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At least 199 records · Page 11

The Mid-Infrared Absorption Spectra of Neutral PAHs in Dense Interstellar Clouds

Polycyclic aromatic hydrocarbons (PAHs) are common throughout the universe and are expected to be present in dense interstellar clouds. In these environments, some P.4Hs may be present in the gas phase, but most should be frozen into ice mantles or adsorbed onto dust grains and their spectral features are expected to be seen in absorption. Here we extend our previous work on the infrared spectral properties of the small PAH naphthalene (C10H8) in several media to include the full mid-infrared laboratory spectra of 11 other PAHs and related aromatic species frozen in H2O ices. These include the molecules 1,2-dihydronaphthalene, anthracene, 9,1O-dihydroanthracene, phenanthrene, pyrene, benzo[e]pyrene, perylene, benzo(k)fluoranthene, pentacene, benzo[ghi]perylene, and coronene. These results demonstrate that PAHs and related molecules, as a class, show the same spectral behaviors as naphthalene when incorporated into H2O-rich matrices. When compared to the spectra of these same molecules isolated in inert matrices (e.g., Ar or N2), the absorption bands produced when they are frozen in H2O matrices are broader (factors of 3-10), show small position shifts in either direction (usually < 4/cm, always < 10/cm), and show variable changes in relative band strengths (typically factors of 1-3). There is no evidence of systematic increases or decreases in the absolute strengths of the bands of these molecules when they are incorporated in H2O matrices. In H2O-rich ices, their absorption bands are relatively insensitive to concentration over the range of 10 < H2O/PAH < 200): The absorption bands of these molecules are also insensitive to temperature over the 10 K < T < 125 K range, although the spectra can show dramatic changes as the ices are warmed through the temperature range in which amorphous H2O ice converts to its cubic and hexagonal crystalline forms (T > 125 Kj. Given the small observed band shifts cause by H2O, the current database of spectra from Ar matrix-isolated neutral PAHs and related molecules should be useful for the search for these species in dense clouds on the basis of observed absorption band positions. Furthermore, these data permit determination of column densities to better than a factor of 3 for PAHs in dense clouds. Column density determination of detected aromatics to better than a factor of 3 will, however, require good knowledge about the nature of the matrix in which the PAH is embedded and laboratory studies of relevant samples.

Bernstein, M. P.↗

A Well-Calibrated Ocean Algorithm for Special Sensor Microwave/Imager

I describe an algorithm for retrieving geophysical parameters over the ocean from special sensor microwave/imager (SSM/I) observations. This algorithm is based on a model for the brightness temperature T(sub B) of the ocean and intervening atmosphere. The retrieved parameters are the near-surface wind speed W, the columnar water vapor V, the columnar cloud liquid water L, and the line-of-sight wind W(sub LS). I restrict my analysis to ocean scenes free of rain, and when the algorithm detects rain, the retrievals are discarded. The model and algorithm are precisely calibrated using a very large in situ database containing 37,650 SSM/I overpasses of buoys and 35,108 overpasses of radiosonde sites. A detailed error analysis indicates that the T(sub B) model rms accuracy is between 0.5 and 1 K and that the rms retrieval accuracies for wind, vapor, and cloud are 0.9 m/s, 1.2 mm, and 0.025 mm, respectively. The error in specifying the cloud temperature will introduce an additional 10% error in the cloud water retrieval. The spatial resolution for these accuracies is 50 km. The systematic errors in the retrievals are smaller than the rms errors, being about 0.3 m/s, 0.6 mm, and 0.005 mm for W, V, and L, respectively. The one exception is the systematic error in wind speed of -1.0 m/s that occurs for observations within +/-20 deg of upwind. The inclusion of the line-of-sight wind W(sub LS) in the retrieval significantly reduces the error in wind speed due to wind direction variations. The wind error for upwind observations is reduced from -3.0 to -1.0 m/s. Finally, I find a small signal in the 19-GHz, horizontal polarization (h(sub pol) T(sub B) residual DeltaT(sub BH) that is related to the effective air pressure of the water vapor profile. This information may be of some use in specifying the vertical distribution of water vapor.

Wentz, Frank J.↗

Mean Estimate Distances for Galaxies with Multiple Estimates in NED-D

Numerous research topics rely on an improved cosmic distance scale (e.g., cosmology, gravitational waves) and the NASA/IPAC Extragalactic Database of Distances (NED-D) supports those efforts by tabulating multiple redshift-independent distances for 12,000 galaxies (e.g., Large Magellanic Cloud (LMC) zero-point). Six methods for securing a mean estimate distance (MED) from the data are presented (e.g., indicator and Decision Tree). All six MEDs yield surprisingly consistent distances for the cases examined, including for the key benchmark LMC and M106 galaxies. The results underscore the utility of the NED-D MEDs in bolstering the cosmic distance scale and facilitating the identification of systematic trends.

79 ASTRONOMY AND ASTROPHYSICS↗

Performance analysis of data intensive cloud systems based on data management and replication: a survey

As we delve deeper into the ‘Digital Age’, we witness an explosive growth in the volume, velocity, and variety of the data available on the Internet. For example, in 2012 about 2.5 quintillion bytes of data was created on a daily basis that originated from myriad of sources and applications including mobiledevices, sensors, individual archives, social networks, Internet of Things, enterprises, cameras, software logs, etc. Such ‘Data Explosions’ has led to one of the most challenging research issues of the current Information and Communication Technology era: how to optimally manage (e.g., store, replicated, filter, and the like) such large amount of data and identify new ways to analyze large amounts of data for unlocking information. It is clear that such large data streams cannot be managed by setting up on-premises enterprise database systems as it leads to a large up-front cost in buying and administering the hardware and software systems. Therefore, next generation data management systems must be deployed on cloud. The cloud computing paradigm provides scalable and elastic resources, such as data and services accessible over the Internet Every Cloud Service Provider must assure that data is efficiently processed and distributed in a way that does not compromise end-users’ Quality of Service (QoS) in terms of data availability, data search delay, data analysis delay, and the like. In the aforementioned perspective, data replication is used in the cloud for improving the performance (e.g., read and write delay) of applications that access data. Through replication a data intensive application or system can achieve high availability, better fault tolerance, and data recovery. In this paper, we survey data management and replication approaches (from 2007 to 2011) that are developed by both industrial and research communities. The focus of the survey is to discuss and characterize the existing approaches of data replication and management that tackle the resource usage and QoS provisioning with different levels of efficiencies. Moreover, the breakdown of both influential expressions (data replication and management) to provide different QoS attributes is deliberated. Furthermore, the performance advantages and disadvantages of data replication and management approaches in the cloud computing environments are analyzed. Open issues and future challenges related to data consistency, scalability, load balancing, processing and placement are also reported.

Malik, Saif Ur Rehman↗

The Effect of Aerosols and Clouds on the Retrieval of Infrared Sea Surface Temperatures

Comparisons are performed between spatially averaged sea surface temperatures (ASST2) as derived from the second Along-Track Scanning Radiometer (ATSR-2) on board the second European Remote Sensing Satellite (ERS-2) and the NOAA-NASA Advanced Very High Resolution Radiometer (AVHRR) Oceans Pathfinder dataset (MPFSST). Difference maps, MPFSST 2 ASST2, along with the application of a simple statistical regression model to aerosol and cloud data from the Total Ozone Mapping Spectrometer ( TOMS), are used to examine the impact of possible aerosol and cloud contamination. Differences varied regionally, but the largest biases were seen off western Africa. Nighttime and daytime differences off western Africa were reduced from -0.5degrees to -0.2degreesC and from -0.1degrees to 0degreesC, respectively. Significant cloud flagging, based on the model, occurred in the Indian Ocean, the equatorial Pacific, and in the vicinity of the Gulf Stream. Comparisons of the MPFSST and the ASST2 with in situ data from the 2002 version of the World Oceanic Database (WOD02) off western Africa show larger mean differences for the MPFSST. The smallest mean differences occurred for nighttime ASST2 - WOD02 with a value of 0.0degrees +/- 0.4degreesC.

clouds↗

CASTLE: Conflict Analysis Strategy Testing Laboratory Environment v.1.0.0

SAND2024-01743O The Conflict Analysis Strategy Testing Laboratory Environment (CASTLE) is a software framework that enables and simplifies building a novel, turn-based strategy game in which it can define its own rules, maps, pieces, and interactions. The software is for novice to experienced programmers with some knowledge of Unity3D, a tool used in game production. CASTLE includes a library of common game mechanics used for strategic wargames and traditional board games, such as cards, tokens, dice, and grid maps. It follows design principles popularized by the video game industry and uses singletons for managing portions of the code. CASTLE builds on Unity's component-based design and can respond to engine events during execution. Among the numerous user-friendly features: Build games quickly and cost-effectively Network in real-time and apply data to new games developed on the framework Host multiple participants online Connect rule- or machine learning-based agents to a CASTLE game to serve as opponents or to simulate games Collect data collection from players and in-game behaviors Create a survey to gather demographics or opinions from players Store data locally or save it to an external database through Representational State Transfer (REST) functions CASTLE, which was prototyped using Microsoft Azure, is also designed for easily distributing online games using popular cloud services. The multiplayer functionality includes an agent interface, allowing developers to construct AI players that can substitute for humans in any of the games. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy’s National Nuclear Security Administration under contract DE-NA0003525.

Fabian, Nathan↗

PERIODIC AND APERIODIC VARIABILITY IN THE MOLECULAR CLOUD ρ OPHIUCHUS

Presented are the results of a near-IR photometric survey of 1678 stars in the direction of the ρ Ophiuchus (ρ Oph) star forming region using data from the 2MASS Calibration Database. For each target in this sample, up to 1584 individual J-, H-, and K{sub s} -band photometric measurements with a cadence of ∼1 day are obtained over three observing seasons spanning ∼2.5 yr; it is the most intensive survey of stars in this region to date. This survey identifies 101 variable stars with ΔK{sub s} -band amplitudes from 0.044 to 2.31 mag and Δ(J – K{sub s} ) color amplitudes ranging from 0.053 to 1.47 mag. Of the 72 young ρ Oph star cluster members included in this survey, 79% are variable; in addition, 22 variable stars are identified as candidate members. Based on the temporal behavior of the K{sub s} time-series, the variability is distinguished as either periodic, long time-scale or irregular. This temporal behavior coupled with the behavior of stellar colors is used to assign a dominant variability mechanism. A new period-searching algorithm finds periodic signals in 32 variable stars with periods between 0.49 to 92 days. The chief mechanism driving the periodic variability for 18 stars is rotational modulation of cool starspots while 3 periodically vary due to accretion-induced hot spots. The time-series for six variable stars contains discrete periodic ''eclipse-like'' features with periods ranging from 3 to 8 days. These features may be asymmetries in the circumstellar disk, potentially sustained or driven by a proto-planet at or near the co-rotation radius. Aperiodic, long time-scale variations in stellar flux are identified in the time-series for 31 variable stars with time-scales ranging from 64 to 790 days. The chief mechanism driving long time-scale variability is variable extinction or mass accretion rates. The majority of the variable stars (40) exhibit sporadic, aperiodic variability over no discernable time-scale. No chief variability mechanism could be identified for these variable stars.

79 ASTRONOMY AND ASTROPHYSICS↗

Disk and circumsolar radiances in the presence of ice clouds

The impact of ice clouds on solar disk and circumsolar radiances is investigated using a Monte Carlo radiative transfer model. The monochromatic direct and diffuse radiances are simulated at angles of 0 to 8° from the center of the sun. Input data for the model are derived from measurements conducted during the 2010 Small Particles in Cirrus (SPARTICUS) campaign together with state-of-the-art databases of optical properties of ice crystals and aerosols. For selected cases, the simulated radiances are compared with ground-based radiance measurements obtained by the Sun and Aureole Measurements (SAM) instrument. First, the sensitivity of the radiances to the ice cloud properties and aerosol optical thickness is addressed. The angular dependence of the disk and circumsolar radiances is found to be most sensitive to assumptions about ice crystal roughness (or, more generally, non-ideal features of ice crystals) and size distribution, with ice crystal habit playing a somewhat smaller role. Second, in comparisons with SAM data, the ice cloud optical thickness is adjusted for each case so that the simulated radiances agree closely (i.e., within 3 %) with the measured disk radiances. Circumsolar radiances at angles larger than ≈ 3° are systematically underestimated when assuming smooth ice crystals, whereas the agreement with the measurements is better when rough ice crystals are assumed. In conclusion, our results suggest that it may well be possible to infer the particle roughness directly from ground-based SAM measurements. In addition, the results show the necessity of correcting the ground-based measurements of direct radiation for the presence of diffuse radiation in the instrument's field of view, in particular in the presence of ice clouds.

54 ENVIRONMENTAL SCIENCES↗

Progress on the FabrIc for Frontier Experiments project at Fermilab

The FabrIc for Frontier Experiments (FIFE) project is an ambitious, major-impact initiative within the Fermilab Scientific Computing Division designed to lead the computing model for Fermilab experiments. FIFE is a collaborative effort between experimenters and computing professionals to design and develop integrated computing models for experiments of varying needs and infrastructure. The major focus of the FIFE project is the development, deployment, and integration of Open Science Grid solutions for high throughput computing, data management, database access and collaboration within experiment. To accomplish this goal, FIFE has developed workflows that utilize Open Science Grid sites along with dedicated and commercial cloud resources. The FIFE project has made significant progress integrating into experiment computing operations several services including new job submission services, software and reference data distribution through CVMFS repositories, flexible data transfer client, and access to opportunistic resources on the Open Science Grid. Hence, the progress with current experiments and plans for expansion with additional projects will be discussed. FIFE has taken a leading role in the definition of the computing model for Fermilab experiments, aided in the design of computing for experiments beyond Fermilab, and will continue to define the future direction of high throughput computing for future physics experiments worldwide

97 MATHEMATICS AND COMPUTING↗

Site Scientist for the North Slope of Alaska Site

Under this grant our team contributed scientific support to the Department of Energy Atmospheric Radiation Program’s (DOE-ARM) Infrastructure team to maintain high quality research data at the DOE-ARM North Slope of Alaska with special emphasis on the radars. Under our guidance two major field campaigns focusing on mixed-phase Arctic clouds were conducted that greatly increased the community’s understanding of the many processes working together to control the evolution of single-layer cloud mixed-phase clouds. A series of modeling and observational studies revealed that the longevity of the radiatively important liquid phase is strongly dependent on how the ice phase develops in mixed-phase clouds. A new ice microphysics parameterization was developed to capture better the natural evolution of ice particle growth in evolving environments. An ice particle scattering database was developed for all ARM radar frequencies. This database was used in a radar simulator (Doppler spectrum and polarimetric variables) to aid in the interpretation of the advanced ARM radars. At the conclusion of this project our team was poised to develop a complete radar simulator consistent with the new microphysical parameterization, taking advantage of parameterization’s advanced characterization of the ice shape and ice density.

47 OTHER INSTRUMENTATION↗

A serach for 'failed clusters' of galaxies

We describe a search for a new type of object - large clouds of hot gas with no visible galaxies - which we call failed clusters of galaxies. We calculate the expected X-ray luminosity, temperature, and angular diameter of such objects as a function of total cloud mass and convert the results to expected X-ray fluxes from failed clusters at different redshifts. Using the Einstein Imaging Proportional Counter (IPC) database, we establish a strategy to search for candidate failed clusters. From this initial screening of 1435 IPC fields, 17 candidates are selected for more detailed analysis, which indicates that 10 of these are very probably extended X-ray sources. Optical follow-up on the 10 prime candidates finds eight clusters of galaxies (including six reproted for the first time in this paper), one stellar identification, and one without an obvious optical counterpart (the candidate with the weakest evidence for X-ray extent). Investigation of several candidates with less evidence for X-ray extent yields two additional new clusters of galaxies. A conservative comparison of our results with the Einstein Extended Medium Sensitivity Survey demonstrates that failed clusters are a relatively unimportant contributor to the mass density of the universe. Our inability to find failed clusters is consistent with the hierarchical clustering scenario for the formation of galaxies and clusters.

Tucker, W. H.↗

Determination of Storm Flashing/Non-Flashing Condition From Convective and Environmental Observations

A simple and fundamental problem in cloud electrification is whether or not a cloud can be determined to be producing lightning or not producing lightning, based solely on knowledge of its microphysical (and perhaps environmental) state. A merged database of TRMM radar, microwave and lightning observations and NCEP reanalysis environmental parameters is used to answer this question, for the tropics. The formal skill of traditional, univariate rule-based approaches (e.g., 35 dBZ occurrence at 6 km altitude) is quantified (via the probability of detection (POD), false alarm rate (FAR) and critical skill index (CSI)). Under indiscriminate application to the tropics, peak rule-based CSI for categorization of flashing storms is approximately 50%, with peak POD approximately 67% and minimum FAR approximately 33%, with peak CSI found for radar reflectivity-based parameters at 7-7.5 km altitude (near -15C). Separation of land and ocean domains yields approximately 5-10% gains in CSI over land. Conventional multivariate categorization techniques (discriminant analysis) are then applied, and less conventional (neural network) categorization techniques are also discussed.

Boccippio, Dennis J.↗

Recent Advancements in Lightning Jump Algorithm Work

In the past year, the primary objectives were to show the usefulness of total lightning as compared to traditional cloud-to-ground (CG) networks, test the lightning jump algorithm configurations in other regions of the country, increase the number of thunderstorms within our thunderstorm database, and to pinpoint environments that could prove difficult for any lightning jump configuration. A total of 561 thunderstorms have been examined in the past year (409 non-severe, 152 severe) from four regions of the country (North Alabama, Washington D.C., High Plains of CO/KS, and Oklahoma). Results continue to indicate that the 2 lightning jump algorithm configuration holds the most promise in terms of prospective operational lightning jump algorithms, with a probability of detection (POD) at 81%, a false alarm rate (FAR) of 45%, a critical success index (CSI) of 49% and a Heidke Skill Score (HSS) of 0.66. The second best performing algorithm configuration was the Threshold 4 algorithm, which had a POD of 72%, FAR of 51%, a CSI of 41% and an HSS of 0.58. Because a more complex algorithm configuration shows the most promise in terms of prospective operational lightning jump algorithms, accurate thunderstorm cell tracking work must be undertaken to track lightning trends on an individual thunderstorm basis over time. While these numbers for the 2 configuration are impressive, the algorithm does have its weaknesses. Specifically, low-topped and tropical cyclone thunderstorm environments are present issues for the 2 lightning jump algorithm, because of the suppressed vertical depth impact on overall flash counts (i.e., a relative dearth in lightning). For example, in a sample of 120 thunderstorms from northern Alabama that contained 72 missed events by the 2 algorithm 36% of the misses were associated with these two environments (17 storms).

Schultz, Christopher J.↗

Quantifying the Relative Impact of Model Microphysics Parameterizations and Scattering Models in Simulating Synthetic Radar and Microwave Radiometer Observations

Output from numerical weather models is often used to simulate observations from remote sensing instruments, for purposes ranging from data assimilation, synthetic retrievals of geophysical quantities, and optimization of observing systems. However, when hydrometeors are present, the level of detail provided by the weather model is generally insufficient to fully constrain the input to the radiative transfer model (RTM), and further assumptions must be made by the RTM user in order to produce synthetic observations. Using a hierarchy of models including cloud-resolving, double-moment, bin microphysical, and ice-habit predicting models, along with scattering properties from the OpenSSP, Atmospheric Radiative Transfer Simulator (ARTS) databases, as well as relatively simple geometries (e.g., cylindrical plates and columns), we demonstrate the spread in synthetic observation output and the extent to which it is reduced when microphysics is more strongly constrained by the model. As an intermediate step, an error budget for the RTM simulations was derived and from that we developed and will describe best practices for observation simulation (e.g., optimal number of hydrometeor size bins, truncation of the particle size distribution, angular resolution of scattering phase function). Some statistical comparisons with observations will also be presented.

Munchak, S. Joseph↗

Radiological data consolidation and 3D modeling of a building - 15473

A portion of a building at an industrial facility that conducted monazite sands-processing operations in the 1950's under contract to the Atomic Energy Commission (AEC) became contaminated. Subsequently the U.S. Department of Energy designated the facility for remedial action under the Formerly Used Sites Remedial Action Program (FUSRAP). Remedial investigation, remedial actions and post-remediation surveys have been conducted in portions of the building. Radiological data for the interior of the building were compiled, evaluated and presented in a three dimensional (3-D) model (the model) created by AMEC Foster Wheeler in order to identify areas that meet the Record of Decision (ROD) cleanup criteria, and identity areas that may require remedial action or may require additional investigation due to data gaps. The data from different phases of investigation and remediation cover different portions of the building and in some cases overlap. In addition, the data were collected over a period of more than ten years, for different objectives, and thus the instruments and methods for establishing efficiency were not necessarily consistent. The data consolidation process included determining the relative quality of data points to include in the model and the development of rationale associated with assigning a quality level (i.e. ranking) to each data point. The rationale for ranking data quality included, as the primary determining factors, chronological order of the data (most recent was ranked as more reliable), certainty of the sample locations within the building, and analytical data quality. A 3-D model of the building was created using a laser point cloud scan which was then converted into a 3-D design model. Sample locations were then entered into the model and linked with the analytical database to allow display of the radiological results in the model. The visual model allows both strategic and tactical decisions to be made, depending on the level of detail examined. The evaluation process allowed maximum use of the historical data set, rather than requiring older data to be disregarded, and provided at a minimum a qualitative sense of data quality/confidence in the data. The (authors)process also highlights the importance of collecting high quality data from the very beginning with a consistent locational coordinate system, and the need for a good visualization model in order to assess contaminant locations during remedial action or post-remediation surveys.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

Design and implementation of wearable devices in machine tools monitoring system - 279

The world's fourth industrial revolution has finally opened after the term Industry 4.0 was proposed by Germany at the Hannover Industrial Fair in 2011, which combined industrial production with an unmanned plant to perform automated production. With the rise of Internet of Things (IoT), cloud computing, and wearing computerized devices has brought more convenience to mankind with the immediate accessibility of the Internet and technology. For example, the development of mobile devices and network technology has inspired the rapid development of wearable devices on mobile devices. Thus, to enhance the current prospects of Taiwan's unmanned machinery factory's monitoring and maintenance capabilities, this paper studies the use of Google glass Machine Tools Monitoring system, GMTM system, to be implemented in Taiwan's machinery factories. GMTM system, via the Internet, monitors sensor tools to collect tool work data to be transferred to cloud computing for analysis, processing and show the actual working conditions of each machine tool. Furthermore, the proposed system uses the monitoring data in the database to inform the factory supervisors the working status of each machine to determine whether there is a need for machine tool maintenance. This system combines real-time monitoring of material with the presentation of Google Glass wearable devices and iBeacon interior space positioning technology. GMTM system can improve the quality of machine tool production and productivity as well as enhance Taiwan's industrial competitiveness. (authors)

47 OTHER INSTRUMENTATION↗

Classification of Cloud Particle Imagery from Aircraft Platforms Using Convolutional Neural Networks

Abstract A vast amount of ice crystal imagery exists from a variety of field campaign initiatives that can be utilized for cloud microphysical research. Here, nine convolutional neural networks are used to classify particles into nine regimes on over 10 million images from the Cloud Particle Imager probe, including liquid and frozen states and particles with evidence of riming. A transfer learning approach proves that the Visual Geometry Group (VGG-16) network best classifies imagery with respect to multiple performance metrics. Classification accuracies on a validation dataset reach 97% and surpass traditional automated classification. Furthermore, after initial model training and preprocessing, 10 000 images can be classified in approximately 35 s using 20 central processing unit cores and two graphics processing units, which reaches real-time classification capabilities. Statistical analysis of the classified images indicates that a large portion (57%) of the dataset is unusable, meaning the images are too blurry or represent indistinguishable small fragments. In addition, 19% of the dataset is classified as liquid drops. After removal of fragments, blurry images, and cloud drops, 38% of the remaining ice particles are largely intersecting the image border (≥10% cutoff) and therefore are considered unusable because of the inability to properly classify and dimensionalize. After this filtering, an unprecedented database of 1 560 364 images across all campaigns is available for parameter extraction and bulk statistics on specific particle types in a wide variety of storm systems, which can act to improve the current state of microphysical parameterizations.

54 ENVIRONMENTAL SCIENCES↗

The National Climate Database (NCDB): An Unbiased 100-Year Dataset for PV Modeling

In this study, we develop a statistical technique to downscale the future projection of solar irradiance for photovoltaics (PV) energy-related applications. A set of Regional Climate Model (RCM)-based projections obtained from the North American Coordinated Regional Climate Downscaling Experiment (NA-CORDEX) are used as inputs to statistical methods to generate high-resolution global horizontal irradiance (GHI) over the contiguous United States (CONUS). The main steps of the statistical downscaling method include (1) regridding RCM output (0.22 degree and daily resolutions) to handle the modeled-observed data sets on a common grid, (2) correcting bias of RCM GHI using satellite-derived observation, and (3) implementing temporal and spatial downscaling to generate GHI at 8-km and hourly resolution. Basically, complex physical processes and interactions between solar radiation and various atmospheric constituents lead solar irradiance to be highly variable and uncertain. Underrepresentation of clouds from the RCM parameterizations is the main source of error and uncertainty in modeling solar irradiance. Thus, we adapt and use the high-quality satellite-derived data from the National Solar Radiation Database (NSRDB) to analyze the bias and error of RCM GHI as well as estimate the statistical parameters for spatial and temporal downscaling. This presentation will summarize the comprehensive analysis conducted to produce and assess the results under two climate scenarios (RCP4.5 and RCP8.5). We will also present a detailed validation demonstrating the strengths of the downscaling method, a summary of the 100-year dataset from 2001-2100, and future extension of this research.

bias correction↗