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

NARCIS (Netherlands)

Lenaerts, JTM; Van Tricht, Kristof; Lhermitte, S.L.M.; L'Ecuyer, T.S.

2017-01-01

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

The sensitivities of in cloud and cloud top phase distributions to primary ice formation in ICON-LEM

Science.gov (United States)

Beydoun, H.; Karrer, M.; Tonttila, J.; Hoose, C.

2017-12-01

Mixed phase clouds remain a leading source of uncertainty in our attempt to quantify cloud-climate and aerosol-cloud climate interactions. Nevertheless, recent advances in parametrizing the primary ice formation process, high resolution cloud modelling, and retrievals of cloud phase distributions from satellite data offer an excellent opportunity to conduct closure studies on the sensitivity of the cloud phase to microphysical and dynamical processes. Particularly, the reliability of satellite data to resolve the phase at the top of the cloud provides a promising benchmark to compare model output to. We run large eddy simulations with the new ICOsahedral Non-hydrostatic atmosphere model (ICON) to place bounds on the sensitivity of in cloud and cloud top phase to the primary ice formation process. State of the art primary ice formation parametrizations in the form of the cumulative ice active site density ns are implemented in idealized deep convective cloud simulations. We exploit the ability of ICON-LEM to switch between a two moment microphysics scheme and the newly developed Predicted Particle Properties (P3) scheme by running our simulations in both configurations for comparison. To quantify the sensitivity of cloud phase to primary ice formation, cloud ice content is evaluated against order of magnitude changes in ns at variable convective strengths. Furthermore, we assess differences between in cloud and cloud top phase distributions as well as the potential impact of updraft velocity on the suppression of the Wegener-Bergeron-Findeisen process. The study aims to evaluate our practical understanding of primary ice formation in the context of predicting the structure and evolution of mixed phase clouds.

Toward the Characterization of Mixed-Phase Clouds Using Remote Sensing

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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.

Validating Satellite-Retrieved Cloud Properties for Weather and Climate Applications

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Minnis, P.; Bedka, K. M.; Smith, W., Jr.; Yost, C. R.; Bedka, S. T.; Palikonda, R.; Spangenberg, D.; Sun-Mack, S.; Trepte, Q.; Dong, X.; Xi, B.

2014-12-01

Cloud properties determined from satellite imager radiances are increasingly used in weather and climate applications, particularly in nowcasting, model assimilation and validation, trend monitoring, and precipitation and radiation analyses. The value of using the satellite-derived cloud parameters is determined by the accuracy of the particular parameter for a given set of conditions, such as viewing and illumination angles, surface background, and cloud type and structure. Because of the great variety of those conditions and of the sensors used to monitor clouds, determining the accuracy or uncertainties in the retrieved cloud parameters is a daunting task. Sensitivity studies of the retrieved parameters to the various inputs for a particular cloud type are helpful for understanding the errors associated with the retrieval algorithm relative to the plane-parallel world assumed in most of the model clouds that serve as the basis for the retrievals. Real world clouds, however, rarely fit the plane-parallel mold and generate radiances that likely produce much greater errors in the retrieved parameter than can be inferred from sensitivity analyses. Thus, independent, empirical methods are used to provide a more reliable uncertainty analysis. At NASA Langley, cloud properties are being retrieved from both geostationary (GEO) and low-earth orbiting (LEO) satellite imagers for climate monitoring and model validation as part of the NASA CERES project since 2000 and from AVHRR data since 1978 as part of the NOAA CDR program. Cloud properties are also being retrieved in near-real time globally from both GEO and LEO satellites for weather model assimilation and nowcasting for hazards such as aircraft icing. This paper discusses the various independent datasets and approaches that are used to assessing the imager-based satellite cloud retrievals. These include, but are not limited to data from ARM sites, CloudSat, and CALIPSO. This paper discusses the use of the various

Providing Access and Visualization to Global Cloud Properties from GEO Satellites

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Chee, T.; Nguyen, L.; Minnis, P.; Spangenberg, D.; Palikonda, R.; Ayers, J. K.

2015-12-01

Providing public access to cloud macro and microphysical properties is a key concern for the NASA Langley Research Center Cloud and Radiation Group. This work describes a tool and method that allows end users to easily browse and access cloud information that is otherwise difficult to acquire and manipulate. The core of the tool is an application-programming interface that is made available to the public. One goal of the tool is to provide a demonstration to end users so that they can use the dynamically generated imagery as an input into their own work flows for both image generation and cloud product requisition. This project builds upon NASA Langley Cloud and Radiation Group's experience with making real-time and historical satellite cloud product imagery accessible and easily searchable. As we see the increasing use of virtual supply chains that provide additional value at each link there is value in making satellite derived cloud product information available through a simple access method as well as allowing users to browse and view that imagery as they need rather than in a manner most convenient for the data provider. Using the Open Geospatial Consortium's Web Processing Service as our access method, we describe a system that uses a hybrid local and cloud based parallel processing system that can return both satellite imagery and cloud product imagery as well as the binary data used to generate them in multiple formats. The images and cloud products are sourced from multiple satellites and also "merged" datasets created by temporally and spatially matching satellite sensors. Finally, the tool and API allow users to access information that spans the time ranges that our group has information available. In the case of satellite imagery, the temporal range can span the entire lifetime of the sensor.

Satellite retrieval of cloud condensation nuclei concentrations by using clouds as CCN chambers

Science.gov (United States)

Rosenfeld, Daniel; Zheng, Youtong; Hashimshoni, Eyal; Pöhlker, Mira L.; Jefferson, Anne; Pöhlker, Christopher; Yu, Xing; Zhu, Yannian; Liu, Guihua; Yue, Zhiguo; Fischman, Baruch; Li, Zhanqing; Giguzin, David; Goren, Tom; Artaxo, Paulo; Pöschl, Ulrich

2016-01-01

Quantifying the aerosol/cloud-mediated radiative effect at a global scale requires simultaneous satellite retrievals of cloud condensation nuclei (CCN) concentrations and cloud base updraft velocities (Wb). Hitherto, the inability to do so has been a major cause of high uncertainty regarding anthropogenic aerosol/cloud-mediated radiative forcing. This can be addressed by the emerging capability of estimating CCN and Wb of boundary layer convective clouds from an operational polar orbiting weather satellite. Our methodology uses such clouds as an effective analog for CCN chambers. The cloud base supersaturation (S) is determined by Wb and the satellite-retrieved cloud base drop concentrations (Ndb), which is the same as CCN(S). Validation against ground-based CCN instruments at Oklahoma, at Manaus, and onboard a ship in the northeast Pacific showed a retrieval accuracy of ±25% to ±30% for individual satellite overpasses. The methodology is presently limited to boundary layer not raining convective clouds of at least 1 km depth that are not obscured by upper layer clouds, including semitransparent cirrus. The limitation for small solar backscattering angles of <25° restricts the satellite coverage to ∼25% of the world area in a single day. PMID:26944081

Towards a Cloud Computing Environment: Near Real-time Cloud Product Processing and Distribution for Next Generation Satellites

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Nguyen, L.; Chee, T.; Minnis, P.; Palikonda, R.; Smith, W. L., Jr.; Spangenberg, D.

2016-12-01

The NASA LaRC Satellite ClOud and Radiative Property retrieval System (SatCORPS) processes and derives near real-time (NRT) global cloud products from operational geostationary satellite imager datasets. These products are being used in NRT to improve forecast model, aircraft icing warnings, and support aircraft field campaigns. Next generation satellites, such as the Japanese Himawari-8 and the upcoming NOAA GOES-R, present challenges for NRT data processing and product dissemination due to the increase in temporal and spatial resolution. The volume of data is expected to increase to approximately 10 folds. This increase in data volume will require additional IT resources to keep up with the processing demands to satisfy NRT requirements. In addition, these resources are not readily available due to cost and other technical limitations. To anticipate and meet these computing resource requirements, we have employed a hybrid cloud computing environment to augment the generation of SatCORPS products. This paper will describe the workflow to ingest, process, and distribute SatCORPS products and the technologies used. Lessons learn from working on both AWS Clouds and GovCloud will be discussed: benefits, similarities, and differences that could impact decision to use cloud computing and storage. A detail cost analysis will be presented. In addition, future cloud utilization, parallelization, and architecture layout will be discussed for GOES-R.

Examination of Regional Trends in Cloud Properties over Surface Sites Derived from MODIS and AVHRR using the CERES Cloud Algorithm

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Smith, W. L., Jr.; Minnis, P.; Bedka, K. M.; Sun-Mack, S.; Chen, Y.; Doelling, D. R.; Kato, S.; Rutan, D. A.

2017-12-01

Recent studies analyzing long-term measurements of surface insolation at ground sites suggest that decadal-scale trends of increasing (brightening) and decreasing (dimming) downward solar flux have occurred at various times over the last century. Regional variations have been reported that range from near 0 Wm-2/decade to as large as 9 Wm-2/decade depending on the location and time period analyzed. The more significant trends have been attributed to changes in overhead clouds and aerosols, although quantifying their relative impacts using independent observations has been difficult, owing in part to a lack of consistent long-term measurements of cloud properties. This paper examines new satellite based records of cloud properties derived from MODIS (2000-present) and AVHRR (1981- present) data to infer cloud property trends over a number of surface radiation sites across the globe. The MODIS cloud algorithm was developed for the NASA Clouds and the Earth's Radiant Energy System (CERES) project to provide a consistent record of cloud properties to help improve broadband radiation measurements and to better understand cloud radiative effects. The CERES-MODIS cloud algorithm has been modified to analyze other satellites including the AVHRR on the NOAA satellites. Compared to MODIS, obtaining consistent cloud properties over a long period from AVHRR is a much more significant challenge owing to the number of different satellites, instrument calibration uncertainties, orbital drift and other factors. Nevertheless, both the MODIS and AVHRR cloud properties will be analyzed to determine trends, and their level of consistency and correspondence with surface radiation trends derived from the ground-based radiometer data. It is anticipated that this initial study will contribute to an improved understanding of surface solar radiation trends and their relationship to clouds.

Validation of Cloud Parameters Derived from Geostationary Satellites, AVHRR, MODIS, and VIIRS Using SatCORPS Algorithms

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Minnis, P.; Sun-Mack, S.; Bedka, K. M.; Yost, C. R.; Trepte, Q. Z.; Smith, W. L., Jr.; Painemal, D.; Chen, Y.; Palikonda, R.; Dong, X.;

Improving Climate Projections by Understanding How Cloud Phase affects Radiation

Science.gov (United States)

Cesana, Gregory; Storelvmo, Trude

2017-01-01

Whether a cloud is predominantly water or ice strongly influences interactions between clouds and radiation coming down from the Sun or up from the Earth. Being able to simulate cloud phase transitions accurately in climate models based on observational data sets is critical in order to improve confidence in climate projections, because this uncertainty contributes greatly to the overall uncertainty associated with cloud-climate feedbacks. Ultimately, it translates into uncertainties in Earth's sensitivity to higher CO2 levels. While a lot of effort has recently been made toward constraining cloud phase in climate models, more remains to be done to document the radiative properties of clouds according to their phase. Here we discuss the added value of a new satellite data set that advances the field by providing estimates of the cloud radiative effect as a function of cloud phase and the implications for climate projections.

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

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

2017-12-01

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

Determining Cloud Thermodynamic Phase from Micropulse Lidar Network Data

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Lewis, Jasper R.; Campbell, James; Lolli, Simone; Tan, Ivy; Welton, Ellsworth J.

2017-01-01

Determining cloud thermodynamic phase is a critical factor in studies of Earth's radiation budget. Here we use observations from the NASA Micro Pulse Lidar Network (MPLNET) and thermodynamic profiles from the Goddard Earth Observing System, version 5 (GEOS-5) to distinguish liquid water, mixed-phase, and ice water clouds. The MPLNET provides sparse global, autonomous, and continuous measurements of clouds and aerosols which have been used in a number of scientific investigations to date. The use of a standardized instrument and a common suite of data processing algorithms with thorough uncertainty characterization allows for straightforward comparisons between sites. Lidars with polarization capabilities have recently been incorporated into the MPLNET project which allows, for the first time, the ability to infer a cloud thermodynamic phase. This presentation will look specifically at the occurrence of ice and mixed phase clouds in the temperature region of -10 C to -40 C for different climatological regions and seasons. We compare MPLNET occurrences of mixed-phase clouds to an historical climatology based on observations from the Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) instrument aboard the Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) spacecraft.

Observational Constraints on Cloud Feedbacks: The Role of Active Satellite Sensors

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Winker, David; Chepfer, Helene; Noel, Vincent; Cai, Xia

2017-11-01

Cloud profiling from active lidar and radar in the A-train satellite constellation has significantly advanced our understanding of clouds and their role in the climate system. Nevertheless, the response of clouds to a warming climate remains one of the largest uncertainties in predicting climate change and for the development of adaptions to change. Both observation of long-term changes and observational constraints on the processes responsible for those changes are necessary. We review recent progress in our understanding of the cloud feedback problem. Capabilities and advantages of active sensors for observing clouds are discussed, along with the importance of active sensors for deriving constraints on cloud feedbacks as an essential component of a global climate observing system.

Validation of satellite-retrieved MBL cloud properties using DOE ARM AMF measurements at the Azores

Science.gov (United States)

Xi, B.; Dong, X.; Minnis, P.; Sun-Mack, S.

2013-05-01

Marine Boundary Layer (MBL) cloud properties derived for the Clouds and the Earth's Radiant Energy System (CERES) Project using Terra and Aqua Moderate Resolution Imaging Spectroradiometer (MODIS) data are compared with observations taken at the Atmospheric Radiation Measurement (ARM) AMF AZORES site from June 2009 through December 2010. Retrievals from ARM surface-based data were averaged over a 1-hour interval centered at the time of each satellite overpass, and the CERES-MODIS Ed4 cloud properties were averaged within a 30-km x 30-km box centered on the ARM AZORES site. Two datasets were analyzed: all of the single-layered unbroken decks (SL) and those cases without temperature inversions. The CERES-MODIS cloud top/base heights were determined from cloud top/base temperature by using a lapse rate method normalized to the 24-h mean surface air temperature. The preliminary results show: for all SL MBL at daytime, they are, on average, 0.148 km (cloud top) and 0.087 km (cloud base) higher than the ARM radar-lidar observed cloud top and base, respectively. At nighttime, they are 0.446 km (cloud top) and 0.334 km (cloud base). For those cases without temperature inversions, the comparisons are close to their SL counterparts. For cloud temperatures, the MODIS-derived cloud-top and -base temperatures are 1.6 K lower and 0.4 K higher than the surface values with correlations of 0.92 during daytime. At nighttime, the differences are slightly larger and correlations are lower than daytime comparisons. Variations in the height difference are mainly caused by uncertainties in the surface air temperatures and lapse rates. Based on a total of 61 daytime and 87 nighttime samples (ALL SL cases), the temperature inversion layers occur about 72% during daytime and 83% during nighttime. The difference of surface-observed lapse rate and the satellite derived lapse rate can be 1.6 K/km for daytime and 3.3K/km for nighttime. From these lapse rates, we can further analyze the surface

Classification of Clouds in Satellite Imagery Using Adaptive Fuzzy Sparse Representation

Directory of Open Access Journals (Sweden)

Wei Jin

2016-12-01

Full Text Available 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.

Classification of Clouds in Satellite Imagery Using Adaptive Fuzzy Sparse Representation

Science.gov (United States)

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

Active sensor synergy for arctic cloud microphysics

Directory of Open Access Journals (Sweden)

Sato Kaori

2018-01-01

Full Text Available In this study, we focus on the retrieval of liquid and ice-phase cloud microphysics from spaceborne and ground-based lidar-cloud radar synergy. As an application of the cloud retrieval algorithm developed for the EarthCARE satellite mission (JAXA-ESA [1], the derived statistics of cloud microphysical properties in high latitudes and their relation to the Arctic climate are investigated.

Estimation of time-series properties of gourd observed solar irradiance data using cloud properties derived from satellite observations

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Watanabe, T.; Nohara, D.

2017-12-01

The shorter temporal scale variation in the downward solar irradiance at the ground level (DSI) is not understood well because researches in the shorter-scale variation in the DSI is based on the ground observation and ground observation stations are located coarsely. Use of dataset derived from satellite observation will overcome such defect. DSI data and MODIS cloud properties product are analyzed simultaneously. Three metrics: mean, standard deviation and sample entropy, are used to evaluate time-series properties of the DSI. Three metrics are computed from two-hours time-series centered at the observation time of MODIS over the ground observation stations. We apply the regression methods to design prediction models of each three metrics from cloud properties. The validation of the model accuracy show that mean and standard deviation are predicted with a higher degree of accuracy and that the accuracy of prediction of sample entropy, which represents the complexity of time-series, is not high. One of causes of lower prediction skill of sample entropy is the resolution of the MODIS cloud properties. Higher sample entropy is corresponding to the rapid fluctuation, which is caused by the small and unordered cloud. It seems that such clouds isn't retrieved well.

Cloud vertical profiles derived from CALIPSO and CloudSat and a comparison with MODIS derived clouds

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Kato, S.; Sun-Mack, S.; Miller, W. F.; Rose, F. G.; Minnis, P.; Wielicki, B. A.; Winker, D. M.; Stephens, G. L.; Charlock, T. P.; Collins, W. D.; Loeb, N. G.; Stackhouse, P. W.; Xu, K.

2008-05-01

CALIPSO and CloudSat from the a-train provide detailed information of vertical distribution of clouds and aerosols. The vertical distribution of cloud occurrence is derived from one month of CALIPSO and CloudSat data as a part of the effort of merging CALIPSO, CloudSat and MODIS with CERES data. This newly derived cloud profile is compared with the distribution of cloud top height derived from MODIS on Aqua from cloud algorithms used in the CERES project. The cloud base from MODIS is also estimated using an empirical formula based on the cloud top height and optical thickness, which is used in CERES processes. While MODIS detects mid and low level clouds over the Arctic in April fairly well when they are the topmost cloud layer, it underestimates high- level clouds. In addition, because the CERES-MODIS cloud algorithm is not able to detect multi-layer clouds and the empirical formula significantly underestimates the depth of high clouds, the occurrence of mid and low-level clouds is underestimated. This comparison does not consider sensitivity difference to thin clouds but we will impose an optical thickness threshold to CALIPSO derived clouds for a further comparison. The effect of such differences in the cloud profile to flux computations will also be discussed. In addition, the effect of cloud cover to the top-of-atmosphere flux over the Arctic using CERES SSF and FLASHFLUX products will be discussed.

Validation of Cloud Properties From Multiple Satellites Using CALIOP Data

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Yost, Christopher R.; Minnis, Patrick; Bedka, Kristopher M.; Heck, Patrick W.; Palikonda, Rabindra; Sun-Mack, Sunny; Trepte, Qing

2016-01-01

The NASA Langley Satellite ClOud and Radiative Property retrieval System (SatCORPS) is routinely applied to multispectral imagery from several geostationary and polar-orbiting imagers to retrieve cloud properties for weather and climate applications. Validation of the retrievals with independent datasets is continuously ongoing in order to understand differences caused by calibration, spatial resolution, viewing geometry, and other factors. The CALIOP instrument provides a decade of detailed cloud observations which can be used to evaluate passive imager retrievals of cloud boundaries, thermodynamic phase, cloud optical depth, and water path on a global scale. This paper focuses on comparisons of CALIOP retrievals to retrievals from MODIS, VIIRS, AVHRR, GOES, SEVIRI, and MTSAT. CALIOP is particularly skilled at detecting weakly-scattering cirrus clouds with optical depths less than approx. 0.5. These clouds are often undetected by passive imagers and the effect this has on the property retrievals is discussed.

Evaluation of the shortwave cloud radiative effect over the ocean by use of ship and satellite observations

Directory of Open Access Journals (Sweden)

T. Hanschmann

2012-12-01

Full Text Available In this study the shortwave cloud radiative effect (SWCRE over ocean calculated by the ECHAM 5 climate model is evaluated for the cloud property input derived from ship based measurements and satellite based estimates and compared to ship based radiation measurements. The ship observations yield cloud fraction, liquid water path from a microwave radiometer, cloud bottom height as well as temperature and humidity profiles from radiosonde ascents. Level-2 products of the Satellite Application Facility on Climate Monitoring (CM~SAF from the Spinning Enhanced Visible and InfraRed Imager (SEVIRI have been used to characterize clouds. Within a closure study six different experiments have been defined to find the optimal set of measurements to calculate downward shortwave radiation (DSR and the SWCRE from the model, and their results have been evaluated under seven different synoptic situations. Four of these experiments are defined to investigate the advantage of including the satellite-based cloud droplet effective radius as additional cloud property. The modeled SWCRE based on satellite retrieved cloud properties has a comparable accuracy to the modeled SWCRE based on ship data. For several cases, an improvement through introducing the satellite-based estimate of effective radius as additional information to the ship based data was found. Due to their different measuring characteristics, however, each dataset shows best results for different atmospheric conditions.

Satellite Cloud and Radiative Property Processing and Distribution System on the NASA Langley ASDC OpenStack and OpenShift Cloud Platform

Science.gov (United States)

Nguyen, L.; Chee, T.; Palikonda, R.; Smith, W. L., Jr.; Bedka, K. M.; Spangenberg, D.; Vakhnin, A.; Lutz, N. E.; Walter, J.; Kusterer, J.

2017-12-01

Cloud Computing offers new opportunities for large-scale scientific data producers to utilize Infrastructure-as-a-Service (IaaS) and Platform-as-a-Service (PaaS) IT resources to process and deliver data products in an operational environment where timely delivery, reliability, and availability are critical. The NASA Langley Research Center Atmospheric Science Data Center (ASDC) is building and testing a private and public facing cloud for users in the Science Directorate to utilize as an everyday production environment. The NASA SatCORPS (Satellite ClOud and Radiation Property Retrieval System) team processes and derives near real-time (NRT) global cloud products from operational geostationary (GEO) satellite imager datasets. To deliver these products, we will utilize the public facing cloud and OpenShift to deploy a load-balanced webserver for data storage, access, and dissemination. The OpenStack private cloud will host data ingest and computational capabilities for SatCORPS processing. This paper will discuss the SatCORPS migration towards, and usage of, the ASDC Cloud Services in an operational environment. Detailed lessons learned from use of prior cloud providers, specifically the Amazon Web Services (AWS) GovCloud and the Government Cloud administered by the Langley Managed Cloud Environment (LMCE) will also be discussed.

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

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

2014-10-01

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

Contributions of Heterogeneous Ice Nucleation, Large-Scale Circulation, and Shallow Cumulus Detrainment to Cloud Phase Transition in Mixed-Phase Clouds with NCAR CAM5

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

2016-12-01

Mixed-phase clouds consisting of both liquid and ice water occur frequently at high-latitudes and in mid-latitude storm track regions. This type of clouds has been shown to play a critical role in the surface energy balance, surface air temperature, and sea ice melting in the Arctic. Cloud phase partitioning between liquid and ice water determines the cloud optical depth of mixed-phase clouds because of distinct optical properties of liquid and ice hydrometeors. The representation and simulation of cloud phase partitioning in state-of-the-art global climate models (GCMs) are associated with large biases. In this study, the cloud phase partition in mixed-phase clouds simulated from the NCAR Community Atmosphere Model version 5 (CAM5) is evaluated against satellite observations. Observation-based supercooled liquid fraction (SLF) is calculated from CloudSat, MODIS and CPR radar detected liquid and ice water paths for clouds with cloud-top temperatures between -40 and 0°C. Sensitivity tests with CAM5 are conducted for different heterogeneous ice nucleation parameterizations with respect to aerosol influence (Wang et al., 2014), different phase transition temperatures for detrained cloud water from shallow convection (Kay et al., 2016), and different CAM5 model configurations (free-run versus nudged winds and temperature, Zhang et al., 2015). A classical nucleation theory-based ice nucleation parameterization in mixed-phase clouds increases the SLF especially at temperatures colder than -20°C, and significantly improves the model agreement with observations in the Arctic. The change of transition temperature for detrained cloud water increases the SLF at higher temperatures and improves the SLF mostly over the Southern Ocean. Even with the improved SLF from the ice nucleation and shallow cumulus detrainment, the low SLF biases in some regions can only be improved through the improved circulation with the nudging technique. Our study highlights the challenges of

Arctic sea ice albedo - A comparison of two satellite-derived data sets

Science.gov (United States)

Schweiger, Axel J.; Serreze, Mark C.; Key, Jeffrey R.

1993-01-01

Spatial patterns of mean monthly surface albedo for May, June, and July, derived from DMSP Operational Line Scan (OLS) satellite imagery are compared with surface albedos derived from the International Satellite Cloud Climatology Program (ISCCP) monthly data set. Spatial patterns obtained by the two techniques are in general agreement, especially for June and July. Nevertheless, systematic differences in albedo of 0.05 - 0.10 are noted which are most likely related to uncertainties in the simple parameterizations used in the DMSP analyses, problems in the ISCCP cloud-clearing algorithm and other modeling simplifications. However, with respect to the eventual goal of developing a reliable automated retrieval algorithm for compiling a long-term albedo data base, these initial comparisons are very encouraging.

Using Information From Prior Satellite Scans to Improve Cloud Detection Near the Day-Night Terminator

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Yost, Christopher R.; Minnis, Patrick; Trepte, Qing Z.; Palikonda, Rabindra; Ayers, Jeffrey K.; Spangenberg, Doulas A.

2012-01-01

With geostationary satellite data it is possible to have a continuous record of diurnal cycles of cloud properties for a large portion of the globe. Daytime cloud property retrieval algorithms are typically superior to nighttime algorithms because daytime methods utilize measurements of reflected solar radiation. However, reflected solar radiation is difficult to accurately model for high solar zenith angles where the amount of incident radiation is small. Clear and cloudy scenes can exhibit very small differences in reflected radiation and threshold-based cloud detection methods have more difficulty setting the proper thresholds for accurate cloud detection. Because top-of-atmosphere radiances are typically more accurately modeled outside the terminator region, information from previous scans can help guide cloud detection near the terminator. This paper presents an algorithm that uses cloud fraction and clear and cloudy infrared brightness temperatures from previous satellite scan times to improve the performance of a threshold-based cloud mask near the terminator. Comparisons of daytime, nighttime, and terminator cloud fraction derived from Geostationary Operational Environmental Satellite (GOES) radiance measurements show that the algorithm greatly reduces the number of false cloud detections and smoothes the transition from the daytime to the nighttime clod detection algorithm. Comparisons with the Geoscience Laser Altimeter System (GLAS) data show that using this algorithm decreases the number of false detections by approximately 20 percentage points.

Improvements of top-of-atmosphere and surface irradiance computations with CALIPSO-, CloudSat-, and MODIS-derived cloud and aerosol properties

Science.gov (United States)

Kato, Seiji; Rose, Fred G.; Sun-Mack, Sunny; Miller, Walter F.; Chen, Yan; Rutan, David A.; Stephens, Graeme L.; Loeb, Norman G.; Minnis, Patrick; Wielicki, Bruce A.; Winker, David M.; Charlock, Thomas P.; Stackhouse, Paul W., Jr.; Xu, Kuan-Man; Collins, William D.

2011-10-01

One year of instantaneous top-of-atmosphere (TOA) and surface shortwave and longwave irradiances are computed using cloud and aerosol properties derived from instruments on the A-Train Constellation: the Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) on the Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO) satellite, the CloudSat Cloud Profiling Radar (CPR), and the Aqua Moderate Resolution Imaging Spectrometer (MODIS). When modeled irradiances are compared with those computed with cloud properties derived from MODIS radiances by a Clouds and the Earth's Radiant Energy System (CERES) cloud algorithm, the global and annual mean of modeled instantaneous TOA irradiances decreases by 12.5 W m-2 (5.0%) for reflected shortwave and 2.5 W m-2 (1.1%) for longwave irradiances. As a result, the global annual mean of instantaneous TOA irradiances agrees better with CERES-derived irradiances to within 0.5W m-2 (out of 237.8 W m-2) for reflected shortwave and 2.6W m-2 (out of 240.1 W m-2) for longwave irradiances. In addition, the global annual mean of instantaneous surface downward longwave irradiances increases by 3.6 W m-2 (1.0%) when CALIOP- and CPR-derived cloud properties are used. The global annual mean of instantaneous surface downward shortwave irradiances also increases by 8.6 W m-2 (1.6%), indicating that the net surface irradiance increases when CALIOP- and CPR-derived cloud properties are used. Increasing the surface downward longwave irradiance is caused by larger cloud fractions (the global annual mean by 0.11, 0.04 excluding clouds with optical thickness less than 0.3) and lower cloud base heights (the global annual mean by 1.6 km). The increase of the surface downward longwave irradiance in the Arctic exceeds 10 W m-2 (˜4%) in winter because CALIOP and CPR detect more clouds in comparison with the cloud detection by the CERES cloud algorithm during polar night. The global annual mean surface downward longwave irradiance of

Uncertainty Estimate of Surface Irradiances Computed with MODIS-, CALIPSO-, and CloudSat-Derived Cloud and Aerosol Properties

Science.gov (United States)

Kato, Seiji; Loeb, Norman G.; Rutan, David A.; Rose, Fred G.; Sun-Mack, Sunny; Miller, Walter F.; Chen, Yan

2012-07-01

Differences of modeled surface upward and downward longwave and shortwave irradiances are calculated using modeled irradiance computed with active sensor-derived and passive sensor-derived cloud and aerosol properties. The irradiance differences are calculated for various temporal and spatial scales, monthly gridded, monthly zonal, monthly global, and annual global. Using the irradiance differences, the uncertainty of surface irradiances is estimated. The uncertainty (1σ) of the annual global surface downward longwave and shortwave is, respectively, 7 W m-2 (out of 345 W m-2) and 4 W m-2 (out of 192 W m-2), after known bias errors are removed. Similarly, the uncertainty of the annual global surface upward longwave and shortwave is, respectively, 3 W m-2 (out of 398 W m-2) and 3 W m-2 (out of 23 W m-2). The uncertainty is for modeled irradiances computed using cloud properties derived from imagers on a sun-synchronous orbit that covers the globe every day (e.g., moderate-resolution imaging spectrometer) or modeled irradiances computed for nadir view only active sensors on a sun-synchronous orbit such as Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation and CloudSat. If we assume that longwave and shortwave uncertainties are independent of each other, but up- and downward components are correlated with each other, the uncertainty in global annual mean net surface irradiance is 12 W m-2. One-sigma uncertainty bounds of the satellite-based net surface irradiance are 106 W m-2 and 130 W m-2.

H31G-1596: DeepSAT's CloudCNN: A Deep Neural Network for Rapid Cloud Detection from Geostationary Satellites

Science.gov (United States)

Kalia, Subodh; Ganguly, Sangram; Li, Shuang; Nemani, Ramakrishna R.

2017-01-01

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

An Automatic Cloud Detection Method for ZY-3 Satellite

Directory of Open Access Journals (Sweden)

CHEN Zhenwei

2015-03-01

Full Text Available Automatic cloud detection for optical satellite remote sensing images is a significant step in the production system of satellite products. For the browse images cataloged by ZY-3 satellite, the tree discriminate structure is adopted to carry out cloud detection. The image was divided into sub-images and their features were extracted to perform classification between clouds and grounds. However, due to the high complexity of clouds and surfaces and the low resolution of browse images, the traditional classification algorithms based on image features are of great limitations. In view of the problem, a prior enhancement processing to original sub-images before classification was put forward in this paper to widen the texture difference between clouds and surfaces. Afterwards, with the secondary moment and first difference of the images, the feature vectors were extended in multi-scale space, and then the cloud proportion in the image was estimated through comprehensive analysis. The presented cloud detection algorithm has already been applied to the ZY-3 application system project, and the practical experiment results indicate that this algorithm is capable of promoting the accuracy of cloud detection significantly.

Top-down and Bottom-up aerosol-cloud-closure: towards understanding sources of unvertainty in deriving cloud radiative flux

Science.gov (United States)

Sanchez, K.; Roberts, G.; Calmer, R.; Nicoll, K.; Hashimshoni, E.; Rosenfeld, D.; Ovadnevaite, J.; Preissler, J.; Ceburnis, D.; O'Dowd, C. D. D.; Russell, L. M.

2017-12-01

Top-down and bottom-up aerosol-cloud shortwave radiative flux closures were conducted at the Mace Head atmospheric research station in Galway, Ireland in August 2015. Instrument platforms include ground-based, unmanned aerial vehicles (UAV), and satellite measurements of aerosols, clouds and meteorological variables. The ground-based and airborne measurements of aerosol size distributions and cloud condensation nuclei (CCN) concentration were used to initiate a 1D microphysical aerosol-cloud parcel model (ACPM). UAVs were equipped for a specific science mission, with an optical particle counter for aerosol distribution profiles, a cloud sensor to measure cloud extinction, or a 5-hole probe for 3D wind vectors. These are the first UAV measurements at Mace Head. ACPM simulations are compared to in-situ cloud extinction measurements from UAVs to quantify closure in terms of cloud shortwave radiative flux. Two out of seven cases exhibit sub-adiabatic vertical temperature profiles within the cloud, which suggests that entrainment processes affect cloud microphysical properties and lead to an overestimate of simulated cloud shortwave radiative flux. Including an entrainment parameterization and explicitly calculating the entrainment fraction in the ACPM simulations both improved cloud-top radiative closure. Entrainment reduced the difference between simulated and observation-derived cloud-top shortwave radiative flux (δRF) by between 25 W m-2 and 60 W m-2. After accounting for entrainment, satellite-derived cloud droplet number concentrations (CDNC) were within 30% of simulated CDNC. In cases with a well-mixed boundary layer, δRF is no greater than 20 W m-2 after accounting for cloud-top entrainment, and up to 50 W m-2 when entrainment is not taken into account. In cases with a decoupled boundary layer, cloud microphysical properties are inconsistent with ground-based aerosol measurements, as expected, and δRF is as high as 88 W m-2, even high (> 30 W m-2) after

DEVELOPMENT OF IMPROVED TECHNIQUES FOR SATELLITE REMOTE SENSING OF CLOUDS AND RADIATION USING ARM DATA, FINAL REPORT

Energy Technology Data Exchange (ETDEWEB)

Minnis, Patrick [NASA Langley Research Center, Hampton, VA

2013-06-28

During the period, March 1997 – February 2006, the Principal Investigator and his research team co-authored 47 peer-reviewed papers and presented, at least, 138 papers at conferences, meetings, and workshops that were supported either in whole or in part by this agreement. We developed a state-of-the-art satellite cloud processing system that generates cloud properties over the Atmospheric Radiation (ARM) surface sites and surrounding domains in near-real time and outputs the results on the world wide web in image and digital formats. When the products are quality controlled, they are sent to the ARM archive for further dissemination. These products and raw satellite images can be accessed at http://cloudsgate2.larc.nasa.gov/cgi-bin/site/showdoc?docid=4&cmd=field-experiment-homepage&exp=ARM and are used by many in the ARM science community. The algorithms used in this system to generate cloud properties were validated and improved by the research conducted under this agreement. The team supported, at least, 11 ARM-related or supported field experiments by providing near-real time satellite imagery, cloud products, model results, and interactive analyses for mission planning, execution, and post-experiment scientific analyses. Comparisons of cloud properties derived from satellite, aircraft, and surface measurements were used to evaluate uncertainties in the cloud properties. Multiple-angle satellite retrievals were used to determine the influence of cloud structural and microphysical properties on the exiting radiation field.

AUTOMATIC CLOUD DETECTION FROM MULTI-TEMPORAL SATELLITE IMAGES: TOWARDS THE USE OF PLÉIADES TIME SERIES

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N. Champion

2012-08-01

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

Assessment of Global Cloud Datasets from Satellites: Project and Database Initiated by the GEWEX Radiation Panel

Science.gov (United States)

Stubenrauch, C. J.; Rossow, W. B.; Kinne, S.; Ackerman, S.; Cesana, G.; Chepfer, H.; Getzewich, B.; Di Girolamo, L.; Guignard, A.; Heidinger, A.;

The Impact of Time Difference between Satellite Overpass and Ground Observation on Cloud Cover Performance Statistics

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Jędrzej S. Bojanowski

2014-12-01

Full Text Available Cloud property data sets derived from passive sensors onboard the polar orbiting satellites (such as the NOAA’s Advanced Very High Resolution Radiometer have global coverage and now span a climatological time period. Synoptic surface observations (SYNOP are often used to characterize the accuracy of satellite-based cloud cover. Infrequent overpasses of polar orbiting satellites combined with the 3- or 6-h SYNOP frequency lead to collocation time differences of up to 3 h. The associated collocation error degrades the cloud cover performance statistics such as the Hanssen-Kuiper’s discriminant (HK by up to 45%. Limiting the time difference to 10 min, on the other hand, introduces a sampling error due to a lower number of corresponding satellite and SYNOP observations. This error depends on both the length of the validated time series and the SYNOP frequency. The trade-off between collocation and sampling error call for an optimum collocation time difference. It however depends on cloud cover characteristics and SYNOP frequency, and cannot be generalized. Instead, a method is presented to reconstruct the unbiased (true HK from HK affected by the collocation differences, which significantly (t-test p < 0.01 improves the validation results.

The International Satellite Cloud Climatology Project H-Series climate data record product

Science.gov (United States)

Young, Alisa H.; Knapp, Kenneth R.; Inamdar, Anand; Hankins, William; Rossow, William B.

2018-03-01

This paper describes the new global long-term International Satellite Cloud Climatology Project (ISCCP) H-series climate data record (CDR). The H-series data contain a suite of level 2 and 3 products for monitoring the distribution and variation of cloud and surface properties to better understand the effects of clouds on climate, the radiation budget, and the global hydrologic cycle. This product is currently available for public use and is derived from both geostationary and polar-orbiting satellite imaging radiometers with common visible and infrared (IR) channels. The H-series data currently span July 1983 to December 2009 with plans for continued production to extend the record to the present with regular updates. The H-series data are the longest combined geostationary and polar orbiter satellite-based CDR of cloud properties. Access to the data is provided in network common data form (netCDF) and archived by NOAA's National Centers for Environmental Information (NCEI) under the satellite Climate Data Record Program (https://doi.org/10.7289/V5QZ281S" target="_blank">https://doi.org/10.7289/V5QZ281S). The basic characteristics, history, and evolution of the dataset are presented herein with particular emphasis on and discussion of product changes between the H-series and the widely used predecessor D-series product which also spans from July 1983 through December 2009. Key refinements included in the ISCCP H-series CDR are based on improved quality control measures, modified ancillary inputs, higher spatial resolution input and output products, calibration refinements, and updated documentation and metadata to bring the H-series product into compliance with existing standards for climate data records.

A cloud-ozone data product from Aura OMI and MLS satellite measurements

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J. R. Ziemke

2017-11-01

Full Text Available Ozone within deep convective clouds is controlled by several factors involving photochemical reactions and transport. Gas-phase photochemical reactions and heterogeneous surface chemical reactions involving ice, water particles, and aerosols inside the clouds all contribute to the distribution and net production and loss of ozone. Ozone in clouds is also dependent on convective transport that carries low-troposphere/boundary-layer ozone and ozone precursors upward into the clouds. Characterizing ozone in thick clouds is an important step for quantifying relationships of ozone with tropospheric H2O, OH production, and cloud microphysics/transport properties. Although measuring ozone in deep convective clouds from either aircraft or balloon ozonesondes is largely impossible due to extreme meteorological conditions associated with these clouds, it is possible to estimate ozone in thick clouds using backscattered solar UV radiation measured by satellite instruments. Our study combines Aura Ozone Monitoring Instrument (OMI and Microwave Limb Sounder (MLS satellite measurements to generate a new research product of monthly-mean ozone concentrations in deep convective clouds between 30° S and 30° N for October 2004–April 2016. These measurements represent mean ozone concentration primarily in the upper levels of thick clouds and reveal key features of cloud ozone including: persistent low ozone concentrations in the tropical Pacific of  ∼ 10 ppbv or less; concentrations of up to 60 pphv or greater over landmass regions of South America, southern Africa, Australia, and India/east Asia; connections with tropical ENSO events; and intraseasonal/Madden–Julian oscillation variability. Analysis of OMI aerosol measurements suggests a cause and effect relation between boundary-layer pollution and elevated ozone inside thick clouds over landmass regions including southern Africa and India/east Asia.

Cloud retrievals from satellite data using optimal estimation: evaluation and application to ATSR

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C. A. Poulsen

2012-08-01

Full Text Available Clouds play an important role in balancing the Earth's radiation budget. Hence, it is vital that cloud climatologies are produced that quantify cloud macro and micro physical parameters and the associated uncertainty. In this paper, we present an algorithm ORAC (Oxford-RAL retrieval of Aerosol and Cloud which is based on fitting a physically consistent cloud model to satellite observations simultaneously from the visible to the mid-infrared, thereby ensuring that the resulting cloud properties provide both a good representation of the short-wave and long-wave radiative effects of the observed cloud. The advantages of the optimal estimation method are that it enables rigorous error propagation and the inclusion of all measurements and any a priori information and associated errors in a rigorous mathematical framework. The algorithm provides a measure of the consistency between retrieval representation of cloud and satellite radiances. The cloud parameters retrieved are the cloud top pressure, cloud optical depth, cloud effective radius, cloud fraction and cloud phase.

The algorithm can be applied to most visible/infrared satellite instruments. In this paper, we demonstrate the applicability to the Along-Track Scanning Radiometers ATSR-2 and AATSR. Examples of applying the algorithm to ATSR-2 flight data are presented and the sensitivity of the retrievals assessed, in particular the algorithm is evaluated for a number of simulated single-layer and multi-layer conditions. The algorithm was found to perform well for single-layer cloud except when the cloud was very thin; i.e., less than 1 optical depths. For the multi-layer cloud, the algorithm was robust except when the upper ice cloud layer is less than five optical depths. In these cases the retrieved cloud top pressure and cloud effective radius become a weighted average of the 2 layers. The sum of optical depth of multi-layer cloud is retrieved well until the cloud becomes thick

Near-Real Time Satellite-Retrieved Cloud and Surface Properties for Weather and Aviation Safety Applications

Science.gov (United States)

Minnis, P.; Smith, W., Jr.; Bedka, K. M.; Nguyen, L.; Palikonda, R.; Hong, G.; Trepte, Q.; Chee, T.; Scarino, B. R.; Spangenberg, D.; Sun-Mack, S.; Fleeger, C.; Ayers, J. K.; Chang, F. L.; Heck, P. W.

2014-12-01

Cloud properties determined from satellite imager radiances provide a valuable source of information for nowcasting and weather forecasting. In recent years, it has been shown that assimilation of cloud top temperature, optical depth, and total water path can increase the accuracies of weather analyses and forecasts. Aircraft icing conditions can be accurately diagnosed in near-real time (NRT) retrievals of cloud effective particle size, phase, and water path, providing valuable data for pilots. NRT retrievals of surface skin temperature can also be assimilated in numerical weather prediction models to provide more accurate representations of solar heating and longwave cooling at the surface, where convective initiation. These and other applications are being exploited more frequently as the value of NRT cloud data become recognized. At NASA Langley, cloud properties and surface skin temperature are being retrieved in near-real time globally from both geostationary (GEO) and low-earth orbiting (LEO) satellite imagers for weather model assimilation and nowcasting for hazards such as aircraft icing. Cloud data from GEO satellites over North America are disseminated through NCEP, while those data and global LEO and GEO retrievals are disseminated from a Langley website. This paper presents an overview of the various available datasets, provides examples of their application, and discusses the use of the various datasets downstream. Future challenges and areas of improvement are also presented.

Near-Real Time Satellite-Retrieved Cloud and Surface Properties for Weather and Aviation Safety Applications

Science.gov (United States)

Minnis, Patrick; Smith, William L., Jr.; Bedka, Kristopher M.; Nguyen, Louis; Palikonda, Rabindra; Hong, Gang; Trepte, Qing Z.; Chee, Thad; Scarino, Benjamin; Spangenberg, Douglas A.;

Automatic Mosaicking of Satellite Imagery Considering the Clouds

Science.gov (United States)

Kang, Yifei; Pan, Li; Chen, Qi; Zhang, Tong; Zhang, Shasha; Liu, Zhang

2016-06-01

With the rapid development of high resolution remote sensing for earth observation technology, satellite imagery is widely used in the fields of resource investigation, environment protection, and agricultural research. Image mosaicking is an important part of satellite imagery production. However, the existence of clouds leads to lots of disadvantages for automatic image mosaicking, mainly in two aspects: 1) Image blurring may be caused during the process of image dodging, 2) Cloudy areas may be passed through by automatically generated seamlines. To address these problems, an automatic mosaicking method is proposed for cloudy satellite imagery in this paper. Firstly, modified Otsu thresholding and morphological processing are employed to extract cloudy areas and obtain the percentage of cloud cover. Then, cloud detection results are used to optimize the process of dodging and mosaicking. Thus, the mosaic image can be combined with more clear-sky areas instead of cloudy areas. Besides, clear-sky areas will be clear and distortionless. The Chinese GF-1 wide-field-of-view orthoimages are employed as experimental data. The performance of the proposed approach is evaluated in four aspects: the effect of cloud detection, the sharpness of clear-sky areas, the rationality of seamlines and efficiency. The evaluation results demonstrated that the mosaic image obtained by our method has fewer clouds, better internal color consistency and better visual clarity compared with that obtained by traditional method. The time consumed by the proposed method for 17 scenes of GF-1 orthoimages is within 4 hours on a desktop computer. The efficiency can meet the general production requirements for massive satellite imagery.

Alpine cloud climatology using long-term NOAA-AVHRR satellite data

Energy Technology Data Exchange (ETDEWEB)

Kaestner, M.; Kriebel, K.T.

2000-07-01

Three different climates have been identified by our evaluation of AVHRR (advanced very high resolution radiometer) data using APOLLO (AVHRR processing scheme over land, clouds and ocean) for a five-years cloud climatology of the Alpine region. The cloud cover data from four layers were spatially averaged in boxes of 15 km by 14 km. The study area only comprises 540 km by 560 km, but contains regions with moderate, Alpine and Mediterranean climate. Data from the period July 1989 until December 1996 have been considered. The temporal resolution is one scene per day, the early afternoon pass, yielding monthly means of satellite derived cloud coverages 5% to 10% above the daily mean compared to conventional surface observation. At nonvegetated sites the cloudiness is sometimes significantly overestimated. Averaging high resolution cloud data seems to be superior to low resolution measurements of cloud properties and averaging is favourable in topographical homogeneous regions only. The annual course of cloud cover reveals typical regional features as foehn or temporal singularities as the so-called Christmas thaw. The cloud cover maps in spatially high resolution show local luff/lee features which outline the orography. Less cloud cover is found over the Alps than over the forelands in winter, an accumulation of thick cirrus is found over the High Alps and an accumulation of thin cirrus north of the Alps. (orig.)

A Multi-Year Data Set of Cloud Properties Derived for CERES from Aqua, Terra, and TRMM

Science.gov (United States)

Minnis, Patrick; Sunny Sun-Mack; Trepte, Quinz Z.; Yan Chen; Brown, Richard R.; Gibson, Sharon C.; Heck, Michael L.; Dong, Xiquan; Xi, Baike

2007-01-01

The Clouds and Earth's Radiant Energy System (CERES) Project is producing a suite of cloud properties from high-resolution imagers on several satellites and matching them precisely with broadband radiance data to study the influence of clouds and radiation on climate. The cloud properties generally compare well with independent validation sources. Distinct differences are found between the CERES cloud properties and those derived with other algorithms from the same imager data. CERES products will be updated beginning in late 2006.

Satellite-based trends of solar radiation and cloud parameters in Europe

Science.gov (United States)

Pfeifroth, Uwe; Bojanowski, Jedrzej S.; Clerbaux, Nicolas; Manara, Veronica; Sanchez-Lorenzo, Arturo; Trentmann, Jörg; Walawender, Jakub P.; Hollmann, Rainer

2018-04-01

Solar radiation is the main driver of the Earth's climate. Measuring solar radiation and analysing its interaction with clouds are essential for the understanding of the climate system. The EUMETSAT Satellite Application Facility on Climate Monitoring (CM SAF) generates satellite-based, high-quality climate data records, with a focus on the energy balance and water cycle. Here, multiple of these data records are analyzed in a common framework to assess the consistency in trends and spatio-temporal variability of surface solar radiation, top-of-atmosphere reflected solar radiation and cloud fraction. This multi-parameter analysis focuses on Europe and covers the time period from 1992 to 2015. A high correlation between these three variables has been found over Europe. An overall consistency of the climate data records reveals an increase of surface solar radiation and a decrease in top-of-atmosphere reflected radiation. In addition, those trends are confirmed by negative trends in cloud cover. This consistency documents the high quality and stability of the CM SAF climate data records, which are mostly derived independently from each other. The results of this study indicate that one of the main reasons for the positive trend in surface solar radiation since the 1990's is a decrease in cloud coverage even if an aerosol contribution cannot be completely ruled out.

Unveiling aerosol-cloud interactions - Part 1: Cloud contamination in satellite products enhances the aerosol indirect forcing estimate

Science.gov (United States)

Christensen, Matthew W.; Neubauer, David; Poulsen, Caroline A.; Thomas, Gareth E.; McGarragh, Gregory R.; Povey, Adam C.; Proud, Simon R.; Grainger, Roy G.

2017-11-01

Increased concentrations of aerosol can enhance the albedo of warm low-level cloud. Accurately quantifying this relationship from space is challenging due in part to contamination of aerosol statistics near clouds. Aerosol retrievals near clouds can be influenced by stray cloud particles in areas assumed to be cloud-free, particle swelling by humidification, shadows and enhanced scattering into the aerosol field from (3-D radiative transfer) clouds. To screen for this contamination we have developed a new cloud-aerosol pairing algorithm (CAPA) to link cloud observations to the nearest aerosol retrieval within the satellite image. The distance between each aerosol retrieval and nearest cloud is also computed in CAPA. Results from two independent satellite imagers, the Advanced Along-Track Scanning Radiometer (AATSR) and Moderate Resolution Imaging Spectroradiometer (MODIS), show a marked reduction in the strength of the intrinsic aerosol indirect radiative forcing when selecting aerosol pairs that are located farther away from the clouds (-0.28±0.26 W m-2) compared to those including pairs that are within 15 km of the nearest cloud (-0.49±0.18 W m-2). The larger aerosol optical depths in closer proximity to cloud artificially enhance the relationship between aerosol-loading, cloud albedo, and cloud fraction. These results suggest that previous satellite-based radiative forcing estimates represented in key climate reports may be exaggerated due to the inclusion of retrieval artefacts in the aerosol located near clouds.

Study of cloud properties using airborne and satellite measurements

Science.gov (United States)

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

2014-08-01

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

Estimating the top altitude of optically thick ice clouds from thermal infrared satellite observations using CALIPSO data

Science.gov (United States)

Minnis, Patrick; Yost, Chris R.; Sun-Mack, Sunny; Chen, Yan

2008-06-01

The difference between cloud-top altitude Z top and infrared effective radiating height Z eff for optically thick ice clouds is examined using April 2007 data taken by the Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) and the Moderate-Resolution Imaging Spectroradiometer (MODIS). For even days, the difference ΔZ between CALIPSO Z top and MODIS Z eff is 1.58 +/- 1.26 km. The linear fit between Z top and Z eff , applied to odd-day data, yields a difference of 0.03 +/- 1.21 km and can be used to estimate Z top from any infrared-based Z eff for thick ice clouds. Random errors appear to be due primarily to variations in cloud ice-water content (IWC). Radiative transfer calculations show that ΔZ corresponds to an optical depth of ~1, which based on observed ice-particle sizes yields an average cloud-top IWC of ~0.015 gm-3, a value consistent with in situ measurements. The analysis indicates potential for deriving cloud-top IWC using dual-satellite data.

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

Science.gov (United States)

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%.

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

Science.gov (United States)

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

1996-12-01

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

Cirrus cloud-temperature interactions over a tropical station, Gadanki from lidar and satellite observations

International Nuclear Information System (INIS)

S, Motty G; Satyanarayana, M.; Krishnakumar, V.; Dhaman, Reji k.

2014-01-01

The cirrus clouds play an important role in the radiation budget of the earth's atmospheric system and are important to characterize their vertical structure and optical properties. LIDAR measurements are obtained from the tropical station Gadanki (13.5 0 N, 79.2 0 E), India, and meteorological indicators derived from Radiosonde data. Most of the cirrus clouds are observed near to the tropopause, which substantiates the strength of the tropical convective processes. The height and temperature dependencies of cloud height, optical depth, and depolarization ratio were investigated. Cirrus observations made using CALIPSO satellite are compared with lidar data for systematic statistical study of cirrus climatology

The Application of the Technology of 3D Satellite Cloud Imaging in Virtual Reality Simulation

Directory of Open Access Journals (Sweden)

Xiao-fang Xie

2007-05-01

Full Text Available Using satellite cloud images to simulate clouds is one of the new visual simulation technologies in Virtual Reality (VR. Taking the original data of satellite cloud images as the source, this paper depicts specifically the technology of 3D satellite cloud imaging through the transforming of coordinates and projection, creating a DEM (Digital Elevation Model of cloud imaging and 3D simulation. A Mercator projection was introduced to create a cloud image DEM, while solutions for geodetic problems were introduced to calculate distances, and the outer-trajectory science of rockets was introduced to obtain the elevation of clouds. For demonstration, we report on a computer program to simulate the 3D satellite cloud images.

Evaluation of the MiKlip decadal prediction system using satellite based cloud products

Directory of Open Access Journals (Sweden)

Thomas Spangehl

2016-12-01

Full Text Available The decadal hindcast simulations performed for the Mittelfristige Klimaprognosen (MiKlip project are evaluated using satellite-retrieved cloud parameters from the CM SAF cLoud, Albedo and RAdiation dataset from AVHRR data (CLARA-A1 provided by the EUMETSAT Satellite Application Facility on Climate Monitoring (CM SAF and from the International Satellite Cloud Climatology Project (ISCCP. The forecast quality of two sets of hindcasts, Baseline-1-LR and Baseline-0, which use differing initialisations, is assessed. Basic evaluation focuses on multi-year ensemble mean fields and cloud-type histograms utilizing satellite simulator output. Additionally, ensemble evaluation employing analysis of variance (ANOVA, analysis rank histograms (ARH and a deterministic correlation score is performed. Satellite simulator output is available for a subset of the full hindcast ensembles only. Therefore, the raw model cloud cover is complementary used. The new Baseline-1-LR hindcasts are closer to satellite data with respect to the simulated tropical/subtropical mean cloud cover pattern than the reference hindcasts (Baseline-0 emphasizing improvements of the new MiKlip initialisation procedure. A slightly overestimated occurrence rate of optically thick cloud-types is analysed for different experiments including hindcasts and simulations using realistic sea surface boundaries according to the Atmospheric Model Intercomparison Project (AMIP. By contrast, the evaluation of cirrus and cirrostratus clouds is complicated by observational based uncertainties. Time series of the 3-year mean total cloud cover averaged over the tropical warm pool (TWP region show some correlation with the CLARA-A1 cloud fractional cover. Moreover, ensemble evaluation of the Baseline-1-LR hindcasts reveals potential predictability of the 2–5 lead year averaged total cloud cover for a large part of this region when regarding the full observational period. However, the hindcasts show only

Top-down and bottom-up aerosol-cloud closure: towards understanding sources of uncertainty in deriving cloud shortwave radiative flux

Science.gov (United States)

Sanchez, Kevin J.; Roberts, Gregory C.; Calmer, Radiance; Nicoll, Keri; Hashimshoni, Eyal; Rosenfeld, Daniel; Ovadnevaite, Jurgita; Preissler, Jana; Ceburnis, Darius; O'Dowd, Colin; Russell, Lynn M.

2017-08-01

Top-down and bottom-up aerosol-cloud shortwave radiative flux closures were conducted at the Mace Head Atmospheric Research Station in Galway, Ireland, in August 2015. This study is part of the BACCHUS (Impact of Biogenic versus Anthropogenic emissions on Clouds and Climate: towards a Holistic UnderStanding) European collaborative project, with the goal of understanding key processes affecting aerosol-cloud shortwave radiative flux closures to improve future climate predictions and develop sustainable policies for Europe. Instrument platforms include ground-based unmanned aerial vehicles (UAVs)1 and satellite measurements of aerosols, clouds and meteorological variables. The ground-based and airborne measurements of aerosol size distributions and cloud condensation nuclei (CCN) concentration were used to initiate a 1-D microphysical aerosol-cloud parcel model (ACPM). UAVs were equipped for a specific science mission, with an optical particle counter for aerosol distribution profiles, a cloud sensor to measure cloud extinction or a five-hole probe for 3-D wind vectors. UAV cloud measurements are rare and have only become possible in recent years through the miniaturization of instrumentation. These are the first UAV measurements at Mace Head. ACPM simulations are compared to in situ cloud extinction measurements from UAVs to quantify closure in terms of cloud shortwave radiative flux. Two out of seven cases exhibit sub-adiabatic vertical temperature profiles within the cloud, which suggests that entrainment processes affect cloud microphysical properties and lead to an overestimate of simulated cloud shortwave radiative flux. Including an entrainment parameterization and explicitly calculating the entrainment fraction in the ACPM simulations both improved cloud-top radiative closure. Entrainment reduced the difference between simulated and observation-derived cloud-top shortwave radiative flux (δRF) by between 25 and 60 W m-2. After accounting for entrainment

Optimizing cloud removal from satellite remotely sensed data for monitoring vegetation dynamics in humid tropical climate

International Nuclear Information System (INIS)

Hashim, M; Pour, A B; Onn, C H

2014-01-01

Remote sensing technology is an important tool to analyze vegetation dynamics, quantifying vegetation fraction of Earth's agricultural and natural vegetation. In optical remote sensing analysis removing atmospheric interferences, particularly distribution of cloud contaminations, are always a critical task in the tropical climate. This paper suggests a fast and alternative approach to remove cloud and shadow contaminations for Landsat Enhanced Thematic Mapper + (ETM + ) multi temporal datasets. Band 3 and Band 4 from all the Landsat ETM + dataset are two main spectral bands that are very crucial in this study for cloud removal technique. The Normalise difference vegetation index (NDVI) and the normalised difference soil index (NDSI) are two main derivatives derived from the datasets. Change vector analysis is used in this study to seek the vegetation dynamics. The approach developed in this study for cloud optimizing can be broadly applicable for optical remote sensing satellite data, which are seriously obscured with heavy cloud contamination in the tropical climate

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

Science.gov (United States)

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.

Using satellites and global models to investigate aerosol-cloud interactions

Science.gov (United States)

Gryspeerdt, E.; Quaas, J.; Goren, T.; Sourdeval, O.; Mülmenstädt, J.

2017-12-01

Aerosols are known to impact liquid cloud properties, through both microphysical and radiative processes. Increasing the number concentration of aerosol particles can increase the cloud droplet number concentration (CDNC). Through impacts on precipitation processes, this increase in CDNC may also be able to impact the cloud fraction (CF) and the cloud liquid water path (LWP). Several studies have looked into the effect of aerosols on the CDNC, but as the albedo of a cloudy scene depends much more strongly on LWP and CF, an aerosol influence on these properties could generate a significant radiative forcing. While the impact of aerosols on cloud properties can be seen in case studies involving shiptracks and volcanoes, producing a global estimate of these effects remains challenging due to the confounding effect of local meteorology. For example, relative humidity significantly impacts the aerosol optical depth (AOD), a common satellite proxy for CCN, as well as being a strong control on cloud properties. This can generate relationships between AOD and cloud properties, even when there is no impact of aerosol-cloud interactions. In this work, we look at how aerosol-cloud interactions can be distinguished from the effect of local meteorology in satellite studies. With a combination global climate models and multiple sources of satellite data, we show that the choice of appropriate mediating variables and case studies can be used to develop constraints on the aerosol impact on CF and LWP. This will lead to improved representations of clouds in global climate models and help to reduce the uncertainty in the global impact of anthropogenic aerosols on cloud properties.

Validation of quasi-invariant ice cloud radiative quantities with MODIS satellite-based cloud property retrievals

International Nuclear Information System (INIS)

Ding, Jiachen; Yang, Ping; Kattawar, George W.; King, Michael D.; Platnick, Steven; Meyer, Kerry G.

2017-01-01

Similarity relations applied to ice cloud radiance calculations are theoretically analyzed and numerically validated. If τ(1–ϖ) and τ(1–ϖg) are conserved where τ is optical thickness, ϖ the single-scattering albedo, and g the asymmetry factor, it is possible that substantially different phase functions may give rise to similar radiances in both conservative and non-conservative scattering cases, particularly in the case of large optical thicknesses. In addition to theoretical analysis, this study uses operational ice cloud optical thickness retrievals from the Moderate Resolution Imaging Spectroradiometer (MODIS) Level 2 Collection 5 (C5) and Collection 6 (C6) cloud property products to verify radiative similarity relations. It is found that, if the MODIS C5 and C6 ice cloud optical thickness values are multiplied by their respective (1–ϖg) factors, the resultant products referred to as the effective optical thicknesses become similar with their ratio values around unity. Furthermore, the ratios of the C5 and C6 ice cloud effective optical thicknesses display an angular variation pattern similar to that of the corresponding ice cloud phase function ratios. The MODIS C5 and C6 values of ice cloud similarity parameter, defined as [(1–ϖ)/(1–ϖg)]"1"/"2, also tend to be similar. - Highlights: • Similarity relations are theoretically analyzed and validated. • Similarity relations are verified with the MODIS Level 2 Collection 5 and 6 ice cloud property products. • The product of ice cloud optical thickness and (1–ϖg) is approximately invariant. • The similarity parameter derived from the MODIS ice cloud effective radius retrieval tends to be invariant.

Distribution and Variability of Satellite-Derived Signals of Isolated Convection Initiation Events Over Central Eastern China

Science.gov (United States)

Huang, Yipeng; Meng, Zhiyong; Li, Jing; Li, Wanbiao; Bai, Lanqiang; Zhang, Murong; Wang, Xi

2017-11-01

This study combined measurements from the Chinese operational geostationary satellite Fengyun-2E (FY-2E) and ground-based weather radars to conduct a statistical survey of isolated convection initiation (CI) over central eastern China (CEC). The convective environment in CEC is modulated by the complex topography and monsoon climate. From May to August 2010, a total of 1,630 isolated CI signals were derived from FY-2E using a semiautomated method. The formation of these satellite-derived CI signals peaks in the early afternoon and occurs with high frequency in areas with remarkable terrain inhomogeneity (e.g., mountain, water, and mountain-water areas). The high signal frequency areas shift from northwest CEC (dry, high altitude) in early summer to southeast CEC (humid, low altitude) in midsummer along with an increasing monthly mean frequency. The satellite-derived CI signals tend to have longer lead times (the time difference between satellite-derived signal formation and radar-based CI) in the late morning and afternoon than in the early morning and night. During the early morning and night, the distinction between cloud top signatures and background terrestrial radiation becomes less apparent, resulting in delayed identification of the signals and thus short and even negative lead times. A decline in the lead time is observed from May to August, likely due to the increasing cloud growth rate and warm-rain processes. Results show increasing lead times with increasing landscape elevation, likely due to more warm-rain processes over the coastal sea and plain, along with a decreasing cloud growth rate from hill and mountain to the plateau.

Sensitivity of Cirrus and Mixed-phase Clouds to the Ice Nuclei Spectra in McRAS-AC: Single Column Model Simulations

Science.gov (United States)

Betancourt, R. Morales; Lee, D.; Oreopoulos, L.; Sud, Y. C.; Barahona, D.; Nenes, A.

2012-01-01

The salient features of mixed-phase and ice clouds in a GCM cloud scheme are examined using the ice formation parameterizations of Liu and Penner (LP) and Barahona and Nenes (BN). The performance of LP and BN ice nucleation parameterizations were assessed in the GEOS-5 AGCM using the McRAS-AC cloud microphysics framework in single column mode. Four dimensional assimilated data from the intensive observation period of ARM TWP-ICE campaign was used to drive the fluxes and lateral forcing. Simulation experiments where established to test the impact of each parameterization in the resulting cloud fields. Three commonly used IN spectra were utilized in the BN parameterization to described the availability of IN for heterogeneous ice nucleation. The results show large similarities in the cirrus cloud regime between all the schemes tested, in which ice crystal concentrations were within a factor of 10 regardless of the parameterization used. In mixed-phase clouds there are some persistent differences in cloud particle number concentration and size, as well as in cloud fraction, ice water mixing ratio, and ice water path. Contact freezing in the simulated mixed-phase clouds contributed to transfer liquid to ice efficiently, so that on average, the clouds were fully glaciated at T approximately 260K, irrespective of the ice nucleation parameterization used. Comparison of simulated ice water path to available satellite derived observations were also performed, finding that all the schemes tested with the BN parameterization predicted 20 average values of IWP within plus or minus 15% of the observations.

Thermal structure of intense convective clouds derived from GPS radio occultations

DEFF Research Database (Denmark)

Biondi, Riccardo; Randel, W. J.; Ho, S. -P.

2012-01-01

Thermal structure associated with deep convective clouds is investigated using Global Positioning System (GPS) radio occultation measurements. GPS data are insensitive to the presence of clouds, and provide high vertical resolution and high accuracy measurements to identify associated temperature...... behavior. Deep convective systems are identified using International Satellite Cloud Climatology Project (ISCCP) satellite data, and cloud tops are accurately measured using Cloud-Aerosol Lidar with Orthogonal Polarization (CALIPSO) lidar observations; we focus on 53 cases of near-coincident GPS...

Thermal structure of intense convective clouds derived from GPS radio occultations

DEFF Research Database (Denmark)

Biondi, Riccardo; Randel, W. J.; Ho, S.-P.

2011-01-01

Thermal structure associated with deep convective clouds is investigated using Global Positioning System (GPS) radio occultation measurements. GPS data are insensitive to the presence of clouds, and provide high vertical resolution and high accuracy measurements to identify associated temperature...... behavior. Deep convective systems are identified using International Satellite Cloud Climatology Project (ISCCP) satellite data, and cloud tops are accurately measured using Cloud-Aerosol Lidar with Orthogonal Polarization (CALIPSO) lidar observations; we focus on 53 cases of near-coincident GPS...

Top-down and bottom-up aerosol–cloud closure: towards understanding sources of uncertainty in deriving cloud shortwave radiative flux

Directory of Open Access Journals (Sweden)

K. J. Sanchez

2017-08-01

Full Text Available Top-down and bottom-up aerosol–cloud shortwave radiative flux closures were conducted at the Mace Head Atmospheric Research Station in Galway, Ireland, in August 2015. This study is part of the BACCHUS (Impact of Biogenic versus Anthropogenic emissions on Clouds and Climate: towards a Holistic UnderStanding European collaborative project, with the goal of understanding key processes affecting aerosol–cloud shortwave radiative flux closures to improve future climate predictions and develop sustainable policies for Europe. Instrument platforms include ground-based unmanned aerial vehicles (UAVs1 and satellite measurements of aerosols, clouds and meteorological variables. The ground-based and airborne measurements of aerosol size distributions and cloud condensation nuclei (CCN concentration were used to initiate a 1-D microphysical aerosol–cloud parcel model (ACPM. UAVs were equipped for a specific science mission, with an optical particle counter for aerosol distribution profiles, a cloud sensor to measure cloud extinction or a five-hole probe for 3-D wind vectors. UAV cloud measurements are rare and have only become possible in recent years through the miniaturization of instrumentation. These are the first UAV measurements at Mace Head. ACPM simulations are compared to in situ cloud extinction measurements from UAVs to quantify closure in terms of cloud shortwave radiative flux. Two out of seven cases exhibit sub-adiabatic vertical temperature profiles within the cloud, which suggests that entrainment processes affect cloud microphysical properties and lead to an overestimate of simulated cloud shortwave radiative flux. Including an entrainment parameterization and explicitly calculating the entrainment fraction in the ACPM simulations both improved cloud-top radiative closure. Entrainment reduced the difference between simulated and observation-derived cloud-top shortwave radiative flux (δRF by between 25 and 60 W m−2. After

Assessment of global cloud datasets from satellites: Project and database initiated by the GEWEX radiation panel

OpenAIRE

Stubenrauch , C.J.; Rossow , W.B.; Kinne , S.; Ackerman , S.; Cesana , G.; Chepfer , H.; Di Girolamo , L.; Getzewich , B.; Guignard , A.; Heidinger , A.; Maddux , B.C.; Menzel , W.P.; Minnis , P.; Pearl , C.; Platnick , S.

2013-01-01

International audience; The Global Energy and Water Cycle Experiment (GEWEX) Radiation Panel initiated the GEWEX Cloud Assessment in 2005 to compare available, global, long-term cloud data products with the International Satellite Cloud Climatology Project (ISCCP). The GEWEX Cloud Assessment database included cloud properties retrieved from different satellite sensor measurements, taken at various local times and over various time periods. The relevant passive satellite sensors measured radia...

Evaluation of the Precision of Satellite-Derived Sea Surface Temperature Fields

Science.gov (United States)

Wu, F.; Cornillon, P. C.; Guan, L.

2016-02-01

A great deal of attention has been focused on the temporal accuracy of satellite-derived sea surface temperature (SST) fields with little attention being given to their spatial precision. Specifically, the primary measure of the quality of SST fields has been the bias and variance of selected values minus co-located (in space and time) in situ values. Contributing values, determined by the location of the in situ values and the necessity that the satellite-derived values be cloud free, are generally widely separated in space and time hence provide little information related to the pixel-to-pixel uncertainty in the retrievals. But the main contribution to the uncertainty in satellite-derived SST retrievals relates to atmospheric contamination and because the spatial scales of atmospheric features are, in general, large compared with the pixel separation of modern infra-red sensors, the pixel-to-pixel uncertainty is often smaller than the accuracy determined from in situ match-ups. This makes selection of satellite-derived datasets for the study of submesoscale processes, for which the spatial structure of the upper ocean is significant, problematic. In this presentation we present a methodology to characterize the spatial precision of satellite-derived SST fields. The method is based on an examination of the high wavenumber tail of the 2-D spectrum of SST fields in the Sargasso Sea, a low energy region of the ocean close to the track of the MV Oleander, a container ship making weekly roundtrips between New York and Bermuda, with engine intake temperatures sampled every 75 m along track. Important spectral characteristics are the point at which the satellite-derived spectra separate from the Oleander spectra and the spectral slope following separation. In this presentation a number of high resolution 375 m to 10 km SST datasets are evaluated based on this approach.

Correcting orbital drift signal in the time series of AVHRR derived convective cloud fraction using rotated empirical orthogonal function

Directory of Open Access Journals (Sweden)

A. Devasthale

2012-02-01

Full Text Available The Advanced Very High Resolution Radiometer (AVHRR instruments onboard the series of National Oceanic and Atmospheric Administration (NOAA satellites offer the longest available meteorological data records from space. These satellites have drifted in orbit resulting in shifts in the local time sampling during the life span of the sensors onboard. Depending upon the amplitude of the diurnal cycle of the geophysical parameters derived, orbital drift may cause spurious trends in their time series. We investigate tropical deep convective clouds, which show pronounced diurnal cycle amplitude, to estimate an upper bound of the impact of orbital drift on their time series. We carry out a rotated empirical orthogonal function analysis (REOF and show that the REOFs are useful in delineating orbital drift signal and, more importantly, in subtracting this signal in the time series of convective cloud amount. These results will help facilitate the derivation of homogenized data series of cloud amount from NOAA satellite sensors and ultimately analyzing trends from them. However, we suggest detailed comparison of various methods and rigorous testing thereof applying final orbital drift corrections.

Satellite remote sensing of aerosol and cloud properties over Eurasia

Science.gov (United States)

Sogacheva, Larisa; Kolmonen, Pekka; Saponaro, Giulia; Virtanen, Timo; Rodriguez, Edith; Sundström, Anu-Maija; Atlaskina, Ksenia; de Leeuw, Gerrit

2015-04-01

Satellite remote sensing provides the spatial distribution of aerosol and cloud properties over a wide area. In our studies large data sets are used for statistical studies on aerosol and cloud interaction in an area over Fennoscandia, the Baltic Sea and adjacent regions over the European mainland. This area spans several regimes with different influences on aerosol cloud interaction such as a the transition from relative clean air over Fennoscandia to more anthropogenically polluted air further south, and the influence maritime air over the Baltic and oceanic air advected from the North Atlantic. Anthropogenic pollution occurs in several parts of the study area, and in particular near densely populated areas and megacities, but also in industrialized areas and areas with dense traffic. The aerosol in such areas is quite different from that produced over the boreal forest and has different effects on air quality and climate. Studies have been made on the effects of aerosols on air quality and on the radiation balance in China. The aim of the study is to study the effect of these different regimes on aerosol-cloud interaction using a large aerosol and cloud data set retrieved with the (Advanced) Along Track Scanning Radiometer (A)ATSR Dual View algorithm (ADV) further developed at Finnish Meteorological Institute and aerosol and cloud data provided by MODIS. Retrieval algorithms for aerosol and clouds have been developed for the (A)ATSR, consisting of a series of instruments of which we use the second and third one: ATSR-2 which flew on the ERS-2 satellite (1995-2003) and AATSR which flew on the ENVISAT satellite (2002-2012) (both from the European Space Agency, ESA). The ADV algorithm provides aerosol data on a global scale with a default resolution of 10x10km2 (L2) and an aggregate product on 1x1 degree (L3). Optional, a 1x1 km2 retrieval products is available over smaller areas for specific studies. Since for the retrieval of AOD no prior knowledge is needed on

Retrieval of Cloud Properties for Partially Cloud-Filled Pixels During CRYSTAL-FACE

Science.gov (United States)

Nguyen, L.; Minnis, P.; Smith, W. L.; Khaiyer, M. M.; Heck, P. W.; Sun-Mack, S.; Uttal, T.; Comstock, J.

2003-12-01

Partially cloud-filled pixels can be a significant problem for remote sensing of cloud properties. Generally, the optical depth and effective particle sizes are often too small or too large, respectively, when derived from radiances that are assumed to be overcast but contain radiation from both clear and cloud areas within the satellite imager field of view. This study presents a method for reducing the impact of such partially cloud field pixels by estimating the cloud fraction within each pixel using higher resolution visible (VIS, 0.65mm) imager data. Although the nominal resolution for most channels on the Geostationary Operational Environmental Satellite (GOES) imager and the Moderate Resolution Imaging Spectroradiometer (MODIS) on Terra are 4 and 1 km, respectively, both instruments also take VIS channel data at 1 km and 0.25 km, respectively. Thus, it may be possible to obtain an improved estimate of cloud fraction within the lower resolution pixels by using the information contained in the higher resolution VIS data. GOES and MODIS multi-spectral data, taken during the Cirrus Regional Study of Tropical Anvils and Cirrus Layers - Florida Area Cirrus Experiment (CRYSTAL-FACE), are analyzed with the algorithm used for the Atmospheric Radiation Measurement Program (ARM) and the Clouds and Earth's Radiant Energy System (CERES) to derive cloud amount, temperature, height, phase, effective particle size, optical depth, and water path. Normally, the algorithm assumes that each pixel is either entirely clear or cloudy. In this study, a threshold method is applied to the higher resolution VIS data to estimate the partial cloud fraction within each low-resolution pixel. The cloud properties are then derived from the observed low-resolution radiances using the cloud cover estimate to properly extract the radiances due only to the cloudy part of the scene. This approach is applied to both GOES and MODIS data to estimate the improvement in the retrievals for each

Comparison of global cloud liquid water path derived from microwave measurements with CERES-MODIS

Science.gov (United States)

Yi, Y.; Minnis, P.; Huang, J.; Lin, B.; Ayers, K.; Sun-Mack, S.; Fan, A.

Cloud liquid water path LWP is a crucial parameter for climate studies due to the link that it provides between the atmospheric hydrological and radiative budgets Satellite-based visible infrared techniques such as the Visible Infrared Solar Split-Window Technique VISST can retrieve LWP for water clouds assumes single-layer over a variety of surfaces If the water clouds are overlapped by ice clouds the LWP of the underlying clouds can not be retrieved by such techniques However microwave techniques may be used to retrieve the LWP underneath ice clouds due to the microwave s insensitivity to cloud ice particles LWP is typically retrieved from satellite-observed microwave radiances only over ocean due to variations of land surface temperature and emissivity Recently Deeter and Vivekanandan 2006 developed a new technique for retrieving LWP over land In order to overcome the sensitivity to land surface temperature and emissivity their technique is based on a parameterization of microwave polarization-difference signals In this study a similar regression-based technique for retrieving LWP over land and ocean using Advanced Microwave Scanning Radiometer - EOS AMSR-E measurements is developed Furthermore the microwave surface emissivities are also derived using clear-sky fields of view based on the Clouds and Earth s Radiant Energy System Moderate-resolution Imaging Spectroradiometer CERES-MODIS cloud mask These emissivities are used in an alternate form of the technique The results are evaluated using independent measurements such

Phase-partitioning in mixed-phase clouds - An approach to characterize the entire vertical column

Science.gov (United States)

Kalesse, H.; Luke, E. P.; Seifert, P.

2017-12-01

The characterization of the entire vertical profile of phase-partitioning in mixed-phase clouds is a challenge which can be addressed by synergistic profiling measurements with ground-based polarization lidars and cloud radars. While lidars are sensitive to small particles and can thus detect supercooled liquid (SCL) layers, cloud radar returns are dominated by larger particles (like ice crystals). The maximum lidar observation height is determined by complete signal attenuation at a penetrated optical depth of about three. In contrast, cloud radars are able to penetrate multiple liquid layers and can thus be used to expand the identification of cloud phase to the entire vertical column beyond the lidar extinction height, if morphological features in the radar Doppler spectrum can be related to the existence of SCL. Relevant spectral signatures such as bimodalities and spectral skewness can be related to cloud phase by training a neural network appropriately in a supervised learning scheme, with lidar measurements functioning as supervisor. The neural network output (prediction of SCL location) derived using cloud radar Doppler spectra can be evaluated with several parameters such as liquid water path (LWP) detected by microwave radiometer (MWR) and (liquid) cloud base detected by ceilometer or Raman lidar. The technique has been previously tested on data from Department of Energy (DOE) Atmospheric Radiation Measurement (ARM) instruments in Barrow, Alaska and is in this study utilized for observations from the Leipzig Aerosol and Cloud Remote Observations System (LACROS) during the Analysis of the Composition of Clouds with Extended Polarization Techniques (ACCEPT) field experiment in Cabauw, Netherlands in Fall 2014. Comparisons to supercooled-liquid layers as classified by CLOUDNET are provided.

Using Deep Learning Model for Meteorological Satellite Cloud Image Prediction

Science.gov (United States)

Su, X.

2017-12-01

A satellite cloud image contains much weather information such as precipitation information. Short-time cloud movement forecast is important for precipitation forecast and is the primary means for typhoon monitoring. The traditional methods are mostly using the cloud feature matching and linear extrapolation to predict the cloud movement, which makes that the nonstationary process such as inversion and deformation during the movement of the cloud is basically not considered. It is still a hard task to predict cloud movement timely and correctly. As deep learning model could perform well in learning spatiotemporal features, to meet this challenge, we could regard cloud image prediction as a spatiotemporal sequence forecasting problem and introduce deep learning model to solve this problem. In this research, we use a variant of Gated-Recurrent-Unit(GRU) that has convolutional structures to deal with spatiotemporal features and build an end-to-end model to solve this forecast problem. In this model, both the input and output are spatiotemporal sequences. Compared to Convolutional LSTM(ConvLSTM) model, this model has lower amount of parameters. We imply this model on GOES satellite data and the model perform well.

Moisture convergence using satellite-derived wind fields - A severe local storm case study

Science.gov (United States)

Negri, A. J.; Vonder Haar, T. H.

1980-01-01

Five-minute interval 1-km resolution SMS visible channel data were used to derive low-level wind fields by tracking small cumulus clouds on NASA's Atmospheric and Oceanographic Information Processing System. The satellite-derived wind fields were combined with surface mixing ratios to derive horizontal moisture convergence in the prestorm environment of April 24, 1975. Storms began developing in an area extending from southwest Oklahoma to eastern Tennessee 2 h subsequent to the time of the derived fields. The maximum moisture convergence was computed to be 0.0022 g/kg per sec and areas of low-level convergence of moisture were in general indicative of regions of severe storm genesis. The resultant moisture convergence fields derived from two wind sets 20 min apart were spatially consistent and reflected the mesoscale forcing of ensuing storm development. Results are discussed with regard to possible limitations in quantifying the relationship between low-level flow and between low-level flow and satellite-derived cumulus motion in an antecedent storm environment.

Ozone mixing ratios inside tropical deep convective clouds from OMI satellite measurements

Directory of Open Access Journals (Sweden)

J. R. Ziemke

2009-01-01

Full Text Available We have developed a new technique for estimating ozone mixing ratio inside deep convective clouds. The technique uses the concept of an optical centroid cloud pressure that is indicative of the photon path inside clouds. Radiative transfer calculations based on realistic cloud vertical structure as provided by CloudSat radar data show that because deep convective clouds are optically thin near the top, photons can penetrate significantly inside the cloud. This photon penetration coupled with in-cloud scattering produces optical centroid pressures that are hundreds of hPa inside the cloud. We combine measured column ozone and the optical centroid cloud pressure derived using the effects of rotational-Raman scattering to estimate O₃ mixing ratio in the upper regions of deep convective clouds. The data are obtained from the Ozone Monitoring Instrument (OMI onboard NASA's Aura satellite. Our results show that low O₃ concentrations in these clouds are a common occurrence throughout much of the tropical Pacific. Ozonesonde measurements in the tropics following convective activity also show very low concentrations of O₃ in the upper troposphere. These low amounts are attributed to vertical injection of ozone poor oceanic boundary layer air during convection into the upper troposphere followed by convective outflow. Over South America and Africa, O₃ mixing ratios inside deep convective clouds often exceed 50 ppbv which are comparable to mean background (cloud-free amounts and are consistent with higher concentrations of injected boundary layer/lower tropospheric O₃ relative to the remote Pacific. The Atlantic region in general also consists of higher amounts of O₃ precursors due to both biomass burning and lightning. Assuming that O₃ is well mixed (i.e., constant mixing ratio with height up to the tropopause, we can estimate the stratospheric column O₃ over

International Satellite Cloud Climatology Project (ISCCP) Climate Data Record, H-Series

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — The International Satellite Cloud Climatology Project (ISCCP) focuses on the distribution and variation of cloud radiative properties to improve the understanding of...

Galactic cosmic ray and El Nino Southern Oscillation trends in International Satellite Cloud Climatology Project D2 low-cloud properties

DEFF Research Database (Denmark)

Marsh, N.; Svensmark, Henrik

2003-01-01

[1] The recently reported correlation between clouds and galactic cosmic rays (GCR) implies the existence of a previously unknown process linking solar variability and climate. An analysis of the interannual variability of International Satellite Cloud Climatology Project D2 (ISCCP-D2) low-cloud...... a strong correlation with GCR, which suggests that low-cloud properties observed in these regions are less likely to be contaminated from overlying cloud. The GCR-low cloud correlation cannot easily be explained by internal climate processes, changes in direct solar forcing, or UV-ozone interactions...... properties over the period July 1983 to August 1994 suggests that low clouds are statistically related to two processes, (1) GCR and (2) El Nino-Southern Oscillation (ENSO), with GCR explaining a greater percentage of the total variance. Areas where satellites have an unobstructed view of low cloud possess...

Comparison of POLDER Cloud Phase Retrievals to Active Remote Sensors Measurements at the ARM SGP Site

International Nuclear Information System (INIS)

Riedi, J.; Goloub, P.; Marchand, Roger T.

2001-01-01

In our present study, cloud boundaries derived from a combination of active remote sensors at the ARM SGP site are compared to POLDER cloud top phase index which is derived from polarimetric measurements using an innovative method. This approach shows the viability of the POLDER phase retrieval algorithm, and also leads to interesting results. In particular, the analysis demonstrates the sensitivity of polarization measurements to ice crystal shape and indicates that occurrence of polycrystalline ice clouds has to be taken into account in order to improve the POLDER phase retrieval algorithm accuracy. Secondly, the results show that a temperature threshold of 240 K could serve for cloud top particle phase classification. Considering the limitations of the analysis, the temperature threshold could be biased high, but not by more than about 5 degrees

Intercomparison of model simulations of mixed-phase clouds observed during the ARM Mixed-Phase Arctic Cloud Experiment. Part II: Multi-layered cloud

Energy Technology Data Exchange (ETDEWEB)

Morrison, H; McCoy, R B; Klein, S A; Xie, S; Luo, Y; Avramov, A; Chen, M; Cole, J; Falk, M; Foster, M; Genio, A D; Harrington, J; Hoose, C; Khairoutdinov, M; Larson, V; Liu, X; McFarquhar, G; Poellot, M; Shipway, B; Shupe, M; Sud, Y; Turner, D; Veron, D; Walker, G; Wang, Z; Wolf, A; Xu, K; Yang, F; Zhang, G

2008-02-27

Results are presented from an intercomparison of single-column and cloud-resolving model simulations of a deep, multi-layered, mixed-phase cloud system observed during the ARM Mixed-Phase Arctic Cloud Experiment. This cloud system was associated with strong surface turbulent sensible and latent heat fluxes as cold air flowed over the open Arctic Ocean, combined with a low pressure system that supplied moisture at mid-level. The simulations, performed by 13 single-column and 4 cloud-resolving models, generally overestimate the liquid water path and strongly underestimate the ice water path, although there is a large spread among the models. This finding is in contrast with results for the single-layer, low-level mixed-phase stratocumulus case in Part I of this study, as well as previous studies of shallow mixed-phase Arctic clouds, that showed an underprediction of liquid water path. The overestimate of liquid water path and underestimate of ice water path occur primarily when deeper mixed-phase clouds extending into the mid-troposphere were observed. These results suggest important differences in the ability of models to simulate Arctic mixed-phase clouds that are deep and multi-layered versus shallow and single-layered. In general, models with a more sophisticated, two-moment treatment of the cloud microphysics produce a somewhat smaller liquid water path that is closer to observations. The cloud-resolving models tend to produce a larger cloud fraction than the single-column models. The liquid water path and especially the cloud fraction have a large impact on the cloud radiative forcing at the surface, which is dominated by the longwave flux for this case.

Sensitivities of simulated satellite views of clouds to subgrid-scale overlap and condensate heterogeneity

Energy Technology Data Exchange (ETDEWEB)

Hillman, Benjamin R. [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Marchand, Roger T. [Univ. of Washington, Seattle, WA (United States); Ackerman, Thomas P. [Univ. of Washington, Seattle, WA (United States)

2017-08-01

Satellite simulators are often used to account for limitations in satellite retrievals of cloud properties in comparisons between models and satellite observations. The purpose of the simulator framework is to enable more robust evaluation of model cloud properties, so that di erences between models and observations can more con dently be attributed to model errors. However, these simulators are subject to uncertainties themselves. A fundamental uncertainty exists in connecting the spatial scales at which cloud properties are retrieved with those at which clouds are simulated in global models. In this study, we create a series of sensitivity tests using 4 km global model output from the Multiscale Modeling Framework to evaluate the sensitivity of simulated satellite retrievals when applied to climate models whose grid spacing is many tens to hundreds of kilometers. In particular, we examine the impact of cloud and precipitation overlap and of condensate spatial variability. We find the simulated retrievals are sensitive to these assumptions. Specifically, using maximum-random overlap with homogeneous cloud and precipitation condensate, which is often used in global climate models, leads to large errors in MISR and ISCCP-simulated cloud cover and in CloudSat-simulated radar reflectivity. To correct for these errors, an improved treatment of unresolved clouds and precipitation is implemented for use with the simulator framework and is shown to substantially reduce the identified errors.

Application of phase coherent transform to cloud clutter suppression

Energy Technology Data Exchange (ETDEWEB)

Ng, L.C. [Lawrence Livermore National Lab., CA (United States)

1994-11-15

This paper describes a tracking algorithm using frame-to-frame correlation with frequency domain clutter suppression. Clutter suppression was mechanized via a `Phase Coherent Transform` (PCT) approach. This approach was applied to explore the feasibility of tracking a post-boost rocket from a low earth orbit satellite with real cloud background data. Simulation results show that the PCT/correlation tracking algorithm can perform satisfactorily at signal-to-clutter ratio (SCR) as low as 5 or 7 dB.

A climate index derived from satellite measured spectral infrared radiation. Ph.D. Thesis

Science.gov (United States)

Abel, M. D.; Fox, S. K.

1982-01-01

The vertical infrared radiative emitting structure (VIRES) climate index, based on radiative transfer theory and derived from the spectral radiances typically used to retrieve temperature profiles, is introduced. It is assumed that clouds and climate are closely related and a change in one will result in a change in the other. The index is a function of the cloud, temperature, and moisture distributions. It is more accurately retrieved from satellite data than is cloudiness per se. The VIRES index is based upon the shape and relative magnitude of the broadband weighting function of the infrared radiative transfer equation. The broadband weighting curves are retrieved from simulated satellite infrared sounder data (spectral radiances). The retrieval procedure is described and the error error sensitivities of the method investigated. Index measuring options and possible applications of the VIRES index are proposed.

Uncertainties in cloud phase and optical thickness retrievals from the Earth Polychromatic Imaging Camera (EPIC)

Science.gov (United States)

Meyer, Kerry; Yang, Yuekui; Platnick, Steven

2018-01-01

This paper presents an investigation of the expected uncertainties of a single channel cloud optical thickness (COT) retrieval technique, as well as a simple cloud temperature threshold based thermodynamic phase approach, in support of the Deep Space Climate Observatory (DSCOVR) mission. DSCOVR cloud products will be derived from Earth Polychromatic Imaging Camera (EPIC) observations in the ultraviolet and visible spectra. Since EPIC is not equipped with a spectral channel in the shortwave or mid-wave infrared that is sensitive to cloud effective radius (CER), COT will be inferred from a single visible channel with the assumption of appropriate CER values for liquid and ice phase clouds. One month of Aqua MODIS daytime granules from April 2005 is selected for investigating cloud phase sensitivity, and a subset of these granules that has similar EPIC sun-view geometry is selected for investigating COT uncertainties. EPIC COT retrievals are simulated with the same algorithm as the operational MODIS cloud products (MOD06), except using fixed phase-dependent CER values. Uncertainty estimates are derived by comparing the single channel COT retrievals with the baseline bi-spectral MODIS retrievals. Results show that a single channel COT retrieval is feasible for EPIC. For ice clouds, single channel retrieval errors are minimal (clouds the error is mostly limited to within 10%, although for thin clouds (COT cloud masking and cloud temperature retrievals are not considered in this study. PMID:29619116

The Dependence of Cloud Property Trend Detection on Absolute Calibration Accuracy of Passive Satellite Sensors

Science.gov (United States)

Shea, Y.; Wielicki, B. A.; Sun-Mack, S.; Minnis, P.; Zelinka, M. D.

2016-12-01

Detecting trends in climate variables on global, decadal scales requires highly accurate, stable measurements and retrieval algorithms. Trend uncertainty depends on its magnitude, natural variability, and instrument and retrieval algorithm accuracy and stability. We applied a climate accuracy framework to quantify the impact of absolute calibration on cloud property trend uncertainty. The cloud properties studied were cloud fraction, effective temperature, optical thickness, and effective radius retrieved using the Clouds and the Earth's Radiant Energy System (CERES) Cloud Property Retrieval System, which uses Moderate-resolution Imaging Spectroradiometer measurements (MODIS). Modeling experiments from the fifth phase of the Climate Model Intercomparison Project (CMIP5) agree that net cloud feedback is likely positive but disagree regarding its magnitude, mainly due to uncertainty in shortwave cloud feedback. With the climate accuracy framework we determined the time to detect trends for instruments with various calibration accuracies. We estimated a relationship between cloud property trend uncertainty, cloud feedback, and Equilibrium Climate Sensitivity and also between effective radius trend uncertainty and aerosol indirect effect trends. The direct relationship between instrument accuracy requirements and climate model output provides the level of instrument absolute accuracy needed to reduce climate model projection uncertainty. Different cloud types have varied radiative impacts on the climate system depending on several attributes, such as their thermodynamic phase, altitude, and optical thickness. Therefore, we also conducted these studies by cloud types for a clearer understanding of instrument accuracy requirements needed to detect changes in their cloud properties. Combining this information with the radiative impact of different cloud types helps to prioritize among requirements for future satellite sensors and understanding the climate detection

The MSG-SEVIRI-based cloud property data record CLAAS-2

Directory of Open Access Journals (Sweden)

N. Benas

2017-07-01

Full Text Available Clouds play a central role in the Earth's atmosphere, and satellite observations are crucial for monitoring clouds and understanding their impact on the energy budget and water cycle. Within the European Organisation for the Exploitation of Meteorological Satellites (EUMETSAT Satellite Application Facility on Climate Monitoring (CM SAF, a new cloud property data record was derived from geostationary Meteosat Spinning Enhanced Visible and Infrared Imager (SEVIRI measurements for the time frame 2004–2015. The resulting CLAAS-2 (CLoud property dAtAset using SEVIRI, Edition 2 data record is publicly available via the CM SAF website (https://doi.org/10.5676/EUM_SAF_CM/CLAAS/V002. In this paper we present an extensive evaluation of the CLAAS-2 cloud products, which include cloud fractional coverage, thermodynamic phase, cloud top properties, liquid/ice cloud water path and corresponding optical thickness and particle effective radius. Data validation and comparisons were performed on both level 2 (native SEVIRI grid and repeat cycle and level 3 (daily and monthly averages and histograms with reference datasets derived from lidar, microwave and passive imager measurements. The evaluation results show very good overall agreement with matching spatial distributions and temporal variability and small biases attributed mainly to differences in sensor characteristics, retrieval approaches, spatial and temporal samplings and viewing geometries. No major discrepancies were found. Underpinned by the good evaluation results, CLAAS-2 demonstrates that it is fit for the envisaged applications, such as process studies of the diurnal cycle of clouds and the evaluation of regional climate models. The data record is planned to be extended and updated in the future.

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

Science.gov (United States)

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.

Progress in Near Real-Time Volcanic Cloud Observations Using Satellite UV Instruments

Science.gov (United States)

Krotkov, N. A.; Yang, K.; Vicente, G.; Hughes, E. J.; Carn, S. A.; Krueger, A. J.

2011-12-01

Volcanic clouds from explosive eruptions can wreak havoc in many parts of the world, as exemplified by the 2010 eruption at the Eyjafjöll volcano in Iceland, which caused widespread disruption to air traffic and resulted in economic impacts across the globe. A suite of satellite-based systems offer the most effective means to monitor active volcanoes and to track the movement of volcanic clouds globally, providing critical information for aviation hazard mitigation. Satellite UV sensors, as part of this suite, have a long history of making unique near-real time (NRT) measurements of sulfur dioxide (SO2) and ash (aerosol Index) in volcanic clouds to supplement operational volcanic ash monitoring. Recently a NASA application project has shown that the use of near real-time (NRT,i.e., not older than 3 h) Aura/OMI satellite data produces a marked improvement in volcanic cloud detection using SO2 combined with Aerosol Index (AI) as a marker for ash. An operational online NRT OMI AI and SO2 image and data product distribution system was developed in collaboration with the NOAA Office of Satellite Data Processing and Distribution. Automated volcanic eruption alarms, and the production of volcanic cloud subsets for multiple regions are provided through the NOAA website. The data provide valuable information in support of the U.S. Federal Aviation Administration goal of a safe and efficient National Air Space. In this presentation, we will highlight the advantages of UV techniques and describe the advances in volcanic SO2 plume height estimation and enhanced volcanic ash detection using hyper-spectral UV measurements, illustrated with Aura/OMI observations of recent eruptions. We will share our plan to provide near-real-time volcanic cloud monitoring service using the Ozone Mapping and Profiler Suite (OMPS) on the Joint Polar Satellite System (JPSS).

Visualizing Cloud Properties and Satellite Imagery: A Tool for Visualization and Information Integration

Science.gov (United States)

Chee, T.; Nguyen, L.; Smith, W. L., Jr.; Spangenberg, D.; Palikonda, R.; Bedka, K. M.; Minnis, P.; Thieman, M. M.; Nordeen, M.

2017-12-01

Providing public access to research products including cloud macro and microphysical properties and satellite imagery are a key concern for the NASA Langley Research Center Cloud and Radiation Group. This work describes a web based visualization tool and API that allows end users to easily create customized cloud product and satellite imagery, ground site data and satellite ground track information that is generated dynamically. The tool has two uses, one to visualize the dynamically created imagery and the other to provide access to the dynamically generated imagery directly at a later time. Internally, we leverage our practical experience with large, scalable application practices to develop a system that has the largest potential for scalability as well as the ability to be deployed on the cloud to accommodate scalability issues. We build upon NASA Langley Cloud and Radiation Group's experience with making real-time and historical satellite cloud product information, satellite imagery, ground site data and satellite track information accessible and easily searchable. This tool is the culmination of our prior experience with dynamic imagery generation and provides a way to build a "mash-up" of dynamically generated imagery and related kinds of information that are visualized together to add value to disparate but related information. In support of NASA strategic goals, our group aims to make as much scientific knowledge, observations and products available to the citizen science, research and interested communities as well as for automated systems to acquire the same information for data mining or other analytic purposes. This tool and the underlying API's provide a valuable research tool to a wide audience both as a standalone research tool and also as an easily accessed data source that can easily be mined or used with existing tools.

Evaluation of cloud properties in the NOAA/NCEP global forecast system using multiple satellite products

Energy Technology Data Exchange (ETDEWEB)

Yoo, Hyelim [University of Maryland, Department of Atmospheric and Oceanic Science, College Park, MD (United States); Li, Zhanqing [University of Maryland, Department of Atmospheric and Oceanic Science, College Park, MD (United States); Beijing Normal University, State Key Laboratory of Earth Surface Processes and Resource Ecology, GCESS, Beijing (China)

2012-12-15

Knowledge of cloud properties and their vertical structure is important for meteorological studies due to their impact on both the Earth's radiation budget and adiabatic heating within the atmosphere. The objective of this study is to evaluate bulk cloud properties and vertical distribution simulated by the US National Oceanic and Atmospheric Administration National Centers for Environmental Prediction Global Forecast System (GFS) using three global satellite products. Cloud variables evaluated include the occurrence and fraction of clouds in up to three layers, cloud optical depth, liquid water path, and ice water path. Cloud vertical structure data are retrieved from both active (CloudSat/CALIPSO) and passive sensors and are subsequently compared with GFS model results. In general, the GFS model captures the spatial patterns of hydrometeors reasonably well and follows the general features seen in satellite measurements, but large discrepancies exist in low-level cloud properties. More boundary layer clouds over the interior continents were generated by the GFS model whereas satellite retrievals showed more low-level clouds over oceans. Although the frequencies of global multi-layer clouds from observations are similar to those from the model, latitudinal variations show discrepancies in terms of structure and pattern. The modeled cloud optical depth over storm track region and subtropical region is less than that from the passive sensor and is overestimated for deep convective clouds. The distributions of ice water path (IWP) agree better with satellite observations than do liquid water path (LWP) distributions. Discrepancies in LWP/IWP distributions between observations and the model are attributed to differences in cloud water mixing ratio and mean relative humidity fields, which are major control variables determining the formation of clouds. (orig.)

Validation of Satellite-Derived Sea Surface Temperatures for Waters around Taiwan

Directory of Open Access Journals (Sweden)

Ming-An Lee

2005-01-01

Full Text Available In order to validate the Advanced Very High Resolution Radiometer (AVHRR-derived sea surface temperatures (SST of the waters around Taiwan, we generated a match-up data set of 961 pairs, which included in situ SSTs and concurrent AVHRR measurements for the period of 1998 to 2002. Availability of cloud-free images, i.e., images with more than 85% of cloud-free area in their coverage, was about 2.23% of all AVHRR images during the study period. The range of in situ SSTs was from _ to _ The satellite derived-SSTs through MCSST and NLSST algorithms were linearly related to the in situ SSTs with correlation coefficients of 0.985 and 0.98, respectively. The MCSSTs and NLSSTs had small biases of 0.009 _ and 0.256 _ with root mean square deviations of 0.64 _ and 0.801 _ respectively, therefore the AVHRR-based MCSSTs and NLSSTs had high accuracy in the seas around Taiwan.

Radiative effect differences between multi-layered and single-layer clouds derived from CERES, CALIPSO, and CloudSat data

International Nuclear Information System (INIS)

Li Jiming; Yi Yuhong; Minnis, Patrick; Huang Jianping; Yan Hongru; Ma Yuejie; Wang Wencai; Kirk Ayers, J.

2011-01-01

Clouds alter general circulation through modification of the radiative heating profile within the atmosphere. Their effects are complex and depend on height, vertical structure, and phase. The instantaneous cloud radiative effect (CRE) induced by multi-layered (ML) and single-layer (SL) clouds is estimated by analyzing data collected by the Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO), CloudSat, and Clouds and Earth's Radiation Energy Budget System (CERES) missions from March 2007 through February 2008. The CRE differences between ML and SL clouds at the top of the atmosphere (TOA) and at the surface were also examined. The zonal mean shortwave (SW) CRE differences between the ML and SL clouds at the TOA and surface were positive at most latitudes, peaking at 120 W m -2 in the tropics and dropping to -30 W m -2 at higher latitudes. This indicated that the ML clouds usually reflected less sunlight at the TOA and transmitted more to the surface than the SL clouds, due to their higher cloud top heights. The zonal mean longwave (LW) CRE differences between ML and SL clouds at the TOA and surface were relatively small, ranging from -30 to 30 W m -2 . This showed that the ML clouds only increased the amount of thermal radiation at the TOA relative to the SL clouds in the tropics, decreasing it elsewhere. In other words, ML clouds tended to cool the atmosphere in the tropics and warm it elsewhere when compared to SL clouds. The zonal mean net CRE differences were positive at most latitudes and dominated by the SW CRE differences.

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

Science.gov (United States)

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

2017-01-01

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

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

Directory of Open Access Journals (Sweden)

Jessica H. Belle

2017-10-01

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

What do satellite backscatter ultraviolet and visible spectrometers see over snow and ice? A study of clouds and ozone using the A-train

Directory of Open Access Journals (Sweden)

A. P. Vasilkov

2010-05-01

Full Text Available In this paper, we examine how clouds over snow and ice affect ozone absorption and how these effects may be accounted for in satellite retrieval algorithms. Over snow and ice, the Aura Ozone Monitoring Instrument (OMI Raman cloud pressure algorithm derives an effective scene pressure. When this scene pressure differs appreciably from the surface pressure, the difference is assumed to be caused by a cloud that is shielding atmospheric absorption and scattering below cloud-top from satellite view. A pressure difference of 100 hPa is used as a crude threshold for the detection of clouds that significantly shield tropospheric ozone absorption. Combining the OMI effective scene pressure and the Aqua MODerate-resolution Imaging Spectroradiometer (MODIS cloud top pressure, we can distinguish between shielding and non-shielding clouds.

To evaluate this approach, we performed radiative transfer simulations under various observing conditions. Using cloud vertical extinction profiles from the CloudSat Cloud Profiling Radar (CPR, we find that clouds over a bright surface can produce significant shielding (i.e., a reduction in the sensitivity of the top-of-the-atmosphere radiance to ozone absorption below the clouds. The amount of shielding provided by clouds depends upon the geometry (solar and satellite zenith angles and the surface albedo as well as cloud optical thickness. We also use CloudSat observations to qualitatively evaluate our approach. The CloudSat, Aqua, and Aura satellites fly in an afternoon polar orbit constellation with ground overpass times within 15 min of each other.

The current Total Ozone Mapping Spectrometer (TOMS total column ozone algorithm (that has also been applied to the OMI assumes no clouds over snow and ice. This assumption leads to errors in the retrieved ozone column. We show that the use of OMI effective scene pressures over snow and ice reduces these errors and leads to a more homogeneous spatial

Classification of Clouds and Deep Convection from GEOS-5 Using Satellite Observations

Science.gov (United States)

Putman, William; Suarez, Max

2010-01-01

With the increased resolution of global atmospheric models and the push toward global cloud resolving models, the resemblance of model output to satellite observations has become strikingly similar. As we progress with our adaptation of the Goddard Earth Observing System Model, Version 5 (GEOS-5) as a high resolution cloud system resolving model, evaluation of cloud properties and deep convection require in-depth analysis beyond a visual comparison. Outgoing long-wave radiation (OLR) provides a sufficient comparison with infrared (IR) satellite imagery to isolate areas of deep convection. We have adopted a binning technique to generate a series of histograms for OLR which classify the presence and fraction of clear sky versus deep convection in the tropics that can be compared with a similar analyses of IR imagery from composite Geostationary Operational Environmental Satellite (GOES) observations. We will present initial results that have been used to evaluate the amount of deep convective parameterization required within the model as we move toward cloud system resolving resolutions of 10- to 1-km globally.

A Global Survey of Cloud Thermodynamic Phase using High Spatial Resolution VSWIR Spectroscopy, 2005-2015

Science.gov (United States)

Thompson, D. R.; Kahn, B. H.; Green, R. O.; Chien, S.; Middleton, E.; Tran, D. Q.

2017-12-01

Clouds' variable ice and liquid content significantly influences their optical properties, evolution, and radiative forcing potential (Tan and Storelvmo, J. Atmos. Sci, 73, 2016). However, most remote measurements of thermodynamic phase have spatial resolutions of 1 km or more and are insensitive to mixed phases. This under-constrains important processes, such as spatial partitioning within mixed phase clouds, that carry outsize radiative forcing impacts. These uncertainties could shift Global Climate Model (GCM) predictions of future warming by over 1 degree Celsius (Tan et al., Science 352:6282, 2016). Imaging spectroscopy of reflected solar energy from the 1.4 - 1.8 μm shortwave infrared (SWIR) spectral range can address this observational gap. These observations can distinguish ice and water absorption, providing a robust and sensitive measurement of cloud top thermodynamic phase including mixed phases. Imaging spectrometers can resolve variations at scales of tens to hundreds of meters (Thompson et al., JGR-Atmospheres 121, 2016). We report the first such global high spatial resolution (30 m) survey, based on data from 2005-2015 acquired by the Hyperion imaging spectrometer onboard NASA's EO-1 spacecraft (Pearlman et al., Proc. SPIE 4135, 2001). Estimated seasonal and latitudinal distributions of cloud thermodynamic phase generally agree with observations made by other satellites such as the Atmospheric Infrared Sounder (AIRS). Variogram analyses reveal variability at different spatial scales. Our results corroborate previously observed zonal distributions, while adding insight into the spatial scales of processes governing cloud top thermodynamic phase. Figure: Thermodynamic phase retrievals. Top: Example of a cloud top thermodynamic phase map from the EO-1/Hyperion. Bottom: Latitudinal distributions of pure and mixed phase clouds, 2005-2015, showing Liquid Thickness Fraction (LTF). LTF=0 corresponds to pure ice absorption, while LTF=1 is pure liquid. The

Uncertainties in cloud phase and optical thickness retrievals from the Earth Polychromatic Imaging Camera (EPIC).

Science.gov (United States)

Meyer, Kerry; Yang, Yuekui; Platnick, Steven

2016-01-01

This paper presents an investigation of the expected uncertainties of a single channel cloud optical thickness (COT) retrieval technique, as well as a simple cloud temperature threshold based thermodynamic phase approach, in support of the Deep Space Climate Observatory (DSCOVR) mission. DSCOVR cloud products will be derived from Earth Polychromatic Imaging Camera (EPIC) observations in the ultraviolet and visible spectra. Since EPIC is not equipped with a spectral channel in the shortwave or mid-wave infrared that is sensitive to cloud effective radius (CER), COT will be inferred from a single visible channel with the assumption of appropriate CER values for liquid and ice phase clouds. One month of Aqua MODIS daytime granules from April 2005 is selected for investigating cloud phase sensitivity, and a subset of these granules that has similar EPIC sun-view geometry is selected for investigating COT uncertainties. EPIC COT retrievals are simulated with the same algorithm as the operational MODIS cloud products (MOD06), except using fixed phase-dependent CER values. Uncertainty estimates are derived by comparing the single channel COT retrievals with the baseline bi-spectral MODIS retrievals. Results show that a single channel COT retrieval is feasible for EPIC. For ice clouds, single channel retrieval errors are minimal (< 2%) due to the particle size insensitivity of the assumed ice crystal (i.e., severely roughened aggregate of hexagonal columns) scattering properties at visible wavelengths, while for liquid clouds the error is mostly limited to within 10%, although for thin clouds (COT < 2) the error can be higher. Potential uncertainties in EPIC cloud masking and cloud temperature retrievals are not considered in this study.

Cloud cover typing from environmental satellite imagery. Discriminating cloud structure with Fast Fourier Transforms (FFT)

Science.gov (United States)

Logan, T. L.; Huning, J. R.; Glackin, D. L.

1983-01-01

The use of two dimensional Fast Fourier Transforms (FFTs) subjected to pattern recognition technology for the identification and classification of low altitude stratus cloud structure from Geostationary Operational Environmental Satellite (GOES) imagery was examined. The development of a scene independent pattern recognition methodology, unconstrained by conventional cloud morphological classifications was emphasized. A technique for extracting cloud shape, direction, and size attributes from GOES visual imagery was developed. These attributes were combined with two statistical attributes (cloud mean brightness, cloud standard deviation), and interrogated using unsupervised clustering amd maximum likelihood classification techniques. Results indicate that: (1) the key cloud discrimination attributes are mean brightness, direction, shape, and minimum size; (2) cloud structure can be differentiated at given pixel scales; (3) cloud type may be identifiable at coarser scales; (4) there are positive indications of scene independence which would permit development of a cloud signature bank; (5) edge enhancement of GOES imagery does not appreciably improve cloud classification over the use of raw data; and (6) the GOES imagery must be apodized before generation of FFTs.

Type-Dependent Responses of Ice Cloud Properties to Aerosols From Satellite Retrievals

Science.gov (United States)

Zhao, Bin; Gu, Yu; Liou, Kuo-Nan; Wang, Yuan; Liu, Xiaohong; Huang, Lei; Jiang, Jonathan H.; Su, Hui

2018-04-01

Aerosol-cloud interactions represent one of the largest uncertainties in external forcings on our climate system. Compared with liquid clouds, the observational evidence for the aerosol impact on ice clouds is much more limited and shows conflicting results, partly because the distinct features of different ice cloud and aerosol types were seldom considered. Using 9-year satellite retrievals, we find that, for convection-generated (anvil) ice clouds, cloud optical thickness, cloud thickness, and cloud fraction increase with small-to-moderate aerosol loadings (types provide valuable constraints on the modeling assessment of aerosol-ice cloud radiative forcing.

Mixed phase clouds: observations and theoretical advances (overview)

Science.gov (United States)

Korolev, Alexei

2013-04-01

Mixed phase clouds play important role in precipitation formation and radiation budget of the Earth. The microphysical measurements in mixed phase clouds are notoriously difficult due to many technical challenges. The airborne instrumentation for characterization of the microstructure of mixed phase clouds is discussed. The results multiyear airborne observations and measurements of frequency of occurrence of mixed phase, characteristic spatial scales, humidity in mixed phase and ice clouds are presented. A theoretical framework describing the thermodynamics and phase transformation of a three phase component system consisting of ice particles, liquid droplets and water vapor is discussed. It is shown that the Wegener-Bergeron-Findeisen process plays different role in clouds with different dynamics. The problem of maintenance and longevity of mixed phase clouds is discussed.

Development and Validation of Improved Techniques for Cloud Property Retrieval from Environmental Satellites

National Research Council Canada - National Science Library

Gustafson, Gary

2000-01-01

...) develop extensible cloud property retrieval algorithms suitable for expanding existing cloud analysis capabilities to utilize data from new and future environmental satellite sensing systems; (2...

Long-term Satellite Observations of Cloud and Aerosol Radiative Effects Using the (A)ATSR Satellite Data Record

Science.gov (United States)

Christensen, M.; McGarragh, G.; Thomas, G.; Povey, A.; Proud, S.; Poulsen, C. A.; Grainger, R. G.

2016-12-01

Radiative forcing by clouds, aerosols, and their interactions constitute some of the largest sources of uncertainties in the climate system (Chapter 7 IPCC, 2013). It is essential to understand the past through examination of long-term satellite observation records to provide insight into the uncertainty characteristics of these radiative forcers. As part of the ESA CCI (Climate Change Initiative) we have recently implemented a broadband radiative flux algorithm (known as BUGSrad) into the Optimal Retrieval for Aerosol and Cloud (ORAC) scheme. ORAC achieves radiative consistency of its aerosol and cloud products through an optimal estimation scheme and is highly versatile, enabling retrievals for numerous satellite sensors: ATSR, MODIS, VIIRS, AVHRR, SLSTR, SEVIRI, and AHI. An analysis of the 17-year well-calibrated Along Track Scanning Radiometer (ATSR) data is used to quantify trends in cloud and aerosol radiative effects over a wide range of spatiotemporal scales. The El Niño Southern Oscillation stands out as the largest contributing mode of variability to the radiative energy balance (long wave and shortwave fluxes) at the top of the atmosphere. Furthermore, trends in planetary albedo show substantial decreases across the Arctic Ocean (likely due to the melting of sea ice and snow) and modest increases in regions dominated by stratocumulus (e.g., off the coast of California) through notable increases in cloud fraction and liquid water path. Finally, changes in volcanic activity and biomass burning aerosol over this period show sizeable radiative forcing impacts at local-scales. We will demonstrate that radiative forcing from aerosols and clouds have played a significant role in the identified key climate processes using 17 years of satellite observational data.

Influence of the Arctic Oscillation on the vertical distribution of clouds as observed by the A-Train constellation of satellites

Directory of Open Access Journals (Sweden)

A. Devasthale

2012-11-01

Full Text Available The main purpose of this study is to investigate the influence of the Arctic Oscillation (AO, the dominant mode of natural variability over the northerly high latitudes, on the spatial (horizontal and vertical distribution of clouds in the Arctic. To that end, we use a suite of sensors onboard NASA's A-Train satellites that provide accurate observations of the distribution of clouds along with information on atmospheric thermodynamics. Data from three independent sensors are used (AQUA-AIRS, CALIOP-CALIPSO and CPR-CloudSat covering two time periods (winter half years, November through March, of 2002–2011 and 2006–2011, respectively along with data from the ERA-Interim reanalysis.

We show that the zonal vertical distribution of cloud fraction anomalies averaged over 67–82° N to a first approximation follows a dipole structure (referred to as "Greenland cloud dipole anomaly", GCDA, such that during the positive phase of the AO, positive and negative cloud anomalies are observed eastwards and westward of Greenland respectively, while the opposite is true for the negative phase of AO. By investigating the concurrent meteorological conditions (temperature, humidity and winds, we show that differences in the meridional energy and moisture transport during the positive and negative phases of the AO and the associated thermodynamics are responsible for the conditions that are conducive for the formation of this dipole structure. All three satellite sensors broadly observe this large-scale GCDA despite differences in their sensitivities, spatio-temporal and vertical resolutions, and the available lengths of data records, indicating the robustness of the results. The present study also provides a compelling case to carry out process-based evaluation of global and regional climate models.

On the Representation of Cloud Phase in Global Climate Models, and its Importance for Simulations of Climate Forcings and Feedbacks

Science.gov (United States)

Storelvmo, Trude; Sagoo, Navjit; Tan, Ivy

2016-04-01

Despite the growing effort in improving the cloud microphysical schemes in GCMs, most of this effort has not focused on improving the ability of GCMs to accurately simulate phase partitioning in mixed-phase clouds. Getting the relative proportion of liquid droplets and ice crystals in clouds right in GCMs is critical for the representation of cloud radiative forcings and cloud-climate feedbacks. Here, we first present satellite observations of cloud phase obtained by NASA's CALIOP instrument, and report on robust statistical relationships between cloud phase and several aerosols species that have been demonstrated to act as ice nuclei (IN) in laboratory studies. We then report on results from model intercomparison projects that reveal that GCMs generally underestimate the amount of supercooled liquid in clouds. For a selected GCM (NCAR 's CAM5), we thereafter show that the underestimate can be attributed to two main factors: i) the presence of IN in the mixed-phase temperature range, and ii) the Wegener-Bergeron-Findeisen process, which converts liquid to ice once ice crystals have formed. Finally, we show that adjusting these two processes such that the GCM's cloud phase is in agreement with the observed has a substantial impact on the simulated radiative forcing due to IN perturbations, as well as on the cloud-climate feedbacks and ultimately climate sensitivity simulated by the GCM.

Statistical modeling of phenological phases in Poland based on coupling satellite derived products and gridded meteorological data

Science.gov (United States)

Czernecki, Bartosz; Jabłońska, Katarzyna; Nowosad, Jakub

2016-04-01

The aim of the study was to create and evaluate different statistical models for reconstructing and predicting selected phenological phases. This issue is of particular importance in Poland where national-wide phenological monitoring was abandoned in the middle of 1990s and the reactivated network was established in 2006. Authors decided to evaluate possibilities of using a wide-range of statistical modeling techniques to create synthetic archive dataset. Additionally, a robust tool for predicting the most distinguishable phenophases using only free of charge data as predictors was created. Study period covers the years 2007-2014 and contains only quality-controlled dataset of 10 species and 14 phenophases. Phenological data used in this study originates from the manual observations network run by the Institute of Meteorology and Water Management - National Research Institute (IMGW-PIB). Three kind of data sources were used as predictors: (i) satellite derived products, (ii) preprocessed gridded meteorological data, and (iii) spatial properties (longitude, latitude, altitude) of the monitoring site. Moderate-Resolution Imaging Spectroradiometer (MODIS) level-3 vegetation products were used for detecting onset dates of particular phenophases. Following indices were used: Normalized Difference Vegetation Index (NDVI), Enhanced Vegetation Index (EVI), Leaf Area Index (LAI), and Fraction of Photosynthetically Active Radiation (fPAR). Additionally, Interactive Multisensor Snow and Ice Mapping System (IMS) products were chosen to detect occurrence of snow cover. Due to highly noisy data, authors decided to take into account pixel reliability information. Besides satellite derived products (NDVI, EVI, FPAR, LAI, Snow cover), a wide group of observational data and agrometeorological indices derived from the European Climate Assessment & Dataset (ECA&D) were used as a potential predictors: cumulative growing degree days (GDD), cumulative growing precipitation days (GPD

Diurnal, Seasonal, and Interannual Variations of Cloud Properties Derived for CERES From Imager Data

Science.gov (United States)

Minnis, Patrick; Young, David F.; Sun-Mack, Sunny; Trepte, Qing Z.; Chen, Yan; Brown, Richard R.; Gibson, Sharon; Heck, Patrick W.

2004-01-01

Simultaneous measurement of the radiation and cloud fields on a global basis is a key component in the effort to understand and model the interaction between clouds and radiation at the top of the atmosphere, at the surface, and within the atmosphere. The NASA Clouds and Earth s Radiant Energy System (CERES) Project, begun in 1998, is meeting this need. Broadband shortwave (SW) and longwave radiance measurements taken by the CERES scanners at resolutions between 10 and 20 km on the Tropical Rainfall Measuring Mission (TRMM), Terra, and Aqua satellites are matched to simultaneous retrievals of cloud height, phase, particle size, water path, and optical depth OD from the TRMM Visible Infrared Scanner (VIRS) and the Moderate Resolution Imaging Spectroradiometer (MODIS) on Terra and Aqua. Besides aiding the interpretation of the broadband radiances, the CERES cloud properties are valuable for understanding cloud variations at a variety of scales. In this paper, the resulting CERES cloud data taken to date are averaged at several temporal scales to examine the temporal and spatial variability of the cloud properties on a global scale at a 1 resolution.

Evaluation of Satellite-Based Upper Troposphere Cloud Top Height Retrievals in Multilayer Cloud Conditions During TC4

Science.gov (United States)

Chang, Fu-Lung; Minnis, Patrick; Ayers, J. Kirk; McGill, Matthew J.; Palikonda, Rabindra; Spangenberg, Douglas A.; Smith, William L., Jr.; Yost, Christopher R.

2010-01-01

Upper troposphere cloud top heights (CTHs), restricted to cloud top pressures (CTPs) less than 500 hPa, inferred using four satellite retrieval methods applied to Twelfth Geostationary Operational Environmental Satellite (GOES-12) data are evaluated using measurements during the July August 2007 Tropical Composition, Cloud and Climate Coupling Experiment (TC4). The four methods are the single-layer CO2-absorption technique (SCO2AT), a modified CO2-absorption technique (MCO2AT) developed for improving both single-layered and multilayered cloud retrievals, a standard version of the Visible Infrared Solar-infrared Split-window Technique (old VISST), and a new version of VISST (new VISST) recently developed to improve cloud property retrievals. They are evaluated by comparing with ER-2 aircraft-based Cloud Physics Lidar (CPL) data taken during 9 days having extensive upper troposphere cirrus, anvil, and convective clouds. Compared to the 89% coverage by upper tropospheric clouds detected by the CPL, the SCO2AT, MCO2AT, old VISST, and new VISST retrieved CTPs less than 500 hPa in 76, 76, 69, and 74% of the matched pixels, respectively. Most of the differences are due to subvisible and optically thin cirrus clouds occurring near the tropopause that were detected only by the CPL. The mean upper tropospheric CTHs for the 9 days are 14.2 (+/- 2.1) km from the CPL and 10.7 (+/- 2.1), 12.1 (+/- 1.6), 9.7 (+/- 2.9), and 11.4 (+/- 2.8) km from the SCO2AT, MCO2AT, old VISST, and new VISST, respectively. Compared to the CPL, the MCO2AT CTHs had the smallest mean biases for semitransparent high clouds in both single-layered and multilayered situations whereas the new VISST CTHs had the smallest mean biases when upper clouds were opaque and optically thick. The biases for all techniques increased with increasing numbers of cloud layers. The transparency of the upper layer clouds tends to increase with the numbers of cloud layers.

Real-Time Estimation of Volcanic ASH/SO2 Cloud Height from Combined Uv/ir Satellite Observations and Numerical Modeling

Science.gov (United States)

Vicente, Gilberto A.

An efficient iterative method has been developed to estimate the vertical profile of SO2 and ash clouds from volcanic eruptions by comparing near real-time satellite observations with numerical modeling outputs. The approach uses UV based SO2 concentration and IR based ash cloud images, the volcanic ash transport model PUFF and wind speed, height and directional information to find the best match between the simulated and the observed displays. The method is computationally fast and is being implemented for operational use at the NOAA Volcanic Ash Advisory Centers (VAACs) in Washington, DC, USA, to support the Federal Aviation Administration (FAA) effort to detect, track and measure volcanic ash cloud heights for air traffic safety and management. The presentation will show the methodology, results, statistical analysis and SO2 and Aerosol Index input products derived from the Ozone Monitoring Instrument (OMI) onboard the NASA EOS/Aura research satellite and from the Global Ozone Monitoring Experiment-2 (GOME-2) instrument in the MetOp-A. The volcanic ash products are derived from AVHRR instruments in the NOAA POES-16, 17, 18, 19 as well as MetOp-A. The presentation will also show how a VAAC volcanic ash analyst interacts with the system providing initial condition inputs such as location and time of the volcanic eruption, followed by the automatic real-time tracking of all the satellite data available, subsequent activation of the iterative approach and the data/product delivery process in numerical and graphical format for operational applications.

Overview of CERES Cloud Properties Derived From VIRS AND MODIS DATA

Science.gov (United States)

Minis, Patrick; Geier, Erika; Wielicki, Bruce A.; Sun-Mack, Sunny; Chen, Yan; Trepte, Qing Z.; Dong, Xiquan; Doelling, David R.; Ayers, J. Kirk; Khaiyer, Mandana M.

2006-01-01

Simultaneous measurement of radiation and cloud fields on a global basis is recognized as a key component in understanding and modeling the interaction between clouds and radiation at the top of the atmosphere, at the surface, and within the atmosphere. The NASA Clouds and Earth s Radiant Energy System (CERES) Project (Wielicki et al., 1998) began addressing this issue in 1998 with its first broadband shortwave and longwave scanner on the Tropical Rainfall Measuring Mission (TRMM). This was followed by the launch of two CERES scanners each on Terra and Aqua during late 1999 and early 2002, respectively. When combined, these satellites should provide the most comprehensive global characterization of clouds and radiation to date. Unfortunately, the TRMM scanner failed during late 1998. The Terra and Aqua scanners continue to operate, however, providing measurements at a minimum of 4 local times each day. CERES was designed to scan in tandem with high resolution imagers so that the cloud conditions could be evaluated for every CERES measurement. The cloud properties are essential for converting CERES radiances shortwave albedo and longwave fluxes needed to define the radiation budget (ERB). They are also needed to unravel the impact of clouds on the ERB. The 5-channel, 2-km Visible Infrared Scanner (VIRS) on the TRMM and the 36-channel 1-km Moderate Resolution Imaging Spectroradiometer (MODIS) on Terra and Aqua are analyzed to define the cloud properties for each CERES footprint. To minimize inter-satellite differences and aid the development of useful climate-scale measurements, it was necessary to ensure that each satellite imager is calibrated in a fashion consistent with its counterpart on the other CERES satellites (Minnis et al., 2006) and that the algorithms are as similar as possible for all of the imagers. Thus, a set of cloud detection and retrieval algorithms were developed that could be applied to all three imagers utilizing as few channels as possible

Oceanic Weather Decision Support for Unmanned Global Hawk Science Missions into Hurricanes with Tailored Satellite Derived Products

Science.gov (United States)

Feltz, Wayne; Griffin, Sarah; Velden, Christopher; Zipser, Ed; Cecil, Daniel; Braun, Scott

2017-04-01

The purpose of this presentation is to identify in-flight hazards to high-altitude aircraft, namely the Global Hawk. The Global Hawk was used during Septembers 2012-2016 as part of two NASA funded Hurricane Sentinel-3 field campaigns to over-fly hurricanes in the Atlantic Ocean. This talk identifies the cause of severe turbulence experienced over Hurricane Emily (2005) and how a combination of NOAA funded GOES-R algorithm derived cloud top heights/tropical overshooting tops using GOES-13/SEVIRI imager radiances, and lightning information are used to identify areas of potential turbulence for near real-time navigation decision support. Several examples will demonstrate how the Global Hawk pilots remotely received and used real-time satellite derived cloud and lightning detection information to keep the aircraft safely above clouds and avoid regions of potential turbulence.

Global cloud database from VIRS and MODIS for CERES

Science.gov (United States)

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.

Theoretical algorithms for satellite-derived sea surface temperatures

Science.gov (United States)

Barton, I. J.; Zavody, A. M.; O'Brien, D. M.; Cutten, D. R.; Saunders, R. W.; Llewellyn-Jones, D. T.

1989-03-01

Reliable climate forecasting using numerical models of the ocean-atmosphere system requires accurate data sets of sea surface temperature (SST) and surface wind stress. Global sets of these data will be supplied by the instruments to fly on the ERS 1 satellite in 1990. One of these instruments, the Along-Track Scanning Radiometer (ATSR), has been specifically designed to provide SST in cloud-free areas with an accuracy of 0.3 K. The expected capabilities of the ATSR can be assessed using transmission models of infrared radiative transfer through the atmosphere. The performances of several different models are compared by estimating the infrared brightness temperatures measured by the NOAA 9 AVHRR for three standard atmospheres. Of these, a computationally quick spectral band model is used to derive typical AVHRR and ATSR SST algorithms in the form of linear equations. These algorithms show that a low-noise 3.7-μm channel is required to give the best satellite-derived SST and that the design accuracy of the ATSR is likely to be achievable. The inclusion of extra water vapor information in the analysis did not improve the accuracy of multiwavelength SST algorithms, but some improvement was noted with the multiangle technique. Further modeling is required with atmospheric data that include both aerosol variations and abnormal vertical profiles of water vapor and temperature.

The Invigoration of Deep Convective Clouds Over the Atlantic: Aerosol Effect, Meteorology or Retrieval Artifact?

Science.gov (United States)

Koren, Ilan; Feingold, Graham; Remer, Lorraine A.

2010-01-01

Associations between cloud properties and aerosol loading are frequently observed in products derived from satellite measurements. These observed trends between clouds and aerosol optical depth suggest aerosol modification of cloud dynamics, yet there are uncertainties involved in satellite retrievals that have the potential to lead to incorrect conclusions. Two of the most challenging problems are addressed here: the potential for retrieved aerosol optical depth to be cloud-contaminated, and as a result, artificially correlated with cloud parameters; and the potential for correlations between aerosol and cloud parameters to be erroneously considered to be causal. Here these issues are tackled directly by studying the effects of the aerosol on convective clouds in the tropical Atlantic Ocean using satellite remote sensing, a chemical transport model, and a reanalysis of meteorological fields. Results show that there is a robust positive correlation between cloud fraction or cloud top height and the aerosol optical depth, regardless of whether a stringent filtering of aerosol measurements in the vicinity of clouds is applied, or not. These same positive correlations emerge when replacing the observed aerosol field with that derived from a chemical transport model. Model-reanalysis data is used to address the causality question by providing meteorological context for the satellite observations. A correlation exercise between the full suite of meteorological fields derived from model reanalysis and satellite-derived cloud fields shows that observed cloud top height and cloud fraction correlate best with model pressure updraft velocity and relative humidity. Observed aerosol optical depth does correlate with meteorological parameters but usually different parameters from those that correlate with observed cloud fields. The result is a near-orthogonal influence of aerosol and meteorological fields on cloud top height and cloud fraction. The results strengthen the case

Satellite-Based Sunshine Duration for Europe

Directory of Open Access Journals (Sweden)

Bodo Ahrens

2013-06-01

Full Text Available In this study, two different methods were applied to derive daily and monthly sunshine duration based on high-resolution satellite products provided by the European Organisation for the Exploitation of Meteorological Satellites (EUMETSAT Satellite Application Facility on Climate Monitoring using data from Meteosat Second Generation (MSG SEVIRI (Spinning Enhanced Visible and Infrared Imager. The satellite products were either hourly cloud type or hourly surface incoming direct radiation. The satellite sunshine duration estimates were not found to be significantly different using the native 15-minute temporal resolution of SEVIRI. The satellite-based sunshine duration products give additional spatial information over the European continent compared with equivalent in situ-based products. An evaluation of the satellite sunshine duration by product intercomparison and against station measurements was carried out to determine their accuracy. The satellite data were found to be within ±1 h/day compared to high-quality Baseline Surface Radiation Network or surface synoptic observations (SYNOP station measurements. The satellite-based products differ more over the oceans than over land, mainly because of the treatment of fractional clouds in the cloud type-based sunshine duration product. This paper presents the methods used to derive the satellite sunshine duration products and the performance of the different retrievals. The main benefits and disadvantages compared to station-based products are also discussed.

Intercomparison of model simulations of mixed-phase clouds observed during the ARM Mixed-Phase Arctic Cloud Experiment. Part I: Single layer cloud

Energy Technology Data Exchange (ETDEWEB)

Klein, S A; McCoy, R B; Morrison, H; Ackerman, A; Avramov, A; deBoer, G; Chen, M; Cole, J; DelGenio, A; Golaz, J; Hashino, T; Harrington, J; Hoose, C; Khairoutdinov, M; Larson, V; Liu, X; Luo, Y; McFarquhar, G; Menon, S; Neggers, R; Park, S; Poellot, M; von Salzen, K; Schmidt, J; Sednev, I; Shipway, B; Shupe, M; Spangenberg, D; Sud, Y; Turner, D; Veron, D; Falk, M; Foster, M; Fridlind, A; Walker, G; Wang, Z; Wolf, A; Xie, S; Xu, K; Yang, F; Zhang, G

2008-02-27

Results are presented from an intercomparison of single-column and cloud-resolving model simulations of a cold-air outbreak mixed-phase stratocumulus cloud observed during the Atmospheric Radiation Measurement (ARM) program's Mixed-Phase Arctic Cloud Experiment. The observed cloud occurred in a well-mixed boundary layer with a cloud top temperature of -15 C. The observed liquid water path of around 160 g m{sup -2} was about two-thirds of the adiabatic value and much greater than the mass of ice crystal precipitation which when integrated from the surface to cloud top was around 15 g m{sup -2}. The simulations were performed by seventeen single-column models (SCMs) and nine cloud-resolving models (CRMs). While the simulated ice water path is generally consistent with the observed values, the median SCM and CRM liquid water path is a factor of three smaller than observed. Results from a sensitivity study in which models removed ice microphysics indicate that in many models the interaction between liquid and ice-phase microphysics is responsible for the large model underestimate of liquid water path. Despite this general underestimate, the simulated liquid and ice water paths of several models are consistent with the observed values. Furthermore, there is some evidence that models with more sophisticated microphysics simulate liquid and ice water paths that are in better agreement with the observed values, although considerable scatter is also present. Although no single factor guarantees a good simulation, these results emphasize the need for improvement in the model representation of mixed-phase microphysics. This case study, which has been well observed from both aircraft and ground-based remote sensors, could be a benchmark for model simulations of mixed-phase clouds.

How do changes in warm-phase microphysics affect deep convective clouds?

Science.gov (United States)

Chen, Qian; Koren, Ilan; Altaratz, Orit; Heiblum, Reuven H.; Dagan, Guy; Pinto, Lital

2017-08-01

Understanding aerosol effects on deep convective clouds and the derived effects on the radiation budget and rain patterns can largely contribute to estimations of climate uncertainties. The challenge is difficult in part because key microphysical processes in the mixed and cold phases are still not well understood. For deep convective clouds with a warm base, understanding aerosol effects on the warm processes is extremely important as they set the initial and boundary conditions for the cold processes. Therefore, the focus of this study is the warm phase, which can be better resolved. The main question is: How do aerosol-derived changes in the warm phase affect the properties of deep convective cloud systems? To explore this question, we used a weather research and forecasting (WRF) model with spectral bin microphysics to simulate a deep convective cloud system over the Marshall Islands during the Kwajalein Experiment (KWAJEX). The model results were validated against observations, showing similarities in the vertical profile of radar reflectivity and the surface rain rate. Simulations with larger aerosol loading resulted in a larger total cloud mass, a larger cloud fraction in the upper levels, and a larger frequency of strong updrafts and rain rates. Enlarged mass both below and above the zero temperature level (ZTL) contributed to the increase in cloud total mass (water and ice) in the polluted runs. Increased condensation efficiency of cloud droplets governed the gain in mass below the ZTL, while both enhanced condensational and depositional growth led to increased mass above it. The enhanced mass loading above the ZTL acted to reduce the cloud buoyancy, while the thermal buoyancy (driven by the enhanced latent heat release) increased in the polluted runs. The overall effect showed an increased upward transport (across the ZTL) of liquid water driven by both larger updrafts and larger droplet mobility. These aerosol effects were reflected in the larger ratio

How do changes in warm-phase microphysics affect deep convective clouds?

Directory of Open Access Journals (Sweden)

Q. Chen

2017-08-01

Full Text Available Understanding aerosol effects on deep convective clouds and the derived effects on the radiation budget and rain patterns can largely contribute to estimations of climate uncertainties. The challenge is difficult in part because key microphysical processes in the mixed and cold phases are still not well understood. For deep convective clouds with a warm base, understanding aerosol effects on the warm processes is extremely important as they set the initial and boundary conditions for the cold processes. Therefore, the focus of this study is the warm phase, which can be better resolved. The main question is: How do aerosol-derived changes in the warm phase affect the properties of deep convective cloud systems? To explore this question, we used a weather research and forecasting (WRF model with spectral bin microphysics to simulate a deep convective cloud system over the Marshall Islands during the Kwajalein Experiment (KWAJEX. The model results were validated against observations, showing similarities in the vertical profile of radar reflectivity and the surface rain rate. Simulations with larger aerosol loading resulted in a larger total cloud mass, a larger cloud fraction in the upper levels, and a larger frequency of strong updrafts and rain rates. Enlarged mass both below and above the zero temperature level (ZTL contributed to the increase in cloud total mass (water and ice in the polluted runs. Increased condensation efficiency of cloud droplets governed the gain in mass below the ZTL, while both enhanced condensational and depositional growth led to increased mass above it. The enhanced mass loading above the ZTL acted to reduce the cloud buoyancy, while the thermal buoyancy (driven by the enhanced latent heat release increased in the polluted runs. The overall effect showed an increased upward transport (across the ZTL of liquid water driven by both larger updrafts and larger droplet mobility. These aerosol effects were reflected in the

Phase transformations in an ascending adiabatic mixed-phase cloud volume

Science.gov (United States)

Pinsky, M.; Khain, A.; Korolev, A.

2015-04-01

Regimes of liquid-ice coexistence that may form in an adiabatic parcel ascending at constant velocity at freezing temperatures are investigated. Four zones with different microphysical structures succeeding one another along the vertical direction have been established. On the basis of a novel balance equation, analytical expressions are derived to determine the conditions specific for each of these zones. In particular, the necessary and sufficient conditions for formation of liquid water phase within an ascending parcel containing only ice particles are determined. The results are compared to findings reported in earlier studies. The role of the Wegener-Bergeron-Findeisen mechanism in the phase transformation is analyzed. The dependence of the phase relaxation time on height in the four zones is investigated on the basis of a novel analytical expression. The results obtained in the study can be instrumental for analysis and interpretation of observed mixed-phase clouds.

Statistical evaluation of the feasibility of satellite-retrieved cloud parameters as indicators of PM2.5 levels.

Science.gov (United States)

Yu, Chao; Di Girolamo, Larry; Chen, Liangfu; Zhang, Xueying; Liu, Yang

2015-01-01

The spatial and temporal characteristics of fine particulate matter (PM2.5, particulate matter research has been conducted on the association between cloud properties and PM2.5 levels. In this study, we analyzed the relationships between ground PM2.5 concentrations and two satellite-retrieved cloud parameters using data from the Southeastern Aerosol Research and Characterization (SEARCH) Network during 2000-2010. We found that both satellite-retrieved cloud fraction (CF) and cloud optical thickness (COT) are negatively associated with PM2.5 levels. PM2.5 speciation and meteorological analysis suggested that the main reason for these negative relationships might be the decreased secondary particle generation. Stratified analyses by season, land use type, and site location showed that seasonal impacts on this relationship are significant. These associations do not vary substantially between urban and rural sites or inland and coastal sites. The statistically significant negative associations of PM2.5 mass concentrations with CF and COT suggest that satellite-retrieved cloud parameters have the potential to serve as predictors to fill the data gap left by satellite aerosol optical depth in satellite-driven PM2.5 models.

CERES cloud property retrievals from imagers on TRMM, Terra, and Aqua

Science.gov (United States)

Minnis, Patrick; Young, David F.; Sun-Mack, Sunny; Heck, Patrick W.; Doelling, David R.; Trepte, Qing Z.

2004-02-01

The micro- and macrophysical properties of clouds play a crucial role in Earth"s radiation budget. The NASA Clouds and Earth"s Radiant Energy System (CERES) is providing simultaneous measurements of the radiation and cloud fields on a global basis to improve the understanding and modeling of the interaction between clouds and radiation at the top of the atmosphere, at the surface, and within the atmosphere. Cloud properties derived for CERES from the Moderate Resolution Imaging Spectroradiometer (MODIS) on the Terra and Aqua satellites are compared to ensure consistency between the products to ensure the reliability of the retrievals from multiple platforms at different times of day. Comparisons of cloud fraction, height, optical depth, phase, effective particle size, and ice and liquid water paths from the two satellites show excellent consistency. Initial calibration comparisons are also very favorable. Differences between the Aqua and Terra results are generally due to diurnally dependent changes in the clouds. Additional algorithm refinement is needed over the polar regions for Aqua and at night over those same areas for Terra. 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.

Normalization and calibration of geostationary satellite radiances for the International Satellite Cloud Climatology Project

Science.gov (United States)

Desormeaux, Yves; Rossow, William B.; Brest, Christopher L.; Campbell, G. G.

1993-01-01

Procedures are described for normalizing the radiometric calibration of image radiances obtained from geostationary weather satellites that contributed data to the International Satellite Cloud Climatology Project. The key step is comparison of coincident and collocated measurements made by each satellite and the concurrent AVHRR on the 'afternoon' NOAA polar-orbiting weather satellite at the same viewing geometry. The results of this comparison allow transfer of the AVHRR absolute calibration, which has been established over the whole series, to the radiometers on the geostationary satellites. Results are given for Meteosat-2, 3, and 4, for GOES-5, 6, and 7, for GMS-2, 3, and 4 and for Insat-1B. The relative stability of the calibrations of these radiance data is estimated to be within +/- 3 percent; the uncertainty of the absolute calibrations is estimated to be less than 10 percent. The remaining uncertainties are at least two times smaller than for the original radiance data.

Intercomparison of model simulations of mixed-phase clouds observed during the ARM Mixed-Phase Arctic Cloud Experiment. Part I: Single layer cloud

Energy Technology Data Exchange (ETDEWEB)

Klein, Stephen A.; McCoy, Renata B.; Morrison, Hugh; Ackerman, Andrew S.; Avramov, Alexander; de Boer, Gijs; Chen, Mingxuan; Cole, Jason N.S.; Del Genio, Anthony D.; Falk, Michael; Foster, Michael J.; Fridlind, Ann; Golaz, Jean-Christophe; Hashino, Tempei; Harrington, Jerry Y.; Hoose, Corinna; Khairoutdinov, Marat F.; Larson, Vincent E.; Liu, Xiaohong; Luo, Yali; McFarquhar, Greg M.; Menon, Surabi; Neggers, Roel A. J.; Park, Sungsu; Poellot, Michael R.; Schmidt, Jerome M.; Sednev, Igor; Shipway, Ben J.; Shupe, Matthew D.; Spangenberg, Douglas A.; Sud, Yogesh C.; Turner, David D.; Veron, Dana E.; von Salzen, Knut; Walker, Gregory K.; Wang, Zhien; Wolf, Audrey B.; Xie, Shaocheng; Xu, Kuan-Man; Yang, Fanglin; Zhang, Gong

2009-02-02

Results are presented from an intercomparison of single-column and cloud-resolving model simulations of a cold-air outbreak mixed-phase stratocumulus cloud observed during the Atmospheric Radiation Measurement (ARM) program's Mixed-Phase Arctic Cloud Experiment. The observed cloud occurred in a well-mixed boundary layer with a cloud top temperature of -15 C. The observed average liquid water path of around 160 g m{sup -2} was about two-thirds of the adiabatic value and much greater than the average mass of ice crystal precipitation which when integrated from the surface to cloud top was around 15 g m{sup -2}. The simulations were performed by seventeen single-column models (SCMs) and nine cloud-resolving models (CRMs). While the simulated ice water path is generally consistent with the observed values, the median SCM and CRM liquid water path is a factor of three smaller than observed. Results from a sensitivity study in which models removed ice microphysics suggest that in many models the interaction between liquid and ice-phase microphysics is responsible for the large model underestimate of liquid water path. Despite this general underestimate, the simulated liquid and ice water paths of several models are consistent with the observed values. Furthermore, there is evidence that models with more sophisticated microphysics simulate liquid and ice water paths that are in better agreement with the observed values, although considerable scatter is also present. Although no single factor guarantees a good simulation, these results emphasize the need for improvement in the model representation of mixed-phase microphysics.

Identifying clouds over the Pierre Auger Observatory using infrared satellite data

Energy Technology Data Exchange (ETDEWEB)

Abreu, Pedro; et al.,

2013-12-01

We describe a new method of identifying night-time clouds over the Pierre Auger Observatory using infrared data from the Imager instruments on the GOES-12 and GOES-13 satellites. We compare cloud identifications resulting from our method to those obtained by the Central Laser Facility of the Auger Observatory. Using our new method we can now develop cloud probability maps for the 3000 km^2 of the Pierre Auger Observatory twice per hour with a spatial resolution of ~2.4 km by ~5.5 km. Our method could also be applied to monitor cloud cover for other ground-based observatories and for space-based observatories.

Modeling the partitioning of organic chemical species in cloud phases with CLEPS (1.1)

Science.gov (United States)

Rose, Clémence; Chaumerliac, Nadine; Deguillaume, Laurent; Perroux, Hélène; Mouchel-Vallon, Camille; Leriche, Maud; Patryl, Luc; Armand, Patrick

2018-02-01

The new detailed aqueous-phase mechanism Cloud Explicit Physico-chemical Scheme (CLEPS 1.0), which describes the oxidation of isoprene-derived water-soluble organic compounds, is coupled with a warm microphysical module simulating the activation of aerosol particles into cloud droplets. CLEPS 1.0 was then extended to CLEPS 1.1 to include the chemistry of the newly added dicarboxylic acids dissolved from the particulate phase. The resulting coupled model allows the prediction of the aqueous-phase concentrations of chemical compounds originating from particle scavenging, mass transfer from the gas-phase and in-cloud aqueous chemical reactivity. The aim of the present study was more particularly to investigate the effect of particle scavenging on cloud chemistry. Several simulations were performed to assess the influence of various parameters on model predictions and to interpret long-term measurements conducted at the top of Puy de Dôme (PUY, France) in marine air masses. Specific attention was paid to carboxylic acids, whose predicted concentrations are on average in the lower range of the observations, with the exception of formic acid, which is rather overestimated in the model. The different sensitivity runs highlight the fact that formic and acetic acids mainly originate from the gas phase and have highly variable aqueous-phase reactivity depending on the cloud acidity, whereas C3-C4 carboxylic acids mainly originate from the particulate phase and are supersaturated in the cloud.

Satellite Observations of Volcanic Clouds from the Eruption of Redoubt Volcano, Alaska, 2009

Science.gov (United States)

Dean, K. G.; Ekstrand, A. L.; Webley, P.; Dehn, J.

2009-12-01

Redoubt Volcano began erupting on 23 March 2009 (UTC) and consisted of 19 events over a 14 day period. The volcano is located on the Alaska Peninsula, 175 km southwest of Anchorage, Alaska. The previous eruption was in 1989/1990 and seriously disrupted air traffic in the region, including the near catastrophic engine failure of a passenger airliner. Plumes and ash clouds from the recent eruption were observed on a variety of satellite data (AVHRR, MODIS and GOES). The eruption produced volcanic clouds up to 19 km which are some of the highest detected in recent times in the North Pacific region. The ash clouds primarily drifted north and east of the volcano, had a weak ash signal in the split window data and resulted in light ash falls in the Cook Inlet basin and northward into Alaska’s Interior. Volcanic cloud heights were measured using ground-based radar, and plume temperature and wind shear methods but each of the techniques resulted in significant variations in the estimates. Even though radar showed the greatest heights, satellite data and wind shears suggest that the largest concentrations of ash may be at lower altitudes in some cases. Sulfur dioxide clouds were also observed on satellite data (OMI, AIRS and Calipso) and they primarily drifted to the east and were detected at several locations across North America, thousands of kilometers from the volcano. Here, we show time series data collected by the Alaska Volcano Observatory, illustrating the different eruptive events and ash clouds that developed over the subsequent days.

SPATIOTEMPORAL VISUALIZATION OF TIME-SERIES SATELLITE-DERIVED CO2 FLUX DATA USING VOLUME RENDERING AND GPU-BASED INTERPOLATION ON A CLOUD-DRIVEN DIGITAL EARTH

Directory of Open Access Journals (Sweden)

S. Wu

2017-10-01

Full Text Available The ocean carbon cycle has a significant influence on global climate, and is commonly evaluated using time-series satellite-derived CO2 flux data. Location-aware and globe-based visualization is an important technique for analyzing and presenting the evolution of climate change. To achieve realistic simulation of the spatiotemporal dynamics of ocean carbon, a cloud-driven digital earth platform is developed to support the interactive analysis and display of multi-geospatial data, and an original visualization method based on our digital earth is proposed to demonstrate the spatiotemporal variations of carbon sinks and sources using time-series satellite data. Specifically, a volume rendering technique using half-angle slicing and particle system is implemented to dynamically display the released or absorbed CO2 gas. To enable location-aware visualization within the virtual globe, we present a 3D particlemapping algorithm to render particle-slicing textures onto geospace. In addition, a GPU-based interpolation framework using CUDA during real-time rendering is designed to obtain smooth effects in both spatial and temporal dimensions. To demonstrate the capabilities of the proposed method, a series of satellite data is applied to simulate the air-sea carbon cycle in the China Sea. The results show that the suggested strategies provide realistic simulation effects and acceptable interactive performance on the digital earth.

Unveiling aerosol-cloud interactions - Part 2: Minimising the effects of aerosol swelling and wet scavenging in ECHAM6-HAM2 for comparison to satellite data

Science.gov (United States)

Neubauer, David; Christensen, Matthew W.; Poulsen, Caroline A.; Lohmann, Ulrike

2017-11-01

Aerosol-cloud interactions (ACIs) are uncertain and the estimates of the ACI effective radiative forcing (ERFaci) magnitude show a large variability. Within the Aerosol_cci project the susceptibility of cloud properties to changes in aerosol properties is derived from the high-resolution AATSR (Advanced Along-Track Scanning Radiometer) data set using the Cloud-Aerosol Pairing Algorithm (CAPA) (as described in our companion paper) and compared to susceptibilities from the global aerosol climate model ECHAM6-HAM2 and MODIS-CERES (Moderate Resolution Imaging Spectroradiometer - Clouds and the Earth's Radiant Energy System) data. For ECHAM6-HAM2 the dry aerosol is analysed to mimic the effect of CAPA. Furthermore the analysis is done for different environmental regimes. The aerosol-liquid water path relationship in ECHAM6-HAM2 is systematically stronger than in AATSR-CAPA data and cannot be explained by an overestimation of autoconversion when using diagnostic precipitation but rather by aerosol swelling in regions where humidity is high and clouds are present. When aerosol water is removed from the analysis in ECHAM6-HAM2 the strength of the susceptibilities of liquid water path, cloud droplet number concentration and cloud albedo as well as ERFaci agree much better with those of AATSR-CAPA or MODIS-CERES. When comparing satellite-derived to model-derived susceptibilities, this study finds it more appropriate to use dry aerosol in the computation of model susceptibilities. We further find that the statistical relationships inferred from different satellite sensors (AATSR-CAPA vs. MODIS-CERES) as well as from ECHAM6-HAM2 are not always of the same sign for the tested environmental conditions. In particular the susceptibility of the liquid water path is negative in non-raining scenes for MODIS-CERES but positive for AATSR-CAPA and ECHAM6-HAM2. Feedback processes like cloud-top entrainment that are missing or not well represented in the model are therefore not well

Improved cloud parameterization for Arctic climate simulations based on satellite data

Science.gov (United States)

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

2015-04-01

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

Influence of satellite-derived photolysis rates and NOx emissions on Texas ozone modeling

Science.gov (United States)

Tang, W.; Cohan, D. S.; Pour-Biazar, A.; Lamsal, L. N.; White, A. T.; Xiao, X.; Zhou, W.; Henderson, B. H.; Lash, B. F.

2015-02-01

Uncertain photolysis rates and emission inventory impair the accuracy of state-level ozone (O3) regulatory modeling. Past studies have separately used satellite-observed clouds to correct the model-predicted photolysis rates, or satellite-constrained top-down NOx emissions to identify and reduce uncertainties in bottom-up NOx emissions. However, the joint application of multiple satellite-derived model inputs to improve O3 state implementation plan (SIP) modeling has rarely been explored. In this study, Geostationary Operational Environmental Satellite (GOES) observations of clouds are applied to derive the photolysis rates, replacing those used in Texas SIP modeling. This changes modeled O3 concentrations by up to 80 ppb and improves O3 simulations by reducing modeled normalized mean bias (NMB) and normalized mean error (NME) by up to 0.1. A sector-based discrete Kalman filter (DKF) inversion approach is incorporated with the Comprehensive Air Quality Model with extensions (CAMx)-decoupled direct method (DDM) model to adjust Texas NOx emissions using a high-resolution Ozone Monitoring Instrument (OMI) NO2 product. The discrepancy between OMI and CAMx NO2 vertical column densities (VCDs) is further reduced by increasing modeled NOx lifetime and adding an artificial amount of NO2 in the upper troposphere. The region-based DKF inversion suggests increasing NOx emissions by 10-50% in most regions, deteriorating the model performance in predicting ground NO2 and O3, while the sector-based DKF inversion tends to scale down area and nonroad NOx emissions by 50%, leading to a 2-5 ppb decrease in ground 8 h O3 predictions. Model performance in simulating ground NO2 and O3 are improved using sector-based inversion-constrained NOx emissions, with 0.25 and 0.04 reductions in NMBs and 0.13 and 0.04 reductions in NMEs, respectively. Using both GOES-derived photolysis rates and OMI-constrained NOx emissions together reduces modeled NMB and NME by 0.05, increases the model

A Cloud Top Pressure Algorithm for DSCOVR-EPIC

Science.gov (United States)

Min, Q.; Morgan, E. C.; Yang, Y.; Marshak, A.; Davis, A. B.

2017-12-01

The Earth Polychromatic Imaging Camera (EPIC) sensor on the Deep Space Climate Observatory (DSCOVR) satellite presents unique opportunities to derive cloud properties of the entire daytime Earth. In particular, the Oxygen A- and B-band and corresponding reference channels provide cloud top pressure information. In order to address the in-cloud penetration depth issue—and ensuing retrieval bias—a comprehensive sensitivity study has been conducted to simulate satellite-observed radiances for a wide variety of cloud structures and optical properties. Based on this sensitivity study, a cloud top pressure algorithm for DSCOVR-EPIC has been developed. Further, the algorithm has been applied to EPIC measurements.

Automatic Detection of Clouds and Shadows Using High Resolution Satellite Image Time Series

Science.gov (United States)

Champion, Nicolas

2016-06-01

Detecting clouds and their shadows is one of the primaries steps to perform when processing satellite images because they may alter the quality of some products such as large-area orthomosaics. The main goal of this paper is to present the automatic method developed at IGN-France for detecting clouds and shadows in a sequence of satellite images. In our work, surface reflectance orthoimages are used. They were processed from initial satellite images using a dedicated software. The cloud detection step consists of a region-growing algorithm. Seeds are firstly extracted. For that purpose and for each input ortho-image to process, we select the other ortho-images of the sequence that intersect it. The pixels of the input ortho-image are secondly labelled seeds if the difference of reflectance (in the blue channel) with overlapping ortho-images is bigger than a given threshold. Clouds are eventually delineated using a region-growing method based on a radiometric and homogeneity criterion. Regarding the shadow detection, our method is based on the idea that a shadow pixel is darker when comparing to the other images of the time series. The detection is basically composed of three steps. Firstly, we compute a synthetic ortho-image covering the whole study area. Its pixels have a value corresponding to the median value of all input reflectance ortho-images intersecting at that pixel location. Secondly, for each input ortho-image, a pixel is labelled shadows if the difference of reflectance (in the NIR channel) with the synthetic ortho-image is below a given threshold. Eventually, an optional region-growing step may be used to refine the results. Note that pixels labelled clouds during the cloud detection are not used for computing the median value in the first step; additionally, the NIR input data channel is used to perform the shadow detection, because it appeared to better discriminate shadow pixels. The method was tested on times series of Landsat 8 and Pl

AUTOMATIC DETECTION OF CLOUDS AND SHADOWS USING HIGH RESOLUTION SATELLITE IMAGE TIME SERIES

Directory of Open Access Journals (Sweden)

N. Champion

2016-06-01

Full Text Available Detecting clouds and their shadows is one of the primaries steps to perform when processing satellite images because they may alter the quality of some products such as large-area orthomosaics. The main goal of this paper is to present the automatic method developed at IGN-France for detecting clouds and shadows in a sequence of satellite images. In our work, surface reflectance orthoimages are used. They were processed from initial satellite images using a dedicated software. The cloud detection step consists of a region-growing algorithm. Seeds are firstly extracted. For that purpose and for each input ortho-image to process, we select the other ortho-images of the sequence that intersect it. The pixels of the input ortho-image are secondly labelled seeds if the difference of reflectance (in the blue channel with overlapping ortho-images is bigger than a given threshold. Clouds are eventually delineated using a region-growing method based on a radiometric and homogeneity criterion. Regarding the shadow detection, our method is based on the idea that a shadow pixel is darker when comparing to the other images of the time series. The detection is basically composed of three steps. Firstly, we compute a synthetic ortho-image covering the whole study area. Its pixels have a value corresponding to the median value of all input reflectance ortho-images intersecting at that pixel location. Secondly, for each input ortho-image, a pixel is labelled shadows if the difference of reflectance (in the NIR channel with the synthetic ortho-image is below a given threshold. Eventually, an optional region-growing step may be used to refine the results. Note that pixels labelled clouds during the cloud detection are not used for computing the median value in the first step; additionally, the NIR input data channel is used to perform the shadow detection, because it appeared to better discriminate shadow pixels. The method was tested on times series of Landsat 8

Synergetic cloud fraction determination for SCIAMACHY using MERIS

Directory of Open Access Journals (Sweden)

C. Schlundt

2011-02-01

Full Text Available Since clouds play an essential role in the Earth's climate system, it is important to understand the cloud characteristics as well as their distribution on a global scale using satellite observations. The main scientific objective of SCIAMACHY (SCanning Imaging Absorption spectroMeter for Atmospheric CHartographY onboard the ENVISAT satellite is the retrieval of vertical columns of trace gases.

On the one hand, SCIAMACHY has to be sensitive to low variations in trace gas concentrations which means the ground pixel size has to be large enough. On the other hand, such a large pixel size leads to the problem that SCIAMACHY spectra are often contaminated by clouds. SCIAMACHY spectral measurements are not well suitable to derive a reliable sub-pixel cloud fraction that can be used as input parameter for subsequent retrievals of cloud properties or vertical trace gas columns. Therefore, we use MERIS/ENVISAT spectral measurements with its high spatial resolution as sub-pixel information for the determination of MerIs Cloud fRation fOr Sciamachy (MICROS. Since MERIS covers an even broader swath width than SCIAMACHY, no problems in spatial and temporal collocation of measurements occur. This enables the derivation of a SCIAMACHY cloud fraction with an accuracy much higher as compared with other current cloud fractions that are based on SCIAMACHY's PMD (Polarization Measurement Device data.

We present our new developed MICROS algorithm, based on the threshold approach, as well as a qualitative validation of our results with MERIS satellite images for different locations, especially with respect to bright surfaces such as snow/ice and sands. In addition, the SCIAMACHY cloud fractions derived from MICROS are intercompared with other current SCIAMACHY cloud fractions based on different approaches demonstrating a considerable improvement regarding geometric cloud fraction determination using the MICROS algorithm.

Estimates of radiation over clouds and dust aerosols: Optimized number of terms in phase function expansion

International Nuclear Information System (INIS)

Ding Shouguo; Xie Yu; Yang Ping; Weng Fuzhong; Liu Quanhua; Baum, Bryan; Hu Yongxiang

2009-01-01

The bulk-scattering properties of dust aerosols and clouds are computed for the community radiative transfer model (CRTM) that is a flagship effort of the Joint Center for Satellite Data Assimilation (JCSDA). The delta-fit method is employed to truncate the forward peaks of the scattering phase functions and to compute the Legendre expansion coefficients for re-constructing the truncated phase function. Use of more terms in the expansion gives more accurate re-construction of the phase function, but the issue remains as to how many terms are necessary for different applications. To explore this issue further, the bidirectional reflectances associated with dust aerosols, water clouds, and ice clouds are simulated with various numbers of Legendre expansion terms. To have relative numerical errors smaller than 5%, the present analyses indicate that, in the visible spectrum, 16 Legendre polynomials should be used for dust aerosols, while 32 Legendre expansion terms should be used for both water and ice clouds. In the infrared spectrum, the brightness temperatures at the top of the atmosphere are computed by using the scattering properties of dust aerosols, water clouds and ice clouds. Although small differences of brightness temperatures compared with the counterparts computed with 4, 8, 128 expansion terms are observed at large viewing angles for each layer, it is shown that 4 terms of Legendre polynomials are sufficient in the radiative transfer computation at infrared wavelengths for practical applications.

New insight of Arctic cloud parameterization from regional climate model simulations, satellite-based, and drifting station data

Science.gov (United States)

Klaus, D.; Dethloff, K.; Dorn, W.; Rinke, A.; Wu, D. L.

2016-05-01

Cloud observations from the CloudSat and CALIPSO satellites helped to explain the reduced total cloud cover (Ctot) in the atmospheric regional climate model HIRHAM5 with modified cloud physics. Arctic climate conditions are found to be better reproduced with (1) a more efficient Bergeron-Findeisen process and (2) a more generalized subgrid-scale variability of total water content. As a result, the annual cycle of Ctot is improved over sea ice, associated with an almost 14% smaller area average than in the control simulation. The modified cloud scheme reduces the Ctot bias with respect to the satellite observations. Except for autumn, the cloud reduction over sea ice improves low-level temperature profiles compared to drifting station data. The HIRHAM5 sensitivity study highlights the need for improving accuracy of low-level (<700 m) cloud observations, as these clouds exert a strong impact on the near-surface climate.

Application of INSAT Satellite Cloud-Imagery Data for Site ...

Indian Academy of Sciences (India)

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Application of INSAT Satellite Cloud-Imagery Data for Site Evaluation. Work of ... sources like Cyg X-3 and AM-Her binary systems (Bhat et al. 1986; Bhat et al. ... one is dealing with in the very high energy (VHE) and ultra high energy (UHE) .... shows the monthly distribution of 'spectroscopic' hours averaged over the 5-year.

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

Science.gov (United States)

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

2018-01-18

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

GEWEX cloud assessment: A review

Science.gov (United States)

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

2013-05-01

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

Improving Mixed-phase Cloud Parameterization in Climate Model with the ACRF Measurements

Energy Technology Data Exchange (ETDEWEB)

Wang, Zhien [Univ. of Wyoming, Laramie, WY (United States)

2016-12-13

Mixed-phase cloud microphysical and dynamical processes are still poorly understood, and their representation in GCMs is a major source of uncertainties in overall cloud feedback in GCMs. Thus improving mixed-phase cloud parameterizations in climate models is critical to reducing the climate forecast uncertainties. This study aims at providing improved knowledge of mixed-phase cloud properties from the long-term ACRF observations and improving mixed-phase clouds simulations in the NCAR Community Atmosphere Model version 5 (CAM5). The key accomplishments are: 1) An improved retrieval algorithm was developed to provide liquid droplet concentration for drizzling or mixed-phase stratiform clouds. 2) A new ice concentration retrieval algorithm for stratiform mixed-phase clouds was developed. 3) A strong seasonal aerosol impact on ice generation in Arctic mixed-phase clouds was identified, which is mainly attributed to the high dust occurrence during the spring season. 4) A suite of multi-senor algorithms was applied to long-term ARM observations at the Barrow site to provide a complete dataset (LWC and effective radius profile for liquid phase, and IWC, Dge profiles and ice concentration for ice phase) to characterize Arctic stratiform mixed-phase clouds. This multi-year stratiform mixed-phase cloud dataset provides necessary information to study related processes, evaluate model stratiform mixed-phase cloud simulations, and improve model stratiform mixed-phase cloud parameterization. 5). A new in situ data analysis method was developed to quantify liquid mass partition in convective mixed-phase clouds. For the first time, we reliably compared liquid mass partitions in stratiform and convective mixed-phase clouds. Due to the different dynamics in stratiform and convective mixed-phase clouds, the temperature dependencies of liquid mass partitions are significantly different due to much higher ice concentrations in convective mixed phase clouds. 6) Systematic evaluations

Optical and geometrical properties of cirrus clouds in Amazonia derived from 1 year of ground-based lidar measurements

Science.gov (United States)

Gouveia, Diego A.; Barja, Boris; Barbosa, Henrique M. J.; Seifert, Patric; Baars, Holger; Pauliquevis, Theotonio; Artaxo, Paulo

2017-03-01

Cirrus clouds cover a large fraction of tropical latitudes and play an important role in Earth's radiation budget. Their optical properties, altitude, vertical and horizontal coverage control their radiative forcing, and hence detailed cirrus measurements at different geographical locations are of utmost importance. Studies reporting cirrus properties over tropical rain forests like the Amazon, however, are scarce. Studies with satellite profilers do not give information on the diurnal cycle, and the satellite imagers do not report on the cloud vertical structure. At the same time, ground-based lidar studies are restricted to a few case studies. In this paper, we derive the first comprehensive statistics of optical and geometrical properties of upper-tropospheric cirrus clouds in Amazonia. We used 1 year (July 2011 to June 2012) of ground-based lidar atmospheric observations north of Manaus, Brazil. This dataset was processed by an automatic cloud detection and optical properties retrieval algorithm. Upper-tropospheric cirrus clouds were observed more frequently than reported previously for tropical regions. The frequency of occurrence was found to be as high as 88 % during the wet season and not lower than 50 % during the dry season. The diurnal cycle shows a minimum around local noon and maximum during late afternoon, associated with the diurnal cycle of precipitation. The mean values of cirrus cloud top and base heights, cloud thickness, and cloud optical depth were 14.3 ± 1.9 (SD) km, 12.9 ± 2.2 km, 1.4 ± 1.1 km, and 0.25 ± 0.46, respectively. Cirrus clouds were found at temperatures down to -90 °C. Frequently cirrus were observed within the tropical tropopause layer (TTL), which are likely associated to slow mesoscale uplifting or to the remnants of overshooting convection. The vertical distribution was not uniform, and thin and subvisible cirrus occurred more frequently closer to the tropopause. The mean lidar ratio was 23.3 ± 8.0 sr. However, for

Combining structure-from-motion derived point clouds from satellites and unmanned aircraft systems images with ground-truth data to create high-resolution digital elevation models

Science.gov (United States)

Palaseanu, M.; Thatcher, C.; Danielson, J.; Gesch, D. B.; Poppenga, S.; Kottermair, M.; Jalandoni, A.; Carlson, E.

2016-12-01

Coastal topographic and bathymetric (topobathymetric) data with high spatial resolution (1-meter or better) and high vertical accuracy are needed to assess the vulnerability of Pacific Islands to climate change impacts, including sea level rise. According to the Intergovernmental Panel on Climate Change reports, low-lying atolls in the Pacific Ocean are extremely vulnerable to king tide events, storm surge, tsunamis, and sea-level rise. The lack of coastal topobathymetric data has been identified as a critical data gap for climate vulnerability and adaptation efforts in the Republic of the Marshall Islands (RMI). For Majuro Atoll, home to the largest city of RMI, the only elevation dataset currently available is the Shuttle Radar Topography Mission data which has a 30-meter spatial resolution and 16-meter vertical accuracy (expressed as linear error at 90%). To generate high-resolution digital elevation models (DEMs) in the RMI, elevation information and photographic imagery have been collected from field surveys using GNSS/total station and unmanned aerial vehicles for Structure-from-Motion (SfM) point cloud generation. Digital Globe WorldView II imagery was processed to create SfM point clouds to fill in gaps in the point cloud derived from the higher resolution UAS photos. The combined point cloud data is filtered and classified to bare-earth and georeferenced using the GNSS data acquired on roads and along survey transects perpendicular to the coast. A total station was used to collect elevation data under tree canopies where heavy vegetation cover blocked the view of GNSS satellites. A subset of the GPS / total station data was set aside for error assessment of the resulting DEM.

Classification of Arctic, Mid-Latitude and Tropical Clouds in the Mixed-Phase Temperature Regime

Science.gov (United States)

Costa, Anja; Afchine, Armin; Luebke, Anna; Meyer, Jessica; Dorsey, James R.; Gallagher, Martin W.; Ehrlich, André; Wendisch, Manfred; Krämer, Martina

2016-04-01

The degree of glaciation and the sizes and habits of ice particles formed in mixed-phase clouds remain not fully understood. However, these properties define the mixed clouds' radiative impact on the Earth's climate and thus a correct representation of this cloud type in global climate models is of importance for an improved certainty of climate predictions. This study focuses on the occurrence and characteristics of two types of clouds in the mixed-phase temperature regime (238-275K): coexistence clouds (Coex), in which both liquid drops and ice crystals exist, and fully glaciated clouds that develop in the Wegener-Bergeron-Findeisen regime (WBF clouds). We present an extensive dataset obtained by the Cloud and Aerosol Particle Spectrometer NIXE-CAPS, covering Arctic, mid-latitude and tropical regions. In total, we spent 45.2 hours within clouds in the mixed-phase temperature regime during five field campaigns (Arctic: VERDI, 2012 and RACEPAC, 2014 - Northern Canada; mid-latitude: COALESC, 2011 - UK and ML-Cirrus, 2014 - central Europe; tropics: ACRIDICON, 2014 - Brazil). We show that WBF and Coex clouds can be identified via cloud particle size distributions. The classified datasets are used to analyse temperature dependences of both cloud types as well as range and frequencies of cloud particle concentrations and sizes. One result is that Coex clouds containing supercooled liquid drops are found down to temperatures of -40 deg C only in tropical mixed clouds, while in the Arctic and mid-latitudes no liquid drops are observed below about -20 deg C. In addition, we show that the cloud particles' aspherical fractions - derived from polarization signatures of particles with diameters between 20 and 50 micrometers - differ significantly between WBF and Coex clouds. In Coex clouds, the aspherical fraction of cloud particles is generally very low, but increases with decreasing temperature. In WBF clouds, where all cloud particles are ice, about 20-40% of the cloud

Cloud Detection from Satellite Imagery: A Comparison of Expert-Generated and Automatically-Generated Decision Trees

Science.gov (United States)

Shiffman, Smadar

2004-01-01

Automated cloud detection and tracking is an important step in assessing global climate change via remote sensing. Cloud masks, which indicate whether individual pixels depict clouds, are included in many of the data products that are based on data acquired on- board earth satellites. Many cloud-mask algorithms have the form of decision trees, which employ sequential tests that scientists designed based on empirical astrophysics studies and astrophysics simulations. Limitations of existing cloud masks restrict our ability to accurately track changes in cloud patterns over time. In this study we explored the potential benefits of automatically-learned decision trees for detecting clouds from images acquired using the Advanced Very High Resolution Radiometer (AVHRR) instrument on board the NOAA-14 weather satellite of the National Oceanic and Atmospheric Administration. We constructed three decision trees for a sample of 8km-daily AVHRR data from 2000 using a decision-tree learning procedure provided within MATLAB(R), and compared the accuracy of the decision trees to the accuracy of the cloud mask. We used ground observations collected by the National Aeronautics and Space Administration Clouds and the Earth s Radiant Energy Systems S COOL project as the gold standard. For the sample data, the accuracy of automatically learned decision trees was greater than the accuracy of the cloud masks included in the AVHRR data product.

[Application of single-band brightness variance ratio to the interference dissociation of cloud for satellite data].

Science.gov (United States)

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.

Comparison of the peak resolution and the stationary phase retention between the satellite and the planetary motions using the coil satellite centrifuge with counter-current chromatographic separation of 4-methylumbelliferyl sugar derivatives.

Science.gov (United States)

Shinomiya, Kazufusa; Zaima, Kazumasa; Harada, Yukina; Yasue, Miho; Harikai, Naoki; Tokura, Koji; Ito, Yoichiro

2017-01-20

Coil satellite centrifuge (CSC) produces the complex satellite motion consisting of the triplicate rotation of the coiled column around three axes including the sun axis (the angular velocity, ω 1 ), the planet axis (ω 2 ) and the satellite axis (the central axis of the column) (ω 3 ) according to the following formula: ω 1 =ω 2 +ω 3 . Improved peak resolution in the separation of 4-methylumbelliferyl sugar derivatives was achieved using the conventional multilayer coiled columns with ethyl acetate/1-butanol/water (3: 2: 5, v/v) for the lower mobile phase at the combination of the rotation speeds (ω 1 , ω 2 , ω 3 )=(300, 150, 150rpm), and (1:4:5, v/v) for the upper mobile phase at (300:100:200rpm). The effect of the satellite motion on the peak resolution and the stationary phase retention was evaluated by each CSC separation with the different rotation speeds of ω 2 and ω 3 under the constant revolution speed at ω 1 =300rpm. With the lower mobile phase, almost constant peak resolution and stationary phase retention were yielded regardless of the change of ω 2 and ω 3 , while with the upper mobile phase these two values were sensitively varied according to the different combination of ω 2 and ω 3 . For example, when ω 2 =147 or 200rpm is used, no stationary phase was retained in the coiled column while ω 2 =150rpm could retain enough volume of stationary phase for separation. On the other hand, the combined rotation speeds at (ω 1 , ω 2 , ω 3 )=(300, 300, 0rpm) or (300, 0, 300rpm) produced insufficient peak resolution regardless of the choice of the mobile phase apparently due to the lack of rotation speed except at (300, 0, 300rpm) with the upper mobile phase. At lower rotation speed of ω 1 =300rpm, better peak resolution and stationary phase retention were obtained by the satellite motion (ω 3 ) than by the planetary motion (ω 2 ), or ω 3 >ω 2 . The effect of the hydrophobicity of the two-phase solvent systems on the stationary phase

Intercomparison between CMIP5 model and MODIS satellite-retrieved data of aerosol optical depth, cloud fraction, and cloud-aerosol interactions

Science.gov (United States)

Sockol, Alyssa; Small Griswold, Jennifer D.

2017-08-01

Aerosols are a critical component of the Earth's atmosphere and can affect the climate of the Earth through their interactions with solar radiation and clouds. Cloud fraction (CF) and aerosol optical depth (AOD) at 550 nm from the Moderate Resolution Imaging Spectroradiometer (MODIS) are used with analogous cloud and aerosol properties from Historical Phase 5 of the Coupled Model Intercomparison Project (CMIP5) model runs that explicitly include anthropogenic aerosols and parameterized cloud-aerosol interactions. The models underestimate AOD by approximately 15% and underestimate CF by approximately 10% overall on a global scale. A regional analysis is then used to evaluate model performance in two regions with known biomass burning activity and absorbing aerosol (South America (SAM) and South Africa (SAF)). In SAM, the models overestimate AOD by 4.8% and underestimate CF by 14%. In SAF, the models underestimate AOD by 35% and overestimate CF by 13.4%. Average annual cycles show that the monthly timing of AOD peaks closely match satellite data in both SAM and SAF for all except the Community Atmosphere Model 5 and Geophysical Fluid Dynamics Laboratory (GFDL) models. Monthly timing of CF peaks closely match for all models (except GFDL) for SAM and SAF. Sorting monthly averaged 2° × 2.5° model or MODIS CF as a function of AOD does not result in the previously observed "boomerang"-shaped CF versus AOD relationship characteristic of regions with absorbing aerosols from biomass burning. Cloud-aerosol interactions, as observed using daily (or higher) temporal resolution data, are not reproducible at the spatial or temporal resolution provided by the CMIP5 models.

Point Cloud Based Relative Pose Estimation of a Satellite in Close Range

Directory of Open Access Journals (Sweden)

Lujiang Liu

2016-06-01

Full Text Available Determination of the relative pose of satellites is essential in space rendezvous operations and on-orbit servicing missions. The key problems are the adoption of suitable sensor on board of a chaser and efficient techniques for pose estimation. This paper aims to estimate the pose of a target satellite in close range on the basis of its known model by using point cloud data generated by a flash LIDAR sensor. A novel model based pose estimation method is proposed; it includes a fast and reliable pose initial acquisition method based on global optimal searching by processing the dense point cloud data directly, and a pose tracking method based on Iterative Closest Point algorithm. Also, a simulation system is presented in this paper in order to evaluate the performance of the sensor and generate simulated sensor point cloud data. It also provides truth pose of the test target so that the pose estimation error can be quantified. To investigate the effectiveness of the proposed approach and achievable pose accuracy, numerical simulation experiments are performed; results demonstrate algorithm capability of operating with point cloud directly and large pose variations. Also, a field testing experiment is conducted and results show that the proposed method is effective.

Towards a Three-Dimensional Near-Real Time Cloud Product for Aviation Safety and Weather Diagnoses

Science.gov (United States)

Minnis, Patrick; Nguyen, Louis; Palikonda, Rabindra; Spangeberg, Douglas; Nordeen, Michele L.; Yi, Yu-Hong; Ayers, J. Kirk

2004-01-01

Satellite data have long been used for determining the extent of cloud cover and for estimating the properties at the cloud tops. The derived properties can also be used to estimate aircraft icing potential to improve the safety of air traffic in the region. Currently, cloud properties and icing potential are derived in near-real time over the United States of America (USA) from the Geostationary Operational Environmental Satellite GOES) imagers at 75 W and 135 W. Traditionally, the results have been given in two dimensions because of the lack of knowledge about the vertical extent of clouds and the occurrence of overlapping clouds. Aircraft fly in a three-dimensional space and require vertical as well as horizontal information about clouds, their intensity, and their potential for icing. To improve the vertical component of the derived cloud and icing parameters, this paper explores various methods and datasets for filling in the three-dimensional space over the USA with cloud water.

Landsat 7 ETM/1G satellite imagery - Hawaiian Islands cloud-free mosaics

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — Cloud-free Landsat satellite imagery mosaics of the islands of the main 8 Hawaiian Islands (Hawaii, Maui, Kahoolawe, Lanai, Molokai, Oahu, Kauai and Niihau). Landsat...

Comparison of Monthly Mean Cloud Fraction and Cloud Optical depth Determined from Surface Cloud Radar, TOVS, AVHRR, and MODIS over Barrow, Alaska

Science.gov (United States)

Uttal, Taneil; Frisch, Shelby; Wang, Xuan-Ji; Key, Jeff; Schweiger, Axel; Sun-Mack, Sunny; Minnis, Patrick

2005-01-01

A one year comparison is made of mean monthly values of cloud fraction and cloud optical depth over Barrow, Alaska (71 deg 19.378 min North, 156 deg 36.934 min West) between 35 GHz radar-based retrievals, the TOVS Pathfinder Path-P product, the AVHRR APP-X product, and a MODIS based cloud retrieval product from the CERES-Team. The data sets represent largely disparate spatial and temporal scales, however, in this paper, the focus is to provide a preliminary analysis of how the mean monthly values derived from these different data sets compare, and determine how they can best be used separately, and in combination to provide reliable estimates of long-term trends of changing cloud properties. The radar and satellite data sets described here incorporate Arctic specific modifications that account for cloud detection challenges specific to the Arctic environment. The year 2000 was chosen for this initial comparison because the cloud radar data was particularly continuous and reliable that year, and all of the satellite retrievals of interest were also available for the year 2000. Cloud fraction was chosen as a comparison variable as accurate detection of cloud is the primary product that is necessary for any other cloud property retrievals. Cloud optical depth was additionally selected as it is likely the single cloud property that is most closely correlated to cloud influences on surface radiation budgets.

Derivation and evaluation of land surface temperature from the geostationary operational environmental satellite series

Science.gov (United States)

Fang, Li

according to the characteristics of the imager onboard the GOES series. For the GOES 8-11 and GOES R series with split window (SW) channels, a new temperature and emissivity separation (TES) approach was proposed for deriving LST and LSE simultaneously by using multiple-temporal satellite observations. Two split-window regression formulas were selected for this approach, and two satellite observations over the same geo-location within a certain time interval were utilized. This method is particularly applicable to geostationary satellite missions from which qualified multiple-temporal observations are available. For the GOES M(12)-Q series without SW channels, the dual-window LST algorithm was adopted to derive LST. Instead of using the conventional training method to generate coefficients for the LST regression algorithms, a machine training technique was introduced to automatically select the criteria and the boundary of the sub-ranges for generating algorithm coefficients under different conditions. A software package was developed to produce a brand new GOES LST product from both operational GOES measurements and historical archive. The system layers of the software and related system input and output were illustrated in this work. Comprehensive evaluation of GOES LST products was conducted by validating products against multiple ground-based LST observations, LST products from fine-resolution satellites (e.g. MODIS) and GSIP LST products. The key issues relevant to the cloud diffraction effect were studied as well. GOES measurements as well as ancillary data, including satellite and solar geometry, water vapor, cloud mask, land emissivity etc., were collected to generate GOES LST products. In addition, multiple in situ temperature measurements were collected to test the performance of the proposed GOES LST retrieval algorithms. The ground-based dataset included direct surface temperature measurements from the Atmospheric Radiation Measurement program (ARM), and

Impact of Antarctic mixed-phase clouds on climate.

Science.gov (United States)

Lawson, R Paul; Gettelman, Andrew

2014-12-23

Precious little is known about the composition of low-level clouds over the Antarctic Plateau and their effect on climate. In situ measurements at the South Pole using a unique tethered balloon system and ground-based lidar reveal a much higher than anticipated incidence of low-level, mixed-phase clouds (i.e., consisting of supercooled liquid water drops and ice crystals). The high incidence of mixed-phase clouds is currently poorly represented in global climate models (GCMs). As a result, the effects that mixed-phase clouds have on climate predictions are highly uncertain. We modify the National Center for Atmospheric Research (NCAR) Community Earth System Model (CESM) GCM to align with the new observations and evaluate the radiative effects on a continental scale. The net cloud radiative effects (CREs) over Antarctica are increased by +7.4 Wm(-2), and although this is a significant change, a much larger effect occurs when the modified model physics are extended beyond the Antarctic continent. The simulations show significant net CRE over the Southern Ocean storm tracks, where recent measurements also indicate substantial regions of supercooled liquid. These sensitivity tests confirm that Southern Ocean CREs are strongly sensitive to mixed-phase clouds colder than -20 °C.

Cloud-based Web Services for Near-Real-Time Web access to NPP Satellite Imagery and other Data

Science.gov (United States)

Evans, J. D.; Valente, E. G.

2010-12-01

We are building a scalable, cloud computing-based infrastructure for Web access to near-real-time data products synthesized from the U.S. National Polar-Orbiting Environmental Satellite System (NPOESS) Preparatory Project (NPP) and other geospatial and meteorological data. Given recent and ongoing changes in the the NPP and NPOESS programs (now Joint Polar Satellite System), the need for timely delivery of NPP data is urgent. We propose an alternative to a traditional, centralized ground segment, using distributed Direct Broadcast facilities linked to industry-standard Web services by a streamlined processing chain running in a scalable cloud computing environment. Our processing chain, currently implemented on Amazon.com's Elastic Compute Cloud (EC2), retrieves raw data from NASA's Moderate Resolution Imaging Spectroradiometer (MODIS) and synthesizes data products such as Sea-Surface Temperature, Vegetation Indices, etc. The cloud computing approach lets us grow and shrink computing resources to meet large and rapid fluctuations (twice daily) in both end-user demand and data availability from polar-orbiting sensors. Early prototypes have delivered various data products to end-users with latencies between 6 and 32 minutes. We have begun to replicate machine instances in the cloud, so as to reduce latency and maintain near-real time data access regardless of increased data input rates or user demand -- all at quite moderate monthly costs. Our service-based approach (in which users invoke software processes on a Web-accessible server) facilitates access into datasets of arbitrary size and resolution, and allows users to request and receive tailored and composite (e.g., false-color multiband) products on demand. To facilitate broad impact and adoption of our technology, we have emphasized open, industry-standard software interfaces and open source software. Through our work, we envision the widespread establishment of similar, derived, or interoperable systems for

Comparison of the characteristic energy of precipitating electrons derived from ground-based and DMSP satellite data

Directory of Open Access Journals (Sweden)

M. Ashrafi

2005-01-01

Full Text Available Energy maps are important for ionosphere-magnetosphere coupling studies, because quantitative determination of field-aligned currents requires knowledge of the conductances and their spatial gradients. By combining imaging riometer absorption and all-sky auroral optical data it is possible to produce high temporal and spatial resolution maps of the Maxwellian characteristic energy of precipitating electrons within a 240240 common field of view. These data have been calibrated by inverting EISCAT electron density profiles into equivalent energy spectra. In this paper energy maps produced by ground-based instruments (optical and riometer are compared with DMSP satellite data during geomagnetic conjunctions. For the period 1995-2002, twelve satellite passes over the ground-based instruments' field of view for the cloud-free conditions have been considered. Four of the satellite conjunctions occurred during moderate geomagnetic, steady-state conditions and without any ion precipitation. In these cases with Maxwellian satellite spectra, there is 71% agreement between the characteristic energies derived from the satellite and the ground-based energy map method.

Comparison of the characteristic energy of precipitating electrons derived from ground-based and DMSP satellite data

Directory of Open Access Journals (Sweden)

M. Ashrafi

2005-01-01

Full Text Available Energy maps are important for ionosphere-magnetosphere coupling studies, because quantitative determination of field-aligned currents requires knowledge of the conductances and their spatial gradients. By combining imaging riometer absorption and all-sky auroral optical data it is possible to produce high temporal and spatial resolution maps of the Maxwellian characteristic energy of precipitating electrons within a 240240 common field of view. These data have been calibrated by inverting EISCAT electron density profiles into equivalent energy spectra. In this paper energy maps produced by ground-based instruments (optical and riometer are compared with DMSP satellite data during geomagnetic conjunctions. For the period 1995-2002, twelve satellite passes over the ground-based instruments' field of view for the cloud-free conditions have been considered. Four of the satellite conjunctions occurred during moderate geomagnetic, steady-state conditions and without any ion precipitation. In these cases with Maxwellian satellite spectra, there is 71% agreement between the characteristic energies derived from the satellite and the ground-based energy map method.

Quantifying the clear-sky bias of satellite-derived infrared LST

Science.gov (United States)

Ermida, S. L.; Trigo, I. F.; DaCamara, C.

2017-12-01

Land surface temperature (LST) is one of the most relevant parameters when addressing the physical processes that take place at the surface of the Earth. Satellite data are particularly appropriate for measuring LST over the globe with high temporal resolution. Remote-sensed LST estimation from space-borne sensors has been systematically performed over the Globe for nearly 3 decades and geostationary LST climate data records are now available. The retrieval of LST from satellite observations generally relies on measurements in the thermal infrared (IR) window. Although there is a large number of IR sensors on-board geostationary satellites and polar orbiters suitable for LST retrievals with different temporal and spatial resolutions, the use of IR observations limits LST estimates to clear sky conditions. As a consequence, climate studies based on IR LST are likely to be affected by the restriction of LST data to cloudless conditions. However, such "clear sky bias" has never been quantified and, therefore, the actual impact of relying only on clear sky data is still to be determined. On the other hand, an "all-weather" global LST database may be set up based on passive microwave (MW) measurements which are much less affected by clouds. An 8-year record of all-weather MW LST is here used to quantify the clear-sky bias of IR LST at global scale based on MW observations performed by the Advanced Microwave Scanning Radiometer-Earth Observing System (AMSR-E) onboard NASA's Aqua satellite. Selection of clear-sky and cloudy pixels is based on information derived from measurements performed by the Moderate Resolution Imaging Spectroradiometer (MODIS) on-board the same satellite.

Evaluation of satellite derived spectral diffuse attenuation coefficients

Digital Repository Service at National Institute of Oceanography (India)

Suresh, T.; Talaulikar, M.; Desa, E.; Mascarenhas, A.A.M.Q.; Matondkar, S.G.P.

, 443, 490, 510, 555 and 670 nm derived from the ocean color satellite sensor, SeaWiFS with the in-situ measured values from the Arabian Sea is compared. The satellite derived values are found to be comparable to the measured values in the lower...

Intercomparison of aerosol-cloud-precipitation interactions in stratiform orographic mixed-phase clouds

Science.gov (United States)

Muhlbauer, A.; Hashino, T.; Xue, L.; Teller, A.; Lohmann, U.; Rasmussen, R. M.; Geresdi, I.; Pan, Z.

2010-09-01

Anthropogenic aerosols serve as a source of both cloud condensation nuclei (CCN) and ice nuclei (IN) and affect microphysical properties of clouds. Increasing aerosol number concentrations is hypothesized to retard the cloud droplet coalescence and the riming in mixed-phase clouds, thereby decreasing orographic precipitation. This study presents results from a model intercomparison of 2-D simulations of aerosol-cloud-precipitation interactions in stratiform orographic mixed-phase clouds. The sensitivity of orographic precipitation to changes in the aerosol number concentrations is analysed and compared for various dynamical and thermodynamical situations. Furthermore, the sensitivities of microphysical processes such as coalescence, aggregation, riming and diffusional growth to changes in the aerosol number concentrations are evaluated and compared. The participating numerical models are the model from the Consortium for Small-Scale Modeling (COSMO) with bulk microphysics, the Weather Research and Forecasting (WRF) model with bin microphysics and the University of Wisconsin modeling system (UWNMS) with a spectral ice habit prediction microphysics scheme. All models are operated on a cloud-resolving scale with 2 km horizontal grid spacing. The results of the model intercomparison suggest that the sensitivity of orographic precipitation to aerosol modifications varies greatly from case to case and from model to model. Neither a precipitation decrease nor a precipitation increase is found robustly in all simulations. Qualitative robust results can only be found for a subset of the simulations but even then quantitative agreement is scarce. Estimates of the aerosol effect on orographic precipitation are found to range from -19% to 0% depending on the simulated case and the model. Similarly, riming is shown to decrease in some cases and models whereas it increases in others, which implies that a decrease in riming with increasing aerosol load is not a robust result

A comparison of ground and satellite observations of cloud cover to saturation pressure differences during a cold air outbreak

Energy Technology Data Exchange (ETDEWEB)

Alliss, R.J.; Raman, S. [North Carolina State Univ., Raleigh, NC (United States)

1996-04-01

The role of clouds in the atmospheric general circulation and the global climate is twofold. First, clouds owe their origin to large-scale dynamical forcing, radiative cooling in the atmosphere, and turbulent transfer at the surface. In addition, they provide one of the most important mechanisms for the vertical redistribution of momentum and sensible and latent heat for the large scale, and they influence the coupling between the atmosphere and the surface as well as the radiative and dynamical-hydrological balance. In existing diagnostic cloudiness parameterization schemes, relative humidity is the most frequently used variable for estimating total cloud amount or stratiform cloud amount. However, the prediction of relative humidity in general circulation models (GCMs) is usually poor. Even for the most comprehensive GCMs, the predicted relative humidity may deviate greatly from that observed, as far as the frequency distribution of relative humidity is concerned. Recently, there has been an increased effort to improve the representation of clouds and cloud-radiation feedback in GCMs, but the verification of cloudiness parameterization schemes remains a severe problem because of the lack of observational data sets. In this study, saturation pressure differences (as opposed to relative humidity) and satellite-derived cloud heights and amounts are compared with ground determinations of cloud cover over the Gulf Stream Locale (GSL) during a cold air outbreak.

Sea ice-atmospheric interaction: Application of multispectral satellite data in polar surface energy flux estimates

Science.gov (United States)

Steffen, Konrad; Key, J.; Maslanik, J.; Schweiger, A.

1993-01-01

This is the third annual report on: Sea Ice-Atmosphere Interaction - Application of Multispectral Satellite Data in Polar Surface Energy Flux Estimates. The main emphasis during the past year was on: radiative flux estimates from satellite data; intercomparison of satellite and ground-based cloud amounts; radiative cloud forcing; calibration of the Advanced Very High Resolution Radiometer (AVHRR) visible channels and comparison of two satellite derived albedo data sets; and on flux modeling for leads. Major topics covered are arctic clouds and radiation; snow and ice albedo, and leads and modeling.

Multi-sensor measurements of mixed-phase clouds above Greenland

Science.gov (United States)

Stillwell, Robert A.; Shupe, Matthew D.; Thayer, Jeffrey P.; Neely, Ryan R.; Turner, David D.

2018-04-01

Liquid-only and mixed-phase clouds in the Arctic strongly affect the regional surface energy and ice mass budgets, yet much remains unknown about the nature of these clouds due to the lack of intensive measurements. Lidar measurements of these clouds are challenged by very large signal dynamic range, which makes even seemingly simple tasks, such as thermodynamic phase classification, difficult. This work focuses on a set of measurements made by the Clouds Aerosol Polarization and Backscatter Lidar at Summit, Greenland and its retrieval algorithms, which use both analog and photon counting as well as orthogonal and non-orthogonal polarization retrievals to extend dynamic range and improve overall measurement quality and quantity. Presented here is an algorithm for cloud parameter retrievals that leverages enhanced dynamic range retrievals to classify mixed-phase clouds. This best guess retrieval is compared to co-located instruments for validation.

Relation of Cloud Occurrence Frequency, Overlap, and Effective Thickness Derived from CALIPSO and CloudSat Merged Cloud Vertical Profiles

Science.gov (United States)

Kato, Seiji; Sun-Mack, Sunny; Miller, Walter F.; Rose, Fred G.; Chen, Yan; Minnis, Patrick; Wielicki, Bruce A.

2009-01-01

A cloud frequency of occurrence matrix is generated using merged cloud vertical profile derived from Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) and Cloud Profiling Radar (CPR). The matrix contains vertical profiles of cloud occurrence frequency as a function of the uppermost cloud top. It is shown that the cloud fraction and uppermost cloud top vertical pro les can be related by a set of equations when the correlation distance of cloud occurrence, which is interpreted as an effective cloud thickness, is introduced. The underlying assumption in establishing the above relation is that cloud overlap approaches the random overlap with increasing distance separating cloud layers and that the probability of deviating from the random overlap decreases exponentially with distance. One month of CALIPSO and CloudSat data support these assumptions. However, the correlation distance sometimes becomes large, which might be an indication of precipitation. The cloud correlation distance is equivalent to the de-correlation distance introduced by Hogan and Illingworth [2000] when cloud fractions of both layers in a two-cloud layer system are the same.

Satellite Data Support for the ARM Climate Research Facility, 8/01/2009 - 7/31/2015

Energy Technology Data Exchange (ETDEWEB)

Minnis, Patrick [NASA Langley Research Center, Hampton, VA (United States); Khaiyer, Mandana M [Science Systems and Applications, Inc., Hampton, VA (United States)

2015-10-06

This report summarizes the support provided by NASA Langley Research for the DOE ARM Program in the form of cloud and radiation products derived from satellite imager data for the period between 8/01/09 through 7/31/15. Cloud properties such as cloud amount, height, and optical depth as well as outgoing longwave and shortwave broadband radiative fluxes were derived from geostationary and low-earth orbiting satellite imager radiance measurements for domains encompassing ARM permanent sites and field campaigns during the performance period. Datasets provided and documents produced are listed.

Absorbing Aerosols Above Cloud: Detection, Quantitative Retrieval, and Radiative Forcing from Satellite-based Passive Sensors

Science.gov (United States)

Jethva, H.; Torres, O.; Remer, L. A.; Bhartia, P. K.

2012-12-01

Light absorbing particles such as carbonaceous aerosols generated from biomass burning activities and windblown dust particles can exert a net warming effect on climate; the strength of which depends on the absorption capacity of the particles and brightness of the underlying reflecting background. When advected over low-level bright clouds, these aerosols absorb the cloud reflected radiation from ultra-violet (UV) to shortwave-IR (SWIR) and makes cloud scene darker-a phenomenon commonly known as "cloud darkening". The apparent "darkening" effect can be seen by eyes in satellite images as well as quantitatively in the spectral reflectance measurements made by space borne sensors over regions where light absorbing carbonaceous and dust aerosols overlay low-level cloud decks. Theoretical radiative transfer simulations support the observational evidence, and further reveal that the strength of the cloud darkening and its spectral signature (or color ratio) between measurements at two wavelengths are a bi-function of aerosol and cloud optical thickness (AOT and COT); both are measures of the total amount of light extinction caused by aerosols and cloud, respectively. Here, we developed a retrieval technique, named as the "color ratio method" that uses the satellite measurements at two channels, one at shorter wavelength in the visible and one at longer wavelength in the shortwave-IR for the simultaneous retrieval of AOT and COT. The present technique requires assumptions on the aerosol single-scattering albedo and aerosol-cloud separation which are supplemented by the Aerosol Robotic Network (AERONET) and space borne CALIOP lidar measurements. The retrieval technique has been tested making use of the near-UV and visible reflectance observations made by the Ozone Monitoring Instrument (OMI) and Moderate Resolution Imaging Spectroradiometer (MODIS) for distinct above-cloud smoke and dust aerosol events observed seasonally over the southeast and tropical Atlantic Ocean

How Often and Why MODIS Cloud Property Retrievals Fail for Liquid-Phase Clouds over Ocean? a Comprehensive Analysis Based on a-Train Observations

Science.gov (United States)

Zhang, Z.; Cho, H. M.; Platnick, S. E.; Meyer, K.; Lebsock, M. D.

2014-12-01

The cloud optical thickness (τ) and droplet effective radius (re) are two key cloud parameters retrieved by MODIS (Moderate Resolution Imaging Spectroradiometer). These MODIS cloud products are widely used in a broad range of earth system science applications. In this paper, we present a comprehensive analysis of the failed cloud τ and/or re retrievals for liquid-phase clouds over ocean in the Collection 6 MODIS cloud product. The main findings from this study are summarized as follows: MODIS retrieval failure rates for marine boundary layer (MBL) clouds have a strong dependence on the spectral combination used for retrieval (e.g., 0.86 + 2.1 µm vs. 0.8 + 3.7 µm) and the cloud morphology (i.e., "good" pixels vs. partly cloudy (PCL) pixels). Combining all clear-sky-restoral (CSR) categories (CSR=0,1 and 3), the 0.86 + 2.1 µm and 0.86 + 3.7 µm spectral combinations have an overall failure rate of about 20% and 12%, respectively (See figure below). The PCL pixels (CSR=1 & 3) have significantly higher failure rates and contribute more to the total failure population than the "good" (CSR=0) pixels. The majority of the failed retrievals are caused by the re too large failure, which explains about 85% and 70% of the failed 0.86 + 2.1 µm and 0.86 + 3.7 µm retrievals, respectively. The remaining failures are either due to the re too small failure or τ retrieval failure. The geographical distribution of failure rates has a significant dependence on cloud regime, lower over the coastal stratocumulus cloud regime and higher over the broken trade-wind cumulus cloud regime over open oceans. Enhanced retrieval failure rates are found when MBL clouds have high sub-pixel inhomogeneity , or are located at special Sun-satellite viewing geometries, such as sunglint, large viewing or solar zenith angle, or cloudbow and glory angles, or subject to cloud masking, cloud overlapping and/or cloud phase retrieval issues. About 80% of the failure retrievals can be attributed to at

Design of a coil satellite centrifuge and its performance on counter-current chromatographic separation of 4-methylumbelliferyl sugar derivatives with polar organic-aqueous two-phase solvent systems.

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Shinomiya, Kazufusa; Tokura, Koji; Kimura, Emiru; Takai, Midori; Harikai, Naoki; Yoshida, Kazunori; Yanagidaira, Kazuhiro; Ito, Yoichiro

2015-05-01

A new high-speed counter-current chromatograph, named coil satellite centrifuge (CSC), was designed and fabricated in our laboratory. The CSC apparatus produces the satellite motion such that the coiled column simultaneously rotates around the sun axis (the angular velocity, ω1), the planet axis (ω2) and the satellite axis (the central axis of the column) (ω3). In order to achieve this triplicate rotary motion without twisting of the flow tube, the rotation of each axis was determined by the following formula: ω1=ω2+ω3. This relation enabled to lay out the flow tube without twisting by the simultaneous rotation of three axes. The flow tube was introduced from the bottom side of the apparatus into the sun axis of the first rotary frame reaching the upper side of the planet axis and connected to the column in the satellite axis. The performance of the apparatus was examined on separation of 4-methylumbelliferyl (MU) sugar derivatives as test samples with organic-aqueous two-phase solvent systems composed of ethyl acetate/1-butanol/water (3:2:5, v/v) for lower phase mobile and (1:4:5, v/v) for upper phase mobile. With lower phase mobile, five 4-MU sugar derivatives including β-D-cellobioside (Cel), β-D-glucopyranoside, α-D-mannopyranoside, β-D-fucopyranoside and α-L-fucopyranoside (α-L-Fuc) were separated with the combined rotation around each axis at counterclockwise (CCW) (ω1) - CCW (ω2) - CCW (ω3) by the flow tube distribution. With upper phase mobile, three 4-MU sugar derivatives including α-L-Fuc, β-D-galactopyranoside and Cel were separated with the combined rotation around each axis at clockwise (CW) (ω1) - CW (ω2) - CW (ω3) by the flow tube distribution. A series of experiments on peak resolution and stationary phase retention revealed that better partition efficiencies were obtained at the flow rate of 0.5 mL/min (column 1) and 0.8 mL/min (column 2) for lower phase mobile and 0.2 mL/min (column 1) and 0.4 mL/min (column 2) for upper phase

Evaluating Cloud and Precipitation Processes in Numerical Models using Current and Potential Future Satellite Missions

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van den Heever, S. C.; Tao, W. K.; Skofronick Jackson, G.; Tanelli, S.; L'Ecuyer, T. S.; Petersen, W. A.; Kummerow, C. D.

2015-12-01

Cloud, aerosol and precipitation processes play a fundamental role in the water and energy cycle. It is critical to accurately represent these microphysical processes in numerical models if we are to better predict cloud and precipitation properties on weather through climate timescales. Much has been learned about cloud properties and precipitation characteristics from NASA satellite missions such as TRMM, CloudSat, and more recently GPM. Furthermore, data from these missions have been successfully utilized in evaluating the microphysical schemes in cloud-resolving models (CRMs) and global models. However, there are still many uncertainties associated with these microphysics schemes. These uncertainties can be attributed, at least in part, to the fact that microphysical processes cannot be directly observed or measured, but instead have to be inferred from those cloud properties that can be measured. Evaluation of microphysical parameterizations are becoming increasingly important as enhanced computational capabilities are facilitating the use of more sophisticated schemes in CRMs, and as future global models are being run on what has traditionally been regarded as cloud-resolving scales using CRM microphysical schemes. In this talk we will demonstrate how TRMM, CloudSat and GPM data have been used to evaluate different aspects of current CRM microphysical schemes, providing examples of where these approaches have been successful. We will also highlight CRM microphysical processes that have not been well evaluated and suggest approaches for addressing such issues. Finally, we will introduce a potential NASA satellite mission, the Cloud and Precipitation Processes Mission (CAPPM), which would facilitate the development and evaluation of different microphysical-dynamical feedbacks in numerical models.

Migratory herbivorous waterfowl track satellite-derived green wave index.

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Mitra Shariatinajafabadi

Full Text Available Many migrating herbivores rely on plant biomass to fuel their life cycles and have adapted to following changes in plant quality through time. The green wave hypothesis predicts that herbivorous waterfowl will follow the wave of food availability and quality during their spring migration. However, testing this hypothesis is hampered by the large geographical range these birds cover. The satellite-derived normalized difference vegetation index (NDVI time series is an ideal proxy indicator for the development of plant biomass and quality across a broad spatial area. A derived index, the green wave index (GWI, has been successfully used to link altitudinal and latitudinal migration of mammals to spatio-temporal variations in food quality and quantity. To date, this index has not been used to test the green wave hypothesis for individual avian herbivores. Here, we use the satellite-derived GWI to examine the green wave hypothesis with respect to GPS-tracked individual barnacle geese from three flyway populations (Russian n = 12, Svalbard n = 8, and Greenland n = 7. Data were collected over three years (2008-2010. Our results showed that the Russian and Svalbard barnacle geese followed the middle stage of the green wave (GWI 40-60%, while the Greenland geese followed an earlier stage (GWI 20-40%. Despite these differences among geese populations, the phase of vegetation greenness encountered by the GPS-tracked geese was close to the 50% GWI (i.e. the assumed date of peak nitrogen concentration, thereby implying that barnacle geese track high quality food during their spring migration. To our knowledge, this is the first time that the migration of individual avian herbivores has been successfully studied with respect to vegetation phenology using the satellite-derived GWI. Our results offer further support for the green wave hypothesis applying to long-distance migrants on a larger scale.

Revisiting the iris effect of tropical cirrus clouds with TRMM and A-Train satellite data

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Choi, Yong-Sang; Kim, WonMoo; Yeh, Sang-Wook; Masunaga, Hirohiko; Kwon, Min-Jae; Jo, Hyun-Su; Huang, Lei

2017-06-01

Just as the iris of human eye controls the light influx (iris effect), tropical anvil cirrus clouds may regulate the Earth's surface warming by controlling outgoing longwave radiation. This study examines this possible effect with monthly satellite observations such as Tropical Rainfall Measuring Mission (TRMM) precipitation, Moderate Resolution Imaging Spectroradiometer cirrus fraction, and Clouds and the Earth's Radiant Energy System top-of-the-atmosphere radiative fluxes averaged over different tropical domains from March 2000 to October 2014. To confirm that high-level cirrus is relevant to this study, Cloud-Aerosol Lidar with Orthogonal Polarization high cloud observations were also analyzed from June 2006 to December 2015. Our analysis revealed that the increase in sea surface temperature in the tropical western Pacific tends to concentrate convective cloud systems. This concentration effect very likely induces the significant reduction of both stratiform rain rate and cirrus fraction, without appreciable change in the convective rain rate. This reduction of stratiform rain rate and cirrus fraction cannot be found over its subregion or the tropical eastern Pacific, where the concentration effect of anvil cirrus is weak. Consistently, over the tropical western Pacific, the higher ratio of convective rain rate to total rain rate (i.e., precipitation efficiency) significantly correlates with warmer sea surface temperature and lower cirrus fraction. The reduced cirrus eventually increased outgoing longwave radiation to a greater degree than absorbed solar radiation. Finally, the negative relationship between precipitation efficiency and cirrus fraction tends to correspond to a low global equilibrium climate sensitivity in the models in the Coupled Model Intercomparison Project Phase 5. This suggests that tropical anvil cirrus clouds exert a negative climate feedback in strong association with precipitation efficiency.

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

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Ozcan, O.

2016-12-01

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

Cloud phase identification of Arctic boundary-layer clouds from airborne spectral reflection measurements: test of three approaches

Directory of Open Access Journals (Sweden)

A. Ehrlich

2008-12-01

Full Text Available Arctic boundary-layer clouds were investigated with remote sensing and in situ instruments during the Arctic Study of Tropospheric Aerosol, Clouds and Radiation (ASTAR campaign in March and April 2007. The clouds formed in a cold air outbreak over the open Greenland Sea. Beside the predominant mixed-phase clouds pure liquid water and ice clouds were observed. Utilizing measurements of solar radiation reflected by the clouds three methods to retrieve the thermodynamic phase of the cloud are introduced and compared. Two ice indices I_S and I_P were obtained by analyzing the spectral pattern of the cloud top reflectance in the near infrared (1500–1800 nm wavelength spectral range which is characterized by ice and water absorption. While I_S analyzes the spectral slope of the reflectance in this wavelength range, I_S utilizes a principle component analysis (PCA of the spectral reflectance. A third ice index I_A is based on the different side scattering of spherical liquid water particles and nonspherical ice crystals which was recorded in simultaneous measurements of spectral cloud albedo and reflectance.

Radiative transfer simulations show that I_S, I_P and I_A range between 5 to 80, 0 to 8 and 1 to 1.25 respectively with lowest values indicating pure liquid water clouds and highest values pure ice clouds. The spectral slope ice index I_S and the PCA ice index I_P are found to be strongly sensitive to the effective diameter of the ice crystals present in the cloud. Therefore, the identification of mixed-phase clouds requires a priori knowledge of the ice crystal dimension. The reflectance-albedo ice index I_A is mainly dominated by the uppermost cloud layer (τ<1.5. Therefore, typical boundary-layer mixed-phase clouds with a liquid cloud top layer will

Is ozone model bias driven by errors in cloud predictions? A quantitative assessment using satellite cloud retrievals in WRF-Chem

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Ryu, Y. H.; Hodzic, A.; Barré, J.; Descombes, G.; Minnis, P.

2017-12-01

Clouds play a key role in radiation and hence O3 photochemistry by modulating photolysis rates and light-dependent emissions of biogenic volatile organic compounds (BVOCs). It is not well known, however, how much of the bias in O3 predictions is caused by inaccurate cloud predictions. This study quantifies the errors in surface O3 predictions associated with clouds in summertime over CONUS using the Weather Research and Forecasting with Chemistry (WRF-Chem) model. Cloud fields used for photochemistry are corrected based on satellite cloud retrievals in sensitivity simulations. It is found that the WRF-Chem model is able to detect about 60% of clouds in the right locations and generally underpredicts cloud optical depths. The errors in hourly O3 due to the errors in cloud predictions can be up to 60 ppb. On average in summertime over CONUS, the errors in 8-h average O3 of 1-6 ppb are found to be attributable to those in cloud predictions under cloudy sky conditions. The contribution of changes in photolysis rates due to clouds is found to be larger ( 80 % on average) than that of light-dependent BVOC emissions. The effects of cloud corrections on O­3 are about 2 times larger in VOC-limited than NOx-limited regimes, suggesting that the benefits of accurate cloud predictions would be greater in VOC-limited than NOx-limited regimes.

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

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Henneberg, O.; Lohmann, U.

2017-12-01

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

Modelling ice microphysics of mixed-phase clouds

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Ahola, J.; Raatikainen, T.; Tonttila, J.; Romakkaniemi, S.; Kokkola, H.; Korhonen, H.

2017-12-01

The low-level Arctic mixed-phase clouds have a significant role for the Arctic climate due to their ability to absorb and reflect radiation. Since the climate change is amplified in polar areas, it is vital to apprehend the mixed-phase cloud processes. From a modelling point of view, this requires a high spatiotemporal resolution to capture turbulence and the relevant microphysical processes, which has shown to be difficult.In order to solve this problem about modelling mixed-phase clouds, a new ice microphysics description has been developed. The recently published large-eddy simulation cloud model UCLALES-SALSA offers a good base for a feasible solution (Tonttila et al., Geosci. Mod. Dev., 10:169-188, 2017). The model includes aerosol-cloud interactions described with a sectional SALSA module (Kokkola et al., Atmos. Chem. Phys., 8, 2469-2483, 2008), which represents a good compromise between detail and computational expense.Newly, the SALSA module has been upgraded to include also ice microphysics. The dynamical part of the model is based on well-known UCLA-LES model (Stevens et al., J. Atmos. Sci., 56, 3963-3984, 1999) which can be used to study cloud dynamics on a fine grid.The microphysical description of ice is sectional and the included processes consist of formation, growth and removal of ice and snow particles. Ice cloud particles are formed by parameterized homo- or heterogeneous nucleation. The growth mechanisms of ice particles and snow include coagulation and condensation of water vapor. Autoconversion from cloud ice particles to snow is parameterized. The removal of ice particles and snow happens by sedimentation and melting.The implementation of ice microphysics is tested by initializing the cloud simulation with atmospheric observations from the Indirect and Semi-Direct Aerosol Campaign (ISDAC). The results are compared to the model results shown in the paper of Ovchinnikov et al. (J. Adv. Model. Earth Syst., 6, 223-248, 2014) and they show a good

Satellite image analysis and a hybrid ESSS/ANN model to forecast solar irradiance in the tropics

International Nuclear Information System (INIS)

Dong, Zibo; Yang, Dazhi; Reindl, Thomas; Walsh, Wilfred M.

2014-01-01

Highlights: • Satellite image analysis is performed and cloud cover index is classified using self-organizing maps (SOM). • The ESSS model is used to forecast cloud cover index. • Solar irradiance is estimated using multi-layer perceptron (MLP). • The proposed model shows better accuracy than other investigated models. - Abstract: We forecast hourly solar irradiance time series using satellite image analysis and a hybrid exponential smoothing state space (ESSS) model together with artificial neural networks (ANN). Since cloud cover is the major factor affecting solar irradiance, cloud detection and classification are crucial to forecast solar irradiance. Geostationary satellite images provide cloud information, allowing a cloud cover index to be derived and analysed using self-organizing maps (SOM). Owing to the stochastic nature of cloud generation in tropical regions, the ESSS model is used to forecast cloud cover index. Among different models applied in ANN, we favour the multi-layer perceptron (MLP) to derive solar irradiance based on the cloud cover index. This hybrid model has been used to forecast hourly solar irradiance in Singapore and the technique is found to outperform traditional forecasting models

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

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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.

Aerosol-cloud interactions in Arctic mixed-phase stratocumulus

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Solomon, A.

2017-12-01

Reliable climate projections require realistic simulations of Arctic cloud feedbacks. Of particular importance is accurately simulating Arctic mixed-phase stratocumuli (AMPS), which are ubiquitous and play an important role in regional climate due to their impact on the surface energy budget and atmospheric boundary layer structure through cloud-driven turbulence, radiative forcing, and precipitation. AMPS are challenging to model due to uncertainties in ice microphysical processes that determine phase partitioning between ice and radiatively important cloud liquid water. Since temperatures in AMPS are too warm for homogenous ice nucleation, ice must form through heterogeneous nucleation. In this presentation we discuss a relatively unexplored source of ice production-recycling of ice nuclei in regions of ice subsaturation. AMPS frequently have ice-subsaturated air near the cloud-driven mixed-layer base where falling ice crystals can sublimate, leaving behind IN. This study provides an idealized framework to understand feedbacks between dynamics and microphysics that maintain phase-partitioning in AMPS. In addition, the results of this study provide insight into the mechanisms and feedbacks that may maintain cloud ice in AMPS even when entrainment of IN at the mixed-layer boundaries is weak.

Using Satellite Observations to Evaluate the AeroCOM Volcanic Emissions Inventory and the Dispersal of Volcanic SO2 Clouds in MERRA

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Hughes, Eric J.; Krotkov, Nickolay; da Silva, Arlindo; Colarco, Peter

2015-01-01

Simulation of volcanic emissions in climate models requires information that describes the eruption of the emissions into the atmosphere. While the total amount of gases and aerosols released from a volcanic eruption can be readily estimated from satellite observations, information about the source parameters, like injection altitude, eruption time and duration, is often not directly known. The AeroCOM volcanic emissions inventory provides estimates of eruption source parameters and has been used to initialize volcanic emissions in reanalysis projects, like MERRA. The AeroCOM volcanic emission inventory provides an eruptions daily SO2 flux and plume top altitude, yet an eruption can be very short lived, lasting only a few hours, and emit clouds at multiple altitudes. Case studies comparing the satellite observed dispersal of volcanic SO2 clouds to simulations in MERRA have shown mixed results. Some cases show good agreement with observations Okmok (2008), while for other eruptions the observed initial SO2 mass is half of that in the simulations, Sierra Negra (2005). In other cases, the initial SO2 amount agrees with the observations but shows very different dispersal rates, Soufriere Hills (2006). In the aviation hazards community, deriving accurate source terms is crucial for monitoring and short-term forecasting (24-h) of volcanic clouds. Back trajectory methods have been developed which use satellite observations and transport models to estimate the injection altitude, eruption time, and eruption duration of observed volcanic clouds. These methods can provide eruption timing estimates on a 2-hour temporal resolution and estimate the altitude and depth of a volcanic cloud. To better understand the differences between MERRA simulations and volcanic SO2 observations, back trajectory methods are used to estimate the source term parameters for a few volcanic eruptions and compared to their corresponding entry in the AeroCOM volcanic emission inventory. The nature of

Satellite retrieval of the liquid water fraction in tropical clouds between −20 and −38 °C

Directory of Open Access Journals (Sweden)

D. L. Mitchell

2012-07-01

Full Text Available This study describes a satellite remote sensing method for directly retrieving the liquid water fraction in mixed phase clouds, and appears unique in this respect. The method uses MODIS split-window channels for retrieving the liquid fraction from cold clouds where the liquid water fraction is less than 50% of the total condensate. This makes use of the observation that clouds only containing ice exhibit effective 12-to-11 μm absorption optical thickness ratios (β_eff that are quasi-constant with retrieved cloud temperature T. This observation was made possible by using two CO₂ channels to retrieve T and then using the 12 and 11 μm channels to retrieve emissivities and β_eff. Thus for T < −40 °C, β_eff is constant, but for T > −40 °C, β_eff slowly increases due to the presence of liquid water, revealing mean liquid fractions of ~ 10% around −22 °C from tropical clouds identified as cirrus by the cloud mask. However, the uncertainties for these retrievals are large, and extensive in situ measurements are needed to refine and validate these retrievals. Such liquid levels are shown to reduce the cloud effective diameter D_e such that cloud optical thickness will increase by more than 50% for a given water path, relative to D_e corresponding to pure ice clouds. Such retrieval information is needed for validation of the cloud microphysics in climate models. Since low levels of liquid water can dominate cloud optical properties, tropical clouds between −25 and −20 °C may be susceptible to the first aerosol indirect effect.

CLAAS: the CM SAF cloud property data set using SEVIRI

Science.gov (United States)

Stengel, M. S.; Kniffka, A. K.; Meirink, J. F. M.; Lockhoff, M. L.; Tan, J. T.; Hollmann, R. H.

2014-04-01

An 8-year record of satellite-based cloud properties named CLAAS (CLoud property dAtAset using SEVIRI) is presented, which was derived within the EUMETSAT Satellite Application Facility on Climate Monitoring. The data set is based on SEVIRI measurements of the Meteosat Second Generation satellites, of which the visible and near-infrared channels were intercalibrated with MODIS. Applying two state-of-the-art retrieval schemes ensures high accuracy in cloud detection, cloud vertical placement and microphysical cloud properties. These properties were further processed to provide daily to monthly averaged quantities, mean diurnal cycles and monthly histograms. In particular, the per-month histogram information enhances the insight in spatio-temporal variability of clouds and their properties. Due to the underlying intercalibrated measurement record, the stability of the derived cloud properties is ensured, which is exemplarily demonstrated for three selected cloud variables for the entire SEVIRI disc and a European subregion. All data products and processing levels are introduced and validation results indicated. The sampling uncertainty of the averaged products in CLAAS is minimized due to the high temporal resolution of SEVIRI. This is emphasized by studying the impact of reduced temporal sampling rates taken at typical overpass times of polar-orbiting instruments. In particular, cloud optical thickness and cloud water path are very sensitive to the sampling rate, which in our study amounted to systematic deviations of over 10% if only sampled once a day. The CLAAS data set facilitates many cloud related applications at small spatial scales of a few kilometres and short temporal scales of a~few hours. Beyond this, the spatiotemporal characteristics of clouds on diurnal to seasonal, but also on multi-annual scales, can be studied.

The effect of aerosol-derived changes in the warm phase on the properties of deep convective clouds

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Chen, Qian; Koren, Ilan; Altaratz, Orit; Heiblum, Reuven; Dagan, Guy

2017-04-01

The aerosol impact on deep convective clouds starts in an increased number of cloud droplets in higher aerosol loading environment. This change drives many others, like enhanced condensational growth, delay in collision-coalescence and others. Since the warm processes serve as the initial and boundary conditions for the mixed and cold-phase processes in deep clouds, it is highly important to understand the aerosol effect on them. The weather research and forecasting model (WRF) with spectral bin microphysics was used to study a deep convective system over the Marshall Islands, during the Kwajalein Experiment (KWAJEX). Three simulations were conducted with aerosol concentrations of 100, 500 and 2000 cm-3, to reflect clean, semipolluted, and polluted conditions. The results of the clean run agreed well with the radar profiles and rain rate observations. The more polluted simulations resulted in larger total cloud mass, larger upper level cloud fraction and rain rates. There was an increased mass both below and above the zero temperature level. It indicates of more efficient growth processes both below and above the zero level. In addition the polluted runs showed an increased upward transport (across the zero level) of liquid water due to both stronger updrafts and larger droplet mobility. In this work we discuss the transport of cloud mass crossing the zero temperature level (in both directions) in order to gain a process level understanding of how aerosol effects on the warm processes affect the macro- and micro-properties of deep convective clouds.

Automated cloud tracking system for the Akatsuki Venus Climate Orbiter data

Science.gov (United States)

Ogohara, Kazunori; Kouyama, Toru; Yamamoto, Hiroki; Sato, Naoki; Takagi, Masahiro; Imamura, Takeshi

2012-02-01

Japanese Venus Climate Orbiter, Akatsuki, is cruising to approach to Venus again although its first Venus orbital insertion (VOI) has been failed. At present, we focus on the next opportunity of VOI and the following scientific observations.We have constructed an automated cloud tracking system for processing data obtained by Akatsuki in the present study. In this system, correction of the pointing of the satellite is essentially important for improving accuracy of the cloud motion vectors derived using the cloud tracking. Attitude errors of the satellite are reduced by fitting an ellipse to limb of an imaged Venus disk. Next, longitude-latitude distributions of brightness (cloud patterns) are calculated to make it easy to derive the cloud motion vectors. The grid points are distributed at regular intervals in the longitude-latitude coordinate. After applying the solar zenith correction and a highpass filter to the derived longitude-latitude distributions of brightness, the cloud features are tracked using pairs of images. As a result, we obtain cloud motion vectors on longitude-latitude grid points equally spaced. These entire processes are pipelined and automated, and are applied to all data obtained by combinations of cameras and filters onboard Akatsuki. It is shown by several tests that the cloud motion vectors are determined with a sufficient accuracy. We expect that longitude-latitude data sets created by the automated cloud tracking system will contribute to the Venus meteorology.

Global Distribution and Vertical Structure of Clouds Revealed by CALIPSO

Science.gov (United States)

Yi, Y.; Minnis, P.; Winker, D.; Huang, J.; Sun-Mack, S.; Ayers, K.

2007-12-01

Understanding the effects of clouds on Earth's radiation balance, especially on longwave fluxes within the atmosphere, depends on having accurate knowledge of cloud vertical location within the atmosphere. The Cloud- Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) satellite mission provides the opportunity to measure the vertical distribution of clouds at a greater detail than ever before possible. The CALIPSO cloud layer products from June 2006 to June 2007 are analyzed to determine the occurrence frequency and thickness of clouds as functions of time, latitude, and altitude. In particular, the latitude-longitude and vertical distributions of single- and multi-layer clouds and the latitudinal movement of cloud cover with the changing seasons are examined. The seasonal variablities of cloud frequency and geometric thickness are also analyzed and compared with similar quantities derived from the Aqua Moderate Resolution Imaging Spectroradiometer (MODIS) using the Clouds and the Earth's Radiant Energy System (CERES) cloud retrieval algorithms. The comparisons provide an estimate of the errors in cloud fraction, top height, and thickness incurred by passive algorithms.

Improving Satellite Quantitative Precipitation Estimation Using GOES-Retrieved Cloud Optical Depth

Energy Technology Data Exchange (ETDEWEB)

Stenz, Ronald; Dong, Xiquan; Xi, Baike; Feng, Zhe; Kuligowski, Robert J.

2016-02-01

To address significant gaps in ground-based radar coverage and rain gauge networks in the U.S., geostationary satellite quantitative precipitation estimates (QPEs) such as the Self-Calibrating Multivariate Precipitation Retrievals (SCaMPR) can be used to fill in both the spatial and temporal gaps of ground-based measurements. Additionally, with the launch of GOES-R, the temporal resolution of satellite QPEs may be comparable to that of Weather Service Radar-1988 Doppler (WSR-88D) volume scans as GOES images will be available every five minutes. However, while satellite QPEs have strengths in spatial coverage and temporal resolution, they face limitations particularly during convective events. Deep Convective Systems (DCSs) have large cloud shields with similar brightness temperatures (BTs) over nearly the entire system, but widely varying precipitation rates beneath these clouds. Geostationary satellite QPEs relying on the indirect relationship between BTs and precipitation rates often suffer from large errors because anvil regions (little/no precipitation) cannot be distinguished from rain-cores (heavy precipitation) using only BTs. However, a combination of BTs and optical depth (τ) has been found to reduce overestimates of precipitation in anvil regions (Stenz et al. 2014). A new rain mask algorithm incorporating both τ and BTs has been developed, and its application to the existing SCaMPR algorithm was evaluated. The performance of the modified SCaMPR was evaluated using traditional skill scores and a more detailed analysis of performance in individual DCS components by utilizing the Feng et al. (2012) classification algorithm. SCaMPR estimates with the new rain mask applied benefited from significantly reduced overestimates of precipitation in anvil regions and overall improvements in skill scores.

CLOUD DETECTION OF OPTICAL SATELLITE IMAGES USING SUPPORT VECTOR MACHINE

Directory of Open Access Journals (Sweden)

K.-Y. Lee

2016-06-01

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

Cloud Detection of Optical Satellite Images Using Support Vector Machine

Science.gov (United States)

Lee, Kuan-Yi; Lin, Chao-Hung

2016-06-01

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

Cloud regimes as phase transitions

Science.gov (United States)

Stechmann, Samuel; Hottovy, Scott

2017-11-01

Clouds are repeatedly identified as a leading source of uncertainty in future climate predictions. Of particular importance are stratocumulus clouds, which can appear as either (i) closed cells that reflect solar radiation back to space or (ii) open cells that allow solar radiation to reach the Earth's surface. Here we show that these clouds regimes - open versus closed cells - fit the paradigm of a phase transition. In addition, this paradigm characterizes pockets of open cells (POCs) as the interface between the open- and closed-cell regimes, and it identifies shallow cumulus clouds as a regime of higher variability. This behavior can be understood using an idealized model for the dynamics of atmospheric water as a stochastic diffusion process. Similar viewpoints of deep convection and self-organized criticality will also be discussed. With these new conceptual viewpoints, ideas from statistical mechanics could potentially be used for understanding uncertainties related to clouds in the climate system and climate predictions. The research of S.N.S. is partially supported by a Sloan Research Fellowship, ONR Young Investigator Award N00014-12-1-0744, and ONR MURI Grant N00014-12-1-0912.

Simulating mixed-phase Arctic stratus clouds: sensitivity to ice initiation mechanisms

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G. McFarquhar

2009-07-01

Full Text Available The importance of Arctic mixed-phase clouds on radiation and the Arctic climate is well known. However, the development of mixed-phase cloud parameterization for use in large scale models is limited by lack of both related observations and numerical studies using multidimensional models with advanced microphysics that provide the basis for understanding the relative importance of different microphysical processes that take place in mixed-phase clouds. To improve the representation of mixed-phase cloud processes in the GISS GCM we use the GISS single-column model coupled to a bin resolved microphysics (BRM scheme that was specially designed to simulate mixed-phase clouds and aerosol-cloud interactions. Using this model with the microphysical measurements obtained from the DOE ARM Mixed-Phase Arctic Cloud Experiment (MPACE campaign in October 2004 at the North Slope of Alaska, we investigate the effect of ice initiation processes and Bergeron-Findeisen process (BFP on glaciation time and longevity of single-layer stratiform mixed-phase clouds. We focus on observations taken during 9–10 October, which indicated the presence of a single-layer mixed-phase clouds. We performed several sets of 12-h simulations to examine model sensitivity to different ice initiation mechanisms and evaluate model output (hydrometeors' concentrations, contents, effective radii, precipitation fluxes, and radar reflectivity against measurements from the MPACE Intensive Observing Period. Overall, the model qualitatively simulates ice crystal concentration and hydrometeors content, but it fails to predict quantitatively the effective radii of ice particles and their vertical profiles. In particular, the ice effective radii are overestimated by at least 50%. However, using the same definition as used for observations, the effective radii simulated and that observed were more comparable. We find that for the single-layer stratiform mixed-phase clouds simulated, process

Simulating mixed-phase Arctic stratus clouds: sensitivity to ice initiation mechanisms

Science.gov (United States)

Sednev, I.; Menon, S.; McFarquhar, G.

2009-07-01

The importance of Arctic mixed-phase clouds on radiation and the Arctic climate is well known. However, the development of mixed-phase cloud parameterization for use in large scale models is limited by lack of both related observations and numerical studies using multidimensional models with advanced microphysics that provide the basis for understanding the relative importance of different microphysical processes that take place in mixed-phase clouds. To improve the representation of mixed-phase cloud processes in the GISS GCM we use the GISS single-column model coupled to a bin resolved microphysics (BRM) scheme that was specially designed to simulate mixed-phase clouds and aerosol-cloud interactions. Using this model with the microphysical measurements obtained from the DOE ARM Mixed-Phase Arctic Cloud Experiment (MPACE) campaign in October 2004 at the North Slope of Alaska, we investigate the effect of ice initiation processes and Bergeron-Findeisen process (BFP) on glaciation time and longevity of single-layer stratiform mixed-phase clouds. We focus on observations taken during 9-10 October, which indicated the presence of a single-layer mixed-phase clouds. We performed several sets of 12-h simulations to examine model sensitivity to different ice initiation mechanisms and evaluate model output (hydrometeors' concentrations, contents, effective radii, precipitation fluxes, and radar reflectivity) against measurements from the MPACE Intensive Observing Period. Overall, the model qualitatively simulates ice crystal concentration and hydrometeors content, but it fails to predict quantitatively the effective radii of ice particles and their vertical profiles. In particular, the ice effective radii are overestimated by at least 50%. However, using the same definition as used for observations, the effective radii simulated and that observed were more comparable. We find that for the single-layer stratiform mixed-phase clouds simulated, process of ice phase initiation

Using long-term ARM observations to evaluate Arctic mixed-phased cloud representation in the GISS ModelE GCM

Science.gov (United States)

Lamer, K.; Fridlind, A. M.; Luke, E. P.; Tselioudis, G.; Ackerman, A. S.; Kollias, P.; Clothiaux, E. E.

2016-12-01

The presence of supercooled liquid in clouds affects surface radiative and hydrological budgets, especially at high latitudes. Capturing these effects is crucial to properly quantifying climate sensitivity. Currently, a number of CGMs disagree on the distribution of cloud phase. Adding to the challenge is a general lack of observations on the continuum of clouds, from high to low-level and from warm to cold. In the current study, continuous observations from 2011 to 2014 are used to evaluate all clouds produced by the GISS ModelE GCM over the ARM North Slope of Alaska site. The International Satellite Cloud Climatology Project (ISCCP) Global Weather State (GWS) approach reveals that fair-weather (GWS 7, 32% occurrence rate), as well as mid-level storm related (GWS 5, 28%) and polar (GWS 4, 14%) clouds, dominate the large-scale cloud patterns at this high latitude site. At higher spatial and temporal resolutions, ground-based cloud radar observations reveal a majority of single layer cloud vertical structures (CVS). While clear sky and low-level clouds dominate (each with 30% occurrence rate) a fair amount of shallow ( 10%) to deep ( 5%) convection are observed. Cloud radar Doppler spectra are used along with depolarization lidar observations in a neural network approach to detect the presence, layering and inhomogeneity of supercooled liquid layers. Preliminary analyses indicate that most of the low-level clouds sampled contain one or more supercooled liquid layers. Furthermore, the relationship between CVS and the presence of supercooled liquid is established, as is the relationship between the presence of supercool liquid and precipitation susceptibility. Two approaches are explored to bridge the gap between large footprint GCM simulations and high-resolution ground-based observations. The first approach consists of comparing model output and ground-based observations that exhibit the same column CVS type (i.e. same cloud depth, height and layering

CHASER: An Innovative Satellite Mission Concept to Measure the Effects of Aerosols on Clouds and Climate

Science.gov (United States)

Renno, N.; Williams, E.; Rosenfeld, D.; Fischer, D.; Fischer, J.; Kremic, T.; Agrawal, A.; Andreae, M.; Bierbaum, R.; Blakeslee, R.; Boerner, A.; Bowles, N.; Christian, H.; Dunion, J.; Horvath, A.; Huang, X.; Khain, A.; Kinne, S.; Lemos, M.-C.; Penner, J.

2012-04-01

The formation of cloud droplets on aerosol particles, technically known as the activation of cloud condensation nuclei (CCN), is the fundamental process driving the interactions of aerosols with clouds and precipitation. Knowledge of these interactions is foundational to our understanding of weather and climate. The Intergovernmental Panel on Climate Change (IPCC) and the Decadal Survey (NRC 2007) indicate that the uncertainty in how clouds adjust to aerosol perturbations dominates the uncertainty in the overall quantification of the radiative forcing attributable to human activities. The Clouds, Hazards, and Aerosols Survey for Earth Researchers (CHASER) mission concept responds to the IPCC and Decadal Survey concerns by studying the activation of CCN and their interactions with clouds and storms. CHASER proposes to revolutionize our understanding of the interactions of aerosols with clouds by making the first global measurements of the fundamental physical entity linking them: activated cloud condensation nuclei. The CHASER mission was conceptualized to measure all quantities necessary for determining the interactions of aerosols with clouds and storms. Measurements by current satellites allow the determination of crude profiles of cloud particle size but not of the activated CCN that seed them. CHASER uses a new technique (Freud et al. 2011; Rosenfeld et al. 2012) and high-heritage instruments to produce the first global maps of activated CCN and the properties of the clouds associated with them. CHASER measures the CCN concentration and cloud thermodynamic forcing simultaneously, allowing their effects to be distinguished. Changes in the behavior of a group of weather systems in which only one of the quantities varies (a partial derivative of the intensity with the desirable quantity) allow the determination of each effect statistically. The high uncertainties of current climate predictions limit their much-needed use in decision-making. CHASER mitigates this

Cloud properties derived from two lidars over the ARM SGP site

Energy Technology Data Exchange (ETDEWEB)

Dupont, Jean-Charles; Haeffelin, Martial; Morille, Y.; Comstock, Jennifer M.; Flynn, Connor J.; Long, Charles N.; Sivaraman, Chitra; Newsom, Rob K.

2011-02-16

[1] Active remote sensors such as lidars or radars can be used with other data to quantify the cloud properties at regional scale and at global scale (Dupont et al., 2009). Relative to radar, lidar remote sensing is sensitive to very thin and high clouds but has a significant limitation due to signal attenuation in the ability to precisely quantify the properties of clouds with a 20 cloud optical thickness larger than 3. In this study, 10-years of backscatter lidar signal data are analysed by a unique algorithm called STRucture of ATmosphere (STRAT, Morille et al., 2007). We apply the STRAT algorithm to data from both the collocated Micropulse lidar (MPL) and a Raman lidar (RL) at the Atmospheric Radiation Measurement (ARM) Southern Great Plains (SGP) site between 1998 and 2009. Raw backscatter lidar signal is processed and 25 corrections for detector deadtime, afterpulse, and overlap are applied. (Campbell et al.) The cloud properties for all levels of clouds are derived and distributions of cloud base height (CBH), top height (CTH), physical cloud thickness (CT), and optical thickness (COT) from local statistics are compared. The goal of this study is (1) to establish a climatology of macrophysical and optical properties for all levels of clouds observed over the ARM SGP site 30 and (2) to estimate the discrepancies induced by the two remote sensing systems (pulse energy, sampling, resolution, etc.). Our first results tend to show that the MPLs, which are the primary ARM lidars, have a distinctly limited range where all of these cloud properties are detectable, especially cloud top and cloud thickness, but even actual cloud base especially during summer daytime period. According to the comparisons between RL and MPL, almost 50% of situations show a signal to noise ratio too low (smaller than 3) for the MPL in order to detect clouds higher than 7km during daytime period in summer. Consequently, the MPLderived annual cycle of cirrus cloud base (top) altitude is

Non-equilibrium ionization around clouds evaporating in the interstellar medium

International Nuclear Information System (INIS)

Ballet, J.; Luciani, J.F.; Mora, P.

1986-01-01

It is of prime importance for global models of the interstellar medium to know whether dense clouds do or do not evaporate in the hot coronal gas. The rate of mass exchanges between phases depends very much on that. McKee and Ostriker's model, for instance, assumes that evaporation is important enough to control the expansion of supernova remnants, and that mass loss obeys the law derived by Cowie and McKee. In fact, the geometry of the magnetic field is nearly unknown, and it might totally inhibit evaporation, if the clouds are not regularly connected to the hot gas. Up to now, the only test of the theory is the U.V. observation (by the Copernicus and IUE satellites) of absorption lines of ions such as OVI or NV, that exist at temperatures of a few 100,000 K typical of transition layers around evaporating clouds. Other means of testing the theory are discussed

Georeferencing UAS Derivatives Through Point Cloud Registration with Archived Lidar Datasets

Science.gov (United States)

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

2016-10-01

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

Airborne observations of cloud properties on HALO during NARVAL

Science.gov (United States)

Konow, Heike; Hansen, Akio; Ament, Felix

2016-04-01

second phase of NARVAL will focus on trade-wind cumuli observations and the NAWDEX (North-Atlantik Waveguide EXperiment) campaign will investigate the warm sector and frontal zones of mid-latitude cyclones. During the first NARVAL campaign, a broad range of cloud regimes from shallow cumuli to cumulonimbus and cold fronts was observed. Derived cloud covers from different instruments on board HALO varied by as much as 25 % since cloud radar, microwave radiometers, lidar and dropsondes measure different aspects of clouds. A cloud mask combining these observations provides a complimentary view of clouds and allows for identification of joint cloud characteristics (e.g., cloud top of ice or water clouds, cloud depth). We will present benefits gained from this combination of measurements and provide a more comprehensive view on clouds and cloud properties in different cloud regimes. Furthermore, we will give an overview of the plans for future campaigns and demonstrate what new insights we can gain from these airborne observations within the scope of past and future campaigns.

A Lagrangian Analysis of Cold Cloud Clusters and Their Life Cycles With Satellite Observations

Science.gov (United States)

Esmaili, Rebekah Bradley; Tian, Yudong; Vila, Daniel Alejandro; Kim, Kyu-Myong

2016-01-01

Cloud movement and evolution signify the complex water and energy transport in the atmosphere-ocean-land system. Detecting, clustering, and tracking clouds as semi coherent cluster objects enables study of their evolution which can complement climate model simulations and enhance satellite retrieval algorithms, where there are large gaps between overpasses. Using an area-overlap cluster tracking algorithm, in this study we examine the trajectories, horizontal extent, and brightness temperature variations of millions of individual cloud clusters over their lifespan, from infrared satellite observations at 30-minute, 4-km resolution, for a period of 11 years. We found that the majority of cold clouds were both small and short-lived and that their frequency and location are influenced by El Nino. More importantly, this large sample of individually tracked clouds shows their horizontal size and temperature evolution. Longer lived clusters tended to achieve their temperature and size maturity milestones at different times, while these stages often occurred simultaneously in shorter lived clusters. On average, clusters with this lag also exhibited a greater rainfall contribution than those where minimum temperature and maximum size stages occurred simultaneously. Furthermore, by examining the diurnal cycle of cluster development over Africa and the Indian subcontinent, we observed differences in the local timing of the maximum occurrence at different life cycle stages. Over land there was a strong diurnal peak in the afternoon while over the ocean there was a semi-diurnal peak composed of longer-lived clusters in the early morning hours and shorter-lived clusters in the afternoon. Building on regional specific work, this study provides a long-term, high-resolution, and global survey of object-based cloud characteristics.

Do clouds save the great barrier reef? satellite imagery elucidates the cloud-SST relationship at the local scale.

Directory of Open Access Journals (Sweden)

Susannah M Leahy

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

FAME-C: cloud property retrieval using synergistic AATSR and MERIS observations

Directory of Open Access Journals (Sweden)

C. K. Carbajal Henken

2014-11-01

Full Text Available A newly developed daytime cloud property retrieval algorithm, FAME-C (Freie Universität Berlin AATSR MERIS Cloud, is presented. Synergistic observations from the Advanced Along-Track Scanning Radiometer (AATSR and the Medium Resolution Imaging Spectrometer (MERIS, both mounted on the polar-orbiting Environmental Satellite (Envisat, are used for cloud screening. For cloudy pixels two main steps are carried out in a sequential form. First, a cloud optical and microphysical property retrieval is performed using an AATSR near-infrared and visible channel. Cloud phase, cloud optical thickness, and effective radius are retrieved, and subsequently cloud water path is computed. Second, two cloud top height products are retrieved based on independent techniques. For cloud top temperature, measurements in the AATSR infrared channels are used, while for cloud top pressure, measurements in the MERIS oxygen-A absorption channel are used. Results from the cloud optical and microphysical property retrieval serve as input for the two cloud top height retrievals. Introduced here are the AATSR and MERIS forward models and auxiliary data needed in FAME-C. Also, the optimal estimation method, which provides uncertainty estimates of the retrieved property on a pixel basis, is presented. Within the frame of the European Space Agency (ESA Climate Change Initiative (CCI project, the first global cloud property retrievals have been conducted for the years 2007–2009. For this time period, verification efforts are presented, comparing, for four selected regions around the globe, FAME-C cloud optical and microphysical properties to cloud optical and microphysical properties derived from measurements of the Moderate Resolution Imaging Spectroradiometer (MODIS on the Terra satellite. The results show a reasonable agreement between the cloud optical and microphysical property retrievals. Biases are generally smallest for marine stratocumulus clouds: −0.28, 0.41 μm and �

Using satellite-derived optical thickness to assess the influence of clouds on terrestrial carbon uptake

Science.gov (United States)

S.J. Cheng; A.L. Steiner; D.Y. Hollinger; G. Bohrer; K.J. Nadelhoffer

2016-01-01

Clouds scatter direct solar radiation, generating diffuse radiation and altering the ratio of direct to diffuse light. If diffuse light increases plant canopy CO2 uptake, clouds may indirectly influence climate by altering the terrestrial carbon cycle. However, past research primarily uses proxies or qualitative categories of clouds to connect...

Classification of Arctic, midlatitude and tropical clouds in the mixed-phase temperature regime

Science.gov (United States)

Costa, Anja; Meyer, Jessica; Afchine, Armin; Luebke, Anna; Günther, Gebhard; Dorsey, James R.; Gallagher, Martin W.; Ehrlich, Andre; Wendisch, Manfred; Baumgardner, Darrel; Wex, Heike; Krämer, Martina

2017-10-01

The degree of glaciation of mixed-phase clouds constitutes one of the largest uncertainties in climate prediction. In order to better understand cloud glaciation, cloud spectrometer observations are presented in this paper, which were made in the mixed-phase temperature regime between 0 and -38 °C (273 to 235 K), where cloud particles can either be frozen or liquid. The extensive data set covers four airborne field campaigns providing a total of 139 000 1 Hz data points (38.6 h within clouds) over Arctic, midlatitude and tropical regions. We develop algorithms, combining the information on number concentration, size and asphericity of the observed cloud particles to classify four cloud types: liquid clouds, clouds in which liquid droplets and ice crystals coexist, fully glaciated clouds after the Wegener-Bergeron-Findeisen process and clouds where secondary ice formation occurred. We quantify the occurrence of these cloud groups depending on the geographical region and temperature and find that liquid clouds dominate our measurements during the Arctic spring, while clouds dominated by the Wegener-Bergeron-Findeisen process are most common in midlatitude spring. The coexistence of liquid water and ice crystals is found over the whole mixed-phase temperature range in tropical convective towers in the dry season. Secondary ice is found at midlatitudes at -5 to -10 °C (268 to 263 K) and at higher altitudes, i.e. lower temperatures in the tropics. The distribution of the cloud types with decreasing temperature is shown to be consistent with the theory of evolution of mixed-phase clouds. With this study, we aim to contribute to a large statistical database on cloud types in the mixed-phase temperature regime.

Sensitivity to deliberate sea salt seeding of marine clouds - observations and model simulations

OpenAIRE

Alterskjaer, K.; Kristjansson, J. E.; Seland, O.

2012-01-01

Sea salt seeding of marine clouds to increase their albedo is a proposed technique to counteract or slow global warming. In this study, we first investigate the susceptibility of marine clouds to sea salt injections, using observational data of cloud droplet number concentration, cloud optical depth, and liquid cloud fraction from the MODIS (Moderate Resolution Imaging Spectroradiometer) instruments on board the Aqua and Terra satellites. We then compare the derived susceptibility function to...

Understanding the drivers of marine liquid-water cloud occurrence and properties with global observations using neural networks

Directory of Open Access Journals (Sweden)

H. Andersen

2017-08-01

Full Text Available The role of aerosols, clouds and their interactions with radiation remain among the largest unknowns in the climate system. Even though the processes involved are complex, aerosol–cloud interactions are often analyzed by means of bivariate relationships. In this study, 15 years (2001–2015 of monthly satellite-retrieved near-global aerosol products are combined with reanalysis data of various meteorological parameters to predict satellite-derived marine liquid-water cloud occurrence and properties by means of region-specific artificial neural networks. The statistical models used are shown to be capable of predicting clouds, especially in regions of high cloud variability. On this monthly scale, lower-tropospheric stability is shown to be the main determinant of cloud fraction and droplet size, especially in stratocumulus regions, while boundary layer height controls the liquid-water amount and thus the optical thickness of clouds. While aerosols show the expected impact on clouds, at this scale they are less relevant than some meteorological factors. Global patterns of the derived sensitivities point to regional characteristics of aerosol and cloud processes.

Improvements in AVHRR Daytime Cloud Detection Over the ARM NSA Site

Science.gov (United States)

Chakrapani, V.; Spangenberg, D. A.; Doelling, D. R.; Minnis, P.; Trepte, Q. Z.; Arduini, R. F.

2001-01-01

Clouds play an important role in the radiation budget over Arctic and Antarctic. Because of limited surface observing capabilities, it is necessary to detect clouds over large areas using satellite imagery. At low and mid-latitudes, satellite-observed visible (VIS; 0.65 micrometers) and infrared (IR; 11 micrometers) radiance data are used to derive cloud fraction, temperature, and optical depth. However, the extreme variability in the VIS surface albedo makes the detection of clouds from satellite a difficult process in polar regions. The IR data often show that the surface is nearly the same temperature or even colder than clouds, further complicating cloud detection. Also, the boundary layer can have large areas of haze, thin fog, or diamond dust that are not seen in standard satellite imagery. Other spectral radiances measured by satellite imagers provide additional information that can be used to more accurately discriminate clouds from snow and ice. Most techniques currently use a fixed reflectance or temperature threshold to decide between clouds and clear snow. Using a subjective approach, Minnis et al. (2001) found that the clear snow radiance signatures vary as a function of viewing and illumination conditions as well as snow condition. To routinely process satellite imagery over polar regions with an automated algorithm, it is necessary to account for this angular variability and the change in the background reflectance as snow melts, vegetation grows over land, and melt ponds form on pack ice. This paper documents the initial satellite-based cloud product over the Atmospheric Radiation Measurement (ARM) North Slope of Alaska (NSA) site at Barrow for use by the modeling community. Cloud amount and height are determined subjectively using an adaptation of the methodology of Minnis et al. (2001) and the radiation fields arc determined following the methods of Doelling et al. (2001) as applied to data taken during the Surface Heat and Energy Budget of the

Integrating Global Satellite-Derived Data Products as a Pre-Analysis for Hydrological Modelling Studies: A Case Study for the Red River Basin

Directory of Open Access Journals (Sweden)

Gijs Simons

2016-03-01

Full Text Available With changes in weather patterns and intensifying anthropogenic water use, there is an increasing need for spatio-temporal information on water fluxes and stocks in river basins. The assortment of satellite-derived open-access information sources on rainfall (P and land use/land cover (LULC is currently being expanded with the application of actual evapotranspiration (ETact algorithms on the global scale. We demonstrate how global remotely sensed P and ETact datasets can be merged to examine hydrological processes such as storage changes and streamflow prior to applying a numerical simulation model. The study area is the Red River Basin in China in Vietnam, a generally challenging basin for remotely sensed information due to frequent cloud cover. Over this region, several satellite-based P and ETact products are compared, and performance is evaluated using rain gauge records and longer-term averaged streamflow. A method is presented for fusing multiple satellite-derived ETact estimates to generate an ensemble product that may be less susceptible, on a global basis, to errors in individual modeling approaches. Subsequently, monthly satellite-derived rainfall and ETact are combined to assess the water balance for individual subcatchments and types of land use, defined using a global land use classification improved based on auxiliary satellite data. It was found that a combination of TRMM rainfall and the ensemble ETact product is consistent with streamflow records in both space and time. It is concluded that monthly storage changes, multi-annual streamflow and water yield per LULC type in the Red River Basin can be successfully assessed based on currently available global satellite-derived products.

Classification of Arctic, midlatitude and tropical clouds in the mixed-phase temperature regime

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A. Costa

2017-10-01

Full Text Available The degree of glaciation of mixed-phase clouds constitutes one of the largest uncertainties in climate prediction. In order to better understand cloud glaciation, cloud spectrometer observations are presented in this paper, which were made in the mixed-phase temperature regime between 0 and −38 °C (273 to 235 K, where cloud particles can either be frozen or liquid. The extensive data set covers four airborne field campaigns providing a total of 139 000 1 Hz data points (38.6 h within clouds over Arctic, midlatitude and tropical regions. We develop algorithms, combining the information on number concentration, size and asphericity of the observed cloud particles to classify four cloud types: liquid clouds, clouds in which liquid droplets and ice crystals coexist, fully glaciated clouds after the Wegener–Bergeron–Findeisen process and clouds where secondary ice formation occurred. We quantify the occurrence of these cloud groups depending on the geographical region and temperature and find that liquid clouds dominate our measurements during the Arctic spring, while clouds dominated by the Wegener–Bergeron–Findeisen process are most common in midlatitude spring. The coexistence of liquid water and ice crystals is found over the whole mixed-phase temperature range in tropical convective towers in the dry season. Secondary ice is found at midlatitudes at −5 to −10 °C (268 to 263 K and at higher altitudes, i.e. lower temperatures in the tropics. The distribution of the cloud types with decreasing temperature is shown to be consistent with the theory of evolution of mixed-phase clouds. With this study, we aim to contribute to a large statistical database on cloud types in the mixed-phase temperature regime.

Cloud type comparisons of AIRS, CloudSat, and CALIPSO cloud height and amount

Directory of Open Access Journals (Sweden)

B. H. Kahn

2008-03-01

Full Text Available The precision of the two-layer cloud height fields derived from the Atmospheric Infrared Sounder (AIRS is explored and quantified for a five-day set of observations. Coincident profiles of vertical cloud structure by CloudSat, a 94 GHz profiling radar, and the Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO, are compared to AIRS for a wide range of cloud types. Bias and variability in cloud height differences are shown to have dependence on cloud type, height, and amount, as well as whether CloudSat or CALIPSO is used as the comparison standard. The CloudSat-AIRS biases and variability range from −4.3 to 0.5±1.2–3.6 km for all cloud types. Likewise, the CALIPSO-AIRS biases range from 0.6–3.0±1.2–3.6 km (−5.8 to −0.2±0.5–2.7 km for clouds ≥7 km (<7 km. The upper layer of AIRS has the greatest sensitivity to Altocumulus, Altostratus, Cirrus, Cumulonimbus, and Nimbostratus, whereas the lower layer has the greatest sensitivity to Cumulus and Stratocumulus. Although the bias and variability generally decrease with increasing cloud amount, the ability of AIRS to constrain cloud occurrence, height, and amount is demonstrated across all cloud types for many geophysical conditions. In particular, skill is demonstrated for thin Cirrus, as well as some Cumulus and Stratocumulus, cloud types infrared sounders typically struggle to quantify. Furthermore, some improvements in the AIRS Version 5 operational retrieval algorithm are demonstrated. However, limitations in AIRS cloud retrievals are also revealed, including the existence of spurious Cirrus near the tropopause and low cloud layers within Cumulonimbus and Nimbostratus clouds. Likely causes of spurious clouds are identified and the potential for further improvement is discussed.

Cloud and Thermodynamic Parameters Retrieved from Satellite Ultraspectral Infrared Measurements

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Zhou, Daniel K.; Smith, William L.; Larar, Allen M.; Liu, Xu; Taylor, Jonathan P.; Schluessel, Peter; Strow, L. Larrabee; Mango, Stephen A.

2008-01-01

Atmospheric-thermodynamic parameters and surface properties are basic meteorological parameters for weather forecasting. A physical geophysical parameter retrieval scheme dealing with cloudy and cloud-free radiance observed with satellite ultraspectral infrared sounders has been developed and applied to the Infrared Atmospheric Sounding Interferometer (IASI) and the Atmospheric InfraRed Sounder (AIRS). The retrieved parameters presented herein are from radiance data gathered during the Joint Airborne IASI Validation Experiment (JAIVEx). JAIVEx provided intensive aircraft observations obtained from airborne Fourier Transform Spectrometer (FTS) systems, in-situ measurements, and dedicated dropsonde and radiosonde measurements for the validation of the IASI products. Here, IASI atmospheric profile retrievals are compared with those obtained from dedicated dropsondes, radiosondes, and the airborne FTS system. The IASI examples presented here demonstrate the ability to retrieve fine-scale horizontal features with high vertical resolution from satellite ultraspectral sounder radiance spectra.

An Examination of the Nature of Global MODIS Cloud Regimes

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Oreopoulos, Lazaros; Cho, Nayeong; Lee, Dongmin; Kato, Seiji; Huffman, George J.

2014-01-01

We introduce global cloud regimes (previously also referred to as "weather states") derived from cloud retrievals that use measurements by the Moderate Resolution Imaging Spectroradiometer (MODIS) instrument aboard the Aqua and Terra satellites. The regimes are obtained by applying clustering analysis on joint histograms of retrieved cloud top pressure and cloud optical thickness. By employing a compositing approach on data sets from satellites and other sources, we examine regime structural and thermodynamical characteristics. We establish that the MODIS cloud regimes tend to form in distinct dynamical and thermodynamical environments and have diverse profiles of cloud fraction and water content. When compositing radiative fluxes from the Clouds and the Earth's Radiant Energy System instrument and surface precipitation from the Global Precipitation Climatology Project, we find that regimes with a radiative warming effect on the atmosphere also produce the largest implied latent heat. Taken as a whole, the results of the study corroborate the usefulness of the cloud regime concept, reaffirm the fundamental nature of the regimes as appropriate building blocks for cloud system classification, clarify their association with standard cloud types, and underscore their distinct radiative and hydrological signatures.

Effects of 3-D clouds on atmospheric transmission of solar radiation: Cloud type dependencies inferred from A-train satellite data

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Ham, Seung-Hee; Kato, Seiji; Barker, Howard W.; Rose, Fred G.; Sun-Mack, Sunny

2014-01-01

Three-dimensional (3-D) effects on broadband shortwave top of atmosphere (TOA) nadir radiance, atmospheric absorption, and surface irradiance are examined using 3-D cloud fields obtained from one hour's worth of A-train satellite observations and one-dimensional (1-D) independent column approximation (ICA) and full 3-D radiative transfer simulations. The 3-D minus ICA differences in TOA nadir radiance multiplied by π, atmospheric absorption, and surface downwelling irradiance, denoted as πΔI, ΔA, and ΔT, respectively, are analyzed by cloud type. At the 1 km pixel scale, πΔI, ΔA, and ΔT exhibit poor spatial correlation. Once averaged with a moving window, however, better linear relationships among πΔI, ΔA, and ΔT emerge, especially for moving windows larger than 5 km and large θ0. While cloud properties and solar geometry are shown to influence the relationships amongst πΔI, ΔA, and ΔT, once they are separated by cloud type, their linear relationships become much stronger. This suggests that ICA biases in surface irradiance and atmospheric absorption can be approximated based on ICA biases in nadir radiance as a function of cloud type.

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

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Comiso, Joey C.

1995-01-01

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

Development of multi-sensor global cloud and radiance composites for earth radiation budget monitoring from DSCOVR

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Khlopenkov, Konstantin; Duda, David; Thieman, Mandana; Minnis, Patrick; Su, Wenying; Bedka, Kristopher

2017-10-01

The Deep Space Climate Observatory (DSCOVR) enables analysis of the daytime Earth radiation budget via the onboard Earth Polychromatic Imaging Camera (EPIC) and National Institute of Standards and Technology Advanced Radiometer (NISTAR). Radiance observations and cloud property retrievals from low earth orbit and geostationary satellite imagers have to be co-located with EPIC pixels to provide scene identification in order to select anisotropic directional models needed to calculate shortwave and longwave fluxes. A new algorithm is proposed for optimal merging of selected radiances and cloud properties derived from multiple satellite imagers to obtain seamless global hourly composites at 5-km resolution. An aggregated rating is employed to incorporate several factors and to select the best observation at the time nearest to the EPIC measurement. Spatial accuracy is improved using inverse mapping with gradient search during reprojection and bicubic interpolation for pixel resampling. The composite data are subsequently remapped into EPIC-view domain by convolving composite pixels with the EPIC point spread function defined with a half-pixel accuracy. PSF-weighted average radiances and cloud properties are computed separately for each cloud phase. The algorithm has demonstrated contiguous global coverage for any requested time of day with a temporal lag of under 2 hours in over 95% of the globe.

Influence of turbidity and clouds on satellite total ozone data over Madrid (Spain)

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Camacho, J.L. [Agencia Estatal de Meteorologia (AEMET), Madrid (Spain); Anton, M. [Granada Univ. (Spain). Dept. de Fisica Aplicada; Loyola, D. [German Aerospace Center (DLR), Wessling (DE). Remote Sensing Technology Inst. (IMF); Hernandez, E. [Madrid Univ. Complutense (Spain). Dept. Fisica de la Tierra II

2010-07-01

This article focuses on the comparison of the total ozone column data from three satellite instruments; Total Ozone Mapping Spectrometers (TOMS) on board the Earth Probe (EP), Ozone Monitoring Instrument (OMI) on board AURA and Global Ozone Monitoring Experiment (GOME) on board ERS/2, with ground-based measurement recorded by a well calibrated Brewer spectrophotometer located in Madrid during the period 1996-2008. A cluster classification based on solar radiation (global, direct and diffuse), cloudiness and aerosol index allow selecting hazy, cloudy, very cloudy and clear days. Thus, the differences between Brewer and satellite total ozone data for each cluster have been analyzed. The accuracy of EP-TOMS total ozone data is affected by moderate cloudiness, showing a mean absolute bias error (MABE) of 2.0%. In addition, the turbidity also has a significant influence on EP-TOMS total ozone data with a MABE {proportional_to}1.6%. Those data are in contrast with clear days with MABE {proportional_to}1.2%. The total ozone data derived from the OMI instrument show clear bias at clear and hazy days with small uncertainties ({proportional_to}0.8%). Finally, the total ozone observations obtained with the GOME instrument show a very smooth dependence with respect to clouds and turbidity, showing a robust retrieval algorithm over these conditions. (orig.)

Remote Sensing of Radiative and Microphysical Properties of Clouds During TC (sup 4): Results from MAS, MASTER, MODIS, and MISR

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King, Michael D.; Platnick, Steven; Wind, Galina; Arnold, G. Thomas; Dominguez, Roseanne T.

2010-01-01

The Moderate Resolution Imaging Spectroradiometer (MODIS) Airborne Simulator (MAS) and MODIS/Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) Airborne Simulator (MASTER) were used to obtain measurements of the bidirectional reflectance and brightness temperature of clouds at 50 discrete wavelengths between 0.47 and 14.2 microns (12.9 microns for MASTER). These observations were obtained from the NASA ER-2 aircraft as part of the Tropical Composition, Cloud and Climate Coupling (TC4) experiment conducted over Central America and surrounding Pacific and Atlantic Oceans between 17 July and 8 August 2007. Multispectral images in eleven distinct bands were used to derive a confidence in clear sky (or alternatively the probability Of cloud) over land and ocean ecosystems. Based on the results of individual tests run as part of the cloud mask, an algorithm was developed to estimate the phase of the clouds (liquid water, ice, or undetermined phase). The cloud optical thickness and effective radius were derived for both liquid water and ice clouds that were detected during each flight, using a nearly identical algorithm to that implemented operationally to process MODIS Cloud data from the Aqua and Terra satellites (Collection 5). This analysis shows that the cloud mask developed for operational use on MODIS, and tested using MAS and MASTER data in TC(sup 4), is quite capable of distinguishing both liquid water and ice clouds during daytime conditions over both land and ocean. The cloud optical thickness and effective radius retrievals use five distinct bands of the MAS (or MASTER), and these results were compared with nearly simultaneous retrievals of marine liquid water clouds from MODIS on the Terra spacecraft. Finally, this MODIS-based algorithm was adapted to Multiangle Imaging SpectroRadiometer (MISR) data to infer the cloud optical thickness Of liquid water clouds from MISR. Results of this analysis are compared and contrasted.

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

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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.

The evaluation of GCMs and a new cloud parameterisation using satellite and in-situ data as part of a Climate Process Team

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Grosvenor, D. P.; Wood, R.

2012-12-01

As part of one of the Climate Process Teams (CPTs) we have been testing the implementation of a new cloud parameterization into the CAM5 and AM3 GCMs. The CLUBB parameterization replaces all but the deep convection cloud scheme and uses an innovative PDF based approach to diagnose cloud water content and turbulence. We have evaluated the base models and the CLUBB parameterization in the SE Pacific stratocumulus region using a suite of satellite observation metrics including: Liquid Water Path (LWP) measurements from AMSRE; cloud fractions from CloudSat/CALIPSO; droplet concentrations (Nd) and Cloud Top Temperatures from MODIS; CloudSat precipitation; and relationships between Estimated Inversion Strength (calculated from AMSRE SSTs, Cloud Top Temperatures from MODIS and ECMWF re-analysis fields) and cloud fraction. This region has the advantage of an abundance of in-situ aircraft observations taken during the VOCALS campaign, which is facilitating the diagnosis of the model problems highlighted by the model evaluation. This data has also been recently used to demonstrate the reliability of MODIS Nd estimates. The satellite data needs to be filtered to ensure accurate retrievals and we have been careful to apply the same screenings to the model fields. For example, scenes with high cloud fractions and with output times near to the satellite overpass times can be extracted from the model for a fair comparison with MODIS Nd estimates. To facilitate this we have been supplied with instantaneous model output since screening would not be possible based on time averaged data. We also have COSP satellite simulator output, which allows a fairer comparison between satellite and model. For example, COSP cloud fraction is based upon the detection threshold of the satellite instrument in question. These COSP fields are also used for the model output filtering just described. The results have revealed problems with both the base models and the versions with the CLUBB

The cloud-phase feedback in the Super-parameterized Community Earth System Model

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Burt, M. A.; Randall, D. A.

2016-12-01

Recent comparisons of observations and climate model simulations by I. Tan and colleagues have suggested that the Wegener-Bergeron-Findeisen (WBF) process tends to be too active in climate models, making too much cloud ice, and resulting in an exaggerated negative cloud-phase feedback on climate change. We explore the WBF process and its effect on shortwave cloud forcing in present-day and future climate simulations with the Community Earth System Model, and its super-parameterized counterpart. Results show that SP-CESM has much less cloud ice and a weaker cloud-phase feedback than CESM.

Comparing airborne and satellite retrievals of cloud optical thickness and particle effective radius using a spectral radiance ratio technique: two case studies for cirrus and deep convective clouds

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Krisna, Trismono C.; Wendisch, Manfred; Ehrlich, André; Jäkel, Evelyn; Werner, Frank; Weigel, Ralf; Borrmann, Stephan; Mahnke, Christoph; Pöschl, Ulrich; Andreae, Meinrat O.; Voigt, Christiane; Machado, Luiz A. T.

2018-04-01

Solar radiation reflected by cirrus and deep convective clouds (DCCs) was measured by the Spectral Modular Airborne Radiation Measurement System (SMART) installed on the German High Altitude and Long Range Research Aircraft (HALO) during the Mid-Latitude Cirrus (ML-CIRRUS) and the Aerosol, Cloud, Precipitation, and Radiation Interaction and Dynamic of Convective Clouds System - Cloud Processes of the Main Precipitation Systems in Brazil: A Contribution to Cloud Resolving Modelling and to the Global Precipitation Measurement (ACRIDICON-CHUVA) campaigns. On particular flights, HALO performed measurements closely collocated with overpasses of the Moderate Resolution Imaging Spectroradiometer (MODIS) aboard the Aqua satellite. A cirrus cloud located above liquid water clouds and a DCC topped by an anvil cirrus are analyzed in this paper. Based on the nadir spectral upward radiance measured above the two clouds, the optical thickness τ and particle effective radius reff of the cirrus and DCC are retrieved using a radiance ratio technique, which considers the cloud thermodynamic phase, the vertical profile of cloud microphysical properties, the presence of multilayer clouds, and the heterogeneity of the surface albedo. For the cirrus case, the comparison of τ and reff retrieved on the basis of SMART and MODIS measurements yields a normalized mean absolute deviation of up to 1.2 % for τ and 2.1 % for reff. For the DCC case, deviations of up to 3.6 % for τ and 6.2 % for reff are obtained. The larger deviations in the DCC case are mainly attributed to the fast cloud evolution and three-dimensional (3-D) radiative effects. Measurements of spectral upward radiance at near-infrared wavelengths are employed to investigate the vertical profile of reff in the cirrus. The retrieved values of reff are compared with corresponding in situ measurements using a vertical weighting method. Compared to the MODIS observations, measurements of SMART provide more information on the

First Transmitted Hyperspectral Light Measurements and Cloud Properties from Recent Field Campaign Sampling Clouds Under Biomass Burning Aerosol

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Leblanc, S.; Redemann, Jens; Shinozuka, Yohei; Flynn, Connor J.; Segal Rozenhaimer, Michal; Kacenelenbogen, Meloe Shenandoah; Pistone, Kristina Marie Myers; Schmidt, Sebastian; Cochrane, Sabrina

2016-01-01

We present a first view of data collected during a recent field campaign aimed at measuring biomass burning aerosol above clouds from airborne platforms. The NASA ObseRvations of CLouds above Aerosols and their intEractionS (ORACLES) field campaign recently concluded its first deployment sampling clouds and overlying aerosol layer from the airborne platform NASA P3. We present results from the Spectrometer for Sky-Scanning, Sun-Tracking Atmospheric Research (4STAR), in conjunction with the Solar Spectral Flux Radiometers (SSFR). During this deployment, 4STAR sampled transmitted solar light either via direct solar beam measurements and scattered light measurements, enabling the measurement of aerosol optical thickness and the retrieval of information on aerosol particles in addition to overlying cloud properties. We focus on the zenith-viewing scattered light measurements, which are used to retrieve cloud optical thickness, effective radius, and thermodynamic phase of clouds under a biomass burning layer. The biomass burning aerosol layer present above the clouds is the cause of potential bias in retrieved cloud optical depth and effective radius from satellites. We contrast the typical reflection based approach used by satellites to the transmission based approach used by 4STAR during ORACLES for retrieving cloud properties. It is suspected that these differing approaches will yield a change in retrieved properties since light transmitted through clouds is sensitive to a different cloud volume than reflected light at cloud top. We offer a preliminary view of the implications of these differences in sampling volumes to the calculation of cloud radiative effects (CRE).

Design of a novel coil satellite centrifuge and its performance on counter-current chromatographic separation of 4-methylumbelliferyl sugar derivatives with organic-aqueous two-phase solvent systems

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Shinomiya, Kazufusa; Tokura, Koji; Kimura, Emiru; Takai, Midori; Harikai, Naoki; Yoshida, Kazunori; Yanagidaira, Kazuhiro; Ito, Yoichiro

2015-01-01

A new high-speed counter-current chromatograph, named coil satellite centrifuge (CSC), was designed and fabricated in our laboratory. The CSC apparatus produces the satellite motion such that the coiled column simultaneously rotates around the sun axis (the angular velocity, ω1), the planet axis (ω2) and the satellite axis (the central axis of the column) (ω3). In order to achieve this triplicate rotary motion without twisting of the flow tube, the rotation of each axis was determined by the following formula: ω1 = ω2 + ω3. This relation enabled to lay out the flow tube by two different ways, the SS type and the JS type. In the SS type, the flow tube was introduced from the upper side of the apparatus into the sun axis of the first rotary frame and connected to the planet axis of the second rotary frame like a double letter SS. In the JS type, the flow tube was introduced from the bottom of the apparatus into the sun axis reaching the upper side of the planet axis an inversed letter J, followed by distribution as in the SS type. The performance of the apparatus was examined on separation of 4-methylumbelliferyl (MU) sugar derivatives as test samples with organic-aqueous two-phase solvent systems composed of ethyl acetate/1-butanol/water (3 : 2 : 5, v/v) for lower phase mobile and (1 : 4 : 5, v/v) for upper phase mobile. With lower phase mobile, five 4-MU sugar derivatives including β-D-cellobioside (Cel), β-D-glucopyranoside, α-D-mannopyranoside, β-D-fucopyranoside and α-L-fucopyranoside (α-L-Fuc) were separated with the combined rotation around each axis at counterclockwise (CCW) (ω1) – CCW (ω2) – CCW (ω3) by the JS type flow tube distribution. With upper phase mobile, three 4-MU sugar derivatives including α-L-Fuc, β-D-galactopyranoside and Cel were separated with the combined rotation around each axis at clockwise (CW) (ω1) – CW (ω2) – CW (ω3) by the JS type flow tube distribution. A series of experiments on peak resolution and

Cloud-to-Ground Lightning Estimates Derived from SSMI Microwave Remote Sensing and NLDN

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Winesett, Thomas; Magi, Brian; Cecil, Daniel

2015-01-01

present in the cloud and electric charge separation occurs. These ice particles efficiently scatter the microwave radiation at the 85 and 37 GHz frequencies, thus leading to large brightness temperature depressions. Lightning flash rate is related to the total amount of ice passing through the convective updraft regions of thunderstorms. Confirmation of this relationship using TRMM LIS and TMI data, however, remains constrained to TRMM observational limits of the tropics and subtropics. Satellites from the Defense Meteorology Satellite Program (DMSP) have global coverage and are equipped with passive microwave imagers that, like TMI, observe brightness temperatures at 85 and 37 GHz. Unlike the TRMM satellite, however, DMSP satellites do not have a lightning sensor, and the DMSP microwave data has never been used to derive global lightning. In this presentation, a relationship between DMSP Special Sensor Microwave Imager (SSMI) data and ground-based cloud-to-ground (CG) lightning data from NLDN is investigated to derive a spatially complete time history of CG lightning for the USA study area. This relationship is analogous to the established using TRMM LIS and TMI data. NLDN has the most spatially and temporally complete CG lightning data for the USA, and therefore provides the best opportunity to find geospatially coincident observations with SSMI sensors. The strongest thunderstorms generally have minimum 85 GHz Polarized Corrected brightness Temperatures (PCT) less than 150 K. Archived radar data was used to resolve the spatial extent of the individual storms. NLDN data for that storm spatial extent defined by radar data was used to calculate the CG flash rate for the storm. Similar to results using TRMM sensors, a linear model best explained the relationship between storm-specific CG flash rates and minimum 85 GHz PCT. However, the results in this study apply only to CG lightning. To extend the results to weaker storms, the probability of CG lightning (instead of the

Cloud detection algorithm comparison and validation for operational Landsat data products

Science.gov (United States)

Foga, Steven Curtis; Scaramuzza, Pat; Guo, Song; Zhu, Zhe; Dilley, Ronald; Beckmann, Tim; Schmidt, Gail L.; Dwyer, John L.; Hughes, MJ; Laue, Brady

2017-01-01

Clouds are a pervasive and unavoidable issue in satellite-borne optical imagery. Accurate, well-documented, and automated cloud detection algorithms are necessary to effectively leverage large collections of remotely sensed data. The Landsat project is uniquely suited for comparative validation of cloud assessment algorithms because the modular architecture of the Landsat ground system allows for quick evaluation of new code, and because Landsat has the most comprehensive manual truth masks of any current satellite data archive. Currently, the Landsat Level-1 Product Generation System (LPGS) uses separate algorithms for determining clouds, cirrus clouds, and snow and/or ice probability on a per-pixel basis. With more bands onboard the Landsat 8 Operational Land Imager (OLI)/Thermal Infrared Sensor (TIRS) satellite, and a greater number of cloud masking algorithms, the U.S. Geological Survey (USGS) is replacing the current cloud masking workflow with a more robust algorithm that is capable of working across multiple Landsat sensors with minimal modification. Because of the inherent error from stray light and intermittent data availability of TIRS, these algorithms need to operate both with and without thermal data. In this study, we created a workflow to evaluate cloud and cloud shadow masking algorithms using cloud validation masks manually derived from both Landsat 7 Enhanced Thematic Mapper Plus (ETM +) and Landsat 8 OLI/TIRS data. We created a new validation dataset consisting of 96 Landsat 8 scenes, representing different biomes and proportions of cloud cover. We evaluated algorithm performance by overall accuracy, omission error, and commission error for both cloud and cloud shadow. We found that CFMask, C code based on the Function of Mask (Fmask) algorithm, and its confidence bands have the best overall accuracy among the many algorithms tested using our validation data. The Artificial Thermal-Automated Cloud Cover Algorithm (AT-ACCA) is the most accurate

In search of the best match: probing a multi-dimensional cloud microphysical parameter space to better understand what controls cloud thermodynamic phase

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Tan, Ivy; Storelvmo, Trude

2015-04-01

Substantial improvements have been made to the cloud microphysical schemes used in the latest generation of global climate models (GCMs), however, an outstanding weakness of these schemes lies in the arbitrariness of their tuning parameters, which are also notoriously fraught with uncertainties. Despite the growing effort in improving the cloud microphysical schemes in GCMs, most of this effort has neglected to focus on improving the ability of GCMs to accurately simulate the present-day global distribution of thermodynamic phase partitioning in mixed-phase clouds. Liquid droplets and ice crystals not only influence the Earth's radiative budget and hence climate sensitivity via their contrasting optical properties, but also through the effects of their lifetimes in the atmosphere. The current study employs NCAR's CAM5.1, and uses observations of cloud phase obtained by NASA's CALIOP lidar over a 79-month period (November 2007 to June 2014) guide the accurate simulation of the global distribution of mixed-phase clouds in 20∘ latitudinal bands at the -10∘ C, -20∘C and -30∘C isotherms, by adjusting six relevant cloud microphysical tuning parameters in the CAM5.1 via Quasi-Monte Carlo sampling. Among the parameters include those that control the Wegener-Bergeron-Findeisen (WBF) timescale for the conversion of supercooled liquid droplets to ice and snow in mixed-phase clouds, the fraction of ice nuclei that nucleate ice in the atmosphere, ice crystal sedimentation speed, and wet scavenging in stratiform and convective clouds. Using a Generalized Linear Model as a variance-based sensitivity analysis, the relative contributions of each of the six parameters are quantified to gain a better understanding of the importance of their individual and two-way interaction effects on the liquid to ice proportion in mixed-phase clouds. Thus, the methodology implemented in the current study aims to search for the combination of cloud microphysical parameters in a GCM that

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

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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.

Modelling micro- and macrophysical contributors to the dissipation of an Arctic mixed-phase cloud during the Arctic Summer Cloud Ocean Study (ASCOS

Directory of Open Access Journals (Sweden)

K. Loewe

2017-06-01

Full Text Available The Arctic climate is changing; temperature changes in the Arctic are greater than at midlatitudes, and changing atmospheric conditions influence Arctic mixed-phase clouds, which are important for the Arctic surface energy budget. These low-level clouds are frequently observed across the Arctic. They impact the turbulent and radiative heating of the open water, snow, and sea-ice-covered surfaces and influence the boundary layer structure. Therefore the processes that affect mixed-phase cloud life cycles are extremely important, yet relatively poorly understood. In this study, we present sensitivity studies using semi-idealized large eddy simulations (LESs to identify processes contributing to the dissipation of Arctic mixed-phase clouds. We found that one potential main contributor to the dissipation of an observed Arctic mixed-phase cloud, during the Arctic Summer Cloud Ocean Study (ASCOS field campaign, was a low cloud droplet number concentration (CDNC of about 2 cm−3. Introducing a high ice crystal concentration of 10 L−1 also resulted in cloud dissipation, but such high ice crystal concentrations were deemed unlikely for the present case. Sensitivity studies simulating the advection of dry air above the boundary layer inversion, as well as a modest increase in ice crystal concentration of 1 L−1, did not lead to cloud dissipation. As a requirement for small droplet numbers, pristine aerosol conditions in the Arctic environment are therefore considered an important factor determining the lifetime of Arctic mixed-phase clouds.

Global spectroscopic survey of cloud thermodynamic phase at high spatial resolution, 2005-2015

Science.gov (United States)

Thompson, David R.; Kahn, Brian H.; Green, Robert O.; Chien, Steve A.; Middleton, Elizabeth M.; Tran, Daniel Q.

2018-02-01

The distribution of ice, liquid, and mixed phase clouds is important for Earth's planetary radiation budget, impacting cloud optical properties, evolution, and solar reflectivity. Most remote orbital thermodynamic phase measurements observe kilometer scales and are insensitive to mixed phases. This under-constrains important processes with outsize radiative forcing impact, such as spatial partitioning in mixed phase clouds. To date, the fine spatial structure of cloud phase has not been measured at global scales. Imaging spectroscopy of reflected solar energy from 1.4 to 1.8 µm can address this gap: it directly measures ice and water absorption, a robust indicator of cloud top thermodynamic phase, with spatial resolution of tens to hundreds of meters. We report the first such global high spatial resolution survey based on data from 2005 to 2015 acquired by the Hyperion imaging spectrometer onboard NASA's Earth Observer 1 (EO-1) spacecraft. Seasonal and latitudinal distributions corroborate observations by the Atmospheric Infrared Sounder (AIRS). For extratropical cloud systems, just 25 % of variance observed at GCM grid scales of 100 km was related to irreducible measurement error, while 75 % was explained by spatial correlations possible at finer resolutions.

Optical and Microphysical Retrievals of Marine Stratocumulus Clouds off the Coast of Namibia from Satellite and Aircraft

Science.gov (United States)

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

Satellite data sets for the atmospheric radiation measurement (ARM) program

Energy Technology Data Exchange (ETDEWEB)

Shi, L.; Bernstein, R.L. [SeaSpace Corp., San Diego, CA (United States)

1996-04-01

This abstract describes the type of data obtained from satellite measurements in the Atmospheric Radiation Measurement (ARM) program. The data sets have been widely used by the ARM team to derive cloud-top altitude, cloud cover, snow and ice cover, surface temperature, water vapor, and wind, vertical profiles of temperature, and continuoous observations of weather needed to track and predict severe weather.

CloudSat 2C-ICE product update with a new Ze parameterization in lidar-only region.

Science.gov (United States)

Deng, Min; Mace, Gerald G; Wang, Zhien; Berry, Elizabeth

2015-12-16

The CloudSat 2C-ICE data product is derived from a synergetic ice cloud retrieval algorithm that takes as input a combination of CloudSat radar reflectivity ( Z e ) and Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation lidar attenuated backscatter profiles. The algorithm uses a variational method for retrieving profiles of visible extinction coefficient, ice water content, and ice particle effective radius in ice or mixed-phase clouds. Because of the nature of the measurements and to maintain consistency in the algorithm numerics, we choose to parameterize (with appropriately large specification of uncertainty) Z e and lidar attenuated backscatter in the regions of a cirrus layer where only the lidar provides data and where only the radar provides data, respectively. To improve the Z e parameterization in the lidar-only region, the relations among Z e , extinction, and temperature have been more thoroughly investigated using Atmospheric Radiation Measurement long-term millimeter cloud radar and Raman lidar measurements. This Z e parameterization provides a first-order estimation of Z e as a function extinction and temperature in the lidar-only regions of cirrus layers. The effects of this new parameterization have been evaluated for consistency using radiation closure methods where the radiative fluxes derived from retrieved cirrus profiles compare favorably with Clouds and the Earth's Radiant Energy System measurements. Results will be made publicly available for the entire CloudSat record (since 2006) in the most recent product release known as R05.

Global distributions of cloud properties for CERES

Science.gov (United States)

Sun-Mack, S.; Minnis, P.; Heck, P.; Young, D.

2003-04-01

The microphysical and macrophysical properties of clouds play a crucial role in the earth's radiation budget. Simultaneous measurement of the radiation and cloud fields on a global basis has long been recognized as a key component in understanding and modeling the interaction between clouds and radiation at the top of the atmosphere, at the surface, and within the atmosphere. With the implementation of the NASA Clouds and Earth's Radiant Energy System (CERES) in 1998, this need is being met. Broadband shortwave and longwave radiance measurements taken by the CERES scanners at resolutions between 10 and 20 km on the Tropical Rainfall Measuring Mission (TRMM), Terra, and Aqua satellites are matched to simultaneous retrievals of cloud height, phase, particle size, water path, and optical depth from the TRMM Visible Infrared Scanner and the Moderate Resolution Imaging Spectroradiometer (MODIS) on Terra and Aqua. The combined cloud-radiation product has already been used for developing new, highly accurate anisotropic directional models for converting broadband radiances to flux. They also provide a consistent measure of cloud properties at different times of day over the globe since January 1998. These data will be valuable for determining the indirect effects of aerosols and for linking cloud water to cloud radiation. This paper provides an overview of the CERES cloud products from the three satellites including the retrieval methodology, validation, and global distributions. Availability and access to the datasets will also be discussed.

Uncertainties and applications of satellite-derived coastal water quality products

Science.gov (United States)

Zheng, Guangming; DiGiacomo, Paul M.

2017-12-01

Recent and forthcoming launches of a plethora of ocean color radiometry sensors, coupled with increasingly adopted free and open data policies are expected to boost usage of satellite ocean color data and drive the demand to use these data in a quantitative and routine manner. Here we review factors that introduce uncertainties to various satellite-derived water quality products and recommend approaches to minimize the uncertainty of a specific product. We show that the regression relationships between remote-sensing reflectance and water turbidity (in terms of nephelometric units) established for different regions tend to converge and therefore it is plausible to develop a global satellite water turbidity product derived using a single algorithm. In contrast, solutions to derive suspended particulate matter concentration are much less generalizable; in one case it might be more accurate to estimate this parameter based on satellite-derived particulate backscattering coefficient, whereas in another the nonagal particulate absorption coefficient might be a better proxy. Regarding satellite-derived chlorophyll concentration, known to be subject to large uncertainties in coastal waters, studies summarized here clearly indicate that the accuracy of classical reflectance band-ratio algorithms depends largely on the contribution of phytoplankton to total light absorption coefficient as well as the degree of correlation between phytoplankton and the dominant nonalgal contributions. Our review also indicates that currently available satellite-derived water quality products are restricted to optically significant materials, whereas many users are interested in toxins, nutrients, pollutants, and pathogens. Presently, proxies or indicators for these constituents are inconsistently (and often incorrectly) developed and applied. Progress in this general direction will remain slow unless, (i) optical oceanographers and environmental scientists start collaborating more closely

Parameterization of the Extinction Coefficient in Ice and Mixed-Phase Arctic Clouds during the ISDAC Field Campaign

Energy Technology Data Exchange (ETDEWEB)

Korolev, A; Shashkov, A; Barker, H

2012-03-06

This report documents the history of attempts to directly measure cloud extinction, the current measurement device known as the Cloud Extinction Probe (CEP), specific problems with direct measurement of extinction coefficient, and the attempts made here to address these problems. Extinction coefficient is one of the fundamental microphysical parameters characterizing bulk properties of clouds. Knowledge of extinction coefficient is of crucial importance for radiative transfer calculations in weather prediction and climate models given that Earth's radiation budget (ERB) is modulated much by clouds. In order for a large-scale model to properly account for ERB and perturbations to it, it must ultimately be able to simulate cloud extinction coefficient well. In turn this requires adequate and simultaneous simulation of profiles of cloud water content and particle habit and size. Similarly, remote inference of cloud properties requires assumptions to be made about cloud phase and associated single-scattering properties, of which extinction coefficient is crucial. Hence, extinction coefficient plays an important role in both application and validation of methods for remote inference of cloud properties from data obtained from both satellite and surface sensors (e.g., Barker et al. 2008). While estimation of extinction coefficient within large-scale models is relatively straightforward for pure water droplets, thanks to Mie theory, mixed-phase and ice clouds still present problems. This is because of the myriad forms and sizes that crystals can achieve, each having their own unique extinction properties. For the foreseeable future, large-scale models will have to be content with diagnostic parametrization of crystal size and type. However, before they are able to provide satisfactory values needed for calculation of radiative transfer, they require the intermediate step of assigning single-scattering properties to particles. The most basic of these is extinction

Three-dimensional cloud characterization from paired whole-sky imaging cameras

International Nuclear Information System (INIS)

Allmen, M.; Kegelmeyer, W.P. Jr.

1994-01-01

Three-dimensional (3-D) cloud characterization permits the derivation of important cloud geometry properties such as fractional cloudiness, mean cloud and clear length, aspect ratio, and the morphology of cloud cover. These properties are needed as input to the hierarchical diagnosis (HD) and instantaneous radiative transfer (IRF) models, to validate sub-models for cloud occurrence and formation, and to Central Site radiative flux calculations. A full 3-D characterization will eventually require the integration of disparate Cloud and Radiation Testbed (CART) data sources: whole-sky imagers (WSIs), radar, satellites, ceilometers, volume-imaging lidar, and other sensors. In this paper, we demonstrate how an initial 3-D cloud property, cloud base height, can be determined from fusing paired times series of images from two whole-sky imagers

Aerosol indirect effects -- general circulation model intercomparison and evaluation with satellite data

Energy Technology Data Exchange (ETDEWEB)

Quaas, Johannes; Ming, Yi; Menon, Surabi; Takemura, Toshihiko; Wang, Minghuai; Penner, Joyce E.; Gettelman, Andrew; Lohmann, Ulrike; Bellouin, Nicolas; Boucher, Olivier; Sayer, Andrew M.; Thomas, Gareth E.; McComiskey, Allison; Feingold, Graham; Hoose, Corinna; Kristjansson, Jon Egill; Liu, Xiaohong; Balkanski, Yves; Donner, Leo J.; Ginoux, Paul A.; Stier, Philip; Feichter, Johann; Sednev, Igor; Bauer, Susanne E.; Koch, Dorothy; Grainger, Roy G.; Kirkevag, Alf; Iversen, Trond; Seland, Oyvind; Easter, Richard; Ghan, Steven J.; Rasch, Philip J.; Morrison, Hugh; Lamarque, Jean-Francois; Iacono, Michael J.; Kinne, Stefan; Schulz, Michael

2009-04-10

Aerosol indirect effects continue to constitute one of the most important uncertainties for anthropogenic climate perturbations. Within the international AEROCOM initiative, the representation of aerosol-cloud-radiation interactions in ten different general circulation models (GCMs) is evaluated using three satellite datasets. The focus is on stratiform liquid water clouds since most GCMs do not include ice nucleation effects, and none of the model explicitly parameterizes aerosol effects on convective clouds. We compute statistical relationships between aerosol optical depth (Ta) and various cloud and radiation quantities in a manner that is consistent between the models and the satellite data. It is found that the model-simulated influence of aerosols on cloud droplet number concentration (Nd) compares relatively well to the satellite data at least over the ocean. The relationship between Ta and liquid water path is simulated much too strongly by the models. It is shown that this is partly related to the representation of the second aerosol indirect effect in terms of autoconversion. A positive relationship between total cloud fraction (fcld) and Ta as found in the satellite data is simulated by the majority of the models, albeit less strongly than that in the satellite data in most of them. In a discussion of the hypotheses proposed in the literature to explain the satellite-derived strong fcld - Ta relationship, our results indicate that none can be identified as unique explanation. Relationships similar to the ones found in satellite data between Ta and cloud top temperature or outgoing long-wave radiation (OLR) are simulated by only a few GCMs. The GCMs that simulate a negative OLR - Ta relationship show a strong positive correlation between Ta and fcld The short-wave total aerosol radiative forcing as simulated by the GCMs is strongly influenced by the simulated anthropogenic fraction of Ta, and parameterisation assumptions such as a lower bound on Nd

Advanced Analysis of the Influence of Clouds, Precipiation and Surface Emissivity on DMSP/NPOESS Satellite Microwave Channels

National Research Council Canada - National Science Library

Isaacs, R

2002-01-01

...: development of databases of brightness temperatures from various satellite sensors; development databases of conventional analysis to verify the presence and amount of clouds and precipitation and for verification of retrieval results...

A numerical study of aerosol influence on mixed-phase stratiform clouds through modulation of the liquid phase

Directory of Open Access Journals (Sweden)

G. de Boer

2013-02-01

Full Text Available Numerical simulations were carried out in a high-resolution two-dimensional framework to increase our understanding of aerosol indirect effects in mixed-phase stratiform clouds. Aerosol characteristics explored include insoluble particle type, soluble mass fraction, influence of aerosol-induced freezing point depression and influence of aerosol number concentration. Simulations were analyzed with a focus on the processes related to liquid phase microphysics, and ice formation was limited to droplet freezing. Of the aerosol properties investigated, aerosol insoluble mass type and its associated freezing efficiency was found to be most relevant to cloud lifetime. Secondary effects from aerosol soluble mass fraction and number concentration also alter cloud characteristics and lifetime. These alterations occur via various mechanisms, including changes to the amount of nucleated ice, influence on liquid phase precipitation and ice riming rates, and changes to liquid droplet nucleation and growth rates. Alteration of the aerosol properties in simulations with identical initial and boundary conditions results in large variability in simulated cloud thickness and lifetime, ranging from rapid and complete glaciation of liquid to the production of long-lived, thick stratiform mixed-phase cloud.

Assessment of Satellite-Derived Surface Reflectances by NASA's CAR Airborne Radiometer over Railroad Valley, Nevada

Science.gov (United States)

Kharbouche, Said; Muller, Jan-Peter; Gatebe, Charles K.; Scanlon, Tracy; Banks, Andrew C.

2017-01-01

CAR (Cloud Absorption Radiometer) is a multi-angular and multi-spectral airborne radiometer instrument, whose radiometric and geometric characteristics are well calibrated and adjusted before and after each flight campaign. CAR was built by NASA (National Aeronautics and Space Administration) in 1984. On 16 May 2008, a CAR flight campaign took place over the well-known calibration and validation site of Railroad Valley in Nevada (38.504 deg N, 115.692 deg W).The campaign coincided with the overpasses of several key EO (Earth Observation) satellites such as Landsat-7, Envisat and Terra. Thus, there are nearly simultaneous measurements from these satellites and the CAR airborne sensor over the same calibration site. The CAR spectral bands are close to those of most EO satellites. CAR has the ability to cover the whole range of azimuth view angles and a variety of zenith angles depending on altitude and, as a consequence, the biases seen between satellite and CAR measurements due to both unmatched spectral bands and unmatched angles can be significantly reduced. A comparison is presented here between CARs land surface reflectance (BRF or Bidirectional Reflectance Factor) with those derived from Terra/MODIS (MOD09 and MAIAC), Terra/MISR, Envisat/MERIS and Landsat-7. In this study, we utilized CAR data from low altitude flights (approx. 180 m above the surface) in order to minimize the effects of the atmosphere on these measurements and then obtain a valuable ground-truth data set of surface reflectance. Furthermore, this study shows that differences between measurements caused by surface heterogeneity can be tolerated, thanks to the high homogeneity of the study site on the one hand, and on the other hand, to the spatial sampling and the large number of CAR samples. These results demonstrate that satellite BRF measurements over this site are in good agreement with CAR with variable biases across different spectral bands. This is most likely due to residual aerosol

Observed aerosol suppression of cloud ice in low-level Arctic mixed-phase clouds

OpenAIRE

Norgren, Matthew S.; Boer, Gijs; Shupe, Matthew D.

2018-01-01

The interactions that occur between aerosols and a mixed-phase cloud system, and the subsequent alteration of the microphysical state of such clouds, is a problem that has yet to be well constrained. Advancing our understanding of aerosol-ice processes is necessary to determine the impact of natural and anthropogenic emissions on Earth’s climate and to improve our capability to predict future climate states. This paper deals specifically with how aerosols influence ice mass production in low-...

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

Energy Technology Data Exchange (ETDEWEB)

Protat, Alain; Young, Stuart; McFarlane, Sally A.; L' Ecuyer, Tristan; Mace, Gerald G.; Comstock, Jennifer M.; Long, Charles N.; Berry, Elizabeth; Delanoe, Julien

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 with 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.

Comparing parameterized versus measured microphysical properties of tropical convective cloud bases during the ACRIDICON–CHUVA campaign

Directory of Open Access Journals (Sweden)

R. C. Braga

2017-06-01

Full Text Available The objective of this study is to validate parameterizations that were recently developed for satellite retrievals of cloud condensation nuclei supersaturation spectra, NCCN(S, at cloud base alongside more traditional parameterizations connecting NCCN(S with cloud base updrafts and drop concentrations. This was based on the HALO aircraft measurements during the ACRIDICON–CHUVA campaign over the Amazon region, which took place in September 2014. The properties of convective clouds were measured with a cloud combination probe (CCP, a cloud and aerosol spectrometer (CAS-DPOL, and a CCN counter onboard the HALO aircraft. An intercomparison of the cloud drop size distributions (DSDs and the cloud water content (CWC derived from the different instruments generally shows good agreement within the instrumental uncertainties. To this end, the directly measured cloud drop concentrations (Nd near cloud base were compared with inferred values based on the measured cloud base updraft velocity (Wb and NCCN(S spectra. The measurements of Nd at cloud base were also compared with drop concentrations (Na derived on the basis of an adiabatic assumption and obtained from the vertical evolution of cloud drop effective radius (re above cloud base. The measurements of NCCN(S and Wb reproduced the observed Nd within the measurements uncertainties when the old (1959 Twomey's parameterization was used. The agreement between the measured and calculated Nd was only within a factor of 2 with attempts to use cloud base S, as obtained from the measured Wb, Nd, and NCCN(S. This underscores the yet unresolved challenge of aircraft measurements of S in clouds. Importantly, the vertical evolution of re with height reproduced the observation-based nearly adiabatic cloud base drop concentrations, Na. The combination of these results provides aircraft observational support for the various components of the satellite-retrieved methodology that was recently developed to

Representation of Arctic mixed-phase clouds and the Wegener-Bergeron-Findeisen process in climate models: Perspectives from a cloud-resolving study

Science.gov (United States)

Fan, Jiwen; Ghan, Steven; Ovchinnikov, Mikhail; Liu, Xiaohong; Rasch, Philip J.; Korolev, Alexei

2011-01-01

Two types of Arctic mixed-phase clouds observed during the ISDAC and M-PACE field campaigns are simulated using a 3-dimensional cloud-resolving model (CRM) with size-resolved cloud microphysics. The modeled cloud properties agree reasonably well with aircraft measurements and surface-based retrievals. Cloud properties such as the probability density function (PDF) of vertical velocity (w), cloud liquid and ice, regimes of cloud particle growth, including the Wegener-Bergeron-Findeisen (WBF) process, and the relationships among properties/processes in mixed-phase clouds are examined to gain insights for improving their representation in General Circulation Models (GCMs). The PDF of the simulated w is well represented by a Gaussian function, validating, at least for arctic clouds, the subgrid treatment used in GCMs. The PDFs of liquid and ice water contents can be approximated by Gamma functions, and a Gaussian function can describe the total water distribution, but a fixed variance assumption should be avoided in both cases. The CRM results support the assumption frequently used in GCMs that mixed phase clouds maintain water vapor near liquid saturation. Thus, ice continues to grow throughout the stratiform cloud but the WBF process occurs in about 50% of cloud volume where liquid and ice co-exist, predominantly in downdrafts. In updrafts, liquid and ice particles grow simultaneously. The relationship between the ice depositional growth rate and cloud ice strongly depends on the capacitance of ice particles. The simplified size-independent capacitance of ice particles used in GCMs could lead to large deviations in ice depositional growth.

A 'special effort' to provide improved sounding and cloud-motion wind data for FGGE. [First GARP Global Experiment

Science.gov (United States)

Greaves, J. R.; Dimego, G.; Smith, W. L.; Suomi, V. E.

1979-01-01

Enhancement and editing of high-density cloud motion wind assessments and research satellite soundings have been necessary to improve the quality of data used in The Global Weather Experiment. Editing operations are conducted by a man-computer interactive data access system. Editing will focus on such inputs as non-US satellite data, NOAA operational sounding and wind data sets, wind data from the Indian Ocean satellite, dropwindsonde data, and tropical mesoscale wind data. Improved techniques for deriving cloud heights and higher resolution sounding in meteorologically active areas are principal parts of the data enhancement program.

Characterization of Mixed-Phase Clouds in the Laboratory

Science.gov (United States)

Foster, T. C.; Hallett, J.

2005-12-01

A technique was developed in which a mixed-phase cloud of controllable ice and water content is created. First a freezer filled with a water droplet cloud becomes supercooled. Then, in an isolated small volume of the freezer, an adjustable adiabatic expansion locally nucleates ice. Finally the two regions of the cloud are vigorously stirred together producing a mixed-phase cloud throughout the chamber. At this point the water droplets evaporate and the crystals grow at a slow measurable rate, until a fully glaciated cloud results. Experiments were carried out at temperatures near -20 C in a standard top-opening chest freezer. A cloud of supercooled water droplets several micrometers in diameter was produced by a commercial ultrasonic nebulizer. Ice was nucleated using the discharge of an empty compressed air pistol pumped to different initial pressures. In that process high-pressure room temperature air in the pistol expands adiabatically, cooling the air enough to nucleate water droplets which then freeze homogeneously if sufficiently cold. The freezer was partitioned with thick movable walls of foam material to isolate the ice cloud in a small volume of the freezer before mixing occurs. Clouds of supercooled water droplets or of ice particles are readily produced and examined in collimated white light beams. They look similar visually in some cases although normally large crystals with flat reflecting surfaces clearly differ due to the flashes of reflected light. When the pistol is discharged into the supercooled water cloud, it displays a distinct hazy bluish "plume." But discharge into the ice particle cloud leaves no such plume: that discharge only mixes the particles present. This discharge is a test of glaciation in our initially mixed freezer cloud. A visible plume indicates that supercooled water remains in the cloud and no plume indicates the cloud is entirely ice at a high concentration. Our first unsuccessful experiments were done with the freezer

Vertical microphysical profiles of convective clouds as a tool for obtaining aerosol cloud-mediated climate forcings

Energy Technology Data Exchange (ETDEWEB)

Rosenfeld, Daniel [Hebrew Univ. of Jerusalem (Israel)

2015-12-23

Quantifying the aerosol/cloud-mediated radiative effect at a global scale requires simultaneous satellite retrievals of cloud condensation nuclei (CCN) concentrations and cloud base updraft velocities (Wb). Hitherto, the inability to do so has been a major cause of high uncertainty regarding anthropogenic aerosol/cloud-mediated radiative forcing. This can be addressed by the emerging capability of estimating CCN and Wb of boundary layer convective clouds from an operational polar orbiting weather satellite. Our methodology uses such clouds as an effective analog for CCN chambers. The cloud base supersaturation (S) is determined by Wb and the satellite-retrieved cloud base drop concentrations (Ndb), which is the same as CCN(S). Developing and validating this methodology was possible thanks to the ASR/ARM measurements of CCN and vertical updraft profiles. Validation against ground-based CCN instruments at the ARM sites in Oklahoma, Manaus, and onboard a ship in the northeast Pacific showed a retrieval accuracy of ±25% to ±30% for individual satellite overpasses. The methodology is presently limited to boundary layer not raining convective clouds of at least 1 km depth that are not obscured by upper layer clouds, including semitransparent cirrus. The limitation for small solar backscattering angles of <25º restricts the satellite coverage to ~25% of the world area in a single day. This methodology will likely allow overcoming the challenge of quantifying the aerosol indirect effect and facilitate a substantial reduction of the uncertainty in anthropogenic climate forcing.

Retrieval of Ice Cloud Properties Using Variable Phase Functions

Science.gov (United States)

Heck, Patrick W.; Minnis, Patrick; Yang, Ping; Chang, Fu-Lung; Palikonda, Rabindra; Arduini, Robert F.; Sun-Mack, Sunny

2009-03-01

An enhancement to NASA Langley's Visible Infrared Solar-infrared Split-window Technique (VISST) is developed to identify and account for situations when errors are induced by using smooth ice crystals. The retrieval scheme incorporates new ice cloud phase functions that utilize hexagonal crystals with roughened surfaces. In some situations, cloud optical depths are reduced, hence, cloud height is increased. Cloud effective particle size also changes with the roughened ice crystal models which results in varied effects on the calculation of ice water path. Once validated and expanded, the new approach will be integrated in the CERES MODIS algorithm and real-time retrievals at Langley.

On the assimilation of satellite derived soil moisture in numerical weather prediction models

Science.gov (United States)

Drusch, M.

2006-12-01

Satellite derived surface soil moisture data sets are readily available and have been used successfully in hydrological applications. In many operational numerical weather prediction systems the initial soil moisture conditions are analysed from the modelled background and 2 m temperature and relative humidity. This approach has proven its efficiency to improve surface latent and sensible heat fluxes and consequently the forecast on large geographical domains. However, since soil moisture is not always related to screen level variables, model errors and uncertainties in the forcing data can accumulate in root zone soil moisture. Remotely sensed surface soil moisture is directly linked to the model's uppermost soil layer and therefore is a stronger constraint for the soil moisture analysis. Three data assimilation experiments with the Integrated Forecast System (IFS) of the European Centre for Medium-range Weather Forecasts (ECMWF) have been performed for the two months period of June and July 2002: A control run based on the operational soil moisture analysis, an open loop run with freely evolving soil moisture, and an experimental run incorporating bias corrected TMI (TRMM Microwave Imager) derived soil moisture over the southern United States through a nudging scheme using 6-hourly departures. Apart from the soil moisture analysis, the system setup reflects the operational forecast configuration including the atmospheric 4D-Var analysis. Soil moisture analysed in the nudging experiment is the most accurate estimate when compared against in-situ observations from the Oklahoma Mesonet. The corresponding forecast for 2 m temperature and relative humidity is almost as accurate as in the control experiment. Furthermore, it is shown that the soil moisture analysis influences local weather parameters including the planetary boundary layer height and cloud coverage. The transferability of the results to other satellite derived soil moisture data sets will be discussed.

Machine learning based cloud mask algorithm driven by radiative transfer modeling

Science.gov (United States)

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

2017-12-01

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

A radiation closure study of Arctic stratus cloud microphysical properties using the collocated satellite-surface data and Fu-Liou radiative transfer model

Science.gov (United States)

Dong, Xiquan; Xi, Baike; Qiu, Shaoyue; Minnis, Patrick; Sun-Mack, Sunny; Rose, Fred

2016-09-01

Retrievals of cloud microphysical properties based on passive satellite imagery are especially difficult over snow-covered surfaces because of the bright and cold surface. To help quantify their uncertainties, single-layered overcast liquid-phase Arctic stratus cloud microphysical properties retrieved by using the Clouds and the Earth's Radiant Energy System Edition 2 and Edition 4 (CERES Ed2 and Ed4) algorithms are compared with ground-based retrievals at the Atmospheric Radiation Measurement North Slope of Alaska (ARM NSA) site at Barrow, AK, during the period from March 2000 to December 2006. A total of 206 and 140 snow-free cases (Rsfc ≤ 0.3), and 108 and 106 snow cases (Rsfc > 0.3), respectively, were selected from Terra and Aqua satellite passes over the ARM NSA site. The CERES Ed4 and Ed2 optical depth (τ) and liquid water path (LWP) retrievals from both Terra and Aqua are almost identical and have excellent agreement with ARM retrievals under snow-free and snow conditions. In order to reach a radiation closure study for both the surface and top of atmosphere (TOA) radiation budgets, the ARM precision spectral pyranometer-measured surface albedos were adjusted (63.6% and 80% of the ARM surface albedos for snow-free and snow cases, respectively) to account for the water and land components of the domain of 30 km × 30 km. Most of the radiative transfer model calculated SW↓sfc and SW↑TOA fluxes by using ARM and CERES cloud retrievals and the domain mean albedos as input agree with the ARM and CERES flux observations within 10 W m-2 for both snow-free and snow conditions. Sensitivity studies show that the ARM LWP and re retrievals are less dependent on solar zenith angle (SZA), but all retrieved optical depths increase with SZA.

Global model comparison of heterogeneous ice nucleation parameterizations in mixed phase clouds

Science.gov (United States)

Yun, Yuxing; Penner, Joyce E.

2012-04-01

A new aerosol-dependent mixed phase cloud parameterization for deposition/condensation/immersion (DCI) ice nucleation and one for contact freezing are compared to the original formulations in a coupled general circulation model and aerosol transport model. The present-day cloud liquid and ice water fields and cloud radiative forcing are analyzed and compared to observations. The new DCI freezing parameterization changes the spatial distribution of the cloud water field. Significant changes are found in the cloud ice water fraction and in the middle cloud fractions. The new DCI freezing parameterization predicts less ice water path (IWP) than the original formulation, especially in the Southern Hemisphere. The smaller IWP leads to a less efficient Bergeron-Findeisen process resulting in a larger liquid water path, shortwave cloud forcing, and longwave cloud forcing. It is found that contact freezing parameterizations have a greater impact on the cloud water field and radiative forcing than the two DCI freezing parameterizations that we compared. The net solar flux at top of atmosphere and net longwave flux at the top of the atmosphere change by up to 8.73 and 3.52 W m-2, respectively, due to the use of different DCI and contact freezing parameterizations in mixed phase clouds. The total climate forcing from anthropogenic black carbon/organic matter in mixed phase clouds is estimated to be 0.16-0.93 W m-2using the aerosol-dependent parameterizations. A sensitivity test with contact ice nuclei concentration in the original parameterization fit to that recommended by Young (1974) gives results that are closer to the new contact freezing parameterization.

Sorghum yield and associated satellite-derived meteorological ...

African Journals Online (AJOL)

Sorghum yield and associated satellite-derived meteorological parameters in semi-arid Botswana. ... African Crop Science Journal ... Sorghum (Sorghum bicolor) yield for five seasons (2005/6 to 2009/10) from the Botswana Department of Crop ... Key Words: Coefficient of determination, NDVI, Pearson correlation ...

Remote Sensing of Tropical Ecosystems: Atmospheric Correction and Cloud Masking Matter

Science.gov (United States)

Hilker, Thomas; Lyapustin, Alexei I.; Tucker, Compton J.; Sellers, Piers J.; Hall, Forrest G.; Wang, Yujie

2012-01-01

Tropical rainforests are significant contributors to the global cycles of energy, water and carbon. As a result, monitoring of the vegetation status over regions such as Amazonia has been a long standing interest of Earth scientists trying to determine the effect of climate change and anthropogenic disturbance on the tropical ecosystems and its feedback on the Earth's climate. Satellite-based remote sensing is the only practical approach for observing the vegetation dynamics of regions like the Amazon over useful spatial and temporal scales, but recent years have seen much controversy over satellite-derived vegetation states in Amazônia, with studies predicting opposite feedbacks depending on data processing technique and interpretation. Recent results suggest that some of this uncertainty could stem from a lack of quality in atmospheric correction and cloud screening. In this paper, we assess these uncertainties by comparing the current standard surface reflectance products (MYD09, MYD09GA) and derived composites (MYD09A1, MCD43A4 and MYD13A2 - Vegetation Index) from the Moderate Resolution Imaging Spectroradiometer (MODIS) onboard the Aqua satellite to results obtained from the Multi-Angle Implementation of Atmospheric Correction (MAIAC) algorithm. MAIAC uses a new cloud screening technique, and novel aerosol retrieval and atmospheric correction procedures which are based on time-series and spatial analyses. Our results show considerable improvements of MAIAC processed surface reflectance compared to MYD09/MYD13 with noise levels reduced by a factor of up to 10. Uncertainties in the current MODIS surface reflectance product were mainly due to residual cloud and aerosol contamination which affected the Normalized Difference Vegetation Index (NDVI): During the wet season, with cloud cover ranging between 90 percent and 99 percent, conventionally processed NDVI was significantly depressed due to undetected clouds. A smaller reduction in NDVI due to increased

Evaluation of the Cloud Fields in the UK Met Office HadGEM3-UKCA Model Using the CCCM Satellite Data Product to Advance Our Understanding of the Influence of Clouds on Tropospheric Composition and Chemistry

Science.gov (United States)

Varma, Sunil; Voulgarakis, Apostolos; Liu, Hongyu; Crawford, James H.; White, James

2016-01-01

To determine the role of clouds in driving inter-annual and inter-seasonal variability of trace gases in the troposphere and lower stratosphere with a particular focus on the importance of cloud modification of photolysis. To evaluate the cloud fields and their vertical distribution in the HadGEM3 model utilizing CCCM, a unique 3-D cloud data product merged from multiple A-Train satellites (CERES, CloudSat, CALIPSO, and MODIS) developed at the NASA Langley Research Center.

Observations of X-ray sources in the Large Magellanic cloud by the OSO-7 satellite

International Nuclear Information System (INIS)

Markert, T.H.; Clark, G.W.

1975-01-01

Observations of the Large Magellanic Cloud with the 1-40 keV X-ray detectors on the OSO-7 satellite are reported. Results include the discovery of a previously unreported source LMC X-5, measurements of the spectral characteristics of four sources, and observations of their variability on time scales of months

Cloud Overlapping Detection Algorithm Using Solar and IR Wavelengths With GOSE Data Over ARM/SGP Site

Science.gov (United States)

Kawamoto, Kazuaki; Minnis, Patrick; Smith, William L., Jr.

2001-01-01

One of the most perplexing problems in satellite cloud remote sensing is the overlapping of cloud layers. Although most techniques assume a 1-layer cloud system in a given retrieval of cloud properties, many observations are affected by radiation from more than one cloud layer. As such, cloud overlap can cause errors in the retrieval of many properties including cloud height, optical depth, phase, and particle size. A variety of methods have been developed to identify overlapped clouds in a given satellite imager pixel. Baum el al. (1995) used CO2 slicing and a spatial coherence method to demonstrate a possible analysis method for nighttime detection of multilayered clouds. Jin and Rossow (1997) also used a multispectral CO2 slicing technique for a global analysis of overlapped cloud amount. Lin et al. (1999) used a combination infrared, visible, and microwave data to detect overlapped clouds over water. Recently, Baum and Spinhirne (2000) proposed 1.6 and 11 microns. bispectral threshold method. While all of these methods have made progress in solving this stubborn problem, none have yet proven satisfactory for continuous and consistent monitoring of multilayer cloud systems. It is clear that detection of overlapping clouds from passive instruments such as satellite radiometers is in an immature stage of development and requires additional research. Overlapped cloud systems also affect the retrievals of cloud properties over the ARM domains (e.g., Minnis et al 1998) and hence should identified as accurately as possible. To reach this goal, it is necessary to determine which information can be exploited for detecting multilayered clouds from operational meteorological satellite data used by ARM. This paper examines the potential information available in spectral data available on the Geostationary Operational Environmental Satellite (GOES) imager and the NOAA Advanced Very High Resolution Radiometer (AVHRR) used over the ARM SGP and NSA sites to study the

Influence of the liquid layer within mixed-phase clouds on radar observations

NARCIS (Netherlands)

Pfitzenmaier, L.; Dufournet, Y.; Unal, C.M.H.; Russchenberg, H.W.J.

2014-01-01

Mixed-phase clouds play an important role in the earth system. They affect earth radiative balance and the climate (Comstock et al., 2007; Solomon et al., 2007) as well as the formation of precipitation (de Boer et al., 2009; Fan et al., 2011; Lamb and Verlinde, 2011). Within such mixed-phase clouds

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

Science.gov (United States)

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

1987-01-01

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

Comparison of Cloud Base Height Derived from a Ground-Based Infrared Cloud Measurement and Two Ceilometers

Directory of Open Access Journals (Sweden)

Lei Liu

2015-01-01

Full Text Available The cloud base height (CBH derived from the whole-sky infrared cloud-measuring system (WSIRCMS and two ceilometers (Vaisala CL31 and CL51 from November 1, 2011, to June 12, 2012, at the Chinese Meteorological Administration (CMA Beijing Observatory Station are analysed. Significant differences can be found by comparing the measurements of different instruments. More exactly, the cloud occurrence retrieved from CL31 is 3.8% higher than that from CL51, while WSIRCMS data shows 3.6% higher than ceilometers. More than 75.5% of the two ceilometers’ differences are within ±200 m and about 89.5% within ±500 m, while only 30.7% of the differences between WSIRCMS and ceilometers are within ±500 m and about 55.2% within ±1000 m. These differences may be caused by the measurement principles and CBH retrieval algorithm. A combination of a laser ceilometer and an infrared cloud instrument is recommended to improve the capability for determining cloud occurrence and retrieving CBHs.

Arctic boundary layer properties and its influence on cloud occurrence frequency, phase and structure in autumn season

Science.gov (United States)

Qiu, S.; Dong, X.; Xi, B.

2017-12-01

In this study, autumnal boundary layer characteristics and cloud properties have been investigated using data collected at the Atmospheric Radiation Measurement North Slope of Alaska (ARM NSA) site from January 2002 to December 2008. We found that both cloud and planetary boundary layer (PBL) properties can be well distinguished by surface wind directions. When the ARM NSA site is dominated by a northerly wind during the period September- November, the PBL is at near saturation for all three months; while the maximum RH layer varies from low and thin in September, to higher and thicker in October, and then it becomes close to surface again in November. Both the ceilometer and the MPL derived cloud base heights coincide well with the RH maximum layer in the PBL for all three autumnal months. The frequencies of occurrence of mixed phase clouds in September and October are around 60-80% under a northerly wind, which are about 1.5 times higher than those during a southerly wind. Under northerly wind, the PDFs of PBL temperature and specific humidity are narrow and unimodal, with a peak probability around 0.4-0.5. Under a southerly wind, on the other hand, the PBL is both warmer and wetter than northerly wind profiles, which result in lower RH values (10-15% lower) in September and October; and the PDFs of PBL temperature and specific humidity are more evenly distributed with larger distribution range and lower PDF peak values (<0.3). In September, colder and dryer PBL is more favorable for mixed phase cloud formation, cloud occurrence frequency decreases from 90% to 60% as PBL temperature and specific humidity increase. In October, the frequency of occurrence of mixed phase clouds also decreases from 90% to 50-60% as PBL temperature increases. While in November, it increases first and then decreases with increasing PBL temperature and specific humidity. The frequency of occurrence of mixed phase clouds is linearly correlated to PBL RH values: for all three months, it

The effects of clouds on the detection of light signals from near-ground nuclear bursts at satellite

International Nuclear Information System (INIS)

Zhang Zhongshan; Zhang Enshan; Zhao Wenli; Gao Chunxia

2002-01-01

The effects of clouds on the detection of light signals from near-ground nuclear bursts are analysed quantitatively. The results indicate: the degree of the effect increasing with the growth of clouds optical thickness and satellite look angle; clouds lead really harmful effect in detectable signal intensity and precision of optical location, but degree of the effect is not great too. The enhancement of the photon optical paths by multiple scattering within the cloud will cause both a delay and a time-broadening of an impulsive light signal, and get 'lower and fat'; upward optical transmission of light through clouds is essentially the same as if there were no cloud present at all, when a point source is above the geometrical mid-plane of the cloud. And if the point source is below the mid-plane, then upward optical transmission of light through clods will be related closely to the distance of the source below the mid-plane. Given also some charts which evaluate conveniently degree of the effect due to clouds for the purpose of reference and use of a person of the same trade or occupation are given also

Local Interactions of Hydrometeors by Diffusion in Mixed-Phase Clouds

Science.gov (United States)

Baumgartner, Manuel; Spichtinger, Peter

2017-04-01

Mixed-phase clouds, containing both ice particles and liquid droplets, are important for the Earth-Atmosphere system. They modulate the radiation budget by a combination of albedo effect and greenhouse effect. In contrast to liquid water clouds, the radiative impact of clouds containing ice particles is still uncertain. Scattering and absorption highly depends in microphysical properties of ice crystals, e.g. size and shape. In addition, most precipitation on Earth forms via the ice phase. Thus, better understanding of ice processes as well as their representation in models is required. A key process for determining shape and size of ice crystals is diffusional growth. Diffusion processes in mixed-phase clouds are highly uncertain; in addition they are usually highly simplified in cloud models, especially in bulk microphysics parameterizations. The direct interaction between cloud droplets and ice particles, due to spatial inhomogeneities, is ignored; the particles can only interact via their environmental conditions. Local effects as supply of supersaturation due to clusters of droplets around ice particles are usually not represented, although they form the physical basis of the Wegener-Bergeron-Findeisen process. We present direct numerical simulations of the interaction of single ice particles and droplets, especially their local competition for the available water vapor. In addition, we show an approach to parameterize local interactions by diffusion. The suggested parameterization uses local steady-state solutions of the diffusion equations for water vapor for an ice particle as well as a droplet. The individual solutions are coupled together to obtain the desired interaction. We show some results of the scheme as implemented in a parcel model.

Minimizing Gaps of Daily Ndvi Map with Geostationary Satellite Remote Sensing Data

Science.gov (United States)

Lee, S.; Ryu, Y.; Jiang, C.

2015-12-01

Satellite based remote sensing has been used to monitor plant phenology. Numerous studies have generally utilized normalized difference vegetation index (NDVI) to quantify phenological patterns and changes in regional to the global scales. Obtaining the NDVI values during summer in East Asian Monsoon regions is important because most plants grow vigorously in this season. However, satellite derived NDVI data are error prone to clouds during most of the period. Various methods have attempted to reduce the effect of cloud in temporal and spatial NDVI monitoring; the fundamental solution is to have a large data pool that includes multiple images in short period and supplements NDVI values in same period. Multiple images of geostationary satellite in a day can be a method to expand the pool. In this study, we suggest an approach that minimizes data gaps in NDVI of the day through geostationary satellite derived NDVI composition. We acquired data from Geostationary Ocean Color Imager (GOCI) which is a satellite that was launched to monitor ocean around the Korean peninsula, China, Japan and Russia. The satellite observes eight times per day (09:00 - 16:00, every hour) at 500 x 500 m resolution from 2011 to 2015. GOCI red- and near infrared radiance was converted into surface reflectance by using 6S Radiative Transfer Model (6S). We calculated NDVI tiles for each of observed eight tiles per day and made one day NDVI through maximum-value composite method. We evaluated the composite GOCI derived NDVI by comparing with daily MODIS-derived NDVI (composited from MOD09GA and MYD09GA), 16-day Landsat 8-derived NDVI, and in-situ light emitting diode (LED) NDVI measurements at a homogeneous deciduous forest and rice paddy sites. We found that GOCI-derived NDVI maps revealed little data gaps compared to MODIS and Landsat, and GOCI derived NDVI time series were smoother than MODIS derived NDVI time series in summer. GOCI-derived NDVI agreed well with in-situ observations of NDVI

A new CM SAF Solar Surface Radiation Climate Data Set derived from Meteosat Satellite Observations

Science.gov (United States)

Trentmann, J.; Mueller, R. W.; Pfeifroth, U.; Träger-Chatterjee, C.; Cremer, R.

2014-12-01

The incoming surface solar radiation has been defined as an essential climate variable by GCOS. It is mandatory to monitor this part of the earth's energy balance, and thus gain insights on the state and variability of the climate system. In addition, data sets of the surface solar radiation have received increased attention over the recent years as an important source of information for the planning of solar energy applications. The EUMETSAT Satellite Application Facility on Climate Monitoring (CM SAF) is deriving surface solar radiation from geostationary and polar-orbiting satellite instruments. While CM SAF is focusing on the generation of high-quality long-term climate data records, also operationally data is provided in short time latency within 8 weeks. Here we present SARAH (Solar Surface Radiation Dataset - Heliosat), i.e. the new CM SAF Solar Surface Radiation data set based on Meteosat satellite observations. SARAH provides instantaneous, daily- and monthly-averaged data of the effective cloud albedo (CAL), the direct normalized solar radiation (DNI) and the solar irradiance (SIS) from 1983 to 2013 for the full view of the Meteosat satellite (i.e, Europe, Africa, parts of South America, and the Atlantic ocean). The data sets are generated with a high spatial resolution of 0.05 deg allowing for detailed regional studies, and are available in netcdf-format at no cost without restrictions at www.cmsaf.eu. We provide an overview of the data sets, including a validation against reference measurements from the BSRN and GEBA surface station networks.

Evaluation results of the optimal estimation based, multi-sensor cloud property data sets derived from AVHRR heritage measurements in the Cloud_cci project.

Science.gov (United States)

Stapelberg, S.; Jerg, M.; Stengel, M.; Hollmann, R.

2014-12-01

In 2010 the ESA Climate Change Initiative (CCI) Cloud project was started with the objectives of generating a long-term coherent data set of cloud properties. The cloud properties considered are cloud mask, cloud top estimates, cloud optical thickness, cloud effective radius and post processed parameters such as cloud liquid and ice water path. During the first phase of the project 3 years of data spanning 2007 to 2009 have been produced on a global gridded daily and monthly mean basis. Next to the processing an extended evaluation study was started in order to gain a first understanding of the quality of the retrieved data. The critical discussion of the results of the evaluation holds a key role for the further development and improvement of the dataset's quality. The presentation will give a short overview of the evaluation study undertaken in the Cloud_cci project. The focus will be on the evaluation of gridded, monthly mean cloud fraction and cloud top data from the Cloud_cci AVHRR-heritage dataset with CLARA-A1, MODIS-Coll5, PATMOS-X and ISCCP data. Exemplary results will be shown. Strengths and shortcomings of the retrieval scheme as well as possible impacts of averaging approaches on the evaluation will be discussed. An Overview of Cloud_cci Phase 2 will be given.

Incorporating GOES Satellite Photosynthetically Active Radiation (PAR) Retrievals to Improve Biogenic Emission Estimates in Texas

Science.gov (United States)

Zhang, Rui; White, Andrew T.; Pour Biazar, Arastoo; McNider, Richard T.; Cohan, Daniel S.

2018-01-01

This study examines the influence of insolation and cloud retrieval products from the Geostationary Operational Environmental Satellite (GOES) system on biogenic emission estimates and ozone simulations in Texas. Compared to surface pyranometer observations, satellite-retrieved insolation and photosynthetically active radiation (PAR) values tend to systematically correct the overestimation of downwelling shortwave radiation in the Weather Research and Forecasting (WRF) model. The correlation coefficient increases from 0.93 to 0.97, and the normalized mean error decreases from 36% to 21%. The isoprene and monoterpene emissions estimated by the Model of Emissions of Gases and Aerosols from Nature are on average 20% and 5% less, respectively, when PAR from the direct satellite retrieval is used rather than the control WRF run. The reduction in biogenic emission rates using satellite PAR reduced the predicted maximum daily 8 h ozone concentration by up to 5.3 ppbV over the Dallas-Fort Worth (DFW) region on some days. However, episode average ozone response is less sensitive, with a 0.6 ppbV decrease near DFW and 0.3 ppbV increase over East Texas. The systematic overestimation of isoprene concentrations in a WRF control case is partially corrected by using satellite PAR, which observes more clouds than are simulated by WRF. Further, assimilation of GOES-derived cloud fields in WRF improved CAMx model performance for ground-level ozone over Texas. Additionally, it was found that using satellite PAR improved the model's ability to replicate the spatial pattern of satellite-derived formaldehyde columns and aircraft-observed vertical profiles of isoprene.

Experimental Satellite Phase 3D before Launch

Directory of Open Access Journals (Sweden)

J. Sebesta

1999-04-01

Full Text Available To build a satellite can be a dream for many engineers. We are happy that we can participate in the AMSAT PHASE 3D project. Our responsibility is very high because one of our on-board receivers is the main one of the command link and will never be switched off. The project is also a very good opportunity for our students to meet satellite technology.

Comparison of CERES-MODIS cloud microphysical properties with surface observations over Loess Plateau

Science.gov (United States)

Yan, Hongru; Huang, Jianping; Minnis, Patrick; Yi, Yuhong; Sun-Mack, Sunny; Wang, Tianhe; Nakajima, Takashi Y.

2015-03-01

To enhance the utility of satellite-derived cloud properties for studying the role of clouds in climate change and the hydrological cycle in semi-arid areas, it is necessary to know their uncertainties. This paper estimates the uncertainties of several cloud properties by comparing those derived over the China Loess Plateau from the MODerate-resolution Imaging Spectroradiometer (MODIS) on Terra and Aqua by the Clouds and Earth's Radiant Energy System (CERES) with surface observations at the Semi-Arid Climate and Environment Observatory of Lanzhou University (SACOL). The comparisons use data from January 2008 to June 2010 limited to single layer and overcast stratus conditions during daytime. Cloud optical depths (τ) and liquid water paths (LWP) from both Terra and Aqua generally track the variation of the surface counterparts with modest correlation, while cloud effective radius (re) is only weakly correlated with the surface retrievals. The mean differences between Terra and the SACOL retrievals are -4.7±12.9, 2.1±3.2 μm and 30.2±85.3 g m-2 for τ, re and LWP, respectively. The corresponding differences for Aqua are 2.1±8.4, 1.2±2.9 μm and 47.4±79.6 g m-2, respectively. Possible causes for biases of satellite retrievals are discussed through statistical analysis and case studies. Generally, the CERES-MODIS cloud properties have a bit larger biases over the Loess Plateau than those in previous studies over other locations.

submitter Phase transition observations and discrimination of small cloud particles by light polarization in expansion chamber experiments

CERN Document Server

Nichman, Leonid; Järvinen, Emma; Ignatius, Karoliina; Höppel, Niko Florian; Dias, Antonio; Heinritzi, Martin; Simon, Mario; Tröstl, Jasmin; Wagner, Andrea Christine; Wagner, Robert; Williamson, Christina; Yan, Chao; Connolly, Paul James; Dorsey, James Robert; Duplissy, Jonathan; Ehrhart, Sebastian; Frege, Carla; Gordon, Hamish; Hoyle, Christopher Robert; Kristensen, Thomas Bjerring; Steiner, Gerhard; McPherson Donahue, Neil; Flagan, Richard; Gallagher, Martin William; Kirkby, Jasper; Möhler, Ottmar; Saathoff, Harald; Schnaiter, Martin; Stratmann, Frank; Tomé, António

2016-01-01

Cloud microphysical processes involving the ice phase in tropospheric clouds are among the major uncertainties in cloud formation, weather, and general circulation models. The detection of aerosol particles, liquid droplets, and ice crystals, especially in the small cloud particle-size range below 50 μm, remains challenging in mixed phase, often unstable environments. The Cloud Aerosol Spectrometer with Polarization (CASPOL) is an airborne instrument that has the ability to detect such small cloud particles and measure the variability in polarization state of their backscattered light. Here we operate the versatile Cosmics Leaving OUtdoor Droplets (CLOUD) chamber facility at the European Organization for Nuclear Research (CERN) to produce controlled mixed phase and other clouds by adiabatic expansions in an ultraclean environment, and use the CASPOL to discriminate between different aerosols, water, and ice particles. In this paper, optical property measurements of mixed-phase clouds and viscous secondary ...

Stable Low Cloud Phase II: Nocturnal Event Study

Science.gov (United States)

Bauman, William H., III; Barrett, Joe, III

2007-01-01

This report describes the work done by the Applied Meteorology Unit (AMU) in developing a database of nights that experienced rapid (formation in a stable atmosphere, resulting in ceilings at the Shuttle Landing Facility (TTS) that violated Space Shuttle Flight Rules (FR). This work is the second phase of a similar AMU task that examined the same phenomena during the day. In the first phase of this work, the meteorological conditions favoring the rapid formation of low ceilings include the presence of any inversion below 8000 ft, high relative humidity (RH) beneath the inversion and a clockwise turning of the winds from the surface to the middle troposphere (-15000 ft). The AMU compared and contrasted the atmospheric and thermodynamic conditions between nights with rapid low ceiling formation and nights with low ceilings resulting from other mechanisms. The AMU found that there was little to discern between the rapidly-forming ceiling nights and other low ceiling nights at TTS. When a rapid development occurred, the average RH below the inversions was 87% while non-events had an average RH of 79%. One key parameter appeared to be the vertical wind profile in the Cape Canaveral, FL radiosonde (XMR) sounding. Eighty-three percent of the rapid development events had veering winds with height from the surface to the middle troposphere (-15,000 ft) while 61% of the non-events had veering winds with height. Veering winds indicate a warm-advection regime, which supports large-scale rising motion and ultimately cloud formation in a moist environment. However, only six of the nights (out of 86 events examined) with low cloud ceilings had an occurrence of rapidly developing ceilings. Since only 7% rapid development events were observed in this dataset, it is likely that rapid low cloud development is not a common occurrence during the night, or at least not as common as during the day. In the AMU work on the daytime rapid low cloud development (Case and Wheeler 2005), nearly

Stratocumulus Cloud Top Radiative Cooling and Cloud Base Updraft Speeds

Science.gov (United States)

Kazil, J.; Feingold, G.; Balsells, J.; Klinger, C.

2017-12-01

Cloud top radiative cooling is a primary driver of turbulence in the stratocumulus-topped marine boundary. A functional relationship between cloud top cooling and cloud base updraft speeds may therefore exist. A correlation of cloud top radiative cooling and cloud base updraft speeds has been recently identified empirically, providing a basis for satellite retrieval of cloud base updraft speeds. Such retrievals may enable analysis of aerosol-cloud interactions using satellite observations: Updraft speeds at cloud base co-determine supersaturation and therefore the activation of cloud condensation nuclei, which in turn co-determine cloud properties and precipitation formation. We use large eddy simulation and an off-line radiative transfer model to explore the relationship between cloud-top radiative cooling and cloud base updraft speeds in a marine stratocumulus cloud over the course of the diurnal cycle. We find that during daytime, at low cloud water path (CWP correlated, in agreement with the reported empirical relationship. During the night, in the absence of short-wave heating, CWP builds up (CWP > 50 g m-2) and long-wave emissions from cloud top saturate, while cloud base heating increases. In combination, cloud top cooling and cloud base updrafts become weakly anti-correlated. A functional relationship between cloud top cooling and cloud base updraft speed can hence be expected for stratocumulus clouds with a sufficiently low CWP and sub-saturated long-wave emissions, in particular during daytime. At higher CWPs, in particular at night, the relationship breaks down due to saturation of long-wave emissions from cloud top.

Parameterizing correlations between hydrometeor species in mixed-phase Arctic clouds

Science.gov (United States)

Larson, Vincent E.; Nielsen, Brandon J.; Fan, Jiwen; Ovchinnikov, Mikhail

2011-01-01

Mixed-phase Arctic clouds, like other clouds, contain small-scale variability in hydrometeor fields, such as cloud water or snow mixing ratio. This variability may be worth parameterizing in coarse-resolution numerical models. In particular, for modeling multispecies processes such as accretion and aggregation, it would be useful to parameterize subgrid correlations among hydrometeor species. However, one difficulty is that there exist many hydrometeor species and many microphysical processes, leading to complexity and computational expense. Existing lower and upper bounds on linear correlation coefficients are too loose to serve directly as a method to predict subgrid correlations. Therefore, this paper proposes an alternative method that begins with the spherical parameterization framework of Pinheiro and Bates (1996), which expresses the correlation matrix in terms of its Cholesky factorization. The values of the elements of the Cholesky matrix are populated here using a "cSigma" parameterization that we introduce based on the aforementioned bounds on correlations. The method has three advantages: (1) the computational expense is tolerable; (2) the correlations are, by construction, guaranteed to be consistent with each other; and (3) the methodology is fairly general and hence may be applicable to other problems. The method is tested noninteractively using simulations of three Arctic mixed-phase cloud cases from two field experiments: the Indirect and Semi-Direct Aerosol Campaign and the Mixed-Phase Arctic Cloud Experiment. Benchmark simulations are performed using a large-eddy simulation (LES) model that includes a bin microphysical scheme. The correlations estimated by the new method satisfactorily approximate the correlations produced by the LES.

Online single particle analysis of ice particle residuals from mountain-top mixed-phase clouds using laboratory derived particle type assignment

Science.gov (United States)

Schmidt, Susan; Schneider, Johannes; Klimach, Thomas; Mertes, Stephan; Schenk, Ludwig Paul; Kupiszewski, Piotr; Curtius, Joachim; Borrmann, Stephan

2017-01-01

In situ single particle analysis of ice particle residuals (IPRs) and out-of-cloud aerosol particles was conducted by means of laser ablation mass spectrometry during the intensive INUIT-JFJ/CLACE campaign at the high alpine research station Jungfraujoch (3580 m a.s.l.) in January-February 2013. During the 4-week campaign more than 70 000 out-of-cloud aerosol particles and 595 IPRs were analyzed covering a particle size diameter range from 100 nm to 3 µm. The IPRs were sampled during 273 h while the station was covered by mixed-phase clouds at ambient temperatures between -27 and -6 °C. The identification of particle types is based on laboratory studies of different types of biological, mineral and anthropogenic aerosol particles. The outcome of these laboratory studies was characteristic marker peaks for each investigated particle type. These marker peaks were applied to the field data. In the sampled IPRs we identified a larger number fraction of primary aerosol particles, like soil dust (13 ± 5 %) and minerals (11 ± 5 %), in comparison to out-of-cloud aerosol particles (2.4 ± 0.4 and 0.4 ± 0.1 %, respectively). Additionally, anthropogenic aerosol particles, such as particles from industrial emissions and lead-containing particles, were found to be more abundant in the IPRs than in the out-of-cloud aerosol. In the out-of-cloud aerosol we identified a large fraction of aged particles (31 ± 5 %), including organic material and secondary inorganics, whereas this particle type was much less abundant (2.7 ± 1.3 %) in the IPRs. In a selected subset of the data where a direct comparison between out-of-cloud aerosol particles and IPRs in air masses with similar origin was possible, a pronounced enhancement of biological particles was found in the IPRs.

Satellite-Surface Perspectives of Air Quality and Aerosol-Cloud Effects on the Environment: An Overview of 7-SEAS BASELInE

Science.gov (United States)

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;

Covariance Between Arctic Sea Ice and Clouds Within Atmospheric State Regimes at the Satellite Footprint Level

Science.gov (United States)

Taylor, Patrick C.; Kato, Seiji; Xu, Kuan-Man; Cai, Ming

2015-01-01

Understanding the cloud response to sea ice change is necessary for modeling Arctic climate. Previous work has primarily addressed this problem from the interannual variability perspective. This paper provides a refined perspective of sea ice-cloud relationship in the Arctic using a satellite footprint-level quantification of the covariance between sea ice and Arctic low cloud properties from NASA A-Train active remote sensing data. The covariances between Arctic low cloud properties and sea ice concentration are quantified by first partitioning each footprint into four atmospheric regimes defined using thresholds of lower tropospheric stability and mid-tropospheric vertical velocity. Significant regional variability in the cloud properties is found within the atmospheric regimes indicating that the regimes do not completely account for the influence of meteorology. Regional anomalies are used to account for the remaining meteorological influence on clouds. After accounting for meteorological regime and regional influences, a statistically significant but weak covariance between cloud properties and sea ice is found in each season for at least one atmospheric regime. Smaller average cloud fraction and liquid water are found within footprints with more sea ice. The largest-magnitude cloud-sea ice covariance occurs between 500m and 1.2 km when the lower tropospheric stability is between 16 and 24 K. The covariance between low cloud properties and sea ice is found to be largest in fall and is accompanied by significant changes in boundary layer temperature structure where larger average near-surface static stability is found at larger sea ice concentrations.

Covariance between Arctic sea ice and clouds within atmospheric state regimes at the satellite footprint level.

Science.gov (United States)

Taylor, Patrick C; Kato, Seiji; Xu, Kuan-Man; Cai, Ming

2015-12-27

Understanding the cloud response to sea ice change is necessary for modeling Arctic climate. Previous work has primarily addressed this problem from the interannual variability perspective. This paper provides a refined perspective of sea ice-cloud relationship in the Arctic using a satellite footprint-level quantification of the covariance between sea ice and Arctic low cloud properties from NASA A-Train active remote sensing data. The covariances between Arctic low cloud properties and sea ice concentration are quantified by first partitioning each footprint into four atmospheric regimes defined using thresholds of lower tropospheric stability and midtropospheric vertical velocity. Significant regional variability in the cloud properties is found within the atmospheric regimes indicating that the regimes do not completely account for the influence of meteorology. Regional anomalies are used to account for the remaining meteorological influence on clouds. After accounting for meteorological regime and regional influences, a statistically significant but weak covariance between cloud properties and sea ice is found in each season for at least one atmospheric regime. Smaller average cloud fraction and liquid water are found within footprints with more sea ice. The largest-magnitude cloud-sea ice covariance occurs between 500 m and 1.2 km when the lower tropospheric stability is between 16 and 24 K. The covariance between low cloud properties and sea ice is found to be largest in fall and is accompanied by significant changes in boundary layer temperature structure where larger average near-surface static stability is found at larger sea ice concentrations.

Satellite-Derived Bathymetry: Accuracy Assessment on Depths Derivation Algorithm for Shallow Water Area

Science.gov (United States)

Said, N. M.; Mahmud, M. R.; Hasan, R. C.

2017-10-01

Over the years, the acquisition technique of bathymetric data has evolved from a shipborne platform to airborne and presently, utilising space-borne acquisition. The extensive development of remote sensing technology has brought in the new revolution to the hydrographic surveying. Satellite-Derived Bathymetry (SDB), a space-borne acquisition technique which derives bathymetric data from high-resolution multispectral satellite imagery for various purposes recently considered as a new promising technology in the hydrographic surveying industry. Inspiring by this latest developments, a comprehensive study was initiated by National Hydrographic Centre (NHC) and Universiti Teknologi Malaysia (UTM) to analyse SDB as a means for shallow water area acquisition. By adopting additional adjustment in calibration stage, a marginal improvement discovered on the outcomes from both Stumpf and Lyzenga algorithms where the RMSE values for the derived (predicted) depths were 1.432 meters and 1.728 meters respectively. This paper would deliberate in detail the findings from the study especially on the accuracy level and practicality of SDB over the tropical environmental setting in Malaysia.

The operational cloud retrieval algorithms from TROPOMI on board Sentinel-5 Precursor

Science.gov (United States)

Loyola, Diego G.; Gimeno García, Sebastián; Lutz, Ronny; Argyrouli, Athina; Romahn, Fabian; Spurr, Robert J. D.; Pedergnana, Mattia; Doicu, Adrian; Molina García, Víctor; Schüssler, Olena

2018-01-01

This paper presents the operational cloud retrieval algorithms for the TROPOspheric Monitoring Instrument (TROPOMI) on board the European Space Agency Sentinel-5 Precursor (S5P) mission scheduled for launch in 2017. Two algorithms working in tandem are used for retrieving cloud properties: OCRA (Optical Cloud Recognition Algorithm) and ROCINN (Retrieval of Cloud Information using Neural Networks). OCRA retrieves the cloud fraction using TROPOMI measurements in the ultraviolet (UV) and visible (VIS) spectral regions, and ROCINN retrieves the cloud top height (pressure) and optical thickness (albedo) using TROPOMI measurements in and around the oxygen A-band in the near infrared (NIR). Cloud parameters from TROPOMI/S5P will be used not only for enhancing the accuracy of trace gas retrievals but also for extending the satellite data record of cloud information derived from oxygen A-band measurements, a record initiated with the Global Ozone Monitoring Experiment (GOME) on board the second European Remote-Sensing Satellite (ERS-2) over 20 years ago. The OCRA and ROCINN algorithms are integrated in the S5P operational processor UPAS (Universal Processor for UV/VIS/NIR Atmospheric Spectrometers), and we present here UPAS cloud results using the Ozone Monitoring Instrument (OMI) and GOME-2 measurements. In addition, we examine anticipated challenges for the TROPOMI/S5P cloud retrieval algorithms, and we discuss the future validation needs for OCRA and ROCINN.

Artificial intelligence techniques applied to hourly global irradiance estimation from satellite-derived cloud index

Energy Technology Data Exchange (ETDEWEB)

Zarzalejo, L.F.; Ramirez, L.; Polo, J. [DER-CIEMAT, Madrid (Spain). Renewable Energy Dept.

2005-07-01

Artificial intelligence techniques, such as fuzzy logic and neural networks, have been used for estimating hourly global radiation from satellite images. The models have been fitted to measured global irradiance data from 15 Spanish terrestrial stations. Both satellite imaging data and terrestrial information from the years 1994, 1995 and 1996 were used. The results of these artificial intelligence models were compared to a multivariate regression based upon Heliosat I model. A general better behaviour was observed for the artificial intelligence models. (author)

Artificial intelligence techniques applied to hourly global irradiance estimation from satellite-derived cloud index

International Nuclear Information System (INIS)

Zarzalejo, Luis F.; Ramirez, Lourdes; Polo, Jesus

2005-01-01

Artificial intelligence techniques, such as fuzzy logic and neural networks, have been used for estimating hourly global radiation from satellite images. The models have been fitted to measured global irradiance data from 15 Spanish terrestrial stations. Both satellite imaging data and terrestrial information from the years 1994, 1995 and 1996 were used. The results of these artificial intelligence models were compared to a multivariate regression based upon Heliosat I model. A general better behaviour was observed for the artificial intelligence models

Feature extraction and classification of clouds in high resolution panchromatic satellite imagery

Science.gov (United States)

Sharghi, Elan

The development of sophisticated remote sensing sensors is rapidly increasing, and the vast amount of satellite imagery collected is too much to be analyzed manually by a human image analyst. It has become necessary for a tool to be developed to automate the job of an image analyst. This tool would need to intelligently detect and classify objects of interest through computer vision algorithms. Existing software called the Rapid Image Exploitation Resource (RAPIER®) was designed by engineers at Space and Naval Warfare Systems Center Pacific (SSC PAC) to perform exactly this function. This software automatically searches for anomalies in the ocean and reports the detections as a possible ship object. However, if the image contains a high percentage of cloud coverage, a high number of false positives are triggered by the clouds. The focus of this thesis is to explore various feature extraction and classification methods to accurately distinguish clouds from ship objects. An examination of a texture analysis method, line detection using the Hough transform, and edge detection using wavelets are explored as possible feature extraction methods. The features are then supplied to a K-Nearest Neighbors (KNN) or Support Vector Machine (SVM) classifier. Parameter options for these classifiers are explored and the optimal parameters are determined.

Aerosol indirect effects ? general circulation model intercomparison and evaluation with satellite data

Energy Technology Data Exchange (ETDEWEB)

Quaas, Johannes; Ming, Yi; Menon, Surabi; Takemura, Toshihiko; Wang, Minghuai; Penner, Joyce E.; Gettelman, Andrew; Lohmann, Ulrike; Bellouin, Nicolas; Boucher, Olivier; Sayer, Andrew M.; Thomas, Gareth E.; McComiskey, Allison; Feingold, Graham; Hoose, Corinna; Kristansson, Jon Egill; Liu, Xiaohong; Balkanski, Yves; Donner, Leo J.; Ginoux, Paul A.; Stier, Philip; Grandey, Benjamin; Feichter, Johann; Sednev, Igor; Bauer, Susanne E.; Koch, Dorothy; Grainger, Roy G.; Kirkevag, Alf; Iversen, Trond; Seland, Oyvind; Easter, Richard; Ghan, Steven J.; Rasch, Philip J.; Morrison, Hugh; Lamarque, Jean-Francois; Iacono, Michael J.; Kinne, Stefan; Schulz, Michael

2010-03-12

Aerosol indirect effects continue to constitute one of the most important uncertainties for anthropogenic climate perturbations. Within the international AEROCOM initiative, the representation of aerosol-cloud-radiation interactions in ten different general circulation models (GCMs) is evaluated using three satellite datasets. The focus is on stratiform liquid water clouds since most GCMs do not include ice nucleation effects, and none of the model explicitly parameterises aerosol effects on convective clouds. We compute statistical relationships between aerosol optical depth ({tau}{sub a}) and various cloud and radiation quantities in a manner that is consistent between the models and the satellite data. It is found that the model-simulated influence of aerosols on cloud droplet number concentration (N{sub d}) compares relatively well to the satellite data at least over the ocean. The relationship between {tau}{sub a} and liquid water path is simulated much too strongly by the models. This suggests that the implementation of the second aerosol indirect effect mainly in terms of an autoconversion parameterisation has to be revisited in the GCMs. A positive relationship between total cloud fraction (f{sub cld}) and {tau}{sub a} as found in the satellite data is simulated by the majority of the models, albeit less strongly than that in the satellite data in most of them. In a discussion of the hypotheses proposed in the literature to explain the satellite-derived strong f{sub cld} - {tau}{sub a} relationship, our results indicate that none can be identified as a unique explanation. Relationships similar to the ones found in satellite data between {tau}{sub a} and cloud top temperature or outgoing long-wave radiation (OLR) are simulated by only a few GCMs. The GCMs that simulate a negative OLR - {tau}{sub a} relationship show a strong positive correlation between {tau}{sub a} and f{sub cld} The short-wave total aerosol radiative forcing as simulated by the GCMs is

The Matsu Wheel: A Cloud-Based Framework for Efficient Analysis and Reanalysis of Earth Satellite Imagery

Science.gov (United States)

Patterson, Maria T.; Anderson, Nicholas; Bennett, Collin; Bruggemann, Jacob; Grossman, Robert L.; Handy, Matthew; Ly, Vuong; Mandl, Daniel J.; Pederson, Shane; Pivarski, James;

The influence of extratropical cloud phase and amount feedbacks on climate sensitivity

Science.gov (United States)

Frey, William R.; Kay, Jennifer E.

2018-04-01

Global coupled climate models have large long-standing cloud and radiation biases, calling into question their ability to simulate climate and climate change. This study assesses the impact of reducing shortwave radiation biases on climate sensitivity within the Community Earth System Model (CESM). The model is modified by increasing supercooled cloud liquid to better match absorbed shortwave radiation observations over the Southern Ocean while tuning to reduce a compensating tropical shortwave bias. With a thermodynamic mixed-layer ocean, equilibrium warming in response to doubled CO2 increases from 4.1 K in the control to 5.6 K in the modified model. This 1.5 K increase in equilibrium climate sensitivity is caused by changes in two extratropical shortwave cloud feedbacks. First, reduced conversion of cloud ice to liquid at high southern latitudes decreases the magnitude of a negative cloud phase feedback. Second, warming is amplified in the mid-latitudes by a larger positive shortwave cloud feedback. The positive cloud feedback, usually associated with the subtropics, arises when sea surface warming increases the moisture gradient between the boundary layer and free troposphere. The increased moisture gradient enhances the effectiveness of mixing to dry the boundary layer, which decreases cloud amount and optical depth. When a full-depth ocean with dynamics and thermodynamics is included, ocean heat uptake preferentially cools the mid-latitude Southern Ocean, partially inhibiting the positive cloud feedback and slowing warming. Overall, the results highlight strong connections between Southern Ocean mixed-phase cloud partitioning, cloud feedbacks, and ocean heat uptake in a climate forced by greenhouse gas changes.

Aerosol and cloud properties derived from hyperspectral transmitted light in the southeast Atlantic sampled during field campaign deployments in 2016 and 2017

Science.gov (United States)

LeBlanc, S. E.; Redemann, J.; Flynn, C. J.; Segal-Rosenhaimer, M.; Kacenelenbogen, M. S.; Shinozuka, Y.; Pistone, K.; Karol, Y.; Schmidt, S.; Cochrane, S.; Chen, H.; Meyer, K.; Ferrare, R. A.; Burton, S. P.; Hostetler, C. A.; Hair, J. W.

2017-12-01

We present aerosol and cloud properties collected from airborne remote-sensing measurements in the southeast Atlantic during the recent NASA ObseRvations of CLouds above Aerosols and their intEractionS (ORACLES) field campaign. During the biomass burning seasons of September 2016 and August 2017, we sampled aerosol layers which overlaid marine stratocumulus clouds off the southwestern coast of Africa. We sampled these aerosol layers and the underlying clouds from the NASA P3 airborne platform with the Spectrometer for Sky-Scanning, Sun-Tracking Atmospheric Research (4STAR). Aerosol optical depth (AOD), along with trace gas content in the atmospheric column (water vapor, NO2, and O3), is obtained from the attenuation in the sun's direct beam, measured at the altitude of the airborne platform. Using hyperspectral transmitted light measurements from 4STAR, in conjunction with hyperspectral hemispheric irradiance measurements from the Solar Spectral Flux Radiometers (SSFR), we also obtained aerosol intensive properties (asymmetry parameter, single scattering albedo), aerosol size distributions, cloud optical depth (COD), cloud particle effective radius, and cloud thermodynamic phase. Aerosol intensive properties are retrieved from measurements of angularly resolved skylight and flight level spectral albedo using the inversion used with measurements from AERONET (Aerosol Robotic Network) that has been modified for airborne use. The cloud properties are obtained from 4STAR measurements of scattered light below clouds. We show a favorable initial comparison of the above-cloud AOD measured by 4STAR to this same product retrieved from measurements by the MODIS instrument on board the TERRA and AQUA satellites. The layer AOD observed above clouds will also be compared to integrated aerosol extinction profile measurements from the High Spectral Resolution Lidar-2 (HSRL-2).

Accounting for the Effects of Surface BRDF on Satellite Cloud and Trace-Gas Retrievals: A New Approach Based on Geometry-Dependent Lambertian-Equivalent Reflectivity Applied to OMI Algorithms

Science.gov (United States)

Vasilkov, Alexander; Qin, Wenhan; Krotkov, Nickolay; Lamsal, Lok; Spurr, Robert; Haffner, David; Joiner, Joanna; Yang, Eun-Su; Marchenko, Sergey

2017-01-01

Most satellite nadir ultraviolet and visible cloud, aerosol, and trace-gas algorithms make use of climatological surface reflectivity databases. For example, cloud and NO2 retrievals for the Ozone Monitoring Instrument (OMI) use monthly gridded surface reflectivity climatologies that do not depend upon the observation geometry. In reality, reflection of incoming direct and diffuse solar light from land or ocean surfaces is sensitive to the sun-sensor geometry. This dependence is described by the bidirectional reflectance distribution function (BRDF). To account for the BRDF, we propose to use a new concept of geometry-dependent Lambertian equivalent reflectivity (LER). Implementation within the existing OMI cloud and NO2 retrieval infrastructure requires changes only to the input surface reflectivity database. The geometry-dependent LER is calculated using a vector radiative transfer model with high spatial resolution BRDF information from the Moderate Resolution Imaging Spectroradiometer (MODIS) over land and the Cox-Munk slope distribution over ocean with a contribution from water-leaving radiance. We compare the geometry-dependent and climatological LERs for two wavelengths, 354 and 466 nm, that are used in OMI cloud algorithms to derive cloud fractions. A detailed comparison of the cloud fractions and pressures derived with climatological and geometry-dependent LERs is carried out. Geometry-dependent LER and corresponding retrieved cloud products are then used as inputs to our OMI NO2 algorithm. We find that replacing the climatological OMI-based LERs with geometry-dependent LERs can increase NO2 vertical columns by up to 50% in highly polluted areas; the differences include both BRDF effects and biases between the MODIS and OMI-based surface reflectance data sets. Only minor changes to NO2 columns (within 5 %) are found over unpolluted and overcast areas.

Accounting for the effects of surface BRDF on satellite cloud and trace-gas retrievals: a new approach based on geometry-dependent Lambertian equivalent reflectivity applied to OMI algorithms

Science.gov (United States)

Vasilkov, Alexander; Qin, Wenhan; Krotkov, Nickolay; Lamsal, Lok; Spurr, Robert; Haffner, David; Joiner, Joanna; Yang, Eun-Su; Marchenko, Sergey

2017-01-01

Most satellite nadir ultraviolet and visible cloud, aerosol, and trace-gas algorithms make use of climatological surface reflectivity databases. For example, cloud and NO2 retrievals for the Ozone Monitoring Instrument (OMI) use monthly gridded surface reflectivity climatologies that do not depend upon the observation geometry. In reality, reflection of incoming direct and diffuse solar light from land or ocean surfaces is sensitive to the sun-sensor geometry. This dependence is described by the bidirectional reflectance distribution function (BRDF). To account for the BRDF, we propose to use a new concept of geometry-dependent Lambertian equivalent reflectivity (LER). Implementation within the existing OMI cloud and NO2 retrieval infrastructure requires changes only to the input surface reflectivity database. The geometry-dependent LER is calculated using a vector radiative transfer model with high spatial resolution BRDF information from the Moderate Resolution Imaging Spectroradiometer (MODIS) over land and the Cox-Munk slope distribution over ocean with a contribution from water-leaving radiance. We compare the geometry-dependent and climatological LERs for two wavelengths, 354 and 466 nm, that are used in OMI cloud algorithms to derive cloud fractions. A detailed comparison of the cloud fractions and pressures derived with climatological and geometry-dependent LERs is carried out. Geometry-dependent LER and corresponding retrieved cloud products are then used as inputs to our OMI NO2 algorithm. We find that replacing the climatological OMI-based LERs with geometry-dependent LERs can increase NO2 vertical columns by up to 50 % in highly polluted areas; the differences include both BRDF effects and biases between the MODIS and OMI-based surface reflectance data sets. Only minor changes to NO2 columns (within 5 %) are found over unpolluted and overcast areas.

Monitoring volcanic ash cloud top height through simultaneous retrieval of optical data from polar orbiting and geostationary satellites

Directory of Open Access Journals (Sweden)

K. Zakšek

2013-03-01

Full Text Available Volcanic ash cloud-top height (ACTH can be monitored on the global level using satellite remote sensing. Here we propose a photogrammetric method based on the parallax between data retrieved from geostationary and polar orbiting satellites to overcome some limitations of the existing methods of ACTH retrieval. SEVIRI HRV band and MODIS band 1 are a good choice because of their high resolution. 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. The proposed method was tested for the case of the Eyjafjallajökull eruption in April 2010. The parallax between MODIS and SEVIRI data can reach 30 km, which implies an ACTH of approximately 12 km at the beginning of the eruption. At the end of April eruption an ACTH of 3–4 km is observed. The accuracy of ACTH was estimated to be 0.6 km.

Monitoring water phase dynamics in winter clouds

Science.gov (United States)

Campos, Edwin F.; Ware, Randolph; Joe, Paul; Hudak, David

2014-10-01

This work presents observations of water phase dynamics that demonstrate the theoretical Wegener-Bergeron-Findeisen concepts in mixed-phase winter storms. The work analyzes vertical profiles of air vapor pressure, and equilibrium vapor pressure over liquid water and ice. Based only on the magnitude ranking of these vapor pressures, we identified conditions where liquid droplets and ice particles grow or deplete simultaneously, as well as the conditions where droplets evaporate and ice particles grow by vapor diffusion. The method is applied to ground-based remote-sensing observations during two snowstorms, using two distinct microwave profiling radiometers operating in different climatic regions (North American Central High Plains and Great Lakes). The results are compared with independent microwave radiometer retrievals of vertically integrated liquid water, cloud-base estimates from a co-located ceilometer, reflectivity factor and Doppler velocity observations by nearby vertically pointing radars, and radiometer estimates of liquid water layers aloft. This work thus makes a positive contribution toward monitoring and nowcasting the evolution of supercooled droplets in winter clouds.

Convective and large-scale mass flux profiles over tropical oceans determined from synergistic analysis of a suite of satellite observations

Science.gov (United States)

Masunaga, Hirohiko; Luo, Zhengzhao Johnny

2016-07-01

A new, satellite-based methodology is developed to evaluate convective mass flux and large-scale total mass flux. To derive the convective mass flux, candidate profiles of in-cloud vertical velocity are first constructed with a simple plume model under the constraint of ambient sounding and then narrowed down to the solution that matches satellite-derived cloud top buoyancy. Meanwhile, the large-scale total mass flux is provided separately from satellite soundings by a method developed previously. All satellite snapshots are sorted into a composite time series that delineates the evolution of a vigorous and organized convective system. Principal findings are the following. First, convective mass flux is modulated primarily by convective cloud cover, with the intensity of individual convection being less variable over time. Second, convective mass flux dominates the total mass flux only during the early hours of the convective evolution; as convective system matures, a residual mass flux builds up in the mass flux balance that is reminiscent of stratiform dynamics. The method developed in this study is expected to be of unique utility for future observational diagnosis of tropical convective dynamics and for evaluation of global climate model cumulus parameterizations in a global sense.

Recent Progress on the Second Generation CMORPH: LEO-IR Based Precipitation Estimates and Cloud Motion Vector

Science.gov (United States)

Xie, Pingping; Joyce, Robert; Wu, Shaorong

2015-04-01

As reported at the EGU General Assembly of 2014, a prototype system was developed for the second generation CMORPH to produce global analyses of 30-min precipitation on a 0.05olat/lon grid over the entire globe from pole to pole through integration of information from satellite observations as well as numerical model simulations. The second generation CMORPH is built upon the Kalman Filter based CMORPH algorithm of Joyce and Xie (2011). Inputs to the system include rainfall and snowfall rate retrievals from passive microwave (PMW) measurements aboard all available low earth orbit (LEO) satellites, precipitation estimates derived from infrared (IR) observations of geostationary (GEO) as well as LEO platforms, and precipitation simulations from numerical global models. Key to the success of the 2nd generation CMORPH, among a couple of other elements, are the development of a LEO-IR based precipitation estimation to fill in the polar gaps and objectively analyzed cloud motion vectors to capture the cloud movements of various spatial scales over the entire globe. In this presentation, we report our recent work on the refinement for these two important algorithm components. The prototype algorithm for the LEO IR precipitation estimation is refined to achieve improved quantitative accuracy and consistency with PMW retrievals. AVHRR IR TBB data from all LEO satellites are first remapped to a 0.05olat/lon grid over the entire globe and in a 30-min interval. Temporally and spatially co-located data pairs of the LEO TBB and inter-calibrated combined satellite PMW retrievals (MWCOMB) are then collected to construct tables. Precipitation at a grid box is derived from the TBB through matching the PDF tables for the TBB and the MWCOMB. This procedure is implemented for different season, latitude band and underlying surface types to account for the variations in the cloud - precipitation relationship. At the meantime, a sub-system is developed to construct analyzed fields of

Lidar studies of extinction in clouds in the ECLIPS project

International Nuclear Information System (INIS)

Martin, C.; Platt, R.; Young, S.A.; Patterson, G.P.

1992-01-01

The Experimental Cloud Lidar Pilot Study (ECLIPS) project has now had two active phases in 1989 and 1991. A number of laboratories around the world have taken part in the study. The observations have yielded new data on cloud height and structure, and have yielded some useful new information on the retrieval of cloud optical properties, together with the uncertainties involved. Clouds have a major impact on the climate of the earth. They have the effect of reducing the mean surface temperature from 30 C for a cloudless planet to a value of about 15 C for present cloud conditions. However, it is not at all certain how clouds would react to a change in the planetary temperature in the event of climate change due to a radiative forcing from greenhouse gases. Clouds both reflect out sunlight (negative feedback) and enhance the greenhouse effect (positive feedback), but the ultimate sign of cloud feedback is unknown. Because of these uncertainties, campaigns to study clouds intensely were initiated. The International Satellite Cloud Climatology (ISCPP) and the FIRE Campaigns (cirrus and stratocumulus) are examples. The ECLIPS was set up similarly to the above experiments to obtain information specifically on cloud base, but also cloud top (where possible), optical properties, and cloud structure. ECLIPS was designed to allow as many laboratories as possible globally to take part to get the largest range of clouds. It involves observations with elastic backscatter lidar, supported by infrared fluxes at the ground and radiosonde data, as basic instrumentation. More complex experiments using beam filter radiometers, solar pyranometers, and satellite data and often associated with other campaigns were also encouraged to join ECLIPS

Studying the influence of temperature and pressure on microphysical properties of mixed-phase clouds using airborne measurements

Science.gov (United States)

Andreea, Boscornea; Sabina, Stefan; Sorin-Nicolae, Vajaiac; Mihai, Cimpuieru

2015-04-01

One cloud type for which the formation and evolution process is not well-understood is the mixed-phase type. In general mixed-phase clouds consist of liquid droplets and ice crystals. The temperature interval within both liquid droplets and ice crystals can potentially coexist is limited to 0 °C and - 40 °C. Mixed-phase clouds account for 20% to 30% of the global cloud coverage. The need to understand the microphysical characteristics of mixed-phase clouds to improve numerical forecast modeling and radiative transfer calculation is of major interest in the atmospheric community. In the past, studies of cloud phase composition have been significantly limited by a lack of aircraft instruments capable of discriminating between the ice and liquid phase for a wide range of particle sizes. Presently, in situ airborne measurements provide the most accurate information about cloud microphysical characteristics. This information can be used for verification of both numerical models and cloud remote-sensing techniques. The knowledge of the temperature and pressure variation during the airborne measurements is crucial in order to understand their influence on the cloud dynamics and also their role in the cloud formation processes like accretion and coalescence. Therefore, in this paper is presented a comprehensive study of cloud microphysical properties in mixed-phase clouds in focus of the influence of temperature and pressure variation on both, cloud dynamics and the cloud formation processes, using measurements performed with the ATMOSLAB - Airborne Laboratory for Environmental Atmospheric Research in property of the National Institute for Aerospace Research "Elie Carafoli" (INCAS). The airborne laboratory equipped for special research missions is based on a Hawker Beechcraft - King Air C90 GTx aircraft and is equipped with a sensors system CAPS - Cloud, Aerosol and Precipitation Spectrometer (30 bins, 0.51-50 µm) and a HAWKEYE cloud probe. The analyzed data in this

Evaluation of Passive Multilayer Cloud Detection Using Preliminary CloudSat and CALIPSO Cloud Profiles

Science.gov (United States)

Minnis, P.; Sun-Mack, S.; Chang, F.; Huang, J.; Nguyen, L.; Ayers, J. K.; Spangenberg, D. A.; Yi, Y.; Trepte, C. R.

2006-12-01

During the last few years, several algorithms have been developed to detect and retrieve multilayered clouds using passive satellite data. Assessing these techniques has been difficult due to the need for active sensors such as cloud radars and lidars that can "see" through different layers of clouds. Such sensors have been available only at a few surface sites and on aircraft during field programs. With the launch of the CALIPSO and CloudSat satellites on April 28, 2006, it is now possible to observe multilayered systems all over the globe using collocated cloud radar and lidar data. As part of the A- Train, these new active sensors are also matched in time ad space with passive measurements from the Aqua Moderate Resolution Imaging Spectroradiometer (MODIS) and Advanced Microwave Scanning Radiometer - EOS (AMSR-E). The Clouds and the Earth's Radiant Energy System (CERES) has been developing and testing algorithms to detect ice-over-water overlapping cloud systems and to retrieve the cloud liquid path (LWP) and ice water path (IWP) for those systems. One technique uses a combination of the CERES cloud retrieval algorithm applied to MODIS data and a microwave retrieval method applied to AMSR-E data. The combination of a CO2-slicing cloud retireval technique with the CERES algorithms applied to MODIS data (Chang et al., 2005) is used to detect and analyze such overlapped systems that contain thin ice clouds. A third technique uses brightness temperature differences and the CERES algorithms to detect similar overlapped methods. This paper uses preliminary CloudSat and CALIPSO data to begin a global scale assessment of these different methods. The long-term goals are to assess and refine the algorithms to aid the development of an optimal combination of the techniques to better monitor ice 9and liquid water clouds in overlapped conditions.

Biotoxicity and bioavailability of hydrophobic organic compounds solubilized in nonionic surfactant micelle phase and cloud point system.

Science.gov (United States)

Pan, Tao; Liu, Chunyan; Zeng, Xinying; Xin, Qiao; Xu, Meiying; Deng, Yangwu; Dong, Wei

2017-06-01

A recent work has shown that hydrophobic organic compounds solubilized in the micelle phase of some nonionic surfactants present substrate toxicity to microorganisms with increasing bioavailability. However, in cloud point systems, biotoxicity is prevented, because the compounds are solubilized into a coacervate phase, thereby leaving a fraction of compounds with cells in a dilute phase. This study extends the understanding of the relationship between substrate toxicity and bioavailability of hydrophobic organic compounds solubilized in nonionic surfactant micelle phase and cloud point system. Biotoxicity experiments were conducted with naphthalene and phenanthrene in the presence of mixed nonionic surfactants Brij30 and TMN-3, which formed a micelle phase or cloud point system at different concentrations. Saccharomyces cerevisiae, unable to degrade these compounds, was used for the biotoxicity experiments. Glucose in the cloud point system was consumed faster than in the nonionic surfactant micelle phase, indicating that the solubilized compounds had increased toxicity to cells in the nonionic surfactant micelle phase. The results were verified by subsequent biodegradation experiments. The compounds were degraded faster by PAH-degrading bacterium in the cloud point system than in the micelle phase. All these results showed that biotoxicity of the hydrophobic organic compounds increases with bioavailability in the surfactant micelle phase but remains at a low level in the cloud point system. These results provide a guideline for the application of cloud point systems as novel media for microbial transformation or biodegradation.

Satellite precipitation estimation over the Tibetan Plateau

Science.gov (United States)

Porcu, F.; Gjoka, U.

2012-04-01

Precipitation characteristics over the Tibetan Plateau are very little known, given the scarcity of reliable and widely distributed ground observation, thus the satellite approach is a valuable choice for large scale precipitation analysis and hydrological cycle studies. However,the satellite perspective undergoes various shortcomings at the different wavelengths used in atmospheric remote sensing. In the microwave spectrum often the high soil emissivity masks or hides the atmospheric signal upwelling from light-moderate precipitation layers, while low and relatively thin precipitating clouds are not well detected in the visible-infrared, because of their low contrast with cold and bright (if snow covered) background. In this work an IR-based, statistical rainfall estimation technique is trained and applied over the Tibetan Plateau hydrological basin to retrive precipitation intensity at different spatial and temporal scales. The technique is based on a simple artificial neural network scheme trained with two supervised training sets assembled for monsoon season and for the rest of the year. For the monsoon season (estimated from June to September), the ground radar precipitation data for few case studies are used to build the training set: four days in summer 2009 are considered. For the rest of the year, CloudSat-CPR derived snowfall rate has been used as reference precipitation data, following the Kulie and Bennartz (2009) algorithm. METEOSAT-7 infrared channels radiance (at 6.7 and 11 micometers) and derived local variability features (such as local standard deviation and local average) are used as input and the actual rainrate is obtained as output for each satellite slot, every 30 minutes on the satellite grid. The satellite rainrate maps for three years (2008-2010) are computed and compared with available global precipitation products (such as C-MORPH and TMPA products) and with other techniques applied to the Plateau area: similarities and differences are

Advanced Technology Cloud Particle Probe for UAS, Phase II

Data.gov (United States)

National Aeronautics and Space Administration — In Phase II SPEC will design, fabricate and flight test a state-of-the-art combined cloud particle probe called the Hawkeye. Hawkeye is the culmination of two...

Radiative effects of clouds and cryosphere in the Antarctic

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Takashi Yamanouchi

1997-03-01

Full Text Available Examination of the effects of clouds, ice sheet and sea ice on the radiation budget in the Antarctic using Earth Radiation Budget Experiment (ERBE data were reported. The continental ice sheet affects not only the albedo, but also the surface temperature because of elevation, and hence the OLR. Sea ice, which is a critical climate feedback factor, appears to have less impact on radiation than do clouds. However, these surfaces lie underneath clouds, and it was found that the independent effect of sea ice is as large as that of clouds, and clouds are masking the radiative effect of sea ice by more than half. The radiation budget at the top of the atmosphere from satellite observation and that at the surface from the surface radiation measurements at Syowa and South Pole Stations were compared. Cloud radiative forcing at both stations for the surface, atmosphere and top of the atmosphere was derived.

A cosmic ray-climate link and cloud observations

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Dunne Eimear M.

2012-11-01

Full Text Available Despite over 35 years of constant satellite-based measurements of cloud, reliable evidence of a long-hypothesized link between changes in solar activity and Earth’s cloud cover remains elusive. This work examines evidence of a cosmic ray cloud link from a range of sources, including satellite-based cloud measurements and long-term ground-based climatological measurements. The satellite-based studies can be divided into two categories: (1 monthly to decadal timescale analysis and (2 daily timescale epoch-superpositional (composite analysis. The latter analyses frequently focus on sudden high-magnitude reductions in the cosmic ray flux known as Forbush decrease events. At present, two long-term independent global satellite cloud datasets are available (ISCCP and MODIS. Although the differences between them are considerable, neither shows evidence of a solar-cloud link at either long or short timescales. Furthermore, reports of observed correlations between solar activity and cloud over the 1983–1995 period are attributed to the chance agreement between solar changes and artificially induced cloud trends. It is possible that the satellite cloud datasets and analysis methods may simply be too insensitive to detect a small solar signal. Evidence from ground-based studies suggests that some weak but statistically significant cosmic ray-cloud relationships may exist at regional scales, involving mechanisms related to the global electric circuit. However, a poor understanding of these mechanisms and their effects on cloud makes the net impacts of such links uncertain. Regardless of this, it is clear that there is no robust evidence of a widespread link between the cosmic ray flux and clouds.

The Global Influence of Cloud Optical Thickness on Terrestrial Carbon Uptake

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Zhu, P.; Cheng, S. J.; Keppel-Aleks, G.; Butterfield, Z.; Steiner, A. L.

2016-12-01

Clouds play a critical role in regulating Earth's climate. One important way is by changing the type and intensity of solar radiation reaching the Earth's surface, which impacts plant photosynthesis. Specifically, the presence of clouds modifies photosynthesis rates by influencing the amount of diffuse radiation as well as the spectral distribution of solar radiation. Satellite-derived cloud optical thickness (COT) may provide the observational constraint necessary to assess the role of clouds on ecosystems and terrestrial carbon uptake across the globe. Previous studies using ground-based observations at individual sites suggest that below a COT of 7, there is a greater increase in light use efficiency than at higher COT values, providing evidence for higher carbon uptake rates than expected given the reduction in radiation by clouds. However, the strength of the COT-terrestrial carbon uptake correlation across the globe remains unknown. In this study, we investigate the influence of COT on terrestrial carbon uptake on a global scale, which may provide insights into cloud conditions favorable for plant photosynthesis and improve our estimates of the land carbon sink. Global satellite-derived MODIS data show that tropical and subtropical regions tend to have COT values around or below the threshold during growing seasons. We find weak correlations between COT and GPP with Fluxnet MTE global GPP data, which may be due to the uncertainty of upscaling GPP from individual site measurements. Analysis with solar-induced fluorescence (SIF) as a proxy for GPP is also evaluated. Overall, this work constructs a global picture of the role of COT on terrestrial carbon uptake, including its temporal and spatial variations.

Assessment of satellite derived diffuse attenuation coefficients ...

Science.gov (United States)

Optical data collected in coastal waters off South Florida and in the Caribbean Sea between January 2009 and December 2010 were used to evaluate products derived with three bio-optical inversion algorithms applied to MOIDS/Aqua, MODIS/Terra, and SeaWiFS satellite observations. The products included the diffuse attenuation coefficient at 490 nm (Kd_490) and for the visible range (Kd_PAR), and euphotic depth (Zeu, corresponding to 1% of the surface incident photosynthetically available radiation or PAR). Above-water hyperspectral reflectance data collected over optically shallow waters of the Florida Keys between June 1997 and August 2011 were used to help understand algorithm performance over optically shallow waters. The in situ data covered a variety of water types in South Florida and the Caribbean Sea, ranging from deep clear waters, turbid coastal waters, and optically shallow waters (Kd_490 range of ~0.03 – 1.29m-1). An algorithm based on Inherent Optical Properties (IOPs) showed the best performance (RMSD turbidity or shallow bottom contamination. Similar results were obtained when only in situ data were used to evaluate algorithm performance. The excellent agreement between satellite-derived remote sensing reflectance (Rrs) and in situ Rrs suggested that

The operational cloud retrieval algorithms from TROPOMI on board Sentinel-5 Precursor

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D. G. Loyola

2018-01-01

Full Text Available This paper presents the operational cloud retrieval algorithms for the TROPOspheric Monitoring Instrument (TROPOMI on board the European Space Agency Sentinel-5 Precursor (S5P mission scheduled for launch in 2017. Two algorithms working in tandem are used for retrieving cloud properties: OCRA (Optical Cloud Recognition Algorithm and ROCINN (Retrieval of Cloud Information using Neural Networks. OCRA retrieves the cloud fraction using TROPOMI measurements in the ultraviolet (UV and visible (VIS spectral regions, and ROCINN retrieves the cloud top height (pressure and optical thickness (albedo using TROPOMI measurements in and around the oxygen A-band in the near infrared (NIR. Cloud parameters from TROPOMI/S5P will be used not only for enhancing the accuracy of trace gas retrievals but also for extending the satellite data record of cloud information derived from oxygen A-band measurements, a record initiated with the Global Ozone Monitoring Experiment (GOME on board the second European Remote-Sensing Satellite (ERS-2 over 20 years ago. The OCRA and ROCINN algorithms are integrated in the S5P operational processor UPAS (Universal Processor for UV/VIS/NIR Atmospheric Spectrometers, and we present here UPAS cloud results using the Ozone Monitoring Instrument (OMI and GOME-2 measurements. In addition, we examine anticipated challenges for the TROPOMI/S5P cloud retrieval algorithms, and we discuss the future validation needs for OCRA and ROCINN.

Comparison of Cloud and Aerosol Detection between CERES Edition 3 Cloud Mask and CALIPSO Version 2 Data Products

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Trepte, Qing; Minnis, Patrick; Sun-Mack, Sunny; Trepte, Charles

Clouds and aerosol play important roles in the global climate system. Accurately detecting their presence, altitude, and properties using satellite radiance measurements is a crucial first step in determining their influence on surface and top-of-atmosphere radiative fluxes. This paper presents a comparison analysis of a new version of the Clouds and Earth's Radiant Energy System (CERES) Edition 3 cloud detection algorithms using Aqua MODIS data with the recently released Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO) Version 2 Vertical Feature Mask (VFM). Improvements in CERES Edition 3 cloud mask include dust detection, thin cirrus tests, enhanced low cloud detection at night, and a smoother transition from mid-latitude to polar regions. For the CALIPSO Version 2 data set, changes to the lidar calibration can result in significant improvements to its identification of optically thick aerosol layers. The Aqua and CALIPSO satellites, part of the A-train satellite constellation, provide a unique opportunity for validating passive sensor cloud and aerosol detection using an active sensor. In this paper, individual comparison cases will be discussed for different types of clouds and aerosols over various surfaces, for daytime and nighttime conditions, and for regions ranging from the tropics to the poles. Examples will include an assessment of the CERES detection algorithm for optically thin cirrus, marine stratus, and polar night clouds as well as its ability to characterize Saharan dust plumes off the African coast. With the CALIPSO lidar's unique ability to probe the vertical structure of clouds and aerosol layers, it provides an excellent validation data set for cloud detection algorithms, especially for polar nighttime clouds.

Estimation of satellite position, clock and phase bias corrections

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Henkel, Patrick; Psychas, Dimitrios; Günther, Christoph; Hugentobler, Urs

2018-05-01

Precise point positioning with integer ambiguity resolution requires precise knowledge of satellite position, clock and phase bias corrections. In this paper, a method for the estimation of these parameters with a global network of reference stations is presented. The method processes uncombined and undifferenced measurements of an arbitrary number of frequencies such that the obtained satellite position, clock and bias corrections can be used for any type of differenced and/or combined measurements. We perform a clustering of reference stations. The clustering enables a common satellite visibility within each cluster and an efficient fixing of the double difference ambiguities within each cluster. Additionally, the double difference ambiguities between the reference stations of different clusters are fixed. We use an integer decorrelation for ambiguity fixing in dense global networks. The performance of the proposed method is analysed with both simulated Galileo measurements on E1 and E5a and real GPS measurements of the IGS network. We defined 16 clusters and obtained satellite position, clock and phase bias corrections with a precision of better than 2 cm.