models that can more accurately classify cloud-particle phase and habit, and make better quantitative estimates of particle size distribution parameters. This dissertation describes the CPRS hardware, and presents colocated 33 GHz and 95 GHz measurements that illustrate the use of dual-frequency measurements to estimate particle size when Mie scattering, is observed in backscatter from rain and ice-phase clouds. Polarimetric measurements are presented as a means of discriminating cloud phase (ice-water) and estimating crystal shape in cirrus clouds. Polarimetric and dual-wavelength observations of insects are also presented with a brief discussion of their impact on the interpretation of precipitation and liquid cloud measurements. In precipitation, Diermendjian's equations for Mie backscatter (1) and the Marshal-Palmer drop-size distribution are used to develop models relating differences in the reflectivity and mean velocity at 33 GHz and 95 GHz to the microphysical parameters of rain. These models are then used to estimate mean droplet size from CPRS measurements of drizzle, which were collected in July, 1993 during the system's first field test in Lincoln, NE. The dissertation also presents cirrus cloud and other measurements collected during the DOE-sponsored Remote Cloud Sensing Intensive Operations Period (RCS-IOP) experiment in April, 1994. Zenith-pointing cirrus measurements show small differences in 33 GHz and 95 GHz reflectivity, as models have predicted (2). Depolarization was also detected in a few cases when ice crystals precipitated from the base of a cloud. On May 29, 1994 CPRS observed a convective storm that produced a cirrus anvil cloud and hail. These storms are one 'engine' producing cirrus clouds and are currently a topic of intensive research by climatologists. Both zenith-pointing and range-height data formats are presented. Measurements of depolarization above the melting/layer are compared to in situ observations of particle size and shape. The RCS-IOP experiment also provided a first opportunity to verify our calibration with aircraft in situ measurements, and to compare our cloud measurements to those collected by other remote sensors. (Abstract shortened by UMI.).

Photogrammetric retrieval of volcanic ash cloud top height from SEVIRI and MODIS

NASA Astrophysics Data System (ADS)

Zakšek, Klemen; Hort, Matthias; Zaletelj, Janez; Langmann, Bärbel

2013-04-01

Even if erupting in remote areas, volcanoes can have a significant impact on the modern society due to volcanic ash dispersion in the atmosphere. The ash does not affect merely air traffic - its transport in the atmosphere and its deposition on land and in the oceans may also significantly influence the climate through modifications of atmospheric CO2. The emphasis of this contribution is the retrieval of volcanic ash plume height (ACTH). ACTH is important information especially for air traffic but also to predict ash transport and to estimate the mass flux of the ejected material. ACTH is usually estimated from ground measurements, pilot reports, or satellite remote sensing. But ground based instruments are often not available at remote volcanoes and also the pilots reports are a matter of chance. Volcanic ash cloud top height (ACTH) can be monitored on the global level using satellite remote sensing. The most often used method compares brightness temperature of the cloud with the atmospheric temperature profile. Because of uncertainties of this method (unknown emissivity of the ash cloud, tropopause, etc.) we propose photogrammetric methods based on the parallax between data retrieved from geostationary (SEVIRI) and polar orbiting satellites (MODIS). The parallax is estimated using automatic image matching in three level image pyramids. The procedure works well if the data from both satellites are retrieved nearly simultaneously. MODIS does not retrieve the data at exactly the same time as SEVIRI. To compensate for advection 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. ACTH is then estimated by intersection of corresponding lines-of-view from MODIS and interpolated SEVIRI data. The proposed method was tested using MODIS band 1 and SEVIRI HRV band for the case of the Eyjafjallajökull eruption in April 2010. The parallax between MODIS and SEVIRI data can reach over 30 km which implies ACTH of more than 12 km. The accuracy of ACTH was estimated to 0.6 km. The limitation of this procedure is that it has difficulties with automatic image matching if the ash cloud is not opaque.

Characterization of Arctic ice cloud properties observed during ISDAC

NASA Astrophysics Data System (ADS)

Jouan, Caroline; Girard, Eric; Pelon, Jacques; Gultepe, Ismail; Delanoë, Julien; Blanchet, Jean-Pierre

2012-12-01

Extensive measurements from ground-based sites and satellite remote sensing (CloudSat and CALIPSO) reveal the existence of two types of ice clouds (TICs) in the Arctic during the polar night and early spring. The first type (TIC-2A), being topped by a cover of nonprecipitating very small (radar unseen) ice crystals (TIC-1), is found more frequently in pristine environment, whereas the second type (TIC-2B), detected by both sensors, is associated preferentially with a high concentration of aerosols. To further investigate the microphysical properties of TIC-1/2A and TIC-2B, airborne in situ and satellite measurements of specific cases observed during Indirect and Semi-Direct Aerosol Campaign (ISDAC) have been analyzed. For the first time, Arctic TIC-1/2A and TIC-2B microstructures are compared using in situ cloud observations. Results show that the differences between them are confined in the upper part of the clouds where ice nucleation occurs. TIC-2B clouds are characterized by fewer (by more than 1 order of magnitude) and larger (by a factor of 2 to 3) ice crystals and a larger ice supersaturation (of 15-20%) compared to TIC-1/2A. Ice crystal growth in TIC-2B clouds seems explosive, whereas it seems more gradual in TIC-1/2A. It is hypothesized that these differences are linked to the number concentration and the chemical composition of aerosols. The ice crystal growth rate in very cold conditions impinges on the precipitation efficiency, dehydration and radiation balance. These results represent an essential and important first step to relate previous modeling, remote sensing and laboratory studies with TICs cloud in situ observations.

Sensitivity of simulated snow cloud properties to mass-diameter parameterizations.

NASA Astrophysics Data System (ADS)

Duffy, G.; Nesbitt, S. W.; McFarquhar, G. M.

2015-12-01

Mass to diameter (m-D) relationships are used in model parameterization schemes to represent ice cloud microphysics and in retrievals of bulk cloud properties from remote sensing instruments. One of the most common relationships, used in the current Global Precipitation Measurement retrieval algorithm for example, assigns the density of snow as a constant tenth of the density of ice (0.1g/m^3). This assumption stands in contrast to the results of derived m-D relationships of snow particles, which imply decreasing particle densities at larger sizes and result in particle masses orders of magnitude below the constant density relationship. In this study, forward simulations of bulk cloud properties (e.g., total water content, radar reflectivity and precipitation rate) derived from measured size distributions using several historical m-D relationships are presented. This expands upon previous studies that mainly focused on smaller ice particles because of the examination of precipitation-sized particles here. In situ and remote sensing data from the GPM Cold season Experiment (GCPEx) and Canadian CloudSAT/Calypso Validation Program (C3VP), both synoptic snowstorm field experiments in southern Ontario, Canada, are used to evaluate the forward simulations against total water content measured by the Nevzorov and Cloud Spectrometer and Impactor (CSI) probe, radar reflectivity measured by a C band ground based radar and a nadir pointing Ku/Ka dual frequency airborne radar, and precipitation rate measured by a 2D video disdrometer. There are differences between the bulk cloud properties derived using varying m-D relations, with constant density assumptions producing results differing substantially from the bulk measured quantities. The variability in bulk cloud properties derived using different m-D relations is compared against the natural variability in those parameters seen in the GCPEx and C3VP field experiments.

Understanding the Microphysical Properties of Developing Cloud Clusters During TCS-08

DTIC Science & Technology

2012-09-30

sensed satellite data In addition to the lightning data , geostationary infrared brightness temperatures and MODIS data have been used to analyze...detailed investigation of genesis using remote-sensed observations from platforms that are maintained on a more permanent basis including satellite -based...searching existing data sources, gathering and maintaining the data needed, and completing and reviewing the collection of information. Send comments

A technique for determining cloud free versus cloud contaminated pixels in satellite imagery

NASA Technical Reports Server (NTRS)

Wohlman, Richard A.

1994-01-01

Weather forecasting has been called the second oldest profession. To do so accurately and with some consistency requires an ability to understand the processes which create the clouds, drive the winds, and produce the ever changing atmospheric conditions. Measurement of basic parameters such as temperature, water vapor content, pressure, windspeed and wind direction throughout the three dimensional atmosphere form the foundation upon which a modern forecast is created. Doppler radar, and space borne remote sensing have provided forecasters the new tools with which to ply their trade.

Deriving temporally continuous soil moisture estimations at fine resolution by downscaling remotely sensed product

NASA Astrophysics Data System (ADS)

Jin, Yan; Ge, Yong; Wang, Jianghao; Heuvelink, Gerard B. M.

2018-06-01

Land surface soil moisture (SSM) has important roles in the energy balance of the land surface and in the water cycle. Downscaling of coarse-resolution SSM remote sensing products is an efficient way for producing fine-resolution data. However, the downscaling methods used most widely require full-coverage visible/infrared satellite data as ancillary information. These methods are restricted to cloud-free days, making them unsuitable for continuous monitoring. The purpose of this study is to overcome this limitation to obtain temporally continuous fine-resolution SSM estimations. The local spatial heterogeneities of SSM and multiscale ancillary variables were considered in the downscaling process both to solve the problem of the strong variability of SSM and to benefit from the fusion of ancillary information. The generation of continuous downscaled remote sensing data was achieved via two principal steps. For cloud-free days, a stepwise hybrid geostatistical downscaling approach, based on geographically weighted area-to-area regression kriging (GWATARK), was employed by combining multiscale ancillary variables with passive microwave remote sensing data. Then, the GWATARK-estimated SSM and China Soil Moisture Dataset from Microwave Data Assimilation SSM data were combined to estimate fine-resolution data for cloudy days. The developed methodology was validated by application to the 25-km resolution daily AMSR-E SSM product to produce continuous SSM estimations at 1-km resolution over the Tibetan Plateau. In comparison with ground-based observations, the downscaled estimations showed correlation (R ≥ 0.7) for both ascending and descending overpasses. The analysis indicated the high potential of the proposed approach for producing a temporally continuous SSM product at fine spatial resolution.

Strategic positioning of the ERATOSTHENES Research Centre for atmospheric remote sensing research in the Eastern Mediterranean and Middle East region

NASA Astrophysics Data System (ADS)

Mamouri, Rodanthi-Elisavet; Ansmann, Albert; Hadjimitsis, Diofantos G.; Nisantzi, Argyro; Bühl, Johannes; Michaelides, Silas; Seifert, Patric; Engelmann, Ronny; Wandinger, Ulla; Kontoes, Charalampos; Schreier, Gunter; Komodromos, Georgios; Themistocleous, Kyriacos

2017-10-01

The aim of this article is to present the importance of a permanent state-of-the-art atmospheric remote sensing ground based station in the region of the Eastern Mediterranean and Middle East (EMME). The ERATOSTHENES Research Centre (ERC) with the vision to become a Centre of Excellence for Earth Surveillance and Space-Based Monitoring of the Environment (EXCELSIOR H2020: Teaming project) already operates (within Phase 1) a fully established EARLINETt-Cloudnet supersite at Limassol, Cyprus, for a period of 2 years, in close collaboration with the German Leibniz Institute for Tropospheric Research (TROPOS), The scientific aspects of this prototype-like field campaign CyCARE (Cyprus Cloud Aerosol and Rain Experiment) - a common initiative between the Cyprus University of Technology (CUT), Limassol and TROPOS- are presented in this paper. Cy-CARE has been designed by TROPOS and CUT to fill a gap in the understanding of aerosol-cloud interaction in one of the key regions of climate change and how precipitation formation is influenced by varying aerosol/pollution and meteorological conditions The guiding questions are: How may rain patterns change in future and what may be the consequences of climate change in arid regions such as EMME. EXCELSIOR is a team effort between CUT (acting as the coordinator), the German Aerospace Centre (DLR), the Institute for Astronomy and Astrophysics Space Applications and Remote Sensing of the National Observatory of Athens (NOA), TROPOS and the Cyprus Department of Electronic Communications of the Ministry of Transport, Communications and Works (DEC-MTCW) who will work together to improve the network structures significantly, resulting in Cyprus being regarded as a cornerstone of a European Network of active remote sensing of the atmosphere.

3D Cloud Tomography, Followed by Mean Optical and Microphysical Properties, with Multi-Angle/Multi-Pixel Data

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.

TERSSE: Definition of the Total Earth Resources System for the Shuttle Era. Volume 3: Mission and System Requirements for the Total Earth Resources System

NASA Technical Reports Server (NTRS)

1974-01-01

Resource management missions to be performed by TERSSE are described. Mission and user requirements are defined along with information flows developed for each major resource management mission. Other topics discussed include: remote sensing platforms, remote sensor requirements, ground system architecture, and such related issues as cloud cover, resolution, orbit mechanics, and aircraft versus satellite.

Midlatitude Cirrus Clouds Derived from Hurricane Nora: A Case Study with Implications for Ice Crystal Nucleation and Shape.

NASA Astrophysics Data System (ADS)

Sassen, Kenneth; Arnott, W. Patrick; O'C. Starr, David; Mace, Gerald G.; Wang, Zhien; Poellot, Michael R.

2003-04-01

Hurricane Nora traveled up the Baja Peninsula coast in the unusually warm El Niño waters of September 1997 until rapidly decaying as it approached southern California on 24 September. The anvil cirrus blowoff from the final surge of tropical convection became embedded in subtropical flow that advected the cirrus across the western United States, where it was studied from the Facility for Atmospheric Remote Sensing (FARS) in Salt Lake City, Utah, on 25 September. A day later, the cirrus shield remnants were redirected southward by midlatitude circulations into the southern Great Plains, providing a case study opportunity for the research aircraft and ground-based remote sensors assembled at the Clouds and Radiation Testbed (CART) site in northern Oklahoma. Using these comprehensive resources and new remote sensing cloud retrieval algorithms, the microphysical and radiative cloud properties of this unusual cirrus event are uniquely characterized.Importantly, at both the FARS and CART sites the cirrus generated spectacular halos and arcs, which acted as a tracer for the hurricane cirrus, despite the limited lifetimes of individual ice crystals. Lidar depolarization data indicate widespread regions of uniform ice plate orientations, and in situ particle replicator data show a preponderance of pristine, solid hexagonal plates and columns. It is suggested that these unusual aspects are the result of the mode of cirrus particle nucleation, presumably involving the lofting of sea salt nuclei in strong thunderstorm updrafts into the upper troposphere. This created a reservoir of haze particles that continued to produce halide-salt-contaminated ice crystals during the extended period of cirrus cloud maintenance. The inference that marine microbiota are embedded in the replicas of some ice crystals collected over the CART site points to the longevity of marine effects. Various nucleation scenarios proposed for cirrus clouds based on this and other studies, and the implications for understanding cirrus radiative properties on a global scale, are discussed.

Midlatitude Cirrus Clouds Derived from Hurricane Nora: A Case Study with Implications for Ice Crystal Nucleation and Shape

NASA Technical Reports Server (NTRS)

Sassen, Kenneth; Arnott, W. Patrick; OCStarr, David; Mace, Gerald G.; Wang, Zhien; Poellot, Michael R.

2002-01-01

Hurricane Nora traveled up the Bala Peninsula coast in the unusually warm El Nino waters of September 1997, until rapidly decaying as it approached Southern California on 24 September. The anvil cirrus blowoff from the final surge of tropical convection became embedded in subtropical flow that advected the cirrus across the western US, where it was studied from the Facility for Atmospheric Remote Sensing (FARS) in Salt Lake City, Utah. A day later, the cirrus shield remnants were redirected southward by midlatitude circulations into the Southern Great Plains, providing a case study opportunity for the research aircraft and ground-based remote sensors assembled at the Clouds and Radiation Testbed (CART) site in northern Oklahoma. Using these comprehensive resources and new remote sensing cloud retrieval algorithms, the microphysical and radiative cloud properties of this unusual cirrus event are uniquely characterized. Importantly, at both the FARS and CART sites the cirrus generated spectacular optical displays, which acted as a tracer for the hurricane cirrus, despite the limited lifetimes of individual ice crystals. Lidar polarization data indicate widespread regions of uniform ice plate orientations, and in situ particle masticator data show a preponderance of pristine, solid hexagonal plates and columns. It is suggested that these unusual aspects are the result of the mode of cirrus particle nucleation, presumably involving the lofting of sea-salt nuclei in thunderstorm updrafts into the upper troposphere. This created a reservoir of haze particles that continued to produce halide-saltcontaminated ice crystals during the extended period of cirrus cloud maintenance. The reference that marine microliters are embedded in the replicas of ice crystals collected over the CART site points to the longevity of marine effects. Various nucleation scenarios proposed for cirrus clouds based on this and other studies, and the implications for understanding cirrus radiative properties or a global scale, are discussed.

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.

Satellite view of the extreme haze clouds over China

NASA Astrophysics Data System (ADS)

Minghui, T.; Chen, L.; Wang, Z.

2013-12-01

Minghui Tao*, Liangfu Chen, Zifeng Wang State Key Laboratory of Remote Sensing Science, Jointly Sponsored by Institute of Remote Sensing and Digital Earth of Chinese Academy of Sciences and Beijing Normal University, Beijing 100101, China *Email: tmh1985@163.com ABSTRACT: In the past decades, great increases in anthropogenic emissions have caused dramatic changes in air quality and regional climate in China, which are further complicated by the natural processes such as dust events and atmospheric dynamics such as variations in intensity of the Asian monsoon. The common urban photochemistry smog, haze, and fog-haze pollution lead to poor air quality in major cities in eastern and middle parts of China. On the other hand, the heavy aerosol loading exerts marked influences on radiation, clouds, and precipitation over China. Satellites usually observed widespread haze clouds over eastern China. In most of previous studies, the dense haze clouds were directly connected with accumulation of anthropogenic emissions. However, satellite observations show that formation processes of haze clouds and local pollution near surface were different. Understanding the connections and interactions between haze clouds and local anthropogenic emissions is essential in chemistry and climate modeling of the aerosols over China. In January 2013, durative haze clouds covered most parts of eastern China, leading to extreme pollution events in many cities. With integrated A-train satellite observations and ground measurements, we investigated variations, optical properties, vertical structures as well as formation process of the extreme haze clouds over eastern China. Satellite-surface results were compared to analyze relations between the haze clouds and surface pollution. Different from traditional views, our results reveal that variation and formation of the haze clouds were driven by large-scale natural processes rather than local anthropogenic emissions. Figure 1. Aqua MODIS true color images of the haze clouds over eastern China on Jan 10, 2013.

Developing Remote Sensing Capabilities for Meter-Scale Sea Ice Properties

DTIC Science & Technology

2013-09-30

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

Assessment of the Accuracy of the Conventional Ray-Tracing Technique: Implications in Remote Sensing and Radiative Transfer Involving Ice Clouds.

NASA Technical Reports Server (NTRS)

Bi, Lei; Yang, Ping; Liu, Chao; Yi, Bingqi; Baum, Bryan A.; Van Diedenhoven, Bastiaan; Iwabuchi, Hironobu

2014-01-01

A fundamental problem in remote sensing and radiative transfer simulations involving ice clouds is the ability to compute accurate optical properties for individual ice particles. While relatively simple and intuitively appealing, the conventional geometric-optics method (CGOM) is used frequently for the solution of light scattering by ice crystals. Due to the approximations in the ray-tracing technique, the CGOM accuracy is not well quantified. The result is that the uncertainties are introduced that can impact many applications. Improvements in the Invariant Imbedding T-matrix method (II-TM) and the Improved Geometric-Optics Method (IGOM) provide a mechanism to assess the aforementioned uncertainties. The results computed by the II-TMþIGOM are considered as a benchmark because the IITM solves Maxwell's equations from first principles and is applicable to particle size parameters ranging into the domain at which the IGOM has reasonable accuracy. To assess the uncertainties with the CGOM in remote sensing and radiative transfer simulations, two independent optical property datasets of hexagonal columns are developed for sensitivity studies by using the CGOM and the II-TMþIGOM, respectively. Ice cloud bulk optical properties obtained from the two datasets are compared and subsequently applied to retrieve the optical thickness and effective diameter from Moderate Resolution Imaging Spectroradiometer (MODIS) measurements. Additionally, the bulk optical properties are tested in broadband radiative transfer (RT) simulations using the general circulation model (GCM) version of the Rapid Radiative Transfer Model (RRTMG) that is adopted in the National Center for Atmospheric Research (NCAR) Community Atmosphere Model (CAM, version 5.1). For MODIS retrievals, the mean bias of uncertainties of applying the CGOM in shortwave bands (0.86 and 2.13 micrometers) can be up to 5% in the optical thickness and as high as 20% in the effective diameter, depending on cloud optical thickness and effective diameter. In the MODIS infrared window bands centered at 8.5, 11, and 12 micrometers biases in the optical thickness and effective diameter are up to 12% and 10%, respectively. The CGOM-based simulation errors in ice cloud radiative forcing calculations are on the order of 10Wm(exp 2).

[Atmospheric Influences Analysis on the Satellite Passive Microwave Remote Sensing].

PubMed

Qiu, Yu-bao; Shi, Li-juan; Shi, Jian-cheng; Zhao, Shao-jie

2016-02-01

Passive microwave remote sensing offers its all-weather work capabilities, but atmospheric influences on satellite microwave brightness temperature were different under different atmospheric conditions and environments. In order to clarify atmospheric influences on Advanced Microwave Scanning Radiometer-Earth Observing System (AMSR-E), atmospheric radiation were simulated based on AMSR-E configuration under clear sky and cloudy conditions, by using radiative transfer model and atmospheric conditions data. Results showed that atmospheric water vapor was the major factor for atmospheric radiation under clear sky condition. Atmospheric transmittances were almost above 0.98 at AMSR-E's low frequencies (< 18.7 GHz) and the microwave brightness temperature changes caused by atmosphere can be ignored in clear sky condition. Atmospheric transmittances at 36.5 and 89 GHz were 0.896 and 0.756 respectively. The effects of atmospheric water vapor needed to be corrected when using microwave high-frequency channels to inverse land surface parameters in clear sky condition. But under cloud cover or cloudy conditions, cloud liquid water was the key factor to cause atmospheric radiation. When sky was covered by typical stratus cloud, atmospheric transmittances at 10.7, 18.7 and 36.5 GHz were 0.942, 0.828 and 0.605 respectively. Comparing with the clear sky condition, the down-welling atmospheric radiation caused by cloud liquid water increased up to 75.365 K at 36.5 GHz. It showed that the atmospheric correction under different clouds covered condition was the primary work to improve the accuracy of land surface parameters inversion of passive microwave remote sensing. The results also provided the basis for microwave atmospheric correction algorithm development. Finally, the atmospheric sounding data was utilized to calculate the atmospheric transmittance of Hailaer Region, Inner Mongolia province, in July 2013. The results indicated that atmospheric transmittances were close to 1 at C-band and X-band. 89 GHz was greatly influenced by water vapor and its atmospheric transmittance was not more than 0.7. Atmospheric transmittances in Hailaer Region had a relatively stable value in summer, but had about 0.1 fluctuations with the local water vapor changes.

Ground-based SMART-COMMIT Measurements for Studying Aerosol and Cloud Properties

NASA Technical Reports Server (NTRS)

Tsay, Si-Chee

2008-01-01

From radiometric principles, it is expected that the retrieved properties of extensive aerosols and clouds from reflected/emitted measurements by satellite (and/or aircraft) should be consistent with those retrieved from transmitted/emitted radiance observed at the surface. Although space-borne remote sensing observations cover large spatial domain, they are often plagued by contamination of surface signatures. Thus, ground-based in-situ and remote-sensing measurements, where signals come directly from atmospheric constituents, the sun, and/or the Earth-atmosphere interactions, provide additional information content for comparisons that confirm quantitatively the usefulness of the integrated surface, aircraft, and satellite data sets. The development and deployment of SMARTCOMMIT (Surface-sensing Measurements for Atmospheric Radiative Transfer - Chemical, Optical & Microphysical Measurements of In-situ Troposphere) mobile facilities are aimed for the optimal utilization of collocated ground-based observations as constraints to yield higher fidelity satellite retrievals and to determine any sampling bias due to target conditions. To quantify the energetics of the surface-atmosphere system and the atmospheric processes, SMART-COMMIT instruments fall into three categories: flux radiometer, radiance sensor and in-situ probe. In this paper, we will demonstrate the capability of SMART-COMMIT in recent field campaigns (e.g., CRYSTAL-FACE, UAE 2, BASEASIA, NAMMA) that were designed and executed to study the compelling variability in temporal scale of both anthropogenic and natural aerosols (e.g., biomass-burning smoke, airborne dust) and cirrus clouds. We envision robust approaches in which well-collocated ground-based measurements and space-borne observations will greatly advance our knowledge of extensive aerosols and clouds.

Scaling of drizzle virga depth with cloud thickness for marine stratocumulus clouds

DOE PAGES

Yang, Fan; Luke, Edward P.; Kollias, Pavlos; ...

2018-04-20

Drizzle plays a crucial role in cloud lifetime and radiation properties of marine stratocumulus clouds. Understanding where drizzle exists in the sub-cloud layer, which depends on drizzle virga depth, can help us better understand where below-cloud scavenging and evaporative cooling and moisturizing occur. In this study, we examine the statistical properties of drizzle frequency and virga depth of marine stratocumulus based on unique ground-based remote sensing data. Results show that marine stratocumulus clouds are drizzling nearly all the time. In addition, we derive a simple scaling analysis between drizzle virga thickness and cloud thickness. Our analytical expression agrees with themore » observational data reasonable well, which suggests that our formula provides a simple parameterization for drizzle virga of stratocumulus clouds suitable for use in other models.« less

Scaling of drizzle virga depth with cloud thickness for marine stratocumulus clouds

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

Yang, Fan; Luke, Edward P.; Kollias, Pavlos

Drizzle plays a crucial role in cloud lifetime and radiation properties of marine stratocumulus clouds. Understanding where drizzle exists in the sub-cloud layer, which depends on drizzle virga depth, can help us better understand where below-cloud scavenging and evaporative cooling and moisturizing occur. In this study, we examine the statistical properties of drizzle frequency and virga depth of marine stratocumulus based on unique ground-based remote sensing data. Results show that marine stratocumulus clouds are drizzling nearly all the time. In addition, we derive a simple scaling analysis between drizzle virga thickness and cloud thickness. Our analytical expression agrees with themore » observational data reasonable well, which suggests that our formula provides a simple parameterization for drizzle virga of stratocumulus clouds suitable for use in other models.« less

Efficient Retrieval of Massive Ocean Remote Sensing Images via a Cloud-Based Mean-Shift Algorithm.

PubMed

Yang, Mengzhao; Song, Wei; Mei, Haibin

2017-07-23

The rapid development of remote sensing (RS) technology has resulted in the proliferation of high-resolution images. There are challenges involved in not only storing large volumes of RS images but also in rapidly retrieving the images for ocean disaster analysis such as for storm surges and typhoon warnings. In this paper, we present an efficient retrieval of massive ocean RS images via a Cloud-based mean-shift algorithm. Distributed construction method via the pyramid model is proposed based on the maximum hierarchical layer algorithm and used to realize efficient storage structure of RS images on the Cloud platform. We achieve high-performance processing of massive RS images in the Hadoop system. Based on the pyramid Hadoop distributed file system (HDFS) storage method, an improved mean-shift algorithm for RS image retrieval is presented by fusion with the canopy algorithm via Hadoop MapReduce programming. The results show that the new method can achieve better performance for data storage than HDFS alone and WebGIS-based HDFS. Speedup and scaleup are very close to linear changes with an increase of RS images, which proves that image retrieval using our method is efficient.

Efficient Retrieval of Massive Ocean Remote Sensing Images via a Cloud-Based Mean-Shift Algorithm

PubMed Central

Song, Wei; Mei, Haibin

2017-01-01

The rapid development of remote sensing (RS) technology has resulted in the proliferation of high-resolution images. There are challenges involved in not only storing large volumes of RS images but also in rapidly retrieving the images for ocean disaster analysis such as for storm surges and typhoon warnings. In this paper, we present an efficient retrieval of massive ocean RS images via a Cloud-based mean-shift algorithm. Distributed construction method via the pyramid model is proposed based on the maximum hierarchical layer algorithm and used to realize efficient storage structure of RS images on the Cloud platform. We achieve high-performance processing of massive RS images in the Hadoop system. Based on the pyramid Hadoop distributed file system (HDFS) storage method, an improved mean-shift algorithm for RS image retrieval is presented by fusion with the canopy algorithm via Hadoop MapReduce programming. The results show that the new method can achieve better performance for data storage than HDFS alone and WebGIS-based HDFS. Speedup and scaleup are very close to linear changes with an increase of RS images, which proves that image retrieval using our method is efficient. PMID:28737699

Infrared remote sensing of the vertical and horizontal distribution of clouds

NASA Technical Reports Server (NTRS)

Chahine, M. T.; Haskins, R. D.

1982-01-01

An algorithm has been developed to derive the horizontal and vertical distribution of clouds from the same set of infrared radiance data used to retrieve atmospheric temperature profiles. The method leads to the determination of the vertical atmospheric temperature structure and the cloud distribution simultaneously, providing information on heat sources and sinks, storage rates and transport phenomena in the atmosphere. Experimental verification of this algorithm was obtained using the 15-micron data measured by the NOAA-VTPR temperature sounder. After correcting for water vapor emission, the results show that the cloud cover derived from 15-micron data is less than that obtained from visible data.

Remote sensing data from CLARET: A prototype CART data set

NASA Technical Reports Server (NTRS)

Eberhard, Wynn L.; Uttal, Taneil; Clark, Kurt A.; Cupp, Richard E.; Dutton, Ellsworth G.; Fedor, Leonard, S.; Intrieri, Janet M.; Matrosov, Sergey Y.; Snider, Jack B.; Willis, Ron J.

1992-01-01

The data set containing radiation, meteorological , and cloud sensor observations is documented. It was prepared for use by the Department of Energy's Atmospheric Radiation Measurement (ARM) Program and other interested scientists. These data are a precursor of the types of data that ARM Cloud And Radiation Testbed (CART) sites will provide. The data are from the Cloud Lidar And Radar Exploratory Test (CLARET) conducted by the Wave Propagation Laboratory during autumn 1989 in the Denver-Boulder area of Colorado primarily for the purpose of developing new cloud-sensing techniques on cirrus. After becoming aware of the experiment, ARM scientists requested archival of subsets of the data to assist in the developing ARM program. Five CLARET cases were selected: two with cirrus, one with stratus, one with mixed-phase clouds, and one with clear skies. Satellite data from the stratus case and one cirrus case were analyzed for statistics on cloud cover and top height. The main body of the selected data are available on diskette from the Wave Propagation Laboratory or Los Alamos National Laboratory.

Icing detection from geostationary satellite data using machine learning approaches

NASA Astrophysics Data System (ADS)

Lee, J.; Ha, S.; Sim, S.; Im, J.

2015-12-01

Icing can cause a significant structural damage to aircraft during flight, resulting in various aviation accidents. Icing studies have been typically performed using two approaches: one is a numerical model-based approach and the other is a remote sensing-based approach. The model based approach diagnoses aircraft icing using numerical atmospheric parameters such as temperature, relative humidity, and vertical thermodynamic structure. This approach tends to over-estimate icing according to the literature. The remote sensing-based approach typically uses meteorological satellite/ground sensor data such as Geostationary Operational Environmental Satellite (GOES) and Dual-Polarization radar data. This approach detects icing areas by applying thresholds to parameters such as liquid water path and cloud optical thickness derived from remote sensing data. In this study, we propose an aircraft icing detection approach which optimizes thresholds for L1B bands and/or Cloud Optical Thickness (COT) from Communication, Ocean and Meteorological Satellite-Meteorological Imager (COMS MI) and newly launched Himawari-8 Advanced Himawari Imager (AHI) over East Asia. The proposed approach uses machine learning algorithms including decision trees (DT) and random forest (RF) for optimizing thresholds of L1B data and/or COT. Pilot Reports (PIREPs) from South Korea and Japan were used as icing reference data. Results show that RF produced a lower false alarm rate (1.5%) and a higher overall accuracy (98.8%) than DT (8.5% and 75.3%), respectively. The RF-based approach was also compared with the existing COMS MI and GOES-R icing mask algorithms. The agreements of the proposed approach with the existing two algorithms were 89.2% and 45.5%, respectively. The lower agreement with the GOES-R algorithm was possibly due to the high uncertainty of the cloud phase product from COMS MI.

Potential of remote sensing of cirrus optical thickness by airborne spectral radiance measurements at different sideward viewing angles

NASA Astrophysics Data System (ADS)

Wolf, Kevin; Ehrlich, André; Hüneke, Tilman; Pfeilsticker, Klaus; Werner, Frank; Wirth, Martin; Wendisch, Manfred

2017-03-01

Spectral radiance measurements collected in nadir and sideward viewing directions by two airborne passive solar remote sensing instruments, the Spectral Modular Airborne Radiation measurement sysTem (SMART) and the Differential Optical Absorption Spectrometer (mini-DOAS), are used to compare the remote sensing results of cirrus optical thickness τ. The comparison is based on a sensitivity study using radiative transfer simulations (RTS) and on data obtained during three airborne field campaigns: the North Atlantic Rainfall VALidation (NARVAL) mission, the Mid-Latitude Cirrus Experiment (ML-CIRRUS) and the Aerosol, Cloud, Precipitation, and Radiation Interactions and Dynamics of Convective Cloud Systems (ACRIDICON) campaign. Radiative transfer simulations are used to quantify the sensitivity of measured upward radiance I with respect to τ, ice crystal effective radius reff, viewing angle of the sensor θV, spectral surface albedo α, and ice crystal shape. From the calculations it is concluded that sideward viewing measurements are generally better suited than radiance data from the nadir direction to retrieve τ of optically thin cirrus, especially at wavelengths larger than λ = 900 nm. Using sideward instead of nadir-directed spectral radiance measurements significantly improves the sensitivity and accuracy in retrieving τ, in particular for optically thin cirrus of τ ≤ 2. The comparison of retrievals of τ based on nadir and sideward viewing radiance measurements from SMART, mini-DOAS and independent estimates of τ from an additional active remote sensing instrument, the Water Vapor Lidar Experiment in Space (WALES), shows general agreement within the range of measurement uncertainties. For the selected example a mean τ of 0.54 ± 0.2 is derived from SMART, and 0.49 ± 0.2 by mini-DOAS nadir channels, while WALES obtained a mean value of τ = 0.32 ± 0.02 at 532 nm wavelength, respectively. The mean of τ derived from the sideward viewing mini-DOAS channels is 0.26 ± 0.2. For the few simultaneous measurements, the mini-DOAS sideward channel measurements systematically underestimate (-17.6 %) the nadir observations from SMART and mini-DOAS. The agreement between mini-DOAS sideward viewing channels and WALES is better, showing the advantage of using sideward viewing measurements for cloud remote sensing for τ ≤ 1. Therefore, we suggest sideward viewing measurements for retrievals of τ of thin cirrus because of the significantly enhanced capability of sideward viewing compared to nadir measurements.

Use of the X-Band Radar to Support the Detection of In-Flight Icing Hazards by the NASA Icing Remote Sensing System

NASA Technical Reports Server (NTRS)

Serke, David J.; Politovich, Marcia K.; Reehorst, Andrew L.; Gaydos, Andrew

2009-01-01

The Alliance Icing Research Study-II (AIRS-II) field program was conducted near Montreal, Canada during the winter of 2003. The NASA Icing Remote Detection System (NIRSS) was deployed to detect in-flight icing hazards and consisted of a vertically pointing multichannel radiometer, a ceilometer and an x-band cloud radar. The radiometer was used to derive atmospheric temperature soundings and integrated liquid water, while the ceilometer and radar were used only to define cloud boundaries. The purpose of this study is to show that the radar reflectivity profiles from AIRS-II case studies could be used to provide a qualitative icing hazard.

Some physical and thermodynamic properties of rocket exhaust clouds measured with infrared scanners

NASA Technical Reports Server (NTRS)

Gomberg, R. I.; Kantsios, A. G.; Rosensteel, F. J.

1977-01-01

Measurements using infrared scanners were made of the radiation from exhaust clouds from liquid- and solid-propellant rocket boosters. Field measurements from four launches were discussed. These measurements were intended to explore the physical and thermodynamic properties of these exhaust clouds during their formation and subsequent dispersion. Information was obtained concerning the initial cloud's buoyancy, the stabilized cloud's shape and trajectory, the cloud volume as a function of time, and it's initial and stabilized temperatures. Differences in radiation intensities at various wavelengths from ambient and stabilized exhaust clouds were investigated as a method of distinguishing between the two types of clouds. The infrared remote sensing method used can be used at night when visible range cameras are inadequate. Infrared scanning techniques developed in this project can be applied directly to natural clouds, clouds containing certain radionuclides, or clouds of industrial pollution.

Daytime Cloud Property Retrievals Over the Arctic from Multispectral MODIS Data

NASA Technical Reports Server (NTRS)

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

2004-01-01

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

Diagnosing causes of cloud parameterization deficiencies using ARM measurements over SGP site

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

Wu, W.; Liu, Y.; Betts, A. K.

2010-03-15

Decade-long continuous surface-based measurements at Great Southern Plains (SGP) collected by the US Department of Energy’s Atmospheric Radiation Measurement (ARM) Climate Research Facility are first used to evaluate the three major reanalyses (i.e., ERA-Interim, NCEP/NCAR Reanalysis I and NCEP/DOE Reanalysis II) to identify model biases in simulating surface shortwave cloud forcing and total cloud fraction. The results show large systematic lower biases in the modeled surface shortwave cloud forcing and cloud fraction from all the three reanalysis datasets. Then we focus on diagnosing the causes of these model biases using the Active Remote Sensing of Clouds (ARSCL) products (e.g., verticalmore » distribution of cloud fraction, cloud-base and cloud-top heights, and cloud optical depth) and meteorological measurements (temperature, humidity and stability). Efforts are made to couple cloud properties with boundary processes in the diagnosis.« less

Remote-sensing reflectance determinations in the coastal ocean environment: impact of instrumental characteristics and environmental variability.

PubMed

Toole, D A; Siegel, D A; Menzies, D W; Neumann, M J; Smith, R C

2000-01-20

Three independent ocean color sampling methodologies are compared to assess the potential impact of instrumental characteristics and environmental variability on shipboard remote-sensing reflectance observations from the Santa Barbara Channel, California. Results indicate that under typical field conditions, simultaneous determinations of incident irradiance can vary by 9-18%, upwelling radiance just above the sea surface by 8-18%, and remote-sensing reflectance by 12-24%. Variations in radiometric determinations can be attributed to a variety of environmental factors such as Sun angle, cloud cover, wind speed, and viewing geometry; however, wind speed is isolated as the major source of uncertainty. The above-water approach to estimating water-leaving radiance and remote-sensing reflectance is highly influenced by environmental factors. A model of the role of wind on the reflected sky radiance measured by an above-water sensor illustrates that, for clear-sky conditions and wind speeds greater than 5 m/s, determinations of water-leaving radiance at 490 nm are undercorrected by as much as 60%. A data merging procedure is presented to provide sky radiance correction parameters for above-water remote-sensing reflectance estimates. The merging results are consistent with statistical and model findings and highlight the importance of multiple field measurements in developing quality coastal oceanographic data sets for satellite ocean color algorithm development and validation.

Effects of ice crystal surface roughness and air bubble inclusions on cirrus cloud radiative properties from remote sensing perspective

NASA Astrophysics Data System (ADS)

Tang, Guanglin; Panetta, R. Lee; Yang, Ping; Kattawar, George W.; Zhai, Peng-Wang

2017-07-01

We study the combined effects of surface roughness and inhomogeneity on the optical scattering properties of ice crystals and explore the consequent implications to remote sensing of cirrus cloud properties. Specifically, surface roughness and inhomogeneity are added to the Moderate Resolution Imaging Spectroradiometer (MODIS) collection 6 (MC6) cirrus cloud particle habit model. Light scattering properties of the new habit model are simulated using a modified version of the Improved Geometric Optics Method (IGOM). Both inhomogeneity and surface roughness affect the single scattering properties significantly. In visible bands, inhomogeneity and surface roughness both tend to smooth the phase function and eliminate halos and the backscattering peak. The asymmetry parameter varies with the degree of surface roughness following a U shape - decreases and then increases - with a minimum at around 0.15, whereas it decreases monotonically with the air bubble volume fraction. Air bubble inclusions significantly increase phase matrix element -P12 for scattering angles between 20°-120°, whereas surface roughness has a much weaker effect, increasing -P12 slightly from 60°-120°. Radiative transfer simulations and cirrus cloud property retrievals are conducted by including both the factors. In terms of surface roughness and air bubble volume fraction, retrievals of cirrus cloud optical thickness or the asymmetry parameter using solar bands show similar patterns of variation. Polarimetric simulations using the MC6 cirrus cloud particle habit model are shown to be more consistent with observations when both surface roughness and inhomogeneity are simultaneously considered.

Earth-based remote sensing of planetary surfaces and atmospheres at radio wavelengths

NASA Technical Reports Server (NTRS)

Dickel, J. R.

1982-01-01

Two reasons for remote sensing from the Earth are given: (1) space exploration, particularly below the surfaces or underneath cloud layers, is limited to only a very few planets; and (2) a program of regular monitoring, currently impractical with a limited number of space probes, is required. Reflected solar and nonthermal radiation are discussed. Relativistic electrons, trapped in large magnetospheres on Saturn and Jupiter, are discussed. These electrons produce synchrotron radiation and also interact with the ionosphere to produce bursts of low frequency emission. Because most objects are black-bodies, continuum radiometry is emphasized. Spectroscopic techniques and the measurement of nonthermal emission are also discussed.

Spectral Resolution and Coverage Impact on Advanced Sounder Information Content

NASA Technical Reports Server (NTRS)

Larar, Allen M.; Liu, Xu; Zhou, Daniel K.; Smith, William L.

2010-01-01

Advanced satellite sensors are tasked with improving global measurements of the Earth s atmosphere, clouds, and surface to enable enhancements in weather prediction, climate monitoring capability, and environmental change detection. Achieving such measurement improvements requires instrument system advancements. This presentation focuses on the impact of spectral resolution and coverage changes on remote sensing system information content, with a specific emphasis on thermodynamic state and trace species variables obtainable from advanced atmospheric sounders such as the Infrared Atmospheric Sounding Interferometer (IASI) and Cross-track Infrared Sounder (CrIS) systems on the MetOp and NPP/NPOESS series of satellites. Key words: remote sensing, advanced sounders, information content, IASI, CrIS

Pseudorandom Noise Code-Based Technique for Cloud and Aerosol Discrimination Applications

NASA Technical Reports Server (NTRS)

Campbell, Joel F.; Prasad, Narasimha S.; Flood, Michael A.; Harrison, Fenton Wallace

2011-01-01

NASA Langley Research Center is working on a continuous wave (CW) laser based remote sensing scheme for the detection of CO2 and O2 from space based platforms suitable for ACTIVE SENSING OF CO2 EMISSIONS OVER NIGHTS, DAYS, AND SEASONS (ASCENDS) mission. ASCENDS is a future space-based mission to determine the global distribution of sources and sinks of atmospheric carbon dioxide (CO2). A unique, multi-frequency, intensity modulated CW (IMCW) laser absorption spectrometer (LAS) operating at 1.57 micron for CO2 sensing has been developed. Effective aerosol and cloud discrimination techniques are being investigated in order to determine concentration values with accuracies less than 0.3%. In this paper, we discuss the demonstration of a PN code based technique for cloud and aerosol discrimination applications. The possibility of using maximum length (ML)-sequences for range and absorption measurements is investigated. A simple model for accomplishing this objective is formulated, Proof-of-concept experiments carried out using SONAR based LIDAR simulator that was built using simple audio hardware provided promising results for extension into optical wavelengths. Keywords: ASCENDS, CO2 sensing, O2 sensing, PN codes, CW lidar

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).

Airborne Particles: What We Have Learned About Their Role in Climate from Remote Sensing, and Prospects for Future Advances

NASA Technical Reports Server (NTRS)

Kahn, Ralph A.

2013-01-01

Desert dust, wildfire smoke, volcanic ash, biogenic and urban pollution particles, all affect the regional-scale climate of Earth in places and at times; some have global-scale impacts on the column radiation balance, cloud properties, atmospheric stability structure, and circulation patterns. Remote sensing has played a central role in identifying the sources and transports of airborne particles, mapping their three-dimensional distribution and variability, quantifying their amount, and constraining aerosol air mass type. The measurements obtained from remote sensing have strengths and limitations, and their value for characterizing Earths environment is enhanced immensely when they are combined with direct, in situ observations, and used to constrain aerosol transport and climate models. A similar approach has been taken to study the role particles play in determining the climate of Mars, though based on far fewer observations. This presentation will focus what we have learned from remote sensing about the impacts aerosol have on Earths climate; a few points about how aerosols affect the climate of Mars will also be introduced, in the context of how we might assess aerosol-climate impacts more generally on other worlds.

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.

A demonstration of adjoint methods for multi-dimensional remote sensing of the atmosphere and surface

NASA Astrophysics Data System (ADS)

Martin, William G. K.; Hasekamp, Otto P.

2018-01-01

In previous work, we derived the adjoint method as a computationally efficient path to three-dimensional (3D) retrievals of clouds and aerosols. In this paper we will demonstrate the use of adjoint methods for retrieving two-dimensional (2D) fields of cloud extinction. The demonstration uses a new 2D radiative transfer solver (FSDOM). This radiation code was augmented with adjoint methods to allow efficient derivative calculations needed to retrieve cloud and surface properties from multi-angle reflectance measurements. The code was then used in three synthetic retrieval studies. Our retrieval algorithm adjusts the cloud extinction field and surface albedo to minimize the measurement misfit function with a gradient-based, quasi-Newton approach. At each step we compute the value of the misfit function and its gradient with two calls to the solver FSDOM. First we solve the forward radiative transfer equation to compute the residual misfit with measurements, and second we solve the adjoint radiative transfer equation to compute the gradient of the misfit function with respect to all unknowns. The synthetic retrieval studies verify that adjoint methods are scalable to retrieval problems with many measurements and unknowns. We can retrieve the vertically-integrated optical depth of moderately thick clouds as a function of the horizontal coordinate. It is also possible to retrieve the vertical profile of clouds that are separated by clear regions. The vertical profile retrievals improve for smaller cloud fractions. This leads to the conclusion that cloud edges actually increase the amount of information that is available for retrieving the vertical profile of clouds. However, to exploit this information one must retrieve the horizontally heterogeneous cloud properties with a 2D (or 3D) model. This prototype shows that adjoint methods can efficiently compute the gradient of the misfit function. This work paves the way for the application of similar methods to 3D remote sensing problems.

SUCCESS Studies of the Impact of Aircraft on Cirrus Clouds

NASA Technical Reports Server (NTRS)

Toon, Owen B.; Condon, Estelle P. (Technical Monitor)

1996-01-01

During April of 1996 NASA will sponsor the SUCCESS project to better understand the impact of subsonic aircraft on the Earth's radiation budget. We plan to better determine the radiative properties of cirrus clouds and of contrails so that satellite observations can better determine their impact on Earth's radiation budget. We hope to determine how cirrus clouds form, whether the exhaust from subsonic aircraft presently affects the formation of cirrus clouds, and if the exhaust does affect the clouds whether the changes induced are of climatological significance. We seek to pave the way for future studies by developing and testing several new instruments. We also plan to better determine the characteristics of gaseous and particulate exhaust products from subsonic aircraft and their evolution in the region near the aircraft. In order to achieve our experimental objectives we plan to use the DC-8 aircraft as an in situ sampling platform. It will carry a wide variety of gaseous, particulate, radiative, and meteorological instruments. We will also use a T-39 aircraft primarily to sample the exhaust from other aircraft. It will carry a suite of instruments to measure particles and gases. We will employ an ER-2 aircraft as a remote sensing platform. The ER-2 will act as a surrogate satellite so that remote sensing observations can be related to the in situ parameters measured by the DC-8 and T-39. The mission strategy calls for a 5 week deployment beginning on April 8, 1996, and ending on May 10, 1996. During this time all three aircraft will be based in Salina, Kansas. A series of flights, averaging one every other day during this period, will be made mainly near the Department of Energy's Climate and Radiation Testbed site (CART) located in Northern Oklahoma, and Southern Kansas. During this same time period an extensive set of ground based measurements will be made by the DOE, which will also be operating several aircraft in the area to better understand the radiative properties of the atmosphere. Additional flights will be made over the Rocky Mountains, to investigate wave clouds. Flights will also be made over the Gulf of Mexico to utilize an oceanic background for remote sensing measurements. The results of this mission will be presented in this talk.

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

Nitschke, Kim

The ARM Climate Research Facility, a DOE scientific user facility, provides the climate research community with strategically located in situ and remote sensing observatories designed to improve the understanding and representation, in climate and earth system models, of clouds and aerosols as well as their interactions and coupling with the Earth’s surface.

Analysis On Land Cover In Municipality Of Malang With Landsat 8 Image Through Unsupervised Classification

NASA Astrophysics Data System (ADS)

Nahari, R. V.; Alfita, R.

2018-01-01

Remote sensing technology has been widely used in the geographic information system in order to obtain data more quickly, accurately and affordably. One of the advantages of using remote sensing imagery (satellite imagery) is to analyze land cover and land use. Satellite image data used in this study were images from the Landsat 8 satellite combined with the data from the Municipality of Malang government. The satellite image was taken in July 2016. Furthermore, the method used in this study was unsupervised classification. Based on the analysis towards the satellite images and field observations, 29% of the land in the Municipality of Malang was plantation, 22% of the area was rice field, 12% was residential area, 10% was land with shrubs, and the remaining 2% was water (lake/reservoir). The shortcoming of the methods was 25% of the land in the area was unidentified because it was covered by cloud. It is expected that future researchers involve cloud removal processing to minimize unidentified area.

Strategic Environmental Research and Development Program: Atmospheric Remote Sensing and Assessment Program -- Final Report. Part 1: The lower atmosphere

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

Tooman, T.P.

1997-01-01

This report documents work done between FY91 and FY95 for the lower atmospheric portion of the joint Department of Defense (DoD) and Department of Energy (DOE) Atmospheric Remote Sensing and Assessment Program (ARSAP) within the Strategic Environmental Research and Development Program (SERDP). The work focused on (1) developing new measurement capabilities and (2) measuring atmospheric heating in a well-defined layer and then relating it to cloud properties an water vapor content. Seven new instruments were develop3ed for use with Unmanned Aerospace Vehicles (UAVs) as the host platform for flux, radiance, cloud, and water vapor measurements. Four major field campaigns weremore » undertaken to use these new as well as existing instruments to make critically needed atmospheric measurements. Scientific results include the profiling of clear sky fluxes from near surface to 14 km and the strong indication of cloudy atmosphere absorption of solar radiation considerably greater than predicted by extant models.« less

Monitoring Aircraft Motion at Airports by LIDAR

NASA Astrophysics Data System (ADS)

Toth, C.; Jozkow, G.; Koppanyi, Z.; Young, S.; Grejner-Brzezinska, D.

2016-06-01

Improving sensor performance, combined with better affordability, provides better object space observability, resulting in new applications. Remote sensing systems are primarily concerned with acquiring data of the static components of our environment, such as the topographic surface of the earth, transportation infrastructure, city models, etc. Observing the dynamic component of the object space is still rather rare in the geospatial application field; vehicle extraction and traffic flow monitoring are a few examples of using remote sensing to detect and model moving objects. Deploying a network of inexpensive LiDAR sensors along taxiways and runways can provide both geometrically and temporally rich geospatial data that aircraft body can be extracted from the point cloud, and then, based on consecutive point clouds motion parameters can be estimated. Acquiring accurate aircraft trajectory data is essential to improve aviation safety at airports. This paper reports about the initial experiences obtained by using a network of four Velodyne VLP- 16 sensors to acquire data along a runway segment.

Applications of the similarity relations in radiative transfer to remote sensing implementation and flux simulation

NASA Astrophysics Data System (ADS)

Yang, P.; Ding, J.; Tang, G.; King, M. D.; Platnick, S. E.; Meyer, K.; Mlawer, E. J.

2017-12-01

Van de Hulst (1974) showed several quasi-invariant quantities in radiative transfer concerning multiple scattering. Recently, we illustrated that the aforesaid quasi-invariant quantities are useful in remote sensing of ice cloud properties from spaceborne radiometric observations (Ding et al. 2017). Specifically, the overall performance of an ice cloud optical property model can be estimated without carrying out detailed retrieval implementation. In this presentation, we will review the radiative transfer similarity relations and some recent results including the study by Ding et al. (2017). Furthermore, we will illustrate an application of the similarity relations to improvement of broadband radiative flux computation. For example, the Rapid Radiative Transfer Model (RRTM, Mlawer et al, 1999) does not consider multiple scattering in the longwave spectral regime (RRTMG-LW) ("G" indicates a version suitable for GCM applications). We show that the similarity relations can be used to effectively improve the accuracy of RRTMG-LW without increasing computational effort.

Reflection of solar radiation by a cylindrical cloud

NASA Technical Reports Server (NTRS)

Smith, G. L.

1989-01-01

Potential applications of an analytic method for computing the solar radiation reflected by a cylindrical cloud are discussed, including studies of radiative transfer within finite clouds and evaluations of these effects on other clouds and on remote sensing problems involving finite clouds. The pattern of reflected sunlight from a cylindrical cloud as seen at a large distance has been considered and described by the bidirectional function method for finite cloud analysis, as previously studied theoretically for plane-parallel atmospheres by McKee and Cox (1974); Schmetz and Raschke (1981); and Stuhlmann et al. (1985). However, the lack of three-dimensional radiative transfer solutions for anisotropic scattering media have hampered theoretical investigations of bidirectional functions for finite clouds. The present approach permits expression of the directional variation of the radiation field as a spherical harmonic series to any desired degree and order.

How do A-train Sensors Inter-Compare in the Retrieval of Above-Cloud Aerosol Optical Depth? A Case Study based Assessment

NASA Astrophysics Data System (ADS)

Jethva, H. T.; Torres, O.; Waquet, F.; Chand, D.

2013-12-01

Atmospheric aerosols are known to produce a net cooling effect in the cloud-free conditions. However, when present over the reflective cloud decks, absorbing aerosols such as biomass burning generated smoke and wind-blown dust can potentially exert a large positive forcing through enhanced atmospheric heating resulting from cloud-aerosol radiative interactions. The interest on this aspect of aerosol science has grown significantly in the recent years. Particularly, development of the satellite-based retrieval techniques and unprecedented knowledge on the above-cloud aerosol optical depth (ACAOD) is of great relevance. A direct validation of satellite ACAOD is a difficult task primarily due to lack of ample in situ and/or remote sensing measurements of aerosols above cloud. In these circumstances, a comparative analysis on the inter-satellite ACAOD retrievals can be performed for the sack of consistency check. Here, we inter-compare the ACAOD of biomass burning plumes observed from different A-train sensors, i.e., MODIS [Jethva et al., 2013], CALIOP [Chand et al., 2008], POLDER [Waquet et al., 2009], and OMI [Torres et al., 2012]. These sensors have been shown to acquire sensitivity and independent capabilities to detect and retrieve aerosol loading above marine stratocumulus clouds--a kind of situation often found over the southeastern Atlantic Ocean during dry burning season. A systematic one-to-one comparison reveals that, in general, all passive sensors and CALIOP-based research methods retrieve comparable ACAOD over homogeneous cloud fields. The high-resolution sensors (MODIS and CALIOP) are able to retrieve aerosols over thin clouds but with larger discrepancies. Given the different types of sensor measurements processed with different algorithms, a reasonable agreement between them is encouraging. A direct validation of satellite-based ACAOD remains an open challenge for which dedicated field measurements over the region of frequent aerosol/cloud overlap are a prime requirement. Jethva, H., O. Torres, L. A. Remer, P. K. Bhartia (2013), A Color Ratio Method for Simultaneous Retrieval of Aerosol and Cloud Optical Thickness of Above-Cloud Absorbing Aerosols From Passive Sensors: Application to MODIS Measurements, Geoscience and Remote Sensing, IEEE Transactions on, 51(7), pp. 3862-3870, doi: 10.1109/TGRS.2012.2230008. Chand, D., T. L. Anderson, R. Wood, R. J. Charlson, Y. Hu, Z. Liu, and M. Vaughan (2008), Quantifying above-cloud aerosol using spaceborne lidar for improved understanding of cloudy-sky direct climate forcing, J. Geophys. Res., 113, D13206, doi:10.1029/2007JD009433. Waquet, F., J. Riedi, L. C. Labonnote, P. Goloub, B. Cairns, J.-L. Deuzeand, and D. Tanre (2009), Aerosol remote sensing over clouds using a-train observations, J. Atmos. Sci., 66(8), 2468-2480, doi: http://dx.doi.org/10.1175/2009JAS3026.1 Torres, O., H. Jethva, and P. K. Bhartia (2012), Retrieval of aerosol optical depth above clouds from OMI observations: Sensitivity analysis and case studies, J. Atmos. Sci., 69(3), 1037-1053, doi: http://dx.doi.org/10.1175/JAS-D-11-0130.

Remote sensing of low visibility over otopeni airport

NASA Astrophysics Data System (ADS)

Buzdugan, Livius; Urlea, Denisa; Bugeac, Paul; Stefan, Sabina

2018-04-01

The paper is focused on the study of atmospheric conditions determining low vertical visibility over Henri Coanda airport. A network of ceilometers and a Sodar were used to detect fog and low level cloud layers. In our study, vertical visibility from ceilometers and acoustic reflectivity from Sodar for November 2016 were used to estimate fog depth and top of fog layers, respectively. The correlation between fog and low cloud occurrence and the wind direction and speed is also investigated.

Solid State Laser Technology Development for Atmospheric Sensing Applications

NASA Technical Reports Server (NTRS)

Barnes, James C.

1998-01-01

NASA atmospheric scientists are currently planning active remote sensing missions that will enable global monitoring of atmospheric ozone, water vapor, aerosols and clouds as well as global wind velocity. The measurements of these elements and parameters are important because of the effects they have on climate change, atmospheric chemistry and dynamics, atmospheric transport and, in general, the health of the planet. NASA will make use of Differential Absorption Lidar (DIAL) and backscatter lidar techniques for active remote sensing of molecular constituents and atmospheric phenomena from advanced high-altitude aircraft and space platforms. This paper provides an overview of NASA Langley Research Center's (LaRC's) development of advanced solid state lasers, harmonic generators, and wave mixing techniques aimed at providing the broad range of wavelengths necessary to meet measurement goals of NASA's Earth Science Enterprise.

Preliminary results of fisheries investigation associated with Skylab-3. [remotely sensed distribution and abundance of gamefish in Gulf of Mexico

NASA Technical Reports Server (NTRS)

Savastano, K. J. (Principal Investigator); Pastula, E. J., Jr.; Woods, G.; Faller, K.

1974-01-01

The author has identified the following significant results. This investigation is to establish the feasibility of utilizing remotely sensed data acquired from aircraft and satellite platforms to provide information concerning the distribution and abundance of oceanic gamefish. Data from the test area in the northeastern Gulf of Mexico has made possible the identification of fisheries significant environmental parameters for white marlin. Predictive models based on catch data and surface truth information have been developed and have demonstrated potential for reducing search significantly by identifying areas which have a high probability of being productive. Three of the parameters utilized by the model, chlorophyll-a, sea surface temperature, and turbidity have been inferred from aircraft sensor data. Cloud cover and delayed receipt have inhibited the use of Skylab data. The first step toward establishing the feasibility of utilizing remotely sensed data to assess amd monitor the distribution of ocean gamefish has been taken with the successful identification of fisheries significant oceanographic parameters and the demonstration of the capability of measuring most of these parameters remotely.

The feasibility of utilizing remotely sensed data to assess and monitor oceanic gamefish

NASA Technical Reports Server (NTRS)

Savastano, K. J.; Leming, T. D.

1975-01-01

An investigation was conducted to establish the feasibility of utilizing remotely sensed data acquired from aircraft and satellite platforms to provide information concerning the distribution and abundance of oceanic gamefish. The data from the test area was jointly acquired by NASA, the Navy, the Air Force and NOAA/NMFS elements and private and professional fishermen in the northeastern Gulf of Mexico. The data collected has made it possible to identify fisheries significant environmental parameters for white marlin. Prediction models, based on catch data and surface truth information, were developed and demonstrated a potential for significantly reducing search by identifying areas that have a high probability of productivity. Three of the parameters utilized by the models, chlorophyll-a, sea surface temperature, and turbidity were inferred from aircraft sensor data and were tested. Effective use of Skylab data was inhibited by cloud cover and delayed delivery. Initial efforts toward establishing the feasibility of utilizing remotely sensed data to assess and monitor the distribution of oceanic gamefish has successfully identified fisheries significant oceanographic parameters and demonstrated the capability of remotely measuring most of the parameters.

Remote sensing of tornadic storms from geosynchronous satellite infrared digital data

NASA Technical Reports Server (NTRS)

Hung, R. J.; Smith, R. E.

1982-01-01

Two cases of GOES digital infrared data were analyzed during the three-hour period immediately prior to the tornado touchdown times. Clouds associated with tornadoes were compared to those without tornadoes using a combination of satellite infrared and rawinsonde data. On the basis of this limited data sample, it appears as if the altitude to which the overshooting cloud top penetrated above the tropopause is the factor which determines whether or not a tornado is formed. In these cases, the overshooting cloud top collapsed about 15 to 30 min before the tornado touchdown.

Atmospheric pollution measurement by optical cross correlation methods - A concept

NASA Technical Reports Server (NTRS)

Fisher, M. J.; Krause, F. R.

1971-01-01

Method combines standard spectroscopy with statistical cross correlation analysis of two narrow light beams for remote sensing to detect foreign matter of given particulate size and consistency. Method is applicable in studies of generation and motion of clouds, nuclear debris, ozone, and radiation belts.

Near UV Aerosol Group Report

NASA Technical Reports Server (NTRS)

Torres, Omar

2013-01-01

2012-13 Report of research on aerosol and cloud remote sensing using UV observations. The document was presented at the 2013 AEROCENTER Annual Meeting held at the GSFC Visitors Center, May 31, 2013. The Organizers of the meeting are posting the talks to the public Aerocentr website, after the meeting.

Comparison of CALIPSO-Like, LaRC, and MODIS Retrievals of Ice Cloud Properties over SIRTA in France and Florida during CRYSTAL-FACE

NASA Technical Reports Server (NTRS)

Chiriaco, M.; Chepfer, H.; Haeffelin, M.; Minnis, P.; Noel, V.; Platnick, S.; McGill, M.; Baumgardner, D.; Dubuisson, P.; Pelon, J.;

Reflections on current and future applications of multiangle imaging to aerosol and cloud remote sensing

NASA Astrophysics Data System (ADS)

Diner, David

2010-05-01

The Multi-angle Imaging SpectroRadiometer (MISR) instrument has been collecting global Earth data from NASA's Terra satellite since February 2000. With its 9 along-track view angles, 4 spectral bands, intrinsic spatial resolution of 275 m, and stable radiometric and geometric calibration, no instrument that combines MISR's attributes has previously flown in space, nor is there is a similar capability currently available on any other satellite platform. Multiangle imaging offers several tools for remote sensing of aerosol and cloud properties, including bidirectional reflectance and scattering measurements, stereoscopic pattern matching, time lapse sequencing, and potentially, optical tomography. Current data products from MISR employ several of these techniques. Observations of the intensity of scattered light as a function of view angle and wavelength provide accurate measures of aerosol optical depths (AOD) over land, including bright desert and urban source regions. Partitioning of AOD according to retrieved particle classification and incorporation of height information improves the relationship between AOD and surface PM2.5 (fine particulate matter, a regulated air pollutant), constituting an important step toward a satellite-based particulate pollution monitoring system. Stereoscopic cloud-top heights provide a unique metric for detecting interannual variability of clouds and exceptionally high quality and sensitivity for detection and height retrieval for low-level clouds. Using the several-minute time interval between camera views, MISR has enabled a pole-to-pole, height-resolved atmospheric wind measurement system. Stereo imagery also makes possible global measurement of the injection heights and advection speeds of smoke plumes, volcanic plumes, and dust clouds, for which a large database is now available. To build upon what has been learned during the first decade of MISR observations, we are evaluating algorithm updates that not only refine retrieval accuracies but also include enhancements (e.g., finer spatial resolution) that would have been computationally prohibitive just ten years ago. In addition, we are developing technological building blocks for future sensors that enable broader spectral coverage, wider swath, and incorporation of high-accuracy polarimetric imaging. Prototype cameras incorporating photoelastic modulators have been constructed. To fully capitalize on the rich information content of the current and next-generation of multiangle imagers, several algorithmic paradigms currently employed need to be re-examined, e.g., the use of aerosol look-up tables, neglect of 3-D effects, and binary partitioning of the atmosphere into "cloudy" or "clear" designations. Examples of progress in algorithm and technology developments geared toward advanced application of multiangle imaging to remote sensing of aerosols and clouds will be presented.

Spectral Dependence of MODIS Cloud Droplet Effective Radius Retrievals for Marine Boundary Layer Clouds

NASA Technical Reports Server (NTRS)

Zhang, Zhibo; Platnick, Steven E.; Ackerman, Andrew S.; Cho, Hyoun-Myoung

2014-01-01

Low-level warm marine boundary layer (MBL) clouds cover large regions of Earth's surface. They have a significant role in Earth's radiative energy balance and hydrological cycle. Despite the fundamental role of low-level warm water clouds in climate, our understanding of these clouds is still limited. In particular, connections between their properties (e.g. cloud fraction, cloud water path, and cloud droplet size) and environmental factors such as aerosol loading and meteorological conditions continue to be uncertain or unknown. Modeling these clouds in climate models remains a challenging problem. As a result, the influence of aerosols on these clouds in the past and future, and the potential impacts of these clouds on global warming remain open questions leading to substantial uncertainty in climate projections. To improve our understanding of these clouds, we need continuous observations of cloud properties on both a global scale and over a long enough timescale for climate studies. At present, satellite-based remote sensing is the only means of providing such observations.

Aerosol Microphysical Effects on Cloud Fraction over the Nighttime Arctic Ocean

NASA Astrophysics Data System (ADS)

Zamora, L. M.; Kahn, R. A.; Stohl, A.; Eckhardt, S.

2017-12-01

Cloud fraction is a key component affecting the surface energy balance in the Arctic. Aerosol microphysical processes can affect cloud fraction, for example through cloud lifetime effects. However, the importance of aerosol impacts on cloud fraction is not well constrained on a regional scale at high latitudes. Here we discuss a new method for identifying and comparing clean and aerosol-influenced cloud characteristics using a combination of multi-year remote sensing data (CALIPSO, CloudSat) and the FLEXPART aerosol model. We use this method to investigate a variety of aerosol microphysical impacts on nighttime Arctic Ocean clouds on regional and local scales. We observe differences in factors that can impact cloud lifetime, including cloud thickness and phase, within a subset of clean vs. polluted clouds. We will also discuss cumulative cloud fraction differences in clean and non-clean environments, as well as their likely impact on longwave cloud radiative effects at the Arctic Ocean surface during polar night.

Spatial Inference for Distributed Remote Sensing Data

NASA Astrophysics Data System (ADS)

Braverman, A. J.; Katzfuss, M.; Nguyen, H.

2014-12-01

Remote sensing data are inherently spatial, and a substantial portion of their value for scientific analyses derives from the information they can provide about spatially dependent processes. Geophysical variables such as atmopsheric temperature, cloud properties, humidity, aerosols and carbon dioxide all exhibit spatial patterns, and satellite observations can help us learn about the physical mechanisms driving them. However, remote sensing observations are often noisy and incomplete, so inferring properties of true geophysical fields from them requires some care. These data can also be massive, which is both a blessing and a curse: using more data drives uncertainties down, but also drives costs up, particularly when data are stored on different computers or in different physical locations. In this talk I will discuss a methodology for spatial inference on massive, distributed data sets that does not require moving large volumes of data. The idea is based on a combination of ideas including modeling spatial covariance structures with low-rank covariance matrices, and distributed estimation in sensor or wireless networks.

A Terminal Area Icing Remote Sensing System

NASA Technical Reports Server (NTRS)

Reehorst, Andrew L.; Serke, David J.

2014-01-01

NASA and the National Center for Atmospheric Research (NCAR) have developed an icing remote sensing technology that has demonstrated skill at detecting and classifying icing hazards in a vertical column above an instrumented ground station. This technology is now being extended to provide volumetric coverage surrounding an airport. With volumetric airport terminal area coverage, the resulting icing hazard information will be usable by aircrews, traffic control, and airline dispatch to make strategic and tactical decisions regarding routing when conditions are conducive to airframe icing. Building on the existing vertical pointing system, the new method for providing volumetric coverage will utilize cloud radar, microwave radiometry, and NEXRAD radar. This terminal area icing remote sensing system will use the data streams from these instruments to provide icing hazard classification along the defined approach paths into an airport. Strategies for comparison to in-situ instruments on aircraft and weather balloons for a planned NASA field test are discussed, as are possible future applications into the NextGen airspace system.

SCIAMACHY validation by aircraft remote sensing: design, execution, and first measurement results of the SCIA-VALUE mission

NASA Astrophysics Data System (ADS)

Fix, A.; Ehret, G.; Flentje, H.; Poberaj, G.; Gottwald, M.; Finkenzeller, H.; Bremer, H.; Bruns, M.; Burrows, J. P.; Kleinböhl, A.; Küllmann, H.; Kuttippurath, J.; Richter, A.; Wang, P.; Heue, K.-P.; Platt, U.; Pundt, I.; Wagner, T.

2005-05-01

For the first time three different remote sensing instruments - a sub-millimeter radiometer, a differential optical absorption spectrometer in the UV-visible spectral range, and a lidar - were deployed aboard DLR's meteorological research aircraft Falcon 20 to validate a large number of SCIAMACHY level 2 and off-line data products such as O3, NO2, N2O, BrO, OClO, H2O, aerosols, and clouds. Within two validation campaigns of the SCIA-VALUE mission (SCIAMACHY VALidation and Utilization Experiment) extended latitudinal cross-sections stretching from polar regions to the tropics as well as longitudinal cross sections at polar latitudes at about 70° N and the equator were generated. This contribution gives an overview over the campaigns performed and reports on the observation strategy for achieving the validation goals. We also emphasize the synergetic use of the novel set of aircraft instrumentation and the usefulness of this innovative suite of remote sensing instruments for satellite validation.

Research on the Construction of Remote Sensing Automatic Interpretation Symbol Big Data

NASA Astrophysics Data System (ADS)

Gao, Y.; Liu, R.; Liu, J.; Cheng, T.

2018-04-01

Remote sensing automatic interpretation symbol (RSAIS) is an inexpensive and fast method in providing precise in-situ information for image interpretation and accuracy. This study designed a scientific and precise RSAIS data characterization method, as well as a distributed and cloud architecture massive data storage method. Additionally, it introduced an offline and online data update mode and a dynamic data evaluation mechanism, with the aim to create an efficient approach for RSAIS big data construction. Finally, a national RSAIS database with more than 3 million samples covering 86 land types was constructed during 2013-2015 based on the National Geographic Conditions Monitoring Project of China and then annually updated since the 2016 period. The RSAIS big data has proven to be a good method for large scale image interpretation and field validation. It is also notable that it has the potential to solve image automatic interpretation with the assistance of deep learning technology in the remote sensing big data era.

Considerations for achieving cross-platform point cloud data fusion across different dryland ecosystem structural states

USDA-ARS?s Scientific Manuscript database

Dryland ecosystems undergo long periods of senescence punctuated by rapid growth following seasonal precipitation events. Remote sensing of vegetation dynamics which capture new growth as well as herbivory and disturbance require both high spatial and temporal resolution data acquired by various op...

The mean-square error optimal linear discriminant function and its application to incomplete data vectors

NASA Technical Reports Server (NTRS)

Walker, H. F.

1979-01-01

In many pattern recognition problems, data vectors are classified although one or more of the data vector elements are missing. This problem occurs in remote sensing when the ground is obscured by clouds. Optimal linear discrimination procedures for classifying imcomplete data vectors are discussed.

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.

The Research on the Spectral Characteristics of Sea Fog Based on Caliop and Modis Data

NASA Astrophysics Data System (ADS)

Wan, J.; Su, J.; Liu, S.; Sheng, H.

2018-04-01

In view of that difficulty of distinguish between sea fog and low cloud by optical remote sensing mean, the research on spectral characteristics of sea fog is focused and carried out. The satellite laser radar CALIOP data and the high spectral MODIS data were obtained from May to December 2017, and the scattering coefficient and the vertical height information were extracted from the atmospheric attenuation of the lower star to extract the sea fog sample points, and the spectral response curve based on MODIS was formed to analyse the spectral response characteristics of the sea fog, thus providing a theoretical basis for the monitoring of sea fog with optical remote sensing image.

The application of unmanned aerial vehicle remote sensing for monitoring secondary geological disasters after earthquakes

NASA Astrophysics Data System (ADS)

Lei, Tianjie; Zhang, Yazhen; Wang, Xingyong; Fu, Jun'e.; Li, Lin; Pang, Zhiguo; Zhang, Xiaolei; Kan, Guangyuan

2017-07-01

Remote sensing system fitted on Unmanned Aerial Vehicle (UAV) can obtain clear images and high-resolution aerial photographs. It has advantages of strong real-time, flexibility and convenience, free from influence of external environment, low cost, low-flying under clouds and ability to work full-time. When an earthquake happened, it could go deep into the places safely and reliably which human staff can hardly approach, such as secondary geological disasters hit areas. The system can be timely precise in response to secondary geological disasters monitoring by a way of obtaining first-hand information as quickly as possible, producing a unique emergency response capacity to provide a scientific basis for overall decision-making processes. It can greatly enhance the capability of on-site disaster emergency working team in data collection and transmission. The great advantages of UAV remote sensing system played an irreplaceable role in monitoring secondary geological disaster dynamics and influences. Taking the landslides and barrier lakes for example, the paper explored the basic application and process of UAV remote sensing in the disaster emergency relief. UAV high-resolution remote sensing images had been exploited to estimate the situation of disaster-hit areas and monitor secondary geological disasters rapidly, systematically and continuously. Furthermore, a rapid quantitative assessment on the distribution and size of landslides and barrier lakes was carried out. Monitoring results could support relevant government departments and rescue teams, providing detailed and reliable scientific evidence for disaster relief and decision-making.

Planning, Implementation, and Scientific Goals of the Studies of Emissions and Atmospheric Composition, Clouds and Climate Coupling by Regional Surveys (SEAC4RS) Field Missions

NASA Technical Reports Server (NTRS)

Toon, Owen B.; Maring, Hal; Dibb, Jack; Ferrare, Richard A.; Jacob, Daniel J.; Jensen, Eric J.; Luo, Z. Johnny; Mace, Gerald G.; Pan, Laura L.; Pfister, Leonhard;

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.

Fog Computing and Edge Computing Architectures for Processing Data From Diabetes Devices Connected to the Medical Internet of Things.

PubMed

Klonoff, David C

2017-07-01

The Internet of Things (IoT) is generating an immense volume of data. With cloud computing, medical sensor and actuator data can be stored and analyzed remotely by distributed servers. The results can then be delivered via the Internet. The number of devices in IoT includes such wireless diabetes devices as blood glucose monitors, continuous glucose monitors, insulin pens, insulin pumps, and closed-loop systems. The cloud model for data storage and analysis is increasingly unable to process the data avalanche, and processing is being pushed out to the edge of the network closer to where the data-generating devices are. Fog computing and edge computing are two architectures for data handling that can offload data from the cloud, process it nearby the patient, and transmit information machine-to-machine or machine-to-human in milliseconds or seconds. Sensor data can be processed near the sensing and actuating devices with fog computing (with local nodes) and with edge computing (within the sensing devices). Compared to cloud computing, fog computing and edge computing offer five advantages: (1) greater data transmission speed, (2) less dependence on limited bandwidths, (3) greater privacy and security, (4) greater control over data generated in foreign countries where laws may limit use or permit unwanted governmental access, and (5) lower costs because more sensor-derived data are used locally and less data are transmitted remotely. Connected diabetes devices almost all use fog computing or edge computing because diabetes patients require a very rapid response to sensor input and cannot tolerate delays for cloud computing.

A General Uncertainty Quantification Methodology for Cloud Microphysical Property Retrievals

NASA Astrophysics Data System (ADS)

Tang, Q.; Xie, S.; Chen, X.; Zhao, C.

2014-12-01

The US Department of Energy (DOE) Atmospheric Radiation Measurement (ARM) program provides long-term (~20 years) ground-based cloud remote sensing observations. However, there are large uncertainties in the retrieval products of cloud microphysical properties based on the active and/or passive remote-sensing measurements. To address this uncertainty issue, a DOE Atmospheric System Research scientific focus study, Quantification of Uncertainties in Cloud Retrievals (QUICR), has been formed. In addition to an overview of recent progress of QUICR, we will demonstrate the capacity of an observation-based general uncertainty quantification (UQ) methodology via the ARM Climate Research Facility baseline cloud microphysical properties (MICROBASE) product. This UQ method utilizes the Karhunen-Loéve expansion (KLE) and Central Limit Theorems (CLT) to quantify the retrieval uncertainties from observations and algorithm parameters. The input perturbations are imposed on major modes to take into account the cross correlations between input data, which greatly reduces the dimension of random variables (up to a factor of 50) and quantifies vertically resolved full probability distribution functions of retrieved quantities. Moreover, this KLE/CLT approach has the capability of attributing the uncertainties in the retrieval output to individual uncertainty source and thus sheds light on improving the retrieval algorithm and observations. We will present the results of a case study for the ice water content at the Southern Great Plains during an intensive observing period on March 9, 2000. This work is performed under the auspices of the U.S. Department of Energy by Lawrence Livermore National Laboratory under Contract DE-AC52-07NA27344.

A Wing Pod-based Millimeter Wave Cloud Radar on HIAPER

NASA Astrophysics Data System (ADS)

Vivekanandan, Jothiram; Tsai, Peisang; Ellis, Scott; Loew, Eric; Lee, Wen-Chau; Emmett, Joanthan

2014-05-01

One of the attractive features of a millimeter wave radar system is its ability to detect micron-sized particles that constitute clouds with lower than 0.1 g m-3 liquid or ice water content. Scanning or vertically-pointing ground-based millimeter wavelength radars are used to study stratocumulus (Vali et al. 1998; Kollias and Albrecht 2000) and fair-weather cumulus (Kollias et al. 2001). Airborne millimeter wavelength radars have been used for atmospheric remote sensing since the early 1990s (Pazmany et al. 1995). Airborne millimeter wavelength radar systems, such as the University of Wyoming King Air Cloud Radar (WCR) and the NASA ER-2 Cloud Radar System (CRS), have added mobility to observe clouds in remote regions and over oceans. Scientific requirements of millimeter wavelength radar are mainly driven by climate and cloud initiation studies. Survey results from the cloud radar user community indicated a common preference for a narrow beam W-band radar with polarimetric and Doppler capabilities for airborne remote sensing of clouds. For detecting small amounts of liquid and ice, it is desired to have -30 dBZ sensitivity at a 10 km range. Additional desired capabilities included a second wavelength and/or dual-Doppler winds. Modern radar technology offers various options (e.g., dual-polarization and dual-wavelength). Even though a basic fixed beam Doppler radar system with a sensitivity of -30 dBZ at 10 km is capable of satisfying cloud detection requirements, the above-mentioned additional options, namely dual-wavelength, and dual-polarization, significantly extend the measurement capabilities to further reduce any uncertainty in radar-based retrievals of cloud properties. This paper describes a novel, airborne pod-based millimeter wave radar, preliminary radar measurements and corresponding derived scientific products. Since some of the primary engineering requirements of this millimeter wave radar are that it should be deployable on an airborne platform, occupy minimum cabin space and maximize scan coverage, a pod-based configuration was adopted. Currently, the radar system is capable of collecting observations between zenith and nadir in a fixed scanning mode. Measurements are corrected for aircraft attitude changes. The near-nadir and zenith pointing observations minimize the cross-track Doppler contamination in the radial velocity measurements. An extensive engineering monitoring mechanism is built into the recording system status such as temperature, pressure, various electronic components' status and receiver characteristics. Status parameters are used for real-time system stability estimates and correcting radar system parameters. The pod based radar system is mounted on a modified Gulfstream V aircraft, which is operated and maintained by the National Center for Atmospheric Research (NCAR) on behalf of the National Science Foundation (NSF). The aircraft is called the High-Performance Instrumented Airborne Platform for Environmental Research (HIAPER) (Laursen et al., 2006). It is also instrumented with high spectral resolution lidar (HSRL) and an array of in situ and remote sensors for atmospheric research. As part of the instrument suite for HIAPER, the NSF funded the development of the HIAPER Cloud Radar (HCR). The HCR is an airborne, millimeter-wavelength, dual-polarization, Doppler radar that serves the atmospheric science community by providing cloud remote sensing capabilities for the NSF/NCAR G-V (HIAPER) aircraft. An optimal radar configuration that is capable of maximizing the accuracy of both qualitative and quantitative estimated cloud microphysical and dynamical properties is the most attractive option to the research community. The Technical specifications of cloud radar are optimized for realizing the desired scientific performance for the pod-based configuration. The radar was both ground and flight tested and preliminary measurements of Doppler and polarization measurements were collected. HCR observed sensitivity as low as -37 dBZ at 1 km range and resolved linear depolarization ratio (LDR) signature better than -29 dB during its latest test flights. References: Kollias, P., and B. A. Albrecht, 2000: The turbulence structure in a continental stratocumulus cloud from millimeter wavelength radar observation. J. Atmos. Sci., 57, 2417-2434. Kollias, P., B.A. Albrecht, R. Lhermitte, and A. Savtchenko, 2001: Radar observations of updrafts, downdrafts, and turbulence in fair weather cumuli. J. Atmos. Sci. 58, 1750-1766. Laursen, K. K., D. P. Jorgensen, G. P. Brasseur, S. L. Ustin, and J. Hunning, 2006: HIAPER: The next generation NSF/NCAR research aircraft. Bulletin of the American Meteorological Society, 87, 896-909. Pazmany, A. L., R. E. McIntosh, R. Kelly, and V. G., 1994: An airborne 95-GHz dual-polarized radar for cloud studies. IEEE Trans. Geosci. Remote Sens., 32, 731-739. Vali, G., Kelly, R.D., French, J., Haimov, S., Leon, D., McIntosh, R., Pazmany, A., 1998. Fine-scale structure and microphysics of coastal stratus. J. Atmos. Sci. 55, 3540-3564.

Developing a novel UAV (Unmanned Aerial Vehicle) helicopter platform for very high resolution environmental monitoring of catchment processes

NASA Astrophysics Data System (ADS)

Freer, J. E.; Richardson, T.; Yang, Z.

2012-12-01

Recent advances in remote sensing and geographic information has led the way for the development of hyperspectral sensors and cloud scanning LIDAR (Light Detection And Ranging). Both these technologies can be used to sense environmental processes and capture detailed spatial information, they are often deployed in ground, aircraft and satellite based systems. Hyperspectral remote sensing, also known as imaging spectroscopy, is a relatively new technology that is currently being investigated by researchers and scientists with regard to the detection and identification of landscapes, terrestrial vegetation, and manmade materials and backgrounds. There are many applications that could take advantages of hyperspectral remote sensing coupled to detailed surface feature mapping using LIDAR. This embryonic project involves developing the engineering solutions and post processing techniques needed to realise an ultra high resolution helicopter based environmental sensing platform which can fly at lower altitudes than aircraft systems and can be deployed more frequently. We aim to present this new technology platform in this special session (the only one of it's kind in the UK). Initial applications are planned on a range of environmental sensing problems that would benefit from such complex and detailed data.We look forward to being able to display and discuss this initiative with colleagues and any potential interest in future collaborative projects.

Developing a novel UAV (Unmanned Aerial Vehicle) helicopter platform for very high resolution environmental monitoring of catchment processes

NASA Astrophysics Data System (ADS)

Freer, J.; Richardson, T. S.

2012-04-01

Recent advances in remote sensing and geographic information has led the way for the development of hyperspectral sensors and cloud scanning LIDAR (Light Detection And Ranging). Both these technologies can be used to sense environmental processes and capture detailed spatial information, they are often deployed in ground, aircraft and satellite based systems. Hyperspectral remote sensing, also known as imaging spectroscopy, is a relatively new technology that is currently being investigated by researchers and scientists with regard to the detection and identification of landscapes, terrestrial vegetation, and manmade materials and backgrounds. There are many applications that could take advantages of hyperspectral remote sensing coupled to detailed surface feature mapping using LIDAR. This embryonic project involves developing the engineering solutions and post processing techniques needed to realise an ultra high resolution helicopter based environmental sensing platform which can fly at lower altitudes than aircraft systems and can be deployed more frequently. We aim to display this new technology platform in this special session (the only one of it's kind in the UK). Initial applications are planned on a range of environmental sensing problems that would benefit from such complex and detailed data. We look forward to being able to display and discuss this initiative with colleagues and any potential interest in future collaborative projects.

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.

Remote sensing of smoke, land, and clouds from the NASA ER-2 during SAFARI 2000

NASA Astrophysics Data System (ADS)

King, Michael D.; Platnick, Steven; Moeller, Christopher C.; Revercomb, Henry E.; Chu, D. Allen

2003-07-01

The NASA ER-2 aircraft was deployed to southern Africa between 13 August and 25 September 2000 as part of the Southern African Regional Science Initiative (SAFARI) 2000. This aircraft carried a sophisticated array of multispectral scanners, multiangle spectroradiometers, a monostatic lidar, a gas correlation radiometer, upward and downward spectral flux radiometers, and two metric mapping cameras. These observations were obtained over a 3200 × 2800 km region of savanna, woody savanna, open shrubland, and grassland ecosystems throughout southern Africa and were quite often coordinated with overflights by NASA's Terra and Landsat 7 satellites. The primary purpose of this high-altitude observing platform was to obtain independent observations of smoke, clouds, and land surfaces that could be used to check the validity of various remote sensing measurements derived by Earth-orbiting satellites. These include such things as the accuracy of the Moderate Resolution Imaging Spectroradiometer (MODIS) cloud mask for distinguishing clouds and heavy aerosol from land and ocean surfaces and Terra analyses of cloud optical and microphysical properties, aerosol properties, leaf area index, vegetation index, fire occurrence, carbon monoxide, and surface radiation budget. In addition to coordination with Terra and Landsat 7 satellites, numerous flights were conducted over surface AERONET sites, flux towers in South Africa, Botswana, and Zambia, and in situ aircraft from the University of Washington, South Africa, and the United Kingdom. As a result of this experiment, the MODIS cloud mask was shown to distinguish clouds, cloud shadows, and fires over land ecosystems of southern Africa with a high degree of accuracy. In addition, data acquired from the ER-2 show the vertical distribution and stratification of aerosol layers over the subcontinent and make the first observations of a "blue spike" spectral emission signature associated with air heated by fire advecting over a cooler land surface.

AccuRT: A versatile tool for radiative transfer simulations in the coupled atmosphere-ocean system

NASA Astrophysics Data System (ADS)

Hamre, Børge; Stamnes, Snorre; Stamnes, Knut; Stamnes, Jakob

2017-02-01

Reliable, accurate, and efficient modeling of the transport of electromagnetic radiation in turbid media has important applications in the study of the Earth's climate by remote sensing. For example, such modeling is needed to develop forward-inverse methods used to quantify types and concentrations of aerosol and cloud particles in the atmosphere, the dissolved organic and particulate biogeochemical matter in lakes, rivers, coastal, and open-ocean waters. It is also needed to simulate the performance of remote sensing detectors deployed on aircraft, balloons, and satellites as well as radiometric detectors deployed on buoys, gliders and other aquatic observing systems. Accurate radiative transfer modeling is also required to compute irradiances and scalar irradiances that are used to compute warming/cooling and photolysis rates in the atmosphere and primary production and warming/cooling rates in the water column. AccuRT is a radiative transfer model for the coupled atmosphere-water system that is designed to be a versatile tool for researchers in the ocean optics and remote sensing communities. It addresses the needs of researchers interested in analyzing irradiance and radiance measurements in the field and laboratory as well as those interested in making simulations of the top-of-the-atmosphere radiance in support of remote sensing algorithm development.

Combined Analysis of SENTINEL-1 and Rapideye Data for Improved Crop Type Classification: AN Early Season Approach for Rapeseed and Cereals

NASA Astrophysics Data System (ADS)

Lussem, U.; Hütt, C.; Waldhoff, G.

2016-06-01

Timely availability of crop acreage estimation is crucial for maintaining economic and ecological sustainability or modelling purposes. Remote sensing data has proven to be a reliable source for crop mapping and acreage estimation on parcel-level. However, when relying on a single source of remote sensing data, e.g. multispectral sensors like RapidEye or Landsat, several obstacles can hamper the desired outcome, for example cloud cover or haze. Another limitation may be a similarity in optical reflectance patterns of crops, especially in an early season approach by the end of March, early April. Usually, a reliable crop type map for winter-crops (winter wheat/rye, winter barley and rapeseed) in Central Europe can be obtained by using optical remote sensing data from late April to early May, given a full coverage of the study area and cloudless conditions. These prerequisites can often not be met. By integrating dual-polarimetric SAR-sensors with high temporal and spatial resolution, these limitations can be overcome. SAR-sensors are not influenced by clouds or haze and provide an additional source of information due to the signal-interaction with plant-architecture. The overall goal of this study is to investigate the contribution of Sentinel-1 SAR-data to regional crop type mapping for an early season map of disaggregated winter-crops for a subset of the Rur-Catchment in North Rhine-Westphalia (Germany). For this reason, RapidEye data and Sentinel-1 data are combined and the performance of Support Vector Machine and Maximum Likelihood classifiers are compared. Our results show that a combination of Sentinel-1 and RapidEye is a promising approach for most crops, but consideration of phenology for data selection can improve results. Thus the combination of optical and radar remote sensing data indicates advances for crop-type classification, especially when optical data availability is limited.

Unmanned Airborne System Deployment at Turrialba Volcano for Real Time Eruptive Cloud Measurements

NASA Astrophysics Data System (ADS)

Diaz, J. A.; Pieri, D. C.; Fladeland, M. M.; Bland, G.; Corrales, E.; Alan, A., Jr.; Alegria, O.; Kolyer, R.

2015-12-01

The development of small unmanned aerial systems (sUAS) with a variety of instrument packages enables in situ and proximal remote sensing measurements of volcanic plumes, even when the active conditions of the volcano do not allow volcanologists and emergency response personnel to get too close to the erupting crater. This has been demonstrated this year by flying a sUAS through the heavy ash driven erupting volcanic cloud of Turrialba Volcano, while conducting real time in situ measurement of gases over the crater summit. The event also achieved the collection of newly released ash samples from the erupting volcano. The interception of the Turrialba ash cloud occurred during the CARTA 2015 field campaign carried out as part of an ongoing program for remote sensing satellite calibration and validation purposes, using active volcanic plumes. These deployments are timed to support overflights of the Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) onboard the NASA Terra satellite on a bimonthly basis using airborne platforms such as tethered balloons, free-flying fixed wing small UAVs at altitudes up to 12.5Kft ASL within about a 5km radius of the summit crater. The onboard instrument includes the MiniGas payload which consists of an array of single electrochemical and infrared gas detectors (SO2, H2S CO2), temperature, pressure, relative humidity and GPS sensors, all connected to an Arduino-based board, with data collected at 1Hz. Data are both stored onboard and sent by telemetry to the ground operator within a 3 km range. The UAV can also carry visible and infrared cameras as well as other payloads, such as a UAV-MS payload that is currently under development for mass spectrometer-based in situ measurements. The presentation describes the ongoing UAV- based in situ remote sensing validation program at Turrialba Volcano, the results of a fly-through the eruptive cloud, as well as future plans to continue these efforts. Work presented here was carried out, in part, at the Jet Propulsion Laboratory, California Institute of Technology, under contract to NASA.

Validation of the FALL3D ash dispersion model using observations of the 2010 Eyjafjallajökull volcanic ash clouds

NASA Astrophysics Data System (ADS)

Folch, A.; Costa, A.; Basart, S.

2012-03-01

During April-May 2010 volcanic ash clouds from the Icelandic Eyjafjallajökull volcano reached Europe causing an unprecedented disruption of the EUR/NAT region airspace. Civil aviation authorities banned all flight operations because of the threat posed by volcanic ash to modern turbine aircraft. New quantitative airborne ash mass concentration thresholds, still under discussion, were adopted for discerning regions contaminated by ash. This has implications for ash dispersal models routinely used to forecast the evolution of ash clouds. In this new context, quantitative model validation and assessment of the accuracies of current state-of-the-art models is of paramount importance. The passage of volcanic ash clouds over central Europe, a territory hosting a dense network of meteorological and air quality observatories, generated a quantity of observations unusual for volcanic clouds. From the ground, the cloud was observed by aerosol lidars, lidar ceilometers, sun photometers, other remote-sensing instruments and in-situ collectors. From the air, sondes and multiple aircraft measurements also took extremely valuable in-situ and remote-sensing measurements. These measurements constitute an excellent database for model validation. Here we validate the FALL3D ash dispersal model by comparing model results with ground and airplane-based measurements obtained during the initial 14-23 April 2010 Eyjafjallajökull explosive phase. We run the model at high spatial resolution using as input hourly-averaged observed heights of the eruption column and the total grain size distribution reconstructed from field observations. Model results are then compared against remote ground-based and in-situ aircraft-based measurements, including lidar ceilometers from the German Meteorological Service, aerosol lidars and sun photometers from EARLINET and AERONET networks, and flight missions of the German DLR Falcon aircraft. We find good quantitative agreement, with an error similar to the spread in the observations (however depending on the method used to estimate mass eruption rate) for both airborne and ground mass concentration. Such verification results help us understand and constrain the accuracy and reliability of ash transport models and it is of enormous relevance for designing future operational mitigation strategies at Volcanic Ash Advisory Centers.

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

NASA Astrophysics Data System (ADS)

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

2009-04-01

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

Pseudorandom Noise Code-Based Technique for Thin Cloud Discrimination with CO2 and O2 Absorption Measurements

NASA Technical Reports Server (NTRS)

Campbell, Joel F.; Prasad, Narasimha S.; Flood, Michael A.

2011-01-01

NASA Langley Research Center is working on a continuous wave (CW) laser based remote sensing scheme for the detection of CO2 and O2 from space based platforms suitable for ACTIVE SENSING OF CO2 EMISSIONS OVER NIGHTS, DAYS, AND SEASONS (ASCENDS) mission. ASCENDS is a future space-based mission to determine the global distribution of sources and sinks of atmospheric carbon dioxide (CO2). A unique, multi-frequency, intensity modulated CW (IMCW) laser absorption spectrometer (LAS) operating at 1.57 micron for CO2 sensing has been developed. Effective aerosol and cloud discrimination techniques are being investigated in order to determine concentration values with accuracies less than 0.3%. In this paper, we discuss the demonstration of a pseudo noise (PN) code based technique for cloud and aerosol discrimination applications. The possibility of using maximum length (ML)-sequences for range and absorption measurements is investigated. A simple model for accomplishing this objective is formulated, Proof-of-concept experiments carried out using SONAR based LIDAR simulator that was built using simple audio hardware provided promising results for extension into optical wavelengths.

NARVAL North - Remote Sensing of Postfrontal Convective Clouds and Precipitation over the North Atlantic with the Research Aircraft HALO

NASA Astrophysics Data System (ADS)

Klepp, Christian; Ament, Felix; Bakan, Stephan; Crewell, Susanne; Hagen, Martin; Hirsch, Lutz; Jansen, Friedhelm; Konow, Heike; Mech, Mario; Pfeilsticker, Klaus; Schäfler, Andreas; Stevens, Bjorn

2014-05-01

The new German research aircraft HALO (High Altitude and Long Range Research Aircraft) became recently available for measurement flights in atmospheric research. It's capacity of measuring from a high altitude vertical profiles of all components of atmospheric water - like vapor, liquid and ice, in both cloud and precipitation forms, as well as the aerosol particles upon which cloud droplets form - makes it a unique research platform. The aircraft, equipped with advanced radiometers, radar and lidar technology, the HALO Microwave Package (HAMP), is an initiative by German climate and environmental research institutions and is operated by the German Aerospace Center (DLR). One of the first major missions to exploit the capabilities of HALO was conducted for the NARVAL project (Next-generation Aircraft Remote-Sensing for Validation Studies) during January 2014. After studying subtropical clouds one month before in the first NARVAL phase, the interest of NARVAL North focused on the study of cold air convection and precipitation in the form of rain and snow. Based at Keflavik airport (Iceland), several flights were conducted to examine the specific small-scale precipitation structures behind the backsides of cold fronts over the North Atlantic. This should help to narrow the gap in the understanding of substantial differences between satellite observations and model calculations in such situations. First data analysis of these measurements indicate promising results. The poster will describe the HALO instrument packages as well as the collected observations during the campaign and will present preliminary scientific findings.

Volcanic plumes fast detection: a methodological proposal for an integrated approach

NASA Astrophysics Data System (ADS)

Bernabeo, R. Alberto; Tositti, Laura; Brattich, Erika

2017-04-01

The behaviour of erupting volcanoes ranges from the quiet, steady effusion of lava to highly explosive eruptions. Therefore volcanic eruptions may present a direct threat to the safety of aircraft in flight and major operational difficulties at aerodromes and in airspaces located downwind the resulting volcanic ash cloud, in particular when eruptions are of high intensity and/or prolonged. Since volcanic ash clouds and gases are not displayed on either airborne or ATC radar and are extremely difficult to identify at night, pilots must rely on reports from air traffic controllers and from other pilots to determine the location of an ash cloud or gases. As a result, there is a clear need to develop extra tools enabling the timely on-board sensing of volcanic plumes for the sake of safety purposes. Large scale eruptions may eject many cubic kilometres of glass particles and pulverized rock (volcanic ash) as well as corrosive/hazardous gases high into the atmosphere, potentially over a wide area for timescales ranging from hours to weeks or even months. Volcanic ash consists mostly of sharp-edged, hard glass particles and pulverized rock. It is very abrasive and, being largely composed of siliceous materials, has a melting temperature below the operating temperature of modern turbine engines at cruise thrust. A volcanic plume in fact contains a complex mixture of water vapour, sulphur dioxide (producing sulphuric acid as a result of gas-to particle conversions reaction catalysed by iron in cloud droplets), chlorine and other halogens, and trace elements which are highly reactive and may interact with the mineral particles to produce corrosive effects hazardous to both airframes and human health. Remotely piloted aircraft system (RPAS) or Unmanned aerial vehicles (UAV) are slowly becoming efficient platforms - with dedicated miniaturized sensors that can be used in scientific/commercial remote sensing applications - and are of fundamental support to the planning, running and control of the territory in which public safety is or may be at risk, and with reference to all those subjects that require a continuous cyclical process of observation, evaluation and interpretation. At the same time, a better knowledge of the chemical properties of volcanic emissions is a must for the future expansion foreseen in the next coming years in air transportation, for the health hazards that a volcanic ash cloud poses around the world and for a better understanding of the reduction already observed in GPS/GNSS satellite signals anytime a volcanic cloud covers the sky (thus obscuring the signal used by the navigation systems of modern aircraft), with associated safety risks. In this paper we propose a multitasking experimental approach based on the integrated use of remote sensing, aerosol sampling and chemical speciation together with the use of drones/tethered balloons equipped with aerosol sensors aimed at providing all the information which have been collected partially so far. The study will also collect information about the 3D distribution of all the aerosol properties described before with the aim of determining and helping the vertical resolution of data from remote sensing.

Stratocumulus Precipitation and Entrainment Experiment (SPEE) Field Campaign Report

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

Albrecht, Bruce; Ghate, Virendra; CADeddu, Maria

2016-06-01

The scientific focus of this project was to examine precipitation and entrainment processes in marine stratocumulus clouds. The entrainment studies focused on characterizing cloud turbulence at cloud top using Doppler cloud radar observations. The precipitation studies focused on characterizing the precipitation and the macroscopic properties (cloud thickness, and liquid water path) of the clouds. This project will contribute to the U.S. Department of Energy (DOE) Atmospheric Radiation Measurement (ARM) Climate Research Facility’s overall objective of providing the remote-sensing observations needed to improve the representation of key cloud processes in climate models. It will be of direct relevance to the componentsmore » of ARM dealing with entrainment and precipitation processes in stratiform clouds. Further, the radar observing techniques that will be used in this study were developed using ARM Southern Great Plains (SGP) facility observations under Atmospheric System Research (ASR) support. The observing systems operating automatously from a site located just north of the Center for Interdisciplinary Remotely-Piloted Aircraft Studies (CIRPAS) aircraft hangar in Marina, California during the period of 1 May to 4 November 2015 included: 1. Microwave radiometer: ARM Microwave Radiometer, 3-Channel (MWR3C) with channels centered at 23.834, 30, and 89 GHz; supported by Dr. Maria Cadeddu. 2. Cloud Radar: CIRPAS 95 GHz Frequency Modulated Continuous Wave (FMCW) Cloud Radar (Centroid Frequency Chirp Rate [CFCR]); operations overseen by Drs. Ghate and Albrecht. 3. Ceilometer: Vaisala CK-14; operations overseen by Drs. Ghate and Albrecht.« less

Ubiquity and impact of thin mid-level clouds in the tropics

PubMed Central

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.

PubMed

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.

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.

An intercomparison of remotely sensed soil moisture products at various spatial scales over the Iberian penisula

USDA-ARS?s Scientific Manuscript database

Soil moisture (SM) can be retrieved from active microwave (AM)-, passive microwave (PM)- and thermal infrared (TIR)-observations, each having their unique spatial- and temporal-coverage. A limitation of TIR-based SM retrievals is its dependency on cloud-free conditions, while microwave retrievals ar...

Remote sensing of rain over the ocean

NASA Technical Reports Server (NTRS)

1978-01-01

Computer models of the microwave emission from the earth's atmosphere were used to study the problem of retrieving meteorological information from the SMMR instrument that will be flown on NIMBUS-G. Methods for retrieving rain rate, wind speed, cloud height, and ocean temperature are described for the case when the satellite is over the ocean.

Automatic 3D Building Detection and Modeling from Airborne LiDAR Point Clouds

ERIC Educational Resources Information Center

Sun, Shaohui

2013-01-01

Urban reconstruction, with an emphasis on man-made structure modeling, is an active research area with broad impact on several potential applications. Urban reconstruction combines photogrammetry, remote sensing, computer vision, and computer graphics. Even though there is a huge volume of work that has been done, many problems still remain…

Refining FIA plot locations using LiDAR point clouds

Treesearch

Charlie Schrader-Patton; Greg C. Liknes; Demetrios Gatziolis; Brian M. Wing; Mark D. Nelson; Patrick D. Miles; Josh Bixby; Daniel G. Wendt; Dennis Kepler; Abbey Schaaf

2015-01-01

Forest Inventory and Analysis (FIA) plot location coordinate precision is often insufficient for use with high resolution remotely sensed data, thereby limiting the use of these plots for geospatial applications and reducing the validity of models that assume the locations are precise. A practical and efficient method is needed to improve coordinate precision. To...

Building damage assessment using airborne lidar

NASA Astrophysics Data System (ADS)

Axel, Colin; van Aardt, Jan

2017-10-01

The assessment of building damage following a natural disaster is a crucial step in determining the impact of the event itself and gauging reconstruction needs. Automatic methods for deriving damage maps from remotely sensed data are preferred, since they are regarded as being rapid and objective. We propose an algorithm for performing unsupervised building segmentation and damage assessment using airborne light detection and ranging (lidar) data. Local surface properties, including normal vectors and curvature, were used along with region growing to segment individual buildings in lidar point clouds. Damaged building candidates were identified based on rooftop inclination angle, and then damage was assessed using planarity and point height metrics. Validation of the building segmentation and damage assessment techniques were performed using airborne lidar data collected after the Haiti earthquake of 2010. Building segmentation and damage assessment accuracies of 93.8% and 78.9%, respectively, were obtained using lidar point clouds and expert damage assessments of 1953 buildings in heavily damaged regions. We believe this research presents an indication of the utility of airborne lidar remote sensing for increasing the efficiency and speed at which emergency response operations are performed.

Surface spectral emissivity derived from MODIS data

NASA Astrophysics Data System (ADS)

Chen, Yan; Sun-Mack, Sunny; Minnis, Patrick; Smith, William L.; Young, David F.

2003-04-01

Surface emissivity is essential for many remote sensing applications including the retrieval of the surface skin temperature from satellite-based infrared measurements, determining thresholds for cloud detection and for estimating the emission of longwave radiation from the surface, an important component of the energy budget of the surface-atmosphere interface. In this paper, data from the Terra MODIS (MODerate-resolution Imaging Spectroradiometer) taken at 3.7, 8.5, 10.8, 12.0 micron are used to simultaneously derive the skin temperature and the surface emissivities at the same wavelengths. The methodology uses separate measurements of the clear-sky temperatures that are determined by the CERES (Clouds and Earth's Radiant Energy System) scene classification in each channel during the daytime and at night. The relationships between the various channels at night are used during the day when solar reflectance affects the 3.7 micron data. A set of simultaneous equations is then solved to derive the emissivities. Global results are derived from MODIS. Numerical weather analyses are used to provide soundings for correcting the observed radiances for atmospheric absorption. These results are verified and will be available for remote sensing applications.

Retrieval of mass and sizes of particles in sandstorms using two MODIS IR bands: A case study of April 7, 2001 sandstorm in China

NASA Astrophysics Data System (ADS)

Gu, Yingxin; Rose, William I.; Bluth, Gregg J. S.

2003-08-01

A thermal infrared remote sensing retrieval method developed by Wen and Rose [1994], which retrieves particle sizes, optical depth, and total masses of silicate particles in the volcanic cloud, was applied to an April 07, 2001 sandstorm over northern China, using MODIS. Results indicate that the area of the dust cloud observed was 1.34 million km2, the mean particle radius of the dust was 1.44 μm, and the mean optical depth at 11 μm was 0.79. The mean burden of dust was approximately 4.8 tons/km2 and the main portion of the dust storm on April 07, 2001 contained 6.5 million tons of dust. The results are supported by both independent remote sensing data (TOMS) and in situ data for a similar event in 1998. This paper demonstrates that Wen and Rose's retrieval method could be successfully applied to past and future sandstorm events using IR channels of AVHRR, GOES or MODIS.

a Gross Error Elimination Method for Point Cloud Data Based on Kd-Tree

NASA Astrophysics Data System (ADS)

Kang, Q.; Huang, G.; Yang, S.

2018-04-01

Point cloud data has been one type of widely used data sources in the field of remote sensing. Key steps of point cloud data's pro-processing focus on gross error elimination and quality control. Owing to the volume feature of point could data, existed gross error elimination methods need spend massive memory both in space and time. This paper employed a new method which based on Kd-tree algorithm to construct, k-nearest neighbor algorithm to search, settled appropriate threshold to determine with result turns out a judgement that whether target point is or not an outlier. Experimental results show that, our proposed algorithm will help to delete gross error in point cloud data and facilitate to decrease memory consumption, improve efficiency.

@KarlTheFog has been mapped!

USGS Publications Warehouse

Torregrosa, Alicia

2016-01-01

Within the world of mapping, clouds are a pesky interference to be removed from satellite remote sensed imagery.  However, to many of us, that is a waste of pixels. Cloud maps are becoming increasingly valuable in the quest to understand land cover change and surface processes. In coastal California, the dynamic summertime interactions between air masses, the ocean, and topography result in blankets of fog and low clouds flowing into low lying areas of the San Francisco Bay Area. The low clouds and fog advected from the Pacific bring moisture and shade to coastal ecosystems. This acts to reduce temperatures and evapotranspiration stress during the otherwise arid Mediterranean climate season, in turn impacting vegetation distribution, irrigation needs, and urban energy consumption.

Mineralogy and Astrobiology Detection Using Laser Remote Sensing Instrument

NASA Technical Reports Server (NTRS)

Abedin, M. Nurul; Bradley, Arthur T.; Sharma, Shiv K.; Misra, Anupam K.; Lucey, Paul G.; Mckay, Chistopher P.; Ismail, Syed; Sandford, Stephen P.

2015-01-01

A multispectral instrument based on Raman, laser-induced fluorescence (LIF), laser-induced breakdown spectroscopy (LIBS), and a lidar system provides high-fidelity scientific investigations, scientific input, and science operation constraints in the context of planetary field campaigns with the Jupiter Europa Robotic Lander and Mars Sample Return mission opportunities. This instrument conducts scientific investigations analogous to investigations anticipated for missions to Mars and Jupiter's icy moons. This combined multispectral instrument is capable of performing Raman and fluorescence spectroscopy out to a >100 m target distance from the rover system and provides single-wavelength atmospheric profiling over long ranges (>20 km). In this article, we will reveal integrated remote Raman, LIF, and lidar technologies for use in robotic and lander-based planetary remote sensing applications. Discussions are focused on recently developed Raman, LIF, and lidar systems in addition to emphasizing surface water ice, surface and subsurface minerals, organics, biogenic, biomarker identification, atmospheric aerosols and clouds distributions, i.e., near-field atmospheric thin layers detection for next robotic-lander based instruments to measure all the above-mentioned parameters. OCIS codes: (120.0280) Remote sensing and sensors; (130.0250) Optoelectronics; (280.3640) Lidar; (300.2530) Fluorescence, laser-induced; (300.6450) Spectroscopy, Raman; (300.6365) Spectroscopy, laser induced breakdown

Biogenic influence on cloud microphysics in the 'clean' oceanic atmosphere

NASA Astrophysics Data System (ADS)

Lana, A.; Simó, R.; Vallina, S. M.; Jurado, E.; Dachs, J.

2009-12-01

A 20 years old hypothesis postulates a feedback relationship between marine biota and climate through the emission of dimethylsulfide (DMS) as the principal natural source of Sulfate Secondary Aerosols (S-DMS) that are very efficient as cloud condensation nuclei (CCN). In recent years, the biological influence on cloud microphysics have been expanded to other potential biogenic cloud precursors: (i) volatile organic compounds produced by plankton and emitted to the atmosphere to form Secondary Organic Aerosols (SOA); (ii) biological particles and biogenic polymers, lifted with the seaspray by wind friction and bubble-bursting processes, that act as Primary Organic Aerosols (POA). Besides these biogenic aerosols, also seaspray-associated Sea Salt (SS) emissions, which are the dominant contribution to aerosol mass in the remote mixed boundary layer, also contribute to cloud condensation. All these aerosols affect cloud microphysics by providing new CCN, reducing the size of cloud droplets, and increasing cloud albedo. We have compared the seasonalities of the parameterized source functions of these natural cloud precursors with that of the satellite-derived cloud droplet effective radius (CLEFRA) over large regions of the ocean. Regions where big loads of continental aerosols (including anthropogenic -industrial, urban, and biomass burning) dominate during a significant part of the year were identified by use of remote sensing aerosol optical properties and excluded from our analysis. Our results show that the seasonality of cloud droplet effective radius matches those of S-DMS and SOA in the clean marine atmosphere, whereas SS and chlorophyll-associated POA on their own do not seem to play a major role in driving cloud droplet size.

Predicting and validating the motion of an ash cloud during the 2006 eruption of Mount Augustine volcano

USGS Publications Warehouse

Collins, Richard L.; Fochesatto, Javier; Sassen, Kenneth; Webley, Peter W.; Atkinson, David E.; Dean, Kenneson G.; Cahill, Catherine F.; Mizutani, Kohei

2007-01-01

On 11 January 2006, Mount Augustine volcano in southern Alaska began erupting after 20- year repose. The Anchorage Forecast Office of the National Weather Service (NWS) issued an advisory on 28 January for Kodiak City. On 31 January, Alaska Airlines cancelled all flights to and from Anchorage after multiple advisories from the NWS for Anchorage and the surrounding region. The Alaska Volcano Observatory (AVO) had reported the onset of the continuous eruption. AVO monitors the approximately 100 active volcanoes in the Northern Pacific. Ash clouds from these volcanoes can cause serious damage to an aircraft and pose a serious threat to the local communities, and to transcontinental air traffic throughout the Arctic and sub-Arctic region. Within AVO, a dispersion model has been developed to track the dispersion of volcanic ash clouds. The model, Puff, was used operational by AVO during the Augustine eruptive period. Here, we examine the dispersion of a volcanic ash (or aerosol) cloud from Mount Augustine across Alaska from 29 January through the 2 February 2006. We present the synoptic meteorology, the Puff predictions, and measurements from aerosol samplers, laser radar (or lidar) systems, and satellites. Aerosol samplers revealed the presence of volcanic aerosols at the surface at sites where Puff predicted the ash clouds movement. Remote sensing satellite data showed the development of the ash cloud in close proximity to the volcano consistent with the Puff predictions. Two lidars showed the presence of volcanic aerosol with consistent characteristics aloft over Alaska and were capable of detecting the aerosol, even in the presence of scattered clouds and where the ash cloud is too thin/disperse to be detected by remote sensing satellite data. The lidar measurements revealed the different trajectories of ash consistent with the Puff predictions. Dispersion models provide a forecast of volcanic ash cloud movement that might be undetectable by any other means but are still a significant hazard. Validation is the key to assessing the accuracy of any predictions. The study highlights the use of multiple and complementary observations used in detecting the trajectory ash cloud, both at the surface and aloft in the atmosphere.

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

Webley, Peter W.; Atkinson, D.; Collins, Richard L.

On 11 January 2006, Mount Augustine volcano in southern Alaska began erupting after 20-year repose. The Anchorage Forecast Office of the National Weather Service (NWS) issued an advisory on 28 January for Kodiak City. On 31 January, Alaska Airlines cancelled all flights to and from Anchorage after multiple advisories from the NWS for Anchorage and the surrounding region. The Alaska Volcano Observatory (AVO) had reported the onset of the continuous eruption. AVO monitors the approximately 100 active volcanoes in the Northern Pacific. Ash clouds from these volcanoes can cause serious damage to an aircraft and pose a serious threat tomore » the local communities, and to transcontinental air traffic throughout the Arctic and sub-Arctic region. Within AVO, a dispersion model has been developed to track the dispersion of volcanic ash clouds. The model, Puff, was used operational by AVO during the Augustine eruptive period. Here, we examine the dispersion of a volcanic ash cloud from Mount Augustine across Alaska from 29 January through the 2 February 2006. We present the synoptic meteorology, the Puff predictions, and measurements from aerosol samplers, laser radar (or lidar) systems, and satellites. UAF aerosol samplers revealed the presence of volcanic aerosols at the surface at sites where Puff predicted the ash clouds movement. Remote sensing satellite data showed the development of the ash cloud in close proximity to the volcano and a sulfur-dioxide cloud further from the volcano consistent with the Puff predictions. Lidars showed the presence of volcanic aerosol with consistent characteristics aloft over Alaska and were capable of detecting the aerosol, even in the presence of scattered clouds and where the cloud is too thin/disperse to be detected by remote sensing satellite data. The lidar measurements revealed the different trajectories of ash consistent with the Puff predictions. Dispersion models provide a forecast of volcanic ash cloud movement that might be undetectable by any other means but are still a significant hazard. Validation is the key to assessing the accuracy of any future predictions. The study highlights the use of multiple and complementary observations used in detecting the trajectory ash cloud, both at the surface and aloft within the atmosphere.« less

Microwave remote sensing from space

NASA Technical Reports Server (NTRS)

Carver, K. R.; Elachi, C.; Ulaby, F. T.

1985-01-01

Spaceborne microwave remote sensors provide perspectives of the earth surface and atmosphere which are of unique value in scientific studies of geomorphology, oceanic waves and topography, atmospheric water vapor and temperatures, vegetation classification and stress, ice types and dynamics, and hydrological characteristics. Microwave radars and radiometers offer enhanced sensitivities to the geometrical characteristics of the earth's surface and its cover, to water in all its forms - soil and vegetation moisture, ice, wetlands, oceans, and atmospheric water vapor, and can provide high-resolution imagery of the earth's surface independent of cloud cover or sun angle. A brief review of the historical development and principles of active and passive microwave remote sensing is presented, with emphasis on the unique characteristics of the information obtainable in the microwave spectrum and the value of this information to global geoscientific studies. Various spaceborne microwave remote sensors are described, with applications to geology, planetology, oceanography, glaciology, land biology, meteorology, and hydrology. A discussion of future microwave remote sensor technological developments and challenges is presented, along with a summary of future missions being planned by several countries.

Estimation of rainfall using remote sensing for Riyadh climate, KSA

NASA Astrophysics Data System (ADS)

AlHassoun, Saleh A.

2013-05-01

Rainfall data constitute an important parameter for studying water resources-related problems. Remote sensing techniques could provide rapid and comprehensive overview of the rainfall distribution in a given area. Thus, the infrared data from the LandSat satellite in conjunction with the Scofield-oliver method were used to monitor and model rainfall in Riyadh area as a resemble of any area in the Kingdom of Saudi Arabia(KSA). Four convective clouds that covered two rain gage stations were analyzed. Good estimation of rainfall was obtained from satellite images. The results showed that the satellite rainfall estimations were well correlated to rain gage measurements. The satellite climate data appear to be useful for monitoring and modeling rainfall at any area where no rain gage is available.

Director's Discretionary Fund Report for Fiscal Year 1996

NASA Technical Reports Server (NTRS)

1997-01-01

Topics covered include: Waterproofing the Space Shuttle tiles, thermal protection system for Reusable Launch Vehicles, computer modeling of the thermal conductivity of cometary ice, effects of ozone depletion and ultraviolet radiation on plants, a novel telemetric biosensor to monitor blood pH on-line, ion mobility in polymer electrolytes for lithium-polymer batteries, a microwave-pumped far infrared photoconductor, and a new method for measuring cloud liquid vapor using near infrared remote sensing. Also included: laser-spectroscopic instrument for turbulence measurement, remote sensing of aircraft contrails using a field portable imaging interferometer, development of a silicon-micromachined gas chromatography system for determination of planetary surface composition, planar Doppler velocimetry, chaos in interstellar chemistry, and a limited pressure cycle engine for high-speed output.

Effect of Clouds on Apertures of Space-based Air Fluorescence Detectors

NASA Technical Reports Server (NTRS)

Sokolsky, P.; Krizmanic, J.

2003-01-01

Space-based ultra-high-energy cosmic ray detectors observe fluorescence light from extensive air showers produced by these particles in the troposphere. Clouds can scatter and absorb this light and produce systematic errors in energy determination and spectrum normalization. We study the possibility of using IR remote sensing data from MODIS and GOES satellites to delimit clear areas of the atmosphere. The efficiency for detecting ultra-high-energy cosmic rays whose showers do not intersect clouds is determined for real, night-time cloud scenes. We use the MODIS SST cloud mask product to define clear pixels for cloud scenes along the equator and use the OWL Monte Carlo to generate showers in the cloud scenes. We find the efficiency for cloud-free showers with closest approach of three pixels to a cloudy pixel is 6.5% exclusive of other factors. We conclude that defining a totally cloud-free aperture reduces the sensitivity of space-based fluorescence detectors to unacceptably small levels.

Vertical variation of ice particle size in convective cloud tops.

PubMed

van Diedenhoven, Bastiaan; Fridlind, Ann M; Cairns, Brian; Ackerman, Andrew S; Yorks, John E

2016-05-16

A novel technique is used to estimate derivatives of ice effective radius with respect to height near convective cloud tops ( dr e / dz ) from airborne shortwave reflectance measurements and lidar. Values of dr e / dz are about -6 μ m/km for cloud tops below the homogeneous freezing level, increasing to near 0 μ m/km above the estimated level of neutral buoyancy. Retrieved dr e / dz compares well with previously documented remote sensing and in situ estimates. Effective radii decrease with increasing cloud top height, while cloud top extinction increases. This is consistent with weaker size sorting in high, dense cloud tops above the level of neutral buoyancy where fewer large particles are present, and with stronger size sorting in lower cloud tops that are less dense. The results also confirm that cloud-top trends of effective radius can generally be used as surrogates for trends with height within convective cloud tops. These results provide valuable observational targets for model evaluation.

Vertical Variation of Ice Particle Size in Convective Cloud Tops

NASA Technical Reports Server (NTRS)

Van Diedenhoven, Bastiaan; Fridlind, Ann M.; Cairns, Brian; Ackerman, Andrew S.; Yorks, John E.

2016-01-01

A novel technique is used to estimate derivatives of ice effective radius with respect to height near convective cloud tops (dr(sub e)/dz) from airborne shortwave reflectance measurements and lidar. Values of dr(sub e)/dz are about -6 micrometer/km for cloud tops below the homogeneous freezing level, increasing to near 0 micrometer/km above the estimated level of neutral buoyancy. Retrieved dr(sub e)/dz compares well with previously documented remote sensing and in situ estimates. Effective radii decrease with increasing cloud top height, while cloud top extinction increases. This is consistent with weaker size sorting in high, dense cloud tops above the level of neutral buoyancy where fewer large particles are present and with stronger size sorting in lower cloud tops that are less dense. The results also confirm that cloud top trends of effective radius can generally be used as surrogates for trends with height within convective cloud tops. These results provide valuable observational targets for model evaluation.

A remote sensing method for estimating regional reservoir area and evaporative loss

DOE PAGES

Zhang, Hua; Gorelick, Steven M.; Zimba, Paul V.; ...

2017-10-07

Evaporation from the water surface of a reservoir can significantly affect its function of ensuring the availability and temporal stability of water supply. Current estimations of reservoir evaporative loss are dependent on water area derived from a reservoir storage-area curve. Such curves are unavailable if the reservoir is located in a data-sparse region or questionable if long-term sedimentation has changed the original elevation-area relationship. In this paper, we propose a remote sensing framework to estimate reservoir evaporative loss at the regional scale. This framework uses a multispectral water index to extract reservoir area from Landsat imagery and estimate monthly evaporationmore » volume based on pan-derived evaporative rates. The optimal index threshold is determined based on local observations and extended to unobserved locations and periods. Built on the cloud computing capacity of the Google Earth Engine, this framework can efficiently analyze satellite images at large spatiotemporal scales, where such analysis is infeasible with a single computer. Our study involves 200 major reservoirs in Texas, captured in 17,811 Landsat images over a 32-year period. The results show that these reservoirs contribute to an annual evaporative loss of 8.0 billion cubic meters, equivalent to 20% of their total active storage or 53% of total annual water use in Texas. At five coastal basins, reservoir evaporative losses exceed the minimum freshwater inflows required to sustain ecosystem health and fishery productivity of the receiving estuaries. Reservoir evaporative loss can be significant enough to counterbalance the positive effects of impounding water and to offset the contribution of water conservation and reuse practices. Our results also reveal the spatially variable performance of the multispectral water index and indicate the limitation of using scene-level cloud cover to screen satellite images. Finally, this study demonstrates the advantage of combining satellite remote sensing and cloud computing to support regional water resources assessment.« less

A remote sensing method for estimating regional reservoir area and evaporative loss

NASA Astrophysics Data System (ADS)

Zhang, Hua; Gorelick, Steven M.; Zimba, Paul V.; Zhang, Xiaodong

2017-12-01

Evaporation from the water surface of a reservoir can significantly affect its function of ensuring the availability and temporal stability of water supply. Current estimations of reservoir evaporative loss are dependent on water area derived from a reservoir storage-area curve. Such curves are unavailable if the reservoir is located in a data-sparse region or questionable if long-term sedimentation has changed the original elevation-area relationship. We propose a remote sensing framework to estimate reservoir evaporative loss at the regional scale. This framework uses a multispectral water index to extract reservoir area from Landsat imagery and estimate monthly evaporation volume based on pan-derived evaporative rates. The optimal index threshold is determined based on local observations and extended to unobserved locations and periods. Built on the cloud computing capacity of the Google Earth Engine, this framework can efficiently analyze satellite images at large spatiotemporal scales, where such analysis is infeasible with a single computer. Our study involves 200 major reservoirs in Texas, captured in 17,811 Landsat images over a 32-year period. The results show that these reservoirs contribute to an annual evaporative loss of 8.0 billion cubic meters, equivalent to 20% of their total active storage or 53% of total annual water use in Texas. At five coastal basins, reservoir evaporative losses exceed the minimum freshwater inflows required to sustain ecosystem health and fishery productivity of the receiving estuaries. Reservoir evaporative loss can be significant enough to counterbalance the positive effects of impounding water and to offset the contribution of water conservation and reuse practices. Our results also reveal the spatially variable performance of the multispectral water index and indicate the limitation of using scene-level cloud cover to screen satellite images. This study demonstrates the advantage of combining satellite remote sensing and cloud computing to support regional water resources assessment.

A remote sensing method for estimating regional reservoir area and evaporative loss

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

Zhang, Hua; Gorelick, Steven M.; Zimba, Paul V.

Evaporation from the water surface of a reservoir can significantly affect its function of ensuring the availability and temporal stability of water supply. Current estimations of reservoir evaporative loss are dependent on water area derived from a reservoir storage-area curve. Such curves are unavailable if the reservoir is located in a data-sparse region or questionable if long-term sedimentation has changed the original elevation-area relationship. In this paper, we propose a remote sensing framework to estimate reservoir evaporative loss at the regional scale. This framework uses a multispectral water index to extract reservoir area from Landsat imagery and estimate monthly evaporationmore » volume based on pan-derived evaporative rates. The optimal index threshold is determined based on local observations and extended to unobserved locations and periods. Built on the cloud computing capacity of the Google Earth Engine, this framework can efficiently analyze satellite images at large spatiotemporal scales, where such analysis is infeasible with a single computer. Our study involves 200 major reservoirs in Texas, captured in 17,811 Landsat images over a 32-year period. The results show that these reservoirs contribute to an annual evaporative loss of 8.0 billion cubic meters, equivalent to 20% of their total active storage or 53% of total annual water use in Texas. At five coastal basins, reservoir evaporative losses exceed the minimum freshwater inflows required to sustain ecosystem health and fishery productivity of the receiving estuaries. Reservoir evaporative loss can be significant enough to counterbalance the positive effects of impounding water and to offset the contribution of water conservation and reuse practices. Our results also reveal the spatially variable performance of the multispectral water index and indicate the limitation of using scene-level cloud cover to screen satellite images. Finally, this study demonstrates the advantage of combining satellite remote sensing and cloud computing to support regional water resources assessment.« less

A Hybrid of Optical Remote Sensing and Hydrological Modeling Improves Water Balance Estimation

NASA Astrophysics Data System (ADS)

Gleason, Colin J.; Wada, Yoshihide; Wang, Jida

2018-01-01

Declining gauging infrastructure and fractious water politics have decreased available information about river flows globally. Remote sensing and water balance modeling are frequently cited as potential solutions, but these techniques largely rely on these same in-decline gauge data to make accurate discharge estimates. A different approach is therefore needed, and we here combine remotely sensed discharge estimates made via at-many-stations hydraulic geometry (AMHG) and the PCR-GLOBWB hydrological model to estimate discharge over the Lower Nile. Specifically, we first estimate initial discharges from 87 Landsat images and AMHG (1984-2015), and then use these flow estimates to tune the model, all without using gauge data. The resulting tuned modeled hydrograph shows a large improvement in flow magnitude: validation of the tuned monthly hydrograph against a historical gauge (1978-1984) yields an RMSE of 439 m3/s (40.8%). By contrast, the original simulation had an order-of-magnitude flow error. This improvement is substantial but not perfect: tuned flows have a 1-2 month wet season lag and a negative base flow bias. Accounting for this 2 month lag yields a hydrograph RMSE of 270 m3/s (25.7%). Thus, our results coupling physical models and remote sensing is a promising first step and proof of concept toward future modeling of ungauged flows, especially as developments in cloud computing for remote sensing make our method easily applicable to any basin. Finally, we purposefully do not offer prescriptive solutions for Nile management, and rather hope that the methods demonstrated herein can prove useful to river stakeholders in managing their own water.

Remote sensing for studying atmospheric aerosols in Malaysia

NASA Astrophysics Data System (ADS)

Kanniah, Kasturi D.; Kamarul Zaman, Nurul A. F.

2015-10-01

The aerosol system is Southeast Asia is complex and the high concentrations are due to population growth, rapid urbanization and development of SEA countries. Nevertheless, only a few studies have been carried out especially at large spatial extent and on a continuous basis to study atmospheric aerosols in Malaysia. In this review paper we report the use of remote sensing data to study atmospheric aerosols in Malaysia and document gaps and recommend further studies to bridge the gaps. Satellite data have been used to study the spatial and seasonal patterns of aerosol optical depth (AOD) in Malaysia. Satellite data combined with AERONET data were used to delineate different types and sizes of aerosols and to identify the sources of aerosols in Malaysia. Most of the aerosol studies performed in Malaysia was based on station-based PM10 data that have limited spatial coverage. Thus, satellite data have been used to extrapolate and retrieve PM10 data over large areas by correlating remotely sensed AOD with ground-based PM10. Realising the critical role of aerosols on radiative forcing numerous studies have been conducted worldwide to assess the aerosol radiative forcing (ARF). Such studies are yet to be conducted in Malaysia. Although the only source of aerosol data covering large region in Malaysia is remote sensing, satellite observations are limited by cloud cover, orbital gaps of satellite track, etc. In addition, relatively less understanding is achieved on how the atmospheric aerosol interacts with the regional climate system. These gaps can be bridged by conducting more studies using integrated approach of remote sensing, AERONET and ground based measurements.

A Design of a Novel Airborne Aerosol Spectrometer for Remote Sensing Validation

NASA Astrophysics Data System (ADS)

Adler, G. A.; Brock, C. A.; Dube, W. P.; Erdesz, F.; Gordon, T.; Law, D. C.; Manfred, K.; Mason, B. J.; McLaughlin, R. J.; Richardson, M.; Wagner, N. L.; Washenfelder, R. A.; Murphy, D. M.

2016-12-01

Aerosols and their effect on the radiative properties of clouds contribute one of the largest sources of uncertainty to the Earth's energy budget. Many current global assessments, of atmospheric aerosol radiative forcing rely heavily on remote sensing observation; therefore, in situ aircraft and ground-based measurements are essential for validation of remote sensing measurements. Cavity ringdown spectrometers (CRD) measure aerosol extinction and are commonly used to validate remote sensing observations. These instruments have been deployed on aircraft based platforms over the years thus providing the opportunity to measure these properties over large areas in various conditions. However, deployment of the CRD on an aircraft platform has drawbacks. Typically, aircraft based CRDs draw sampled aerosol into a cabin based instrument through long lengths of tubing. This limits the ability of the instrument to measure: 1) Course mode aerosols (e.g. dust) 2) Aerosols at high relative humidity (above 90%) Here we describe the design of a novel aircraft based open path CRD. The open path CRD is intended to be mounted external to the cabin and has no sample tubing for aerosol delivery, thus measuring optical properties of all aerosol at the ambient conditions. However, the design of an open path CRD for operation on a wing-mounted aircraft platform has certain design complexities. The instrument's special design features include 2 CRD channels, 2 airfoils around the open Path CRD and a configuration which could be easily aligned and rigid at the same time. This novel implementation of cavity ringdown spectroscopy will provide a better assessment of the accuracy of remote sensing satellite measurements

Laser Doppler velocimeter aerial spray measurements

NASA Technical Reports Server (NTRS)

Zalay, A. D.; Eberle, W. R.; Howle, R. E.; Shrider, K. R.

1978-01-01

An experimental research program for measuring the location, spatial extent, and relative concentration of airborne spray clouds generated by agricultural aircraft is described. The measurements were conducted with a ground-based laser Doppler velocimeter. The remote sensing instrumentation, experimental tests, and the results of the flight tests are discussed. The cross section of the aerial spray cloud and the observed location, extent, and relative concentration of the airborne particulates are presented. It is feasible to use a mobile laser Doppler velocimeter to track and monitor the transport and dispersion of aerial spray generated by an agricultural aircraft.

Aerosol and cloud observations from the Lidar In-space Technology Experiment

NASA Technical Reports Server (NTRS)

Winker, D. M.

1995-01-01

The Lidar In-Space Technology Experiment (LITE) is a backscatter lidar built by NASA Langley Research Center to fly on the Space Shuttle. The purpose of the program was to develop the engineering processes required for space lidar and to demonstrate applications of space lidar to remote sensing of the atmosphere. The instrument was flown on Discovery in September 1994. Global observations of clouds and aerosols were made between the latitudes of 57 deg N and 57 deg S during 10 days of the mission.

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

Riihimaki, L.; McFarlane, S.; Sivaraman, C.

The ndrop_mfrsr value-added product (VAP) provides an estimate of the cloud droplet number concentration of overcast water clouds retrieved from cloud optical depth from the multi-filter rotating shadowband radiometer (MFRSR) instrument and liquid water path (LWP) retrieved from the microwave radiometer (MWR). When cloud layer information is available from vertically pointing lidar and radars in the Active Remote Sensing of Clouds (ARSCL) product, the VAP also provides estimates of the adiabatic LWP and an adiabatic parameter (beta) that indicates how divergent the LWP is from the adiabatic case. quality control (QC) flags (qc_drop_number_conc), an uncertainty estimate (drop_number_conc_toterr), and a cloudmore » layer type flag (cloud_base_type) are useful indicators of the quality and accuracy of any given value of the retrieval. Examples of these major input and output variables are given in sample plots in section 6.0.« less

Augmenting Satellite Precipitation Estimation with Lightning Information

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

Mahrooghy, Majid; Anantharaj, Valentine G; Younan, Nicolas H.

2013-01-01

We have used lightning information to augment the Precipitation Estimation from Remotely Sensed Imagery using an Artificial Neural Network - Cloud Classification System (PERSIANN-CCS). Co-located lightning data are used to segregate cloud patches, segmented from GOES-12 infrared data, into either electrified (EL) or non-electrified (NEL) patches. A set of features is extracted separately for the EL and NEL cloud patches. The features for the EL cloud patches include new features based on the lightning information. The cloud patches are classified and clustered using self-organizing maps (SOM). Then brightness temperature and rain rate (T-R) relationships are derived for the different clusters.more » Rain rates are estimated for the cloud patches based on their representative T-R relationship. The Equitable Threat Score (ETS) for daily precipitation estimates is improved by almost 12% for the winter season. In the summer, no significant improvements in ETS are noted.« less

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

NASA Astrophysics Data System (ADS)

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

2017-09-01

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

IPRT polarized radiative transfer model intercomparison project - Three-dimensional test cases (phase B)

NASA Astrophysics Data System (ADS)

Emde, Claudia; Barlakas, Vasileios; Cornet, Céline; Evans, Frank; Wang, Zhen; Labonotte, Laurent C.; Macke, Andreas; Mayer, Bernhard; Wendisch, Manfred

2018-04-01

Initially unpolarized solar radiation becomes polarized by scattering in the Earth's atmosphere. In particular molecular scattering (Rayleigh scattering) polarizes electromagnetic radiation, but also scattering of radiation at aerosols, cloud droplets (Mie scattering) and ice crystals polarizes. Each atmospheric constituent produces a characteristic polarization signal, thus spectro-polarimetric measurements are frequently employed for remote sensing of aerosol and cloud properties. Retrieval algorithms require efficient radiative transfer models. Usually, these apply the plane-parallel approximation (PPA), assuming that the atmosphere consists of horizontally homogeneous layers. This allows to solve the vector radiative transfer equation (VRTE) efficiently. For remote sensing applications, the radiance is considered constant over the instantaneous field-of-view of the instrument and each sensor element is treated independently in plane-parallel approximation, neglecting horizontal radiation transport between adjacent pixels (Independent Pixel Approximation, IPA). In order to estimate the errors due to the IPA approximation, three-dimensional (3D) vector radiative transfer models are required. So far, only a few such models exist. Therefore, the International Polarized Radiative Transfer (IPRT) working group of the International Radiation Commission (IRC) has initiated a model intercomparison project in order to provide benchmark results for polarized radiative transfer. The group has already performed an intercomparison for one-dimensional (1D) multi-layer test cases [phase A, 1]. This paper presents the continuation of the intercomparison project (phase B) for 2D and 3D test cases: a step cloud, a cubic cloud, and a more realistic scenario including a 3D cloud field generated by a Large Eddy Simulation (LES) model and typical background aerosols. The commonly established benchmark results for 3D polarized radiative transfer are available at the IPRT website (http://www.meteo.physik.uni-muenchen.de/ iprt).

Alaska Volcano Observatory's satellite remote sensing of the Okmok and Kasatochi 2008 eruptions

NASA Astrophysics Data System (ADS)

Dean, K.; Webley, P. W.; Lovick, J.; Puchrik, R.; Bailey, J. E.; Dehn, J.; Valcic, L.

2008-12-01

In July and August 2008, Okmok and Kasatochi volcanoes erupted explosively, both sending ash clouds up to 15 km above sea level (ASL). Okmok volcano last showed signs of volcanic activity in 1997 and Kasatochi in 1899, and then only with suggested steaming. Prior to erupting neither eruption showed any thermal precursors in infrared satellite data, as is common for Aleutian volcanoes. Okmok volcano (53.4 N, 168.2 W, 1073 m ASL) erupted on July 12 at 19:43 UTC, with a phreatomagmatic eruption and within a few hours the ash cloud had reached several 100 km from the volcano. The initial ash cloud reached 16 km ASL, effecting air traffic in the region and caused evacuations of local communities. By July 13, the eruption showed a bifurcated plume with the ash portions at lower elevations than the water rich portion. Kasatochi volcano (52.17 N, 175.51 W, 314 m ASL) erupted on August 7 at approx 22:00 UTC, with two more explosive events on August 8 at 02:00 and 04:35 UTC. The initial plume heights for these events were from 12 to 15 km ASL. From August 7 to 11, the volcanic ash cloud was seen to track across the northeastern portion of the Pacific Ocean and in combination with the sulfur dioxide detected cloud and dispersion modeling predictions resulted in cancellations of numerous flights into Alaska. Here, we show the remote sensing data collected during these two volcanic eruptions, illustrating the strength of the ash signal during the Kasatochi event and also the effect the water rich plume had on the ash detection during the beginning of the Okmok eruption.

The Hico Image Processing System: A Web-Accessible Hyperspectral Remote Sensing Toolbox

NASA Astrophysics Data System (ADS)

Harris, A. T., III; Goodman, J.; Justice, B.

2014-12-01

As the quantity of Earth-observation data increases, the use-case for hosting analytical tools in geospatial data centers becomes increasingly attractive. To address this need, HySpeed Computing and Exelis VIS have developed the HICO Image Processing System, a prototype cloud computing system that provides online, on-demand, scalable remote sensing image processing capabilities. The system provides a mechanism for delivering sophisticated image processing analytics and data visualization tools into the hands of a global user community, who will only need a browser and internet connection to perform analysis. Functionality of the HICO Image Processing System is demonstrated using imagery from the Hyperspectral Imager for the Coastal Ocean (HICO), an imaging spectrometer located on the International Space Station (ISS) that is optimized for acquisition of aquatic targets. Example applications include a collection of coastal remote sensing algorithms that are directed at deriving critical information on water and habitat characteristics of our vulnerable coastal environment. The project leverages the ENVI Services Engine as the framework for all image processing tasks, and can readily accommodate the rapid integration of new algorithms, datasets and processing tools.

Atmospheric Radiative Transfer for Satellite Remote Sensing: Validation and Uncertainty

NASA Technical Reports Server (NTRS)

Marshak, Alexander

2007-01-01

My presentation will begin with the discussion of the Intercomparison of three-dimensional (3D) Radiative Codes (13RC) project that has been started in 1997. I will highlight the question of how well the atmospheric science community can solve the 3D radiative transfer equation. Initially I3RC was focused only on algorithm intercomparison; now it has acquired a broader identity providing new insights and creating new community resources for 3D radiative transfer calculations. Then I will switch to satellite remote sensing. Almost all radiative transfer calculations for satellite remote sensing are one-dimensional (1D) assuming (i) no variability inside a satellite pixel and (ii) no radiative interactions between pixels. The assumptions behind the 1D approach will be checked using cloud and aerosol data measured by the MODerate Resolution Imaging Spectroradiometer (MODIS) on board of two NASA satellites TERRA and AQUA. In the discussion, I will use both analysis technique: statistical analysis over large areas and time intervals, and single scene analysis to validate how well the 1D radiative transfer equation describes radiative regime in cloudy atmospheres.

High Resolution Stratigraphic Mapping in Complex Terrain: A Comparison of Traditional Remote Sensing Techniques with Unmanned Aerial Vehicle - Structure from Motion Photogrammetry

NASA Astrophysics Data System (ADS)

Nesbit, P. R.; Hugenholtz, C.; Durkin, P.; Hubbard, S. M.; Kucharczyk, M.; Barchyn, T.

2016-12-01

Remote sensing and digital mapping have started to revolutionize geologic mapping in recent years as a result of their realized potential to provide high resolution 3D models of outcrops to assist with interpretation, visualization, and obtaining accurate measurements of inaccessible areas. However, in stratigraphic mapping applications in complex terrain, it is difficult to acquire information with sufficient detail at a wide spatial coverage with conventional techniques. We demonstrate the potential of a UAV and Structure from Motion (SfM) photogrammetric approach for improving 3D stratigraphic mapping applications within a complex badland topography. Our case study is performed in Dinosaur Provincial Park (Alberta, Canada), mapping late Cretaceous fluvial meander belt deposits of the Dinosaur Park formation amidst a succession of steeply sloping hills and abundant drainages - creating a challenge for stratigraphic mapping. The UAV-SfM dataset (2 cm spatial resolution) is compared directly with a combined satellite and aerial LiDAR dataset (30 cm spatial resolution) to reveal advantages and limitations of each dataset before presenting a unique workflow that utilizes the dense point cloud from the UAV-SfM dataset for analysis. The UAV-SfM dense point cloud minimizes distortion, preserves 3D structure, and records an RGB attribute - adding potential value in future studies. The proposed UAV-SfM workflow allows for high spatial resolution remote sensing of stratigraphy in complex topographic environments. This extended capability can add value to field observations and has the potential to be integrated with subsurface petroleum models.

Using LiDAR data to measure the 3D green biomass of Beijing urban forest in China.

PubMed

He, Cheng; Convertino, Matteo; Feng, Zhongke; Zhang, Siyu

2013-01-01

The purpose of the paper is to find a new approach to measure 3D green biomass of urban forest and to testify its precision. In this study, the 3D green biomass could be acquired on basis of a remote sensing inversion model in which each standing wood was first scanned by Terrestrial Laser Scanner to catch its point cloud data, then the point cloud picture was opened in a digital mapping data acquisition system to get the elevation in an independent coordinate, and at last the individual volume captured was associated with the remote sensing image in SPOT5(System Probatoired'Observation dela Tarre)by means of such tools as SPSS (Statistical Product and Service Solutions), GIS (Geographic Information System), RS (Remote Sensing) and spatial analysis software (FARO SCENE and Geomagic studio11). The results showed that the 3D green biomass of Beijing urban forest was 399.1295 million m(3), of which coniferous was 28.7871 million m(3) and broad-leaf was 370.3424 million m(3). The accuracy of 3D green biomass was over 85%, comparison with the values from 235 field sample data in a typical sampling way. This suggested that the precision done by the 3D forest green biomass based on the image in SPOT5 could meet requirements. This represents an improvement over the conventional method because it not only provides a basis to evalue indices of Beijing urban greenings, but also introduces a new technique to assess 3D green biomass in other cities.

Using LiDAR Data to Measure the 3D Green Biomass of Beijing Urban Forest in China

PubMed Central

He, Cheng; Convertino, Matteo; Feng, Zhongke; Zhang, Siyu

2013-01-01

The purpose of the paper is to find a new approach to measure 3D green biomass of urban forest and to testify its precision. In this study, the 3D green biomass could be acquired on basis of a remote sensing inversion model in which each standing wood was first scanned by Terrestrial Laser Scanner to catch its point cloud data, then the point cloud picture was opened in a digital mapping data acquisition system to get the elevation in an independent coordinate, and at last the individual volume captured was associated with the remote sensing image in SPOT5(System Probatoired'Observation dela Tarre)by means of such tools as SPSS (Statistical Product and Service Solutions), GIS (Geographic Information System), RS (Remote Sensing) and spatial analysis software (FARO SCENE and Geomagic studio11). The results showed that the 3D green biomass of Beijing urban forest was 399.1295 million m3, of which coniferous was 28.7871 million m3 and broad-leaf was 370.3424 million m3. The accuracy of 3D green biomass was over 85%, comparison with the values from 235 field sample data in a typical sampling way. This suggested that the precision done by the 3D forest green biomass based on the image in SPOT5 could meet requirements. This represents an improvement over the conventional method because it not only provides a basis to evalue indices of Beijing urban greenings, but also introduces a new technique to assess 3D green biomass in other cities. PMID:24146792

Absorption of Solar Radiation by Clouds: An Overview

NASA Technical Reports Server (NTRS)

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

2000-01-01

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

ARM Evaluation Product : Droplet Number Concentration Value-Added Product

DOE Data Explorer

Riihimaki, Laura

2014-05-15

Cloud droplet number concentration is an important factor in understanding aerosol-cloud interactions. As aerosol concentration increases, it is expected that droplet number concentration, Nd, will increase and droplet size decrease, for a given liquid water path (Twomey 1977), which will greatly affect cloud albedo as smaller droplets reflect more shortwave radiation. However, the magnitude and variability of these processes under different environmental conditions is still uncertain. McComiskey et al. (2009) have implemented a method, based on Boers and Mitchell (1994), for calculating Nd from ground-based remote sensing measurements of optical depth and liquid water path. They show that the magnitude of the aerosol-cloud interactions (ACI) varies with a range of factors, including the relative value of the cloud liquid water path (LWP), the aerosol size distribution, and the cloud updraft velocity. Estimates of Nd under a range of cloud types and conditions and at a variety of sites are needed to further quantify the impacts of aerosol cloud interactions.

Remote Distributed Vibration Sensing Through Opaque Media Using Permanent Magnets

DOE PAGES

Chen, Yi; Mazumdar, Anirban; Brooks, Carlton F.; ...

2018-04-05

Vibration sensing is critical for a variety of applications from structural fatigue monitoring to understanding the modes of airplane wings. In particular, remote sensing techniques are needed for measuring the vibrations of multiple points simultaneously, assessing vibrations inside opaque metal vessels, and sensing through smoke clouds and other optically challenging environments. Here, in this paper, we propose a method which measures high-frequency displacements remotely using changes in the magnetic field generated by permanent magnets. We leverage the unique nature of vibration tracking and use a calibrated local model technique developed specifically to improve the frequency-domain estimation accuracy. The results showmore » that two-dimensional local models surpass the dipole model in tracking high-frequency motions. A theoretical basis for understanding the effects of electronic noise and error due to correlated variables is generated in order to predict the performance of experiments prior to implementation. Simultaneous measurements of up to three independent vibrating components are shown. The relative accuracy of the magnet-based displacement tracking with respect to the video tracking ranges from 40 to 190 μm when the maximum displacements approach ±5 mm and when sensor-to-magnet distances vary from 25 to 36 mm. Finally, vibration sensing inside an opaque metal vessel and mode shape changes due to damage on an aluminum beam are also studied using the wireless permanent-magnet vibration sensing scheme.« less

Remote Distributed Vibration Sensing Through Opaque Media Using Permanent Magnets

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

Chen, Yi; Mazumdar, Anirban; Brooks, Carlton F.

Vibration sensing is critical for a variety of applications from structural fatigue monitoring to understanding the modes of airplane wings. In particular, remote sensing techniques are needed for measuring the vibrations of multiple points simultaneously, assessing vibrations inside opaque metal vessels, and sensing through smoke clouds and other optically challenging environments. Here, in this paper, we propose a method which measures high-frequency displacements remotely using changes in the magnetic field generated by permanent magnets. We leverage the unique nature of vibration tracking and use a calibrated local model technique developed specifically to improve the frequency-domain estimation accuracy. The results showmore » that two-dimensional local models surpass the dipole model in tracking high-frequency motions. A theoretical basis for understanding the effects of electronic noise and error due to correlated variables is generated in order to predict the performance of experiments prior to implementation. Simultaneous measurements of up to three independent vibrating components are shown. The relative accuracy of the magnet-based displacement tracking with respect to the video tracking ranges from 40 to 190 μm when the maximum displacements approach ±5 mm and when sensor-to-magnet distances vary from 25 to 36 mm. Finally, vibration sensing inside an opaque metal vessel and mode shape changes due to damage on an aluminum beam are also studied using the wireless permanent-magnet vibration sensing scheme.« less

Laser Remote Sensing from ISS: CATS Cloud and Aerosol Level 2 Data Products (Heritage Edition)

NASA Technical Reports Server (NTRS)

Rodier, Sharon; Palm, Steve; Vaughan, Mark; Yorks, John; McGill, Matt; Jensen, Mike; Murray, Tim; Trepte, Chip

2016-01-01

With the recent launch of the Cloud-Aerosol Transport System (CATS) we have the opportunity to acquire a continuous record of space based lidar measurements spanning from the Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) era to the start of the EarthCARE mission. Utilizing existing well-validated science algorithms from the CALIPSO mission, we will ingest the CATS data stream and deliver high-quality lidar data sets to the user community at the earliest possible opportunity. In this paper we present an overview of procedures necessary to generate CALIPSO-like lidar level 2 data products from the CATS level 1 data products.

Satellite Imagery Analysis for Nighttime Temperature Inversion Clouds

NASA Technical Reports Server (NTRS)

Kawamoto, K.; Minnis, P.; Arduini, R.; Smith, W., Jr.

2001-01-01

Clouds play important roles in the climate system. Their optical and microphysical properties, which largely determine their radiative property, need to be investigated. Among several measurement means, satellite remote sensing seems to be the most promising. Since most of the cloud algorithms proposed so far are daytime use which utilizes solar radiation, Minnis et al. (1998) developed a nighttime use one using 3.7-, 11 - and 12-microns channels. Their algorithm, however, has a drawback that is not able to treat temperature inversion cases. We update their algorithm, incorporating new parameterization by Arduini et al. (1999) which is valid for temperature inversion cases. This updated algorithm has been applied to GOES satellite data and reasonable retrieval results were obtained.

Remote sensing of cloud droplet size distributions in DC3 with the UMBC-LACO Rainbow Polarimetric Imager (RPI)

NASA Astrophysics Data System (ADS)

Buczkowski, S.; Martins, J.; Fernandez-Borda, R.; Cieslak, D.; Hall, J.

2013-12-01

The UMBC Rainbow Polarimetric Imager is a small form factor VIS imaging polarimeter suitable for use on a number of platforms. An optical system based on a Phillips prism with three Bayer filter color detectors, each detecting a separate polarization state, allows simultaneous detection of polarization and spectral information. A Mueller matrix-like calibration scheme corrects for polarization artifacts in the optical train and allows retrieval of the polarization state of incoming light to better than 0.5%. Coupled with wide field of view optics (~90°), RPI can capture images of cloudbows over a wide range of aircraft headings and solar zenith angles for retrieval of cloud droplet size distribution (DSD) parameters. In May-June 2012, RPI was flown in a nadir port on the NASA DC-8 during the DC3 field campaign. We will show examples of cloudbow DSD parameter retrievals from the campaign to demonstrate the efficacy of such a system to terrestrial atmospheric remote sensing. RPI image from DC3 06/15/2012 flight. Left panel is raw image from the RPI 90° camera. Middle panel is Stokes 'q' parameter retrieved from full three camera dataset. Right panel is a horizontal cut in 'q' through the glory. Both middle and right panels clearly show cloudbow features which can be fit to infer cloud DSD parameters.

Remote sensing of vegetation and land-cover change in Arctic Tundra Ecosystems

USGS Publications Warehouse

Stow, Douglas A.; Hope, Allen; McGuire, David; Verbyla, David; Gamon, John A.; Huemmrich, Fred; Houston, Stan; Racine, Charles H.; Sturm, Matthew; Tape, Ken D.; Hinzman, Larry D.; Yoshikawa, Kenji; Tweedie, Craig E.; Noyle, Brian; Silapaswan, Cherie; Douglas, David C.; Griffith, Brad; Jia, Gensuo; Howard E. Epstein,; Walker, Donald A.; Daeschner, Scott; Petersen, Aaron; Zhou, Liming; Myneni, Ranga B.

2004-01-01

The objective of this paper is to review research conducted over the past decade on the application of multi-temporal remote sensing for monitoring changes of Arctic tundra lands. Emphasis is placed on results from the National Science Foundation Land–Air–Ice Interactions (LAII) program and on optical remote sensing techniques. Case studies demonstrate that ground-level sensors on stationary or moving track platforms and wide-swath imaging sensors on polar orbiting satellites are particularly useful for capturing optical remote sensing data at sufficient frequency to study tundra vegetation dynamics and changes for the cloud prone Arctic. Less frequent imaging with high spatial resolution instruments on aircraft and lower orbiting satellites enable more detailed analyses of land cover change and calibration/validation of coarser resolution observations.The strongest signals of ecosystem change detected thus far appear to correspond to expansion of tundra shrubs and changes in the amount and extent of thaw lakes and ponds. Changes in shrub cover and extent have been documented by modern repeat imaging that matches archived historical aerial photography. NOAA Advanced Very High Resolution Radiometer (AVHRR) time series provide a 20-year record for determining changes in greenness that relates to photosynthetic activity, net primary production, and growing season length. The strong contrast between land materials and surface waters enables changes in lake and pond extent to be readily measured and monitored.

Perspectives of methods of laser monitoring of the atmosphere and sea surface

NASA Astrophysics Data System (ADS)

Pashayev, Arif; Tunaboylu, Bahadir; Usta, Metin; Sadixov, Ilham; Allahverdiyev, Kerim

2016-01-01

Laser monitoring (remote sensing) may be considered as the science of collecting and interpreting information about the atmosphere, earth and sea using sensors on earth, on platforms in our atmosphere (airplanes, balloons) or in space (satellites) without being in direct physical contact with them. Remote sensing by LIDARs (Light Identification Detection and Ranging) has wide applications as technique to probe the Earth's atmosphere, ocean and land surfaces. LIDARs are widely used to get knowledge of spatial and temporal variations in meteorological quantities (e.g. temperature, humidity, clouds and aerosol properties) and to monitor the changes in these quantities on different timescales. Subject of the present work is quite wide. It is rather difficult to perform analysis and to provide full knowledge about existing information. In the present work, in addition to the literature data, the information will be provided also about KA-09 aerosol LIDAR developed at the Marmara Research Centre of TÜBITAK (Turkish Scientific and technological Research Council) and also about KA-14 LIDAR developed at the National Aviation Academy of Azerbaijan for remote sensing of contaminations on water surfaces taking place during oil-gas production. The main goal of this paper is to give students insight in different remote sensing instruments and techniques (including their perspectives) that are used for the derivation of meteorological quantities and obtaining the information about water surface.

Compositing multitemporal remote sensing data sets

USGS Publications Warehouse

Qi, J.; Huete, A.R.; Hood, J.; Kerr, Y.

1993-01-01

To eliminate cloud and atmosphere-affected pixels, the compositing of multi temporal remote sensing data sets is done by selecting the maximum vale of the normalized different vegetation index (NDVI) within a compositing period. The NDVI classifier, however, is strongly affected by surface type and anisotropic properties, sensor viewing geometries, and atmospheric conditions. Consequently, the composited, multi temporal, remote sensing data contain substantial noise from these external conditions. Consequently, the composited, multi temporal, remote sensing data contain substantial noise from these external effects. To improve the accuracy of compositing products, two key approaches can be taken: one is to refine the compositing classifier (NDVI) and the other is to improve existing compositing algorithms. In this project, an alternative classifier was developed and an alternative pixel selection criterion was proposed for compositing. The new classifier and the alternative compositing algorithm were applied to an advanced very high resolution radiometer data set of different biome types in the United States. The results were compared with the maximum value compositing and the best index slope extraction algorithms. The new approaches greatly reduced the high frequency noises related to the external factors and repainted more reliable data. The results suggest that the geometric-optical canopy properties of specific biomes may be needed in compositing. Limitations of the new approaches include the dependency of pixel selection on the length of the composite period and data discontinuity.

Analysis of the atmospheric upward radiation in low latitude area

NASA Astrophysics Data System (ADS)

Li, Haiying; Wu, Zhensen; Lin, Leke; Lu, Changsheng

2016-10-01

Remote sensing using THz wave has irreplaceable advantage comparing to the microwave and the infrared waves, and study on the THz remote sensing become more and more popular in recent years. The major applications of the remote sensing in THz wavelengths are the retrieval of the atmospheric parameters and the microphysical information of the ice cloud. The remote sensing of the atmosphere is based on the radiation of THz wave along the earth-space path of which the most significant part is the upward radiation of the atmosphere. The upward radiation of the atmosphere in sunny day in the low latitude area is computed and analyzed in this paper. The absorption of THz wave by the atmosphere is calculated using the formulations illustrated in the Recommendation ITU-R P.676 to save machine hour, the frequency range is then restricted below 1THz. The frequencies used for the retrieval of atmospheric parameters such as temperature and water content are usually a few hundred GHz, at the lower end of THz wavelengths, so this frequency range is sufficient. The radiation contribution of every atmospheric layer for typical frequencies such as absorption window frequencies and peak frequencies are analyzed. Results show that at frequencies which absorption is severe, information about lower atmosphere cannot reach the receiver onboard a satellite or other high platforms due to the strong absorption along the path.

Boundary Layer Thermodynamics and Cloud Microphysics for a Mixed Stratocumulus and Cumulus Cloud Field Observed during ACE-ENA

NASA Astrophysics Data System (ADS)

Jensen, M. P.; Miller, M. A.; Wang, J.

2017-12-01

The first Intensive Observation Period of the DOE Aerosol and Cloud Experiments in the Eastern North Atlantic (ACE-ENA) took place from 21 June through 20 July 2017 involving the deployment of the ARM Gulfstream-159 (G-1) aircraft with a suite of in situ cloud and aerosol instrumentation in the vicinity of the ARM Climate Research Facility Eastern North Atlantic (ENA) site on Graciosa Island, Azores. Here we present preliminary analysis of the thermodynamic characteristics of the marine boundary layer and the variability of cloud properties for a mixed cloud field including both stratiform cloud layers and deeper cumulus elements. Analysis combines in situ atmospheric state observations from the G-1 with radiosonde profiles and surface meteorology from the ENA site in order to characterize the thermodynamic structure of the marine boundary layer including the coupling state and stability. Cloud/drizzle droplet size distributions measured in situ are combined with remote sensing observations from a scanning cloud radar, and vertically pointing cloud radar and lidar provide quantification of the macrophysical and microphysical properties of the mixed cloud field.

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

A New Approach for Estimating Entrainment Rate in Cumulus Clouds

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

Lu C.; Liu, Y.; Yum, S. S.

2012-02-16

A new approach is presented to estimate entrainment rate in cumulus clouds. The new approach is directly derived from the definition of fractional entrainment rate and relates it to mixing fraction and the height above cloud base. The results derived from the new approach compare favorably with those obtained with a commonly used approach, and have smaller uncertainty. This new approach has several advantages: it eliminates the need for in-cloud measurements of temperature and water vapor content, which are often problematic in current aircraft observations; it has the potential for straightforwardly connecting the estimation of entrainment rate and the microphysicalmore » effects of entrainment-mixing processes; it also has the potential for developing a remote sensing technique to infer entrainment rate.« less

Optical and Microphysical Retrievals of Marine Stratocumulus Clouds off the Coast of Namibia from Satellite and Aircraft

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.

PROGRA2 experiment: New results for dust clouds and regoliths analogs

NASA Astrophysics Data System (ADS)

Hadamcik, E.; Renard, J.-B.; Levasseur-Regourd, A. C.; Worms, J.-C.

2006-01-01

With the PROGRA2 experience, linear polarization of scattered light is measured on various types of dust clouds lifted by microgravity, or by an air-draught. The aim is to compare the phase curves for dust analogs with those obtained in the Solar System (cometary comae, and solid particles in planetary atmospheres) by remote-sensing and in situ techniques. Measurements are also performed on layers of particles (on the ground) and compared with remote measurements on asteroidal regoliths and planetary surfaces. New phase curves have been obtained, e.g., for quartz samples, crystals, fluffy mixtures of silica and carbon blacks and a high porosity regolith analog made of micron-sized silica spheres. This work will contribute to the choice of the samples to be studied with the ICAPS experiment onboard the ISS and on the precursor experiment.

Remote measurement of cloud microphysics and its influence in predicting high impact weather events

NASA Astrophysics Data System (ADS)

Bipasha, Paul S.; Jinya, John

2016-05-01

Understanding the cloud microphysical processes and precise retrieval of parameters governing the same are crucial for weather and climate prediction. Advanced remote sensing sensors and techniques offer an opportunity for monitoring micro-level developments in cloud structure. . Using the observations from a visible and near-infrared lidar onboard CALIPSO satellite (part of A-train) , the spatial variation of cloud structure has been studied over the Tropical monsoon region . It is found that there is large variability in the cloud microphysical parameters manifesting in distinct precipitation regimes. In particular, the severe storms over this region are driven by processes which range from the synoptic to the microphysical scale. Using INSAT-3D data, retrieval of cloud microphysical parameters like effective radius (CER) and optical depth (COD) were carried out for tropical cyclone Phailine. It was observed that there is a general increase of CER in a top-down direction, characterizing the progressively increasing number and size of precipitation hydrometeors while approaching the cloud base. The distribution of CER relative to cloud top temperature for growing convective clouds has been investigated to reveal the evolution of the particles composing the clouds. It is seen that the relatively high concentration of large particles in the downdraft zone is closely related to the precipitation efficiency of the system. Similar study was also carried using MODIS observations for cyclones over Indian Ocean (2010-2013), in which we find that that the mean effective radius is 24 microns with standard deviation 4.56, mean optical depth is 21 with standard deviation 13.98, mean cloud fraction is 0.92 with standard deviation 0.13 and mainly ice phase is dominant. Thus the remote observations of microstructure of convective storms provide very crucial information about the maintenance and potential devastation likely to be associated with it. With the synergistic observations from A-Train , geostationary and futuristic imaging spectroscopic sensors, a multi-dimensional, and multi-scalar exploration of cloud systems is anticipated leading to accurate prediction of high impact weather events.

Introducing two Random Forest based methods for cloud detection in remote sensing images

NASA Astrophysics Data System (ADS)

Ghasemian, Nafiseh; Akhoondzadeh, Mehdi

2018-07-01

Cloud detection is a necessary phase in satellite images processing to retrieve the atmospheric and lithospheric parameters. Currently, some cloud detection methods based on Random Forest (RF) model have been proposed but they do not consider both spectral and textural characteristics of the image. Furthermore, they have not been tested in the presence of snow/ice. In this paper, we introduce two RF based algorithms, Feature Level Fusion Random Forest (FLFRF) and Decision Level Fusion Random Forest (DLFRF) to incorporate visible, infrared (IR) and thermal spectral and textural features (FLFRF) including Gray Level Co-occurrence Matrix (GLCM) and Robust Extended Local Binary Pattern (RELBP_CI) or visible, IR and thermal classifiers (DLFRF) for highly accurate cloud detection on remote sensing images. FLFRF first fuses visible, IR and thermal features. Thereafter, it uses the RF model to classify pixels to cloud, snow/ice and background or thick cloud, thin cloud and background. DLFRF considers visible, IR and thermal features (both spectral and textural) separately and inserts each set of features to RF model. Then, it holds vote matrix of each run of the model. Finally, it fuses the classifiers using the majority vote method. To demonstrate the effectiveness of the proposed algorithms, 10 Terra MODIS and 15 Landsat 8 OLI/TIRS images with different spatial resolutions are used in this paper. Quantitative analyses are based on manually selected ground truth data. Results show that after adding RELBP_CI to input feature set cloud detection accuracy improves. Also, the average cloud kappa values of FLFRF and DLFRF on MODIS images (1 and 0.99) are higher than other machine learning methods, Linear Discriminate Analysis (LDA), Classification And Regression Tree (CART), K Nearest Neighbor (KNN) and Support Vector Machine (SVM) (0.96). The average snow/ice kappa values of FLFRF and DLFRF on MODIS images (1 and 0.85) are higher than other traditional methods. The quantitative values on Landsat 8 images show similar trend. Consequently, while SVM and K-nearest neighbor show overestimation in predicting cloud and snow/ice pixels, our Random Forest (RF) based models can achieve higher cloud, snow/ice kappa values on MODIS and thin cloud, thick cloud and snow/ice kappa values on Landsat 8 images. Our algorithms predict both thin and thick cloud on Landsat 8 images while the existing cloud detection algorithm, Fmask cannot discriminate them. Compared to the state-of-the-art methods, our algorithms have acquired higher average cloud and snow/ice kappa values for different spatial resolutions.

Proceedings of the 2004 High Spatial Resolution Commercial Imagery Workshop

NASA Technical Reports Server (NTRS)

2006-01-01

Topics covered include: NASA Applied Sciences Program; USGS Land Remote Sensing: Overview; QuickBird System Status and Product Overview; ORBIMAGE Overview; IKONOS 2004 Calibration and Validation Status; OrbView-3 Spatial Characterization; On-Orbit Modulation Transfer Function (MTF) Measurement of QuickBird; Spatial Resolution Characterization for QuickBird Image Products 2003-2004 Season; Image Quality Evaluation of QuickBird Super Resolution and Revisit of IKONOS: Civil and Commercial Application Project (CCAP); On-Orbit System MTF Measurement; QuickBird Post Launch Geopositional Characterization Update; OrbView-3 Geometric Calibration and Geopositional Accuracy; Geopositional Statistical Methods; QuickBird and OrbView-3 Geopositional Accuracy Assessment; Initial On-Orbit Spatial Resolution Characterization of OrbView-3 Panchromatic Images; Laboratory Measurement of Bidirectional Reflectance of Radiometric Tarps; Stennis Space Center Verification and Validation Capabilities; Joint Agency Commercial Imagery Evaluation (JACIE) Team; Adjacency Effects in High Resolution Imagery; Effect of Pulse Width vs. GSD on MTF Estimation; Camera and Sensor Calibration at the USGS; QuickBird Geometric Verification; Comparison of MODTRAN to Heritage-based Results in Vicarious Calibration at University of Arizona; Using Remotely Sensed Imagery to Determine Impervious Surface in Sioux Falls, South Dakota; Estimating Sub-Pixel Proportions of Sagebrush with a Regression Tree; How Do YOU Use the National Land Cover Dataset?; The National Map Hazards Data Distribution System; Recording a Troubled World; What Does This-Have to Do with This?; When Can a Picture Save a Thousand Homes?; InSAR Studies of Alaska Volcanoes; Earth Observing-1 (EO-1) Data Products; Improving Access to the USGS Aerial Film Collections: High Resolution Scanners; Improving Access to the USGS Aerial Film Collections: Phoenix Digitizing System Product Distribution; System and Product Characterization: Issues Approach; Innovative Approaches to Analysis of Lidar Data for the National Map; Changes in Imperviousness near Military Installations; Geopositional Accuracy Evaluations of QuickBird and OrbView-3: Civil and Commercial Applications Project (CCAP); Geometric Accuracy Assessment: OrbView ORTHO Products; QuickBird Radiometric Calibration Update; OrbView-3 Radiometric Calibration; QuickBird Radiometric Characterization; NASA Radiometric Characterization; Establishing and Verifying the Traceability of Remote-Sensing Measurements to International Standards; QuickBird Applications; Airport Mapping and Perpetual Monitoring Using IKONOS; OrbView-3 Relative Accuracy Results and Impacts on Exploitation and Accuracy Improvement; Using Remotely Sensed Imagery to Determine Impervious Surface in Sioux Falls, South Dakota; Applying High-Resolution Satellite Imagery and Remotely Sensed Data to Local Government Applications: Sioux Falls, South Dakota; Automatic Co-Registration of QuickBird Data for Change Detection Applications; Developing Coastal Surface Roughness Maps Using ASTER and QuickBird Data Sources; Automated, Near-Real Time Cloud and Cloud Shadow Detection in High Resolution VNIR Imagery; Science Applications of High Resolution Imagery at the USGS EROS Data Center; Draft Plan for Characterizing Commercial Data Products in Support of Earth Science Research; Atmospheric Correction Prototype Algorithm for High Spatial Resolution Multispectral Earth Observing Imaging Systems; Determining Regional Arctic Tundra Carbon Exchange: A Bottom-Up Approach; Using IKONOS Imagery to Assess Impervious Surface Area, Riparian Buffers and Stream Health in the Mid-Atlantic Region; Commercial Remote Sensing Space Policy Civil Implementation Update; USGS Commercial Remote Sensing Data Contracts (CRSDC); and Commercial Remote Sensing Space Policy (CRSSP): Civil Near-Term Requirements Collection Update.

Computation of European carbon balance components through synergistic use of CARBOEUROPE eddy covariance, MODIS remote sensing data and advanced ecosystem and statistical modeling

NASA Astrophysics Data System (ADS)

Reichstein, M.; Dinh, N.; Running, S.; Seufert, G.; Tenhunen, J.; Valentini, R.

2003-04-01

Here we present spatially distributed bottom-up estimates of European carbon balance components for the year 2001, that stem from a newly built modeling system that integrates CARBOEUROPE eddy covariance CO_2 exchange data, remotely sensed vegetation properties via the MODIS-Terra sensor, European-wide soils data, and a suite of carbon balance models of different complexity. These estimates are able to better constrain top-down atmospheric-inversion carbon balance estimates within the dual-constraint approach for estimating continental carbon balances. The models that are used to calculate gross primary production (GPP) include a detailed layered canopy model with Farquhar-type photosynthesis (PROXELNEE), sun-shade big-leaf formulations operating at a daily time-step and a simple radiation-use efficiency model. These models are parameterized from eddy covariance data through inverse estimation techniques. Also for the estimation of soil and ecosystem respiration (Rsoil, Reco) we profit from a large data set of eddy covariance and soil chamber measurements, that enables us to the parameterize and validate a recently developed semi-empirical model, that includes a variable temperature sensitivity of respiration. As the outcome of the modeling system we present the most likely daily to annual numbers of carbon balance components (GPP, Reco, Rsoil), but we also issue a thorough analysis of biases and uncertainties in carbon balance estimates that are introduced through errors in the meteorological and remote sensing input data and through uncertainties in the model parameterization. In particular, we analyze 1) the effect of cloud contamination of the MODIS data, 2) the sensitivity to the land-use classification (Corine versus MODIS), 3) the effect of different soil parameterizations as derived from new continental-scale soil maps, and 4) the necessity to include soil drought effects into models of GPP and respiration. While the models describe the eddy covariance data quite well with r^2 values always greater than 0.7, there are still uncertainties in the European carbon balance estimate that exceed 0.3 PgC/yr. In northern (boreal) regions the carbon balance estimate is very much contingent on a high-quality filling of cloud contaminated remote sensing data, while in the southern (Mediterranean) regions a correct description of the soil water holding capacity is crucial. A major source of uncertainty also still is the estimation of heterotrophic respiration at continental scales. Consequently more spatial surveys on soil carbon stocks, turnover and history are needed. The study demonstrates that both, the inclusion of considerable geo-biological variability into a carbon balance modeling system, a high-quality cloud screening and gap-filling of the MODIS remote sensing data, and a correct description of soil drought effects are mandatory for realistic bottom-up estimates of European carbon balance components.

Global Multispectral Cloud Retrievals from MODIS

NASA Technical Reports Server (NTRS)

King, Michael D.; Platnick, Steven; Ackerman, Steven A.; Menzel, W. Paul; Riedi, Jerome C.; Baum, Bryan A.

2003-01-01

The Moderate Resolution Imaging Spectroradiometer (MODIS) was developed by NASA and launched onboard the Terra spacecraft on December 18,1999 and Aqua spacecraft on May 4,2002. It achieved its final orbit and began Earth observations on February 24, 2000 for Terra and June 24, 2002 for Aqua. A comprehensive set of remote sensing algorithms for cloud masking and the retrieval of cloud physical and optical properties has been developed by members of the MODIS atmosphere science team. The archived products from these algorithms have applications in climate change studies, climate modeling, numerical weather prediction, as well as fundamental atmospheric research. 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. We will describe the various cloud properties being analyzed on a global basis from both Terra and Aqua, and will show characteristics of cloud optical and microphysical properties as a function of latitude for land and ocean separately, and contrast the statistical properties of similar cloud types in various parts of the world.

Microphysical parameters of cirrus clouds using lidar at a tropical station, Gadanki, Tirupati (13.5° N, 79.2°E), India

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.

A hotspot model for leaf canopies

NASA Technical Reports Server (NTRS)

Jupp, David L. B.; Strahler, Alan H.

1991-01-01

The hotspot effect, which provides important information about canopy structure, is modeled using general principles of environmental physics as driven by parameters of interest in remote sensing, such as leaf size, leaf shape, leaf area index, and leaf angle distribution. Specific examples are derived for canopies of horizontal leaves. The hotspot effect is implemented within the framework of the model developed by Suits (1972) for a canopy of leaves to illustrate what might occur in an agricultural crop. Because the hotspot effect arises from very basic geometrical principles and is scale-free, it occurs similarly in woodlands, forests, crops, rough soil surfaces, and clouds. The scaling principles advanced are also significant factors in the production of image spatial and angular variance and covariance which can be used to assess land cover structure through remote sensing.

Modern and prospective technologies for weather modification activities: Developing a framework for integrating autonomous unmanned aircraft systems

NASA Astrophysics Data System (ADS)

DeFelice, T. P.; Axisa, Duncan

2017-09-01

This paper builds upon the processes and framework already established for identifying, integrating and testing an unmanned aircraft system (UAS) with sensing technology for use in rainfall enhancement cloud seeding programs to carry out operational activities or to monitor and evaluate seeding operations. We describe the development and assessment methodologies of an autonomous and adaptive UAS platform that utilizes in-situ real time data to sense, target and implement seeding. The development of a UAS platform that utilizes remote and in-situ real-time data to sense, target and implement seeding deployed with a companion UAS ensures optimal, safe, secure, cost-effective seeding operations, and the dataset to quantify the results of seeding. It also sets the path for an innovative, paradigm shifting approach for enhancing precipitation independent of seeding mode. UAS technology is improving and their application in weather modification must be explored to lay the foundation for future implementation. The broader significance lies in evolving improved technology and automating cloud seeding operations that lowers the cloud seeding operational footprint and optimizes their effectiveness and efficiency, while providing the temporal and spatial sensitivities to overcome the predictability or sparseness of environmental parameters needed to identify conditions suitable for seeding, and how such might be implemented. The dataset from the featured approach will contain data from concurrent Eulerian and Lagrangian perspectives over sub-cloud scales that will facilitate the development of cloud seeding decision support tools.

Ice formation in altocumulus clouds over Leipzig: Remote sensing measurements and detailed model simulations

NASA Astrophysics Data System (ADS)

Simmel, Martin; Bühl, Johannes; Ansmann, Albert; Tegen, Ina

2014-05-01

Over Leipzig, altocumulus clouds are frequently observed using a suite of remote sensing instruments. These observations cover a wide range of heights, temperatures, and microphysical properties of the clouds ranging from purely liquid to heavily frozen. For the current study, two cases were chosen to test the sensitivity of these clouds with respect to several microphysical and dynamical parameters such as aerosol properties (CCN, IN), ice particle shape as well as turbulence. The mixed-phase spectral microphysical model SPECS was coupled to a dynamical model of the Asai-Kasahara type resulting in the model system AK-SPECS. The relatively simple dynamics allows for a fine vertical resolution needed for the rather shallow cloud layers observed. Additionally, the proper description of hydrometeor sedimentation is important especially for the fast growing ice crystals to realistically capture their interaction with the vapour and liquid phase (Bergeron-Findeisen process). Since the focus is on the cloud microphysics, the dynamics in terms of vertical velocity profile is prescribed for the model runs and the feedback of the microphysics on dynamics by release or consumption of latent heat due to phase transfer is not taken into account. The microphysics focuses on (1) ice particle shape allowing hexagonal plates and columns with size-dependant axis ratios and (2) the ice nuclei (IN) budget realized with a prognostic temperature resolved field of potential IN allowing immersion freezing only when active IN and supercooled drops above a certain size threshold are present within a grid cell. Sensitivity studies show for both cases that ice particle shape seems to have the major influence on ice mass formation under otherwise identical conditions. This is due to the effect (1) on terminal fall velocity of the individual ice particle allowing for longer presence times in conditions supersaturated with respect to ice and (2) on water vapour deposition which is enhanced due to increased capacitance because of deviation from the spherical shape.

Classification of Clouds in Satellite Imagery Using Adaptive Fuzzy Sparse Representation.

PubMed

Jin, Wei; Gong, Fei; Zeng, Xingbin; Fu, Randi

2016-12-16

Automatic cloud detection and classification using satellite cloud imagery have various meteorological applications such as weather forecasting and climate monitoring. Cloud pattern analysis is one of the research hotspots recently. Since satellites sense the clouds remotely from space, and different cloud types often overlap and convert into each other, there must be some fuzziness and uncertainty in satellite cloud imagery. Satellite observation is susceptible to noises, while traditional cloud classification methods are sensitive to noises and outliers; it is hard for traditional cloud classification methods to achieve reliable results. To deal with these problems, a satellite cloud classification method using adaptive fuzzy sparse representation-based classification (AFSRC) is proposed. Firstly, by defining adaptive parameters related to attenuation rate and critical membership, an improved fuzzy membership is introduced to accommodate the fuzziness and uncertainty of satellite cloud imagery; secondly, by effective combination of the improved fuzzy membership function and sparse representation-based classification (SRC), atoms in training dictionary are optimized; finally, an adaptive fuzzy sparse representation classifier for cloud classification is proposed. Experiment results on FY-2G satellite cloud image show that, the proposed method not only improves the accuracy of cloud classification, but also has strong stability and adaptability with high computational efficiency.

Investigation of ice cloud microphysical properties of DCSs using aircraft in situ measurements during MC3E over the ARM SGP site

DOE PAGES

Wang, Jingyu; Dong, Xiquan; Xi, Baike

2015-03-25

In this study, six deep convective systems (DCSs) with a total of 5589 five-second samples and a range of temperatures from -41°C to 0°C during the Midlatitude Continental Convective Clouds Experiment (MC3E) were selected to investigate the ice cloud microphysical properties of DCSs over the Department of Energy Atmospheric Radiation Measurement (ARM) Southern Great Plains (SGP) site. The ice cloud measurements of the DCS cases were made by the University of North Dakota Citation II research aircraft, and the ice cloud properties were derived through the following processes. First, the instances of supercooled liquid water in the ice-dominated cloud layersmore » of DCSs have been eliminated using multisensor detection, including the Rosemount Icing Detector, King and Cloud Droplet Probes, as well as 2DC and Cloud Imaging Probe images. Then the Nevzorov-measured ice water contents (IWCs) at maximum diameter D max < 4000 µm are used as the best estimation to determine a new mass-dimensional relationship. Finally, the newly derived mass-dimensional relationship (a = 0.00365, b = 2.1) has been applied to a full spectrum of particle size distributions (PSDs, 120–30,000 µm) constructed from both 2DC and High-Volume Precipitation Spectrometer measurements to calculate the best-estimated IWCs of DCSs during MC3E. The averages of the total number concentrations (N t), median mass diameter (D m), maximum diameter (D max), and IWC from six selected cases are 0.035 cm -3, 1666 µm, 8841 µm, and 0.45 g m -3, respectively. The gamma-type-size distributions are then generated matching the observed PSDs (120–30,000 µm), and the fitted gamma parameters are compared with the observed PSDs through multimoment assessments including first moment (D m), third moment (IWC), and sixth moment (equivalent radar reflectivity, Z e). Lastly, for application of observed PSDs to the remote sensing community, a series of empirical relationships between fitted parameters and Z e values has been derived, and the bullet rosette ice crystal backscattering relationship has been suggested for ground-based remote sensing.« less

Study of UV cloud modification factors in Southern Patagonia

NASA Astrophysics Data System (ADS)

Wolfram, Elian A.; Orte, Facundo; Salvador, Jacobo; Quiroga, Jonathan; D'Elia, Raúl; Antón, Manuel; Alados-Arboledas, Lucas; Quel, Eduardo

2017-02-01

Anthropogenic perturbation of the ozone layer has induced change in the amount of UV radiation that reaches the Earth's surface, mainly through the Antarctic ozone hole, making the ozone and ultraviolet (UV) radiation two important issues in the study of Earth atmosphere in the scientific community. Also the clouds have been identified as the main modulator of UV amount in short time scales and produce the main source of uncertainty in the projection of surface UV level as consequence of projected ozone recovery. While clouds can decrease direct radiation, they can produce an increase in the diffuse component, and as consequence the surface UV radiation may be higher than an equivalent clear sky scenario for several minutes. In particular this situation can be important when low ozone column and partially cloud cover skies happen simultaneously. These situations happen frequently in southern Patagonia, where the CEILAP Lidar Division has established the Atmospheric Observatory of Southern Patagonia, an atmospheric remote sensing site near the city of Río Gallegos (51°55'S, 69°14'W). In this paper, the impact of clouds over the UV radiation is investigated by the use of ground based measurements from the passive remote sensing instruments operating at this site, mainly of broad and moderate narrow band filter radiometers. We analyzed the UV Index obtained from a multiband filter radiometer GUV-541 (UVI) [Biospherical Inc.] installed in the Observatorio Atmosférico de la Patagonia Austral, Río Gallegos, since 2005. Cloud modification factors (CMF, ratio between the measured UV radiation in a cloudy sky and the simulated radiation under cloud-free conditions) are evaluated for the study site. The database used in this work covers the period 2005-2012 for spring and summer seasons, when the ozone hole can affect these subpolar regions. CMF higher than 1 are found during spring and summer time, when lower total ozone columns, higher solar elevations and high cloud cover occur simultaneously, producing extreme erythemal irradiance at ground surface. Enhancements as high as 25% were registered. The maximum duration of the enhancement was around 30 minute. This produces dangerous sunbathing situations for the Río Gallegos citizen.

Investigation of the radiative forcings of thin cirrus in the tropical atmosphere using remote sensing data

NASA Astrophysics Data System (ADS)

Yue, Qing

Cirrus clouds have a unique influence on the climate system through their effects on the radiation budget of the earth and the atmosphere. To better understand the radiative effect of cirrus clouds, the microphysical and radiative properties of these clouds, especially tropical thin cirrus clouds, are studied based on both insitu cirrus measurements and satellite remote sensing observations. We perform a correlation analysis involving ice water content (IWC) and mean effective diameter (De) for applications to radiative transfer calculations and climate models using insitu measurements obtained from numerous field campaigns in the tropics, midlatitude, and Arctic regions. In conjunction with the study of cirrus clouds, we develop a high-resolution spectral infrared radiative transfer model for thin cirrus cloudy atmosphere, which is employed to retrieve De and cirrus optical depth from the Atmospheric Infrared Sounder (AIRS) infrared spectra. Numerical simulations show that cirrus cloudy radiances in the 800-1130 cm-1 thermal infrared window are sufficiently sensitive to variations in cirrus optical depth, and ice crystal size and habit. A number of nighttime thin cirrus scenes over the Atmospheric Radiation Measurement (ARM) program's Tropical Western Pacific sites have been selected from AIRS datasets for this study. The radiative transfer model is applied to these selected cases to determine cirrus optical depth, De and habit factors. Solar and infrared radiative forcings and heating rates produced by thin cirrus in the tropical atmosphere have been calculated using the retrieved cirrus optical and microphysical properties along with a modified Fu and Liou broadband radiative transfer scheme to analyze their dependence on cirrus cloud properties. Generally, larger TOA warming and smaller surface warming are associated with higher cirrus clouds. To cross-check the validity of our model, the collocated and coincident surface radiation measurements taken by ARM pyrgeometers have been compared with the calculated surface fluxes. Using the method developed in this study, regional radiation budget analyses can be carried out in the future study to quantitatively understand the role of thin cirrus clouds on solar and thermal infrared radiative forcings at the top of the atmosphere, the tropopause, and the surface.

A Method to Analyze How Various Parts of Clouds Influence Each Other's Brightness

NASA Technical Reports Server (NTRS)

Varnai, Tamas; Marshak, Alexander; Lau, William (Technical Monitor)

2001-01-01

This paper proposes a method for obtaining new information on 3D radiative effects that arise from horizontal radiative interactions in heterogeneous clouds. Unlike current radiative transfer models, it can not only calculate how 3D effects change radiative quantities at any given point, but can also determine which areas contribute to these 3D effects, to what degree, and through what mechanisms. After describing the proposed method, the paper illustrates its new capabilities both for detailed case studies and for the statistical processing of large datasets. Because the proposed method makes it possible, for the first time, to link a particular change in cloud properties to the resulting 3D effect, in future studies it can be used to develop new radiative transfer parameterizations that would consider 3D effects in practical applications currently limited to 1D theory-such as remote sensing of cloud properties and dynamical cloud modeling.

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.

Analysis of warm convective rain events in Catalonia

NASA Astrophysics Data System (ADS)

Ballart, D.; Figuerola, F.; Aran, M.; Rigo, T.

2009-09-01

Between the end of September and November, events with high amounts of rainfall are quite common in Catalonia. The high sea surface temperature of the Mediterranean Sea near to the Catalan Coast is one of the most important factors that help to the development of this type of storms. Some of these events have particular characteristics: elevated rain rate during short time periods, not very deep convection and low lightning activity. Consequently, the use of remote sensing tools for the surveillance is quite useless or limited. With reference to the high rain efficiency, this is caused by internal mechanisms of the clouds, and also by the air mass where the precipitation structure is developed. As aforementioned, the contribution of the sea to the air mass is very relevant, not only by the increase of the big condensation nuclei, but also by high temperature of the low layers of the atmosphere, where are allowed clouds with 5 or 6 km of particles in liquid phase. In fact, the freezing level into these clouds can be detected by -15ºC. Due to these characteristics, this type of rainy structures can produce high quantities of rainfall in a relatively brief period of time, and, in the case to be quasi-stationary, precipitation values at surface could be very important. From the point of view of remote sensing tools, the cloud nature implies that the different tools and methodologies commonly used for the analysis of heavy rain events are not useful. This is caused by the following features: lightning are rarely observed, the top temperatures of clouds are not cold enough to be enhanced in the satellite imagery, and, finally, reflectivity radar values are lower than other heavy rain cases. The third point to take into account is the vulnerability of the affected areas. An elevated percentage of the Catalan population lives in the coastal region. In the central coast of Catalonia, the urban areas are surrounded by a not very high mountain range with small basins and steep slopes. These factors increase the number of flash floods and the risk indexes. In the present study it is showed the general characteristics of the warm rain events observed in Catalonia, using meteorological, pluviometric, thermodynamic, and remote sensing data. Beside this, other heavy rain events with different features have been analyzed with the purpose of identify the main differences and to improve the knowledge in order to provide enough information for surveillance tasks

Impact of atmospheric water vapor on the thermal infrared remote sensing of volcanic sufur dioxide emmisions: A case study from Pu'u 'O'o vent of Kilauea volcano, Hawaii

NASA Technical Reports Server (NTRS)

Realmuto, V. J.; Worden, H. M.

2000-01-01

The December 18, 1999, launch of NASA's Terra satellite put two multispectral thermal infrared imaging instruments into Earth orbit. Experiments with airborne instruments have demonstrated that the data from such instruments can be used to detect volcanic SO2 plumes and clouds.

Remote sensing and modelling analysis of the extreme dust storm hitting the Middle East and eastern Mediterranean in September 2015

NASA Astrophysics Data System (ADS)

Solomos, Stavros; Ansmann, Albert; Mamouri, Rodanthi-Elisavet; Binietoglou, Ioannis; Patlakas, Platon; Marinou, Eleni; Amiridis, Vassilis

2017-03-01

The extreme dust storm that affected the Middle East and the eastern Mediterranean in September 2015 resulted in record-breaking dust loads over Cyprus with aerosol optical depth exceeding 5.0 at 550 nm. We analyse this event using profiles from the European Aerosol Research Lidar Network (EARLINET) and the Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO), geostationary observations from the Meteosat Second Generation (MSG) Spinning Enhanced Visible and Infrared Imager (SEVIRI), and high-resolution simulations from the Regional Atmospheric Modeling System (RAMS). The analysis of modelling and remote sensing data reveals the main mechanisms that resulted in the generation and persistence of the dust cloud over the Middle East and Cyprus. A combination of meteorological and surface processes is found, including (a) the development of a thermal low in the area of Syria that results in unstable atmospheric conditions and dust mobilization in this area, (b) the convective activity over northern Iraq that triggers the formation of westward-moving haboobs that merge with the previously elevated dust layer, and (c) the changes in land use due to war in the areas of northern Iraq and Syria that enhance dust erodibility.

Spatial and Temporal Distribution of Tropospheric Clouds and Aerosols 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.; Remer, Lorraine A.

2006-01-01

Remote sensing of cloud and aerosol optical properties is routinely obtained using the Moderate Resolution Imaging Spectroradiometer (MODIS) onboard the Terra and Aqua satellites. Instruments that are being used to enhance our ability to characterize the global distribution of cloud and aerosol properties include well-calibrated multispectral radiometers that measure in the visible, near-infrared, and thermal infrared. The availability of thermal channels to enhance detection of cloud when estimating aerosol properties is an important improvement. In this paper, we describe the radiative properties of clouds as currently determined from satellites (cloud fraction, optical thickness, cloud top pressure, and cloud particle effective radius) and highlight the global/regional cloud microphysical properties currently available for assessing climate variability and forcing. These include the latitudinal distribution of cloud optical and radiative properties of both liquid water and ice clouds, as well as joint histograms of cloud optical thickness and effective particle radius for selected geographical locations around the world. In addition, we will illustrate the radiative and microphysical properties of aerosol particles (in cloud free regions) that are currently available from space-based observations, and show the latitudinal distribution of aerosol optical properties over both land and ocean surfaces.

Mountaintop and radar measurements of anthropogenic aerosol effects on snow growth and snowfall rate

NASA Astrophysics Data System (ADS)

Borys, Randolph D.; Lowenthal, Douglas H.; Cohn, Stephen A.; Brown, William O. J.

2003-05-01

A field campaign designed to investigate the second indirect aerosol effect (reduction of precipitation by anthropogenic aerosols which produce more numerous and smaller cloud droplets) was conducted during winter in the northern Rocky Mountains of Colorado. Combining remote sensing and in-situ mountain-top measurements it was possible to show higher concentrations of anthropogenic aerosols (~1 μg m-3) altered the microphysics of the lower orographic feeder cloud to the extent that the snow particle rime growth process was inhibited, or completely shut off, resulting in lower snow water equivalent precipitation rates.

Fusion of Cross-Track TerraSAR-X PS Point Clouds over Las Vegas

NASA Astrophysics Data System (ADS)

Wang, Ziyun; Balz, Timo; Wei, Lianhuan; Liao, Mingsheng

2014-11-01

Persistent scatterer interferometry (PS-InSAR) is widely used in radar remote sensing. However, because the surface motion is estimated in the line-of-sight (LOS) direction, it is not possible to differentiate between vertical and horizontal surface motions from a single stack. Cross-track data, i.e. the combination of data from ascending and descending orbits, allows us to better analyze the deformation and to obtain 3d motion information. We implemented a cross-track fusion of PS-InSAR point cloud data, making it possible to separate the vertical and horizontal components of the surface motion.

NASA Wrangler: Automated Cloud-Based Data Assembly in the RECOVER Wildfire Decision Support System

NASA Technical Reports Server (NTRS)

Schnase, John; Carroll, Mark; Gill, Roger; Wooten, Margaret; Weber, Keith; Blair, Kindra; May, Jeffrey; Toombs, William

2017-01-01

NASA Wrangler is a loosely-coupled, event driven, highly parallel data aggregation service designed to take advantageof the elastic resource capabilities of cloud computing. Wrangler automatically collects Earth observational data, climate model outputs, derived remote sensing data products, and historic biophysical data for pre-, active-, and post-wildfire decision making. It is a core service of the RECOVER decision support system, which is providing rapid-response GIS analytic capabilities to state and local government agencies. Wrangler reduces to minutes the time needed to assemble and deliver crucial wildfire-related data.

Analysis of Unmanned Aerial Vehicle (UAV) hyperspectral remote sensing monitoring key technology in coastal wetland

NASA Astrophysics Data System (ADS)

Ma, Yi; Zhang, Jie; Zhang, Jingyu

2016-01-01

The coastal wetland, a transitional zone between terrestrial ecosystems and marine ecosystems, is the type of great value to ecosystem services. For the recent 3 decades, area of the coastal wetland is decreasing and the ecological function is gradually degraded with the rapid development of economy, which restricts the sustainable development of economy and society in the coastal areas of China in turn. It is a major demand of the national reality to carry out the monitoring of coastal wetlands, to master the distribution and dynamic change. UAV, namely unmanned aerial vehicle, is a new platform for remote sensing. Compared with the traditional satellite and manned aerial remote sensing, it has the advantage of flexible implementation, no cloud cover, strong initiative and low cost. Image-spectrum merging is one character of high spectral remote sensing. At the same time of imaging, the spectral curve of each pixel is obtained, which is suitable for quantitative remote sensing, fine classification and target detection. Aimed at the frontier and hotspot of remote sensing monitoring technology, and faced the demand of the coastal wetland monitoring, this paper used UAV and the new remote sensor of high spectral imaging instrument to carry out the analysis of the key technologies of monitoring coastal wetlands by UAV on the basis of the current situation in overseas and domestic and the analysis of developing trend. According to the characteristic of airborne hyperspectral data on UAV, that is "three high and one many", the key technology research that should develop are promoted as follows: 1) the atmosphere correction of the UAV hyperspectral in coastal wetlands under the circumstance of complex underlying surface and variable geometry, 2) the best observation scale and scale transformation method of the UAV platform while monitoring the coastal wetland features, 3) the classification and detection method of typical features with high precision from multi scale hyperspectral images based on time sequence. The research results of this paper will help to break the traditional concept of remote sensing monitoring coastal wetlands by satellite and manned aerial vehicle, lead the trend of this monitoring technology, and put forward a new technical proposal for grasping the distribution of the coastal wetland and the changing trend and carrying out the protection and management of the coastal wetland.

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.

Comparison of the MODIS Multilayer Cloud Detection and Thermodynamic Phase Products with CALIPSO and CloudSat

NASA Technical Reports Server (NTRS)

Platnick, Steven; King, Michael D.; Wind, Gala; Holz, Robert E.; Ackerman, Steven A.; Nagle, Fred W.

2008-01-01

CALIPSO and CloudSat, launched in June 2006, provide global active remote sensing measurements of clouds and aerosols that can be used for validation of a variety of passive imager retrievals derived from instruments flying on the Aqua spacecraft and other A-Train platforms. The most recent processing effort for the MODIS Atmosphere Team, referred to as the "Collection 5" stream, includes a research-level multilayer cloud detection algorithm that uses both thermodynamic phase information derived from a combination of solar and thermal emission bands to discriminate layers of different phases, as well as true layer separation discrimination using a moderately absorbing water vapor band. The multilayer detection algorithm is designed to provide a means of assessing the applicability of 1D cloud models used in the MODIS cloud optical and microphysical product retrieval, which are generated at a 1 h resolution. Using pixel-level collocations of MODIS Aqua, CALIOP, and CloudSat radar measurements, we investigate the global performance of the thermodynamic phase and multilayer cloud detection algorithms.

Investigation of aerosol effects on shallow marine convection - Lidar measurements during NARVAL-I and NARVAL-II

NASA Astrophysics Data System (ADS)

Groß, Silke; Wirth, Martin; Gutleben, Manuel; Ewald, Florian; Kiemle, Christoph; Kölling, Tobias; Mayer, Bernhard

2017-04-01

Clouds and aerosols have a large impact on the Earth's radiation budget by scattering and absorption of solar and terrestrial radiation. Furthermore aerosols can modify cloud properties and distribution. Up to now no sufficient understanding in aerosol-cloud interaction and in climate feedback of clouds is achieved. Especially shallow marine convection in the trade wind regions show large uncertainties in climate feedback. Thus a better understanding of these shallow marine convective clouds and how aerosols affect these clouds, e.g. by changing the cloud properties and distribution, is highly demanded. During NARVAL-I (Next-generation airborne remote-sensing for validation studies) and NARVAL-II a set of active and passive remote sensing instruments, i.e. a cloud radar, an aerosol and water vapor lidar system, microwave radiometer, a hyper spectral imager (NARVAL-II only) and radiation measurements, were installed on the German research aircraft HALO. Measurements were performed out of Barbados over the tropical North-Atlantic region in December 2013 and August 2016 to study shallow trade wind convection as well as its environment in the dry and wet season. While no or only few aerosol layers were observed above the marine boundary layer during the dry season in December 2013, part of the measurement area was influenced by high aerosol load caused by long-range transport of Saharan dust during the NARVAL-II measurements in August 2016. Measurement flights during NARVAL-II were conducted the way that we could probed aerosol influenced regions as well as areas with low aerosol load. Thus the measurements during both campaigns provide the opportunity to investigate if and how the transported aerosol layers change the distribution and formation of the shallow marine convection by altering their properties and environment. In our presentation we will focus on the lidar measurements performed during NARVAL-I and NARVAL-II. We will give an overview of the measurements and of the general aerosol and cloud situation, and we will show first results how cloud properties and distribution of shallow marine convection change in the presence of lofted aerosol layers. In particular we will determine if aerosols modify horizontal cloud distribution and cloud top height distribution by looking on the correlations between aerosol load and cloud distribution, and we will investigate if and how the presence of the lofted aerosol layer changes the properties of the clouds, e.g. by acting as ice nuclei.

Remote sensing science for the Nineties; Proceedings of IGARSS '90 - 10th Annual International Geoscience and Remote Sensing Symposium, University of Maryland, College Park, May 20-24, 1990. Vols. 1, 2, & 3

NASA Technical Reports Server (NTRS)

1990-01-01

Various papers on remote sensing (RS) for the nineties are presented. The general topics addressed include: subsurface methods, radar scattering, oceanography, microwave models, atmospheric correction, passive microwave systems, RS in tropical forests, moderate resolution land analysis, SAR geometry and SNR improvement, image analysis, inversion and signal processing for geoscience, surface scattering, rain measurements, sensor calibration, wind measurements, terrestrial ecology, agriculture, geometric registration, subsurface sediment geology, radar modulation mechanisms, radar ocean scattering, SAR calibration, airborne radar systems, water vapor retrieval, forest ecosystem dynamics, land analysis, multisensor data fusion. Also considered are: geologic RS, RS sensor optical measurements, RS of snow, temperature retrieval, vegetation structure, global change, artificial intelligence, SAR processing techniques, geologic RS field experiment, stochastic modeling, topography and Digital Elevation model, SAR ocean waves, spaceborne lidar and optical, sea ice field measurements, millimeter waves, advanced spectroscopy, spatial analysis and data compression, SAR polarimetry techniques. Also discussed are: plant canopy modeling, optical RS techniques, optical and IR oceanography, soil moisture, sea ice back scattering, lightning cloud measurements, spatial textural analysis, SAR systems and techniques, active microwave sensing, lidar and optical, radar scatterometry, RS of estuaries, vegetation modeling, RS systems, EOS/SAR Alaska, applications for developing countries, SAR speckle and texture.

An assessment of aerosol optical properties from remote-sensing observations and regional chemistry-climate coupled models over Europe

NASA Astrophysics Data System (ADS)

Palacios-Peña, Laura; Baró, Rocío; Baklanov, Alexander; Balzarini, Alessandra; Brunner, Dominik; Forkel, Renate; Hirtl, Marcus; Honzak, Luka; María López-Romero, José; Montávez, Juan Pedro; Pérez, Juan Luis; Pirovano, Guido; San José, Roberto; Schröder, Wolfram; Werhahn, Johannes; Wolke, Ralf; Žabkar, Rahela; Jiménez-Guerrero, Pedro

2018-04-01

Atmospheric aerosols modify the radiative budget of the Earth due to their optical, microphysical and chemical properties, and are considered one of the most uncertain climate forcing agents. In order to characterise the uncertainties associated with satellite and modelling approaches to represent aerosol optical properties, mainly aerosol optical depth (AOD) and Ångström exponent (AE), their representation by different remote-sensing sensors and regional online coupled chemistry-climate models over Europe are evaluated. This work also characterises whether the inclusion of aerosol-radiation (ARI) or/and aerosol-cloud interactions (ACI) help improve the skills of modelling outputs.Two case studies were selected within the EuMetChem COST Action ES1004 framework when important aerosol episodes in 2010 all over Europe took place: a Russian wildfire episode and a Saharan desert dust outbreak that covered most of the Mediterranean Sea. The model data came from different regional air-quality-climate simulations performed by working group 2 of EuMetChem, which differed according to whether ARI or ACI was included or not. The remote-sensing data came from three different sensors: MODIS, OMI and SeaWIFS. The evaluation used classical statistical metrics to first compare satellite data versus the ground-based instrument network (AERONET) and then to evaluate model versus the observational data (both satellite and ground-based data).Regarding the uncertainty in the satellite representation of AOD, MODIS presented the best agreement with the AERONET observations compared to other satellite AOD observations. The differences found between remote-sensing sensors highlighted the uncertainty in the observations, which have to be taken into account when evaluating models. When modelling results were considered, a common trend for underestimating high AOD levels was observed. For the AE, models tended to underestimate its variability, except when considering a sectional approach in the aerosol representation. The modelling results showed better skills when ARI+ACI interactions were included; hence this improvement in the representation of AOD (above 30 % in the model error) and AE (between 20 and 75 %) is important to provide a better description of aerosol-radiation-cloud interactions in regional climate models.

Estimation de la superficie du couvert nival a partir d'une combinaison des donnees de teledetection MODIS et AMSR-E dans un contexte de prevision des crues printanieres au Quebec

NASA Astrophysics Data System (ADS)

Bergeron, Jean

Snow cover estimation is a principal source of error for spring streamflow simulations in Québec, Canada. Optical and near infrared remote sensing can improve snow cover area (SCA) estimation due to high spatial resolution but is limited by cloud cover and incoming solar radiation. Passive microwave remote sensing is complementary by its near-transparence to cloud cover and independence to incoming solar radiation, but is limited by its coarse spatial resolution. The study aims to create an improved SCA product from blended passive microwave (AMSR-E daily L3 Brightness Temperature) and optical (MODIS Terra and Aqua daily snow cover L3) remote sensing data in order to improve estimation of river streamflow caused by snowmelt with Québec's operational MOHYSE hydrological model through direct-insertion of the blended SCA product in a coupled snowmelt module (SPH-AV). SCA estimated from AMSR-E data is first compared with SCA estimated with MODIS, as well as with in situ snow depth measurements. Results show good agreement (+95%) between AMSR-E-derived and MODIS-derived SCA products in spring but comparisons with Environment Canada ground stations and SCA derived from Advanced Very High Resolution Radiometer (AVHRR) data show lesser agreements (83 % and 74% respectively). Results also show that AMSR-E generally underestimates SCA. Assimilating the blended snow product in SPH-AV coupled with MOHYSE yields significant improvement of simulated streamflow for the aux Écorces et au Saumon rivers overall when compared with simulations with no update during thaw events, These improvements are similar to results driven by biweekly ground data. Assimilation of remotely-sensed passive microwave data was also found to have little positive impact on springflood forecast due to the difficulty in differentiating melting snow from snow-free surfaces. Considering the direct-insertion and Newtonian nudging assimilation methods, the study also shows the latter method to be superior to the former, notably when assimilating noisy data. Keywords: Snow cover, spring streamflow, MODIS, AMSR-E, hydrological model.

Using Remotely Sensed Fluorescence and Soil Moisture to Better Understand the Seasonal Cycle of Tropical Grasslands

NASA Astrophysics Data System (ADS)

Smith, Dakota Carlysle

Seasonal grasslands account for a large area of Earth's land cover. Annual and seasonal changes in these grasslands have profound impacts on Earth's carbon, energy, and water cycles. In tropical grasslands, growth is commonly water-limited and the landscape oscillates between highly productive and unproductive. As the monsoon begins, soils moisten providing dry grasses the water necessary to photosynthesize. However, along with the rain come clouds that obscure satellite products that are commonly used to study productivity in these areas. To navigate this issue, we used solar induced fluorescence (SIF) products from OCO-2 along with soil moisture products from the Soil Moisture Active Passive satellite (SMAP) to "see through" the clouds to monitor grassland productivity. To get a broader understanding of the vegetation dynamics, we used the Simple Biosphere Model (SiB4) to simulate the seasonal cycles of vegetation. In conjunction with SiB4, the remotely sensed SIF and soil moisture observations were utilized to paint a clearer picture of seasonal productivity in tropical grasslands. The remotely sensed data is not available for every place at one time or at every time for one place. Thus, the study was focused on a large area from 15° E to 35° W and from 8°S to 20°N in the African Sahel. Instead of studying productivity relative to time, we studied it relative to soil moisture. Through this investigation we found soil moisture thresholds for the emergence of grassland growth, near linear grassland growth, and maturity of grassland growth. We also found that SiB4 overestimates SIF by about a factor of two for nearly every value of soil moisture. On the whole, SiB4 does a surprisingly good job of predicting the response of seasonal growth in tropical grasslands to soil moisture. Future work will continue to integrate remotely sensed SIF & soil moisture with SiB4 to add to our growing knowledge of carbon, water, and energy cycling in tropical grasslands.

Satellite-Surface Perspectives of Air Quality and Aerosol-Cloud Effects on the Environment: An Overview of 7-SEAS BASELInE

NASA Technical Reports Server (NTRS)

Tsay, Si-Chee; Maring, Hal B.; Lin, Neng-Huei; Buntoung, Sumaman; Chantara, Somporn; Chuang, Hsiao-Chi; Gabriel, Philip M.; Goodloe, Colby S.; Holben, Brent N.; Hsiao, Ta-Chih;

Observed microphysical changes in Arctic mixed-phase clouds when transitioning from sea-ice to open ocean

NASA Astrophysics Data System (ADS)

Young, Gillian; Jones, Hazel M.; Crosier, Jonathan; Bower, Keith N.; Darbyshire, Eoghan; Taylor, Jonathan W.; Liu, Dantong; Allan, James D.; Williams, Paul I.; Gallagher, Martin W.; Choularton, Thomas W.

2016-04-01

The Arctic sea-ice is intricately coupled to the atmosphere[1]. The decreasing sea-ice extent with the changing climate raises questions about how Arctic cloud structure will respond. Any effort to answer these questions is hindered by the scarcity of atmospheric observations in this region. Comprehensive cloud and aerosol measurements could allow for an improved understanding of the relationship between surface conditions and cloud structure; knowledge which could be key in validating weather model forecasts. Previous studies[2] have shown via remote sensing that cloudiness increases over the marginal ice zone (MIZ) and ocean with comparison to the sea-ice; however, to our knowledge, detailed in-situ data of this transition have not been previously presented. In 2013, the Aerosol-Cloud Coupling and Climate Interactions in the Arctic (ACCACIA) campaign was carried out in the vicinity of Svalbard, Norway to collect in-situ observations of the Arctic atmosphere and investigate this issue. Fitted with a suite of remote sensing, cloud and aerosol instrumentation, the FAAM BAe-146 aircraft was used during the spring segment of the campaign (Mar-Apr 2013). One case study (23rd Mar 2013) produced excellent coverage of the atmospheric changes when transitioning from sea-ice, through the MIZ, to the open ocean. Clear microphysical changes were observed, with the cloud liquid-water content increasing by almost four times over the transition. Cloud base, depth and droplet number also increased, whilst ice number concentrations decreased slightly. The surface warmed by ~13 K from sea-ice to ocean, with minor differences in aerosol particle number (of sizes corresponding to Cloud Condensation Nuclei or Ice Nucleating Particles) observed, suggesting that the primary driver of these microphysical changes was the increased heat fluxes and induced turbulence from the warm ocean surface as expected. References: [1] Kapsch, M.L., Graversen, R.G. and Tjernström, M. Springtime atmospheric energy transport and the control of Arctic summer sea-ice extent. Nature Clim. Change 3, 744-748, doi:10.1038/nclimate1884 (2013) [2] Palm, S. P., Strey, S. T., Spinhirne, J., and Markus, T.: Influence of Arctic sea ice extent on polar cloud fraction and vertical structure and implications for regional climate. Journal of Geophysical Research (Atmospheres), 115, D21209, doi:10.1029/2010JD013900 (2010)

Airborne lidar measurements to investigate the impact of long-range transported dust on shallow marine trade wind convection

NASA Astrophysics Data System (ADS)

Gross, S.; Gutleben, M.; Wirth, M.; Ewald, F.

2017-12-01

Aerosols and clouds are still main contributors to uncertainties in estimates and interpretation of the Earth's changing energy budget. Their interaction with the Earth's radiation budged has a direct component by scattering and absorbing solar and terrestrial radiation, and an indirect component, e.g. as aerosols modify the properties and thus the life-time of clouds or by changing the atmosphere's stability. Up to know now sufficient understanding in aerosol-cloud interaction and climate feedback is achieved. Thus studies with respect to clouds, aerosols, their interaction and influence on the radiation budged are highly demanded. In August 2016 the NARVAL-II (Next-generation airborne remote sensing for validation studies) mission took place. Measurements with a combined active (high spectral resolution and water vapor differential absorption lidar and cloud radar) and passive remote sensing (microwave radiometer, hyper spectral imager, radiation measurements) payload were performed with the German high altitude and long-range research aircraft HALO over the subtropical North-Atlantic Ocean to study shallow marine convection during the wet and dusty season. With this, NARVAL-II is follow-up of the NARVAL-I mission which took place during the dry and dust free season in December 2013. During NARVAL-II the measurement flights were designed the way to sample dust influenced areas as well as dust free areas in the trades. One main objective was to investigate the optical and macro physical properties of the dust layer, differences in cloud occurrence in dusty and non-dusty areas, and to study the influence of aerosols on the cloud properties and formation. This allows comparisons of cloud and aerosol distribution as well as their environment between the dry and the wet season, and of cloud properties and distribution with and without the influence of long-range transported dust across the Atlantic Ocean. In our presentation we will give an overview of the NARVAL-I and NARVAL-II mission and on the general measurement situation. For the analysis we focus on the lidar measurements during both campaigns. We will show comparisons of the cloud distribution between both measurement seasons and we will show first results of how aerosol distribution and properties change in the presence of long-range transported dust.

Conference on Satellite Meteorology and Oceanography, 6th, Atlanta, GA, Jan. 5-10, 1992, Preprints

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

Not Available

The present volume on satellite meteorology and oceanography discusses cloud retrieval from collocated IR sounder data and imaging systems, satellite retrievals of marine stratiform cloud systems, multispectral analysis of satellite observations of smoke and dust, and image and graphical analysis of principal components of satellite sounding channels. Attention is given to an evaluation of results from classification retrieval methods, the use of TOVS radiances, estimation of path radiance on the basis of remotely sensed data, and a reexamination of SST as a predictor for tropical storm intensity. Topics addressed include optimal smoothing of GOES VAS for upper-atmosphere thermal waves, obtainingmore » cloud motion vectors from polar orbiting satellites, the use of cloud relative animation in the analysis of satellite data, and investigations of a polar low using geostationary satellite data.« less

The evaluation and development of the Met Office Unified Model using surface and space borne radar.

NASA Astrophysics Data System (ADS)

Petch, J.

2012-12-01

The Met Office Unified Model is used for the prediction of weather and climate on time scales of hours through to centuries. Therefore, the parametrizations in that model need to work on weather and climate timescale, and with grid-lengths from hundres of meters through to several hundred kilometres. Focusing on the development of the cloud and radiation schemes I will discuss how we are using ground-based remote-sensing observations from Chilbolton (England) and a combination of Cloudsat and Calipso data to evaluate and improve the performance of the model. I will show how the prediction of the clouds has improved since the AR5 version of the model and how we have developed an improved cloud generator to rebresent the sub-grid variability of clouds for radiative transfer.

Offshore Radiation Observations for Climate Research at the CERES Ocean Validation Experiment

NASA Technical Reports Server (NTRS)

Rutledge, Charles K.; Schuster, Gregory L.; Charlock, Thomas P.; Denn, Frederick M.; Smith, William L., Jr.; Fabbri, Bryan E.; Madigan, James J., Jr.; Knapp, Robert J.

2006-01-01

When radiometers on a satellite are pointed towards the planet with the goal of understanding a phenomenon quantitatively, rather than just creating a pleasing image, the task at hand is often problematic. The signal at the detector can be affected by scattering, absorption, and emission; and these can be due to atmospheric constituents (gases, clouds, and aerosols), the earth's surface, and subsurface features. When targeting surface phenomena, the remote sensing algorithm needs to account for the radiation associated with the atmospheric constituents. Likewise, one needs to correct for the radiation leaving the surface, when atmospheric phenomena are of interest. Rigorous validation of such remote sensing products is a real challenge. In visible and near infrared wavelengths, the jumble of effects on atmospheric radiation are best accomplished over dark surfaces with fairly uniform reflective properties (spatial homogeneity) in the satellite instrument's field of view (FOV). The ocean's surface meets this criteria; land surfaces - which are brighter, more spatially inhomogeneous, and more changeable with time - generally do not. NASA's Clouds and the Earth's Radiant Energy System (CERES) project has used this backdrop to establish a radiation monitoring site in Virginia's coastal Atlantic Ocean. The project, called the CERES Ocean Validation Experiment (COVE), is located on a rigid ocean platform allowing the accurate measurement of radiation parameters that require precise leveling and pointing unavailable from ships or buoys. The COVE site is an optimal location for verifying radiative transfer models and remote sensing algorithms used in climate research; because of the platform's small size, there are no island wake effects; and suites of sensors can be simultaneously trained both on the sky and directly on ocean itself. This paper describes the site, the types of measurements made, multiple years of atmospheric and ocean surface radiation observations, and satellite validation results.

Generalized Radiative Transfer as an Efficient Computational Tool for Spatial and/or Spectral Integration over Unresolved Variability in Multi-Angle Observations

NASA Astrophysics Data System (ADS)

Davis, A. B.; Xu, F.; Diner, D. J.

2017-12-01

Two perennial problems in applied theoretical and computational radiative transfer (RT) are: (1) the impact of unresolved spatial variability on large-scale fluxes (in climate models) or radiances (in remote sensing); and (2) efficient-yet-accurate estimation of broadband spectral integrals in radiant energy budget estimation as well as in remote sensing, in particular, of trace gases.Generalized RT (GRT) is a modification of classic RT in an optical medium with uniform extinction where Beer's exponential law for direct transmission is replaced by a monotonically decreasing function with a slower power-law decay. In a convenient parameterized version of GRT, mean extinction replaces the uniform value and just one new property is introduced. As a non-dimensional metric for the unresolved variability, we use the square of the mean extinction coefficient divided by its variance. This parameter is also the exponent of the power-law tail of the modified transmission law.This specific form of sub-exponential transmission has explored for almost two decades in application to spatial variability in the presence of long-range correlations, much like in turbulent media such as clouds, with a focus on multiple scattering. It has also been proposed by Conley and Collins (JQSRT, 112, 1525-, 2011) to improve on the standard (weak-line) implementation of the correlated-k technique for efficient spectral integration.We have merged these two applications within a rigorous formulation of the combined problem, and solve the new integral RT equations in the single-scattering limit. The result is illustrated by addressing practical problems in multi-angle remote sensing of aerosols using the O2 A-band, an emerging methodology for passive profiling of coarse aerosols and clouds.

Timing constraints on remote sensing of wildland fire burned area in the southeastern US

USGS Publications Warehouse

Picotte, J.J.; Robertson, K.

2011-01-01

Remote sensing using Landsat Thematic Mapper (TM) satellite imagery is increasingly used for mapping wildland fire burned area and burn severity, owing to its frequency of collection, relatively high resolution, and availability free of charge. However, rapid response of vegetation following fire and frequent cloud cover pose challenges to this approach in the southeastern US. We assessed these timing constraints by using a series of Landsat TM images to determine how rapidly the remotely sensed burn scar signature fades following prescribed burns in wet flatwoods and depression swamp community types in the Apalachicola National Forest, Florida, USA during 2006. We used both the Normalized Burn Ratio (NBR) of reflectance bands sensitive to vegetation and exposed soil cover, as well as the change in NBR from before to after fire (dNBR), to estimate burned area. We also determined the average and maximum amount of time following fire required to obtain a cloud-free image for burns in each month of the year, as well as the predicted effect of this time lag on percent accuracy of burn scar estimates. Using both NBR and dNBR, the detectable area decreased linearly 9% per month on average over the first four months following fire. Our findings suggest that the NBR and dNBR methods for monitoring burned area in common southeastern US vegetation community types are limited to an average of 78-90% accuracy among months of the year, with individual burns having values as low as 38%, if restricted to use of Landsat 5 TM imagery. However, the majority of burns can still be mapped at accuracies similar to those in other regions of the US, and access to additional sources of satellite imagery would improve overall accuracy. ?? 2011 by the authors.

Timing constraints on remote sensing of wildland fire burned area in the southeastern US

USGS Publications Warehouse

Picotte, Joshua J.; Robertson, Kevin

2011-01-01

Remote sensing using Landsat Thematic Mapper (TM) satellite imagery is increasingly used for mapping wildland fire burned area and burn severity, owing to its frequency of collection, relatively high resolution, and availability free of charge. However, rapid response of vegetation following fire and frequent cloud cover pose challenges to this approach in the southeastern US. We assessed these timing constraints by using a series of Landsat TM images to determine how rapidly the remotely sensed burn scar signature fades following prescribed burns in wet flatwoods and depression swamp community types in the Apalachicola National Forest, Florida, USA during 2006. We used both the Normalized Burn Ratio (NBR) of reflectance bands sensitive to vegetation and exposed soil cover, as well as the change in NBR from before to after fire (dNBR), to estimate burned area. We also determined the average and maximum amount of time following fire required to obtain a cloud-free image for burns in each month of the year, as well as the predicted effect of this time lag on percent accuracy of burn scar estimates. Using both NBR and dNBR, the detectable area decreased linearly 9% per month on average over the first four months following fire. Our findings suggest that the NBR and dNBR methods for monitoring burned area in common southeastern US vegetation community types are limited to an average of 78–90% accuracy among months of the year, with individual burns having values as low as 38%, if restricted to use of Landsat 5 TM imagery. However, the majority of burns can still be mapped at accuracies similar to those in other regions of the US, and access to additional sources of satellite imagery would improve overall accuracy.

Remote sensing with intense filaments enhanced by adaptive optics

NASA Astrophysics Data System (ADS)

Daigle, J.-F.; Kamali, Y.; Châteauneuf, M.; Tremblay, G.; Théberge, F.; Dubois, J.; Roy, G.; Chin, S. L.

2009-11-01

A method involving a closed loop adaptive optic system is investigated as a tool to significantly enhance the collected optical emissions, for remote sensing applications involving ultrafast laser filamentation. The technique combines beam expansion and geometrical focusing, assisted by an adaptive optics system to correct the wavefront aberrations. Targets, such as a gaseous mixture of air and hydrocarbons, solid lead and airborne clouds of contaminated aqueous aerosols, were remotely probed with filaments generated at distances up to 118 m after the focusing beam expander. The integrated backscattered signals collected by the detection system (15-28 m from the filaments) were increased up to a factor of 7, for atmospheric N2 and solid lead, when the wavefronts were corrected by the adaptive optic system. Moreover, an extrapolation based on a simplified version of the LIDAR equation showed that the adaptive optic system improved the detection distance for N2 molecular fluorescence, from 45 m for uncorrected wavefronts to 125 m for corrected.

SCIAMACHY validation by aircraft remote measurements: design, execution, and first results of the SCIA-VALUE mission

NASA Astrophysics Data System (ADS)

Fix, A.; Ehret, G.; Flentje, H.; Poberaj, G.; Gottwald, M.; Finkenzeller, H.; Bremer, H.; Bruns, M.; Burrows, J. P.; Kleinböhl, A.; Küllmann, H.; Kuttippurath, J.; Richter, A.; Wang, P.; Heue, K.-P.; Platt, U.; Wagner, T.

2004-12-01

For the first time three different remote sensing instruments - a sub-millimeter radiometer, a differential optical absorption spectrometer in the UV-visible spectral range, and a lidar - were deployed aboard DLR's meteorological research aircraft Falcon 20 to validate a large number of SCIAMACHY level 2 and off-line data products such as O3, NO2, N2O, BrO, OClO, H2O, aerosols, and clouds. Within two main validation campaigns of the SCIA-VALUE mission (SCIAMACHY VALidation and Utilization Experiment) extended latitudinal cross-sections stretching from polar regions to the tropics as well as longitudinal cross sections at polar latitudes at about 70° N and the equator have been generated. This contribution gives an overview over the campaigns performed and reports on the observation strategy for achieving the validation goals. We also emphasize the synergetic use of the novel set of aircraft instrumentation and the usefulness of this innovative suite of remote sensing instruments for satellite validation.

Synergistic use of MODIS cloud products and AIRS radiance measurements for retrieval of cloud parameters

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.

Understanding rapid changes in phase partitioning between cloud liquid and ice in an Arctic stratiform mixed-phase cloud

NASA Astrophysics Data System (ADS)

Kalesse, Heike; de Boer, Gijs; Solomon, Amy; Oue, Mariko; Ahlgrimm, Maike; Zhang, Damao; Shupe, Matthew; Luke, Edward; Protat, Alain

2016-04-01

In the Arctic, a region particularly sensitive to climate change, mixed-phase clouds occur as persistent single or multiple stratiform layers. For many climate models, the correct partitioning of hydrometeor phase (liquid vs. ice) remains a challenge. However, this phase partitioning plays an important role for precipitation processes and the radiation budget. To better understand the partitioning of phase in Arctic clouds, observations using a combination of surface-based remote sensors are useful. In this study, the focus is on a persistent low-level single-layer stratiform Arctic mixed-phase cloud observed during March 11-12, 2013 at the US Department of Energy's (DOE) Atmospheric Radiation Measurement (ARM) North Slope of Alaska (NSA) permanent site in Barrow, Alaska. This case is of particular interest due to two significant shifts in observed precipitation intensity over a 36 hour period. For the first 12 hours of this case, the observed liquid portion of the cloud cover featured a stable cloud top height with a gradually descending liquid cloud base and continuous ice precipitation. Then the ice precipitation intensity significantly decreased. A second decrease in ice precipitation intensity was observed a few hours later coinciding with the advection of a cirrus over the site. Through analysis of the data collected by extensive ground-based remote-sensing and in-situ observing systems as well as Nested Weather Research and Forecasting (WRF) simulations and ECMWF radiation scheme simulations, we try to shed light on the processes responsible for these rapid changes in precipitation rates. A variety of parameters such as the evolution of the internal dynamics and microphysics of the low-level mixed-phase cloud and the influence of the cirrus cloud are evaluated.

Cloud Ice: A Climate Model Challenge With Signs and Expectations of Progress

NASA Astrophysics Data System (ADS)

Li, F.; Waliser, D.; Bacmeister, J.; Chern, J.; Del Genio, T.; Jiang, J.; Kharitondov, M.; Liou, K.; Meng, H.; Minnis, P.; Rossow, B.; Stephens, G.; Sun-Mack, S.; Tao, W.; Vane, D.; Woods, C.; Tompkins, A.; Wu, D.

2007-12-01

Global climate models (GCMs), including those assessed in the IPCC AR4, exhibit considerable disagreement in the amount of cloud ice - both in terms of the annual global mean as well as their spatial variability. Global measurements of cloud ice have been difficult due to the challenges involved in remotely sensing ice water content (IWC) and its vertical profile - including complications associated with multi-level clouds, mixed-phases and multiple hydrometer types, the uncertainty in classifying ice particle size and shape for remote retrievals, and the relatively small time and space scales associated with deep convection. Together, these measurement difficulties make it a challenge to characterize and understand the mechanisms of ice cloud formation and dissipation. Fortunately, there are new observational resources recently established that can be expected to lead to considerable reduction in the observational uncertainties of cloud ice, and in turn improve the fidelity of model representations. Specifically, these include the Microwave Limb Sounder (MLS) on the Earth Observing System (EOS) Aura satellite, and the CloudSat and Calipso satellite missions, all of which fly in formation in what is referred to as the A-Train. Based on radar and limb-sounding techniques, these new satellite measurements provide a considerable leap forward in terms of the information gathered regarding upper-tropospheric cloud IWC as well as other macrophysical and microphysical properties. In this presentation, we describe the current state of GCM representations of cloud ice and their associated uncertainties, the nature of the new observational resources for constraining cloud ice values in GCMs, the challenges in making model-data comparisons with these data resources, and prospects for near-term improvements in model representations.

Remote Sensing of chlorophyll fluorescence and the impact of clouds on the retrival

NASA Astrophysics Data System (ADS)

Köhler, Philipp; Guanter, Luis; Frankenberg, Christian

2013-04-01

Remote sensing of sun-induced chlorophyll fluorescence (SIF) is a new, alternative option to gain information about terrestrial photosynthesis and CO2 assimilation on a global scale. The SIF is an electromagnetic signal emitted in the aprox. 650-800 nm spectral window by the photosynthesis apparatus, and can therefore be considered as a direct indicator of plant biochemical processes. The general approach to measure SIF from space is the evaluation of the in-filling of solar Fraunhofer lines or atmospheric absorption bands by SIF. To distinguish the SIF signal from the total incoming radiance at the sensor, which is about 100 times more intense, is a challenge and high resolution measurements are required. The high spectral resolution (approx. 0.02 nm) of the Fourier Transform Spectrometer (FTS) on-board the Greenhouse Gases Observing Satellite (GOSAT) enables such a measurement of SIF by means of the evaluation of the in-filling of solar Fraunhofer lines by SIF. The narrow wavelength band from 755 to 759 nm and around 770 nm can be used for this purpose because they are free from atmospheric absorption features, the solar radiation shows several Fraunhofer lines and the SIF values in this region are relatively high. A new SIF retrieval approach (GARLiC, for GOSAT Retrieval of cholorphyll fluorescence) will be presented in this contribution. This method is intended to simplify some of the assumptions of existing retrieval approaches without a loss in accuracy. The comparison of the GARLiC fluorescence retrievals with two state-of-the-art SIR retrieval methods such as those by Frankenberg et al. (2011) and Guanter et al. (2012) from GOSAT data shows corresponding and feasible results. In addition to the basics of SIF remote sensing, this contribution will assess the effect of clouds in the retrieval. To do this, the SIF retrieval has been coupled to a cloud optical thickness (COT) retrieval algorithm adapted to GOSAT-FTS O2A-band measurements, so that SIF and COT are estimated from the same soundings. Especial attention will be given to the impact of optically-thin cirrus clouds on SIF retrievals, which is of particular interest over tropical rainforest areas. The detection of cirrus clouds is difficult due to their optical properties. Therefore the measurement of GOSAT in the 2 µm region is applicable to add a cirrus filter. Due to the strongly absorbing H2O-band in this spectral region, the signal in clear sky conditions should not be significantly higher than the noise level of the instrument. With the appearance of cirrus clouds, the light path is shortened and less absorption of H2O yields to a significant signal. Based on this principle, different thresholds for a cirrus filter are applied to study the impact of cirrus clouds on the retrieved SIF.

Smart Point Cloud: Definition and Remaining Challenges

NASA Astrophysics Data System (ADS)

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

2016-10-01

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

Pattern recognition of satellite cloud imagery for improved weather prediction

NASA Technical Reports Server (NTRS)

Gautier, Catherine; Somerville, Richard C. J.; Volfson, Leonid B.

1986-01-01

The major accomplishment was the successful development of a method for extracting time derivative information from geostationary meteorological satellite imagery. This research is a proof-of-concept study which demonstrates the feasibility of using pattern recognition techniques and a statistical cloud classification method to estimate time rate of change of large-scale meteorological fields from remote sensing data. The cloud classification methodology is based on typical shape function analysis of parameter sets characterizing the cloud fields. The three specific technical objectives, all of which were successfully achieved, are as follows: develop and test a cloud classification technique based on pattern recognition methods, suitable for the analysis of visible and infrared geostationary satellite VISSR imagery; develop and test a methodology for intercomparing successive images using the cloud classification technique, so as to obtain estimates of the time rate of change of meteorological fields; and implement this technique in a testbed system incorporating an interactive graphics terminal to determine the feasibility of extracting time derivative information suitable for comparison with numerical weather prediction products.

Comparison of the MODIS Collection 5 Multilayer Cloud Detection Product with CALIPSO

NASA Technical Reports Server (NTRS)

Platnick, Steven; Wind, Gala; King, Michael D.; Holz, Robert E.; Ackerman, Steven A.; Nagle, Fred W.

2010-01-01

CALIPSO, launched in June 2006, provides global active remote sensing measurements of clouds and aerosols that can be used for validation of a variety of passive imager retrievals derived from instruments flying on the Aqua spacecraft and other A-Train platforms. The most recent processing effort for the MODIS Atmosphere Team, referred to as the Collection 5 scream, includes a research-level multilayer cloud detection algorithm that uses both thermodynamic phase information derived from a combination of solar and thermal emission bands to discriminate layers of different phases, as well as true layer separation discrimination using a moderately absorbing water vapor band. The multilayer detection algorithm is designed to provide a means of assessing the applicability of 1D cloud models used in the MODIS cloud optical and microphysical product retrieval, which are generated at a 1 km resolution. Using pixel-level collocations of MODIS Aqua, CALIOP, we investigate the global performance of multilayer cloud detection algorithms (and thermodynamic phase).

Spatial Distribution of Large Cloud Drops

NASA Technical Reports Server (NTRS)

Marshak, A.; Knyazikhin, Y.; Larsen, M.; Wiscombe, W.

2004-01-01

By analyzing aircraft measurements of individual drop sizes in clouds, we have shown in a companion paper (Knyazikhin et al., 2004) that the probability of finding a drop of radius r at a linear scale l decreases as l(sup D(r)) where 0 less than or equal to D(r) less than or equal to 1. This paper shows striking examples of the spatial distribution of large cloud drops using models that simulate the observed power laws. In contrast to currently used models that assume homogeneity and therefore a Poisson distribution of cloud drops, these models show strong drop clustering, the more so the larger the drops. The degree of clustering is determined by the observed exponents D(r). The strong clustering of large drops arises naturally from the observed power-law statistics. This clustering has vital consequences for rain physics explaining how rain can form so fast. It also helps explain why remotely sensed cloud drop size is generally biased and why clouds absorb more sunlight than conventional radiative transfer models predict.

Improving winter leaf area index estimation in coniferous forests and its significance in estimating the land surface albedo

NASA Astrophysics Data System (ADS)

Wang, Rong; Chen, Jing M.; Pavlic, Goran; Arain, Altaf

2016-09-01

Winter leaf area index (LAI) of evergreen coniferous forests exerts strong control on the interception of snow, snowmelt and energy balance. Simulation of winter LAI and associated winter processes in land surface models is challenging. Retrieving winter LAI from remote sensing data is difficult due to cloud contamination, poor illumination, lower solar elevation and higher radiation reflection by snow background. Underestimated winter LAI in evergreen coniferous forests is one of the major issues limiting the application of current remote sensing LAI products. It has not been fully addressed in past studies in the literature. In this study, we used needle lifespan to correct winter LAI in a remote sensing product developed by the University of Toronto. For the validation purpose, the corrected winter LAI was then used to calculate land surface albedo at five FLUXNET coniferous forests in Canada. The RMSE and bias values for estimated albedo were 0.05 and 0.011, respectively, for all sites. The albedo map over coniferous forests across Canada produced with corrected winter LAI showed much better agreement with the GLASS (Global LAnd Surface Satellites) albedo product than the one produced with uncorrected winter LAI. The results revealed that the corrected winter LAI yielded much greater accuracy in simulating land surface albedo, making the new LAI product an improvement over the original one. Our study will help to increase the usability of remote sensing LAI products in land surface energy budget modeling.

Simulating Local and Intercontinental Pollutant Effects of Biomass Burning: Integration of Several Remotely Sensed Datasets

NASA Technical Reports Server (NTRS)

Chatfield, Robert B.; Vastano, John A.; Guild, Liane; Hlavka, Christine; Brass, James A.; Russell, Philip B. (Technical Monitor)

1994-01-01

Burning to clear land for crops and to destroy pests is an integral and largely unavoidable part of tropical agriculture. It is easy to note but difficult to quantify using remote sensing. This report describes our efforts to integrate remotely sensed data into our computer model of tropical chemical trace-gas emissions, weather, and reaction chemistry (using the MM5 mesoscale model and our own Global-Regional Atmospheric Chemistry Simulator). The effects of burning over the continents of Africa and South America have been noticed in observations from several satellites. Smoke plumes hundreds of kilometers long may be seen individually, or may merge into a large smoke pall over thousands of kilometers of these continents. These features are related to intense pollution in the much more confined regions with heavy burning. These emissions also translocate nitrogen thousands of kilometers in the tropical ecosystems, with large fixed-nitrogen losses balanced partially by locally intense fertilization downwind, where nitric acid is rained out. At a much larger scale, various satellite measurements have indicated the escape of carbon monoxide and ozone into large filaments which extend across the Tropical and Southern Atlantic Ocean. Our work relates the source emissions, estimated in part from remote sensing, in part from conventional surface reports, to the concentrations of these gases over these intercontinental regions. We will mention work in progress to use meteorological satellite data (AVHRR, GOES, and Meteosat) to estimate the surface temperature and extent and height of clouds, and explain why these uses are so important in our computer simulations of global biogeochemistry. We will compare our simulations and interpretation of remote observations to the international cooperation involving Brazil, South Africa, and the USA in the TRACE-A (Transport and Atmospheric Chemistry near the Equator - Atlantic) and SAFARI (Southern Africa Fire Atmosphere Research Initiative) and remote-sensing /aircraft/ecosystem observational campaigns.

Ground-based Network and Supersite Measurements for Studying Aerosol Properties and Aerosol-Cloud Interactions

NASA Technical Reports Server (NTRS)

Tsay, Si-Chee; Holben, Brent N.

2008-01-01

From radiometric principles, it is expected that the retrieved properties of extensive aerosols and clouds from reflected/emitted measurements by satellite (and/or aircraft) should be consistent with those retrieved from transmitted/emitted radiance observed at the surface. Although space-borne remote sensing observations contain large spatial domain, they are often plagued by contamination of surface signatures. Thus, ground-based in-situ and remote-sensing measurements, where signals come directly from atmospheric constituents, the sun, and the Earth-atmosphere interactions, provide additional information content for comparisons that confirm quantitatively the usefulness of the integrated surface, aircraft, and satellite datasets. The development and deployment of AERONET (AErosol RObotic NETwork) sunphotometer network and SMART-COMMIT (Surface-sensing Measurements for Atmospheric Radiative Transfer - Chemical, Optical & Microphysical Measurements of In-situ Troposphere) mobile supersite are aimed for the optimal utilization of collocated ground-based observations as constraints to yield higher fidelity satellite retrievals and to determine any sampling bias due to target conditions. To characterize the regional natural and anthropogenic aerosols, AERONET is an internationally federated network of unique sunphotometry that contains more than 250 permanent sites worldwide. Since 1993, there are more than 480 million aerosol optical depth observations and about 15 sites have continuous records longer than 10 years for annual/seasonal trend analyses. To quantify the energetics of the surface-atmosphere system and the atmospheric processes, SMART-COMMIT instrument into three categories: flux radiometer, radiance sensor and in-situ probe. Through participation in many satellite remote-sensing/retrieval and validation projects over eight years, SMART-COMMIT have gradually refine( and been proven vital for field deployment. In this paper, we will demonstrate the capability of AERONET SMART-COMMIT in current Asian Monsoon Year-2008 campaigns that are designed and being executed to study the compelling variability in temporal scale of both anthropogenic and natural aerosols (e.g., airborne dust, smoke, mega-city pollutant). Feedback mechanisms between aerosol radiative effects and monsoon dynamics have been recently proposed, however there is a lack of consensus on whether aerosol forcing would be more likely to enhance or reduce the strength of the monsoon circulation. We envision robust approaches which well-collocated ground-based measurements and space-borne observations will greatly advance our understanding of absorbing aerosols (e.g., "Global Dimming" vs. "Elevated Heat-Pump" effects) on aerosol cloud water cycle interactions.

a New Approach for Accuracy Improvement of Pulsed LIDAR Remote Sensing Data

NASA Astrophysics Data System (ADS)

Zhou, G.; Huang, W.; Zhou, X.; He, C.; Li, X.; Huang, Y.; Zhang, L.

2018-05-01

In remote sensing applications, the accuracy of time interval measurement is one of the most important parameters that affect the quality of pulsed lidar data. The traditional time interval measurement technique has the disadvantages of low measurement accuracy, complicated circuit structure and large error. A high-precision time interval data cannot be obtained in these traditional methods. In order to obtain higher quality of remote sensing cloud images based on the time interval measurement, a higher accuracy time interval measurement method is proposed. The method is based on charging the capacitance and sampling the change of capacitor voltage at the same time. Firstly, the approximate model of the capacitance voltage curve in the time of flight of pulse is fitted based on the sampled data. Then, the whole charging time is obtained with the fitting function. In this method, only a high-speed A/D sampler and capacitor are required in a single receiving channel, and the collected data is processed directly in the main control unit. The experimental results show that the proposed method can get error less than 3 ps. Compared with other methods, the proposed method improves the time interval accuracy by at least 20 %.

Interannual variation of the surface temperature of tropical forests from satellite observations

DOE PAGES

Gao, Huilin; Zhang, Shuai; Fu, Rong; ...

2016-01-01

Land surface temperatures (LSTs) within tropical forests contribute to climate variations. However, observational data are very limited in such regions. This study used passive microwave remote sensing data from the Special Sensor Microwave/Imager (SSM/I) and the Special Sensor Microwave Imager Sounder (SSMIS), providing observations under all weather conditions, to investigate the LST over the Amazon and Congo rainforests. The SSM/I and SSMIS data were collected from 1996 to 2012. The morning and afternoon observations from passive microwave remote sensing facilitate the investigation of the interannual changes of LST anomalies on a diurnal basis. As a result of the variability ofmore » cloud cover and the corresponding reduction of solar radiation, the afternoon LST anomalies tend to vary more than the morning LST anomalies. The dominant spatial and temporal patterns for interseasonal variations of the LST anomalies over the tropical rainforest were analyzed. The impacts of droughts and El Niños on this LST were also investigated. Lastly, the differences between early morning and late afternoon LST anomalies were identified by the remote sensing product, with the morning LST anomalies controlled by humidity (according to comparisons with the National Centers for Environmental Prediction (NCEP) reanalysis data).« less

Optical properties of volcanic ash: improving remote sensing observations.

NASA Astrophysics Data System (ADS)

Whelley, Patrick; Colarco, Peter; Aquila, Valentina; Krotkov, Nickolay; Bleacher, Jake; Garry, Brent; Young, Kelsey; Rocha Lima, Adriana; Martins, Vanderlei; Carn, Simon

2016-04-01

Many times each year explosive volcanic eruptions loft ash into the atmosphere. Global travel and trade rely on aircraft vulnerable to encounters with airborne ash. Volcanic ash advisory centers (VAACs) rely on dispersion forecasts and satellite data to issue timely warnings. To improve ash forecasts model developers and satellite data providers need realistic information about volcanic ash microphysical and optical properties. In anticipation of future large eruptions we can study smaller events to improve our remote sensing and modeling skills so when the next Pinatubo 1991 or larger eruption occurs, ash can confidently be tracked in a quantitative way. At distances >100km from their sources, drifting ash plumes, often above meteorological clouds, are not easily detected from conventional remote sensing platforms, save deriving their quantitative characteristics, such as mass density. Quantitative interpretation of these observations depends on a priori knowledge of the spectral optical properties of the ash in UV (>0.3μm) and TIR wavelengths (>10μm). Incorrect assumptions about the optical properties result in large errors in inferred column mass loading and size distribution, which misguide operational ash forecasts. Similarly, simulating ash properties in global climate models also requires some knowledge of optical properties to improve aerosol speciation.

A Technique for Remote Sensing of Suspended Sediments and Shallow Coastal Waters Using MODIS Visible and Near-IR Channels

NASA Technical Reports Server (NTRS)

Li, Rong-Rong; Kaufman, Yoram J.

2002-01-01

We have developed an algorithm to detect suspended sediments and shallow coastal waters using imaging data acquired with the Moderate Resolution Imaging SpectroRadiometer (MODIS). The MODIS instruments on board the NASA Terra and Aqua Spacecrafts are equipped with one set of narrow channels located in a wide 0.4 - 2.5 micron spectral range. These channels were designed primarily for remote sensing of the land surface and atmosphere. We have found that the set of land and cloud channels are also quite useful for remote sensing of the bright coastal waters. We have developed an empirical algorithm, which uses the narrow MODIS channels in this wide spectral range, for identifying areas with suspended sediments in turbid waters and shallow waters with bottom reflections. In our algorithm, we take advantage of the strong water absorption at wavelengths longer than 1 micron that does not allow illumination of sediments in the water or a shallow ocean floor. MODIS data acquired over the east coast of China, west coast of Africa, Arabian Sea, Mississippi Delta, and west coast of Florida are used in this study.

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

Gao, Huilin; Zhang, Shuai; Fu, Rong

Land surface temperatures (LSTs) within tropical forests contribute to climate variations. However, observational data are very limited in such regions. This study used passive microwave remote sensing data from the Special Sensor Microwave/Imager (SSM/I) and the Special Sensor Microwave Imager Sounder (SSMIS), providing observations under all weather conditions, to investigate the LST over the Amazon and Congo rainforests. The SSM/I and SSMIS data were collected from 1996 to 2012. The morning and afternoon observations from passive microwave remote sensing facilitate the investigation of the interannual changes of LST anomalies on a diurnal basis. As a result of the variability ofmore » cloud cover and the corresponding reduction of solar radiation, the afternoon LST anomalies tend to vary more than the morning LST anomalies. The dominant spatial and temporal patterns for interseasonal variations of the LST anomalies over the tropical rainforest were analyzed. The impacts of droughts and El Niños on this LST were also investigated. Lastly, the differences between early morning and late afternoon LST anomalies were identified by the remote sensing product, with the morning LST anomalies controlled by humidity (according to comparisons with the National Centers for Environmental Prediction (NCEP) reanalysis data).« less

Providing Data Quality Information for Remote Sensing Applications

NASA Astrophysics Data System (ADS)

Albrecht, F.; Blaschke, T.; Lang, S.; Abdulmutalib, H. M.; Szabó, G.; Barsi, Á.; Batini, C.; Bartsch, A.; Kugler, Zs.; Tiede, D.; Huang, G.

2018-04-01

The availability and accessibility of remote sensing (RS) data, cloud processing platforms and provided information products and services has increased the size and diversity of the RS user community. This development also generates a need for validation approaches to assess data quality. Validation approaches employ quality criteria in their assessment. Data Quality (DQ) dimensions as the basis for quality criteria have been deeply investigated in the database area and in the remote sensing domain. Several standards exist within the RS domain but a general classification - established for databases - has been adapted only recently. For an easier identification of research opportunities, a better understanding is required how quality criteria are employed in the RS lifecycle. Therefore, this research investigates how quality criteria support decisions that guide the RS lifecycle and how they relate to the measured DQ dimensions. Subsequently follows an overview of the relevant standards in the RS domain that is matched to the RS lifecycle. Conclusively, the required research needs are identified that would enable a complete understanding of the interrelationships between the RS lifecycle, the data sources and the DQ dimensions, an understanding that would be very valuable for designing validation approaches in RS.

A Technique For Remote Sensing Of Suspended Sediments And Shallow Coastal Waters Using MODIS Visible and Near-IR Channels

NASA Astrophysics Data System (ADS)

Li, R.; Kaufman, Y.

2002-12-01

ABSTRACT We have developed an algorithm to detect suspended sediments and shallow coastal waters using imaging data acquired with the Moderate Resolution Imaging SpectroRadiometer (MODIS). The MODIS instruments on board the NASA Terra and Aqua Spacecrafts are equipped with one set of narrow channels located in a wide 0.4 - 2.5 micron spectral range. These channels were designed primarily for remote sensing of the land surface and atmosphere. We have found that the set of land and cloud channels are also quite useful for remote sensing of the bright coastal waters. We have developed an empirical algorithm, which uses the narrow MODIS channels in this wide spectral range, for identifying areas with suspended sediments in turbid waters and shallow waters with bottom reflections. In our algorithm, we take advantage of the strong water absorption at wavelengths longer than 1 æm that does not allow illumination of sediments in the water or a shallow ocean floor. MODIS data acquired over the east coast of China, west coast of Africa, Arabian Sea, Mississippi Delta, and west coast of Florida are used in this study.

Radiative consequences of low-temperature infrared refractive indices for supercooled water clouds

NASA Astrophysics Data System (ADS)

Rowe, P. M.; Neshyba, S.; Walden, V. P.

2013-07-01

Simulations of cloud radiative properties for climate modeling and remote sensing rely on accurate knowledge of the complex refractive index (CRI) of water. Although conventional algorithms employ a temperature independent assumption (TIA), recent infrared measurements of supercooled water have demonstrated that the CRI becomes increasingly ice-like at lower temperatures. Here, we assess biases that result from ignoring this temperature dependence. We show that TIA-based cloud retrievals introduce spurious ice into pure, supercooled clouds, or underestimate cloud thickness and droplet size. TIA-based downwelling radiative fluxes are lower than those for the temperature-dependent CRI by as much as 1.7 W m-2 (in cold regions), while top-of-atmosphere fluxes are higher by as much as 3.4 W m-2 (in warm regions). Proper accounting of the temperature dependence of the CRI, therefore, leads to significantly greater local greenhouse warming due to supercooled clouds than previously predicted. The current experimental uncertainty in the CRI at low temperatures must be reduced to properly account for supercooled clouds in both climate models and cloud property retrievals.

Radiative consequences of low-temperature infrared refractive indices for supercooled water clouds

NASA Astrophysics Data System (ADS)

Rowe, P. M.; Neshyba, S.; Walden, V. P.

2013-12-01

Simulations of cloud radiative properties for climate modeling and remote sensing rely on accurate knowledge of the complex refractive index (CRI) of water. Although conventional algorithms employ a temperature-independent assumption (TIA), recent infrared measurements of supercooled water have demonstrated that the CRI becomes increasingly ice-like at lower temperatures. Here, we assess biases that result from ignoring this temperature dependence. We show that TIA-based cloud retrievals introduce spurious ice into pure, supercooled clouds, or underestimate cloud optical thickness and droplet size. TIA-based downwelling radiative fluxes are lower than those for the temperature-dependent CRI by as much as 1.7 W m-2 (in cold regions), while top-of-atmosphere fluxes are higher by as much as 3.4 W m-2 (in warm regions). Proper accounting of the temperature dependence of the CRI, therefore, leads to significantly greater local greenhouse warming due to supercooled clouds than previously predicted. The current experimental uncertainty in the CRI at low temperatures must be reduced to account for supercooled clouds properly in both climate models and cloud-property retrievals.

The Segmentation of Point Clouds with K-Means and ANN (artifical Neural Network)

NASA Astrophysics Data System (ADS)

Kuçak, R. A.; Özdemir, E.; Erol, S.

2017-05-01

Segmentation of point clouds is recently used in many Geomatics Engineering applications such as the building extraction in urban areas, Digital Terrain Model (DTM) generation and the road or urban furniture extraction. Segmentation is a process of dividing point clouds according to their special characteristic layers. The present paper discusses K-means and self-organizing map (SOM) which is a type of ANN (Artificial Neural Network) segmentation algorithm which treats the segmentation of point cloud. The point clouds which generate with photogrammetric method and Terrestrial Lidar System (TLS) were segmented according to surface normal, intensity and curvature. Thus, the results were evaluated. LIDAR (Light Detection and Ranging) and Photogrammetry are commonly used to obtain point clouds in many remote sensing and geodesy applications. By photogrammetric method or LIDAR method, it is possible to obtain point cloud from terrestrial or airborne systems. In this study, the measurements were made with a Leica C10 laser scanner in LIDAR method. In photogrammetric method, the point cloud was obtained from photographs taken from the ground with a 13 MP non-metric camera.

Aircraft-Induced Hole Punch and Canal Clouds

NASA Astrophysics Data System (ADS)

Heymsfield, A. J.; Kennedy, P.; Massie, S. T.; Schmitt, C. G.; Wang, Z.; Haimov, S.; Rangno, A.

2009-12-01

The production of holes and channels in altocumulus clouds by two commercial turboprop aircraft is documented for the first time. An unprecedented data set combining in situ measurements from microphysical probes with remote sensing measurements from cloud radar and lidar, all operating from the NSF/NCAR C130 aircraft, as well as ground-based NOAA and CSU radars, is used to describe the radar/lidar properties of a hole punch cloud and channel and the ensuing ice microphysical properties and structure of the ice column that subsequently developed. Ice particle production by commercial turboprop aircraft climbing through clouds much warmer than the regions where contrails are produced has the potential to modify significantly the cloud microphysical properties and effectively seed them under some conditions. Jet aircraft may also be producing hole punch clouds when flying through altocumulus with supercooled droplets at heights lower than their normal cruise altitudes where contrails can form. Commercial aircraft therefore can generate ice and affect the clouds at temperatures as much as 30°C warmer than the -40°C contrail formation threshold temperature.

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

Chitra Sivaraman, PNNL

Cloud droplet number concentration is an important factor in understanding aerosol-cloud interactions. As aerosol concentration increases, it is expected that droplet number concentration (Nd) will increase and droplet size will decrease, for a given liquid water path. This will greatly affect cloud albedo as smaller droplets reflect more shortwave radiation; however, the magnitude and variability of these processes under different environmental conditions is still uncertain.McComiskey et al. (2009) have implemented a method, based onBoers and Mitchell (1994), for calculating Nd from ground-based remote sensing measurements of optical depth and liquid water path. They show that the magnitude of the aerosol-cloudmore » interactions (ACI) varies with a range of factors, including the relative value of the cloud liquid water path (LWP), the aerosol size distribution, and the cloud updraft velocity. Estimates of Nd under a range of cloud types and conditions and at a variety of sites are needed to further quantify the impacts of aerosol cloud interactions. In order to provide data sets for studying aerosol-cloud interactions, the McComiskey et al. (2009) method was implemented as the Droplet Number Concentration (NDROP) value-added product (VAP).« less

Interfacing with in-Situ Data Networks during the Arctic Boreal Vulnerability Experiment (ABoVE)

NASA Astrophysics Data System (ADS)

McInerney, M.; Griffith, P. C.; Duffy, D.; Hoy, E.; Schnase, J. L.; Sinno, S.; Thompson, J. H.

2014-12-01

The Arctic Boreal Vulnerability Experiment (ABoVE) is designed to improve understanding of the causes and impacts of ecological changes in Arctic/boreal regions, and will integrate field-based studies, modeling, and data from airborne and satellite remote sensing. ABoVE will result in a fuller understanding of ecosystem vulnerability and resilience to environmental change in the Arctic and boreal regions of western North America, and provide scientific information required to develop options for societal responses to the impacts of these changes. The studies sponsored by NASA during ABoVE will be coordinated with research and in-situ monitoring activities being sponsored by a number of national and international partners. The NASA Center for Climate Simulation at the Goddard Space Flight Center has partnered with the NASA Carbon Cycle & Ecosystems Office to create a science cloud designed for this field campaign - the ABoVE Science Cloud (ASC). The ASC combines high performance computing with emerging technologies to create an environment specifically designed for large-scale modeling, analysis of remote sensing data, copious disk storage with integrated data management, and integration of core variables from in-situ networks identified by the ABoVE Science Definition Team. In this talk, we will present the scientific requirements driving the development of the ABoVE Science Cloud, discuss the necessary interfaces, both computational and human, with in-situ monitoring networks, and show examples of how the ASC is being used to meet the needs of the ABoVE campaign.

Results from the Two-Year Infrared Cloud Imager Deployment at ARM's NSA Observatory in Barrow, Alaska

NASA Astrophysics Data System (ADS)

Shaw, J. A.; Nugent, P. W.

2016-12-01

Ground-based longwave-infrared (LWIR) cloud imaging can provide continuous cloud measurements in the Arctic. This is of particular importance during the Arctic winter when visible wavelength cloud imaging systems cannot operate. This method uses a thermal infrared camera to observe clouds and produce measurements of cloud amount and cloud optical depth. The Montana State University Optical Remote Sensor Laboratory deployed an infrared cloud imager (ICI) at the Atmospheric Radiation Monitoring North Slope of Alaska site at Barrow, AK from July 2012 through July 2014. This study was used to both understand the long-term operation of an ICI in the Arctic and to study the consistency of the ICI data products in relation to co-located active and passive sensors. The ICI was found to have a high correlation (> 0.92) with collocated cloud instruments and to produce an unbiased data product. However, the ICI also detects thin clouds that are not detected by most operational cloud sensors. Comparisons with high-sensitivity actively sensed cloud products confirm the existence of these thin clouds. Infrared cloud imaging systems can serve a critical role in developing our understanding of cloud cover in the Arctic by provided a continuous annual measurement of clouds at sites of interest.

Spatial and Temporal Distribution of Tropospheric Clouds Observed by MODIS Onboard the Terra and Aqua Satellites

NASA Technical Reports Server (NTRS)

King, Michael D.

2005-01-01

The Moderate Resolution Imaging Spectroradiometer (MODIS) was developed by NASA and launched onboard the Terra spacecraft on December 18, 1999 and Aqua spacecraft on May 4, 2002. It achieved its final orbit and began Earth observations on February 24, 2000 for Terra and June 24, 2002 for Aqua. A comprehensive set of remote sensing algorithms for cloud masking and the retrieval of cloud physical and optical properties has been developed by members of the MODIS atmosphere science team. The archived products from these algorithms have applications in climate change studies, climate modeling, numerical weather prediction, as well as fundamental atmospheric research. 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. We will describe the various cloud properties being analyzed on a global basis from both Terra and Aqua. These include the latitudinal distribution of cloud optical and radiative properties of both liquid water and ice clouds, as well as joint histograms of cloud optical thickness and effective radius for selected geographical locations around the world.

Spatial and Temporal Distribution of Tropospheric Clouds Observed by MODIS Onboard the Terra and Aqua Satellites

NASA Technical Reports Server (NTRS)

King, Michael D.; Platnick, Steven

2005-01-01

The Moderate Resolution Imaging Spectroradiometer (MODIS) was developed by NASA and launched onboard the Terra spacecraft on December 18,1999 and Aqua spacecraft on May 4, 2002. It achieved its final orbit and began Earth observations on February 24, 2000 for Terra and June 24, 2002 for Aqua. A comprehensive set of remote sensing algorithms for cloud masking and the retrieval of cloud physical and optical properties has been developed by members of the MODIS atmosphere science team. The archived products from these algorithms have applications in climate change studies, climate modeling, numerical weather prediction, as well as fundamental atmospheric research. 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. We will describe the various cloud properties being analyzed on a global basis from both Terra and Aqua. These include the latitudinal distribution of cloud optical and radiative properties of both liquid water and ice clouds, as well as joint histograms of cloud optical thickness and effective radius for selected geographical locations around the world.

Joint retrievals of cloud and drizzle in marine boundary layer clouds using ground-based radar, lidar and zenith radiances

DOE PAGES

Fielding, M. D.; Chiu, J. C.; Hogan, R. J.; ...

2015-02-16

Active remote sensing of marine boundary-layer clouds is challenging as drizzle drops often dominate the observed radar reflectivity. We present a new method to simultaneously retrieve cloud and drizzle vertical profiles in drizzling boundary-layer cloud using surface-based observations of radar reflectivity, lidar attenuated backscatter, and zenith radiances. Specifically, the vertical structure of droplet size and water content of both cloud and drizzle is characterised throughout the cloud. An ensemble optimal estimation approach provides full error statistics given the uncertainty in the observations. To evaluate the new method, we first perform retrievals using synthetic measurements from large-eddy simulation snapshots of cumulusmore » under stratocumulus, where cloud water path is retrieved with an error of 31 g m −2. The method also performs well in non-drizzling clouds where no assumption of the cloud profile is required. We then apply the method to observations of marine stratocumulus obtained during the Atmospheric Radiation Measurement MAGIC deployment in the northeast Pacific. Here, retrieved cloud water path agrees well with independent 3-channel microwave radiometer retrievals, with a root mean square difference of 10–20 g m −2.« less

Characterization of the cloud conditions at Ny-Ålesund using sensor synergy and representativeness of the observed clouds across Arctic sites

NASA Astrophysics Data System (ADS)

Nomokonova, Tatiana; Ebell, Kerstin; Löhnert, Ulrich; Maturilli, Marion

2017-04-01

Clouds are one of the crucial components of the hydrological and energy cycles and thus affecting the global climate. Their special importance in Arctic regions is defined by cloud's influence on the radiation budget. Arctic clouds usually occur at low altitudes and often contain highly concentrated tiny liquid drops. During winter, spring, and autumn periods such clouds tend to conserve the long-wave radiation in the atmosphere and, thus, produce warming of the Arctic climate. In summer though clouds efficiently scatter the solar radiation back to space and, therefore, induce a cooling effect. An accurate characterization of the net effect of clouds on the Arctic climate requires long-term and precise observations. However, only a few measurement sites exist which perform continuous, vertically resolved observations of clouds in the Arctic, e.g. in Alaska, Canada, and Greenland. These sites typically make use of a combination of different ground-based remote sensing instruments, e.g. cloud radar, ceilometer and microwave radiometer in order to characterize clouds. Within the Transregional Collaborative Research Center (TR 172) "Arctic Amplification: Climate Relevant Atmospheric and Surface Processes, and Feedback Mechanisms (AC)3" comprehensive observations of the atmospheric column are performed at the German-French Research Station AWIPEV at Ny-Ålesund, Svalbard. Ny-Ålesund is located in the warmest part of the Arctic where climate is significantly influenced by adiabatic heating from the warm ocean. Thus, measurements at Ny-Ålesund will complement our understanding of cloud formation and development in the Arctic. This particular study is devoted to the characterization of the cloud macro- and microphysical properties at Ny-Ålesund and of the atmospheric conditions, under which these clouds form and develop. To this end, the information of the various instrumentation at the AWIPEV observatory is synergistically analysed: information about the thermodynamic structure of the atmosphere is obtained from long-term radiosonde launches. In addition, continuous vertical profiles of temperature and humidity are provided by the microwave radiometer HATPRO. A set of active remote sensing instruments performs cloud observations at Ny-Ålesund: a ceilometer and a Doppler lidar operating since 2011 and 2013, respectively, are now complemented with a novel 94 GHz FMCW cloud radar. As a first step, the CLOUDNET algorithms, including a target categorization and classification, are applied to the observations. In this study, we will present a first analysis of cloud properties at Ny-Ålesund including for example cloud occurrence, cloud geometry (cloud base, cloud top, and thickness) and cloud type (liquid, ice, mixed-phase). The different types of clouds are set into context to the environmental conditions such as temperature, amount of water vapour, and liquid water. We also expect that the cloud properties strongly depend on the wind direction. The first results of this analysis will be also shown.

(?) The Air Force Geophysics Laboratory: Aeronomy, aerospace instrumentation, space physics, meteorology, terrestrial sciences and optical physics

NASA Astrophysics Data System (ADS)

McGinty, A. B.

1982-04-01

Contents: The Air Force Geophysics Laboratory; Aeronomy Division--Upper Atmosphere Composition, Middle Atmosphere Effects, Atmospheric UV Radiation, Satellite Accelerometer Density Measurement, Theoretical Density Studies, Chemical Transport Models, Turbulence and Forcing Functions, Atmospheric Ion Chemistry, Energy Budget Campaign, Kwajalein Reference Atmospheres, 1979, Satellite Studies of the Neutral Atmosphere, Satellite Studies of the Ionosphere, Aerospace Instrumentation Division--Sounding Rocket Program, Satellite Support, Rocket and Satellite Instrumentation; Space Physics Division--Solar Research, Solar Radio Research, Environmental Effects on Space Systems, Solar Proton Event Studies, Defense Meteorological Satellite Program, Ionospheric Effects Research, Spacecraft Charging Technology; Meteorology Division--Cloud Physics, Ground-Based Remote-Sensing Techniques, Mesoscale Observing and Forecasting, Design Climatology, Aircraft Icing Program, Atmospheric Dynamics; Terrestrial Sciences Division--Geodesy and Gravity, Geokinetics; Optical Physics Division--Atmospheric Transmission, Remote Sensing, INfrared Background; and Appendices.

Satellite estimation of incident photosynthetically active radiation using ultraviolet reflectance

NASA Technical Reports Server (NTRS)

Eck, Thomas F.; Dye, Dennis G.

1991-01-01

A new satellite remote sensing method for estimating the amount of photosynthetically active radiation (PAR, 400-700 nm) incident at the earth's surface is described and tested. Potential incident PAR for clear sky conditions is computed from an existing spectral model. A major advantage of the UV approach over existing visible band approaches to estimating insolation is the improved ability to discriminate clouds from high-albedo background surfaces. UV spectral reflectance data from the Total Ozone Mapping Spectrometer (TOMS) were used to test the approach for three climatically distinct, midlatitude locations. Estimates of monthly total incident PAR from the satellite technique differed from values computed from ground-based pyranometer measurements by less than 6 percent. This UV remote sensing method can be applied to estimate PAR insolation over ocean and land surfaces which are free of ice and snow.

Recovering of images degraded by atmosphere

NASA Astrophysics Data System (ADS)

Lin, Guang; Feng, Huajun; Xu, Zhihai; Li, Qi; Chen, Yueting

2017-08-01

Remote sensing images are seriously degraded by multiple scattering and bad weather. Through the analysis of the radiative transfer procedure in atmosphere, an image atmospheric degradation model considering the influence of atmospheric absorption multiple scattering and non-uniform distribution is proposed in this paper. Based on the proposed model, a novel recovering method is presented to eliminate atmospheric degradation. Mean-shift image segmentation and block-wise deconvolution are used to reduce time cost, retaining a good result. The recovering results indicate that the proposed method can significantly remove atmospheric degradation and effectively improve contrast compared with other removal methods. The results also illustrate that our method is suitable for various degraded remote sensing, including images with large field of view (FOV), images taken in side-glance situations, image degraded by atmospheric non-uniform distribution and images with various forms of clouds.

Remote Sensing of Precipitation from Airborne and Spaceborne Radar. Chapter 13

NASA Technical Reports Server (NTRS)

Munchak, S. Joseph

2017-01-01

Weather radar measurements from airborne or satellite platforms can be an effective remote sensing tool for examining the three-dimensional structures of clouds and precipitation. This chapter describes some fundamental properties of radar measurements and their dependence on the particle size distribution (PSD) and radar frequency. The inverse problem of solving for the vertical profile of PSD from a profile of measured reflectivity is stated as an optimal estimation problem for single- and multi-frequency measurements. Phenomena that can change the measured reflectivity Z(sub m) from its intrinsic value Z(sub e), namely attenuation, non-uniform beam filling, and multiple scattering, are described and mitigation of these effects in the context of the optimal estimation framework is discussed. Finally, some techniques involving the use of passive microwave measurements to further constrain the retrieval of the PSD are presented.

Yb:YAG Lasers for Space Based Remote Sensing

NASA Technical Reports Server (NTRS)

Ewing, J.J.; Fan, T. Y.

1998-01-01

Diode pumped solid state lasers will play a prominent role in future remote sensing missions because of their intrinsic high efficiency and low mass. Applications including altimetry, cloud and aerosol measurement, wind velocity measurement by both coherent and incoherent methods, and species measurements, with appropriate frequency converters, all will benefit from a diode pumped primary laser. To date the "gold standard" diode pumped Nd laser has been the laser of choice for most of these concepts. This paper discusses an alternate 1 micron laser, the YB:YAG laser, and its potential relevance for lidar applications. Conceptual design analysis and, to the extent possible at the time of the conference, preliminary experimental data on the performance of a bread board YB:YAG oscillator will be presented. The paper centers on application of YB:YAG for altimetry, but extension to other applications will be discussed.

Remote Sensing of Aerosol and their Radiative Forcing of Climate

NASA Technical Reports Server (NTRS)

Kaufman, Yoram J.; Tanre, Didier; Remer, Lorraine A.

1999-01-01

Remote sensing of aerosol and aerosol radiative forcing of climate is going through a major transformation. The launch in next few years of new satellites designed specifically for remote sensing of aerosol is expected to further revolutionized aerosol measurements: until five years ago satellites were not designed for remote sensing of aerosol. Aerosol optical thickness was derived as a by product, only over the oceans using one AVHRR channel with errors of approx. 50%. However it already revealed a very important first global picture of the distribution and sources of aerosol. In the last 5 years we saw the introduction of polarization and multi-view observations (POLDER and ATSR) for satellite remote sensing of aerosol over land and ocean. Better products are derived from AVHRR using its two channels. The new TOMS aerosol index shows the location and transport of aerosol over land and ocean. Now we anticipate the launch of EOS-Terra with MODIS, MISR and CERES on board for multi-view, multi-spectral remote sensing of aerosol and its radiative forcing. This will allow application of new techniques, e.g. using a wide spectral range (0.55-2.2 microns) to derive precise optical thickness, particle size and mass loading. Aerosol is transparent in the 2.2 microns channel, therefore this channel can be used to detect surface features that in turn are used to derive the aerosol optical thickness in the visible part of the spectrum. New techniques are developed to derive the aerosol single scattering albedo, a measure of absorption of sunlight, and techniques to derive directly the aerosol forcing at the top of the atmosphere. In the last 5 years a global network of sun/sky radiometers was formed, designed to communicate in real time the spectral optical thickness from 50-80 locations every day, every 15 minutes. The sky angular and spectral information is also measured and used to retrieve the aerosol size distribution, refractive index, single scattering albedo and the spectral flux reaching the surface. Effort to introduce remote sensing from lidars will literally additional dimension to aerosol remote sensing. The vertical dimension is a critical link between the global satellite observations and modeling of aerosol transport. Lidars are also critical to study aerosol impact on cloud microphysics and reflectance. Both lidar ground networks and satellite systems are in development. This new capability is expected to put remote sensing in the forefront of aerosol and climate studies. Together with field experiments, chemical analysis and chemical transport models we anticipate, in the next decade, to be able to resolve some of the outstanding questions regarding the role of aerosol in climate, in atmospheric chemistry and its influence on human health and life on this planet.

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

Wang, Jingyu; Dong, Xiquan; Xi, Baike

In this study, six deep convective systems (DCSs) with a total of 5589 five-second samples and a range of temperatures from -41°C to 0°C during the Midlatitude Continental Convective Clouds Experiment (MC3E) were selected to investigate the ice cloud microphysical properties of DCSs over the Department of Energy Atmospheric Radiation Measurement (ARM) Southern Great Plains (SGP) site. The ice cloud measurements of the DCS cases were made by the University of North Dakota Citation II research aircraft, and the ice cloud properties were derived through the following processes. First, the instances of supercooled liquid water in the ice-dominated cloud layersmore » of DCSs have been eliminated using multisensor detection, including the Rosemount Icing Detector, King and Cloud Droplet Probes, as well as 2DC and Cloud Imaging Probe images. Then the Nevzorov-measured ice water contents (IWCs) at maximum diameter D max < 4000 µm are used as the best estimation to determine a new mass-dimensional relationship. Finally, the newly derived mass-dimensional relationship (a = 0.00365, b = 2.1) has been applied to a full spectrum of particle size distributions (PSDs, 120–30,000 µm) constructed from both 2DC and High-Volume Precipitation Spectrometer measurements to calculate the best-estimated IWCs of DCSs during MC3E. The averages of the total number concentrations (N t), median mass diameter (D m), maximum diameter (D max), and IWC from six selected cases are 0.035 cm -3, 1666 µm, 8841 µm, and 0.45 g m -3, respectively. The gamma-type-size distributions are then generated matching the observed PSDs (120–30,000 µm), and the fitted gamma parameters are compared with the observed PSDs through multimoment assessments including first moment (D m), third moment (IWC), and sixth moment (equivalent radar reflectivity, Z e). Lastly, for application of observed PSDs to the remote sensing community, a series of empirical relationships between fitted parameters and Z e values has been derived, and the bullet rosette ice crystal backscattering relationship has been suggested for ground-based remote sensing.« less

Development of a pulsed 9.5 micron lidar for regional scale O3 measurement

NASA Technical Reports Server (NTRS)

Stewart, R. W.

1980-01-01

A pulsed infrared lidar system designed for application to the remote sensing of atmospheric trace gases from an airborne platform is described. The system is also capable of measuring the infrared backscatter characteristics of the ocean surface, terrain, cloud, and aerosol targets. The lidar employed is based on dual wavelength pulse energy measurements in the 9-11 micrometer wavelength region.

A lower limit on the top of Jupiter's haze layer

NASA Technical Reports Server (NTRS)

Cook, A. F., II; Duxbury, T. C.; Hunt, G. E.

1979-01-01

Remote sensing observations of the Jovian atmosphere at wavelengths ranging from UV to the IR are affected by the presence of haze layers above the visible clouds. These layers are difficult to detect as they generally contain submicron particles. In the present paper, a sequence of Voyager images of high-latitude haze, which extends through the Jovian stratosphere into the mesosphere is presented and discussed.

Stereosat: A proposed private sector/government joint venture in remote sensing from space

NASA Technical Reports Server (NTRS)

Anglin, R. L.

1980-01-01

Stereosat, a free flying Sun synchronous satellite whose purpose is to obtain worldwide cloud-free stereoscopic images of the Earth's land masses, is proposed as a joint private sector/government venture. A number of potential organization models are identified. The legal, economic, and institutional issues which could impact the continuum of potential joint private sector/government institutional structures are examined.

A13K-0336: Airborne Multi-Wavelength High Spectral Resolution Lidar for Process Studies and Assessment of Future Satellite Remote Sensing Concepts

NASA Technical Reports Server (NTRS)

Hostetler, Chris A.; Ferrare, Rich A.; Hair, Johnathan W.; Cook, Anthony L.; Harper, David B.; Mack, Terry L.; Hare, Richard J.; Cleckner, Craig S.; Rogers, Raymond R.; Muller, Detlef;

NASA's Future Active Remote Sensing Missing for Earth Science

NASA Technical Reports Server (NTRS)

Hartley, Jonathan B.

2000-01-01

Since the beginning of space remote sensing of the earth, there has been a natural progression widening the range of electromagnetic radiation used to sense the earth, and slowly, steadily increasing the spatial, spectral, and radiometric resolution of the measurements. There has also been a somewhat slower trend toward active measurements across the electromagnetic spectrum, motivated in part by increased resolution, but also by the ability to make new measurements. Active microwave instruments have been used to measure ocean topography, to study the land surface. and to study rainfall from space. Future NASA active microwave missions may add detail to the topographical studies, sense soil moisture, and better characterize the cryosphere. Only recently have active optical instruments been flown in space by NASA; however, there are currently several missions in development which will sense the earth with lasers and many more conceptual active optical missions which address the priorities of NASA's earth science program. Missions are under development to investigate the structure of the terrestrial vegetation canopy, to characterize the earth's ice caps, and to study clouds and aerosols. Future NASA missions may measure tropospheric vector winds and make vastly improved measurements of the chemical components of the earth's atmosphere.

Satellite Remote Sensing of Tropical Precipitation and Ice Clouds for GCM Verification

NASA Technical Reports Server (NTRS)

Evans, K. Franklin

2001-01-01

This project, supported by the NASA New Investigator Program, has primarily been funding a graduate student, Darren McKague. Since August 1999 Darren has been working part time at Raytheon, while continuing his PhD research. Darren is planning to finish his thesis work in May 2001, thus some of the work described here is ongoing. The proposed research was to use GOES visible and infrared imager data and SSM/I microwave data to obtain joint distributions of cirrus cloud ice mass and precipitation for a study region in the Eastern Tropical Pacific. These joint distributions of cirrus cloud and rainfall were to be compared to those from the CSU general circulation model to evaluate the cloud microphysical amd cumulus parameterizations in the GCM. Existing algorithms were to be used for the retrieval of cloud ice water path from GOES (Minnis) and rainfall from SSM/I (Wilheit). A theoretical study using radiative transfer models and realistic variations in cloud and precipitation profiles was to be used to estimate the retrieval errors. Due to the unavailability of the GOES satellite cloud retrieval algorithm from Dr. Minnis (a co-PI), there was a change in the approach and emphasis of the project. The new approach was to develop a completely new type of remote sensing algorithm - one to directly retrieve joint probability density functions (pdf's) of cloud properties from multi-dimensional histograms of satellite radiances. The usual approach is to retrieve individual pixels of variables (i.e. cloud optical depth), and then aggregate the information. Only statistical information is actually needed, however, and so a more direct method is desirable. We developed forward radiative transfer models for the SSM/I and GOES channels, originally for testing the retrieval algorithms. The visible and near infrared ice scattering information is obtained from geometric ray tracing of fractal ice crystals (Andreas Macke), while the mid-infrared and microwave scattering is computed with Mie scattering. The radiative transfer is performed with the Spherical Harmonic Discrete Ordinate Method (developed by the PI), and infrared molecular absorption is included with the correlated k-distribution method. The SHDOM radiances have been validated by comparison to version 2 of DISORT (the community "standard" discrete-ordinates radiative transfer model), however we use SHDOM since it is computationally more efficient.

[Application of single-band brightness variance ratio to the interference dissociation of cloud for satellite data].

PubMed

Qu, Wei-ping; Liu, Wen-qing; Liu, Jian-guo; Lu, Yi-huai; Zhu, Jun; Qin, Min; Liu, Cheng

2006-11-01

In satellite remote-sensing detection, cloud as an interference plays a negative role in data retrieval. How to discern the cloud fields with high fidelity thus comes as a need to the following research. A new method rooting in atmospheric radiation characteristics of cloud layer, in the present paper, presents a sort of solution where single-band brightness variance ratio is used to detect the relative intensity of cloud clutter so as to delineate cloud field rapidly and exactly, and the formulae of brightness variance ratio of satellite image, image reflectance variance ratio, and brightness temperature variance ratio of thermal infrared image are also given to enable cloud elimination to produce data free from cloud interference. According to the variance of the penetrating capability for different spectra bands, an objective evaluation is done on cloud penetration of them with the factors that influence penetration effect. Finally, a multi-band data fusion task is completed using the image data of infrared penetration from cirrus nothus. Image data reconstruction is of good quality and exactitude to show the real data of visible band covered by cloud fields. Statistics indicates the consistency of waveband relativity with image data after the data fusion.

Support for the Harvard University Water Vapor and Total Water Instruments for the 2004 NASA WB57 Middle Latitude Cirrus Experiment

NASA Technical Reports Server (NTRS)

Anderson, James G.

2005-01-01

In order to improve our understanding of the role clouds play in the climate system, NASA is investing considerable effort in characterizing clouds with instruments ranging from passive remote sensors on board the EOS platforms, to the forthcoming active remote sensors on Cloudsat and Calipso. These missions, when taken together, have the capacity to advance our understanding of the coupling between various components of the hydrologic cycle and the atmospheric circulation, and hold the additional potential of leading to significant improvements in the characterization of cloud feedbacks in global models. This is especially true considering that several of these platforms will be flown in an identical orbit within several minutes of one another-a constellation of satellites known as the A-Train. The algorithms that are being implemented and developed to convert these new data streams from radiance and reflectivity measurements into geophysical parameters invariably rely on some set of simplifymg assumptions and empirical constants. Uncertainties in these relationships lead to poorly understood random and systematic errors in the retrieved properties. This lack of understanding introduces ambiguity in interpreting the data and in using the global data sets for their intended purposes. In light of this, a series of flights with the W57F was proposed to address certain specific issues related to the basic properties of mid latitude cirrus clouds: the NASA WE357 Middle Latitude Cirrus Experiment ("MidCiX"). The science questions addressed are: 1) Can cloud property retrieval algorithms developed for A-Train active and passive remote sensing measurements accurately characterize the microphysical properties of synoptic and convectively generated cirrus cloud systems? 2) What are the relationships between the cirrus particle mass, projected area, and particle size spectrum in various genre of cirrus clouds? 3) Does the present compliment of state of the art in situ cloud probes provide the level of precision and accuracy needed to develop and validate algorithms and to contribute to our understanding of the characteristics and microphysical processes operating in cirrus clouds?

Classification of Clouds in Satellite Imagery Using Adaptive Fuzzy Sparse Representation

PubMed Central

Jin, Wei; Gong, Fei; Zeng, Xingbin; Fu, Randi

2016-01-01

Automatic cloud detection and classification using satellite cloud imagery have various meteorological applications such as weather forecasting and climate monitoring. Cloud pattern analysis is one of the research hotspots recently. Since satellites sense the clouds remotely from space, and different cloud types often overlap and convert into each other, there must be some fuzziness and uncertainty in satellite cloud imagery. Satellite observation is susceptible to noises, while traditional cloud classification methods are sensitive to noises and outliers; it is hard for traditional cloud classification methods to achieve reliable results. To deal with these problems, a satellite cloud classification method using adaptive fuzzy sparse representation-based classification (AFSRC) is proposed. Firstly, by defining adaptive parameters related to attenuation rate and critical membership, an improved fuzzy membership is introduced to accommodate the fuzziness and uncertainty of satellite cloud imagery; secondly, by effective combination of the improved fuzzy membership function and sparse representation-based classification (SRC), atoms in training dictionary are optimized; finally, an adaptive fuzzy sparse representation classifier for cloud classification is proposed. Experiment results on FY-2G satellite cloud image show that, the proposed method not only improves the accuracy of cloud classification, but also has strong stability and adaptability with high computational efficiency. PMID:27999261

Remote sensing solutions for estimating runoff and recharge in arid environments.

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

Milewski, A.; Sultan, M.; Yan, E.

2009-06-30

Efforts to understand and to quantify precipitation and its partitioning into runoff evapo-transpiration, and recharge are often hampered by the absence or paucity of appropriate monitoring systems. We applied methodologies for rainfall-runoff and groundwater recharge computations that heavily rely on observations extracted from a wide-range of global remote sensing data sets (TRMM, SSM/I, Landsat TM, AVHRR, AMSR-E, and ASTER) using the arid Sinai Peninsula (SP; area: 61,000 km{sup 2}) and the Eastern Desert (ED; area: 220,000 km{sup 2}) of Egypt as our test sites. A two-fold exercise was conducted. Spatiotemporal remote sensing data (TRMM, AVHRR and AMSR-E) were extracted frommore » global data sets over the test sites using RESDEM, the Remote Sensing Data Extraction Model, and were then used to identify and to verify precipitation events throughout the past 10 years (1998-2007). This was accomplished by using an automated cloud detection technique to identify clouds and to monitor their propagation prior to and throughout the identified precipitation events, and by examining changes in soil moisture (extracted from AMSR-E data) following the identification of clouds. For the investigated period, 246 of 327 events were verified in the SP, and 179 of 304 in the ED. A catchment-based, continuous, semi-distributed hydrologic model (Soil Water and Assessment Tool model; SWAT) was calibrated against observed runoff values from Wadi Girafi Watershed (area: 3350 km{sup 2}) and then used to provide a continuous simulation (1998-2007) of the overland flow, channel flow, transmission losses, evaporation on bare soils and evapo-transpiration, and groundwater recharge for the major (area: 2014-22,030 km{sup 2}) watersheds in the SP (Watir, El-Arish, Dahab, and Awag) and the ED (Qena, Hammamat, Asyuti, Tarfa, El-Quffa, El-Batur, Kharit, Hodein, and Allaqi) covering 48% and 51% of the total areas of the SP and the ED, respectively. For the investigated watersheds in the SP, the average annual precipitation, average annual runoff, and average annual recharge through transmission losses were found to be: 2955 x 10{sup 6}m{sup 3}, 508 x 10{sup 6}m{sup 3} (17.1% total precipitation (TP)), and 463 x 10{sup 6}m{sup 3} (15.7% TP), respectively, whereas in the ED these values are: 807 x 10{sup 6}m{sup 3}, 77.8 x 10{sup 6}m{sup 3} (9.6% TP), and 171 x 10{sup 6}m{sup 3} (21.2% TP), respectively. Results demonstrate the enhanced opportunities for groundwater development in the SP (compared to the ED) and highlight the potential for similar applications in arid areas elsewhere. The adopted remote sensing-based, regionalization approach is not a substitute for traditional methodologies that rely on extensive field datasets from rain gauge and stream flow networks, yet could provide first-order estimates for rainfall, runoff, and recharge over large sectors of the arid world lacking adequate coverage with spatial and temporal precipitation and field data.« less

Satellite Derived Volcanic Ash Product Inter-Comparison in Support to SCOPE-Nowcasting

NASA Astrophysics Data System (ADS)

Siddans, Richard; Thomas, Gareth; Pavolonis, Mike; Bojinski, Stephan

2016-04-01

In support of aeronautical meteorological services, WMO organized a satellite-based volcanic ash retrieval algorithm inter-comparison activity, to improve the consistency of quantitative volcanic ash products from satellites, under the Sustained, Coordinated Processing of Environmental Satellite Data for Nowcasting (SCOPEe Nowcasting) initiative (http:/ jwww.wmo.int/pagesjprogjsatjscopee nowcasting_en.php). The aims of the intercomparison were as follows: 1. Select cases (Sarychev Peak 2009, Eyjafyallajökull 2010, Grimsvötn 2011, Puyehue-Cordón Caulle 2011, Kirishimayama 2011, Kelut 2014), and quantify the differences between satellite-derived volcanic ash cloud properties derived from different techniques and sensors; 2. Establish a basic validation protocol for satellite-derived volcanic ash cloud properties; 3. Document the strengths and weaknesses of different remote sensing approaches as a function of satellite sensor; 4. Standardize the units and quality flags associated with volcanic cloud geophysical parameters; 5. Provide recommendations to Volcanic Ash Advisory Centers (VAACs) and other users on how to best to utilize quantitative satellite products in operations; 6. Create a "road map" for future volcanic ash related scientific developments and inter-comparison/validation activities that can also be applied to SO2 clouds and emergent volcanic clouds. Volcanic ash satellite remote sensing experts from operational and research organizations were encouraged to participate in the inter-comparison activity, to establish the plans for the inter-comparison and to submit data sets. RAL was contracted by EUMETSAT to perform a systematic inter-comparison of all submitted datasets and results were reported at the WMO International Volcanic Ash Inter-comparison Meeting to held on 29 June - 2 July 2015 in Madison, WI, USA (http:/ /cimss.ssec.wisc.edujmeetings/vol_ash14). 26 different data sets were submitted, from a range of passive imagers and spectrometers and these were inter-compared against each other and against validation data such as CALIPSO lidar, ground-based lidar and aircraft observations. Results of the comparison exercise will be presented together with the conclusions and recommendations arising from the activity.

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

NASA Astrophysics Data System (ADS)

Braun, Andreas; Hagensieker, Ron; Hochschild, Volker

2016-08-01

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

Remote sensing of cloud distributions over the Bayanhar Mountains - Watershed of the Yangtze and Yellow rivers

NASA Technical Reports Server (NTRS)

Hung, R. J.; Liu, J. M.; Dodge, J. C.; Smith, R. E.

1986-01-01

Although the two largest rivers in China originate in the same region separated only by the Bayanhar Mountains as a watershed, the Yangtze and Yellow rivers behave in quite different ways. Most of the warm and humid air currents from the Arabian sea and the Bay of Bengal are blocked by the Bayanhar Mountains. As a result the amount of water in the Yellow River is only 5 percent of that in the Yangtze river. Based on the cloud coverage area and the cloud volumetric distributions, and also the thickness above 9.4 km of the cumulus clouds located north and south of the Bayanhar Mountains from the geosynchronous satellite infrared imagery, the results suggest that a more detailed investigation is warranted in the hope that the proper modification of cumuli north of the Bayanhar Mountains would enhance the rainfall over the fountainhead of the Yellow River.

Outdoor Illegal Construction Identification Algorithm Based on 3D Point Cloud Segmentation

NASA Astrophysics Data System (ADS)

An, Lu; Guo, Baolong

2018-03-01

Recently, various illegal constructions occur significantly in our surroundings, which seriously restrict the orderly development of urban modernization. The 3D point cloud data technology is used to identify the illegal buildings, which could address the problem above effectively. This paper proposes an outdoor illegal construction identification algorithm based on 3D point cloud segmentation. Initially, in order to save memory space and reduce processing time, a lossless point cloud compression method based on minimum spanning tree is proposed. Then, a ground point removing method based on the multi-scale filtering is introduced to increase accuracy. Finally, building clusters on the ground can be obtained using a region growing method, as a result, the illegal construction can be marked. The effectiveness of the proposed algorithm is verified using a publicly data set collected from the International Society for Photogrammetry and Remote Sensing (ISPRS).

Satellite remote sensing of water resources in the Yangtze and Yellow Rivers of China based on infrared imagery of cloud distributions

NASA Technical Reports Server (NTRS)

Hung, R. J.; Dodge, James C.

1990-01-01

Although the two largest rivers in China originate in the same region, separated only by the Bayanhar Mountains as a watershed, the Yangtze and Yellow Rivers behave in quite different ways. Most of the warm and humid air currents from the Arabian Sea and Bay of Bengal are blocked by the Bayanhar Mountains. As a result, the amount of water in the Yellow River is only 5 percent of that in the Yangtze River. Based on the cloud coverage area and the cloud volumetric distributions, and also the thickness above 9.4 kms of the cumulus clouds located north and south of the Bayanhar Mountains, from GEO satellite IR imagery, the results suggest that a more detailed investigation is warranted in the hope that the proper modification of cumuli north of the Bayanhar Mountains would enhance the rainfall over the fountainhead of the Yellow River.

Passive and Active Detection of Clouds: Comparisons between MODIS and GLAS Observations

NASA Technical Reports Server (NTRS)

Mahesh, Ashwin; Gray, Mark A.; Palm, Stephen P.; Hart, William D.; Spinhirne, James D.

2003-01-01

The Geoscience Laser Altimeter System (GLAS), launched on board the Ice, Cloud and Land Elevation Satellite in January 2003 provides space-borne laser observations of atmospheric layers. GLAS provides opportunities to validate passive observations of the atmosphere for the first time from space with an active optical instrument. Data from the Moderate Resolution Imaging Spectrometer aboard the Aqua satellite is examined along with GLAS observations of cloud layers. In more than three-quarters of the cases, MODIS scene identification from spectral radiances agrees with GLAS. Disagreement between the two platforms is most significant over snow-covered surfaces in the northern hemisphere. Daytime clouds detected by GLAS are also more easily seen in the MODIS data as well, compared to observations made at night. These comparisons illustrate the capabilities of active remote sensing to validate and assess passive measurements, and also to complement them in studies of atmospheric layers.

Fine-scale Horizontal Structure of Arctic Mixed-Phase Clouds.

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

Rambukkange,M.; Verlinde, J.; Elorante, E.

2006-07-10

Recent in situ observations in stratiform clouds suggest that mixed phase regimes, here defined as limited cloud volumes containing both liquid and solid water, are constrained to narrow layers (order 100 m) separating all-liquid and fully glaciated volumes (Hallett and Viddaurre, 2005). The Department of Energy Atmospheric Radiation Measurement Program's (DOE-ARM, Ackerman and Stokes, 2003) North Slope of Alaska (NSA) ARM Climate Research Facility (ACRF) recently started collecting routine measurement of radar Doppler velocity power spectra from the Millimeter Cloud Radar (MMCR). Shupe et al. (2004) showed that Doppler spectra has potential to separate the contributions to the total reflectivitymore » of the liquid and solid water in the radar volume, and thus to investigate further Hallett and Viddaurre's findings. The Mixed-Phase Arctic Cloud Experiment (MPACE) was conducted along the NSA to investigate the properties of Arctic mixed phase clouds (Verlinde et al., 2006). We present surface based remote sensing data from MPACE to discuss the fine-scale structure of the mixed-phase clouds observed during this experiment.« less

Forest understory trees can be segmented accurately within sufficiently dense airborne laser scanning point clouds.

PubMed

Hamraz, Hamid; Contreras, Marco A; Zhang, Jun

2017-07-28

Airborne laser scanning (LiDAR) point clouds over large forested areas can be processed to segment individual trees and subsequently extract tree-level information. Existing segmentation procedures typically detect more than 90% of overstory trees, yet they barely detect 60% of understory trees because of the occlusion effect of higher canopy layers. Although understory trees provide limited financial value, they are an essential component of ecosystem functioning by offering habitat for numerous wildlife species and influencing stand development. Here we model the occlusion effect in terms of point density. We estimate the fractions of points representing different canopy layers (one overstory and multiple understory) and also pinpoint the required density for reasonable tree segmentation (where accuracy plateaus). We show that at a density of ~170 pt/m² understory trees can likely be segmented as accurately as overstory trees. Given the advancements of LiDAR sensor technology, point clouds will affordably reach this required density. Using modern computational approaches for big data, the denser point clouds can efficiently be processed to ultimately allow accurate remote quantification of forest resources. The methodology can also be adopted for other similar remote sensing or advanced imaging applications such as geological subsurface modelling or biomedical tissue analysis.

Atmospheric water parameters in mid-latitude cyclones observed by microwave radiometry and compared to model calculations

NASA Technical Reports Server (NTRS)

Katsaros, Kristina B.; Hammarstrand, Ulla; Petty, Grant W.

1990-01-01

Existing and experimental algorithms for various parameters of atmospheric water content such as integrated water vapor, cloud water, precipitation, are used to examine the distribution of these quantities in mid latitude cyclones. The data was obtained from signals given by the special sensor microwave/imager (SSM/I) and compared with data from the nimbus scanning multichannel microwave radiometer (SMMR) for North Atlantic cyclones. The potential of microwave remote sensing for enhancing knowledge of the horizontal structure of these storms and to aid the development and testing of the cloud and precipitation aspects of limited area numerical models of cyclonic storms is investigated.

Spatial and Temporal Distribution of Tropospheric Clouds and Aerosols Observed by MODIS Onboard the Terra and Aqua Satellites

NASA Technical Reports Server (NTRS)

King, Michael D.; Platnick, Steven; Remer, Lorraine A.; Kaufman, Yoram J.

2004-01-01

Remote sensing of cloud and aerosol optical properties is routinely obtained using the Moderate Resolution Imaging Spectroradiometer (MODIS) onboard the Terra and Aqua satellites. Techniques that are being used to enhance our ability to characterize the global distribution of cloud and aerosol properties include well-calibrated multispectral radiometers that rely on visible, near-infrared, and thermal infrared channels. The availability of thermal channels to aid in cloud screening for aerosol properties is an important additional piece of information that has not always been incorporated into sensor designs. In this paper, we describe the radiative properties of clouds as currently determined from satellites (cloud fraction, optical thickness, cloud top pressure, and cloud effective radius), and highlight the global and regional cloud microphysical properties currently available for assessing climate variability and forcing. These include the latitudinal distribution of cloud optical and radiative properties of both liquid water and ice clouds, as well as joint histograms of cloud optical thickness and effective radius for selected geographical locations around the world. In addition, we will illustrate the radiative and microphysical properties of aerosol particles that are currently available from space-based observations, and show selected cases in which aerosol particles are observed to modify the cloud optical properties.

STORMVEX: The Storm Peak Lab Cloud Property Validation Experiment Science and Operations Plan

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

Mace, J; Matrosov, S; Shupe, M

2010-09-29

During the Storm Peak Lab Cloud Property Validation Experiment (STORMVEX), a substantial correlative data set of remote sensing observations and direct in situ measurements from fixed and airborne platforms will be created in a winter season, mountainous environment. This will be accomplished by combining mountaintop observations at Storm Peak Laboratory and the airborne National Science Foundation-supported Colorado Airborne Multi-Phase Cloud Study campaign with collocated measurements from the second ARM Mobile Facility (AMF2). We describe in this document the operational plans and motivating science for this experiment, which includes deployment of AMF2 to Steamboat Springs, Colorado. The intensive STORMVEX field phasemore » will begin nominally on 1 November 2010 and extend to approximately early April 2011.« less

NOAA/APT Satellite Data for Online and Real Time Monitoring of Tungurahua Volcanic Eruption and Temperature Profile in Ecuador

NASA Astrophysics Data System (ADS)

Jaffer, G.; Nader, R.; Koudelka, O.

2010-12-01

The Ecuadorian Space Agency (EXA) has built HERMES, an online and real time ground station (GS) available to participating schools/universities for free access to NOAA and other remote sensing satellites. The GS is being used by students and scientists in Austria, USA, Japan and Ecuador to access NOAA satellites and spacecrafts online using only a computer and an internet connection with immediate access to satellite imaging and science data for their educational and research projects. The accuracy of analysed data can be used in research areas like forecasting, monitoring and damage assessment caused by eruptions. The HERMES internet-to-orbit gateway transforms a laptop into a full space-qualified GS on-the-move. The purpose of this paper is to present results of Andean mountain area in Ecuador being affected by high temperatures over 30 degree Celsius located over 3000 m high. From May 15 - 20, 2010, we received images from NOAA-18 and NOAA-19 using HERMS GS and applied Surface Temperature (ST), a remote sensing tool to process these images in real-time. Moreover, measured results have been validated by the records from the local meteorological stations network. Additionally, the visual observations revealed that due to high temperature, those glaciers were in fact receding and exposing terrain, never seen before. This paper also highlights the possible causes of this rapid thermal change. The second event dealt by this paper happened on May 28th; we captured a large ash cloud emanating from Tungurahua volcano eruption in the Andean region along with a large ash cloud from the Pacaya volcano in Guatemala using far infrared images from NOAA-18 satellite with overlaid geo-reference coordinates. Both events were analysed with remote sensing tools and image enhancement schemes like 'thermal', 'hvct' and 'fire', available in weather decoding software using free APT data. The aftermath correlation results of volcanic eruption with high temperature profile in the same region are presented in this paper. We got the image of the fleeting ash cloud due to unique location of HERMES GS which remarks the importance of having this kind of stations around the world and the scientists have remote access via HERMES GS. NOAA has already granted free access to the world, now users must move forward to build new or network existing worldwide ground stations to get composite, 3D and animated information of the meteorological and atmospheric conditions to keep an eye on the abrupt changes for proper mitigation. As comes out from the current studies, real time monitoring of natural disasters is a key to receive first hand remote sensing data that can play a decisive role in evaluating damages and to prepare for current and future disaster management along with its educational perspective.

Engaging observers to look at clouds from both sides: connecting NASA mission science with authentic STEM experiences

NASA Astrophysics Data System (ADS)

Chambers, L. H.; Taylor, J.; Ellis, T. D.; McCrea, S.; Rogerson, T. M.; Falcon, P.

2016-12-01

In 1997, NASA's Clouds and the Earth's Radiant Energy System (CERES) team began engaging K-12 schools as ground truth observers of clouds. CERES seeks to understand cloud effects on Earth's energy budget; thus accurate detection and characterization of clouds is key. While satellite remote sensing provides global information about clouds, it is limited in time and resolution. Ground observers, on the other hand, can observe clouds at any time of day (and sometimes night), and can see small and thin clouds that are challenging to detect from space. In 2006, two active sensing satellites, CloudSat and CALIPSO, were launched into the A-Train, which already contained 2 CERES instruments on the Aqua spacecraft. The CloudSat team also engaged K-12 schools to observe clouds, through The GLOBE Program, with a specialized observation protocol customized for the narrow radar swath. While providing valuable data for satellite assessment, these activities also engage participants in accessible, authentic science that gets people outdoors, helps them develop observation skills, and is friendly to all ages. The effort has evolved substantially since 1997, adopting new technology to provide a more compelling experience to citizen observers. Those who report within 15 minutes of the passage of a wide range of satellites (Terra, Aqua, CloudSat, CALIPSO, NPP, as well as a number of geostationary satellites) are sent a satellite image centered on their location and are invited to extend the experience beyond simple observation to include analysis of the two different viewpoints. Over the years these projects have collected large amounts of cloud observations from every continent and ocean basin on Earth. A number of studies have been conducted comparing the ground observations to the satellite results. This presentation will provide an overview of those results and also describe plans for a coordinated, thematic cloud observation and data analysis activity going forward.

A comparison between CloudSat and aircraft data for mixed-phase and cirrus clouds

NASA Astrophysics Data System (ADS)

Mioche, G.; Gayet, J.-F.; Minikin, A.; Herber, A.; Pelon, J.

2009-04-01

Nowadays, space remote sensing measurements are a very useful way to study the atmosphere on a global scale. Among the numerous scientific satellites in space, the A-Train is a constellation of 6 satellites flying together with on board complementary instruments of new generation (radiometers, radar, lidar, spectrometers…) to study all parts of the atmosphere: gas composition, clouds and aerosols distribution and properties, and radiation budget. Among these satellites, two of them where launched in 2006: CALIPSO and CloudSat, respectively with a Lidar (532 and 1064 nm channels with depolarization) and a 94 GHz radar on board. They are especially dedicated to the study of clouds and aerosols, and will allow to obtain for the first time the vertical profiles of clouds and aerosols on a global scale during 3 years. However, to determine clouds and aerosols properties from space raw data, retrieval methods need to be developed. In order to validate these retrieved techniques, and thus the clouds and aerosols properties, numerous validation plans take place around the world, included different ways as ground based measurements, in situ measurements, or airborne remote sensing instruments in collocation with the satellite tracks. In this context, the ASTAR-2007 and POLARCAT-2008 campaigns took place respectively in the Arctic region of Spitzbergen-Norway in April 2007 and in North part of Sweden in April 2008 to study mixed-phase clouds and the CIRCLE-2 campaign was carried out in Western Europe in May 2007 to sample mid-latitude cirrus clouds. The main objectives are the study of microphysical and optical properties of mixed-phase and ice clouds with particular interest on the validation of clouds products derived from CloudSat and CALIPSO data during co-located remote and in situ observations. The airborne microphysical instruments include the Polar Nephelometer probe to measure the scattering phase function and asymmetry parameter of cloud particles, the high resolution Cloud Particle Imager probe (CPI) for imaging the ice particle morphology (2.3 microns pixels size) and standard PMS probes: 2D-C, FSSP-100 and FSSP-300. This presentation focuses on the validation of the standard parameter of the Cloud Profiling Radar (CPR) of CloudSat (equivalent radar reflectivity factor Z). The different IWC(ice water content)-Z relationships determined from combined CloudSat and in situ data are then discussed. The method to derive equivalent reflectivity factor from the CPI data is first presented. According to the particle shape, a mass-diameter relationship and thus a reflectivity factor is determined for each type of ice crystal. This technique noticeably decreases the discrepancies of radar reflectivity-derived values due to the natural variability of ice crystal shapes. Comparisons of the reflectivity factor deduced from CPI and those from CloudSat for various types of clouds are then discussed. The next step to the interpretation of the CloudSat product is to derive IWC-Z relationships for assessing IWC distributions on a global scale, which is an important improvement to constrain global scale modelling. Several IWC-Z relationships are determined from in situ measurements according to the various case studies including Arctic mixed-phase clouds, Arctic and mid-latitude cirrus. The improvements on the results by using the CPI data-processing method are discussed. Acknowledgements: This work was funded by the Centre National d'Etudes Spatiales (CNES), the Agence Nationale de la Recherche (ANR BLAN06-1_137670), the Institut National des Sciences de l'Univers (INSU/CNRS), the Institut Polaire Français Paul Emile Victor (IPEV), the Alfred Wegener Institute (AWI) and the Deutsches Zentrum für Luft-und Raumfahrt (DLR). The CloudSat data are courtesy of the CloudSat Data Processing Center.

Ground-based remote sensing of thin clouds in the Arctic

NASA Astrophysics Data System (ADS)

Garrett, T. J.; Zhao, C.

2012-11-01

This paper describes a method for using interferometer measurements of downwelling thermal radiation to retrieve the properties of single-layer clouds. Cloud phase is determined from ratios of thermal emission in three "micro-windows" where absorption by water vapor is particularly small. Cloud microphysical and optical properties are retrieved from thermal emission in two micro-windows, constrained by the transmission through clouds of stratospheric ozone emission. Assuming a cloud does not approximate a blackbody, the estimated 95% confidence retrieval errors in effective radius, visible optical depth, number concentration, and water path are, respectively, 10%, 20%, 38% (55% for ice crystals), and 16%. Applied to data from the Atmospheric Radiation Measurement program (ARM) North Slope of Alaska - Adjacent Arctic Ocean (NSA-AAO) site near Barrow, Alaska, retrievals show general agreement with ground-based microwave radiometer measurements of liquid water path. Compared to other retrieval methods, advantages of this technique include its ability to characterize thin clouds year round, that water vapor is not a primary source of retrieval error, and that the retrievals of microphysical properties are only weakly sensitive to retrieved cloud phase. The primary limitation is the inapplicability to thicker clouds that radiate as blackbodies.

Estimation of the Cloud condensation nuclei concentration(CCN) and aerosol optical depth(AOD) relation in the Arctic region

NASA Astrophysics Data System (ADS)

Jung, C. H.; Yoon, Y. J.; Ahn, S. H.; Kang, H. J.; Gim, Y. T.; Lee, B. Y.

2017-12-01

Information of the spatial and temporal variations of cloud condensation nuclei (CCN) concentrations is important in estimating aerosol indirect effects. Generally, CCN aerosol is difficult to estimate using remote sensing methods. Although there are many CCN measurements data, extensive measurements of CCN are not feasible because of the complex nature of the operation and high cost, especially in the Arctic region. Thus, there have been many attempts to estimate CCN concentrations from more easily obtainable parameters such as aerosol optical depth (AOD) because AOD has the advantage of being readily observed by remote sensing from space by several sensors. For example, some form of correlation was derived between AOD and the number concentration of cloud condensation nuclei (CCN) through the comparison results from AERONET network and CCN measurements (Andreae 2009). In this study, a parameterization of CCN concentration as a function of AOD at 500 nm is given in the Arctic region. CCN data was collected during the period 2007-2013 at the Zeppelin observatory (78.91° N, 11.89° E, 474 masl). The AERONET network and MODIS AOD data are compared with ground measured CCN measurement and the relations between AOD and CCN are parameterized. The seasonal characteristics as well as long term trends are also considered. Through the measurement, CCN concentration remains high during spring because of aerosol transportation from the mid-latitudes, known as Arctic Haze. Lowest CCN number densities were observed during Arctic autumn and early winter when aerosol long-range transport into the Arctic is not effective and new particle formation ceases. The results show that the relation between AOD and CCN shows a different parameter depending on the seasonal aerosol and CCN characteristics. This seasonal different CCN-AOD relation can be interpreted as many physico-chemical aerosol properties including aerosol size distribution, composition. ReferenceAndreae, M. O. (2009) Correlation between cloud condensation nuclei concentration and aerosol optical thickness in remote and polluted regions,2009, Atmos. Chem. Phys., 9, 543-556.

Plasmonic Hotspots in Air: An Omnidirectional Three-Dimensional Platform for Stand-Off In-Air SERS Sensing of Airborne Species.

PubMed

Phan-Quang, Gia Chuong; Lee, Hiang Kwee; Teng, Hao Wen; Koh, Charlynn Sher Lin; Yim, Barnabas Qinwei; Tan, Eddie Khay Ming; Tok, Wee Lee; Phang, In Yee; Ling, Xing Yi

2018-05-14

Molecular-level airborne sensing is critical for early prevention of disasters, diseases, and terrorism. Currently, most 2D surface-enhanced Raman spectroscopy (SERS) substrates used for air sensing have only one functional surface and exhibit poor SERS-active depth. "Aerosolized plasmonic colloidosomes" (APCs) are introduced as airborne plasmonic hotspots for direct in-air SERS measurements. APCs function as a macroscale 3D and omnidirectional plasmonic cloud that receives laser irradiation and emits signals in all directions. Importantly, it brings about an effective plasmonic hotspot in a length scale of approximately 2.3 cm, which affords 100-fold higher tolerance to laser misalignment along the z-axis compared with 2D SERS substrates. APCs exhibit an extraordinary omnidirectional property and demonstrate consistent SERS performance that is independent of the laser and analyte introductory pathway. Furthermore, the first in-air SERS detection is demonstrated in stand-off conditions at a distance of 200 cm, highlighting the applicability of 3D omnidirectional plasmonic clouds for remote airborne sensing in threatening or inaccessible areas. © 2018 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim.

New Satellite Estimates of Mixed-Phase Cloud Properties: A Synergistic Approach for Application to Global Satellite Imager Data

NASA Astrophysics Data System (ADS)

Smith, W. L., Jr.; Spangenberg, D.; Fleeger, C.; Sun-Mack, S.; Chen, Y.; Minnis, P.

2016-12-01

Determining accurate cloud properties horizontally and vertically over a full range of time and space scales is currently next to impossible using data from either active or passive remote sensors or from modeling systems. Passive satellite imagers provide horizontal and temporal resolution of clouds, but little direct information on vertical structure. Active sensors provide vertical resolution but limited spatial and temporal coverage. Cloud models embedded in NWP can produce realistic clouds but often not at the right time or location. Thus, empirical techniques that integrate information from multiple observing and modeling systems are needed to more accurately characterize clouds and their impacts. Such a strategy is employed here in a new cloud water content profiling technique developed for application to satellite imager cloud retrievals based on VIS, IR and NIR radiances. Parameterizations are developed to relate imager retrievals of cloud top phase, optical depth, effective radius and temperature to ice and liquid water content profiles. The vertical structure information contained in the parameterizations is characterized climatologically from cloud model analyses, aircraft observations, ground-based remote sensing data, and from CloudSat and CALIPSO. Thus, realistic cloud-type dependent vertical structure information (including guidance on cloud phase partitioning) circumvents poor assumptions regarding vertical homogeneity that plague current passive satellite retrievals. This paper addresses mixed phase cloud conditions for clouds with glaciated tops including those associated with convection and mid-latitude storm systems. Novel outcomes of our approach include (1) simultaneous retrievals of ice and liquid water content and path, which are validated with active sensor, microwave and in-situ data, and yield improved global cloud climatologies, and (2) new estimates of super-cooled LWC, which are demonstrated in aviation safety applications and validated with icing PIREPS. The initial validation is encouraging for single-layer cloud conditions. More work is needed to test and refine the method for global application in a wider range of cloud conditions. A brief overview of our current method, applications, verification, and plans for future work will be presented.

Continuous Water Vapor Profiles from Operational Ground-Based Active and Passive Remote Sensors

NASA Technical Reports Server (NTRS)

Turner, D. D.; Feltz, W. F.; Ferrare, R. A.

2000-01-01

The Atmospheric Radiation Measurement program's Southern Great Plains Cloud and Radiation Testbed site central facility near Lamont, Oklahoma, offers unique operational water vapor profiling capabilities, including active and passive remote sensors as well as traditional in situ radiosonde measurements. Remote sensing technologies include an automated Raman lidar and an automated Atmospheric Emitted Radiance Interferometer (AERI), which are able to retrieve water vapor profiles operationally through the lower troposphere throughout the diurnal cycle. Comparisons of these two water vapor remote sensing methods to each other and to radiosondes over an 8-month period are presented and discussed, highlighting the accuracy and limitations of each method. Additionally, the AERI is able to retrieve profiles of temperature while the Raman lidar is able to retrieve aerosol extinction profiles operationally. These data, coupled with hourly wind profiles from a 915-MHz wind profiler, provide complete specification of the state of the atmosphere in noncloudy skies. Several case studies illustrate the utility of these high temporal resolution measurements in the characterization of mesoscale features within a 3-day time period in which passage of a dryline, warm air advection, and cold front occurred.

Interactions between deep convective clouds and aerosols as observed by satellites

NASA Astrophysics Data System (ADS)

Yuan, T.; Li, Z. I.; Remer, L.; Martins, V.

2008-12-01

Major uncertainties regarding interactions between deep convective clouds (DCC) exist due partly to observational difficulty and partly to the entanglement among remotely sensed properties of aerosols and clouds and entanglement between meteorology and possible aerosol signals. In this study we adopt a novel, physically sound relationship between cloud crystal effective radius(CER) and brightness temperature (BT) and utilize ample sampling opportunity provided by MODIS instrument. We reveal aerosol impacts on DCCs by analyzing an ensemble data. Through a conceptual model we demonstrate how aerosol may affect DCC properties. We outline a few scenarios where aerosol signals are best separated and pronounced. Based on our results, anthropogenic pollutions and smokes are shown to effectively decrease CER and to elevate glaciation level of DCCs. On the other hand, dust particles from local sources have the opposite effects, namely, increasing cloud ice particle size and enhancing glaciation by acting possibly as giant CCN or IN. Implications of these effects for aerosols are discussed along with feedbacks of these effects to dynamics.

Studies of Emissions and Atmospheric Composition, Clouds, and Climate Coupling by Regional Surveys (SEAC4RS) Field Campaign Report

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

Schmid, B.; Flynn, C.

Studies of Emissions and Atmospheric Composition, Clouds and Climate Coupling by Regional Surveys (SEAC4RS), a National Aeronautics and Space Administration (NASA) field campaign, was based out of Ellington Field in Houston, Texas, during August and September 2013. The study focused on pollution emissions and the evolution of gases and aerosols in deep convective outflow, and the influences and feedbacks of aerosol particles from anthropogenic pollution and biomass burning on meteorology, clouds, and climate. The project required three aircraft to accomplish these goals. The NASA DC-8 provided observations from near the surface to 12 km, while the NASA ER-2 provided high-altitudemore » observations reaching into the lower stratosphere as well as important remote-sensing observations connecting satellites with observations from lower-flying aircraft and surface sites. The SPEC, Inc. Learjet obtained aerosol and cloud microphysical measurement in convective clouds and convective outflow.« less

Modification of the Atmospheric Boundary Layer by a Small Island: Observations from Nauru

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

Matthews, Stuart; Hacker, Jorg M.; Cole, Jason N.

2007-03-01

Nauru, a small island in the tropical pacific, generates plumes of clouds that may grow to several hundred km length. This study uses observations to examine the mesoscale disturbance of the marine atmospheric boundary layer by the island that produces these cloud streets. Observations of the surface layer were made from two ships in the vicinity of Nauru and from instruments on the island. The structure of the atmospheric boundary layer over the island was investigated using aircraft flights. Cloud production over Nauru was examined using remote sensing instruments. During the day the island surface layer was warmer than themore » marine surface layer and wind speed was lower than over the ocean. Surface heating forced the growth of a thermal internal boundary layer, above which a street of cumulus clouds formed. The production of clouds resulted in reduced downwelling shortwave irradiance at the island surface. A plume of warm-dry air was observed over the island which extended 15 – 20 km downwind.« less

The economic value of remote sensing of earth resources from space: An ERTS overview and the value of continuity of service. Volume 8: Atmosphere

NASA Technical Reports Server (NTRS)

Miles, R.; Fawkes, G.

1974-01-01

The economic value of an ERS system in the resource area of atmosphere is determined. Benefits which arise from air pollution and cloud observations correlated to ground stations are discussed along with cost savings associated with air pollution monitoring by satellite. Social benefits due to more precise knowledge of the effects of pollution are presented.