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DOE OSTI2020

Improvements to the Modeling of the TREAT Reactor and Experiments

This paper summarizes the latest improvements and lessons learned from the modeling and simulation of the transient test reactor at Idaho National Laboratory using the MAM- MOTH reactor physics application. MAMMOTH is a MOOSE-based, Finite Element Method application that specializes in the analysis of the spatial dynamics behavior of nuclear reactors. Since early 2018 several transient tests have been conducted at TREAT, thus providing the opportunity to apply and benchmark modern modeling and simulation tools. MAMMOTH was used to provide predictions of the power coupling factor between the core and the experiment for various experiments. Even though the power coupling factor predictions agree very well with the experimental data, within the bounds of the experimental uncertainty, one shortcoming was the underprediction of the total energy deposited in the core and in the experiment. Determination of the sources for this discrepancy are ongoing, but several key problems have been identified and resolved, thus providing valuable insights for future research. This paper discusses several of these lessons learned. First, the heat capacity data for the TREAT fuel has some significant problems due to limitations of the measurement techniques used circa 1960s. The sensitivity of the peak power and the total energy deposition to various representations of the heat capacity is approximately 5%. Second, the effects of the biological shield and thermal column on the modeling of the core are non-negligible, since they affect the mean generation time and the effective reflection of neutrons back into the core, which is suspected to be important during the core heat up. Matching the reactor period resolves the fact that the reduced spatial domain used in the MAMMOTH model underpredicts the mean generation time. The neutron reflection from these regions is marginally improved with the use of an albedo boundary condition. Third, modeling of the control rod movement with a multi-scheme method is introduced and its current limitations are exposed. Fourth, we explore the effects of using a homogenized model with Superhomogenization equivalence and how that differs from fully heterogeneous simulations. Finally, the energy condensation effects for this graphite core are significant. Solutions with 10 and 26 energy groups show the benefits of using a finer coarse group structure.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

DOE OSTI2021

PV Fleet Performance Data Initiative: Performance Index-Based Analysis

In this analysis, we report on 250 PV systems throughout the US, comprising 157 MWdc of system capacity and over 10,000 monthly PI values based on high-frequency (subhourly) energy data and satellite-based resource data. The distribution of PI values is analyzed, and multiple causes of underperformance are assessed, including first-year startup issues, snowfall and inverter downtime. An initial distribution of raw monthly PI values was collected with mean measured / modeled performance of PI = 0.935. After correcting for the three identifiable loss factors mentioned above, an average monthly performance of PI = 0.994 was obtained, with a distribution closely following a Gumbel Extreme Value distribution. In particular, inverter availability was found to contribute a system energy loss of 2.3% on average, except in the first six months of operation when availability losses are closer to 8%. Other startup issues beyond inverter downtime such as partial string outage contributed an additional 5% underperformance in the first year of operation across the fleet. Winter performance was also found to be 5%-10% below summer performance on average, likely due to snowfall. A simple linear relationship was found between snow loss and monthly snowfall accumulation in cm, indicating between 6% - 40% loss in months with nonzero snowfall, depending on climate.

14 SOLAR ENERGY↗

DOE OSTI2022

Artificial intelligence inferred microstructural properties from voltage–capacity curves

Abstract The quantification of microstructural properties to optimize battery design and performance, to maintain product quality, or to track the degradation of LIBs remains expensive and slow when performed through currently used characterization approaches. In this paper, a convolution neural network-based deep learning approach (CNN) is reported to infer electrode microstructural properties from the inexpensive, easy to measure cell voltage versus capacity data. The developed framework combines two CNN models to balance the bias and variance of the overall predictions. As an example application, the method was demonstrated against porous electrode theory-generated voltage versus capacity plots. For the graphite|LiMn $$_2$$ 2 O $$_4$$ 4 chemistry, each voltage curve was parameterized as a function of the cathode microstructure tortuosity and area density, delivering CNN predictions of Bruggeman’s exponent and shape factor with 0.97 $$R^2$$ R 2 score within 2 s each, enabling to distinguish between different types of particle morphologies, anisotropies, and particle alignments. The developed neural network model can readily accelerate the processing-properties-performance and degradation characteristics of the existing and emerging LIB chemistries.

25 ENERGY STORAGE↗

DOE OSTI2022

Viewing convection as a solar farm phenomenon broadens modern power predictions for solar photovoltaics

We report heat mitigation for large-scale solar photovoltaic (PV) arrays is crucial to extend lifetime and energy harvesting capacity. PV module temperature is dependent on site-specific farm geometry, yet common predictions consider panel-scale and environmental factors only. Here, we characterize convective cooling in diverse PV array designs, capturing combined effects of spatial and atmospheric variation on panel temperature and production. Parameters, including row spacing, panel inclination, module height, and wind velocity, are explored through wind tunnel experiments, high-resolution numerical simulations, and operating field data. A length scale based on fractal lacunarity encapsulates all aspects of arrangement (angle, height, etc.) in a single value. When applied to the Reynolds number Re within the canonical Nusselt number heat transfer correlation, lacunarity reveals a relationship between convection and farm-specific geometry. This correlation can be applied to existing and forthcoming array designs to optimize convective cooling, ultimately increasing production and PV cell life.

14 SOLAR ENERGY↗

NASA NTRS1997

Design and Operational Evaluation of the Traffic Management Advisor at the Ft. Worth Air Route Traffic Control Center

NASA and the FAA have designed and developed and an automation tool known as the Traffic Management Advisor (TMA). The system was operationally evaluated at the Ft. Worth Air Route Traffic Control Center (ARTCC). The TMA is a time-based strategic planning tool that provides Traffic Management Coordinators and En Route Air Traffic Controllers the ability to efficiently optimize the capacity of a demand impacted airport. The TMA consists of trajectory prediction, constraint-based runway scheduling, traffic flow visualization and controllers advisories. The TMA was used and operationally evaluated for forty-one rush traffic periods during a one month period in the Summer of 1996. The evaluations included all shifts of air traffic operations as well as periods of inclement weather. Performance data was collected for engineering and human factor analysis and compared with similar operations without the TMA. The engineering data indicates that the operations with the TMA show a one to two minute per aircraft delay reduction during rush periods. The human factor data indicate a perceived reduction in en route controller workload as well as an increase in job satisfaction. Upon completion of the evaluation, the TMA has become part of the normal operations at the Ft. Worth ARTCC.

Swenson, Harry N.↗

DOE OSTI2026

Machine learning based prediction of airflow maldistribution in air-to-refrigerant heat exchangers

Flow maldistribution is a common challenge in heat exchanger (HX) design and particularly important for air-to-refrigerant geometries where capacity losses can approach 65%. This has a major impact on central air conditioning systems, as compact duct design motivates the use of A-type HXs which are known to be affected by airflow maldistribution. Because velocity profiles are difficult to predict, components are often oversized leading to increased material cost, system footprint, and refrigerant charge. Several studies detail airflow maldistribution for individual HXs and packages, but findings cannot always be extrapolated to new designs. In this work, a machine learning (ML) based flow profile prediction framework is developed and applied to two common package configurations: (i) A-type and (ii) U-type HXs, across a broad range of HX geometries and flow rates. Porous media CFD simulations are validated against independent data for both package types as well as comprehensive in house measurements for a finless geometry with shape optimized non-round tubes, which validates the framework for new heat transfer surfaces. The ML models are trained on the porous media CFD simulations, predicting volumetric flow rate (VFR) within 1.1% and 1.9% with maximum relative L 2 norm errors of 0.48 and 0.65, respectively, while also delivering 10 5 speed up factor compared to full porous media CFD. HX level simulations show an up to 9% reduction in heat transfer from flow maldistribution, with greater losses occurring at smaller half apex angles. This framework enables rapid and highly accurate prediction of airflow maldistribution induced capacity degradation.

42 ENGINEERING↗

DOE OSTI2024

An experimentally validated electro-thermal EV battery pack model incorporating cycle-life aging and cell-to-cell variations

Lithium-ion batteries are used in a wide variety of applications. To meet the power and energy demands of these applications battery packs are composed of hundreds to thousands of cells. The electrical and thermal interactions between cells introduce additional complexity in the pack dynamics. To capture these effects, a battery pack model composed of 192 cells based on a first-generation (2012) Nissan Leaf battery pack is developed in MATLAB/Simulink/Simscape. Here, with this model, we simulate the electrical dynamics (using a first-order equivalent-circuit model), the thermal dynamics (using a first-order lumped-parameter thermal model), and the aging dynamics (using a semi-empirical severity factor-based model) of every cell in the pack and we also create a pack thermal model that explicitly captures the heat exchange between the modules, and the cells contained within, during operation. The models are calibrated and validated, both at the cell and pack level, with experimental data. Two different case studies of this pack model are investigated. In the first case study, an initial, normally-distributed, cell-to-cell capacity variation is introduced and its effect on the pack voltage and module temperatures is studied. In the second case study, we deliberately insert cells with lower than nominal capacity into the pack and we investigate how this type of initial cell-to-cell capacity variation affects the pack’s ability to deliver energy over time. Finally, we also study how parallel-connected cells can reduce the effects of cell-to-cell variations at the expense of increased aging of the pack overall.

25 ENERGY STORAGE↗

NASA NTRS1976

Comparative performance of solar thermal power generation concepts

A performance comparison is made between the central receiver system (power tower) and a distributed system using either dishes or troughs and lines to transport fluids to the power station. These systems were analyzed at a rated capacity of 30 MW of thermal energy delivered in the form of superheated steam at 538 C (1000 F) and 68 atm (1000 psia), using consistent weather data, collector surface waviness, pointing error, and electric conversion efficiency. The comparisons include technical considerations for component requirements, land utilization, and annual thermal energy collection rates. The relative merits of different representative systems are dependent upon the overall conversion as expressed in the form of performance factors in this paper. These factors are essentially indices of the relative performance effectiveness for different concepts based upon unit collector area. These performance factors enable further economic tradeoff studies of systems to be made by comparing them with projected production costs for these systems.

Wen, L.↗

DOE OSTI2023

Feasibility Analysis for the Use of Retrofitted Air-Conditioners Using Thermal Energy Storage (TES) for High Ambient Temperature (HAT) Countries

In high ambient temperature (HAT) countries, summer temperatures exceed 35℃, degrading the performance of air-conditioning systems and straining power grids. In this paper, a feasibility analysis was conducted to investigate potential savings during the peak using latent Thermal Energy Storage (TES) at near room phase-change temperatures, replacing condensers, thus, minimizing temperature lifts. Weather data, building loads, and baseline air-conditioning systems data were gathered for Dubai. A transient vapor-compression model in Modelica was used to compare the COP, total power input and cooling capacity of the air-conditioner at peak hours when ambient temperatures range between 35 – 45 ⁰C versus the TES-Phase-Change Material (PCM) melting temperatures from 22 – 28⁰C. The results indicate that the TES-PCM can enhance the system COP at the peak by a factor 1.4 and 2 for during for outdoor temperatures of 35 – 40⁰C, and 40 – 45⁰C, respectively. Lower melting temperature PCMs were able to reduce the required power input by 30-50%, with more savings occurring at higher temperature days. On the other hand, higher temperature PCMs enhancements were minimal especially at outdoor ambient temperatures ranging between 35 – 40⁰C. Improvements to the cooling capacity range from 8 – 18 % for the outdoor temperature range of 35 – 45 ⁰C. An economic analysis was conducted to find the potential saving in utility costs for 30%, 60%, and 90% of the space cooling demands of Dubai, and find the trade-off points between utility savings and cost of PCM-TES implementation. If the peak loads are to be shifted by 6 hours daily, the percentage utility savings for the city is 18%. Using estimated costs of the PCM-TES, ranging from $200-500/kWh, the daily load shifting hours were estimated to range from 4 hours at the lowest cost systems to 2.5 hours at the highest costs.

25 ENERGY STORAGE↗

DOE OSTI2024

Voltage and temperature effects on low cobalt lithium-ion battery cathode degradation

Degradation of low cobalt lithium-ion cathodes was tested using a full factorial combination of upper cut-off voltage (4.0 V and 4.3 V vs. Li/Li + ) and operating temperature (25 °C and 60 °C). Half-cell batteries were analyzed with electrochemical and microstructural characterization methods. Electrochemical performance was assessed with galvanostatic cycling, cyclic voltammetry (CV), and electrochemical impedance spectroscopy (EIS) supported by distribution of relaxation times (DRT) analysis. Electrode microstructure was characterized with scanning electron microscopy (SEM), X-ray diffraction (XRD), and X-ray absorption near edge structure (XANES) imaging. Higher cut-off voltage cycling shows presence of NiO x formation, a low diffusivity rock-salt phase, in both CV and XRD data. XRD patterns confirmed that the rock-salt phase was beginning to form at the low cut-off voltage at high temperature, but in much lower intensity than at the high cut-off voltage. Higher temperature accelerates degradation processes at both voltages. Degradation factors at high temperature include NiO x formation, cathode material dissolution, and electrolyte decomposition. SEM analysis suggests that supporting phases may isolate and disconnect active material particles reducing capacity retention and battery life cycle. DRT analysis and XANES imaging show that both high temperature samples revealed a NiO x phase based on an increased diffusive impedance and a visible shift in the XANES spectra. The low cut-off voltage, high temperature sample showed a split peak and shift to lower energies indicating early formation of the NiO x phase. The diffusive impedance, which hinders intercalation and deintercalation, is driven by the formation of the NiO x phase. While primarily driven by cut-off voltage, elevated temperature also contributes to this degradation mechanism.

electrochemical impedance spectroscopy↗

DOE OSTI2025

Reevaluation of Radiation-Protection Standards for Workers and the Public Based on Current Scientific Evidence

President Trump’s recent executive orders to “Usher in a Nuclear Renaissance,” coupled with the global pledge to triple nuclear energy capacity by 2050, underscore nuclear energy’s importance to national security and economic prosperity. This renewed interest has prompted efforts to spur nuclear-energy deployment, including assessing factors impeding it. One issue that has previously been identified as adding to the cost of nuclear energy is excessively conservative requirements, including those related to radiation protection. This technical review, therefore, examines current radiation-protection standards that were established decades ago when more limited data were available and nuclear-energy expansion was not a national priority. The review focuses on scientific evidence regarding the health effects of ionizing radiation at annual doses of 10,000 mrem or less. The review evaluates epidemiological studies, radiobiological research, and positions of relevant professional organizations to assess whether such doses result in discernable or observable increases in negative health outcomes. The review also surveys the literature related to economic and practical implications of current radiation-protection standards and practices. Based on this assessment, we propose maintaining an annual occupational whole-body dose limit of 5,000 mrem/yr and eliminating all “as low as reasonably achievable” requirements and limits below this threshold. This change could potentially reduce radiation-protection costs by millions of dollars annually for each reactor, as well as decrease the overall costs and correct misconceptions about the risks associated with all nuclear technologies. The evidence further supports future consideration of a 10,000 mrem/yr limit that would maintain appropriate safety margins while further reducing protection costs. Similarly, given the data and that the average annual radiation dose per person in the U.S. is 620 mrem, we believe the public dose limits of 100 mrem/yr are unnecessarily restrictive; increasing to 500 mrem/yr would maintain substantial safety margins—a factor of 10 below the occupational limit—while reducing regulatory burdens and associated bureaucracy. While we acknowledge ongoing scientific debate and encourage continued research on the health effects of ionizing radiation, our review indicates current frameworks are overly conservative. These overly stringent limits not only impose unnecessary economic burdens without corresponding health benefits but also divert safety focus and resources from more important considerations. Although this study was motivated by nuclear-power considerations, reforms to radiation-protection requirements have significant positive implications for other areas, such as nuclear medical applications, environmental remediation, nuclear-waste management and disposal, and industrial applications of nuclear technologies.

61 RADIATION PROTECTION AND DOSIMETRY↗

NASA NTRS1974

Thermodynamic properties derived from the free volume model of liquids

An equation of state and expressions for the isothermal compressibility, thermal expansion coefficient, heat capacity, and entropy of liquids have been derived from the free volume model partition function suggested by Turnbull. The simple definition of the free volume is used, and it is assumed that the specific volume is directly related to the cube of the intermolecular separation by a proportionality factor which is found to be a function of temperature and pressure as well as specific volume. When values of the proportionality factor are calculated from experimental data for real liquids, it is found to be approximately constant over ranges of temperature and pressure which correspond to the dense liquid phase. This result provides a single-parameter method for calculating dense liquid thermodynamic properties and is consistent with the fact that the free volume model is designed to describe liquids near the solidification point.

Miller, R. I.↗

DOE OSTI2020

Cesium Removal Performance Comparisons of Crystalline Silicotitanate Media Batches with Savannah River Site Waste Simulant

The Tank Closure Cesium Removal (TCCR) system uses ion exchange columns filled with Crystalline Silicotitanate (CST) media to process radioactive waste solutions for the removal of Cs137. TCCR currently focuses on dissolving Savannah River Site (SRS) Tank 10H waste (primarily sodium salt cake solids) within the tank followed by at-tank ion exchange column treatment. Plans are underway to prepare and install a second TCCR unit at SRS. Capacity and particle size differences exist between archived (IE-911) and more recently-prepared CST media batches (9120- B and 9140-B). Side-by-side comparison testing was performed to evaluate the cesium removal performance of each batch to aid in selecting the preferred CST batch and media characteristics to load into the second TCCR unit. Batch contact equilibrium and flow-through column tests have been conducted with three CST batches using an SRS Average Simulant. Simulant batch contact equilibrium cesium loading results for the three CST batches (including two lots of one batch) are provided in Table ES-1. The 35 °C data indicates that the archived IE-911 batch has a higher cesium capacity than recently-prepared CST media and that the minor TCCR CST 9120-B media lot (2099000035) has similar cesium removal performance to the major TCCR lot (2099000034). Tests conducted at 25 ºC for the archived IE-911 CST batch indicated lower cesium removal performance with this simulant batch than was observed recently with a different SRS Average Simulant batch. A dilution factor (DF) is typically utilized when modeling engineered CST media cesium loading performance to account for mass contributions from the binder material. In cases where CST performance is lower than expected, this factor includes corrections for the binder and for low performance. The ZAM (Zheng, Anthony, and Miller) Isotherm Model DF values are provided in Table ES-1 for each simulant batch contact result. DF values near 0.5 were determined for the 9120-B and 9140-B CST batch contact tests while DF values near 0.6 (20% higher) were determined for the tests with IE-911. These dilution factors are lower than recently observed with a different SRS Average Simulant batch (9140-B DF = 0.68; IE-911 DF = 1.0). Based on these results, it appears that some component in the simulant solution used for equilibrium testing may have resulted in reduced cesium loading on the CST media.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

DOE OSTI2020

Benchmarking Utility-Scale PV Operational Expenses and Project Lifetimes: Results from a Survey of U.S. Solar Industry Professionals

This paper draws on a survey of solar industry professionals and other sources to clarify trends in the expected useful life and operational expenditure (OpEx) of utility-scale photovoltaic (PV) plants in the United States. Solar project developers, sponsors, long-term owners, and consultants have increased project-life assumptions over time, from an average of ~21.5 years in 2007 to ~32.5 years in 2019. Current assumptions range from 25 years to more than 35 years depending on the organization; 17 out of 19 organizations surveyed or reviewed use 30 years or more. Levelized, lifetime OpEx estimates have declined from an average of ~$\$$35/kW DC -yr for projects built in 2007 to an average of ~$\$$17/kW DC -yr in 2019. Across 13 sources, the range in average lifetime OpEx for projects built in 2019 is broad, from $\$$13 to $\$$25/kW DC -yr. Operations and maintenance (O&M) costs—one component of OpEx—have declined precipitously in recent years, to $\$$5-8/kW DC -yr in many cases. Property taxes and land lease costs are highly variable across sites, but on average are—together—of similar magnitude. Other OpEx line items include security, insurance, and asset management. Given 2007-2009 values for not only project life and OpEx but also other drivers of the levelized cost of energy (LCOE, excluding the investment tax credit), the LCOE for utility-scale PV projects built from 2007 through 2009 averaged $\$$305 /MWh. Using 2019 values for all parameters yields an average LCOE of $\$$51 /MWh. The decline in LCOE from $\$$305 /MWh to $\$$51 /MWh was predominantly caused by reductions in up-front expenditures (and, to a much lesser extent, by changes in capacity factors, financing costs, and tax rates), but 9% ($\$$22 /MWh) of the overall decline is due to improvements in project life and OpEx. Project life extensions and OpEx reductions have had similarly sized impacts on LCOE over this period, at $\$$11 /MWh each. Had project life and OpEx not improved over the last decade, LCOE in 2019 would have instead been $\$$73 /MWh—43% higher. Given the limited quantity and comparability of previously available data on these cost drivers, the data and trends presented here may inform assumptions used by electric system planners, modelers, and analysts. The results may also provide useful benchmarks to the solar industry, helping developers and assets owners compare their expectations for project life and OpEx with those of their peers.

14 SOLAR ENERGY↗

DOE OSTI2023

Assessment of Cloud-Based Applications Enabling a Scalable Risk-Informed Predictive Maintenance Strategy Across the Nuclear Fleet

The current light water reactor fleet uses time-based or failure-based maintenance strategies to achieve high-capacity factors. But to make nuclear more competitive in the energy market, these reactors could utilize emerging technologies in terms of artificial intelligence (AI) and cloud computing to enable a cost-effective, predictive maintenance strategy. This report examines the feasibility of cloud computing for the nuclear industry’s needs in terms of the cloud’s computing capabilities, feasibility, and regulatory concerns. The technical viability of cloud computing was analyzed using one year worth of data from a boiling water reactor’s safety relief valve. Models were hosted on a local desktop, Idaho National Laboratory’s high-performance computer, and Microsoft Azure. Data was loaded, processed, and two types of models were trained in an A/B fashion. Based on the speed at which these actions were completed, it was used to determined that cloud computing has adequate computing resources. Additionally, the computing power can scale with the demanded load. To enable cloud computing in the existing fleet, additional sensors, networks, and other requirements must be implemented to ensure a smooth transition from current maintenance strategies. However, there is a benefit as the plant no longer needs manage their own servers, software, cybersecurity, and IT support staff. Many of these features can be offloaded on to the cloud provider. A comprehensive analysis was completed that showed the current annual cost of operating is more expensive than using cloud computing resources. Lastly, the regulatory framework does not explicitly address AI or autonomous control. Currently, the NRC and other regulatory bodies are evaluating providing guidance to address gaps rather than new regulations to address the use of AI and ML. But since many of the AI applications are focused on non-safety related applications, such as balance-of-plant components, they will likely have little or no regulatory restrictions or necessary approvals. Demonstrating how AI can improve maintenance and operation of these non-safety related systems seems like the likely path forward for implementing AI and cloud computing resources inside nuclear power plants (NPPs).

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

NASA NTRS1994

The MAMMOTH project

On the surface MAMMOTH is a high performance 5.25-inch half-high 8mm helical scan tape drive that records a native 20 Gigabytes of data on Advanced Metal Evaporated media at a sustained throughput of 3 Megabyte per second over a high speed SCSI interface, that is scheduled for production in the second half of 1995. But it's much more than that. Inside its custom designed sheet metal enclosure lies one of the greatest technical achievements of its kind. Exabyte's strategic direction is to increase throughput and capacity while continuing to improve drive, data and media reliability to its products. MAMMOTH adheres to that direction and the description of its technical advances is described in this paper. MAMMOTH can be broken down into four main functional assemblies: high-performance integrated digital electronics, high-reliability tape transport mechanism, high-performance scanner, and advanced metal evaporated media. All this technology is packaged into a standard 5.25-inch half-high form factor that dissipates only 15 watts.

Gerchar, Tim↗

NASA NTRS2002

Bandwidth Enabled Flight Operations: Examining the Possibilities

The Bandwidth Enabled Flight Operations project is a research effort at the NASA Ames Research Center to investigate the use of satellite communications to improve aviation safety and capacity. This project is a follow on to the AeroSAPIENT Project, which demonstrated methods for transmitting high bandwidth data in various configurations. For this research, we set a goal to nominally use only 10 percent of the available bandwidth demonstrated by AeroSAPIENT or projected by near-term technology advances. This paper describes the results of our research, including available satellite bandwidth, commercial and research efforts to provide these services, and some of the limiting factors inherent with this communications medium. It also describes our investigation into the needs of the stakeholders (Airlines, Pilots, Cabin Crews, ATC, Maintenance, etc). The paper also describes our development of low-cost networked flight deck and airline operations center simulations that were used to demonstrate two application areas: Providing real time weather information to the commercial flight deck, and enhanced crew monitoring and control for airline operations centers.

Pisanich, Greg↗

NASA NTRS2010

Large Scale Covariability in the Aerosol-SST-Precipitation Relation: A Satellite Perspective

Although large scale aerosol effects on precipitation have attracted increasing attention in recent years, significant uncertainties still remain in the current understanding of'such effects. One of the factors contributing to these uncertainties is the availability of aerosol data sets that are sufficiently long, stable, and comprehensive to be used for climate analysis. Such data sets are crucial for any long-term studies that are needed to demonstrate the statistical significance of large scale aerosol effects on precipitation when compared to the effects from other climate factors, such as remote or local sea surface temperature (SST) variability (ENSO. etc.). A longterm consistent aerosol product that complements the existing MODIS and AVHRR aerosol products is therefore needed to minimize aerosol data uncertainty issues for such Studies. The SeaWiFS instrument was primarily designed to measure ocean color, and it has been the mayor source for providing a comprehensive global data set of such measurements since its launch in 1997. Besides being used in this capacity, however, the well-calibrated set of radiances measured in the wavelength range from the visible (0.41 m) to the near infrared (0.87 m) is also well suited to creating long-term climate data records of aerosols. Recently, a new 13-year SeaWiFS aerosol optical depth dataset has been developed that expands its capacity to be used for such atmospheric studies. This SeaWiFS aerosol product provides us with an unprecedented opportunity to examine the covariability of aerosol, SST and precipitation on both a regional and global scale. We also use concurrent independent SST (NOAA Optimum Interpolation, OI, SST V2) and precipitation (GPCP V2) datasets for this study. We will present and discuss results from this study over several aerosol hot spot regions ( -,North Atlantic. South Atlantic, Western Pacific, Indian Ocean etc.) during the SeaWIFS data period (1997 -- current) from this study will be presented and discussed. These results will highlight the value and impact of this unique product to climate studies

Hsu, N. Christina↗