Search NASA⌕ Search

SEARCH · Search NASA

Results for “cloud database”

Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 109 records · Page 6
All sourcesNASA NTRSDOE OSTI
NASA NTRS2018

Reply to "Comments on 'A CloudSat-CALIPSO View of Cloud and Precipitation Properties Across Cold Fronts over the Global Oceans'"

In Naud et al., a compositing method was utilized with CloudSat-CALIPSO observations to obtain mean transects of cloud vertical distribution and surface precipitation across cold fronts, and to examine their sensitivity to the large-scale properties of the parent extratropical cyclone. This reply demonstrates the value of compositing for evaluating numerical models, and presents additional results that address the issue of the sensitivity of the initial results to the frontal detection methodology and the potential misclassification of occlusions as cold fronts. Here a sensitivity study of the cold front composite transects of cloud cover to the input datasets or the method utilized to locate the cold fronts demonstrates that these composite transects are robust and only marginally sensitive to cold front location methods. The same conclusion is reached for the robustness of the contrast between Northern and Southern Hemisphere cloud transects. While occlusions cannot directly be flagged within the database at this point, comparisons of transects obtained for subsets of cyclones of different age indicate that the misclassification of occluded fronts as cold fronts does not explain the predominance of cloud and precipitation on the warm side of the cold fronts. The strong signal on the warm side might be better explained by a predominance of forward sloping cold fronts, or the presence of the warm conveyor belt.

Cloud cover; Cold fronts; Extratropical cyclones; ↗
DOE OSTI2017

The Star-formation Law in Galactic High-mass Star-forming Molecular Clouds

We study the star-formation (SF) law in 12 Galactic molecular clouds with ongoing high-mass star-formation (HMSF) activity, as traced by the presence of a bright IRAS source and other HMSF tracers. We define the molecular cloud (MC) associated with each IRAS source using {sup 13}CO line emission, and count the young stellar objects (YSOs) within these clouds using GLIMPSE and MIPSGAL 24 μm Spitzer databases. The masses for high-luminosity YSOs (L {sub bol} > 10 L {sub ⊙}) are determined individually using pre-main-sequence evolutionary tracks and the evolutionary stages of the sources, whereas a mean mass of 0.5 M {sub ⊙} was adopted to determine the masses in the low-luminosity YSO population. The star-formation rate surface density (Σ{sub SFR}) corresponding to a gas surface density (Σ{sub gas}) in each MC is obtained by counting the number of the YSOs within successive contours of {sup 13}CO line emission. We find a break in the relation between Σ{sub SFR} and Σ{sub gas}, with the relation being a power law (Σ{sub SFR}∝Σ{sub gas}{sup N}) with the index N varying between 1.4 and 3.6 above the break. The Σ{sub gas} at the break is between 150–360 M {sub ⊙} pc{sup −2} for the sample clouds, which compares well with the threshold gas density found in recent studies of Galactic star-forming regions. Our clouds treated as a whole lie between the Kennicutt relation and the linear relation for Galactic and extra-galactic dense star-forming regions. We find a tendency for the high-mass YSOs to be found preferentially in dense regions at densities higher than 1200 M {sub ⊙} pc{sup −2} (∼0.25 g cm{sup −2}).

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2018

Workflow-based automatic processing for Internet of Floating Things crowdsourced data

Data from sensors incorporated into mobile devices, such as networked navigational sensors, can be used to capture detailed environmental information. We describe here a workflow and framework for using sensors on boats to construct unique new datasets of underwater topography (bathymetry). Starting with a large number of measurements of position, depth, etc., obtained from such an Internet of Floating Things, we illustrate how, with a specialized protocol, data can be communicated to cloud resources, even when using delayed, intermittent, or disconnected networks. We then propose a method for automatic sensor calibration based on a novel reputation approach. Sampled depth data are interpolated efficiently on a cloud computing platform in order to provide a continuously updated bathymetric database. Our prototype implementation uses the FACE-IT Galaxy workflow engine to manage network communication and exploits the computational power of GPGPUs in a virtualized cloud environment, working with a CUDA-parallel algorithm, for efficient data processing. We report on an initial evaluation involving data from a sailing vessel in Italian coastal waters.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS1985

Collisional excitation of molecules in dense interstellar clouds

State transitions which permit the identification of the molecular species in dense interstellar clouds are reviewed, along with the techniques used to calculate the transition energies, the database on known molecular transitions and the accuracy of the values. The transition energies cannot be measured directly and therefore must be modeled analytically. Scattering theory is used to determine the intermolecular forces on the basis of quantum mechanics. The nuclear motions can also be modeled with classical mechanics. Sample rate constants are provided for molecular systems known to inhabit dense interstellar clouds. The values serve as a database for interpreting microwave and RF astrophysical data on the transitions undergone by interstellar molecules.

Green, S.↗
NASA NTRSDate not supplied

Implementation of A New Microwave Scattering Database and A Forward Model for Active Microwave Sensors in CRTM

Radiative transfer models are extensively used for the assimilation of satellite observations into NWP models as well as retrieving geophysical products from satellite measurements. CRTM is a community model developed by NOAA JCSDA and widely used for different purposes requiring RT calculations. CRTM requires bulk scattering lookup tables in order to perform all-sky RT calculations. However, the current CRTM lookup tables for microwave frequencies were generated based on the Mie theory by assuming spherical frozen particles. The scattering lookup tables generated using the DDA technique has shown to largely improve the RT scattering calculations in the MW region. This presentation targets (i) the implementation and validation of a DDA database that was originally developed for the ARTS RT model into CRTM, and (ii) developing the CRTM active sensor module that takes advantage of the backscattering coefficients computed using the DDA method. The DDA database only provides single scattering properties of different habits, while CRTM requires bulk scattering properties. The CRTM cloud coefficients were previously generated based on the effective radius for representing the size of the particles. However, effective radius is neither measurable nor provided by the NWP models, thus need to be estimated from other geophysical variables such as water content. Therefore, in addition to calculating the CRTM bulk scattering properties from the DDA single scattering database, the CRTM was also largely modified to use cloud water content (kg.m-3), instead of effective radius, for performing the interpolation over size/mass of the particles. CRTM already requires water content as input, thus no extra variables are required for performing scattering calculations using the new ARTS DDA database. The CRTM scattering modules search for effective radius in cloud coefficient files and will use the cloud water content if the effective radius dimension is not found in the cloud coefficient files. Figure 1 shows the CRTM simulated brightness temperatures computed using different cloud coefficients versus ATMS observed values over Hurricane Irma on September 7, 2017 at 18:00 UTC. We used all the cloud water content values included in ERA5 with default CRTM/DDA habits for water, rain, snow, ice, hail, and graupel. ERA5 does not provide separate water content values for ice, hail, and graupel, thus the ice water content values were divided between ice, hail, and graupel clouds similar to what was explained in the previous section. In channels with a frequency lower than 90 GHz, emission from water and rain clouds can compensate for cloud scattering so that cloud contaminated Tbs are larger than corresponding clear sky Tbs. The DDA simulations for channels 1-7 largely perform better than the Mie simulations. The DDA simulations show a mix of small negative and positive simulated minus observed values, while the Mie results show large negative biases. The weighting functions for some of the ATMS temperature sounding channels (channels 9-15) peak mostly above the clouds, therefore the measured Tbs become less sensitive to clouds so that the results of both Mie and DDA become very similar. The Mie lookup tables generate excessive scattering for channel 16, but not enough scattering for the water vapor channels. In the specific case of Hurricane Maria, the DDA lookup tables do not generate enough scattering for channel 16, but the DDA results are much more consistent with observations for water vapor channels than for channel 16. It should be noted that the results may vary if we use other habits to represent snow, hail, and graupel in the DDA simulations. Although these results clearly show the advantage of the DDA database over the Mie dataset, different error sources such as error in the observations, displacement of clouds in the ERA5 reanalysis, and also lack of convective clouds or in general errors in the input atmospheric and cloud profiles contribute to the differences between the simulated and observed values. Aside from the improvements in the simulations, a major advantage of the new dataset is a large number of habits that can be used to tune the data assimilation systems to perform well in different weather conditions.

Isaac Moradi↗
NASA NTRS2019

Analysis Ready Data in Analytics Optimized Data Stores for Analysis of Big Earth Data in the Cloud

Cloud computing offers the possibility of making the analysis of Big Data approachable for a wider community due to affordable access to computing power, an ecosystem of usable tools for parallel processing, and migration of many large datasets to archives in the cloud, allowing data-proximal computing. Generally, data analysis acceleration in the cloud comes from running multiple nodes in a split-combine-apply strategy. Data systems such as the Earth Observing System Data and Information System are in a position to "pre-split" the data by storing them in a data store that is optimized for data parallel computing, i.e., an Analytics-Optimized Data Store (AODS). A variety of approaches to AODS are possible, from highly scalable databases to scalable filesystems to data formats optimized for cloud access (e.g., zarr and cloud-optimized datasets), with the optimal choice dependent on both the types of analysis and the geospatial structure of the data. A key question is how much preprocessing of the data to do, both before splitting and as the first part of the apply step. Again, the geospatial structure of the data and the analysis type influence the decision, with the added complexity of the user type. Trans-disciplinary users who are not well-versed in the nuances of quality-filtering and georeferencing of remote sensing orbit/swath/scene data tend to ask for more highly processed data, relying on the data provider to make sensible decisions on preprocessing parameters. (This accounts for the popularity of "Level 3" gridded data, despite the lower spatial resolution it provides.) In this case, data can be preprocessed before the split, resulting in higher performance in the rest of the "apply" step, which can be transformative for use cases such as interactive data exploration at scale. Discipline researchers who are experienced with remote sensing data often prefer more flexibility in customizing the preprocessing data into Analysis Ready Data, resulting in more need for on-the-fly preprocessing.

Lynnes, Christopher↗
NASA NTRS1995

Upper Thermosphere Winds and Temperatures in the Geomagnetic Polar Cap: Solar Cycle, Geomagnetic Activity, and Interplanetary Magnetic Field Dependencies

Ground-based Fabry-Perot interferometers located at Thule, Greenland (76.5 deg. N, 69.0 deg. W, lambda = 86 deg.) and at Sondre Stromfjord, Greenland (67.0 deg. N, 50.9 deg. W, lambda = 74 deg.) have monitored the upper thermospheric (approx. 240-km altitude) neutral wind and temperature over the northern hemisphere geomagnetic polar cap since 1983 and 1985, respectively. The thermospheric observations are obtained by determining the Doppler characteristics of the (OI) 15,867-K (630.0-nm) emission of atomic oxygen. The instruments operate on a routine, automatic, (mostly) untended basis during the winter observing seasons, with data coverage limited only by cloud cover and (occasional) instrument failures. This unique database of geomagnetic polar cap measurements now extends over the complete range of solar activity. We present an analysis of the measurements made between 1985 (near solar minimum) and 1991 (near solar maximum), as part of a long-term study of geomagnetic polar cap thermospheric climatology. The measurements from a total of 902 nights of observations are compared with the predictions of two semiempirical models: the Vector Spherical Harmonic (VSH) model of Killeen et al. (1987) and the Horizontal Wind Model (HWM) of Hedin et al. (1991). The results are also analyzed using calculations of thermospheric momentum forcing terms from the Thermosphere-ionosphere General Circulation Model TGCM) of the National Center for Atmospheric Research (NCAR). The experimental results show that upper thermospheric winds in the geomagnetic polar cap have a fundamental diurnal character, with typical wind speeds of about 200 m/s at solar minimum, rising to up to about 800 m/s at solar maximum, depending on geomagnetic activity level. These winds generally blow in the antisunward direction, but are interrupted by episodes of modified wind velocity and altered direction often associated with changes in the orientation of the Interplanetary Magnetic Field (IMF). The central polar cap (greater than approx. 80 magnetic latitude) antisunward wind speed is found to be a strong function of both solar and geomagnetic activity. The polar cap temperatures show variations in both solar and geomagnetic activity, with temperatures near 800 K for low K(sub p) and F(sub 10.7) and greater than about 2000 K for high K(sub p) and F(sub 10.7). The observed temperatures are significantly greater than those predicted by the mass spectrometer/incoherent scatter model for high activity conditions. Theoretical analysis based on the NCAR TIGCM indicates that the antisunward upper thermospheric winds, driven by upstream ion drag, basically 'coast' across the polar cap. The relatively small changes in wind velocity and direction within the polar cap are induced by a combination of forcing terms of commensurate magnitude, including the nonlinear advection term, the Coriolis term, and the pressure gradient force term. The polar cap thennospheric thermal balance is dominated by horizontal advection, and adiabatic and thermal conduction terms.

Killeen, T. L.↗
NASA NTRS2005

A Model Based Mars Climate Database for the Mission Design

A viewgraph presentation on a model based climate database is shown. The topics include: 1) Why a model based climate database?; 2) Mars Climate Database v3.1 Who uses it ? (approx. 60 users!); 3) The new Mars Climate database MCD v4.0; 4) MCD v4.0: what's new ? 5) Simulation of Water ice clouds; 6) Simulation of Water ice cycle; 7) A new tool for surface pressure prediction; 8) Acces to the database MCD 4.0; 9) How to access the database; and 10) New web access

Source record↗
DOE OSTI2022

Deep Convection Initiation, Growth, and Environments in the Complex Terrain of Central Argentina during CACTI

This study characterizes the wide range of deep convective cloud life cycles and their relationships with ambient environments observed during the Cloud, Aerosol, and Complex Terrain Interactions (CACTI) field campaign near the Sierras de Córdoba (SDC) range in central Argentina. We develop a novel convective cell tracking database for the entire field campaign using C-band polarimetric radar observations. The cell tracking database includes timing, location, area, depth, merge/split information, microphysical properties, collocated satellite-retrieved cloud properties, and sounding-derived environmental conditions. Results show that the SDC exerts a strong control on convection initiation (CI) and growth. CI preferentially occurs east of the SDC ridge during the afternoon, and cells often undergo upscale growth through the evening as they travel eastward toward the plains. Larger and more intense cells tend to occur in more unstable and humid low-level environments, and surface-based cells are stronger than elevated cells. Midtropospheric relative humidity and vertical wind shear also jointly affect the size and depth of the cells. Rapid cell area growth rates exhibit dependence on both large environmental wind shear and low-level moisture. Evolution of convective cell macro- and microphysical properties are strongly influenced by convective available potential energy and low-level humidity, as well as the presence of other cells in their vicinity. This cell tracking database demonstrates a framework that ties measurements from various platforms centering around convective life cycles to facilitate process understanding of factors that control convective evolution.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRSDate not supplied

Harmonized Sentinel-1 SAR Global River Geometry and Inundation Database

Satellite-based observations on river geometries are sporadic in time, space, or both. Most satellite-based surface water maps, river widths, water surface elevations (WSE), slopes, and bathymetry are asynchronized in time and space. The current configuration of satellites such as Sentinel-6 measured the WSE but is missing the river width, slopes, and depths. To advance hydrological sciences research, there is a need to produce a harmonized time series of river geometry data of non-SWOT satellites in partnership with the upcoming SWOT mission. The SWOT satellite will measure river width, height, and slope but missing river depth measurements in space and time. Further, none of these current satellites measure the WSE, river width, and slopes synchronously. In this work, we use the Sentinel-1 SAR satellite data archive from 2015 to the present to create a global river width and surface water database at the reach scale. A modified version of the Sentinel SAR surface water classification algorithm from ASF is used to quantify the surface water extent on the stream approximately every six days (at the equator) at 10m spatial resolution globally. This 10m water mask is fed into a workflow to quantify the river widths, surface water inundations, slopes, and synthetic bathymetry in SWORD (SWOT River Database) stream networks. A Satellite HAND is used to address the cloud obscured surface water observations using a trained machine learning algorithm. We use WSE derived from the Global Water Monitor from NASA GSFC, Hydroweb from LEGOS, and ICESat-2 to harmonize the WSE observation. And Landsat-8/9 and Sentinel-2 water observations to fill the gaps in the Sentinel-1 SAR database. We use Congo River Basin as a test case where we have more than 500 radar altimetry-based WSE, continuous series of Sentinel-1, ICESat-2, Landsat-8/9, and Sentinel-2 observations. A Congo River hydrologic model is used to generate the streamflow discharge. The satellite observed river reaches are assimilated with the stream flows computed by the routing models. And the downstream reaches in the river network without satellite observations get optimized for discharge/river geometry at each observation cycle. Our final product is a harmonized river geometry dataset (reach's water extent, WSE, slope, synthetic bathymetry) for Congo Basin's SWORD reaches.

Chandana Gangodagamage↗
NASA NTRS2003

Satellite and Surface Data Synergy for Developing a 3D Cloud Structure and Properties Characterization Over the ARM SGP. Stage 1: Cloud Amounts, Optical Depths, and Cloud Heights Reconciliation

One of the primary Atmospheric Radiation Measurement (ARM) Program objectives is to obtain measurements applicable to the development of models for better understanding of radiative processes in the atmosphere. We address this goal by building a three-dimensional (3D) characterization of the cloud structure and properties over the ARM Southern Great Plains (SGP). We take the approach of juxtaposing the cloud properties as retrieved from independent satellite and ground-based retrievals, and looking at the statistics of the cloud field properties. Once these retrievals are well understood, they will be used to populate the 3D characterization database. As a first step we determine the relationship between surface fractional sky cover and satellite viewing angle dependent cloud fraction (CF). We elaborate on the agreement intercomparing optical depth (OD) datasets from satellite and ground using available retrieval algorithms with relation to the CF, cloud height, multi-layer cloud presence, and solar zenith angle (SZA). For the SGP Central Facility, where output from the active remote sensing cloud layer (ARSCL) valueadded product (VAP) is available, we study the uncertainty of satellite estimated cloud heights and evaluate the impact of this uncertainty for radiative studies.

Genkova, I.↗
NASA NTRS2004

Web-Based Satellite Products Database for Meteorological and Climate Applications

The need for ready access to satellite data and associated physical parameters such as cloud properties has been steadily growing. Air traffic management, weather forecasters, energy producers, and weather and climate researchers among others can utilize more satellite information than in the past. Thus, it is essential that such data are made available in near real-time and as archival products in an easy-access and user friendly environment. A host of Internet web sites currently provide a variety of satellite products for various applications. Each site has a unique contribution with appeal to a particular segment of the public and scientific community. This is no less true for the NASA Langley's Clouds and Radiation (NLCR) website (http://www-pm.larc.nasa.gov) that has been evolving over the past 10 years to support a variety of research projects This website was originally developed to display cloud products derived from the Geostationary Operational Environmental Satellite (GOES) over the Southern Great Plains for the Atmospheric Radiation Measurement (ARM) Program. It has evolved into a site providing a comprehensive database of near real-time and historical satellite products used for meteorological, aviation, and climate studies. To encourage the user community to take advantage of the site, this paper summarizes the various products and projects supported by the website and discusses future options for new datasets.

Phan, Dung↗
DOE OSTI2018

The efficacy of aerosol–cloud radiative perturbations from near-surface emissions in deep open-cell stratocumuli

Aerosol–cloud radiative effects are determined and quantified in simulationsof deep open-cell stratocumuli observed during the VAMOS Ocean-Cloud-Atmosphere-LandStudy Regional Experiment (VOCALS-REx) campaign offthe west coast of Chile. The cloud deck forms in a boundarylayer 1.5 km deep, with cell sizes reaching 50 km in diameter. Global databases of shiptracks suggest that these linear structures are seldom found in boundarylayers this deep. Here, we quantify the changes in cloud radiative propertiesto a continuous aerosol point source moving along a fixed emission linereleasing 10 17 particles per second. We show that a spatially coherentcloud perturbation is not evident along the emission line. Yet our modelsimulates an increase in domain-mean all-sky albedo of 0.05, corresponding toa diurnally averaged cloud radiative effect of 20 W m -2 , given theannual mean solar insolation at the VOCALS-REx site. Therefore, markedchanges in cloud radiative properties in precipitating deep open cells may bedriven by anthropogenic near-surface aerosol perturbations, such as thosegenerated by ships.Furthermore, we demonstrate that these changes in cloud radiative propertiesare masked by the naturally occurring variability within the organised cloudfield. A clear detection and attribution of cloud radiative effects to aperturbation in aerosol concentrations becomes possible when sub-filtering ofthe cloud field is applied, using the spatio-temporal distribution of theaerosol perturbation. Therefore, this work has implications for the detectionand attribution of effective cloud radiative forcing in marine stratocumuli,which constitutes one of the major physical uncertainties within the climatesystem. Our results suggest that ships may sometimes have a substantialradiative effect on marine clouds and albedo, even when ship tracks are notreadily visible.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS2019

Macro-Scale Findings of the DebriSat Debris Field Obtained from X-Rays of the Catch Panels

The DebriSat project analyzes the debris from a hypervelocity impact test conducted on a 56 kg-simulated satellite target in 2014. Its purpose is to generate a comprehensive database of the size, mass, material, shape, and the radar and optical properties of fragments generated from orbital collisions of modern-built spacecraft. Three hundred ninety-one foam catch panels from the DebriSat test have been X-rayed to locate the particles within them for subsequent extraction and assessment. The data from the tens of thousands of extracted particles has heretofore been the focus of the debris assessment. The work presented here connects the X-ray sample location images to reconstruct the 3D distribution of the entire fragment cloud. Although some errors are inherent to the process, this 3D database is valuable for qualitative studies of size and energy distributions. Further, the 3D database can indicate the extent of bending or breaking of the fragments as they decelerated to full capture. By virtue of its full sphere perspective, the 3D database allows graphical insight to the physics of the collision and breakup. This 3D representation has been developed as a “point and click” graphical interface to retrieve the full data set on individual recovered and assessed fragments within the growing database. Overall, this macro-level screening technique has added enormous insight to the experiment in unexpected ways.

Allen, Anthony↗
NASA NTRS2006

NASA Tech Briefs, October 2006

Topics covered include: Protein Sensors Based on Optical Ring Resonators; Phase Sensor for Aligning a Segmented Telescope Mirror; Control Software for Advanced Video Guidance Sensor; Generating Control Commands From Gestures Sensed by EMG; Multiple-Flat-Panel System Displays Multidimensional Data; 3D X-Ray Luggage-Screening System; Probe Station and Near-Field Scanner for Testing Antennas; Photodetector Arrays for Multicolor Visible/Infrared Imaging; Semiconductor Bolometers Give Background-Limited Performance; Multichannel X-Band Dielectric-Resonator Oscillator; Automatic Alignment of Displacement-Measuring Interferometer; Earth Observing System Data Gateway; Power User Interface; Mercury Shopping Cart Interface; Cassini Archive Tracking System; Architecture Adaptive Computing Environment; Computing Fault Displacements from Surface Deformations; Oxygen-Permeable, Hydrophobic Membranes of Silanized alpha-Al2O3; SiC Composite Turbine Vanes; Retaining Device for the Interior Structure of a Spacecraft Payload; Tool for Torquing Circular Electrical-Connector Collars; System for Continuous Deaeration of Hydraulic Oil; Solar-Powered Cooler and Heater for an Automobile Interior; Improved Oxygen-Beam Texturing of Glucose-Monitoring Optics; Tool for Two Types of Friction Stir Welding; Stationary Apparatus Would Apply Forces of Walking to Feet; Instrument Would Detect and Collect Biological Aerosols; Boundary Condition for Modeling Semiconductor Nanostructures; Miniature Distillation Column for Producing LOX From Air; Even Illumination from Fiber-Optic-Coupled Laser Diodes; Optically Driven Deformable Mirrors; Algorithm for Automated Detection of Edges of Clouds; Exploiting Quantum Resonance to Solve Combinatorial Problems; Hybrid Terrain Database; On Release of Microbe-Laden Particles from Mars Landers; A Concept for Run-Time Support of the Chapel Language; Thermoelectric Inhomogeneities in (Ag(sub 1-y)SbTe2)(sub x)(PbTe)(sub 1-x); and Spacecraft Escape Capsule.

Source record↗
NASA NTRS2015

NASA ROVER, Tackling Citizen Science With Grand Challenges and Everyday Problems

ROVER is the Citizen Science arm of the NASA Clouds and the Earth's Radiant Energy System (CERES) Students' Cloud Observations On-Line (S'COOL) Project. Since 2007, participants around the world have been making and reporting ground truth observations of clouds to assist in the validation of the NASA CERES satellite instrument. NASA scientists are very interested in learning how clouds affect our atmosphere, weather, and climate (relating to climate change). It is the clouds, in part, that affect the overall temperature and energy balance of the Earth. The more we know about clouds, the more we will know about our Earth as a system and citizen scientists are an important piece of that puzzle! As a ROVER cloud observer, all participants follow simple online tutorials to collect data on cloud type, height, cover and related conditions. Observations are sent to NASA to be matched to similar information obtained from satellites and sent back to participants for comparison and analysis. The supporting ROVER website houses a searchable database archiving all participant reports and matching satellite data. By involving Citizen Scientists in cloud observations and reporting we can gain a valuable set of data that would have been previously unavailable to science teams due to funding, manpower, and resource limitations or would have taken an unreasonable amount of time to collect. Reports from a wide range of Citizen Scientist locations are helpful to assess the satellite data under different conditions. With nothing more than their eyes and an internet connection participants provide a different perspective and analysis of clouds, adding to a more complete picture of what's happening in the atmosphere in which we live.

Crecelius, Sarah↗
NASA NTRS2012

Validation of Satellite-Based Objective Overshooting Cloud-Top Detection Methods Using CloudSat Cloud Profiling Radar Observations

Two satellite infrared-based overshooting convective cloud-top (OT) detection methods have recently been described in the literature: 1) the 11-mm infrared window channel texture (IRW texture) method, which uses IRW channel brightness temperature (BT) spatial gradients and thresholds, and 2) the water vapor minus IRW BT difference (WV-IRW BTD). While both methods show good performance in published case study examples, it is important to quantitatively validate these methods relative to overshooting top events across the globe. Unfortunately, no overshooting top database currently exists that could be used in such study. This study examines National Aeronautics and Space Administration CloudSat Cloud Profiling Radar data to develop an OT detection validation database that is used to evaluate the IRW-texture and WV-IRW BTD OT detection methods. CloudSat data were manually examined over a 1.5-yr period to identify cases in which the cloud top penetrates above the tropopause height defined by a numerical weather prediction model and the surrounding cirrus anvil cloud top, producing 111 confirmed overshooting top events. When applied to Moderate Resolution Imaging Spectroradiometer (MODIS)-based Geostationary Operational Environmental Satellite-R Series (GOES-R) Advanced Baseline Imager proxy data, the IRW-texture (WV-IRW BTD) method offered a 76% (96%) probability of OT detection (POD) and 16% (81%) false-alarm ratio. Case study examples show that WV-IRW BTD.0 K identifies much of the deep convective cloud top, while the IRW-texture method focuses only on regions with a spatial scale near that of commonly observed OTs. The POD decreases by 20% when IRW-texture is applied to current geostationary imager data, highlighting the importance of imager spatial resolution for observing and detecting OT regions.

Bedka, Kristopher M.↗
NASA NTRS2017

Effects of Surface BRDF on the OMI Cloud and NO2 Retrievals: A New Approach Based on Geometry-Dependent Lambertian Equivalent Reflectivity (GLER) Derived from MODIS

The Ozone Monitoring Instrument (OMI) cloud and NO2 algorithms use a monthly gridded surface reflectivity climatology that does 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 (GLER). Implementation within the existing OMI cloud and NO2 retrieval infrastructure requires changes only to the input surface reflectivity database. GLER is calculated using a vector radiative transfer model with high spatial resolution BRDF information from MODIS over land and the Cox Munk slope distribution over ocean with a contribution from water-leaving radiance. We compare GLER and climatological LER at 466 nm, which is used in the OMI O2-O2cloud algorithm to derive effective cloud fractions. A detailed comparison of the cloud fractions and pressures derived with climatological and GLERs is carried out. GLER and corresponding retrieved cloud products are then used as input to the OMI NO2 algorithm. We find that replacing the climatological OMI-based LERs with GLERs 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.

MODIS BRDF OMI clouds NO2 GLER↗